# Household water, sanitation, and hygiene practices in Ghana from 1993–2022: a non-linear multivariate Poisson decomposition and traditional predictive modelling approach

## TL;DR

This study tracks WASH improvements in Ghana from 1993 to 2022, finding progress but persistent rural-urban and wealth-based inequalities.

## Contribution

The study introduces a nonlinear multivariate Poisson decomposition to quantify rural-urban WASH disparities and uses predictive modeling to identify key determinants.

## Key findings

- Access to improved water increased from 56.1% in 1993 to 83.9% in 2022, but rural-urban gaps persist.
- Wealth, education, and urban residence strongly predict better WASH access, while larger household size reduces it.
- Predictive models achieved AUC scores of 0.78 for water access and 0.77 for composite WASH.

## Abstract

Access to safe water, sanitation, and hygiene (WASH) remain public health and sustainable development necessities. While Ghana has made notable progress over the past three decades, persistent disparities and structural inequalities limit universal coverage. This study examined long-term trends, determinants, and rural–urban inequalities in household WASH in Ghana from 1993 to 2022 using multivariate decomposition and predictive modelling approaches.

We analysed pooled data from six waves of the Ghana Demographic and Health Survey (GDHS) spanning 1993–2022 (N = 59,597 households). Key outcomes included access to improved water, sanitation, handwashing facilities, time to water source, and a composite WASH index. Weighted descriptive statistics, multivariable Poisson regression, and predictive modelling (AUC-ROC) assessed determinants and predictive performance. Rural–urban inequalities were quantified using a nonlinear multivariate Poisson decomposition.

Access to improved water rose from 56.1% in 1993 to 83.9% in 2022, while improved sanitation increased modestly to 69.1%. Handwashing facilities improved from 39.2% (2014) to 52.0% (2022), and the composite WASH index reached 18.8% in 2022. Wealth, education, female headship, and urban residence were strong predictors of improved WASH, while larger household size and more children under five reduced access. Predictive models showed good performance for improved water (AUC = 0.78) and composite WASH (AUC = 0.77). Decomposition analyses revealed persistent rural–urban gaps of 21.6 percentage points for improved water and 13.4 points for composite WASH, driven largely by wealth, education, and differential returns to socioeconomic resources. Rural households derived fewer benefits from wealth and education compared to their urban counterparts.

Despite significant progress in WASH coverage in Ghana, inequities remain entrenched, particularly for rural and poorer households. Targeted interventions addressing structural inequalities in wealth, education, and infrastructure are essential to accelerate Ghana’s progress toward universal WASH access and Sustainable Development Goal 6.