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Robustness of life table methods in large populations--a study by computer simulation.

The robustness of the product life table estimator of the survival function was studied for large populations under perturbations in the age distribution, changing levels of mortality and changing patterns of fertility. A macrosimulation system, based on a class of stochastic population models called generalised age-dependent branching processes, was used to carry out the numerical investigations. Aside from drastic perturbations in the age distribution and changes in levels of mortality, the product life table estimator of the survival function was found to be robust in large populations, under a variety of conditions.

Age Factors↗

Life tables of Venturia canescens (Hymenoptera: Ichneumonidae) parasitizing the Mediterranean flour moth (Lepidoptera: Pyralidae).

Effects of temperature, adult feeding, and host instar on life table parameters of Venturia canescens Gravenhorst (Hymenoptera: Ichneumonidae) parasitizing larvae of Ephestia kuehniella Zeller (Lepidoptera: Pyralidae) were studied in the laboratory. Experimental adults lived under various regimes of temperature (15, 20, 25, and 30 degrees C), food supply (with or without access to honey), and host instar (second, third, fourth, and fifth). Temperature increase resulted in higher values of the intrinsic rate of natural increase (r(m)), the net reproductive rate (R(o)), the finite capacity of increase (lambda), and the gross reproductive rate (GRR), whereas it was followed by decrease of the mean generation time (G) and the doubling time (DT) values. Feeding on honey caused remarkable increase of r(m), R(o), and GRR, whereas r(m) and lambda reached their maximum when full-grown hosts (fifth instar) were parasitized. This is the first time life table parameters of V. canescens have been studied. The findings of the current study are discussed on the basis of improving V. canescens performance as a biological agent against moth pests of stored products.

Animals↗

Two regional (rural-urban) life tables for India.

"This paper proposes to construct, for India, a two-regional life table, considering two regions viz., rural and urban. Such a table provides information on the probabilities of survivorship and migration, as well as life expectancy by age, region and place of birth and in particular information on: (1) The probability that an individual living in a rural area at age x will be living in an urban area at age y. (2) Life expectancy at birth in a rural area, and the number of years on average this individual may live in an urban area. The aim here is to compare and contrast rural to urban and urban to rural migration probabilities by sex and age for the years 1971, 1981 and 1991, and provide the underlying reasons. Region-specific life expectancy is also compared for these years." (SUMMARY IN ITA AND FRE)

Age Factors↗

Effects of azadirachtin/Neemazal on different stages and adult life table parameters of Trichogramma cacoeciae (Hymenoptera: Trichogrammatidae).

The effects of azadirachtin/Neemazal on adults, emergence, and life table parameters of Trichogramma cacoeciae Marchal were studied. The adults were exposed to fresh residues of the insecticide applied on glass plates. Based on the dose-response study, the LC50 value was 1330 ppm or 13.3 microg (AI)/ml. The effect of Neemazal on three developmental stages of the parasitoid was tested by dipping parasitized Sitotroga cerealella (Olivier) and Cydia pomonella (L.) eggs at the field-recommended concentration 3, 6, and 9 d after parasitization corresponding to larval, prepupal, and pupal stages. The emergence of adult parasitoids was adversely affected in both hosts, but the adverse effect was more in S. cerealella eggs compared with C. pomonella. The adult emergence was reduced by 73.3 and 33.76% in Sitotroga and Cydia eggs compared with controls, respectively. Longevity and progeny production of the emergent adults did not differ significantly from control. Neemazal affected stable population parameters (r(m), T, and DT) significantly. The intrinsic rate of increase for the control and Neemazal-exposed populations was 0.340 and 0.335 female offspring per female per day, respectively. Because some of postemergence life table parameters of adults were significantly reduced by the insecticide treatment, emergence rate of the parasitoid from treated eggs is not an adequate measure of ecological selectivity, and field studies are needed to determine the actual impact of neem on T. cacoeciae.

Animals↗

Longevity minimalists: life table studies of two species of northern Michigan adult mayflies.

Life table studies were conducted on both sexes of newly emerged subimagoes of the mayfly species, Hexagenia limbata (n = 4472) and Ephemera simulans (n = 1254), which have two- and one-year life cycles, respectively. The expectation of life at emergence for H. limbata was approximately 2.6 days for both sexes with the last individual (a female) dying on day 8. Expectation of life for E. simulans was 1.6 and 2.0 days for males and females, respectively, with the last individuals (both sexes) dying on day 3. The results reveal that mortality does not occur in one large step in this group of rapidly senescing organisms. Rather deaths are spread over several days when the adult mayflies are maintained under laboratory conditions.

Animals↗

Recovery in major depressive disorder: analysis with the life table and regression models.

Regression models and life tables were used to describe the phenomenon of recovery from major depressive disorder for 101 patients in a naturalistic study in which treatment was not controlled by the investigators. Time to recovery from the onset of the episode was protracted, as only about 50% of patients recovered by one year. Annual rates of recovery then declined steadily to 28% in the second year, 22% in the third year, and 18% in the fourth year. In contrast, speed of recovery from entry into the study was more rapid, and 63% of patients recovered by four months. The recovery rates were about 20% each month for the first four months and then declined sharply for the remaining months of the one-year follow-up. Several clinical variables were statistically significant predictors of recovery when measured from entry into the study: superimposition of the acute episode on a chronic underlying depression, acuteness of onset of he depression, and severity of depression for the subgroup of patients without superimposed illness.

Actuarial Analysis↗

Use of the life table method in determining attrition from treatment.

Life table analysis of attendance at an outpatient clinic indicates levels of attrition similar to those reported by follow-up and other studies of treatment for drug dependence. With appropriate qualifications, rates of attrition may be viewed as measures of treatment outcome.

