The impact of education on risk factors and the occurrence of multimorbidity in the EPIC-Heidelberg cohort.
BACKGROUND
In aging populations, the prevalence of multimorbidity is high, and the role of socioeconomic status and its correlates is not well described. Thus, we investigated the association between educational attainment and multimorbidity in a prospective cohort study, taking also into account intermediate factors that could explain such associations.


METHODS
We included 13,781 participants of the Heidelberg cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC), who were 50-75 years at the end of follow-up. Information on diet and lifestyle was collected at recruitment (1994-1998). During a median follow-up of 8.7 years, information on chronic conditions and death were collected.


RESULTS
Overall, the prevalence of multimorbidity (>= 2 concurrent chronic diseases) was 67.3%. Compared to the highest educational category, the lowest was statistically significantly associated with increased odds of multimorbidity in men (OR = 1.43; 95% CI 1.28-1.61) and women (OR = 1.33; 95% CI 1.18-1.57). After adjustment, the positive associations were attenuated (men: OR = 1.28; 95% CI 1.12-1.46; women: OR = 1.16; 95% CI 0.99-1.36). Increasing BMI was more strongly than smoking status an intermediate factor in the association between education and multimorbidity.


CONCLUSIONS
In this German population, the prevalence of multimorbidity is high and is significantly associated with educational level. Increasing BMI is the most important predictor of this association. However, even the fully adjusted model, i.e. considering also other known risk factors for chronic diseases, could not entirely explain socio-economic inequalities in multimorbidity. Educational level should be considered in the development and implementation of prevention strategies of multimorbidity.
Nagel
Gabriele
G
Institute of Epidemiology, Ulm University, Ulm, Germany. gabriele.nagel@uni-ulm.de
Peter
Richard
R
Braig
Stefanie
S
Hermann
Silke
S
Rohrmann
Sabine
S
Linseisen
Jakob
J
D000367:Age Factors; D000368:Aged; D000886:Anthropometry; D015992:Body Mass Index; D002908:Chronic Disease / Q000145:classification / Q000453:epidemiology*; D015331:Cohort Studies; D015897:Comorbidity; D003430:Cross-Sectional Studies; D004032:Diet; D004522:Educational Status; D005260:Female; D005858:Germany / Q000453:epidemiology; D006297:Health Services Accessibility; D006305:Health Status Indicators; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D016016:Proportional Hazards Models; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors