| Literature DB >> 35841531 |
Paul A Agius1,2,3, Julia C Cutts1,4, Peige Song5,6, Igor Rudan5, Diana Rudan7, Victor Aboyans8, Mary M McDermott9, Michael H Criqui10, F Gerald R Fowkes5, Freya J I Fowkes11,12,13.
Abstract
An epidemiological transition in the prevalence of peripheral artery disease (PAD) is taking place especially in low- and middle-income countries (LMICs) where an ageing population and adoption of western lifestyles are associated with an increase in PAD. We discuss the limited evidence which suggests that infection, potentially mediated by inflammation, may be a risk factor for PAD, and show by means of an ecological analysis that country-level prevalence of the major endemic infections of HIV, tuberculosis and malaria are associated with the prevalence of PAD. While further research is required, we propose that scientists and health authorities pay more attention to the interplay between communicable and non-communicable diseases, and we suggest that limiting the occurrence of endemic infections might have some effect on slowing the epidemiological transition in PAD.Entities:
Keywords: Epidemiology; HIV; Malaria; Peripheral arterial disease; Tuberculosis
Mesh:
Year: 2022 PMID: 35841531 PMCID: PMC9287714 DOI: 10.1007/s44197-022-00049-1
Source DB: PubMed Journal: J Epidemiol Glob Health ISSN: 2210-6006
Fig. 1Prevalence of peripheral artery disease and country-level prevalence of malaria (A), HIV (B) and tuberculosis (C). PAD peripheral artery disease. TB tuberculosis. HIV human immunodeficiency virus. The black line shows average PAD probability (equivalent to PAD prevalence) by natural log prevalence of infection, with 95% confidence intervals shown by red shading. The circles depict individual studies by World Bank country income group [19] (red = low-income country, orange = low–middle-income country, green = upper middle-income country, blue = high-income country). Larger circles represent larger studies. The analysis used study-specific PAD cases (numerator) and respective sample sizes (denominator) to undertake binomial form logit estimation in generalised linear mixed modelling at two levels (level 1, studies; level 2, countries; and a random intercept for country)