Ethnic and geographic variations in multimorbidty: Evidence from three large cohorts.
A common characteristic of patients seen at the Veterans Health Administration (VHA) is a high number of concurrent comorbidities (i.e. multimorbidity). This study (i) examines the magnitude and patterns of multimorbidity by race/ethnicity and geography; (ii) compares the level of variation explained by these factors in three multimorbidity measures across three large cohorts. We created three national cohorts for Veterans with chronic kidney disease (CKD:n = 2,190,564), traumatic brain injury (TBI:n = 167,954) and diabetes-mellitus (DM:n = 1,263,906). Multimorbidity was measured by Charlson-Deyo, Elixhauser and Walraven-Elixhauser scores. Multimorbidity differences by race/ethnicity and geography were compared using generalized linear models (GLM). Latent class analysis (LCA) was used to identify groups of conditions that are highly associated with race/ethnic groups. Differences in age (CKD,74.5, TBI,49.7, DM, 66.9 years), race (CKD,80.9%, TBI,76.4%, DM, 63.8% NHW) and geography (CKD,64.4%, TBI,70%, DM, 70.9% urban) were observed among the three cohorts. Accounting for these differences, GLM results showed that risk of multimorbidity in non-Hispanic blacks (NHB) with CKD were 1.16 times higher in urban areas and 1.10 times higher in rural areas compared to non-Hispanic whites (NHW) with CKD. DM and TBI showed similar results with risk for NHB, 1.05 higher in urban areas and 0.97 lower in rural areas for both diseases. Overall, our results show that (i) multimorbidity risk was higher for NHB in urban areas compared to rural areas in all three cohorts; (ii) multimorbidity risk was higher for Hispanics in urban areas compared to rural areas in the DM and CKD cohorts; and (iii) the highest overall multimorbidity risk of any race group or location exists for Hispanics in insular islands for all three disease cohorts. These findings are consistent among the three multimorbidity measures. In fact, our LCA also showed that a three class LC model based on Elixhauser or Charlson provides good discrimination by type and extent of multimorbidity.
['Gebregziabher|Mulugeta|M|', 'Ward|Ralph C|RC|', 'Taber|David J|DJ|', 'Walker|Rebekah J|RJ|', 'Ozieh|Mukoso|M|', 'Dismuke|Clara E|CE|', 'Axon|Robert N|RN|', 'Egede|Leonard E|LE|']
D000328:Adult D000368:Aged D015331:Cohort Studies D015897:Comorbidity D048909:Diabetes Complications D003920:Diabetes Mellitus D005007:Ethnology D005260:Female D062305:Geographic Mapping D006801:Humans D006973:Hypertension D008297:Male D008875:Middle Aged D000076322:Multimorbidity D009765:Obesity D044469:Racial Groups D014481:United States D014493:United States Department of Veterans Affairs D014728:Veterans
Multimorbidity Elixhauser Walraven-elixhauser Insular-island Racial disparities