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Keywords:

  • cancer screening;
  • mammography;
  • Pap;
  • prostate specific antigen;
  • colorectal screening;
  • National Health Interview Survey

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

BACKGROUND

Understanding differences in cancer screening among population groups in 2000 and successes or failures in reducing disparities over time among groups is important for planning a public health strategy to reduce or eliminate health disparities, a major goal of Healthy People 2010 national cancer screening objectives. In 2000, the new cancer control module added to the National Health Interview Survey (NHIS) collected more detailed information on cancer screening compared with previous surveys.

METHODS

Data from the 2000 NHIS and earlier surveys were analyzed to discern patterns and trends in cancer screening practices, including Pap tests, mammography, prostate specific antigen (PSA) screening, and colorectal screening. The data are reported for population subgroups that were defined by a number of demographic and socioeconomic characteristics.

RESULTS

Women who were least likely to have had a mammogram within the last 2 years were those with no usual source of health care (61%), women with no health insurance (67%), and women who immigrated to the United States within the last 10 years (61%). Results for Pap tests within the last 3 years were similar. Among both men and women, those least likely to have had a fecal occult blood test or endoscopy within the recommended screening interval had no usual source of care (14% for men and 18% for women), no health insurance (20% for men and 18% for women), or were recent immigrants (20% for men and 18% for women). An analysis of changes in test use since the 1987 survey indicates that the disparities are widening among groups with no usual source of care.

CONCLUSIONS

No striking improvements have been observed for the groups with greatest need. Although screening use for most groups has increased since 1987, major disparities remain. Some groups, notably individuals with no usual source of care and the uninsured are falling further behind; and, according to the 2000 data, recent immigrants also experience a significant gap in screening utilization. More attention is needed to overcome screening barriers for these groups if the population benefits of cancer screening are to be achieved. Cancer 2003;97:1528–40. Published 2003 by the American Cancer Society.

DOI 10.1002/cncr.11208

The Nation's progress toward Healthy People 2000 and Healthy People 2010 national objectives for cancer screening has been monitored for more than a decade by the National Health Interview Survey (NHIS). The survey is administered annually by the National Center for Health Statistics of the Centers for Disease Control and Prevention (CDC).1 The National Cancer Institute (NCI) developed and supported cancer control supplements to the NHIS in 1987, 1992, and 2000. The 2000 supplement, a collaboration of the NCI and the CDC, was administered in the same year as the 2000 Census, which provided concurrent population denominators.

The objective of this report is to examine the prevalence of several cancer screening practices reported by adults in the year 2000, with a focus on differences in screening among subgroups of the United States population that historically have been underserved. In addition, we examined trends among those groups from 1987 through 2000 to determine whether differences in screening prevalence are changing. Regular monitoring both of current differences among groups in 2000 and of the success or failure in reducing past differences will be needed to plan public health strategies for reducing or eliminating disparities in the use of cancer screening services, a major objective of Healthy People 2010.

The cancer screening tests that are the focus of this article include those recommended by the U.S. Preventive Services Task Force (USPSTF), an independent, expert advisory panel convened by the U.S. Public Health Service, Department of Health and Human Services, to review evidence on hundreds of preventive services and to recommend tests, immunizations, and other medical interventions only when scientific investigation clearly demonstrates that they are effective. Currently, the USPSTF recommends Pap tests for cervical cancer screening; mammography for breast cancer screening; and fecal occult blood test (FOBT) or sigmoidoscopy for colorectal cancer screening.2 In addition, this article presents the first national data on men's reports of prostate specific antigen (PSA) testing for prostate cancer. Although there is no consensus on the effectiveness of PSA testing in reducing cancer mortality, and the balance of potential harms and benefits is not clear, we include these data because the use of PSA testing appears to be widespread and increasing.3, 4 Moreover, the American Cancer Society (ACS) and the CDC recommend that men should be given information on the potential risks and benefits of getting a PSA test in a way that they can understand, so that each individual can make the best decision for himself.5 This is the first national survey to monitor this screening modality.

In this descriptive study, we examine the prevalence and progress of cancer screening among subgroups defined by a number of demographic and socioeconomic variables that have been found to influence screening practices and for which disparities have been identified.6–19 These include age, gender, race/ethnicity, time since immigration, residence in a metropolitan statistical area (MSA), income (poverty status), education, health insurance status, disability, and having a usual source of health care.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

NHIS

The annual NHIS is one of the principle sources of health information on the civilian, noninstitutionalized population in the United States.20 Each year, a clustered, randomized sample of U.S. households is used to obtain the data. In-person interviews yield a basic set of demographic and health items for each participating household. The core questionnaire remains nearly the same from year to year, with major revisions approximately every decade; the most recent questionnaire is from 1997. Each year, one or more supplements focus on specific health topics. The entire survey, including the core and supplement, are submitted for approval by the U.S. Office of Management and Budget (OMB), as required by the Privacy Act, and prospective respondents are provided information appropriate to informed consent requirements. The NHIS sample was redesigned in 1995 for the period 1995–2004 and added Hispanics as the second over-sampled group, along with African Americans.21, 22

The Cancer Control Supplements

Cancer supplements were fielded in 1987, 1992, and 2000. The 1998 Prevention Module contained many of the same questions related to cancer screening, and trends in cancer screening from 1987 to 1998 were reported in a previous publication.23 The 2000 supplement was administered to one adult sample person who was selected randomly from men and women age ≥ 18 years living in the households participating in the NHIS. Previous cancer supplements to the NHIS were administered to split samples using two different survey instruments. With the split-sample design, only one-half of the overall sample received the screening questions. The 1992 survey was administered for only 6 months due to budgetary constraints. The 1998 Prevention Module covered much more than cancer, limiting the number of screening questions. Although earlier questionnaires included attitudinal and knowledge questions, the 2000 Cancer Control Module (CCM) focused on behaviors. The sample sizes have varied, but the household response rates for the cancer supplement years of the NHIS have remained fairly stable at more than 85% since 1987.21

The 2000 Cancer Control Module

In 2000, information for the NHIS was collected from 38,633 households, 88.9% of those selected, and 32,374 sample adults responded to the sample adult questionnaire, for an overall response rate of 72.1%. Of these respondents, 1152 did not complete the cancer control module.21 The cancer control questions have evolved to reflect changes in knowledge and practice, although the basic categories have remained the same: cancer-related health behaviors and practices. For all cancer supplements, these have included mammogram, Pap test, blood stool test, and endoscopy. To construct the 2000 CCM, previous supplements were evaluated carefully, and the questions were updated and tailored to reflect current evidence, practice, and priorities. Chest X-ray, digital rectal examination, breast self-examination, and oral cancer examination questions were removed. First-time, screening-related additions to the cancer supplement in 2000 included family history of cancer, genetic testing for cancer risk, separate questions on three types of endoscopy for colorectal cancer (sigmoidoscopy, colonoscopy, and proctoscopy), and questions on PSA testing. Questions were added to obtain information on follow-up to screening tests; decision making for prostate cancer; and for mammography, new questions covered out-of-pocket costs and location of test.

