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BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. However it is unclear how specific factors are differentially associated with COVID-19 mortality as compared to mortality from other causes.MethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged ≥18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration, the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths were estimated by fitting age- and sex-adjusted logistic models for these two outcomes.Results17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for ≥80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]).InterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19.FundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.

AimTo examine socioeconomic inequalities in risk of comorbidity between overweight (including obesity) and mental ill-health in two national cohorts. We investigated independent effects of childhood and adulthood socioeconomic disadvantage on comorbidity from childhood to mid-adulthood, and differences by sex and cohort.MethodsData were from 1958 National Child Development Study (NCDS58) and 1970 British Cohort Study (BCS70) [total N=30,868, 51% males] assessed at ages 10, 16, 23, 34 and 42 years. Socioeconomic indicators included childhood and adulthood social class and educational level. Risk for i. having healthy BMI and mental ill-health, ii. overweight and good mental health, and iii. overweight and mental ill-health was analysed using multinomial logistic regression.ResultsSocioeconomic disadvantage was consistently associated with greater risk for overweight-mental ill-health comorbidity at all ages (RRR 1.43, 2.04, 2.38, 1.64 and 1.71 at ages 10, 16, 23, 34 and 42 respectively for unskilled/skilled vs. professional/managerial class). The observed inequalities in co-morbidity were greater than that observed for either condition alone (overweight; RRR 1.39 and 1.25, mental ill-health; 1.36 and 1.22 at ages 16 and 42 respectively, for unskilled/skilled vs. professional/managerial class). In adulthood, childhood and adulthood socioeconomic disadvantage were independently associated with comorbid overweight-mental ill-health, with a clear inverse gradient between educational level and risk for comorbidity; no education, RRR 6.11 (95% CI 4.31-8.65) at age 34 and 4.42 (3.28-5.96) at age 42 compared to university education. There were no differences observed in the extent of inequalities by sex and differences between cohorts were limited.ConclusionsSocioeconomic disadvantage in childhood and adulthood are consistently and independently associated with greater risk for mental ill-health and overweight separately, and even greater inequalities in the risk for comorbidity between both conditions through the lifecourse. These findings are significant given the increasing global prevalence of obesity and mental ill-health, and their implications for lifelong health and mortality.

Background Diet-tracking mobile apps have gained increased interest from both academic and clinical fields. However, quantity-focused diet tracking (eg, calorie counting) can be time-consuming and tedious, leading to unsustained adoption. Diet quality—focusing on high-quality dietary patterns rather than quantifying diet into calories—has shown effectiveness in improving heart disease risk. The Healthy Heart Score (HHS) predicts 20-year cardiovascular risks based on the consumption of foods from quality-focused food categories, rather than detailed serving sizes. No studies have examined how mobile health (mHealth) apps focusing on diet quality can bring promising results in health outcomes and ease of adoption. Objective This study aims to design a mobile app to support the HHS-informed quality-focused dietary approach by enabling users to log simplified diet quality and view its real-time impact on future heart disease risks. Users were asked to log food categories that are the main predictors of the HHS. We measured the app’s feasibility and efficacy in improving individuals’ clinical and behavioral factors that affect future heart disease risks and app use. Methods We recruited 38 participants who were overweight or obese with high heart disease risk and who used the app for 5 weeks and measured weight, blood sugar, blood pressure, HHS, and diet score (DS)—the measurement for diet quality—at baseline and week 5 of the intervention. Results Most participants (30/38, 79%) used the app every week and showed significant improvements in DS (baseline: mean 1.31, SD 1.14; week 5: mean 2.36, SD 2.48; 2-tailed t test t29=−2.85; P=.008) and HHS (baseline: mean 22.94, SD 18.86; week 4: mean 22.15, SD 18.58; t29=2.41; P=.02) at week 5, although only 10 participants (10/38, 26%) checked their HHS risk scores more than once. Other outcomes, including weight, blood sugar, and blood pressure, did not show significant changes. Conclusions Our study showed that our logging tool significantly improved dietary choices. Participants were not interested in seeing the HHS and perceived logging diet categories irrelevant to improving the HHS as important. We discuss the complexities of addressing health risks and quantity- versus quality-based health monitoring and incorporating secondary behavior change goals that matter to users when designing mHealth apps.

