Abstract
Importance
The likelihood of benefit from a preventive intervention in an older adult depends on its time-to-benefit and the adult’s life expectancy. For example, the time-to-benefit from cancer screening is >10 years, so adults with <10-year life expectancy are unlikely to benefit.
Objective
To examine receipt of screening for breast, prostate, or colorectal cancer and receipt of immunizations by 10-year life expectancy.
Design
Analysis of 2019 National Health Interview Survey.
Participants
8,329 non-institutionalized adults >65 years seen by a healthcare professional in the past year, representing 46.9 million US adults.
Main Measures
Proportions of breast, prostate, and colorectal cancer screenings, and immunizations, were stratified by 10-year life expectancy, estimated using a validated mortality index. We used logistic regression to examine receipt of cancer screening and immunizations by life expectancy and sociodemographic factors.
Key Results
Overall, 54.7% of participants were female, 41.4% were >75 years, and 76.4% were non-Hispanic White. Overall, 71.5% reported being current with colorectal cancer screening, including 61.4% of those with <10-year life expectancy. Among women, 67.0% reported a screening mammogram in the past 2 years, including 42.8% with <10-year life expectancy. Among men, 56.8% reported prostate specific antigen screening in the past two years, including 48.3% with <10-year life expectancy. Reported receipt of immunizations varied from 72.0% for influenza, 68.8% for pneumococcus, 57.7% for tetanus, and 42.6% for shingles vaccination. Lower life expectancy was associated with decreased likelihood of cancer screening and shingles vaccination but with increased likelihood of pneumococcal vaccination.
Conclusions
Despite the long time-to-benefit from cancer screening, in 2019 many US adults age >65 with <10-year life expectancy reported undergoing cancer screening while many did not receive immunizations with a shorter time-to-benefit. Interventions to improve individualization of preventive care based on older adults’ life expectancy may improve care of older adults.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11606-023-08439-2.
KEY WORDS: preventive care, older adults, life expectancy, time to benefit, cancer screening, immunizations
Introduction
Numerous preventive interventions (e.g., cancer screenings, immunizations) are recommended for older adults; however, for high-value preventive care, experts recommend comparing an older adult’s life expectancy to the time-to-benefit from the preventive intervention to ensure some chance of benefit.1 For example, on average it takes 10 years for one of out of 1,000 adults to avoid death from breast (women only) or colorectal cancer (CRC), as a result of screening.2 Therefore, adults with <10-year life expectancy are unlikely to benefit from cancer screening and are vulnerable to the immediate risks (e.g., anxiety or complications from work-up of cancer, harms from unnecessary treatments). Despite this, approximately 50% of adults >65 years at high-risk (50-74%) of 9-year mortality reported screening for prostate, breast, and/or colorectal cancer in the 2000-2010 National Health Interview Survey (NHIS); an annual population-based survey of non-institutionalized U.S. adults.3 Meanwhile, 32% of adults >65 did not receive an influenza vaccination and 40% did not receive a pneumococcal vaccination in 2010 despite trials showing benefits within months.4–7
Efforts have been made over the last ten years to increase the benefits and decrease harms of preventive interventions for older adults. In 2011, the Center for Medicare Services (CMS) incentivized Annual Wellness Visits (AWVs) for adults >65.8 In 2012, the American Board of Internal Medicine launched the Choosing Wisely campaign, which warns about potential harms of screening older adults with <10-year life expectancy for cancer.9, 10 Subsequently, many professional organizations revised their guidelines to recommend against cancer screening for adults with <10-year life expectancy.11–13 To help clinicians and older adults consider life expectancy in healthcare decisions, in 2012, researchers developed a unique website (www.eprognosis.ucsf.edu) of evidence-based prognostic indices for estimating life expectancy based on overall health rather than a disease-specific estimate.14, 15 This website is accessed over 15,000 times per month and the tools it features have been validated.16–18 However, the US Preventive Services Task Force (USPSTF) still uses age for suggested cessation of cancer screening; specifically, age 75 for breast cancer, 70 for prostate cancer, and 76 for CRC.19–21
Little is known about how preventive interventions such as cancer screenings and immunizations are currently prioritized in older adults based on life expectancy. Therefore, we examined receipt of cancer screening and immunizations in adults >65 using 2019 NHIS pre-pandemic data. Although cancer screening declined during the pandemic, studies suggest that screening is rising and approaching pre-pandemic levels.22–24 Due to efforts to individualize preventive care for older adults over the past decade, we hypothesized that adults >65 with lower life expectancy participating in the 2019 NHIS would be less likely to be screened than those with higher life expectancy and that cancer screening among adults with <10-year life expectancy would be uncommon (i.e., <30%). We further hypothesized that receipt of immunizations would not be associated with life expectancy since immunizations have a shorter time-to-benefit and thus may benefit nearly all older adults.6, 7, 25
Methods
Data Source
The NHIS is a large, nationally representative, in-person household interview survey of non-institutionalized U.S. civilians conducted annually by the U.S. Census Bureau for the National Center for Health Statistics. NHIS collects participant demographics, health history, and medical service utilization. Its sampling design uses stratification clustering, and oversampling of specific subgroups.26 Within households, one “sample adult” per family is randomly selected to participate. To better meet users’ needs, in 2019, NHIS updated its content and included preventive health topics. The 2019 NHIS household response rate was 61.1%.
