Association between socioeconomic status and diet quality in Mexican men and women: A cross-sectional study

Autoři: Nancy López-Olmedo aff001;  Barry M. Popkin aff001;  Lindsey Smith Taillie aff001
Působiště autorů: Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United Stated of America aff001
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224385


Examining the potential differences in diet quality among socioeconomic status (SES) subgroups in Mexican adults may help to explain SES disparities in the burden of non-communicable diseases. We determined the association between SES, gender and diet quality among Mexican adults. We analyzed data from adults participating in the subsample with dietary information from the Mexican National Health and Nutrition Survey 2012 (n = 2,400), and developed the Mexican Diet Quality Index based on the Mexican Dietary Guidelines. We tested the interaction between sex and SES indicators using multivariable linear regression models. Sex was not a modifier; therefore, the analyses were carried out in the overall sample of men and women. The mean age was 42 (SE = 0.4) years, the total diet quality score was 38 (SE = 0.4), and a high percentage of men and women were classified with reading/writing skills or 3–9 years of school. A higher percentage of adults were classified with high versus medium or low assets index. In the multivariable model further adjusted for the assets index, for adults with education in the reading and/or 3–9 years of schooling and those with ≥10 years of school, there was a 3.7 and 5.8 points lower total diet quality score than with adults with no reading/writing skills (p < 0.05). Likewise, in multivariable model further adjusted for educational level, the total diet quality score was 2.5 points and 3.3 points lower in adults classified with medium and high assets index, respectively, versus low assets index (p < 0.05). The difference between individuals with medium and high assets index was not statistically significant. Although there is currently better diet quality among adults with low SES, this needs to continue to be monitored as Mexico progress through the nutrition transition.

Klíčová slova:

Diet – Educational attainment – Fats – Mexican people – Nutrition – Physical activity – Schools – Socioeconomic aspects of health


1. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;393(10184):1958–72. Epub 2019/04/08. doi: 10.1016/S0140-6736(19)30041-8 30954305.

2. Gómez-Dantés H, Fullman N, Lamadrid-Figueroa H, Cahuana-Hurtado L, Darney B, Avila-Burgos L, et al. Dissonant health transition in the states of Mexico, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. The Lancet. 2016;388(10058):2386–402.

3. Hosseinpoor AR, Bergen N, Kunst A, Harper S, Guthold R, Rekve D, et al. Socioeconomic inequalities in risk factors for non communicable diseases in low-income and middle-income countries: results from the World Health Survey. BMC public health. 2012;12(1):912.

4. Frances R. Association of Socioeconomic Position With Health Behaviors and Mortality. Year Book of Psychiatry & Applied Mental Health. 2012;2012:188–9.

5. Willett WC, Stampfer MJ. Current evidence on healthy eating. Annual review of public health. 2013;34:77–95. Epub 2013/01/10. doi: 10.1146/annurev-publhealth-031811-124646 23297654.

6. Niessen LW, Mohan D, Akuoku JK, Mirelman AJ, Ahmed S, Koehlmoos TP, et al. Tackling socioeconomic inequalities and non-communicable diseases in low-income and middle-income countries under the Sustainable Development agenda. The Lancet. 2018.

7. Stern D, Piernas C, Barquera S, Rivera JA, Popkin BM. Caloric Beverages Were Major Sources of Energy among Children and Adults in Mexico, 1999–2012. The Journal of Nutrition. 2014;144(6):949–56. doi: 10.3945/jn.114.190652 24744311

8. Aburto TC, Pedraza LS, Sanchez-Pimienta TG, Batis C, Rivera JA. Discretionary Foods Have a High Contribution and Fruit, Vegetables, and Legumes Have a Low Contribution to the Total Energy Intake of the Mexican Population. J Nutr. 2016;146(9):1881s–7s. Epub 2016/08/12. doi: 10.3945/jn.115.219121 27511928.

