Review of Economics and Development Studies       Vol. I, No 1, June 2015 

 

33 
 

 

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 1 June 2015 

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

 

Households Socio-Economic Determinants of Childhood Diarrhoea Morbidity in 

Selected South Asian Countries 
 

1
Sofia Anwar, 

2
Aisha Iftikhar, 

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.  

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.  

 

 

ARTICLEDETAILS  ABSTRACT  

History 

Revised format: May 2015 

Available online: June 2015 

 

 This study attempts to find out the association between the household 

socioeconomic factors with childhood diarrhoea in Pakistan, Bangladesh 

and Nepal. To estimate the determinants of diarrhoea, the study uses the 

data derived from the Demographic and Health Surveys (DHS) in three 

Asian countries: Pakistan, Bangladesh and Nepal from 2011 to 2013. To 

find out the diarrhoea morbidity among child under five, the child age, 

child gender, mother’s education and working status, child immunization, 

source of drinking water, type of toilet facility, washing hands behavior, 

floor material, and economic status of household has been used as 

independent variables. Binary logistic model is used to estimate the 

probability of diarrhoea morbidity among children of selected countries in 

this study. The results of binary logistic regression indicate that to reduce 

diarrhoea morbidity, washing hands especially after using toilet and at 

time of preparing food and eating food can play a major part. Mother’s 

education and work status have significant impact on diarrhoea morbidity. 

The study concludes that family size has a strong impact on childhood 

diarrhoea morbidity. In small families, mothers have more time for child 

care than large families. So the chances of diarrhoea incidence are less in 

small families. 

 

© 2015 The authors, under a Creative Commons Attribution-

NonCommercial 4.0                                                         

Keywords 

Diarrhoea Morbidity 

Demographic and Health 

Surveys (DHS) Pakistan 

Bangladesh  

Nepal 

 

JEL Classification 

I12, I15, I18 

 

 

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

Recommended citation: Anwar, S., Iftikhar, A., Asif, A. and Batool, Z. (2015). Households Socio-Economic 

Determinants of Childhood Diarrhoea Morbidity in Selected South Asian Countries. Review of Economics and 

Development Studies, 1 (1) 33-44 

DOI: https://doi.org/10.26710/reads.v1i1.114 

 

 
 

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


Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

34 
 

 

1. Introduction  

According to United Nations Children’s Fund (UNICEF) diarrhoea is the ranked 2nd among the primary 

killers of children less than five worldwide. It is estimated that nearly 1.7 billion cases of diarrhea are 

reported around 760 000 not survive every year (UNICEF/WHO, 2013).According to WHO in the under 

five children deaths 9 percent are due to diarrhoea and the same figure is prevalent in Pakistan while 

Nepal and Bangladesh have 6 percent share of death owing to this menace (WHO, 2015).About 72% of 

deaths associated with diarrhoea occur in the early 2 years of child life with peaks at age 6–11 months 

and therefore mortality is highest from age 0–11 months, the ages at which the risk of disease and severe 

disease also peak. 

 

Further the global burden of incidence and severe disease for diarrhoea and pneumonia is highest in 

southeast Asia and Africa (walker and et al, 2013). The incidence and case-fatality ratios are much 

higher in low-income than in middle-income and high-income countries. It was targeted in the 

Millennium Development Goals that efforts must be taken to decrease child mortality up to two thirds 

between 1990 and 2015.  

 

Diarrhea is a communicable disease that may be caused by viral or bacterial. It is transmitted by food or 

water used by the patient. The socioeconomic factors of diarrhea incidence have been explained in the 

literature. But it is essential to identify their degree so that it can be decided that how much care is 

necessary to handle diarrhea. Diarrhea is usually caused by any waterborne or food borne pathogens. To 

reduce the occurrence of diarrhea, improvement in ecological factors, i.e. availability of sufficient and 

clean drinking water, providing better cleanliness, facilities, and individual cleanliness can play a 

significant part (Chakrabarti, 2003). 

 

Diarrhea can spread more easily in these unhygienic environments. It is generally familiar that coverage 

to diarrheal pathogens in under developing countries is due to factors, i.e. infant’s age, accommodation 

situation, quality of water, education level, accessibility of lavatory services, the economic position of 

people, feeding habits, the common hygienic conditions (individual or home hygiene) around the house 

and living place (Woldemicael, 2001). There are many interventions in sanitation, water and cleanliness 

programs that work to decrease the rate of diarrhea (Azizullah, 2011; Nantan et al., 2008; Walker et al., 

2003; Woldemicael, 2001).  

