Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam
Abstract
1. Introduction
2. Methods
3. Results
3.1. Demographics
3.2. OWOB Prevalence
3.3. Nutrition Factors
3.4. Sleep and Screen-Time
3.5. Acculturation
4. Discussion
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Ogden, C.L.; Carroll, M.D.; Kit, B.K.; Flegal, K.M. Prevalence of childhood and adult obesity in the United States, 2011–2012. JAMA 2014, 311, 806–814. [Google Scholar] [CrossRef] [PubMed]
- Ogden, C.L.; Carroll, M.D.; Fryar, C.D.; Flegal, K.M. Prevalence of Obesity among Adults and Youth: United States, 2011–2014. NCHS Data Brief 2015, 219, 1–8. [Google Scholar]
- Yang, L.; Colditz, G.A. Prevalence of Overweight and Obesity in the United States, 2007–2012. JAMA Intern. Med. 2015, 175, 1412–1413. [Google Scholar] [CrossRef] [PubMed]
- Afshin, A.; Forouzanfar, M.H.; Reitsma, M.B.; Sur, P.; Estep, K.; Lee, A.; Marczak, L.; Mokdad, A.H.; Moradi-Lakeh, M.; Naghavi, M.; et al. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N. Engl. J. Med. 2017, 377, 13–27. [Google Scholar] [CrossRef]
- Ng, M.; Fleming, T.; Robinson, M.; Thomson, B.; Graetz, N.; Margano, C.; Mullany, C.E.; Biryukov, S.; Abbafati, C.; Abera, F.S.; et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014, 384, 766–781. [Google Scholar] [CrossRef]
- Novotny, R.; Fialkowski, M.K.; Li, F.; Paulino, Y.S.N.; Vargo, D.; Jim, R.; Coleman, P.; Bersamin, A.; Nigg, C.R.; Leon Guerrero, R.T.; et al. Systematic review of prevalence of young child overweight and obesity in the United States Affiliated Pacific region compared to the 48 contiguous states: A the Children’s Health Living Program. Am. J. Pub. Health 2015. [Google Scholar] [CrossRef]
- Underwood, J. The native origins of the neo-Chamorros of the Mariana Islands. Micronesia 1976, 12, 203–209. [Google Scholar]
- Vilar, M.G.; Chan, C.W.; Santos, D.R.; Lynch, D.; Spathis, R.; Garruto, R.M.; Lum, J.K. The origins and genetic distinctiveness of the Chamorros of the Marianas Islands: An mtDNA perspective. Am. J. Hum. Biol. 2013, 25, 116–122. [Google Scholar] [CrossRef]
- Central Intelligence Agency: The World Factbook. Available online: https://www.cia.gov/library/publications/the-world-factbook/geos/gq.html (accessed on 30 June 2020).
- Asian and Pacific Islander American Health Forum Health Briefs: Chamorros in the United States. Asian and Pacific Islander American Health Forum. 2006. Available online: https://www.apiahf.org/wp-content/uploads/2011/02/APIAHF_Healthbrief08j_2006-1.pdf (accessed on 25 June 2020).
- Guerrero, R.T.L.; Paulino, Y.C.; Novotny, R.; Murphy, S.P. Diet and obesity among Chamorro and Filipino adults on Guam. Asia Pac. J. Clin. Nutr. 2008, 17, 216–222. [Google Scholar]
- Hankin, J.; Reed, D.; Labarthe, D.; Nichaman, M.; Stallones, R. Dietary and Disease Patterns among Micronesians. Am. J. Clin. Nutr. 1970, 23, 346–357. [Google Scholar] [CrossRef]
- Pollock, N. Food habits in Guam over 500 years. Pac. Viewp. 1986, 27, 120–143. [Google Scholar] [CrossRef]
- Uncangco, A.; Badowski, G.; David, A.; Ehlert, M.; Haddock, R.; Paulino, Y. First Guam BRFSS Report 2007–2010; Guam Department of Public Health & Social Services: Mangilao, Guam, USA, 2012.
- 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]
- Barker, D.J.; Osmond, C.; Forsen, T.J.; Kajantie, E.; Eriksson, J.G. Trajectories of growth among children who have coronary events as adults. N. Engl. J. Med. 2005, 353, 1802–1809. [Google Scholar] [CrossRef] [PubMed]
- Wilken, L.R.; Novotny, R.; Fialkowski, M.K.; Boushey, C.J.; Nigg, C.; Paulino, Y.; Leon Guerrero, R.; Bersamin, A.; Vargo, D.; Kim, J.; et al. Children’s Healthy Living (CHL) Program for remote underserved minority populations in the Pacific region: Rationale and design of a community randomized trial to prevent early childhood obesity. BMC Pub. Health 2013, 13, 944. [Google Scholar] [CrossRef] [PubMed]
- Novotny, R.; Fialkowski, M.K.; Areta, A.A.; Bersamin, A.; Braun, K.; DeBaryshe, B.; Deenik, J.; Dunn, M.; Hollyer, J.; Kim, J.; et al. The Pacific Way to Child Wellness: The Children’s Healthy Living Program for Remote Underserved Minority Populations of the Pacific Region (CHL). Hawaii J. Med. Pub. Health 2013, 72, 406–408. [Google Scholar]
- McGreavey, J.A.; Donnan, P.T.; Pagliari, H.C.; Sullivan, F.M. The tayside children’s sleep questionnaire: A simple tool to evaluate sleep problems in young children. Child Care Health Dev. 2005, 31, 539–544. [Google Scholar] [CrossRef]
- Hirshkowitz, M.; Whiton, K.; Albert, S.M.; Alessi, C.; Bruni, O.; DonCarlos, L.; Hazen, N.; Herman, J.; Katz, E.S.; Kheirandish-Gozal, L.; et al. National Sleep Foundation’s sleep time duration recommendations: Methodology and results summary. Sleep Health 2015, 1, 40–43. [Google Scholar] [CrossRef]
- Coleman-Jensen, A.; Gregory, C.; Singh, A. Household Food Security in the United States in 2013; US Department of Agriculture, Economic Research Service, Ed.; USDA Economic Research Service: Washington, DC, USA, 2014.
