Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort

Mortality among Canadian population with multimorbidity: A retrospective cohort study

Objective

The aim of this study was to examine the effect of multimorbidity and the joint effect of chronic diseases on all-cause mortality among subjects aged 35 years and above.

Study Design

Population-based retrospective cohort study.

Methods

Multimorbidity was defined by the respondent's self-report of having two or more chronic diseases of the nine considered. The Canadian Community Health Surveys conducted in 2003/2004, 2005/2006 and 2007 to 2014 were linked with the Canadian Vital Statistics Death Database to examine the association between multimorbidity and all-cause mortality in subjects aged 35 years and above. Cox's proportional hazards models were used to estimate risk of multimorbidity on death after adjusting for the confounders in three age groups.

Results

Multimorbidity had an increased risk of death in all three age groups with the youngest having the highest risk after adjusting for potential confounders (35 to 54 years: hazard ratio (HR) = 3.77, 95% CI: 3.04, 4.67; 55 to 64 years: HR = 2.64, 95% CI: 2.36, 2.95; 65 years and above: HR = 1.71; 95% CI:1.63,1.80). Subjects with cancer had the highest risk of death in the three age groups. When the interactions between chronic diseases were considered, subjects with COPD and diabetes had a significantly increased risk of death in comparison to those without COPD or diabetes in the 55 to 64 years. (HR = 2.59, 95% CI: 2.01, 3.34).

Conclusions

Prevention of multimorbidity should be targeted not only in the older population but also in the younger populations. Synergistic effects of chronic diseases should be considered in the management of multimorbidities.

Association between risk, duration and cause of hospitalisations in people with rheumatoid arthritis and multimorbidity in the UK Biobank and Scottish Early Rheumatoid Arthritis (SERA) cohorts: Longitudinal observational study

OBJECTIVES

To investigate association between presence of multimorbidity in people with established and early rheumatoid arthritis (RA) and risk, duration and cause of hospitalisations.

DESIGN

Longitudinal observational study.

SETTING

UK Biobank, population-based cohort recruited between 2006 and 2010, and the Scottish Early Rheumatoid Arthritis (SERA), inception cohort recruited between 2011 and 2015. Both linked to mortality and hospitalisation data.

PARTICIPANTS

4757 UK Biobank participants self-reporting established RA; 825 SERA participants with early RA meeting the 2010 ACR/EULAR classification criteria. Participants stratified by number of long-term conditions (LTCs) in addition to RA (RA only, RA + 1 LTC and RA + ≥ 2 LTCs) and matched to five non-RA controls.

MAIN OUTCOME MEASURES

Number and duration of hospitalisations and their causes. Incidence rate ratios (IRR) and 95% confidence intervals (CI) calculated using negative binomial regression models.

RESULTS

Participants with RA + ≥ 2 LTCs experienced higher hospitalisation rates compared to those with RA alone (UK Biobank: IRR 2.10, 95% CI 1.91 to 2.30; SERA: IRR 1.74, 95% CI 1.23 to 2.48). Total duration of hospitalisation in RA + ≥ 2 LTCs was also higher (UK Biobank: IRR 2.48, 95% CI 2.17 to 2.84; SERA: IRR 1.90, 95% CI 1.07 to 3.38) than with RA alone. Rate and total duration of hospitalisations was higher in UK Biobank RA participants than non-RA controls with equivalent number of LTCs. Hospitalisations for respiratory infection were higher in early RA than established RA and were the commonest cause of hospital admission in early RA.

CONCLUSIONS

Participants with established or early RA with multimorbidity experienced a higher rate and duration of hospitalisations than those with RA alone and with non-RA matched controls.

Classification of long-term condition patterns in rheumatoid arthritis and associations with adverse health events: a UK Biobank cohort study

PURPOSE

We aimed to classify individuals with RA and ≥2 additional long-term conditions (LTCs) and describe the association between different LTC classes, number of LTCs and adverse health outcomes.

METHODS

We used UK Biobank participants who reported RA (n=5,625) and employed latent class analysis (LCA) to create classes of LTC combinations for those with ≥2 additional LTCs. Cox-proportional hazard and negative binomial regression were used to compare the risk of all-cause mortality, major adverse cardiac events (MACE), and number of emergency hospitalisations over an 11-year follow-up across the different LTC classes and in those with RA plus one additional LTC. Persons with RA without LTCs were the reference group. Analyses were adjusted for demographic characteristics, smoking, BMI, alcohol consumption and physical activity.

RESULTS

A total of 2,566 (46%) participants reported ≥2 LTCs in addition to RA. This involved 1,138 distinct LTC combinations of which 86% were reported by ≤2 individuals. LCA identified 5 morbidity-classes. The distinctive condition in the class with the highest mortality was cancer (class 5; HR 2.66 95%CI (1.91-3.70)). The highest MACE (HR 2.95 95%CI (2.11-4.14)) and emergency hospitalisations (rate ratio 3.01 (2.56-3.54)) were observed in class 3 which comprised asthma, COPD & CHD. There was an increase in mortality, MACE and emergency hospital admissions within each class as the number of LTCs increased.

CONCLUSIONS

The risk of adverse health outcomes in RA varied with different patterns of multimorbidity. The pattern of multimorbidity should be considered in risk assessment and formulating management plans in patients with RA.

Geospatial assessment of the convergence of communicable and non-communicable diseases in South Africa

Introduction

Several low-and middle-income countries are undergoing rapid epidemiological transition with a rising burden of non-communicable diseases (NCDs). South Africa (SA) is a country with one of the largest HIV epidemics worldwide and a growing burden of NCDs where the collision of these epidemics poses a major public health challenge.

Methods

Using data from a large nationally representative survey, the South Africa Demographic and Health Survey (SADHS 2016), we conducted a geospatial analysis of several diseases including HIV, tuberculosis (TB), cardiovascular, respiratory, and metabolic diseases to identify areas with a high burden of co-morbidity within the country. We explored the spatial structure of each disease and associations between diseases using different spatial and visual data methodologies. We also assessed the individual level co-occurrence of HIV and the other diseases included in the analysis.

Results

The spatial distribution for HIV prevalence showed that this epidemic is most intense in the eastern region of the country, mostly within the Gauteng, Mpumalanga, and Kwazulu-Natal provinces. In contrast, chronic diseases had their highest prevalence rates the southern region of the country, particularly in the Eastern and Western Cape provinces. Individual-level analyses were consistent with the spatial correlations and found no statistically significant associations between HIV infection and the presence of any NCDs.

Conclusions

We found no evidence of geospatial overlap between the HIV epidemic and NCDs in SA. These results evidence the complex epidemiological landscape of the country, characterized by geographically distinct areas exhibiting different health burdens. The detailed description of the heterogenous prevalence of HIV and NCDs in SA reported in this study could be a useful tool to inform and direct policies to enhance targeted health service delivery according to the local health needs of each community.

Chronic pain and COVID-19 hospitalisation and mortality: a UK Biobank cohort study

ABSTRACT

The risk of COVID-19 in those with chronic pain is unknown. We investigated whether self-reported chronic pain was associated with COVID-19 hospitalisation or mortality. UK Biobank recruited 502,624 participants aged 37 to 73 years between 2006 and 2010. Baseline exposure data, including chronic pain (>3 months, in at least 1 of 7 prespecified body sites) and chronic widespread pain (>3 months, all over body), were linked to COVID-19 hospitalisations or mortality. Univariable or multivariable Poisson regression analyses were performed on the association between chronic pain and COVID-19 hospitalisation and Cox regression analyses of the associations with COVID-19 mortality. Multivariable analyses adjusted incrementally for sociodemographic confounders, then lifestyle risk factors, and finally long-term condition count. Of 441,403 UK Biobank participants with complete data, 3180 (0.7%) were hospitalised for COVID-19 and 1040 (0.2%) died from COVID-19. Chronic pain was associated with hospital admission for COVID-19 even after adjustment for all covariates (incidence rate ratio 1.16; 95% confidence interval [CI] 1.08-1.24; P < 0.001), as was chronic widespread pain (incidence rate ratio 1.33; 95% CI 1.06-1.66; P = 0.012). There was clear evidence of a dose-response relationship with number of pain sites (fully adjusted global P -value < 0.001). After adjustment for all covariates, there was no association between chronic pain (HR 1.01; 95% CI 0.89-1.15; P = 0.834) but attenuated association with chronic widespread pain (HR 1.50, 95% CI 1.04-2.16, P -value = 0.032) and COVID-19 mortality. Chronic pain is associated with higher risk of hospitalisation for COVID-19, but the association with mortality is unclear. Future research is required to investigate these findings further and determine whether pain is associated with long COVID.

Use of fish oil and mortality of patients with cardiometabolic multimorbidity: A prospective study of UK biobank

BACKGROUND AND AIMS

Cardiometabolic multimorbidity (CMM) has risen as a global issue of public health, with an in-creasing prevalence and more severe clinical prognosis. This study aimed to estimate the association between use of fish oil and mortality among patients with CMM.

METHODS AND RESULTS

In this prospective study based on UK Biobank, participants with ≥2 of cardiometabolic diseases (CMDs, including coronary heart disease [CHD], diabetes, hypertension, and stroke in this study) at recruitment were included. Use of fish oil was derived from touchscreen questionnaires at baseline. All-cause and cardiovascular mortality were accessed via electronic health-related records. Kaplan-Meier curves and flexible parametric Royston-Parmar proportion-hazard models were fitted to assess the as-sociations of fish-oil use with all-cause, cardiovascular mortality, and related life expectancy alterations. Among 30 068 participants from UK Biobank (67.9% men; mean age 61.75 years), 5357 deaths were reported during 12.03 years of follow-up. For patients with CMM, use of fish oil was associated with a 17% lower risk of all-cause mortality (95% confidence interval [95% CI] 0.78-0.88, P < 0.001), and 19% lower risk of cardiovascular mortality (95% CI 0.72-0.90, P < 0.001) in multivariable-adjusted models. At 45 years old, using fish oil was associated with 1.66 years of life expectancy gained.

CONCLUSION

Among patients with CMM, use of fish oil was associated with a significantly reduced risk of all-cause, cardiovascular mortality, and prolonged life expectancy.

Assessing trial representativeness using serious adverse events: an observational analysis using aggregate and individual-level data from clinical trials and routine healthcare data

BACKGROUND

The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. We explore an approach assessing trial representativeness by comparing rates of trial serious adverse events (SAE) to rates of hospitalisation/death in routine care.

METHODS

This was an observational analysis of individual (125 trials, n=122,069) and aggregate-level drug trial data (483 trials, n=636,267) for 21 index conditions compared to population-based routine healthcare data (routine care). Trials were identified from ClinicalTrials.gov . Routine care comparison from linked primary care and hospital data from Wales, UK (n=2.3M). Our outcome of interest was SAEs (routinely reported in trials). In routine care, SAEs were based on hospitalisations and deaths (which are SAEs by definition). We compared trial SAEs in trials to expected SAEs based on age/sex standardised routine care populations with the same index condition. Using IPD, we assessed the relationship between multimorbidity count and SAEs in both trials and routine care and assessed the impact on the observed/expected SAE ratio additionally accounting for multimorbidity.

