ABSTRACT
Objective
Preference for outdoor and indoor exercises is essential when choosing a place to exercise. This study compared adults' healthy lifestyle behaviors and life satisfaction according to physical activity location preferences.
Subject and Methods
The study is conducted using a cross‐sectional design between May and October 2023, with visitors to a gym (n = 270). The study sample included participants in the activities of two outdoor sports groups and two gyms operating. Study. The questionnaire for data collection consists of demographic characteristics, Health Promotion Lifestyle Profile (HPLP), Life Satisfaction Scale (SLS), Three‐Factor Eating Questionnaire‐R (TFEQ). Percentage, mean, standard deviation, t‐test, ANOVA posthoc analysis, and Chi‐square tests were used to analyze the data.
Results
The mean age of the participants was 25.87 ± 8.59 years. The rate of people doing indoor activity is 67.4%. The rate of those who prefer outdoor exercise is 87.8%. Many parameters were significant for indoor and outdoor exercisers compared to those in a single location (p < 0.05).
Conclusion
Healthy lifestyle behaviors are better for those who prefer both locations for exercise. A fuller picture of this study is that balance is important for the preference of outdoor and indoor exercises. Individuals should be encouraged to exercise outdoors and indoors.
Keywords: exercise psychology, healthy lifestyle, indoor exercises, life satisfaction, outdoor exercises, physical activity
1. Background
The place where people prefer to do activities is influenced by many factors: technology, environment, gender, and age. While the elderly prefer open spaces such as parks, young people prefer sports centers (Zhai et al. 2023). Aside from this fact, elderly individuals are vulnerable to the environment due to limitations in body mechanics. It is necessary to prepare the environment for activity for all individuals by promoting activity‐friendly environments (Portegijs, Lee, and Zhu 2023). The situation is not clear for middle‐aged adults. It is recommended to conduct studies on activity location preferences in different groups with different needs (Zhai et al. 2023). Another evidence is that gender differences in physical activity location preferences. For example, women may prefer indoor spaces due to time constraints (Kretchmar et al. 2024). Technology is an important marker for activity preferences. While screen addiction reduces activity, technology enables to be aware of new activity opportunities and to act as a group through social networks (Portegijs, Lee, and Zhu 2023). According to studies, exercise is also used as a coping tool. A study shows that exercise preference is useful for post‐traumatic stress disorders (Pebole et al. 2024). In one study, it was found that regular exercise with a group improved the prognosis of Parkinson's disease (Sonne et al. 2024). Many studies have also used exercise to cope with loneliness and to socialize (Martínez‐Velilla et al. 2024; Surkalim et al. 2024). Regardless of individuals' location preferences for physical activity, a preference balance is a factor that improves the quality of the activity (Kretchmar et al. 2024).
Activities in nature are defined as outdoor exercises. Within the scope of these activities, individuals spend their free time in nature by participating in sports such as mountaineering, cycling, hiking, surface and underwater activities, and paragliding. It has been proven that outdoor activities provide significant cognitive, affective and physical benefits to individual and community life. These benefits include leadership, decision‐making and reasoning skills in individuals. It has also been revealed that it positively affects academic achievement. In the literature, studies on outdoor activities are not sufficient (Dinc 2021). In a study, it was determined that individuals who participated in cycling and hiking activities were mostly individuals who lived alone, were mostly retired, had a predominantly middle income level, and generally had a university education. In the same study, participants stated that they felt happier, healthier, stronger, and more relaxed by practicing nature sports (Ardahan and Lapa 2011). In another study, it was determined that mountaineering, rock climbing, cycling, and hiking or participating in these activities positively affected individuals' emotional intelligence and life satisfaction (Kaplan and Ardahan 2013). People may prefer indoors when outdoor and climatic conditions are not suitable. People may think that they receive services in indoors because they are customers (Kurhan et al. 2023). This increases their motivation for sports. Many people think that exercising in indoor is more ergonomic to improve quality of life. They can move in groups in indoors. Sports equipment, swimming, Pilates, Zumba, aerobic exercises, spinning are some of the preferred types of exercise that people can do in indoors (Anggeraeni et al. 2024; Budhwani and Patil 2024). A previous studies related to the physical exercise location preferences that found results by addressing physical activity preferences in the center of gender. It was found that women had higher exercise self‐confidence than men (Tsartsapakis, Chalatzoglidis, and Zafeiroudi 2023). Another study concluded that outdoor exercise is better for individuals' psychological health than indoor exercise. It was also found that individuals' exercise motivation and oxygen saturation increased and heart rate decreased. In the same study it was stated that similar research is needed. Outdoor exercise was positively emphasized (Dessalegn 2023). On the other hand, another study emphasized indoor exercises. In this study, it was argued that indoor exercise can prevent outdoor injuries, and that with the help of technology and augmented reality, the outdoor environment can be prepared while exercising indoors. Indoor exercise was positively emphasized (Hasnan et al. 2024).
