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Origins of the “flame within”: Social and Physical Correlates of Inflammation in U.S. Children. Jennifer Beam Dowd, Hunter College, CUNY Institute for Demographic Research (CIDR) Anna Zajacova, Allison Aiello, Center for Social Epidemiology and Population Health, University of Michigan.
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Origins of the “flame within”: Social and Physical Correlates of Inflammation in U.S. Children. Jennifer Beam Dowd, Hunter College, CUNY Institute for Demographic Research (CIDR) Anna Zajacova, Allison Aiello, Center for Social Epidemiology and Population Health, University of Michigan
Background and Motivation • Disparities in health by SES in the U.S. begin in childhood (Case, Lubotsky, Paxson 2002) • Biological pathways linking SES to health, especially in children, are not clear. • Early environments can shape developing physiological systems (critical and sensitive periods) Background Data/Methods Results Conclusions
Inflammation: • Integral part of the human stress and immune response • Pro-inflammatory cytokines regulate the production of acute-phase proteins such as C-reactive protein (CRP) which fight infection and promote repair of damaged issues. • Little is known about the predictors of low-grade inflammation in children Background Data/Methods Results Conclusion
Contributors to inflammation • Independent predictors of increased inflammation in adults: • Higher BMI (inflammatory cytokines expressed in adipose tissue) • Smoking • Poor sleep quality/short sleep • Diet high in saturated and trans fat • Chronic Infections Background Data/Methods Results Conclusion
Health Consequences of Inflammation • Elevated CRP is associated with risk of: • myocardial infarction, stroke, atherosclerosis • insulin resistance, Type II diabetes • vascular dementia, Alzheimer’s disease. • Life-long inflammatory burden may shape later life patterns of aging and mortality. (Crimmins and Finch 2006). Background Data/Methods Results Conclusion
“Inflamm-aging” • Chronic immune activation, including a persistent inflammatory status, may drive what we considered “age” related declines in functioning and immune response– • Thus large differences across groups (race/ethnicity/SES) in burden of inflammation could play a role in observed differences in aging rates and longevity. Background Data/Methods Results Conclusion
Previous Work • Lower SES associated with higher CRP in U.S. adults • Mixed results for race/ethnicity-some studies show highest levels for blacks, some for Hispanics • European studies have not found social inequalities in CRP in childhood, differences emerge later. • To our knowledge, no existing studies looking at CRP disparities in U.S. children Background Data/Methods Results Conclusion
Primary Research Questions • Are physical (infections, BMI, etc) and social (family income, race/ethnicity) risk factors associated with inflammation in U.S. children? • Do physical risk factors mediate the relationship between social factors and levels of inflammation in U.S. children? Background Data/Methods Results Conclusion
Secondary Question • Hygiene hypothesis: Mixed evidence on whether higher infectious burden in childhood promotes better or worse regulation of inflammation later in life— • Are chronic infections related to inflammation in U.S. children? Are proxy measures of pathogen exposure related to inflammation in U.S. children? Background Data/Methods Results Conclusion
Data • National Health and Nutrition Examination Survey (NHANES), 1999-2004 • Cross-sectional, representative sample of non-institutionalized U.S. population • Face-to-face interview, medical exam, collection of blood and urine • Our sample consists of children aged 3-17, N= 6338 BackgroundData/Methods Results Conclusion
Measures: Outcome High Sensitivity C-reactive Protein (CRP) mg/L: Distribution is right-skewed, transformed to Ln(CRP) BackgroundData/Methods Results Conclusion
Measures: Physical Predictors • Infections: Positive Serostatus for Cytomegalovirus (CMV) Herpes Simplex Virus Type 1 (HSV-1) Helicobacter Pylori (H Pylori) Cryptosporidium Toxoplasmosis Hepatitis A Virus (HAV) • Infectious Burden (Factor Score) BackgroundData/Methods Results Conclusion
Measures: Physical Predictors • Body Mass Index (BMI) (kg/m2) • Illness in the last 30 days (0/1) • Low birth weight (0/1) • Mother Smoked during pregnancy (0/1) • Currently a smoker in the Household (0/1) • Cotinine (log transformed) • Triclosan (log transformed, N=557) • White Blood Cell Count • Vitamin D (log transformed) BackgroundData/Methods Results Conclusion
Measures: Social Predictors Age (continuous) Sex Foreign Born (0/1) Household size (continuous) Race/ethnicity (White/Black/Mexican-American) SES: • Poverty-Income Ratio (Ratio of Family Income to Poverty Line) • Years of Education of the Household Reference Person BackgroundData/Methods Results Conclusion
Methods • OLS Regressions: Ln(CRP)= α + β1(Social) +β2(Physical) + ε • Infection burden score created with M-Plus, confirmatory factor analysis with full-information maximum likelihood estimation • All analyses conducted with STATA 10.0 SVY commands to account for complex survey design BackgroundData/Methods Results Conclusion
Conclusions • BMI and current/recent illness are strong predictors of CRP in U.S. children • Differences in CRP levels by income largely accounted for by BMI and recent illness. • Higher levels for Mexican-American race/ethnicity not explained by physical vars.
Conclusions • Hygiene Hypothesis: Still a mystery • --Pro: increased HH size associated with lower CRP, Being foreign-born associated with lower CRP • --Cons: infection coefficients all reflect positive effects on CRP, foreign-born effect explained by BMI, Triclosan coefficient negative
Conclusions/Next Steps • Higher BMI and potentially more frequent acute infections contribute to greater levels of low-grade inflammation among U.S. children with lower family income. • What explains higher levels for Mexican-American children? • Potential life-course health implications: aging, CVD, cognition and learning?
Acknowledgements • Thanks to collaborators Anna Zajacova and Allison Aiello, Research assistance from Megan Todd • Support from the NIH: 1R21NR011181-01