Report On Comparative Study On Nutritional Status Of Children And Their Mothers (Part-2)

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 continueBreast Feedingupto<24 months

4.5

3.3

12-24 months

36.4

63.3

>24 months

59.1

33.3

Total

100.0

100.0

FollowedBreast Feedingtill0-1month

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 monthsBreast 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.

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 FoodYes

15.5

49.5

No

84.5

50.0

Total

100.0

100.0

Cause of Not Providing Fresh Cooked FoodUnaware

31.7

37.8

Can not afford

68.3

56.2

Total

100.0

100.0

Prepare Separate food for childrenYes

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.

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.

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 to -3SD(Moderate)

33.3

17.6

≥-2SD (Normal)

49.0

56.8

Total

100.0

100.0

Non-slum< -3SD (Severe )

4.4

12.0

<-2SD to -3SD(Moderate)

11.1

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 to -3SD(Moderate)

19.6

22.7

≥-2SD to 2SD (Normal)

70.6

63.6

> 2SD (Overweight)

0.0

0.0

Total

100.0

100.0

Non-slum< -3SD (Severe )

8.5

4.2

<-2SD to -3SD(Moderate)

8.5

6.3

≥-2SD to 2SD (Normal)

78.7

75.0

> 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.

1.1.2. 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.

1.1.3.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

%

HairDiscolored

26.3 (25)

17.9 (17)

Sparce

14.7 (14)

EyesNight Blindness

5.3 (5)

Bitot’s Spot
Conjunctival Xerosis
Corneal Xerosis
Keratomalacia
Pallor
LipsAngular 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)

GumsBleeding gums
Swollen red Papillae
Fever
Tongue

Smooth

2.1 (2)

   Raw and Red    NoseNasolabial Dyssebacea

2.1 (2)

   GlandEnlarged Thyroid Gland

13.7 (13)

 

7.4(7)

 SkinFlakypaint dermatosis

2.1 (2)

  Follicular hyperkeratosis    NailKoilonychia

6.3 (6)

   SkeletalKnock Knee/ Bow leg

4.2 (4)

  OthersEdema

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

(Stunted)

>= -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-scorePearson 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-scorePearson 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 (Stunted)

>= -2.00 SD (Normal)

Slum

<6 month

21.4

78.6

100.0

.027

>6 month

54.4

45.6

100.0

Non-slum

 

<6 month

17.5

82.5

100.0

.138

>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-scorePearson Correlation

1.000

-.262

Sig. (2-tailed)

.

.027

N

71

71

Time of starting weaningPearson 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-scorePearson Correlation

1.000

-.152

Sig. (2-tailed)

.

.140

N

95

95

Time of starting weaningPearson 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 PlacePearson 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 ChildrenPearson Correlation

1.000

.486

Sig. (2-tailed)

.

.000

N

95

95

Hemoglobin Level of MotherPearson 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 ChildrenPearson Correlation

1.000

.471

Sig. (2-tailed)

.

.000

N

190

190

Height-for-age Z-scorePearson 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<0.05.

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 MotherPearson Correlation

1.000

.062

Sig. (2-tailed)

.

.550

N

95

95

Percentage of fulfillment of RDAPearson 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 MotherPearson Correlation

1.000

.249

Sig. (2-tailed)

.

.015

N

95

95

Percentage of fulfillment of RDAPearson 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 latrinePearson Correlation

1.000

-.370

Sig. (2-tailed)

.

.000

N

95

95

Worm infestation of motherPearson Correlation

-.370

1.000

Sig. (2-tailed)

.000

.

N

95

95

** Correlation is significant at the 0.01 level (2-tailed).

1.1.6. 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.

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 (%<-2 z-score) among the pre-school children was higher in the urban slums, followed by the rural and urban non-slum areas (66.2%, 61.1%, and 52.5%) respectively.8 So, it can be said this study findings resembles the results of study by ICDDRB-HKI in terms of child nutritional status.

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.

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.

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.

Some more parts

Report On Comparative Study On Nutritional Status Of Children And Their Mothers (Part-1)