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Article

Social-Ecological Factors Predict College Students’ Physical Activities and Sedentary Behavior

by
Tao Zhang
1,*,
Joonyoung Lee
2,
Xiaoxia Zhang
3 and
Xiangli Gu
4
1
Department of Kinesiology, Health Promotion and Recreation, University of North Texas, Denton, TX 76203, USA
2
Department of Health, Physical Education, and Recreation, Jackson State University, Jackson, MS 39217, USA
3
Department of Kinesiology, Centenary College of Louisiana, Shreveport, LA 71104, USA
4
Department of Kinesiology, University of Texas at Arlington, Arlington, TX 76019, USA
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(19), 12873; https://doi.org/10.3390/su141912873
Submission received: 25 August 2022 / Revised: 5 October 2022 / Accepted: 7 October 2022 / Published: 9 October 2022
(This article belongs to the Special Issue Adolescents' Self-Exploration and Physical Activity in Leisure Experience)
Versions Notes

Abstract

:
Guided by the socio-ecological model, the aim of this study was to investigate the predictive strengths of individual, social, and physical environmental factors toward different intensities of physical activity (PA; vigorous PA, moderate PA, walking) and sedentary behavior (SB) among college students. A cross-sectional research design was used. There were 287 college students (Mage = 20.75 ± 2.91; 54% female) recruited from a public research university in the Southwestern United States. Participants completed previously validated questionnaires assessing their PA, SB, and perceptions of self-efficacy, social support, and physical environment variables. Correlation and hierarchical regression analyses were performed to examine the associations and the relative contributions of those individual, social, and physical environmental factors to PA and SB, respectively. The findings indicated that self-efficacy, social support from friends, and convenience of using exercise facilities were positively correlated with vigorous PA. Self-efficacy and physical environmental factor such as convenience of using exercise facilities were significantly associated with students’ moderate PA. Physical environmental factors, including convenience of using exercise facilities, satisfaction with neighborhood services, ease of walking to public transportation stop, and detached single-family residence were significantly related to walking, while only detached single-family residence was associated to SB. The results highlight PA interventions may do well to focus on the promotion of individual and environmental variables to increase PA in college students. More evidence is needed to determine the relationships between social ecological factors and SB.