RESULTS

For 12/21 index conditions, the pooled observed/expected SAE ratio was <1, indicating fewer SAEs in trial participants than in routine care. A further 6/21 had point estimates <1 but the 95% CI included the null. The median pooled estimate of observed/expected SAE ratio was 0.60 (95% CI 0.55-0.64; COPD) and the interquartile range was 0.44 (0.34-0.55; Parkinson's disease) to 0.87 (0.58-1.29; inflammatory bowel disease). Higher multimorbidity count was associated with SAEs across all index conditions in both routine care and trials. For most trials, the observed/expected SAE ratio moved closer to 1 after additionally accounting for multimorbidity count, but it nonetheless remained below 1 for most.

CONCLUSIONS

Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess the applicability of trial findings to older populations in whom multimorbidity and frailty are common.

Education and income-related inequalities in multimorbidity among older Brazilian adults

OBJECTIVES

This study aimed to evaluate the existence of socioeconomic inequalities related to the prevalence of multimorbidity in the Brazilian population aged 60 and older.

METHODS

This was a cross-sectional study with data from the last Brazilian National Health Survey (PNS) collected in 2019. Multimorbidity was the dependent variable and was defined as the presence of two or more chronic diseases. All the diseases were assessed based on a self-reported previous medical diagnosis. Education and per capita family income were the measures of socioeconomic position. Socioeconomic inequalities related to multimorbidity were assessed using two complex measures of inequality; the Slope Index of Inequality (SII) and the Concentration Index (CI).

RESULTS

The prevalence of multimorbidity in Brazil was 56.5% 95% CI (55.4; 57.6) and varied from 46.9% (44.3; 49.6) in the North region to 59.3% (57.0; 61.5) in the South region. In general, individuals with higher socioeconomic positions had a lower prevalence of multimorbidity. Significant absolute and relative income inequalities were observed in the South region [SII -9.0; CI -0.054], Southeast [SII -9.8; CI -0.06], and Middle-east [SII -10.4; CI -0.063]. Absolute and relative education inequalities were significant for the country and two of its regions (Southeast [SII -12.7; CI -0.079] and South [SII -19.0; CI -0.109]).

CONCLUSIONS

The prevalence of multimorbidity is high in Brazil and all of its macro-regions. The significant findings concerning the inequalities suggest that the distribution of this condition is more concentrated among those with lower education and income.

Systemic Multimorbidity Clusters in People with Periodontitis

This study aimed to identify systemic multimorbidity clusters in people with periodontitis via a novel artificial intelligence-based network analysis and to explore the effect of associated factors. This study utilized cross-sectional data of 3,736 participants across 3 cycles of the National Health and Nutrition Examination Survey (2009 to 2014). Periodontal examination was carried out by trained dentists for participants aged ≥30 y. The extent of periodontitis was represented by the proportion of sites with clinical attachment loss (CAL)≥ 3 mm, split into 4 equal quartiles. A range of systemic diseases reported during the survey were also extracted. Hypergraph network analysis with eigenvector centralities was applied to identify systemic multimorbidity clusters and single-disease influence in the overall population and when stratified by CAL quartile. Individual factors that could affect the systemic multimorbidity clusters were also explored by CAL quartile. In the study population, the top 3 prevalent diseases were hypertension (63.9%), arthritis (47.6%), and obesity (45.9%). A total of 106 unique systemic multimorbidity clusters were identified across the study population. Hypertension was the most centralized disease in the overall population (centrality [C]: 0.50), followed closely by arthritis (C: 0.45) and obesity (C: 0.42). Diabetes had higher centrality in the highest CAL quartile (C: 0.31) than the lowest (C: 0.26). "Hypertension, obesity" was the largest weighted multimorbidity cluster across CAL quartiles. This study has revealed a range of common systemic multimorbidity clusters in people with periodontitis. People with periodontitis are more likely to present with hypertension and obesity together, and diabetes is more influential to multimorbidity clusters in people with severe periodontitis. Factors such as ethnicity, deprivation, and smoking status may also influence the pattern of multimorbidity clusters.

Effects of potential risk factors on the development of cardiometabolic multimorbidity and mortality among the elders in China

Objectives

To examine the impact of demographic, socioeconomic, and behavioral factors on the development of cardiometabolic multimorbidity and mortality in Chinese elders.

Methods

Data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) 2002–2018 was used in the study. Cardiometabolic multimorbidity was defined as the presence of two or more cardiometabolic disorders, such as hypertension, diabetes, cardiovascular disease (CVD), heart disease, or stroke. Cox regression model and multi-state Markov model were developed to evaluate the association of the study factors with the progression of cardiometabolic conditions and mortality. The outcomes included three states (first cardiometabolic disease, cardiometabolic multimorbidity, and all-cause mortality) and five possible transitions among the three states.

Results

Of the 13,933 eligible individuals, 7,917 (56.8%) were female, and 9,540 (68.50%) were over 80 years old. 2,766 (19.9%) participants had their first cardiometabolic disease, 975 (7.0%) participants suffered from cardiometabolic multimorbidity, and 9,365 (67.2%) participants died. The progression to cardiometabolic multimorbidity was positively associated with being female (HR = 1.42; 95%CI, 1.10 − 1.85), living in the city (HR = 1.41; 95%CI, 1.04 − 1.93), overweight (HR = 1.43; 95%CI, 1.08 − 1.90), and obesity (HR = 1.75; 95% CI, 1.03 − 2.98). A higher risk for the first cardiometabolic disease was associated with being female (HR = 1.26; 95% CI, 1.15 − 1.39), higher socioeconomic status (SES, HR = 1.17; 95%CI, 1.07 − 1.28), lack of regular physical activity (HR = 1.13; 95%CI, 1.04 − 1.23), smoking (HR = 1.20; 95%CI, 1.08 − 1.33), ≤ 5 h sleep time (HR = 1.15; 95%CI, 1.02 − 1.30), overweight (HR = 1.48; 95% CI, 1.32 − 1.66), and obesity (HR = 1.34; 95%CI, 1.06 − 1.69). It also should be noted that not in marriage, lower SES and unhealthy behavioral patterns were risk factors for mortality.

Conclusion

This study emphasized the importance of lifestyle and SES in tackling the development of cardiometabolic conditions among Chinese elders and provided a reference for policy-makers to develop a tailored stage-specific intervention strategy.

Are polymorphisms affecting serum urate, renal urate handling and alcohol intake associated with co-morbidities in gout cases? A case-control study using data from the UK Biobank

To examine the association between common comorbidities, eGFR and loci involved in the hyperuricaemia-gout transition. This study was conducted in people with gout from the UK Biobank. Logistic regression was used to examine the association between self-reported physician-diagnosed hypertension, diabetes, hypercholesterolemia and ischaemic heart disease (IHD) with the following variants: rs1260326(GCKR), rs16890979(SLC2A9), rs2231142(ABCG2), rs1229984(ADH1B) and rs2078267(SLC22A11) and adjusted for age, sex and 10-principal components. Linear regression was used to examine the association with eGFR. 7,049 participants with gout were included. After adjusting for multiple testing, there was a statistically significant positive association between urate lowering allele at SLC2A9 and hypertension, and negative association between urate raising allele at ABCG2 and hypertension (OR 1.17 and OR 0.86, respectively). Number of urate lowering risk alleles associated with hypertension [OR (95%CI) 1.13 (1.06-1.21)]. High eGFR associated with urate raising allele at rs2231142 (β = 1.38). The SNP in ADH1B that protects from alcohol excess showed a negative association with IHD (OR 0.53). Unlike in general population studies urate lowering genetic variants associate with hypertension in gout patients with dose-response. This may be due to high prevalence of other risk factors of hypertension such as obesity, poor diet etc. and needs validation in independent datasets.

Association of mood disorder with cardiometabolic multimorbidity trajectory and life expectancy, a prospective cohort study

BACKGROUND

Cardiometabolic diseases (CMDs) including hypertension, coronary heart disease, diabetes and stroke, are always combined with each other, leading to cardiometabolic multimorbidity (CMM). Mood disorder was associated with onset of CMD. However, the impact of mood disorder on the transition from single CMD to CMM was poorly understood.

METHODS

A total of 95,351 participants with single CMD, with median age of 59 (range 40 to 71) years from UK Biobank were enrolled at baseline. Competing risk regression models were used to estimated hazard ratios (HRs) and 95 % confidence intervals (CIs) of association between mood disorder categories and progress from single CMD to CMM. Association of mood disorder with mortality, and life expectancy differences were also calculated by flexible parametric proportion-hazard models.

RESULTS

Relative associations were observed between mood disorder and the progress from first onset of CMD to CMM. Adjusted HRs for progress to CMM from those with comorbid CMD plus depression or bipolar were increased (depression: 1.23 [1.19 1.27]; bipolar: 1.47 [1.31 1.66]), compared with those with the sole CMD. Mood disorder also had impact on all-cause mortality (depression: 1.17 [1.10 1.24]; bipolar: 2.03 [1.74 2.32]) and reduced life expectancy estimates for those with single CMD.

LIMITATIONS

This cohort primarily comprises White individuals. Covariates only measured at baseline and assumed unchanged during follow-up.

CONCLUSIONS

Mood disorder conferred greater hazard on the CMM and mortality outcome. This study highlighted the importance of depression and bipolar in disease progression, from single CMD, to multimorbidity or mortality.

Association of Multimorbidity, Disease Clusters, and Modification by Genetic Factors With Risk of Dementia

IMPORTANCE

Individual conditions have been identified as risk factors for dementia; however, it is important to consider the role of multimorbidity, as conditions often co-occur.

OBJECTIVE

To investigate whether multimorbidity is associated with incident dementia and whether associations vary by different clusters of disease and genetic risk for dementia.

DESIGN, SETTING, AND PARTICIPANTS

This population-based prospective cohort study used data from the UK Biobank cohort, with baseline data collected between 2006 and 2010 and with up to 15 years of follow-up. Participants included women and men without dementia and aged at least 60 years at baseline. Medical conditions were captured as part of nurse-led verbal interviews conducted at baseline assessment centers. Data were analyzed from October 2020 to July 2022.

EXPOSURES

The presence of at least 2 long-term conditions from a preselected list of 42 conditions was used to define multimorbidity. High genetic risk for dementia was based on presence of 1 or 2 apolipoprotein (APOE) ε4 alleles.

MAIN OUTCOMES AND MEASURES

The main outcome, incident dementia, was derived from hospital inpatient and death registry records. Associations of multimorbidity with dementia were assessed with Cox proportional hazards models.

