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Background: The increasing prevalence of colorectal cancer (CRC) in Iran over the past three decades has made it a key public health burden. This study aimed to predict metastasis in CRC patients using machine learning (ML) approaches in terms of demographic and clinical factors., Methods: This study focuses on 1,127 CRC patients who underwent appropriate treatments at Taleghani Hospital, a tertiary care facility. The patients were divided into training and test datasets in an 80:20 ratio. Various ML methods, including Naive Bayes (NB), random rorest (RF), support vector machine (SVM), neural network (NN), decision tree (DT), and logistic regression (LR), were used for predicting metastasis in CRC patients. Model performance was evaluated using 5-fold cross-validation, reporting sensitivity, specificity, the area under the curve (AUC), and other indexes., Results: Among the 1,127 patients, 183 (16%) had experienced metastasis. In the predictionof metastasis, both the NN and RF algorithms had the highest AUC, while SVM ranked third in both the original and balanced datasets. The NN and RF algorithms achieved the highest AUC (100%), sensitivity (100% and 100%, respectively), and accuracy (99.2% and 99.3%, respectively) on the balanced dataset, followed by the SVM with an AUC of 98.8%, a sensitivity of 97.5%, and an accuracy of 97%. Moreover, lower false negative rate (FNR), false positive rate (FPR), and higher negative predictive value (NPV) can be confirmed by these two methods. The results also showed that all methods exhibited good performance in the test datasets, and the balanced dataset improved the performance of most ML methods. The most important variables for predicting metastasis were the tumor stage, the number of involved lymph nodes, and the treatment type. In a separate analysis of patients with tumor stages I-III, it was identified that tumor grade, tumor size, and tumor stage are the most important features., Conclusion: This study indicated that NN and RF were the best among ML-based approaches for predicting metastasis in CRC patients. Both the tumor stage and the number of involved lymph nodes were considered the most important features., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Talebi, Celis-Morales, Akbari, Talebi, Borumandnia and Pourhoseingholi.)

Background: Preliminary evidence demonstrates some parameters of metabolic control, including glycaemic control, lipid control and insulin resistance, vary across the menstrual cycle. However, the literature is inconsistent, and the underlying mechanisms remain uncertain. This study aimed to investigate the association between the menstrual cycle phase and metabolites and to explore potential mediators and moderators of these associations., Methods: We undertook a cross-sectional cohort study using UK Biobank. The outcome variables were glucose; triglyceride; triglyceride to glucose index (TyG index); total, HDL and LDL cholesterol; and total to HDL cholesterol ratio. Generalised additive models (GAM) were used to investigate non-linear associations between the menstrual cycle phase and outcome variables. Anthropometric, lifestyle, fitness and inflammatory markers were explored as potential mediators and moderators of the associations between the menstrual cycle phase and outcome variables., Results: Data from 8694 regularly menstruating women in UK Biobank were analysed. Non-linear associations were observed between the menstrual cycle phase and total (p < 0.001), HDL (p < 0.001), LDL (p = 0.012) and total to HDL cholesterol (p < 0.001), but not glucose (p = 0.072), triglyceride (p = 0.066) or TyG index (p = 0.100). Neither anthropometric, physical fitness, physical activity, nor inflammatory markers mediated the associations between the menstrual cycle phase and metabolites. Moderator analysis demonstrated a greater magnitude of variation for all metabolites across the menstrual cycle in the highest and lowest two quartiles of fat mass and physical activity, respectively., Conclusions: Cholesterol profiles exhibit a non-linear relationship with the menstrual cycle phase. Physical activity, anthropometric and fitness variables moderate the associations between the menstrual cycle phase and metabolite concentration. These findings indicate the potential importance of physical activity and fat mass as modifiable risk factors of the intra-individual variation in metabolic control across the menstrual cycle in pre-menopausal women., (© 2023. The Author(s).)

Objective: To investigate the association between a lifestyle score and all-cause mortality in the Chilean population., Design: Prospective study., Settings: The score was based on seven modifiable behaviours: salt intake, fruit and vegetable intake, alcohol consumption, sleep duration, smoking, physical activity and sedentary behaviours. 1-point was assigned for each healthy recommendation. Points were summed to create an unweighted score from 0 (less healthy) to 7 (healthiest). According to their score, participants were then classified into: less healthy (0-2 points), moderately healthy (3-4 points) and the healthiest (5-7 points). Associations between the categories of lifestyle score and all-cause mortality were investigated using Cox proportional hazard models adjusted for confounders. Nonlinear associations were also investigated., Participants: 2706 participants from the Chilean National Health Survey 2009-2010., Results: After a median follow-up of 10·9 years, 286 (10·6 %) participants died. In the maximally adjusted model, and compared with the healthiest participants, those less healthy had 2·55 (95 % CI 1·75, 3·71) times higher mortality risk due to any cause. Similar trends were identified for the moderately healthy group. Moreover, there was a significant trend towards increasing the mortality risk when increasing unhealthy behaviours (hazard ratio model 3: 1·61 (95 % CI 1·34, 1·94)). There was no evidence of nonlinearity between the lifestyle score and all-cause mortality., Conclusion: Individuals in the less healthy lifestyle category had higher mortality risk than the healthiest group. Therefore, public health strategies should be implemented to promote adherence to a healthy lifestyle across the Chilean population.

