Calculation of longevity and life expectancy in captive elephants

The concepts of longevity (longest lived) and life expectancy (typical age at death) are common demographic parameters that provide insight into a population. Defined as the longest lived individual, longevity is easily calculated but is not representative, as only one individual will live to this extreme. Longevity records for North American Asian elephants (Elephas maximus) and African elephants (Loxodonta africana) have not yet been set, as the oldest individuals (77 and 53 years, respectively) are still alive. One Asian elephant lived to 86 years in the Taipei Zoo. This is comparable to the maximum (though not typical) longevity estimated in wild populations. Calculation of life expectancy, however, must use statistics that are appropriate for the data available, the distribution of the data, and the species' biology. Using a simple arithmetic mean to describe the non‐normally distributed age at death for elephant populations underestimates life expectancy. Use of life‐table analysis to estimate median survivorship or survival analysis to estimate average survivorship are more appropriate for the species' biology and the data available, and provide more accurate estimates. Using a life‐table, the median life expectancy for female Asian elephants (Lx=0.50) is 35.9 years in North America and 41.9 years in Europe. Survival analysis estimates of average life expectancy for Asian elephants are 47.6 years in Europe and 44.8 years in North America. Survival analysis estimates for African elephants are less robust due to less data. Currently the African elephant average life expectancy estimate in North America is 33.0 years, but this is likely to increase with more data, as it has over the past 10 years. Zoo Biol 23:365–373, 2004. © 2004 Wiley‐Liss, Inc.     

Narrowing sex differentials in life expectancy in the industrialized world: Early 1970's to early 1990's

Abstract

Between the early 1970's and 1990's, twelve industrialized nations experienced for the first time a narrowing of their sex differences in life expectancy at age zero. In another set of countries, the differential has not yet reached a stage of convergence, although in some of these nations the female advantage appears to be increasing at a slower pace than ever before. We discuss the demographic and epidemiologic conditions for this new and largely unanticipated trend, as well as its applied and theoretical implications in the context of the following questions: (1) Is the observed change a function of males’ faster pace of gains in life expectancy since the early 1970s? (2) What is the relationship between country differences in socioeconomic development (as measured by GNP) and the degree of convergence in the sex gap in average length of life? (3) What is the degree of association between temporal change in age‐sex specific death rates and change in the sex gap in life expectancy over the twenty‐year interval between the early 1970s and early 1990s? Our results indicate that where some convergence has taken place, in relation to women, men have experienced more rapid gains in survival; the higher a nation's level of social and economic development, the greater the amount of convergence in male and female life expectancies. The most pronounced age‐specific association with the changing sex gap in longevity is that of ages 25–59, where the greater reductions in male mortality, as compared to that for females, contributed to a significant portion of the observed convergence in life expectancy across industrialized nations.     

Genetic variants associated with VLDL, LDL and HDL particle size differ with race/ethnicity

Specific constellations of lipoprotein particle features, reflected as differences in mean lipoprotein particle diameters, are associated with risk of insulin resistance (IR) and cardiovascular disease (CVD). The associations of lipid profiles with disease risk differ by race/ethnicity, the reason for this is not clear. We aimed to examine whether there were additional genetic differences between racial/ethnic groups on lipoprotein profile. Genotypes were assessed using the Affymetrix 6.0 array in 817 related Caucasian participants of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). Association analysis was conducted on fasting mean particle diameters using linear models, adjusted for age, sex and study center as fixed effects, and pedigree as a random effect. Replication of associations reaching P < 1.97 × 10^?05 (the level at which we achieved at least 80 % power to replicate SNP-phenotype associations) was conducted in the Caucasian population of the Multi-Ethnic Study of Atherosclerosis (MESA; N = 2,430). Variants which replicated across both Caucasian populations were subsequently tested for association in the African-American (N = 1,594), Chinese (N = 758), and Hispanic (N = 1,422) populations of MESA. Variants in the APOB gene region were significantly associated with mean VLDL diameter in GOLDN, and in the Caucasian and Hispanic populations of MESA, while variation in the hepatic lipase (LIPC) gene was associated with mean HDL diameter in both Caucasians populations only. Our findings suggest that the genetic underpinnings of mean lipoprotein diameter differ by race/ethnicity. As lipoprotein diameters are modifiable, this may lead new strategies to modify lipoprotein profiles during the reduction of IR that are sensitive to race/ethnicity.     

