Walking pace and the time between the onset of noncommunicable diseases and mortality: a UK Biobank prospective cohort study.

PURPOSE: To estimate time spent in various cardiovascular disease (CVD) and cancer states, according to self-reported walking pace. METHODS: In total, 391,744 UK Biobank participants were included (median age = 57 years; 54.7% women). Data were collected 2006-2010, with follow-up collected in 2021. Usual walking pace was self-defined as slow, steady, average, or brisk. Multistate modeling determined the transition rate and mean sojourn time in and across three different states (healthy, CVD or cancer, and death) upon a time horizon of 10 years. RESULTS: The mean sojourn time in the healthy state was longer, while that in the CVD or cancer state was shorter in individuals reporting an average or brisk walking pace (vs. slow). A 75-year-old woman reporting a brisk walking pace spent, on average, 8.4 years of the next 10 years in a healthy state; an additional 8.0 (95% CI: 7.3, 8.7) months longer than a 75-year-old woman reporting a slow walking pace. This corresponded to 4.3 (3.7, 4.9) fewer months living with CVD or cancer. Similar results were seen in men. CONCLUSIONS: Adults reporting an average or brisk walking pace at baseline displayed a lower transition to disease development and a greater proportion of life lived without CVD or cancer. AVAILABILITY OF DATA AND MATERIALS: Research was conducted using the UK Biobank resource under Application #33266. The UK Biobank resource can be accessed by researchers on application. Variables derived for this study have been returned to the UK Biobank for future applicants to request. No additional data are available.

Diabetes and Multiple Long-term Conditions: A Review of Our Current Global Health Challenge.

Use of effective treatments and management programs is leading to longer survival of people with diabetes. This, in combination with obesity, is thus contributing to a rise in people living with more than one condition, known as multiple long-term conditions (MLTC or multimorbidity). MLTC is defined as the presence of two or more long-term conditions, with possible combinations of physical, infectious, or mental health conditions, where no one condition is considered as the index. These include a range of conditions such as cardiovascular diseases, cancer, chronic kidney disease, arthritis, depression, dementia, and severe mental health illnesses. MLTC has major implications for the individual such as poor quality of life, worse health outcomes, fragmented care, polypharmacy, poor treatment adherence, mortality, and a significant impact on health care services. MLTC is a challenge, where interventions for prevention and management are lacking a robust evidence base. The key research directions for diabetes and MLTC from a global perspective include system delivery and care coordination, lifestyle interventions and therapeutic interventions.

Self-reported walking pace and 10-year cause-specific mortality: A UK biobank investigation.

OBJECTIVE: To investigate associations of self-reported walking pace (SRWP) with relative and absolute risks of cause-specific mortality. PATIENTS AND METHODS: In 391,652 UK Biobank participants recruited in 2006-2010, we estimated sex- and cause-specific (cardiovascular disease [CVD], cancer, other causes) mortality hazard ratios (HRs) and 10-year mortality risks across categories of SRWP (slow, average, brisk), accounting for confounders and competing risk. Censoring occurred in September 30, 2021 (England, Wales) and October 31, 2021 (Scotland). RESULTS: Over a median follow-up of 12.6 years, 22,413 deaths occurred. In women, the HRs comparing brisk to slow SRWP were 0.74 (95% CI: 0.67, 0.82), 0.40 (0.33, 0.49), and 0.29 (0.26, 0.32) for cancer, CVD, and other causes of death, respectively, and 0.71 (0.64, 0.78), 0.38 (0.33, 0.44), and 0.29 (0.26, 0.32) in men. Compared to CVD, HRs were greater for other causes (women: 39.6% [6.2, 72.9]; men: 31.6% [9.8, 53.5]) and smaller for cancer (-45.8% [-58.3, -33.2] and - 45.9% [-54.8, -36.9], respectively). For all causes in both sexes, the 10-year mortality risk was higher in slow walkers, but varied across sex, age, and cause, resulting in different risk reductions comparing brisk to slow: the largest were for other causes of death at age 75 years [women: -6.8% (-7.7, -5.8); men: -9.5% (-10.6, -8.4)]. CONCLUSION: Compared to slow walkers, brisk SRWP was associated with reduced cancer (smallest reduction), CVD, and other (largest) causes of death and may therefore be a useful clinical predictive marker. As absolute risk reductions varied across age, cause, and SRWP, certain groups may particularly benefit from interventions to increase SRWP.

