effect of socio-economic and demographic factors on...

CHAPTER • VIII

EFFECT OF SOCIO-ECONOMIC AND DEMOGRAPHIC

FACTORS ON NUTRITIONAL STATUS

Vlll.1: Introduction

It is evident from several studies that many factors affect the level of

stunting, underweight and wasting. Socio economic and demographic

factors have a significant influence on nutritional status of children.

Likewise, maternal and child health factors have profound effect on

nutritional status of children. It is also apparent that compound effect of

anthropometric failures can affect a child, this effect can studied by using

CIAF. From many studies it can be understand that logistic regression is

reflective statistical tool to identify the effect of dependent variables on

stunting, underweight and wasting. This chapter gives more profound idea

on nutritional status of children.

Vlll.2: The Reference Value

From the study it is clear that only 13.5 percent children have height

for-age, equal or above the reference value and remaining 86.5 percent

(includes stunted and severely stunted) children fall below the reference

value or required height-for-age. Another heartening fact is that only 11.9

percent children have weight-for-age, equal or above the reference value

and remaining 88.1 percent (includes underweight and severely

underweight) children fall below the reference value or required weight-for

age. Again 33.4 percent children have weight-for-height, equal or above the

reference value and remaining 66.6 percent (includes wasted and severely

wasted) children fall below the reference value or required weight-for

height.

154

V1I1.3: Socio Economic and Demographic Index

Using the selected socio economic and demographic factors such

as type of house, source of water, toilet facility, education of parents,

occupation of the father, monthly family income, exposure to mass media,

birth order of the child, preceding birth interval and succeeding birth

interval; an index is constructed and the values are classified in to low,

medium and high. The following table VII1.1 reveals the percentage

distribution of children by socio economic and demographic index.

Table VIII. 1: Percentage Distribution of Children by

Socio Economic and Demographic Index

Level Percentage

Low 48.4

Medium 36.9

High 14.7

Total 100.0 (1007)

The graph also shows the socio economic and demographic index.

Rg.VIII.1: Distribution of Children by Socio

Economic and Demographic Index

60 -,--------------'+Q.'!+----,IIICl~ 40 -r-----:-:--=-~--,--.'--r==;;;;;;_---j

~ 20 14.7~

~ 0

High Medium

Index Value

iSS

Low

From the graph and table it is clear that only 14. 7 percent children

belongs high level, 36.9 percent children belongs to medium level and 48.4

percent children belongs to low level. The table (Vlll.2) shows the

percentage distribution of children by anthropometric measurement and

Socio Economic and Demographic Index.

Table Vll/.2: Percentage Distribution of Children by Anthropometric

Measurement and Socio Economic and Demographic Index

Socio Economic Stunted Underweight Wasted

and Demographic

Index

Low 32.8 (487) 19.5 (487) 15.8 (487)

(54.0) (53.7) (51.3)

Medium 29.0 (372) 17.5(372) 14.2 (372)

(36.6) (36.7) (35.3)

High 21.6 (148) 14.2 (148) 13.5 (148)

(9.4) (9.6) (13.4)

29.3 (1007) 17.6 (1007) 14.9 (1007)

Total (100.0) (100.0) (100.0)

(295) (177) (150)

From the table it can be noted that 32.8 percent children belongs to

the low socio economic and demographic level are stunted, 29 percent

children belong to medium socio economic and demographic level are

stunted and 21.6 percent children belonging to high level are also stunted.

So this table shows that stunting is high among those children who have

low or medium socio economic and demographic status.

From the table it is also found that 19.5 percent children belong to

the low socio economic and demographic level are underweight, 17.5

percent children belong to medium socio economic and demographic level

156

are underweight and 14.2 percent children belong to high level are

underweight. So the table shows that underweight is high among those

children who have low socio economic and demographic status. Again the

table shows that 15.8 percent children belong to low socio economic and

demographic level are wasted, 14.2 percent children belongs to medium

socio economic and demographic level are wasted and 13.5 percent

children belongs to high level are wasted. So this table shows that wasting

is high among those children who have low socio economic and

demographic level. From this table it can see that children belong to low

socio-economic and demographic status are more prone to stunted,

underweight and wasted.

Vlll.4: Maternal and Child Health Index

Using the indicators of maternal and child health such as first

antenatal checkup, frequency of antenatal checkup, mother's acceptance

of iron or folic acid tablets, premature birth, birthweight, initiation of breast

feeding, child immunization status and continuous disease an index is

created. The percentage distribution of children by maternal and child

health index is given in table VIII. 3.

