Not all women are equally at risk: A Demographic health survey (DHS) 2023 based analysis of overweight and obesity inequalities among women in the Democratic Republic of the Congo

Background In sub-Saharan Africa, women are navigating overlapping burdens of undernutrition and rising overweight/obesity, often within fragile health system and rapidly changing food environments. In the DRC, theses tensions may be intensified by rapid urbanization, socioeconomic disparities, insecurity and shifting lifestyles. Despite those changes, national level evidence on who is the most affected by excess weight and why remains scarce. This study assessed the determinant of overweight and obesity among Congolese women of reproductive age, aiming to highlight the social and geographic inequalities. Methods We analysed nationally representative data from the 2023 DHS. The analysis included 10,740 non-pregnant women aged 15-49 years with valid anthropometric measurements. Overweight/obesity was defined as BMI [&ge;] 25 Kg/m2. We examined a broad range of potential associated factors, including province, residence, socioeconomic status, household structure, education level, marital status, occupation, dietary diversity score, healthy diet related indicators, media exposure, internet use and health service utilisation. Weighted analyses accounted for the DHS sampling design. Variables associated at p value < 0.20 were retained for multivariable modelling. Multicollinearity was assed via adjusted GVIFs. Four hierarchical weighted logistic regression were built; the fully adjusted model guided final interpretation. Results Nearly on five women of reproductive age (19.5%) lived overweight or obesity. However, this burden was not evenly distributed. Women from Kongo Central and Tshuapa exhibited significantly lower odds, while those in Bas-Uele, Nord-Kivu, Sud-Kivu and Maniema were substantially more affected, highlighting spatial inequities. Women living in rural areas had lower odds of overweight/obesity compared with their urban counterparts (aOR=0.6; 95% CI: 0.48-0.79; p<0.001). A pronounced socioecomic gradient was observed. Compared with the poorest households, the likelihood of excess weight increases progressively among women in middle income household (aOR=1.65;95% CI:1.13-2.41), rich households (aOR=2.41; 95%CI:1.62-3.60), and was highest among the richest (aOR=4.19; 95%CI: 2.45-7.16). Larger households appeared protective, with lower odds observed in household of 4-5 members (aOR=0.68; 95%CI:0.5-0.92), 6-7 (aOR=0.72;95% CI: 0.54-0.97) and [&ge;]8 members (aOR=0.69; 95%CI:0.50-0.95) compared with smaller household. Age was the strongest predictor, with risk sharply accelerating after 30 years. Being married or in union was associated with higher odds. Notably, frequent internet use independently predicted overweight/obesity. In contrast, dietary diversity and unhealthy food indicators were not significantly significant in the fully adjusted models. Conclusion Overweight and obesity are rising among Congolese women, but unevenly and unjustly. Urban residence, socioeconomic status, age and digital exposure strongly sharply shape who is the most affected, revealing deep social and geographic inequities. Addressing this growing epidemic requires equity-oriented, province specific actions, alongside stronger primary prevention. Key-word: Overweight-obesity-associated factors, DRCongo, DHS