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. 2013 Mar 8;13(6):744–750. doi: 10.1080/17461391.2013.776638

Physical activity in the lifestyle of Czech university students: Meeting health recommendations

Dagmar Sigmundová 1,, František Chmelík 1, Erik Sigmund 1, Dana Feltlová 2, Karel Frömel 1
PMCID: PMC3869079  PMID: 24251753

Abstract

The decline of physical activity (PA) in adults as well as children and youth is a worldwide phenomenon. The aim of this study is to analyse the amount of PA in Czech university students’ daily lives. The research on university students was conducted as part of nationwide research on PA in the adult population of the Czech Republic. A total of 906 students at eight selected universities were asked to participate in this study. The response rate was 79.5%. We analysed data from 641 university students: 318 male [mean age 21.63 ± 1.73; mean Body Mass Index (BMI) 23.50 ± 1.91] and 323 female (mean age 21.08 ± 1.53; mean BMI 21.23 ± 2.20). The students wore Yamax SW-701 pedometers continuously for seven days. With respect to BMI, the recommendation of 10,000 steps per day on an average day was met by 76% of men and 68% of women of normal weight, 67% of male students who were overweight or obese and 85% of female students who were overweight or obese. Of all monitored days, in both females and males, the number of steps taken on Sunday was significantly lower (p < 0.0001) in comparison to other days of a week. No significant differences were found in the number of steps taken among students of normal weight, students who were overweight and students who were obese on any of the monitored days. The majority of Czech male university students are of normal weight. Only 9% of students meet the criterion of 10,000 steps every day. Approximately two-thirds of students meet the 10,000 steps daily criterion on four or more days per week. The lowest number of steps is taken on Sundays; this finding supports the need for intervention programmes to enhance PA on weekends.

Keywords: Number of steps, pedometer, BMI, days, weekend

Introduction

Many studies have addressed the worldwide decline in physical activity (PA) and the increase in the prevalence of overweight and obesity (Sigmundová, El Ansari, Sigmund, & Fromel, 2011; World Health Organization, 2010). PA decline was evident during young adults’ transition into early adulthood, with the steepest decline occurring at the time of entering a university (Kwan, Cairney, Faulkner, & Pullenayegum, 2012). In addition to the decline of PA with ageing, negative secular trends have also been found in PA behaviour in the adolescent population (Mak & Day, 2010; Nelson, Neumark-Stzainer, Hannan, Sirard, & Story, 2006; Sigmundová, El Ansari, Sigmund et al., 2011). One-third of active students in high school became insufficiently active upon transitioning to university life (Bray & Born, 2004). Overall, the transition into early adulthood marks a critical period of life in terms of health-related behaviours: decreases in PA and increases in alcohol consumption and smoking (Kwan et al., 2012). However, for adults who had early experience of PA during adolescence and young adulthood, decline of PA is less substantial (Barnekow-Bergkvist, Herberg, Janlert, & Jansoon, 1996). In other words, PA during early adulthood is strongly associated with PA later in adulthood (Nogueira et al., 2009). Moreover, daily PA in childhood had a significant health effect in adult men, substantially reducing the risk of becoming a regular smoker (Trudeau, Laurencelle, Tremblay, Rajic, & Shephard, 1999).

The effort to mitigate the negative health trends has led researchers to search for new ways of encouraging healthy lifestyles, such as creating a physical-activity-friendly environment or other interventions that can increase PA in the population (Biddle, Brehm, Verheijden, & Hopman-Rock, 2011; Roesch, Norman, Villodas, Sallis, & Patrick, 2010; Sigmundová, El Ansari, & Sigmund, 2011). To contextualise individuals’ adaptations to their environment, relevant days of the week should be considered. Previous research has shown that PA patterns on weekends differ from weekday patterns and are related to sex and age (Buchowski, Acra, Ajchrzak, Sun, & Chen, 2004).

Generally, people with higher levels of education engage in more PA than people with lower education levels (Droomers, Schrijvers, & Mackenbach, 2001; Steffen et al., 2006). This phenomenon has not yet been confirmed for the Czech Republic (Sigmundová, El Ansari, & Sigmund, 2011), but other studies have shown that educated people (especially due to their greater likelihood of sedentary employment and little leisure PA) may engage in less PA than less educated people (Vašíčková, Roberson, & Frömel, 2012).

