Intra-urban spatial variability of breast and cervical cancer mortality in the city of São Paulo: analysis of associated factors

Abstract

Objective: To identify spatial variability of mortality from breast and cervical cancer and to assess factors associated in the city of São Paulo. Methods: Between 2009 and 2016, 10,124 deaths from breast cancer and 2,116 deaths from cervical cancer were recorded in the Mortality Information System among women aged 20 years and over. The records were geocoded by address of residence and grouped according to Primary Health Care coverage areas. A spatial regression modeling was put together using the Bayesian approach with a Besag-York-Mollié structure to verify the association of deaths with selected indicators. Results: Mortality rates from these types of cancer showed inverse spatial patterns. These variables were associated with breast cancer mortality: travel time between one and two hours to work (RR – relative risk: 0.97; 95%CI – credible interval: 0.93–1.00); women being the head of the household (RR 0.97; 95%CI 0.94–0.99) and deaths from breast cancer in private health institutions (RR 1.04; 95%CI 1.00–1.07). The following variables were associated with mortality from cervical cancer: travel time to work between half an hour and one hour (RR 0.92; 95%CI 0.87–0.98); per capita household income of up to 3 minimum wages (RR 1.27; 95%CI 1.18–1.37) and ratio of children under one year of age related to the female population aged 15 to 49 years (RR 1.09; 95%CI 1.01–1.18). Conclusion: The predicted RR for mortality from these cancers were calculated and associated with the socioeconomic conditions of the areas covered.

Health care accessibility and mobility in breast cancer: a Latin American perspective

“…Table 1 provides the main characteristics of each included study, an outline of the individual characteristics of each study population, and the context in which the impact of mobility was studied. Regarding mobility outcomes, 4 studies reported travel distance [ 6 , 7 , 18 , 19 ], 3 studies reported travel time [ 20 – 22 ], and 7 studies reported any effect measure such as mammograms not performed or effect on access to cancer screening [ 23 – 29 ]. To facilitate understanding of the results, the following sections are divided into the impact of mobility on BC screening and the impact of mobility on BC treatment.…”

“…Also in the Northeast of Brazil, de Sousa et al [ 18 ] demonstrated that, despite important data on geographic distance and time to treatment, treatment delay was not linked to geographic barriers but rather to a fragmentation of health services, that is, to a need to shift the points of care from primary to specialized care with a well-defined patient flow. Finally, Aguiar et al [ 22 ] reported that work commutes of 1 to 2 h were negatively associated with BC mortality in the city of São Paulo, Brazil, and that these findings were important to guide cancer prevention policies.…”

“…Table 2 provides the quantitative results of individual studies and the impact of mobility on the related oncological outcomes. Regarding quantitative data analysis, the heterogeneity was notably high (I 2 = 93%), and the number of studies that provided sufficient information for a meta-analysis was limited to 7, rendering the meta-analysis inadequate for reporting the primary outcome [ 6 , 7 , 19 , 20 , 22 , 26 ]. We performed an exploratory subgroup analysis to investigate the regions of Brazil where the studies had been conducted as a potential source of heterogeneity.…”

“…de Almeida et al [ 20 ] showed that women traveling to another city to receive BC care were more likely to have advanced disease at the time of diagnosis and that late diagnosis increases the cost of treatment and compromises the patient’s clinical outcome. Despite the ‘60-day law’ and health care policy initiatives in Brazil, there appears to be a gap between policy intentions and their actual implementation, particularly for patients living outside major urban centers [ 22 , 23 , 27 , 29 ]. Some studies have highlighted the underrepresentation of geographic barriers in patients’ perceptions, emphasizing the need for a nuanced contextual understanding.…”