Causal inference in obesity research

Contamination status and health risk assessment of potentially toxic trace elements in soils surrounding rare earth tailings in China: A retrospective review

The contamination of soils surrounding rare earth tailings (SRET) with potentially toxic trace elements (PTEs), including Ni, Cd, Cr, As, Pb, Mn, Cu, Zn, and Hg, has garnered increasing scientific concern. However, existing studies predominantly focused on localized regions, limiting insights into nationwide pollution patterns associated with SRET. To address this gap, we systematically compiled and analyzed PTE concentration data from SRET across China using peer-reviewed studies published between 2012 and 2023. The index of geo-accumulation (Igeo) was applied to quantify contamination levels, while Monte Carlo simulation (MCS) was employed to assess uncertainty and sensitivity in health risks posed by ingestion, inhalation, and dermal exposure pathways. Results revealed that average concentrations of Cd, As, Pb, Mn, Zn, and Hg exceeded Chinese soil background values by up to 11.16-fold. Igeo revealed significant Cd contamination in SRET in Inner Mongolia (Igeo = 1.77), Fujian (Igeo = 5.64), and Sichuan (Igeo = 3.89). Moderate Mn contamination was identified in Guangdong (Igeo = 1.80) and Inner Mongolia (Igeo = 1.63). Adults exhibited elevated health risks via oral ingestion of PTEs-contaminated SRET. MCS demonstrated that the median hazard index (HI) and carcinogenic risk (CR) values in five provinces surpassed safety thresholds (CR > 1.00 ×10-6, HI > 1.00). Sensitivity analyses identified daily soil intake and exposure duration were positively linked to health risks, with As, Ni, Cd, Cr, and Mn concentrations contributing substantially to cumulative risks. This study provides actionable insights for optimizing cost-effective PTE remediation strategies in SRET-affected regions.

Trends and analysis of risk factor differences in the global burden of chronic kidney disease due to type 2 diabetes from 1990 to 2021: A population-based study

BACKGROUND

Chronic kidney disease (CKD) is a significant contributor to the global burden of disease. Among its causes, chronic kidney disease due to type 2 diabetes (CKD-T2D) is the primary subtype. This study aims to provide an updated assessment of the global disease burden of CKD-T2D from 1990 to 2021. It will analyse the trends in the global burden of CKD-T2D and the differences in risk factors, as well as project changes over the next 15 years.

METHODS

The data for this study were derived from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2021. Estimates of prevalence, incidence, deaths and disability-adjusted life years (DALYs) for CKD-T2D, along with their 95% uncertainty intervals (UIs), were extracted. The trends in CKD-T2D burden from 1990 to 2021 were analysed from overall and local perspectives. An age-period-cohort model was used to estimate the age, period and cohort effects on the prevalence and incidence of CKD-T2D between 1990 and 2021. A decomposition analysis was conducted to assess the contribution of population size, age structure and epidemiological changes to the burden of CKD-T2D. Population-attributable fractions were determined for each risk factor, and a difference analysis was conducted. Additionally, projections were made regarding changes in the burden of CKD-T2D over the next 15 years.

RESULTS

In 2021, the global burden of CKD-T2D remained significant, with a total of 107 559 955 cases. The age-standardized prevalence rate (ASPR) was 1259.63 per 100 000 people. The age-standardized incidence rate (ASIR) was 23.07 per 100 000 people, and the age-standardized death rate (ASDR) was 5.72 per 100 000 people. The age-standardized disability-adjusted life years (DALYs) was 131.08 per 100 000. The global burden of CKD-T2D showed variation across different socio-demographic index (SDI) regions. In 2021, the overall burden of CKD-T2D continued to rise, with the age effect increasing with age. Both prevalence and incidence risks showed an upward trend over time. Decomposition analysis indicated that population growth and ageing were the primary contributors to the global burden of DALYs related to CKD-T2D. Metabolic risk factors such as high fasting plasma glucose and high body mass index (BMI) are the most significant attributable risk factors. It is projected that by 2036, the trends in ASPR, ASIR, ASDR and age-standardized DALYs will stabilize. However, ASIR and age-standardized DALYs are expected to continue rising, and the number of cases of prevalence, incidence, mortality and DALYs will persist in their upward trend.

