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Reliable information on dietary trends is essential. We compared individual-level dietary estimates for total energy, carbohydrate, fat, and protein intake over time with national supply data from the Global Expanded Nutrient Supply Model (186 paired estimates from 1961 to 2011, 18 countries). We hypothesized that supply data would overestimate individual measures and that the two measures would be weakly correlated. Individual- and supply-level estimates were compared using Spearman correlation coefficients and linear mixed-effect models were used to estimate the differences between measures. Overall, the correlations between individual- and supply-level measures were moderate for energy (r s = 0.34) and carbohydrate (r s = 0.39), strong for fat (r s = 0.85), and protein (r s = 0.69). Trends in total energy measured by individual-level surveys and total energy supply were positively correlated in 38.9% of countries, whereas trends in macronutrients aligned between estimates in most countries. Supply-level dietary data overestimated individual-level intakes, especially in higher income countries in Europe and in the United States. In the United States, supply-level data exceeded individual-level estimates by 26.3% to 29.9% for energy, carbohydrate, and fat, whereas protein estimates were similar between measures. In Europe, supply-level estimates overestimated individual-level intake by 19.9% for energy, 17.0% for carbohydrate, 13.7% for fat, and 7.7% for protein, whereas estimates for energy and macronutrients were similar in Asia. In Asia and lower income countries, our findings generally support the use of supply-level data in the absence of individual-level data, though this finding may be related to smaller sample size and differences in underlying national statistics that inform supply data. This article compares individual-level diet measures of energy, carbohydrate, fat, and protein to national supply-level data in 18 countries. Time trends in macronutrient intake and, to a lesser degree, total energy, align between individual and supply data. Supply data overestimated individual intakes, especially in the United States and higher income countries. Supply data may be an appropriate alternative in Asia and in lower income settings that lack individual data. Abbreviation: 95% CI, 95% confidence interval. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: The association of nuts with cardiovascular disease and deaths has been investigated mostly in Europe, the USA, and East Asia, with few data available from other regions of the world or from low- and middle-income countries., Objective: To assess the association of nuts with mortality and cardiovascular disease (CVD)., Methods: The Prospective Urban Rural Epidemiology study is a large multinational prospective cohort study of adults aged 35-70 y from 16 low-, middle-, and high-income countries on 5 continents. Nut intake (tree nuts and ground nuts) was measured at the baseline visit, using country-specific validated FFQs. The primary outcome was a composite of mortality or major cardiovascular event [nonfatal myocardial infarction (MI), stroke, or heart failure]., Results: We followed 124,329 participants (age = 50.7 y, SD = 10.2; 41.5% male) for a median of 9.5 y. We recorded 10,928 composite events [deaths (n = 8,662) or major cardiovascular events (n = 5,979)]. Higher nut intake (>120 g per wk compared with <30 g per mo) was associated with a lower risk of the primary composite outcome of mortality or major cardiovascular event [multivariate HR (mvHR): 0.88; 95% CI: 0.80, 0.96; P-trend = 0.0048]. Significant reductions in total (mvHR: 0.77; 95% CI: 0.69, 0.87; P-trend <0.0001), cardiovascular (mvHR: 0.72; 95% CI: 0.56, 0.92; P-trend = 0.048), and noncardiovascular mortality (mvHR: 0.82; 95% CI: 0.70, 0.96; P-trend = 0.0046) with a trend to reduced cancer mortality (mvHR: 0.81; 95% CI: 0.65, 1.00; P-trend = 0.081) were observed. No significant associations of nuts were seen with major CVD (mvHR: 0.91; 95% CI: 0.81, 1.02; P-trend = 0.14), stroke (mvHR: 0.98; 95% CI: 0.84, 1.14; P-trend = 0.76), or MI (mvHR: 0.86; 95% CI: 0.72, 1.04; P-trend = 0.29)., Conclusions: Higher nut intake was associated with lower mortality risk from both cardiovascular and noncardiovascular causes in low-, middle-, and high-income countries., (Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.)

