BURDEN OF RISK FACTORS IN THE PREVENTION OF CARDIOVASCULAR DISEASE AMONG ADULTS IN AKTOBE AND AKTOBE REGION, REPUBLIC OF KAZAKHSTAN

2021

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DOI 10.1097/01.hjh.0000746352.55769.24
Data confidence 70 medium
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Abstract

Objective: The overall goal of the survey was to evaluate the current health status of population one of the regions of Kazakhstan and its components, prevalence of main risk factors of CVDs using a standard WHO methodology designed to assess risk factors prevalence and renew preventive activities on CVDs using the collected and analyzed data. Design and method: A cross-sectional study was conducted to assess the prevalence and risk factors of CVDs using the WHO STEPS questionnaire survey, physical measurements and biochemical measurements. Sample size was 1,500 people aged 18–69 years. Samples composition: 900 urban and 600 rural population according to the overall urban/rural residents ratio specific for the region. Results: Based on the interview results and physical and biochemical measurements, the following risk factors were used: The percentage of respondents with 0, 1–2 or 3–5 risk factors by age group and sex are presented in table. In 3.56% (95% CI: 2.71–4.41) of the study population, none of the abovementioned five risk factors were identified; 52.54% (95% CI: 51.69–53.39) of the respondents had 1–2 risk factors; and 12.01% (95% CI: 11.16–12.86) has 3–5 of the risk factors listed. Prevalence of 3–5 combined risk factors was much higher in the age group 55–69 years (17.28, 95% CI:16.44–18.12), while prevalence of 1–2 risk factors was higher in the age group 18–34 years (58.95%, 95% CI: 58.15–59.75). Differences were statistically significant. A higher proportion of men had 3–5 risk factors (22.06%, 95% CI: 21.18–22.94) than women (9.01%, 95% CI: 8.20–9.82). In addition, the percentage of women with 1–2 risk factors (54.37, 95% CI: 53.56–55.18) was higher than that of men (46.42%, 95% CI: 45.54–47.30). Conclusions: Primary prevention continues to evolve and with greater availability of long-term data comes improved understanding of the means by which we can reduce CVD risk.