1. Introduction

According to Healthy People 2030 [1], there is substantial evidence that participation in regular physical activity (PA) across the life-span is an influential factor in maintaining an individual’s physical and mental health (e.g., weight control, quality of life). Regular PA participation, even at lower doses, is associated with reduced risk of all-cause mortality and is an effective strategy (strong or moderate evidence of effect) for the prevention and treatment for a variety of chronic conditions [2]. On the other hand, physical inactivity and/or excessive sedentary behaviors (SB) have been found to increase the risk of all-cause and cardiovascular disease mortality [3], obesity, and type 2 diabetes [4,5], as well as different types of cancers [6].
Despite the health benefits of regular PA participation, appropriately 60% of young adults, especially college students, fail to meet national PA guidelines (at least 150 min of moderate PA or 75 min of vigorous PA) [7,8]. It is reported that U.S. college students spend over 10 h daily being sedentary on average, and around 44% sit more than 11 h [9]. There is also a consistently high proportion (32.9%) of college students being overweight and obese [8]. Notably, the lifestyles developed during college years will likely persist throughout adulthood [1,10,11,12]; hence, it is critical to help college students establish healthy and active lifestyles. In recent years, the COVID-19 pandemic has been challenging to individuals’ work, education, recreation, and engagement in PA and SB. Several studies reported that college students spent significantly less time performing PA and more on SB during the COVID-19 pandemic when compared to the pre-COVID-19 period [13,14,15]; however, there was also a group of studies that showed mixed findings (e.g., increased both PA and SB during the COVID-19 era or decreased PA during lockdown, followed with an increasing trend). These incongruent findings indicate that young adults’ behavior is influenced by multiple factors given the restrictions on college students’ life during the COVID-19 pandemic. Thus, comprehensive approaches are needed to address the prevalence of physical inactivity, SB, and high rate of obesity among college students [16].
The socio-ecological model has been recognized as a promising theoretical model in understanding PA behaviors [17]. This model emphasizes the multi-level influential factors towards PA promotion, including individual-level factors (e.g., self-efficacy, attitude), social environmental factors (e.g., social support from friends and family), and physical environmental factors (e.g., satisfaction with neighborhood services, convenience of using exercise facilities). The basic assumption of the socio-ecological model is that individuals’ behaviors are the result of interactions among individual, social, and physical environmental factors occurring with a specific behavioral setting [17]. To date, research focused on PA promotions has primarily investigated the individual-level factors (e.g., attitudes and self-efficacy) and suggested that high self-efficacy promotes a strong sense of commitment to PA behaviors [18,19,20,21,22]. A burgeoning research direction has started to investigate the roles of the social and physical environmental factors on PA behaviors. Researchers pointed out that family and peer support at the social environmental level can add significant impact on PA and SB in addition to individual factors [23,24].
Little attention, however, has focused on the contributions of physical environmental factors in addition to the individual and social environmental factors on PA and SB. The emerging evidence indicated that physical environmental factors, especially the neighborhood environment, was also a significant correlate of PA behaviors [25,26]. For instance, a longitudinal study indicated that college students who were living off campus significantly decreased PA across years comparing to those living on campus [27]. One recent study suggested that the built environment and/or neighborhood socioeconomic status (SES) are associated with SB but not leisure-time PA among Spanish university students [28]. Castro and colleagues [29] also noted in their review that the majority of correlates of SB were intrapersonal, with a limited number of studies having examined interpersonal and environmental factors. For example, individual-level factors, such as self-efficacy, have been reported to correlate with SB among college students [30]. It was also noticed that individuals’ SB was influenced by their peers’ perceptions and PA behaviors [31]. Physical environment, such as living in lower-SES neighborhoods and those with a higher risk of crime, were associated with more sedentary lifestyles than those living in higher-SES neighborhoods [28]. Considerable increases in physical inactivity among college students suggest the need to examine the modifiable factors toward the prevalence of SB. Decreasing time spent in SB and increasing time spent in PA are related but also independent; thus, examining the combined effects of individual, social, and physical environment on both PA and SB among young adults is urgent, which will expand the existing literature of the socio-ecological framework [17,29].
The influence of social environmental and physical environmental factors on college students’ different intensities of PA and SB is still unclear, representing an essential line of research. The socio-ecological model would provide a promising and comprehensive understanding of college students’ different intensity levels of PA participation and SB [17]. The primary purpose of this study, therefore, was to investigate the associations of individual, social environmental, and physical environmental factors with different intensity levels of PA (vigorous PA, moderate PA, and walking) and SB among college students guided by the socio-ecological model. We hypothesize that the individual, social environmental, and physical environmental factors will have different associations with PA behaviors (vigorous PA, moderate PA, and walking) and SB.

2. Materials and Methods

2.1. Sample

Convenience sampling was used in this study. A total of 287 college students (Mage = 20.75 ± 2.91; 54% female) were recruited from a public university in the Southwestern United States. In the sample, 76% lived in apartment/condo settings, 13% lived with parents, 6% lived in a residential hall, and 5% lived in fraternity/sorority housing. Participants were 77% White, 16% African American, 3% Asian American, and 4% from other ethnic backgrounds. The sample size was large enough to generate statistically significant findings (N > 226, G*power 3.1) [32].

2.2. Measures

2.2.1. Demographic Variables

Participants provided basic demographic information, including their gender, age, race, and current living arrangement.

2.2.2. Self-Efficacy

Students’ self-efficacy for PA was measured using the questionnaire developed by Sallis et al. [33]. This measure is a 12-item self-report inventory that assesses students’ confidence to engage in PA when faced with common barriers. Participants rated each of the 12 statements by responding to the stem, “How sure are you that you can do these things?” A sample statement was: “Stick to your exercise program when social obligations are very time consuming”. A 5-point Likert scale, ranging from 1 (I know I cannot) to 5 (I know I can), was used for all responses. Acceptable internal consistency (Cronbach’s a = 0.85), test–retest reliability (r = 0.68), and validity have been reported for this measure [33]. In the present study, the internal consistency showed a sufficient reliability score (a = 0.91).

