Multimorbidity in middle age predicts more subsequent hospital admissions than in older age: A nine-year retrospective cohort study of 121,188 discharged in-patients

Age-specific Multimorbidity Patterns and Burden on All-Cause Mortality and Public Direct Medical Expenditure: A Retrospective Cohort Study

OBJECTIVE

To evaluate age-specific multimorbidity patterns and morbidity burden on mortality and healthcare expenditure across age groups.

PATIENTS AND METHODS

Retrospective observational study between January 1, 2009 to December 31, 2017 using electronic health records in Hong Kong: Individuals were stratified by age (< 50, 50-64, 65-79, ≥ 80), and sub-classified by number of morbidities (0, 1, 2, 3, ≥ 4) out of 21 common chronic conditions. Clustering analyses were conducted to identify specific patterns of multimorbidity. Association between the number as well as combinations of morbidities and all-cause mortality and public expenditure was examined.

RESULTS

4,562,832 individuals with a median follow-up of 7 years were included. Mental disorders were the top morbidities among young individuals, while cardiovascular diseases were prevalent in the elderly. An increased number of morbidities was associated with a greater relative risk for mortality and medical expenditure, and this relationship was stronger among younger patients. Compared to individuals in the same age group without morbidity, the hazard ratios (HR; 95% CI) of all-cause mortality in patients aged < 50 and ≥ 80 with two comorbidities 3.81 (3.60-4.03) and 1.38 (1.36-1.40), respectively, which increased to 14.22 (9.87-20.47) and 2.20 (2.13-2.26), respectively, as the number of morbidities increased to ≥ 4. The stroke-hypertension cluster was shown to be associated with the highest HR of mortality 2.48 (2.43-2.53) among all identified clusters arising from the clustering analysis.

CONCLUSION

Given the stronger association between multimorbidity and all-cause mortality and greater opportunity costs in younger populations, prevention and management of early-onset multimorbidity are warranted. (248 words).

Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination

BACKGROUND

It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association.

AIM

To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination.

DESIGN

Nested case-control study.

METHODS

We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity.

RESULTS

In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger.

CONCLUSIONS

We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.

Development and validation of new multimorbidity-weighted index for ICD-10-coded electronic health record and claims data: an observational study

OBJECTIVE

Map multimorbidity-weighted index (MWI) conditions to International Classification of Diseases, 10th Revision (ICD-10), expand the conditions and codes to develop a new ICD-10-coded MWI (MWI-ICD10) and updated MWI-ICD9, and assess their consistency.

DESIGN

Population-based retrospective cohort.

SETTING

Large medical centre between 2013 and 2017.

PARTICIPANTS

Adults ≥18 years old with encounters in each of 4 years (2013, 2014, 2016, 2017).

MAIN OUTCOME MEASURES

MWI conditions mapped to ICD-10 codes, and additional conditions and codes added to produce a new MWI-ICD10 and updated MWI-ICD9. We compared the prevalence of ICD-coded MWI conditions within the ICD-9 era (2013-2014), within the ICD-10 era (2016-2017) and across the ICD-9-ICD-10 transition in 2015 (washout period) among adults present in both sets of comparison years. We computed the prevalence and change in prevalence of conditions when using MWI-ICD10 versus MWI-ICD9.

RESULTS

88 175 adults met inclusion criteria. Participants were 60.8% female, 50.5% white, with mean age 54.7±17.3 years and baseline MWI-ICD9 4.47±6.02 (range 0-64.33). Of 94 conditions, 65 had <1% difference across the ICD-9-ICD-10 transition and similar minimal changes within ICD coding eras.

CONCLUSIONS

MWI-ICD10 captured the prevalence of chronic conditions nearly identically to that of the validated MWI-ICD9, along with notable but explicable changes across the ICD-10 transition. This new comprehensive person-centred index enables quantification of cumulative disease burden and physical functioning in adults as a clinically meaningful measure of multimorbidity in electronic health record and claims data.

Lack of leisure time physical activity and variations in cardiovascular mortality across US communities: a comprehensive county-level analysis (2011-2019)

OBJECTIVES

To investigate the associations between county-level proportions of adults not engaging in leisure-time physical activity (no LTPA) and age-adjusted cardiovascular mortality (AACVM) rates in the overall US population and across demographics.

METHODS

Analysing 2900 US counties from 2011 to 2019, we used the Centers for Disease Control and Prevention (CDC) databases to obtain annual AACVM rates. No LTPA data were sourced from the CDC's Behavioural Risk Factor Surveillance System survey and county-specific rates were calculated using a validated multilevel regression and poststratification modelling approach. Multiple regression models assessed associations with county characteristics such as socioeconomic, environmental, clinical and healthcare access factors. Poisson generalised linear mixed models were employed to calculate incidence rate ratios (IRR) and additional yearly deaths (AYD) per 100 000 persons.

