Socioeconomic inequalities in prevalence and development of multimorbidity across adulthood: A longitudinal analysis of the MRC 1946 National Survey of Health and Development in the UK

Effects of mental health status during adolescence on primary care costs in adulthood across three British cohorts

PURPOSE

This study examines the association between mental health problems in adolescence and general practice (GP) costs during adulthood up to age 50 in the UK.

METHODS

We conducted secondary analyses of three British birth cohorts (individuals born in single weeks in 1946, 1958 and 1970). Data for the three cohorts were analysed separately. All respondents who participated in the cohort studies were included. Adolescent mental health status was assessed in each cohort using the Rutter scale (or, for one cohort, a forerunner of that scale) completed in interviews with parents and teachers when cohort members were aged around 16. Presence and severity of conduct and emotional problems were modelled as independent variables in two-part regression models in which the dependent variable was costs of GP services from data collection sweeps up to mid-adulthood. All analyses were adjusted for covariates (cognitive ability, mother's education, housing tenure, father's social class and childhood physical disability).

RESULTS

Adolescent conduct and emotional problems, particularly when coexisting, were associated with relatively high GP costs in adulthood up to age 50. Associations were generally stronger in females than males.

CONCLUSION

Associations between adolescent mental health problems and annual GP cost were evident decades later, to age 50, suggesting that there could be significant future savings to healthcare budgets if rates of adolescent conduct and emotional problems could be reduced.

TRIAL REGISTRATION

Not applicable.

Socioeconomic inequalities in accumulation of multimorbidity in England from 2019 to 2049: a microsimulation projection study

BACKGROUND

There are socioeconomic inequalities in the prevalence of multimorbidity and its accumulation across the life course. Estimates of multimorbidity prevalence in English primary care increased by more than two-thirds from 2004 to 2019. We developed a microsimulation model to quantify current and projected multimorbidity inequalities in the English adult population.

METHODS

We used primary care data for adults in England from the Clinical Practice Research Datalink Aurum database between 2004 and 2019, linked to the 2015 English Index of Multiple Deprivation (IMD), to model time individuals spent in four health states (healthy, one chronic condition, basic multimorbidity [two or more chronic conditions], and complex multimorbidity [three or more chronic conditions affecting three or more body systems]) by sex, age, IMD quintile, birth cohort, and region. We applied these transition times in a stochastic dynamic continuous-time microsimulation model to Office for National Statistics population estimates for adults aged 30-90 years. We calculated projected prevalence and cumulative incident cases from 2019 to 2049 by IMD quintile, age group (younger than 65 years vs 65 years and older), and years to be lived without multimorbidity at age 30 years.

FINDINGS

Under the assumption that all chronic conditions were lifelong, and that once diagnosed there was no recovery, we projected prevalence of multimorbidity (basic or complex) increases by 34% from 53·8% in 2019 to 71·9% (95% uncertainty interval 71·8-72·0) in 2049. This rise equates to an 84% increase in the number of people with multimorbidity: from 19·2 million in 2019 to 35·3 million in 2049 (35·3 million to 35·4 million). This projected increase is greatest in the most deprived quintile, with an excess 1·07 million (1·04 million to 1·10 million) cumulative incident basic multimorbidity cases and 0·70 million (0·67 million to 0·74 million) complex multimorbidity cases over and above the projected cases for the least deprived quintile, largely driven by inequalities in those younger than 65 years. The median expected number of years to be lived without multimorbidity at age 30 years in 2019 is 15·12 years (14·62-16·01) in the least deprived IMD quintile and 12·15 years (11·61-12·60) in the most deprived IMD quintile.

INTERPRETATION

The number of people living with multimorbidity will probably increase substantially in the next 30 years, a continuation of past observed increases partly driven by changing population size and age structure. Inequalities in the multimorbidity burden increase at each stage of disease accumulation, and are projected to widen, particularly among the working-age population. Substantial action is needed now to address population health and to prepare health-care and social-care systems for coming decades.

FUNDING

University of Liverpool and National Institute for Health and Care Research School for Public Health Research.

