Socioeconomic trajectories across the life course and health outcomes in midlife: evidence for the accumulation hypothesis?

Archana Singh-Manoux, Jane E Ferrie, Tarani Chandola and Michael Marmot

International Centre for Health and Society, Department of Epidemiology and Public Health, University College London, 1–19 Torrington Place, London WC1E 6BT, UK. E-mail: A.Singh-Manoux{at}public-health.ucl.ac.uk


    Abstract
 Top
 Abstract
 Data and Methods
 Results
 Discussion
 References
 
Background Recent research in social epidemiology has established the importance of considering the accumulation of advantage and disadvantage across the life course when examining adult health outcomes. This paper examines (1) accumulation across trichotomous categories of socioeconomic position (SEP), and (2) accumulation in analysis stratified by adult SEP.

Methods Data are from the Whitehall II study. Each participant was categorized as having high (0), intermediate (1), or low (2) SEP at three time points in the life course, leading to 27 socioeconomic trajectories. These trajectories were summarized to yield a scale ranging from 0 (high SEP at all three time points) to 6 (low SEP at all three time points). Logistic regression was used to examine odds of incident coronary heart disease (CHD), poor mental and physical functioning, and minor psychiatric disorder.

Results There was a graded linear relationship between accumulation of socioeconomic exposure and health. Men with a score of 6 had increased odds of CHD (2.53, 95% CI: 1.3, 5.1), poor physical functioning (2.19, 95% CI: 1.4, 4.1), and poor mental functioning (2.60, 95% CI: 1.4, 4.9) compared with men with a score of 0. In women there was an accumulation effect for CHD and physical functioning. No cumulative effect of SEP on minor psychiatric disorder was observed. The effects of accumulation were weaker in analyses stratified by adult SEP, with early deprivation followed by high adult SEP particularly detrimental for CHD.

Conclusions The health effects of socioeconomic disadvantage accumulate over the life course. In addition to accumulation effects, analysis stratified by adult SEP also provided support for the critical period and the pathway model.


Keywords Life course, accumulation hypothesis, pathway model, critical period model, socioeconomic position, Whitehall II study

Accepted 5 April 2004

Research shows that effects associated with adverse socioeconomic circumstances on mental and physical health are evident at different stages of the life course.1–7 In addition, the social gradient suggests a dose–response relationship between social circumstances and health, with individuals characterized by the best socioeconomic circumstances experiencing the best health, those at the next level having slightly worse health and so on, with those with the worst socioeconomic circumstances having the worst health.8–12 In recent years, interest has focused on the impact of cumulative effects of disadvantage across the life course on mental and physical health. Lynch and colleagues found graded relationships between the number of times (out of three) Alameda County Study respondents were classified as being poor and their mental and physical health.13 Similar analyses of workers in Western Scotland were based on the number of occasions in which the respondent's class location was manual (out of three measures of social class—fathers, own first, own current).2,14 Replication of this analysis in the Stockholm Heart Epidemiology programme also suggests an accumulation effect on myocardial infarction of being in the manual class.15 Other US data also suggest that being ‘working class’ in both childhood and adulthood is detrimental to women's health outcomes.16

This paper takes the ‘accumulation hypothesis’ further by examining the accumulation effect in greater detail. The almost linear relationship between different indicators of socioeconomic position and health merits an examination of the accumulation hypothesis that goes beyond simple dichotomies of socioeconomic position (SEP). Data from the Whitehall II study, on white collar employees, allow a more finely grained analysis of the accumulation hypothesis. Three levels of SEP from three points in the life course (childhood, education, and employment grade at entry into the Whitehall II study) are used to examine the accumulation hypothesis.

We also examine the accumulation effect for a given adult SEP. Research clearly shows adult measures of SEP to be more powerful predictors of health than SEP measures from earlier in the life course.17–19 This is likely to be the case, at least in part, because adult measures of SEP provide effective summaries of social trajectories over the life course. However, it remains unclear if different pathways to a given adult SEP, implicating different levels of accumulated socioeconomic exposure, are associated with the same risks for health. In analysis stratified by adult SEP, this paper will examine if there is an effect of accumulation of advantage and/or disadvantage of different trajectories to the same adult SEP.

To summarize, two specific research questions will be explored in this paper: (1) Does socioeconomic exposure over the life course have a cumulative effect on health outcomes? (2) Does the accumulation hypothesis hold for a given level of adult SEP?


    Data and Methods
 Top
 Abstract
 Data and Methods
 Results
 Discussion
 References
 
Participants
The target population for the Whitehall II study was all the London-based office staff, aged 35–55, working in 20 Civil Service departments.20 With a response rate of 73%, the final cohort consisted of 10 308 participants (6895 men and 3413 women) at the first phase of data collection between 1985 and 1988. The screening at baseline (Phase I) involved a clinical examination, and a self-administered questionnaire containing sections on demographic characteristics, health, lifestyle factors, work characteristics, social support, and life events. Since baseline screening five further data collection rounds have been completed. Successive phases alternate between collecting data by self-administered questionnaire only and collecting data via a clinical screening in addition to questionnaire completion. The most recent phase of data collection (Phase VI) was completed between 2000 and 2001.

Measures
Indicators of socioeconomic position (SEP)
Childhood SEP was assessed with a latent variable made up of two measures: father's social class and socioeconomic circumstances in childhood. Father's social class was assessed using Registrar General's Social Class classification (Questionnaire data from Phase 1 and VI). In order to assess socioeconomic circumstances in childhood respondents were asked to recall family conditions before they were 16 years of age (Questionnaire data from Phase V). A four-item scale was used: father/mother unemployed when they wanted to be working, family had continuing financial problems, family did not have an inside toilet, and family did not have a car. Participants responded either ‘yes’ or ‘no’, and the ‘yes’ responses were summed so that a high score indicated poor socioeconomic circumstances in childhood. Principal component analysis on these two items revealed one factor explaining 68.2% of the variance. This factor was divided into tertiles of high, intermediate, and low childhood SEP (Table 1).


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Table 1 Frequency of individual measures of socioeconomic position (SEP)

 
Education was measured as the highest level of education achieved, with the respondent choosing one of 11 categories (Questionnaire data from Phase V). This was regrouped into three standard hierarchic levels: high (degree or higher degree), intermediate (higher secondary education), and low (lower secondary or no formal education) (Table 1).

Occupational position at Phase 1 Occupational position was assessed as civil service employment grade on entry to the Whitehall II study.20 The 12 non-industrial grade levels where regrouped to form three categories: high (administrative), intermediate (professional and executive), and low (clerical and office support staff) grade (Table 1).

Outcomes
Measures of health outcome used in the analyses are till (CHD) or from Phase V (1997–1999).

Coronary Heart Disease (CHD) This outcome consisted of fatal CHD or incidence of non-fatal myocardial infarction (MI) or angina between phases I and V. In all, 10 300 (99.9%) participants were ‘flagged’ at the National Health Service Central Registry providing information on date and cause of death. Coronary death was indicated by an International Classficiation of Diseases, Ninth Revision (ICD-9) code 410–414.21 Potential non-fatal myocardial infarction (MI) and angina events were ascertained by questionnaire items on: chest pain (World Health Organization Rose questionnaire),22 treatment (nitrates or revascularization), recall of a doctor's diagnosis, and investigation (exercise electrocardiography, stress imaging, or angiography). The latter were verified against clinical records. Twelve lead resting electrocardiograms were performed at study Phases I, III, and V (Simmons Mingorec) and classified according to the Minnesota code.22,23 Two independent trained coders carried out the classification of MI and angina, with adjudication by a third coder in the (rare) event of disagreement.

Health Functioning was assessed using the Short Form 36 (SF-36) General Health Survey Scales.24 The SF-36 is a 36-item questionnaire that covers issues relating to physical, psychological, and social functioning. It is coded into eight scales: physical functioning, social functioning, role limitations due to physical problems, role limitations due to emotional problems, vitality, bodily pain, general health perception, and general mental health. These eight scales of the SF-36 can be summarized into physical and mental components scores (PCS and MCS) using factor analysis.25,26 Poor health functioning was indicated by being in the worst quintile for PCS and MCS.

Minor psychiatric disorder was assessed using the General Health Questionnaire (GHQ). The GHQ is a 30-item screening questionnaire for minor psychiatric disorder suitable for use in the general population samples.27 A threshold of 4/5 on the GHQ was chosen; all those scoring 0–4 were considered ‘non-cases’ and those scoring 5+ were considered ‘cases’.