Background: Components of social connection are associated with mortality, but research examining their independent and combined effects in the same dataset is lacking. This study aimed to examine the independent and combined associations between functional and structural components of social connection and mortality., Methods: Analysis of 458,146 participants with full data from the UK Biobank cohort linked to mortality registers. Social connection was assessed using two functional (frequency of ability to confide in someone close and often feeling lonely) and three structural (frequency of friends/family visits, weekly group activities, and living alone) component measures. Cox proportional hazard models were used to examine the associations with all-cause and cardiovascular disease (CVD) mortality., Results: Over a median of 12.6 years (IQR 11.9-13.3) follow-up, 33,135 (7.2%) participants died, including 5112 (1.1%) CVD deaths. All social connection measures were independently associated with both outcomes. Friends/family visit frequencies < monthly were associated with a higher risk of mortality indicating a threshold effect. There were interactions between living alone and friends/family visits and between living alone and weekly group activity. For example, compared with daily friends/family visits-not living alone, there was higher all-cause mortality for daily visits-living alone (HR 1.19 [95% CI 1.12-1.26]), for never having visits-not living alone (1.33 [1.22-1.46]), and for never having visits-living alone (1.77 [1.61-1.95]). Never having friends/family visits whilst living alone potentially counteracted benefits from other components as mortality risks were highest for those reporting both never having visits and living alone regardless of weekly group activity or functional components. When all measures were combined into overall functional and structural components, there was an interaction between components: compared with participants defined as not isolated by both components, those considered isolated by both components had higher CVD mortality (HR 1.63 [1.51-1.76]) than each component alone (functional isolation 1.17 [1.06-1.29]; structural isolation 1.27 [1.18-1.36])., Conclusions: This work suggests (1) a potential threshold effect for friends/family visits, (2) that those who live alone with additional concurrent markers of structural isolation may represent a high-risk population, (3) that beneficial associations for some types of social connection might not be felt when other types of social connection are absent, and (4) considering both functional and structural components of social connection may help to identify the most isolated in society., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Aims: To investigate the combined association of adiposity and walking pace with incident type 2 diabetes., Methods: We undertook a prospective cohort study in 194 304 White-European participants (mean age 56.5 years, 55.9% women). Participants' walking pace was self-reported as brisk, average or slow. Adiposity measures included body mass index (BMI), waist circumference (WC) and body fat percentage (BF%). Associations were investigated using Cox proportional hazard models, with a 2-year landmark analysis. A four-way decomposition analysis was used for mediation and additive interaction., Results: The median (interquartile range) follow-up was 5.4 (4.8-6.3) years. During the follow-up period, 4564 participants developed type 2 diabetes. Compared to brisk-walking participants with normal BMI, those with obesity who walked briskly were at an approximately 10- to 12-fold higher risk of type 2 diabetes (hazard ratio [HR] 9.64, 95% confidence interval [CI] 7.24-12.84, in women; HR 11.91, 95% CI 8.80-16.12, in men), whereas those with obesity and walked slowly had an approximately 12- to 15-fold higher risk (HR 12.68, 95% CI 9.62-16.71, in women; HR 15.41, 95% CI 11.27-21.06, in men). There was evidence of an additive interaction between WC and BF% and walking pace among women, explaining 17.8% and 47.9% excess risk respectively. Obesity mediated the association in women and men, accounting for 60.1% and 44.9%, respectively., Conclusions: Slow walking pace is a risk factor for type 2 diabetes independent of adiposity. Promoting brisk walking as well as weight management might be an effective type 2 diabetes prevention strategy given their synergistic effects., (© 2023 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Background: Coffee is among the most consumed beverages worldwide. Coffee consumption has been associated with lower risk of type 2 diabetes mellitus (T2D), but underlying mechanisms are not well understood. We aimed to study the role of classic and novel-T2D biomarkers with anti- or pro-inflammatory activity in the association between habitual coffee intake and T2D risk. Furthermore, we studied differences by coffee types and smoking status in this association., Methods: Using two large population-based cohorts, the UK-Biobank (UKB; n = 145,368) and the Rotterdam Study (RS; n = 7111), we investigated associations of habitual coffee consumption with incident T2D and repeated measures of insulin resistance (HOMA-IR), using Cox proportional hazards and mixed effect models, respectively. Additionally, we studied associations between coffee and subclinical inflammation biomarkers including C-reactive protein (CRP) and IL-13, and adipokines, such as adiponectin and leptin, using linear regression models. Next, we performed formal causal mediation analyses to investigate the role of coffee-associated biomarkers in the association of coffee with T2D. Finally, we evaluated effect modification by coffee type and smoking. All models were adjusted for sociodemographic, lifestyle and health-related factors., Results: During a median follow-up of 13.9 (RS) and 7.4 (UKB) years, 843 and 2290 incident T2D cases occurred, respectively. A 1 cup/day increase in coffee consumption was associated with 4% lower T2D risk (RS, HR = 0.96 [95%CI 0.92; 0.99], p = 0.045; UKB, HR = 0.96 [0.94; 0.98], p < 0.001), with lower HOMA-IR (RS, log-transformed β = -0.017 [-0.024;-0.010], p < 0.001), and with lower CRP (RS, log-transformed β = -0.014 [-0.022;-0.005], p = 0.002; UKB, β = -0.011 [-0.012;-0.009], p < 0.001). We also observed associations of higher coffee consumption with higher serum adiponectin and IL-13 concentrations, and with lower leptin concentrations. Coffee-related CRP levels partially mediated the inverse association of coffee intake with T2D incidence (average mediation effect RS β = 0.105 (0.014; 0.240), p = 0.016; UKB β = 6.484 (4.265; 9.339), p < 0.001), with a proportion mediated by CRP from 3.7% [-0.012%; 24.4%] (RS) to 9.8% [5,7%; 25.8%] (UKB). No mediation effect was observed for the other biomarkers. Coffee-T2D and coffee-CRP associations were generally stronger among consumers of ground (filtered or espresso) coffee and among never and former smokers., Conclusions: Lower subclinical inflammation may partially mediate the beneficial association between coffee consumption and lower T2D risk. Consumers of ground coffee and non-smokers may benefit the most. KEYWORDS (MESH TERMS): coffee consumptions; diabetes mellitus, type 2; inflammation; adipokines; biomarkers; mediation analysis; follow-up studies., Competing Interests: Conflict of Interest The authors declare no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Gastric cancer (GC), with a 5-year survival rate of less than 40%, is known as the fourth principal reason of cancer-related mortality over the world. This study aims to develop predictive models using different machine learning (ML) classifiers based on both demographic and clinical variables to predict metastasis status of patients with GC. The data applied in this study including 733 of GC patients, divided into a train and test groups at a ratio of 8:2, diagnosed at Taleghani tertiary hospital. In order to predict metastasis in GC, ML-based algorithms, including Naive Bayes (NB), Random Forest (RF), Support Vector Machine (SVM), Neural Network (NN), Decision Tree (RT) and Logistic Regression (LR), with 5-fold cross validation were performed. To assess the model performance, F1 score, precision, sensitivity, specificity, area under the curve (AUC) of receiver operating characteristic (ROC) curve and precision-recall AUC (PR-AUC) were obtained. 262 (36%) experienced metastasis among 733 patients with GC. Although all models have optimal performance, the indices of SVM model seems to be more appropiate (training set: AUC: 0.94, Sensitivity: 0.94; testing set: AUC: 0.85, Sensitivity: 0.92). Then, NN has the higher AUC among ML approaches (training set: AUC: 0.98; testing set: AUC: 0.86). The RF of ML-based models, which determine size of tumor and age as two essential variables, is considered as the third efficient model, because of higher specificity and AUC (84% and 87%). Based on the demographic and clinical characteristics, ML approaches can predict the metastasis status in GC patients. According to AUC, sensitivity and specificity in both SVM and NN can be regarded as better algorithms among 6 applied ML-based methods., (© 2023. The Author(s).)

Diet, the most important modulator of inflammatory and immune responses, may affect COVID-19 incidence and disease severity. Data from 196,154 members of the UK biobank had at least one 24 h dietary recall. COVID-19 outcomes were based on PCR testing, hospital admissions, and death certificates. Adjusted Poisson regression analyses were performed to estimate the risk ratios (RR) and their 95% confidence intervals (CI) for dietary inflammatory index (DII)/energy-adjusted DII (E-DII) scores. Models were adjusted for sociodemographic factors, comorbidities, smoking status, physical activity, and sleep duration. Between January 2020 and March 2021, there were 11,288 incident COVID-19 cases, 1270 COVID-19-related hospitalizations, and 315 COVID-19-related deaths. The fully adjusted model showed that participants in the highest (vs. lowest) DII/E-DII quintile were at 10-17% increased risk of COVID-19 (DII: RR Q5 vs . Q1 = 1.10, 95% CI 1.04-1.17, P trend < 0.001; E-DII: RR Q5 vs . Q1 = 1.17, 95% CI 1.10-1.24, P trend < 0.001) and ≈40% higher risk was observed for disease severity (DII: RR Q5 vs . Q1 = 1.40, 95% CI 1.18-1.67, P trend < 0.001; E-DII: RR Q5 vs . Q1 = 1.39, 95% CI 1.16-1.66, P trend < 0.001). There was a 43% increased risk of COVID-19-related death in the highest DII quintile (RR Q5 vs . Q1 = 1.43, 95% CI 1.01-2.01, P trend = 0.04). About one-quarter of the observed positive associations between DII and COVID-19-related outcomes were mediated by body mass index (25.8% for incidence, 21.6% for severity, and 19.8% for death). Diet-associated inflammation increased the risk of COVID-19 infection, severe disease, and death.

