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RESEARCH AND PRACTICE |
Debbie A. Lawlor is with the Department of Social Medicine, University of Bristol, Bristol, England. At the time of this study, G. David Batty was with the Department of Social Medicine, Institute of Public Health, University of Copenhagen, Copenhagen, Denmark. Susan M. B. Morton is with the School of Population Health, University of Auckland, Auckland, New Zealand. Heather Clark is with the Dugald Baird Centre for Research on Womens Health, University of Aberdeen, Aberdeen, Scotland. Sally Macintyre is with the MRC Social and Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland. David A. Leon is with the Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, England.
Correspondence: Requests for reprints should be sent to Debbie A. Lawlor, Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol BS7 8QA, United Kingdom (e-mail: d.a.lawlor{at}bristol.ac.uk).
| ABSTRACT |
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Objectives. We assessed the associations of childhood socioeconomic position with cardiovascular disease risk factors (smoking, binge alcohol drinking, and being overweight) and examined the roles of educational attainment and cognitive functioning in these associations.
Methods. Data were derived from a cohort study involving 7184 individuals who were born in Aberdeen, Scotland, between 1950 and 1956; had detailed records on perinatal characteristics, childhood anthropometry, and cognitive functioning; and responded to a mailed questionnaire when they were aged 45 to 52 years.
Results. Strong graded associations existed between social class at birth and smoking, binge drinking, and being overweight. Adjustment for educational attainment completely attenuated these associations. However, after control for adult social class, adult income and other potential confounding or mediating factors, some association remained.
Conclusions. Educational attainment is an important mediating factor in the relation between socioeconomic adversity in childhood and smoking, binge drinking, and being overweight in adulthood.
| INTRODUCTION |
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| METHODS |
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Assessment of Childhood Socioeconomic Position
Childhood SEP was assessed at 2 time points. Social class at birth was based on the occupation of the study participants father; these data were obtained from Aberdeen Maternity and Neonatal Databank obstetric records. Six categories were included: professional, managerial, skilled nonmanual, skilled manual, semiskilled, and unskilled manual. These categories can be collapsed into the 2 general categories of nonmanual (professional, managerial, and nonmanual/skilled nonmanual) and manual (manual/skilled manual, semiskilled, and unskilled manual). At the time of the childhood survey (1962), fathers occupation was reported by each child and was similarly coded. All analyses were conducted with these 2 measures as exposure variables; however, none of the results differed substantively between the 2 measures, and thus we present results only for associations with social class at the time of birth.
Assessment of Cognitive Functioning and Educational Attainment
Throughout the 1950s in Aberdeen, cognitive function was routinely tested through the administration of IQ tests to children at the ages of 7, 9, and 11 years. These IQ scores were abstracted for the study participants, and results of tests taken after December 1962 and up until 1964 also were obtained as they became available. In this study, we used the results from the tests administered when the participants were aged 7 and 11 years. The tests conducted at 7 years provided an indication of the childrens functioning before they had completed a significant amount of formal education, thus reflecting early postnatal exposures and family environment. Conversely, the tests conducted at age 11 reflected cognitive functioning at the end of the childrens primary school education, and thus scores were influenced by the educational process and peer relationships as well as earlier exposures.
At 7 years of age the participants were administered the Moray House Picture Intelligence Tests.18 All participants were administered the test within 6 months of their 7th birthday. The tests given at age 11, also conducted within 6 months of participants 11th birthday, included a battery of Moray House tests: 2 tests of verbal reasoning and 1 each of arithmetic and English. Because the mean verbal reasoning score was highly correlated with the arithmetic and English scores (Pearson correlation coefficients of 0.86 and 0.89, respectively, P < .001 for both) and all 3 showed similar associations with exposures and outcomes in this study, mean verbal reasoning scores at 11 years were used as the measure of cognitive functioning at that age.
In the mailed health questionnaire, participants were asked to report the age at which they left secondary education and to indicate their educational or vocational qualifications. A list was provided that included an option of "no formal qualification" and then a hierarchy of seven formal United Kingdom educational qualifications from leaving certificate (lower level of qualification by those leaving school at a minimum school-leaving ageaged 15 years for this cohort) through a university degree.
