Leslie S Craig1, Colette A Cunningham-Myrie2, David R Hotchkiss3, Julie H Hernandez4, Jeanette Gustat5, Katherine P Theall3. 1. Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, USA. lcraig1@tulane.edu. 2. Department of Community Health & Psychiatry, University of the West Indies, Mona, Jamaica. 3. Department of Global Community Health and Behavioral Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA. 4. Department of Health Policy and Management, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA. 5. Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
Abstract
BACKGROUND: Non-communicable disease (NCD) multimorbidity is associated with impaired functioning, lower quality of life and higher mortality. Susceptibility to accumulation of multiple NCDs is rooted in social, economic and cultural contexts, with important differences in the burden, patterns, and determinants of multimorbidity across settings. Despite high prevalence of individual NCDs within the Caribbean region, exploration of the social epidemiology of multimorbidity remains sparse. This study aimed to examine the social determinants of NCD multimorbidity in Jamaica, to better inform prevention and intervention strategies. METHODS: Latent class analysis (LCA) was used to examine social determinants of identified multimorbidity patterns in a sample of 2551 respondents aged 15-74 years, from the nationally representative Jamaica Health and Lifestyle Survey 2007/2008. Multimorbidity measurement was based on self-reported presence/absence of 11 chronic conditions. Selection of social determinants of health (SDH) was informed by the World Health Organization's Commission on SDH framework. Multinomial logistic regression models were used to estimate the association between individual-level SDH and class membership. RESULTS: Approximately one-quarter of the sample (24.05%) were multimorbid. LCA revealed four distinct profiles: a Relatively Healthy class (52.70%), with a single or no morbidity; and three additional classes, characterized by varying degrees and patterns of multimorbidity, labelled Metabolic (30.88%), Vascular-Inflammatory (12.21%), and Respiratory (4.20%). Upon controlling for all SDH (Model 3), advancing age and recent healthcare visits remained significant predictors of all three multimorbidity patterns (p < 0.001). Private insurance coverage (relative risk ratio, RRR = 0.63; p < 0.01) and higher educational attainment (RRR = 0.73; p < 0.05) were associated with lower relative risk of belonging to the Metabolic class while being female was a significant independent predictor of Vascular-Inflammatory class membership (RRR = 2.54; p < 0.001). Material circumstances, namely housing conditions and features of the physical and neighbourhood environment, were not significant predictors of any multimorbidity class. CONCLUSION: This study provides a nuanced understanding of the social patterning of multimorbidity in Jamaica, identifying biological, health system, and structural determinants as key factors associated with specific multimorbidity profiles. Future research using longitudinal designs would aid understanding of disease trajectories and clarify the role of SDH in mitigating risk of accumulation of diseases.
BACKGROUND: Non-communicable disease (NCD) multimorbidity is associated with impaired functioning, lower quality of life and higher mortality. Susceptibility to accumulation of multiple NCDs is rooted in social, economic and cultural contexts, with important differences in the burden, patterns, and determinants of multimorbidity across settings. Despite high prevalence of individual NCDs within the Caribbean region, exploration of the social epidemiology of multimorbidity remains sparse. This study aimed to examine the social determinants of NCD multimorbidity in Jamaica, to better inform prevention and intervention strategies. METHODS: Latent class analysis (LCA) was used to examine social determinants of identified multimorbidity patterns in a sample of 2551 respondents aged 15-74 years, from the nationally representative Jamaica Health and Lifestyle Survey 2007/2008. Multimorbidity measurement was based on self-reported presence/absence of 11 chronic conditions. Selection of social determinants of health (SDH) was informed by the World Health Organization's Commission on SDH framework. Multinomial logistic regression models were used to estimate the association between individual-level SDH and class membership. RESULTS: Approximately one-quarter of the sample (24.05%) were multimorbid. LCA revealed four distinct profiles: a Relatively Healthy class (52.70%), with a single or no morbidity; and three additional classes, characterized by varying degrees and patterns of multimorbidity, labelled Metabolic (30.88%), Vascular-Inflammatory (12.21%), and Respiratory (4.20%). Upon controlling for all SDH (Model 3), advancing age and recent healthcare visits remained significant predictors of all three multimorbidity patterns (p < 0.001). Private insurance coverage (relative risk ratio, RRR = 0.63; p < 0.01) and higher educational attainment (RRR = 0.73; p < 0.05) were associated with lower relative risk of belonging to the Metabolic class while being female was a significant independent predictor of Vascular-Inflammatory class membership (RRR = 2.54; p < 0.001). Material circumstances, namely housing conditions and features of the physical and neighbourhood environment, were not significant predictors of any multimorbidity class. CONCLUSION: This study provides a nuanced understanding of the social patterning of multimorbidity in Jamaica, identifying biological, health system, and structural determinants as key factors associated with specific multimorbidity profiles. Future research using longitudinal designs would aid understanding of disease trajectories and clarify the role of SDH in mitigating risk of accumulation of diseases.
Entities:
Keywords:
Jamaica; Latent class analysis; Multimorbidity; Non-communicable diseases; Social determinants
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