BMC Cardiovascular Disorders (Mar 2020)

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

  • Olaniyan Akintunde Babatunde,
  • Sunday Olakunle Olarewaju,
  • Adeleye Abiodun Adeomi,
  • Joel Olufunminiyi Akande,
  • Adebobola Bashorun,
  • Chukwuma David Umeokonkwo,
  • James Olusegun Bamidele

DOI
https://doi.org/10.1186/s12872-020-01438-9
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 10

Abstract

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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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