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. Author manuscript; available in PMC: 2024 Jun 1.
Published in final edited form as: J Appl Gerontol. 2024 Feb 27;43(6):755–764. doi: 10.1177/07334648241231374

Vision Impairment and Frailty among Mexican American Older Adults: A Longitudinal Study

Mandi L Sonnenfeld 1, Monique R Pappadis 2,6, Timothy A Reistetter 3, Mukaila A Raji 4, Kenneth Ottenbacher 5, Soham Al Snih 2,4,5,6
PMCID: PMC11052670  NIHMSID: NIHMS1961852  PMID: 38412864

Abstract

We examined the relationship between vision impairment (VI) and new-onset frailty among non-frail Mexican American older adults (≥ 70 years) at baseline and determined the differential impact of VI on each frailty criteria. Data were from an 18-year prospective cohort from the Hispanic Established Population for the Epidemiologic Study of the Elderly (1998/1999, N=1072 to 2016, N=175). Frailty was defined as ≥3 criteria: unintentional weight loss of >10 pounds, weakness, exhaustion, low physical activity, and slowness. VI was defined as difficulty in recognizing a friend at arm’s length’s away, across the room, or across the street. We found that participants with VI (near or distant) and distant VI had greater odds of frailty (near or distant VI, OR=1.89, 95% CI=1.30–2.73 and distant VI, OR=1.95, 95% CI=1.34–2.86, respectively) after controlling for covariates over time. Early screening (optimal management) of VI may prevent or delay onset of frailty among older Mexican Americans.

Keywords: vision, frailty, longitudinal methods, older adults, Mexican Americans

INTRODUCTION

Vision impairment (VI)—a potentially preventable disability—affects two billion persons worldwide (World Health Organization, 2023). The International Classification of Diseases (ICD-11) (2018) classified vision impairment into two groups, distance and near presenting vision impairment (World Health Organization, 2018). The ICD-11 classifies distance vision impairment (DVI) as mild (visual acuity worse than 6/12 to 6/18), moderate (visual acuity worse than 6/18 to 6/60), severe (visual acuity worse than 6/60 to 3/60), and blindness (visual acuity worse than 3/60); and near vision impairment (NVI) as near visual acuity worse than N6 or M.08 at 40 cm (World Health Organization, 2018).

VI becomes increasingly common with older age for healthy individuals due to the normal aging process such as slower tear production (Association for the Advancement of Retired Persons, 2019), decreased number of mucous cells in the conjunctiva (Merck Manual, 2022), and reduced flexibility of eye lenses (University of California Irvine Health, 2018). Furthermore, VI is more common among individuals with additional medical conditions such as diabetes, arthritis, and stroke (Court et al., 2014; Garin et al., 2014; Rogers et al., 2017; Shukla & Tripathy, 2023). Findings from the Health, Aging and Body Composition study showed that VI was associated with higher incidence of walking and stair climbing limitations over 5 years of follow-up (Swenor et al., 2015). Similarly, VI has been associated with the development of cognitive impairment over 4 years of follow-up (Ehrlich et al., 2021).

Frailty has been defined as an increased vulnerability to adverse health outcomes following stressors and is reported by Clegg et al. 2013 to be the “most problematic expression of population ageing” (Clegg et al., 2013; L. P. Fried et al., 2004). For a person to be considered frail, three or more of the following five indicators must be present: weight loss, exhaustion, weakness, slowness, and low physical activity (Linda P. Fried et al., 2004). The prevalence of frailty increases with age ranging from 9% among the youngest old to over 35% in the oldest old (Bandeen-Roche et al., 2015). Numerous factors are associated with frailty, such as older age, female sex, cognitive impairment, decreased physical activity, and smoking (Bandeen-Roche et al., 2015; Cano et al., 2011; Fabrício-Wehbe et al., 2016; Rogers et al., 2017; Trevisan et al., 2017).

