Availability of sports facilities as moderator of the intention–sports participation relationship among adolescents

Health Education Research, Jun 2010

Prins, Richard G., van Empelen, Pepijn, te Velde, Saskia J., Timperio, Anna, van Lenthe, Frank J., Tak, Nannah I., Crawford, David, Brug, Johannes, Oenema, Anke

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Availability of sports facilities as moderator of the intention–sports participation relationship among adolescents

Availability of sports facilities as moderator of the intention-sports participation relationship among adolescents Richard G. Prins 0 3 Pepijn van Empelen 0 3 Saskia J. te Velde 1 3 Anna Timperio 2 3 Frank J. van Lenthe 0 3 Nannah I. Tak 1 3 David Crawford 2 3 Johannes Brug 1 3 Anke Oenema 0 3 0 Department of Public Health, Erasmus University Medical Center , PO Box 2040, 3000 CA, Rotterdam , The Netherlands 1 EMGO Institute for Health and Care Research and the Department of Epidemiology and Biostatistics, VU University Medical Center , Van der Boechorststraat 7, 1081 BT, Amsterdam , The Netherlands 2 Centre for Physical Activity and Nutrition Research, Deakin University , 221 Burwood Highway, Burwood, VIC 3125 Australia 3 The Author 2010. Published by Oxford University Press. All rights reserved. Downloaded from https://academic.oup.com/her/article-abstract/25/3/489/656624 by guest on 01 This longitudinal study aimed to identify individual and environmental predictors of adolescents' sports participation and to examine whether availability of sports facilities moderated the intention-behaviour relation. Data were obtained from the ENvironmental Determinants of Obesity in Rotterdam SchoolchildrEn study (2005/2006 to 2007/2008). A total of 247 adolescents (48% boys, mean age at follow-up 15 years) completed the surveys at baseline and follow-up. At baseline, adolescents completed a survey that assessed engagement in sports participation, attitude, subjective norm, perceived behavioural control and intention towards sports participation. Availability of sports facilities (availability) was assessed using a geographic information system. At follow-up, sports participation was again examined. Multiple logistic regression analyses were conducted to test associations between availability of sports facilities, theory of planned behaviour variables and the interaction of intention by availability of sports facilities, with sports participation at follow-up. Simple slopes analysis was conducted to decompose the interaction effect. A significant availability 3 intention interaction effect [odds ratio: 1.10; 95% confidence interval: 1.00-1.20] was found. Simple slopes analysis showed that intention was more strongly associated with sports participation when sports facilities were more readily available. The results of this study indicate that the intention-sports participation association appears to be stronger when more facilities are available. Introduction Promoting physical activity (PA) is an important public health priority [ 1?3 ]. Besides daily activities of moderate intensity, more intensive sport activities to increase physical fitness are also recommended, especially for children and adolescents [ 4 ]. Moderate and higher intensity activities are beneficial for health, quality of life and social integration during adolescence, as well as later in life [ 2, 3, 5? 7 ]. Furthermore, continuous PA throughout youth increases the probability of becoming an active adult [ 8 ]. However, even though many adolescents in Western countries engage in sports activities when they are younger [ 9 ], engagement in sports declines rapidly during adolescence [ 9, 10 ]. Thus, it is important to promote sports participation in adolescence. To do this efficiently, interventions should be theory and evidence based [11] and intervene on important modifiable behavioural determinants [ 12 ]. The present study aims to identify individual and environmental determinants of sports participation and their potential interplay. According to socio-ecological models [ 13?15 ] and extended motivational models [ 16 ], behaviour is not only determined by predictors at the individual level (i.e. cognitions) but also by environmental factors, such as availability of sports facilities. These models also assume an interplay between individual cognitions and environmental factors through mediation [ 14 ] or moderation [ 16 ]. Until recently, most studies, exploring determinants of PA and sports participation, focused on the individual level correlates, such as derived from the theory of planned behaviour (TPB) [ 17, 18 ]. According to the TPB, behavioural intention (i.e. the decision to engage in a specific behaviour) is the most proximal determinant of behaviour [19]. Intention in turn is determined by attitudes, subjective norm and perceived behavioural control (PBC). Attitudes refer to a person?s evaluation of the advantages and disadvantages of engagement in a specific behaviour. Subjective norm is related to the perception of what important others think you should do. Perceived behavioural control refers to the perceived ease or difficulty of performing a specific behaviour. The few studies available that used the TPB for explaining sports participation did not find consistent