Life satisfaction, which is a subjective concept, is defined as the judgment that emerges as a result of the evaluation of the individual's life achievements, quality of life, and expectations by the individual himself/herself (Cella 1994). Life satisfaction is a measure of satisfaction with one's life. Life satisfaction is affected by social determinants of health such as marital status and age (Guler and Usluca 2021). There is a relationship between an individual's behaviors and life satisfaction. In a study among nursing students, it was determined that the life satisfaction of the participants increased as their healthy lifestyle behaviors increased (Baksi, Surucu, and Cetik 2020).
Eating behaviors are critical for life balance of people. Especially in sick individuals, eating behaviors either change spontaneously or have to be changed to adapt to treatment. People who are under psychological pressure and stress tend to increase or decrease their tendency to eat (Maalouf et al. 2023). In a study on lifestyles and eating behaviors, participants reported that they were concerned about nutrition and had difficulties maintaining a healthy lifestyle. In the same study, it was emphasized that although it is proven that lifestyle is through quality and balanced nutrition, there are few initiatives in this regard (Moscatelli et al. 2023). Another study found a strong association between addiction and eating behaviors and lifestyle. It is inevitable to question eating behaviors in order to gain healthy lifestyle behaviors or to conduct research on this subject (Wang et al. 2023).
Regular physical activity, healthy eating, stress management, interpersonal support, self‐actualization, and health responsibility are among healthy lifestyle behaviors in nursing literature (Yilmazel et al. 2013). Acquiring healthy lifestyle behaviors positively affects the individual's quality of life. Regular physical activity positively affects many systemic functions (Vatansever et al. 2015). The most important of these are to improve the muscle function of individuals and regulate the body's oxygen regulation and to provide neuro‐hormonal activation, which is an important element of heart diseases, which are among the major chronic diseases today (Chrysohoou et al. 2015). Mentz et al. (2013) found that exercise reduced the risk of heart failure by 11%–30% in a study they conducted. The body perception of individuals with healthy eating habits does not require them to require a diet; in other words, the individual does not need to have a disease in order to have these behaviors; it is beneficial for the individual to gain while healthy (Ongoren 2015).
Lifestyle is all behaviors that are under the control of individuals and affect their health risks. According to the holistic health approach, health protection (risk reduction and prevention) and health promotion behaviors are an integral part of a healthy lifestyle. Health promotion and health protection are important strategies for improving the overall health status of the population and providing basic care services from public health nurses (Salari et al. 2017). Healthy lifestyle behavior is all behaviors that affect a person's health and can be controlled against factors that have a significant impact on health (Walker, Sechrist, and Pender 1987). In Satisfaction with Life, the individual “willingly” engages in disease prevention activities. Examples of healthy lifestyle behavior include desirable behaviors such as maintaining good health; living a balanced life; exercising; and striving to be cognitively, emotionally, psychologically, physically, or spiritually well.
Unlike the literature, differently this study created the opportunity to examine indoor and outdoor exercises objectively. To emphasize the unique value of the study, this study was conducted on a topic on which there are few studies in the literature and more studies are recommended in the future (Tsartsapakis, Chalatzoglidis, and Zafeiroudi 2023; Hasnan et al. 2024; Dessalegn 2023). It is predicted that this will fill an important gap in the literature. In one study, it was observed that participants who felt moderate fatigue during the activity had significantly higher health beliefs than those who felt high fatigue. In the same study, it was stated that the literature needs evidence related to recreational sporting activities (Cingoz et al. 2022). This study was conducted to compare the healthy lifestyle behaviors and life satisfaction of adults according to their physical activity location preferences.
1.1. Research Questions
Do the healthy lifestyle behaviors of the adults participating in this study change according to their physical activity location preferences?
Do the life satisfaction of the adults participating in this study change according to their physical activity location preferences?
2. Methodology
2.1. Study Design and Study Sample
The study is a descriptive cross‐sectional study. The study sample included participants in the activities of an outdoor exercises sports group and registered customers to a Gym operating in the center between May 2023 and October 2023 (n = 270). The questionnaires were applied face‐to‐face. Being 18 years of age or older and volunteering to participate in the study were determined as inclusion criteria. Power analysis was performed with the G*Power 3.1.9.7 program to determine the minimum number of participants who could participate in the study. t tests: sample calculation was made according to multiple regression test. Effect size f = 0.15, α err prob = 0.05, power = 0.95, number of predictors = 2, and the minimum number of participants to be sampled was determined as 74 participants. Effect size is based on previous studies (Huang et al. 2020; Delbaere et al. 2021; Huang et al. 2021; Makino et al. 2021). The inclusion criteria for the participants were volunteering to participate in the study, the center where the study was selected, and participating in the groups to exercise.