Maternal obesity is associated with younger age at obesity onset in U.S. adolescent offspring followed into adulthood

Objective: The objective was to test the hypothesis that maternal obesity is associated with younger age of offspring's obesity onset. Research Methods and Procedures: We used prospective, nationally representative, longitudinal data collected across Waves I (1995; 12 to 20 years), II (1996; 13 to 20 years), and III (2001; 18 to 28 years) of the National Longitudinal Study of Adolescent Health (N = 14,654; 49% female). Interval regression analysis was used to assess the association between maternal obesity and age at offspring's obesity onset (International Obesity Task Force BMI ≥30 equivalent age‐ and sex‐specific cut‐off points for adolescents and BMI ≥30 for young adults) using self‐reported heights and weights, adjusting for race/ethnicity, sex, parental education, and family income, accounting for complex sampling design. Results: The net effect of having an obese mother varied by race/ethnicity and was associated with a significantly earlier age at obesity onset (p = 0.0001) for whites [β= ?8.1 year, 95% confidence interval (CI), ?9.3; ?6.9)], blacks (β = ?10.8 years, 95% CI, ?12.4; ?9.2), Hispanics (β = ?7.0 years, 95% CI, ?9.2; ?4.8), and Asians (β = ?8.6 years, 95% CI, ?13.3; ?3.9). Earlier obesity onset (<18 years) was associated with increased severity at young adulthood (mean BMI, 36.0 ± 0.3 kg/m²) vs. onset after age 18 (mean BMI, 34.4 ± 0.2 kg/m²; p = 0.0001). There were no sex differences in the association of maternal obesity to age at obesity onset. Conclusions: Having an obese mother was associated with earlier age at obesity onset across all race/ethnic groups, particularly non‐Hispanic blacks. Early obesity onset has important health consequences because of its association with more severe adult obesity.     

Closing the Gap: Increases in Life Expectancy among Treated HIV-Positive Individuals in the United States and Canada

Background

Combination antiretroviral therapy (ART) has significantly increased survival among HIV-positive adults in the United States (U.S.) and Canada, but gains in life expectancy for this region have not been well characterized. We aim to estimate temporal changes in life expectancy among HIV-positive adults on ART from 2000–2007 in the U.S. and Canada.

Methods

Participants were from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD), aged ≥20 years and on ART. Mortality rates were calculated using participants'' person-time from January 1, 2000 or ART initiation until death, loss to follow-up, or administrative censoring December 31, 2007. Life expectancy at age 20, defined as the average number of additional years that a person of a specific age will live, provided the current age-specific mortality rates remain constant, was estimated using abridged life tables.

Results

The crude mortality rate was 19.8/1,000 person-years, among 22,937 individuals contributing 82,022 person-years and 1,622 deaths. Life expectancy increased from 36.1 [standard error (SE) 0.5] to 51.4 [SE 0.5] years from 2000–2002 to 2006–2007. Men and women had comparable life expectancies in all periods except the last (2006–2007). Life expectancy was lower for individuals with a history of injection drug use, non-whites, and in patients with baseline CD4 counts <350 cells/mm³.

Conclusions

A 20-year-old HIV-positive adult on ART in the U.S. or Canada is expected to live into their early 70 s, a life expectancy approaching that of the general population. Differences by sex, race, HIV transmission risk group, and CD4 count remain.     

