Taking a life course approach to healthy ageing and multimorbidity: defining risk factors is not the end, we can do more
Authors: Josephine Jackisch, Can Liu
Journal: The Lancet Healthy Longevity (2023)

Extensive research shows the role of social and familial risk factors in early life for developing chronic diseases.1Kuh D Ben Shlomo Y Ezra S A life course approach to chronic disease epidemiology. Oxford University Press, Oxford2004Crossref Google Scholar In The Lancet Healthy Longevity, Markus J Haapanen and colleagues2Haapanen MJ Vetrano DL Mikkola TM et al.Early growth, stress, and socioeconomic factors as predictors of the rate of multimorbidity accumulation across the life course: a longitudinal birth cohort study.Lancet Healthy Longev. 2023; (published online Dec 13.)https://doi.org/10.1016/S2666-7568(23)00231-3PubMed Google Scholar investigate the role of developmental factors for the accumulation of multimorbidity, drawing on unique data from a large prospective cohort from Helsinki. The authors show that socioeconomic background, maternal factors during pregnancy, and individual factors in childhood are associated with the pace at which adults accumulate chronic diseases. The novel finding is that this range of early life factors not only predicts individual chronic disease but also the progression of multimorbidity. An accelerated speed of accumulating additional chronic diseases matters because it leads to increasing inequalities over time and might be connected to a poorer prognosis, quality of life, and complex care needs.2Haapanen MJ Vetrano DL Mikkola TM et al.Early growth, stress, and socioeconomic factors as predictors of the rate of multimorbidity accumulation across the life course: a longitudinal birth cohort study.Lancet Healthy Longev. 2023; (published online Dec 13.)https://doi.org/10.1016/S2666-7568(23)00231-3PubMed Google Scholar The authors state that to improve health of future generations, interventions should focus on preventing maternal and childhood obesity on a global scale. Moreover they conclude that children evacuated to avoid war and those with lower socioeconomic status are at higher risk of multimorbidity accumulation, who might require targeted early intervention. The authors use adjusted linear mixed-effect models to estimate the association of each factor with the pace of chronic disease accumulation. We should be cautious when interpreting associational findings. To definitively conclude that optimising maternal health or preventing childhood obesity would improve long-term health the authors would need to pose a causal research question. Some challenges in the methods of this study include the absence of a clear definition of the target population and causal estimands, differential mortality as a competing event, and probable violations of the identifiability assumptions such as unmeasured confounding and consistency, which preclude causal interpretations. Although the identified early life risk factors emphasise the importance of socioeconomic and familial factors for individual outcomes, key questions remain unanswered—including the “So what?” question. We outline two directions through which life course research could enrich the research field of multimorbidity and healthy ageing. Research questions could then be modified to 1) more concretely inform intervention strategies and 2) better understand the complex interplay between factors across life stages and embracing the complexities of socially embedded life courses. First, to inform decision making of individuals, families, clinicians, and policy makers, we need to ask questions about what would happen to multimorbidity if we intervened to prevent a risk factor from occurring.3Vetrano DL Calderón-Larrañaga A Marengoni A et al.An international perspective on chronic multimorbidity: approaching the elephant in the room.J Gerontol A Biol Sci Med Sci. 2018; 73: 1350-1356Crossref PubMed Scopus (106) Google Scholar New causal inference methods allow us to estimate causal effects from observational data under specific sets of assumptions. However, consequential estimands rely on the careful choice of the target population, a relevant outcome contrast and modifiable factor to hypothetically intervene on. At what scale it would be possible to modify the investigated developmental factors of maternal obesity or adverse birth outcomes remains unclear. War-time separation might be a more interesting exposure in this regard, as one could chose to not send any children abroad by themselves in times of war. Yet one should not forget that the intention of such a decision is to protect children from additional harm. Like in studies of placement of children in out-of-home care, such well intended interventions might be associated with chronic diseases many years later.4Keyes K Galea S What matters most: quantifying an epidemiology of consequence.Ann Epidemiol. 2015; 25: 305-311Crossref PubMed Scopus (0) Google Scholar It remains difficult to tease apart the effect of the separation from the underlying experiences of adversities that lead to the decision to send a child away in the first place. Second, when taking a life course approach it can help to ask research questions to better understand the timing and mechanisms of how and when factors matter most.5Jackisch J Almquist YB Childhood adversity is associated with hospitalisations and survival following external causes and non-communicable diseases: a 46-year follow-up of a Stockholm birth cohort.J Epidemiol Community Health. 2023; 77: 209-215Crossref PubMed Scopus (1) Google Scholar Perinatal and childhood factors are part of the complex interplay of exposures across different life stages. Life course models are used to frame relevant questions of timing.6Lynch J Smith GD A life course approach to chronic disease epidemiology.Annu Rev Public Health. 2005; 26: 1-35Crossref PubMed Scopus (639) Google Scholar, 7Wagner C Carmeli C Chiolero A Cullati S Life course socioeconomic conditions and multimorbidity in old age–a scoping review.Ageing Res Rev. 2022; 78: 101630Crossref PubMed Scopus (3) Google Scholar Such an approach could help discern whether maternal BMI acts independently of the child's BMI later or early in life growth. BMI might mediate socioeconomic factors of interact with those in time-varying ways. We acknowledge that it is highly complex taking time or the interactions between the biological, social, and structural factors into account. Nevertheless, we are not alone in arguing that it might be time to embrace the challenge of such complexity in public health.8Rod NH Broadbent A Rod MH Russo F Arah OA Stronks K Complexity in epidemiology and public health. addressing complex health problems through a mix of epidemiologic methods and data.Epidemiology. 2023; 34: 505-514Crossref PubMed Scopus (4) Google Scholar, 9Galea S Hall C Kaplan GA Social epidemiology and complex system dynamic modelling as applied to health behaviour and drug use research.Int J Drug Policy. 2009; 20: 209-216Crossref PubMed Scopus (90) Google Scholar Life course research can be a catalyst to go beyond documenting risk factors. The life course field has provided concepts and approaches to consider complex exposures and outcomes over the life course. It could now help us ask more consequential questions and embrace the complex interactions across time affecting health outcomes at older ages. JJ reports funding from the Swiss National Science Foundation. CL reports funding from the Swedish Research Council and the Swedish Research Council for Health, Working Life and Welfare. Early growth, stress, and socioeconomic factors as predictors of the rate of multimorbidity accumulation across the life course: a longitudinal birth cohort studyOur 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. Full-Text PDF Open Access