Review of Economics and Development Studies                                      Vol. I, No 2, December 2015 

 

143 
 

 

Volume and Issues Obtainable at Center for Sustainability Research and Consultancy 

 

Review of Economics and Development Studies 
ISSN:2519-9692 ISSN (E): 2519-9706 

Volume 1: Issue 2 December 2015 

Journal homepage: www.publishing.globalcsrc.org/reads 

 

Impact of Socioeconomic and Demographic Factors Affecting Child Health in 

Selected South Asian Countries 
 

1
Sofia Anwar, 

2
Maria Khushbakhet, 

3
Aisha Asif, 

4
Zahira Batool 

 
1
Professor and chairperson, Department of Economics, Government College University Faisalabad, Pakistan, 

sofia_eco@gcuf.edu.pk 
2
MPhil Scholar, Department of Economics, Government College University Faisalabad, Pakistan, 

mkch_89@yahoo.com 
3
PhD Scholar, Department of Economics, Government College University Faisalabad, Pakistan, 

aieshasif@gmail.com 
4
Associate Professor, Department of Sociology, Government College University Faisalabad, Pakistan 

 

ARTICLE DETAILS  ABSTRACT 
History 
Revised format: Nov 2015 

Available online: Dec 2015 

 

 Development of any nation is estimated through child health condition. 

In particular, the fourth millennium development goal out of eight is to 

reduce the mortality rate. The target set under this goal was to reduce by 

two-third, between 1990 and 2015, the proportion of child mortality. 

Maternal BMI is closely associated with child nutritional status. Weak 

mother having low BMI has low nutrition status which effect child 

weight. Healthy and balance food of mothers have positive effect on their 

child. Underweight mother can have impaired and poor growing kids. 

This study presents impact of some socio-economic demographic and 

maternal health related factors on health status of children in selected 

South Asian countries i.e. Pakistan, Bangladesh and Nepal. The study 

used micro data from demographic and health survey (DHS) of Pakistan, 

Bangladesh and Nepal. Multinomial logistic regression results revealed 

that mother education, mother working status, mother health, availability 

of safe drinking water, family size and vaccination have significant effect 

on child health. Mother’s education is positively associated with healthy 

child. Working mothers are more likely to have healthy child. Weak and 

obese children are positively associated with malnourished and 

overweight mothers respectively. Small family size has positive impact 

on weak child health. Vaccination and availability of improved and safe 

water are positively associated with child health. 

 

© 2015 The authors, under a Creative Commons Attribution-

NonCommercial 4.0                                                         

Keywords 

Child health,  

Body Mass index,  

Mother health,  

Working mothers,  

Safe water,  

Pakistan,  

Bangladesh,  

Nepal 

 

 

JEL Classification 

I12; I15; I18; J13 
 

 

 
Corresponding author’s email address: sofia_eco@gcuf.edu.pk 

Recommended citation: Anwar, S., Khushbakhet, M., Asif, A. and Batool, Z. (2015). Impact of 

Socioeconomic and Demographic Factors Affecting Child Health in Selected South Asian Countries. Review 

of Economics and Development Studies, 1 (2) 143-151 

DOI: https://doi.org/10.26710/reads.v1i2.120 

 

  

http://www.publishing.globalcsrc.org/reads
mailto:sofia_eco@gcuf.edu.pk
mailto:mkch_89@yahoo.com
mailto:aieshasif@gmail.com
mailto:sofia_eco@gcuf.edu.pk


Review of Economics and Development Studies                                      Vol. I, No 2, December 2015 

 

144 
 

  

1. Introduction and Literature Review 
Development of any nation is estimated through child health condition (Anwar et al., 2012). Many 

developing nations included; Pakistan joined the United Nations Millennium summit and agreed to 

make efforts to achieve the Millennium Development Goals (MDGs).The attainment of MDGs is the 

numerical measurement of the progress in which efforts are made by any country. In particular, the 

fourth millennium development goal out of eight is to reduce the mortality rate. The target set under 

this goal is to reduce by two-third, between 1990 and 2015, the proportion of child motility (WHO, 

2005).  

 

Underweight in children are the main causes of child health problems in developing countries. 

