Biodemographic trajectories of longevity.

Old-age survival has increased substantially since 1950. Death rates decelerate with age for insects, worms, and yeast, as well as humans. This evidence of extended postreproductive survival is puzzling. Three biodemographic insights--concerning the correlation of death rates across age, individual differences in survival chances, and induced alterations in age patterns of fertility and mortality--offer clues and suggest research on the failure of complicated systems, on new demographic equations for evolutionary theory, and on fertility-longevity interactions. Nongenetic changes account for increases in human life-spans to date. Explication of these causes and the genetic license for extended survival, as well as discovery of genes and other survival attributes affecting longevity, will lead to even longer lives.

[Investigation of disability prevalence in men and women of advanced age].

Disability prevalence among men and women are investigated using NLTCS surveys conducted in 1982, 1984, 1989, 1994 and 1999 in the US population, on persons older than 65 years, and data from LSADT surveys conducted in 1995, 1997, 1999 and 2001 in the population of the Danish Twins Registry, on persons older than 75 years. In both surveys women are more disabled than men. The probability of becoming disabled and surviving is higher for women than men. The probability of recovering from a disability differs between the sexes statistically insignificant. No time trends are observed in the probabilities of becoming disabled, reversing disability or dying disabled. Calculations show that a decrease in disability prevalence observed in the USA resulted from a decrease in disability prevalence in ages younger than 65 years. Using LSADT data heritability of disability in women older than 75 years is estimated to be 36% (14%; 54%). In men of the same ages the estimate is 11% (0%; 40%) and for both sexes heritability is estimated at 28% (10%; 45%).

A two-disease model of female breast cancer: mortality in 1969 among white females in the United States.

A mathematical model of the age distribution of breast cancer mortality was developed on the basis of the two-disease theory of breast cancer incidence. The model included representations of the time from tumor initiation to death, the competing risk effects of other disease, and differential susceptibility to each of the disease components. This model successfully predicted the single year of age frequency of breast canceomponents of this model was consistent with several epidemiologic findings. Most significantly, the age distribution of breast cancer deaths from premenopausal disease was consistent with incidence patterns in non-Western countries, where the incidence of the postmenopausal disease component was hypothesized to be lower because of nutritional differences.

Comparison of temporal changes in U.S. and Swedish lung cancer, 1950-51 to 1981-82.

A comparison was made of temporal changes in lung cancer risk for the U.S. white and Swedish populations from 1950-51 to 1981-82 with the use of both life-table- and cohort-specific proportional hazard models to illustrate different features of the time series. Marked differences were noted for the two populations; Swedish lung cancer risks were generally lower than those in the United States. Sex-specific analyses were conducted that showed that Swedish males had a mortality rate roughly half that for U.S. males over the entire period. In contrast, U.S. white female mortality rates, though roughly equal to those for Swedish females in 1950-51, experienced a relatively more rapid increase; their rates were double the Swedish rates by 1980. The factors contributing to these patterns, such as marked cohort differences in risk, are identified by the various stages of analysis.

Statistically adjusted estimates of geographic mortality profiles.

The spatial variation of site-specific cancer mortality rates at the county or state economic area level can provide a) insights into possible etiologic factors and b) the basis for more detailed epidemiologic studies. One difficulty with such studies, especially for rare cancer types, is that unstable local area rate estimates, resulting from small population sizes, can obscure the underlying spatial pattern of disease risk. This paper presents a methodology for producing more stable rate estimates by statistically weighting the local area rate estimate toward the experience at the national level. The methodology is illustrated by the analysis of the spatial variation of two cancer types, bladder and lung, for U.S. white males over the three decades 1950-79.

The risk of radiation-induced cerebrovascular disease in Chernobyl emergency workers.

