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

Association of Depression With the Progression of Multimorbidity in Older Adults: A Population-Based Cohort Study

BACKGROUND

The relationship between depression and the risk of multimorbidity progression has rarely been studied in older adults. This study was aimed to determine whether depression is associated with progression in the severity and complexity of multimorbidity, considering the influence of depression's severity and subtype.

METHODS

As a part of the Korean Longitudinal Study on Cognitive Aging and Dementia, this population-based cohort study followed a random sample of community-dwelling Koreans aged 60 and older for 8 years at 2-year intervals starting in 2010. Participants included those who completed mood and multimorbidity assessments and did not exhibit complex multimorbidity at the study's outset. Depression was assessed using the Geriatric Depression Scale, while multimorbidity was evaluated using the Cumulative Illness Rating Scale. The study quantified multimorbidity complexity by counting affected body systems and measured multimorbidity severity by averaging scores across 14 body systems.

FINDINGS

The 2,486 participants (age = 69.1 ± 6.5 years, 57.6% women) were followed for 5.9 ± 2.4 years. Linear mixed models revealed that participants with depression had a faster increase in multimorbidity complexity score (β = .065, SE = 0.019, p = 0.001) than those without depression, but a comparable increase in multimorbidity severity score (β = .001, SE = .009, p = 0.870) to those without depression. Cox proportional hazard models revealed that depression was associated with the risk of developing highly complex multimorbidity affecting five or more body systems, particularly in severe or anhedonic depression.

INTERPRETATION

Depression was associated with the worsening of multimorbidity in Korean older adults, particularly when severe or anhedonic. Early screening and management of depression may help to reduce the burden of multimorbidity in older adults.

Relationship between 2nd-generation angiotensin receptor blockers and the risk of hypotension in COVID-19 patients admitted to hospital

It has not yet been established whether angiotensin II receptor blockers (ARB), statins, and multiple drugs affect the severity of COVID-19. Therefore, we herein performed an observational study on the effects of 1st- and 2nd-generation ARB, statins, and multiple drugs, on COVID-19 in patients admitted to 15 Japanese medical facilities. The results obtained showed that ARB, statins, and multiple drugs were not associated with the primary outcome (odds ratio: 1.040, 95% confidence interval: 0.688-0.571; 0.696, 0.439-1.103; 1.056, 0.941-1.185, respectively), each component of the primary outcome (in-hospital death, ventilator support, extracorporeal membrane oxygenation support, and admission to the intensive care unit), or the secondary outcomes (oxygen administration, disturbed consciousness, and hypotension, defined as systolic blood pressure ≤90 mmHg). ARB were divided into 1st- and 2nd-generations based on their approval for use (before 2000 and after 2001), with the former consisting of losartan, candesartan, and valsartan, and the latter of telmisartan, olmesartan, irbesartan, and azilsartan. The difference of ARB generation was not associated with the primary outcome (odds ratio with 2nd-generation ARB relative to 1st-generation ARB: 1.257, 95% confidence interval: 0.613-2.574). The odd ratio for a hypotension as one of the secondary outcomes with 2nd-generation ARB was 1.754 (95% confidence interval: 1.745-1.763) relative to 1st-generation ARB. These results suggest that patients taking 2nd-generation ARB may be at a higher risk of hypotension than those taking 1st-generation ARB and also that careful observations are needed. Further studies are continuously needed to support decisions to adjust medications for co-morbidities.

When the Going Gets Tough: Multimorbidity and Heavy and Binge Drinking Among Adults

INTRODUCTION

Multimorbidity, the presence of two or more long-term health conditions in the same individual, is an emerging epidemic associated with increased morbidity and mortality. Continued drinking concurrent with alcohol-related chronic conditions, particularly with multimorbidity, is likely to further elevate health risk. This study aimed to examine the associations of multimorbidity among diabetes, hypertension, heart disease, and cancer with drinking, and moderation of these associations by age.