Objective: To investigate the association between self-reported walking pace and type 2 diabetes (T2D) incidence and whether it differed by physical activity levels and walking time., Methods: There were 162,155 participants (mean age, 57.1 years; 54.9% women) from the UK Biobank prospective study, recruited between 2006 and 2010, included in the study. Walking pace was self-reported and classified as brisk, average, or slow. Total physical activity and walking time were self-reported using the International Physical Activity Questionnaire. Association between walking pace and T2D incidence and the potential moderating role of physical activity and walking time were investigated using Cox proportional hazards models., Results: The median follow-up was 7.4 (interquartile range, 6.7 to 8.2) years. There were 4442 participants in whom T2D developed during the follow-up period. In the fully adjusted model (sociodemographic factors, diet, body mass index, and physical activity), average walking pace (hazard ratio [HR], 1.28; 95% CI, 1.14 to 1.44) and slow walking pace (HR, 1.91; 95% CI, 1.62 to 2.24) were associated with a higher T2D risk compared with brisk walking among women. Among men, average walking pace (HR, 1.28; 95% CI, 1.17 to 1.40) and slow walking pace (HR, 1.73; 95% CI, 1.50 to 1.99) were also associated with higher T2D risk. Compared with slow walkers, brisk walkers have the same diabetes incidence rate 18.6 and 16.0 years later, for women and men, respectively., Conclusion: Average and slow walking pace was associated with a higher risk of incident T2D in both men and women, independent of major confounding factors. The associations were consistent across different physical activity levels and walking time., (Copyright © 2022 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Gamma-glutamyltransferase (GGT) levels in the blood can be a sensitive marker of liver injury but the extent to which they give insight into risk across multiple outcomes in a clinically useful way remains uncertain., Methods: Using data from 293,667 UK Biobank participants, the relationship of GGT concentrations to self-reported alcohol intake and adiposity markers were investigated. We next investigated whether GGT predicted liver-related, cardiovascular (CV) or all-cause mortality, and potentially improved CV risk prediction., Findings: Higher alcohol intake and greater waist circumference (WC) were associated with higher GGT; the association was stronger for alcohol with evidence of a synergistic effect of WC. Higher GGT concentrations were associated with multiple outcomes. Compared to a GGT of 14.5 U/L (lowest decile), values of 48 U/L for women and 60 U/L for men (common upper limits of 'normal') had hazard ratios (HRs) for liver-related mortality of 1.83 (95% CI 1.60-2.11) and 3.25 (95% CI 2.38-4.42) respectively, for CV mortality of 1.21 (95% CI 1.14-1.28) and 1.43 (95% CI 1.27-1.60) and for all-cause mortality of 1.15 (95% CI 1.12-1.18) and 1.31 (95% CI 1.24-1.38). Adding GGT to a risk algorithm for CV mortality reclassified an additional 1.24% (95% CI 0.14-2.34) of participants across a binary 5% 10-year risk threshold., Interpretation: Our study suggests that a modest elevation in GGT levels should trigger a discussion with the individual to review diet and lifestyle including alcohol intake and consideration of formal liver disease and CV risk assessment if not previously done., Funding: British Heart Foundation Centre of Research Excellence Grant (grant number RE/18/6/34217), NHS Research Scotland (grant number SCAF/15/02), the Medical Research Council (grant number MC&#95;UU&#95;00022/2); and the Scottish Government Chief Scientist Office (grant number SPHSU17)., Competing Interests: PW has received research grants from Roche Diagnostics, AstraZeneca and Boehringer Ingelheim outside the submitted work, and NS has received grants from AstraZeneca, Boehringer Ingelheim, and Roche Diagnostics, and personal fees from Afimmune, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Hanmi Pharmaceuticals, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pfizer, and Sanofi outside the submitted work. JGFC has received research grants from Bayer, Pharmacosmos and Vifor outside the submitted work All the other authors declare no conflict of interests., (© 2022 The Authors.)

Objective: Type 2 diabetes has been associated with high dementia risk. However, the links to different dementia subtypes is unclear. We examined to what extent type 2 diabetes is associated with dementia subtypes and whether such associations differed by glycemic control., Research Design and Methods: We used data from the Swedish National Diabetes Register and included 378,299 patients with type 2 diabetes and 1,886,022 control subjects matched for age, sex, and county randomly selected from the Swedish Total Population Register. The outcomes were incidence of Alzheimer disease, vascular dementia, and nonvascular dementia. The association of type 2 diabetes with dementia was stratified by baseline glycated hemoglobin (HbA1c) in patients with type 2 diabetes only. Cox regression was used to study the excess risk of outcomes., Results: Over the follow-up (median 6.8 years), dementia developed in 11,508 (3.0%) patients with type 2 diabetes and 52,244 (2.7%) control subjects. The strongest association was observed for vascular dementia, with patients with type 2 diabetes compared with control subjects having a hazard ratio [HR] of 1.34 (95% CI 1.28, 1.41). The association of type 2 diabetes with nonvascular dementia was more modest (HR 1.10 [95% CI 1.07, 1.13]). However, risk for Alzheimer disease was lower in patients with type 2 diabetes than in control subjects (HR 0.94 [95% CI 0.90, 0.99]). When the analyses were stratified by circulating concentrations of HbA1c, a dose-response association was observed., Conclusions: The association of type 2 diabetes with dementia differs by subtypes of dementia. The strongest detrimental association is observed for vascular dementia. Moreover, patients with type 2 diabetes with poor glycemic control have an increased risk of developing vascular and nonvascular dementia., (© 2022 by the American Diabetes Association.)

Aims: To investigate the population attributable fraction due to elevated lipoprotein (a) (Lp(a)) and the utility of measuring Lp(a) in cardiovascular disease (CVD) risk prediction., Methods and Results: In 413 734 participants from UK Biobank, associations of serum Lp(a) with composite fatal/non-fatal CVD (n = 10 066 events), fatal CVD (n = 3247), coronary heart disease (CHD; n = 18 292), peripheral vascular disease (PVD; n = 2716), and aortic stenosis (n = 901) were compared using Cox models. Median Lp(a) was 19.7 nmol/L (interquartile interval 7.6-75.3 nmol/L). About 20.8% had Lp(a) values >100 nmol/L; 9.2% had values >175 nmol/L. After adjustment for classical risk factors, 1 SD increment in log Lp(a) was associated with a hazard ratio for fatal/non-fatal CVD of 1.12 [95% confidence interval (CI) 1.10-1.15]. Similar associations were observed with fatal CVD, CHD, PVD, and aortic stenosis. Adding Lp(a) to a prediction model containing traditional CVD risk factors in a primary prevention group improved the C-index by +0.0017 (95% CI 0.0008-0.0026). In the whole cohort, Lp(a) above 100 nmol/L was associated with a population attributable fraction (PAF) of 5.8% (95% CI 4.9-6.7%), and for Lp(a) above 175 nmol/L the PAF was 3.0% (2.4-3.6%). Assuming causality and an achieved Lp(a) reduction of 80%, an ongoing trial to lower Lp(a) in patients with CVD and Lp(a) above 175 nmol/L may reduce CVD risk by 20.0% and CHD by 24.4%. Similar benefits were also modelled in the whole cohort, regardless of baseline CVD., Conclusion: Population screening for elevated Lp(a) may help to predict CVD and target Lp(a) lowering drugs, if such drugs prove efficacious, to those with markedly elevated levels., (© The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Introduction: The aim of this study was to determine risk of being SARS-CoV-2 positive and severe infection (associated with hospitalization/mortality) in those with family history of diabetes., Methods: We used UK Biobank, an observational cohort recruited between 2006 and 2010. We compared the risk of being SARS-CoV-2 positive and severe infection for those with family history of diabetes (mother/father/sibling) against those without., Results: Of 401,268 participants in total, 13,331 tested positive for SARS-CoV-2 and 2282 had severe infection by end of January 2021. In unadjusted models, participants with ≥2 family members with diabetes were more likely to be SARS-CoV-2 positive (risk ratio-RR 1.35; 95% confidence interval-CI 1.24-1.47) and severe infection (RR 1.30; 95% CI 1.04-1.59), compared to those without. The excess risk of being tested positive for SARS-CoV-2 was attenuated but significant after adjusting for demographics, lifestyle factors, multimorbidity and presence of cardiometabolic conditions. The excess risk for severe infection was no longer significant after adjusting for demographics, lifestyle factors, multimorbidity and presence of cardiometabolic conditions, and was absent when excluding incident diabetes., Conclusion: The totality of the results suggests that good lifestyle and not developing incident diabetes may lessen risks of severe infections in people with a strong family of diabetes., (© 2021 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)

Introduction: To investigate type 2 diabetes as a risk factor for COVID-19 death following hospital admission in Kuwait., Methods: A retrospective cohort study using data from a central hospital that cared for all hospitalized COVID-19 patients in Kuwait. We investigated the association between type 2 diabetes, with COVID-19 mortality using multiply imputed logistic regression and calculated the population attributable fraction., Results: A total of 5333 patients were admitted with COVID-19, of whom 244 died (4.6%). Diabetes prevalence was 24.8%, but 53.7% of those who died had diabetes. After adjusting for age, sex, ethnicity and other comorbidities, diabetes was associated with death (OR 1.70 [95% CI 1.23, 2.34]) and admission to the intensive care unit more than 3 days after initial admission (OR 1.78 [95% CI 1.17, 2.70]). Assuming causality, the population attributable fraction for type 2 diabetes in COVID-19 death was 19.6% (95% CI 10.8, 35.6)., Conclusion: Type 2 diabetes is a strong risk factor for COVID-19 death in the Middle East. Given the high prevalence of type 2 diabetes in the Middle East, as well as many Western countries, the public health implications are considerable., (© 2021 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)