Background: The infant gut is rapidly colonized by microorganisms soon after birth, and the composition of the microbiota is dynamic in the first year of life. Although a stable microbiome may not be established until 1 to 3 years after birth, the infant gut microbiota appears to be an important predictor of health outcomes in later life., Methods: We obtained stool at one year of age from 173 white Caucasian and 182 South Asian infants from two Canadian birth cohorts to gain insight into how maternal and early infancy exposures influence the development of the gut microbiota. We investigated whether the infant gut microbiota differed by ethnicity (referring to groups of people who have certain racial, cultural, religious, or other traits in common) and by breastfeeding status, while accounting for variations in maternal and infant exposures (such as maternal antibiotic use, gestational diabetes, vegetarianism, infant milk diet, time of introduction of solid food, infant birth weight, and weight gain in the first year)., Results: We demonstrate that ethnicity and infant feeding practices independently influence the infant gut microbiome at 1 year, and that ethnic differences can be mapped to alpha diversity as well as a higher abundance of lactic acid bacteria in South Asians and a higher abundance of genera within the order Clostridiales in white Caucasians., Conclusions: The infant gut microbiome is influenced by ethnicity and breastfeeding in the first year of life. Ethnic differences in the gut microbiome may reflect maternal/infant dietary differences and whether these differences are associated with future cardiometabolic outcomes can only be determined after prospective follow-up.

Aims: Why South Asians are at increased risk of premature atherosclerotic cardiovascular diseases compared with other ethnic groups is not fully understood. Atherogenic dyslipoproteinemia - hypertriglyceridemia, elevated numbers of low-density lipoprotein (LDL) particles and low high-density lipoprotein cholesterol (HDL-C) - is more common in South Asians but the mechanisms responsible have not been explicated. Here we examined whether the circulating lipid transfer protein, cholesteryl ester transfer protein (CETP), plays a role in the pathogenesis of the atherogenic dyslipoproteinemia among South Asians., Methods and Results: CETP activity was determined by exogenous substrate assay in the serum of healthy, metabolically well-characterized individuals of South Asian and European descent (N = 244 and 238, respectively). Serum and lipoprotein lipids and apolipoproteins were measured and lipoprotein particle number and size were quantified via nuclear magnetic resonance spectroscopy. All the elements of the atherogenic dyslipoproteinemia were more severe in South Asians and CETP activity was significantly greater by 30% in South Asians compared with Europeans, adjusted for age, sex, body mass index and waist circumference (p < 0.0001). CETP activity was directly associated with serum triglycerides and inversely with HDL-C in the whole population. CETP activity was also directly related to apoB and LDL particle number. Finally, increased CETP activity was associated with pro-atherogenic reductions in HDL and LDL particle size., Conclusions: We identified novel associations between elevated CETP activity and the triad of quantitative and qualitative lipoprotein abnormalities in the atherogenic dyslipidemia in South Asians, a major contributor of increased atherosclerotic cardiovascular diseases in South Asians., (© The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

Aims/hypothesis: South Asians are up to four times more likely to develop type 2 diabetes than white Europeans. It is postulated that the higher prevalence results from greater genetic risk. To evaluate this hypothesis, we: (1) systematically reviewed the literature for single nucleotide polymorphisms (SNPs) predisposing to type 2 diabetes in South Asians; (2) compared risk estimates, risk alleles and risk allele frequencies of predisposing SNPs between South Asians and white Europeans; and (3) tested the association of novel SNPs discovered from South Asians in white Europeans., Methods: MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL) and the Cochrane registry were searched for studies of genetic variants associated with type 2 diabetes in South Asians. Meta-analysis estimates for common and novel bi-allelic SNPs in South Asians were compared with white Europeans from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium. The population burden from predisposing SNPs was assessed using a genotype score., Results: Twenty-four SNPs from 21 loci were associated with type 2 diabetes in South Asians after meta-analysis. The majority of SNPs increase odds of the disorder by 15-35% per risk allele. No substantial differences appear to exist in risk estimates between South Asians and white Europeans from SNPs common to both groups, and the population burden also does not differ. Eight of the 24 are novel SNPs discovered from South Asian genome-wide association studies, some of which show nominal associations with type 2 diabetes in white Europeans., Conclusions/interpretation: Based on current literature there is no strong evidence to indicate that South Asians possess a greater genetic risk of type 2 diabetes than white Europeans.

