METHODS: In 14 Central England general practices, a novel case-finding tool (Familial Hypercholetserolaemia Case Ascertainment Tool, FAMCAT1) was applied to the electronic health records of 86 219 patients with cholesterol readings (44.5% of total practices' population), identifying 3375 at increased risk of FH. Of these, a cohort of 336 consenting to completing Family History Questionnaire and detailed review of their clinical data, were offered FH genetic testing in primary care.

RESULTS: Genetic testing was completed by 283 patients, newly identifying 16 with genetically confirmed FH and 10 with variants of unknown significance. All 26 (9%) were recommended for referral and 19 attended specialist assessment. In a further 153 (54%) patients, the test suggested polygenic hypercholesterolaemia who were managed in primary care. Total cholesterol and low-density lipoprotein-cholesterol levels were higher in those patients with FH-causing variants than those with other genetic test results (p=0.010 and p=0.002).

CONCLUSION: Electronic case-finding and genetic testing in primary care could improve identification of FH; and the better targeting of patients for specialist assessment. A significant proportion of patients identified at risk of FH are likely to have polygenic hypercholesterolaemia. There needs to be a clearer management plan for these individuals in primary care.

METHODS: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS: Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

MATERIALS AND METHODS: This cross-sectional study included 150 subjects aged 30 years and above who attended a health screening in a Malaysian tertiary institution. Sociodemographics, clinical characteristics and laboratory parameters (lipids, glucose, and sdLDL) were obtained. Lipoprotein subfraction was analysed using the polyacrylamide gel electrophoresis method.

RESULTS: Malays and females made up the majority of subjects and the median age was 37 years. Normolipidaemic Pattern B was significantly higher in women (p=0.008). Significant independent predictors of Pattern B were gender (p=0.02), race (p=0.01), body mass index (BMI) [p=0.02] and lipid status (p=0.01). Triglyceride was the only independent predictor of sdLDL (p=0.001).

METHODS: A total of 200 participants (n = 100 kratom users and n = 100 healthy subjects who do not use kratom) were recruited for this analytical cross-sectional study. Data on sociodemographic status, kratom use characteristics, cigarette smoking, physical activity, body mass index (BMI), fasting serum lipid profile, and liver function were collected from all participants.

RESULTS: The liver parameters of the study participants were within normal range. The serum total cholesterol and LDL of kratom users were significantly lower than those of healthy subjects who do not use kratom. There were no significant differences in the serum triglyceride and HDL levels. However, higher average daily frequency of kratom use and increasing age were associated with increased serum total cholesterol among kratom users. Other kratom use characteristics such as age of first kratom intake, duration of kratom use, and quantity of daily kratom intake were not associated with increased serum triglyceride, total cholesterol, LDL, and HDL levels.

OBJECTIVE: To analyze trends in levels of lipids and apolipoprotein B in US youths during 18 years from 1999 through 2016.

DESIGN, SETTING, AND PARTICIPANTS: Serial cross-sectional analysis of US population-weighted data for youths aged 6 to 19 years from the National Health and Nutrition Examination Surveys for 1999 through 2016. Linear temporal trends were analyzed using multivariable regression models with regression coefficients (β) reported as change per 1 year.

EXPOSURES: Survey year; examined periods spanned 10 to 18 years based on data availability.

MAIN OUTCOMES AND MEASURES: Age- and race/ethnicity-adjusted mean levels of high-density lipoprotein (HDL), non-HDL, and total cholesterol. Among fasting adolescents (aged 12-19 years), mean levels of low-density lipoprotein cholesterol, geometric mean levels of triglycerides, and mean levels of apolipoprotein B. Prevalence of ideal and adverse (vs borderline) levels of lipids and apolipoprotein B per pediatric lipid guidelines.

RESULTS: In total, 26 047 youths were included (weighted mean age, 12.4 years; female, 51%). Among all youths, the adjusted mean total cholesterol level declined from 164 mg/dL (95% CI, 161 to 167 mg/dL) in 1999-2000 to 155 mg/dL (95% CI, 154 to 157 mg/dL) in 2015-2016 (β for linear trend, -0.6 mg/dL [95% CI, -0.7 to -0.4 mg/dL] per year). Adjusted mean HDL cholesterol level increased from 52.5 mg/dL (95% CI, 51.7 to 53.3 mg/dL) in 2007-2008 to 55.0 mg/dL (95% CI, 53.8 to 56.3 mg/dL) in 2015-2016 (β, 0.2 mg/dL [95% CI, 0.1 to 0.4 mg/dL] per year) and non-HDL cholesterol decreased from 108 mg/dL (95% CI, 106 to 110 mg/dL) to 100 mg/dL (95% CI, 99 to 102 mg/dL) during the same years (β, -0.9 mg/dL [95% CI, -1.2 to -0.6 mg/dL] per year). Among fasting adolescents, geometric mean levels of triglycerides declined from 78 mg/dL (95% CI, 74 to 82 mg/dL) in 1999-2000 to 63 mg/dL (95% CI, 58 to 68 mg/dL) in 2013-2014 (log-transformed β, -0.015 [95% CI, -0.020 to -0.010] per year), mean levels of low-density lipoprotein cholesterol declined from 92 mg/dL (95% CI, 89 to 95 mg/dL) to 86 mg/dL (95% CI, 83 to 90 mg/dL) during the same years (β, -0.4 mg/dL [95% CI, -0.7 to -0.2 mg/dL] per year), and mean levels of apolipoprotein B declined from 70 mg/dL (95% CI, 68 to 72 mg/dL) in 2005-2006 to 67 mg/dL (95% CI, 65 to 70 mg/dL) in 2013-2014 (β, -0.4 mg/dL [95% CI, -0.7 to -0.04 mg/dL] per year). Favorable trends were generally also observed in the prevalence of ideal and adverse levels. By the end of the study period, 51.4% (95% CI, 48.5% to 54.2%) of all youths had ideal levels for HDL, non-HDL, and total cholesterol; among adolescents, 46.8% (95% CI, 40.9% to 52.6%) had ideal levels for all lipids and apolipoprotein B, whereas 15.2% (95% CI, 13.1% to 17.3%) of children aged 6 to 11 years and 25.2% (95% CI, 22.2% to 28.2%) of adolescents aged 12 to 19 years had at least 1 adverse level.

METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.

OBJECTIVE: We aimed to identify a posteriori dietary patterns for Chinese, Malay, and Indian ethnic groups in an urban Asian setting, compare these with a priori dietary patterns, and ascertain associations with cardiovascular disease risk factors including hypertension, obesity, and abnormal blood lipid concentrations.

METHODS: We used cross-sectional data from 8433 Singapore residents (aged 21-94 y) from the Multi-Ethnic Cohort study of Chinese, Malay, and Indian ethnicity. Food consumption was assessed using a validated 169-item food-frequency questionnaire. With the use of 28 food groups, dietary patterns were derived by principal component analysis, and their association with cardiovascular disease risk factors was assessed using multiple linear regression. Associations between derived patterns and a priori patterns (aHEI-2010-Alternative Healthy Eating Index-2010, aMED-alternate Mediterranean Diet, and DASH-Dietary Approaches to Stop Hypertension) were assessed, and the magnitude of associations with risk factors compared.

RESULTS: We identified a "healthy" dietary pattern, similar across ethnic groups, and characterized by high intakes of whole grains, fruit, dairy, vegetables, and unsaturated cooking oil and low intakes of Western fast foods, sugar-sweetened beverages, poultry, processed meat, and flavored rice. This "healthy" pattern was inversely associated with body mass index (BMI; in kg/m2) (-0.26 per 1 SD of the pattern score; 95% CI: -0.36, -0.16), waist circumference (-0.57 cm; 95% CI: -0.82, -0.32), total cholesterol (-0.070 mmol/L; 95% CI: -0.091, -0.048), LDL cholesterol (-0.054 mmol/L; 95% CI: -0.074, -0.035), and fasting triglycerides (-0.22 mmol/L; 95% CI: -0.04, -0.004) and directly associated with HDL cholesterol (0.013 mmol/L; 95% CI: 0.006, 0.021). Generally, "healthy" pattern associations were at least as strong as a priori pattern associations with cardiovascular disease risk factors.

DESIGN: Two cross-sectional studies using the WHO STEPS methodology.

SETTING: Both the urban and rural areas of the Yangon Region, Myanmar.

PARTICIPANTS: A total of 1370 men and women aged 25-74 years participated based on a multistage cluster sampling. Physically and mentally ill people, monks, nuns, soldiers and institutionalised people were excluded.

RESULTS: Compared with rural counterparts, urban dwellers had a significantly higher age-standardised prevalence of hypercholesterolaemia (50.7% vs 41.6%; p=0.042) and a low HDL level (60.6% vs 44.4%; p=0.001). No urban-rural differences were found in the prevalence of hypertriglyceridaemia and high LDL. Men had a higher age-standardised prevalence of hypertriglyceridaemia than women (25.1% vs 14.8%; p<0.001), while the opposite pattern was found in the prevalence of a high LDL (11.3% vs 16.3%; p=0.018) and low HDL level (35.3% vs 70.1%; p<0.001).Compared with rural inhabitants, urban dwellers had higher age-standardised mean levels of total cholesterol (5.31 mmol/L, SE: 0.044 vs 5.05 mmol/L, 0.068; p=0.009), triglyceride (1.65 mmol/L, 0.049 vs 1.38 mmol/L, 0.078; p=0.017), LDL (3.44 mmol/L, 0.019 vs 3.16 mmol/L, 0.058; p=0.001) and lower age-standardised mean levels of HDL (1.11 mmol/L, 0.010 vs 1.25 mmol/L, 0.012; p<0.001). In linear regression, the total cholesterol was significantly associated with an urban location among men, but not among women.

METHODS: We recruited 54 abdominally obese subjects to participate in a prospective cross-over design, single-blind trial comparing isocaloric 2000 kcal MUFA or carbohydrate-enriched diet with SFA-enriched diet (control). The control diet consisted of 15E% protein, 53E% carbohydrate and 32E% fat (12E% SFA, 13E% MUFA). A total of ∼7E% of MUFA or refined carbohydrate was exchanged with SFA in the MUFA-rich and carbohydrate-rich diets respectively for 6-weeks. Blood samples were collected at fasting upon trial commencement and at week-5 and 6 of each dietary-intervention phase to measure levels of cytokines (IL-6, IL-1β), C-reactive protein (CRP), thrombogenic markers (E-selectin, PAI-1, D-dimer) and lipid subfractions. Radial pulse wave analysis and a 6-h postprandial mixed meal challenge were carried out at week-6 of each dietary intervention. Blood samples were collected at fasting, 15 and 30 min and hourly intervals thereafter till 6 h after a mixed meal challenge (muffin and milkshake) with SFA or MUFA (872.5 kcal, 50 g fat, 88 g carbohydrates) or CARB (881.3 kcal, 20 g fat, 158 g carbohydrates)- enrichment corresponding to the background diets.