Report on Nutritional Status of Children of aged 6 to 24 months

Introduction

Nutritional status is the result of complex interactions between food consumption, overall health status and care practices. At the individual level inadequate or inappropriate feeding patterns lead to malnutrition. Numerous socio-economic and cultural factors influence patterns of feeding and nutritional status. Poor nutritional status is one of the most important health and welfare problems facing Bangladesh. Malnutrition is a result and cause of the social and economical underdevelopment of Bangladesh. The prevalence of malnutrition in Bangladesh is among the highest in the world. Millions of children and women suffer from one or more forms of malnutrition including low birth weight, wasting, stunting, underweight and anemia.

Malnutrition not only affects individuals but its effects are passed from one generation to the next as malnourished mothers give birth to infants who struggle to develop and thrive.
A factor that contributes to malnutrition among infants is that 50 percent of children in Bangladesh are born with low birth weight (LBW). This is caused by maternal malnutrition and high prevalence (75 percent) of anemia during pregnancy. Globally malnutrition is attributed to almost one-half of all children deaths. 1 Survivors are left vulnerable to illness, stunted growth and lack of intelligence. If these children are girls, they often grow up to become malnourished mothers themselves.

The gift of nature is that a malnourished mother can even is able to provide enough good quality milk for the normal growth of her child, as indicated by growth pattern of exclusively breastfed infants.2 Breastfeeding also affects mothers by physiologically suppressing the return to fertility, thereby affecting the length of interval between pregnancies. UNICEF and WHO recommend that children be exclusively breastfed for the first six months of life and that children be given solid or semisolid complementary foods beginning with the seventh month of life. The standard indicator of exclusive breastfeeding is the percentage of children less than six months of age who are exclusively breastfeeding. The standard indicator of timely complementary feeding is the percentage of children age 6-9 months who are breastfeeding and receiving complementary foods. The WHO recommends that breastfeeding be continued through the second year of life.3

If infants are exposed to faulty feeding and weaning practices they becomes malnourished and already LBW babies can not catch up growth. Breastfeeding and weaning practices are crucial for optimal growth and development during infancy and play a vital role in determining the optimal development of infants. Poor breastfeeding and infant feeding practices have adverse consequences for the health and nutritional status of children. This, in turn, has consequences for their mental and physical development. For example, if complementary foods are introduced inappropriately and with insufficient dietary diversity malnutrition occurs.4 After the age of two years, the effects of under nutrition are largely irre¬versible. Missing the “window of opportunity” – the thousand-day period from conception to two years of age – to improve nutrition can result in long-term permanent damage.5

These problems are very crucial and common factors contributing to high prevalence of malnutrition in Bangladesh. From an initially disadvantaged beginning, many Bangladeshi infants briefly improve in nutritional status during the first six months of life due to near-universal breast-feeding. However after weaning at age 6 months, inadequate food intake and a high burden of diarrhoea and other diseases exert a serious toll on the nutritional status of a child. In most cases, in our country complementary foods are introduced too early or too late with insufficient quality and quantity. Although there is a national Infant and Young Child Feeding (IYCF) strategy, there is no implementation plan for that and as a result, the strategy has not led to the desired impact. UNICEF supports the National Nutrition Programme to scale-up community-based peer counseling through mothers’ support groups. An estimated 50,000 pregnant women and lactating mothers are getting counseling on Infant and Young Child Feeding (IYCF) through Mother Support Groups in ten upozillas covered by the National Nutrition programme and supported by UNICEF.6
Prevalence of anemia among women of reproductive age and children are very common in Bangladesh. Successive pregnancy, high rate of abortion, inappropriate maternal care for pregnant and lactating mothers, intra-household insecurity of food –all these are contributory factors for anemia among lactating females. To prevent anemia in children, adolescent girls and pregnant and lactating women some packages of interventions have been taken by government and different national and international NGO. These projects include iron-folate supplements, deworming tablets and counseling to improve dietary intake, control disease and improve iron-folate intake. A network of adolescent girls groups is used to reach those who do not have regular contact with health services. In some urban slums of Dhaka and seven selected upazillas, Multiple Micronutrient Powder is being provided to families to prevent and correct anemia in children under five by UNICEF.6

In the recent decades rapid urbanization has become a trend in almost all developing countries. Majority of the world’s biggest cities are in the developing countries and 60 percent of their population lives in the urban slums.7 Urbanization is associated with industrialization and economic development and results in an increase in slum and squatter settlements.8 Urban population growth is also occurring at an alarming rate throughout Bangladesh. Thirty millions of people, over 20 percent of the population of Bangladesh, live in urban areas. Urban growth is currently estimated at over 9 percent per year in Bangladesh.9 This rate includes a significant number of poor and landless households moving to city slums from rural areas in search of better opportunities.

In 2010, the population of the city of Dhaka has been projected at 17.6 million people, with upto 60 percent in the slums. Everyday we observe the influx of hundreds of new people to Dhaka city. There are two factors behind mostly encouraging people to come to Dhaka. These are – pull factor and push factor. Bangladesh is urbanizing fast. People are moving to places where there are or perceived to have jobs and opportunities. The cities are the new centers of jobs and opportunities. The bigger the center, the stronger is the pool. Dhaka is the primate city in Bangladesh according for over 30 percent of the total GDP. It is pulling rural migrants faster and larger than any other cities in Bangladesh. Findings showed that, 56 percent people migrated to Dhaka city for economic reasons. There are also some push factors working in the process of migration to the cities, especially to Dhaka city. Now-a-days maximum slum dwellers are one kind of environmental migrants. The often natural disasters: flood, drought, cyclones, riverbank erosion destroys the agricultural outcomes every year. While Bangladesh is an agro-based country these disasters are much painful for the farmers and they are obliged to go to the cities. The job sectors of rural areas are not much strong so people are pushed to the cities. And for many other people demonstration effect is big enough to push them to the cities.10 This uncontrollable rapid growth of urban population is accompanied by increasing poverty, food insecurity and malnutrition, which leaves serious implications for welfare and well being of the country’s urban population.11 However urbanization adversely affects the social environment when it outstrips the capacity of the infrastructure to meet people’s needs. In addition, overcrowding and poor working conditions can lead to anxiety, depression and chronic stress and have a detrimental effect on the quality of life of families and communities.12

The population of slums in 2008 was estimated at between six and seven million people, 30 per cent of the metropolitan population and about 15 percent of the overall urban population. In other words, the population of slums is about 5 percent of the total population or about 7 million people in 2010. Number of migrants is increasing everyday in Dhaka, which is leading towards new slum areas. A World Bank study counted 1,925 slums in Dhaka comprising 275,000 households (1.5 million people). 13 Within the fast growing urban slums in each of the three major cities – Dhaka, Khulna and Chittagong, there exists such communities where prevalence of malnutrition is higher than in the worst affected rural areas of Bangladesh.14 Compared to other parts of the country, currently Khulna has the lowest prevalence of underweight population (38.9 percent), followed by Dhaka (45.2 percent).15

Slum dwellers are distressed migrants from rural areas, with poverty-driven urbanization due to unsustainable rural economy. Consistent with a 1993 UNICEF report, the main reasons for migration to Dhaka remain poverty, landlessness, unemployment and river erosion. The urban poor have been noted to pay very high rent for dismal housing and dwellings in Dhaka are often on government-owned land, moving within slums is common due to land re-appropriation. Unsanitary latrine conditions are found in 76.6 percent and many pay intermediaries for utilities. Though most slum dwellers uses pumped/tap water for drinking while open or surface water is used for non-drinking purposes. 16 The inhabitants of slums are exposed to new environmental dynamics of poor housing, water supply and sanitation with poor access to health care. Moreover, most urban slum dwellers face particular hardships that contribute to high rates of child illness, malnutrition and food insecurity. Many of the main hazards to health are present in these urban slum areas such as over-crowding, together with the unhealthy environment due to poor sanitation, inadequate supply of clean water, pollution and lack of systematic removal of garbage and solid wastes.17 Slum people are exposed to greater risk of nutritional deficiency disease than non-slum urban areas. Young children and women of reproductive age among slum dwellers are more vulnerable to nutritional deficits.

Rationale of the Study

Malnutrition is a serious public health and socio-economic problem of Bangladesh, where the most affected populations are under 5 years’ children, adolescent girls, pregnant and lactating women. The infant mortality rate (IMR) is 57 per 1000 in the country. However, 43 percent preschool age children are stunted and 17 percent of them are severely stunted. Again, 13 percent are wasted and 1 percent is severely wasted. In our country 48 percent of the children are underweight, with 13% severely underweight.15

Rates of child malnutrition rise very rapidly from 6 months of age and reach their peak during weaning age among nutritionally vulnerable children aged 6 to 24 months.
There are many factors which accelerate malnutrition. Non-exclusive breast feeding, delay of early initiation of breast milk, delayed and faulty weaning practices, prolong breast feeding are the most crucial factors among those. Maternal malnutrition is another significant cause of child malnutrition. A malnourished mother gives birth of Low Birth Weight (LBW) babies. However, if those children are not taken care with proper feeding practices, it expedites malnutrition.

Anemia is a most common public health concern among all age groups, but highest among children and pregnant and lactating women and affects about 2 billion people in developing countries. The consequences of anemia in pregnant women include increased risk of low birth weight or premature delivery, pre-natal and neonatal mortality, inadequate iron stores for the newborn, lowered physical activity, fatigue and increased risk of maternal morbidity. It is also responsible for almost a quarter of maternal deaths. Inadequate iron store in a newborn child, coupled with insufficient iron rich food intake during the weaning period, causes impaired intellectual development by adversely affecting language, cognitive, and motor development of the child. Iron deficiency among adults contributes to low labor productivity. Exclusive breastfeeding until age of 6 months and continuation of breastfeeding after this age combined with qualitatively and quantitatively appropriate feeding may contribute towards an increase in hemoglobin concentration in the first year of life. So, in a nutshell infant and young child feeding practices not only influence the growth, development, nutritional and health status of the child but also have life long implications on the health of a person.

Intra-uterine malnutrition resulting in low birth weight of the new born coupled with early childhood malnutrition is the major cause of diet related chronic diseases like diabetes, hypertension, cardio-vascular diseases and other chronic diseases in later life. However, nutritional deficiency disorders affect productivity of the person resulting in household food insecurity thus making a vicious cycle of poverty and malnutrition. Through precipitating disease and speeding its progression, malnutrition is a leading contributor to infant, child and maternal mortality and morbidity. Children and lactating mothers living in slum areas are more affected as they belong to an overcrowded under hygienic environment. The urban non-slum children along with their mothers are expected to give a different picture because of their better socio-economic and educational attainment.

The study was taken to evaluate the nutritional status of children aged 6 to 24 months and their mothers to identify the current nutrition situation. A comparison has been done between the slum and non-slum child-mother pairs. This study will help decision making to maximize utilization of limited resources particularly important for developing countries like us burdened with numerous health, nutrition and economic problems to address.

Chapter 2
Literature Review

In developing countries inadequate access to food and nutrients, inadequate care of mother and children, inadequate health services and unhealthy environment are very common all of which leads to malnutrition. Leading scientists link 60 percent of all childhood deaths to malnutrition.19 The five major nutrition problems in Asia and the Pacific Region are- Low birth weight (LBW) which related to maternal malnutrition, early childhood growth failure, iron deficiency anemia (IDA), Vitamin A deficiency and Iodine deficiency disorders (IDD).20

Child under nutrition is not spread evenly across the globe but is instead concentrated in a few countries and regions. More than 90 percent of the world’s stunted children live in Africa and Asia, where rates of stunting are 40 percent and 36 percent respec¬tively. 21

Bangladesh is a poverty stricken malnourished nation with a population of 112 million denser than any other country. Malnutrition is endemic in the country with high infant, under five children and maternal morbidity and mortality. Almost the whole population suffers from micro nutrient deficiencies, chronic dietary deficiencies, non food factors such as personal and environmental hygiene, sanitation, quality of water that is used for drinking and washing, the ways of waste disposal all contribute to the present state of malnutrition. Both food and non food factor assumed special importance in case of expected and nursing mothers, adolescent girls and children who constitute the vulnerable group of the population.22

The prevalence of malnutrition in Bangladesh is amongst the highest in the world. 2.4% of all children was severely malnourished by Gomez classification of Malnutrition (WAM < 60%), 34.7% were moderately malnourished (WAS = 60 – 74%) and 50.7% were mildly malnourished (WAM = 75 – 89%). 11.5% children were normal (WAM = 90 – 109%) by Gomez classification and 0.6 % were over weight (WAM ≥ 110%). 23
In Bangladesh 43 percent of children under five are stunted, and 16 percent are severely stunted, seventeen percent of children under five are wasted, and 3 percent are severely wasted. Weight-for-age results show that 41 percent of children under five are underweight, with 12 percent are severely underweight (measured in WHO Child Growth Standard) in our country. 15

In the recent decades child malnutrition has been addressed at a successful rate. Prevalence of underweight in children under five years (%) in Bangladesh in 1988–92 was 56.5; whereas in 2003–08 it decreased to 41.3.24 This rate is still alarming.

To assess the nutritional status and to determine potential risk factors of malnutrition in children under 3 years of age in Nghean, Vietnam a study was undertaken. The study carried out in November 2007, a total of 383 child/mother pairs were selected by using a 2-stage cluster sampling methodology. A structured questionnaire was administered to mothers in their home settings. Anthropometric measurement was defined as being underweight (Weight-for-age), wasting (weight-for-height) and stunting (Height-for-age) on the basis of reference data from the National Center for Health Statistics (NCHS) / World Health Organization (WHO). Logistic regression analysis was used to into account the hierarchical relationships between potential determinants of malnutrition. The mean Z-score for weight-for-age was -1.51 (95% CI -1.64, -1.38), for height-for-age was -1.51 (95% CI -1.65, -1.37) and for weight-for-height was -0.63 (95% CI -0.78, -0.48). Of the children, 103 (27.7.8%) were underweight, 135 (36.3%) were stunted and 38 (10.2%) were wasted. Region of residence, ethnic, mother’s occupation, household size, mother’s BMI, number of children in family, weight at birth, time of initiation of breast-feeding and duration of exclusive breast-feeding were found to be significantly related to malnutrition. The findings of this study indicate that malnutrition is still an important problem among children under three and socio-economic, environmental factors and feeding practices are significant risk factors for malnutrition among under-three years of age in Nghean, Vietnam. This study also identified that a greater risk of malnutrition was associated with poor knowledge of mothers on child feeding practice. These findings are very importance, suggesting the need for improving knowledge of mothers on child feeding practice. 25

Pregnant women and children during growth stages are the groups most vulnerable to iron deficiency anemia. This is a highly prevalent disease worldwide, but rates are highest in developing countries. The highest prevalence is detected among children in the 6 to 24 month age group, a period which coincides with the termination of breastfeeding. There is also evidence that the occurrence of anemia decreases as the child grows, even though anemia is still an important health problem among preschool children.

A study was undertaken to assess the relationship between hemoglobin concentration and breastfeeding and complementary feeding during the first years of life in the city of Salvador, Bahia, in northeastern Brazil, between July 1998 and August 1999. A Cross-sectional study was conducted among 553 children under age 12 months, who attended public healthcare facilities. Hemoglobin concentration was measured by cyanmethaemoglobin method, using the HemoCue system. As an outcome of the study Hemoglobin concentrations compatible with anemia were identified in 62.8% of the children studied, with greater occurrence among the 6-12 months age group (72.6%).
Exclusive breastfeeding during the first six months of life was associated with the highest levels of hemoglobin. The remaining feeding regimes were associated with different levels of reduction in hemoglobin levels, which became compatible with anemia in children fed with formula (p=0,009). Tea and/or water consumption was associated with a reduction in hemoglobin concentration of 0.76 g/dl (p<0,001) among children under age 6 months. For children aged 6-12 months, hemoglobin concentrations increased significantly with the consumption of sugar (p=0.017) and beans (p=0.018), and decreased significantly with the consumption of fruit (p<0.001).26

Micronutrient deficiencies especially iron and folic acid deficiencies that result in nutritional anemia in children and women and neural tube defects in newborns remain a public health problem in Bangladesh. Poor intake of foods rich in iron and folic acid and multiple infections have resulted in high rates of anemia among pregnant women and children under two years. Coverage of pre and postnatal iron and folic acid supplements is very low (only 15% of pregnant women in rural areas take at least 100 tablets during pregnancy) 27 due, in part, to low compliance rates and low coverage of antenatal services. Coverage of multiple micronutrient supplements formulated to address iron and other micronutrient deficiencies is also very low.

