Abstract
Objectives
The percentage of older adults in Mexico with difficulty completing activities of daily living (ADL) who receive assistance from family appears to be decreasing. We compared 2 birth cohorts of older adults in Mexico to investigate whether this trend reflects an increase in unmet caregiving needs or a decrease in the need for care.
Methods
We selected Mexican Health and Aging Study participants aged 60–76 in 2001 (n = 4,805) and 2018 (n = 6,494). ADL tasks were dressing, walking, bathing, getting in and out of bed, and toileting. Participants who reported difficulty with an ADL were asked if anyone helped them with the task. Logistic regression was used to estimate adjusted odds ratios (aOR) for cohort differences in ≥1 ADL limitations and help with ≥1 ADL. We used a decomposition analysis to identify participant characteristics that mediated cohort differences in receiving help with ≥1 ADL.
Results
The 2018 cohort had higher odds for ≥1 ADL limitations (aOR = 1.85, 95% CI = 1.60–2.14) but lower odds for help with ≥1 ADL (aOR = 0.66, 95% CI = 0.49–0.89). Among participants with ADL disability, the 2018 cohort had fewer living children and a lower prevalence of probable dementia. The lower number of living children and lower prevalence of probable dementia explained 9.34% and 43.7% of the cohort effect on receiving help with ≥1 ADL, respectively.
Discussion
The declining percentage of older adults in Mexico with ADL disability receiving assistance may not reflect increasing unmet needs. However, the increased prevalence of ADL disability will increase the number of older adults needing informal care.
Keywords: Activities of daily living, Caregiving, Cohort analysis
Population aging in Mexico has coincided with a rapid epidemiological transition (Stevens et al., 2008). Consequently, older adults in Mexico have survived early life exposures to infectious diseases (Samper-Ternent et al., 2012) and have aged in a time of increasing prevalence of chronic health conditions, such as diabetes and dementia (Meza et al., 2015; Prince et al., 2016). Additionally, the epidemiological transition in Mexico has occurred in the context of high social inequality (Stevens et al., 2008), and many older adults have experienced socioeconomic disadvantages their entire lives (Torres & Wong, 2013; Wong & Palloni, 2009).
Early life disadvantages, chronic conditions, and experiencing social inequities over the life course are all risk factors for limitations in activities of daily living (ADLs) among older adults (Bowen & Gonzalez, 2010; Macinko et al., 2021; Martin et al., 2017). Data from cohort studies of aging in Mexico indicate that ten to fifteen percent of older adults in the early 2000s and 2010s had ≥1 ADL limitations (Gerst-Emerson et al., 2015; Lee et al., 2018; Payne, 2015). These percentages are similar to the percentage of older adults with ADL disability in the United States during the same period (Gerst-Emerson et al., 2015; Payne, 2015). Evidence suggests a compression of ADL morbidity in many high-income countries (Chatterji et al., 2015; Freedman et al., 2002; Tawiah et al., 2021), but these trends may not occur for middle-aged and older adults in Mexico. Using data from the Mexican Health and Aging Study, Payne and Wong (2019) reported that the proportion of total life expectancy spent living with ≥1 ADL limitations (ADL disability) doubled between 2001 and 2012 for adults aged 50–59 and aged 60–69 in Mexico. Furthermore, the proportion of remaining life expectancy with ADL disability increased from 13% for adults aged 70–79 in 2001 to 19% for adults aged 70–79 in 2012 (Payne & Wong, 2019).
