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Open Access 01-12-2021 | Obesity | Research

Educational inequalities, urbanicity and levels of non-communicable diseases risk factors: evaluating trends in Argentina (2005–2013)

Authors: Santiago Rodríguez López, Usama Bilal, Ana F. Ortigoza, Ana V. Diez-Roux

Published in: BMC Public Health | Issue 1/2021

Abstract

Background

We investigated a) whether urbanicity is associated with individual-level non-communicable diseases (NCD) risk factors and whether urbanicity modifies trends over time in risk factors; and (b) whether educational inequalities in NCD risk factors change over time or are modified by province urbanicity.

Methods

We used data from three large national surveys on NCD risk factors (Encuesta Nacional de Factores de Riesgo; ENFR_{2005–2009-2013}) conducted in urban areas of Argentina (n = 108,489). We used gender-stratified logistic random-intercept models (individuals nested within provinces) to determine adjusted associations of self-reported individual NCD risk factors (hypertension, diabetes, obesity, and current smoking) with education and urbanicity.

Results

In both men and women, the prevalence of obesity and diabetes increased over time but smoking decreased. Hypertension prevalence increased over time in men. Higher urbanicity was associated with higher odds of smoking and lower odds of hypertension in women but was not associated with NCD risk factors in men. Obesity increased more over time in more compared to less urbanized provinces (in men) while smoking decreased more over time in less urbanized provinces. All risk factors had a higher prevalence in persons with lower education (stronger in women than in men), except for diabetes in men and smoking in women. Educational inequalities in obesity (in men) and hypertension (in men and women) became stronger over time, while an initial inverse social gradient in smoking for women reverted and became similar to other risk factors over time. In general, the inverse associations of education with the risk factors became stronger with increasing levels of province urbanicity.

Conclusion

Increasing prevalence of diabetes and obesity over time and growing inequities by education highlight the need for policies aimed at reducing NCD risk factors among lower socioeconomic populations in urban environments in Argentina.

World Health Organization (WHO). Global status report on noncommunicable diseases 2014. Switzerland; 2014. http://www.who.int/nmh/publications/ncd-status-report-2014/en/.

Rose G. Sick individuals and sick populations. Int J Epidemiol. 1985;14(1):32–8. https://doi.org/10.1093/ije/14.1.32.CrossRefPubMed

Link BG, Phelan J. Social conditions as fundamental causes of disease. J Health Soc Behav. 1995:80–94.

Diez Roux AV. Residential environments and cardiovascular health. J Urban Health. 2003;80(4):569–89. https://doi.org/10.1093/jurban/jtg065.CrossRefPubMedPubMedCentral

Karvonen S, Rimpelä A. Socio-regional context as a determinant of adolescents’ health behaviour in Finland. Soc Sci Med. 1996;43(10):1467–74. https://doi.org/10.1016/0277-9536(96)00044-5.CrossRefPubMed

World Economic Forum. Global Risks 2015 - 10th Edition. 2015. www.weforum.org/risks.

Dye C. Health and Urban living. Science. 2008;319(5864):766–9. https://doi.org/10.1126/science.1150198.CrossRefPubMed

Fay M, Ruggeri Laderchi C. Urban Poverty in Latin America and the Caribbean: Setting the Stage. In: Fay M, editor. The Urban Poor in Latin America: The World Bank; 2005. p. 19–46.CrossRef

Cyril S, Oldroyd JC, Renzaho A. Urbanisation, urbanicity, and health: a systematic review of the reliability and validity of urbanicity scales. BMC Public Health. 2013;13(1):513. https://doi.org/10.1186/1471-2458-13-513.CrossRefPubMedPubMedCentral

10.

Reddy KS. Cardiovascular diseases in the developing countries: dimensions, determinants, dynamics and directions for public health action. Public Health Nutr. 2002;5(1a):231–7. https://doi.org/10.1079/PHN2001298.CrossRefPubMed

11.