- Kaholokula, J.K.; Iwane, M.K.; Nacapoy, A.H. Effects of perceived racism and acculturation on hypertension in Native Hawaiians. Hawaii Med. J. 2010, 69, 11–15. [Google Scholar]
- Li, F.; Wilkens, L.R.; Novotny, R.; Fialkowski, M.; Paulino, Y.C.; Nelson, R.; Bersamin, A.; Martin, U.; Deenik, J.; Boushey, C. Anthropometric Measurement Standardization in the US-Affiliated Pacific: Report from the Children’s Healthy Living Program. Am. J. Hum. Biol. 2016, 28, 364–371. [Google Scholar] [CrossRef]
- Cook, S.; Auinger, P.; Huang, T.T. Growth curves for cardio-metabolic risk factors in children and adolescents. J. Pediatr. 2009, 155, e15–e26. [Google Scholar] [CrossRef]
- Barlow, S. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: Summary report. Pediatrics 2007, 120 (Suppl. 4), S164–S192. [Google Scholar] [CrossRef] [PubMed]
- Centers for Disease Control and Prevention A SAS Program for the 2000 CDC Growth Charts (Ages 0 to <20 Years); Centers for Disease Control and Prevention; 2014. Available online: https://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm (accessed on 6 April 2020).
- Zimmet, P.; Alberti, K.G.; Kaufman, F.; Tajima, N.; Silink, M.; Arslanian, S.; Wong, G.; Bennett, P.; Shaw, J.; Caprio, S.; et al. The metabolic syndrome in children and adolescents—An IDF consensus report. Pediatr. Diabetes 2007, 8, 299–306. [Google Scholar] [CrossRef] [PubMed]
- Novotny, R.; Nigg, C.; McGlone, K.; Renda, G.; Jung, N.; Matsunaga, M.; Karanja, N. Pacific tracker 2—Expert system (PacTrac2-ES) behavioural assessment and intervention tool for the pacific kids DASH for health (PacDASH) study. Food Chem. 2013, 140, 471–477. [Google Scholar] [CrossRef] [PubMed]
- Martin, C.L.; Murphy, S.P.; Leon Guerrero, R.T.; Davison, N.; Jung, Y.O.; Novotny, R. The Pacific Tracker (PacTrac): Development of a dietary assessment instrument for the Pacific. J. Food Compost. Anal. 2008, 21, S103–S108. [Google Scholar] [CrossRef] [PubMed]
- Murphy, S.; Blitz, C.; Novotny, R. Pacific tracker (PacTrac): An interactive dietary assessment program at the CRCH website. Hawaii Med. J. 2006, 65, 175–178. [Google Scholar] [PubMed]
- Rolland-Cachera, M.F.; Akrout, M.; Peneau, S. Nutrient Intakes in Early Life and Risk of Obesity. Int. J. Environ. Res. Public Health 2016, 13, 564. [Google Scholar] [CrossRef]
- Weihrauch-Blüher, S.; Wiegand, S. Risk Factors and Implications of Childhood Obesity. Curr. Obes. Rep. 2018, 7, 254–259. [Google Scholar] [CrossRef]
- 2015 Poverty Guidelines. Office of the Assistant Secretary for Planning and Evaluation. US Department of Public Health and Social Services. Available online: https://aspe.hhs.gov/2015-poverty-guidelines (accessed on 9 July 2020).
- U.S. Department of Health and Human Services and U.S. Department of Agriculture. 2015–2020 Dietary Guidelines for Americans, 8th ed.; December 2015. Available online: http://health.gov/dietaryguidelines/2015/guidelines/ (accessed on 22 April 2020).
- Bowman, S.; Friday, J.; Moshfegh, A. MyPyramid Equivalents Database, 2.0 for USDA Survey Foods, 2003–2004 [Online]; Food Surveys Research Group, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S., Ed.; Department of Agriculture: Beltsville, MD, USA, 2008.
- Friday, J.; Bowman, S. MyPyramid Equivalents Database for USDA Survey Food Codes, 1994–2002 Version 1.0. [Online]; USDA, Agricultural Research Service, Beltsville Human Nutrition Research Center, Ed.; Community Nutrition Research Group: Beltsville, MD, USA, 2006.
- Popkin, B.M.; Armstrong, L.E.; Bray, G.M.; Caballero, B.; Frei, B.; Willett, W.C. A new proposed guidance system for beverage consumption in the United States. Am. J. Clin. Nutr. 2006, 83, 529–542. [Google Scholar] [CrossRef]
- American Academy of Pediatrics. Children, adolescents, and television. Pediatrics 2001, 107, 423–426. [Google Scholar] [CrossRef]
- Renzaho, A.M.; Swinburn, B.; Burns, C. Maintenance of traditional cultural orientation is associated with lower rates of obesity and sedentary behaviours among African migrant children to Australia. Int. J. Obes. 2008, 32, 594–600. [Google Scholar] [CrossRef]
- Hixson, L.; Hepler, B.B.; Kim, M.O. The Native Hawaiian and other Pacific Islander Population: 2010; US Census Bureau, Ed.; US Census Bureau: Washington, DC, USA, 2012.
