Review of Short-Form Questions for the Evaluation of a Diet, Physical Activity, and Sedentary Behaviour Intervention in a Community Program Targeting Vulnerable Australian Children
Abstract
:1. Introduction
2. Results
2.1. Diet Questionnaires
2.2. Physical Activity and Sedentary Behaviour Questionnaires
2.3. Diet and Physical Activity/Sedentary Behaviour Questionnaires in Aboriginal and Torres Strait Islander Groups
2.4. Quality Ratings
3. Discussion
4. Materials and Methods
4.1. Search Criteria
4.2. Selection and Inclusion Criteria
- components of diet, physical activity or sedentary behaviour questions relevant to current Australian nutrition and physical activity/sedentary behaviour policies for those aged 5–12 and 13–17 years, or that make a significant contribution to components of concern identified in policy documents; and
- short questionnaires with ≤50 items for diet [44] and ≤15 items for physical activity (expert opinion); and
- validity or reliability information in the population of interest (7–13 year old Australians); and
- questionnaire administration details indicating completion by children/adolescents or parent proxy.
4.3. Data Extraction
4.4. Assessment of Quality
“Were the statistical tests used appropriate to assess reliability for the main physical activity constructs between tests for the self-report measure?”(The statistical techniques used must be appropriate to the data e.g., intra-class correlation co-efficient, weighted kappa).
4.5. Recommendations on Questions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Broyles, S.T.; Denstel, K.D.; Church, T.S.; Chaput, J.P.; Fogelholm, M.; Hu, G.; Kuriyan, R.; Kurpad, A.; Lambert, E.V.; Maher, C.; et al. The epidemiological transition and the global childhood obesity epidemic. Int. J. Obes. Suppl. 2015, 5, S3–S8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hardy, L.L.; Mihrshahi, S.; Gale, J.; Drayton, B.A.; Bauman, A.; Mitchell, J. 30-year trends in overweight, obesity and waist-to-height ratio by socioeconomic status in australian children, 1985 to 2015. Int. J. Obes. 2017, 41, 76–82. [Google Scholar] [CrossRef] [PubMed]
- World Health Organisation. Report of the Commission on Ending Childhood Obesity; World Health Organisation: Geneva, Switzerland, 2016. [Google Scholar]
- Sanders, R.H.; Han, A.; Baker, J.S.; Cobley, S. Childhood obesity and its physical and psychological co-morbidities: A systematic review of Australian children and adolescents. Eur. J. Pediatr. 2015, 174, 715–746. [Google Scholar] [CrossRef] [PubMed]
- Pulgaron, E.R. Childhood obesity: A review of increased risk for physical and psychological comorbidities. Clin. Ther. 2013, 35, A18–A32. [Google Scholar] [CrossRef] [PubMed]
- Laitinen, J.; Power, C.; Jarvelin, M.R. Family social class, maternal body mass index, childhood body mass index, and age at menarche as predictors of adult obesity. Am. J. Clin. Nutr. 2001, 74, 287–294. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Singh, A.S.; Mulder, C.; Twisk, J.W.; van Mechelen, W.; Chinapaw, M.J. Tracking of childhood overweight into adulthood: A systematic review of the literature. Obes. Rev. 2008, 9, 474–488. [Google Scholar] [CrossRef] [PubMed]
- Ma, S.; Frick, K.D. A simulation of affordability and effectiveness of childhood obesity interventions. Acad. Pediatr. 2011, 11, 342–350. [Google Scholar] [CrossRef] [PubMed]
- Doring, N.; Mayer, S.; Rasmussen, F.; Sonntag, D. Economic evaluation of obesity prevention in early childhood: Methods, limitations and recommendations. Int. J. Environ. Res. Public Health 2016, 13, 911. [Google Scholar] [CrossRef] [PubMed]
- John, J.; Wolfenstetter, S.B.; Wenig, C.M. An economic perspective on childhood obesity: Recent findings on cost of illness and cost effectiveness of interventions. Nutrition 2012, 28, 829–839. [Google Scholar] [CrossRef] [PubMed]
- Wen, L.M.; Baur, L.A.; Simpson, J.M.; Rissel, C.; Wardle, K.; Flood, V.M. Effectiveness of home based early intervention on children’s BMI at age 2: Randomised controlled trial. Br. Med. J. 2012, 344. [Google Scholar] [CrossRef] [PubMed]
- Wen, L.M.; Baur, L.A.; Rissel, C.; Flood, V.; Simpson, J.M.; Hayes, A.; Hardy, L.L.; Wardle, K. Healthy beginnings trial phase 2 study: Follow-up and cost-effectiveness analysis. Contemp. Clin. Trials 2012, 33, 396–401. [Google Scholar] [CrossRef] [PubMed]
- Oude Luttikhuis, H.; Baur, L.; Jansen, H.; Shrewsbury, V.A.; O’Malley, C.; Stolk, R.P.; Summerbell, C.D. Interventions for treating obesity in children. Cochrane Database Syst. Rev. 2009. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Berry, D.; Melkus, G.; Savoye, M.; Grey, M. An intervention for multiethnic obese parents and overweight children. Appl. Nurs. Res. 2007, 20, 63–71. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Australian Bureau of Statistics. 4364.0.55.001—National Health Survey: First Results, 2014–2015. Available online: http://www.abs.gov.au/ausstats/[email protected]/Lookup/by%20Subject/4364.0.55.001~2014-15~Main%20Features~Children’s%20risk%20factors~31 (accessed on 14 July 2017).
- Australian Bureau of Statistics. 4727.0.55.001—Australian Aboriginal and Torres Strait Islander Health Survey: First Results, Australia, 2012–2013. Available online: http://www.abs.gov.au/ausstats/[email protected]/Lookup/A07BD8674C37D838CA257C2F001459FA?opendocument (accessed on 14 July 2017).