The tumor suppressor folliculin (FLCN) forms a repressor complex with AMP-activated protein kinase (AMPK). Given that AMPK is a master regulator of cellular energy homeostasis, we generated an adipose-specific Flcn (Adipoq-FLCN) knockout mouse model to investigate the role of FLCN in energy metabolism. We show that loss of FLCN results in a complete metabolic reprogramming of adipose tissues, resulting in enhanced oxidative metabolism. Adipoq-FLCN knockout mice exhibit increased energy expenditure and are protected from high-fat diet (HFD)-induced obesity. Importantly, FLCN ablation leads to chronic hyperactivation of AMPK, which in turns induces and activates two key transcriptional regulators of cellular metabolism, proliferator-activated receptor γ (PPARγ) coactivator-1α (PGC-1α) and estrogen-related receptor α (ERRα). Together, the AMPK/PGC-1α/ERRα molecular axis positively modulates the expression of metabolic genes to promote mitochondrial biogenesis and activity. In addition, mitochondrial uncoupling proteins as well as other markers of brown fat are up-regulated in both white and brown FLCN-null adipose tissues, underlying the increased resistance of Adipoq-FLCN knockout mice to cold exposure. These findings identify a key role of FLCN as a negative regulator of mitochondrial function and identify a novel molecular pathway involved in the browning of white adipocytes and the activity of brown fat.

BackgroundCardiometabolic affections greatly contribute to the global burden of disease. The susceptibility to these conditions associates with the ancestral genetic composition and gut microbiota. However, studies explicitly testing associations between genetic ancestry and gut microbes are rare. We examined whether the ancestral genetic composition was associated with gut microbiota, and split apart the effects of genetic and non-genetic factors on host health.ResultsWe performed a cross-sectional study of 441 community-dwelling Colombian mestizos from five cities. We characterized the host genetic ancestry using 40 ancestry informative markers and gut microbiota through 16S rRNA gene sequencing. We measured variables related to cardiometabolic health (adiposity, blood chemistry and blood pressure), diet (calories, macronutrients and fiber) and lifestyle (physical activity, smoking and medicament consumption). The ancestral genetic composition of the studied population was 67±6% European, 21±5% Native American and 12±5% African. While we found limited evidence of associations between genetic ancestry and gut microbiota or disease risk, we observed a strong link between gut microbes and cardiometabolic health. Multivariable-adjusted linear models indicated that gut microbiota was more likely to explain variance in host health than genetic ancestry. Further, we identified 9 OTUs associated with increased disease risk and 11 with decreased risk.ConclusionsGut microbiota seems to be more meaningful to explain cardiometabolic disease risk than genetic ancestry in this mestizo population. Our study suggests that novel ways to control cardiometabolic disease risk, through modulation of the gut microbial community, could be applied regardless of the genetic ancestry of the intervened population.

The cJun N-terminal kinase (JNK) signaling pathway is a key mediator of metabolic stress responses caused by consuming a high-fat diet, including the development of obesity. To test the role of JNK, we examined diet-induced obesity in mice with targeted ablation of Jnk genes in the anterior pituitary gland. These mice exhibited an increase in the pituitary expression of thyroid-stimulating hormone (TSH), an increase in the blood concentration of thyroid hormone (T4), increased energy expenditure, and markedly reduced obesity compared with control mice. The increased amount of pituitary TSH was caused by reduced expression of type 2 iodothyronine deiodinase (Dio2), a gene that is required for T4-mediated negative feedback regulation of TSH expression. These data establish a molecular mechanism that accounts for the regulation of energy expenditure and the development of obesity by the JNK signaling pathway.

