Dietary trends: Estimates from food supply and survey data

Objective: To illustrate methodological issues involved in estimating dietary trends in populations using data obtained from various sources in Australia in the 1980s and 1990s. Methods: Estimates of absolute and relative change in consumption of selected food items were calculated using national data published annually on the national food supply for 1982-83 to 1992-93 and responses to food frequency questions in two population based risk factor surveys in 1983 and 1994 in the Hunter Region of New South Wales, Australia. The validity of estimated food quantities obtained from these inexpensive sources at the beginning of the period was assessed by comparison with data from a national dietary survey conducted in 1983 using 24 h recall. Results: Trend estimates from the food supply data and risk factor survey data were in good agreement for increases in consumption of fresh fruit, vegetables and breakfast food and decreases in butter, margarine, sugar and alcohol. Estimates for trends in milk, eggs and bread consumption, however, were inconsistent. Conclusions: Both data sources can be used for monitoring progress towards national nutrition goals based on selected food items provided that some limitations are recognized. While data collection methods should be consistent over time they also need to allow for changes in the food supply (for example the introduction of new varieties such as low-fat dairy products). From time to time the trends derived from these inexpensive data sources should be compared with data derived from more detailed and quantitative estimates of dietary intake.

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.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

Data grid for the management, reconstruction, analysis and visualisation of archaeological data

In 2007 Associate Professor Jay Hall retires from the University of Queensland after more than 30 years of service to the Australian archaeological community. Celebrated as a gifted teacher and a pioneer of Queensland archaeology, Jay leaves a rich legacy of scholarship and achievement across a wide range of archaeological endeavours. An Archæological Life brings together past and present students, colleagues and friends to celebrate Jay’s contributions, influences and interests.