Previous research examining VI and frailty among older adults demonstrated that low vision predicted frailty over time (Gonzales-Turín et al., 2021; Liljas et al., 2017; Swenor, Lee, Tian, et al., 2020). Findings from the Women’s Health and Aging Studies (WHAS), reported that non-frail participants with moderate/severe VI were 3.5 times more likely to develop frailty than those without VI over 3 years of follow-up (Swenor, Lee, Tian, et al., 2020). In the English Longitudinal Study of Ageing (ELSA), participants with poor vision had increased odds of prefrailty and frailty (2.07 and 3.24, respectively) over 4 years of follow-up (Liljas et al., 2017).

In the United States (US) alone, Varma et al. (2016) reported four million Americans had a VI and indicated that this number will double to 8 million by the year 2050 (Lopez, 2015; Varma et al., 2016), especially among Mexican American older adults, one of the fastest growing segments of older Americans (Lopez, 2015; National Eye Institute, 2022). The American Academy of Ophthalmology determined that Hispanic men — predominantly Mexican Americans — will be the largest population of Americans with low vision over the next few decades (American Academy of Ophthalmology, 2014). For example, Mexican American older adults have a high prevalence of Type 2 diabetes, one of the most common risk factors for developing VI (Wang et al., 2021). It is thus important to study and understand the impact of untreated VI/low vision on physical activity engagement, energy level, muscle strength, maintenance of healthy weight and ability to walk and move safely, all of which are criteria of frailty. Low access to quality of health care and communication barriers from language and cultural differences have been reported among Mexican American communities (Pew Research Center, 2022). Accordingly, it is essential to study VI, a potentially preventable health factor, among the Mexican American population. Findings from such study can guide the development of culturally appropriate interventions to improve physical activity engagement and mitigate onset of various criteria of frailty in Mexican American older adults.

There is paucity of research examining the long-term relationship between VI and new-onset frailty in older Mexican Americans, a population with high rates of frailty and high prevalence of vision-impairing diseases (Ottenbacher et al., 2005). Knowing the differential impact of VI on different frailty criteria can inform the design of tailored and patient-specific interventions to address VI-related frailty and help seniors age in place (Szanton et al., 2015). The purpose of this study was two-fold: 1) to determine the relationship between VI and frailty among non-frail Mexican American older adults at baseline and whether NVI or DVI (when analyzed separately) drove the relationship between VI and frailty over 18 years of follow-up after controlling for covariates; and 2) to determine the differential impact of VI on each frailty criteria after controlling for covariates. It is hypothesized that non-frail older Mexican Americans with VI will have increased odds of frailty onset over 18 years of follow-up and that VI will have a differential impact on at least three frailty criteria after controlling for covariates.

METHODS

Data Source

Data were from the Hispanic Established Populations for the Epidemiologic Study of the Elderly (H-EPESE). The H-EPESE survey collected data from Mexican Americans aged 65 years and older located in the states of Arizona, California, Colorado, New Mexico, and Texas. At baseline (1993/94), 3,050 participants were interviewed, and follow-up interviews were conducted every two or three years. Of these participants, 2435 were interviewed in Wave 2, 219 were confirmed dead through the National Death Index and reported from relatives, and 109 were lost to follow-up or refused to be reinterviewed. The present study used data obtained on 1,979 participants interviewed at Wave 3 (1998/99, hereafter baseline). The first and second wave (1993/94 and 1995/96) were not included because the variable of self-reported VI was not collected. We used data collected from Wave 3 to Wave 9 (2016). The H-EPESE datasets are available at the National Archive of Computerized Data on Aging (Markides et al., 2016).

