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The American Journal of Managed Care March 2013
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Multilevel Predictors of Colorectal Cancer Screening Use in California
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Multilevel Predictors of Colorectal Cancer Screening Use in California

Salma Shariff-Marco, PhD, MPH; Nancy Breen, PhD; David G. Stinchcomb, MS, MA; and Carrie N. Klabunde, PhD
We studied contextual factors and found that locality, availability of primary care, and HMO membership influenced use of colorectal cancer screening in California.
Background: Screening can detect colorectal cancer (CRC) early, yet its uptake needs to be improved. Social determinants of health (SDOH) may be linked to CRC screening use but are not well understood.

Objectives: To examine geographic variation in CRC screening and the extent to which multilevel SDOH explain its use in California, the most populous and racially/ethnically diverse state in the United States.

Study Design: Analysis of individual and neighborhood data on 20,626 adult respondents aged >50 years from the 2005 California Health Interview Survey.

Methods: We used multilevel logistic regression models to estimate the effects of individual characteristics and area-level segregation, socioeconomic status (SES), and healthcare resources at 2 different geographic levels on CRC screening use.

Results: We confirmed that individual-level factors (eg, race/ethnicity, income, insurance) were strong predictors and found that area-level healthcare resources were associated with CRC screening. Primary care shortage in the Medical Service Study Area was associated with CRC screening for any modality (odds ratio [OR] = 0.89; 95% confidence interval [CI], 0.80-1.00). County-level HMO penetration (OR = 1.85; 95% CI, 1.47-2.33) and primary care shortage (OR = 0.73; 95% CI, 0.53-0.99) were associated with CRC screening with flexible sigmoidoscopy.

Conclusions: Contextual factors including locality, primary care resources, and HMO membership are important determinants of CRC screening uptake; SES and segregation did not explain variation in screening behavior. More studies of contextual factors and varying geographic scales are needed to further elucidate their impact on CRC screening uptake.

Am J Manag Care. 2013;19(3):205-216
We studied contextual factors and found that locality, availability of primary care, and HMO membership influenced use of colorectal cancer (CRC) screening in California.

  • Medical Service Study Areas are useful geographic units for understanding CRC screening use in California.

  • There was less use of screening by flexible sigmoidoscopy in counties with a shortage of primary care resources and low HMO penetration.

  • Multilevel analyses offer a more complete picture of CRC screening use and the opportunity to prioritize interventions for appropriate subgroups and geographic areas.
Colorectal cancer (CRC), the second-leading cause of cancer death in the United States, resulted in an estimated 51,370 deaths in the United States in 2010.1 Screening reduces CRC burden by identifying early-stage disease and/or removing precancerous polyps.2-4 Although CRC mortality rates could be reduced by as much as 50% with complete adherence to screening guidelines, only one-half of United States adults 50 years and older report being up-todate with CRC screening.2,5 Evidence-based guidelines for screening individuals at average risk for CRC recommend annual fecal occult blood testing (FOBT), flexible sigmoidoscopy (FSIG) every 5 years, or colonoscopy every 10 years.4

Use of CRC screening has been shown to vary by individual race/ethnicity, sex, education, income, marital status, insurance coverage, and immigration status.2,6-16 Other individual characteristics associated with CRC screening uptake include perceived risk, intention for future screening, information-seeking patterns, perceived medical discrimination, life stressors, social support, and healthcare context.2,6,14,16-21 Of these, having higher education, having higher income, being married, having health insurance and a usual source of care, seeing a physician, receiving a recommendation from a physician to obtain screening, not reporting medical discrimination experiences, and perceiving oneself to be at risk for CRC are most consistently associated with increased CRC screening use.

A few prior studies have assessed how contextual factors influence access to CRC screening.18,22-25 Prior multilevel analyses26-28 used poverty rates or rural/urban status as proxy measures of fundamental factors and environmental resources available to communities and the individuals within those communities,29,30 but findings are not consistent. One recent study examined deprivation and general practitioner density per 100,000 residents, and showed that only the deprivation index was associated with CRC screening use.31

To more closely examine which contextual factors might influence CRC screening use, we drew on the World Health Organization social determinants of health framework. This framework underscores the importance of the contexts in which individuals live, work, socialize, and access healthcare for health behaviors and outcomes.32 The World Health Organization framework matched our broad conceptualization of social determinants of health because, unlike most other social determinants of health frameworks, it includes healthcare access. Social determinants of health can shape the opportunities and resources that affect health-related behaviors of individuals, including participation in cancer screening.9,32,33 Healthcare resources can be conceptualized both at the area level as the local supply of healthcare services and also at the individual level as a measure of insurance or a usual source of care. We used a multilevel framework to study the influences of socioeconomic status (SES), racism, and healthcare resources on CRC screening uptake at individual and area levels with population-based data from the California Health Interview Survey (CHIS). We selected data from California, the largest and most racially/ethnically diverse state in the United States with a large HMO market share that varies by geography. In 1994, California’s dominant HMO, Kaiser Permanente, initiated organized CRC screening using FSIG and FOBT and in 2004, using fecal immunochemical tests.34,35 Other HMOs also implemented interventions to increase use of CRC screening during this time.36,37


We studied CRC screening use among California residents nested within Medical Service Study Areas (MSSAs) and counties, 2 geographic levels important for healthcare resource delivery in California. Medical Service Study Areas are subcity and subcounty administrative areas identifying “rational service areas” for a variety of healthcare resources and medically underserved designations.38 California designates health professional shortage areas at both MSSA and county levels. The California Department of Health and Human Services organizes its health services delivery (eg, Medi-Cal, Child Health and Disability Prevention Program, cancer screenings) at the county level.

