Calculate Life Expectancy Research Articles

Subjective Life Expectancy Among College Students

ABSTRACTEstablishing healthy habits in college is important for long-term health. Despite existing health promotion efforts, many college students fail to meet recommendations for behaviors such as healthy eating and exercise, which may be due to low perceived risk for health problems. The goals of this study were to examine: (1) the accuracy of life expectancy predictions, (2) potential individual differences in accuracy (i.e., gender and conscientiousness), and (3) potential change in accuracy after inducing awareness of current health behaviors. College students from a small northeastern university completed an electronic survey, including demographics, initial predictions of their life expectancy, and their recent health behaviors. At the end of the survey, participants were asked to predict their life expectancy a second time. Their health data were then submitted to a validated online algorithm to generate calculated life expectancy. Participants significantly overestimated their initial life expectancy, and neither gender nor conscientiousness was related to the accuracy of these predictions. Further, subjective life expectancy decreased from initial to final predictions. These findings suggest that life expectancy perceptions present a unique—and potentially modifiable—psychological process that could influence college students' self-care.

Personalized predictive modeling for patients with Alzheimer\u2019s disease using an extension of Sullivan\u2019s life table model

BackgroundAlzheimer’s disease (AD) progression varies substantially among patients, hindering calculation of residual total life expectancy (TLE) and its decomposition into disability-free life expectancy (DFLE) and disabled life expectancy (DLE) for individual patients with AD. The objective of the present study was to assess the accuracy of a new synthesis of Sullivan’s life table (SLT) and longitudinal Grade of Membership (L-GoM) models that estimates individualized TLEs, DFLEs, and DLEs for patients with AD. If sufficiently accurate, such information could enhance the quality of important decisions in AD treatment and patient care.MethodsWe estimated a new SLT/L-GoM model of the natural history of AD over 10 years in the Predictors 2 Study cohort: N = 229 with 6 fixed and 73 time-varying covariates over 21 examinations covering 11 measurement domains including cognitive, functional, behavioral, psychiatric, and other symptoms/signs. Total remaining life expectancy was censored at 10 years. Disability was defined as need for full-time care (FTC), the outcome most strongly associated with AD progression. All parameters were estimated via weighted maximum likelihood using data-dependent weights designed to ensure that the estimates of the prognostic subtypes were of high quality. Goodness of fit was tested/confirmed for survival and FTC disability for five relatively homogeneous subgroups defined to cover the range of patient outcomes over the 21 examinations.ResultsThe substantial heterogeneity in initial patient presentation and AD progression was captured using three clinically meaningful prognostic subtypes and one terminal subtype exhibiting highly differentiated symptom severity on 7 of the 11 measurement domains. Comparisons of the observed and estimated survival and FTC disability probabilities demonstrated that the estimates were accurate for all five subgroups, supporting their use in AD life expectancy calculations. Mean 10-year TLE differed widely across subgroups: range 3.6–8.0 years, average 6.1 years. Mean 10-year DFLE differed relatively even more widely across subgroups: range 1.2–6.5 years, average 4.0 years. Mean 10-year DLE was relatively much closer: range 1.5–2.3 years, average 2.1 years.ConclusionsThe SLT/L-GoM model yields accurate maximum likelihood estimates of TLE, DFLE, and DLE for patients with AD; it provides a realistic, comprehensive modeling framework for endpoint and resource use/cost calculations.

Prognosis Communication in Late-Life Disability: A Mixed Methods Study.

Long-term prognosis informs clinical and personal decisions for older adults with late-life disability. However, many clinicians worry that telling patients their prognosis may cause harm. To explore the safety of and reactions to prognosis communication in late-life disability. Participants estimated their own life expectancy and were then presented their calculated life expectancy using a validated prognostic index. We used a semi-structured interview guide to ask for their reactions. Qualitative data were analyzed using constant comparative analysis. Potential psychological and behavioral outcomes in response to receiving one's calculated prognosis were recorded and re-assessed 2-4 weeks later. Community-dwelling older adults age 70+ residing in the San Francisco Bay Area. Thirty five older adults with a median age of 80 requiring assistance with ≥1 Activity of Daily Living. Self-estimates of life expectancy were similar to calculated results for 16 participants. 15 estimated their life expectancy to be longer than their calculated life expectancy by >2 years, while 4 shorter by >2 years. An overarching theme of, "fitting life expectancy into one's narrative" emerged from qualitative analysis. Discussing life expectancy led participants to express how they could alter their life expectancy (subtheme "locus of control"), how they saw their present health (subtheme "perceived health"), and their hopes and fears for the remaining years of their lives (subtheme "outlook on remaining years"). Feelings of anxiety and sadness in reaction to receiving calculated prognosis were rare. About half of the disabled older adults' self-estimates of prognosis were similar to calculated estimates. Evidence of sadness or anxiety was rare. These data suggest that in most cases, clinicians may offer to discuss prognosis.