Urban population growth is occurring at an alarming rate throughout Bangladesh. The national census conducted in 2001 showed that the urban population had grown by 38% in the previous ten years, compared with only 10% in rural areas.28 The scale of urban poverty in Bangladesh has become a critical policy issue. If current trends continue, it is predicted that the numbers affected by urban poverty will rise to 23 million by 2010.29The rate of urbanization in Bangladesh includes a significant number of poor and landless households moving to city slums from rural areas in search of better opportunities.9 However, it adversely affects the social environment when it out strips the capacity of the infrastructure to meet peoples’ need. In addition, overcrowding and poor working condition can lead to anxiety, depression and chronic stress and have a detrimental effect on the quality of life of families and communities.12

Under-nutrition remains a major problem in most developing countries, especially in underserved areas such as urban slums. A cross-sectional study was planned to know the role of various factors influencing the nutritional status. The study was conducted in the urban slums of Rohtak, a city in Haryana, on 540 children aged 1-6 years and the relation of under-nutrition with age, sex, birth order, and type of family, literacy, and calorie intake were studied and analyzed using percentages and chi-square test. 57.4% of children were found malnourished. Proportion of malnourishment was more in males. Birth order, age type of family, number of living children, literacy status of mother and calorie intake were statistically significantly associated with grades of malnutrition.30
In Bangladesh the prevalence of stunting (% The Nutrition Surveillance Project conducts nutrition and health surveillance in partnership with NGOs in 4 urban slum working areas of Dhaka, Chittagong and Khulna and 41 sites throughout rural Bangladesh. In December 1996, the Helen Keller International (HKI) and the International Centre for Diarrhoeal Disease Research, Bangladesh collaborated on a crosssectional health and nutrition study in Lalbagh, a non-slum area in Dhaka. Data from the December round of the NSP for slum areas (n=1,788) and the rural sites (n=16,140) were used with the non-slum site (n=1,392). The prevalence of stunting (% As seen from this analysis, the pre-school children in the slum areas of Dhaka and other sites were at equal or greater risk of poor health and malnutrition than their counterparts in the rural and non-slum areas. While the malnutrition rates for children living in the areas are also high by international standards, the results of the study suggest that particular attention should be given to improve the situation for children living in the urban slums.8

In selected upazilas of Chittagong Hill Tracts, seven National Nutrition Program convergence upazilas and selected slums of Dhaka and Chittagong City Corporation areas Community-based models for preventing anemia in children, adolescent girls and women have been piloted. This pilot project is being expanded to other areas in urban and rural Bangladesh, targeting 75,000 children, 15,000 adolescent girls and 6,000 women. 1

In many developing countries, the low status of women is considered to be one of the primary determinants of under nutrition across the life cycle. Women’s low status can result in their own health outcomes being compromised, which in turn can lead to lower infant birth weight and may affect the quality of infant care and nutrition. A study in India showed that women with higher autonomy (indicated by access to money and freedom to choose to go to the market) were significantly less likely to have a stunted child when compared with their peers who had less autonomy. 32

The mean height of Bangladeshi women is 150 centimeters, which is above the critical height of 145 centimeters. Thirty percent of women are chronically malnourished, their body mass index (BMI) being less than 18.5. One in weight women was found to be overweight or obese (BMI 25 or higher). A woman’s place of residence, level of education and household wealth status are strongly associated with her nutritional status. For example, 33 percent of rural women are considered thin (<18.5), compared with 20 percent of their urban counterparts. Between the 2004 and 2007 BDHS surveys, the proportion of women who are over-weight or obese increased slightly from 10 percent to 12 percent. The average height of women did not change. 15 Lower health care facilities for women of reproductive age result in higher maternal malnutrition in the country. In Bangladesh 1 in 5 women (21 percent) with a live birth receives postnatal care from a medically trained provider, and mostly only in the first two days after delivery. 15 Data from the 2007 BDHS show that under-five mortality (65 deaths per 1000 live births) has continued its notable decline. Large decreases were observed in child mortality (age 1-4 years). The number of children die before reaching the first birthday has decreased from one in fifteen children compared to one in 19 (52 deaths per 1000 live births) in the 2004 BDHS. 15 Another contributing factor for malnutrition is faulty treatment seeking behavior and absence of health care facility for the target population. . Among children under 5 years of age, 5 % showed the symptoms of acute respirator illness in the two weeks preceding the Bangladesh Demographic and Health Survey 2007. Of these, only 37% were taken to a health facility or a medically trained provider for the treatment while 13% received no treatment at all. Among thirty eight percent of children under five years had a fever in the two weeks preceding the survey. Of these 24 percent were taken to a medically trained provider or health facility for treatment. For 23 percent of children with fever, help was sought at a pharmacy. 15 There is a strong association between under-five mortality and mother’s education. It ranges from 32 deaths per 1000 live births among children of women with secondary complete or higher education to 93 deaths per 1000 live births among children of women with no education.15 A greater risk of malnutrition is associated with poor knowledge of mothers on child feeding practice. Almost all (98 %) Bangladeshi children are breastfed for some period of time. Forty-five percent of last-born infants who ere ever breastfed were put to the breast within one hour of birth, and 89 percent started breastfeeding within the first day. The median duration of any breastfeeding in Bangladesh is 32 months. Exclusive breastfeeding of children under six months (based on 24-hour period before the survey) has not improved in the past 15 years; it remained unchanged at around 45 percent in between 1993-94 and 1999-2000, declined to 42 percent in 2004, and remained essentially unchanged, 43 percent in 2007.15 The majority of mothers breastfed their children well into the second year of life (>88% of children aged 12-14 mo and >74% of children aged 21-23 mo), and many for much longer.33

On the other hand, supplementary feeding of children who are also breastfed has greatly increased over the past 15 years. In 1993-1994, only 29 percent of children age 6-9 months received complementary foods while being breastfed, compared with 62 percent in 2004 and 74 percent in 2007.The most commonly used complementary foods are those made from grains such as rice, wheat and porridge (over 60 percent; one-third of the children in this age group received fruits and vegetables rich in vitamin A. Sixteen percent received meat, fish, poultry or eggs. 18

Maternal malnutrition, insufficient health care facilities, lower education level, poor knowledge, attitude and practices about child feeding are more common in slum areas. Maximum people of the slum are below poverty level and are living vulnerable life as malnutrition and poverty in interlinked. Their housing conditions are appalling with many living in flimsy shakes (Jhupri). Only 41% have access to sanitary toilets. Most of their income is spent on food. They enjoy any utility services very hardly. They use open spaces and drains for defecation and cook their food on the street.34

Many tens of thousands of people live in desperately poor circumstances in the slums of towns and cities of Bangladesh and all the evidence suggests that their numbers are rising. The number of slum settlements has grown rapidly in recent years and the urban poor are now estimated at around 11 million or 37% of the urban population of Bangladesh. Most of these slums only provide shelter for poor people.11

A study was done to asses the determinants of malnutrition among the children under 2 years of age of Dhaka city. For this purpose, two hundred and twenty five mothers of Dhaka medical college hospital are interviewed to investigate of determinants of malnutrition. All of the respondents were under two years of age. One hundred fourteen of them were girls and rests 111 were boys. All of the children were from different socio-economic status coming different places of Bangladesh. 28% of the respondents’ family monthly income was below 3001-5000, 3.6% were below 20,000-25,000 and 16.4% were 10,000-15,000, 21.3% respondents’ mothers were illiterate, 24.4% mothers completed primary level, 32% completed secondary level, 11.1% completed higher secondary level and 11.1% mothers were graduated. The nutritional status children were not found very from normal to 3 degree malnourishment. Nearly 45.8% were normal, 1.8% was over nourished and 2.2% were 3 degree malnourished. 35

Recent findings from a survey of slums in Dhaka suggested that anemia is a serious public health problem among the school children. Special study from the urban slum sides of the GOB/HKI nutrition surveillance project (NSP) showed that 75.8% of children aged 6-59 months suffered from anemia (Hemoglobin < 110g/L). The prevalence of anemia was highest among children aged 6-11 months (92.3%) and children aged 12-23 months (87.4%). Many mothers and children are still malnourished and according to WHO definitions, prevalence of malnutrition was very high or serious during most time of the year. Data showed that 58-70% of households in slums of Dhaka had an energy intake ≤ 2122Kcal/Person/Day indicating at least moderate poverty. The majority of these households also had an intake below 1805Kcal/Person/Day (29-34%) in Dhaka. Approximately a quarter of mothers were under weight. Severity of child wasting (Low weight of height) was poor (4-8%) prevalence was higher among 0-23 months old children in the slums of Dhaka.9

In the above context, it can be concluded that a large number of the population of Bangladeshi children are suffering from malnutrition and are likely to grow smaller and smaller. This is implication of the fact that we are heading towards a nation that will see its children to be of small status and low weight population. So, we need to give highest priority to child health and nutrition if we hope for a brighter future of our country.

Chapter 3
Objectives
General Objective

To assess the nutritional status of children aged 6 to 24 months and their mothers from selected slum and non-slum areas of Dhaka city and to compare the existing nutritional situation in terms of feeding practices as well as socio-economic conditions.
Specific Objectives

To assess the socio-economic and demographic situation of the slum and non-slum target populations.
To evaluate the nutritional status of children (6 to 24 months) and their mothers by anthropometric measurements and clinical observations between two target populations.
To estimate blood hemoglobin level of both mothers and children (aged 6 to 24 months) from two target populations using HemoCue method.
To assess Knowledge, Attitude and Practice (KAP) between two target populations in terms of pregnancy, delivery and lactation aspects of the mothers.
To find out child feeding practices and to evaluate dietary intake pattern of the mothers using 24 hours dietary recall method of both target populations.
To understand the morbidity pattern of children and treatment seeking behavior of two target populations.
To compare the existing situation between the selected slum and non-slum populations of Dhaka city in terms of study parameters.
Finally, to recommend appropriate interventions to improve the feeding practices as well as nutritional status of both target populations based on the study findings.

Hypothesis

Conceptual Framework

A conceptual framework was drawn to summarize all influential factors that affecting nutritional status of mothers and in turn their children. Maternal malnutrition is the outcome of poor socio-economic and demographic condition (i.e. low income, low level of education, occupation and family size), which is expedite by poor sanitation, frequent morbidity, lack of health care facilities, lack of pure water source for different usages, unhealthy environment and living condition. An unhealthy mother with poor body storage of different nutrients and short stature gives birth of a low birth weight (LBW) baby in most cases. Again improper treatment seeking behavior, frequent morbidity, lack of proper Knowledge, Attitude and Practice (KAP) of mothers about pregnancy, delivery, lactation and faulty feeding practices (non-exclusive breast feeding, faulty complementary feeding practice, prolonged breast feeding) – all these leaves a dangerous impact on child growth and development. Children at their early life fail to catch-up growth. Such trauma at the beginning of life has bad consequences in the long run. A malnourished child becomes a malnourished adult and the cycle of malnutrition continues from generation to generation.

Chapter 4
Materials and Methods
Study Design

This was a comparative cross-sectional study. The study was conducted among the children aged 6 to 24 months and their mothers of selected slum and non-slum areas of Dhaka Metropolitan city. The aim of the study was to investigate the comparison between the target populations from slum and non-slum areas. The study was, therefore designed into the following four schematic parts:

Part one: Socio-economic & demographic information:
It included age, education, religion, occupation, total family member, monthly income, sector wise expenditures, utility facilities and water sources for different household usages.

Part two: KAP related Information among mothers:
I. Information related to pregnancy, lactation and delivery
II. Feeding Practices: Colostrum feeding, Pre-lacteal feeding, exclusive breast feeding, supplementary feeding and complementary feeding practices.
III. Morbidity and treatment seeking behavior

Part three: Anthropometric assessment:
Height/length and weight of target children
Height and weight of their mothers

Part four: Biochemical assessment:
Hemoglobin level of target children and their mothers

Part five: Dietary assessment:
Food Intake of mothers by 24 hour recall method
Part six: Clinical Assessment:
Clinical signs and symptoms of target children and their mothers

Part seven: Statistical analysis:
Different statistical analysis was undertaken. These are-
Descriptive analysis
Pearson’s Chi-square test
Bivariate correlation
Linear regression

Time Frame: The study was carried out from January to December 2010 which includes study design, data collection, data analysis and write up.
Study Location

The study was conducted at Koilarghat slum, Chandirghat slum at Kamrangirchar slum area and randomly selected non-slum areas of Dhaka city. Data for non-slum areas were collected from the mother-child (aged 6 to 24 months) pairs visiting different immunization centers in Dhaka city. These were the immunization centers of Holy Family Red Crescent Medical College and Hospital, Monowara Hospital Private Ltd and Brighton Hospital, Dhaka. The places were chosen in a purpose to reach the target population during the limited time of data collection. A large number of mother-child pairs from different parts of non-slum Dhaka attended these centers for immunization.
Study Population

The study was conducted among 95 child-mother pairs from both slum and non-slum areas of Dhaka city by simple random sampling. The study subjects included children aged 6 to 24 months and their mothers. Ages of the children were confirmed mostly by using the child’s birth certificate or immunization card. The purpose of the study was explained to the authority of those centers and all the respondents. To conduct the study, consent was taken from the mothers of the children.
Sample Selection Criteria

Inclusion Criteria:
Mother alive as well as care giver of 6-24 months child
Residing in the habitation for at least 6 months

Exclusion Criteria:
Severely sick child or mother
Mother is not the caregiver
Sample Size Calculation

The sample size was estimated by considering the prevalence of malnutrition among the children aged less than two years of slums of Dhaka. The prevalence of underweight children of less than 2 years of age in urban slum of Dhaka is 46%.36
The sample size for slum and non-slum children (6 -24 months) was estimated using the following formula:
n=z^2/d^2 .p.q

Considering p=0.46 (q=0.54), z=1.96 and d=10% we obtain

n=〖1.96〗^2/〖0.1〗^2 *0.46*0.54=95.425≅95
Where,
p = 0.46 (maximum variability i.e. prevalence of underweight in < 2 years children in urban slum Dhaka)
q = (1-p) = (1-0.46) = 0.54
Z = the value associated with 95% confidence interval = 1.96
e = level of precision (±10%) = 0.1

A total of 95 children aged 6 to 24 months were thus selected in the study having equal number of their mothers. Similarly for comparative purpose equal number that is 95 child-mother pairs were included in the study, even though the prevalence of malnutrition among non-slum area children is much lesser in number.
Thus a total of 190 child-mother (6-24 months) pairs who were residing in their habitation for more than 6 months were selected randomly for the study purposes.
Questionnaire Design and Field Trial

A standard close ended questionnaire was developed to obtain relevant information based on the objectives of the study. In order to standardize the data collection procedure, pre-testing of the questionnaire was conducted in both slum and non-slum areas who were not included in the study. Based on the observations and pre-test findings necessary corrections were made in the questionnaire. The questionnaire was then finalized. A detail questionnaire is given in annexure1.
Overview of Data Collection Method

The mothers were interviewed to collect information. In the slum areas target child-mother pairs were reached by door to door visit. Data for non-slum areas were collected from the target child-mother pairs visiting different immunization centers in Dhaka city. These were the immunization centers of Holy Family Red Crescent Medical College and Hospital, Monowara Hospital Private Ltd and Brighton Hospital, Dhaka. The places were chosen in a purpose to reach the target population during the limited time of data collection.

To avoid information missing or faulty information, the collected information from the locations were checked, coded everyday and crosschecked at the field sites in order to avoid any misreporting. Any confusion arising in this matter was settled on the following day during subsequent spot visit.

Socio-economic & Demographic Data Collection:
Information regarding socio- economic and demographic condition was collected as an essential part of the study by a personal interview with target mothers. Socio-economic information such as educational attainment, occupation, number of family members, income, monthly expenditure age, religion, sector wise expenditures, utility facilities and water sources for different household usages were carefully investigated and recorded in the specified portion of the questionnaire.

KAP related Data Collection:
Data was collected about:
I. Information related to pregnancy, lactation and delivery
II. Child feeding practices: colostrum feeding, pre-lacteal feeding, exclusive breast feeding, supplementary feeding, complementary feeding practices.
III. Morbidity and treatment seeking behavior

Anthropometric Data Collection:
Nutritional status of the target children and their mothers were assessed with the help of anthropometric measurements.

Weight: Body weight of children and their mothers were weighed by using weighing scale, which was calibrated with known weight and balanced at zero before each series of measurements. Mother was made to stand at the center of the platform with hands on his side, barefoot and in light clothing and her weight was recorded to the nearest 0.1 kilogram. Then the mother was made to stand with the baby in her lap and then their combined weight was taken. Then by subtracting the two values the weight of the child was estimated.

Height: For mothers and children (who were able to stand alone), the height was measured using a vertical scale. Boards for measuring height were manufactured with the assistance of INFS. After removing the shoes, the subject was made to stand on the flat surface of the scale with feet parallel to heels and eyes looking straight ahead with arms hanging loosely at the sides. The headpiece of the measuring device was a metal bar, which gently lowered crushing the hair and contact with the top of the head. The measuring scale was 175 cm and height was measured to an accuracy of 0.1 cm.

Since the measurement of standing height for most of children was not possible, a recumbent length (crown-heel length) was measured. The child was laid on a table or flat surface placing head firmly against the fixed metal headpiece with the baby’s eyes looking vertically and extending the knee by firm pressure, and flexing the feet at right angles to the lower legs against the upright foot piece of the height scale. The length of the child was read to the nearest 0.1 cm.

Weight-for-age, height-for-age, weight-for-height (in z-scores) were adopted for characterizing the child’s anthropometric status. The cut-off points for WHO Global Database on Child Growth and Malnutrition was used in this study as standards for classification of children in various grades of nutritional status.

The cut-off levels are given below:
Height-for-age Z-score (HAZ) Classification
< –3SD Severe stunted
< -2SD to –3SD Moderate stunted
≥ -2SD Normal (not stunted)
Weight-for-age Z-score (WAZ) Classification
< –3SD Severe under weight
< -2SD to –3SD Moderate under weight
≥ -2SD Normal (not under weight)
Weight-for-height Z-score (WHZ) Classification
< –3SD Severe wasted
< -2SD to –3SD Moderate wasted ≥ -2SD to 2SD Normal (not wasted) > 2SD Over weight

Mothers’ nutritional status was measured by Body Mass Index (BMI). BMI is calculated by dividing weight in kilogram by the square of height in meter. The cut-off value was adopted for characterizing mother’s nutritional status by using WHO reference (1995).

BMI (kg/m²)
Principal cut-off points Classification
≤ 18.49 Under Nutrition
18.50 – 24.99 Normal
≥ 25.00 Obese

Blood Collection:
Level of blood hemoglobin was used as an index of biochemical status. Hemoglobin concentration was determined in the field using the cyanmethemoglobin method, in HemoCue system (WHO, 2001), considered as reliable and recommended for the determination of hemoglobin concentration during fieldwork. Blood collection was done by fingertip lancing, using disposable lance. 20 micro liter of blood was collected by microcuvettes from each target population. Which was preserved by soaking in blotting paper and was stored in the refrigerator until the blood test was carried out the following day.

