Methods: Analyses were performed on 243 women (mean body mass index 31.27 ± 4.14 kg/m2) who completed a 12-month lifestyle intervention in low socioeconomic communities in Klang Valley, Malaysia. Analysis of covariance (ANCOVA) was used to compare changes of cardiometabolic risk factors across weight change categories (2% gain, ±2% maintain, >2 to <5% loss, and 5 to 20% loss) within intervention and control group.
Results: A graded association for changes in waist circumference, fasting insulin, and total cholesterol (p=0.002, for all variables) across the weight change categories were observed within the intervention group at six months postintervention. Participants who lost 5 to 20% of weight had the greatest improvements in those risk markers (-5.67 cm CI: -7.98 to -3.36, -4.27 μU/mL CI: -7.35, -1.19, and -0.59 mmol/L CI: -.99, -0.19, respectively) compared to those who did not. Those who lost >2% to <5% weight reduced more waist circumference (-4.24 cm CI: -5.44 to -3.04) and fasting insulin (-0.36 μU/mL CI: -1.95 to 1.24) than those who maintained or gained weight. No significant association was detected in changes of risk markers across the weight change categories within the control group except for waist circumference and adiponectin.
Conclusion: Weight loss of >2 to <5% obtained through lifestyle intervention may represent a reasonable initial weight loss target for women in the low socioeconomic community as it led to improvements in selected risk markers, particularly of diabetes risk.
METHODS: The Prospective Urban Rural Epidemiology study is ongoing in 21 countries. Here we report an analysis done in 18 countries with data on clinical outcomes. Eligible participants were adults aged 35-70 years without cardiovascular disease, sampled from the general population. We used morning fasting urine to estimate 24 h sodium and potassium excretion as a surrogate for intake. We assessed community-level associations between sodium and potassium intake and BP in 369 communities (all >50 participants) and cardiovascular disease and mortality in 255 communities (all >100 participants), and used individual-level data to adjust for known confounders.
FINDINGS: 95 767 participants in 369 communities were assessed for BP and 82 544 in 255 communities for cardiovascular outcomes with follow-up for a median of 8·1 years. 82 (80%) of 103 communities in China had a mean sodium intake greater than 5 g/day, whereas in other countries 224 (84%) of 266 communities had a mean intake of 3-5 g/day. Overall, mean systolic BP increased by 2·86 mm Hg per 1 g increase in mean sodium intake, but positive associations were only seen among the communities in the highest tertile of sodium intake (p<0·0001 for heterogeneity). The association between mean sodium intake and major cardiovascular events showed significant deviations from linearity (p=0·043) due to a significant inverse association in the lowest tertile of sodium intake (lowest tertile <4·43 g/day, mean intake 4·04 g/day, range 3·42-4·43; change -1·00 events per 1000 years, 95% CI -2·00 to -0·01, p=0·0497), no association in the middle tertile (middle tertile 4·43-5·08 g/day, mean intake 4·70 g/day, 4·44-5.05; change 0·24 events per 1000 years, -2·12 to 2·61, p=0·8391), and a positive but non-significant association in the highest tertile (highest tertile >5·08 g/day, mean intake 5·75 g/day, >5·08-7·49; change 0·37 events per 1000 years, -0·03 to 0·78, p=0·0712). A strong association was seen with stroke in China (mean sodium intake 5·58 g/day, 0·42 events per 1000 years, 95% CI 0·16 to 0·67, p=0·0020) compared with in other countries (4·49 g/day, -0·26 events, -0·46 to -0·06, p=0·0124; p<0·0001 for heterogeneity). All major cardiovascular outcomes decreased with increasing potassium intake in all countries.
INTERPRETATION: Sodium intake was associated with cardiovascular disease and strokes only in communities where mean intake was greater than 5 g/day. A strategy of sodium reduction in these communities and countries but not in others might be appropriate.
FUNDING: Population Health Research Institute, Canadian Institutes of Health Research, Canadian Institutes of Health Canada Strategy for Patient-Oriented Research, Ontario Ministry of Health and Long-Term Care, Heart and Stroke Foundation of Ontario, and European Research Council.
CONCLUSION: The risk factors that are reviewed here are hypertension, dyslipidemia, smoking, obesity, lack of exercise, hyperglycemia and diabetic nephropathy. We highlight the importance of early identification, and interventions, which include optimizing glycemic control, pharmacotherapy, regular physical activity and dietary changes.
