Systems Nutrology of Adolescents with Divergence between Measured and Perceived Weight Uncovers a Distinctive Profile Defined by Inverse Relationships of Food Consumption
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Assessment of Diet
2.3. Evaluation of Anthropometric Status
2.4. Self-Perception Assessment and Divergence between Measured and Perceived Weight
2.5. Statistical Analysis
2.6. Systems Nutrology Analysis
2.7. Ethics Statement
3. Results
3.1. Characteristics of Participants
3.2. Association between Anthropometric Status and Divergence between Measured and Perceived Weight
3.3. Dietary Patterns
3.4. Network Analysis of Food Consumption
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Cash, T.F. Body image: Past, present, and future. Body Image 2004, 1, 1–5. [Google Scholar] [CrossRef]
- Millstein, R.A.; Carlson, S.A.; Fulton, J.E.; Galuska, D.A.; Zhang, J.; Blanck, H.M.; Ainsworth, B.E. Relationships between body size satisfaction and weight control practices among US adults. Medscape J. Med. 2008, 10, 119. [Google Scholar] [PubMed]
- Mintem, G.C.; Horta, B.L.; Domingues, M.R.; Gigante, D.P. Body size dissatisfaction among young adults from the 1982 Pelotas birth cohort. Eur. J. Clin. Nutr. 2015, 69, 55–61. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Casey, B.J.; Jones, R.M.; Levita, L.; Libby, V.; Pattwell, S.S.; Ruberry, E.J.; Soliman, F.; Somerville, L.H. The storm and stress of adolescence: Insights from human imaging and mouse genetics. Dev. Psychobiol. 2010, 52, 225–235. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Santos, E.; Tassitano, R.M.; Nascimento, W.; Petribú, M.; Cabral, P.C. Body satisfaction and associated factors among high school students. Rev. Paul. Pediatr. 2011, 29, 214–223. [Google Scholar] [CrossRef] [Green Version]
- Nahhas, M.A.; Asamoah, F.; Mullen, S.; Nwaru, B.I.; Nurmatov, U. Epidemiology of overweight and obesity in early childhood in the Gulf Cooperation Council countries: A systematic review and meta-analysis protocol. BMJ Open 2018, 8, e019363. [Google Scholar] [CrossRef]
- Styne, D.M.; Arslanian, S.A.; Connor, E.L.; Farooqi, I.S.; Murad, M.H.; Silverstein, J.H.; Yanovski, J.A. Pediatric Obesity-Assessment, Treatment, and Prevention: An Endocrine Society Clinical Practice Guideline. J. Clin. Endocrinol. Metab. 2017, 102, 709–757. [Google Scholar] [CrossRef]
- Moreno, L.A.; Rodriguez, G.; Fleta, J.; Bueno-Lozano, M.; Lazaro, A.; Bueno, G. Trends of dietary habits in adolescents. Crit. Rev. Food Sci. Nutr. 2010, 50, 106–112. [Google Scholar] [CrossRef]
- Cuypers, K.; Kvaloy, K.; Bratberg, G.; Midthjell, K.; Holmen, J.; Holmen, T.L. Being Normal Weight but Feeling Overweight in Adolescence May Affect Weight Development into Young Adulthood-An 11-Year Followup: The HUNT Study, Norway. J. Obes. 2012, 2012, 601872. [Google Scholar] [CrossRef]
- De Santana, M.L.; Assis, A.M.; Silva, R.D.C.R.; Raich, R.M.; Machado, M.E.; Pinto Ede, J.; de Moraes, L.T.; Ribeiro Hda, C. Risk Factors for Adopting Extreme Weight-Control Behaviors among Public School Adolescents in Salvador, Brazil: A Case-Control Study. J. Am. Coll. Nutr. 2016, 35, 113–117. [Google Scholar] [CrossRef]
