IntroductionType 2 Diabetes Mellitus (T2DM) is a rising global health concern, heavily influenced by modifiable lifestyle and psychosocial factors. However, most predictive tools focus on biomedical markers and rely on real-time data from wearables or electronic health records, limiting their scalability in resource-constrained settings. This study presents a novel digital twin (DT) framework that uses retrospective lifestyle, behavioral, and psychosocial data to forecast T2DM onset and simulate the estimated effects of preventive interventions.MethodsData were drawn from 19,774 participants in the UK Biobank cohort, followed for up to 17 years. A penalized Cox proportional hazards model was employed to estimate individual time-to-event risk trajectories based on 90 candidate predictors. Predictors were selected through univariate screening, multicollinearity assessment, and variance filtering, yielding a final model with 14 significant variables. Causal inference techniques, including directed acyclic graphs (DAGs) and counterfactual simulations, were used to explore intervention effects on disease progression.ResultsThe model demonstrated strong predictive performance (C-index = 0.90, SD = 0.004). Psychosocial stressors such as loneliness, insomnia, and poor mental health emerged as strong independent predictors and were associated with estimated increases in absolute T2DM risk of approximately 35 percentage points individually and nearly 78 percentage points when combined, under the modeled assumptions. These effects were partly reinforced through diet, with high intake of processed meat, salt, and sugary cereals acting as risk amplifiers within the modeled causal pathways. Cheese intake was protective overall, but its estimated benefit was attenuated under psychosocial stress, where reduced consumption produced a small, directionally harmful mediation effect. Counterfactual simulations suggested that improvements in psychosocial conditions could reduce estimated T2DM risk by approximately 11.6 percentage points within the modeled cohort, with protective dietary patterns such as cheese consumption re-emerging as psychosocial stress was alleviated. The model also revealed pronounced ethnic disparities, with South Asian, African, and Caribbean participants exhibiting significantly higher estimated risk than White counterparts within this cohort. These findings highlight the potential of integrated, stress-informed prevention strategies that address both psychosocial and dietary pathways.ConclusionThis study introduces a transparent, simulation-enabled DT framework for estimating T2DM risk and exploring behavioral intervention scenarios without reliance on real-time data streams. It enables interpretable, personalized prevention planning and supports exploration of scalable deployment in public health, particularly in underserved or low-infrastructure environments. The integration of psychosocial and lifestyle data represents an important step toward more equitable and behaviorally informed digital health solutions.

OBJECTIVE:Studies have examined the association between excess body weight and risk of cardiovascular (CV) outcomes in the general population. However, the impact of the follow-up period of excess body weight on the association between excess weight and CV outcomes is less investigated. We sought to investigate this using the UK Biobank data. STUDY DESIGN:Population-based prospective cohort study. SETTING:The UK. PARTICIPANTS:Adults aged between 40 and 69 years were recruited between 2006 and 2010. The study included 469 162 participants; the median (IQR) age was 57 (50-63) years, and 56.3% of the participants were female. EXPOSURES:Body mass index, age, gender, ethnicity, education, smoking status (never, previous and current), alcohol status (never, previous and current), systolic blood pressure, sleep duration, walking pace, overall health rating (excellent, good, fair and poor), dietary patterns (such as red and processed meat consumption, and intake of fish, fruit, poultry and vegetables) and self-reported medical history (such as diabetes, chest pain/discomfort and falls). OUTCOMES:CV outcomes, including CV events such as cerebrovascular disease, ischaemic heart disease, heart failure and CV death. RESULTS:Of the 469 162 participants without CV disease at baseline, 56.3% were female. The mean age was 57 (SD: 9.6) years. During the median follow-up of 13.7 (IQR: 12.9-14.4) years, 27 305 participants developed a CV outcome, including 6698 who had a CV death. Overall, the strength of association between obesity and CV outcomes increased gradually as the follow-up period increased compared with normal weight. A significant association between obesity and the first CV event was observed after 4 years follow-up period (HR (95% CI) 1.14 (1.02 to 1.26)). The association of obesity with CV death was found after 10 years of follow-up, and there was an increasing strength of the association between 10 years (1.11 (1.01 to 1.22)) and 15 years (1.21 (1.13 to 1.29)) follow-up periods. No association was found between being overweight and CV death at any follow-up. Both overweight and obesity in men were associated with CV death observed before 8 years, while obese women were found to be associated with CV events and CV death after 8 years follow-up period. CONCLUSIONS:This large observation study shows that obesity could lead to CV death as early as 10 years follow-up period, while individuals who were obese were more likely to have their first CV event after 4 years follow-up. No association between being overweight and CV death was observed in any follow-up time. Further studies are needed to evaluate the impact of the follow-up period on associations between overweight/obesity and CV outcomes. Screening or early intervention for obesity can be highly valuable for preventing and managing CV outcomes in a primary care setting.

