Low socioeconomic status is associated with a higher incidence risk of stroke in multiple populations worldwide. Although differences in the prevalence and severity of vascular risk factors likely contribute to this disparity, these risks may also be modified by negative socioeconomically driven influences throughout an individual’s lifespan. Becher et al. sought to investigate this further by conducting a case-control study to investigate the contribution of socioeconomic, genetic, and infectious risk factors during childhood, adolescence, and adulthood with respect to the risk of ischemic stroke in adulthood.
The study was nested in a population-based stroke registry in the city of Ludwigshafen, a city in South-West Germany with about 160,000 inhabitants. Patients of Caucasian race-ethnicity ages 18-80 with first-ever ischemic stroke treated at the only stroke unit within the city were compared to age and sex matched controls who were randomly selected from the general population. Patients with prior stroke, myocardial infarction within the last 90 days, dementia or severe communication barriers were excluded. 

Variables that were studied included anthropometric measures, medical history, smoking status, alcohol intake, diet, physical activity and medications. Socioeconomic measures were separated by age group (childhood, up to age 14; adolescence, age 15-25; adulthood,> age 25). Childhood socioeconomic conditions included parents’ occupation (divided into academic, non-academic white collar, blue collar and unskilled labor) during subjects’ childhood as well as living, familial, material and self-estimated financial conditions. For adolescence, highest school degree and professional education was used.  Last, profession, marital status and periods of unemployment were used as conditions for adulthood. Risk scores were calculated prior to analysis by summing scores according to weights chosen a priori based on previous work. Principal component analysis was also performed, as well as classification into tertiles of the summed scores based on distribution in controls. Odds ratio estimates were determined using both univariate and multivariate analyses, with the latter adjusted for known risk factors for stroke and the other life periods. 

A total of 470 subjects agreed to participate in the study and were compared to 809 controls. For childhood conditions, a higher number of siblings (OR=1.48[1.12-1.96]), lack of an own toilet (OR=1.52[1.12-2.05]), and estimated lower family income (OR=2.9[2.18-3.87]) were independently  associated with stroke in multivariate analysis. Lack of vocational training in adolescence (OR=1.93[1.03-3.63]) was independently associated with stroke.  In adulthood, single, divorced or windowed persons (OR=1.63[1.20-2.22]), greater than 6 months of unemployment (OR=1.52[1.05-2.19]) and unskilled last profession (OR=1.99[1.11-3.60]) were independently associated with stroke. In the fully adjusted model (adjusting for age, sex, medical and lifestyle risk factors, and the other life stages), low socioeconomic conditions during childhood (OR=1.77[1.20-2.60]) and adulthood (OR=1.74[1.16-2.60]) were independently associated with stroke risk. Interestingly, adjustment for medical risk factors attenuated the socioeconomic effect in childhood whereas lifestyle risk factors reduced the effect during adolescence and adulthood. When analyzed by stroke subtype, less favorable childhood socioeconomic conditions were associated with a strong risk of large artery stroke (OR=2.13[1.24-3.67]) that was not found for other etiologies of stroke or life stages. 

This study provides an intriguing insight into the impact of various socioeconomic conditions during each stage of life on stroke risk during adulthood. The relatively large number of patients and variety of factors assessed contribute to the strength of the study, although the lack of knowledge about the precise way that socioeconomic conditions affect health makes confounding factors difficult to assess and control. The attenuation of childhood risk after adjustment for medical factors suggests that factors in childhood may be causally linked to the development of known medical risk factors for stroke later in life, and the attenuation of adult risk after adjustment for lifestyle factors suggests that their effects may be independent of medical risk factors. Further study looking at associations with childhood socioeconomic conditions and medical risk factors for stroke could provide further clarity on this issue. The association of low socioeconomic conditions in childhood with large artery strokes may be related to this relationship, as there are many commonalities between medical risk factors for atherogenesis and stroke. The authors’ hypothesis related to chronic systemic inflammation could be further investigated using high-sensitivity CRP values either in a similarly designed study or, ideally, a longitudinal cohort that would track these values over time.   

The racial and geographical homogeneity of the study population limits its generalizability.  Conducting and reviewing similar studies with racially diverse populations in a variety of locations could be helpful in identifying common factors, as there is likely important variation in diet and environmental exposures between low socioeconomic status groups in different regions worldwide. This study and similar studies will be vital in expanding our understanding of how social conditions contribute to stroke risk.