Estimation of Hemoglobin:
Photometric Colorimetric Test (cyanmethemoglobin method) has been carried out for the determination of hemoglobin from collected blood sample using Drabkin’s solution prepared previously in the laboratory of INFS. The absorbance (optical density) was measured in the spectrophotometer at 540 nm.

Calculation of Hemoglobin Concentration:
Blood hemoglobin level was calculated using the following equation:
Hemoglobin (g/dl) = 36.8 ×Optical Density

The cut-off values for hemoglobin concentration to determine anemia was considered based on the suggested criteria for the diagnosis of anemia (WHO, 2001).

Population Group Levels of Hemoglobin considered anemic
Children aged 6 months to 6 years Adult Females : non pregnant

Dietary Information:
Data regarding mothers’ dietary intake were collected by 24 hour recall method. The mothers were interviewed and asked to demonstrate the amounts of food eaten over the past 24 hours by her. Detailed information on menu, family measurement and food ingredients were collected from mothers. Bangladeshi food conversion table developed by INFS was used to code and calculate the weight of all foods. Information on the child’s regular food consumption was obtained at the time of interviewing mothers.

Clinical Observations:
The target children and mothers from both slum and non-slum areas were carefully observed to examine if there are any clinical signs and symptoms.
Analytical Methods

A data entry form was first prepared and data from the finally checked questionnaires were entered in that form using Statistical Package for Social Scientists (SPSS) Windows version17 software and this was followed by an extensive period of logical checking to identify any data entry errors. Those identified errors were corrected by consulting the original questionnaires.

Then data analyzed by applying percentages, means, standard deviations, chi-square test, correlation test and regression analysis. Anthropometric status evaluation was carried out using WHO Anthro program. Dietary analysis was done by using Fortran 77 software.

Descriptive analysis was undertaken to explore the differences in household socioeconomic, demographic, monthly income, sector wise monthly expenditure, parity, number of abortion, delivery place, birth weight, colostrums feeding, exclusive breast feeding, supplementary feeding, complementary feeding, morbidity and treatment seeking behavior, anthropometric status, dietary intake, anemia level, clinical findings among the children aged 6 to 24 months and their mothers of both slum and non-slum areas. Chi-square test was done to see the level of significance and bivariate correlation test was done to estimate the strength of correlation between two variables. Linear regression analysis was done for estimating the correlation coefficient between dependent and independent variables for the target population from both slum and non-slum areas of Dhaka.
Limitations of the Study

During the time of the study some difficulties and challenges were faced which were addressed and mitigated properly to ensure most accuracy. Those are:

1. The study was conducted in different areas of Dhaka city where the level of education and standard of living were different than those of slum dwellers who were sometimes difficult to communicate.
2. The respondents (mothers) had to give the history of dietary intake by 24 hours recall method, where assumption of amount of food consumed may not be accurate.
3. Most of the respondents were unwilling to express their original monthly income. Several of them tried to lessen their income.
4. Some of the households in non-slum areas were not cooperative for allowing blood collection for hemoglobin estimation, so it needed more persuasion to convince them.
5. Managing time for interview of non-slum mothers were one of the difficult tasks which was overcome by repeated motivations.
6. While collecting age of the mothers in slum, some difficulties were faced as few of them had no birth cards or immunization cards and even they could not remember the exact year. Various referral questions related to remarked incidents were asked to make her recall for calculating the approximate age. So, there is a chance of recall bias.

Chapter 5
Results of the Study
Socio-economic & Demographic Information

Background Characteristics:
Table 1 shows the composition of respondents by their religion. 94.7% of the respondents from slum area were Muslim, 5.3% of them were Hindu. Among the non-slum respondents 88.4% were Muslim, 8.4% were Hindu and 3.2% was Christian. 91.6% of all respondents were Muslim. So, it is clear that in the total sample most of the respondents were Muslims.

Table 1: Percent Distribution of Households by Religion
Religion Slum (%) Non-slum (%) Total (%)
Islam 94.7 (90) 88.4 (84) 91.6 (174)
Hindu 5.3 (5) 8.4 (8) 6.8 (13)
Christian 0 (0) 3.2 (3) 1.6 (3)
Total 100.0 (95) 100.0 (95) 100.0 (190)
* (Figures in parenthesis are numbers of respondents)

Figure 1 represents that most of the respondents belong to small family with maximum 4 family members. Only 3.2 slum families and 2.1 percent non-slum families were large.

Figure 1: Percent Distribution of Households by Number of Family Members

Table 2 represents that most of the slum mothers (58.9 percent) were between 19 and 25 years, whereas the largest portion of mothers (49.5 percent) in the non-slum areas were from 26 to 32 years of age.

Table 2: Distribution of Mothers according to their age
Age of Mothers Slum
( n=95) Non-slum
(n=95)
16 to 18 years 10.5 2.1
19 to 25 years 58.9 23.2
26 to 32 years 22.1 49.5
33 years & above 8.4 25.3
Total 100.0 100.0

Education Level
Marked variations were found in the education level of slum and non-slum population. Table 3 shows the education level of the mothers and main income earners of both slum and non-slum areas. However, 35.8 percent of the mothers from slum were illiterate, 4.7 percent had completed primary level and 29.5 percent had completed S.S.C., no mother in the slum found completed H.S.C. level. On the contrary, education level of mothers of non-slum areas was at least S.S.C. level. Again, 52.6 percent mothers reported having had graduation or above, 18.9 percent mothers from non-slum areas had completed primary level and 28.4 percent had completed H.S.C.

In case of education level of the main income earner a big portion (77.9 percent) from non-slum areas were graduated or had higher education level, 7.4 percent had completed S.S.C. and 14.7 percent had completed H.S.C. On the other hand, in the slum area, 30.5 percent of the main income earners were illiterate, 35.8 percent reported having had primary education, 28.4 percent had completed S.S.C. and only 5.3 percent had completed H.S.C. It is thus evident that, respondents from slum were lagging behind in terms of education level than from non-slum respondents.

Table 3: Education Level by Areas
Education Level Mother Main Income Earner
Slum (%) Non-slum (%) Slum (%) Non-slum (%)
Illiterate 35.8 0 30.5 0
Upto Primary level 34.7 0 35.8 0
Completed S.S.C. 29.5 18.9 28.4 7.4
Completed H.S.C. 0 28.4 5.3 14.7
≥ Graduate 0 52.6 0 77.9
Total 100 100 100 100

Economic Condition:

Figure 2 shows that in slum areas, 57.9 percent of the mothers reported being housewives whereas, 23.2 percent was industry workers, 11.6 percent was day laborer and 5.3 percent was involved in small business, while 2.1 percent reported as worker.

Main occupations of the main income earners of the households have been given in figure 3. Among them 35.4 percent of slum areas was involved in small business. A large part (34.7 percent) reported as day laborer.

Figure 2: Percent Distribution of Occupation of mothers of slum

Figure 3: Percent Distribution of Occupation of main income earners of slum

Figure 4 and 5 respectively represents the occupation of mothers and main income earning members of non-slum areas. 65.3 percent mothers of non-slum areas were housewives. Major portion (54.7 percent) of the main income earning members of non-slum areas was service holder. 5.5 percent major income earning members were found working at abroad.

Figure 4: Percent Distribution of occupation of Non-slum mothers

Figure 5: Percent Distribution of occupation of Non-slum Main Income Earners

Figure 6 demonstrates that 16.8 % households of slum had a monthly income less than Tk. 4000, 18.9 % had a monthly income Tk. 4001 to Tk. 7000, 51.6 % had a monthly income Tk. 7001 to Tk. 10000, 12.6 % had a monthly income Tk. 10001 to Tk. 15000.

Figure 7 shows that 2.1 % households of non-slum areas had a monthly income from Tk. 10001 to Tk. 15000, 6.3 % had a monthly income Tk. 15001 to Tk. 20000, 47.4 % had a monthly income Tk. 20001 to Tk. 30000, 37.9 % had a monthly income Tk. 30001 to Tk. 50000 and 6.3% had more than Tk50000.

Figure 6: Percent Distribution of Households of Slum by Monthly Income

Figure 7: Percent Distribution of Households of Non-slum by Monthly Income

Data on per capita monthly income is shown in table 4. In the slum areas, 37.9 percent of households reported having per capita monthly income of Tk. 1500 or less, 62.1 % a per capita monthly income of Tk. 1501 to Tk. 2500. In the non-slum areas, 42.1 percent of households reported having per capita monthly income of Tk. 4001 to 6000, 42.1 % a per capita monthly income of Tk. 6001 to Tk. 8000, 15.8 percent a per capita monthly income was above Tk. 8000
Table 4: Percent Distribution of Households by Per Capita Monthly Income
Per Capita Monthly Income
(Taka) Slum (%)
( n=95) Non-slum (%)
(n=95)
8000 0.0 15.8
Total 100.0 100.0

Figure 8 shows monthly mean expenditure in different sectors in slum and non-slum areas. The mean food cost in slum area was Tk.5242, whereas the mean food cost was Tk.11858 in non-slum areas and the mean treatment cost in slum areas was Tk.400, whereas the mean treatment cost was Tk.1611 in non-slum areas. In each sector a huge difference existed.
Figure 8: Percent Distribution of Households by Sector wise Average Monthly Expenditure

Utility Facilities and Practices:
The respondents in slum did not use to live a decent life in healthy abodes. They did not have any gas or water supply. According to table 5 in slum areas, it was found that 58.9 percent of them only had kitchen facilities. During data collection it was observed that most of the accommodation set up in slum was mostly a house with 5 to 6 rooms, one toilet and one kitchen, where each family resides in a room and share the single bathroom and kitchen with other residents. 74.8 percent respondents reported having sanitary latrine in slum areas.

Table 5: Percent Distribution of Households by selected variables regarding Utility
Utility Facilities Slum (%)
( n=95) Non-slum (%)
(n=95)
Sanitary Latrine Yes 75.8 100.0
No 24.2 0.0
Kitchen Yes 58.9 98.9
No 41.1 1.1
Water Supply Yes 0.0 94.7
No 100.0 5.3
Gas
Supply Yes 0.0 91.6
No 100.0 8.4
Source of water is of great importance for better health and nutritional status. Though 66.3 percent slum people reported drinking deep tubewell water; only 46.5 percent used water from deep tubewell for cooking purpose.

All respondents in slum areas reported washing utensils in the nearer river or pond, whereas 93.7 percent also reported bathing by this same source of water. A major part of non-slum respondents reported same source of water for drinking, cooking, utensil washing and bathing which is tap water. Data on different sources of water is given in table 6.

Table 6: Percent Distribution of Households by selected variables regarding Water Sources

Water Usage Sources of Water Slum (%)
( n=95) Non-slum (%)
(n=95)
Drinking Water Tap 0.0 94.7
River/Pond 33.7 0.0
Deep tubewell 66.3 3.2
Tubewell 0.0 2.2
Cooking Water Tap 0.0 94.7
River/Pond 53.5 0.0
Deep tubewell 46.5 3.2
Tubewell 0.0 2.2
Utensil Washing Water Tap 0.0 94.7
River/Pond 100.0 0.0
Deep tubewell 0.0 3.2
Tubewell 0.0 2.2
Bathing Water Tap 0.0 94.7
River/Pond 93.7 0.0
Deep tubewell 6.3 3.2
Tubewell 0.0 2.2
KAP related Information among Mothers

Information related to Pregnancy, Delivery and Lactation:

Reproductive health situation in slum and non-slum areas of Dhaka city has been focused through the given tables and figures.

Figure 9 demonstrates most (76.8 percent) of the non-slum respondents got married at the age of more than 18 years, whereas in slum the situation was found completely different. Only 12.6 percent mothers in slum were of more than 18 years of age while marrying.

Adoption of family planning was higher among the non-slum occupants. Figure 10 and figure 11 respectively demonstrate the percentage of households adopted family planning or not in slum and non-slum areas. However, 30 percent of slum respondents reported adopted family planning, whereas adoption of family planning was much higher (67 percent) among non-slum households.

Figure 9: Percent Distribution of Mothers according to their Age of Marriage

High parity and abortion rate both are very crucial incidences for women health. Socio-economic different influential factors promote their occurrences. From table 7, it is clear that percentage of parity was almost similar in both slum and non-slum areas. This was because the target children were mostly the first children of slum mothers.

Occurrence of abortion is higher (38.9 percent) among the non-slum mothers. It is clear from the table that among the mothers who had incidence of abortion in their life, most of them (69.5percent in slum and 63.2 percent in non-slum area) experienced multiple abortions.

Child spacing is important for maternal and child health. Short birth intervals are associated with an increased risk of death for mother and child. Studies have shown that children born at less than 24 months after a previous sibling are generally of poorer health. Short birth intervals also threaten maternal health.

However, 77 percent slum mothers did not have child spacing for at least 3 years, while the value for this in non-slum area is 58 percent.
Table 7: Percent Distribution of Mothers according to Reproductive Characteristics
Reproductive Characteristics Slum (%)
( n=95) Non-slum (%)
(n=95)
Parity < 3 83.2 87.4
≥3 16.8 12.6
Total 100.0 100.0
Abortion Occurred 29.5 38.9
Never Occurred 70.5 61.1
Total 100.0 100.0
No. of Abortion ≥2 69.5 63.2
Total 100.0 100.0
Child Spacing ≥3 Years 23.0 42.0
< 3 Years 77.0 58.0
Total 100.0 100.0

Table 8 shows that a major part of the respondents’ place of delivery was the nearest NGO delivery centre. Most of them reported mainly BRAC delivery centre as their delivery place. In case of non-slum part of Dhaka, 91.6 percent mothers reported different hospitals and clinics as their delivery place.

However, 66.3 percent of non-slum mothers reported that their last baby was caesarean, whereas in slum most babies (69.5 percent) were delivered normally. Major respondents from both areas (15.8 percent for slum and 23.2 percent form non-slum) did not report about much blood loss after delivery.

It was seen that 43.2 percent mothers of slum reported that their last child born between 8 to 9 months. Again, 66.3 percent non-slum mothers reported giving last child birth at less than 8 months of pregnancy.

Low birth weight leads to malnutrition in later life. Table 8 shows that 58.7 percent mothers gave birth of LBW babies in slum and 25.8 percent non-slum mothers also reported giving birth of LBW babies.

Table 8: Percent Distribution of Mothers according to Delivery Information
Delivery related Information Slum (%)
( n=95) Non-slum (%)
(n=95)
Place of Delivery Home 33.7 8.4
NGO Delivery Centre 54.7 0.0
Hospital/ Clinic 11.6 91.6
Total 100.0 100.0
Type of Delivery Normal 69.5 33.7
Caesarean 30.5 66.3
Total 100.0 100.0
Blood Loss After Delivery Occurred 15.8 23.2
Not Occurred 84.3 76.5
Total 100.0 100.0
Month of
Child Birth 9 Months 23.2 6.3
Total 100.0 100.0
Birth Weight of Child ≥2.5 Kg (normal) 41.3 74.2
Total 100.0 100.0

KAP regarding Anemia

Anemia is very common among women of reproductive age in our country. Before and during pregnancy if it is not corrected mother gives birth of baby with depleted iron store and most dangerously the mother’s body iron status become poorer and she becomes more anemic. Knowledge about Anemia can help one to win against it.

Table 9 shows that 68.4 percent of slum mothers did not have knowledge about anemia which is very alarming. 25.3 percent non-slum mothers also did not know about this.

70.5 percent of slum mothers even did not know that if they were suffering from anemia during pregnancy or not. 43.2 percent non-slum mothers had anemia during pregnancy whereas 21.1 percent among them also did not know that if they had anemia during pregnancy or not.

Only 23.2 percent slum mothers got Iron supplementation during pregnancy. Among them 52 percent had taken 1 to 150 iron tablets during whole pregnancy.57.9 percent mothers reported that they did not take any folic acid supplementation during pregnancy period.

Table 9: Percent Distribution of Mothers according to Knowledge, Prevalence of Anemia and Supplementation (Iron, Folic acid) taken during Pregnancy
Criteria Variables Slum (%)
( n=95) Non-slum (%)
(n=95)
Knowledge about Anemia Know 31.6 74.7
Don’t Know 68.4 25.3
Total 100.0 100.0
Anemia During Pregnancy Yes 20.0 43.2
No 9.5 35.8
Don’t Know 70.5 21.1
Total 100.0 100.0
Iron Supplementation Taken 26.3 71.6
Not Taken 73.7 28.4
Total 100.0 100.0
No. of Iron Tablet Taken 1-150 52.0 39.7
151-300 8.0 11.8
301-500 4.0 17.6
Unlimited 36.0 30.9
Total 100.0 100.0
Folic Acid Supplementation Taken 7.4 58.9
Not Taken 57.9 20.0
Don’t Know 34.7 21.1
Total 100.0 100.0

Information related to Feeding Practices

Feeding Practices of Newborns
Breast feeding is the first fundamental right of a baby. The initiation of breast feeding and the timely introduction of adequate and safe appropriate complementary foods in conjunction with continued breast feeding are of prime importance for the growth, development, health and nutrition of infants and children.
Breast feeding also have importance for mothers. Breast feeding promotes uterine contractions and expels the placenta in the immediate postpartum period and reduces maternal blood loss.
According to Figure 12, most newborns from both slum (61.1 percent) and non-slum (67.4 percent) areas were first introduced colostrum just after birth. A big portion of the respondents gave different pre-lacteal foods to their newborns other than colostrum. 15.8 percent of slum respondents used to give sweetened water as pre-lacteal feed to their babies. It is to be mentioned that introducing formula milk to the newborns as first feed is higher (14.7 percent) among non-slum respondents.

Figure 11: Percent Distribution of Households by First Feed after Birth

Figure 13 represents the usage of different methods for pre-lacteal feeding. 32.5 percent babies used finger tip for pre-lacteal feeding. Usage of plastic feeder bottle is higher in non-slum areas (14.7 percent) than in non-slum counterparts (3.2 percent).