An increase in the prevalence of ADL disability among older adults in Mexico could place greater demands on family members to provide care (Angel et al., 2021). Mexico has a limited infrastructure to meet the needs of an aging population, and it is unclear how the caregiving needs of older adults will be met. An analysis of the Mexican Health and Aging Study indicated that the percentage of participants with ADL disability who reported receiving assistance with ≥1 ADL decreased from 53.2% in 2001 and 55.1% in 2003 to 25.5% in 2012 and 27.7% in 2015 (Andrade & López Ortega, 2021). A concern is that this trend reflects an increase in the proportion of older adults in Mexico with unmet needs. Government policies in the 1960s and 1970s that promoted family planning contributed to families in Mexico having fewer children (Diaz-Venegas et al., 2017). Additionally, more adult children are moving away for work (Pérez-Campuzano et al., 2018), and more women are entering the workforce (Braunstein & Seguino, 2018). The decrease in family size and increase in labor force participation has reduced the number of children available to help older family members with daily tasks.
Older adults in Mexico often expect their children to help them meet their housing, financial, and long-term care needs (Gutiérrez-Robledo et al., 2012). Traditional gender roles in Mexico have resulted in the expectation that women provide informal care rather than men (Angst et al., 2019). Gender roles have also contributed to the idea that daughters will assist with daily activities and other direct care tasks, whereas sons will provide financial support. However, the type of ADL assistance (e.g., mobility versus bathing) and the parent’s gender can influence whether a daughter or other family member provides care (Pillemer & Suitor, 2014).
The increasing number of older adults in Mexico living with chronic conditions such as diabetes, hypertension, and dementia has important implications for whether the family can continue to be a primary source of long-term care for older adults. Older adults with multiple chronic conditions are at an increased risk of having limitations in several ADLs, which places increased demands on families to provide care. Family members may also feel unprepared to take on caregiving tasks, such as administering medications, that are important to older adults safely managing their chronic conditions.
The shrinking family sizes, increasing number of older adults living with chronic conditions associated with ADL disability, and decreasing availability of family members who can provide care all suggest the trends in ADL disability and receiving assistance with ADL tasks are evidence of rising unmet needs for older adults in Mexico. However, other interpretations and explanations warrant investigation. Receiving assistance with ADLs can be a marker of more severe ADL disability (Yang et al., 2022). Therefore, an alternative interpretation of the decreasing trend in ADL assistance is that more recent cohorts of older adults in Mexico have less severe disability and thus have less need for family care.
When studying population-level trends, it is important to consider the changing social context in population aging in Mexico is occurring. Mexico has expanded social support programs and implemented health care reforms that have caused successive generations of older adults to age in different social contexts. These contextual changes could contribute to population-level trends in the severity of ADL disability and the likelihood of receiving assistance in daily activities for older adults in Mexico. From 2000 to 2018, Mexico expanded the eligibility criteria and benefits of several social support programs, including noncontributary pension programs such as 70 y más. The program 70 y más began in 2007 and provides a monthly pension to older adults who do not receive social security benefits (Aguila & Casanova, 2020). The 70 y más has been effective in reducing the prevalence of ADL limitations and thus a reduction in the percentage of older adults who received assistance with ADLs (López-Ortega & Aguila, 2022). Other social support programs that have benefited older adults include the conditional cash transfer program Progresa, a supplemental income program for workers in agriculture (PROCAMPO—Program of Direct Supports to the Farmland), and a retirement benefit program from Mexico’s National Institute of Senior Citizens (INAPAM—Instituto Nacional de las Personas Adultas Mayores), formally known as INSEN (Instituto Nacional de la Senectud).
In 2004, Mexico introduced a public health insurance program called Seguro Popular that provided health care coverage for a broad range of health care services to individuals and their families who were previously uninsured (Gakidou et al., 2006). Seguro Popular was effective in reducing the uninsured population. The percentage of uninsured adults aged 50 and older decreased from 45.9% in 2001 to 14.8% in 2012 (Avila et al., 2020). Seguro Popular increased the use of diagnostic screenings and treatment of chronic conditions associated with ADL disability, such as diabetes and hypertension (Beltran-Sanchez et al., 2015; Parker et al., 2018). Additionally, evidence suggests Seguro Popular has had small effects on slowing declines in mobility, ADLs, and instrumental ADLs (IADLs) for middle-aged and older adults with chronic conditions (van Gameren & Enciso, 2022).
