To determine the independent contributions of family and neighbourhood environments to changes in youth physical activity and body mass index (BMI) z-score over 5 years.
In 2001, 2004 and 2006, 301 children (10–12 years at baseline) had their height and weight measured (BMI was converted to z-scores using Centers for Disease Control and Prevention reference charts; see http://www.cdc.gov/growthcharts) and moderate-to-vigorous physical activity (MVPA) assessed using accelerometers. In 2001, parents reported on the home environment (social support, role modelling, rules and restrictions, physical environment) and perceived neighbourhood environment (local traffic, road safety, sporting venues, public transport), and Geographic Information Systems were used to map features of the neighbourhood environment (destinations, road connectivity, traffic exposure). Generalized estimating equations were used to predict average BMI z-score and MVPA over time from baseline home and perceived and objective neighbourhood environment factors.
Among boys, maternal education and heavy traffic were inversely associated, and sibling physical activity, maternal role modelling of MVPA and the presence of dead-end roads were positively associated with MVPA. Having unmarried parents, maternal MVPA role modelling and number of home sedentary items were positively associated with BMI z-score among boys. Among girls, having siblings, paternal MVPA role modelling, physical activity rules and parental physical activity co-participation were positively associated with MVPA. Having unmarried parents and maternal sedentary behaviour role modelling were positively associated, and number of sedentary behaviour rules and physical activity items were inversely associated with BMI z-score among girls.
The home environment seems more important than the neighbourhood environment in influencing children's physical activity and BMI z-score over 5 years. Physical activity and weight gain programmes among youth should focus on parental role modelling, rules around sedentary and active pursuits, and parental support for physical activity. Intervention studies to investigate these strategies are warranted.
With rates of childhood obesity increasing dramatically, there is a pressing need to develop effective prevention strategies. Although the causes of obesity are self-evident, the underlying drivers of poor eating patterns and physical inactivity are far less well understood.1 Without a more sophisticated understanding of the influences on energy balance behaviours, it is likely that health officials will continue to struggle to find effective strategies to combat childhood obesity.2 Although both eating and physical activity behaviours are recognized to be important in terms of obesity risk, this paper focuses on children's physical activity and sedentary behaviour. A range of factors have been posited as potential influences on children's physical activity and sedentary behaviours; however, the role played by the home and local neighbourhood environments have recently received attention in the literature as two potentially potent sources of influence.3 This emphasis is consistent with the socio-ecological model, which proposes that behaviour is not only influenced by individual factors such as attitudes and beliefs, but that social factors and other environmental factors are also important determinants.4
The home environment seems to have an important function in children's physical activity and obesity risk in a number of ways. For example, parental modelling of physical activity and of sedentary behaviour is associated with children's activity levels,5, 6 their sedentary habits7 and a greater likelihood of being overweight in girls.8 Sibling physical activity has also been inversely associated with weight change in girls.9 The opportunities that parents provide at home for sedentary pursuits are also important. For example, children with televisions (TVs) in their bedrooms watch more TV and are more likely to be overweight than other children,7, 10 and in the family home, the number of sedentary items is positively associated, and the number of physical activity items negatively associated, with weight change among boys and girls, respectively.9 In addition, parents can influence children's physical activity by implementing rules regarding physical activity and sedentary pursuits.11 Parents can also have a practical role in supporting children's physical activity through encouragement to participate and by providing transportation to sporting activities.12