METHODS

Logistic regression modeling was performed in 2023 using a nationally representative sample of U.S. adults from the 2015-19 National Survey on Drug Use and Health. Multimorbidity was assessed using (1) a count of these conditions and (2) disease-specific categories. The outcomes were past month heavy drinking (7+/14+ drinks weekly) and binge drinking (4+/5+ drinks per occasion) for women and men.

RESULTS

A pattern of reduced odds for drinking outcomes associated with a greater degree of multimorbidity was found. This pattern was more apparent in models using the continuous measure of multimorbidity than in those using the categorical measure, and more consistent for binge drinking than for heavy drinking and for women than for men. Significant age interactions were found: the log odds of heavy drinking and binge drinking for both men and women decreased as the number of conditions increased, and more steeply for those ages 50+ than the younger. The log odds of heavy drinking varied little among men under age 50 regardless of multimorbidity.

CONCLUSIONS

Alcohol interventions to reduce drinking with multimorbidity, particularly among heavy-drinking men under age 50, are warranted.

Identifying multi-resolution clusters of diseases in ten million patients with multimorbidity in primary care in England

BACKGROUND

Identifying clusters of diseases may aid understanding of shared aetiology, management of co-morbidities, and the discovery of new disease associations. Our study aims to identify disease clusters using a large set of long-term conditions and comparing methods that use the co-occurrence of diseases versus methods that use the sequence of disease development in a person over time.

METHODS

We use electronic health records from over ten million people with multimorbidity registered to primary care in England. First, we extract data-driven representations of 212 diseases from patient records employing (i) co-occurrence-based methods and (ii) sequence-based natural language processing methods. Second, we apply the graph-based Markov Multiscale Community Detection (MMCD) to identify clusters based on disease similarity at multiple resolutions. We evaluate the representations and clusters using a clinically curated set of 253 known disease association pairs, and qualitatively assess the interpretability of the clusters.

RESULTS

Both co-occurrence and sequence-based algorithms generate interpretable disease representations, with the best performance from the skip-gram algorithm. MMCD outperforms k-means and hierarchical clustering in explaining known disease associations. We find that diseases display an almost-hierarchical structure across resolutions from closely to more loosely similar co-occurrence patterns and identify interpretable clusters corresponding to both established and novel patterns.

CONCLUSIONS

Our method provides a tool for clustering diseases at different levels of resolution from co-occurrence patterns in high-dimensional electronic health records, which could be used to facilitate discovery of associations between diseases in the future.

Correlation of cardiometabolic index and sarcopenia with cardiometabolic multimorbidity in middle-aged and older adult: a prospective study

Background

Research has demonstrated that sarcopenia and visceral obesity are significant risk factors for chronic disease in middle-aged and older adults. However, the relationship between sarcopenia, the cardiac metabolic index (CMI), a novel measure of visceral obesity, and cardiometabolic multimorbidity (CMM) remains unclear. In this study, data from the China Longitudinal Study of Health and Retirement (CHARLS) were analyzed to investigate the association between sarcopenia and CMI with CMM in the middle-aged and older adult population.

Methods

The study included 4,959 participants aged 45 and over. Sarcopenia was defined using the criteria of the Asian Sarcopenia Working Group 2019. CMM is defined as having two or more of the following conditions: physician-diagnosed heart disease, diabetes, stroke, and/or hypertension. CMI was calculated using the formula: CMI = (TG/HDL-C) × WHtR. To explore the association between CMI and sarcopenia and CMM, cox proportional risk regression models were used.

Results

The median age of all participants was 57 years, with 47.1% being male. Over the 8-year follow-up, 1,362 individuals developed CMM. The incidence of CMM was 8.7/1,000 person-years in the group without sarcopenia or high CMI, 17.37/1,000 person-years in those with high CMI, 14.22/1,000 person-years in the sarcopenia group, and 22.34/1,000 person-years in the group with both conditions. After adjusting for covariates, the group with both sarcopenia and high CMI had a significantly increased risk of CMM (HR 2.48, 95% CI 1.12-5.51) and heart disease (HR 2.04, 95% CI 1.05-3.98). Among those over 65 years, sarcopenia was discovered to be associated with an increased risk of CMM [HR (95% CI: 4.83 (1.22, 19.06)]. The risk of CMM was further increased to 7.31-fold (95% CI:1.72, 31.15) when combined with high CMI.