The paper deals with estimating radiation risks of non-cancer diseases of the circulatory system among the Chernobyl emergency workers based on data from the Russian National Medical and Dosimetric Registry. The results for the cohort of 61,017 people observed between 1986 and 2000 are discussed. These are essentially updated results for the similar cohort that was studied by authors earlier in 1986-1996. Newly discovered is the statistically significant dose risk of ischemic heart disease [ERR Gy = 0.41, 95% CI = (0.05; 0.78)]. Confirmation is provided for the existence of significant dose risks for essential hypertension [ERR Gy = 0.36, 95% CI = (0.005; 0.71)] and cerebrovascular diseases [ERR Gy = 0.45, 95% CI = (0.11; 0.80)]. In 1996-2000, the assessed ERR Gy for cerebrovascular diseases was 0.22 with 95% CI = (-0.15; 0.58). Special consideration is given to cerebrovascular diseases in the cohort of 29,003 emergency workers who arrived in the Chernobyl zone during the first year after the accident. The statistically significant heterogeneity of the dose risk of cerebrovascular diseases is shown as a function of the duration of stay in the Chernobyl zone: ERR Gy = 0.89 for durations of less than 6 wk, and ERR Gy = 0.39 on average. The at-risk group with respect to cerebrovascular diseases are those who received external radiation doses greater than 150 mGy in less than 6 wk [RR = 1.18, 95% CI = (1.00; 1.40)]. For doses above 150 mGy, the statistically significant risk of cerebrovascular diseases as a function of averaged dose rate (mean daily dose) was observed: ERR per 100 mGy d = 2.17 with 95% CI = (0.64; 3.69). The duration of stay within the Chernobyl zone itself, regardless of the dose factor, had little influence on cerebrovascular disease morbidity: ERR wk = -0.002, with 95% CI = (-0.004; -0.001). The radiation risks in this large-scale cohort study were not adjusted for recognized risk factors such as excessive weight, hypercholesterolemia, smoking, alcohol consumption, and others.

Modeling the effects of biologically incorporated radionuclides and chronic low-dose ionizing radiation exposure on both cancer and chronic non-cancer diseases.

Efforts to model the health effects of low-dose ionizing radiation (IR) have often focused on cancer. Meanwhile, significant evidence links IR and age-associated non-cancer diseases. Modeling of such complex processes, which are not currently well understood, is a challenging problem. In this paper we briefly overview recent successful attempts to model cancer on a population level and propose how those models may be adapted to include the impact of IR and to describe complex non-cancer diseases. We propose three classes of models which we believe are well suited for the analysis of the health effects in human populations exposed to low-dose IR. These models use biostatistical/epidemiological techniques and mathematical formulas describing the biological mechanisms of the impact of IR on human health. They can combine data from multiple sources and from distinct levels of biological/population organization. The proposed models are intrinsically multivariate and non-linear and capture the dynamic aspects of health change.

Population models for the health effects of ionizing radiation.

In this paper we review recently-developed extension frailty, quadratic hazard, stochastic process, microsimulation, and linear latent structure models, which have the potential to describe the health effects of human populations exposed to ionizing radiation. We discuss the most common situations for which such models are appropriate. We also provide examples of how to estimate the parameters of these models from datasets of various designs. Carcinogenesis models are reviewed in context of application to epidemiologic data of population exposed to ionizing radiation. We also discuss the ways of how to generalize stochastic process and correlated frailty models for longitudinal and family analyses in radiation epidemiology.

Depressive symptoms and depressive diagnoses in a community population. Use of a new procedure for analysis of psychiatric classification.

A multivariate classification technique was used to examine whether depressive symptoms and symptoms frequently associated with depressive disorders would cluster into recognizable syndromes that parallel traditional DSM-III psychiatric diagnoses. An analysis was made of all respondents in the Epidemiologic Catchment Area (ECA) project of the Piedmont region of North Carolina who reported suffering from depressive symptoms (n = 406) at the second wave of the ECA study. The analysis identified five profiles of symptoms that adequately described the interrelationships of the symptoms as reported in the population. One profile included a set of symptoms nearly identical to the symptoms associated with the DSM-III classification of major depression. Other depressive syndromes emerged and included a premenstrual syndrome among younger women and a mixed anxiety/depression syndrome. The existence of these other depressive syndromes may explain the present discrepancy in the epidemiologic literature between a high prevalence of depressive symptoms and a low prevalence of traditional depressive diagnoses in community populations.

Psychiatric disorders. A rural/urban comparison.

We studied rural/urban differences in the prevalence of nine psychiatric disorders from a community survey (part of the Epidemiologic Catchment Area Program) of 3,921 adults living in the Piedmont of North Carolina. Crude comparisons disclosed that major depressive episodes and drug abuse and/or dependence were more common in the urban area, whereas alcohol abuse/dependence was more common in the rural area. When prevalence for these disorders was stratified for age, sex, race, and education (factors that may confound urban/rural comparisons), a number of significant differences were identified, such as higher prevalence of major depression in female and white subjects and higher prevalence of alcohol abuse/dependence in the less educated subjects. A logistic-regression analysis was used to determine if significant urban/rural differences persisted when these potential confounders were controlled. Major depressive disorders were found to be twice as frequent in the urban area in this controlled analysis.