Background:Prediction models for Type 2 Diabetes Mellitus (T2DM) often rely on biochemical markers such as glycated hemoglobin, fasting glucose, or lipid profiles. While clinically informative, these indicators typically reflect established dysglycemia, limiting their value for early prevention. In contrast, psychosocial stress, sleep disturbance, tobacco use, and dietary quality represent modifiable, non-clinical factors that can be observed long before metabolic abnormalities are clinically detectable. Yet most studies examine these factors in isolation or as additive lifestyle scores, overlooking how their interdependencies reorganize in the preclinical phase. A systems-level approach is therefore needed to capture how disruptions in behavioral coherence signal emerging vulnerability. Methods:This study develops a dual-analytic framework that integrates Cox proportional hazards models with artificial neural network (ANN) coherence analysis. Using longitudinal data from the UK Biobank (n=15,774; follow-up up to 17 years), we identified non-clinical predictors of incident T2DM and examined how behavioral networks reorganize across health states. Predictors were screened through multivariate survival analysis and mapped into ANN-derived influence matrices to quantify stability, direction, and systemic coherence of relationships among diet, sleep, psychosocial states, and demographics. Results:Eighteen significant predictors of T2DM onset were identified. Elevated risk was linked to loneliness, psychiatric consultation, emotional distress, insomnia, irregular sleep, tobacco use, and high intake of processed meat, beef, and refined grains. Protective effects were observed for 7-8 h of sleep, oat and muesli consumption, and fermented dairy. ANN analyses revealed a pronounced breakdown of behavioral coherence in T2DM: foods that stabilized mood in healthy individuals became associated with distress, age and BMI lost their anchoring roles, and emotional states emerged as dominant but erratic drivers of diet. These reversals and destabilizations were consistent across model iterations, suggesting robust signatures of preclinical vulnerability. Conclusion:T2DM risk is better conceptualized as systemic reorganization within behavioral networks rather than the additive effects of isolated factors. By combining survival models with ANN-derived coherence mapping, this study demonstrates that early prediction is possible from modifiable, everyday behaviors without laboratory measures. The framework highlights leverage points for psychologically informed, personalized prevention strategies.

BackgroundStudies have examined the association between weight change and risk of cardiovascular (CV) outcomes in the general population. However, very few literature reported the association among obese people with established CV disease (CVD) and the factors associated with weight change are not clear. We sought to investigate this using the UK Biobank data.MethodsIn this large prospective population-based cohort study, absolute interval change scores in weight were calculated between weight measurements at baseline and the follow-up. The estimated HRs with 95% CIs were obtained from the Cox regression models to assess the association between weight change and the risk of CV death, cerebrovascular and ischaemic heart diseases and all-cause mortality.ResultsOf the 8297 obese participants who had CVD with repeated weight measurements, 43.1% were female. The mean age was 56.6 (SD: 7.2) years. The overall median follow-up of the study was 13.9 (IQR: 13.1–14.6) years. 52.7% of the participants had stable weight change (weight loss or gain<5 kg), 14.2% had large weight loss (≥10 kg) and 5.1% had large weight gain (≥10 kg). Compared with stable weight, only large weight gain was associated with an increased risk of CV death and all-cause mortality (fully adjusted HR (95% CI): 3.05 (1.40 to 6.67) for CV death and 1.93 (1.15 to 3.26) for all-cause mortality).ConclusionsAmong obese individuals with CVD, large weight gain is associated with a higher risk of CV death and all-cause mortality. Further studies are needed to understand the exact mechanisms underlying the associations between weight loss or weight gain and mortality.

BACKGROUND:The association between arterial stiffness and alcohol consumption is still controversial. We investigated this relationship by performing continuous analysis in men drinking only beer/cider, and women drinking only red wine. METHODS:This cross-sectional study involved participants aged 40-69 years consisting of 9029 men who drank only beer/cider, and 6989 women drinking only red wine. Alcohol consumption was captured by self-reported questionnaire and reported as units per week, where one unit is equal 10 mL pure ethanol. Arterial stiffness index (ASI) was estimated using photoplethysmography. RESULTS:In men consuming a mean 17.8 (5th and 95th percentiles, 2.6-76.7) units/week, ASI increased by heptiles (sevenths) of alcohol captured from beer/cider consumption and after adjusting for age (9.14, 9.40, 9.51, 9.53, 9.80, 9.80, 10.00 m/s; p-trend < 0.001) and after full adjustment (9.29, 9.46. 9.55, 9.55, 9.73, 9.73, 9.75 m/s; p-trend = 0.013). Similarly, in women consuming a mean 8.1 (1.6-29.3) units/week, ASI increased by heptiles of alcohol captured from red wine consumption and after adjusting for age (8.05, 8.05, 8.05, 8.11, 8.17, 8.30, 8.45 m/s; p-trend = 0.012) and borderline significant after full adjustment (8.05, 8.07, 8.05, 8.07, 8.11, 8.22, 8.43 m/s; p-trend = 0.055). These associations were confirmed in multivariable-adjusted regression analysis in all men, men younger and older than 50 years, and when consuming more than 14 units per week. Similarly, these associations were confirmed in all women, women older than 50 years, and in those consuming more than 14 units per week. CONCLUSIONS:Positive linear relationships exist between arterial stiffness and alcohol, irrespective of whether captured from beer/cider consumption in men or red wine consumption in women. No evidence existed to support the notion that our arteries benefit from any level of alcohol consumption.

Objective: We investigated three potential errors embedded in epidemiological evidence that could mask the health effects of alcohol, i.e., by using abstainers as reference group, combining alcohol from all drink types, and including protective relationships with ischemic heart disease when assessing overall cardiovascular (CV) risk. Design and method: The UK Biobank cohort consists of over 500,000 participants that attended one of 22 assessment centers across the United Kingdom. We calculated baseline alcohol intake as grams per week and followed CV outcomes for a median 6.9 years. Results: Never drinkers were at higher risk for all CV events (P < 0.0001), ischemic heart disease (P < 0.0001) and cerebrovascular disease (P < 0.0001). Alcohol from all drink types combined and beer/cider and spirits combined predicted CV events (both P < 0.024) and cerebrovascular events (both P < 0.011). Associations were stronger for beer/cider and spirits for both CV events (hazard ratio, 1.24 vs 1.08, P < 0.0001) and cerebrovascular events (hazard ratio, 1.30 vs 1.15, P < 0.0001). No relationships existed with ischemic heart disease (both P > 0.11). Wine was protective for CV events (P = 0.008) and ischemic heart disease (P < 0.0001), but not cerebrovascular events (P = 0.34). Excluding ischemic heart disease events resulted in the nullification of CV protection from wine (P = 0.95), while alcohol captured from beer/cider and spirits remained predictive (P < 0.0001). Conclusions: The use of abstainers as reference group, combining of all drink types including wine when capturing alcohol intake, and embedding the protective relationship between ischemic heart disease and wine in CV risk prediction, masks the health risks associated with alcohol intake and falsely portrays alcohol as protective.

