Early-life predictors of future multi-morbidity: results from the Hertfordshire Cohort

Risk and protective factors of asthma and mental health condition multimorbidity in a national sample of Canadian children

BACKGROUND

The coexistence of childhood asthma and mental health (MH) conditions can impact management and health outcomes but we need to better understand the etiology of multimorbidity. We investigated the association between childhood asthma and MH conditions as well as the determinants of their coexistence.

METHODS

We used data from the Canadian Health Survey of Children and Youth 2019 (3-17 years; n = 47,871), a cross-sectional, nationally representative Statistics Canada dataset. Our primary outcome was condition status (no asthma or MH condition; asthma only; MH condition only; both asthma, and a MH condition (AMHM)). Predictors of condition status were assessed using multiple multinomial logistic regression. Sensitivity analyses considered individual MH conditions.

RESULTS

MH condition prevalence was almost two-fold higher among those with asthma than those without asthma (21.1% vs. 11.6%, respectively). There were increased risks of each condition category associated with having allergies, other chronic conditions, and family members smoking in the home while there were protective associations with each condition status category for being female and born outside of Canada. Four additional variables were associated with AMHM and MH condition presence with one additional variable associated with both AMHM and asthma. In sensitivity analyses, the associations tended to be similar for most characteristics, although there was some variability.

CONCLUSION

There are common risk factors of asthma and MH conditions along with their multimorbidity with a tendency for MH risk factors to be associated with multimorbidity. MH condition presence is common and important to assess among children with asthma.

Early growth, stress, and socioeconomic factors as predictors of the rate of multimorbidity accumulation across the life course: a longitudinal birth cohort study

BACKGROUND

Early growth, stress, and socioeconomic factors are associated with future risk of individual chronic diseases. It is uncertain whether they also affect the rate of multimorbidity accumulation later in life. This study aimed to explore whether early life factors are associated with the rate at which chronic diseases are accumulated across older age.

METHODS

In this national birth cohort study, we studied people born at Helsinki University Central Hospital, Helsinki, Finland between Jan 1, 1934, and Dec 31, 1944, who attended child welfare clinics in the city, and were living in Finland in 1971. Individuals who had died or emigrated from Finland before 1987 were excluded, alongside participants without any registry data and who died before the end of the registry follow-up on Dec 31, 2017. Early anthropometry, growth, wartime parental separation, and socioeconomic factors were recorded from birth, child welfare clinic, or school health-care records, and Finnish National Archives. International Classification of Diseases codes of diagnoses for chronic diseases were obtained from the Care Register for Health Care starting from 1987 (when participants were aged 42-53 years) until 2017. Linear mixed models were used to study the association between early-life factors and the rate of change in the number of chronic diseases over 10-year periods.

FINDINGS

From Jan 1, 1934, to Dec 31, 2017, 11 689 people (6064 [51·9%] men and 5625 [48·1%] women) were included in the study. Individuals born to mothers younger than 25 years (β 0·09; 95% CI 0·06-0·12), mothers with a BMI of 25-30 kg/m2 (0·08; 0·05-0·10), and mothers with a BMI more than 30 kg/m2 (0·26; 0·21-0·31) in late pregnancy accumulated chronic diseases faster than those born to older mothers (25-30 years) and those with a BMI of less than 25 kg/m2. Individuals with a birthweight less than 2·5 kg (0·17; 0·10-0·25) and those with a rapid growth in height and weight from birth until age 11 years accumulated chronic diseases faster during their life course. Additionally, paternal occupational class (manual workers vs upper-middle class 0·27; 0·23-0·30) and wartime parental separation (0·24; 0·19-0·29 for boys; 0·31; 0·25-0·36 for girls) were associated with a faster rate of chronic disease accumulation.

INTERPRETATION

Our findings suggest that the foundation for accumulating chronic diseases is established early in life. Early interventions might be needed for vulnerable populations, including war evacuee children and children with lower socioeconomic status.

