The "double jeopardy" of midlife and old age mortality trends in the United States.

Since 2010, US life expectancy growth has stagnated. Much research on US mortality has focused on working-age adults given adverse trends in drug overdose deaths, other external causes of death, and cardiometabolic deaths in midlife. We show that the adverse mortality trend at retirement ages (65+ y) has in fact been more consequential to the US life expectancy stagnation since 2010, as well as excess deaths and years of life lost in 2019, than adverse mortality trends at working ages. These results reveal that the United States is experiencing a "double jeopardy" that is driven by both mid-life and older-age mortality trends, but more so by older-age mortality. Understanding and addressing the causes behind the worsening mortality trend in older ages will be essential to returning to the pace of life expectancy improvements that the United States had experienced for decades.

Lifetime years married held steady for men with a BA degree since 1960 but dropped to lowest level since 1880 for men without a BA.

Trends in life expectancy and marriage patterns work together to determine expected lifetime years married. In 1880, adult life expectancy was short and marriages were more likely to end by death than divorce. Since then, although there have been substantial life expectancy gains in adulthood, marriage has been increasingly delayed or forgone and cohabitation and divorce are far more prevalent. Whether adults today can expect to spend more or fewer years married than in the past depends on the relative magnitude of changes in mortality and marriage. We estimate trends in men's expected lifetime years married (and in other marital statuses) from 1880 to 2019 and by bachelor's degree (BA) status from 1960 to 2019. Our results show a rise in men's expected lifetime years married between 1880 and the Baby Boom era and a subsequent fall. There are large and growing differences by BA status. Men with a BA have had high and relatively stable expected lifetime years married since 1960. For men without a BA, expected lifetime years married has plummeted to lows not seen among men since 1880. Cohabitation accounts for a substantial fraction, although not all, of these declines. Our results demonstrate how increasing inequality in both life expectancy and marriage patterns combine to amplify educational differences in lifetime experiences of coresidential partnerships.

Excess Mortality and Loss of Life Expectancy After Myocardial Infarction: A Registry-Based Matched Cohort Study.

BACKGROUND: The effect of myocardial infarction (MI) on life expectancy is difficult to study because the prevalence of MI hinders direct comparison with the life expectancy of the general population. We sought to assess this in relation to age, sex, and left ventricular ejection fraction (LVEF) by comparing individuals with MI with matched comparators without previous MI. METHODS: We included patients with a first MI between 1991 and 2022 from the nationwide SWEDEHEART registry (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies), each matched with up to 5 comparators on age, sex, and region of residence. Flexible parametric survival models were used to estimate excess mortality risk and mean loss of life expectancy (LOLE) depending on index year, age, sex, and LVEF, and adjusted for differences in characteristics. RESULTS: A total of 335 748 cases were matched to 1 625 396 comparators. A higher LOLE was observed in younger individuals, women, and those with reduced LVEF (<50%). In 2022, the unadjusted and adjusted mean LOLE spanned from 11.1 and 9.5 years in 50-year-old women with reduced LVEF to 5 and 3.7 months in 80-year-old men with preserved LVEF. Between 1992 and 2022, the adjusted mean LOLE decreased by 36% to 55%: from 4.4 to 2.0 years and from 3.3 to 1.9 years in 50-year-old women and men, respectively, and from 1.7 to 1.0 years and from 1.4 to 0.9 years in 80-year-old women and men, respectively. CONCLUSIONS: LOLE is higher in younger individuals, women, and those with reduced LVEF, but is attenuated when adjusting for comorbidities and risk factors. Advances in MI treatment during the past 30 years have almost halved LOLE, with no clear sign of leveling off to a plateau.

Social disadvantage, economic inequality, and life expectancy in nine Indian states.