Given the different interpretations of the trends in ADL disability and receiving assistance with ADL tasks among older adults in Mexico, our primary research question was, does the decrease in the percentage of older adults in Mexico with ADL disability who receive assistance with daily tasks reflect an increase in unmet caregiver needs or less need for informal care? Our objective was to identify sociodemographic and health characteristics of older adults in Mexico that may contribute to the population-level trend in receiving assistance with ADL tasks. We focused our analysis on family size and household composition, chronic conditions, and social support programs because of the large changes in these characteristics among older adults in Mexico. These characteristics are also associated with ADL disability and/or receiving assistance with daily tasks.
Method
Data and Sample Selection
The MHAS is an ongoing longitudinal study of population aging in Mexico (Wong et al., 2017). The MHAS began in 2001 with a sample of 15,373 participants aged 50 and older and their spouse or partner. Follow-up interviews were completed in 2003, 2012, 2015, 2018, and 2021. The MHAS was replenished in 2012 with a cohort of 5,896 participants aged 50–59 and in 2018 with 4,598 participants aged 50–55.
We conceptualized a cohort effect as the unique social and cultural contexts a person is born into and lives that shape their life course experiences as they age (Keyes et al., 2010). Thus, we used data from the 2001 and 2018 observation waves to create two independent birth cohorts of participants aged 60–76 in 2001 (birth years 1925–1941) and aged 60–76 in 2018 (birth years 1942–1958). We chose these birth years because it allowed for our analysis to include the largest number of MHAS participants interviewed in 2001 and 2018 who were born in nonoverlapping years. We first identified 5,915 participants in 2001 and 7,424 participants in 2018 who were 60–76 (Figure 1). As key measurements about ADL disability and care were not asked of proxies, we excluded 420 and 498 participants from the 2001 and 2018 cohorts, respectively, who required a proxy interview. Next, we excluded 128 participants from the 2001 cohort who reported never seeing a physician. We removed these participants because they were not asked about self-reported health conditions. We excluded 562 participants from the 2001 cohort and 432 from the 2018 cohort who were missing values for one or more variables of interest. The 2001 cohort included 4,805 participants and 6,494 participants for the 2018 cohort.
Figure 1.
Selection of Mexican Health and Aging Study participants aged 60–76 in 2001 and aged 60–76 in 2018.
Participants in the 2001 cohort with missing data completed fewer years of education (3.1 years vs 3.9 years, p < .01) and were less likely to live in a community with ≥100,000 people (46.4% vs 59.9%, p < .01) than the 4,805 participants in the final sample. The differences in the average age, sex, and number of living children among participants in the 2001 cohort according to missing ≥1 variables were not statistically significant. We did not detect any statistically significant differences in the demographic characteristics of participants in the 2018 cohort according to missing data for ≥1 variable.
Variables
Difficulty in activities of daily living
Participants were asked if they have difficulty because of a health problem with dressing, walking across a room, bathing, eating, getting in or out of bed, and toileting. We categorized participants who answered yes or cannot do as having a limitation for the ADL task. Our primary outcome was having ≥1ADL limitations. We also summed the number of ADL limitations for the descriptive analysis and categorized participants as having 0, 1, or ≥2 ADL limitations. Two or more ADL limitations can indicate severe ADL disability (Wu et al., 2019).
Receiving help with activities of daily living
Participants who respond yes, cannot do, or does not do when asked if they have difficulty with an ADL task are then asked if a spouse helps them complete the task and if anyone else helps them. We used the responses from these two questions to identify participants who reported receiving help with each ADL task and participants who received help with one or more ADL tasks.