RESULTS

A total of 206 960 participants (mean [SD] age, 64.1 [2.9] years, 108 982 [52.7%] women) were included in the final sample, of whom 89 201 participants (43.1%) had multimorbidity. Over a mean (SD) of 11.8 (2.2) years of follow-up, 6182 participants (3.0%) developed dementia. The incidence rate was 1.87 (95% CI, 1.80-1.94) per 1000 person-years for those without multimorbidity and 3.41 (95% CI, 3.30-3.53) per 1000 person-years for those with multimorbidity. In Cox proportional hazards models adjusted for age, sex, ethnicity, education, socioeconomic status, and APOE-ε4 carrier status, multimorbidity was associated with an increased risk of incident dementia (hazard ratio [HR], 1.63 [95% CI, 1.55-1.71]). The highest dementia risk was observed for the hypertension, diabetes, and coronary heart disease cluster (HR, 2.20 [95% CI, 1.98-2.46]) and pain, osteoporosis, and dyspepsia cluster (HR, 2.00 [95% CI, 1.68-2.37]) in women and in the diabetes and hypertension cluster (HR, 2.24 [95% CI, 1.97-2.55]) and coronary heart disease, hypertension, and stroke cluster (HR, 1.94 [95% CI, 1.71-2.20]) in men, compared with no multimorbidity. The associations between multimorbidity and dementia were greater in those with a lower genetic risk of dementia (HR, 1.96 [95% CI, 1.81-2.11]) than in those with a higher genetic risk of dementia (HR, 1.39 [95% CI, 1.30-1.49]). Similar findings were observed when stratifying diseases clusters by genetic risk for dementia.

CONCLUSIONS AND RELEVANCE

These findings suggest that multimorbidity was associated with an increased risk of dementia. The associations varied by clusters of disease and genetic risk for dementia. These findings could help with the identification of individuals at high risk of dementia as well as the development of targeted interventions to reduce or delay dementia incidence.

Associations between consumption of three types of beverages and risk of cardiometabolic multimorbidity in UK Biobank participants: a prospective cohort study

BACKGROUND

Although the association between beverages and a single cardiometabolic disease has been well studied, their role in disease progression from the single cardiometabolic disease state to cardiometabolic multimorbidity (CMM) state remains unclear. This study examined the associations between three types of beverages: sugar-sweetened beverages (SSBs), artificially sweetened beverages (ASBs), and pure fruit/vegetable juices, and the incidence of CMM in patients with a single cardiometabolic disease.

METHODS

Our analysis included 37,994 participants from the UK Biobank who completed at least one dietary questionnaire and were diagnosed with only one cardiometabolic disease at the time of recruitment. Competing risk models were used to examine the association between the three types of beverages and incidence of CMM. We conducted analysis both in patients with any single cardiometabolic disease and in patients with specific cardiometabolic disease.

RESULTS

During a median follow-up of 9.1 years (interquartile range [IQR] 9.0-9.8), a total of 6399 participants developed CMM. The consumption of SSBs and ASBs (>1 serving per day) was associated with a higher risk of CMM (SSBs: hazard ratio [HR] 1.19, 95% confidence interval [95% CI] 1.08-1.31; ASBs: HR 1.15, 95% CI 1.04-1.27). Intake of pure fruit/vegetable juices was inversely associated with the incidence of CMM (0-1 serving per day: HR 0.90, 95% CI 0.85-0.94; >1 serving per day: HR 0.90, 95% CI 0.81-0.99). However, the association of the high-level consumption of pure fruit/vegetable juices (>1 serving per day) was not statistically significant after correcting for multiple testing. In the analysis of patients with specific cardiometabolic diseases, positive associations were observed in patients with hypertension for SSBs consumption, while inverse associations persisted in patients with cardiovascular disease (coronary heart disease or stroke) and in hypertensive patients for pure fruit/vegetable juice consumption.

CONCLUSIONS

Consuming >1 serving of SSBs and ASBs per day was associated with a higher risk of CMM in patients with a single cardiometabolic disease. In contrast, intake of pure fruit/vegetable juices was inversely associated with the risk of CMM. Our findings highlight the need to limit the use of SSBs and ASBs in patients with a single cardiometabolic disease.

Muscle strength and incidence of depression and anxiety: findings from the UK Biobank prospective cohort study

BACKGROUND

Depression and anxiety are the leading mental health problems worldwide; depression is ranked as the leading cause of global disability with anxiety disorders ranked sixth. Preventive strategies based on the identification of modifiable factors merit exploration. The aim of the present study was to investigate the associations of handgrip strength (HGS) with incident depression and anxiety and to explore how these associations differ by socio-demographic, lifestyle, and health-related factors.

METHODS

The analytic sample comprised 162 167 participants (55% women), aged 38-70 years, from the UK Biobank prospective cohort study. HGS was assessed at baseline using dynamometry. Depression and anxiety were extracted from primary care and hospital admission records. Cox proportional models were applied, with a 2 year landmark analysis, to investigate the associations between HGS and incident depression and anxiety.

RESULTS

Of the 162 167 participants included, 5462 (3.4%) developed depression and 6614 (4.1%) anxiety, over a median follow-up period of 10.0 years (inter-quartile range: 9.3-10.8) for depression and 9.9 (inter-quartile range: 9.0-10.8) for anxiety. In the fully adjusted model, a 5 kg lower HGS was associated with a 7% (HR: 1.07 [95% CI: 1.05, 1.10]; P < 0.001) and 8% (HR: 1.08 [95% CI: 1.06, 1.10]; P < 0.001) higher risk of depression and anxiety, respectively. Compared with participants in the sex and age-specific highest tertiles of HGS, those in the medium and lowest tertiles had an 11% (HR: 1.11 [95% CI: 1.04, 1.19]; P = 0.002) and 24% (HR: 1.24 [95% CI: 1.16, 1.33]; P < 0.001) higher risk of depression and 13% (HR: 1.13 [95% CI: 1.06, 1.20]; P < 0.001) and 27% (HR: 1.27 [95% CI: 1.19, 1.35]; P < 0.001) higher risk of anxiety, respectively. The association of HGS with depression was stronger among participants with average or brisk walking pace (vs. slow walking pace; P_interaction  < 0.001). The association with anxiety was stronger in those participants aged ≥58 years (vs. ≤58 years; P_interaction  = 0.002) and those living in more affluent areas (vs. deprived; P_interaction  = 0.001).

CONCLUSIONS

Handgrip strength was inversely associated with incident depression and anxiety. Because HGS is a simple, non-invasive, and inexpensive measure, it could be easily used in clinical practice to stratify patients and identify those at elevated risk of mental health problems. However, future research should assess if resistance training aimed at increasing HGS can prevent the occurrence of mental health conditions.

MorbidGCN: prediction of multimorbidity with a graph convolutional network based on integration of population phenotypes and disease network

Exploring multimorbidity relationships among diseases is of great importance for understanding their shared mechanisms, precise diagnosis and treatment. However, the landscape of multimorbidities is still far from complete due to the complex nature of multimorbidity. Although various types of biological data, such as biomolecules and clinical symptoms, have been used to identify multimorbidities, the population phenotype information (e.g. physical activity and diet) remains less explored for multimorbidity. Here, we present a graph convolutional network (GCN) model, named MorbidGCN, for multimorbidity prediction by integrating population phenotypes and disease network. Specifically, MorbidGCN treats the multimorbidity prediction as a missing link prediction problem in the disease network, where a novel feature selection method is embedded to select important phenotypes. Benchmarking results on two large-scale multimorbidity data sets, i.e. the UK Biobank (UKB) and Human Disease Network (HuDiNe) data sets, demonstrate that MorbidGCN outperforms other competitive methods. With MorbidGCN, 9742 and 14 010 novel multimorbidities are identified in the UKB and HuDiNe data sets, respectively. Moreover, we notice that the selected phenotypes that are generally differentially distributed between multimorbidity patients and single-disease patients can help interpret multimorbidities and show potential for prognosis of multimorbidities.

Multimorbidity

Multimorbidity (two or more coexisting conditions in an individual) is a growing global challenge with substantial effects on individuals, carers and society. Multimorbidity occurs a decade earlier in socioeconomically deprived communities and is associated with premature death, poorer function and quality of life and increased health-care utilization. Mechanisms underlying the development of multimorbidity are complex, interrelated and multilevel, but are related to ageing and underlying biological mechanisms and broader determinants of health such as socioeconomic deprivation. Little is known about prevention of multimorbidity, but focusing on psychosocial and behavioural factors, particularly population level interventions and structural changes, is likely to be beneficial. Most clinical practice guidelines and health-care training and delivery focus on single diseases, leading to care that is sometimes inadequate and potentially harmful. Multimorbidity requires person-centred care, prioritizing what matters most to the individual and the individual's carers, ensuring care that is effectively coordinated and minimally disruptive, and aligns with the patient's values. Interventions are likely to be complex and multifaceted. Although an increasing number of studies have examined multimorbidity interventions, there is still limited evidence to support any approach. Greater investment in multimorbidity research and training along with reconfiguration of health care supporting the management of multimorbidity is urgently needed.

Prospective associations between vitamin D and depression in middle-aged adults: findings from the UK Biobank cohort

BACKGROUND

A possible role of vitamin D in the pathophysiology of depression is currently speculative, with more rigorous research needed to assess this association in large adult populations. The current study assesses prospective associations between vitamin D status and depression in middle-aged adults enrolled in the UK Biobank.

METHODS

We assessed prospective associations between vitamin D status at the baseline assessment (2006-2010) and depression measured at the follow-up assessment (2016) in 139 128 adults registered with the UK Biobank.

RESULTS

Amongst participants with no depression at baseline (n = 127 244), logistic regression revealed that those with vitamin D insufficiency [adjusted odds ratio (aOR) = 1.14, 95% confidence interval (CI) = 1.07-1.22] and those with vitamin D deficiency (aOR = 1.24, 95% CI 1.13-1.36) were more likely to develop new-onset depression at follow-up compared with those with optimal vitamin D levels after adjustment for a wide range of relevant covariates. Similar prospective associations were reported for those with depression at baseline (n = 11 884) (insufficiency: aOR = 1.11, 95% CI 1.00-1.23; deficiency: aOR = 1.30, 95% CI 1.13-1.50).

CONCLUSIONS

The prospective associations found between vitamin D status and depression suggest that both vitamin D deficiency and insufficiency might be risk factors for the development of new-onset depression in middle-aged adults. Moreover, vitamin D deficiency (and to a lesser extent insufficiency) might be a predictor of sustained depressive symptoms in those who are already depressed. Vitamin D deficiency and insufficiency is very common, meaning that these findings have significant implications for public health.

Temporal trajectories of important diseases in the life course and premature mortality in the UK Biobank

BACKGROUND

Little is known regarding life-course trajectories of important diseases. We aimed to identify diseases that were strongly associated with mortality and test temporal trajectories of these diseases before mortality.

METHODS

Our analysis was based on UK Biobank. Diseases were identified using questionnaires, nurses' interviews, or inpatient data. Mortality register data were used to identify mortality up to January 2021. The association between 60 individual diseases at baseline and in the life course and incident mortality was examined using Cox proportional regression models. Those diseases with great contribution to mortality were identified and disease trajectories in life course were then derived.

