Lucy Kaluvu, Ogechukwu Augustina Asogwa, Anna Marzà-Florensa, Catherine Kyobutungi, Naomi S Levitt, Daniel Boateng, Kerstin Klipstein-Grobusch
{"title":"Multimorbidity of communicable and non-communicable diseases in low- and middle-income countries: A systematic review.","authors":"Lucy Kaluvu, Ogechukwu Augustina Asogwa, Anna Marzà-Florensa, Catherine Kyobutungi, Naomi S Levitt, Daniel Boateng, Kerstin Klipstein-Grobusch","doi":"10.1177/26335565221112593","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The aim of this systematic review is to analyse existing evidence on prevalence, patterns, determinants, and healthcare challenges of communicable and non-communicable disease multimorbidity in low- and middle-income countries (LMICs).</p><p><strong>Methods: </strong>PubMed, Cochrane, and Embase databases were searched from 1<sup>st</sup> January 2000 to 31<sup>st</sup> July 2020. The National Institute of Health (NIH) quality assessment tool was used to critically appraise studies. Findings were summarized in a narrative synthesis. The review was registered with PROSPERO (CRD42019133453).</p><p><strong>Results: </strong>Of 3718 articles screened, 79 articles underwent a full text review of which 11 were included for narrative synthesis. Studies reported on 4 to 20 chronic communicable and non-communicable diseases; prevalence of multimorbidity ranged from 13% in a study conducted among 242,952 participants from 48 LMICS to 87% in a study conducted among 491 participants in South Africa. Multimorbidity was positively associated with older age, female sex, unemployment, and physical inactivity. Significantly higher odds of multimorbidity were noted among obese participants (OR 2.33; 95% CI: 2.19-2.48) and those who consumed alcohol (OR 1.44; 95% CI: 1.25-1.66). The most frequently occurring dyads and triads were HIV and hypertension (23.3%) and HIV, hypertension, and diabetes (63%), respectively. Women and participants from low wealth quintiles reported higher utilization of public healthcare facilities.</p><p><strong>Conclusion: </strong>The identification and prevention of risk factors and addressing evidence gaps in multimorbidity clustering is crucial to address the increasing communicable and non-communicable disease multimorbidity in LMICs. To identify communicable and non-communicable diseases trends over time and identify causal relationships, longitudinal studies are warranted.</p>","PeriodicalId":73843,"journal":{"name":"Journal of multimorbidity and comorbidity","volume":" ","pages":"26335565221112593"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445468/pdf/","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of multimorbidity and comorbidity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/26335565221112593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Objective: The aim of this systematic review is to analyse existing evidence on prevalence, patterns, determinants, and healthcare challenges of communicable and non-communicable disease multimorbidity in low- and middle-income countries (LMICs).
Methods: PubMed, Cochrane, and Embase databases were searched from 1st January 2000 to 31st July 2020. The National Institute of Health (NIH) quality assessment tool was used to critically appraise studies. Findings were summarized in a narrative synthesis. The review was registered with PROSPERO (CRD42019133453).
Results: Of 3718 articles screened, 79 articles underwent a full text review of which 11 were included for narrative synthesis. Studies reported on 4 to 20 chronic communicable and non-communicable diseases; prevalence of multimorbidity ranged from 13% in a study conducted among 242,952 participants from 48 LMICS to 87% in a study conducted among 491 participants in South Africa. Multimorbidity was positively associated with older age, female sex, unemployment, and physical inactivity. Significantly higher odds of multimorbidity were noted among obese participants (OR 2.33; 95% CI: 2.19-2.48) and those who consumed alcohol (OR 1.44; 95% CI: 1.25-1.66). The most frequently occurring dyads and triads were HIV and hypertension (23.3%) and HIV, hypertension, and diabetes (63%), respectively. Women and participants from low wealth quintiles reported higher utilization of public healthcare facilities.
Conclusion: The identification and prevention of risk factors and addressing evidence gaps in multimorbidity clustering is crucial to address the increasing communicable and non-communicable disease multimorbidity in LMICs. To identify communicable and non-communicable diseases trends over time and identify causal relationships, longitudinal studies are warranted.