Mobility limitations
MHAS participants were asked if they have difficulty because of a health problem with getting up from a chair, stooping, kneeling, or crouching, reaching or extending arms above shoulder level, lifting or carrying objects heavier than 5 kg, and pulling or pushing large objects. We dichotomized participants as having one or more limitations and summed the number of limitations. We refer to this functional domain as mobility limitations as most items are important to mobility.
Health characteristics
Self-reported health conditions included having been diagnosed with hypertension, diabetes, chronic lung disease (e.g., emphysema and asthma), heart attack, stroke, and arthritis. Participants could respond yes or no. To account for the comorbidity burden, we summed the number of self-reported health conditions and categorized participants as having zero, one, two, three, or four or more conditions. Participants were also asked if they had fallen in the last 2 years and if they often suffered from pain. Participants could respond yes or no.
Cognitive status
We categorized participants as having no cognitive impairment, cognitive impairment with no dementia (CIND), functional impairment with no cognitive impairment (FICI), and probable dementia according to their performance on five cognitive assessments and difficulty completing IADL (Mejia-Arango & Gutierrez, 2011). The five cognitive assessments were recalling an eight-word list (immediate and delayed recall), copying a figure, drawing the figure from memory, and animal naming (Mejia-Arango et al., 2021). We used MHAS data files that included imputed values for participants with missing values or nonresponse on one or more cognitive items (Downer et al., 2021). The IADL measures were cooking a hot meal, shopping, taking medicine, or managing finances. We dichotomized participants as having difficulty in ≥1 IADL. Participants who scored 1.5 standard deviations or lower than the sample mean on ≥2 assessments and had limitations in ≥1 IADL were categorized as dementia. Participants with cognitive impairment but no IADL limitations were classified as CIND. Participants with one or more IADL limitations but no cognitive impairment were classified as FICI. All other participants were classified as having no impairment (Mejia-Arango & Gutierrez, 2011).
Family size and living arrangements
We defined family size as the number of living children. All participants who had at least one child born alive were asked how many of their children were still alive. Participants with zero living children included participants who had never had children.
We used the household roster to create a categorical variable that reflected a participant’s living arrangement with a spouse or partner, children, and extended family. We differentiated between participants who lived with children according to whether any of these children were a daughter aged 15 and older. We used age 15 as the cutoff to identify daughters who were conceivably old enough to provide informal care. We grouped participants into five mutually exclusive categories: (a) Alone; (b) Partner only; (c) Partner and with ≥1 daughter aged 15+ or with daughters aged 15+ only; (d) Partner and with children (son only or son and daughters younger than aged 15) or children only (e) Partner and with extended family or with extended family only; and (f) other. To minimize the number of groups, we did not consider whether participants lived with grandchildren.
Health insurance and social support programs
We included variables for health insurance coverage and receiving financial support from a social program. In 2001, participants were asked if they had health insurance coverage through the Mexican Social Security Institute, Institute for Social Security and Services for State Workers, Pemex (Petróleos Mexicanos—a state oil company that provides health insurance to employees), defense or navy, private provider, or other. In 2018, Seguro Popular was added as a response option for health insurance coverage. We dichotomized participants as having any form of health insurance coverage.
In both observation waves, participants were asked if, in the last year, they received financial support from a social program, such as Procampo, Progresa, or INSEN. Participants could respond as yes or no.
Demographic characteristics
Demographic characteristics included age, sex, years of formal education, marital status, and community size. We categorized marital status as: (a) married; (b) widowed; and (c) not married (divorced, separated, or single). The MHAS groups participants according to living in a community into four categories: (a) ≥100,000 residents; (b) 15,000–99,999 residents; (c) 2,500–14,999 residents; and (d) < 2,500 residents.
Statistical Analysis
We used a pooled sample of both birth cohorts and included a cohort term for all analyses. The 2001 cohort was the reference group in all analyses. Differences in demographic and health characteristics between the 2001 and 2018 cohorts were described using Chi-square tests and independent sample t tests. To assess the differences between the cohorts, we calculated the standardized difference in demographic and health characteristics between the 2001 and 2018 cohorts. The standardized mean difference is often used to assess the balance of covariates before and after propensity score matching, with values greater than 0.25 indicating a meaningful difference between unmatched and matched samples (Stuart et al., 2013).
Logistic regression was used to estimate adjusted odds ratios for cohort differences in ≥1 ADL limitations, limitations for each ADL task, receiving help with each ADL task, and help with ≥1 ADL. All analyses were adjusted for age, sex, education, community size, number of self-reported health conditions, falls, pain, and cognitive status. The analyses for receiving help with ADLs were further adjusted for the number of living children and living arrangements. The models for receiving help with ADLs only included participants with ADL disability. We used the Karlson, Holm, and Breen method (Kohler et al., 2011) to test the mediating effects of participant characteristics on cohort differences in receiving help with ≥1 ADL.
We included education, number of living children, living arrangements, cognitive status, health conditions, social programs, and health insurance as mediating variables in the KHB analysis. We selected these mediating variables based on evidence for birth-cohort differences in these characteristics for older adults in Mexico (Diaz-Venegas et al., 2017; Payne & Wong, 2019; Wong et al., 2017). These demographic and health characteristics also contribute to whether an older adult receives assistance in daily activities, and thus represent plausible mechanisms that could contribute to birth cohort differences in receiving assistance with daily activities. Age, sex, and community size were included as confounding variables.
The descriptive analyses and logistic regression models were completed using R version 4.1.2. The decomposition analysis using the KHB method was completed using STATA.
Results
Cohort Differences in Demographic and Health Characteristics
Supplementary Table 1 shows the demographic and health characteristics of all participants in the 2001 and 2018 cohorts and those with ADL disability. In 2001, 4.5% of participants had ADL disability and received assistance with ≥1 ADL, and 7.6% had ADL disability but did not receive assistance with ≥1 ADL task. The percentage of participants in the 2018 cohort with ADL disability who did and did not receive assistance with ≥1 ADL task was 4.4% and 12.0%, respectively. For all participants, the largest cohort differences according to the standardized mean difference were for years of education, the number of living children, having health insurance, and receiving benefits from a social program (Supplementary Table 1).
In general, the cohort differences between participants with ADL disability were similar to the total sample (Supplementary Table 1). An exception was the percentage of participants with ≥2 ADL limitations. In the total sample, the percentage of participants with ≥2 ADL limitations was higher in 2018 (7.3%) than in 2001 (6.2%). Conversely, among participants with ADL disability, the percentage of participants with ≥2 ADL limitations was lower in 2018 (44.9%) than in 2001 (50.9%). We also detected large differences in the distributions of cognitive status in the total sample compared with participants with ADL disability. The percentage of participants in the total sample with probable dementia decreased from 3.7% in 2001 to 2.4% in 2018 compared to 18.8% to 8.2% for participants with ADL disability. These differences in ADL limitations and probable dementia among participants with ADL disability remained statistically significant after adjusting for age, sex, education, community size, and the number of health conditions (Supplementary Table 2).
Cohort differences in ADL disability
Supplementary Table 3 shows the cohort differences in the percentage of participants with ADL disability and limitations in each ADL task. The percentage of participants with ADL disability was 12.2% in 2001 and 16.4% in 2018. The percentage of participants with difficulty in each ADL task ranged from 9.2% (dressing) to 1.6% (eating). The 2018 cohort had 1.86 higher odds of having ADL disability (Figure 2). Additionally, the 2018 cohort had significantly higher odds of reporting difficulty dressing, getting in or out of bed, toileting, and walking.
Figure 2.
Adjusted odds ratios for differences in limitations of activities of daily living between Mexican Health and Aging Study participants aged 60–76 in 2001 and aged 60–76 in 2018. Odds ratios are adjusted for age, sex, education, community size, health insurance, social programs, total number of health conditions, pain, having fallen in the last 2 years, and cognitive status. ADL = xxx.
