Mortality from type 2 diabetes and implementation of the PREVENIMSS program: a time series study in Mexico, 1998-2015

Oswaldo Sinoe Medina-Gómez Ismael Seth Medina-Reyes About the authors

Abstract:

Type 2 diabetes is the leading cause of morbidity and mortality in the world. In Mexico it is the first cause of mortality, disability, and potential years of life lost due to premature death. The Mexican Institute of Social Security (IMSS) implemented the PREVENIMSS strategy. The aim of the current study was to estimate the program’s effect on the mortality trend from type 2 diabetes, based on an interrupted time series analysis. At the beginning of the target period, the diabetes mortality rate was higher in IMSS beneficiaries than in the control population. After the program’s implementation, there was a slight reduction in the mortality trend, while the control group showed an upward trend. Differences in the trends between the two groups suggest that they are not the exclusive result of institutional interventions. Living and work conditions could explain these differences.

Keywords:
Diabetes Mellitus; Mortality; Time Series Studies

Introduction

Non-communicable diseases are one of the most serious health challenges in the 21st century, and national development requires measures to avoid their expansion 11. World Health Organization. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization; 2010..

To deal with this challenge, the World Action Plan for the Prevention and Control of Non-Communicable Diseases was launched for 2013-2020, emphasizing the need for progress in the health system, reoriented and strengthened to improve early detection of persons with non-communicable diseases in order to avoid complications, reduce the need for hospitalizations and complex interventions, and prevent premature death 22. World Health Organization. Plan de acción mundial para la prevención y el control de las enfermedades no transmisibles 2013-2020. Geneva: World Health Organization; 2013..

Type 2 diabetes is the leading global cause of mortality and morbidity, affecting 285 to 347 million people in the world. Global prevalence of diabetes in 2014 was 10% and is expected to continue to increase 11. World Health Organization. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization; 2010.,22. World Health Organization. Plan de acción mundial para la prevención y el control de las enfermedades no transmisibles 2013-2020. Geneva: World Health Organization; 2013.,33. Danaei G, Finucane MM, Lu Y, Singh GM, Cowan MJ, Paciorek CJ, et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants. Lancet 2011; 378:31-40..

In Mexico, type 2 diabetes is the leading cause of mortality, years of life lost due to premature death, years with disability, and years of healthy life lost 44. Lozano R, Gómez-Dantés H, Garrido-Latorre F, Jiménez-Corona A, Campuzano-Rincón JC, Franco-Marina F, et al. La carga de enfermedad, lesiones, factores de riesgo y desafíos para el sistema de salud en México. Salud Pública Méx 2013; 55:580-94.. Prevalence of diagnosed diabetes in Mexico increased from 7% to 8.9% from 2006 to 2012 and increased with age, reaching its peak between 65 and 68 years. According to estimates, the incidence of diagnosed diabetes increased exponentially from 1960 to 2012. The projected rates in various incidence-by-age scenario suggest that prevalence of diabetes in adults may reach 13.7-22.5% by 2050 55. Meza R, Barrientos-Gutiérrez T, Rojas-Martínez R, Reynoso-Noverón N, Palacio-Mejía LS, Lazcano-Ponce E, et al. Burden of type 2 diabetes in Mexico: past, current and future prevalence and incidence rates. Prev Med 2015; 81:445-50..

Mexico’s health system is heterogeneous and fragmented 66. Laurell A. La reforma contra la salud y seguridad social. México DF: Ediciones Era; 1997.. The public health agencies consist mainly of the Mexican Institute of Social Security (IMSS) and the Institute of State Employees’ Social Security and Social Services (ISSSTE), based on a contributive system covering workers in the formal sector, while the agencies provide care to the population without social security like the program IMSS-Oportunidades (IMSS-O) and Popular Health Insurance (SPS). Meanwhile, the private sector consists of service providers working in private offices, clinics, and hospitals, besides purchase of services from insurance companies 77. Gómez-Dantés O, Sesma S, Becerril V, Knaul F, Arreola H, Frenk J. Sistema de salud de México. Salud Pública Méx 2011; 53 Suppl 2:S220-32..

