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Where are Disabled Women amidst the Sustainable Development Agenda in Costa Rica?

Erika Sanborne, University of Minnesota

I first shared an iteration of this study at:
Population Association of America (PAA 2023) Annual Meeting,
New Orleans, LA US, April 13, 2023

Session: Health, Health Behaviors, and Healthcare

View my original PAA 2023 poster pdf.

This page was updated on

disabled people at work

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Research Questions

  1. How do education, healthcare and perceived discrimination relate to subjective well-being among Costa Rican women, and how does perceived discrimination vary by ethnicity?
  2. How does the high disability prevalence in Costa Rica intersect with the overall high subjective well-being, and does this reveal something about the adaptive preferences of disabled women?

Background

Case Study: Costa Rica

When evaluative well-being data are aggregated at the country level and appropriately weighted, Costa Rica emerges as a standout. From my preliminary, exploratory analysis of life evaluation using IPUMS MICS-6 data, Costa Rica emerged as a necessary case study.

This shows Costa Rica in the top right corner on disability and life evaluation
This is a two-way categorical data visualization depicting my preliminary analysis of life evaluation (Cantril Ladder) on the y-axis, and disability prevalence (percent) on the x-axis. The graph shows that Costa Rica is the nearly the highest on both measures, which is paradoxical, because disabled people do not usually also have high evaluative well-being.

Numerous other sources, such as the Happy Planet Index (Abdallah, Hoffman and Akenji 2024), the Sustainable Development Index (Hickel 2020), and the World Happiness Report (Helliwell et al. 2024), affirm Costa Rica’s comparatively highly ranked subjective well-being among countries, based on its high aggregate evaluative well-being scores in their measures as well.

These observations align with other assessments. The World Bank (2024) recognizes Costa Rica as “a success story in terms of development” due to its steady economic growth, stable democracy, and commitment to social progress. The Costa Rican economy is one of the strongest, and its poverty rates are among the lowest in the Latin America and Caribbean (LAC) region (World Bank 2024). By 2023, poverty levels had returned to pre-pandemic benchmarks.

Costa Rica shows losing ground on 5 of 15 SDGs
This is a graphic from the Sustainable Development Report 2023 Summary. Shared with permission. It depicts “Headline Indicators” for Costa Rica.

The previous graphic gives a snapshot overview of where Costa Rica is with respect to their sustainable development goals as of 2023. While this summary reflects moderately improving amidst significant challenges for SDG #3, the detailed report reveals that their target for subjective well-being is “in the green” at 7.1. This suggests Costa Rica is on track towards the 2030 goal of 7.6. Costa Rica has also shown a commitment to expanding capabilities through investments in universally accessible socialized healthcare and public elementary education (Misión Permanente de Costa Rica ante Naciones Unidas 2024).

But what of the inexplicably high prevalence of disability, where so many have deemed development a success? According to the National Survey on Disability, this disability prevalence is even higher among Costa Rican women (60.9%) versus Costa Rican men (39.1%) (INEC 2019).

In developing countries, disability prevalence is generally exacerbated by poverty-related risks like malnutrition, limited healthcare access, unsafe work conditions, environmental pollution, and inadequate water and sanitation facilities (World Bank 2024).

Such disparities in healthcare access, water and sanitation, ecology and other indicators of progress underscore the United Nations’ call for disability-disaggregated data to pinpoint and address structural inequalities (United Nations 2019; United Nations Development Group 2011; United Nations Development Programme 2021).

In this way, disability prevalence can potentially not only reflect a range of social and economic inequalities but may also illuminate the reciprocal impact of systemic challenges on mulitply marginalized people.

What remains as a question with Costa Rica, then, is what is going on? Why is there such high disability prevalence, especially among women, when key indicators seem to suggest this should not be the case here?

This paradoxical situation of disabled development also raises important questions about both the nature of subjective well-being and its measurement. In this first study, I hope to contribute to theory and to the demographic study of evaluative well-being by investigating this paradox.

