INTRODUCTION

In recent decades, the prevalence of obesity has continued to increase across the world [1], representing a considerable global public health issue [2]. Obesity is defined as an excessive or abnormal fat accumulation, presenting health risks related to multiple chronic conditions. Physical activity is a modifiable factor for obesity, which was reported to be correlated with the built environment.

The obesity has doubled worldwide and is considered the fifth risk factor for mortality. Future projections estimates a 33% increase in obesity and 130% increase in severe obesity prevalence in 2030 [3]. Obesity is associated with a reduction in individual mobility, aggravating previous sedentary lifestyle [4, 5]. Activities of daily living (ADL) are impaired due not only to excessive body fat accumulation but also to mechanical factors that might reduce walking capacity.

Adipose tissue represents the largest energy depot in the human body. More and more people exhibit excessive fat deposition in adipose tissue, which leads to obesity, a multifactorial disease with both adverse health effects and economic implications. Although obesity has troubled humanity since ancient times, it has reached epidemic proportions only in recent years [6-9]. Since its primary cause is a chronic imbalance between energy intake and energy expenditure in favor of the former, the road to fighting obesity (excluding pharmaceutical interventions) necessarily passes through creating a negative energy balance [10].

Since many obese people have reduced physical fitness, are not familiar with exercise, and are at increased risk for musculoskeletal injuries due to excess body weight, it is important to prescribe exercise that is safe and makes them feel comfortable, thus ensuring adherence to the exercise training program. Walking on flat terrain, which is the basic locomotor activity of a person and is maximally adapted to it, meets these criteria. Such a program should be defined by the appropriate parameters of frequency, duration, intensity, type, and progressivity, which, in turn, should be determined according to individual abilities, preferences, and responses. It is also recommended that exercise be supervised by a specialized trainer, at least during an initial period. Despite the proven health benefits of aerobic exercise training, traditional modes, such as land walking and running, are often associated with an increased risk of musculoskeletal injury due to accumulated stress on the lower extremities [11], particularly in the obese. Furthermore, pain and injury from exercise are often cited as reasons for discontinuing exercise training. The recommendations apply to both women and men, as there seem to be no differences between sexes in the weight loss caused by equivalent exercise [7].

Regular physical activity (PA) is an important component of overall health. PA is well known to improve cardiorespiratory fitness, blood pressure, and body composition, which are all negatively correlated with the risks of chronic disease [12]. PA also plays a role in body weight regulation through its effects on energy expenditure and energy intake, providing a potential disruption to the energy balance equation [13]. Because exercise creates an energy deficit that may perturb homeostasis and hormone levels, the effects of exercise on energy intake are of interest.

Evidence summarized mainly in many medical staff supports the view that exercise constitutes an indispensable tool in the management of obesity. Yet, in our experience, this tool is often underestimated, and preference is given to other means such as dieting, medication, and surgery. People who are overweight or obese often claim that they are not able to implement an exercise program as individuals of normal body mass, and if they complete the program, its results will be significantly worse than that of people of normal weight [11,14].

Therefore, the aim of our study was to verify the effect of physical intervention based on walking in men of middle age with different weight status with minimal changes in their eating habits.

MATERIALS AND METHODS

Participants

Physically inactive, normal body mass, overweight, and obese men were recruited from the Prague and surroundings communities to participate in the study. Potential volunteers were recruited through informational flyers, through e-mail announcements, and by word of mouth. Volunteers were screened to ensure that they had not participated in regular aerobic activity for the previous 3 months (physically inactive) and were classified as normal body mass, overweight or obese by either body mass index (BMI) or percent body fat as measured by whole body bioimpedance analysis. Subjects were stratified according to the Czech standards for risk of cardiovascular disease, and those for whom it was required underwent a physical examination by a cardiologist before participation in the experiment. Preliminary anthropometrical and physiological characteristics of the all subjects who completed the study are presented in Table 1.

Table 1.

Demographic and selected functional data of subjects and practical and statistical significance upon entry to the study.