Cohort differences in receiving help with ADL tasks
Approximately, 31% of all participants with ADL disability reported receiving help with ≥1 ADL (Supplementary Table 4). Participants with difficulty eating had the highest percentage of participants who reported receiving help (56.7%), and participants with difficulty dressing had the lowest percentage (29.2%). The 2018 cohort had 0.66 (95% CI = 0.49–0.89) lower odds of receiving help with ≥1 ADL (Figure 3). Receiving help with dressing was the only ADL item with a statistically significant cohort difference. Other participant characteristics associated with significantly higher odds of receiving help with ≥1 ADL task were having three or more chronic conditions, being classified as FICI, CIND, or probable dementia, and living with a partner only, with a partner and/or daughters aged 15+, and with a partner and/or sons or daughters younger than 15 (Supplementary Table 5).
Figure 3.
Adjusted odds ratios for differences in receiving help with activities of daily living between Mexican Health and Aging Study participants aged 60–76 in 2001 and aged 60–76 in 2018. Odds ratios are adjusted for age, sex, education, community size, health insurance, social programs, living arrangement, total number of health conditions, pain, having fallen in the last 2 years, and cognitive status. ADL = xxx.
Mediation analysis
The mediating variables explained 32.8% of the total effect of the birth cohort on receiving help with ≥1 ADL (Table 1). Years of education, four or more chronic conditions, dementia, and living with a partner and/or sons or daughters younger than 15 had a statistically significant mediating effect. Participants in the 2018 cohort completed more years of education and were more likely to live with a partner and/or sons or daughters younger than 15 than in 2001, and both characteristics were positively associated with receiving assistance in ≥1 ADL. Thus, years of education had a 12.3% suppression effect, and living with a partner and/or sons or daughters younger than 15 had a 7.16% suppression effect on the total effect of the birth cohort. Conversely, a lower percentage of probable dementia in the 2018 cohort explained 44.3% of the total effect for the birth cohort. The number of living children explained 9.34% of the total effect for the birth cohort but this finding was not statistically significant.
Table 1.
Mediating Effects of Demographic and Health Characteristics on Cohort Differences in Receiving Assistance with One or More Activities of Daily Living
| Variable | Coefficient (SE) | Odds ratio (95% CI) | % Reduceda | p Value |
|---|---|---|---|---|
| Total effect | −0.58 (0.12) | 0.56 (0.44–0.71) | ||
| Direct effect | −0.40 (0.13) | 0.67 (0.50–0.90) | ||
| Indirect effect | −0.19 (0.07) | — | ||
| Mediating variableb | ||||
| Years of education | 0.07 (0.03) | −12.3 | .03 | |
| Number of living children | −0.05 (0.03) | 9.34 | .08 | |
| Number of health conditions | ||||
| 0 | — | — | — | |
| 1 | −0.01 (0.01) | 2.03 | .68 | |
| 2 | −0.01 (0.02) | 1.09 | .62 | |
| 3 | −0.03 (0.02) | 4.79 | .32 | |
| 4 or more | 0.06 (0.03) | −9.48 | .04 | |
| Cognitive status | ||||
| No impairment | — | — | — | |
| FICI | 0.01 (0.01) | −2.46 | .16 | |
| CIND | −0.03 (0.04) | 4.99 | .48 | |
| Dementia | −0.25 (0.04) | 43.7 | <.01 | |
| Health insurance | −0.005 (0.06) | 0.93 | .93 | |
| Social program | 0.03 (0.03) | −4.50 | .41 | |
| Living arrangement | ||||
| Alone | — | — | — | |
| Partner only | 0.02 (0.02) | −4.23 | .19 | |
| Partner and/or daughter aged 15+ | −0.02 (0.02) | 4.23 | .19 | |
| Partner and/or children | 0.04 (0.02) | −7.16 | .04 | |
| Partner and/or extended family | −0.0003 (0.005) | 0.06 | .95 | |
| Other | −0.008 (0.007) | 1.34 | .26 | |
Notes: CI = confidence interval; CIND = cognitive impairment no dementia; FICI = functional impairment no cognitive impairment; SE = standard error. The mediating variables explained 32.8% of the total effect. This percentage was calculated by dividing the indirect effect coefficient by total effect coefficient (−0.19/ −0.58 = 0.328).
