Sedentarism in Recreational Marathon Runners

Introduction

Sedentary behavior (SB) has been a major health concern in the industrialized societies.^1,2 USA adults reported 9.5 h·day⁻¹ of sedentary time mostly accumulated in the leisure (mainly watching television/videos or engaged in Internet/computer use) and work life domains.² SB (defined as sitting more than 4.5 h·day⁻¹) increased in the European Union from 49.3% in 2002 to 53.4% in 2017.¹ This behavior has been associated with an increased risk for several non-communicable diseases such as and add some examples³ and health-related quality of life.⁴ In agreement with the significance of this behavior, research on this topic has grown exponentially in the last decade.⁵

Paradoxically, despite the increase of the prevalence of SB during the last years, an increase of participation in endurance running events such as marathon was shown in studies on New York City Marathon 1970–2017,⁶ Boston Marathon 1972–2017⁷ and Berlin Marathon 1974–2019.⁸ There was debate whether high levels of physical activity (PA; such in the case of recreational marathon runners) could fully counteract the harms of SB.⁹ For instance, SB was associated with higher levels of adiposity, independent of moderate-to-vigorous PA; however, it was unclear whether this independent relationship still existed in highly trained athletes.⁹

Although an association of high SB with low cardiorespiratory and muscular fitness was observed in the general population,¹⁰ little information existed about this relationship in marathon runners. What was known in marathon runners was that SB was not associated with training duration.¹¹ A review of 13 studies on SB and PA in athletes reported that, compared to the general population, athletes spent more time in SB and moderate-to-vigorous PA, and less time in light intensity PA.¹² Exel et al¹³ studied SB and PA in master amateur runners and footballers and observed alarming times in bouts of 30-min of SB on weekdays. They highlighted the need to consider the excessive amounts of SB in master athletes that cannot be masquerade by adequate PA profiles.

In this context, the knowledge about the relationship of SB with anthropometric and physiological characteristics in marathon runners would provide practical information about the potential role of endurance exercise to offset the negative effects of SB. Therefore, the present study aimed to examine (a) the prevalence and trends of SB, ie, sex and age-related differences, differences between workdays and non-workdays; and (b) the relationship of SD with anthropometric, physiological and training characteristics in recreational marathon runners. We hypothesized that SB would be less prevalent in recreational marathon runners than in the general population, would differ between weekdays and weekends, and would correlate with worse performance characteristics.

Methods

Study Design and Participants

This is a cross-sectional study, where 151 finishers [women, n = 29; men, n = 122; age 43.1 (8.7) years, mean (standard deviation)] in the Athens marathon 2017 performed a series of anthropometric and physiological tests and completed a series of questionnaires including the Multi-context sitting time questionnaire (MSTQ).¹¹ Data from the participants’ measurements have already been published;^14–16 however, MSTQ was not previously reported. All participants were recruited – mostly from the area of Athens – through public calls using social media and provided written informed consent before the testing session. Inclusion criteria were the successful participation in the Athens marathon in 2017 and the intention to compete in 2018. The study was conducted in accordance with the ethical principles derived from the Declaration of Helsinki about research in humans and was approved by the local review board (Exercise Physiology Laboratory, Nikaia, Greece; EPL 2017/3).

Protocols and Equipment

Considering the evaluation of SB, the parameters evaluated by MSTQ included sittitng while (a) working, (b) watching TV, (c) watching PC (non-working), (d) transportation and (e) socializing, in addition to sleep duration, separately for weekdays and weekends. Then, total SB was calculated as the sum of a, b, c, d and e. Whitfield et al¹⁷ developed and tested the psychometric characteristics of the MSTQ. They supported that this tool has several improvements compared to previous tools and used it on marathon and half-marathon runners.¹¹ Recently, it was used on weight-loss maintainers,¹⁸ college students,¹⁹ minority group²⁰ and the general population.²¹ The protocols and equipment of the measurements of the anthropometric and physiological characteristics can be found elsewhere in details.^14–16 Briefly, these measurements included the chronological age, height, weight, body mass index (BMI), body fat percentage using the sum of 10 skinfolds (BF), number of finished marathon races, marathon race record, training days and distance per week, maximal oxygen uptake (VO₂max) from a graded exercise test on a treadmill, sit-and-reach test (SAR), squat jump (SJ), countermovement jump (CMJ) and maximal power of a force velocity test on a cycle ergometer.