In 2002, the IMSS implemented the PREVENIMSS strategy to respond to previously dispersed health measures and the epidemiological transition. A process of improvement in family medicine was implemented, including the Integrated Health Programs strategy, designed in 2001 and launched in 2002, with the acronym PREVENIMSS, merging the concept of prevention with the Institute’s initials. The strategy systematically organizes the provision of preventive services in five major programs: Children’s Health (up to 10 years of age), Adolescents’ Health (10 to 19 years), Women’s Health (20 to 59 years), Men’s Health (20 to 59 years), and Health of the Elderly (60 and older). The programs’ content was based on the magnitude, transcendence, impact, and susceptibility to the harms or risk factors for prevention 88. Gutiérrez G, Flores S, Fernández IH, Martínez OG, Velazco V, Fernández S, et al. Estrategia de prestación y evaluación de servicios preventivos. Rev Méd Inst Mex Seguro Soc 2006; 44 Suppl 1:S3-21.. The component of PREVENIMSS for the detection of type 2 diabetes aims to identify the change in blood glucose based on a capillary blood sample and reading with a blood glucose meter, timely diagnosis, and prevention of progression and the development of chronic complications. Screening for altered glucose tolerance was done each year at the beginning of the program and currently every three years in the population over 45 years of age, and starting at 20 years in individuals with overweight or obesity and a direct family history of diabetes.

Based on the above, the aim of the current study is to show the effect of the PREVENIMSS program on the mortality trend from type 2 diabetes in the IMSS beneficiary population.

Material and methods

A descriptive study was conducted, based on interrupted time series analysis, both pre-post type for the IMSS beneficiary population as well as pre-post, considering the threat to the internal validity or inferential validity derived from distinct external events in relation to target intervention known as a historical factor in such studies. The factor was controlled by studying and comparing with a control group, consisting of deaths in non-IMSS beneficiaries over 20 of age during the same period analyzed. Definition of type 2 diabetes was based on codes E11-E14 of the International Classification of Diseases, 10th revision. The National Health Information System of the Mexican Health Secretariat (SINAIS) was the source of annual death records from diabetes mellitus from 1998 to 2015 in persons over 20 years of age, according to state of residence and type of health service (Secretaría de Salud. Bases de datos de defunciones generales años 1998 a 2015. http://www.dgis.salud.gob.mx/contenidos/basesdedatos/BD_Cubos_gobmx.html, accessed on Feb/2017).

Importantly, SINAIS is administered by the General Division of Health Information, whose responsibilities defining parameters for death certificates, coordinating the elaboration of guides for exchange of health information, and serving as the official source of health information in Mexico.

The overall mortality rate for beneficiaries of the IMSS was defined as the number of deaths in the total population according to estimates conducted by the National Population Council (CONAPO), per 100,000 inhabitants (Proyecciones de la población 2010-2015. http://www.conapo.gob.mx/es/CONAPO/Proyecciones, accessed on Feb/2017), due to the lack of available information for identifying the IMSS beneficiary population per age group in 1998-2002. A direct adjustment of the mortality rate from type 2 diabetes was performed using Epidat (Xunta de Galicia, Spain; http://dxsp.sergas.es/default.asp).

The R statistical package, version 3.4.2 (The R Foundation for Statistical Computing, Vienna, Austria; http://www.r-project.org), was used for interrupted time series analysis, with 2002 as the reference year for the intervention, considering the initial implementation of the PREVENIMSS program, with the country of Mexico as the unit of analysis.