Blood groups might influence susceptibility to COVID-19 [1-7]. We investigated associations between blood groups and COVID-19 infection in UK Biobank participants, a prospective population-based study that, between 2006 and 2010, enrolled 502,620 people aged 38–73 years in the United Kingdom. All participants gave written informed consent for their data to be used for research purposes, which was also approved by an ethics committee. Six blood group genotypes (AA, AB, AO, BB, BO and OO) provided four phenotypes (A, B, AB and O) [2]. Blood groups O (43.4%; n = 211 412) and A (43.4%; AA genotype: n = 36 332; AO genotype: n = 175 173) were similarly common, blood groups B (9.6%; BB genotype: n = 2789; BO genotype: n = 44 049) and AB (3.6%; n = 17 610) less so. Blood group was not available for 15,520 (3.0%) participants. By the 24th of August 2020, of 18 221 participants (3.6%) tested for COVID-19, 1713 (0.3% of all participants) had at least one positive test, of whom 623 (36.4%) were hospitalized and 318 (18.6%) died. Of those who tested negative, 4,623 were hospitalized (28.0%) and 597 (3.6%) died. Blood group was known for all but 635 (3.5%) of those tested. Amongst those tested for COVID-19, median age (70 years at the time of infection) and the proportions who were men (48%) were similar amongst blood groups but those with blood group B were less likely to be white (82.7%) compared with other blood groups (89.3% for O, 91.6% for A and 85.2% for AB). Participants had similar level of higher education (college or university) for all blood groups (28%). The percentage of participants tested was similar amongst blood groups as was the rate of positive tests for COVID-19 (Table 1). However, participants with blood group O were less likely to be hospitalized with COVID-19 after a positive test (33.3% versus 38.0%). Amongst those who tested negative for COVID-19, the rate of subsequent hospitalization was similar amongst blood groups (data not shown). In contrast to our results, others have found that people with blood group O have lower rates for a positive COVID-19 test but that the risk of developing severe symptoms requiring hospitalization after a positive test is similar amongst blood groups [3-5]. The reasons for these observed associations and the disparities amongst reports remain speculative [6, 7] but could reflect the play of chance, differences in case ascertainment or variations in the prevalence of blood groups according to ethnicity. We did not have information on Rhesus factor or other blood groups. To date, too few deaths have occurred to conduct reliable analyses for mortality. Our findings should be added to the accumulating evidence on the relationship between blood group and COVID-19. This research has been conducted using UK Biobank resource under application number 23183. The authors declared no conflict of interest. JZ and JC designed the study and drafted the letter; JZ, JC, PP and RS interpreted the data; JZ analysed the data. All authors critically revised and approved the final version of the letter.

Objective: There is increasing evidence that red and processed meat consumption is associated with increased risk of cardiovascular (CV) disease. However, little literature reported the association among people with obesity versus those without obesity. We sought to investigate this using the UK Biobank data. Methods: In this large prospective population-based cohort study, the red and processed meat consumption was assessed through the UK Biobank touch-screen questionnaire at baseline. The estimated hazards ratios (HRs) with 95% confidence intervals (CIs) were obtained from the Cox proportional hazard models to assess the association between red and processed meat consumption and the risk of CV death, cerebrovascular, and ischemic heart diseases in participants with and without obesity. Results: Of 428,070 participants, 100,175 (23.4%) were obese with the mean age of 56 (SD: 7.9) years old and 54% were female. Participants without obesity, the mean age was 56 (SD: 5.2) years old and 55% were female. The overall median follow-up was 7.2 (IQR: 6.5-7.8) years. red and processed meat consumption had increased risk of CV death (HR (95%CI):1.04 (1.01-1.08) per week serve for participants with obesity and 1.04 (1.02-1.07) for those without obesity) after adjusted for age, sex, ethnicity, education, smoking and alcohol status and overall health. The moderate positive association between red and processed meat consumption and ischemic heart disease was only observed in participants without obesity (HR (95%CI): 1.15 (1.00-1.31) for the highest versus lowest terciles of red and processed meat consumption). No association was found with cerebrovascular disease in the participants regardless of obesity. Conclusions: Consumption frequency of red and processed meat is associated with higher risk of CV death regardless of obesity. The risk of ischemic heart disease associated with red and processed meat consumption may be higher in participants without obesity. Further studies are needed to understand the full extent of the mechanism of the association. 0 2020 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Iron deficiency anaemia (IDA) is a worldwide healthcare problem affecting approximately 25% of the global population. The most common IDA treatment is oral iron supplementation, which has been associated with gastrointestinal (GI) side effects such as constipation and bloating. These can result in treatment non-adherence and the persistence of IDA. Intravenous iron does not cause GI side effects, which may be due to the lack of exposure to the intestinal lumen. Luminal iron can cause changes to the gut microbiota, aiding the promotion of pathogenic species and decreasing beneficial protective species. Iron is vital for methanogenic archaea, which rely on iron for growth and metabolism. Increased intestinal methane has been associated with slowing of intestinal transit, constipation, and bloating. Here we explore the literature to understand a potential link between iron and methanogenesis as a novel way to understand the mechanism of oral iron supplementation induced GI side effects.