Prognostic significance of hemoglobin A1c level in patients hospitalized with coronary artery disease. A systematic review and meta-analysis

Background

To estimate the incidence of complications, life expectancy and diabetes related mortality in the Mexican diabetic population over the next two decades using data from a nation-wide, population based survey and the United Kingdom Prospective Diabetes Study (UKPDS) outcome model

Methods

The cohort included all patients with type 2 diabetes evaluated during the National Health and Nutrition Survey (ENSANut) 2006. ENSANut is a probabilistic multistage stratified survey whose aim was to measure the prevalence of chronic diseases. A total of 47,152 households were visited. Results are shown stratified by gender, time since diagnosis (> or ≤ to 10 years) and age at the time of diagnosis (> or ≤ 40 years).

Results

The prevalence of diabetes in our cohort was 14.4%. The predicted 20 year-incidence for chronic complications per 1000 individuals are: ischemic heart disease 112, myocardial infarction 260, heart failure 113, stroke 101, and amputation 62. Furthermore, 539 per 1000 patients will have a diabetes-related premature death. The average life expectancy for the diabetic population is 10.9 years (95%CI 10.7-11.2); this decreases to 8.3 years after adjusting for quality of life (CI95% 8.1-8.5). Male sex and cases diagnosed after age 40 have the highest risk for developing at least one major complication during the next 20 years.

Conclusions

Based on the current clinical profile of Mexican patients with diabetes, the burden of disease related complications will be tremendous over the next two decades.     

Effect of age,sex, and race on selenium status of healthy residents of Augusta,Georgia

In this study we determined the possible effects of age, sex, and race on selenium (Se) concentration in plasma and erythrocytes and on glutathione peroxidase (GSH-Px) activity in erythrocytes. Two hundred six healthy blacks, whites, males, and females ranging in age from 11 to 60 yr were studied. For the entire population, mean±SDM Se concentrations were 0.104±0.021 μg/mL for plasma and 0.158±0.035 μg/mL for erythrocytes. Mean concentration of Se in plasma was higher in white subjects compared to black subjects (P<0.02). This difference was due exclusively to higher values in young adult white males (age, race, sex interaction). Neither plasma nor erythrocyte Se concentration nor erythrocyte GSH-Px activity were otherwise affected by age. In all groups plasma Se was correlated with erythrocyte Se (P<0.001), but not with glutathione peroxidase. Erythrocyte Se also was correlated inversely with years of smoking (P<0.033) and coffee intake (p<0.01). These results have defined the Se status in this healthy population in Augusta, Georgia as below the reported US mean. The factors underlying the age, race, sex interaction and the health significance of the low Se status in this population should be investigated.     

Disparities in survival improvement for U.S. childhood and adolescent cancer between 1995 and 2019: An analysis of population-based data

BackgroundAlthough treatment advances have increased childhood and adolescent cancer survival, whether patient subgroups have benefited equally from these improvements is unclear.MethodsData on 42,865 malignant primary cancers diagnosed between 1995 and 2019 in individuals ≤ 19 years were obtained from 12 Surveillance, Epidemiology, and End Results registries. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for cancer-specific mortality by age group (0–14 and 15–19 years), sex, and race/ethnicity were estimated using flexible parametric models with a restricted cubic spline function in each of the periods: 2000–2004, 2005–2009, 2010–2014 and 2015–2019, versus 1995–1999. Interactions between diagnosis period and age group (children 0–14 and adolescents 15–19 years at diagnosis), sex, and race/ethnicity were assessed using likelihood ratio tests. Five-year cancer-specific survival rates for each diagnosis period were further predicted.ResultsCompared with the 1995–1999 cohort, the risk of dying from all cancers combined decreased in subgroups defined by age, sex and race/ethnicity with HRs ranging from 0.50 to 0.68 for the 2015–2019 comparison. HRs were more variable by cancer subtype. There were no statistically significant interactions by age group (P_interaction=0.05) or sex (P_interaction=0.71). Despite non-significant differences in cancer-specific survival improvement across different races and ethnicities (P_interaction=0.33) over the study period, minorities consistently experienced inferior survival compared with non-Hispanic Whites.ConclusionsThe substantial improvements in cancer-specific survival for childhood and adolescent cancer did not differ significantly by different age, sex, and race/ethnicity groups. However, persistent gaps in survival between minorities and non-Hispanic Whites are noteworthy.     

