Impact of the COVID-19 pandemic on indigenous women’s access to healthcare in Chile

Impacto da pandemia de COVID-19 no acesso à saúde das mulheres indígenas no Chile

Impacto de la pandemia de COVID-19 en el acceso a la salud de las mujeres indígenas en Chile

Abstract

The overarching aim of this study was to determine the extent to which the COVID-19 pandemic has affected the healthcare accessibility of indigenous women in Chile compared to other demographic groups. For this, we use regression models with fixed effects at the municipality level and simulating a differences-in-differences strategy. Data for this study were sourced from the Socioeconomic Characterization Surveys (CASEN) spanning the years 2013, 2015, 2017, and 2020. The initial three-year period serves as the baseline for establishing healthcare disparities between indigenous and non-indigenous populations and between men and women in the pre-COVID era. Our findings affirm our initial hypothesis regarding the heterogeneous and concentrated effects of the COVID-19 pandemic on indigenous women’s medical attention in Chile. We observed a decline of over 4.5% in the level of healthcare utilization for indigenous women during the pandemic. This exceeds the effect found for women in the aggregate by more than 3 percentage points, indicating that the impact is indeed concentrated on indigenous women. Our results encourage political decisions; access to health must consider the particularities of historically segregated groups. The needs of indigenous women in crisis contexts seem to exacerbate inequality in access to health.

Key words:
Indigenous women; Healthcare access; COVID-19; Social determinants of health

Resumo

O objetivo geral do estudo foi determinar até que ponto a pandemia da COVID-19 afetou a acessibilidade à saúde de mulheres indígenas no Chile em comparação com outros grupos demográficos. Para isso, usamos modelos de regressão com efeitos fixos no nível municipal e simulando uma estratégia de diferenças em diferenças. Os dados para este estudo foram obtidos das Pesquisas de Caracterização Socioeconômica (CASEN) abrangendo os anos de 2013, 2015, 2017 e 2020. O período inicial de três anos serve como linha de base para estabelecer disparidades de saúde entre populações indígenas e não indígenas e entre homens e mulheres na era pré-COVID. As descobertas confirmam nossa hipótese inicial sobre os efeitos heterogêneos e concentrados da pandemia de COVID-19 na atenção médica de mulheres indígenas no Chile. Observamos um declínio de mais de 4,5% no nível de utilização de assistência médica para mulheres indígenas durante a pandemia. Isso excede o efeito encontrado para mulheres no agregado em mais de 3 pontos percentuais, indicando que o impacto está de fato concentrado em mulheres indígenas. Nossos resultados encorajam decisões políticas - o acesso à saúde deve considerar as particularidades de grupos historicamente segregados. As necessidades das mulheres indígenas em contextos de crise parecem exacerbar a desigualdade no acesso à saúde.

Palavras-chave:
Mulheres indígenas; Acesso à assistência médica; COVID-19; Determinantes sociais da saúde

Resumen

El objetivo general de este estudio fue determinar en qué medida la pandemia de COVID-19 ha afectado la accesibilidad a la atención médica de las mujeres indígenas en Chile en comparación con otros grupos demográficos. Para ello, utilizamos modelos de regresión con efectos fijos a nivel municipal y simulamos una estrategia de diferencias en diferencias. Los datos para este estudio se obtuvieron de las Encuestas de Caracterización Socioeconómica (CASEN) de los años 2013, 2015, 2017 y 2020. El período inicial de tres años sirve como base para establecer las disparidades en la atención médica entre las poblaciones indígenas y no indígenas y entre hombres y mujeres en la era anterior a la COVID. Nuestros hallazgos afirman nuestra hipótesis inicial sobre los efectos heterogéneos y concentrados de la pandemia de COVID-19 en la atención médica de las mujeres indígenas en Chile. Observamos una disminución de más del 4,5% en el nivel de utilización de servicios de salud por parte de las mujeres indígenas durante la pandemia. Esto supera el efecto encontrado para las mujeres en el agregado en más de 3 puntos porcentuales, lo que indica que el impacto se concentra en las mujeres indígenas. Nuestros resultados alientan la toma de decisiones políticas; el acceso a la salud debe considerar las particularidades de los grupos históricamente segregados. Las necesidades de las mujeres indígenas en contextos de crisis parecen exacerbar la desigualdad en el acceso a la salud.

