Variation in rates of caesarean section among English NHS trusts after accounting for maternal and clinical risk: cross sectional study

Objective To determine whether the variation in unadjusted rates of caesarean section derived from routine data in NHS trusts in England can be explained by maternal characteristics and clinical risk factors

Impacts of wastewater treatment plant effluent on energetics and stress response of rainbow darter (Etheostoma caeruleum) in the Grand River watershed

The final publication is available at Elsevier via https://doi.org/10.1016/j.cbpb.2017.11.011. © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The objective of this study was to assess the effects of municipal wastewater treatment plant effluent on the energetics and stress response of rainbow darter (Etheostoma caeruleum). Male and female rainbow darter were collected upstream and downstream of the Waterloo WWTP in the Grand River watershed, ON, Canada. To assess the effects of wastewater treatment plant effluent on whole-body and tissue specific metabolic capacity, closed-chamber respirometry and muscle-enzyme activity analyses were performed. Plasma cortisol was also collected from fish before and after an acute air-exposure stressor to evaluate the cortisol stress response in fish exposed to additional stressors. Male and female rainbow darter collected downstream of the effluent had higher oxygen consumption rates, while differences in enzyme activities were primarily associated with sex rather than collection site. No impairment in the cortisol stress response between downstream and upstream fish was observed, however baseline cortisol levels in female fish from the downstream site were significantly higher compared to other baseline groups. Stress-induced cortisol levels were also higher in female fish from both sites when compared to their male counterparts. Overall, this study demonstrates that chronic exposure to WWTP effluent impacts whole-body metabolic performance. This study was also able to demonstrate that sex-differences are a key determinant of various metabolic changes in response to physiological stress, thereby, providing a novel avenue to be considered and further explored.Natural Sciences and Engineering Research Council (Grant RGPIN-2015-05643)Canada Foundation for Innovation (Grant CFI 34317

A smartphone app for improving mental health through connecting with urban nature

In an increasingly urbanised world where mental health is currently in crisis, interventions to increase human engagement and connection with the natural environment are one of the fastest growing, most widely accessible, and cost-effective ways of improving human wellbeing. This study aimed to provide an evaluation of a smartphone app-based wellbeing intervention. In a randomised controlled trial study design, the app prompted 582 adults, including a subgroup of adults classified by baseline scores on the Recovering Quality of Life scale as having a common mental health problem (n = 148), to notice the good things about urban nature (intervention condition) or built spaces (active control). There were statistically significant and sustained improvements in wellbeing at one-month follow-up. Importantly, in the noticing urban nature condition, compared to a built space control, improvements in quality of life reached statistical significance for all adults and clinical significance for those classified as having a mental health difficulty. This improvement in wellbeing was partly explained by significant increases in nature connectedness and positive affect. This study provides the first controlled experimental evidence that noticing the good things about urban nature has strong clinical potential as a wellbeing intervention and social prescription

Unhealthy Food and Beverage Marketing to Children in the Digital Age: Global Research and Policy Challenges and Priorities.

Food and nonalcoholic beverage marketing is implicated in poor diet and obesity in children. The rapid growth and proliferation of digital marketing has resulted in dramatic changes to advertising practices and children's exposure. The constantly evolving and data-driven nature of digital food marketing presents substantial challenges for researchers seeking to quantify the impact on children and for policymakers tasked with designing and implementing restrictive policies. We outline the latest evidence on children's experience of the contemporary digital food marketing ecosystem, conceptual frameworks guiding digital food marketing research, the impact of digital food marketing on dietary outcomes, and the methods used to determine impact, and we consider the key research and policy challenges and priorities for the field. Recent methodological and policy developments represent opportunities to apply novel and innovative solutions to address this complex issue, which could drive meaningful improvements in children's dietary health

Sex differences in the association between socioeconomic status and diabetes prevalence and incidence in China: cross-sectional and prospective studies of 0.5 million adults

Aims/hypothesis China has undergone rapid socioeconomic transition accompanied by lifestyle changes that are expected to have a profound impact on the health of its population. However, there is limited evidence from large nationwide studies about the relevance of socioeconomic status (SES) to risk of diabetes. We describe the associations of two key measures of SES with prevalent and incident diabetes in Chinese men and women. Methods The China Kadoorie Biobank study included 0.5 million adults aged 30–79 years recruited from ten diverse areas in China during 2004–2008. SES was assessed using the highest educational level attained and annual household income. Prevalent diabetes was identified from self-report and plasma glucose measurements. Incident diabetes was identified from linkage to disease and death registries and national health insurance claim databases. We estimated adjusted ORs and HRs for prevalent and incident diabetes associated with SES using logistic and Cox regression models, respectively. Results At baseline, 30,066 (5.9%) participants had previously diagnosed (3.1%) or screen-detected (2.8%) diabetes among 510,219 participants included for cross-sectional analyses. There were 480,153 people without prevalent diabetes at baseline, of whom 9544 (2.0%) had new-onset diabetes during follow-up (median 7 years). Adjusted ORs (95% CIs) for prevalent diabetes, comparing highest vs lowest educational level, were 1.21 (1.09, 1.35) in men and 0.69 (0.63, 0.76) in women; for incident diabetes, the corresponding HRs were 1.27 (1.07, 1.51) and 0.80 (0.67, 0.95), respectively. For household income, the adjusted ORs for prevalent diabetes, comparing highest vs lowest categories, were 1.45 (1.34, 1.56) in men and 1.26 (1.19, 1.34) in women; for incident diabetes, the HRs were 1.36 (1.19, 1.55) and 1.06 (0.95, 1.17), respectively. Conclusions/interpretation Among Chinese adults, the associations between education and diabetes prevalence and incidence differed qualitatively between men and women, whereas higher household income was positively associated with diabetes prevalence and incidence in both sexes, with a stronger relationship in men than in women.</p