2.2. Measures
The questionnaire to be used for data collection consists of Personal Information Form, Health Promotion Lifestyle Profile, Life Satisfaction Scale, and Three‐Factor Eating Scale.
Health Promotion Lifestyle Profile (HPLP) was developed by Walker, Sechrist, and Pender (1987). The validity and reliability of the scale were conducted by Esin (1997). The HPLP is a 48‐item, four‐point Likert‐type scale consisting of never, sometimes, frequently, and regularly antecedents. There are six independent subdimensions of the HPLP. These dimensions are represent spiritual growth, health responsibility, physical activity, nutrition, interpersonal relationships, and stress management. In the evaluation of the scale, “never”: 1, “sometimes”: 2, “often”: 3, “often”: 3, and “regularly”: 4. The lowest score for the whole scale is 48 and the highest score is 192. The higher the score, the higher the level of positive health behavior.
Life Satisfaction Scale (LSS): The five‐item Satisfaction With Life Scale developed by Diener et al. (1985). It was adapted into Turkish by Dagli and Baysal (2016). The scale is a five‐point Likert‐type scale consisting of Strongly Disagree, Slightly Agree, Moderately Agree, Strongly Agree, and Strongly Agree. As a result of the reliability studies of the scale, Cronbach Alpha internal consistency coefficient was calculated as 0.88.
The Three‐Factor Eating Questionnaire‐R (TFEQ) developed by Stunkard and Messick (1985). The validity and reliability of the scale was conducted by Karakus, Yıldırım, and Büyüköztürk (2016). All of the items in the section are in four‐point Likert type and the responses are 1 = Absolutely wrong, 2 = Mostly wrong, 3 = Mostly right, and 4 = Absolutely right. The scale shows a 3‐factors. These dimensions are represent including disinhibition, cognitive restraint, and perceived hunger. As a result of the reliability studies of the scale, Cronbach Alpha internal consistency coefficient was calculated as sub scales; disinhibition (0.801), cognitive restraint (0.870), perceived hunger (0.787) (Karakus, Yıldırım, and Büyüköztürk 2016).
2.3. Statistical Analysis
The data of the study were evaluated on the computer with SPSS 25 analysis program. Skewness and Kurtosis tests and Z values from normality tests will be examined to determine the normal distribution of the data. Percentage, mean, standard deviation, t test, ANOVA, post‐hoc analysis, Bonferroni ve Tamhane, Chi‐square tests were used to analyze the data. The significance level was accepted as 0.05 in all statistical procedures used in the research.
3. Results
The mean age of the participants was 25.87 ± 8.59 (minimum 18; maximum 64). A total of 58.5% of the participants were female. The rate of those with normal body mass index was 59.6%. 80.4% of the participants are single and 60.7% of them consider their income to be equal to or more than their expenses. The majority (78.5%) were bachelor graduates and 66.3% were not working. 11.1% of the participants reported that they had chronic diseases and 11.9% reported that they used medication. Some of those who were ill reported asthma, diabetes, and ankylosing spondylitis. Participants who smoked cigarettes stated that they had been smoking for an average of 8.18 ± 7.06 years; 23.3% of them reported that they were addicted to smoking. 77.4% of the participants reported that they did not consume alcohol. Approximately half of the participants (58.5) stated that they were in good health. The rate of those who go to the indoor is 67.4. They are preferred for using sports equipment (37.7) and swimming (26.6). The frequency of indoor use was defined as irregular (27.1), 1 day a week (5.9), 2 or 3 days a week (16.3), and more than 3 days a week (18.1). The rate of those who prefer outdoor exercise is 87.8. Walking (40.5), cycling (13.8), and gardening (13.1) are more common. The frequency of doing outdoor exercises was determined as irregular (44.8%), 1 day a week (11.5%), 2 or 3 days a week (16.3%), and more than 3 days a week (15.2%) (Table 1).
TABLE 1.
Sociodemographic and health characteristics of the participants (n = 270).
