Patterns of multimorbidity and their association with health outcomes within Yorkshire, England: baseline results from the Yorkshire Health Study

Development of a brief, generic, modular resource-use measure (ModRUM): piloting with patients

BACKGROUND

Bespoke self-report resource-use measures (RUMs) are commonly developed or adapted for each new randomised controlled trial. Consequently, RUMs lack standardisation and validation is rarely conducted. A new generic RUM, ModRUM, has been developed using a rigorous process, including consultation with health economists and patients. ModRUM includes a concise core healthcare module, designed to be included in all trials, and depth-adding questions, which can replace or be added to core questions as needed. Modules covering other sectors are under development. The aim of this study was to test the acceptability, feasibility, and criterion and construct validity of the healthcare module of ModRUM.

METHODS

Patients who had a recent appointment at their GP practice were invited to complete ModRUM (core module or core module with depth questions), a characteristics form and the EQ-5D-5L. Acceptability was assessed via response rates and questionnaire completion time. Feasibility was assessed by reviewing issues observed in participants' responses and question completion rates. Construct validity was tested via hypothesis testing and known-group analyses, using Wilcoxon rank-sum and Kruskal-Wallis tests, and a generalised linear model. Criterion validity was tested by comparing ModRUM results with primary care medical records. Sensitivity, specificity, and agreement using Lin's concordance correlation coefficient (pc) were estimated.

RESULTS

One hundred patients participated from five GP practices in the South-West of England. Acceptability was higher for the core module (20% versus 10% response rate). Question completion rates were high across both versions (> 90%). Some support was observed for construct validity, with results suggesting that healthcare costs differ dependent on the number of long-term conditions (p < 0.05) and are negatively associated with health-related quality of life (p < 0.01). Sensitivity was high for all questions (> 0.83), while specificity varied (0.33-0.88). There was a good level of agreement for GP contacts and costs, and prescribed medication costs (pc > 0.6).

CONCLUSION

This study provided preliminary evidence of the acceptability, feasibility, and criterion and construct validity of ModRUM. Further testing is required within trials and with groups that were less well represented in this study.

Prevalence of comorbidities and its associated factors among type-2 diabetes patients: a hospital-based study in Jashore District, Bangladesh

OBJECTIVE

This study aimed to estimate the prevalence of comorbidity and its associated factors among Bangladeshi type-2 diabetes (T2D) patients.

DESIGN

A hospital-based cross-sectional study.

SETTING

This study was conducted in two specialised diabetic centres residing in the Jashore District of Bangladesh. A systematic random sampling procedure was applied to identify the T2D patients through a face-to-face interview.

PARTICIPANTS

A total of 1036 patients with T2D were included in this study. A structured questionnaire was administered to collect data on demographic, lifestyle, medical and healthcare access-related data through face-to-face and medical record reviews.

OUTCOME MEASURES AND ANALYSES

The main outcome variable for this study was comorbidities. The prevalence of comorbidity was measured using descriptive statistics. A logistic regression model was performed to explore the factors associated with comorbidity among Bangladeshi T2D patients.

RESULTS

The overall prevalence of comorbidity was 41.4% and the most prevalent conditions were hypertension (50.4%), retinopathy (49.6%), obesity (28.7%) and oral problem (26.2). In the regression model, the odds of comorbidities increased with gender (male: OR: 1.27, 95% CI 0.62 to 1.87), age (50-64 years: OR: 2.14, 95% CI 1.32 to 2.93; and above 65 years: OR: 2.96, 95% CI 1.83 to 4.16), occupation (unemployment: OR: 3.32, 95% CI 0.92 to 6.02 and non-manual worker: OR: 2.31, 95% CI 0.91 to 5.82), duration of diabetes (above 15 years: OR: 3.28, 95% CI 1.44 to 5.37), body mass index (obese: OR: 2.62, 95% CI 1.24 to 4.26) of patients. We also found that individuals with recommended moderate to vigorous physical activity levels (OR: 0.41, 95% CI 1.44 to 5.37) had the lowest odds of having comorbidity. Meanwhile, respondents with limited self-care practice, unaffordable medicine and financial problems had 1.82 times, 1.94 times and 1.86 times higher odds of developing comorbidities.

CONCLUSION

The findings could be useful in designing and implementing effective intervention strategies and programmes for people with T2D to reduce the burden of comorbidity.

Ethnic inequalities in multiple long-term health conditions in the United Kingdom: a systematic review and narrative synthesis

Indicative evidence suggests that minoritised ethnic groups have higher risk of developing multiple long-term conditions (MLTCs), and do so earlier than the majority white population. While there is evidence on ethnic inequalities in single health conditions and comorbidities, no review has attempted to look across these from a MLTCs perspective. As such, we currently have an incomplete understanding of the extent of ethnic inequalities in the prevalence of MLTCs. Further, concerns have been raised about variations in the way ethnicity is operationalised and how this impedes our understanding of health inequalities. In this systematic review we aimed to 1) describe the literature that provides evidence of ethnicity and prevalence of MLTCs amongst people living in the UK, 2) summarise the prevalence estimates of MLTCs across ethnic groups and 3) to assess the ways in which ethnicity is conceptualised and operationalised. We focus on the state of the evidence prior to, and during the very early stages of the pandemic. We registered the protocol on PROSPERO (CRD42020218061). Between October and December 2020, we searched ASSIA, Cochrane Library, EMBASE, MEDLINE, PsycINFO, PubMed, ScienceDirect, Scopus, Web of Science, OpenGrey, and reference lists of key studies/reviews. The main outcome was prevalence estimates for MLTCs for at least one minoritised ethnic group, compared to the majority white population. We included studies conducted in the UK reporting on ethnicity and prevalence of MLTCs. To summarise the prevalence estimates of MLTCs across ethnic groups we included only studies of MLTCs that provided estimates adjusted at least for age. Two reviewers screened and extracted data from a random sample of studies (10%). Data were synthesised using narrative synthesis. Of the 7949 studies identified, 84 met criteria for inclusion. Of these, seven contributed to the evidence of ethnic inequalities in MLTCs. Five of the seven studies point to higher prevalence of MLTCs in at least one minoritised ethnic group compared to their white counterparts. Because the number/types of health conditions varied between studies and some ethnic populations were aggregated or omitted, the findings may not accurately reflect the true level of ethnic inequality. Future research should consider key explanatory factors, including those at the macrolevel (e.g. racism, discrimination), as they may play a role in the development and severity of MLTCs in different ethnic groups. Research is also needed to ascertain the extent to which the COVID19 pandemic has exacerbated these inequalities.

Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): An exploratory analysis of a longitudinal smartwatch feasibility study

Introduction

People living with multiple long-term conditions (MLTC-M) (multimorbidity) experience a range of inter-related symptoms. These symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices, and then summarised to provide useful clinical insight.