Participants
Among 31,997 sample adult respondents to the 2019 NHIS, 8,329 were ≥65 and reported having seen their doctor or healthcare professional in the past year, representing 46.9 million US adults (eFigure1). We chose to limit our sample to adults who saw a healthcare professional in the past year since many preventive services are delivered during an encounter and because patients often prefer to discuss stopping cancer screening with their clinicians.27
Life Expectancy
For each participant, we estimated 10-year life expectancy using the Schonberg index; the only index, to our knowledge, developed and validated to estimate 10-year prognosis in NHIS.16–18 The index was developed and validated using 1997-2004 NHIS data with mortality follow-up through 2011. It includes 11 risk factors independently and significantly associated with mortality, including age, sex, cigarette use, body mass index, function, mobility, prior year hospitalizations, perceived health, and history of emphysema, diabetes, and cancer (excluding non-melanoma skin cancers). As done previously, we considered respondents with >50% 10-year mortality risk (≥ 10 points) to have a life expectancy <10-years since life expectancy is the average survival of a population.28
The 2019 NHIS redesign affected three questions in the index: 1) instead of asking about difficulty with walking 3 city blocks, the 2019, NHIS asks about difficulty walking 1 OR 5 city blocks; 2) instead of asking about number of prior year hospitalizations (coded as 0, 1, or 2+), the 2019 NHIS asks whether participants were hospitalized in the past year (yes/no); and 3) the wording for a question on difficulty getting around and household chores changed to difficulty doing errands and shopping (eTable1 details these changes). For our primary analyses, we considered participants who reported difficulty walking 5 city blocks to have mobility difficulty (42% of our 2019 cohort reported this difficulty similar to the proportion reporting difficulty walking 3 city blocks in the original development cohort) and we assumed that participants who were hospitalized in the past year were hospitalized once.17 In sensitivity analyses, we re-estimated life expectancy defining mobility by having difficulty walking a block and/or assuming participants who were hospitalized were hospitalized at least twice.
Preventive Care Measures
Our primary outcomes were self-reported receipt of cancer screening using USPSTF screening intervals and receipt of immunizations using Center for Disease Control and Prevention (CDC) timelines (detailed in eTable2 and eTable3). Current cancer screening was defined as routine mammography within 2 years, routine prostate specific antigen (PSA) screening within 2 years, and routine colonoscopy within 10 years, stool testing within 1 year, or stool-DNA testing within 3 years for CRC.19–21 NHIS specifically asks participants if their most recent mammogram, PSA, or colonoscopy was done as part of a routine exam or because of a problem. We excluded participants who reported a test done due to a problem during the time-threshold the USPSTF uses to define current screening. For CRC screening, we also excluded 356 participants (<1% of participants) because they reported recent flexible sigmoidoscopy or CT colonography and NHIS did not assess whether these tests were screening or diagnostic tests (eFigure2). Current immunizations were defined as influenza vaccination within the past year, any shingles vaccination, any pneumococcal vaccination, and any tetanus vaccine within 10 years.29 eFigures2-8 present the sample inclusion/exclusion diagrams for each outcome.
Statistical analysis
Analyses were performed using SAS v9.4 survey procedures to account for the complex sampling design and data were weighted to reflect national estimates.26 We analyzed the proportion of adults receiving preventive interventions overall and by life expectancy using chi-square tests. For cancer screening we also analyzed receipt by USPSTF guideline-recommended age-thresholds (age 70 for prostate cancer, age 75 for breast cancer, and age 76 for CRC). In multivariable logistic regression models we examined the relationship between participant 10-year life expectancy and reported receipt of preventive interventions adjusting for participant age, sex (except for breast/prostate cancer screening), insurance, race/ethnicity, marital status, region, educational attainment, income, and having a prior year “wellness visit, physical, or general purpose check-up”; factors previously shown to be associated with receipt of preventive care.28, 30–32 We also tested if there was an interaction between wellness visits and life expectancy on receipt of preventive interventions. P-values <0.05 were considered statistically significant. To adjust for multiple hypothesis testing, we used the Holm-Sidak procedure (to control for the familywise error rate). To facilitate interpretation of results, we present relative risks rather than odds ratios. Relative risk estimates and tests of pairwise differences with the reference group were calculated using the SAS 9.4 NLMEANS macro on the output from PROC SURVEYLOGISTIC.8, 26, 33
Results
Of the 8,329 participants, 8.3% were Hispanic, 4.4% were non-Hispanic Asian, and 9.1% were non-Hispanic Black; 41.4% were >75; 27.5% had a high-school education or less; and 5.0% of surveys were completed by proxy (8.5% for adults >75), Table 1. Participants were more likely to be from the south (37.9%) than other regions. Most (54.5%) had Private/Medicare insurance, 28.5% had Medicare Advantage plans, and 7.3% were Medicare/Medicaid dually eligible; 80.2% reported a prior year wellness visit. Overall, 38.8% of participants had <10-year life expectancy including 90.9% of women >85 and 100% of men >85. Regardless of which NHIS 2019 variables were used to define mobility and hospitalizations in the index, life expectancy estimates were similar (eTable4).
