Inequalities in developing multimorbidity over time: A population-based cohort study from an urban, multi-ethnic borough in the United Kingdom

Racial inequalities in the development of multimorbidity of chronic conditions: results from a Brazilian prospective cohort

BACKGROUND

The occurrence of multimorbidity and its impacts have differentially affected population subgroups. Evidence on its incidence has mainly come from high-income regions, with limited exploration of racial disparities. This study investigated the association between racial groups and the development of multimorbidity and chronic conditions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

METHODS

Data from self-reported white, brown (pardos or mixed-race), and black participants at baseline of ELSA-Brasil (2008-2010) who were at risk for multimorbidity were analysed. The development of chronic conditions was assessed through in-person visits and self-reported diagnosis via telephone until the third follow-up visit (2017-2019). Multimorbidity was defined when, at the follow-up visit, the participant had two or more morbidities. Cumulative incidences, incidence rates, and adjusted incidence rate ratios (IRRs) were estimated using Poisson models.

RESULTS

Over an 8.3-year follow-up, compared to white participants: browns had a 27% greater incidence of hypertension and obesity; and blacks had a 62% and 45% greater incidence, respectively. Blacks also had 58% more diabetes. The cancer incidence was greater among whites. Multimorbidity affected 41% of the participants, with a crude incidence rate of 57.5 cases per 1000 person-years (ranging from 56.3 for whites to 63.9 for blacks). Adjusted estimates showed a 20% higher incidence of multimorbidity in black participants compared to white participants (IRR: 1.20; 95% CI: 1.05-1.38).

CONCLUSIONS

Significant racial disparities in the risk of chronic conditions and multimorbidity were observed. Many associations revealed a gradient increase in illness risk according to darker skin tones. Addressing fundamental causes such as racism and racial discrimination, alongside considering social determinants of health, is vital for comprehensive multimorbidity care. Intersectoral, equitable policies are essential for ensuring health rights for historically marginalized groups.

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.

Associations between social determinants of health and comorbidity and multimorbidity in people of black ethnicities with HIV

OBJECTIVE

Social determinants of health (SDH) are important determinants of long-term conditions and multimorbidity in the general population. The intersecting relationship between SDH and multimorbidity in people with HIV remains poorly studied.

DESIGN

A cross-sectional study investigating the relationships between eight socio-economic parameters and prevalent comorbidities of clinical significance and multimorbidity in adults of African ancestry with HIV aged 18-65 years in South London, UK.

METHODS

Multivariable logistic regression analysis was used to evaluate associations between SDH and comorbidities and multimorbidity.

RESULTS

Between September 2020 and January 2022, 398 participants (median age 52 years, 55% women) were enrolled; 85% reported at least one SDH and 72% had at least one comorbidity. There were no associations between SDH and diabetes mellitus or kidney disease, few associations between SDH (job and food insecurity) and cardiovascular or lung disease, and multiple associations between SDH (financial, food, housing and job insecurity, low educational level, social isolation, and discrimination) and poor mental health or chronic pain. Associations between SDH and multimorbidity mirrored those for constituent comorbidities.

CONCLUSION

We demonstrate strong associations between SDH and poor mental health, chronic pain and multimorbidity in people of black ethnicities living with HIV in the UK. These findings highlight the likely impact of enduring socioeconomic hardship in these communities and underlines the importance of holistic health and social care for people with HIV to address these adverse psychosocial conditions.

Prevalence of multiple long-term conditions (multimorbidity) in England: a whole population study of over 60 million people

OBJECTIVES

To determine the prevalence of multiple long-term conditions (MLTC) at whole English population level, stratifying by age, sex, socioeconomic status and ethnicity.

DESIGN

A whole population study.

SETTING

Individuals registered with a general practice in England and alive on 31 March 2020.

PARTICIPANTS

60,004,883 individuals.

MAIN OUTCOME MEASURES

MLTC prevalence, defined as two or more of 35 conditions derived from a number of national patient-level datasets. Multivariable logistic regression was used to assess the independent associations of age, sex, ethnicity and deprivation decile with odds of MLTC.