CONCLUSION

CKD-T2D imposes a significant global disease burden, with health disparities and unequal disease outcomes continuing to worsen across countries and regions due to differences in socio-economic development levels. This burden is primarily driven by population growth, ageing and metabolic risks such as obesity, hyperglycaemia and hypertension. Although the rate of increase in disease burden may slow over the next 15 years, the number of cases is expected to rise substantially. Therefore, enhancing prevention, early screening and effective treatment interventions, particularly in high-risk areas, is crucial for reducing the disease burden and narrowing health disparities.

A machine learning tool for identifying metastatic colorectal cancer in primary care

BACKGROUND

Detection of colorectal cancer (CRC) is mainly achieved by clinical assessment. As new treatments become available for metastatic CRC (MCRC), it is important to accurately identify these patients.

AIM

To develop a predictive model for identifying MCRC in primary health care patients using diagnostic data analysed with machine learning.

DESIGN AND SETTING

A case-control study utilising data on primary health care visits for 146 patients >18 years old diagnosed with MCRC in the Västra Götaland Region, Sweden during 2011, and 577 sex-, age, and primary health care centre-matched controls.

METHOD

Stochastic gradient boosting was used to construct a model for predicting the presence of MCRC based on diagnostic codes from primary health care consultations during the year before index (diagnosis) date and number of consultations. Variable importance was estimated using the normalised relative influence (NRI) score. Risks of having MCRC were calculated using odds ratios of marginal effects (ORME).

RESULTS

The optimal model included 76 variables with non-zero influence, had an area under the curve of 76.5%, a sensitivity of 77.8%, and a specificity of 69.2%. The 10 most important variables had a combined NRI of 61.0%. Number of consultations during the year before index date had the highest NRI at 19.2%, with an ORME of 3.3.

CONCLUSION

A machine learning method based on primary health care consultation frequency and diagnoses may be used to identify important variables for predicting presence of MCRC. Both primary health care consultations and associated diagnostic codes need to be taken into consideration.

Sequence variants associated with BMI affect disease risk through BMI itself

Mendelian Randomization studies indicate that BMI contributes to various diseases, but it's unclear if this is entirely mediated by BMI itself. This study examines whether disease risk from BMI-associated sequence variants is mediated through BMI or other mechanisms, using data from Iceland and the UK Biobank. The associations of BMI genetic risk score with diseases like fatty liver disease, knee replacement, and glucose intolerance were fully attenuated when conditioned on BMI, and largely for type 2 diabetes, heart failure, myocardial infarction, atrial fibrillation, and hip replacement. Similar attenuation was observed for chronic kidney disease and stroke, though results varied. Findings were consistent across sexes, except for myocardial infarction. Residual effects may result from temporal BMI changes, pleiotropy, measurement error, non-linear relationships, non-collapsibility, or confounding. The attenuation extent of BMI genetic risk score on disease associations suggests the potential impact of reducing BMI on disease risk.

The association between air pollution and obesity: an umbrella review of meta-analyses and systematic reviews

The objective of this umbrella review was to investigate comprehensive and synthesized evidence of the association between ambient air pollution and obesity based on the current systematic reviews and meta-analyses. Related studies from databases including PubMed, EMBASE, Web of Science, and the Cochrane Library, published before July 16, 2023, were considered in the analysis. All selected systematic reviews and meta-analyses were included in accordance with PRISMA guidelines. The risk of bias and the methodological quality were evaluated using the AMSTAR 2 tool. The protocol for this umbrella review was documented in PROSPERO with the registration number: CRD42023450191. This umbrella review identified 7 studies, including 5 meta-analyses and 2 systematic reviews, to assess the impacts of air pollutants on obesity. Commonly examined air pollutants included PM1, PM2.5, PM10, NO2, SO2, O3. Most of the included studies presented that air pollution exposure was positively associated with the increased risk of obesity. The impact of air pollution on obesity varied by different ambient air pollutants. This study provided compelling evidence that exposure to air pollution had a positive association with the risk of obesity. These findings further indicate the importance of strengthening air pollution prevention and control. Future studies should elucidate the possible mechanisms and pathways linking air pollution to obesity.

Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data

A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for prevention efforts. In our study, we summarized the risk factors for AD/ADRD by reviewing existing meta-analyses and review articles on risk and preventive factors for AD/ADRD. In total, we extracted 477 risk factors in 10 categories from 537 studies. We constructed an interactive knowledge map to disseminate our study results. Most of the risk factors are accessible from structured Electronic Health Records (EHRs), and clinical narratives show promise as information sources. However, evaluating genomic risk factors using RWD remains a challenge, as genetic testing for AD/ADRD is still not a common practice and is poorly documented in both structured and unstructured EHRs. Considering the constantly evolving research on AD/ADRD risk factors, literature mining via NLP methods offers a solution to automatically update our knowledge map.

Association between periodontitis and uric acid levels in blood and oral fluids: a systematic review and meta-analysis

BACKGROUND

Uric acid, a formerly-known antioxidant that has recently been linked to numerous inflammatory diseases as a pro-inflammatory and -oxidative mediator in pathological conditions. It is imperative to reassess the association between periodontitis and uric acid locally and systematically. The aim of this systematic review was to systemically evaluate the association between periodontitis and the uric acid (UA) levels in blood, saliva and gingival crevicular fluid (GCF).

METHODS

Relevant clinical studies up to January 28, 2023 were identified and retrieved from electronic databases including PubMed, Scopus, EMBASE and Web of Science, with periodontitis, uric acid, hyperuricemia and gout as the keywords. The weighted (WMD) or standardized mean difference (SMD) was calculated using fixed- or random-effect models. Methodological heterogeneity was assessed.

RESULTS

Sixteen eligible observational studies and one RCT were enrolled, which included 1354 patients with periodontitis and 989 controls. Three sample types for UA detection were involved, including blood (n = 8), saliva (n = 9) and GCF (n = 1). Meta-analysis demonstrated an enhanced plasma UA concentration (WMD = 1.00 mg/dL, 95% CI 0.63 to 1.37, P < 0.001) but a decreased salivary UA level (SMD = -0.95, 95% CI -1.23 to -0.68, P < 0.001) in periodontitis versus control. Statistical heterogeneity among the plasma- and saliva-tested studies were moderate (I² = 58.3%, P = 0.066) and low (I² = 33.8%, P = 0.196), respectively.

CONCLUSIONS

Within the limitations of the enrolled studies, it seems that there is an association between periodontitis and increased blood UA and decreased salivary UA. (Registration no. CRD42020172535 in Prospero).

The weight of words: Discursive constructions of health in weight-neutral peer-reviewed journal articles

Weight-neutral approaches to health, like the Health at Every Size® (HAES®) approach arose in response to emerging evidence showing the negative health consequences of weight-focused approaches through the effects of stigma and marginalization in many settings, including healthcare. While the discourses of dominant 'weight-normative' approaches are well-researched and described, little is known about how language and discourse is creating certain 'truths' about weight-neutral approaches. The aim of this study was to explore how academic discourses create truths about weight-neutral approaches to health. A discourse analysis of 63 academic journal articles was conducted. We found that the language used in academic literature is creating confusing and contradictory messages about weight and weight-neutral approaches to health (like the HAES® approach) through: (i) the continued use of stigmatising and normative labels like 'overweight' and 'obese', (ii) paradoxical language like 'flexible restraint', and (iii) a focus on individual responsibility and blame for health and weight without acknowledgement of broader societal and systemic factors. More research is needed to characterize weight-neutral approaches and develop a clearer framework for researchers wishing to engage with the weight-neutral paradigm of health.

Systematic review of Mendelian randomization studies on risk of cancer

BACKGROUND

We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence.

METHODS

We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded.

RESULTS

We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer.

CONCLUSIONS

Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.

Urban-rural differences in the association between long-term exposure to ambient air pollution and obesity in China

INTRODUCTION

Ambient air pollution might increase the risk of obesity; however, the evidence regarding the relationship between air pollution and obesity in comparable urban and rural areas is limited. Therefore, our aim was to contrast the effect estimates of varying air pollution particulate matter on obesity between urban and rural areas.