Of the 1,979 participants interviewed at baseline, we excluded 146 who were frail at baseline and 761 because of missing variable information on VI, frailty phenotype, or covariates, leaving a final sample size of 1,072. Participants excluded from the study were more likely to be older; to be unmarried; to have financial strain; to report comorbidities (cancer, heart attack, hip fracture, and stroke), high depressive symptoms, hearing impairment, NVI, DVI, and VI (near or distant); and to have a lower Mini-Mental State Examination (MMSE) score (Folstein et al., 1975) than included participants. At the end of follow up (2016), 175 participants were re-interviewed in person, 80 were lost to follow up or refused to be re-interviewed, and 149 were reported as deceased from the National Death Index and the decedent’s relatives. Figure S1 presents the sample flow chart. At the time of interview, oral informed consent was provided for each participant and the study protocol was approved by the University’s Institutional Review Board (IRB# 16–004).

Measures

Independent Variable – Vision Impairment

Vision impairment was defined in three different ways: DVI, NVI, or any VI. DVI was assessed with the following question: “When wearing your glasses/contacts can you see well enough to recognize a friend across the street or across the room?” NVI was assessed with the following question: “When wearing your glasses/contacts, can you see well enough to recognize a friend who is at arm’s length away?” If NVI and/or DVI was indicated, then the participant was classified as having a VI. These questions are similar to questions utilized in the Behavioral Risk Factor Surveillance System data set for VI assessment (Centers for Disease Control and Prevention, 2021; Chou et al., 2012; McGwin et al., 2010).

Dependent Variable – Modified Frailty Phenotype

Frailty status was determined by using a modified version of the frailty phenotype defined by Fried et al. (2001) (Fried et al., 2001). The modified frailty phenotype measure used in this study was previously validated in this sample population (Li et al., 2019). The criteria were weight loss, weakness, slowness, low physical activity, and exhaustion (Fried et al., 2001; Li et al., 2019). Weight loss: >10 pounds, calculated as the difference between weight measured in 1995/96 and in 1998/99. Weakness: handgrip strength test in the bottom 20% (adjusted for sex and Body Mass Index [BMI]) or those unable to perform the test. Slowness: a timed 8-foot walk in the bottom 20% (height-sex adjusted) or unable to perform the test. Low physical activity: answered “No” to the question “Can you walk half a mile without help from anyone else?” (sex-adjusted). Exhaustion: positive responses to the following questions: “Everything I did was an effort” or “I could not get going” from the Center for Epidemiologic Studies Depression (CES-D) Scale (Radloff, 1977). Participants were classified as non-frail if they met none of the criteria, pre-frail if they met 1–2 of the criteria, and frail if they met 3 or more of the criteria. Frailty was assessed at each interview during the 18-year study period.

Covariates

Specific covariates were included in the analysis as they have been reported to be associated with VI and frailty (Afunugo et al., 2023; Court et al., 2014; Ehrlich et al., 2021; Garin et al., 2014; Ong et al., 2018; Rutherford et al., 2022; Shukla & Tripathy, 2023; Swenor et al., 2015; Ventura et al., 2023; Vetrano et al., 2018; Welch et al., 2021; Zheng et al., 2018). Covariates included socio-demographic variables (age, sex, marital status, years of education, financial strain, nativity status, language of interview, social isolation [lives with family vs. alone]), BMI, current smoking status, comorbidities (hypertension, arthritis, cancer, diabetes, heart attack, hip fracture, and stroke), hearing impairment, depressive symptoms using the CES-D (Radloff, 1977), and cognitive function assessed with the MMSE (Folstein et al., 1975).

Statistical Analysis

T-test and Chi-square tests were used to examine the distribution of the variables by VI at baseline. Mean, standard deviation (SD), and ranges were reported for continuous variables (age and years of education). Frequency and percents were reported for variables that were categorized (socio-demographics, smoking, BMI, comorbidities, cognitive impairment, depressive symptoms, and hearing impairment). T-test was performed for continuous variables with normal distribution and the p-value chosen was based on the homogeneity of variance assumption. Chi-square tests and Fisher’s Exact test were conducted to test the differences of the categorical variables.