An ordinary least squares model was performed with the following formula:

Outcomejt= β0+ β1*timet+ β2*level+ β3*trendjt+ Ɛjt

The Durbin-Watson test was used to identify autocorrelation between the residuals, and a year-adjusted model was performed which identified statistically significant correlation, considering violation of the assumption of independence between the residuals and compromise to the reliability of the results of the model’s adjustment 99. Krämer W. Durbin-Watson test. In: Lovric M, editor. International encyclopedia of statistical science. Berlin: Springer; 2011. p. 408-9.,1010. Lopez-Bernal J, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 2017; 46:348-55..

Later, we calculated the generalized least squares adjusted for maximum likelihood 1010. Lopez-Bernal J, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 2017; 46:348-55. to identify changes in the historical trend of the disease and following implementation of PREVENIMSS in the beneficiary population. A comparison was performed with a control group consisting of the mortality rate in persons with other types of health services, thus not targeted by the program’s activities, using the following formula:

Outcomejkt= β0+ β1*timet+ β2*groupk+ β3*groupk* timet+ β4* levelt+ β5* trendjt+ β6* leveljt* groupk+ β7* trendjt* groupk+ Ɛjkt

Where β0 is the baseline result in the control group; β1 is the preexisting trend in the control group; β2 is the baseline difference between the control group and the intervention group; β3 is the preexisting difference in the trend between the control group and the intervention group; β4 is the level change in the control group; β5 is the trend change in the control group; β6 is the difference in the level change between the control group and the intervention group; and β7 is the slope change from the beginning of the intervention of the second variable of interest.

The hypothetical scenario constructed from the interrupted time series design is initially to identify the “expected” trend if the intervention had not taken place and is called the “counterfactual scenario”, that is, the scenario theoretically expected considering the historical trend; this first scenario provides a basis of comparison for the trend following the intervention.

Since the study was based on official sources and did not use private data, it was considered risk-free according to Chapter 1, Article 17 of Mexico’s General Law on Health Research.

Results

During the period studied, there were 1,229,877 deaths from diabetes, of which 526,110 were individuals covered by the IMSS. In the year 1998 the mortality rate from type 2 diabetes in the IMSS was higher than in the population not covered by the IMSS (Figure 1). However, in 2015 the diabetes mortality rate was higher in the population not covered (Table 1). The model exclusively analyzing the program’s effect on the beneficiary population points to a baseline mortality rate (intercept) of 26.3 per 100,000 beneficiaries; the time value shows an insignificant increase in the monthly mortality rate prior to the intervention (p = 0.04), while the level value (mortality rate after the intervention) increased by 4.1 per 100,000 beneficiaries, and the trend later decreased to 1.06 per year (Table 2).

Figure 1
Real and expected mortality trends from diabetes in Mexico, 1998-2015.

Table 1
Mortality rate (per 100,000 inhabitants) from type 2 diabetes in Mexico, 1998-2015.
Table 2
Interrupted time series analysis for mortality from type 2 diabetes.

In the mortality analysis of the IMSS beneficiary population, the Durbin Watson test showed a statistically significant negative correlation in time period 3, so it was necessary to shape the adjustment model based on this time period (Table 3).

Table 3
Results of Durbin-Watson test.

In the mortality analysis of the beneficiary population compared to the control group (not covered by the IMSS), the results of the Durbin-Watson test did not show correlation (Table 3).

The model built with the control group shows that at the start of the study period, diabetes mortality was higher in IMSS beneficiaries than in controls. The mortality trend from type 2 diabetes after the year in which PREVENIMSS program was implemented showed an increase in the monthly mortality rate of 6.6 deaths per 100,000 inhabitants on average, compared to the change in the mortality trend for the control group (p < 0.001), while the mortality trend in IMSS beneficiaries after 2002 showed a mean reduction of 3.6 deaths per 100,000 inhabitants (p < 0.001), compared to the control group (Table 2). The historical trend in the control group shows a statistically significant increase (p < 0.001) that exceeds that of the IMSS beneficiary population (Figure 1).