RESULTS

The overall prevalence of MLTC was 14.8% (8,878,231), varying from 0.9% (125,159) in those aged 0-19 years to 68.2% (1,905,979) in those aged 80 years and over. In multivariable regression analyses, compared with the 50-59 reference group, the odds ratio was 0.04 (95% confidence interval (CI): 0.04-0.04; p < 0.001) for those aged 0-19 years and 10.21 (10.18-10.24; p < 0.001) for those aged 80 years and over. Odds were higher for men compared with women, 1.02 (1.02-1.02; p < 0.001), for the most deprived decile compared with the least deprived, 2.26 (2.25-2.27; p < 0.001), and for Asian ethnicity compared with those of white ethnicity, 1.05 (1.04-1.05; p < 0.001). Odds were lower for black, mixed and other ethnicities (0.94 (0.94-0.95) p < 0.001, 0.87 (0.87-0.88) p < 0.001 and 0.57 (0.56-0.57) p < 0.001, respectively). MLTC for persons aged 0-19 years were dominated by asthma, autism and epilepsy, for persons aged 20-49 years by depression and asthma, for persons aged 50-59 years by hypertension and depression and for those aged 60 years and older, by cardiometabolic factors and osteoarthritis. There were large numbers of combinations of conditions in each age group ranging from 5936 in those aged 0-19 years to 205,534 in those aged 80 years and over.

CONCLUSIONS

While this study provides useful insight into the burden across the English population to assist health service delivery planning, the heterogeneity of MLTC presents challenges for delivery optimisation.

Effect of timeframes to define long term conditions and sociodemographic factors on prevalence of multimorbidity using disease code frequency in primary care electronic health records: retrospective study

Objective

To determine the extent to which the choice of timeframe used to define a long term condition affects the prevalence of multimorbidity and whether this varies with sociodemographic factors.

Design

Retrospective study of disease code frequency in primary care electronic health records.

Data sources

Routinely collected, general practice, electronic health record data from the Clinical Practice Research Datalink Aurum were used.

Main outcome measures

Adults (≥18 years) in England who were registered in the database on 1 January 2020 were included. Multimorbidity was defined as the presence of two or more conditions from a set of 212 long term conditions. Multimorbidity prevalence was compared using five definitions. Any disease code recorded in the electronic health records for 212 conditions was used as the reference definition. Additionally, alternative definitions for 41 conditions requiring multiple codes (where a single disease code could indicate an acute condition) or a single code for the remaining 171 conditions were as follows: two codes at least three months apart; two codes at least 12 months apart; three codes within any 12 month period; and any code in the past 12 months. Mixed effects regression was used to calculate the expected change in multimorbidity status and number of long term conditions according to each definition and associations with patient age, gender, ethnic group, and socioeconomic deprivation.

Results

9 718 573 people were included in the study, of whom 7 183 662 (73.9%) met the definition of multimorbidity where a single code was sufficient to define a long term condition. Variation was substantial in the prevalence according to timeframe used, ranging from 41.4% (n=4 023 023) for three codes in any 12 month period, to 55.2% (n=5 366 285) for two codes at least three months apart. Younger people (eg, 50-75% probability for 18-29 years v 1-10% for ≥80 years), people of some minority ethnic groups (eg, people in the Other ethnic group had higher probability than the South Asian ethnic group), and people living in areas of lower socioeconomic deprivation were more likely to be re-classified as not multimorbid when using definitions requiring multiple codes.

Conclusions

Choice of timeframe to define long term conditions has a substantial effect on the prevalence of multimorbidity in this nationally representative sample. Different timeframes affect prevalence for some people more than others, highlighting the need to consider the impact of bias in the choice of method when defining multimorbidity.

Association between dental visit behavior and mortality: a nationwide longitudinal cohort study from NHANES

OBJECTIVES

The benefits of professional dental treatment for oral diseases have been widely investigated. However, it is unclear whether professional dental treatment provides additional benefits for improving general health.

MATERIALS AND METHODS

Data were obtained from the US National Health and Nutrition Examination Survey (NHANES) 1999 to 2004 and 2011 to 2018 cycles. A total of 36,174 participants were included and followed-up for mortality until December 31, 2019. Dental visit behavior was defined as the time interval of last dental visit (TIDV, < 0.5 year, 0.5-1 year, 1-2 years, 2-5 years, and > 5 years) and the main reasons of the last dental visit (treatment, examination, and other reasons). The Cox proportional risk model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

Compared with participants with time interval of less than 0.5 year, the multivariate-adjusted HRs and 95%CI for participants with time interval of more than 5 years were 1.45 (1.31, 1.61) for all-cause mortality (P trend < 0.0001), 1.49 (1.23, 1.80) for cardiovascular diseases mortality (P trend = 0.0009) and 1.53 (1.29, 1.81) for cancer mortality (P trend = 0.013). Compared with dental visit for examination, participants who had their dental visit for treatment had higher risk for mortality. For participants with dental visit for examination, TIDV of less than 1 year showed lower risk for mortality, whereas TIDV of less than 0.5 year is recommend for population with dental visit for treatment.

