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

Background We aimed to estimate multimorbidity trajectories and quantify socioeconomic inequalities based on childhood and adulthood socioeconomic position (SEP) in the risks and rates of multimorbidity accumulation across adulthood. Methods and findings Participants from the UK 1946 National Survey of Health and Development (NSHD) birth cohort study who attended the age 36 years assessment in 1982 and any one of the follow-up assessments at ages 43, 53, 63, and 69 years (N = 3,723, 51% males). Information on 18 health conditions was based on a combination of self-report, biomarkers, health records, and prescribed medications. We estimated multimorbidity trajectories and delineated socioeconomic inequalities (based on childhood and adulthood social class and highest education) in multimorbidity at each age and in longitudinal trajectories. Multimorbidity increased with age (0.7 conditions at 36 years to 3.7 at 69 years). Multimorbidity accumulation was nonlinear, accelerating with age at the rate of 0.08 conditions/year (95% CI 0.07 to 0.09, p < 0.001) at 36 to 43 years to 0.19 conditions/year (95% CI 0.18 to 0.20, p < 0.001) at 63 to 69 years. At all ages, the most socioeconomically disadvantaged had 1.2 to 1.4 times greater number of conditions on average compared to the most advantaged. The most disadvantaged by each socioeconomic indicator experienced an additional 0.39 conditions (childhood social class), 0.83 (adult social class), and 1.08 conditions (adult education) at age 69 years, independent of all other socioeconomic indicators. Adverse adulthood SEP was associated with more rapid accumulation of multimorbidity, resulting in 0.49 excess conditions in partly/unskilled compared to professional/intermediate individuals between 63 and 69 years. Disadvantaged childhood social class, independently of adulthood SEP, was associated with accelerated multimorbidity trajectories from age 53 years onwards. Study limitations include that the NSHD cohort is composed of individuals of white European heritage only, and findings may not be generalizable to the non-white British population of the same generation and did not account for other important dimensions of SEP such as income and wealth. Conclusions In this study, we found that socioeconomically disadvantaged individuals have earlier onset and more rapid accumulation of multimorbidity resulting in widening inequalities into old age, with independent contributions from both childhood and adulthood SEP.


Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported -This is summarised with sufficient detail in the Introduction.
Objectives 3 State specific objectives, including any prespecified hypotheses.
Last paragraph in introduction states the objectives.

Study design 4
Present key elements of study design early in the paper First 2 paragraphs (study participants & design) in the Methods section describe the cohort and the study design in detail.
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection.
Described in detail in beginning of the Methods section.
Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up We describe in detail the study participants eligible for this study. As this study is based on the National Survey of Health and Development (NSHD), a cohort followedup over several decades, we describe the cohort in general and the particular waves and data used for this study. Tables 1 and 2 also provide information on the different variables (the 18 conditions used in estimating multimorbidity) and sources of data.

Bias 9
Describe any efforts to address potential sources of bias In longitudinal studies one of the biggest issues is attrition over time. We report on rates of missing data and conduct imputation to account for attrition over time.
Study size 10 Explain how the study size was arrived at This is described in the last 2 paragraphs of the 'study participants and design' section in the beginning of the Methods.

Quantitative variables 11
Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why We describe in detail all variables used to estimate multimorbidity, our outcome of interest. We describe how we estimated multimorbidity, and how we categorised covariates of interests (socioeconomic variables and gender).
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding This is described in the Methods-Analysis section. We separately describe the different statistical analyses used: summary statistics, cross-sectional and longitudinal analyses.
(b) Describe any methods used to examine subgroups and interactions We describe in detail how we estimated the development of multimorbidity over time in the full study sample and then separately by the main covariates of interest (three socioeconomic variables: childhood and adulthood social class and educational level).
The only interactions we tested were those between socioeconomic and time (spline variables) in the longitudinal analysis. This is described in detail in the second last paragraph in the statistical analysis section.
(c) Explain how missing data were addressed We addressed missing data using multiple imputation. This is described at the end of the statistical analysis section.
(d) If applicable, explain how loss to follow-up was addressed We describe missing data and numbers at each follow-up. The study was restricted to those participants that attended any of the ages 36, 43, 53, 63 and 69 waves and missing data was addressed with the use of multiple imputation. Frequencies and distributions of non-imputed and imputed variables were largely similar for most conditions and are presented in Supplementary Table 3 and Table 1 respectively.

(e) Describe any sensitivity analyses
Descriptive analysis with and without multiple imputation.

Results
Participants 13* (a) Report numbers of individuals at each stage of study-eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed We described attrition (number of participants) lost during follow-up and the final number of participants included in this study in the Methods section.

(b) Give reasons for non-participation at each stage
The reasons for non-participation vary and sometimes are not known. This information is briefly presented in the manuscript, where known, in the participants section under the subheading 'attrition'.
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders The first paragraph in the Results section summarises the main characteristics of the study participants. We also describe how multimorbidity develops over time and differences in multimorbidity by socioeconomic covariates of interest.

(b) Indicate number of participants with missing data for each variable of interest
This information is presented in Suppl Table 3 Outcome data 15* Report numbers of outcome events or summary measures over time Multimorbiditythe outcome of interestis described in detail including how it develops over time (at the five different ages between ages 36 and 69 years) in Table   1.
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included We provide the unadjusted values of multimorbidity at each of the five ages over follow-up, as well as unadjusted estimates of multimorbidity by socioeconomic covariates of interest. We also provide the adjusted estimates for multimorbidity (for example, estimates for multimorbidity mutually adjusted for all three socioeconomic variables and gender). This is done for both cross-sectional (adjusted estimates from multivariable linear regression modelling) and longitudinal (adjusted estimates from mixed-effects models) analyses. All regression estimates are reported with corresponding 95% Cis in both text and tables.
(b) Report category boundaries when continuous variables were categorized NA, no continuous variables were categorised.
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period NA, outcome is a continuous variable.
Other analyses 17 Report other analyses done-eg analyses of subgroups and interactions, and sensitivity analyses We describe results of interactions (between socioeconomic variables and spline variables) included in mixed-effects models used for longitudinal analysis, how these can be interpreted as well as graphs to visually display the interactions (for example how multimorbidity trajectories vary by socioeconomic variables) over time.

Discussion
Key results 18 Summarise key results with reference to study objectives This is described in detail in the first paragraph of the Discussion.

Limitations 19
Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias.
We describe the limitations of the study including potential limitations in our estimation of multimorbidity in the discussion, paras 2,4,5.
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence See Discussion all paragraphs.

Generalisability 21
Discuss the generalisability (external validity) of the study results.
We discuss that generalisability of results could be limited (for example with non-White individuals).

Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based.
Source of funding and all details have been provided in the online system as requested by the journal *Give information separately for exposed and unexposed groups.