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Alcohol and smoking consumption behaviours in older Australian adults: prevalence, period and socio-demographic differentials in the DYNOPTA sample

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Abstract

Purpose

Alcohol consumption and tobacco use are key risk factors for chronic disease and health burden across the adult lifespan. We estimate the prevalence of alcohol consumption and smoking by age and time period in adults from mid to old age.

Methods

Participants (n = 50,652) were drawn from the Dynamic Analyses to Optimise Ageing (DYNOPTA) project and were compared with Australian National Health Survey data. Alcohol and smoking consumption DYNOPTA data were weighted to the estimated resident population of the sampling frame for each contributing study according to age and sex distributions within major statistical regions.

Results

Comparisons in the rates of smoking and alcohol consumption between DYNOPTA and other national surveys were comparable. Males were more likely to be (RRR = 2.12) or have been smokers (RRR = 2.97), whilst females were more likely to be non-drinkers (RRR = 2.52). Period effects were also identified; higher prevalence rates in consumption of alcohol (RRR = 3.21) and smoking (RRR = 1.67) for those contributing studies from the early 1990’s, in comparison with those studies from the latter half of the decade, were reported.

Conclusions

Over a decade, prevalence rates for high-risk consumption of alcohol and current smoking behaviour declined and suggest the possible impact of government health policy, with targeted-health policies, that included bans on public smoking, and a toughening of legislation against alcohol-related crime.

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Acknowledgments

This work was supported by a National Health and Mental Medical Research Council grant (# 410215). The data on which this research is based were drawn from several Australian longitudinal studies including: the Australian Longitudinal Study of Ageing (ALSA), the Australian Longitudinal Study of Women’s Health (ALSWH), the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), the Blue Mountain Eye Study (BMES), the Canberra Longitudinal Study of Ageing (CLS), the Household, Income and Labour Dynamics in Australia study (HILDA), the Melbourne Longitudinal Studies on Healthy Ageing (MELSHA), the Personality and Total Health Through Life Study (PATH) and the Sydney Older Persons Study (SOPS). These studies were pooled and harmonized for the Dynamic Analyses to Optimize Ageing (DYNOPTA) project. All studies would like to thank the participants for volunteering their time to be involved in the respective studies. Details of all studies contributing data to DYNOPTA, including individual study leaders and funding sources, are available on the DYNOPTA website (http://DYNOPTA.anu.edu.au). The findings and views reported in this paper are those of the author(s) and not those of the original studies or their respective funding agencies. Anstey is funded by an NHMRC Fellowship #1002560. The authors thank Dr. Timothy Windsor, Dr. Olivier Piguet, and Prof. Mary Luszcz for their suggestions and having proofed a copy of the manuscript.

Conflict of interest

None.

Ethical standards

All studies contributing to DYNOPTA were approved by the appropriate ethics committee and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki.

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Authors and Affiliations

  1. Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, Australia

    Richard A. Burns & Kaarin J. Anstey

  2. Centre for Statistical and Survey Methodology, University of Wollongong, Wollongong, NSW, Australia

    Carole L. Birrell & David Steel

  3. Department of Ophthalmology, University of Sydney, Sydney, NSW, Australia

    Paul Mitchell

Authors
  1. Richard A. Burns
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  2. Carole L. Birrell
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  3. David Steel
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  4. Paul Mitchell
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  5. Kaarin J. Anstey
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Correspondence to Richard A. Burns.

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Burns, R.A., Birrell, C.L., Steel, D. et al. Alcohol and smoking consumption behaviours in older Australian adults: prevalence, period and socio-demographic differentials in the DYNOPTA sample. Soc Psychiatry Psychiatr Epidemiol 48, 493–502 (2013). https://doi.org/10.1007/s00127-012-0558-x

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  • DOI: https://doi.org/10.1007/s00127-012-0558-x

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