Purpose: The purpose of this study was to examine the protective effects of different modes of physical activity (PA) on all-cause mortality in adults. Methods: Data for this research came from the 2001-2002 National Health and Nutrition Examination Survey (NHANES). Participants 18+ years of age who were eligible for mortality linkage were used in the analysis. Different modes of PA were determined from a series of questions asking respondents if they participated in transportation (TPA), home/yard (HPA), moderate recreational (MPA), vigorous recreational (VPA), or muscle strengthening (MSPA) physical activity. Those respondents answering “yes” to either question were considered participating in that PA mode. Cox proportional hazards regression was used to model the effects of PA mode on mortality while controlling for age, sex, race, and income. Results: Adults were at less risk of mortality if they participated in TPA (Hazard Ratio (HR) =0.72, 95% CI: 0.57, 0.90), HPA (HR=0.43, 95% CI: 0.33-0.55), VPA (HR=0.30, 95% CI: 0.23-0.38), MPA (HR=0.53, 95% CI: 0.45-0.62), and MSPA (HR=0.44, 95% CI: 0.32-0.60). The adjusted model showed a 24.0% decrease in mortality (HR=0.76, 95% CI: 0.67-0.85) for each additional PA mode adopted. Conclusions: Results from this study indicate that various types of PA protect adults from all-cause mortality. Additionally, a dose-response relationship exists between the number of PA modes adopted and risk of mortality.
Physical activity (PA) is a preventive health behavior that protects against chronic disease as well as premature mortality 1. Current U.S. guidelines on PA recommend that all adults accumulate at least 150 minutes each week of moderate-intensity PA or a combined moderate with vigorous-intensity equivalent 2. Studies have shown that meeting recommended levels of PA is associated with positive health outcomes in adults 3. Evidence also supports that meeting current PA guidelines is associated with mortality. One such study using a large cohort of Japanese adults showed that accumulating 150 minutes of PA was associated with lower risk of mortality 4. This study additionally showed that both moderate and vigorous-intensity forms of PA contributed to the reduced mortality risk.
Another study that examined the relationship between PA and health used a sample of community-dwelling men 70+ years of age 5. This study specifically examined the effect of walking speed on mortality and found that men with greater speeds saw less risk of both all-cause and cardiovascular mortality. A final study on Belgian men used both PA at work and in leisure-time combined with physical fitness as predictors of mortality 6. Results from this study showed that low levels of both forms of PA increased risk of all-cause mortality. However, men with low levels of leisure-time PA and high levels of work PA were still at greater risk of mortality, with even greater mortality risk if they were physically less fit.
Despite our knowledge regarding the protective effect of PA on various health outcomes, less is known about the various modes of PA and longevity in large-scale populations. Therefore, the purpose of this study was to examine the protective effects of different modes of PA on all-cause mortality in adults.
Data for this research came from the 2001-02 National Health and Nutrition Examination Survey (NHANES) and associated mortality file 6. NHANES is comprised of a series of continuous surveys designed to assess health and nutrition behavior and status in U.S. children and adults. Continuous NHANES data are organized into categories: demographics, dietary, examination, laboratory, questionnaire, and limited access data. NHANES provides a rich source of health data due to the physical examination and clinical laboratory data components. Mortality data were linked to NHANES participants by the National Center for Health Statistics (NCHS) and the most recent mortality status follow-up ended December 31, 2011. A total of 5,985 participants who were 18+ years of age, answered all PA questions, and who were eligible for mortality linkage were used in the analysis.