Vidutinė tikėtina gyvenimo trukmė tarpukario Lietuvoje

Vidutinė gyvenimo trukmė (VTGT, arba e°x) šiuo metu laikoma vienu iš patikimiausių gerovės rodiklių, naudojamų jos tarptautiniams skirtumams ir pokyčiams per tam tikrą laiką palyginti. Pirmos išsamios mirtingumo lentelės, reikalingos vidutinei tikėtinai gyvenimo trukmei (VTGT) apskaičiuoti, Lietuvoje buvo išleistos (vien „tarnybiniam naudojimui“) tik 1963 m. ir apėmė 1958–1959 m. laikotarpį. Nuo praėjusio amžiaus aštuntojo dešimtmečio išsiplėtė osteologine medžiaga pagrįsti senovės Lietuvos gyventojų paleodemografiniai tyrimai. Šiuo metu apie Lietuvos gyventojų VTGT viduriniajame geležies amžiuje (V–VII a. po Kr.) ir vėlyvaisiais viduramžiais žinome daugiau negu XX amžiuje (iki 1958–1959 m.), nes tėra vienas šio laikotarpio VTGT skaičiavimas, kurį 1966 m. apgintoje disertacijoje pateikė Antanas Merčaitis: 1925–1926 m.visų Lietuvos gyventojų e°0 = 50, 25 metų (vyrų – 48,58; moterų – 51,89). Naudojant kitokį metodą, straipsnyje pateikiami nauji VTGT Lietuvoje 1925 m. ir 1932 m. skaičiavimai (mirtingumo lentelės), rodantys per šį laikotarpį vykusią gerovės pažangą. 1925 m. visų Lietuvos gyventojųe°0 = 48,72 metai (vyrų – 47,12; moterų – 50,27). 1932 m. VTGT padidėjo iki e°0 = 52,07 metų visų gyventojų, 50,43 vyrų ir 53,62 moterų. Straipsnis baigiamas VTGT Lietuvoje ir kitose tarpukario Europos šalyse palyginimu.

Impact of injury-related mortality on life expectancy in Zhejiang, China based on death and population surveillance data

BackgroundLife expectancy is a statistical measure of the average time an organism is expected to live. The purpose of this study was to evaluate the impact of injury-related mortality on life expectancy in Zhejiang Province.MethodsOur study used standard life tables to calculate life expectancy and cause-removed life expectancy based on mortality data from the Zhejiang Chronic Disease Surveillance System.ResultsLife expectancy of residents in Zhejiang was 77.83 years in 2013, with females having a higher life expectancy than males. The decrease in life expectancy caused by injury-related deaths was 1.19 years, the effect of which was reduced for females and urban residents compared with males and rural residents. The greatest impact on life expectancy was road traffic injuries (RTIs), (0.29 years lost overall, 0.36 for men vs. 0.21 for women and 0.26 for urban residents vs. 0.31 for rural residents). The main causes were falls (0.29 years lost overall, 0.30 for men vs. 0.28 for women and 0.28 for urban residents vs. 0.30 for rural residents), followed by drowning (0.15 years lost), suicide (0.11 years lost), and poisoning (0.04 years). For children less than 5 years old and elders aged over 65, drowning had a greater impact than falls.ConclusionsOur findings indicate that injury deaths had a major impact on life expectancy in Zhejiang. More attention should be paid to road traffic injury, and preventive action should be taken to reduce injury-related deaths to increase life expectancy, especially in children under five years of age and the elders over 65 years of age.