Cancer Screening Questions

Women participants age ≥ 18 years were asked whether they ever had a Pap test. For the other screening tests, participants younger than the recommended age were questioned, as in previous supplements. Specifically, women age ≥ 30 years were asked whether they had ever had a mammogram. Those who responded positively were asked when they had their most recent examination. Those who could not recall a month and year were asked whether they could recall how long ago it occurred and, if that could not be recalled, whether it was within a specific number of years. Men age ≥ 40 years were asked whether they had heard of a PSA or prostate specific antigen test; and, if they were hesitant, a prompt explanation was read, a PSA test is a blood test to detect prostate cancer. Those who had heard of it were asked whether they ever had a PSA test. Men and women age ≥ 40 years were asked whether they ever had a sigmoidoscopy, colonoscopy, or proctoscopy and were read definitions if necessary. Questions on FOBT defined the procedure and distinguished home tests (with specimen collected at home) from office tests. The NCI and the CDC agreed that it was important to include this distinction, because only home tests have demonstrated effectiveness in clinical trials.24 The follow-up questions to determine whether prostate and colorectal tests were recent were similar to the questions used for Pap and mammogram screening. Persons who reported that they never had the test or who had not had the test recently were asked to provide the main reason.

Test Intervals

To monitor progress in screening for this study, we included tests that were conducted for any purpose, not just as part of a routine examination. We did this for several reasons. First, a person who had the test within the recommended interval has been screened appropriately and ordinarily does not need another test until the recommended time interval has passed. In addition, the baseline and progress toward Healthy People 2010 national cancer screening objectives are measured in this manner. We considered that the test occurred within the recommended interval if it occurred within a specific time prior to the interview. For Pap tests, mammography, and FOBT, intervals of 3 years, 2 years, and 1 year, respectively, were used. These were based on the USPSTF recommendations of testing at least every 3 years, every 1–2 years, and annually, respectively. For sigmoidoscopy/colonoscopy/proctoscopy (hereafter referred to as endoscopy) screening, the USPSTF has no recommendation regarding interval. We used 5 years for the 2000 cross-sectional data, because testing within 5 years is recommended in other colorectal cancer screening guidelines.25–27 For trend comparisons for endoscopy, we used 3 years to maintain consistency with the manner in which data on recent testing were collected in earlier NHIS surveys. For the PSA test, we used the annual screening recommendation of the ACS.5

Age Groups

The age groups for analysis were selected with consideration of screening recommendations and other age-related influences on screening, such as Medicare benefits for those age ≥ 65 years. The survey questions on Pap tests were asked of women age ≥ 18 years, but the youngest age group analyzed was 25 years, constructing a comparison of groups for which educational attainment usually is complete. Other analyses focused on mammography for women age ≥ 40 years and on PSA and colorectal screening of individuals age ≥ 50 years, reflecting the recommended starting ages for those tests. Recommendations for mammography for women age 40–49 years have varied over the years, making this a group of particular interest for comparisons over time. Each table provides results for the entire age range as well as for the separate age groupings (see Tables 1–5.

Table 1. Women who Had a Pap Test Within the Last 3 Yearsa
CharacteristicNo.Age ≥ 25 yrsaAge 25–39 yrsAge 40–49 yrsAge 50–64 yrsAge ≥ 65 yrs
%CI%CI%CI%CI%CI
  • a

    CI: confidence interval; MSA: metropolitan statistical area; AI/AN: American Indian/Alaska Native.

  • b Persons with missing or unknown data were excluded from the numerator and denominator. Percentages were weighted.

  • c

    Standardized to the 2000 projected population by 5-year age groups.

  • d Pacific Islanders are coded with “other” for confidentiality reasons in 2000. Persons who reported more than one race and who selected a main race were coded according to their main race for consistency with data collected before Office of Management and Budget Directive 15 took effect.

