Sedentary Activities and Food Intake among Children and Adolescents in the Zhejiang Province of China: A Cross-Sectional Study
Abstract
:1. Introduction
2. Methods
2.1. Participants
2.2. Data Collection
2.3. Ethical Approval
2.4. Statistical Analysis
3. Results
3.1. Study Population
3.2. Time of Sedentary Behavior and Food Intake
3.3. Time Taken to Go to School by Bus or Subway and Food Intake
4. Discussion
Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Matias, T.S.; Silva, K.S.; da Silva, J.A.; de Mello, G.T.; Salmon, J. Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school–based health survey (PeNSE 2015). BMC Public Health 2018, 18, 1283. [Google Scholar] [CrossRef] [PubMed]
- Leech, R.M.; McNaughton, S.A.; Timperio, A. The clustering of diet, physical activity and sedentary behavior in children and adolescents: A review. Int. J. Behav. Nutr. Phys. Act. 2014, 11, 4. [Google Scholar] [CrossRef] [PubMed]
- Dumuid, D.; Olds, T.; Lewis, L.K.; Martin-Fernández, J.A.; Katzmarzyk, P.T.; Barreira, T.; Broyles, S.T.; Chaput, J.-P.; Fogelholm, M.; Hu, G.; et al. Health-Related Quality of Life and Lifestyle Behavior Clusters in School-Aged Children from 12 Countries. J. Pediatr. 2017, 183, 178–183.e2. [Google Scholar] [CrossRef]
- Jacka, F.N.; Rothon, C.; Taylor, S.; Berk, M.; Stansfeld, S.A. Diet quality and mental health problems in adolescents from East London: A prospective study. Soc. Psychiatry 2013, 48, 1297–1306. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.C.; McPherson, K.; Marsh, T.; Gortmaker, S.L.; Brown, M. Health and economic burden of the projected obesity trends in the USA and the UK. Lancet 2011, 378, 815–825. [Google Scholar] [CrossRef]
- Murray, C.J.; Aravkin, A.Y.; Zheng, P.; Abbafati, C.; Abbas, K.M.; Abbasi-Kangevari, M.; Abd-Allah, F.; Abdelalim, A.; Abdollahi, M.; Abdollahpour, I.; et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020, 396, 1223–1249. [Google Scholar] [CrossRef]
- Alberga, A.S.; Sigal, R.J.; Goldfield, G.; Homme, D.P.; Kenny, G.P. Overweight and obese teenagers: Why is adolescence a critical period? Pediatr. Obes. 2012, 7, 261–273. [Google Scholar] [CrossRef]
- World Health Organization (WHO) Obesity and Overweight. 2020. Available online: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 18 February 2021).
- World Health Organization. Report of the Commission on Ending Childhood Obesity; World Health Organization: Geneva, Switzerland, 2016. [Google Scholar]
- Jakes, R.W.; Day, N.E.; Khaw, K.-T.; Luben, R.; Oakes, S.; Welch, A.; Bingham, S.; Wareham, N.J. Television viewing and low participation in vigorous recreation are independently associated with obesity and markers of cardiovascular disease risk: EPIC-Norfolk population-based study. Eur. J. Clin. Nutr. 2003, 57, 1089–1096. [Google Scholar] [CrossRef]
- Hu, F.B.; Li, T.Y.; Colditz, G.A.; Willett, W.C.; Manson, J.E. Television Watching and Other Sedentary Behaviors in Relation to Risk of Obesity and Type 2 Diabetes Mellitus in Women. JAMA 2003, 289, 1785–1791. [Google Scholar] [CrossRef]