METHODS: The study was conducted in two stages. First, the factors affecting nutritional behaviors associated with cardiovascular disease on 350 women who were referred to Fasa urban health centers were determined based on the TPB. In the second stage, based on the results of a cross-sectional study, quasi-expeimental study was performed on 200 women covered by Fasa health centers. The questionnaire used for the study was a questionnaire based on TPB. The questionnaire was completed by the experimental and control groups before and three months after the intervention. Data were analyzed by SPSS software using logistic regression, paired t-test, independent sample t-test, and chi-square test. The level of significance is considered 0.05.
RESULT: The constructs of attitude, subjective norms, and perceived behavioral control (PBC) were predictors of nutritional behaviors associated with cardiovascular disease in women. The constructs predicted 41.6% of the behavior. The results showed that mean scores of attitude, subjective norms, PBC, intention, nutritional performance related to the cardiovascular disease before intervention were, respectively, 24.32, 14.20, 18.10, 13.37 and 16.28, and after the intervention, were, respectively, 42.32, 25.40, 33.72, 30.13 and 41.38. All the constructs except the attitude in the intervention group were significantly higher (p cardiovascular disease in women. Considering the role of mothers in providing family food baskets and the effect of their nutritional behaviors on family members, the education of this group can promote healthy eating behaviors in the community and family.
PURPOSE: This paper explores the effects of SQ in CVD.
METHODS: A systematic review of the literature was performed to identify relevant studies about SQ and CVD. A comprehensive search in Medline and Scopus for relevant studies published between the years 1946 and 2019 was performed. The main inclusion criteria were that the study was published in English; that the study reported association or effect of SQ and CVD; and that CVD should be related to lifestyle variables, aging, or experimentally induced conditions.
RESULTS: The literature searches identified 5562 potentially relevant articles, whereby 21 studies met the inclusion criteria. There were three human studies and 18 animal experimental studies included in this paper. Only one human study reported positive outcome of SQ in CVD. The remaining two studies reported inconsistent and/or no effect. For animal studies, 15 studies reported positive effect while the remaining reported negative and/or no effect of SQ on various related parameters.
CONCLUSIONS: This evidence-based review emphasizes the potential of SQ being used for cardiovascular-related diseases. The effect of SQ, especially of plant-based warrants further exploration. Controlled human observational studies should be performed to provide comprehensive evidence.
METHODS: Consecutive NAFLD patients attending five clinics in Asia were included in this study. The 10-year cardiovascular disease risk was calculated based on the Framingham Heart Study, and patients were categorized as moderate, high, or very high risk for cardiovascular disease on the basis of the American Association of Clinical Endocrinologist 2017 Guidelines. The low-density lipoprotein cholesterol treatment goal for each of the risk groups was 2.6, 2.6, and 1.8 mmol/L, respectively.
RESULTS: The data for 428 patients were analyzed (mean age 54.4 ± 11.1 years, 52.1% male). Dyslipidemia was seen in 60.5% (259/428), but only 43.2% (185/428) were on a statin. The percentage of patients who were at moderate, high, and very high risk for cardiovascular disease was 36.7% (157/428), 27.3% (117/428), and 36.0% (154/428), respectively. Among patients who were on a statin, 58.9% (109/185) did not achieve the treatment target. Among patients who were not on a statin, 74.1% (180/243) should be receiving statin therapy. The percentage of patients who were not treated to target or who should be on statin was highest among patients at very high risk for cardiovascular disease at 79.6% (78/98) or 94.6% (53/56), respectively.
CONCLUSION: This study highlights the suboptimal treatment of dyslipidemia and calls for action to improve the treatment of dyslipidemia in NAFLD patients.
AREAS COVERED: We searched PubMed and reviewed literatures related to statin intolerance published between February 2015 and February 2020. Important large-scale or landmark studies published before 2015 were also cited as key evidence.
EXPERT OPINION: Optimal lowering of low-density lipoprotein cholesterol with statins substantially reduces the risk of cardiovascular events. Muscle adverse events (AEs) were the most frequently reported AEs by statin users in clinical practice, but they usually occurred at a similar rate with statins and placebo in randomized controlled trials and had a spurious causal relationship with statin treatment. We proposed a rigorous definition for identifying true statin intolerance and present the criteria for defining different forms of muscle AEs and an algorithm for their management. True statin intolerance is uncommon, and every effort should be made to exclude false statin intolerance and ensure optimal use of statins. For the management of statin intolerance, statin-based approaches should be prioritized over non-statin approaches.
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).