Background: Body mass index (BMI) is widely used to assess risk for cardiovascular disease and type 2 diabetes. Cut points for the classification of obesity (BMI >30 kg/m2) have been developed and validated among people of European descent. It is unknown whether these cut points are appropriate for non-European populations. We assessed the metabolic risk associated with BMI among South Asians, Chinese, Aboriginals, and Europeans., Methods and Results: We randomly sampled 1078 subjects from 4 ethnic groups (289 South Asians, 281 Chinese, 207 Aboriginals, and 301 Europeans) from 4 regions in Canada. Principal components factor analysis was used to derive underlying latent or "hidden" factors associated with 14 clinical and biochemical cardiometabolic markers. Ethnic-specific BMI cut points were derived for 3 cardiometabolic factors. Three primary latent factors emerged that accounted for 56% of the variation in markers of glucose metabolism, lipid metabolism, and blood pressure. For a given BMI, elevated levels of glucose- and lipid-related factors were more likely to be present in South Asians, Chinese, and Aboriginals compared with Europeans, and elevated levels of the blood pressure-related factor were more likely to be present among Chinese compared with Europeans. The cut point to define obesity, as defined by distribution of glucose and lipid factors, is lower by approximately 6 kg/m2 among non-European groups compared with Europeans., Conclusions: Revisions may be warranted for BMI cut points to define obesity among South Asians, Chinese, and Aboriginals. Using these revised cut points would greatly increase the estimated burden of obesity-related metabolic disorders among non-European populations.

Background: Small increases in the inflammatory marker C-reactive protein (CRP) are predictive of vascular events among asymptomatic individuals. There are few data supporting the use of CRP as a risk marker among nonwhite individuals., Methods and Results: 1250 adults of South Asian, Chinese, European, and Aboriginal ancestry were randomly sampled from 4 communities in Canada. Participants provided fasting blood samples for CRP, glucose, lipids, and coagulation factors, and they had undergone a carotid B-mode ultrasound. Cardiovascular disease was determined by history and electrocardiogram. The age- and sex-adjusted mean CRP was 3.74 mg/L (standard error, 0.14) among Aboriginals, 2.59 mg/L (0.12) among South Asians, and 1.18 mg/L (0.13) among Chinese compared with 2.06 mg/L (0.12) among Europeans (overall P<0.0001). Differences in the CRP concentration between ethnic groups were substantially diminished, but not abolished, after adjustment for metabolic factors. CRP was independently associated with CVD after adjusting for the Framingham risk factors, atherosclerosis, anthropometric measurements, and ethnicity (OR=1.03 for a 0.1-increase in CRP; P=0.02)., Conclusions: CRP varies substantially between people of different ethnic origin and is influenced by their differences in metabolic factors. Prospective validation of CRP as a risk predictor for cardiovascular disease among nonwhite ethnic groups is required.

We developed three ethnic food frequency questionnaires (FFQs) to characterize the diets of South Asian, Chinese, and European immigrants. FFQs were developed from foods reported in the diet records and recalls of 29 South Asians, 25 Chinese, and 20 Europeans participating in a pilot study from 1995-1996 in Hamilton, Ontario, Canada. The FFQ and a seven-day diet record were then administered to 342 South Asians, 317 Chinese, and 346 Europeans participating in the Study of Health Assessment and Risk in Ethnic groups (SHARE) in three Canadian centers from 1996-1998. For FFQ validation, a subset of these participants completed a second seven-day diet record and second FFQ 8 to 10 months later. The FFQ generally underestimated macronutrient and overestimated micronutrient intake compared with the records. Consumption of most macronutrients was lower among South Asians. Energy-adjusted deattenuated correlation coefficients between the records and second FFQ ranged from 0.32 to 0.73 (South Asians), 0.17 to 0.84 (Chinese), and 0.30 to 0.83 (Europeans). The FFQs generally performed well and will be used to investigate diet-disease relations in SHARE. Lower correlations for dietary fats among Chinese persons (0.17 to 0.31) may be improved with more direct questions on the FFQ regarding brand, type, and amount of oil consumed in stirfry servings.