Conclusions

The combination of sarcopenia and high CMI is associated with an increased risk of developing CMM. Early identification and intervention of sarcopenia and CMI not only enable the development of targeted therapeutic strategies but also provide potential opportunities to reduce the morbidity and mortality of CMM.

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province

Objectives

The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases.

Methods

This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30-79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities.

Results

The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20-1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19-3.19) and 28.19 (95% CI = 14.85-53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22-15.31).

Conclusion

The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions.

Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (PERFORM): protocol for a randomised feasibility trial

INTRODUCTION

Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (PERFORM) is a research programme that seeks to develop and evaluate a comprehensive exercise-based rehabilitation intervention designed for people with multimorbidity, the presence of multiple long-term conditions (MLTCs). This paper describes the protocol for a randomised trial to assess the feasibility and acceptability of the PERFORM intervention, study design and processes.

METHODS AND ANALYSIS

A multicentre, parallel two-group randomised trial with individual 2:1 allocation to the PERFORM exercise-based intervention plus usual care (intervention) or usual care alone (control). The primary outcome of this feasibility trial will be to assess whether prespecified progression criteria (recruitment, retention, intervention adherence) are met to progress to the full randomised trial. The trial will be conducted across three UK sites and 60 people with MLTCs, defined as two or more LTCs, with at least one having evidence of the beneficial effect of exercise. The PERFORM intervention comprises an 8-week (twice a week for 6 weeks and once a week for 2 weeks) supervised rehabilitation programme of personalised exercise training and self-management education delivered by trained healthcare professionals followed by two maintenance sessions. Trial participants will be recruited over a 4.5-month period, and outcomes assessed at baseline (prerandomisation) and 3 months postrandomisation and include health-related quality of life, psychological well-being, symptom burden, frailty, exercise capacity, physical activity, sleep, cognition and serious adverse events. A mixed-methods process evaluation will assess acceptability, feasibility and fidelity of intervention delivery and feasibility of trial processes. An economic evaluation will assess the feasibility of data collection and estimate the costs of the PERFORM intervention.

ETHICS AND DISSEMINATION

The trial has been given favourable opinion by the West Midlands, Edgbaston Research Ethics Service (Ref: 23/WM/0057). Participants will be asked to give full, written consent to take part by trained researchers. Findings will be disseminated via journals, presentations and targeted communications to clinicians, commissioners, service users and patients and the public.

TRIAL REGISTRATION NUMBER

ISRCTN68786622.

PROTOCOL VERSION

2.0 (16 May 2023).

Ethnic differences in multimorbidity after accounting for social-economic factors, findings from The Health Survey for England

BACKGROUND

Social-economic factors and health behaviours may be driving variation in ethnic health inequalities in multimorbidity including among distinct ethnic groups.

METHODS

Using the cross-sectional nationally representative Health Surveys for England 2011-18 (N = 54 438, aged 16+), we performed multivariable logistic regression on the odds of having general multimorbidity (≥2 longstanding conditions) by ethnicity [British White (reference group), White Irish, Other White, Indian, Pakistani, Bangladeshi, Chinese, African, Caribbean, White mixed, Other Mixed], adjusting for age, sex, education, area deprivation, obesity, smoking status and survey year. This was repeated for cardiovascular multimorbidity (N = 37 148, aged 40+: having ≥2 of the following: self-reported diabetes, hypertension, heart attack or stroke) and multiple cardiometabolic risk biomarkers (HbA1c ≥6.5%, raised blood pressure, total cholesterol ≥5mmol/L).