aCalculated by dividing the mediating variable coefficient by the total effect coefficient. Participants who live with children are those who live with son(s) only or sons and daughters younger than age 15.
bSum of the mediating variable coefficients is the indirect effect coefficient.
Discussion
Determining if older adults in Mexico are experiencing an increase in unmet caregiving needs or a decrease in the need for family care is critical to Mexico meeting the long-term care needs of a growing older adult population. Consistent with prior research (Andrade & López Ortega, 2021; Payne & Wong, 2019), we found that older adults in 2018 were more likely to have ADL disability and, among those with ADL disability, were less likely to report receiving assistance with ≥1 ADL tasks. However, our decomposition analysis produced evidence that the cohort difference in receiving assistance with ≥1 ADL among adults aged 60–76 with ADL disability is not an indication of more unmet needs. Fewer living children for the 2018 cohort explained 9.34% of the total birth cohort effect on receiving assistance with ≥1 ADL tasks. We expected the number of living children to have a greater mediating effect because of the large difference in the number of children, and the important role children have in providing informal care. One explanation is that the cohort differences in living arrangements and the decrease in number of a participants with ADL disability who live alone may offset the mediating effect of the number of living children.
The lower prevalence of probable dementia in the 2018 birth cohort explained 44% of the total birth cohort effect. Older adults with dementia are more likely to have severe ADL disability and need more intensive care than older adults without dementia (Ali et al., 2022). The prevalence and incidence of dementia may be decreasing in high-income countries (Langa et al., 2017; Prince et al., 2016), but data from Mexico indicates these rates are not changing (Mejia-Arango et al., 2021). However, few studies have focused on older adults with ADL disability or who may have caregiving needs. A study of nearly 400,000 older adults in Australia who received long-term care reported that the prevalence of dementia decreased from 50.0% in 2008 to 46.6% in 2014 and from 25.9% to 20.9% over a similar period for the approximately 190,000 older adults who received home care (Harrison et al., 2020).
A concern is how older adults in Mexico who live alone will have their caregiving needs met (Angel et al., 2017). Mexico has implemented several supplemental income programs that have benefited older adults, but these programs have not addressed the need for caregiver support. Older adult recipients do not appear to be using the additional income to pay for a caregiver and the programs have not reduced the number of hours a family member provides care (Aguila et al., 2019). These programs have been associated with increased household size, but this increase was driven by grandchildren and great-grandchildren moving in with grandparents and the percentage of older adults who lived alone was unchanged (Aguila et al., 2020). Given that Mexico has a long history of successfully implementing social support programs, one strategy could be to provide older adults who live alone with supplemental income that they can only use to pay a family member or nonfamily member to give caregiving assistance.
Comparing two independent birth cohorts allowed us to evaluate how the changing context of population aging in Mexico has contributed to trends in ADL disability and caregiving needs, but the narrow age range limits the generalizability of our findings. Middle-aged adults with ADL disability could be at an increased risk to having unmet needs because a spouse or adult child may not expect a middle-aged family member to need support with daily tasks. Conversely, widowhood is a major cause of living alone for adults aged 80 and older in Mexico, which could increase the need for extended family to provide informal care (Angel et al., 2023). Evidence from the MHAS also indicates the prevalence of probable dementia among adults aged 75 and older has slightly increased from 2001 to 2015 (Mejia-Arango et al., 2021). Continued research on population-level trends in receiving assistance with ADL tasks that include younger and older age groups is needed to determine if similar trends are occurring for other age groups in Mexico or if these trends are unique to this specific age group.