Newly born babies who have completed 37 weeks of gestation and have low birth weight (less than 

2.5 kg) have greater possibility to contain growth restrain whereas this situation refer to low birth 

weight and weak child. The nutritional condition measures stunting and obesity which are considered 

as risk factors whose exposure applied to all children of less than five years (Black et al., 2008). The 

child malnutrition more often leads to illness and death (Cheah et al., 2010).There are number of 

factors which results in child malnutrition like food security (availability and access), mother’s poor 

nutritional level, low literacy level, less awareness of health care service and child care where 

malnourishment is the most important determinant of child BMI (Linnemayr et al., 2008).  

 

Childhood obesity is directly correlated with weight problems during adulthood. The obese children 

have greater probability to be involved in health issues like blood pressure and diabetes in early 

adolescence (Serdula et al., 1993; Whitaker et al., 1997; and Freedman et al., 2007). Obesity is also 

cause of overweight and slow metabolic system (Modi et al., 2011). Furthermore, obesity among 

children is related with a number of long term psychological issues (Dietz, 1998; Strauss, 2000; 

Daniels, 2006; Mocan & Tekin, 2007).  

 

The mother’s education leads to improvement in child health via more efficient child care in the 

home along with the enhanced use of prevention services and treatment (Caldwell, 1994). There is 

no specific threshold level of mother’s education which should be attained before the benefits of 

mother’s education forward to the child health. Mother’s education  aware them about their child 

health which cause lower death rates, longer life expectancies and nutrition status (Abuya et al.,2013; 

Barrera, 1990; Hadden & London, 1996). 
 

There is direct Relationship between mother’s working status and child health as working mothers 

have enough money to purchase healthy and hygienic food (energy and protein dense food) , services 

of house cleaner and utensils washer as well as vehicle which offer them more time to spend in child 

care activities (Gwozdz at al., 2013). Working mother spent some hours at work so they are more 

conscious about their child care working mothers have healthy child as the working mothers of under 

five children have less chance to be weak than non-working mothers (Fukuda et al., 2014).  

 

The age of mother is associated with the child health (Abuya et al., 2012). Teenage mothers are 

psychologically less mature and remain unaware and hesitant regarding reproductive matters 

(Garenne et al., 2000; Woldemicael, 2005).The child health increase with the age of mother and the 

marriage in early age increases the infant mortality (Tagoe-Dark, 1995).  

 

Weak mother has low nutrition status which effect child weight. Healthy and balance food of 

mothers have positive effect on their child. Underweight mother can impair to growing infants, 

because underweight mother may have premature and underweight baby at birth. Children of 

overweight mother associated with higher BMI and fat in their liver children and the consequence of 

mothers BMI on their child’s improvement in the womb may cause of path towards lifetime 

metabolic health problems (Modi et al, 2011; Negash et al., 2015). 



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This study is important as there exists lacuna on the subject of child health regarding comparison of 

developing countries which are of same continent. This study will provide important facts about 

demographic, socioeconomic and health factors effecting child health. This study is limited to the 

socio economic, demographic and health factors which effect child health of age five and under five. 

 

2. Data and Methodology 
 

2.1. Data 
The data for this study is derived from Pakistan Demographic and Health Survey (12-2013), 

Bangladesh Demographic and health survey (2011-12) and Nepal demographic and health survey 

(2011-12) in order to compare the effects of socioeconomic, demographic and health factors on child 

health in Pakistan, Bangladesh and Nepal.  

 
To put DHS in useable format some manipulation were adopted. There were many missing values in 
PDHS data set. It was inevitable to fill those missing values because analysis has been done by SPSS 

version 20. So missing values are excluded. The data was required on child with age 5 and below for 
proxy of child health which is child Body Mass Index, DHS provide data for children up to age 13 in 

Pakistan and in Nepal up to age 12. We filtered the data set to obtain required data for analysis. The 
values of child body mass index far beyond the lower and upper bound of standard values were 

considered as outliers and removed. In DHS some variables had large categories (Wealth Index, 
House hold size, water source, toilet facility and etc.), we merge them categories into 3 and 4 

subcategories.  