Human obesity is characterized by enlargement of visceral white adipose tissue (WAT) mass and is associated with a greater propensity to develop type 2 diabetes, hypertension, dyslipidemia, cardiovascular diseases, and cancer (Vague 1947; Montague and O'Rahilly 2000). Visceral fat enlargement encompasses an increase in both adipocyte cell size and cell number. However, it is predominantly the increase in visceral adipocyte cell size (adipocyte hypertrophy) that is strongly influenced by diet and is linked to a greater susceptibility of developing obesity-related pathologies (Donohoe et al. 2011). Indeed, nutrient overload, a key factor in promoting the obese state, induces adipocyte hypertrophy and can promote development of insulin resistance and glucose intolerance (Kopecky et al. 2004). Several lines of evidence suggest that visceral adipose tissue of obese human subjects and mouse models of obesity is poorly oxygenated, implying that adipose tissue expansion in response to chronic and excessive nutrient consumption creates a state of relative hypoxia due to an inability of the pre-existing adipose tissue vasculature to meet the oxygen demands of the expanding tissue (Wood et al. 2009). In mammals, decreased oxygen availability is directly connected to the activation of hypoxia-inducible factor (HIF), dimers composed of oxygen-regulated HIF1α, HIF2α, or HIF3α (collectively HIFα) and HIF1β/ARNT subunits. The ensuing induction of HIF-dependent target genes mediates the many adaptive responses to low oxygen (hypoxia), including the promotion of angiogenesis and cell survival, as well as changes in cellular metabolism (Kaelin and Ratcliffe 2008). There is evidence to suggest that among the HIFα subunits, in a context-dependent manner, HIF1α preferentially activates genes important for glycolysis, while HIF2α appears to favor the activation of genes involved in angiogenesis (Hu et al. 2003). The reprogramming of cellular metabolism by HIF involves a switch toward increased glycolysis and free fatty acid and triacylglyceride synthesis (Krishnan et al. 2009; Wellen and Thompson 2010), implicating a central role for HIF1α in the change of metabolic strategy following a reduction in ambient oxygen concentrations. In this regard, there is evidence to suggest that HIF1α protein accumulates in adipocytes of obese humans and mouse models of obesity (Ye 2009). While mouse models wherein HIF1α has been either overexpressed (Halberg et al. 2009), deleted in WAT (Jiang et al. 2011), or expressed as a dominant-negative form (Zhang et al. 2010) have been generated, they have not been suitable to interrogate a specific requirement of HIF1α function for maintaining the obese state (as opposed to the development of the obese state) and its associated pathologies. Hence, it remains unclear whether and how HIF1α function contributes to the maintenance of adiposity and its associated pathologies in the context of a pre-existing obese, diabetic, and cardiomyopathic state. Here we demonstrate that Hif1α protein accumulation is restricted to adipose depots of pathologically obese and diabetic humans and mice and that this accumulation results in an inhibition of fatty acid oxidation (FAO) and energetic uncoupling via transcriptional repression of sirtuin 2 (Sirt2), a member of the silent information regulator two class I (sirtuins, Sirt1–3) family of NAD+-dependent deacetylases. Sirt2 is the most abundantly expressed family member in adipocytes and has been implicated in promoting FAO by deacetylating various substrates (Jing et al. 2007; Wang et al. 2007). In this regard, adipocyte-specific inactivation of Hif1α in obese mice induces the accumulation of nuclear Sirt2 and an attendant reduction of acetylation of the transcriptional coactivator PPARγ coactivator 1α (Pgc1α). We propose that the negative effects of Hif1α on the sirtuin–Pgc1α metabolic regulatory system contributes to the suppression of genes involved in promoting energy expenditure and fatty acid catabolism. Therefore, our data assign a key role for Hif1α in the promotion and maintenance of dietary obesity and suggest that these effects are brought about, at least in part, by suppressing adipocyte lipid catabolism.

The cJun N-terminal kinase 1 (JNK1) is implicated in diet-induced obesity. Indeed, germline ablation of the murine Jnk1 gene prevents diet-induced obesity. Here we demonstrate that selective deficiency of JNK1 in the murine nervous system is sufficient to suppress diet-induced obesity. The failure to increase body mass is mediated, in part, by increased energy expenditure that is associated with activation of the hypothalamic–pituitary–thyroid axis. Disruption of thyroid hormone function prevents the effects of nervous system JNK1 deficiency on body mass. These data demonstrate that the hypothalamic–pituitary–thyroid axis represents an important target of metabolic signaling by JNK1.

Intrinsic aerobic exercise capacity can influence many complex traits including obesity and aging. To study this connection we established two rat lines by divergent selection of untrained aerobic capacity. After 32 generations the high capacity runners (HCR) and low capacity runners (LCR) differed in endurance running distance and body fat, blood glucose, other health indicators, and natural life span. To understand the interplay among genetic differences, chronological age, and acute exercise we performed microarray-based gene expression analyses in skeletal muscle with a 2×2×2 design to simultaneously compare HCR and LCR, old and young animals, and rest and exhaustion. Transcripts for mitochondrial function are expressed higher in HCRs than LCRs at both rest and exhaustion and for both age groups. Expression of cell adhesion and extracellular matrix genes tend to decrease with age. This and other age effects are more prominent in LCRs than HCRs, suggesting that HCRs have a slower aging process and this may be partly due to their better metabolic health. Strenuous exercise mainly affects transcription regulation and cellular response. The effects of any one factor often depend on the other two. For example, there are ∼140 and ∼110 line-exercise “interacting” genes for old and young animals, respectively. Many genes highlighted in our study are consistent with prior reports, but many others are novel. The gene- and pathway-level statistics for the main effects, either overall or stratified, and for all possible interactions, represent a rich reference dataset for understanding the interdependence among lines, aging, and exercise.

