Abstract
BACKGROUND: Maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) are important determinants of maternal and neonatal health. While there is a link between maternal weight and pregnancy complications, evidence in multiethnic regions with diverse lifestyles and socioeconomic backgrounds is scarce. Yunnan Province, located in southwest china, is a multiethnic region with significant geographic and cultural diversity, providing a unique setting to examine these associations in underrepresented populations. This study examines the impact of pre-pregnancy BMI and GWG on pregnancy outcomes within Yunnan's diverse cohorts, with the aim of addressing localised knowledge gaps and informing the development of targeted antenatal care strategies. METHODS: A retrospective cohort study was conducted using data from 13,221 pregnant women from 25 ethnic groups in Yunnan Province between 2019 and 2023. Prepregnancy BMI was classified according to Chinese standards (underweight: <18.5 kg/m²; normal: 18.5-23.9 kg/m²; overweight: 24.0-27.9 kg/m²; obese: ≥28.0 kg/m²). GWG adequacy was assessed against Institute of Medicine guidelines. Prenatal records, delivery modes, and neonatal outcomes were extracted from provincial maternal health databases. Chi-square tests and multivariate logistic regression analyses were used to identify risk factors. Structural equation modelling (SEM) was employed to quantify the direct and indirect effects to prepregnancy BMI and GWG on outcomes such as birth weight and preterm birth. RESULTS: The cohort included 13,221 women with an average age of 20.01 years and an average BMI of prepregnancy of 22.26 kg/m2[standard deviation (SD)3.70] . Nutritional profiles varied: 11.9% were underweight (compared to a national average of 8.2%), and 51.5% had abnormal GWG (20.0% insufficient and 31.5% excessive). Compared to normal weight women, underweight women were at an increased risks of cesarean delivery (OR 1.43, 95% CI 1.26-1.63), postpartum haemorrhage (OR 1.35, 95% CI 1.10-1.67), low birth weight (OR 4.71, 95% CI: 2.53-8.77), and gestational diabetes (OR 3.58, 95% CI: 1.57-8.17). SEM analysis indicated that prepregnancy BMI directly predicted birth weight (β=0.036, p<0.001), while GWG moderated the overall effect of BMI on premature birth (indirect effect 0.18, p<0.01) but not on birth weight (p=0.89). CONCLUSION: Low prepregnancy weight has been found to be associated with adverse pregnancy outcomes, such as caesarean section, low birth weight and premature delivery. Our findings suggest that prepregnancy BMI influences outcome via dual-pathway effects: it directly influences birth weight and indirectly modulation preterm risk through gestational diabetes. Those findings emphasise the importance of ethnicity-specific GWG monitoring and targeted antenatal care strategies.