The Barriers to and Facilitators of Physical Activity and Sport for Oceania with Non-European, Non-Asian (ONENA) Ancestry Children and Adolescents: A Mixed Studies Systematic Review
Abstract
:1. Introduction
2. Methodology
2.1. Protocol and Registration
2.2. Eligibility Criteria
2.3. Information Sources and Search Strategy
2.4. Data Extraction
2.5. Quality Appraisal
3. Results
3.1. Study Selection
3.2. Study Characteristics
3.3. Participants
3.4. Quality Appraisal
3.5. Barriers and Facilitators
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Author (Year), Country, Funding Agency | Aim | Design/ Theoretical Framework | ONENA Sample (Sex, Age, Grades) | Data Collection and Analysis | Key Findings as Reported in Papers |
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Collier, A.F. et al. [57], Palau, NR. | To establish an advisory council of local stakeholders. Conduct an extensive needs assessment with youth, parents, professionals, and the lay public in Palau to inform a wellness intervention. | Qualitative study with cross-sectional data collected (CBPR model). | The mean age of participants was 30.6 years; 38.5% of the sample was under 18 years of age. The majority of the 43 youth and adults in the sample were Palauan (81%). | -Study 1 examined the reasons for overeating in Palau; the best methods of service delivery for the program; and the key features for the wellness program. The sample included youth and adults. -Study 2 examined rates of ow/ob, eating disorder symptomatology, exercise, and the patterns and types of food eaten by Palauan youth. -Data analysis was not reported in the paper. | Barriers to PA: -The average air temperature in Palau is 82 °F (28 °C) and the average relative humidity 82%. Due to the excessive heat, it was indeed challenging for participants to find exercise activities that they wanted to do. -Excessive heat and humidity make it difficult to walk outside during daylight and there are few options for indoor exercise. Facilitators for PA: -More work is needed to brainstorm with community members of different ages the types of physical activity that they can do, as well as what time of day works best for them. -Working with participants to design physical activities that can be completed inside at home or work would also be beneficial. -More emphasis on finding individual partners for physical activity would be helpful for compliance. |
Curtis, A.D. et al. [53], New Zealand, NR. | To determine which factors influence children from areas of socioeconomic deprivation to engage in after school activities. Findings intended to provide a cross-sectional study basis for developing future after school physical activity programs in these areas. | Qualitative study with cross-sectional anthropometric data collected (e.g., BMI)/NR. | Nine children (age range ~8–12 years old) and 21 parents (age range ~31–43 years old) participated in the study; 38% of the sample identified as Pacific Islander (28%) or Maori (10%). | -Focus groups with children, utilising photo-voice prompts for discussion. -Focus groups and semi-structured interviews were conducted with parents. -Content analysis of data was undertaken. | Barriers to PA: -Parents perceived that time, money, and transport were all barriers to children participating in physical activities after school. Facilitators for PA: -Both children and parents described physical activity and play as different constructs; physical activity was considered as an organised activity and play was identified as fun. -Parents explained that children’s enjoyment of a particular activity, as well as positive self-esteem, influenced children’s participation in physical activity. -Community support and communication were also identified as important in creating safer communities and places to play for children. |
Fotu, K.F. et al. [44], Tonga, Welcome Trust (UK), the National Health and Medical Research Council (Australia) and the Health Research Council (New Zealand) through their innovative International Collaborative Research Grant Scheme. | This paper presents the results of the Ma’alahi Youth Project (MYP), the first community-based intervention to target adolescent obesity in the Kingdom of Tonga. | The Ma’alahi Youth Project, the Tongan arm of the Pacific Obesity Prevention in Communities project, was a 3-year, quasi-experimental study of community-based interventions among adolescents in three districts on Tonga’s main island (Tongatapu) compared to the island of Vava’u/CBPR | The intervention group comprised 815 secondary school students aged 11–19 years from the districts of Houma, Nukunuku, and Kolonga on the main island of Tongatapu. The comparison group comprised 897 secondary school students aged 11–19 years from the island of Vava’u. | Anthropometric data, including height, weight, waist