Aim

We aimed to perform an exploratory analysis to summarise the extent and trajectory of multiple symptom ratings tracked via a smartwatch, and to investigate the relationship between these symptom ratings and demographic factors in people living with MLTC-M in a feasibility study.

Methods

'Watch Your Steps' was a prospective observational feasibility study, administering multiple questions per day over a 90 day period. Adults with more than one clinician-diagnosed long-term condition rated seven core symptoms each day, plus up to eight additional symptoms personalised to their LTCs per day. Symptom ratings were summarised over the study period at the individual and group level. Symptom ratings were also plotted to describe day-to-day symptom trajectories for individuals.

Results

Fifty two participants submitted symptom ratings. Half were male and the majority had LTCs affecting three or more disease areas (N = 33, 64%). The symptom rated as most problematic was fatigue. Patients with increased comorbidity or female sex seemed to be associated with worse experiences of fatigue. Fatigue ratings were strongly correlated with pain and level of dysfunction.

Conclusion

In this study we have shown that it is possible to collect and descriptively analyse self reported symptom data in people living with MLTC-M, collected multiple times per day on a smartwatch, to gain insights that might support future clinical care and research.

Differentials in Health and Wellbeing in Older Adults with Obesity in England: A Cross-Sectional Analysis Using the English Longitudinal Study of Ageing

The aim of the study is to explore the association of obesity by body mass index (BMI) measurements with subjective health status (SHS), objective health status (OHS) and wellbeing status among older adults in England. The sample of 5640 participants (aged 50 years and over) are considered from the English Longitudinal Study of Ageing Wave 8 dataset. Multivariate logistic regression analysis is performed to explore the cross-sectional relationship of the study variables. The statistical analyses explored those overweight and obese older adults are progressively vulnerable to increasing odds of poor SHS, OHS and poor wellbeing in an adjusted model compared to their normal-weight counterparts. The outcome of the present study would enable policymakers and healthcare providers to have greater insight into the effects of socio-demographic and lifestyle factors and the effect of high BMI on older adults’ health and wellbeing.

Multimorbidity is associated with the income, education, employment and health domains of area-level deprivation in adult residents in the UK

Evidence suggests that there are social inequalities in multimorbidity, with a recent review indicating that area levels of deprivation are consistently associated with greater levels of multimorbidity. Definitions of multimorbidity, the most common of which is the co-occurrence of more than one long term condition, can include long term physical conditions, mental health conditions or both. The most commonly used measure of deprivation in England and Wales is the Index of Multiple Deprivation (IMD), an index of seven different deprivation domains. It is unclear which features of IMD may be mediating associations with multimorbidity. Thus, there may be associations because of the individual characteristics of those living in deprived areas, characteristics of the areas themselves or overlap in definitions. Data from over 25,000 participants (aged 16+) of Understanding Society (Wave 10, 1/2018–3/2020) were used to understand the most salient features of multimorbidity associated with IMD and whether physical or mental conditions are differentially associated with the seven domains of IMD. 24% of participants report multimorbidity. There is an increased prevalence of multimorbidity composed of only long-term physical conditions in the most deprived decile of deprivation (22%, 95% CI[19,25]) compared to the least deprived decile (16%, 95% CI[14,18]). Mental health symptoms but not reporting of conditions vary by decile of IMD. Associations with multimorbidity are limited to the health, income, education and employment domains of IMD. We conclude that multimorbidity represents a substantial population burden, particularly in the most deprived areas in England and Wales.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Inequalities in the progress of multiple chronic conditions: A systematic review of longitudinal studies

The objective of this review is to assess the impact of socioeconomic factors on the progress of multiple chronic health conditions (MCC) in Adults. Two independent investigators searched three databases (MEDLINE, EMBASE and LILACS) up to August 2021 to identify longitudinal studies on inequalities in progress of MCC. Grey literature was searched using Open Grey and Google Scholar. Inclusion criteria were retrospective and prospective longitudinal studies; adult population; assessed socioeconomic inequalities in progress of MCC. Quality of included studies and risk of bias were assessed using the Newcastle Ottawa Quality Assessment Scale for longitudinal studies. Nine longitudinal studies reporting socioeconomic inequalities in progress of MCC were included. Two of the studies had poor quality. Studies varied in terms of follow-up time, sample size, included chronic conditions and socioeconomic indicators. Due to high heterogeneity meta-analysis was not possible. The studies showed positive association between lower education (five studies), lower income and wealth (two studies), area deprivation (one study), lower job categories (two studies) and belonging to ethnic minority (two study) and progress of MCC. The review demonstrated socioeconomic inequality in progress of multiple chronic conditions.

trial registratiom: The review protocol was registered in the International Prospective Register of Systematic Reviews (CRD42021229564).

Ethnic variation, socioeconomic status, and factors associated with cardio-metabolic multi-morbidity among uncontrolled hypertension in multiethnic Singapore

Identifying patients with hypertension at high risk of cardio-metabolic multi-morbidity (CMM) is key for intervention. We examined the independent association of CMM with ethnicity and socioeconomic status (SES) among patients with uncontrolled hypertension. Demographic, socioeconomic, lifestyle, and clinical factors were obtained from 921 patients aged ≥40 years with hypertension in the multiethnic Singapore. CMM was defined as having ≥2 chronic diseases (diabetes mellitus, heart disease, stroke, and chronic kidney disease), which were confirmed by medical records or laboratory measurements. The overall CMM prevalence was 20.9% (95% confidence interval [CI]: 18.4-23.6%). The CMM prevalence was higher in Malays (27.1%) and Indians (30.2%) than Chinese (18.8%), and it was higher among patients with lower SES (ranging from 21.3 to 23.9% using education, employment status, housing ownership and housing types as proxies) compared to those with higher SES (13.1-20.8%). In a multivariate model comprising demographic and socioeconomic factors (age, sex, ethnicity and SES), higher CMM odds were independently associated with ethnic minorities (Malays [OR 1.81; 95% CI: 1.10-2.98] or Indians [OR 2.21; 95% CI: 1.49-3.29] vs. Chinese) and lower SES (unemployment [OR 1.45; 95% CI: 1.02-2.05] and residing in smaller public housing [OR 1.95; 95% CI: 1.16-3.28]). Other correlates of CMM included age, men, central obesity, and poorer dietary quality (lower fruits and vegetables intakes). CMM affected one out of five patients with hypertension in Singapore. Intervention programs should target patients with hypertension, particularly those of ethnic minorities and from lower socioeconomic strata.

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

Background

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

Aim

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

Design and setting

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

Method

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

Results

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

Conclusion

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

Role of social support in the relationship between financial hardship and multimorbidity-a causal mediation analysis

BACKGROUND

Social disadvantage is a key determinant of multimorbidity. Pathways through which social disadvantage leads to multimorbidity are yet undefined. In this study, we first examined the causal effect of moving into financial hardship on multimorbidity among Australian adults, and then the role of social support as a mediator of the relationship between financial hardship and multimorbidity.

