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.

Background Combinations of lifestyle factors interact to increase mortality. Combinations of traditional factors such as smoking and alcohol are well described, but the additional effects of emerging factors such as television viewing time are not. The effect of socioeconomic deprivation on these extended lifestyle risks also remains unclear. We aimed to examine whether deprivation modifies the association between an extended score of lifestyle-related risk factors and health outcomes. Methods Data for this prospective analysis were sourced from the UK Biobank, a prospective population-based cohort study. We assigned all participants an extended lifestyle score, with 1 point for each unhealthy lifestyle factor (incorporating sleep duration and high television viewing time, in addition to smoking, excessive alcohol, poor diet [low intake of oily fish or fruits and vegetables, and high intake of red meat or processed meats], and low physical activity), categorised as most healthy (score 0-2), moderately healthy (score 3-5), or least healthy (score 6-9). Cox proportional hazards models were used to examine the association between lifestyle score and health outcomes (all-cause mortality and cardiovascular disease mortality and incidence), and whether this association was modified by deprivation. All analyses were landmark analyses, in which participants were excluded if they had an event (death or cardiovascular disease event) within 2 years of recruitment. Participants with non-communicable diseases (except hypertension) and missing covariate data were excluded from analyses. Participants were also excluded if they reported implausible values for physical activity, sleep duration, and total screen time. All analyses were adjusted for age, sex, ethnicity, month of assessment, history of hypertension, systolic blood pressure, medication for hypercholesterolaemia or hypertension, and body-mass index categories. Findings 328 594 participants aged 40-69 years were included in the study, with a mean follow-up period of 4•9 years (SD 0•83) after the landmark period for all-cause and cardiovascular disease mortality, and 4•1 years (0•81) for cardiovascular disease incidence. In the least deprived quintile, the adjusted hazard ratio (HR) in the least healthy lifestyle category, compared with the most healthy category, was 1•65 (95% CI 1•25-2•19) for all-cause mortality, 1•93 (1•16-3•20) for cardiovascular disease mortality, and 1•29 (1•10-1•52) for cardiovascular disease incidence. Equivalent HRs in the most deprived quintile were 2•47 (95% CI 2•04-3•00), 3•36 (2•36-4•76), and 1•41 (1•25-1•60), respectively. The HR for trend for one increment change towards least healthy in the least deprived quintile compared with that in the most deprived quintile was 1•25 (95% CI 1•12-1•39) versus 1•55 (1•40-1•70) for all-cause mortality, 1•30 (1•05-1•61) versus 1•83 (1•54-2•18) for cardiovascular disease mortality, and 1•10 (1•04-1•17) versus 1•16 (1•09-1•23) for cardiovascular disease incidence. A significant interaction was found betwe...

Background Sarcopenia is defined as the loss of muscle mass and strength. Despite the seriousness of this disease, a single diagnostic criterion has not yet been established. Few studies have reported the prevalence of sarcopenia globally, and there is a high level of heterogeneity between studies, stemmed from the diagnostic criteria of sarcopenia and the target population. The aims of this systematic review and meta-analysis were (i) to identify and summarize the diagnostic criteria used to define sarcopenia and severe sarcopenia and (ii) to estimate the global and region-specific prevalence of sarcopenia and severe sarcopenia by sociodemographic factors. Methods Embase, MEDLINE, and Web of Science Core Collections were searched using relevant MeSH terms. The inclusion criteria were cross-sectional or cohort studies in individuals aged ≥18 years, published in English, and with muscle mass measured using dual-energy x-ray absorptiometry, bioelectrical impedance, or computed tomography (CT) scan. For the meta-analysis, studies were stratified by diagnostic criteria (classifications), cut-off points, and instruments to assess muscle mass. If at least three studies reported the same classification, cut-off points, and instrument to measure muscle mass, they were considered suitable for meta-analysis. Following this approach, 6 classifications and 23 subgroups were created. Overall pooled estimates with inverse-variance weights obtained from a random-effects model were estimated using the metaprop command in Stata. Results Out of 19 320 studies, 263 were eligible for the narrative synthesis and 151 for meta-analysis (total n = 692 056, mean age: 68.5 years). Using different classifications and cut-off points, the prevalence of sarcopenia varied between 10% and 27% in the studies included for meta-analysis. The highest and lowest prevalence were observed in Oceania and Europe using the European Working Group on Sarcopenia in Older People (EWGSOP) and EWGSOP2, respectively. The prevalence ranged from 8% to 36% in individuals <60 years and from 10% to 27% in ≥60 years. Men had a higher prevalence of sarcopenia using the EWGSOP2 (11% vs. 2%) while it was higher in women using the International Working Group on Sarcopenia (17% vs. 12%). Finally, the prevalence of severe sarcopenia ranged from 2% to 9%. Conclusions The prevalence of sarcopenia and severe sarcopenia varied considerably according to the classification and cut-off point used. Considering the lack of a single diagnostic for sarcopenia, future studies should adhere to current guidelines, which would facilitate the comparison of results between studies and populations across the globe.

