Cause‐specific mortality among older African‐Americans: Correlates and consequences of age misreporting

Abstract

This paper examines the quality of age reporting on death certificates of elderly African‐Americans by major causes of death. We utilize a sample of death certificates linked to early census records and to Social Security Administration records to establish a “true” age at death. We then examine the patterns, predictors, and consequences of age misreporting for major causes of death. We find a pattern of greater age misreporting among females, identify educational background as a key predictor of accurate age reporting, and show that mortality crossovers are eliminated for most causes of death when more accurate age data are used.     

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.     

Cancer mortality among adolescents and young adults: A historical cohort in a reference institution for cancer treatment in Santa Catarina/South of Brazil 2002–2013

ObjectiveTo identify factors associated with early mortality from cancer in adolescents and young adults in a reference institution for oncology treatment in Santa Catarina, Brazil.MethodsWe studied a retrospective cohort with an intentional sample of adolescents (ages 15–19) and young adults (ages 20–29) diagnosed with neoplasia. Secondary data were acquired from January 2002 to December 2013. Kaplan–Meier and Cox regression methods were used for survival analysis. Logistical analysis tested the association between early death (lower tertile between diagnosis and death, according to cancer type) and clinical or sociodemographic variables.ResultsWe included a total of 889 cases with an average age of 23, with similar gender distributions and a predominance of Caucasian ethnicity. Using the Cox framework of proportional risks adjusted for neoplasia types and gender, individuals with non-hematological neoplasia (solid tumors) presented a 47% higher risk of dying when compared with individuals diagnosed with leukemias and lymphomas (HR: 1.47; 95%CI: 1.12–1.93). Chances of death were 31% higher for males than for females (HR: 1.31; 95%CI: 1.02–1.69). When adjusting for type of neoplasia and age (15–24 and 25–29) the risk of death by cancer was 51% greater in individuals diagnosed with non-hematological neoplasia when compared with individuals diagnosed with leukemias and lymphomas (HR: 1.51; 95%CI: 1.15–1.99). The chance of death by cancer in patients under the age of 25 was 33% greater when compared to that in older patients between the ages of 25 and 29 (HR: 1.33; 95%CI: 1.04–1.75). In multiple regression analysis, factors associated with early mortality from cancer were the number of years in school (P = 0.011) and time between diagnosis and start of treatment (P < 0.001).ConclusionsThe sample studied with a longer period of time between diagnosis and the start of treatment (access to oncology therapy) and with fewer years in school showed that these factors had important roles in early death from cancer for the observed individuals. This must be considered when planning and identifying risk in young cancer patients in order to lower the impact of the disease on mortality for this age group.     

Causes of death which contribute to the mortality crossover effect

Abstract

Death rates vary over the life cycle in a standard fashion, with mortality probabilities being highest at infant and older ages. Nevertheless, when age curves of mortality are compared for different populations, they sometimes can be seen to intersect so that one population has higher death rates at younger and middle ages and lower rates at older ages. Past research has shown that this phenomenon is not due to erroneous data and is probably a result of some type of selection in survival patterns. A sample of pairs of mortality curves, 31 of which cross over and 31 of which do not, for combinations of countries and dates are analyzed to discover which causes of death are associated with the crossover phenomenon at the older ages. Cardiovascular and “other and unknown” diseases appear to contribute strongly to the crossover effect. Further research should deal with other comparisons and explore the underlying social and environmental factors.     

Causes of death and mortality crossovers by race

Abstract

The phenomenon of “mortality crossovers,” the intersection of age curves of mortality at older ages, has been observed in comparisons of various populations for some time. Some researchers have argued that crossovers are an artifact of deficient reporting of age that is greater for some populations than others. Other researchers attribute crossovers to selective processes by age that vary by group. We use mortality data from the National Center for Health Statistics for the U.S. at ages 55 and over, supplemented by comparable data from matched records of the National Health Interview Survey and National Death Index, to reexamine causes of death linked to mortality crossovers for Whites and Blacks in the U.S. Findings portray a more elaborate set of influences of causes of death than has been discovered heretofore; however, the major finding is that the mortality crossover for Whites and Blacks in the U. S. is real and, although observed for several causes of death, operates principally through varying trajectories of heart disease mortality.     

