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Cadernos de Saúde Pública

versão impressa ISSN 0102-311X

Cad. Saúde Pública vol.27  supl.3 Rio de Janeiro  2011

http://dx.doi.org/10.1590/S0102-311X2011001500010 

ARTICLE ARTIGO

 

Energy expenditure through physical activity in a population of community-dwelling Brazilian elderly: cross-sectional evidences from the Bambuí cohort study of aging

 

Gasto energético com atividades físicas em idosos Brasileiros residentes em comunidade: evidências do estudo de coorte de idosos de Bambuí

 

 

Juciany Rodrigues de Oliveira Ramalho; Maria Fernanda Lima-Costa; Josélia O. A. Firmo; Sérgio Viana Peixoto

Núcleo de Estudos em Saúde Pública e Envelhecimento, Fundação Oswaldo Cruz/Universidade Federal de Minas Gerais, Belo Horizonte, Brasil

Correspondence

 

 


ABSTRACT

The aim of this study was to estimate physical activity energy expenditure among older adults. The study comprised 1,585 residents in Bambuí, Minas Gerais State, Brazil, aged > 60 years (91% of the town's total elderly), and examined the frequency and duration of 23 types of physical activity among them. Median energy expenditure was 975 MET.min/week (1,195.8 among men and 803.1 among women), declining significantly with age in both sexes. The prevalence of sedentary lifestyles (< 450 MET.min/week) was 31.2%. Unhurried walking accounted for about 1/3 of total energy expenditure. Multivariate analysis based on ordinal logistic regression showed inverse associations between energy expenditure and age and hospitalizations in both sexes. Among men, inverse associations were observed with smoking, number of chronic diseases and number of medical appointments. These results emphasize the need for effective strategies to increase physical activity in older elderly, and underscore the high prevalence of walking in this group.

Motor Activity; Energy Metabolism; Aged; Cohort Studies


RESUMO

O objetivo deste trabalho foi estimar o gasto energético das atividades físicas entre idosos. Participaram do estudo 1.585 residentes da cidade de Bambuí, Minas Gerais, Brasil, com > 60 anos (91% da população total de idosos). Foram pesquisados 23 tipos de atividade física, sua frequência e duração. A mediana do gasto energético foi de 975,0 MET.min/semana, (1.195,8 entre homens e 803,1 entre mulheres), com acentuado declínio com a idade nos dois sexos. A prevalência do sedentarismo (< 450 MET.min/semana) foi de 31,2%. Caminhar normalmente (sem pressa) correspondeu a cerca de 1/3 do total do gasto energético estimado. Em ambos os sexos, os resultados da análise multivariada baseada na regressão logística ordinal mostraram associações inversas entre gasto energético e idade e ocorrência de hospitalizações. Entre homens, foram observadas associações inversas com tabagismo, número de doenças crônicas e consultas médicas. Esses resultados ressaltam a necessidade de estratégias efetivas para aumentar as atividades físicas de idosos mais velhos, chamando atenção para o predomínio da caminhada nesse grupo.

Atividade Motora; Metabolismo Energético; Idoso; Estudos de Coortes


 

 

Introduction

Regular physical activity is the factor that most consistently predicts healthy aging, as observed in several cohort studies of older adults 1,2,3. Physical activities reduce cardiovascular disease rate independently of arterial pressure and other risk factors 4,5. Among older adults, physical activity also leads to a reduction in incapacitating conditions, as well as falls and fractures 6,7. Increased physical activity among the population can mean improved quality of life and lower health care costs for this population group 8.

In order to estimate physical activity in a population (its prevalence and the factors associated with low levels), the instruments used should offer good validity and reproducibility, in addition to easy applicability, particularly in population-based epidemiologic studies 9. The doubly-labeled water method, best practice for evaluating physical activity 10, is rarely used in population studies due to its high cost and operational difficulties 9,11.