Discussion and conclusions

Time series analysis is widely used to assess policies or interventions in various scenarios 1111. Soumerai SB. How do you know which health care effectiveness research you can trust? A guide to study design for the perplexed. Prev Chronic Dis 2015; 12:E101.,1212. Lau WC, Murray M, El-Turki A, Saxena S, Ladhani S, Long P, et al. Impact of pneumococcal conjugate vaccines on childhood otitis media in the United Kingdom. Vaccine 2015; 33:5072-9.,1313. Elgar FJ, Pförtner TK, Moor I, De Clercq B, Stevens GW, Currie C. Socioeconomic inequalities in adolescent health 2002-2010: a time-series analysis of 34 countries participating in the Health Behaviour in School-aged Children study. Lancet 2015; 385:2088-95., including successful applications to evaluate public health programs 1212. Lau WC, Murray M, El-Turki A, Saxena S, Ladhani S, Long P, et al. Impact of pneumococcal conjugate vaccines on childhood otitis media in the United Kingdom. Vaccine 2015; 33:5072-9.,1414. Derde LP, Cooper BS, Goossens H, Malhotra-Kumar S, Willems RJL, Gniadkowski M, et al. Interventions to reduce colonisation and transmission of antimicrobial-resistant bacteria in intensive care units: an interrupted time series study and cluster randomised trial. Lancet Infect Dis 2014; 14:31-9.,1515. Dennis J, Ramsay T, Turgeon AF, Zarychanski R. Helmet legislation and admissions to hospital for cycling related head injuries in Canadian provinces and territories: interrupted time series analysis. BMJ 2013; 346:f2674.,1616. Grundy C, Steinbach R, Edwards P, Green J, Armstrong B, Wilkinson P. Effect of 20 mph traffic speed zones on road injuries in London, 1986-2006: controlled interrupted time series analysis. BMJ 2009; 339:b4469.. The strength of the analysis used with the control group is that the results allow showing the evidence of the effects of health interventions while controlling confounders that could compromise validity 1010. Lopez-Bernal J, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 2017; 46:348-55.. However, one should acknowledge that estimation of mortality rates according to age groups in IMSS beneficiaries in 1998-2002 does not necessarily reflect the real mortality rate.

As for the PREVENIMSS program’s effect on diabetes, some authors contend that the reduction in diabetes mortality rates could be explained both by changes in the incidence rates and changes in the case-fatality rates with early detection and treatment as a result of the potential effect of the PREVENIMSS program 1717. Borja-Aburto V, González-Anaya JA, Dávila-Torres J, Rascón-Pacheco RA, González-León M. Evaluation of the impact on non-communicable chronic diseases of a major integrated primary health care program in Mexico. Fam Pract 2016; 33:219-25., but there is no hard evidence in this direction. No evaluation of the program exists, and the studies that have been performed focus on identifying immediate changes in individuals’ behaviors, but without determining their long-term effects 1818. Figueroa-Suárez ME, Cruz-Toledo JE, Ortiz-Aguirre AR, Lagunes-Espinosa AL, Jiménez-Luna J, Rodríguez-Moctezuma JR. Estilo de vida y control metabólico en diabéticos del programa DiabetIMSS. Gac Méd Méx 2014; 150:29-34.,1919. Romero E, ZonanaNacach A, Colín M. Control de glucosa en pacientes que asistieron al programa de educación DiabetIMSS en Tecate, Baja California. Rev Cuba Med Gen Integr 2014; 30:317-25.,2020. León M, Araujo G, Linos Z. Eficacia del programa de educación en diabetes. Rev Méd Inst Mex Seguro Soc 2012; 51:74-9..