VariablesNBM
(1)		OV
(2)		OB
(3)		1-21-32-3
Number252618
Age (years)43.7±3.642.0±2.943.8±3.0NSNSNS
Body mass (kg)78.3±3.989.9.7±3.197.4±4.6* α** αα** αα
Body height (cm)177.5±4.6178.1±4.0178.3±3.2NSNSNS
%BF (%)22.1±2.127.9±2.233.1±3.4** α** α** α
BCM/ECM0.85±0.030.93±0.041.01±0.04NS** αNS
VO2peak.kg-1(ml.kg-1.min-1) - BM32.2±2.6429.1±2.926.1±3.2NS** αNS
VO2peak.kg-1(ml.kg-1.min-1) - FFM41.3±2.740.4±2.839.1±3.1NSNSNS

The study protocol was reviewed and approved by the local Ethics Committee Faculty of P.E. and Sports and followed the guidelines of the World Medical Assembly Declara-tion of Helsinki. Written informed consent to participate was provided by guardians and verbal assessment was provided by the participants.

Methods

Subjects were instructed to maintain their accustomed dietary and physical activity habits throughout the course of the study. No attempt was made to modify diet or activity outside of the exercise training protocol. To verify compliance with these instructions, dietary and activity habits were assessed on two occasions by questionnaire coinciding with the beginning and end of exercise training.

The walking exercise used in this study is one of the most widely known cardiovascular exercises [15]. Walking is the most fundamental physical activity of humans to which the individual is maximally adapted. It is the easiest and the most familiar form of exercise, both physically and mentally. Most people enjoy walking as a type of exercise regardless of age, fitness level, or technique, and it is associated with very little risk of injury. It is therefore well suited for individuals who have minimal experience with movement training.

In order to achieve the greatest possible effect of physical intervention and especially to maintain adherence to PA, a physical program was designed for a duration of 15 weeks. Each session included approximately 10 minutes of warm-up and cool-down, during which participants focused on range of motion and active stretching. The main portion of the walking exercise program, which consisted of 3 walking sessions per week, was designed following the ACSM physical activity guidelines for adults between the ages of 18–64 years [16]. In order to reap greater health benefits from the exercise program, a minimum of 300 minutes per week. 100 minutes per session was ensured with mean intensity of exercise on the level HR ranged from 80 to 90% of age-recommended values. Intensity - walking speed in field conditions was controlled using Sportesters (Polar Oy, Finland) or Smart mobile phones. The outside temperatue during walking was in the range of 15 - 20 degrees Celsius. Body composition was determined by the whole-body bioimpedance in the lying position.

The electrodes were in tetrapolar configuration in the places recommended by the manufacturer (BIA 2000, Datainput, Germany). Predictive equations for calculation of body composition variables (BC, BCM – body cell mass, ECM – extracellular mas) were modified for the Czech population according to verification by DEXA method. We use the ECM/BCM ratio to assess the exercise load assumptions, where ECM is the extracellular mass and BCM is the body cell mass. It holds that FFM = ECM + BCM. The lower this value, the better the movement preconditions the subject has. For trained athletes, we find values of this coefficient lower than 0.7, on the contrary, the values of untrained individuals are close to 1.00 [17,18].

The body cell mass is calculated using the FFM and phase angle between whole impedance vector and resistance [19]. The FFM was calculated according to modified formula of Deurenberg et al. [20]. An incremental maximal graded exercise test was conducted by walking on a motor-driven treadmill for VO2peak determination. Oxygen consumption during exercise was assessed using an automated gas analysis system The maximal functional variables determined on a treadmill with slope of 5% during a progressive walking test until subjective exhaustion. After two familiar walking speeds of 3 and 5 km / h with zero treadmill, the initial walking intensity of 3 km / h on the treadmill with a slope of 5% was increased every minute by 1 km / h until the subject subjectively exhausted. The cardiorespiratory variables were measured in an open system using an on line method by TEEM 100 (Aerosport, USA) and/or Metalyzer 3b (CORTEX, Germany). All analyzers were checked before and after each exercise test series by a calibration gas of known concentration. The ventilation was controlled before and after test series by mechanical pump. Each subject was tested using the same metabolic equipment at pretraining and posttraining assessment periods. VO2peak was taken as the highest 20-s average oxygen uptake achieved during the exercise test. HR was monitored continuously by Sportester Polar.