Background: Abdominal aortic aneurysm (AAA) can occur in patients who are ineligible for routine ultrasound screening. A simple AAA risk score was derived and compared with current guidelines used for ultrasound screening of AAA., Methods: United Kingdom Biobank participants without previous AAA were split into a derivation cohort (n=401 820, 54.6% women, mean age 56.4 years, 95.5% White race) and validation cohort (n=83 816). Incident AAA was defined as first hospital inpatient diagnosis of AAA, death from AAA, or an AAA-related surgical procedure. A multivariable Cox model was developed in the derivation cohort into an AAA risk score that did not require blood biomarkers. To illustrate the sensitivity and specificity of the risk score for AAA, a theoretical threshold to refer patients for ultrasound at 0.25% 10-year risk was modeled. Discrimination of the risk score was compared with a model of US Preventive Services Task Force (USPSTF) AAA screening guidelines., Results: In the derivation cohort, there were 1570 (0.40%) cases of AAA over a median 11.3 years of follow-up. Components of the AAA risk score were age (stratified by smoking status), weight (stratified by smoking status), antihypertensive and cholesterol-lowering medication use, height, diastolic blood pressure, baseline cardiovascular disease, and diabetes. In the validation cohort, over 10 years of follow-up, the C-index for the model of the USPSTF guidelines was 0.705 (95% CI, 0.678-0.733). The C-index of the risk score as a continuous variable was 0.856 (95% CI, 0.837-0.878). In the validation cohort, the USPSTF model yielded sensitivity 63.9% and specificity 71.3%. At the 0.25% 10-year risk threshold, the risk score yielded sensitivity 82.1% and specificity 70.7% while also improving the net reclassification index compared with the USPSTF model +0.176 (95% CI, 0.120-0.232). A combined model, whereby risk scoring was combined with the USPSTF model, also improved prediction compared with USPSTF alone (net reclassification index +0.101 [95% CI, 0.055-0.147])., Conclusions: In an asymptomatic general population, a risk score based on patient age, height, weight, and medical history may improve identification of asymptomatic patients at risk for clinical events from AAA. Further development and validation of risk scores to detect asymptomatic AAA are needed.

Background: To investigate whether the excess risk of adverse health outcomes associated with a lower physical capability in adulthood differs by deprivation levels., Methods: 279,030 participants from the UK Biobank were included. Handgrip strength and walking pace were the exposures. All-cause mortality, CVD mortality and incidence were the outcomes. Townsend deprivation index was treated as a potential effect modifier. The associations were investigated using Cox-regression models with years of follow-up as the time-varying covariate., Results: A significant interaction between deprivation and handgrip strength was found for all-cause mortality (p = 0.024), CVD mortality (p = 0.006) and CVD incidence (p = 0.001). The hazard ratio for all-cause mortality was 1.18 [1.09; 1.29] per 1-tertile higher level of grip strength in the least deprived group, whereas it was 1.30 [1.18; 1.43] in the most deprived individuals. Similar results were found for CVD mortality and incidence per tertile increment in handgrip strength in the least and most deprived quintiles, respectively. No significant interactions between deprivation and walking pace were found for any of the outcomes., Conclusion: Low handgrip strength is a stronger predictor of morbidity and mortality in individuals living in more deprived areas.

Objectives: We aimed to investigate demographic, lifestyle, socioeconomic and clinical risk factors for COVID-19, and compared them to risk factors for pneumonia and influenza in UK Biobank., Design: Cohort study., Setting: UK Biobank., Participants: 49-83 year olds (in 2020) from a general population study., Main Outcome Measures: Confirmed COVID-19 infection (positive SARS-CoV-2 test). Incident influenza and pneumonia were obtained from primary care data. Poisson regression was used to study the association of exposure variables with outcomes., Results: Among 235 928 participants, 397 had confirmed COVID-19. After multivariable adjustment, modifiable risk factors were higher body mass index and higher glycated haemoglobin (HbA1C) (RR 1.28 and RR 1.14 per SD increase, respectively), smoking (RR 1.39), slow walking pace as a proxy for physical fitness (RR 1.53), and use of blood pressure medications as a proxy for hypertension (RR 1.33). Higher forced expiratory volume in 1 s (FEV1) and high-density lipoprotein (HDL) cholesterol were both associated with lower risk (RR 0.84 and RR 0.83 per SD increase, respectively). Non-modifiable risk factors included male sex (RR 1.72), black ethnicity (RR 2.00), socioeconomic deprivation (RR 1.17 per SD increase in Townsend Index), and high cystatin C (RR 1.13 per SD increase). The risk factors overlapped with pneumonia somewhat, less so for influenza. The associations with modifiable risk factors were generally stronger for COVID-19, than pneumonia or influenza., Conclusion: These findings suggest that modification of lifestyle may help to reduce the risk of COVID-19 and could be a useful adjunct to other interventions, such as social distancing and shielding of high risk., Competing Interests: Competing interests: PW has received research grants from Roche Diagnostics, AstraZeneca and Boehringer Ingelheim outside the submitted work, and NS has received grant and personal fees from Boehringer Ingelheim, and personal fees from Amgen, AstraZeneca, Eli Lilly, Novo Nordisk, Pfizer, and Sanofi outside the submitted work. All authors declare no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Older people have been reported to be at higher risk of COVID-19 mortality. This study explored the factors mediating this association and whether older age was associated with increased mortality risk in the absence of other risk factors., Methods: In UK Biobank, a population cohort study, baseline data were linked to COVID-19 deaths. Poisson regression was used to study the association between current age and COVID-19 mortality., Results: Among eligible participants, 438 (0.09%) died of COVID-19. Current age was associated exponentially with COVID-19 mortality. Overall, participants aged ≥75 years were at 13-fold (95% CI 9.13-17.85) mortality risk compared with those <65 years. Low forced expiratory volume in 1 second, high systolic blood pressure, low handgrip strength, and multiple long-term conditions were significant mediators, and collectively explained 39.3% of their excess risk. The associations between these risk factors and COVID-19 mortality were stronger among older participants. Participants aged ≥75 without additional risk factors were at 4-fold risk (95% CI 1.57-9.96, P = 0.004) compared with all participants aged <65 years., Conclusions: Higher COVID-19 mortality among older adults was partially explained by other risk factors. 'Healthy' older adults were at much lower risk. Nonetheless, older age was an independent risk factor for COVID-19 mortality., Competing Interests: The authors have declared that no competing interests exist.

Objective: To inform potential guideline development, we investigated nonlinear associations between television viewing time (TV time) and adverse health outcomes., Methods: From 2006 to 2010, 490,966 UK Biobank participants, aged 37 to 73 years, were recruited. They were followed from 2006 to 2018. Nonlinear associations between self-reported TV time (hours per day) and outcomes explored using penalized cubic splines in Cox proportional hazards adjusted for demographics and lifestyle. Population-attributable and potential impact fractions were calculated to contextualize population-level health outcomes associated with different TV time levels. Nonlinear isotemporal substitution analyses were used to investigate substituting TV time with alternative activities. Primary outcomes were mortality: all-cause, cardiovascular disease (CVD) and cancer; incidence: CVD and cancer; secondary outcomes were incident myocardial infarction, stroke, and heart failure and colon, lung, breast, and prostate cancer., Results: Those with noncommunicable disease (109,867 [22.4%]), CVD (32,243 [6.6%]), and cancer (37,81 [7.7%]) at baseline were excluded from all-cause mortality, CVD, and cancer analyses, respectively. After 7.0 years (mortality) and 6.2 years (disease incidence) mean follow-up, there were 10,306 (2.7%) deaths, 24,388 (5.3%) CVD events, and 39,121 (8.7%) cancer events. Associations between TV time and all-cause and CVD mortality were curvilinear (P non-linear ≤.003), with lowest risk observed <2 hours per day. Theoretically, 8.64% (95% confidence interval [CI], 6.60-10.73) of CVD mortality is attributable to TV time. Limiting TV time to 2 hours per day might have prevented, or at least delayed, 7.97% (95% CI, 5.54-10.70) of CVD deaths. Substituting TV time with sleeping, walking, or moderate or vigorous physical activity was associated with reduced risk for all outcomes when baseline levels of substitute activities were low., Conclusion: TV time is associated with numerous adverse health outcomes. Future guidelines could suggest limiting TV time to less than 2 hours per day to reduce most of the associated adverse health events., (Copyright © 2020. Published by Elsevier Inc.)