The odds ratio (OR) and 95% Confidence Interval (CI) of frailty as a function of VI were estimated using Generalized Estimating Equation (GEE) models with logit link for a binomial distribution and the autoregressive covariance structure to account for repeated measures of participants. The covariance matrixes for GEE models were chosen based on the Akaike information criterion and Bayesian information criterion values (Zeger & Liang, 1986). Using GEE models, we minimize the selection bias from missing information, since this procedure allows for the use of all available data from all follow-up interviews while accounting for differences in the follow-up duration; we therefore lose only the observations for which the participant is missing, and not all the measurements. To estimate the working correlation parameters, all non-missing pairs of data were used from the same participants over time. All models were controlled for sociodemographic and health factors over time. All variables were analyzed as time varying (potential to change over time) except for sex, education, and nativity. Age and years of education were analyzed as continuous variables in the GEE analysis and all other covariates were analyzed as categorical. Participants who died, refused to participate, or were lost to follow up were included until their last follow-up date (last interview date over the 18-year follow-up period). Analyses were performed using SAS, version 9.0 (SAS Institute, Inc., Cary, NC). A p-value of < 0.05 was considered statistically significant.

RESULTS

Table 1 presents baseline descriptive characteristics of the sample among non-frail participants at baseline. The mean age of the overall sample was 76.68 (SD ± 5.11) years, and the mean years of education was 5.15 (SD ± 3.95). The overall sample was primarily female (57.74%), married (54.66%), US born (58.02%), had financial strain (52.15%), and were not currently smoking (89.27%). The most common comorbidities were arthritis (47.67%), hypertension (46.08%), and diabetes (26.68%). Approximately forty percent were overweight, followed by obesity category 1 (24.44%), normal weight (24.25%), obesity category 2 (10.07%), and underweight (1.31%). About twenty nine percent had a MMSE score < 21, 19.50% indicated having a hearing impairment, and 9.98% had high depressive symptoms.

Table 1.

Baseline descriptive characteristics of the overall sample and by vision impairment (near or distant) among Mexican American older adults (n=1072).