9. Arvaniti F, Panagiotakos DB. Healthy indexes in public health practice and research: a review. Critical reviews in food science and nutrition. 2008;48(4):317–27. doi: 10.1080/10408390701326268 18409114

10. Wong JE, Parnell WR, Howe AS, Black KE, Skidmore PM. Development and validation of a food-based diet quality index for New Zealand adolescents. BMC Public Health. 2013;13:562. Epub 2013/06/14. doi: 10.1186/1471-2458-13-562 23759064.

11. Previdelli AN, de Andrade SC, Fisberg RM, Marchioni DM. Using Two Different Approaches to Assess Dietary Patterns: Hypothesis-Driven and Data-Driven Analysis. Nutrients. 2016;8(10). Epub 2016/09/27. doi: 10.3390/nu8100593 27669289.

12. Potter J, Brown L, Williams RL, Byles J, Collins CE. Diet Quality and Cancer Outcomes in Adults: A Systematic Review of Epidemiological Studies. International journal of molecular sciences. 2016;17(7). Epub 2016/07/12. doi: 10.3390/ijms17071052 27399671.

13. Harmon BE, Boushey CJ, Shvetsov YB, Ettienne R, Reedy J, Wilkens LR, et al. Associations of key diet-quality indexes with mortality in the Multiethnic Cohort: the Dietary Patterns Methods Project. The American journal of clinical nutrition. 2015;101(3):587–97. Epub 2015/03/04. doi: 10.3945/ajcn.114.090688 25733644.

14. Schwingshackl L, Hoffmann G. Diet Quality as Assessed by the Healthy Eating Index, the Alternate Healthy Eating Index, the Dietary Approaches to Stop Hypertension Score, and Health Outcomes: A Systematic Review and Meta-Analysis of Cohort Studies. Journal of the Academy of Nutrition and Dietetics. 2015;115(5):780–800.e5. 25680825

15. Wang Z, Adair LS, Cai J, Gordon-Larsen P, Siega-Riz AM, Zhang B, et al. Diet Quality Is Linked to Insulin Resistance among Adults in China. The Journal of nutrition. 2017;147(11):2102–8. doi: 10.3945/jn.117.256180 28978676

16. Ponce X, Rodriguez-Ramirez S, Mundo-Rosas V, Shamah T, Barquera S, Gonzalez de Cossio T. Dietary quality indices vary with sociodemographic variables and anthropometric status among Mexican adults: a cross-sectional study. Results from the 2006 National Health and Nutrition Survey. Public Health Nutr. 2014;17(8):1717–28. Epub 2013/10/16. doi: 10.1017/S1368980013002462 24124890.

17. Satia JA. Diet-related disparities: understanding the problem and accelerating solutions. Journal of the American Dietetic Association. 2009;109(4):610. doi: 10.1016/j.jada.2008.12.019 19328255

18. Mullie P, Clarys P, Hulens M, Vansant G. Dietary patterns and socioeconomic position. European journal of clinical nutrition. 2010;64(3):231. doi: 10.1038/ejcn.2009.145 20087378

19. Wang DD, Leung CW, Li Y, Ding EL, Chiuve SE, Hu FB, et al. Trends in dietary quality among adults in the United States, 1999 through 2010. JAMA internal medicine. 2014;174(10):1587–95. doi: 10.1001/jamainternmed.2014.3422 25179639

20. Backholer K, Spencer E, Gearon E, Magliano DJ, McNaughton SA, Shaw JE, et al. The association between socio-economic position and diet quality in Australian adults. Public health nutrition. 2016;19(3):477–85. doi: 10.1017/S1368980015001470 25989940

21. Dynesen AW, Haraldsdottir J, Holm L, Astrup A. Sociodemographic differences in dietary habits described by food frequency questions—results from Denmark. European journal of clinical nutrition. 2003;57(12):1586–97. Epub 2003/12/04. doi: 10.1038/sj.ejcn.1601728 14647224.

22. Wang Z, Gordon-Larsen P, Siega-Riz AM, Cai J, Wang H, Adair LS, et al. Sociodemographic disparity in the diet quality transition among Chinese adults from 1991 to 2011. European journal of clinical nutrition. 2016. Epub 2016/09/30. doi: 10.1038/ejcn.2016.179 27677363.