RESULTS

Twenty percent of adults had general multimorbidity. In fully adjusted models, compared with the White British majority, Other White [odds ratio (OR) = 0.63; 95% confidence interval (CI) 0.53-0.74], Chinese (OR = 0.58, 95% CI 0.36-0.93) and African adults (OR = 0.54, 95% CI 0.42-0.69), had lower odds of general multimorbidity. Among adults aged 40+, Pakistani (OR = 1.27, 95% CI 0.97-1.66; P = 0.080) and Bangladeshi (OR = 1.75, 95% CI 1.16-2.65) had increased odds, and African adults had decreased odds (OR = 0.63, 95% CI 0.47-0.83) of general multimorbidity. Risk of cardiovascular multimorbidity was higher among Indian (OR = 3.31, 95% CI 2.56-4.28), Pakistani (OR = 3.48, 95% CI 2.52-4.80), Bangladeshi (OR = 3.67, 95% CI 1.98-6.78), African (OR = 1.61, 95% CI 1.05-2.47), Caribbean (OR = 2.18, 95% CI 1.59-2.99) and White mixed (OR = 1.98, 95% CI 1.14-3.44) adults. Indian adults were also at risk of having multiple cardiometabolic risk biomarkers.

CONCLUSION

Ethnic inequalities in multimorbidity are independent of social-economic factors. Ethnic minority groups are particularly at risk of cardiovascular multimorbidity, which may be exacerbated by poorer management of cardiometabolic risk requiring further investigation.

Multimorbidity and 11-year mortality in adults: a prospective analysis using the Chilean National Health Survey

Research on morbidity and mortality often emphasizes individual diseases over the cumulative effects of multimorbidity, especially in low- and middle-income countries. This study aimed to analyze the association between multimorbidity and all-cause mortality in a representative sample of the Chilean population. This longitudinal study used data from 3701 subjects aged ≥15 years who participated in the Chilean National Health Survey conducted between 2009 and 2010. We included 16 self-reported highly prevalent morbidities. All-cause mortality data from an 11-year follow-up were collected from the Chilean Civil Registry. The Cox proportional hazard model, adjusted for confounders, determined the association between multimorbidity categories and all-cause mortality. Of the total sample, 24.3% reported no morbidity, while 50.4% two or more. After adjustment, participants with four or more morbidities had a 1.66 times higher mortality risk [95% confidence interval (CI): 1.03-2.67] than those without morbidities. The mortality risk increased by 10% for each additional morbidity [HR: 1.09 (CI: 1.04-1.16)]. Multimorbidity was common in the Chilean population and increased the mortality risk, which greatly challenges the health system to provide an integral and coordinated approach to healthcare.

Personalised lung cancer risk stratification and lung cancer screening: do general practice electronic medical records have a role?

BACKGROUND

In the United Kingdom (UK), cancer screening invitations are based on general practice (GP) registrations. We hypothesize that GP electronic medical records (EMR) can be utilised to calculate a lung cancer risk score with good accuracy/clinical utility.

METHODS

The development cohort was Secure Anonymised Information Linkage-SAIL (2.3 million GP EMR) and the validation cohort was UK Biobank-UKB (N = 211,597 with GP-EMR availability). Fast backward method was applied for variable selection and area under the curve (AUC) evaluated discrimination.

RESULTS

Age 55-75 were included (SAIL: N = 574,196; UKB: N = 137,918). Six-year lung cancer incidence was 1.1% (6430) in SAIL and 0.48% (656) in UKB. The final model included 17/56 variables in SAIL for the EMR-derived score: age, sex, socioeconomic status, smoking status, family history, body mass index (BMI), BMI:smoking interaction, alcohol misuse, chronic obstructive pulmonary disease, coronary heart disease, dementia, hypertension, painful condition, stroke, peripheral vascular disease and history of previous cancer and previous pneumonia. The GP-EMR-derived score had AUC of 80.4% in SAIL and 74.4% in UKB and outperformed ever-smoked criteria (currently the first step in UK lung cancer screening pilots).

DISCUSSION

A GP-EMR-derived score may have a role in UK lung cancer screening by accurately targeting high-risk individuals without requiring patient contact.