Characteristic Total n (%) Vision Impairment No Vision Impairment p-value
Total 1072 (100) 134 (12.50) 938 (87.50)
Age (years), Mean ± SD, range 76.68 ± 5.11, (70–103) 78.51 ± 5.76, (70–103) 76.41 ± 4.96, (70–93) <0.01
Sex 0.50
 Female 619 (57.74) 81 (60.45) 538 (57.36)
 Male 453 (42.26) 53 (39.55) 400 (42.64)
Marital Status 0.55
 Married 586 (54.66) 70 (52.24) 516 (55.75)
 Not married 486 (45.34) 51 (38.06) 462 (49.25)
Education (years), Mean ± SD, range 5.15 ± 3.95, (0–20) 4.99 ± 3.61, (0–17) 5.17 ± 4.00, (0–20) 0.60
Financial Strain 0.02
 Yes 559 (52.15) 83 (61.94) 476 (50.75)
 No 513 (47.85) 51 (38.06) 462 (49.25)
Nativity Status 0.48
 US born 622 (58.02) 74 (55.22) 548 (58.42)
 Foreign born 450 (41.98) 60 (44.78) 390 (41.58)
Language of Interview 0.05
 Spanish 770 (71.83) 106 (79.10) 664 (70.79)
 English 302 (28.17) 28 (20.90) 274 (29.21)
Lives with family 0.63
 Yes 810 (75.56) 99 (73.88) 711 (75.80)
 No 262 (24.44) 35 (26.12) 227 (24.20)
Hypertension 0.18
 Yes 494 (46.08) 69 (51.49) 425 (45.31)
 No 578 (53.92) 65 (48.51) 513 (54.69)
Arthritis 0.34
 Yes 511 (47.67) 69 (51.49) 442 (47.12)
 No 561 (52.33) 65 (48.51) 496 (52.88)
Cancer 0.02
 Yes 53 (4.94) 12 (8.96) 41 (4.37)
 No 1019 (95.06) 122 (91.04) 897 (95.63)
Diabetes 0.37
 Yes 286 (26.68) 40 (29.85) 246 (26.23)
 No 786 (73.32) 94 (70.15) 692 (73.77)
Heart Attack 0.02
 Yes 41 (3.82) 10 (7.46) 31 (3.30)
 No 1031 (96.18) 124 (92.54) 907 (96.70)
Hip fracture 0.22
 Yes 9 (0.84) 2 (1.49) 7 (0.75)
 No 1063 (99.16) 132 (98.51) 931 (99.25)
Stroke 0.02
 Yes 26 (2.43) 7 (5.22) 19 (2.03)
 No 1046 (97.57) 127 (94.78) 919 (97.97)
BMI Categories
 Underweight 14 (1.31) 1 (0.75) 13 (1.39) 0.31
 Normal 260 (24.25) 34 (25.37) 226 (24.09) 0.75
 Overweight 428 (39.93) 56 (41.79) 372 (39.66) 0.64
 Obese Category 1 262 (24.44) 30 (22.39) 232 (24.73) 0.55
 Obese Category 2 108 (10.07) 13 (9.70) 95 (10.13) 0.88
Cognitive Impairment <0.01
 Yes (MMSE < 21) 308 (28.73) 64 (47.76) 244 (26.01)
 No (MMSE ≥ 21) 764 (71.27) 70 (52.24) 694 (73.99)
Depressive symptoms <0.01
 Yes (CES-D ≥ 16) 107 (9.98) 24 (17.91) 83 (8.85)
 No (CES-D < 16) 965 (90.02) 110 (82.09) 855 (91.15)
Current Smoking 0.28
 Yes 115 (10.73) 18 (13.43) 97 (10.34)
 No 957 (89.27) 116 (86.57) 841 (89.66)
Hearing Impairment 0.01
 Yes 209 (19.50) 37 (27.61) 172 (18.34)
 No 863 (80.50) 97 (72.39) 766 (81.66)
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Abbreviations: SD=standard deviation; US=United States; BMI=body mass index; MMSE=Mini Mental State Exam; CES-D=Center for Epidemiologic Studies Depression Scale; kg=kilograms; m=meters

Note: p-values for continuous variables were obtained using t-test and p-values for nominal or categorical variables were obtained using Chi-square tests or Fisher’s Exact Test.

Thirteen percent of Mexican American older adults reported VI. Participants with VI compared to those without VI were significantly more likely to be older (78.51 SD ± 5.76 vs. 76.41 SD ± 4.96; p-value <0.01), indicate financial strain (61.94% vs. 50.75%; p-value 0.02), and have the interview conducted in Spanish (79.10% vs 70.79%; p-value 0.05). Additionally, participants with VI compared to those without VI were significantly more likely to report co-morbid conditions such as cancer (8.96% vs. 4.37%; p-value 0.02), heart attack (7.46% vs. 3.30%; p-value 0.02), and stroke (5.22% vs. 2.03%; p-value 0.02). Lastly, participants with VI compared to those without VI were significantly more likely to have scored < 21 on the MMSE (47.76% vs. 26.01%; p-value <0.01), have high depressive symptoms (17.91% vs. 8.85%; p-value <0.01), and have hearing impairment (27.61% vs. 18.34%; p-value 0.01). No significant differences were found by sex, marital status, years of education, nativity status, living status (with family vs. alone), BMI, and smoking status.

