Predicting Patterns of Mammography Use: A Geographic Perspective on National Needs for Intervention Research

Legler, Julie M.; Breen, Nancy; Meissner, Helen I.; Malec, Don; Coyne, Cathy A.

doi:10.1034/j.1600-0560.2002.59.x

Cited by 20 publications

(20 citation statements)

References 25 publications

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“…These findings support the need for ongoing efforts to strengthen and develop the healthcare infrastructures in communities considered to be underserved and outside of major urban cities. For example, as indicated by Legler et al, 44 the use of mobile mammogram vans may help increase screening rates in HPSAs.…”

Section: Discussionmentioning

confidence: 99%

“…3 Despite the known benefits of annual or biannual screening mammography beginning at age 40 or 50, 4 approximately 25%-50% of American women report not having a mammogram in the past 2 years. 4,5 High variation in average rates of screening mammography adherence can be attributed to the lack of consensus about the efficacy of screening for women aged [40][41][42][43][44][45][46][47][48][49], variation in availability of screening facilities, and other factors that may disproportionately impact those residing in communities with fewer healthcare resources. 6 Elting et al 7 documented that mammography facilities were available in only 49% of Texas counties.…”

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confidence: 99%

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Utilization of Screening Mammography Among Middle-Aged and Older Women

Smith

Hochhalter²,

Ahn³

et al. 2011

Journal of Women's Health

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Aims: This study examines patterns of screening mammogram use, investigating the relationship of screening with demographic, health status, and healthcare factors. Methods: Data from 1242 women aged ‡ 41 were obtained from a random sample of mailed surveys to community households in an eight-county region in Central Texas in 2010. The dependent variable was the timing of the participants' most recent screening mammography (in the past 12 months, between 1 and 2 years, or > 2 years). Predictor variables included demographic, health status, and healthcare access factors. Multinomial logistic regression identified variables associated with screening mammography practices. Results: The majority of women reported having at least one mammogram during their lifetime (93.0%) and having a mammography within the past 2 years (76.2%). Participants who reported not having a routine checkup in the past 12 months (odds ratio [OR] 0.12, p < 0.001), having a lapse of insurance in the past 3 years (OR 2.95, p < 0.05), and living in a health provider shortage area (OR 1.42, p < 0.05) were less likely to be screened within the past 2 years. Conclusions: Routine healthcare plays a major role in preventive screening, which indicates screening mammography practices can be enhanced by improving participation in routine checkups with medical providers, continuity of insurance coverage, and women's access to healthcare. Interventions to encourage screening mammography may be particularly needed for women who have experienced a lapse in insurance or have not had a checkup in the past year.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Utilization of Screening Mammography Among Middle-Aged and Older Women

Smith

Hochhalter²,

Ahn³

et al. 2011

Journal of Women's Health

View full text Add to dashboard Cite

show abstract

“…Some studies have found that socioeconomic variables affect health outcomes independently at both the neighborhood and the individual levels [38,39]. We therefore considered several variables from the 2000 Census for our study that have been shown previously to have independent association with mammography use [11,28,29]. Those included percentage of adults with HS diploma, percentage of persons in rural area, percentage of persons in suburban area, mammography facility located in a census tract, median family income, percentage of white collar workers, and median home values measured at the census tract level.…”

Section: Data Sets and Linkagementioning

confidence: 99%

“…Geographic accessibility to mammography facilities is an important contextual factor for mammography screening [11]. Only recently, with the advent of more local data, larger sample sizes, and the development of spatial analysis techniques, has it been possible to study geographic accessibility to cancer screening [12].…”

Section: Introductionmentioning

confidence: 99%

Impact of geography on mammography use in California

Jackson

Davis

Waldron

et al. 2009

Cancer Causes Control

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“…Although successful strategies to increase cancer screening among underutilizing populations have recently been reported, there has been unevenness in the targeting of intervention research, resulting in gaps in coverage. These gaps are evident geographically, which may warrant further investigation of the need for tailoring intervention research as well (Legler et al 2002). …”

Section: The Need For Small-area Estimatesmentioning

confidence: 99%

Combining Information From Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening

Raghunathan

Xie

Schenker

et al. 2007

Journal of the American Statistical Association

109

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Cancer surveillance requires estimates of the prevalence of cancer risk factors and screening for small areas such as counties. Two popular data sources are the Behavioral Risk Factor Surveillance System (BRFSS), a telephone survey conducted by state agencies, and the National Health Interview Survey (NHIS), an area probability sample survey conducted through face-to-face interviews. Both data sources have advantages and disadvantages. The BRFSS is a larger survey, and almost every county is included in the survey; but it has lower response rates as is typical with telephone surveys, and it does not include subjects who live in households with no telephones. On the other hand, the NHIS is a smaller survey, with the majority of counties not included; but it includes both telephone and non-telephone households and has higher response rates. A preliminary analysis shows that the distributions of cancer screening and risk factors are different for telephone and non-telephone households. Thus, information from the two surveys may be combined to address both nonresponse and noncoverage errors. A hierarchical Bayesian approach that combines information from both surveys is used to construct county-level estimates. The proposed model incorporates potential noncoverage and nonresponse biases in the BRFSS as well as complex sample design features of both surveys. A Markov Chain Monte Carlo method is used to simulate draws from the joint posterior distribution of unknown quantities in the model based on the design-based direct estimates and county-level covariates. Yearly prevalence estimates at the county level for 49 states, as well as for the entire state of Alaska and the District of Columbia, are developed for six outcomes using BRFSS and NHIS data from the years 1997-2000. The outcomes include smoking and use of common cancer screening procedures. The NHIS/BRFSS combined county-level estimates are substantially different from those based on BRFSS alone. Combining Information from Two Surveys to Estimate AbstractCancer surveillance research requires estimates of the prevalence of cancer risk factors and screening for small areas such as counties. Two popular data sources are the Behavioral Risk Factor Surveillance System (BRFSS), a telephone survey conducted by state agencies, and the National Health Interview Survey (NHIS), an area probability sample survey conducted through face-to-face interviews. Both data sources have advantages and disadvantages. The BRFSS is a larger survey, and almost every county is included in the survey; but it has lower response rates as is typical with with telephone surveys, and it does not include subjects who live in households with no telephones.On the other hand, the NHIS is a smaller survey, with the majority of counties not included; but it includes both telephone and non-telephone households and has higher response rates. A preliminary analysis shows that the distributions of cancer screening and risk factors are different for telephone and non-telephone households. Thus,...

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Predicting Patterns of Mammography Use: A Geographic Perspective on National Needs for Intervention Research

Cited by 20 publications

References 25 publications

Utilization of Screening Mammography Among Middle-Aged and Older Women

Utilization of Screening Mammography Among Middle-Aged and Older Women

Impact of geography on mammography use in California

Combining Information From Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening

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