Total           
 No.n = 15318n = 5180n = 3289n = 3343n = 3506
 %82.481.7–83.189.288.2–90.286.685.2–88.083.782.3–85.164.662.7–66.5
Educationn = 15232n = 5164n = 3272n = 3325n = 3471
 Less than high school317974.372.4–76.179.576.2–82.981.076.5–85.473.369.3–77.356.753.5–60.0
 High school graduate457880.979.7–82.287.285.0–89.483.180.3–86.081.479.1–83.867.064.2–69.9
 Some college or AA degree414584.282.9–85.490.188.4–91.887.785.5–90.085.983.3–88.469.966.0–73.7
 College graduate (BA/BS)333088.286.8–89.694.192.6–95.691.589.3–93.892.390.3–94.369.864.3–75.3
Family income/poverty ration = 15318n = 5180n = 3289n = 3343n = 3506
 <200%440674.272.5–75.983.080.8–85.275.070.9–79.173.069.3–76.659.256.1–62.3
 200–299%201278.576.5–80.588.185.5–90.882.778.3–87.174.469.7–79.262.457.1–67.6
 300–399%151384.582.5–86.692.490.2–94.586.282.0–90.483.579.4–87.772.666.7–78.4
 400–499%121486.283.8–88.693.390.7–95.885.681.2–90.087.783.6–91.777.469.0–85.7
 ≥500%271190.589.0–92.094.792.9–96.595.293.8–96.791.489.5–93.479.273.0–85.5
 Unknown346282.080.6–83.387.384.6–90.087.484.7–90.284.881.9–87.763.259.9–66.4
MSAn = 15318n = 5180n = 3289n = 3343n = 3506
 Non-MSA309280.779.0–82.487.785.0–90.385.682.4–88.882.479.4–85.461.757.9–65.4
 MSA1222682.982.0–83.789.688.5–90.686.885.2–88.484.182.6–85.665.663.4–67.8
Usual source of caren = 15313n = 5176n = 3288n = 3343n = 3506
 No154458.355.3–61.372.768.9–76.558.452.6–64.257.250.2–64.337.228.1–46.3
 Yes1376984.784.0–85.491.790.8–92.790.088.7–91.385.684.2–86.965.964.0–67.8
Health insurancen = 15276n = 5171n = 3278n = 3331n = 3496
 None211262.458.1–66.876.373.0–79.666.661.8–71.461.155.8–66.440.414.3–66.6
 Public249279.276.8–81.587.884.2–91.485.980.6–91.178.573.7–83.358.755.5–62.0
 Private/military1067285.885.1–86.692.591.6–93.490.088.6–91.487.486.0–88.867.865.5–70.1
Chronic disabilityn = 15193n = 5144n = 3249n = 3320n = 3480
 Yes281677.775.3–80.082.977.8–87.983.880.0–87.779.475.9–82.957.153.8–60.3
 No1237783.482.6–84.189.788.7–90.786.985.4–88.484.783.2–86.268.866.6–71.0
Race/ethnicitycn = 15286n = 5165n = 3280n = 3337n = 3504
 Hispanic239277.475.2–79.783.881.5–86.181.376.7–85.975.970.9–81.066.960.4–73.3
 Non-Hispanic white1013483.482.6–84.290.689.4–91.987.886.2–89.485.083.5–86.564.362.1–66.4
 Non-Hispanic black232684.182.5–85.891.589.6–93.589.186.5–91.783.780.0–87.567.462.0–72.8
 Non-Hispanic AI/AN9173.063.5–82.586.873.5–100.061.139.0–83.163.439.9–86.975.745.9–100.0
 Non-Hispanic Asian34370.865.3–76.275.467.6–83.168.956.0–81.871.960.2–83.758.937.7–80.1
Racecn = 14697n = 4847n = 3153n = 3253n = 3444
 White1186382.882.0–83.689.788.5–90.887.385.7–88.884.382.8–85.764.462.3–66.4
 Black236884.082.4–85.791.489.3–93.489.086.4–91.683.880.1–87.567.462.0–72.8
 AI/AN11875.066.2–83.788.477.3–99.561.841.2–82.562.641.0–84.180.557.3–100.0
 Asian34870.965.5–76.375.567.7–83.268.655.6–81.671.960.5–83.458.937.7–80.1
Immigrationn = 15115n = 5089n = 3237n = 3314n = 3475
 In U.S. < 10 yrs61361.055.2–66.876.170.9–81.364.952.7–77.166.851.3–82.321.60.4–42.8
 In U.S. ≥ 10 yrs156379.477.0–81.885.281.6–88.881.476.5–86.380.776.3–85.266.559.9–73.1
 Born in U.S.1293983.482.6–84.190.989.8–92.087.786.3–89.184.382.9–85.764.762.8–66.7
Table 2. Women who Had a Mammogram Within the Last 2 Yearsa
CharacteristicNo.Age ≥ 40 yrsaAge 40–49 yrsAge 50–64 yrsAge ≥65 yrs
%CI%CI%CI%CI
  • a

    CI: confidence interval; MSA: metropolitan statistical area; AI/AN: American Indian/Alaska Native.

  • b Persons with missing or unknown data were excluded from the numerator and denominator. Percentages were weighted.

  • c

    Standardized to the 2000 projected population by 5-year age groups.

  • d Pacific Islanders are coded with “other” for confidentiality reasons in 2000. Persons who reported more than one race and who selected a main race were coded according to their main race for consistency with data collected before Office of Management and Budget Directive 15 took effect.

Total         
 No.n = 10212n = 3308n = 3349n = 3555
 %70.169.0–71.264.262.2–66.278.676.9–80.368.066.2–69.8
Educationn = 10142n = 3291n = 3331n = 3520
 Less than high school235257.254.4–59.947.041.0–52.766.362.0–70.757.654.6–60.4
 High school graduate331868.566.6–70.359.055.3–62.776.673.9–79.372.069.1–74.9
 Some college or AA degree253672.670.8–74.566.062.8–69.281.277.9–84.572.668.7–76.6
 College graduate (BA/BS)193680.078.0–82.175.672.8–78.487.584.8–90.276.871.8–81.8
Family income/poverty ration = 10212n = 3308n = 3349n = 3555
 <200%283355.853.4–58.243.538.9–48.065.561.6–69.458.655.7–61.6
 200–299%123066.463.1–69.759.053.2–64.770.965.4–76.370.065.8–74.3
 300–399%90771.768.7–74.862.657.1–68.179.875.1–84.676.370.7–82.0
 400–499%74877.173.5–80.772.366.7–77.982.777.9–87.579.571.1–87.9
 ≥500%185382.880.7–84.976.973.7–80.088.686.2–91.084.579.1–89.9
 Unknown264169.767.6–71.864.160.0–68.277.474.1–80.768.065.0–71.0
MSAn = 10212n = 3308n = 3349n = 3555
 Non-MSA227064.962.0–67.758.953.9–64.075.371.2–79.561.157.3–64.8
 MSA794271.770.5–72.965.663.5–67.879.677.7–81.470.368.3–72.4
Usual source of caren = 10211n = 3307n = 3349n = 3555
 No79334.630.7–38.628.122.9–33.247.740.5–54.827.218.8–35.6
 Yes941873.071.9–74.168.666.6–70.780.879.1–82.569.868.0–71.6
Health Insurancen = 10177n = 3296n = 3337n = 3544
 None102538.431.5–45.433.829.1–38.448.743.2–54.235.68.3–62.9
 Public196861.758.2–65.252.144.7–59.671.666.0–77.261.658.5–64.7
 Private/military718475.274.0–76.470.368.2–72.583.782.1–85.471.669.5–73.7
Chronic disabilityn = 10123n = 3268n = 3326n = 3529
 Yes250165.863.5–68.160.355.0–65.673.870.3–77.461.057.9–64.1
 No762271.670.3–72.864.862.6–67.079.777.9–81.671.969.7–74.0
Race/ethnicitycn = 10195n = 3299n = 3343n = 3553
 Hispanic125860.757.5–63.854.248.7–59.666.461.5–71.468.262.6–73.8
 Non-Hispanic white725372.070.7–73.267.164.8–69.580.578.6–82.568.266.2–70.3
 Non-Hispanic black145067.864.8–70.960.955.9–66.077.773.0–82.465.960.2–71.5
 Non-Hispanic AI/AN5852.140.9–63.249.826.0–73.549.527.2–71.767.541.2–93.9
 Non-Hispanic Asian17658.150.1–66.042.530.0–55.164.551.0–78.063.642.5–84.6
Racecn = 9921n = 3170n = 3258n = 3493
 White819771.270.0–72.465.963.7–68.179.677.8–81.568.266.3–70.2
 Black147267.664.5–70.661.256.2–66.276.972.1–81.665.860.1–71.5
 AI/AN7252.341.7–63.048.025.8–70.351.230.7–71.759.230.0–88.4
 Asian18058.750.7–66.842.830.3–55.266.153.1–79.163.642.5–84.6
Immigrationn = 10102n = 3255n = 3323n = 3524
 In U.S. <10 yrs18039.329.9–48.632.020.9–43.052.036.7–67.440.312.0–68.6
 In U.S. ≥10 yrs104064.761.2–68.155.749.5–61.973.468.4–78.466.460.3–72.4
 Born in U.S.888271.370.1–72.566.163.9–68.379.677.8–81.568.666.7–70.5
Table 3. Patients who Had a Home Blood Stool Test Within the Last Year or Colorectal Endoscopy Within the Last 5 Yearsa
CharacteristicNo.MenWomen
Age ≥ 50 yrsbAge 50–64 yrsAge ≥65 yrsNo.Age ≥ 50 yrsAge 50–64 yrsAge ≥65 yrs
%CI%CI%CI%CI%CI%CI
  • a