Statistical and Data Analysis

Two statistical packages, IBM SPSS v.29.0 (SPSS, Chicago, IL, USA) and GraphPad Prism v. 7.05 (GraphPad Software, San Diego, CA, USA), were used for statistical analyses. Descriptive statistics of SB were presented as medians and interquartile ranges (IQR).^11,17–21 A related-sample Wilcoxon Signed Rank test compared SB between weekday and weekend. An independent-sample Mann–Whitney U-test examined differences in SB between women and men. A cut-off of 9.0 h total SB was used to group participants into non-sedentary and sedentary, and the chi-square test examined their distribution by sex. Descriptive characteristics of the anthropometric and physiological characteristics were presented as means and standard deviations.^14–16 Spearman correlation coefficient (rho) examined the relationship of SB (non-parametric variable) with anthropometric and physiological characteristics (parametric variables) by sex. The magnitude of the correlations was evaluated as trivial (rho < 0.10), small (0.10 ≤ rho < 0.30), moderate (0.30 ≤ rho <0.50), large (0.50 ≤ rho< 0.70), very large (0.70 ≤ rho < 0.90) and almost perfect (rho ≥ 0.90).²² The alpha level was 0.05.

Results

Total week SB was 9.0 h (6.8–10.9; median and IQR) in all participants, 8.0 h (6.9–11.2) in women and 9.1 (6.7–10.9) in men. A related-samples Wilcoxon Signed Rank test showed a difference between weekday and weekend in total SB (Z = −7.906, p < 0.001), sleep duration (Z = 7.263, p < 0.001), working (Z = −8.607, p < 0.001), watching TV (Z = 6.047, p < 0.001), transportation (Z = −2.902, p = 0.004) and socializing (Z = 2.446, p = 0.014), whereas no difference was found in watching PC (Z = 1.942, p = 0.052) (Table 1). According to independent-sample Mann–Whitney U-test, no difference was observed in SB parameters between women and men (p ≥ 0.150).

Table 1 Sedentary Behavior of Participants

In total, the number of non-sedentary (n = 75, 49.7%) was similar to that of sedentary participants (n = 76, 50.3%). Sedentary was 44.8% of women (n = 13) and 51.6% (n = 63) of men; however, no sedentary*sex association was observed (chi-square = 0.435, p = 0.510). No difference was observed between non-sedentary and sedentary participants, except in the cases of age and training days in women, where sedentary participants were younger and trained fewer days per week than their non-sedentary peers (Table 2). The correlation of SB with training, anthropometric and physiological characteristics can be seen in Table 3, where no correlation was shown except with age and jumping ability in women.

Table 2 Training, Anthropometric and Physiological Characteristics by Sex and Sedentary Behavior

Table 3 Correlations (Spearman’s Rho) of Training, Anthropometric and Physiological Characteristics with Total Sedentary Behavior by Sex

Discussion

The main findings of the present study were that (a) recreational marathon runners had high levels of SB, (b) their SB did not correlate with physiological, anthropometric, and training characteristics, and (c) marathon runners with different levels of SB did not differ for physiological, anthropometric and training characteristics. These findings did not confirm our research hypotheses of the detrimental role of SB on the performance characteristics of recreational marathon runners.