A growing body of evidence suggests that aspects of the local neighbourhood environment may also be an important influence on children's physical activity. Much existing research has focused on adults and is cross-sectional. It shows, for example, that street connectivity, mixed land use, population density and perceived aesthetics of a neighbourhood are associated with walking.13, 14, 15 Although the data available regarding the relation between neighbourhood environment and children's physical activity are limited, a recent review concluded that access to recreational facilities and schools, the presence of sidewalks and controlled intersections, and access to destinations and public transport were positively associated with physical activity participation among children.16 A more recent review showed that active travel by children and adolescents is positively associated with social interactions, the presence of facilities that support travel, urban form, shorter route length and road safety.12 Fewer studies have examined associations between the neighbourhood environment and children's obesity risk. These cross-sectional studies have found positive associations for heavy traffic and parental concern about traffic with overweight and obesity in 10–12 years olds,17 and negative associations with living in ‘walkable’ neighbourhoods and neighbourhoods with many intersections with overweight in preschool children.18 The availability of recreational facilities generally seems to be unrelated to risk of obesity in preschoolers18, 19 and older children.9
Although the home and neighbourhood environments are likely to influence children's physical activity and thus the risk of overweight and obesity, there are few studies that have examined these concurrently and comprehensively, and none that have assessed these prospectively. In a cross-sectional study of 88 children in New York, street connectivity, neighbourhood land use diversity and percentage park area were associated with increased physical activity among boys, and the number of TV sets in the home (the only home environment variable assessed) was associated with TV viewing.20 In an Australian cross-sectional study of 912 children, perceptions of the local neighbourhood environment were found to constrain children's active commuting to school (having few other children in area, no lights or crossings for the child to use, busy roads to cross, a steep incline and more direct route to school), but there were no associations with family factors (marital status, number of siblings, having adults home after school).21 A cross-sectional study of 1804 Chinese adolescents found that not having a lane around the house and high maternal education were associated with increased odds of overweight/obesity among boys, whereas a video game machine at home was inversely associated with overweight/obesity among girls.22 In the same study, difficult access to public facilities, no sidewalks around the house, larger family size and higher paternal education level were associated with increased odds of girls' physical inactivity; among boys, transportation by automobile, no vacant field around the house and no video game shops around the house were associated with increased odds of inactivity, whereas parental exercise involvement was associated with decreased odds of inactivity.23
Notably, each of the studies described above are cross-sectional in design, which limits inferences about the temporal nature of associations. This study, therefore, aimed to prospectively examine the independent contribution of home and neighbourhood environments to changes in overall youth physical activity and body mass index (BMI) z-score over 5 years. The findings presented in the present paper are based on data from the Children Living in Active Neighbourhoods (CLAN) Study. We have earlier reported cross-sectional associations between perceptions of the neighbourhood environment and children's active commuting21, 24 and weight status17 based on CLAN. We have also earlier reported 3-year changes in children's weight and their association with home environment9 and 5-year changes in physical activity during the critical window (after school) and on weekends and their association with the family environment based on CLAN.25
Materials and methods
The Deakin University Human Research Ethics Committee and the Department of Education and Training Victoria provided ethical approval to conduct the CLAN study17, 24, 26 (originally known as the Children's Leisure Activities Study). All parents and children participating in the study provided informed written consent. Data were collected between July and December 2001 (T1), 2004 (T2) and 2006 (T3).
Families of children aged 10–12 years were recruited from 19 state primary schools in high (n=10) and low (n=9) socio-economic areas in Melbourne, Australia. Twenty-four schools were selected using stratified random sampling proportionate to school size, with five schools declining to participate. In total, 2096 10–12-year-old children were provided with consent forms to take home to their parents, with only those returning consent forms being eligible to participate (n=926; 44% response rate). Families indicated whether they could be re-contacted for further research; of 695 who agreed, 402 provided data at the first follow-up in 2004 (43% retention) and 342 of these participants agreed to further follow-up. In 2006, 314 families provided data as part of the second follow-up (34% retention).
There were no significant differences in baseline BMI z-score (girls), moderate-to-vigorous physical activity (MVPA) or number of siblings between those who participated in follow-up and those who did not. However, a significantly greater proportion of families who participated in follow-up had high maternal education (41 vs 30% P<0.05). In addition, boys who participated in follow-up had significantly (P<0.05) lower baseline BMI z-scores (0.39 vs 0.63 kg m–2) and a higher proportion had parents who were married or living as married (86 vs 79%, P<0.01).