METHODS

Data were obtained from the Household, Income and Labour Dynamics in Australia (HILDA) Survey (2009-2013). We identified individuals who moved into financial hardship between 2010 and 2011 (n = 5775). Inverse probability treatment weighting with regression adjustment was used to examine the relationship between financial hardship and multimorbidity. Causal mediation analysis was applied to decompose the total effect of financial hardship on multimorbidity into the proportion attributable to social support and the proportion not occurring through measured pathways. We accounted for baseline covariates including age, sex, marital status, educational attainment, employment status, income, country of birth, multimorbidity and social support. Bootstrapping with 1000 replications was used to calculate 95% confidence intervals (CIs).

RESULTS

The risk of multimorbidity was higher in those with financial hardship by 19% [relative risk 1.19 (95% CI: 1.02-1.37) and absolute risk difference 0.036 (95% CI: 0.004-0.067)] than those without financial hardship. Social support accounted for 30% of the total effect of financial hardship on multimorbidity, risk difference 0.009 (95% CI: 0.003-0.018).

CONCLUSIONS

Financial hardship leads to increased risk of multimorbidity. Interventions directed at increasing social support among those in financial hardship may reduce their risk of multimorbidity.

Assessing polypharmacy in the older population: Comparison of a self-reported and prescription based method

PURPOSE

To explore differences in the prevalence and determinants of polypharmacy in the older general population in Belgium between self-reported and prescription based estimates and assess the relative merits of each data source.

METHODS

Data were used from participants aged ≥65 years of the Belgian national health survey 2013 (n = 1950). Detailed information was asked on the use of medicines in the past 24 h and linked with prescription data from the Belgian compulsory health insurance (BCHI). Agreement between polypharmacy (use or prescription ≥5 medicines) and excessive polypharmacy (≥10 medicines) between both sources was assessed with kappa statistics. Multinomial logistic regression was used to study determinants of moderate (5-9 medicines) and excessive polypharmacy (≥10 medicines) and over- and underestimation of prescription based compared to self-reported polypharmacy.

RESULTS

Self-reported and prescription based polypharmacy prevalence estimates were respectively 27% and 32%. Overall agreement was moderate, but better in men (kappa 0.60) than in women (0.45). Determinants of moderate polypharmacy did not vary substantially by source of outcome indicator, but restrictions in activities of daily living (ADL), living in an institution and a history of a hospital admission was associated with self-reported based excessive polypharmacy only.

CONCLUSIONS

Surveys and prescription data measure polypharmacy from a different perspective, but overall conclusions in terms of prevalence and determinants of polypharmacy do not differ substantially by data source. Linking survey data with prescription data can combine the strengths of both data sources resulting in a better tool to explore polypharmacy at population level.

Systematic review on the instruments used for measuring the association of the level of multimorbidity and clinically important outcomes

OBJECTIVES

There are multiple instruments for measuring multimorbidity. The main objective of this systematic review was to provide a list of instruments that are suitable for use in studies aiming to measure the association of a specific outcome with different levels of multimorbidity as the main independent variable in community-dwelling individuals. The secondary objective was to provide details of the requirements, strengths and limitations of these instruments, and the chosen outcomes.

METHODS

We conducted the review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO registration number: CRD42018105297). We searched MEDLINE, Embase and CINAHL electronic databases published in English and manually searched the Journal of Comorbidity between 1 January 2010 and 23 October 2020 inclusive. Studies also had to select adult patients from primary care or general population and had at least one specified outcome variable. Two authors screened the titles, abstracts and full texts independently. Disagreements were resolved with a third author. The modified Newcastle-Ottawa Scale was used for quality assessment.

RESULTS

Ninety-six studies were identified, with 69 of them rated to have a low risk of bias. In total, 33 unique instruments were described. Disease Count and weighted indices like Charlson Comorbidity Index were commonly used. Other approaches included pharmaceutical-based instruments. Disease Count was the common instrument used for measuring all three essential core outcomes of multimorbidity research: mortality, mental health and quality of life. There was a rise in the development of novel weighted indices by using prognostic models. The data obtained for measuring multimorbidity were from sources including medical records, patient self-reports and large administrative databases.

CONCLUSIONS

We listed the details of 33 instruments for measuring the level of multimorbidity as a resource for investigators interested in the measurement of multimorbidity for its association with or prediction of a specific outcome.

Trajectories of healthy ageing among older adults with multimorbidity: A growth mixture model using harmonised data from eight ATHLOS cohorts

Objectives

In this study we aimed to 1) describe healthy ageing trajectory patterns, 2) examine the association between multimorbidity and patterns of healthy ageing trajectories, and 3) evaluate how different groups of diseases might affect the projection of healthy ageing trajectories over time.

Setting and participants

Our study was based on 130880 individuals from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) harmonised dataset, as well as 9171 individuals from Waves 2–7 of the English Longitudinal Study of Ageing (ELSA).

Methods

Using a healthy ageing index score, which comprised 41 items, covering various domains of health and ageing, as outcome, we employed the growth mixture model approach to identify the latent classes of individuals with different healthy ageing trajectories. A multinomial logistic regression was conducted to assess if and how multimorbidity status and multimorbidity patterns were associated with changes in healthy ageing, controlled for sociodemographic and lifestyle risk factors.

Results

Three similar patterns of healthy ageing trajectories were identified in the ATHLOS and ELSA datasets: 1) a ‘high stable’ group (76% in ATHLOS, 61% in ELSA), 2) a ‘low stable’ group (22% in ATHLOS, 36% in ELSA) and 3) a ‘rapid decline’ group (2% in ATHLOS, 3% in ELSA). Those with multimorbidity were 1.7 times (OR = 1.7, 95% CI: 1.4–2.1) more likely to be in the ‘rapid decline’ group and 11.7 times (OR = 11.7 95% CI: 10.9–12.6) more likely to be in the ‘low stable’ group, compared with people without multimorbidity. The cardiorespiratory/arthritis/cataracts group was associated with both the ‘rapid decline’ and the ‘low stable’ groups (OR = 2.1, 95% CI: 1.2–3.8 and OR = 9.8, 95% CI: 7.5–12.7 respectively).

Conclusion

Healthy ageing is heterogeneous. While multimorbidity was associated with higher odds of having poorer healthy ageing trajectories, the extent to which healthy ageing trajectories were projected to decline depended on the specific patterns of multimorbidity.

Household and area-level social determinants of multimorbidity: a systematic review

BACKGROUND

No clear synthesis of evidence examining household and area-level social determinants of multimorbidity exists. This study aimed to systematically review the existing literature on associations between household and area-level social determinants of health (SDoH) and multimorbidity prevalence or incidence in the general population.

METHODS

Six databases (MedLine, EMBASE, PsychINFO, Web of Science, CINAHL Plus and Scopus) were searched. The search was limited to peer-reviewed studies conducted in high-income countries and published in English between 2010 and 2019. A second reviewer screened all titles with abstracts and a subset of full texts. Study quality was assessed and protocol pre-registered (CRD42019135281).

