Frank, Philipp

Kivimäki, Mika

English

UCL Discovery

CommentTackling socioeconomic disparities in multimorbidityMika Kivimäkia,b,∗ and Philipp Franka,baUCL Brain Sciences, University College London, London, UKbClinicum, University of Helsinki, Helsinki, FinlandThe Lancet RegionalHealth - Europe2023;32: 100689Published Online xxxhttps://doi.org/10.1016/j.lanepe.2023.100689Medical and public health research and practice havelong relied on trials and studies that use the occur-rence of single adverse events, such as cardiovasculardisease, cancer, or death, as their primary outcomemeasures. Undoubtedly, these studies hold significantvalue, but their scope is limited in comprehendinghealth beyond specific diseases. With the ageingpopulation and improved medical care, a growingnumber of individuals are living long enough to facemultiple chronic conditions simultaneously. Pro-jections suggest that by 2035, as many as one-fifth ofUK residents aged 65 and older will have four or morehealth conditions.1 Hence, alongside identifying pre-vention and treatment strategies for specific diseases,attention must be directed toward other transitions inhealth, including the progression from single diseasesto multimorbidity.Multimorbidity, the coexistence of two or morechronic conditions, poses unique challenges for resear-chers and healthcare providers.2 The interplay betweenconcurrent conditions can worsen disease progressionand complicate disease management, necessitatingcarefully designed treatment plans to address poly-pharmacy and medication interactions. Patient charac-teristics, such as age, sex, ethnicity, and socioeconomicbackground, may further impede the prevention andtreatment of multimorbidity. Research in this field israpidly expanding to better understand risk factorsassociated with multimorbidity and, ultimately, to tacklethese challenges.In the current issue of The Lancet Regional HealthEurope, Lyons and colleagues conducted a study inves-tigating socioeconomic disadvantage as a risk factor forthe occurrence of 132 diseases, multimorbidity andmortality across the lifespan.3 The study was based on acohort of 965,905 Welsh residents aged 5–104 years,with a follow-up period from 2000 to 2019. By employ-ing multi-state modelling and analysing data fromgeneral practitioner records, hospital admissions, anddeath certifications, the authors found that individualsliving in the most socioeconomically deprived areasexperienced faster transitions from a healthy state todisease, multimorbidity, and ultimately death comparedDOI of original article: https://doi.org/10.1016/j.lanepe.2023.100687*Corresponding author. UCL Brain Sciences, University College Lon-don, London, UK.E-mail address: m.kivimaki@ucl.ac.uk (M. Kivimäki).© 2023 The Author(s). Published by Elsevier Ltd. This is an open accessarticle under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).www.thelancet.com Vol 32 September, 2023with those residing in the least deprived areas. Thus,among disease-free individuals, 20.9% in the most de-prived areas developed one chronic condition, comparedwith 18.6% in the least deprived areas (a difference of2.3 percentage points). The discrepancy between the twogroups increased to 3.1 percentage points for the de-velopment of two or more chronic conditions, and 7.2percentage points for mortality following the onset ofmultimorbidity.The study’s strengths lie in its outcome-wide ap-proach to socioeconomic disparities in health transi-tions, and the utilization of population-based data,covering a wide age range from childhood to old age.This allowed for a comprehensive assessment of par-ticipants’ medical history. Additionally, the study bene-fits from a large sample size and a long follow-upperiod. These strengths contribute to insights that arecomplementary to previous smaller-scale studies, whichfocused on a narrower range of diseases, limited theirscope to adulthood and old age, and used non-representative samples.4–6 The findings by Lyons et al.are consistent with suggestions that emphasise theimpact of socioeconomic status on the risk of multi-morbidity, frailty, and disability.7The study’s limitations primarily relate to dataavailability, as the use of residential deprivation as thesole socioeconomic marker may not capture the fullrange of socioeconomic circumstances. Furthermore,relying on routine healthcare data and record linkagemay overlook individuals who have not been