Flexible parametric methods for calculating life expectancy in small populations.

BACKGROUND: Life expectancy is a simple measure of assessing health differences between two or more populations but current life expectancy calculations are not reliable for small populations. A potential solution to this is to borrow strength from larger populations from the same source, but this has not formally been investigated. METHODS: Using data on 451,222 individuals from the Clinical Practice Research Datalink on the presence/absence of intellectual disability and type 2 diabetes mellitus, we compared stratified and combined flexible parametric models, and Chiang's methods, for calculating life expectancy. Confidence intervals were calculated using the Delta method, Chiang's adjusted life table approach and bootstrapping. RESULTS: The flexible parametric models allowed calculation of life expectancy by exact age and beyond traditional life expectancy age thresholds. The combined model that fit age interaction effects as a spline term provided less bias and greater statistical precision for small covariate subgroups by borrowing strength from the larger subgroups. However, careful consideration of the distribution of events in the smallest group was needed. CONCLUSIONS: Life expectancy is a simple measure to compare health differences between populations. The use of combined flexible parametric methods to calculate life expectancy in small samples has shown promising results by allowing life expectancy to be modelled by exact age, greater statistical precision, less bias and prediction of different covariate patterns without stratification. We recommend further investigation of their application for both policymakers and researchers.

Socioeconomic inequalities of Long COVID: a retrospective population-based cohort study in the United Kingdom.

OBJECTIVES: To estimate the risk of Long COVID by socioeconomic deprivation and to further examine the inequality by sex and occupation. DESIGN: We conducted a retrospective population-based cohort study using data from the ONS COVID-19 Infection Survey between 26 April 2020 and 31 January 2022. This is the largest nationally representative survey of COVID-19 in the UK with longitudinal data on occupation, COVID-19 exposure and Long COVID. SETTING: Community-based survey in the UK. PARTICIPANTS: A total of 201,799 participants aged 16 to 64 years and with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. MAIN OUTCOME MEASURES: The risk of Long COVID at least 4 weeks after SARS-CoV-2 infection by index of multiple deprivation (IMD) and the modifying effects of socioeconomic deprivation by sex and occupation. RESULTS: Nearly 10% (n = 19,315) of participants reported having Long COVID. Multivariable logistic regression models, adjusted for a range of variables (demographic, co-morbidity and time), showed that participants in the most deprived decile had a higher risk of Long COVID (11.4% vs. 8.2%; adjusted odds ratio (aOR): 1.46; 95% confidence interval (CI): 1.34, 1.59) compared to the least deprived decile. Significantly higher inequalities (most vs. least deprived decile) in Long COVID existed in healthcare and patient-facing roles (aOR: 1.76; 95% CI: 1.27, 2.44), in the education sector (aOR: 1.68; 95% CI: 1.31, 2.16) and in women (aOR: 1.56; 95% CI: 1.40, 1.73) than men (aOR: 1.32; 95% CI: 1.15, 1.51). CONCLUSIONS: This study provides insights into the heterogeneous degree of inequality in Long COVID by deprivation, sex and occupation. These findings will help inform public health policies and interventions in incorporating a social justice and health inequality lens.

Life expectancy following a cardiovascular event in individuals with and without type 2 diabetes: A UK multi-ethnic population-based observational study.

