{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12(1)"],"submitter":["You W"],"pubmed_abstract":["Socioeconomic status has been associated with obesity prevalence increase in both males and females worldwide. We examined the magnitude of the difference between the two relationships and explored the independence of both relationships. Country specific data on gross domestic product (GDP) per capita, sex-specific obesity prevalence rates, urbanisation, total calories availability and level of obesity, genetic background accumulation (measured by the Biological State Index, I<sub>bs</sub>) were obtained for 191 countries. Curvilinear regressions, bivariate and partial correlations, linear mixed models and multivariate linear regression analyses were used to examine the relationship between GDP and obesity prevalence rates in males and females respectively. Fisher's r-to-z transformation, "],"journal":["Scientific reports"],"pagination":["15757"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9492695"],"repository":["biostudies-literature"],"pubmed_title":["Significantly different roles of economic affluence in sex-specific obesity prevalence rates: understanding more modifications within female body weight management."],"pmcid":["PMC9492695"],"pubmed_authors":["Henneberg M","You W"],"additional_accession":[]},"is_claimable":false,"name":"Significantly different roles of economic affluence in sex-specific obesity prevalence rates: understanding more modifications within female body weight management.","description":"Socioeconomic status has been associated with obesity prevalence increase in both males and females worldwide. We examined the magnitude of the difference between the two relationships and explored the independence of both relationships. Country specific data on gross domestic product (GDP) per capita, sex-specific obesity prevalence rates, urbanisation, total calories availability and level of obesity, genetic background accumulation (measured by the Biological State Index, I<sub>bs</sub>) were obtained for 191 countries. Curvilinear regressions, bivariate and partial correlations, linear mixed models and multivariate linear regression analyses were used to examine the relationship between GDP and obesity prevalence rates in males and females respectively. Fisher's r-to-z transformation, ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Sep","modification":"2025-04-05T12:32:29.123Z","creation":"2025-04-05T12:32:29.123Z"},"accession":"S-EPMC9492695","cross_references":{"pubmed":["36130963"],"doi":["10.1038/s41598-022-19633-3"]}}