The literature shows a wide diversity of methods used to measure physical activity 9. The questionnaire is the instrument most commonly used in epidemiologic studies. The interview may comprise a single question or a question for each activity domain 12,13,14,15,16 or even several questions to secure more detailed information on the activity's frequency, intensity and duration 17,18.

Evaluation of physical activity using a single question or one question for each activity domain offers reasonable validity 19,20, and is a strategy widely used in Brazil 13,16,21 and in other countries 22,23. More recently it has become possible to estimate weekly or daily energy expenditure 24, using instruments such as the International Physical Activity Questionnaire (IPAQ) 25,26,27,28,29,30, and others 31,32,33,34. However, to our knowledge, there are no Brazilian population-based studies estimating energy expenditure from physical activity among the elderly.

The aim of this study was to estimate energy expenditure in physical activities and the associated factors with such expenditure among baseline participants in the elderly cohort of Bambuí, Minas Gerais State, Brazil.

 

Methods

Bambuí cohort of older adults

The Bambuí cohort study of older adults was conducted in the town of Bambuí (population approximately 15,000), in Minas Gerais State, Brazil. The study design and procedures have been described in previous publications 35,36. The baseline population comprised all the town's residents aged 60 years or over on January 1st, 1997, as identified by a complete census performed by the research team. Of the 1,742 elderly residents, 1,606 (92.2%) participated in the baseline interviews conducted from February to May 1997. All baseline participants were included for this study.

The study was approved by the Ethics Research Committee of the Oswaldo Cruz Foundation (Fundação Oswaldo Cruz), Rio de Janeiro. All participants signed a declaration of free, informed consent.

Study variables

Physical activity

Estimation of energy expenditure was based on 23 closed and two open questions on physical activities performed in the previous 90 days. The questions included the type and frequency of activity, and the average time (in minutes) spent on each activity. The following activities were considered: walking normally without hurrying (walking, 2.5mph), climbing stairs at normal speed (up stairs, using or climbing up ladder), climbing stairs quickly or carrying a load (carrying load upstairs, general), sweeping or mopping the floor (mopping and scrubbing floors), cleaning windows (cleaning - wash windows), swimming (swimming, leisurely, not lap swimming, general), dancing (dancing, general), rhythmic dancing (dancing, general), riding a bicycle (bicycling, < 10mph, leisure, to work or for pleasure), wall painting (home repair, painting), shuttlecock (volleyball), tennis (tennis, general), volleyball, basketball (basketball, non-game, general), soccer (soccer, casual, general), walking quickly (walking, 3.5mph, level brisk, firm surface, walking for exercise), going to a gym or doing exercises at home (gymnastics, general), running or jogging (jogging, general), digging to plant garden or vegetable patch (lawn and garden: digging, spading, filling garden, composting), sawing wood (forestry, sawing by hand), cycling quickly (bicycling, general), riding a horse at a gallop or trot (horse racing, galloping; horse racing, trotting), and riding a bicycle uphill (bicycling, mountain). The open questions included activities not covered in the list above, and the related responses were carefully coded by a physiotherapist (J.R.O.R.). Those activities included picking coffee, milking, brush-cutting, using a wheelchair, pruning trees, picking beans, carrying firewood, walking slowly with a stick, well-cleaning with a hoe, putting up a fence, cutting firewood, and stonemasonry or carpentry.

The intensity of each activity was coded according to the Compendium of Physical Activities, which permits international comparisons 37, and only activities of moderate to vigorous intensity were considered. Levels of physical activity were calculated on the basis of estimated oxygen consumption for each activity, which allowed energy expenditure to be quantified in metabolic equivalents (METs). Estimation of energy expenditure included only physical activities where each instance lasted at least ten minutes, given that shorter durations of physical activity yield less significant benefits 6,38,39. Energy expenditure was calculated using the following formula: MET (intensity of the activity) x time (duration of the activity in minutes) x frequency (number of times per week the activity was performed) 38. Sedentary individuals were considered to be those whose energy expenditure was less than 450 MET.min/week, which corresponds to at least 150 minutes per week of moderately to vigorously intense physical activity, in line with recommendations for older adults 6,40.