Data analysis
Initial analysis involved the examination of the bivariate relationship between health and individual measures of SEP, which were set at three levels: 0 = high SEP, 1 = intermediate SEP, and 2 = low SEP. The next step involved the construction of trajectories representing life course socioeconomic exposure. A combination of the 3 levels of SEP at 3 time points resulted in 27 different life course trajectories. Life course trajectory 1 was represented by socioeconomic exposure 000, implying high SEP at all three time points in the life course. Trajectory 27 was represented by exposure 222, implying low SEP at all three time points.

In order to represent cumulative socioeconomic exposure over the life course a summary score was created by summing up the exposure level at the three time points for each trajectory. This score ranged from 0 (representing exposure level 000) to 6 (representing exposure level 222). Summary score 1 represented three different trajectories: 001, 010, and 100. Summary score 2 represented six different trajectories: 002, 011, 020, 101, 110, and 200. Summary score 3 represented seven different trajectories: 012, 021, 102, 111, 120, 201, and 210. Summary score 4 represented six different trajectories: 022, 112, 121, 202, 211, and 220. Summary score 5 represented three different trajectories: 122, 212, and 221. Logistic regression was used to examine the relationship between the summary score for life course SEP exposure and health outcomes. All analyses were carried out separately for men and women to explore a possible effect modification by gender and all analyses were controlled for age.

The next set of analyses examined the accumulation hypothesis for a given destination SEP (own grade at Phase 1 in our analysis). There are nine possible ways of getting to each of the three levels of destination SEP. For those with high own SEP, the different trajectories were: 000, 010, 100, 110, 020, 200, 120, 210, and 220 (cumulative summary score from 0 to 4). Intermediate SEP at time point 3 implicated the following trajectories: 001, 011, 101, 111, 021, 201, 121, 211, and 221 (cumulative summary score from 1 to 5). Finally, for those with low SEP at time point 3, the trajectories were: 002, 012, 102, 112, 022, 202, 122, 212, and 222 (cumulative summary score from 2 to 6). Test of trend was used to examine the accumulation hypothesis. Logistic regression, with the category having the lowest cumulative score for each destination SEP as the reference group, was used to calculate odds of poor health.


    Results
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 Abstract
 Data and Methods
 Results
 Discussion
 References
 
Table 1 shows the frequency distribution of the three measures of SEP examined in this study. Only individuals with complete information on SEP at the three time points were included in the analysis, 4418 men and 1710 women. The top half of Table 1 shows the frequency distribution of each measure of SEP. The bottom half of Table 1 shows the frequency distribution for those with complete data across the SEP trajectory. Employment grade is the only variable with no missing data. 355 individuals had died by Phase V, leaving 9953 respondents. Data on 6128 of these individuals have been analysed here. Missing data were more common among those from the lowest employment grade.

Table 2 shows the age-adjusted bivariate relationship between individual measures of SEP and health outcomes. Although all measures of SEP show some association with the health outcomes examined, it is employment grade that has the most consistent relationship. Level of education is not associated with measures of mental health, as assessed by the MCS and the GHQ, in either men or women.


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Table 2 Individual measures of socioeconomic position (SEP) and healtha: age-adjusted odds ratios (OR)b

 
Table 3 shows the relationship between the summary score, representing cumulative life course socioeconomic exposure, and health outcomes. In men there is a clear linear cumulative dose–response relationship between socioeconomic exposure and CHD, and physical and mental functioning. In women, the accumulation hypothesis holds for CHD and physical functioning. There were no effects of accumulative socioeconomic disadvantage on minor psychiatric disorder, either in men or in women.


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Table 3 Summary score (SS) of cumulative life course soicoeconomic exposure and health:a Age-adjusted odds ratios (OR)b

 
Results relating to the second research question are shown in Table 4. There were nine different trajectories possible for individuals occupying high SEP at time point 3 (000, 010, 100, 110, 020, 200, 120, 210, and 220). These have been converted to summary scores ranging from 0 to 4. Of the men, 25.9% and 44.3% of women with high employment grade (SEP at time point 3) had high SEP across the three time points. In this category of destination SEP, as evident from the test for trend, there was a significant accumulation effect for CHD, mental functioning (MCS) and GHQ outcomes among men. Among women there was no evidence of an accumulation effect. Further analysis of individual trajectories in men (results not shown) reveals the effect for CHD to be concentrated in trajectories 200 and 220 compared with trajectory 000. Similarly, poor mental functioning was evident in trajectories 100, 200, and 210; and poor GHQ scores in trajectories 100, 110, 200.