BackgroundLeucocyte telomere length (LTL), a potential marker of biological age, has been associated with risk of many diseases. We investigated whether LTL is associated with risk of frailty, a multidimensional syndrome of decline that affects multiple systems and predisposes to adverse health outcomes.MethodsIn a cross–sectional analysis, we studied 441,781 UK Biobank participants (aged 40–70 years), with complete data on LTL and frailty indicators. We defined frailty as the presence of at least three of five indicators: weaker grip strength, slower walking pace, weight loss in the past year, lower physical activity, and exhaustion in the past two weeks. We evaluated association of LTL with frailty using adjusted (chronological age, sex, deprivation, smoking, alcohol intake, body mass index, multimorbidity) multinomial and ordinal regression models. We used Mendelian randomisation (MR), using 131 genetic variants associated with LTL, to assess if the association of LTL with frailty was causal.FindingsFrail participants (4·6%) were older (median age difference (95% CI): 3 (2·5; 3·5) years), more likely to be female (61%), and had shorter LTL (−0·13SD vs 0·03SD) than non–frail. In adjusted analyses, both age and LTL were associated with frailty (OR=1·03 (95%CI: 1·02–1·04) per year of older chronological age; 1·10 (1·08; 1·11) per SD shorter LTL). Within each age group (40–49, 50–59, 60–69 years) the prevalence of frailty was about 33% higher in participants with shorter (−2SD) versus longer telomeres (+2SD). MR analysis showed an association of LTL with frailty that was directionally consistent with the observational association, but not statistically significant.InterpretationInter–individual variation in LTL is associated with the risk of frailty independently of chronological age and other risk factors. Our findings provide evidence for an additional biological determinant of frailty.FundingThe UK Medical Research Council, the Biotechnology and Biological Sciences Research Council and the British Heart Foundation (MRC grant: MR/M012816/1) funded our measurements of LTL in UK Biobank. The funders had no role in study design; the collection, analysis, and interpretation of data; the writing of the report; and the decision to submit the paper for publication.Research in contextEvidence before this studyTelomere length has been proposed as a biomarker of biological age. Shorter leucocyte telomere length (LTL) is associated with higher incidence of several age–associated diseases, spanning multiple body systems, and with lower life expectancy. However, the association of shorter LTL with frailty, a multidimensional syndrome of decline across multiple systems, is inconclusive. We searched PubMed using the terms “telomere length AND frailty” in the title, abstract, or text with no language restrictions. This search identified 50 papers published before 30 November, 2020. Of these, three systematic reviews and/ or meta–analyses of modest size (five to nine studies, with total nAdded value of this studyOur large–scale population–based study, involving over 441,000 participants, provides strong evidence that shorter LTL is associated with higher risk of both pre–frailty and frailty even after adjustment for chronological age and other established determinants of frailty, namely, age, sex, alcohol intake, smoking, obesity, deprivation and multimorbidity. Within each age group (40–49, 50–59, 60–69 years) the prevalence of frailty was about 33% higher in participants with shorter (−2SD) versus longer telomeres (+2SD). Part of the association of shorter LTL with higher risk of frailty may be due to the association in aggregate of LTL with diseases. Findings using genetic variants associated with LTL as instruments were directionally consistent with the observational association, but not statistically significant.Implications of all the available evidenceShorter LTL is associated with frailty independent of chronological age and several other risk factors. The observation that risk of frailty associated with shorter LTL is proportionately similar across the age range of 40–70 years suggests that shorter LTL acts through a mechanism beyond just accelerating the impact of chronological ageing on risk of frailty.