Objectives:Previous studies suggest that changes in body weight can lead to an increased risk of mortality in the general population, although the results are controversial. The current study sought to investigate this association further using data from the UK Biobank.Study design:This is a large prospective population-based cohort study. Data were derived from the UK Biobank, with the initial assessments commencing between 2006 and 2010.Methods:Proportional hazard models were used to assess the association between self-reported weight change and risk of all-cause, cancer and cardiovascular mortality. The effect of gender was also investigated.Results:Of 433,829 participants with data for self-reported weight change, the mean age was 56 (standard deviation [SD]: 8.1) years and 55% were female. In total, 55% of participants reported no weight change, 28% gained weight, 15% lost weight, 2% did not know and 0.1% preferred not to give an answer. The median follow-up was 7.1 (interquartile range [IQR]: 6.4-7.8) years. Compared with participants with no weight change, those with weight loss had an increased risk of all-cause mortality (adjusted hazard ratio [HR] 1.25, 95% confident interval [CI] 1.18-1.32), cancer death (HR 1.17, 95% CI 1.08-1.27) and cardiovascular death (HR 1.26, 95% CI 1.12-1.43). Similarly, participants reporting weight gain also had an increased risk of all-cause mortality (HR 1.08, 95% CI 1.02-1.13), cancer death (HR 1.14, 95% CI 1.07-1.22) and cardiovascular death (HR 1.27, 95% CI 1.14-1.42). Participants who had a response 'do not know' or 'prefer not to answer' showed an increased risk of all-cause and cardiovascular mortality, particularly in men.Conclusions:The results of this study highlight the importance of maintaining a stable weight in middle-aged adults. Further studies are needed to understand the pathophysiology of weight change and its effects on mortality.

Abstract CVD is the most common chronic condition and the highest cause of mortality in the USA. The aim of the present work was to investigate diet and sedentary behaviour in relation to mortality in US CVD survivors. The National Health and Nutrition Examination Surveys conducted between 1999 and 2014 linked to the US mortality registry updated to 2015 were investigated. Multivariate adjusted Cox regression was used to derive mortality hazards in relation to sedentary behaviour and nutrient intake. A multiplicative and additive interaction analysis was conducted to evaluate how sedentariness and diet influence mortality in US CVD survivors. A sample of 2473 participants followed for a median period of 5·6 years resulted in 761 deaths, and 199 deaths were due to CVD. A monotone increasing relationship between time spent in sedentary activities and mortality risk was observed for all-cause and CVD mortality (hazard ratio (HR) = 1·20, 95 % CI 1·09, 1·31 and HR = 1·19, 95 % CI 1·00, 1·67, respectively). Inverse mortality risks in the range of 22–34 % were observed when comparing the highest with the lowest tertile of dietary fibre, vitamin A, carotene, riboflavin and vitamin C. Sedentariness below 360 min/d and dietary fibre and vitamin intake above the median interact on an additive scale influencing positively all-cause and CVD mortality risk. Reduced sedentariness in combination with a varied diet rich in dietary fibre and vitamins appears to be a useful strategy to reduce all-cause and CVD mortality in US CVD survivors.

BACKGROUND & AIMS:Uncertainty still exists on the impact of low to moderate consumption of different drink types on population health. We therefore investigated the associations of different drink types in the form of beer/cider, champagne/white wine, red wine and spirits with various health outcomes. METHODS:Over 500,000 participants were recruited to the UK Biobank cohort. Alcohol consumption was self-reported as pints beer/cider, glasses champagne/white wine, glasses of red wine, and measures of spirits per week. We followed health outcomes for a median of 7.02 years and reported all-cause mortality, cardiovascular events, ischemic heart disease, cerebrovascular events, and cancer. RESULTS:In continuous analysis after excluding non-drinkers, beer/cider and spirits intake associated with an increased risk for all-cause mortality (beer/cider: hazard ratio, 1.56; 95% confidence interval, 1.45-1.68; spirits: 1.47; 1.35-1.60), cardiovascular events (beer/cider: 1.25; 1.17-1.33; spirits: 1.25; 1.16-1.36), ischemic heart disease (beer/cider:1.12; 0.99-1.26 [P = 0.056]; spirits: 1.17; 1.02-1.35), cerebrovascular disease (beer/cider: 1.63; 1.32-2.02; spirits: 1.59; 1.25-2.02) and cancer (beer/cider: 1.14; 1.05-1.24; spirits: 1.14; 1.03-1.26), while both champagne/white wine and red wine associated with a decreased risk for ischemic heart disease only (champagne/white wine: 0.84; 0.72-0.98; red wine: 0.88; 0.77-0.99). CONCLUSIONS:Our findings do not support the notion that alcohol from any drink type is beneficial to health. Consuming low levels of beer/cider and spirits already associated with an increased risk for all health outcomes, while wine showed opposite protective relationships only with ischemic heart disease.

BACKGROUND:Excessive alcohol use is the third leading cause of mortality in the United States, where alcohol use consistently increased over the last decades. This trend is currently maintained, despite regulatory policies aimed to counteract it. While the increased health risks resulting from alcohol use are evident, some open questions regarding alcohol use and its consequences in the US population remain.OBJECTIVES:The current work aims to evaluate the relation between alcohol consumption trends over a period of 15 y with all-cause and cause-specific mortality. In addition, we evaluate the adequacy of the current alcohol recommended limits according to the 2015-2020 US Dietary Guidelines for Americans (USDGA).METHODS:This was a prospective population-based study defined by the NHANES conducted over the period 1999-2014 linked to US mortality registry in 2015.RESULTS:The sample, composed of 34,672 participants, was observed for a median period of 7.8 y, totaling 282,855 person-years. In the present sample, 4,303 deaths were observed. Alcohol use increased during the period 1999-2014. Alcohol use above the current US recommendations was associated with increased all-cause and cause-specific mortality risk, ranging from 39% to 126%. A proportion of these deaths, ranging from 19% to 26%, could be theoretically prevented if US citizens followed current guidelines, and 13% of all-cause deaths in men could be avoided if the current US guidelines for women (1 standard drink/d) were applied to them.CONCLUSIONS:The present study provides evidence in support of limiting alcohol intake in adherence to the USDGA recommendations.