RESULTS

During a median follow-up of 11.8 years, 31,373 individuals (median age at death (interquartile range): 70.7 (65.3-74.8) years, 59.4% male) died of all-cause mortality (with complete data on diagnosis date of disease), with 16,237 dying with cancer and 6702 with cardiovascular disease (CVD). We identified 37 diseases including cancers and heart diseases that were associated with an increased risk of mortality independent of other diseases (hazard ratio ranged from 1.09 to 7.77). Among those who died during follow-up, 2.2% did not have a diagnosis of any disease of interest and 90.1% were diagnosed with two or more diseases in their life course. Individuals who were diagnosed with more diseases in their life course were more likely to have longer longevity. Cancer was more likely to be diagnosed following hypertension, hypercholesterolemia, CVD, or digestive disorders and more likely to be diagnosed ahead of CVD, chronic kidney disease (CKD), or digestive disorders. CVD was more likely to be diagnosed following hypertension, hypercholesterolemia, or digestive disorders and more likely to be diagnosed ahead of cancer or CKD. Hypertension was more likely to precede other diseases, and CKD was more likely to be diagnosed as the last disease before more mortality.

CONCLUSIONS

There are significant interplays between cancer and CVD for mortality. Cancer and CVD were frequently clustered with hypertension, CKD, and digestive disorders with CKD highly being diagnosed as the last disease in the life course. Our findings underline the importance of health checks among middle-aged adults for the prevention of premature mortality.

Physical multimorbidity and psychological distress among Chinese older adults: Findings from Chinese Longitudinal Healthy Longevity Survey

BACKGROUND

Research has linked multimorbidity with psychological distress among people with multimorbidity but the available findings are inconsistent. This study was to investigate the prevalence of multimorbidity and incidence of psychological distress in a nationally representative sample of Chinese older adults and examine the association between multimorbidity and psychological distress in this population.

METHODS

This study was a cross-sectional, secondary analysis using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Participants' socio-demographic characteristics and clinical information were obtained. Psychological distress including anxiety and depression were assessed by the Generalized Anxiety Disorder-7 (GAD-7) and the Center for Epidemiologic Studies Depression Scale (10-item CES-D). Binary logistic regression was used to ascertain the association between multimorbidity and psychological distress with covariates adjustment.

RESULTS

Compared with those without physical chronic conditions, having five or more physical chronic conditions was associated with the likelihood of depression after covariates adjustment.

CONCLUSION

Psychological distress is a common health issue among Chinese older adults with multimorbidity. Having multimorbidity might not be associated with psychological distress represented by anxiety and depression. Management of multimorbidity among this population would benefit from more attention on the mental health domain.

Multimorbidity and fit note receipt in working-age adults with long-term health conditions

BACKGROUND

Research on sickness absence has typically focussed on single diagnoses, despite increasing recognition that long-term health conditions are highly multimorbid and clusters comprising coexisting mental and physical conditions are associated with poorer clinical and functional outcomes. The digitisation of sickness certification in the UK offers an opportunity to address sickness absence in a large primary care population.

METHODS

Lambeth Datanet is a primary care database which collects individual-level data on general practitioner consultations, prescriptions, Quality and Outcomes Framework diagnostic data, sickness certification (fit note receipt) and demographic information (including age, gender, self-identified ethnicity, and truncated postcode). We analysed 326 415 people's records covering a 40-month period from January 2014 to April 2017.

RESULTS

We found significant variation in multimorbidity by demographic variables, most notably by self-defined ethnicity. Multimorbid health conditions were associated with increased fit note receipt. Comorbid depression had the largest impact on first fit note receipt, more than any other comorbid diagnoses. Highest rates of first fit note receipt after adjustment for demographics were for comorbid epilepsy and rheumatoid arthritis (HR 4.69; 95% CI 1.73-12.68), followed by epilepsy and depression (HR 4.19; 95% CI 3.60-4.87), chronic pain and depression (HR 4.14; 95% CI 3.69-4.65), cardiac condition and depression (HR 4.08; 95% CI 3.36-4.95).

CONCLUSIONS

Our results show striking variation in multimorbid conditions by gender, deprivation and ethnicity, and highlight the importance of multimorbidity, in particular comorbid depression, as a leading cause of disability among working-age adults.

The association between a lifestyle score, socioeconomic status, and COVID-19 outcomes within the UK Biobank cohort

BACKGROUND

Infection with SARS-CoV-2 virus (COVID-19) impacts disadvantaged groups most. Lifestyle factors are also associated with adverse COVID-19 outcomes. To inform COVID-19 policy and interventions, we explored effect modification of socioeconomic-status (SES) on associations between lifestyle and COVID-19 outcomes.

METHODS

Using data from UK-Biobank, a large prospective cohort of 502,536 participants aged 37-73 years recruited between 2006 and 2010, we assigned participants a lifestyle score comprising nine factors. Poisson regression models with penalised splines were used to analyse associations between lifestyle score, deprivation (Townsend), and COVID-19 mortality and severe COVID-19. Associations between each exposure and outcome were examined independently before participants were dichotomised by deprivation to examine exposures jointly. Models were adjusted for sociodemographic/health factors.

RESULTS

Of 343,850 participants (mean age > 60 years) with complete data, 707 (0.21%) died from COVID-19 and 2506 (0.76%) had severe COVID-19. There was evidence of a nonlinear association between lifestyle score and COVID-19 mortality but limited evidence for nonlinearity between lifestyle score and severe COVID-19 and between deprivation and COVID-19 outcomes. Compared with low deprivation, participants in the high deprivation group had higher risk of COVID-19 outcomes across the lifestyle score. There was evidence for an additive interaction between lifestyle score and deprivation. Compared with participants with the healthiest lifestyle score in the low deprivation group, COVID-19 mortality risk ratios (95% CIs) for those with less healthy scores in low versus high deprivation groups were 5.09 (1.39-25.20) and 9.60 (4.70-21.44), respectively. Equivalent figures for severe COVID-19 were 5.17 (2.46-12.01) and 6.02 (4.72-7.71). Alternative SES measures produced similar results.

CONCLUSIONS

Unhealthy lifestyles are associated with higher risk of adverse COVID-19, but risks are highest in the most disadvantaged, suggesting an additive influence between SES and lifestyle. COVID-19 policy and interventions should consider both lifestyle and SES. The greatest public health benefit from lifestyle focussed COVID-19 policy and interventions is likely to be seen when greatest support for healthy living is provided to the most disadvantaged groups.

Multimorbidity patterns and association with mortality in 0.5 million Chinese adults

BACKGROUND

Few studies have assessed the relationship between multimorbidity patterns and mortality risk in the Chinese population. We aimed to identify multimorbidity patterns and examined the associations of multimorbidity patterns and the number of chronic diseases with the risk of mortality among Chinese middle-aged and older adults.

METHODS

We used data from the China Kadoorie Biobank and included 512,723 participants aged 30 to 79 years. Multimorbidity was defined as the presence of two or more of the 15 chronic diseases collected by self-report or physical examination at baseline. Multimorbidity patterns were identified using hierarchical cluster analysis. Cox regression was used to estimate the associations of multimorbidity patterns and the number of chronic diseases with all-cause and cause-specific mortality.

RESULTS

Overall, 15.8% of participants had multimorbidity. The prevalence of multimorbidity increased with age and was higher in urban than rural participants. Four multimorbidity patterns were identified, including cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), gastrointestinal and hepatorenal multimorbidity (gallstone disease, chronic kidney disease, cirrhosis, peptic ulcer, and cancer), and mental and arthritis multimorbidity (neurasthenia, psychiatric disorder, and rheumatoid arthritis). During a median of 10.8 years of follow-up, 49,371 deaths occurred. Compared with participants without multimorbidity, cardiometabolic multimorbidity (hazard ratios [HR] = 2.20, 95% confidence intervals [CI]: 2.14 - 2.26) and respiratory multimorbidity (HR = 2.13, 95% CI:1.97 - 2.31) demonstrated relatively higher risks of mortality, followed by gastrointestinal and hepatorenal multimorbidity (HR = 1.33, 95% CI:1.22 - 1.46). The mortality risk increased by 36% (HR = 1.36, 95% CI: 1.35 - 1.37) with every additional disease.

CONCLUSION

Cardiometabolic multimorbidity and respiratory multimorbidity posed the highest threat on mortality risk and deserved particular attention in Chinese adults.

The role of cardiac rehabilitation in improving cardiovascular outcomes

Cardiac rehabilitation is a complex intervention that seeks to improve the functional capacity, wellbeing and health-related quality of life of patients with heart disease. A substantive evidence base supports cardiac rehabilitation as a clinically effective and cost-effective intervention for patients with acute coronary syndrome or heart failure with reduced ejection fraction and after coronary revascularization. In this Review, we discuss the major contemporary challenges that face cardiac rehabilitation. Despite the strong recommendation in current clinical guidelines for the referral of these patient groups, global access to cardiac rehabilitation remains poor. The COVID-19 pandemic has contributed to a further reduction in access to cardiac rehabilitation. An increasing body of evidence supports home-based and technology-based models of cardiac rehabilitation as alternatives or adjuncts to traditional centre-based programmes, especially in low-income and middle-income countries, in which cardiac rehabilitation services are scarce, and scalable and affordable models are much needed. Future approaches to the delivery of cardiac rehabilitation need to align with the growing multimorbidity of an ageing population and cater to the needs of the increasing numbers of patients with cardiac disease who present with two or more chronic diseases. Future research priorities include strengthening the evidence base for cardiac rehabilitation in other indications, including heart failure with preserved ejection fraction, atrial fibrillation and congenital heart disease and after valve surgery or heart transplantation, and evaluation of the implementation of sustainable and affordable models of delivery that can improve access to cardiac rehabilitation in all income settings.

Associations between multimorbidity and adverse health outcomes in UK Biobank and the SAIL Databank: A comparison of longitudinal cohort studies

BACKGROUND

Cohorts such as UK Biobank are increasingly used to study multimorbidity; however, there are concerns that lack of representativeness may lead to biased results. This study aims to compare associations between multimorbidity and adverse health outcomes in UK Biobank and a nationally representative sample.