 

It is widely recognized that child morbidity influenced by socio-economic, demographic, and 

environmental factors such as child age, maternal education and occupation, socio-economic status, 

place of residence, housing conditions, improved toilet facilities and water source and number of 

children in the household (Ahuja et al., 2014; Chakrabarti, 2012; Kandala et al., 2008; 2009; Mihrete et 

al., 2014; Verma et al., 2016;   Woldemicael, 2001; Zeleke et al., 2014). Higher morbidity has also been 

reported in children during complementary feeding as a result of increased exposure to contaminated 

food. In related studies, low level of maternal education and maternal power to take decisions were 

observed to be risk factors for childhood morbidity (Amugsi et al., 2014). 

 

Identifying the basic environmental and socio-demographic factors that determine childhood morbidity 

remains important in reducing child mortality. Indeed, several studies have shown that childhood 

morbidity in less developed countries is the result of interactions among behavioral, socio-economic and 

environmental factors (Mihrete et al., 2014; UNICEF/WHO, 2009, 2012, 2013). It stands to reason that 

understanding childhood morbidity involves explaining the relationship and interactions of these factors. 

This is crucial for more focused implementation of child health interventions for policy formulation and 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

35 
 

intervention prioritization in Pakistan, Bangladesh and Nepal. 

 

This research explains the main factor associated with diarrhea. The findings of the study can be useful 

to make hygiene programs further efficient. This study proves a valuable involvement to the presented 

verification on association among diarrhea morbidity and household’s socioeconomic determinants. This 

study carries to explore the association between the household socioeconomic factors with childhood 

diarrhea in Pakistan, Bangladesh and Nepal. 

 

2. Data and Methodology 

 

A. Data 

To estimate the factors of diarrhea, the cross-sectional data were used. The data were taken from the 

Demographic and Health Surveys (DHS) in three Asian countries: Pakistan, Bangladesh and Nepal from 

2011 to 2013. The DHS surveys are household survey dataset from the selected countries at the national 

level. It is generally conducted in low and middle income countries. 

 

B. Description of Variables 

The study took the households having the child less than five years of analysis. To find out the diarrhea 

morbidity among child under five, child sex, education and working status of mother, child 

immunization, drinking water source, toilet facility, washing hands behavior, floor material, economic 

status of households and household size used as independent variables.  

 

C. Methodology 

To analyze the dichotomous, continuous and categorical explanation of variables by the use of 

categorical independent variables Logistic Regression was used. The dependent variable will be the 

incidence of diarrhea among children less than five. 

 The dependent variable will be in binary form, i.e. if diarrhea is prevailing among children, then value 

will be 1 otherwise 0. This function is said to be a logistic distribution function and to estimate it, 

maximum likelihood (ML) method is used. The main feature of this function is that it ensures that the 

likelihood ranges from 0 to 1. This study will use binary logistic model to estimate the probability of 

diarrhea morbidity among children of selected countries. 

The logistic model is written as follows: 

 
Here Y = 1 shows that a specific child is affected by diarrhea and X is the set of independent variables. 

Pi is the restricted possibility that a specific child is having diarrhea. In the perspective of logic model it 

can be written as 

 

It can be written as Zi=  

 

 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

36 
 

If Pi shows the chance of having diarrhea then (1 – Pi) indicates the chance of no diarrhea. 

 
 

The proportion of diarrheal morbidity to no diarrhea is 

 
Pi / (1 – Pi) is the odds ratio of having diarrhea. If we take the natural log of the odd ratio we get 

 
As 

 
So it can be said that Li is linear with reference to the parameters and Xi shows the independent 

variables. The benefit of this model is that only Li is linearly associated with not the probabilities 

(Gujarati, 2004). 

 

3. Results and Discussions  

Table 1, 2 and 3 depicts frequency distribution and cross tabulation of individual’s various demographic, 

economic, environmental and behavioral variables factors with reference to diarrhea in  Pakistan, 

Bangladesh and Nepal.In Pakistan, there are 80 percent chances of not having diarrhea morbidity and 19 

percent chance of having diarrhea in children in urban areas. The childhood diarrhea in rural areas of 

Pakistan is 22 percent. While the 78 percent children have no diarrhea in rural areas of Pakistan (Ali et 

al., 2009).  

