Diabetes treatment and control: the effect of public health insurance for the poor in Mexico

512 Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Diabetes treatment and control: the effect of public health insurance for the poor in Mexico Sandra G Sosa-Rubí,a Omar Galárraga b & Ruy López-Ridaura c Objective To analyse the effect of enrolment in the public health insurance scheme known as Seguro Popular [People’s Insurance] on access to health resources, treatment and blood glucose control among poor adults with diabetes in Mexico. Methods We analysed cross-sectional data from the 2006 National Health and Nutrition Survey and compared health care access and biological health outcomes, specifically glycosylated haemoglobin (HbA1c) levels, among adults with diabetes who were enrolled in the Seguro Popular (treatment group) and those who had no health insurance (control group). Standard propensity score matching was used to create a highly comparable control group. Findings Adults with diabetes who were enrolled in the Seguro Popular had significantly more access than comparable uninsured adults to some type of blood glucose control test (by a difference of 9.5 percentage points; 95% confidence interval, CI: 2.4–16.6) and to insulin injections (3.13 more per week; 95% CI: 0.04–6.22). Those with insurance were also significantly more likely to have appropriately-controlled blood glucose levels (HbA1c £ 7%) than their uninsured counterparts (by a difference of 5.6 percentage points; 95% CI: 0.9–10.3). Very poor glucose control (HbA1c > 12%) was found in a significantly smaller proportion of adults in the insured group than in the uninsured group (by a difference of 17.5 percentage points; 95% CI: 6.5–28.5). Conclusion The Seguro Popular appears to have improved access to health care and blood glucose control among poor adults with diabetes in Mexico, and it may have had a positive effect on the management of other chronic health conditions, but its long-term effects are yet to be demonstrated. Although the findings are most relevant to Mexico, they may also be applicable to other developing countries seeking to improve health-care coverage for the poor by expanding their public health insurance programmes. Une traduction en français de ce résumé figure à la fin de l’article. Al final del artículo se facilita una traducción al español. .ةلاقلما هذهل لماكلا صنلا ةياهن في ةصلاخلا هذهل ةيبرعلا ةمجترلا a National Institute of Public Health, Health Economics Division, Av. Universidad 655, Cuernavaca, CP 62100, Mexico. b Institute of Business and Economic Research, University of California, Berkeley, CA, United States of America. c Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico. Correspondence to Omar Galárraga (e-mail: ogalarraga@insp.mx). (Submitted: 17 March 2008 – Revised version received: 20 October 2008 – Accepted: 11 November 2008 – Published online: 26 May 2009 ) Introduction Lack of health insurance can deprive the poor of access to services or put them at risk of financial hardship. To protect the poor against excessive health expenditures, many coun- tries have implemented mechanisms such as community- based health insurance,1,2 national health insurance3–6 and targeted public health insurance.7,8 Mexico has multiple health insurance providers. The Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado [State Employee’s Social Security and Social Ser- vices Institute, ISSSTE] provides coverage for government employees and the Instituto Mexicano del Seguro Social [Mexi- can Social Security Institute, IMSS] covers for private-sector employees. By 2001, however, nearly half of the Mexican working-age population had no health insurance.9 The Seguro Popular [People’s Insurance], launched that year, represented a major effort to protect the working-age population against steep health-care costs. Enrolment in the Seguro Popular is not dependent on health status or pre-existing illness, there is no co-payment in accordance with the type of health care received, and family contributions are determined solely by ability to pay.10 Medical interventions are offered mainly through the public health network. The Seguro Popular, which covers health care for many diseases, including cancer, asthma, anaemia, pneumonia and diabetes,11 was implemented gradually between 2001 and 2005, but only in communities with health units having ac- creditation, that is, the proven capacity – medical resources, personnel and infrastructure, etc. – to provide the health interventions covered by the Seguro Popular. Thus, during the implementation phase, people chose to enrol based largely on programme availability at the regional level, and this, in turn, was determined by health infrastructure capacity. Background According to WHO estimates, by 2030, approximately 366 million adults will have diabetes (type 2 in over 90% of the cases), and 75% of these adults will be living in developing countries.12 In Mexico, type 2 diabetes is the leading cause of death among adults, according to the 2007 National Death Registry.13 Data from the 2005–2006 cross-sectional Encuesta