Abstract
Objectives
Food insecurity has gained attention as a potential risk factor for vision impairment. However, research on this topic is limited. This objective of this study was to investigate the relationship between food insecurity and visual impairment among adults aged 50 years or older using data from six low-and middle-income countries (LMIC).
Design and Setting
Data from the longitudinal Study on global AGEing and adult health (SAGE) were analyzed in a community-based, cross-sectional, and nationally representative sample.
Participants
Adults aged 50 years or older from six low- and middle-income countries (LMICs) including China, India, Mexico, Russia, South Africa, and Ghana.
Measurements
Food insecurity was evaluated using a questionnaire comprised of two questions that addressed the frequency of eating inadequately and hunger due to a lack of food in last 12 months. Distance and/or near vision impairment was considered as a visual acuity score of less than 6/18 in the eye with better vision.
Results
The analytical sample consisted of 29,804 adults (mean (SD) for age: 63.2 (9.54) years; 54.3% female). The prevalence of food insecurity, near vision and distance vision impairment in the sample was 16.4%, 36.7%, and 13.9%, respectively. Adjusted pooled analyses across countries revealed a significant association between food insecurity and distance (OR: 1.16; 95% CI: 1.01, 1.33; P=0.04, significant individually in India and South Africa) and near (OR: 1.12; 95% CI: 1.02, 1.22; P=0.01, significant individually in South Africa) vision impairment, and a between-country heterogeneity of 46.30% and 25.99%, respectively.
Conclusion
Food insecurity was associated with both distance and near vision impairment in adults aged 50 years or older across six LMIC. Food policies and intervention programs targeted at decreasing food insecurity in vulnerable households are essential.
Key words: Food insecurity, near vision impairment, distance vision impairment, LMICs
Introduction
Visual impairment is associated with disability, poor quality of life, unfavorable health outcomes and social dependence, particularly in older adulthood (1). According to recent data from the World Health Organization (WHO), at least 2.2 billion people are affected by near or distance visual impairment globally and nearly half of the impairments could have been prevented (2). The majority of cases experiencing the largest burden of vision impairment and blindness are in older adults (aged ≥ 50 years) and people from low- and middle-income countries (2). It is estimated that population growth and aging will continue to increase the number of age-related eye conditions (3). The high prevalence of visual impairment in older adults is of concern because it is associated with several adverse health outcomes including depression, difficulty managing meals and taking medications, dependency on family for life activities, social isolation, falls and fractures, and higher health care costs (1, 4). There is an urgent need to identify the risk factors and causes of visual impairment to adopt strategies for primary prevention and implement well-designed interventions to reduce the occurrence.
Several risk factors have been identified in the development of eye-related diseases and vision loss including ethnicity, age, gender, lower education, lower income, poor access to healthcare and having a chronic health condition, such as diabetes or high blood pressure (5). In addition, unhealthy behaviors, such as poor dietary quality, have been identified as modifiable risk factors of vision impairment (1). Several observational studies have reported an association between low dietary intake of antioxidants and omega-3 fatty acids and a higher risk of eye-related diseases (1, 6, 7). Dietary quality and specific dietary components have been associated with the leading causes of visual impairment including diabetic retinopathy, cataract, age-related macular degeneration and glaucoma (2, 8).
Poor dietary quality is more frequently observed among lower socioeconomic status populations, often due to the higher costs of healthier foods and reduced access to nutritious foods (9, 10). Lower socioeconomic status populations, especially in low- and middle-income countries (LMIC), are more likely to experience food insecurity (9). Food insecurity is a condition in which the availability and dietary intake of nutritious foods is disrupted due to insufficient resources and financial concerns (9, 10). It often disrupts the quality of dietary patterns and reduces the variety and desirability of nutritious foods, which may eventually compromise the intake of micronutrients and lead to poor nutrition (9, 10). Poor nutrition caused by food insecurity is distinct from other types because it may be accompanied by compensatory measures such as, binge eating during periods of food sufficiency, hunger during times of insufficiency and lower diversity and nutritional quality of food choices. Therefore, food insecurity acts as a unique and cyclic factor independent of other socioeconomic determinants (10, 11).
