pmc81111041254Breast Cancer Res TreatBreast Cancer Res TreatBreast cancer research and treatment0167-68061573-7217336668311084653810.1007/s10549-021-06160-4HHSPA1869220ArticleMammography use and breast cancer incidence among older U.S. womenhttp://orcid.org/0000-0002-5228-9606TurbowSara D.1WhiteMary C.2BreslauErica S.3SabatinoSusan A.2Division of Preventive Medicine, Department of Family and Preventive Medicine and Division of General Internal Medicine, Department of Medicine, Emory University School of Medicine, 49 Jesse Hill Jr Dr. SE, Atlanta, GA 30303, USADivision of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), Atlanta, GA, USADivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

Author’s contributions ST: Conception and design, data analysis and interpretation, drafting and revising article, final approval of submitted version. MW: Conception and design, data interpretation, drafting and revising article, final approval of submitted version. EB: Conception and design, data interpretation, drafting and revising article, final approval of submitted version. SS: Conception and design, data analysis and interpretation, drafting and revising article, final approval of submitted version.

Sara D. Turbow, sara.turbow@emory.edu
281202372021053202106220241881307316Purpose

The death rate for female breast cancer increases progressively with age, but organizations differ in their mammography screening recommendations for older women. To understand current patterns of screening mammography use and breast cancer diagnoses among older women, we examined recent national data on mammography screening use and breast cancer incidence and stage at diagnosis among women aged ≥ 65 years.

Methods

We examined breast cancer incidence using the 2016 United States Cancer Statistics dataset and analyzed screening mammography use among women aged ≥ 65 years using the 2018 National Health Interview Survey.

Results

Women aged 70–74 years had the highest breast cancer incidence rate (458.3 cases per 100,000 women), and women aged ≥ 85 years had the lowest rate (295.2 per 100,000 women). The proportion of cancer diagnosed at distant stage or with unknown stage increased with age. Over half of women aged 80–84 years and 26.0% of women aged ≥ 85 years reported a screening mammogram within the last 2 years. Excellent/very good/good self-reported health status (p = .010) and no dependency in activities of daily living/instrumental activities of daily living (p < .001) were associated with recent mammography screening.

Conclusion

Breast cancer incidence rates and stage at diagnosis vary by age. Many women aged ≥ 75 years receive screening mammograms. The results of this study point to areas for further investigation to promote optimal mammography screening among older women.

Older adultsMammogramBreast cancerIncidence
Introduction

Since 2009, the United States Preventive Services Task Force (USPSTF) has recommended biennial breast cancer screening with mammography for average-risk women aged 50–74 years [1]. Based on the lack of inclusion of women aged ≥ 75 years in key breast cancer screening trials and unanswered questions about reductions in advanced breast cancer and treatment morbidity from mammography screening, the USPSTF concluded that there was insufficient evidence to balance the benefits and harms of screening for women aged ≥ 75 years [1]. Uncertainty about the benefits of routine mammography screening at older ages is reflected in guidelines created by specialty societies with differing recommendations for older women [2]. For example, the American Cancer Society recommended women in good health and with life expectancy of at least 10 years continue screening [3], and the American College of Radiology recommends that screening can be individualized considering life expectancy, comorbidities, and intention to undergo treatment if cancer is diagnosed [4], and the American College of Physicians stated that average-risk women aged ≥ 75 years and those with life expectancy ≤ 10 years should discontinue screening [5]. These differences in recommendations could confuse patients and providers alike [6]. The complexity of decisions around breast cancer screening in older women is compounded by the fact that breast cancer incidence is high in this age group and the highest breast cancer mortality rates occur among women aged ≥ 75 years [7].

In light of the increasingly nuanced guidance for breast cancer screening among older women, the goals of this analysis are first, to examine recent incidence data for breast cancer among older women using a national database, and second, to describe mammography screening use among women near and beyond the upper USPSTF screening age range. These data can be used to inform future research and policy discussions regarding breast cancer screening among older women.

MethodsData sources

This was an analysis of the 2016 United States Cancer Statistics Database (USCS) [8] and the 2018 National Health Interview Survey (NHIS) [9], each the most recent year of data available at the time of study initiation. USCS is a national database covering 100% of the U.S. population that combines information from two federally funded cancer registry programs: the Centers for Disease Control and Prevention’s National Program of Cancer Registries (NCPR) and the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program (SEER) dataset [10, 11]. For 2016, all participating registries met USCS publication criteria [11].