Social connection and mortality in UK Biobank: a prospective cohort analysis

BACKGROUND

Components of social connection are associated with mortality, but research examining their independent and combined effects in the same dataset is lacking. This study aimed to examine the independent and combined associations between functional and structural components of social connection and mortality.

METHODS

Analysis of 458,146 participants with full data from the UK Biobank cohort linked to mortality registers. Social connection was assessed using two functional (frequency of ability to confide in someone close and often feeling lonely) and three structural (frequency of friends/family visits, weekly group activities, and living alone) component measures. Cox proportional hazard models were used to examine the associations with all-cause and cardiovascular disease (CVD) mortality.

RESULTS

Over a median of 12.6 years (IQR 11.9-13.3) follow-up, 33,135 (7.2%) participants died, including 5112 (1.1%) CVD deaths. All social connection measures were independently associated with both outcomes. Friends/family visit frequencies < monthly were associated with a higher risk of mortality indicating a threshold effect. There were interactions between living alone and friends/family visits and between living alone and weekly group activity. For example, compared with daily friends/family visits-not living alone, there was higher all-cause mortality for daily visits-living alone (HR 1.19 [95% CI 1.12-1.26]), for never having visits-not living alone (1.33 [1.22-1.46]), and for never having visits-living alone (1.77 [1.61-1.95]). Never having friends/family visits whilst living alone potentially counteracted benefits from other components as mortality risks were highest for those reporting both never having visits and living alone regardless of weekly group activity or functional components. When all measures were combined into overall functional and structural components, there was an interaction between components: compared with participants defined as not isolated by both components, those considered isolated by both components had higher CVD mortality (HR 1.63 [1.51-1.76]) than each component alone (functional isolation 1.17 [1.06-1.29]; structural isolation 1.27 [1.18-1.36]).

CONCLUSIONS

This work suggests (1) a potential threshold effect for friends/family visits, (2) that those who live alone with additional concurrent markers of structural isolation may represent a high-risk population, (3) that beneficial associations for some types of social connection might not be felt when other types of social connection are absent, and (4) considering both functional and structural components of social connection may help to identify the most isolated in society.

Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort

BACKGROUND

People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare.

AIMS

To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk.

METHOD

Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological).

RESULTS

People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors.

CONCLUSIONS

People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.

Childhood adversity and COVID-19 outcomes in the UK Biobank

OBJECTIVES

This study aims to investigate the association between childhood adversity and COVID-19-related hospitalisation and COVID-19-related mortality in the UK Biobank.

DESIGN

Cohort study.

SETTING

UK.

PARTICIPANTS

151 200 participants in the UK Biobank cohort who had completed the Childhood Trauma Screen were alive at the start of the COVID-19 pandemic (January 2020) and were still active in the UK Biobank when hospitalisation and mortality data were most recently updated (November 2021).

MAIN OUTCOME MEASURES

COVID-19-related hospitalisation and COVID-19-related mortality.

RESULTS

Higher self-reports of childhood adversity were related to greater likelihood of COVID-19-related hospitalisation in all statistical models. In models adjusted for age, ethnicity and sex, childhood adversity was associated with an odds ratio (OR) of 1.227 of hospitalisation (95% CI 1.153 to 1.306, childhood adversity z=6.49, p<0.005) and an OR of 1.25 of a COVID-19-related death (95% CI 1.11 to 1.424, childhood adversity z=3.5, p<0.005). Adjustment for potential confounds attenuated these associations, although associations remained statistically significant.

CONCLUSIONS

Childhood adversity was significantly associated with COVID-19-related hospitalisation and COVID-19-related mortality after adjusting for sociodemographic and health confounders. Further research is needed to clarify the biological and psychosocial processes underlying these associations to inform public health intervention and prevention strategies to minimise COVID-19 disparities.