The subjects were verbally encouraged to continue the exercise to the point of exhaustion. To acknowledge that the subjects had achieved VO2peak, at least two of the following three criteria were met: (a) a plateau of VO2 (change <150 ml·kg-1·min-1); (b) respiratory exchange ratio (RER) ≥1.10; and (c) heart rate (HR) within 10 beats·min-1 of the maximum level expected for age of the maximum level expected for age. Energy when walking on flat terrain was calculated for walking speeds lower than 7 km.h-1 from the linear relationship between movement speed and oxygen consumption, which applies to walking speeds in the range of 3 - 7 km·h-1 [20]. VO2.kg-1 (mL·kg−1·min−1) = 2.957*v (km·h-1) + 2.777. We used the relation 1 l VO2 = 4.8 kcal for load intensity with predominantly aerobic payment of energy requirements [21,22].

Data analysis

The normality of distribution was verified by the Shapiro-Wilk test. The parametric paired t-test was used for the assessment of statistical significance of the differences pre-intervention and post-intervention data. The level of statistical significance for all the used tests was set at p<0.05. Practical significance was assessed using the effect size by Cohen (Cohen’s d). The d value at the level of 0.2 indicates a minor change, 0.5 an intermediate change and 0.8 a major change. The value of Cohen’s d ≥ 0.5 is considered practically significant. The practical significance between the groups independent of the sample size was assessed using the Cohen effect of size. The results were statistically processed using IBM SPSS Statistics (Version 21 for Windows; IBM, Armonk, NY, USA).

RESULTS

The time spent at the prescribed exercise intensity per week ranged between 90-250 min (mean 156.8±48.9 min). Walking time ranged between 82 and 233 min (mean 142.8±45.7 min). In relative description of total exercise time walking ranged from 90.0 % to 93.2 %. The time spent at the described exercise intensity per week ranged between 90-250 min (mean 156.8±48.9 min).

The weekly exercise energy content per kg BM was in subjects with:

• normal BM 20.40 ± 4.51 kcal∙kg-1 (13.4–25.3 kcal∙kg-1),

• overweight 20.36 ± 3.00 kcal∙kg-1 (15.4–24.5 kcal∙kg-1)

• obese 20.33 ± 3.39 kcal∙kg-1 (17.6–24.0 kcal∙kg-1).

Table 2.

Values of demographic and selected functional after intervention and their changes in % of starting value of subjects practical and statistical significance of changes upon entry to the study.

VariablesNBM
(1)		OV
(2)		OB
(3)		1-21-32-3
BM (kg)73.6±2.083.7±2.189.6±2.3* α** αα* α
ΔBM (%)- 6.0±1.9- 6.9±2.1- 8.0±2.2NSNSNS
BF (%)20.2±2.125.4±2.429.8±2.6NS** ααNS
ΔBF (%)- 8.6±2.1- 9.0±2.4- 9.9±2.7NSNSNS
ECM/BCM0.80±0.020.87±0.020.94±0.03* α** αα** αα
ΔBCM/ECM (%)- 6.2±1.7- 6.6±1.9- 7.4±2.0NS** ααNS
VO2peak.kg-1 (ml.kg-1.min-1) - BM36.5±2.433.8±2.429.4±2.7NS* αNS
ΔVO2peak.kg-1 (%)+ 10.3±2.2+ 11.9±2.4+ 12.7±2.6NSNSNS
VO2peak.kg-1 (ml.kg-1.min-1) - FFM45.4±2.644.8±2.343.9±2.7NSNSNS
ΔVO2peak.kg-1 (%)+ 10.0±2.4+ 11.1±2.3+ 12.2±2.7NSNSNS

The differences in the energy intensity of the implemented walking-based exercise program are independent of the weight status of the followed men. The values of functional and anthropometric parameters in individuals with normal weight are practically identical to the values of untrained Czech men [23,24]. The values in overweight or obese men are fundamentally affected by their body mass and differ significantly from the values of individuals with normal body mass. If we convert the values of oxygen consumption to kg FFM, then we find insignificant differences between the monitored groups. Changes in demographic and selected functional data in % of starting value of subjects upon entry to the study are presented in Table 2.