Independent variables

The independent variables of the study included socio-demographic characteristics (age, schooling and marital status), health-related habits (tobacco and alcohol use), number of chronic diseases and use of health services (number of medical appointments and hospitalizations in the previous 12 months). Tobacco users were considered those who reported having smoked at least 100 cigarettes in their lives, and who continued smoking. Alcohol use was defined as intake of more than two measures per day in the previous 12 months. The number of chronic diseases was based on the history of medical diagnosis for arterial hypertension, cholesterol, angina, myocardial infarction, arthritis or rheumatism, diabetes and Chagas disease. Further details can be found in other publications 35,36.

Data analysis

Unadjusted data analysis was based on the Student t-test, Kruskal-Wallis test and Pearson chi-square test, respectively, for comparisons among means, medians and frequencies. Multivariate analysis was based on prevalence ratios (PRs) and confidence intervals of 95% estimated by logistic regression model in order to examine the strength of the associations between the independent variables and energy expenditure expressed in tertiles. The parallel regression assumption for the PRs was examined by the Wald test. For that assumption to hold, the PR estimated by comparing the lower tertile with the upper two tertiles will be the same as when the lower two tertiles are compared with the upper tertile 41; schooling among women was the only variable that did not fulfill that assumption, when separate PRs were calculated for each energy expenditure tertile. The analyses were stratified by sex and it was performed using the Stata statistics package, version 11.0 (Stata Corp., College Station, USA).

 

Results

Of the 1,606 baseline participants in the cohort, complete information on all the variables considered in this study was available for 1,585 (98.7%), who were included in this analysis. Of those participants, 633 (39.9%) were men and 952 (60.1%), women.

Table 1 shows the distribution of the socio-demographic characteristics, health-related behavior, number of chronic diseases and use of health services among the study participants. Participants' mean age was 69.3 years (standard deviation - SD = 7.4), and they had predominantly little schooling (65.4% had completed less than four years' schooling). A spouse was reported by 49.3%. Prevalence of current tobacco use was 18.8% and excessive alcohol consumption was reported by 2%, while 74.2% had a medical diagnosis of at least one chronic disease and, in the previous 12 months, 80.4% had visited a doctor and 22.4% had been hospitalized on at least one occasion. Important differences were observed between the sexes: significantly more men reported a spouse, current tobacco use and excessive consumption of alcohol. Women reported more diagnoses of chronic diseases, medical appointments and hospitalizations.

The most frequent physical activity was unhurried walking (72.4%), followed by sweeping or mopping the floor (48.8%), digging to plant a garden or vegetable patch (32.7%), walking briskly (29.5%), window cleaning (13.9%), horse-riding at a gallop or trot (7.2%) and dancing (6.1%). Prevalences of all these activities were significantly higher in men then in women, except for housework (sweeping or mopping the floor, and cleaning windows were more frequent activities among women), and dancing (where there was no significant difference) (Table 2).

 

 

Among the activities above, "walking normally without hurrying" was responsible for the greatest percentage of energy expenditure in the population studied (median = 34.8%; p25-p75: 8.5%-71.1%), corresponding to around 1/3 of total expenditure. The corresponding values for men and women were, respectively, 43.7% (p25-p75: 21.4%-91.1%) and 27.3% (p25-p75: 3.1%-57.8%) (p < 0.001).

Table 3 shows physical activity energy expenditures by age and sex. Median total energy expenditure in the population studied was 975.0 METs.min/week (p25-p75: 292.5-1881.8). That value was significantly higher (p < 0.001) in men (1195.8; p25-p75: 397.5-2677.0) than in women (803.1; p25-p75: 237.2-1630.3), and the difference was observed consistently in the three age groups. By age, energy expenditures were observed to decline sharply in both sexes from the youngest to the oldest age group.