Table V/11.3: Percentage Distribution of Children by

Maternal and Child Health Index

Level Percentage

Low 41.1

Medium 31.3

High 27.6

Total 100.0(1007)

The following graph shows the percentage distribution of maternal and

child health index.

157

Fig.VIII.2: Distribution of Children by Maternal andChild Health Index

31.3Gl 60 ,---....,,--.,.-----------------,

E 40 +--r:::~ 20~ 0

High Medium Low

Index Value

41.1 percent children belong to low level while 31.3 percent children

belong to medium level and there are 27.6 percent children falls in the high

level in the maternal and child health index.

The table (VillA) shows the percentage distribution of children by

anthropometric measurement and Maternal and Child Health Index. The

table shows that 32.6 percent children belong to low maternal and child

health level are stunted, 27.3 percent children belongs to medium level are

stunted and 26.6 percent children belongs to high level are stunted. So this

table shows that stunting is high among those children who have low

maternal and child health level. Again, 23.2 percent of the children who

falls in the low maternal and child health status are underweight, while 14.9

percent of the medium level children are underweight and among high

status it is only 12.2 percent. Further the table shows that 17.3 percent

children belong to low maternal and child health level are wasted, 15.5

percent children belongs to medium status are wasted and in the case of

high status group it is only 10.2 percent. So this table shows that wasting is

high among those children who have low maternal and child health level.

iS8

Table Vll/.4: Percentage Distribution of Children by Anthropometric

measurement and Maternal and Child Health Index

Maternal and Stunted Underweight Wasted

Child Health

Index

Low 32.6 (414) 23.2 (414) 17.3 (414)

(45.8) (54.2) (47.3)

Medium 27.3 (315) 14.9(315) 15.5(315)

(29.2) (26.6) (32.7)

High 26.6 (278) 12.2 (278) 10.2 (278)

(25.1) (19.2) (20.0)

29.3 (1007} 17.6 (1007} 14.9 (1007}

Total (100.0} (100.0} (100.0}

i (295} (177} (150} I

Again, the maternal and child health index also provides that

children belong to low category are more vulnerable with stunting,

undervveight and wasting compared to other group of children.

Vlll.5: CIAF (Composite Index for Anthropometric Failure}

CIAF permits desegregation of the undernourished children into

different subgroups as shown in the table Vlll.5.

From the table it is clear that overall only 57.6 percent children

studied are anthropometrically normal; remaining 42.4 percent children are

suffering from one or other form of anthropometric failure. There are 18

percent children with stunting alone, 1.6 percent children with underweight

only and 7 .1 percent children with wasting alone. It is also seen that 7 .8

percent children affected with both stunting and underweight, 0.1 percent

159

i

children with stunting and wasting and 4.7 percent children with

underweight and wasting.

Table V/11.5: Percentage Distribution of Children by

Anthropometric failure

Anthropometric failure Percentage

No failure 57.6

Stunting Only 18.0

Underweight Only 1.6

Wasting Only 7.1

Stunting + Underweight 7.8

Stunting + Wasting 0.1

Underweight+ Wasting 4.7

Stunting + Underweight + Wasting 3.2

Total 100.0 (1007)

Again 3.2 percent children have all these anthropometric failures.

From this table it is clear that there are children who suffer from one or

other form of anthropometric failures. This is a very serious problem by any

scale. Under such conditions our intervention efforts need to be broader

than providing supplementary nutrition alone.

Vlll.6: Logistic Regression

In order to study the influence of various socio-economic and

demographic variables on anthropometric failures, logistic regression is

found to be a worthwhile statistical technique. Using logistic regression

technique Arshad Mahmood (2001) found that socio-economic factors have

significant impact on malnutrition. The logistic regression result revealed

that children of age 24-35 months are equally likely and the children of age

160

36-47 months are likely to be severely underweight as that of the children

of age 12-23 months (Rajarethnam and Jyothi Hallad, 2000).They also

uncovered that the likelihood of children of SC/ST communities being

severely underweight is only slightly higher. Using logistic regression

Tharakan and Suchindran (1999) explained that the coefficients are

positive for age and month's breastfed, their odds ratios are greater than

one, indicating increased probability of stunting for unit increase in the

value of any of these variables. Again, age and months of breast fed have

positive coefficients with and odds ratios greater than one indicating

increase in their values is associated with increase in the probability of

underweight. And fathers education level has positive coefficient and an

odds ratio greater than one, indicating increased probability for wasting

when they increase in value. Mozumder et.al. (2000) used logistic

regression and found that short subsequent birth intervals emerge as a

significant predictor of malnutrition among children. The odds of being

stunted varied by fathers education in Goa and mothers education in

Kerala (Rajram.et.al, 2003). Again, Rohini Pande (2003) identified that girls

and boys no longer have significantly different odds for severe stunting. So

this technique is found to be appropriate for studying the relationship of

independent variables on nutritional status. The results of logistic

regression are discussed in the following paragraphs.