Regional differences in awareness and attitudes regarding genetic testing for disease risk and ancestry

Little is known about the lay public’s awareness and attitudes concerning genetic testing and what factors influence their perspectives. The existing literature focuses mainly on ethnic and socioeconomic differences; however, here we focus on how awareness and attitudes regarding genetic testing differ by geographical regions in the US. We compared awareness and attitudes concerning genetic testing for disease risk and ancestry among 452 adults (41% Black and 67% female) in four major US cities, Norman, OK; Cincinnati, OH; Harlem, NY; and Washington, DC; prior to their participation in genetic ancestry testing. The OK participants reported more detail about their personal ancestries (p = 0.02) and valued ancestry testing over disease testing more than all other sites (p < 0.01). The NY participants were more likely than other sites to seek genetic testing for disease (p = 0.01) and to see benefit in finding out more about one’s ancestry (p = 0.02), while the DC participants reported reading and hearing more about genetic testing for African ancestry than all other sites (p < 0.01). These site differences were not better accounted for by sex, age, education, self-reported ethnicity, religion, or previous experience with genetic testing/counseling. Regional differences in awareness and attitudes transcend traditional demographic predictors, such as ethnicity, age and education. Local sociocultural factors, more than ethnicity and socioeconomic status, may influence the public’s awareness and belief systems, particularly with respect to genetics.     

A reassessment of demographic estimates for Pecos Pueblo

The original demographic estimates for Pecos Pueblo, New Mexico (Hooton, 1930) indicated a 60/40 male/female adult sex ratio and an average life expectancy at birth of 42.9 years. A reanalysis of sexes and ages for a subsample of the Pecos collection as well as a reevaluation of a more recent report suggests that the adult sex ratio for Pecos is probably closer to 50/50 and that the mean age at death should be greatly reduced, perhaps by as much as 15 to 20 years.     

Personalized Prediction of Lifetime Benefits with Statin Therapy for Asymptomatic Individuals: A Modeling Study

Background

Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks.

Methods and Findings

A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk.

Conclusions

We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their individual outcomes with statin therapy. Please see later in the article for the Editors'' Summary     

The Promise of Prevention: The Effects of Four Preventable Risk Factors on National Life Expectancy and Life Expectancy Disparities by Race and County in the United States

Background

There has been substantial research on psychosocial and health care determinants of health disparities in the United States (US) but less on the role of modifiable risk factors. We estimated the effects of smoking, high blood pressure, elevated blood glucose, and adiposity on national life expectancy and on disparities in life expectancy and disease-specific mortality among eight subgroups of the US population (the “Eight Americas”) defined on the basis of race and the location and socioeconomic characteristics of county of residence, in 2005.