NHIS is a yearly, cross-sectional, household, in-person survey that collects data on the health and health behaviors of a nationally representative sample of the US civilian, noninstitutionalized, population (https://www.cdc.gov/nchs/nhis/about_nhis.htm). For 2018, information was collected about the household and each family in the household, as well as a randomly selected sample child and adult in each family. The 2018 final sample adult response rate was 53.1% [12].

Incidence

All data for the incidence analysis were obtained from the 2016 USCS. Women with invasive breast cancer diagnosed at age ≥ 65 years in 2016 were included. Women aged ≥ 65 years were included so that the incidence of breast cancer among older women, both within the USPSTF screening age range and beyond it, could be examined. Incident breast cancers were defined by the International Classification of Diseases for Oncology third edition (ICD-O-3) codes (C500-C506, C508-C509) [13]. Race was categorized into four major racial groups (White, Black, American Indian and Alaska Native (AIAN), Asian/Pacific Islander), and ethnicity was categorized as Hispanic/Latino or non-Hispanic/Latino. Information about race and Hispanic ethnicity was collected separately in USCS. More information about classification of race and ethnicity in USCS is available elsewhere [14]. Stage was categorized as localized (confined to the primary site), regional (spread directly beyond the primary site or to regional lymph nodes), and distant (spread to other organs or remote lymph nodes) based on the SEER Summary Stage 2000 [15]. Receptor status was defined as estrogen receptor and/or progesterone receptor positive (ER + and/or PR +) or negative (ER− and PR−). ER/PR borderline cases were included with positive cases [16, 17].

Mammography usePopulation

Data on mammography use among women aged ≥ 65 years were obtained from the 2018 NHIS. Participants were asked “have you ever had a mammogram?” but not asked about the type of mammogram, such as digital mammography or tomosynthesis. An age range beginning at 65 years was chosen to examine mammography use among older women who were within the USPSTF screening age range compared to mammography use among women past this age range. Exclusions included women who reported ever having breast cancer (n = 419), women with missing information about mammography history or mammography use/timing (n = 150), and women who reported their most recent mammogram was not for screening (defined as answering “because of a problem,” “other reason,” “refused,” “not ascertained,” or “don’t know”) (n = 198).

Sociodemographic, access to care, and health factors

Age was categorized as 65–69, 70–74, 75–79, 80–84, and ≥ 85 years. NHIS top-codes ages of participants over 85 years old to protect confidentiality; these respondents were combined into a ≥ 85 years category. Race was categorized into five categories: White, Black, AIAN, Asian, and multiple race. Educational attainment was categorized as less than high school, completed high school/some college, college/associate degree, and graduate/professional degree.

Insurance status was categorized as any private (including Medicare with private supplemental coverage), Other Medicare (Medicare only, Medicare Advantage, or Medicare/Medicaid), and other/uninsured/unknown. Having a usual source of care was categorized as yes (clinic, health center, hospital outpatient department, and doctor’s office/HMO, “some other place,” “more than one place”) or no (no usual source of care or hospital emergency department only).

Functional status was assessed with two questions: “Because of a physical, mental, or emotional problem, do you need the help of other persons with personal care needs, such as eating, bathing, dressing, or getting around inside this home?” assessed dependency in activities of daily living (ADLs), and “Because of a physical, mental, or emotional problem, do you need the help of other persons in handling routine needs, such as everyday household chores, doing necessary business, shopping, or getting around for other purposes?” assessed dependency in instrumental activities of daily living (IADLs) [18]. Self-reported health status was categorized as “excellent/very good/good” or “fair/poor.”

Analysis

Breast cancer incidence analyses were conducted in SEER*Stat Version 8.3.6 (https://seer.cancer.gov/seerstat/). Incidence rates per 100,000 women were age adjusted to the 2000 U.S. standard population [14]. Rates are presented by age group as well as by race, ethnicity, stage, and hormone receptor (estrogen and progesterone receptor) status.

For all NHIS analyses, SAS-callable SUDAAN version 11.0 (Research Triangle Institute, Research Triangle, NC) was used with survey weights and design variables to account for the complex sample design. Findings are reported as weighted proportions and 95% confidence intervals. Proportions with a relative standard estimate ≥ 30% or denominator < 50 were suppressed. Mammography use was defined by time since most recent mammogram and categorized as ≤ 2 years ago, > 2–5 years ago, > 5 years ago, or never. We report mammography use for all women aged ≥ 65 years by age group.