Palabras clave:
Mujeres indígenas; Acceso a la atención médica; COVID-19; Determinantes sociales de la salud

Introduction

The COVID-19 pandemic has exposed preexisting vulnerabilities in social, economic, and healthcare systems worldwide. In this context, a body of related research has been conducted, particularly focused on understanding differences among long-disadvantaged groups, including Afro-descendant women, migrants, indigenous peoples, and/or sexual minorities. Studies have addressed various aspects, ranging from the incidence of infection in different groups^1-5 and the link between morbidity and COVID-19^6,7 to the relationship between mental health and COVID-19^8,9. However, inequities in access to healthcare during the COVID-19 pandemic have been more extensively studied in the Global North^10,11 and less so in southern countries, specifically in Latin America. This is something we address in this manuscript, for the case of Chile. As mentioned, this is something highly relevant, as minority groups who are already facing various barriers to healthcare, experienced increased difficulties as a consequence of the COVID-19 pandemic.

Understanding the existence of disparities in access to healthcare is important not only because it is considered a social determinant of health but also because decision-makers and public policy at the state level must allocate resources for preventing and treating severe diseases related to COVID-19. Particularly in specific groups, this understanding is essential for advancing efforts to reduce gaps. Similarly, comparative evidence in Latin America has highlighted how the state acts to maintain or increase inequalities in access to public services, especially healthcare¹².

The primary objective of this study was to examine the impact of the COVID-19 pandemic on healthcare accessibility among indigenous women in Chile in comparison to other demographic groups. We posit that, while all groups may have experienced challenges in accessing healthcare during the pandemic, indigenous women were particularly vulnerable to its effects. Specifically, we aimed to determine whether the COVID-19 pandemic engendered changes in the probability of seeking medical consultation once individuals reported experiencing medical problems. We have conducted a quantitative study to accomplish these objectives by employing various regression models with fixed effects at the commune level while simulating a difference-in-differences framework. We do not use a common DiD model since we do not have a control group affected by treatment (the COVID-19 pandemic); thus, we assume that the impact of treatment (the COVID-19 pandemic) affects all demographic groups (at least to some extent), which underpins our data handling methodology. The data for this study were sourced from the Socioeconomic Characterization Surveys (CASEN) spanning the years 2013, 2015, 2017, and 2020.

Research on social inequality in health has made considerable strides in strengthening the social and subnational lens of healthcare access, imbuing the concept of inequality with a robust multidimensional dimension, which was conventionally restricted to income inequity^13,14. This study focuses on health access inequality as a multidimensional phenomenon that has undergone evolution while persisting as a foundational underpinning of social disparities in Chile^15,16.

Our focus will be on inequality in access to health, a concept derived from the framework of social determinants of health^17,18. We approach the inequality in access to health from an “availability” perspective¹⁹. Consequently, we measure access as the possibility of accessing or not accessing medical care in the face of illness or accident^10,20-22. We acknowledge that this understanding of health access is not the only one available and limits us to a global understanding of the scenario during the pandemic. However, the assessment of this concept is closely linked to the data source and its recording methodologies, including the vital consideration of transparent health reporting systems.

Given this conceptualization, there are substantive premises or hypotheses that may shed light on the phenomenon of health access. A diverse set of studies has indicated that migrants and refugees are among the most affected groups^23-25. This has also been analyzed in groups where sex and race intersect^26-28. The pandemic has also adversely affected sexual minorities (LGBTQ), limiting access to medical care^29-31, with even more robust outcomes for migrants belonging to sexual or racialized minority groups^10,32.

In Latin America, the situation mirrors global trends. Access to healthcare services during the pandemic has been a crucial problem³³. Given that indigenous populations, migrants, and racialized individuals experience underlying inequality in access to healthcare, the threat of the COVID-19 pandemic emerged as a critical factor³⁴ that impacted infection and mortality rates. The study by Kruse et al.³³ is particularly illuminating for this research, as it reveals that differences between Latin American regions, especially when analyzing data for the southern cone, might incorrectly signal the absence or nonexistence of substantive differences between groups regarding health access.