SignificanceIndia is one of the most hierarchical societies in the world. Because vital statistics are incomplete, mortality disparities are not quantified. Using survey data on more than 20 million individuals from nine Indian states representing about half of India's population, we estimate and decompose life expectancy differences between higher-caste Hindus, comprising other backward classes and high castes, and three marginalized social groups: Adivasis (indigenous peoples), Dalits (oppressed castes), and Muslims. The three marginalized groups experience large disadvantages in life expectancy at birth relative to higher-caste Hindus. Economic status explains less than half of these gaps. These large disparities underscore parallels between diverse systems of discrimination akin to racism. They highlight the global significance of addressing social inequality in India.

Significant impacts of the COVID-19 pandemic on race/ethnic differences in US mortality.

The coronavirus 2019 (COVID-19) pandemic triggered global declines in life expectancy. The United States was hit particularly hard among high-income countries. Early data from the United States showed that these losses varied greatly by race/ethnicity in 2020, with Hispanic and Black Americans suffering much larger losses in life expectancy compared with White people. We add to this research by examining trends in lifespan inequality, average years of life lost, and the contribution of specific causes of death and ages to race/ethnic life-expectancy disparities in the United States from 2010 to 2020. We find that life expectancy in 2020 fell more for Hispanic and Black males (4.5 and 3.6 y, respectively) compared with White males (1.5 y). These drops nearly eliminated the previous life-expectancy advantage for the Hispanic compared with the White population, while dramatically increasing the already large gap in life expectancy between Black and White people. While the drops in life expectancy for the Hispanic population were largely attributable to official COVID-19 deaths, Black Americans saw increases in cardiovascular diseases and "deaths of despair" over this period. In 2020, lifespan inequality increased slightly for Hispanic and White populations but decreased for Black people, reflecting the younger age pattern of COVID-19 deaths for Hispanic people. Overall, the mortality burden of the COVID-19 pandemic hit race/ethnic minorities particularly hard in the United States, underscoring the importance of the social determinants of health during a public health crisis.

Cardiovascular Health and Life Expectancy Among Adults in the United States.

BACKGROUND: Cardiovascular disease may be the main reason for stagnant growth in life expectancy in the United States since 2010. The American Heart Association recently released an updated algorithm for evaluating cardiovascular health (CVH)-Life's Essential 8 (LE8) score. We aimed to quantify the associations of CVH levels, estimated by the LE8 score, with life expectancy in a nationally representative sample of US adults. METHODS: We included 23 003 nonpregnant, noninstitutionalized participants aged 20 to 79 years who participated in the National Health and Nutrition Examination Survey from 2005 to 2018 and whose mortality was identified through linkage to the National Death Index through December 31, 2019. The overall CVH was evaluated by the LE8 score (range, 0-100), as well as the score for each component of diet, physical activity, tobacco/nicotine exposure, sleep duration, body mass index, non-high-density lipoprotein cholesterol, blood glucose, and blood pressure. Life table method was used to estimate life expectancy by levels of the CVH. RESULTS: During a median of 7.8 years of follow-up, 1359 total deaths occurred. The estimated life expectancy at age 50 years was 27.3 years (95% CI, 26.1-28.4), 32.9 years (95% CI, 32.3-33.4), and 36.2 years (95% CI, 34.2-38.2) in participants with low (LE8 score <50), moderate (50≤ LE8 score <80), and high (LE8 score ≥80) CVH, respectively. Equivalently, participants with high CVH had an average 8.9 (95% CI, 6.2-11.5) more years of life expectancy at age 50 years compared with those with low CVH. On average, 42.6% of the gained life expectancy at age 50 years from adhering to high CVH was attributable to reduced cardiovascular disease death. Similarly significant associations of CVH with life expectancy were observed in men and women, respectively. Similarly significant associations of CVH with life expectancy were observed in White participants and Black participants but not in Mexican participants. CONCLUSIONS: Adhering to a high CVH, defined as the LE8 score, is related to a considerably increased life expectancy in US adults, but more research needs to be done in other races and ethnicities (eg, Hispanic and Asian).

Life expectancy among Native Americans during the COVID-19 pandemic: estimates, uncertainty, and obstacles.