RESULTS

Of 309.9 million residents in 2900 counties in 2011, 7.38 million (2.4%) cardiovascular deaths occurred by 2019. County attributes such as socioeconomic, environmental and clinical factors accounted for up to 65% (adjusted R2=0.65) of variance in no LTPA rates. No LTPA rates associated with higher AACVM across demographics, notably among middle-aged adults (standardised IRR: 1.06; 95% CI (1.04 to 1.07)), particularly women (1.09; 95% CI (1.07 to 1.12)). The highest AYDs were among elderly non-Hispanic black individuals (AYD=68/100 000).

CONCLUSIONS

Our study reveals a robust association between the high prevalence of no LTPA and elevated AACVM rates beyond other social determinants. The most at-risk groups were middle-aged women and elderly non-Hispanic black individuals. Further, county-level characteristics accounted for substantial variance in community LTPA rates. These results emphasise the need for targeted public health measures to boost physical activity, especially in high-risk communities, to reduce AACVM.

Multimorbidity impacts cardiovascular disease risk following percutaneous coronary intervention: latent class analysis of the Melbourne Interventional Group (MIG) registry

BACKGROUND

Multimorbidity is strongly associated with disability or functional decline, poor quality of life and high consumption of health care services. This study aimed (1) To identify patterns of multimorbidity among patients undergoing first recorded percutaneous coronary intervention (PCI); (2) To explore the association between the identified patterns of multimorbidity on length of hospital stay, 30-day and 12- month risk of major adverse cardiac and cerebrovascular events (MACCE) after PCI.

METHODS

A retrospective cohort study of the Melbourne Interventional Group (MIG) registry. This study included 14,025 participants who underwent their first PCI from 2005 to 2015 in Victoria, Australia. Based on a probabilistic modelling approach, Latent class analysis was adopted to classify clusters of people who shared similar combinations and magnitude of the comorbidity of interest. Logistic regression models were used to estimate odd ratios and 95% confidence interval (CI) for the 30-day and 12-month MACCE.

RESULTS

More than two-thirds of patients had multimorbidity, with the most prevalent conditions being hypertension (59%) and dyslipidaemia (60%). Four distinctive multimorbidity clusters were identified each with significant associations for higher risk of 30-day and 12-month MACCE. The cluster B had the highest risk of 30-day MACCE event that was characterised by a high prevalence of reduced estimated glomerular filtration rate (92%), hypertension (73%) and reduced ejection fraction (EF) (57%). The cluster C, characterised by a high prevalence of hypertension (94%), dyslipidaemia (88%), reduced eGFR (87%), diabetes (73%) and reduced EF (65%) had the highest risk of 12-month MACCE and highest length of hospital stay.

CONCLUSION

Hypertension and dyslipidaemia are prevalent in at least four in ten patients undergoing coronary angioplasty. This study showed that clusters of patients with multimorbidity had significantly different risk of 30-day and 12-month MACCE after PCI. This suggests the necessity for treatment approaches that are more personalised and customised to enhance patient outcomes and the quality of care delivered to patients in various comorbidity clusters. These results should be validated in a prospective cohort and to evaluate the potential impacts of these clusters on the prevention of MACCE after PCI.

The association between specific narrative elements and patient perspectives on acute pain treatment

BACKGROUND

Narratives are effective tools for communicating with patients about opioid prescribing for acute pain and improving patient satisfaction with pain management. It remains unclear, however, whether specific narrative elements may be particularly effective at influencing patient perspectives.

METHODS

This study was a secondary analysis of data collected for Life STORRIED, a multicenter RCT. Participants included 433 patients between 18 and 70 years-old presenting to the emergency department (ED) with renal colic or musculoskeletal back pain. Participants were instructed to view one or more narrative videos during their ED visit in which a patient storyteller discussed their experiences with opioids. We examined associations between exposure to individual narrative features and patients' 1) preference for opioids, 2) recall of opioid-related risks and 3) perspectives about the care they received.

RESULTS

Participants were more likely to watch videos featuring storytellers who shared their race or gender. We found that participants who watched videos that contained specific narrative elements, for example mention of prescribed opioids, were more likely to recall having received information about pain treatment options on the day after discharge (86.3% versus 72.9%, p = 0.02). Participants who watched a video that discussed family history of addiction reported more participation in their treatment decision than those who did not (7.6 versus 6.8 on a ten-point scale, p = 0.04).

CONCLUSIONS

Participants preferentially view narratives featuring storytellers who share their race or gender. Narrative elements were not meaningfully associated with patient-centered outcomes. These findings have implications for the design of narrative communication tools.

