Gender, Age, Family and Territorial Features of Dietary and Physical Activity Patterns in Russian Youths
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Sampling
2.2. Data Collection Tools
2.3. Assessment of Diet and Physical Activity
2.4. Statistical Data Processing
3. Results
3.1. Two-Way Associations of the Proportion of Children in Adverse Patterns
3.2. Effect of Gender, Age and Place of Residence on the Likelihood of Adverse Patterns
3.3. Effect of Social Conditions on the Likelihood of Adverse Patterns
4. Discussion
4.1. Gender-Specific and Age-Specific Dietary Features
4.2. Gender-Specific and Age-Specific Features of PA
4.3. Territorial Dietary Features vs. PA
4.4. Socioeconomic Dietary Features vs. Physical Activity
4.5. Study Advantages and Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Cecchini, M.; Sassi, F.; Lauer, J.A.; Lee, Y.Y.; Guajardo-Barron, V.; Chisholm, D. Tackling of unhealthy diets, physical inactivity, and obesity: Health effects and cost-effectiveness. Lancet 2010, 376, 1775–1784. [Google Scholar] [CrossRef]
- World Health Organization (WHO). Global Health Risks: Mortality and Burden of Disease Attributable to Selected Major Risks; World Health Organization: Geneva, Switzerland, 2009. [Google Scholar]
- Guthold, R.; Cowan, M.J.; Autenrieth, C.S.; Kann, L.; Riley, L.M. Physical activity and sedentary behavior among school students: A 34-country comparison. J. Pediatr. 2010, 157, 43–49. [Google Scholar] [CrossRef] [PubMed]
- Monzani, A.; Ricotti, R.; Caputo, M.; Solito, A.; Archero, F.; Bellone, S.; Prodam, F. A systematic review of the association of skipping breakfast with weight and cardiometabolic risk factors in children and adolescents. What should we better investigate in the future? Nutrients 2019, 11, 387. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Currie, J.L.; Rossin-Slater, M. Early-life origins of life-cycle well-being: Research and policy implications. J. Policy Anal. Manag. 2015, 34, 208–242. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Aparicio-Cercós, C.; Alacreu, M.; Salar, L.; Moreno Royo, L. Waist-to-height ratio and skipping breakfast are predictive factors for high blood pressure in adolescents. Sci. Rep. 2020, 10, 16704. [Google Scholar] [CrossRef]
- Haines, J.; Haycraft, E.; Lytle, L.; Nicklaus, S.; Kok, F.J.; Merdji, M.; Fisberg, M.; Moreno, L.A.; Goulet, O.; Hughes, S.O. Nurturing children’s healthy eating: Position statement. Appetite 2019, 137, 124–133. [Google Scholar] [CrossRef]
- Wennberg, M.; Gustafsson, P.E.; Wennberg, P.; Hammarström, A. Poor breakfast habits in adolescence predict the metabolic syndrome in adulthood. Public Health Nutr. 2015, 18, 122–129. [Google Scholar] [CrossRef] [Green Version]
- Smith, K.J.; Gall, S.L.; McNaughton, S.A.; Blizzard, L.; Dwyer, T.; Venn, A.J. Skipping breakfast: Longitudinal associations with cardiometabolic risk factors in the Childhood Determinants of Adult Health Study. Am. J. Clin. Nutr. 2010, 92, 1316–1325. [Google Scholar] [CrossRef]
- Mâsse, L.C.; de Niet-Fitzgerald, J.E.; Watts, A.W.; Naylor, P.J.; Saewyc, E.M. Associations between the school food environment, student consumption and body mass index of Canadian adolescents. Int. J. Behav. Nutr. Phys. Act. 2014, 11, 29. [Google Scholar] [CrossRef] [Green Version]
- Briefel, R.R.; Wilson, A.; Gleason, P.M. Consumption of low-nutrient, energy-dense foods and beverages at school, home, and other locations among school lunch participants and nonparticipants. J. Am. Diet Assoc. 2009, 109, S79–S90. [Google Scholar] [CrossRef]