To identify groups of women who received recent mammograms beyond the upper USPSTF screening age range, we also examined mammography use among women aged ≥ 77 years. This analysis was restricted to women aged ≥ 77 years to capture mammograms done within the prior two years but after age 74 years, the upper USPSTF screening age range. For example, if a 77-year-old woman reported on the NHIS that her last mammogram had been ≤ 2 years ago, she would have received that mammogram when she was at least 75 years old—timing that would put her beyond the upper age recommendation offered by USPSTF. We performed this sub-analysis to obtain more granular information about mammography use among older women past the USPSTF-recommended screening age limit. Differences in mammography use by sociodemographic, health, and access-to-care factors among these women were examined using chi-squared tests. Statistical significance was set at p < 0.05.

Results

Table 1 displays the incidence and 95% confidence interval of breast cancer across demographic categories and tumor characteristics in 2016. Women aged 70–74 years had the highest incidence of breast cancer (458.3 cases per 100,000 women) and women aged ≥ 85 years the lowest (295.2 per 100,000 women). Within age categories, most cancers were diagnosed at a localized stage; the proportion from highest to lowest by age group was 71.9% for ages 70–74, 70.4% for ages 75–79, 70.1% for 65–69, 67.7% for 80–84, and 62.0% for ≥ 85 (data not shown). The incidence rates for distant stage cancer and cancer of unknown stage also varied by age group; the highest incidence rates for both occurred in age groups above 74 years. The proportion of breast cancer diagnosed at distant stage increased with age and was 2.2% for 65–69, 2.3% for 70–74, 2.7% for 75–79, 3.4% for 80–84, and 6.6% for ≥ 85 years (data not shown). The pattern of rates of ER + and/or PR + cancers by age group was similar to that of breast cancer overall. As for stage at diagnosis, rates of unknown ER/PR status increased with age.

Characteristics of women in the analysis of mammography use overall and by age group are shown in Table 2. Of these women, 31.2% (n = 1085) were aged 65–69 years, 25.8% (n = 898) were 70–74 years old, 18.2% (n = 635) were 75–79 years old, 12.5% (n = 434) were 80–84 years old, and 12.3% (n = 429) were 85 years old or older. Greater percentages of women aged 65–74 years reported higher educational attainment and at least good health status.

Regarding mammography use, 64.4% (n = 2,226) reported having a mammogram within 2 years, 14.7% (n = 506) more than 2 but less than 5 years, 15.8% (n = 558) over 5 years ago, and 5.2% (n = 191) reported never having a mammogram. The percentage of women reporting a mammogram within the prior 2 years decreased with increasing age (Fig. 1).

Table 3 displays demographic and clinical variables by time since mammography among women aged ≥ 77 years. Overall, 46.8% of women aged ≥ 77 years had a mammogram within the last 2 years. The proportion who reported their last mammogram occurred less than 2 years ago decreased with age, from over half of women aged 77–84 years to 26.0% of women aged ≥ 85 years. There was no difference in time since last mammography by race, ethnicity, or region. Women who reported Medicare coverage versus private insurance, not completing high school, fair or poor health, or dependency in one or more ADLs or IADLs had lower use of recent mammography than other women.

Discussion

This analysis of national data on breast cancer incidence and screening mammography use in older women reveals several points. This analysis found that more than 70% of women aged 65–74 years–for whom the USPSTF recommends routine screening—have received it. Although breast cancer incidence decreased with age from its peak among women aged 70–74 years, incidence remained high among women aged 75–79 years, beyond the upper USPSTF screening age range for recommended routine screening. Many women received screening mammograms at ages ≥ 75 years. However, approximately one quarter of women aged 65–74 years, for whom routine screening is recommended by multiple expert organizations, had not received a mammogram in the prior 2 years. Thus, many women may not be up-to-date with recommended screening as they approach the age at which screening may not be encouraged.

Mammography use declined with increasing age, as did breast cancer incidence after age 74 years. In contrast, the incidence rate of distant stage disease at diagnosis was highest in the 75–79 and 80–84-year-old age groups. Findings of high breast cancer incidence rates and increased risk of advanced disease at diagnosis for some after age 74 years may suggest a potential benefit from continued screening for some older women. Hartman et al. examined screening-detected breast cancer among women aged ≥ 75 years at one institution and reported a favorable cancer detection rate and a high proportion of early stage cancers [6]. A recent review also concluded that screening performance metrics improved with age [7]. However, a study of Medicare beneficiaries concluded that annual mammography screening after age 75 years did not reduce breast cancer mortality over an 8-year time period [19]. Whether newer screening technologies will improve the balance of benefits and harms for older women is uncertain [20].

