The impact of socioeconomic status and multimorbidity on mortality: a population-based cohort study

Analysis of Health Ailments and Associated Risk Factors in Small-Scale Fisherfolk Community of Indian Sundarbans: A Cross-Sectional Study

Background

Small-scale fishers of Indian Sundarbans depend on open-water fisheries for their livelihoods. They often face health, occupational, and safety issues in their profession due to environmental, socio-economic, and policy changes. The morbidity pattern and related risk factors are important indicators of well-being for any community, hence applicable to small-scale fishers of Sundarbans. The present study was designed to assess patterns of morbidities, associated risk factors including occupational health hazards, and treatment-seeking behavior of small-scale fishers in the Indian Sundarbans.

Material and Methods

Household surveys, focused group discussions, and personal interviews were conducted through a predesigned pretested structured questionnaire. Associated risk factors and the nature of seeking treatment were considered during the data collection covering 650 individuals from 132 fishers' families.

Results

Morbidities were more frequent in males (39.33%) than in females (28.5%). The fever (31%) was the most dominant reason for morbidities followed by ocular ailments (23%), musculoskeletal disorder (20%), dermatological ailments (17%), and respiratory illness (9%). The highest morbidities (25%) were recorded in the age group of 21-30 years in males while that was 20% in the 11-20 years age group in the case of the females. Physical labor for fishing activities predisposes to health ailments of the studied population.

Conclusions

The prevalence of morbidity among the fishermen community was found to be 28.5%. The understanding of the morbidity profile of a population in general and specific age groups of both sexes in specific sheds light on the vulnerability of working groups that will help for effective healthcare planning and resource allocation.

Comorbidity patterns in cardiovascular diseases: the role of life-stage and socioeconomic status

Cardiovascular diseases stand as a prominent global cause of mortality, their intricate origins often entwined with comorbidities and multimorbid conditions. Acknowledging the pivotal roles of age, sex, and social determinants of health in shaping the onset and progression of these diseases, our study delves into the nuanced interplay between life-stage, socioeconomic status, and comorbidity patterns within cardiovascular diseases. Leveraging data from a cross-sectional survey encompassing Mexican adults, we unearth a robust association between these variables and the prevalence of comorbidities linked to cardiovascular conditions. To foster a comprehensive understanding of multimorbidity patterns across diverse life-stages, we scrutinize an extensive dataset comprising 47,377 cases diagnosed with cardiovascular ailments at Mexico's national reference hospital. Extracting sociodemographic details, primary diagnoses prompting hospitalization, and additional conditions identified through ICD-10 codes, we unveil subtle yet significant associations and discuss pertinent specific cases. Our results underscore a noteworthy trend: younger patients of lower socioeconomic status exhibit a heightened likelihood of cardiovascular comorbidities compared to their older counterparts with a higher socioeconomic status. By empowering clinicians to discern non-evident comorbidities, our study aims to refine therapeutic designs. These findings offer profound insights into the intricate interplay among life-stage, socioeconomic status, and comorbidity patterns within cardiovascular diseases. Armed with data-supported approaches that account for these factors, clinical practices stand to be enhanced, and public health policies informed, ultimately advancing the prevention and management of cardiovascular disease in Mexico.

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

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

Healthcare fragmentation, multimorbidity, potentially inappropriate medication, and mortality: a Danish nationwide cohort study

BACKGROUND

Patients with multimorbidity are frequent users of healthcare, but fragmented care may lead to suboptimal treatment. Yet, this has never been examined across healthcare sectors on a national scale. We aimed to quantify care fragmentation using various measures and to analyze the associations with patient outcomes.

METHODS

We conducted a register-based nationwide cohort study with 4.7 million Danish adult citizens. All healthcare contacts to primary care and hospitals during 2018 were recorded. Clinical fragmentation indicators included number of healthcare contacts, involved providers, provider transitions, and hospital trajectories. Formal fragmentation indices assessed care concentration, dispersion, and contact sequence. The patient outcomes were potentially inappropriate medication and all-cause mortality adjusted for demographics, socioeconomic factors, and morbidity level.

RESULTS

The number of involved healthcare providers, provider transitions, and hospital trajectories rose with increasing morbidity levels. Patients with 3 versus 6 conditions had a mean of 4.0 versus 6.9 involved providers and 6.6 versus 13.7 provider transitions. The proportion of contacts to the patient's own general practice remained stable across morbidity levels. High levels of care fragmentation were associated with higher rates of potentially inappropriate medication and increased mortality on all fragmentation measures after adjusting for demographic characteristics, socioeconomic factors, and morbidity. The strongest associations with potentially inappropriate medication and mortality were found for ≥ 20 contacts versus none (incidence rate ratio 2.83, 95% CI 2.77-2.90) and ≥ 20 hospital trajectories versus none (hazard ratio 10.8, 95% CI 9.48-12.4), respectively. Having less than 25% of contacts with your usual provider was associated with an incidence rate ratio of potentially inappropriate medication of 1.49 (95% CI 1.40-1.58) and a mortality hazard ratio of 2.59 (95% CI 2.36-2.84) compared with full continuity. For the associations between fragmentation measures and patient outcomes, there were no clear interactions with number of conditions.

CONCLUSIONS

Several clinical indicators of care fragmentation were associated with morbidity level. Care fragmentation was associated with higher rates of potentially inappropriate medication and increased mortality even when adjusting for the most important confounders. Frequent contact to the usual provider, fewer transitions, and better coordination were associated with better patient outcomes regardless of morbidity level.

Multimorbidity and determinants for initiating outpatient trajectories: A population-based study

INTRODUCTION

Individuals with multimorbidity often receive high numbers of hospital outpatient services in concurrent trajectories. Nevertheless, little is known about factors associated with initiating new hospital outpatient trajectories; identified as the continued use of outpatient contacts for the same medical condition.

PURPOSE

To investigate whether the number of chronic conditions and sociodemographic characteristics in adults with multimorbidity is associated with entering a hospital outpatient trajectory in this population.

METHODS

This population-based register study included all adults in Denmark with multimorbidity on January 1, 2018. The exposures were number of chronic conditions and sociodemographic characteristics, and the outcome was the rate of starting a new outpatient trajectory during 2018. Analyses were stratified by the number of existing outpatient trajectories. We used Poisson regression analysis, and results were expressed as incidence rates and incidence rate ratios with 95% confidence intervals. We followed the individuals during the entire year of 2018, accounting for person-time by hospitalization, emigration, and death.

RESULTS

Incidence rates for new outpatient trajectories were highest for individuals with low household income and ≥3 existing trajectories and for individuals with ≥3 chronic conditions and in no already established outpatient trajectory. A high number of chronic conditions and male gender were found to be determinants for initiating a new outpatient trajectory, regardless of the number of existing trajectories. Low educational level was a determinant when combined with 1, 2, and ≥3 existing trajectories, and increasing age, western ethnicity, and unemployment when combined with 0, 1, and 2 existing trajectories.