Vlll.6.1: Logistic regression - Stunting

The following table (Vlll.6) shows the result of logistic regression.

Here the dependent variable for logistic regression analysis is, children with

stunting, assign value one, otherwise zero.

The result clears that the children belonging age group 2-3 have 53

percent more chances of being stunted than children belong to 1-2 age

group. It is also noted that chances of getting stunted decreases with age.

There is no gender difference in the case of getting stunted.

161

Table Vl//.6: Logistic Regression-Dependent Variable: Stunting-1, No-0

Name of the variable Exp(B)

Age of the child

1-2 (R)

2-3 1.532*

3-4 1.294*

4-5 1.173*

Sex of the child

Female (R)

Male 1.009*

Religion

Hindu (R)

Muslim 1.441 *

Christian 0.794*

Community

Others (R)

SC/ST 1.595*

Place of Residence

Rural (R)

Urban 0.693*

Coastal 1.534*

Type of House

Kutcha(R)

Pucca 0.0891 *

Source of water

Own pipe or well(R)

Other sources 1.421 **

162

Toilet facility

Yes(R)

No 1.634**

Education of Father

Below Primary Level (R)

Middle Level 0.961 *

High School Level 0.835*

Higher secondary or above 0.621 *

Education of Mother


Middle Level 0.824*


Higher secondary or above 0.643*

Occupation of father

Govt.Employees(R)

Coolie 1.396*

Others 1.447*

Occupation of Mother

Working(R)

Not Working 1.092*

Monthly Family Income

Below 5000Rs/-(R)

Above 5000 0.566**

Exposure to Mass media

No(R)

Yes 0.883*

Antenatal Checkup

Irregular (R)

Regular 0.784*

163

Premature Birth

No (R)

Yes 1.927*

Birthweight

>2.5 Kg (R)

2.5 Kg-3.5 Kg 0.701**

>3.5 Kg 0.982*

Breast Feeding

Fed within hour(R)

Fed in the first day 1.122*

Fed after first day 2.034**

Birth order

First or Second(R)

Above 1.315*

Continuous Disease

No (R)

Yes 1.242*

Caring of child

Self (R)

With husband 0.821 *

With senior person 0.842*

Others 1.412*

* Significance Level 1 % level, * Significance Level 5% level

Muslim children have· 44 percent more chances of being stunted

than Hindu children, while Christian children have lesser chances than

Hindu children. Children belonging to SC/ST community have about 60

percent more chances of being stunted and children belongs to urban

areas have low chances of being stunted than rural children and the

coastal children have 53 percent higher chances than rural children.

164

The result of logistic regression also shows that as education of

parents increases the chances being stunted decreases. Children whose

fathers are in the Govt.service have low chances being stunted compared

to children of coolie and other workers. Children whose mothers are not

working have low chances of being stunted. It is also noted that children

belongs to high monthly income families have low chances of being stunted

and children who belong to houses with media exposure have low chances

of being stunted.

Mothers who receive regular antenatal checkup have low chances of

being stunted children and premature babies have nearly 93 percent more

chances of being stunted than matured babies. Children with birth weight

ranging 2.5 Kg to 3.5 Kg have less chances of being stunted than others

and it is also noted that children who are breastfed within one hour after

delivery have low chances of being stunted and the result is found to be

signi ficant Again children, who are from higher birth order, have more

chances of being stunted and children with continuous disease have high

chances of being stunted. It can also apparent from table that children are

found to be more stunted if they are cared by others (servant etc.).

Vlll.6.2: Logistic regression - Underweight


The dependent variable for logistic regression analysis is, children with

underweight, assign value one, otherwise zero.

The result shows that as age of the child increases the chances of

being underweight also increasing and female children have slightly less

chances of being underweight. Children belongs to Muslim religion have

high chances of being underweight than others and children who belongs

to SC/ST community have 36 percent high chances of being underweight

than others. Urban children have low chances of being underweighed and

165

children who belong to pucca houses have about 21 percent less chance of

being underweighed. Also children belongs to those family with own source

of drinking water have low chances of being underweighed. The likelihood

of having underweight is low among houses with toilet facility.