Nacional de Salud y Nutrición [National Health and Nutrition Survey, ENSANUT] showed that 7.1% of adults reported having been diagnosed with type 2 diabetes by a physician.14 Test results based on fasting blood serum samples collected for the ENSANUT suggest that a large number of Mexican adults have undiagnosed diabetes and that the estimated overall prevalence of diabetes is about 14%. (S Villalpando, personal communication). Diabetes requires life-long treatment and periodic clinical follow-up. Health care is needed on a regular basis to attain good control of blood glucose levels, blood pressure, blood 513Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes controlSandra G Sosa-Rubí et al. lipids and body weight; to reduce or delay the onset of complications, and to delay or prevent death from the disease. Periodic health-care visits (three to four per year, according to Mexican and in- ternational guidelines) should include laboratory testing to assess the need for more aggressive therapy.15,16 Lifestyle intervention, including a healthy diet and physical activity, is the first line of treatment for diabetes, but the American Diabetes Association and the European Association for the Study of Diabetes17 recommend aggressive treatment of the disease, including early initiation of insulin therapy. Diabetes management also involves close moni- toring for chronic complications affect- ing the kidneys, eyes or feet.15,16 In Mexico, the total annual cost of managing diabetes and its complica- tions in 2000 was estimated at over 15 billion United States dollars (US$), of which approximately US$ 765 mil- lion represented direct medication costs.18 In that same year, an estimated 44% of adults who had been previously diagnosed with diabetes in Mexico re- ported having no health insurance.19 Diabetic patients who lack health insur- ance are less likely to adhere to medical care.20 The Seguro Popular was intended to improve the treatment options and laboratory tests available to Mexicans with diabetes, as well as to ensure their access to appropriate medication. Previous empirical research sug- gests that people who are Seguro Popu- lar beneficiaries have better access to health care than those who are not. Bleich et al.21 found that hypertensive adults enrolled in the Seguro Popular were more likely to be treated for high blood pressure and to attain good control. Sosa-Rubí et al.22 found that pregnant women enrolled in the Seguro Popular were more likely to receive for- mal obstetric care. This paper examines the effect of Seguro Popular enrolment on access to health care, specifically health resources (medical visits, laboratory tests and use of medication, including insulin injec- tions), and on blood glucose control (as measured by glycosylated haemoglobin, HbA1c, the gold standard for blood glucose control surveillance).15,16 An HbA1c test is required at least twice a year for diabetes patients with stable blood glucose and at least four times a year for patients without stable blood glucose or for those who have just begun or changed therapy.16 To reduce confounding in the observational data analysed, we used propensity score matching to estimate the average treat- ment effect, with “treatment” defined as enrolment in the Seguro Popular. Our working hypothesis was that enrolment in the Seguro Popular im- proves access to treatment and health outcomes among patients with diabe- tes. This hypothesis is consistent with the stated goal of the Seguro Popular: to improve access to qualified and special- ized health services among poor and uninsured Mexicans. Methods From the 2005–2006 ENSANUT we obtained data on treatment, medical care and biological outcomes in dia- betes patients.14 The ENSANUT is a nationally representative survey that in 2005–2006 had a sample of 48 304 households and 206 700 individuals. We selected a subsample of 2960 adults with diabetes (i.e. adults who had been diagnosed with diabetes by a physician or who reported being under treat- ment for diabetes). After we excluded pregnant women with hyperglycaemia (assumed to have gestational diabetes), adults with access to social security ser- vices, and responses with missing data, our final sample for analysis included 1491 adults (Fig. 1). Adults (aged 20–80 years) provided the following information: number of visits to physicians for diabetes control; frequency and type of treatment (diet, alternative medicines or standard drug therapy, such as insulin and oral hypo- glycaemic agents); and access to labora- tory tests, including testing frequency. In addition, a random subsample of Fig. 1. Selection of participants: a flow diagram 48 304 Households participating in National Health and Nutrition Survey (ENSANUT), 2006 206 700 Individuals 2 960 Adults with diabetes Drop those with access to social security services, missing values and women with gestational diabetes 1 491 Observations in “analytical sample” patients (n = 1115) was selected for HbA1c testing. Variables We analysed access outcomes and biological outcomes. The first included access to laboratory tests; four