This article is a preprint and has not been peer-reviewed [what does this mean?]. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice. Copyright © 2021 the author(s). Objectives: Obesity prevalence is increasing in West Africa. This study explores obesity determinants in West Africa to inform policy. Methods: Scopus, Web of Science and PsycINFO were searched for relevant papers from March to April 2020. The search strategy included combinations of key words specific to each database. Eligibility criteria included studies on obesity determinants conducted in West Africa, and involving participants aged eighteen years and above. The quality of the studies was appraised using the Agency for Healthcare Research and Quality checklist. Data was synthesized qualitatively. Results: Sixty-three (63) papers were selected. Majority of the studies originated from Ghana (n=22) and Nigeria (n=19). All included studies used cross-sectional study design. In all, 36 determinants were identified, of which 20 were demographic, socio-economic, lifestyle and biological factors, and sixteen 16 were environmental factors, like physical proximity to fast food outlets. Increasing age (OR=0.09, 95% CI= 0.12 to 65.91) and being a woman (OR=1.38, 95% CI=1.18 to 55.40) were the common determinants of obesity in West Africa. Conclusion: Obesity in West Africa is determined by complex multi-faceted factors. There is an urgent need for robust engagement with wider stakeholder groups to develop obesity prevention and control policies in West Africa. The authors did not receive any funding for this study from any funding agency in the public, commercial, or not-for-profit sectors.

Obesity (and the consequent obesity epidemic) is a complex, adaptive process, taking place over a time span of many years. Energy intake is recognized as a potentially important driver of obesity, especially in the context of an identifiable energy imbalance which, it is surmised, must lead to weight gain. Similarly, energy expenditure must play an important role. However, both show an enormous degree of individual variation. Therefore, measuring them is an exceedingly difficult task, especially in the context of large populations and long time periods. It has been argued that population-level observed weight gain can be traced back to very small daily energy imbalances while, at the same time, positing that a much larger maintenance energy gap is responsible for maintaining the energy requirements of the increased weight population. In this paper we examine the relation between BMI and energy intake as functions of age. The convexity of the BMI curves as a function of age and gender demonstrate the enhanced obesity risk apparent in young adults and women, and imply that no settling points exist at the population level. Consistent with other studies, overall weight increases are consistent with a very small daily energy imbalance, about 7 cal. Consumption as a function of age shows a small, steady, linear decrease of about 8 cal per year, and can be associated with a maximal energy excess/deficit of about 250cal for the youngest and oldest age groups. By examining weight differences between age groups as a function of age, we argue that this excess/deficit is an important motor for the observed weight differences, and argue that the apparent energy imbalance of 250 cal, due to excess consumption, leads to an effective imbalance of only 7 cal due to the existence of various physiological and behavioral mechanisms that enhance weight homeostasis and effectively reduce the energy excess from 250 cal to 7 cal. We discuss several possibilities for such mechanisms.

Fibroblast growth factor 21 (FGF21) is a member of the fibroblast growth factor (FGF) family of proteins. The biological activity of FGF21 was first shown to induce insulin independent glucose uptake in adipocytes through the GLUT1 transporter. Subsequently, it was shown to have effects on the liver to increase fatty acid oxidation. FGF21 treatment provides beneficial metabolic effects in both animal models and patients with obesity, type 2 diabetes mellitus (T2D) and/or fatty liver disease. In this paper, we revisited the original finding and found that insulin independent glucose uptake in adipocytes is preserved in the presence of an insulin receptor antagonist. Using a 40 kDa PEGylated (PEG) and half-life extended form of FGF21 (FGF21-PEG), we extended these in vitro results to two different mouse models of diabetes. FGF21-PEG normalized plasma glucose in streptozotocin-treated mice, a model of type 1 diabetes (T1D), without restoring pancreatic β-cell function. FGF21-PEG also normalized plasma glucose levels and improved glucose tolerance in mice chronically treated with an insulin competitive insulin receptor antagonist, a model of autoimmune/Type-B insulin resistance. These data extend the pharmacological potential of FGF21 beyond the settings of T2D, fatty liver and obesity.

IntroductionCOVID-19 pandemic has caused havoc worldwide, and different comorbidities have been seen to exacerbate the condition. Obesity is one of the leading comorbidities, which is associated with many other diseases. In this paper, we present a systematic review and meta-analysis estimating the effects of overweight and obesity on COVID-19 disease severity.MethodologyTwo electronic databases (Medline and Cochrane library) and one grey literature database (Grey Literature Report) were searched using the following keywords: overweight, obesity, body mass index, respiratory disease, coronavirus, COVID-19. The risks of bias of the selected studies were assessed by using the Navigation Guide method for human data. Both random and fixed effect meta-analysis were determined using Review Manager (RevMan) software version 5.4.ResultsAfter initial screening, 12 studies (7 cohort studies, four case-control studies, and one cross-sectional study) were fulfilled the eligibility criteria, comprising a total of 405359 patients and included in the systematic review. The pooled risk of disease severity was 1.31 times higher based on both fixed and random effect model among those overweight patients,I20% and 2.09 and 2.41 times higher based on fixed and random effect respectively among obese patients,I242% compared to healthy individuals.ConclusionOverweight and obesity are common risk factors for disease severity of COVID-19 patients. However, further assessment of metabolic parameters included BMI, waist-hip ratio, and insulin levels, are required to estimate the risk factors of COVID-19 patients and understanding the mechanism between COVID-19 and body mass index.

