Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-25T18:37:04.844Z Has data issue: false hasContentIssue false
  • English
  • Français

Variation in dietary intake and body fatness by socioeconomic status among women in the context of Costa Rican nutrition transitions

Published online by Cambridge University Press:  20 June 2019

Traci A. Bekelman Open the ORCID record for Traci A. Bekelman [Opens in a new window] ,
Carolina Santamaría-Ulloa  and
Darna L. Dufour
Traci A. Bekelman*
Affiliation:
Department of Pediatrics/Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, USA
Carolina Santamaría-Ulloa
Affiliation:
Instituto de Investigaciones en Salud (INISA), Universidad de Costa Rica, San José, Costa Rica
Darna L. Dufour
Affiliation:
Department of Anthropology, University of Colorado Boulder, Boulder, USA
Get access Rights & Permissions [Opens in a new window]

Abstract

The Nutrition Transition model posits that vegetable oils, animal source foods (ASFs) and caloric sweeteners contribute to increases in adiposity and hence body mass index. Body mass index (BMI) is increasing more rapidly among Latin American populations of low versus high socioeconomic status (SES). The objectives of this study among Costa Rican women were to: (1) compare indicators of adiposity and dietary intake by SES and (2) evaluate the relationship between intake of foods high in vegetable oils, ASFs or caloric sweeteners and body fatness. This cross-sectional study, conducted in 2014–2015, included 128 low-, middle- and high-SES non-pregnant, non-lactating women aged between 25 and 45 years with 1–4 live births. Anthropometry was used to assess BMI, body composition and body fat distribution. Dietary recalls (n = 379) were used to assess dietary intake. Percentage body fat was greater in low- versus high-SES women (31.5 ± 3.9 vs 28.2 ± 4.7%). Skinfold measurements at four sites on the upper and lower body were greater in low- versus high-SES women. Body mass index did not vary in low- versus high-SES women. Intake frequency of foods high in vegetable oils was greater in low- and middle- (1.8 and 1.8 times/day, respectively) versus high- (1.1 times/day) SES women. For individual foods, intake frequency varied significantly by SES for high-fat condiments, fried vegetables, dairy, sweetened coffee/tea and pastries and desserts. Intake frequency of Nutrition Transition food categories was not associated with percentage body fat after adjustment for energy intake. Indicators of body composition provide additional information beyond BMI that are useful in understanding SES–adiposity associations in Latin America. Approaches to understanding diet and adiposity in Latin America that focus on vegetable oils, ASFs and caloric sweeteners should consider within-country variation in the pace of the Nutrition Transition, especially when explaining variation in adiposity by SES.

