The Prevalence of Underweight, Overweight/Obesity and Their Related Lifestyle Factors in Indonesia, 2014–15

<strong>Objective:</strong> To quantify the prevalence of&nbsp;underweight and overweight or obesity&nbsp;and&nbsp;its related factors (socio-demographic, health behavior, health status) in a national adult population in Indonesia. <strong>Material and Methods</strong>: In a national cross-sectional population-based survey in 2014–15 in Indonesia, 29509 adults (median age 41.0 years, Inter Quartile Range=22.0, age range of 18–103 years) completed questionnaires and anthropometric measurements. Multinomial logistic regression modelling was used to determine the association between socio-demographic, health behavior and health status factors and underweight and overweight or obesity. <strong>Results</strong>: Of total sample (n = 29509), 11.2% measured underweight (13.5% among men and 9.1% among women) (&lt;18.5 kg/m²), 39.8% normal weight (48.1% among men and 32.0% among women) and 49.0% had overweight or obesity (≥23 kg/m²) (38.3% among men and 58.9% among women); 24.6% of the overall sample had class I obesity (25–29.9 kg/m²), and 8.5% had class II obesity (30 or more kg/m²). Among different age groups, underweight was the highest among 18–29 year-olds (20.0%) and those 70 years and older (29.8%), while overweight or obesity was the highest in the age group 30 to 59 years (more than 53%). In adjusted multinomial logistic regression, having less education, living in rural areas and not having chronic conditions were associated with underweight status. While better education, higher economic status, urban residency, dietary behavior (infrequent meals, frequent meat, fried snacks and fast food consumption), physical inactivity, not using tobacco, having chronic conditions (diabetes, hypertension, hypercholesterol), and better perceived health and happiness status were associated with overweight or obesity. <strong>Conclusions:</strong> A dual burden of both adult underweight and having overweight or obesity was found in Indonesia. Sociodemographic, health risk behavior and health status risk factors were identified, which can guide public health interventions to address both these conditions