| Characteristics | n | % |
|---|---|---|
| Gender | ||
| Woman | 158 | 58.5 |
| Men | 112 | 41.5 |
| BMI (WHO, 2010) | ||
| Underweight (< 18.5) | 27 | 10.0 |
| Normal weight (18.5–24.9) | 161 | 59.6 |
| Overweight (25–29.9) | 63 | 23.4 |
| Obesity classes (≥ 30) | 19 | 7.0 |
| Marital status | ||
| Married | 49 | 18.1 |
| Single or divorced | 221 | 81.9 |
| Income status | ||
| Less than expenditure | 106 | 39.3 |
| Equal to expenditure | 115 | 42.6 |
| More than expenditure | 49 | 18.1 |
| Education status | ||
| Primary‐secondary school | 11 | 4.1 |
| Middle School | 25 | 9.3 |
| Bachelor or higher | 234 | 86.7 |
| Employment status | ||
| Working | 82 | 30.4 |
| Not working or retired | 188 | 69.6 |
| Chronic disease state | ||
| Yes | 30 | 11.1 |
| No | 240 | 88.9 |
| Medication usage | ||
| Yes | 32 | 11.9 |
| No | 238 | 88.1 |
| Cigarette consumption | ||
| I consume | 63 | 23.3 |
| I do not consume | 207 | 76.7 |
| Alcohol consumption | ||
| Irregular | 32 | 11.9 |
| Regular (Each day or once a week or once a month) | 29 | 10.7 |
| I do not consume | 209 | 77.4 |
| Health status | ||
| Good | 158 | 58.5 |
| Fair or bad | 112 | 41.5 |
The difference between the total HPLP, cognitive restraint, spiritual growth, health responsibility, physical activity, nutrition, interpersonal relationships subdimensions of the scales and physical activity location preferences is statistically significant (p < 0.05). Bonferroni and Tamhane post hoc tests were performed to determine which groups the difference originated from. There is a significant difference between those who do outdoor exercises and those who do exercises in both places in terms of health responsibility (p = 0.08). There is a significant difference between those who do outdoor activity and those who do exercises in both places in terms of cognitive restriction (p = 0.02). There is a significant difference between those who do outdoor activity and those who do exercises in both places in terms of HPLP total score, interpersonal relationships, spiritual growth, nutrition, and physical activity sub‐dimensions (p < 0.05). There is a significant difference (p < 0.05) between those who do exercises in the indoor and those who do exercises in both places in terms of the total score of HPLP, interpersonal relationships, spiritual growth, nutrition, and physical activity sub‐dimensions (Table 2).
TABLE 2.
Sport behavior characteristics of the participants (n = 270).
| Behaviors | n | % |
|---|---|---|
| Physical Activity Preferences | ||
| Outdoor exercise | 77 | 28.5 |
| Indoor exercise | 34 | 12.6 |
| Outdoor and indoor exercise | 159 | 58.9 |
| Routines of gym | ||
| I do not use | 88 | 32.6 |
| Irregular | 73 | 27.1 |
| One day a week | 16 | 5.9 |
| Two or three days a week | 44 | 16.3 |
| More than 3 days a week | 49 | 18.1 |
| Gym usage features* | ||
| Sports equipment | 129 | 37.7 |
| Swimming | 91 | 26.6 |
| Pilates | 39 | 11.4 |
| Zumba | 29 | 8.5 |
| Aerobic exercises | 29 | 8.5 |
| Spinning | 25 | 7.3 |
| Routines of outdoor exercise | ||
| I do not use | 33 | 12.2 |
| Irregular | 121 | 44.8 |
| One day a week | 31 | 11.5 |
| Two or three days a week | 44 | 16.3 |
| More than 3 days a week | 41 | 15.2 |
| Outdoor exercise features* | ||
| Walking | 220 | 40.5 |
| Biking | 75 | 13.8 |
| Gardening | 71 | 13.1 |
| Running | 58 | 10.7 |
| Team sports | 42 | 7.7 |
| Camping | 34 | 6.3 |
| Trekking | 23 | 4.2 |
| Mountaineering | 20 | 3.7 |
Participants were able to tick more than one option.
The difference between the participants who exercised in the indoor and nonpatient participants and the LSS, TFEQ, and HPLP scale was found to be statistically significant (p < 0.05). Bonferroni and Tamhane post hoc tests were performed to determine from which groups the difference originated. There is a significant difference in life satisfaction between those who do exercises in the indoor and those with good and moderate health status (p < 0.05). There is a significant difference in terms of HPLP between those who do outdoor activity, those whose income is equal to their expenses and those whose income is more than their expenses (p < 0.05) (Table 2).
A significant difference was found between primary‐secondary school graduates and university graduates who practiced exercises in both places in terms of HPLP (p < 0.05). A significant difference was found between those who practiced exercises in both places, whose income was equal to their expenses, and those whose income was less than their expenses in terms of life satisfaction (p < 0.05) (Table 3). A significant difference was determined between those who practiced exercises in both places, whose income was equal to their expenses, and those whose income was less than their expenses in terms of HPLP (p < 0.05) (Table 4).
TABLE 3.