Figure 12: Percent Distribution of Households by Methods for Pre-lacteal Feeding

Early initiation of breastfeeding is encouraged for a number of reasons. It is also benefitial for mothers because early suckling stimulates breast milk production and facilitates the release of oxytocin, which helps the contraction of the uterus and reduces postpartum blood loss. The first breast milk is known as colostrum, which is highly nutritious and contains antibodies that protect the newborn from infection and diseases. Early initiation of breastfeeding also encourages bonding between a mother and her newborn. Breast feeding within an hour or two after delivery is associated with the establishment of exclusive breast feeding and also for longer or more successful breast feeding.

Percentage of mothers who had started breast feeding immediately after birth has been shown in figure 14, where it is seen that the rate is higher in non-slum areas which is 56.8 percent. However, 10.5 percent of slum children were never breast fed and in the non-slum areas it was 6.3 percent. First starting time of breast feeding of 7.4 percent babies of slum was after 48 hours of birth.

Figure 13: Percent Distribution of Households by First Starting time of Breast Feeding

Colostrum is important for child’s nutrition, immunological protection and brain development. UNICEF and WHO recommend that children be fed colostrum (the first breast milk) immediately after birth and continue to be exclusively breastfed even if regular breast milk has not begun flowing. Table 10 illustrates that major parts of both slum and non-slum areas had fed colostrum to their newborns. The reason to reject colostrum was mostly mother’s illness. However this percentage was 56.5 in non-slum areas and 30.5 percent in slum areas.

Lack of knowledge about benefit of colostrum reflects a practical reasoning of the basic cause of rejecting colostrum. Almost all non-slum respondents (95.6 percent) reported that they knew about the benefits of colostrum, this percentage was 79.8 for slum respondents.

Table 10: Percent Distribution of Information related to Colostrum feeding
Criteria Variables Slum (%)
( n=95) Non-slum (%)
(n=95)
Fed
Colostrum Given 69.5 77.9
Rejected 30.5 22.1
Total 100.0 100.0
Reason to
Reject Colostrum Mother’s Illness 48.3 56.5
Ignorance 17.2 17.4
Don’t Feel it Necessary 13.8 17.4
Family Discourage 17.2 8.7
Total 100.0 100.0
Benefits of
Colostrum Known 79.8 95.8
Not Known 20.2 4.2
Total 100.0 100.0

Exclusive Breast Feeding and Supplementary Feeding

Exclusive breast feeding is recommended by WHO for the first six months from birth. Mother’s milk alone provides all the required nutrients for the baby at proper quantity and quality during this period. Figure 15 shows that exclusive breast feeding was not practiced in almost half of the total respondents in both slum(48.2 percent) and non-slum areas (50.5 percent).
Figure 14: Percent Distribution of Children according to Exclusive Breast Feeding

It is recommended that no supplementary food is needed from birth till 6 months if mother is not severely ill. Almost every mother is capable of breast feeding, rare exceptions can be due to HIV positive cases and other selective communicable disease conditions. However breast size, diet, fluid intake, exercise, multiple births sometimes cause less milk production. But infant suckling can initiate and sustain this breast feeding process. Artificial feeding is expensive and carries risks of additional illness, particularly where the levels of infectious disease are high and access to safe water is poor. So, if supplementary food is given to the child it has to ensure that foods are prepared and given in a safe manner, meaning that measures are taken to minimize the risk of contamination with pathogens. And they are given in a way that is appropriate, meaning that foods are of appropriate texture and given in sufficient quantity.

According to figure 16, Suji was the most common (33.3 percent) as supplementary feeding among slum respondents. However, 26.6 percent of slum respondents reported feeding confectionary or snacks as supplementary feeding which was very health hazardous. Because eating confectionary or snacks leads to less appetite and the growth chart automatically starts declining.

Figure 15: Percent Distribution of Slum Children according to Supplementary Feeding

Figure 17 illustrates the percentage of feeding different supplementary foods in non-slum areas. Use of formula milk as supplementary feeding is found most common (52.1 percent) among non-slum respondents.

Figure 16: Percent Distribution of Noon-slum Children according to Supplementary Feeding

Complementary feeding

Early cessation of breast feeding causes post partum depression in mothers. Again prolonged breast feeding may cause anemia and growth retardation to children. Breast feeding is promoted internationally to be continued up to two years with the addition of weaning food after 6 months.

Table 11 shows the duration of breast feeding of the respondents.59.1 percent slum mothers showed their interest to breast feed their children more than 2 years of children’s age, this percentage was 33.3 percent for non-slum mothers. 36.4 percent slum mothers showed their interest to breast feed their children up to 2 years, this percentage was 63.3 percent for non-slum mothers. Among the mothers who already ceased breast feeding reported that 35 percent breast fed their children up to 1 year from slum and 37.9 percent non-slum mothers’ breast fed their children up to 6 months.

Table 11: Percent Distribution of Children according to Breast Feeding Practices
Breast Feeding Slum (%)
( n=95) Non-slum (%)
(n=95)
Continuing Breast Feeding 77.6 62.6
Not Continuing Breast Feeding 22.4 37.4
Total 100.0 100.0
Will continue
Breast Feeding
upto 24 months 59.1 33.3
Total 100.0 100.0
Followed
Breast Feeding
till 0-1month 15.0 3.3
0-4months 20.0 11.8
0-6months 15.0 37.9
0-12months 35.0 29.4
0-18months 15.0 17.6
Total 100.0 100.0

Complementary feeding should be timely, meaning that all infants should start receiving foods in addition to breast milk from 6 months onwards. It should be adequate, meaning that the nutritional value of complementary foods should parallel at least that of breast milk. WHO recommendation for weaning is starting complementary feeding gradually at 6 months of age. From the table 12, it is seen that among the slum respondents 40.8 percent started weaning at six to seven months of age. It is to mention that 35.2 percent slum children were introduced weaning at eight to twelve months. In the study it was found that 42.1 percent non-slum mothers started weaning before six months. 53.7 percent children were started weaning at proper time in non-slum areas.

Table 12: Percent Distribution of Children according to Weaning Practices
Feeding Practices Slum (%)
( n=95) Non-slum (%)
(n=95)
First Start of Weaning Food < 6 months 19.7 42.1 6-7 months 40.8 53.7 8-12 months 35.2 2.1 > 12 months 4.2 2.1
Total 100.0 100.0
Causes of Weaning before 6 months Breast milk not enough for children 12.5 5.6
Less Breast Milk Production 62.5 44.4
Due to Work Load 12.5 22.2
Family Pressure 5.6 22.2
Others 6.9 5.6
Total 100.0 100.0

When breast milk is no longer enough to meet the nutritional needs of the infant, complementary foods should be added to the diet of the child. Complementary feeding typically covers the period from six to 24 months of age, and is a very vulnerable period. It is the time when malnutrition starts in many infants, contributing significantly to the high prevalence of malnutrition in later ages.

Figure 18 represents that all foods were gradually introduced among only 33.4 percent slum-children and 42.1 percent non-slum children. A very few respondents also reported about feeding fruits, cerelac, suji, animal milk or formula milk individually as complementary feeding, which is a bad practice. Again,10.5 percent of non-slum children were introduced rice and Dahl or khuchuri with vegetables only without giving meat , fish or egg due to digestional problem of child.

Figure 17: Percent Distribution of Children according to Complementary Feeding

Foods should be prepared and given in a safe manner to minimize the risk of contamination. And they should be given in a appropriate way that is in appropriate texture and sufficient quantity. Feeding young infants requires active care and stimulation, where the caregiver is responsive to the child clues for hunger is easily understood and caregiver also encourages the child to eat.
Table 13 illustrates different child feeding practices that indirectly influence child nutritional status. However, 53.7 percent slum mothers maintain preselected fixed timing for feeding their babies. The percentage of feeding non-slum children according to child’s wish (44.2 percent) and at fixed time (45.3 percent) is almost equal. Percentage of providing fresh cooked food is higher (49.5 percent) among non-slum respondents, though almost half of the non-slum respondents reported not feeding their child fresh cooked food every time. However 84.5 percent slum mothers also reported that they did not use to feed their child fresh cooked food each time. Among these slum mothers 64.8 percent said that they can not afford feeding fresh cooked food always. It is to be mentioned that 37.8 mothers found unaware of the benefit of feeding fresh cooked food. In the study it was found that only 11.6 slum mothers used to cook separate food for their children, whereas 73.1 percent non-slum mothers reported cooking separate food for their children.

Table 13: Percent Distribution of Mothers according to Child feeding Practices
Criteria Variables Slum (%)
( n=95) Non-slum (%)
(n=95)
Time of Feeding Children
Child’s wish 32.6 44.2
At fixed time 53.7 45.3
Mother-in-law’s wish 2.1 8.4
When the child cries 11.6 4.2
Total 100.0 100.0
Fresh Cooked Food Yes 15.5 49.5
No 84.5 50.0
Total 100.0 100.0
Cause of Not Providing Fresh Cooked Food Unaware 31.7 37.8
Can not afford 68.3 56.2
Total 100.0 100.0
Prepare Separate food for children Yes 11.6 73.1
No 88.4 26.9
Total 100.0 100.0

Information related to Morbidity and Treatment Seeking Behavior
Poor nutritional status leads to frequent morbidity and again morbidity contributes to poor nutritional status. Figure 19 interprets that among the study population, the highest prevalence of morbidity prevailed among slum children, which is 85.3 percent. The percentage of children suffered from disease within last 3 months preceding the study was not so less. However 64.2 percent non-slum children were found suffering from different diseases.
Figure 18: Percent Distribution of Children according to suffering of Diseases within last 3 months preceding the study

The prevalence of diarrhea is highest at age 6 to 24 months, a period during which solid foods are first introduced into the child’s diet. This pattern is believed to be associated with increased exposure to illness as a result of both weaning and the greater mobility of the child, as well as with the immature immune system of children in this age group.
Table 14 translates that prevalence of diarrhoea was higher (20.7 percent) among slum children. However, 12.2 percent slum children suffered from cold and another 12.2 percent slum children were attacked by pneumonia. However 19.5 percent of slum children were found suffered from both fever and cold. Non-slum children suffered mostly (28.9 percent) from fever. The second highest prevalent (24.4 percent) disease was fever and cold among non-slum children.
Table 14: Percent Distribution of Children according to Diseases they suffered
Diseases Slum (%)
( n=95) Non-slum (%)
(n=95)
Fever 7.3 28.9
Cold 12.2 17.8
Fever + Cold 19.5 24.4
Diarrhoea 20.7 8.9
Diarrhoea + Fever 6.1 4.4
Diarrhoea + Fever + Cold 9.8 4.4
Typhoid 6.1 6.7
Pneumonia 12.2 4.4
Jaundice 2.4 0.0
Measles 3.7 0.0
Total 100.0 100.0

A huge difference in treatment seeking behavior between slum and non-slum respondents was found in figure 20. Among non-slum respondents 76.8 percent reported that they used to take their children to physician when their children used to get sick, in case of slum respondents this measure was 27.4 percent. Homeopathy seems to be the most common (27.4 percent) mode of treatment. A total of 16.8 percent slum respondents used to go to the traditional healer for treatment purpose for their babies. Another 16.8 percent of them reported following traditional ways.

Figure 19: Percent Distribution of Households according to Treatment Seeking Behavior for their children

Anthropometric Findings

Anthropometric Information of Child of slum and non-slum area:

Table 15 shows that mean height and weight of children aged 6 to 24 months in the slum areas was 74 cm and mean wt was 8.12 kg. Mean Height-for-age z-score, Weight-for-age z-score, height for weight z-score were -1.72, -2.30, -1.43 respectively. Mean height and weight of children aged 6 to 24 months in the non-slum areas was 77.38 cm and mean wt was 9.96 kg. Mean Height-for-age z-score, Weight-for-age z-score, height for weight z-score were -0.76, -0.74, -0.05 respectively.

Table 15: Mean and Standard Deviation of Anthropometric indicators of Slum and Non-slum children
Anthropometric Indicators for Children Slum (%)
( n=95) Non-slum (%)
(n=95)
Mean Std. Deviation Mean Std. Deviation
Height (cm) 74.00 6.51 77.38 8.24
Weight (Kg) 8.12 1.54 9.96 1.71
WHOHAZ -1.72 1.53 -0.76 1.75
WHOWAZ -2.30 .95 -0.74 1.02
WHOWHZ -1.43 1.43 -0.05 2.18

According to Height-for-age z-score in table 16, among slum male children 49 percent had normal nutritional status, 33.3 percent were moderately stunted and 17.6 percent were severely stunted. Among slum female children 56.8 percent had normal nutritional status, 17.6 percent were moderately stunted and 11.4 percent were severely stunted.

However in case of non-slum children 84.5 percent male children were found not stunted, for female children this percentage was 76 percent. Among them 11.1 percent boy and 12 percent girl were moderately stunted, 4.4 percent boy and 12 percent girl were severely stunted.

Table 16: Percentage of Stunted Children by Sex between Slum and Non-slum areas
Area HAZ Sex of the Child
Male (%) Female (%)
Slum < -3SD (Severe ) 17.6 11.4
≥-2SD (Normal) 49.0 56.8
Total 100.0 100.0
Non-slum < -3SD (Severe ) 4.4 12.0
≥-2SD (Normal) 84.5 76.0
Total 100.0 100.0

According to Weight-for-age z-score in figure 21 among slum male children 29.4 percent had normal nutritional status, 45.1 percent were moderately under weight and 25.5 percent were severely under weight. Among slum female children 45.5 percent had normal nutritional status, 40.9 percent were moderately under weight and 13.6 percent were severely under weight. In case of non-slum children 77.8 percent male children were not found under weight, for female children this percentage was 94 percent. Among the slum 22.2 percent boy and 6 percent girls was moderately under weight.
Figure 20: Percentage of Under Weight Children by Sex between Slum and Non-slum areas

According to weight-for-height z-score in table 17, among slum male children 68.6 percent had normal nutritional status, 19.6 percent were moderately wasted and 9.8 percent were severely wasted. Among slum female children 63.6 percent had normal nutritional status, 22.7 percent were moderately wasted and 13.6 percent were severely wasted.

However in case of non-slum children 82.2percent male children were found not wasted, for female children this percentage was 74 percent. Among them 8.9 percent boy and 6.0 percent girl were moderately wasted, 8.9 percent boy and 4 percent girl were severely wasted. However 2.0 percent slum male children were found over weight, on the contrary among non-slum children 16 percent female were found obese.

Table 17: Percentage of Wasted Children by Sex between Slum and Non-slum areas
Area WHZ Sex of the Child
Male (%) Female (%)
Slum < -3SD (Severe ) 9.8 13.6
2SD (Overweight) 0.0 0.0
Total 100.0 100.0
Non-slum < -3SD (Severe ) 8.5 4.2
2SD (Overweight) 4.3 14.6
Total 100.0 100.0

Anthropometric Information of Mothers of slum and non-slum area:

A woman’s height can be used to predict the risk of difficulty during pregnancy, given the relationship between height and pelvic size. The risk of giving birth to low-weight babies is also higher among women of small stature. Table 18 demonstrates the mean and standard deviations of different anthropometric indices. Mean height of slum mothers was 150.80 cm, mean weight was 48.27 kg and mean BMI was 21.23 kg/m². According to the table mean height of non-slum mothers was 154.99 cm, mean weight was 57.68 kg and mean BMI was 24.17 kg/m². Standard deviation for BMI of slum mothers was 3.19 and for non-slum mothers it was 3.69.

Table 18: Mean and Standard Deviation of Anthropometric indicators of mothers from Slum and Non-slum areas
Anthropometric Indicators for Mothers Slum
( n=95) Non-slum
(n=95)
Mean Std.Deviation Mean Std. Deviation
Height (cm) 150.80 4.75 154.99 12.25
Weight (Kg) 48.27 7.71 57.68 8.98
BMI of Mothers(kg/m²) 21.23 3.19 24.17 3.69

From the figure 22 it is seen that 55.3 percent non-slum mothers had normal nutritional status, 28.9 percent were obese and 15.8 percent were malnourished according to their BMI. It was also found that 45.3 percent slum mothers had normal nutritional status, 12.6 percent were obese and 42.1 percent were malnourished according to their BMI.

Figure 21: Distribution of Nutritional status of mothers according to BMI

Biochemical Assessment

Blood hemoglobin levels of mothers and children were measured as an index of biochemical status. Figure 23 illustrates that 42.1 percent children aged 6-24 months of slum were anemic and in non slum 21.1 percent were anemic.

Figure 22: Anemia level of Children aged 6-24 months

Figure 24 demonstrates that 60 percent mothers of slum were anemic and in non slum 28.4 percent mothers were anemic.

Figure 23: Anemia level of Mothers

Dietary Information of Mothers

From the table 19, it is found that mean energy intake of slum mothers was 1544.3 Kcal and for non-slum mothers it was 2048.7 kcal. Mean protein intake of slum mothers was 39.6 g and for non-slum mothers it was 79.5 g. Again, mean iron intake of slum mothers was 13.3 mg and for non-slum mothers it was 27.3 mg. In case of vitamin intake, mean vitamin A intake of slum mothers was 141.1 IU and for non-slum mothers it was 852.8 IU. However, mean vitamin C intake of slum mothers was 30.9 mg and for non-slum mothers it was 62.3 mg.

Table 19: Per Capita Nutrient Intake of Mothers
Nutrients Slum
( n=95) Non-slum
(n=95)
Mean Std. Deviation Mean Std. Deviation
Energy (Kcal) 1544.3 349.2 2048.7 684.4
Protein (g) 39.6 14.5 79.5 41.2
Fat (gm) 7.5 2.9 22.4 14.2
Carbohydrate (g) 325.9 82.0 379.8 115.7
Calcium (mg) 275.6 192.7 493.5 318.5
Iron (mg) 13.3 11.8 27.3 19.3
Vitamin A (IU) 141.1 363.9 852.8 2145.7
Carotene (µg) 5078.2 6137.1 6073.1 9245.8
Thiamin (mg) 1.08 .32 1.77 .82
Riboflavin (mg) .38 .18 .76 .34
Niacin (mg) 17.1 4.2 22.6 7.8
Vitamin C (mg) 30.9 32.1 63.4 62.3
Zinc (g) 6.0 1.7 28.0 33.7

Table 20 shows that mean meat intake of slum mothers was 20 g and non-slum mothers was 63. Again fruit intake of slum mothers was 20 g and non-slum mothers was 63 , as well as fats & oils intake of slum mothers was 4 g and non-slum mothers was 12.