The study’s results indicate two scenarios in the IMSS beneficiary population. In one, mortality from type 2 diabetes decreased following implementation of PREVENIMSS in relation to the baseline year and modifying the historically upward trend in mortality from diabetes. The second scenario shows a significant contrast with the control group, with a significant increase in mortality. However, the differences between the groups associated with coverage versus non-coverage by the IMSS go beyond the factor targeted by the study, namely the PREVENIMSS strategy. It is necessary to investigate IMSS beneficiaries’ specific conditions that distinguish them from non-beneficiaries and that determine health conditions, diet, and social and economic status as they relate to diabetes. The main differences between the two groups feature employment status: while workers covered by the IMSS have formal employment with social and economic benefits, workers without social security generally lack job security and work in informal jobs, underemployment, and part-time or seasonal jobs with no benefits. These differences determine access to services, goods, food, and services that have a differential impact on social groups’ health conditions.

Various national strategies have been used to combat overweight, obesity, and diabetes 2121. Córdova JA, Barriguete JA, Radilla CC, Bourges H, Arakelian A, Aldunate L, et al. Estrategia 5 Pasos para la salud escolar. Programa Escuela y Salud. México DF: Secretaría de Educación Pública; 2012.,2222. Secretaría de Salud; Secretaría de Educación Pública. Guía de alimentos y bebidas. México DF: Secretaría de Salud/Secretaría de Educación Pública; 2014. http://alimentosescolares.insp.mx/guia.
http://alimentosescolares.insp.mx/guia...
,2323. Secretaría de Economía. Modificación de la Norma Oficial Mexicana NOM-051-SCFI/SSA1-2010. Especificaciones generales de etiquetado para alimentos y bebidas no alcohólicas preenvasados - información comercial y sanitaria. Diario Oficial de la Federación 2010; 5 abr., and the IMSS has launched specific programs under the PREVENIMSS strategy, like DiabetIMSS, despite major weaknesses that limit the follow-up of persons with the disease 2424. Zuñiga M, Villarreal E, Vargas E, Galicia L, Martínez L, Cervantes R. Perfil de uso de los servicios del módulo DiabetIMSS por pacientes con diabetes mellitus 2. Rev Enferm Inst Mex Seguro Soc 2013; 21:69-77..

In light of the above, studies are needed that address living and work conditions that determine lifestyles in order to explain differences in mortality from type 2 diabetes in the population covered by the IMSS when compared to individuals with access to other health services, with the aim of implementing programs that affect the structural and proximal social determinants of health 2525. Medina-Gómez O, López-Arellano O. Una aproximación a los determinantes sociales de la diabetes mellitus tipo 2. In: Chapela C, editora. En el debate: la diabetes en México. México DF: Universidad Autónoma Metropolitana Xochimilco; 2010. p. 25-52.. Current efforts focusing on lifestyle changes take a prevention-centered approach with individual responsibility 2626. Handelsman Y, Mechanick JI, Blonde L, Grunberger G, Bloomgarden ZT, Bray GA, et al. American Association of Clinical Endocrinologists medical guidelines for clinical practice for developing a diabetes mellitus comprehensive care plan. Endocr Pract 2011; 17 Suppl 2:1-53.,2727. Ávila-Jiménez L, Cerón D, Ramos-Hernández R, Velázquez L. Asociación del control glicémico con el apoyo familiar y el nivel de conocimientos en pacientes con diabetes tipo 2. Rev Méd Chil 2013; 141:173-80.,2828. Laguna-Alcaraz AD, Mejía-Rodríguez O, Rendón-Paredes AL, Villa-Barajas R, Paniagua R. Impact of a comprehensive intervention to families with teenage sons with overweight and obesity in a primary care setting: a case report. Diabetes Metab Syndr 2016; 11 Suppl 1:S195-200., despite evidence that obesity and diabetes require multisector action involving different sectors that contribute to the production, distribution, and marketing of foods while creating an environment that facilitates physical activity 11. World Health Organization. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization; 2010.. Meanwhile, health systems should join forces with other sectors to ensure that social determinants include the planning and provision of services in each community 22. World Health Organization. Plan de acción mundial para la prevención y el control de las enfermedades no transmisibles 2013-2020. Geneva: World Health Organization; 2013., since there are conditions outside the health system that determine glycemic control in individuals with diabetes 2525. Medina-Gómez O, López-Arellano O. Una aproximación a los determinantes sociales de la diabetes mellitus tipo 2. In: Chapela C, editora. En el debate: la diabetes en México. México DF: Universidad Autónoma Metropolitana Xochimilco; 2010. p. 25-52., thus requiring public policies that guarantee patients’ well-being with an inter-sector approach and social justice.