Table Vlll. 7: Logistic Regression-Dependent Variable:

Underweight-1, No-0


Age of the child

1-2 (R)

2-3 1.414*

3-4 1.495*

4-5 1.534*

Sex of the child

Female (R)

Male 1.017*

Religion

Hindu (R)

Muslim 1.011 *

Christian 0.934*

Community

Others (R)

SC/ST 1.365*

Place of Residence

Rural (R)

Urban 0.712*

Coastal 1.004*

Type of House

Kutcha(R)

Pucca 0.781*

166

Source of water

Own pipe or well(R)

Other sources 1.371**

Toilet facility

Yes(R)

No 1.329**

Education of Father


Middle Level 0.841*



Education of Mother


Middle Level 0.824*




Govt.Employees(R)

Coolie 1.416*

Others 1.436*


Working(R)

Not Working 1.019*


Below 5000Rs/-(R)

Above 5000 0.732**


No(R)

Yes 0.773*

167

Antenatal Checkup

Irregular (R)

Regular 0.814*

Premature Birth

No (R)

Yes 1.757*

Birthweight

>2.5 Kg (R)

2.5 Kg-3.5 Kg 0.063**

>3.5 Kg 0.832*

Breast Feeding

Fed within hour(R)



Birth order

First or Second(R)

Above 1.042*

Continuous Disease

No (R)

Yes 1.734*

Caring of child

Self (R)

With husband 0.773*


Others 1.312*

** Significance Level 1 % level, * Significance Level 5% level

As in the case of stunting the educational level of parent's increases,

the chances of being underweight children is decreases and children who

belong to the fathers working in Govt. service have low chances of being

stunted. It is also noted that children who belongs to nonworking mothers

168

have low chances of being underweighed children. Children who belong to

low monthly income families have more chances of become underweight

and children who belongs household with mass media exposure have low

chances of being underweight.

Mothers who received irregular antenatal checkup have more

chance of having underweight children. Premature babies have 75 percent

more chances of being underweight than others and children who have

birthweight ranging from 2.5Kg to 3 Kg have low chances of being

underweight and this relationship is found to be more significant. Likewise

children who were early breastfed have low chances of being underweight.

Children who have high birth order have slightly more chances of being

underweighed and children who have continuous disease have about 73

percent more chances of being underweight and this result is found to be

highly significant. Children who got care from others have more chances of

underweight.

Vlll.6.3 Logistic regression - Wasting


The dependent variable here used for logistic regression analysis is,

children with wasting, assign value one, otherwise zero.

The chances of wasting are found to have increases as the age of

the child increases and males have slightly more chances (12 percent) of

being wasted than females. Children belong to Muslim and Christian has

low chances of being wasted than reference category and the children

belong to SC/ST category have more chance of being wasted. Again the

children who belong to urban and coastal areas have low chances of being

wasted and the children belong to pucca houses have low chances of

being wasted. It is also noted that children who belongs to families with

common or other source of drinking water have 6 percent more chances of

169

wasted and the children belongs to household with toilet facility have less

chance of being wasted.

Table Vl//.8: Logistic Regression-Dependent Variable: Wasting-1, No-0


Age of the child

1-2 (R)

2-3 1.355*

3-4 1.513*

4-5 1.604*

Sex of the child

Female (R)

Male 1.124*

Religion

Hindu (R)

Muslim 0.984

Christian 0.892*

Community

Others (R)

SC/ST 1.006*

Place of Residence

Rural (R)

Urban 0.934*

Coastal 0.904*

Type of House

Kutcha(R)

Pucca 0.936*

Source of water

Own pipe or well(R)

Other sources 1.064*

170

Toilet facility

Yes(R)

No 1.140*

Education of Father


Middle Level 0.948*



Education of Mother


Middle Level 0.914*




Govt.Employees(R)

Coolie 1.546*

Others 1.606*


Working(R)

Not Working 0.916*


Below 5000Rs/-(R)

Above 5000 0.942*


No(R)

Yes 1.014*

Antenatal Checkup

Irregular (R)

Regular 0.973*

171

Premature Birth

No (R)

Yes 1.014*

Birthweight

>2.5 Kg (R)

2.5 Kg-3.5 Kg 0.917**

>3.5 Kg 0.784*

Breast Feeding

Fed within hour(R)

Fed in the first day 1.321 **

Fed after first day 2.106*

Birth order

First or Second(R)

Above 1.637*

Continuous Disease

No (R)

Yes 1.012*

Caring of child

Self (R)

With husband 0.962*


Others 1.143*


As education of parents increases the chances of having wasted

children becomes low. Govt.employed fathers have low chances of getting

wasted children and working mothers has low chances of getting wasted

children. Children belong to low income families have more chance of

wasting than others. Children who belong to family with mass media

exposure have low chances of being wasted.