23. Jaime PC, Bandoni DH, Duran ACdFL, Fisberg RM. Diet quality index adjusted for energy requirements in adults. Cadernos de saude publica. 2010;26:2121–8. doi: 10.1590/s0102-311x2010001100013 21180985

24. Lynch JL, von Hippel PT. An education gradient in health, a health gradient in education, or a confounded gradient in both? Social Science & Medicine. 2016;154:18–27.

25. Zajacova A, Lawrence EM. The Relationship Between Education and Health: Reducing Disparities Through a Contextual Approach. Annual review of public health. 2018;(0).

26. Winkleby MA, Jatulis DE, Frank E, Fortmann SP. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. American journal of public health. 1992;82(6):816–20. doi: 10.2105/ajph.82.6.816 1585961

27. Arganini C, Saba A, Comitato R, Virgili F, Turrini A. Gender differences in food choice and dietary intake in modern western societies. Public health-social and behavioral health: InTech; 2012.

28. MacIntyre S, Hunt K. Socio-economic position, gender and health: how do they interact? Journal of health psychology. 1997;2(3):315–34. doi: 10.1177/135910539700200304 22013025

29. Basto-Abreu A, Barrientos-Gutierrez T, Zepeda-Tello R, Camacho V, Gimeno Ruiz de Porras D, Hernandez-Avila M. The Relationship of Socioeconomic Status with Body Mass Index Depends on the Socioeconomic Measure Used. Obesity (Silver Spring, Md). 2018;26(1):176–84. Epub 2017/11/21. doi: 10.1002/oby.22042 29152913.

30. Abassi MM, Sassi S, El Ati J, Ben Gharbia H, Delpeuch F, Traissac P. Gender inequalities in diet quality and their socioeconomic patterning in a nutrition transition context in the Middle East and North Africa: a cross-sectional study in Tunisia. Nutrition journal. 2019;18(1):18. Epub 2019/03/23. doi: 10.1186/s12937-019-0442-6 30898119.

31. Chong SP, Appannah G, Sulaiman N. Predictors of Diet Quality as Measured by Malaysian Healthy Eating Index among Aboriginal Women (Mah Meri) in Malaysia. Nutrients. 2019;11(1). Epub 2019/01/13. doi: 10.3390/nu11010135 30634596.

32. Hernandez EM, Margolis R, Hummer RA. Educational and Gender Differences in Health Behavior Changes After a Gateway Diagnosis. Journal of aging and health. 2018;30(3):342–64. Epub 2016/12/13. doi: 10.1177/0898264316678756 27940641.

33. Romero-Martínez M, Shamah-Levy T, Franco-Nuñez A, Villalpando S, Cuevas-Nasu L, Gutiérrez JP. Encuesta Nacional de Salud y Nutrición 2012: diseño y cobertura. Salud publica de Mexico. 2013;55.

34. López-Olmedo N, Carriquiry AL, Rodríguez-Ramírez S, Ramírez-Silva I, Espinosa-Montero J, Hernández-Barrera L, et al. Usual Intake of Added Sugars and Saturated Fats Is High while Dietary Fiber Is Low in the Mexican Population. The Journal of Nutrition. 2016;146(9):1856S–65S. doi: 10.3945/jn.115.218214 27511932

35. Blanton CA, Moshfegh AJ, Baer DJ, Kretsch MJ. The USDA Automated Multiple-Pass Method accurately estimates group total energy and nutrient intake. J Nutr. 2006;136(10):2594–9. Epub 2006/09/22. doi: 10.1093/jn/136.10.2594 16988132.

36. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. The American journal of clinical nutrition. 2003;77(5):1171–8. Epub 2003/04/30. doi: 10.1093/ajcn/77.5.1171 12716668.

37. Agricultural Research Service, Food Surveys Research Group. USDA Food and Nutrient Database for Dietary Studies, 4.1 Beltsville (MD)2010 [updated October 21 2016; cited 2017 January 10].