METHODS AND FINDINGS

These are observational analyses of cohorts identified from linked routine healthcare data from UK Biobank participants (n = 211,597 from England, Scotland, and Wales with linked primary care data, age 40 to 70, mean age 56.5 years, 54.6% women, baseline assessment 2006 to 2010) and from the Secure Anonymised Information Linkage (SAIL) databank (n = 852,055 from Wales, age 40 to 70, mean age 54.2, 50.0% women, baseline January 2011). Multimorbidity (n = 40 long-term conditions [LTCs]) was identified from primary care Read codes and quantified using a simple count and a weighted score. Individual LTCs and LTC combinations were also assessed. Associations with all-cause mortality, unscheduled hospitalisation, and major adverse cardiovascular events (MACEs) were assessed using Weibull or negative binomial models adjusted for age, sex, and socioeconomic status, over 7.5 years follow-up for both datasets. Multimorbidity was less common in UK Biobank than SAIL (26.9% and 33.0% with ≥2 LTCs in UK Biobank and SAIL, respectively). This difference was attenuated, but persisted, after standardising by age, sex, and socioeconomic status. The association between increasing multimorbidity count and mortality, hospitalisation, and MACE was similar between both datasets at LTC counts of ≤3; however, above this level, UK Biobank underestimated the risk associated with multimorbidity (e.g., mortality hazard ratio for 2 LTCs 1.62 (95% confidence interval 1.57 to 1.68) in SAIL and 1.51 (1.43 to 1.59) in UK Biobank, hazard ratio for 5 LTCs was 3.46 (3.31 to 3.61) in SAIL and 2.88 (2.63 to 3.15) in UK Biobank). Absolute risk of mortality, hospitalisation, and MACE, at all levels of multimorbidity, was lower in UK Biobank than SAIL (adjusting for age, sex, and socioeconomic status). Both cohorts produced similar hazard ratios for some LTCs (e.g., hypertension and coronary heart disease), but UK Biobank underestimated the risk for others (e.g., alcohol-related disorders or mental health conditions). Hazard ratios for some LTC combinations were similar between the cohorts (e.g., cardiovascular conditions); however, UK Biobank underestimated the risk for combinations including other conditions (e.g., mental health conditions). The main limitations are that SAIL databank represents only part of the UK (Wales only) and that in both cohorts we lacked data on severity of the LTCs included.

CONCLUSIONS

In this study, we observed that UK Biobank accurately estimates relative risk of mortality, unscheduled hospitalisation, and MACE associated with LTC counts ≤3. However, for counts ≥4, and for some LTC combinations, estimates of magnitude of association from UK Biobank are likely to be conservative. Researchers should be mindful of these limitations of UK Biobank when conducting and interpreting analyses of multimorbidity. Nonetheless, the richness of data available in UK Biobank does offers opportunities to better understand multimorbidity, particularly where complementary data sources less susceptible to selection bias can be used to inform and qualify analyses of UK Biobank.

Multimorbidity and co-occurring musculoskeletal pain do not modify the effect of the SELFBACK app on low back pain-related disability

BACKGROUND

SELFBACK, an artificial intelligence (AI)-based app delivering evidence-based tailored self-management support to people with low back pain (LBP), has been shown to reduce LBP-related disability when added to usual care. LBP commonly co-occurs with multimorbidity (≥ 2 long-term conditions) or pain at other musculoskeletal sites, so this study explores if these factors modify the effect of the SELFBACK app or influence outcome trajectories over time.

METHODS

Secondary analysis of a randomized controlled trial with 9-month follow-up. Primary outcome is as follows: LBP-related disability (Roland Morris Disability Questionnaire, RMDQ). Secondary outcomes are as follows: stress/depression/illness perception/self-efficacy/general health/quality of life/physical activity/global perceived effect. We used linear mixed models for continuous outcomes and logistic generalized estimating equation for binary outcomes. Analyses were stratified to assess effect modification, whereas control (n = 229) and intervention (n = 232) groups were pooled in analyses of outcome trajectories.

RESULTS

Baseline multimorbidity and co-occurring musculoskeletal pain sites did not modify the effect of the SELFBACK app. The effect was somewhat stronger in people with multimorbidity than among those with LBP only (difference in RMDQ due to interaction, - 0.9[95 % CI - 2.5 to 0.6]). Participants with a greater number of long-term conditions and more co-occurring musculoskeletal pain had higher levels of baseline disability (RMDQ 11.3 for ≥ 2 long-term conditions vs 9.5 for LBP only; 11.3 for ≥ 4 musculoskeletal pain sites vs 10.2 for ≤ 1 additional musculoskeletal pain site); along with higher baseline scores for stress/depression/illness perception and poorer pain self-efficacy/general health ratings. In the pooled sample, LBP-related disability improved slightly less over time for people with ≥ 2 long-term conditions additional to LBP compared to no multimorbidity and for those with ≥4 co-occurring musculoskeletal pain sites compared to ≤ 1 additional musculoskeletal pain site (difference in mean change at 9 months = 1.5 and 2.2, respectively). All groups reported little improvement in secondary outcomes over time.

CONCLUSIONS

Multimorbidity or co-occurring musculoskeletal pain does not modify the effect of the selfBACK app on LBP-related disability or other secondary outcomes. Although people with these health problems have worse scores both at baseline and 9 months, the AI-based selfBACK app appears to be helpful for those with multimorbidity or co-occurring musculoskeletal pain.

TRIAL REGISTRATION

NCT03798288 . Date of registration: 9 January 2019.

Multimorbidity, polypharmacy, and mortality in older patients with pacemakers

BACKGROUND

The prevalence of multimorbidity and polypharmacy and its association with all-cause mortality in older patients with pacemakers are largely unknown. We aimed to clarify the prevalence of multimorbidity and polypharmacy, and its association with all-cause mortality in patients ≥75 years of age with pacemakers.

METHODS

We retrospectively investigated 256 patients aged ≥75 years (mean age 84.0 ± 5.3 years; 45.7% male) with newly implanted pacemakers. The study endpoint was all-cause mortality ("with events"). Multimorbidity was defined as a Charlson Comorbidity Index ≥3. Polypharmacy was defined as the use of ≥5 medications.

RESULTS

During the follow-up period (median, 3.1 years), 60 all-cause deaths were reported. The Charlson Comorbidity Index (2.9 ± 1.9 vs. 1.7 ± 1.7, p < .001) and prevalence of multimorbidity (56.7% vs. 26.0%, p < .001) were significantly higher in deceased patients than in survivors. The number of drugs (6.9 ± 3.0 vs. 5.9 ± 3.3, p = .03) and the prevalence of polypharmacy (78.3% vs. 63.8%, p = .04) were significantly higher in patients with events than in those without events. The event-free survival rate was significantly higher among patients without multimorbidity than in those with multimorbidity (log-rank, p < .001), and was also significantly higher among patients without polypharmacy than in those with polypharmacy (log-rank, p < .001). Multimorbidity (hazard ratio [HR]: 3.21; 95% confidence interval [CI]: 1.85-5.58; p < .001) and polypharmacy (HR: 1.97; 95% CI: 1.03-3.77; p = .04) were independent predictors of all-cause mortality.

CONCLUSIONS

Multimorbidity and its associated polypharmacy, which are common in the older population, are prevalent in patients with pacemakers and are independent predictors of poor prognosis.

The association of anxiety and stress-related disorders with C-reactive protein (CRP) within UK Biobank

Anxiety and stress-related disorders are both common and disabling psychiatric conditions. There are a number of hypotheses suggesting the underlying pathophysiology of these disorders, however, the exact mechanism is unknown. Inflammation has previously been linked with depression and has more recently been suggested as a possible link to anxiety aetiology. The objectives of this study are to assess the relationship between different anxiety/stress-related disorders and inflammation (measured by C-reactive protein) using the UK Biobank, and also determine whether any relationship between anxiety/stress disorders and inflammation is explained by depressive symptoms and other social and health-related factors. We utilised the UK Biobank for the sample of this study. Our sample included 353,136 participants of which 12,759 (3.61%) had a history of an anxiety (phobic, obsessive-compulsive, or other anxiety disorder including generalised anxiety and panic disorders) or stress-related disorder (including acute stress reaction, post-traumatic stress disorder and adjustment disorders). Four logistic regression models were calculated in which we tested the association between anxiety/stress disorders and C-reactive protein (CRP) >3 ​mg/L, adjusting for covariates (including age, sex, ethnicity, education level, socioeconomic deprivation, depressive symptoms, body mass index (BMI) and multimorbidity). An association was observed between other anxiety disorders (including panic and generalised anxiety disorders) and CRP (OR: 1.164 [95% CI: 1.096–1.236]). This was attenuated in models after the addition of BMI, multimorbidity and depressive symptoms. Stress/adjustment disorders followed a similar pattern of results (OR: 1.107 [95% CI: 1.040, 1.178]), with the association attenuated with the addition of BMI and multimorbidity). Phobic anxiety disorders (OR: 1.059 [95% CI: 0.896, 1.251]) and obsessive-compulsive disorders (OR: 1.299 [95% CI: 0.973, 1.733]) both showed no statistically significant results in any of the models. Our results support the hypothesis that some anxiety and stress-related disorders may be associated with high levels of inflammatory markers, as measured by CRP. Further studies are required to untangle the potential causal relationships involved.

•

We explored the association of anxiety and stress-related disorders with C-reactive protein (CRP) using UK Biobank.

•

Several disorders (e.g. generalised anxiety, panic and stress/adjustment) were associated with higher levels of CRP.

•

Associations were attenuated with adjustment for health-related factors, such as multimorbidity and depressive symptoms.

Long-term conditions, multimorbidity and colorectal cancer risk in the UK Biobank cohort

PURPOSE

Early identification of colorectal cancer (CRC) is an international priority. Multimorbidity (presence of ≥2 long-term conditions (LTCs)) is increasing and the relationship between CRC and LTCs is little-understood. This study explores the relationship between individual LTCs, multimorbidity and CRC incidence and mortality.

METHODS

Longitudinal analysis of the UK Biobank cohort, participants recruited 2006-2010; N = 500,195; excluding previous CRC at baseline. Baseline data was linked with cancer/mortality registers. Demographic characteristics, lifestyle factors, 43 LTCs, CRC family history, non-CRC cancers, and multimorbidity count were recorded. Variable selection models identified candidate LTCs potentially predictive of CRC outcomes and Cox regression models tested for significance of associations between selected LTCs and outcomes.

RESULTS

Participants' age range: 37-73 (mean age 56.5; 54.5% female). CRC was diagnosed in 3669 (0.73%) participants, and 916 (0.18%) died from CRC during follow-up (median follow-up 7 years). CRC incidence was higher in the presence of heart failure (Hazard Ratio (HR) 1.96, 95% Confidence Interval (CI) 1.13-3.40), diabetes (HR 1.15, CI 1.01-1.32), glaucoma (HR 1.36, CI 1.06-1.74), male cancers (HR 1.44, CI 1.01-2.08). CRC mortality was higher in presence of epilepsy (HR 1.83, CI 1.03-3.26), diabetes (HR 1.32, CI 1.02-1.72), osteoporosis (HR 1.67, CI 1.12-2.58). No significant association was found between multimorbidity (≥2 LTCs) and CRC outcomes.

CONCLUSIONS

The associations of certain LTCs with CRC incidence and mortality has implications for clinical practice: presence of certain LTCs in patients presenting with CRC symptoms could trigger early investigation and diagnosis. Future research should explore causative mechanisms and patient perspectives.

Collecting and sharing self-generated health and lifestyle data: Understanding barriers for people living with long-term health conditions - a survey study

Background

The growing popularity of collecting self-generated health and lifestyle data presents a valuable opportunity to develop our understanding of long-term health conditions and improve care. Barriers remain to the effective sharing of health and lifestyle data by those living with long-term health conditions which include beliefs around concepts of Trust, Identity, Privacy and Security, experiences of stigma, perceptions of risk and information sensitivity.