2.2.3. Social Support from Friends and Family

The perceived social support from friends and family was assessed with a modified version of the parent–peer support scale developed by Prochaska, Rodgers, and Sallis [34]. The scale consists of a total of ten items, five addressing friends’ support and five addressing family support. The stem for these items was “During a typical week, how often…” Items related to friend’s support included questions about encouragement and praise from friends and engaging in activities with friends. Questions assessing family support focus on providing encouragement and praise, engaging in activities, and providing support, such as transportation. One sample item was: “A member of your household encouraged you to do physical activities or play sports”. Students rated each item on a 5-point Likert scale, ranging from 1 (none) to 5 (every day). The average scores of social support from friends and social support from family were calculated. In this study, the score of internal consistency indicated good reliability, 0.73 for social support from friends, and 0.87 for social support from family.

2.2.4. Physical Environment

To measure students’ perceptions of environmental variables relevant to PA and SB, participants completed a previously validated 81-item instrument developed and used by previous studies [35,36]. This instrument assesses neighborhood environmental variables believed to be related to walking and cycling for transportation and leisure. The physical environmental variables included residential density (detached single-family residence, row house, and apartment), land use mix (diversity of uses and access to local shopping), ease of walking to public transportation stops, availability of sidewalks, availability of bike lanes, neighborhood aesthetics, perceived safety from crime, perceived safety from traffic, connectivity, satisfaction with neighborhood services, emotional satisfaction with neighborhood, PA equipment in home environment, neighborhood features, and convenience of using exercise facilities [35,36]. In the present study, a neighborhood was defined as the university campus if students lived on-campus. If the participant lived off-campus, the neighborhood was defined as a half-mile radius or a 10-miniute walk from the respondent’s home. Each scale consists of four-to-seven-point Likert scales. The mean of each subscale’s item was calculated. The physical environment variables showed adequate single-measure test–retest reliability intraclass correlation coefficients (ranged 0.40–0.97) in the previous study [35,36].

2.2.5. PA and SB

To measure students’ different intensities of PA and SB, the 7-item short-version of the International PA Questionnaire-Short Form (IPAQ-SF) was used to determine the time spent being physically active in the last 7 days [37]. Participants reported vigorous PA, moderate PA, walking, and SB that they had performed in the last 7 days. The IPAQ instruments are recommended as a viable method of monitoring population levels of PA and SB globally for a population of 15–69 years of age [37]. Individuals’ metabolic equivalent (MET)-mins can be computed for vigorous PA, moderate PA, and walking using the following formula: MET level (i.e., MET vigorous = 8.0; MET moderate = 4.0; MET walking = 3.3) × mins of activity/day × days per week). The mean score for each intensity level of PA was used for the MET score in this study. The IPAQ-SF also includes items regarding time spent sitting as a domain of SB. Validity and reliability results in 12 countries demonstrate that the IPAQ has comparable reliability and validity to other self-report measures of PA and SB [37].

2.3. Procedures

After obtaining the approval of the Institutional Review Board (IRB), the researchers recruited participants through multiple lecture courses in the university, such as Principles of Health, Introduction to Kinesiology, Sociology of Sport, and Scientific Principles and Practices of Health-related Fitness. Participants voluntarily participated in the study and were provided written informed consent. Researchers administered and collected questionnaires during regularly scheduled lecture classes at the end of the semester. Participants were told that their answers would be confidential, and they were asked to complete self-reported surveys as honestly and completely as possible. The data collection sessions took appropriately 20–30 min.

2.4. Data Analysis

Prior to the data analysis, data were cleaned and screened for accuracy and normality. Given the non-normal distribution of energy expenditure (MET score), a logarithmic transformation was used to improve the normality of the distribution for energy expenditure of college students’ vigorous PA, moderate PA, walking, and SB [35]. After logarithmic transformation, the assumptions for executing hierarchical regression analyses were met for all dependent and independent variables.
All statistical analyses were conducted using SPSS 28.0 (IBM Corp., Armonk, NY, USA). The data were analyzed through three steps. First, descriptive statistics were used to summarize participants’ demographic characteristics. Second, Pearson correlations were calculated to examine the associations among study variables. Finally, four hierarchical linear regression analyses were performed to assess the predictive strengths of college students’ self-efficacy, social support from friends and family, and physical environmental variables (independent variables) on students’ vigorous PA, moderate PA, walking, and SB (dependent variables). Specifically, self-efficacy was entered in the first block of the model, followed by social support from friends and family in the second block, and then physical environmental variables in the third block [38]. The alpha level of 0.05 was used for all statistical analyses.