- Jonsson, K.R.; Corell, M.; Löfstedt, P.; Adjei, N.K. The clustering of multiple health and lifestyle behaviors among Swedish adolescents: A person-oriented analysis. Front. Public Health 2023, 11, 1178353. [Google Scholar] [CrossRef]
- Parrish, A.-M.; Okely, A.D.; Salmon, J.; Trost, S.; Hammersley, M.; Murdoch, A. Making ‘being less sedentary feel normal’–investigating ways to reduce adolescent sedentary behaviour at school: A qualitative study. Int. J. Behav. Nutr. Phys. Act. 2023, 20, 85. [Google Scholar] [CrossRef]
- Yang-Huang, J.; Van Grieken, A.; Wang, L.; Jansen, W.; Raat, H. Clustering of Sedentary Behaviours, Physical Activity, and Energy-Dense Food Intake in Six-Year-Old Children: Associations with Family Socioeconomic Status. Nutrients 2020, 12, 1722. [Google Scholar] [CrossRef] [PubMed]
- Milanović, S.M.; Buoncristiano, M.; Križan, H.; Rathmes, G.; Williams, J.; Hyska, J.; Duleva, V.; Zamrazilová, H.; Hejgaard, T.; Jørgensen, M.B.; et al. Socioeconomic disparities in physical activity, sedentary behavior and sleep patterns among 6- to 9-year-old children from 24 countries in the WHO European region. Obes. Rev. 2021, 22 (Suppl. S6), e13209. [Google Scholar] [CrossRef] [PubMed]
- Leow, S.; Jackson, B.; Alderson, J.A.; Guelfi, K.J.; Dimmock, J.A. A Role for Exercise in Attenuating Unhealthy Food Consumption in Response to Stress. Nutrients 2018, 10, 176. [Google Scholar] [CrossRef] [PubMed]
- Cartanyà-Hueso, À.; González-Marrón, A.; Lidón-Moyano, C.; Garcia-Palomo, E.; Martín-Sánchez, J.C.; Martínez-Sánchez, J.M. Association between Leisure Screen Time and Junk Food Intake in a Nationwide Representative Sample of Spanish Children (1–14 Years): A Cross-Sectional Study. Healthcare 2021, 9, 228. [Google Scholar] [CrossRef] [PubMed]
- Dalene, K.E.; Anderssen, S.A.; Andersen, L.B.; Steene-Johannessen, J.; Ekelund, U.; Hansen, B.H.; Kolle, E. Secular and longitudinal physical activity changes in population-based samples of children and adolescents. Scand. J. Med. Sci. Sports 2018, 28, 161–171. [Google Scholar] [CrossRef]
- Byun, D.; Kim, R.; Oh, H. Leisure-time and study-time Internet use and dietary risk factors in Korean adolescents. Am. J. Clin. Nutr. 2021, 114, 1791–1801. [Google Scholar] [CrossRef]
- Ryu, S.; Jang, H.; Oh, H. Smartphone Usage Patterns and Dietary Risk Factors in Adolescents. J. Nutr. 2022, 152, 2109–2116. [Google Scholar] [CrossRef]
- Avery, A.; Anderson, C.; McCullough, F. Associations between children’s diet quality and watching television during meal or snack consumption: A systematic review. Matern. Child Nutr. 2017, 13, e12428. [Google Scholar] [CrossRef]
- Cambridge Dictionary Junk Food Definition. 2021. Available online: https://dictionary.cambridge.org/es/diccionario/ingles/junk-food[Reflist]) (accessed on 18 February 2021).
- Vandelanotte, C.; Sugiyama, T.; Gardiner, P.; Owen, N. Associations of Leisure-Time Internet and Computer Use with Overweight and Obesity, Physical Activity and Sedentary Behaviors: Cross-Sectional Study. J. Med. Internet Res. 2009, 11, e28. [Google Scholar] [CrossRef]
- Australian Bureau of Statistics. Household Use of Information Technology 2006–2007. Canberra. 2007. Available online: http://www.abs.gov.au/Ausstats/[email protected]/lookup (accessed on 29 February 2008).