CONCLUSIONS

Poor dental visit behavior is associated with an increased risk of mortality. Further well-designed studies are needed to confirm the association between professional dental visit and mortality.

CLINICAL RELEVANCE

This study highlights the potential benefits of regular dental visits in maintaining general health.

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England

BACKGROUND

Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions.

METHODS AND FINDINGS

We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results.

CONCLUSIONS

Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

Identifying populations with chronic pain in primary care: developing an algorithm and logic rules applied to coded primary care diagnostic and medication data

BACKGROUND

Estimates of chronic pain prevalence using coded primary care data are likely to be substantially lower than estimates derived from community surveys. Most primary care studies have estimated chronic pain prevalence using data searches confined to analgesic medication prescriptions. Increasingly, following recent NICE guideline recommendations, patients and doctors opt for non-drug treatment of chronic pain thus excluding these patients from prevalence estimates based on medication codes. We aimed to develop and test an algorithm combining medication codes with selected diagnostic codes to estimate chronic pain prevalence using coded primary care data.

METHODS

Following a scoping review 4 criteria were developed to identify cohorts of people with chronic pain. These were (1) people with one of 12 ('tier 1') conditions that almost always results in the individual having chronic pain (2) people with one of 20 ('tier 2') conditions included when there are also 3 or more prescription-only analgesics issued in the last 12 months (3) chronic neuropathic pain, or (4) 4 or more prescription-only analgesics issued in the last 12 months. These were translated into 8 logic rules which included 1,932 SNOMED CT codes.

RESULTS

The algorithm was run on primary care data from 41 GP Practices in Lambeth. The total population consisted of 386,238 GP registered adults ≥ 18 years as of the 31st March 2021. 64,135 (16.6%) were identified as people with chronic pain. This definition demonstrated notably high rates in Black ethnicity females, and higher rates in the most deprived, and older population.

CONCLUSIONS

Estimates of chronic pain prevalence using structured healthcare data have previously shown lower prevalence estimates for chronic pain than reported in community surveys. This has limited the ability of researchers and clinicians to fully understand and address the complex multifactorial nature of chronic pain. Our study demonstrates that it may be possible to establish more representative prevalence estimates using structured data than previously possible. Use of logic rules offers the potential to move systematic identification and population-based management of chronic pain into mainstream clinical practice at scale and support improved management of symptom burden for people experiencing chronic pain.

Trajectories in chronic disease accrual and mortality across the lifespan in Wales, UK (2005-2019), by area deprivation profile: linked electronic health records cohort study on 965,905 individuals

Background

Understanding and quantifying the differences in disease development in different socioeconomic groups of people across the lifespan is important for planning healthcare and preventive services. The study aimed to measure chronic disease accrual, and examine the differences in time to individual morbidities, multimorbidity, and mortality between socioeconomic groups in Wales, UK.

Methods

Population-wide electronic linked cohort study, following Welsh residents for up to 20 years (2000-2019). Chronic disease diagnoses were obtained from general practice and hospitalisation records using the CALIBER disease phenotype register. Multi-state models were used to examine trajectories of accrual of 132 diseases and mortality, adjusted for sex, age and area-level deprivation. Restricted mean survival time was calculated to measure time spent free of chronic disease(s) or mortality between socioeconomic groups.

Findings

In total, 965,905 individuals aged 5-104 were included, from a possible 2.9 m individuals following a 5-year clearance period, with an average follow-up of 13.2 years (12.7 million person-years). Some 673,189 (69.7%) individuals developed at least one chronic disease or died within the study period. From ages 10 years upwards, the individuals living in the most deprived areas consistently experienced reduced time between health states, demonstrating accelerated transitions to first and subsequent morbidities and death compared to their demographic equivalent living in the least deprived areas. The largest difference were observed in 10 and 20 year old males developing multimorbidity (-0.45 years (99% CI: -0.45, -0.44)) and in 70 year old males dying after developing multimorbidity (-1.98 years (99% CI: -2.01, -1.95)).