Miranda J, Gilman RH, Smeeth L. Differences in cardiovascular risk factors in rural, urban and rural-to-urban migrants in Peru. Heart. 2011;97(10):787–96. https://doi.org/10.1136/hrt.2010.218537.CrossRefPubMed

12.

Gong P, Liang S, Carlton EJ, Jiang Q, Wu J, Wang L, et al. Urbanization and health in China. Lancet. 2012;379(9818):843–52. https://doi.org/10.1016/S0140-6736(11)61878-3.CrossRefPubMedPubMedCentral

13.

Thompson AL, Houck KM, Adair L, Gordon-Larsen P, Popkin B. Multilevel examination of the association of urbanization with inflammation in Chinese adults. Health Place. 2014;28:177–86. https://doi.org/10.1016/j.healthplace.2014.05.003.CrossRefPubMedPubMedCentral

14.

Attard SM, Howard AG, Herring AH, Zhang B, du S, Aiello AE, et al. Differential associations of urbanicity and income with physical activity in adults in urbanizing China: findings from the population-based China health and nutrition survey 1991-2009. Int J Behav Nutr Phys Act. 2015;12(1):152. https://doi.org/10.1186/s12966-015-0321-2.CrossRefPubMedPubMedCentral

15.

Jaitman L. Urban infrastructure in Latin America and the Caribbean: public policy priorities. Lat Am Econ Rev. 2015;24:3.CrossRef

16.

Censo Nacional de Población, Hogares y Viviendas 2010 [National Census of Population, Households and housing 2010]. 2010. https://www.indec.gob.ar/indec/web/Nivel4-Tema-2-41-135.

17.

Konfino J, Linetzky B, Ferrante D. Evolución y estado actual de las enfermedades no transmisibles en Argentina. Rev Argentina Salud Pública. 2010;1:37–9.

18.

Ferrante D, Jörgensen N, Langsam M, Marchioni C, Torales S, Torres R. Inequalities in the distribution of cardiovascular disease risk factors in Argentina. A study from the 2005, 2009 and 2013 National Risk Factor Survey (NRFS). Rev Argent Cardiol. 2016;84(2):139–45. https://doi.org/10.7775/rac.es.v84.i2.8261.CrossRef

19.

Linetzky B, De Maio F, Ferrante D, et al. Sex-stratified socio-economic gradients in physical inactivity, obesity, and diabetes: evidence of short-term changes in Argentina. Int J Public Health. 2013;58(2):277–84. https://doi.org/10.1007/s00038-012-0371-z.CrossRefPubMed

20.

Santero M, Melendi S, Hernández-Vásquez A, et al. Socio-economic inequalities in smoking prevalence and involuntary exposure to tobacco smoke in Argentina: analysis of three cross-sectional nationally representative surveys in 2005, 2009 and 2013. PLoS One. 2019;14:1–16.

21.

Fleischer NL, Diez Roux AV, Alazraqui M, Spinelli H, de Maio F. Socioeconomic gradients in chronic disease risk factors in middle-income countries: evidence of effect modification by urbanicity in Argentina. Am J Public Health. 2011;101(2):294–301. https://doi.org/10.2105/AJPH.2009.190165.CrossRefPubMedPubMedCentral

22.

Christine PJ, Diez Roux AV, Wing JJ, Alazraqui M, Spinelli H. Temporal trends in BMI in Argentina by socio-economic position and province-level economic development, 2005–2009. Public Health Nutr. 2015;18(5):817–26. https://doi.org/10.1017/S1368980014001694.CrossRefPubMed

23.

De Maio FG, Linetzky B, Virgolini M. An average/deprivation/inequality (ADI) analysis of chronic disease outcomes and risk factors in Argentina. Popul Health Metrics. 2009;7(1):8. https://doi.org/10.1186/1478-7954-7-8.CrossRef

24.

Censo Nacional de Población, Hogares y Viviendas 2001 [National Census of Population, Households and housing 2001]. 2001. https://www.indec.gob.ar/micro_sitios/webcenso/index.asp

25.

