Infrarenal aortic diameter predicts all-cause mortality

Objective - To assess the relationship between infrarenal aortic diameter and subsequent all-cause mortality in men aged 65 years or older. Methods and Results - Aortic diameter was measured using ultrasound in 12 203 men aged 65 to 83 years as part of a trial of screening for abdominal aortic aneurysms. A range of cardiovascular risk factors was also documented. Mortality over the next 3 to 7 years was assessed using record linkage. Initial aortic diameter was categorized into 10 intervals, and the relationship between increasing diameter and subsequent mortality was explored using Cox proportional hazard models. Median diameter increased from 21.4 mm in the youngest men to 22.1 mm in the oldest men. The cumulative all-cause mortality increased in a graded fashion with increasing aortic diameter. Using the diameter interval 19 to 22 mm as the reference, the adjusted hazard ratio for all-cause mortality increased from 1.26 (95% CI: 1.09, 1.44; P = 0.001) for aortic diameters of 23 to 26 mm to 2.38 (95% CI: 1.22, 4.61; P = 0.011) for aortic diameters of 47 to 50 mm. Analysis of causes of death indicated that cardiovascular disease was an important contributor to this increase. Conclusion - Infrarenal aortic diameter is an independent marker of subsequent all-cause mortality.

Non-cancer mortality among people diagnosed with cancer (Australia)

Objective To investigate whether people diagnosed with cancer have an increased risk of death from non-cancer causes compared to the general population. Methods The non-cancer mortality of people diagnosed with cancer in Queensland (Australia) between 1982 and 2002 who had not died before 1 January 1993 was compared to the mortality of the total Queensland population, matching by age group and sex, and reporting by standardised mortality ratios. Results Compared to the non-cancer mortality in the general population, cancer patients (all cancers combined) were nearly 50% more likely to die of non-cancer causes (SMR = 149.9, 95% CI = [147-153]). This varied by cancer site. Overall melanoma patients had significantly lower non-cancer mortality, female breast cancer patients had similar non-cancer mortality to the general population, while increased non-cancer mortality risks were observed for people diagnosed with cervical cancer, colorectal cancer, prostate cancer, non-Hodgkin lymphoma and lung cancer. Conclusions Although cancer-specific death rates underestimate the mortality directly associated with a diagnosis of cancer, quantifying the degree of underestimation is difficult due to various competing explanations. There remains an important role for future research in understanding the causes of morbidity among cancer survivors, particularly those looking at both co-morbid illnesses and reductions in quality of life.

Asthma mortality in Australia 1920-94: Age, period, and cohort effects

Study objective-To investigate asthma mortality during 1920-94 in Australia in order to assess the relative role of period and birth cohort effects. Design-Asthma mortality (both sexes) was age standardised and examined for changes over time. The data were also examined for age, period, and cohort (APC) effects using Poisson regression modelling. Setting-National Australian mortality data. Participants-Population (both sexes) aged 15-34 years, 1920-94. Main results-Age adjusted period rates indicate an increase in asthma mortality during the 1950s, and increases and subsequent falls (epidemics) during the mid 1960s and late 1980s. APC modelling suggested an increasing cohort effect (adjusted for both age and period) from the birth cohort 1950-54 onwards. Period effects (adjusted for age and cohort) are characterised by an increase in the 1950s (possibly due to changes in diagnostic labelling), minimal or no increases in the mid 1960s and late 1980s (where period peaks had been noted when data were adjusted for age only), and declines in mortality risk subsequent to the periods where age-period analysis had noted increases. Thus, in Australia, some of the mid 1960s epidemic in asthma deaths, and all of the late 1980s mortality increase, seem to be attributable to cohort effects. Conclusions-The increase in asthma mortality cohort effect is consistent with empirical evidence of recent increases in prevalence (and presumably incidence) of asthma in Australia, and suggests the need for more research into the underlying environmental aetiology of this condition.

Fertility and female work force participation in Bangladesh: Causality and cointegration

This paper examines the causal links between fertility and female labor force participation in Bangladesh over the period 1974-2000 by specifying a bivariate and several trivariate models in a vector error correction framework. The three trivariate models alternatively include average age at first marriage for females, per capita GDP and infant mortality rate, which control for the effects of other socio-economic factors on fertility and female labor force participation. All the specified models indicate an inverse long-run relationship between fertility and female labor force participation. While the bivariate model also indicates bidirectional causality, the multivariate models confirm only a unidirectional causality – from labor force participation to fertility. Further, per capita GDP and infant mortality rate appear to Granger-cause both fertility and female labor force participation.

Quasi-stationarity in populations that are subject to large-scale mortality or emigration

We shall examine a model, first studied by Brockwell et al. [Adv Appl Probab 14 (1982) 709.], which can be used to describe the longterm behaviour of populations that are subject to catastrophic mortality or emigration events. Populations can suffer dramatic declines when disease, such as an introduced virus, affects the population, or when food shortages occur, due to overgrazing or fluctuations in rainfall. However, perhaps surprisingly, such populations can survive for long periods and, although they may eventually become extinct, they can exhibit an apparently stationary regime. It is useful to be able to model this behaviour. This is particularly true of the ecological examples that motivated the present study, since, in order to properly manage these populations, it is necessary to be able to predict persistence times and to estimate the conditional probability distribution of population size. We shall see that although our model predicts eventual extinction, the time till extinction can be long and the stationary exhibited by these populations over any reasonable time scale can be explained using a quasistationary distribution. (C) 2001 Elsevier Science Ltd. All rights reserved.