The mean differences in the values of the ECM/BCM coefficient signal different movement assumptions in men with different body mass§ which reflects their movement regime before the start of the movement intervention. On the other hand, the changes in these ECM/BCM assumptions are the same in relative terms due to exercise intervention and are independent of individual weights.

The mean differences between the monitored anthropometric parameters and oxygen consumption related to kg BM or FFM in our groups of men differ insignificantly (p<0.05, d = 0.6) if the changes are expressed in % of pre-intervention values. When comparing extreme individuals in weight groups, the differences may be significant (p<0.05, d = 0.5). The differences in the monitored variables due to the implemented movement intervention in absolute values are practically the same as in the pre-intervention parameters.

DISCUSSION

Worse results of anthropometric and functional parameters in individuals with increased weight are largely due to their weight status, which is a consequence of their inadequate exercise regime. Diminished daily physical activity explains, in part, why obesity have become worldwide epidemics. In particular, chair use has replaced ambulation, so that obese individuals tend to sit for approximately 2.5 h/day more than lean counterparts [9,25].

From activities carried out by overweight or obese individuals walking was the most preferred/enjoyed activity for both men and women [14]. Otherwise, the other preferred PA were cycling, swimming and rowing in the Baillot et al. study [26], and dance or Zumba, cycling, water activities, and martial arts in the Joseph et al. [14] study which was performed among women with obesity. The preference for physical activities in these individuals is also determined by what physical activities they have personal experience with, or which PAs they implemented at a time when they were not overweight or obese. Resistance training was less often identified as a preferred type of PA in women but more in men [14].

Walking exercise appears to be an effective exercise, and an active walking program had positive effect on the level of obesity, and significantly reduced body weight, body fat and waist circumference [27]. Also, walking exercise contributed to reductions in body weight and body fat by increasing muscle tissue, maintaining muscular strength and increasing flexibility [28].

The largest changes in preintervention values of VO2peak due to applied movement training are found in obese individuals (12.7 ± 2.6%). This is consistent with the original results of Dempsey et al. [29], which reported in a cross-sectional study that as the workload increased, oxygen consumption increased more rapidly in obese than in lean subjects, leading to the decreased efficiency in obese subjects. Although the activity type and measurement methodology are different from our study.

These reports support our present findings, which suggest that walking serves as an effective exercise for overweight and obese individuals with low movement experience. Therefore, continuous and systematic implementation of such an exercise program is needed.

Increased abdominal fat, among the various criteria used to evaluate obesity, is known to result in decreased balance as it negatively affects flexibility while shifting the musculoskeletal structure [28]. Obesity tends to cause arching of the affected individual’s back, and increased stress on the muscles surrounding the spine can result in back pain). Subsequent postural instability can also lead to low back pain and diminished flexibility, and the resulting limited range of motion can lead to secondary inactivity and obesity [9]. The main goal of obesity management is to decrease the size of the fat tissues while minimizing the effects on FFM. Cardiovascular exercise is known to be the very effective at decreasing the amount of accumulated fat by utilizing fat as fuel to produce energy. Walking exercise, like many other cardio exercises, improves cardio-respiratory endurance and increases secretion of growth hormones (epinephrine and nor-epinephrine), which are known to promote loss of accumulated fat.

Assumption changes for PA assessed using the ECM/BCM coefficient are greatest in absolute terms for overweight individuals. This is probably due to the lower volume of spontaneous PA in obese individuals compared to individuals with better weight status. These individuals usually solve the necessary daily activities more often by using a car, for example, than individuals with lower body mass status. It turns out that a sedentary lifestyle is directly proportional to weight and an active lifestyle is very rare in these people [23,26,27].

On the other hand, the current fitness assessed using the VO2peak kg of FFM is practically independent of the weight status of the person, although there is evidence of lower muscle mass in the literature as a result of lower PA. At the same time, it should be recalled that the necessary physical activities performed represent a greater burden on the muscular system of overweight or obese individuals, which is probably reflected by a larger volume of muscle mass compensating for insufficient physical activity, as represented by oxygen consumption values per kg FFM.