Study Sample and Individual-Level Data

Individual-level data were obtained from the 2005 CHIS adult component, a random-digit dial telephone survey of 43,020 adults conducted in English, Spanish, Mandarin, Cantonese, Vietnamese, and Korean.39 The overall response rate was 29.5% for households and 26.9% for adults. The CHIS response rates are comparable to other telephone-administered population surveys, including the California Behavioral Risk Factor Surveillance System.39 More detailed information on CHIS is available at Our study sample included 20,626 adults. We excluded respondents younger than 50 years (n = 21,014), older than 84 years (n = 1016), with a prior CRC diagnosis (n = 329), or with a proxy interview (n = 141). Sample size for FSIG analyses varied due to skip patterns and resulting missing responses. The MSSA and county data were linked to CHIS respondents using census tract and county variables.

Colorectal Cancer Screening. To evaluate whether individuals were up-to-date with CRC screening, we examined 2 outcomes: (1) up-to-date screening by any modality (ie, FOBT in the past year, FSIG in the past 5 years, or colonoscopy in the past 10 years); and (2) up-to-date screening by FSIG (FSIG within the past 5 years vs not up-to-date by any modality).

To measure up-to-date screening we used the following questions from CHIS:

  • Have you ever had a sigmoidoscopy or colonoscopy? These are exams in which a healthcare professional inserts a tube into the rectum to look for signs of cancer or other problems. [If yes:]
    • How long ago did you have your most recent exam?
    • Was your most recent exam a sigmoidoscopy, a colonoscopy, or something else?
  • Have you ever done a blood stool test, using a home test kit? [If yes:]
    • How long ago did you do your most recent home blood stool test?

Individual-Level Characteristics. Individual characteristics include race/ethnicity (non-Hispanic White, Latino, African American, American Indian/Alaska Native, Asian American and Pacific Islander, multiracial); age (50-64 years, 65-84 years); sex (male, female); marital status (married/living with a partner, widowed/divorced/separated/never married); educational attainment (less than a bachelor’s degree, at least a bachelor’s degree); income (less than 300% of the federal poverty level, at least 300% of the federal poverty level); insurance coverage (yes, no), place of birth (born in the United States, not born in the United States); and language spoken at home (English only, other language alone or in combination with English). Stressors measured include neighborhood safety, food security, and racial/ethnic discrimination. Perceived neighborhood safety compared safe all/most of the time with safe some/none of the time (responses were missing for nonowners/nonrenters). Food security, which assessed food availability at the household level, compared secure with insecure. Self-reported experiences of any racial/ethnic discrimination (both general and in healthcare) compared yes with no. By testing for the effects of stress-related variables (eg, racial/ethnic discrimination, food insecurity, and acculturation), which have not been extensively examined in previous studies of cancer screening, this study may inform the literature on individual-level stress-related predictors of CRC screening use.10,11,17

Medical Service Study Area and County-Level Data

Medical Service Study Area data were obtained from the California Office of Statewide Health Planning and Development, the Spatial Impact Factors data set, and the 2005 CHIS.38,40,41 County data were obtained from the Spatial Impact Factors data set and the 2004 Area Resource File.40,42 We examined 4 contextual factors at the county and MSSA levels, capturing fundamental causes (SES and racial/ethnic residential segregation) and healthcare resources (primary care shortage and HMO penetration).

Areas were categorized as having a primary care shortage by using the criteria developed by the Health Resources and Services Administration.42 HMO penetration was categorized as whether the proportion of the county population enrolled in HMO plans was above or below the median level for the state.43 At the MSSA level, we used 2005 CHIS data on enrollment in an HMO to measure HMO penetration. Based on 2 items that ask about Medicare coverage provided through an HMO and (for non-Medicare users) whether the main health plan is an HMO, we estimated the percentage of MSSA residents who were enrolled in an HMO.

Areas were categorized as having fewer than 20% or at least 20% of their residents living in poverty. Segregation was measured using a diversity index. The diversity index estimated the probability of an individual from one group interacting with an individual from another group within a defined area, with scores ranging from 0 (complete segregation) to 1 (complete integration).44 We recoded the diversity index to indicate areas above and below the median values in California. We chose the diversity index as the measure of segregation because it can be computed for more than 2 racial/ethnic groups; thus, it does not require that the analyses be stratified by racial/ethnic group. Metropolitan Statistical Area/Primary Metropolitan Statistical Area, counties, and Census Place are common levels of geography at which residential segregation is measured. For this study, we constructed a segregation measure for subcounty MSSAs in addition to counties because we were interested in evaluating whether MSSAs are a meaningful geographic level for assessing the effects of contextual factors on health behaviors such as CRC screening.


We used descriptive statistics to characterize our study sample, ArcGIS ( to map the geographic variation in MSSA and county-level CRC screening use, and logistic regression models to estimate the association between CRC screening use and respondent characteristics. Individual-level descriptive analyses were weighted and adjusted for the design effect of CHIS 2005 using SAS-callable SUDAAN with jackknife replicate weights.45 To reduce the likelihood of false-positive (type 1) error due to multiple comparisons, the standard critical P value of .05 was adjusted using Bonferroni’s correction. We applied the adjusted critical P value of .00125 (.05/[2 outcomes X 20 characteristics]).

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