Assessment of Other Childhood Characteristics
Birthweight and gestational age data were abstracted from obstetric records at the time of the 1962 survey.18 Participants intrauterine growth rate was estimated by calculating standardized z (standard deviation) scores for sex and gestational age (in weeks). Height and weight at school entry were measured directly, and these data were linked to the childhood survey data participants in 1962. Age- and sex-standardized z scores based on 3-month age categories were derived for height and weight.
Adult Characteristics
At the time of the questionnaire mailing (2000), 291 (2.4%) of the 12 150 original cohort members had emigrated (outside the United Kingdom), 62 (0.5%) were in the armed forces or institutionalized, 479 (4.0%) had died, and 36 could not be reached for other reasons. The remaining 11 282 participants were mailed a follow-up health questionnaire, and 7183 (63.7%) responded. In comparison with nonresponders, responders were more likely to be female, to have been categorized as affluent in terms of childhood SEP, and to have had high cognitive function scores as children.18,21
Participants were asked about their most recent occupation. Occupations were categorized into the same 6 categories used for childhood social class. Also, participants were asked to indicate their personal gross annual income (no income, less than £2000, £2000£5999, £6000£9999, £10 000£14 999, £15 000£19 999, £20 000£29 999, £30000£39999, £40000 or more); weekly equivalent amounts were provided for each category.
Respondents were asked about their own smoking behavior and whether their parents had smoked when they were children. Binge drinking was defined as consumption of 4 or more alcoholic drinks in 1 episode at least once a week.
In addition, participants were asked to record their weight and height. Of the 7007 respondents who provided an estimate of their weight, 6092 (87%) reported that they had used a scale. There was a tendency for those who had not used a scale to report weights lower than their weights (74.5 kg vs 75.5 kg; P = .07). Therefore, all analyses that included body mass index, obesity, or weight were adjusted by including a dummy variable for scale nonuse in the multivariate models. Overweight was defined as a body mass index of 25 kg/m2 or more.22
Statistical Analysis
Means for continuous variables, and prevalences for dichotomous variables, are presented in regard to participant characteristics according to social class at birth. We fit regression models to assess linear trends across these categories by entering social class at birth as a score in these models and conducting an F test.
Relative indexes of inequality (RIIs)23 were estimated for the associations of social class at birth, educational attainment, adult social class, and adult income with childhood and adult height. For each SEP exposure, a score was assigned to each category on the basis of the midpoint of the proportion of the population in that category. For example, if 10% of the respondents were assigned to the professional social class category and a score from 0 (highest SEP) to 1 (lowest SEP) represented the entire population, participants in this group would be allocated a score of 0.05 (0.1/2); if 20% of the respondents were in the managerial category, this group would be allocated a score of 0.20 (0.1 + 0.2/2); and so on. The index of inequality was then obtained by regressing the outcome on each of these SEP scores. The virtue of this technique is that it is directly interpretable as comparing, in each case, the highest (0) and lowest (1) SEP indicators assigned.23
A series of multiple logistic regression models was used to assess the associations of social class at birth with the risk factors examined. In these models, participants age, cognitive functioning at ages 7 and 11, age at leaving secondary school, intrauterine growth z score, and childhood height and body mass index were all entered as continuous variables. Birth order, family size, adult social class, adult income, parental smoking, and educational qualifications were all entered as categorical variables. These analyses were repeated with the inclusion of RII scores (as just detailed) for social class at birth and each measure of adult SEP and education. Likelihood ratio tests were used to assess interactions. All analyses were conducted with Stata version 8.0 (Stata Corp, College Station, Tex).
| RESULTS |
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Table 2
presents the adult characteristics of the participants according to their social class at birth. The response proportion decreased linearly with decreasing SEP. All 3 CVD risk factors showed a graded association across the social class distribution, with the most unfavorable level of each seen in adults who were born in the lowest-status socioeconomic groups. Adult social class, income, and educational attainment also showed strong incremental associations with social class at birth. The prevalence and means of adult characteristics according to whether the participants father was unemployed at the time of the participants birth are also shown in Table 2
. In general, results for this unemployed category were similar to those for the manual social class category. Because those who are unemployed are likely to be a heterogeneous group and cannot be grouped according to an occupational classification, all further results, including the trend tests presented in Table 2
, exclude participants whose fathers were unemployed.
