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K G Manton

Publications and source records attributed to K G Manton.

At least 163 records · Page 9Linked to original sources
PubMed1980

Estimates of U.S. multiple cause life tables.

Cause elimination life tables estimated from multiple cause of death data for four race/sex groups are presented for the U.S. population in 1969. These "multiple cause" life tables are then compared to cause elimination life tables where the mortality risk eliminated is that of the cause of death only in its occurrence as the underlying cause of death. An evaluation is made of the possible effects of the multiple cause data on our perception of the relative importance of the major causes of death. The reconceptualization of mortality risks made possible by the multiple cause of death data is also assessed in terms of its providing further insight into the "Taeuber paradox."

Adolescent↗
PubMed1980

Mortality of the chronically impaired.

An analysis of the effects of diabetes and generalized atherosclerosis on death due to ischemic heart disease or stroke was conducted using multiple cause mortality statistics. Specifically, all U.S. deaths in 1969 were classified into two groups on the basis of whether diabetes or generalized atherosclerosis was mentioned anywhere on the death certificate. Then race and sex specific analyses were made of ischemic heart disease deaths (or alternately of stroke deaths) using modified life table techniques for each group (one with the specified chronic disease and one without). Comparisons were made of mortality due to the acute circulatory events (ischemic heart disease or stroke) in the two groups to determine the implications of the chronic disease for the progression of the circulatory disease events. It was found, according to expectations, that diabetes and generalized atherosclerosis play very different roles in deaths due to stroke and ischemic heart disease.

Actuarial Analysis↗
PubMed1979

A stochastic compartment model of stomach cancer with correlated waiting time distributions.

The incidence and growth rate of stomach cancer in the US population is modelled, for each sex, as a partially observed, discrete state stochastic process. Explicit evaluation of the transition rates between the states of the model is made possible by identifying them as specific functions of the time spent within each state. The functions used in the model were selected from the medical and epidemiological literature. With the model it was found possible to obtain fits to the age distribution of deaths due to stomach cancer for white males in 1975 and for selected age ranges for white females. These results suggested that the natural history of stomach cancer is different for females above and below age 65.

Adult↗
PubMed1979

Effects of dependency among causes of death for cause elimination life table strategies.

A study is made of the effects of associated causes of death, and of dependency among causes of death, by observing the relative importance of one cause of death when another is eliminated under various competing risk models. Two disease pairs, cancer and infectious disease and stroke and ischemic heart disease, are selected for analysis because they represent different types of disease dependence. Crude probabilities of death for each disease are calculated for the U.S. white male population in 1969. Next, the effects of the complementary disease in a pair are hypothetically eliminated in one of three ways: (a) a standard competing risk adjustment for cause elimination when deaths are singly caused (Chiang, 1968), (b) lethal defect-pattern of failure computations for multiply caused death when no causal order is inferred (Manton et al., 1976), and (c) relative susceptibility, computations for multiply caused deaths when causes are ordered (Wong, 1977). The paper closes with a discussion of the relative merits of the three types of adjustments.

Actuarial Analysis↗
PubMed1979

Longitudinal analysis of the dynamics and risk of coronary heart disease in the Framingham Study.

Statistical methods designed specifically for the analysis of chronic disease incidence and progression in longitudinal studies are presented. These method model the risk of acute phases of chronic disease separately from the temporal change in risk variables. This could be accomplished because, under a specific biological model of the disease mechanism, the problems of estimating the risk of an acute event and of predicting the change in risk variables are independent. Specifically, a quadratic equation relating risk variable values to chronic disease risk and a system of linear equations predicting future risk variable values from present values may beestimated separately. Taken together, they utilize the full information available in a longitudinal study on the temporal dimension of chronic disease progression. In addition, the model is found to possess a number of attractive statistical and theoretical properties. These methods are applied to longitudinal data from the Framingham Study on coronary heart disease (CHD) in males. A quadratic function relating the risk of a CHD event to selected risk variables (age, and the natural logarithms of serum cholesterol, uric acid, diastolic blood pressure and pulse pressure) was estimated from measurements made at four points equally spaced in time (two years) with a further morbidity follow-up at a fifth point. The risk function was found to predict CHD risk accurately. It showed that, apart from the linear effects of the risk variables, cohort effects, quadratic effects and interaction effects were important predictors of CHD risk. The linear regression equations used to predict future risk variable values showed that there was an intricate network of cross-temporal associations. Study of the two types of equations jointly show that putative risk variables could affect the risk of CHD incidence both directly, by being associated with higher levels of risk, and indirectly, by causing other risk variable values to change with time. The results led us to identify several different roles that risk variables might play in CHD incidence.

Coronary Disease↗
PubMed1979

The impact of heterogeneity in individual frailty on the dynamics of mortality.

Life table methods are developed for populations whose members differ in their endowment for longevity. Unlike standard methods, which ignore such heterogeneity, these methods use different calculations to construct cohort, period, and individual life tables. The results imply that standard methods overestimate current life expectancy and potential gains in life expectancy from health and safety interventions, while underestimating rates of individual aging, past progress in reducing mortality, and mortality differentials between pairs of populations. Calculations based on Swedish mortality data suggest that these errors may be important, especially in old age.

Actuarial Analysis↗
PubMed1978

Compartment model approach to the estimation of tumor incidence and growth: investigation of a model of cancer latency.