FUNDING

Finska Läkaresällskapet, Liv och Hälsa rf, the Finnish Pediatric Research Foundation, and Folkhälsan Research Center.

TRANSLATIONS

For the Finnish and Swedish translations of the abstract see Supplementary Materials section.

Risk factors for multimorbidity in adulthood: A systematic review

BACKGROUND

Multimorbidity, the coexistence of multiple chronic diseases in an individual, is highly prevalent and challenging for healthcare systems. However, its risk factors remain poorly understood.

OBJECTIVE

To systematically review studies reporting multimorbidity risk factors.

METHODS

A PRISMA-compliant systematic review was conducted, searching electronic databases (MEDLINE, EMBASE, Web of Science, Scopus). Inclusion criteria were studies addressing multimorbidity transitions, trajectories, continuous disease counts, and specific patterns. Non-human studies and participants under 18 were excluded. Associations between risk factors and multimorbidity onset were reported.

RESULTS

Of 20,806 identified studies, 68 were included, with participants aged 18-105 from 23 countries. Nine risk factor categories were identified, including demographic, socioeconomic, and behavioral factors. Older age, low education, obesity, hypertension, depression, low pysical function were generally positively associated with multimorbidity. Results for factors like smoking, alcohol consumption, and dietary patterns were inconsistent. Study quality was moderate, with 16.2% having low risk of bias.

CONCLUSIONS

Several risk factors seem to be consistently associated with an increased risk of accumulating chronic diseases over time. However, heterogeneity in settings, exposure and outcome, and baseline health of participants hampers robust conclusions.

Childhood health and educational disadvantage are associated with adult multimorbidity in the global south: findings from a cross-sectional analysis of nationally representative surveys in India and Brazil

INTRODUCTION

Multimorbidity has emerged as a major healthcare challenge in low/middle-income countries (LMICs) such as India and Brazil. Life course epidemiology suggests that adverse events in early life contribute to an individual's later health in adulthood. However, little is known about the influence of early life health and social factors on the development of multimorbidity in adulthood in LMICs. We aimed to explore the association of adult multimorbidity with childhood health and social disadvantages among two LMICs, India and Brazil.

METHODS

We conducted a secondary data analysis of older adults aged ≥50 years using nationally representative surveys from Longitudinal Ageing Study in India, 2017-2018 (n=51 481) and 'Estudo Longitudinal da Saude e Bem-Estar dos Idosos Brasileirous', 2015-2016 (n=8730). We estimated the prevalence of multimorbidity along with 95% CI as a measure of uncertainty for all weighted proportions. Log link in generalised linear model was used to assess the association between childhood health and disadvantages with multimorbidity, reported as adjusted prevalence ratio (APR).

RESULTS

The prevalence of multimorbidity was 25.53% and 55.24% in India and Brazil, respectively. Participants who perceived their childhood health as poor and missed school for a month or more due to illness had the highest level of multimorbidity across both countries. After adjusting for age and gender, a significant association between adult multimorbidity and poor self-rated childhood health (APR: (India: 1.38, 1.16 to 1.65) and (Brazil: 1.19, 1.09 to 1.30)); and missed school for a month due to illness (AOR: (India: 1.73, 1.49 to 2.01) and (Brazil: 1.16, 1.08 to 1.25)) was observed.

CONCLUSION

Early life health, educational and economic disadvantages are associated with adult multimorbidity and appear to contribute to the later course of life. A life course approach to the prevention of multimorbidity in adulthood in LMICs may be useful in health programmes and policies.

Early-Life Factors and Multimorbidity Risk Later in Older Age: Evidence Based on CHARLS

INTRODUCTION

Early-life factors were reported to exert influence on the health condition of individuals in the long-term. However, limited research explored the connection between early-life factors and multimorbidity in later years.