In the case of Chile, studies associated with access to healthcare during the COVID-19 pandemic are scarce^7,35-37. Existing studies highlight, however, different elements. Millalen et al.⁷ emphasize the significant gap in terms of COVID-19 contagion between indigenous and nonindigenous populations in Chile. Alvear-Vega et al.³⁵ underscore social determinants, such as belonging to the indigenous population, as factors for not utilizing public policy -known as explicit health guarantees (GESs) - due to mistrust or acceptability issues. This is understood as a failure in health access¹⁹, however, there is a need to advance more specific analyses of inequality in health access from an intersectional perspective. Such an approach would enable the examination of more specific dynamics concerning how certain population groups access or do not access the health system and to what extent the provision of these public goods by the state is exacerbated in a pandemic context.

Material and methods

Our primary data source comprises the Socioeconomic Characterization Surveys (CASEN) for the years 2013, 2015, 2017 and 2020. The initial three years serve as a baseline for establishing the usual disparities in healthcare access between indigenous and nonindigenous populations and between women and men, while the 2020 survey enables us to investigate whether any shifts in trends or gaps occurred among these groups due to the COVID-19 pandemic.

The CASEN survey is a cross-sectional household survey that offers representative data at the national and regional levels, with a substantial number of observations, typically exceeding 200,000 individuals per year. Our sample is limited to individuals older than 15 years of age who possess positive labor incomes and full information on the relevant variables of interest and controls, as denoted below. We then inquired whether this group sought medical consultation, given their self-reported medical problems.

According to the Social Observatory in charge of CASEN 2020, the following is detailed: Considering the health restrictions derived from the Coronavirus, this version of the Casen Survey, called Casen Survey in Pandemic 2020, was carried out in a mixed sequential modality of three phases: face-to-face pre-contact, telephone application of the questionnaire and face-to-face recovery (only in 268 cases - https://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-casen-en-pandemia-2020).

The question we answer is whether, conditional on the initial gap between men and women and indigenous and nonindigenous groups in terms of their healthcare access, indigenous women were particularly vulnerable to its effects. Do indigenous women reduce their healthcare access relatively more than other groups during the COVID-19 pandemic? We hypothesize that, whereas all groups might have been affected in terms of healthcare access during the pandemic, indigenous women were the hardest hit. Our main results should be interpreted as indicating the relative additional impact that indigenous women face as a consequence of the COVID-19 pandemic in terms of their healthcare access.

Nonetheless, it is conceivable that any observed impact, if discernible, could be attributed to a more significant effect on either women (regardless of indigenous status) or indigenous individuals (both women and men). Consequently, we undertook separate assessments to ascertain the existence of any additional effects of COVID-19 on women or indigenous individuals, separately. For women, our initial estimation model is as follows:

$Y_{ijt}={\beta }_1{M}_{ijt}+{\beta }_2{I}_{ijt}+{\beta }_3{C}_t+{\beta }_4{M}_{ijt}{C}_t+\gamma X_{ijt}+{\varnothing }_j+{\mathcal{E}}_{ijt}$ (1)

where Y _ijt represents the healthcare access of individual i living in community j in year t. M _ijt , I _ijt and C _t are dummy variables that identify whether the individual is female (1 = female, 0 = male), indigenous (1 = yes, 0 = no), or whether the period considered is during the COVID-19 pandemic (1 = year 2020, 0 = previous years), respectively. X _ijt is a vector of control variables at the individual level, including variables such as the type of health insurance held by the individual, their level of education, autonomous income (in logarithms), age, age squared, employment status, and the urban/rural area of residence. The parameter Ø _j is a municipality fixed effect, capturing structural differences in healthcare provision and other distinctive elements of each municipality that do not vary over time.

