The estimated population aged ≥ 20 years in Mexico with no social security who reported no use of private health care services was 26.5 million in 2017. This population was considered to be under the primary medical care responsibility of 12,086 MOH PHCs in the country. The national prevalence of T2D was 10.3% (95% CI: 9.9–10.7%) according to the ENSANUT 2018 (reported prevalence within the population with no social security), which is equivalent to 2.6 million people living with T2D and who potentially needed primary health care (Table 1).
Table 1
Description of the study population under the responsibility of PHCs and effective coverage components at national and state levels
| | | | | Effective coverage dimensions |
| | | | | Need (N = 1) | Utilization (U) | Quality (Q) | Effective coverage (EC) |
| A | B | C | D | E | F | G | H |
| Health jurisdictions | MOH PHCs | Population 20 + without social security | Prevalence (%) | Population 20 + who needs medical care for T2D | Percentage of population who needed and received medical care for T2D | Percentage of population 20 + who received medical care and improved metabolic condition | EC = Q × U | N = 1 |
| | | | | E = D*C | | |
| N | N | N | Mean | Mean | Mean | Mean | Mean |
| | | (HJ minimum - HJ maximum) | (HJ minimum - HJ maximum) | (HJ minimum - HJ maximum) | (HJ minimum - HJ maximum) | (HJ minimum - HJ maximum) | (HJ minimum - HJ maximum) |
National | 245 | 12,086 | 26,534,076 (5-322,557) | 10.3 (6.0-16.1) | 16,717 (595 − 47,073) | 37.9 (5.3–94.2) | 25.8 (1.5–82.1) | 9.5 (0.2–38.6) |
Aguascalientes | 3 | 91 | 218,184 (3,641 − 103,644) | 7.6 (7.3–9.2) | 7,600 (2,117-9,954) | 53.5 (47.6–63.6) | 20.9 (16.9–23.1) | 11.1 (8.0-11.5) |
Baja California | 3 | 174 | 449,493 (18,465 − 182,327) | 10.6 (9.8–11.5) | 17,927 (9,577 − 23,397) | 40.7 (36.5–42.4) | 23.1 (9.6–49.0) | 9.0 (4.1–17.9) |
Baja California Sur | 4 | 60 | 117,218 (4,542 − 41,560) | 9.8 (7.5–14.8) | 4,069 (1,147 − 25,857) | 37.7 (10.0-42.6) | 36.6 (32.8–59.0) | 13.7 (3.3–19.3) |
Campeche | 3 | 140 | 256,050 (4,678 − 53,819) | 13.8 (12.9–14.3) | 14,245 (7,798 − 19,549) | 33.8 (29.3–43.8) | 16.8 (13.9–24.6) | 5.7 (4.1–8.4) |
Chiapas | 10 | 740 | 1,702,440 (452 − 113,127) | 8.1 (6.0-9.8) | 17,120 (4,051 − 28,079) | 20.1 (10.0-43.9) | 12.7 (1.5–32.8) | 2.7 (0.2–6.9) |
Chihuahua | 10 | 255 | 508,213 (346 − 118,070) | 9.9 (8.3–12.9) | 10,658 (1,034 − 25,857) | 53.5 (10.0-75.3) | 27.1 (7.8–39.7) | 14.3 (3.3–29.4) |
Mexico City | 16 | 223 | 1,348,687 (24,691 − 322,557) | 12.2 (9.1–14.1) | 18,425 (2,247 − 41,287) | 32.4 (24.5–74.0) | 40.3 (29.3–50.7) | 12.8 (9.0-30.2) |
Coahuila de Zaragoza | 8 | 148 | 258,925 (256 − 45,800) | 12.5 (9.8–14.1) | 6,059 (595 − 25,857) | 10.5 (6.5–46.6) | 45.9 (21.7–76.6) | 4.9 (1.5–14.0) |
Colima | 3 | 127 | 162,196 (2,834 − 40,542) | 11.3 (10.9–11.6) | 6,726 (3,803-8,540) | 39.5 (24.0–47.0) | 15.7 (8.6–18.3) | 6.5 (2.1–8.6) |