- Wate, J. Chapter 2: The Obesity Pandemic in the Pacific. In Wealthy but Unhealthy: Overweight and Obesity in Asia and the Pacific: Trends, Costs, and Policies for Better Health; Helble, M., Sato, A., Eds.; Asian Development Bank Institute: Tokyo, Japan, 2018. [Google Scholar]
- Skinner, A.C.; Ravanbakht, S.N.; Skelton, J.A.; Perrin, E.M.; Armstrong, S.C. Prevalence of obesity and severe obesity in US children, 1999–2016. Pediatrics 2018. [Google Scholar] [CrossRef] [PubMed]
- Paulino, Y.C.; Guerrero, R.T.; Uncangco, A.A.; Rosadino, M.G.; Quinene, J.C.; Natividad, Z.N. Overweight and obesity prevalence among public school children in Guam. J. Health Care Poor Underserved 2015, 26 (Suppl. 2), 53–62. [Google Scholar] [CrossRef] [PubMed]
- Minster, R.L.; Hawley, N.L.; Su, C.T.; Sun, G.; Kershaw, E.E.; Cheng, H.; Buhule, O.D.; Lin, J.; Reupena, M.S.; Viali, S.; et al. A thrifty variant in CREBRF strongly influences body mass index in Samoans. Nat. Genet. 2016, 48, 1049–1054. [Google Scholar] [CrossRef] [PubMed]
- Furusawa, T.; Naka, I.; Yamauchi, T.; Natsuhara, K.; Kimura, R.; Nakazawa, M.; Ishida, T.; Inaoka, T.; Matsumura, Y.; Ataka, Y.; et al. The Q223R polymorphism in LEPR is associated with obesity in Pacific Islanders. Hum. Genet. 2010, 127, 287–294. [Google Scholar] [CrossRef]
- Brambilla, P.; Bedogni, G.; Heo, M.; Pietrobelli, A. Waist circumference-to-height ratio predicts adiposity better than body mass index in children and adolescents. Int. J. Obes. 2013, 37, 943–946. [Google Scholar] [CrossRef]
- Vieira, S.A.; Ribeiro, A.Q.; Hermsdorff, H.H.M.; Pereira, P.F.; Priore, S.E.; Franceschini, S. Waist-to-height ratio index or the prediction of overweight in children. Rev. Paul. Pediatr. 2018, 36, 7. [Google Scholar]
- Rakić, R.; Pavlica, T.; Bjelanović, J.; Vasiljević, P. Predictive ability of waist-to-hip-ratio and waist-to-height-ratio in relation to overweight/obesity in adolescents from Vojvodina (the Republic of Serbia) predictive ability of waist-to-hip-ratio and waist-to-height-ratio: Predictive Ability of Waist-to-Hip-Ratio and Waist-to-Height-Ratio. Prog. Nutr. 2019, 24, 992–998. [Google Scholar]
- Staiano, A.E.; Gupta, A.K.; Katzmarzyk, P.T. Cardiometabolic risk factors and fat distribution in children and adolescents. J. Pediatr. 2014, 164, 560–565. [Google Scholar] [CrossRef]
- Freedman, D.S.; Dietz, W.H.; Srinivasan, S.R.; Berenson, G.S. The relation of overweight to cardiovascular risk factors among children and adolescents: The Bogalusa Heart Study. Pediatrics 1999, 103 Pt 1, 1175–1182. [Google Scholar] [CrossRef]
- Kahn, H.S.; Imperatore, G.; Cheng, Y.J. A population-based comparison of BMI percentiles and waist-to-height ratio for identifying cardiovascular risk in youth. J. Pediatr. 2005, 146, 482–488. [Google Scholar] [CrossRef]
- Dixon, B.; Peña, M.M.; Taveras, E.M. Lifecourse approach to racial/ethnic disparities in childhood obesity. Adv. Nutr. 2012, 3, 73–82. [Google Scholar] [CrossRef] [PubMed]
- Epstein, L.H.; Myers, M.D.; Anderson, K. The association of maternal psychopathology and family socioeconomic status with psychological problems in obese children. Obes. Res. 1996, 4, 65–74. [Google Scholar] [CrossRef] [PubMed]
- Davis, M.; Young, L.; Davis, S.P.; Moll, G. Parental depression, family functioning and obesity among African American children. J. Cult. Divers. 2008, 15, 61–65. [Google Scholar] [PubMed]
- McConley, R.L.; Mrug, S.; Gilliland, M.J.; Lowry, R.; Elliott, M.N.; Schuster, M.A.; Bogart, L.M.; Franzini, L.; Escobar-Chaves, S.L.; Franklin, F.A. Mediators of maternal depression and family structure on child BMI: Parenting quality and risk factors for child overweight. Obesity 2011, 19, 345–352. [Google Scholar] [CrossRef]
- Pacheco, S.R.; Miranda, A.M.; Coelho, R.; Monteiro, A.C.; Braganca, G.; Loureiro, H.C. Overweight in youth and sleep quality: Is there a link? Arch. Endocrinol. Metab. 2017. [Google Scholar] [CrossRef]
- Navarro-Solera, M.; Carrasco-Luna, J.; Pin-Arboledas, G.; Gonzalez-Carrascosa, R.; Soriano, J.M.; Codoner-Franch, P. Short Sleep Duration Is Related to Emerging Cardiovascular Risk Factors in Obese Children. J. Pediatr. Gastroenterol. Nutr. 2015, 61, 571–576. [Google Scholar] [CrossRef]
- Sakamoto, N.; Gozal, D.; Smith, D.L.; Yang, L.; Morimoto, N.; Wada, H.; Maruyama, K.; Ikeda, A.; Suzuki, Y.; Nakayama, M.; et al. Sleep duration, snoring prevalence, obesity, and behavioral problems in a large cohort of primary school students in Japan. Sleep 2017, 40. [Google Scholar] [CrossRef]
