Driving to work and overweight and obesity: findings from the 2003 New South Wales Health Survey, Australia

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1 (2006) 30, & 2006 Nature Publishing Group All rights reserved /06 $30.00 ORIGINAL ARTICLE : findings from the 2003 New South Wales Health Survey, Australia LM Wen, N Orr, C Millett and C Rissel Health Promotion Unit (Eastern Zone), Sydney South West Area Health Service, Camperdown, NSW, Australia Objectives: To examine possible associations between driving to work, physical activity and overweight and obesity. Design: Secondary analysis of cross-sectional data from a representative sample of the 2003 New South Wales Adult Health Survey, Australia. Subjects: A total of 6810 respondents aged 16 years or over. Measurements: Self-reported height and weight, modes of transport to work, level of physical activity, fruit and vegetable intake and social-economic status. Results: Almost half of the respondents (49%) were overweight. The main mode of transport to work was driving a car (69%), 15% used public transport, 7% walked, 2% cycled and 6% worked at home. People who drove to work were less likely to achieve recommended levels of physical activity compared to non-car users (56.3 vs 44.3%, w 2 ¼ 82.5, Po0.0001). Driving to work was associated with being overweight or obese (adjusted odds ratio ¼ 1.13 (95% CI ), P ¼ 0.047). Inadequate level of physical activity was independently associated with overweight or obesity. Socially and economically disadvantaged people were also more likely to be overweight and obese. In addition, being female or never married or having higher level of education was associated with a significantly reduced odds ratio of being overweight or obese, as was speaking a language other than English at home. No association was found between weight status and recommended vegetable or fruit intake. Conclusions: Driving to work is the dominant mode of commuting in a modern society and its impact on health requires scrutiny. The association found in this study between driving to work and overweight and obesity warrants further investigation to establish whether this relationship is causal. If proved as such, then promoting active transport modes such as walking, cycling and public transport should form a key component of global obesity prevention efforts. (2006) 30, doi: /sj.ijo ; published online 10 January 2006 Keywords: driving; overweight; health survey Introduction The dramatic increase in overweight and obesity has been well documented in studies worldwide 1,2 and now represents the second leading cause of premature mortality in developed countries. 3,4 Prevalence appears higher among males, older age groups, those with lower socio-economic status and within particular ethnic groups. 5,6 Increasingly, sedentary lifestyles together with greater consumption of highenergy foods appear to be major contributing factors. 7 9 Correspondence: Dr LM Wen, Health Promotion Unit, Sydney South West Area Health Service, Level 9, King George V Building, Missenden Road, Camperdown, NSW 2050, Australia. lmwen@ .cs.nsw.gov.au Received 9 May 2005; revised 17 October 2005; accepted 24 October 2005; published online 10 January 2006 A clear example of increasing sedentary lifestyles is our growing car dependency. Travel by car is the dominant mode of commuting in all developed countries. For example, car ownership and use increased by 14 and 20%, respectively, in Sydney, Australia between 1981 and 1991 despite population growth of only 9% over this period. 10 Britain has experienced a similar upward trend, including a significant increase in the number of car journeys made for short distances. 11 These shifts appear to have had a considerable impact on population levels of walking, cycling and public transport use, which are collectively known as active transport. 12 The British National Travel Survey found that the total miles travelled (non-leisure) fell by 26% in Britain between 1975/76 and 1999/2000 for both walking and cycling. 13 There is little empirical evidence supporting a relationship between mode of transport used and overweight and obesity.