3. Results

3.1. Descriptive Analyses

Means (M) and standard deviations (SD) for the perceptions of self-efficacy, friends’ support, family’s support, and physical environmental variables are reported in Table 1. The mean scores of the study variables in this sample were displayed as follows: self-efficacy (M = 3.62, SD = 0.79), friend’s support (M = 3.40, SD = 0.69), family’s support (M = 2.81, SD = 1.05), detached single-family residence (M = 1.87, SD = 0.75), townhouse/row house (M = 1.91, SD = 0.80), apartment/condo (M = 2.31, SD = 0.80), dormitory/residential housing (M = 1.61, SD = 0.82), land use mix-diversity (M = 2.99, SD = 0.91), land use mix-access to local shopping (M = 2.56, SD = 0.83), ease of walking to public transportation stop (M = 3.08, SD = 1.17), availability of sidewalks (M = 3.00, SD = 1.10), availability of bike lanes (M = 2.50, SD = 0.86), neighborhoods aesthetic (M = 2.85, SD = 0.68), perceived safety from crime (M = 3.17, SD = 0.81), perceived safety from traffic (M = 2.54, SD = 0.68), street connectivity (M = 2.51, SD = 0.84), satisfaction with neighborhood services (M = 4.56, SD = 1.54), emotional satisfaction with neighborhood (M = 4.64, SD = 1.25), physical activity equipment in home environment (M = 5.45 SD = 2.94), neighborhood features (M = 5.88, SD = 1.41), convenience of using exercise facilities (M = 10.63, SD = 4.23), vigorous PA (M = 2.47, SD = 1.49), moderate PA (M = 2.25, SD = 1.33), walking (M = 2.49, SD = 1.17), and SB (M = 1.76, SD = 1.10).

3.2. Correlations

The associations among social-ecological factors and vigorous PA, moderate PA, walking, and SB are presented in Table 1. Correlation analyses revealed significant positive associations of self-efficacy, friends’ support, and family’s support with students’ vigorous PA and moderate PA (r ranged from 0.20 to 0.40). Among physical environmental factors, the convenience of using exercise facilities was significantly correlated with students’ vigorous PA, moderate PA, and walking (r ranged from 0.22 to 0.23). Emotional satisfaction with their neighborhood was significantly associated with students’ vigorous PA (r = 0.12). Satisfaction with neighborhood services, emotional satisfaction with neighborhood, and satisfaction with neighborhood features were significantly and positively related to walking (r ranged from 0.12 to 0.13). Detached single-family residence, ease of walking to public transportation stops, availability of bike lanes, and satisfaction with neighborhood services demonstrated significant associations with students’ SB (r ranged from 0.12 to 0.17). Different intensity levels of PA and SB were positively correlated one another (r ranged from 0.19 to 0.45). No significant associations were found for any of the other physical environment variables.

3.3. Hierarchical Linear Regressions

Results of the hierarchical regression analyses are summarized in Table 2. For vigorous PA, the overall model accounted for 25% of the variance. In the first block, self-efficacy (β = 0.36, p < 0.01) was significantly related to students’ vigorous PA, accounting for 13% of the variance. In the second block, friends’ support (β = 0.28, p < 0.01) and self-efficacy (β = 0.22, p < 0.01) were significantly associated with students’ vigorous PA, accounting for an extra 7% of variance in vigorous PA. In the third block, friends’ support (β = 0.27, p < 0.01), self-efficacy (β = 0.22, p < 0.01), and convenience of using exercise facilities (β = 0.13, p < 0.05) were significantly related to vigorous PA.
For moderate PA, the overall model accounted for 14% of variances. In addition to self-efficacy (β = 0.14, p < 0.05), physical environmental factors such as convenience of using exercise facilities (β = 0.20, p < 0.05) accounted for an extra 6% of variances on moderate PA. For walking, the final model accounted for 13% of the variance. Only physical environmental factors, including the convenience of using exercise facilities (β = 0.24, p < 0.01), satisfaction with neighborhood services (β = 0.19, p < 0.05), ease of walking to public transportation stop (β = −0.18, p < 0.05), and detached single-family residence (β = 13, p < 0.05) were significantly related to walking. For SB, the overall model accounted for 10% of variance, and detached single-family residence (β = 0.19, p < 0.01) was the only significant predictor in this study.

