Using the WHO Health Equity Assessment Toolkit to investigate changes in rural vs urban malnutrition inequality for low- and middle-income countries

Reducing health inequalities is a key element in the World Health Organization’s (WHO) sustainable development goals (SDG). While previous research has analyzed individual childhood malnutrition indicators and inequality by place of residence, there are no studies that have looked over time for rural vs. urban inequalities for all five-childhood malnutrition indicators for low- and middle-income countries (LMIC). The goal of the current study is to provide preliminary results to address this research gap by using a free software developed by WHO, the Health Equity Assessment Toolkit (HEAT). The 52 countries included in this study had at least two Demographics and Health Survey (DHS) datasets, between 1990 and 2021, available through the WHO HEAT. All five childhood malnutrition indicators (overweight, stunting, underweight, wasting, and severe wasting) were evaluated. An increase in inequality was considered to be an increase over time in the difference between the rural prevalence and the urban prevalence of a malnutrition indicator. Out of the 52 countries, 15 (29%) reduced inequality across all five malnutrition indicators, 13 (25%) reduced inequality for 4 indicators, 7 (13%) reduced inequality for 3 indicators, 7 (13%) reduced inequality for 2 indicators, 7 (13%) reduced inequality for one indicator, and 3 (6%) did not reduce inequality for any indicator. The overweight indicator had the most countries (42%) showing an increase in inequality, while the underweight indicator had the fewest countries (19%) showing an increase in inequality. Overall, most LMIC were showing progress towards reducing malnutrition inequality based on place of residence. Results show that malnutrition inequality is generally decreasing for LMIC, with the exception of the overweight indicator. To further understand what is driving the observed inequalities and inform policy changes, future analyses should evaluate possible drivers such as economic transitions, urbanization rates, or health policy changes. WHO HEAT software provides free and easy access to relevant survey data and provides summary statistics and plots that allow the user to understand the data and answer a variety of inequality-related research questions.