CONCLUSION

A high number of chronic conditions, male gender, high age, low educational level and unemployment were determinants for initiation of an outpatient trajectory. The rate was modified by the existing number of outpatient trajectories. The results may help identify those with multimorbidity at greatest risk of having a new hospital outpatient trajectory initiated.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

CONCLUSIONS

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

Experience of living with multimorbidity and health workers perspectives on the organization of health services for people living with multiple chronic conditions in Bahir Dar, northwest Ethiopia: a qualitative study

BACKGROUND

Multimorbidity-the simultaneous occurrence of two or more chronic Non-Communicable Diseases) in an individual is increasing globally and challenging health systems. Although individuals living with multimorbidity face a range of adverse consequences and difficulty in getting optimal health care, the evidence base in understanding the burden and capacity of the health system in managing multimorbidity is sparse in low-and middle-income countries (LMICs). This study aimed at understanding the lived experiences of patients with multimorbidity and perspective of service providers on multimorbidity and its care provision, and perceived capacity of the health system for managing multimorbidity in Bahir Dar City, northwest Ethiopia.

METHODS

A facility-based phenomenological study design was conducted in three public and three private health facilities rendering chronic outpatient Non-Communicable Diseases (NCDs) care in Bahir Dar City, Ethiopia. Nineteen patient participants with two or more chronic NCDs and nine health care providers (six medical doctors and three nurses) were purposively selected and interviewed using semi-structured in-depth interview guides. Data were collected by trained researchers. Interviews were audio-recorded using digital recorders, stored and transferred to computers, transcribed verbatim by the data collectors, translated into English and then imported into NVivo V.12 software for data analysis. We employed a six-step inductive thematic framework analysis approach to construct meaning and interpret experiences and perceptions of individual patients and service providers. Codes were identified and categorized into sub-themes, organizing themes and main themes iteratively to identify similarities and differences across themes, and to interpret them accordingly.

RESULTS

A total of 19 patient participants (5 Females) and nine health workers (2 females) responded to the interviews. Participants' age ranged from 39 to 79 years for patients and 30 to 50 years for health professionals. About half (n = 9) of the participants had three or more chronic conditions. The key themes produced were feeling dependency, social rejection, psychological distress, poor medication adherence and poor quality of care. Living with multimorbidity poses a huge burden on the physical, psychological, social and sexual health of patients. In addition, patients with multimorbidity are facing financial hardship to access optimal multimorbidity care. On the other hand, the health system is not appropriately prepared to provide integrated, person-centered and coordinated care for people living with multiple chronic conditions.

CONCLUSION AND RECOMMENDATIONS

Living with multimorbidity poses huge impact on physical, psychological, social and sexual health of patients. Patients seeking multimorbidity care are facing challenges to access care attributable to either financial constraints or the lack of integrated, respectful and compassionate health care. It is recommended that the health system must understand and respond to the complex care needs of the patients with multimorbidity.

Social inequalities in all-cause mortality among adults with multimorbidity: a 10-year prospective study of 0.5 million Chinese adults

BACKGROUND

Chinese individuals face an increase in multimorbidity, but little is known about the mortality gradients of multimorbid people in different socio-economic groups. This study measures relative and absolute socio-economic inequality in mortality among multimorbid Chinese.

METHODS

For this study, the prospective China Kadoorie Biobank (CKB) enrolled 512 712 participants ages 30-79 y from 10 areas of China between 25 June 2004 and 15 July 2008. All-cause mortality was accessed with a mean follow-up period of 10 y (to 31 December 2016). Associations between multimorbidity and mortality were assessed using Cox proportional hazards models, with the relative index of inequality (RII) and slope index of inequality (SII) in mortality calculated to measure disparities.

RESULTS

Mortality risk was highest for those who had not attended formal school and with four or more long-term conditions (LTCs) (hazard ratio 3.11 [95% confidence interval {CI} 2.75 to 3.51]). Relative educational inequality was lower in participants with four or more LTCs (RII 1.92 [95% CI 1.60 to 2.30]), especially in rural areas. Absolute disparities were greater in adults with more LTCs (SII 0.18 [95% CI 0.14 to 0.21] for rural participants with three LTCs).

CONCLUSIONS

Whereas the relative inequality in all-cause mortality was lower among multimorbid people, absolute inequality was greater among multimorbid men, especially in rural areas.

Mortality among Canadian population with multimorbidity: A retrospective cohort study

Objective

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

Study Design

Population-based retrospective cohort study.

Methods

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

Results

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

Conclusions

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

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

Introduction

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

Methods

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

Results

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

Conclusions

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

The influence of childhood socioeconomic status on non-communicable disease risk factor clustering and multimorbidity among adults in Botswana: a life course perspective

Childhood socioeconomic circumstances have a great influence on the health of individuals in adult life. We used cross-sectional data from a non-communicable disease (NCD) survey conducted in 2016, and respondents aged ≥15 y were selected from 3 cities/towns, 15 urban villages and 15 rural areas using a multistage probability-sampling technique. The total sample for the study was 1178. Two multinomial logistic regression models were fitted to data to ascertain the association between childhood socioeconomic status (SES) and NCD risk factor clustering and multimorbidity, using SPSS version 27. All comparisons were considered to be statistically significant at a 5% level. The prevalence of multiple NCD risk factors and multimorbidity was 30.1 and 5.3%, respectively. The odds of reporting NCD risk factor clustering were significantly high among individuals who reported low (adjusted OR [AOR]=1.88, 95% CI 1.21 to 2.78) and middle (AOR=1.22, 95% CI 1.02 to 2.05) childhood SES compared with high childhood SES. Conversely, individuals from a low SES background were more likely to report both single (AOR=1.17, 95% CI 1.00 to 2.01) and multiple NCD conditions (AOR=1.78, 95% CI 1.11 to 2.68) compared with those with a high childhood SES background. There is a need to stimulate policy debate and research to take cognisance of childhood socioeconomic circumstances in health policy planning.

Multimorbidity and associations with clinical outcomes in a middle-aged population in Iran: a longitudinal cohort study

Background

As the populations of lower-income and middle-income countries age, multimorbidity is increasing, but there is little information on its long-term consequences. We aimed to show associations between multimorbidity and outcomes of mortality and hospitalisation in Iran, a middle-income country undergoing rapid economic transition.

Methods

We conducted a secondary analysis of longitudinal data collected in the Golestan Cohort Study. Data on demographics, morbidities and lifestyle factors were collected at baseline, and information on hospitalisations or deaths was captured annually. Logistic regression was used to analyse the association between baseline multimorbidity and 10-year mortality, Cox-proportional hazard models to measure lifetime risk of mortality and zero-inflation models to investigate the association between hospitalisation and multimorbidity. Multimorbidity was classified as ≥2 conditions or number of conditions. Demographic, lifestyle and socioeconomic variables were included as covariables.

Results

The study recruited 50 045 participants aged 40–75 years between 2004 and 2008, 47 883 were available for analysis, 416 (57.3%) were female and 12 736 (27.94%) were multimorbid. The odds of dying at 10 years for multimorbidity defined as ≥2 conditions was 1.99 (95% CI 1.86 to 2.12, p<0.001), and it increased with increasing number of conditions (OR of 3.57; 95% CI 3.12 to 4.08, p<0.001 for ≥4 conditions). The survival analysis showed the hazard of death for those with ≥4 conditions was 3.06 (95% CI 2.74 to 3.43, p<0.001). The number of hospital admissions increased with number of conditions (OR of not being hospitalised of 0.36; 95% CI 0.31 to 0.52, p<0.001, for ≥4 conditions).

