Cardiovascular diseases (CVDs) are the leading cause of mortality globally. Cardiovascular risk scores are reliable tools used to predict an individual’s chance of developing a cardiovascular event. This study assesses the distribution of cardiovascular risk among diabetic patients attending a diabetic clinic in a district hospital in Kumasi. This is a hospital-based cross-sectional study among 94 diabetic patients attending a diabetic clinic in Kumasi, Ghana. Data collected includes sociodemographic information, anthropometry, medical history and lipid profile which were then used to compute the cardiovascular risk score using the pooled cohort equation (PCE) and WHO non-laboratory scoring tools. The average risk score was 13.5% [CI 95: 10.8 – 16.1] according to the PCE tool and 7.2% [CI 95: 6.2 – 8.1] according to the WHO non-laboratory risk scoring tool. The PCE categorised 52.1%, 25.5% and 22.3% as low, moderate and high risk respectively whiles the WHO non-lab categorised 78.7% and 21.3% as low and moderate risk respectively, with no one at high risk. Majority of our study participants were at low risk of developing a cardiovascular event in 10-years according to both tools. There was significant difference between the pooled cohort equation and WHO non-lab risk scoring calculators.
Published in | Cardiology and Cardiovascular Research (Volume 7, Issue 3) |
DOI | 10.11648/j.ccr.20230703.11 |
Page(s) | 50-56 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Cardiovascular Risk, Pooled Cohort Equation, WHO Non-Laboratory, Diabetic Patients, Kumasi
[1] | Roth GA, Mensah GA, Johnson CO, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020; 76 (25): 2982-3021. doi: 10.1016/j.jacc.2020.11.010. |
[2] | Agyei-Mensah S, De-Graft Aikins A. Epidemiological transition and the double burden of disease in Accra, Ghana. J Urban Heal. 2010; 87 (5): 879-897. doi: 10.1007/s11524-010-9492-y. |
[3] | Agyemang C, Attah-Adjepong G, Owusu-Dabo E, et al. Stroke in Ashanti region of Ghana. Ghana Med J. 2012; 46 (2 Suppl): 12-17. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3645146/pdf/GMJ462S-0012.pdf. Accessed August 19, 2021. |
[4] | Salem H, Hasan DM, Eameash A, El-Mageed HA, Hasan S, Ali R. WORLDWIDE PREVALENCE OF HYPERTENSION: A POOLED META-ANALYSIS OF 1670 STUDIES IN 71 COUNTRIES WITH 29.5 MILLION PARTICIPANTS. J Am Coll Cardiol. 2018; 71 (11): A1819. doi: 10.1016/S0735-1097(18)32360-X. |
[5] | Addo J, Amoah AGB, Kwadwo KA. The changing patterns of hypertension in Ghana: A study of four rural communities in the Ga District. Ethn Dis. 2006; 16 (4): 894-899. doi: 10.1016/j.na.2012.04.011. |
[6] | IDF (International Diabetes Federation). Diabetes. Int Diabetes Fed. 2015. doi: 10.1289/image.ehp.v119.i03. |
[7] | Bild D, Teutsch SM. The control of hypertension in persons with diabetes: a public health approach. Public Health Rep. 1980; 102 (5): 522-529. doi: 10.1089/bar.2009.9953. |
[8] | Alanazi TO, Alenezi YM, Ibrahim M, et al. Coexistence of Hypertension and Diabetes Mellitus in Elderly Population of Arar City, Northern Saudi Arabia. 2017; 69 (October): 3154-3159. doi: 10.12816/0042867. |
[9] | Mcdonnell LA, Pipe AL, Westcott C, et al. Perceived vs Actual Knowledge and Risk of Heart Disease in Women: Findings From a Canadian Survey on Heart Health Awareness, Attitudes, and Lifestyle. Can J Cardiol. 2014; 30: 827-834. doi: 10.1016/j.cjca.2014.05.007. |