or more yearly visits to a physician for diabe- tes control; treatment with any drug, including insulin; number of weekly insulin injections (if on insulin); and number of blood glucose control tests per month. Biological outcomes were based on blood glucose control, as determined by HbA1c levels. We constructed two indicators of glucose control on the basis of recommended levels of HbA1c. Patients were initially categorized as having “appropriate glucose control” (HbA1c £ 7%) or “poor glucose con- trol” (HbA1c > 7%) and were then further classified in accordance with the more extreme values: “very poor glucose control” (HbA1c > 12%) or “appropriate and poor glucose control” (HbA1c £ 12%). Patients in the “very poor glucose control” category were those having the poorest outcomes and the highest risk of premature death and complications.23 For analysis, health insurance status, as reported by surveyed indi- viduals, was the exposure variable. We compared individuals enrolled in the Seguro Popular (“treatment” category) with individuals who reported having no insurance (control category). We assessed characteristics of the individual, the household and the state as treatment predictors: for the individual, age, sex, education and ethnicity; for the household, family as- sets (as a proxy for family wealth) and 514 Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes control Sandra G Sosa-Rubí et al. rural or urban residential area; for the state, the general region of the country (north, east central, west central and south–southeast). We also considered potential confounders (e.g. using body mass index, BMI, as a proxy for lifestyle) and time since diabetes was diagnosed. Finally, data from Mexico’s 2005 Registro Nacional de Infraestructura en Salud [National Registry of Health Infrastructure] was added to determine whether the availability of health profes- sionals (i.e. the numbers of physicians and nurses) and health units per 1000 population modified the treatment ef- fect.24 To estimate the number of physi- cians, nurses and health units per 1000 population, we used 2005 census data for municipalities generated by Mexico’s National Geographical Institute.25 Statistical methods Because enrolment in the Seguro Popu- lar is voluntary, health insurance status is not randomly allocated and the data may be subject to self-selection bias. To reduce this bias, we used standard propensity score matching. We first constructed a propensity score that estimated the probability of enrol- ment in the Seguro Popular given a set Table 1. Sociodemographic characteristics of adults with diabetes enrolled in the Seguro Popular and of uninsured adults, Mexico, 2006 Unmatched samples Matched samples Percentage reduction in biasSeguro Popular a n = 430 Uninsureda n = 1061 t-test P-value Seguro Popular a n = 425 Uninsureda n = 1029 t-test P-value Individual characteristic Sex Maleb 30.9 40.1 Female 69.1 59.9 0.001 68.9 69.9 0.115 89.1 Age, in years 20–39 17.5 16.3 0.558 17.2 15.1 0.709 –69.0 40–59 50.0 48.2 0.518 50.12 55.3 0.002 –179 60–79 29.4 31.8 0.378 29.7 26.6 0.109 –30.7 ³ 80b 3.0 3.9 Marital status Married 73.1 64.8 0.002 72.9 80.2 0.000 12.5 Unmarriedb 26.7 35.3 Education Noneb 21.4 21.6 Primary 66.8 57.7 0.001 66.8 64.2 0.018 72.5 Secondary 8.7 12.6 0.032 8.7 8.5 0.166 94.0 High school/college 2.8 8.4 0.000 2.8 3.0 0.000 95.8 Ethnicity (self-identified) Indigenous 23.8 23.3 0.830 24.1 26.8 0.016 –442 Not indigenousb 76.3 76.7 Family assets Mean (asset index)c –0.504 –0.235 0.000 –0.495 –0.433 0.000 76.9 Regional characteristic Area of residence Metropolitan 20.9 42.0 0.000 20.9 22.1 0.000 94.5 Urban 39.9 32.3 0.005 40.0 37.6 0.049 69.4 Ruralb 39.4 25.8 Region of residence North 16.4 19.7 0.136 16.5 13.4 0.001 8.4 East central 15.7 26.9 0.000 15.8 15.1 0.002 93.7 West central 39.6 26.3 0.000 39.5 39.8 0.000 98.3 South–southeastb 27.9 26.9 a Values are percentages, unless otherwise noted; percentages may not add up to 100% due to rounding error. b Omitted (reference) category. Table reports nearest neighbour matching with common support. The t test for each covariable may show statistical significance for the variable evaluated for the entire sample; however, for the propensity score, t tests for insignificant differences were conducted at each propensity score block (results not shown). The percentage of bias reduction reports reduction in absolute bias between the treatment category (Seguro Popular enrollees) and the control category (the uninsured) as a percentage of the square root of the average of the sample variances in the treated and non-treated groups.31 c The asset index is based upon household infrastructure, building materials, and ownership of certain durable assets, as a proxy for household’s wealth. It may be negative because it is constructed with principal components analysis. A more negative index indicates lower household wealth. Estimations based on data from the 2006 Encuesta Nacional de Salud y Nutrición.14 515Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes controlSandra G Sosa-Rubí et al. Table 2. Logistic modela of the