The Impact of Multimorbidity on All-Cause Mortality: A Longitudinal Study of 87,151 Thai Adults

Objectives: To investigate associations between multimorbidity, socio-demographic and health behaviour factors, and their interactions (multimorbidity and these factors) with all-cause mortality among Thai adults. Methods: Associations between multimorbidity (coexistence of two + chronic diseases) and mortality between 2005 and 2019 were investigated among Thai Cohort Study (TCS) participants (n = 87,151). Kaplan-Meier survival curves estimated and compared survival times. Multivariate Cox proportional hazards models examined associations between risk factors, and interactions between multimorbidity, these factors, and survival. Results: 1,958 cohort members died between 2005 and 2019. The risk of death was 43% higher for multimorbid people. In multivariate Cox proportional hazard models, multimorbidity/number of chronic conditions, age, long sleep duration, smoking and drinking were all independent factors that increased mortality risk. Women, urbanizers, university education, over 20,000-baht personal monthly income and soybean products consumption lowered risk. The interactions between multimorbidity and these variables (except for female, urbanizers and soybeans intake) also had significant (p < 0.05) impact on all-cause mortality. Conclusion: The results emphasise the importance of healthy lifestyle and reduced intake of alcohol and tobacco, in reducing premature mortality, especially when suffering from multimorbidity.

Cardiometabolic risk in people under 40 years with severe mental illness: reading between the guidelines

People with severe mental illness (SMI) have a shorter life expectancy than the rest of the population. Multimorbidity and poorer physical health contribute to this health inequality. Cardiometabolic multimorbidity confers a significant mortality risk in this population. Multimorbidity is not restricted to older people and people with SMI present with multimorbidity earlier in life. Despite this, most screening, prevention and treatment strategies target older people. People under 40 years with SMI are underserved by current guidelines for cardiovascular risk assessment and reduction. Research is needed to develop and implement interventions to reduce cardiometabolic risk in this population.

Association of ultra-processed food consumption with incident depression and anxiety: a population-based cohort study

Background: Global ultra-processed food (UPF) consumption has risen rapidly. The development and prognosis of depression and anxiety remain unclarified. Herein, we aimed to examine the association between UPF consumption and the incidence and progression trajectory of depression and anxiety. Methods: In our study, participants were recruited between 2006 and 2010. UPF consumption was expressed as UPF servings, energy ratio, and weight ratio. The relationships between UPF consumption and depression or anxiety were assessed using the Cox proportional hazards model. Multi-state models were used to explore the association between UPF consumption and the risks of all transitions from a healthy state to depression or anxiety and then to all-cause mortality. Results: Among the 183 474 participants, 5453 were diagnosed with depression and 6763 with anxiety during the follow-up of 13.1 years. The participants in the highest quartile (Q4) of UPF servings, energy ratio, and weight ratio had an increased risk of depression compared to those in the lowest quartile (Q1), with hazard ratios (HRs) and 95% confidence intervals [CIs] of 1.22 (1.13-1.31), 1.13 (1.05-1.22), and 1.26 (1.17-1.36), respectively. Similarly, participants in Q4 of UPF consumption had a higher risk of anxiety, with HRs (95% CIs) of 1.13 (1.06-1.21), 1.13 (1.05-1.21), and 1.11 (1.04-1.19), compared to those in Q1. The study also found a significant association between UPF consumption and all-cause mortality, which disappeared for participants with depression or anxiety. Conclusions: Our findings revealed that UPF consumption is associated with depression or anxiety.

Global perspectives on heart disease rehabilitation and secondary prevention: a scientific statement from the Association of Cardiovascular Nursing and Allied Professions, European Association of Preventive Cardiology, and International Council of Cardiovascular Prevention and Rehabilitation

Cardiovascular disease is a leading cause of death, morbidity, disability, and reduced health-related quality of life, as well as economic burden worldwide, with some 80% of disease burden occurring in the low- and middle-income country (LMIC) settings. With increasing numbers of people living longer with symptomatic disease, the effectiveness and accessibility of secondary preventative and rehabilitative health services have never been more important. Whilst LMICs experience the highest prevalence and mortality rates, the global approach to secondary prevention and cardiac rehabilitation, which mitigates this burden, has traditionally been driven from clinical guidelines emanating from high-income settings. This state-of-the art review provides a contemporary global perspective on cardiac rehabilitation and secondary prevention, contrasting the challenges of and opportunities for high vs. lower income settings. Actionable solutions to overcome system, clinician, programme, and patient level barriers to cardiac rehabilitation access in LMICs are provided.