 
2.2. Methodology 

Multinomial logit model is the extensive form of the logit model. Multinomial logistic function is 

used in this study to examine the effects of child Body Mass Index. Outcome of independent variable 

is different for each type of dependent variable. In this model one category of dependent variable is 

used as the reference category. All further categories defined in the perspective of that reference 

category. It could be the first, last or the category with maximum incidence. For all N categories N-1 

equations are estimated. In Equation form multinomial logit model with three dependent variables 

and different independent variables is. 

 

( , , ) , , ( , , )

1

Pr( , )
ln ( )

Pr( )

J

a b c i a b c a b c j ij

j

Y a b
Y Z

Y c
 




  


 …………………...(1) 

 
Where; 

 Y= dependent variable 

N= a, b, c are the three different categories of child health. 

Here it determines the probability of ith children facing one of the jth outcomes (of being week, 

healthy and obese). 

Yi is the end results practiced by c 

 

pr(Child Health / BMI = Weak Child)
Ln = β + β X + β X .......+ β X

0 1 1 2 2 k kpr(Child Health / BMI  = Healthy Child)
…………………………..(2)  

 
pr(Child Health / BMI =Obese)

Ln = β + β X + β X .......+ β X
0 1 1 2 2 k kpr(Child Health / BMI  = Healthy Child)

…………………………...(3) 

 

2.3. Results and Discussion: 
 



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Relative probability of weak children rather than healthy children is significantly higher in urban 

areas than in rural areas keeping other factors constant in Nepal documented by previous studies 

(Ruel, 2003). Obese Child lives in urban areas than rural areas are relatively 41% more likelihood 

rather than healthy child in Pakistan.  

 

The relative probability of weak children rather than healthy children is significantly 32% and 31 % 

increasing for uneducated mothers and lower educated mothers than educated mothers in Nepal and 

Bangladesh respectively. It is supported by studies (Mondal et al., 2009; Frost et al., 2005). The 

relative probability of obese child than healthy child is 73% more than uneducated mothers. Pakistan 

has insignificant effect which shows it has not direct effect on child health. 

 

The relative probability of weak children rather than healthy children is 28 % higher for not working 

women than working mothers in Pakistan reported by previous studies (Ogada, 2014) that working 

mothers of age under five children has less chance to be weak those who not working mothers. 

Relative probability of obese child rather than healthy child strongly significantly 52% and 80%  

higher of not working mothers than working mothers keeping all others factors constant in Pakistan 

and Nepal. Gwozdz et al., (2013) recommended that working mothers have a tendency to utilize their 

money to take time off and take care of their children. 

 

The relative probability of weak children than healthy children is significantly 33 % increasing for 

middle than rich in Pakistan. In Bangladesh and Nepal it has positive but insignificant relationship. 

Household wealth is not significant and direct relation with child health. Parental income has 

negligible effect on child health. Relative probability of obese child rather than healthy child is 78% 

and 24% higher for poor and middle socioeconomic status than higher socioeconomic status than 

keeping other factors constant (Gouda, 2014).  

  



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Table 1: Household’s Socioeconomic and Demographic Variables Distribution With Reference 

To Child Health  in Selected South Asian Countries 
 

Table 2: Socioeconomic and Demographic Variables Affecting the Probability of Weak Child 

Health in Selected South Asian Countries 
Independent variables Pakistan Bangladesh Nepal 

Independent Variables 

Child Health/BMI 

Pakistan Bangladesh Nepal 

Weak 

Child 

Healthy 

Child 

Obese 

Child 

Weak 

Child 

Healthy 

Child 

Obese 

Child 

Weak 

Child 

Healthy 

Child 

Obese 

Child 

Place of  

Residence 

Urban = 1 
404 

(42.9) 
212 

(22.5) 
326 

(34.6) 
483 

(66.5) 
113 

(15.6) 
130 

(17.9) 
274 

(62.8) 
103 

(23.6) 
59 

(13.5) 

Rural = 0 
647 

(43.6) 

351 

(23.7) 

486 

(32.7) 

1155 

(69.0) 

257 

(15.4) 

262 

(15.7) 