 

 

Overall prevalence of sedentarism was 31.2%. Prevalence was higher in women (34.4%) than in men (26.4%) (p = 0.001). Prevalence of sedentarism increased markedly with age (22.5%, 36.2% and 57.2% in the 60-69, 70-79 and 80 years or over age groups, respectively; p < 0.001).

Tables 4 and 5 show the results of multivariate analysis of the association between energy expenditure tertiles and socio-demographic characteristics, health-related behavior, health conditions and use of health services, by sex. Graded negative associations were observed between energy expenditure and age and number of hospitalizations in both sexes. Among men only, graded negative associations were observed between energy expenditure and current tobacco use, number of chronic diseases, and number of medical appointments in the previous 12 months. Among women, a positive association was found between energy expenditure and greater schooling.

 

Discussion

The results of this study show that median energy expenditure in the population studied (975.0 MET.min/week) was 2.2 times greater than the 450 MET.minutes/week stipulated as the defining cutoff for sedentarism 6,41. Relative to that cutoff point, prevalence of sedentarism among older adults in Bambuí was 31.2%.

A study using data from Risk and Protective Factors Surveillance System for Chronic Non-Communicable Diseases Through Telephone Interview (VIGITEL), conducted on a representative sample of adults residing in domiciles with fixed telephones in the capitals of 26 states and the Federal District, showed that the prevalence of leisure-time sedentarism (physical activities of light or moderate intensity for at least 30 minutes < 3 days a week) among older adults was 86.3% 21. Another study, using the baseline survey of the Bambuí cohort of older adults and using the same instrument, showed a prevalence of leisure-time sedentarism similar to that observed in the VIGITEL population (87.2%) 13. Brazilian studies of other elderly populations, using various instruments that do not estimate energy expenditure, have shown prevalence of leisure-time sedentarism between 70.9% and 77.7% 42,43 and prevalence of sedentarism in overall activities ranging from 26.1% to 69.1% 25,26,44.

The main physical activity of older adults in Bambui was unhurried walking, which corresponded to about 1/3 of total energy expenditure reported by that population. Other activities included housework (sweeping or mopping the floor and cleaning windows), particularly among women, in addition to digging to plant a garden or vegetable patch and horse-riding, reflecting specific characteristics to the area studied, where agriculture occupies an prominent place in the economy 35,36.

Our results show marked differences in physical activities between older men and women. Generally speaking, energy expenditure was greater among men than women in all age groups. When analyzed separately, greater prevalences were observed in men for all activities except housework. These results agree with those of other studies indicating that by and large, women are less active in most domains of physical activity, except in the domain of household activities 30,45.

Age was strongly associated with declining energy expenditure, even when adjusted for other significant factors, and that decline was observed consistently in both sexes. The gradual reduction of physical activities with age has been amply described of the literature 16,25,31, and our results agree with those observations. The number of chronic diseases showed a graded, inverse association with energy expenditure among men, reflecting the difficulty that people in worse health conditions have in practicing physical activities. The number of hospitalizations also showed an inverse association with energy expenditure among both men and women. Number of medical appointments was also associated positively associated with less energy expenditure among men. One plausible explanation for that association is the existence of incapacitating conditions that lead to greater recourse to health care.

The association between schooling and physical activity has been amply described in the literature; better levels of education area have been associated with lower prevalence of sedentarism 27,33,42. However, schooling showed a positive association with energy expenditure only among women. Tobacco use is another factor described in the literature as associated with reduced physical activities, including among older adults 27,33,42. This study found an inverse association between the condition of current smoker and energy expenditure among men, but not among women. This inconsistency is probably due to the low prevalence of tobacco use among older women.