Calculating life expectancy to inform prostate cancer screening and treatment decisions

Calculating life expectancy to inform prostate cancer screening and treatment decisions

Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble

SummaryBackgroundProjections of future mortality and life expectancy are needed to plan for health and social services and pensions. Our aim was to forecast national age-specific mortality and life expectancy using an approach that takes into account the uncertainty related to the choice of forecasting model.MethodsWe developed an ensemble of 21 forecasting models, all of which probabilistically contributed towards the final projections. We applied this approach to project age-specific mortality to 2030 in 35 industrialised countries with high-quality vital statistics data. We used age-specific death rates to calculate life expectancy at birth and at age 65 years, and probability of dying before age 70 years, with life table methods.FindingsLife expectancy is projected to increase in all 35 countries with a probability of at least 65% for women and 85% for men. There is a 90% probability that life expectancy at birth among South Korean women in 2030 will be higher than 86·7 years, the same as the highest worldwide life expectancy in 2012, and a 57% probability that it will be higher than 90 years. Projected female life expectancy in South Korea is followed by those in France, Spain, and Japan. There is a greater than 95% probability that life expectancy at birth among men in South Korea, Australia, and Switzerland will surpass 80 years in 2030, and a greater than 27% probability that it will surpass 85 years. Of the countries studied, the USA, Japan, Sweden, Greece, Macedonia, and Serbia have some of the lowest projected life expectancy gains for both men and women. The female life expectancy advantage over men is likely to shrink by 2030 in every country except Mexico, where female life expectancy is predicted to increase more than male life expectancy, and in Chile, France, and Greece where the two sexes will see similar gains. More than half of the projected gains in life expectancy at birth in women will be due to enhanced longevity above age 65 years.InterpretationThere is more than a 50% probability that by 2030, national female life expectancy will break the 90 year barrier, a level that was deemed unattainable by some at the turn of the 21st century. Our projections show continued increases in longevity, and the need for careful planning for health and social services and pensions.FundingUK Medical Research Council and US Environmental Protection Agency.

Study on Some Indicators of Healthy Life Expectancy in the Democratic People’s Republic of Korea

Nowadays it is one of the important issues to work out and analyze how long people lead a healthy life in order to clearly understand the health status of population in our country and to take countermeasures for the improvement of their health. Compute the disability life expectancy and disability-free life expectancy (DFLE) in DPRK by sex, age group, urban and rural areas, and types of disability among several indicators which reflect the healthy life expectancy of the population. For the first time, the 2008 census in DPRK provided data on degree of impairments related to human activities. The disability life expectancy is derived from the method commonly used in life expectancy calculation and the DFLE is derived in continuous time and, because of data limitation, implemented using piecewise-constant disability prevalence. (Hereunder disability life expectancy will be expressed as life expectancy.) The life expectancy (LE) of men at birth is 65.6 years and that of women is 72.7 years in DPRK. The life expectancy is 70.5 years in urban areas and 67.6 years in rural areas. The LE at age 60 is 13.2 years for males and 19.1 years for females. The DFLE at age 60 is 8.1 years for males and 10.8 years for females. In DPRK, women live longer than men, on average, but spend more years of living with disability. People in urban areas live longer than those in rural areas and they spend more years of living, free of disability. Such calculation and analysis will contribute to the promotion of the public health effectively in the future.

Change in life expectancy with type 2 diabetes: a study using claims data from lower Saxony, Germany

BackgroundThis study estimates life expectancy with and without type 2 diabetes for individuals in Lower Saxony, Germany in order to detect a trend in population health.MethodsMorbidity and mortality data derived from German administrative claims data (statutory health insurance, AOK Niedersachsen, N = 2,900,065) were used covering 10 years from 2005 to 2014. Life table analysis was applied for calculating life expectancy, life expectancy free of type 2 diabetes, life expectancy with type 2 diabetes, and the proportion of life expectancy free of diabetes to total life expectancy using the Sullivan method.ResultsThe total life expectancy increase is stronger in men than in women: At the age of 20, total life expectancy was 55.0 years in 2005 and 56.3 years in 2014 for men, whereas it was 61.7 years in 2005 and 62.5 years in 2014 for women. Decreases in life expectancy without type 2 diabetes were more pronounced in women than in men. Accordingly, life expectancy with type 2 diabetes increased in both women and in men. The proportion of life expectancy without diabetes to total life expectancy decreased, indicating a similar development in both. For example, at the age of 60, the proportion of life expectancy without diabetes to total life expectancy decreased from 0.75 in 2005 to 0.66 in 2014 for men, while it decreased from 0.77 in 2005 to 0.70 in 2014 for women.ConclusionsAgainst the background of increasing total life expectancy, the time spent in morbidity increased for the case of type 2 diabetes in Lower Saxony, Germany.

