{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:02:45Z","timestamp":1787022165335,"version":"build-2736575974"},"reference-count":23,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T00:00:00Z","timestamp":1749427200000},"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>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The World Health Organization (WHO) non-laboratory cardiovascular disease (CVD) risk chart is sub-region-specific and is advocated in resource-constrained settings. However, the extent of agreement with laboratory-based assessment among hypertensive adults attending primary health centers (PHCs) in the West Africa sub-region remains unknown. This study compared 10-year CVD risk among adults with hypertension attending PHCs in Ghana and Nigeria.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>This cross-sectional study recruited 319 adults with hypertension at PHCs in Ghana and Nigeria. All participants had their blood pressure, anthropometrics, fasting blood sugar, and fasting cholesterol measured following standard procedures. WHO laboratory and non-laboratory CVD risks were assessed and compared using Kappa statistics, correlation, and Bland-Altman Plot,<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The median (interquartile range) for laboratory-based and non-laboratory-based CVD risk scores were comparable [7.0 (4.0 11.0) vs. 7.0 (4.0 to 11.0), p = 0.914]. Of the 319 participants, laboratory-based assessment classified 214 (67.1%) as low risk, while 210 (65.8%) were classified as low risk using the non-laboratory method. Eleven (3.4%) and 14 (4.4%) participants were classified as high-risk using laboratory- and non-laboratory-based methods, respectively. Overall, there was a very good positive correlation between the CVD risk assessment methods (r = 0.948, p&lt;0.001). For all participants combined, there was substantial agreement (Kappa statistics), with K = 0.766. Bland-Altman showed a mean bias of 0.15 (SD = 1.74) in favor of non-laboratory-based assessment of CVD with an upper limit of 3.57 and a lower limit of \u20133.26.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>There was substantial agreement between laboratory- and non-laboratory-based WHO CVD risk charts in this study. In low-resource settings, such as Ghana and Nigeria, the WHO non-laboratory CVD risk prediction model offers a huge opportunity for primary CVD prevention in adults with hypertension.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0317640","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T13:36:08Z","timestamp":1749476168000},"page":"e0317640","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["Comparison of WHO laboratory-based and non-laboratory-based CVD risk charts among hypertensive adults attending primary healthcare centers in West Africa sub-region"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-3879-299X","authenticated-orcid":true,"given":"Kojo Awotwi","family":"Hutton-Mensah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2621-6593","authenticated-orcid":true,"given":"Olayinka Rasheed","family":"Ibrahim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adaku","family":"Nwankwo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George Bediako","family":"Nketiah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Funmi Temidayo","family":"Adeniyi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abukari Yakubu","family":"Natogmah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James Ayodele","family":"Ogunmodede","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dike","family":"Ojji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olumide","family":"Adesola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Biodun Sulyman","family":"Alabi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olugbenga Ayodeji","family":"Mokuolu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Sarpong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,6,9]]},"reference":[{"key":"pone.0317640.ref001","volume-title":"World Heart Report 2023: Confronting the World\u2019s Number One Killer","year":"2023"},{"issue":"19","key":"pone.0317640.ref002","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1161\/CIRCULATIONAHA.123.063671","article-title":"Cardiovascular diseases in Nigeria: current status, threats, and opportunities","volume":"148","author":"OS Ogah","year":"2023","journal-title":"Circulation"},{"issue":"24","key":"pone.0317640.ref003","article-title":"Cardiometabolic risk factors and preclinical target organ damage among adults in Ghana: findings from a national study","volume":"9","author":"J Li","year":"2020","journal-title":"J Am Heart Assoc"},{"issue":"2","key":"pone.0317640.ref004","first-page":"95","article-title":"Hypertension in sub-Saharan Africa: the current profile, recent advances, gaps, and priorities","volume":"39","author":"LF Gafane-Matemane","year":"2025","journal-title":"J Hum Hypertens"},{"issue":"7","key":"pone.0317640.ref005","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.3390\/jpm12071180","article-title":"Cardiovascular risk prediction models and scores in the era of personalized medicine","volume":"12","author":"A Sofogianni","year":"2022","journal-title":"J Pers Med"},{"issue":"1","key":"pone.0317640.ref006","doi-asserted-by":"crossref","DOI":"10.1136\/bmjgh-2020-003499","article-title":"Estimating the burden of cardiovascular risk in community dwellers over 40 years old in South Africa, Kenya, Burkina Faso and Ghana","volume":"6","author":"RG Wagner","year":"2021","journal-title":"BMJ Glob