Clean Water, Sanitation and Diarrhoea in Indonesia: Effects of household and community factors

NiCE Working Paper 14-105
                        October 2014

  Clean Water, Sanitation and Diarrhoea in
Indonesia: Effects of household and community
                           factors

                  Ahmad Komarulzaman
                         Jeroen Smits
                        Eelke de Jong

        Nijmegen Center for Economics (NiCE)
          Institute for Management Research
             Radboud University Nijmegen

         P.O. Box 9108, 6500 HK Nijmegen, The Netherlands
                http://www.ru.nl/nice/workingpapers

                                0

Abstract

In Indonesia, diarrheal disease is the third leading cause of child death. This study examines
the effects of drinking water and sanitation facilities on diarrhoea incidence among children
under five, while controlling for risk factors at household and community level. We used
nationally representative data from two waves (2007 and 2012) of the Indonesian
Demographic and Health Survey. Multilevel logistic regression analysis was used.
Interactions were studied between the water and sanitation variables and other risk factors to
assess the role of the context. We found that piped water, child age and sex, household
wealth, living in an urban area, environmental hygiene, health status and health facilities to be
negatively associated with diarrhoea incidence. Water treatment, and mother’s education were
not significantly associated with diarrhoea. An interaction analysis showed that the protective
effects of piped water and sanitation are more important when conditions within the
communities are poor.

Keywords

Child health, Diarrhoea, Drinking water, Indonesia, Multilevel analysis, Sanitation

Acknowledgments
We are grateful to DHS Program for making the Indonesia DHS data available for this study.
This work was supported by DHGE Scholarship from the Ministry of Education and Culture,
Republic of Indonesia.

Correspondence Address

Nijmegen Center for Economics, Institute for Management Research, Radboud University
Nijmegen, Thomas van Aquinostraat 5, 6525GD Nijmegen, The Netherlands;
a.komarulzaman@fm.ru.nl

                                                1

Introduction

   The latest WHO-UNICEF1 report on the progress of sanitation and drinking water
estimated that in 2011 over 750 million people lacked access to safe drinking water and that
185 million of them had to rely on surface water for their water consumption. About 83% of
the households with unimproved drinking water lived in rural areas. Even though the urban
drinking-water coverage is with 96% almost complete, the water supply is often
discontinuous which may increase the contamination risks.
   In Indonesia, still about 18% of households rely for their drinking water on surface water
sources, such as spring, river, pond, and lake which are prone to hygiene issues. 2 Meanwhile,
about 11% of households have access to piped water inside their dwelling2 but the quality is
often below the minimum requirement for drinking water, with fluctuating debit, and frequent
supply interruptions.3 The problem is not only the low capacity of the piped water system, but
also that the water is often contaminated by faecal coliform and is unsafe to be consumed
without processing steps.4 Moreover, although almost all households boil their drinking
water,5 this is not done effectively as 55 percent of drinking water samples have been found
contaminated by fecal coliform.6
   The biggest concern related to the poor water access and high contamination risk is water
borne diseases such as diarrhoea. It was found that 88% of the diarrhoea mortality among
children in the world can be attributed to lack of safe drinking water, good sanitation and
hygiene practices.7 Given the poor availability of water and sanitation in Indonesia, it comes
as no surprise that diarrhoea stills remains a major health concern in the country. Diarrhoea is
the major cause of 31% of post neonatal mortality and of 25% of child mortality in
Indonesia.8
   Diarrhoea cannot be solved simply by providing households with improved drinking water
and sanitation. Other factors are important too, such as hygienic behaviour and a clean living
environment. Research indicates that there is substantial variation in the incidence of
diarrhoea among socio-economic groups and according to availability of health facilities and
of cleanliness of the environment.9-11 Hence, the determinants of diarrheal disease are not only
found at the level of the individual sufferer (e.g. age and sex) and household in which the
individual lives (e.g. socio-economic factors, water supply and sanitation) but also at the
level of the larger context in which that household is living (e.g. infrastructure, health
services, pollution).

                                                 2

Given that many of these determinants are related to each other (poor households live in
regions with poorer facilities and more pollution), estimating their importance needs to be
done within a multilevel framework, whereby all relevant factors at the different levels are
included simultaneously. Multilevel research on determinants of children’s health has already
been applied to several health outcomes for children.12,13 However, no multilevel research has
yet been done for diarrhoea in Indonesia. In recent systematic reviews of water, sanitation and
diarrhoea9,14,15 only two studies on diarrhoea in Indonesia were included, neither of which
focused on the importance of water and sanitation. The few available studies on effects of
water and sanitation on childhood diarrhoea in Indonesia16-20 were focused only on specific
communities and region(s) of the country.
   In this paper, national representative data of the Indonesian Demographic and Health
Surveys 2007 and 2012 are used to study the effects of drinking water and sanitation on
diarrhoea incidence among children under five, while controlling for other risk factors at the
household and community level. To make the outcomes of our analyses more policy relevant,
we also explore the existence of interactions between the risk factors at the different levels
and the indicators for water and sanitation quality. These interactions aim to increase our
understanding of the circumstances under which bad water and sanitation characteristics are
more or less problematic and hence on which situations and groups policy measures aimed at
reducing diarrhoea should focus.