2 A study examining urban sprawl and weight status in Atlanta found an association between car use and obesity. 14 However, the significance of this finding for population health in other settings may be limited by the fact that the study was undertaken in a single US city, achieved a low response rate and did not include overweight as part of the main outcome measure. Moreover, the study did not include a recognized measure of physical activity levels. In 2003, active transport questions were added to the New South Wales (NSW) Continuous Health Survey, which is the primary mechanism for monitoring health status and risk factors in NSW. This permitted the relationship between health status, health behaviour and mode of transport to be investigated in a large population survey, and marks the first time that such a comprehensive health survey has included questions about modes of transport in Australia. The principal aim of the study was to examine associations between driving to work, physical activity and overweight and obesity. Methods The NSW Continuous Health Survey was conducted by telephone among a representative sample of residents aged 16 years or over in NSW, Australia. 15 The main issues covered in the survey include health behaviours (e.g. physical activity and smoking), health service utilization, health status (e.g. self-rated health status, overweight or obesity), as well as socio-demographic characteristics. In 2003, respondents completed the survey, of which 52% of respondents who reported that they had a job were included in this study (n ¼ 6810). A job was defined very broadly and included full or part time, paid or voluntary. This group of the respondents was the focus of the study. Study variables Study variables included age, gender, education level, marital status, language spoken at home, fruit and vegetable intake, socio-economic status (SEIFA), adequate levels of physical activity and usual modes of transport to work. The study outcome variable was weight status (BMI). Full descriptions of variable definitions can be found on the NSW Health Survey website. 16 An adequate level of physical activity was defined as undertaking physical activity for a total of 150 min/week over five separate occasions. 15 The total minutes were calculated by adding minutes in the last week spent walking (continuously for at least 10 min), minutes doing moderate physical activity, plus minutes doing vigorous physical activity multiplied by two. This measure is recommended by the US Surgeon General. 17 Recommended daily fruit and vegetable intake was based on the Australian Guide to Healthy Eating. 18 The recommended daily consumption of fruit is three serves for people aged years, and two serves for people aged 19 years and over. One serve is equivalent to one medium or two small pieces of fruit. The recommended daily intake of vegetables is four serves for female subjects of any age and for males aged years or over 60 years, and five serves for males aged years. Socio-economic status was assessed using the Socio Economic Index for Areas (SEIFA) measure of disadvantage, which is a commonly used measure of socio-economic status developed by the Australian Bureau of Statistics. 19 The SEIFA values were grouped into quintiles, with quintile one being the least disadvantaged, and five the most disadvantaged. Modes of transport to work were determined by responses to the question, How do you usually get to work? which allowed for multiple responses. The responses included travel by train, bus, ferry, tram, bicycle or walking only, or travel by car as the driver or passenger or working from home. For the purpose of identifying driving commuters, the responses were dichotomized into either drivers or nondrivers. For a subset of respondents resident in the Central Sydney region (n ¼ 462), the frequency of car use in the past week was also asked. The responses were coded into either less than 6, 6 10 or more than 10 times a week. Identification of overweight and obesity was based on body mass index (BMI), which was calculated using selfreported height and weight with standard classifications (o25 ¼ normal or underweight, and 25 or more overweight and obese ). Data analysis Prevalence estimates of study variables were weighted for the probability of selection based on the household size, and for age and sex based on NSW component of the 2001 Australian Census of Population and Housing. Weighted data were used for all statistical analyses. Relationships between study and outcome variables were examined using the Pearson w 2 tests and Mantel Haenszel trend tests. Variables that were found to be associated with overweight and obesity in univariate analyses were entered into a logistic regression model in order to identify health behavioural and transport risk factors that predict overweight and obesity in those commuting by car. In the logistic regression analysis, all variables were entered in one step and removed from the model according to their statistical significance on entry, and whether they met the removal criteria (P ¼ 0.10) (which is the algorithm used by SPSS for Windows 12.0 using the enter modeling option in the logistic regression procedure). Adjusted odds ratios (ORs) with 95% confidence intervals were then calculated as a measure of the predictive power of the risk factor. Results The overall response rate to the 2003 NSW Health Survey was 67.9%. Among those 6810 respondents who were in the 783