172

Mothers who received regular antenatal checkup have low chances

of getting wasted children and premature babies are more chances of

being wasted. Children whose birthweight above reference category have

low chances of being wasted and children who are early breastfed have

low chances of being wasted and are found to be more significant. Children

with higher birth order have 63 percent more chances of being wasted and

this relationship is also highly significant. Again children with continuous

disease have more chances of being wasted and children who cared by

respondent or with the help of their husband have low chances of being

wasted.

Vlll.6.4: Logistic regression - Anthropometric failure


The dependent variable for logistic regression analysis is, if the child

suffering any one of the anthropometric failure, assign value one, otherwise

zero.

The result shows that the children who belonging to age group 2-3

have 64 percent more chances of being failure than reference category and

male children have a little chances of being failure. Children belonging to

Muslim community have 28 percent more chances of being failure than

children belonging to Hindus and Christians have less chances of being

failure than Hindus. The likelihood of having failure is more for children

belong to SC/ST category.

The likelihood of having failure is more among coastal children and

less among urban children compared to rural children. Children who belong

to pucca houses have low chance of being anthropometrically normal than

others.

173

Table V/11.9: Logistic Regression-Dependent Variable:

Anthropometric failure-1, No-0


Age of the child

1-2 (R)

2-3 1.642*

3-4 1.244*

4-5 1.213*

Sex of the child

Female (R)

Male 1.016*

Religion

Hindu (R)

Muslim 1.281*

Christian 0.824*

Community

Others (R)

SC/ST 1.825*

Place of Residence

Rural (R)

Urban 0.743*

Coastal 1.414*

Type of House

Kutcha(R)

Pucca 0.842*

Source of water

Own pipe or well(R)

Other sources 1.323**

174

Toilet facility

Yes(R)

No 1.525**

Education of Father


Middle Level 0.932*



Education of Mother


Middle Level 0.876*




Govt.Employees(R)

Coolie 1.396*

Others 1.447*


Working(R)

Not Working 1.074*


Below 5000Rs/-(R)

Above 5000 0.637**


No(R)

Yes 0.845*

Antenatal Checkup

Irregular (R)

Regular 0.784*

175

Premature Birth

No (R)

Yes 1.927*

Birthweight

>2.5 Kg (R)

2.5 Kg-3.5 Kg 0.071**

>3.5 Kg 0.982*

Breast Feeding

Fed within hour(R)



Birth order

First or Second(R)

Above 1.334*

Continuous Disease

No (R)

Yes 1.242*

Caring of child

Self (R)

With husband 0.821 *


Others 1.412*


Children who belong to household with other source of water have

32 percent more chances of being anthropometric failure than household

with own pipe or well. Children belong to houses without toilet facility has

53 percent higher chances of getting anthropometrically failure. As

education of parent's increases, the chance of being anthropometric failure

in children is found to be decreasing. Children of Government employees

and working mothers have less chances of being anthropometric failure.

176

Children with high monthly income household have less chances of being

anthropometrically failure. Again children whose parents are exposed to

mass media have less chance of being anthropometric failure.

Children to mothers who had regular antenatal checkup have low

chances of being anthropometrically failure and premature babies have 93

percent more chances to become failure than matured babies and this

result is highly significant. The children with adequate birthweight have 28

percent low chance of being failure and this relation is also found to be

highly significant. The children who breastfed after first day have more than

double chances of being failure than others children who had fed within one

hour of delivery (Significance one percent level). The children with higher

birth order have more chances of being failure. Children who suffer

continuous diseases have 24 percent more chances of being failure than

other children. It is also noted that the chances of being failure is high

among to children whose daily care provided by others (servants etc.) than

with the help of husband or senior persons compared to reference

category.

Vlll.7: Conclusion

The socio-economic and demographic index and maternal and child

health index that divides the sample in to three classes (low, medium and

high) are given in this chapter. Again the influence of these three classes

on stunting, underweight and wasting were described. The children were

classified in to two groups using CIAF technique. The effect of various

socio-economic, demographic and health factors studied using statistical

technique, logistic regression. The next chapter presents the summary and

concluding remarks and suggestions and policies to improve the nutritional

status of children.

177

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