Methods
Data
   This study utilized the Indonesia Demographic and Health Surveys (DHS) from 2007 and
2012.21,22 These DHS datasets were designed to be representative for the national, urban,
rural, as well as provincial level. The DHS-2007 and DHS-2012 included 40,701 and 43,852
households living in 33 provinces in Indonesia. The response rates were over 95%. Both
datasets collected information on demographic, socioeconomic, and health-related issues. To
ensure the protection of the human subject, all DHS protocols are reviewed by an ethics
review panel or institutional review board in the country where the survey is conducted.23
   For the current study, both surveys were combined into a single dataset, including 33,399
children under five years old from 28,547 mothers living in 2,480 subdistricts within 488
Indonesian districts. We excluded children with missing data on diarrhoea infection (N=338)
and missing response(s) on explanatory variable(s) (N=1,521, 4.4% of children who answered
the diarrhoea question).

                                                3

Outcome variable
   The outcome variable of interest was the diarrhoea incidence. It was based on a mother’s
answer to the question whether the child suffered from diarrhoea in the past two weeks. This
question was asked to all mothers with living children under five years old.

Independent variables
   Control variables were included at the household and subdictrict level. Context variables at
subdistrict level were aggregated from households data. They were calculated as the
proportion of individuals or the mean of the variable with a certain characteristic.
   The main household level predictors in this study were piped water in the dwelling (yes,
no), point-of-use water treatment (yes, no), and improved toilet (yes, no). The point-of-use
water treatment was defined as whether the household did any appropriate treatment method,
such as boiling, bleaching, chlorinating, filtering, or solar disinfection to the water before its
consumption, in order to increase the water quality. Improved sanitation is a toilet facility that
ensures the separation of human excreta from human contact, including a toilet with septic
tank, pit latrines, and composting toilet.24
   Other household factors were the child’s gender (girl, boy), age (0-4 years), mother’s
education (years), household wealth index, living in an urban area (yes, no) and DHS 2012
(yes, no). Household wealth was measured by an index based on household assets. Following
Smits & Steendijk25, this wealth indicator was constructed by applying a principal component
analysis (PCA) on household assets, including radio, television, refrigerator, telephone, car,
bicycle, motor bike, type of floor, and the presence of electricity in the dwelling. The
procedure was used to create a standardized continuous index ranging from 0 – 100.
   Context factors: At subdistrict level (called community henceforth), we included seven
contextual variables. The first two were improved water coverage and environmental
hygiene, measured by the proportion of households in the community with improved water
and improved toilet facility,24 respectively. Health facilities coverage was indicated by the
proportion of mothers who gave birth in proper health facilities such as a hospital, health
centre, village health post, or with help of a village midwife. Another health indicator at the
community level was the proportion of children in the community who received three polio
vaccinations. The community level of development was indicated by the proportion of
households in the sub district owning a car. Two context variables—adults’ education and
maternal decision power—were created to measure the cultural differences among

                                                 4

communities. Adults’ education was measured by the average years of education completed
by adults aged 15 and over in the community. As indicator of maternal decision power, the
proportion of mothers who reported that they could decide by themselves whether a child
should be taken for medical treatment was used. All context variables were standardised to
make the coefficients comparable.

Statistical analysis
   To investigate the effect of drinking water and sanitation on diarrhoea incidence, a three
level multilevel logistic regression model was constructed, with children (level 1) nested in
sub-districts (level 2), nested in districts (level 3). The analysis was conducted using MLwiN
V.2.29 (Center for Multilevel Modelling, Bristol, UK) with a second order penalised quasi-
likelihood linearization procedure. Both bivariate and multivariate multilevel models were
estimated. The multivariate model was supplemented with an interaction analysis in which
interactions with the five main variables (piped water in the dwelling, point-of-use water
treatment, improved toilet, improved water coverage, and environmental hygiene) were
studied. Given the explorative nature of the interaction analysis, we tested for all potential
interactions with the independent variables, but included only the significant ones in the
model. In the interaction analyses, centered or standardized versions of the variables were
used. The main effects of the variables included in the interactions therefore are average
effects. Statistical significance was evaluated at p

In the bivariate analysis reported in Table 2, all of the household and community
coefficients were significantly associated with diarrhoea incidence, except for point-of-use
water treatment and adults’ education. Children with better water and sanitation facilities both
in the household and at the community level were less likely to get diarrhoea.

