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PubMedDate not supplied

The problem of choosing model life tables for African countries.

"This study seeks to investigate contemporary practice among mortality analysts whereby the South Model life table in the Coale Demeny system is used for analysing mortality data for countries in the North African subregion while the corresponding North Model is used for Sub-Saharan African countries. The two analytical methods proposed...are discussed and empirically tested with pertinent data from Algeria and Egypt (North Africa) and Liberia, Togo, Reunion and Mauritius (Sub-Saharan Africa)." The above practice is not completely validated. "It is therefore suggested that rather than use a predetermined model life table for analysing mortality data in African countries, the methods used in the study should first be applied to determine the model type that best fits the specific country data situation." (summary in FRE, ITA)

Africa↗
PubMed1978

A fetal-infant life table based on single births in Norway, 1967--1973.

The study is based on 440,452 single births occurring in Norway, 1967--1973, with known gestational age. The information was collected through a notification system known as "Medical Registration of Births," covering all births occurring in Norway, and the data are made available through the Medical Birth Registry of Norway, which allows for linkage between births and infant deaths. The life table describes the experience of women still pregnant at a gestational age of 16 completed weeks, and states for each subsequent week the number of pregnancy terminations, the outcome, and the number of women still pregnant. Seven outcomes of pregnancy are considered: fetal death prior to labor, fetal death during labor, death within 24 hours, death 1--6 days, death 7--27 days, death 28 days--1 year, and survival of one year or more. The data in the life table provide information on the probability of pregnancy termination in each week of gestation (after 16 completed weeks), and the probabilities of the various outcomes. The fetal-infant life table is considered as an extension of descriptive perinatal statistics and is of value in monitoring health changes and in comparing perinatal mortality between populations. It also provides information on time of pregnancy termination and outcome, which has some clinical applications.

Adult↗
PubMedDate not supplied

[Some problems in the use of the new U.N. model life tables].

"After a brief introduction to new United Nations model life tables for developing countries, we have proceeded to point out some blanks contained in them....[A theoretical] approach has allowed us to demonstrate the inadequacy of some fundamental assumptions on which the methods used are based. [An empirical approach] has enabled us to point out some of the problems that may be encountered when using the tables." (SUMMARY IN ENG AND ITA)

Demography↗
PubMed1988

A set of test life tables for theoretical gerontology.

Prediction of life tables, which provide the most empirical information available about the statistical properties of aging, provides a rigorous test for any theory of aging as manifested at the organismic level of biological organization. For this purpose, a set of test tables for the wild boar (Sus scrofa), domestic sheep (Ovis aries), Dall sheep (Ovis dalli dalli), African buffalo (Syncerus cafer), and hippopotamus (Hippopotamus amphibius) is reconstructed from primary data taken from the literature. The tables, which exhibit a broad range of survival characteristics, satisfy the criteria that (1) the data are statistically sound, (2) their survival functions are concave, except for the limiting case of the convex wild boar function, and (3) the species are natural populations (i.e., are in the same environment in which they evolved). Each test table is reported numerically and as a least-squares regression formula for the age-specific mortality rate over a given range of age.

Actuarial Analysis↗
PubMed1986

A modified actuarial life-table approach to the analysis of implantable device performance.

The actuarial life-table method is often used by pacemaker manufacturers and the pacing research community to describe pacemaker and lead performance. Most life-table methods allow for differing lengths of follow-up but assume that all devices were followed from implant. Occasionally, however, devices come under follow-up observation sometime after implant. This presentation describes an extension of the actuarial method to accommodate these kinds of data. The specific example to be considered involves follow-up data collected by CardioCare, a commercial cardiac monitoring service, on the performance of Medtronic polyurethane leads. Patients subscribe to this service, generally at some time after actual device implant. Results showed that of 12,112 patients with Models 4002, 6971, and 6972 leads who were followed by CardioCare, only 85 were followed from implant. If one were to exclude patients not followed since implant, more than 99% of the data would be lost. Using the modified approach with allowance for postimplant, entry resulted in an estimated three-year cumulative survival probability for these leads of 95.7%. Treating all patients as if they were followed since implant, the probability would be 96.9%, an optimistic and biased estimate.

