METHODS: Disproportionate stratified sampling followed by systematic sampling were used in 3568 (total) respondents of whom 2743 were non-diabetics, 179 newly diagnosed diabetics and 150 known diabetics. Amongst the diabetics, there were 185 Chinese, 66 Malays and 78 Asian Indians. Diagnosis of diabetes mellitus (DM) was based on the 2 h glucose alone, after a 75 g oral glucose tolerance test. Blood pressure (BP), lipid profile, glucose, insulin and anthropometric indices were obtained from all subjects.
RESULTS: Subjects with diabetes (new and known) exhibited significantly higher triglyceride (TG), lower high density lipoprotein cholesterol (HDL-C) and low density lipoprotein (LDL)/apolipoprotein B (apo B) ratio (LDL size) compared with normoglycaemic subjects. They were more obese (generalised and central) and had higher systolic and diastolic BP. There was no difference in lipid risk factors between the two groups with diabetes although those with new diabetes were more obese whilst those with known diabetes had higher fasting glucose. Amongst subjects with diabetes, there were no significant differences between ethnic groups in TG, HDL-C, LDL/apo B ratio, or waist to hip ratio (WHR). Female Malays with diabetes had higher total cholesterol and were more obese whilst male Asian Indians with diabetes had higher fasting insulin.
CONCLUSION: Asian Indians had lower HDL-C and LDL/apo B ratio than Chinese or Malays amongst normoglycaemic subjects. However, these differences between ethnic groups were not seen in subjects with DM.
METHODS: This study included 1740 males (1146 Chinese, 327 Malays and 267 Asian Indians) and 1950 females (1329 Chinese, 360 Malays and 261 Asian Indians) with complete data on anthropometric indices, fasting lipids, smoking status, alcohol consumption, exercise frequency and genotype at the APOE locus.
RESULTS: Malays and Asian Indians were more obese compared with the Chinese. Smoking was uncommon in all females but Malay males had significantly higher prevalence of smokers. Malays had the highest LDL-C whilst Indians had the lowest HDL-C, The epsilon 3 allele was the most frequent allele in all three ethnic groups. Malays had the highest frequency of epsilon 4 (0.180 and 0.152) compared with Chinese (0.085 and 0.087) and Indians (0.108 and 0.075) in males and females, respectively. The epsilon 2 allele was the least common in Asian Indians. Total cholesterol (TC) and LDL-C was highest in epsilon 4 carriers and lowest in epsilon 2 carriers. The reverse was seen in HDL-C with the highest levels seen in epsilon 2 subjects. The association between ethnic group and HDL-C differed according to APOE genotype and gender. Asian Indians had the lowest HDL-C for each APOE genotype except in Asian Indian males with epsilon 2, where HDL-C concentrations were intermediate between Chinese and Malays.
CONCLUSION: Ethnic differences in lipid profile could be explained in part by the higher prevalence of epsilon 4 in the Malays. Ethnicity may influence the association between APOE genotypes and HDL-C. APOE genotype showed no correlation with HDL-C in Malay males whereas the association in Asian Indians was particularly marked. Further studies of interactions between genes and environmental factors will contribute to the understanding of differences of coronary risk amongst ethnic groups.
METHODS: Lead Investigators from countries formally involved in the EAS FHSC by mid-May 2018 were invited to provide a brief report on FH status in their countries, including available information, programmes, initiatives, and management.
RESULTS: 63 countries provided reports. Data on FH prevalence are lacking in most countries. Where available, data tend to align with recent estimates, suggesting a higher frequency than that traditionally considered. Low rates of FH detection are reported across all regions. National registries and education programmes to improve FH awareness/knowledge are a recognised priority, but funding is often lacking. In most countries, diagnosis primarily relies on the Dutch Lipid Clinics Network criteria. Although available in many countries, genetic testing is not widely implemented (frequent cost issues). There are only a few national official government programmes for FH. Under-treatment is an issue. FH therapy is not universally reimbursed. PCSK9-inhibitors are available in ∼2/3 countries. Lipoprotein-apheresis is offered in ∼60% countries, although access is limited.
CONCLUSIONS: FH is a recognised public health concern. Management varies widely across countries, with overall suboptimal identification and under-treatment. Efforts and initiatives to improve FH knowledge and management are underway, including development of national registries, but support, particularly from health authorities, and better funding are greatly needed.
METHODS: This was a cross-sectional study involving PCP with ≥1-year working experience in Malaysian primary care settings. An adapted and validated 25-item FH-KAP questionnaire was disseminated during primary care courses. Total score for each domain was calculated by summing-up the correct responses, converted into percentage scores. Normality distribution was examined and comparisons of mean/median percentage scores were made between the two groups of PCP.
RESULTS: A total of 372 PCP completed the questionnaire. Regarding knowledge, 77.7% correctly defined FH. However, only 8.3% correctly identified coronary artery disease risk in untreated FH. The mean percentage knowledge score was significantly higher in PCP-PG-Qual compared to PCP-noPG-Qual (48.9, SD ± 13.92 vs. 35.2, SD ± 14.13), t(370) = 8.66, p
METHODS: FH patients attending clinics in seven countries were invited to participate in a cross-sectional survey study. Consenting patients (N = 551) completed self-report measures of generalized beliefs about medication overuse and harms, beliefs in treatment effectiveness, specific beliefs about taking medication (attitudes, subjective norms, perceived behavioral control), and intentions to take medication. Participants also completed measures of demographic variables (age, gender, education level, income, cardiovascular disease status). Data were analysed using path analysis controlling for country and demographic variables.
RESULTS: Attitudes (β = .331, p<0.001), subjective norms (β = .121, p=0.009), and beliefs about medication overuse (β = -.160, p<0.001) were significant predictors of intentions to take medication. Treatment beliefs predicted intentions indirectly (β = .088, p<0.001) through attitudes and subjective norms. There was also an indirect effect of beliefs about medication overuse on intentions (β = -.045, p=0.056), but the effect was small compared with the direct effect.
CONCLUSIONS: The findings indicate the importance among FH patients of specific beliefs about taking medication and generalized beliefs about medication overuse and treatment in predicting medication intentions. When managing patients, clinicians should emphasize the efficacy of taking cholesterol-lowering drugs and the importance of treatment outcomes, and allay concerns about medication overuse.
METHODS: A systematic review was performed for all the articles retrieved from multiple databases, up until March 2017. Data were extracted from all eligible studies, and meta-analysis was carried out using RevMan 5.3 and R package 3.2.1. The strength of association between each studied polymorphism and ischemic stroke risk was measured as odds ratios (ORs) and 95% confidence intervals (CIs), under fixed- and random-effect models.
RESULTS: A total of 79 studies reporting on the association between the studied polymorphisms and ischemic stroke risk were identified. The pooled data indicated that all genetic models of APOA5 rs662799 (ORs = 1.23-1.43), allelic and over-dominant models of APOA5 rs3135506 (ORs = 1.77-1.97), APOB rs1801701 (ORs = 1.72-2.13) and APOB rs1042031 (ORs = 1.66-1.88) as well as dominant model of ABCA1 rs2230806 (OR = 1.31) were significantly associated with higher risk of ischemic stroke. However, no significant associations were observed between ischemic stroke and the other five polymorphisms, namely ApoB (rs693) and APOC3 (rs4520, rs5128, rs2854116 and rs2854117), under any genetic model.
CONCLUSIONS: The present meta-analysis confirmed a significant association of APOA5 rs662799 CC, APOA5 rs3135506 CG, APOB rs1801701 GA, APOB rs1042031 GA and ABCA1 rs2230806 GG with increased risk of ischemic stroke.