Obesity Kuznets Curve in Africa: Economic Growth, Urbanization, Trade, and Gender-Based Health Insights (2000–2020)

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A recent study by Wang et al. (2025) titled “Obesity Kuznets Curve conjecture assessment in African economies: conditioning effects of urbanization, food, and trade using gender-based regional analysis” published in Globalization and Health by Springer Nature reveals that Africa currently faces a double burden of malnutrition, rising obesity alongside persistent undernutrition.

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Africa’s obesity trends follow a region- and gender-specific Kuznets Curve, requiring tailored policies addressing malnutrition.– Wang et al. 2025

The study explores the intricate link between economic growth and obesity prevalence across 46 African countries from 2000 to 2020. It examines the Obesity Kuznets Curve (OKC) hypothesis, which proposes a non-linear, inverted U-shaped relationship between income levels and obesity rates. In essence, obesity tends to rise in the early stages of economic growth but may decline after a certain income threshold, as populations adopt healthier lifestyles. Africa currently faces a double burden of malnutrition—rising obesity alongside persistent undernutrition—making this research particularly significant. The study focuses exclusively on African economies, breaks down findings by region (Eastern, Western, Central, and Southern Africa), and investigates gender-specific trends in obesity among males, females, and both sexes combined.

How the Study was Conducted

The study employed a rigorous, multi-layered econometric framework to investigate the Obesity Kuznets Curve (OKC) hypothesis across 46 African countries over a 20-year period (2000–2020). Using quantitative panel data analysis, the researchers examined obesity prevalence in Eastern, Western, Central, and Southern Africa, disaggregating results by gender (males, females, and both sexes) to capture nuanced differences often hidden in aggregate data.

The analysis drew on data from the WHO Global Health Observatory and the World Bank Development Indicators. The response variables were obesity prevalence for both sexes (OBB), males (OBM), and females (OBF), all measured for individuals aged 18 and above. Key explanatory variables included economic growth (per capita GDP in constant 2015 USD), urbanization (total urban population), trade openness (percentage of GDP from imports and exports), and the food production index (base year 2014–2016 = 100).

Methodologically, the study progressed through a series of rigorous steps. First, cross-sectional dependence was tested using Pesaran’s PCD, CDw, and CDw+ tests to detect interdependencies among countries. Unit root tests (PMSB, CADF, and CIPS) confirmed the stationarity of variables, followed by cointegration analysis using Westerlund-Edgerton and Durbin-Hausman tests, which established the existence of long-run relationships. The Pesaran-Yamagata slope homogeneity test further revealed variations in the effects of explanatory variables across different countries.

For model estimation, the authors applied the Bias-Corrected Method of Moments (BCMM) estimator within a dynamic fixed-effect panel model. This advanced approach accounted for unobserved heterogeneity, cross-sectional dependence, and the lagged effects of obesity prevalence, making it well-suited for complex, multi-country datasets. Robustness was ensured through Arellano-Bond autocorrelation tests (AR[2]), F-statistics for model fit, white noise residual tests, and alternative GMM estimations.

This methodological design was not only statistically rigorous but strategically insightful. By combining macroeconomic and structural variables with gender- and region-specific analyses, the study illuminated patterns that would have been obscured in a continent-wide average, offering a deeper understanding of the economic and structural drivers of obesity in Africa.

What the Authors Found

The authors found that the Obesity Kuznets Curve holds true for Western, Central, and Southern Africa but not Eastern Africa, with strong regional and gender differences in how economic growth, urbanization, trade, and food production influence obesity trends.

Why is this important

Addressing Africa’s Double Burden of Malnutrition: The study highlights the coexistence of undernutrition and rising obesity, urging balanced interventions that tackle both without worsening either problem.

Economic Growth Does Not Guarantee Better Health: Findings challenge the assumption that higher incomes automatically improve health, showing that economic growth can initially fuel obesity without proper policy safeguards.

Gender-Sensitive Health Strategies Are Essential: Women face disproportionately higher obesity rates, underscoring the need for tailored nutrition programs, targeted health campaigns, and cultural- and economic-sensitive support systems.

Urbanization and Trade as Double-Edged Swords: While boosting economies, these factors also drive obesity by increasing access to unhealthy foods, reducing physical activity, and deepening dependence on ultra-processed imports.

Supporting Global Nutrition and Health Goals: The research provides region-specific insights that advance SDG 2 (Zero Hunger) and SDG 3 (Good Health and Well-being), making global targets more actionable in African contexts.

A Toolkit for Evidence-Based Policy Making: Governments, NGOs, and health agencies can apply these findings to design targeted interventions, allocate resources efficiently, and monitor progress using robust data benchmarks.

What the Authors Recommended

The authors of the study propose a comprehensive set of policy recommendations tailored to Africa’s unique developmental and public health landscape. Their goal is to curb the rising tide of obesity while addressing the continent’s double burden of malnutrition.

• Promote Affordable, Healthy Diets: Subsidize nutritious foods, tax ultra-processed and sugary products, and support local farmers to increase access to fresh, nutrient-rich produce.
• Regulate Unhealthy Food Imports: Align trade policies with public health goals by controlling the influx of processed, calorie-dense foods—especially under agreements like AfCFTA.
• Design Cities for Active Living: Incorporate pedestrian-friendly infrastructure, green spaces, and recreational facilities into urban planning to encourage active commuting and reduce sedentary lifestyles.
• Implement Gender-Sensitive Health Programs: Create tailored interventions that reflect regional and gender-specific obesity patterns, address cultural norms, and provide community-based fitness and support networks.
• Adopt Region-Specific Strategies: Tackle early-stage obesity risks in Western, Central, and Southern Africa while simultaneously addressing undernutrition and obesity in Eastern Africa.
• Boost Public Awareness and Nutrition Literacy: Run education campaigns highlighting the dangers of processed foods, promote traditional diets, and encourage healthier eating habits.
• Transform Food Production Systems: Incentivize diverse, nutrient-rich crop cultivation, preserve traditional agricultural practices, and curb gender-targeted marketing of unhealthy foods.

In conclusion, Wang et al. (2025) provide compelling evidence that Africa’s obesity trends are shaped by complex interactions between economic growth, urbanization, trade, and gender-specific factors. Their study demonstrates that the Obesity Kuznets Curve is regionally and gender-sensitive, highlighting the need for tailored, evidence-based policies that address both undernutrition and rising obesity. By emphasizing affordable healthy diets, urban planning, trade regulation, and culturally informed health programs, the research offers actionable strategies to curb the double burden of malnutrition and advance sustainable health outcomes across the continent.