Methods and Findings

We combined data from the National Health and Nutrition Examination Survey and the Behavioral Risk Factor Surveillance System to estimate unbiased risk factor levels for the Eight Americas. We used data from the National Center for Health Statistics to estimate age–sex–disease-specific number of deaths in 2005. We used systematic reviews and meta-analyses of epidemiologic studies to obtain risk factor effect sizes for disease-specific mortality. We used epidemiologic methods for multiple risk factors to estimate the effects of current exposure to these risk factors on death rates, and life table methods to estimate effects on life expectancy. Asians had the lowest mean body mass index, fasting plasma glucose, and smoking; whites had the lowest systolic blood pressure (SBP). SBP was highest in blacks, especially in the rural South—5–7 mmHg higher than whites. The other three risk factors were highest in Western Native Americans, Southern low-income rural blacks, and/or low-income whites in Appalachia and the Mississippi Valley. Nationally, these four risk factors reduced life expectancy at birth in 2005 by an estimated 4.9 y in men and 4.1 y in women. Life expectancy effects were smallest in Asians (M, 4.1 y; F, 3.6 y) and largest in Southern rural blacks (M, 6.7 y; F, 5.7 y). Standard deviation of life expectancies in the Eight Americas would decline by 0.50 y (18%) in men and 0.45 y (21%) in women if these risks had been reduced to optimal levels. Disparities in the probabilities of dying from cardiovascular diseases and diabetes at different ages would decline by 69%–80%; the corresponding reduction for probabilities of dying from cancers would be 29%–50%. Individually, smoking and high blood pressure had the largest effect on life expectancy disparities.

Conclusions

Disparities in smoking, blood pressure, blood glucose, and adiposity explain a significant proportion of disparities in mortality from cardiovascular diseases and cancers, and some of the life expectancy disparities in the US. Please see later in the article for the Editors'' Summary     

Constitution and By-Laws of the American Association of Physical Anthropologists

From parent populations (N = 50,000) statistically generated, representing different levels of correlation (r) between the age at death and a hypothetical biological indicator (r = 0.8-0.98), reference samples and target demographic samples are randomly drawn. Two iterative techniques, proportional fitting procedure and Bayesian, are used to estimate from the reference samples the age distribution of the targets. Due to the random fluctuations of the pattern of aging, both in the reference and target samples, these techniques converge only in expectation toward the true value of a distribution, but not in practice for any particular realization. Nevertheless, these techniques allow the estimation of the average of an age distribution, even if its shape is unknown. Under the hypothesis that the target sample is drawn from a stationary population, this average represents the life expectancy at 20 years (plus 20 years). Using this mean age at death for the adults and the juvenility index at death (D5-14/D20-ω), a new set of paleodemographic estimators were derived from 40 archaic life tables. For a hypothesized stable population, they give the life expectancy at birth and at 20 years, and the probability of death at 1 and 5 years. © 1996 Wiley-Liss, Inc.     

Years of potential life lost caused by prostate cancer deaths in the United States—Projection from 2004 through 2050

BackgroundThe purpose of this study is to estimate and project the number of years of potential life lost (YPLL) among males who die of prostate cancer in the United States from 2004 through 2050 and compare the projections by race/ethnicity and age, accounting for demographic changes and population growth.MethodsWe applied the life expectancy method to estimate YPLL caused by deaths of prostate cancer and all cancers in men by using 1999–2004 national mortality data, 2008 census population demographic projections, and 2004 U.S. life tables. We performed sensitivity analyses by varying death rate and population projections, and examined increase in YPLL from population growth, changes in demographics, and death rates.ResultsThe number of YPLL caused by prostate cancer deaths was projected to increase by 226.1%, from 291,853 in 2004 to 951,753 in 2050. Hispanics were projected to have the fastest growth in YPLL (977.1% from 2004 to 2050) caused by prostate cancer, followed by non-Hispanic blacks (543.1%), and non-Hispanic others (269.7%). People aged 75 or older was projected to account for 62.0% of YPLL from prostate cancer in 2050 compared with 50.8% in 2004. Of the projected increase in YPLL caused by prostate cancer deaths by 2050, 9.8% were due to changes in demographic composition, 26.8% because of mortality change, and 63.4% because of population growth.ConclusionsYPLL due to prostate cancer deaths are projected to increase dramatically, and become a greater burden in the future. The projections highlight the importance of comprehensive cancer control and research on cancers including prostate cancer and racial/ethnic-specific estimates.     

The reversal of fortunes: trends in county mortality and cross-county mortality disparities in the United States

Background

Counties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long-term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases to county level mortality trends.