In Eq. (1), parameters β ₄ captures the additional penalty that women (both indigenous and nonindigenous) face in terms of their access to healthcare services as a consequence of the COVID-19 pandemic. The same model is estimated again, but this time, the variables I _ijt and C _t are interacted to determine whether the COVID-19 pandemic impacted indigenous communities to a greater extent (regardless of sex).

It is important to note that a model such as the one described above, with a single interaction for women or indigenous individuals during the COVID-19 period, does not allow us to ascertain whether any impact, if it exists, is primarily driven by the effect of COVID-19 on women or on indigenous individuals. Therefore, the final model considered, which underpins our main results, contains multiple interactions to separately identify each of these effects and the additional effect exclusively for indigenous women during the COVID-19 pandemic. Thus, our preferred specification is the one presented in Eq. (2).

$Y_{ijt}={\beta }_1{M}_{ijt}+{\beta }_2{I}_{ijt}+{\beta }_3{C}_t+{\beta }_4{M}_{ijt}{C}_t+\gamma X_{ijt}+{\varnothing }_j+{\mathcal{E}}_{ijt}$ (2)

In Eq. (2), all the variables and parameters remain the same as those presented previously in Eq. (1), with only one significant difference. The interaction associated with β ₄ now incorporates multiple effects that allow us to identify the differential impact of COVID-19 specifically on indigenous women compared to the rest of the population. This is achieved because Eq. (2), in its final specification, includes the partial interactions mentioned in the models of Eq. (1), namely, women and COVID-19, indigenous and COVID-19, and indigenous women across the whole period of observation. For the sake of simplicity, all these interactions have been omitted here, but they are included in the results presented in the corresponding section. Consequently, parameter β ₄ now specifically identifies the additional penalty that indigenous women face in the probability of seeking medical consultation because of the COVID-19 pandemic.

Given that the sample of the indigenous population is relatively small in all CASEN datasets, for all the models, the use of probability weights from each sample is considered. Finally, in addition to the use of municipality fixed effects mentioned earlier, we cluster the standard errors at the region level since baseline differences between regions are expected both in terms of healthcare access and in the proportion of indigenous communities.

Our methodological approach is akin to a difference-in-differences design, with the caveat that the treatment (COVID-19 pandemic) affected all groups simultaneously and, at least in principle, in a similar fashion. Or at the very least, we cannot assume a priori that there were “untreated” groups during the pandemic. However, it is likely that the treatment acted differently for various groups based on their levels of vulnerability. This is precisely what the proposed model captures.

Under the assumptions that our hypothesis is correct and that the probability of receiving medical attention during the pandemic is reduced, a potential issue could arise if, for some reason not explored in this article, the indigenous population experienced fewer illnesses and, therefore, had fewer medical needs during the COVID-19 pandemic. In such a case, the potential reduction observed in medical care would solely be attributed to a decrease in medical needs among the indigenous population rather than a lack of access to medical services. It is worth mentioning that our estimations consider only the population that reported having medical issues in each respective period; thus, the results represent the likelihood of seeking medical attention only for those who indicate needing it.

However, to further test the hypothesis that perhaps the population, particularly comprising indigenous women, had reduced their healthcare needs during the COVID-19 pandemic but not as a consequence of the pandemic, we repeated our preferred model, presented in Eq. (2), and changed the dependent variable to the question of whether the person reported having health problems. For example, if we find an effect on this variable, then part of our main results could be explained by a change in healthcare needs rather than a lack of access. On the other hand, if we do not find an association between the probability of having a medical need and the COVID-19 pandemic for indigenous women, then we can interpret our initial results with greater confidence.

Results

Before presenting the main results of the study, it is important to briefly remind the reader about the sample used. For the analyses conducted, we refer to a population of 91,107 individuals who, when experiencing a medical issue, responded to the question of whether they sought medical consultation or not. Approximately 20% of the individuals reported having some medical issue, while more than 90% of those who claimed to have a medical problem sought medical consultation. Approximately 10% of the sample was indigenous, and 56% were women. More than 80% of the sample was covered by the public health system (FONASA), and approximately 12% had private health insurance (ISAPRE). Regarding education, 26% of the sample had a college degree. In our sample, 64% of the individuals are employed, while the rest are either unemployed or inactive, and the average age is almost 53 years. Finally, 82% of the respondents lived in urban areas, and only 18% lived in rural areas.

