Brittany McKinnon1, Sam Harper, Spencer Moore. 1. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Purvis Hall, Montreal, QC, H3A 1A2, Canada. brittany.mckinnon@mail.mcgill.ca
Abstract
OBJECTIVES: The development of successful policies to reduce income-related inequalities in cervical cancer screening rates requires an understanding of the reasons why low-income women are less likely to be screened. We sought to identify important determinants contributing to inequality in cervical screening rates. METHODS: We analyzed data from 92,541 women aged 25-64 years, who participated in the World Health Survey in 2002-2003. Income-related inequality in Pap screening was measured using the concentration index (CI). Using a decomposition method for the CI, we quantified the contribution to inequality of age, education level, marital status, urbanicity and recent health-care need. RESULTS: There was substantial heterogeneity in the contributions of different determinants to inequality among countries. Education generally made the largest contribution (median = 15%, interquartile range [IQR] = 23%), although this varied widely even within regions (e.g., 5% in Austria, 28% in Hungary). The contribution of rural residence was greatest in African countries (median = 10%, IQR = 13%); however, there was again substantial within-region variation (e.g., 26% in Zambia, 2% in Kenya). CONCLUSIONS: Considerable heterogeneity in the contributions of screening determinants among countries suggests interventions to reduce screening inequalities may require country-specific approaches.
OBJECTIVES: The development of successful policies to reduce income-related inequalities in cervical cancer screening rates requires an understanding of the reasons why low-income women are less likely to be screened. We sought to identify important determinants contributing to inequality in cervical screening rates. METHODS: We analyzed data from 92,541 women aged 25-64 years, who participated in the World Health Survey in 2002-2003. Income-related inequality in Pap screening was measured using the concentration index (CI). Using a decomposition method for the CI, we quantified the contribution to inequality of age, education level, marital status, urbanicity and recent health-care need. RESULTS: There was substantial heterogeneity in the contributions of different determinants to inequality among countries. Education generally made the largest contribution (median = 15%, interquartile range [IQR] = 23%), although this varied widely even within regions (e.g., 5% in Austria, 28% in Hungary). The contribution of rural residence was greatest in African countries (median = 10%, IQR = 13%); however, there was again substantial within-region variation (e.g., 26% in Zambia, 2% in Kenya). CONCLUSIONS: Considerable heterogeneity in the contributions of screening determinants among countries suggests interventions to reduce screening inequalities may require country-specific approaches.
Authors: Patama Vapattanawong; Margaret C Hogan; Piya Hanvoravongchai; Emmanuela Gakidou; Theo Vos; Alan D Lopez; Stephen S Lim Journal: Lancet Date: 2007-03-10 Impact factor: 79.321