Individual-level and neighborhood-level shifts in mortality patterns among drug poisoning deaths in a high-density Asian city: a territory-wide, case-only analysis

BACKGROUND

The shifts in individual-level and neighborhood-level patterns of drug poisoning deaths in a high-density Asian city over time have been underestimated, although they provide essential information for community-based surveillance and interventions.

METHODS

A case-only analysis with a 16-y, territory-wide, population-based registry in Hong Kong was applied to compare drug poisoning deaths from 2001 to 2010 with 2011 to 2016. Drug poisoning deaths, deaths from heroin and deaths from other opioids (codeine or morphine) were extracted (ICD codes: T36-T50, T40.1, T40.2). Binomial regressions were used to estimate the shifts in mortality patterns.

RESULTS

Among 3069 drug poisoning deaths, a significant shift in mortality patterns was found despite a decreasing mortality trend in Hong Kong. Overall, drug poisoning deaths shifted towards middle-aged/young-old, widowed/divorced, economically active, white collar and non-local born. Since 2011, more deaths from heroin were in older ages and non-local born, but less were never married and economically inactive. More deaths from other opioids were middle-aged, young-old and divorced. In particular, most decedents shifted towards young-old, especially deaths from other opioids. Compared with deaths during 2001-2010, there were 3.72- and 6.50-fold more deaths from heroin and deaths from other opioids in those aged ≥60 y since 2021 (ORs: 3.72 [2.37, 5.86], 6.50 [3.97, 10.65]), respectively. Additionally, drug poisoning deaths shifted towards areas with less neighborhood deprivation (more high-education individuals and a mix of private/public housing residents), especially deaths from other opioids.

CONCLUSION

Misuse of registered drugs (e.g. opioid pain relievers) could be a rising trend among vulnerable subpopulations in Hong Kong other than illegal drug use (heroin). Health officials should provide more advice and support on drug information. Specifically, an improved health system with education regarding the appropriate use of registered drugs for medical treatments should be provided to mid-/high-income and local-born individuals.

Associations of hospitalisation - admission, readmission and length to stay - with multimorbidity patterns by age and sex in adults and older adults: the ELSI-Brazil study

BACKGROUND

Although the association between multimorbidity (MM) and hospitalisation is known, the different effects of MM patterns by age and sex in this outcome needs to be elucidated. Our study aimed to analyse the association of hospitalisations' variables (occurrence, readmission, length of stay) and patterns of multimorbidity (MM) according to sex and age.

METHODS

Data from 8.807 participants aged ≥ 50 years sourced from the baseline of the Brazilian Longitudinal Study of Ageing (ELSI-Brazil) were analysed. Multimorbidity was defined as ≥ 2 (MM2) and ≥ 3 (MM3) chronic conditions. Poisson regression was used to verify the association between the independent variables and hospitalisation according to sex and age group. Multiple linear regression models were constructed for the outcomes of readmission and length of stay. Ising models were used to estimate the networks of diseases and MM patterns.

RESULTS

Regarding the risk of hospitalisation among those with MM2, we observed a positive association with male sex, age ≥ 75 years and women aged ≥ 75 years. For MM3, there was a positive association with hospitalisation among males. For the outcomes hospital readmission and length of stay, we observed a positive association with male sex and women aged ≥ 75 years. Network analysis identified two groups that are more strongly associated with occurrence of hospitalisation: the cardiovascular-cancer-glaucoma-cataract group stratified by sex and the neurodegenerative diseases-renal failure-haemorrhagic stroke group stratified by age group.

CONCLUSION

We conclude that the association between hospitalisation, readmission, length of stay, and MM changes when sex and age group are considered. Differences were identified in the MM patterns associated with hospitalisation according to sex and age group.

Association between multimorbidity and hospitalization in older adults: systematic review and meta-analysis

Background

Multimorbidity is defined as the presence of multiple chronic conditions in the same individual. Multimorbidity is more prevalent in older adults and can lead to several adverse health outcomes.

Methods

We systematically reviewed evidence from observational studies to verify the association between multimorbidity and hospitalization in older adults. Furthermore, we also aimed to identify whether it changes according to gender, advanced age, institutionalization, and wealth of the country of residence. We searched the PubMed, Embase and Scopus databases from December 2020 to April 2021. The analysed outcomes were as follows: hospitalization, length of stay and hospital readmission.

Results

Of the 6,948 studies identified in the databases, 33 were included in this review. From the meta-analysis results, it was found that multimorbidity, regardless of the country’s wealth, was linked to hospitalization in older adults (OR = 2.52, CI 95% = 1.87–3.38). Both definitions of multimorbidity, ≥2 (OR = 2.35, 95% CI = 1.34–4.12) and ≥3 morbidities (OR = 2.52, 95% CI = 1.87–3.38), were associated with hospitalization. Regardless of gender, multimorbidity was associated with hospitalization (OR = 1.98, 95% CI = 1.67–2.34) and with readmission (OR = 1.07, 95% CI = 1.04–1.09). However, it was not possible to verify the association between multimorbidity and length of stay.

