Understanding Geospatial Factors Associated With Cervical Cancer Screening Uptake in Amazonian Peruvian Women

Abstract

Purpose: Cervical cancer (CC) is the most common and second-most deadly cancer among Peruvian women. Access to services is strongly associated with CC screening uptake. This study investigated geospatial features contributing to utilization of screening. We used geolocated data and screening information from a Knowledge, Attitudes, and Practice (KAP) survey implemented in Iquitos, Peru in 2017.

Materials and methods: The KAP collected cross-sectional CC screening history from 619 female interviewees age 18-65 years within 5 communities of varying urbanization levels. We used spatial statistics to determine if screened households tended to cluster together or cluster around facilities offering screening in greater numbers than expected, given the underlying population density.

Results: On the basis of K-functions, screened households displayed greater clustering among each other as compared with clustering among unscreened households. Neighborhood-level factors, such as outreach, communication, or socioeconomic condition, may be functioning to generate pockets of screened households. Cross K-functions showed that screened households are generally located closer to health facilities than unscreened households. The significance of facility access is apparent and demonstrates that travel and time barriers to seeking health services must be addressed.

Conclusion: This study highlights the importance of considering geospatial features when determining factors associated with CC screening uptake. Given the observed clustering of screened households, neighborhood-level dynamics should be further studied to understand how they may be influencing screening rates. In addition, results demonstrate that accessibility issues must be carefully considered when designing an effective cancer screening program that includes screening, follow-up, and treatment.

FIG 1

Locations of the 5 Iquitos communities selected for study. America and Progreso are urban communities, Santo Tomas is peri-urban, and Paujil and Varillal are rural.

FIG 2

Difference in K-functions between screened and unscreened households, and difference in cross K-functions between screened households and the health facility, and unscreened households and the health facility within the 5 Iquitos communities. Ninety-five percent significance boundaries were obtained through Monte Carlo random labeling. (A) America, K difference. (B) America, cross K difference. (C) Paujil, K difference. (D) Paujil, cross K difference. (E) Progreso, K difference. (F) Progreso, cross K difference. (G) Santo Tomas, K difference. (H) Varillal, K difference. (I) Varillal, cross K difference. Results for Santo Tomas, cross K difference not presented, as the interviewed Santo Tomas households were too far removed from the health facility to allow for meaningful analyses.