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Random Forest Analysis of Out-of-Pocket Health Expenditures Associated with Cardiometabolic Diseases, Lifestyle, Lipid Profile, and Genetic Information in São Paulo, Brazil.
- Source :
- Healthcare (2227-9032); Nov2024, Vol. 12 Issue 22, p2275, 18p
- Publication Year :
- 2024
-
Abstract
- Background/Objectives: There is a lack of empirical studies of out-of-pocket health expenditures associated with dyslipidemias, which are major cardiovascular risk factors, especially in underrepresented admixed populations. The study investigates associations of health costs with lipid traits, GWAS-derived genetic risk scores (GRSs), and other cardiometabolic risk factors. Methods: Data from the observational cross-sectional 2015 ISA-Nutrition comprised lifestyle, environmental factors, socioeconomic and demographic variables, and biochemical and genetic markers related to the occurrence of cardiometabolic diseases. GWAS-derived genetic risk scores were estimated from SNPs previously associated with lipid traits. There was phenotypic and genetic information available for 490 independent individuals, which was used as inputs for random forests and logistic regression to explain private quantitative and categorical health costs. Results: There were significant correlations between GRSs and their respective lipid phenotypes. The main relevant variables across techniques and outcome variables comprised income per capita, principal components of ancestry, diet quality, global physical activity, inflammatory and lipid markers, and LDL-c GRS and non-HDL-c GRS. The area under the ROC curve (AUC) of quartile-based categorical health expenditure without GRSs was 0.76. GRSs were not significant for this categorical outcome. Conclusions: We present an original contribution to the investigation of determinants of private health expenditures in a highly admixed population, providing insights on associations between genetic and socioeconomic dimensions of health in Brazil. Ancestry information was also among the main factors contributing to health expenses, providing a novel view of the role of genetic ancestry on cardiometabolic risk factors and its potential impact on health costs. [ABSTRACT FROM AUTHOR]
- Subjects :
- LIFESTYLES
RISK assessment
CROSS-sectional method
RANDOM forest algorithms
LIPID metabolism disorders
GENOME-wide association studies
HYPERLIPIDEMIA
RECEIVER operating characteristic curves
RESEARCH funding
SCIENTIFIC observation
STATISTICAL sampling
GENETIC markers
SOCIOECONOMIC factors
INTERVIEWING
BLOOD collection
LIPIDS
LOGISTIC regression analysis
CARDIOVASCULAR diseases risk factors
DESCRIPTIVE statistics
GENETIC risk score
GENETIC variation
SURVEYS
GENETIC polymorphisms
INSULIN resistance
GENETIC disorders
CLUSTER sampling
NUTRITIONAL status
SOCIODEMOGRAPHIC factors
ANTHROPOMETRY
MACHINE learning
CONFIDENCE intervals
DATA analysis software
MEDICAL care costs
EDUCATIONAL attainment
INTERLEUKINS
OBESITY
SENSITIVITY & specificity (Statistics)
Subjects
Details
- Language :
- English
- ISSN :
- 22279032
- Volume :
- 12
- Issue :
- 22
- Database :
- Complementary Index
- Journal :
- Healthcare (2227-9032)
- Publication Type :
- Academic Journal
- Accession number :
- 181166650
- Full Text :
- https://doi.org/10.3390/healthcare12222275