METHODS

We utilized the data from the China Health and Retirement Longitudinal Study to assess this possible association in the present cross-sectional study. Multimorbidity was determined based on 14 common chronic diseases included in the study. Logistic regression was employed to examine the link between early-life factors and subsequent multimorbidity.

RESULTS

Out of 7,578 participants who met the inclusion criteria for analysis, 3,765 (49.68%) were females. The mean age was 68.25 ± 6.70 years. Participants who rated their health during childhood as average (odds ratio [OR] 0.78, 95% confidence interval [CI] 0.63-0.96) or better [OR 0.72, 95% CI 0.57-0.91] were significantly less likely to experience multimorbidity in older life. By contrast, experiencing violence from two of the family members was significantly associated with future multimorbidity (OR [95% CI], 1.29 [1.04-1.60]). A superior family financial situation was also negatively associated with multimorbidity, with average (OR [95% CI], 0.72 [0.63-0.83]) and better off than average (OR [95% CI], 0.76 [0.62-0.93]).

DISCUSSION

Individuals with poor health status, inferior family socioeconomic status, or experienced violence from family members in childhood were more likely to suffer from multimorbidity in later life. Enhanced social monitoring of potentially adverse conditions in youngsters and targeted interventions could help mitigate the progression of multimorbidity in later life.

Multimorbidity in People with Epilepsy

Multimorbidity is an emerging priority in healthcare due to associations with the ageing population, frailty, polypharmacy, health and social care demands. It affects 60-70% of adults and 80% of children with epilepsy. Neurodevelopmental conditions are commonly seen in children with epilepsy, while cancer, cardiovascular and neurodegenerative conditions often afflict older people with epilepsy. Mental health problems are common across the lifespan. Genetic, environmental, social and lifestyle factors contribute to multimorbidity and its consequences. Multimorbid people with epilepsy (PWE) are at higher risk of depression and suicide, premature death, suffer lower health-related quality of life, and require more hospital admissions and health care costs. The best management of multimorbid PWE requires a paradigm shift from the traditional single disease-single comorbidity approach and a refocus on a person-centred approach. Improvements in health care must be informed by assessing the burden of multimorbidity associated with epilepsy, delineating disease clusters, and measuring the effects on health outcomes.

Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) - protocol for a research collaboration

Background

Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as 'early onset'). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at different life stages. We have established a research collaboration titled 'MELD-B' to understand how wider determinants, sentinel conditions (the first LTC in the lifecourse) and LTC accrual sequence affect risk of early-onset, burdensome MLTC-M, and to inform prevention interventions.

Aim

Our aim is to identify critical periods in the lifecourse for prevention of early-onset, burdensome MLTC-M, identified through the analysis of birth cohorts and electronic health records, including artificial intelligence (AI)-enhanced analyses.

Design

We will develop deeper understanding of 'burdensomeness' and 'complexity' through a qualitative evidence synthesis and a consensus study. Using safe data environments for analyses across large, representative routine healthcare datasets and birth cohorts, we will apply AI methods to identify early-onset, burdensome MLTC-M clusters and sentinel conditions, develop semi-supervised learning to match individuals across datasets, identify determinants of burdensome clusters, and model trajectories of LTC and burden accrual. We will characterise early-life (under 18 years) risk factors for early-onset, burdensome MLTC-M and sentinel conditions. Finally, using AI and causal inference modelling, we will model potential 'preventable moments', defined as time periods in the life course where there is an opportunity for intervention on risk factors and early determinants to prevent the development of MLTC-M. Patient and public involvement is integrated throughout.