BackgroundBased on systematic literature reviews, the Institute of Health Metrics and Evaluation (IHME) Global Burden of Disease (GBD) landmark risk factor paper attributes about 8 million noncommunicable diseases deaths/year to a composite of 15 dietary risk factors. Another 27 million noncommunicable deaths out of 56.5 million total deaths worldwide are attributed to high levels of metabolic risk factors.MethodsWe format and population weight IHME GBD worldwide data resulting in7886 rows of data from cohorts of about 1 million people each representing about 7.8 billion people in 2020. Noncommunicable disease deaths/100k/year (NCD) are correlated with the four metabolic risk factors, 15 dietary risk factors, six dietary covariates, and the composite “dietary risks” variable. We compare NCD groups of cohorts (about 1000 cohorts, representing about 1 billion people) with the lowest and highest NCD and the same for body mass index (BMI). We compare literature reviews attributions of NCD causation with findings from the GBD data in assessing the impact of dietary and metabolic risk factors on NCD.FindingsLiterature review derived dietary risks composite risk factor correlated with NCD account for 1.9% of worldwide NCD. Using GBD data to compare groups with the lowest versus the highest rates of NCD: the lowest NCD 990 cohorts average 923.8 NCD and consume 320.4 kcal/day from six animal foods. The highest NCD 1054 cohorts average 2064 NCD and on average and consume 117.2 kcal/day of six animal foods. Vitamin A deficiency in children is 75% higher in children in the high NCD cohorts. Evaluating high BMI cohorts, 973 cohorts with BMI≥25 account for 10.5% of the worldwide NCD. These high BMI cohorts also have higher than average fasting plasma glucose (FPG: FPG mean=4.71 versus FPG mean=4.25) and low density lipoprotein cholesterol (LDLC: LDLC mean=2.79 versus LDLC mean=2.30).InterpretationThe evidence basis of the dietary risks composite risk factor, accounting for only 1.9% of NCD worldwide should be questioned. Systematic literature reviews based versus GBD data based estimates of metabolic and dietary risk factor impacts on NCD vary markedly. Systematic literature reviews of studies involving individual subjects are better at ascertaining the impact on NCD of obesity, hyperglycemia, high LDLC, and hypertension. High levels of metabolic risk factors cannot be analysed with GBD data giving only the mean values for NCD and risk factors. Since high mean BMI cohorts (mean BMI≥25) account for only 10.5% of worldwide NCD, literature reviews appear to overestimate the worldwide impacts of high metabolic risk factors on NCD (i.e., accounting for nearly 50% of worldwide deaths: 27 million/56.5 million worldwide deaths). High NCD, including cardiovascular disease deaths, associated with low animal food intake suggests that fat soluble vitamin deficiencies (vitamins A, D, E and K2, all largely from animal foods that also supply fatty acids for gut absorption) may partly account for high rates of NCD worldwide, especially in developing countries. Literature review based and GBD raw data based approaches should be complementary in assessing dietary and other attributable risks for NCD and other individual health outcomes.FundingNoneResearch in contextEvidence before this studyThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD 2019) provides the most recent assessment of deaths, attributable to metabolic, environmental and occupational, and behavioural risk factors. Controversies abound in the field of nutritional epidemiology. The lipid hypothesis that dietary saturated fat and cholesterol promote cardiovascular diseases has been disputed with no scientific consensus on the outcome.Added value of this studyThis study assesses the evidence basis of deaths attributed to dietary risks and metabolic risk factors derived from systematic reviews of the medical literature in GBD 2019. This study uses GBD raw data formatted and population weighted to assess the worldwide deaths from noncommunicable diseases attributable to dietary and metabolic risk factors. With this GBD data analysis methodology, the levels of 20 dietary risk factors are assessed in cohorts with the highest and lowest rates of noncommunicable disease deaths. Worldwide GBD data show that many deaths are associated with low levels of animal foods and saturated fatty acids (kcal/day percapita) and associated with low levels of metabolic risk factors. These findings are at variance with the lipid hypothesis operating uniformly worldwide. In the UK, USA, Mexico, and Japan, with subnational GBD data, many deaths are attributable to high levels of animal foods, saturated fatty acids, and metabolic risk factors, supporting the lipid hypothesis.Implications of all the available evidenceThe findings of systematic literature reviews in assessing the health impacts of high metabolic risk factors are superior than using GBD data analysis because GBD data only assess mean cohort levels of metabolic risk factors. However, GBD data can show effects of dietary risk factors acting directly and mediating metabolic risks leading to noncommunicable disease deaths. This GBD data based methodology can enhance understanding of the complex interrelationships of diet, metabolic risk factors and noncommunicable disease deaths. The findings are consistent with a “fat soluble vitamin hypothesis” that deficiencies of vitamins A, D, E, and K2 and fatty acids from inadequate animal food consumption lead to increased cardiovascular disease and noncommunicable disease deaths.

