Adaptive line transect sampling.

Adaptive line transect sampling offers the potential of improved population density estimation efficiency over conventional line transect sampling when populations are spatially clustered. In adaptive sampling, survey effort is increased when areas of high animal density are located, thereby increasing the number of observations. Its disadvantage is that the survey effort required is not known in advance. We develop an adaptive line transect methodology that, by varying the degree of adaptation, allows total effort to be fixed at the design stage. Relative to conventional line transect surveys, it also provides better survey coverage in the event of disruption in survey effort, e.g., due to poor weather. In analysis, sightings from the adaptive sections are downweighted in proportion to the increase in effort. We evaluate the methodology by simulation and report on surveys of harbor porpoise in the Gulf of Maine, in which the approach was compared with conventional line transect sampling.

Life table analysis of the United States' Year 2000 mortality objectives.

BACKGROUND: The US Year 2000 mortality objectives are model standards cast as targeted changes in age-adjusted cause-specific death rates. This research centred on the projected impact of such changes on life expectancy and the mortality toll for each sex. METHODS: A computer simulation was conducted using single decrement, multiple decrement and cause-elimination life table techniques, together with a decomposition procedure. RESULTS: Male and female life expectancy at birth was projected to increase by 1.71 and 1.51 years, respectively, between the designated 1987 baseline and 2000. The leading beneficiaries would be those aged 65 and older, followed by those aged 45-64, and infants. Declines in coronary heart disease, stroke and injury death rates would most influence the projected life expectancy changes, irrespective of sex. Approximately 782,000 male deaths and 730,000 female deaths would be averted under Year 2000 assumptions. CONCLUSIONS: Life expectancy would be a useful summary measure to incorporate into official evaluations of the Year 2000 mortality objectives. Targeting of excess male mortality in the US and other highly industrialized nations is recommended.

The Gompertz distribution and its applications.

"In this paper we study the underlying Gompertz distribution and develop formulae for the moments and other characteristics of this useful but apparently unknown distribution. We find that the skewness and kurtosis of the distribution are fixed constants independent of the two distribution parameters, and this would appear to be the reason for the mixed success writers have experienced fitting the curve to fertility data. We also show the distribution of the minimum of n independent Gompertz variables, all having the same c-parameter, is itself a Gompertz variable with the same c-parameter." (SUMMARY IN FRE AND ITA)

On the use of health surveys for estimating transition rates for morbidity processes.

"In this paper, we describe a potential source of useful data for estimating disease onset, recovery and death rates, and derive the necessary equations for estimating the rates. The limitations of the method, both theoretical and practical, are described, and numerical results are reported in the cases of two Italian health surveys of the 1980s.... Our goal in this paper is to study quality of life, and to attempt to provide measures which may allow health policy decisions affecting quality of life. For this purpose, estimates of morbidity provided by general population health surveys would seem to be appropriate." (SUMMARY IN FRE AND ITA)

Fun with Gompertz.

PIP: The author examines Gompertz's law of mortality and describes approximations and shortcuts in calculations made using the law. The usefulness of these formulas for the demographer is noted. The formulas are illustrated using data for the Federal Republic of Germany and Yugoslavia. (SUMMARY IN FRE AND ITA)^ieng

Morbidity and mortality: differentials and their trends.

"To establish whether medical science has managed to ensure quality of life during the additional years of life now available in many populations requires a relatively complex interactive model of morbidity and mortality. The development of such a model has been the prime objective of this paper. For the model we describe, formulae were derived which allow a health scientist to explain the contributions, by age, of different diseases to changes in life expectancy in healthy or less than healthy states, and for a particular disease, the contribution of disease prevention, successful disease treatment (leading to recovery) and mortality prevention. Such an analysis can be very helpful for health policy purposes. Formulae were also developed for studying trends in life expectancy differentials in terms of changes in rates of disease prevention, disease treatment success and mortality prevention." (SUMMARY IN FRE)

On the derivation of a full life table from mortality data recorded in five-year age groups.

Mortality data are often gathered using 5-year age groups rather than individual years of life. Furthermore, it is common practice to use a large open-ended interval (such as 85 and over) for mortality data at the older ages. These limitations of the data pose problems for the actuary or demographer who wishes to compile a full and accurate life table using individual years of life. The author devises formulae which handle these problems. He also devises methods for handling mortality during the 1st year of life and for dealing with other technical problems which arise in the compilation of the full life table from grouped data.

On the decomposition of changes in expectation of life and differentials in life expectancy.

The projection of mortality rates requires inter alia close examination of the mortality experience of a population over a long period of time and will usually also involve the analysis of mortality trends by cause of death. In two of the more important recent contributions, techniques were devised for explaining change in life expectancy in terms of mortality changes in particular age groups and by different causes of death. The approaches adopted by the authors differ, and the purpose of this article is to reconcile the two and tie the results in with those obtained by earlier writers. A new method for explaining the change in a life expectancy differential in terms of the observed changes in the mortality differentials and the observed change in overall mortality level is also described.

Cause of death in Australia 1971-1981.

PIP: The author examines developments in the causes of death in Australia between 1971 and 1981 using official statistics. Particular attention is given to age and sex differentials in the major causes of death. Selected historical data to 1901 are included as well as projected mortality rates for 1991^ieng

Bias in graduated life table functions.

Survival proportions and expectations of life estimated directly from observed crude mortality rates are usually unbiased. Estimates of survival proportions and expectations of life obtained from graduated mortality rates at individual ages tend to be positively biased, although the actual bias is small for reasonably large experiences.