Conclusion

The long-terms effects of multimorbidity on mortality and hospitalisation are similar in this population to those seen in high-income countries.

The effect of disease onset chronology on mortality among patients with multimorbidity: A Danish nationwide register study

Background

Multimorbidity is associated with increased mortality. Certain combinations of diseases are known to be more lethal than others, but the limited knowledge of how the chronology in which diseases develop impacts mortality may impair the development of effective clinical interventions for patients with multimorbidity.

Objective

To explore if in multimorbidity the chronology of disease onset is associated with mortality. Design: A prospective nationwide cohort study, including 3,986,209 people aged ≥18 years on 1 January 2000, was performed. We included ten diagnosis groups: lung, musculoskeletal, endocrine, mental, cancer, neurological, gastrointestinal, cardiovascular, kidney, and sensory organs. We defined multimorbidity as the presence of at least two diagnoses from two diagnosis groups (out of ten). To determine mortality, logistic regression models were used to calculate odds ratios (OR) and ratio of ORs (RORs).

Results

For most combinations of multimorbidity, the chronology of disease onset does not change mortality. However, when multimorbidity included mental health diagnoses, mortality was in general higher if the mental health diagnosis appeared first. If multimorbidity included heart and sensory diagnoses, mortality was higher if these developed second. For the majority of multimorbidity combinations, there was excess mortality if multimorbidity was diagnosed simultaneously, rather than consecutively, for example, heart and kidney (3.58 ROR; CI 2.39–5.36), or mental health and musculoskeletal diagnoses (2.38 ROR; CI 1.70–3.32).

Conclusions

Overall, in multimorbidity, the chronology in which diseases develop is not associated with mortality, with few exceptions. For almost all combinations of multimorbidity, diagnoses act synergistically in relation to mortality if diagnosed simultaneously.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

OBJECTIVES

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

STUDY DESIGN

This was a cohort study.

METHODS

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

RESULTS

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

CONCLUSIONS

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

Performance of quantitative measures of multimorbidity: a population-based retrospective analysis

BACKGROUND

Multimorbidity measures are useful for resource planning, patient selection and prioritization, and factor adjustment in clinical practice, research, and benchmarking. We aimed to compare the explanatory performance of the adjusted morbidity group (GMA) index in predicting relevant healthcare outcomes with that of other quantitative measures of multimorbidity.

METHODS

The performance of multimorbidity measures was retrospectively assessed on anonymized records of the entire adult population of Catalonia (North-East Spain). Five quantitative measures of multimorbidity were added to a baseline model based on age, gender, and socioeconomic status: the Charlson index score, the count of chronic diseases according to three different proposals (i.e., the QOF, HCUP, and Karolinska institute), and the multimorbidity index score of the GMA tool. Outcomes included all-cause death, total and non-scheduled hospitalization, primary care and ER visits, medication use, admission to a skilled nursing facility for intermediate care, and high expenditure (time frame 2017). The analysis was performed on 10 subpopulations: all adults (i.e., aged > 17 years), people aged > 64 years, people aged > 64 years and institutionalized in a nursing home for long-term care, and people with specific diagnoses (e.g., ischemic heart disease, cirrhosis, dementia, diabetes mellitus, heart failure, chronic kidney disease, and chronic obstructive pulmonary disease). The explanatory performance was assessed using the area under the receiving operating curves (AUC-ROC) (main analysis) and three additional statistics (secondary analysis).

RESULTS

The adult population included 6,224,316 individuals. The addition of any of the multimorbidity measures to the baseline model increased the explanatory performance for all outcomes and subpopulations. All measurements performed better in the general adult population. The GMA index had higher performance and consistency across subpopulations than the rest of multimorbidity measures. The Charlson index stood out on explaining mortality, whereas measures based on exhaustive definitions of chronic diagnostic (e.g., HCUP and GMA) performed better than those using predefined lists of diagnostics (e.g., QOF or the Karolinska proposal).

CONCLUSIONS

The addition of multimorbidity measures to models for explaining healthcare outcomes increase the performance. The GMA index has high performance in explaining relevant healthcare outcomes and may be useful for clinical practice, resource planning, and public health research.

Multimorbidity measures from health administrative data using ICD system codes: A systematic review

BACKGROUND

We aimed to identify and characterize adult population-based multimorbidity measures using health administrative data and the International Classification of Diseases (ICD) codes for disease identification.

METHODS

We performed a narrative systematic review of studies using or describing development or validation of multimorbidity measures. We compared the number of diseases included in the measures, the process of data extraction (case definition) and the validation process. We assessed the methodological robustness using eight criteria, five based on general criteria for indicators (AIRE instrument) and three multimorbidity-specific criteria.

RESULTS

Twenty-two multimorbidity measures were identified. The number of diseases they included ranged from 5 to 84 (median = 20), with 19 measures including both physical and mental conditions. Diseases were identified using ICD codes extracted from inpatient and outpatient data (18/22) and sometimes including drug claims (10/22). The validation process relied mainly on the capacity of the measures to predict health outcome (5/22), or on the validation of each individual disease against a gold standard (8/22). Six multimorbidity measures met at least six of the eight robustness criteria assessed.

CONCLUSION

There is significant heterogeneity among the measures used to assess multimorbidity in administrative databases, and about a third are of low to moderate quality. A more consensual approach to the number of diseases or groups of diseases included in multimorbidity measures may improve comparison between regions, and potentially provide better control for multimorbidity-related confounding in studies.

The influence of community health on hospitals attainment of Magnet designation: Implications for policy and practice

AIMS

To determine if there is an association between better County Health Rankings and the increased odds of a hospital gaining Magnet designation in subsequent years (2014-2019) compared with counties with lower rankings.

BACKGROUND

The Magnet hospital model is recognized to have a great effect on nurses, patients and organizational outcomes. Although Magnet hospital designation is a well-established structural marker for nursing excellence, the effect of County Health Rankings and subsequent hospital achievement of Magnet status is unknown.

DESIGN

A descriptive, cross-sectional quantitative approach was adopted for this study.

METHODS

Data were derived from 2010 to 2019 U.S. County Health Rankings, American Hospital Association, and American Nursing Credentialing Center databases. Logistic regression models were utilized to determine associations between county rankings for health behaviours, clinical care, social and economic factors, physical environment and counties with a new Magnet hospital after 2014.

RESULTS

Counties with the worst rankings for clinical care and socio-economic status had reduced odds of obtaining a Magnet hospital designation compared with best-ranking counties. While middle-ranking counties for the physical environment ranking had increased odds of having Magnet designation compared with best-ranking counties. Additionally, having an increased percent of government non-federal hospital or a higher percentage of critical access hospitals in the county reduced the odds of having a Magnet-designated facility after 2014.

CONCLUSION

The findings underscore the important associations between Magnet-designated facilities' location and the health of its surrounding counties. This study is the first to examine the relationship between County Health Rankings and a hospital's likelihood of obtaining Magnet status and points to the need for future research to explore outcomes of care previously identified as improved in Magnet-designated hospitals.

IMPLICATIONS

Recognizing the benefits of Magnet facilities, it is important for health care leaders and policy makers to seek opportunities to promote centres of excellence in higher need communities through policy and financial intervention.