- Australian Bureau of Statistics. 4364.0.55.003—Australian Health Survey: Updated Results, 2011–2012. Available online: http://www.abs.gov.au/ausstats/[email protected]/Lookup/33C64022ABB5ECD5CA257B8200179437?opendocument (accessed on 14 July 2017).
- Nichols, M.S.; Reynolds, R.C.; Waters, E.; Gill, T.; King, L.; Swinburn, B.A.; Allender, S. Community-based efforts to prevent obesity: Australia-wide survey of projects. Health Promot. J. Aust. 2013, 24, 111–117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pettman, T.; Bolton, K.; Love, P.; Waters, E.; Gill, T.; Whelan, J.; Boylan, S.; Armstrong, R.; Coveney, J.; Booth, S.; et al. A snapshot of the scope of obesity prevention practice in Australia. Health Promot. Int. 2016, 31, 582–594. [Google Scholar] [CrossRef] [PubMed]
- Moores, C.J.; Miller, J.; Perry, R.A.; Chan, L.L.H.; Daniels, L.A.; Vidgen, H.A.; Magarey, A.M. Consort to community: Translation of an RCT to a large-scale community intervention and learnings from evaluation of the upscaled program. BMC Public Health 2017, 17, 918. [Google Scholar] [CrossRef] [PubMed]
- Welsby, D.; Nguyen, B.; O’Hara, B.J.; Innes-Hughes, C.; Bauman, A.; Hardy, L.L. Process evaluation of an up-scaled community based child obesity treatment program: NSW Go4Fun®. BMC Public Health 2014, 14, 140. [Google Scholar] [CrossRef] [PubMed]
- Henderson, L.; Lukeis, S.; O’Hara, B.; McGill, B.; Innes-Hughes, C.; Rissel, C. Go4Fun®: Evidence and Evaluation Summary (2011–2015); NSW Ministry of Health: North Sydney, Australia, 2016.
- Kolotourou, M.; Radley, D.; Gammon, C.; Smith, L.; Chadwick, P.; Sacher, P.M. Long-term outcomes following the MEND 7–13 child weight management program. Child. Obes. 2015, 11, 325–330. [Google Scholar] [CrossRef] [PubMed]
- Sacher, P.M.; Kolotourou, M.; Chadwick, P.M.; Cole, T.J.; Lawson, M.S.; Lucas, A.; Singhal, A. Randomized controlled trial of the MEND program: A family-based community intervention for childhood obesity. Obesity 2010, 18 (Suppl. 1), S62–S68. [Google Scholar] [CrossRef] [PubMed]
- Flood, V.; Gwynn, J.; Gifford, J.; Tuner, N.; Hardy, L. Evidence on Existing, Validated Short-Form Survey Instruments for Children’s Diet, Physical Activity, and Sedentary Behaviour: An Evidence Check Review Brokered by the Sax Institute (www.Saxinstitute.Org.Au) for the NSW Ministry of Health, 2016; Sax Institute: Ultimo, Australia, 2016; Available online: https://www.saxinstitute.org.au/category/publications/ (accessed on 29 March 2018).
- Finch, M.; Begley, A.; Sutherland, R.; Harrison, M.; Collins, C. Development and reproducibility of a tool to assess school food-purchasing practices and lifestyle habits of Australian primary school-aged children. Nutr. Diet. 2007, 64, 86–92. [Google Scholar] [CrossRef]
- Hendrie, G.A.; Viner Smith, E.; Golley, R.K. The reliability and relative validity of a diet index score for 4-11-year-old children derived from a parent-reported short food survey. Public Health Nutr. 2014, 17, 1486–1497. [Google Scholar] [CrossRef] [PubMed]
- Magarey, A.; Golley, R.; Spurrier, N.; Goodwin, E.; Ong, F. Reliability and validity of the Children’s Dietary Questionnaire; a new tool to measure children’s dietary patterns. Int. J. Pediatr. Obes. 2009, 4, 257–265. [Google Scholar] [CrossRef] [PubMed]
- Gwynn, J.D.; Flood, V.M.; D’Este, C.A.; Attia, J.R.; Turner, N.; Cochrane, J.; Wiggers, J.H. On Behalf of the Many Rivers Diabetes Prevention Project Study Team. The reliability and validity of a short FFQ among Australian Aboriginal and Torres Strait Islander and non-Indigenous rural children. Public Health Nutr. 2011, 14, 388–401. [Google Scholar] [CrossRef] [PubMed]
- Wilson, A.M.; Magarey, A.M.; Mastersson, N. Reliability and relative validity of a child nutrition questionnaire to simultaneously assess dietary patterns associated with positive energy balance and food behaviours, attitudes, knowledge and environments associated with healthy eating. Int. J. Behav. Nutr. Phys. Act. 2008, 5, 5. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Booth, M.L.; Okely, A.D.; Chey, T.N.; Bauman, A. The reliability and validity of the Adolescent Physical Activity Recall Questionnaire. Med. Sci. Sports Exerc. 2002, 34, 1986–1995. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gwynn, J.D.; Hardy, L.L.; Wiggers, J.H.; Smith, W.T.; D’Este, C.A.; Turner, N.; Cochrane, J.; Barker, D.J.; Attia, J.R. The validation of a self-report measure and physical activity of Australian Aboriginal and Torres Strait Islander and non-Indigenous rural children. Aust. N. Z. J. Public Health 2010, 34 (Suppl. 1), S57–S65. [Google Scholar] [CrossRef] [PubMed]
- Lubans, D.; Morgan, P. Impact of an extra-curricular school sport programme on determinants of objectively measured physical activity among adolescents. Health Educ. J. 2008, 67, 305–320. [Google Scholar] [CrossRef]
- Prochaska, J.J.; Sallis, J.F.; Long, B. A physical activity screening measure for use with adolescents in primary care. Arch. Pediatr. Adolesc. Med. 2001, 155, 554–559. [Google Scholar] [CrossRef] [PubMed]
- Hardy, L.L.; Bass, S.L.; Booth, M.L. Changes in sedentary behavior among adolescent girls: A 2.5-year prospective cohort study. J. Adolesc. Health 2007, 40, 158–165. [Google Scholar] [CrossRef] [PubMed]