Table 20: Food Intake of Mothers by Food Group
Food Group Slum
( n=95) Non-slum
(n=95)
Mean Std. Deviation Mean Std. Deviation
Cereal 374 99 387 112
Roots & tubers 58 71 85 86
W Potato 54 67 57 60
Pulses & nuts 10 33 74 154
Leafy vegetables 140 166 166 139
Green vegetables 35 49 35 82
Green Yellow vegetables 42 76 59 70
Non-leafy Vegetables 63 161 72 95
Fruits 21 60 40 71
Meats 20 46 63 76
Eggs 4 13 14 25
Fish 26 34 44 47
Milk Protein 1 7 6 22
Fats & Oils 4 0 12 16
Miscellaneous Foods 3 9 8 22
Total Food 662 197 917 266

Calorie requirement for lactating mothers needs additional 550 kcal per day other than normal requirement. According to the figure 25, 100% RDA was fulfilled among 1.05 percent slum mothers and 23.4 percent non-slum mothers, 75-99% RDA was fulfilled among 23.2 percent slum mothers and 40.4 percent non-slum mothers. However, 50-74% RDA was fulfilled among 62.1 percent slum mothers and 28.7 percent non-slum mothers, less than 50% RDA was fulfilled among 13.7 percent slum mothers and 7.4 percent non-slum mothers.

Figure 24: Percentage of fulfillment of RDA of energy of lactating Mothers of slum and non-slum areas.

Clinical Findings

Clinical assessment consists of a routine physical examination to detect physical sign (i.e. observations made by a qualified examiner) and symptoms (i.e. manifestation reported by the patient) associated with malnutrition. These findings are most useful during the advance stages of nutritional definition, when overt disease is present.

According to Table 21 major clinical findings among slum mothers and children were discolored hair, angular stomatitis and worm infestation. Among them 26.3 percent mothers and 17.9 percent children were found having discolored hair, 11.6 percent mothers and 6.3 percent children were found suffering from angular stomatitis. However, 6.3 percent mothers and 17.9 percent children were worm infested.

Table 21: Percentages of mothers and Children (6 -24 months) of both Slum and Non-slum areas having clinical signs and symptoms
Clinical Signs Slum (n=95) Non-slum (n=95)
Mothers % Children % Mothers % Children
%
Hair Discolored 26.3 (25) 17.9 (17)
Sparce 14.7 (14)
Eyes Night Blindness 5.3 (5)
Bitot’s Spot
Conjunctival Xerosis
Corneal Xerosis
Keratomalacia
Pallor
Lips Angular Stomatitis 11.6 (11) 6.3 (6) 2.1 (2) 3.1 (3)
Angular Scars
Cheilosis 4.2 (4) 3.1 (3) 1.1 (1) 1.1 (1)
Gums Bleeding gums
Swollen red Papillae
Fever
Tongue
Smooth 2.1 (2)
Raw and Red
Nose Nasolabial Dyssebacea 2.1 (2)
Gland Enlarged Thyroid Gland 13.7 (13) 7.4(7)
Skin Flakypaint dermatosis 2.1 (2)
Follicular hyperkeratosis
Nail Koilonychia 6.3 (6)
Skeletal Knock Knee/ Bow leg 4.2 (4)
Others Edema 2.1 (2) 1.1 (1) 3.1 (3)
Enlarged abdomen
(Worm Infestation) 6.3 (6) 17.9 (17) 2.1 (2) 4.2 (4)
(Figures in parenthesis are number of mothers or children)
Comparative Analysis of Influential factors and Nutritional Status of Children and Mothers
Table 22 shows the relationship between BMI of mothers and Height-for-age Z-score of children. From the table we found that there was a significant association between BMI of mothers and Height-for-age Z-score of children for slum areas as P< 0.01.It can be said that this association is significant at 1% level.

No association between BMI of mothers and Height-for-age Z-score of children for non-slum areas were found.

Table 22: Value of chi-square test of Child’s Height-for-age Z-score with their mother’s BMI for slum and non-slum areas

Area Mothers’ BMI Height-for-age Z-score Total P Value
= -2.00 SD (Normal)
Slum <18.49(Malnourished) 92.5 7.5 100.0 0.000
18.50-24.99(Normal) 4.7 95.3 100.0
≥25.00 (Obese) 8.3 91.7 100.0
Non-slum <18.49(Malnourished) 26.7 73.3 100.0 0.159
18.50-24.99(Normal) 31.0 69.0 100.0
≥25.00 (Obese) 13.2 86.8 100.0

A correlation test has been carried out and given in table 23to see how strongly the two variables- BMI of mothers and Height-for-age Z-score of children for slum areas were correlated. However, from table 23, it is found that these two variables were strongly correlated as r value is nearer to 1.

Table 23: Correlations for Child’s Height-for-age Z-score with their mother’s BMI for slum area

Correlation Tests Mother’s BMI Height-for-age Z-score
Mother’s BMI Pearson Correlation 1.000 0.761**
Sig. (2-tailed) 0.0 0.000
N 95 95
Height-for-age
Z-score
Pearson Correlation 0.761** 1.000
Sig. (2-tailed) 0.000 0.0
N 95 95
** Correlation is significant at the 0.01 level (2-tailed)

Table 24 shows the relationship between education level of mothers and Weight-for-age Z-score of children of slum area. From the table we found that there was a significant association between education level of mothers and Weight-for-age Z-score of children for slum areas as P< 0.01.It can be said that this association is significant at 1% level.
Table 24: Value of chi-square test of Education level of Mothers and Weight-for-age Z-score of Children of Slum area

Education level of Mothers < -2.00 SD (Under weight) ≥ -2.00 SD (Normal) Total P value
Illiterate 61.8 38.2 100.0 .007
Upto Primary level 81.8 18.2 100.0
Completed SSC 42.9 57.1 100.0

Correlation test between the two variables- education level of mothers and Weight-for-age Z-score of children for slum areas were carried out. However, from table 25, it is seen that these two variables were moderately correlated (as r =0.141).

Table 25: Correlation of Education level of Mothers and Weight-for-age Z-score of Children of Slum area

Correlation Tests Weight-for-age Z-score Education level of Mothers
Weight-for-age Z-score Pearson Correlation 1.000 0.141
Sig. (2-tailed) 0.0 0.172
N 95 95
Education level of Mothers Pearson Correlation 0.141 1.000
Sig. (2-tailed) 0.172 0.0
N 95 95

Table 26 shows the relationship between education level of mothers and Weight-for-age Z-score of children of non-slum area. From the table we found that there was a significant association between education level of mothers and Weight-for-age Z-score of children for slum areas as P< 0.1.It can be said that this association is significant at 10% level.

Table 26: Value of chi-square test of Education level of Mothers and Weight-for-age Z-score of Children of Non-slum area
Education level of Mothers < -2.00 SD (Under nutrition) ≥ -2.00 SD (Normal) Total P Value
Primary to SSC 27.8 72.2 100.0 .094
HSC 7.4 92.6 100.0
Graduate and above 10.0 90.0 100.0
Correlation test between the two variables- education level of mothers and Weight-for-age Z-score of children for non-slum areas were carried out. However, from table 27, it is seen that these two variables were moderately correlated (as r =0.165).

Table 27: Correlation of Education level of Mothers and Weight-for-age Z-score of Children of Non-slum area

Correlation Tests Weight-for-age Z-score Education level of Mothers
Weight-for-age Z-score Pearson Correlation 1.000 .165
Sig. (2-tailed) . .110
N 95 95
Education level of Mothers Pearson Correlation .165 1.000
Sig. (2-tailed) .110 .
N 95 95

Association has been found between weaning practice between slum and non-slum area. Table 28 illustrates that there was a significant association between first starting time of weaning food in slum and non-slum areas as P< 0.01.It can be said that this association is significant at 1% level.

Table 28: Value of chi-square test of slum and non-slum Children according to starting time of Weaning

Feeding Practices Slum (%)
( n=95) Non-slum (%)
(n=95) P value
First Start of Weaning Food < 6 months 19.7 42.1 .000 6-8 months 40.8 53.7 9-12 months 35.2 2.1 > 12 months 4.2 2.1
Total 100.0 100.0

Table 29 demonstrates that there is weak correlation between Time of starting weaning Food in slum area and that is in non-slum area (as r = -0.429).

Table 29: Correlation of slum and non-slum Children according to starting time of Weaning
Correlation Tests Time of starting weaning Food Area
Time of starting weaning Food
Pearson Correlation 1.000 -.429
Sig. (2-tailed) . .000
N 166 166
Area
Pearson Correlation -.429 1.000
Sig. (2-tailed) .000 .
N 166 190
** Correlation is significant at the 0.01 level (2-tailed).

Table 30 shows the relationship between time of starting weaning food and Height-for-age Z-score of children of slum and non-slum area. From the table we found that there was a significant association between education level of mothers and Weight-for-age Z-score of children for slum areas as P< 0.05.It can be said that this association is significant at 5% level.

Association between these two variables non-slum area were found significant at 10% level (as p<0.1).

Table 30: Value of chi-square test of time of starting weaning food and Height-for-age Z-score of Children between Slum and Non-slum areas
Area Time of starting weaning Height-for-age Z-score (%)
Total P Value
= -2.00 SD (Normal)
Slum
6 month 54.4 45.6 100.0
Non-slum
6 month 30.9 69.1 100.0

Correlation test between time of starting weaning food and Height-for-age Z-score of children of slum area was carried out. However, from table 31, it is seen that these two variables were weekly correlated (as r =-0.262).

Table 31: Correlation of time of starting weaning food and Height-for-age Z-score of Children for slum area

Correlation Tests Height-for-age Z-score Time of starting weaning
Height-for-age Z-score Pearson Correlation 1.000 -.262
Sig. (2-tailed) . .027
N 71 71
Time of starting weaning Pearson Correlation -.262 1.000
Sig. (2-tailed) .027 .
N 71 95
* Correlation is significant at the 0.05 level (2-tailed).

Correlation test between time of starting weaning food and Height-for-age Z-score of children of slum area was carried out. However, from table 32, it is seen that these two variables were weekly correlated (as r =-0.152).

Table 32: Correlation of time of starting weaning food and Height-for-age Z-score of Children for non-slum area

Correlation Tests Height-for-age Z-score Time of starting weaning
Height-for-age Z-score Pearson Correlation 1.000 -.152
Sig. (2-tailed) . .140
N 95 95
Time of starting weaning Pearson Correlation -.152 1.000
Sig. (2-tailed) .140 .
N 95 95
** Correlation is significant at the 0.01 level (2-tailed).

Pearson Chi square tests for nutrient intake of slum and non-slum mothers. From table 33, it was found that there is significant difference in energy, protein, fat, carbohydrate, calcium, iron, X thiamin, riboflavin, niacin, vitamin C and Zinc intake (as for all nutrients P=0.000). There was also significant difference in vitamin A intake between slum and non-slum areas (P= 0.002). No significant difference in carotene intake was found.

Table 33: Value of chi-square test of Per Capita Nutrient Intake of slum and non-slum Mothers
Nutrients Slum (Mean) Non-slum (Mean) P Value
Energy 1544.3 2048.7 .000
Protein 39.6 79.5 .000
Fat 7.5 22.4 .000
Carbohydrate 325.9 379.8 .000
Calcium 275.6 493.5 .000
Iron 13.3 27.3 .000
Vitamin A 141.1 852.8 .002
Carotene 5078.2 6073.1 .383
Thiamin 1.08 1.77 .000
Riboflavin .38 .76 .000
Niacin 17.1 22.6 .000
Vitamin C 30.9 63.4 .000
Zinc 6.0 28.0 .000

P values for intake of roots & tubers, pulses & nuts, fruits, meats, eggs, fish, milk protein, fats & oils is less than 0.05. So it can be said that there is significant difference in intake of these foods between slum and non-slum areas.

Table 34: Value of chi-square test of Food Intake of Mothers by Food Group
Food Group Slum Non-slum P Values
Mean Mean
Roots & tubers 58 85 .019
Pulses & nuts 10 74 .000
Fruits 21 40 .039
Meats 20 63 .000
Eggs 4 14 .001
Fish 26 44 .003
Milk Protein 1 6 .044
Fats & Oils 4 12 .000

Table 35 shows the relationship between time of colostrum feeding and delivery place of slum and non-slum respondents. From the table we found that there was a significant association between these two variables for slum areas as P< 0.01.It can be said that this association is significant at 1% level.

Table 35: Value of chi-square test of Place of delivery and Colostrum feeding of slum
Delivery Place Colostrum Feeding Total P Value
Yes No
At home 31.3 68.8 100.0 .000
At NGO delivery centre 94.2 5.8 100.0
At hospital 63.6 36.4 100.0

Correlation test between time of colostrum feeding and delivery place of slum respondents was carried out. However, from table 36, it is seen that these two variables were weekly correlated (as r =-0.429).

Table 36: Correlation of Place of delivery and Colostrum feeding of slum
Correlation Tests Delivery Place Colostrum Feeding
Delivery Place Pearson Correlation 1.000 -.429
Sig. (2-tailed) . .000
N 166 166
Colostrum Feeding
Pearson Correlation -.429 1.000
Sig. (2-tailed) .000 .
N 166 190
** Correlation is significant at the 0.01 level (2-tailed).

Table 37 shows the relationship between child’s anemia and mother’s anemia for both slum and non-slum respondents. From the table, we found that there was a significant association between these two variables for slum areas as P< 0.1.It can be said that this association is significant at 10% level. A significant association between these two variables for non-slum areas was also found as P=0.000.So, It can be said that this association is significant at 1% level.

Table 37: Value of chi-square test of child’s anemia and their mother’s anemia
Area Hemoglobin level of child hemoglobin level of mother Total P Value
≥ 12 gm/dl (normal) ≤ 12 g/dl (anemic)
Slum ≥ 11 gm/dl (normal) 68.4 50.9 57.9 .068
≤ 11 g/dl (anemic) 31.6 49.1 42.1
Total 100.0 100.0 100.0
Non-Slum ≥ 11 gm/dl (normal) 97.1 33.3 78.9 .000
≤ 11 g/dl (anemic) 2.9 66.7 21.1
Total 100.0 100.0 100.0
Correlation test between child’s anemia and mother’s anemia for non-slum respondents was carried out. However, from table 38, it is seen that these two variables were strongly correlated (as r =0.486).

Table 38: Correlations of child’s anemia and their mother’s anemia in non-slum area
Hemoglobin Level Correlation Test Hemoglobin Level of Children Hemoglobin Level of Mother
Hemoglobin Level of Children Pearson Correlation 1.000 .486
Sig. (2-tailed) . .000
N 95 95
Hemoglobin Level of Mother Pearson Correlation .486 1.000
Sig. (2-tailed) .000 .
N 95 95
** Correlation is significant at the 0.01 level (2-tailed).

Table 39 shows the relationship between hemoglobin level of child and Height-for-age Z-score for both slum and non-slum respondents. From the table, we found that there was a significant association between these two variables for slum areas as P< 0.01.So, It can be said that this association is significant at 1% level. A significant association between these two variables for non-slum areas was also found at 10% level (as p=0.062).

Table 39: Value of chi-square test of Hemoglobin level of child and Height-for-age Z-score
Area Height-for-age Z-score hemoglobin level of Child Total P Value
≥ 11 g/dl (normal) ≤ 11 g/dl (anemic)
Slum < -2.00 SD
(Under nutrition) 21.8 82.5 47.4 .000
≥ -2.00 SD
(Normal) 78.2 17.5 52.6
Total 100.0 100.0 100.0
Non-Slum < -2.00 SD
(Under nutrition) 16.0 35.0 20.0 .062
≥ -2.00 SD
(Normal) 84.0 65.0 80.0
Total 100.0 100.0 100.0

Correlation test between hemoglobin level and Height-for-age Z-score of children for slum area was carried out. Table 40 shows that these two variables were strongly correlated (as r =0.471).

Table 40: Correlations of hemoglobin level and Height-for-age Z-score of slum children
Variables Correlation Test Hemoglobin Level of Children Height-for-age Z-score
Hemoglobin Level of Children Pearson Correlation 1.000 .471
Sig. (2-tailed) . .000
N 190 190
Height-for-age Z-score Pearson Correlation .471 1.000
Sig. (2-tailed) .000 .
N 190 190
** Correlation is significant at the 0.01 level (2-tailed).

Table 41 shows the relationship between BMI of Mothers and percentage of fulfillment of RDA of mothers of slum and non-slum respondents. From the table we found that there was a significant association between these two variables for slum areas as P< 0.01.It can be said that this association is significant at 1% level.

For non-slum area significant association was found at 5% level as P

Table 41: Value of chi-square test of BMI of Mothers and percentage of fulfillment of RDA of mothers
Area BMI of Mothers Classification Total P Value
Energy intake
<75% of required Energy intake
≥75% of required
Slum <18.49
(Malnourished) 75.0 25.0 100.0 .003
18.50-24.99 (Normal) 93.0 7.0 100.0
≥25.00 (Obese) 50.0 50.0 100.0
Non-Slum <18.49
(Malnourished) 66.7 33.3 100.0 .041
18.50-24.99 (Normal) 40.5 59.5 100.0
≥25.00 (Obese) 66.7 33.3 100.0

Correlation test between BMI of Mothers and percentage of fulfillment of RDA of mothers of slum area was carried out. However, from table 42, it is seen that these two variables were weekly correlated (as r =-0.062).