Conclusions

Multimorbidity was linked to a higher hospitalization risk, and this risk was not affected by the country’s wealth and patient’s gender. Multimorbidity was also linked to a higher hospital readmission rate in older adults. PROSPERO Registration (Registration number: CRD42021229328).

Multimorbidity and adverse events of special interest associated with Covid-19 vaccines in Hong Kong

Prior research using electronic health records for Covid-19 vaccine safety monitoring typically focuses on specific disease groups and excludes individuals with multimorbidity, defined as ≥2 chronic conditions. We examine the potential additional risk of adverse events 28 days after the first dose of CoronaVac or Comirnaty imposed by multimorbidity. Using a territory-wide public healthcare database with population-based vaccination records in Hong Kong, we analyze a retrospective cohort of patients with chronic conditions. Thirty adverse events of special interest according to the World Health Organization are examined. In total, 883,416 patients are included and 2,807 (0.3%) develop adverse events. Results suggest vaccinated patients have lower risks of adverse events than unvaccinated individuals, multimorbidity is associated with increased risks regardless of vaccination, and the association of vaccination with adverse events is not modified by multimorbidity. To conclude, we find no evidence that multimorbidity imposes extra risks of adverse events following Covid-19 vaccination.

Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults

Background

Multimorbidity presents an enormous problem to societal and healthcare utilization under the context of aging population in low- and middle-income countries (LMICs). Currently, systematic studies on the profile of multimorbidity and its characteristics among Chinese elderly are lacking. We described the temporal and spatial trends in the prevalence of multimorbidity and explored chronological changes of comorbidity patterns in a large elderly population survey.

Methods

Data were extracted from the Chinese Longitudinal Healthy Longevity Study (CLHLS) conducted between 1998 and 2018 in a random selection of half of the counties and city districts. All the elderly aged 65 and older were included in the survey of eight waves. We used 13 investigated chronic diseases to measure the prevalence of multimorbidity by means of geography, subpopulation, and chronological changes. The patterns of multimorbidity were assessed by computing the value of relative risk (RR indicates the likelihood of certain diseases to be associated with multimorbidity) and the observed-to-expected ratio (O/E indicates the likelihood of the coexistence of a multimorbidity combination).

Results

From 1998 to 2018, the prevalence of multimorbidity went from 15.60 to 30.76%, increasing in the fluctuation across the survey of eight waves (p_{for trend} = 0.020). Increasing trends were observed similarly in a different gender group (p_male = 0.009; p_female = 0.004) and age groups among female participants (p_~80 = 0.009; p₈₁₋₉₀ = 0.004; p₉₁₋₁₀₀ = 0.035; p_101~ = 0.018). The gap in the prevalence of multimorbidity between the north and the south was getting narrow across the survey of eight waves. Hypertension was the highest prevalent chronic condition while diabetes was most likely to coexist with other chronic conditions in the CLHLS survey. The most frequently occurring clusters were hypertension and heart disease, hypertension and cataract, and hypertension and chronic lung disease. And, the cancer, TB, and Parkinson's disease cluster took the domination of O/E rankings over time, which had a higher probability of coexistence in all the multimorbidity combinations.

Conclusions

The prevalence of multimorbidity has been increasing nationwide, and more attention should be paid to a rapid growth in the southern part of China. It demands the effective diagnosis and treatment adopted to the highly prevalent comorbidities, and strategies and measures were adjusted to strongly relevant clusters.

Comparing Multimorbidity Patterns Among Discharged Middle-Aged and Older Inpatients Between Hong Kong and Zurich: A Hierarchical Agglomerative Clustering Analysis of Routine Hospital Records

Background: Multimorbidity, defined as the co-occurrence of ≥2 chronic conditions, is clinically diverse. Such complexity hinders the development of integrated/collaborative care for multimorbid patients. In addition, the universality of multimorbidity patterns is unclear given scarce research comparing multimorbidity profiles across populations. This study aims to derive and compare multimorbidity profiles in Hong Kong (HK, PRC) and Zurich (ZH, Switzerland).

Methods: Stratified by sites, hierarchical agglomerative clustering analysis (dissimilarity measured by Jaccard index) was conducted with the objective of grouping inpatients into clinically meaningful clusters based on age, sex, and 30 chronic conditions among 20,000 randomly selected discharged multimorbid inpatients (10,000 from each site) aged ≥ 45 years. The elbow point method based on average within-cluster dissimilarity, complemented with a qualitative clinical examination of disease prevalence, was used to determine the number of clusters.