propensity score to estimate the effect of Seguro Popular enrolment on diabetes treatment and control in Mexico, 2006 (n = 1479) Variable Probability of enrolment in the Seguro Popular Coefficient Z-value P-value Individual characteristic Sex Female 0.43 3.27 0.001 Age, in years 20–39 0.44 1.16 0.246 40–59 0.28 0.78 0.434 60–79 0.11 0.3 0.763 Marital status Married 0.43 3.06 0.002 Education Primary school 0.18 1.15 0.249 Secondary school –0.20 –0.77 0.444 High school/university –0.61 –1.67 0.094 Ethnicity Indigenous –0.13 –0.88 0.381 Household characteristic Family assets –0.26 –3.41 0.001 Regional characteristic Area of residence Metropolitan –0.03 –0.18 0.860 Urban –0.80 –4.77 0.000 Region of residence North 0.23 1.19 0.233 East-central –0.43 –2.39 0.017 West-central 0.48 3.1 0.002 a Log-likelihood ratio test, c² (degrees of freedom): 139.15 (15); probability > c² = 0.000. of predictors, and we then created a control group (uninsured) and a treat- ment group (insured) having similar propensity scores. We used a logistic regression model to estimate the con- ditional probability of Seguro Popular enrolment, given a set of covariates (X). Nearest neighbour matching allowed us to match insured and uninsured individuals with similar propensity scores.26,27 If outcomes are assumed to be in- dependent of programme participation after controlling for propensity score, the average treatment effect is: ATT = E [E [Y1| SPi = 1, p(Xi )] – E [Y0 | SPi = 0, p(Xi )]] where SPi = 1 if the individual is en- rolled in the Seguro Popular and SPi = 0 if not; and where the expectations [E] are conditional on treatment status, as represented by the vertical bar. ATT is the difference between the mean outcomes for those treated (Y1) and for those untreated (Y0), after controlling for observed variables with the propen- sity score p(Xi ). To ensure comparability, we tested the balancing property: pre-treatment covariates did not differ statistically between Seguro Popular enrolees and people without health insurance. 28 We followed the algorithm suggested by Dehejia and Wahba29,30 to find the best model specification. The method in- volved the use of different specifications until we obtained a balanced distribu- tion of the following covariates: sex, age, family asset index, residence area, residence region, ethnicity, education and marital status. Furthermore, we estimated the percentage bias reduction by calculating the difference in absolute bias between treated and control groups as a percentage of the square root of the average of the sample variances.31 We performed sensitivity analysis to test the association of HbA1c results with the potential lifestyle confounders (using BMI as a proxy for lifestyle) and the time since diabetes was first diag- nosed. We also checked the indepen- dent effect of Seguro Popular enrolment and of health professional availability on the coverage of diabetes treatment and control. This involved estimating a multivariate model using matched data for two outcomes: regular use of any blood glucose control test and propor- tion of patients with “very poor glucose control”. We adjusted the multivariate model with clustering for the potential effect modifier of health professional availability, as determined by the num- ber of physicians, nurses and health units in a given location compared with the median for the entire municipality. Results Table 1 presents the sociodemographic characteristics of the uninsured popula- tion and of the population enrolled in the Seguro Popular. The table shows both raw (unmatched) and matched means. In the unmatched sample, adults enrolled in the Seguro Popular had less formal education and fewer family assets but were more likely to be female and married and to live in rural areas and in Mexico’s West central and South–southeast regions, than unin- sured adults. In the matched samples, the differences between Seguro Popular enrolees and uninsured individuals (i.e. the bias) 31 were considerably smaller for most of the variables. The t test for some predictors still showed statisti- cal significance for the entire sample; however, for the propensity score esti- mation, the t test showed statistically insignificant differences for the covari- ables at each of the seven propensity score blocks (results not shown). Table 2 shows the logistic regres- sion model for propensity scores. In the model, females and married people were more likely to be enrolled in the Seguro Popular, as were adults with diabetes who had fewer assets or who lived in rural areas or in the west central region. Table 3 presents differences in health outcomes between individuals with and without insurance. Those en- rolled in the Seguro Popular reported, on average, greater access to blood glucose control tests of any type (including 516 Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes control Sandra G Sosa-Rubí et al. Table 3. Average effect of enrolment in the Seguro Popular in terms of diabetes treatment and control, Mexico, 2006a Outcome variable Mean Unmatched Matched Seguro Popular Uninsured Unmatched differenceb t-value