Development of Multimorbidity Over Time: An Analysis of Belgium Primary Care Data Using Markov Chains and Weighted Association Rule Mining

Background

The prevalence of multimorbidity is increasing in recent years, and patients with multimorbidity often have a decrease in quality of life and require more health care. The aim of this study was to explore the evolution of multimorbidity taking the sequence of diseases into consideration.

Methods

We used a Belgian database collected by extracting coded parameters and more than 100 chronic conditions from the Electronic Health Records of general practitioners to study patients older than 40 years with multiple diagnoses between 1991 and 2015 (N = 65 939). We applied Markov chains to estimate the probability of developing another condition in the next state after a diagnosis. The results of Weighted Association Rule Mining (WARM) allow us to show strong associations among multiple conditions.

Results

About 66.9% of the selected patients had multimorbidity. Conditions with high prevalence, such as hypertension and depressive disorder, were likely to occur after the diagnosis of most conditions. Patterns in several disease groups were apparent based on the results of both Markov chain and WARM, such as musculoskeletal diseases and psychological diseases. Psychological diseases were frequently followed by irritable bowel syndrome.

Conclusions

Our study used Markov chains and WARM for the first time to provide a comprehensive view of the relations among 103 chronic conditions, taking sequential chronology into consideration. Some strong associations among specific conditions were detected and the results were consistent with current knowledge in literature, meaning the approaches were valid to be used on larger data sets, such as National Health care Systems or private insurers.

Possible associations between callers' degree-of-worry and their socioeconomic status when contacting out-of-hours services: a prospective cohort study

Background

Telephone triage within out-of-hours (OOH) services aims to ascertain the urgency of a caller’s medical condition in order to determine the correct type of health care needed, ensuring patient safety. To improve the triage process by increasing patient-centred communication, a triage tool has been developed, whereby callers are asked to rate their degree-of-worry (DOW) as a measure of self-evaluated urgency. Studies show that low socioeconomic status (SES), being single and non-Western ethnicity are associated to low self-rated health and high morbidity and these factors may also be associated with high DOW. The aim of this paper was to examine if low SES, being single and non-Western ethnicity were associated to high DOW of callers contacting OOH services.

Methods

A prospective cohort study design, at the OOH services for the Capital Region of Denmark. Over 2 weeks, 6869 of 38,787 callers met the inclusion criteria: ≥18 years, patients themselves or close relative/friend, reported DOW, had a valid personal identification number and gave informed consent. Callers were asked to report their DOW (1 = minimal worry to 5 = maximal worry), which was dichotomized into low (1–3) and high (4, 5) DOW and linked to data from electronical medical records and Statistics Denmark. Socioeconomic factors (education and annual household income), marital status and ethnicity were assessed in relation to DOW by logistic regression.

Results

High DOW was reported by 38.2% of the participants. Low SES (low educational level; OR 1.5, 95% CI 1.3–1.7 and low annual household income; 1.5, 1.3–1.6) was associated with high DOW and so too was being single; 1.2, 1.1–1.3 and of non-Western ethnicity; 2.9, 2.5–3.4.

Conclusions

Knowledge of the association of low SES, marital status as single and non-Western ethnicity with high DOW among callers to OOH services may give call handlers a better understanding of callers’ DOW. If this does not correspond to the call handler’s perception of urgency, this knowledge may further encourage patient-centred communication, aid the triage process and increase patient safety. A better understanding of socioeconomic variables and their relation to callers’ DOW gives direction for future research to improve telephone triage of OOH services.

The incidence of multimorbidity and patterns in accumulation of chronic conditions: A systematic review

Multimorbidity, the presence of 1+ chronic condition in an individual, remains one of the greatest challenges to health on a global scale. Although the prevalence of multimorbidity has been well-established, its incidence is not fully understood. This systematic review determined the incidence of multimorbidity across the lifespan; the order in which chronic conditions accumulate to result in multimorbidity; and cataloged methods used to determine and report accumulation of chronic conditions resulting in multimorbidity. Studies were identified by searching MEDLINE, Embase, CINAHL, and Cochrane electronic databases. Two independent reviewers evaluated studies for inclusion and performed quality assessments. Of 36 included studies, there was high heterogeneity in study design and operational definitions of multimorbidity. Studies reporting incidence (n = 32) reported a median incidence rate of 30.7 per 1,000 person-years (IQR 39.5 per 1,000 person-years) and a median cumulative incidence of 2.8% (IQR 28.7%). Incidence was notably higher for persons with older age and 1+ chronic conditions at baseline. Studies reporting patterns in accumulation of chronic conditions (n = 5) reported hypertensive and heart diseases, and diabetes, as among the common starting conditions resulting in later multimorbidity. Methods used to discern patterns were highly heterogenous, ranging from the use of latent growth trajectories to divisive cluster analyses, and presentation using alluvial plots to cluster trajectories. Studies reporting the incidence of multimorbidity and patterns in accumulation of chronic conditions vary greatly in study designs and definitions used. To allow for more accurate estimations and comparison, studies must be transparent and consistent in operational definitions of multimorbidity applied.

Changes in cannabis use according to socioeconomic status among Finnish adolescents from 2000 to 2015

BACKGROUND

Despite reduced sanctions and more permissive attitudes toward cannabis use in the USA and Europe, the prevalences of adolescent cannabis use have remained rather stable in the twenty-first century. However, whether trends in adolescent cannabis use differ between socioeconomic groups is not known. The aim of this study was to examine trends in cannabis use according to socioeconomic status among Finnish adolescents from 2000 to 2015.

METHODS

A population-based school survey was conducted biennially among 14-16-year-old Finns between 2000 and 2015 (n = 761,278). Distributions for any and frequent cannabis use over time according to socioeconomic adversities were calculated using crosstabs and chi-square test. Associations between any and frequent cannabis use, time, and socioeconomic adversities were studied using binomial logistic regression results shown by odds ratios with 95% confidence intervals.

RESULTS

At the overall level, the prevalences of lifetime and frequent cannabis use varied only slightly between 2000 and 2015. Cannabis use was associated with socioeconomic adversities (parental unemployment in the past year, low parental education, and not living with both parents). The differences in any and frequent cannabis use between socioeconomic groups increased significantly over the study period.

CONCLUSIONS

Although the overall changes in the prevalence of adolescent cannabis use were modest, cannabis use increased markedly among adolescents with the most socioeconomic adversities. Socioeconomic adversities should be considered in the prevention of adolescent cannabis use.

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.

Multimorbidity and mortality in Ontario, Canada: A population-based retrospective cohort study

Objective:

To examine the relationship between multimorbidity and mortality, and whether relationship varied by material deprivation/rural location and by age.

Methods:

Retrospective population-based cohort study conducted using 2013–14 data from previously created cohort of Ontario, Canada residents classified according to whether or not they had multimorbidity, defined as having 3+ of 17 chronic conditions. Adjusted rate ratios were calculated to compare mortality rates for those with and without multimorbidity, comparing rates by material deprivation/rural location, and by age group.

Results:

There were 13,581,191 people in the cohort ages 0 to 105 years; 15.2% had multimorbidity. Median length of observation was 365 days. Adjusted mortality rate ratios did not vary by material deprivation/rural location; overall adjusted mortality rate ratio was 2.41 (95% CI 2.37–2.45). Adjusted mortality rate ratios varied by age with ratios decreasing as age increased. Overall rate ratio was 14.7 (95% CI 14.48–14.91). Children (0–17 years) had highest ratio, 40.06 (95% CI 26.21–61.22). Youngest adult age group (18–24 years) had rate ratio of 9.96 (95% CI 7.18–13.84); oldest age group (80+ years) had rate ratio of 1.97 (95% CI 1.94–2.04).