996 

(57.3) 

505 

(29.1) 

237 

(13.6) 

 
Chi Sq. Value = 5.510^ 

Gamma = .087^ 
Chi Sq. Value = 2.043 

Gamma = -.057 
Chi Sq. Value = .988 

Gamma = -.024 

Gender of Child 

Male = 1 
538 

(43.9) 

272 

(22.2) 

416 

(33.9) 

872 

(71.2) 

155 

(12.7) 

198 

(16.2) 

694 

(61.1) 

302 

(26.6) 

139 

(12.2) 

Female = 0 
513 

(42.8) 

291 

(24.3) 

396 

(33.0) 

766 

(65.2) 

215 

(18.3) 

194 

(16.5) 

576 

(55.4) 

306 

(29.5) 

157 

(15.1) 

 
Chi Sq. Value = 1.450 

Gamma = .003 

Chi Sq. Value = 15.592* 

Gamma = .105* 

Chi Sq. Value = 7.861^ 

Gamma = .109^ 

Household size 

1-5 Members = 1 
218 

(51.7) 
101 

(23.9) 
103 

(24.4) 
847 

(77.1) 
139 

(12.6) 
113 

(10.3) 
642 

(62.0) 
267 

(25.8) 
127 

(12.3) 

6-7 Members = 2 
269 

(48.7) 

130 

(23.6) 

153 

(27.7) 

453 

(63.3) 

128 

(17.9) 

135 

(18.9) 

387 

(59.6) 

179 

(27.6) 

83 

(12.8) 

8-10 Members = 3 
297 

(40.6) 
165 

(22.6) 
269 

(36.8) 
236 

(56.6) 
70 

(16.8) 
111 

(26.6) 
186 

(50.1) 
120 

(32.3) 
65 

(17.5) 

Above 11 Members= 

3 

267 

(37.0) 

167 

(23.2) 

287 

(39.8) 

102 

(60.7) 

33 

(19.6) 

33 

(19.6) 

55 

(46.6) 

42 

(35.6) 

21 

(17.8) 

 
Chi Sq. Value = 45.439* 

Gamma = .164* 
Chi Sq. Value = 91.119* 

Gamma = .227* 
Chi Sq. Value = 23.785* 

Gamma = .134* 

Wealth Index 

Poor = 1 
512 

(42.0) 

266 

(21.8) 

442 

(36.2) 

714 

(70.8) 

142 

(14.1) 

152 

(15.1) 

672 

(60.2) 

307 

(27.5) 

138 

(12.4) 

Middle = 2 
173 

(40.3) 
108 

(25.2) 
148 

(34.5) 
294 

(66.7) 
72 

(16.3) 
75 

(17.0) 
239 

(57.9) 
121 

(29.3) 
53 

(12.8) 

Rich = 3 
366 

(47.1) 

189 

(24.3) 

222 

(28.6) 

630 

(66.2) 

156 

(16.4) 

165 

(17.4) 

359 

(55.7) 

180 

(28.0) 

105 

(16.3) 

 
Chi Sq. Value = 14.623^ 

Gamma = -.085^ 
Chi Sq. Value = 5.395 

Gamma = .072^ 
Chi Sq. Value = 6.654 

Gamma = .071^ 

Mother’s 

Education 

No Education = 1 
626 

(41.8) 

339 

(22.6) 

532 

(35.5) 

376 

(75.7) 

72 

(14.5) 

49 

(9.9) 

647 

(63.7) 

267 

(26.3) 

101 

(10.0) 

Primary = 2 
167 

(47.9) 
81 

(23.2) 
101 

(28.9) 
519 

(72.0) 
98 

(13.6) 
104 

(14.4) 
231 

(54.6) 
132 

(31.2) 
60 

(14.2) 

Secondary & Higher 

= 3 

258 

(44.5) 

143 

(24.7) 

179 

(30.9) 

743 

(62.9) 

200 

(16.9) 

239 

(20.2) 

392 

(53.3) 

209 

(28.4) 

135 

(18.3) 

