Repositioning of the global epicentre of non-optimal cholesterol NCD Risk Factor Collaboration (NCD-RisC)* High blood cholesterol is typically considered a feature of wealthy western countries 1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world 3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health 4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low-and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium,
SummaryBackgroundDiabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA1c. We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions.MethodsWe used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT ≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori.FindingsPopulation prevalence of diabetes based on FPG-or-2hOGTT was correlated with prevalence based on FPG alone (r=0·98), but was higher by 2–6 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42·8% of age–sex–survey groups and higher in another 41·6%; in the other 15·6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA1c-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8% (95% CI 51·3–54·3%) and a pooled specificity of 99·74% (99·71–99·78%) compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30·5% (28·7–32·3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA1c versus FPG.InterpretationDifferent biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA1c-based definition alo...
Both protein-energy malnutrition (PEM) and obesity represent major challenges for paediatric nutrition. The aim of this review is to summarise available data regarding the effect of PEM and obesity on the availability of essential-and long-chain polyunsaturated fatty acids (LC-PUFAs) in childhood.Signi®cantly lower arachidonate (C20: 4n-6, AA) values in malnourished children than in controls is a consistent ®nding in all studies, whereas it is controversial whether the availability of docosahexaenoate (C22: 6n-3, DHA) is also affected. We found signi®cantly lower percentages (% wt/wt) of both AA and DHA in plasma phospholipids [AA: 7.0 (0.7) vs 8.7 (0.8); DHA: 0.90 (0.2) vs 2.6 (0.7), median (interquartile range), P`0.001] in severely malnourished children aged 29 (7) months than in control subjects. Product/substrate ratios indicated reduced delta-5-desaturation in children with PEM. We speculate that severely malnourished children may bene®t from enhanced dietary supply of both n-6 and n-3 LC-PUFAs.In obese adults AA has been reported to constitute a lower percentage of plasma phospholipid fatty acids, and AA supplementation of weight reduction diets has been suggested. In contrast, we found signi®cantly higher plasma phospholipid AA values [12.6 (2.4) vs 8.3 (1.4), P`0.001] in markedly obese children aged 13.8 (1.1) years than in non-obese controls. Product/substrate ratios of the delta-6-desaturase enzyme indicated enhanced conversion activity. These data suggest that obese children do not require LC-PUFA supplementation to low fat diets.The available data indicates that both PEM and obesity alter fatty acid composition of plasma and erythrocyte membrane lipids. The underlying mechanism appears to be altered activity of the bioconversion of essential fatty acids to their LC-PUFA metabolites. Sponsorship:
The simultaneous presence of various cardiovascular risk factors in the same individual is not rare, even in the pediatric age group. The clustering of risk factors can be termed insulin resistance syndrome (IRS) because of the putative central role of tissue insulin insensitivity in the background of the inter-related metabolic disturbances. Fasting hyperinsulinemia, impaired glucose tolerance, dyslipidemia, and hypertension are considered to represent the basic abnormalities of IRS. The most prevalent related disturbances are increased plasma levels of plasminogen activator inhibitor-1, fibrinogen, uric acid, homocysteine, and C-reactive protein, as well as visceral adiposity, microalbuminuria, disturbed essential fatty acid metabolism, low availability of lipid-soluble antioxidant vitamins, and enhanced expression of tumor necrosis factor-alpha in adipose tissues. Certain genetic abnormalities have been associated with IRS, but explain only a small part of the variability in insulin resistance. The exact prevalence of IRS in children remains to be defined; it was found to be 9% in one survey among children with obesity seeking medical attention. Modification of lifestyle, i.e. reduction of energy intake and enhancement of physical activity, are unquestionable prerequisites for long-term success in the management of IRS. In at least two randomized controlled studies, metformin proved to be clinically effective in increasing insulin sensitivity in hyperinsulinemic, nondiabetic adolescents. Thiazolidinediones have been successfully tested for the treatment of insulin resistance in adults, but not in children as yet. Prevention of the development of IRS in children is obviously of great significance for the health status of the community. However, the efficacy of various preventive approaches should be investigated further in carefully designed controlled trials.
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