Ministerio del Interior Obras Públicas y Vivienda. Plan Estrategico Territorial. Ciudad de Buenos Aires: Argentina urbana; 2018. https://www.argentina.gob.ar/sites/default/files/plan_estrategico_territorial_2018_baja.pdf

26.

Ernstsen L, Strand BH, Nilsen SM, Espnes GA, Krokstad S. Trends in absolute and relative educational inequalities in four modifiable ischaemic heart disease risk factors: repeated cross-sectional surveys from the Nord-Trøndelag health study (HUNT) 1984–2008. BMC Public Health. 2012;12(266). https://doi.org/10.1186/1471-2458-12-266.

27.

Mackenbach JP, Kunst AE. Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe. Soc Sci Med. 1997;44(6):757–71. https://doi.org/10.1016/S0277-9536(96)00073-1.CrossRefPubMed

28.

Singh-Manoux A, Ferrie JE, Lynch JW, Marmot M. The role of cognitive ability (intelligence) in explaining the association between socioeconomic position and health: evidence from the Whitehall II prospective cohort study. Am J Epidemiol. 2005;161(9):831–9. https://doi.org/10.1093/aje/kwi109.CrossRefPubMed

29.

Khang YH, Yun SC, Lynch JW. Monitoring trends in socioeconomic health inequalities: it matters how you measure. BMC Public Health. 2008;8(1):66. https://doi.org/10.1186/1471-2458-8-66.CrossRefPubMedPubMedCentral

30.

Harper S, Lynch J. Measuring health inequalities. In: Oakes J, Kaufman J, editors. Methods in social epidemiology. San Francisco: Jossey-Bass; 2006. p. 134–68.

31.

Diez-Roux AV, Link BG, Northridge ME. Multilevel analysis of income inequality and cardiovascular disease risk factors. Soc Sci Med. 2000;50(5):673–87. https://doi.org/10.1016/S0277-9536(99)00320-2.CrossRefPubMed

32.

StataCorp. Stata Statistical Software: Release 14. 2015.

33.

Idris BI, Giskes K, Borrell C, Benach J, Costa G, Federico B, et al. Higher smoking prevalence in urban compared to non-urban areas: time trends in six European countries. Health Place. 2007;13(3):702–12. https://doi.org/10.1016/j.healthplace.2006.11.001.CrossRefPubMed

34.

Flies EJ, Mavoa S, Zosky GR, Mantzioris E, Williams C, Eri R, et al. Urban-associated diseases: candidate diseases, environmental risk factors, and a path forward. Environ Int. 2019;133(Pt A):105187. https://doi.org/10.1016/j.envint.2019.105187.CrossRefPubMed

35.

Goryakin Y, Rocco L, Suhrcke M. The contribution of urbanization to non-communicable diseases: evidence from 173 countries from 1980 to 2008. Econ Hum Biol. 2017;26:151–63. https://doi.org/10.1016/j.ehb.2017.03.004.CrossRefPubMed

36.

Allender S, Foster C, Hutchinson L, Arambepola C. Quantification of urbanization in relation to chronic diseases in developing countries: a systematic review. J Urban Health. 2008;85(6):938–51. https://doi.org/10.1007/s11524-008-9325-4.CrossRefPubMedPubMedCentral

37.

Ruel MT, Garrett James L, Yosef S, et al. Urbanization, food security and nutrition. In: de Pee Douglas Taren MWB, editor. Nutrition and Health in a Developing World: Humana Press; 2017. p. 705–35.CrossRef

38.

Hernandez AV, Pasupuleti V, Deshpande A, et al. Effect of rural-to-urban within-country migration on cardiovascular risk factors in low- and middle-income countries: a systematic review. Heart. 2012;98(3):185–94. https://doi.org/10.1136/heartjnl-2011-300599.CrossRefPubMed

39.