Population-based epidemiologic studies estimating energy expenditure are rare, and older adults generally take part as one of several adult age groups 29,34. That is justified by the operational difficulties of applying such instruments in large populations. This study used an instrument containing twenty three questions on physical activities in different older age groups, in addition to questions on the frequency and duration of such activities; that was one advantage of this study. Other advantages were the large population base, the high survey response rate, the exhaustive training of the field teams, and the standardization of data collection 35,36. The main limitation was the cross-sectional nature of the study, from which it is impossible to establish time relationships among the variables or to examine how individual energy expenditure evolved over time. However, this design is appropriate for prevalence studies, as is the outcome here.

To summarize, the results of this study lead to the following conclusions: firstly, the broad predominance of walking among older adults' physical activities underlines the need to encourage this practice in health promotion policies for this population; secondly, the marked reduction in caloric expenditure with age raises the need for effective strategies to increase physical activities among the older elderly.

 

Contributors

J. R. O. Ramalho participated in the data analysis, interpretation of results, and drafting the paper. M. F. Lima-Costa collaborated in the study design, data analysis, and review of the manuscript. J. O. A. Firmo contributed to the study design, and critical review of the manuscript. S. V. Peixoto was responsible for supervising the data analysis, discussion of the results, and drafting and final review of the manuscript.

 

Acknowledgments

FINEP funded this study. M. F. Lima-Costa is a research productivity scholar of CNPq.

 

References

1. Guralnik JM, Kaplan GA. Predictors of healthy aging: prospective evidence from the Alameda County study. Am J Public Health 1989; 79:703-8.         [ Links ]

2. Leveille SG, Guaralnik J, Ferrucci L, Langois JA. Aging successfully until death in old age: opportunities for increasing active life expectancy. Am J Epidemiol 1999; 149:654-64.         [ Links ]

3. Haveman-Nies A, de Groot LC, van Staveren WA. Dietary quality, lifestyle factors and healthy ageing in Europe: the SENECA study. Age Ageing 2003; 32:427-34.         [ Links ]

4. Mancia G, De Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G, et al. 2007 guidelines for the management of arterial hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology (ESC). Eur Heart J 2007; 28:1462-536.         [ Links ]

5. Gando Y, Yamamoto K, Murakami H, Ohmori Y, Kawakami R, Sanada K, et al. Longer time spent in light physical activity is associated with reduced arterial stiffness in older adults. Hypertension 2010; 56:540-6.         [ Links ]

6. U.S. Department of Health and Human Services. Physical activity guidelines for Americans. Washington DC: U.S. Department of Health and Human Services; 2008.         [ Links ]

7. Guideline for the prevention of falls in older persons. American Geriatrics Society, British Geriatrics Society, and American Academy of Orthopaedic Surgeons Panel on Falls Prevention. J Am Geriatr Soc 2001; 49:664-72.         [ Links ]

8. Stewart AL, Verboncoeur CJ, McLellan BY, Gillis DE, Rush S, Mills KM, et al. Physical activity outcomes of CHAMPS II: a physical activity promotion program for older adults. J Gerontol A Biol Sci Med Sci 2001; 56:M465-70.         [ Links ]

9. Lagerros YT, Lagiou P. Assessment of physical activity and energy expenditure in epidemiological research of chronic diseases. Eur J Epidemiol 2007; 22:353-62.         [ Links ]

10. Lamonte MJ, Ainsworth BE. Quantifying energy expenditure and physical activity in the context of dose response. Med Sci Sports Exerc 2001; 33(6 Suppl):S370-8.         [ Links ]

11. Keim NL, Blanton CA, Kretsch MJ. America's obesity epidemic: measuring physical activity to promote an active lifestyle. J Am Diet Assoc 2004; 104:1398-409.         [ Links ]

12. Sternfeld B, Cauley J, Harlow S, Liu G, Lee M. Assessment of physical activity with a single global question in a large, multiethnic sample of midlife women. Am J Epidemiol 2000; 152:678-87.         [ Links ]