Changes in the ECM/BCM coefficient depending on the applied exercise mode show that walking is not only a means of weight reduction, but that at the same time the predispositions for exercise load are also improving - ECM/BCM is moving significantly lower. Our obese patients presented a functional performance similar to healthy individuals. In previous studies, morbid obese individuals presented functional capacity similar to elderly population [29] or to patients with cardiac and pulmonary diseases [30-32].

Brisk walking is a recommended form of exercise for obese individuals. However, lower-extremity joint loads and the associated risk of musculoskeletal injury or pathological disease increase with walking speed. Walking uphill at a slower speed is an alternative form of moderate intensity exercise that may reduce joint loading. These results suggest that walking at a relatively slow speed up a moderate incline is a potential exercise strategy that may reduce the risk of musculoskeletal injury/pathological disease while providing proper cardiovascular stimulus in obese adults.

Walking on an incline at a relatively slow speed is not a common exercise recommendation for obese adults and this may be due to the lack of research on the effects of slow walking speeds and inclines on the biomechanics of walking in this population. In fact, there has only been limited research on the biomechanics of incline walking in non-obese adults, and no studies have examined the combined effects of speed and grade.

Walking is the simplest, most accessible, and preferred method of physical activity prescribed for the treatment and prevention of obesity [27,33]. Additionally, it is important to make walking part of a lifestyle change and incorporate it into daily activities, such as using it as a form of commuting. Exercising in groups also is the preferred method of support to increase physical activity among inactive adults [14]. Though participation rate for our initial pilot project was low, 98% of participants stated that they would use the walking buses again, suggesting that these types of programs may be a viable way to increase physical activity among overweight and obese individuals.

Walking is a popular and comfortable form of physical activity and is part of an effective weight management strategy for obese individuals [14] that increases energy expenditure associated with daily leisure activities. However, the higher energy costs for walking (energy expenditure per unit of distance associated with walking movements) reported in obese individuals compared to lean individuals [31] may contribute to impaired mobility due to fatigue, and thus reduce the energy expenditure of free movements. Experiencing daily activities [ie thermogenesis of untrained activities] and reducing the effectiveness of walking weight management programs.

When recommending exercise for adults with overweight or obesity, it is important to balance any positive with potential negative effects on health. In the general population, exercise is associated with an increased risk of musculoskeletal injuries and adverse cardiac events, but there is evidence from non-randomized trials and observational studies that the benefits of exercise far outweigh the risks in most adults [34]. Musculoskeletal injuries are the most frequent negative side effects of exercise. There is however very little information on musculoskeletal injuries in adults with overweight or obesity during exercise interventions.

To reduce the risk of muscle injuries, it is necessary to provide quality footwear for physical training of individuals with higher body mass. At the same time, it is necessary to pay attention to the walking technique, which is usually not good [35,36] especially for individuals with physical deficits and weight gain, and contributes to faster onset of fatigue, which leads to premature termination of physical intervention and demotivation of individuals for regular physical training.

It is likely that a larger percentage of adults with overweight or obesity falls in physically inactive group compared to lean subjects. On the other hand, the largest benefits on all-cause mortality are attained when this group is moved to an at least “moderately active” level [6,37]. By analogy with the general population, overall it seems prudent to advise habitually inactive adults with obesity to become more active by a gradual progression of exercise volume by adjusting exercise duration, frequency, and/or intensity [35,36,38].

Body mass management, lack of motivation and pain are important PA motives and barriers in people with obesity. PA motives and barriers are both weight and non-weight related in people with obesity. For this reason, weight loss cannot be the only solution to remove PA barriers, and these should be addressed in PA interventions with the support of health professionals to facilitate PA initiation and maintenance. Further research is needed to investigate the PA preferences of people with obesity. Although, one size intervention does not fit all, the improvement of knowledge on PA barriers, motives and preferences would help health professionals to better address them, and develop intervention to reach the larger number of people with obesity in order to decrease physical inactivity in this population.

Study limits

The limits of the study include a limited number of subjects, which makes it impossible to generalize the conclusions. Another limit is that not all men completed the intervention on the same date, some in the spring and others in the fall. The information on the overall exercise regime was evaluated only by questioning and could be inaccurately interpreted. They were all tested by the same instruments on the same day of the week and in the morning.

