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RESEARCH AND PRACTICE |
Alfredo Morabia and Michael C. Costanza are with the Division of Clinical Epidemiology, Geneva University Hospitals, Geneva, Switzerland.
Correspondence: Requests for reprints should be sent to Alfredo Morabia, MD, PhD, Division of Clinical Epidemiology, Geneva University Hospitals, 25, Rue Micheli-du-Crest, 1211 Geneva 14, Switzerland (e-mail: alfredo.morabia{at}hcuge.ch).
| ABSTRACT |
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Small physical activity increases may prevent weight gain in most populations. Geneva residents completed validated quantitative physical activity frequency questionnaires from 1997 to 2001. Fifteen minutes per day of moderate or brisk walking, or 30 minutes per day of slow walking, could increase physical activity at the population level; however, if the specific goal is to approach expending 420 kJ/d (100 kcal/d) through walking, the duration should be closer to 60 minutes for slow walking and 30 minutes for moderate or brisk walking.
| INTRODUCTION |
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The intensity of a physical activity can be assessed by the energy expenditure it produces in terms of a multiple of an individuals (sex-age-height-weight-specific) basal metabolic rate, which is the resting energy expenditure rate.4 The typical basal metabolic rate of a Western adult is 4.2 kJ/min. Walking slowly expends 3.1 times ones basal metabolic rate. Hence, someone with a basal metabolic rate of 4.2 who walks slowly for 15 minutes expends 195 kJ.
We used a unique monitoring system for measuring the total energy expenditure of the adult resident population of Geneva, Switzerland, to simulate the potential effect of campaigns promoting different combinations of duration and intensity of daily walking on the populations total energy expenditure.
| METHODS |
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We used the 1997 to 2001 physical activity frequency questionnaire data first to estimate the existing population distribution of total energy expenditure (kJ/d). We then simulated the potential effects of a hypothetical public health campaign to persuade all adults to walk at least 15 minutes per day at various recommended intensity levels on the total energy expenditure. In the calculations, we assumed that (1) adults who already walked 15 minutes or more per day at a given recommended intensity level (prevalent compliers) would continue to do so with no change; (2) adults who did not walk at least 15 minutes per day at a given recommended intensity (nor at a higher intensity level) (eligible adults) would be persuaded to walk at exactly the minimum campaign-recommended level (unless noted otherwise); and (3) the individual basal metabolic rate multiples were 3.1 for slow walking, 3.9 for moderate walking, 4.7 for brisk walking, and 6.0 for athletic/brisk walking.
Sedentarism was defined as spending less than 10% of ones total energy expenditure in physical activities with at least an intensity of 3.9 basal metabolic rate, which corresponds to moderate walking. We repeated the calculations assuming various degrees of less-than-full participation by eligible adults. For a given participation rate, we generated a random number from the uniform distribution on the interval from 0 to 1 for each eligible adult to randomly classify each participant as a complier or noncomplier with the campaign recommendation.
| RESULTS |
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For athletic-brisk walking at 6.0 basal metabolic rate and 100% compliance, the energy expenditure gains would be +326 kJ/d for 15 minutes per day and +690 kJ/d for 30 minutes per day. With only 50% compliance by eligible adults, these gains would be reduced to +165 kJ/d and +336 kJ/d, respectively.
| DISCUSSION |
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We have used these data to promote brisk walking and to compute the statistical power to monitor its effect in collaboration with the Geneva Public Health Department. Brisk walking is a high energyexpending activity, and it can be almost universally performed in populations. In addition, changes in urban environments can be conceived to promote walking rather than other means of transportation in the population.6 This campaign will allow us to assess the validity of our simulation because changes in physical activity and other health-related behaviors will be monitored. It may well be that the effect of the intervention is greater than expected under our linear model. The walking habit may grow more rapidly once it has been adopted by a minority (i.e., a snowball effect), and it may stimulate weight-reducing dietary changes.
The population-based simulation approach proposed here can be extended to other candidate activities that can be integrated easily into everyday life by the whole population (e.g., bicycling instead of driving, climbing stairs instead of taking elevators) or by subgroups (e.g., sports).
| Acknowledgments |
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We thank Cecile Delhumeau, PhD, for performing some preliminary analyses and Martine S. Bernstein, MD, for her contributions in developing the physical activity frequency questionnaire and for supervising the data collection.
Human Participant Protection
All study subjects provided written informed consent to participate in the study, which was approved by the University of Geneva ethics committee.
| Footnotes |
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Accepted for publication June 19, 2003.
| References |
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2. Galobardes B, Costanza MC, Bernstein MS, Delhumeau C, Morabia A. Trends in risk factors for lifestyle-related diseases by socioeconomic position in Geneva, Switzerland, 19932000: health inequalities persist. Am J Public Health. 2003;93:13021309.
3. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity and the environment: where do we go from here? Science. 2003;299:853855.
4. World Health Organization. Energy and Protein Requirements. Geneva, Switzerland: World Health Organization; 1986.
5. Bernstein M, Sloutskis D, Kumanyika S, Sparti A, Schutz Y, Morabia A. Data-based approach for developing a physical activity frequency questionnaire. Am J Epidemiol. 1998;147:147154.
6. Kumanyika S, Jeffery RW, Morabia A, Ritenbaugh C, Antipatis VJ. Obesity prevention: the case for action. Int J Obes Relat Metab Disord. 2002;26:425436.[ISI][Medline]
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