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  1. Selvarajah S, Haniff J, Kaur G, Guat Hiong T, Bujang A, Chee Cheong K, et al.
    PMID: 23442728 DOI: 10.1186/1471-2261-13-10
    Recent increases in cardiovascular risk-factor prevalences have led to new national policy recommendations of universal screening for primary prevention of cardiovascular disease in Malaysia. This study assessed whether the current national policy recommendation of universal screening was optimal, by comparing the effectiveness and impact of various cardiovascular screening strategies.
    Matched MeSH terms: Cardiovascular Diseases/economics
  2. Rosengren A, Smyth A, Rangarajan S, Ramasundarahettige C, Bangdiwala SI, AlHabib KF, et al.
    Lancet Glob Health, 2019 06;7(6):e748-e760.
    PMID: 31028013 DOI: 10.1016/S2214-109X(19)30045-2
    BACKGROUND: Socioeconomic status is associated with differences in risk factors for cardiovascular disease incidence and outcomes, including mortality. However, it is unclear whether the associations between cardiovascular disease and common measures of socioeconomic status-wealth and education-differ among high-income, middle-income, and low-income countries, and, if so, why these differences exist. We explored the association between education and household wealth and cardiovascular disease and mortality to assess which marker is the stronger predictor of outcomes, and examined whether any differences in cardiovascular disease by socioeconomic status parallel differences in risk factor levels or differences in management.

    METHODS: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family.

    FINDINGS: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (pinteraction<0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (pinteraction<0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (pinteraction<0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries.

    INTERPRETATION: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education.

    FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).

    Matched MeSH terms: Cardiovascular Diseases/economics
  3. Selvarajah S, Haniff J, Kaur G, Hiong TG, Cheong KC, Lim CM, et al.
    Eur J Prev Cardiol, 2013 Apr;20(2):368-75.
    PMID: 22345688 DOI: 10.1177/2047487312437327
    BACKGROUND: This study aimed to estimate the prevalence of cardiovascular risk factors and its clustering. The findings are to help shape the Malaysian future healthcare planning for cardiovascular disease prevention and management.
    METHODS: Data from a nationally representative cross-sectional survey was used. The survey was conducted via a face-to-face interview using a standardised questionnaire. A total of 37,906 eligible participants aged 18 years and older was identified, of whom 34,505 (91%) participated. Focus was on hypertension, hyperglycaemia (diabetes and impaired fasting glucose), hypercholesterolaemia and central obesity.
    RESULTS: Overall, 63% (95% confidence limits 62, 65%) of the participants had at least one cardiovascular risk factor, 33% (32, 35%) had two or more and 14% (12, 15%) had three risk factors or more. The prevalence of hypertension, hyperglycaemia, hypercholesterolaemia and central obesity were 38%, 15%, 24% and 37%, respectively. Women were more likely to have a higher number of cardiovascular risk factors for most age groups; adjusted odds ratios ranging from 1.1 (0.91, 1.32) to 1.26 (1.12, 1.43) for the presence of one risk factor and 1.07 (0.91, 1.32) to 2.00 (1.78, 2.25) for two or more risk factors.
    CONCLUSIONS: Cardiovascular risk-factor clustering provides a clear impression of the true burden of cardiovascular disease risk in the population. Women displayed higher prevalence and a younger age shift in clustering was seen. These findings signal the presence of a cardiovascular epidemic in an upcoming middle-income country and provide evidence that drastic measures have to be taken to safeguard the health of the nation.
    Study name: National Health and Morbidity Survey (NHMS-2006)
    Matched MeSH terms: Cardiovascular Diseases/economics
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