CONCLUSIONS

We may conclude that, although the groups showed different exercise intensities, but similar overall energy intensity, which regulate fat oxidation, the changes in all parameters monitored were similar between the groups. We can conclude that an exercise program with a similar energy content, form and intensity causes the similar changes in adiposity and in motor and functional performance in middle age men, differing in BM. Movement intervention based on walking reduces body weight and at the same time improves the morphological preconditions for physical activity. The study was supported by grant of Charles University Progress Q 41.

REFERENCES

  1. NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet 2016; 387: 1377–1396. doi: 10.1016/S0140-6736(16)30054-X
  2. World Health Organization Obesity: Preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894: 1–253
  3. Finkelstein EA, Khavjou OA, Thompson H, Trogdon JG, Pan L, Sherry B, et al. Obesity and severe obesity forecasts through 2030. Am J Prev Med 2012; 42: 563–570. doi: 10.1016/j.amepre.2011.10.026
  4. Hemmingsson E, Ekelund U. Is the association between physical activity and body mass index obesity dependent? Int J Obes. 2007; 31: 663–668
  5. Wiacek M, Zubrzycki ZI, Tomasiuk R. Worldwide Obesity Trends: An Analysis of WHO Data. J Obes Bod Weig 2021; 2: 005
  6. Bunc V. Obesity – causes and remedies. Phys Act Rev 2016; 4: 50–55. doi: 10.16926/par.2016.04.06
  7. Bray GA, Heisel WE, Afshin A, Jensen MD, Dietz WH, Long M, et al. The science of obesity management: an Endocrine Society scientific statement. Endocr Rev 2018; 79-132. doi: 10.1210/er.2017-00253
  8. Oppert J-M, Bellicha A, van Baak MA, et al. Exercise training in the management of overweight and obesity in adults: Synthesis of the evidence and recommendations from the European Association for the Study of Obesity Physical Activity Working Group. Obes Rev 2021; 22(S4): e13273. doi: 10.1111/obr.13273
  9. Petridou A, A. Siopi A,Mougios V. Exercise in the management of obesity. Metabolism 2019; 92: 163–169. doi: 10.1016/j.metabol.2018.10.009
  10. Chen KY, 8.A. Petridou, A. Siopi,V. Mougios. Exercise in the management of obesity. Metabolism. (2019) Volume 92, March 2019, Pages 163-169. doi: 10.1016/j.metabol.2018.10.009
  11. Ballor DL, Keesey RE. A meta-analysis of the factors affecting exercise-induced changes in body-mass, fat mass and fat-free mass in males and females. Intl J Obes. 1991; 15: 717–726.
  12. King NA, Hopkins M, Caudwell P, et al. Beneficial effects of exercise: shifting the focus from body weight to other markers of health. Brit J Sports Med 2009; 43: 924–927
  13. Martins C, Morgan L, Truby H. A review of the effects of exercise on appetite regulation: an obesity perspective. Int J Obes 2008; 32: 1337–1347. doi: 10.1038/ijo.2008.98
  14. Joseph RP, Ainsworth BE, Mathis L, Hooker SP, Keller C. Utility of Social Cognitive Theory in Intervention Design for Promoting Physical Activity among African-American Women: A Qualitative Study. Am J Health Behav 2017; 41(5): 518–533
  15. Murphy MH, Nevill AM, Murtagh EM, Holder RL: The effect of walking on fitness, fatness and resting blood pressure: a meta-analysis of randomised, controlled trials. Prev Med, 2007, 44: 377-385
  16. ACSM. American College of Sports Medicine. Guidelines for Exercise Testing and Prescription. 7th ed. Philadelphia (PA): Lippincott Williams & Wilkins; 21-22, 141-149, 2006
  17. Bunc V, Hráský P, Baláš J. Body composition, functional and performance characteristics in top Czech young athletes. ACC Journal 2011; 17(2): 17–27