- Hardy, L.L.; Booth, M.L.; Okely, A.D. The reliability of the Adolescent Sedentary Activity Questionnaire (ASAQ). Prev. Med. 2007, 45, 71–74. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Leech, R.M.; McNaughton, S.A.; Timperio, A. Clustering of children’s obesity-related behaviours: Associations with sociodemographic indicators. Eur. J. Clin. Nutr. 2014, 68, 623–628. [Google Scholar] [CrossRef] [PubMed]
- Salmon, J.; Timperio, A.; Telford, A.; Carver, A.; Crawford, D. Association of family environment with children’s television viewing and with low level of physical activity. Obes. Res. 2005, 13, 1939–1951. [Google Scholar] [CrossRef] [PubMed]
- Moore, H.J.; Ells, L.J.; McLure, S.A.; Crooks, S.; Cumbor, D.; Summerbell, C.D.; Batterham, A.M. The development and evaluation of a novel computer program to assess previous-day dietary and physical activity behaviours in school children: The Synchronised Nutrition and Activity Program (SNAP). Br. J. Nutr. 2008, 99, 1266–1274. [Google Scholar] [CrossRef] [PubMed]
- Strugnell, C.; Renzaho, A.; Ridley, K.; Burns, C. Reliability of the modified Child and Adolescent Physical Activity and Nutrition Survey, Physical Activity (CAPANS-PA) Questionnaire among Chinese-Australian youth. BMC Med. Res. Methodol. 2011, 11, 122. [Google Scholar] [CrossRef] [PubMed]
- Telford, A.; Salmon, J.; Jolley, D.; Crawford, D. Reliability and validity of physical activity questionnaires for children: The Children’s Leisure Activities Study Survey (CLASS). Pediatr. Exerc. Sci. 2004, 16, 64–78. [Google Scholar] [CrossRef]
- Active Healthy Kids Australia. Is Sport Enough? The 2014 Active Healthy Kids Australia Report Card on Physical Activity for Children and Young People; Active Healthy Kids Australia: Adelaide, Australia, 2014. [Google Scholar]
- Trost, S.G.; Marshall, A.L.; Miller, R.; Hurley, J.T.; Hunt, J.A. Validation of a 24-h physical activity recall in Indigenous and non-Indigenous Australian adolescents. J. Sci. Med. Sport 2007, 10, 428–435. [Google Scholar] [CrossRef] [PubMed]
- Golley, R.K.; Bell, L.K.; Hendrie, G.A.; Rangan, A.M.; Spence, A.; McNaughton, S.A.; Carpenter, L.; Allman-Farinelli, M.; de Silva, A.; Gill, T.; et al. Validity of short food questionnaire items to measure intake in children and adolescents: A systematic review. J. Hum. Nutr. Diet. 2016. [Google Scholar] [CrossRef] [PubMed]
- Nelson, M.; Bingham, S. Assessment of food consumption and nutrient intake. In Design Concepts in Nutritional Epidemiology, 2nd ed.; Margetts, B., Nelson, M., Eds.; Oxford University Press: Oxford, UK, 1997; pp. 123–169. [Google Scholar]
- Collins, C.E.; Bucher, T.; Taylor, A.; Pezdirc, K.; Lucas, H.; Watson, J.; Rollo, M.; Duncanson, K.; Hutchesson, M.J.; Burrows, T. How big is a food portion? A pilot study in Australian families. Health Promot. J. Aust. 2015, 26, 83–88. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zheng, M.; Wu, J.H.; Louie, J.C.; Flood, V.M.; Gill, T.; Thomas, B.; Cleanthous, X.; Neal, B.; Rangan, A. Typical food portion sizes consumed by Australian adults: Results from the 2011–12 Australian National Nutrition and Physical Activity Survey. Sci. Rep. 2016, 6, 19596. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baranowski, T. Validity and reliability of self report measures of physical activity: An information-processing perspective. Res. Q. Exerc. Sport 1988, 59, 314–327. [Google Scholar] [CrossRef]
- Sallis, J.F. Self-report measures of children’s physical activity. J. Sch. Health 1991, 61, 215–219. [Google Scholar] [CrossRef] [PubMed]
- Sirard, J.R.; Pate, R.R. Physical activity assessment in children and adolescents. Sports Med. 2001, 31, 439–454. [Google Scholar] [CrossRef] [PubMed]
- Willis, E.A.; Ptomey, L.T.; Szabo-Reed, A.N.; Honas, J.J.; Lee, J.; Washburn, R.A.; Donnelly, J.E. Length of moderate-to-vigorous physical activity bouts and cardio-metabolic risk factors in elementary school children. Prev. Med. 2015, 73, 76–80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Poitras, V.J.; Gray, C.E.; Borghese, M.M.; Carson, V.; Chaput, J.P.; Janssen, I.; Katzmarzyk, P.T.; Pate, R.R.; Gorber, S.C.; Kho, M.E.; et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl. Physiol. Nutr. Metab. 2016, 41, S197–S239. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chinapaw, M.J.; Mokkink, L.B.; van Poppel, M.N.; van Mechelen, W.; Terwee, C.B. Physical activity questionnaires for youth: A systematic review of measurement properties. Sports Med. 2010, 40, 539–563. [Google Scholar] [CrossRef] [PubMed]
- Pedisic, Z.; Zhong, A.; Hardy, L.L.; Salmon, J.; Okely, A.D.; Chau, J.; van der Ploeg, H.P.; Bauman, A. Physical activity prevalence in Australian children and adolescents: Why do different surveys provide so different estimates, and what can we do about it? Kinesiology 2017, 49, 135–145. [Google Scholar] [CrossRef]
- Australian Government Department of Health. Australia’s Physical Activity and Sedentary Behaviour Guidelines. Available online: http://www.health.gov.au/internet/main/publishing.nsf/Content/health-pubhlth-strateg-phys-act-guidelines (accessed on 31 January 2018).
- Chaput, J.P.; Klingenberg, L.; Astrup, A.; Sjodin, A.M. Modern sedentary activities promote overconsumption of food in our current obesogenic environment. Obes. Rev. 2011, 12, e12–e20. [Google Scholar] [CrossRef] [PubMed]
- Tremblay, M.S.; LeBlanc, A.G.; Kho, M.E.; Saunders, T.J.; Larouche, R.; Colley, R.C.; Goldfield, G.; Connor Gorber, S. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int. J. Behav. Nutr. Phys. Act. 2011, 8, 98. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lenhart, A. Teens, Smartphones & Texting; Pew Research Center’s Internet and American Life Project: Washington, DC, USA, 2012. [Google Scholar]
- Weerakkody, N. Mobile phones and children: An Australian perspective. In Proceedings of the 2008 Informing Science + Information Technology Education Conference, Varna, Bulgaria, 22–25 June 2008; Informing Science Institute: Varna, Bulgaria, 2008. [Google Scholar]
- Thurber, K.A.; Dobbins, T.; Neeman, T.; Banwell, C.; Banks, E. Body mass index trajectories of Indigenous Australian children and relation to screen time, diet, and demographic factors. Obesity 2017, 25, 747–764. [Google Scholar] [CrossRef] [PubMed]
- Crowe, R.; Stanley, R.; Probst, Y.; McMahon, A. Culture and healthy lifestyles: A qualitative exploration of the role of food and physical activity in three urban Australian indigenous communities. Aust. N. Z. J. Public Health 2017, 41, 411–416. [Google Scholar] [CrossRef] [PubMed]
- Croyden, D. PEACHTM QLD Final Report; Queensland Government Department of Health: Brisbane, Australia, 2016.
- Wood, A.; Johnson, M. Green Prescriptions (GRX) Active Families Survey Report; Ministry of Health: Wellington, DC, USA, 2015.
- Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred reporting items for systematic reviews and meta-analyses: The prisma statement. J. Clin. Epidemiol. 2009, 62, 1006–1012. [Google Scholar] [CrossRef] [PubMed]
- Hagstromer, M.; Ainsworth, B.E.; Kwak, L.; Bowles, H.R. A checklist for evaluating the methodological quality of validation studies on self-report instruments for physical activity and sedentary behavior. J. Phys. Act. Health 2012, 9 (Suppl. 1), S29–S36. [Google Scholar] [CrossRef] [PubMed]
- Downs, S.H.; Black, N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J. Epidemiol. Community Health 1998, 52, 377–384. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Reference | Setting | Design | Sample | Questionnaire | Administration | Statistics |
---|---|---|---|---|---|---|
Finch et al., 2007 [26] | Local government primary school (Hunter Region, New South Wales (NSW), Australia). | Questionnaire development and reliability testing. Administered one week apart for reliability testing. | n = 245 children from Year 4 (n = 88), Year 5 (n = 84), Year 6 (n = 73). Mean age 10.7 ± 0.91 years. 52% F Ethnicity not indicated. | The School Food Eating Habits and Lifestyle Survey (SEHLS) with 35 items, including 27 on assessing “usual” food habits, five on “usual” physical activity and sedentary pursuits, and three on demographic variables. | Self-administered in class by children with teacher supervision. The questionnaire took around 30 min to complete in pilot testing. | Reliability Kappa 0.18–0.68 for food habit questions. All were within the 95% CI. |
Gwynn et al., 2011 [29] | Many Rivers Diabetes Prevention Project. Eleven Department of Education and Training primary schools in three regional areas (north coast, NSW, Australia). | A short FFQ was completed twice, two weeks apart (reliability) and compared with the mean of three 24-h recalls (validity). | Reliability n = 241 age not specified. 59% F n = 92 Aboriginal and Torres Strait Islander, n = 149 non-Indigenous Validity n = 205 10–12 years, mean age 10.8 ± 0.7 years 58% F n = 78 Aboriginal and Torres Strait Islander children n = 127 non-Indigenous children | The Short Food Frequency Questionnaire (SFFQ) consisting of three demographic questions and 36 items (number of response categories 4–7) including 28 short questions on usual food intake. | Self-administered by the child. Culturally appropriate support was provided to Aboriginal and Torres Strait Islander children throughout the study. | Reliability Kappa 0.30–0.82. Validity 18 of 23 questions had increasing trends (p < 0.05) for mean daily weight and/or frequency as survey response categories increased. |
Hendrie et al., 2014 [27] | Various, Adelaide (South Australia (SA), Australia). | The questionnaire was completed twice, one week apart (reliability). This was compared against the mean of three 24-h recalls (validity). Daily intake was used to calculate diet quality from both the questionnaire and the 24-h recalls. | n = 63 4–11 years, mean age 7.1 ± 2.1 years 97% F (parents), 44% F (children). 69.8% “normal” weight; 15.9% overweight/obese. Ethnicity not indicated. Generally from high-income, well-educated families. | The Short Food Survey (SFS) consisting of 38 items on “usual” intake, including 35 on food and three on beverages. | The survey was completed online by the parent. | Reliability The ICC was 0.43–0.94 for food groups/beverages, and 0.92 for the total diet index score (all p < 0.01). Validity The ICC was 0.04–0.44 for food groups/beverages and 0.44 for the total diet index score (p < 0.01). Percentage agreement across tertiles of index scores was 84% between the administrations and 43% when comparing the SFS with the mean of the recalls. Bias values were within the 95% CI. |
Magarey et al., 2009 [28] | Five study samples of children from Adelaide (South Australia, Australia) and Sydney (NSW, Australia). | Reliability (studies 2 and 5; range 5–57 days between administration, median 10 days), internal consistency (Studies 1 (baseline), 3 and 5), and relative validity (Studies 4 and 5) using a 7-day food checklist, with the ability to detect change (Study 1). | n = 706 children (all five studies) age range 4–16 years Ethnicity not specified. Study 1 n = 168 (baseline) n = 132 (at 6 months) Age 5–10 years BMI z score ≥1.07–4.0 (22% overweight, 78% obese) Study 2 n = 39 Age 4–5 years 15% overweight, 7% obese Study 3 n = 280 Age 4–5 years 15% overweight, 6% obese Study 4 n = 126 Age 5–6 years Study 5 n = 92 (reliability), n = 87 (validity) Age 5–16 years 16% overweight, 1% obese. | The Children’s Dietary Questionnaire (CDQ), a 28-item semi-quantitative FFQ. Four separate food group scores were calculated. Scores reflected food group intake in the previous 24 h by dividing items that measured intake in the past week by seven before summing. | Self-administered by the parent or caregiver (with or without researcher assistance). A trained researcher responded in three studies and a parent responded in two studies. | Reliability ICC 0.51–0.90 (p < 0.001, studies 2 and 5). Validity Pearson’s correlations 0.31–0.60 (p < 0.001, studies 4 and 5). Internal consistency Alpha co-efficient 0.13–0.76. Item: total correlation range from (0.10–0.37) to (0.49–0.62). Ability to detect change Significant changes in the expected direction for dietary patterns (baseline vs. 6 months). |
Wilson et al., 2008 [30] | Eat well be active Community Programs, a community-based childhood obesity intervention project in South Australia. A mix of public and private, and metropolitan and rural primary schools. | Reliability (test–retest period not indicated/varied) and validity against 7-day food records (following both administrations of the questionnaire) was tested. | n = 134 (reliability), n = 117 (validity) 36% from Year 5, 33%, from Year 6, 31%, from Year 7 (not indicated which samples the proportions relate to). 10–12 years 62% F 66% attended metropolitan schools, 61% attended public schools. 14% overweight (9% M, 17% F), 6% obese (4% M, 8% F). Ethnicity not indicated. | The Child Nutrition Questionnaire (CNQ) assessing (a) dietary patterns relating to childhood obesity, and (b) behaviours, attitudes, environments and knowledge associated with healthy eating. 14 questions with a variable number of items; 12 scores were developed from the questionnaire and placed into five categories. | Self-administered by the child. Assistance was available. The questionnaire took 20 min to complete. | Reliability ICC 0.16–0.66. All were within 95% CI. Validity Spearman’s correlations 0.34–0.48 (all p < 0.01). Mean bias ranged from −1.2 to 0.6 and all values were within limits of agreement. |
Reference | Setting | Design | Sample | Questionnaire | Administration | Statistics |
---|---|---|---|---|---|---|
Booth et al., 2002 [31] | 44 randomly selected high schools from three education sectors across NSW (Australia). | The questionnaire was administered twice, two weeks apart (reliability). It was tested against the Multistage Fitness Test (MFT; validity). The validity study was conducted independently of the reliability study (different students at different schools). | Reliability n = 226 (n = 121 Year 8, n = 105 Year 10). Mean age 13.7 ± 0.40 years (Year 8), 15.7 ± 0.40 years (Year 10) 48% F (Year 8), 29% F (Year 10) Ethnicity not indicated Validity n = 2026 (n = 1072 Year 8, n = 954 Year 10) Mean age 13.1 years (SD not given; Year 8), 15.1 years (SD not given; Year 10) 48% F (Year 8), 45% F (Year 10) 82% English-speaking, 7.0% Asian, 4.5% Middle Eastern, 4.2% European, 2.6% did not respond or were otherwise classified. | The Adolescent Physical Activity Recall Questionnaire (APARQ): four items with sub-items (a list of up to seven activities with frequency and time reported for each). The four items ask about organised and non-organised activities undertaken in summer (terms 1 and 4) and winter (terms 2 and 3). | Self-administered by the child. | Reliability Per cent agreement 67–83% and weighted kappa 0.33–0.71 for the three-category measure (vigorously active, moderately active, inactive). Per cent agreement 76–90% and kappa 0.25–0.74 for the two-category measure (adequately active, inactive). ICC (95% CI) for total energy expenditure from 0.30 (0.05–0.51) to 0.91 (0.82–0.96). Validity Higher mean laps in the moderately and vigorously active categories than the inactive category for girls, but only the vigorously active and inactive categories were different for boys (three-category measure). Higher mean laps in active vs. inactive category for all groups (two-category measure). Spearman’s correlations (energy expenditure and MFT laps): 0.14–0.39 (p < 0.01– p < 0.001). |
Gwynn et al., 2010 [32] | Many Rivers Diabetes Prevention project. Eleven Department of Education and Training primary schools in three regional areas (north coast, NSW, Australia). | Validity was assessed against accelerometers for seven consecutive days. | n = 86 10–12 years; mean age 11.1 ± 0.7 years 59% F 23% overweight or obese n = 40 Aboriginal and Torres Strait Islander, n = 46 non-Indigenous children. | The Many Rivers Physical Activity Recall Questionnaire (MRPARQ; a modified version of the Adolescent Physical Activity Recall Questionnaire (APARQ)). All organised and non-organised physical activity in a “normal” week during summer and winter. | Self-administered by children seated in small groups with one or two members of the research team to assist, which always included an Aboriginal Health Worker for assistance. | Validity ICC 0.25 (p < 0.05) and Pearson’s correlation 0.37 (p < 0.05) for the overall average weekday daily MVPA accelerometer and MRPARQ. |