Table 2 presents GEE models for frailty as a function of NVI (Model 1), DVI (Model 2), and VI (Model 3) over time. No significant association was found between NVI and frailty after controlling for all covariates. Participants with DVI had greater odds of developing frailty (OR=1.95, 95% CI 1.34–2.86) over time, controlling for all covariates. Participants with VI (near or distant) had greater odds of developing frailty (OR=1.89, 95% CI 1.30–2.73) over time, controlling for all covariates. Time (years), age, financial strain, arthritis, cancer, lower MMSE score, and depressive symptoms were also factors associated with greater odds of frailty. Lower odds of frailty were found for participants in all VI models who were overweight (NVI: OR=0.65, 95% CI 0.48–0.90, DVI: OR=0.65, 95% CI 0.47–0.90, VI: OR=0.65, 95% CI 0.47–0.90) and those who reported hypertension (NVI: OR=0.69, 95% CI 0.52–0.92, DVI: OR=0.70, 95% CI 0.53–0.93, VI: OR=0.70, 95% CI 0.53–0.94).

Table 2.

Generalized Estimating Equation models for frailty as a function of vision impairment over 18-years of follow up among non-frail Mexican American older adults at baseline (N=1072).

Model 1 Model 2 Model 3
Predictors OR (95% CI) OR (95% CI) OR (95% CI)
Time 1.22 (1.18–1.26) 1.22 (1.18–1.26) 1.22 (1.18–1.26)
Near VI 1.67 (0.87–3.21)
Distant VI 1.95 (1.34–2.86)
VI 1.89 (1.30–2.73)
Age (years) 1.07 (1.04–1.10) 1.07 (1.03–1.10) 1.07 (1.04–1.10)
Female 1.06 (0.75–1.48) 1.05 (0.75–1.47) 1.05 (0.75–1.47)
Married 0.93 (0.66–1.32) 0.94 (0.66–1.34) 0.93 (0.66–1.32)
Education (years) 1.00 (0.96–1.04) 1.00 (0.96–1.04) 1.00 (0.96–1.04)
Financial Strain 1.52 (1.14–2.03) 1.49 (1.11–1.99) 1.49 (1.12–2.00)
Nativity (Foreign born) 0.98 (0.72–1.34) 0.99 (0.73–1.36) 0.99 (0.72–1.34)
Spanish Interview 0.94 (0.64–1.38) 0.94 (0.64–1.39) 0.94 (0.64–1.39)
Lives with Family 1.23 (0.87–1.75) 1.22 (0.86–1.72) 1.23 (0.87–1.73)
Current Smoking 1.40 (0.81–2.40) 1.33 (0.77–2.31) 1.34 (0.78–2.33)
BMI Categories
Underweight 2.15 (0.96–4.84) 2.10 (0.92–4.85) 2.13 (0.92–4.89)
Normal Reference Reference Reference
Overweight 0.65 (0.48–0.90) 0.65 (0.47–0.90) 0.65 (0.47–0.90)
Obesity Category 1 0.86 (0.57–1.31) 0.86 (0.56–1.30) 0.86 (0.57–1.30)
Obesity Category 2 1.27 (0.75–2.16) 1.28 (0.76–2.18) 1.28 (0.76–2.17)
Hypertension 0.69 (0.52–0.92) 0.70 (0.53–0.93) 0.70 (0.53–0.94)
Arthritis 1.42 (1.06–1.90) 1.40 (1.05–1.88) 1.41 (1.05–1.88)
Cancer 1.88 (1.16–3.05) 1.81 (1.12–2.94) 1.83 (1.13–2.97)
Diabetes 1.10 (0.80–1.52) 1.12 (0.81–1.54) 1.12 (0.81–1.54)
Heart Attack 1.08 (0.61–1.94) 1.01 (0.56–1.81) 1.02 (0.57–1.83)
Hip Fracture 2.08 (0.82–5.25) 1.93 (0.76–4.89) 1.95 (0.77–4.93)
Stroke 1.35 (0.72–2.55) 1.36 (0.73–2.53) 1.36 (0.73–2.53)
Cognitive Impairment (MMSE < 21) 1.51 (1.11–2.06) 1.42 (1.03–1.95) 1.42 (1.03–1.95)
Depressive symptoms (CES-D ≥ 16) 4.69 (3.45–6.38) 4.48 (3.29–6.11) 4.51 (3.31–6.15)
Hearing impairment 0.97 (0.69–1.36) 0.96 (0.69–1.35) 0.95 (0.68–1.32)
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Abbreviations: VI=vision impairment; OR=odds ratio; CI=confidence interval; BMI=body mass index; MMSE=Mini Mental State Exam; CES-D=Center for Epidemiologic Studies Depression Scale