Background. Excessive alcohol use is the third leading cause of mortality in the USA where alcohol use consistently increased over the last decades. This trend is currently maintained, despite regulatory policies aimed to counteract it. While the increased health risks resulting from alcohol use is evident, some open questions regarding alcohol use and its consequences in the US population remain. Objective. The current work aims to evaluate the relationship between alcohol consumption trends over a period of 15 years with all-cause and cause-specific mortality. In addition, we evaluate the adequacy of the current alcohol use recommendation according to the 2015-2020 US Dietary Guidelines for Americans (USDGA). Design. Prospective population based study defined by the NHANES surveys conducted over the period 1999-2014 linked to US mortality registry in 2015. Results. The sample, composed of 34,672 participants, was observed for a median period of 7.8 years totalling 282,855 person-years. In the present sample 4,303 deaths were observed. Alcohol use increased during the period 1999-2014. Alcohol use above the current US recommendations was associated with increased all-cause and cause-specific mortality risk, ranging from 39% to 126%. A proportion of these deaths, ranging from 19 to 26%, could be theoretically be prevented if US citizens followed current guidelines, and 13% of all-cause deaths in men could be avoided if the current US guidelines for women (one standard drink for day) were applied to them. Conclusions. The present study provides evidence in support of limiting alcohol intake in adherence with the USDGA recommendations.

Background: Despite several muscle mass measures being used in the current definitions of sarcopenia, their usefulness is uncertain due to limited data on their association with health outcomes. The aim of the study was to compare the performance of different muscle mass measures for predicting incident osteoporosis in postmenopausal women. Methods: This study included data from 149,166 participants (aged 60.3±5.5 years) as part of the UK Biobank cohort. Body composition was assessed using bioelectrical impedance. The muscle mass measures included were total body skeletal muscle (SMM) and appendicular skeletal muscle mass (aSMM) divided by height squared (ht2), derived residuals, SMM, SMM adjusted for body mass (SMM/bm×100) and aSMM normalised for body mass index (aSMM/BMI). Diagnoses of the events were confirmed by primary care physicians and coded according to the World Health Organization’s International Classification of Diseases 10th Revision (ICD-10: M80-M82). Results: Over a median follow-up of 6.75 (5th to 95th percentile interval, 1.53 to 8.37) years. 394 newly diagnosed cases of osteoporosis occurred, with 40 (10.2%) cases being associated with a pathological fracture. SMM/ht2, aSMM/ht2 residual and SMM were lower in postmenopausal women with osteoporosis compared to women without (all P <0.0001), while SMM/bm×100 (P=0.003), but not aSMM/BMI (P=0.59), was higher in the osteoporosis group. The unadjusted rates of osteoporosis increased with decreasing quintiles for SMM/ht2, aSMM/ht2, residuals and SMM (all P trend <0.0001), while the incidence of osteoporosis increased with increasing SMM/bm×100 (P trend =0.001), but not for aSMM/BMI (P=0.45). After minimally adjusting for age, and after full adjustment, SMM/ht2, aSMM/ht2 and SMM were the only measure that consistently predicted osteoporosis in the total group of postmenopausal women (hazard ratio [HR] 0.65–0.67, all P≤0.0001), in lean women (HR 0.62–0.68; all P≤0.001), and women with increased adiposity (HR 0.64–0.68; all P≤0.01). In fully adjusted models, the changes in the R2 statistic were 13.4%, 11.6% and 15.3% for the SMM/ht2 (aSMM/ht2), residual and SMM, but only 4.9% and 1.3% for SMM/bm×100 and aSMM/BMI. Conclusions: Muscle mass measures adjusted for height only (SMM/ht2, aSMM/ht2) appear to be better muscle-relevant risk factors for incident osteoporosis in postmenopausal women, including when stratified into lean participants and participants with increased adiposity.

Introduction: Hypertension, particularly in black populations. is often accompanied by augmented sympathetic nervous system activity and suppressed renin activity, indicative of possible blood pressure (BP) dysregulation. The potential role of the interrelationship between the renin-anotensin-aldosterone system (RAAS and the sympathetic nervous system in the context of low-renin conditions is unclear. We therefore explored whether surrogate measures of sympathetic activity [noradrenaline, 24-hour heart rate (HR) and percentage (%) dipping of night-time HR] relate to renin, aldosterone and aldosterone-to-renin ratio (ARR) in black and white South Africans. Methods: We included black (n = 127) and white (n = 179) males and females aged 20-63 years. W measured 24-hour BP and HR and calculated night-time dipping. We determined renin and aldosterone levels in plasma and calculated ARR. Noradrenaline and creatinine levels were determined in urine and the noradrenaline:creatinine ratio was calculated. Results: More blacks had low renin levels (80.3%) compared to whites (58.7%) (p < 0.001). In univariate and after multivariate analyses the following significant associations were evident in only the black group: FIR dipping was associated negatively with aldosterone level (beta= 0.18. p = 0.024) and ARR (beta = -0.20,p = 0.011), while 24-hour HR was associated positively with renin level (beta = 0.20, p = 0.024). Additionally, there was a borderline significant positive association between noradrenaline:creatinine ratio and aldosterone level (beta = 0.19. p = 0,051). Conclusion: The observed associations between surrogate measures of sympathetic nervous system activity and components of the RAAS in the black group suggest that the adverse effects of aldosterone and its ratio to renin on the cardiovascular system may be coupled to the effects of the sympathetic nervous system.