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

Objective

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

Method

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

Results

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

Conclusions

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

Life-course socioeconomic conditions, multimorbidity and polypharmacy in older adults: A retrospective cohort study

Socioeconomic conditions across the life course may contribute to differences in multimorbidity and polypharmacy in old age. However, whether the risk of multimorbidity changes during ageing and whether life-course socioeconomic conditions are associated with polypharmacy remain unclear. We investigated whether disadvantaged childhood socioeconomic conditions (CSCs) predict increased odds of multimorbidity and polypharmacy in older adults, whether CSCs remain associated when adjusting for adulthood socioeconomic conditions (ACSs), and whether CSCs and ACSs are associated cumulatively over the life course. We used data for 31,432 participants (multimorbidity cohort, mean [SD] age 66·2[9] years), and 21,794 participants (polypharmacy cohort, mean age 69·0[8.9] years) from the Survey of Health, Ageing, and Retirement in Europe (age range 50-96 years). We used mixed-effects logistic regression to assess the associations of CSCs, ASCs, and a life-course socioeconomic conditions score (0-8; 8, most advantaged) with multimorbidity (≥2 chronic conditions) and polypharmacy (≥5 drugs taken daily). We found an association between CSCs and multimorbidity (reference: most disadvantaged; disadvantaged: odds ratio (OR) = 0·79, 95% confidence interval (CI) 0·70-0·90; middle: OR = 0·60; 95%CI 0·53-0·68; advantaged: OR = 0·52, 95%CI 0·45-0·60, most advantaged: OR = 0·40, 95%CI 0·34-0·48) but not polypharmacy. This multimorbidity association was attenuated but remained significant after adjusting for ASCs. The life-course socioeconomic conditions score was associated with multimorbidity and polypharmacy. We did not find an association between CSCs, life-course socioeconomic conditions, and change in odds of multimorbidity and polypharmacy with ageing. Exposure to disadvantaged socioeconomic conditions in childhood or over the entire life-course could predict multimorbidity in older age.

Children and adolescents are not small adults: towards a better understanding of multimorbidity in younger populations

Multimorbidity is of increasing importance for the health of both children and adults but research has hitherto focused on adult multimorbidity. Hence, public awareness, practice and policy lack vital information about multimorbidity in childhood and adolescence. We convened an international and interdisciplinary group of experts from six nations to identify key priorities supported by published evidence to strengthen research for children and adolescent with multimorbidity. Future research is encouraged 1) To develop a conceptual framework to capture unique aspects of child and adolescent multimorbidity - including definitions, characteristic patterns of conditions for different age groups, its dynamic nature through childhood and adolescence and understanding of severity and trajectories for different clusters of multiple chronic conditions, 2) To define new indices to classify the presence of multimorbidity in children and adolescents, 3) To improve the availability and linkage of data across countries, 4) To synthesize evidence on the global phenomenon of multimorbidity in childhood and adolescence as well as health inequalities, 5) To involve children and adolescents in research relevant to their health.

Population health science as a unifying foundation for translational clinical and public health research

Separated both in academics and practice since the Rockefeller Foundation effort to "liberate" public health from perceived subservience to clinical medicine a century ago, research in public health and clinical medicine have evolved separately. Today, translational research in population health science offers a means of fostering their convergence, with potentially great benefit to both domains. Although evidence that the two fields need not and should not be entirely distinct in their methods and goals has been accumulating for over a decade, the prodigious efforts of biomedical and social sciences over the past year to address the COVID-19 pandemic has placed this unifying approach to translational research in both fields in a new light. Specifically, the coalescence of clinical and population-level strategies to control disease and novel uses of population-level data and tools in research relating to the pandemic have illuminated a promising future for translational research. We exploit this unique window to re-examine how translational research is conducted and where it may be going. We first discuss the transformation that has transpired in the research firmament over the past two decades and the opportunities these changes afford. Next, we present some of the challenges-technical, cultural, legal, and ethical- that need attention if these opportunities are to be successfully exploited. Finally, we present some recommendations for addressing these challenges.

Effects of individual and parental educational levels on multimorbidity classes: a register-based longitudinal study in a Danish population

OBJECTIVES

To assess the effects of individual educational level in adulthood and parental educational level during childhood, as well as combinations of individual and parental educational levels, on multimorbidity classes.