circumference, and body fat percentage. Behavioural and quality of life survey data were collected. Health-related quality of life was measured using two instruments: the Assessment of Quality-of-Life instrument (AQoL-6D) and the Paediatric Quality of Life Inventory 4.0 (PedsQL; generic module for 13- to 18-year-olds). | Barriers to PA: Negative outcomes relating to physical activity with a smaller proportion of intervention participants walking/riding to or from school (p = 0.001), being active at lunchtime (p = 0.001), and engaged in after-school activity (p = 0.008) than comparison group participants at follow-up. Facilitators for PA: -Greater integration of strategies to address socio-cultural factors under-pinning food and physical activity patterns, as well as body size perception, into the intervention may have strengthened the “dose” of the overall intervention and led to more beneficial outcomes. |
Hohepa, M. et al. [54], New Zealand, Health Research Council of New Zealand and Auckland University of Technology. | To explore the views of school students on various physical activity contexts and their ideas for potential physical activity promoting strategies. | Qualitative study/socio-ecological model. | In total, 44 participants took part in focus group discussions: 24 females and 20 males (age = 13–15 years). Maori participants comprised just over 50% of the female (n = 13) and male (n = 11) sub-samples. | Nine focus group sessions. The focus groups were separated according to ethnicity (Maori and New Zealand European) and gender, and included a maximum of six participants (range 3–6) in each group. Data analysis included thematic induction using the long table approach. | Barriers to PA: -Six major themes relating to supportive sedentary environments (e.g., passive transport, accessibility and availability, electronic devices), peer influences, structure of PA opportunities, physical constraint (e.g., distance, safety), motivation level, and lack of time (e.g., home/school/work duties). Facilitators for PA: -Five major themes relating to fun, achievement, physical (e.g., health benefits, physical appearance), psychological (e.g., mood and confidence), and preferential activity (e.g., get away from domestic duties/expectations) factors. Potential physical activity promoting strategies: -Identified by high school students: Availability and accessibility, peer and familial support, and self-responsibility. |
Mandic, S., Hopkins, D., et al. [45], New Zealand, National Heart Foundation of New Zealand, Lottery Health Research Grant, University of Otago Research Grant, Dunedin City Council. | The aim of the study was to compare correlates and perceptions of walking versus cycling to school in Dunedin adolescents living less than 4 km from school. | Cross-sectional study/socio-ecological model | Adolescents (n = 764; 44.6% males; 13–18 years; mean age 15.2 years ± 1.4 years) from 12 secondary schools. Maori participants = 9.3%. | Participants completed an online survey about perceptions of walking and cycling to school. Distance to school was calculated using Geographic Information Systems network analysis. Variables assessing perceptions of walking versus cycling using 4-point or 7-point Likert scales were analysed as continuous variables using paired t-tests. To calculate the proportion of adolescents agreeing with each statement, 4-point Likert scale items were also recoded into “disagree” and “agree” and 7-point Likert scale items were recoded as “disagree”, “neutral”, or “agree”. Data analysis was performed using SPSS Statistical Package (Version 22). To account for multiple tests, a p-value of 0.001 was chosen to indicate statistical significance. | -Overall, 50.8% of adolescents walked and 2.1% cycled to school, 44.1% liked cycling for recreation and 58.8% were capable/able/confident to cycle to school. Barriers to PA: -Compared to walking, adolescents reported that cycling to school was perceived as less safe by themselves (cycling vs. walking; 61.3% vs. 89.8%) and their parents (71.4% vs. 88.6%) and was less encouraged by their parents (23.0% vs. 67.0%), peers (18.8% vs. 48.4%), and schools (19.5% vs. 30.8%) (all p = 0.001). -The route to school had fewer cycle paths compared to footpaths (37.2% vs. 91.0%; p = 0.001). -Compared to walking, cycling to school provided less opportunity for socialising with friends (p < 0.001) and posed more personal barriers (e.g., too much to carry, after school schedule, need for planning and getting sweaty) (<0.001). Distance to school (p = 0.189) and wet and cold weather (p = 0.845) were barriers for both walking and cycling. Facilitators for PA: -Adolescents expressed more positive experiential (walking: 45.9%; cycling: 34.9%) and instrumental beliefs (walking: 74.2%; cycling: 59.2%) towards walking versus cycling to school (p = 0.001). Potential physical activity promoting strategies: -Cycle friendly uniforms (41.4%), safer bicycle storage at school (40.1%), slower traffic (36.4%), bus bicycle racks (26.2%), and bicycle ownership (32.7%) would encourage cycling to school. |