Keywords

Nutrition transitionSocioeconomic statusLatin America
Type
Research Article
Information
Journal of Biosocial Science , Volume 52 , Issue 2 , March 2020 , pp. 230 - 247
Copyright
© Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agüero, MLA (2009) National Nutrition Survey, Costa Rica 2008–2009 [in Spanish]. Ministry of Health San Jose, Costa Rica.Google Scholar
Aguilar-Farias, N, Martino-Fuentealba, P, Carcamo-Oyarzun, J, Cortinez-O’ryan, A, Cristi-Montero, C, Von Oetinger, A and Sadarangani, KP (2018) A regional vision of physical activity, sedentary behaviour and physical education in adolescents from Latin America and the Caribbean: results from 26 countries. International Journal of Epidemiology, doi: 10.1093/ije/dyy033.CrossRefGoogle Scholar
Albala, C, Vio, F, Kain, J and Uauy, R (2002) Nutrition transition in Chile: determinants and consequences. Public Health Nutrition 5(1A), 123–128.CrossRefGoogle ScholarPubMed
Amoateng, AY, Doegah, PT and Udomboso, C (2017) Socio-demographic factors associated with dietary behaviour among young Ghanaians aged 15-34 years. Journal of Biosocial Science 49(2), 187–205.CrossRefGoogle ScholarPubMed
Arps, S (2011) Socioeconomic status and body size among women in Honduran Miskito communities. Annals of Human Biology 38(4), 508–519.CrossRefGoogle ScholarPubMed
Bekelman, TA, Santamaria-Ulloa, C., Dufour, DL, Marin-Arias, L and Dengo, AL (2017) Using the protein leverage hypothesis to understand socioeconomic variation in obesity. American Journal of Human Biology 29(3), e22953.CrossRefGoogle ScholarPubMed
Bekelman, TA, Santamaría-Ulloa, C, Dufour, DL and Dengo, AL (2016) Perceptions of food availability and self-reported dietary intake in urban Costa Rican women: a pilot study. Población y Salud en Mesoamérica 13(2), 1–23.CrossRefGoogle Scholar
Boissonnet, C, Schargrodsky, H, Pellegrini, F, Macchia, A, Marcet Champagne, B, Wilson, E and Tognoni, F (2011) Educational inequalities in obesity, abdominal obesity, and metabolic syndrome in seven Latin American cities: the CARMELA Study. European Journal of Cardiovascular Prevention and Rehabilitation 18(4), 550–556.CrossRefGoogle ScholarPubMed
Bojorquez, I, Unikel, C, Cortez, I and Cerecero, D (2015) The social distribution of dietary patterns. Traditional, modern and healthy eating among women in a Latin American city. Appetite 92, 43–50.Google Scholar
Bouchard, C (2007) BMI, fat mass, abdominal adiposity and visceral fat: where is the ‘beef’? International Journal of Obesity 31(10), 1552–1553.CrossRefGoogle Scholar
Camargo, DM, Ramirez, PC, Quiroga, V, Rios, P, Fermino, RC and Sarmiento, OL (2018) Physical activity in public parks of high and low socioeconomic status in Colombia using observational methods. Journal of Physical Activity and Health, 1–11.CrossRefGoogle Scholar
Cantor, A, Pena, J and Himmelgreen, D (2013) “We never ate like that, not fast food, or junk foods”: accounts of changing maternal diet in a tourist community in rural Costa Rica. Ecology of Food and Nutrition 52(6), 479–496.CrossRefGoogle Scholar
Cohen, E, Gradidge, PJ, Ndao, A, Duboz, P, Macia, E, Gueye, L et al. (2018) Biocultural determinants of overweight and obesity in the context of nutrition transition in Senegal: a holistic anthropological approach. Journal of Biosocial Science, doi: 10.1017/S0021932018000287.CrossRefGoogle Scholar
Colon-Ramos, U, Kabagambe, EK, Baylin, A, Ascherio, A, Campos, H and Peterson, KE (2007) Socio-economic status and health awareness are associated with choice of cooking oil in Costa Rica. Public Health Nutrition 10(11), 1214–1222.CrossRefGoogle ScholarPubMed
Cuevas, A, Alvarez, V and Olivos, C (2009) The emerging obesity problem in Latin America. Expert Review of Cardiovascular Therapy 7(3), 281–288.CrossRefGoogle ScholarPubMed
Cunha, DB, De Almeida, RM, Sichieri, R and Pereira, RA (2010) Association of dietary patterns with BMI and waist circumference in a low-income neighbourhood in Brazil. British Journal of Nutrition 104(6), 908–913.CrossRefGoogle Scholar
Denova-Gutierrez, E, Castanon, S, Talavera, JO, Flores, M, Macias, N, Rodriguez-Ramirez, S et al. (2011) Dietary patterns are associated with different indexes of adiposity and obesity in an urban Mexican population. Journal of Nutrition 141(5), 921–927.CrossRefGoogle Scholar