13. Lima-Costa MF, Barreto SM, Uchôa E, Firmo JO, Vidigal PG, Guerra HL. The Bambuí Health and Aging Study (BHAS): prevalence of risk factors and use of preventive health care services. Rev Panam Salud Pública 2001; 9:219-27.         [ Links ]

14. Santos JLF, Lebrão ML, Duarte YAO, Lima FD. Functional performance of the elderly in instrumental activities of daily living: an analysis in the municipality of São Paulo, Brazil. Cad Saúde Pública 2008; 24:879-86.         [ Links ]

15. Abu-Omar K, Rutten A. Relation of leisure time, occupational, domestic, and commuting physical activity to health indicators in Europe. Prev Med 2008; 47:319-23.         [ Links ]

16. Malta DC, Moura EC, Castro AM, Cruz DKA, Morais Neto OL, Monteiro CA. Padrão de atividade física em adultos brasileiros: resultados de um inquérito por entrevistas telefônicas, 2006. Epidemiol Serv Saúde 2009; 18:7-16.         [ Links ]

17. Macera CA, Ham SA, Jones DA, Kimsey CD, Ainsworth BE, Neff LJ. Limitations on the use of a single screening question to measure sedentary behavior. Am J Public Health 2001; 91:2010-2.         [ Links ]

18. Manini TM, Everhard JE, Patel KV, Schoeller DA, Cummings S, Mackey DC, et al. Activity energy expenditure and mobility limitation in older adults: differential associations by sex. Am J Epidemiol 2009; 169:1507-16.         [ Links ]

19. Slater CH, Green LW, Vernon SW, Keith VM. Problems in estimating the prevalence of physical activity from national surveys. Prev Med 1987; 16:107-18.         [ Links ]

20. Weiss TW, Slater CH, Green LW, Kennedy VC, Albright DL, Wun CC. The validity of single-item, self-assessment questions as measures of adult physical activity. J Clin Epidemiol 1990; 43:1123-9.         [ Links ]

21. Lima-Costa MF, Peixoto SWV, Malta DC, Moura ECM. Comportamentos em saúde entre idosos hipertensos, Brasil, 2006. Rev Saúde Pública 2009; 43:18-26.         [ Links ]

22. Singh GK, Yu SM, Siahpush M, Kogan MD. High levels of physical inactivity and sedentary behaviors among US immigrant children and adolescents. Arch Pediatr Adolesc Med 2008; 162:756-63.         [ Links ]

23. Ainsworth BE. How do I measure physical activity in my patients? Questionnaires and objective methods. Br J Sports Med 2009; 43:6-9.         [ Links ]

24. Franco OH, Laet C, Peeters A, Jonker J, Mackenbach J, Nusselder W. Effects of physical activity on life expectancy with cardiovascular disease. Arch Intern Med 2005; 165:2355-60.         [ Links ]

25. Hallal PC, Victora CG, Wells JCK, Lima RC. Physical inactivity: prevalence and associated variables in Brazilian adults. Med Sci Sports Exerc 2003; 35:1894-990.         [ Links ]

26. Siqueira FV, Facchini LA, Piccini RX, Tomasi E, Thumé E, Silveira DS. Atividade física em adultos e idosos residentes em áreas de abrangência de unidades básicas de saúde de municípios das regiões Sul e Nordeste do Brasil. Cad Saúde Pública 2008; 24:39-54.         [ Links ]

27. Florindo AA, Guimarães VV, Cesar CLG, Barros MBA, Alves MCGP, Goldbaum M. Epidemiology of leisure, transportation, occupational and household physical activity: prevalence and associated factors. J Phys Act Health 2009; 6:625-32.         [ Links ]

28. Simões EJ, Hallal PC, Pratt M, Ramos L, Munk M, Damascena W, et al. Effects of a community-based, professionally supervised intervention on physical activity levels among residents of Recife, Brazil. Am J Public Health 2009; 99:68-75.         [ Links ]

