Gopinath B, Flood VM, Burlutsky G, Mitchell P. Combined Influence of Health Behaviors on Total and Cause-Specific Mortality. Arch Intern Med. 2010;170(17):1605-1607. doi:10.1001/archinternmed.2010.303
A recent article in the Archives1 prospectively examined the individual and collective influence of 4 risk factors (physical activity, diet, smoking, and alcohol consumption) on total and cause-specific mortality. In the Health and Lifestyle Survey (HALS), adjusted hazard ratios and 95% confidence intervals (CIs) for total mortality associated with 1, 2, 3, and 4 poor health behaviors compared with none were 1.85 (95% CI, 1.28-2.68), 2.23 (95% CI, 1.55-3.20), 2.76 (95% CI, 1.91-3.99), and 3.49 (95% CI, 2.31-5.26), respectively (P value for trend, <.001). Only a handful of population-based studies2- 4 have examined the combined effect of these behaviors on mortality. We investigated whether the collective influence of similar poor health behaviors as detailed by Kvaavik et al1 influenced the risk of total and cause-specific mortality in a cohort of older Australian adults.
The Blue Mountains Eye Study (BMES-1) is a population-based cohort study of sensory loss and other health outcomes, with methods previously reported.5 During 1992 through 1994, 3654 participants 49 years or older were examined (82.4% participation). At 5-year follow-up examinations (BMES-2), 2335 surviving participants (75.1% of participants; 543 had died) were examined. Of the 2335 survivors in BMES-2, 1952 (75.6% of survivors; 1103 persons died) were re-examined at 10-year follow-up examinations (BMES-3).
To identify and confirm persons who died after the baseline examination, participants were cross-matched with Australian National Death Index data6 for deaths until the end of December 2007 (15-year follow-up). Total and cause-specific mortality were assessed using the International Classification of Diseases, Ninth Revision definitions, as used in the HALS.1 We used similar methods to define health behaviors and to generate an index ranging from 0 to 4, as detailed by Kvaavik et al.1 However, our physical activity measures included not only exercise during leisure time as in the HALS but also other activities such as walking or work-related exercise. We defined poor physical activity as less than 3 times per week. Because we did not have detailed information on arterial disease, bronchitis, emphysema, tuberculosis, and other respiratory tract diseases, these comorbidities were not adjusted for in the multivariable model.
Of the 3654 participants at baseline, 2897 had information on all 4 risk factors: 14.2% were current smokers, 20.3% reported poor drinking behavior, 18.4% consumed less than 4 servings per day of fruits and/or vegetables, and 55.1% reported participating in physical activity for less than 3 times per week. The adjusted hazard ratio for 4 poor health behaviors compared with none for all-cause mortality was 4.58 (95% CI, 2.57-8.15), and the corresponding effect estimates for cardiovascular disease and cancer mortality were 4.45 (95% CI, 1.91-10.40) and 4.34 (95% CI, 1.71-11.01), respectively (Table). Compared with participants without any poor health behaviors, the mortality risk for each outcome increased progressively with greater number of poor health behaviors (P value for trend, <.01). The difference in β coefficients between a health score of 0 vs 4 was 1.45, equivalent to approximately 14 years in chronological age for mortality risk.
The collective effect of poor health behaviors on mortality was substantial in our older cohort, with BMES participants who engaged in all 4 poor health behaviors having a 4-fold greater risk of total, cardiovascular disease, and cancer mortality compared with those exhibiting none of these behaviors. This is relatively similar to the 3-fold increase in mortality risk observed in the younger HALS cohort.1 Furthermore, in HALS, the mortality risk for those with 0 compared with 4 poor health behaviors was equivalent to being 12 years younger in chronological age—similar to the 14-year difference observed in our study and in the European Prospective Investigation of Cancer–Norfolk study.2 Hence, data from both the BMES and HALS provide further supportive evidence that even modest differences in lifestyle and diet could make a significant difference to health at both the individual and population level.
Correspondence: Dr Mitchell, Centre for Vision Research, University of Sydney, Westmead Hospital, Hawkesbury Road, Westmead, NSW 2145, Australia (firstname.lastname@example.org).
Author Contributions:Study concept and design: Gopinath and Mitchell. Acquisition of data: Flood and Mitchell. Analysis and interpretation of data: Gopinath, Flood, Burlutsky, and Mitchell. Drafting of the manuscript: Gopinath. Critical revision of the manuscript for important intellectual content: Gopinath, Flood, Burlutsky, and Mitchell. Statistical analysis: Burlutsky. Obtained funding: Mitchell. Administrative, technical, and material support: Flood. Study supervision: Mitchell.
Financial Disclosure: None reported.