Method

We surveyed 250 UK adults who reported living with a range of long-term health conditions. We recorded data to assess self-reported behaviours, experiences, attitudes and motivations relevant to sharing self-generated health and lifestyle data. We also asked participants about their beliefs about Trust, Identity, Privacy and Security, stigma, and perceptions of risk and information sensitivity regarding their health and lifestyle data.

Results

Three-quarters of our sample reported recording information about their health and lifestyle on a daily basis. However, two-thirds reported never or rarely sharing this information with others. Trust, Identity, Privacy and Security concerns were considered to be 'very important' by those with long-term health conditions when deciding whether or not to share self-generated health and lifestyle data with others, with security concerns considered most important. Of those living with a long-term health condition, 58% reported experiencing stigma associated with their condition. The greatest perceived risk from sharing with others was the potential for future harm to their social relationships.

Conclusions

Our findings suggest that, in order for health professionals and researchers to benefit from the increased prevalence of self-generated health and lifestyle data, more can be done to address security concerns and to understand perceived risks associated with data sharing. Digital platforms aimed at facilitating the sharing of self-generated health and lifestyle data may look to highlight security features, enable users to control the sharing of certain information types, and emphasise the practical benefits to users of sharing health and lifestyle data with others.

Cardiac rehabilitation for older adults: current evidence and future potential

INTRODUCTION

Growth of the older adult demographic has resulted in an increased number of older patients with cardiovascular disease (CVD) in combination with comorbid diseases and geriatric syndromes. Cardiac rehabilitation (CR) is utilized to promote recovery and improve outcomes, but remains underutilized, particularly by older adults. CR provides an opportunity to address the distinctive needs of older adults, with focus on CVD as well as geriatric domains that often dominate management and outcomes.

AREAS COVERED

Utility of CR for CVD in older adults as well as pertinent geriatric syndromes (e.g. multimorbidity, frailty, polypharmacy, cognitive decline, psychosocial stress, and diminished function) that affect CVD management.

EXPERT OPINION

Mounting data substantiate the importance of CR as part of recovery for older adults with CVD. The application of CR as a standard therapy is especially important as the combination of CVD and geriatric syndromes catalyzes functional decline and can trigger progressive clinical deterioration and dependency. While benefits of CR for older adults with CVD are already evident, further reengineering of CR is necessary to better address the needs of older candidates who may be frail, especially as remote and hybrid formats of CR are becoming more widespread.

Association between multimorbidity and mortality in a cohort of patients admitted to hospital with COVID-19 in Scotland

OBJECTIVES

We investigated the association between multimorbidity among patients hospitalised with COVID-19 and their subsequent risk of mortality. We also explored the interaction between the presence of multimorbidity and the requirement for an individual to shield due to the presence of specific conditions and its association with mortality.

DESIGN

We created a cohort of patients hospitalised in Scotland due to COVID-19 during the first wave (between 28 February 2020 and 22 September 2020) of the pandemic. We identified the level of multimorbidity for the patient on admission and used logistic regression to analyse the association between multimorbidity and risk of mortality among patients hospitalised with COVID-19.

SETTING

Scotland, UK.

PARTICIPANTS

Patients hospitalised due to COVID-19.

MAIN OUTCOME MEASURES

Mortality as recorded on National Records of Scotland death certificate and being coded for COVID-19 on the death certificate or death within 28 days of a positive COVID-19 test.

RESULTS

Almost 58% of patients admitted to the hospital due to COVID-19 had multimorbidity. Adjusting for confounding factors of age, sex, social class and presence in the shielding group, multimorbidity was significantly associated with mortality (adjusted odds ratio 1.48, 95%CI 1.26-1.75). The presence of multimorbidity and presence in the shielding patients list were independently associated with mortality but there was no multiplicative effect of having both (adjusted odds ratio 0.91, 95%CI 0.64-1.29).

CONCLUSIONS

Multimorbidity is an independent risk factor of mortality among individuals who were hospitalised due to COVID-19. Individuals with multimorbidity could be prioritised when making preventive policies, for example, by expanding shielding advice to this group and prioritising them for vaccination.

Preterm birth and the risk of chronic disease multimorbidity in adolescence and early adulthood: A population-based cohort study

BACKGROUND

People who were born prematurely have high risks of many individual diseases and conditions in the early part of the life course. However, our knowledge of the burden of multiple diseases (multimorbidity) among prematurely born individuals is limited. We aimed to investigate the risk and patterns of chronic disease multimorbidity in adolescence and early adulthood among individuals born across the spectrum of gestational ages, comparing preterm and full-term born individuals.

METHODS AND FINDINGS

We used individual-level data from linked nationwide registers to examine the associations of gestational age at birth with specialised healthcare records of ≥2 chronic diseases (multimorbidity) in adolescence (age 10-17 years) and early adulthood (age 18-30 years). Our study population comprised 951,116 individuals (50.2% females) born alive in Finland between 1st January 1987 and 31st December 2006, inclusive. All individuals were followed from age 10 years to the onset of multimorbidity, emigration, death, or 31 December 2016 (up to age 30 years). We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for multimorbidity using flexible parametric survival models. During 6,417,903 person-years at risk (median follow-up: 7.9 years), 11,919 individuals (1.3%) had multimorbidity in adolescence (18.6 per 10,000 person-years). During 3,967,419 person-years at risk (median follow-up: 6.2 years), 15,664 individuals (1.7%) had multimorbidity in early adulthood (39.5 per 10,000 person-years). Adjusted HRs for adolescent multimorbidity, comparing preterm to full-term born individuals, were 1.29 (95% CI: 1.22 to 1.36) and 1.26 (95% CI: 1.18 to 1.35) in females and males, respectively. The associations of preterm birth with early adult multimorbidity were less marked, with the adjusted HRs indicating 1.18-fold risk in females (95% CI: 1.12 to 1.24) and 1.10-fold risk in males (95% CI: 1.04 to 1.17). We observed a consistent dose-response relationship between earlier gestational age at birth and increasing risks of both multimorbidity outcomes. Compared to full-term born males, those born at 37-38 weeks (early term) had a 1.06-fold risk of multimorbidity in adolescence (95% CI: 0.98 to 1.14) and this risk increased in a graded manner up to 6.85-fold (95% CI: 5.39 to 8.71) in those born at 23-27 weeks (extremely premature), independently of covariates. Among females, the same risks ranged from 1.16-fold (95% CI: 1.09 to 1.23) among those born at 37-38 weeks to 5.65-fold (95% CI: 4.45 to 7.18) among those born at 23-27 weeks. The corresponding risks of early adult multimorbidity were similar in direction but less marked in magnitude, with little difference in risks between males and females born at 36-37 weeks but up to 3-fold risks observed among those born at 23-27 weeks.

CONCLUSIONS

Our findings indicate that an earlier gestational age at birth is associated with increased risks of chronic disease multimorbidity in the early part of the life course. There are currently no clinical guidelines for follow-up of prematurely born individuals beyond childhood, but these observations suggest that information on gestational age would be a useful characteristic to include in a medical history when assessing the risk of multiple chronic diseases in adolescent and young adult patients.

Trends in Cardiometabolic and Cancer Multimorbidity Prevalence and Its Risk With All-Cause and Cause-Specific Mortality in U.S. Adults: Prospective Cohort Study

Several prospective cohort studies have assessed the association between multimorbidity and all-cause mortality, but the findings have been inconsistent. In addition, limited studies have assessed the association between multimorbidity and cause-specific mortality. In this study, we used the population based cohort study of National Health Interview Survey (1997–2014) with linkage to the National Death Index records to 31 December 2015 to examine the trends in prevalence of multimorbidity from 1997 to 2014, and its association with the risk of all-cause and cause-specific mortality in the U.S. population. A total of 372,566 adults aged 30–84 years were included in this study. From 1997 to 2014, the age-standardized prevalence of specific chronic condition and multimorbidity increased significantly (P < 0.0001). During a median follow-up of 9.0 years, 50,309 of 372,566 participants died from all causes, of which 11,132 (22.1%) died from CVD and 13,170 (26.2%) died from cancer. Compared with participants without the above-mentioned chronic conditions, those with 1, 2, 3, and ≥4 of chronic conditions had 1.41 (1.37–1.45), 1.94 (1.88–2.00), 2.64 (2.54–2.75), and 3.68 (3.46–3.91) higher risk of all-cause mortality after adjustment for important covariates. Similarly, a higher risk of CVD-specific and cancer-specific mortality was observed as the number of chronic conditions increased, with the observed risk stronger for CVD-mortality compared with cancer-specific mortality. Given the prevalence of multimorbidity tended to increase from 1997 to 2014, our data suggest effective prevention and intervention programs are necessary to limit the increased mortality risk associated with multimorbidity.

Mediating role of multimorbidity in inequality in mortality: a register study on the Danish population

BACKGROUND

The social inequality in mortality is due to differential incidence of several disorders and injury types, as well as differential survival. The resulting clustering and possible interaction in disadvantaged groups of several disorders make multimorbidity a potentially important component in the health divide. This study decomposes the effect of education on mortality into a direct effect, a pure indirect effect mediated by multimorbidity and a mediated interaction between education and multimorbidity.

METHODS

The study uses the Danish population registers on the total Danish population aged 45-69 years. A multimorbidity index based on all somatic and psychiatric hospital contacts as well as prescribed medicines includes 22 diagnostic groups weighted together by their 5 years mortality risk as weight. The Aalen additive hazard model is used to estimate and decompose the 5 years risk difference in absolute numbers of deaths according to educational status.

RESULTS

Most (69%-79%) of the effect is direct not involving multimorbidity, and the mediated effect is for low educated women 155 per 100 000 of which 87 is an effect of mediated interaction. For low educated men, the mediated effect is 250 per 100 000 of which 93 is mediated interaction.

CONCLUSION

Multimorbidity plays an important role in the social inequality in mortality among middle aged in Denmark and mediated interaction represents 5%-17%. As multimorbidity is a growing challenge in specialised health systems, the mediated interaction might be a relevant indicator of inequities in care of multimorbid patients.

Associations of A Body Shape Index (ABSI) with Cancer Incidence, All-Cause, and at 23 Sites-Findings from the UK Biobank Prospective Cohort Study

BACKGROUND

Few studies have explored the emerging adiposity marker A Body Shape Index (ABSI) with cancer risk. This study investigated the associations between ABSI and the incidence of cancer at 23 sites and all cancer combined.

METHODS

Data from 442,610 participants from the UK Biobank prospective study were included in this study. ABSI was used as the exposure. Incidence of cancer at 23 sites was the outcome. Cox proportional hazard models were performed to explore the association of ABSI, and combined ABSI and body mass index (BMI) with cancer risk, after adjusting for multiple testing.

RESULTS

36,961 individuals developed cancer during the 8.8 years median follow-up. In multivariable analyses, participants in the highest tertile of ABSI had higher risk of lung [HR, 1.58; 95% confidence interval (CI), 1.44-1.74], liver (HR, 1.45; 95% CI, 1.18-1.77), esophagus (HR, 1.32; 95% CI, 1.12-1.57), colorectal (HR, 1.19; 95% CI, 1.10-1.28), and breast (HR, 1.05; 95% CI, 1.04-1.17) cancers, and all cancers combined (HR, 1.11; 95% CI, 1.08-1.14) compared with the lowest tertile. These associations remained significant after adjustment for BMI. When ABSI was combined with BMI, participants in the highest ABSI who also had a BMI ≥ 25 kg/m² were at higher risk of uterus, esophagus, liver, stomach, colorectal, and breast cancers, as well as all cancers combined, compared with those in the lowest ABSI tertile with a normal BMI.

