H Budhwani1, P De2. 1. University of Alabama at Birmingham, Department of Health Care Organization and Policy and African American Studies, 517D Ryals Public Health Building, 1665 University Boulevard, Birmingham, AL, 35294, USA. Electronic address: budhwani@uab.edu. 2. Department of Economics and Business, The Colin Powell School for Civic and Global Leadership, The City College of City University of New York, 160 Convent Avenue, New York, NY 10031, USA. Electronic address: pde@ccny.cuny.edu.
Abstract
OBJECTIVE: The aim of this study is to examine the effects of ethnicity, disaggregating Asian Indian from other Asians, health insurance coverage, and nativity on influenza vaccination rates in the United States. STUDY DESIGN: National Health Interview Survey data (2013), collected by the National Center for Health Statistics, were analysed. METHODS: Multivariable regression models were used to compute estimates and 95% confidence intervals. RESULTS: Asian Indians had higher proportions of college graduate rates (mean = 0.85; CI = [0.80, 0.90]) and above-average income (mean = 0.56, CI = [0.48, 0.64]) than both Whites (mean = 0.406; CI = [0.39, 0.42]) and other Asian sub-groups, such as Chinese (mean = 0.544; CI = [0.47, 0.62]) and Filipino Americans (mean = 0.419; CI = [0.35, 0.48]). However, this higher socio-economic status did not uniformly translated into higher vaccine uptake rates. Asian Indian influenza vaccine uptake rate (mean = 0.403; CI = [0.33, 0.47]), while higher than Whites (mean = 0.366; CI = [0.36, 0.38]), were lower than Chinese (mean = 0.435; CI = [0.35, 0.52]) and Filipino Americans (mean = 0.431; CI = [0.37. 0.49]). In regression models, although Asian Indians were significantly more likely to receive the influenza vaccine than White Americans before controlling for health insurance status (OR = 1.38; CI = [1.004, 1.899]), when coverage was included, effects of race and ethnicity were eliminated (OR = 1.24; CI = [0.897, 1.705]). CONCLUSION: Health disparities research often analyses Asians as a homogenous mass; however, the availability of disaggregated data allows researchers to parse effects leading to nuanced findings which highlight behavioural diversity within groups. Findings may inform the development of targeted interventions by public health practitioners and adjustments to polices designed to improve health insurance coverage in racial and ethnic minorities, regardless of citizenship status, leading to enhanced population health.
OBJECTIVE: The aim of this study is to examine the effects of ethnicity, disaggregating Asian Indian from other Asians, health insurance coverage, and nativity on influenza vaccination rates in the United States. STUDY DESIGN: National Health Interview Survey data (2013), collected by the National Center for Health Statistics, were analysed. METHODS: Multivariable regression models were used to compute estimates and 95% confidence intervals. RESULTS: Asian Indians had higher proportions of college graduate rates (mean = 0.85; CI = [0.80, 0.90]) and above-average income (mean = 0.56, CI = [0.48, 0.64]) than both Whites (mean = 0.406; CI = [0.39, 0.42]) and other Asian sub-groups, such as Chinese (mean = 0.544; CI = [0.47, 0.62]) and Filipino Americans (mean = 0.419; CI = [0.35, 0.48]). However, this higher socio-economic status did not uniformly translated into higher vaccine uptake rates. Asian Indian influenza vaccine uptake rate (mean = 0.403; CI = [0.33, 0.47]), while higher than Whites (mean = 0.366; CI = [0.36, 0.38]), were lower than Chinese (mean = 0.435; CI = [0.35, 0.52]) and Filipino Americans (mean = 0.431; CI = [0.37. 0.49]). In regression models, although Asian Indians were significantly more likely to receive the influenza vaccine than White Americans before controlling for health insurance status (OR = 1.38; CI = [1.004, 1.899]), when coverage was included, effects of race and ethnicity were eliminated (OR = 1.24; CI = [0.897, 1.705]). CONCLUSION: Health disparities research often analyses Asians as a homogenous mass; however, the availability of disaggregated data allows researchers to parse effects leading to nuanced findings which highlight behavioural diversity within groups. Findings may inform the development of targeted interventions by public health practitioners and adjustments to polices designed to improve health insurance coverage in racial and ethnic minorities, regardless of citizenship status, leading to enhanced population health.
Authors: Olivia R Orta; Elizabeth E Hatch; Annette K Regan; Rebecca Perkins; Amelia K Wesselink; Sydney K Willis; Ellen M Mikkelsen; Kenneth J Rothman; Lauren A Wise Journal: Vaccine Date: 2020-05-11 Impact factor: 3.641
Authors: Chelsea K Ayers; Karli K Kondo; Beth E Williams; Devan Kansagara; Shailesh M Advani; Mia Smith; Sarah Young; Somnath Saha Journal: J Gen Intern Med Date: 2021-03-31 Impact factor: 5.128