Children's physical activity
At each of the three time points, children were asked to wear a Manufacturing Technology Inc (Actigraph Model, AM7164-2.2C, Fort Walton Beach, Florida, USA) uniaxial accelerometer for an 8-day period during waking hours, except bathing and aquatic activities. This accelerometer measures movement in the vertical plane and has been validated as an objective measure of children's physical activity.27, 28 Children were instructed in the use of the accelerometer by trained data collectors. Data recorded on the first and last days were discarded because of incompleteness on these days (monitors were administered and collected during school hours) and possible reactivity effects on the first day. Children with a minimum of four complete days of accelerometer data were included in analyses.29 Days where total accelerometer counts were <10 000 or >20 000 000 or duration of vigorous-intensity activity totalled >6 h were excluded, as this indicated a possible accelerometer malfunction.
Movement count thresholds were applied to the data using a custom-designed data reduction programme to calculate minutes spent in MVPA. Thresholds were based on an age-specific energy expenditure prediction equation: METs=2.757+(0.0015·counts·min−1)−(0.08957·age (years))−(0.000038·counts·min–1·age (years))30 and were defined in METs (metabolic equivalents of rest) as moderate 3.0–5.9 METs and vigorous-intensity 6.0+ METs. MVPA minutes per day were calculated by summing total minutes for each day and dividing by the number of days the accelerometer met the inclusion criteria.
At each of the three time points, children's height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg) in no shoes and light clothing were measured using a portable stadiometer and digital scales, respectively, by trained technicians using a standardized protocol. BMI was calculated (kg m–2) and converted to BMI z-scores using Centers for Disease Control and Prevention 2000 reference charts (http://www.cdc.gov/growthcharts).
The selection of predictor measures was guided by existing literature and based on a Social-Ecological framework.
At baseline, parents completed a questionnaire on average 2 weeks before their child wore the accelerometer. The home environment measures, scoring and acceptability of test–retest reliability (where known) have been reported earlier9 and are described briefly below. The questionnaire also collected demographic information on the child's sex and age; and on maternal education as a proxy for socio-economic position (low=some high school or less, medium=high school or technical certificate, high=tertiary education), consistent with earlier studies;31, 32, 33 parental marital status (married/living as married, not married) and the number of children under the age of 18 years living in the household.
Role modelling: At baseline, parents reported the total time in a typical week that they and their partner (if applicable) usually spent doing vigorous physical activity and moderate activity (for at least 10 min continuously), watching TV, playing electronic games and using the computer during their leisure time.9, 34, 35, 36 Total duration of maternal and paternal physical activity, TV viewing, computer use and electronic games use were summed separately. Parents were also asked to report how often other children in the family participated in physical activity (‘sibling physical activity’), which was dichotomized as ⩾3 times per week and <3 times per week.
Rules and restrictions: At baseline, frequency of restricting the time that their child spends watching TV and playing outside, and level of agreement (on a five-point Likert scale ranging from strongly agree to strongly disagree) with statements that their child must be supervised when playing outside, watching TV and using the internet, and that they disallow play outside after dark, TV during meal times and TV/Playstation/Nintendo until homework is completed (each categorized as ‘yes' or ‘no’) were assessed.9 The sedentary-related items have acceptable reliability.11, 37 The three items related to playing outside (range: 0–3) and the five items related to TV viewing/sedentary behaviours (range: 0–5), respectively, were summed.
Social support: At baseline, parents reported how often the father/male carer, mother/female carer and siblings actively participated in physical activity with the child, and how often the father/male carer and mother/female carer provided support for physical activity such as taking them to training, providing money for participation and buying sports clothing/equipment for their child (adapted from existing measures).38 How frequently children watched TV or videos, and played computer or electronic games, together as a family (that is with at least one adult family member), and how frequently the mother/female carer and father/male carer praised the child for participating in physical activity were also assessed (adapted from existing measures).39 Separate scores were computed for physical activity co-participation, direct support for physical activity, family sedentary behaviour co-participation and parental praise for physical activity.
