Social determinants of multimorbidity in Jamaica: application of latent class analysis in a cross-sectional study

Autor: Leslie S. Craig, Colette A. Cunningham-Myrie, David R. Hotchkiss, Julie H. Hernandez, Jeanette Gustat, Katherine P. Theall
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: BMC Public Health, Vol 21, Iss 1, Pp 1-15 (2021)
Druh dokumentu: article
ISSN: 1471-2458
DOI: 10.1186/s12889-021-11225-6
Popis: 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
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