[10] | Khambhati J, Allard-Ratick M, Dhindsa D, et al. The art of cardiovascular risk assessment. Clin Cardiol. 2018; 41 (5): 677-684. doi: 10.1002/clc.22930. |
[11] | New Zealand Guidelines Group. Guideline the Assessment and Management of Cardiovascular. Rev Lit Arts Am. 2003; (December). |
[12] | Boateng D, Agyemang C, Beune E, et al. Cardiovascular disease risk prediction in sub-Saharan African populations — Comparative analysis of risk algorithms in the RODAM study. Int J Cardiol. 2017; 254: 310-315. doi: 10.1016/j.ijcard.2017.11.082. |
[13] | Danquah I, Bedu-Addo G, Terpe K-J, et al. Diabetes mellitus type 2 in urban Ghana: characteristics and associated factors. BMC Public Health. 2012; 12: 210. doi: 10.1186/1471-2458-12-210. |
[14] | Nelson RH. Hyperlipidemia as a Risk Factor for Cardiovascular Disease. Prim Care - Clin Off Pract. 2013; 40 (1): 195-211. doi: 10.1016/j.pop.2012.11.003. |
[15] | Kavishe B, Vanobberghen F, Katende D, et al. Dyslipidemias and cardiovascular risk scores in urban and rural populations in northwestern Tanzania and southern Uganda. PLoS One. 2019; 14 (12). doi: 10.1371/journal.pone.0223189. |
[16] | Macek P, Biskup M, Terek-Derszniak M, et al. Optimal cut-off values for anthropometric measures of obesity in screening for cardiometabolic disorders in adults. 2020; 10: 11253. doi: 10.1038/s41598-020-68265-y. |
[17] | Alzaman N, Wartak SA, Friderici J, Rothberg MB. Effect of Patients’ Awareness of CVD Risk Factors on Health-Related Behaviors. 2013. doi: 10.1097/SMJ.0000000000000013. |
[18] | McGurnaghan S, Blackbourn LAK, Mocevic E, et al. Cardiovascular disease prevalence and risk factor prevalence in Type 2 diabetes: a contemporary analysis. Diabet Med. 2019; 36 (6): 718-725. doi: 10.1111/dme.13825. |
[19] | Cappuccio FP, Miller MA. Cardiovascular disease and hypertension in sub-Saharan Africa: burden, risk and interventions. Intern Emerg Med. 2016; 11 (3): 299-305. doi: 10.1007/s11739-016-1423-9. |
[20] | Nsiah K, Shang Vo, Boateng Ka, Mensah F. Prevalence of metabolic syndrome in type 2 diabetes mellitus patients. Int J Appl Basic Med Res. 2015; 5 (2): 133. doi: 10.4103/2229-516x.157170. |
[21] | Diemer FS, Brewster LM, Haan YC, Oehlers GP, van Montfrans GA, Nahar-van Venrooij LMW. Body composition measures and cardiovascular risk in high-risk ethnic groups. Clin Nutr. 2019; 38 (1): 450-456. doi: 10.1016/j.clnu.2017.11.012. |
[22] | Owolabi EO, Ter Goon D, Adeniyi OV. Central obesity and normal-weight central obesity among adults attending healthcare facilities in Buffalo City Metropolitan Municipality, South Africa: A cross-sectional study. J Heal Popul Nutr. 2017; 36 (1). doi: 10.1186/s41043-017-0133-x. |
[23] | Yadav R, Yadav RK, Sarvottam K, Netam R. Framingham risk score and estimated 10-year cardiovascular disease risk reduction by a short-term yoga-based lifestyle intervention. J Altern Complement Med. 2017; 23 (9): 730-737. doi: 10.1089/acm.2016.0309. |
[24] | Commodore-Mensah Y, Agyemang C, Aboagye JA, et al. Obesity and cardiovascular disease risk among Africans residing in Europe and Africa: the RODAM study. Obes Res Clin Pract. 2020; 14 (2): 151-157. doi: 10.1016/j.orcp.2020.01.007. |