- Morrissey, B.; Allender, S.; Strugnell, C. Dietary and activity factors influence poor sleep and the sleep-obesity nexus among children. Int. J. Environ. Res. Public Health 2019, 16, 1778. [Google Scholar] [CrossRef]
- Trinh, M.H.; Sundaram, R.; Robinson, S.L.; Lin, T.C.; Bell, E.M.; Ghassabian, A.; Yeung, E.H. Association of trajectory and covariates of children’s screen media time. JAMA Pediatr. 2019, 174, 71–78. [Google Scholar] [CrossRef]
- Twenge, J.M.; Hisler, G.C.; Krizan, Z. Associations between screen time and sleep duration are primarily driven by portable electronic devices: Evidence from a population-based study of U.S. children ages 0–17. Sleep Med. 2019, 56, 211–218. [Google Scholar] [CrossRef]
- Guerrero, M.D.; Barnes, J.D.; Chaput, J.P.; Tremblay, M.S. Screen time and problem behaviors in children: Exploring the mediating role of sleep duration. Int. J. Behav. Nutr. Phys. Act. 2019, 16, 105. [Google Scholar] [CrossRef] [PubMed]
- Aflague, T.; Boushey, C.; Leon Guerrero, R.; Ahmad, Z.; Kerr, D.; Delp, E. Feasibility and use of the mobile food record for capturing eating occasions among children ages 3–10 years in Guam. Nutrients 2015, 7, 4403–4415. [Google Scholar] [CrossRef] [PubMed]
- Burt, C.H.; Simons, R.L.; Gibbons, F.X. Racial discrimination, ethnic-racial socialization, and crime: A micro-sociological model of risk and resilience. Am. Sociol. Rev. 2012, 77, 648–677. [Google Scholar] [CrossRef] [PubMed]
- Delavari, M.; Sønderlund, A.L.; Swinburn, B.; Mellor, D.; Renzaho, A. Acculturation and obesity among migrant populations in high income countries—A systematic review. BMC Public Health 2013, 13, 458. [Google Scholar] [CrossRef] [PubMed]
- Lind, C.; Mirchandani, G.G.; Castrucci, B.C.; Chávez, N.; Handler, A.; Hoelscher, D.M. The effects of acculturation on healthy lifestyle characteristics among Hispanic fourth-grade children in Texas public schools, 2004–2005. J. School Health 2012, 82, 166–174. [Google Scholar] [CrossRef] [PubMed]
- Bolstad, A.L.; Bungum, T. Diet, acculturation, and BMI in Hispanics living in southern Nevada. Am. J. Health Behav. 2013, 37, 218–226. [Google Scholar] [CrossRef]
- Lee, S.; Sobal, J.; Frongillo, E. Acculturation, food consumption, and diet-related factors among Korean Americans. J. Nutr. Educ. 1999, 31, 321–330. [Google Scholar] [CrossRef]
- Pobocik, R.S.; Richer, J.J.; Hentges, D.L. Food sources of macronutrients in the diets of fifth grade children on Guam. Asian Am. Pac. Isl. J. Health 1999, 7, 25–37. [Google Scholar]
- Pobocik, R.S.; Richer, J.J. Estimated intake and food sources of vitamin, A.; folate, vitamin, C.; vitamin, E.; calcium, iron, and zinc for Guamanian children aged 9 to 12. Pac. Health Dialog 2002, 9, 193–202. [Google Scholar]
- LeonGuerrero, R.T.; Workman, R.L. Physical activity and nutritional status of adolescents on Guam. Pac. Health Dialog 2002, 9, 177–185. [Google Scholar]
- Thomson, J.L.; Landry, A.S.; Tussing-Humphreys, L.M.; Goodman, M.H. Diet quality of children in the United States by body mass index and sociodemographic characteristics. Obes. Sci. Pract. 2020, 6, 84–98. [Google Scholar] [CrossRef] [PubMed]
- Koletzko, B.; Godfrey, K.M.; Poston, L.; Szajewska, H.; van Goudoever, J.B.; de Waard, M.; Brands, B.; Grivell, R.M.; Deussen, A.R.; Dodd, J.M.; et al. Nutrition during pregnancy, lactation and early childhood and its implications for maternal and long-term child health: The early nutrition project recommendations. Ann. Nutr. Metab. 2019, 74, 93–106. [Google Scholar] [CrossRef] [PubMed]
- Koletzko, B.; Brands, B.; Grote, V.; Kirchberg, F.F.; Prell, C.; Rzehak, P.; Uhl, O.; Weber, M. Long-term health impact of early nutrition: The power of programming. Ann. Nutr. Metab. 2017, 70, 161–169. [Google Scholar] [CrossRef] [PubMed]
- Horta, B.L.; Loret de Mola, C.; Victora, C.G. Long-term consequences of breastfeeding on cholesterol, obesity, systolic blood pressure and type 2 diabetes: A systematic review and meta-analysis. Acta. Paediatr. 2015, 104, 30–37. [Google Scholar] [CrossRef]
- Keller, A.; Bucher Della Torre, S. Sugar-sweetened beverages and obesity among children and adolescents: A review of systematic literature reviews. Child. Obes. 2015, 11, 338–346. [Google Scholar] [CrossRef]
- Scharf, R.J.; DeBoer, M.D. Sugar-Sweetened Beverages and Children’s Health. Annu. Rev. Public Health 2016, 37, 273–293. [Google Scholar] [CrossRef]