Durango | 4 | 167 | 367,341 (650 − 108,493) | 10.9 (9.8–13.1) | 13,957 (3,265 − 25,857) | 25.5 (10.0-46.3) | 14.5 (4.8–32.8) | 3.2 (2.2–4.4) |
Guanajuato | 8 | 443 | 1,565,296 (2,814 − 245,217) | 9.8 (8.6–11.9) | 20,070 (14,576 − 24,864) | 57.5 (5.3–81.3) | 44.8 (39.9–51.3) | 25.8 (2.7–36.2) |
Guerrero | 7 | 951 | 1,293,050 (2,558 − 190,446) | 11.2 (8.9–12.9) | 25,393 (13,826 − 47,073) | 46.4 (34.3–55.8) | 14.0 (10.5–15.8) | 6.4 (3.9–8.2) |
Hidalgo | 17 | 550 | 886,803 (1,349 − 50,632) | 12.9 (11.9–14.3) | 8,226 (1,757 − 13,080) | 29.4 (15.3–39.5) | 24.8 (15.8–35.1) | 7.3 (3.4–11.9) |
Jalisco | 13 | 740 | 1,457,426 (979 − 189,524) | 7.8 (6.5–9.5) | 10,054 (2,545 − 16,797) | 46.6 (15.3–93.2) | 38.0 (19.4–58.3) | 15.8 5.3–38.6) |
Michoacán de Ocampo | 8 | 482 | 1,109,399 (1,343 − 116,072) | 10.0 (9.3–11.2) | 15,833 (5,315 − 25,857) | 38.9 (10.0-48.4) | 9.0 (3.2–32.8) | 3.4 (0.9–5.2) |
Morelos | 3 | 206 | 538,891 (3,337 − 73,053) | 12.1 (12.0-12.5) | 24,719 (10,763 − 28,714) | 26.8 (16.3–36.0) | 16.1 (10.0-17.6) | 4.4 (1.6–6.1) |
Mexico State | 19 | 1,078 | 3,409,474 (1,464 − 245,434) | 9.4 (8.3–11.0) | 20,212 (9,163 − 30,035) | 37.4 (10.0–73.0) | 17.4 (6.0-33.4) | 6.2 (1.5–16.5) |
Nayarit | 3 | 208 | 285,409 (3,183 − 54,044) | 10.7 (9.7–12.2) | 15,386 (8,531 − 26,748) | 22.5 (21.2–23.2) | 46.9 (42.4–53.4) | 10.5 (9.8–11.3) |
Nuevo León | 8 | 431 | 513,227 (379 − 106,915) | 13.2 (10.4–16.1) | 10,526 (3,325 − 17,213) | 28.3 (18.6–45.6) | 43.8 (34.9–61.7) | 12.3 (6.5–18.5) |
Oaxaca | 6 | 802 | 1,307,705 (5–53,066) | 10.2 (9.2–11.7) | 24,093 (10,115 − 36,140) | 35.5 (10.0-70.5) | 6.1 (1.7–32.8) | 1.6 (0.6–3.3) |
Puebla | 10 | 673 | 1,625,491 (172–238,031) | 9.1 (7.8–10.2) | 17,355 (4,282 − 25,857) | 36.0 (10.0-56.7) | 43.9 (27.2–82.1) | 14.9 (3.3–26.3) |
Querétaro | 4 | 252 | 407,080 (4,444 − 107,661) | 7.7 (7.1–8.2) | 9,450 (3,393 − 12,045) | 71.9 (59.8–94.2) | 18.3 (12.7–35.0) | 13.1 (9.2–28.3) |
Quintana Roo | 3 | 185 | 277,187 (6,806 − 76,725) | 8.6 (7.8–9.9) | 9,210 (5,166 − 11,819) | 79.2 (71.0-81.1) | 18.3 (11.6–31.2) | 15.6 (9.4–23.5) |
San Luis Potosí | 7 | 291 | 714,735 (722 − 113,474) | 10.9 (9.8–12.7) | 12,078 (6,835 − 25,857) | 45.5 (10.0–51.0) | 28.0 (20.3–32.8) | 12.6 (3.3–14.0) |
Sinaloa | 6 | 266 | 531,099 (6,930 − 93,946) | 10.8 (10.2–11.9) | 10,871 (4,288 − 14,975) | 27.6 (19.2–33.7) | 26.0 (12.8–41.7) | 6.8 (3.7–9.5) |
Sonora | 6 | 207 | 420,723 (152 − 88,660) | 12.2 (9.8–13.2) | 10,386 (2,603 − 25,857) | 25.6 (10.0-38.1) | 24.7 (14.1–32.8) | 6.6 (2.5–11.2) |
Tabasco | 17 | 584 | 766,993 (13,685 − 143,183) | 11.5 (9.2–13.0) | 13,514 (1,779 − 47,073) | 47.1 (31.2–76.2) | 26.3 (8.9–79.0) | 11.7 (5.0-26.1) |
Tamaulipas | 12 | 296 | 641,955 (633 − 82,712) | 14.0 (12.8–16.0) | 8,990 (2,841 − 13,363) | 34.8 (26.4–47.3) | 32.3 (13.5–76.8) | 10.7 (4.1–23.2) |
Tlaxcala | 3 | 123 | 433,665 (1,235 − 33,366) | 9.2 (8.7–9.5) | 15,412 (7,600 − 20,838) | 62.5 (57.9–70.3) | 17.7 (17.0-19.4) | 9.8 (8.3–12.1) |
