Tipping the Scales: Population Estimates and Risk Factors for Severe Thinness, Thinness, Overweight and Obesity Among Pregnant Women and Mothers in India

Abstract

Abstract Objectives Thinness and overweight/obesity are prevalent among women of reproductive age in India but there is limited evidence on the burden and predictors of this during pregnancy and post-partum. We estimated prevalence and risk factors for thinness and overweight among pregnant and recently delivered women (RDW). Methods We used India's National Family Health Survey (2015–2016), including 16,153 pregnant women <20 weeks of gestation and 19,430 RDW of 2–6-month-old infants. All women were classified as severe thin (ST), thin (TH), overweight (OV) or obese (OB) (body mass index, BMI <16, <18.5, ≥23 and ≥25 kg/m2, respectively), using cutoffs for Asian populations. Logistic regression was used to examine associated factors (including socio-demography, hygiene and sanitation, antenatal health services and diet) with those outcomes. Results Barely 40% of women were of normal BMI. ST, TH, OV/OB and OB were seen in 2%, 20%, 25% and 13% respectively among pregnant women, and for RDW, they were 2%, 21%, 24% and 13%. Factors associated with a lower odds of ST and TH among pregnant women and RDW included higher wealth quintile (adjusted odds ratios, AORs ranging from 0.58–0.63 for highest quintile), higher education (AORs: 0.64–0.81), age group ≥25 y (AORs: 0.58–0.83), and improved toilet facility (AOR 0.81). Multiparous pregnant women had higher odds of TH compared to primiparas (AORs: 1.24–1.31). Factors associated with OV and OB among pregnant women and RDW were belonging in higher socio-economic group (AORs: 1.34–1.53), higher wealth quintile (AORs: 1.56–8.49), age group ≥25 y (AORs: 2.73–5.09), urban residence (AOR 1.16–1.36), and having higher education (AORs: 1.44–1.60). Among RDW, receiving supplementary food and health and nutrition education increased odds of TH (AORs: 1.15) and reduced odds of OV and OB (AORs: 0.83–0.87), but this is likely attributable to selection bias in program use. Conclusions TN and OV/OB affect 1 in 5 pregnant women and 1 in 4 RDW in India. Socio-economic factors, sanitation, parity, education and age influence TN and OV/OB. Better diet and physical activity estimates are needed to understand OV and OB in this population. Given the high burden of both forms of malnutrition, a policy focus on healthy weight gain is essential. Funding Sources UNICEF; Bill & Melinda Gates Foundation (via POSHAN).