Continued research is also needed before making definitive statements on whether our findings represent an increase in unmet caregiving needs or a decrease in Mexican older adults’ need for informal care. Future research should consider population-level trends in other daily activities that are important to living independently, such as cooking, shopping, and managing medications. Such research would provide a more comprehensive view of older adults’ caregiving needs and allow for other conceptualizations of disability severity. For example, the interval of need concept originally proposed by Isaacs and Neville (1976) and later modified (Jagger et al., 2011; Willis et al., 2019) defines disability severity according to an older adult’s ability to complete combinations of IADL and ADL tasks. How often an older adult needs to complete a task can influence if they have sufficient assistance from another person (Willis et al., 2019). Older adults who have difficulty with shopping, cleaning their home, or managing finances would need less frequent caregiver assistance than an older adult who has difficulty bathing, dressing, and cooking or who have difficulty eating, transferring, or taking medications (Willis et al., 2019).
A limitation of our analysis is we had to exclude participants who required a proxy to complete their interview. Consequently, we excluded participants who likely have ADL disability. A second limitation is we did not investigate whether older parents were living with grandchildren. Many families live in multigenerational households, and grandchildren can be an important source of informal care. Thus, we may have underestimated the availability of family care. Finally, the MHAS survey does not ask participants about the level of difficulty they experience when performing the task or if they have a person available to assist with ADL tasks. These kinds of survey questions would provide additional insights into the severity of an older adult’s ADL limitations and clarify if not receiving assistance from another person represents unmet caregiving needs.
Conclusion
Our analysis showed that older adults in 2018 were more likely to have difficulty completing ≥1 ADL but were less likely to receive assistance with ≥1 ADL tasks than older adults in 2001. Although we did not find strong evidence to suggest that these trends represent an increase in unmet caregiving needs, the higher prevalence of ADL disability is cause for concern. The progressive nature of ADL disability means that more older adults will need help with daily tasks as the population continues to age (Kingston et al., 2018). Mexico lacks the institutional resources to provide this help or to support families providing this care (Gutiérrez-Robledo et al., 2012). The expected increases in the number of older adults in Mexico living with dementia, living alone, and shrinking family sizes have important implications for future generations of older adults and how they will meet their long-term care needs.
Supplementary Material
Contributor Information
Brian Downer, Department of Population Health and Health Disparities, School of Public and Population Health, University of Texas Medical Branch, Galveston, Texas, USA; Sealy Center on Aging, University of Texas Medical Branch, Galveston, Texas, USA.
Rafael Samper-Ternent, Department of Management, Policy & Community Health, School of Public Health, University of Texas Health Sciences Center at Houston, Houston, Texas, USA.
Philip Cantu, Department of Internal Medicine, John Sealy School of Medicine, University of Texas Medical Branch, Galveston, Texas, USA.
Matthew Miller, Sealy Center on Aging, University of Texas Medical Branch, Galveston, Texas, USA.
Rebeca Wong, Department of Population Health and Health Disparities, School of Public and Population Health, University of Texas Medical Branch, Galveston, Texas, USA; Sealy Center on Aging, University of Texas Medical Branch, Galveston, Texas, USA.
Marc A Garcia, (Social Sciences Section).
Funding
This research was supported in part by the National Institutes of Health (RF1AG068988, R01AG018016, P30AG059301, and P30AG024832). The manuscript’s contents are solely the responsibility of the authors and do not represent the views of the NIH.
Conflict of Interest
None.
Data Availability
All data sets used in this analysis are publicly available at www.mhasweb.org. Data pre-processing and analysis scripts are available upon request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data sets used in this analysis are publicly available at www.mhasweb.org. Data pre-processing and analysis scripts are available upon request.