METHODS

Four obesity indicators were evaluated in this study, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Exposure to ambient air pollution (e.g., particulate matter with aerodynamic diameters 1.0 μm [PM₁], PM_2.5, and PM₁₀) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between air pollution particulate matter and obesity. Furthermore, the effect estimates of different air pollution particulates were contrasted between urban and rural areas.

RESULTS

A total of 36,998 participants in urban areas and 31, 256 in rural areas were included. We found positive associations between long-term exposure to PM₁, PM_2.5, and PM₁₀ and obesity. Of these air pollutants, PM_2.5 had the strongest association. The results showed that the odds ratios (ORs) for general obesity were 1.8 (95% CI, 1.64 to 1.98) per interquartile range (IQR) μg/m³ increase in PM₁, 1.89 (95% CI, 1.71 to 2.1) per IQR μg/m³ increase in PM_2.5, and 1.74 (95% CI, 1.58 to 1.9) per IQR μg/m³ increase in PM₁₀. The concentrations of air pollutants were lower in rural areas, but the effects of air pollution on obesity of rural residents were higher than those of urban residents.

CONCLUSION

Long-term (3 years average) exposure to ambient air pollution was associated with an increased risk of obesity. We observed regional disparities in the effects of particulate matter exposure from air pollution on the risk of obesity, with higher effect estimates found in rural areas. Air quality interventions should be prioritized not only in urban areas but also in rural areas to reduce the risk of obesity.

Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative

Diabetes Mellitus is one of the World Health Organization's priority diseases under research by the first and second programmes of Innovative Medicines Initiative, with the acronyms IMI1 and IMI2, respectively. Up to October of 2019, 13 projects were funded by IMI for Diabetes & Metabolic disorders, namely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. In order to prompt a better integration of achievements between the different projects, we perform a literature review and used three data sources, namely the official project's websites, the contact with the project's coordinators and co-coordinator, and the CORDIS database. From the 662 citations identified, 185 were included. The data collected were integrated into the objectives proposed for the four IMI2 program research axes: (1) target and biomarker identification, (2) innovative clinical trials paradigms, (3) innovative medicines, and (4) patient-tailored adherence programmes. The IMI funded projects identified new biomarkers, medical and research tools, determinants of inter-individual variability, relevant pathways, clinical trial designs, clinical endpoints, therapeutic targets and concepts, pharmacologic agents, large-scale production strategies, and patient-centered predictive models for diabetes and its complications. Taking into account the scientific data produced, we provided a joint vision with strategies for integrating personalized medicine into healthcare practice. The major limitations of this article were the large gap of data in the libraries on the official project websites and even the Cordis database was not complete and up to date.

Circulating Metabolites Associated with Body Fat and Lean Mass in Adults with Overweight/Obesity

The interplay between fat mass and lean mass within human metabolism is not completely understood. We aimed to identify specific circulating metabolomic profiles associated with these body composition compartments. Cross-sectional analyses were conducted over 236 adults with overweight/obesity from the Satiety Innovation (SATIN) study. Body composition was assessed by dual-energy X-ray absorptiometry. A targeted multiplatform metabolite profiling approach was applied. Associations between 168 circulating metabolites and the body composition measures were assessed using elastic net regression analyses. The accuracy of the multimetabolite weighted models was evaluated using a 10-fold cross-validation approach and the Pearson's correlation coefficients between metabolomic profiles and body compartments were estimated. Two different profiles including 86 and 65 metabolites were selected for % body fat and lean mass. These metabolites mainly consisted of lipids (sphingomyelins, phosphatidylcholines, lysophosphatidylcholines), acylcarnitines, and amino acids. Several metabolites overlapped between these body composition measures but none of them towards the same direction. The Pearson correlation coefficients between the metabolomic profiles and % body fat or lean mass were 0.80 and 0.79, respectively. Our findings suggest alterations in lipid metabolism, fatty acid oxidation, and protein degradation with increased adiposity and decreased lean body mass. These findings could help us to better understand the interplay between body composition compartments with human metabolic processes.