Results: Nine clusters were derived for each site. Both similarities and dissimilarities of multimorbidity patterns were observed. There was one stroke-oriented cluster (3.9% in HK; 6.5% in ZH) and one chronic kidney disease-oriented cluster (13.1% in HK; 11.5% ZH) in each site. Examples of site-specific multimorbidity patterns, on the other hand, included a myocardial infarction-oriented cluster in ZH (2.3%) and several clusters in HK with high prevalence of heart failure (>65%) and chronic pain (>20%).

Conclusion: This is the first study using hierarchical agglomerative clustering analysis to profile multimorbid inpatients from two different populations to identify universalities and differences of multimorbidity patterns. Our findings may inform the coordination of integrated/collaborative healthcare services.

Examine the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings

Background

Multimorbidity, often defined as having two or more chronic conditions is a global phenomenon. This study examined the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings. The prevalence of individual diseases was also investigated by age and sex.

Methods

The Canada Community Health Survey and linked health administrative databases were used to examine the association between multimorbidity, sociodemographic, behavioral, and other risk factors in the province of Ontario. A multivariable logistic regression model was used to conduct the main analysis.

Results

Analyses were stratified by age (20-64 and 65-95) and area of residence (rural and urban). A total sample of n = 174,938 residents between the ages of 20-95 were examined in the Ontario province, of which 18.2% (n = 31,896) were multimorbid with 2 chronic conditions, and 23.4% (n = 40,883) with 3+ chronic conditions. Females had a higher prevalence of 2 conditions (17.9% versus 14.6%) and 3+ conditions (19.7% vs. 15.6%) relative to males. Out of all examined variables, poor self-perception of health, age, Body Mass Index, and income were most significantly associated with multimorbidity. Smoking was a significant risk factor in urban settings but not rural, while drinking was significant in rural and not urban settings. Income inequality was associated with multimorbidity with greater magnitude in rural areas. Prevalence of multimorbidity and having three or more chronic conditions were highest among low-income populations.

Conclusion

Interventions targeting population weight, age/sex specific disease burdens, and additional focus on stable income are encouraged.

Patterns of multimorbidity and their association with hospitalisation: a population-based study of older adults in urban Tanzania

BACKGROUND

while the HIV epidemic remains a considerable challenge in sub-Saharan Africa, a dramatic reduction in the associated mortality has led to a fundamental shift in the public health priorities aimed at tackling multimorbidity. Against the unprecedented level of urbanisation taking place in Tanzania, the burden of multimorbidity and its consequences among ageing adults, in the form of costly inpatient hospitalisation, remain unquantified.

METHODS

we used data from one of Africa's largest urban population cohort, the Dar es Salaam Health and the Demographic Surveillance System, to quantity the extent of multimorbidity (occurrence of 2 ≥ health conditions) and discordant multimorbidity (occurrence of conditions in 2 ≥ domains in mental health, non-communicable and communicable health) among 2,299 adults aged ≥40 years in Dar es Salaam, Tanzania. We fitted logistic regression models to investigate the association between multimorbidity and inpatient hospitalisation.

RESULTS

the prevalence of multimorbidity and discordant multimorbidity were 25.3 and 2.5%, respectively. Although the severe forms of multimorbidity (2.0% with ≥4 health conditions) and discordancy were low, hospitalisation was significantly higher based on the regression analyses. Household food insecurity was the only socio-economic variable that was significantly and consistently associated with a greater hospitalisation.

CONCLUSION

we found an alarmingly high degree of multimorbidity among this ageing urban population where hospitalisation was driven by multimorbidity. As public health resources remain scarce, reducing costly inpatient hospitalisation requires multilevel interventions that address clinical- and structural-level challenges (e.g. food insecurity) to mitigate multimorbidity and promote long-term healthy independent living among older adults in Tanzania.

Super fragmented: a nationally representative cross-sectional study exploring the fragmentation of inpatient care among super-utilizers

Background

Super-utilizers with 4 or more admissions per year frequently receive low-quality care and disproportionately contribute to healthcare costs. Inpatient care fragmentation (admission to multiple different hospitals) in this population has not been well described.

Objective

To determine the prevalence of super-utilizers who receive fragmented care across different hospitals and to describe associated risks, costs, and health outcomes.

Research design

We analyzed inpatient data from the Health Care Utilization Project’s State Inpatient and Emergency Department database from 6 states from 2013. After identifying hospital super-utilizers, we stratified by the number of different hospitals visited in a 1-year period. We determined how patient demographics, costs, and outcomes varied by degree of fragmentation. We then examined how fragmentation would influence a hospital’s ability to identify super-utilizers.

Subjects

Adult patients with 4 or more inpatient stays in 1 year.

Measures

Patient demographics, cost, 1-year hospital reported mortality, and probability that a single hospital could correctly identify a patient as a super-utilizer.