Level of Sedentary Behavior and Inter-Day Variation

An alarming finding was the high levels of SB (~9h·day⁻¹) in the participants. This was lower than that reported in endurance runners,¹¹ which might be explained using both marathon and half-marathon runners suggesting a sample of more “recreational” athletes. An alarming prevalence of SB was already mentioned in an analysis of post-training activity in football players revealing that most of the post-training activity was spent in sedentary activities.²³ With regards to inter-day variation, we observed a similar trend as in previous research, where total sitting time was higher on workdays than nonwork days (~11 and 8 h, respectively) in marathon and half-marathon runners.¹¹

Sedentarism and Physiological Characteristics

The most important finding was that SB did correlate with physiological characteristics. This disagreed with a meta-analysis of 21 original research studies on healthy adults observing a small negative correlation between SB and cardiorespiratory fitness, ie the higher the SB, the lower the cardiorespiratory fitness, and suggesting SB can be associated with poor physical fitness in adults.¹⁰ The evidence found suggested that sedentary time could be associated with poor physical fitness in adults (ie, muscular strength, cardiorespiratory fitness, and balance), so strategies should be created to encourage behavioral changes. However, our findings indicated that regular exercise training might counterbalance this negative role of SB.

Sedentarism and Anthropometric Characteristics

Interestingly, we did not observe any association of SB with indices of fatness such as BMI and BF. However, this finding was in disagreement with a study on athletes, where total screen time – particularly cell phone screen time – was related to BF, ie the more the screen time, the higher the BF.⁹ The findings of Judice et al indicated that athletes (age 22 years) with higher amounts of SB presented higher levels of total and trunk fatness, regardless of weekly training time, and it was concluded that even high moderate-to-vigorous PA levels did not mitigate the associations between SB and body fatness in highly trained athletes.⁹ In contrast, the lack of association of SB with fatness in the present sample might be attributed to different sample characteristics and qualitative content of SB. For instance, the majority of SB (~60%) during weekdays in our sample was spent in sitting while working.

Sedentarism and Training Characteristics

This finding agreed with a study on marathon and half-marathon runners that observed that SB was not related to training duration or sports performance.¹¹ Previous research has found that SB was not impacted by high levels of aerobic training in recreational marathon runners.²⁴ On the other hand, the intensity and duration that older masters and recreational athletes spent in their sport were inversely associated with the amount of sedentary time accumulated in recreational athletes older than 55 years.²⁵ Future studies might further examine the relationship between training and SB considering our preliminary findings suggesting that these two aspects were not related.

Limitations, Strength and Practical Applications

A limitation of the present study was that – although the anthropometric and physiological characteristics of participants were measured using “direct” assessment methods – SB was evaluated using a questionnaire. It was acknowledged that motion trackers such as accelerometers might provide more detailed information. Furthermore, nutritional and health aspects such as detailed daily food consumption and use of medication were not considered. For instance, nutritional habits have been shown previously to relate with both SB and physical fitness.^26,27 Since these aspects were not controlled in the present study, future research should consider the role of nutrition and health, too.

On the other hand, it should be highlighted that this questionnaire was also previously used to evaluate SB in marathon runners making it possible to compare our data with a study on a similar population.¹¹ The strength of our research was the sample consisted of a large number of 43-year-old recreational marathon runners. Thus, the findings would have especially practical application in middle age groups. The participants could be considered “newcomers” who can achieve high levels of performance through regular training even at an advanced age, and this benefit can offset performance losses due to a sedentary lifestyle.²⁸ Accordingly, the findings would have practical applications for researchers and professionals working with marathon runners. So far, there has been little information about the relationship of SB and fitness in marathon runners, and generally in athletes; thus, the results of the present study would be a significant contribution to the limited literature. Moreover, sports federations and coaches may improve athletes’ body composition by targeting specific sedentary pursuits, ie total screen time and cell phone screen time, during athletes’ recovery time.⁹

Conclusions

Previous findings on the general population indicated an association of high SB with low cardiorespiratory and muscular fitness. Nevertheless, our finding of no correlation between SB and physical fitness in marathon runners suggested that endurance exercise might offset the negative effects of SB. Based on our results, people spending many hours sitting while working should be advised to be involved in regular high-volume exercise training of low-to-moderate intensity. Future studies might examine this topic using a longitudinal study design to verify our findings.