Social determination, health selection or indirect selection? Examining the causal directions between socioeconomic status and obesity in the Chinese adult population

Using nationally representative longitudinal data from 2010 to 2016 in China, this paper aims to systematically investigate the dynamic relationship between socioeconomic status (SES) and obesity in the Chinese adult population. We apply maximum likelihood estimations of dynamic panel models with fixed effects to evaluate the causal directions between SES and obesity, thus providing empirical evidence of the relative importance of the "social determination" hypothesis (SES determines obesity), the "health selection" hypothesis (obesity influences SES) and the "indirect selection" hypothesis (some third factors cause obesity and SES). All analyses were conducted for women and men separately. Our analyses mostly support the contention that after two years, there are no significant causal effects of either lagged SES on Body Mass Index (BMI) or BMI on SES, after controlling for time-invariant unobserved confounders. While there is weak evidence of social determination among men, non-manual workers tend to have a higher BMI than those who are unemployed. We conclude that the indirect selection hypothesis may be the most important explanation in understanding the relationship between SES and obesity in China.

What influences the "when" of eating and sleeping?A qualitative interview study

Timing of eating relative to sleep and endogenous circadian rhythm impacts weight and cardiometabolic health. We used qualitative methods to explore what influences the "when" of eating and sleeping. We conducted 37 one-on-one semi-structured interviews among participants with a body mass index (BMI) ≥ 25 kg/m² recruited from three internal medicine clinics affiliated with an urban academic hospital. Participants (70.3% Female; 51.4% White; Age range: 21-83 years old) completed measures of social jetlag, physical activity, eating habits, and mobile application use and participated in interviews following a guide developed by the study team. Responses were recorded, transcribed and coded sequentially by two trained researchers using editing-style analysis to identify themes. We identified two main themes, each with subthemes: 1) influences on the "when" of eating and sleeping, with subthemes including social jetlag and being overscheduled, and 2) contextualizing beliefs and perceptions about the "when" of eating and sleeping, with subthemes including perceived recommendations for timing of eating and sleeping, and alignment of behaviors with perceived recommendations. Many participants noted being more flexible in their eating and sleeping times on work-free vs work days. The themes this study identified should be considered when designing interventions that influence the timing of eating and sleeping for weight management.

Have Our Attempts to Curb Obesity Done More Harm Than Good?

Dieting is a common method for weight loss, maintenance, and prevention of weight gain, but the harmful outcomes of dieting are understudied. Dieting is typically advised for obese patients for the sake of their health, though this does not account for the many complicated factors surrounding obesity. We conducted a search through the PubMed database on obesity, dieting, and eating disorders and did not limit the study by population or year. We found studies showing that although dieting may cause short-term weight loss, it is associated with weight gain in the long-term. We also found studies assessing the negative psychological and physical outcomes of dieting. Though there are many studies that emphasize the negative psychological impact of dieting, few studies have explored how dieting may contribute to the development of eating disorders in the obese. Studies on the physical impact of dieting were less conclusive but warrant further study. While it is difficult to draw any substantial conclusions from the data, our results showed that dieting may carry more risks than benefits as a means to lose weight.

Rebalancing glucolipid metabolism and gut microbiome dysbiosis by nitrate-dependent alleviation of high-fat diet-induced obesity

INTRODUCTION

High-fat diet (HFD)-induced obesity is accompanied by compromised nitric oxide (NO) signaling and gut microbiome dysregulation. Inorganic dietary nitrate, which acts as a NO donor, exerts beneficial effects on metabolic disorders. Here, we evaluated the effects of dietary nitrate on HFD-induced obesity and provided insights into the underlying mechanism.

RESEARCH DESIGN AND METHODS

To investigate the preventive effect of dietary nitrate on HFD-induced obesity, C57BL/6 mice were randomly assigned into four groups (n=10/group), including normal control diet group (normal water and chow diet), HFD group (normal water and HFD), HFD+NaNO₃ group (water containing 2 mM NaNO₃ and HFD), and HFD+NaCl group (water containing 2 mM NaCl and HFD). During the experiment, body weight was monitored and glucolipid metabolism was evaluated. The mechanism underlying the effects of nitrate on HFD-induced obesity was investigated by the following: the NO₃^--NO₂^--NO pathway; endothelial NO synthase (eNOS) and cyclic guanosine monophosphate (cGMP) levels; gut microbiota via 16SRNA analysis.