- Claro, R.M.; Santos, M.A.S.; Oliveira-Campos, M. Body image and extreme attitudes toward weight in Brazilian schoolchildren (PeNSE 2012). Rev. Bras. Epidemiol. 2014, 17 (Suppl. 1), 146–157. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Garcia, G.C.B.; Gambardella, A.M.D.; Frutuoso, M.F.P. Nutritional status and food consumption of adolescents registered at a center of youth from the city of São Paulo, Brazil. Rev. Nutr. 2003, 16, 41–50. [Google Scholar] [CrossRef] [Green Version]
- Araújo, C.L.; Dumith, S.C.; Menezes, A.M.B.; Hallal, P.C. Measured weight, self-perceived weight, and associated factors in adolescents. Pan Am. J. Public Health 2010, 27, 360–367. [Google Scholar] [CrossRef] [Green Version]
- Andrade, V.M.B.; de Santana, M.L.P.; Fukutani, K.F.; Queiroz, A.T.L.; Arriaga, M.B.; Conceicao-Machado, M.E.P.; Silva, R.C.R.; Andrade, B.B. Multidimensional Analysis of Food Consumption Reveals a Unique Dietary Profile Associated with Overweight and Obesity in Adolescents. Nutrients 2019, 11, 1946. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Breitling, R. What is systems biology? Front. Physiol. 2010, 1, 159. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- WHO. Physical status: The use and interpretation of anthropometry. In Report of a WHO Expert Committee; WHO: Geneva, Switzerland, 1995. [Google Scholar]
- Tanner, J.M. Growth at Adolescence, 2nd ed.; Blackwell: Oxford, UK, 1962. [Google Scholar]
- Mascarenhas, J.M.; Silva, R.C.; Machado, M.E.; Santos, C.A.; Marchioni, D.M.; Barreto, M.L. Validation of a food frequency questionnaire designed for adolescents in Salvador, Bahia, Brazil. Rev. Nutr. 2016, 29, 163–171. [Google Scholar] [CrossRef] [Green Version]
- WHO. Growth Reference Data for 5–19 Years, WHO Reference 2007. Available online: http://www.who.int/growthref/en (accessed on 4 May 2020).
- Saleem, M.D.; Ahmed, G.; Mulla, J.; Haider, S.S.; Abbas, M. Weight misperception amongst youth of a developing country: Pakistan -a cross-sectional study. BMC Public Health 2013, 13, 707. [Google Scholar] [CrossRef] [Green Version]
- Shivakoti, R.; Dalli, J.; Kadam, D.; Gaikwad, S.; Barthwal, M.; Colas, R.A.; Mazzacuva, F.; Lokhande, R.; Dharmshale, S.; Bharadwaj, R.; et al. Lipid mediators of inflammation and Resolution in individuals with tuberculosis and tuberculosis-Diabetes. Prostaglandins Lipid Mediat. 2020, 147, 106398. [Google Scholar] [CrossRef]
- Webb, D.J. The statistics of relative abundance and diversity. J. Theor. Biol. 1974, 43, 277–291. [Google Scholar] [CrossRef]
- Reedy, J.; Subar, A.F.; George, S.M.; Krebs-Smith, S.M. Extending Methods in Dietary Patterns Research. Nutrients 2018, 10, 571. [Google Scholar] [CrossRef] [Green Version]
- Hearty, A.P.; Gibney, M.J. Dietary patterns in Irish adolescents: A comparison of cluster and principal component analyses. Public Health Nutr. 2013, 16, 848–857. [Google Scholar] [CrossRef] [PubMed]
- Francisco, P.M.; Donalisio, M.R.; Barros, M.B.; Cesar, C.L.; Carandina, L.; Goldbaum, M. Association measures in cross-sectional studies with complex sampling: Odds ratio and prevalence ratio. Rev. Bras. Epidemiol. 2008, 11, 347–355. [Google Scholar] [CrossRef] [Green Version]