    CI: confidence interval; MSA: metropolitan statistical area; AI/AN: American Indian/Alaska Native.

  • b

    Persons with missing or unknown data were excluded from the numerator and denominator Percentages were weighted.

  • c

    Standardized to the 2000 projected population by 5-year age groups.

  • d Pacific Islanders are coded with “other” for confidentiality reasons in 2000. Persons who reported more than one race and who selected a main race were coded according to their main race for consistency with data collected before Office of Management and Budget Directive 15 took effect.

Total              
 No.n = 4844n = 2728n = 2116n = 6778n = 3315n = 3463
 %41.039.4–42.635.533.5–37.548.445.8–51.037.536.2–38.933.731.9–35.542.540.4–44.6
Educationn = 4797n = 2705n = 2092n = 6726n = 3299n = 3427
 Less than high school129129.026.2–31.721.317.3–25.240.335.9–44.6179728.826.2–31.324.420.8–28.134.831.5–38.0
 High school graduate130139.736.6–42.933.629.5–37.648.443.6–53.1235135.633.4–37.730.127.1–33.043.140.1–46.1
 Some college or AA degree107842.439.1–45.737.433.1–41.747.041.7–52.2152241.739.0–44.437.834.0–41.547.343.0–51.7
 College graduate (BA/BS)112751.948.2–55.544.440.3–48.661.255.8–66.6105648.344.6–52.041.237.0–45.456.350.3–62.2
Family income poverty ration = 4844n = 2728n = 2116n = 6778n = 3315n = 3463
 < 200%110633.830.4–37.128.623.8–33.341.736.8–46.5203631.328.7–33.926.622.6–30.637.734.5–40.8
 200–299%61736.131.8–40.427.421.4–33.547.040.9–53.179139.635.5–43.837.632.0–43.242.336.7–47.9
 300–399%43440.534.9–46.135.027.4–42.650.142.2–58.056039.635.5–43.731.125.4–36.852.645.5–59.6
 400–499%37341.835.9–47.734.127.8–40.554.643.7–65.641839.533.9–45.037.131.0–43.343.133.4–52.9
 ≥500%111353.249.4–56.946.042.1–49.861.154.9–67.3106246.843.0–50.540.537.2–43.854.247.4–60.9
 Unknown120136.834.1–39.529.025.1–32.847.142.8–51.5191134.632.3–36.928.825.4–32.241.538.1–44.8
MSAn = 4844n = 2728n = 2116n = 6778n = 3315n = 3463
 Non-MSA107738.535.3–41.734.630.2–39.143.938.9–49.0160735.032.3–37.732.228.6–35.938.834.9–42.8
 MSA376741.839.9–43.635.733.5–38.049.846.7–52.8517138.436.8–39.934.132.1–36.243.841.3–46.3
Usual source of caren = 4841n = 2725n = 2116n = 6778n = 3315n = 3463
 No47813.910.2–17.512.48.3–16.417.59.9–25.139513.49.4–17.412.07.7–16.215.18.0–22.2
 Yes436343.241.5–44.938.436.2–40.649.847.2–52.5638339.037.6–40.435.333.4–37.143.841.6–46.0
Health insurancen = 4827n = 2718n = 2109n = 6755n = 3303n = 3452
 None38719.811.3–28.414.510.0–19.024.36.6–42.147918.011.1–24.918.414.3–22.627.11.0–53.2
 Public89735.330.8–39.830.423.3–37.643.038.5–47.5164631.928.4–35.428.723.1–34.335.832.7–38.8
 Private/military354343.841.9–45.738.636.4–40.850.947.8–53.9463040.739.1–42.336.434.4–38.446.143.4–48.8
Chronic disabilityn = 4812n = 2710n = 2102n = 6734n = 3293n = 3441
 Yes127443.540.1–46.939.434.3–44.449.645.3–53.9201238.936.3–41.537.733.6–41.739.235.9–42.5
 No353840.238.4–42.134.432.2–36.747.945.0–50.9472237.536.0–39.032.830.8–34.844.341.8–46.7
Race/ethnicitycn = 4834n = 2721n = 2113n = 6770n = 3309n = 3461
 Hispanic54427.322.6–32.019.914.3–25.538.630.7–46.470926.622.4–30.827.521.9–33.126.921.3–32.4
 Non-Hispanic white362642.540.7–44.337.335.0–39.749.746.8–52.5506439.337.8–40.835.433.3–37.544.341.9–46.6
 Non-Hispanic black53540.335.1–45.435.328.7–41.945.237.9–52.587332.028.6–35.429.024.3–33.735.930.8–41.1
 Non-Hispanic AI/AN3039.528.5–50.540.520.0–61.025.00.0–59.32726.612.3–41.026.55.4–47.627.40.0–58.0
 Non-Hispanic Asian9933.423.7–43.022.810.1–35.442.626.5–58.69728.120.1–36.118.68.2–28.940.726.6–54.7
Racecn = 4719n = 2646n = 2073n = 6638n = 3227n = 3411
 White404341.740.0–43.436.234.0–38.549.246.5–52.0562138.737.2–40.135.033.0–37.043.541.2–45.8
 Black54240.135.1–45.134.928.3–41.545.338.2–52.488231.828.5–35.128.724.1–33.335.830.7–41.0
 AI/AN3336.625.7–47.637.117.5–56.829.60.0–63.63527.514.1–41.026.97.5–46.426.40.0–53.3
 Asian10133.624.0–43.323.310.7–35.942.626.5–58.610027.219.5–34.817.77.9–27.540.726.6–54.7
Immigrationn = 4797n = 2700n = 2097n = 6717n = 3287n = 3430
 In U.S. <10 yrs5820.310.8–29.77.30.0–15.535.45.4–65.57315.88.4–23.311.51.4–21.518.70.0–39.5
 In U.S. ≥10 yrs50532.527.9–37.227.021.2–32.839.731.3–48.263731.026.7–35.327.621.9–33.335.829.4–42.3
 Born in U.S.423442.340.7–44.037.034.8–39.149.646.9–52.4600738.537.1–39.934.732.7–36.643.541.3–45.7
Table 4. Men who Had a Prostate Specific Antigen Test Within the Last Yeara
CharacteristicNo.Age ≥ 50 yrsbAge 50–64 yrsAge ≥ 65 yrs
%CI%CI%CI
  • a