Health"},{"key":"pone.0317640.ref007","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.ijcard.2017.11.082","article-title":"Cardiovascular disease risk prediction in sub-Saharan African populations - Comparative analysis of risk algorithms in the RODAM study","volume":"254","author":"D Boateng","year":"2018","journal-title":"Int J Cardiol"},{"issue":"10","key":"pone.0317640.ref008","doi-asserted-by":"crossref","DOI":"10.1016\/S2214-109X(19)30318-3","article-title":"World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions","volume":"7","author":"S Kaptoge","year":"2019","journal-title":"Lancet Glob Health"},{"issue":"1","key":"pone.0317640.ref009","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1186\/s12874-023-01961-1","article-title":"Laboratory-based versus non-laboratory-based World Health Organization risk equations for assessment of cardiovascular disease risk","volume":"23","author":"A Dehghan","year":"2023","journal-title":"BMC Med Res Methodol"},{"issue":"1","key":"pone.0317640.ref010","doi-asserted-by":"crossref","first-page":"1742","DOI":"10.1186\/s12889-022-13944-w","article-title":"Evaluation of cardiovascular diseases risk calculators for CVDs prevention and management: scoping review","volume":"22","author":"MAEMD Badawy","year":"2022","journal-title":"BMC Public Health"},{"issue":"6","key":"pone.0317640.ref011","doi-asserted-by":"crossref","first-page":"1448","DOI":"10.1016\/j.numecd.2024.01.026","article-title":"Performance of the non-laboratory based 2019 WHO cardiovascular disease risk prediction chart in Eastern Sub-Saharan Africa","volume":"34","author":"A Bendera","year":"2024","journal-title":"Nutr Metab Cardiovasc Dis"},{"issue":"1","key":"pone.0317640.ref012","doi-asserted-by":"crossref","first-page":"64","DOI":"10.5334\/gh.1148","article-title":"WHO non-lab-based CVD risk assessment: a reliable measure in a North Indian Population","volume":"17","author":"P Ananda Selva Das","year":"2022","journal-title":"Glob Heart"},{"issue":"4","key":"pone.0317640.ref013","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1038\/s41371-022-00688-8","article-title":"Rural-urban difference in the prevalence of hypertension in West Africa: a systematic review and meta-analysis","volume":"38","author":"RN Sani","year":"2024","journal-title":"J Hum Hypertens"},{"key":"pone.0317640.ref014"},{"key":"pone.0317640.ref015","first-page":"76","article-title":"Sample size estimation using Yamane and Cochran and Krejcie and Morgan and Green formulas and Cohen statistical power analysis by G*power and comparisons","volume":"10","author":"C Uakarn","year":"2021","journal-title":"Apheit Int J"},{"issue":"1","key":"pone.0317640.ref016","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1177\/10105395231211997","article-title":"Comparison of laboratory and non-laboratory-based 2019 World Health Organization Cardiovascular risk charts in the Bhutanese population","volume":"36","author":"K Chhezom","year":"2024","journal-title":"Asia Pac J Public Health"},{"issue":"11","key":"pone.0317640.ref017","article-title":"Agreement between the laboratory-based and non-laboratory-based WHO cardiovascular risk charts: a cross-sectional analysis of a national health survey in Peru","volume":"12","author":"WC Guzman-Vilca","year":"2022","journal-title":"BMJ Open"},{"key":"pone.0317640.ref018","unstructured":"World Health Organization-Ghana. Ghana steps report 2023. 2024 Sep."},{"issue":"2","key":"pone.0317640.ref019","doi-asserted-by":"crossref","first-page":"99","DOI":"10.4103\/WHO-SEAJPH.WHO-SEAJPH_53_22","article-title":"Availability of hypertension and diabetes mellitus care services at subdistrict level in Bangladesh","volume":"12","author":"S Jubayer","year":"2023","journal-title":"WHO South East Asia J Public Health"},{"key":"pone.0317640.ref020","volume-title":"Assessment of ten-year cardiovascular disease risk in Bangladesh: a comparative analysis of laboratory and non-laboratory-based WHO risk prediction models","author":"MM Monower","year":"2024"},{"issue":"1","key":"pone.0317640.ref021","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1186\/s12967-022-03336-4","article-title":"Comparison of laboratory-based and non-laboratory-based WHO cardiovascular disease risk charts: a population-based study","volume":"20","author":"F Rezaei","year":"2022","journal-title":"J Transl Med"},{"issue":"2","key":"pone.0317640.ref022","doi-asserted-by":"crossref","first-page":"96","DOI":"10.12997\/jla.2023.12.2.96","article-title":"Risk stratification of cardiovascular disease according to age groups in new prevention guidelines: a review","volume":"12","author":"K-I Kim","year":"2023","journal-title":"J Lipid Atheroscler"},{"key":"pone.0317640.ref023","doi-asserted-by":"crossref","first-page":"105986","DOI":"10.1016\/j.ypmed.2020.105986","article-title":"Predictive value of traditional risk factors for cardiovascular disease in older people: a systematic review","volume":"132","author":"EF van Bussel","year":"2020","journal-title":"Prev Med"}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0317640","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T13:36:18Z","timestamp":1749476178000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0317640"}},"subtitle":[],"editor":[{"given":"Ryan G","family":"Wagner","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,6,9]]},"references-count":23,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,6,9]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0317640","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2025.01.05.25320020","asserted-by":"object"}]},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,9]]}}}