References

  • 1
    World Health Organization. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization; 2010.
  • 2
    World Health Organization. Plan de acción mundial para la prevención y el control de las enfermedades no transmisibles 2013-2020. Geneva: World Health Organization; 2013.
  • 3
    Danaei G, Finucane MM, Lu Y, Singh GM, Cowan MJ, Paciorek CJ, et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants. Lancet 2011; 378:31-40.
  • 4
    Lozano R, Gómez-Dantés H, Garrido-Latorre F, Jiménez-Corona A, Campuzano-Rincón JC, Franco-Marina F, et al. La carga de enfermedad, lesiones, factores de riesgo y desafíos para el sistema de salud en México. Salud Pública Méx 2013; 55:580-94.
  • 5
    Meza R, Barrientos-Gutiérrez T, Rojas-Martínez R, Reynoso-Noverón N, Palacio-Mejía LS, Lazcano-Ponce E, et al. Burden of type 2 diabetes in Mexico: past, current and future prevalence and incidence rates. Prev Med 2015; 81:445-50.
  • 6
    Laurell A. La reforma contra la salud y seguridad social. México DF: Ediciones Era; 1997.
  • 7
    Gómez-Dantés O, Sesma S, Becerril V, Knaul F, Arreola H, Frenk J. Sistema de salud de México. Salud Pública Méx 2011; 53 Suppl 2:S220-32.
  • 8
    Gutiérrez G, Flores S, Fernández IH, Martínez OG, Velazco V, Fernández S, et al. Estrategia de prestación y evaluación de servicios preventivos. Rev Méd Inst Mex Seguro Soc 2006; 44 Suppl 1:S3-21.
  • 9
    Krämer W. Durbin-Watson test. In: Lovric M, editor. International encyclopedia of statistical science. Berlin: Springer; 2011. p. 408-9.
  • 10
    Lopez-Bernal J, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 2017; 46:348-55.
  • 11
    Soumerai SB. How do you know which health care effectiveness research you can trust? A guide to study design for the perplexed. Prev Chronic Dis 2015; 12:E101.
  • 12
    Lau WC, Murray M, El-Turki A, Saxena S, Ladhani S, Long P, et al. Impact of pneumococcal conjugate vaccines on childhood otitis media in the United Kingdom. Vaccine 2015; 33:5072-9.
  • 13
    Elgar FJ, Pförtner TK, Moor I, De Clercq B, Stevens GW, Currie C. Socioeconomic inequalities in adolescent health 2002-2010: a time-series analysis of 34 countries participating in the Health Behaviour in School-aged Children study. Lancet 2015; 385:2088-95.
  • 14
    Derde LP, Cooper BS, Goossens H, Malhotra-Kumar S, Willems RJL, Gniadkowski M, et al. Interventions to reduce colonisation and transmission of antimicrobial-resistant bacteria in intensive care units: an interrupted time series study and cluster randomised trial. Lancet Infect Dis 2014; 14:31-9.
  • 15
    Dennis J, Ramsay T, Turgeon AF, Zarychanski R. Helmet legislation and admissions to hospital for cycling related head injuries in Canadian provinces and territories: interrupted time series analysis. BMJ 2013; 346:f2674.
  • 16
    Grundy C, Steinbach R, Edwards P, Green J, Armstrong B, Wilkinson P. Effect of 20 mph traffic speed zones on road injuries in London, 1986-2006: controlled interrupted time series analysis. BMJ 2009; 339:b4469.