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When RII scores were estimated for childhood SEP, education, adult income, and social class in these models, the patterns of the associations and effects of potential mediating factors were similar to those shown in Table 4
. For example, after adjustment for all covariates other than education (equivalent to model 13 in Table 4
), the RII for current smoking associated with social class at birth was 1.35 (95% CI = 1.03, 1.72); after additional adjustment for educational attainment (equivalent to model 14), this RII decreased to 1.19 (95% CI = 0.92, 1.54). Results were similar for binge drinking (corresponding RIIs of 1.23 [95% CI = 1.01, 1.55] and 1.04 [95% CI = 0.79, 1.35]) and being overweight (corresponding RIIs of 1.37 [95% CI = 1.08, 1.72] and 1.19 [95% CI = 0.93, 1.49]).
| DISCUSSION |
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The present associations between SEP at birth and smoking and binge drinking were largely explained by educational attainment. Adjustment for educational attainment also importantly attenuated the association between childhood SEP and being overweight in adulthood.
Study Limitations
Although the majority of eligible survivors (64%) responded to the questionnaire mailed in 2000, important differences were found between responders and nonresponders. Prevalence rates of smoking and overweight were higher among Scottish Health Survey respondents aged 45 to 54 years than among respondents in our cohort (Table 1
).24 These differences may reflect socioeconomic differentials between the 2 groups of respondents, real differences in smoking and overweight rates between Aberdeen and the rest of Scotland, or both.24 Differences between responders and nonresponders in our study would have resulted in exaggerated associations being observed between SEP at birth and adult behaviors only if there were no associations among nonresponders or these associations were in the opposite direction (i.e., nonresponders in more affluent family circumstances at the time of their birth were more likely to smoke, binge drink, and be overweight later in life) from those among responders.
Similarly, for the role of education in this association to be exaggerated by response bias, one would have to assume that among nonresponders the association between low SEP at birth and low educational attainment or the association between low educational attainment and adult risk behaviors was nonexistent or in the opposite direction from that among responders. While we cannot rule out these possibilities, they seem unlikely.
A strength of this study is the use of a measure of childhood SEP assessed at study initiation rather than one retrospectively reported in adulthood. However, a weakness is that we included only 1 measure of childhood SEP: fathers social class. Such a single measure is unlikely to encompass the entire spectrum of childhood social circumstances, and its effect on adult risk factorsand, therefore, our resultsmay have led to underestimations of the true magnitude of this association.
Our measure of adult income was based on individuals rather than households. Among women in particular, this may not reflect true disposable income, because individuals with spouses will vary widely in regard to household income. This may explain the interactions between gender and income that we observed in the case of some of the outcomes. To address this issue, we included an interaction term between gender and income in the multivariate models.
Adult body mass index was determined from self-reported weight and height, which have been shown to be strongly correlated with direct measurements.2527 However, despite these strong correlations, indicative that self-reports and direct measurements result in similar height and weight values, individuals who are obese tend to underestimate their body mass index. 2527 If this systematic misreporting of weight was similar across social class groups in our study, it would have tended to dilute rather than exaggerate the magnitude of the associations observed. Any variations in misreporting according to social class could have biased our results in either direction. We found that participants who indicated not using scales to estimate their weight reported slightly lower weights on average, and this difference did not vary according to childhood or adult social class. This result provided some evidence that misreporting of weight did not differ according to social class.
Data on parental smoking were not collected during the original survey, so we relied on information obtained from the 20002002 questionnaire. If there were no differences in misreporting with respect to social class at birth, our results may have underestimated the effects of parental smoking on the association between social class at birth and adult CVD risk factors. This may in part explain why adjustment for adult smoking had very little effect on the association between social class at birth and smoking in adulthood.
The participants in this cohort are too young to have experienced a sufficient number of CVD events to allow determination of the pathways between childhood SEP and adult disease events. However, by continuing to conduct follow-ups with these individuals, we will be able to obtain important information on the roles of cognitive functioning, educational attainment, and CVD risk factors in the associations between childhood SEP and risk of CVD in adulthood.