 

Variables description 

Diarrhea 

Pakistan Bangladesh Nepal 

No Yes Total No Yes Total No Yes 
Tota

l 

D
e
m

o
g
r
a
p

h
ic

  
v
a
r
ia

b
le

s
 P
la

c
e
 o

f 
 

R
e
si

d
e
n

c
e
 Urban = 1 

3567 

(80) 

888 

(20) 

4455 

(100) 

2163 

(95) 

95 

(4.2) 

2258 

(100) 

913 

(87) 

136 

(13) 

1049 

(100) 

Rural = 0 
4675 

(78) 

1311 

(22) 

5986 

(100) 

4611 

(9.9) 

249 

(5.1) 

4860 

(100) 

3462 

(86) 

543 

(14) 

4005 

(100) 

 
Chi Sq. Value =5. 95 

Gamma =0. 59 

Chi Sq. Value = 2.81 

Gamma = 0.10 

Chi Sq. Value =.252 

Gamma = 0.26^ 

G
e
n

d
e
r
 o

f 
C

h
il

d
 

Male =1 
4156 

(78) 

1173 

(22) 

5329 

(100) 

3490 

(95) 

191 

(5.2) 

3681 

(100) 

2224 

(84) 

396 

(15) 

2620 

(100) 

Female= 0 
4086 

(80) 

1026 

(20) 

5112 

(100) 

3284 

(96) 

153 

(4.5) 

3437 

(100) 

2151 

(88) 

283 

(11) 

2434 

(100) 

 
Chi Sq. Value=5.914^ 

Gamma =   -.058^ 

Chi Sq. Value=2. 101 

Gamma =   -.080 

Chi Sq. 

Value=13.196* 

Gamma =   -. 150^ 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

37 
 

Table 1: Household’s Demographic Variables Distribution With Reference To Diarrhea 

Morbidity Selected South Asian Countries 

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.  

 

  

H
o
u

se
h

o
ld

 s
iz

e
 

1-5 members = 1 
1491 

(76) 

468 

(24) 

1959 

(100) 

3470 

(95) 

167 

(4.6) 

3637 

(100) 

2056 

(86) 

313 

(13) 

2369 

(100) 

6-10 members =2 
4302 

(79) 

1129 

(20) 

5431 

(100) 

2830 

(95) 

147 

(4.9) 

2977 

(100) 

2076 

(86) 

333 

(13) 

2409 

(100) 

11-15 members 

=3 

1770 

(80) 

445 

(20) 

2215 

(100) 

399 

(93) 

28 

(6.6) 

427 

(100) 

197 

(87) 

29 

(12) 

226 

(100) 

> 15 members = 

4 

679 

(81) 

157 

(18) 

836 

(100) 

75 

(97) 

2 

(2.6) 

77 

(100) 

46 

(92) 

4 

(8) 

50 

(100) 

 
Chi Sq .Value=13.544^ 

Gamma =   -. 067* 

Chi Sq. Value =.248^ 

Gamma =.058 

Chi Sq. Value = 

1.754 

Gamma =.008* 

M
o
th

e
r
’s

 E
d

u
c
a
ti

o
n

 

No Education=1 

 

4639 

(78) 

1238 

(21) 

5877 

(100) 

1210 

(95) 

64 

(5) 

1274 

(100) 

2026 

(86) 

312 

(13) 

2338 

(100) 

Incomplete 

Primary=2 

400 

(73) 

143 

(26) 

543 

(100) 

1153 

(93) 

76 

(6.2) 

1229 

(100) 

618 

(87) 

89 

(12) 

707 

(100) 

Complete 

Primary= 3 

749 

(79) 

191 

(20) 

940 

(100) 

837 

(93) 

59 

(6.6) 

896 

(100) 

256 

(84) 

46 

(15) 

302 

(100) 

Secondary= 4 
1465 

(78) 

410 

(21) 

1875 

(100) 

2982 

(96) 

119 

(3.8) 

3101 

(100) 

1222 

(86) 

192 

(13) 

1414 

(100) 

Higher=5 
989 

(82) 

217 

(18) 

1206 

(100) 

592 

(95) 

26 

(4.2) 

618 

(100) 

253 

(86) 

40 

(13) 

293 

(100) 

 
Chi Sq. Value = 16.955* 

Gamma = -. 019 

Chi Sq. Value 18.164* 

Gamma = -. 144^ 

Chi Sq. Value 

=1.327  Gamma 

=.010^ 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

38 
 

Table 2: Household’s Economic Variables Distribution With Reference To Diarrhea Morbidity 

Selected South Asian Countries 

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.  

