Pathways From Childhood Intelligence and Socioeconomic Status to Late-Life Cardiovascular Disease Risk

• Published in: Health psychology 2012-07, Vol.31 (4), p.403-412
• Main Authors: Hagger-Johnson, Gareth, Mõttus, René, Craig, Leone C. A., Starr, John M., Deary, Ian J.
• Format: Article
• Language: English
• Subjects: Aged; At Risk Populations; Biological and medical sciences; Biomarkers; Body Mass Index; C-Reactive Protein - analysis; Cardiovascular diseases; Cardiovascular Diseases - blood; Cardiovascular Diseases - epidemiology; Cardiovascular Disorders; Child; Childhood; Childhood Development; Cohort Studies; European Continental Ancestry Group; Female; Fundamental and applied biological sciences. Psychology; Geriatrics; Health Behavior; Human; Humans; Illness and personality; Income; Inflammation; Intelligence; Life Span; Male; Medical sciences; Models, Theoretical; Personality, behavior and health; Proteins; Psychology and medicine; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Psychopathology. Psychiatry; Risk; Risk Factors; Scotland - epidemiology; Social Class; Socioeconomic Status
• ISSN: 0278-6133; 1930-7810
• DOI: 10.1037/a0026775

Objective: C-reactive protein (CRP) is an acute-phase marker of systemic inflammation and considered an established risk marker for cardiovascular disease (CVD) in old age. Previous studies have suggested that low childhood intelligence, lower socioeconomic status (SES) in childhood or in later life, unhealthy behaviors, poor wellbeing, and high body mass index (BMI) are associated with inflammation. Life course models that simultaneously incorporate all these risk factors can explain how CVD risks accumulate over time, from childhood to old age. Methods: Using the data from 1,091 Scottish adults (Lothian Birth Cohort Study, 1936), a path model was constructed to predict CRP at age 70 from concurrent health behaviors, self-perceived quality of life, and BMI and adulthood SES as mediating variables, and from parental SES and childhood intelligence as distal risk factors. Results: A well-fitting path model (CFI = .92, SRMR = .05) demonstrated significant indirect effects from childhood intelligence and parental social class to inflammation via BMI, health behaviors and quality of life (all ps < .05). Low childhood intelligence, unhealthy behaviors, and higher BMI were also direct predictors of CRP. Conclusions: The life course model illustrated how CVD risks may accumulate over time, beginning in childhood and being both direct and transmitted indirectly via low adult SES, unhealthy behaviors, impaired quality of life, and high BMI. Knowledge on the childhood risk factors and their pathways to poor health can be used to identify high-risk individuals for more intensive and tailored behavior change interventions, and to develop effective public health policies.