BACKGROUND AND AIMS: We aimed to evaluate the life expectancy following the first cardiovascular disease (CVD) event by type 2 diabetes (T2D) status and ethnicity. METHODS AND RESULTS: We used the Clinical Practice Research Datalink database in England (UK), linked to the Hospital Episode Statistics information, to identify individuals with and without T2D who survived a first CVD event between 1st Jan 2007 and 31st Dec 2017; subsequent death events were extracted from the Office for National Statistics database. Ethnicity was categorised as White, South Asian (SA), Black, or other. Flexible parametric survival models were used to estimate survival and predict life expectancy. 59,939 individuals with first CVD event were included: 7596 (12.7%) with T2D (60.9% men; mean age at event: 69.7 years [63.2 years in SA, 65.9 in Black, 70.2 in White]) and 52,343 without T2D (56.7% men; 65.9 years [54.7 in Black, 58.2 in SA, 66.3 in White]). Accounting for potential confounders (sex, deprivation, lipid-lowering medication, current smoking, and pre-existing hypertension), comparing individuals with vs without T2D the mortality rate was 53% higher in White (hazard ratio [HR]: 1.53 [95% CI: 1.44, 1.62]), corresponding to a potential loss of 3.87 (3.30, 4.44) life years at the age of 50 years in individuals with T2D. No evidence of a difference in life expectancy was observed in individuals of SA (HR: 0.82 [0.52, 1.29]; -1.36 [-4.58, 1.86] life years), Black (HR: 1.26 [0.59, 2.70]; 1.21 [-2.99, 5.41] life years); and other (HR: 1.64 [0.80, 3.39]; 3.89 [-2.28, 9.99] life years) ethnic group. CONCLUSION: Following a CVD event, T2D is associated with a different prognosis and life years lost among ethnic groups.

Healthy lifestyle choices and microvascular complications: New insights into diabetes management.

Yogini Chudasama and Kamlesh Khunti discuss new evidence, published in PLOS Medicine, highlighting the importance of healthy lifestyle behaviours in diabetes management.

COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates.

BACKGROUND: Despite generally high coronavirus disease 2019 (COVID-19) vaccination rates in the UK, vaccination hesitancy and lower take-up rates have been reported in certain ethnic minority communities. METHODS: We used vaccination data from the National Immunisation Management System (NIMS) linked to the 2011 Census and individual health records for subjects aged ≥40 years (n = 24 094 186). We estimated age-standardized vaccination rates, stratified by ethnic group and key sociodemographic characteristics, such as religious affiliation, deprivation, educational attainment, geography, living conditions, country of birth, language skills and health status. To understand the association of ethnicity with lower vaccination rates, we conducted a logistic regression model adjusting for differences in geographic, sociodemographic and health characteristics. ResultsAll ethnic groups had lower age-standardized rates of vaccination compared with the white British population, whose vaccination rate of at least one dose was 94% (95% CI: 94%-94%). Black communities had the lowest rates, with 75% (74-75%) of black African and 66% (66-67%) of black Caribbean individuals having received at least one dose. The drivers of these lower rates were partly explained by accounting for sociodemographic differences. However, modelled estimates showed significant differences remained for all minority ethnic groups, compared with white British individuals. CONCLUSIONS: Lower COVID-19 vaccination rates are consistently observed amongst all ethnic minorities.

Estimates of years of life lost depended on the method used: tutorial and comparative investigation.

OBJECTIVES: This review aims to summarize key methods for estimating years of life lost (YLL), highlighting their differences and how they can be implemented in current software, and applies them in a real-world example. STUDY DESIGN AND SETTING: We investigated the common YLL methods: (1) Years of potential life lost (YPLL); (2) Global Burden of Disease (GBD) approach; (3) Life tables; (4) Poisson regression; and (5) Flexible parametric Royston-Parmar regression. We used data from UK Biobank and multimorbidity as our example. RESULTS: For the YPLL and GBD method, the analytical procedures allow only to quantify the average YLL within each group (with and without multimorbidity) and, from them, their difference; conversely, for the other methods both the remaining life expectancy within each group and the YLL could be estimated. At 65 years, the YLL in those with vs. without multimorbidity was 1.8, 1.2, and 2.7 years using the life tables approach and the Poisson, and Royston-Parmar regression, respectively; corresponding values were -0.73 and -0.05 years for YPLL and using the GBD approach. CONCLUSION: While deciding among different methods to estimate YLL, researchers should consider the purpose of the research, the type of available data, and the flexibility of the model.

The effectiveness of a structured group education programme for people with established type 2 diabetes in a multi-ethnic population in primary care: A cluster randomised trial.

BACKGROUND AND AIMS: Structured self-management education has been shown to be effective in type 2 diabetes (T2DM) but more research is needed to look at culturally appropriate programmes in ethnic minority groups, where prevalence of T2DM is higher and diagnosis earlier. The study tested the effectiveness of a group education programme for people with established T2DM in a multi-ethnic primary care population. METHODS AND RESULTS: Cluster randomised trial conducted in two multi-ethnic UK sites. Practices were randomised (1:1) to a structured T2DM group education programme or to continue with routine care. A culturally-adapted version was offered to South Asians, who formed the majority of ethnic minority participants. Other ethnic minority groups were invited to attend the standard programme. Primary outcome was change in HbA1c at 12 months. All analyses accounted for clustering and baseline value.367 participants (64(SD 10.8) years, 36% women, 34% from minority ethnic groups) were recruited from 31 clusters. At 12 months, there was no difference in mean change in HbA1c between the two groups (-0.10%; (95% CI: -0.37, 0.17). Subgroup analyses suggested the intervention was effective at lowering HbA1c in White European compared with ethnic minority groups. The intervention group lost more body weight than the control group (-0.82 kg at 6 months and -1.06 kg at 12 months; both p = 0.03). CONCLUSION: Overall, the programme did not result in HbA1c improvement but in subgroup analysis, a beneficial effect occurred in White Europeans. Findings emphasise a need to develop and evaluate culturally-relevant programmes for ethnic minority groups.

Admission Blood Glucose Level and Its Association With Cardiovascular and Renal Complications in Patients Hospitalized With COVID-19.

OBJECTIVE: To investigate the association between admission blood glucose levels and risk of in-hospital cardiovascular and renal complications. RESEARCH DESIGN AND METHODS: In this multicenter prospective study of 36,269 adults hospitalized with COVID-19 between 6 February 2020 and 16 March 2021 (N = 143,266), logistic regression models were used to explore associations between admission glucose level (mmol/L and mg/dL) and odds of in-hospital complications, including heart failure, arrhythmia, cardiac ischemia, cardiac arrest, coagulation complications, stroke, and renal injury. Nonlinearity was investigated using restricted cubic splines. Interaction models explored whether associations between glucose levels and complications were modified by clinically relevant factors. RESULTS: Cardiovascular and renal complications occurred in 10,421 (28.7%) patients; median admission glucose level was 6.7 mmol/L (interquartile range 5.8-8.7) (120.6 mg/dL [104.4-156.6]). While accounting for confounders, for all complications except cardiac ischemia and stroke, there was a nonlinear association between glucose and cardiovascular and renal complications. For example, odds of heart failure, arrhythmia, coagulation complications, and renal injury decreased to a nadir at 6.4 mmol/L (115 mg/dL), 4.9 mmol/L (88.2 mg/dL), 4.7 mmol/L (84.6 mg/dL), and 5.8 mmol/L (104.4 mg/dL), respectively, and increased thereafter until 26.0 mmol/L (468 mg/dL), 50.0 mmol/L (900 mg/dL), 8.5 mmol/L (153 mg/dL), and 32.4 mmol/L (583.2 mg/dL). Compared with 5 mmol/L (90 mg/dL), odds ratios at these glucose levels were 1.28 (95% CI 0.96, 1.69) for heart failure, 2.23 (1.03, 4.81) for arrhythmia, 1.59 (1.36, 1.86) for coagulation complications, and 2.42 (2.01, 2.92) for renal injury. For most complications, a modifying effect of age was observed, with higher odds of complications at higher glucose levels for patients age <69 years. Preexisting diabetes status had a similar modifying effect on odds of complications, but evidence was strongest for renal injury, cardiac ischemia, and any cardiovascular/renal complication. CONCLUSIONS: Increased odds of cardiovascular or renal complications were observed for admission glucose levels indicative of both hypo- and hyperglycemia. Admission glucose could be used as a marker for risk stratification of high-risk patients. Further research should evaluate interventions to optimize admission glucose on improving COVID-19 outcomes.