38. Ledesma Solano J, Chávez Villasana A, Pérez-Gil Romo F, Mendoza Martínez F, Calvo Carrillo C. Composición de Alimentos "Miriam Muñoz de Chávez". Valor nutritivo de los alimentos de mayor consumo. [Food Composition "Miriam Muñoz de Chávez". Nutrition value od the most consumed foods]. 2a ed. ed. Mexico: McGraw-Hill; 2010.

39. U.S. Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory. National Nutrient Database for Standard Reference, Release 24. 2013 [updated August 13 2016; cited 2017 January 10].

40. Villalpando S, Ramírez-Silva I, Bernal Medina D, De la Cruz Góngora V. Tablas de composición de ácidos grasos de alimentos frecuentes en la dieta mexicana. [Tables of fatty acids composition of common foods in the Mexican diet]. Cuernavaca (Mexico): National Institute of Public Health; 2007.

41. Bonvecchio-Arenas A, Fernández-Gaxiola AC, Plazas-Belusteguigoitia M, Kaufer-Horwitz M, Pérez-Lizaur AB, Rivera JA. Guías alimentarias y de actividad física en contexto de sobrepeso y obesidad en la población Mexicana [Dietary and physical activity guidelines in the context of overweight and obesity in the Mexican population]. Academia Nacional de Medicina ed. Mexico2015.

42. Robert Wood Johnson Foundation. Recommendations for Healthier Beverages Princeton (NJ)2013 [cited 2017 May 23].

43. World Health Organization. Guideline: Sugars intake for adults and children. Geneva: World Health Organization, 2015.

44. Bourges H, Casanueva E, Rosado J. Recomendaciones de ingestion de nutrimentos para la poblacion Mexicana: bases fiosiológicas. Tomo 2. [Recommendations of nutrient intake for the Mexican population: physiological basis]: Editorial Medica Panamericana Sa de; 2008.

45. World Health Organization / Food And Agriculture Organization of the United Nations. Diet, Nutrition and Prevention of Chronic Diseases. Report of a Joint WHO/FAO Expert Consultation. WHO Technical Report Series no. 916. Geneva: WHO, 2003.

46. Micha R, Shulkin ML, Peñalvo JL, Khatibzadeh S, Singh GM, Rao M, et al. Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE). PloS one. 2017;12(4):e0175149. doi: 10.1371/journal.pone.0175149 28448503

47. Sánchez-Pimienta TG, Batis C, Lutter CK, Rivera JA. Sugar-Sweetened Beverages Are the Main Sources of Added Sugar Intake in the Mexican Population. The Journal of Nutrition. 2016;146(9):1888S–96S. doi: 10.3945/jn.115.220301 27511931

48. Vallejo M, Colin-Ramirez E, Rivera Mancia S, Cartas Rosado R, Madero M, Infante Vazquez O, et al. Assessment of Sodium and Potassium Intake by 24 h Urinary Excretion in a Healthy Mexican Cohort. Archives of medical research. 2017;48(2):195–202. Epub 2017/06/20. doi: 10.1016/j.arcmed.2017.03.012 28625323.

49. Martínez R, Fernández A. Impacto social y económico del analfabetismo: modelo de análisis y estudio piloto. 2010.

50. Robles JN, Navarro DM. Analfabetismo en México: una deuda social. Realidad, Datos, y Espacio: Revista Internacional de Estadistica y Geografia. 2013;3:5–17.

51. Gutiérrez JP. Clasificación por niveles socioeconómicos de los hogares entrevistados para la Encuesta Nacional de Salud y Nutrición 2006: nota metodológica. [Classification of the interviewed households by socioeconomic levels for the National Health and Nutrition Survey 2006: methodological note.]. Cuernavaca (Mexico): National Institute of Public Health, 2008.