2.2. MeasuresFive different PA independent variables were used: transportation (TPA), home/yard (HPA), moderate recreational (MPA), vigorous recreational (VPA), and muscle strengthening (MSPA). PA mode status was determined from a series of questions asking respondents if they participated in TPA, HPA, MPA, VPA, and/or MSPA 7. HPA was assessed by the following question: “Over the past 30 days, did you do any tasks in or around your home or yard for at least 10 minutes that required moderate or greater physical effort? By moderate physical effort I mean, tasks that caused light sweating or a slight to moderate increase in your heart rate or breathing. [Such as raking leaves, mowing the lawn or heavy cleaning.]” TPA was assessed by the following question: “Over the past 30 days, have you walked or bicycled as part of getting to and from work, or school, or to do errands?” MPA was assessed by the following question “Over the past 30 days, did you do moderate activities for at least 10 minutes that cause only light sweating or a slight to moderate increase in breathing or heart rate? Some examples are brisk walking, bicycling for pleasure, golf, and dancing.” VPA was assessed by the following question “Over the past 30 days, did you do any vigorous activities for at least 10 minutes that caused heavy sweating, or large increases in breathing or heart rate? Some examples are running, lap swimming, aerobics classes or fast bicycling.” Finally, MSPA was assessed by the following question: “Over the past 30 days, did you do any physical activities specifically designed to strengthen your muscles such as lifting weights, push-ups or sit-ups?” Those respondents answering “yes” to either question were considered participating in that PA mode. Covariates were used to describe the sample and for controlling confounding in the statistical models. These covariates included sex (male/female), age (yr), race/ethnicity (White/Black/Mexican/Other), and income (U.S. $).
2.3. Statistical AnalysisPrevalence estimates with their 95% confidence intervals (CIs) were computed for PA modes, overall and across demographic variables. Estimates were also computed across survival status and differences in prevalence tested using the chi-square statistic. Cox proportional hazards regression was used to model the effects of PA mode on mortality while controlling for age, sex, race, and income. SAS version 9.4 was used to account for the sampling design 8, 9, 10, 11. All significance levels were set to p=.05.
A total of 5,985 adults were included in this analysis with a mean (median) person-year follow-up of 9.24 (9.83) and 965 deaths. Table 1 displays prevalence estimates of PA by mode across relevant demographic characteristics. Weighted prevalence estimates for TPA, HPA, VPA, MPA, and MSPA in 2001-02 were 24.1% (SE=1.7), 64.0% (1.1), 38.4% (1.5), 52.1% (1.6), and 29.7% (1.7), respectively. The prevalence of both VPA and MSPA decreased proportionately with age (p<.05). Contrarily, the prevalence of HPA, VPA, MPA, and MSPA increased proportionately with income (p<.05).
Table 2 displays prevalence estimates by mode and mortality status. Prevalence of PA across all modes were significantly (ps<.001) different between those that died and those that survived through follow-up. Most noteworthy, the number (0 to 5) of different PA modes adopted by participants was indirectly (p<.001) related to mortality risk. That is, among those adopting zero PA modes, 23% (95% CI: 20.17-25.2) experienced mortality, whereas among those adopting all five PA modes, 4.0% (95% CI: 0.4-7.7) experienced mortality by follow-up.
Table 3 displays hazards associated with PA mode. Adults were at less risk of mortality if they participated in TPA (Hazard Ratio (HR) =0.72, 95% CI: 0.55, 0.90), HPA (HR=0.43, 95% CI: 0.33-0.55), VPA (HR=0.30, 95% CI: 0.23-0.38), MPA (HR=0.53, 95% CI: 0.45-0.62), and MSPA (HR=0.44, 95% CI: 0.32-0.60). TPA and MSPA lost significance in the adjusted models, however, both suggested (ps<.09) predictive ability. In the unadjusted model, a 37.0% decrease in mortality (HR=0.63, 95% CI: 0.56-0.70) was seen for each additional PA mode adopted. The adjusted model showed a 24.0% decrease in mortality (HR=0.76, 95% CI: 0.67-0.85) for each additional PA mode adopted.
The purpose of this study was to examine the protective effects of different modes of PA on all-cause mortality in adults. A secondary purpose was to determine the extent to which a relationship exists between the number of PA modes adopted and survival. The results clearly showed that adopting any and all PA modes protected adults from mortality, even after adjusting for all sociodemographic confounders. Additionally, a dose-response relationship was found between the number of PA modes adopted by adults and subsequent mortality risk. That is, adults adopting more PA modes appeared to be at less risk than their counterparts adopting fewer PA modes. The evidence supporting the effects of various PA modes on mortality is sparse. One study has reported similar findings using a large sample (over 7,000) of French adults and assessed participant walking, sports-related activity, gardening, housework, and do-it-yourself project activity 12. Findings from this study showed a protective effect across many different modes, however, only sports-related activity and do-it-yourself project activity remained protective after fully adjusting the models.