Veracruz | 11 | 793 | 2,038,825 (597 − 69,718) | 11.6 (9.8–12.8) | 23,174 (15,434 − 29,281) | 26.0 (10.0-30.9) | 34.6 (24.2–67.9) | 8.8 (3.3–14.2) |
Yucatán | 3 | 166 | 451,156 (149 − 92,967) | 10.4 (9.8–11.0) | 16,984 (7,845 − 25,857) | 39.8 (10.0-49.4) | 23.8 (18.6–32.8) | 9.0 (3.3–9.9) |
Zacatecas | 7 | 234 | 469,740 (245 − 58,991) | 10.9 (9.6–12.5) | 8,775 (3,070 − 25,857) | 40.0 (10.0-55.1) | 14.7 (6.3–32.8) | 5.6 (2.6–9.4) |
Ranges in parentheses are those at the HJ level. |
HJ, health jurisdiction; MOH, Ministry of Health; PHC, primary health center; T2D, type 2 diabetes. |
Among states, the average percentage of the population requiring medical care for T2D ranged from a minimum of 7.6% (within-state range: 7.3–9.2%) in Aguascalientes to a maximum of 14.0% in Tamaulipas (within-state range: 12.8–16.0%). Notably, some northern states, such as Nuevo León, Tamaulipas, Sonora, and Coahuila, and states located around the Gulf of Mexico, such as Veracruz, Tabasco, and Campeche, presented the highest need in the country (Fig. 1A). Among health jurisdictions, the need ranged from 6.0% in Ocosingo, Chiapas to 16.1% in Monterrey, Nuevo Leon (Supplementary Table 1, Fig. 1A).
According to the information recorded in the SIC during 2017, 998,135 individuals (283,706 men and 714,429 women) sought at least one medical consultation in their respective MOH PHCs, meaning that only 37.1% of the base population with T2D who needed health services at the PHCs received medical attention. Across the country, states with the highest proportion of the population that received health care for T2D were Quintana Roo (79.2%), Querétaro (71.9%), Guanajuato (53.7%), and Chihuahua (53.5%). We observed the lowest utilization in the states of Coahuila (10.5%), Chiapas (20.1%), Nayarit (22.5%), and Durango (25.5%) (Table 1, column F). The within-state variability in utilization among health care jurisdictions ranged between 5.3% and 94.2% (Supplementary Table 1, Fig. 1B).
The change in metabolic glucose levels and T2D control (quality) was assessed for 584,899 adults (13.6% of patients diagnosed with T2D) because these individuals had at least two measurements (baseline and follow-up). Among the total population, 26.6% improved their metabolic condition. Importantly, 43% of the population who attended a PHC more than once still had an uncontrolled or worsened metabolic condition. The states with the best performance, on average, were Nayarit, Coahuila, Guanajuato, Puebla, Nuevo León, and Mexico City, all of which had values over 40% (Table 1, column G). In contrast, Oaxaca, Michoacán, Chiapas, Guerrero, Durango, and Zacatecas presented the worst capability concerning improving the health of people living with T2D (under 15%). This indicator showed the greatest variability among health jurisdictions, ranging from 1.5–82.1% (Supplementary Table 1) (Fig. 1C).