Our findings of recent screening among women aged ≥ 77 years are consistent with previous work reporting continued screening at older ages after the USPSTF had set an upper age limit [21]. Torke and colleagues reported that some older adults felt stopping cancer screening would “require a major decision,” whereas continuing screening would not. They also found that patients felt mistrustful of panel recommendations about screening cessation, and that a recommendation to stop screening from their physician might threaten their trust [22].

Our study suggests that for some women, neither age nor overall health are considered reasons to stop screening. Among women aged ≥ 77 years who self-reported their health as “fair” or “poor,” 39.1% had a mammogram within the last two years. Mammography’s potential benefit to an individual patient has been based largely on her life expectancy, and there is an estimated 10-year lag time for survival benefit from mammography [23, 24]. Several studies have suggested that comorbidities and life expectancy are associated with mammography screening among older women [2527], but many women in their 70 s and 80 s with shorter life expectancies receive mammograms [26, 28]. In 2004, prior to the USPSTF recommendation of an upper screening age limit, Schonberg et al. reported that over 50% of women aged ≥ 80 years had received a screening mammogram in the previous 2 years, including 43.9% of women with two or more significant diseases [25]. Lee et al. recently summarized the available evidence on screening after age 74 years and concluded that more than age alone should be considered, including overall health status [7]. As Brawley has proposed, breast cancer screening recommendations for older women in the future are likely to be tailored to the individual woman rather than based on age, to identify women who are at risk for breast cancer and in good health and therefore likely to benefit from screening [29].

In our study, women who reported dependency in one or more ADLs or IADLs were more likely to have had a mammogram > 5 years ago or never (59.1% for ADLs, 54.8% for IADLs), which is consistent with previous work by Warner and colleagues who reported that women with complex multimorbidity were less likely to have had a screening mammogram. However, women who thought they might live another 10–15 years were more likely to have a screening mammogram, even if their health status or advanced age suggested otherwise [30].

Information about healthcare provider discussions with women who had a mammogram after age 74 years was not collected on the 2018 NHIS and therefore not examined in this study. Schoenborn and colleagues suggest that communication about the benefits and risks of screening and shifted health priorities could be preferable to discussions about life expectancy for both primary care providers and older adults [31]. A recent study showed that some clinicians hold negative opinions about the value of life expectancy predictions for cancer screening decisions. Others have underscored the importance of considering a woman’s goals and values in individualizing screening decisions [32]. Decision aids may be useful when engaging older women in conversations about screening [32].

We found that the incidence rate of “unknown” stage disease—possibly suggesting no or limited further workup done after diagnosis—increased with increasing age. The highest rates of unknown stage (6.6% of incident cases) and missing both ER and PR status (8.9% of incident cases) occurred among women aged ≥ 85 years. This raises questions as to whether diagnostic workup or data reporting for breast cancer among women at the oldest ages differs from that of women at younger ages. Many women, particularly those in the oldest age groups, may not receive additional workup after their diagnosis of breast cancer, which may be consistent with a decision not to treat.

Limitations

This analysis has several important limitations. First, both datasets only report specific ages up to age 85 years. The NHIS relies on patient self-report for its data; medical records are not accessed to confirm the accuracy of an individual’s statements. Although women who responded that their mammogram was performed because of a problem were excluded from the analysis, women may not have accurately understood the reason for their mammogram. Thus, the proportion of women who received a screening mammogram may have been overestimated. Information was not obtained on family history, whether a provider had discussed screening recommendations, or a woman’s perceived life expectancy. The sensitivity of recall of timing of last screening mammogram declines with increasing time intervals and is reported to be around 80% at one year post-mammogram [33]. Categorizing mammography use into multi-year groups may reduce misclassification of screening dates due to imprecise recall. The overall response rate for the 2018 NHIS was 53%, so non-response bias remains a possibility. It is unknown whether response rates vary with age, however, survey weights are adjusted for non-response [12].

Conclusions

This study provides updated incidence rates of breast cancer by age and stage at diagnosis among women aged ≥ 65 years using national data covering 100% of the U.S. population; it also describes differences in breast cancer incidence and screening mammography use by age as women approach and live beyond the upper USPSTF screening age range. Our findings suggest that many women received a recent screening mammogram at ages ≥ 75 years, even women who self-reported “fair” or “poor” health. In addition, the proportion of breast cancers diagnosed at later stages increased with age, raising questions about possible missed opportunities for early diagnosis through screening for some older women. These findings point to potential problems with over-screening for some older women and underscreening for others. To promote optimal mammography screening among older women, future studies could investigate the systemic reasons why older women are or are not screened. In addition, the quality of provider communications with older women about screening use could be examined.