Aims: We examined the link between BMI and risk of a positive test for SARS-CoV-2 and risk of COVID-19-related death among UK Biobank participants., Methods: Among 4855 participants tested for SARS-CoV-2 in hospital, 839 were positive and of these 189 died from COVID-19. Poisson models with penalised thin plate splines were run relating exposures of interest to test positivity and case-fatality, adjusting for confounding factors., Results: BMI was associated strongly with positive test, and risk of death related to COVID-19. The gradient of risk in relation to BMI was steeper in those under 70, compared with those aged 70 years or older for COVID-19 related death (P interaction  = 0.03). BMI was more strongly related to test positivity (P interaction  = 0.010) and death (P interaction  = 0.002) in non-whites (predominantly South Asians and Afro-Caribbeans), compared with whites., Conclusions: These data add support for adiposity being more strongly linked to COVID-19-related deaths in younger people and non-white ethnicities. If future studies confirm causality, lifestyle interventions to improve adiposity status may be important to reduce the risk of COVID-19 in all, but perhaps particularly, non-white communities., Competing Interests: Declaration of competing interest NS reports personal fees from Amgen, AstraZeneca, Eli Lilly, Novo Nordisk, Pfizer, and Sanofi, and grants and personal fees from Boehringer Ingelheim, outside the submitted work. PW reports grant from Boehringer Ingelheim outside submitted work. All other authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: It is unclear what combinations of physical capability markers used to define sarcopenia have the strongest associations with health outcomes., Aim: To compare the associations between different combinations of physical capability markers of sarcopenia with cardiovascular and respiratory outcomes and all-cause mortality., Study Design: 469,830 UK Biobank participants were included in this prospective study. Four groups were derived based on combinations of three physical capability markers used to define sarcopenia or severe sarcopenia: gait speed, grip strength and muscle mass. Outcomes studied were all-cause mortality, as well as incidence and mortality from cardiovascular disease (CVD), respiratory disease and chronic obstructive pulmonary disease (COPD)., Results: All combinations of physical capability markers used to define sarcopenia or severe sarcopenia identified individuals at increased risk of respiratory disease and all-cause mortality. However, the definition most strongly associated with a wide range of adverse health outcomes was the combination of slow gait speed plus low muscle mass, followed by severe sarcopenia, and the combination of slow gait speed plus low grip strength. The current definition of sarcopenia (low grip strength plus low muscle mass) had the weakest associations with all-cause (HR: 1.35 [95% CI: 1.07 to 1.71]) and respiratory mortality (HR: 1.88 [95% CI: 1.15 to 3.10]), as well as respiratory disease (HR: 1.38 [95% CI: 1.11 to 1.73]) and COPD incidence (HR: 2.08 [95% CI: 1.14 to 3.79])., Conclusions: Associations of sarcopenia with adverse outcomes were strongest when sarcopenia was defined as slow gait speed plus low muscle mass, followed by severe sarcopenia, suggesting that this combination of physical capability markers should be still considered in the diagnosis of sarcopenia., Competing Interests: Conflict of intereset The authors declare that they have no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The aim of the current study was to investigate the association between diet and handgrip strength. The current study included 68,002 participants (age 63.8 ± 2.7 years, 50.3% women, 49.7% men) from UK Biobank. Diet and nutritional data (carotene, retinol, potassium, vitamin C, foliate, vitamin B12, vitamin B6, iron, vitamin E, calcium, magnesium, carbohydrates, protein, polyunsaturated fat, fat, starch and saturated fat) were collected and handgrip strength measured. Associations were compared, stratified by sex, using regression analyses, after adjustment for age, sex, month of assessment, ethnicity, deprivation index, height, comorbidities and total energy intake. The current data revealed negative associations between carbohydrate intake and handgrip strength as well as positive associations between oily fish, retinol and magnesium intake and grip strength in both sexes. In women, positive associations were observed between intake of red meat, fruit and vegetables, vitamin E, iron, vitamin B12, folate and vitamin C and hand grip strength. In men only negative associations were seen between bread and processed meat with grip strength. We have shown associations of several nutrients and food items with muscle strength and appropriately designed trials are needed to investigate whether these nutrients/food items may be beneficial in the maintenance of muscle during ageing., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background and Aims: COVID-19 and low levels of vitamin D appear to disproportionately affect black and minority ethnic individuals. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 risk, and whether it explained the higher incidence of COVID-19 in black and South Asian people., Methods: UK Biobank recruited 502,624 participants aged 37-73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration and ethnicity, were linked to COVID-19 test results. Univariable and multivariable logistic regression analyses were performed for the association between 25(OH)D and confirmed COVID-19, and the association between ethnicity and both 25(OH)D and COVID-19., Results: Complete data were available for 348,598 UK Biobank participants. Of these, 449 had confirmed COVID-19 infection. Vitamin D was associated with COVID-19 infection univariably (OR = 0.99; 95% CI 0.99-0.999; p = 0.013), but not after adjustment for confounders (OR = 1.00; 95% CI = 0.998-1.01; p = 0.208). Ethnicity was associated with COVID-19 infection univariably (blacks versus whites OR = 5.32, 95% CI = 3.68-7.70, p-value<0.001; South Asians versus whites OR = 2.65, 95% CI = 1.65-4.25, p-value<0.001). Adjustment for 25(OH)D concentration made little difference to the magnitude of the association., Conclusions: Our findings do not support a potential link between vitamin D concentrations and risk of COVID-19 infection, nor that vitamin D concentration may explain ethnic differences in COVID-19 infection., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2020 Diabetes India. Published by Elsevier Ltd. All rights reserved.)

Physical activity (PA) and sedentary behaviours (SB) are two independent risk factors for non-communicable diseases. However, there is a lack of objectively measured information on PA and SB in low- and middle-income countries. The aim of this study was to use objective data to characterise socio-demographic patterns of PA and SB in eight Latin American countries. 2732 participants (aged 15-65 years) from the Latin American Study of Nutrition and Health (ELANS) were included. PA and SB data were collected using accelerometers. Overall and country-specific average levels of time spent in PA and SB were compared by sex, age, socioeconomic and education level. Overall, the mean time spent in SB was 571.6 min/day, ranging from 553.8 min/day in Chile to 596.7 min/day in Peru. Average levels of light, moderate-to-vigorous physical activity (MVPA) and total PA were 311.1 min/day (95% CI: 307.7; 314.5), 34.9 min/day (95% CI: 34.0; 35.9) and 7531.2 MET-min/week (95% CI: 7450.4; 7611.9), respectively. MVPA and total PA were higher in men than women. The prevalence of physical inactivity was 40.6%, ranging from 26.9% (Chile) to 47% (Costa Rica and Venezuela). Women were more physically inactive than men (47.7% versus 33.0%). SB levels were highest among those with higher education; PA graded positively with socioeconomic level. Our findings can inform the planning of health policies and programmes designed to reduce levels of physical inactivity, as well as inform the local and cultural adaptation of these policies and programmes for implementation in Latin America. Highlights Worldwide studies of physical activity (PA) and sedentary behaviours (SB) have historically under-represented Latin American countries due to the lack of surveillance data. Across eight Latin American countries, the ELANS study collected data on PA and SB using an objective method (accelerometers) which we have analysed to quantify and characterise socio-demographic patterns. Over four-in-ten participants were physically inactive (40.6%); with a gender gap (47.7% women; 33.0% men); and striking differences between countries (47% Costa Rica and Venezuela; 26.9% Chile). In all countries, levels of moderate-to-vigorous physical activity (MVPA) were lowest, and levels of SB were highest, among participants in the higher education groups. Our findings on the unequal distribution of PA and SB increases the evidence base and can help to inform future intervention strategies in Latin America.