A first approach to our research question is to examine the evolution of the dependent variables before and during the COVID-19 pandemic for the different groups considered. Our focus is on indigenous women. However, given our methodological approach, we are interested not in the level of healthcare attendance but rather in observing how medical care for indigenous women changes with respect to other groups, as a consequence of the COVID-19 pandemic.

Figure 1 shows that indigenous people are slightly less affected by health problems than nonindigenous people were, both before (left panel) and during the pandemic (right panel). Similarly, women always report having more health problems than men. Perhaps the most interesting aspect of Figure 1 is how the reported level of health problems decreased for all groups during the COVID-19 pandemic. For the case of indigenous women, the prevalence of pregnancy decreased from 21% in the years before the pandemic to 17% in the year 2020.

Figure 1
Prevalence of health problems by group, before and during the COVID-19 pandemic.

Figure 2 displays the changes in the number of medical consultations among those who reported health problems before and during the COVID-19 pandemic for all groups. Unlike what was observed in Figure 1, there were no evident changes in attendance between the periods, nor were there significant differences between groups. Perhaps the only noticeable difference is that nonindigenous individuals attend medical appointments more frequently, but even so, this difference does not exceed 2% for any group in any period.

Figure 2
Medical consultations by group, before and during the COVID-19 pandemic.

Tables 1, 2, and 3 present the main results of the study. In all three cases, the results without controls are presented in column [1], whereas the results with individual-level sociodemographic controls are presented in column [2]. However, fixed effects at the municipality level are considered in all cases as a way to control for unobservable time-invariant characteristics that differ between municipalities and can significantly affect access to healthcare (local governance, the number and quality of hospitals) or that can speak to the demographic composition of the population within each municipality, among other general characteristics that tend to remain constant over time. The dependent variable for all three tables is whether a visit to the medical center occurred (1) or not (0). For parsimony, we have chosen to only present the main estimates here and leave the table with all the coefficients for the appendix.

Table 1
Impact of COVID-19 on women’s medical attention.

Variable	[1]	[2]
Woman (1 = yes)	0.0190***	0.0200***
	(0.00521)	(0.00457)
COVID year (1 = year 2020)	0.0114	0.0123
	(0.00775)	(0.00763)
Woman*COVID	-0.0122**	-0.0120***
	(0.00425)	(0.00395)
Indigenous (1 = yes)		-0.0160***
		(0.00404)
		(0.00588)
Constant	0.892***	0.835***
	(0.00435)	(0.0184)
Observations	91,107	91,107

• Note: clustered standard errors at the region level in parentheses. Both regressions include fixed effects at the municipality level. Full version of this table, with all considered controls, is presented in the Supplementary Material Table A1. *** p < 0.01, ** p < 0.05, * p < 0.1.
• Source: Own elaboration based on CASEN 2013, 2015, 2017, and 2020.

Table 2
Impact of COVID-19 on indigenous’ medical attention.

Variable	[1]	[2]
Indigenous (1 = yes)	-0.0242***	-0.0201***
	(0.00574)	(0.00560)
COVID year (1 = year 2020)	0.00342	0.00409
	(0.00530)	(0.00535)
Indigenous*COVID	0.0155	0.0154
	(0.0131)	(0.0130)
Woman (1 = yes)		0.0172***
		(0.00436)
Constant	0.905***	0.836***
	(0.00189)	(0.0184)
Observations	91,107	91,107

• Note: clustered standard errors at the region level in parentheses. Both regressions include fixed effects at the municipality level. Full version of this table, with all considered controls, is presented in the Supplementary Material Table A2. *** p < 0.01, ** p < 0.05, * p < 0.1.
• Source: Authors based on CASEN 2013, 2015, 2017, and 2020.

Table 3
Impact of COVID-19 on medical attention of indigenous women.