Deurenberg, P, Deurenberg-Yap, M and Guricci, S (2002) Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obesity Reviews 3(3), 141–146.CrossRefGoogle ScholarPubMed
Dressler, WW, Oths, KS, Ribeiro, RP, Balieiro, MC. and Dos Santos, JE (2008) Cultural consonance and adult body composition in urban Brazil. American Journal of Human Biology 20(1), 15–22.Google ScholarPubMed
Dufour, DL, Bender, RL and Reina, JC (2015) Local trends in diet in urban Colombia, 1990–1995 to 2008: little evidence of a nutrition transition among low-income women. American Journal of Human Biology 27(1), 106–115.CrossRefGoogle ScholarPubMed
Durnin, JV and Rahaman, MM (1967) The assessment of the amount of fat in the human body from measurements of skinfold thickness. British Journal of Nutrition 21(3), 681–689.CrossRefGoogle ScholarPubMed
Fisberg, M, Kovalskys, I, Gomez, G, Rigotti, A, Sanabria, LYC, Garcia, MCY et al. (2018) Total and added sugar intake: assessment in eight Latin American countries. Nutrients 10(4).CrossRefGoogle Scholar
Flores, M, Macias, N, Rivera, M, Lozada, A, Barquera, S, Rivera-Dommarco, J and Tucker, KL (2010) Dietary patterns in Mexican adults are associated with risk of being overweight or obese. Journal of Nutrition 140(10), 1869–1873.CrossRefGoogle ScholarPubMed
Food and Agriculture Organization (2017) FAOSTAT Data. URL: http://www.fao.org/faostat/en/#homeGoogle Scholar
Frisancho, AR (1974) Triceps skin fold and upper arm muscle size norms for assessment of nutrition status. American Journal of Clinical Nutrition 27(10), 1052–1058.CrossRefGoogle ScholarPubMed
Gallagher, D, Visser, M, Sepulveda, D, Pierson, RN, Harris, R and Heymsfield, SB (1996) How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? American Journal of Epidemiology 143(3), 228–239.CrossRefGoogle ScholarPubMed
Gibson, RS (2005) Principles of Nutritional Assessment. Oxford University Press, Oxford.Google Scholar
Heredia-Blonval, K, Blanco-Metzler, A, Montero-Campos, M and Dunford, EK (2014) The salt content of products from popular fast-food chains in Costa Rica. Appetite 83, 173–177.CrossRefGoogle ScholarPubMed
Heymsfield, SB, Peterson, CM, Thomas, DM, Heo, M, Schuna, JM Jr (2016) Why are there race/ethnic differences in adult body mass index-adiposity relationships? A quantitative critical review. Obesity Review 17, 262–275.CrossRefGoogle ScholarPubMed
Himmelgreen, DA, Cantor, A, Arias, S and Romero-Daza, N (2014) Using a biocultural approach to examine migration/globalization, diet quality, and energy balance. Physiology and Behavior 134, 76–85.CrossRefGoogle ScholarPubMed
Jeon, H, Salinas, D and Baker, DP (2015) Non-linear education gradient across the nutrition transition: mothers’ overweight and the population education transition. Public Health Nutrition 18(17), 3172–3182.CrossRefGoogle ScholarPubMed
Kain, J, Vio, F and Albala, C (2003) Obesity trends and determinant factors in Latin America. Cadernos de Saúde Publica 19 (Supplemebnt 1), S77–S86.CrossRefGoogle ScholarPubMed
Kulkarni, B, Hills, AP and Byrne, NM (2014) Nutritional influences over the life course on lean body mass of individuals in developing countries. Nutrition Reviews 72(3), 190–204.CrossRefGoogle ScholarPubMed
Lohmann, T and Martorell, R. (1988) Anthropometric Standardization Reference Manual. Human Kinetics Books, Champaign, IL.Google Scholar
Ministerio de Salud (2009) Encuesta Nacional de Nutrición. URL: Ministerio de Salud: San José, Costa Rica.Google Scholar
Monge-Rojas, R, Smith-Castro, V, Colon-Ramos, U, Aragon, MC and Herrera-Raven, R (2013) Psychosocial factors influencing the frequency of fast-food consumption among urban and rural Costa Rican adolescents. Nutrition 29(7–8), 1007–1012.CrossRefGoogle Scholar
Monteiro, CA Mh DaB, Conde, WL and Popkin, BM (2000) Shifting obesity trends in Brazil. European Journal of Clinical Nutrition 54(4), 342–346.CrossRefGoogle Scholar
Okorodudu, DO, Jumean, MF, Montori, VM, Romero-Corral, A, Somers, VK, Erwin, PJ and Lopez-Jimenez, F. (2010) Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis. International Journal of Obesity 34(5), 791–799.CrossRefGoogle ScholarPubMed