Jiwani SS, Carrillo-Larco RM, Hernández-Vásquez A, Barrientos-Gutiérrez T, Basto-Abreu A, Gutierrez L, et al. The shift of obesity burden by socioeconomic status between 1998 and 2017 in Latin America and the Caribbean: a cross-sectional series study. Lancet Glob Health. 2019;7(12):e1644–54. https://doi.org/10.1016/S2214-109X(19)30421-8.CrossRefPubMed

40.

Bixby H, Bentham J, Zhou B, et al. Rising rural body-mass index is the main driver of the global obesity epidemic in adults. Nature. 2019;569:260–4.CrossRef

41.

United Nations Development Programme. Human Development Indices and Indicators 2018. Hum Dev Indices Indic. 2018;2018. https://doi.org/10.18356/656a3808-en.

42.

Jaacks LM, Vandevijvere S, Pan A, McGowan CJ, Wallace C, Imamura F, et al. The obesity transition: stages of the global epidemic. Lancet Diabetes Endocrinol. 2019;7(3):231–40. https://doi.org/10.1016/S2213-8587(19)30026-9.CrossRefPubMedPubMedCentral

43.

Miranda JJ, Barrientos-Gutiérrez T, Corvalan C, Hyder AA, Lazo-Porras M, Oni T, et al. Understanding the rise of cardiometabolic diseases in low- and middle-income countries. Nat Med. 2019;25(11):1667–79. https://doi.org/10.1038/s41591-019-0644-7.CrossRefPubMed

44.

NCD Risk Factor Collaboration (NCD-RisC)—Americas Working Group. Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys. Lancet Glob Health. 2020;8:e123–33.CrossRef

45.

Rubinstein A, Gutierrez L, Beratarrechea A, et al. Increased prevalence of diabetes in Argentina is due to easier health care access rather than to an actual increase in prevalence. PLoS One. 2014;9:1–5.

46.

World Health Organization (WHO). WHO Report on the global tobacco epidemic, 2013: Enforcing bans on tobacco advertising, promotion and sponsorship: executive summary: World Health Organization; 2013. https://apps.who.int/iris/handle/10665/85381

47.

Reitsma MB, Fullman N, Ng M, Salama JS, Abajobir A, Abate KH, et al. Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015: a systematic analysis from the global burden of disease study 2015. Lancet. 2017;389(10082):1885–906. https://doi.org/10.1016/S0140-6736(17)30819-X.CrossRef

48.

Nighbor TD, Doogan NJ, Roberts ME, et al. Smoking prevalence and trends among a U.S. national sample of women of reproductive age in rural versus urban settings. PLoS One. 2018;13:e0207818.CrossRef

49.

Doogan NJ, Roberts ME, Wewers ME, Stanton CA, Keith DR, Gaalema DE, et al. A growing geographic disparity: rural and urban cigarette smoking trends in the United States. Prev Med. 2017;104:79–85. https://doi.org/10.1016/j.ypmed.2017.03.011.CrossRefPubMedPubMedCentral

50.

Fleischer N, Diez Roux AV, Alazraqui M, et al. Socioeconomic patterning in tobacco use in Argentina, 2005. Nicotine Tob Res. 2011;13(10):894–902. https://doi.org/10.1093/ntr/ntr090.CrossRefPubMedPubMedCentral

51.

Faggiano F, Versino E, Lemma P. Decennial trends of social differentials in smoking habits in Italy. Cancer Causes Control. 2001;12(7):665–71. https://doi.org/10.1023/A:1011247024979.CrossRefPubMed

52.

Huisman M, Kunst AE, Mackenbach JP. Educational inequalities in smoking among men and women aged 16 years and older in 11 European countries. Tob Control. 2005;14(2):106–13. https://doi.org/10.1136/tc.2004.008573.CrossRefPubMedPubMedCentral

53.

Santos AC, Barros H. Smoking patterns in a community sample of Portuguese adults, 1999-2000. Prev Med. 2004;38(1):114–9. https://doi.org/10.1016/j.ypmed.2003.09.040.CrossRefPubMed

54.

