Examining multimorbidity differences across racial groups: a network analysis of electronic medical records

Abstract

Health disparities across ethnic or racial groups are typically examined through single behavior at a time. The syndemics and multimorbidity health disparities have not been well examined by race. In this study, we study health disparities by identifying the networks of multimorbidities among individuals from seven population groups based on race, including White, African American, Asian, Hispanic, Native American, Bi- or Multi-racial and Pacific Islander. We examined a large electronic medical record (EMR) containing health records of more than 18.7 million patients and created multimorbidity networks considering their lifetime history from medical records in order to compare the network properties among seven population groups. In addition, the networks at organ system level depicting the relationship among disorders belonging to different organ systems are also compared. Our macro analysis at the organ-level indicates that African-Americans have a stronger multimorbidity network followed by Whites and Native Americans. The networks of Asians and Hispanics are sparse. Specifically, the relationship of infectious and parasitic disorders with respiratory, circulatory and genitourinary system disorders is stronger among African Americans than others. On the other hand, the relationship of mental disorders with respiratory, musculoskeletal system and connective tissue disorders is more prevalent in Whites. Similar other disparities are discussed. Recognition and explanation of such differences in multimorbidities inform the public health policies, and can inform clinical decisions as well. Our multimorbidity network analysis identifies specific differences in diagnoses among different population groups, and presents questions for biological, behavioral, clinical, social science, and policy research.

Associations between physical multimorbidity patterns and common mental health disorders in middle-aged adults: A prospective analysis using data from the UK Biobank

“…Several covariates were included, and their selection was informed by previous literature and theory. Sociodemographic variables such as age, gender, ethnicity (White/ethnic minority group), social deprivation, education level, and employment status are known to be associated with both physical multimorbidity and common mental health disorders and were therefore included as covariates [ 8 , 33 , 34 ]. Deprivation was based on Townsend deprivation indices [35] derived from aggregated data on car ownership, household overcrowding, owner occupation and unemployment.…”

Identifying multimorbidity clusters with the highest primary care use: 15 years of evidence from a multi-ethnic metropolitan population

“…Part of the complexity behind multimorbidity lies in understanding social factors that enable patients to use health services such as income or ethnicity. Differences in multimorbidity composition and prognosis across ethnic groups have been documented (22)(23)(24), but whether the impact of multimorbidity on primary care needs is magnified for certain ethnic groups remains unknown (14). Morbidities tend to accumulate within individuals over time (25) but relatively few analyses use longitudinal data (14,26).…”

Patterns Of Multimorbidity Of Patients In Geriatric Care – A Register-Based Cohort Study In Sweden

“…In Oklahoma State in the U.S. a study of multimorbidity was performed, where the patterns of various ethnic groups were displayed and illustrated with locations on and around the shape of a body. 37 Compared to our study with data from about one year's period, in their study every diagnosis during the individual's whole lifetime was used.…”