European Journal of Clinical InvestigationVolume 49, Issue 10 e13163 REPORT Research update for articles published in EJCI in 2017 Elena Arellano-Orden, Medical-Surgical Unit of Respiratory Diseases, University Hospital Virgen del Rocio, Seville, Spain Institute of Biomedicine of Seville (IBiS), Seville, Spain Center for Biomedical Research in Respiratory Diseases Network, Carlos III Health Institute, Madrid, SpainSearch for more papers by this authorFlora Bacopoulou, First Department of Pediatrics, Center for Adolescent Medicine and UNESCO Chair on Adolescent Health Care, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children's Hospital, Athens, GreeceSearch for more papers by this authorCristian Baicus, Department of Internal Medicine, Carol Davila University of Medicine and Pharmacy, Colentina Clinical Hospital, Bucharest, RomaniaSearch for more papers by this authorLeonilde Bonfrate, Department of Biomedical Sciences & Human Oncology, Clinica Medica "A. Murri", University of Bari Medical School, Bari, ItalySearch for more papers by this authorJames Broadbent, Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UKSearch for more papers by this authorChrista Buechler, Department of Internal Medicine I, Regensburg University Hospital, Regensburg, GermanySearch for more papers by this authorFederico Carbone, First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy IRCCS Ospedale Policlinico San Martino Genoa – Italian Cardiovascular Network, Genoa, ItalySearch for more papers by this authorEvangelia Charmandari, Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children’s Hospital, Athens, Greece Division of Endocrinology and Metabolism, Clinical, Experimental Surgery and Translational Research Center, Biomedical Research Foundation of the Academy of Athens, Athens, GreeceSearch for more papers by this authorGreggory R. Davis, Red Lerille's/LEQSF Regents Endowed Professor in Health and Physical Education, University of Louisiana at Lafayette, Lafayette, LA, USASearch for more papers by this authorRobin P. F. Dullaart, Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The NetherlandsSearch for more papers by this authorVasiliki Efthymiou, First Department of Pediatrics, Center for Adolescent Medicine and UNESCO Chair on Adolescent Health Care, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children's Hospital, Athens, GreeceSearch for more papers by this authorFelix Goeser, Department of Internal Medicine I, University of Bonn, Bonn, German German Center for Infection Research, Bonn, GermanySearch for more papers by this authorNandu Goswami, Physiology Division, Otto Loewi Research Center of Vascular Biology, Immunity and Inflammation, Medical University of Graz, Graz, AustriaSearch for more papers by this authorGwo-Ping Jong, Division of Internal Cardiology, Chung Shan Medical University Hospital and Chung Shan Medical University, Taichung, Taiwan ROCSearch for more papers by this authorMichael Lichtenauer, Department of Cardiology, Paracelsus Medical University, Salzburg, AustriaSearch for more papers by this authorYi-Sheng Liou, Department of Family Medicine, Taichung Veteran General Hospital, Taichung, ROC School of Public Health, National Defense Medical Center, Taipei, Taiwan ROCSearch for more papers by this authorPhilipp Lutz, Department of Internal Medicine I, University of Bonn, Bonn, German German Center for Infection Research, Bonn, GermanySearch for more papers by this authorMichael Maeng, Department of Cardiology, Aarhus University Hospital, Aarhus N, DenmarkSearch for more papers by this authorGurbet Özge Mert, Department of Cardiology, Eskişehir Yunus Emre State Hospital, Eskişehir, TurkeySearch for more papers by this authorKadir Uğur Mert, Department of Cardiology, Eskisehir Osmangazi University, Eskişehir, TurkeySearch for more papers by this authorFabrizio Montecucco, IRCCS Ospedale Policlinico San Martino Genoa – Italian Cardiovascular Network, Genoa, Italy First Clinic of Internal Medicine, Department of Internal Medicine and Centre of Excellence for Biomedical Research (CEBR), University of Genoa, Genoa, ItalySearch for more papers by this authorGjin Ndrepepa, Deutsches Herzzentrum München, München, GermanySearch for more papers by this authorKevin Kris Warnakula Olesen, Department of Cardiology, Aarhus University Hospital, Aarhus N, DenmarkSearch for more papers by this authorPaulo Oliveira, CNC – Center for Neuroscience and Cell Biology, UC-Biotech, University of Coimbra, Cantanhede, PortugalSearch for more papers by this authorFrank G. Perton, Laboratory Center, University Medical Center Groningen, University of Groningen, Groningen, The NetherlandsSearch for more papers by this authorPiero Portincasa, Department of Biomedical Sciences & Human Oncology, Clinica Medica "A. Murri", University of Bari Medical School, Bari, ItalySearch for more papers by this authorFrancisco Rodriguez-Panadero, Medical-Surgical Unit of Respiratory Diseases, University Hospital Virgen del Rocio, Seville, Spain Institute of Biomedicine of Seville (IBiS), Seville, SpainSearch for more papers by this authorChristiana Schernthaner, Department of Cardiology, Paracelsus Medical University, Salzburg, AustriaSearch for more papers by this authorRudolph Schutte, School of Allied Health, Faculty of Health, Education, Medicine and Social Care, Anglia Ruskin University, Chelmsford, UKSearch for more papers by this author Elena Arellano-Orden, Medical-Surgical Unit of Respiratory Diseases, University Hospital Virgen del Rocio, Seville, Spain Institute of Biomedicine of Seville (IBiS), Seville, Spain Center for Biomedical Research in Respiratory Diseases Network, Carlos III Health Institute, Madrid, SpainSearch for more papers by this authorFlora Bacopoulou, First Department of Pediatrics, Center for Adolescent Medicine and UNESCO Chair on Adolescent Health Care, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children's Hospital, Athens, GreeceSearch for more papers by this authorCristian Baicus, Department of Internal Medicine, Carol Davila University of Medicine and Pharmacy, Colentina Clinical Hospital, Bucharest, RomaniaSearch for more papers by this authorLeonilde Bonfrate, Department of Biomedical Sciences & Human Oncology, Clinica Medica "A. Murri", University of Bari Medical School, Bari, ItalySearch for more papers by this authorJames Broadbent, Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, UKSearch for more papers by this authorChrista Buechler, Department of Internal Medicine I, Regensburg University Hospital, Regensburg, GermanySearch for more papers by this authorFederico Carbone, First Clinic of Internal Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy IRCCS Ospedale Policlinico San Martino Genoa – Italian Cardiovascular Network, Genoa, ItalySearch for more papers by this authorEvangelia Charmandari, Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children’s Hospital, Athens, Greece Division of Endocrinology and Metabolism, Clinical, Experimental Surgery and Translational Research Center, Biomedical Research Foundation of the Academy of Athens, Athens, GreeceSearch for more papers by this authorGreggory R. Davis, Red Lerille's/LEQSF Regents Endowed Professor in Health and Physical Education, University of Louisiana at Lafayette, Lafayette, LA, USASearch for more papers by this authorRobin P. F. Dullaart, Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The NetherlandsSearch for more papers by this authorVasiliki Efthymiou, First Department of Pediatrics, Center for Adolescent Medicine and UNESCO Chair on Adolescent Health Care, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children's Hospital, Athens, GreeceSearch for more papers by this authorFelix Goeser, Department of Internal Medicine I, University of Bonn, Bonn, German German Center for Infection Research, Bonn, GermanySearch for more papers by this authorNandu Goswami, Physiology Division, Otto Loewi Research Center of Vascular Biology, Immunity and Inflammation, Medical University of Graz, Graz, AustriaSearch for more papers by this authorGwo-Ping Jong, Division of Internal Cardiology, Chung Shan Medical University Hospital and Chung Shan Medical University, Taichung, Taiwan ROCSearch for more papers by this authorMichael Lichtenauer, Department of Cardiology, Paracelsus Medical University, Salzburg, AustriaSearch for more papers by this authorYi-Sheng Liou, Department of Family Medicine, Taichung Veteran General Hospital, Taichung, ROC School of Public Health, National Defense Medical Center, Taipei, Taiwan ROCSearch for more papers by this authorPhilipp Lutz, Department of Internal Medicine I, University of Bonn, Bonn, German German Center for Infection Research, Bonn, GermanySearch for more papers by this authorMichael Maeng, Department of Cardiology, Aarhus University Hospital, Aarhus N, DenmarkSearch for more papers by this authorGurbet Özge Mert, Department of Cardiology, Eskişehir Yunus Emre State Hospital, Eskişehir, TurkeySearch for more papers by this authorKadir Uğur Mert, Department of Cardiology, Eskisehir Osmangazi University, Eskişehir, TurkeySearch for more papers by this authorFabrizio Montecucco, IRCCS Ospedale Policlinico San Martino Genoa – Italian Cardiovascular Network, Genoa, Italy First Clinic of Internal Medicine, Department of Internal Medicine and Centre of Excellence for Biomedical Research (CEBR), University of Genoa, Genoa, ItalySearch for more papers by this authorGjin Ndrepepa, Deutsches Herzzentrum München, München, GermanySearch for more papers by this authorKevin Kris Warnakula Olesen, Department of Cardiology, Aarhus University Hospital, Aarhus N, DenmarkSearch for more papers by this authorPaulo Oliveira, CNC – Center for Neuroscience and Cell Biology, UC-Biotech, University of Coimbra, Cantanhede, PortugalSearch for more papers by this authorFrank G. Perton, Laboratory Center, University Medical Center Groningen, University of Groningen, Groningen, The NetherlandsSearch for more papers by this authorPiero Portincasa, Department of Biomedical Sciences & Human Oncology, Clinica Medica "A. Murri", University of Bari Medical School, Bari, ItalySearch for more papers by this authorFrancisco Rodriguez-Panadero, Medical-Surgical Unit of Respiratory Diseases, University Hospital Virgen del Rocio, Seville, Spain Institute of Biomedicine of Seville (IBiS), Seville, SpainSearch for more papers by this authorChristiana Schernthaner, Department of Cardiology, Paracelsus Medical University, Salzburg, AustriaSearch for more papers by this authorRudolph Schutte, School of Allied Health, Faculty of Health, Education, Medicine and Social Care, Anglia Ruskin University, Chelmsford, UKSearch for more papers by this author First published: 16 September 2019 https://doi.org/10.1111/eci.13163 Correspondence Editorial office, EJCI. Email: ejci.editor@gmail.com Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Volume49, Issue10October 2019e13163 RelatedInformation