Few reliable estimates have been available for assessing the impact of the COVID-19 pandemic on mortality among Native Americans. Using deidentified publicly available data on deaths and populations by age, we estimated life expectancy for the years 2019-2022 for single-race non-Hispanic Native Americans. Life expectancy in 2022 was 67.8 years, 2.3 years higher than in 2021 but a huge 4-year loss from 2019. Although our life expectancy estimates for 2022 varied under different assumptions about racial/ethnic classification and age misreporting errors, all estimates were lower than the average for middle-income countries. Estimates of losses and gains in life expectancy were consistent across assumptions. Large reductions in COVID-19 death rates between 2021 and 2022 were largely offset by increases in rates of death from unintentional injuries (particularly drug overdoses), chronic liver disease, diabetes, and heart disease, underscoring the difficulties facing Native Americans in achieving reductions in mortality, let alone returning to levels of mortality prior to the pandemic. Serious data problems have persisted for many years, but the scarcity and inadequacy of estimates during the pandemic have underscored the urgent need for timely and accurate demographic data on the Native American population.

Life Expectancy Changes During the COVID-19 Pandemic, 2019-2021: Highly Racialized Deaths in Young and Middle Adulthood in the United States as Compared With Other High-Income Countries.

We estimated changes in life expectancy between 2019 and 2021 in the United States (in the total population and separately for 5 racial/ethnic groups) and 20 high-income peer countries. For each country's total population, we decomposed the 2019-2020 and 2020-2021 changes in life expectancy by age. For US populations, we also decomposed the life expectancy changes by age and number of coronavirus disease 2019 (COVID-19) deaths. Decreases in US life expectancy in 2020 (1.86 years) and 2021 (0.55 years) exceeded mean changes in peer countries (a 0.39-year decrease and a 0.23-year increase, respectively) and disproportionately involved COVID-19 deaths in midlife. In 2020, Native American, Hispanic, Black, and Asian-American populations experienced larger decreases in life expectancy and greater losses in midlife than did the White population. In 2021, the White population experienced the largest decrease in US life expectancy, although life expectancy in the Native American and Black populations remained much lower. US losses during the pandemic were more severe than in peer countries and disproportionately involved young and middle-aged adults, especially adults of this age in racialized populations. The mortality consequences of the COVID-19 pandemic deepened a US disadvantage in longevity that has been growing for decades and exacerbated long-standing racial inequities in US mortality.

Estimating scenarios for survival time in patients with advanced melanoma receiving immunotherapy and targeted therapy.

BACKGROUND: We aim to provide survival scenario estimates for patients with advanced melanoma starting targeted therapies and immunotherapies. MATERIALS AND METHODS: We sought randomized trials of targeted therapies and immunotherapies for advanced melanoma and recorded the following percentiles (represented survival scenario) from each overall survival (OS) curve: 90th (worst-case), 75th (lower-typical), 50th (median), 25th (upper-typical), and 10th (best-case). We tested whether these scenarios can be estimated for each OS curve by multiplying its median by 4 multiples: 0.25 (worst-case), 0.5 (lower-typical), 2 (upper-typical), and 3 (best-case). RESULTS: We identified 15 trials with 8025 patients. For first-line combination targeted therapy treatment groups, the median (interquartile range, IQR) in months for each percentile was: 90th, 6.2 (6.0-6.5); 75th, 11.3 (11.3-11.4); and median, 24.4 (23.5-25.3). For the first-line combination immunotherapy treatment group, the percentiles in months were: 90th, 3.9 (2.8-4.5); 75th, 13.4 (10.1-15.4), median 73 (not applicable). In targeted therapy groups, simple multiples of the median OS were accurate for estimating the 90th percentile in 80%; 75th percentile in 40%; 25th percentile in 100%. In immunotherapy groups, these multiples were accurate at 0% for the 90th percentile, and 43% for the 75th percentile. The 90th percentile (worst-case scenario) was better estimated as 1/6× median OS, and the 75th percentile (lower-typical) as 1/3× median OS. CONCLUSIONS: Simple multiples of the median OS are a useful framework to estimate scenarios for survival for patients receiving targeted therapies, not immunotherapy. Longer follow-up is required to estimate upper-typical and best-case scenarios.