The post-communist block countries (e.g. the Czech Republic) appear to have a tendency to replicate the ‘negative’ health trends that have been witnessed in economically developed Western countries (Knai, Suhrcke, & Lobstein, 2007). Indeed, Central and Eastern European countries could learn from such ‘negative’ Western European and global experiences. Uncovering the levels and patterns of PA in Czech university students could help elucidate current health trends.

The aim of the study is to analyse the amount of PA undertaken by Czech university students in their daily lives. Specific aims are as follows:

• to analyse the amount of PA (number of steps) per day for men and women separately;

• to analyse the amount of PA (number of steps) overall per week, on working days and on weekends, for men and women;

• to describe the proportion of students by their Body Mass Index (BMI) categories (based on self-reported height and weight) and the proportion of students meeting a generally accepted health criterion of PA for adults – achieving 10,000 steps per day (Tudor-Locke, Hatano, Pangrazi, & Kang, 2008).

Methods

Ethics

The current study was undertaken in the Czech Republic after approval by the Institutional Research Ethics Committee at Palacky University. Participation was voluntary; participants received no incentives. Young adults were provided with information about the aims, objectives and methods of the study before the start of PA monitoring. Data were anonymous and confidential, and data protection was observed at all times. Each participant gave informed consent for inclusion in the study.

Participants

The study of university students was a part of nationwide research on PA in adults in the Czech Republic (Research grant of Ministry of Education, Youth and Sports of the Czech Republic ‘Physical activity and inactivity of inhabitants of the Czech Republic in the context of behavioural changes’ reg. No. 6198959221). A total of eight universities from different regional towns (Sigmundová, El Ansari, & Sigmund, 2011) joined the nationwide research effort and participated in the study between the years 2008 and 2010. Each selected town represented a delineated region within the Czech Republic (Brno – Southern Moravia; Olomouc – Central Moravia; Ostrava – Northern Moravia; Ĉeské Budějovice – Southern Bohemia; Hradec Králové and Liberec – Eastern Bohemia; Plzeň – Western Bohemia; and Ústí nad Labem – Northern Bohemia). Afterwards, study years or entire study groups of students were randomly selected, regardless of their study focus (students were either technically or teaching oriented; some were physical education students, and some were not). A total of 906 students were chosen from the selected schools, and 720 of those students actively participated in the research (response rate of 79.5%). Responses with missing and incomplete data (weight, height, age and sex) were excluded from the analysis. In accordance with the study by Tudor-Locke, Giles-Corti, Knuiman, and McCormack (2008), we did not include extreme values (number of steps more than 30,000 per day or less than 1000 in a particular day). In total, 79 participants were excluded from the analysis. Finally, we analysed data from 641 university students – 318 male (mean ± SD: age 21.63 ± 1.73, BMI 23.50±1.91) and 323 female (mean ± SD: age 21.08 ± 1.53, BMI 21.23 ± 2.20). In accordance with the WHO (Branca, Nikogosian, & Lobstein, 2007), we defined overweight as a BMI greater than or equal to 25 kg/m2 and obesity as a BMI ≥ 30 kg/m2. Participants with BMI < 25 kg/m2 are considered to be normal weight.

Assessment of PA and inactivity

Number of steps was determined using the pedometer Yamax SW-701. The Yamax SW-701 pedometer has been tested (in terms of number of steps) against direct observation (actual steps were tallied with a hand counter) at different speeds. In comparison to a hand counter, the Yamax SW-701 did not significantly overestimate or underestimate the number of steps at any speed. Of the ten types of pedometers, the Yamax SW-701 was the most accurate at predicting steps, distance and gross kilocalories for walking (Crouter, Schneider, Karabulut, & Bassett, 2003). This pedometer is suitable for applied PA research (Schneider, Crouter, & Bassett, 2004). In general, pedometers are more accurate for assessing steps than for assessing distance or kilocalories (Crouter et al., 2003).