Home physical environment: In the baseline questionnaire, parents were asked whether they had in their yard or garden a swimming pool/spa, trampoline, sandpit/swings/play equipment or basketball ring and whether their child used nine types of physical activity equipment (balls, bats/rackets, bikes, home gym equipment, rollerblades, skateboards, skipping rope, scooter and toys that encourage active play) and seven types of sedentary equipment (free-to-air TV, pay TV, video/DVD player, electronic games, computer, internet access and a TV in the child's bedroom) at home (recoded as ‘has item’ or ‘does not have item’). The number of different types of physical activity (range: 0–13) and sedentary behaviour items (range: 0–7) were summed.
Aspects of the baseline neighbourhood physical activity environment were objectively measured using a Geographic Information System (GIS) in 2004–2005. Spatial analyses were conducted using ESRI ArcView 3.3 and related extensions. A GIS dataset was built using cadastral and road/road infrastructure data supplied by the State of Victoria (VicMap Property, VicMap Address and VicMap Transport) and the Open Space 2002 spatial dataset (owned by the Australian Research Centre for Urban Ecology). Participant addresses were geocoded within the GIS. Parents also reported their perceptions of their neighbourhood environment.
Destinations: Using the GIS, the number of freely accessible public open spaces (no fees or restricted opening hours) and the number of public open spaces classified as sport/recreation within a 2-km radius of each participant's residence were computed. The locations (sourced from community directories, local government, electronic telephone directories and other websites) of facilities in which sports or physical activities (basketball, BMX riding, cricket, football, gym, netball, swimming, skating, soccer, squash and tennis) could be undertaken were geocoded, and the number of different sports with facilities within 2 km of each participant's home was computed. Total linear kilometres of walking and cycling tracks within 2 km (identified using VicMap Transport (January 2004) and Melway Map Images (edition 31 October 2003, Ausway Publishing)) was computed (excluding overpasses and access lanes/throughways between buildings). Distance to school was calculated using Network Analyst V1.0b, based on the shortest possible route along the road network.40
Road connectivity: Using the GIS, the number of intersections and cul-de-sacs within 2 km of each child's home was computed, and the number of ⩾four-way intersections was expressed as a proportion of the total number of intersections. Total linear kilometres of ‘access’ paths (including overpasses, access lanes and throughways between buildings) within 2 km were computed (identified using VicMap Transport (January 2004) and Melway Map Images (edition 31 October 2003, purchased from Ausway Publishing)).
Traffic exposure: Using the GIS, the total length of ‘busy’ roads (freeways, highways or arterial roads) and the total length of ‘local’ roads (identified using VicMap Transport, January 2004) were summed to provide an indicator of traffic exposure.
Perceptions of the neighbourhood: At baseline, parents reported their agreement with six statements on a five-point Likert scale about local traffic (‘there is heavy traffic in our local streets’), road safety concerns (‘road safety is a concern in our area’), lights/crossings (‘there are no lights/crossings for my child to use’), busy roads (‘my child would have to cross several roads to get to areas where he/she can play’), sporting venues (‘there are few sporting venues within our local area’) and public transport (‘public transport is limited in my area’).24 All responses were categorized as ‘agree’ (strongly agree, agree) or ‘not agree’ (neutral, disagree, strongly disagree, do not know).
Analyses were restricted to children who had complete data collected at baseline plus one other time point (n=301). Average values for MVPA and BMI z-score were calculated by sex and year and plotted graphically. One-way analysis-of-variance was used to determine whether there were significant differences in MVPA and BMI z-score cross-sectionally for each sex at each time point. The χ2, analysis-of-variance and Kruskal–Wallis equality-of-populations rank test were used to determine significant differences in categorical baseline predictor variables, continuous baseline predictor variables with equal variances and continuous baseline predictor variables with unequal variances, respectively.
The longitudinal relationship between the baseline predictor variables (family and neighbourhood environment) and average MVPA and BMI z-score over time was examined using generalized estimating equations.41, 42 This method takes into account repeated observations within individuals and involves a pooled analysis of cross-sectional (between-subjects) and longitudinal (within-subjects) relationships, resulting in a single regression coefficient that incorporates between-subject and within-subject correlations, using all data available.43 First, the bivariable relationship between each predictor variable and each outcome variable was established (Model 1). Predictor variables that showed a relationship with the outcome at P<0.1 from Model 1 were eligible for inclusion in Model 2. Before entry into Model 2, the correlation between predictor variables was assessed; no variables were correlated (using the more conservative criteria of r>0.4 than the suggested r>0.7).44 In the final model (Model 3), an additional adjustment was made for the alternate outcome (that is in models predicting BMI z-score, MVPA was included in the model, whereas in models predicting MVPA, BMI z-score was included in the model). The final model, therefore, represents the influence of baseline family and neighbourhood environment factors on the longitudinal development of MVPA and BMI z-score independently of BMI z-score and MVPA, respectively. All models take the effects of within-subject clustering by school (the unit of recruitment at baseline) into consideration, and adjust for baseline age.
Children's BMI z-score and MVPA over 5 years
Significant (P<0.01) increases in BMI z-score and decreases in MVPA were observed over the 5-year period in boys and girls, as anticipated (Figure 1). BMI z-score and MVPA were significantly higher among boys than among girls at each time point, except at T2 in which girls had significantly higher BMI z-scores than boys. The greatest changes in BMI z-score and MVPA were observed between T2 and T3 for both boys (BMI z-score: 98% increase; MVPA: 44% decrease) and girls (BMI z-score: 46% increase; MVPA: 44% decrease).
Children's home and neighbourhood environments
There was little difference in the family and neighbourhood environment characteristics of boys and girls at baseline (Table 1). However, a higher proportion of girls were from a family with low maternal education and a higher proportion of boys were from a family with medium maternal education. The majority of parents were married or living as married (82%), and most parents (80%) were born in Australia, New Zealand, the United Kingdom or the Republic of Ireland.
Home and neighbourhood environments and children's MVPA
Home environment variables were more commonly associated with children's MVPA over 5 years in the final multivariable models than neighbourhood factors (Table 2). Among boys, maternal education and perceived heavy local traffic were inversely associated and maternal role modelling of MVPA, sibling physical activity and road connectivity were positively associated with MVPA. Among girls, number of siblings, paternal role modelling of MVPA, number of rules related to physical activity and parental co-participation in physical activity were significant positive predictors of MVPA.
The following home environment variables were not associated with MVPA in the final model: maternal education (girls only); parental marital status; number of siblings (boys only); maternal role modelling of MVPA (girls only); paternal role modelling of MVPA (boys only); maternal and paternal sedentary behaviour; sibling physical activity (girls only); number of rules related to physical activity (boys only); number of rules related to sedentary behaviour; parental co-participation in physical activity (boys only); family co-participation in sedentary behaviour; direct parental support for physical activity; parental praise for physical activity; the number of physical activity and sedentary behaviour items in the home. The following neighbourhood environment variables were not associated with MVPA in the final model: the number of freely available public open spaces; the number of sport and recreation public open spaces; the number of sport options within 2 km; the total length of walking/cycling tracks; the distance to school; the number of intersections within 2 km; the number of four-way intersections within 2 km; the number of cul-de-sacs (girls only); the total length of access tracks; the total length of busy roads within 2 km; the total length of local roads within 2 km; perceived heavy local traffic (girls only); perceived road safety concerns; perceptions of no lights or crossings, of busy roads to cross, of few sporting venues or of limited public transport.
Home and neighbourhood environments and children's BMI z-score
Home factors were more commonly associated with children's BMI z-score over 5 years in the final multivariable models than neighbourhood factors (Table 3). Among boys, having non-married parents, maternal role modelling of MVPA and number of sedentary behaviour items in the home were significantly positively associated with BMI z-score. Among girls, having non-married parents and maternal role modelling of sedentary behaviour were positively associated, and number of rules related to sedentary behaviour and number of physical activity items in the home were negatively associated with BMI z-score.