Assessing the impact of type 2 diabetes on mortality and life expectancy according to the number of risk factor targets achieved: an observational study.

BACKGROUND: Type 2 diabetes (T2D) is associated with an increased risk of premature death. Whether multifactorial risk factor modification could attenuate T2D-related excess risk of death is unclear. We aimed to examine the association of risk factor target achievement with mortality and life expectancy among patients with T2D, compared with individuals without diabetes. METHODS: In this longitudinal cohort study, we included 316 995 participants (14 162 with T2D and 302 833 without T2D) free from cardiovascular disease (CVD) or cancer at baseline between 2006 and 2010 from the UK Biobank. Participants with T2D were categorised according to the number of risk factors within target range (non-smoking, being physically active, healthy diet, guideline-recommended levels of glycated haemoglobin, body mass index, blood pressure, and total cholesterol). Survival models were applied to calculate hazard ratios (HRs) for mortality and predict life expectancy differences. RESULTS: Over a median follow-up of 13.8 (IQR 13.1-14.4) years, deaths occurred among 2105 (14.9%) participants with T2D and 18 505 (6.1%) participants without T2D. Compared with participants without T2D (death rate per 1000 person-years 4.51 [95% CI 4.44 to 4.57]), the risk of all-cause mortality among those with T2D decreased stepwise with an increasing number of risk factors within target range (0-1 risk factor target achieved: absolute rate difference per 1000 person-years 7.34 [4.91 to 9.78], HR 2.70 [2.25 to 3.25]; 6-7 risk factors target achieved: absolute rate difference per 1000 person-years 0.68 [-0.62 to 1.99], HR 1.16 [0.93 to 1.43]). A similar pattern was observed for CVD and cancer mortality. The association between risk factors target achievement and all-cause mortality was more prominent among participants younger than 60 years than those 60 years or older (P for interaction = 0.012). At age 50 years, participants with T2D who had 0-1 and 6-7 risk factors within target range had an average 7.67 (95% CI 6.15 to 9.19) and 0.99 (-0.59 to 2.56) reduced years of life expectancy, respectively, compared with those without T2D. CONCLUSIONS: Individuals with T2D who achieved multiple risk factor targets had no significant excess mortality risk or reduction in life expectancy than those without diabetes. Early interventions aiming to promote risk factor modification could translate into improved long-term survival for patients with T2D.

All-cause and cause-specific mortality risk and loss in life expectancy associated with incident type 2 diabetes onset age and duration.

BACKGROUND: Evidence on type 2 diabetes onset age and duration on mortality risk has been limited by short follow-up, inadequate control for confounding, missing repeated measurements, and inability to cover the full range of onset age, duration, and major causes of death. Moreover, scarce data dissect how type 2 diabetes onset age and duration shape life expectancy. METHODS: We evaluate prospectively these topics based on 270,075 eligible participants in the Nurses' Health Studies and Health Professionals Follow-up Study, leveraging repeated measurements throughout up to 40 years of follow-up. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: In fully adjusted analyses, incident early onset type 2 diabetes (diagnosed <40 years of age) was associated with significantly higher mortality from all-causes (HR, 95% CI was 3.16, 2.64-3.79; vs. individuals without type 2 diabetes), cardiovascular disease (6.56, 4.27-10.1), respiratory disease (3.43, 1.38-8.51), neurodegenerative disease (5.13, 2.09-12.6), and kidney disease (8.55, 1.98-36.9). The relative risk elevations declined dramatically with each higher decade of age at diagnosis for deaths from most of these causes, though the absolute risk difference increased continuously. A substantially higher cumulative incidence of mortality and a greater loss in life expectancy were associated with younger age at type 2 diabetes diagnosis. Longer disease duration was associated with generally higher relative and absolute risk of mortality. CONCLUSION: Early onset of type 2 diabetes and longer disease duration are associated with substantially increased risk of all-cause and cause-specific mortality and greater loss in life expectancy.