University students wore Yamax SW-701 pedometers continuously for seven days (at least 10 hours per day), excluding sleeping, hygiene and bathing times. The week-long PA monitoring was based on continuous, all-day monitoring using the pedometer and a personal log (to record the data from the pedometer and to provide more detailed information about the type and duration of PA and physical inactivity). Students recorded actual time and number of steps measured by the pedometer in their personal log every morning and evening. During the day, they could also record the time and the actual number of steps as they entered and left school and at the beginning and end of a session of organised or unorganised PA. In the evening, students recorded the duration of PA (with a minimum duration of 10 minutes) performed during the day (such as walking, running, dancing, football, volleyball, basketball, gardening, housekeeping, etc.). Students also recorded information about the duration of sedentary activities, such as watching TV, working on a computer, studying, reading, sitting during transportation, sitting at school, etc. Participants were asked to wear the pedometer on either the left or the right side of the hip, as previous research showed that pedometers did not significantly differ in their estimates when used on either side of the body (Crouter et al., 2003). Students were informed to put the pedometer on in the morning, remove it before sleeping and take it off only during water-based activities (the device is not waterproof).

Statistical analysis

Statistical analysis was undertaken using STATISTICA v. 8 and SPSS v. 18. For the pedometer data, analysis of variance (ANOVA) test with related Fisher's least significant difference (LSD) post-hoc test and coefficient of effect size d = (M1M2)/SDpooled (Cortina & Nouri, 2000) computed any significant differences between the number of steps achieved on working days and on the weekend and between number of steps (respective self-reported PA and inactivity) of males and females and between cohorts. For the self-reported data, to assess any significant differences in self-reported PA and inactivity, we used the non-parametric two-tailed Kruskal-Wallis test and the relevant η2 coefficient (from the effect size coefficients). In line with other studies (Morse, 1999), η2 = 0.01 was considered to be low effect, η2 = 0.06 medium effect and η2 = 0.14 large effect.

Results

Average number of steps per week – analysis by day of week

ANOVA for repeated measures showed differences in the number of steps between individual days of monitoring (F(6, 641) = 48.44; p < 0.001). Fisher LSD post-hoc test did not show differences between Tuesdays, Wednesdays and Fridays – on these days, men reported equal numbers of steps. Men take a lower and significantly different (p < 0.001) number of steps on Sundays in comparison to all other days (Figure 1). For women, no significant difference was found between the number of steps taken on Tuesday, Wednesday, Thursday and Friday, but on Sundays they were found to take a lower and significantly different (p < 0.001) number of steps compared to the other days.

Figure 1.

Figure 1.

Number of steps per day by gender.

Of all monitored days, Sunday showed – both in males and females – the lowest, significantly different number of steps (p < 0.0001) in comparison to the number of steps taken on other days. The effect of weight according to BMI (normal, overweight and obese) on the number of steps taken was not significant, and according to post-hoc LSD testing, no significant differences were found between steps taken by students with normal weight, overweight students and those with obesity on any monitored days.

Differences in PA between weekdays and weekends

Independent of sex, we find differences between the PA of university students on working days and on weekends (F(1, 641) = 193.26; p < 0.001; d = 0.60). Figure 2 shows that both males and females achieved a lower, significantly different number of steps on weekends than on working days.

Figure 2.

Figure 2.

Average number of steps per working days, weekend and week, by gender.

Proportion of students by BMI and by meeting health recommendations for number of achieved daily steps

In males, 83% reported normal weight (BMI < 25 kg/m2), 16% were overweight and 1% were obese (BMI ≥ 30 kg/m2). In females, 95% reported normal weight, 4% were overweight and 1% were reportedly obese. The recommendation of 10,000 steps per day (for health-enhancing daily number of steps achieved) was met, on an average day, by 74% of males and 69% of females in our sample. The recommendation was met by 67% of overweight or obese male students and 85% of overweight or obese female students.

A detailed analysis of meeting health-enhancing daily number of steps showed that, on average, both men and women meet the criterion on four days out of the week. Approximately 9% of students, regardless of sex, meet the health criterion of 10,000 steps every day. Only 67% of men and 64% of women meet this criterion on four or more days per week. Figure 3 shows that 2.5% of women and 3.3% of men do not meet the criterion of 10,000 steps a day on any monitored day.

Figure 3.

Figure 3.

Proportion meeting health recommendations (10,000 steps per day) in university students by gender and by number of days of meeting recommendation during the week.