 

 

The results depicted in table 4 indicate that in Pakistan and Bangladesh urban children have less 

probability of having diarrhea as compared to rural children, but results are insignificant. Results are 

consistent with the studies (Arif & Naheed 2012). The results illustrate that the probability of diarrhea 

morbidity in female children is more than the male children in all three countries. This may be due to the 

care in gender bias in these countries. Household size has a significant impact on childhood diarrheal 

morbidity. Children living in households with 1 to 5 members have less probability to have diarrhea 

morbidity as compared to those children who lives in household above 15 members in three countries. In 

small household size, the chances of diarrhea are. .44 times, .27 times and. 26 times less than large 

household size. Results are consistent with (Kaas, 1994).  

 

 

 

 

 

 

 

 

Variables description 

Diarrhea 

Pakistan Bangladesh Nepal 

No Yes Total No Yes 
Tota

l 
No Yes 

Tota

l 

E
c
o
n

o
m

ic
 V

a
r
ia

b
le

s 

W
e
a
lt

h
 I

n
d

e
x

 

Poorest = 1 
1904 

(78) 

513 

(21) 

2417 

(100) 

1398 

(94) 

82 

(5.5) 

1480 

(100) 

1377 

(87) 

201 

(12) 

1578 

(100) 

Poorer = 2 
1588 

(76) 

501 

(24) 

2089 

(100) 

1292 

(95) 

68 

(5.0) 

1360 

(100) 

895 

(86) 

138 

(13) 

1033 

(100) 

Middle = 3 
1584 

(78) 

431 

(21) 

2015 

(100) 

1289 

(94) 

78 

(5.7) 

1367 

(100) 

748 

(84) 

139 

(15) 

887 

(100) 

Richer = 4 
1538 

(78) 

421 

(21) 

1959 

(100) 

136 

(96) 

53 

(3.7) 

1422 

(100) 

693 

(85) 

114 

(14) 

807 

(100) 

Richest = 5 
1628 

(83) 

333 

(17) 

1961 

(100) 

1426 

(95) 

63 

(4.2) 

1489 

(100) 

662 

(88) 

87 

(11) 

749 

(100) 

 
Chi Sq. Value = 30.747* 

Gamma =.061* 

Chi Sq. Value 8.91^ 

Gamma =.058 

Chi Sq. Value 

=6.941 

Gamma =.007^ 

M
o
th

e
r
’s

 W
o

r
k

 

S
ta

tu
s 

Not Working = 1 
6727 

(79) 

1723 

(20) 

8450 

(100) 

6076 

(95) 

307 

(4.8) 

6383 

(100) 

1623 

(85) 

274 

(14) 

1897 

(100) 

Working=0 
1490 

(76) 

469 

(23) 

1959 

(100) 

698 

(95) 

37 

(5.0) 

735 

(100) 

2752 

(87) 

405 

(12) 

3157 

(100) 

 
Chi Sq. Value = 12.058* 

Gamma=.103* 

Chi Sq. Value = .072 

Gamma = .024 

Chi Sq. Value = 

2.658 

Gamma = -.069^ 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

39 
 

Table 3: Household’s Environmental and Behavioural Variables Distribution With Reference To 

Diarrhea Morbidity Selected South Asian Countries 

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.  