Effects of multimorbidity coexistence on the risk of mortality in the older adult population in China

Background

Multimorbidity coexistence is a serious public health issue affecting a significant number of older adults worldwide. However, associations between multimorbidity and mortality are rarely studied in China. We assessed the effects of multimorbidity coexistence on mortality among a nationwide sample of older adults from China.

Objective

We analyzed 10-year (2008-2018) longitudinal data of 12,337 individuals who took part in China, a nationwide survey of people aged 65 years and above. We used the Cox proportional hazard model to determine the effects of multimorbidity on the all-cause mortality risk. We also examined mortality risk between sex and age obtained through differential analysis.

Results

At baseline, 30.2, 29.9, and 39.9% of participants had 0, 1, and 2 or more diseases, respectively. The cumulative follow-up of this study was 27,428 person-years (median follow-up = 2.7 years; range, 0.01-11.3 years), with 8297 deaths. The HRs (95% CIs) for all-cause mortality in participants with 1, and 2 or more conditions compared with those with none were 1.04 (0.98, 1.10) and 1.12 (1.06, 1.18), respectively. The heterogeneity analysis indicated that, the mortality risk for 80-94 years and 95-104 years group with multimorbidity coexistence is 1.12 (1.05-1.21) and 1.11 (1.01-1.23), respectively, but the mortality risk for 65-79 years group with multimorbidity coexistence was not statistically significant. The heterogeneity analysis indicated that, the mortality risk for men and women in older adults with multimorbidity coexistence is 1.15 (1.06, 1.25) and 1.08 (1.01, 1.17), respectively.

Conclusion

Multimorbidity coexistence is associated with an increase in an increased risk of death in older individuals, with the effect being relatively significant in those aged 80-94 years.

Identifying the potential causal role of insomnia symptoms on 11,409 health-related outcomes: a phenome-wide Mendelian randomisation analysis in UK Biobank

BACKGROUND

Insomnia symptoms are widespread in the population and might have effects on many chronic conditions and their risk factors but previous research has focused on select hypothesised associations/effects rather than taking a systematic hypothesis-free approach across many health outcomes.

METHODS

We performed a Mendelian randomisation (MR) phenome-wide association study (PheWAS) in 336,975 unrelated white-British UK Biobank participants. Self-reported insomnia symptoms were instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). A total of 11,409 outcomes from UK Biobank were extracted and processed by an automated pipeline (PHESANT) for the MR-PheWAS. Potential causal effects (those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible.

RESULTS

Four hundred thirty-seven potential causal effects of insomnia symptoms were observed for a diverse range of outcomes, including anxiety, depression, pain, body composition, respiratory, musculoskeletal and cardiovascular traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across main and sensitivity analyses) for 30 of these. These included novel findings (by which we mean not extensively explored in conventional observational studies and not previously explored using MR based on a systematic search) of an adverse effect on risk of spondylosis (OR [95%CI] = 1.55 [1.33, 1.81]) and bronchitis (OR [95%CI] = 1.12 [1.03, 1.22]), among others.

CONCLUSIONS

Insomnia symptoms potentially cause a wide range of adverse health-related outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

Association between multimorbidity patterns and incident depression among older adults in Taiwan: the role of social participation

Background

Previous research has found different multimorbidity patterns that negatively affects health outcomes of older adults. However, there is scarce evidence, especially on the role of social participation in the association between multimorbidity patterns and depression. Our study aimed to explore the relationship between multimorbidity patterns and depression among older adults in Taiwan, including the social participation effect on the different multimorbidity patterns.

Methods

Data were retracted from the Taiwan longitudinal study on ageing (TLSA) for this population-based cohort study. 1,975 older adults (age > 50) were included and were followed up from 1996 to 2011. We used latent class analysis to determine participants’ multimorbidity patterns in 1996, whereas their incident depression was determined in 2011 by CES-D. Multivariable logistic regression was used to analyse the relationship between multimorbidity patterns and depression.