- Frantsve-Hawley, J.; Bader, J.D.; Welsh, J.A.; Wright, J.T. A systematic review of the association between consumption of sugar-containing beverages and excess weight gain among children under age 12. J. Public Health Dent. 2017, 77 (Suppl. 1), S43–S66. [Google Scholar] [CrossRef]
- Laverty, A.A.; Magee, L.; Monteiro, C.A.; Saxena, S.; Millett, C. Sugar and artificially sweetened beverage consumption and adiposity changes: National longitudinal study. Int. J. Behav. Nutr. Phys. Act. 2015, 12, 137. [Google Scholar] [CrossRef]
- Wojcicki, J.M.; Medrano, R.; Lin, J.; Epel, E. Increased cellular aging by 3 years of age in latino, preschool children who consume more sugar-sweetened beverages: A pilot study. Child. Obes. 2018, 14, 149–157. [Google Scholar] [CrossRef]
- Macintyre, A.K.; Marryat, L.; Chambers, S. Exposure to liquid sweetness in early childhood: Artificially-sweetened and sugar-sweetened beverage consumption at 4–5 years and risk of overweight and obesity at 7–8 years. Pediatr. Obes. 2018, 13, 755–765. [Google Scholar] [CrossRef]
- Dubois, L.; Farmer, A.; Girard, M.; Peterson, K. Regular sugar-sweetened beverage consumption between meals increases risk of overweight among preschool-aged children. J. Am. Diet. Assoc. 2007, 107, 924–934. [Google Scholar] [CrossRef] [PubMed]
- Snowdon, W.; Raj, A.; Reeve, E.; Guerrero, R.; Fesaitu, J.; Cateine, K.; Guignet, C. Processed foods available in the Pacific Islands. Glob. Health 2013, 9, 53. [Google Scholar] [CrossRef] [PubMed]
Total | CHamoru (n = 561) | Other Micronesians (n = 223) | Filipino (n = 81) | Other (n = 10) | p Value | |
---|---|---|---|---|---|---|
Child Participant | ||||||
Age, years | 5.79 ± 0.062 | 5.80 ± 0.078 | 5.66 ± 0.123 | 5.99 ± 0.062 | 6.24 ± 0.670 | |
2–5 years old | 465 (53.76%) | 296 (52.76%) | 123 (57.76%) | 42 (51.85%) | 4 (40%) | 0.418 |
6–8 years old | 400 (46.24%) | 265 (47.23%) | 90 (42.25%) | 39 (48.14%) | 6 (60%) | |
Birthplace | 0.0001 | |||||
Guam | 723 (84.46%) | 488 (88.09%) | 170 (80.19%) | 62 (76.54%) | 3 (33.33%) | |
U.S. Mainland | 52 (6.08%) | 36 (6.50%) | 9 (4.25%) | 3 (3.70%) | 4 (44.44%) | |
Saipan, CNMI | 34 (3.97%) | 28 (5.05%) | 5 (2.36%) | 1 (1.24%) | 0 (0%) | |
Other Islands in Micronesia | 28 (3.27%) | 0 (0%) | 28 (13.21%) | 0 (0%) | 0 (0%) | |
Philippines | 15 (1.75%) | 0 (0%) | 0 (0%) | 15 (18.52%) | 0 (0%) | |
Other | 4 (0.47%) | 2 (0.36%) | 0 (0%) | 0 (0%) | 2 (22.22%) | |
Ever Breastfed? | 0.0006 | |||||
Yes | 557 (67.19%) | 341 (62.80%) | 155 (78.68%) | 53 (67.09%) | 8 (80%) | |
No | 272 (32.81%) | 202 (37.20%) | 42 (21.32%) | 26 (32.91%) | 2 (20%) | |
Child fed both breastmilk & infant formula | 0.8223 | |||||
Yes | 443 (54.23%) | 291 (54.09%) | 102 (53.40%) | 46 (58.23%) | 4 (44.45%) | |
No | 374 (45.77%) | 247 (45.91%) | 89 (46.60%) | 33 (41.77%) | 5 (55.55%) | |
Child age (months) when weaned from breastmilk | 9.76 ± 0.438 | 8.63 ± 0.519 | 12.48 ± 0.958 | 8.511 ± 1.165 | 18.0 ± 3.928 | |
Average Sleep Duration (h/d) | 8.61 ± 0.078 | 8.86 ± 0.086 † | 7.75 ± 0.200 | 8.99 ± 0.206 † | 9.05 ± 0.273 | 0.0001 |
TCSQ Sleep Score | 6.34 ± 0.205 | 6.583 ± 0.246 | 6.011 ± 0.4621 | 5.231 ± 0.554 | 8.00 ± 3.386 | |
Met Sleep Recommendations Ƒ | 0.0136 | |||||
Yes | 343 (40.35%) | 240 (43.09%) | 63 (30.58%) | 35 (43.75%) | 5 (50%) | |
No | 507 (59.65%) | 317 (56.91%) | 143 (69.42%) | 45 (65.25%) | 5 (50%) | |
Average Screen-time (hr/d) | 5.29 ± 0.132 | 5.13 ± 0.154 § | 5.45 ± 0.308 | 6.24 ± 0.425 | 3.59 ± 0.550 | |
Met Screen-time Recommendations Ω | 0.0069 | |||||
Yes | 124 (16.89%) | 82 (16.73%) | 39 (22.54%) | 3 (4.61%) | 0 (0%) | |
No | 610 (83.11%) | 408 (83.27%) | 134 (77.46%) | 62 (95.39%) | 6 (100%) | |
Height (cm) | 110.56 ± 0.46 | 109.07 ± 0.59 | 111.31 ± 1.71 | 112.98 ± 1.22 | 114.75 ± 5.03 | |
Weight (kg) | 21.05 ± 0.25 | 20.78 ± 0.31 | 21.50 ± 0.54 | 21.55 ± 0.72 | 22.4 ± 2.44 | |
Body Mass Index (kg/m2) | 16.84 ± 0.11 | 16.77 ± 0.14 | 17.09 ± 0.43 | 16.65 ± 0.27 | 16.42 ± 0.61 | |
BMI z-score | 0.402 ± 0.039 | 0.352 ± 0.048 † | 0.544 ± 0.08 | 0.395 ± 0.132 | 0.189 ± 0.284 | 0.0397 |
BMI Categories ß | ||||||
Underweight | 25 (2.96%) | 18 (32.91%) | 4 (1.93%) | 3 (3.75%) | 0 (0%) | 0.6945 |
Healthy weight | 595 (70.49%) | 392 (71.66%) | 144 (69.56%) | 51 (63.75%) | 8 (80%) | 0.4523 |
Overweight, % (≥85th%ile) | 113 (13.39%) | 77 (14.08%) | 21 (10.14%) | 14 (17.50%) | 1 (10%) | 0.3385 |
Obesity, % (≥95th%ile) | 111 (13.15%) | 60 (10.97%) | 38 (18.36%) | 12 (15.0%) | 1 (10%) | 0.0314 |
OWOB by Age | ||||||