Table 1.
Screening Sample Characteristics by Gender and Age
| Overall N=8,329 47.0M |
Women N=4,771 25.7M |
Men N=3,558 21.3M |
|
|---|---|---|---|
| Characteristic | % (SE) | % (SE) | % (SE) |
| Age, years | |||
| 65-69 | 31.6 (0.6) | 30.8 (0.8) | 32.7 (1.0) |
| 70-74 | 27.0 (0.6) | 26.3 (0.8) | 27.8 (0.9) |
| 75-79 | 18.1 (0.5) | 18.1 (0.7) | 18.1 (0.7) |
| 80-84 | 11.9 (0.4) | 12.4 (0.6) | 11.3 (0.7) |
| 85+ | 11.4 (0.4) | 12.5 (0.6) | 10.2 (0.6) |
| Insurance | |||
| Private/Medicare | 54.5 (0.8) | 55.0 (1.0) | 53.9 (1.1) |
| Medicare Advantage | 28.5 (0.7) | 30.4 (0.9) | 26.2 (0.9) |
| Dual Eligible | 7.3 (0.4) | 8.8 (0.6) | 5.5 (0.5) |
| Other* | 9.0 (0.4) | 5.1 (0.4) | 13.7 (0.8) |
| Uninsured | 0.7 (0.1) | 0.7 (0.2) | 0.7 (0.2) |
| Race/ethnicity | |||
| Hispanic | 8.3 (0.6) | 8.2 (0.7) | 8.4 (0.7) |
| Non-Hispanic Asian | 4.4 (0.4) | 4.6 (0.5) | 4.2 (0.5) |
| Non-Hispanic Black | 9.1 (0.6) | 9.9 (0.7) | 8.1 (0.6) |
| Non-Hispanic White | 76.4 (0.9) | 75.6 (1.1) | 77.5 (1.1) |
| Other | 1.8 (0.2) | 1.8 (0.3) | 1.8 (0.3) |
| Marital Status | |||
| Married or living with partner | 59.8 (0.7) | 48.3 (0.9) | 73.6 (0.9) |
| Not currently married | 40.2 (0.7) | 51.7 (0.9) | 26.4 (0.9) |
| Region | |||
| Northeast | 19.5 (0.7) | 18.9 (0.8) | 20.1 (1.0) |
| Midwest | 21.1 (0.7) | 20.8 (0.9) | 21.5 (0.9) |
| South | 37.9 (0.9) | 37.8 (1.1) | 38.0 (1.2) |
| West | 21.5 (0.8) | 22.4 (0.9) | 20.4 (0.9) |
| Education | |||
| High school or less | 45.1 (0.8) | 47.2 (1.0) | 42.6 (1.1) |
| Some college | 27.5 (0.6) | 29.0 (0.8) | 25.7 (0.9) |
| College graduate | 15.5 (0.4) | 13.7 (0.6) | 17.5 (0.7) |
| Advanced Degree | 11.9 (0.4) | 10.1 (0.5) | 14.2 (0.7) |
| Income | |||
| <100% FPL | 8.8 (0.4) | 10.4 (0.6) | 6.9 (0.6) |
| 100%-199% FPL | 20.7 (0.6) | 22.9 (0.8) | 18.1 (0.9) |
| ≥ 200% FPL | 70.5 (0.8) | 66.7 (0.9) | 75.0 (1.1) |
| Wellness visit in past year | 80.2 (0.6) | 80.1 (0.8) | 80.3 (0.8) |
| Proxy completed survey | 5.0 (0.3) | 5.3 (0.5) | 4.6 (0.5) |
| Body Mass Index (BMI) < 25 | 33.0 (0.6) | 37.2 (0.9) | 27.9 (0.9) |
| General Health | |||
| Excellent/Very Good | 42.8 (0.7) | 43.8 (0.9) | 41.6 (1.0) |
| Good | 31.9 (0.6) | 31.8 (0.8) | 32.0 (0.9) |
| Fair/Poor | 25.3 (0.6) | 24.4 (0.8) | 26.4 (1.0) |
| COPD | 10.8 (0.4) | 10.9 (0.5) | 10.7 (0.6) |
| Cancer † | 22.1 (0.5) | 20.8 (0.7) | 23.6 (0.8) |
| Diabetes | 20.8 (0.6) | 19.2 (0.8) | 22.6 (0.8) |
| Difficulty doing errands alone | 17.1 (0.5) | 19.9 (0.8) | 13.7 (0.7) |
| Walk 5 city blocks without aid | |||
| No difficulty | 58.4 (0.7) | 52.9 (0.9) | 65.0 (1.0) |
| Some difficulty or cannot do | 41.6 (0.7) | 47.1 (0.9) | 35.0 (1.0) |
| Walk 1 city block without aid | |||
| No difficulty | 68.4 (0.7) | 64.2 (0.9) | 73.5 (0.9) |
| Some difficulty or cannot do | 31.6 (0.7) | 35.8 (0.9) | 26.5 (0.9) |
| Cigarette Use | |||
| Never smoked | 52.7 (0.7) | 61.3 (0.9) | 42.5 (1.0) |
| Former smoker | 39.4 (0.6) | 31.7 (0.8) | 48.8 (1.0) |
| Current smoker | 7.8 (0.4) | 7.1 (0.5) | 8.8 (0.5) |
| Hospitalized overnight within 12 mos | 17.2 (0.5) | 16.9 (0.7) | 17.7 (0.8) |
| <10 year Life expectancy ‡ | 38.8 (0.7) | 32.1 (0.9) | 46.9 (1.1) |
*Other insurance includes other public, other government, military
†excluding non-melanoma skin cancer
‡Schonberg Index – Estimated by scoring 10 or more points on the Schonberg index; mobility was defined by difficulty walking 5 blocks and assuming one overnight hospitalization
Cancer Screening
Breast cancer
Among women 65-74, 79.2% reported mammography screening within 2 years including 59.5% of women with <10-year life expectancy. Among women >75, 50.6% reported mammography screening within 2 years; including 38.3% of women with <10-year life expectancy (Table 2). Overall, among women >65 with <10-year life expectancy, 42.8% were screened. Shorter life expectancy, older age, less education, lower income, no wellness visit, and being non-Hispanic Asian were associated with being less likely to be screened for breast cancer, Table 3; Non-Hispanic Blacks and those with Medicare Advantage were more likely to be screened. 1.17 (0.95-1.38)
Table 2.