[25] | Chido-Amajuoyi OG, Fueta P, Mantey D. Age at Smoking Initiation and Prevalence of Cigarette Use Among Youths in Sub-Saharan Africa, 2014-2017. JAMA Netw Open. 2021; 4 (5): e218060. doi: 10.1001/jamanetworkopen.2021.8060. |
[26] | Titty FK. Glycaemic control, dyslipidaemia and metabolic syndrome among recently diagnosed diabetes mellitus patients in Tamale Teaching Hospital, Ghana. West Afr J Med. 2010; 29 (1): 8-11. doi: 10.4314/wajm.v29i1.55946. |
[27] | Nyiambam W, Sylverken AA, Owusu IK, Buabeng KO, Boateng FA, Owusu-Dabo E. Cardiovascular disease risk assessment among patients attending two cardiac clinics in the Ashanti Region of Ghana. Ghana Med J. 2020; 54 (3): 140-145. doi: 10.4314/gmj.v54i3.3. |
[28] | Garg N, Muduli SK, Kapoor A, et al. Comparison of different cardiovascular risk score calculators for cardiovascular risk prediction and guideline recommended statin uses. Indian Heart J. 2017; 69 (4): 458-463. doi: 10.1016/j.ihj.2017.01.015. |
[29] | Orimoloye OA, Budoff MJ, Dardari ZA, et al. Race/ethnicity and the prognostic implications of coronary artery calcium for all-cause and cardiovascular disease mortality: The coronary artery calcium consortium. J Am Heart Assoc. 2018; 7 (20). doi: 10.1161/JAHA.118.010471. |
[30] | Mosepele M, Hemphill LC, Palai T, et al. Cardiovascular disease risk prediction by the American College of Cardiology (ACC)/American Heart Association (AHA) Atherosclerotic Cardiovascular Disease (ASCVD) risk score among HIV-infected patients in sub-Saharan Africa. PLoS One. 2017; 12 (2). doi: 10.1371/journal.pone.0172897. |
[31] | Oulhaj A, Bakir S, Aziz F, et al. Agreement between cardiovascular disease risk assessment tools: An application to the United Arab Emirates population. PLoS One. 2020; 15 (1). doi: 10.1371/journal.pone.0228031. |
[32] | Selvarajah S, Kaur G, Haniff J, et al. Comparison of the Framingham Risk Score, SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population. Int J Cardiol. 2014; 176 (1): 211-218. doi: 10.1016/j.ijcard.2014.07.066. |
[33] | Otgontuya D, Oum S, Buckley BS, Bonita R. Assessment of total cardiovascular risk using WHO/ISH risk prediction charts in three low and middle income countries in Asia. BMC Public Health. 2013; 13 (1): 1. doi: 10.1186/1471-2458-13-539. |
APA Style
Shiako Joshua Tei, Dassah Ebenezer, Adu-Gyamfi Adwoa Agyemang, Brenyah Joseph Kwasi. (2023). Distribution of Cardiovascular Risk Among Diabetic Patients in Kumasi. Cardiology and Cardiovascular Research, 7(3), 50-56. https://doi.org/10.11648/j.ccr.20230703.11
ACS Style
Shiako Joshua Tei; Dassah Ebenezer; Adu-Gyamfi Adwoa Agyemang; Brenyah Joseph Kwasi. Distribution of Cardiovascular Risk Among Diabetic Patients in Kumasi. Cardiol. Cardiovasc. Res. 2023, 7(3), 50-56. doi: 10.11648/j.ccr.20230703.11
AMA Style
Shiako Joshua Tei, Dassah Ebenezer, Adu-Gyamfi Adwoa Agyemang, Brenyah Joseph Kwasi. Distribution of Cardiovascular Risk Among Diabetic Patients in Kumasi. Cardiol Cardiovasc Res. 2023;7(3):50-56. doi: 10.11648/j.ccr.20230703.11