Association of hospital-treated infectious diseases and infection burden with cardiovascular diseases and life expectancy.

BACKGROUND: The association of a broad spectrum of infectious diseases with cardiovascular outcomes remains unclear. OBJECTIVES: We aim to provide the cardiovascular risk profiles associated with a wide range of infectious diseases and explore the extent to which infections reduce life expectancy. METHODS: We ascertained exposure to 900+ infectious diseases before cardiovascular disease (CVD) onset in 453,102 participants from the UK Biobank study. Time-varying Cox proportional hazard models were used. Life table was used to estimate the life expectancy of individuals aged ≥50 with different levels of infection burden (defined as the number of infection episodes over time and the number of co-occurring infections). RESULTS: Infectious diseases were associated with a greater risk of CVD events (adjusted HR [aHR] 1.79 [95% confidence interval {CI} 1.74-1.83]). For type-specific analysis, bacterial infection with sepsis had the strongest risk of CVD events [aHR 4.76 (4.35-5.20)]. For site-specific analysis, heart and circulation infections posed the greatest risk of CVD events [aHR 4.95 (95% CI 3.77-6.50)], whereas noncardiac infections also showed excess risk [1.77 (1.72-1.81)]. Synergistic interactions were observed between infections and genetic risk score. A dose-response relationship was found between infection burden and CVD risks (p-trend <0.001). Infection burden >1 led to a CVD-related life loss at age 50 by 9.3 years [95% CI 8.6-10.3]) for men and 6.6 years [5.5-7.8] for women. CONCLUSIONS: The magnitude of the infection-CVD association showed specificity in sex, pathogen type, infection burden, and infection site. High genetic risk and infection synergistically increased the CVD risk.

Influenza: cause or excuse? An analysis of flu's influence on worsening mortality trends in England and Wales, 2010-19.

BACKGROUND: England and Wales experienced a stagnation of previously improving life expectancy during the 2010s. Public bodies cited influenza as an important cause. SOURCES OF DATA: We used data from the Office for National Statistics to examine mortality attributed directly to influenza and to all influenza-like diseases for the total population of England and Wales 2010-19. Several combinations of ICD-10 codes were used to address the possibility of under-counting influenza deaths. AREAS OF AGREEMENT: Deaths from influenza and influenza-like diseases declined between 2010 and 2019, while earlier improvements in mortality from all causes of death were stalling and, with some causes, worsening. Our findings support existing research showing that influenza is not an important cause of the stalling of mortality rates 2010-19. AREAS OF CONTROVERSY: Influenza was accepted by many as an important cause of stalling life expectancy for much of the 2010s, while few in public office have accepted austerity as a key factor in the changes seen during that time. GROWING POINTS: This adds to the mounting evidence that austerity damaged health prior to COVID-19 and left the population more vulnerable when it arrived. AREAS FOR DEVELOPING TIMELY RESEARCH: Future research should explore why so many in public office were quick to attribute the change in trends in overall mortality in the UK in this period to influenza, and why many continue to do so through to 2023 and to deny the key role of austerity in harming population health.

Trends in Locoregional Therapy in Older Women with Early-Stage Hormone Receptor-Positive Breast Cancer by Frailty and Life Expectancy.