Purpose: To identify predictors of favorable changes to postprandial insulin and glucose levels in response to interrupting prolonged sitting time with standing or light-intensity physical activity., Methods: Data were combined from four similarly designed randomized acute cross-over trials (n = 129; body mass index [BMI] range, 19.6-44.6 kg·m; South Asian = 31.0%; dysglycemia = 27.1%). Treatments included: prolonged sitting (6.5 h) or prolonged sitting broken-up with either standing or light-intensity physical activity (5 min every 30 min). Time-averaged postprandial responses for insulin and glucose were calculated for each treatment (mean ± 95% confidence interval). Mutually adjusted interaction terms were used to examine whether anthropometric (BMI), demographic (age, sex, ethnicity [white European vs South Asian]) and a cardiometabolic variable (Homeostatic Model Assessment of Insulin Resistance)-modified responses., Results: Postprandial insulin and glucose were reduced when individuals interrupted prolonged sitting with bouts of light physical activity, but not with standing. Reductions in time-averaged postprandial insulin were more pronounced if individuals were South Asian compared with white European (-18.9 mU·L [-23.5%] vs -8.2 mU·L [-9.3%]), female compared with male (-15.0 mU·L [-21.2%] vs -12.1 mU·L [-17.6%]) or had a BMI ≥27.2 kg·m (-20.9 mU·L [-22.9%] vs -8.7 mU·L [-18.2%]). Similarly, being female (-0.4 mmol·L [-0.6 mmol·L, -0.2 mmol·L], -6.8% vs -0.1 mmol·L [-0.3 mmol·L, 1 mmol·L], -1.7%) or having a BMI ≥27.2 kg·m (-0.4 mmol·L [-0.6 mmol·L, -0.2 mmol·L], -6.7% vs -0.2 mmol·L [-0.4 mmol·L, 0.0 mmol·L], -3.4%) modified the postprandial glucose response. No significant interactions were found for Homeostatic Model Assessment of Insulin Resistance or age., Conclusions: Being female, South Asian, or having a higher BMI, all predicted greater reductions in postprandial insulin, whereas being female and having a higher BMI predicted greater reductions in postprandial glucose when sitting was interrupted with light physical activity. These results could help to guide personalized interventions in high-risk participants for whom breaking prolonged sitting time with light activity may yield the greatest therapeutic potential.

Objective: To investigate whether the addition of grip strength and/or self-reported walking pace to established cardiovascular disease (CVD) risk scores improves their predictive abilities., Patients and Methods: A total of 406,834 participants from the UK Biobank, with baseline measurements between March 13, 2006, and October 1, 2010, without CVD at baseline were included in this study. Associations of grip strength and walking pace with CVD outcomes were investigated using Cox models adjusting for classical risk factors (as included in established risk scores), and predictive utility was determined by changes in C-index and categorical net reclassification index., Results: Over a median of 8.87 years of follow-up (interquartile range 3, 8.25-9.47 years), there were 7274 composite fatal/nonfatal events (on the basis of the American College of Cardiology/American Heart Association [ACC/AHA] outcome) and 1955 fatal events (on the basis of the Systematic Coronary Risk Evaluation [SCORE] risk score). Both grip strength and walking pace were inversely associated with CVD outcomes after adjusting for classical risk factors. Addition of grip strength (change in C-index: ACC/AHA, +0.0017; SCORE, +0.0047), usual walking pace (ACC/AHA, +0.0031; SCORE, +0.0130), and both combined (ACC/AHA, +0.0041; SCORE, +0.0148) improved the C-index and also improved the net reclassification index (grip, +0.55%; walking pace, +0.53%; combined, 1.12%)., Conclusion: The present study has found that the addition of grip strength or usual walking pace to existing risk scores results in improved CVD risk prediction, with an additive effect when both are added. As both these measures are cheap and easy to administer, these tools could provide an important addition to CVD risk screening, although further external validation is required., (Copyright © 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Recent efforts to address the obesity epidemic have focused on sugar consumption, especially sugar-sweetened beverages. However, sugar takes many forms, is only one contributor to overall energy consumption and is correlated with other health-related lifestyle factors. The objective was to investigate the associations with all-cause mortality of sugar- and artificially sweetened beverages and naturally sweet juices., Methods: Setting: UK Biobank, UK. Participants joined the UK Biobank study from 2006 to 2010 and were followed up until 2016; 198,285 men and women aged 40-69 years were eligible for this study (40% of the UK Biobank), of whom 3166 (1.6%) died over a mean of 7 years follow-up., Design: prospective population-based cohort study. Exposure variables: dietary consumption of sugar-sweetened beverages, artificially sweetened beverages, naturally sweet juices (100% fruit/vegetable juices) and total sugar intake, self-reported via 24-h dietary assessment tool completed between 2009 and 2012., Main Outcome: all-cause mortality. Cox regression analyses were used to study the association between the daily intake of the above beverages and all-cause mortality. Models were adjusted for sociodemographic, economic, lifestyle and dietary confounders., Results: Total energy intake, total sugar intake and percentage of energy derived from sugar were comparable among participants who consumed > 2/day sugar-sweetened beverages and > 2/day fruit/vegetable juices (10,221 kJ/day versus 10,381 kJ/day; 183 g versus 190 g; 30.6% versus 31.0%). All-cause mortality was associated with total sugar intake (highest quintile adj. HR 1.28, 95% CI 1.06-1.55) and intake of sugar-sweetened beverages (> 2/day adj. HR 1.84, 95% CI 1.42-2.37) and remained so in sensitivity analyses. An association between artificially sweetened beverage intake and mortality did not persist after excluding deaths in the first 2 years of follow-up (landmark analysis) nor after excluding participants with recent weight loss. Furthermore, the inverse association between fruit/vegetable juice intake and mortality did not persist after additional adjustment for a diet quality score., Conclusions: Higher mortality is associated with sugar-sweetened beverages specifically. The lack of an adverse association with fruit/vegetable juices suggests that source of sugar may be important and the association with artificially sweetened beverage may reflect reverse causation.

Objective: HbA 1c levels are increasingly measured in screening for diabetes; we investigated whether HbA 1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association (ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems., Research Design and Methods: UK Biobank participants without baseline CVD or known diabetes ( n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes., Results: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% ( n = 11,665) had prediabetes (42.0-47.9 mmol/mol [6.0-6.4%]) and 0.7% ( n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69-1.97) and 2.26 (95% CI 1.96-2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03-1.20) and 1.20 (1.04-1.38), respectively. Adding HbA 1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001-0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models., Conclusions: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA 1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed., (© 2019 by the American Diabetes Association.)

Background: Although there is high prevalence of obesity and other cardiovascular risk factors among Latin American adolescents, there is limited evidence on dietary intake and physical activity (PA) patterns in this population. Therefore, we characterized anthropometry, dietary intake, PA and sitting time (ST) in adolescents aged 15-17 years from eight Latin American countries., Methods: Six hundred seventy-one adolescents (41.4% girls) from the Latin American Study of Nutrition and Health (ELANS) were included. Nutritional status was classified by four BMI (kg/m 2 ) categories. Waist circumference (WC) was categorized as above or below thresholds. Dietary intake was assessed through two non-consecutive 24-h dietary recalls. PA and ST were measured using the International Physical Activity Questionnaire (IPAQ). We calculated overall and country-specific estimates by sex and tested for differences between boys and girls., Results: Differences in the prevalence of overweightness (15.1 and 21.6%) and obesity (8.5 and 6.5%) between boys and girls, respectively, were statistically insignificant (p = 0.059). Average energy intake was 2289.7 kcal/day (95% CI: 2231-2350) for boys and 1904.2 kcal/day (95% CI: 1840-1963) for girls (p < 0.001). In relation to macronutrient intake for boys and girls, respectively, the average intake (expressed as percentage of total energy) was 15.0 and 14.9% for protein; 55.4 and 54.9% for carbohydrates; 14.1 and 14.5% for added sugar; 29.5 and 30.1% for total fat; and 9.6 and 9.9% for saturated fat (p > 0.05 for all outcomes). There was no statistically significant difference in the prevalence of total energy (TE) saturated fat and added sugar (>10% of TE) between girls and boys (49.6% versus 44.8 and 81.7% versus 76.1%, respectively). Prevalence of physical inactivity was 19% in boys and 43.7% in girls (p < 0.001). Median levels of vigorous-intensity PA and total PA were significantly higher for boys than for girls (p < 0.05 for both outcomes); whereas levels of ST were similar (273.7 versus 220.0 min/day for boys and girls, respectively; p > 0.05)., Conclusions: These findings highlight the high prevalence of poor dietary intake and physical inactivity in adolescents from Latin American countries. Therefore, effective and sustainable strategies and programmes are needed that promote healthier diets, regular PA and reduce ST among Latin American adolescents., Trial Registration: Clinical Trials NCT02226627. Retrospectively registered on August 27, 2014.