Report on the Joint Workshop on the Relations between Health Inequalities, Ageing and Multimorbidity, Iceland, May 3-4, 2023

This paper is a summary of key presentations from a workshop in Iceland on May 3-4, 2023 arranged by Aarhus University and with participation of the below-mentioned scientists. Below you will find the key messages from the presentations made by: Professor Jan Vandenbroucke, Department of Clinical Epidemiology, Aarhus University, Emeritus Professor, Leiden University; Honorary Professor, London School of Hygiene & Tropical Medicine, UKProfessor, Chair Henrik Toft Sørensen, Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, DenmarkProfessor David H. Rehkopf, Director, the Stanford Center for Population Health Sciences, Stanford University, CA., USProfessor Jaimie Gradus, Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts, USProfessor Johan Mackenbach, Emeritus Professor, Department of Public Health, Erasmus University Rotterdam, HollandProfessor, Chair M Maria Glymour, Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, Massachusetts, USProfessor, Dean Sandro Galea, School of Public Health, Boston University, Boston, Massachusetts, USProfessor Victor W. Henderson, Departments of Epidemiology & Population Health and of Neurology & Neurological Sciences, Stanford University, Stanford, CA, US; Department of Clinical Epidemiology, Aarhus University, Aarhus, DK.

Socioeconomic Status Plays a Moderating Role in the Association Between Multimorbidity and Health-Related Quality of Life Among Cancer Patients

This study aimed to explore the moderating role of socioeconomic status (SES) in the association between multimorbidity and health-related quality of life (HRQOL) among cancer patients in Anhui China. A total of 560 cancer patients were recruited for the cross-section study. Socio-demographic and clinical characteristics were analyzed using descriptive statistics. Tobit regression analysis was employed to investigate the relationship between multimorbidity and HRQOL as well as to assess the moderating effect of SES. The research findings indicated that 76.61% of cancer patients experienced multimorbidity, with psychological multimorbidity being the most prevalent (45.54%), followed by physical-psychological multimorbidity (20.89%). Moreover, physical-psychological multimorbidity had the most substantial adverse effect on HRQOL (P < .001). The presence of multimorbidity was correlated with a significant decline in HRQOL, with a 17.5% (P < .001) decrease in HRQOL for each additional multimorbidity. Additionally, SES played a significant role in moderating the impact of multimorbidity on HRQOL in cancer patients. (Marginal effect = -0.022, P < .01). The high SES group exhibited a higher overall HRQOL than the low SES group (Marginal effect = 0.068, P < .001). And with the increase of multimorbidity, HRQOL in the higher SES showed a more pronounced downward trend, compared with the lower SES (β = -.270 vs β = -.201, P < .001). Our findings underscore the importance of preventing and managing multimorbidity in cancer patients, particularly those with low SES. Furthermore, it is essential to consider the impact of the rapid decline in HRQOL as the number of multimorbidity increases in individuals with higher SES. It is imperative to explore interdisciplinary and continuous collaborative management models.

Socioeconomic inequalities in physical, psychological, and cognitive multimorbidity in middle-aged and older adults in 33 countries: a cross-sectional study

BACKGROUND

Many physical, psychological, and cognitive disorders are highly clustered among populations with low socioeconomic status. However, the extent to which socioeconomic status is associated with different combinations of these disorders is unclear, particularly outside high-income countries. We aimed to evaluate these associations in 33 countries including high-income countries, upper-middle-income countries, and one lower-middle-income country.

METHODS

This cross-sectional multi-region study pooled individual-level data from seven studies on ageing between 2017 and 2020. Education and total household wealth were used to measure socioeconomic status. Physical disorder was defined as having one or more of the self-reported chronic conditions. Psychological and cognitive disorders were measured by study-specific instruments. The outcome included eight categories: no disorders, physical disorder, psychological disorder, cognitive disorder, and their four combinations. Multivariable-adjusted logistic regression models were used to estimate odds ratios (ORs) and 95% CIs for the associations of socioeconomic status with these outcomes separately for high-income countries, upper-middle-income countries, and the lower-middle-income country.