formallydiagnosed. While the first limitation may have led to anunderestimation of the extent of socioeconomic dispar-ities, the latter is unlikely to have introduced major biassince this limitation impacted all socioeconomic groupsequally. It is also important to note that the observa-tional study by Lyons et al. does not allow for causalinferences. Instead, the results merely identify a groupthat faces a significantly elevated risk of experiencingpoor health and multimorbidity.Besides addressing these limitations, future researchexploring social inequalities in multimorbidity shouldprioritise diagnosis-specific analyses of disease trajec-tories, elucidating potential clustering of specific mor-bidities linked to social status. Prior research hasindicated that specific disorders manifest at different lifestages.8,9 For example, infections are particularly preva-lent during childhood, while obesity and mental healthissues tend to arise in early adulthood. Dyslipidaemiaand hypertension become more prominent in midlife,whereas type 2 diabetes, vascular disease, osteoporosis,1Comment2and dementia are commonly observed in old age.8 Theextent to which socially disadvantaged individualsexperience these conditions within disease trajectories isan important topic for future research. Gaining a betterunderstanding of the cellular and molecular mecha-nisms involved in these phenomena is also crucial. Thisknowledge will provide valuable insights into the effectsof socially patterned health-damaging processes,including environmental exposures, dysregulated stresssystems, and accelerated ageing.10,11With the addition of Lyons and colleagues’ work, theevidence calls for action by healthcare providers andpolicymakers to address social inequalities across allstages of health. Enhancements in primordial, primary,secondary, and tertiary prevention of chronic diseasesare warranted.ContributorsBoth authors contributed to the concept and writing of the manuscript.Declaration of interestsThe authors declare no competing interests.References1 Kingston A, Robinson L, Booth H, et al. Projections of multi-morbidity in the older population in England to 2035: estimatesfrom the population ageing and care simulation (PACSim) model.Age Ageing. 2018;47:374–380.2 Academy of Medical Sciences. Multimorbidity: a priority for globalhealth research. London: Academy of Medical Sciences; 2018.3 Lyons J, Akbari A, Abrams KR, et al. Chronic disease and mortalitydisparities across the lifespan between socioeconomic groups inWales, UK (2000-2019): linked electronic health records cohortstudy with 29.1 million person-years follow up. Lancet Reg HealthEur. 2023. https://doi.org/10.1016/j.lanepe.2023.100687.4 Singh-Manoux A, Fayosse A, Sabia S, et al. Clinical, socioeconomic,and behavioural factors at age 50 years and risk of cardiometabolicmultimorbidity and mortality: a cohort study. PLoS Med. 2018;15:e1002571.5 Mira R, Newton T, Sabbah W. Inequalities in the progress ofmultiple chronic conditions: a systematic review of longitudinalstudies. PLoS One. 2022;17:e0263357.6 Kivimäki M, Batty GD, Pentti J, et al. Association between socio-economic status and the development of mental and physical healthconditions in adulthood: a multi-cohort study. Lancet Public Health.2020;5:e140–e149.7 Dugravot A, Fayosse A, Dumurgier J, et al. Social inequalities inmultimorbidity, frailty, disability, and transitions to mortality: a 24-year follow-up of the Whitehall II cohort study. Lancet PublicHealth. 2020;5:e42–e50.8 Kuan V, Denaxas S, Gonzalez-Izquierdo A, et al. A chronologicalmap of 308 physical and mental health conditions from 4 millionindividuals in the English National Health Service. Lancet DigitHealth. 2019;1:e63–e77.9 Siggaard T, Reguant R, Jorgensen IF, et al. Disease trajectorybrowser for exploring temporal, population-wide disease progres-sion patterns in 7.2 million Danish patients. Nat Commun.2020;11:4952.10 Snyder-Mackler N, Burger JR, Gaydosh L, et al. Social determinantsof health and survival in humans and other animals. Science.2020;368:eaax9553.11 Kivimäki M, Bartolomucci A, Kawachi I. The multiple roles of lifestress in metabolic disorders. Nat Rev Endocrinol. 2023;19:10–27.www.thelancet.com Vol 32 September, 2023

Tackling socioeconomic disparities in multimorbidity

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Tackling socioeconomic disparities in multimorbidity

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