Objective: To investigate the association of cardiorespiratory fitness with all-cause mortality, and cardiovascular disease (CVD), respiratory disease, chronic obstructive pulmonary disease (COPD) and cancer mortality and incidence., Design: Prospective population-based study., Setting: UK Biobank., Participants: Of the 5 02 628 (5.5% response rate) participants recruited by UK Biobank, we included 73 259 (14.6%) participants with available data in this analysis. Of these, 1374 participants died and 4210 developed circulatory diseases, 1293 respiratory diseases and 4281 cancer, over a median of 5.0 years (IQR 4.3-5.7) follow-up., Main Outcome Measures: All-cause mortality and circulatory disease, respiratory disease, COPD and cancer (such as colorectal, lung, breast and prostate) mortality/incidence. Fitness was estimated using a submaximal cycle ergometer test., Results: The HR for all-cause mortality for each metabolic equivalent of task (MET) higher fitness was 0.96 (95% CI 0.93 to 0.98). Similar results were observed for incident circulatory disease (HR 0.96 [0.95 to 0.97]), respiratory disease (HR 0.96 [0.94 to 0.98]), COPD (HR 0.90 [0.86 to 0.95) and colorectal cancer (HR 0.96 [0.92 to 1.00]). Nonlinear analysis revealed that a high level of fitness (>10METs) was associated with a greater incidence of atrial fibrillation (HR 1.24 [1.07 to 1.44]) and prostate cancer (HR 1.16 [1.02 to 1.32]) compared with average fitness. All results were adjusted for sociodemographic, lifestyle and dietary factors, body composition, and morbidity at baseline and excluded events in the first 2 years of follow-up., Conclusions: Higher cardiorespiratory fitness was associated with lower risk of premature mortality and incidence of CVD, respiratory disease and colorectal cancer., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk-prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine which was the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models and adjusting for atherosclerotic risk factors (per relevant risk scores), and the predictive utility was determined by the C-statistic and categorical net reclassification index. We show that eGFRcys is most strongly associated with CVD and mortality, and, along with albuminuria, adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment.

Objective: To investigate the associations of objectively measured cardiorespiratory fitness (CRF) and grip strength (GS) with incident heart failure (HF), a clinical syndrome that results in substantial social and economic burden, using UK Biobank data., Patients and Methods: Of the 502,628 participants recruited into the UK Biobank between April 1, 2007, and December 31, 2010, a total of 374,493 were included in our GS analysis and 57,053 were included in CRF analysis. Associations between CRF and GS and incident HF were investigated using Cox proportional hazard models, with adjustment for known measured confounders., Results: During a mean of 4.1 (range, 2.4-7.1) years, 631 HF events occurred in those with GS data, and 66 HF events occurred in those with CRF data. Higher CRF was associated with 18% lower risk for HF (hazard ratio [HR], 0.82; 95% CI, 0.76-0.88) per 1-metabolic equivalent increment increase and GS was associated with 19% lower incidence of HF risk (HR, 0.81; 95% CI, 0.77-0.86) per 5-kg increment increase. When CRF and GS were standardized, the HR for CRF was 0.50 per 1-SD increment (95% CI, 0.38-0.65), and for GS was 0.65 per 1-SD increment (95% CI, 0.58-0.72)., Conclusion: Our data indicate that objective measurements of physical function (GS and CRF) are strongly and independently associated with lower HF incidence. Future studies targeting improving CRF and muscle strength should include HF as an outcome to assess whether these results are causal., (Copyright © 2019 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Driving is a common type of sedentary behaviour; an independent risk factor for poor health. The study explores whether driving is also associated with other unhealthy lifestyle factors., Methods: In a cross-sectional study of UK Biobank participants, driving time was treated as an ordinal variable and other lifestyle factors dichotomized into low/high risk based on guidelines. The associations were explored using chi-square tests for trend and binary logistic regression., Results: Of the 386 493 participants who drove, 153 717 (39.8%) drove <1 h/day; 140 140 (36.3%) 1 h/day; 60 973 (15.8%) 2 h/day; and 31 663 (8.2%) ≥3 h/day. Following adjustment for potential confounders, driving ≥3 h/day was associated with being overweight/obese (OR = 1.74, 95% CI: 1.64-1.85), smoking (OR = 1.48, 95% CI: 1.37-1.63), insufficient sleep (1.70, 95% CI: 1.61-1.80), low fruit/vegetable intake (OR = 1.26, 95% CI: 1.18-1.35) and low physical activity (OR = 1.05, 95% CI: 1.00-1.11), with dose relationships for the first three, but was not associated with higher alcohol consumption (OR = 0.94, 95% CI: 0.87-1.02)., Conclusions: Sedentary behaviour, such as driving, is known to have an independent association with adverse health outcomes. It may have additional impact mediated through its effect on other aspects of lifestyle. People with long driving times are at higher risk and might benefit from targeted interventions., (© The Author(s) 2018. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: higher grip strength is associated with better health outcomes. The optimal way to report grip strength (i.e. absolute vs. relative) for prediction, however, remains to be established., Methods: in participants (aged 37-73 at baseline) from the UK Biobank, we examined the associations of grip strength, expressed in absolute terms (kilograms) and relative to anthropometric variables, with mortality and disease incidence, after exclusion of the first 2 years of follow-up, and compared risk predictions scores of handgrip strength when differentially expressed., Results: of the 356 721 participants included in the analysis 6,234 died (1.7%) and 4,523 developed CVD (1.3%) over a mean follow-up of 5.0 years (ranging from 3.3 to 7.8) for mortality and 4.1 years (ranging from 2.4 to 7.0) for disease incidence data. As expected, baseline higher grip strength was associated with lower risk of all-cause and cause specific mortality and incidence. These associations did not meaningfully differ when grip-strength was expressed in absolute terms, vs. relative to height, weight, fat-free mass, BMI, fat-free mass index and fat-free mass, or as z-scores. Similarly the different ways of expressing grip strength had little effect on the ability of grip strength to improve risk prediction, based on C-index change, of an office-based risk score., Conclusions: the ability of grip strength to predict mortality is not altered by changing how it is expressed., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Total cholesterol and high-density lipoprotein cholesterol (HDL-C) measurements are central to cardiovascular disease (CVD) risk assessment, but there is continuing debate around the utility of other lipids for risk prediction., Methods: Participants from UK Biobank without baseline CVD and not taking statins, with relevant lipid measurements (n=346 686), were included in the primary analysis. An incident fatal or nonfatal CVD event occurred in 6216 participants (1656 fatal) over a median of 8.9 years. Associations of nonfasting lipid measurements (total cholesterol, HDL-C, non-HDL-C, direct and calculated low-density lipoprotein cholesterol [LDL-C], and apolipoproteins [Apo] A1 and B) with CVD were compared using Cox models adjusting for classical risk factors, and predictive utility was determined by the C-index and net reclassification index. Prediction was also tested in 68 649 participants taking a statin with or without baseline CVD (3515 CVD events)., Results: ApoB, LDL-C, and non-HDL-C were highly correlated (r>0.90), while HDL-C was strongly correlated with ApoA1 (r=0.92). After adjustment for classical risk factors, 1 SD increase in ApoB, direct LDL-C, and non-HDL-C had similar associations with composite fatal/nonfatal CVD events (hazard ratio, 1.23, 1.20, 1.21, respectively). Associations for 1 SD increase in HDL-C and ApoA1 were also similar (hazard ratios, 0.81 [both]). Adding either total cholesterol and HDL-C, or ApoB and ApoA, to a CVD risk prediction model (C-index, 0.7378) yielded similar improvement in discrimination (C-index change, 0.0084; 95% CI, 0.0065, 0.0104, and 0.0089; 95% CI, 0.0069, 0.0109, respectively). Once total and HDL-C were in the model, no further substantive improvement was achieved with the addition of ApoB (C-index change, 0.0004; 95% CI, 0.0000, 0.0008) or any measure of LDL-C. Results for predictive utility were similar for a fatal CVD outcome, and in a discordance analysis. In participants taking a statin, classical risk factors (C-index, 0.7118) were improved by non-HDL-C (C-index change, 0.0030; 95% CI, 0.0012, 0.0048) or ApoB (C-index change, 0.0030; 95% CI, 0.0011, 0.0048). However, adding ApoB or LDL-C to a model already containing non-HDL-C did not further improve discrimination., Conclusions: Measurement of total cholesterol and HDL-C in the nonfasted state is sufficient to capture the lipid-associated risk in CVD prediction, with no meaningful improvement from addition of apolipoproteins, direct or calculated LDL-C.