Other studies have corroborated these findings in terms of their investigation of PA intensity and its relationship to mortality. One study pooled data from six different cohort studies to examine the effects of leisure-time PA on mortality 13. Results from this study showed that light activity (e.g., brisk walking) was associated with a gain of almost 2 years toward life expectancy, as compared to inactive counterparts. Additionally, higher levels of PA was associated with even greater gains in life expectancy, as compared to inactive counterparts. Another study used meta-analytical techniques and analyzed data from 22 studies to examine PA intensity and subsequent all-cause mortality 14. Results from this study showed that 30 minutes per day on 5 days per week of moderate-intensity PA was associated with an almost 20% reduction in mortality, as compared with no activity. Due to the limited data supporting the findings from this current study, these results should be considered novel. More research should also be directed toward confirming these findings.
The strength of this study is its use of nationally representative sample data. Due to the complex nature of the NHANES sampling scheme, the results from this study can be generalized to all U.S. adults 18+ years of age. Therefore, our study has an advantage over similar studies that examine relationships between PA and mortality in specific subpopulations and are then limited to specific generalizations. Our study does, however, have limitations worth mentioning. The main limitation in this study is the use of self-reported PA to assess the adoption of various modes of PA. Participant recall of PA has several drawbacks, as compared to objective measurement methods (i.e., accelerometers, pedometers, etc.). The main drawback of self-reported PA is that participants tend to overestimate their PA amounts and intensity and often as a consequence are misclassified as meeting recommended PA guidelines 15, 16, 17, 18, 19. Considering this limitation, some studies have shown moderate agreement between subjective and objective measurement methods of PA 20, 21, 22, 23. Furthermore, this study was not concerned with the assessment of participant PA amounts. In contrast, this study examined the simple case of participants acknowledging being active in various modes of PA. The two intensity-related questions used to assess MPA and VPA gave examples of respective activities and so were considered two different sets of PA modalities of varying degrees and less so considered for their ability to accurately measure PA intensity. Therefore, PA misclassification in this case would seem less severe as opposed to the scenario of assessing PA amounts and intensities. Even though, because of these limitations, the results of this study should be interpreted with caution.
Results from this study indicate that various types of PA protect adults from all-cause mortality. Additionally, a dose-response relationship exists between the number of PA modes adopted and risk of mortality. Public health efforts may benefit from the promotion of multiple different PA modes to ensure increased longevity in U.S. adults.
No financial assistance was used to assist with this project.