Variable	[1]	[2]
Indigenous (1 = yes)	-0.0320***	-0.0275***
	(0.00753)	(0.00746)
Woman (1 = yes)	0.0183***	0.0191***
	(0.00512)	(0.00451)
COVID year (1 = year 2020)	0.00799	0.00872
	(0.00734)	(0.00720)
Indigenous*COVID	0.0423***	0.0416***
	(0.0105)	(0.0105)
Woman*COVID	-0.00828*	-0.00813*
	(0.00429)	(0.00392)
Woman*Indigenous	0.0125**	0.0125**
	(0.00558)	(0.00544)
Woman*Indigenous*COVID	-0.0459***	-0.0452***
	(0.0139)	(0.0130)
Constant	0.895***	0.836***
	(0.00420)	(0.0184)
Observations	91,107	91,107

• Note: clustered standard errors at the region level in parentheses. Both regressions include fixed effects at the municipality level. Full version of this table, with all considered controls, is presented in the Supplementary Material Table A3. *** p < 0.01, ** p < 0.05, * p < 0.1.
• Source: Authors based on CASEN 2013, 2015, 2017, and 2020.

Table 1 presents something that was somewhat clear from the descriptive statistics; women show a higher level of medical attention in general. In both cases, the coefficient is close to 0.02, meaning that, regardless of the pandemic, women, on average, visit doctors 2% more often than men. Interestingly, the pandemic did not reduce the number of medical visits at the aggregate level (both coefficients are not statistically significant for this variable), but it did result in a specific reduction in the number of visits for women. That is, as a consequence of the COVID-19 pandemic, women reduced their attendance by 1.2% relative to men. Table 2 also shows that the indigenous population has a lower level of medical care (1.6%) than the nonindigenous population does, that the population with private health insurance (ISAPRE) visits doctors more than does the population in the public health system (FONASA) (the base group), and that individuals’ income also helps explain doctor visits.

Table 2 repeats the analysis but now for indigenous communities, confirming what was mentioned in the previous results. Indigenous individuals have a level of medical care approximately 2% lower than that of their nonindigenous counterparts, regardless of the COVID-19 pandemic. However, unlike women, indigenous communities, when considered together (both men and women), did not experience an additional relative reduction in their level of medical attention because of the pandemic. The rest of the results are similar to those presented previously.

Thus far, it has been established that women seek medical attention more frequently than men do, but that as a consequence of the pandemic, women are more affected in terms of medical visits than their male counterparts are (a 1.2% reduction in their medical visits, relative to men). In this regard, the pandemic had a particularly harsh impact on women’s access to healthcare. On the other hand, individuals belonging to indigenous communities have an overall lower level of attendance to healthcare centers, but the pandemic has not caused a change (either positive or negative) in the gap they usually experience. The remaining question is whether there is an additional penalty for indigenous women specifically, with respect to the rest of the groups in the sample. This is addressed in the results presented in Table 3.

Table 3 presents the main results of the study. First, the previous findings remain consistent; indigenous communities have fewer medical visits, with a difference of more than 2% with respect to nonindigenous individuals. On the other hand, women seek medical attention more frequently than men do, with a coefficient approximately 2% higher than that of men.

Once again, we see that the COVID-19 pandemic did not lead to a significant reduction in overall medical visits. In fact, for the group of indigenous men, the COVID-19 period may have even increased their medical visits. The main finding in Table 3 is the coefficient associated with the interaction term “indigenous woman during COVID-19”. Here, we observe a decrease of more than 4.5% in the level of healthcare utilization for indigenous women during the pandemic. The difference observed for indigenous women, at just over 3 percentage points compared to women in the aggregate, indicates a concentrated impact on this demographic group. Importantly, this result remains statistically significant and largely consistent in magnitude even when controlling for other variables in the regression analysis. Our results confirm our initial hypothesis regarding the heterogeneous effects of the COVID-19 pandemic on medical attention. To this end, it is important to note that (1) indigenous communities at a clear disadvantage under so-called “normal” conditions, with a lower probability of seeking medical attention when in need, and (2) indigenous women were the most affected group in terms of medical visits during the COVID-19 pandemic.