Impact of cardiometabolic multimorbidity and ethnicity on cardiovascular/renal complications in patients with COVID-19.

OBJECTIVE: Using a large national database of people hospitalised with COVID-19, we investigated the contribution of cardio-metabolic conditions, multi-morbidity and ethnicity on the risk of in-hospital cardiovascular complications and death. METHODS: A multicentre, prospective cohort study in 302 UK healthcare facilities of adults hospitalised with COVID-19 between 6 February 2020 and 16 March 2021. Logistic models were used to explore associations between baseline patient ethnicity, cardiometabolic conditions and multimorbidity (0, 1, 2, >2 conditions), and in-hospital cardiovascular complications (heart failure, arrhythmia, cardiac ischaemia, cardiac arrest, coagulation complications, stroke), renal injury and death. RESULTS: Of 65 624 patients hospitalised with COVID-19, 44 598 (68.0%) reported at least one cardiometabolic condition on admission. Cardiovascular/renal complications or death occurred in 24 609 (38.0%) patients. Baseline cardiometabolic conditions were independently associated with increased odds of in-hospital complications and this risk increased in the presence of cardiometabolic multimorbidity. For example, compared with having no cardiometabolic conditions, 1, 2 or ≥3 conditions was associated with 1.46 (95% CI 1.39 to 1.54), 2.04 (95% CI 1.93 to 2.15) and 3.10 (95% CI 2.92 to 3.29) times higher odds of any cardiovascular/renal complication, respectively. A similar pattern was observed for all-cause death. Compared with the white group, the South Asian (OR 1.19, 95% CI 1.10 to 1.29) and black (OR 1.53 to 95% CI 1.37 to 1.72) ethnic groups had higher risk of any cardiovascular/renal complication. CONCLUSIONS: In hospitalised patients with COVID-19, cardiovascular complications or death impacts just under half of all patients, with the highest risk in those of South Asian or Black ethnicity and in patients with cardiometabolic multimorbidity.

COVID-19 vaccine uptake and hesitancy opinions from frontline health care and social care workers: Survey data from 37 countries.

BACKGROUND AND AIMS: Vaccine hesitancy is an ongoing major challenge. We aimed to assess the uptake and hesitancy of the COVID-19 vaccination. METHODS: A short online survey was posted between April 12 to July 31, 2021 targeted at health and social care workers (HCWs) across the globe. RESULTS: 275 from 37 countries responded. Most were hospital or primary care physicians or nurses, 59% women, aged 18-60 years, and 21% had chronic conditions with most prevalent being diabetes, hypertension, and asthma. We found that most HCWs (93%) had taken or willing to receive the COVID-19 vaccine. While 7% were vaccine hesitant (mainly women aged 30-39 years), respondents main concerns was the safety or potential side effects. Vaccine willing respondents raised concerns of unequal access to the COVID-19 vaccination in some countries, and highlighted that the only solution to overcoming COVID-19 infections was the vaccine booster doses given annually and free mass vaccination. CONCLUSIONS: This study found that the majority of the frontline HCWs are willing to receive the COVID-19 vaccine. Further promotion of the COVID-19 vaccine would reassure and persuade HCWs to become vaccinated.

Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the U.K.