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Table 4 Different trajectories to high, medium, and low occupational position and health:a Age-adjusted odds ratios (OR)b

 
Individuals who occupied intermediate SEP at time point 3 also have nine possible ways of getting there (001, 011, 101, 111, 021, 201, 121, 211, and 221) leading to a cumulative summary score ranging from 1 to 5 (Table 4). The trend test shows that there was an accumulation effect only for CHD in men. Further analysis did not show this effect to be concentrated in a particular trajectory. The final set of results in Table 4 show the effects of accumulation for individuals with low SEP at time point 3. Of the men, 29.2% and 42% of women in this category have low SEP across the three time points. Test for trend shows the accumulation effect to be evident for CHD in women. However, this effect was in the opposite direction. Women who had experienced disadvantage across the life course (trajectory 222) had less CHD risk when compared with trajectory 002.


    Discussion
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 Abstract
 Data and Methods
 Results
 Discussion
 References
 
Research on a wide variety of available data has shown that investigation into the socioeconomic determinants of health would benefit from considering accumulation of socioeconomic advantage and disadvantage over the lifecourse.2,7,28 The analysis presented in this paper adds to the existing evidence on the relationship between accumulation of life course socioeconomic exposure and health outcomes in adulthood. It differs from other studies examining this issue as we analyse the effect of accumulation using trichotomous rather than dichotomous categories of SEP. A summary measure of socioeconomic exposure, reflecting place in the socioeconomic hierarchy at three points in the life course, was created to capture socioeconomic exposure over the life course. Results show a clear graded effect of accumulation of socioeconomic exposure on CHD and physical functioning in men and women, and on mental functioning in men. Increasing levels of socioeconomic disadvantage over the life course were associated with increasingly poor health. No cumulative effect of SEP was found on minor psychiatric disorder.

In analysis stratified by destination SEP (employment grade at time point 3), the evidence for the accumulation hypothesis is weaker, being mostly confined to men in the high employment grade. Three conceptual models have been identified within the life course framework to explain the association between health and socioeconomic circumstances over the lifecourse.13,29–31 These are: critical periods or the latent effects model, the accumulation model, and the pathways model. The critical periods model views specific biological (e.g. low birthweight) or developmental factors at sensitive periods of development, usually early life, to have a lifelong impact on health, independently of adult circumstances.32 The accumulation model proposes that disadvantage at different points in the life course has a cumulative dose–response relationship with health. The pathway model views early environment to be important, but only because it shapes and influences the socioeconomic trajectories of individuals.

The three life course models have often been set up as competing hypotheses. However, a recent paper shows that they are interrelated in such a way that it is impossible to empirically disentangle them within the life course perspective.15 Our analysis clearly shows that these hypotheses are not mutually exclusive. There is support for the accumulation hypothesis in the first set of analysis (Table 3). However, the second set of analysis, related to our second research question, supports all three models. The accumulation hypothesis was most evident, in terms of the number of significant effects, among men who had high destination SEP (Table 4). The importance of the pathway model is evident in the weakening of the accumulation effect when analysis is stratified by adult SEP. Results relating to CHD suggest early deprivation followed by affluence to be a risk factor, thus supporting the ‘critical periods’ model. Our analysis intimates that evidence used to support one model over others is entirely dependent on the health outcome examined and the chosen method of analysis.

A gradient in the accumulation effect on CHD and physical functioning was also seen among women. In order to test the accumulation hypothesis we used the same measures of SEP in men and women to construct the trajectories. Some studies use household SEP for women,33 while others have argued that a woman's own occupation or education is a better reflection of her SEP.34–36 In keeping with a recent paper by Heslop and colleagues on the cohort of workers from Western Scotland,14 we have shown results with trajectories based on own social class rather than partner's or household SEP. As in the Western Scotland cohort, our results show an accumulation effect in women. However, there is little evidence of a cumulative effect of SEP in women when the analysis is stratified by employment grade. Future analysis will determine whether this suggests a stronger evidence for the pathways model among women or the effect is related to different mobility patterns in men and women.