Olszowy, KM, Dufour, DL, Bender, RL, Bekelman, TA and Reina, JC (2012) Socioeconomic status, stature, and obesity in women: 20-year trends in urban Colombia. American Journal of Human Biology 24(5), 602–610.CrossRefGoogle ScholarPubMed
Perez-Cueto, FJ, Naska, A, Monterrey, J, Almanza-Lopez, M, Trichopoulou, A and Kolsteren, P (2006) Monitoring food and nutrient availability in a nationally representative sample of Bolivian households. British Journal of Nutrition 95(3), 555–567.CrossRefGoogle Scholar
Poggio, R, Seron, P, Calandrelli, M, Ponzo, J, Mores, N, Matta, MG, Gutierrez, L et al. (2016) Prevalence, patterns, and correlates of physical activity among the adult population in Latin America: cross-sectional results from the CESCAS I study. Global Heart 11(1), 81–88.e81.CrossRefGoogle ScholarPubMed
Popkin, BM (2006) Global nutrition dynamics: the world is shifting rapidly toward a diet linked with noncommunicable diseases. American Journal of Clinical Nutrition 84(2), 289–298.CrossRefGoogle Scholar
Popkin, BM (2012) Sugary beverages represent a threat to global health. Trends in Endocrinology and Metabolism 23(12), 591–593.CrossRefGoogle ScholarPubMed
Popkin, BM, Adair, LS and Ng, SW (2012) Global nutrition transition and the pandemic of obesity in developing countries. Nutrition Reviews 70(1), 3–21.CrossRefGoogle ScholarPubMed
Popkin, BM and Reardon, T (2018) Obesity and the food system transformation in Latin America. Obesity Reviews, doi: 10.1111/obr.12694.CrossRefGoogle Scholar
Prentice, AM and Jebb, SA (2001) Beyond body mass index. Obesity Reviews 2(3), 141–147.CrossRefGoogle ScholarPubMed
Rhee, JJ, Mattei, J and Campos, H (2012) Association between commercial and traditional sugar-sweetened beverages and measures of adiposity in Costa Rica. Public Health Nutrition 15(8), 1347–1354.CrossRefGoogle ScholarPubMed
Rivera, JA, Barquera, S, Campirano, F, Campos, I, Safdie, M and Tovar, V (2002) Epidemiological and nutritional transition in Mexico: rapid increase of non-communicable chronic diseases and obesity. Public Health Nutrition 5(1A), 113–122.CrossRefGoogle ScholarPubMed
Romero-Corral, A, Somers, VK, Sierra-Johnson, J, Korenfeld, Y, Boarin, S, Korinek, J et al. (2010) Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. European Heart Journal 31(6), 737–746.CrossRefGoogle ScholarPubMed
Schargrodsky, H, Hernandez-Hernandez, R, Champagne, BM, Silva, H, Vinueza, R, Silva Aycaguer, LC et al. (2008) CARMELA: assessment of cardiovascular risk in seven Latin American cities. American Journal of Medicine 121(1), 58–65.CrossRefGoogle ScholarPubMed
Siri, WE (1956) The gross composition of the body. Advances in Biological and Medical Physics 4, 239–280.CrossRefGoogle Scholar
Stalsberg, R and Pedersen, AV (2018) Are differences in physical activity across socioeconomic groups associated with choice of physical activity variables to report? International Journal of Environmental Research and Public Health 15(5), 922.CrossRefGoogle ScholarPubMed
Uauy, R and Monteiro, CA (2004) The challenge of improving food and nutrition in Latin America. Food and Nutrition Bulletin 25(2), 175–182.CrossRefGoogle ScholarPubMed
United Nations Development Program (2013) Informe nacional sobre desarrollo humano 2013. Aprendiendo a vivir juntos: Convivencia y desarrollo humano en Costa Rica. PNUD, San José, Costa Rica.Google Scholar
Vio, F, Albala, C and Kain, J (2008) Nutrition transition in Chile revisited: mid-term evaluation of obesity goals for the period 2000–2010. Public Health Nutrition 11(4), 405–412.Google ScholarPubMed
Wang, Z, Gordon-Larsen, P, Siega-Riz, AM, Cai, J, Wang, H, Adair, LS and Popkin, BM (2017) Sociodemographic disparity in the diet quality transition among Chinese adults from 1991 to 2011. European Journal of Clinical Nutrition 71(4), 486–493.CrossRefGoogle ScholarPubMed
Wong-McClure, R, Gregg, EW, Barcelo, A, Sanabria-Lopez, L, Lee, K, Abarca-Gomez, L et al. (2016) Prevalence of diabetes and impaired fasting glucose in Costa Rica: Costa Rican National Cardiovascular Risk Factors Survey, 2010. Journal of Diabetes 8(5), 686–692.CrossRefGoogle ScholarPubMed
World Health Organization (2015) Body Mass Index – BMI. URL: http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle/body-mass-index-bmiGoogle Scholar