Mandic, S., Sandretto, S., et al. [46], New Zealand, National Heart Foundation of New Zealand, Lottery Health Research Grant, University of Otago Research Grant, Dunedin City Council. | This study examined correlates of adolescents’ enrolment in the closest school in the absence of school zoning policies. | Cross-sectional study/socio-ecological model | Adolescents (n = 797; age: 15.2 ± 1.4 years; 51.4% boys) from six non-integrated (regular) public secondary schools without school zoning in Dunedin, New Zealand. Maori participants = 12.7%. | Participants completed an online survey about school choice. Distance to school was calculated using Geographic Information Systems network analysis. Data were analysed using t-tests, Chi-square tests and mixed effects binary logistic regressions. | Facilitators for PA: Overall, 51.3% of adolescents enrolled in the closest school (range across schools: 28.3% to 81.6%). Adolescents enrolled in the closest school had five-times higher rates of active transport (46.5% vs. 8.8%) and lower rates of motorised transport to school (40.3% vs. 68.8%) compared to their counterparts (all p < 0.05). |
Mandic, S. et al. [47], New Zealand, Health Research Council of New Zealand Emerging Researcher First Grant, the National Heart Foundation of New Zealand, a Lottery Health Research Grant, a University of Otago Research Grant, the Dunedin City Council. | This study examined parents’ and adolescents’ perceptions of school bag weights and actual school bag weights for adolescents in New Zealand. | Cross-sectional study/socio-ecological model | Parents (n = 331; 76.7% women; 6.0% Maori) and adolescents (n = 682; age 15.1 SD 1.4 years; 57.3% boys; 10.9% Maori). | Parents and adolescents completed the BEATS Study Parental or Student Survey, respectively. Survey questions were related to demographics (age, gender, ethnicity), travel to school behaviours, and perceptions of walking and cycling to school. Home and school addresses were geocoded (converted into coordinates), then used to calculate distance to school using the shortest path on a connected street network using geographic information system (GIS) network analysis. Height (custom-built portable stadiometer), weight (A&D scale UC321, A&D Medical, San Jose, CA, USA), and waist circumference were collected from adolescents. | Barriers to PA: -Overall, 68.3% of parents perceived that adolescents’ school bags were too heavy to carry to school. This parental perception differed by adolescents’ mode of transport to school (active/motorized/combined: 35.1%/78.4%/68.8%, p < 0.001). -Adolescents perceived that their school bags were too heavy to carry to walk (57.8%) or cycle (65.8%) to school. -Adolescent perceptions differed by mode of transport to school (for walking (active/motorized/combined): 30.9%/69.2%/55.9% agree, p < 0.001; for cycling: 47.9%/72.8%/67.7%; p < 0.001). |
Mandic, S. et al. [48], New Zealand, Health Research Council of New Zealand Emerging Researcher First Grant, National Heart Foundation of New Zealand, Lottery Health Research Grant, University of Otago Research Grant and Dunedin City Council. | The purpose of this study was two-fold: (a) to compare parental perceptions of walking versus cycling to school in an urban setting; and, (b) to examine if those parental perceptions of motivations for, and barriers to, walking and cycling to school differed based on distance between adolescents’ home and their school. | Cross-sectional study/socio-ecological model. | Parents (n = 341; age: 47.5 ± 5.2 years; 77.1% females; Maori = 6.6% and Pacific = 1.5%) completed a survey about their adolescent’s (age: 13–18 years; 48.1% boys) school travel and their own perceptions of walking/cycling to school. | Parents completed the BEATS Study Parental Survey. The geocoded home address was also used to calculate distance from home to adolescents’ school based on the shortest path on a connected street network using geographic information system (GIS) network analysis. Participants were categorised into three groups according to distance to school as “walkable” (2.25 km), “cyclable” (>2.25–4.0 km), and “beyond cyclable” (>4.0 km). The 4-point or 7-point Likert scale data were analysed as continuous variables with paired t-tests to compare parental perceptions of walking versus cycling to school. One-way ANOVA with Scheffe post hoc multiple comparisons or, when the assumption of homogeneity of variance was violated, Tamahane’s T2 test for comparisons across three distances to school categories were used. Comparison across two distances to school categories were conducted using an independent t-test or Mann-Whitney U test. | Common modes of transport to school differed significantly across the ‘walkable’/’cyclable’/’beyond cyclable’ categories (car passenger: 25.7%/40.5%/60.6%; public/school bus: 5.5%/15.4%/28.4%; walking: 66.2%/28.2%/1.2%; cycling: 0.0%/7.7%/0.5%; all p < 0.001). Barriers to PA: Compared to walking, parents perceived cycling to school to be less important (walking/cycling: 87.5%/62.5%), with less social support from parents (46.2%/17.1%), peers (20.6%/4.8%), and school (24.5%/12.4%), less interest from adolescents (48.5%/31.9%), fewer cycle paths (26.5%) versus footpaths (65.0%), and more safety concerns (35.0%/64.6%; all p < 0.001). |