Table 42: Correlations of BMI of Mothers and percentage of fulfillment of RDA of mothers of slum area
Variables Correlation Test BMI of Mother Percentage of fulfillment of RDA
BMI of Mother Pearson Correlation 1.000 .062
Sig. (2-tailed) . .550
N 95 95
Percentage of fulfillment of RDA Pearson Correlation .062 1.000
Sig. (2-tailed) .550 .
N 95 95
** Correlation is significant at the 0.01 level (2-tailed).

Correlation test between BMI of Mothers and percentage of fulfillment of RDA of mothers of non-slum area was carried out. However, from table 43, it is seen that these two variables were moderately correlated (as r =-0.249).

Table 43: Correlations of BMI of Mothers and percentage of fulfillment of RDA of mothers of non-slum area
Variables Correlation Test BMI of Mother Percentage of fulfillment of RDA
BMI of Mother Pearson Correlation 1.000 .249
Sig. (2-tailed) . .015
N 95 95
Percentage of fulfillment of RDA Pearson Correlation .249 1.000
Sig. (2-tailed) .015 .
N 95 95
** Correlation is significant at the 0.01 level (2-tailed).

Association has been found between having sanitary toilet facilities and worm infestation of mothers of slum area. Table 44 illustrates that there was a significant association between these two variables. As P< 0.01.It can be said that this association is significant at 1% level.

Table 44: Value of chi-square test of having sanitary toilet facilities and worm infestation of mothers of slum area
Sanitary latrine Worm infestation of mother P Value
Yes No
Yes 16.7 80.9 .000
No 83.3 19.1
Total 100.0 100.0

Correlation test between having sanitary toilet facilities and worm infestation of mothers of slum area was carried out. Table 45 illustrates that these two variables were weekly correlated (as r = -0.370).

Table 45: Correlation between having sanitary toilet facilities and worm infestation of mothers of slum area
Variables Correlation Test Sanitary latrine Worm infestation
of mother
Sanitary latrine Pearson Correlation 1.000 -.370
Sig. (2-tailed) . .000
N 95 95
Worm infestation of mother Pearson Correlation -.370 1.000
Sig. (2-tailed) .000 .
N 95 95
** Correlation is significant at the 0.01 level (2-tailed).
Causal analysis and modeling of nutritional status of children and mothers

Table 46: Regression analysis of Child’s HAZ with other independent variables of slum
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) -8.716 2.154 -4.047 .000
Mother’s Hemoglobin level 0.06754 .124 .054 .544 .588
Mother’s BMI 0.02362 .035 .069 .909 .364
No. of abortions -0.163 .245 -.090 -.665 .508
Child Hemoglobin level 0.512 .141 .354 3.628 .000
Dependent Variable: WHOHAZ

Table 46 shows the correlation coefficient between the dependent variable Height-for-age of slum children with the independent variables.

The equation that can be formed from this table is given below:

WHOHAZ = -8.716 + 0.06754 (Mother’s Hemoglobin level) + 0.02362 (Mother’s BMI) – 0.163 (No. of abortions) + 0.512 (Child Hemoglobin level

So, it is evident that in slum areas, with the increase of 1 unit change in mother’s hemoglobin level, child’s HAZ will positively change almost for 0.07 unit, with the increase of 1 unit change in mother’s BMI Child’s HAZ will positively change almost for 0.02 unit, with the increase of 1 unit change in No. of abortions, Child’s HAZ will decrease for almost 0.16 unit and for 1 unit change in child hemoglobin level, child’ HAZ will be positively change for 0.51 unit.

Table 47: Regression analysis of Child’s WAZ with other independent variables of slum
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) -3.769 1.029 -3.665 .000
No. of abortions -0.01263 .115 -.011 -.109 .913
Child Hemoglobin level 0.133 .093 .149 1.435 .155
Dependent Variable: WHOWAZ

Table 47 shows the correlation coefficient between the dependent variable Weight-for-age of slum children with the independent variables.

The equation that can be formed from this table is given below:
WHOWAZ = -3.769- 0.1263(No. of abortions) + 0.133 (Child Hemoglobin level)

So, it is evident that within slum areas, the increase of 1 unit change in No. of abortions, Child’s WAZ will decrease for almost 0.13 unit and for 1 unit change in child hemoglobin level, child’s WAZ will be positively change for 0.13 unit.

Table 48: Regression analysis of Child’s WHZ with other independent variables of slum
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) -1.662 1.014 -1.639 .105
No. of abortions -0.02232 .176 -.013 -.127 .899
Mother’s Hemoglobin level 0.01159 .047 .026 .247 .806
Dependent Variable: WHOWHZ

Table 48 shows the correlation coefficient between the dependent variable weight-for-height of slum children with the independent variables.

The equation that can be formed from this table is given below:

WHOWHZ = -1.662 – 0.02232 (No. of abortions) + 0.01159 (Mother’s Hemoglobin level

So, it is evident that in slum areas, with the increase of 1 unit change in mother’s hemoglobin level, child’s WHZ will positively change almost for 0.01 unit, with the increase of 1 unit change in No. of abortions, Child’s WHZ will decrease for almost 0.02 unit.

Table 49: Regression analysis of Child’s HAZ with other independent variables of non-slum
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) -7.962 1.877 -4.243 .000
Per capita monthly food cost .005798 .004 .106 1.340 .182
Mother’s Hemoglobin level 0.05411 .111 .035 .487 .627
Mother’s BMI 0.03156 .035 .069 .909 .364
Child Hemoglobin level 0.445 .115 .271 3.883 .000
Dependent Variable: WHOHAZ

Table 49 shows the correlation coefficient between the dependent variable Height-for-age of non-slum children with the independent variables.

The equation that can be formed from this table is given below:

WHOHAZ = -7.962 + .005798 (Per capita monthly food cost) + 0.06754 (Mother’s Hemoglobin level) + 0.02362 (Mother’s BMI) + 0.512 (Child Hemoglobin level)

So, it is evident that in non-slum areas, with the increase of 1 unit change in per capita monthly food cost, child’s HAZ will positively change almost for 0.005 unit, with the increase of 1 unit change in mother’s hemoglobin level, child’s HAZ will positively change almost for 0.05 unit, with the increase of 1 unit change in mother’s BMI, Child’s HAZ will positively change almost for 0.03 unit and for 1 unit change in child hemoglobin level, child’ HAZ will be positively change for 0.45 unit.

Table 50: Regression analysis of Child’s WAZ with other independent variables of non-slum
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) -4.051 .886 -4.575 .000
Per capita monthly food cost 0.01586 .003 .392 5.420 .000
Child Hemoglobin level 0.120 .078 .099 1.531 .127
Protein intake of mother 0.004079 .002 .119 1.648 .101
Dependent Variable: WHOWAZ

Table 50 shows the correlation coefficient between the dependent variable Weight-for-age of non-slum children with the independent variables.
The equation that can be formed from this table is given below:
WHOWAZ = -4.051 + 0.02 (Per capita monthly food cost) + 0.12 (Child Hemoglobin level) + 0.004 (Protein intake of mother)
So, it is evident that in non-slum areas, with the increase of 1 unit change in per capita monthly food cost, child’s WAZ will positively change almost for 0.02 unit and for 1 unit change in child hemoglobin level, child’ WAZ will be positively change for 0.004 unit and for 1 unit change in protein intake of mother, 0.004 unit positive change will take place for Child’s WAZ.

Table 51: Regression analysis of Child’s WHZ with other independent variables of non-slum area
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) -2.080 .338 -6.153 .000
Protein intake of mother 0.01082 .004 .202 2.586 .010
Per capita monthly food cost 0.0208 .005 .191 2.466 .015
No. of abortions -0.01636 .155 -.007 -.106 .916
Dependent Variable: WHOWHZ

Table 51 shows the correlation coefficient between the dependent variable weight-for-height of non-slum children with the independent variables.

The equation that can be formed from this table is given below:

WHOWHZ = -2.080 + 0.0208 (Per capita monthly food cost) + 0.01082 (Protein intake of mother) – 0.01636 (No. of abortions)

So, it is evident that in non-slum areas, for 1 unit change in protein intake of mother, 0.01 unit positive change will take place for Child’s WAZ, with the increase of 1 unit change in per capita monthly food cost, child’s WHZ will positively change almost for 0.02 unit, with the increase of 1 unit change in No. of abortions, Child’s WHZ will decrease for almost 0.01 unit.

From these results (table 46, 47, 48, 49, 50, 51) it can be said that the general hypothesis which was assumed for the study is proved as there are different influential factors affecting nutritional status of slum and non-slum children aged 6 to 24 months.

Table 52: Regression analysis of Mother (BMI) with other independent variables of slum

Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) 14.629 3.822 3.827 .000
Energy intake of mother 0.04545 .023 .206 2.007 .048
Mother’s Hemoglobin level 0.257 .275 .099 .935 .352
Parity -0.329 .408 -.115 -.806 .422
Per capita monthly food cost 0.06429 .056 .123 1.151 .253
Dependent Variable: Mother’s BMI

Table 52 shows the correlation coefficient between the dependent variable mother’s BMI of slum with the independent variables.

The equation that can be formed from this table is given below:

Mother’s BMI = 14.629 + 0.04545 (Energy intake of mothers) +0.257 (Mother’s Hemoglobin level) – 0.329 (Parity) – 0.543 (No. of abortions) + 0.06429 (Per capita monthly food cost)

So, it is evident that in slum areas, for 1 unit change in energy intake of mother, 0.05 unit positive change will take place for mother’s BMI, with the increase of 1 unit change in mother’s hemoglobin level, mother’s BMI will positively change almost for 0.26 unit, with the increase of 1 unit change in parity, mother’s BMI will decrease for almost 0.33 unit and with the increase of 1 unit change in per capita monthly food cost, mother’s BMI will positively change almost for 0.06 unit.
Table 53: Regression analysis of Mother (BMI) with other independent variables of Non-slum

Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
(Constant) 18.591 2.878 6.460 .000
Per capita monthly food cost 0.04787 .009 .398 5.143 .000
Parity -0.02429 .211 -.008 -.115 .909
Mother’s Hemoglobin level 0.113 .238 .034 .473 .637
Energy intake of mother 0.02541 .023 .206 2.007 .048
Dependent Variable: Mother’s BMI

Table 53 shows the correlation coefficient between the dependent variable non- slum mother’s BMI with the independent variables.
The equation that can be formed from this table is given below:

Mother’s BMI = 18.591 + 0.04787 (Per capita monthly food cost) – 0.02429 (Parity) + 0.113 (Mother’s Hemoglobin level) + 0.02541 (Energy intake of mothers)

So, it is evident that in non-slum areas, with the increase of 1 unit change in per capita monthly food cost, mother’s BMI will positively change almost for 0.05 unit, with the increase of 1 unit change in mother’s hemoglobin level, mother’s BMI will positively change almost for 0.11 unit and for 1 unit change in energy intake of mother, 0.03 unit positive change will take place in case of mother’s BMI.

From these results (table 52, 53) it can be said that the general hypothesis which was assumed for the study is proved as there are different influential factors affecting the nutritional status of mothers having children aged 6 to 24 months in selected slum and non-slum areas.

Chapter 6
Discussion

This is a cross sectional comparative study which was conducted to assess and compare the nutritional status of children aged 6 to 24 months and their mothers between the selected slum and non-slum areas of Dhaka city. In the study, a comparative picture was found between target populations of slum and non-slum areas of Dhaka city in respect to socio-economic and demographic condition, KAP regarding pregnancy, delivery, lactation, child feeding practices, morbidity and treatment seeking behavior as well as anthropometric, dietary, biochemical and clinical assessment. These findings of the study has been compared with different national level studies conducted mostly from Bangladesh Demographic and Health Survey (BDHS, 2007), Child and Maternal Nutrition Survey of Bangladesh (CMNS, 2005), Bangladesh National Nutrition Survey (BNNS,1995-96), Study of Urban Poverty in Bangladesh (2005) as well as few studies similarly done in abroad.

In this study it is found that, 16.8 % households of slum had a monthly income less than Tk. 4000, 12.6 % had a monthly income Tk. 10001-15000. (figure 6) In case of non-slum areas, 2.1 % households of non-slum areas had a monthly income within Tk. 10001 -15000, 6.3 % had a monthly income Tk.15001-20000, 47.4 % had a monthly income Tk.20001 -30000 (figure 7).According to a study to assess the determinants of malnutrition among the children under 2 years of age of Dhaka city 28% of the respondents’ family monthly income was below Tk.3001-5000, 3.6% were below Tk.20000-25000 and 16.4% were Tk.10000-15000.35 It is seen that monthly income is lower in slum and higher in non-slum areas in this study compared to the previous study in Dhaka.

In the study, the mean food cost in slum and non-slum areas was Tk.5242 and Tk11858. The mean house rent cost was Tk.1279 and Tk.11721 for slum and non-slum areas. According to Study of Urban Poverty in Bangladesh (2005) the urban poor mostly spend their earnings to fulfill their basic needs especially for food and shelter. 37 So, the findings are similar to this result though there were quite difference in both study sample.

In the studied slum areas, 35.8 percent of the mothers were illiterate, no mother in the slum reported completed H.S.C. level and 30.5 percent of the main income earner were illiterate, only 5.3 percent had completed H.S.C (table 3). According to an UNESCO report, education figures for slums in Bangladesh’s capital Dhaka are among the worst in the South-Asian country.10 The result in the study also suggests that the education level in slum areas were also very low.
In this study, 18.9% completed primary level and 28.4% had completed H.S.C., 52.6 percent mothers were graduate or more educated. (table 3) According to a study to assess the determinants of malnutrition among the children under 2 years of age of Dhaka city, 24.4% mothers completed primary level, 32% completed secondary level, 11.1% completed higher secondary level and 11.1% mothers were graduate.35 Though these studies are different in sample selection and methodology, education level of non-slum mothers is found higher in this study.

In the study, 43.2 percent non-slum women got married and only 21.1 percent slum women got married (figure 9). According to BNNS (1995-96), 54.2 percent urban women get married at the age of 15 to 18 years. 35 So, it is evident that there is a huge difference in case of mother’s age at marriage between slum and non-slum areas even in respect to national data. Use of family planning has increased steadily in Bangladesh. In 2007, 80 percent of ever-married women of reproductive age reported having used a family planning method at some time, compared with only 14 percent in 1975; this is more than a fivefold increase over the past three decades. 18 In the study, only 30 percent of slum mothers and 67 percent of non-slum mothers adopted family planning (figure 10, 11). So, in compare to the national data the study population in both slum and non-slum areas use family planning.

In this study, 66.3 percent of births in slum areas took place at a health facility, mostly in NGO sector- BRAC delivery center. In non-slum areas 91.6 percent child birth took place in hospitals or clinics (table 8).The 2007 BDHS shows that 15 percent of births in Bangladesh take place at a health facility, about half in the public sector and half in the private/NGO sector. 18 So, both slum and non- slum areas in the study showed better situation in terms of place of delivery of child.
In this study, 30.5 and 66.3 percent child birth was caesarean is slum and non-slum areas respectively (table 8). According to the 2007 BDHS, 8 percent of babies born in the five years preceding the survey were delivered by caesarean section. 18 Though there were difference between these two studies in terms of sample size and methodology, it can be said that caesarean deliveries were found many times manifold than that in this study.

Breastfeeding is almost universal in Bangladesh. In the study, 89.5 percent of slum children and 93.7 percent from non-slum areas were breastfed at some point (figure 14). According to BDHS 2007, 98 percent Bangladeshi children were breastfed13. However, according to BDHS 2007, 92 percent of last-born children received first milk or colostrum. The likelihood of a child receiving colostrum increases with mother’s education and, to a lesser degree, household wealth. Children who are born in urban areas, who are born at health facilities, and whose birth is attended by a health professional are more likely to receive colostrum than other children.18 Among the studied children 69.5 percent of slum areas and 77.9 percent of non-slum areas were given colostrum (table 10). It was also found that place of delivery and colostrum feeding were correlated (table 35). So, it can be concluded that breast feeding rate is almost same but colostrum feeding rate is lower in both studied slum and non-slum areas in respect to national survey.

Pre-lacteal feeding is widely practiced in Bangladesh. Among the studied children, the rate of pre-lacteal feeding was 38.9 percent and 32.6 percent in slum and non-slum areas respectively (figure 12).According to BDHS, more than six in ten newborns (62 percent) receive a pre-lacteal feed. Pre-lacteal feeds are more common in Dhaka, Khulna and Rajshahi, compared with the other divisions. 18 In this study, 56.8 percent among non-slum children and 41.1 percent among slum children were breast fed immediately after birth. Again, 25.3 and 16.8 percent children were breastfed within one day after delivery (figure 14).According to BDHS 2007, overall, 43 percent of children are breastfed within one hour of birth, and 89 percent are breastfed within one day after delivery. Initiation of breastfeeding within one day after birth is highest in Barisal (92 percent) and lowest in Dhaka (88 percent) according to BDHS 2007. 18 So, though the study was quite different in respect to sample size and other issues it can be said that pre-lacteal feeding and the percentage of starting breast feeding immediately after birth is found much lower in both slum and non-slum areas in respect to national survey.

In this study we found that, 51.8 percent slum children and 49.5 percent non-slum children were exclusively breast feed (figure 15). According to BNNS (1995-96), 10.8 percent urban children aged 0 to 24 months was exclusively breastfed. 38 So, we can say that exclusive breast feeding practice has changed positively by these years in both of the studied slum and non-slum areas in respect to national data.