@article{10.11648/j.ccr.20230703.11, author = {Shiako Joshua Tei and Dassah Ebenezer and Adu-Gyamfi Adwoa Agyemang and Brenyah Joseph Kwasi}, title = {Distribution of Cardiovascular Risk Among Diabetic Patients in Kumasi}, journal = {Cardiology and Cardiovascular Research}, volume = {7}, number = {3}, pages = {50-56}, doi = {10.11648/j.ccr.20230703.11}, url = {https://doi.org/10.11648/j.ccr.20230703.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ccr.20230703.11}, abstract = {Cardiovascular diseases (CVDs) are the leading cause of mortality globally. Cardiovascular risk scores are reliable tools used to predict an individual’s chance of developing a cardiovascular event. This study assesses the distribution of cardiovascular risk among diabetic patients attending a diabetic clinic in a district hospital in Kumasi. This is a hospital-based cross-sectional study among 94 diabetic patients attending a diabetic clinic in Kumasi, Ghana. Data collected includes sociodemographic information, anthropometry, medical history and lipid profile which were then used to compute the cardiovascular risk score using the pooled cohort equation (PCE) and WHO non-laboratory scoring tools. The average risk score was 13.5% [CI 95: 10.8 – 16.1] according to the PCE tool and 7.2% [CI 95: 6.2 – 8.1] according to the WHO non-laboratory risk scoring tool. The PCE categorised 52.1%, 25.5% and 22.3% as low, moderate and high risk respectively whiles the WHO non-lab categorised 78.7% and 21.3% as low and moderate risk respectively, with no one at high risk. Majority of our study participants were at low risk of developing a cardiovascular event in 10-years according to both tools. There was significant difference between the pooled cohort equation and WHO non-lab risk scoring calculators.}, year = {2023} }
TY - JOUR T1 - Distribution of Cardiovascular Risk Among Diabetic Patients in Kumasi AU - Shiako Joshua Tei AU - Dassah Ebenezer AU - Adu-Gyamfi Adwoa Agyemang AU - Brenyah Joseph Kwasi Y1 - 2023/08/05 PY - 2023 N1 - https://doi.org/10.11648/j.ccr.20230703.11 DO - 10.11648/j.ccr.20230703.11 T2 - Cardiology and Cardiovascular Research JF - Cardiology and Cardiovascular Research JO - Cardiology and Cardiovascular Research SP - 50 EP - 56 PB - Science Publishing Group SN - 2578-8914 UR - https://doi.org/10.11648/j.ccr.20230703.11 AB - Cardiovascular diseases (CVDs) are the leading cause of mortality globally. Cardiovascular risk scores are reliable tools used to predict an individual’s chance of developing a cardiovascular event. This study assesses the distribution of cardiovascular risk among diabetic patients attending a diabetic clinic in a district hospital in Kumasi. This is a hospital-based cross-sectional study among 94 diabetic patients attending a diabetic clinic in Kumasi, Ghana. Data collected includes sociodemographic information, anthropometry, medical history and lipid profile which were then used to compute the cardiovascular risk score using the pooled cohort equation (PCE) and WHO non-laboratory scoring tools. The average risk score was 13.5% [CI 95: 10.8 – 16.1] according to the PCE tool and 7.2% [CI 95: 6.2 – 8.1] according to the WHO non-laboratory risk scoring tool. The PCE categorised 52.1%, 25.5% and 22.3% as low, moderate and high risk respectively whiles the WHO non-lab categorised 78.7% and 21.3% as low and moderate risk respectively, with no one at high risk. Majority of our study participants were at low risk of developing a cardiovascular event in 10-years according to both tools. There was significant difference between the pooled cohort equation and WHO non-lab risk scoring calculators. VL - 7 IS - 3 ER -