BACKGROUND: In women ≥ 70 years of age with T1N0 hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer, breast surgery type and omission of axillary surgery or radiation therapy (RT) do not impact overall survival. Although frailty and life expectancy ideally factor into therapy decisions, their impact on therapy receipt is unclear. We sought to identify trends in and factors associated with locoregional therapy type by frailty and life expectancy. METHODS: Women ≥ 70 years of age with T1N0 HR+/HER2- breast cancer diagnosed in the Surveillance, Epidemiology, and End Results (SEER)-Medicare database between 2010 and 2015 were stratified by validated claims-based frailty and life expectancy measures. Therapy trends over time by regimen intensity ('high intensity': lumpectomy + axillary surgery + RT, or mastectomy + axillary surgery; 'moderate intensity': lumpectomy + RT, lumpectomy + axillary surgery, or mastectomy only; or 'low intensity': lumpectomy only) were analyzed. Factors associated with therapy type were identified using generalized linear mixed models. RESULTS: Of 16,188 women, 21.8% were frail, 22.2% had a life expectancy < 5 years, and only 12.3% fulfilled both criteria. In frail women with a life expectancy < 5 years, high-intensity regimens decreased significantly (48.8-31.2%; p < 0.001) over the study period, although in 2015, 30% still received a high-intensity regimen. In adjusted analyses, frailty and life expectancy < 5 years were not associated with breast surgery type but were associated with a lower likelihood of axillary surgery (frailty: odds ratio [OR] 0.86, 95% confidence interval [CI] 0.76-0.96; life expectancy < 5 years: OR 0.22, 95% CI 0.20-0.25). Life expectancy < 5 years was also associated with a lower likelihood of RT receipt in breast-conserving surgery patients (OR 0.30, 95% CI 0.27-0.34). CONCLUSIONS: Rates of high-intensity therapy are decreasing but overtreatment persists in this population. Continued efforts aimed at appropriate de-escalation of locoregional therapy are needed.

Potential Overtreatment of DCIS in Patients with Limited Life Expectancy.

INTRODUCTION: As the benefits of intensive locoregional therapy for ductal carcinoma in situ (DCIS) are realized over time in older adults, life expectancy may help to guide treatment decisions. We examined whether life expectancy was associated with extent of locoregional therapy in this population. PATIENTS AND METHODS: Women ≥ 70 years old with < 5 cm of DCIS diagnosed 2010-2015 were identified in the Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset and categorized by a life expectancy ≤ 5 or > 5 years, defined by a validated claims-based measure. Differences in locoregional therapy (mastectomy + axillary surgery, mastectomy-only, lumpectomy + radiation therapy (RT) + axillary surgery, lumpectomy + RT, lumpectomy-only, and no treatment) by life expectancy were assessed using Pearson chi-squared tests. Generalized linear mixed models were used to identify factors associated with receipt of lumpectomy-only. RESULTS: Of 5346 women (median age of 75 years, range 70-97 years), 927 (17.3%) had a life expectancy ≤ 5 years. Of the 4041 patients who underwent lumpectomy, 710 (13.3%) underwent axillary surgery. More patients with life expectancy ≤ 5 years underwent lumpectomy-only (39.4% versus 27%), mastectomy-only (8.1% versus 5.3%), or no treatment (5.8% versus 3.2%; p < 0.001). On multivariable analysis, women with life expectancy ≤ 5 years had a significantly greater likelihood of undergoing lumpectomy-only [OR 1.90, 95% CI (1.63-2.22)]. CONCLUSIONS: Life expectancy is associated with lower-intensity locoregional therapy for older women with DCIS, yet a large proportion of patients with a life expectancy ≤ 5 years received RT and axillary surgery, highlighting potential overtreatment and opportunities to de-escalate locoregional therapy in older adults.

Time to pregnancy and life expectancy: a cohort study of 18 796 pregnant couples.