Interpretation

This study adds to the existing literature on health inequalities by demonstrating that individuals living in more deprived areas consistently experience accelerated time to diagnosis of chronic disease and death across all ages, accounting for competing risks.

Funding

UK Medical Research Council, Health Data Research UK, and Administrative Data Research Wales.

Healthy immigrants, unhealthy ageing? Analysis of health decline among older migrants and natives across European countries

The probability of having multiple chronic conditions simultaneously, or multimorbidity, tends to increase with age. Immigrants face a particularly high risk of unhealthy ageing. This study investigates the immigrant-native disparities in the speed of age-related chronic disease accumulation, focusing on the number of chronic health conditions; and considers the heterogeneity of this trajectory within immigrant populations by origin and receiving country. We use data from the Survey of Health, Ageing and Retirement in Europe from 2004 to 2020 on adults aged 50 to 79 from 28 European countries and employ both cross-sectional and longitudinal analyses. For longitudinal panel analyses, we use fixed-effects regression models to account for the unobserved heterogeneity related to individual characteristics including migration background. Our results indicate that immigrants report a higher number of chronic conditions at all ages relative to their native-born peers, but also that the immigrant-native differential in the number of chronic conditions decreases from age 65 onwards. When considering differences by origin country, we find that the speed of chronic disease accumulation is slower among immigrants from the Americas and the Asia and Oceania country groups than it is among natives. When looking at differences by receiving country group, we observe that the speed of accumulating chronic diseases is slower among immigrants in Eastern Europe than among natives, particularly at older ages. Our findings suggest that age-related trajectories of health vary substantially among immigrant populations by origin and destination country, which underscore that individual migration histories play a persistent role in shaping the health of ageing immigrant populations throughout the life course.

Aging-Related Comorbidity Burden Among Women and Men With or At-Risk for HIV in the US, 2008-2019

Importance

Despite aging-related comorbidities representing a growing threat to quality-of-life and mortality among persons with HIV (PWH), clinical guidance for comorbidity screening and prevention is lacking. Understanding comorbidity distribution and severity by sex and gender is essential to informing guidelines for promoting healthy aging in adults with HIV.

Objective

To assess the association of human immunodeficiency virus on the burden of aging-related comorbidities among US adults in the modern treatment era.

Design, Setting, and Participants

This cross-sectional analysis included data from US multisite observational cohort studies of women (Women's Interagency HIV Study) and men (Multicenter AIDS Cohort Study) with HIV and sociodemographically comparable HIV-seronegative individuals. Participants were prospectively followed from 2008 for men and 2009 for women (when more than 80% of participants with HIV reported antiretroviral therapy use) through last observation up until March 2019, at which point outcomes were assessed. Data were analyzed from July 2020 to April 2021.

Exposures

HIV, age, sex.

Main Outcomes and Measures

Comorbidity burden (the number of total comorbidities out of 10 assessed) per participant; secondary outcomes included individual comorbidity prevalence. Linear regression assessed the association of HIV status, age, and sex with comorbidity burden.

Results

A total of 5929 individuals were included (median [IQR] age, 54 [46-61] years; 3238 women [55%]; 2787 Black [47%], 1153 Hispanic or other [19%], 1989 White [34%]). Overall, unadjusted mean comorbidity burden was higher among women vs men (3.4 [2.1] vs 3.2 [1.8]; P = .02). Comorbidity prevalence differed by sex for hypertension (2188 of 3238 women [68%] vs 2026 of 2691 men [75%]), psychiatric illness (1771 women [55%] vs 1565 men [58%]), dyslipidemia (1312 women [41%] vs 1728 men [64%]), liver (1093 women [34%] vs 1032 men [38%]), bone disease (1364 women [42%] vs 512 men [19%]), lung disease (1245 women [38%] vs 259 men [10%]), diabetes (763 women [24%] vs 470 men [17%]), cardiovascular (493 women [15%] vs 407 men [15%]), kidney (444 women [14%] vs 404 men [15%]) disease, and cancer (219 women [7%] vs 321 men [12%]). In an unadjusted model, the estimated mean difference in comorbidity burden among women vs men was significantly greater in every age strata among PWH: age under 40 years, 0.33 (95% CI, 0.03-0.63); ages 40 to 49 years, 0.37 (95% CI, 0.12-0.61); ages 50 to 59 years, 0.38 (95% CI, 0.20-0.56); ages 60 to 69 years, 0.66 (95% CI, 0.42-0.90); ages 70 years and older, 0.62 (95% CI, 0.07-1.17). However, the difference between sexes varied by age strata among persons without HIV: age under 40 years, 0.52 (95% CI, 0.13 to 0.92); ages 40 to 49 years, -0.07 (95% CI, -0.45 to 0.31); ages 50 to 59 years, 0.88 (95% CI, 0.62 to 1.14); ages 60 to 69 years, 1.39 (95% CI, 1.06 to 1.72); ages 70 years and older, 0.33 (95% CI, -0.53 to 1.19) (P for interaction = .001). In the covariate-adjusted model, findings were slightly attenuated but retained statistical significance.