2–5 years old | 107 (23.94%) | 59 (20.85%) | 32 (26.89%) | 16 (39.02%) | 0 (0%) | 0.0378 |
6–8 years old | 117 (29.47%) | 78 (29.54%) | 27 (30.68%) | 10 (25.64%) | 2 (33.33%) | 0.9441 |
Waist Circumference (cm) | 55.07 ± 0.30 | 54.76 ± 0.38 | 55.44 ± 0.58 | 56.104 ± 0.95 | 55.64 ± 2.50 | |
Abdominal Obesity € | 0.6782 | |||||
Yes | 76 (8.94%) | 48 (8.77%) | 17 (7.98%) | 10 (12.50%) | 1 (10%) | |
No | 774 (91.06%) | 499 (91.23%) | 196 (92.02%) | 70 (87.5%) | 9 (90%) | |
Consumed SSB? | 0.0001 | |||||
Yes | 497 (74.74%) | 361 (81.49%) | 95 (61.29%) | 36 (59.01%) | 5 (50%) | |
No | 168 (25.26%) | 82 (18.51%) | 60 (38.71%) | 25 (40.99%) | 5 (50%) | |
Beverage Consumption ‡,¶ | ||||||
Water (c/d) | 1.47 ± 0.048 | 1.306 ± 0.45 | 1.298 ± 0.66 | 1.401 ± 0.105 | 1.522 ± 0.429 | |
Milk (c/d) | 1.241 ± 0.024 | 1.280 ± 0.029 †,§ | 1.028 ± 0.045 | 1.454 ± 0.081 † | 1.660 ± 0.139 | |
Sugar-sweet drinks (c/d) | 0.845 ± 0.029 | 0.958 ± 0.036 †,§,‡ | 0.560 ± 0.050 Ø | 0.727 ± 0.101 | 1.095 ± 0.269 | |
Fruit Consumption ‡ (c/d) | 0.882 ± 0.021 | 0.88 ± 0.025 | 0.846 ± 0.045 | 0.956 ± 0.080 | 1.153 ± 0.240 | |
Vegetable Consumption ‡,¶ (c/d) | 0.609 ± 0.013 | 0.648 ± 0.015 | 0.472 ± 0.026 | 0.651 ± 0.041 | 0.850 ± 0.139 | |
Met Recommendation for: | ||||||
Fruit Intake | 257 (41.35%) | 182 (41.08%) | 63 (40.65%) | 27 (44.26%) | 3 (50%) | 0.9312 |
Vegetable Intake | 6 (0.90%) | 5 (1.13%) | 1 (0.65%) | 0 (0%) | 0 (0%) | 0.8064 |
Parent/Caregiver/Household | ||||||
Annual Family Income Level | 0.0001 | |||||
<$20,000 | 348 (57.91%) | 220 (54.18%) | 92 (82.88%) | 32 (43.24%) | 4 (40%) | |
$20,000–$34,999 | 182 (14.81%) | 59 (14.53%) | 9 (8.11%) | 17 (22.97%) | 4 (40%) | |
$35,000–$59,999 | 93 (15.47%) | 71 (17.49%) | 5 (4.51%) | 17 (22.97%) | 0 (0%) | |
>$60,000 | 71 (11.81%) | 56 (13.80%) | 5 (7.20%) | 8 (10.82%) | 2 (20%) | |
Receiving any Food Assistance | 0.0001 | |||||
Yes | 676 (80.38%) | 447 (81.57%) | 176 (86.70%) | 47 (58.75%) | 6 (60%) | |
No | 165 (19.62%) | 101 (18.43%) | 27 (13.30%) | 33 (41.25%) | 4 (40%) | |
Type of Food Assistance | ||||||
SNAP ∂ | 585 (67.85%) | 401 (71.61%) | 146 (69.19%) | 33 (40.74%) | 5 (50%) | 0.0001 |
Local Food Bank | 101 (11.72%) | 69 (12.32%) | 28 (13.27%) | 4 (4.94%) | 0 (0%) | 0.1319 |
WIC ∞ | 274 (31.79%) | 162 (28.93%) | 86 (40.76%) | 22 (27.16%) | 4 (40%) | 0.0114 |
Free School Lunch/Breakfast | 248 (28.77%) | 202 (36.07%) | 33 (15.64%) | 10 (12.35%) | 3 (30%) | 0.0001 |
Food Insecurity δ | 0.0001 | |||||
Always/most times | 127 (16.82%) | 86 (17.20%) | 32 (18.71%) | 7 (9.46%) | 2 (20%) | |
Sometimes | 262 (34.70%) | 128 (25.6%) | 96 (56.16%) | 35 (47.29%) | 3 (30%) | |
Seldom/never | 366 (48.48%) | 286 (57.20%) | 43 (25.15%) | 32 (43.24%) | 5 (50%) | |
Parent/Caregiver Education | 0.0001 | |||||
<12th Grade | 281 (32.48%) | 184 (32.80%) | 79 (37.08%) | 17 (20.98%) | 1 (10%) | |
12th Grade/GED | 351 (40.58%) | 237 (42.24%) | 97 (45.54%) | 13 (16.05%) | 4 (40%) | |
Some college or higher | 233 (26.94%) | 140 (24.96%) | 37 (17.38%) | 32 (62.97%) | 5 (50%) | |
Parent Marital Status | 0.0001 | |||||
Married | 340 (39.31%) | 190 (33.89%) | 90 (42.25%) | 55 (67.90%) | 5 (50%) | |
Not Married | 525 (60.69%) | 371 (66.13%) | 123 (57.75%) | 26 (32.10%) | 5 (50%) | |
Number Children in Household | 4.19 ± 0.077 | 4.29 ± 0.096 § | 4.35 ± 0.164 § | 3.14 ± 0.151 | 3.4 ± 0.306 | 0.0001 |
Household Size | 0.008 | |||||
1–2 children | 205 (23.78%) | 127 (22.72%) | 48 (22.64%) | 29 (35.80%) | 1 (1%) | |
3–4 children | 341 (39.56%) | 220 (39.36%) | 75 (35.38%) | 39 (48.15%) | 7 (70%) | |
5 or more children | 316 (36.66%) | 212 (37.92%) | 89 (41.98%) | 13 (16.05%) | 2 (20%) | |
Acculturation γ | 0.0565 | |||||
Integrated | 572 (79.89%) | 388 (80.15%) | 123 (75.00%) | 55 (88.71%) | 6 (100%) | |
Traditional | 101 (14.11%) | 74 (15.29%) | 24 (14.63%) | 3 (4.84%) | 0 | |
Assimilated | 17 (2.37%) | 7 (1.45%) | 7 (4.27%) | 3 (4.83%) | 0 | |
Marginalized | 26 (3.63%) | 15 (3.10%) | 10 (6.10%) | 1 (1.61%) | 0 |
Participant & Family Characteristics | Total Mean ± SE or n(%) | Healthy Weight * Mean ± SE or n (%) | OWOB * Mean ± SE or n (%) | p Value |
---|---|---|---|---|
Age | 0.069 | |||
2–5 years old | 437 (53.2%) | 329 (55.1%) | 108 (48%) | |
6–8 years old | 385 (46.8%) | 268 (44.9%) | 117 (52%) | |
Sex | 0.917 | |||
Boys | 425 (51.7%) | 308 (51.6%) | 117 (52.0%) | |
Girls | 397 (48.3%) | 289 (48.4%) | 108 (48.0%) | |
Child Ethnicity | 0.455 | |||
CHamoru | 528 (64.55%) | 392 (65.88%) | 137 (61.16%) | |
Other Micronesians | 203 (24.82%) | 144 (24.20%) | 59 (26.34%) | |