Pengpid, S. & Peltzer, K. [49], Cook Islands, Kiribati, Samoa, Solomon Islands, Tonga, Tuvalu and Vanuatu, WHO and Ministries of Education and Health in each country. | The aim of this investigation was to estimate the relationship between parental involvement and health behaviour and mental health among school-going adolescents in seven Pacific Island countries. | A secondary analysis of cross-sectional data using a two-stage cluster sampling study design/NR. | The sample included 10,968 school-going adolescents (mean age 14.1 years, SD = 1.4) from Cook Islands (overall response rate = 84%, n = 1274), Kiribati (85%, 1582), Samoa (79%, n = 2418), Solomon Islands (85%, n = 2211), Tonga (80%, n = 943), Tuvalu (90%, n = 943), and Vanuatu (response rate = 72%, n = 1119). | The “Global School-based Student Health Survey”(GSHS) comprises ten modules on various health behaviours, protective factors, and demographics. Pearson Chi-square statistics for categorical variables and ANOVA for continuous variables to calculate differences in proportion. | Overall, only 14.1% of the participants met daily PA recommendations, ranging from 10.8% in Vanuatu to 19.7% in Cook Islands. Facilitators for PA: -Parental involvement covered 4 areas: supervision (ranging from lowest 23.0% in Kiribati to highest 41.7% in Samoa), connectedness (15.3% in Kiribati to 32.6% in Samoa), bonding (18.8% in Tuvalu to 36.2% in Cook Islands), and respect of privacy (40.9% in Solomon Islands to 86.8% Tuvalu). -Higher parental involvement scores were positively correlated with meeting physical activity recommendations. Potential physical activity promoting strategies identified: -Parenting support programs, such as health-promoting strengthening activities for parents and children, should be supported in the study countries, to eventually improve health promotion targets. |
Sheridan, S.A. et al. [55], Vanuatu, European Union’s Seventh Framework Program and the Australian Government’s NH&MRC-European Union Collaborative Research Grants. | This paper examined the perspectives of youth in Vanuatu on essential health needs in the context of the post-2015 development agenda, to make these concerns more visible for their communities, stakeholders, and health policy decision makers. | Qualitative study/NR. | The sample included twenty 17 year old secondary school students in Vanuatu. | Two focus group sessions, each consisting of 5 male and 5 female participants. A deductive thematic analysis was conducted. | Barriers to PA: -Local village leaders were often not reinforcing the government’s health promotion activities, and were seen to disregard the importance of PA. |
Tuagalu, C. [50], Samoa, NR. | The research questions were (1) What are Samoan people’s perceptions and experiences of physical activity? (2) What barriers make it less likely that they will participate in physical activity? (3) What factors would make it easier for Samoan people to participate in physical activity? | Cross-sectional study/NR. | The sample included 801 participants from Samoa aged between 13–50 years, with 76% of the sample in the 13–18 years age group and two thirds (66%) were females. | The survey included questions that explored perceptions about physical activity, health, barriers to physical activity, sources of encouragement, and demographic trends. The data was analysed descriptively using Excel 2007 and SPSS. | Barriers to PA: -The participants reported that cultural (family, housework, and church), environmental (e.g., village curfew restrictions, safety—particularly from dogs, lack of footpaths), and discomfort (e.g., boring, too much effort) barriers were most likely to affect their participation in physical activity. Facilitators for PA: -The participants reported that their friends, school, church, doctor, partner, and village were a main source of encouragement to being physically active. -Most participants had a positive attitude towards physical activity, and more than half of them wanted to be more active. |