Conclusions and Relevance

In this cross-sectional study, the overall burden of aging-related comorbidities was higher in women vs men, particularly among PWH, and the distribution of comorbidity prevalence differed by sex. Comorbidity screening and prevention strategies tailored by HIV serostatus and sex or gender may be needed.

Air pollution associated with incidence and progression trajectory of chronic lung diseases: a population-based cohort study

BACKGROUND

No prior study has examined the effects of air pollution on the progression from healthy to chronic lung disease, subsequent chronic lung multimorbidity and further to death.

METHODS

We used data from the UK Biobank of 265 506 adults free of chronic lung disease at recruitment. Chronic lung multimorbidity was defined as the coexistence of at least two chronic lung diseases, including asthma, chronic obstructive pulmonary disease and lung cancer. The concentrations of air pollutants were estimated using land-use regression models. Multistate models were applied to assess the effect of air pollution on the progression of chronic lung multimorbidity.

RESULTS

During a median follow-up of 11.9 years, 13 863 participants developed at least one chronic lung disease, 1055 developed chronic lung multimorbidity and 12 772 died. We observed differential associations of air pollution with different trajectories of chronic lung multimorbidity. Fine particulate matter showed the strongest association with all five transitions, with HRs (95% CI) per 5 µg/m3 increase of 1.31 (1.22 to 1.42) and 1.27 (1.01 to 1.57) for transitions from healthy to incident chronic lung disease and from incident chronic lung disease to chronic lung multimorbidity, and 1.32 (1.21 to 1.45), 1.24 (1.01 to 1.53) and 1.91 (1.14 to 3.20) for mortality risk from healthy, incident chronic lung disease and chronic lung multimorbidity, respectively.

CONCLUSION

Our study provides the first evidence that ambient air pollution could affect the progression from free of chronic lung disease to incident chronic lung disease, chronic lung multimorbidity and death.

Prevalence and factors associated with multimorbidity in adults in Brazil, according to sex: a population-based cross-sectional survey

Introduction

Multimorbidity, defined as the coexistence of two or more chronic diseases in the same individual, represents a significant health challenge. However, there is limited evidence on its prevalence and associated factors in developing countries, such as Brazil, especially stratified by sex. Thus, this study aims to estimate the prevalence and analyze the factors associated with multimorbidity in Brazilian adults according to sex.

Methods

Cross-sectional population-based household survey carried out with Brazilian adults aged 18 years or older. The sampling strategy consisted of a three-stage conglomerate plan. The three stages were performed through simple random sampling. Data were collected through individual interviews. Multimorbidity was classified based on a list of 14 self-reported chronic diseases/conditions. Poisson regression analysis was performed to estimate the magnitude of the association between sociodemographic and lifestyle factors with the prevalence of multimorbidity stratified by sex.

Results

A total of 88,531 individuals were included. In absolute terms, the prevalence of multimorbidity was 29.4%. The frequency in men and women was 22.7 and 35.4%, respectively. Overall, multimorbidity was more prevalent among women, the older people, residents of the South and Southeast regions, urban area residents, former smokers, current smokers, physically inactive, overweight, and obese adults. Individuals with complete high school/incomplete higher education had a lower prevalence of multimorbidity than those with higher educational level. The associations between education and multimorbidity differed between sexes. In men, multimorbidity was inversely associated with the strata of complete middle school/incomplete high school and complete high school/incomplete higher education, while in women, the association between these variables was not observed. Physical inactivity was positively associated with a higher prevalence of multimorbidity only in men. An inverse association was verified between the recommended fruit and vegetable consumption and multimorbidity for the total sample and both sexes.