Variables description 

Diarrhea 

Pakistan Nepal Bangladesh 

No Yes Total No Yes 
Tota

l 
No Yes Total 

E
n

v
ir

o
n

m
e
n

ta
l 

a
n

d
 B

e
h

a
v
io

u
r
a
l 

V
a
r
ia

b
le

s 

S
o
u

r
c
e
 o

f 

d
r
in

k
in

g
 w

a
te

r
 

Improved 

Source = 1 

7008 

(79) 

1858 

(21) 

8866 

(100) 

5973 

(95) 

298 

(4.8) 

6271 

(100) 

3399 

(86) 

524 

(13) 

3923 

(100) 

Non-improved 

source = 0 

1232 

(78) 

341 

(21) 

1573 

(100) 

801 

(94) 

46 

(4.4) 

847 

(100) 

976 

(86) 

155 

(13) 

1131 

(100) 

 
Chi Sq. Value = .419 

Gamma = .022 

Chi Sq. Value = .748 

Gamma =  .070 

Chi Sq. Value =.091 

Gamma = .015^ 

T
y
p

e
 o

f 
T

o
il

e
t 

F
a
c
il

it
y
 

Improved = 1 
5778 

(79) 

1483 

(20) 

7261 

(100) 

3262 

(95) 

154 

(4.5) 

3419 

(100) 

1987 

(87) 

281 

(12) 

2208 

(100) 

Non-improved 

= 2 

426 

(78) 

114 

(21) 

540 

(100) 

2372 

(94) 

128 

(5.1) 

2500 

(100) 

376 

(88) 

50 

(11) 

426 

(100) 

No facility= 3 
2036 

(77) 

602 

(22) 

2638 

(100) 

1135 

(94) 

62 

(5.2) 

1197 

(100) 

2072 

(85) 

348 

(14) 

2420 

(100) 

 
Chi Sq. Value = 6.68^ 

Gamma = .062^ 

Chi Sq. Value = 1.563 

Gamma =  .056 

Chi Sq. Value = 3.868 

Gamma = .063^ 

V
a
c
c
in

a
ti

o
n

 

No = 1 
1338 

(77) 

382 

(22) 

1720 

(100) 

1557 

(94) 

83 

(5.1) 

1640 

(100) 

813 

(85.3) 

140 

(14.

7) 

953 

(100) 

Yes = 2 
6904 

(79) 

1817 

(20) 

8721 

(100) 

5217 

(95) 

261 

(4.8) 

5478 

(100) 

3562 

(86) 

539 

(13) 

4101 

(100) 

 
Chi Sq. Value = 1.633 

Gamma = -. 041 

Chi Sq. Value =.241 

Gamma = -. 032 

Chi Sq. Value =1.592   

Gamma =    -. 065^ 

U
se

 S
a
v
e
 W

a
te

r
 No = 1 

3216 

(60) 

2097 

(39) 

5313 

(100) 

4134 

(92) 

329 

(7.4) 

4463 

(100) 

1646 

(72) 

639 

(28) 

2285 

(100) 

Yes = 2 
5026 

(98) 

102 

(2) 

5128 

(100) 

2640 

(99) 

15 

(6) 

2655 

(100) 

2729 

(98) 

40 

(1.4

) 

2769 

(100) 

 
Chi Sq. Value =2204.8* 

Gamma = -.940* 

Chi Sq. Value = 

167.69* 

Gamma =  -.867* 

Chi Sq. Value = 

757.10* 

Gamma = -.927^ 

U
se

 C
le

a
n

in
g
 A

g
e
n

t 

 

Soap = 1 
4766 

(80) 

1185 

(19) 

5951 

(100) 

2967 

(95) 

118 

(4.1) 

3095 

(100) 

1989 

(86) 

312 

(13) 

2301 

(100) 

Mud = 2 
1152 

(78) 

325 

(22) 

1477 

(100) 

592 

(95) 

28 

(4.5) 

620 

(100) 

1123 

(86) 

179 

(13) 

1302 

(100) 

Nothing = 3 
2324 

(77) 

689 

(22) 

3013 

(100) 

3215 

(94) 

188 

(5.5) 

3403 

(100) 

1263 

(87) 

188 

(13s

s) 

1451 

(100) 

 
Chi Sq. Value = 11.42^ 

Gamma = .072^ 

Chi Sq. Value =6.94^ 

Gamma =    .132^ 

Chi Sq. Value = .426 

Gamma =  -.015^ 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

40 
 

The results also point out that family economic position is a vital and important forecaster of infant 

diarrhea in three selected countries. Children belonging to poorer families have a more significant 

probability of diarrhea morbidity than richer families in three countries. Past research showed the same 

results (Arif & Naheed 2012).  