4. Discussion

The primary purpose of this study was to understand the associations of individual, social, and physical environmental variables with different intensities of PA and SB among college students through a comprehensive social-ecological perspective. Our findings highlight the importance of investigating multi-level correlators of PA and SB.
In line with recent studies [19,21,22], our findings identified that self-efficacy was significantly correlated with vigorous PA and moderate PA. To date, few researchers have assessed the predictive strengths of the self-efficacy and the three different intensities of PA among college students. Our findings indicated that self-efficacy appears to be the most influential under challenging circumstances, which is engaging in vigorous PA and moderate PA. This finding provides initial support for the utility of enhancing an individual’s targeting self-efficacy as a potential means of increasing vigorous and moderate PA behaviors among college students [39].
Furthermore, as college students enter young adulthood, the relative influence of family members lessens while friends begin to take on a greater role in determining PA behaviors. This is in line with developmental psychologists’ findings that family’s support diminished during college years [39]. In the present study, social support from friends was related to students’ vigorous PA. This is in accordance with previous studies indicating that friends’ support provides a considerable amount of influence on PA levels among adolescents and college students [11,34,40]. Friends’ support, therefore, holds considerable potential as a contributor of effective PA interventions for college students. This finding suggests interventions should target strengthening existing supportive ties with friends, developing new ties, or utilizing indigenous helpers.
In the present study, convenience of using exercise facilities was an important predictor of students’ vigorous PA, moderate PA, and walking. The convenience of using exercise facilities refers to whether exercise facilities (e.g., basketball court, dance studio, public park) are on a frequently traveled route or within a 5 min drive from home/school. Based on our finding, the more exercise facilities that are geographically easier to be accessed, the more college students were likely to be engaging in PA at all intensity levels. This finding is also aligned with previous studies that college students’ PA intensity and duration were positively associated with proximity of exercise facilities [41,42]. It is suggested that the distance from exercise facilities as small as one mile or one-half mile can impact the amount of PA participation [43]. Thus, it is necessary to provide sufficient exercise facilities in order to promote college students’ different intensities of PA. In addition, more physical environmental factors (e.g., residential density, ease of walking to public transportation stops, satisfaction with neighborhood services) were associated with light PA (i.e., walking) compared to vigorous PA and moderate PA. Previous studies also indicated that the influence of physical environmental factors is relatively more important for light PA rather than moderate and vigorous PA [44,45]. Modifications to the physical environment, such as increased safety of neighborhood services, might be effective in fostering engagement in light PA among college students.
It is worth noting that the percent variance accounted for by these physical environmental factors, however, is relatively small. This might be due to other potential factors, such as motor competence, motivation, physical literacy, and goal settings, that have been suggested to influence individual’s PA engagement [46,47,48,49,50]. Given the small variance explained, increasing light PA may be very important in efforts to increase the regular PA of college students who adopt sedentary lifestyles. Increasing their time spent walking has the potential to yield significant health benefits for this population [45].
Another unique finding of this study was that low residential density emerged as a significant predictor on SB among these college students. College students who live in a low residential area are likely to sit more. One possible reason might be that people living in a low-density community tend to experience higher levels of social isolation. Consistent with previous research that increasing social isolation was related to high risk of SB among adolescents and older adults [51,52], this finding suggests strengthening the social connections for less SB among college students who live in low-residential-density areas. Colleges and communities may establish PA-related health promotion strategies and support by providing some light exercise facilities in open areas or creating social events (e.g., Friday night out in the yard, monthly walk events) and social interaction among college student residents.
On the other hand, our research did not find associations between SB and the other factors, including self-efficacy, social support from friends and family, and the rest of the physical environment factors. Research has shown a wide range of associations between self-efficacy and SB [53] and a lack of standardized measures of factors related to SB [54]. As the first attempt to examine these three layers of social ecological factors on SB among college students simultaneously, more evidence is required to support or refute this finding. Our findings did not find the significant association between convenience of using exercise facilities and SB. However, it is worth noting that the satisfaction with neighborhood services was related to both walking and SB among this population. It suggests a special focus on modifiable correlates in addressing the issue of accelerated sedentary behavior in college students. In this regard, physical activity promotion programs in colleges may focus on promoting active commuting and neighborhood/campus design, and building more walkable and bikeable environments. The findings of this study can provide practical implications aiming to promote different intensities of PA and decrease SB among college students.
Several limitations in the present study need to be acknowledged. First, different intensities of PA and SB were assessed through self-report survey, which may result in overestimated results. More accurate and objective instruments that assess PA and SB, such as accelerometers, should be included in future studies. Second, a causal relationship cannot be inferred in the present study because of the cross-sectional research design. Longitudinal or experimental research design, therefore, is needed to investigate the temporal relations among individual, social environmental, physical environmental factors, and different intensities of PA and SB in the future endeavors. Finally, given that socio-demographic differences, such as gender and race, exist in PA and SB levels among college students [55], future research is needed to examine gender and race differences in the socio-ecological variables of PA and SB.