Actuarial Analysis↗
PubMed2006

A comparison of models for dynamic life tables. Application to mortality data from the Valencia Region (Spain).

The graduation of mortality data aims to estimate the probabilities of death at age x, q ( x ), by means of an age-dependent function, whose parameters are adjusted from the crude probabilities that are directly obtainable from the data. However, current life tables have a problem, the need for periodic updates due to changes in mortality over short periods of time. The table containing mortality rates for different ages in different years, q ( xt ), is called a dynamic life table, which captures mortality variation over time. This paper proposes a review of the most commonly used dynamic models and compares the results obtained by each of them when applied to mortality data from the Valencia Region (Spain). The result of the comparison leads us to the conclusion that the Lee-Carter method offers the best results for both sexes, while that based on Heligman and Pollard functions provides the best fit for men alone. Our working method is of additional interest as it may be applied to mortality data for a wide range of ages in any geographical location, allowing the most appropriate dynamic life table to be selected for the case at hand.

Humans↗
PubMed1989

Assessing hospital nursing staff retention and turnover. A life table approach.

This research applied the life table technique to nursing personnel data in two types of hospitals to illustrate how administrators can examine patterns of continued employment. Although a large proportion of nurses were short-stay employees, the teaching hospital was found to have a higher retention rate than the community hospital corporation. The retention patterns are examined by personal and professional characteristics, as well as by reason for termination. Implications of our findings are discussed with respect to policy concerns related to hiring, retention, productivity, and staff development.

Actuarial Analysis↗
PubMed1992

Recent trends in mortality in Australia--an analysis of the causes of death through the application of life table techniques.

"The paper examines the post-1971 reduction in Australian mortality in light of data on causes of death. Multiple-decrement life tables for eleven leading causes of death by sex are calculated and the incidence of each cause of death is presented in terms of the values of the life table functions. The study found that in the overall decline in mortality over the last 20 years significant changes occurred in the contribution of the various causes to total mortality.... The sex-age-cause-specific incidence of mortality changed and the median age at death increased for all causes except for deaths due to motor-vehicle accidents for both sexes and suicide for males. The paper also deciphers the gains in the expectation of life at birth over various time periods and the sex-differentials in the expectation of life at birth at a point in time in terms of the contributions made by the various sex-age-cause-specific mortality rates."

Age Factors↗
PubMed2004

Demographic window to aging in the wild: constructing life tables and estimating survival functions from marked individuals of unknown age.

Summary We address the problem of establishing a survival schedule for wild populations. A demographic key identity is established, leading to a method whereby age-specific survival and mortality can be deduced from a marked cohort life table established for individuals that are randomly sampled at unknown age and marked, with subsequent recording of time-to-death. This identity permits the construction of life tables from data where the birth date of subjects is unknown. An analogous key identity is established for the continuous case in which the survival schedule of the wild population is related to the density of the survival distribution in the marked cohort. These identities are explored for both life tables and continuous lifetime data. For the continuous case, they are implemented with statistical methods using non-parametric density estimation methods to obtain flexible estimates for the unknown survival distribution of the wild population. The analytical model provided here serves as a starting point to develop more complex models for residual demography, i.e. models for estimating survival of wild populations in which age-at-entry is unknown and using remaining information in randomly encountered individuals. This is a first step towards a broad new concept of 'expressed demographic information content of marked or captured individuals'.

Age Factors↗
PubMed2001

Modelling physical activity: a multi-state life-table approach.

OBJECTIVE: To develop a consistent set of epidemiological estimates (incidence, prevalence, remission, mortality) for physical activity in New Zealand; project these estimates in the light of demographic trends; and predict the effectiveness of different health promotion strategies. METHOD: Multi-state life tables were constructed using physical inactivity prevalence data from the 1996/97 New Zealand Health Survey, and estimates of the relative risk of mortality, and of remission rates, from the literature. Statistics New Zealand population projections were used to forecast these multi-state life tables to 2021. Two physical activity health promotion strategies -uptake (remission enhancement) and maintenance (incidence or relapse reduction)--were simulated by changing the relevant epidemiological variables. RESULTS: The current fatal burden of physical inactivity in New Zealand is estimated to be 2,600 deaths per year (9% of all deaths). By 2021, the prevalence of physical inactivity will rise 4% as a result of demographic trends. Relapse reduction (enabling active people to remain active) is about 50% more effective than uptake enhancement (enabling inactive people to become active) as a physical activity health promotion strategy, but the two approaches are additive. Maximum realistic changes in relapse prevention and uptake enhancement could reduce the prevalence of physical inactivity by about 30%. CONCLUSIONS AND IMPLICATIONS: Multi-state life table methods can be used to model health risks (such as behaviours), as well as (chronic) diseases. The model has provided valuable insights for policy makers into the burden of physical inactivity in New Zealand, the impact of demographic trends, and the relative effectiveness of different health promotion strategies.