Discussion

In terms of the first objective, the analysis of PA on individual days showed that Sunday is the most critical day of a week in terms of the number of steps taken. Our monitored university students (both male and female) take the lowest number of steps on weekends. Sunday is the most critical day regarding the amount of PA performed by adults, as has been confirmed repeatedly in literature (Tudor-Locke et al., 2005; Vašíčková et al., 2012). Effects of overweight or obesity on the number of steps taken on Sunday were not observed in our sample, and our results thus do not comply with findings that argue that Sunday is a particularly critical day for overweight or obese people (Clemes, Hamilton, & Lindley, 2008; de Looze et al., 2012).

The current study shows different numbers of steps on particular days of a week. In terms of the number of steps taken, Tuesday, Wednesday and Friday are equal for male and female students. Differences on other days could be influenced by the diverse study programmes during the semesters and at different universities. Numbers of steps on particular weekdays may differ due to varied campus and university settings (class rooms, libraries, canteens, shops, dormitories and sports gymnasiums) and according to the classes and study duties found in the daily schedule (Yan, Sigmund, Sigmundová, & Yan, 2007).

Regarding objective two, the present study found differences in PA (number of steps) between working days and weekends. Similar to our research, other studies have reported differences in PA patterns on weekdays and weekends (Buchowski et al., 2004; Lake, Townshend, Alvanides, Stamp, & Adamson, 2009; Sigmundová, El Ansari, Sigmund et al., 2011; Young, Jerome, Chen, Laferriere, & Vollmer, 2009). Both female students and male students show significantly lower PA on weekends than on working days. A similar pattern of weekly PA in adults has been confirmed by international studies (Behrens & Dinger, 2007; Tudor-Locke et al., 2004). Understanding the differences in PA patterns (for example, during weekdays and weekends) can aid in the development of suitable intervention programmes (Lake et al., 2009; Young et al., 2009).

We used the value of 10,000 steps as the criterion for meeting health recommendations as this is accepted for the general adult population (Tudor-Locke, Hatano et al., 2008). In this study, the criterion of 10,000 steps is met daily by only approximately 9% of male students and 9% of female students. With respect to WHO Global strategy (World Health Organization, 2006), various types and amounts of PA on most days of a week (≥ 4 days) reduce the risk of cardiovascular disease, diabetes and cancer (World Health Organization, 2010). The American Heart Association recommends that all adults accumulate 30 minutes of PA on most days of a week. Additional benefits will likely be derived if activity levels exceed this minimum recommendation. At least 60 minutes of PA on most days of a week is recommended for adults who are attempting to lose weight (Lichtenstein et al., 2006). Using the adult cadence of 100 steps/minute (Tudor-Locke et al., 2011), this recommendation could be fulfilled by the achievement of 10,000 steps on four or more days of a week.

The recommendations were met on four or more days per week by 67% of men and 64% of women. Czech university students are more physically active than the adult population of regional towns, in which 51% of inhabitants meet the health recommendations (Sigmundová, El Ansari, & Sigmund, 2011). Previous research studying university students from 23 countries showed that, of students from Central and Eastern Europe, only 32% of men and 18% of women met the recommended frequency of leisure-time PA (Haase, Steptoe, Sallis, & Wardle, 2004). Better results were accomplished by university students from Australia, where 47% of males and 51% of females from a total of 103 students achieved 10,000 steps per working day (Villanueva, Giles-Corti, & McCormack, 2008). A Canadian study found students who reported engaging in moderate and strenuous PA for a total of 30 minutes (all at once or in 10–15-minute blocks) at least five days per week. A total of 51% of these students were categorised as active (Irwin, 2007). Similarly, results from a Spanish study indicated that 45% of university students are not active enough, especially females (Hoyos et al., 2011). The average daily values of number of steps taken by participants in this study are higher than those found in a cross-sectional study of the Czech population, where men reached an average value of 11,200 steps/day and women 10,612 steps/day (Sigmundová, Zacpal, & Sigmund, 2010). This result shows that in some cases university students have a higher level of PA than that of the general population.