Background: The clustering of impaired glucose metabolism, elevated triglycerides, low HDL cholesterol, and abdominal obesity is known as the metabolic syndrome. Individuals with this syndrome suffer an excess of cardiovascular disease (CVD) for reasons that are unclear., Methods and Results: We randomly sampled 1276 adults of South Asian, Chinese, European, and Native Indian ancestry from 4 communities in Canada. Participants provided fasting blood samples for glucose, lipids, and fibrinolytic measurements; had an oral glucose tolerance test; and underwent a B-mode carotid ultrasound examination. CVD was determined by history and ECG. The prevalence of the metabolic syndrome was 25.8% (95% CI, 23.5 to 28.2) and varied substantially by ethnic group: 41.6% among Native Indians, 25.9% among South Asians, and 22.0% among Europeans, compared with 11.0% among the Chinese (overall, P=0.0001). People with the metabolic syndrome had more atherosclerosis (maximum intimal medial thickness, 0.78+/-0.18 versus 0.74+/-0.18 mm; P=0.0005), CVD (17.2% versus 7.0%; P=0.0001), and elevated plasminogen activator inhibitor-1 (24.2 versus 14.6 U/mL; P=0.001) compared with levels among people without the metabolic syndrome. For the same amount of atherosclerosis, people with the metabolic syndrome had a greater prevalence of CVD, even among nondiabetic individuals. This difference in CVD prevalence among the groups was attenuated after adjustment for plasminogen activator inhibitor-1 levels, suggesting that fibrinolytic dysfunction mediates the increased risk of CVD in individuals with the metabolic syndrome., Conclusions: CVD among people with the metabolic syndrome is explained by their excess of atherosclerosis and impaired fibrinolysis. Interventions to prevent atherosclerosis progression and improve fibrinolytic function require evaluation in this high-risk group.

Objective: Identifying individuals who have elevated glucose concentrations is important for clinicians so that preventive strategies can be invoked, and it is useful for researchers who study associations between elevated glucose and adverse health outcomes. These methods should be applicable worldwide across different ethnic groups. Therefore, the objective of our analysis was to determine whether using the fasting glucose and HbA(1c) together could improve the classification of individuals with impaired glucose tolerance and diabetes in a multiethnic cohort randomly assembled in Canada., Research Design and Methods: We determined the optimum diagnostic criteria to identify people with abnormal glucose tolerance using fasting plasma glucose, 2-h post-glucose load plasma glucose, and HbA(1c) in 936 Canadians of South Asian, Chinese, and European descent., Results: The sensitivity of the American Diabetes Association (ADA) criteria to diagnose diabetes compared with the World Health Organization definitions was poor at 48.3% (95% confidence interval [CI] 35.7-61.0). Using a receiver operator characteristic curve, the optimum combined cut-point using fasting glucose and HbA(1c) to diagnose diabetes was a fasting glucose > or =5.7 mmol/l and an HbA(1c) > or =5.9%. These cut-points were associated with a sensitivity and specificity of 71.7% (60.3-83.1) and 95.0% (93.5-96.4), respectively, a positive likelihood ratio (LR) of 14.3 (9.6-19.0), and a negative LR of 0.3 (0.2-0.4). Significant ethnic variation in the sensitivity and specificity of this approach was observed: 47.4% (24.9-69.8) and 97.6% (95.9-99.4) among Europeans, 78.6% (57.1-100) and 95.9% (93.6-98.2) among Chinese, and 85.2% (71.8-98.6) and 91.3% (88.1-94.6) among South Asians, respectively. Participants with impaired glucose tolerance could not be identified reliably using the fasting glucose or HbA(1c) alone or in combination., Conclusions: The sensitivity of the ADA criteria to diagnose diabetes is low, and there is substantial variation between ethnic groups. Fasting glucose and HbA(1c) may be used together to improve the identification of individuals who have diabetes, allowing clinicians to streamline the use of the oral glucose tolerance test.