RESULTS

Dietary nitrate reduced the body weight gain and lipid accumulation in adipose and liver tissues in HFD-fed mice. Hyperlipidemia and insulin resistance caused by HFD were improved in mice supplemented with nitrate. The level of eNOS was upregulated by nitrate in the serum, liver, and inguinal adipose tissue. Nitrate, nitrite, and cGMP levels were decreased in mice fed on HFD but reversed in the HFD+NaNO₃ group. Nitrate also rebalanced the colon microbiota and promoted a normal gut microbiome profile by partially attenuating the impacts of HFD. Bacteroidales S24-7, Alistipes, Lactobacillus, and Ruminococcaceae abundances were altered, and Bacteroidales S24-7 and Alistipes abundances were higher in the HFD+NaNO₃ group than that in the HFD group.

CONCLUSIONS

Inorganic dietary nitrate alleviated HFD-induced obesity and ameliorated disrupted glucolipid metabolism via NO₃^--NO₂^--NO pathway activation and gut microbiome modulation.

Obesity and Cancer Treatment Outcomes: Interpreting the Complex Evidence

A wealth of epidemiological evidence, combined with plausible biological mechanisms, present a convincing argument for a causal relationship between excess adiposity, commonly approximated as body mass index (BMI, kg/m²), and incident cancer risk. Beyond this relationship, there are a number of challenges posed in the context of interpreting whether being overweight (BMI 25.0-29.9 kg/m²) or obese (BMI ≥ 30.0 kg/m²) adversely influences disease progression, cancer mortality and survival. Elevated BMI (≥ 25.0 kg/m²) may influence treatment selection of, for example, the approach to surgery; the choice of chemotherapy dosing; the inclusion of patients into randomised clinical trials. Furthermore, the technical challenges posed by an elevated BMI may adversely affect surgical outcomes, for example, morbidity (increasing the risk of surgical site infections), reduced lymph node harvest (and subsequent risk of under-staging and under-treatment) and increased risk of margin positivity. Suboptimal chemotherapy dosing, associated with capping chemotherapy in obese patients as an attempt to avoid excess toxicity, might be a driver of poor prognostic outcomes. By contrast, the efficacy of immune checkpoint inhibition may be enhanced in patients who are obese, although in turn, this observation might be due to reverse causality. So, a central research question is whether being overweight or obese adversely affects outcomes either directly through effects of cancer biology or whether adverse outcomes are mediated through indirect pathways. A further dimension to this complex relationship is the obesity paradox, a phenomenon where being overweight or obese is associated with improved survival where the reverse is expected. In this overview, we describe a framework for evaluating methodological problems such as selection bias, confounding and reverse causality, which may contribute to spurious interpretations. Future studies will need to focus on prospective studies with well-considered methodology in order to improve the interpretation of causality.

Associations between adipose tissue volume and small molecules in plasma and urine among asymptomatic subjects from the general population

Obesity is one of the major risk factor for cardiovascular and metabolic diseases. A disproportional accumulation of fat at visceral (VAT) compared to subcutaneous sites (SAT) has been suspected as a key detrimental event. We used non-targeted metabolomics profiling to reveal metabolic pathways associated with higher VAT or SAT amount among subjects free of metabolic diseases to identify possible contributing metabolic pathways. The study population comprised 491 subjects [mean (standard deviation): age 44.6 yrs (13.0), body mass index 25.4 kg/m² (3.6), 60.1% females] without diabetes, hypertension, dyslipidemia, the metabolic syndrome or impaired renal function. We associated MRI-derived fat amounts with mass spectrometry-derived metabolites in plasma and urine using linear regression models adjusting for major confounders. We tested for sex-specific effects using interactions terms and performed sensitivity analyses for the influence of insulin resistance on the results. VAT and SAT were significantly associated with 155 (101 urine) and 49 (29 urine) metabolites, respectively, of which 45 (27 urine) were common to both. Major metabolic pathways were branched-chain amino acid metabolism (partially independent of insulin resistance), surrogate markers of oxidative stress and gut microbial diversity, and cortisol metabolism. We observed a novel positive association between VAT and plasma levels of the potential pharmacological agent piperine. Sex-specific effects were only a few, e.g. the female-specific association between VAT and O-methylascorbate. In brief, higher VAT was associated with an unfavorable metabolite profile in a sample of healthy, mostly non-obese individuals from the general population and only few sex-specific associations became apparent.

