8/10/2012. Education level and diabetes risk: The EPIC-InterAct study AIM. Background. Case-cohort design. Int J Epidemiol 2012 (in press)

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1 Education level and diabetes risk: The EPIC-InterAct study 50 authors from European countries Int J Epidemiol 2012 (in press) Background Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases worldwide. In high-income countries, low education level (as a proxy for SES) seems to be related to a high incidence of T2DM. Nevertheless, the relationship between educational level and T2DM is complex, as it is mediated by anthropometric factors, lifestyle, behaviour, access to health services and knowledge of health promotion. Educational level as a proxy for SES because it is easily and accurately reported and is unaffected by poor health in adulthood. To assess the association between risk of T2DM and educational level (as a proxy for SES) for the first time in a large European case-cohort study with a validated case ascertainment procedure and detailed information on other risk factors that were measured in a standardized manner across eight Western European countries. AIM The EPIC-InterAct study The InterAct project: To investigate how genetic and lifestyle behavioural factors interact for the risk of developing diabetes and how knowledge about such interactions may be translated into preventive action. The EPIC-InterAct study: As part of the wider InterAct Project, consortium partners have established a case cohort study of incident type 2 diabetes (InterAct Study) based on cases occurring in European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts between 1991 and 2007 in eight of ten EPIC countries participating in InterAct. Case-cohort design Cases: The case cohort design of the InterAct Study differs from the nested case control design in that a random subcohort is selected instead of a set of matched controls. A total of 340, 234 EPIC participants were followed up for a mean time of 11.7 years during which verified incident cases of T2DM were identified and included in the InterAct project. Subcohort: A sub-cohort of 16,835 individuals was randomly selected from those with available stored blood and buffy coat, stratified by centre. Why case-cohort study: Selecting a random subcohort (nested case cohort study) rather than matched controls (nested case control study) has the additional advantage that it facilitates the design and conduct of future case cohort studies for other diseases occurring in the same background population or cohort. 1

2 Ascertainment and verification of incident cases of T2DM A high sensitivity approach was adopted for the ascertainment of incident cases of T2DM, with the aim of identifying all incident cases and excluding all individuals with prevalent diabetes. Evidence based on: Self-reported T2DM in follow-up questionnaires (T2DM diagnosed by a medical doctor or anti-diabetic drug use), Linkage to primary and secondary care registers, Medication use (prescription registers), and Hospital admission and mortality data. T2DM cases were included in the study only if confirmation of the diagnosis was secured from no less than two independent sources, including individual medical-record review. Relative indices of inequality (RII) The midpoint of the cumulative proportional distributions of each educational level was used to calculate the RII score. Example: 60% attended primary school (low education level) 30% attended secondary school (middle education level) 10% attended high school (high education level) RII score: For low education level, RII score = 0.30 (mid point of 60%) For middle education level, RII score = 0.75 = /2 For high education level, RII score = 0.95 = /2 Other variables Self-administered questionnaires for lifestyle factors & dietary habits BMI (continuous variable), Marital status (single, married, separated and widowed), Smoking status (never, former and current smoker), Alcohol consumption (never, former and current drinker), Physical activity (covering occupation and recreational activity according to a validated physical activity index; inactive, moderately inactive, moderately active and active), Macronutrient intake (total energy, total proteins, total carbohydrates and total fats (continuous variable)), and Weight and height measurements (continuous variable) Statistical analysis The distribution of exposures and putative confounders were summarized in the sub-cohort using means and standard deviations for continuous variables, and percentages and frequencies for categorical variables. Causal diagram in the next page 2

3 Tertiles of RII score The purpose of this index in the present study was to quantify the effect of the RII score on T2DM risk. The RII expresses inequality within the whole socioeconomic continuum and can be interpreted as the ratio of the risk of T2DM between the high educational level (RII tertile 1) and the low educational level (RII tertile 3). Propensity score matching Due to a small effect of dietary variables, the propensity score matching was used. The propensity score represents the probability that an individual belongs to a certain RII tertile given his or her macronutrient intake (total energy, total proteins, total carbohydrates and total fats). Tertile I : low inequality - high educational level Tertile II : middle inequality - middle educational level Tertile III: high inequality - low educational level Note: The RII has considerable advantage for cross-national comparisons, in particular, they are not prone to different group sizes and (somewhat) different categorizations of the socio-economic factor. Models Model I: Physical activity, smoking status and propensity score according to macronutrient intake Model II: Physical activity, smoking status, propensity score according to macronutrient intake, and BMI (in quartiles) Age and gender were not adjusted, because the principal determinant was already standardized by those variables Alcohol consumption was not adjusted, following the results of the DAG analysis Hazard ratios (HR) were calculated using a weighted Cox proportional hazards regression analysis, modified to be appropriate for this case-cohort design. Statistical analysis The proportional hazard assumptions were tested in the subcohort using the Grambsch and Therneau test. Prentice weight: all sub-cohort individuals were equally weighted in the likelihood function. Incident cases of T2DM were not weighted until they were diagnosed with T2DM. Once diagnosed they were considered incident cases of T2DM and given the same weight as the incident cases of T2DM in the random sub-cohort. Used a fixed effects model to obtain pooled HRs Sensitivity analysis Two sided test Software: STATA v10.0 and Comprehensive Meta-Analysis v2.2. 3

4 Discussion Educational level (and SES in general) does not have a direct biological effect on disease; instead its effects are mediated by other risk factors that can be biologically related to disease (i.e. smoking status, BMI, physical activity). In the InterAct project, the association between lower educational level and higher risk of T2DM was not demonstrably mediated by any of the variables. In this study, the association between lower educational level and higher risk of T2DM was demonstrably mediated by behavioural risk factors. Strengths and limitations Strengths: Possibility to study the relationship between diabetes and SES in more than one country. Many risk factors measured in a standardized manner across countries. Limitations: African or Hispanic groups, a much higher prevalence of diabetes, were not represented in the cohort. Recruit people belonging either to the lower strata of higher social classes or the highest strata of lower social classes. Residual confounding caused by unmeasured variables such as psychological factors and stress is possible. Key massages Lower educational level is inversely associated with the risk of type 2 diabetes mellitus across different Western European countries, even in those with a history of social equality. Only adjustment for body mass index, and not for other risk factors, partially reduced inequalities in the risk of type 2 diabetes mellitus due to differences in educational levels in men and women. 4

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