FINDINGS

Among 167 376 individuals aged 45 years and older, the prevalence of multimorbidity was 24·5% in high-income countries, 33·9% in upper-middle-income countries, and 8·1% in the lower-middle-income country (India). Lower levels of education, household wealth, and a combined socioeconomic status score were strongly associated with physical, psychological, and cognitive multimorbidity in high-income countries and upper-middle-income countries, with ORs (low vs high socioeconomic status) for physical-psychological-cognitive multimorbidity of 12·36 (95% CI 10·29-14·85; p<0·0001) in high-income countries and of 23·84 (18·85-30·14; p<0·0001) in upper-middle-income countries. The associations in the lower-middle-income country were mixed. Participants with both a low level of education and low household wealth had the highest odds of multimorbidity (eg, OR for physical-psychological-cognitive multimorbidity 21·21 [15·95-28·19; p<0·0001] in high-income countries, 37·07 [25·66-53·56; p<0·0001] in upper-middle-income countries, and 54·96 [7·66-394·38; p<0·0001] in the lower-middle-income country).

INTERPRETATION

In study populations from high-income countries, upper-middle-income countries, and the lower-middle-income country, the odds of multimorbidity, which included physical, psychological, and cognitive disorders, were more than ten times greater in individuals with low socioeconomic status. Equity-oriented policies and programmes that reduce social inequalities in multimorbidity are urgently needed to achieve Sustainable Development Goals.

FUNDING

Zhejiang University, Fundamental Research Funds for the Central Universities, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Wellcome Trust, Medical Research Council, National Institute on Aging, and Academy of Finland.

TRANSLATION

For the Chinese translation of the abstract see Supplementary Materials section.

Reynolds N, R. Barnes M, Hull S, Finer S, Mathur R. Ethnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: A cross-sectional study using clustering in the UK Clinical Practice Research Datalink

BACKGROUND

The population prevalence of multimorbidity (the existence of at least 2 or more long-term conditions [LTCs] in an individual) is increasing among young adults, particularly in minority ethnic groups and individuals living in socioeconomically deprived areas. In this study, we applied a data-driven approach to identify clusters of individuals who had an early onset multimorbidity in an ethnically and socioeconomically diverse population. We identified associations between clusters and a range of health outcomes.

METHODS AND FINDINGS

Using linked primary and secondary care data from the Clinical Practice Research Datalink GOLD (CPRD GOLD), we conducted a cross-sectional study of 837,869 individuals with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) registered with an English general practice between 2010 and 2020. The study population included 777,906 people of White ethnicity (93%), 33,915 people of South Asian ethnicity (4%), and 26,048 people of Black African/Caribbean ethnicity (3%). A total of 204 LTCs were considered. Latent class analysis stratified by ethnicity identified 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity was more common among South Asian (59%, 33,915) and Black (56% 26,048) groups compared to the White population (42%, 777,906). Latent class analysis revealed physical and mental health conditions that were common across all ethnic groups (i.e., hypertension, depression, and painful conditions). However, each ethnic group also presented exclusive LTCs and different sociodemographic profiles: In White groups, the cluster with the highest rates/odds of the outcomes was predominantly male (54%, 44,150) and more socioeconomically deprived than the cluster with the lowest rates/odds of the outcomes. On the other hand, South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. At the end of the study, 4% (34,922) of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black early onset multimorbidity populations (535 and 570, respectively); however, the latter groups died younger and lost more years of life. The 3 ethnic groups each displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. Study limitations include the exclusion of individuals with missing ethnicity information, the age of diagnosis not reflecting the actual age of onset, and the exclusion of people from Mixed, Chinese, and other ethnic groups due to insufficient power to investigate associations between multimorbidity and health-related outcomes in these groups.

CONCLUSIONS

These findings emphasise the need to identify, prevent, and manage multimorbidity early in the life course. Our work provides additional insights into the excess burden of early onset multimorbidity in those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity and highlights the need to ensure healthcare improvements are equitable.