Long-term trends (1973-14) for obesity and educational inequalities among Austrian adults: men in the fast lane

BACKGROUND

The examination of obesity trends is important to plan public health interventions specific to target-groups. We investigated long-term trends of obesity for the Austrian adult population between 1973 and 2014 according to their sex, age and education and the magnitude of educational-inequalities.

METHODS

Data were derived from six national, representative, cross-sectional interview surveys (N = 194 030). Data correction factors for self-reported body mass index (BMI) were applied. Obesity was defined as BMI ≥ 30 kg/m2. Absolute changes (ACs) and aetiologic fractions (AFs) were calculated to identify trends in the obesity prevalence. To measure the extent of social inequality, the relative index of inequality was computed based on educational levels.

RESULTS

In 2014, the age-adjusted prevalence of obesity was 14.6% (95%CI: 14.0-15.3) for women and 16.8% (95%CI: 16.1-17.9) for men. Obesity was most prevalent among subjects aged 55-74 years and those with low educational status. The AC in the obesity prevalence during the study period was highest for men aged 75 years and older with high/middle educational levels (16.2%) and also high for subjects aged 55 years and older with low educational levels. The greatest dynamics for obesity were observed among the oldest men with high/middle educational levels. Educational inequalities for obesity were higher among women, but only increased among men.

CONCLUSIONS

Since 1973, the prevalence for obesity was observed to be higher for men than women in Austria for the first time. Men showed the greatest increase in prevalence and risk for obesity during the study period. Further studies are needed to determine the drivers behind these trends.

Best practices in nutrition science to earn and keep the public's trust

Public trust in nutrition science is the foundation on which nutrition and health progress is based, including sound public health. An ASN-commissioned, independent Advisory Committee comprehensively reviewed the literature and available public surveys about the public's trust in nutrition science and the factors that influence it and conducted stakeholder outreach regarding publicly available information. The Committee selected 7 overlapping domains projected to significantly influence public trust: 1) conflict of interest and objectivity; 2) public benefit; 3) standards of scientific rigor and reproducibility; 4) transparency; 5) equity; 6) information dissemination (education, communication, and marketing); and 7) accountability. The literature review comprehensively explored current practices and threats to public trust in nutrition science, including gaps that erode trust. Unfortunately, there is a paucity of peer-reviewed material specifically focused on nutrition science. Available material was examined, and its analysis informed the development of priority best practices. The Committee proposed best practices to support public trust, appropriate to ASN and other food and nutrition organizations motivated by the conviction that public trust remains key to the realization of the benefits of past, present, and future scientific advances. The adoption of the best practices by food and nutrition organizations, such as ASN, other stakeholder organizations, researchers, food and nutrition professionals, companies, government officials, and individuals working in the food and nutrition space would strengthen and help ensure earning and keeping the public's continued trust in nutrition science.

Primary care management of obesity: Individualized treatment strategies

Obesity is a growing epidemic in the United States. This article explores the popular diet trends in the country and analyzes their potential for use among patients with comorbid conditions. The American Association of Clinical Endocrinologists and American College of Endocrinology guidelines for obesity management are used as a framework for comparison of obesity management options.

Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: a cross-sectional study of 91 105 participants from the UK Biobank

BACKGROUND

Disruption of sleep and circadian rhythmicity is a core feature of mood disorders and might be associated with increased susceptibility to such disorders. Previous studies in this area have used subjective reports of activity and sleep patterns, but the availability of accelerometer-based data from UK Biobank participants permits the derivation and analysis of new, objectively ascertained circadian rhythmicity parameters. We examined associations between objectively assessed circadian rhythmicity and mental health and wellbeing phenotypes, including lifetime history of mood disorder.

