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Capturing Health Inequities: An Intersectional Examination of the Ukrainian Population

Gender
Women
Methods
Olena Hankivsky
Simon Fraser University
Olena Hankivsky
Simon Fraser University

Abstract

On a global scale, health inequities are persistent, growing, and deadly (Beckfield & Krieger, 2009; Marmot, 2007; Wibulpolprasert et al., 2008). This situation is especially true for Ukraine, a country in transition, which is experiencing an internationally recognized health crisis (CIDA, 2009; Cockerham et al., 2006; Hankivsky & Salnykova, 2012; Tarantino et al., 2011; World Bank, 2009). As with all former Soviet states, slow socio-economic progress, coupled with deteriorating social security and political instability, has contributed to high morbidity, lower life expectancy, and growing health inequities within the population, the magnitude of which is only starting to be recognized. For example, over 25% of the adult Ukrainian population between the ages of 18 and 65 years has a chronic disease or condition (Lekhan et al., 2010). The average life expectancy at birth is 9.1 years lower than in the European Union (World Bank, 2009). According to Euromonitor International (2012), Ukraine is projected to experience the single largest absolute population loss in Europe between 2011 and 2020. The human and economic costs of such a crisis for individuals, their families, and the nation are significant. However, according to the World Bank, about 50% of deaths under the age of 75 could be prevented with adequate prevention and treatment interventions (World Bank 2009, p.9). At first glance, the health inequities created by the crisis in Ukraine appear to be gendered because of the 10-year mortality gap between men and women (Lekhan et al., 2010). While gender is an important determinant of health, the way it intersects with other factors, such as income and social status, education and literacy, culture, social and physical environments, personal health practices and coping skills, creates varied experiences and health statuses across populations. For example, Ukraine is a multiethnic country with more than 110 nationalities and ethnic groups, and issues of ethnic and linguistic diversity have become very serious concerns (Kolisnichenko & Rosenbaum, 2009, p.937). Every third citizen in Ukraine lives in a rural area, and there still exists an evident urban-rural divide (ETF, 2005), especially in terms of accessing and affording health care (Lekhan et al., 2010). Over one-third of the population lives in poverty (CIA, 2010). An aging population is also an issue of growing concern (Lisinkova, 2009). Further, it is estimated that nearly 6% of the population is disabled, although by many accounts, this may be an underestimate (Phillips, 2011). In order to effectively curb the growth of health inequities, the diversity in and among Ukrainian females and males has to be addressed (Hankivsky, 2012a). Health policy needs to account for the associations among gender and other factors of importance in the Ukrainian context - namely age, employment status, region, and ethnicity. Successful interventions also require policies that are feasible within the Ukrainian context, taking into account the history, politics, economics, and culture of the country. This paper will present the findings of a three year mixed methods research project that used an intersectionality framework, to interrogate the differential effects and experiences of the health crisis in Ukraine. Specifically, the focus will be on the results of a secondary analysis of an Omnibus Survey (nationally representative survey that included specifically designed health and health –related questions) and the results of national community consultations with over 1000 citizens of Ukraine, in all regions and in both rural and urban settings. The overall challenges of applying intersectionality to both quantitative and qualitative data collection and analysis will be explored. Significantly, specific attention will be paid to discussing the strategies for overcoming data limitations and combining different data sets, while still trying to be as consistent as possible with an intersectionality perspective.