Sex differentials in infant and child mortality in Korea

Abstract

This paper reports on a study of infant and child mortality in the Republic of Korea, a country known for a strong son preference, using the 1974 World Fertility Survey data. When the age‐specific probabilities of dying for ages zero to five are compared for male and female children, an unusual pattern of relatively high female mortality is observed. The higher female mortality is more pronounced during childhood than during infancy. Multivariate analysis of life tables, using a hazard model, shows that covariates influencing the mortality at young ages differ for male and female children and suggests that male and female children receive unequal care by their parents. The analysis also reveals different patterns of interaction between infant and child mortality and mother's fertility control behavior depending on the sex of the child.     

DNA methylation age of blood predicts all-cause mortality in later life

BackgroundDNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age.ResultsHere we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δ_age) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δ_age and mortality. A 5-year higher Δ_age is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δ_age. A pedigree-based heritability analysis of Δ_age was conducted in a separate cohort. The heritability of Δ_age was 0.43.ConclusionsDNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.     

Emerging tobacco hazards in China: 2. Early mortality results from a prospective study

ObjectiveTo monitor the evolving epidemic of mortality from tobacco in China following the large increase in male cigarette use in recent decades.DesignProspective study of smoking and mortality starting with 224 500 interviewees who should eventually be followed for some decades.Setting45 nationally representative small urban or rural areas distributed across China.SubjectsMale population aged 40 or over in 1991, of whom about 80% were interviewed about smoking, drinking, and medical history.Results74% were smokers (73% current, only 1% former), but few of this generation would have smoked substantial numbers of cigarettes since early adult life. Overall mortality is increased among smokers (risk ratio 1.19; 95% confidence interval 1.13 to 1.25, P<0.0001). Almost all the increased mortality involved neoplastic, respiratory, or vascular disease. The overall risk ratios currently associated with smoking are less extreme in rural areas (1.26, 1.12, or 1.02 respectively for smokers who started before age 20, at 20-24, or at older ages) than in urban areas (1.73, 1.40, or 1.16 respectively).ConclusionThis prospective study and the accompanying retrospective study show that by 1990 smoking was already causing about 12% of Chinese male mortality in middle age. This proportion is predicted to rise to about 33% by 2030. Long term continuation of the prospective study (with periodic resurveys) can monitor the evolution of this epidemic.

Key messages

• In recent years most young men in China have become persistent cigarette smokers, starting at about age 20; this will cause high mortality in middle age and old age
• Currently, however, most middle aged and older smokers (particularly in rural areas) have not persistently used substantial daily numbers of cigarettes ever since they were young adults, so their current tobacco attributed mortality is more limited
• Nationally representative retrospective and prospective studies now show that in about 1990 “only” about 12% of adult male deaths in middle age were caused by smoking
• Continuation of the present prospective study will monitor the growth of the epidemic of tobacco related deaths in China over the next few decades

     

Associations between early-life growth pattern and body size and follicular lymphoma risk and survival: a family-based case-control study

BackgroundThe influence of early-life growth pattern and body size on follicular lymphoma (FL) risk and survival is unclear. In this study, we aimed to investigate the association between gestational age, growth during childhood, body size, changes in body shape over time, and FL risk and survival.MethodsWe conducted a population-based family case-control study and included 706 cases and 490 controls. We ascertained gestational age, growth during childhood, body size and body shape using questionnaires and followed-up cases (median=83 months) using record linkage with national death records. We used a group-based trajectory modeling approach to identify body shape trajectories from ages 5–70. We examined associations with FL risk using unconditional logistic regression and used Cox regression to assess the association between body mass index (BMI) and all-cause and FL-specific mortality among cases.ResultsWe found no association between gestational age, childhood height and FL risk. We observed a modest increase in FL risk with being obese 5 years prior to enrolment (OR=1.43, 95 %CI=0.99–2.06; BMI ≥30 kg/m²) and per 5-kg/m² increase in BMI 5 years prior to enrolment (OR=1.14, 95 %CI=0.99–1.31). The excess risk for obesity 5 years prior to enrolment was higher for ever-smokers (OR=2.00, 95 %CI=1.08–3.69) than never-smokers (OR=1.14, 95 %CI=0.71–1.84). We found no association between FL risk and BMI at enrolment, BMI for heaviest lifetime weight, the highest categories of adult weight or height, trouser size, body shape at different ages or body shape trajectory. We also observed no association between all-cause or FL-specific mortality and excess adiposity at or prior to enrolment.ConclusionWe observed a weak association between elevated BMI and FL risk, and no association with all-cause or FL-specific mortality, consistent with previous studies. Future studies incorporating biomarkers are needed to elucidate possible mechanisms underlying the role of body composition in FL etiology.     