 
Chi Sq. Value = 8.574^ 

Gamma = -.70 
Chi Sq. Value = 39.360* 

Gamma = .209* 
Chi Sq. Value = 34.15* 

Gamma = .171* 

Mother’s Work 
Status 

Not Working = 1 
799 

(43.0) 

408 

(22.0) 

649 

(35.0) 

1414 

(67.2) 

330 

(15.7) 

361 

(17.1) 

463 

(57.2) 

206 

(25.4) 

141 

(17.4) 

Working= 0 
252 

(44.2) 
155 

(27.2) 
163 

(28.6) 
224 

(75.9) 
40 

(13.6) 
31 

(10.5) 
807 

(59.2) 
402 

(29.5) 
155 

(11.4) 

 
Chi Sq. Value = 10.52^ 

Gamma = -.067
t 

Chi Sq. Value = 10.64^ 

Gamma = .057 

Chi Sq. Value = 16.94* 

Gamma = -.075^ 

Mother BMI 

Underweight = 1 
192 

(54.7) 
83 

(23.6) 
76 

(21.7) 
467 

(70.9) 
95 

(14.4) 
97 

(14.7) 
265 

(68.1) 
95 

(24.4) 
29 

(7.5) 

Normal weight= 2 
553 

(43.5) 

289 

(22.7) 

429 

(33.8) 

1006 

(68.2) 

220 

(14.9) 

248 

(16.8) 

890 

(57.1) 

441 

(28.3) 

228 

(14.6) 

Overweight = 3 
306 

(38.1) 

191 

(23.8) 

307 

(38.2) 

165 

(61.8) 

55 

(20.6) 

47 

(17.6) 

115 

(50.9) 

72 

(31.9) 

39 

(17.3) 

 
Chi Sq. Value = 35.90* 

Gamma = .162* 
Chi Sq. Value = 9.132^ 

Gamma = .086^ 
Chi Sq. Value = 26.17* 

Gamma = .198* 

Mother   age at 1
st
 

Birth 

Under 18 Age = 1 
328 

(41.6) 

189 

(24.0) 

272 

(34.5) 

1070 

(69.8) 

240 

(15.7) 

222 

(14.5) 

530 

(58.2) 

261 

(28.7) 

119 

(13.1) 

19-23 Age = 2 
493 

(42.3) 
270 

(23.2) 
403 

(34.6) 
479 

(65.2) 
115 

(15.6) 
141 

(19.2) 
617 

(60.1) 
268 

(26.1) 
142 

(13.8) 

Above 24 Age = 3 
230 

(48.8) 

104 

(22.1) 

137 

(29.1) 

89 

(66.9) 

15 

(11.3) 

29 

(21.8) 

123 

(51.9) 

79 

(33.3) 

35 

(14.8) 

 
Chi Sq. Value = 7.95

t 

Gamma = -.062^ 
Chi Sq. Value = 12.46^ 

Gamma = .100^ 
Chi Sq. Value = 6.565 

Gamma = .025 

Source:  Demographic and Health Surveys (DHS), author's own calculation 

Note:      Figures in parenthesis are the percentages 

^, *, t indicate coefficients are significant at 1, 5 and 10 percent level respectively. 



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B 
Odd 

Ratios 
B 

Odd 

Ratios 
B 

Odd 

Ratios 

Intercept .487  .420  -.868**  

Place of Residence                           Urban = 1 .068 1.070 -.082 .921 .374** 1.454 

Rural = 2 Reference Category 

Mother education                  no education = 1 .133 1.143 .189 1.208 .274*** 1.315 

primary education .264 1.302 .272 *** 1.313 .071 1.076 

Secondary& higher education Reference Category 

Mother’s Work Status,         Not Working = 1 .246** 1.279 -.155 .857 .111 1.118 

 Working = 0 Reference Category 

Socio economic status ,                      Poor =1  .105 1.11 .044 .957 .183 1.201 

Middle= 2 .28*** 1.325 .099 .906 .081 1.084 

Rich=3 Reference Category 

Water Source,                    Improved water=1 -.26*** .769 -.894* .409 -.21*** .805 