Disability in the 2030 Agenda

The 2030 Agenda for Sustainable Development with its 17 sustainable development goals (SDGs) and 169 targets sets out to try to end poverty and the unequal access to resources that produces it (United Nations 2016). The overarching stated value of the 2030 Agenda is to “leave no one behind” (United Nations 2020b) because development would not be sustainable if only some subpopulations were a part of it.

The words “disability” or “persons with disabilities” can be found 11 times in the 2030 Agenda, and “persons in vulnerable situations” appears six additional times. To leave no one behind requires first disaggregating data, and by more than just gender, age, race/ethnicity and location, in order to unmask inequalities so that they can be addressed (United Nations 2020a).

The UN Convention on the Rights of Persons with Disabilities (CRPD) and its Optional Protocol (OP) were adopted in 2006 with the objective of extending to disabled people equal human rights and respect (United Nations 2006). This provides the international backdrop of disability justice in development.

A recent study using DHS and MICS data, along with the Multidimensional Poverty Index, considered questions about the magnitude of deprivations and poverty for disabled people in consideration of sustainable development (Pinilla-Roncancio and Alkire 2021). Their main finding was a development-disability gap, which was greater in middle-income countries than in low-income countries.

As of the 13th Session of the CRPD, 190 States have ratified the Convention (United Nations Office at Geneva 2024). The CRPD recently reviewed Costa Rica’s progress on disability rights. They praised its employment initiatives and accessible tourism. Experts inquired about efforts to ensure outdoor activities are accessible and raised concerns about abortion policies, especially in cases involving intellectual disabilities and violence. Costa Rica stressed its commitment to disabled people’s access to public and private services and equal opportunity, and the report overall was a positive one (United Nations Office at Geneva 2024b).

Social Stress Process Model

Sociologists can understand the relationship between social factors and social outcomes (such as life evaluation or evaluative well-being) through the social stress process (Pearlin 1989). A fundamental principle of the stress process model is that well-being outcomes are not randomly distributed in society. When systematic gaps are observed, they are thought to reflect social, structural conditions that systematically disadvantage subgroups (Pearlin 1999).

It’s important to not discount the power of that which moderates the relationships between those elements of social structure (i.e. “the constellation of stressors”) and the outcomes of interest (i.e. well-being). In other words, just because multiply marginalized groups are structurally disadvantaged, they are not necessarily going to score lower on outcomes that reflect evaluative well-being and similar metrics.

That sort of paradox or surprise too can be accounted for via the social stress process, because of the presence of possible coping resources, themselves an elaborate constellation. Researchers found such an explanation to a paradox they initially observed in mental well-being data for Black Americans (Louie et al. 2022).

The paradox they had observed was that even though the group (Black Americans) experience greater burdens, which would suggest lower mental health scores, the group also possesses more coping resources, such as self-esteem and social support, which partially mediated the influence of racism on their mental health. It doesn’t mean the racism wasn’t bad, just that the coping resources were magnificent.

Social stress model remains the conceptual base for the sociological study of how social factors and evaluative well-being are related today (George 2014:251). It has also been the basis of considerable scholarship on related sociological topics, such as understanding links between education and health (Ross and Wu 1995), or minority stress and mental health in gay men (Meyer 1995).

We do these kinds of analyses because subpopulations can have categorically different levels of an important outcome, and the explanation may be found in the left side of the equation, within the constellation of stressors which reflect the social structure itself.

These explanations may also be found in the array of coping resources that mediates or moderates the effects. This framing offers a sociological framework for identifying inequalities that moves beyond describing differences in frequency distributions.

Moving beyond describing differences in life well-being across subnational regions, an analysis grounded in the social stress model will seek to identify how the subgroups meaningfully differ. By applying the social stress model, researchers may also identify underlying structural issues potentially influencing these well-being gaps.

Capability Approach

Predominant frameworks for measuring well-being today involve standard indicators such as income or consumption. Income serves as an initial proxy for the standard of living and, where it may fall short, researchers often supplement it with measures of consumption, according to non-capability researchers using traditional, resource-based measures of well-being (Burchardt and Hick 2018:43).

The resource-based models also include additional non-monetary indicators, such as assets and access to basic needs like housing, water, education, and healthcare. The OECD Wellbeing Framework, shared in the Methods discussion: About the Cantril ladder, is mostly a resource-based model for measuring multidimensional well-being.

In contrast to conceiving of well-being in terms of resources, the capability approach, developed by Amartya Sen (Sen 1987; Sen 1999), and elaborated by Martha Nussbaum (2000, 2011) is a normative framework that emphasizes the importance of individuals having the opportunities and freedoms to achieve well-being in ways that they value. This approach challenges traditional and most modern metrics by focusing on what people are actually able to do and be, rather than solely on what they have.

A central tenet of the capability approach is the enhancement of possibilities, looking beyond economic success to a broader range of individual freedoms and opportunities. Nussbaum further contributes to this framework and notes that protecting these capabilities should be a priority in justice considerations (Nussbaum 2011).

The capability approach is useful for assessing inequalities in well-being across groups. It takes into account a wide range of factors that affect individuals’ real freedoms and choices. The capability approach’s view of well-being makes it a suitable theoretical lens through which to consider the relationships between education, healthcare, disability, discrimination and life evaluation among subpopulations of women.

For additional methods discussion, including the limitations of the evaluative well-being measures from a capability approach perspective, and the concern for adaptive preferences, please see the Methods discussion: About the Cantril ladder.

Hypotheses

Hypothesis 1a: Education and healthcare are positively associated with life evaluation among Costa Rican women, reflecting their roles as capability-enhancing factors.

Hypothesis 1b: Perceived discrimination is negatively associated with life evaluation, indicating the adverse effects of social stressors.

Hypothesis 1c: Indigenous and Black/Afro-Costa Rican women report higher rates of perceived discrimination compared to White women.

Hypothesis 2: Despite the high prevalence of disability, disabled women in Costa Rica report higher levels of evaluative well-being compared to global norms for disabled people, suggesting that adaptive preferences may play a role in their life evaluation.

Contributions

This study fills a critical data gap in country, adding to the 2018 National Survey on Disability data and underscoring the importance of disability-disaggregated subjective well-being data. It also investigates a paradoxical empirical situation of high evaluative well-being coupled with high disability prevelance, both in aggregate. Given how important it is for disabled women to not be left behind, this situation poses important questions about the nature of well-being.

This study also includes a possible empirical test of an aspect of the capability approach, by exploring the concept of adaptive preferences as applied to the Cantril ladder’s measurement of well-being among disabled women in Costa Rica.

By examining the extent to which disabled women report unexpectedly high evaluative well-being—consistent with hypothesis #2—this research could affirm the Cantril ladder’s ability to capture aspects of well-being that are not influenced by such adaptation.

If the study does find that disabled women in Costa Rica report high evaluative well-being, such a finding would suggest that the Cantril ladder may be capturing the influence of adaptive preferences on well-being assessments.

From a theoretical perspective, this would suggest further investigation into the conditions under which adaptive preferences operate and their limits in contributing to the Cantril ladder measure of subjective well-being or life evaluation.

References

Methods

Data Source

This research will analyze the IPUMS MICS Round 6 for Costa Rica. Please find a Methods discussion: About IPUMS MICS on the home page for this prospectus.

Dependent Variable: Life Evaluation Measure

The outcome measure of evaluative well-being in this study is the Cantril ladder item, from IPUMS MICS Round 6. See also: Methods discussion: About the Cantril ladder.

Key Independent Variable: Constructed Disability Indicator

Disability is functional impairment in this study. The indicator of disabled here is constructed from six IPUMS MICS ordinal survey items that ask respondents to report their level of functional impairment.

Women were asked whether they had difficulty: seeing, hearing, walking, remembering and concentrating, communicating, and with self care. For each item, women could report that they have ‘no difficulty’, ‘some difficulty’, ‘a lot of difficulty’, or whether they cannot perform the given function at all.

If women report at least ‘some difficulty’ in at least one domain, they are coded as disabled in the present study. While this leads to higher prevalence rates than studies which focus on so-called ‘severe disability’, my intention here is to include as many disabled women as possible. I had also hoped to use a cut-off that would result in overall disability prevalence rates consistent with the National Survey on Disability carried out during the same year in Costa Rica (INEC 2019), and this threshold accomplishes that comparability.