Adolescent↗
PubMed1994

[Analysis of therapeutic prognosis of primary open-angle glaucoma by the proportional hazards model and the life-table method].

We retrospectively analyzed the therapeutic prognosis of primary open-angle glaucoma by the life-table method and the proportional hazards model. One hundred and eight patients (202 eyes) were studied. The follow-up period ranged from 6 to 125 months (40 +/- 25 months: mean +/- SD). The Kaplan-Meier life-table method indicated that therapeutic prognosis was significantly related to pretreatment intraocular pressure (IOP) and visual field defect, and that more intensive treatment was needed for higher IOP and more deteriorated visual field defect. Analysis by the proportional hazards model showed that pretreatment IOP and mean deviation (MD) measured by static perimetry were significant prognostic factors for non-surgical treatment and that the hazard ratios were 1.29-1.31 for a 5 mmHg rise in IOP and 1.44-1.83 for a 10 dB fall in MD. We concluded that the therapeutic prognosis of primary open-angle glaucoma is highly related to the level of IOP and the severity of visual field defect at the time of diagnosis.

Adult↗
PubMed1980

Life-table analysis of abstinence in a study evaluating the efficacy of disulfiram.

Data from a study evaluating the efficacy of disulfiram for the treatment of alcoholism were analyzed by life-table methods. Previous analysis by more commonly used statistical tests showed a trend favoring disulfiram treatment, but the results were not statistically significant. Life-table methods are the appropriate techniques for analyzing longitudinal studies because they evaluate response to treatment over time rather than at one point in time. Analysis of our data using these methods revealed that disulfiram, combined with medical care and counseling, was superior to medical care and counseling alone in 128 men followed for 1 yr. This report demonstrates: (A) the advantage of life-table methods for evaluating treatment outcome data in alcoholism studies; and (B) the importance of disulfiram treatment in alcoholic patients similar to those we studied.

Actuarial Analysis↗
PubMed2004

Life table study of Sitotroga cerealella (Lepidoptera: Gelichiidae), a strain from West Africa.

Life table studies for the Angoumois grain moth, Sitotroga cerealella (Olivier), a pest on stored maize, Zea mays L., in West Africa, were conducted as part of the expansion of a mathematical simulation model that has been developed for two pests of stored maize. The effects of four temperatures (20, 25, 30, and 35 degrees C) and two relative humidity levels (44 and 80%) on developmental time, age-specific survivorship and fecundity, sex ratio, and intrinsic rate of natural increase (r(m)) of S. cerealella were investigated. Sex ratio was close to 1:1 at all temperatures and humidity. Minimum development time occurred close to 32 degrees C and 80% RH for both males and females, and developmental time of females was significantly shorter than that of males. Immature survivorship was highest between 25 and 30 degrees C and 80% RH and lowest at 35 degrees C under both humidity conditions. A similar low level was found at 20 degrees C and 44% RH. The greatest fecundity (124 eggs per female) occurred at 20 degrees C, 80% RH. The maximum r(m) value was 0.086 d(-1) at 30 degrees C and 80% RH, but the growth rate declined dramatically at 35 degrees C. If compared with the few other life table studies conducted on this species on maize in India and North America, some variation among the strains becomes evident. A common conclusion for the current study and previous ones is that optimal population development for S. cerealella occurs at approximately 30 degrees C and at high humidity.

Africa, Western↗
PubMed1998

Preventing fatal diseases increases healthcare costs: cause elimination life table approach.