When we jointly analyzed the components of need, utilization, and quality, we estimated that the EC achieved in MOH PHCs at the national level was 9.5% (within-health jurisdiction range: 0.2–38.6%). The states with the lowest EC were Chiapas, Durango, Michoacán, and Oaxaca; states with the highest EC were Guanajuato, Jalisco, Puebla, Quintana Roo, Puebla, and Chihuahua (Table 1, column H).
We observed different performance patterns concerning the EC achieved among states, according to the relationship between PHC utilization and T2D control (quality). Figure 2 shows that those states with lower utilization and lower T2D control (Chiapas, Durango, Morelos, and Oaxaca) also had the lowest EC (lower left quadrant). States in the upper left quadrant (Mexico City, Nuevo León, Nayarit, Coahuila, and Veracruz) represent those states with lower utilization but better T2D control, with an EC close to the national value. States with higher utilization but poorer T2D control (Aguascalientes, Querétaro, Guerrero, Quintana Roo, and Tlaxcala) are shown in the lower right quadrant of Fig. 2. Finally, states with the best performance, i.e., with higher utilization and better T2D control (Jalisco and Guanajuato), are shown in the upper right quadrant of the figure.
Important differences in EC can be observed within regions of Mexico at the municipality level (Fig. 1D). The correlation analysis revealed that the highest quintiles of EC showed an inverse and statistically significant correlation with population size, population density, population with low education, population without access to health services, and population lacking basic sanitation services (Table 2).
Table 2
Correlation analysis of effective coverage and social health determinants by municipality
| Quintiles of effective coverage | |
Characteristic | Q1 | Q2 | Q3 | Q4 | Q5 | p-value (Kruskal–Wallis test) |
| Mean (min – max) | Mean (min – max) | Mean (min – max) | Mean (min – max) | Mean (min – max) |
Effective coverage (%) | 1.6 (0.1–3.2) | 4.9 (3.2–6.5) | 8.7 (6.5–10.9) | 14.4 (10.9–19.1) | 34.4 (19.2–100.0) | |
Population | 45,425 (537-1,679,610) | 68,576 (345-1,789,531) | 84,479 (234-1,503,505) | 67,799 (375-1,815,551) | 23,029 (288–610,700) | 0.0001 |
Population density | 187.0 (0.8-7882.5) | 371.3 (0.3-12494.2) | 521.6 (0.5-16435.4) | 398.3 (0.1-16898.2) | 126.9 (0.4–7856.0) | 0.0001 |
Population with multidimensional poverty (%) | 70.5 (19.0-97.3) | 65.5 (21.4–97.4) | 63.4 (12.8–97.0) | 64.6 (8.7–96.6) | 67.5 (14.3–96.4) | 0.0001 |
Population with low education (%) | 32.3 (8.2–62.5) | 29.1 (8.7–53.1) | 28.3 (5.4–59.5) | 28.6 (3.7–61.1) | 30.9 (4.8–65.1) | 0.0001 |
Population without access to health services (%) | 15.5 (1.9–50.2) | 14.6 (2.0-40.8) | 13.7 (3.0-39.3) | 13.3 (2.0-34.6) | 12.9 (0.9–77.4) | 0.0001 |
Population lacking basic sanitation services (%) | 50.1 (0.3–99.6) | 43.1 (0.1–99.9) | 41.6 (0.1–98.7) | 39.0 (0.0-100.0) | 43.0 (0.0-100.0) | 0.0001 |
Discussion
This report provides evidence of the three components of EC—need, use, and quality—in a population with no social security who are nonusers of private services, at national, state, health jurisdiction, and municipality levels. Our results suggested that there is an urgent need to expand and improve the EC of T2D as part of policies to reduce the burden of disease and health vulnerability in the Mexican population.
Several studies have demonstrated that EC is a good indicator to quantify the improvement of the health of the population who receive one or more interventions from the health care system when needed [22–26]. In the Latin America region, Mexico was the first country that measured the EC of the health care system at the national and state levels through 18 basic health programs; in the following years several studies to evaluate EC at the state level have been conducted in Mexico [26–31]. The present study reports the first evaluation of T2D in the population with no social security coverage and nonusers of private health care services at state, health jurisdiction, and municipality levels using the SIC, the first nominal registry that tracks patient health information. The results could be useful not only to understand the effectiveness of interventions, but also to provide practical information to improve PHC services [32].