   [insert Table 2 here]

Multilevel analysis
   Results of the multilevel analysis are presented in Table 3. Model 1 includes only main
effects and model 2 includes both the main and interaction effects.

   [insert Table 3 here]

   After controlling for other factors, access to piped water in the premises remained
significantly associated with diarrhoea incidence (OR=0.81, 95% CI 0.71 to 0.93). Treating
the water before consumption remained insignificant (OR=1.08, 95% CI 0.97 to 1.20) while
the presence of an improved toilet in the household lost its significance (OR=1.00, 95% CI
0.91 to 1.10). These findings are in contrast with those at the community level, where
environmental hygiene was significantly and negatively associated with diarrhoea incidence
(OR=0.91, 95% CI 0.84 to 0.99) while the coverage of improved water in the community had
no direct effect on diarrhoea (OR=0.98 95% CI 0.93 to 1.03).
   There were no major changes in the effects of the children’s characteristics. Both child sex
and age remained strongly significant and negatively related with diarrhoea. However, the
results for other household characteristics were more mixed. The direct effect of maternal
education was diminished while household wealth remained significant. Except for car
ownership in the community, all other contextual variables remained significantly associated
with a lower diarrhoea incidence. The effect of the adults’ education at community level was
not linear. Additional analysis shows that the diarrhoea risk increased with increasing adult’s
education in the community, but after 9.2 years of education the diarrhoea risk decreased
again with increasing adult’s education.
   Interaction Effects: We studied interactions between the five main variables (piped water
in the dwelling, water treatment, improved toilet, improved water coverage, environmental
hygiene) and all household and contextual variables. All interactions were iteratively tested,

                                               6

but only significant interaction effects were included in the model (see Model 2, Table 3).
Apart from negligible changes in the value of the coefficients, the main/direct effects were not
substantially different between the multivariate and the interaction model. Except for
environmental hygiene and mother decision power, all variables that were significant in the
multivariate model remain significant in the interaction model with no changes in
coefficients’ sign indicating the robustness of the direct effect of household and community
level variables. Eleven interactions were found significant.
   Living in a community with good health facilities coverage and with more educated adults
strengthened the positive effect of piped water (OR=0.71, 95% CI 0.59 to 0.84 and OR=0.83,
95% CI 0.69 to 0.99, respectively). Living in an urban area or in a community with higher
vaccination coverage, weakened the piped water effect. Improved sanitation was helpful in
reducing diarrhoea risk particularly for older children (OR=0.92, 95% CI 0.88 to 0.97) and in
situations with lower levels of maternal decision power (OR=1.10, 95% CI 1.01 to 1.21).
   The effect of improved water coverage on reducing the risk of diarrhoea diminished when
the children have access to an improved toilet in the household (OR=1.10, 95% CI 1.01 to
1.21) and when the level of development of the area is higher (more cars; OR=1.13, 95% CI
1.06 to 1.20), thus indicating that an improved water coverage in the area may partly
compensate the lack of good toilet facilities and a low level of development of the area.
   Meanwhile, improved water coverage and environmental hygiene in the community
strengthen each other in reducing the diarrhoea risk (OR=0.92, 95% CI 0.87 to 0.98). Finally
we see that better environmental hygiene has a larger influence on reducing the diarrhoea risk
for the wealthier household (OR=0.92, 95% CI 0.88 to 0.97) and in communities with lower
levels of adult education (OR=1.11, 95% CI 1.01 to 1.22). None of the interaction effects with
point-of-use water treatment was significant.

Discussion
   The current study found that, except the point-of-use water treatment, all of the variables
were individually associated with diarrhoea incidence among infants. Although several
variables lost their significance in the multilevel analysis, findings make clear that the
probability of children having diarrhoea depends not only on household characteristics, but
also on characteristics of the community in which the child resides.
   Our analysis shows that the presence of piped water on the premises had the biggest effect
on preventing diarrhoea among children under five. This effect was stronger in communities
with better health facilities and a more highly educated adult population. However, the