- Al-Hazzaa, H.M.; Al-Sobayel, H.I.; Abahussain, N.A.; Qahwaji, D.M.; Alahmadi, M.A.; Musaiger, A.O. Association of dietary habits with levels of physical activity and screen time among adolescents living in Saudi Arabia. J. Hum. Nutr. Diet. 2014, 27 (Suppl. S2), 204–213. [Google Scholar] [CrossRef] [PubMed]
- Rohilla, K.K.; Seema, S.; Kalyani, V.C.; Babbar, P. Prevalence and contributing factors for adolescent obesity in present era: Cross-sectional Study. J. Fam. Med. Prim. Care 2021, 10, 1890–1894. [Google Scholar] [CrossRef] [PubMed]
- Duncan, D.T.; Méline, J.; Kestens, Y.; Day, K.; Elbel, B.; Trasande, L.; Chaix, B. Walk Score, Transportation Mode Choice, and Walking Among French Adults: A GPS, Accelerometer, and Mobility Survey Study. Int. J. Environ. Res. Public Health 2016, 13, 611. [Google Scholar] [CrossRef]
- Mujahid, M.S.; Roux, A.V.D.; Morenoff, J.D.; Raghunathan, T.E.; Cooper, R.S.; Ni, H.; Shea, S. Neighborhood Characteristics and Hypertension. Epidemiology 2008, 19, 590–598. [Google Scholar] [CrossRef] [PubMed]
- Sadler, R.C.; Clark, A.F.; Wilk, P.; O’connor, C.; Gilliland, J.A. Using GPS and activity tracking to reveal the influence of adolescents’ food environment exposure on junk food purchasing. Can. J. Public Health 2016, 107 (Suppl. S1), 5346. [Google Scholar] [CrossRef]
- Davies, A.; Chan, V.; Bauman, A.; Signal, L.; Hosking, C.; Gemming, L.; Allman-Farinelli, M. Using wearable cameras to monitor eating and drinking behaviours during transport journeys. Eur. J. Nutr. 2021, 60, 1875–1885. [Google Scholar] [CrossRef]
- D’Souza, N.J.; Kuswara, K.; Zheng, M.; Leech, R.; Downing, K.L.; Lioret, S.; Campbell, K.J.; Hesketh, K.D. A systematic review of lifestyle patterns and their association with adiposity in children aged 5–12 years. Obes. Rev. 2020, 21, e13029. [Google Scholar] [CrossRef]
Sedentary Behavior (h/Day) | Food Category (Spearman’s Rho) | ||||||||
---|---|---|---|---|---|---|---|---|---|
Staple Food | Beans | Vegetables | Fruits | Dairy | Meat | Eggs | Snacks | Water and Beverages | |
Watching TV (mid-week) | 0.018 | 0.143 | −0.296 * | 0.255 | 0.107 | 0.24 | 0.121 | 0.232 | 0.251 |
Watching TV (on weekends) | 0.183 | 0.193 | 0.008 | 0.008 | −0.097 | −0.006 | −0.132 | 0.25 | 0.052 |
Watching movies or TV shows online or on a smartphone (mid-week) | 0.303 | −0.05 | 0.232 | −0.368 | 0.04 | 0.474 | 0.25 | 0.442 | −0.013 |
Watching movies or TV shows online or on a smartphone (on weekends) | 0.486 * | 0.26 | 0.226 | −0.121 | −0.157 | 0.196 | −0.192 | 0.39 | −0.168 |
Online browsing (mid-week) | 0.020 | 0.2 | 0.038 | 0.083 | 0.528 * | 0.356 | 0.164 | 0.503 * | −0.111 |
Online browsing (on weekends) | 0.261 | 0.296 | 0.245 | 0.071 | 0.152 | 0.219 | 0.036 | 0.411 | −0.113 |
Online chat, including QQ and WeChat (mid-week) | −0.014 | 0.184 | 0.409 * | −0.251 | −0.117 | −0.15 | 0.163 | 0.259 | 0.03 |
Online chat (on weekends), including QQ and WeChat | 0.310 * | 0.415 * | 0.53 * | −0.101 | −0.052 | 0.152 | −0.141 | 0.427 * | 0.028 |
Playing computer or smartphone games (mid-week) | 0.046 | 0.229 | 0.545 * | 0.064 | −0.277 | −0.144 | 0.058 | 0.220 | −0.243 |
Playing computer or smartphone games (on weekends) | 0.057 | 0.421 * | 0.345 | 0.168 | −0.113 | 0.058 | −0.037 | 0.450 * | −0.042 |
