TY - JOUR
T1 - Socioeconomic and Ethnic Inequalities in the Progress of Multimorbidity and the Role of Health Behaviors
AU - Mira, Rolla
AU - Newton, Tim
AU - Sabbah, Wael
N1 - Funding Information:
This research did not receive any funding from agencies in the public, commercial, or not-for-profit sectors.
Publisher Copyright:
© 2023 The Authors
PY - 2023/6
Y1 - 2023/6
N2 - Objectives: To assess socioeconomic and ethnic inequalities in the progress of multimorbidity and whether behavioral factors explain these inequalities among older Americans. Design: Health and Retirement Study, a longitudinal survey of older American adults. Setting and Participants: Data pooled from 2006 to 2018 (waves 8–14), which include 38,061 participants. Methods: We used 7 waves of the survey from 2006 to 2018. Socioeconomic factors were indicated by education, total wealth, poverty-income ratio (income), and race/ethnicity. Multimorbidity was indicated by self-reported diagnoses of 5 chronic conditions: diabetes, heart conditions, lung diseases, cancer, and stroke. Behavioral factors were smoking, excessive alcohol consumption, physical activity, and body mass index (BMI). Multilevel mixed effects generalized linear models were constructed to assess socioeconomic and ethnic inequalities in the progress of multimorbidity and the role of behavior. All variables included in the analysis were time-varying except gender, race/ethnicity, and education. Results: African American individuals had higher rates of multimorbidity than White individuals; however, after adjusting for income and education, the association was reversed. There were clear income, wealth, and education gradients in the progress of multimorbidity. After adjusting for behavioral factors, the relationships were attenuated. The rate ratio (RR) of multimorbidity attenuated by 9% among participants with the lowest level of education after accounting for behavior (RR 1.21; 95% CI 1.18–1.23 and 1.11; 95% CI 1.17–1.14) in the models unadjusted and adjusted for behaviors, respectively. Similarly, RR for multimorbidity among those in the lowest wealth quartile attenuated from 1.47 (95% CI 1.44–1.51) and 1.31 (95% CI 1.26–1.36) after accounting for behaviors. Conclusion and implications: Ethnic inequalities in the progress of multimorbidity were explained by wealth, income, and education. Behavioral factors partially attenuated socioeconomic inequalities in multimorbidity. The findings are useful in identifying the behaviors that should be included in health promotion programs aiming at tackling inequalities in multimorbidity.
AB - Objectives: To assess socioeconomic and ethnic inequalities in the progress of multimorbidity and whether behavioral factors explain these inequalities among older Americans. Design: Health and Retirement Study, a longitudinal survey of older American adults. Setting and Participants: Data pooled from 2006 to 2018 (waves 8–14), which include 38,061 participants. Methods: We used 7 waves of the survey from 2006 to 2018. Socioeconomic factors were indicated by education, total wealth, poverty-income ratio (income), and race/ethnicity. Multimorbidity was indicated by self-reported diagnoses of 5 chronic conditions: diabetes, heart conditions, lung diseases, cancer, and stroke. Behavioral factors were smoking, excessive alcohol consumption, physical activity, and body mass index (BMI). Multilevel mixed effects generalized linear models were constructed to assess socioeconomic and ethnic inequalities in the progress of multimorbidity and the role of behavior. All variables included in the analysis were time-varying except gender, race/ethnicity, and education. Results: African American individuals had higher rates of multimorbidity than White individuals; however, after adjusting for income and education, the association was reversed. There were clear income, wealth, and education gradients in the progress of multimorbidity. After adjusting for behavioral factors, the relationships were attenuated. The rate ratio (RR) of multimorbidity attenuated by 9% among participants with the lowest level of education after accounting for behavior (RR 1.21; 95% CI 1.18–1.23 and 1.11; 95% CI 1.17–1.14) in the models unadjusted and adjusted for behaviors, respectively. Similarly, RR for multimorbidity among those in the lowest wealth quartile attenuated from 1.47 (95% CI 1.44–1.51) and 1.31 (95% CI 1.26–1.36) after accounting for behaviors. Conclusion and implications: Ethnic inequalities in the progress of multimorbidity were explained by wealth, income, and education. Behavioral factors partially attenuated socioeconomic inequalities in multimorbidity. The findings are useful in identifying the behaviors that should be included in health promotion programs aiming at tackling inequalities in multimorbidity.
UR - http://www.scopus.com/inward/record.url?scp=85148957869&partnerID=8YFLogxK
U2 - 10.1016/j.jamda.2023.01.009
DO - 10.1016/j.jamda.2023.01.009
M3 - Article
SN - 1525-8610
VL - 24
SP - 811
EP - 815
JO - Journal Of The American Medical Directors Association
JF - Journal Of The American Medical Directors Association
IS - 6
ER -