DESIGN AND SETTING

In this longitudinal study, we used data from a random sample of the Danish population aged 32-56 years without multimorbidity in 2010 (n=102 818). The study population was followed until 2018. Information on individual and parental educational levels and chronic conditions was obtained from national registers. Multinomial logistic regression analyses were adjusted for sex, age and ethnicity.

OUTCOME MEASURE

Seven multimorbidity classes were identified using latent class analysis based on 47 chronic conditions. Persons deceased during follow-up comprised a separate class.

RESULTS

We found an independent effect of individual educational level on five multimorbidity groups and death, most pronounced for the multimorbidity group 'Many conditions' (OR=1.89, 95% CI 1.58 to 2.26 for medium and OR=3.22, 95% CI 2.68 to 3.87 for short compared with long educational level) and of parental education on four groups and death, most pronounced for the multimorbidity group 'Many conditions' (OR=1.36, 95% CI 1.07 to 1.73 for medium and OR=1.48, 95% CI 1.15 to 1.89 for short compared with long educational level). Odds of belonging to four multimorbidity classes increased with lower combination of individual and parental educational levels, most pronounced for the multimorbidity group 'Many conditions'.

CONCLUSION

As both individual and parental educational levels contribute to the risk of multimorbidity, it is important to address inequality throughout the life course to mitigate multimorbidity. Future studies could adopt a life course approach to investigate the mediating role of behavioural, clinical, environmental and other social factors.

Impact of prenatal and childhood adversity effects around World War II on multimorbidity: results from the KORA-Age study

Background

While risk factors for age-related diseases may increase multimorbidity (MM), early life deprivation may also accelerate the development of chronic diseases and MM.

Methods

This study explores the prevalence and pattern of MM in 65–71 year-old individuals born before, during, and after World War II in Southern Germany based on two large cross-sectional KORA (Cooperative Health Research in the Region of Augsburg) -Age studies in 2008/9 and 2016. MM was defined as having at least two chronic diseases, and birth periods were classified into five phases: pre-war, early war, late war, famine, and after the famine period. Logistic regression models were used to analyze the effect of the birth phases on MM with adjustment for sociodemographic and lifestyle risk factors. Furthermore, we used agglomerative hierarchical clustering to investigate the co-occurrence of diseases.

Results

Participants born during the late war phase had the highest prevalence of MM (62.2%) and single chronic diseases compared to participants born during the other phases. Being born in the late war phase was significantly associated with a higher odds of MM (OR = 1.83, 95% CI: 1.15–2.91) after adjustment for sociodemographic and lifestyle factors. In women, the prevalence of joint, gastrointestinal, eye diseases, and anxiety was higher, while heart disease, stroke, and diabetes were more common in men. Moreover, three main chronic disease clusters responsible for the observed associations were identified as: joint and psychosomatic, cardiometabolic and, other internal organ diseases.

Conclusions

Our findings imply that adverse early-life exposure may increase the risk of MM in adults aged 65–71 years. Moreover, identified disease clusters are not coincidental and require more investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02793-2.

Prevalence and early-life determinants of mid-life multimorbidity: evidence from the 1970 British birth cohort

BACKGROUND

We sought to: [1] estimate the prevalence of multimorbidity at age 46-48 in the 1970 British Cohort Study-a nationally representative sample in mid-life; and [2] examine the association between early-life characteristics and mid-life multimorbidity.

METHOD

A prospective longitudinal birth cohort of a community-based sample from the 1970 British Cohort Study (BCS70). Participants included all surviving children born in mainland Britain in a single week in April 1970; the analytical sample included those with valid data at age 46-48 (n = 7951; 2016-2018). The main outcome was multimorbidity, which was operationalised as a binary indicator of two or more long-term health conditions where at least one of these conditions was of physical health. It also included symptom complexes (e.g., chronic pain), sensory impairments, and alcohol problems.