Conclusion:

Compared to people without multimorbidity, multimorbidity conferred higher risk of death in this study at all age groups. Risk was greater in early and middle adulthood than in older ages. Results reinforce the fact multimorbidity is not just a problem of aging, and multimorbidity leads not only to poorer health and higher health care utilization, but also to a higher risk of death at a younger age.

Socioeconomic Position, Multimorbidity and Mortality in a Population Cohort: The HUNT Study

Multimorbidity and socioeconomic position are independently associated with mortality. We investigated the association of occupational position and several multimorbidity measures with all-cause mortality. A cohort of people aged 35 to 75 years who participated in the Trøndelag Health Study in 2006-2008 and had occupational data was linked to the Norwegian National Population Registry for all-cause mortality from study entry until 1 February 2019. Logistic regression models for each occupational group were used to analyze associations between the number of conditions and 10-year risk of death. Cox regression models were used to examine associations between combinations of multimorbidity, occupational position, and mortality. Analyses were conducted for men and women. Included were 31,132 adults (16,950 women (54.4%)); occupational groups: high, 7501 (24.1%); low, 15,261 (49.0%)). Increased mortality was associated with lower occupational group, more chronic conditions, and all multimorbidity measures. The joint impact of occupational group and multimorbidity on mortality was greater in men than women. All multimorbidity measures are strongly associated with mortality, with varying occupational gradients. Social differences in multimorbidity are a public health challenge and necessitate consideration in health care. Men in lower occupational groups seem to be a particularly vulnerable group.

Long-term effects of socioeconomic status on the incidence of decreased glomerular filtration rate in a Southeast Asian cohort

BACKGROUND

There is limited information on the role of low socioeconomic status (SES) in the development of new chronic kidney disease (CKD) in the general population, especially from developing countries. This study will test the hypothesis that low SES increases the risk of incidence of decreased glomerular filtration rate (GFR, used as an estimate for CKD) in a Thai worker cohort.

METHOD

In this prospective, longitudinal observational study, we evaluated the association of income and educational attainment on incident decreased GFR (iGFR <60 mL/min/1.73 m²) over a 27-year period in employees of Electricity Generating Authority of Thailand. In 1985, subjects participated in a health survey and were re-examined in 1997, 2002, 2007 and 2012. Education was classified into three categories: low, 0-8th grade; medium, 9-12th grade; and high, >12th grade. Income was categorised as follows: low <10 000 Thai Baht (THB)/month; medium, 10 000-20 000 THB/month; and high, >20 000 THB/month. HRs of iGFR<60 mL/min/1.73 m² were estimated using Cox interval-censored models with high income or education as the reference groups after adjustments for clinical risk factors.

RESULTS

Participants (n=3334) were followed for 23 (15, 27) years. When evaluated separately, both education and income were risk factors for iGFR<60 mL/min/1.73 m² (adjusted HR education: medium-1.26 (95% CI 1.13 to1.42) and low-1.57 (95% CI 1.36 to 1.81) and adjusted HR income: medium-1.21 (95% CI 0.97 to 1.50) and low-1.47 (95% CI 1.18 to 1.82)). When both income and education were included together, low and medium education remained independently associated with iGFR<60 mL/min/1.73 m².

CONCLUSIONS

Low education was independently associated with increased risk of decreased GFR in a Thai worker population. Strategies to identify risk factors among low SES may be useful to prevent early CKD.

Cohort profile: The prospective study on Chinese elderly with multimorbidity in primary care in Hong Kong

PURPOSE

This is an ongoing prospective cohort aiming to examine the biopsychosocial health profiles and predictors of health outcomes of older patients with multimorbidity in primary care in Hong Kong.

PARTICIPANTS

From April 2016 to October 2017, 1077 patients aged 60+ years with at least two chronic diseases were recruited in four public primary care clinics in the New Territories East Region of Hong Kong.

FINDINGS TO DATE

After weighting, the patients had 4.1 (1.8) chronic conditions and 2.5 (1.9) medications on average; 37% forgot taking medication sometimes; 71% rated their health as fair or poor; 17% were frail; 73% reported one (21%) or two or more (52%) body pain areas; 62% were overweight/obese; 23% reported chewing difficulty, 18% reported incontinence; 36% had current stage 1/2 hypertension; 38% had handgrip strength below the cut-off; 10% screened positive in sarcopenia; 17% had mild or severer cognitive impairment; 17% had mild to severe depression; 16% had mild to severe anxiety; 50% had subthreshold to severe insomnia; 28% indicated being lonely; 12% needed help in at least one out of the five daily functions and the EuroQoL-5-Dimensions-5-Level index score was 0.81 (0.20) and its Visual Analogue Scale (VAS) score was 67.6 (14.6). In the past 12 months, 17% were hospitalised, 92% attended general outpatient clinics, 70% attended specialist outpatient clinics and 10% used elderly daycare centre services, the median out-of-pocket health cost was HK$1000 (US$150). Female and male patients showed significant differences in many biopsychosocial health aspects.

FUTURE PLANS

With assessments and clinical data, the cohort can be used for understanding longitudinal trajectories of biopsychosocial health profiles of Chinese older patients with multimorbidity in primary care. We are also initially planning cohort studies on factors associated with various health outcomes, as well as quality of life and healthcare use.

COHORT REGISTRATION NUMBER

ChiCTR-OIC-16008477.

The prognostic significance of geriatric syndromes and resources

BACKGROUND

Geriatric syndromes (GS) do not fit into discrete disease categories and are often underdiagnosed in hospitalized older adults. Geriatric resources (GR) are also not routinely collected in clinical settings, although this may potentiate the beneficial effects of clinical decisions. The prognostic relevance of GS and GR has never been systematically evaluated through clinical tools developed for clinical decision purposes.

AIM

To ascertain the impact of common GS and GR on patients' prognosis as assessed by means of the comprehensive geriatric assessment (CGA)-based Multidimensional Prognostic Index (MPI).

METHODS

One hundred and thirty-five hospitalized patients aged 70 years and older underwent a CGA evaluation with calculation of the MPI on admission and discharge. Accordingly, patients were subdivided in low (MPI-1, score 0-0.33), moderate (MPI-2, score 0.34-0.66), and severe (MPI-3, score 0.67-1)-risk of mortality at 1 month and 1 year. Nine GR and 17 GS were identified and collected accordingly.

RESULTS

A lower number of GS and a higher number of GR were shown to be highly significantly correlated with a lower MPI, as well as years of education, grade of care, and number of medications independent of age, sex and number of GS or GR. Underweight and obesity according to the BMI were significantly correlated to higher number of GS. Patients with more GR had a significantly higher chance of being discharged home.

CONCLUSIONS

The MPI evaluation together with GS and GR in acute care for older patients should be encouraged to improve clinical decision-making.