52. WHO. Obesity: preventing and managing the global epidemic: World Health Organization; 2000.

53. Medina C, Janssen I, Campos I, Barquera S. Physical inactivity prevalence and trends among Mexican adults: results from the National Health and Nutrition Survey (ENSANUT) 2006 and 2012. BMC Public Health. 2013;13(1):1–10. doi: 10.1186/1471-2458-13-1063 24215173

54. Organization WH. Global strategy on diet, physical activity and health. 2004.

55. Medina C, Tolentino-Mayo L, López-Ridaura R, Barquera S. Evidence of increasing sedentarism in Mexico City during the last decade: Sitting time prevalence, trends, and associations with obesity and diabetes. PloS one. 2017;12(12):e0188518–e. doi: 10.1371/journal.pone.0188518 29194458.

56. Medina C, Barquera S, Janssen I. Validity and reliability of the International Physical Activity Questionnaire among adults in Mexico. Rev Panam Salud Publica. 2013;34.

57. Flores M, Macias N, Rivera M, Lozada A, Barquera S, Rivera-Dommarco J, et al. Dietary patterns in Mexican adults are associated with risk of being overweight or obese. The Journal of nutrition. 2010;140(10):1869–73. doi: 10.3945/jn.110.121533 20739452

58. Imamura F, Micha R, Khatibzadeh S, Fahimi S, Shi P, Powles J, et al. Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment. The Lancet Global Health. 2015;3(3):e132–e42. doi: 10.1016/S2214-109X(14)70381-X 25701991

59. Mayen AL, Marques-Vidal P, Paccaud F, Bovet P, Stringhini S. Socioeconomic determinants of dietary patterns in low- and middle-income countries: a systematic review. The American journal of clinical nutrition. 2014;100(6):1520–31. Epub 2014/11/21. doi: 10.3945/ajcn.114.089029 25411287.

60. Popkin BM, Adair LS, Ng SW. NOW AND THEN: The Global Nutrition Transition: The Pandemic of Obesity in Developing Countries. Nutrition reviews. 2012;70(1):3–21 22221213

61. Popkin BM, Siega-Riz AM, Haines PS. A comparison of dietary trends among racial and socioeconomic groups in the United States. N Engl J Med. 1996;335(10):716–20. doi: 10.1056/NEJM199609053351006 8703172.

62. Popkin BM, Siega-Riz AM, Haines PS. A comparison of dietary trends among racial and socioeconomic groups in the United States. New England Journal of Medicine. 1996;335(10):716–20. doi: 10.1056/NEJM199609053351006 8703172

63. Pérez-Ferrer C, McMunn A, Zaninotto P, Brunner EJ. The nutrition transition in Mexico 1988–2016: the role of wealth in the social patterning of obesity by education. Public health nutrition. 2018:1–8.

64. López-Olmedo N, Popkin BM, Taillie LS. The socioeconomic disparities in intakes and purchases of less-healthy foods and beverages have changed over time in urban Mexico. The Journal of nutrition. 2018;148(1):109–16. doi: 10.1093/jn/nxx007 29378043

65. Rehm CD, Monsivais P, Drewnowski A. Relation between diet cost and Healthy Eating Index 2010 scores among adults in the United States 2007–2010. Preventive medicine. 2015;73:70–5. doi: 10.1016/j.ypmed.2015.01.019 25625693

66. Lopez-Olmedo N, Popkin BM, Gordon-Larsen P, Taillie LS. Cross-sectional association between diet quality and cardiometabolic risk by education level in Mexican adults. Public Health Nutr. 2019:1–11. Epub 2019/07/10. doi: 10.1017/s1368980019001678 31282318.

67. Lopez-Olmedo N, Popkin BM, Mendez MA, Taillie LS. The association of overall diet quality with BMI and waist circumference by education level in Mexican men and women. Public Health Nutr. 2019:1–16. Epub 2019/06/14. doi: 10.1017/s136898001900065x 31190677.

68. Dodd KW, Guenther PM, Freedman LS, Subar AF, Kipnis V, Midthune D, et al. Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. Journal of the American Dietetic Association. 2006;106(10):1640–50. doi: 10.1016/j.jada.2006.07.011 17000197

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