P-value Matched ATTc (95% CI) t-value P-value Health care access outcome Regular use of any blood glucose control testd 0.809 0.754 0.055 2.300 *** 0.095 (0.020-0.161) 2.626 *** No. of insulin users 0.0415 0.0479 –0.0064 –0.504 NS 0.001 (–0.032-0.034) 0.066 NS No. of insulin shots per week among insulin users 12.6 8.99 3.600 2.922 *** 3.133 (0.04-6.22) 1.988 ** No. of blood sugar control tests per month 1.02 0.87 0.144 0.825 NS 0.142 (0.024-0.260) 2.371 *** Four or more physician visits per year 0.918 0.811 0.107 4.795 *** 0.093 (0.032-0.154) 3.019 *** Biological outcome Proportion of diabetics with appropriate glucose control e 0.089 0.074 0.015 0.624 NS 0.056 (0.009-0.103) 2.316 *** Proportion of diabetics with very poor glucose control f 0.367 0.462 –0.095 –2.122 *** –0.175 (–0.285-0.065) –3.159 *** **P < 0.05; ***P < 0.01, using t tests, of mean differences between treatment and control (unmatched and matched) groups. ATT, average treatment effect on the treated; CI, confidence interval; NS, not significant. a The data are not weighted. b This is the raw difference between unmatched samples, or the difference between the mean observed in Seguro Popular enrollees and the mean observed in the uninsured population. c The ATT is based on the differences in mean outcome for propensity-score-matched individuals using nearest neighbour matching. d Tests may include urine or capillary blood reactive strips, blood glucose, or glycosylated haemoglobin (HbA1c). e Appropriate glucose control (HbA1c £ 7%) compared with poor glucose control (HbA1c > 7%). f Very poor glucose control (HbA1c > 12%) compared with normal and poor glucose control (HbA1c £ 12%). urine and capillary blood reactive strips) and more blood glucose control tests per month. After propensity matching, these differences became significant. The proportion of adults with diabetes who were under insulin treatment was similar between groups, and matched differences were not significant. How- ever, among adults who used insulin, those enrolled in the Seguro Popular received, on average, 3.13 more insulin injections per week than those without insurance. Uninsured insulin users re- ceived a median of seven insulin injec- tions per week (probably one injection per day), while insured insulin users received a median of 14 insulin injec- tions per week (probably two injections per day). In addition, those enrolled in the Seguro Popular had more blood glucose tests per month and a greater likelihood of having visited a physician four times or more per year. Finally, Seguro Popular enrolees had appropriate glucose control, based on HbA1c levels, in greater propor- tion than uninsured patients (8.9% versus 7.4%, respectively). Conversely, uninsured patients had very poor glu- cose control in greater proportion than Seguro Popular enrolees (46.2% versus 36.7%, respectively). On the basis of propensity score matching, the average treatment effect was an increase of 5.6 percentage points in those with appro- priate control and a decrease of 17.5 percentage points in those with very poor glucose control. These differences are of obvious clinical importance. In sensitivity analyses, we examined whether the number of physicians, nurses or health units per 1000 popula- tion altered the model in terms of the regular use of some type of blood glu- cose control test. After adjustment for Seguro Popular enrolment, no odds ratio (OR) showed statistical significance. However, the interaction term that showed a greater availability of physi- cians among Seguro Popular enrolees was significant and positive. People insured through the Seguro Popular and who lived in municipalities with an above-median number of physicians per 1000 population had considerably higher odds of regularly using any glu- cose control test (OR: 15.85; z-statistic: 2.62). We then analysed the interaction between the number of physicians, nurses and health units per 1000 population and the “very poor glucose control” indicator. Municipalities with more health units per 1000 popula- tion had a greater likelihood of being the place of residence of those with “very poor glucose control” (OR: 3.17; z-statistic: 2.08). Similarly, Seguro Popu- lar enrolees and people living in areas with more nurses per 1000 population had a greater likelihood of not having “very poor glucose control” (OR: 4.59; z-statistic: 1.75). Sensitivity analyses showed that the association between potential con- founders (BMI as proxy for lifestyle and time since diabetes first diagnosed) and health-care outcomes was not significant. Such confounders were sig- nificantly associated with the biologi- cal outcomes but did not substantially modify the results presented already. The additional covariates showed no sig- nificance in the propensity score model. 517Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes controlSandra G Sosa-Rubí et al. Résumé Traitement des diabètes et lutte contre ces maladies : effet de la couverture par l’assurance santé publique de la population pauvre du Mexique Objectif Analyser l’effet de la couverture par le schéma d’assurance santé publique appelé Seguro Popular (Assurance du peuple) sur l’accès aux ressources de santé, au traitement et au contrôle de la glycémie pour les adultes pauvres et diabétiques du Mexique. Méthodes Nous avons analysé des données transversales provenant de l’Enquête nationale sur la santé et la nutrition de 2006 et comparé l’accès aux soins de santé et les résultats biologiques, notamment les taux d’hémoglobine glyquée (HbA1c), chez des adultes diabétiques bénéficiant de Seguro Popular (groupe traité) et chez des adultes diabétiques dépourvus d’assurance santé (groupe témoin). On a fait appel à l’appariement par scores de propension standard pour constituer un groupe témoin hautement comparable. Résultats Les adultes diabétiques bénéficiant de Seguro Popular disposaient d’un accès significativement plus important que les adultes comparables non assurés à certains types de contrôles de la glycémie (différence de 9,5 points de pourcentage ; intervalle de confiance à 95 %, IC : 2,4-16,6) et aux injections d’insuline (3,13 de plus par semaine ; IC à 95 % : 0,04-6,22). Les individus assurés avaient une probabilité significativement plus élevée de présenter une glycémie correctement contrôlée (HbA1c £ 7 %) que leurs homologues non assurés (différence de 5,6 points de pourcentage ; IC à 95 % : 0,9-10,3). On a relevé une proportion significativement plus faible d’adultes présentant un contrôle de la glycémie très insatisfaisant (HbA1c > 12 %) dans le groupe assuré que dans le groupe non assuré (différence de 17,5 points de pourcentage ; IC à 95 % : 6,5-28,5). Conclusion L’assurance Seguro Popular semble avoir amélioré l’accès aux soins de santé et au contrôle de la glycémie pour les adultes pauvres et diabétiques du Mexique et pourrait avoir eu un effet positif sur la prise en charge d’autres maladies chroniques. Néanmoins, ses effets à long terme restent à démontrer. Si ces résultats concernent principalement le Mexique, ils peuvent aussi être applicables à d’autres pays en développement désireux d’améliorer la couverture des plus démunis par les soins de santé à travers l’élargissement de leurs programmes d’assurance santé publique. Discussion The findings of this study suggest that the Seguro Popular has improved both access to health services and biological health outcomes among adults with diabetes. Over the past 20 years, various countries in Latin America – Argentina, Brazil, Chile and Colombia – have implemented health insurance reform to improve the coverage of marginal- ized groups.32 The current study dem- onstrates the success of an insurance programme targeted to the poor in Mexico. Its results may be relevant for other populations living in a similar socioeconomic setting and may help to shape programmes for improving ac- cess to health services and health status among the poor. Although adults with diabetes who were Seguro Popular enrolees had better access to health care and better blood glucose level control, the effect of en- rolment on biological outcomes was modest: a large proportion of both the insured and uninsured remained in the “very poor glucose control” category. It is too early to determine whether the Seguro Popular will reduce premature deaths from the chronic complications of diabetes, but continued emphasis on quality of care and treatment will be necessary to meet this long-term goal. Limitations This study has limitations. It is cross- sectional, hence it captures only a single point in time. Responses to questions about the past are subject to recall bias. Furthermore, self-reported outcomes, such as the number of visits to a phy- sician, are subject to reporting bias. The biological tests performed provide more objective measures. Although we controlled for many variables that influence insurance choice (including age, sex, marital status and residential region), other factors (e.g. genetic or environmental) could also make an individual more prone to diabetes and less likely to enrol in the Seguro Popu- lar. We also assumed (as is common in studies with propensity score matching) that unobservable components could be ignored. Health insurance for the poor is a relatively new concept and its effect has not been widely evaluated yet. The results provided here are among the very few based on an assessment of individual health status indicators. As the Seguro Popular programme is quite new, these are early results; effects over the longer term should be the subject of future research. ■ Acknowledgements We thank Heleen Vermandere for her research assistance and the two anony- mous reviewers for their helpful com- ments and constructive suggestions. Funding: This work was initially car- ried out within the context of Mexico’s National Institute of Public Health’s evaluation of the Seguro Popular com- missioned by the Health Ministry of Mexico (SSA). Competing interests: None declared. 518 Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes control Sandra G Sosa-Rubí et al. صخلم كيسكلما في ءارقفلا لىع يمومعلا يحصلا ينمأتلا رثأ :يركسلا طبضو ةجلاعم مساب فورعلما يمومعلا يحصلا ينمأتلا ماظن جاردإ رثأ ليلحت :فدهلا ركس طبضو ةجلاعمو ةيحصلا دراولما لىإ لوصولا لىع »يبعشلا ينمأتلا« .