Economic evaluation of a multimorbidity patient centered care model implemented in the Chilean public health system

Multimorbidity and patient-centered care approaches are growing challenges for health systems and patients. The cost of multimorbidity patients and the transition to a new care strategy is still sightly explored. In Chile, more than 70% of the adult population suffer from multimorbidity, opening an opportunity to implement a Multimorbidity patient-centered care model. The objective of this study was to perform an economic evaluation of the model from the public health system perspective.The methodology used a cost-consequence evaluation comparing seven exposed with seven unexposed primary care centers, and their reference hospitals. It followed three steps. First, we performed a Time-Driven Activity-Based Costing with routinely collected data routinely collected. Second, we run a comparative analysis through a propensity score matching and an estimation of the attributable costs to health services utilization at primary, secondary and tertiary care and health outcomes. Third, we estimated implementation and transaction costs.Results showed savings in aggregate costs of the total population (-0.12 (0.03) p < 0.01) during the period under evaluation. Costs in primary care showed a significant increase, whereas tertiary care showed significant savings. Health outcomes were associated with higher survival in patients under the new care model (HR 0.70 (0.05) p < 0.01). Implementation and transaction costs increased as the number of pilot intervention centers increased, and they represented 0,07% of the total annual budget of the Servicio de Salud Metropolitano Sur Oriente. After three years of piloting, the implementation and transaction cost for the total period was USD 1,838,767 and 393,775, respectively.The study's findings confirm the purpose of the new model to place primary health care at the center of care for people with non-communicable chronic diseases. Thus, it is necessary to consider implementation and transaction costs to introduce a broad health system multimorbidity approach. The health system should assume some of them permanently to guarantee sustainability and facilitate scale-up.

Do associations of physical activity and sedentary behaviour with cardiovascular disease and mortality differ across socioeconomic groups? A prospective analysis of device-measured and self-reported UK Biobank data

OBJECTIVE

To examine if individual-level and area-level socioeconomic status (SES) modifies the association of moderate-to-vigorous physical activity (MVPA), domain-specific physical activity and sedentary behaviour with all-cause mortality (ACM) and incident cardiovascular disease (CVD).

METHODS

We used self-reported (International Physical Activity Questionnaire short form) and accelerometer-measured physical activity and sedentary behaviour data from the UK Biobank. We created an individual-level composite SES index using latent class analysis of household income, education and employment status. The Townsend Index was the measure of area-level SES. Cox proportional hazards regression models stratified across SES were used.

RESULTS

In 328 228 participants (mean age 55.9 (SD 8.1) years, 45% men) with an average follow-up of 12.1 (1.4) years, 18 033 deaths and 98 922 incident CVD events occurred. We found an increased ACM risk of low physical activity and high sedentary behaviour and an increased incident CVD risk of low accelerometer-measured moderate-to-vigorous physical activity (ACCEL_MVPA) and high sitting time. We observed statistically significant interactions for all exposures in ACM analyses by individual-level SES (p<0.05) but only for screen time in area-level SES-ACM analysis (p<0.001). Compared with high self-reported moderate-to-vigorous physical activity (IPAQ_MVPA), adjusted ACM HRs for low IPAQ_MVPA were 1.14 (95% CI 1.05 to .25), 1.15 (95% CI 1.06 to 1.24) and 1.22 (95% CI 1.13 to 1.31) in high, medium and low individual-level SES, respectively. There were higher detrimental associations of low ACCEL_MVPA with decreasing area-level SES for both outcomes and of high screen time with ACM in low area-level SES.

CONCLUSION

We found modest evidence suggesting that the detrimental associations of low MVPA and high screen time with ACM and incident CVD are accentuated in low SES groups.

Adverse childhood experiences and the development of multimorbidity across adulthood-a national 70-year cohort study

AIM

To examine impact of adverse childhood experiences (ACE) on rates and development of multimorbidity across three decades in adulthood.

METHODS

Sample: Participants from the 1946 National Survey of Health and Development, who attended the age 36 assessment in 1982 and follow-up assessments (ages 43, 53, 63, 69; N = 3,264, 51% males). Prospectively collected data on nine ACEs was grouped into (i) psychosocial, (ii) parental health and (iii) childhood health. For each group, we calculated cumulative ACE scores, categorised into 0, 1 and ≥2 ACEs. Multimorbidity was estimated as the total score of 18 health disorders.Serial cross-sectional linear regression was used to estimate associations between grouped ACEs and multimorbidity during follow-up. Longitudinal analysis of ACE-associated changes in multimorbidity trajectories across follow-up was estimated using linear mixed-effects modelling for ACE groups (adjusted for sex and childhood socioeconomic circumstances).