Other Dependent Variables

ethnicity: constructed binary indicator; Costa Rica is about 2/3 White and due to data limitations, ethnicity of household head needed to be binned into white and people of color (non-white respondents).

discrimination: binary indicator constructed such that 1=report of having felt personally discriminated against in the 12 months prior to survey administration, for one or more of the six categories surveyed (sexual orientation, age, religion or belief, disability, gender, or any other reason).

wealth: binary indicator constructed from wealth index score to be 1 for respondents with positive wealth index score and 0 for those with negative wealth index score.

marital: binary indicator constructed using marital status, categories were combined so that women were 1=married or partnered, and 0=not married, with the latter including women who reported being divorced, widowed, separated or never married.

education: highest level of school attended by the woman, categorized into four ordered levels (less than primary, primary, secondary, or tertiary/higher/university).

healthinsur: indicates whether a woman has health insurance.

region: reports the categorical, geographic subnational region according to which of the seven provinces the woman lives within in Costa Rica.

Regression Model

Generalized Ordered Logit Model

Let Yi represent the ordered response for life satisfaction bin (lsbin), for individual i. The generalized ordered logistic regression model for estimating the probabilities of Yi ≤ j falling into specific categories given the predictors is:

Where:

  • j indexes the cutpoints (or thresholds) for each category of lsbin, excluding the highest category.
  • αj are the intercept terms or threshold parameters for each category j.
  • β1 through β7 are the coefficients associated with the predictors.

This model was selected because of the ordered nature of the dependent variable, where categories on the Cantril ladder are ordered but the distances between rungs are not meaningful distances. While the distribution’s shape is not specifically constrained, the proportional odds assumption must be maintained.

Briefly, this implies that the effect of model factors, such as disability, remains constant across the scale of the outcome. Therefore, if being disabled influences the likelihood of a person rating their well-being as a 9 on the 0-10 Cantril ladder, it should similarly affect their ratings at 6 or 2, with all other factors held constant.

I use the user-written Stata command gologit2 to test the proportional odds assumptions for each term. This command fits a partial proportional odds model—unlike ologit, which assumes full proportional odds—allowing for varying effects of some predictors across the Cantril ladder’s outcome levels.

gologit2 computes Wald tests to check the consistency of predictor effects across categories. If the effects are not significantly different, the proportional odds assumption is supported for those predictors. If the assumption holds only for certain predictors, gologit2 can adjust to fit a partial proportional odds model accordingly.

Preliminary Results

Figure 1: Life Evaluation by Province and Disability Status

disabled women left behind

Note. This graph shows kernel density plots for the life evaluation outcome measure (binned Cantril ladder) for Heredia, the wealthiest province, and for Limón, the least wealthy province. Noteworthy is the well-being penalty associated with disability for women living in Limón. Despite having the fewest economic resources, non-disabled women in Limón (and Puntarenas) have the highest life satisfaction of women in Costa Rica.

Table 1: Regional Disability Prevalence by Country

Disability
Indicator
Costa Rica Cuba Dominican
Republic
Honduras Suriname Total
Not Disabled 4,554
51.10%
7,334
80.51%
16,426
68.49%
12,817
57.36%
6,033
70.70%
47,164
67.84%
Disabled 3,663
48.90%
1,608
19.49%
6,562
31.51%
8,024
42.64%
2,500
29.30%
22,357
32.16%
Total 8,217
100.00%
8,942
100.00%
22,988
100.00%
20,841
100.00%
8,533
100.00%
69,521
100.00%

Note. These are IPUMS MICS Round 6 data (2018-2019) for countries in Latin America and Caribbean (LAC) Region. This is a frequency table of the disability indicator used in this study, in which a person is disabled if they have at least ‘some’ difficulty in at least one functional domain. This coding results in a prevalence rate closer to the 2018 National Survey on Disability conducted by INEC-Costa Rica, which found 50.7% of women to be mild-to-moderately disabled.