- Kristiansen, A.L.; Lande, B.; Sexton, J.A.; Andersen, L.F. Dietary patterns among Norwegian 2-year-olds in 1999 and in 2007 and associations with child and parent characteristics. British. J. Nutr. 2013, 110, 135–144. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cutler, G.J.; Flood, A.; Hannan, P.; Neumark-Sztainer, D. Multiple sociodemographic and socioenvironmental characteristics are correlated with major patterns of dietary intake in adolescents. J. Am. Diet Assoc. 2011, 111, 230–240. [Google Scholar] [CrossRef] [PubMed]
- Fulkerson, J.A.; Larson, N.; Horning, M.; Neumark-Sztainer, D. A review of associations between family or shared meal frequency and dietary and weight status outcomes across the lifespan. J. Nutr. Educ. Behav. 2014, 46, 2–19. [Google Scholar] [CrossRef] [PubMed]
- Iguacel, I.; Fernández-Alvira, J.M.; Ahrens, W.; Bammann, K.; Gwozdz, W.; Lissner, L.; Michels, N.; Reisch, L.; Russo, P.; Szommer, A.; et al. IDEFICS consortium. Prospective associations between social vulnerabilities and children’s weight status. Results from the IDEFICS study. Int. J. Obes. 2018, 42, 1691–1703. [Google Scholar] [CrossRef] [PubMed]
- Casali, M.E.; Borsari, L.; Marchesi, I.; Borella, P.; Bargellini, A. Lifestyle and food habits changes after migration: A focus on immigrant women in Modena (Italy). Ann. Ig. 2015, 27, 748–759. [Google Scholar] [CrossRef] [PubMed]
- Roberts, E.; Speight, S.; Childcare use and attitudes: Literature review and feasibility study. Digit. Educ. Resour. Arch. 2017. Available online: https://dera.ioe.ac.uk/id/eprint/29114 (accessed on 6 May 2022).
- Laughlin, L. A Child’s Day: Living Arrangements, Nativity, and Family Transitions: 2011 (Selected Indicators of Child Well-Being). Current Population Reports; US Census Bureau: Suitland-Silver Hill, MD, USA, 2014; pp. 70–139. [Google Scholar]
- Lazarou, C.; Kalavana, T. Urbanization influences dietary habits of Cypriot children: The CYKIDS study. Int. J. Public Health 2009, 54, 69–77. [Google Scholar] [CrossRef]
- Maksimov, S.; Karamnova, N.; Shalnova, S.; Drapkina, O. Sociodemographic and regional determinants of dietary patterns in Russia. Int. J. Environ. Res. Pub. Health 2020, 17, 328. [Google Scholar] [CrossRef] [Green Version]
- Costa, C.D.S.; Flores, T.R.; Wendt, A.; Neves, R.G.; Assunção, M.C.F.; Santos, I.S. Sedentary behavior and consumption of ultra-processed foods by Brazilian adolescents: Brazilian National School Health Survey (PeNSE), 2015. Cad. Saude Publica 2018, 34, e00021017. [Google Scholar] [CrossRef] [Green Version]
- Bloch, K.V.; Cardoso, M.A.; Sichieri, R. Study of cardiovascular risk factors in adolescents (ERICA): Results and potentiality. Rev. Saude Publica 2016, 50, 3–5. [Google Scholar] [CrossRef] [Green Version]
- Sousa, S.F.; Wolf, V.L.W.; Martini, M.C.S.; Assumpção, D.; Barros Filho, A.A. Frequency of meals consumed by Brazilian adolescents and associated habits: Systematic review. Rev. Paul. Pediatr. 2020, 38, e2018363. [Google Scholar] [CrossRef]
- Rodrigues, P.R.M.; Luiz, R.R.; Monteiro, L.S.; Ferreira, M.G.; Gonçalves-Silva, R.M.; Pereira, R.A. Adolescents’ unhealthy eating habits are associated with meal skipping. Nutrition 2017, 42, 114–120.e1. [Google Scholar] [CrossRef]
- De Moraes, A.C.; Adami, F.; Falcão, M.C.; Understanding the correlates of adolescents’ dietary intake patterns. A multivariate analysis. Appetite 2012, 58, 1057–1062. [Google Scholar] [CrossRef] [PubMed]