Acknowledgements

The authors would like to thank Jessica King and Zahava Berkowitz for statistical and programming consultation. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the National Cancer Institute.

Funding

Dr. Turbow’s work on this project and paper was supported in part by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under grant number D33HP31669 and title “Preventive Medicine Residencies” for $1,936,878. This information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS, or the U.S. Government.

Conflict of interest

Dr. Turbow has received grant support from Gilead Sciences, Inc. and Merck for research unrelated to this work. No other financial or personal conflicts exist. No other authors reported conflicts of interest.

Code availability SAS and SUDAAN code will be made available upon reasonable request.

Data availability

All data is free and available online at the links included in the manuscript and references.

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Timing of Most Recent Screening Mammogram among Women ≥ 65 Years Old, United States 2018

Age-Adjusted Incidence of Invasive Breast Cancer among Women Aged ≥ 65 Years by Age Group, 2016

Age group (years)
65–6970–7475–7980–84≥ 85
Incidence rated(95% CI)(n = 8,889,353)Incidence rated(95% CI)(n = 6,360,203)Incidence rated(95% CI)(n = 4,647,676)Incidence rated(95% CI)(n = 3,413,802)Incidence rated(95% CI)(n = 4,154,029)
Overall417.7 (413.4–421.9)N = 37,127458.3 (453.0–463.6)N = 29,147442.7 (436.7–448.8)N = 20,575393.5 (386.9–400.2)N = 13,433295.2 (290.0–300.5)N = 12,263
Race
 White423.3 (418.6–428.0)N = 31,174468.9 (463.2–474.8)N = 25,109452.8 (446.2–459.5)N = 17,797400.3 (393.1–407.6)N = 11,677296.4 (290.8–302.0)N = 10,744
 Black406.3 (393.8–419.1)N = 3,992418.4 (402.8–434.5)N = 2,705413.7 (395.4–432.6)N = 1,918383.0 (362.0–405.0)N = 1,243301.1 (283.1–319.9)N = 1,045
 AIANa273.5 (238.2–312.5)N = 216267.5 (224.4–316.4)N = 136265.6 (213.6–326.5)N = 90207.3 (151.2–277.4)N = 45141.2 (95.3–201.6)N = 30
 APIb282.2 (267.1–297.9)N = 1,305293.0 (274.3–312.8)N = 904254.0 (233.3–276.0)N = 558206.5 (184.2–230.7)N = 311178.7 (158.6–200.6)N = 287
Ethnicity
 Hispanic/Latino328.2 (315.5–341.2)N = 2,534333.6 (318.4–349.3)N = 1,804310.7 (293.4–328.8)N = 1,204259.5 (240.7–279.4)N = 12,729205.5 (189.2–222.9)N = 586
 Non-Hispanic/Latino426.1 (421.7–430.7)N = 34,591469.9 (464.3–475.5)N = 27,343454.7 (448.3–461.1)N = 19,370405.1 (398.0–412.2)N = 704301.8 (296.4–307.3)N = 11,677
Stage
 Localized292.9 (289.3–296.4)N = 26,034329.7 (325.3–334.2)N = 20,970311.9 (306.8–317.0)N = 14,496266.6 (261.1–272.1)N = 9,100182.9 (178.8–187.1)N = 7,598
 Regional93.4 (91.4–95.4)N = 8,30394.5 (92.2–96.9)N = 6,01291.4 (88.7–94.2)N = 4,25085.6 (82.5–88.7)N = 2,92167.8 (65.3–70.4)N = 2,817
 Distant22.0 (21.0–23.0)N = 1,95523.4 (22.3–24.6)N = 1,49027.5 (26.0–29.0)N = 1,27727.9 (26.1–29.7)N = 95224.9 (23.4–26.5)N = 1,036
 Unknown9.4 (8.7–10.0)N = 83310.6 (9.8–11.4)N = 67511.9 (10.9–12.9)N = 55213.4 (12.2–14.7)N = 45919.5 (18.2–20.9)N = 811
Receptor Status
 ER + or PR +352.3 (348.4–356.2)N = 31,317387.8 (383.0–392.7)N = 24,664371.7 (366.2–377.3)N = 17,275325.6 (319.6–331.8)N = 11,117231.7 (227.1–236.4)N = 9,625
 ER and PR−51.7 (50.2–53.2)N = 4,59554.6 (52.8–56.5)N = 3,47551.9 (49.8–54.0)N = 2,41148.8 (46.5–51.2)N = 1,66736.9 (35.1–38.8)N = 1,533
 Unknown13.7 (12.9–14.5)N = 1,19715.8 (14.9–16.9)N = 1,00219.1 (17.9–20.4)N = 88719.0 (17.6–20.5)N = 64426.6 (25.1–28.2)N = 1,095