Patterns of mortality and causes of death among Rhode Island Jews, 1979–1981

Abstract

Using information provided by institutions handling Jewish deaths, this study identified 735 deaths among Jewish residents of Rhode Island during 1979–81. Official death records then provided data on the characteristics of the deceased and on cause of death, allowing comparisons of Jewish/non‐ Jewish patterns of mortality and cause of death, as well as analysis of differentials among the Jewish decedents, taking account of birthplace and occupation. The findings indicate that relatively fewer Jewish males die at ages below 65, and more at ages 85 and over than is true of total white males. Jewish females exhibit an age‐at‐death pattern more similar to that of all white women. These sex differences characterize cause of death as well. Differences are more pronounced between Jewish and non‐Jewish males than between the female groups. Most noteworthy, Jewish male deaths from diabetes are significantly higher and deaths from respiratory disease significantly lower than among total white men. Differentials in age of death between Jewish native‐born and foreign‐born are largely a function of their differential age composition, and socioeconomic status showed no clear relation to age at death or cause of death.     

Cancer in Guam and Hawaii: A comparison of two U.S. Island populations

BackgroundCancer disparities within and across populations provide insight into the influence of lifestyle, environment, and genetic factors on cancer risk.MethodsGuam cancer incidence and mortality were compared to that of Hawaii using data from their respective population-based, central cancer registries.ResultsIn 2009–2013, overall cancer incidence was substantially lower in Guam than in Hawaii for both sexes while overall cancer mortality was higher for Guam males. Cervical cancer incidence and prostate cancer mortality were higher in Guam. Both incidence and mortality were higher among Guam men for cancers of the lung & bronchus, liver & intrahepatic bile duct, and nasopharynx; Chamorro men were disproportionately affected by these cancers. Filipinos and Whites in Guam had lower overall cancer incidence compared to Filipinos and Whites in Hawaii. Although breast cancer incidence was significantly lower in Guam compared to Hawaii, women in Guam presented at younger ages and with rarer disease histologies such as inflammatory carcinoma were more prevalent. Guam patients were also diagnosed at younger ages for cancers of bladder, pancreas, colon & rectum, liver & intrahepatic bile duct, lung & bronchus, stomach, non-Hodgkin lymphoma, and leukemia.ConclusionSmoking, infectious agents, and betel nut chewing appear to be important contributors to the burden of cancer in Guam. Earlier onset of cancer in Guam suggests earlier age of exposure to key risk factors and/or a more aggressive pathogenesis. Contrasting cancer patterns within Guam and between Guam and Hawaii underscore the potential influence of genes, lifestyle, and environmental factors on cancer development and progression.     

Patterns and Trends in Accidental Poisoning Deaths: Pennsylvania’s Experience 1979-2014

IntroductionThe purpose of this study was to examine county and state-level accidental poisoning mortality trends in Pennsylvania from 1979 to 2014.MethodsCrude and age-adjusted death rates were formed for age group, race, sex, and county for accidental poisonings (ICD 10 codes X40-X49) from 1979 to 2014 for ages 15+ using the Mortality and Population Data System housed at the University of Pittsburgh. Rate ratios were calculated comparing rates from 1979 to 2014, overall and by sex, age group, and race. Joinpoint regression was used to detect statistically significant changes in trends of age-adjusted mortality rates.ResultsRate ratios for accidental poisoning mortality in Pennsylvania increased more than 14-fold from 1979 to 2014. The largest rate ratios were among 35–44 year olds, females, and White adults. The highest accidental poisoning mortality rates were found in the counties of Southwestern Pennsylvania, those surrounding Philadelphia, and those in Northeast Pennsylvania near Scranton.ConclusionsThe patterns and locations of accidental poisoning mortality by race, sex, and age group provide direction for interventions and policy makers. In particular, this study found the highest rate ratios in PA among females, whites, and the age group 35–44.     

Age differences between spouses in first marriages

Absract

Vital statistics data indicate that the age difference between spouses in first marriages has narrowed for those born between 1931 and 1951 and married by age 25. It appears that the largest declines have occurred at the older ages of marriage, although there have been reductions at all ages. The possibility that the narrowing of the age gap can be attributed to the recent “marriage squeeze” is examined using data from the 1976 National Survey of Family Growth. Insofar as it is adequately measured, the squeeze is found to be insignificant. It seems that age at marriage of the wife is inversely related to a couple's age difference. That this might simply be due to the age distribution of available men is considered and rejected. It is speculated that the relation between age difference and age at marriage is a consequence of changing preferences, not of the supposed shortage of suitable single men.     

Alcohol consumption and mortality: modelling risks for men and women at different ages

ObjectiveTo estimate the relation between alcohol consumption and risk of death, the level of alcohol consumption at which risk is least, and how these vary with age and sex.DesignAnalysis using published systematic reviews and population data.SettingEngland and Wales in 1997.ResultsA direct dose-response relation exists between alcohol consumption and risk of death in women aged 16-54 and in men aged 16-34. At older ages the relation is U shaped. The level at which the risk is lowest increases with age, reaching 3 units a week in women aged over 65 and 8 units a week in men aged over 65. The level at which the risk is increased by 5% above this minimum is 8 units a week in women aged 16-24 and 5 units a week in men aged 16-24, increasing to 20 and 34 units a week in women and men aged over 65, respectively.ConclusionsSubstantially increased risks of all cause mortality can occur even in people drinking lower than recommended limits, and especially among younger people.

What is already known on this topic

Non-drinkers and heavy drinkers have higher all cause mortality rates than light drinkers—the U shaped curveThe precise shape and location of the U are likely to depend on age and sex, but this has not been quantified

What this study adds

The level of alcohol consumption that carries the lowest mortality ranges from 0 in men and women aged under 35 to 3 units a week in women aged over 65 and 8 units a week in men aged over 65The level of alcohol consumption that carries a 5% increase in mortality increases with age from 8 to 20 units a week in women and from 5 to 34 units a week in menOur calculations were for England and Wales in 1997: nadirs are likely to be lower in the future and in countries with less ischaemic heart disease     

Sudden infant death syndrome and the age‐cause proxy relationship in infancy

Abstract

Evidence from a longitudinal study of the relationship between socioeconomic status and infant mortality in metropolitan Ohio is presented in an effort to throw additional light on the continuing debate over the validity of the age‐cause proxy relationship in infancy. The results indicate that while there is a fairly strong and consistent association between neonatal mortality and endogenous causes of death that is little affected by the classification of Sudden Infant Death Syndrome, the nature of the association between postneonatal mortality and exogenous causes of death varies from weak to moderate depending upon where this cause is included. Additional evidence pertaining to the role of SIDS in contributing to the long‐standing inverse association between infant mortality and socioeconomic status is presented, thus further emphasizing the need for continued research to clarify the etiologic mechanisms of this poorly understood condition.     

How does variation in fetal loss affect the distribution of waiting times to conception?

Abstract

Unmeasured variation has long been a concern in analyses of the waiting time to conception. Recent work by Heckman and Walker (1991) and Trussell and Rodriguez (1990) has underscored the fact that statistical considerations alone cannot discriminate among likely models describing the distribution. Here, we specify a single theoretically important source of heterogeneity, namely variability in intrauterine mortality, and assess its effects on the waiting times to a conception which results in a live birth. We find that the effects of variation in fetal loss are confined to the tail of the distribution. Unless variation in fetal loss is extremely large or a substantial proportion of observed waiting times are initiated at late ages, variation in fetal loss does not appear to explain much variation in conception waits. We conclude that heterogeneity in fetal loss does not explain the variation in fecundability that has been observed for first birth intervals. This conclusion supports the hypothesis that at early ages (below age 35) variation in the waiting time to a fertile conception may largely reflect the proportion of nonsusceptible couples in the population. The analyses suggest that for the purposes of testing theoretically motivated models, future efforts should be directed toward examining reproductive experience after age 35 and toward incorporating information on characteristics of the fertile period as it becomes known.     

Reproductive and socioeconomic determinants of child survival: Confounded,interactive, and age‐dependent effects

Abstract

Studies of infant and child mortality have evolved to distinguish between two sets of explanatory variables—factors related to reproductive or maternal characteristics and socioeconomic factors, generally described as characteristics of the family or household. Almost all multivariate analyses include variables from each of these two sets, but there has been little consideration of the relationship between them. We examine how these two sets of variables jointly affect mortality. We test first for confounded effects by examining socioeconomic effects while excluding and then including reproductive variables in nested multivariate models. Next, we look for age‐dependent effects among the explanatory variables and find that reproductive and socioeconomic factors affect mortality at differing ages of children. Finally, we examine interactive effects of the two sets of variables. We conclude that the higher mortality observed among the low status groups is not a result of greater concentration of poor reproductive patterns in those groups. Instead, higher status groups probably have more resources available for combating the negative effects of the same high‐risk reproductive patterns.     