In the study, among slum children prevalence of diarrhoea was most common and among non-slum children fever and cold was found most frequently occurring diseases (table 14). According to BDHS, Major contributors to childhood morbidity and mortality in Bangladesh takes place due to childhood diarrhoea, acute respiratory infection (ARI) and fever. Among children under 5 years of age, 5 % showed the symptoms of acute respirator illness and 38 percent of children under five years had a fever in the two weeks preceding the survey. 18 However, in this study almost same, 19.5 percent of slum children and 24.4 percent of non-slum children were found suffered from both fever and cold. Again 7.3 and 28.9 percent children from slum and non-slum areas were suffering from fever only (table 14). Though this study differed much from the survey in respect to sample size and methodology, it can be said that suffering from fever is lower but suffering from cold or respiratory illness is higher among both slum and non-slum target children in respect to BDHS 2007.

In this study, mean height-for-age z-score, weight-for-age z-score, height-for-weight z-score for slum children are -1.72, -2.30 and 1.43 respectively. Mean height-for-age z-score, Weight-for-age z-score, height-for-weight z-score for non-slum children are -0.76, -0.74, -0.05 respectively (Table 15).According to a study on children under 3 years of age in Vietnam in 2007, the mean Z-score for height-for-age was -1.51 , for weight-for-age was -1.51s and for weight-for-height was -0.63.25 so, it can be said that mean height-for-age z-score, weight-for-age z-score and height-for-weight z-score for slum children is lower but non-slum children is higher in compare to data for Vietnam.

In this study, 49 percent slum male children have normal nutritional status, 33.3 percent are moderately stunted and 17.6 percent are severely stunted. Among slum female children 56.8 percent have normal nutritional status, 17.6 percent are moderately stunted and 11.4 percent are severely stunted. However in case of non-slum children, 84.5 percent male children are not stunted, for female children this percentage is 76 percent. Among them 11.1 percent boy and 12 percent girl are moderately stunted, 4.4 percent boy and 12 percent girl are severely stunted. (table 16)According to a comparative study on nutritional status among pre-school children living in rural, slum and urban Dhaka by ICDDRB-HKI, in Bangladesh the prevalence of stunting (%

In this study, among slum male children 68.6 percent were not wasted, 19.6 percent were moderately wasted and 9.8 percent were severely wasted. Among slum female children 63.6 percent had normal nutritional status, 22.7 percent were moderately wasted and 13.6 percent were severely wasted. However in case of non-slum children 82.2percent male children were found not wasted, for female children this percentage was 74 percent. Among them 8.9 percent boy and 6.0 percent girl were moderately wasted, 8.9 percent boy and 4 percent girl were severely wasted. However 2.0 percent slum male children were found over weight, on the contrary among non-slum children 16 percent female were found obese (table 17). According to a study of IPHN-HKI, Severity of child wasting (Low weight of height) was poor (4-8%) and this prevalence was higher among 0-23 months old children in the slums of Dhaka.9 So, the result of the study concludes almost similarly of the result of the study of HKI.

In the study, slum male children 29.4 percent had normal nutritional status, 45.1 percent were moderately under weight and 25.5 percent were severely under weight. Among slum female children 45.5 percent had normal nutritional status, 40.9 percent were moderately under weight and 13.6 percent were severely under weight. However in case of non-slum children 77.8 percent male children were not found under weight, for female children this percentage was 94 percent. Among the slum 22.2 percent boy and 6 percent girl were moderately under weight (figure 21). BDHS 2007 Weight-for-age results show that 41 percent of children under five are underweight, with 12 percent are severely underweight in our country.18 So, the result of this study concludes almost similarly of the result of the national study.

In this study, the mean BMI of mothers from slum and non-slum areas are 21.23 kg/m² and 24.17 kg/m² respectively (table 18) and the mean BMI for women aged 15 to 49 years was 20.6 kg/m² according to BDHS 2007 and BDHS 2007 also shows that about six in ten women (59 percent) are considered to have normal BMI, while 30 percent are undernourished or thin (BMI less than 18.5), and 12 percent are overweight or obese (BMI 25 or higher). 18 Whereas in this study, 55.3 percent non-slum mothers had normal nutritional status, 28.9 percent were obese and 15.8 percent were malnourished according to their BMI. It was also found that 45.3 percent slum mothers had normal nutritional status, 12.6 percent were obese and 42.1 percent were malnourished according to their BMI (figure 22). So, it can be said that the mean BMI of mothers for both slum and non-slum areas are higher comparing to the national data but the percentage of mothers having normal BMI in this study was less than that of in BDHS 2007.

In this study, 42.1 percent children aged 6-24 months of slum are anemic (figure 23). Special study from the urban slum sides of the GOB/HKI nutrition surveillance project (NSP) showed that 75.8 percent of children aged 6-59 months suffered from anemia. 9 So, it is seen that prevalence of anemia is lower in studied slum areas than that of in NSP. In this study, in non-slum areas 21.1 percent children aged 6-24 months are found anemic (figure 23). According to BNNS (1995-96), 35.6 percent urban male children aged 6 to 71 months were anemic and 43.3 percent female children were anemic. So, it can be said that prevalence of anemia in non-slum areas are lower comparing to national data for urban children. 31

Again according to BNNS (1995-96), 80.9 percent lactating female were anemic whereas in the study 60 percent of slum and 28.4 percent of non-slum lactating mothers were anemic (figure 24). So, prevalence of anemia both in studied slum and non-slum areas are lower than that of in national survey report. 31

In this study, daily average intake of cereal of lactating mothers is 374 g and 387 g for slum and non-slum areas, root and tuber intake is 58 and 85 g for slum and non-slum areas, pulse intake is 10 g and 74 g for slum and non-slum areas, fruit intake is 21 g and 40 g, fish intake is 26 and 44 g, meat intake is 20 and 63 g, fat intake is 4g and 12 g (table 19). According to BNNS (1995-96), daily average cereal intake of lactating mothers was 437.1 g, root and tuber intake was 69.2 g, pulse intake was 69.2 g, fruit intake was 4.4 g, fish intake was 47.3 g, meat intake was 15.2 g and fat intake was 8.4 g. 31 So, it can be concluded that, in comparison to national survey report, cereal intake of the studied population is less among both slum and non-slum mothers, root and tuber intake is lesser in slum areas and higher in non-slum areas, pulse intake is very low among slum mothers whereas that is much higher among non-slum mothers, Fruit and meat intake is higher in both slum and non-slum areas and fish intake is lower in both slum and non-slum areas than for all populations of Dhaka city

In this study, mean energy intake of slum mothers is 1544.3 Kcal and for non-slum mothers it is 2048.7 kcal. Mean protein intake of slum mothers is 39.6 g and for non-slum mothers it is 79.5 g. Again, mean iron intake of slum mothers is 13.3 mg and for non-slum mothers it is 27.3 mg. In case of vitamin intake, mean vitamin A intake of slum mothers is 141.1 IU and for non-slum mothers it is 852.8 IU. However, mean vitamin C intake of slum mothers is 30.9 mg and for non-slum mothers it is 62.3 mg (table 20). According to BNNS, per capita nutrient intake of population of Dhaka city in 1995-96 was 1692.2 kcal calorie, 50.56 g protein, 32.50 g fat, 299 g carbohydrate, 17 mg iron, 2834 IU vitamin A and 46.15 mg vitamin C. 31 For each nutrient amounts taken by slum mothers were less and amounts taken by non-slum mothers were higher than that of the BNNS data mentioned previously.

According to BNNS (1995-96), prevalence of sparce hair among urban lactating mothers is 15 percent31, which is 14.7 percent among slum mothers in the study (table 21). However, 2 percent children aged 0 to 4 years were found having knock knee or bowed leg31, whereas 4.2 percent target slum children had bowed leg or knock knee (table 21). Though there are differences in sample size and methodology to some extent between national survey and this study, prevalence of sparce hair of mothers has found almost same in these two studies. But prevalence of knock knee or bowed leg in slum children has found higher than the national data.
Conclusion

The study revealed nutritional profile of target child-mother pairs between slum and non-slum areas of Dhaka city from the specific point of views of socio-economic and demographic situation, Knowledge, Attitude and Practice (KAP) of pregnancy, delivery and lactation, child feeding practices, dietary intake pattern of the mothers, morbidity pattern of children and treatment seeking behavior. Comparative analysis was done to explore comparison of the existing situations between the slum and non-slum target populations. A conceptual framework was developed to address all influential factors affecting the existing nutritional situation of both slum and non-slum areas in the context of our country under the general hypothesis assumed for the study.

In the study, differences were found between slum and non-slum respondents in respect to education level and occupation of mothers and main income earners, income, utility facilities, age of marriage of mothers, adoption of family planning, child spacing, percentage of expenditure on house rent, place of delivery, type of delivery, age of child birth, knowledge about anemia, prevalence of anemia among pregnant mother, iron, folic acid supplementation, supplement formula milk , feeding cerelac as complementary food, child’s age of starting weaning food, frequency of child’s diseases and practice of visiting physician for treatment of children.

On the other hand, almost no differences were found between slum and non-slum respondents in respect to parity (as most of the target children were the first baby among slum population), numbers of abortion, colostrum feeding, time of first introducing breast milk and percentage of exclusive breast feeding.

Prevalence of moderate stunting in slum areas (45.1 percent male, 40.9 percent female) was higher than that of non-slum areas (11.1 percent male, 12.0 percent female) with moderate wasting was also being higher in slum areas (19.6 percent male, 22.6 percent female) than that of non-slum areas (8.5 percent male, 6.3 percent female).Within the slum children 29.4 percent male and 45.5 percent female were not under weight while in non-slum children the percentages were higher (77.8 percent male, 94 percent female). However, 4.3 percent male and 14.6 percent female children were found over weight in non-slum areas, whereas no evidence of over weight in slum areas was found. Slum mothers (42.1 percent) were more malnourished than non-slum mothers (15.8 percent) with obese children being 28.9 percent and 12.6 percent respectively. Prevalence of anemia was double among slum children (42.1 percent) than those of non-slum (21.1 percent), whereas the prevalence of anemia among mothers was 60 percent for slum areas and 28.4 percent for non-slum areas. At least 75 percent of RDA for energy was fulfilled only among 24.25 percent slum mothers and 63.8 percent non-slum mothers. However, 26.3 percent mothers and 17.9 percent children had discolored hair, 11.6 percent mothers and 6.3 percent children had angular stomatitis as well as, 6.3 percent mothers and 17.9 percent children had worm infestation in slum areas.

Significant associations between BMI of mothers and HAZ of children (P< 0.01, r=0.761) for slums, education level of mothers and WAZ of children (P< 0.01, r==0.141)) for non-slum areas were found. A significant difference was found for energy, protein, fat, carbohydrate, calcium, iron, thiamin, riboflavin, niacin, vitamin C and Zinc intake (as for all nutrients P<0.01). Significant association was found between child’s anemia and mother’s anemia for non-slum areas (P<0.01, r= 0.486). A significant association was found between child’s hemoglobin level and HAZ for slum areas as P< 0.01, as r =0.471. For non-slum area significant association between BMI of mothers and percentage of fulfillment of RDA of mothers was found at 5 percent level. A significant association was found between having sanitary toilet facilities and worm infestation of mothers in slum areas as P< 0.01, r = -0.37.

Positive correlation for HAZ of children with mother’s hemoglobin level, mother’s BMI, child hemoglobin level in slum areas and with per capita monthly food cost, mother’s hemoglobin level, mother’s BMI, child hemoglobin level in non-slum areas was found. In case of child’s WAZ in slum areas child hemoglobin level had positive and number of abortions had negative correlation and in non-slum areas per capita monthly food cost, child hemoglobin level, protein intake of mother had positive correlation with child’s WAZ. It was evident that in slum areas mother’s hemoglobin level had positive and number of abortions had negative correlation with child’s WHZ and in non-slum areas protein intake of mother, per capita monthly food cost had positive and number of abortions had negative correlations. Mother’s BMI was positively correlated with energy intake, mother’s hemoglobin level, per capita monthly food cost was negatively correlated with parity and in non-slum areas per capita monthly food cost, mother’s hemoglobin level, energy intake of mothers were seen positively correlated with mother’s BMI.

The findings of this study indicate that malnutrition is an alarming problem among children aged 6 to 24 months and their mothers in slum areas. Existing risk factors and prevalence of malnutrition in non-slum areas can not be neglected also. Socio-economic, environmental factors and feeding practices are risk factors for malnutrition among children aged 6 to 24 months in our country. This study also identified that a greater risk of malnutrition was associated with poor KAP of mothers regarding pregnancy, delivery, lactation, child feeding practices, treatment seeking behavior. Twenty four hours dietary recall method brought up the miserable picture mostly of slum mothers suffering from poor quality and quantity of food at that stage of life when dietary requirement is the highest for them. Comparatively poor knowledge and high prevalence of anemia was found in both slum and non-slum areas. Thus the hypothesis of the study assumed before has been proved from the above findings.
These findings are very important, suggesting the need for improving KAP of mothers on these aspects and taking other measures to combat malnutrition. Urban planning for health interventions and infrastructure for increasingly large slum areas needs to be undertaken in future.
Recommendations

The study highlighted the existing situation of nutritional status, KAP in terms of pregnancy, lactation, feeding practices and health seeking behavior of the respondents households in both slum and non-slum areas of Dhaka city. Based on the study findings and comparative analysis the following recommendations are given below:

In order to improve the nutritional status of children (aged 6 to 24 months) among slum population, extensive behavior change communication in terms of nutritional awareness and appropriate feeding practices needs to be strengthened by both government and NGO activities. Information on feeding practices can also be disseminated using various electronic media channels for the urban population. There is a national Infant and Young Child Feeding (IYCF) strategy in our country but there is no implementation plan. So a systematic planning is required for IYCF strategy to bring the desired impact.

To tackle the problem of anemia periodic de-worming of the children as well as ensuring iron folate tablet to pregnant women needs to be carried out.

Ensuring nutrition education for adolescent girls, pregnant and lactating mothers with innovative approaches of dissemination of information should be developed instead of traditional education procedure so that the target population can adopt it easily and effectively.
An emphasis on adoption of family planning services can also help in improving the child health situation in slum area.

A social safety net program should be introduced for children aged 6 to 24 months from poor households as well as pregnant women and severely malnourished mothers and children by supplementary feeding program.

Growth monitoring and promotion of low birth weight (LBW) babies, malnourished (mild to moderate) children and undernourished pregnant women should be followed up.

Slum area will have to be developed expeditiously with utility facilities, drains, and needed to be upgraded with all other amenities to give the occupants a new facelift.

Systematic surveys are needed to be undertaken in both slum and non-slum areas to update comparison among health and nutritional status of vulnerable groups.

Chapter 7
References

UNICEF report, ‘Child and Maternal Nutrition in Bangladesh’, April 2009.

Arifeen SE, Black RE, Caulfield LE, Antelman G, Baqui AH. Determinants of infant growth in the slums of Dhaka: size and maturity at birth, breastfeeding and morbidity. Eur J Clin Nutr 2001; 53: 167-178.

Bangladesh Child and maternal nutrition Survey, 2005

Schneider K, Roy P K and Hasan, Emergencies, Emergency impact and Nutrition surveys, Issue 36, p.28, July 2009.

Victora, C. G., L. Adair, C. Fall, P. C. Hallal, R. Martorell, L. Richter, H. Singh Sachdev, for the Maternal and Child Undernutrition Study Group. 2008. Maternal and child undernutrition: Consequences for adult health and human capital. The Lancet 371 (9609): 340–57.

Understanding Urban Inequalities in Bangladesh; a prerequisite for achieving Vision 2021, UNICEF Bangladesh, November 2010

Sting A. Uber Urbanization, Verelendun and Gesundhei Kolumbien. Offiztelles Gesundherts-wesen 1990; 52: 277-281.

Kiess L., Comparison of Nutritional Status among Pre-school Children Living in Rural, Slum and Urban Dhaka,Helen Keller International – the International Centre for Diarrhoeal Disease Research, Bangladesh, December 1996.

HKI/IPHN, High anemia prevalence among Bangladeshi children in urban slums. Nutritional Surveillance Project Bulletin No. 1. HKI, Dhaka, 2000.

Rubel, MD., Slums In Dhaka City: Life of Misery, May 2010

‘Health and Nutrition Surveillance for Development’, November 2002g, Annual Report 2001, NSP, HKI Bangladesh, pp: 99-117.

“Health, Nutrition and Population Sector Program (HNPSP, July 2003 – June 2006)”, Program Implementation Plan (PIP), October 2003.

Bangladesh Census of Urban Slums, 2005

‘Health and Nutrition Surveillance in Urban slums in Dhaka, Khulna and Chittagong divisons’, Annual Report 2001, NSP,HKI, Bangladesh, Bulletin No. 9, 10, 11, November 2002d, 2002e, 2002f.

Trends in child malnutrition, 1990 to 2005, Nutritional Surveillance Project, Bulletin No. 19, August 2006

Noorani S, Multiple Indicators Clusters Survey Bangladesh (MICS) 2006, BBS-UNICEF, Dhaka, May 2007.

Bhuyan MAH, Report on evaluation of UPHCP-1 and developing a package of Nutrition and Health interventions for UPHCP-2, May 2004.

Bangladesh Demographic and Health Survey, NIPORT, Final Report, 2007.

Gupta A, Dadhich J. P., Faridi M.M.A., Indian Journal of Pediatrics, Vol: 361, pp: 2226-2234, 2010.

Allen, LH and Gillespie, SR., “What Works? A review of the Efficacy and Effectiveness of Nutrition Interventions”, ADB with UN ACC Sub-committee on Nutrition, 2001.

UNICEF 2003–08. Mali: Statistics, Tracking progress on child and maternal nutrition: A survival and development priority. New York, 2009b.

“Bangladesh National Food and Nutrition Policy”, 1997, Ministry of Health and Family Welfare, Government of the Peoples Republic of Bangladesh.

Child Nutrition Survey (CNS) of BBS, 2002.

The Challenge of Hunger: Focus on the Crisis of Child Under Nutrition, Global Hunger Index, 2010.

Nguyen Ngoc Hien, Nguyen Ngoc Hoa, Nutritional Status and Determinants of Malnutrition in Children under Three Years of Age in Nghean, Vietnam, Pakistan Journal of Nutrition, vol:8, issue; 7, p:958, Jan 2009.