Vancampfort, D. et al. [51], Kiribati, Samoa, Solomon Islands, Tonga, Vanuatu, Fiji and Tuvalu, no funding. | The study identified PA correlates including demographic variables (age, gender), policy related variables (e.g., provision of physical education classes), socio-environmental factors (e.g., food insecurity as a measure of proxy for socio-economic status, parental support, bullying), health behavior related variables (e.g., smoking, alcohol use, diet pattern), and health-related variables (obesity) among adolescents aged 12–15 years living in a LMIC and who participated in the Global school-based Student Health Survey (GSHS). | Cross-sectional study/NR. | The final sample consisted of 142,118 adolescents aged 12–15 years with a mean (SD) age of 13.8 (1.0) years, and 49.0% were girls. From the total sample, data from the following PICTs were included: Kiribati (collected in 2011; 85% participation rate), Samoa (2011; 79%), Solomon Islands (2011; 85%), Tonga (2010; 80%), Vanuatu (2011; 72%), Fiji (2016; 79%), and Tuvalu (2013; 90%) only. | Data from the Global school-based Student Health Survey (GSHS) were analysed. A multivariable logistic regression analysis was employed to assess the association between each correlate (exposure) and adequate PA (outcome). The analysis was adjusted for age, sex, and food in-security (proxy of low socioeconomic status). The association of age, sex, and food security with adequate PA was assessed with a model that mutually adjusted for these three variables. | Barriers to PA: -Adolescents with food insecurity (OR = 0.85; 95% CI = 0.80–0.90), low parental support/monitoring (OR = 0.68; 95% CI = 0.62–0.74), no friends (OR = 0.80; 95% CI = 0.72–0.88), and who experienced bullying (OR = 0.93; 95% CI = 0.86–0.99) were less likely to have adequate levels of PA. Facilitators for PA: Boys (OR = 1.64; 95% CI = 1.47–1.83) and those who participated in physical education for ≥5 days/week (OR = 1.12; 95% CI = 1.10–1.15) were more likely to meet PA guidelines. |
Vargo, D. et al. [52], Samoa, US Department of Agriculture National Research Initiative | To describe a serious public health hazard in American Samoa that may plague other jurisdictions that tolerate a significant free-roaming dog population. | Cross-sectional questionnaire/NR | A survey of 437 adolescents (13–18 years; 220 males and 217 females) documented their experiences regarding unprovoked dog attacks. | The survey was designed to measure knowledge, attitudes, and practices regarding nutrition and exercise. Chi-square tests were performed using SigmaStat 3.1. | Barriers to PA: -About one-third of adolescents reported having been bitten by a dog between September 2010 and May 2011. About 10% of males and 17% of females attributed the fear of being bitten as a factor preventing them from being physically active. -Only “lack of time” and “lack of energy” elicited a greater number of responses than did the fear of being bitten. |
Waqa, G. et al. [56], Fiji, Welcome Trust (in the UK) and the Fiji Health Sector Improvement Project of the Ministry of Health (MoH) of Fiji, | This paper describes the process evaluation for the Healthy Youth Healthy Communities project, undertaken in Fiji between 2006 and 2008. Process evaluation is important to determine whether the intervention was implemented as planned; to describe the intervention activities in terms of dose, frequency, and reach; and to identify any barriers to implementation. | Process evaluation/NR | A data collection proforma was developed to collate information about intervention planning and delivery activities (a description of the activity), processes (how the activity was conducted), dose (scale/duration of the activity), reach (how many and type of people involved in the activity), frequency (how often the activity was conducted), and associated resource use (for use in a subsequent economic evaluation). These data were supplemented by intervention reports, meeting minutes, correspondence, and communication between the research team staff and other personnel involved. A study manager, project coordinator and four research assistants (RAs) collected the data and completed the proformas. | Data were entered into an Excel database: more than 600 entries were recorded throughout the 2-year duration of intervention activities. Thematic analysis according to the four objectives of the Healthy Youth Healthy Communities project was conducted. | Facilitators for PA: -Walking, traditional dance, and aerobics. -Physical activity was often integrated successfully into the promotion of other strategies, such as the consumption of a healthy breakfast, fruit, vegetables, and water, especially during athletics season. |