RESULTS

41 studies spanning North America, Europe and Australasia were included. Household income and area-level deprivation were the most explored with fairly consistent findings. The odds of multimorbidity were up to 4.4 times higher for participants with the lowest level of income compared with the highest level. Those living in the most deprived areas had the highest prevalence or incidence of multimorbidity (pooled OR 1.42, 95% CI 1.41 to 1.42). Associations between deprivation and multimorbidity differed by age and multimorbidity type. Findings from the few studies investigating household tenure, household composition and area-level rurality were mixed and contradictory; homeownership and rurality were associated with increased and decreased multimorbidity, while living alone was found to be associated with a higher risk of multimorbidity and not associated.

CONCLUSION

Improving our understanding of broader social determinants of multimorbidity-particularly at the household level-could help inform strategies to tackle multimorbidity.

At-risk population for COVID-19: multimorbidity characteristics of a European small Island state

OBJECTIVES

Multimorbidity, defined as the co-occurrence of at least two chronic diseases, is a common occurrence with ageing and a recognised public health concern, especially during the COVID-19 pandemic. The multimorbidity population is more susceptible to the virus, its complications, and death. The study aimed to explore the multimorbidity characteristics and their associations at a population level for the first time in Malta. Such data enables adequate priority and policy planning due to COVID-19's predilection for this population.

STUDY AND METHODS

Baseline data was collected from 3,947 adults recruited between 2014-2016 through a cross-sectional study. A single-stage sampling strategy was implemented and stratified by age (18 -70 years), sex and locality. Participants were invited to attend a health examination survey consisting of a questionnaire, anthropometric and biological measurements. Descriptive (chi-square) and analytic (regression modelling) statistics were used to determine the characteristics and associations of the multimorbidity population. The chronic diseases considered for multimorbidity were type 2 diabetes, obesity, hypertension, myocardial infraction, coronary heart disease and dyslipidaemia.

RESULTS

Multimorbidity was present in 33% (95% confidence interval 31.54-34.47) of the study population, with a male predominance. Hypertension and myocardial infarction were the commonest multimorbidity combination from a young age group (20-30 years). Low socio-economic status and residing on the island of Gozo were positively associated with multimorbidity.

CONCLUSION

Multimorbidity in Malta was evident from a young age, with the highest occurrence among the low socio-economic status and residents of Gozo, bringing forward the need for preventive action. An adaptive healthcare system and policies are recommended to prevent, support, and manage multimorbidity non-communicable diseases while bracing for the current COVID-19 pandemic.

Health-Related Quality of Life and Health Service Use among Multimorbid Middle-Aged and Older-Aged Adults in China: A Cross-Sectional Study in Shandong Province

(1) Background: The management of multiple chronic diseases challenges China's health system, but current research has neglected how multimorbidity is associated with poor health-related quality of life (HRQOL) and high health service demands by middle-aged and older adults. (2) Methods: A cross-sectional study was conducted in Shandong province, China in 2018 across three age groups: Middle-aged (45 to 59 years), young-old (60 to 74 years), and old-old (75 or above years). The information about socio-economic, health-related behaviors, HRQOL, and health service utilization was collected via face-to-face structured questionnaires. The EQ-5D-3L instrument, comprising a health description system and a visual analog scale (VAS), was used to measure participants' HRQOL, and χ² tests and the one-way ANOVA test were used to analyze differences in socio-demographic factors and HRQOL among the different age groups. Logistic regression models estimated the associations between lifestyle factors, health service utilization, and multimorbidity across age groups. (3) Results: There were 17,867 adults aged 45 or above in our sample, with 9259 (51.82%) female and 65.60% living in rural areas. Compared with the middle-aged adults, the young-old and old-old were more likely to be single and to have a lower level of education and income, with the old-old having lower levels than the young-old (P < 0.001). We found that 2465 (13.80%) suffered multimorbidities of whom 75.21% were older persons (aged 60 or above). As age increased, both the mean values of EQ-5D utility and the VAS scale decreased, displaying an inverse trend to the increase in the number of chronic diseases (P < 0.05). Ex-smokers and physical check-ups for middle or young-old respondents and overweight/obesity for all participants (P < 0.05) were positively correlated with multimorbidity. Drinking within the past month for all participants (P < 0.001), and daily tooth-brushing for middle (P < 0.05) and young-old participants (P < 0.001), were negatively associated with multimorbidity. Multimorbidities increased service utilization including outpatient and inpatient visits and taking self-medicine; and the probability of health utilization was the lowest for the old-old multimorbid patients (P < 0.001). (4) Conclusions: The prevalence and decline in HRQOL of multimorbid middle-aged and older-aged people were severe in Shandong province. Old patients also faced limited access to health services. We recommend early prevention and intervention to address the prevalence of middle-aged and old-aged multimorbidity. Further, the government should set-up special treatment channels for multiple chronic disease sufferers, improve medical insurance policies for the older-aged groups, and set-up multiple chronic disease insurance to effectively alleviate the costs of medical utilization caused by economic pressure for outpatients and inpatients with chronic diseases.

Role of clinical, functional and social factors in the association between multimorbidity and quality of life: Findings from the Survey of Health, Ageing and Retirement in Europe (SHARE)

OBJECTIVE

An increasing number of diseases is linked to deterioration of quality of life (QoL). Part of this association can be explained by socio-economic factors, which are most commonly accounted for. Our aim was to explore the potential contribution of other factors related to clinical burden, social interaction and functioning.

METHODS

A cross-sectional analysis was conducted on wave 6 of the population-based Survey of Health, Ageing and Retirement in Europe (SHARE), among participants aged 50+ (n = 67 179). The Control, Autonomy, Self-Realization and Pleasure (CASP-12v1) questionnaire measured QoL. The association between number of diseases and QoL was tested in a mixed-effects linear regression model. The base model controlled for socio-economic characteristics. Factors of interest (symptoms, polypharmacy, unmet care needs, utilisation of care, social network, personal and financial help, loneliness and activities of daily living (ADL) with instrumental activities (IADL)) were added to the base model one at a time and tested for relevance (i.e. change in the β-coefficient of the number of conditions of 15% or more).

RESULTS

Symptoms, polypharmacy, loneliness and ADL/IADL appeared relevant and were retained in the final model. The association between number of conditions and QoL in the base model was -2.44 [95% CI: -2.72; -2.16], while this association was -0.76 [95%CI: -0.97; -0.54] after all relevant factors were included.

CONCLUSION

Factors beyond the socio-economic circumstances play an important role in explaining the association between number of conditions and QoL. These factors should be considered to better estimate the impact of chronic diseases on QoL, and for improving patient care.