- Caram, A.L.; Lamazi, E.A. Eating habits, nutritional status and body image perceptions of adolescents. Adolesc. Saude 2012, 9, 21–29. [Google Scholar]
- Silva, F.A.; Candiá, S.M.; Pequeno, M.S.; Sartorelli, D.S.; Mendes, L.L.; Oliveira, R.; Netto, M.P.; Cândido, A.P.C. Daily meal frequency and associated variables in children and adolescents. J. Pediatr. 2017, 93, 79–86. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- So, H.K.; Nelson, E.A.S.; Li, A.M.; Guldan, G.S.; Yin, J.; Ng, P.C.; Sung, R.Y.T. Breakfast frequency inversely associated with BMI and body fatness in Hong Kong Chinese children aged 9–18 years. Br. J. Nutr. 2011, 106, 742–751. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tee, E.S.; Nurliyana, A.R.; Karim, N.A.; Jan Mohamed, H.J.B.; Tan, S.Y.; Appukutty, M.; Hopkins, S.; Thielecke, F.; Ong, M.K.; Ning, C.; et al. Breakfast consumption among Malaysian primary and secondary school children and relationship with body weight status-Findings from the MyBreakfast Study. Asia Pac. J. Clin. Nutr. 2018, 27, 421–432. [Google Scholar] [CrossRef]
- Archero, F.; Ricotti, R.; Solito, A.; Carrera, D.; Civello, F.; Di Bella, R.; Bellone, S.; Prodam, F. Adherence to the mediterranean diet among school children and adolescents living in northern Italy and unhealthy food behaviors associated to overweight. Nutrients 2018, 10, 1322. [Google Scholar] [CrossRef] [Green Version]
- Vereecken, C.; Dupuy, M.; Rasmussen, M.; Kelly, C.; Nansel, T.R.; Al Sabbah, H.; Baldassari, D.; Jordan, M.D.; Maes, L.; Niclasen, B.V.L.; et al. Breakfast consumption and its socio-demographic and lifestyle correlates in school students in 41 countries participating in the HBSC study. Int. J. Public Health 2009, 54, 180–190. [Google Scholar] [CrossRef] [Green Version]
- O’Neil, C.E.; Nicklas, T.A.; Fulgoni, V.L. Nutrient intake, diet quality, and weight measures in breakfast patterns consumed by children compared with breakfast skippers: NHANES 2001–2008. AIMS Public Health 2015, 2, 441–468. [Google Scholar] [CrossRef]
- Kesztyüs, D.; Traub, M.; Lauer, R.; Kesztyüs, T.; Steinacker, J.M. Skipping breakfast is detrimental for primary school children: Cross-sectional analysis of determinants for targeted prevention. BMC Public Health 2017, 17, 258. [Google Scholar] [CrossRef] [Green Version]
- Coulthard, J.D.; Palla, L.; Pot, G.K. Breakfast consumption and nutrient intakes in 4–18-year-olds: UK National Diet and Nutrition Survey Rolling Programme (2008–2012). Br. J. Nutr. 2017, 118, 280–290. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Myrtveit, S.M.; Sivertsen, B.; Haugland, S. Health complaints in late adolescence; frequency, factor structure and the association with socio-economic status. Scand. J. Public Health 2018, 46, 141–149. [Google Scholar] [CrossRef] [PubMed]
- Husárová, D.; Veselská, Z.D.; Sigmundová, D.; Gecková, A.M. Age and gender differences in prevalence of screen based behaviour, physical activity and health complaints among Slovak school-aged children. Cent. Eur. J. Public Health 2015, 23, S30. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ceschini, F.L.; Andrade, D.R.; Oliveira, L.C.; Araújo Júnior, J.F.; Matsudo, V.K.R. Prevalence of physical inactivity and associated factors among high school students from state’s public schools. J. Pediatr. 2009, 85, 301–306. [Google Scholar] [CrossRef]