results with regard to the predictability of intention on sports behaviour. Other studies have focussed on built environmental factors, such as the availability and accessibility of PA opportunities, as potential determinants of sports participation among adolescents [ 20, 21 ]. There are, however, few studies that take both individual and environmental determinants of sports participation and their interrelationship into account, and the studies that have done so mainly have relied on a cross-sectional design, weakening the interpretation of the relationships. In the present study, the potential moderating effect of environmental-level predictors on the intention?behaviour relation suggested by Fishbein [ 16 ] in the extended TPB model is examined. According to this model, the environment, such as the availability of sports facilities, can act as a facilitator for behaviour. Hence, when sports facilities are available, people are more likely to act on their positive intentions, suggesting a stronger intention? behaviour association in circumstances of high availability. Insight into these mechanisms may help to shape PA promotion interventions for adolescents and may contribute to the explanation of the intention?behaviour gap, as has been observed for PA and other behaviours [ 18, 22 ]. Few studies have examined the role of environmental factors on the intention?behaviour association. One study found that the proximity to recreational facilities moderates the intention? walking behaviour association in adults [ 23 ], while another found no evidence of moderation of active transportation among students [ 24 ]. Both studies used a self-report measure of the built environment, which was seen as an important limitation [ 23 ]. The aim of the present longitudinal study was to identify individual and environmental predictors of adolescent sports participation and to examine if the objective availability of sports facilities moderates the intention?behaviour relationship. We hypothesized that (i) intentions are significantly associated with sports participation at follow-up, (ii) objectively measured availability of sports facilities is associated with sports participation at follow-up and (iii) objectively measured availability of sports facilities moderates the association between intention at baseline and sports participation at followup, with more facilities contributing to a stronger intention?behaviour relationship. Methods This study draws on longitudinal data from the study on ENvironmental Determinants of Obesity in Rotterdam SchoolchildrEn (ENDORSE). The ENDORSE study was conducted in Rotterdam in 2005?2006 (baseline) and 2007?2008 (follow-up) among adolescents in the first and third year of secondary education. This is an age period in which considerable declines in sports participation can be expected [ 25, 26 ]. Rotterdam is the second largest city of The Netherlands, with approximately 600 000 inhabitants, of which 46% are of non-Dutch origin [27]. The medical ethics committee of the Erasmus University Medical Center in Rotterdam issued a ?declaration of no objection? for the study. A detailed description of the study protocol is published elsewhere [ 28 ]. Sampling and procedure At baseline, 56 schools were approached to take part in the study and 24 schools were willing to participate. A random selection of 17 of these schools participated in the study. These schools were selected after stratification according to the area of the city in which they were located (north, south, east or city centre) to ensure a range of physical and cultural environments. Approximately five classes within each school were selected for the study. Thirteen schools had classes with adolescents in their first year of secondary education at baseline, and these schools were included in the present study. During one school hour, the adolescents completed a printed questionnaire on dietary and PA behaviours and potential determinants of these behaviours in the presence of a research assistant and a teacher. In this paper, we analysed the data on sports behaviour from ENDORSE and additional objective measures of availability of sports facilities in the local neighbourhood. Only adolescents who lived in neighbourhoods within the city of Rotterdam that were not adjacent to other municipalities were eligible for analyses because objective environmental data were only available for Rotterdam. A total of 488 adolescents met this inclusion criterion at baseline. Measures Physical activity An adapted version of the Activity QUestionnaire for Adolescents and Adults (AQUAA) [ 29 ] was used to assess PA levels at baseline and followup. The AQUAA showed a fair to moderate test? retest reproducibility, with intra-class correlations ranging from 0.44 to 0.59. Items related to frequency of sports participation were used in this paper. Adolescents were asked to name up to three sports they had participated in during the previous week and indicate on how many days of the week (0?7 days) they had participated in each sports activity. An overall measure of frequency of sports participation per week was created by summing the frequencies of the reported sports activities at baseline and at follow-up, respectively. These variables were collapsed into two