Background and aimsThis paper describes the data resource profile of South Asia Biobank (SAB), which was set up in South Asia from November 2018 to March 2020, to identify the risk factors and their complex interactions underlying the development of type-2 diabetes mellitus, cardiovascular disease and other chronic diseases in South Asians.Data resource basicsThis cross-sectional population-based study has recruited 52713 South Asian adults from 118 surveillance sites at five centres of excellence in South Asia (Bangladesh, North India, South India, Pakistan and Sri Lanka). Structured assessments of participants included six complementary domains: i). Registration and consent; ii). Questionnaire (information on behavioural risk factors, personal and family medical history, medications, socioeconomic status); iii). Physical measurements (height, weight, waist and hip circumference and bio-impedance for body fat composition, blood pressure, cardiac evaluation, retinal photography, respiratory evaluation); iv). Biological samples (blood and urine); v). Physical activity monitoring and vi). Dietary intake by a 24-hour recall. Aliquots of whole blood, serum, plasma, and urine were put into storage at −80°C for further analysis.Key resultsThe prevalence of obesity is 6.6% in Bangladesh, 19.7% in India, 33.9% in Pakistan and 15.7% in Sri Lanka. The prevalence of diabetes is 11.5%, 27.7%, 25.3%, and 24.8%, and the prevalence of hypertension is 26.7%, 36.9%, 44.5%, 35.0% in Bangladesh, India, Pakistan and Sri Lanka respectively.Collaboration and data accessSAB is the first comprehensive biobank of South Asian individuals. Collected data are available to the global scientific community upon request.

BackgroundCongenital heart defects (CHDs) are the most common congenital malformations. The aetiology of CHDs is complex. Large cohort studies and systematic reviews and meta-analyses based on these have reported an association between higher risk of CHDs in the offspring and individual maternal metabolic disorders such as obesity, diabetes, hypertension, and preeclampsia, all conditions that can be related to insulin resistance or hyperglycaemia. However, the clinical reality is that these conditions often occur simultaneously. The aim of this review is, in consequence, both to evaluate the existing evidence on the association between maternal metabolic disorders, defined as obesity, diabetes, hypertension, preeclampsia, dyslipidaemia and CHDs in the offspring, as well as the significance of combinations, such as metabolic syndrome, as risk factors.MethodsA systematic literature search of papers published between January 1, 1990 and January 14, 2021 was conducted using PubMed and Embase. Studies were eligible if they were published in English and were case-control or cohort studies. The exposures of interest were maternal overweight or obesity, hypertension, preeclampsia, diabetes, dyslipidaemia, and/or metabolic syndrome, and the outcome of interest was CHDs in the offspring. Furthermore, the studies were included according to a quality assessment score.ResultsOf the 2,250 identified studies, 32 qualified for inclusion. All but one study investigated only the individual metabolic disorders. Some disorders (obesity, gestational diabetes, and hypertension) increased risk of CHDs marginally whereas pre-gestational diabetes and early-onset preeclampsia were strongly associated with CHDs, without consistent differences between CHD subtypes. A single study suggested a possible additive effect of maternal obesity and gestational diabetes.ConclusionsFuture studies of the role of aberrations of the glucose-insulin homeostasis in the common aetiology and mechanisms of metabolic disorders, present during pregnancy, and their association, both as single conditions and–particularly–in combination, with CHDs are needed.