- Vasques, D.G.; Lopes, A.S. Fatores associados à atividade física e aos comportamentos sedentários em adolescentes. Rev. Bras. Cineantropom Desempenho Hum. 2009, 11, 59–66. [Google Scholar] [CrossRef] [Green Version]
- Micha, R.; Khatibzadeh, S.; Shi, P.; Andrews, K.G.; Engell, R.E.; Mozaffarian, D. Global, regional and national consumption of major food groups in 1990 and 2010: A systematic analysis including 266 country-specific nutrition surveys worldwide. BMJ Open 2015, 5, e008705. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Freisling, H.; Fahey, M.T.; Moskal, A.; Ocké, M.C.; Ferrari, P.; Jenab, M.; Norat, T.; Naska, A.; Welch, A.A.; Navarro, C.; et al. Region-specific nutrient intake patterns exhibit a geographical gradient within and between European countries. J. Nutr. 2010, 140, 1280–1286. [Google Scholar] [CrossRef] [Green Version]
- Cohen, S.A.; Greaney, M.L.; Klassen, A.C. A “Swiss paradox” in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans. Int. J. Health Geogr. 2019, 18, 28. [Google Scholar] [CrossRef]
- Bringolf-Isler, B.; Mäder, U.; Dössegger, A.; Hofmann, H.; Puder, J.J.; Braun-Fahrländer, C.; Kriemler, S. Regional differences of physical activity and sedentary behaviour in Swiss children are not explained by socio-demographics or the built environment. Int. J. Public Health 2015, 60, 291–300. [Google Scholar] [CrossRef] [Green Version]
- Caleyachetty, R.; Echouffo-Tcheugui, J.B.; Tait, C.A.; Schilsky, S.; Forrester, T.; Kengne, A.P. Prevalence of behavioural risk factors for cardiovascular disease in adolescents in low-income and middle-income countries: An individual participant data meta-analysis. Lancet Diabetes Endocrinol. 2015, 3, 535–544. [Google Scholar] [CrossRef]
- Quon, E.C.; McGrath, J.J. Province-level income inequality and health outcomes in Canadian adolescents. J. Pediatr. Psychol. 2015, 40, 251–261. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Singh, G.K.; Kogan, M.D.; Siahpush, M.; van Dyck, P.C. Prevalence and correlates of state and regional disparities in vigorous physical activity levels among US children and adolescents. J. Phys. Act. Health 2009, 6, 73–87. [Google Scholar] [CrossRef] [PubMed]
- Maksimov, S.A.; Shalnova, S.A.; Balanova, Y.A.; Kutsenko, V.A.; Evstifeeva, S.E.; Imaeva, A.E.; Drapkina, O.M. What regional living conditions affect individual smoking of adults in Russia. Int. J. Pub. Health 2021, 66, 599570. [Google Scholar] [CrossRef] [PubMed]
- Currie, C.; Grieber, R.; Inchley, J.; Theunissen, A.; Molcho, M.; Samdal, O.; Dür, W. (Eds.) Health Behaviour in School-Aged Children (HBSC) Study Protocol: Background, Methodology and Mandatory Items for the 2009/10 Survey; CAHRU & Vienna: LBIHPR: Edinburgh, Scotland, 2010; Available online: http://www.hbsc.org (accessed on 6 May 2022).
- Aleksandrov, A.A.; Kotova, M.B.; Zvezdina, I.V.; Ivanova, E.I.; Vaganov, A.D. Feeding habits, behavior, and knowledge about healthy lifestyles of school students in Murmansk. Pediatrics 2014, 93, 176–181. (In Russian) [Google Scholar]
- Kotova, M.B.; Rozanov, V.B.; Aleksandrov, A.A.; Ivanova, E.I.; Klimovich, V. Association of smoking with different risk behaviors in adolescents. Issues Psychol. 2015, 4, 38–49. (In Russian) [Google Scholar]
- Judd, S.E.; Letter, A.J.; Shikany, J.M.; Roth, D.L.; Newby, P.K. Dietary patterns derived using exploratory and confirmatory factor analysis are stable and generalizable across race, region, and gender subgroups in the REGARDS study. Front. Nutr. 2015, 1, 29. [Google Scholar] [CrossRef] [Green Version]
