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Combined effect of physical inactivity and obesity on health expenditures of adults assisted by primary care

Grant number: 20/01464-4
Support type:Scholarships abroad - Research
Effective date (Start): July 04, 2022
Effective date (End): February 03, 2023
Field of knowledge:Health Sciences - Physical Education
Principal researcher:Jamile Sanches Codogno
Grantee:Jamile Sanches Codogno
Host: Wendy Joan Brown
Home Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
Research place: University of Queensland, Brisbane (UQ), Australia  

Abstract

The increase in the prevalence of obesity and chronic diseases is a constant source of concern for national health budgets worldwide, especially in countries that manage national health services, such as Australia, Canada, the United Kingdom and Brazil. Considering that obesity and physical inactivity could contribute negatively to health spending, the objective of the present study will be to analyze the combined effect of physical inactivity and obesity on health spending in primary care of SUS patients, as well as, see if this model replicates in data from the Australian population. For this purpose, cohort data from the city of Bauru that followed primary care patients (n = 963) for eight years will be analyzed. Health expenditures were analyzed by reading medical records. To assess the level of physical activity, the Baecke questionnaire was applied. Obesity was assessed using the Body Mass Index. The following confounding variables were included in the study: sex, age, occurrence of diseases, economic condition, smoking and alcohol consumption. In addition, throughout the development of the BPE, the necessary measures will be taken to access the Australian database. Statistical analysis will be used in order to describe the data, compare them over time and create the Brazilian models that will be compared with the Australian data. In terms of data description, descriptive statistics will consist of values of mean, median, standard deviation, interquartile range (DQ) and 95% confidence intervals (95% CI). For categorical data, relative frequencies and their respective 95% CI will be used. Comparisons over time will be performed using analysis of variance (ANOVA) for repeated measures. The fit of the models will be tested using the Mauckley sphericity test. Effect-size measurements will be expressed as eta-squared (ES-r) values. Binary logistic regression will be used to generate the models that will describe the combined impact of obesity and physical inactivity on health costs and, also, the determinants of health costs accumulated over eight years. All analyzes will be generated by the statistical software SPSS version 20.0 and the statistical significance (p-value) will be pre-fixed at values below 5%. (AU)

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