Results

Of the 167,515 hospital super-utilizers, 97,404 (58.1%) visited more than 1 hospital in a 1-year period. Fragmentation was more likely among younger, non-white, low-income, under-insured patients, in population-dense areas. Patients with fragmentation were more likely to be admitted for chronic disease management, psychiatric illness, and substance abuse. Inpatient fragmentation was associated with higher yearly costs and lower likelihood of being identified as a super-utilizer.

Conclusions

Inpatient care fragmentation is common among super-utilizers, disproportionately affects vulnerable populations. It is associated with high yearly costs and a decreased probability of correctly identifying super-utilizers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06323-5.

Association between antipsychotic use and acute ischemic heart disease in women but not in men: a retrospective cohort study of over one million primary care patients

BACKGROUND

Research comparing sex differences in the effects of antipsychotic medications on acute ischemic heart disease (IHD) is limited and the findings ambiguous. This study aimed to investigate these associations within a primary care setting.

METHODS

Hong Kong public general outpatient electronic records of patients aged 45+ during 2007-2010 were extracted, with the last consultation date as the baseline for a 4-year follow-up period to observe acute IHD hospitalizations (2011-2014). Antipsychotic use was defined as any prescription over the previous 12 months from a list of 16 antipsychotics, while acute IHD was defined by ICD-9: 410.00-411.89. Both sex-specific and sex-combined (both sexes) mixed-effects Cox models (random intercept across 74 clinics) were implemented to examine the association and test the interaction between antipsychotics and sex.

RESULTS

Among 1,043,236 included patients, 17,780 (1.7%) were prescribed antipsychotics, and 8342 (0.8%) developed IHD. In sex-specific analyses, antipsychotic prescription was associated with a 32% increased hazard rate of acute IHD among women (95% CI 1.05-1.67) but not among men. A likelihood ratio test comparing sex-combined models with and without the interaction between antipsychotic use and sex suggested significant interaction (χ² = 4.72, P = 0.030). The association between antipsychotic use and IHD among women attenuated and became non-significant when haloperidol was omitted from the operationalization of antipsychotic use (HR = 1.23, 95% CI 0.95-1.60).

CONCLUSION

Our results suggest that antipsychotic prescription is moderately associated with an increased risk of acute IHD among women in primary care and this relationship may be explained by specific antipsychotics. Further research should observe and capture the potential intermediary mechanisms and the dose-response relationship of this association to provide more rigorous evidence to establish causality and inform clinical practices.

Sociodemographic and lifestyle predictors of incident hospital admissions with multimorbidity in a general population, 1999-2019: the EPIC-Norfolk cohort

BACKGROUND

The ageing population and prevalence of long-term disorders with multimorbidity are a major health challenge worldwide. The associations between comorbid conditions and mortality risk are well established; however, few prospective community-based studies have reported on prior risk factors for incident hospital admissions with multimorbidity. We aimed to explore the independent associations for a range of demographic, lifestyle and physiological determinants and the likelihood of subsequent hospital incident multimorbidity.

METHODS

We examined incident hospital admissions with multimorbidity in 25 014 men and women aged 40-79 in a British prospective population-based study recruited in 1993-1997 and followed up until 2019. The determinants of incident multimorbidity, defined as Charlson Comorbidity Index ≥3, were investigated using multivariable logistic regression models for the 10-year period 1999-2009 and repeated with independent measurements in a second 10-year period 2009-2019.

RESULTS

Between 1999 and 2009, 18 179 participants (73% of the population) had a hospital admission. Baseline 5-year and 10-year incident multimorbidities were observed in 6% and 12% of participants, respectively. Age per 10-year increase (OR 2.19, 95% CI 2.06 to 2.33) and male sex (OR 1.32, 95% CI 1.19 to 1.47) predicted incident multimorbidity over 10 years. In the subset free of the most serious diseases at baseline, current smoking (OR 1.86, 95% CI 1.60 to 2.15), body mass index >30 kg/m² (OR 1.48, 95% CI 1.30 to 1.70) and physical inactivity (OR 1.16, 95% CI 1.04 to 1.29) were positively associated and plasma vitamin C (a biomarker of plant food intake) per SD increase (OR 0.86, 95% CI 0.81 to 0.91) inversely associated with incident 10-year multimorbidity after multivariable adjustment for age, sex, social class, education, alcohol consumption, systolic blood pressure and cholesterol. Results were similar when re-examined for a further time period in 2009-2019.

CONCLUSION

Age, male sex and potentially modifiable lifestyle behaviours including smoking, body mass index, physical inactivity and low fruit and vegetable intake were associated with increased risk of future incident hospital admissions with multimorbidity.

