Background: Lack of access to water, sanitation and hygiene (WASH) is of great concern
globally as an estimated 748 million people worldwide are without an improved source of
drinking water and 2.5 billion people are without adequate access to improved sanitation. Serious
disparities exist and the unequal distribution has been recognized globally. However, it is
important to further examine the distributions on a national and sub-national scale to understand
disparities in access. In Timor-Leste, the determinants of disparities in access to improved
drinking water and sanitation systems are poorly understood. Therefore, this present study sought
to examine geographical and socioeconomic disparities in access to improved drinking water,
distance to water and sanitation in the country.
Methods: This study analyzed 11,463 households and 13,137 women observations from the
Timor-Leste Demographic and Health Survey (TLDHS) 2009-2010. Analyses were performed
separately for household and individual level. Sampling weights were used to account for
complex sampling of the population of interest. Weighted descriptive statistics were computed to
display the frequency distribution of outcome variables. Weighted bivariate logistic regression
analysis was performed to assess associations between each independent variable (type of
residence, municipalities, region, wealth index, education level and literacy) and each outcome
variable (improved drinking water source, improved sanitation facility and travel times of 30
minutes or less to the water source). Weighted multivariate logistic regression analysis was
performed to examine the associations between independent variables and the outcome variable.
This study also utilized spatial data to map out the distribution of drinking water source,
sanitation type and distance to the water source in 13 municipalities of Timor-Leste.
Results: Significant predictors in weighted multivariate logistic regression analysis included
urban/rural status, region and wealth index for disparities in access to improved drinking water
and only wealth index for disparities in access to improved sanitation. Overall, disparities seem
to be starker for sanitation than they are for water due to larger values of odds ratio for sanitation
outcome, especially when looking across wealth index predictor at both the household and
individual level of analysis.
Conclusion: Policies and programming aiming to address disparities should encompass WASH
interventions with emphasis on a poverty reduction approach by targeting the poorest population.
Future longitudinal model and/or randomized trials are needed to examine the trends and to
enable causal inferences.