A growing body of evidence has found an association between food insecurity and well-known risk factors for eye diseases, diabetes and hypertension, especially among older adults who are at a higher risk of developing them (5, 11). However, to the best of our knowledge, very few studies have investigated the direct relationship between food insecurity and visual impairment and no studies have evaluated the associations in LMIC. One study evaluated this relationship in the US population (10). While another study evaluated the relationship between food security and visual impairment as a secondary outcome using only one question to evaluate food insecurity (3). Therefore, the present study aimed to use criteria that has been frequently used in previous studies and appears to be a more comprehensive method as two questions can capture more aspects of food insecurity (9, 12, 13). Previous research has also presented results separately for different countries (3). Instead, the present study performed pooled analyses to combine the results from different countries.
The objective of the present study was to investigate the relationship between food insecurity and visual impairment in a large nationally representative sample of adults aged 50 years or older from six LMIC. This research will provide evidence on if food insecurity is a potential risk factor for vision impairment which may inform efforts towards the prevention of visual impairment and inform interventions to help reduce the occurrence.
Methods
Study design
The present study was a secondary analysis using existing data from the Study on global AGEing and adult health (SAGE) developed by the WHO (wave 1 of data collection: 2007–2010), which is available at the following link: https://www.who.int/data/data-collection-tools/study-on-global-ageing-and-adult-health/sage-waves. The SAGE protocols have been previously published in detail elsewhere (14). SAGE is a longitudinal study gathering data through a series of cross-sectional interviews, surveys, and physical examinations from a large nationally representative sample of adults aged 50 years or older and a smaller sample of adults aged 18–49 years in six LMIC including China, Ghana, India, Mexico, Russian Federation, and South Africa between the years of 2007 and 2010. A multistage, stratified, random-clustered sampling design method by the World Health Survey was used to collect data from nationally representative samples. Weighted sampling yields data that is generalizable to population structures as reported by the United Nations Statistical Division. In-person interviews were administered via standard questionnaires in the participant's native language. To ensure cross-country comparability, standard translation procedures were carried out (15). Response rates among the included countries were as follows: China (93%), Russia (83%), Ghana (81%), South Africa (75%), India (68%) and Mexico (53%).
Adults aged 50 years or older from these countries were included in the study. Participants with missing data on objective visual impairment (primary outcome) or food insecurity (primary exposure) were excluded. The WHO Ethical Review Committee and local ethics research review boards approved the SAGE protocol. All participants provided written informed consent prior to study enrolment.
Primary Exposure: Food Insecurity
Two questions were used to assess food insecurity: (1) “In the last 12 months, how often did you eat less than you felt you should because there wasn't enough food?”; and (2) “In the last 12 months, were you ever hungry, but didn't eat because you couldn't afford enough food?”. Each question used a numeric Likert scale ranging from 1 – 5 points. The response options were as follows: every month (point = 1); almost every month (point = 2); some months, but not every month (point = 3); only in 1 or 2 months (point = 4); and never (point = 5). Food security status was classified as: (1) Severely food insecure: responded between 1 – 3 points on both questions or 1 point on one of the individual questions; (2) Moderately food insecure: responded between 2 – 4 points for either of the questions and did not meet the criteria for severely food insecure; and (3) Food secure: responded as 5 points on both of the questions (9). In the present study, a dichotomous variable for food insecurity was used (severe and moderate were considered as the same group) in the analyses.
Outcome: Objective Visual Impairment
Outcomes evaluated included distance-presenting vision impairment and near-presenting vision impairment. The examination of both distance and near visual acuity was conducted for each eye separately, using the Tumbling E LogMAR chart. The participant was seated in a chair that was 4 meters away from the eye chart to evaluate distance visual acuity. To evaluate near visual acuity, a 40 cm string was used to measure distance. The examiners were instructed to confirm that the charts were well-lighted and a glare was not present. The participants were asked to keep medical contact lenses or glasses on, if applicable (3, 15). The WHO criteria for distance-presenting visual impairment was used and represented the assessment of the ‘better' eye: Visual impairment was classified as a visual acuity worse than 6/18 (0.48 E LogMAR) (2).