    CI: confidence interval; MSA: Metropolitan statistical area; AI/AN. American Indian/Alaska Native.

  • b

    Persons with missing or unknown data were excluded from the numerator and denominator. Percentages were weighted.

  • c

    Standardized to the 2000 projected population by 5-year age groups.

  • d Pacific Islanders are coded with “other” for confidentiality reasons in 2000. Persons who reported more than one race and who selected a main race were coded according to their main race for consistency with data collected before Office of Management and Budget Directive 15 took effect.

Total       
 No.n = 4834n = 2705n = 2129
 %41.039.4–42.533.631.4–35.851.349.0–53.6
Educationn = 4788 n = 2682n = 2106
 Less than high school129929.026.4–31.621.217.3–25.139.935.7–44.0
 High school graduate130738.735.7–41.630.126.0–34.151.246.8–55.7
 Some college or AA degree105845.942.5–49.336.332.1–40.556.451.4–61.4
 College graduate (BA/BS)112451.948.4–55.542.037.5–46.564.159.2–69.0
Family income/poverty ration = 4834 n = 2705n = 2129
 <200%110931.728.6–34.926.021.3–30.740.135.9–44.3
 200–299%61233.829.9–37.825.119.4–30.749.443.4–55.3
 300–399%43139.635.0–44.231.624.8–38.554.346.5–62.0
 400–499%36643.337.1–49.634.727.9–41.454.643.4–65.8
 ≥500%109854.350.6–58.042.838.7–46.966.060.1–71.9
 Unknown121839.336.3–42.429.225.0–33.553.248.7–57.6
MSAn = 4834n = 2705n = 2129
 Non-MSA106736.933.5–40.231.627.1–36.145.640.9–50.3
 MSA376742.240.5–44.034.231.6–36.753.050.4–55.6
Usual source of caren = 4831n = 2702n = 2129
 No48211.47.6–15.18.95.4–12.515.37.6–23.0
 Yes434943.441.8–45.136.834.4–39.253.050.6–55.4
Health insurancen = 4816n = 2696n = 2120
 None38312.67.2–18.011.77.3–16.118.63.1–34.1
 Public90233.329.2–37.325.719.4–32.144.240.0–48.4
 Private/military353144.342.4–46.237.034.5–39.454.651.9–57.3
Chronic disabilityn = 4800n = 2686n = 2114
 Yes126639.636.2–43.033.328.3–38.348.243.9–52.4
 No353441.539.7–43.333.631.2–36.152.750.0–55.3
Race/ethnicitycn = 4825n = 2698n = 2127
 Hispanic54729.925.0–34.924.218.8–29.736.929.5–44.3
 Non-Hispanic white360642.640.9–44.334.832.3–37.353.551.0–56.0
 Non-Hispanic black53937.832.8–42.736.129.2–43.042.333.7–50.9
 Non-Hispanic AI/AN2935.623.5–47.724.96.3–43.552.910.7–95.2
 Non-Hispanic Asian10426.018.9–33.118.98.9–28.838.625.6–51.7
Racecn = 4710n = 2622n = 2088
 White402841.940.3–43.534.131.7–36.552.650.2–55.1
 Black54437.432.6–42.335.929.0–42.741.933.4–50.3
 AI/AN3227.913.5–42.422.75.8–39.649.69.0–90.2
 Asian10626.219.1–33.319.49.5–29.338.625.6–51.7
Immigrationn = 4785n = 2676n = 2109
 In U.S. <10 yrs6217.45.9–28.911.01.6–20.425.80.0–57.0
 In U.S. ≥10 yrs50831.526.3–36.822.516.3–28.742.134.3–49.8
 Born in U.S.421542.440.7–44.035.332.9–37.752.550.1–55.0
Table 5. Percentage Change in the Use of Cancer Screening Tests, 1987–2000 National Health Interview Surveya
CharacteristicPap testbMammogramcFOB/CREd
1987 %DiffCI1987 %DiffCI1987 %DiffCI
  • FOB/CRE: fecal occult blood/colorectal examination; Diff: difference; CI: confidence interval; MSA: metropolitan statistical area; AI/AN: American Indian/Alaska Native.

  • a

    Persons with missing or unknown data were excluded from the numerator and denomination. Percentages were weighted and standardized to the 2000 projected population by 5-year age group.

  • b

    Pap test within the last 3 years, women age ≥ 25 years.

  • c

    Mammogram within the last 2 years, women age ≥ 40 years.

  • d

    Home or office blood stool test within the last year or colorectal endoscopy within the last 3 years, age ≥ 50 years.

  • e

    Pacific Islanders are coded with “other” for confidentiality reasons in 2000. Persons who reported more than one race and who selected a main race were coded according to their main race for consistency with data collected before Office of Management and Budget Directive 15 took effect.