Self-Reported Receipt of Preventive Interventions by Life Expectancy (LE) and USPSTF Guideline-based Age-Thresholds (Weighted %)
| Overall | LE > 10yr | LE <10yr | |||||
|---|---|---|---|---|---|---|---|
| Total N | Weighted % | Total N | Weighted % | Total N | Weighted % | p-value | |
| Cancer Screening | |||||||
| Breast Cancer* | |||||||
| All 65+ | 4,177 (22.7M) | 67.1 | 2,878 (15.7M) | 77.9 | 1,299 (7.0M) | 42.8 | 0.001 |
| Age 65-74 | 2,323 (13.1M) | 79.2 | 2,078 (11.6M) | 81.8 | 245 (1.5M) | 59.5 | 0.001 |
| Age 75+ | 1,854 (9.6M) | 50.6 | 800 (4.1M) | 67.0 | 1,054 (5.5M) | 38.3 | 0.001 |
| Prostate Cancer† | |||||||
| All 65+ | 2,842 (17.1M) | 56.8 | 1,593 (9.7M) | 63.2 | 1,249 (7.4M) | 48.3 | 0.001 |
| Age 65-69 | 975 (6.0M) | 61.8 | 783 (4.9M) | 63.9 | 192 (1.1M) | 52.8 | 0.009 |
| Age 70+ | 1,867 (11.2M) | 54.1 | 810 (4.9M) | 62.5 | 1,057 (6.3M) | 47.5 | 0.001 |
| Colorectal Cancer‡ | |||||||
| All 65+ | 6,833 (38.9M) | 71.5 | 4,275 (24.3M) | 77.6 | 2,558 (14.6M) | 61.4 | 0.001 |
| Age 65-75 | 4,210 (24.6M) | 77.3 | 3,460 (19.9M) | 78.9 | 750 (4.7M) | 70.7 | 0.001 |
| Age 76+ | 2,623 (14.3M) | 61.4 | 815 (4.4M) | 71.5 | 1,808 (9.9M) | 57.0 | 0.001 |
| Vaccinations | |||||||
| Flu Vaccine§ | 8,317 (46.9M) | 72.0 | 5,082 (28.7M) | 70.2 | 3,235 (18.2M) | 74.9 | 0.001 |
| Shingles Vaccine‖ | 8,184 (46.1M) | 42.6 | 5,032 (28.4M) | 45.3 | 3,152 (17.7M) | 38.2 | 0.001 |
| Pneumococcal Vaccine¶ | 8,168 (46.0M) | 68.8 | 5,010 (28.3M) | 66.3 | 3,158 (17.7M) | 72.8 | 0.001 |
| Tetanus Vaccine# | 7,880 (44.5M) | 57.7 | 4,839 (27.4M) | 60.9 | 3,041 (17.1M) | 52.7 | 0.001 |
*Breast Cancer Screening: routine mammography in past 2 years
†Prostate Cancer Screening: routine Prostate Specific Antigen (PSA) test in past 2 years
‡Colorectal Cancer Screening: routine colonoscopy in past 10 years or blood stool/FIT test with a home kit in prior year or FIT/DNA stool test in the past year (excluding those with flexible sigmoidoscopy or CT colonography within 5 years because NHIS did not assess if these tests were done for screening or diagnostic purposes).
§Flu vaccine: single dose of influenza vaccine administered with last year
‖Shingles Vaccine: any shingles vaccine (includes those who had one Shingrix as part of two-part series)
¶Pneumococcal Vaccine: ≥ 1 dose of pneumococcal vaccine ever
#Tetanus Vaccine: Tetanus or Tdap within last 10 years
Table 3.