Abstract Background Despite several muscle mass measures being used in the current definitions of sarcopenia, their usefulness is uncertain because of limited data on their association with health outcomes. The aim of the study was to compare the performance of different muscle mass measures for predicting incident osteoporosis in postmenopausal women. Methods This study included data from 149 166 participants (aged 60.3 ± 5.5 years) as part of the UK Biobank cohort. Body composition was assessed using bioelectrical impedance. The muscle mass measures included were total body skeletal muscle mass (SMM) and appendicular SMM (aSMM) divided by height squared (ht2), derived residuals, SMM, SMM adjusted for body mass (SMM/bm × 100), and aSMM normalized for body mass index (aSMM/BMI). Diagnoses of the events were confirmed by primary care physicians and coded according to the World Health Organization's International Classification of Diseases 10th Revision (ICD‐10: M80‐M82). Results Over a median follow‐up of 6.75 (5th to 95th percentile interval, 1.53 to 8.37) years, 394 newly diagnosed cases of osteoporosis occurred, with 40 (10.2%) cases being associated with a pathological fracture. SMM/ht2, aSMM/ht2 residual, and SMM were lower in postmenopausal women with osteoporosis compared with women without (all P < 0.0001), while SMM/bm × 100 (P = 0.003), but not aSMM/BMI (P = 0.59), was higher in the osteoporosis group. The unadjusted rates of osteoporosis increased with decreasing quintiles for SMM/ht2, aSMM/ht2, residuals, and SMM (all P trend <0.0001), while the incidence of osteoporosis increased with increasing SMM/bm × 100 (P trend =0.001), but not for aSMM/BMI (P = 0.45). After minimally adjusting for age and after full adjustment, SMM/ht2, aSMM/ht2, and SMM were the only measure that consistently predicted osteoporosis in the total group of postmenopausal women [hazard ratio (HR) 0.65–0.67, all P ≤ 0.0001], in lean women (HR 0.62–0.68; all P ≤ 0.001), and women with increased adiposity (HR 0.64–0.68; all P ≤ 0.01). In fully adjusted models, the changes in the R2 statistic were 13.4%, 11.6%, and 15.3% for the SMM/ht2 (aSMM/ht2), residual, and SMM, but only 4.9% and 1.3% for SMM/bm × 100 and aSMM/BMI. Conclusions Muscle mass measures adjusted for height only (SMM/ht2, aSMM/ht2) appear to be better muscle‐relevant risk factors for incident osteoporosis in postmenopausal women, including when stratified into lean participants and participants with increased adiposity.