categories [yes (1), participated in some sports and no (0), did not participate in any sports] due to the skewed distribution. TPB measures All TPB variables were measured at baseline using five-point response scales. Attitude was assessed by two items using semantic differential response scales ?I think that sports and leisure time physical activity are .? [very good (5) to very bad (1) and very pleasant (5) to very unpleasant (1)]. Cronbach?s alpha of the attitude items was 0.80 and a mean attitude score was calculated. PBC was assessed by two items, assessing perceived capability and control (Cronbach?s alpha = 0.27). However, as the Cronbach?s alpha was low, it was decided to use these items as separate scales in the analyses. Capability was assessed by the item ?How easy or difficult would it be for you to engage in sports or leisure time physical activity if you want to?? [very easy (5) to very difficult (1)]. Control was assessed by the item ?To what extent do you decide for yourself to engage in sports or leisure time physical activity?? [I decide it all by myself (5) to I do not decide this by myself at all (1)]. One item was used to assess parental subjective norm: ?If I engage in sports or physical activity, my parents think that this is .?? [very good (5) to very bad (1)]. Intention was also assessed by one item: ?Do you plan to start/remain engaging in sports and physical activity in the next half year?? [yes certainly (5) to certainly not (1)]. Objective physical environment Geographical information system (GIS) data on the availability of sports facilities at baseline were retrieved from a database managed by the municipality of Rotterdam. This database contains geographical co-ordinates of sports facilities (including sports halls, skate parks, fitness centers, sporting grounds and swimming pools). Addresses of adolescents? homes were geocoded by using the centroid of the six-digit zip codes of their home address. ArcGIS 9.3 was used to count the number of sports facilities within a crow-fly buffer of 1600 m (i.e. approximately 1 mile) from the adolescents? home. This radius was based on a study by Colabianchi et al. [ 30 ] in which an average acceptable travel time of 15 min was found. Given that cycling is a common mode of transport in The Netherlands, 1600 m can be easily reached within 15 min. Demographics The baseline ENDORSE questionnaire provided information on gender and country of birth of the adolescents, their mothers and fathers and from these variables an ethnic background variable (Western or non-Western) was constructed according to the standards of Statistics Netherlands [ 31 ]. In The Netherlands, secondary education is provided at different levels, ranging from lower vocational to senior general secondary education schools preparing for universities. School level was categorized into higher general secondary education (i.e. preparatory education for university) and vocational education. Analyses Descriptive statistics were used to describe the study population. Clustering of behaviour in neighbourhoods was tested in MLwiN 2.02 by calculating the intra-cluster coefficient (ICC) of the nill-model of sports participation (i.e. only the intercept was in the model) and by testing significance of variation. No significant clustering in neighbourhoods was observed (ICC: 0.06, neighbourhood level variance 0.30, 95% confidence interval: 0.36 to 0.81). Therefore, it was decided to conduct all analyses in SPSS 15.0 without adjustments for clustering at the neighbourhood level. Bivariate Spearman correlations were calculated to analyse univariate associations between the 492 cognitive, environmental and behavioural variables. Subsequently, multiple logistic regression analyses were conducted to test associations between TPB variables and availability of sports facilities at baseline with sports participation at follow-up. All analyses were adjusted for gender, age, school level, ethnicity and sports participation at baseline. Variables were entered stepwise: in the first step demographics and sports participation at baseline; in the second step availability of sports facilities; in the third step attitude, subjective norm and PBC; in the fourth step intention and in the last step the intention 3 availability of sports facilities interaction term. If the interaction term proved to be significant (P < 0.10), simple slope analyses were conducted to visualize the moderation effect by using an SPSS script developed by Hayes and Matthes [ 32 ]. Due to severe skewness and therewith problematic interpretation of the simple slopes analyses, intention was dichotomized based on median split. The dichotomized intention variable was used in all analyses. For all associations, a result was considered significant if the P-value was lower than 0.05 for a two-sided test. Results Participants and dropout Adolescents eligible for the analyses at baseline (N = 488) were significantly more likely to be girls and of non-Western origin than those not eligible at baseline for analyses (N = 211). Follow-up data were available for 288 of the adolescents included for analysis (59%). The other 41% could not be traced because they had left school, declined to participate or were absent during the week that follow-up measurements