- Andrade, B.B.; Singh, A.; Narendran, G.; Schechter, M.E.; Nayak, K.; Subramanian, S.; Anbalagan, S.; Jensen, S.M.; Porter, B.O.; Antonelli, L.R.; et al. Mycobacterial antigen driven activation of CD14++CD16− monocytes is a predictor of tuberculosis-associated immune reconstitution inflammatory syndrome. PLoS Pathog. 2014, 10, e1004433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mendonca, V.R.; Queiroz, A.T.; Lopes, F.M.; Andrade, B.B.; Barral-Netto, M. Networking the host immune response in Plasmodium vivax malaria. Malar. J. 2013, 12, 69. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bibiloni Mdel, M.; Pich, J.; Pons, A.; Tur, J.A. Body image and eating patterns among adolescents. BMC Public Health 2013, 13, 1104. [Google Scholar] [CrossRef] [Green Version]
- Damasceno, V.O.; Vianna, V.R.; Vianna, J.M.; Lacio, M.; Lima, J.R.P.; Novaes, J.S. Body image and ideal body. Rev. Bras. Ciênc. Mov. 2008, 14, 81–94. [Google Scholar] [CrossRef]
- Farhat, T.; Iannotti, R.J.; Summersett-Ringgold, F. Weight, Weight Perceptions, and Health-Related Quality of Life among a National Sample of US Girls. J. Dev. Behav. Pediatr. 2015, 36, 313–323. [Google Scholar] [CrossRef]
- Kim, S.; So, W.-Y. Prevalence and sociodemographic trends of weight misperception in Korean adolescents. BMC Public Health 2014, 14, 452. [Google Scholar] [CrossRef] [Green Version]
- Bodde, A.E.; Beebe, T.J.; Chen, L.P.; Jenkins, S.; Perez-Vergara, K.; Finney Rutten, L.J.; Ziegenfuss, J.Y. Misperceptions of weight status among adolescents: Sociodemographic and behavioral correlates. Patient Relat. Outcome Meas. 2014, 5, 163–171. [Google Scholar] [CrossRef] [Green Version]
- Buscemi, S.; Marventano, S.; Castellano, S.; Nolfo, F.; Rametta, S.; Giorgianni, G.; Matalone, M.; Marranzano, M.; Mistretta, A. Role of anthropometric factors, self-perception, and diet on weight misperception among young adolescents: A cross-sectional study. Eat. Weight Disord. 2018, 23, 107–115. [Google Scholar] [CrossRef]
- Boa-Sorte, N.; Neri, L.A.; Leite, M.; Brito, S.M.; Meirelles, A.R.; Luduvice, F.; Santos, J.P.; Viveiros, M.R.; Ribeiro, H.J.J.P. Maternal perceptions and self-perception of the nutritional status of children and adolescents from private schools. J. Pediatr. 2007, 83, 349–356. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kilpatrick, M.; Ohannessian, C.; Bartholomew, J.B. Adolescent weight management and perceptions: An analysis of the National Longitudinal Study of Adolescent Health. J. Sch. Health 1999, 69, 148–152. [Google Scholar] [CrossRef] [PubMed]
- Sirirassamee, T.; Phoolsawat, S.; Limkhunthammo, S. Relationship between body weight perception and weight-related behaviours. J. Int. Med Res. 2018, 46, 3796–3808. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Aerts, D.; Madeira, R.R.; Zart, V.B. Imagem corporal de adolescentes escolares em Gravataí-RS. Epidemiol. Serv. Saúde 2010, 19, 283–291. [Google Scholar] [CrossRef]
- Pasch, K.E.; Klein, E.G.; Laska, M.N.; Velazquez, C.E.; Moe, S.G.; Lytle, L.A. Weight misperception and health risk behaviors among early adolescents. Am. J. Health Behav. 2011, 35, 797–806. [Google Scholar] [CrossRef] [Green Version]