Background & aims: The relationship between total body iron and cardiovascular disease remains controversial and information absent in black sub-Saharan Africans in whom alcohol consumption tends to be high. The level of total body iron is tightly regulated, however this regulation is compromised by high alcohol intake causing iron loading. The aim of this study is to investigate total body iron, as represented by serum ferritin, and its interaction with measures of alcohol intake in predicting all-cause and cardiovascular mortality. Methods: We followed health outcomes for a median of 9.22 years in 877 randomly selected HIV negative African women (mean age: 50.4 years). Results: One hundred and five deaths occurred of which 40 were cardiovascular related. Ferritin averaged 84.0 (5th to 95th percentile interval, 7.5-533.3) ng/ml and due to the augmenting effect of inflammation, lowered to 75.3 (6.9-523.2) ng/ml after excluding 271 participants with high-sensitivity C-reactive protein (CRP) levels (above 8 mg/l). CRP increased by quartiles of ferritin in the total group (P trend = 0.002), but this relationship was absent after excluding the 271 participants with high CRP values (P trend = 0.10). Ferritin, gamma-glutamyl transferase and carbohydrate deficient transferrin (all P < 0.0001) were higher in drinkers compared to non-drinkers, but CRP was similar (P = 0.77). In multivariable-adjusted analyses, ferritin predicted both all-cause (hazard ratio, 2.08; 95% confidence interval, 1.62-2.68; P < 0.0001) and cardiovascular (1.94; 1.29-2.92; P = 0.002) mortality. In participants with CRP levels below or equal to 8 mg/l, the significant relationship remained between ferritin and all cause (2.51; 1.81-3.49; P < 0.0001) and cardiovascular mortality (2.34; 1.45-3.76; P= 0.0005). In fully adjusted models, interactions existed between ferritin and gamma-glutamyl transferase, self-reported alcohol use and carbohydrate deficient transferrin in predicting all-cause (P < 0.012) and cardiovascular mortality (P < 0.003). Conclusions: Iron loading in African women predicted all-cause and cardiovascular mortality and the intake of alcohol seems mechanistically implicated. (C) 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Background To investigate associations between active transport, employment status and objectively measured moderate-to-vigorous physical activity (MVPA) in a representative sample of US adults. Methods Cross-sectional analyses of data from the National Health and Nutrition Examination Survey. A total of 5180 adults (50.2 years old, 49.0% men) were classified by levels of active transportation and employment status. Outcome measure was weekly time spent in MVPA as recorded by the Actigraph accelerometer. Associations between active transport, employment status and objectively measured MVPA were examined using multivariable linear regression models adjusted for age, body mass index, race and ethnicity, education level, marital status, smoking status, working hour duration (among the employed only) and self-reported leisure time physical activity. Results Patterns of active transport were similar between the employed (n=2897) and unemployed (n=2283), such that 76.0% employed and 77.5% unemployed engaged in no active transport. For employed adults, those engaging in high levels of active transport (≥90 min/week) had higher amount of MVPA than those who did not engage in active transport. This translated to 40.8 (95% CI 15.7 to 65.9) additional minutes MVPA per week in men and 57.9 (95% CI 32.1 to 83.7) additional minutes MVPA per week in women. Among the unemployed adults, higher levels of active transport were associated with more MVPA among men (44.8 min/week MVPA, 95% CI 9.2 to 80.5) only. Conclusions Findings from the present study support interventions to promote active transport to increase population level physical activity. Additional strategies are likely required to promote physical activity among unemployed women.