Non Improved water =2 Reference Category 

Child Gender  

Male = 1  
.127 1.135 .481* 1.618 .21*** 1.227 

Female = 0 Reference Category 

Mother age at 1st  birth,         Age up to 18=1 .260 1.296 .498 .608 .439** 1.551 

Age 19-23 =2 -.214 .808 -.413 .662 -.566* .567 

Age above 23= 3 Reference Category 

Birth Order,                                      1 birth=1 .090 1.094 -.030 .970 -.430 .650 

2-3 birth=2 -.281 .755 .069 1.071 -.528** .590 

4-6 birth=3 -.238 .788 .103 1.108 -.417 .659 

Above 6 birth=4 Reference Category 

Family Size,                           1-5 members=1 -.369** .691 -.421 *** .656 -.683* .505 

6-7 members =2  -.322** .724 -.022 .978 -.513** .598 

8-10 members =3 -.146 .864 -.006 .994 -.105 .900 

Above 10  members = 4 Reference Category 

Mother BMI,                         Underweight =1 .442** 1.556 .572** 1.771 .463** 1.590 

Healthy = 2 -.22*** .803 -.499** .607 -.119 .887 

Overweight = 3 Reference Category 

Vaccination Status,          Not  Vaccinated =1  .341** 1.406 .163 1.177 2.292* 9.897 

Vaccinated = 2 Reference Category 

Source: Author’s own calculations based on PDHS (2013), BDHS (2011) & NDHS (2011) 

Note: a) *, ** and *** indicates coefficient are significant at 1%, 5% &10% 

b) The reference category is 2= healthy child 

 

Table 3: Socioeconomic and Demographic Variables Affecting the Probability of Obese Child 

Health in Selected South Asian Countries 

Independent variables 

Pakistan Bangladesh Nepal 

B 
Odd 

Ratios 
B 

Odd 

Ratios 
B 

Odd 

Ratios 

Intercept .453  .878  .001  

Place of Residence                           Urban = 1 .343** 1.410 .238 1.269 .012 1.012 

Rural = 2 Reference Category 

Mother education                  no education = 1 .021 1.021 .127 1.135 .573* 1.773 

primary education .098 1.102 .041 1.042 .377** 1.457 

Secondary& higher education Reference Category 

Mother’s Work Status,         Not Working = 1 .420** 1.522 .238 1.268 .593* 1.809 

 Working = 0 Reference Category 

Socio economic status ,                      Poor =1  .576* 1.780 .292 1.339 .073 1.076 

Middle= 2 .298*** 1.348 -.008 .992 -.061 .941 

Rich=3 Reference Category 

Water Source,                    Improved water=1 -.690* .502 -1.849* .157 -.758* .468 

Non Improved water =2 Reference Category 

Child Gender ,                                   Male = 1  .160 1.174 .295*** 1.344 -.121 .886 

Female = 0 Reference Category 

Mother age at 1st  birth,         Age up to 18=1 -.022 .978 -.496 .609 .079 1.082 



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Age 19-23 =2 .056 1.058 -.292 .747 .145 1.157 

Age above 23= 3 Reference Category 

Birth Order,                                      1 birth=1 .031 1.032 .322 .725 .183 1.20 

2-3 birth=2 -.233 .792 -.115 .891 -.276 .759 

4-6 birth=3 -.278 .757 -.430 .651 -.321 .726 

Above 6 birth=4 Reference Category 

Family Size,                           1-5 members=1 .398** 1.488 .401 1.494 .005 1.005 

6-7 members =2  -.29 *** .748 .145 1.156 -.041 .960 

8-10 members =3 -.037 .963 .429 1.536 .112 1.118 

Above 10  members = 4 Reference Category 

Mother BMI,                         Underweight =1 -.602** .548 -.011 .989 -.402 .669 

Healthy = 2 -.192 .825 -.144 .865 -.124 .883 

Overweight = 3 Reference Category 

Vaccination Status,          Not  Vaccinated =1  .33*** 1.398 -.618** .539 -.679 .507 

Vaccinated = 2 Reference Category 

Source: Author’s own calculations based on PDHS (2013), BDHS (2011) & NDHS (2011) 

Note: a) *, ** and *** indicates coefficient are significant at 1%, 5% &10% 

b) The reference category is 2= healthy child 

 

The relative probability of weak children rather than healthy children is significantly lower by 77%, 

41% and 81% to the child intake improved and piped water source than non-improved water source 

in Pakistan. Relative probability of obese child rather than healthy child is 50%, 15% and 47% lower 

and strongly significant for all three countries using improved water than non-improved water. 