Author (Year) | 1. Qualitative | 4. Quantitative | Quality of Studies (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1.1 Approach Appropriate to the Research Question | 1.2 Data Collection Methods Adequate | 1.3 Findings Adequately Derived from Data | 1.4 Interpretation of Results Substantiated by Data | 1.5 Coherence between the Data Source, Collection, Analysis, Interpretation | 4.1 Sampling Strategy Relevant to the Research Question | 4.2 The Sample Representative of the Population | 4.3 Measurements Appropriate | 4.4 Risk of Nonresponse Bias Low | 4.5 Statistical Analysis Appropriate to the Research Question | ||
Collier [57] | Yes | Yes | Yes | No | Yes | 80 | |||||
Curtis [53] | Yes | Yes | Yes | No | Yes | 80 | |||||
Fotu [44] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Hohepa [54] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Mandic [45] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Mandic [46] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Mandic [47] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Mandic [48] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Pengpid [49] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Sheridan [55] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Tuagalu [50] | Yes | Yes | No | Yes | No | 60 | |||||
Vancampfort [51] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Vargo [52] | Yes | Yes | Yes | Yes | Yes | 100 | |||||
Waqa [56] | Yes | Yes | No | Yes | No | 60 |
Socio-Ecological Level | Description of Barrier/Facilitator | Study Reference, Income (High (H), Middle to High (MH), Low to Middle (LM) and Low (L)) and Reporting Barrier (B)/Facilitator (F) | Total Number of B and F | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Collier [57], H | Curtis [53], H | Fotu [44], MH | Hohepa [54], H | Mandic [45], H | Mandic [46], H | Mandic [47], H | Mandic [48], H | Pengpid [49], MH, LM, L | Sheridan [55], LM | Tuagalu [50], LM | Vancampfort [51], MH, LM, L | Vargo [52], LM | Waqa [56], MH | B | F | ||
Individual | |||||||||||||||||
Time | B | B | 2 | ||||||||||||||
Play | F | 1 | |||||||||||||||
Fun | F | F | 2 | ||||||||||||||
Preferential activity | F | 1 | |||||||||||||||
Positive self-esteem | F | 1 | |||||||||||||||
Feelings of achievement | F | 1 | |||||||||||||||
Physical health benefits | F | 1 | |||||||||||||||
Physical appearance | F | 1 | |||||||||||||||
Mood, confidence | F | 1 | |||||||||||||||
Low interest | B | B | 2 | ||||||||||||||
Discomfort/sweaty | B | B | 2 | ||||||||||||||
Energy | B | 1 | |||||||||||||||
Interpersonal | |||||||||||||||||
Friends/PA partner | F | F | B | F | 1 | 3 | |||||||||||
Money | B | 1 | |||||||||||||||
Transportation | B | 1 | |||||||||||||||
Bullying/no friends | B | 1 | |||||||||||||||
Walking to school | F | 1 | |||||||||||||||
Parental support and involvement | F | F | F | F | 4 | ||||||||||||
Connection to cultural practices (e.g., church, traditional dance, walking) | BF | F | 1 | 2 | |||||||||||||
Heavy school bags | B | 1 | |||||||||||||||
Community | |||||||||||||||||
Medical/doctor support | F | 1 | |||||||||||||||
Address socio-cultural factors | F | 1 | |||||||||||||||
Community leaders’ support | F | F | F | 3 | |||||||||||||
Weather conditions | B | B | 2 | ||||||||||||||
Minimal indoor facilities for PA/sport | B | 1 | |||||||||||||||
Distance for active transport | B | F | 1 | 1 | |||||||||||||
Safety | B | B | B | B | B | 5 | |||||||||||
Fear of dogs and dog bites | B | B | 2 | ||||||||||||||
Inadequate footpaths/cycle paths | B | B | 2 | ||||||||||||||
Structure of PA/sport opportunities | B | B | 2 | ||||||||||||||
Policy/institutional | |||||||||||||||||
Availability and continual access to PA/sport programs | F | 1 | |||||||||||||||
PE in schools 5 days/week | F | 1 | |||||||||||||||
Food insecurity | B | 1 | |||||||||||||||
Village curfews | B | 1 |
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Peralta, L.R.; Cinelli, R.L.; Cotton, W.; Morris, S.; Galy, O.; Caillaud, C. The Barriers to and Facilitators of Physical Activity and Sport for Oceania with Non-European, Non-Asian (ONENA) Ancestry Children and Adolescents: A Mixed Studies Systematic Review. Int. J. Environ. Res. Public Health 2022, 19, 11554. https://doi.org/10.3390/ijerph191811554
Peralta LR, Cinelli RL, Cotton W, Morris S, Galy O, Caillaud C. The Barriers to and Facilitators of Physical Activity and Sport for Oceania with Non-European, Non-Asian (ONENA) Ancestry Children and Adolescents: A Mixed Studies Systematic Review. International Journal of Environmental Research and Public Health. 2022; 19(18):11554. https://doi.org/10.3390/ijerph191811554
Chicago/Turabian StylePeralta, Louisa R., Renata L. Cinelli, Wayne Cotton, Sarah Morris, Olivier Galy, and Corinne Caillaud. 2022. "The Barriers to and Facilitators of Physical Activity and Sport for Oceania with Non-European, Non-Asian (ONENA) Ancestry Children and Adolescents: A Mixed Studies Systematic Review" International Journal of Environmental Research and Public Health 19, no. 18: 11554. https://doi.org/10.3390/ijerph191811554