Internet access in Brazilian federative units related to epidemiological indices of breast and cervical cancer types in women

• Grant number: 19/11780-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: September 01, 2019
• End date: August 31, 2020
• Field of knowledge: Health Sciences - Collective Health - Preventive Medicine
• Principal Investigator: Francisco Winter dos Santos Figueiredo
• Grantee: Felipe Marsiglia Faustino Saporito
• Host Institution: Centro Universitário Saúde ABC. Fundação do ABC. Santo André , SP, Brazil

Abstract

Breast and cervical cancers have high incidence and when the diagnosis is early there is a higher chance of cure. Access to information is related to the demand for health services since the disease is not yet manifested. In Brazil, socioeconomic disparities are related to both these types of cancer and access to information through the Internet. Objective: to analyze the relationship between income inequality, Internet access and epidemiological indicators of cervical and breast cancer in women in the federative units of Brazil. Methods: An ecological Study with data from 2000 and 2010 referring to income inequality among women and epidemiological indicators of cervical and breast cancers in Brazilian federative units. Data will be collected from the following bases: Institute for Health Metrics and Evaluation; United Nations Development Programme; Brazilian Institute of Geography and Statistics; Department of Informatics of the unified Health system; Health System performance Evaluation project. The epidemiological indicators of breast and cervix cancers, income inequality among women, internet access and other variables related to risk factors, socioeconomic indicators and access to health services will be studied. To evaluate the adherence of quantitative data to normal distribution, the Shapiro-Wilk test will be used. Linear regression will be performed between the epidemiological indicators, Internet access and the indicators of income inequality for women, by the stepwise backward strategy to select the variables for the composition of the models.