Lubans et al., 2008 [33] | One secondary school in Oxford (United Kingdom (UK)) and one independent school in Newcastle (NSW, Australia). | Reliability was assessed in the UK sample via administration of the questionnaire twice, one week apart. Validity was assessed in the Australian sample by comparing the questionnaire data to accelerometer data from four consecutive school days (worn prior to questionnaire administration). | Reliability n = 87 Mean age 13.1 ± 0.9 years 44.8% F “Predominantly white” Mixed socioeconomic backgrounds Validity n = 51 Mean age 12.6 ± 0.5 years 47.1% F “Predominantly white” Mixed socioeconomic backgrounds. | Oxford Physical Activity Questionnaire (OPAQ); Eight items excluding demographics on the last seven days. Items include travel to/from school, activities at school, activities after school and on weekends, and other activities. | Self-administered by children. The questionnaire took 15 min to complete. | Reliability The ICC (95% CI) for moderate activity was 0.76 (0.63–0.84), vigorous activity 0.80 (0.70–0.87), and moderate to vigorous activity 0.91 (0.87–0.95). Validity Spearman’s correlations with moderate activity was r = 0.01 (NS), vigorous activity r = 0.33 (p = 0.01), moderate to vigorous activity r = 0.32 (p = 0.02). |
Prochaska et al., 2001 [34] | Two high schools and two middle schools in San Diego, California, Pittsburgh (Pennsylvania, USA). | Three studies; two studies evaluated test–retest reliability and concurrent validity (against accelerometry) of six single-item and three composite measures of physical activity. A third study evaluated the best measure of those examined (and modified) in the previous two studies. | Study 1 n = 250 Mean age 14.6 ± 1.4 years 56% F 36% white, 25% Asian/Pacific Islander, 17% African American, 9% Hispanic, 13% other. Study 2 n = 57 Mean age 13.9 ± 1.7 years 37% white, 25% Asian/Pacific Islander, 4% African American, 12% Hispanic, 23% other. Study 3 n = 148 Mean age 12.1 ± 0.9 years 65% F 27% white, 24% Asian/Pacific Islander, 7% African American, 5% Hispanic, 23% multiracial, 14% other. | The recommended measure had two recall assessing frequency of past seven days and “usual” activity performed for a total of at least 60 min per day. | Self-administered by children, supervised by research staff. | Reliability ICC 0.77 (kappa 61%). Validity MVPA correlation with accelerometer data r = 0.40 (p < 0.001). |
Hardy et al., 2007a [35] | High schools near the study centre, Girls’ Healthy Development Study (Sydney, Australia). | Prospective cohort study (2.5 years), comprising five data collections, six months apart, between 2000 and 2002. Construct validity of the questionnaire was assessed using accelerometers worn at each time point for seven consecutive days. | n = 163 Mean ages for data collections 1 to 5 were 12.8, 13.4, 13.9, 14.4, and 14.9 years, respectively. 100% F ~25% non-English speaking background. | Sedentary Behaviour Questionnaire. Three main items (with sub-items) on sedentary behaviour on weekday and weekends and movie-going. | Self-administered by children. | Validity Bland–Altman plots showed <5% of data points were outside the limits of agreement (2 SD; 26.5 to 20.1 h/week). |
Hardy et al., 2007b [36] | Four primary and four high schools randomly selected from Sydney (NSW, Australia). | The questionnaire was completed twice, two weeks apart (reliability) during autumn 2002. | n = 250 (Grade 6 = 98; Grade 8 = 73 and Grade 10 = 79) Mean age 11.3 years (Year 6), 13.3 years (Year 8) and 15.3 (Year 10). 44% F (overall), 49% F (Year 6), 47% F (Year 8), 37% F (Year 10). Ethnicity not indicated. | The Adolescent Sedentary Activities Questionnaire (ASAQ). Two main items with the same question; one on school days, one on weekends (11–12 identical sub-items except for the addition of church on weekends). “Usual” week during school term. | Self-administered by children. | Reliability ICC (95% CI) 0.01 (−0.88–0.46) to 0.95 (0.89–0.88). Most ICC ≥ 0.70. Validity Face validity was determined via pilot testing with a group of approximately 50 students (mean age 12 years). |
Leech et al., 2014 [37] | Health Eating and Play study (HEAPS), state and Catholic primary schools in greater Melbourne (Victoria (VIC), Australia). | Cross-sectional study, including a 56-item FFQ, 7-day accelerometer data, and questions on sedentary behaviour. Questions were administered twice, 2–3 weeks apart. | n = 972 children (n = 362 5–6 years, n = 610 10–12 years). n = 133 parents (reliability study). 50% F 5–6 years, 56% F 10–12 years. 22% overweight/obese (5–6 years) and 29% overweight/obese (10–12 years) 19% maternal education low (5–6 years), 23% maternal education low (10–12 years) 92% of families of children aged 5–6 years usually spoke English at home, 87% of families of children aged 10–12 years usually spoke English at home. | Questions on sedentary behaviour asked about the number of hours (range: 0–6 or more hours), in 30-min blocks, their child watched (1) commercial and (2) non-commercial TV/DVDs on a typical school and weekend day. Usual daily TV viewing (minute/day) was calculated. | Self-administered by parents. | Reliability ICC (95% CI) 0.78 (0.69–0.84) usual daily TV viewing (minutes/day) |