  • f

    Health insurance from 1992 National Health Interview Survey data. (not collected in 1987)

Total73.58.97.7–10.229.141.039.2–42.927.212.310.6–14.0
Age (yrs         
 25–3987.41.80.2–3.4
 40–4978.58.05.3–10.832.132.028.7–35.3
 50–6469.214.611.8–17.332.246.443.5–49.326.210.38.0–12.5
 ≥6548.515.512.8–18.321.745.743.2–48.128.514.712.3–17.0
Gender         
 Male26.214.411.8–17.1
 Female73.58.97.7–10.229.141.039.2–42.928.210.78.6–12.8
Education         
 Less than high school63.610.77.7–13.617.439.836.3–43.319.710.27.3–13.0
 High school graduate74.16.84.7–8.930.837.734.8–40.628.29.57.0–12.1
 Some college or AA degree78.25.93.4–8.537.135.531.1–39.934.47.63.4–11.8
 College graduate (BA/BS)81.46.84.1–9.538.341.737.4–46.140.59.65.2–14.0
Family income/poverty ratio         
 <200%65.38.96.3–11.519.236.633.4–39.820.012.79.9–15.5
 200–299%73.45.11.8–8.526.539.934.9–45.026.513.99.0–18.7
 300–399%76.18.55.5–11.432.439.334.8–43.829.79.95.3–14.5
 400–499%80.16.11.9–10.337.639.533.6–45.434.66.90.2–13.6
 ≥500%83.07.54.7–10.342.840.135.4–44.737.212.77.9–17.4
 Unknown71.510.57.5–13.425.843.939.9–48.024.911.07.3–14.6
MSA         
 Non-MSA70.89.97.4–12.523.940.936.9–44.921.014.711.3–18.1
 MSA74.38.67.1–10.030.841.038.9–43.129.411.39.4–13.2
Usual source of care         
 No57.90.4−3.9–4.614.819.915.0–24.812.20.3−3.5–4.1
 Yes75.69.27.8–10.530.842.240.2–44.229.112.310.5–14.0
Race/ethnicitye         
 Hispanic64.113.48.1–18.617.742.937.3–48.616.810.13.4–16.9
 Non-Hispanic white74.19.37.9–10.731.140.938.8–43.128.812.010.2–13.8
 Non-Hispanic black77.27.04.2–9.723.344.639.8–49.319.917.713.4–22.0
 Non-Hispanic AI/AN78.6−5.6−18.1–6.918.733.418.8–48.010.932.821.5–44.1
 Non-Hispanic Asian59.511.3−1.2–23.817.240.826.5–55.114.321.210.1–32.3
Racee         
 White73.59.38.0–10.730.241.038.9–43.028.311.79.9–13.5
 Black76.77.34.6–10.123.244.339.7–49.019.618.013.7–22.2
 AI/AN80.0−5.016.7–6.719.632.718.1–47.319.222.08.3–35.7
 Asian60.810.1−1.8–22.015.443.330.1–56.514.320.59.6–31.4
Health insurancef         
 None64.5−2.0−7.9–3.922.016.47.9–24.914.73.7−4.0–11.5
 Public70.09.24.2–14.238.922.815.3–30.429.95.1−0.9–11.2
 Private/military79.46.44.8–8.062.812.49.9–14.935.66.94.5–9.3

Other Population Subgroups

The criteria for other demographic and socioeconomic variables that have been found to influence screening practices are described below.

Poverty level.

For the 2000 survey, a detailed indicator of poverty status was created by utilizing published information from the U.S. Census Bureau regarding 1999 poverty thresholds.28 A ratio of the 1999 income value reported by respondents to the poverty threshold for the same year was constructed, given information on the family's overall size as well as the number of children age ≤ 17 years present in the family. The resulting ratio subsequently was ordered into a poverty gradient consisting of 14 categories.21 For purposes of comparison, we grouped income levels into multiples of this figure (< 200%, 200–299%, 300–399%, 400–499%, ≥ 500%, and unknown) corresponding to the analyses of earlier cancer modules. This was the only variable for which unknown was included as a category due to the relatively large rate (23%) of nonresponses to the question relating to income.

MSA.

Metropolitan Statistical Areas (MSA) are defined by the OMB according to standards applied to the Census. An MSA is a county or group of counties that contains at least 1 city with a population of 50,000 or more or a Census Bureau-defined urbanized area of at least 50,000 with a metropolitan population of at least 100,000.21 We used the MSA or non-MSA distinction to compare urban and rural populations.

Usual source of care.

The variable usual source of care was measured by asking respondents whether there was a place that they usually went when they were sick or needed advice about their health. Those who responded yes were asked what kind of place they went to most often—a clinic, physician's office, emergency room, or some other place. Persons responding with emergency room were defined as having no usual source of care.29

Health insurance.

Respondents were asked whether they were covered by any kind of health insurance or some other kind of health care plan. Those who responded affirmatively were asked what kind of coverage they had. Persons were included under private insurance if they reported having a private insurance plan, single service plan, military plan, CHAMPUS, or Tricare. Public health insurance included Medicaid, Medicare without private supplementation, Children's Health Insurance Program, Indian Health Service, or other public assistance, such as state-sponsored programs.21

Disability.

For the 2000 NHIS, each condition reported as a cause of an individual's activity limitation was classified as chronic, not chronic, or unknown if chronic. Conditions that were not cured, once acquired (such as heart disease and diabetes), were considered chronic. Other conditions had to be present for ≥ 3 months to be considered chronic.21

Race and ethnicity.

Race and ethnicity were determined by asking separate questions, with the questions about Hispanic ethnicity and origin first.21 For this analysis, race was considered both separately and together with Hispanic ethnicity.

Immigration status.

For this analysis, persons who immigrated to the United States < 10 years ago were distinguished from those who entered ≥ 10 years ago and those who were born in the United States.

Data Analysis

The NHIS has a complex design involving stratification, clustering, and multistage sampling.21 Percentages for the total samples are age-adjusted using the 2000 Census population. The Survey Data Analysis (SUDAAN) computer package was used to analyze the data, because it takes into account the sample design of the survey to calculate the standard errors, from which the confidence intervals were derived.30 All sample weights were included with the data file. Respondents who indicated they had never heard of the test (asked only about PSA) were reported as not having had the test. Those who responded yes to having had a test were asked when they had their most recent test. Respondents who could not recall the time well enough to select a categoric answer were reported as unknown. Except for income, unknown responses were excluded from the analysis. Disparities or differences in screening use were determined by subtracting the lowest percentage under a specific variable category from the highest; standard errors are reported.