Early childhood is a critical period of life when nutritional choice and mealtime routines develop and obesogenic tendencies may be established. There is a need for greater understanding of toddlers and how parent-child interactions over time and across contexts relate to development of obesity. The purpose of this protocol paper is to describe the recruitment strategy, protocol, and characteristics of participants in the Play & Grow cohort. Between December 2017 and May 2019, three-hundred caregivers and their 16- to 19-month-old toddler (57% male) were recruited from records of the major pediatric provider in Central Ohio and enrolled in an ongoing 2-year prospective study. The cohort is diverse in race and ethnicity, parent education and age, household income, and family composition. Thirty-seven percent of children were born preterm (

The evidence for transgenerational transmission of pathologies in rodents exposed to pesticides is largely based on studies with weaknesses in design and analysis and a lack of transparency in reporting the results. This paper examines these methodological and statistical issues in detail. Its particular focus is on the estimation of ‘litter effects’: the tendency for rodents within a litter to be more alike than rodents in different litters. Appropriate statistical models were fitted to published data from a series of widely reported studies carried out at Washington State University. These studies were amalgamated into a single dataset in order to estimate these litter effects and the associated treatment effects. Litter effects varied by outcome and were often substantial. Consequently, the effective sample size was often substantially less than the number of observations with implications for the power of the studies. Moreover, the reported precision of the estimates of treatment effects was too low. These problems are exacerbated by unexplained missing data across generations. Researchers in the life sciences could be more cognisant of the guidelines established in medicine for reporting randomised controlled trials, particularly cluster randomised trials. More attention should be paid to the design and analysis of multi-generational rodent studies; their imperfections have important implications for assessments of the evidence relating to the risks of pesticides for public health.

This paper investigates whether genetic makeup moderates the effects of education on health. Low statistical power and endogenous measures of environment have been obstacles to the credible estimation of such gene-by-environment interactions. We overcome these obstacles by combining a natural experiment that generated variation in secondary education with polygenic scores for a quarter million individuals. The additional schooling affected body size, lung function, and blood pressure in middle age. The improvements in body size and lung function were larger for individuals with high genetic predisposition to obesity. As a result, education reduced the gap in unhealthy body size between those with high and low genetic risk of obesity from 20 to 6 percentage points.

BackgroundObesity and its co-morbidities are characterized by a chronic low-grade inflammatory state, uncontrolled expression of metabolic measurements and dis-regulation of various forms of stress response. However, the contribution and correlation of inflammation, metabolism and stress responses to the disease are not fully elucidated. In this paper a cross-sectional case study was conducted on clinical data comprising 117 human male and female subjects with and without type 2 diabetes (T2D). Characteristics such as anthropometric, clinical and bio-chemical measurements were collected.MethodsAssociation of these variables with T2D and BMI were assessed using penalized hierarchical linear and logistic regression. In particular, elastic net, hdi and glinternet were used as regularization models to distinguish between cases and controls. Differential network analysis using closed-form approach was performed to identify pairwise-interaction of variables that influence prediction of the phenotype.ResultsFor the 117 participants, physical variables such as PBF, HDL and TBW had absolute coefficients 0.75, 0.65 and 0.34 using the glinternet approach, biochemical variables such as MIP, ROS and RANTES were identified as determinants of obesity with some interaction between inflammatory markers such as IL4, IL-6, MIP, CSF, Eotaxin and ROS. Diabetes was associated with a significant increase in thiobarbituric acid reactive substances (TBARS) which are considered as an index of endogenous lipid peroxidation and an increase in two inflammatory markers, MIP-1 and RANTES. Furthermore, we obtained 13 pairwise effects. The pairwise effects include pairs from and within physical, clinical and biochemical features, in particular metabolic, inflammatory, and oxidative stress markers.ConclusionsWe showcase that markers of oxidative stress (derived from lipid peroxidation) such as MIP-1 and RANTES participate in the pathogenesis of diseases such as diabetes and obesity in the Arab population.

Two papers appearing in this issue report the generation of transgenic mice largely devoid of white adipose tissue (WAT). In both cases the resulting mice display anatomical and physiological properties very similar to human patients suffering from generalized lipodystrophy. Such patients lack WAT, a condition resulting from either genetic or autoimmune etiologies, and are severely diabetic (Foster 1994; Seip and Trygstad 1996). The present reports provide fresh and interesting observations regarding the physiological consequences of life without fat and, moreover, establish animal models that offer new opportunities for the study of type 2 diabetes.