Mother’s education indicates a negative relationship by the danger of diarrhea in the three selected 

countries. Children of uneducated and low educated mothers have 1.36times, 1.96 times and 2 times 

more likelihoods of diarrheal morbidity respectively as compare to the children of highly educated 

mothers.  The findings are in line with (Arif & Naheed, 2012). 

 

Table 4: Household’s Socioeconomic Determinants of Childhood Diarrhea 

Morbidity in Selected South Asian Countries 

Independent variables 

Pakistan Bangladesh Nepal 

B 
Odd 

Ratios 
B 

Odd 

Ratios 
B 

Odd 

Ratios 

Place of Residence 

Urban = 1 
-0.004 0.99 -0.01 0.99 0.09 1.09 

Rural = 2 Reference Category 

Child Gender  

1  = Male = 1  
-0.09 0.91 -0.21

t 
0.81 -0.39* 0.67 

0 = female = 2 Reference Category 

Households Size 

1-5 members =1 
-0.81* 0.44 -1.31

t 
0.26 -1.34^ 0.26 

6 -10 members = 2 -0.79* 0.45 -0.86 0.42 -0.69 0.49 

11-15 members = 3 -0.37^ 0.68 0.06 1.06 -0.20 0.81 

Above 15 members = 4 Reference Category 

Wealth Index  

Poorest = 1 
0.27

t 
1.31 0.31 1.38 0.34 1.41 

Poorer = 2 0.31^ 1.36 0.41 1.51 0.52^ 1.69 

Middle =3 0.09 1.09 0.28 1.33 0.49^ 1.63 

 Richer = 4 0.15 1.16 0.70^ 2.02 0.25 1.28 

Richest =5 Reference Category 

Mother education 

no education = 1 
0.30^ 1.36 0.67^ 1.96 0.69^ 2.00 

Incomplete Primary = 2 0.07 1.08 0.37 1.45 0.66^ 1.94 

complete primary = 3 0.26^ 1.30 0.18 1.21 0.48 1.63 

secondary= 4 0.07 1.07 0.60^ 1.84 0.22 1.25 

higher education = 5 Reference Category 

Work Status 

Working = 1 
0.129

t 
1.138 0.01 1.01 0.17

t 
1.19 

Not working = 0 Reference Category 

Water Source 

Improved = 1 
-0.27^ 0.76 -1.31* 0.26 -0.28^ 0.01 

Non improved = 0 Reference Category 

Toilet Facility 

Improved toilet = 1 
-0.15^ 0.86 -0.22 0.80 -0.25^ 0.77 

Non-improved = 2 -0.30^ 0.73 -0.29 0.74 -0.16 0.84 

No Toilet = 3 Reference Category 

Flooring Type 0.052 1.05 -0.30 0.73 0.48^ 1.62 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

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Natural Floor = 1 

Rudimentary = 2 -0.55 0.577 1.017 2.766 0.629 1.88 

Finished = 3 Reference Category 

Vaccination 

Yes =1 
-0.24^ 0.785 0.158 1.171 -0.152 0.859 

No = 0 Reference Category 

Use save water 

Yes = 1 
-3.78* 0.023 -2.64* .071 -0.16 0.846 

No = 0 Reference Category 

Cleaning Agent 

Soap = 1 
- 0.19^ 0.82 -1.92* 0.146 0.721* 0.48 

Mud= 2 -.065* 0.94 -2.05* 0.128 0.304^ 0.73 

Nothing =3 Reference Category 

Constant 0.826* 2.284 1.69
 

5.417 0.71 2.035 

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

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

 

Working status of mothers is positively related to the possibility of children being ill due to diarrhea in 

Pakistan and Nepal. Workers’ children have 1.14 times 1.192 times more chances of diarrhea than 

housewife’s children in above cited countries. Past research concluded similar results (Arif, 2004) 

About 88% global deaths due to diarrhea are considered with insecure water, insufficient cleanliness, 

and portable sanitation (WHO/UNICEF, 2004). Our study, confirming the same, finds that type of 

source of drinking water, toilet facility, flooring type, adopts any methods to save water and use soap or 

other cleansing agent for washing hands and quality of drinking water are significantly associated with 

diarrhea (Palit et al., 2012). Results show that those children existing in those houses with natural 

flooring are 1.63 times more probable to be ill due to diarrhea than those living in homes with finished 

flooring in Nepal, other two countries revealed insignificant results. 