Results

The participants’ average age was 62.1 years in 1996. Four multimorbidity patterns were discovered through latent class analysis, as follows: (1) Cardiometabolic group (n = 93), (2) Arthritis-cataract group (n = 105), (3) Multimorbidity group (n = 128) and (4) Relatively healthy group (n = 1649). Greater risk of incident depression was found among participants in the Multimorbidity group (OR: 1.62; 95% CI: 1.02–2.58) than the Relatively healthy group after the multivariable analysis. Compare to participants in the relatively healthy group with social participation, participants in the arthritis-cataract group without social participation (OR: 2.22, 95% CI: 1.03–4.78) and the multimorbidity group without social participation (OR: 2.21, 95% CI: 1.14–4.30) had significantly increased risk of having depression.

Conclusion

Distinct multimorbidity patterns among older adults in Taiwan are linked with the incident depression during later life, and social participation functioned as a protective factor.

Socioeconomic gradient in mortality of working age and older adults with multiple long-term conditions in England and Ontario, Canada

BACKGROUND

There is currently mixed evidence on the influence of long-term conditions and deprivation on mortality. We aimed to explore whether number of long-term conditions contribute to socioeconomic inequalities in mortality, whether the influence of number of conditions on mortality is consistent across socioeconomic groups and whether these associations vary by working age (18-64 years) and older adults (65 + years). We provide a cross-jurisdiction comparison between England and Ontario, by replicating the analysis using comparable representative datasets.

METHODS

Participants were randomly selected from Clinical Practice Research Datalink in England and health administrative data in Ontario. They were followed from 1 January 2015 to 31 December 2019 or death or deregistration. Number of conditions was counted at baseline. Deprivation was measured according to the participant's area of residence. Cox regression models were used to estimate hazards of mortality by number of conditions, deprivation and their interaction, with adjustment for age and sex and stratified between working age and older adults in England (N = 599,487) and Ontario (N = 594,546).

FINDINGS

There is a deprivation gradient in mortality between those living in the most deprived areas compared to the least deprived areas in England and Ontario. Number of conditions at baseline was associated with increasing mortality. The association was stronger in working age compared with older adults respectively in England (HR = 1.60, 95% CI 1.56,1.64 and HR = 1.26, 95% CI 1.25,1.27) and Ontario (HR = 1.69, 95% CI 1.66,1.72 and HR = 1.39, 95% CI 1.38,1.40). Number of conditions moderated the socioeconomic gradient in mortality: a shallower gradient was seen for persons with more long-term conditions.

CONCLUSIONS

Number of conditions contributes to higher mortality rate and socioeconomic inequalities in mortality in England and Ontario. Current health care systems are fragmented and do not compensate for socioeconomic disadvantages, contributing to poor outcomes particularly for those managing multiple long-term conditions. Further work should identify how health systems can better support patients and clinicians who are working to prevent the development and improve the management of multiple long-term conditions, especially for individuals living in socioeconomically deprived areas.

Multimorbidity in People with Epilepsy

Multimorbidity is an emerging priority in healthcare due to associations with the ageing population, frailty, polypharmacy, health and social care demands. It affects 60-70% of adults and 80% of children with epilepsy. Neurodevelopmental conditions are commonly seen in children with epilepsy, while cancer, cardiovascular and neurodegenerative conditions often afflict older people with epilepsy. Mental health problems are common across the lifespan. Genetic, environmental, social and lifestyle factors contribute to multimorbidity and its consequences. Multimorbid people with epilepsy (PWE) are at higher risk of depression and suicide, premature death, suffer lower health-related quality of life, and require more hospital admissions and health care costs. The best management of multimorbid PWE requires a paradigm shift from the traditional single disease-single comorbidity approach and a refocus on a person-centred approach. Improvements in health care must be informed by assessing the burden of multimorbidity associated with epilepsy, delineating disease clusters, and measuring the effects on health outcomes.

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.

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.

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.

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.

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.