AIAN = American Indian/Alaska Native, b. API = Asian/Pacific Islander, c. ER = Estrogen Receptor, PR = Progesterone Receptor

Data Source: NPCR and SEER Incidence – U.S. Cancer Statistics Public Use Research Database, Nov 2018 submission (2001–2016), United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Released June 2019, based on November 2018 submissions. Available at www.cdc.gov/cancer/public-use

Data are from population-based registries that participate in CDC’s National Program of Cancer Registries and/or NCI’s Surveillance, Epidemiology, and End Results Program and meet high-quality data criteria. These registries cover approximately 100% of the United States population

Rates are per 100,000 women and are age adjusted to the 2000 U.S. standard population (19 age groups – Census P25–1130)

Demographics of Women Aged ≥ 65 Years, United States, 2018

Age group (years)
Overall Weighted %(95% CI)(n = 3,481)a65–69 Weighted %(95% CI)(n = 1,085)a70–74 Weighted %(95% CI)(n = 898)a75–79 Weighted %(95% CI)(n = 635)a80–84 Weighted %(95% CI)(n = 434)a≥ 85 Weighted %(95% CI)(n = 429)a
Race
 White83.0% (81.0–84.8)(n = 2,889)82.2% (79.1–88.0)n = 88282.3% (78.9–85.3)n = 74483.4% (79.5–86.6)n = 53184.6% (79.7–88.4)n = 36384.4% (79.2–88.5)n = 369
 Black9.5% (8.4–10.8) (n = 373)9.8% (7.8–12.0) n = 12210.2% (8.0–12.9) n = 9910.3% (7.9–13.3) n = 73 * *
 AIANb * * * * * *
 Asian5.1% (4.1–6.4)(n = 133) * * * * *
 Multiracial1.5% (1.1–2.2)(n = 54) * * * * *
Ethnicity
 Non-Hispanic Latino90.6% (89.1–92.0)(n = 3201)90.0% (87.3–92.3)n = 98890.7% (88.0–92.8)n = 82790.8% (87.6–93.3)n = 59090.4% (86.3–93.3)n = 39592.4% (88.6–94.9) n = 401
 Hispanic/Latino9.4% (8.0–10.9)(n = 280)10.0% (7.8–12.7)n = 979.3% (7.2–12.0)n = 719.2% (6.7–12.5)n = 459.7% (6.7–13.7)n = 397.7% (5.1–11.4)n = 28
Insurance Status
 Any Private39.9% (37.8–42.1)(n = 1461)42.9% (39.6–46.3)n = 48240.5% (36.5–44.7)n = 37134.9% (30.6–39.4)n = 24238.8% (33.5–44.4)n = 17938.9% (33.2–44.9) n = 187
 Other Medicarec52.6% (50.4–54.8)(n = 1789)49.2% (45.7–52.6)n = 53154.1% (49.9–58.3)n = 48055.8% (51.3–60.3)n = 34655.2% (49.7–60.7)n = 22751.3% (45.3–57.3)n = 205
 Other/Uninsured/Unknown8.0% (6.0–10.5)n = 725.4% (3.9–7.4)n = 479.3% (6.6–12.4)n = 476.0% (3.9–9.0)n = 289.9% (6.9–13.9)n = 37
Educational Level
 Less than High School15.9% (14.4–17.6)(n = 564)10.9% (8.9–13.4)n = 12116.0% (13.3–19.1)n = 14013.8% (12.7–19.4)n = 10123.7% (19.1–28.9)n = 9922.0% (17.8–26.8) n = 103
 High School/Some College46.5% (44.4–48.6) (n = 1651)42.2% (38.7–45.7) n = 46444.6% (40.8–48.4) n = 41051.2% (46.7–55.7) n = 32948.9% (43.3–54.6) n = 21353.3% (47.3–59.3) n = 235