Consideration is made of the problems involved in determining the effects of a chronic disease process, such as stomach cancer, on the observed mortality of the U.S. population. Specifically, since the time of initiation of tumor growth is unknown and the tumor becomes clinically manifest only after reaching considerable size, the early rate and pattern of tumor growth is unobserved. As a possible solution to the analysis of such problems, it is proposed to use stochastic compartment modelling techniques which deal with the problems of estimating the transition probabilities of a partially observed stochastic process. Implementation of the stochastic compartment techniques in this case depends on the selection of certain mathematical expressions from theories of carcinogenesis, epidemiologic studies and animal studies which allow the calculation of transition probabilities to unobserved states by making them explicit functions of time or age. Though the selection of the specific functions might be subject to debate, the general strategy of explicitly selecting such functions, and thereby exposing them for review in terms of biologic reasonableness and consistency with the data, seems to be a valid and useful methodology. Furthermore, various ways of viewing the model results (say from its internal behavior, e.g., from implied distributions of waiting times in various disease states) yield different insights into the various factors in carcinogenesis. The model, with parameters representing tumor incidence, time to tumor death given onset, genetic susceptibility to tumor growth and the effects of competing forces of mortality, is fitted to data on deaths due to stomach cancer for male U.S. residents age 25 and over in 1969. Two basic forms of the model, one with a waiting time distribution for occupants of the latent state and another with a single latency time, achieved excellent fits to the data. Examination of parameter estimates and compartment waiting time distributions are consistent with theoretical expectations and intuition. It is concluded that such strategies, involving the integration of clinical, experimental and vital statistics data into a comprehensive model of population carcinogenesis, are potentially powerful tools for investigation of the temporal dimensions of disease development in a human population.

Adult↗
PubMed1978

A linear models application of competing risks to multiple causes of death.

An analysis is performed to ascertain the joint incidence of two causes of death, acute myocardial infarct and stroke, for the deaths of residents of Massachusetts and North Carolina in 1969. To assay their association an explicit biological model of the nature of the relation is posited. It is shown that, under this model, Chiang's (1968) theory of competing risks may be extended to the case in which an individual's death may have multiple causes. Furthermore, techniques are developed which allow us to model the survival parameters derived under the model by categorical data procedures of the type introduced by Grizzle, Starmer and Koch (1969). The study shows that there is a greater incidence of the joint occurrence of stroke and myocardial infarct on death certificates in North Carolina than in Massachusetts, a pattern consistent with the generally higher stroke mortality in North Carolina. Furthermore, the incidence of the joint occurrence of the two diseases shows a clear age "gradient" increasing through the age range of the analysis. Males and females show somewhat different patterns of age variation in that state-by-age interaction terms are more prominent in the model fitted for females than for males.

Age Factors↗
PubMed1977

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.

Germany, West↗
PubMed1977

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.

Demography↗
PubMed1977

An extension of the sign test for replicated measurements.

An extension of the sign test is proposed for the case where there are paired groups or sets of replicated measurements; the individual measurements are unpaired between groups. A class of methods is investigated where the values of the groups of replicates are replaced by summary statistics (exceedances) whose distribution is independent, under the null hypothesis, of the underlying parametric structure. Possible adjustment for discontinuity of the underlying distribution (ties) is discussed and a normal approximation is presented. The proposed sign text extension, appropriate for small samples and large numbers of replicates, is used to compare the relative strengths of aqueous and lyophilized solutions of ragweed pollen at three dilutions for two types of reactions (erythematous and wheal area). Because correlations for individual reactions at two separate measurement times could not be estimated under the non-parametric procedures the analyses were performed for the cases where the responses at two measurement times were presumed to be (1) perfectly correlated, and (2) uncorrelated. Comparison of exact results with the normal approximation showed good correspondence for both cases, e.g., where n = 4 (n = number of subjects) and r = 8 (r = replicates) and n = 8 and r = 4. The analysis showed that the lyophilized product was superior to the aqueous at all solution strengths and for both measures of reactivity.

Freeze Drying↗
PubMed1976

Life table techniques for multiple-cause mortality.

A lethal defect-wear model of mortality is presented which rationalizes the assumption of independent risks when death may be due to more than a single condition. Under this model, it is shown how competing risk theory and standard categorical data methods may be merged in a unified approach to the analysis of multiple-cause mortality data. The methodology is used to analyze linkages among diseases in the mortality data and evaluate the implication of the elimination of patterns of morbid states for multiple-cause mortality data from deaths occurring in 1969 in North Carolina.

Aging↗
PubMedDate not supplied

Strategies for analysing ecological health data: models of the biological risk of individuals.

Frequently, the analysis of environmental health hazards using ecological data does not involve explicit recognition of the difficulties in translating health effects expressed in the aggregate to the health risks of individuals. We discuss these difficulties and suggest the need for the appropriate conceptualization of risk mechanisms at the individual level and of the population processes that determine the form in which these risk mechanisms are expressed in aggregate data. To illustrate the implications of these concepts we develop a biologically motivated model of lung cancer risk and apply it to both national and county data. In addition, to measure the total health effects of the long term elevation or depression of lung cancer incidence rates, we calculate prevalence distributions from the time series analysis of incidence patterns in county data.

Adult↗
PubMedDate not supplied

Models of the interaction of mortality and the evolution of risk factor distribution: a general stochastic process formulation.

Generally analyses of longitudinal studies of chronic disease risks do not directly model the change with time of risk factor values and the interactions of those changes with risk levels. Failure to account for such process characteristics can lead to incorrect inferences about the specific effects of risk factors on mortality, the inability to accurately forecast the future risk of the cohort, and inaccurate statements about the effects of specific risk factor interventions on mortality. We present a model which does describe such a process and show how it can be estimated from longitudinal studies. We also illustrate the effects of certain risk factor process features on the evolution of disease risk data from males in the Framingham, Massachusetts study.

Actuarial Analysis↗