Conclusion

One in four adults had multimorbidity. Prevalence increased with increasing age, among women, and was associated with some lifestyles. Multimorbidity was significantly associated with educational level and physical inactivity only in men. The results suggest the need to adopt integrated strategies to reduce the magnitude of multimorbidity, specific by gender, including actions for health promotion, disease prevention, health surveillance and comprehensive health care in Brazil.

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.

A new era of HIV care for age-associated multimorbidity

PURPOSE OF REVIEW

The management of people with HIV has shifted focus from acute AIDS-defining illness towards improving detection of chronic disease and reducing impact of multimorbidity. In this review, we explore this shifting paradigm of HIV care and the evidence for alternative models proposed to provide integrated holistic services for people with HIV (PWH) with multimorbidity.

RECENT FINDINGS

Despite 25 years of the antiretroviral treatment (ART) era an increased incidence of noncommunicable disease (NCD) and multimorbidity in PWH persists. As the world moves closer to universal ART coverage this phenomenon is now reported in low- and middle-income settings. Multimorbidity affects PWH disproportionately compared to the general population and results in reduced health related quality of life (HRQoL), greater hospitalization and higher mortality. There is evidence that NCD care provision and outcomes may be inferior for PWH than their HIV negative counterparts. Various models of integrated multimorbidity care have developed and are grouped into four categories; HIV specialist clinics incorporating NCD care, primary care services incorporating HIV care, community NCD clinics offering integrated HIV care, and multidisciplinary care integrated with HIV in secondary care. Evidence is limited as to the best way to provide multimorbidity care for PWH.

SUMMARY

A new era of HIV care for an ageing population with multimorbidity brings challenges for health providers who need to develop holistic patient focused services which span a range of coexisting conditions.

Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

BACKGROUND

The COVID-19 pandemic caused rapid changes in primary care delivery in the UK, with concerns that certain groups of the population may have faced increased barriers to access. This study assesses the impact of the response to the COVID-19 pandemic on primary care consultations for individuals with multimorbidity and identifies ethnic inequalities.

METHODS

A longitudinal study based on monthly data from primary care health records of 460,084 patients aged ≥18 years from 41 GP practices in South London, from February 2018 to March 2021. Descriptive analysis and interrupted time series (ITS) models were used to analyse the effect of the pandemic on primary care consultations for people with multimorbidity and to identify if the effect varied by ethnic groups and consultation type.

RESULTS

Individuals with multimorbidity experienced a smaller initial fall in trend at the start of the pandemic. Their primary care consultation rates remained stable (879 (95% CI 869-890) per 1000 patients in February to 882 (870-894) March 2020), compared with a 7% decline among people without multimorbidity (223 consultations (95% CI 221-226) to 208 (205-210)). The gap in consultations between the two groups reduced after July 2020. The effect among individuals with multimorbidity varied by ethnic group. Ethnic minority groups experienced a slightly larger fall at the start of the pandemic. Individuals of Black, Asian, and Other ethnic backgrounds also switched from face-to-face to telephone at a higher rate than other ethnic groups. The largest fall in face-to-face consultations was observed among people from Asian backgrounds (their consultation rates declined from 676 (659-693) in February to 348 (338-359) in April 2020), which may have disproportionately affected their quality of care.

CONCLUSIONS

The COVID-19 pandemic significantly affected primary care utilisation in patients with multimorbidity. While there is evidence of a successful needs-based prioritisation of multimorbidity patients within primary care at the start of the pandemic, inequalities among ethnic minority groups were found. Strengthening disease management for these groups may be necessary to control widening inequalities in future health outcomes.

A conceptual framework for characterising lifecourse determinants of multiple long-term condition multimorbidity

Objective

Social, biological and environmental factors in early-life, defined as the period from preconception until age 18, play a role in shaping the risk of multiple long-term condition multimorbidity. However, there is a need to conceptualise these early-life factors, how they relate to each other, and provide conceptual framing for future research on aetiology and modelling prevention scenarios of multimorbidity. We develop a conceptual framework to characterise the population-level domains of early-life determinants of future multimorbidity.