CONCLUSIONS

ABSI is associated with an increased risk of five cancers as well as all cancers combined, independently of BMI.

IMPACT

ABSI is a useful marker for adiposity. However, cancer risk prediction improves with the combination of BMI.

Associations between long-term conditions and upper gastrointestinal cancer incidence: A prospective population-based cohort of UK Biobank participants

Background/Aims

Upper gastrointestinal cancers (oesophageal/stomach) have high mortality rates and are often diagnosed after the disease has progressed, making it important to identify populations at greater risk of upper gastrointestinal (UGI) cancer to promote earlier diagnosis. This study aims to determine if there is an association between a broad range of long-term conditions (LTCs) and incidence of UGI cancers.

Method

A prospective-based cohort of 487,798 UK Biobank participants (age 37-73 years) after excluding previous UGI cancer. Least Absolute Shrinkage and Selection Operator (LASSO) regression used to identify candidate LTCs as predictors for UGI cancer. Strength of association was studied using Cox's regression adjusting for demographics and lifestyle factors.

Results

After median follow-up period of 86 months, 598 participants developed oesophageal cancer; 397 developed stomach cancer. In fully adjusted models, participants with alcohol addiction (Hazard Ratio-HR 4.11, 95% Confidence Interval-CI 2.01-8.43), Barrett's oesophagus (HR 5.68, 95% CI 3.36-9.58), bronchiectasis (HR 2.72, 95% CI 1.01-7.31), diabetes (HR 1.38, 95% CI 1.06-1.81), hiatus hernia (HR 1.69, 95% CI 1.16-2.45), Parkinson's disease (HR 3.86, 95% CI 1.60-9.37) and psoriasis/eczema (HR 1.53, 95% 1.08-2.17) were observed to have a higher risk of oesophageal cancer. Stomach cancer incidence was higher among participants with anorexia/bulimia (HR 8.86, 95% CI 1.20-65.14), Barrett's oesophagus (HR 3.37, 95% 1.39-8.14), chronic fatigue syndrome (HR 3.36, 95% CI 1.25-9.03), glaucoma (HR 2.06, 95% CI 1.16-3.67), multiple sclerosis (HR 4.60, 95% CI 1.71-12.34), oesophageal stricture (HR 1.04, 95% CI 1.46-74.46) and pernicious anaemia (HR 6.93, 95% CI 3.42-14.03).

Conclusion

Previously unrecognised LTCs may have a role in symptom appraisal and risk assessment of UGI cancer in primary care. Further research should explore mechanisms underpinning these findings and determine whether they are replicable in other populations.

Hospitalisation events in people with chronic kidney disease as a component of multimorbidity: parallel cohort studies in research and routine care settings

BACKGROUND

Chronic kidney disease (CKD) typically co-exists with multimorbidity (presence of 2 or more long-term conditions: LTCs). The associations between CKD, multimorbidity and hospitalisation rates are not known. The aim of this study was to examine hospitalisation rates in people with multimorbidity with and without CKD. Amongst people with CKD, the aim was to identify risk factors for hospitalisation.

METHODS

Two cohorts were studied in parallel: UK Biobank (a prospective research study: 2006-2020) and Secure Anonymised Information Linkage Databank (SAIL: a routine care database, Wales, UK: 2011-2018). Adults were included if their kidney function was measured at baseline. Nine categories of participants were used: zero LTCs; one, two, three and four or more LTCs excluding CKD; and one, two, three and four or more LTCs including CKD. Emergency hospitalisation events were obtained from linked hospital records.

RESULTS

Amongst 469,339 UK Biobank participants, those without CKD had a median of 1 LTC and those with CKD had a median of 3 LTCs. Amongst 1,620,490 SAIL participants, those without CKD had a median of 1 LTC and those with CKD had a median of 5 LTCs. Compared to those with zero LTCs, participants with four or more LTCs (excluding CKD) had high event rates (rate ratios UK Biobank 4.95 (95% confidence interval 4.82-5.08)/SAIL 3.77 (3.71-3.82)) with higher rates if CKD was one of the LTCs (rate ratios UK Biobank 7.83 (7.42-8.25)/SAIL 9.92 (9.75-10.09)). Amongst people with CKD, risk factors for hospitalisation were advanced CKD, age over 60, multiple cardiometabolic LTCs, combined physical and mental LTCs and complex patterns of multimorbidity (LTCs in three or more body systems).

CONCLUSIONS

People with multimorbidity have high rates of hospitalisation. Importantly, the rates are two to three times higher when CKD is one of the multimorbid conditions. Further research is needed into the mechanism underpinning this to inform strategies to prevent hospitalisation in this very high-risk group.

Effect of education and multimorbidity on mortality among older adults: findings from the health, well-being and ageing cohort study (SABE)

OBJECTIVES

This study assessed the moderating role of education on the relationship between multimorbidity and mortality among older adults in Brazil.

STUDY DESIGN

This was a cohort study.

METHODS

This study used data from 1768 participants of the Health, Well-Being and Ageing Cohort Study (SABE) who were assessed between 2006 and 2015. The Cox Proportional Risks Model was used to evaluate the association between multimorbidity (two or more chronic diseases) and mortality. An interaction term between education and multimorbidity was included to test the moderating role of education in this association.

RESULTS

The average follow-up time was 4.5 years, with a total of 589 deaths in the period. Multimorbidity increased the risk of mortality (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.27-1.91), and this association was not moderated by education (HR 1.06, 95% CI 1.00-1.13; P value = 0.07).

CONCLUSIONS

The impact of education and multimorbidity on mortality emphasises the need for an integrated approach directed towards the social determinants of health to prevent multimorbidity and its burden among older adults.

Living with a chronic disease: insights from patients with a low socioeconomic status

Background

Little is known about how patients with low socioeconomic status (SES) experience their chronic disease, and how it impacts health-related quality of life (HRQoL). Compared to their more affluent counterparts, worse outcomes have been reported. A better understanding of the domains of HRQoL that are relevant to these specific populations is therefore needed. We explored the experiences of living with a chronic disease in low SES persons.

Methods

A qualitative interview study was performed in Flanders, Belgium. Semi-structured interviews were conducted in chronically ill patients, selected through purposive sampling. Interviews were audio-recorded and transcribed verbatim. Analysis followed an inductive and iterative approach.

Results

Fifteen patients were interviewed. Six major themes were identified: a heavy bag to carry, loss of autonomous life, inner and outer loneliness, emotional imbalance, unmet need for support, and coping strategies. Patients experienced their illness as an additional problem on top of all other problems (i.e. financial/social problems, traumatic life events). In general, the disease burden and non-disease burden were mutually reinforcing, resulting in greater dependency, greater risk of social isolation, greater psychological distress, and greater risk of impaired HRQoL.

Conclusions

This study is the first to provide detailed insight into the experiences of living with a chronic disease in low SES persons. A conceptual model is proposed that can be used in daily clinical practice to raise awareness among clinicians and health care providers that the patient’s needs go beyond the disease itself. Future research is needed to validate and test the model.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01578-7.

Multimorbidity and the risk of major adverse kidney events: findings from the UK Biobank cohort

Background

Multimorbidity [the presence of two or more long-term conditions (LTCs)] is associated with a heightened risk of mortality, but little is known about its relationship with the risk of kidney events.

Methods

Associations between multimorbidity and major adverse kidney events [MAKE: the need for long-term kidney replacement therapy, doubling of serum creatinine, fall of estimated glomerular filtration rate (eGFR) to <15 mL/min/1.73 m² or 30% decline in eGFR] were studied in 68 505 participants from the UK Biobank cohort. Participants were enrolled in the study between 2006 and 2010. Associations between LTC counts and MAKE were tested using survival analyses accounting for the competing risk of death.

Results

Over a median follow-up period of 12.0 years, 2963 participants had MAKE. There were associations between LTC count categories and the risk of MAKE [one LTC adjusted subhazard ratio (sHR) = 1.29, 95% confidence interval (CI) 1.15–1.45; two LTCs sHR = 1.74 (95% CI 1.55–1.96); and three or more LTCs sHR = 2.41 (95% CI 2.14–2.71)]. This finding was more pronounced when only cardiometabolic LTCs were considered [one LTC sHR = 1.58 (95% CI 1.45–1.73); two LTCs sHR = 3.17 (95% CI 2.80–3.59); and three or more LTCs sHR = 5.24 (95% CI 4.34–6.33)]. Combinations of LTCs associated with MAKE were identified. Diabetes, hypertension and coronary heart disease featured most commonly in high-risk combinations.

Conclusions

Multimorbidity, and in particular cardiometabolic multimorbidity, is a risk factor for MAKE. Future research should study groups of patients who are at high risk of progressive kidney disease based on the number and type of LTCs.

Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices

BACKGROUND

Myocardial infarction (MI), stroke and diabetes share underlying risk factors and commonalities in clinical management. We examined if their combined impact on mortality is proportional, amplified or less than the expected risk separately of each disease and whether the excess risk is explained by their associated comorbidities.

METHODS

Using large-scale electronic health records, we identified 2,007,731 eligible patients (51% women) and registered with general practices in the UK and extracted clinical information including diagnosis of myocardial infarction (MI), stroke, diabetes and 53 other long-term conditions before 2005 (study baseline). We used Cox regression to determine the risk of all-cause mortality with age as the underlying time variable and tested for excess risk due to interaction between cardiometabolic conditions.

RESULTS

At baseline, the mean age was 51 years, and 7% (N = 145,910) have had a cardiometabolic condition. After a 7-year mean follow-up, 146,994 died. The sex-adjusted hazard ratios (HR) (95% confidence interval [CI]) of all-cause mortality by baseline disease status, compared to those without cardiometabolic disease, were MI = 1.51 (1.49-1.52), diabetes = 1.52 (1.51-1.53), stroke = 1.84 (1.82-1.86), MI and diabetes = 2.14 (2.11-2.17), MI and stroke = 2.35 (2.30-2.39), diabetes and stroke = 2.53 (2.50-2.57) and all three = 3.22 (3.15-3.30). Adjusting for other concurrent comorbidities attenuated these estimates, including the risk associated with having all three conditions (HR = 1.81 [95% CI 1.74-1.89]). Excess risks due to interaction between cardiometabolic conditions, particularly when all three conditions were present, were not significantly greater than expected from the individual disease effects.

CONCLUSION

Myocardial infarction, stroke and diabetes were associated with excess mortality, without evidence of any amplification of risk in people with all three diseases. The presence of other comorbidities substantially contributed to the excess mortality risks associated with cardiometabolic disease multimorbidity.

