Objetivos. Describir el estado nutricional en adultos mayores y su asociación con características sociodemográficas. Materiales y métodos. Se realizó un estudio transversal analítico. El muestreo. fue probabilístico, estratificado y multietápico. El estado nutricional se evalúo mediante el índice de masa corporal (IMC) según la clasificación del estado nutricional para el adulto mayor del Ministerio de Salud de Perú. El análisis estadístico consideró la ponderación necesaria para muestras complejas. Resultados. Se incluyó a 7267 adultos mayores con una media de edad de 70,1 ± 8,3 años. El 26,8% presentaron delgadez, 21,7% sobrepeso y 10,6% obesidad. El analfabetismo (OR 1,9; IC 95%: 1,2-3,0), nivel educativo primario (OR 1,9; IC 95%:1,3-2,9), pobreza extrema (OR 2,0; IC 95%:1,6-2,5), residir en área rural (OR 1,8; IC 95%:1,5-2,1), sierra (OR 1,6; IC 95%: 1,2-2,2) o selva (OR 1,6; IC 95%:1,1-2,2) fueron factores asociados a delgadez. El sexo femenino (OR 1,8; IC 95%:1,4-2,1), residir en área urbana (OR 2,0; IC 95%: 1,6-2,5) o costa (OR 1,5; IC 95%:1,2-1,8); y ser no pobre (OR 1,9; IC 95%: 1,3-2,9) se asoció a sobrepeso. El sexo femenino (OR 3,1; IC 95%: 2,3-4,1), nivel educativo primario (OR 2,4; IC 95%: 1,5-4,0) y secundario (OR 2,0; IC 95%: 1,2-3,4); vivir en área urbana (OR 2,2; IC 95%:1,6-2,9), la costa (OR 1,8; IC 95%: 1,3-2,4), Lima Metropolitana (OR 1,6; IC 95%:1,1-2,2) selva (OR 1,6; IC 95%: 1,1-2,2), y ser no pobre (OR 3,5; IC 95%:1,8-7,0) estuvieron asociados a obesidad. Conclusiones. Los datos sugieren que tanto la delgadez como el exceso de peso son frecuentes en la población de adultos mayores estudiada.

Objectives. To describe the nutritional status in older adults and its association with sociodemographic characteristics. Materials and methods. A cross-sectional study was conducted. Sampling was probabilistic, stratifi and multistage. Nutritional status was assessed by body mass index (BMI) according to the classifi of nutritional status for the elderly from the Ministry of Health of Peru. The statistical analysis considered the necessary weight for complex samples. Results. The study included 7,267 older adults. 26.8% of participants were underweight, 21.7% overweight, 10.6% obese and 40.8% normal. The average age in the sample was 70.1 ± 8.3 years. Illiteracy (OR 1.9; 95% CI 1.2-3.0), primary education (OR 1.9; 95% CI 1.3-2.9), extreme poverty (OR 2.0; 95% CI 1.6-2.5), living in rural areas (OR 1.8; 95% CI 1.5-2.1), living in the mountains (OR 1.6; 95% CI 1.2-2.2) or jungle (OR 1.6; 95% CI 1.1-2.2) were found associated with underweight. Females (OR 1.8; 95% CI 1.4-2.1), living in urban areas (OR 2.0; 95% CI 1.6-2.5), living in the coastal region (OR 1.5; 95% CI 1.2- 1.8); and not classifi as poor (OR 1.9; 95% CI 1.3-2.9) were associated with overweight. Female sex (OR 3.1; 95% CI 2.3-4.1), primary education (OR 2.4; 95% CI 1.5-4.0) and secondary (OR 2.0; 95% CI 1.2-3.4); live in urban areas (OR 2.2; 95% CI 1.6-2.9), inhabiting the coast (OR 1.8; 95% CI 1.3-2.4), Metro (OR 1.6, 95% CI 1.1-2.2) and jungle (OR 1.6; 95% CI 1.1-2.2), and not classifi as poor (OR 3.5; 95% CI 1.8-7.0) were associated with obesity. Conclusions. The data suggest that both underweight and overweight are common in the elderly population studied.