Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk. We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Symptom Study smartphone application (app) from March 24 (UK) and March 29 (USA) to April 23, 2020. Participants were voluntary users of the app and at first use provided information on demographic factors (including age, sex, race or ethnic background, height and weight, and occupation) and medical history, and subsequently reported any COVID-19 symptoms. We used Cox proportional hazards modelling to estimate multivariate-adjusted hazard ratios (HRs) of our primary outcome, which was a positive COVID-19 test. The COVID Symptom Study app is registered with ClinicalTrials.gov, NCT04331509. Among 2 035 395 community individuals and 99 795 front-line health-care workers, we recorded 5545 incident reports of a positive COVID-19 test over 34 435 272 person-days. Compared with the general community, front-line health-care workers were at increased risk for reporting a positive COVID-19 test (adjusted HR 11·61, 95% CI 10·93–12·33). To account for differences in testing frequency between front-line health-care workers and the general community and possible selection bias, an inverse probability-weighted model was used to adjust for the likelihood of receiving a COVID-19 test (adjusted HR 3·40, 95% CI 3·37–3·43). Secondary and post-hoc analyses suggested adequacy of PPE, clinical setting, and ethnic background were also important factors. In the UK and the USA, risk of reporting a positive test for COVID-19 was increased among front-line health-care workers. Health-care systems should ensure adequate availability of PPE and develop additional strategies to protect health-care workers from COVID-19, particularly those from Black, Asian, and minority ethnic backgrounds. Additional follow-up of these observational findings is needed. Zoe Global, Wellcome Trust, Engineering and Physical Sciences Research Council, National Institutes of Health Research, UK Research and Innovation, Alzheimer's Society, National Institutes of Health, National Institute for Occupational Safety and Health, and Massachusetts Consortium on Pathogen Readiness.

Frailty is a syndrome of growing importance given the global ageing population. While frailty is a multifactorial process, poor nutritional status is considered a key contributor to its pathophysiology. As nutrition is a modifiable risk factor for frailty, strategies to prevent and treat frailty should consider dietary change. Observational evidence linking nutrition with frailty appears most robust for dietary quality: for example, dietary patterns such as the Mediterranean diet appear to be protective. In addition, research on specific foods, such as a higher consumption of fruit and vegetables and lower consumption of ultra-processed foods are consistent, with healthier profiles linked to lower frailty risk. Few dietary intervention studies have been conducted to date, although a growing number of trials that combine supplementation with exercise training suggest a multi-domain approach may be more effective. This review is based on an interdisciplinary workshop, held in November 2020, and synthesises current understanding of dietary influences on frailty, focusing on opportunities for prevention and treatment. Longer term prospective studies and well-designed trials are needed to determine the causal effects of nutrition on frailty risk and progression and how dietary change can be used to prevent and/or treat frailty in the future.

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic – area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