Overweight: A Protective Factor against Comorbidity in the Elderly

The aim of this study was to investigate the relationship between body mass index (BMI) categories and comorbidity in 9067 patients (age range 18‒94 years) who underwent upper digestive endoscopy in Northern Sardinia, Italy. The majority of participants (62.2%) had a BMI under 25 kg/m², overweight was detected in 30.4%, and obesity (BMI ≥ 30 kg/m²) in 7.4% of patients. The most frequent illness recorded was hypertension followed by cardiovascular and liver disease. The multivariate analysis, after adjusting for sex, residence, marital status, smoking habits, occupation and hospitalization detected an association between comorbidity and aging that was statistically significant and progressive. Among patients younger than 60 years (n = 5612) the comorbidity risk was higher for BMI ranging 27.5‒29.9 kg/m² compared with BMI 25.0‒27.4 kg/m² (RR = 1.38; 95% CI 1.27‒1.50 vs. RR = 0.86; 95% CI 0.81‒0.90). In patients older than 60 years (n= 3455) the risk was lower for a BMI in the range 27.5–29.9 kg/m² compared with a BMI in the range 25.0–27.4 kg/m² (RR = 1.11; 95% CI 1.05‒1.18 vs. RR = 1.28; 95% CI 1.21‒1.35). These results suggest that being moderately overweight is a marker of a healthy aging process and might protect, at least in part, against comorbidity. However, further research is needed to better understand this unexpected finding.

Health related quality of life in multimorbidity: a primary-care based study from Odisha, India

BACKGROUND

Multimorbidity, the coexistence of two or more chronic conditions is increasingly prevalent in primary care populations. Despite reports on its adverse impact on health outcomes, functioning and well-being, it's association with quality of life is not well known in low and middle income countries. We assessed the health-related quality of life (HRQoL) of primary care patients with multimorbidity and identified the influencing factors.

METHODS

This cross-sectional study was done across 20 public and 20 private primary care facilities in Odisha, India. Data were collected from 1649 adult out-patients using a structured multimorbidity assessment questionnaire for primary care (MAQ-PC). HRQoL was assessed by the 12-item short-form health survey (SF-12). Both physical (PCS) and mental components scores (MCS) were calculated. Multiple regression analysis was performed to determine the association of HRQoL with socio-demographics, number, severity and typology of chronic conditions.

RESULTS

Around 28.3% [95% CI: 25.9-30.7] of patients had multimorbidity. Mean physical component scope (PCS) and mental component score (MCS) of QoL in the study population was 43.56 [95% CI: 43.26-43.86] and 43.69 [95% CI: 43.22-44.16], respectively. Patients with multimorbidity reported poorer mean PCS [43.23, 95% CI: 42.62-43.84] and MCS [41.58, 95% CI: 40.74-42.43] compared to those without. After adjusting for other variables, morbidity severity burden score was found to be negatively associated with MCS [adjusted coefficient: -0.24, 95% CI - 0.41 to - 0.08], whereas no significant association was seen with PCS. Hypertension and diabetes with arthritis and acid peptic diseases were found to be negatively related with MCS. Within multimorbidity, lower education was inversely associated with mental QoL and positively associated with physical QoL score after adjusting for other variables.

CONCLUSION

Our findings demonstrate the diverse negative effects of multimorbidity on HRQoL and reveal that apart from count of chronic conditions, severity and pattern also influence HRQoL negatively. Health care providers should consider severity as an outcome measure to improve QoL especially in individuals with physical multimorbidity. Given the differences observed between age groups, it is important to identify specific care needs for each group. Musculoskeletal clusters need prioritised attention while designing clinical guidelines for multimorbidity.

Mortality of midlife women with surgically verified endometriosis—a cohort study including 2.5 million person-years of observation

STUDY QUESTION

Is all-cause and cause-specific mortality increased among women with surgically verified endometriosis?

SUMMARY ANSWER

The all-cause and cause-specific mortality in midlife was lower throughout the follow-up among women with surgically verified endometriosis compared to the reference cohort.

WHAT IS KNOWN ALREADY

Endometriosis has been associated with an increased risk of comorbidities such as certain cancers and cardiovascular diseases. These diseases are also common causes of death; however, little is known about the mortality of women with endometriosis.

STUDY DESIGN, SIZE, DURATION

A nationwide retrospective cohort study of women with surgically verified diagnosis of endometriosis was compared to the reference cohort in Finland (1987–2012). Follow-up ended at death or 31 December 2014. During the median follow-up of 17 years, 2.5 million person-years accumulated.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Forty-nine thousand nine hundred and fifty-six women with at least one record of surgically verified diagnosis of endometriosis in the Finnish Hospital Discharge Register between 1987 and 2012 were compared to a reference cohort of 98 824 age- and municipality-matched women. The age (mean ± standard deviation) of the endometriosis cohort was 36.4 ± 9.0 and 53.6 ± 12.1 years at the beginning and at the end of the follow-up, respectively. By using the Poisson regression models the crude and adjusted all-cause and cause-specific mortality rate ratios (MRR) and 95% confidence intervals (CI) were assessed. Calendar time, age, time since the start of follow-up, educational level, and parity adjusted were considered in the multivariate analyses.

MAIN RESULTS AND THE ROLE OF CHANCE

A total of 1656 and 4291 deaths occurred in the endometriosis and reference cohorts, respectively. A lower all-cause mortality was observed for the endometriosis cohort (adjusted MRR, 0.73 [95% CI 0.69 to 0.77])—there were four deaths less per 1000 women over 10 years. A lower cause-specific mortality contributed to this: the adjusted MRR was 0.88 (95% CI 0.81 to 0.96) for any cancer and 0.55 (95% CI 0.47 to 0.65) for cardiovascular diseases, including 0.52 (95% CI 0.42 to 0.64) for ischemic heart disease and 0.60 (95% CI 0.47 to 0.76) for cerebrovascular disease. Mortality due to alcohol, accidents and violence, respiratory, and digestive disease-related causes was also decreased.

LIMITATIONS, REASONS FOR CAUSATION

These results are limited to women with endometriosis diagnosed by surgery. In addition, the study does not extend into the oldest age groups. The results might be explained by the characteristics and factors related to women’s lifestyle, and/or increased medical attention and care received, rather than the disease itself.

WIDER IMPLICATIONS OF THE FINDINGS

These reassuring data are valuable to women with endometriosis and to their health care providers. Nonetheless, more studies are needed to address the causality.

STUDY FUNDING/COMPETING INTEREST

This research was funded by the Hospital District of Helsinki and Uusimaa and The Finnish Medical Foundation. None of the authors report any competing interest in relation to the present work; all the authors have completed the disclosure form.

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

BACKGROUND

Multimorbidity is associated with higher mortality, but the relationship with cancer and cardiovascular mortality is unclear. The influence of demographics and type of condition on the relationship of multimorbidity with mortality remains unknown. We examine the relationship between multimorbidity (number/type) and cause of mortality and the impact of demographic factors on this relationship.

METHODS

Data source: the UK Biobank; 500,769 participants; 37-73 years; 53.7% female. Exposure variables: number and type of long-term conditions (LTCs) (N = 43) at baseline, modelled separately. Cox regression models were used to study the impact of LTCs on all-cause/vascular/cancer mortality during median 7-year follow-up. All-cause mortality regression models were stratified by age/sex/socioeconomic status.