Table S1 presents GEE models for each frailty criterion as a function of NVI, DVI, and VI (near or distant) over 18 years of follow up among non-frail Mexican American older adults at baseline. Participants with NVI, DVI, or VI had greater odds of low physical activity (OR=1.94, 95% CI 1.23–3.06; OR=2.02, 95% CI 1.57–2.61; and OR=2.03, 95% CI 1.60–2.59, respectively) over time, controlling for all covariates. Those with VI had greater odds of weakness (OR=1.29, 95% CI 1.01–1.65) and those with DVI and VI had greater odds of exhaustion (OR=1.46, 95% CI 1.07–1.99 and OR=1.48, 95% CI 1.10–2.00, respectively) over time, controlling for all covariates.

DISCUSSION

The purpose of this study was to examine the longitudinal relationship between VI and frailty over 18 years of follow up among non-frail Mexican American older adults at baseline and whether NVI or DVI (when analyzed separately) drove the relationship between VI and frailty. We found DVI and VI (NVI or DVI) were associated with frailty over time. In our study, NVI was not associated with frailty. When we examined the relationship between VI and each frailty criteria, we found VI associated with low physical activity, weakness, and exhaustion.

Some mechanisms may explain the relationship between VI and frailty. For example, VI increases the risk for low physical activity and low participation in activities of daily living, which can subsequently lead to weakness and exhaustion (Lam et al., 2013; Ong et al., 2018; Swenor et al., 2015; Welch et al., 2021). VI can also increase social isolation, which increases the risk of sedentary lifestyle and depression, which can in turn also precipitate weakness and exhaustion (Coyle et al., 2017; Tetteh et al., 2020). The negative effect of VI — on physical and cognitive function as well as on social (loneliness, decreased social engagement) and psychological (depression, anxiety) factors — leads to frailty, disability, comorbidity, and mortality (Swenor, Lee, Varadaraj, et al., 2020). VI also increases the risk of hospitalization, which is itself a risk factor for frailty (Morse et al., 2019) (Chang et al., 2018). Interventions to increase access to timely eye care among Mexican American older adults can have myriad downstream health benefits, given the well-described cardiovascular, metabolic, neurological, and psychiatric consequences of physical inactivity. In addition, Mexican Americans have known barriers to health care access related to culture and communication (Pew Research Center, 2022). Eye care diagnosis and treatment interventions from health care professionals should be adapted to decrease barriers, such as the use of a medical interpreter being standard across health care delivery systems (Hamm et al., 2021). Furthermore, individuals with language barriers are less likely to use preventative services, which may cause a delay in diagnoses of comorbidities that lead to VI (Hall et al., 2022). Additional supports for navigating the health care system may be needed to obtain appropriate vision care, such as which vision provider is most appropriate to visit (ophthalmologist vs. optometrist), identification of options for vision funding sources (insurance, underinsured, and no insurance), or assistance determining if reading glasses obtained from a local drug store are sufficient to correct current vision difficulties.

The findings of this study are similar to those found in the longitudinal study of the WHAS, the ELSA, the National Health and Aging Trends Study, and the Toledo Study for Healthy Aging, all of which found that older adults with VI had greater odds of developing frailty (Gonzales-Turín et al., 2021; Hou et al., 2022; Liljas et al., 2017; Swenor, Lee, Tian, et al., 2020). Participants who were overweight had lower odds of frailty, although prior research has shown overweight to be associated with frailty (Rutherford et al., 2022; Strandberg et al., 2012; Yuan et al., 2021). In addition, hypertension was associated with greater odds of frailty in previous studies (Vetrano et al., 2018); however, in this study, participants who reported hypertension had lower odds of frailty.