 

Children living in households having improved sources (piped water or a motor-pump) inside the house 

were 77 times, .25 times and .28 times in Pakistan, Bangladesh and Nepal respectively, fewer expected 

to be sicker than kids in those families having other an improved sources of water, including well or 

river unprotected dug well or springs, tanker truck/cart and surface water. The quality of drinking is 

measured by adopting any method to save water is significantly associated with the odds of suffering 

from diarrhea (Galen et al. 2003 Banda; et al. 2007; Alam 2007).  

 

In our study, the children with access to safe drinking water are almost .023 times, .07 times and.84 

times in Pakistan, Bangladesh and Nepal respectively, less likely to suffer from diarrhea than those who 

use unsafe water. This is the estimated example, as piped water is generally said to be less polluted than 

other sources. Results also show that the prevalence of diarrhea among children who lived in households 

that had an improved toilet facilities (with flush system) was substantially lower than among those who 

lived in households without the flush system.  

 

Children belonging to households equipped with separate flush toilet are almost .8 times in all selected 

countries less likely to suffer from diarrhea than the children with access to Other type of toilets 

(includes pit latrine, dry toilet and toilet shared by other households). Toilets covered under another type 

are generally unhygienic and shows a higher risk of getting diarrhoea among children. 

Hands washing behavior of children has significant impact on diarrhea morbidity. Hand washing with 

soap significantly .82 times, .15 times and .48 times had lowered the incidence of diarrhea among 

children in three selected countries. If children use soap or mud to wash their hands, they have less 



Review of Economics and Development Studies      Vol. I, No 1, June 2015 

 

42 
 

possibility to become sick because of diarrhea than those who do not use anything to wash hands (Luby, 

2011). Use the soap for washing hands has exposed to decrease the frequency of diarrheal infection by 

over 40 per cent (UNICEF/WHO, 2009). It previously indicates that water and sanitation interventions 

can show a significant part in reducing the frequency of this sickness between kids (Palit et al., 2012; 

Roushdy et al., 2012; Waddington et al., 2009). 

 

Hand washing has received significant attention in efforts to promote better hygiene. Washing  

Children who had immunized were .78 times less likely to be sick more due to diarrhea than children 

who did not have this immunization in Pakistan but these results were insignificant in other two 

countries. The studies proved that immunization is not directly linked with diarrhea morbidity but 

immunization is probably helpful to defend children against measles linked diarrhea (Arif, 1998). 

 

4. Conclusion & Recommendations  

This study explains the factors related to diarrhea among children of less than age five in three South 

Asian (Pakistan, Bangladesh and Nepal) countries. Although different variables play different roles for 

diarrhea morbidity across the countries, but still we can express the significance of various factors which 

may supportive to manage diarrhea morbidity in South. Although the results of binary logistic regression 

showed that the residential place, mother’s education, flooring type have not a significant impact on 

diarrhea morbidity in three countries but they showed positive association with diarrhea morbidity. The 

focus of present study is on the contact of sanitation conditions on diarrhea morbidity and has 

established a significant relationship among diarrhea morbidity and sanitation conditions mainly water 

source and do something to make water safe. 

 

The study concluded that in order to attain Millennium Development Goal 4 (to decrease under-five 

death by two-thirds between 1990 and 2015); there is a need to promote attention specified to diverse 

factors influencing the identical allocation of economic and environment resources and amenities to all 

parts of the world particularly the high-mortality countries. There is a need to introduce different 

programs to promote family cleanliness and hygiene. It has been proved by research that cleanliness and 

hygiene are more vital than the quality of water. 

 

The study found that children with measles immunization are having fewer chances to be sick due to 

diarrhea. So it can be concluded that immunization of children reduces child mortality as well as to 

reduce diarrhea morbidity among children under age five. It is clear from the results of binary logistic 

regression that washing hands behavior of children has significant impact on diarrheal morbidity. The 

study indicated that to reduce diarrhea morbidity, washing hands especially after using the toilet and at 

the time of preparing food and eating food can play a major part. Education of mother and employment 

position has not significant impact on diarrhea morbidity but they have a strong association with 

diarrhea morbidity. The study concluded that family size has a strong impact on childhood diarrheal 

morbidity. In small families, mothers have more time for child care than large families. So the chances 

of diarrhea incidence are less in small families. 

 

 

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