3 784 workforce, the main mode of transport to work (69%) was driving a car, followed by public transport (15%), 7% reported walking only, 2% cycled and 6% worked at home. About 57% were male and 43% were female subjects, with a mean age of 39 years. A total of 51% were married. The majority (82%) had finished secondary or tertiary education (having graduated from a college or university) and 87% reported speaking English at home. The most common languages other than English spoken at home in NSW are Chinese (1.8%), Arabic/Lebanese (1.3%), Greek (1.1%), Italian (0.9%), Spanish (0.5%) and Vietnamese (0.3%). Only 17% of respondents reported that they usually consumed the recommended vegetable intake, with 44% consuming the recommended fruit intake. Over half of the respondents (56%) reported inadequate levels of physical activity. Most respondents (87%) rated their health as good, very good or excellent. An approximately equal proportion of respondents were allocated to each of the five SEIFA quintiles. On univariate analysis, weight status was significantly associated with gender, age, marital status, level of education, language spoken at home, level of physical activity, driving to work and the SEIFA index. No association was found between weight status and recommended vegetable or fruit intake. Among those consuming the recommended daily vegetable intake, 46.2% were overweight or obese compared to 49.3% for those not having recommended daily vegetable intake, although this was not statistically significant (w 2 ¼ 3.52, P ¼ 0.06). There was a significant relationship between driving to work and level of physical activity. People driving to work were less likely to achieve recommended levels of physical activity compared to non-car users (44.3 vs 56.3%, w 2 ¼ 82.5 Po0.0001). Based on the data collected from 462 Central Sydney residents, the higher frequency of car use also showed a positive significant association with overweight and obesity using the Mantel Haenszel trend test. Among respondents driving more than 10 times a week, 47% were overweight or obese, compared with 41% among those driving six to 10 times and 30% among those driving less than six times (w 2 ¼ 6.38, P trend ¼ 0.012). The results of the multivariate analysis are shown in Table 1. All variables that were associated with being overweight or obese in the univariate analysis retained their significance in the multivariate logistic regression model, after adjusting for the other variables. Among those respondents driving to work, 51% were classified as being overweight or obese compared to 43% of non-car drivers, with an adjusted ORs of 1.13 (95% CI , Po0.05). Inadequate levels of physical activity were also associated with overweight and obesity (OR ¼ 1.32 (95% CI ), Po0.0001). There was a clear dose response relationship between overweight and obesity and ageing. Further, respondents in the most disadvantaged quintile were at almost double the risk of being overweight and obese compared to those in the least disadvantaged group (OR ¼ 1.96 (95% CI ), Po0.0001). In addition, being female or never married or having a higher level of education significantly reduced the risk of being overweight or obese, as did people speaking a language other than English at home (adjusted OR 0.79 with 95% CI , P ¼ 0.003). Discussion We found that after controlling for potential confounders, there was a significant association between commuting to work by car and overweight or obesity (adjusted OR ¼ 1.13) compared with active transport to work such as walking, cycling or public transport. In addition, we also found a significant association between car use and physical inactivity, which may contribute to our understanding of the relationship between car use and overweight or obesity. Further investigations are needed to test the hypothesis that regularly commuting to work by car leads to lower levels of physical activity, which results in overweight or obesity because of inadequate energy expenditure. Our findings are consistent with a recently published study conducted in Atlanta that found a 6% increased likelihood of obesity with each additional hour per day spent in a car. 14 In that study, car use was found to be lower in areas with mixed land use (co-location of residential, commercial, office and institutional buildings) in white but not black respondents. However, car use appears to represent only one of several causal pathways between urban design and overweight and obesity. 14,20 For example, walk ability and ease of access to affordable, nutritious foods are likely to be other key factors, which are known to be enabling factors with regard to physical activity and energy intake. 21,22 Increased car use in China has also been linked to obesity in a cohort study that followed up those people who acquired cars and those who did not. 23 Strengths and weaknesses This study provides some of the first empirical evidence linking car use to physical activity levels and overweight and obesity internationally. It demonstrates the value of including questions on transport use and other key social determinants within routine population health surveys. While our findings may not be directly comparable to previous research given that they relate to employed persons rather than the general population, our finding of a relationship between overweight and obesity and key demographic variables such as age, gender, marital status, level of formal education and social-economic status is consistent with previous population studies. 5,6 We acknowledge the need to exercise caution in making inferences about causality based on cross-sectional surveys of this kind. Further studies are required in order to establish whether