took place. Adolescents with follow-up data were significantly more likely to participate in sports at baseline (72 versus 62%; P < 0.01) and were on average 0.14 years younger than those without follow-up data. Of the adolescents with follow-up data, 41 (14%) did not have complete data on the variables of interest. The sample available for analyses thus consisted of 247 adolescents. Descriptive statistics The average age of the final sample at baseline was 13.2 (SD: 0.6) years and at follow-up 15.2 (SD: 0.6) years; 57.6% of the adolescent sample had a nonWestern ethnicity and 47.9% were male. A majority of adolescents reported to participate in sports at baseline (74.1%). At follow-up, however, sports participation had declined to 47.9%. On average, adolescents in the final sample had 14.94 (SD: 8.13) sports facilities available within a radius of 1600 m (Table I). At baseline, adolescents reported on average a positive attitude (mean: 4.4; SD: 0.6; range: 2.5?5), subjective norm (mean: 4.6; SD: 0.6; range: 3?5), control dimension of PBC (mean: 4.3; SD: 0.8; range: 1?5), the capability dimension of PBC (mean: 4.5; SD: 0.7; range: 2?5) and intention (68% in high category) towards sports and PA (Table I). Univariate analyses Bivariate correlations showed positive associations between availability of sports facilities and attitudes towards sports and the control dimension of PBC, but not with behaviour at follow-up. Positive associations were also found between attitude, subjective norm, the capability and control dimension of PBC and intention to participate in sports (Table I). Intention at baseline was positively correlated with sports participation at follow-up. Most effect sizes were small or medium [ 33 ]. Multivariate analyses of intention and availability of sports facilities with sports participation The results of the multivariate logistic regression analyses are shown in Table II. The number of sports facilities available at baseline was not associated with participation in sports at follow-up, after adjustment for demographics and sports participation at baseline. Of the TPB variables entered in Step 3, attitude and subjective norm were significantly associated with sports participation. Attitude remained significant in the subsequent and final model. Subjective norm was also significant in the final model. Intention at baseline, entered in Step 4, was not significantly associated with sports participation at follow-up. The availability 3 intention interaction term was significantly associated with sports participation at follow-up, indicating moderation of availability on the intention?sports participation relation. Moderation of the availability of sports facilities on the intention?behaviour relation Simple slope analyses were conducted to interpret the availability 3 intention interaction effect (Fig. 1). In this figure, the predicted probability of participating in sports is plotted for two levels of intention (low and high) for three levels of availability (low availability, 1 SD below mean; mean Small effect size: r > 0.10; medium effect size: 0.30 < r < 0.50; large effect size r = >0.50. 1, Availability of sports facilities; 2, Attitude; 3, PBC?control; 4, PBC?capability; 5, Subjective norm; 6, Intention. **P < 0.01. Significant values are represented in bold. CI, confidence interval. OR, odds ratio. aReference is high education. bReference is male. cReference is western background. dSports participation at baseline or not (1/0). eDichotomized measure (0 = low, 1 = high). Step 1 OR (95% CI) availability and high availability, 1 SD above mean). Figure 1 shows that the intention?sports participation relationship is stronger with increasing availability of sports facilities. Discussion This study aimed to identify individual and environmental predictors of adolescent sports participation and to examine whether availability of sports facilities moderated the intention?behaviour relation. In summary, we found that attitude and subjective norm were associated with sports participation at follow-up. Intention was associated with sports participation in the univariate analyses, but not in the multivariate models. Availability of sports facilities was not associated with sports participation. However, the availability of sports facilities significantly moderated the intention?sports participation association, with the intention?behaviour relationship being stronger when there were more facilities available. The study also confirmed results of earlier 494 studies [ 9, 10 ], showing large declines in sports participation during adolescence. This study is among the first to examine aspects of the physical environment as a moderator of the intention?behaviour relationship for PA among adolescents. Further strengths of the study include its longitudinal design and the objective assessment of sports facilities availability. In line with our hypothesis, we found that the availability of sports facilities moderates the intention?sports participation relation in such a way that a higher availability of sports facilities contributes to a stronger intention? behaviour relationship. Similar results were found by Rhodes et al. [ 23 ] for neighbourhood recreation facilities and walking among adults. Our findings support