Identifying multimorbidity clusters with the highest primary care use: 15 years of evidence from a multi-ethnic metropolitan population

Background

People with multimorbidity have complex healthcare needs. Some co-occurring diseases interact with each other to a larger extent than others and may have a different impact on primary care use.

Aim

To assess the association between multimorbidity clusters and primary care consultations over time.

Design and setting

A retrospective longitudinal (panel) study design was used. Data comprised electronic primary care health records of 826 166 patients registered at GP practices in an ethnically diverse, urban setting in London between 2005 and 2020.

Method

Primary care consultation rates were modelled using generalised estimating equations. Key controls included the total number of long-term conditions, five multimorbidity clusters, and their interaction effects, ethnic group, and polypharmacy (proxy for disease severity). Models were also calibrated by consultation type and ethnic group.

Results

Individuals with multimorbidity used two to three times more primary care services than those without multimorbidity (incidence rate ratio 2.30, 95% confidence interval = 2.29 to 2.32). Patients in the alcohol dependence, substance dependence, and HIV cluster (Dependence+) had the highest rate of increase in primary care consultations as additional long-term conditions accumulated, followed by the mental health cluster (anxiety and depression). Differences by ethnic group were observed, with the largest impact in the chronic liver disease and viral hepatitis cluster for individuals of Black or Asian ethnicity.

Conclusion

This study identified multimorbidity clusters with the highest primary care demand over time as additional long-term conditions developed, differentiating by consultation type and ethnicity. Targeting clinical practice to prevent multimorbidity progression for these groups may lessen future pressures on primary care demand by improving health outcomes.

Family history of diabetes and risk of SARS-COV-2 in UK Biobank: A prospective cohort study

INTRODUCTION

The aim of this study was to determine risk of being SARS-CoV-2 positive and severe infection (associated with hospitalization/mortality) in those with family history of diabetes.

METHODS

We used UK Biobank, an observational cohort recruited between 2006 and 2010. We compared the risk of being SARS-CoV-2 positive and severe infection for those with family history of diabetes (mother/father/sibling) against those without.

RESULTS

Of 401,268 participants in total, 13,331 tested positive for SARS-CoV-2 and 2282 had severe infection by end of January 2021. In unadjusted models, participants with ≥2 family members with diabetes were more likely to be SARS-CoV-2 positive (risk ratio-RR 1.35; 95% confidence interval-CI 1.24-1.47) and severe infection (RR 1.30; 95% CI 1.04-1.59), compared to those without. The excess risk of being tested positive for SARS-CoV-2 was attenuated but significant after adjusting for demographics, lifestyle factors, multimorbidity and presence of cardiometabolic conditions. The excess risk for severe infection was no longer significant after adjusting for demographics, lifestyle factors, multimorbidity and presence of cardiometabolic conditions, and was absent when excluding incident diabetes.

CONCLUSION

The totality of the results suggests that good lifestyle and not developing incident diabetes may lessen risks of severe infections in people with a strong family of diabetes.

Associations between physical multimorbidity patterns and common mental health disorders in middle-aged adults: A prospective analysis using data from the UK Biobank

BACKGROUND

We aimed to identify specific patterns of physical multimorbidity, defined as the presence of two or more physical long-term conditions, and to examine the extent to which these specific patterns could predict future incident and persistent common mental health disorders (CMDs) in middle-aged adults enrolled in the UK Biobank.

METHODS

We assessed prospective associations between physical multimorbidity status at the baseline assessment (2006-2010) and depression and anxiety 'caseness' according to the Patient Health Questionnaire (PHQ)-9 and the Generalised Anxiety Disorder Assessment (GAD)-7 at the follow-up assessment (2016) in 154,367 middle-aged adults enrolled in the UK Biobank (median age: 57 years, interquartile range = 50-62 years, 56.5% female, mean duration of follow-up: 7.6 years, standard deviation = 0.87). Patterns of physical multimorbidity were identified using exploratory factor analysis. Logistic regression was used to assess prospective associations between physical multimorbidity patterns at baseline and both incident and persistent depression and anxiety at follow-up.

FINDINGS

Compared to those with no physical multimorbidity, having two (adjusted odds ratio (aOR) =1.41, 95%CI 1.32 to 1.53), three (aOR = 1.94, 95%CI 1.76 to 2.14), four (aOR = 2.38, 95%CI 2.07 to 2.74), and five or more (aOR = 2.89, 95%CI 2.42 to 3.45) physical conditions was prospectively associated with incident depression at follow-up in a dose response manner. Similar trends emerged for incident anxiety, persistent depression, and persistent anxiety, but associations were strongest for incident CMDs. Regarding specific patterns of physical MM, the respiratory pattern (aOR = 3.23, 95%CI 2.44 to 4.27) and the pain/gastrointestinal pattern (aOR = 2.19, 95%CI 1.92 to 2.50) emerged as the strongest predictors of incident depression. Similar results emerged for incident anxiety.

INTERPRETATION

These findings highlight patterns of physical multimorbidity with the poorest prognosis for both emerging and persisting depression and anxiety. These findings might have significant implications for the implementation of integrated mental and physical healthcare and facilitate the development of targeted preventative interventions and treatment for those with physical multimorbidity.

FUNDING

AR is supported by Guy's Charity grant number EIC180702; JAT is funded by Medical Research Council (MRC) number MR/SO28188/1; AD is funded by Guy's Charity grant number EIC180702 and MRC grant number MR/SO28188/1. JD is part supported by the ESRC Centre for Society and Mental Health at King's College London (ES/S012567/1), grants from the ESRC (ES/S002715/1), by the Health Foundation working together with the Academy of Medical Sciences, for a Clinician Scientist Fellowship, and by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London and the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust. The views expressed are those of the author[s] and not necessarily those of the ESRC, NIHR, the Department of Health and Social Care or King's College London.

Non-communicable disease, sociodemographic factors, and risk of death from infection: a UK Biobank observational cohort study

BACKGROUND

Non-communicable diseases (NCDs) have been highlighted as important risk factors for COVID-19 mortality. However, insufficient data exist on the wider context of infectious diseases in people with NCDs. We aimed to investigate the association between NCDs and the risk of death from any infection before the COVID-19 pandemic (up to Dec 31, 2019).

METHODS

For this observational study, we used data from the UK Biobank observational cohort study to explore factors associated with infection death. We excluded participants if data were missing for comorbidities, body-mass index, smoking status, ethnicity, and socioeconomic deprivation, and if they were lost to follow-up or withdrew consent. Deaths were censored up to Dec 31, 2019. We used Poisson regression models including NCDs present at recruitment to the UK Biobank (obesity [defined by use of body-mass index] and self-reported hypertension, chronic heart disease, chronic respiratory disease, diabetes, cancer, chronic liver disease, chronic kidney disease, previous stroke or transient ischaemic attack, other neurological disease, psychiatric disorder, and chronic inflammatory and autoimmune rheumatological disease), age, sex, ethnicity, smoking status, and socioeconomic deprivation. Separate models were constructed with individual NCDs replaced by the total number of prevalent NCDs to define associations with multimorbidity. All analyses were repeated with non-infection-related death as an alternate outcome measure to establish differential associations of infection death and non-infection death. Associations are reported as incidence rate ratios (IRR) accompanied by 95% CIs.

FINDINGS

After exclusion of 9210 (1·8%) of the 502 505 participants in the UK Biobank cohort, our study sample comprised 493 295 individuals. During 5 273 731 person-years of follow-up (median 10·9 years [IQR 10·1-11·6] per participant), 27 729 deaths occurred, of which 1385 (5%) were related to infection. Advancing age, male sex, smoking, socioeconomic deprivation, and all studied NCDs were independently associated with the rate of both infection death and non-infection death. Compared with White ethnicity, a pooled Black, Asian, and minority ethnicity group was associated with a reduced risk of infection death (IRR 0·64, 95% CI 0·46-0·87) and non-infection death (0·80, 0·75-0·86). Stronger associations with infection death than with non-infection death were observed for advancing age (age 65 years vs 45 years: 7·59, 95% CI 5·92-9·73, for infection death vs 5·21, 4·97-5·48, for non-infection death), current smoking (vs never smoking: 3·69, 3·19-4·26, vs 2·52, 2·44-2·61), socioeconomic deprivation (most vs least deprived quintile: 2·13, 1·78-2·56, vs 1·38, 1·33-1·43), class 3 obesity (vs non-obese: 2·21, 1·74-2·82, vs 1·55, 1·44-1·66), hypertension (1·36, 1·22-1·53, vs 1·15, 1·12-1·18), respiratory disease (2·21, 1·96-2·50, vs 1·28, 1·24-1·32), chronic kidney disease (5·04, 4·28-7·31, vs 2·50, 2·20-2·84), psychiatric disease (1·56, 1·30-1·86, vs 1·23, 1·18-1·29), and chronic inflammatory and autoimmune rheumatological disease (2·45, 1·99-3·02, vs 1·41, 1·32-1·51). Accrual of multimorbidity was also more strongly associated with risk of infection death (five or more comorbidities vs none: 9·53, 6·97-13·03) than of non-infection death (5·26, 4·84-5·72).

INTERPRETATION

Several NCDs are associated with an increased risk of infection death, suggesting that some of the reported associations with COVID-19 mortality might be non-specific. Only a subset of NCDs, together with the accrual of multimorbidity, advancing age, smoking, and socioeconomic deprivation, were associated with a greater IRR for infection death than for other causes of death. Further research is needed to define why these risk factors are more strongly associated with infection death, so that more effective preventive strategies can be targeted to high-risk groups.

FUNDING

British Heart Foundation.

A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank

BACKGROUND

Multimorbidities greatly increase the global health burdens, but the landscapes of their genetic risks have not been systematically investigated.

METHODS

We used the hospital inpatient data of 385,335 patients in the UK Biobank to investigate the multimorbid relations among 439 common diseases. Post-GWAS analyses were performed to identify multimorbidity shared genetic risks at the genomic loci, network, as well as overall genetic architecture levels. We conducted network decomposition for the networks of genetically interpretable multimorbidities to detect the hub diseases and the involved molecules and functions in each module.

RESULTS

In total, 11,285 multimorbidities among 439 common diseases were identified, and 46% of them were genetically interpretable at the loci, network, or overall genetic architecture levels. Multimorbidities affecting the same and different physiological systems displayed different patterns of the shared genetic components, with the former more likely to share loci-level genetic components while the latter more likely to share network-level genetic components. Moreover, both the loci- and network-level genetic components shared by multimorbidities converged on cell immunity, protein metabolism, and gene silencing. Furthermore, we found that the genetically interpretable multimorbidities tend to form network modules, mediated by hub diseases and featuring physiological categories. Finally, we showcased how hub diseases mediating the multimorbidity modules could help provide useful insights for the genetic contributors of multimorbidities.

CONCLUSIONS

Our results provide a systematic resource for understanding the genetic predispositions of multimorbidities and indicate that hub diseases and converged molecules and functions may be the key for treating multimorbidities. We have created an online database that facilitates researchers and physicians to browse, search, or download these multimorbidities ( https://multimorbidity.comp-sysbio.org ).