Salmon et al., 2005 [38] | Nineteen primary schools in Melbourne (VIC, Australia) | Parents completed a questionnaire about their child’s television viewing (validity). Questions were tested for reliability among a sample of the children (1 week apart) and parents (2 weeks apart). | n = 878 children with complete TV viewing data 54% F 22% F overweight, 5% F obese, 22% M overweight, 9% M obese 82% F (responding parents) Maternal education level was used as an indicator of SES; SES was evenly distributed across families (low SES, 30%; medium SES, 37%; high SES, 33%). Reliability n = 147 children Mean age 11.8 ± 0.8 years 55% F n = 156 parents mean age 40.0 ± 5.2 years 88% F 94% of all families reported speaking English at home, but it is not clear what the proportion was for the reproducibility element. | Three items on time spent in sedentary behaviour (watching TV, playing electronic games, and using the computer) were presented for a typical week (Monday to Friday) and a typical weekend (Saturday and Sunday). | Self-administered by children and parents. | Reliability * The ICC of the proxy-reported time (minutes per day) spent on each of these screen based behaviours ranged from 0.6 to 0.8. Validity * The ICC of the proxy-reported time (minutes per day) spent on each of these screen-based behaviours ranged from 0.44 to 0.61. * Report states that “Because proxy-reported sedentary time was more reliably reported, these items were used in analyses rather than the children’s self-reports.” (p. 1942). |
Finch et al., 2007 [26] | One local government primary school (Hunter Region, NSW, Australia). | Questionnaire development and reliability testing. The questionnaire was administered twice, 1 week apart. | n = 245 (n = 88 Year 4, n = 84 Year 5, n = 73 Year 6) Mean age 10.7 ± 0.91 years 52% F Ethnicity not indicated. | School Food Eating Habits and Lifestyle Survey (SEHLS) with 35 items, including 27 on assessing “usual” food habits, 5 on “usual” physical activity and sedentary pursuits, and 3 on demographic variables. | Self-administered in class by children with teacher supervision. | Reliability Physical activity questions: kappa 0.57–0.71 Sedentary behaviour questions: kappa 0.51–0.59. |
Moore et al., 2008 [39] | A local primary and secondary school, Northeast England (UK). | Children wore an accelerometer for 2 days (day 1, to desensitise them to wearing the monitor, and day 2, the day of recall) to assess validity of recalled activities. | n = 121 7–15 years, mean age 10.7 ± 2·2 years. 60% F 94% spoke English as their first language. | The Synchronised Nutrition and Activity ProgramTM (SNAPTM) Recall of previous day activity. The overall number of items was not indicated. 29 common physical activities within the domains of sedentary activities, structured activities, household chores, play activities, and a free-text option were included. Transport activities were also assessed. | Self-administered by children (some availability of assistance was indicated, but this was not detailed). Web-based. The whole questionnaire (including nutrition questions) took 15–40 min dependent primarily on reading ability and Internet connection speed. | Validity Passing–Bablok regression equation established an overall bias of less than 4 min between the two methods, indicating good validity. |
Strugnell et al., 2011 [40] | Three separate school samples from two Chinese weekend cultural schools from eastern metropolitan Melbourne (VIC, Australia). | Reliability of individual items and scales within the questionnaire determined by administration twice, 1 week apart. | n = 77 11–14 years, mean age 12 ± 0.8 years. 51% F 82% were of Chinese ethnicity (born in China, having both parents born in China, or having both maternal grandparents being born in China). | The Child and Adolescent Physical Activity and Nutrition Survey—Physical Activity (CAPANS-PA). The questionnaire the same as the Western Australian (WA) Child and Adolescent Physical Activity and Nutrition Survey (CAPANS) with minor modifications. Investigates 7 days of school and non-school based physical activity, sedentary behaviours, and associated correlates. Items within the CAPANS-PA were derived from several sources, including The Children’s Leisure Activity Study (CLASS) and APARQ. | Self-administered by children. Takes 15 min to complete. | Reliability Kappa (95% CI) for individual activities −0.04 (−0.07–0) to 0.82 (0.57–1.00). Kappa was >0.50 for most individual activities |
Telford et al., 2004 [41] | Five state primary schools in Melbourne (VIC Australia). | Reliability of a parental proxy questionnaire and a children’s self-report questionnaire (2 weeks apart for parents and 1 week apart for children). Criterion validity assessed using accelerometry. | n = 169 children (n = 58 aged 5–6 years, n = 111 aged 10–12 years). n = 169 parents (n = 58 parents of children in the 5–6 year age group, n = 111 parents of children in the 10–12 year age group (2 excluded)). Mean age 5.3 ± 0.5 year (5–6 years), 37.4 ± 6.2 years (parents of children in the 5–6 year age group), 10.6 ± 0.8 years (10–12 year age group), 40.3 ± 5.9 years (parents of children in the 10–12 year age group). 37% F (5–6 years) 91% F (parents of children aged 5–6 years) 63% F (10–12 years) 83% F (parents of children aged 5–6 years) 77% of parents Australian-born (5–6 year age group). 75% of parents Australian-born (10–12 year age group). | The Children’s Leisure Activities Study Survey (CLASS) Consists of a list of 30 physical activities. Participants indicate participation in activities during a typical week (Monday to Friday) and during a typical weekend (Saturday and Sunday). For each activity, frequency and the total time spent is reported. | Self-administered by parents (proxy report for children aged both 5–6-years and 10–12-years), and children aged 10–12 years who completed the questionnaire in class guided by an investigator. The questionnaire took 10 min for parents to complete and 15 min for children to complete. | Reliability ICC for 10–12 years only: For self-report it ranged from 0.36 (p < 0.001) for total activity (frequency) to 0.74 (p < 0.001) for total activity (duration). For proxy report it ranged from 0.24 (NS) for total activity (duration) to 0.75 (p < 0.001) for vigorous activity (frequency). Validity Spearmans correlations between children (10–12 years) and proxy report: Vigorous activity: frequency rs = 0.13 (NS), duration rs = 0.19 (p < 0.05). Moderate activity: frequency rs = 0.07 (NS), duration rs = 0.14 (NS). Total activity frequency: rs = 0.25 (p < 0.01). |