Methods and Findings

We used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each county''s life expectancy using a time-based simulation model. Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women, respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had nonsignificant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross-county life expectancy SD was unlikely to be caused by migration.

Conclusions

There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure.     

The association between sleep chronotype and obesity among black and white participants of the Bogalusa Heart Study

ABSTRACT

Research indicates that sleep duration and quality are inter-related factors that contribute to obesity, but few studies have focused on sleep chronotype, representing an individual’s circadian proclivity, nor assessed these factors in racially diverse middle-aged samples. We examined the associations between chronotype and obesity among black and white men and women participating in the Bogalusa Heart Study (BHS).

Body mass index (BMI) and sleep data were available for 1,197 middle-aged men and women (mean age 48.2 ± 5.3 years) who participated in the BHS 2013–2016. Based on the reduced Morningness-Eveningness Questionnaire’s cutoff values for chronotypes, we combined ‘definitely morning’ and ‘moderately morning’ types into ‘morning’ type, ‘definitely evening’ and ‘moderately evening’ types into ‘evening’ type and kept those who were “neither” type in a separate group. We used ‘morning’ type as the referent group. Obesity was defined as a BMI ≥ 30. Multivariable logistic regression models were used to examine associations adjusting for sex, age, education, smoking, alcohol use and drug use, depression, shift work, physical activity and sleep duration.

Evening chronotype, reported by 11.1% of participants, was associated with obesity after multi-variable adjustment, including shift work, physical activity and sleep duration (OR 1.67, 95% CI: 1.08–2.56). However, once stratified by race (black/white), this association was found only among white participants (OR = 1.91, 95% CI = 1.12–3.25) after full adjustment.

In our biracial, community-based population, evening chronotype was independently associated with obesity, specifically among white participants. Further research is needed to identify behavioral, endocrine, nutritional and genetic pathways which underlie these associations.     

The effect of pharmaceutical innovation on longevity: Evidence from the U.S. and 26 high-income countries

This study examines the impact that pharmaceutical innovation, which accounts for most private biomedical research expenditure, has had on longevity. We perform two types of two-way fixed-effects analyses, which control for the effects of many potentially confounding variables. First, we analyze long-run (2006–2018) changes in longevity associated with different diseases in a single country: the U.S. Then, we analyze relative longevity levels associated with different diseases in 26 high-income countries during a single time period (2006–2016). The measure of longevity we analyze, mean age at time of death, is strongly positively correlated across countries with life expectancy at birth. The measure of pharmaceutical innovation we use is the mean vintage (year of initial world launch) of the drugs used to treat each disease in each country. Changes in the vintage distribution of drugs are due to both entry of new drugs and exit of old drugs. Our analysis of U.S. data indicates that the diseases for which there were larger increases in drug vintage tended to have larger increases in the longevity of Americans of all races and both sexes. In other words, the lower the mean age of the drugs, the higher the mean age at death. We test, and are unable to reject, the “parallel trends” hypothesis. We estimate that the 2006–2018 increase in drug vintage increased the mean age at death of Americans by about 6 months (66% of the observed increase). Controlling for sex, race, and education has only a small effect on the estimate of the vintage coefficient. The estimates indicate that drug vintage did not have a significant effect on the mean age at death of decedents with less than 9 years of education. Drug vintage had a positive and significant effect on the mean age at death of decedents with at least 9 years of education, and a larger effect on the mean age at death of decedents with at least 13 years of education. The finding that pharmaceutical innovation has a larger effect on the longevity of people with more education is consistent with previous evidence that more educated people are more likely to use newer drugs. Our analysis of data on 26 high-income countries indicates that the higher the vintage of drugs available to treat a disease in a country, the higher mean age at death was, controlling for fixed disease and country effects. The increase in drug vintage is estimated to have increased mean age at death in the 26 countries by 1.23 years between 2006 and 2016—73% of the observed increase. We obtain estimates of the cost of pharmaceutical innovation—its impact on drug expenditure—as well as estimates of an important benefit of pharmaceutical innovation—the number of life-years gained from it—and of their ratio, i.e., the incremental cost-effectiveness ratio. Estimates of the cost per life-year gained for the U.S. and the 26 countries are $35,817 and $13,904, respectively. Both figures are well below per capita GDP in the respective regions, suggesting that, overall, pharmaceutical innovation was highly cost-effective.     