the proposition that the environment is a relevant prerequisite for being physically active but is not sufficient to promote PA levels [ 34 ]. When sufficient facilities are available, intention to be more active appears to be of additional importance. Availability of sports facilities may facilitate sports participation for those with a positive intention, which is in line with the assumptions in Fishbein?s [ 16 ] model in which it is postulated that the environment may provide the opportunity to act on positive intentions. Thus, lack of appropriate availability of sports facilities may be one of the reasons for the intention?behaviour gap. The inconsistent findings in the literature [ 17, 18 ] on the relationship between intentions and sports participations can potentially be explained by the present findings. In contrast to what we had hypothesized, we did not observe a significant direct association of sports facilities at baseline on sports participation at follow-up. Even though such relationships are assumed in ecological models such as the EnRG framework [ 14 ], so far empirical evidence does not show consistent results. Some studies have shown associations between objectively measured availability and PA behaviour among adolescents [ 35?37 ], while others have not [ 20, 38 ]. Most of these studies had a cross-sectional design. Reasons for inconsistent findings may be methodological issues in the measurement of environmental influences, such as the buffer sizes used to objectively capture the environment. Additionally, it is noteworthy that we did find direct associations between attitude, subjective norm and sports participation that were not specifically hypothesized. The direct attitude?behaviour relationship has also been shown for other healthrelated behaviours [ 39 ], and could potentially be explained by the MODE (Motivation and Opportunity as DEterminants) model [ 40 ], which suggests that when attitudes are strong (i.e. easily accessible from memory), people may automatically act on them. The direct effect of the subjective norm may be explained by its measurement as parental norm. Whereas norms are normally operationalized as the expectations of others, the influence of parents may go beyond that of a motivational drive and may reflect actual support. Hence, within adolescence, the role of parents is likely to be important, both indirectly as a motivator and directly as a facilitator of various health-related behaviours. There are limitations that have to be taken into account in interpreting the results. Firstly, the time span between baseline and follow-up measurements was 2 years, which may be too long to find a strong association between determinants and behaviour, especially since the intention item was framed as intention to do PA or sports within 6 months. Secondly, the TPB constructs are measured 495 with a limited number of items which might question the validity of the operationalization. However, the inter-item correlations and relationship of TPB variables with intention (data not shown) and behaviour are comparable to other studies [ 41 ]. Thirdly, adolescents who did not participate in sports at baseline were less likely to be included in the study since they were more likely to have no follow-up data. Furthermore, this study was conducted among a sample of urban Dutch adolescents. Care should be taken in generalizing these results to other populations. A final limitation is that PA was self-reported. Although the instrument was reliable, reporting of PA behaviour may not have been completely accurate. In conclusion, this study indicates that objectively measured availability of sports facilities moderates the longitudinal association between intention and sports participation among adolescents. If confirmed in further research, the implication may be that motivating adolescents to engage in sports is indeed more useful when sufficient opportunities are present. Funding Netherlands Organization for Health Research and Development (ZonMW; 7110.0001 to R.G.P, P.E. and A.O., 12200003 to F.J.L.); The World Cancer Research Fund (2007/47 to S.V., N.T. and J.B.); Public Health Research Fellowships from the Victorian Health Promotion Foundation to A.T. and D.C. Conflict of interest statement None declared. 496 1. Lagerros YT , Hsieh SF , Hsieh CC . Physical activity in adolescence and young adulthood and breast cancer risk: a quantitative review . Eur J Cancer Prev 2004 ; 13 : 5 - 12 . 2. Cavil N. Children and Young People: The Importance of Physical Activity. A paper published in the context of the European Heart Health Initiative . Brussels: European Heart Network, 2001 . 3. U.S. Department of Health and Human Services . Physical Activity Fundamental to Preventing Diseases. Washington D.C.: U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation, 2002 . 4. Ortega FB , Ruiz JR , Castillo MJ et al. 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Prins, Richard G., van Empelen, Pepijn, te Velde, Saskia J., Timperio, Anna, van Lenthe, Frank J., Tak, Nannah I., Crawford, David, Brug, Johannes, Oenema, Anke. Availability of sports facilities as moderator of the intention–sports participation relationship among adolescents, Health Education Research, 2010, 489-497, DOI: 10.1093/her/cyq024