Aims/hypothesis: Individuals of South Asian origin have a high risk of type 2 diabetes and of dying from a diabetes-attributable cause. Lifestyle modification intervention trials to prevent type 2 diabetes in high-risk South Asian adults have suggested more modest effects than in European-origin populations. The strength of the evidence of individual studies is limited, however. We performed an individual participant data meta-analysis of available RCTs to assess the effectiveness of lifestyle modification in South Asian populations worldwide., Methods: We searched PubMed, EMBASE, Cochrane Library and Web of Science (to 24 September 2018) for RCTs on lifestyle modification interventions incorporating diet and/or physical activity in South Asian adults. Reviewers identified eligible studies and assessed the quality of the evidence. We obtained individual participant data on 1816 participants from all six eligible trials (four from Europe and two from India). We generated HR estimates for incident diabetes (primary outcome) and mean differences for fasting glucose, 2 h glucose, weight and waist circumference (secondary outcomes) using mixed-effect meta-analysis overall and by pre-specified subgroups. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system to rate the quality of evidence of the estimates. The study is registered with the International Prospective Register of Systematic Reviews ([PROSPERO] CRD42017078003)., Results: Incident diabetes was observed in 12.6% of participants in the intervention groups and in 20.0% of participants in the control groups. The pooled HR for diabetes incidence was 0.65 (95% CI 0.51, 0.81; I 2  = 0%) in intervention compared with control groups. The absolute risk reduction was 7.4% (95% CI 4.0, 10.2), with no interactions for the pre-specified subgroups (sex, BMI, age, study duration and region where studies were performed). The quality of evidence was rated as moderate. Mean difference for lifestyle modification vs control groups for 2 h glucose was -0.34 mmol/l (95% CI -0.62, -0.07; I 2  = 50%); for weight -0.75 kg (95% CI -1.34, -0.17; I 2  = 71%) and for waist -1.16 cm (95% CI -2.16, -0.16; I 2  = 75%). No effect was found for fasting glucose. Findings were similar across subgroups, except for weight for European vs Indian studies (-1.10 kg vs -0.08 kg, p = 0.02 for interaction)., Conclusions/interpretation: Despite modest changes for adiposity, lifestyle modification interventions in high-risk South Asian populations resulted in a clinically important 35% relative reduction in diabetes incidence, consistent across subgroups. If implemented on a large scale, lifestyle modification interventions in high-risk South Asian populations in Europe would reduce the incidence of diabetes in these populations.

Objective: To investigate whether the association between a genetic profile risk score for obesity (GPRS-obesity) (based on 93 SNPs) and body mass index (BMI) was modified by physical activity (PA), cardiorespiratory fitness, commuting mode, walking pace and sedentary behaviours., Methods: For the analyses we used cross-sectional baseline data from 310,652 participants in the UK Biobank study. We investigated interaction effects of GPRS-obesity with objectively measured and self-reported PA, cardiorespiratory fitness, commuting mode, walking pace, TV viewing, playing computer games, PC-screen time and total sedentary behaviour on BMI. Body mass index (BMI) was the main outcome measure., Results: GPRS-obesity was associated with BMI (β:0.54 kg.m -2 per standard deviation (SD) increase in GPRS, [95% CI: 0.53; 0.56]; P = 2.1 × 10 -241 ). There was a significant interaction between GPRS-obesity and objectively measured PA (P [interaction]  = 3.3 × 10 -11 ): among inactive individuals, BMI was higher by 0.58 kg.m -2 per SD increase in GPRS-obesity (p = 1.3 × 10 -70 ) whereas among active individuals the relevant BMI difference was less (β:0.33 kg.m -2 , p = 6.4 × 10 -41 ). We observed similar patterns for fitness (Unfit β:0.72 versus Fit β:0.36 kg.m -2 , P [interaction]  = 1.4 × 10 -11 ), walking pace (Slow β:0.91 versus Brisk β:0.38 kg.m -2 , P [interaction]  = 8.1 × 10 -27 ), discretionary sedentary behaviour (High β:0.64 versus Low β:0.48 kg.m -2 , P [interaction]  = 9.1 × 10 -12 ), TV viewing (High β:0.62 versus Low β:0.47 kg.m -2 , P [interaction]  = 1.7 × 10 -11 ), PC-screen time (High β:0.82 versus Low β:0.54 kg.m -2 , P [interaction]  = 0.0004) and playing computer games (Often β:0.69 versus Low β:0.52 kg.m -2 , P [interaction]  = 8.9 × 10 -10 ). No significant interactions were found for commuting mode (car, public transport, active commuters)., Conclusions: Physical activity, sedentary behaviours and fitness modify the extent to which a set of the most important known adiposity variants affect BMI. This suggests that the adiposity benefits of high PA and low sedentary behaviour may be particularly important in individuals with high genetic risk for obesity.

Objective: Grip strength is a well-characterised measure of weakness and of poor muscle performance, but there is a lack of consensus on its prognostic implications in terms of cardiac adverse events in patients with cardiac disorders., Methods: Articles were searched in PubMed, Cochrane Library, BioMed Central and EMBASE. The main inclusion criteria were patients with cardiac disorders (ischaemic heart disease, heart failure (HF), cardiomyopathies, valvulopathies, arrhythmias); evaluation of grip strength by handheld dynamometer; and relation between grip strength and outcomes. The endpoints of the study were cardiac death, all-cause mortality, hospital admission for HF, cerebrovascular accident (CVA) and myocardial infarction (MI). Data of interest were retrieved from the articles and after contact with authors, and then pooled in an individual patient meta-analysis. Univariate and multivariate logistic regression was performed to define predictors of outcomes., Results: Overall, 23 480 patients were included from 7 studies. The mean age was 62.3±6.9 years and 70% were male. The mean follow-up was 2.82±1.7 years. After multivariate analysis grip strength (difference of 5 kg, 5× kg) emerged as an independent predictor of cardiac death (OR 0.84, 95% CI 0.79 to 0.89, p<0.0001), all-cause death (OR 0.87, 95% CI 0.85 to 0.89, p<0.0001) and hospital admission for HF (OR 0.88, 95% CI 0.84 to 0.92, p<0.0001). On the contrary, we did not find any relationship between grip strength and occurrence of MI or CVA., Conclusion: In patients with cardiac disorders, grip strength predicted cardiac death, all-cause death and hospital admission for HF., Trial Registration Number: CRD42015025280., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: This study aimed to investigate whether the association between a validated genetic profile risk score for BMI (GPRS-BMI) (based on 93 single-nucleotide polymorphisms) and phenotypic obesity (BMI) was modified by the combined categories of physical activity (PA) and sedentary behaviors in a large population-based study., Methods: This study included cross-sectional baseline data from 338,216 white European adult men and women aged 37 to 73 years. Interaction effects of GPRS-BMI with the combined categories of PA and sedentary behaviors on BMI were investigated., Results: There was a significant interaction between GPRS-BMI and the combined categories of objectively measured PA and total sedentary behavior (P [interaction]   =  3.5 × 10 -6 ); among physically inactive and highly sedentary individuals, BMI was higher by 0.60 kg/m 2 per 1-SD increase in GPRS-obesity (P  =  8.9 × 10 -50 ), whereas the relevant BMI difference was 38% lower among physically active individuals and those with low sedentary time (β: 0.37 kg/m 2 ; P  =  2.3 × 10 -51 ). A similar pattern was observed for the combined categories of objective PA and TV viewing (inactive/high TV viewing β: 0.60 vs. active/low TV viewing β: 0.40 kg/m 2 ; P [interaction]   =  2.9 × 10 -6 )., Conclusions: This study provides evidence that combined categories of PA and sedentary behaviors modify the extent to which genetic predisposition to obesity results in higher BMI., (© 2019 The Obesity Society.)