Cost-effectiveness of a patient-centred approach to managing multimorbidity in primary care: a pragmatic cluster randomised controlled trial

OBJECTIVE

Patients with multiple chronic health conditions are often managed in a disjointed fashion in primary care, with annual review clinic appointments offered separately for each condition. This study aimed to determine the cost-effectiveness of the 3D intervention, which was developed to improve the system of care.

DESIGN

Economic evaluation conducted alongside a pragmatic cluster-randomised trial.

SETTING

General practices in three centres in England and Scotland.

PARTICIPANTS

797 adults with three or more chronic conditions were randomised to the 3D intervention, while 749 participants were randomised to receive usual care.

INTERVENTION

The 3D approach: comprehensive 6-monthly general practitioner consultations, supported by medication reviews and nurse appointments.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary economic evaluation assessed the cost per quality-adjusted life year (QALY) gained from the perspective of the National Health Service (NHS) and personal social services (PSS). Costs were related to changes in a range of secondary outcomes (QALYs accrued by both participants and carers, and deaths) in a cost-consequences analysis from the perspectives of the NHS/PSS, patients/carers and productivity losses.

RESULTS

Very small increases were found in both QALYs (adjusted mean difference 0.007 (-0.009 to 0.023)) and costs (adjusted mean difference £126 (£-739 to £991)) in the intervention arm compared with usual care after 15 months. The incremental cost-effectiveness ratio was £18 499, with a 50.8% chance of being cost-effective at a willingness-to-pay threshold of £20 000 per QALY (55.8% at £30 000 per QALY).

CONCLUSIONS

The small differences in costs and outcomes were consistent with chance, and the uncertainty was substantial; therefore, the evidence for the cost-effectiveness of the 3D approach from the NHS/PSS perspective should be considered equivocal.

TRIAL REGISTRATION NUMBER

ISCRTN06180958.

Specific Measures of Quality of Life in Patients with Multimorbidity in Primary Healthcare: A Systematic Review on Patient-Reported Outcome Measures' Adequacy of Measurement

Purpose

The aim of this study is to search systematically for Patient Reported Outcome Measures (PROMs) used among patients with multimorbidity. Furthermore, the aim is to evaluate the adequacy and validity of the PROMs identified.

Design and setting

This systematic review follows the PRISMA guidelines. To assess the adequacy and validity of the identified PROMs the COSMIN Risk of Bias Checklist is used, more specifically a validation of the development, content validity, structural validity, and internal consistency of the PROMs.

Results

Four PROMs were identified in the primary search, and one was found from references. The sixth PROM was published after the primary search. None of the identified PROMs were aimed specifically at measuring the quality of life in patients with multimorbidity. According to the checklist, the development process and content validity were rated “adequate” in only one measure and “invalid”/“doubtful”/“inadequate” in the rest of the measures. The structural validity of the measures was rated “adequate” in four measures and “very good” in one. Regarding the internal consistency, two measures were rated doubtful and three “very good”. None of the six PROMs reported analyses about invariant measurement. The COSMIN Risk of Bias Checklist proved easy to use; however, there are some concerns in the rating of bias, that are discussed further.

Conclusion

All six PROMs developed for patients with multimorbidity identified possessed inadequacy in their measurement properties. Therefore, the aim for the future is to develop a valid and adequate measure of the quality of life among patients with multimorbidity.

Bayesian Hierarchical Models for Meta-Analysis of Quality-of-Life Outcomes: An Application in Multimorbidity

BACKGROUND

Health-related quality of life (HRQoL) is a key outcome in cost-utility analyses, which are commonly used to inform healthcare decisions. Different instruments exist to evaluate HRQoL, however while some jurisdictions have a preferred system, no gold standard exists. Standard meta-analysis struggles with the variety of outcome measures, which may result in the exclusion of potentially relevant evidence.

OBJECTIVE

Using a case study in multimorbidity, the objective of this analysis is to illustrate how a Bayesian hierarchical model can be used to combine data across different instruments. The outcome of interest is the slope relating HRQoL to the number of coexisting conditions.

METHODS

We propose a three-level Bayesian hierarchical model to systematically include a large number of studies evaluating HRQoL using multiple instruments. Random effects assumptions yield instrument-level estimates benefitting from borrowing strength across the evidence base. This is particularly useful where little evidence is available for the outcome of choice for further evaluation.

RESULTS

Our analysis estimated a reduction in quality of life of 3.8-4.1% per additional condition depending on HRQoL instrument. Uncertainty was reduced by approximately 80% for the instrument with the least evidence.

CONCLUSION

Bayesian hierarchical models may provide a useful modelling approach to systematically synthesize data from HRQoL studies.

Prevalence of multimorbidity among Bangladeshi adult population: a nationwide cross-sectional study

OBJECTIVE

This study aimed to report prevalence and evaluate the association between multimorbidity and associated risk factors in the adult population of Bangladesh.

DESIGN

A cross-sectional study was conducted using a multistage clustered random sampling strategy.

SETTING

The study was conducted among the general population of 58 districts in Bangladesh.

PARTICIPANTS

A total of 12 338 male and female individuals aged ≥35 were included for analysis in this study. Identified through a household listing conducted prior to the study, from 15 297 individuals meeting the inclusion criteria, 12 338 participants were included based on availability during data collection, consent and health condition.

OUTCOME MEASURES

Multimorbidity in terms of hypertension, diabetes, cancer, cardiovascular diseases, stroke and chronic obstructive pulmonary disease.

RESULTS

Approximately 8.4% (95% CI 7.0 to 9.7) of individuals suffer from multimorbidity, of which hypertension accounted for (30.1%) followed by diabetes (10.6%). The mean age of the population was 58.6 (SD ±9.2) years. The prevalence of multimorbidity was lower among men (7.7%) compared with women (8.9%). The likelihood of having multimorbidity among obese individuals were more than double than people with normal body mass index (BMI). Physical activity protected individuals from developing multimorbidity: however, the physical activity adjusted OR was 0.5 (95% CI 0.2 to 1.2). After adjusting for all covariates, higher age, higher educational status, economic status, and higher BMI were found to be significantly associated with the odds of developing multimorbidity, with an overall adjusted OR of 0.02 (95% CI 0.01 to 0.02).

CONCLUSION

This study reported a high prevalence of multimorbidity in Bangladesh, although it explored the burden and identified risk factors considering only six chronic diseases. Further detailed exploration through longitudinal studies considering a wider range of diseases is needed to document the actual burden, develop effective preventive measures and clinical guidelines to improve the quality of life of the population.