Completing homework (mid-week) | 0.164 | 0.177 | −0.103 | 0.227 * | 0.066 | 0.104 | 0.149 | 0.359 * | 0.320 * |
Completing homework (on weekends) | 0.790 | 0.286 | 0.314 | 0.031 | 0.143 | 0.204 | 0.791 | 0.245 | 0.243 |
Reading (books, newspapers, and magazines), writing, or drawing (mid-week) | −0.069 | 0.198 | 0.094 | 0.049 | −0.062 | 0.120 | 0.358 * | 0.231 | 0.208 |
Reading (books, newspapers, and magazines), writing, or drawing (on weekends) | −0.050 | 0.297 * | 0.182 | 0.000 | −0.014 | 0.049 | 0.257 * | 0.253 * | 0.278 |
Unstandardized Coefficients | Standardized Coefficients | 95% CI for B | |||||
---|---|---|---|---|---|---|---|
Factors | B | Std.E | β | t | p | Lower Bound | Upper Bound |
Staple food | −0.011 | 0.016 | −0.090 | −0.714 | 0.478 | −0.043 | 0.021 |
Beans | 0.067 | 0.024 | 0.382 | 2.804 | 0.007 | 0.019 | 0.116 |
Vegetables | −0.025 | 0.010 | −0.353 | −2.516 | 0.015 | −0.045 | −0.005 |
Snacks | −0.057 | 0.022 | −0.357 | −2.641 | 0.011 | 0.101 | −0.014 |
Age | −3.710 | 1.178 | −0.364 | −3.149 | 0.003 | −6.076 | −1.345 |
Sedentary Behavior (h/Day) | Food Category (Spearman’s Rho) | ||||||||
---|---|---|---|---|---|---|---|---|---|
Staple Food | Beans | Vegetables | Fruits | Dairy | Meat | Eggs | Snacks | Water and Beverages | |
Walk | 0.076 | 0.128 | 0.2 | 0.204 | 0.178 | 0.3 | 0.276 | 0.3 | 0.313 |
Bus and subway | 0.453 * | 0.444 * | 0.444 * | −0.087 | −0.087 | 0.479 * | −0.126 | 0.479 * | −0.096 |
Cars, taxis, and motorcycles (electric vehicles) | 0.294 * | 0.201 | 0.354 * | 0.109 | 0.207 | 0.125 | 0.15 | 0.278 | 0.03 |
Unstandardized Coefficients | Standardized Coefficients | 95%CI for B | |||||
---|---|---|---|---|---|---|---|
Factors | B | Std.E | β | t | p | Lower Bound | Upper Bound |
Staple Food | 0.005 | 0.022 | 0.032 | 0.229 | 0.821 | −0.040 | 0.049 |
Beans | −0.090 | 0.050 | −0.348 | −1.790 | 0.087 | −0.194 | 0.014 |
Vegetables | −0.029 | 0.015 | −0.311 | −1.952 | 0.063 | −0.060 | 0.002 |
Meat | 0.019 | 0.031 | 0.098 | 0.623 | 0.540 | −0.045 | 0.084 |
Snacks | −0.186 | 0.061 | −0.456 | −3.068 | 0.005 | −0.312 | −0.061 |
Age | 0.329 | 1.420 | 0.030 | 0.232 | 0.819 | −2.609 | 3.266 |
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Zou, Y.; Huang, L.; He, M.; Zhao, D.; Su, D.; Zhang, R. Sedentary Activities and Food Intake among Children and Adolescents in the Zhejiang Province of China: A Cross-Sectional Study. Nutrients 2023, 15, 3745. https://doi.org/10.3390/nu15173745
Zou Y, Huang L, He M, Zhao D, Su D, Zhang R. Sedentary Activities and Food Intake among Children and Adolescents in the Zhejiang Province of China: A Cross-Sectional Study. Nutrients. 2023; 15(17):3745. https://doi.org/10.3390/nu15173745
Chicago/Turabian StyleZou, Yan, Lichun Huang, Mengjie He, Dong Zhao, Danting Su, and Ronghua Zhang. 2023. "Sedentary Activities and Food Intake among Children and Adolescents in the Zhejiang Province of China: A Cross-Sectional Study" Nutrients 15, no. 17: 3745. https://doi.org/10.3390/nu15173745
APA StyleZou, Y., Huang, L., He, M., Zhao, D., Su, D., & Zhang, R. (2023). Sedentary Activities and Food Intake among Children and Adolescents in the Zhejiang Province of China: A Cross-Sectional Study. Nutrients, 15(17), 3745. https://doi.org/10.3390/nu15173745