Life Expectancy in Pleural and Peritoneal Mesothelioma.

Background. Mesothelioma is a rare cancer with a historically dire prognosis. We sought to calculate life expectancies for patients with pleural or peritoneal mesothelioma, both at time of diagnosis and several years later, and to examine whether survival has improved in recent years. Methods. Data on 10,258 pleural and 1,229 peritoneal patients from the SEER US national cancer database, 1973–2011, were analyzed using the Cox proportional hazards regression model. Results. The major factors related to survival were age, sex, stage, grade, histology, and treatment. Survival improved only modestly over the study period: 0.5% per year for pleural and 2% for peritoneal. Conclusions. Life expectancies were markedly reduced from normal, even amongst 5-year survivors with the most favorable characteristics and treatment options.

Personalized risk communication for personalized risk assessment: Real world assessment of knowledge and motivation for six mortality risk measures from an online life expectancy calculator

ABSTRACTIn the clinical setting, previous studies have shown personalized risk assessment and communication improves risk perception and motivation. We evaluated an online health calculator that estimated and presented six different measures of life expectancy/mortality based on a person’s sociodemographic and health behavior profile. Immediately after receiving calculator results, participants were invited to complete an online survey that asked how informative and motivating they found each risk measure, whether they would share their results and whether the calculator provided information they need to make lifestyle changes. Over 80% of the 317 survey respondents found at least one of six healthy living measures highly informative and motivating, but there was moderate heterogeneity regarding which measures respondents found most informative and motivating. Overall, health age was most informative and life expectancy most motivating. Approximately 40% of respondents would share the results with their clinician (44%) or social networks (38%), although the information they would share was often different from what they found informative or motivational. Online personalized risk assessment allows for a more personalized communication compared to historic paper-based risk assessment to maximize knowledge and motivation, and people should be provided a range of risk communication measures that reflect different risk perspectives.

Life expectancy calculation in urology: Are we equitably treating older patients?

IntroductionThe aim of our study was to determine the contemporary practice in the utilization of life expectancy (LE) calculations among urological clinicians.Material and methodsMembers of the Irish Society of Urology (ISU) and the British Association of Urological Surgeons (BAUS) completed a questionnaire on LE utilization in urological practice.ResultsThe survey was delivered to 1251 clinicians and the response rate was 17% (n = 208/1251). The majority (61%, n = 127) of urologists were aware of methods available for estimated LE calculation.Seventy-one percent (n = 148) had never utilized LE analysis in clinical practice and 81% (n = 170) routinely used 'eyeballing' (empiric prediction) for estimating LE. Life expectancy tables were utilized infrequently (12%, n = 25) in making the decision for treatment in the setting of multi-disciplinary meetings.ConclusionsLE is poorly integrated into treatment decision-making; not only for the management of urological patients but also in the multidisciplinary setting. Further education and awareness regarding the importance of LE is vital.

Demografická analýza kultúr popolnicových polí na Slovensku

Based on the anthropological analyses the content of cremation graves from the Urnfield period was established demographic structure of the population. There was calculated life expectancy and age structure. These data were compared with two cultural complexes of Urnfields (Lusatian culture and cultural complex of South-eastern Urnfields) in Slovakia. The values have been shown on transparent each tables and graphs

Host plants mixture and fitness ofKolla paulula: with an evaluation of the application of Weibull function

AbstractThe xylem‐feeding leafhopperKolla paulula(Walker), a vector of Pierce's disease, occurs primarily on weeds in and around fruit and ornamental crop orchards in Taiwan. Because our preliminary studies showed thatK. paululaperformed poorly when reared on pilose beggarticks (Bidens pilosaL. var.radiata) (PB) or trilobate wedelia (Wedelia triloba(L.)) (TW) alone, we collected the life table data ofK. paululareared on a mixture of both host plants to determine the effect at the population level. During their lifespan, 95.6% of feeding time was spent on the major host plant (PB) and only 4.4% on the minor host plant (TW). The intrinsic rate of increase (r), finite rate of increase (λ), net reproduction rate (R0) and mean generation time (T) ofK. paululawere 0.0487, 1.0500 day−1, 35.86 offspring and 73.4 days, respectively. Because more than 95% of the insects have been observed feeding on both plants, this would indicate that the minor host plant may play an important role in the fitness ofK. paulularegardless of the short feeding time. We calculated the percentage contribution to the population parameters made by females that had fed on both PB and TW and compared these with the values obtained for offspring of females that had fed solely on PB. We also evaluated the usefulness of applying the Weibull distribution in demographic studies. We demonstrated that when there is a higher mortality in specific life stages, the fitted Weibull distribution would be inaccurate in describing the survival curve and that application of the fitted curve to the calculation of life expectancy or other statistics would result in significant discrepancy to the actual curve.

