Anthropometric indicators in traditional peoples and communities in Brazil: analysis of individual records from the Food and Nutrition Surveillance System, 2019

Indicadores antropométricos en pueblos y comunidades tradicionales en Brasil: análisis de registros individuales del Sistema de Vigilancia Alimentaria y Nutricional, 2019

Abstract

Objective:  To describe the prevalence of underweight and obesity indicators among individuals registered as traditional peoples and communities in the Food and Nutrition Surveillance System, across Brazil, in 2019.

Methods:  This was a descriptive study using individual secondary data from participants receiving care in the Primary Health Care within the Brazilian National Health System.

Results:  In the study population (N = 13,944), there was a higher prevalence of short stature among male children and adolescents (14.2%), when compared to their female counterparts (11.8%); in the adult female population, there was a higher prevalence of obesity (23.0%), when compared to the male population (11.3%); the prevalence of low height-for-age in riverine communities (18.5%) and obesity in the adult faxinalense population (75.1%) stood out.

Conclusion:  Anthropometric disparities between different communities require tailored responses, emphasizing targeted primary health care and programs to ensure food and nutrition security.

Keywords:
Nutritional Epidemiology; Primary Health Care; Health Information Systems; Quilombolas; Roma (Ethnic Group); Descriptive Studies

Study contributions

Main results  It was possible to identify a higher prevalence of low weight and height-for-age in the child population of riverine communities, while faxinalense communities showed a higher prevalence of obesity in adults.

Implications for services  Continuous improvement in the implementation of SISVAN protocols is recommended, as well as strengthening the assistance provided to communities with the worst indicators.

Perspectives  Studies assessing the potential impact of interventions to mitigate the effects of malnutrition in communities, through in-depth qualitative research or probabilistic quantitative studies using primary data.