STUDY QUESTION: Is fecundity, measured as time to pregnancy (TTP), associated with mortality in parents? SUMMARY ANSWER: Prolonged TTP is associated with increased mortality in both mothers and fathers in a dose-response manner. WHAT IS KNOWN ALREADY: Several studies have linked both male and female fecundity to mortality. In women, infertility has been linked to several diseases, but studies suggest that the underlying conditions, rather than infertility, increase mortality. STUDY DESIGN, SIZE, DURATION: A prospective cohort study was carried out on 18 796 pregnant couples, in which the pregnant women attended prophylactic antenatal care between 1973 and 1987 at a primary and tertiary care unit. The couples were followed in Danish mortality registers from their child's birth date until death or until 2018. The follow-up period was up to 47 years, and there was complete follow-up until death, emigration or end of study. PARTICIPANTS/MATERIALS, SETTING, METHODS: At the first antenatal visit, the pregnant women were asked to report the time to the current pregnancy. Inclusion was restricted to the first pregnancy, and TTP was categorised into <12 months, ≥12 months, not planned, and not available. In sub-analyses, TTP ≥12 was further categorized into 12-35, 36-60, and >60 months. Information for parents was linked to several Danish nationwide health registries. Survival analysis was used to estimate the hazard ratios (HRs) with a 95% CI for survival and adjusted for age at the first attempt to become pregnant, year of birth, socioeconomic status, mother's smoking during pregnancy, and mother's BMI. MAIN RESULTS AND THE ROLE OF CHANCE: Mothers and fathers with TTP >60 months survived, respectively, 3.5 (95% CI: 2.6-4.3) and 2.7 (95% CI: 1.8-3.7) years shorter than parents with a TTP <12 months. The mortality was higher for fathers (HR: 1.21, 95% CI: 1.09-1.34) and mothers (HR: 1.29, 95% CI: 1.12-1.49) with TTP ≥12 months compared to parents with TTP <12 months. The risk of all-cause mortality during the study period increased in a dose-response manner with the highest adjusted HR of 1.98 (95% CI: 1.62-2.41) for fathers and 2.03 (95% CI: 1.56-2.63) for mothers with TTP >60 months. Prolonged TTP was associated with several different causes of death in both fathers and mothers, indicating that the underlying causes of the relation between fecundity and survival may be multi-factorial. LIMITATIONS, REASONS FOR CAUTION: A limitation is that fecundity is measured using a pregnancy-based approach. Thus, the cohort is conditioned on fertility success and excludes sterile couples, unsuccessful attempts and spontaneous abortions. The question used to measure TTP when the pregnant woman was interviewed at her first attended prophylactic antenatal care: 'From the time you wanted a pregnancy until it occurred, how much time passed?' could potentially have led to serious misclassification if the woman did not answer on time starting unprotected intercourse but on the start of wishing to have a child. WIDER IMPLICATIONS OF THE FINDINGS: We found that TTP is a strong marker of survival, contributing to the still-emerging evidence that fecundity in men and women reflects their health and survival potential. STUDY FUNDING/COMPETING INTEREST(S): The authors acknowledge an unrestricted grant from Ferring. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication. M.L.E. is an advisor to Ro, VSeat, Doveras, and Next. TRIAL REGISTRATION NUMBER: N/A.

Variation in Receipt of Cancer Screening and Immunizations by 10-year Life Expectancy among U.S. Adults aged 65 or Older in 2019.

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.

Tackling Guideline Non-concordance: Primary Care Barriers to Incorporating Life Expectancy into Lung Cancer Screening Decision-Making-A Qualitative Study.

BACKGROUND: Primary care providers (PCPs) are often the first point of contact for discussing lung cancer screening (LCS) with patients. While guidelines recommend against screening people with limited life expectancy (LLE) who are less likely to benefit, these patients are regularly referred for LCS. OBJECTIVE: We sought to understand barriers PCPs face to incorporating life expectancy into LCS decision-making for patients who otherwise meet eligibility criteria, and how a hypothetical point-of-care tool could support patient selection. DESIGN: Qualitative study based on semi-structured telephone interviews. PARTICIPANTS: Thirty-one PCPs who refer patients for LCS, from six Veterans Health Administration facilities. APPROACH: We thematically analyzed interviews to understand how PCPs incorporated life expectancy into LCS decision-making and PCPs' receptivity to a point-of-care tool to support patient selection. Final themes were organized according to the Cabana et al. framework Why Don't Physicians Follow Clinical Practice Guidelines, capturing the influence of clinician knowledge, attitudes, and behavior on LCS appropriateness determinations. KEY RESULTS: PCP referrals to LCS for patients with LLE were influenced by limited knowledge of the life expectancy threshold at which patients are less likely to benefit from LCS, discomfort estimating life expectancy, fear of missing cancer at the point of early detection, and prioritization of factors such as quality of life, patient values, clinician-patient relationship, and family support. PCPs were receptive to a decision support tool to inform and communicate LCS appropriateness decisions if easy to use and integrated into clinical workflows. CONCLUSIONS: Our study suggests knowledge gaps and attitudes may drive decisions to offer screening despite LLE, a behavior counter to guideline recommendations. Integrating a LCS decision support tool that incorporates life expectancy within the electronic medical record and existing clinical workflows may be one acceptable solution to improve guideline concordance and increase confidence in selecting high benefit patients for LCS.