RESULTS

Prevalence of mid-life multimorbidity was 33.8% at age 46-48. Those with fathers from unskilled social occupational class (vs professional) at birth had 43% higher risk of mid-life multimorbidity (risk ratio = 1.43, 95% confidence interval 1.15 to 1.77). After accounting for potential child and family confounding, an additional kilogram of birthweight was associated with 10% reduced risk of multimorbidity (risk ratio = 0.90, 95% confidence interval 0.84 to 0.96); a decrease of one body mass index point at age 10 was associated with 3% lower risk (risk ratio = 1.03, 95% confidence interval 1.01 to 1.05); one standard deviation higher cognitive ability score at age 10 corresponded to 4% lower risk (risk ratio = 0.96, 95% confidence interval 0.91 to 1.00); an increase of one internalising problem at age 16 was equated with 4% higher risk (risk ratio = 1.04, 95% confidence interval 1.00 to 1.08) and of one externalising problem at age 16 with 6% higher risk (risk ratio = 1.06, 1.03 to 1.09).

CONCLUSION

Prevalence of multimorbidity was high in mid-life (33.8% at age 46-48) in Britain. Potentially modifiable early-life exposures, including early-life social circumstances, cognitive, physical and emotional development, were associated with elevated risk of mid-life multimorbidity.

A New Path to Address Multimorbidity? Longitudinal Analyses of Retirement Sequences and Chronic Diseases in Old Age

Chronic disease and multimorbidity are growing health challenges for aging populations, often coinciding with retirement. We examine late-life predictors of multimorbidity, focusing on the association between retirement sequences and number of chronic diseases. We modeled the number of chronic diseases as a function of six types of previously identified 10-year retirement sequences using Health and Retirement Study (HRS) data for 7,880 Americans observed between ages 60 to 61 and 70 to 71. Our results show that at baseline, the adjusted prevalence of multimorbidity was lowest in sequences characterized by late retirement from full-time work and highest in sequences characterized by early labor-force disengagement. Age increases in multimorbidity varied across retirement sequences, though overall differences in prevalence persisted at age 70 to 71. Earlier life disadvantages did not moderate these associations. Findings suggest further investigation of policies that target health limitations affecting work, promote continued beneficial employment opportunities, and ultimately leverage retirement sequences as a novel path to influence multimorbidity in old age.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Multimorbidity: the case for prevention

Multimorbidity is of increasing concern for healthcare systems globally, particularly in the context of ageing population structures, such as in the European Union and the UK. Although there is growing attention on developing strategies to manage the health and healthcare burden of older patients with multimorbidity, little research or policy focus has been placed on how to best prevent the development of multimorbidity in future generations. In this research agenda piece, we argue for a shift from a sole focus on the management of multimorbidity in old age to a multimorbidity agenda that considers prevention and management throughout the life-course.

Impact of educational attainment on the association between social class at birth and multimorbidity in middle age in the Aberdeen Children of the 1950s cohort study

OBJECTIVE

Multimorbidity (the coexistence of two or more health conditions) is increasingly prevalent. No long-term cohort study has examined the impact of contemporaneously measured birth social class along with educational attainment on adult self-reported multimorbidity. We investigated the impact of educational attainment on the relationship between social class at birth and adult self-reported multimorbidity in the Aberdeen Children of the 1950s (ACONF) cohort.

METHODS

A prospective cohort study using the ACONF cohort. ACONF included 12 150 individuals born in Aberdeen, Scotland 1950-1956. In 2001, 7184 (64%) responded to a questionnaire providing information including self-reported morbidity and educational attainment. The exposure was father's social class at birth from birth records and the outcome was self-reported multimorbidity.Logistic regression assessed the association between social class and multimorbidity with adjustment for gender, then by educational attainment and finally by childhood cognition and secondary school type. ORs and 95% CIs were presented.