Leptospirosis: Morbidity,mortality, and spatial distribution of hospitalized cases in Ecuador. A nationwide study 2000-2020

BackgroundIn Ecuador, leptospirosis surveillance involves a mandatory notification of all cases and a hospitalization for severe illness. Morbidity and mortality are, nevertheless, underestimated and contribute directly to the status of leptospirosis as a neglected disease. Leptospira spp. is zoonotic in Ecuador with established endemic transmission in the Tropics. Here, we review retrospective national data within the country to aid in control strategies.Methodology/Principal findingsIn a population-based nationwide study, we analysed morbidity, mortality, and spatial distribution on confirmed hospital-discharged leptospirosis cases from 2000–2020 from a publicly accesible National Database, including males and females of all ages. We computed data for the 24 provinces across the four-geoclimatic regions of Ecuador based on seasonal and monthly variations and calculated rates according to age and sex. The spatial distribution was estimated at the level of ecoregions, provinces, and cantons. A total of 2,584 hospitalizations were recorded over all three continental regions in 22 provinces, except Carchi province and the Galapagos Islands. The annual incidence varied from 0.27 to 2.45 cases per 100,000 inhabitants with ages ranging from 1 to 98 years-old and an overall male/female ratio of 1.92:1. Most hospitalizations and deaths occurred in males ages 25–34 years. We registered 79 fatalities (3.06%); the highest mortality rate was 0.05 per 100,000 inhabitants. More cases clustered in the tropical cantons of central and north of the Coast and in the southern Amazon when compared to the Andes.Conclusions and significanceOur findings evidence leptospirosis endemicity and pinpoint the highest incidence within resource-poor tropical settings. The highest incidence occurred in males of adult age, with those also exhibiting the highest mortality. The national incidence rate was stable, but peaks occurred intermittently during the rainy seasons. Thus, strategies aimed at leptospirosis monitoring and control involving the application of preventive measures should consider this season and the aforementioned high-risk groups.     

Evolutionary perturbations of optimal life histories

Summary An optimal age-structured life history is perturbed by increasing the mortality factors specific to an agek. These can be density dependent (DD) or independent (DI), avoidable or unavoidable. The last two refer to whether their effect on any individual depends or not on how much energy it devotes to defence. Agespecific trade-offs between the allocation of energy to defence and fecundity exist: survival probabilities through each agex, P _x, are concave decreasing functions of the fecundity per unit size at that age,b _x. These are constraints for the optimal life history. The changes induced by perturbation are evaluated by equations that predict whether some extra energy is diverted towards survivorship at the expense of fecundity or vice versa. The model predicts that for DI environments the degree of avoidability of the mortality source perturbed, is a decisive factor for the strategy selected at agek, but not for any other age class. DD environments are more complex since all ages are simultaneously embedded in density effects. The perturbations not only act directly — as in the DI situation — but also indirectly through their effect on equilibrium density,N ^*. When any kind of mortality source becomes more intense at agek, N ^* always decreases and all ages react in consequence according to the effect of density on each age-specific trade-off. Either coincidental or opposing reactions can be expected from direct and indirect effects. The resultant strategy for any age would be a matter of magnitude comparisons. Some possible general patterns are discussed.     

The ghost of Christmas past: health effects of poverty in London in 1896 and 1991

ObjectivesTo compare the extent to which late 20th century patterns of mortality in London are predicted by contemporary patterns of poverty and by late 19th century patterns of poverty. To test the hypothesis that the pattern of mortality from causes known to be related to deprivation in early life can be better predicted by the distribution of poverty in the late 19th century than by that in the late 20th century.DesignData from Charles Booth''s survey of inner London in 1896 were digitised and matched to contemporary local government wards. Ward level indices of relative poverty were derived from Booth''s survey and the 1991 UK census of population. All deaths which took place within the surveyed area between 1991 and 1995 were identified and assigned to contemporary local government wards. Standardised mortality ratios for various causes of death were calculated for each ward for all ages, under age 65, and over age 65. Simple correlation and partial correlation analysis were used to estimate the contribution of the indices of poverty from 1896 and 1991 in predicting ward level mortality ratios in the early 1990s.SettingInner London.ResultsFor many causes of death in London, measures of deprivation made around 1896 and 1991 both contributed strongly to predicting the current spatial distribution. Contemporary mortality from diseases which are known to be related to deprivation in early life (stomach cancer, stroke, lung cancer) is predicted more strongly by the distribution of poverty in 1896 than that in 1991. In addition, all cause mortality among people aged over 65 was slightly more strongly related to the geography of poverty in the late 19th century than to its contemporary distribution.ConclusionsContemporary patterns of some diseases have their roots in the past. The fundamental relation between spatial patterns of social deprivation and spatial patterns of mortality is so robust that a century of change in inner London has failed to disrupt it.