5. Conclusions

In summary, using the socio-ecological model as an organizational framework, the present study adds to the growing body of evidence examining how individual, social, and physical environmental factors influence college students’ different intensities of PA and SB. Directions for future research should target self-efficacy, social support from friends, and physical environmental variables such as the convenience of using exercise facilities when developing effective interventions for college students. PA interventions may do well to focus on the establishment and promotion of individual and environmental variables to promote PA in college students. More evidence is needed to determine the relationships between social ecological factors and SB.

Author Contributions

Conceptualization, T.Z.; methodology, T.Z. and J.L.; software, T.Z. and J.L.; validation, J.L., X.Z. and X.G.; formal analysis, T.Z. and J.L.; investigation, T.Z.; resources, T.Z.; data curation, J.L. and X.Z.; writing—original draft preparation, T.Z., J.L., X.Z. and X.G.; writing—review and editing, T.Z., J.L., X.Z. and X.G.; visualization, T.Z., J.L., X.Z. and X.G.; supervision, T.Z.; project administration, T.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Louisiana State University’s Institutional Review Board (protocol code 3258).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Acknowledgments

We want to thank the course instructors for supporting our data collection in their classes. A special thanks to all students that participated in our study.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Descriptive statistics among variables and correlations (N = 287).
Table 1. Descriptive statistics among variables and correlations (N = 287).
VariablesRangeM ± SDVigorous PAModerate PAWalkingSB
Self-efficacy1–53.62 ± 0.790.36 **0.23 **0.100.04
Friends’ support1–53.40 ± 0.690.40 **0.23 **-0.020.02
Family’s support1–52.81 ± 1.050.27 **0.20 **−0.020.06
Detached single-family residence1–31.87 ± 0.75−0.010.060.100.17 **
Townhouse/Row house1–31.91 ± 0.800.010.01−0.040.07
Apartment/Condo1–32.31 ± 0.80−0.02−0.03−0.020.03
Dormitory/Residential housing1–31.61 ± 0.820.060.020.050.01
Land use mix—diversity1–52.99 ± 0.910.040.040.040.05
Land use mix—access to local shopping1–42.56 ± 0.830.070.090.100.02
Ease of walking to public transportation stops1–43.08 ± 1.170.050.10−0.020.13 *
Availability of sidewalks1–43.00 ± 1.100.060.010.050.08
Availability of bike lanes1–42.50 ± 0.860.010.020.050.12 *
Neighborhood aesthetics1–42.85 ± 0.68−0.030.070.060.01
Perceived safety from crime1–43.17 ± 0.810.02−0.020.100.10
Perceived safety from traffic1–42.54 ± 0.680.060.090.050.04
Street connectivity1–42.51 ± 0.840.050.010.040.03
Satisfaction with neighborhood services1–74.56 ± 1.540.070.110.13 *0.13 *
Emotional satisfaction with neighborhood1–74.64 ± 1.250.12 *0.080.13 *0.11
Physical activity equipment in home environment1–155.45 ± 2.940.100.060.050.01
Neighborhood features1–85.88 ± 1.410.060.050.12 *0.10
Convenience of using exercise facilities1–1810.63 ± 4.230.22 **0.23 **0.23 **0.08