Geographic distribution of hereditary myopathies in northeast Italy

Abstract

The conventional approach to the measurement of mortality conceptualizes mortality as a function of the age distribution of deaths. Because at contemporary mortality levels the great bulk of deaths are concentrated at the high ages, measures based on deaths are insensitive to mortality changes over most of the life span. An alternative is to conceptualize mortality as a function of the age distribution of death rates. When this is done, large differentials in mortality by sex and by race emerge from the data, calling attention to serious social issues that have been masked by conventional mortality indicators.     

Exploring mechanisms of sex differences in longevity: lifetime ovary exposure and exceptional longevity in dogs

To move closer to understanding the mechanistic underpinnings of sex differences in human longevity, we studied pet dogs to determine whether lifetime duration of ovary exposure was associated with exceptional longevity. This hypothesis was tested by collecting and analyzing lifetime medical histories, age at death, and cause of death for a cohort of canine ‘centenarians’– exceptionally long‐lived Rottweiler dogs that lived more than 30% longer than average life expectancy for the breed. Sex and lifetime ovary exposure in the oldest‐old Rottweilers (age at death, ≥ 13 years) were compared to a cohort of Rottweilers that had usual longevity (age at death, 8.0–10.8 years). Like women, female dogs were more likely than males to achieve exceptional longevity (OR, 95% CI = 2.0, 1.2–3.3; P = 0.006). However, removal of ovaries during the first 4 years of life erased the female survival advantage. In females, a strong positive association between ovaries and longevity persisted in multivariate analysis that considered other factors, such as height, body weight, and mother with exceptional longevity. A beneficial effect of ovaries on longevity in females could not be attributed to resistance against a particular disease or major cause of death. Our results document in dogs a female sex advantage for achieving exceptional longevity and show that lifetime ovary exposure, a factor not previously evaluated in women, is associated with exceptional longevity. This work introduces a conceptual framework for designing additional studies in pet dogs to define the ovary‐sensitive biological processes that promote healthy human longevity.     

Adverse Trends in Ischemic Heart Disease Mortality among Young New Yorkers,Particularly Young Black Women

Background

Ischemic heart disease (IHD) mortality has been on the decline in the United States for decades. However, declines in IHD mortality have been slower in certain groups, including young women and black individuals.

Hypothesis

Trends in IHD vary by age, sex, and race in New York City (NYC). Young female minorities are a vulnerable group that may warrant renewed efforts to reduce IHD.

Methods

IHD mortality trends were assessed in NYC 1980–2008. NYC Vital Statistics data were obtained for analysis. Age-specific IHD mortality rates and confidence bounds were estimated. Trends in IHD mortality were compared by age and race/ethnicity using linear regression of log-transformed mortality rates. Rates and trends in IHD mortality rates were compared between subgroups defined by age, sex and race/ethnicity.

Results

The decline in IHD mortality rates slowed in 1999 among individuals aged 35–54 years but not ≥55. IHD mortality rates were higher among young men than women age 35–54, but annual declines in IHD mortality were slower for women. Black women age 35–54 had higher IHD mortality rates and slower declines in IHD mortality than women of other race/ethnicity groups. IHD mortality trends were similar in black and white men age 35–54.

Conclusions

The decline in IHD mortality rates has slowed in recent years among younger, but not older, individuals in NYC. There was an association between sex and race/ethnicity on IHD mortality rates and trends. Young black women may benefit from targeted medical and public health interventions to reduce IHD mortality.