[1] | US Department of Health and Human Services, Office of Disease Prevention and Health Promotion, US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy people 2020. | ||
In article | |||
[2] | Physical Activity Guidelines Advisory Committee. Physical activity guidelines advisory committee report, 2008. Washington, DC: US Department of Health and Human Services. 2008 Jun 24; 2008: A1-H14. | ||
In article | |||
[3] | Hart, P. D., Benavidez, G. A., & Erickson, J. (2017). Meeting recommended levels of physical activity in relation to preventive health behavior and health status among adults. Journal of Preventive Medicine and Public Health. 2017; 50(1): 10-17. | ||
In article | View Article PubMed | ||
[4] | Kikuchi H, Inoue S, Lee IM, Odagiri Y, Sawada N, Inoue M, Tsugane S. Impact of moderate-intensity and vigorous-intensity physical activity on mortality. Medicine and science in sports and exercise. 2017 Oct 19. | ||
In article | View Article PubMed | ||
[5] | Hsu B, Merom D, Blyth FM, Naganathan V, Hirani V, Le Couteur DG, Seibel MJ, Waite LM, Handelsman DJ, Cumming RG. Total Physical Activity, Exercise Intensity, and Walking Speed as Predictors of All-Cause and Cause-Specific Mortality Over 7 Years in Older Men: The Concord Health and Aging in Men Project. Journal of the American Medical Directors Association. 2017 Oct 6. | ||
In article | View Article | ||
[6] | National Center for Health Statistics. Office of Analysis and Epidemiology. Analytic Guidelines for NCHS 2011 Linked Mortality Files, August, 2013. Hyattsville, Maryland | ||
In article | |||
[7] | Zipf G, Chiappa M, Porter KS, et al. National Health and Nutrition Examination Survey: Plan and operations, 1999-2010. National Center for Health Statistics. Vital Health Stat 1(56). 2013. | ||
In article | |||
[8] | Tabachnick BG, Fidell LS. Using multivariate statistics, 5th. Needham Height, MA: Allyn & Bacon. 2007. | ||
In article | PubMed | ||
[9] | Cody RP, Smith JK. Applied statistics and the SAS programming language. North-Holland; 1985. | ||
In article | View Article | ||
[10] | Allison PD. Survival analysis using SAS: a practical guide. SAS Institute; 2010. | ||
In article | View Article | ||
[11] | SAS/STAT(R) 14.1 User's Guide. Introduction to Survey Sampling and Analysis Procedures. SAS Institute. July 2015. | ||
In article | |||
[12] | Sabia S, Dugravot A, Kivimaki M, Brunner E, Shipley MJ, Singh-Manoux A. Effect of intensity and type of physical activity on mortality: results from the Whitehall II cohort study. American journal of public health. 2012 Apr;102(4):698-704. | ||
In article | View Article PubMed | ||
[13] | Moore SC, Patel AV, Matthews CE, de Gonzalez AB, Park Y, Katki HA, Linet MS, Weiderpass E, Visvanathan K, Helzlsouer KJ, Thun M. Leisure time physical activity of moderate to vigorous intensity and mortality: a large pooled cohort analysis. PLoS medicine. 2012 Nov 6; 9(11):e1001335. | ||
In article | View Article PubMed | ||
[14] | Woodcock J, Franco OH, Orsini N, Roberts I. Non-vigorous physical activity and all-cause mortality: systematic review and meta-analysis of cohort studies. International Journal of Epidemiology. 2010 Jul 14; 40(1): 121-38. | ||
In article | View Article PubMed | ||
[15] | Neil-Sztramko SE, Ghayyur A, Edwards J, Campbell KL. Physical Activity Levels of Physiotherapists across Practice Settings: A Cross-Sectional Comparison Using Self-Report Questionnaire and Accelerometer Measures. Physiotherapy Canada. 2017; 69(2): 152-60. | ||
In article | View Article PubMed | ||
[16] | Meyer MR, Baller SL, Mitchell SM, Trost SG. Comparison of 3 accelerometer data reduction approaches, step counts, and 2 self-report measures for estimating physical activity in free-living adults. Journal of Physical Activity and Health. 2013 Sep; 10(7): 1068-74. | ||
In article | View Article | ||
[17] | Sievi NA, Brack T, Brutsche MH, Frey M, Irani S, Leuppi JD, Thurnheer R, Kohler M, Clarenbach CF. accelerometer-versus questionnaire-based assessment of physical activity and their changes over time in patients with COPD. International journal of chronic obstructive pulmonary disease. 2017; 12: 1113. | ||