Vigorous PA0–4.232.47 ± 1.49-0.45 **0.19 **0.21 **
Moderate PA0–4.072.25 ± 1.33 -0.39 **0.28 **
Walking0–3.742.49 ± 1.17 -0.29 **
SB0–2.911.76 ± 1.10 -
Note. M = mean; SD = standard deviation; PA = physical activity; SB = sedentary behavior; ** p < 0.01, * p < 0.05.
Table
Table 2. Hierarchical regression of the social ecological factors on PA and SB (N = 287).
Table 2. Hierarchical regression of the social ecological factors on PA and SB (N = 287).
PredictorsVigorous PAModerate PAWalkingSB
R2∆R2βFR2∆R2βFR2∆R2βFR2∆R2βF
Block 10.130.13 41.80 **0.050.05 15.93 **0.010.01 2.700.010.01 0.55
Self-efficacy 0.36 ** 0.23 ** 0.11 0.04
Block 20.200.07 23.83 **0.080.03 8.05 **0.020.01 1.410.010.01 0.42
Self-efficacy 0.22 ** 0.15 * 0.13 * 0.03
Friends’ support 0.28 ** 0.11 −0.06 −0.02
Family’s support 0.05 0.11 −0.04 0.06
Block 30.250.05 4.20 **0.140.06 2.06 **0.130.11 1.84 **0.100.09 1.32
Self-efficacy 0.22 ** 0.14 * 0.10 0.01
Friends’ support 0.27 ** 0.11 −0.04 −0.01
Family’s support 0.01 0.06 −0.10 0.06
Detached single-family residence −0.02 0.04 0.13 * 0.19 **
Townhouse/Row house 0.05 0.03 −0.03 0.05
Apartment/Condo −0.08 −0.08 0.02 −0.01
Dormitory/ Residential housing 0.02 −0.04 0.08 −0.04
Land use mix—diversity 0.01 −0.02 −0.01 0.06
Land use mix—access to local shopping 0.01 −0.01 −0.04 −0.06
Ease of walking to public transportation stops 0.04 0.11 −0.18 * 0.11
Availability of sidewalks 0.01 −0.08 −0.02 0.01
Availability of bike lanes −0.04 −0.05 −0.04 0.05
Neighborhood aesthetics −0.13 0.05 −0.02 −0.08
Perceived safety from crime 0.01 −0.03 0.11 0.11
Perceived safety from traffic 0.05 0.10 0.02 0.04
Street connectivity 0.08 0.03 0.04 0.04
Satisfaction with neighborhood services −0.04 0.04 0.19 * 0.08
Emotional satisfaction with neighborhood 0.13 0.01 −0.02 0.05
Physical activity equipment in home environment 0.01 −0.06 −0.03 −0.04
Neighborhood features 0.01 −0.01 0.07 0.03
Convenience of using exercise facilities 0.13 * 0.20 ** 0.24 ** 0.03
Note. R2 values are cumulative, with each incremental step adding to the variance explained; β values are standardized regression coefficients from the final stage of the regression analysis. PA = physical activity; SB = sedentary behavior; ∆R2 = R2 Change. ** p < 0.01, * p < 0.05.
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Zhang, T.; Lee, J.; Zhang, X.; Gu, X. Social-Ecological Factors Predict College Students’ Physical Activities and Sedentary Behavior. Sustainability 2022, 14, 12873. https://doi.org/10.3390/su141912873

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Zhang T, Lee J, Zhang X, Gu X. Social-Ecological Factors Predict College Students’ Physical Activities and Sedentary Behavior. Sustainability. 2022; 14(19):12873. https://doi.org/10.3390/su141912873

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Zhang, Tao, Joonyoung Lee, Xiaoxia Zhang, and Xiangli Gu. 2022. "Social-Ecological Factors Predict College Students’ Physical Activities and Sedentary Behavior" Sustainability 14, no. 19: 12873. https://doi.org/10.3390/su141912873

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