                                                7

coverage of improved water at community level did not help much in preventing diarrhoea.
This indicates that the transport of water from a village water point to the home increases the
contamination risk. These findings not only highlight the importance of safe water, but also
make clear that it should be provided primarily at the household level.
   Interestingly, point-of-use water treatment had neither a direct nor an indirect (interaction)
effect on diarrhoea incidence. This might indicate that the water treatment was conducted
inappropriately. The contamination of the water could occur both during the water treatment
and or during the storage of the water after treatment.19
   Quality of the inhouse toilet facility had no direct effect on diarrhoea risk, but was found to
be important under specific circumstances; for older children and children living in
communities with low maternal decision power, the presence of an improved toilet in the
home reduces the risk of diarrhoea. Environmental hygiene, as measured by the sanitation
level in the community, was found to help reduce diarrhoea in wealthy households and in
communities with lower educational levels. The effect of environmental hygiene is
strengthened in communities with improved water coverage, which indicates that
improvement of water and sanitation should go hand in hand to get the strongest positive
effect.
   Some interaction effects had an unexpected sign. Our interpretation of these coefficients is
that the role for water and sanitation facilities in reducing diarrhoea incidence is less in better
circumstances such as in urban area, higher vaccination coverage, developed region, and
higher mother’s decision power.
   A limitation of this study is the use of a cross sectional design, which limits the
possibilities to determine causal relationship. Second, the incidence of diarrhoea was based on
mother’s self-reports, which are potentially biased by problems of recall. Also the information
on water treatment was self-reported and did not capture the exact process and the resulting
quality of the water being consumed.

Conclusion
   Diarrhoea is important health issue in Indonesia. Clean water and sanitation are supposed
to be important factors in preventing diarrhoea, but the mechanisms are not yet conclusively
identified. The importance of the context factors water supply and environmental hygiene for
diarrhoea prevention has been acknowledged, but has got little attention in research focussing
on Indonesia.

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Preventing diarrhoea among young children in Indonesia requires an integrated approach
in which water and sanitation facilities at household and community level are improved
simultaneously. A critical finding is that treating water before its consumption does not
significantly reduce diarrhoea risk. Hence the public should be warned that for getting a false
feeling of security.
   Access to piped water on the premises is strongly associated with lower diarrhoea
incidence among children under five in Indonesia. The availability of improved water at the
community level only helps to reduce diarrhoea risk under specific circumstances (in poor
communities, for households without improved toilet facilities and if also the environmental
hygiene level is higher). Hence, for an optimal effect, the provision of clean drinking water
should go hand in hand with the improvement of sanitation at both household and community
level.
   This study reconfirms findings of earlier research5 that water treatment is not effective in
reducing diarrhoea risk. It is therefore important that households are warned not to rely on
their current treatment practices and that further research is done on what exactly goes wrong
in the treatment process. More generally, we can conclude that to reduce the incidence of
diarrhoea in Indonesia and most likely also in comparable countries, both household and
context factors should be considered and that the effects of these factors depends on the
specific situation at household and community level. Reducing diarrhoea risk thus calls for an
integrated approach in which improvement of water and sanitation facilities at household and
community level goes hand in hand with improvement of economic and gender related factors
at these levels.

                                                9

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10. Keusch GT, Fontaine O, Bhargava A, et al. Diarrheal Diseases. In: DT J, JG B, AR M, Al.
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Hyg 2011;84(3):443-50.

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Table 1 Descriptive characteristics of under five years old children in Indonesia, Demographic and
Health Survey, 2007 and 2012

                                                                   All sample
Variables
                                                                   n                   %
  Total                                                            33,399              100.00
Diarrhoea
    No (Ref)                                                       28,579              85.57
    Yes                                                            4,820               14.43
Household factors
  Piped water in the dwelling
    No (Ref)                                                       28,997              86.82
    Yes                                                            4,402               13.18
  Point-of-use water treatment
    No (Ref)                                                       7,038               21.07
    Yes                                                            26,361              78.93
  Improved toilet
    No (Ref)                                                       13,919              41.67
    Yes                                                            19,480              58.33
  Gender
    Boy (Ref)                                                      17,389              52.06
    Girl                                                           16,010              47.94
  Child age
    Mean age (SD/ range)                                           1.98                (1.42/ 0 - 4)
  Mother education
    Mean years of education (SD/ range)                            8.67                (3.85/ 0 - 15)
  Household wealth
    Mean wealth (SD/ range)                                        51.62               (25.94/ 0 - 100)
  Living in urban area
    Rural (Ref)                                                    19,362              57.97
    Urban                                                          14,037              42.03
  Survey year
    2007 (Ref)                                                     16,925              50.68
    2012                                                           16,474              49.32
Context factors
  Mean improved water coverage (SD/ range)                         0.50                (0.29/ 0 - 1)
  Mean environmental hygiene (SD/ range)                           0.59                (0.30/ 0 - 1)
  Mean health facilities coverage (SD/ range)                      0.48                (0.37/ 0 - 1)
  Mean vaccination coverage (SD/ range)                            0.65                (0.24/ 0 - 1)
  Mean car ownership (SD/ range)                                   0.07                (0.10/ 0 - 1)
  Mean adults’ education (SD/ range)                               7.94                (2.25/ 0.26 - 16)
  Mean mother decision power (SD/ range)                           0.82                (0.18/ 0 - 1)
Ref, reference category

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Table 2 Bivariate analysis of the diarrhoea incidence of children aged

Table 3 Multilevel analysis of the diarrhoea incidence of children aged