Although the focus of this paper is not the proximal mediating mechanisms through which socioeconomic circumstances affect health, the results obtained here do necessitate further reflection on these pathways. The specific pathways that are more susceptible to the accumulative effect of SEP are yet to be specified. However, the behavioural pathway,13,37 linking factors like physical activity, smoking behaviour, diet, and alcohol consumption is an obvious candidate as patterns of behaviour are often set in early childhood. The same is likely to be true for the physiological factors related to stress mechanisms,38 and material disadvantage that may be implicated in sustaining the link.

There are obvious caveats to conclusions drawn in the paper. First, data limitations have led us to use different measures of socioeconomic position, all of which do not have the same meaning to construct socioeconomic trajectories.39 Even though education is not strictly a measure of SEP, it is widely used as a marker of social circumstances. It may be useful to have better and more comprehensive measures of socioeconomic circumstances at each time point in order to estimate better the cumulative impact of socioeconomic circumstances on health. Second, the socioeconomic measure at time point 3 in our analysis, occupational position at the start of the Whitehall II study, covers a wide age range, 35–55 years. Age is always a concern when using life course data to examine the association between socioeconomic exposure and health outcomes. As well as controlling for age in our analyses we also carried out age-stratified analysis (results not shown) in order to ensure that the socioeconomic indicator had the same meaning for all individuals at time point 3. As has been found in another study, the age range at time point 3 did not unduly influence our results.40

Third, the 20-year age difference between the youngest and oldest members of the Whitehall II cohort suggests that there may be cohort differences in the meaning of educational qualifications and father's social class. Older members of the cohort are more likely to have fewer qualifications; change in the occupational structure in the 20th century has meant that younger respondents are less likely to have a father from a manual social class. However, even though the normative distribution of these measures of socioeconomic circumstances may have changed over the lifetime of the Whitehall II cohort, other research has shown the social gradient in health to be similar across the 1946, 1958, and 1970 British birth cohorts.41 Finally, it is highly likely that all the effects have been underestimated due to the particularities of the sample; which entirely comprises white collar civil servants in employment, and with no missing data.

In conclusion, our results show the accumulation hypothesis to operate across the socioeconomic spectrum in a cohort of white collar civil servants. The fact that the accumulation effect in our data was stronger for some health outcomes (CHD) and weaker or non-existent for others (GHQ) requires further investigation. Even in analysis stratified by adult SEP, CHD was the health outcome most susceptible to the accumulation hypothesis. CHD represents a diverse set of pathological entities and it is possible that it implicates multiple pathways. Future research, perhaps with more comprehensive measures of socioeconomic circumstances used to construct trajectories will shed further light on this issue. Further work is also required on the effect of particular trajectory types, upward and downwards mobility for instance, on health.


KEY MESSAGES

  • It has been shown that disadvantage over the life course has a cumulative effect on health, with most of the evidence coming from comparisons of manual versus non-manual categories.
  • We show accumulation of socioeconomic advantage and disadvantage in a cohort of white collar civil servants.
  • The effects of accumulation of socioeconomic position (SEP) exposure are evident in men and women for coronary heart disease and health functioning.
  • In addition to accumulation effects, analysis stratified by adult SEP also provided support for the critical period and pathway model.

 


    Acknowledgments
 
The Whitehall II study has been supported by grants from the Medical Research Council; British Heart Foundation; Health and Safety Executive; Department of Health; National Heart Lung and Blood Institute (HL36310), US, NIH: National Institute on Aging (AG13196), US, NIH; Agency for Health Care Policy Research (HS06516); and the John D and Catherine T MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health. MM is supported by an MRC Research Professorship. The authors would like to thank Dr Paul Clarke for help with the idea of trajectories. We also thank all participating civil service departments and their welfare, personnel, and establishment officers; the Occupational Health and Safety Agency; the Council of Civil Service Unions; all participating civil servants in the Whitehall II study; and all members of the Whitehall II study team.


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 Discussion
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