How does chronic multimorbidity affect daily routines? An experience sampling study of community-dwelling adults in Hong Kong

Limited by conventional data collection methods, it is unclear how community-dwelling multimorbid people's daily routines are affected by their co-occurring illnesses. This study investigated the differences in everyday life schedules between multimorbid and nonmultimorbid people. Three hundred community-dwelling adults, representative of the Hong Kong Chinese population, provided real-time self-reports of daily routines over a 7-day study period. Stratified by baseline multimorbidity status, we implemented generalized linear mixed models (binomial) for each of the four outcomes: meal, chores, conversation, and work/school, with time intervals as independent variable and potential confounders adjusted. The odds of engaging in these activities were compared between multimorbid and nonmultimorbid participants by time intervals. Significant differences were identified. Unlike nonmultimorbid participants, late evening (22:00-24:00) was estimated to be the most frequently observed meal time among multimorbid participants (adjusted odds ratio [AOR] = 8.21, 95% confidence interval [CI] = 2.59-26.01 vs. 14:00-16:00), who also did chores significantly earlier in the morning (AOR = 1.97, 95% CI = 1.09-3.58 in 8:00-10:00 vs. 14:00-16:00). Conversations were significantly less likely among multimorbid participants throughout the day. Last, multimorbid participants seemed to have less typical working/schooling hours. Further studies are warranted to investigate how these disruptions may lead to lower levels of quality of life and poorer mental health.

Association of comorbidities with clinical outcomes in patients after acute myocardial infarction

BACKGROUND

Multimorbidity becomes more prevalent in patients admitted for acute myocardial infarction (AMI). We investigated the association of an increasing number of comorbidities with the excess risk of in-hospital mortality and other clinically outcomes in hospitalized AMI patients.

METHODS

In this population-based cohort study, we analyzed 104'906 admissions for AMI between 2012 and 2018 in Switzerland. We stratified patients based on four different age categories and investigated the association of the number of five common comorbidities (diabetes, chronic kidney-, chronic obstructive pulmonary-, cerebrovascular-, and peripheral artery disease) and risk of in-hospital mortality and other outcomes.

RESULTS

A total of 5'029 admitted AMI patients (4.8%) died during the hospital stay. We found a stepwise increase in mortality risk with each additional comorbidity. Compared to AMI patients with no comorbidity, comorbid patients had a 26% increased risk for mortality (adjusted odds ratio [OR] 1.26, 95% confidence interval [CI] 1.20 to 1.33) with a pronounced association in younger patients. The overall risk for ICU admission, prolonged length of hospital stay (LOS), and 30-day readmission was higher in comorbid patients as compared to those without a comorbidity of interest (ICU: OR 1.19, 95% CI 1.16 to 1.22; LOS: OR 1.84, 95% CI 1.79 to 1.89; Readmission: OR 1.23, 95% CI 1.19 to 1.28), respectively. Again, the association of the numbers of prevalent comorbidities with adverse outcomes was strongest in the youngest patient population.

CONCLUSIONS

In patients with AMI, the burden of comorbidities has a strong association with in-hospital mortality and other adverse outcomes - especially in younger patients.

Multimorbidity among Two Million Adults in China

To explore the multimorbidity prevalence and patterns among middle-aged and older adults from China. Data on thirteen chronic diseases were collected from 2,097,150 participants aged over 45 years between January 1st 2011 and December 31st 2015 from Beijing Medical Claim Data for Employees. Association rule mining and hierarchical cluster analysis were applied to assess multimorbidity patterns. Multimorbidity prevalence was 51.6% and 81.3% in the middle-aged and older groups, respectively. The most prevalent disease pair was that of osteoarthritis and rheumatoid arthritis (OARA) with hypertension (HT) (middle-aged: 22.5%; older: 41.8%). Ischaemic heart disease (IHD), HT, and OARA constituted the most common triad combination (middle-aged: 11.0%; older: 31.2%). Among the middle-aged group, the strongest associations were found in a combination of cerebrovascular disease (CBD), OARA, and HT with IHD in males (lift = 3.49), and CBD, OARA, and COPD with IHD in females (lift = 3.24). Among older patients, glaucoma and cataracts in females (lift = 2.95), and IHD, OARA, and glaucoma combined with cataracts in males (lift = 2.45) were observed. Visual impairment clusters, a mixed cluster of OARA, IHD, COPD, and cardiometabolic clusters were detected. Multimorbidity is prevalent among middle-aged and older Chinese individuals. The observations of multimorbidity patterns have implications for improving preventive care and developing appropriate guidelines for morbidity treatment.

Prevalence of secondary care multimorbidity in mid-life and its association with premature mortality in a large longitudinal cohort study

OBJECTIVES

Multimorbidity is the coexistence of two or more health conditions in an individual. Multimorbidity in younger adults is increasingly recognised as an important challenge. We assessed the prevalence of secondary care multimorbidity in mid-life and its association with premature mortality over 15 years of follow-up, in the Aberdeen Children of the 1950s (ACONF) cohort.