Public Health Implications
Our results concerning CVD risk factors are consistent with a systematic review of previous studies indicating that childhood socioeconomic adversity is associated with adverse behavioral risk factors both at young ages28 and with other studies showing similar associations with adverse risk factors in adulthood.4,5,7,9,11,12 Previous studies also have demonstrated associations of educational attainment with CVD risk factors.2931 The importance of our results resides in demonstrating the role of educational attainment as a mediator in the association between childhood SEP and adult behavioral risk factors. Given that cigarette smoking, binge drinking, and being overweight are known to increase CVD risk, our results suggest that a pathway leading from childhood socioeconomic adversity to low educational attainment and adverse CVD risk factors may explain in part the association between childhood SEP and CVD.
The role of educational attainment in the association between childhood SEP and adult behaviors could be explained via a number of pathways. Educational attainment will itself be influenced by childhood SEP, and its effect on the association between social class at birth and adult behaviors may indicate its value as a measure of childhood SEP. The association between social class at birth and childhood growth and height was stronger than that between education and childhood growth, suggesting that our measure of social class at birth was a better indicator of childhood socioeconomic circumstances than educational attainment. Educational attainment is associated with adult occupation and income, and thus it may reflect the availability of material resources, which are thought to be important determinants of health outcomes.32
We found that neither adult social class nor income fully explained the associations between childhood social class and adult risk factors, whereas education did explain these associations. Income is arguably the best single indicator of material living standards, but there is some evidence in the United Kingdom that survey participants may be reluctant to provide information on income and that, when they do, the information is inaccurate33; however, this observation has been disputed.34
Our results suggest that, rather than material resources, other factors related to higher educational achievement most likely explain the association between childhood SEP and behavioral risk factors in adulthood. The sociocultural characteristics of those at higher educational levels, for example self-confidence and ability to access and understand health promotional materials, may be relevant. Moreover, peoples behaviors with respect to tobacco and alcohol consumption, diet, and physical activity, which will affect their body mass index, are likely to be influenced by their peers. Educational experiences will determine ones peers at the sensitive life course periods (late adolescence and early adulthood) during which these behaviors tend to be adopted.
In conclusion, we have shown that childhood SEP is associated with adult CVD risk factors. It is notable that the fathers occupation when participants were born could have predicted which participants were most likely to be smokers and indulge in other risky behaviors in adulthood. Educational attainment appears to largely explain these associations. Our findings suggest that programs aimed at improving educational attainment may be important in enhancing health behaviors and therefore reducing CVD risk.
| Acknowledgments |
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We are very grateful to Raymond Illsley for providing us with the data from the Aberdeen Child Development Survey and for his advice about the study. Graeme Ford played a crucial role in identifying individual cohort members and in helping us initiate the process of revitalizing the cohort. Doris Campbell, George Davey Smith, Marion Hall, Bianca de Stavola, David Godden, Di Kuh, Glyn Lewis, and Viveca Östberg collaborated with the authors to revitalize the cohort. Margaret Beveridge assisted in study management.
We also thank staff at the Information and Statistics Division (Edinburgh), the General Regional Office (Scotland), and the National Health Service Central Register (Southport, England) for their substantial contributions and John Lemon, who undertook the linkage to the Aberdeen Maternity and Neonatal Databank. Finally, we thank the study participants who responded to a mailed questionnaire 40 years after the original survey was completed.
Note. The views expressed in this article are those of the authors and not necessarily those of any funding body.
Human Participant Protection
The revitalization of the Aberdeen Children of the 1950s Study cohort was approved by the Scottish multicenter research ethics committee and local research ethics committees, along with the Scottish Privacy Advisory Committee. Participants responding to the questionnaire provided informed consent to be involved in the study.
| Footnotes |
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Contributors
D. A. Lawlor and D. A. Leon developed the idea for this article. D. A. Lawlor undertook the statistical analysis, wrote the first draft of the article, and coordinated the writing of the article. H. Clark managed the study. All of the authors were involved in the writing of the article.
Accepted for publication July 13, 2004.
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