For this analysis, we excluded individuals who reported seeking health care services through the private sector, which represents almost 50% of the population without social security [11, 33]. According to Colchero et al., between 2004 and 2018 in Mexico, the membership to health services for the nonsocial security population grew almost 10 times, from 4.8 to 42.0 million people, but this increase was not accompanied by an equivalent increase in the availability of public health care services [34]. In contrast, the availability of private health care services grew rapidly, mostly by offices adjacent to pharmacies. Such offices have been successfully competing with public options at the primary level of care in Mexico, which contributes to the low use of public services. However, there is no regulation for private facilities, and the quality and effectiveness of private care is not known [34].
We estimated that there were 2.6 million individuals without social security living with T2D in Mexico, who mainly depend on MOH PHCs for medical care. Most of this population is therefore expected to receive treatment and follow-up care according to the Mexican health system, which is obligated to guarantee universal health access to all Mexican citizens within their communities [35]. Nevertheless, we found an evident disconnect among need, utilization, and quality rates across the country.
The greatest need was found in the health jurisdictions and municipalities located mainly in northern Mexico and around the Gulf of Mexico. However, most of the jurisdictions in those regions achieved a low to moderate rate of utilization. In contrast, health jurisdictions in Nuevo León and Mexico City were classified among the top 10 states in which patients maintained, achieved, or improved T2D metabolic control, despite those states having the lowest rates of PHC utilization. Fortunately, some jurisdictions in states such as Jalisco achieved both high rates of utilization and high quality of care (health gain).
This analysis revealed that glycemic control was generally poor among individuals with T2D; this finding is alarming and requires immediate action to improve the quality of primary health care. International evidence has shown that the lack of metabolic control increases the probability of complications, which can lead to economic losses owing to absence from work, hospitalization, and premature death [28]. Therefore, indicators related to improving health care must be monitored in primary care through preventive measures and timely diagnosis and treatment of patients [31, 36, 37]. Although it is well established that longer duration of T2D is associated with poor glycemic control and worse self-care [38, 39], disease duration was not included in the present analysis and thus somewhat limits our interpretation of the results. The concept of ambulatory care-sensitive hospitalization (ACSH) can also be applied to assess the impact of adequate T2D care on the economic factors listed above. ACSH (hospitalization that could be prevented by adequate intervention in primary care) for T2D complications has increased greatly in Mexico in recent years, and the financial costs and increased health burden related to ACSH suggest that improvements in primary care (and thus, EC) could considerably ease this burden [40, 41]. Nowadays, the second-highest cause of ACSH at the national level in Mexico is T2D and non-communicable diseases, representing more than 30% of total consultations in the age group above 50 years [42].
In this analysis, we found that some factors were correlated with EC at the municipality level, such as the lack of access to health services and lack of sanitation. These results are consistent with those previously reported in other studies [36, 37].
Even though our analysis did not assess early detection of T2D, we recognize that early detection presents one of the greatest challenges to overcome and is an area where the health care system must take an active role through timely screening. Previously we showed that screening strategies for pre-disease states (such as pre-T2D) are crucial in the continuum of care and ideally should be included as part of the effective coverage [43]. We identified in a large population size analysis that 13.4% of the screened population presented this condition.
One strength of this analysis is that the quality component of EC was assessed using the biomarker HbA1c, similar to previous studies that used HbA1c to assess T2D EC [44]. However, this limited the study in that T2D control could only be assessed for the 584,899 adults who had HbA1c data available for analysis. Furthermore, although we attempted to estimate prevalence by age and sex, these calculations were not sufficiently precise at the municipality level to draw meaningful conclusions. Another weakness of the analyses is that we included routine secondary source data from ENSANUT to estimate need (ex-post approach). An additional strength for the other two components (utilization and quality) is that they were measured consistently and taken from the SIC registry designed for this purpose (ex-ante approach). The combination of both sources of information allowed us to make estimations not only at the state level but also at the health jurisdictional and municipality levels. Health information systems are useful in providing routine data for administrative and clinical purposes and are key tools in assessment of EC [32]. It has been shown that electronic health records can be used to evaluate clinic performance and interventions in Mexico [45]. Furthermore, as shown in this analysis, the combination of health information systems with population data results is a useful tool for benchmarking the performance of PHCs at national, state, health jurisdictional, or municipality levels. Thus, the present results are beneficial for health authorities and decision-makers to prioritize and focus on developing appropriate local health policies.