Multidimensional dataset for the analysis of body composition in the Colombian adult population.
Description
This dataset was developed to analyze regional differences in body composition among adults living in the metropolitan area of Medellín, Colombia. The research hypothesis proposes that variations in biological and demographic characteristics across populations can influence the electrical and anthropometric parameters used to estimate body composition. By providing a multidimensional dataset that integrates electrical, anthropometric, metabolic, and demographic information, this resource enables the study of how these variables interact within a specific Latin American context. The dataset includes 546 measurements from 204 adult participants (127 men and 77 women) aged 18 to 81 years, all of whom reported good health and no functional limitations. Data collection followed standardized procedures to ensure quality and reproducibility. Participants fasted for at least four hours, avoided alcohol, caffeine, and diuretics before the test, and rested in a supine position prior to measurement. Body composition was assessed using an eight-electrode multifrequency bioimpedance analyzer (seca mBCA 525, 1–500 kHz). Anthropometric measurements, including weight, height, and waist circumference, were obtained using a Detecto mechanical scale with stadiometer and a Seca 201 measuring tape. The dataset is organized into four interrelated tables contained in a single Excel file: User: demographic and contextual variables. Anthropometric: body measurements, indices (BMI, FFMI, FMI), Z-scores, percentiles, and derived mass components (fat, fat-free, skeletal muscle, water, and visceral adipose tissue). Electric: multifrequency resistance and reactance by body segment (arms, legs, trunk) and related vectorial parameters, including phase angle. Metabolic: estimated energy expenditure and total body energy content. Each participant has a unique identifier linking multiple measurements over time, allowing longitudinal or cross-sectional analyses. Preliminary inspection of the data shows consistent differences in electrical parameters and body composition between sex and age groups, as well as variation in water distribution and body mass components across individuals. This dataset can be interpreted as a detailed representation of the physiological, electrical, and metabolic characteristics of Colombian adults. It may be reused for regional and comparative studies, development of new equations for body composition estimation, or for educational and methodological purposes in health and sports sciences.
Files
Steps to reproduce
Data were collected from adults residing in the metropolitan area of Medellín, Colombia, following a standardized and reproducible protocol. Participants were required to be over 18 years old, in good self-reported health, and without mobility limitations. Individuals with amputations, metallic implants, pregnancy, electronic devices, or deep skin lesions in electrode contact areas were excluded. Prior to each assessment, participants were instructed to fast for at least four hours, avoid alcohol for 48 hours, refrain from caffeine and physical activity within 12 hours, and not take diuretics during the previous seven days. All measurements were performed with participants in a resting state after 5–10 minutes in a supine position to ensure fluid redistribution and minimize variability. Anthropometric data (weight, height, and waist circumference) were measured using a Detecto mechanical scale with stadiometer and a Seca 201 tape, following World Health Organization (WHO) recommendations. Body composition was assessed by multifrequency bioimpedance analysis using a seca mBCA 525 analyzer (seca GmbH, Germany). The device employs eight adhesive, disposable PVC-free electrodes. Each measurement lasted approximately 30 seconds, and data were automatically stored by the device software. The resulting dataset was organized into four relational tables—User, Anthropometric, Electric, and Metabolic—linked by a unique participant identifier. Data cleaning and integration were performed in Microsoft Excel without modification of the original measurements. This workflow ensures that the dataset can be easily reproduced by applying the same measurement protocol, equipment, and data organization structure in similar population setting
Institutions
- Instituto Tecnologico Metropolitano