كيسكلما في ينيركسلا نم ءارقفلا ينغلابلا ينب مدلا ةحصلل ينطولا حسملل ضيرعلا عطقلما تايطعم نوثحابلا للح :ةقيرطلا ةيحصلا لئاصحلاو ةيحصلا ةياعرلل لوصولا ةيلمع اونراقو 2006 ةيذغتلاو ينغلابلا ىدل HbAc1 يزوكيلغلا ينبولغوميهلا تايوتسم مايسلاو ،ةيجولويبلا ينبو )ةجلاعلما ةعومجم( ”يبعشلا ينمأتلا“ ماظن نمض ينجردلما ينيركسلا ًازرح اومدختساو .)دهاوشلا ةعومجم( ماظنلا كلذ نمض ينجردلما يرغ .ةيلاع ةجردب ةنراقملل ةلباق دهاوش ةعومجم ءاشنلإ ةمءاوملل ًايرايعم ينمأتلا“ ماظن نمض نوجردلما نويركسلا نوغلابلا عتمتي :تادوجولما عتمتي مام ثركأ مدلا ركس طبض تارابتخا طانمأ ضعبل لوصوب ”يبعشلا ةقث لاجبم طاقنلا نم ةئلماب 9.5 لىإ لصي قرفلاو( ماظنلاب ينجردلما يرغ هب ةقث لاجبم عوبسأ لكل ثركأ 3.13( ينلوسنلإا نقحلو )16.6 – 2.4 :95% ةيرهاظلا زوكولغلا طبض تايوتسم نوكت نأ بلغيو .)6.22 – 0.04 :95% مام ينمأتلاب ينعتمتلما ىدل ثركأ ،)7% نع لقي وأ لداعي HbAc1 ىوتسم( لاجبم ،ةيوئلما طاقنلا نم 5.6 قرافب( ينمأتلاب ينعتمتلما يرغ نم مهنارقأ ىدل زوكولغل ادج ئسلا طبضلا تايوتسم تدجوو .)10.3 – 0.9 :95% ةيقوثوم ينغلابلا ةعومجم ىدل ايرثك لقأ ةبسنب )12% نم ثركأ HbAc1( مدلا نم 17.5 قرافب( ينمأتلاب ينعتمتلما يرغ ةعومجم ىدل مام ،ينمأتلاب ينعتمتلما .)28.5 – 6.5 : 9.5% ةيقوثوم لاجبمو ةيوئلما طاقنلا ةياعرلل لوصولا ةيناكمإ نم يبعشلا ينمأتلا ماظن نسح دقل :جاتنتسلاا ،كيسكلما في ينيركسلا ءارقفلا ينغلابلا ينب مدلا زوكولغ طبضو ةيحصلا لاإ ،ىرخلأا ةنمزلما ةيحصلا تلااحلا يربدت لىع بياجيإ يرثأت هل نوكي دقو ةقلاع تاذ تادوجولما نأ مغرو .دعب حضتت لم دملأا ةديعبلا هتايرثأت نأ نع ثحبت يتلا ىرخلأا ةيمانلا نادلبلا لىع قبطنت دق اهنإف ،كيسكلماب ثركأ ينمأتلا جمارب عيسوت للاخ نم ءارقفلل ةيحصلا ةياعرلاب ةيطغتلا ينسحت .اهيف يمومعلا يحصلا References 1. Ranson MK. Reduction of catastrophic health care expenditures by a community-based health insurance scheme in Gujarat, India: current experiences and challenges. Bull World Health Organ 2002;80:613-21. PMID:12219151 2. Wang H, Yip W, Zhang L, Wang L, Hsiao W. Community-based health insurance in poor rural China: the distribution of net benefits. Health Policy Plan 2005;20:366-74. PMID:16143589 doi:10.1093/heapol/czi045 3. Chu TB, Liu TC, Chen CS, Tsai YW, Chiu WT. Household out-of-pocket medical expenditures and national health insurance in Taiwan: income and regional inequality. BMC Health Serv Res 2005;5:60. PMID:16137336 doi:10.1186/1472-6963-5-60 4. Obermann K, Jowett MR, Alcantara MO, Banzon EP, Bodart C. Social health insurance in a developing country: the case of the Philippines. Soc Sci Med 2006;62:3177-85. PMID:16406248 doi:10.1016/j.socscimed.2005.11.047 5. Wagstaff A, van Doorslaer E. Catastrophe and impoverishment in paying for health care: with applications to Vietnam 1993-1998. Health Econ 2003;12:921-34. PMID:14601155 doi:10.1002/hec.776 6. Limwattananon S, Tangcharoensathien V, Prakongsai P. Catastrophic and poverty impacts of health payments: results from national household surveys in Thailand. Bull World Health Organ 2007;85:600-6. PMID:17768518 doi:10.2471/BLT.06.033720 7. Wagstaff A, Lindelowb M, Jun G, Ling X, Juncheng Q. Extending health insurance to the rural population: an impact evaluation of China’ s new cooperative medical scheme (The World Bank Policy Research Working Paper Series 4150). Washington, DC: The World Bank; 2007. 8. Frenk J, González-Pier E, Gómez-Dantés O, Lezana MA, Knaul FM. Comprehensive reform to improve health system performance in Mexico. Lancet 2006;368:1524-34. PMID:17071286 doi:10.1016/S0140- 6736(06)69564-0 9. Gakidou E, Lozano R, González-Pier E, Abbott-Klafter J, Barofsky JT, Bryson-Cahn C, et al. Assessing the effect of the 2001-06 Mexican health reform: an interim report card. Lancet 2006;368:1920-35. PMID:17126725 doi:10.1016/S0140-6736(06)69568-8 Resumen Tratamiento y control de la diabetes: efectos de un seguro médico público para los pobres en México Objetivo Analizar los efectos de la cobertura por el plan de seguro médico público conocido como Seguro Popular en el acceso a los recursos de salud y el tratamiento y control de la glucemia entre los adultos pobres con diabetes en México. Métodos Analizamos datos transversales de la Encuesta Nacional de Salud y Nutrición de 2006 a fin de comparar el acceso a la atención de salud y el valor de variables biológicas, concretamente de los niveles de glucohemoglobina (HbA1c), en adultos con diabetes beneficiarios del Seguro Popular (grupo de tratamiento) y en una población similar que carecía de seguro de enfermedad (grupo control). Se utilizó el método estándar de apareamiento según propensión para crear un grupo control altamente comparable. Resultados Los adultos con diabetes beneficiarios del Seguro Popular disfrutaron de un acceso significativamente mayor que los adultos no asegurados comparables a algún tipo de prueba de control de la glucemia (diferencia de 9,5 puntos porcentuales, con un intervalo de confianza, IC, del 95% de 2,4–16,6) y a inyecciones de insulina (3,13 más por semana; IC95%: 0,04–6,22). Los acogidos al seguro tenían también una mayor probabilidad de presentar una glucemia bien controlada (HbA1c £ 7%) que sus homólogos no asegurados (diferencia de 5,6 puntos porcentuales; IC95%: 0,9–10,3). En el grupo asegurado