Actuarial Analysis↗

Calculation of life tables from survey data: a technical note.

Life table calculations from survey data are frequently based on events for which exact dates are not available. When these dates are coded in monthly form (e.g., century months), estimates should take into account the fact that the first duration interval--the interval which captures events occurring in the first month of exposure--is half the length of all remaining intervals. Although failure to do so has a trivial effect on many demographic calculations, estimates which are based on events which occur with high frequency in the first few months of exposure can be substantially biased. Estimates of fecundability for four countries in the World Fertility Survey are used to illustrate this bias.

Actuarial Analysis↗

New developments in the Life Table Analysis System of the National Institute for Occupational Safety and Health.

In the 1970s, the National Institute for Occupational Safety and Health developed a Life Table Analysis System to analyze occupational cohort studies. We have updated the original system by adding two new features: direct standardization with a test for linear trend, and analyses by lagged exposure (either duration of exposure or cumulative exposure). We have also updated US reference rates through 1989. The updated systems and documentation (version F) are available upon request. In collaboration with the National Cancer Institute, we have also developed multiple cause-of-death rate files, which consider contributory as well as underlying cause. These files (also available upon request) will enable investigators to derive the expected prevalence of diseases at death, which can then be compared with the observed prevalence in an exposed cohort. Work is currently underway to produce a personal computer version of the Life Table Analysis System.

Cause of Death↗

Stratified trend and homogeneity analyses of proportions and life table data.

Tests for linear trend and homogeneity among proportions and analogous time adjusted tests for life table data are programmed for stratified data. For proportions, the maximum likelihood estimator of the common logistic slope and its approximate standard error is given. This parameter is related to the relative risk for the factor under test. The model is a simpler and more relevant subcase of the general linear multiple logistic model. Tests of fit include a chi-square test of departure from trend for both types of data, and, for proportions, a test for the equality of slopes among groups of strata. The program is particularly useful for large prospective studies in epidemiology, but may also prove helpful for case-control studies, clinical trials, and combining animal studies. Several optional analyses are included. The program generalizes most aspects of a previously published program by Thomas, Breslow, and Gart (Trend and homogeneity analyses of proportions and life table data. Comp. Biomed. Res. 10, 373 (1977)). A FORTRAN card deck with documentation is available upon request.

Actuarial Analysis↗

[Life table analysis of Tsuga longibracteata population].

Tsuga longibracteata is a rare and endangered tree species in China. Based on the life table of population and the theory of survival analysis, the authors worked out the life table of Tsuga longibracteata population drew the curves of mortality density function, hazard rate function and survival, and analyzed the population dynamics. The results show that the population had two peaks of mortality, and the survival curve of the population trended to the type of Deevey II.

China↗

Life table method for analyzing relationship between smoking and hypertension.

The life table method is introduced for describing the relationship of smoking amount to prevalence rate of hypertension. The smoking level at different sex groups are collected and grouped according to their cumulative smoking amount. Using the total number of peasants, and the number of hypertensives in each group, one is able to calculate the probability of occurrence of hypertension for each dose group as well as for each cumulative dose group, which indicated that there was a dose-effect curve in estimating the relationship between the cumulative smoking and the probability of hypertension, and females presented a significantly higher probability of hypertension than males in same smoking level.

Adult↗

In-vitro fertilization and embryo transfer. Prospects of pregnancy by life-table analysis.

Data have been analysed for 1775 laparoscopies that were undertaken for the collection of oocytes, and for 1401 embryo transfers that were undertaken for the treatment of infertility by in-vitro fertilization, by the Monash University in-vitro fertilization unit team. The cumulative success rates with multiple attempts were analysed by life-table analysis and life-table graphs were constructed. Almost half the patients were pregnant after five laparoscopies. These findings suggest that treatment should consist of multiple laparoscopies and that improvements should be aimed at decreasing the morbidity, stress and cost of multiple attempts.

Actuarial Analysis↗

Estimating the age-at-onset function using life-table methods.

In the analysis of dominantly inherited diseases, the age-at-onset function is often estimated from the observed age-at-onset distribution of cases. This estimate is confounded with the age distribution of the population from which the cases were sampled and is accurate only if there are no competing causes of death. In this paper, we present a straightforward method for calculating a more accurate age-at-onset function under etiologic heterogeneity. We use the life-table approach and survival analysis methods. This method is illustrated using data on first-degree relatives of probands from two sets of families with high cancer incidence: one with breast/ovarian cancer and the other with colon cancer. A comparison of the estimated age-at-onset function obtained by the two methods is presented. In both cases, colon cancer as well as breast/ovarian cancer, the estimates of onset probabilities based on proportion of cases, are consistently higher than those obtained by the life-table method. For breast/ovarian cancer, this difference is not as striking as it is in the case of colon cancer; nevertheless, the method using proportion of cases tends to give a lower estimate of the age-at-onset function (higher probability of being affected at lower age) than the life-table approach.

Actuarial Analysis↗

[Hazard function and life table: an introduction to the failure time analysis].

Failure time analysis has become popular in demographic studies. It can be viewed as a part of regression analysis with limited dependent variables as well as a special case of event history analysis and multistate demography. The idea of hazard function and failure time analysis, however, has not been properly introduced to nor commonly discussed by demographers in Japan. The concept of hazard function in comparison with life tables is briefly described, where the force of mortality is interchangeable with the hazard rate. The basic idea of failure time analysis is summarized for the cases of exponential distribution, normal distribution, and proportional hazard models. The multiple decrement life table is also introduced as an example of lifetime data analysis with cause-specific hazard rates.

Demography↗