Adjusted Relative Risk of Reporting Cancer Screening
| Characteristic | Breast RR (95% CI) N=4,177 |
Prostate RR (95% CI) N=2,842 |
Colorectal RR (95% CI) N=6,833 |
|---|---|---|---|
| Gender | |||
| Male | N/A | Men only | 1.0 |
| Female | Women only | N/A | 1.00 (0.94-1.07) |
| Age | |||
| 65-69 | 1.0 | 1.0 | 1.0 |
| 70-74 | 0.94 (0.86-1.01) | 0.96 (0.82-1.09) | 0.99 (0.92-1.06) |
| 75-79 | 0.85 (0.77-0.93) | 0.88 (0.73-1.03) | 0.94 (0.87-1.02) |
| 80-84 | 0.68 (0.58-0.77) | 0.74 (0.57-0.92) | 0.75 (0.66-0.84) |
| 85+ | 0.39 (0.30-0.49) | 0.56 (0.38-0.74) | 0.57 (0.48-0.66) |
| Insurance | |||
| Private/Medicare | 1.0 | 1.0 | 1.0 |
| Medicare Advantage | 1.12 (1.03-1.22) | 1.02 (0.87-1.16) | 1.05 (0.99-1.10) |
| Dual Eligible | 0.95 (0.78-1.12) | 1.02 (0.72-1.32) | 0.88 (0.77-0.99) |
| Other | 0.97 (0.79-1.14) | 0.96 (0.79-1.14) | 0.98 (0.89-1.07) |
| Uninsured | 0.94 (0.48-1.39) | 0.59 (-0.02-1.21) | 0.39 (0.08-0.70) |
| Race/ethnicity | |||
| Hispanic | 1.17 (0.95-1.38) | 0.95 (0.69-1.21) | 1.04 (0.90-1.18) |
| Non-Hispanic Asian | 0.76 (0.55-0.97) | 0.80 (0.50-1.10) | 0.65 (0.50-0.79) |
| Non-Hispanic Black | 1.17 (1.03-1.30) | 0.96 (0.76-1.16) | 1.15 (1.04-1.26) |
| Non-Hispanic White | 1.0 | 1.0 | 1.0 |
| Other | 1.03 (0.67-1.38) | 0.76 (0.37-1.16) | 1.01 (0.80-1.23) |
| Marital Status | |||
| Married or living with partner | 1.0 | 1.0 | 1.0 |
| Not currently married | 0.92 (0.84-1.00) | 0.77 (0.66-0.87) | 0.83 (0.77-0.89) |
| Region | |||
| Northeast | 1.0 | 1.0 | 1.0 |
| Midwest | 1.07 (0.94-1.21) | 0.85 (0.68-1.03) | 0.93 (0.84-1.02) |
| South | 1.02 (0.90-1.44) | 0.96 (0.78-1.14) | 0.95 (0.87-1.03) |
| West | 0.95 (0.83-1.07) | 0.81 (0.64-0.98) | 0.93 (0.83-1.02) |
| Education | |||
| High school or less | 1.0 | 1.0 | 1.0 |
| Some college | 1.09 (0.98-1.20) | 1.27 (1.06-1.48) | 1.14 (1.04-1.23) |
| College graduate | 1.13 (1.00-1.27) | 1.30 (1.08-1.52) | 1.19 (1.07-1.30) |
| Advanced Degree | 1.27 (1.11-1.42) | 1.36 (1.09-1.62) | 1.25 (1.13-1.38) |
| Income | |||
| <100% FPL | 1.0 | 1.0 | 1.0 |
| 100%-199% FPL | 1.07 (0.89-1.24) | 1.33 (0.89-1.77) | 1.18 (1.02-1.34) |
| ≥ 200% FPL | 1.23 (1.02-1.44) | 1.91 (1.32-2.50) | 1.35 (1.18-1.53) |
| Wellness visit in past year | |||
| Yes | 1.19 (1.06-1.31) | 1.18 (0.99-1.37) | 1.10 (1.01-1.19) |
| Life Expectancy Index V1 | |||
| <10 yr LE | 0.75 (0.66-0.83) | 0.92 (0.78-1.05) | 0.95 (0.87-1.02) |
Bolded values highlight statistical significance
Prostate cancer
Among men 65-69 years, 61.8% reported PSA screening within 2 years including 52.8% of men with <10-year life expectancy. Among men >70 years, 54.1% reported PSA screening, including 47.5% of men with <10-year life expectancy (Table 2). Overall, among men >65 with <10-year life expectancy, 48.3% were screened within 2 years. Older age, less education, lower income, being unmarried, and being from the West were associated with being less likely to be screened (Table 3).
CRC
Among adults 65-75, 77.3% reported current CRC screening including 70.7% of adults with <10-year life expectancy. Among adults >76, 61.4% reported current CRC screening, including 57.0% of adults with <10-year life expectancy (Table 2). Overall, 61.4% of adults >65 with <10-year life expectancy were screened. Older age, less education, lower income, being uninsured or Medicare/Medicaid dually eligible, not married, or non-Hispanic Asian, and no wellness visit were associated with being less likely to be screened for CRC; Non-Hispanic Blacks were more likely to be screened. Of those screened, 94.5% reported colonoscopy within 10 years (78.1% within 5 years), 5.5% reported any stool testing within the past year, and 0.1% more reported stool/DNA testing within 3 years.