Association of vitamin D with risk of type 2 diabetes:A Mendelian randomisation study in European and Chinese adults

BACKGROUND:Observational studies have reported that higher plasma 25-hydroxyvitamin D (25[OH]D) concentrations are associated with lower risks of diabetes, but it is unclear if these associations are causal. The aim of this study was to test the relevance of 25(OH)D for type 2 diabetes using genetically instrumented differences in plasma 25(OH)D concentrations. METHODS AND FINDINGS:Data were available on four 25(OH)D single nucleotide polymorphisms (SNPs; n = 82,464), plasma 25(OH)D concentrations (n = 13,565), and cases with diabetes (n = 5,565) in the China Kadoorie Biobank (CKB). The effects on risk of diabetes were assessed by a genetic score using two 25(OH)D synthesis SNPs (DHCR7-rs12785878 and CYP2R1-rs10741657), with and without the addition of SNPs affecting the transport (GC/DBP-rs2282679) and catabolism (CYP24A1-rs6013897) of 25(OH)D. The CKB results were combined in a meta-analysis of 10 studies for the 2 synthesis SNPs (n = 58,312 cases) and 7 studies for all 4 SNPs (n = 32,796 cases). Mean (SD) 25(OH)D concentration was 62 (20) nmol/l in CKB, and the per allele effects of genetic scores on 25(OH)D were 2.87 (SE 0.39) for the synthesis SNPs and 3.54 (SE 0.32) for all SNPs. A 25-nmol/l higher biochemically measured 25(OH)D was associated with a 9% (95% CI: 0%-18%) lower risk of diabetes in CKB. In a meta-analysis of all studies, a 25-nmol/l higher genetically instrumented 25(OH)D concentration was associated with a 14% (95% CI: 3%-23%) lower risk of diabetes (p = 0.01) using the 2 synthesis SNPs. An equivalent difference in 25(OH)D using a genetic score with 4 SNPs was not significantly associated with diabetes (odds ratio 8%, 95% CI: -1% to 16%, lower risk, p = 0.07), but had some evidence of pleiotropy. A limitation of the meta-analysis was the access only to study level rather than individual level data. CONCLUSIONS:The concordant risks of diabetes for biochemically measured and genetically instrumented differences in 25(OH)D using synthesis SNPs provide evidence for a causal effect of higher 25(OH)D for prevention of diabetes

Frequency and types of clusters of major chronic diseases in 0.5 million adults in urban and rural China

Background: Little is known about the frequency and types of disease clusters involving major chronic diseases that contribute to multimorbidity in China. We examined the frequency of disease clusters involving major chronic diseases and their relationship with age and socioeconomic status in 0.5 million Chinese adults.Methods: Multimorbidity was defined as the presence of at least two or more of five major chronic diseases: stroke, ischaemic heart disease (IHD), diabetes, chronic obstructive pulmonary disease (COPD) and cancer. Multimorbid disease clusters were estimated using both self-reported doctor-diagnosed diseases at enrolment and incident cases during 10-year follow-up. Frequency of multimorbidity was assessed overall and by age, sex, region, education and income. Association rule mining (ARM) and latent class analysis (LCA) were used to assess clusters of the five major diseases.Results: Overall, 11% of Chinese adults had two or more major chronic diseases, and the frequency increased with age (11%, 24% and 33% at age 50-59, 60-69 and 70-79 years, respectively). Multimorbidity was more common in men than women (12% vs 11%) and in those living in urban than in rural areas (12% vs 10%), and was inversely related to levels of education. Stroke and IHD were the most frequent combinations, followed by diabetes and stroke. The patterns of self-reported disease clusters at baseline were similar to those that were recorded during the first 10 years of follow-up.Conclusions: Cardiometabolic and cardiorespiratory diseases were most common disease clusters. Understanding the nature of such clusters could have implications for future prevention strategies.</div

Multi-ancestry genome-wide study in &gt;2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P&lt;5×10 - 8 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care. </p

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p