  18. Bunc V, Heller J, Horčic J, Novotny J (1996). Physiological characteristics of best Czech male and female young triathletes, J Sports Med Phys Fitness 1996; 36(4): 262–270
  19. Bunc V. Energy cost of running in non/trained females differing in body fat. J Sports Med Phys Fitness 2000, 40: 290-296
  20. Deurenberg P, Schouten FJM. Loss of total body water and extracellular water assessed by multifrequency impedance. Eur J Clin Nutr 1992; 4: 247255
  21. Bunc V, Dlouhá R. Energy cost of treadmill walking. J Sports Med Phys Fitness. 1997, 37(2):103-10
  22. Astrand PO, Rodahl K. Textbook of work physiology, 3rd ed. New York: McGraw Hill Book Co.; 1986
  23. Bunc V. Walking as a tool of physical fitness and body composition influence. Antropomotoryka 2012; 57: 63–72
  24. Bunc V, Skalská M. Effect of walking on body composition and aerobic fitness in non-trained men of middle age. Antropomotoryka 2011; 21: 39–46
  25. Levine JA, McCrady SK, Lanningham-Foster LM, Kane PH, Foster RC, Manohar CU. The role of free-living daily walking in human weight gain and obesity. Diabetes. 2008; 57(3): 548–554. doi: 10.2337/db07-0815
  26. Baillot, A., Chenail, S., Polita, N. B., et al. Physical activity motives, barriers, and preferences in people with obesity: A systematic review. Plos One 2021; 16(6): e0253114
  27. Mabire L, Mani R, Liu L, Mulligan H, Baxter D. The Influence of Age, Sex and Body Mass Index on the Effectiveness of Brisk Walking for Obesity Management in Adults: A Systematic Review and Meta-Analysis. J Phys Act Health. 2017; 14(5): 389–407. doi: 10.1123/jpah.2016-0064
  28. Greene NP, Lambert BS, Greene ES, Carbuhn AF. Green JS, Crouse SF. Comparative Efficacy of Water and Land Treadmill Training for Overweight or Obese Adults, Med Sci Sports Exerc 2009; 41(9): 1808–1815. doi: 10.1249/MSS.0b013e3181a23f7f
  29. Dempsey JA, Reddan W, Blake B, Rankin J. Work capacity determinants and physiologic cost of weight-support work in obesity. J Appl Physiol 1966; 21: 1815–1820
  30. Lee JS, Jeon BJ. A study on the balance ability and obesity of rural elderly persons in Nonsan. J Occu Ther 2008; 16: 55–66
  31. Ehlen KA, Reiser RF 2nd, Browning RC. Energetics and biomechanics of inclined treadmill walking in obese adults. Med Sci Sports Exerc 2011; 43(7): 1251–1259. doi: 10.1249/MSS.0b013e3182098a6c
  32. Correia de Faria Santarém G, de Cleva R, Santo MA, Bernhard AB, Gadducci AV, Greve JM, Silva PR. Correlation between Body Composition and Walking Capacity in Severe Obesity. PLoS One 2015; 10(6): e0130268. doi: 10.1371/journal.pone.0130268
  33. Baker EH, Milner AN, Campbell AD. A pilot study to promote walking among obese and overweight individuals: walking buses for adults. Public Health 2015; 129(6): 822–824. doi: 10.1016/j.puhe.2015.03.021
  34. Garber CE, Blissmer B, Deschenes MR, et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc 2011; 43(7): 1334–1359. doi: 10.1249/MSS.0b013e318213fefb
  35. Fernández Menéndez A, Saubade M, Millet GP, Malatesta D. Energy-saving walking mechanisms in obese adults. J Appl Physiol (1985) 2019; 126(5): 1250–1258. doi: 10.1152/japplphysiol.00473.2018
  36. Primavesi J, Fernández Menéndez A, Hans D, Favre L, Crettaz von Roten F, Malatesta D. The Effect of Obesity Class on the Energetics and Mechanics of Walking. Nutrients 2021; 18; 13(12): 4546. doi: 10.3390/nu13124546
  37. Bauman AE. Updating the evidence that physical activity is good for health: an epidemiological review 2000-2003. J Sci Med Sport. 2004; 7(1 Suppl): 6- 19
  38. M.M. Schubert, B. Desbrow, S. Sabapathy, M. Leveritt Acute exercise and subsequent energy intake. A meta-analysis. Appetite 2013; 63: 92–104. doi: 10.1016/j.appet.2012.12.010