 College/Associate’s Degree26.2% (24.5–28.0) (n = 886)32.3% (29.0–35.7) n = 35026.5% (23.4–29.9) n = 23723.6% (20.0–27.7) n = 14419.7% (15.8–24.4) n = 8618.7% (14.0–24.6) n = 69
 Advanced Degree10.5% (9.3–11.8) (n = 364)13.4% (11.3–25.8) n = 14412.4% (9.9–15.5) n = 1098.1% (6.0–11.0) n = 577.7.% (5.1–11.4) n = 364.4% (2.6–7.6) n = 18
Region
 Northeast20.0% (18.4–21.7) (n = 635)21.7% (18.3–25.6) n = 20717.9% (15.2–21.0) n = 14517.6% (14.4–21.3) n = 10420.2% (16.2–25.0) n = 8523.5% (18.8–29.0) n = 94
 Midwest22.0% (20.2–23.8)(n = 826)20.6% (17.8–23.7) n = 24221.7% (18.6–25.2) n = 21323.7% (20.1–27.6) n = 15322.0% (17.5–27.2) n = 9924.1% (19.4–29.5) n = 119
 South35.4% (33.4–37.5)(n = 1259)35.3% (32.0–38.8) n = 39138.0% (34.1–42.0) n = 34637.5% (33.3–42.0) n = 25133.4% (28.4–38.8) n = 15128.8% (23.8–3 4.4) n = 120
 West22.6% (20.6–24.7)(n = 761)22.3% (19.4–25.6) n = 24522.4% (19.0–26.4) n = 19421.2% (17.6–25.4) n = 12724.5% (19.3–30.5) n = 9923.6% (18.7–29.3) n = 96
Usual Source of Care
 Yes96.1% (95.2–96.8) (n = 3341)95.1% (93.1–96.6) n = 102995.9% (94.0–97.2) n = 86297.1% (95.1–98.2) n = 61696.8% (94.6–98.1) n = 41896.9% (94.3–98.4) n = 416
 No3.9% (3.2–4.8) (n = 140)4.9% (3.4–6.9) n = 564.1% (2.8–6.0) n = 363.0% (1.8–4.9) n = 193.2% (1.9–5.4) n = 16 *
Perceived Health Status
Excellent/Very Good/Good78.2% (76.3–79.9) (n = 2763)81.9% (78.4–85.0) n = 89980.9% (77.9–83.6) n = 72376.3% (72.0–80.1) n = 49473.7% (68.0–78.7) n = 33068.8% (63.1–73.9) n = 317
Fair or Poor21.8% (20.1–23.7) (n = 718)18.1% (15.1–21.6) n = 18619.1% (16.4–22.1) n = 17523.7% (19.9–28.0) n = 14126.3% (21.3–32.0) n = 10431.2% (26.1–36.9) n = 112
Functional Status
 Dependency ≥ 1 ADLd
  No92.4% (91.1–93.5) (n = 3241)96.8% (95.4–97.8) n = 104695.0% (92.9–96.5) n = 85591.2% (88.0–93.6) n = 58389.1% (83.9–92.8) n = 39778.7% (72.7–83.8) n = 360
  Yes7.6% (6.5–8.9) (n = 240)3.2% (2.2–4.6) n = 395.0% (3.5–7.1)n = 438.8% (6.4–12.0) n = 5210.9% (7.2–16.2) n = 3721.3% (16.3–27.3) n = 69
 Dependency ≥ 1 IADLe
  No87.1% (85.7–88.4) (n = 3013)94.8% (93.2–96.0) n = 102089.7% (87.0–91.9) n = 80486.8% (83.5–89.5) n = 54980.2% (75.0–84.5) n = 34566.6% (60.9–71.9) n = 295
  Yes12.9% (11.6–14.3) (n = 468)5.2% (4.0–6.8) n = 6510.3% (8.1–13.0) n = 9413.2% (10.5–16.5) n = 8619.8% (15.5–25.0) n = 8933.4% (28.1–39.1) n = 134

Unweighted numbers reported

AIAN = American Indian/Alaska Native

Medicare includes Medicare only, Medicare Advantage, and dual eligible (Medicare/Medicaid)