Table 2: Regional Severe Disability Prevalence by Country

Disability
Indicator
Costa Rica Cuba Dominican
Republic
Honduras Suriname Total
Not Disabled 7,470
90.58%
8,807
98.50%
22,177
95.62%
19,256
91.73%
8,221
96.34%
65,931
94.84%
Disabled 747
9.42%
135
1.50%
811
4.38%
1,585
8.27%
312
3.66%
3,590
5.16%
Total 8,217
100.00%
8,942
100.00%
22,988
100.00%
20,841
100.00%
8,533
100.00%
69,521
100.00%

Note. These are based on IPUMS MICS Round 6 data (2018-2019). This is a frequency table of an indicator of severe disability, in which a person is disabled if they have at least ‘a lot’ of difficulty in at least one functional domain.

Figure 2: Life Evaluation for Women in IPUMS MICS 6 Costa Rica, 2018 (n = 7483)

Note. This graph shows the distribution of lsladder for all surveyed women in Costa Rica (with levels 0-4 binned together). The outcome measure is an 11-level ordinal variable but, as is shown in this graph, only 3% of women rated their life satisfaction 0-4 on that scale. And while I believe it is very important to tell their stories, because they are the women who are most left behind, it’s mathematically unhelpful to not bin those low categories together.

Table 3: A Few Findings from the First Generalized Ordered Logit Estimate, for discussion (n = 6971)

Preliminary Unfiltered Findings on Life Evaluation Factors from the Stata Output
Variable/Level Direction Coefficient P>|t| 95% CI
Education (Tertiary/Higher) Positive 1.385 (Level 4) 0.013 [0.299, 2.470]
Health Insurance (Yes) Positive 0.255 (Levels 4, 5, 6) 0.023 [0.035, 0.475]
Disabled Negative -0.692 (Level 4) 0.010 [-1.220, -0.164]
Disabled Negative -0.826 (Level 5) 0.000 [-1.095, -0.557]

Note. Tertiary or higher education, and having health insurance, are positively associated with higher life evaluation levels, supporting Hypothesis 1a. Conversely, and as expected, being disabled is significantly negatively associated with life evaluation, which partially aligns with Hypothesis 2 but also suggests that while disability might involve adaptive preferences, it still poses challenges to subjective well-being. Briefly, I don’t think it’s the disabled women who are buoying the Costa Rican subjective well-being targets. I think they are being left behind, and this, along with Figure 1, is early affirmation, or a focal point for the additional data discoveries to be revealed in the remaining analyses from Study 1.

Limitations

While the popularity of well-being economy and subjective well-being measures are going strong, limitations span from methodological challenges to the subjective nature of an outcome measure such as the Cantril ladder. Limitations of the outcome measure are discussed in the Methods discussion: Catril ladder section.

While exploring adaptive preferences is an intentional part of this study, it also brings a limitation. Adaptive preferences can be complex to measure and interpret because they involve subjective adjustments to aspirations based on circumstance, which might not be accurately assessed through survey data. There is always a risk of response bias/social desireability also.

And even while a life course perspective is likely to aid in understanding observed patterns, and in interpreting results, the same effects possibly influencing people can include factors that are unexamined altogether. This could reflect omitted variable bias perhaps, or some other confound.

I’m mindful of the critique raised by Kimberlé Crenshaw, that unless an intersectional analysis is taken to a political level, all we’re doing is describing people differently. In the unlikely event that it is all I end up doing with this dissertation research, then I too will have done nothing.

I also feel that there are some limitations to using the Washington Group Short Set (WG-SS) disability items. They have evolved to be accepted as a sort of unequivocal gold standard for comparative survey data science with disability disaggregated data.

They tout themselves as the social model variables, yet they still lean heavily towards “personal problem” rather than “social issue” and, in my opinion, the risk here is that our research, even while doing what’s recommended, could devolve into “counting crips” like so much medical research does. As one weary, disabled researcher, I think this is something we should be talking about as well, and which I will take up to some extent in study 2.

Stata Code

Loading and Merging Data

Cleaning Data and Creating Indicators

Descriptives

Analysis

About Erika Sanborne

Erika Sanborne has been producing digital media since 2010, specializing in portraiture for people who hate it but need it, digital graphics restoration of many kinds, accessible explainers and instructional technology (corporate explainers, classroom tech), data visualizations and animation.