Modeling the Economic Impact of Interventions for Older Populations with Multimorbidity: A Method of Linking Multiple Single-Disease Models

Introduction. Individuals from older populations tend to have more than 1 health condition (multimorbidity). Current approaches to produce economic evidence for clinical guidelines using decision-analytic models typically use a single-disease approach, which may not appropriately reflect the competing risks within a population with multimorbidity. This study aims to demonstrate a proof-of-concept method of modeling multiple conditions in a single decision-analytic model to estimate the impact of multimorbidity on the cost-effectiveness of interventions. Methods. Multiple conditions were modeled within a single decision-analytic model by linking multiple single-disease models. Individual discrete event simulation models were developed to evaluate the cost-effectiveness of preventative interventions for a case study assuming a UK National Health Service perspective. The case study used 3 diseases (heart disease, Alzheimer's disease, and osteoporosis) that were combined within a single linked model. The linked model, with and without correlations between diseases incorporated, simulated the general population aged 45 years and older to compare results in terms of lifetime costs and quality-adjusted life-years (QALYs). Results. The estimated incremental costs and QALYs for health care interventions differed when 3 diseases were modeled simultaneously (£840; 0.234 QALYs) compared with aggregated results from 3 single-disease models (£408; 0.280QALYs). With correlations between diseases additionally incorporated, both absolute and incremental costs and QALY estimates changed in different directions, suggesting that the inclusion of correlations can alter model results. Discussion. Linking multiple single-disease models provides a methodological option for decision analysts who undertake research on populations with multimorbidity. It also has potential for wider applications in informing decisions on commissioning of health care services and long-term priority setting across diseases and health care programs through providing potentially more accurate estimations of the relative cost-effectiveness of interventions.

Multimorbidity and quality of life: Systematic literature review and meta-analysis

Multimorbidity is typically defined as the co-existence of two or more chronic diseases within an individual. Its prevalence is highest among the elderly, with poor quality of life (QoL) being one of the major consequences. This study aims to: (1) understand the relationship between multimorbidity and QoL or health-related quality of life (HRQoL) through systematic literature review; (2) explore the strength of this association by conducting the first meta-analysis on the subject. Following PRISMA, Medline/PubMed, Embase, CINAHL and PsycINFO were searched for studies published through September 1st, 2018. Original studies with clear operationalization of multimorbidity and validated QoL (or HRQoL) measurement were retained. For random-effect meta-analysis, a minimum of three studies with the same multimorbidity tool (e.g. number of diseases or equal comorbidity index) and the same QoL tool were required. Number of diseases was most common and the only measure on which meta-analysis was carried out. The outcome of interest was the linear regression slope between increasing number of diseases and QoL. Heterogeneity was explored with meta-regression. Out of 25,890 studies initially identified, 74 studies were retained for systematic review (total of 2,500,772 participants), of which 39 were included in the meta-analysis. The mean decrease in HRQoL per each added disease, depending on the scale, ranged from: -1.55% (95%CI: -2.97%, -0.13%) for the mental component summary score of pooled SF-36, -12 and -8 scales to -4.37% (95%CI: -7.13%, -1.61%) for WHOQoL-BREF physical health domain. Additional studies considering severity, duration and patterns of diseases are required to further clarify this association.

Multimorbidity and health seeking behaviours among older people in Myanmar: A community survey

BACKGROUND

The world population is aging very rapidly and the impact is more severe in developing countries because of insufficient resources and low awareness of the challenges faced by older people. This study aimed to explore multimorbidity of older people in Myanmar and their health seeking behaviours.

METHODS

A community-based cross-sectional study was conducted in both urban and rural areas of Bago Region and Mon State during October 2016. A multistage sampling method was used to select 4,859 people aged 60 years and older. Participants were interviewed face-to-face using a questionnaire. Multinominal logistic regression was used to analyse data.

RESULTS

More than half of the study participants (57.9%) reported at least one chronic condition in the last year and 33.2% reported two or more conditions (multimorbidity). The common conditions were hypertension (67.3%), arthritis (24.7%), arrhythmia (14.7%), coronary heart disease (13.8%) and diabetes (13.7%). A majority (61.7%) of participants with a chronic condition took western medicine. Older people usually saw a doctor (60.2%) or health assistant (21.9%) at a nearby clinic or rural health center; 1.6% reported seeing uncredentialed medical persons. Factors associated with multimorbidity were being female (adjusted Prevalence Ratio (aPR) = 2.14, 95% confidence interval (CI) 1.63-2.82) and having fair (aPR = 2.20, 95% CI 1.59-3.04) or poor self-reported health (aPR = 3.93, 95% CI 2.79-5.52). Those with less than middle school education (aPR = 0.50, 95% CI 0.25-0.99) and those living in rural areas (aPR = 0.78, 95% CI 0.62-0.98) were less likely to have multimorbidity. Older people in rural areas had less access to health care than their urban counterparts.

CONCLUSION

Chronic conditions are common among older people in Myanmar, with higher prevalence in women and in urban areas. The lower prevalence of chronic conditions in those who live in rural areas may be related to living a more traditional lifestyle.

The association between multimorbidity and health-related quality of life: a cross-sectional survey among community middle-aged and elderly residents in southern China

BACKGROUND

Multimorbidity is common among the middle-aged and elderly residents. And it is associated to the reduction of health-related quality of life (HRQoL), including physical and psychological dimensions. However, there are few studies that have paid attention to the HRQoL of residents with multimorbidity in China. Therefore, this study aims to investigate the relationships between different multimorbidity patterns and HRQoL among middle-aged and elderly adults in China.

METHODS

Based on a cross-sectional survey, the information regarding 18,137 adults, who were at least 45 years of age, was collected through interviews. Self-perceived HRQoL was assessed with the EQ-5D-3 L instrument, and the EQ-5D-3 L index score was calculated using the Chinese EQ-5D-3 L value set. The Tobit regression was used to explore the impacts of multimorbidity groups on HRQoL.

RESULTS

Of 18,137 respondents, more than a fifth (3773,20.8%) of people had multimorbidity. Mean (SD) of EQ-5D index and VAS values were 0.95(0.14) and 76.02(13.66), respectively. Significant correlations were found between a lower HRQoL and increasing numbers of chronic conditions (P < 0.001). Most of chronic diseases co-occurred frequently, and the association between hypertension and diabetes mellitus was the strongest (adjusted OR = 3.82). The most prevalent disease is hypertension (5052,27.9%), and the most prevalent chronic diseases pair is hypertension and diabetes mellitus (841,4.6%). Among those chronic diseases with high prevalence, the effects on HRQoL ranged from chronic pain to hypertension (adjust b = - 0.036 to - 0.008). In the common multimorbidity patterns, co-occurrence of chronic pain and bone disease (adjust b = - 0.039) had the greatest impact on HRQoL.

CONCLUSIONS

The HRQoL of middle-aged and elderly adults declines by multimorbidity. More attention should be paid to the HRQoL of residents with multimorbidity in China. The effect of different multimorbidity patterns on HRQoL is not simply added by two diseases, but changes by the different combination. Identifying different multimorbidity patterns of residents can provide more targeted measures to improve the HRQoL.