It is important to note that some categories of variables resulted in wide confidence intervals when the percentages of the population in those categories were small, such as for the smaller racial/ethnic groups, for persons age ≥ 65 years, and for the age specific estimates among recent immigrants. Rather than excluding information on these subgroups of the population, we choose to provide the results and corresponding confidence intervals, which will alert readers to the lack of precision in these estimates.

To show changes in screening use from the first cancer supplement in 1987 to the 2000 module, the base (1987) percentage is presented along with the difference from the current (2000) percentage and corresponding confidence intervals. This change in percentage was computed for the three screening modalities on which data were collected in both surveys: Pap test, mammogram, and colorectal screening.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Pap Smear

Table 1 shows that, overall, > 82.4% of women (confidence interval [CI], 81.7–83.1) age ≥ 25 years reported having a Pap test within the last 3 years. Looking at the respondents who were least likely to have had the test, 58.3% (CI, 55.3–61.3) of women without a usual source of health care reported no Pap test within the previous 3 years, along with 62.4% (CI, 58.1–66.8) of women without health insurance and 61.0% (CI, 55.2–66.8) of women who immigrated to the United States within the last 10 years. Women with lower levels of education, women with limited incomes, and women with chronic disabilities had lower levels of use compared with women in the comparison groups, although the levels of use were not as low as those associated with no usual source of care and recent immigration status. Living in a nonurban location was not associated with less utilization. Although both Asian and American Indian/Alaska Native women showed lower levels of use, the confidence intervals were too wide to confer significance to the results for these smaller population groups.

The greatest disparities in Pap test use during the previous 3 years, defined as differences between highest and lowest groups for all age groups combined, were associated with having or not having a usual source of care (26 percentage point difference; standard error [SE], 1.6), having or not having health insurance (23 percentage point difference; SE, 2.1), age (25 percentage point difference between persons age ≥ 65 years and persons age 25–39 years; SE, 1.1 years), and immigration within the last 10 years compared with being born in the United States (22 percentage point difference; SE, 2.9). In fact, a significant downward gradient with rising age was observed. Disparities by level of education, family income, chronic disability, race, and ethnicity were observed, although they were not as great as those due to health care access, age, and immigration.

Mammography

Among women age ≥ 40 years, 70.1% (CI, 69.0–71.2) reported having a mammogram within the previous 2 years (Table 2). Women who were least likely to have had a mammogram during the previous 2 years were the same groups least likely to have had a Pap test, that is, women with no usual source of health care (34.6%; CI, 30.7–38.6), women without health insurance (38.4%; CI, 31.5–45.4), and women who immigrated to the United States within the last 10 years (39.3%; CI, 29.9–48.6).

Similar to Pap tests, the greatest disparities or differences in mammography use were associated with lacking a usual source of health care (38 percentage point difference; SE, 2.1) or health insurance (37 percentage point difference; SE, 3.6) and recent immigration (32 percentage point difference; SE, 4.8). However, these differences were greater compared with the differences for Pap smears.

Colorectal Cancer Screening

Table 3 shows that, overall, 41.0% of men (CI, 39.4–42.6) and 37.5% of women (CI, 36.2–38.9) age ≥ 50 years reported having either an FOBT within the past year or colorectal endoscopy within the past 5 years. Those least likely to have had FOBT or endoscopy within the recommended screening interval had no usual source of care (men: 13.9%; CI, 10.2–17.5; women: 13.4%; CI, 9.4–17.4), no health insurance (men: 19.8%; CI, 11.3–28.4; women: 18.0%; CI, 11.1–24.9), or were recent immigrants (men: 20.3%; CI, 10.8–29.7; women: 15.8%; CI, 8.4–23.3).

The greatest disparities in colorectal cancer screening were associated with usual source of care (men: 29 percentage point difference; SE, 2.1; women: 26 percentage point difference; SE, 2.2), health insurance (men: 24 percentage point difference; SE, 4.5; women: 23 percentage point difference; SE, 3.6), and immigration (men: 22 percentage point difference; SE, 4.9; women: 23 percentage point difference; SE, 3.9). There were also gradients for education and family income.

PSA Testing

Among men age ≥ 50 years, 41.0% (CI, 39.4–42.5) had a PSA test within the last year. Again, men who were least likely to have had the test during the previous year (Table 4) were those with no usual source of care (11.4%; CI, 7.6–15.1), those with no health insurance (12.6%; CI, 7.2–18.0), and recent immigrants (17.4%; CI, 5.9–28.9). The greatest differences were associated with the same characteristics: a 32 percentage point difference for lack of a usual source of care (SE, 2.1) or health insurance (SE, 3.0) and a 25 percentage point difference for recent immigration (SE, 6.0).

Changes in Test Use, 1987–2000

Figure 1 shows the overall trends for men and women in recent use of cancer screening tests based on data from the 1987, 1992, 1998, and 2000 surveys. For women, the use of Pap smear, mammography, and colorectal endoscopy has increased; and the use of FOBT increased until 1998 and then stabilized. For men, use of colorectal endoscopy and FOBT increased until 1998 but may have fallen off more recently. The manner of asking the question about endoscopy changed in 2000, which may account for the decrease.

thumbnail image

Figure 1. Recent use of cancer screening tests: 1987, 1992, 1998, and 2000. Source: National Health Interview Survey. Percentages are standardized to the 2000 standard million. Pap smear: within the last 3 years, age ≥ 25 years; Mammogram: within the last 2 years, age ≥ 40 years; FOBT: fecal occult blood test within the last year, age ≥ 50 years; CRE: colorectal endoscopy within the last 3 years, age ≥ 50 years.

Download figure to PowerPoint

Table 5 summarizes the differences in Pap test, mammography, and colorectal screening use from 1987 to 2000, showing the 1987 rates and changes in percentages for 2000. To decrease disparities in screening utilization among groups, those with lower rates in 1987 should have seen the greatest growth. For Pap tests, a possible narrowing of the gap is indicated between age groups and levels of education. For colorectal cancer screening, there is an indication of decreasing disparities by race. For both tests, decreases in disparities have been small. For mammography, there appears to have been no decline in differences among groups. Groups with some of the lowest rates of screening use in 1987 show a widening gap. These include respondents with no usual source of health care (for all tests). The findings suggest the same for American Indian/Alaska Native populations for Pap tests and mammography, although the confidence intervals are too wide to allow a conclusion that is statistically significant.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

This report examines both the prevalence and long-term changes in prevalence of cancer screening practices for a broad range of historically underserved populations. It presents new data that can be compared with analyses of earlier cancer control supplements, and it broadens the focus on underserved populations to new groups, such as recent immigrants, and adds more detailed information on changes over time.

