Multimorbidity in Diverse Populations: Stratified Analysis of Race/Ethnicity, Age, Obesity, and Healthcare Costs

dc.contributor.advisorMadlock-Brown, Charisse
dc.contributor.authorAlshakhs, Manal Jawad
dc.date.accessioned2023-07-03T06:10:04Z
dc.date.available2023-07-03T06:10:04Z
dc.date.issued2023
dc.description.abstractThis research aims to fill an essential gap in understanding how Body Mass Index (BMI) cutoffs relate to multimorbidity across races in the United States (US). Given the significant and growing rates of obesity and multimorbidity, as well as the known differences in healthy fat distribution among different races, this is an important area of research. BMI is a widely used but imperfect measure of obesity, as it does not account for differences in body composition. However, it is still used as a diagnostic tool. It is vital to ensure that the cutoffs used to define obesity are appropriate for all populations, particularly given the racial disparities in multimorbidity rates. This proposed framework for evaluating BMI cutoffs across races for multimorbidity considered a range of measures, such as, including incidence rates of prevalent diseases, age, gender, type of patient visits, and type of health insurance to arrive at questioning the current World Health Organization (WHO) BMI cutoffs in the US. This research demonstrated that having the exact BMI cutoffs across all races does not serve all populations ideally through three assessments. First, it assessed differences in the prevalence of multimorbidity by race. It identified disease combinations shared by all races/ethnicities, shared by some, and those unique to one group for each age/obesity level. These findings demonstrated that despite controlling for age and obesity, there are differences in multimorbidity prevalence across races. Second, the study developed models to project total charges for the most common multimorbidity combinations in the US and evaluated the accuracy of these models across different racial and ethnic groups and multimorbidity patterns. The relationship between healthcare costs and multimorbidity varied for each racial group and depended on the specific combination of chronic conditions, age, and obesity status. Third, it assessed the relationship between BMI and healthcare burden across race and healthcare utilization among middle-aged patients in the US. It demonstrated that the relationship between BMI and healthcare burden varied across races within the same healthcare care utilization category. This research can improve health outcomes and reduce the risk of chronic diseases associated with obesity and multimorbidity, particularly among vulnerable populations. It will also be essential to consider the potential implications of any new BMI cutoffs on clinical practice and health policies related to obesity and multimorbidity in serving unique clinical needs. More work must be done to understand how multimorbidity, BMI, age, and healthcare burden associate across races.
dc.format.extent106
dc.identifier.otherORCID 0009-0001-1271-3097
dc.identifier.urihttps://hdl.handle.net/20.500.14154/68472
dc.language.isoen_US
dc.publisherSaudi Digital Library
dc.subjectmultimorbidity
dc.subjecthealthcare costs
dc.subjectrace/ethnicity stratification
dc.subjecthealthcare utilization
dc.subjecthealthcare burden
dc.titleMultimorbidity in Diverse Populations: Stratified Analysis of Race/Ethnicity, Age, Obesity, and Healthcare Costs
dc.typeThesis
sdl.degree.departmentGraduate Health Sciences
sdl.degree.disciplineHealth Informatics and Information Management
sdl.degree.grantorUniversity of Tennessee Health Science Center
sdl.degree.nameDoctor Of Philosophy
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