Evidence map›Paper›PMID 20302614›Full record

ArticleBMC public health2010

Breast and cervical cancer screening among women in metropolitan areas of the United States by county-level commuting time to work and use of public transportation, 2004 and 2006.

Steven S Coughlin, Jessica King

Abstract read
In one paragraph

Article in BMC public health, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Predictors and Trend in Attendance for Breast Cancer Screening in Lithuania, 2006-2014.International journal of environmental research and public health · 2019
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. The relationship between four health-related quality-of-life indicators and use of mammography and Pap test screening in US women.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2015
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Area-level Socioeconomic Inequalities in the Use of Mammography Screening: A Multilevel Analysis of the Health of Houston Survey.Women's health issues : official publication of the Jacobs Institute of Women's Health
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Steven S CoughlinDivision of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA, USA. steven.coughlin@va.gov
Jessica King

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommuting times and behaviors have been associated with a variety of chronic disease outcomes and health behaviors. We examined the relationships between ecologic measures of commuting time and use of public transportation in relation to breast and cervical cancer screening among women in U.S. metropolitan areas who participated in the 2004 and 2006 Behavioral Risk Factor Surveillance System (BRFSS) surveys.

methodsSelf-reported county of residence was used to classify respondents as residents of metropolitan statistical areas (MSAs). Only BRFSS respondents who resided in the 39 MSAs with a population of > or = 1.5 million in 2007--representing a total of 337 counties--were included in this analysis. A total of 76,453 women aged > or = 40 years were included in analyses on mammography. Analyses on Pap testing were limited to women aged > or =18 years with no history of hysterectomy (n = 80,959). Area-based measures of socio-economic status (SES) were obtained by utilizing county-level information from the 2000 U.S. Census.

resultsWith adjustment for age, no important associations were observed between receipt of a recent mammogram and either a county-level measure of commute time or residence in an area where more residents had access to a car. Similarly, women living in counties where at least four percent of the residents used public transportation were as likely to have had a recent mammogram or Pap test compared with women in areas where less than four percent of residents used public transportation. However, women living in counties where < 2% of residents had no access to a car were somewhat more likely to have had a Pap test in the past 3 years than women in areas where > or = 3% of the residents had no access to a car (87.3% versus 84.5%; p-value for test for trend < 0.01). In multivariate analysis, living in a county with a median commute time of at least 30 minutes was not significantly associated with having had a Pap test in the past 3 years (adjusted odds ratio (OR) = 1.1, 95% CI 0.9-1.2, p = .50), or with having had a mammogram in the past 2 years (adjusted OR = 0.9, 95% CI 0.9-1.1, p = .28). A weak positive association was observed between residence in a county with less use of public transportation and having had a Pap test in the past 3 years, which was of borderline significance (adjusted OR 1.2, 95% CI 1.0-1.4, p = .05).

conclusionsIn large U.S. metropolitan areas, transportation issues may play a role in whether a woman obtains cancer screening along with other factors (e.g., Hispanic ethnicity, low income, and no physician visit in the past year). In this contextual analysis, a longer commute time was not associated with breast and cervical cancer screening.

Indexed as

Health Services AccessibilityAdultAgedBehavioral Risk Factor Surveillance SystemBreast NeoplasmsContinuity of Patient CareEarly Detection of CancerFemaleHealth BehaviorHumansInsurance CoverageMammographyMiddle AgedMultivariate AnalysisSocioeconomic FactorsTime Factors

Identifiers

PMID20302614
PMCPMC2848633

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.