BACKGROUND: Pre-existing comorbidities have been linked to SARS-CoV-2 infection but evidence is sparse on the importance and pattern of multimorbidity (2 or more conditions) and severity of infection indicated by hospitalisation or mortality. We aimed to use a multimorbidity index developed specifically for COVID-19 to investigate the association between multimorbidity and risk of severe SARS-CoV-2 infection. METHODS: We used data from the UK Biobank linked to laboratory confirmed test results for SARS-CoV-2 infection and mortality data from Public Health England between March 16 and July 26, 2020. By reviewing the current literature on COVID-19 we derived a multimorbidity index including: (1) angina; (2) asthma; (3) atrial fibrillation; (4) cancer; (5) chronic kidney disease; (6) chronic obstructive pulmonary disease; (7) diabetes mellitus; (8) heart failure; (9) hypertension; (10) myocardial infarction; (11) peripheral vascular disease; (12) stroke. Adjusted logistic regression models were used to assess the association between multimorbidity and risk of severe SARS-CoV-2 infection (hospitalisation/death). Potential effect modifiers of the association were assessed: age, sex, ethnicity, deprivation, smoking status, body mass index, air pollution, 25-hydroxyvitamin D, cardiorespiratory fitness, high sensitivity C-reactive protein. RESULTS: Among 360,283 participants, the median age was 68 [range 48-85] years, most were White (94.5%), and 1706 had severe SARS-CoV-2 infection. The prevalence of multimorbidity was more than double in those with severe SARS-CoV-2 infection (25%) compared to those without (11%), and clusters of several multimorbidities were more common in those with severe SARS-CoV-2 infection. The most common clusters with severe SARS-CoV-2 infection were stroke with hypertension (79% of those with stroke had hypertension); diabetes and hypertension (72%); and chronic kidney disease and hypertension (68%). Multimorbidity was independently associated with a greater risk of severe SARS-CoV-2 infection (adjusted odds ratio 1.91 [95% confidence interval 1.70, 2.15] compared to no multimorbidity). The risk remained consistent across potential effect modifiers, except for greater risk among older age. The highest risk of severe infection was strongly evidenced in those with CKD and diabetes (4.93 [95% CI 3.36, 7.22]). CONCLUSION: The multimorbidity index may help identify individuals at higher risk for severe COVID-19 outcomes and provide guidance for tailoring effective treatment.

Clustering of comorbidities.

Within the last decade, clustering of comorbidities has become an increasing health problem on a global scale and will continue to challenge healthcare professionals in the coming years. People with multiple diseases find difficulties in managing their daily lives due to the implications each disease brings; attending and keeping up to date with hospital appointments, being prescribed and taking various medications, the effects of mental health and quality of life, and the impact it has on their families. Most research in clinical trials often exclude individuals with multimorbidity and observational studies mainly focus on single disease outcomes, therefore there is an opportunity to encourage future research in an area which could help prevent further cases and improve the lives of those already living with multimorbidity. This review aims to summarise the rising prevalence and most common clusters, highlight the challenges faced in healthcare, and explore ways to improve future research.

Ethnic, social and multimorbidity disparities in therapeutic inertia: A UK primary care observational study in patients newly diagnosed with type 2 diabetes.