In relation to the third objective, in this sample of university students from the Czech Republic, 16% of male students and 4% of female students were overweight, and only 1 % of male students and 1 % of female students were obese. The prevalence of overweight and obesity in our sample is low in comparison to the results of a study of the population of Czech university students, in which 14% of students were overweight or obese (Vašíčková, Frömel, & Nykodým, 2008). These values may be influenced by the fact that overweight or obese students are less likely to participate in similar studies. A national study of the Czech adult population between the ages of 18–24 years living in regional towns reported the prevalence of overweight and obesity (based on self-reported height and weight) in 4% of women and 26% of men (Sigmundová, El Ansari, & Sigmund, 2011).

Limitations

Despite a large amount of analysed data (641 students × 7 days), this study has limitations. The analysis includes students from faculties of sports, which may partly influence the final results regarding levels of PA. The use of pedometers lacks a blinded display, and participants also registered the number of daily steps into the record charts. These facts suggest that pedometers could be ‘semi-objective’ (Sigmundová, El Ansari, Sigmund et al., 2011). Step counts could be higher in our study due to the use of unsealed pedometers and resulting reactivity. Reactivity to unsealed pedometers, causing increased steps, can last for a period of one week (Clemes & Deans, 2012).

Only a small number of overweight or obese people joined the research; most respondents were of normal weight. Compared to the population of Czech university students (Vašíčková et al., 2008), our sample may have been slightly biased; thus, caution should be exercised when generalising the results. The body composition of the participants was not monitored, and this study did not include the influence of environment and background of colleges and universities, which can influence PA behaviour in students.

Conclusions

The day on which the lowest number of steps was taken was Sunday. On an average day (averaged over seven days), 69% of female students and 74% of male students met the criterion. Only 9% of students met the criterion on a daily basis. Approximately two-thirds of students met the criterion of 10,000 steps on four or more days a week. Lower PA was recorded on the weekend than on working days, both in male and female students. The majority of male Czech university students (83%) show normal weight, as do female students, at 95%. Only 1% of students are obese. Further research should focus on the possibility of enhancing PA, especially on weekends, and the performance of recommended PA on a daily basis. Positive findings in the level of BMI and PA show a reasonable basis for health promotion among university students. Further research should address the relationship between a physically active lifestyle and students’ transitions to adulthood in the area of Central and Eastern Europe.

Acknowledgements

This study was supported by a research grant from the Ministry of Education, Youth and Sports of the Czech Republic [6198959221]: ‘Physical activity and inactivity of inhabitants of the Czech Republic in the context of behavioral changes'. This paper was supported by the ECOP project, “Strengthening scientific potential of the research teams in promoting physical activity at Palacky University,” reg. No. CZ.1.07/2.3.00/20.0171.