Apolipoprotein E genotype determines survival in the oldest old (85 years or older) who have good cognition.

OBJECTIVE: To quantify the influence of apolipoprotein E (APOE) polymorphism on cognition and survival in a population sample aged 75 years or older. DESIGN: The Kungsholmen Project established a cohort of 1810 residents in a district in Stockholm, Sweden, aged 75 years or older in 1987. Information on cognition at cohort inception is available for all subjects. Subjects were followed up for mortality to January 1, 1995. SUBJECTS: Included in this study are 1077 subjects (of 1124 genotyped for APOE) with the common epsilon 2/3, epsilon 3/3, and epsilon 3/4 APOE genotypes. RESULTS: The odds of cognitive impairment for the epsilon 3/4 vs epsilon 3/3 genotype declined with age: 4.8 for age 75 through 79 years; 1.7 for age 80 through 84 years; and 1.0 (i.e., no association) for age 85 years or older. Despite this association, APOE polymorphism did not significantly predict survival in subjects younger than 85 years, nor did it predict survival in subjects 85 years or older who were cognitively impaired. Instead, survival varied fourfold with respect to APOE polymorphism in those 85 years or older who had good cognition: Mortality in subjects with the epsilon 2/3 genotype was half that in those who carried the epsilon 3/3 genotype (hazard ratio, 0.5; 95% confidence interval, 0.2 to 0.9), and mortality in subjects with the epsilon 3/4 genotype was twice that in those who carried the epsilon 3/3 genotype (hazard ratio, 2.0; 95% confidence interval, 1.1 to 3.5). This fourfold variation resulted in 2-year differences in survival. CONCLUSIONS: The minor sequence variation in the apolipoprotein E isoforms resulted in a fourfold difference in the risk of death among the oldest old (age > or = 85 years) with good cognition. The observed variation in mortality was unlikely to have been caused by cognitive impairment, as APOE polymorphism was not a risk factor for cognitive impairment in this age group.

Demographic analysis and modeling of human populations exposed to ionizing radiation.

The health effects of ionizing radiation on human populations are often analyzed using epidemiological statistical methods. Because of the complexity of the health consequences of ionizing radiation and the prolonged period during which the consequences emerge, we propose to evaluate these health effects using mathematical models that are based on the best theoretical reasoning and prior biological evidence about disease mechanisms. We believe this will improve the ability of the model to identify health effects and reduce erroneous inferences.

U.S. cancer mortality 1950-1978: a strategy for analyzing spatial and temporal patterns.

There are a number of technical and statistical problems in monitoring the temporal and spatial variation of local area death rates in the United States for evidence of systematically elevated risks. An analytic strategy is proposed to reduce one of the major statistical concerns, i.e., that of identifying areas with truly elevated mortality risks from a large number of local area comparisons. This analytic strategy involves two stages. The first is a procedure for examining the entire distribution of local area death rates instead of simply selecting high risk "outliers." The second is the development of an analytic procedure to relate the temporal changes in the cross-sectional distribution of local area death rates to models of the disease process operating within the populations in those areas. The procedures are applied to data on cancer mortality for the 3050 counties (or county equivalents) of the United States over the period 1950 to 1978. A number of striking mortality patterns, both within the entire United States and within various regions and states, are identified. For example, perhaps the most persistent finding was that the risk increases in the death rates for respiratory cancer mortality were due to a "catching up" of nonmetropolitan county mortality rates with metropolitan area mortality rates.

Assessment of spatial variation of risks in small populations.

Often environmental hazards are assessed by examining the spatial variation of disease-specific mortality or morbidity rates. These rates, when estimated for small local populations, can have a high degree of random variation or uncertainty associated with them. If those rate estimates are used to prioritize environmental clean-up actions or to allocate resources, then those decisions may be influenced by this high degree of uncertainty. Unfortunately, the effect of this uncertainty is not to add "random noise" into the decision-making process, but to systematically bias action toward the smallest populations where uncertainty is greatest and where extreme high and low rate deviations are most likely to be manifest by chance. We present a statistical procedure for adjusting rate estimates for differences in variability due to differentials in local area population sizes. Such adjustments produce rate estimates for areas that have better properties than the unadjusted rates for use in making statistically based decisions about the entire set of areas. Examples are provided for county variation in bladder, stomach, and lung cancer mortality rates for U.S. white males for the period 1970 to 1979.