Method

This work was conducted as part of the Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B) study. The conceptualisation of multimorbidity lifecourse determinant domains was shaped by a review of existing research evidence and policy, and co-produced with public involvement via two workshops.

Results

Early-life risk factors incorporate personal, social, economic, behavioural and environmental factors, and the key domains discussed in research evidence, policy, and with public contributors included adverse childhood experiences, socioeconomics, the social and physical environment, and education. Policy recommendations more often focused on individual-level factors as opposed to the wider determinants of health discussed within the research evidence. Some domains highlighted through our co-production process with public contributors, such as religion and spirituality, health screening and check-ups, and diet, were not adequately considered within the research evidence or policy.

Conclusions

This co-produced conceptualisation can inform research directions using primary and secondary data to investigate the early-life characteristics of population groups at risk of future multimorbidity, as well as policy directions to target public health prevention scenarios of early-onset multimorbidity.

Osteoarthritis is positively associated with self-reported sleep trouble in older adults

BACKGROUND

Osteoarthritis (OA) is a leading cause of disability in older adults. Most research has focused on minimizing pain and maximizing physical function so as to maintain patient mobility preceding joint arthroplasty. However, few studies have formally studied the relationship between OA and sleep trouble, although it is clinically recognized that OA may affect sleep.

METHODS

The study was based on the National Health and Nutrition Examination Survey (NHANES) database from 2011-2018. Participants were defined as adults aged 60 years or older with diagnoses of OA and self-reported sleep trouble. Multivariable regression analyses were applied to assess the association between OA and sleep trouble, adjusting for age, sex, body mass index, race/ethnicity, education level, marital status, income, depression level, etc. RESULTS: This study included 4154 participants, consisting of the control group (n = 2966) and the OA group (n = 1188). OA individuals were 2.11 (95% CI 1.79-2.47, p < 0.001) times more likely to have sleep trouble compared with those without OA. On subgroup analyses, there was lower odds ratio value of sleep trouble in men compared with women, and in the highest income group compared with the other income groups.

CONCLUSIONS

OA was positively associated with sleep trouble in older adults, with different odds ratio values among different subgroups. Our results suggest that older adults with OA should be aggressively screened for sleep problems.

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.

Ethnic inequities in multimorbidity among people with psychosis: a retrospective cohort study

AIMS

Research shows persistent ethnic inequities in mental health experiences and outcomes, with a higher incidence of illnesses among minoritised ethnic groups. People with psychosis have an increased risk of multiple long-term conditions (MLTC; multimorbidity). However, there is limited research regarding ethnic inequities in multimorbidity in people with psychosis. This study investigates ethnic inequities in physical health multimorbidity in a cohort of people with psychosis.

METHODS

In this retrospective cohort study, using the Clinical Records Interactive Search (CRIS) system, we identified service-users of the South London and Maudsley NHS Trust with a schizophrenia spectrum disorder, and then additional diagnoses of diabetes, hypertension, low blood pressure, overweight or obesity and rheumatoid arthritis. Logistic and multinomial logistic regressions were used to investigate ethnic inequities in odds of multimorbidity (psychosis plus one physical health condition), and multimorbidity severity (having one or two physical health conditions, or three or more conditions), compared with no additional health conditions (no multimorbidity), respectively. The regression models adjusted for age and duration of care and investigated the influence of gender and area-level deprivation.

RESULTS

On a sample of 20 800 service-users with psychosis, aged 13-65, ethnic differences were observed in the odds for multimorbidity. Controlling for sociodemographic factors and duration of care, compared to White British people, higher odds of multimorbidity were found for people of Black African [adjusted Odds Ratio = 1.41, 95% Confidence Intervals (1.23-1.56)], Black Caribbean [aOR = 1.79, 95% CI (1.58-2.03)] and Black British [aOR = 1.64, 95% CI (1.49-1.81)] ethnicity. Reduced odds were observed among people of Chinese [aOR = 0.61, 95% CI (0.43-0.88)] and Other ethnic [aOR = 0.67, 95% CI (0.59-0.76)] backgrounds. Increased odds of severe multimorbidity (three or more physical health conditions) were also observed for people of any Black background.

CONCLUSIONS

Ethnic inequities are observed for multimorbidity among people with psychosis. Further research is needed to understand the aetiology and impact of these inequities. These findings support the provision of integrated health care interventions and public health preventive policies and actions.

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.