Abstract
BACKGROUND: In recent years, obesity has transitioned from being an individual health issue to a chronic public health problem that has reached alarming levels worldwide, contributing to numerous fatal diseases. Using the G7 panel over the period 1990-2021, this article estimates the links between economic, environmental, social and dietary behaviors on obesity. In particular, the role of Load Capacity Factor (LCF) as a proxy for environmental quality in the evolution of obesity has not yet been empirically explored. This is also a crucial article in terms of evaluating the linear and non-linear effects of economics on obesity. METHODS: The multiple model of obesity, which incorporates income, environmental quality, unemployment and dietary risk variables, is tested using the Method of Moments Quantile Regression (MMQR). To address the robustness of dietary risk measures, the aggregate dietary risk variable is further disaggregated into "low consumption of protective foods" and "high consumption of unhealthy foods". RESULTS: The baseline findings indicate significant coefficients for all variables across all quantiles. For the G7 panel, both income and the square of income exhibit positive and significant effects on obesity. This implies a continuously increasing relationship between income and obesity, rather than indicating a turning point where obesity decreases after a certain income level. Therefore, the results do not support the classical Obesity Kuznets Curve (OKC) hypothesis, which assumes an inverted U-shaped relationship between income and obesity. In terms of environmental quality, it has been determined that increasing LCF triggers obesity. The rise of unemployment, which is a social determinant, also contributes to the escalation of obesity. While the aggregate dietary risk indicator initially produced negative coefficients, further disaggregation clarified the underlying dynamics. Low consumption of protective foods significantly increases obesity in the upper quantiles, whereas high consumption of unhealthy foods exerts a consistently positive and significant effect across the entire distribution. This highlights the necessity of distinguishing dietary risk dimensions in order to capture their true impact on obesity. Moreover, similar to the aggregate specification, the disaggregated dietary risk specifications for the G7 panel provide clear evidence against the inverted U-shaped relationship form, as no turning point is observed. Notably, increases in environmental quality and unemployment also elevate obesity, and this pattern remains consistent across all specifications. CONCLUSION: The article offers recommendations for G7 governments to prioritize health policies alongside economic and environmental strategies, and underscores the importance of public policies aimed at reducing unemployment. Furthermore, the clarification of dietary risk effects suggests that nutritional interventions should simultaneously encourage protective food consumption and limit unhealthy dietary patterns. Therefore, the current article guides policymakers in exploring the economic, environmental and social determinants of obesity.