ObjectiveTo 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.DesignProspective population-based study.SettingUK Biobank.ParticipantsOf 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 measuresAll-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.ResultsThe 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.ConclusionsHigher cardiorespiratory fitness was associated with lower risk of premature mortality and incidence of CVD, respiratory disease and colorectal cancer.

Objective To investigate the association of macronutrient intake with all cause mortality and cardiovascular disease (CVD), and the implications for dietary advice. Design Prospective population based study. Setting UK Biobank. Participants 195 658 of the 502 536 participants in UK Biobank completed at least one dietary questionnaire and were included in the analyses. Diet was assessed using Oxford WebQ, a web based 24 hour recall questionnaire, and nutrient intakes were estimated using standard methodology. Cox proportional models with penalised cubic splines were used to study non-linear associations. Main outcome measures All cause mortality and incidence of CVD. Results 4780 (2.4%) participants died over a mean 10.6 (range 9.4-13.9) years of follow-up, and 948 (0.5%) and 9776 (5.0%) experienced fatal and non-fatal CVD events, respectively, over a mean 9.7 (range 8.5-13.0) years of follow-up. Non-linear associations were found for many macronutrients. Carbohydrate intake showed a non-linear association with mortality; no association at 20-50% of total energy intake but a positive association at 50-70% of energy intake (3.14 v 2.75 per 1000 person years, average hazard ratio 1.14, 95% confidence interval 1.03 to 1.28 (60-70% v 50% of energy)). A similar pattern was observed for sugar but not for starch or fibre. A higher intake of monounsaturated fat (2.94 v 3.50 per 1000 person years, average hazard ratio 0.58, 0.51 to 0.66 (20-25% v 5% of energy)) and lower intake of polyunsaturated fat (2.66 v 3.04 per 1000 person years, 0.78, 0.75 to 0.81 (5-7% v 12% of energy)) and saturated fat (2.66 v 3.59 per 1000 person years, 0.67, 0.62 to 0.73 (5-10% v 20% of energy)) were associated with a lower risk of mortality. A dietary risk matrix was developed to illustrate how dietary advice can be given based on current intake. Conclusion Many associations between macronutrient intake and health outcomes are non-linear. Thus dietary advice could be tailored to current intake. Dietary guidelines on macronutrients (eg, carbohydrate) should also take account of differential associations of its components (eg, sugar and starch).

Introduction recently, the European Working Group on Sarcopenia in Older People (EWGSOP) established a new operational definition and cut-off points for sarcopenia. The aim of this study was, therefore, to compare the prevalence of sarcopenia and its associations with different health outcomes using the old (EWGSOP1) and new (EWGSOP2) definitions of sarcopenia in the UK Biobank cohort. Methods sarcopenia was defined as low grip strength plus low muscle mass. Using both EWGSOP cut-off points, we created specific sarcopenia variables. Prevalence of sarcopenia derived using both EWGSOP definitions was calculated and compared as well as prospective health outcomes including all-cause mortality as well as incidence and mortality from cardiovascular disease (CVD), respiratory disease and chronic obstructive pulmonary disease (COPD). Results the prevalence of sarcopenia based on the EWGSOP1 and EWGSOP2 classifications were 8.14 and 0.36%, respectively. Sarcopenia defined by EWGSOP1 was associated with a higher risk of respiratory disease and COPD as well as mortality from all-cause, CVD and respiratory diseases. However, only respiratory incidence remained associated with sarcopenia when EWGSOP2 was used (HR: 1.32 [95% CI: 1.05–1.66]). Moreover, although individuals classified as sarcopenic using both classifications had the highest risk of all-cause mortality and respiratory disease, those with sarcopenia based on EWGSOP1 only experienced a more extensive range of poorer health outcomes. Conclusion in comparison with EWGSOP1, the new classification (EWGSOP2) produced a lower estimate of sarcopenia prevalence and fewer associations with adverse health outcomes. Although these associations were higher, many become non-significant.