Across cancers, older age was strongly associated with being less likely to be screened, Figure 1 and Table 3. In multivariable analyses, lower life expectancy was significantly associated with being less likely to be screened for breast cancer but there was no association between life expectancy and prostate or CRC screening. Wellness visits were associated with greater screening across cancers but the association was not significant for prostate cancer. There was no significant interaction between life expectancy and wellness visits (eTable5).
Figure 1.
Preventive care by age and life expectancy. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001.
Immunizations
Receipt of immunizations varied from 72.0% for influenza, 68.8% for pneumococcus, 57.7% for tetanus, and 42.6% for shingles (Table 2). Older age and female sex were associated with being more likely to receive influenza, shingles, and pneumococcal vaccination but less likely to receive tetanus vaccination (Table 4). Lower life expectancy was associated with being more likely to receive pneumococcal vaccination but less likely to receive shingles vaccination (eFigure9). Non-Hispanic Whites were more likely to receive vaccines than other racial/ethnic groups, except for influenza vaccination, which was similar across populations, except for non-Hispanic Blacks, which was lower. Other insurance (mainly government insurance [e.g., military or state]) was associated with being more likely to receive vaccinations while those who were uninsured were less likely. Wellness visits were not associated with receipt of vaccination. Unmarried adults and those with less education were less likely to be vaccinated.
Table 4.
Adjusted Relative Risk of Reporting Vaccinations
| Characteristic | Flu RR (95% CI) N=8,317 |
Shingles RR (95% CI) N=8,184 |
Pneumococcal RR (95% CI) N=8,168 |
Tetanus RR (95% CI) N=7,880 |
|---|---|---|---|---|
| Gender | ||||
| Male | 1.0 | 1.0 | 1.0 | 1.0 |
| Female | 1.06 (1.01-1.11) | 1.15 (1.06-1.24) | 1.20 (1.13-1.27) | 0.90 (0.84-0.95) |
| Age | ||||
| 65-69 | 1.0 | 1.0 | 1.0 | 1.0 |
| 70-74 | 1.05 (0.98-1.12) | 1.16 (1.04-1.28) | 1.20 (1.11-1.29) | 0.93 (0.86-0.99) |
| 75-79 | 1.21 (1.12-1.29) | 1.27 (1.13-1.40) | 1.32 (1.21-1.43) | 0.96 (0.89-1.03) |
| 80-84 | 1.24 (1.14-1.34) | 1.15 (0.99-1.31) | 1.30 (1.16-1.43) | 0.83 (0.74-0.91) |
| 85+ | 1.23 (1.13-1.34) | 1.21 (1.03-1.39) | 1.18 (1.05-1.32) | 0.75 (0.66-0.85) |
| Insurance | ||||
| Private/Medicare | 1.0 | 1.0 | 1.0 | 1.0 |
| Medicare Advantage | 1.04 (0.99-1.08) | 1.02 (0.94-1.10) | 1.09 (1.03-1.15) | 1.06 (0.99-1.12) |
| Dual Eligible | 1.01 (0.93-1.08) | 1.00 (0.81-1.20) | 0.99 (0.88-1.10) | 1.12 (0.98-1.25) |
| Other | 1.08 (1.02-1.14) | 1.27 (1.12-1.42) | 1.19 (1.10-1.28) | 1.12 (1.01-1.23) |
| Uninsured | 0.42 (0.15-0.68) | 0.48 (0.05-0.92) | 0.62 (0.27-0.97) | 0.70 (0.28-1.13) |
| Race/ethnicity | ||||
| Hispanic | 0.94 (0.85-1.03) | 0.67 (0.54-0.81) | 0.78 (0.69-0.87) | 0.82 (0.71-0.93) |
| Non-Hispanic Asian | 1.02 (0.90-1.14) | 0.70 (0.53-0.86) | 0.69 (0.57-0.81) | 0.79 (0.64-0.95) |
| Non-Hispanic Black | 0.86 (0.79-0.94) | 0.71 (0.61-0.82) | 0.85 (0.77-0.92) | 0.84 (0.74-0.92) |
| Non-Hispanic White | 1.0 | 1.0 | 1.0 | 1.0 |
| Other | 0.92 (0.74-1.10) | 0.95 (0.70-1.19) | 0.85 (0.68-1.02) | 1.00 (0.81-1.19) |
| Marital Status | ||||
| Married or living with partner | 1.0 | 1.0 | 1.0 | 1.0 |
| Not currently married | 0.91 (0.87-0.95) | 0.85 (0.79-0.92) | 0.95 (0.90-0.99) | 0.97 (0.91-1.03) |
| Region | ||||
| Northeast | 1.0 | 1.0 | 1.0 | 1.0 |
| Midwest | 1.00 (0.94-1.06) | 1.15 (1.01-1.29) | 1.04 (0.95-1.13) | 1.11 (1.003-1.22) |
| South | 0.97 (0.91-1.03) | 1.02 (0.90-1.14) | 0.96 (0.88-1.04) | 0.96 (0.87-1.04) |
| West | 1.01 (0.94-1.08) | 1.31 (1.14-1.49) | 0.98 (0.89-1.07) | 1.10 (0.99-1.21) |
| Education | ||||
| High school or less | 1.0 | 1.0 | 1.0 | 1.0 |
| Some college | 1.03 (0.98-1.09) | 1.28 (1.16-1.40) | 1.10 (1.02-1.17) | 1.22 (1.13-1.31) |
| College graduate | 1.11 (1.04-1.18) | 1.53 (1.36-1.70) | 1.11 (1.02-1.20) | 1.18 (1.08-1.27) |
| Advanced Degree | 1.13 (1.05-1.21) | 1.50 (1.32-1.68) | 1.16 (1.06-1.25) | 1.24 (1.13-1.35) |
| Income | ||||
| <100% FPL | 1.0 | 1.0 | 1.0 | 1.0 |
| 100%-199% FPL | 1.04 (0.95-1.14) | 1.21 (0.97-1.45) | 1.04 (0.91-1.59) | 1.08 (0.95-1.22) |
| ≥ 200% FPL | 1.11 (1.01-1.20) | 1.52 (1.24-1.81) | 1.22 (1.08-1.36) | 1.17 (1.04-1.31) |
| Well visit in past year | ||||
| Yes | 1.03 (0.98-1.09) | 0.97 (0.87-1.06) | 1.01 (0.95-1.07) | 0.97 (0.90-1.04) |
| Life Expectancy | ||||
| <10-year life expectancy | 1.05 (0.98-1.11) | 0.88 (0.80-0.97) | 1.16 (1.07-1.24) | 0.95 (0.88-1.03) |
Bolded values highlight statistical significance
Discussion