- Araújo, J.; Teixeira, J.; Gaio, A.R.; Lopes, C.; Ramos, E. Dietary patterns among 13-y-old Portuguese adolescents. Nutrition 2015, 31, 148–154. [Google Scholar] [CrossRef] [Green Version]
- Santos, J.S.; Costa, M.C.O.; Nascimento Sobrinho, C.L.; Silva, M.C.; Souza, K.E.; Melo, B.O. Anthropometric profile and food intake of adolescents in Teixeira de Freitas—Bahia, Brazil. Rev. Nutr. 2005, 18, 623–632. [Google Scholar] [CrossRef] [Green Version]
- Schwedhelm, C.; Iqbal, K.; Knuppel, S.; Schwingshackl, L.; Boeing, H. Contribution to the understanding of how principal component analysis-derived dietary patterns emerge from habitual data on food consumption. Am. J. Clin. Nutr. 2018, 107, 227–235. [Google Scholar] [CrossRef] [Green Version]
- Prada-Medina, C.A.; Fukutani, K.F.; Pavan Kumar, N.; Gil-Santana, L.; Babu, S.; Lichtenstein, F.; West, K.; Sivakumar, S.; Menon, P.A.; Viswanathan, V.; et al. Systems Immunology of Diabetes-Tuberculosis Comorbidity Reveals Signatures of Disease Complications. Sci. Rep. 2017, 7, 1999. [Google Scholar] [CrossRef]
- Qin, T.T.; Xiong, H.G.; Yan, M.M.; Sun, T.; Qian, L.; Yin, P. Body Weight Misperception and Weight Disorders among Chinese Children and Adolescents: A Latent Class Analysis. Curr. Med. Sci. 2019, 39, 852–862. [Google Scholar] [CrossRef]
Characteristic | Total n (%) | Agreed n (%) | Underestimated n (%) | Overestimated n (%) | p-Value |
---|---|---|---|---|---|
N | 1496 | 1022 | 294 | 180 | |
Age-years median (IQR) | 14.3 (13.2–15.5) | 14.3 (13.2–15.3) | 14.5 (13.2–15.6) | 14.3 (13.4–15.7) | 0.4383 |
Sex | <0.001 | ||||
Female | 854 (57.1) | 562 (55) | 153 (52) | 139 (77.2) | |
Male | 642 (42.9) | 460 (45) | 141 (48) | 41 (22.8) | |
Socioeconomic status * | 0.1347 | ||||
Good economic condition | 727 (48.6) | 506 (49.5) | 129 (43.9) | 92 (51.1) | |
Poor economic condition | 721 (48.2) | 479 (46.9) | 158 (53.7) | 84 (46.7) | |
BMI-Kg/m2 median (IQR) | 18.9 (17.2–21.0) | 19.0 (17.2–20.8) | 18.4 (17.0–21.6) | 19.6 (17.1–21.3) | 0.7086 |
Pubertal development * | 0.1828 | ||||
Pre-pubertal | 126 (8.4) | 87 (8.5) | 31 (10.5) | 8 (4.4) | |
Pubertal | 325 (21.7) | 228 (22.3) | 57 (19.4) | 40 (22.2) | |
Post-pubertal | 1040 (69.6) | 704 (68.9) | 205 (69.7) | 131 (72.8) |
Food or Food Group | Total | Agreed | Underestimated | Overestimated | p-Value |
---|---|---|---|---|---|
Sugar and sweets | 243.3 (130.2–436.1) | 242 (134.4–426.5) | 244.2 (122.6–485.2) | 245.7 (132.7–420.5) | 0.6203 |
Sweetened beverages | 480.4 (200.0–915.3) | 480 (213.3–880) | 533.4 (193.3–960.1) | 466.7 (160.1–946.9) | 0.6436 |
Processed meat products | 11.0 (5.5–33.0) | 10.99 (5.5–33) | 11 (5.5–33) | 11 (5.5–32.9) | 0.6126 |
Fast food | 170.4 (80.3–352.7) | 165.4 (80.32–339.2) | 202.5 (83–419.8) | 157 (79.5–323.9) | 0.1092 |
Typical Brazilian dishes | 97.3 (49.3–239.8) | 96.6 (50–238.3) | 112.6 (51.7–246.7) | 97.2 (38.3–225.3) | 0.2162 |
Oils | 29.3 (11.5–51.1) | 29.3 (11.47–50.3) | 29.7 (13.9–55) | 25.7 (10.7–44.7) | 0.0995 |
Milk and dairy | 166.4 (70.9–337.6) | 167.6 (73.7–335.9) | 175.7 (72.9–386.9) | 154.7 (52.7–313.1) | 0.2092 |
Meat | 122.7 (64.0–236.7) | 117.7 (62.7–225.3) | 137.3 (69.3–271.3) | 129.3 (62–240) | 0.0711 |
