BACKGROUND: Low socioeconomic status and high levels of body mass are two risk factors for elevated C-reactive protein, a biomeasure signifying inflammation. Though past research identifies the additive effect of these particular risk factors, this study examines their interactive effects to uncover whether body mass index exacerbates or levels the detrimental consequences of occupying a disadvantaged social position. METHODS: This study employs a representative survey of American adults, aged 57-84 years, using self-reported and laboratory measures. Additive and multiplicative linear regression models are used to analyze logged C-reactive protein levels (mg/l) drawn from assayed blood samples. RESULTS: Significant negative interactions were observed between body mass index and two indicators of low socioeconomic status on C-reactive protein, reflecting a cross-over effect. CONCLUSIONS: The results demonstrated the importance of a multiplicative model for studying risk factor accumulation and identify low socioeconomic status as an early and primary risk factor for elevated C-reactive protein.
BACKGROUND: Low socioeconomic status and high levels of body mass are two risk factors for elevated C-reactive protein, a biomeasure signifying inflammation. Though past research identifies the additive effect of these particular risk factors, this study examines their interactive effects to uncover whether body mass index exacerbates or levels the detrimental consequences of occupying a disadvantaged social position. METHODS: This study employs a representative survey of American adults, aged 57-84 years, using self-reported and laboratory measures. Additive and multiplicative linear regression models are used to analyze logged C-reactive protein levels (mg/l) drawn from assayed blood samples. RESULTS: Significant negative interactions were observed between body mass index and two indicators of low socioeconomic status on C-reactive protein, reflecting a cross-over effect. CONCLUSIONS: The results demonstrated the importance of a multiplicative model for studying risk factor accumulation and identify low socioeconomic status as an early and primary risk factor for elevated C-reactive protein.
Authors: Fen Wu; Farzana Jasmine; Muhammad G Kibriya; Mengling Liu; Oktawia Wójcik; Faruque Parvez; Ronald Rahaman; Shantanu Roy; Rachelle Paul-Brutus; Stephanie Segers; Vesna Slavkovich; Tariqul Islam; Diane Levy; Jacob L Mey; Alexander van Geen; Joseph H Graziano; Habibul Ahsan; Yu Chen Journal: Am J Epidemiol Date: 2012-04-24 Impact factor: 4.897
Authors: Joe Verghese; Roee Holtzer; Mooyeon Oh-Park; Carol A Derby; Richard B Lipton; Cuiling Wang Journal: J Gerontol A Biol Sci Med Sci Date: 2011-06-30 Impact factor: 6.053
Authors: Stephanie T Broyles; Amanda E Staiano; Kathryn T Drazba; Alok K Gupta; Melinda Sothern; Peter T Katzmarzyk Journal: PLoS One Date: 2012-09-25 Impact factor: 3.240