Ten-years cardiovascular risk among Bangladeshi population using non-laboratory-based risk chart of the World Health Organization: Findings from a nationally representative survey

• Published in: PloS one Vol. 16; no. 5; p. e0251967
• Main Authors: Hanif, Abu Abdullah Mohammad, Hasan, Mehedi, Khan, Md Showkat Ali, Hossain, Md. Mokbul, Shamim, Abu Ahmed, Hossaine, Moyazzam, Ullah, Mohammad Aman, Sarker, Samir Kanti, Rahman, S. M Mustafizur, Bulbul, Md Mofijul Islam, Mitra, Dipak Kumar, Mridha, Malay Kanti
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 26.05.2021; Public Library of Science (PLoS)
• Subjects: Age groups; Biology and Life Sciences; Blood pressure; Cardiovascular diseases; Charts; Cholesterol; Computer and Information Sciences; Diabetes; Diabetes mellitus; Diseases; Editing; Evaluation; Exercise; Food service; Ghettos; Health risks; Health surveillance; Heart; Households; Laboratories; Low income groups; Medical personnel; Medicine and Health Sciences; Methodology; Nutrition; Older people; People and Places; Population; Public health; Public health administration; Risk assessment; Risk factors; Rural areas; Sample size; Sampling techniques; Smoking; Social Sciences; Bangladesh
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0251967

The World Health Organization (WHO) has recently developed a non-laboratory based cardiovascular disease (CVD) risk chart considering the parameters age, sex, current smoking status, systolic blood pressure, and body mass index. Using the chart, we estimated the 10-years CVD risk among the Bangladeshi population aged 40-74 years. We analyzed data from a nationally representative survey conducted in 2018-19. The survey enrolled participants from 82 clusters (57 rural, 15 non-slum urban, and 10 slums) selected by multistage cluster sampling. Using the non-laboratory-based CVD risk chart of the World Health Organization (WHO), we categorized the participants into 5 risk groups: very low (<5%), low (5% to <10%), moderate (10% to <20%), high (20% to = 30%) risk. We performed descriptive analyses to report the distribution of CVD risk and carried out univariable and multivariable logistic regression to identify factors associated with elevated CVD risk (> = 10% CVD risk). Of the 7,381 participants, 46.0% were female. The median age (IQR) was 59.0 (48.0-64.7) years. Overall, the prevalence of very low, low, moderate, high, and very high CVD risk was 34.7%, 37.8%, 25.9%, 1.6%, and 0.1%, respectively. Elevated CVD risk (> = 10%) was associated with poor education, currently unmarried, insufficient physical inactivity, smokeless tobacco use, and self-reported diabetes in both sexes, higher household income, and higher sedentary time among males, and slum-dwelling and non-Muslim religions among females. One in every four Bangladeshi adults had elevated levels of CVD risk, and males are at higher risk of occurring CVD events. Non-laboratory-based risk prediction charts can be effectively used in low resource settings. The government of Bangladesh and other developing countries should train the primary health care workers on the use of WHO non-laboratory-based CVD risk charts, especially in settings where laboratory tests are not available.