Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Sociobehavioral, Biological and Health Characteristics of Riverside People in the Xingu Region, Pará, Brazil

Version 1 : Received: 12 January 2023 / Approved: 17 January 2023 / Online: 17 January 2023 (01:52:29 CET)

A peer-reviewed article of this Preprint also exists.

Lucianelli Junior, D.; Pereira, A.L.; Santos, O.S.; Paes, M.C.F.; Ikuta, Y.M.; Silveira, R.; Valentin, F.N. Sociobehavioral, Biological, and Health Characteristics of Riverside People in the Xingu Region, Pará, Brazil. Int. J. Environ. Res. Public Health 2023, 20, 5542. Lucianelli Junior, D.; Pereira, A.L.; Santos, O.S.; Paes, M.C.F.; Ikuta, Y.M.; Silveira, R.; Valentin, F.N. Sociobehavioral, Biological, and Health Characteristics of Riverside People in the Xingu Region, Pará, Brazil. Int. J. Environ. Res. Public Health 2023, 20, 5542.

Abstract

Aim: This study aimed to evaluate the sociodemographic, behavioral, and biological profile and its relationship with the emergence of chronic non-communicable diseases in riverside populations in the Xingu region, Pará, Brazil. Methods: Characteristics related to health indicators and which risk factors are considered most important were also analyzed. This is a cross-sectional, exploratory, and descriptive study. The sample consisted of riverside people over 18 years of both sexes. The sample size (n.86) was calculated with a confidence level of 95% and a sample error of 5%. To divide the groups, the K-means clustering algorithm was adopted through an unsupervised method and the values were expressed as median. For continuous and categorical data, the Mann-Whitney and Chi-square tests were used, respectively, and the significance level was set at p<5%. To classify the degree of importance of each variable, the multi-layer perceptron algorithm was applied. Results: Based on this information, the sample was divided into two groups: the group with low or no education, with bad habits and worse health conditions, and the group with opposite characteristics. The risk factors considered for cardiovascular diseases and diabetes in the groups were low education (p < 0.001), sedentary lifestyle (p < 0.01), smoking, alcoholism, body mass index (p < 0.05) and the waist-hip ratio, with values above the expected, in both groups. Conclusions: The factors considered important to have a good health condition or not were the educational and social conditions of these communities and a part of the riverside population was considered healthier than the other.

Keywords

education level; eating behavior; healthy lifestyle habits; non-communicable chronic diseases; machine learning

Subject

Public Health and Healthcare, Public Health and Health Services

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