Previous research found a positive relationship between access to piped water and child health 

(Merrick, 1985; Thomas and Strauss, 1992; Lee et al., 1997, and Japan and Ravallion, 2003). 

Relative probability of obese child is 34 % higher than healthy child for male children than female 

children in Bangladesh. 

 

Male children are significantly more relative chance by 62% and 23% to be weak as compared to 

female children than healthy children in Bangladesh and Nepal. There is no sex discrimination as 

cleared by previous studies (Mge & Donnar, 2004; Khoury, 1987). 

 

Younger mothers are significantly more likelihood to have weak children by 55 % as compared to 

elder mothers relative to healthy children in Nepal. The risk of dying of child at 1
st
 birth is higher for 

younger mothers. (Gubhaju, 1991 and Furstenberg, 1990) suggested that teenage mothers were less 

able to overcome the economic and child bearing problems. 

 

In Pakistan first birth order have more relative probability to be weak children as compared to higher 

birth order as compared to healthy children keeping all other factors constant. Infant weakness was 

found to decline with higher birth order in one study (Gubhaju et al., 1987). In Pakistan and Nepal 

lower birth order have less chance to be weak than higher birth. It is supported by (Horton, 1998) 

explained that there is competition with younger siblings for resources. 

 

The relative probability of weak child is significantly 69%, 65% and 50% lower than healthy child in 

small families than largeer family’s children in Pakistan, Bangladesh and Nepal (Heaton, 2004; black 

1989 & Downey 1995). 

 

There are relatively more chances to be weak child than healthy child by 56%, 77% and 59% for 

underweight mothers than overweight mothers keeping all other factors constant reported by ( Nahar, 

2010) where mother with lower BMI has lower birth weight which effect breast feeding aptitude and 

capacity and results in lower BMI in infants and children. Normal weight mother has less chance by 

80%, 60% and 89% to have weak child in Pakistan, Bangladesh and Nepal. 

 



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150 
 

Children those are not vaccinated are strongly significantly more relative probability by 40% and 

89% to be weak as compared to the vaccinated children than healthy children keeping all others 

factors constant in Pakistan, Bangladesh. It is justified by (Wang, 2002 and Bonday et al., 2008) 

where it significantly affect children. 

 

3. Conclusion and Recommendations 
This study conclude that mother schooling play important role and helpful to make nutrition decision 

for their children to improve child height and weight so make sure to improve and facilitate women 

to educate and provide health knowledge to mothers. Source of water has positive and significant 

effect on child health so piped and clean water must be assessable to children to save them from 

deficiencies. 

 

 Mother working status has its positive impact on child health in Pakistan and Nepal. Working 

mothers are more conscious to take care of their children and due to move in social society they are 

able to obtain knowledge about their child health and can afford nutritional and hygienic food as well 

as cleaner objects. So steps must be taken for provision of job opportunities. Socioeconomic status 

also has its impact on child weight. Poor families have weak and obese children due to lack of 

money they have access to cheap and unhygienic food items. Income sources must be provided to 

poor families. Teenage mothers are less able to overcome the economic as well as child bearing 

problems and there may be intervention of education attainment.  

Small families have less chance of weak children in each country Pakistan, Bangladesh and Nepal. 

As parents can put more attention to their children in in small family. Small families have positive 

impact on child health as deep attention can be given by parents to take care of their children. 

 
Mother’s BMI is associated with child BMI. Weak mother has low nutrition status which effect less 

child birth weight and also compromise in capacity of breast feeding and results in low child BMI. 

Special campaigns are suggested to improve the BMI of mothers to have health new generation. . 

 

Maternal education is most important factor which effect child health so Government should take 

steps to improve female education and also provide health knowledge to females as mother education 

effect child health. It provides more awareness to mothers about how to nurture children.  

 

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