{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T17:59:30Z","timestamp":1790704770532,"version":"4.1.0"},"reference-count":77,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The prevalence of cardiometabolic diseases like obesity, hypertension, diabetes, and dyslipidaemia is increasing rapidly, particularly in low- and middle-income countries (LMICs). Informal workers in Ghana, who account for the majority of the national workforce, contribute significantly to the country\u2019s socioeconomic growth. Often, their work predisposes them to cardiometabolic diseases. This study examines the cardiometabolic burden, its associated factors, and the diagnostic heterogeneity among this unique population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study used cross-sectional data on 948 informal workers (traders, fisherfolk, artisans, farmers, and drivers) in the Cape Coast Metropolis, Ghana. Sociodemographic, lifestyle, anthropometric, and biochemical data were obtained in accordance with standard procedures. Multiple diagnostic criteria were used to characterise diabetes, prediabetes, and obesity. Diagnostic concordance was evaluated using Venn diagrams and UpSet plots, and independent associated factors were identified using multivariate logistic regression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The prevalence of obesity, hypertension, prediabetes, and diabetes was 45.46%, 40.19%, 29.54%, and 13.40%, respectively. Women and middle-aged adults (45\u201359 years) were most impacted. There was significant heterogeneity in classification criteria, with just 9.28% of obese participants and 2.36% of diabetic participants being diagnosed by all diagnostic criteria. While the absence of childhood obesity was associated with lower odds of obesity (aOR = 0.43, 95% CI: 0.30\u20130.61), diabetes (aOR = 0.64, 95% CI: 0.42\u20130.99), and hypertension (aOR = 0.63, 95% CI: 0.46\u20130.88), older age (\u226560 years) was strongly associated with obesity (aOR = 2.54, 95% CI: 1.51\u20134.32) and hypertension (aOR = 4.82, 95% CI: 3.06\u20137.68). Low physical activity was significantly linked to hypertension (aOR = 1.73, 95% CI: 1.16\u20132.62), and elevated triglycerides were associated with diabetes (aOR = 2.16, 95% CI: 1.21\u20133.75) and hypertension (aOR = 1.84, 95% CI: 1.13\u20133.04).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The burden of cardiometabolic diseases among Ghana\u2019s informal workers is disproportionately high and diagnostically diverse. The findings emphasise the critical need for sex- and occupation-sensitive health interventions, life-course prevention strategies, and context-specific diagnostic guidelines to reduce cardiometabolic disease risk among informal workers in LMICs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0359530","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T17:25:41Z","timestamp":1790702741000},"page":"e0359530","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prevalence and risk factors of cardiometabolic disease among informal sector workers in Cape Coast, Ghana: Insights from the CarMeR study"],"prefix":"10.1371","volume":"21","author":[{"given":"Thomas","family":"Hormenu","sequence":"first","affiliation":[{"name":"Physical Education and Recreation, University of Cape Coast","place":["Cape Coast, Ghana"],"department":["Department of 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Epidemiology Research Laboratory"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juliet Elikem","family":"Paku","sequence":"additional","affiliation":[{"name":"Physical Education and Recreation, University of Cape Coast","place":["Cape Coast, Ghana"],"department":["Department of Health"]},{"name":"University of Cape Coast","place":["Cape Coast, Ghana"],"department":["Cardiometabolic Epidemiology Research Laboratory"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward Edem","family":"Nartey","sequence":"additional","affiliation":[{"name":"Physical Education and Recreation, University of Cape Coast","place":["Cape Coast, Ghana"],"department":["Department of Health"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaibu","family":"Bukari","sequence":"additional","affiliation":[{"name":"University of Cape Coast","place":["Ghana"],"department":["Department of Labour and Human Resource 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