References

  1. Barnekow-Bergkvist M., Hedberg G., Janlert U., Jansson E. Physical activity pattern in men and women at the ages of 16 and 34 and development of physical activity from adolescence to adulthood. Scandinavian Journal of Medicine & Science in Sports. 1996;6:359–370. doi: 10.1111/j.1600-0838.1996.tb00108.x. doi:10.1111/j.1600-0838.1996.tb00108.x. [DOI] [PubMed] [Google Scholar]
  2. Behrens T. K., Dinger M. K. Motion sensor reactivity in physically active young adults. Research Quarterly for Exercise and Sport. 2007;78(2):1–8. doi: 10.1080/02701367.2007.10762229. doi:10.5641/193250307X13082490460139. [DOI] [PubMed] [Google Scholar]
  3. Biddle S. J. H., Brehm W., Verheijden M., Hopman-Rock M. Population physical activity behaviour change: A review for the European College of Sport Science. European Journal of Sport Science. 2011;12(4):367–383. doi:10.1080/17461391.2011.635700. [Google Scholar]
  4. Branca F., Nikogosian H., Lobstein T., editors. The challenge of obesity in the WHO European Region and the strategies for response: Summary. Copenhagen: WHO Regional Office for Europe; 2007. [Google Scholar]
  5. Bray S. R., Born H. A. Transition to university and vigorous physical activity: Implications for health and psychological well-being. Journal of American College Health. 2004;52(4):181–188. doi: 10.3200/JACH.52.4.181-188. doi:10.3200/JACH.52.4.181-188. [DOI] [PubMed] [Google Scholar]
  6. Buchowski M. S., Acra S., Ajchrzak K. M., Sun M., Chen K. Y. Patterns of physical activity in free-living adults in the Southern United States. European Journal of Clinical Nutrition. 2004;58(5):828–837. doi: 10.1038/sj.ejcn.1601928. doi:10.1038/sj.ejcn.1601928. [DOI] [PubMed] [Google Scholar]
  7. Clemes S. A., Deans N. K. Presence and duration of reactivity to pedometers in adults. Medicine & Science in Sports & Exercise. 2012;44(6):1097–1101. doi: 10.1249/MSS.0b013e318242a377. doi:10.1249/MSS.0b013e318242a377. [DOI] [PubMed] [Google Scholar]
  8. Clemes S. A., Hamilton S. L., Lindley M. R. Four-week pedometer-determined activity patterns in normal-weight, overweight and obese adults. Preventive Medicine. 2008;46(4):325–330. doi: 10.1016/j.ypmed.2007.11.013. doi:10.1016/j.ypmed.2007.11.013. [DOI] [PubMed] [Google Scholar]
  9. Cortina J. M., Nouri H. Effect size for ANOVA design. Thousand Oaks, CA: Sage; 2000. [Google Scholar]
  10. Crouter S. E., Schneider P. L., Karabulut M., Bassett D. R. Validity of 10 electronic pedometers for measuring steps, distance, and energy cost. Medicine & Science in Sports & Exercise. 2003;35(8):1455–1460. doi: 10.1249/01.MSS.0000078932.61440.A2. doi:10.1249/01.MSS.0000078932.61440.A2. [DOI] [PubMed] [Google Scholar]
  11. de Looze M., Pickett W., Raaijmakers Q., Kuntsche E., Hublet A., Nic Gabhainn S., ter Bogt T. Early risk behaviors and adolescent injury in 25 European and North American countries. The Journal of Early Adolescence. 2012;32(1):104–125. doi:10.1177/0272431611414062. [Google Scholar]
  12. Droomers M., Schrijvers C. T. M., Mackenbach J. P. Educational level and decreases in leisure time physical activity: Predictors from the longitudinal GLOBE study. Journal of Epidemiology and Community Health. 2001;55(8):562–568. doi: 10.1136/jech.55.8.562. doi:10. 1136/jech.55.8.562. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Haase A., Steptoe A., Sallis J. F., Wardle J. Leisure-time physical activity in university students from 23 countries: Associations with health beliefs, risk awareness, and national economic development. Preventive Medicine. 2004;39(1):182–190. doi: 10.1016/j.ypmed.2004.01.028. doi:10.1016/j.ypmed.2004.01.028. [DOI] [PubMed] [Google Scholar]
  14. Hoyos I., Irazusta A., Gravina L., Gil S. M., Gil J., Irazusta J. Reduced cardiovascular risk is associated with aerobic fitness in university students. European Journal of Sport Science. 2011;11(2):87–94. doi:10.1080/17461391.2010.487116. [Google Scholar]
  15. Irwin J. D. The prevalence of physical activity maintenance in a sample of university students: A longitudinal study. Journal of American College Health. 2007;56(1):37–41. doi: 10.3200/JACH.56.1.37-42. doi:10.3200/JACH.56.1.37-42. [DOI] [PubMed] [Google Scholar]