We anticipated significant improvements in test use for all population groups over the 13-year period between the initial cancer control supplement and the 2000 module. For those with the lower rates of testing in 1987, we wanted to see that use has increased at a faster pace. Although there have been measurable increases in use for most groups since 1987, there have been no major successes in overcoming disparities and no striking improvements in underserved groups compared with groups that had higher screening levels in 1987 or 1992. Some groups, notably individuals with no usual source of care and the uninsured (the latter measured since 1992), are falling further behind. When we look at the 2000 data alone, another group at risk comes to our attention repeatedly: namely, recent immigrants.

When we examine mammography specifically, we see gains for most groups of > 30 percentage points, and particularly noteworthy are the increases among African-American women. However, among women with no usual source of care, the increase was only 20 percentage points. Mammography was the only modality for which there was any significant improvement among those without a usual source of care, undoubtedly due at least in part to public health programs targeted to this subgroup of the population.31 This possibility is underscored by comparison of insurance groupings in Table 5 (for health insurance, 1992 data were compared due to the lack of insurance questions on the 1987 survey), which shows that mammography had the smallest gain for those with private or military insurance. In relation to the Healthy People 2010 objectives, the overall mammography target of 70% has been met, although several population groups are far below the target despite their gains. In addition to those with no usual source of care or no health insurance, these include women who are poorer, less educated, recent immigrants, or are among the Hispanic, Asian, or American Indian/Alaska Native populations.

The target for Pap smears (90%) has been met for both white women and black women age 25–39 years. This is good news. However, complacency is not warranted, because the same population groups are lagging behind that are lagging behind with mammography. For colorectal cancer testing, although the periods are different for Healthy People 2010 (50% target for sigmoidoscopy ever and for FOBT in past 2 years), gradients also are evident for income, education, immigration status, health insurance, usual source of care, and race/ethnicity. The results are similar for PSA testing.

Recognizing that not all cancer tests were initiated for screening purposes, the greatest deficits in utilization and the greatest disparities in use are associated with lack of access to health care (not having a usual source of care and not having health insurance) and with recent immigration to the United States, which can be related to access.32, 33 The estimated number of adults age ≥ 18 years without a usual source of care approximated 30 million in 2000 and has remained fairly steady (ranging from 15% to 22%) across the survey years examined in this study. Approximately 31 million persons age ≥ 18 years had no health insurance in 2000, up from 25 million in 1992, although the percentage of the overall population remained similar (14–15%). The estimated number of recent immigrants (< 10 years in the United States) was nearly 9 million in the 2000 survey (weighted estimates were computed from the NHIS surveys; data not shown).

Other factors consistently associated with deficits in use are Hispanic ethnicity and income below 200% of the poverty level. The data indicate that having a chronic disability may affect the use of Pap test and mammography to a significant degree for most age categories. The use of screening among disabled women may depend on the type and severity of the disability, which is discussed in greater detail by Iezzoni et al. in an analysis of 1994–1995 NHIS data.19 Education gradients for women are found in the use of mammography and Pap tests.

Some of the factors that limit analysis of these data over time are inherent in research and in the medical care system. The screening modalities and recommendations for using them have changed and evolved over the years of the cancer supplements, and the survey questions have changed to reflect this trend. For example, the colorectal screening questions originally asked about proctoscopy, a procedure largely eclipsed by sigmoidoscopy and colonoscopy. Intervals between tests also have varied in the questions. Insurance coverage was not measured annually by the NHIS until the 1990s; and, since then, the questions have broadened to capture the widening range of plans. Other limiting factors are related to the sample sizes for small populations and their resultant wide confidence intervals, shown consistently for the American Indian/Alaska Native populations (1% of the population) and the Asian populations (3–4% of the population). Although the numbers of Native Hawaiians and Pacific Islanders were too small to include as a separate entity, we felt that information for other, more sizeable subgroups of U.S. adults should not be excluded. The confidence intervals provide readers with information about the precision of the estimates. For some subgroups subdivided by age, the confidence intervals are even wider. Finally, the usual problems associated with self-reporting can produce differences in validity among the various screening modalities.

Despite the limitations, the results of the NHIS cancer control supplement should send a clear message that some of the population groups that have lagged behind in use of cancer screening still have not caught up. Differences between the highest and lowest groups, in relation to income and education, have not narrowed as much as expected. This echoes the findings of several recent reports, including those of the Kaiser Commission on Medicaid and the Uninsured and the Institute of Medicine's Committee on the Consequences of Uninsurance.34, 35 A recent analysis of the effectiveness of interventions to promote mammography among women with historically lower mammography rates found that the strongest approaches were those that enhanced access in addition to other interventions, like reminders and telephone calls.36 Successful strategies included reduced-cost mammograms; translation services; assistance with scheduling, transportation, and dependent care; and navigation through the medical system. The logic of that analysis is reiterated by the results reported here.

The U.S. Task Force on Community Preventive Services, with the CDC and NCI, is conducting additional reviews to assess the effectiveness of interventions to increase screening for colorectal, breast, and cervical cancers and will publish recommendations on effective strategies to increase screening for these cancers. These reviews and recommendations are part of a larger set of reviews and recommendations published in The Guide to Community Preventive Services (http://www.thecommunityguide.org/home_f.html).37 The Community Guide addresses a variety of health topics important to communities, public health agencies, and health care systems. It summarizes what is known about the effectiveness and cost-effectiveness of population-based interventions designed to promote health and to prevent disease, injury, disability, and premature death as well as exposure to environmental hazards. The NHIS data delineate the population groups at greatest disadvantage in relation to cancer screening. The greatest opportunities for interventions to increase mammography, Pap smears, and colorectal screening are among persons who are without a usual source of care, the uninsured, and recent immigrants.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

The authors thank Mr. Tim McNeel and Mr. James Cucinelli of Information Management Services, Inc. for their expert technical assistance.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES
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