- Bedeian, A.G.; Armenakis, A.A.; Randolph, W.A. The significance of congruence coefficients: A comment and statistical test. J. Manag. 1988, 14, 559–566. [Google Scholar] [CrossRef]
- Smith, K.J.; Breslin, M.C.; McNaughton, S.A.; Gall, S.L.; Blizzard, L.; Venn, A.J. Skipping breakfast among Australian children and adolescents; findings from the 2011-12 National Nutrition and Physical Activity Survey. Aust. N. Z. J. Public Health. 2017, 41, 572–578. [Google Scholar] [CrossRef]
- Ree, M.; Riediger, N.; Moghadasian, M.H. Factors affecting food selection in Canadian population. Eur. J. Clin. Nutr. 2008, 62, 1255–1262. [Google Scholar] [CrossRef] [Green Version]
- Anschutz, D.J.; Van Strien, T.; Engels, R.C. Exposure to slim images in mass media: Television commercials as restriction in restrained eaters. Health Psychol. 2008, 27, 401–408. [Google Scholar] [CrossRef] [Green Version]
- Bargiota, A.; Pelekanou, M.; Tsitouras, A.; Koukoulis, G.N. Eating habits and factors affecting food choice of adolescents living in rural areas. Hormones 2013, 12, 246–253. [Google Scholar] [CrossRef] [PubMed]
- Loth, K.A.; MacLehose, R.F.; Fulkerson, J.A.; Crow, S.; Neumark-Sztainer, D. Are food restriction and pressure-to-eat parenting practices associated with adolescent disordered eating behaviors? Int. J. Eat Disord. 2014, 47, 310–314. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schnettler, B.; Grunert, K.G.; Lobos, G.; Miranda-Zapata, E.; Denegri, M.; Ares, G.; Hueche, C. A latent class analysis of family eating habits in families with adolescents. Appetite 2018, 129, 37–48. [Google Scholar] [CrossRef] [PubMed]
- de Lemus, S.; Spears, R.; Bukowski, M.; Moya, M.; Lupiáñez, J. Reversing implicit gender stereotype activation as a function of exposure to traditional gender roles. J. Soc. Psychol. 2013, 44, 109–116. [Google Scholar] [CrossRef]
- Monge-Rojas, R.; Fuster-Baraona, T.; Garita, C.; Sánchez, M.; Smith-Castro, V.; Valverde-Cerros, O.; Colon-Ramos, U. The influence of gender stereotypes on eating habits among Costa Rican adolescents. Am. J. Health Promot. 2015, 29, 303–310. [Google Scholar] [CrossRef]
- Beck, A.L.; Iturralde, E.; Haya-Fisher, J.; Kim, S.; Keeton, V.; Fernandez, A. Barriers and facilitators to healthy eating among low-income Latino adolescents. Appetite 2019, 138, 215–222. [Google Scholar] [CrossRef]
- Payán, D.D.; Sloane, D.C.; Illum, J.; Farris, T.; Lewis, L.B. Perceived barriers and facilitators to healthy eating and school lunch meals among adolescents: A qualitative study. Am. J. Health Behav. 2017, 41, 661–669. [Google Scholar] [CrossRef]
- Watts, A.W.; Lovato, C.Y.; Barr, S.I.; Hanning, R.M.; Mâsse, L.C. A qualitative study exploring how school and community environments shape the food choices of adolescents with overweight/obesity. Appetite 2015, 95, 360–367. [Google Scholar] [CrossRef]
- Chamberlin, A.; Nguyen-Rodriguez, S.; Gray, V.B.; Reiboldt, W.; Peterson, C.; Spruijt-Metz, D. Academic-related factors and emotional eating in adolescents. J. Sch. Health 2018, 88, 493–499. [Google Scholar] [CrossRef]
- Bellisle, F.; Hébel, P.; Salmon-Legagneur, A.; Vieux, F. Breakfast Consumption in French children, adolescents, and adults: A nationally representative cross-sectional survey examined in the context of the international breakfast research initiative. Nutrients 2018, 10, 1056. [Google Scholar] [CrossRef] [Green Version]