METHOD

A prospective cohort study using linked electronic health and mortality records. Scottish ACONF participants were linked to their Scottish Morbidity Record hospital episode data and mortality records. Multimorbidity was defined as two or more conditions and was assessed using healthcare records in 2001 when the participants were aged between 45 and 51 years. The association between multimorbidity and mortality over 15 years of follow-up (to ages 60-66 years) was assessed using Cox proportional hazards regression. There was also adjustment for key covariates: age, gender, social class at birth, intelligence at age 7, secondary school type, educational attainment, alcohol, smoking, body mass index and adult social class.

RESULTS

Of 9625 participants (51% males), 3% had multimorbidity. The death rate per 1000 person-years was 28.4 (95% CI 23.2 to 34.8) in those with multimorbidity and 5.7 (95% CI 5.3 to 6.1) in those without. In relation to the reference group of those with no multimorbidity, those with multimorbidity had a mortality HR of 4.5 (95% CI 3.4 to 6.0) over 15 years and this association remained when fully adjusted for the covariates (HR 2.5 (95% CI 1.5 to 4.0)).

CONCLUSION

Multimorbidity prevalence was 3% in mid-life when measured using secondary care administrative data. Multimorbidity in mid-life was associated with premature mortality.

Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: A scoping review

BACKGROUND

Multimorbidity is rising in low- and middle-income countries (LMICs). However, the evidence on its epidemiology from LMICs settings is limited and the available literature has not been synthesized as yet.

OBJECTIVES

To review the available evidence on the epidemiology of multimorbidity in LMICs.

METHODS

PubMed, Scopus, PsycINFO and Grey literature databases were searched. We followed the PRISMA-ScR reporting guideline.

RESULTS

Of 33, 110 articles retrieved, 76 studies were eligible for the epidemiology of multimorbidity. Of these 76 studies, 66 (86.8%) were individual country studies. Fifty-two (78.8%) of which were confined to only six middle-income countries: Brazil, China, South Africa, India, Mexico and Iran. The majority (n = 68, 89.5%) of the studies were crosssectional in nature. The sample size varied from 103 to 242, 952. The largest proportion (n = 33, 43.4%) of the studies enrolled adults. Marked variations existed in defining and measuring multimorbidity. The prevalence of multimorbidity in LMICs ranged from 3.2% to 90.5%.

CONCLUSION AND RECOMMENDATIONS

Studies on the epidemiology of multimorbidity in LMICs are limited and the available ones are concentrated in few countries. Despite variations in measurement and definition, studies consistently reported high prevalence of multimorbidity. Further research is urgently required to better understand the epidemiology of multimorbidity and define the best possible interventions to improve outcomes of patients with multimorbidity in LMICs.

A Multicenter Study of Multimorbidity in Older Adult Inpatients in China

OBJECTIVES

Multimorbidity is common in older hospitalized adults. To date, however, few studies have addressed multimorbidity in the older population of Chinese inpatients. We aimed to investigate the multimorbidity rate and associated risk factors in older adult inpatients in China.

DESIGN, SETTING, PARTICIPANTS

This study was conducted in the medical wards of a tertiary-care hospital from. The patients were recruited aged between 60 to 101 (74.14±8.46) years.

MEASUREMENTS

Data were obtained from the China Comprehensive Geriatric Assessment Study, conducted in 2011-2012 in China. A total of 4,633 inpatients older than 60 years was recruited from 12 hospitals in 7 cities throughout China. The prevalence of comorbidity, distribution of common chronic diseases, and the associated risk factors were studied.

RESULTS

A total of 4,348 people aged 60 to 101 (74.14±8.46) years completed questionnaires. The average frequency of multimorbidity was 69.3% (95% CI, 67.9% to 70.6%). The prevalence of multimorbidity increased with age and was higher in men (71.6%; 95% CI, 69.9% to 73.3%) than in women (65.3%, 95% CI 63.0% to 67.6%), and higher in the northern region (71.7%, 95% CI 69.9% to 73.5%) than in the southern region (66.0%; 95% CI, 63.8% to 68.1%). The most frequent chronic diseases were hypertension, coronary heart disease, diabetes, cataract, and stroke. Area (OR=0.556; 95% CI, 0.465 to 0.666), region (OR=0.834; 95% CI, 0.723 to 0.962), body mass index (BMI) (OR=1.124; 95% CI, 1.017 to 1.242), and impairment of activities of daily living (OR=0.911; 95% CI, 0.855 to 0.970) were independent factors associated with multimorbidity.

CONCLUSIONS

Multimorbidity is common in older Chinese inpatients with a national prevalence of 69.3% that increases in line with age. Age, region, area, BMI, and daily activities were independent factors significantly associated with multimorbidity in older inpatients. Clinicians should therefore focus more attention on multimorbidity.