Prevalence and correlates of multimorbidity among adults in border areas of the Central Highland Region of Vietnam, 2017

Introduction:

The objectives of this study are to estimate the prevalence of multimorbidity (MM) among adults in the Central Highland Region (a poor region) of Vietnam in 2017 and to identify the sociodemographic correlates of these conditions.

Methods:

We used data from a cross-sectional study conducted in 2018 on health status among people in four provinces in the Central Highlands Region (Tay Nguyen) of Vietnam. A sample of 1680 adults (aged 15 years and older) were randomly selected for this study. Respondents were asked whether they had been told by a health worker that they had cancer, heart and circulatory conditions, chronic joint problems, chronic pulmonary diseases, chronic kidney problems, chronic digestive problems, psychological illness, diabetes, and/or other chronic conditions.

Results:

The prevalence of MM among the study participants was 16.4% (95% confidence interval (CI): 14.6%–18.2%). By looking at the 95% CIs, the differences in MM prevalence between the groups classified by gender, age, education, and occupation were not statistically significant. Only the difference in MM prevalence between farmers and government staff was statistically significant. Multivariate logistic analyses show education and occupations were shown to be significant correlates of MM.

Conclusion:

MMs were quite common among the adult populations in the study area, especially among people with lower socioeconomic status. Given the evidence, actions to reduce levels of MM in the setting are clearly urgent. The interventions should address all people in society, with focus on disadvantaged groups, like those with lower education and farmers.

Self-efficacy and health-related quality of life: a cross-sectional study of primary care patients with multi-morbidity

BACKGROUND

Multi-morbidity in chronic long-term conditions is a major concern for health services. Self-management in concert with clinical care forms part of the effective management of multi-morbidity. Self-efficacy is a mechanism through which self-management can be achieved. Quality of life is adversely impacted by multi-morbidity but could be improved by effective self-management. This study examines the relationship between self-efficacy and quality of life in primary care patients with multi-morbidity.

METHODS

A cross-sectional survey was conducted with primary care patients in England. Potential participants were mailed a questionnaire containing quality of life measures (the EQ-5D-5L and the Long-Term Conditions Questionnaire (LTCQ)), the Disease Burden Impact Scale (DBIS) and the Self-efficacy for Managing Chronic Disease Scale. Descriptive statistics, analysis of variance and linear regression analyses were conducted to examine the relationship between quality of life (dependent variable), self-efficacy, and demographic and disease-related variables.

RESULTS

The 848 participants living with multi-morbidity reported a mean of 6.46 (SD 3.49) chronic long-term conditions, with the mean number of physical conditions 5.99 (SD 3.34) and mental health conditions 0.47 (SD 0.66). The mean scores were 15.45 (SD 12.00) for disease burden, 0.69 (SD 0.28) for the EQ-5D-5L, 65.44 (SD 23.66) for the EQ-VAS, and 69.31 (SD 21.77) for the LTCQ. The mean self-efficacy score was 6.69 (SD 2.53). The regression models were all significant at p < 0.001 (adjusted R2 > 0.70). Significant factors in all models were self-efficacy, disease burden and being permanently sick or disabled. Other factors varied between models, with the most notable being the presence of a mental health condition in the LTCQ model.

CONCLUSIONS

Multi-morbid primary care patients with lower self-efficacy and higher disease burden have lower quality of life. Awareness of self-efficacy levels among patients with multi-morbidity may help health professionals identify patients who are in need of enhanced self-management support. Providing self-management support for chronic disease has been hailed as a hallmark of good care. Higher self-efficacy may lead to enhanced quality of life in multi-morbidity.

Widening inequalities in multimorbidity? Time trends among the working population between 2005 and 2015 based on German health insurance data

BACKGROUND

Previous research has produced evidence for social inequalities in multimorbidity, but little is known on how these disparities change over time. Our study investigates the development of social inequalities in multimorbidity among the middle-aged and older working population. Special attention is paid to whether differing time trends between socio-economic status (SES) groups have taken place, increasing or decreasing inequalities in multimorbidity.

METHODS

The analyses are based on claims data of a German statutory health insurance company covering an observation period from 2005 to 2015. Multimorbidity prevalence risks are estimated using logistic generalized estimation equations (GEE) models. Predicted probabilities of multimorbidity prevalence are used to assess time trends in absolute social inequalities in terms of educational level, income, and occupational group.

RESULTS

The prevalence risks of multimorbidity rose among all SES groups and social gradients persist throughout the observation period, indicating significantly higher multimorbidity prevalence risks for individuals with lower SES. Widening absolute inequalities are found among men in terms of educational level and among women in terms of occupational groups.

CONCLUSIONS

The increases in multimorbidity prevalence among the working population are accompanied by widening social inequalities, pointing towards a growing disadvantage for men and women in lower SES groups. The rising burden and the increasing inequalities among the working population stress the importance of multimorbidity as a major public health concern.

Widening inequalities in multimorbidity? Time trends among the working population between 2005 and 2015 based on German health insurance data

Background

Previous research has produced evidence for social inequalities in multimorbidity, but little is known on how these disparities change over time. Our study investigates the development of social inequalities in multimorbidity among the middle-aged and older working population. Special attention is paid to whether differing time trends between socio-economic status (SES) groups have taken place, increasing or decreasing inequalities in multimorbidity.

Methods

The analyses are based on claims data of a German statutory health insurance company covering an observation period from 2005 to 2015. Multimorbidity prevalence risks are estimated using logistic generalized estimation equations (GEE) models. Predicted probabilities of multimorbidity prevalence are used to assess time trends in absolute social inequalities in terms of educational level, income, and occupational group.

Results

The prevalence risks of multimorbidity rose among all SES groups and social gradients persist throughout the observation period, indicating significantly higher multimorbidity prevalence risks for individuals with lower SES. Widening absolute inequalities are found among men in terms of educational level and among women in terms of occupational groups.

Conclusions

The increases in multimorbidity prevalence among the working population are accompanied by widening social inequalities, pointing towards a growing disadvantage for men and women in lower SES groups. The rising burden and the increasing inequalities among the working population stress the importance of multimorbidity as a major public health concern.

Electronic supplementary material

The online version of this article (10.1186/s12939-018-0815-z) contains supplementary material, which is available to authorized users.

Quality of life and burden of morbidity in primary care users with multimorbidity

Purpose

The aim of this study was to assess the quality of life, number of diseases and burden of morbidity of multimorbid primary care users and whether a simple disease count or a multimorbidity burden score is more predictive of quality of life.

Patients and methods

Primary care patients with at least 1 of 11 specified chronic conditions were invited to participate in a postal survey. Participants completed the Disease Burden Impact Scale (DBIS) questionnaire, the five dimension-five level Euro-Qol (EQ-5D-5L) and standard demographics questions. The DBIS asks participants to self-report chronic conditions and to rate the impact of each condition. Descriptive statistics and analysis of variance were used to determine quality of life, count of diseases and burden of morbidity. Multiple linear regression analyses determined whether disease count or the DBIS, adjusted for demographics, was more predictive of the EQ-5D-5L scores.