METHODS

UK residents aged 37-73 years were recruited into the UK Biobank general population cohort from 2006 to 2010. We used data from a subset of participants whose activity levels were recorded by wearing a wrist-worn accelerometer for 7 days. From these data, we derived a circadian relative amplitude variable, which is a measure of the extent to which circadian rhythmicity of rest-activity cycles is disrupted. In the same sample, we examined cross-sectional associations between low relative amplitude and mood disorder, wellbeing, and cognitive variables using a series of regression models. Our final model adjusted for age and season at the time that accelerometry started, sex, ethnic origin, Townsend deprivation score, smoking status, alcohol intake, educational attainment, overall mean acceleration recorded by accelerometry, body-mass index, and a binary measure of childhood trauma.

FINDINGS

We included 91 105 participants with accelerometery data collected between 2013 and 2015 in our analyses. A one-quintile reduction in relative amplitude was associated with increased risk of lifetime major depressive disorder (odds ratio [OR] 1·06, 95% CI 1·04-1·08) and lifetime bipolar disorder (1·11, 1·03-1·20), as well as with greater mood instability (1·02, 1·01-1·04), higher neuroticism scores (incident rate ratio 1·01, 1·01-1·02), more subjective loneliness (OR 1·09, 1·07-1·11), lower happiness (0·91, 0·90-0·93), lower health satisfaction (0·90, 0·89-0·91), and slower reaction times (linear regression coefficient 1·75, 1·05-2·45). These associations were independent of demographic, lifestyle, education, and overall activity confounders.

INTERPRETATION

Circadian disruption is reliably associated with various adverse mental health and wellbeing outcomes, including major depressive disorder and bipolar disorder. Lower relative amplitude might be linked to increased susceptibility to mood disorders.

FUNDING

Lister Institute of Preventive Medicine.

Ethnic and population differences in the genetic predisposition to human obesity

Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.

Precision Medicine in Obesity and Type 2 Diabetes: The Relevance of Early-Life Exposures

BACKGROUND

Type 2 diabetes is highly prevalent and devastating. Obesity is a diabetogenic factor, driving insulin resistance and a compensatory demand for increased insulin secretion from the pancreatic β cells; a failure to address this demand results in diabetes. Accordingly, primary and secondary prevention of obesity are at the core of diabetes prevention programs. The development of obesity and declining β-cell function often span many years or decades before diabetes is clinically manifest. Thus, characterizing the early-life process and risk factors that set disease trajectories may yield novel targets for early intervention and help improve the accuracy of prediction algorithms, factors germane to the emerging field of precision medicine.

CONTENT

Here, we overview the concepts of precision medicine and fetal programming. We discuss the barriers to preventing obesity and type 2 diabetes in adulthood and present the rationale for considering early-life events in this context. In so doing, we discuss proof-of-concept studies and cutting-edge technological developments that are likely to transform current thinking on the etiology and pathogenesis of obesity and type 2 diabetes. We also review the factors hampering progress, including the success and failures of pregnancy intervention trials.

SUMMARY

Obesity and type 2 diabetes are among the major health and economic burdens of our time. Defeating these diseases is likely to require life-course approaches, which may include aggressive interventions informed by biomarker profiling undertaken during early life.

Relationships between Sexual Orientation, Weight, and Health in a Population-Based Sample of California Women

BACKGROUND

Most biomedical research has reported associations between weight and physical health problems; little is known about whether those associations vary by sexual identity.

METHODS

Pooled data from the 2003 through 2013 waves of the California Health Interview Survey was used to construct logistic regression models to examine whether the associations between weight and four chronic conditions (type 2 diabetes, hypertension, heart disease, and asthma) varied by sexual identity.

RESULTS

A total of 97,720 heterosexual and 2,822 lesbian/bisexual women comprised the analytic sample. There was a significant interaction between weight status and sexual identity (p < .001) for all four chronic diseases. Among lesbian/bisexual women, weight status was positively associated with heart disease, hypertension, asthma, and diabetes, although the associations between any weight status and heart disease, and between overweight and asthma, were not statistically significant. Among heterosexual women, weight status was positively and significantly associated with heart disease, hypertension, asthma, and diabetes. Except for overweight and heart disease, these associations remained significant after adjustment for covariates.

CONCLUSION

This study underscores the importance of disaggregating analyses by sexual identity in studies that examine weight-chronic disease associations.