Abstract
Smoking and obesity are two leading causes of preventable death. Further understanding of the relationship between these two risk factors can assist in reducing avoidable morbidity and mortality. This study investigates the empirical association between obesity and the propensity to smoke and to quit smoking, using a Seemingly Unrelated (SUR) probit approach that takes into consideration the potential for reverse causality and unobserved heterogeneity. Using Australian health survey data, this article demonstrates the usefulness of the SUR probit approach in generating information on the relationship between unobserved factors influencing both smoking behaviour and obesity, and in providing estimates of the conditional probabilities of each risk factor. Results suggest the two risk factors are not independent. The presence, size and direction of correlation between the unobserved factors are found to vary by smoking behaviour and by gender. Estimates of conditional probabilities demonstrate smokers have a lower probability of obesity, particularly among females, and ex-smokers have a higher probability of obesity, particularly among males. These findings suggest that health policies targeted at one risk factor may have unintended implications for the other.
Acknowledgements
We are grateful to the Victorian Department of Human Services for providing us with the data and an anonymous referee for helpful comments.
Notes
1 Participants in the VPHS were asked: ‘Which of the following best describes your smoking status? 1. I smoke daily; 2. I smoke occasionally; 3. I don’t smoke now but I used to; 4. I’ve tried it a few times but never smoked regularly; or, 5. I’ve never smoked’. Respondents are classified as smokers if they answered 1 or 2, ex-smokers if they answered 3, and never-smokers if they answered 4 or 5.
2 Variables for ethnicity are based on the country of birth of the respondents and their parents. For example, a person is considered Asian if born in Asia or if born in Australia with both parents born in Asia. Respondents are considered Australian native if they and at least one parent was born in Australia.
3 Following similar methodology to Rhum (2005), household incomes are assumed to be at the midpoint of each income band and 125% of the (unbounded) top category. Median incomes are calculated for 32 groups stratified by gender (male or female), marital status (married, never-married, divorced, widowed) and education (primary, high-school, TAFE, University).