FINDINGS

Accumulation of psychosocial and childhood health ACEs were associated with progressively higher multimorbidity scores throughout follow-up. For example, those with ≥2 psychosocial ACEs experienced 0.20(95% CI 0.07, 0.34) more disorders at age 36 than those with none, rising to 0.61(0.18, 1.04) disorders at age 69.All three grouped ACEs were associated with greater rates of accumulation and higher multimorbidity trajectories across adulthood. For example, individuals with ≥2 psychosocial ACEs developed 0.13(-0.09, 0.34) more disorders between ages 36 and 43, 0.29(0.06, 0.52) disorders between ages 53 and 63, and 0.30(0.09, 0.52) disorders between ages 63 and 69 compared with no psychosocial ACEs.

INTERPRETATIONS

ACEs are associated with widening inequalities in multimorbidity development in adulthood and early old age. Public health policies should aim to reduce these disparities through individual and population-level interventions.

What is the impact of multimorbidity on out-of-pocket healthcare expenditure among community-dwelling older adults in Ireland? A cross-sectional study

OBJECTIVES

Individuals with multimorbidity use more health services and take more medicines. This can lead to high out-of-pocket (OOP) healthcare expenditure. This study, therefore, aimed to assess the association between multimorbidity (two or more chronic conditions) and OOP healthcare expenditure in a nationally representative sample of adults aged 50 years or over.

DESIGN

Cross-sectional analysis of data collected in 2016 from wave 4 of The Irish Longitudinal Study on Ageing.SettingIreland.ParticipantsCommunity-dwelling adults aged 50 years and over.MethodA generalised linear model with log-link and gamma distributed errors was fitted to assess the association between multimorbidity and OOP healthcare expenditure (including general practitioner, emergency department, outpatients, specialist consultations, hospital admissions, home care and prescription drugs).

RESULTS

Overall, 3453 (58.5%) participants had multimorbidity. Among those with any OOP healthcare expenditure, individuals with multimorbidity spent more on average per annum (€806.8 for two conditions, €885.8 for three or more conditions), than individuals with no conditions (€580.3). Pharmacy-dispensed medicine expenditure was the largest component of expenditure. People with multimorbidity on average spent more of their equivalised household income on healthcare (7.1% for two conditions, 9.7% for three or more conditions), than people with no conditions (5.0%). A strong positive association was found between number of conditions and OOP healthcare expenditure (p<0.001) and between having private health insurance and OOP healthcare expenditure (p<0.001). A strong negative association was found between eligibility for free primary/hospital care and heavily subsidised medicines and OOP healthcare expenditure (p<0.001).

CONCLUSIONS

This study suggests that having multimorbidity in Ireland increases OOP healthcare expenditure, which is problematic for those with more conditions who have lower incomes. This highlights the need for this financial burden to be considered when designing healthcare/funding systems to address multimorbidity, so that access to essential healthcare can be maximised for those with greatest need.

Multiple Chronic Diseases Associated With Tooth Loss Among the US Adult Population

Background

Half of US adults aged 20–64 years have lost at least one permanent tooth; one in six adults aged 65 and over in the USA is edentulous. Tooth loss and edentulism interfere with nutritional intake and quality of life. Although selected chronic diseases (e.g., diabetes) have been identified as possible risk factors for tooth loss, data on multiple chronic diseases and on having two or more concurrent chronic diseases (multimorbidity) in relation to tooth loss are lacking. Therefore, this study aimed to assess the association between multiple chronic diseases, multimorbidity, and tooth loss in US adults.

Methods

We performed a secondary data analysis using the US 2012 Behavioral Risk Factor Surveillance System (BRFSS), a national cross-sectional telephone survey studying health conditions and health behaviors among US adults (≥18 years) who are non-institutionalized residents. Variables were derived from the BRFSS Standard Core Questionnaire. Descriptive analysis including means, standard deviations (SDs), and percentages was calculated. Sample weights were applied. The stepwise multinomial logistic regression method was used to examine the relationship between several chronic diseases and tooth loss. Separate multinomial logistic regression models were used to examine the relationship between multimorbidity and tooth loss among all adults aged more than 18 years, adults aged 18–64 years, and adults aged more than 65 years, respectively.