Comparison of physical activity preferences according to sociodemographic characteristics of the participants with chi square tests (n = 270).
| Characteristics | Indoor exercise | Outdoor exercise | Outdoor and indoor exercise |
x2 |
p |
|---|---|---|---|---|---|
| Gender | |||||
| Woman | 12 (7.6%) | 61 (38.6%) | 85 (53.8%) | 22.826 | < 0.05 |
| Men | 22 (19.6%) | 16 (14.3%) | 74 (66.1%) | ||
| BMI (WHO, 2010) | |||||
| Underweight (< 18.5) | 3 (11.1%) | 12 (44.4%) | 12 (44.4%) | 11.320 | 0.079 |
| Normal weight (18.5–24.9) | 17 (10.6%) | 47 (29.2%) | 97 (60.2%) | ||
| Overweight (25–29.9) | 13 (20.6%) | 11 (17.5%) | 39 (61.9%) | ||
| Obesity classes (≥ 30) | 1 (5.3%) | 7 (36.8%) | 11 (57.9%) | ||
| Marital status | |||||
| Married | 8 (16.3%) | 11 (22.4%) | 30 (61.2%) | 1.492 | 0.474 |
| Single or divorced | 26 (11.8%) | 66 (29.9%) | 129 (58.4%) | ||
| Income status | |||||
| Less than expenditure | 13 (12.3%) | 35 (33.0%) | 58 (54.7%) | 3.800 | 0.434 |
| Equal to expenditure | 12 (10.4%) | 31 (27.0%) | 72 (62.6%) | ||
| More than expenditure | 9 (18.4%) | 11 (22.4%) | 29 (59.2%) | ||
| Education status | |||||
| Primary‐secondary school | 2 (18.2%) | 3 (27.3%) | 6 (54.5%) | 3.886 | 0.422 |
| Middle School | 6 (24.0%) | 7 (28.0%) | 12 (48.0%) | ||
| Bachelor or higher | 26 (11.1%) | 67 (28.6%) | 141 (60.3%) | ||
| Employment status | |||||
| Working | 13 (15.9%) | 13 (15.9%) | 56 (68.3%) | 9.387 | < 0.05 |
| Not working or retired | 21 (11.2%) | 64 (34.0%) | 103 (54.8%) | ||
| Chronic disease state | |||||
| Yes | 2 (6.7%) | 9 (30.0%) | 19 (63.3%) | 1.080 | 0.583 |
| No | 32 (13.3%) | 68 (28.3%) | 140 (58.3%) | ||
| Medication usage | |||||
| Yes | 2 (6.3%) | 7 (21.9%) | 23 (71.9%) | 2.761 | 0.251 |
| No | 32 (13.4%) | 70 (29.4%) | 136 (57.1%) | ||
| Cigarette consumption | |||||
| I consume | 13 (20.6%) | 13 (20.6%) | 37 (58.7%) | 6.012 | < 0.05 |
| I do not consume | 21 (10.1%) | 64 (30.9%) | 122 (58.9%) | ||
| Alcohol consumption | |||||
| Irregular | 3 (9.4%) | 3 (9.4%) | 26 (81.2%) | 19.064 | < 0.05 |
| Regular | 3 (10.3%) | 2 (6.9%) | 24 (82.8%) | ||
| I do not consume | 28 (13.4%) | 72 (34.4%) | 109 (52.2%) | ||
| Health status | |||||
| Good | 20 (12.7%) | 42 (26.6%) | 96 (60.8%) | 0.728 | 0.695 |
| Fair or Bad | 14 (12.5%) | 35 (31.3%) | 63 (56.3%) | ||
TABLE 4.
Comparison of scale averages according to participants' physical activity locations with one way ANOVA test (n = 270).
| Scales and dimensions | Groups | n | mean ± sd | F | p |
|---|---|---|---|---|---|
|
Life satisfaction scale (LSS) |
Indoor | 77 | 14.64 ± 0.83 | 2.704 | 0.069 |
| Outdoor | 34 | 13.36 ± 0.42 | |||
| Indoor and outdoor | 159 | 14.72 ± 0.34 | |||
| Three‐factor eating scale (TFEQ) | Indoor | 77 | 46.94 ± 2.12 | 1.373 | 0.255 |
| Outdoor | 34 | 44.59 ± 1.05 | |||
| Indoor and outdoor | 159 | 46.96 ± 0.85 | |||
|
Sub dimension, Disinhibition |
Indoor | 77 | 20.67 ± 0.97 | 0.641 | 0.528 |
| Outdoor | 34 | 20.11 ± 0.51 | |||
| Indoor and outdoor | 159 | 20.96 ± 0.45 | |||
|
Sub dimension, Cognitive restraint |
Indoor | 77 | 13.47 ± 0.68 | 3.418 | < 0.05 |
| Outdoor | 34 | 12.25 ± 0.44 | |||
| Indoor and outdoor | 159 | 13.75 ± 0.33 | |||
|
Sub dimension, Perceived hunger |
Indoor | 77 | 12.79 ± 0.77 | 0.218 | 0.804 |
| Outdoor | 34 | 12.22 ± 0.51 | |||
| Indoor and outdoor | 159 | 12.25 ± 0.36 | |||
| Health promotion lifestyle profile (HPLP) | Indoor | 77 | 120.79 ± 2.97 | 14.780 | < 0.05 |
| Outdoor | 34 | 117.98 ± 1.80 | |||
| Indoor and outdoor | 159 | 132.37 ± 1.79 | |||
|
Sub dimension, Spiritual growth |
Indoor | 77 | 33.88 ± 0.99 | 7.891 | < 0.05 |
| Outdoor | 34 | 34.23 ± 0.60 | |||
| Indoor and outdoor | 159 | 37.39 ± 0.58 | |||
|
Sub dimension, Health responsibility |
Indoor | 77 | 24.88 ± 0.82 | 4.638 | < 0.05 |