Filipino | 77 (9.41%) | 51 (8.57%) | 26 (11.61%) | |
Other | 10 (1.22%) | 8 (1.34%) | 2 (0.89%) | |
Annual Family Income Level | 0.473 | |||
<$20,000 | 331 (57.6%) | 234 (56.9%) | 97 (59.1%) | |
$20,000–$34,999 | 86 (15%) | 63 (15.3%) | 23 (14%) | |
$35,000–$59,999 | 89 (15.5%) | 60 (14.6%) | 29 (17.7%) | |
>$60,000 | 69 (12%) | 54 (13.1%) | 15 (9.1%) | |
Receiving any Food Assistance | 0.768 | |||
Yes | 645 (78.5%) | 470 (78.7%) | 175 (77.8) | |
No | 177 (21.5%) | 127 (21.3%) | 50 (22.2%) | |
Type of Food Assistance | ||||
SNAP | 556 (67.9%) | 408 (68.7%) | 148 (65.8%) | 0.426 |
Local Food Bank | 99 (12.15%) | 72 (72.7%) | 27 (27.3%) | 0.977 |
WIC | 258 (31.5%) | 196 (33.0%) | 62 (27.6%) | 0.135 |
Free School Lunch/Breakfast | 238 (29.1%) | 169 (28.5%) | 69 (30.7%) | 0.533 |
Food Insecurity | 0.566 | |||
Always/most times | 120 (16.7%) | 88 (16.8%) | 32 (16.3%) | |
Sometimes | 253 (35.2%) | 178 (34%) | 75 (38.3%) | |
Seldom/never | 346 (48.1%) | 257 (49.1%) | 89 (45.4%) | |
Parent/Caregiver Education | 0.052 | |||
<12th Grade | 269 (32.7%) | 207 (34.7%) | 62 (27.6%) | |
12th Grade/GED | 331 (40.3%) | 241 (40.4%) | 90 (40%) | |
Some college or higher | 222 (27%%) | 149 (25%) | 73 (32.4%) | |
Parent Marital Status | 0.06 | |||
Married | 326 (39.7%) | 225 (37.7%) | 101 (44.9%) | |
Not Married | 496 (60.3%) | 372 (62.3%) | 124 (55.1%) | |
Number Children in Household | 4.19 ± 0.077 | 4.19 ± 0.094 | 4.22 ± 0.152 | 0.838 |
Household Size | 0.491 | |||
1–2 children | 197 (24.1%) | 145 (24.4%) | 52 (23.1%) | |
3–4 children | 319 (38.9%) | 224 (37.7%) | 95 (42.2%) | |
5 or more children | 303 (37%) | 225 (37.9%) | 78 (34.7%) | |
Birthplace | 0.0070 | |||
Guam | 685 (84.46%) | 505 (85.45%) | 180 (81.45%) | |
U.S. Mainland | 52 (6.41%) | 37 (6.26%) | 15 (6.79%) | |
Saipan, CNMI | 31 (3.82%) | 20 (3.38%) | 13 (5.88%) | |
Other Islands in Micronesia | 25 (3.08%) | 21 (3.55%) | 4 (1.81%) | |
Philippines | 13 (1.60%) | 8 (1.35%) | 5 (2.26%) | |
Other | 4 (0.49%) | 1 (0.17%) | 4 (1.82%) | |
Acculturation | 0.2913 | |||
Integrated | 542 (80.30%) | 394 (79.60%) | 148 (82.22%) | |
Traditional | 94 (13.78%) | 72 (14.54%) | 21 (12.14%) | |
Assimilated | 17 (2.52%) | 10 (2.02%) | 7 (3.89%) | |
Marginalized | 23 (3.41%) | 19 (3.84%) | 4 (2.22%) | |
Ever Breastfed? | 0.2140 | |||
Yes | 529 (64.59%) | 373 (66.13%) | 156 (70.59%) | |
No | 256 (35.41%) | 191 (33.87%) | 65 (29.41%) | |
Exclusively Breastfed? | 0.5655 | |||
Yes | 97 (13.13%) | 68 (12.69%) | 29 (14.29%) | |
No | 642 (86.87%) | 468 (87.13%) | 174 (85.71%) | |
Child age (mos) when weaned from breastmilk | 9.76 ± 0.438 (n = 495) | 10.22 ± 0.542 | 9.23 ± 0.844 | 0.3248 |
Child fed both breastmilk & infant formula | 0.5135 | |||
Yes | 421 (54.39%) | 300 (53.67%) | 121(56.28%) | |
No | 353 (45.61%) | 259 (44.33%) | 94 (43.72%) | |
Average Sleep Duration (h/d) | 8.62 ± 0.08 | 8.64 ± 0.096 | 8.59 ± 0.142 | 0.7122 |
TCSQ Sleep Score | 6.34 ± 0.205 | 6.55 ± 0.257 | 5.59 ± 0.341 | 0.0421 |
Met Sleep Recommendations | 0.725 | |||
Yes | 327 (40.4%) | 236 (40%) | 91 (41.4%) | |
No | 483 (59.6%) | 354 (60%) | 129 (58.6%) | |
Average Screen-time (h/d) | 5.26 ± 0.132 | 5.15 ± 0.150 | 5.55 ± 0.270 | 0.1743 |
Met Screen-time Recommendations | 0.444 | |||
Yes | 117 (16.8%) | 82 (16.2%) | 35 (18.6%) | |
No | 578 (83.2%) | 425 (83.8%) | 153 (81.4%) | |
Height (cm) | 110.52 ± 0.47 | 108.71 ± 0.528 | 115.34 ± 0.912 | 0.0001 |
Weight (kg) | 21.26 ± 0.26 | 18.77 ± 0.185 | 27.91 ± 0.635 | 0.0001 |
BMI, kg/m2 | 16.95 ± 0.11 | 15.64 ± 0.038 | 20.45 ± 0.280 | 0.0001 |
BMI z-score | 0.485 ± 0.036 | 0.007 ± 0.026 | 1.79 ± 0.045 | 0.0001 |
Waist Circumference (cm) | 55.07 ± 0.457 | 51.93 ±0.188 | 64.40 ± 0.707 | 0.0001 |
Abdominal Obesity | 0.0001 | |||
Yes | 75 (9.2%) | 0 (0%) | 75 (33.60%) | |
No | 741 (90.8%) | 591 (100%) | 148 (66.40%) | |
Beverage Consumption ‡ | ||||
Water (c/d) | 1.31 ± 0.035 | 1.32 ± 0.043 | 1.28 ± 0.070 | 0.5793 |
Milk (c/d) | 1.24 ± 0.24 | 1.25 ± 0.028 | 1.21 ± 0.048 | 0.5994 |
Sugar-sweetened drinks (c/d) | 0.84 ± 0.03 | 0.81 ± 0.34 | 0.93 ± 0.061 | 0.0676 |
Vegetable Intake ‡ (c/d) | 0.61 ± 0.013 | 0.60 ± 0.015 | 0.63 ± 0.027 | 0.2535 |
Fruit Intake ‡ (c/d) | 0.88 ± 0.021 | 0.87 ± 0.025 | 0.89 ± 0.040 | 0.7324 |
Met Recommendation for: | ||||
Fruit Intake | 257 (41.35%) | 185 (39.96%) | 79 (46.20%) | 0.1571 |
Vegetable Intake | 6 (0.90%) | 4 (0.86%) | 2 (1.17%) | 0.7242 |
Variable | n | % OWOB † (95% CI) | Adjusted OR †† (95% CI) |
---|---|---|---|