RESULTS

All-cause mortality is 2.9% (14,348 participants). Of all deaths, 8350 (58.2%) were cancer deaths and 2985 (20.8%) vascular deaths. Dose-response relationship is observed between the increasing number of LTCs and all-cause/cancer/vascular mortality. A strong association is observed between cardiometabolic multimorbidity and all three clinical outcomes; non-cardiometabolic multimorbidity (excluding cancer) is associated with all-cause/vascular mortality. All-cause mortality risk for those with ≥ 4 LTCs was nearly 3 times higher than those with no LTCs (HR 2.79, CI 2.61-2.98); for ≥ 4 cardiometabolic conditions, it was > 3 times higher (HR 3.20, CI 2.56-4.00); and for ≥ 4 non-cardiometabolic conditions (excluding cancer), it was 50% more (HR 1.50, CI 1.36-1.67). For those with ≥ 4 LTCs, morbidity combinations that included cardiometabolic conditions, chronic kidney disease, cancer, epilepsy, chronic obstructive pulmonary disease, depression, osteoporosis and connective tissue disorders had the greatest impact on all-cause mortality. In the stratified model by age/sex, absolute all-cause mortality was higher among the 60-73 age group with an increasing number of LTCs; however, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those 37-49 years, especially men. While socioeconomic status was a significant predictor of all-cause mortality, mortality risk with increasing number of LTCs remained constant across different socioeconomic gradients.

CONCLUSIONS

Multimorbidity is associated with higher all-cause/cancer/vascular mortality. Type, as opposed to number, of LTCs may have an important role in understanding the relationship between multimorbidity and mortality. Multimorbidity had a greater relative impact on all-cause mortality in middle-aged as opposed to older populations, particularly males, which deserves exploration.

Bringing complexity into clinical practice: An internistic approach

Modern medicine, still largely focused on single diseases, is unprepared for managing clinical complexity (CC), which is an emerging issue. Ageing of the general population has favoured the occurrence of chronic diseases, which generate multimorbidity that has been considered for many years the main feature of CC. However, more recent studies have shown that CC is something more and different and originates from the dynamic interaction among the patient's intrinsic factors (age, gender, multimorbidity, frailty) as well as contextual factors (socioeconomic, behavioural, cultural, and environmental). The result of these interactions is non-linear and unpredictable behaviour, which is difficult to manage both in clinical practice and in the organisation of care. Up to now, the prevalent approach has consisted of breaking down and separately analysing each CC component. Consequently, only incomplete strategies to improve health outcomes have been developed, such as limited patient-centred algorithms, deprescription of therapies, and local clinical governance interventions. Medical education has a pivotal role in transmitting the knowledge of complexity, making it realistically understandable and manageable. Future research should aim at implementing our knowledge of CC, developing new tools for its quantitation, and finding new solutions to improve important health outcomes at a sustainable cost.

Multimorbidity and functional impairment-bidirectional interplay, synergistic effects and common pathways

This review discusses the interplay between multimorbidity (i.e. co-occurrence of more than one chronic health condition in an individual) and functional impairment (i.e. limitations in mobility, strength or cognition that may eventually hamper a person's ability to perform everyday tasks). On the one hand, diseases belonging to common patterns of multimorbidity may interact, curtailing compensatory mechanisms and resulting in physical and cognitive decline. On the other hand, physical and cognitive impairment impact the severity and burden of multimorbidity, contributing to the establishment of a vicious circle. The circle may be further exacerbated by people's reduced ability to cope with treatment and care burden and physicians' fragmented view of health problems, which cause suboptimal use of health services and reduced quality of life and survival. Thus, the synergistic effects of medical diagnoses and functional status in adults, particularly older adults, emerge as central to assessing their health and care needs. Furthermore, common pathways seem to underlie multimorbidity, functional impairment and their interplay. For example, older age, obesity, involuntary weight loss and sedentarism can accelerate damage accumulation in organs and physiological systems by fostering inflammatory status. Inappropriate use or overuse of specific medications and drug-drug and drug-disease interactions also contribute to the bidirectional association between multimorbidity and functional impairment. Additionally, psychosocial factors such as low socioeconomic status and the direct or indirect effects of negative life events, weak social networks and an external locus of control may underlie the complex interactions between multimorbidity, functional decline and negative outcomes. Identifying modifiable risk factors and pathways common to multimorbidity and functional impairment could aid in the design of interventions to delay, prevent or alleviate age-related health deterioration; this review provides an overview of knowledge gaps and future directions.

Social determinants and cardiovascular disease mortality in Panama, 2012-2016

Background

The aims of this study were to determine the geographic and time variation of social determinants of health (SDH) and cardiovascular disease (CVD) mortality in Panama from 2012 to 2016, and to identify which of the SDH has the strongest correlation with a socioeconomic index (SEI).

Methods

We conducted an ecological study obtaining mortality from the National Mortality Register and socioeconomic variables derived from the National Household Survey (NHS). The International Classification of Diseases 10th revision codes I20–I25 and I60–I69 were used for ischemic heart disease (IHD) and stroke, respectively. Standardized age-adjusted mortality rates were calculated by direct method. Mortality rates and socioeconomic variables were evaluated together in a panel data model. A SEI was developed from factorial analysis by principal components with a polychoric correlation matrix. Provinces and regions were categorized in tertiles according to median value of the SEI score.

Results

The NHS evaluated an average of 15,919 households per year. The mean of age throughout the study period was 41 years. The average monthly income increased, from US$ (SD) 331.94 (5.38) in 2012, to 406.24 (5.81) in 2016, whereas the social security health coverage remained in a range of 57–58%. The mean number of school years was twelve. Significant geographical and temporal variations in social determinants and mortality rates were observed throughout the country. Colon, categorized in the middle tertile according to the SEI, presented higher IHD mortality rates. Darién (in the lowest SEI tertile) Colón and Herrera had higher stroke mortality rates. The SEI categorized indigenous territories in the lowest tertile. Total years of education was the strongest correlated variable with the SEI, when we excluded the population living in indigenous territories. However, when this population was included, social security coverage had the strongest correlation with the SEI.

Conclusion

We observed geographical and temporal disparities in SDH and CVD mortality rates. Further epidemiological studies are warranted in the provinces of Colón, Darien, Herrera and Los Santos to explore in-depth the higher CVD mortality rates observed in these provinces.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6508-8) contains supplementary material, which is available to authorized users.

Composite health behaviour classifier as the basis for targeted interventions and global comparisons in men's health

INTRODUCTION

Lifestyle-related diseases are the leading cause of death among North American men. We evaluated health behaviours and their predictors that contribute to morbidity and mortality among Canadian men as a means to making recommendations for targeted interventions.

METHODS

A cross-sectional analysis of Canadian men drawn from 5362 visitors to our online survey page was conducted. The current study sample of 2000 men (inclusion: male and >18 years; exclusion: incomplete surveys) were stratified to the 2016 Canadian census. The primary outcome was the number of unhealthy men classified using our Canadian Composite Classification of Health Behaviour (CCCHB) score. Secondary outcomes included the number of men with unhealthy exercise, diet, smoking, sleep, and alcohol intake, as well as socioeconomic and demographic factors associated with unhealthy behaviours to be used for targeting future interventions.

RESULTS

Only 118/2000 (5.9%) men demonstrated 5/5 healthy behaviours, and 829 (41.5%) had 3/5 unhealthy behaviours; 391 (19.6%) men currently smoked, 773 (38.7%) demonstrated alcohol overuse, 1077 (53.9%) did not get optimal sleep (<7 or >9 hours per night), 977 (48.9%) failed to exercise >150 minutes/week, and 1235 (61.8%) had an unhealthy diet. Multivariate analysis indicated that men with high school education were at increased risk of unhealthy behaviours (odds ratio [OR] 1.58; 95% confidence interval [CI] 1.15-2.18; p=0.005), as were men living with relatives (OR 2.10; 95% CI1.04-4.26; p=0.039), or with their partner and children (OR 1.34; 95% CI 1.02-1.76; p=0.034).

CONCLUSIONS

An overwhelming 41.5% of Canadian men had 3/5 unhealthy behaviours, affirming the need for targeted lifestyle interventions. Significant health inequities within vulnerable subgroups of Canadian men were identified and may guide the content and delivery of future interventions.

Mortality and its predictors in patients with rheumatoid arthritis: a Danish population-based inception cohort study

OBJECTIVES

To investigate mortality and its predictors in a retrospectively defined population-based rheumatoid arthritis (RA) inception cohort Method: We included patients ascertained with incident RA from a region in the southern part of Denmark from 1995 to 2002. All patients fulfilled the 1987 American College of Rheumatology criteria for RA. The patients were followed from RA classification until death, emigration, or end of follow-up on 31 December 2013. We used personal record linkage with national public registers to obtain information on education, employment, cohabitation, comorbidity, and vital status.

RESULTS

The cohort comprised 509 patients, of whom 200 (39%) died during 6079 person-years. The most frequent underlying causes of death were cardiovascular disease (34%), neoplasms (26%), and respiratory disease (12%). In rheumatoid factor (RF)-positive males, the standardized mortality ratio (95% confidence interval) from all causes was 1.47 (1.15-1.88), from cardiovascular disease 1.63 (1.09-2.46), from respiratory disease 2.03 (1.06-3.90), and from neoplasms 2.26 (1.02-5.03) in the age group < 70 years, and 2.45 (1.23-4.90) in the age group > 79 years. On applying Cox models after multiple imputations by chained equations, we found that RF modified the effect of age. Employment status, comorbidity, and gender were independent baseline predictors of subsequent mortality.

CONCLUSION

In this cohort, significant excess mortality was confined to RF-positive males. The effect of age was modified by RF, and employment status and comorbidity were independent predictors of mortality.

ESTABLISHED COMORBIDITY IN ARTERIAL HYPERTENSION PATIENTS IN RURAL AREAS

Aim. To analyze the specifics of comorbidity forming and age­related correlations of the risk factors (RF) distribution in arterial hypertension (AH) patients living in rural areas.

Material and methods. In 2015­2017 a retrospective analysis of 2500 patients database was done at two general practitioners offices in Konakovsky District of Tverskaya Oblast. Of those, 350 were selected (14%) at the age 44­53 (164 males, 186 females) among the charts containing most complete data on the dispanserization. Additionally, surveying of the group was done for more detailed retrospective analysis of comorbidity and RF existence during lifetime of 25­35 years.

Results. In the structure of comorbidity AH predominates, which has been diagnosed in 50,86% of patients; mostly it is diagnosed at the age 44­53 (81,06%). After AH, 2nd place is held by dorsopathies (24%), 3rd — gastrointestinal disorders (12%). For chronic pulmonary obstructive disease and cerebrovascular disease — it is less than 3%. 96,1% of men with AH are smokers at the age 18 to 53 y. o. By the age 53, in 40,26% of men and 36,63% of women there is bodyweight increase; and raised cholesterol — in 48,05% and 22,77%, respectively.

Conclusion. In rural areas inhabitants, the formation of comorbidity is ongoing mostly at age 44­53 y. o. Of the specifics of comorbidity in these patients, there is often combination of AH with dorsopathies, and quite rare — with chronic obstructive lung disease or cerebrovascular diseases. The observed at the age 34­43 “diagnostic gap” points on the necessity for attention to this exact age strata with the aim of ontime diagnostics and early stages of diseases reveal. The structure of RF during the lifetime is not homogenic and is the highest at the age of comorbidity forming (except smoking and professional harms). All the considered RF are more prominent in men than in women.

Multimorbidity and mortality: A 15-year longitudinal registry-based nationwide Danish population study

BACKGROUND

Knowledge about prevalent and deadly combinations of multimorbidity is needed.

OBJECTIVE

To determine the nationwide prevalence of multimorbidity and estimate mortality for the most prevalent combinations of one to five diagnosis groups. Furthermore, to assess the excess mortality of the combination of two groups compared to the product of mortality associated with the single groups.

DESIGN

A prospective cohort study using Danish registries and including 3.986.209 people aged ≥18 years on 1 January, 2000. Multimorbidity was defined as having diagnoses from at least 2 of 10 diagnosis groups: lung, musculoskeletal, endocrine, mental, cancer, neurological, gastrointestinal, cardiovascular, kidney, and sensory organs. Logistic regression (odds ratios, ORs) and ratio of ORs (ROR) were used to study mortality and excess mortality.

RESULTS

Prevalence of multimorbidity was 7.1% in the Danish population. The most prevalent combination was the musculoskeletal-cardiovascular (0.4%), which had double the mortality (OR, 2.03) compared to persons not belonging to any of the diagnosis groups but showed no excess mortality (ROR, 0.97). The neurological-cancer combination had the highest mortality (OR, 6.35), was less prevalent (0.07%), and had no excess mortality (ROR, 0.94). Cardiovascular-lung was moderately prevalent (0.2%), had high mortality (OR, 5.75), and had excess mortality (ROR, 1.18). Endocrine-kidney had high excess mortality (ROR, 1.81) and cancer-mental had low excess mortality (ROR, 0.66). Mortality increased with the number of groups.

CONCLUSIONS

All combinations had increased mortality risk with some of them having up to a six-fold increased risk. Mortality increased with the number of diagnosis groups. Most combinations did not increase mortality above that expected, that is, were additive rather than synergistic.

Socioeconomic Status, Frailty, and All-Cause Mortality in Korean Older Adults: A 3-Year Population-Based Prospective Study

Background

Little is known regarding the effects of socioeconomic status (SES) and frailty on mortality in Korea.

Objective

This study investigated the combined impact of low SES and frailty on all-cause mortality in Korean older adults.

Methods

Study sample at baseline comprised 7,960 community-dwelling adults (56.8% women) aged 65 years and older. The Cox proportional hazards model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of low SES and frailty for all-cause mortality.

Results

Overall, low SES plus frailty resulted in an increased risk of all-cause mortality (HR = 1.56, 95% CI = 1.09–2.23, P = 0.015) even after adjustments for all the measured covariates, as compared with high SES plus nonfrailty (HR = 1). Among older adults aged 65–75 years, the increased mortality risk of either low SES plus nonfrailty (HR = 1.37, 95% CI = 1.02–1.84, P = 0.038) or high SES plus frailty (HR = 2.09, 95% CI = 1.12–3.91, P = 0.021) remained significant even after adjustments for all the covariates, as compared with high SES plus nonfrailty (HR = 1).

Conclusion

The current findings suggest that either low SES or frailty is significantly associated with increased all-cause mortality in Korean older adults.