Aimed at covering the large fraction of workers in the informal sector without access to a social security program, the Mexican public health insurance program Seguro Popular began in 2002 and now reaches more than 50 million individuals. We estimate impacts of Seguro Popular for the population aged 50 and older on a set of indicators related to health care including utilization, diagnostic/preventive tests, and treatment conditional on being ill. Using the longitudinal Mexican Health and Aging Study over the period 2001–2012, we conduct before and after difference-in-difference matching impact estimators. Our results suggest large and important effects of the Program on utilization and diagnostic tests. We find overall smaller effects on the probability of being in treatment for individuals with chronic diseases, but these effects are concentrated in rural areas with relatively more health services versus rural areas with lower levels of health services. These results suggest that, to the extent that health services become more available in rural areas lacking services, effects of health insurance may increase.
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For the purposes of this article, the aging population is defined as the population aged 50 and older.
An interesting research question is how Seguro Popular might affect the supply and quality of services. The Seguro Popular program does not have or build health facilities of its own but might affect construction of health facilities by the Secretary of Health through increased demand for health services associated with participation in the program. If this occurs, any impacts of Seguro Popular would reflect not only program characteristics but also these new facilities.
Lloyd-Sherlock et al. (2014) studied hypertension in six low- and middle-income countries, including Mexico, and found that for the case of hypertension, only about 44 % of Mexicans with hypertension were aware of their condition. They also found that only about 12 % of the ill population has effective control of their hypertension.
We do not use the MHAS 2012 subsample biomarker data to study impacts of the Seguro Popular for two reasons. First, our empirical strategy requires pre- and postprogram data, and the MHAS 2001 baseline does not include biomarkers. Second, the sample size of those with biomarkers in 2012 in our sample who report having a chronic disease is small.
Individuals in the subsample with biomarkers in 2012 are informed about the results of these tests. However, the biomarker tests were conducted after the self-report of treatment-seeking behaviors (in a subsequent health visit); thus, responses on treatment for ill individuals should not be biased by the results of the tests.
We also carry out impact estimates using nearest neighbor matching (two and five neighbors). Given their similarity to the estimates reported here, we report only estimates based on local linear matching.
Heckman and Smith (1995) coined the term “substitution bias” to refer to the situation in which individuals in a comparison group obtain a close substitute of the treatment. In our context, approximately 40 % of nonbeneficiaries in 2012 had an alternative form of health insurance in rural areas versus more than 60 % in urban areas.
Some studies (e.g., Maloney 1999) have shown substantial worker mobility in Mexico between formal (i.e., with social security benefits) and informal jobs (i.e., without social security benefits). Bosch and Campos-Vazquez (2014) demonstrated that the Seguro Popular program has reduced the number of employees affiliated with IMSS from small firms by approximately 4 %.
Censuses were conducted in 2000, 2005, and 2010. INEGI constructs population figures between census years by using a geometric model to extrapolate. The National Population Council (CONAPO) provides its own population series, adjusting for possible underreporting of census numbers. Results using either the INEGI series or the CONAPO series are extremely similar.
We analyze the effect of the Seguro Popular program on mortality in more detail in a separate study using survival analysis techniques (Parker et al. 2015).
We carry out balancing tests based on Dehejia and Wahba (2002), which examine whether the distribution of the covariates included in the propensity score model is independent of program participation conditional on the estimated propensity score—as it should be if the propensity score model is correctly specified, and the estimator is consistent. The test stratifies treatment and control observations into strata, based on the estimated propensity score (in quintiles), and then tests for significant differences between the covariates within each stratum. Nearly all of our covariates did not show significant differences.
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The authors gratefully acknowledge the assistance of Ana Cristina Perez Gea. They also acknowledge support from the Sealy Center on Aging at the University of Texas Medical Branch in Galveston, and the Health of Older Minorities T32AG00270 training grant from the National Institutes of Health/National Institute on Aging (NIH/NIA), as well as support from the Davis School of Gerontology at the University of Southern California from the Multidisciplinary Research Training Grant in Gerontology (T32AG000037) and award P30AG043073—all from the NIH/NIA. The MHAS (Mexican Health and Aging Study) is partly sponsored by the NIH/NIA (R01AG018016) and the Statistical Bureau (INEGI) in Mexico. Data files and documentation are public use and available at www.MHASweb.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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Parker, S.W., Saenz, J. & Wong, R. Health Insurance and the Aging: Evidence From the Seguro Popular Program in Mexico. Demography 55, 361–386 (2018). https://doi.org/10.1007/s13524-017-0645-4
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