- Darling, K.E.; Ruzicka, E.B.; Fahrenkamp, A.J.; Sato, A.F. Perceived stress and obesity-promoting eating behaviors in adolescence: The role of parent-adolescent conflict. Fam. Syst. Health 2019, 37, 62–67. [Google Scholar] [CrossRef] [PubMed]
- Cabrera, S.G.; Fernández, N.H.; Hernández, C.R.; Nissensohn, M.; Román-Viña, B.; Serra-Majem, L. KIDMED test; prevalence of low adherence to the Mediterranean Diet in children and young; a systematic review. Nutr. Hosp. 2015, 32, 2390–2399. [Google Scholar] [CrossRef]
- Djordjevic-Nikic, M.; Dopsaj, M. Characteristics of eating habits and physical activity in relation to body mass index among adolescents. J. Am. Coll. Nutr. 2013, 32, 224–233. [Google Scholar] [CrossRef]
- Deshmukh-Taskar, P.; Nicklas, T.A.; Radcliffe, J.D.; O’Neil, C.E.; Liu, Y. The relationship of breakfast skipping and type of breakfast consumed with overweight/obesity, abdominal obesity, other cardiometabolic risk factors and the metabolic syndrome in young adults. The National Health and Nutrition Examination Survey (NHANES): 1999–2006. Public Health Nutr. 2013, 16, 2073–2082. [Google Scholar] [CrossRef] [Green Version]
- Silva, D.F.; Lyra, C.O.; Lima, S.C. Dietary habits of adolescents and associated cardiovascular risk factors: A systematic review. Ciênc. Saúde Colet. 2016, 21, 1181–1196. [Google Scholar] [CrossRef] [Green Version]
- Sugiyama, S.; Okuda, M.; Sasaki, S.; Kunitsugu, I.; Hobara, T. Breakfast habits among adolescents and their association with daily energy and fish, vegetable, and fruit intake: A community-based cross-sectional study. Environ. Health Prev. Med. 2012, 17, 408–414. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Trancoso, S.C.; Cavalli, S.B.; Proença, R.P.C. Breakfast: Characterization, consumption and importance for health. Rev. Nutr. 2010, 23, 859–869. [Google Scholar] [CrossRef] [Green Version]
- Timlin, M.T.; Pereira, M.A.; Story, M.; Neumark-Sztainer, D. Breakfast eating and weight change in a 5-year prospective analysis of adolescents: Project EAT (Eating among Teens). Pediatrics 2008, 121, e638–e645. [Google Scholar] [CrossRef] [Green Version]
- Cohen, B.; Evers, S.; Manske, S.; Bercovitz, K.; Edward, H.G. Smoking, physical activity and breakfast consumption among secondary school students in a southwestern Ontario community. Can J. Public Health 2003, 94, 41–44. [Google Scholar] [CrossRef]
- Crowley, S.J.; Acebo, C.; Carskadon, M.A. Sleep, circadian rhythms, and delayed phase in adolescence. Sleep Med. 2007, 8, 602–612. [Google Scholar] [CrossRef]
- Roenneberg, T.; Kuehnle, T.; Pramstaller, P.P.; Ricken, J.; Havel, M.; Guth, A.; Merrow, M. A marker for the end of adolescence. Curr. Biol. 2004, 14, R1038-9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Barufaldi, L.A.; De Azevedo Abreu, G.; Oliveira, J.S.; Dos Santos, D.F.; Fujimori, E.; Vasconcelos, S.M.L.; De Vasconcelos, F.A.G.; Tavares, B.M. ERICA: Prevalence of healthy eating habits among Brazilian adolescents. Rev. Saude Publica 2016, 50 (Suppl. 1). [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hinnig, P.F.; Monteiro, J.S.; De Assis, M.A.A.; Levy, R.B.; Peres, M.A.; Perazi, F.M.; Porporatti, A.L.; Canto, G.L. Dietary Patterns of children and adolescents from high, medium and low human development countries and associated socioeconomic factors: A systematic review. Nutrients 2018, 10, 436. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De la Torre-Moral, A.; Fàbregues, S.; Bach-Faig, A.; Fornieles-Deu, A.; Medina, F.X.; Aguilar-Martínez, A.; Sánchez-Carracedo, D. Family meals, conviviality, and the Mediterranean diet among families with adolescents. Int. J. Environ. Res. Pub. Health 2021, 18, 2499. [Google Scholar] [CrossRef] [PubMed]