4 Table 1 Association between driving to work and overweight or obesity 785 Study variables Characteristics of study sample weighted % (n ¼ 6810) Overweight or obese % Adjust OR a 95% CI P Modes of transport to work By other modes By driving a car Gender Male Female o Age in groups (years) o o o o Marital status Married Widowed Separated/divorced Never married o Education level Up to year HSC/TAFE Tertiary o Language spoken at home English Other than English Level of physical activity Adequate Not adequate o SIEFA index o o o a Odds ratio was adjusted for other variables in the table. the relationship between driving to work and overweight and obesity is a causal one. For example, we cannot rule out the possibility that employees who were overweight or obese were driving cars to work because of their excess body weight, rather than their driving habits being the cause of their overweight. In addition, the measurement of all key variables in the survey, including overweight and obesity, may have been prone to response bias given that they were based on self-report. However, the overall response rate for the NSW Health Survey was fairly high at 68%, which would have minimized the impact of non-response bias. Policy implications Our findings may have a number of important policy implications for addressing physical inactivity and global obesity prevention efforts, if subsequent studies confirm a casual relationship between car use and overweight and obesity. While government efforts to discourage car use remain motivated primarily by the need to curb congestion levels, the findings in this study may also provide support for this strategy based on population health considerations, such as the prevention of obesity. Much can be learnt from European countries such as the Netherlands and Germany in this regard, where the use of active transport, such as cycling, has become more commonplace. 24,25 In these countries, the greatest improvements have stemmed from making active transport alternatives more attractive, rather than by focusing on discouraging car use through health promotion or advocacy campaigns. For example, these countries have experienced significant increased investment in public

5 786 transport, which has resulted both in increased frequency of services and lower public transport fares. However, in Australia, where the trend with regard to transport appears to be moving towards an even greater role for private cars, more substantial investment in public transport as well as active transport infrastructure may be required in order to address the epidemic of overweight and obesity. Acknowledgements The data used in this study was collected by Centre for Epidemiology and Research, NSW Department of Health, Australia. CM was partly funded through a Staff Development Grant from Guy s and St Thomas Charitable Foundation in London. References 1 Ebbeling C, Pawlak D, Ludwig D. Childhood obesity: publichealth crises, common sense cure. Lancet 2002; 360: AIHW Are all Australians gaining weight? Differentials in overweight and obesity 1989/ Australian Institute of Health & Welfare Bulletin, 11 December 2003, Canberra. 3 Mokdad A, Marks J, Stroup D, Gerberding J. Actual causes of death in the United States, JAMA 2004; 291: Mokdad A, Marks J, Stroup D, Gerberding J. Correction: actual causes of death in the United States, JAMA 2005; 293: Tackling obesity in England. Report by the Comptroller and Auditor General. National Audit Office. The Stationary Office: London, Sobal J, Stunkard A. Socio-economic status and obesity: a review of the literature. Psychol Bull 1989; 105: Armstrong T, Bauman A, Davies J. Physical activity patterns of Australian adults. AIHW Catalogue CVD 10. Australian Institute of Health & Welfare: Canberra, Craig C, Russell S, Cameron C, Bauman A. Twenty-year trends in physical activity among Canadian adults. Can J Public Health 2004; 95: Stubbs C, Lee A. The obesity epidemic: both energy intake and physical activity contribute. The Medical Journal of Australia 2004; 181: New South Wales State of the Environment Department of Environment and Conservation: Sydney ISSN EPA 2003\ Transport Statistics Report. Transport Trends 2003 Edition, DfT and National Statistics, Department of transport, London, UK, Promoting active transport. An Intervention Portfolio to Increase Physical Activity as a Means of Transport. National Public Health Partnership Secretariat: Melbourne, The National Travel Survey 1999/2001. National Statistics, Department of Transport, UK, Frank L, Andresen M, Schmid T. Obesity relationships with community design, physical activity, and time spent in cars. Am J Prev Med 2004; 27: Centre for Epidemiology and Research, NSW Department of Health. New South Wales Adult Health Survey NSW Public Health Bull 2004; 15 (S-4): NSW Department of Health website. gov.au/public-health/phbsup/ahs2003.pdf accessed on March 17, US Department of Health and Human Services (USDHHS). (1996). Physical activity and health: a report of the Surgeon General. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion: Atlanta, GA. 18 NSW Department of Health website. pubhlth/strateg/food/guide/ accessed on March 17, Australian Bureau of Statistics Census of population and housing: socio-economic indexes for areas. Information Paper, Catalogue no ABS: Canberra, Ewing R, Schmid T, Killingsworth R, Zlot A, Raudenbush S. Relationship between urban sprawl and physical activity, obesity, and morbidity. Am J Health Promot 2003; 18: Pikora T, Giles-Corti B, Bull F, Jamrozik K, Donovan R. Developing a framework for assessment of the environmental determinants of walking and cycling. Soc Sci Med 2003; 56: Webb K, King L. Food, nutrition and the built environment. In: Chris Johnson (ed). Healthy Environments, Chapter 4 Government Architect s Publications (GAP): Sydney, Bell CA, Ge K, Popkin BM. The road to obesity or the path to prevention: motorized transportation and obesity in China. Obes Res 2002; 10: ADONIS Project. Analysis and Development of New Insight into Substitution of Short Car Trips by Cycling and Walking. European Communities: Italy, Pucher J, Dijkstra L. Promoting safe walking and cycling to improve public health: lessons from the Netherlands and Germany. Am J Public Health 2003; 93: