Newton001-Developing tools to study inequalities in women's access to breast and cervical cancer control activities in Brazil using health-related DB

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Brazil, like many other low and middle-income countries (LMICs), is undergoing a cancer transition whereby cancers with an infection-related aetiology are being surpassed by those with a non-communicable origin. This transition is particularly evident among women, with breast cancer (BC) having now surpassed cervical cancer (CC) as the most common female cancer in Brazil (estimated number of incident cases in 2012: ~67,000 BC vs. ~18,000 CC). The Sistema Único de Saude (SUS) was established by the Brazilian government in 1988 to provide universal free access to health care. In 1999-2002 guidelines were issued for women aged 25-59 years to undergo a gynaecological examination every 3 years, and in 2004 for mammographic screening every two years of those aged 50-64, with information systems established to manage these screening activities. SISCOLO, implemented in 1999, records information on all Pap smear requests whereas SISMAMA, established in 2009, records data on all mammograms. Despite the success of these programs, and the lower BC incidence in Brazil than in the UK (59.5/100,000 vs. 95/100,000 in 2012), BC mortality is similar (14.3/100,000 vs. 17.1/100,000, respectively) and both CC incidence and mortality remain much higher in Brazil (16.3/100,000 and 7.3/100,000, respectively) than in the UK (7.1/100,000 and 1.8/100,000, respectively). Such disproportionately higher mortality rates are likely to be related to low coverage of the population targeted by screening and late presentation. It is the aim of this Research Partnership to investigate whether this is the case, in the first instance, by creating the tools necessary to study access to early diagnosis and treatment for the two most common female cancers - BC and CC. In particular we will:1. Gain access to, and link, at a national level, SISMAMA and SISCOLO national data to Censuses, hospital and mortality records, socioeconomic surveys, and Bolsa Familia.2. Develop a multi-disciplinary conceptual framework to identify demand (e.g. socio-economic status, belief system) and supply determinants (e.g. services availability) of inequalities in health care using such comprehensive data linkage.3. Strengthen analytic capacity to deal with the methodological challenges raised by interrogating large routinely-collected datasets. These include addressing potential sources of bias affecting the linked data and the adoption of appropriate statistical methodology for examining pathways to inequalities in health care.