In article | View Article PubMed | ||
[18] | Garriguet D, Tremblay S, Colley RC. Comparison of Physical Activity Adult Questionnaire results with accelerometer data. Health reports. 2015 Jul 1; 26(7): 11. | ||
In article | PubMed | ||
[19] | Oyeyemi AL, Umar M, Oguche F, Aliyu SU, Oyeyemi AY. Accelerometer-determined physical activity and its comparison with the International Physical Activity Questionnaire in a sample of Nigerian adults. PloS one. 2014 Jan 28; 9(1): e87233. | ||
In article | View Article PubMed | ||
[20] | Slootmaker SM, Schuit AJ, Chinapaw MJ, Seidell JC, Van Mechelen W. Disagreement in physical activity assessed by accelerometer and self-report in subgroups of age, gender, education and weight status. International Journal of Behavioral Nutrition and Physical Activity. 2009 Mar 25;6(1):17. | ||
In article | View Article PubMed | ||
[21] | Siebeling L, Wiebers S, Beem L, Puhan MA, ter Riet G. Validity and reproducibility of a physical activity questionnaire for older adults: questionnaire versus accelerometer for assessing physical activity in older adults. Clinical epidemiology. 2012; 4: 171. | ||
In article | View Article PubMed | ||
[22] | Mynarski W, Psurek A, Borek Z, Rozpara M, Grabara M, Strojek K. Declared and real physical activity in patients with type 2 diabetes mellitus as assessed by the International Physical Activity Questionnaire and Caltrac accelerometer monitor: a potential tool for physical activity assessment in patients with type 2 diabetes mellitus. Diabetes research and clinical practice. 2012 Oct 31; 98(1): 46-50. | ||
In article | View Article PubMed | ||
[23] | Chandonnet N, Saey D, Alméras N, Marc I. French Pregnancy Physical Activity Questionnaire compared with an accelerometer cut point to classify physical activity among pregnant obese women. PLoS One. 2012 Jun 11; 7(6): e38818. | ||
In article | View Article PubMed | ||
Published with license by Science and Education Publishing, Copyright © 2017 Peter D. Hart
This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
[1] | US Department of Health and Human Services, Office of Disease Prevention and Health Promotion, US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy people 2020. | ||
In article | |||
[2] | Physical Activity Guidelines Advisory Committee. Physical activity guidelines advisory committee report, 2008. Washington, DC: US Department of Health and Human Services. 2008 Jun 24; 2008: A1-H14. | ||
In article | |||
[3] | Hart, P. D., Benavidez, G. A., & Erickson, J. (2017). Meeting recommended levels of physical activity in relation to preventive health behavior and health status among adults. Journal of Preventive Medicine and Public Health. 2017; 50(1): 10-17. | ||
In article | View Article PubMed | ||
[4] | Kikuchi H, Inoue S, Lee IM, Odagiri Y, Sawada N, Inoue M, Tsugane S. Impact of moderate-intensity and vigorous-intensity physical activity on mortality. Medicine and science in sports and exercise. 2017 Oct 19. | ||
In article | View Article PubMed | ||
[5] | Hsu B, Merom D, Blyth FM, Naganathan V, Hirani V, Le Couteur DG, Seibel MJ, Waite LM, Handelsman DJ, Cumming RG. Total Physical Activity, Exercise Intensity, and Walking Speed as Predictors of All-Cause and Cause-Specific Mortality Over 7 Years in Older Men: The Concord Health and Aging in Men Project. Journal of the American Medical Directors Association. 2017 Oct 6. | ||
In article | View Article | ||
[6] | National Center for Health Statistics. Office of Analysis and Epidemiology. Analytic Guidelines for NCHS 2011 Linked Mortality Files, August, 2013. Hyattsville, Maryland | ||
In article | |||
[7] | Zipf G, Chiappa M, Porter KS, et al. National Health and Nutrition Examination Survey: Plan and operations, 1999-2010. National Center for Health Statistics. Vital Health Stat 1(56). 2013. | ||
In article | |||
[8] | Tabachnick BG, Fidell LS. Using multivariate statistics, 5th. Needham Height, MA: Allyn & Bacon. 2007. | ||
In article | PubMed | ||