OBJECTIVES: To examine whether elimination of fatal diseases will increase healthcare costs. DESIGN: Mortality data from vital statistics combined with healthcare spending in a cause elimination life table. Costs were allocated to specific diseases through the various healthcare registers. SETTING AND SUBJECTS: The population of the Netherlands, 1988. MAIN OUTCOME MEASURES: Healthcare costs of a synthetic life table cohort, expressed as life time expected costs. RESULTS: The life time expected healthcare costs for 1988 in the Netherlands were 56,600 Pounds for men and 80,900 Pounds for women. Elimination of fatal diseases--such as coronary heart disease, cancer, or chronic obstructive lung disease--increases healthcare costs. Major savings will be achieved only by elimination of non-fatal disease--such as musculoskeletal diseases and mental disorders. CONCLUSION: The aim of prevention is to spare people from avoidable misery and death not to save money on the healthcare system. In countries with low mortality, elimination of fatal diseases by successful prevention increases healthcare spending because of the medical expenses during added life years.

Accidents↗
PubMed1983

A modified life-table analysis system for cohort studies.

A person-years at risk life-table analysis system of computer programs has been developed by the National Institute for Occupational Safety and Health (NIOSH) and is available with detailed documentation. The system was specifically designed to analyze occupational cohort mortality data. These programs require more computer core space and processing time than other available life-table programs. However, the NIOSH programs are advantageous because they include the following: (1) input data editing and modification, (2) mortality rates for 89 cause-of-death categories, (3) assignment of cumulative doses to specific person-years based on either personal or area exposure data, and (4) simultaneous examination of observed and expected deaths by duration of employment (or dose), latency, age, and calendar time.

Actuarial Analysis↗
PubMedDate not supplied

An alternative procedure for fitting relational model life tables.

"The paper considers the problem of fitting a relational model life table to mortality data which does not include reliable estimates of infant and child mortality. This type of data could arise from indirect estimation of adult mortality using orphanhood or widowhood, or from adjustment of incomplete registration data using growth balance methods in a population recently de-stabilized by falls in fertility. The proposed fitting technique can give equal weight to all the age specific mortality risk information available, rather than giving more weight to the information for younger ages, as is the case with the traditional method. An application to Brazilian data is presented." (SUMMARY IN ITA AND FRE)

Americas↗
PubMed1982

Approximate confidence intervals for probabilities of survival and quantiles in life-table analysis.

For survival probabilities with censored data, Rothman (1978, Journal of Chronic Diseases 31, 557-560) has recommended the use of quadratic confidence limits based on the assumption that the product of the 'effective' sample size at time t and the life-table estimate of the survival probability past time t follows a binomial distribution. This paper shows that the proposed confidence limits are asymptotically correct for continuous survival data. These intervals, as well as those based on the arcsine transformation, the logit transformation and the log(--log) transformation, are compared by simulation to those based on Greenwood's formula--the usual method of interval estimation in life-table analysis. With large amounts of data, the alternatives to the Greenwood method all produce acceptable intervals. On the basis of overall performance, the intervals suggested by Rothman are preferred for smaller samples. Any of these methods may be used to generate confidence sets for the median survival time or for any other quantile.

Actuarial Analysis↗
PubMed1987

Comparison of risk estimates using life-table methods.

Risk estimates promulgated by various radiation protection authorities in recent years have become increasingly more complex. Early "integral" estimates in the form of health effects per 0.01 person-Gy (per person-rad) or per 10(4) person-Gy (per 10(6) person-rad) have tended to be replaced by "differential" estimates which are age- and sex-dependent and specify both minimum induction (latency) and duration of risk expression (plateau) periods. These latter types of risk estimate must be used in conjunction with a life table in order to reduce them to integral form. In this paper, the life table has been used to effect a comparison of the organ and tissue risk estimates derived in several recent reports. In addition, a brief review of life-table methodology is presented and some features of the models used in deriving differential coefficients are discussed. While the great number of permutations possible with dose-response models, detailed risk estimates and proposed projection models precludes any unique result, the reduced integral coefficients are required to conform to the linear, absolute-risk model recommended for use with the integral risk estimates reviewed.

Actuarial Analysis↗