On the other hand, as mentioned earlier, these results could reflect a lower incidence of disease among indigenous women during the pandemic than among their peers. To assess this possibility, an additional model was estimated, repeating the analysis from Table 3 but using the presence (or absence) of medical problems as the dependent variable. The results, available in the Supplementary Material (Table A4), show that there is no significant relationship between the COVID-19 year and a change in levels of health problems in the group of indigenous women. Therefore, these results suggest that the main impact of COVID-19 pandemic is on the relative decrease in healthcare utilization among indigenous women who had health problems but could not seek medical attention during the pandemic.

Final discussion

The COVID-19 pandemic represents a phenomenon that provides a particularly relevant context for understanding the role of the State in the provision of public goods. Faced with the exogenous shock of the pandemic, it becomes possible to observe to what extent the State accentuates the structural inequalities in access to public services in Chile.

We believe the obtained results contribute significantly to the literature on inequality in various domains. First, the study confirms the importance of the intersectional approach for understanding health inequalities^38,39. The mere observation of a single category, such as differences in access to healthcare between men and women, is insufficient to comprehend the full scope of inequality. Instead, the intersection of categories, in this case women and indigenous, highlights the multiplying effect that inequality gains in access to state services, in line with previous research^40-44. From a broader perspective of political economy, the results prompt us to reflect on the structural, political, and public policy determinants that explain health inequality⁴⁵.

Concerning indigenous matters from Chile, in 2000, the Special Health and Indigenous Peoples Program (PESPI by its acronym in Spanish) came into effect, aimed at generating strategies to address health inequities faced by indigenous people resulting from cultural barriers (linguistic, identity-related, differences in perception of health issues, among others). Recent impact evaluations have revealed the lack of resources and proper implementation to promote adherence to healthcare access, particularly in CESFAMs.

The reality of public health in Chile begins to show a discouraging path when observed through an intersectional lens. This is particularly important when considering the health profile of Chile’s indigenous population, which has a “prolonged and polarized epidemiological transition pattern, where high levels of common infections, chronic-degenerative diseases, and injuries persist, within a context of exacerbated social inequalities in health” (p. 2) according to epidemiological studies carried out by Undersecretary of Public Health⁴⁶.

In 2021, the Chilean government conducted an evaluation, concluding that inequalities suffered by indigenous peoples in Chile in terms of form and substance remain in place. The report details that the indigenous population, in general, is at a greater risk of getting sick and dying than is the rest of the population, has a life expectancy 20 years lower than that of nonindigenous groups, and faces precarious health conditions due to structural poverty. These comorbidities increase the vulnerability of these individuals to complications caused by COVID-19, generating concerns about how the epidemic could behave within the indigenous population in terms of its evolution and severity.

In this study, we showed how the relative decrease in healthcare utilization among indigenous women is crucial for understanding the level of inequality in access to health, even when compared to that of their male/indigenous counterparts. There is a significant bias in the distribution of inequality, with a multiplicative component associated with gender and ethnicity in Chile.

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• Funding
  This study received support from the Chilean National Agency for Research and Development (ANID) through a Fondecyt Iniaicion grant (ANID/FONDECYT/11230798), Research funded by grant 2022GEN-SC-0, Temuco Catholic University and grant NCS2022_013 of the Millennium Scientific Initiative of the Ministry of Economy, Development and Tourism (Chile).
• Data availability statement
  The datasets analyzed for this study can be found in the National Socioeconomic Characterization Survey, Casen: https://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-casen. Supplementary material available at: https://doi.org/10.48331/SCIELODATA.U3L6BQ.

• Editores-chefes:
  Maria Cecília de Souza Minayo, Romeu Gomes, Antônio Augusto Moura da Silva, Vania de Matos Fonseca

Data availability

The datasets analyzed for this study can be found in the National Socioeconomic Characterization Survey, Casen: https://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-casen. Supplementary material available at: https://doi.org/10.48331/SCIELODATA.U3L6BQ.

Publication Dates

• Publication in this collection
  17 Aug 2026
• Date of issue
  Aug 2026

History

• Received
  04 Sept 2024
• Accepted
  14 May 2025
• Published
  16 May 2025