Rice and cereals | 460.7 (261.8–730.6) | 460.4 (262.2–729.6) | 488.8 (282.8–733.8) | 439.7 (248.2–753.8) | 0.7168 |
Roots | 24.7 (6.8–71.8) | 24.7 (6.8–67) | 24.7 (3.5–91.2) | 27 (3.5–73.3) | 0.8940 |
Beans and legumes | 148.8 (78.0–286.0) | 154.6 (78–286) | 148.8 (56.4–286) | 143 (57.8–286) | 0.0530 |
Vegetables | 67.3 (23.1–161.2) | 66.1 (25.3–164.1) | 71.5 (16.1–167.7) | 61.5 (22–149.7) | 0.5295 |
Fruits | 465.7 (218.3–988.4) | 457 (229.5–987.1) | 574.2 (205.6–1071) | 429.3 (183–848.6) | 0.0691 |
Coffee and tea | 106.7 (13.3–293.3) | 146.7 (16.7–293.3) | 80 (13.3–293.3) | 80 (13.3–293.3) | 0.4200 |
Food or Food Group | Dietary Patterns | ||||
---|---|---|---|---|---|
Pattern 1 | Pattern 2 | Pattern 3 | Pattern 4 | p-Value | |
Sugar and sweets | 22.9 ± 18.3 | 13.6 ± 9.8 | 18.1 ± 14.1 | 43.0 ± 39.5 | <0.001 |
Sweetened beverages | 49.7 ± 41.2 | 30.4 ± 24.7 | 35.7 ± 28.2 | 137.4 ± 111.9 | <0.001 |
Processed meat products | 16.0 ± 21.0 | 10.5 ± 19.7 | 12.3 ± 18.1 | 30.8 ± 32.0 | <0.001 |
Fast food | 13.6 ± 13.3 | 10.2 ± 8.8 | 11.5 ± 13.4 | 35.8 ± 35.1 | <0.001 |
Typical Brazilian dishes | 24.8 ± 24.6 | 19.9 ± 10.1 | 20.5 ± 21.2 | 63.7 ± 63.1 | <0.001 |
Oils | 5.7 ± 5.1 | 2.2 ± 2.7 | 4.0 ± 3.3 | 7.2 ± 8.1 | <0.001 |
Milk and dairy | 17.2 ± 17.5 | 8.4 ± 6.5 | 15.0 ± 15.0 | 41.9 ± 40.6 | <0.001 |
Meat | 15.7 ± 14.0 | 9.7 ± 12.9 | 15.9 ± 20.1 | 29.8 ± 26.2 | <0.001 |
Rice and cereals | 34.1 ± 18.3 | 14.8 ± 11.2 | 28.6 ± 16.8 | 53.2 ± 36.6 | <0.001 |
Roots | 11.8 ± 18.3 | 6.6 ± 7.8 | 10.3 ± 16.5 | 27.1 ± 36.9 | <0.001 |
Beans and legumes | 82.3 ± 59.1 | 17.4 ± 15.9 | 111.6 ± 71.9 | 104.8 ± 76.3 | <0.001 |
Vegetables | 15.2 ± 17.8 | 8.4 ± 9.3 | 10.3 ± 10.9 | 29.0 ± 24.6 | <0.001 |
Fruits | 30.5 ± 32.0 | 17.4 ± 17.7 | 21.8 ± 18.7 | 58.5 ± 48.5 | <0.001 |
Coffee and tea | 156.2 ± 64.5 | 10.9 ± 11.2 | 32.8 ± 31.7 | 74.2 ± 91.2 | <0.001 |
© 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/).
Share and Cite
Andrade, V.M.B.; Santana, M.L.P.d.; Fukutani, K.F.; Queiroz, A.T.L.; Arriaga, M.B.; Damascena, N.F.; Menezes, R.C.; Fernandes, C.D.; Conceição-Machado, M.E.P.; Silva, R.d.C.R.; et al. Systems Nutrology of Adolescents with Divergence between Measured and Perceived Weight Uncovers a Distinctive Profile Defined by Inverse Relationships of Food Consumption. Nutrients 2020, 12, 1670. https://doi.org/10.3390/nu12061670
Andrade VMB, Santana MLPd, Fukutani KF, Queiroz ATL, Arriaga MB, Damascena NF, Menezes RC, Fernandes CD, Conceição-Machado MEP, Silva RdCR, et al. Systems Nutrology of Adolescents with Divergence between Measured and Perceived Weight Uncovers a Distinctive Profile Defined by Inverse Relationships of Food Consumption. Nutrients. 2020; 12(6):1670. https://doi.org/10.3390/nu12061670
Chicago/Turabian StyleAndrade, Vanessa M. B., Mônica L. P. de Santana, Kiyoshi F. Fukutani, Artur T. L. Queiroz, Maria B. Arriaga, Nadjane F. Damascena, Rodrigo C. Menezes, Catarina D. Fernandes, Maria Ester P. Conceição-Machado, Rita de Cássia R. Silva, and et al. 2020. "Systems Nutrology of Adolescents with Divergence between Measured and Perceived Weight Uncovers a Distinctive Profile Defined by Inverse Relationships of Food Consumption" Nutrients 12, no. 6: 1670. https://doi.org/10.3390/nu12061670