AIM: To investigate factors associated with delays in receiving glucose-lowering therapy in patients newly diagnosed with type 2 diabetes mellitus (T2DM), and explore the preferential order and time of intensifications. MATERIALS AND METHODS: Retrospective cohort study including 120 409 adults with T2DM initiating first- to fourth-line glucose-lowering therapy in primary care between 2000 and 2018, using the UK Clinical Practice Research Datalink linked to Hospital Episode Statistics, Office of National Statistics death registration, and 2007 Index of Multiple Deprivation data. Associations were investigated using time-to-event analysis. RESULTS: The longest delays to prescription of first-line therapy were observed in older patients, of black or other ethnicities, and with multimorbidity. People from the most deprived areas received earlier first-line treatment than those from the least deprived areas. The majority were treated with metformin (82.4%) as the first-line prescription, sulphonylurea (50.4%) as second-line, dipeptidyl peptidase-4 inhibitor (27.7%) as third-line, and insulin (28.0%) as fourth-line. In the past 5 years, there was an increase in prescriptions of dipeptidyl peptidase-4-inhibitor and sodium-glucose transport protein-2 inhibitor. The median time was 0.5 years for first-line prescription, 4.1 for second-line, 4.6 for third-line and 4.7 for fourth-line. After T2DM diagnosis, 25% of patients developed cardiovascular disease and non-cardiovascular disease complications within a median time of 12-14 years, and received intensification 5-6 years later. CONCLUSIONS: Within the complex challenges of managing blood glucose levels and risk of additional comorbidities, future health care research and guidelines should focus on overcoming therapeutic inertia particularly at an earlier stage for older patients, from ethnic minorities and with multimorbidities.

Healthy lifestyle and life expectancy in people with multimorbidity in the UK Biobank: A longitudinal cohort study.

BACKGROUND: Whether a healthy lifestyle impacts longevity in the presence of multimorbidity is unclear. We investigated the associations between healthy lifestyle and life expectancy in people with and without multimorbidity. METHODS AND FINDINGS: A total of 480,940 middle-aged adults (median age of 58 years [range 38-73], 46% male, 95% white) were analysed in the UK Biobank; this longitudinal study collected data between 2006 and 2010, and participants were followed up until 2016. We extracted 36 chronic conditions and defined multimorbidity as 2 or more conditions. Four lifestyle factors, based on national guidelines, were used: leisure-time physical activity, smoking, diet, and alcohol consumption. A combined weighted score was developed and grouped participants into 4 categories: very unhealthy, unhealthy, healthy, and very healthy. Survival models were applied to predict life expectancy, adjusting for ethnicity, working status, deprivation, body mass index, and sedentary time. A total of 93,746 (19.5%) participants had multimorbidity. During a mean follow-up of 7 (range 2-9) years, 11,006 deaths occurred. At 45 years, in men with multimorbidity an unhealthy score was associated with a gain of 1.5 (95% confidence interval [CI] -0.3 to 3.3; P = 0.102) additional life years compared to very unhealthy score, though the association was not significant, whilst a healthy score was significantly associated with a gain of 4.5 (3.3 to 5.7; P < 0.001) life years and a very healthy score with 6.3 (5.0 to 7.7; P < 0.001) years. Corresponding estimates in women were 3.5 (95% CI 0.7 to 6.3; P = 0.016), 6.4 (4.8 to 7.9; P < 0.001), and 7.6 (6.0 to 9.2; P < 0.001) years. Results were consistent in those without multimorbidity and in several sensitivity analyses. For individual lifestyle factors, no current smoking was associated with the largest survival benefit. The main limitations were that we could not explore the consistency of our results using a more restrictive definition of multimorbidity including only cardiometabolic conditions, and participants were not representative of the UK as a whole. CONCLUSIONS: In this analysis of data from the UK Biobank, we found that regardless of the presence of multimorbidity, engaging in a healthier lifestyle was associated with up to 6.3 years longer life for men and 7.6 years for women; however, not all lifestyle risk factors equally correlated with life expectancy, with smoking being significantly worse than others.

Impact of COVID-19 on routine care for chronic diseases: A global survey of views from healthcare professionals.

Routine care for chronic disease is an ongoing major challenge. We aimed to evaluate the global impact of COVID-19 on routine care for chronic diseases. An online survey was posted 31 March to 23 April 2020 targeted at healthcare professionals. 202 from 47 countries responded. Most reported change in routine care to virtual communication. Diabetes, chronic obstructive pulmonary disease, and hypertension were the most impacted conditions due to reduction in access to care. 80% reported the mental health of their patients worsened during COVID-19. It is important routine care continues in spite of the pandemic, to avoid a rise in non-COVID-19-related morbidity and mortality.