Sustained 10-year gain in adult life expectancy following antiretroviral therapy roll-out in rural Malawi: July 2005 to June 2014

Background: Improved life expectancy in high HIV prevalence populations has been observed since antiretroviral therapy (ART) scale-up. However, it is unclear if the benefits are sustained, and the mortality among HIV-positive individuals not (yet) on ART is not well described. We assessed temporal change in mortality over 9 years in rural Malawi. Methods: Within a demographic surveillance site in northern rural Malawi, we combined demographic, HIV and ART uptake data. We calculated life expectancy using Kaplan-Meier estimates, and compared mortality rates and rate ratios using Poisson regression, by period of ART availability (July 2005–June 2008, July 2008–June 2011 and July 2011–June 2014). Results: Among 32 664 individuals there were 1424 deaths; 1930 individuals were known HIV-positive, of whom 1382 started ART. Overall, life expectancy at age 15 years increased by 10 years within 5 years of ART introduction, and plateaued. Age-standardized adult mortality rates declined from 11.3/1000 to 7.5/1000 person-years between the first and last time period. In July 2011-June 2014 compared with July 2005–June 2008, mortality declined in HIV-positive individuals on ART (rate ratio adjusted (aRR) for age, sex, location and education, 0.3; 95% confidence interval (CI) 0.2–0.5) and in those not (yet) on ART (aRR 0.3; 95%CI 0.1–0.5) but not in HIV-negative individuals (aRR 1.1; 95%CI 0.7–1.9). Conclusions: Total population adult life expectancy increased toward that of HIV-negative individuals by 2011 and remained raised. The reduction in all-cause and HIV-related mortality in HIV-positive individuals not (yet) on ART suggests ART uptake is occurring at an earlier disease stage, particularly in women.

Prostate cancer: Estimated life expectancy: integration of age and comorbidities.

Most guidelines recommend integration of estimated life expectancy into the routine decision-making process in prostate cancer treatment. This article underlines the use of both age and comorbidities to calculate life expectancy, which is highly dependent on the health status of the individual patient.

Increasing inequality in age of death at shared levels of life expectancy: A comparative study of Scotland and England and Wales

There is a strong negative correlation between increasing life expectancy and decreasing lifespan variation, a measure of inequality. Previous research suggests that countries achieving a high level of life expectancy later in time generally do so with lower lifespan variation than forerunner countries. This may be because they are able to capitalise on lessons already learnt. However, a few countries achieve a high level of life expectancy later in time with higher inequality. Scotland appears to be such a country and presents an interesting case study because it previously experienced lower inequality when reaching the same level of life expectancy as its closest comparator England and Wales. We calculated life expectancy and lifespan variation for Scotland and England and Wales for the years 1950 to 2012, comparing Scotland to England and Wales when it reached the same level of life expectancy later on in time, and assessed the difference in the level of lifespan variation. The lifespan variation difference between the two countries was then decomposed into age-specific components. Analysis was carried out for males and females separately. Since the 1950s Scotland has achieved the same level of life expectancy at least ten years later in time than England and Wales. Initially it did so with lower lifespan variation. Following the 1980s Scotland has been achieving the same level of life expectancy later in time than England and Wales and with higher inequality, particularly for males. Decomposition revealed that higher inequality is partly explained by lower older age mortality rates but primarily by higher premature adult age mortality rates when life expectancy is the same. Existing studies suggest that premature adult mortality rates are strongly associated with the social determinants of health and may be amenable to social and economic policies. So addressing these policy areas may have benefits for both inequality and population health in Scotland.