- Grosso, G.G. Mediterranean diet adherence in children and adolescents in Southern European countries. NFS J. 2016, 3, 13–19. [Google Scholar] [CrossRef] [Green Version]
- Arcan, C.; Friend, S.; Flattum, C.F.; Story, M.; Fulkerson, J.A. Fill “half your child’s plate with fruits and vegetables”: Correlations with food-related practices and the home food environment. Appetite 2019, 133, 77–82. [Google Scholar] [CrossRef]
- Bielawska, A.; Tomczyk, K.; Adamek, B.; Rybus-Kalinowska, B.; Warakomski, J.; Łabuz-Roszak, B. Eating habits of the youths from Ruda Slaska. Wiad. Lek. 2018, 71 Pt 2, 358–365. (In Polish) [Google Scholar]
- Rogers, I.; Emmett, P. ALSPAC Study Team. The effect of maternal smoking status, educational level and age on food and nutrient intakes in preschool children: Results from the Avon Longitudinal Study of Parents and Children. Eur. J. Clin. Nutr. 2003, 57, 854–864. [Google Scholar] [CrossRef] [Green Version]
- Karamnova, N.S.; Shalnova, S.A.; Deev, A.D.; Tarasov, V.I.; Balanova, Y.; Imaeva, A.E.; Kontsevaya, A.V.; Muromtseva, G.A.; Kapustina, A.V.; Evstifeeva, S.E.; et al. Smoking status and nutrition type of adult population: Variety of meals. Results from the ESSE-RF study. Russ. J. Cardiol. 2018, 6, 131–140. (In Russian) [Google Scholar] [CrossRef] [Green Version]
- Larson, N.I.; Story, M.; Perry, C.L.; Neumark-Sztainer, D.; Hannan, P.J. Are diet and physical activity patterns related to cigarette smoking in adolescents? Findings from Project EAT. Prev. Chronic. Dis. 2007, 4, A51. [Google Scholar]
- Kotova, M.B.; Rozanov, V.B.; Ivanova, E.I.; Alexandrov, A.A. Family-based association of smoking with self-assessment of health, lifestyle and quality of life in school students. Prev. Med. 2020, 23, 85–98. (In Russian) [Google Scholar] [CrossRef]
Groups | 10–12 y/o | 13–15 y/o | 16–17 y/o | TOTAL by Gender | TOTAL in Cities | |
---|---|---|---|---|---|---|
Moscow | Girls | 29.9 (66) | 40.7 (90) | 29.4 (65) | 100.0 (221) | 100.0 (441) |
Boys | 32.7 (72) | 36.9 (81) | 30.4 (67) | 100.0 (220) | ||
Murmansk | Girls | 31.4 (50) | 40.9 (65) | 27.7 (44) | 100.0 (159) | 100.0 (342) |
Boys | 24.6 (45) | 51.4 (94) | 24.0 (44) | 100.0 (183) |
Parameters | Identified Patterns | |||
---|---|---|---|---|
DP 1 | DP 2 | DP 3 | PAP | |
Fruits and vegetables | 0.48 | - | - | - |
Hot meals | 0.48 | - | - | - |
Meat and meat products | 0.64 | - | - | - |
Fish and fish products | 0.45 | - | - | - |
Milk and dairy products | 0.57 | - | - | - |
Fast food | - | −0.78 | - | - |
Carbonated drinks | - | −0.78 | - | - |
Smoked meats and canned food | - | 0.52 | - | - |
Meal frequency | - | - | 0.81 | - |
Availability of breakfast | - | - | 0.78 | - |
Sleep duration | - | - | - | −0.64 |
Morning exercises | - | - | - | 0.73 |
Physical education lessons | - | - | - | 0.42 |
Outdoor walks | - | - | - | 0.32 |
Explained variance, % | 0.15 | 0.16 | 0.13 | 0.31 |
Groups | 3rd Tertile DP1 | 3rd Tertile DP2 | 3rd Tertile DP3 | 3rd Tertile PAP | |||||
---|---|---|---|---|---|---|---|---|---|
% (n) | p | % (n) | p | % (n) | p | % (n) | p | ||
Gender | Girls | 32.6 (124) | 0.85 | 23.2 (88) | <0.0001 | 38.9 (148) | 0.0055 | 36.6 (139) | 0.12 |