29. Jurakic D, Pedisic Z, Andrijasevic M. Physical activity of Croatian population: cross-sectional study using International Physical Activity Questionnaire. Croat Med J 2009; 50:165-73.         [ Links ]

30. Knuth AG, Bacchieri G, Victora CG, Hallal PC. Changes in physical activity among Brazilian adults over a 5-year period. J Epidemiol Community Health 2010; 64:591-5.         [ Links ]

31. Wilcox S, Irwin ML, Addy C, Ainsworth BE, Stolarczyk L, Whitt M, et al. Agreement between participant-rated and compendium-coded intensity of daily activities in a triethnic sample of women ages 40 years and older. Ann Behav Med 2001; 23:253-62.         [ Links ]

32. Varo JJ, Martínez-González MA, Irala-Estévez J, Kearney J, Gibney M, Martínez JA. Distribution and determinants of sedentary lifestyles in the European Union. Int J Epidemiol 2003; 32:138-46.         [ Links ]

33. Dong L, Block G, Mandel S. Activities contributing to total energy expenditure in the United States: results from the NHAPS Study. Int J Behav Nutr Phys Act 2004; 1:4.         [ Links ]

34. Yue AS, Woo J, Ip KW, Sum CM, Kwok T, Hui SS. Effect of age and gender on energy expenditure in common activities of daily living in a Chinese population. Disabil Rehabil 2007; 29:91-6.         [ Links ]

35. Lima-Costa MF, Firmo JOA, Uchôa E. Cohort profile: the Bambui (Brazil) Cohort Study of Aging. Int J Epidemiol 2010; [Epub ahead of print]         [ Links ].

36. Lima-Costa MF, Matos DL, Laurenti R, Mello-Jorge MH, Cesar CC. Time trends and predictors of mortality from ill-defined causes in old age: 9 year follow-up of the Bambuí cohort study (Brazil). Cad Saúde Pública 2010; 26:514-22.         [ Links ]

37. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000; 32(9 Suppl):S498-504.         [ Links ]

38. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 2007; 116:1081-93.         [ Links ]

39. Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, et al. Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995; 273:402-7.         [ Links ]

40. Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King AC, et al. Physical activity and public health in older adults. Recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007; 39:1435-45.         [ Links ]

41. Long JS, Freese J. Regression models for categorical dependent variables using Stata. College Station: Stata Press; 2006.         [ Links ]

42. Zaitune MPA, Barros MBA, César CLG, Carandina L, Goldbaum M. Fatores associados ao sedentarismo no lazer em idosos, Campinas, São Paulo, Brasil. Cad Saúde Pública 2007; 23:1329-38.         [ Links ]

43. Pitanga FJG, Lessa I. Prevalência e fatores associados ao sedentarismo no lazer em adultos. Cad Saúde Pública 2005; 21:870-7.         [ Links ]

44. Zaitune MPA, Barros MBA, César CLG, Carandina L, Goldbaum M, Alves MCGP. Fatores associados à prática de atividade física global e de lazer em idosos: Inquérito de Saúde no Estado de São Paulo (ISA-SP), Brasil. Cad Saúde Pública 2010; 26:1606-18.         [ Links ]

45. Bicalho PG, Hallal PC, Gazzinelli A, Knuth AG, Velásquez-Meléndez G. Atividade física e fatores associados em adultos de área rural em Minas Gerais, Brasil. Rev Saúde Pública 2010; 44:884-93.         [ Links ]

 

 

Correspondence:
J. R. O. Ramalho
Núcleo de Estudos em Saúde Pública e Envelhecimento
Fundação Oswaldo Cruz/Universidade Federal de Minas Gerais
Av. Augusto de Lima 1715, 6º andar
Belo Horizonte, MG 30190-002, Brasil
jucianyr@cpqrr.fiocruz.br

Submitted on 04/Feb/2011
Final version resubmitted on 12/Apr/2011
Approved on 07/May/2011