  16. Knai C., Suhrcke M., Lobstein T. Obesity in Eastern Europe: An overview of its health and economic implications. Economics & Human Biology. 2007;5(3):392–408. doi: 10.1016/j.ehb.2007.08.002. doi:10.1016/j.ehb.2007.08.002. [DOI] [PubMed] [Google Scholar]
  17. Kwan M. Y., Cairney J., Faulkner G. E., Pullenayegum E. E. Physical activity and other health-risk behaviors during the transition into early adulthood: A longitudinal cohort study. American Journal of Preventive Medicine. 2012;42(1):14–20. doi: 10.1016/j.amepre.2011.08.026. doi:10.1016/j.amepre.2011.08.026. [DOI] [PubMed] [Google Scholar]
  18. Lake A. A., Townshend T., Alvanides S., Stamp E., Adamson A. J. Diet, physical activity, sedentary behaviour and perceptions of the environment in young adults. Journal of Human Nutrition and Dietetics. 2009;22(5):444–454. doi: 10.1111/j.1365-277X.2009.00982.x. doi:10.1111/j.l365-277X.2009.00982.x. [DOI] [PubMed] [Google Scholar]
  19. Lichtenstein A. H., Appel L. J., Brands M., Carnethon M., Daniels S., Franch H. A., Wylie-Rosett J. Diet and lifestyle recommendations revision 2006: A scientific statement from the American Heart Association Nutrition Committee. Circulation. 2006;114(1):82–96. doi: 10.1161/CIRCULATIONAHA.106.176158. doi:10.1161/circulationaha.106.176158. [DOI] [PubMed] [Google Scholar]
  20. Mak K.-K., Day J. R. Secular trends of sports participation, sedentary activity and physical self-perceptions in Hong Kong adolescents, 1995–2000. Acta Pædiatrica. 2010;99(11):1731–1734. doi: 10.1111/j.1651-2227.2010.01928.x. doi:10.1111/j.1651-2227.2010.01928.x. [DOI] [PubMed] [Google Scholar]
  21. Morse D. T. MINSIZE2: A computer program for determining effect size and minimum sample size for statistical significance for univariate, multivariate, and nonparametric tests. Educational and Psychological Measurement. 1999;59(3):518–531. doi:10.1177/00131649921969901. [Google Scholar]
  22. Nelson M. C., Neumark-Stzainer D., Hannan P. J., Sirard J. R., Story M. Longitudinal and secular trends in physical activity and sedentary behavior during adolescence. Pediatrics. 2006;118(6):e1627–e1634. doi: 10.1542/peds.2006-0926. doi:10.1542/peds.2006-0926. [DOI] [PubMed] [Google Scholar]
  23. Nogueira D., Faerstein E., Rugani I., Chor D., Lopes C. S., Werneck G. L. Does leisure-time physical activity in early adulthood predict later physical activity? Pro-Saude Study. Revista Brasileira de Epidemiologia. 2009;12(1):3–9. doi:10.1590/S1415-790X2009000100001. [Google Scholar]
  24. Roesch S. C., Norman G. J., Villodas F., Sallis J. F., Patrick K. Intervention-mediated effects for adult physical activity: A latent growth curve analysis. Social Science & Medicine. 2010;71(3):494–501. doi: 10.1016/j.socscimed.2010.04.032. doi:10.1016/j.socscimed.2010.04.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Schneider P. L., Crouter S. E., Bassett D. R. Pedometer measures of free-living physical activity: Comparison of 13 models. Medicine & Science in Sports & Exercise. 2004;36(2):331–335. doi: 10.1249/01.MSS.0000113486.60548.E9. doi:10.1249/01.MSS.0000113486.60548.E9. [DOI] [PubMed] [Google Scholar]
  26. Sigmundová D., El Ansari W., Sigmund E. Neighbourhood environment correlates of physical activity: A study of eight Czech regional towns. International Journal of Environmental Research and Public Health. 2011;8(2):341–357. doi: 10.3390/ijerph8020341. doi:10.3390/ijerph8020341. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Sigmundová D., El Ansari W., Sigmund E., Frömel K. Secular trends: A ten-year comparison of the amount and type of physical activity and inactivity of random samples of adolescents in the Czech Republic. BMC Public Health. 2011;11(1):731. doi: 10.1186/1471-2458-11-731. doi:10.1177/1256336X05052892. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Sigmundová D., Zacpal J., Sigmund E. The level of influence of organised physical activity on meeting the healthy criterion of 10,000 steps daily: Application of regression and formal concept analysis. Acta Universitatis Palackianae Olomucensis Gymnica. 2010;40(4):15–24. Retrieved from http://gymnica.upol.cz/index.php/gymnica/article/view/220. [Google Scholar]
