10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria

Abstract Background Globally, cardiovascular diseases (CVDs) have continued to ravage the human existence through the premature deaths of its workforce. Despite this burden, many studies in Nigeria have focused on determining the prevalence of risk factors which alone are insufficient to assess the...

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Main Authors: Olaniyan Akintunde Babatunde, Sunday Olakunle Olarewaju, Adeleye Abiodun Adeomi, Joel Olufunminiyi Akande, Adebobola Bashorun, Chukwuma David Umeokonkwo, James Olusegun Bamidele
Format: Article
Language:English
Published: BMC 2020-03-01
Series:BMC Cardiovascular Disorders
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12872-020-01438-9
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author Olaniyan Akintunde Babatunde
Sunday Olakunle Olarewaju
Adeleye Abiodun Adeomi
Joel Olufunminiyi Akande
Adebobola Bashorun
Chukwuma David Umeokonkwo
James Olusegun Bamidele
author_facet Olaniyan Akintunde Babatunde
Sunday Olakunle Olarewaju
Adeleye Abiodun Adeomi
Joel Olufunminiyi Akande
Adebobola Bashorun
Chukwuma David Umeokonkwo
James Olusegun Bamidele
author_sort Olaniyan Akintunde Babatunde
collection DOAJ
description Abstract Background Globally, cardiovascular diseases (CVDs) have continued to ravage the human existence through the premature deaths of its workforce. Despite this burden, many studies in Nigeria have focused on determining the prevalence of risk factors which alone are insufficient to assess the risk of future cardiovascular events. Therefore, we determined the pattern and predictors of 10-year risk for CVDs in South-western Nigeria. Methods We conducted a cross-sectional study among workers at the local government areas (LGAs) of Oyo State. Using a multi-stage sampling technique, we recruited 260 respondents from the LGA secretariats. A pre-tested, interviewer-administered questionnaire was administered to obtain information on the socio-demographics and behavioural attributes. Lipid analysis, anthropometric, blood pressure, fasting blood glucose measurements were done using standard protocols. The respondents’ CVD risk was assessed using WHO prediction chart. Data were analyzed using IBM SPSS version 25; bivariate analysis was done using Chi-square and binary logistic regression was used to identify the predictors of 10-year risk for CVDs at 5% level of significance. Results The mean age of respondents was 46.0 + 6.7 years. The proportion of respondents with good knowledge of risk factors was 57.7%. The prevalence of CVD risk factors were as follows: systolic hypertension (29.6%), visceral obesity (35.8%), diabetes mellitus (18.8%), smoking (5.8%), elevated total cholesterol (55.4%) and physical inactivity (84.6%). The proportion of respondents with low, moderate and high risk of developing CVDs within 10 years was 76.9, 8.5 and 14.6% respectively. Respondents with age ≥ 40 years (aOR = 2.6, 95% CI = 1.3–8.5), management cadre (aOR = 3.8, 95% CI = 1.6–9.6), obesity (aOR = 4.8, 95% CI = 1.2–120), abnormal waist circumference (aOR = 2.8, 95% CI = 1.3–5.2) and physical inactivity (aOR = 2.4, 95% CI = 1.2–4.7) were associated with the higher likelihood of developing CVDs. Conclusion About one-sixth of the respondents had high risk of developing CVDs within the next 10 years and it is likely that it will reduce the productivity of the State. Lifestyle modification and early detection of risk factors through regular screening programmes for those with high CVD risk is therefore recommended.
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spelling doaj.art-87493adb5fa04b93808477055a931b3b2022-12-21T17:48:38ZengBMCBMC Cardiovascular Disorders1471-22612020-03-0120111010.1186/s12872-020-01438-910-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western NigeriaOlaniyan Akintunde Babatunde0Sunday Olakunle Olarewaju1Adeleye Abiodun Adeomi2Joel Olufunminiyi Akande3Adebobola Bashorun4Chukwuma David Umeokonkwo5James Olusegun Bamidele6Department of Community Medicine, Ladoke Akintola University of TechnologyDepartment of Community Medicine, Osun State UniversityDepartment of Community Medicine, Obafemi Awolowo UniversityDepartment of Chemical Pathology, BOWEN University Teaching HospitalAfrican Field Epidemiology NetworkNigeria Field Epidemiology and Laboratory Training ProgramDepartment of Community Medicine, Ekiti State UniversityAbstract Background Globally, cardiovascular diseases (CVDs) have continued to ravage the human existence through the premature deaths of its workforce. Despite this burden, many studies in Nigeria have focused on determining the prevalence of risk factors which alone are insufficient to assess the risk of future cardiovascular events. Therefore, we determined the pattern and predictors of 10-year risk for CVDs in South-western Nigeria. Methods We conducted a cross-sectional study among workers at the local government areas (LGAs) of Oyo State. Using a multi-stage sampling technique, we recruited 260 respondents from the LGA secretariats. A pre-tested, interviewer-administered questionnaire was administered to obtain information on the socio-demographics and behavioural attributes. Lipid analysis, anthropometric, blood pressure, fasting blood glucose measurements were done using standard protocols. The respondents’ CVD risk was assessed using WHO prediction chart. Data were analyzed using IBM SPSS version 25; bivariate analysis was done using Chi-square and binary logistic regression was used to identify the predictors of 10-year risk for CVDs at 5% level of significance. Results The mean age of respondents was 46.0 + 6.7 years. The proportion of respondents with good knowledge of risk factors was 57.7%. The prevalence of CVD risk factors were as follows: systolic hypertension (29.6%), visceral obesity (35.8%), diabetes mellitus (18.8%), smoking (5.8%), elevated total cholesterol (55.4%) and physical inactivity (84.6%). The proportion of respondents with low, moderate and high risk of developing CVDs within 10 years was 76.9, 8.5 and 14.6% respectively. Respondents with age ≥ 40 years (aOR = 2.6, 95% CI = 1.3–8.5), management cadre (aOR = 3.8, 95% CI = 1.6–9.6), obesity (aOR = 4.8, 95% CI = 1.2–120), abnormal waist circumference (aOR = 2.8, 95% CI = 1.3–5.2) and physical inactivity (aOR = 2.4, 95% CI = 1.2–4.7) were associated with the higher likelihood of developing CVDs. Conclusion About one-sixth of the respondents had high risk of developing CVDs within the next 10 years and it is likely that it will reduce the productivity of the State. Lifestyle modification and early detection of risk factors through regular screening programmes for those with high CVD risk is therefore recommended.http://link.springer.com/article/10.1186/s12872-020-01438-9Cardiovascular diseasesRisk factorsPrevalencePrediction chartCivil servants
spellingShingle Olaniyan Akintunde Babatunde
Sunday Olakunle Olarewaju
Adeleye Abiodun Adeomi
Joel Olufunminiyi Akande
Adebobola Bashorun
Chukwuma David Umeokonkwo
James Olusegun Bamidele
10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria
BMC Cardiovascular Disorders
Cardiovascular diseases
Risk factors
Prevalence
Prediction chart
Civil servants
title 10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria
title_full 10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria
title_fullStr 10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria
title_full_unstemmed 10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria
title_short 10-year risk for cardiovascular diseases using WHO prediction chart: findings from the civil servants in South-western Nigeria
title_sort 10 year risk for cardiovascular diseases using who prediction chart findings from the civil servants in south western nigeria
topic Cardiovascular diseases
Risk factors
Prevalence
Prediction chart
Civil servants
url http://link.springer.com/article/10.1186/s12872-020-01438-9
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