Keyes KM, March D, Link BG, Chilcoat HD, Susser E. Do socio-economic gradients in smoking emerge differently across time by gender? Implications for the tobacco epidemic from a pregnancy cohort in California, USA. Soc Sci Med. 2013;76(1):101–6. https://doi.org/10.1016/j.socscimed.2012.10.011.CrossRefPubMed

55.

Bilal U, Beltrán P, Fernández E, et al. Gender equality and smoking: a theory-driven approach to smoking gender differences in Spain. Tob Control. 2015;25:295–300.CrossRef

56.

Schaap MM, Kunst AE, Leinsalu M, Regidor E, Espelt A, Ekholm O, et al. Female ever-smoking, education, emancipation and economic development in 19 European countries. Soc Sci Med. 2009;68(7):1271–8. https://doi.org/10.1016/j.socscimed.2009.01.007.CrossRefPubMed

57.

Monteiro CA, Conde WL, Popkin BM. Independent effects of income and education on the risk of obesity in the Brazilian adult population. J Nutr. 2001;131(3):881S–6S. https://doi.org/10.1093/jn/131.3.881S.CrossRef

58.

Smith KV, Goldman N. Socioeconomic differences in health among older adults in Mexico. Soc Sci Med. 2007;65(7):1372–85. https://doi.org/10.1016/j.socscimed.2007.05.023.CrossRefPubMed

59.

National Ministry of Education. Completion Plan for Primary and Secondary Studies (FinES). Buenos Aires; 2009. https://www.argentina.gob.ar/educacion/fines.

60.

NNational Ministry of Health. National Program on Tobacco Control. Buenos Aires; 2006. http://www.msal.gob.ar/ent/index.php/institucional/normativas.

61.

National Ministry of Health. National Strategy for the Prevention and Control of Non-communicable Diseases and the Healthy Argentina National Plan. Buenos Aires; 2009. http://www.msal.gob.ar/ent/index.php/institucional/normativas.

62.

Steele CJ, Schöttker B, Marshall AH, et al. Education achievement and type 2 diabetes—what mediates the relationship in older adults? Data from the ESTHER study: a population-based cohort study. BMJ Open. 2017;7:e013569.CrossRef

63.

Okura Y, Urban LH, Mahoney DW, Jacobsen SJ, Rodeheffer RJ. Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure. J Clin Epidemiol. 2004;57(10):1096–103. https://doi.org/10.1016/j.jclinepi.2004.04.005.CrossRefPubMed

64.

Patrick DL, Cheadle A, Thompson DC, Diehr P, Koepsell T, Kinne S. The validity of self-reported smoking: a review and meta-analysis. Am J Public Health. 1994;84(7):1086–93. https://doi.org/10.2105/AJPH.84.7.1086.CrossRefPubMedPubMedCentral

65.

Merlo J, Gerdtham U-G, Lynch J, et al. Social inequalities in health- do they diminish with age? Revisiting the question in Sweden 1999. Int J Equity Health. 2003;2:1–5.CrossRef

66.

McMunn A, Nazroo J, Breeze E. Inequalities in health at older ages: a longitudinal investigation of the onset of illness and survival effects in England. Age Ageing. 2009;38:181–7.CrossRef

67.

Beckett M. Converging health inequalities in later life - an artifact of mortality selection? J Health Soc Behav. 2000;41(1):106–19. https://doi.org/10.2307/2676363.CrossRefPubMed

Title: Educational inequalities, urbanicity and levels of non-communicable diseases risk factors: evaluating trends in Argentina (2005–2013)
Authors: Santiago Rodríguez López
Usama Bilal
Ana F. Ortigoza
Ana V. Diez-Roux
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Obesity
Obesity
Hypertension
Hypertension
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-11617-8

2024 ASCO Annual Meeting

Springer Medicine

Educational inequalities, urbanicity and levels of non-communicable diseases risk factors: evaluating trends in Argentina (2005–2013)

Abstract

Background

Methods

Results

Conclusion

2024 ASCO Annual Meeting

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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