| Outdoor | 34 | 23.42 ± 0.56 | |||
| Indoor and outdoor | 159 | 25.76 ± 0.46 | |||
|
Sub dimension, Physical activity |
Indoor | 77 | 11.58 ± 0.45 | 46.665 | < 0.05 |
| Outdoor | 34 | 9.44 ± 0.26 | |||
| Indoor and outdoor | 159 | 13.32 ± 0.25 | |||
|
Sub dimension, Nutrition |
Indoor | 77 | 14.61 ± 0.47 | 6.133 | < 0.05 |
| Outdoor | 34 | 14.90 ± 0.31 | |||
| Indoor and outdoor | 159 | 16.22 ± 0.28 | |||
| Sub dimension, Interpersonal relationships | Indoor | 77 | 18.73 ± 0.53 | 6.654 | < 0.05 |
| Outdoor | 34 | 19.50 ± 0.41 | |||
| Indoor and outdoor | 159 | 20.86 ± 0.30 | |||
|
Sub dimension, Stress management |
Indoor | 77 | 16.91 ± 0.57 | 12.704 | 0.069 |
| Outdoor | 34 | 16.01 ± 0.38 | |||
| Indoor and outdoor | 159 | 18.52 ± 0.31 |
Note: p < 0.05.
The most interesting finding of the study was that there was no significant difference with any parameter according to smoking and physical activity preferences (Table 5). Finally, body mass index showed a significant difference with the disinhibition subdimension in those who exercised indoor and with the cognitive restraint subdimension in those who exercised outdoors and in both places. 5
TABLE 5.
Comparison of total scale averages according to sociodemographic characteristics of the participants with multiple linear regression.
|
Life Satisfaction Scale |
Three‐Factor Eating Scale | Health Promotion Lifestyle Profile | |
|---|---|---|---|
| β Coef a (95 % CI) | β Coef a (95 % CI) | β Coef a (95 % CI) | |
| Indoor exercises (model 1) | |||
| Gender | −0.071 (−5.501–4.087) | 0.044 (−12.153–14.395) | 0.248 (−11.969–29.707) |
| BMI (WHO, 2010) | 0.196 (−2.460–5.216) | −0.192 (−14.064–7.187) | 0.154 (−12.808–20.552) |
| Marital status | 0.071 (−5.495–7.088) | 0.266 (−9.756–25.083) | 0.280 (−16.075–38.618) |
| Income status | 0.148 (−1.973–3.757) | 0.067 (−6.906–8.958) | −0.039 (−13.292–11.612) |
| Education status | 0.095 (−5.100–6.686) | −0.180 (−20.170–12.462) | −0.044 (−26.944–24.284) |
| Employment status | 0.404 (−2.108–10.053) | −0.112 (−19.641–14.029) | −0.088 (−29.511–23.346) |
| Chronic disease state | 0.157 (−5.615–11.989) | 0.352 (−6.105–42.636) | 0.074 (−32.910–43.604) |
| Medication usage | 0.073 (−7.167–10.119) | −0.037 (−25.852–22.008) | 0.123 (−28.612–46.521) |
| Cigarette consumption | −0.564 (−10.883–0.210) | −0.455 (−26.208–3.343) | 0.102 (−19.603–26.787) |
| Alcohol consumption | 0.193 (−0.811–2.176) | 0.302 (−1.403–6.868) | 0.188 (−4.116–8.867) |
| Health status | −0.216 (−6.118–1.914) | −0.076 (−12.997–9.243) | 0.064 (−15.225–19.687) |
| Outdoor exercises (model 2) | |||
| Gender | 0.164 (−0.778–3.813) | −0.078 (−7.551–4.005) | −0.141 (−15.525–4.535) |
| BMI (WHO, 2010) | −0.017 (−1.391–1.235) | 0.267 (−0.208–6.402) | 0.043 (−4.886–6.588) |
| Marital status | −0.323 (−7.494–0.584) | −0.100 (−12.801–7.529) | 0.158 (−10.522–24.769) |
| Income status | 0.126 (−0.585–1.918) | 0.008 (−3.051–3.249) | −0.030 (−6.138–4.798) |
| Education status | 0.366 (0.167–5.707) | 0.386 (0.636–14.580) | 0.093 (−8.945–15.260) |
| Employment status | 0.261 (−0.287–5.508) | 0.026 (−6.641–7.944) | 0.163 (−5.789–19.529) |
| Chronic disease state | −0.160 (−5.001–1.270) | −0.061 (−9.629–6.153) | −0.151 (−21.133–6.263) |
| Medication usage | −0.218 (−6.572–0.899) | 0.152 (−4.526–14.275) | −0.054 (−19.309–13.328) |
| Cigarette consumption | −0.007 (−2.660–2.511) | −0.084 (−8.574–4.438) | −0.086 (−14.927–7.660) |
| Alcohol consumption | 0.357 (0.449–2.537) | 0.056 (−2.052–3.203) | −0.041 (−5.288–3.835) |
| Health status | −0.241 (−3.681–0.55) | 0.182 (−1.337–8.065) | −0.038 (−9.360–6.962) |
| Indoor and outdoor exercises (model 3) | |||
| Gender | −0.146 (−2.630–0.063) | −0.076 (−5.205–1.922) | −0.127 (−12.684–1.234) |
| BMI (WHO, 2010) | 0.051 (−0.672–1.307) | 0.128 (−0.681–4.556) | 0.069 (−2.914–7.313) |