The following home environment variables were not associated with BMI z-score in the final model: maternal education; number of siblings; maternal role modelling of MVPA (girls only); paternal role modelling of MVPA; paternal sedentary behaviour; maternal sedentary behaviour (boys only); sibling physical activity; number of rules related to physical activity; number of rules related to sedentary behaviour (boys only); parental co-participation in physical activity (boys only); family co-participation in sedentary behaviour; direct parental support for physical activity; parental praise for physical activity; the number of physical activity behaviour items in the home (boys only); the number of sedentary behaviour items in the home (girls only). The following neighbourhood environment variables were not associated with BMI z-score in the final model: the number of freely available public open spaces; the number of sport and recreation public open spaces; the number of sport options within 2 km; the total length of walking/cycling tracks; the distance to school; the number of intersections within 2 km; the number of four-way intersections within 2 km; the number of cul-de-sacs; the total length of access tracks; the total length of busy roads within 2 km; the total length of local roads within 2 km; perceived heavy local traffic; perceived road safety concerns; perceptions of no lights or crossings, of busy roads to cross, of few sporting venues or of limited public transport.
This study sought to examine the independent effects of home and neighbourhood environments to 5-year changes in physical activity and BMI z-score among older children. As expected, physical activity declined and BMI z-score increased over the 5 years of the study as the 10–12-year-old children became teenagers. Although the neighbourhood environment has been suggested as a potentially potent influence on physical activity and risk of overweight,1 in this study, factors in the home environment were more often associated with physical activity and BMI z-score than either the perceived or objective measures of the local neighbourhood environment. As far as we are aware, this is to our knowledge the first longitudinal study to have concurrently examined the influence of home and neighbourhood factors on changes in children's activity and weight status.
Consistent with earlier research,5, 6 a number of social factors in the home environment, such as the presence of siblings, role modelling by parents or siblings and parents' participation in physical activity with the child by parents, were positively associated with changes in children's physical activity. Having rules regarding physical activity, such as restricting the amount of time children played outside and not allowing children to play outside after dark, was another aspect of the home environment that was associated with girls' physical activity, supporting earlier research.11 The finding that maternal education was inversely associated with boys' MVPA (that is high maternal education was associated with lower MVPA) was surprising and warrants further investigation. It is plausible that more educated mothers are absent from home more because of full-time employment, and are, therefore, unavailable to co-participate in, or model, positive physical activity behaviours, nor drive their sons to sporting activities. However, further analyses found that adjusting for employment status made no difference to this finding (data not shown), suggesting this was not the case. This finding requires further confirmation in future prospective studies, and if evident, warrants further investigation.
Similar to the findings for physical activity, the home environment rather than the local neighbourhood environment was more important in predicting average BMI z-score over 5 years. The finding that children of single parents had higher average BMI z-scores over the 5-year follow-up period is consistent with earlier research.45 In this study, parental marital status was associated with average BMI z-score independent of maternal education (a proxy for socio-economic status) and role modelling by mothers, suggesting that other factors (for example, having disposable income to support children's participation in sport or to purchase healthy foods) may be important. Other home environment factors that independently predicted average BMI z-score included the number of sedentary opportunities in the home and time spent by mothers in sedentary pursuits (both positively associated), and having rules regarding sedentary behaviour and the number of physical activity items available in the home (both negatively associated), all of which are consistent with earlier findings from this and other studies.8, 9, 10 The finding that time spent doing activity by mothers was positively associated with average BMI z-score in boys is difficult to explain and may require further investigation if other prospective studies show similar findings.
Only two aspects of the local neighbourhood environment—the presence of cul-de-sacs and the perception that there was heavy traffic—were independently associated with physical activity, and only for boys, and none were independently associated with BMI z-score. This was despite the fact that there was considerable heterogeneity in the objective and subjective measures of the neighbourhood environment. It may be that other aspects of the physical neighbourhood environment not assessed in this study are important in influencing children's physical activity and BMI z-score over time. However, this is unlikely as a broad range of measures capturing different aspects of the local neighbourhood were assessed. It may be that aspects of children's neighbourhood relating to the availability of healthy and unhealthy food choices may have been more important in explaining BMI z-score, although earlier cross-sectional analysis of CLAN participants,46 and other studies of children,47, 48 suggest that the availability of fast food outlets is unrelated to weight status. Nonetheless, the lack of data regarding the local food environment and eating behaviours must be acknowledged as a limitation of the present analysis.