Results

Thirty-one percent (n=917) responded, from which 69 were excluded as they reported no or only one condition, leaving 848 (92%) in the analysis. Slightly more women (50.9%) participated; the mean age was 67.0 (SD 13.9) and the mean number of conditions was 6.5 (SD 3.49). The mean scores were: DBIS 15.5 (SD 12.00; score range 0–140, with higher scores indicating higher multimorbidity burden), EQ-5D-5L score 0.69 (SD 0.28; score range −0.28 [a state worse than death] to 1 [best possible health state]) and EQ-5D Visual Analog Scale (EQ-VAS) 65.44 (SD 23.66; score range 0–100 with higher scores meaning better health). The model using the DBIS score was more predictive of the EQ-5D-5L score and EQ-VAS than the model using the disease count (R²_adj=0.53 using DBIS and R²_adj=0.42 using disease count for EQ-5D-5L score, and R²_adj=0.44 using DBIS versus R²_adj=0.34 using disease count for EQ-VAS). All models were statistically significant (p<0.001).

Conclusion

The DBIS is a useful measure for assessing multimorbidity from the perspective of primary care users in particular, as it is more predictive of health outcomes than a simple count of conditions.

The effect of social deprivation on hip fracture incidence in England has not changed over 14 years: an analysis of the English Hospital Episodes Statistics (2001-2015)

Deprivation predicts increased hip fracture risk. Over 14 years, hip fracture incidence increased among men with persisting inequalities. Among women, inequalities in incidence were less pronounced; whilst incidence decreased overall, this improvement was seen marginally less in women from the most deprived areas. Hip fracture prevention programmes have not reduced inequalities.

PURPOSE

Deprivation is associated with increased hip fracture risk. We examined the effect of area-level deprivation on hip fracture incidence in England over 14 years to determine whether inequalities have changed over time.

METHODS

We used English Hospital Episodes Statistics (2001/2002-2014/2015) to identify hip fractures in adults aged 50+ years and mid-year population estimates (2001-2014) from the Office for National Statistics. The Index of Multiple Deprivation measured local area deprivation. We calculated age-adjusted incidence rate ratios (IRR) for hip fracture, stratified by gender and deprivation quintiles.

RESULTS

Over 14 years, we identified 747,369 hospital admissions with an index hip fracture; the number increased from 50,640 in 2001 to 55,092 in 2014; the proportion of men increased from 22.2% to 29.6%. Whereas incidence rates decreased in women (annual reduction 1.1%), they increased in men (annual increase 0.6%) (interaction p < 0.001). Incidence was higher in more deprived areas, particularly among men: IRR most vs. least deprived quintile 1.50 [95% CI 1.48, 1.52] in men, 1.17 [1.16, 1.18] in women. Age-standardised incidence increased for men across all deprivation quintiles from 2001 to 2014. Among women, incidence fell more among those least compared to most deprived (year by deprivation interaction p < 0.001).

CONCLUSIONS

Deprivation is a stronger relative predictor of hip fracture incidence in men than in women. However, given their higher hip fracture incidence, the absolute burden of deprivation on hip fractures is greater in women. Despite public health efforts to prevent hip fractures, the health inequality gap for hip fracture incidence has not narrowed for men, and marginally widened among women.

Prevalence of multimorbidity in Germany: impact of age and educational level in a cross-sectional study on 19,294 adults

BACKGROUND

Multimorbidity is one of the most important and challenging aspects in public health. Multimorbid people are associated with more hospital admissions, a large number of drug prescriptions and higher risks of mortality. As there is evidence that multimorbidity varies with age and socioeconomic disparity, the main objective aimed at determining age-specific prevalence rates as well as exploring educational differences relating to multimorbidity in Germany.

METHODS

This cross-sectional analysis is based on the national telephone health interview survey "German Health Update" (GEDA2012) conducted between March 2012 and March 2013 with nearly 20,000 adults. GEDA2012 provides information on 17 self-reported health conditions along with sociodemographic characteristics. Multimorbidity was defined as the occurrence of two or more chronic conditions in one individual at the same time. Descriptive statistical analysis was used to examine multimorbidity according to age and education, which was defined by the International Standard Classification of Education (ISCED 1997).

RESULTS

Overall, 39.6% (95% confidence interval (CI) 38.7%-40.6%) of the 19,294 participants were multimorbid and the proportion of adults with multimorbidity increased substantially with age: nearly half (49.2%, 95% CI 46.9%-51.5%) of the adults aged 50-59 years had already two or more chronic health conditions. Prevalence rates of multimorbidity differed considerably between the levels of education. Low-level educated adults aged 40-49 years were more likely to be multimorbid with a prevalence rate of 47.4% (95% CI 44.2%-50.5%) matching those of highly educated men and women aged about ten years older.

CONCLUSIONS

Our findings demonstrate that both, age and education are associated with a higher risk of being multimorbid in Germany. Hence, special emphasis in the development of new approaches in national public health and prevention programs on multimorbidity should be given to low-level educated people aged <65 years.

Prevalence, Correlates, and Time Trends of Multiple Chronic Conditions Among Israeli Adults: Estimates From the Israeli National Health Interview Survey, 2014-2015

INTRODUCTION

Chronic diseases constitute a major public health challenge. The prevalence of multiple chronic conditions (MCC) has increased. The objective of our study was to describe the prevalence, correlates, and time trends of MCC in the Israeli population and among the nation's 2 main population groups (Jewish and Arab).

METHODS

To describe the prevalence of correlates of MCC, we used data from the 2014-2015 Israeli National Health Interview Survey-III (INHIS-III). MCC was defined as having 2 or more of the following 10 self-reported physician-diagnosed chronic conditions: asthma, arthritis, cancer, diabetes, dyslipidemia, heart attack, hypertension, migraine, osteoporosis, or thyroid disease. For trend analysis, we used data from INHIS-I (2003-2004) and INHIS-II (2007-2010). Logistic regression was used for multivariate analysis. Estimates were weighted to the 2014 Israeli population. P for trend was calculated by using the Cochran-Armitage test for proportions.

RESULTS

In 2014-2015, the prevalence of MCC was 27.3% (95% confidence interval, 25.7%-28.8%). In multivariate analysis, MCC was associated with older age, female sex, a monthly household income of USD$3,000 or less, current and past smoking, and overweight or obesity. After adjusting for age, sex, income, smoking status, and body mass index, differences in MCC between Jewish and Arab populations disappeared. Dyslipidemia and hypertension were the most prevalent dyad among both men and women. Dyslipidemia, hypertension, and diabetes were the most prevalent triad among both men and women. The age-adjusted prevalence of MCC increased by 6.7% between 2003-2004 and 2014-2015.

CONCLUSION

With the increase in the prevalence of MCC, a comprehensive approach is needed to reduce the burden of chronic conditions. Of special concern are the groups most prone to MCC.