Proxy response patterns among the aged: effects on estimates of health status and medical care utilization from the 1982-1984 long-term care surveys.

We examined the use of proxies in samples of persons aged 65 years and over from the 1982 and 1984 National Long-Term Care Surveys (NLTCS). The NLTCS are designed to describe the Medicare-enrolled elderly population, their health and functioning, hospital, home health, and institutional use. The NLTCS, being longitudinal, allows trends in functional and health status to be examined as well as the changing character of community-based and institutional services used by chronically disabled persons aged 65 years and older. In analyses of proxy responses there was little evidence of differences in accuracy between self- and proxy reports in persons with different health and functional characteristics. The amount and type of proxy reporting did depend on the health and functional characteristics of the sample person. The cognitively impaired, and the frail elderly, had high levels of proxy use as well as small differences in the accuracy of reporting service use and program enrollment. The results are consistent with methodological studies of proxy reporting in health surveys of other populations.

Racial differences in acute lymphocytic leukemia mortality and incidence trends.

Mortality and morbidity rates for childhood leukemia are examined with reference to time trends and racial differences. Prior to 1964, white and nonwhite children had very different acute lymphocytic leukemia (ALL) mortality rates. With the advent of successful chemotherapy, the mortality rate of ALL in white children has decreased resulting in virtually no racial differences in ALL mortality. The reasons for a stable ALL mortality rate in nonwhite children despite successful chemotherapy include poor access to health care, undefined socioeconomic factors and a biologically different type of ALL occurring in nonwhite children. Recent data from two cancer surveys (1969-1971, 1973-1976) reveal that nonwhite children have a lower incidence of ALL than white children. Underreporting in the nonwhite children could partly account for the difference, but other contributing factors might include a genetic predisposition, undefined socioeconomic influences, and perhaps, a viral agent. Further studies of the factors contributing to racial differences in ALL incidence and mortality are needed.

The structure of urban mortality. A methodological study of Hannover, Germany. Part I.

An analysis is made of the association between density factors and the profile of cause specific death rates in small areas (Bezirke) of Hannover, Germany, in 1968-69. Evaluation of urban ecological methods and logic is done to determine the plausibility of making meaningful statements about cause specific death risks due to areal attributes. Efforts are made to develop an appropriate multiple indicator structural equation model to determine if underlying patterns of mortality can be discerned. Evidence is found that measures of crowding, apart from classical density, predict a general mortality component.

The structure of urban mortality. A methodological study of Hannover, Germany. Part II.

An extension is made of a prior analysis of the relation of density to cause-specific mortality in small areas of Hannover, Germany. The analysis was designed to impose statistical controls for certain socio-demographic characteristics of these small areas under a model where all of the effects of density were assumed to operate on mortality only indrectly by affecting the residential decisions of select socio-demographic groups. It was found that, despite the sizeable effects of socio-demographic factors on cause-specific mortality, density retained a direct effect on five of 14 cause-specific rates. Implications of these results for modelling density-mortality relations are discussed.

A cohort analysis of U.S. stomach cancer mortality 1950-1977.

Models of human carcinogenesis, such as the multi-stage model of Armitage and Doll, are designed to explain the age increase in the incidence of cancers in individuals. As a consequence, analyses of population level age-specific death rates via such models are appropriately applied to cohort data where such data are available. In this study a multi-stage model is applied to cohort data for stomach cancer death rates in the U.S. population for nine distinct cohorts observed over a recent 28-year period (1950-1977). The multi-stage model parameters obtained from the analysis of the cohort data show significant differences from the parameters obtained from analyses of cross-sectional mortality data under the assumption of no cohort differences in age-specific stomach cancer death rates.

Forecasting chronic disease risks in developing countries.

Declining fertility and infant mortality has caused the population in many developing countries to age. Population ageing can produce a rapid shift in the predominant public health problems from infant mortality and infectious diseases to chronic disease mortality at later ages. Designing public health strategies to deal with the health consequences of population ageing in developing countries is difficult both because of a remaining burden of infectious diseases and because of changes in life style associated with economic development that may raise chronic disease risks. Because there are few longitudinal studies of chronic disease risks in developing countries, we investigate the use of a planning and forecasting model, which combines data from multiple sources, in six developing countries.