Ana Marlúcia Oliveira AssisI; Edileuza Nunes GaudenziI; GecynaldaGomes*; Rita de Cássia RibeiroI; Sophia C SzarfarcII; Sonia B de SouzaII, Hemoglobin concentration, breastfeeding and complementary feeding in the first year of life, Aug. 2004

Nutrition Surveillance Programme, Helen Keller International / IPHN, 2006

Population Census, Preliminary Report, Bangladesh Bureau of Statistics, Dhaka, 2001.

Islam N, Urbanization, Urban Planning and Development, and Urban Governance. Centre for Urban Studies, Dhaka, 2001.

M. K. Goel, R. Mishra, D. R. Gaur & A. Das, Nutrition Surveillance In 1-6 Years Old Children In Urban Slums Of A City In Northern India . The Internet Journal of Epidemiology, Volume 5 Number 1, 2007.
Bangladesh National Nutrition Survey,1995-96

Tracking Progress on Child and Maternal Nutrition: A survival and development priority, UNICEF, November 2009.

Nutritional Surveillance Project, Nutrition and Health Surveillance in Urban Slums in Dhaka, Annual report 2001, Bulletin No.9, Helen Keller International/IPHN, November 2002

Bangladesh National Nutrition Council, Bangladesh National Plan of Action for Nutrition (NPAN), 1997.

Niger T, Khatun S, Sultana M, Islam N. and Kazuhiro O, ‘Determinants of Malnutrition among the Children under 2 Years of Age”, Pakistan Journal of Nutrition 9 (1): 27-34, 2010.

Concern’s Urban Nutrition and Household Food Security Project (UNFHSP), May 2002 – April 2007

Poverty and Vulnerability in Dhaka Slums: The Urban Livelihoods Study Bangladesh e-Journal of Sociology. Vol. 2. No. 1. January 2005

Chapter 8
Annexure
Operational Definitions

Anemia: The condition of having less than the normal number of red blood cells or less than the normal quantity of hemoglobin in the blood. The oxygen-carrying capacity of the blood is, therefore, decreased.

Angular stomatitis: This is an affection of the skin at the angles of the mouth, characterized by heaping-up of grayish white sodden epithelium into ridges, giving the appearance of fissures radiating outwards from the mouth. Due to riboflavin, pyridoxine deficiency or in association with iron deficiency anemia it takes place.

Anthropometry: This is the technique that deals with the measurement of the size, weight and proportions of the human body. The anthropometric measurements taken in this study are height or length and weight.

Biochemical Assessment: It refers to measurement of a nutrient in biological fluids or tissues, measurement of the urinary excretion rate of the nutrient and measuring the production of an abnormal metabolite or changes in the activities of certain enzymes or blood components dependent on a nutrient. In the study, hemoglobin level was measured from blood collected from study population.

Bitot’s spot: Grayish or glistening white plaques formed of desquamated thickened conjunctival epithelium, usually triangular in shape and firmly adherent to the underlying conjunctiva, which is associated with vitamin A deficiency.

Bivariate analysis: It refers to testing hypothesis of “association” and causality. In its simplest form, association simply refers to the extent to which it becomes easier to know or predict a value for the Dependent variable if we know a case’s value on the independent variable. A measure of association helps us to understand this relationship. These measures of association relate to how well an independent variable relates to the dependent variable.

BMI: It is used to measure thinness or obesity. It is defined as weight in kilograms divided by height in meters squared (kg/m2). The main advantage of the BMI is that it does not require a reference table from a well-nourished population. A cutoff point in the BMI of 18.5 is used to define thinness or acute under nutrition. A BMI of 25 or above usually indicates overweight or obesity and 30 or above indicates obesity.

Child Spacing: Examination of birth intervals, defined as the length of time between two successive live births.

Chi-square test (χ2 test): It is any statistical hypothesis test in which the sampling distribution of the test statistic is a chi-square distribution when the null hypothesis is true, or any in which this is asymptotically true, meaning that the sampling distribution (if the null hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by making the sample size large enough.

Clinical Assessment: It consists of a routine medical history and a physical examination to detect physical sign (i.e. observations made by a qualified examiner) and symptoms (i.e. manifestation reported by the patient) associated with malnutrition. These assessment procedures are normally used in community nutrition surveys and in clinical medicine. They are most useful during the advance stages of nutritional definition, when overt disease is present.

Colostrum: It is also known as first milk is the sticky yellowish Milky fluid secreted for the first day or two after parturition. It contains antibodies to protect the newborn against disease, as well as being lower in fat and higher in protein than ordinary milk.

Complementary feeding: The process starting when breast milk alone or infant formula alone is no longer sufficient to meet the nutritional requirements of an infant, and therefore other foods and liquids are needed along with breast milk or a breast milk substitute. The target range for complementary feeding is generally considered to be 6–24 months.

Conjunctival xerosis: The bulbar conjunctiva becomes dry, thickened, wrinkled and pigmented, due to failure to shed the epithelial cells, and consequent keratinisation. It is common in children under 5 years due to vitamin A deficiency.

Corneal xerosis: Dull, hazy appearance of cornea due to dryness and caused by vitamin A deficiency.

Exclusive breastfeeding: Infant receives only breast milk. Medicines, oral rehydration solution, vitamins and minerals, as recommended by health providers, are allowed during exclusive breastfeeding.

Flacky paint dermatosis: This is characterstic of PEM. The skin becomes hyper pigmented and keratin separates in flakes.

Follicular hyperkeratosis: The follicles become blocked with plugs or keratin derived from the epithelial lining which has undergone squamous metaplasia. This pathological change has been attributed to vitamin A deficiency.

Height-for-age: It measures linear growth. A child who is below two standard deviations (-2 SD) from the median of the WHO reference population in terms of height-for-age is considered short for his/her age, or stunted. This condition reflects the cumulative effect of chronic malnutrition. If a child is below minus three standard deviations (-3 SD) from the reference median, then he/she is considered to be severely stunted. Stunting reflects a failure to receive adequate nutrition over a long period of time and is worsened by recurrent and chronic illness. Height-for-age, therefore, reflects the long-term effects of malnutrition in a population and does not vary appreciably according to recent dietary intake.
Keratomalacia: Softening, dissolution of cornea, ulceration and inflammation takes place. Without treatment it results in perforation and at last in total blindness

Low birth weight: An infant weighing less than 2,500 grams at birth.

Malnutrition: It is a broad term commonly used as an alternative to under nutrition, but technically it also refers to over nutrition. People are malnourished if their diet does not provide adequate nutrients for growth and maintenance or they are unable to fully utilize the food they eat due to illness (under nutrition). They are also malnourished if they consume too many calories (over nutrition).

Nasolabial dyssebacea: The appearance of enlarged follicles around the sides of the nose and sometimes extending over the cheeks and forehead due to riboflavin deficiency.

Night Blindness: Inability to see clearly in dim light, mainly due to a deficiency of vitamin A.

Nutrition: It is a dynamic process concerning with ingestion, digestion, absorption and assimilation (metabolism) of food substances by which growth, repair and maintenance of activities in the body as well as a whole or in any of its parts are accomplished.

Nutritional Status: The condition of the body resulting from the utilization of the essential nutrients available to the body is termed as nutritional status.

Obese: It is defined as weight-for-height above three standard deviations from the median weight-for-height of the standard reference population. It also refers to BMI greater or equal to thirty.

Overweight: It is defined as weight-for-height above two standard deviations from the median weight-for-height of the standard reference population.

Parity: the number of live born children a woman has delivered.
Pearson’s chi-square test: It is also known as the chi-square goodness-of-fit test or chi-square test for independence. When mentioned without any modifiers or without other precluding context, this test is usually understood (for an exact test used in place of χ2.
Pre-lacteal feeding: it is the practice of giving other liquids to a child during the first three days of life.

Regression analysis: It includes any techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps us understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed.

Standard Deviation Score (SD score or Z-score): Z-score is a multiple of standard deviation. It is estimated by taking median value of the reference population, divided by the standard deviation for the reference population.

Z-score =(Observed Value –Median Reference Value )/(Standard Deviation for the Reference Population)

Stunting: It is defined as Height-for-age below minus two standard deviations from the median Height-for-age of the standard reference population. Linear growth is a more stable indicator of nutritional status and stunting indicates reduced linear growth compared to the expected growth in a child of same age. Stunting is usually the end result of chronic and less severe inadequate nutrition.

Supplementary feeding: Additional foods provided to vulnerable groups, including moderately malnourished children.

Twenty-four Hour Recall Method: This is a method to recall the subject’s exact food intake during the previous twenty-four hour period or preceding day. Detailed descriptions of all foods and beverages consumed, including cooking methods. Vitamin and mineral supplement use is also noted. Quantities of foods consumed are usually estimated in household measures.

Under nutrition: the outcome of insufficient food intake, inadequate care and infectious diseases. It includes being underweight for one’s age, too short for one’s age (stunting), dangerously thin for one’s height (wasting) and deficient in vitamins and minerals (micronutrient deficiencies).

Underweight: It means a deficit in body weight compared to the expected weight for the same age, which may result either from a failure in growth or loss of body weight due to infections. It is a composite form of under nutrition that includes elements of stunting and wasting and is defined as weight-for-age below minus two standard deviations from the median weight-for-age of the standard reference population.

Wasting: Wasting means a deficit in body weight (tissue and fat) compared to the expected weight for the same height or length. If the child is under weight for his height or length he os she is currently on a deficient diet and is classified as wasted. It is defined as weight-for-height below minus two standard deviations from the median weight-for-height of the standard reference population. A child can be moderately wasted (between minus two and minus three standard deviations from the median weight-for-height) or severely wasted (below minus three standard deviations from the median weight-for-height).

Weight-for-age: A child can be underweight for his age because he/she is stunted, because he/she is wasted, or both. Children whose weight-for-age is below two standard deviations (-2 SD) from the median of the reference population are classified as underweight. Children whose weight-for-age is below three standard deviations (-3 SD) from the median of the reference population are considered severely underweight.

Weight-for-height: It describes current nutritional status. A child who is below two standard deviations (-2 SD) from the reference median for weight-for-height is considered to be too thin for his/her height, or wasted. This condition reflects acute or recent nutritional deficit. As with stunting, wasting is considered severe if the child is more than three standard deviations below the reference median. Severe wasting is closely linked to mortality risk.
Questionnaire

Institute of Nutrition and Food Science
University of Dhaka

Comparative Study on Nutritional Status of Children (aged 6 to 24 months) and their Mothers between Selected Slum and Non-Slum Areas of Dhaka City

Household no:
Date: _ _ _ _ _ _ _ _ _ _ _ _ _
Name of the Area: _ _ _ _ _ _ _ _ _ _ _ _ _
Name of the Interviewer: _ _ _ _ _ _ _ _ _
Name of the Respondent: _ _ _ _ _ _ _ _ _

Identification of the respondent:

Name of the Head of the House: ………………………………..
Name of the Mother: ……………………………..
Mother’s Age:………. Year
Number of Children (from 6 month to 24 month): …..………………
Name of the children:………………………….
Child Identification Number (CIN) Name of the
Child Gender Age (Month)
1
2

Code for Gender:
Male=1
Female=2

Socio-economic & Demographic Information:
How long have you been living in this slum/ Dhaka city? _ _ _ _ _ _ _ _ _ _ _ _ _
Religion of the family:
Code:
Islam=1
Hindu=2
Christian=3
Buddhist=4
Others=5

Total Household members:
Education level of mother:
Code:
Illiterate=1
Can Sign one’s name=2
Can read and write=3
Class I-V=4

Education level of main income earner:
Code:
Illiterate=1
Can Sign one’s name=2
Can read and write=3
Class I-V=4

Occupation of mother:
Code:
Housewife=1
Industry worker=2
Day labour =3
Business=4
Others=5

Occupation of main income earner :
Code:
Rickshaw puller / Van driver = 1
Small business=2
Daily labour=3
Motor car driver =4
Service=5
Others=6

Monthly family income :

Family expenditure:
Food cost
House rent cost
Clothing cost
Treatment cost
Education Cost
Other cost

Facilities you have:
Sanitary Latrine
Kitchen
Water supply
Gas supply for cooking

Code:
Yes=1
No=2

Water Sources:
Drinking water
Cooking water
Utensil washing water
Bathing water
Code:
Tube well=1
Tap water=2

KAP related Information among mothers:

Information related to pregnancy, Lactation and delivery:

What was your age at the time of marriage?
Code:
18 years=3

What is your parity?
Did abortion occur in your life?
Code:
Yes=1
No=2
If yes, how many times it took place?

Was there child spacing for atleast 3 years between two children?
Code:
Yes=1
No=2
Not applicable=3

Did you use any family planning before (last) pregnancy?
Code:
Yes=1
No=2
Where did your last child delivered?
Code:
At home=1
At NGO delivery centre=2
At hospital=3

What was the type of delivery?
Code:
Normal=1
Caesarean=2
Did too much blood loss take place after delivery?
Code:
Yes=1
No=2
At what month did your child took birth?
Code:
At < 8 month=1 At 8 to 9 month =2 At > 9 month= 3

What was the birth weight?
Code:
2.5 Kg=2
Don’t Know=3

Do you know what is Anemia?
Code:
Yes=1
No=2
Did you have Anemia during pregnancy?
Code:
Yes=1
No=2
Don’t Know=3

Did you take iron tablet during pregnancy?
Code:
Yes=1
No=2

If yes, then how many did you take?
Code:
1-150=1
15i-300=2
Did not took=5

Did you take folic acid tablet during pregnancy?
Code:
Yes=1
No=2
Don’t Know=3

Feeding Practices:

What did you first feed to your infant after birth?
Code:
Colostrum=1
Honey=2
Swteened water=3
Plain water=4

What was the method for postlacteal feeding?
Code:
Tip of finger =1
Spoon =2
Plasti feeder bottle =3
Need not to use ant method =9

When did you start breast feeding to the infant?
Code:
Never breast fed=1
Immediately after birth= 2
Within 24 hours=3
Within 48 Hours=4
> 48 hours =5

Did you give colostrum to your new born?
Code:
Yes=1
No=2
Can not remember=3

If not; then what was the reason to reject colostrum?
Code:
Mother’s illness=1
Ignorance=2
Don’t feel it necessary=3
Family discourage=4
Bad for baby=5
Feed colostrum=9

Do you know the benefits of colostrum?
Code:
Yes=1
No=2

Did you exclusively breast feed your child upto 6 months?
Code:
Yes=1
No=2
Never breast fed=3

If no, then what did you offered for supplementation?
Code:
Formula Milk=1
Cow’s milk=2
Cerelac=3
Suji (Semolina)=4

Are you continuing breast feeding to your child ?
Code:
Yes=1
No=2
If yes, how long will you continue breast feeding to your child?
Code:
< 12 months=1 12-24 months=2 > 24 months=3

If no, how long did you follow breast feeding?
Code:
0- 1 month=1
0-4 month- =2
0-6 months=3

When did you start weaning food?
Code:
< 6 month=1
6-8 month=2

If before 6 months, why?
Code:
Breast milk is not enough to fulfill child requirement=1
Less breast milk production=2
Due to work load=3
Family pressure=4
Others=5
Started after 6 months =9

What are the foods do you give your chid as complementary
food now?
Code:
Formula Milk=1
Suji (Semolina)=2
Fruit/Fruit juice=3
Rice+Dahl/ Khichuri=4
Rice+Dahl/ Khichuri
with meat/fish/egg=5

When do you feed your child?
Code:
Child’s wish=1
At fixed time=2
Mother-in-law’s wish=3
When the child cries=4
Other=5

Do you give your child fresh cooked food every time?
Code:
Yes=1
No=2
NA= 9

If not, why?
Code:
Unaware =1
Can not afford=2
Not Applicable=9

Do you prepare separate food for your child?
Code:
Yes=1
No=2
Not Applicable=9

Morbidity and Treatment Seeking Behavior:
Did your Child suffer from any disease within last 3 months?
Code:
Yes=1
No=2

If yes, Name of the disease he/she suffered?
Code:
Fever=1
Cold=2
Fever+Cold=3
Diarrhoea=4
Diarrhoea+ Fever =5

What do you do when your child gets sick?
Code:
To physician =1
To Homeopath =2
To Traditional healer=3
To the nearer NGO centre=4

Anthropometric Assessment (mother and target children):

dentification Height /
Length (cm) Weight
(kg)

Mother of the child

Child Identification number (CIN)

Biochemical Assessment (mother and target children):

Identification Optical Density Hemoglobin
(gm/dl)

Mother of the child

Child Identification number (CIN)

Dietary Assessment :
Food Intake of mother by 24 hour recall method:
Age of the Mother: _________ Year
How was yesterday in respect of food intake?
Code: As usual normal day =1
Festival =2
Sick =3
Time of Eating Menu Cooked / Raw Food Code of the Food
Total Weight
(gm)

Family measurement Ingredients Cooked wt (gm) Cooking Method

Breakfast

Mid morning Snacks

Lunch

Mid Afternoon Snacks

Dinner

Clinical Assessment:

Clinical Signs Mother CIN
1 2
Hair Discolored
Sparce
Eyes Night Blindness
Bitot’s Spot
Conjunctival Xerosis
Corneal Xerosis
Keratomalacia
Pallor
Lips Angular Stomatitis
Angular Scars
Cheilosis
Gums Bleeding gums
Swollen red Papillae
Fever
Tongue
Smooth
Raw and Red
Nose Nasolabial Dyssebacea
Gland Enlarged Thyroid Gland
Skin Flakypaint dermatosis
Follicular hyperkeratosis
Nail Koilonychia
Skeletal Knock Knee/ Bow leg
Edema
Others Enlarged abdomen
(Worm Infestation)

Pictures of the Study

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Location Map of Slum and Non-slum areas of Dhaka city