Reference | Setting | Design | Sample | Questionnaire | Administration | Statistics |
---|---|---|---|---|---|---|
Gwynn et al., 2011 [29] | Many Rivers Diabetes Prevention Project. Eleven Department of Education and Training primary “priority funded” (disadvantaged) schools in three regional areas (north coast, NSW, Australia). | A short FFQ was completed twice, two weeks apart (reliability) and compared with the mean of three 24 h recalls (validity). | Reliability n = 241 age not specified. 59% F n = 92 Aboriginal and Torres Strait Islander, n = 149 non-Indigenous. Validity n = 205 10–12 years, mean age 10.8 ± 0.7 years. 58% F n = 78 Aboriginal and Torres Strait Islander children, n = 127 non-Indigenous children. | The Short Food Frequency Questionnaire (SFFQ) consisted of three demographic questions, 36 items (number of response categories 4–7) including 28 short questions on usual food intake. | Self-administered by the child. Culturally appropriate support was provided to Aboriginal and Torres Strait Islander children throughout the study. | Reliability Kappa 0.28–0.89 in Aboriginal and Torres-Strait Islander children. Kappa 0.33–0.77 in non-Indigenous children. Validity 18 of 23 questions had increasing trends (p < 0.05) for mean daily weight and/or frequency as survey response categories increased. |
Gwynn et al., 2010 [32] | Many Rivers Diabetes Prevention project. Eleven Department of Education and Training primary “priority funded” (disadvantaged) schools in three regional areas (north coast, NSW, Australia). | Validity was assessed against accelerometers for seven consecutive days. | n = 86 10–12 years; mean age 11.1 ± 0.7 years. 59% F 23% overweight or obese n = 40 Aboriginal and Torres Strait Islander, n = 46 non-Indigenous children | The Many Rivers Physical Activity Recall Questionnaire (MRPARQ), a modified version of the Adolescent Physical Activity Recall Questionnaire (APARQ)). All organised and non-organised physical in a “normal” week during summer and winter. | Self-administered by children seated in small groups with one or two members of the research team to assist, which always included an Aboriginal Health Worker for assistance. | Validity ICC 0.16 (p < 0.05) and Pearson’s correlation 0.31 (NS) for average weekday daily MVPA accelerometer and MRPARQ in Aboriginal and Torres Strait Islander children. ICC 0.31 (p < 0.05) and Pearson’s correlation 0.38 (p < 0.05) for average weekday daily MVPA accelerometer and MRPARQ in non-Indigenous children. |
Trost et al., 2007 [43] | Public secondary schools from Brisbane South (QID, Australia). | Validity was assessed against a pedometer worn on the day previous to answering the questionnaire. | n = 122 13.8 ± 1.2 years 53% F n = 63 Aboriginal and Torres Strait Islander, n = 59 non-indigenous | 24-h physical activity recall (the PDPAR-24). Participants entered the main activity (of 69) in which he/she participated during each 30-min time period between 9 a.m. and 9 a.m. in the previous 24 h (excluding midnight–5 am). | Children self-administered the instrument in groups of approximately five individuals under the supervision of the research team who followed a standardised administrator script. | Validity Spearman’s correlations for mean METs, vigorous physical activity, MVPA, and screen-based activity were 0.34 (p < 0.05), 0.34 (p < 0.05), 0.28 (p < 0.05), and −0.13 (NS), respectively, in Aboriginal and Torres Strait Islander children and 0.32 (p < 0.05), 0.26 (p < 0.05), 0.28 (p < 0.05), and −0.20 (NS), respectively in non-Indigenous children. |
Field 1 | Field 2 | Field 3 | Field 4 | Field 5 † |
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(diet OR diet * OR food) OR (“physical activity” OR exercise OR sedentary OR inactivity) | Child * OR teen * OR adolescen * | Survey OR FFQ OR food frequency questionnaire OR questionnaire OR screening OR checklist OR diet quality OR diet index OR physical activity index | Valid * OR reprod * OR reliab * | Austral * ((Aborigin * OR Torres Strait Islander OR Indigenous) AND Austral *) |
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Gifford, J.A.; Gwynn, J.D.; Hardy, L.L.; Turner, N.; Henderson, L.C.; Innes-Hughes, C.; Flood, V.M. Review of Short-Form Questions for the Evaluation of a Diet, Physical Activity, and Sedentary Behaviour Intervention in a Community Program Targeting Vulnerable Australian Children. Children 2018, 5, 95. https://doi.org/10.3390/children5070095
Gifford JA, Gwynn JD, Hardy LL, Turner N, Henderson LC, Innes-Hughes C, Flood VM. Review of Short-Form Questions for the Evaluation of a Diet, Physical Activity, and Sedentary Behaviour Intervention in a Community Program Targeting Vulnerable Australian Children. Children. 2018; 5(7):95. https://doi.org/10.3390/children5070095
Chicago/Turabian StyleGifford, Janelle A., Josephine D. Gwynn, Louise L. Hardy, Nicole Turner, Lily C. Henderson, Christine Innes-Hughes, and Victoria M. Flood. 2018. "Review of Short-Form Questions for the Evaluation of a Diet, Physical Activity, and Sedentary Behaviour Intervention in a Community Program Targeting Vulnerable Australian Children" Children 5, no. 7: 95. https://doi.org/10.3390/children5070095