ADL = Activities of Daily Living

IADL = Instrumental Activities of Daily Living

Estimate suppressed because it did not meet reliability criteria

Data Source: National Health Interview Survey, 2018

Time Since Most Recent Mammography in Women 77 Years Old and Older, 2018

Screening GroupScreened ≤ 2 Years Ago Weighted % (95% CI) (n = 562)Screened > 2- ≤ 5 Years Ago Weighted % (95% CI) (n = 233)Screened > 5 Years Ago or Never Screened Weighted % (95% CI) (n = 407)p
Age (years)
 77–7963.0% (56.6–69.0) (n = 214)18.8% (14.4–24.2) (n = 66)18.2% (13.7–23.9) (n = 59) < 0.001
 80–8451.1% (45.5–56.6) (n = 227)18.2% (14.2–23.0) (n = 81)30.7% (25.7–36.2) (n = 126)
 ≥8526.0% (21.4–31.3) (n = 121)20.8% (16.1–26.4) (n = 86)53.2% (47.4–58.9) (n = 222)
Race
 White46.1% (42.7–49.6) (n = 476)19.5% (16.7–22.7) (n = 196)34.4% (30.9–38.0) (n = 336)0.346
 Black51.7% (41.8–61.5) (n = 61)15.3% (9.7–23.3) (n-22)33.0% (24.1–43.3) (n = 42)
 AIANa * * *
 Asian * * *
 Multiracial * * *
Ethnicity
 Non-Hispanic Latino45.9% (42.6–49.3) (n = 518)19.0% (16.3–22.0) (n = 215)35.1% (31.8–38.5) (n = 376)0.822
 Hispanic/Latino42.9% (33.7–52.6) (n = 44)21.9% (13.3–33.9) (n = 18)35.2% (26.3–45.2) (n = 31)
Insurance Status
 Any Private51.5% (46.4–56.6) (n = 256)19.7% (15.9–24.2) (n = 98)28.8% (24.4–33.5) (n = 144) 0.017
 Other Medicare42.1% (37.7–46.5) (n = 265)18.6% (15.1–22.7) (n = 117)39.3% (34.8–44.1) (n = 227)
 Uninsured/Other/Unknown41.6% (31.5–52.5) (n = 41)21.4% (13.1–32.8) (n = 18)37.0% (27.0–48.3) (n = 36)
Educational Level
 Less than High School35.9% (29.5–42.8) (n = 104)22.4% (16.6–29.5) (n = 52)41.7% (34.3–49.6) (n = 106) 0.016
 High School/Some College46.8% (42.3–51.5) (n = 294)16.3% (13.3–19.8) (n = 111)36.9% (32.5–41.6) (n = 221)
 College/Associate’s Degree49.2% (40.8–57.6) (n = 113)22.2% (15.6–30.5) (n = 49)21.9% (16.1–36.4) (n = 63)
 Advanced Degree52.9% (40.4–65.0) (n = 47)23.8% (14.1–37.3) (n = 19)23.4% (13.9–36.6) (n = 16)
Region
 Northeast42.0% (36.0–48.2) (n = 102)19.5% (13.8–26.8) (n = 43)38.5% (31.9–45.6) (n = 91)0.562
 Midwest45.6% (39.3–51.9) (n = 145)22.1% (17.1–28.0) (n = 69)32.4% (26.7–38.6) (n = 94)
 South48.8% (43.3–54.4) (n = 204)18.2% (14.2–23.2) (n = 70)32.9% (27.6–38.7) (n = 134)
 West44.4% (37.5–51.5) (n = 111)17.6% (12.7–23.8) (n = 51)38.1% (31.3–45.3) (n = 88)
Usual Source of Care
 Yes46.7% (43.5–50.0) (n = 556)19.4% (16.8–22.3) (n = 227)33.9% (30.8–37.2) (n = 380) < 0.001
 No * * *
Perceived Health Status
 Excellent/Very Good/Good48.1% (44.3–52.0) (n = 436)20.4% (17.4–23.8) (n = 182)31.4% (28.0–35.2) (n = 288) 0.010
 Fair or Poor39.1% (32.8–45.7) (n = 126)16.2% (12.0–21.6) (n = 51)44.7% (37.8–51.8) (n = 119)
Functional Status
Dependency in ≥ 1 ADLb
 No50.2 (46.8–53.6) (n = 535)18.6 (16.0–21.5) (n = 206)31.2 (28.0–34.6) (n = 327) < 0.001
 Yes17.4% (11.3–25.9) (n = 27)23.5% (15.1–34.6) (n = 27)59.1% (48.4–69.0) (n = 80)
Dependency in ≥ 1 IADLc
 No51.2 (47.5–54.9) (n = 482)19.5 (16.6–22.8) (n = 182)29.3 (26.0–33.0) (n = 268) < 0.001
 Yes26.7% (21.1–33.1) (n = 80)18.5% (13.5–24.8) (n = 51)54.8% (47.4–62.0) (n = 139)

Boldface indicates statistical significance p < 0.05

Percentages shown are weighted percentages. Unweighted numbers reported

Estimate suppressed because it did not meet reliability criteria

AIAN = American Indian/Alaska Native

ADL = Activities of Daily Living

IADL = Instrumental Activities of Daily Living

Data Source: National Health Interview Survey, 2018