The lack of association between the local neighbourhood and children's physical activity and BMI z-score might also be a function of the fact that, in terms of characterizing the neighbourhood with regards to its impact on physical activity and obesity risk, it is challenging to know where to look and what to count.40 For example, we have earlier argued that the field lacks strong conceptual frameworks to guide the selection and operationalization of environmental measures, and what constitutes a ‘neighbourhood’ is open to debate.40 We used a 2-km radius to define a neighbourhood using the GIS; however, this may have been too extensive. Features closer to home, for example within an easy round-trip walk, may be more important, as found by Holt et al.49 However, it may also be the case that for younger children, in terms of its relative importance, the local neighbourhood environment has a less significant role than the home environment in influencing physical activity and BMI z-score longitudinally, as the present findings suggest. In addition, we examined overall physical activity and it may be that the neighbourhood environment is more strongly associated with specific physical activity behaviours such as walking.40
Limitations of this study include the baseline response rate and attrition. Although follow-up information on non-participants was not available because of existing privacy legislation, comparison with the baseline characteristics of those who participated in follow-up showed no significant differences in baseline MVPA (P=0.22) or girls' BMI z-score. However, boys who participated in follow-up had significantly lower baseline BMI z-scores than boys who did not participate (0.4 vs 0.6, P<0.05), and a higher proportion of children who participated in follow-up had university-educated mothers (41 vs 30%, P<0.05). The assessment of the home and neighbourhood environment at one time point may have influenced findings. Although the neighbourhood environment is likely to be relatively static, the home environment is likely to change over time. The use of a 2-km buffer to assess neighbourhood variables may also be a limitation. There has been a suggestion that a 2-km buffer may be too extensive for young children,49 although the eldest children in that study were of similar age to the youngest children in this study at baseline, who were then substantially older (aged 15 years) at the final follow-up. A further limitation is that the model of accelerometer used in the study cannot be worn in water-based activities, which will result in an underestimation of children's physical activity.
Despite these limitations, this study had a number of important strengths including the 5-year follow-up period involving data collection at three time points, which allows for greater insights into the temporal nature of associations. The inclusion of an objective measure of physical activity, accelerometry, is important for reducing biases inherent in self-report measures. The inclusion of both objective and perceived measures of the local neighbourhood environment is an additional strength, as there is much debate about their relative importance.40 Furthermore, few studies have concurrently examined the independent contribution of the home and neighbourhood environment, and few have concurrently examined the influence of these factors on changes in children's physical activity and adiposity over time.
This study found that aspects of the home environment were generally more important than aspects of the neighbourhood environment in predicting children's average physical activity and BMI z-score over 5 years. This finding suggests that in younger children and adolescence, proximal influences within the home, such as whom they reside with and their behaviour, may be more important than distal influences, such as where they reside. This finding was evident despite the transition from childhood into adolescence, where there is presumably more autonomy and greater independence in decision making about leisure activities. It could be argued that the environment is necessary but not sufficient in terms of its impact on obesity-risk behaviours. Interventions to promote physical activity and prevent unhealthy weight gain among children and adolescents may need to focus more strongly on family influences, such as parental role modelling, rules around sedentary and active pursuits, and support for physical activity. Intervention studies to investigate the efficacy and effectiveness of such strategies are warranted.
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This project was supported by a grant from the National Health and Medical Research Council (NHMRC) (ID 274309). David Crawford and Anna Timperio are supported by fellowships from the Victorian Health Promotion Foundation. Verity Cleland, Kylie Ball, and Billie Giles-Corti are supported by fellowships from the NHMRC. Jo Salmon is supported by a Fellowship from the National Heart Foundation and sanofi-aventis.
The authors declare no conflict of interest.
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Crawford, D., Cleland, V., Timperio, A. et al. The longitudinal influence of home and neighbourhood environments on children's body mass index and physical activity over 5 years: the CLAN study. Int J Obes 34, 1177–1187 (2010). https://doi.org/10.1038/ijo.2010.57
- physical activity
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