  29. Steffen L. M., Arnett D. K., Blackburn H., Shah G., Armstrong C., Luepker R. V., Jacobs D. R. J. Population trends in leisure-time physical activity: Minnesota Heart Survey, 1980–2000. Medicine & Science in Sports & Exercise. 2006;38(10):1716–1723. doi: 10.1249/01.mss.0000227407.83851.ba. doi:10.1249/01.mss.0000227407.83851.ba. [DOI] [PubMed] [Google Scholar]
  30. Trudeau F., Laurencelle L., Tremblay J., Rajic M., Shephard R. J. Daily primary school physical education: Effects on physical activity during adult life. Medicine and Science in Sports and Exercise. 1999;31(1):111–117. doi: 10.1097/00005768-199901000-00018. doi:10.1097/00005768-199901000-00018. [DOI] [PubMed] [Google Scholar]
  31. Tudor-Locke C., Bassett D. R., Swartz A. M., Strath S. J., Parr B. B., Reis J. P., Ainsworth B. E. A preliminary study of one year of pedometer self-monitoring. Annals of Behavioral Medicine. 2004;28(3):158–162. doi: 10.1207/s15324796abm2803_3. doi:10.1207/sl5324796abm2803_3. [DOI] [PubMed] [Google Scholar]
  32. Tudor-Locke C., Burkett L., Reis J. P., Ainsworth B. E., Macera C. A., Wilson D. K. How many days of pedometer monitoring predict weekly physical activity in adults? Preventive Medicine. 2005;40(3):293–298. doi: 10.1016/j.ypmed.2004.06.003. doi:10.1016/j.ypmed.2004.06.003. [DOI] [PubMed] [Google Scholar]
  33. Tudor-Locke C., Craig C. L., Aoyagi Y., Bell R. C., Croteau K. A., De Bourdeaudhuij I., Blair S. N. How many steps/day are enough? For older adults and special populations. International Journal of Behavioral Nutrition and Physical Activity. 2011;8(1):80. doi: 10.1186/1479-5868-8-80. doi:10.1186/1479-5868-8-80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Tudor-Locke C., Giles-Corti B., Knuiman M., McCormack G. Tracking of pedometer-determined physical activity in adults who relocate: Results from RESIDE. International Journal of Behavioral Nutrition and Physical Activity. 2008;5(1):39. doi: 10.1186/1479-5868-5-39. doi:10.1186/1479-5868-5-39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Tudor-Locke C., Hatano Y., Pangrazi R. P., Kang M. Revisiting “How many steps are enough?”. Medicine & Science in Sports & Exercise. 2008;40(7 Suppl. 1):S537–s543. doi: 10.1249/MSS.0b013e31817c7133. [DOI] [PubMed] [Google Scholar]
  36. Vašíčková J., Frömel K., Nykodým J. Physical activity recommendation and its association with demographic variables in Czech university students. Acta Universitatis Palackianae Olomucensis Gymnica. 2008;38(2):75–84. Retrieved from http://gymnica.upol.cz/index.php/gymnica/article/view/18. [Google Scholar]
  37. Vašíčková J., Roberson D., Frömel K. The education level and socio-demographic determinants of physical activity in Czech adults. Human Movement. 2012;13(1):54–64. doi:10.2478/V10038-012-0005-6. [Google Scholar]
  38. Villanueva K., Giles-Corti B., McCormack G. Achieving 10,000 steps: A comparison of public transport users and drivers in a university setting. Preventive Medicine. 2008;47(3):338–341. doi: 10.1016/j.ypmed.2008.03.005. doi:10.1016/j.ypmed.2008.03.005. [DOI] [PubMed] [Google Scholar]
  39. World Health Organization. Global strategy on diet, physical activity and health. Geneva: WHO Press; 2006. [Google Scholar]
  40. World Health Organisation. Global recommendations on physical activity for health. Geneva: WHO Press; 2010. [PubMed] [Google Scholar]
  41. Yan Z., Sigmund E., Sigmundová D., Yan L. Comparison of physical activity between Olomouc and Beijing university students using an International Physical Activity Questionnaire. Acta Universitatis Palackianae Olomucensis. Gymnica. 2007;37(4):107–114. [Google Scholar]
  42. Young R. D., Jerome J. G., Chen C., Laferriere D., Vollmer M. W. Patterns of physical activity among overweight and obese adults. Preventing Chronic Disease. 2009;6(3):A90. Retrieved from http://www.cdc.gov/pcd/issues/2009/jul/08_0186.htm. [PMC free article] [PubMed] [Google Scholar]

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