Severity: Warning
Message: file_get_contents(https://...@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f08&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456312 | PMC |
http://dx.doi.org/10.1200/GO.20.00096 | DOI Listing |
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