Despite guidelines recommending against cancer screening for adults with <10-year life expectancy, many US adults >65 with <10-year life expectancy are screened. In multivariable analyses, older age was a strong predictor of not being screened while short life expectancy was only associated with not being screened for breast cancer; suggesting that interventions to reduce mammography screening in older women with <10-year life expectancy may be working. Encouragingly, among adults >65 who reported seeing a healthcare professional in the past year, 80% reported a wellness visit. Despite this, many were not up-to-date with recommended immunizations. While Medicare wellness visits were a groundbreaking advancement in older adult care, the contents of these visits may need to be better individualized based on the life expectancy and needs of older adults.34
Few studies have examined cancer screening by life-expectancy for multiple cancers simultaneously. Using 2011 National Health and Aging Trends Study data linked with Medicare claims, Schoenborn et al. found that 27.0% of women >65 with <10-year life expectancy were screened for breast cancer and 38.4% of men >65 with <10-year life expectancy were screened for prostate cancer.35 Using 2000-2010 NHIS data, Royce et al. found that 47% of adults >65 were screened for CRC, 63% of women >65 were screened for breast cancer (72% ages 65-74 vs. 55% ages >75), and 64% of men >65 were screened for prostate cancer in the past two years. Among those at high-risk (50-74% chance) of 9-year mortality, 49.8% were screened for CRC, 53.3% for breast cancer, and 60.0% for prostate cancer. Comparing our findings to these earlier NHIS data suggests that breast cancer screening rose among women 65-74 (79.2% screened in 2019) but declined among women with <10-year life expectancy (42.8% screened in 2019) and for women >75 (50.6% screened in 2019) and that prostate cancer screening dropped among men >65 (56.8% in 2019). Schonberg et al. examined CRC screening over 10 years in adults >65 using 2008-2010 NHIS data and found 56.3% were screened for CRC including 50.9% with <10-year life expectancy suggesting CRC screening rose in adults >65 regardless of life expectancy (71.2% current with CRC screening in 2019, including 61.0% of those with <10-year life expectancy).31
The decline in prostate cancer screening is likely because the USPSTF recommended against prostate cancer screening in all men in 201236; although in 2018 they reversed this recommendation to encourage shared decision-making for men 55-69.20 Choosing Wisely recommends not screening adults with <10-year life expectancy for cancer; however, the message seems to have impacted breast cancer screening decisions more so than other cancers. Mainstream news outlets (e.g., New York Times) have reported on overuse of mammography in older women several times in the past decade37, 38; while messaging has generally focused on increasing CRC screening and decreasing prostate cancer screening regardless of an individual’s age or life expectancy.39, 40 Also, since screening intervals for CRC screening are longer than for breast or prostate cancer, there may have been fewer opportunities for clinicians to discuss stopping CRC screening with older adults. This is important since many older adults are encouraged to continue screening at the time of a colonoscopy.41
We also found that receipt of immunizations increased among adults >65 since 2010 (e.g., 72.0% of adults >65 reported receiving influenza vaccination compared to 67% in 2011).4, 5 However, still only 42.6% of adults >65 reported receiving shingles vaccination. To improve vaccination rates, as of January 2023, Medicare now fully covers all CDC recommended vaccinations, including Shingrix and Tdap, which often previously required co-pays.42 While reported receipt of any tetanus vaccination was also low (58%) in 2019, data suggest that decennial tetanus vaccination after age 65 does not impact life expectancy and is less cost effective than a single vaccination/booster at age 65.43 We further found that 69% of adults >65 reported a pneumococcal vaccination, including 73% with <10-year life expectancy who may be at greatest risk; however, pneumococcal vaccination may benefit adults >65 regardless of life expectancy.44
Similar to others we found an association between wellness visits and receipt of cancer screening.45–47 However, we did not find an association between wellness visits and better targeting of cancer screening by life expectancy nor did we find an association between wellness visits and receipt of immunizations possibly because our study sample was already limited to adults who saw a healthcare professional in the past year, of which 80% reported a wellness visit.30 However, there is increasing recognition that wellness visits may need to be more focused on older adults’ individual needs, priorities, and life expectancy.34 Although clinicians report apprehension about using prognostic indices and discussing patient 10-year life expectancy in qualitative studies,48–50 in practice, data from a pilot study suggest that when primary care clinicians are provided scripts and strategies for discussing cancer screening cessation and information on the patients’ 10-year life-expectancy they find the information helpful and half use the information to discuss life expectancy with their patients; possibly as a result fewer of their older patients intend to be screened for cancer.51, 52 Similarly, in a clinical trial, use of a decision aid on mammography screening for women >75 years that included prognostic information from the Schonberg index led to fewer older women being screened; 87% of patients found the decision aid helpful.53 This decision aid and others as well as prognostic indices and information on the time-to-benefit from different preventive interventions may be found at the ePrognosis website.14, 52–54