Interaction of patient age and high-grade prostate cancer on targeted biopsies of MRI suspicious lesions.

OBJECTIVES: To evaluate the interaction of patient age and Prostate Imaging-Reporting and Data System (PI-RADS) score in determining the grade of prostate cancer (PCa) identified on magnetic resonance imaging (MRI)-targeted biopsy in older men. PATIENTS AND METHODS: From a prospectively accrued Institutional Review Board-approved comparative study of MRI-targeted and systematic biopsy between June 2012 and December 2022, men with at least one PI-RADS ≥3 lesion on pre-biopsy MRI and no prior history of PCa were selected. Ordinal and binomial logistic regression analyses were performed. RESULTS: A total of 2677 men met study criteria. The highest PI-RADS score was 3 in 1220 men (46%), 4 in 950 men (36%), and 5 in 507 men (19%). The median (interquartile range [IQR]) patient age was 66.7 (60.8-71.8) years, median (IQR) prostate-specific antigen (PSA) level was 6.1 (4.6-9.0) ng/mL, median (IQR) prostate volume was 48 (34-68) mL, and median (IQR) PSA density was 0.13 (0.08-0.20) ng/mL/mL. Clinically significant (cs)PCa and high-risk PCa were identified on targeted biopsy in 1264 (47%) and 321 (12%) men, respectively. Prevalence of csPCa and high-risk PCa were significantly higher in the older age groups. On multivariable analyses, patient age was significantly associated with csPCa but not high-risk PCa; PI-RADS score and the interaction of age and PI-RADS score were significantly associated with high-risk PCa but not csPCa. CONCLUSION: In our cohort, the substantial rate of high-risk PCa on MRI-ultrasound fusion targeted biopsies in older men, and its significant association with MRI findings, supports the value of pre-biopsy MRI to localise disease that could cause cancer mortality even in older men.

Appropriate Categorization of Inequality to Inform Policy Decisions: Estimating Distribution of Lifetime Health Using Alternative Approaches to Socioeconomic Stratification.

OBJECTIVES: Estimation of gradients in lifetime health, notably quality-adjusted life expectancy (QALE), has largely focused on index of multiple deprivation to categorize the population by socioeconomic position. In this article, we estimate QALE using alternate, individual- rather than area-level, indicators of socioeconomic position. METHODS: Building on previous research methods, the distribution of QALE is estimated across education and income groups based on data from the Health Survey for England and the Office for National Statistics. QALE is estimated for each group by combining multivariate mortality rates and health-related quality of life (HRQL) weights using life tables. HRQL weights were estimated using ordinary least squares and missing data were handled using multiple imputation. RESULTS: The estimated lifetime HRQL weights decreased with increased age, lower educational attainment, and lower income. For example, the QALE at birth for males in the lowest educational attainment group was 61.69 quality-adjusted life-years (QALYs), 1.54 QALYs lower than females in the same group. This is in contrast to 76.58 and 75.89 QALYs for males and females in the highest educational attainment group, respectively. A similar trend was observed across income quintiles albeit the gap was less pronounced. CONCLUSIONS: The use of index of multiple deprivation to assess health inequalities may be masking important information about individual-level variation. Decisions makers should consider this alongside the merits of using area-level approaches to categorizing the population if individual-level approaches are preferable.