Past inhabitants of Garbary – a biocultural perspective

The present work analyses the bone material unearthed at the graveyard of St Peter the Little’s Church in Garbary. The study is based on research from the years 1978 and 2012. A total of 111 skeletons were analysed, all of them of medium condition, dating back to the modern period. The material’s diversity level was verified by biological distance assessment. Ward’s method was used for selected measurement features of the neurocranium and the facial skeleton. Sex and age were established simultaneously by means of methods commonly applied in anthropology. The assessment was based on the morphology of the skull and pelvic bones as well as the deciduous and permanent teeth eruption sequence. Cranial measurements and indices were subjected to analysis. Osteometric data provided the basis for an analysis of long bone symmetry, limb length and proportions and bone massiveness indices. A multi-planar reconstruction of individuals’ stature was performed by means of regression formulas developed by various authors. Sexual dimorphism index served indirectly as a measurement of the living conditions of individuals in the population, whereas an analysis of muscular and skeletal stress markers on bones allowed us to evaluate build types. Calculated life expectancy table parameters were used to recreate e.g. individuals’ lifespans and life expectancy structure (by age at death) characteristic of historical populations of Krakow.

Obesity and Life Expectancy with and without Diabetes in Adults Aged 55 Years and Older in the Netherlands: A Prospective Cohort Study.

BackgroundOverweight and obesity are associated with increased risk of type 2 diabetes. Limited evidence exists regarding the effect of excess weight on years lived with and without diabetes. We aimed to determine the association of overweight and obesity with the number of years lived with and without diabetes in a middle-aged and elderly population.Methods and FindingsThe study included 6,499 individuals (3,656 women) aged 55 y and older from the population-based Rotterdam Study. We developed a multistate life table to calculate life expectancy for individuals who were normal weight, overweight, and obese and the difference in years lived with and without diabetes. For life table calculations, we used prevalence, incidence rate, and hazard ratios (HRs) for three transitions (healthy to diabetes, healthy to death, and diabetes to death), stratifying by body mass index (BMI) at baseline and adjusting for confounders. During a median follow-up of 11.1 y, we observed 697 incident diabetes events and 2,192 overall deaths. Obesity was associated with an increased risk of developing diabetes (HR: 2.13 [p < 0.001] for men and 3.54 [p < 0.001] for women). Overweight and obesity were not associated with mortality in men and women with or without diabetes. Total life expectancy remained unaffected by overweight and obesity. Nevertheless, men with obesity aged 55 y and older lived 2.8 (95% CI −6.1 to −0.1) fewer y without diabetes than normal weight individuals, whereas, for women, the difference between obese and normal weight counterparts was 4.7 (95% CI −9.0 to −0.6) y. Men and women with obesity lived 2.8 (95% CI 0.6 to 6.2) and 5.3 (95% CI 1.6 to 9.3) y longer with diabetes, respectively, compared to their normal weight counterparts. Since the implications of these findings could be limited to middle-aged and older white European populations, our results need confirmation in other populations.ConclusionsObesity in the middle aged and elderly is associated with a reduction in the number of years lived free of diabetes and an increase in the number of years lived with diabetes. Those extra years lived with morbidity might place a high toll on individuals and health care systems.

Increased Life Expectancy in New York City, 2001-2010: An Exploration by Cause of Death and Demographic Characteristics.

New York City's (NYC's) life expectancy gains have been greater than those seen nationally. We examined life-expectancy changes over the past decade in selected NYC subpopulations and explored which age groups and causes of death contributed most to the increases. We calculated life expectancy with 95% confidence intervals (CIs) for 2001-2010 by sex and race/ethnicity. Life expectancy was decomposed by age group and cause of death. Logistic regressions were conducted to reinforce the results from decomposition by controlling confounders. Overall, NYC residents' life expectancy at birth increased from 77.9 years (95% CI, 77.8-78.0) in 2001 to 80.9 years (95% CI, 80.8-81.0) in 2010. Decreases in deaths from heart disease, cancer, and HIV disease accounted for 50%, 16%, and 11%, respectively, of the gains. Decreased mortality in older age groups (≥65 years) accounted for 45.6% of the overall change. Life expectancy increased for both sexes, across all racial/ethnic groups, and for both the US-born and the foreign-born. Disparities in life expectancy decreased as overall life expectancy increased. Decreased mortality among older adults and from heart disease, cancer, and HIV infection accounted for most of the increases.