  • 17
    Borja-Aburto V, González-Anaya JA, Dávila-Torres J, Rascón-Pacheco RA, González-León M. Evaluation of the impact on non-communicable chronic diseases of a major integrated primary health care program in Mexico. Fam Pract 2016; 33:219-25.
  • 18
    Figueroa-Suárez ME, Cruz-Toledo JE, Ortiz-Aguirre AR, Lagunes-Espinosa AL, Jiménez-Luna J, Rodríguez-Moctezuma JR. Estilo de vida y control metabólico en diabéticos del programa DiabetIMSS. Gac Méd Méx 2014; 150:29-34.
  • 19
    Romero E, ZonanaNacach A, Colín M. Control de glucosa en pacientes que asistieron al programa de educación DiabetIMSS en Tecate, Baja California. Rev Cuba Med Gen Integr 2014; 30:317-25.
  • 20
    León M, Araujo G, Linos Z. Eficacia del programa de educación en diabetes. Rev Méd Inst Mex Seguro Soc 2012; 51:74-9.
  • 21
    Córdova JA, Barriguete JA, Radilla CC, Bourges H, Arakelian A, Aldunate L, et al. Estrategia 5 Pasos para la salud escolar. Programa Escuela y Salud. México DF: Secretaría de Educación Pública; 2012.
  • 22
    Secretaría de Salud; Secretaría de Educación Pública. Guía de alimentos y bebidas. México DF: Secretaría de Salud/Secretaría de Educación Pública; 2014. http://alimentosescolares.insp.mx/guia.
  • 23
    Secretaría de Economía. Modificación de la Norma Oficial Mexicana NOM-051-SCFI/SSA1-2010. Especificaciones generales de etiquetado para alimentos y bebidas no alcohólicas preenvasados - información comercial y sanitaria. Diario Oficial de la Federación 2010; 5 abr.
  • 24
    Zuñiga M, Villarreal E, Vargas E, Galicia L, Martínez L, Cervantes R. Perfil de uso de los servicios del módulo DiabetIMSS por pacientes con diabetes mellitus 2. Rev Enferm Inst Mex Seguro Soc 2013; 21:69-77.
  • 25
    Medina-Gómez O, López-Arellano O. Una aproximación a los determinantes sociales de la diabetes mellitus tipo 2. In: Chapela C, editora. En el debate: la diabetes en México. México DF: Universidad Autónoma Metropolitana Xochimilco; 2010. p. 25-52.
  • 26
    Handelsman Y, Mechanick JI, Blonde L, Grunberger G, Bloomgarden ZT, Bray GA, et al. American Association of Clinical Endocrinologists medical guidelines for clinical practice for developing a diabetes mellitus comprehensive care plan. Endocr Pract 2011; 17 Suppl 2:1-53.
  • 27
    Ávila-Jiménez L, Cerón D, Ramos-Hernández R, Velázquez L. Asociación del control glicémico con el apoyo familiar y el nivel de conocimientos en pacientes con diabetes tipo 2. Rev Méd Chil 2013; 141:173-80.
  • 28
    Laguna-Alcaraz AD, Mejía-Rodríguez O, Rendón-Paredes AL, Villa-Barajas R, Paniagua R. Impact of a comprehensive intervention to families with teenage sons with overweight and obesity in a primary care setting: a case report. Diabetes Metab Syndr 2016; 11 Suppl 1:S195-200.

Publication Dates

  • Publication in this collection
    10 May 2018

History

  • Received
    15 June 2017
  • Reviewed
    29 Nov 2017
  • Accepted
    07 Dec 2017
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz Rio de Janeiro - RJ - Brazil
E-mail: cadernos@ensp.fiocruz.br