RESULTS

Of 7184 individuals (mean age 48, 52% female), 5.4% reported multimorbidity. Birth social class was associated with adult multimorbidity. For example, the OR of multimorbidity adjusted by gender was 0.62 (95% CI 0.39 to 1.00) in the highest social class group (I/II) in relation to the reference group (III (manual)) and was 1.85 (95% CI 1.19 to 2.88) in the lowest social class group. This was partially attenuated in all social class categories by educational attainment, for example, the OR was 0.74 (95% CI 0.45 to 1.21) in group I/II following adjustment.

CONCLUSION

Lower social class at birth was associated with developing multimorbidity in middle age. This was partially mediated by educational attainment and future research should consider identifying the other explanatory variables. The results are relevant to researchers and to those aiming to reduce the impact of multimorbidity.

Prevalence of multimorbidity in community settings: A systematic review and meta-analysis of observational studies

BACKGROUND

With ageing world populations, multimorbidity (presence of two or more chronic diseases in the same individual) becomes a major concern in public health. Although multimorbidity is associated with age, its prevalence varies. This systematic review aimed to summarise and meta-analyse the prevalence of multimorbidity in high, low- and middle-income countries (HICs and LMICs).

METHODS

Studies were identified by searching electronic databases (Medline, Embase, PsycINFO, Global Health, Web of Science and Cochrane Library). The term 'multimorbidity' and its various spellings were used, alongside 'prevalence' or 'epidemiology'. Quality assessment employed the Newcastle-Ottawa scale. Overall and stratified analyses according to multimorbidity operational definitions, HICs/LMICs status, gender and age were performed. A random-effects model for meta-analysis was used.

RESULTS

Seventy community-based studies (conducted in 18 HICs and 31 LMICs) were included in the final sample. Sample sizes ranged from 264 to 162,464. The overall pooled prevalence of multimorbidity was 33.1% (95% confidence interval (CI): 30.0-36.3%). There was a considerable difference in the pooled estimates between HICs and LMICs, with prevalence being 37.9% (95% CI: 32.5-43.4%) and 29.7% (26.4-33.0%), respectively. Heterogeneity across studies was high for both overall and stratified analyses (I 2 > 99%). A sensitivity analysis showed that none of the reviewed studies skewed the overall pooled estimates.

CONCLUSION

A large proportion of the global population, especially those aged 65+, is affected by multimorbidity. To allow accurate estimations of disease burden, and effective disease management and resources distribution, a standardised operationalisation of multimorbidity is needed.

Childhood adversity: A gateway to multimorbidity in older age?

BACKGROUND

Multimorbidity, or co-occurrence of several chronic diseases, has major consequences in terms of function, quality of life and mortality. Recent advances suggest that the aetiology of multimorbidity includes a life-long process. The purpose of this study was to determine the association between childhood adversity and multimorbidity in community-dwelling older adults, and to investigate variation in participants born immediately before, during and at the end of the Second World War.

METHODS

Participants were 4731 community-dwelling older adults who enrolled in the Lausanne cohort 65+ study (Switzerland) at age 65-70 years in 2004/2009/2014. A baseline questionnaire provided several indicators of childhood adversity including premature birth, food restrictions, child labour, family economic environment, serious illness/accident, and stressful life events. Multimorbidity at age 67-72 years was defined as ≥2 active chronic diseases at the 2-year follow-up questionnaire.

RESULTS

All childhood adversity indicators except premature birth were significantly associated with multimorbidity. Odds ratio (OR) ranged from 1.23 (P = 0.034) for poor family economic environment to 1.74 (P < 0.001) for stressful life events. In a multivariable model adjusted for socioeconomic status, health behaviours and stressful life events in adulthood (>16 years), a history of serious illness/accident (OR = 1.45; P < 0.001) and stressful life events (OR = 1.42; P = 0.001) in childhood remained significantly associated with multimorbidity. Comparisons between cohorts indicated substantial variations in the prevalence of childhood adversity indicators but similar associations with multimorbidity.

CONCLUSION

There was an independent association between childhood adversity and multimorbidity after age 65. This study encourages a comprehensive life-course perspective to better understand and potentially prevent multimorbidity.