Background Frailty has been associated with worse prognosis following COVID-19 infection. While several studies have reported the association between frailty and COVID-19 mortality or length of hospital stay, there have been no community-based studies on the association between frailty and risk of severe infection. Considering that different definitions have been identified to assess frailty, this study aimed to compare the association between frailty and severe COVID-19 infection in UK Biobank using two frailty classifications: the frailty phenotype and the frailty index. Methods A total of 383,845 UK Biobank participants recruited 2006–2010 in England (211,310 [55.1%] women, baseline age 37–73 years) were included. COVID-19 test data were provided by Public Health England (available up to 28 June 2020). An adapted version of the frailty phenotype derived by Fried et al. was used to define frailty phenotype (robust, pre-frail, or frail). A previously validated frailty index was derived from 49 self-reported questionnaire items related to health, disease and disability, and mental wellbeing (robust, mild frailty, and moderate/severe frailty). Both classifications were derived from baseline data (2006–2010). Poisson regression models with robust standard errors were used to analyse the associations between both frailty classifications and severe COVID-19 infection (resulting in hospital admission or death), adjusted for sociodemographic and lifestyle factors. Results Of UK Biobank participants included, 802 were admitted to hospital with and/or died from COVID19 (323 deaths and 479 hospitalisations). After analyses were adjusted for sociodemographic and lifestyle factors, a higher risk of COVID-19 was observed for pre-frail (risk ratio (RR) 1.47 [95% CI 1.26; 1.71]) and frail (RR 2.66 [95% CI 2.04; 3.47]) individuals compared to those classified as robust using the frailty phenotype. Similar results were observed when the frailty index was used (RR mildly frail 1.46 [95% CI 1.26; 1.71] and RR moderate/severe frailty 2.43 [95% CI 1.91; 3.10]). Conclusions Frailty was associated with a higher risk of severe COVID-19 infection resulting in hospital admission or death, irrespective of how it was measured and independent of sociodemographic and lifestyle factors. Public health strategies need to consider the additional risk that COVID-19 poses in individuals with frailty, including which additional preventive measures might be required.

Introduction-The critical sociodemographic, lifestyle and diseases factors influencing sarcopenia, defined by the current European Working Group on Sarcopenia 2 (EWGSOP2) classification and cutoff points, have not yet been fully elucidated. This study aimed, therefore, to determine sociodemographic, anthropometric, lifestyle and health-related factors associated with sarcopenia using the new EWGSOP2 definition. Study design-396,283 participants (52.8% women, age 38-73 years) were included in this crosssectional study. The potential factors associated with sarcopenia were allocated to four categories: sociodemographic (sex, age, education, income and professional qualification), anthropometric (nutritional status, abdominal obesity, body fat and birth weight), lifestyle (physical activity, smoking, sleeping and sitting time, TV viewing, alcohol, and dietary intakes) and health status (self-reported prevalent diseases). P-values were corrected for multiple testing using the Bonferroni method. Results-Age, women, lower education, higher deprivation, underweight, lower birth weight, and chronic diseases such as rheumatoid arthritis, chronic bronchitis and osteoporosis were associated with a higher likelihood of sarcopenia. Conversely, overweight, obese, as well as a self-reported higher intake of energy, protein, vitamins (B12 and B9) and minerals (potassium, calcium and magnesium) were associated with lower odds of sarcopenia. Conclusion-Women, adults older than 65 years, underweight people and those with rheumatoid arthritis were most likely to have sarcopenia. Considering the increase in the ageing population, sarcopenia is likely to become more prevalent. Identifying factors associated with sarcopenia could inform future strategies for early identification of individuals at high risk of sarcopenia and therefore, the implementation of preventive strategies against the disease.