Background: Data for frontline healthcare workers (HCWs) and risk of SARS-CoV-2 infection are limited and whether personal protective equipment (PPE) mitigates this risk is unknown. We evaluated risk for COVID-19 among frontline HCWs compared to the general community and the influence of PPE. Methods: We performed a prospective cohort study of the general community, including frontline HCWs, who reported information through the COVID Symptom Study smartphone application beginning on March 24 (United Kingdom, U.K.) and March 29 (United States, U.S.) through April 23, 2020. We used Cox proportional hazards modeling to estimate multivariate-adjusted hazard ratios (aHRs) of a positive COVID-19 test. Findings: Among 2,035,395 community individuals and 99,795 frontline HCWs, we documented 5,545 incident reports of a positive COVID-19 test over 34,435,272 person-days. Compared with the general community, frontline HCWs had an aHR of 11·6 (95% CI: 10·9 to 12·3) for reporting a positive test. The corresponding aHR was 3·40 (95% CI: 3·37 to 3·43) using an inverse probability weighted Cox model adjusting for the likelihood of receiving a test. A symptom-based classifier of predicted COVID-19 yielded similar risk estimates. Compared with HCWs reporting adequate PPE, the aHRs for reporting a positive test were 1·46 (95% CI: 1·21 to 1·76) for those reporting PPE reuse and 1·31 (95% CI: 1·10 to 1·56) for reporting inadequate PPE. Compared with HCWs reporting adequate PPE who did not care for COVID-19 patients, HCWs caring for patients with documented COVID-19 had aHRs for a positive test of 4·83 (95% CI: 3·99 to 5·85) if they had adequate PPE, 5·06 (95% CI: 3·90 to 6·57) for reused PPE, and 5·91 (95% CI: 4·53 to 7·71) for inadequate PPE. Interpretation: Frontline HCWs had a significantly increased risk of COVID-19 infection, highest among HCWs who reused PPE or had inadequate access to PPE. However, adequate supplies of PPE did not completely mitigate high-risk exposures. Funding: Zoe Global Ltd., Wellcome Trust, EPSRC, NIHR, UK Research and Innovation, Alzheimer’s Society, NIH, NIOSH, Massachusetts Consortium on Pathogen Readiness RESEARCH IN CONTEXT: Evidence before this study: The prolonged course of the coronavirus disease 2019 (COVID-19) pandemic, coupled with sustained challenges supplying adequate personal protective equipment (PPE) for frontline healthcare workers (HCW), have strained global healthcare systems in an unprecedented fashion. Despite growing awareness of this problem, there are few data to inform policy makers on the risk of COVID-19 among HCWs and the impact of PPE on their disease burden. Prior reports of HCW infections are based on cross sectional data with limited individual-level information on risk factors for infection. A PubMed search for articles published between January 1, 2020 and May 5, 2020 using the terms “covid-19”, “healthcare workers”, and “personal protective equipment,” yielded no population-scale investigations exploring this topic. Added value of this study: In a prospective study of 2,135,190 individuals, frontline HCWs may have up to a 12-fold increased risk of reporting a positive COVID-19 test. Compared with those who reported adequate availability of PPE, frontline HCWs with inadequate PPE had a 31% increase in risk. However, adequate availability of PPE did not completely reduce risk among HCWs caring for COVID-19 patients. Implications of all the available evidence: Beyond ensuring adequate availability of PPE, additional efforts to protect HCWs from COVID-19 are needed, particularly as lockdown is lifted in many regions of the world.

Socioeconomic inequalities in health and mortality are well established, but the biological mechanisms underlying these associations are less understood. In parallel, the gut microbiome is emerging as a potentially important determinant of human health, but little is known about its broader environmental and social determinants. We test the association between gut microbiota composition and individual- and area-level socioeconomic factors in a well-characterized twin cohort. In this study, 1672 healthy volunteers from twin registry TwinsUK had data available for at least one socioeconomic measure, existing fecal 16S rRNA microbiota data, and all considered co-variables. Associations with socioeconomic status (SES) were robust to adjustment for known health correlates of the microbiome; conversely, these health-microbiome associations partially attenuated with adjustment for SES. Twins discordant for IMD (Index of Multiple Deprivation) were shown to significantly differ by measures of compositional dissimilarity, with suggestion the greater the difference in twin pair IMD, the greater the dissimilarity of their microbiota. Future research should explore how SES might influence the composition of the gut microbiota and its potential role as a mediator of differences associated with SES.

Muscle mass, strength, and physical function are known to decline with age. This is associated with the development of geriatric syndromes including sarcopenia and frailty. Dietary protein is essential for skeletal muscle function. Resistance exercise appears to be the most beneficial form of physical activity for preserving skeletal muscle and a synergistic effect has been noted when this is combined with dietary protein. However, older adults have shown evidence of anabolic resistance, where greater amounts of protein are required to stimulate muscle protein synthesis, and response is variable. Thus, the recommended daily amount of protein is greater for older people. The aetiologies and mechanisms responsible for anabolic resistance are not fully understood. The gut microbiota is implicated in many of the postulated mechanisms for anabolic resistance, either directly or indirectly. The gut microbiota change with age, and are influenced by dietary protein. Research also implies a role for the gut microbiome in skeletal muscle function. This leads to the hypothesis that the gut microbiome might modulate individual response to protein in the diet. We summarise the existing evidence for the role of the gut microbiota in anabolic resistance and skeletal muscle in aging people, and introduce the metabolome as a tool to probe this relationship in the future.