This study is unique because it is the first known study to analyze types of VI (near or distant) separately to determine if there were differences between vision impairment type and frailty criteria over time. All types of VI (near, distant, any) had the highest association with low physical activity frailty criteria when compared to other frailty criteria. Thus, addressing VI in older Mexican Americans may increase physical activity among this population.

The present study has some limitations. First, VI was a self-reported measure and was not objectively measured using vision assessments, such as the commonly used Snellen visual acuity chart. However, self-reported VI has previously demonstrated a significant association with objectively measured VI (Zimdars et al., 2012). Second, the exclusion of participants at baseline may have underestimated the relationship between VI and frailty. Third, generalizability of the study is limited to Mexican American older adults living in the geographic region of the Southwestern US (Arizona, California, Colorado, New Mexico, and Texas). Fourth, due to longitudinal follow up over 18 years of time, attrition from loss to follow up or death occurred. However, the most appropriate statistical method of GEE modeling was used to account for this attrition limitation. There are many strengths of this study. First, our study is unique in that it included a long follow up over 18 years, using as time varying all available data on VI, socio-demographics, comorbidities, BMI, and frailty. Second, this study captured results for both self-reported NVI and DVI separately, making this study unique when compared to other longitudinal surveys which uses one definition for both NVI and DVI.

This study has several implications. Focusing on VI prevention and correction may help decrease disability related to specific frailty criteria among Mexican American older adults. VI is an important issue to address because it relates to a major cause of disability among older adults. Our findings suggest early screening (and optimal management) of VI represents an important step in preventing or delaying the onset of frailty in Mexican American older adults, a population projected to comprise the largest population of Americans with low vision in the next few decades.

Statement of research material access: The datasets generated during and/or analyzed during the current study are available at https://www.icpsr.umich.edu/icpsrweb/NACDA/series/546.

Supplementary Material

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What the paper adds

  • Vision impairment (VI) was associated with frailty among Mexican American older adults.

  • When VI was analyzed separately for distant and near VI, greater odds of frailty were found for participants with distant VI, while no significant association was found between near VI and new-onset frailty.

  • Low physical activity, exhaustion, and weakness frailty criteria were the most affected among Mexican American older adults with VI.

Applications of study findings

  • Minority populations are underserved and have low access to care; addressing VI among older Mexican Americans can prevent or delay the onset of frailty.

  • Vision health screening should be included as a core concept when addressing frailty among older adults.

  • Treating VI can reduce the impact on specific frailty criteria.

Acknowledgements:

I, Dr. Sonnenfeld, the corresponding author, affirm that I have listed everyone who contributed significantly to this work and have obtained written consent from all contributors who are not authors and are named in the Acknowledgement section. The authors acknowledge the assistance of Sarah Toombs Smith, PhD, ES, in article preparation.

Funders:

This work was supported in part by the National Institute on Aging (R01 AG10939), the National Institute on Minority Health and Health Disparities (R01 MD010355). Dr. Sonnenfeld is supported by the Health Professions Education Evaluation and Research (HPEER) fellowship, through the VA Office of Academic Affiliations Advanced Fellowships Program (3HPECCD2020) and the U.S. Department of Veterans Affairs Health Services Research & Development Service (VA HSR&D Grant # CIN 13-413). The content is solely the responsibility of the authors and does not necessarily represent the official views of the HPEER program or the Department of Veterans Affairs.

Footnotes

Declaration of Conflicting Interests’: The authors declare that there is no conflict of interest.

IRB protocol/human subjects approval numbers: The study and all research protocols were approved by the Institutional Review Board of the University of Texas Medical Branch (IRB#: 16-0014).

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