se observó que la proporción de adultos con un control muy deficiente de la glucosa (HbA1c > 12%) era significativamente inferior a la hallada en el grupo no asegurado (diferencia de 17,5 puntos porcentuales; IC95%: 6,5–28,5). Conclusión El Seguro Popular parece haber mejorado el acceso a la atención de salud y el control de la glucemia entre los adultos pobres con diabetes de México, y puede haber tenido un efecto positivo en el tratamiento de otras dolencias crónicas, pero quedan por demostrar sus efectos a largo plazo. Aunque los resultados son de especial interés para México, posiblemente pueden aplicarse también a otros países en desarrollo que aspiran a mejorar la cobertura de atención sanitaria de la población pobre ampliando sus programas de seguro médico público. 519Bull World Health Organ 2009;87:512–519 | doi:10.2471/BLT.08.053256 Research Mexico’s public health insurance and diabetes controlSandra G Sosa-Rubí et al. 10. Frenk J, Sepúlveda J, Gómez-Dantés O, Knaul F. Evidence-based health policy: three generations of reform in Mexico. Lancet 2003;362:1667-71. PMID:14630451 doi:10.1016/S0140-6736(03)14803-9 11. Popular S. Secretaría de Salud [Internet]. Mexico City: SSA. Catálogo universal de servicios de salud 2008. Available from: http://www.seguro- popular.salud.gob.mx/images/contenidos/Normateca/Spss/causes_2009.pdf [accessed on 16 June 2009]. 12. Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047-53. PMID:15111519 doi:10.2337/diacare.27.5.1047 13. Sistema Nacional de Información en Salud. Secretaría de Salud [Internet]. Mexico City: SSA; National Death Registry 2007. Available from: http:// sinais.salud.gob.mx/descargas/xls/diezprincausasmort2007_CNEGySR.xls [accessed on 7 April 2009]. 14. Olaiz-Fernández G, Rivera-Dommarco J, Shamah-Levy T, Rojas R, Villalpando-Hernández S, Hernández-Avila M, et al. Encuesta Nacional de Salud y Nutrición 2006. Cuernavaca, Mexico: Instituto Nacional de Salud Pública; 2006. 15. Mexico, Secretaría de Salud. Modificación de la norma oficial mexicana NOM- 015-SSAA2-1994 para la prevención, tratamiento y control de la diabetes mellitus en la atención primaria. Mexico City: SS; 2001. 16. American Diabetes Association. Standards of medical care in diabetes – 2007. Diabetes Care 2007;30 Suppl 1;S4-41. PMID:17192377 doi:10.2337/ dc07-S004 17. Nathan DM, Buse JB, Davidson MB, Heine RJ, Holman RR, Sherwin R, et al. Management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy; a consensus statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2006;29:1963-72. PMID:16873813 doi:10.2337/ dc06-9912 18. Barcelo A, Aedo C, Rajpathak S, Robles S. The cost of diabetes in Latin America and the Caribbean. Bull World Health Organ 2003;81:19-27. PMID:12640472 19. Olaiz-Fernández G, Rojas R, Aguilar-Salinas CA, Rauda J, Villalpando S. Diabetes mellitus en adultos mexicanos: Resultados de la Encuesta Nacional de Salud 2000. Salud Publica Mex 2007;49 S3;s331-7. 20. Lerman-Garber I. La atención del paciente más allá del primer nivel de atención. Salud Publica Mex 2007;49:99-103. 21. Bleich SN, Cutler DM, Adams AS, Lozano R, Murray CJ. Impact of insurance and supply of health professionals on coverage of treatment for hypertension in Mexico: population based study. BMJ 2007;335:875. PMID:17954519 doi:10.1136/bmj.39350.617616.BE 22. Sosa-Rubi SG, Galarraga O, Harris JE. Heterogeneous impact of the “Seguro Popular” program on the utilization of obstetrical services in Mexico, 2001. A multinomial probit model with a discrete endogenous variable. J Health Econ 2009;28:20-34. PMID:18824268 doi:10.1016/j.jhealeco.2008.08.002 23. Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ 2000;321:405-12. PMID:10938048 doi:10.1136/bmj.321.7258.405 24. Mexico, Secretaría de Salud. Subsistema de Información de Equipamiento, Recursos Humanos e Infraestructura para la Atención de la Salud (SINERHIAS). Mexico City: SSA; 2005. 25. Instituto Nacional de Estadística, Geografía e Informática. Conteo de población y vivienda 2005. Mexico, DF: INEGI; 2005. 26. Becker S, Ichino A. The estimation of average treatment effects based on propensity scores. Stata J. 2002;2:358-77. 27. Leuven E, Sianesi B. Psmatch2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing, 2003 [Internet site]. Available from: http://ideas.repec. org/c/boc/bocode/s432001.html [accessed on 7 April 2009]. 28. Rosenbaum P, Rubin D. The central role of the propensity score in observational studies for causal effects. Biometrika 1983;70:41-55. doi:10.1093/biomet/70.1.41 29. Dehejia RH, Wahba S. Propensity score-matching methods for nonexperimental causal studies. Rev Econ Stat 2002;84:151-61. doi:10.1162/003465302317331982 30. Dehejia RH, Wahba S. Causal effects in nonexperimental studies: re-evaluating the evaluation of training programs. J Am Stat Assoc 1999;94:1053-62. doi:10.2307/2669919 31. Rosenbaum P, Rubin D. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat 1985;39:33-8. doi:10.2307/2683903 32. Jack W. Public intervention in health insurance markets: theory and four examples from Latin America. World Bank Res Obs 2002;17:67-88. doi:10.1093/wbro/17.1.67