Trajectories of multiple long-term conditions and mortality in older adults: A retrospective cohort study using English Longitudinal Study of Ageing (ELSA)

Abstract

AbstractObjectivesTo classify older adults with MLTC into clusters based on accumulating conditions as trajectories over time, characterise clusters and quantify associations between derived clusters and all-cause mortality.DesignWe conducted a retrospective cohort study using the English Longitudinal Study of Ageing (ELSA) over nine years (n=15,091 aged 50 years and older). Group-based trajectory modelling was used to classify people into MLTC clusters based on accumulating conditions over time. Derived clusters were used to quantify the associations between MLTC trajectory memberships, sociodemographic characteristics, and all-cause mortality.ResultsFive distinct clusters of MLTC trajectories were identified and characterised as: “no-LTC” (18.57%), “single-LTC” (31.21%), “evolving MLTC” (25.82%), “moderate MLTC” (17.12%), and “high MLTC” (7.27%). Increasing age was consistently associated with an increased number of MLTC. Female sex (aOR = 1.13; 95%CI 1.01 to 1.27) and ethnic minority (aOR = 2.04; 95%CI 1.40 to 3.00) were associated with the “moderate MLTC” and “high MLTC” clusters, respectively. Higher education and paid employment were associated with a lower likelihood of progression over time towards an increased number of MLTC. All the clusters had higher all-cause mortality than the “no-LTC” cluster.ConclusionsThe development of MLTC and the increase in the number of conditions over time follow distinct trajectories. These are determined by non-modifiable (age, sex, ethnicity) and modifiable factors (education and employment). Stratifying risk through clustering will enable practitioners to identify older adults with a higher likelihood of worsening MLTC over time to tailor effective interventions.Strengths and limitationsThe main strength of the current study is the use of a large dataset, assessing longitudinal data to examine MLTC trajectories and a dataset that is nationally representative of people aged 50 years and older, including a wide range of long-term conditions and sociodemographics.The measurement of MLTC was limited to ten long-term conditions, which was all of what was available in the English of Longitudinal Study of Ageing, which may not be exhaustive of all possible long-term conditions.