Boys | 32.0 (129) | 44.2 (178) | 29.5 (119) | 31.3 (126) | |||||
Age | 10–12 y/o | 30.5 (71) | 0.24 | 33.5 (78) | 0.86 | 27.9 (65) | 0.021 | 11.6 (27) | <0.0001 |
13–15 y/o | 30.6 (101) | 33.3 (110) | 39.1 (129) | 40.6 (134) | |||||
16–17 y/o | 36.8 (81) | 35.4 (78) | 33.2 (73) | 47.3 (104) | |||||
City | Moscow | 33.8 (149) | 0.32 | 33.6 (148) | 0.78 | 32.4 (143) | 0.26 | 36.5 (161) | 0.074 |
Murmansk | 30.4 (104) | 34.5 (118) | 36.6 (124) | 30.4 (104) | |||||
Room | Separate | 30.6 (184) | 0.065 | 34.3 (206) | 0.74 | 32.8 (197) | 0.16 | 34.3 (206) | 0.64 |
Shared | 37.9 (69) | 33.0 (60) | 38.5 (70) | 32.4 (59) | |||||
Family | Incomplete | 32.1 (52) | 0.95 | 40.1 (65) | 0.063 | 42.0 (68) | 0.018 | 40.1 (65) | 0.058 |
Complete | 32.4 (201) | 32.4 (201) | 32.0 (199) | 32.2 (200) | |||||
Number of children | 1 child | 31.7 (120) | 0.71 | 35.6 (135) | 0.35 | 31.7 (120) | 0.16 | 32.7 (124) | 0.52 |
2 or more | 32.9 (133) | 32.4 (131) | 36.4 (147) | 34.9 (141) | |||||
Mother’s education | Not higher | 34.1 (74) | 0.51 | 37.8 (82) | 0.16 | 37.8 (82) | 0.18 | 29.9 (65) | 0.15 |
Higher | 31.6 (179) | 32.5 (184) | 32.7 (185) | 35.4 (200) | |||||
Smoking | No | 28.9 (141) | 0.0099 | 29.8 (145) | 0.0015 | 31.6 (154) | 0.061 | 34.7 (169) | 0.52 |
Yes | 37.8 (112) | 40.9 (121) | 38.2 (113) | 32.4 (96) |
Groups | 3rd Tertile DP1 | 3rd Tertile DP2 | 3rd Tertile DP3 | 3rd Tertile PAP | |||||
---|---|---|---|---|---|---|---|---|---|
OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
Gender (reference: girls) | Boys | 1.00 | 0.74–1.36 | 2.72 * | 1.97–3.75 | 0.65 * | 0.48–0.88 | 0.78 | 0.56–1.07 |
Age (reference: 10–12 y/o) | 13–15 y/o | 1.06 | 0.72–1.55 | 0.74 | 0.71–1.63 | 1.63 * | 1.12–2.38 | 5.69 * | 3.55–9.13 |
16–17 y/o | 1.36 | 0.90–2.00 | 0.99 | 0.68–1.45 | 1.20 | 0.79–1.82 | 7.34 * | 4.45–12.10 | |
City (reference: Moscow) | Murmansk | 0.89 | 0.65–1.22 | 1.00 | 0.73–1.38 | 1.16 | 0.85–1.59 | 0.71 * | 0.51–0.99 |
Room (reference: separate) | Shared | 1.40 | 0.98–1.99 | 1.01 | 0.70–1.48 | 1.23 | 0.86–1.76 | 0.90 | 0.61–1.32 |
Family (reference: incomplete) | Complete | 1.08 | 0.74–1.60 | 0.70 | 0.47–1.02 | 0.66 * | 0.45–0.96 | 0.71 | 0.48–1.05 |
Number of children (reference: 1) | 2 or more | 0.92 | 0.67–1.27 | 0.77 | 0.56–1.07 | 1.22 | 0.89–1.68 | 1.01 | 0.73–1.40 |
Mother’s education (reference: not higher) | Higher | 0.87 | 0.62–1.24 | 0.69 | 0.48–0.98 | 0.85 | 0.61–1.20 | 1.02 | 0.71–1.48 |
Smoking (reference: none) | Yes | 1.47 * | 1.07–2.03 | 1.64 * | 1.18–2.27 | 1.27 | 0.93–1.75 | 0.74 | 0.53–1.03 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kotova, M.B.; Maksimov, S.A.; Drapkina, O.M. Gender, Age, Family and Territorial Features of Dietary and Physical Activity Patterns in Russian Youths. Int. J. Environ. Res. Public Health 2022, 19, 5779. https://doi.org/10.3390/ijerph19095779
Kotova MB, Maksimov SA, Drapkina OM. Gender, Age, Family and Territorial Features of Dietary and Physical Activity Patterns in Russian Youths. International Journal of Environmental Research and Public Health. 2022; 19(9):5779. https://doi.org/10.3390/ijerph19095779
Chicago/Turabian StyleKotova, Marina B., Sergey A. Maksimov, and Oksana M. Drapkina. 2022. "Gender, Age, Family and Territorial Features of Dietary and Physical Activity Patterns in Russian Youths" International Journal of Environmental Research and Public Health 19, no. 9: 5779. https://doi.org/10.3390/ijerph19095779