A prior study found that older non-Hispanic Blacks were less likely to receive cancer screenings than older non-Hispanic Whites; however, we found that non-Hispanic Blacks were more likely to be screened for breast and CRC possibly because our models included more sociodemographic factors.55 However, non-Hispanic Asians were less likely to receive breast and CRC screening and several immunizations. Others have also found lower rates of cancer screening among non-Hispanic Asians possibly due to limited English proficiency and/or cultural differences.56 Compared to non-Hispanic Whites, other racial/ethnic groups, were less likely to receive immunizations in general possibly due to access and a historical basis for decreased trust in pharmaceutical and healthcare institutions.57, 58 It may also be helpful to address reasons for hesitancy in receiving preventive care during wellness visits to enhance appropriate receipt of such care.
Our study has limitations. First, self-reported data may overestimate receipt of preventive interventions by 14%.59 Second, our data are cross-sectional and life expectancy at the time of screening may have differed; however, most screenings were completed recently and prior NHIS studies also had this limitation. Also, our data are from 2019 and we know that cancer screening dropped precipitously due to stay-at-home orders at the pandemic’s beginning.32 However, from March 2021 to February 2022, mammography screening was only 1.9% lower than expected among Medicare beneficiaries ages 65-74.60 Others have found that CRC screening remained stable during the pandemic due to increases in stool-based testing.32 Therefore, 2019 data may provide a realistic estimate of current screening practices. Three of the questions used in the Schonberg mortality index were changed in NHIS’s redesign; however, accounting for these changes in sensitivity analyses did not change the direction of our findings (eTable6). Finally, alternative prognostic indices for 10-year life-expectancy exist, but they contain several variables not included within the NHIS survey.61 Reassuringly, their predictions have been shown to correlate strongly with that of the Schonberg index.62
Conclusions
Despite the long time-to-benefit, many US adults >65 with <10-year life expectancy reported receiving cancer screening in 2019 while many did not receive immunizations with a shorter time-to-benefit. Modifying wellness visits to be more focused on older adults’ individual needs, priorities, and life expectancy (such as through use of ePrognosis) is one strategy to improve preventive care delivery to older adults.
Supplementary Information
(DOCX 383 kb)
Author’s contribution
Lindsey Yourman, MD: contributed to the conception of the work, drafting and revising, approval of the final version, and is accountable for the study integrity. Jaclyn (Nikki) Bergstrom, M.S.: contributed to the design of the work, data analysis and interpretation, drafting of the work, approval of the final version, and is accountable for the study integrity. Elizabeth A. Bryant, MD, MPH: contributed to the interpretation of the data, draft, approval of the final version, and is accountable for the study integrity. Alina Pollner: contributed to the data analysis and interpretation, draft of the work, approval of the final version, and is accountable for the study integrity. Alison A. Moore MD, MPH: contributed to the design of the work, interpretation of data, critical revisions for important content, approval of the final version, and is accountable for the study integrity. Nancy Li Schoenborn, MD, MHS: contributed to the conception of the work, interpretation of data, critical revisions for important content, approval of the final version, and is accountable for the study integrity. Mara A. Schonberg, MD, MPH: contributed to the conception and design of the work, acquisition, and interpretation of data, drafting and revising, approval of the final version, and is accountable for the study integrity. All authors have access to the publicly available National Health Interview Survey upon which our study is based.
Funding
Dr. Schonberg’s time on this project was supported by a NIH/NIA K24 (AG071906). Dr. Schoenborn’s time on this project was supported by NIH/NIA K76 (AG059984).
Declarations
Conflict of interest
All authors have no conflicts of interest to report.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Lindsey Yourman and Jaclyn Bergstrom contributed equally to this work.
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