Overall | 822 | 27.4 (24.3–30.4) | |
Child Characteristics | |||
Sex | |||
Males | 425 | 27.5 (23.3–31.8) | Referent |
Females | 397 | 27.2 (22.8–31.6) | 1.001 (0.734–1.366) |
Age | |||
2–5 years | 437 | 24.7 (20.7–28.8) | Referent |
6–8 years | 385 | 30.4 (25.8–35.0) | 1.337 (0.982–1.821) |
Ethnicity | |||
CHamoru | 531 | 26.0 (22.3–29.7) | Referent |
Other Micronesians | 204 | 28.9 (22.7–35.2) | 1.186 (0.824–1.706) |
Filipino | 77 | 33.8 (23.0–44.6) | 1.454 (0.870–2.430) |
Other | 10 | 20.0 (−10.2–50.2) | 0.693 (0.144–3.329) |
Child was breastfed? | |||
Yes | 530 | 29.4 (25.5–33.3) | 1.212 (0.861–1.708) |
No | 258 | 25.6 (20.2–30.9) | Referent |
Child met sleep standard for his/her age group? | |||
Yes | 327 | 27.8 (23.0–32.7) | 0.994 (0.717–1.378) |
No | 483 | 26.7 (22.8–30.7) | Referent |
Child met recommendation for screen-time of ≤ 2 h/day? | |||
Yes | 117 | 29.9 (21.5–38.3) | 1.184 (0.757–1.851) |
No | 578 | 26.5 (22.9–30.1) | Referent |
Child met recommendation for vegetable intake for his/her age group? | |||
Yes | 6 | 33.3 (−20.9–87.5) | 1.342 (0.236–7.649) |
No | 628 | 26.9 (23.4–30.4) | Referent |
Child met recommendation for fruit intake for his/her age group? | |||
Yes | 264 | 29.9 (24.4–35.5) | 1.274 (0.89–1.823) |
No | 370 | 24.9 (20.4–29.3) | Referent |
SSB beverage intake ‡ (cups/day) | |||
(zero intake—referent) | 160 | 21.3 (14.8–27.7) | Referent |
Tertile 1 (≤0.42) | 54 | 33.3 (20.4–46.3) | 2.064 (1.024–4.160) |
Tertile 2 (0.42–1.09) | 208 | 26.4 (20.4–32.5) | 1.495 (0.90–2.485) |
Tertile 3 (≥1.09) | 212 | 30.2 (24.0–36.4) | 1.824 (1.106–3.007) |
p-value for trend | 0.022 | ||
Water beverage intake ‡ (cups/day) | |||
(zero intake—referent) | 26 | 30.8 (11.8–49.8) | Referent |
Tertile 1 (≤0.92) | 195 | 26.2 (19.9–32.4) | 0.827 (0.333–2.057) |
Tertile 2 (0.92–1.62) | 201 | 28.4 (22.1–34.6) | 0.965 (0.388–2.401) |
Tertile 3 (≥1.62) | 212 | 25.9 (20.0–31.9) | 0.819 (0.330–2.033) |
p-value for trend | 0.597 | ||
Parent/Caregiver/Household Characteristics | |||
Education Level | |||
Less than 12th grade (use this as reference) | 269 | 23.1 (18.0–28.1) | Referent |
12th grade/GED or higher | 553 | 29.5 (25.7–33.3) | 1.415 (1.004–1.994) |
Marital Status | |||
Married | 326 | 31.0 (25.9–36.0) | Referent |
Not married | 496 | 25.0 (21.2–28.8) | 0.776 (0.564–1.067) |
Annual household income | |||
<$20,000 | 331 | 29.3 (24.4–34.2) | Referent |
$20,000–$34,999 | 86 | 26.7 (17.2–36.3) | 0.867 (0.501–1.502) |
$35,000–$59,999 | 89 | 32.6 (22.7–42.5) | 1.121 (0.664–1.892) |
$60,000+ | 69 | 21.7 (11.8–31.7) | 0.600 (0.315–1.143) |
Food Insecurity | |||
Yes | 120 | 26.7 (18.6–34.7) | 0.982 (0.627–1.539) |
No | 599 | 27.4 (23.8–31.0) | Referent |
Receiving any food assistance | |||
Yes | 645 | 27.1 (23.4–30.6) | 1.027 (0.699–1.509) |
No | 177 | 28.3 (21.6–35.0) | Referent |
Number of children in household | |||
1–2 children | 197 | 26.4 (20.2–32.6) | Referent |
3–4 children | 319 | 29.8 (24.7–34.8) | 1.18 (0.789–1.766) |
5 or more children | 303 | 25.7 (20.8–30.7) | 0.948 (0.622–1.446) |
Acculturation—Family considers themselves ‘integrated’ into culture | |||
Yes | 545 | 27.3 (23.6–31.1) | 1.162 (0.747–1.81) |
No | 134 | 24.6 (17.2–32.0) | Referent |
© 2020 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 (http://creativecommons.org/licenses/by/4.0/).
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Leon Guerrero, R.T.; Barber, L.R.; Aflague, T.F.; Paulino, Y.C.; Hattori-Uchima, M.P.; Acosta, M.; Wilkens, L.R.; Novotny, R. Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam. Nutrients 2020, 12, 2527. https://doi.org/10.3390/nu12092527
Leon Guerrero RT, Barber LR, Aflague TF, Paulino YC, Hattori-Uchima MP, Acosta M, Wilkens LR, Novotny R. Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam. Nutrients. 2020; 12(9):2527. https://doi.org/10.3390/nu12092527
Chicago/Turabian StyleLeon Guerrero, Rachael T., L. Robert Barber, Tanisha F. Aflague, Yvette C. Paulino, Margaret P. Hattori-Uchima, Mark Acosta, Lynne R. Wilkens, and Rachel Novotny. 2020. "Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam" Nutrients 12, no. 9: 2527. https://doi.org/10.3390/nu12092527
APA StyleLeon Guerrero, R. T., Barber, L. R., Aflague, T. F., Paulino, Y. C., Hattori-Uchima, M. P., Acosta, M., Wilkens, L. R., & Novotny, R. (2020). Prevalence and Predictors of Overweight and Obesity among Young Children in the Children’s Healthy Living Study on Guam. Nutrients, 12(9), 2527. https://doi.org/10.3390/nu12092527