| Marital status | −0.061 (−2.746–1.366) | 0.017 (−4.971–5.913) | 0.063 (−7.009–14.244) |
| Income status | 0.368 (1.305–3.207) | 0.069 (−1.478–3.554) | 0.245 (2.787–12.613) |
| Education status | −0.117 (−2.956–0.667) | 0.070 (−3.130–6.459) | 0.168 (−0.999–17.726) |
| Employment status | 0.077 (−0.874–2.292) | 0.109 (−1.742–6.637) | 0.081 (−4.347–12.016) |
| Chronic disease state | 0.081 (−1.503–3.697) | 0.083 (−4.119–9.645) | −0.066 (−18.008–8.868) |
| Medication usage | −0.038 (−2.900–1.949) | −0.144 (−10.810–2.025) | 0.136 (−3.813–21.250) |
| Cigarette consumption | 0.162 (−0.005–3.371) | 0.144 (0.807–8.127) | 0.106 (−3.064–14.381) |
| Alcohol consumption | 0.073 (−0.256–0.641) | −0.099 (−1.830–0.544) | −0.013 (−2.500–2.136) |
| Health status | −0.151 (−2.758–0.046) | −0.068 (−5.211–2.211) | −0.178 (−15.445–0.951) |
Note: Bold highlighting indicates statistical significance (p < 0.05).
Standardized coefficients beta.
4. Discussion
This cross‐sectional paper aimed to study the compare the healthy lifestyle behaviors and life satisfaction of adults according to their physical activity location preferences, indoors and outdoors. This study provides evidence as to whether sportive activities differ according to the places where they are performed. In current study, it had a positive effect on the mean scores of those who exercised both outdoors and indoors. Also, according to this research, people's use of outdoor and indoor together positively affected their healthy lifestyle behaviors. The reason for this may be related to the fact that doing exercises in both places will increase the duration of exercise. In a study conducted by Kretchmar and team (2024) a similar conclusion was reached emphasizing the result in our study. Balance in the type of physical exercise was recognized as a factor that improves the quality of the activity.
As an unexpected result, no significant difference was found only in the stress management subdimension. This may be because exercise has a positive effect on stress in any environment, regardless of where it is practiced. In the literature, many studies argue that exercise is effective on stress independent of our findings (Maalouf et al. 2023; Pebole et al. 2024; Su et al. 2024). Besides, in one of the studies supporting our findings, it was concluded that the effect of exercise on stress did not vary according to the environment in which exercise was performed (Hammad 2017). In particular, a meta‐analyses exhibit evidence that exercise interventions reduce depression and anxiety, even if the level of evidence is insufficient (Su et al. 2024). However, the response may differ between individuals. In this study, the reason why there was no statistical difference in the stress management subdimension may be due to interindividual differences. Emotional eating has been associated with individuals with lower self‐esteem and poorer perception of physical fitness (Jáuregui‐Lobera et al. 2014). In this study, the reason why there was no statistical difference in the emotional eating dimension may be due to the fact that physically active individuals, regardless of physical exercise location preference, have higher self‐esteem and a stronger perception of physical fitness. The present results show that body composition is related to nutrition. This is similar to that reported by Myers et al. who concluded that there is a relationship between adiposity and uncontrolled eating (Myers et al. 2017). In this study, body mass index showed a significant difference between the subdimension of uncontrolled eating in those who exercised in the indoors, and with the subdimension of cognitive eating in those who exercised outdoors and in both places. Our findings support this study.