[9] | Cody RP, Smith JK. Applied statistics and the SAS programming language. North-Holland; 1985. | ||
In article | View Article | ||
[10] | Allison PD. Survival analysis using SAS: a practical guide. SAS Institute; 2010. | ||
In article | View Article | ||
[11] | SAS/STAT(R) 14.1 User's Guide. Introduction to Survey Sampling and Analysis Procedures. SAS Institute. July 2015. | ||
In article | |||
[12] | Sabia S, Dugravot A, Kivimaki M, Brunner E, Shipley MJ, Singh-Manoux A. Effect of intensity and type of physical activity on mortality: results from the Whitehall II cohort study. American journal of public health. 2012 Apr;102(4):698-704. | ||
In article | View Article PubMed | ||
[13] | Moore SC, Patel AV, Matthews CE, de Gonzalez AB, Park Y, Katki HA, Linet MS, Weiderpass E, Visvanathan K, Helzlsouer KJ, Thun M. Leisure time physical activity of moderate to vigorous intensity and mortality: a large pooled cohort analysis. PLoS medicine. 2012 Nov 6; 9(11):e1001335. | ||
In article | View Article PubMed | ||
[14] | Woodcock J, Franco OH, Orsini N, Roberts I. Non-vigorous physical activity and all-cause mortality: systematic review and meta-analysis of cohort studies. International Journal of Epidemiology. 2010 Jul 14; 40(1): 121-38. | ||
In article | View Article PubMed | ||
[15] | Neil-Sztramko SE, Ghayyur A, Edwards J, Campbell KL. Physical Activity Levels of Physiotherapists across Practice Settings: A Cross-Sectional Comparison Using Self-Report Questionnaire and Accelerometer Measures. Physiotherapy Canada. 2017; 69(2): 152-60. | ||
In article | View Article PubMed | ||
[16] | Meyer MR, Baller SL, Mitchell SM, Trost SG. Comparison of 3 accelerometer data reduction approaches, step counts, and 2 self-report measures for estimating physical activity in free-living adults. Journal of Physical Activity and Health. 2013 Sep; 10(7): 1068-74. | ||
In article | View Article | ||
[17] | Sievi NA, Brack T, Brutsche MH, Frey M, Irani S, Leuppi JD, Thurnheer R, Kohler M, Clarenbach CF. accelerometer-versus questionnaire-based assessment of physical activity and their changes over time in patients with COPD. International journal of chronic obstructive pulmonary disease. 2017; 12: 1113. | ||
In article | View Article PubMed | ||
[18] | Garriguet D, Tremblay S, Colley RC. Comparison of Physical Activity Adult Questionnaire results with accelerometer data. Health reports. 2015 Jul 1; 26(7): 11. | ||
In article | PubMed | ||
[19] | Oyeyemi AL, Umar M, Oguche F, Aliyu SU, Oyeyemi AY. Accelerometer-determined physical activity and its comparison with the International Physical Activity Questionnaire in a sample of Nigerian adults. PloS one. 2014 Jan 28; 9(1): e87233. | ||
In article | View Article PubMed | ||
[20] | Slootmaker SM, Schuit AJ, Chinapaw MJ, Seidell JC, Van Mechelen W. Disagreement in physical activity assessed by accelerometer and self-report in subgroups of age, gender, education and weight status. International Journal of Behavioral Nutrition and Physical Activity. 2009 Mar 25;6(1):17. | ||
In article | View Article PubMed | ||
[21] | Siebeling L, Wiebers S, Beem L, Puhan MA, ter Riet G. Validity and reproducibility of a physical activity questionnaire for older adults: questionnaire versus accelerometer for assessing physical activity in older adults. Clinical epidemiology. 2012; 4: 171. | ||
In article | View Article PubMed | ||
[22] | Mynarski W, Psurek A, Borek Z, Rozpara M, Grabara M, Strojek K. Declared and real physical activity in patients with type 2 diabetes mellitus as assessed by the International Physical Activity Questionnaire and Caltrac accelerometer monitor: a potential tool for physical activity assessment in patients with type 2 diabetes mellitus. Diabetes research and clinical practice. 2012 Oct 31; 98(1): 46-50. | ||
In article | View Article PubMed | ||
[23] | Chandonnet N, Saey D, Alméras N, Marc I. French Pregnancy Physical Activity Questionnaire compared with an accelerometer cut point to classify physical activity among pregnant obese women. PLoS One. 2012 Jun 11; 7(6): e38818. | ||
In article | View Article PubMed | ||