Results

Among the samples (n = 471,107, mean age 55 years, 60% female), 55% reported losing no tooth loss, 30% reported losing one to five teeth, 10% reported losing six or more but not all teeth, and 5% reported losing all teeth. After adjusting for demographic characteristics, socioeconomic status, smoking, BMI, and dental care, chronic diseases that were associated with edentulism were chronic obstructive pulmonary disease (COPD) [adjusted risk ratio (adj. RR) 2.18, 95% confidence interval (CI) 2.08–2.29]; diabetes (adj. RR 1.49, 95% CI 1.44–1.56); arthritis (adj. RR 1.49, 95% CI 1.44–1.54); cardiovascular disease (adj. RR 1.38, 95% CI 1.30–1.45); stroke (adj. RR 1.31, 95% CI 1.24–1.40); kidney disease (adj. RR 1.16, 95% CI 1.08–1.25); cancer (adj. RR 1.05, 95% CI 1.01–1.11); and asthma (adj. RR 1.07, 95% CI 1.02–1.12). For those who reported losing six or more teeth, the association remained significant for all the chronic diseases mentioned, albeit the magnitude of association appeared to be comparative or smaller. In addition, adults with multimorbidity were more likely to have tooth loss (loss of one to five teeth: adj. RR 1.17, 95% CI 1.14–1.19; loss of six or more teeth: adj. RR 1.78, 95% CI 1.73–1.82; edentulous: adj. RR 2.03, 95% CI 1.96–2.10).

Conclusions

Multiple chronic diseases were associated with edentulism and tooth loss. People with multimorbidity are more likely to be edentulous than those with one or no chronic disease. The findings from this study will help to identify populations at increased risk for oral problems and nutritional deficits, thus the assessment of oral health should be evaluated further as an important component of chronic illness care.

Household Tenure and Its Associations with Multiple Long-Term Conditions amongst Working-Age Adults in East London: A Cross-Sectional Analysis Using Linked Primary Care and Local Government Records

Multiple long-term conditions (MLTCs) are influenced in extent and nature by social determinants of health. Few studies have explored associations between household tenure and different definitions of MLTCs. This study aimed to examine associations between household tenure and MLTCs amongst working-age adults (16 to 64 years old, inclusive). This cross-sectional study used the 2019−2020 wave of an innovative dataset that links administrative data across health and local government for residents of a deprived borough in East London. Three definitions of MLTCs were operationalised based on a list of 38 conditions. Multilevel logistic regression models were built for each outcome and adjusted for a range of health and sociodemographic factors. Compared to working-age owner-occupiers, odds of basic MLTCs were 36% higher for social housing tenants and 19% lower for private renters (OR 1.36; 95% CI 1.30−1.42; p < 0.001 and OR 0.81, 95% CI 0.77−0.84, p < 0.001, respectively). Results were consistent across different definitions of MLTCs, although associations were stronger for social housing tenants with physical-mental MLTCs. This study finds strong evidence that household tenure is associated with MLTCs, emphasising the importance of understanding household-level determinants of health. Resources to prevent and tackle MLTCs among working-age adults could be differentially targeted by tenure type.

The relative impact of socioeconomic position and frailty varies by population setting

Introduction

Frailty and socioeconomic position (SEP) are well-established determinants of health. However, we know less about the contributions of frailty and SEP in older adults, especially in acute settings. We set out to answer how frailty and SEP might influence health outcomes in older people, comparing a population sample and patients managed by a speciality acute frailty service.

Methods

We used the Delirium and Population Health Informatics Cohort, a population sample of 1510 individuals aged ≥70 years from the London Borough of Camden and 1750 acute frailty patients. SEP was determined using the Index of Multiple Deprivation. Linear and Cox proportional hazard regression models were conducted to assess SEP on frailty, readmission, and mortality outcomes.

Results

In the population sample, SEP was significantly associated with frailty and mortality with successive increases in rate of death for each IMD quintile (HR = 1.28, 95% CI 1.11 to 1.49, P < 0.005). Increasing SEP, age, and admission status among hospitalized individuals were associated with greater frailty. For individuals seen by the speciality frailty service, SEP was not associated with frailty, mortality, or readmission.

Discussion

When older people experience acute illness severe enough to require secondary care, particularly specialist services, this overcomes any prior advantages conferred by a higher SEP.

Theoretical explanations for socioeconomic inequalities in multimorbidity: a scoping review

OBJECTIVE

To document socioepidemiological theories used to explain the relationship between socioeconomic disadvantage and multimorbidity.

DESIGN

Scoping review.

METHODS

A search strategy was developed and then applied to multiple electronic databases including Medline, Embase, PsychInfo, Web of Science, Scielo, Applied Social Sciences, ERIC, Humanities Index and Sociological Abstracts. After the selection of studies, data were extracted using a data charting plan. The last search was performed on the 28 September 2021. Extracted data included: study design, country, population subgroups, measures of socioeconomic inequality, assessment of multimorbidity and conclusion on the association between socioeconomic variables and multimorbidity. Included studies were further assessed on their use of theory, type of theories used and context of application. Finally, we conducted a meta-narrative synthesis to summarise the results.

RESULTS

A total of 64 studies were included in the review. Of these, 33 papers included theories as explanations for the association between socioeconomic position and multimorbidity. Within this group, 16 explicitly stated those theories and five tested at least one theory. Behavioural theories (health behaviours) were the most frequently used, followed by materialist (access to health resources) and psychosocial (stress pathways) theories. Most studies used theories as post hoc explanations for their findings or for study rationale. Supportive evidence was found for the role of material, behavioural and life course theories in explaining the relationship between social inequalities and multimorbidity.

CONCLUSION

Given the widely reported social inequalities in multimorbidity and its increasing public health burden, there is a critical gap in evidence on pathways from socioeconomic disadvantage to multimorbidity. Generating evidence of these pathways will guide the development of intervention and public policies to prevent multimorbidity among people living in social disadvantage. Material, behavioural and life course pathways can be targeted to reduce the negative effect of low socioeconomic position on multimorbidity.

eHealth interventions targeting poor diet, alcohol use, tobacco smoking and vaping among disadvantaged youth: A systematic review protocol (Preprint)

Background

Chronic disease burden is higher among disadvantaged populations. Preventing lifestyle risk behaviors such as poor diet, alcohol use, tobacco smoking, and vaping in adolescence is critical for reducing the risk of chronic disease and related harms in adolescence and adulthood. Although eHealth interventions are a promising prevention approach among the general population, it is unclear whether they adequately serve adolescents from disadvantaged backgrounds such as those living in geographically remote or lower socioeconomic areas.

Objective

This is the first systematic review to identify, evaluate, and synthesize evidence for the effectiveness of eHealth interventions targeting adolescents living in geographically remote or lower socioeconomic areas in preventing poor diet, alcohol use, tobacco smoking, and vaping.

Methods

A systematic search will be conducted in 7 electronic databases: the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, PROSPERO, MEDLINE (Ovid), Embase (Ovid), Scopus, and PsycInfo (Ovid). The search will be limited to eHealth-based experimental studies (ie, randomized controlled trials and quasi-experimental studies) targeting diet, alcohol use, tobacco smoking, and vaping among adolescents (aged 10-19 years). Eligible studies will be those reporting on at least one marker of socioeconomic status (eg, social class, household income, parental occupation status, parental education, and family affluence) or geographical remoteness (eg, living in rural, regional, and remote areas, or living outside major metropolitan centers). One reviewer will screen all studies for eligibility, of which 25% will be double-screened. Data will be extracted and summarized in a narrative synthesis. Risk of bias will be assessed using the Cochrane Revised Risk of Bias Tool.

Results

As of December 2021, the title and abstract screening of 3216 articles was completed, and the full-text review was underway. The systematic review is expected to be completed in 2022.

Conclusions

This systematic review will provide an in-depth understanding of effective eHealth interventions targeting poor diet, alcohol use, tobacco smoking, and vaping among adolescents living in geographically remote or lower socioeconomic areas and the factors that contribute to their effectiveness. This in turn will provide critical knowledge to improve future interventions delivered to these populations.

Trial Registration

PROSPERO CRD42021294119; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=294119

International Registered Report Identifier (IRRID)

PRR1-10.2196/35408