According to this study, no difference was found in terms of the subdimension of uncontrolled eating according to activity location preferences. A randomized controlled trial lasting 6 months reported that the sedentary group had an inverse relationship with uncontrolled eating, while those who engaged in moderate activity had a direct relationship with uncontrolled eating (Martinez‐Avila et al. 2020). In a study, it was reported that healthy adults who were physically active were more likely to recognize uncontrolled eating behaviors (Oh and Taylor 2013). This may be one of the reasons why there was no statistical difference in this study. Studies have reported that the only eating behavior characteristic altered by exercise was increased emotional eating in the severe‐intensity exercise group. This suggests that exercise may have negatively affected the ability to resist emotional cues or to eat in response to different negative emotions. This may be explained by the effect of exercise on emotional state and mood. Hormonal changes that occur during exercise may positively affect mood and reduce stress indicators (Pedersen and Saltin 2015; Su et al. 2024).
In this study, the healthy lifestyle behaviors of those who preferred both outdoor and indoor exercises were higher than the others. In the literature, there are many studies on indoor and outdoor exercise. The cognitive activity and creativity of people rise after outdoor exercise, according to indoor exercises (Plante et al. 2006). In women, outdoor exercises caused them to consume greater energy, while indoor virtual exercises caused them to consume less energy. In both genders, it was detected walking with virtual reality was more relaxed and had the least tension (Kimura et al. 2023). The difference in perception is an important determinant for indoor and outdoor exercises. On the other hand, many factors have been identified in the literature that may negatively affect outdoor exercise. These include air pollution, cold and dry air, and ultraviolet rays (Carlsen et al. 2005). Exercise location preferences are ineffective for eating behaviors except for life satisfaction and cognitive eating restriction. Individuals should be encouraged to exercise outdoors and indoors and not stick to only one place.
5. Conclusions
Healthy lifestyle behaviors are better of those who preferred both locations for exercise. This study shows that balance is vital for the preference for outdoor and indoor exercises. Individuals should be encouraged to exercise outdoors and indoors. In the current study, unlike the literature, it was concluded that individuals who can create a driving force in both environments need both (Dessalegn 2023; Hasnan et al. 2024). This result makes our study different and unique. It has been proven in the literature that exercise is necessary to improve quality of life. In this study, the place, and quality of exercise were studied. In future studies, unidirectional trends can be examined in detail. For example, in‐depth qualitative research can be conducted on people who only use indoor exercises or people who only practice outdoor exercises.
The most important limitation of this study is that it was carried out only on one indoor and one outdoor sample. There are many types of indoor areas and many types of outdoor areas. The second important limitation we identified in the study is that the number of participants is different in the two types of centers. This may have affected the results of our research.
In future studies, exercise location preferences can be customized according to exercise types. Interventional studies are limited in the literature. Studies with high evidence value are needed, especially nursing area. Researchers are recommended to use this suggestion. Finally, it is recommended that such studies be examined in different age groups. For example, it would be valuable to conduct studies on the exercise preferences and needs of children, disabled, or disadvantaged individuals. Public health nurses can be supported by the results of this study when encouraging physical people to engage in activity to stay healthy.
Author Contributions
Conceptualization: Fatma Avsar and Nildem Kizilaslan. Methodology: Fatma Avsar and Nildem Kizilaslan. Software/Formal analysis: Fatma Avsar. Validation: Fatma Avsar. Investigation: Fatma Avsar and Nildem Kizilaslan. Resources: Fatma Avsar and Nildem Kizilaslan. Data Curation: Fatma Avsar and Nildem Kizilaslan. Writing—Original Draft: Fatma Avsar. Writing—Review and Editing: Fatma Avsar and Nildem Kizilaslan. Visualization: Fatma Avsar. Supervision: Nildem Kizilaslan. Design: Fatma Avsar. Literature review: Fatma Avsar and Nildem Kizilaslan. Language: Fatma Avsar.
Ethics Statement
In order to evaluate the ethical appropriateness of the research; necessary permissions were obtained from Tokat Gaziosmanpasa University, Social and Human Sciences Research Ethics Committee (24.03.2022 date, decision no. 06.03‐148260). Written consent was obtained from the students participating in the study.
Conflicts of Interest
We declare no conflict of interest for the manuscript. All procedures performed in this study were in accordance with the ethical standards of Tokat Gaziosmanpasa University and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Acknowledgments
We thank the participants in our study. Also, our thanks to the gym and outdoor exercises, sports group managers, and staff.
Funding: Open access funding was provided by TUBITAK. The author received no specific funding for this work.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request from fatma.avsar@gop.edu.tr.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request from fatma.avsar@gop.edu.tr.