title: Childhood socioeconomic disadvantage and prediabetes and diabetes in later life: a study of biopsychosocial pathways.
abstract: OBJECTIVE
  We examined the relationship between childhood socioeconomic status (SES) and glucoregulation in later life and used a life-course framework to examine critical periods and underlying pathways.
  
  
  METHODS
  Data came from the Midlife in the US (MIDUS) national study (n = 895). Childhood SES indicators retrospectively reported at MIDUS I were used to create a childhood SES disadvantage index. Adult SES disadvantage and potential pathways were measured at MIDUS I and included waist circumference, depressive symptoms, and physical activity. Glucose and hemoglobin A1c, measured approximately 9 to 10 years later at MIDUS II, were used to create the ordinal outcome measure (no diabetes/prediabetes/diabetes).
  
  
  RESULTS
  Childhood SES disadvantage predicted increased odds of prediabetes and diabetes net of age, sex, race, and smoking (odds ratio = 1.11, 95% confidence interval = 1.01-1.22). Childhood SES disadvantage predicted adult SES disadvantage (β = .26, p = .001) and the three key mediators: waist circumference (β = 0.10, p = .002), physical activity (β = -0.11, p = .001), and depressive symptoms (β = 0.07, p = .072). When childhood and adult SES disadvantage were in the same model, only adult SES predicted glucoregulation (odds ratio = 1.07, 95% confidence interval = 1.01-1.13). The SES disadvantage measures were no longer significantly associated with glucoregulation after including waist circumference, physical activity, and depressive symptoms, all of which were significant predictors of glucoregulation.
  
  
  CONCLUSIONS
  The consequences of childhood SES disadvantage are complex and include both critical period and pathway effects. The lack of a direct effect of childhood SES on glucoregulation does not negate the importance of early environment but suggests that early-life socioeconomic factors propel unequal life-course trajectories that ultimately influence health.
authors.affiliation: From the Center for Women's Health and Health Disparities Research (V.T.), University of Wisconsin-Madison, Madison, Wisconsin; Department of Sociology, (T.P.), University of Texas at Austin, Austin, Texas; and Department of Medicine (A.K.), UCLA, Los Angeles, California.
authors.forename: Vera
authors.initials: V
authors.lastname: Tsenkova
authors.forename: Tetyana
authors.initials: T
authors.lastname: Pudrovska
authors.forename: Arun
authors.initials: A
authors.lastname: Karlamangla
mesh_terms: D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000032:analysis; D002648:Child; D003863:Depression / Q000453:epidemiology; D003920:Diabetes Mellitus / Q000209:etiology*; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D011236:Prediabetic State / Q000209:etiology*; D011584:Psychology; D012189:Retrospective Studies; D012959:Socioeconomic Factors; D014481:United States; D035862:Vulnerable Populations / Q000706:statistics & numerical data*; D055105:Waist Circumference
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human