Covariates
Socio-demographic information including age, gender, ethnicity, income, education, marital status, alcohol use within 30 days prior to the study, smoking, body mass index, low physical activity and presence of diabetes and hypertension were considered as confounding variables, which were identified from previous research (10). Presence of diabetes and hypertension were defined as a self-reported diagnosis (a systolic blood pressure >=140 mmHg or diastolic blood pressure >=90 mmHg for hypertension). Low physical activity was considered as less than 150 minutes of moderate to vigorous intensity per week as assessed by the Global Physical Activity Questionnaire.
Statistical Analysis
All statistical analyses were performed using Stata (Version 17.0). Multivariable binomial logistic regression was used in a country-wise analysis to assess the association between food insecurity and each of the outcome variables (near vision impairment and distance vision impairment). Subgroup analyses were performed for age and gender since these two factors may affect food insecurity and visual impairment. All analyses were adjusted for age, gender, income, tobacco use, alcohol use in the past 30 days, presence of a chronic condition (diabetes or hypertension), physical activity, BMI, and education level. All covariates were included in the models as categorical variables. The results were presented as odds ratios (ORs) and 95% confidence intervals (CIs). Additionally, Higgins' I2 was calculated according to estimates from each nation to explore any between-country heterogeneity in the relationship between food insecurity and vision impairment. Higgins' I2 is a measure of heterogeneity that is not explained by sampling error, with a value of <40% commonly classified as negligible and 40% – 60% classified as moderate heterogeneity. A random-effects meta-analysis model was used to produce a pooled estimate for the association between food insecurity and visual impairment.
Results
The analytical sample consisted of 29,804 adults aged 50 years or older from China (n=11,660), Ghana (n=4102), India (n=6035), Mexico (n=2028) Russia (n=2935), and South Africa (n=3044). The mean age was 63.2 (SD=9.54) years and 54.3% were female. The prevalence of food insecurity in the entire sample was 16.4%. The prevalence of vision impairment in the entire sample was 36.7% for near vision impairment and 13.9% for distance vision impairment. Additional sample characteristics are presented in Table 1.
Table 1.
Socio-demographic characteristics among older adults (≥ 50 years) in six low- and middle-incomes countries
| China (N=11660) | India (N=6035) | Mexico (N=2028) | Russia (N=2935) | South Africa (N=3044) | Ghana (N=4102) | ||
|---|---|---|---|---|---|---|---|
| Food Insecurity | |||||||
| Secure | 11511 (98.7%) | 4987 (82.6%) | 1458(71.9%) | 2572 (87.6%) | 2164 (71.1%) | 2230 (54.4%) | |
| Insecure | 156 (1.3%) | 1048 (17.4%) | 570 (28.1%) | 363 (12.4%) | 880 (28.9%) | 1872 (45.6%) | |
| gender | |||||||
| Male | 5406 (46.4%) | 3043 (50.4%) | 792 (39.1%) | 1053 (35.9%) | 1198 (39.4%) | 2137 (52.1%) | |
| Age | |||||||
| 50–59 | 5189 (44.5%) | 2814 (46.6%) | 394 (19.4%) | 1156 (39.4%) | 1337 (43.9%) | 1626 (39.6%) | |
| 60–69 | 3509 (30.1%) | 2050 (34.0%) | 847 (41.8%) | 804 (27.4%) | 977 (32.1%) | 1149 (28.0%) | |
| 70–79 | 2392 (20.5%) | 925 (15.3%) | 554 (27.3%) | 730 (24.9%) | 532 (17.5%) | 931 (22.7%) | |
| 80+ | 570 (4.9%) | 246 (4.1%) | 233 (11.5%) | 245 (8.3%) | 198 (6.5%) | 396 (9.7%) | |
| BMI | |||||||
| Underweight | 522 (4.5%) | 2106 (34.9%) | 57 (2.8%) | 109 (3.7%) | 147 (4.8%) | 642 (15.7%) | |
| Normal Weight | 7241 (62.1%) | 3039 (50.4%) | 506 (25.0%) | 642 (21.9%) | 764 (25.1%) | 2289 (55.8%) | |
| Overweight | 3228 (27.7%) | 690 (11.4%) | 812 (40.0%) | 1186 (40.4%) | 846 (27.8%) | 765 (18.6%) | |
| Obese | 669 (5.7%) | 200 (3.3%) | 653 (32.2%) | 998 (34.0%) | 1287 (42.3%) | 406 (9.9%) | |
| Income Quintiles | |||||||
| Quintile 1 | 2293 (19.7%) | 986 (16.3%) | 437 (21.5%) | 540 (18.4%) | 572 (18.8%) | 805 (19.6%) | |
| Quintile 2 | 2349 (20.1%) | 1119 (18.5%) | 431 (21.3%) | 571 (19.5%) | 627 (20.6%) | 815 (19.9%) | |
| Quintile 3 | 2370 (20.3%) | 1096 (18.2%) | 362 (17.9%) | 583 (19.9%) | 616 (20.2%) | 821 (20.0%) | |
| Quintile 4 | 2427 (20.8%) | 1304 (21.6%) | 410 (20.2%) | 582 (19.8%) | 620 (20.4%) | 838 (20.4%) | |
| Quintile 5 | 2228 (19.1%) | 1530 (25.4%) | 388 (19.1%) | 659 (22.5%) | 609 (20.0%) | 823 (20.1%) | |
| Diabetes | |||||||
| Yes | 750 (6.4%) | 434 (7.2%) | 402 (19.8%) | 251 (8.6%) | 301 (9.9%) | 157 (3.8%) | |
| Hypertension | |||||||
| Yes | 3164 (27.1%) | 1049 (17.4%) | 775 (38.2%) | 1646 (56.1%) | 941 (30.9%) | 547 (13.3%) | |
| Smoking | |||||||
| Yes | 3194 (27.4%) | 2877 (47.7%) | 370 (18.2%) | 521 (17.8%) | 785 (25.8%) | 512 (12.5%) | |
| Alcohol | |||||||
| Yes | 2419 (20.7%) | 448 (7.4%) | 280 (13.8%) | 939 (32.0%) | 461 (15.1%) | 1276 (31.1%) | |
| Education | |||||||
| Didn't Complete High School | 9686 (83.1%) | 5215 (86.4%) | 1819 (89.7%) | 861 (29.3%) | 2692 (88.4%) | 3272 (79.8%) | |
| Physical Activity | |||||||
| High | 6527 (56.0%) | 4060 (67.3%) | 828 (40.8%) | 2144 (73.0%) | 1155 (37.9%) | 3021 (73.6%) | |
| Distanced VI | |||||||
| No VI | 10363 (88.9%) | 5004 (82.9%) | 1693(83.5%) | 2346 (79.9%) | 2650 (87.1%) | 3595 (87.6%) | |
| Have VI | 1297 (11.1%) | 1031 (17.1%) | 335 (16.5%) | 589 (20.1%) | 394 (12.9%) | 507 (12.4%) | |
| Near VI | |||||||
| No VI | 7506 (64.4%) | 3451 (57.2%) | 1213(59.8%) | 1760 (60.0%) | 1971 (64.8%) | 2974 (72.5%) | |
| Have VI | 4154 (35.6%) | 2584 (42.8%) | 815 (40.2%) | 1175 (40.0%) | 1073 (35.2%) | 1128 (27.5%) | |
The associations between food insecurity and vision impairment are presented in Table 2. In the crude model, food insecurity was significantly associated with distance vision impairment in India (OR: 1.47; 95% CI: 1.25 to 1.73; P < 0.001), Russia (OR: 1.47; 95% CI: 1.14 to 1.89; P = 0.003), and South Africa (OR: 1.35; 95% CI: 1.08 to 1.69; P = 0.009). However, in the adjusted model the association between food insecurity and distance vision impairment only remained significant in India (OR: 1.31; 95% CI: 1.09 to 1.57; P = 0.004) and South Africa (OR: 1.29; 95% CI: 1.02 to 1.64; P = 0.040). In the crude model, food insecurity was significantly associated with near vision impairment in Russia (OR: 1.26; 95% CI: 1.00 to 1.57; P = 0.040) and South Africa (OR: 1.33; 95% CI: 1.13 to 1.40; P < 0.001). However, in the adjusted model the association between food insecurity and near vision impairment only remained significant in South Africa (OR: 1.30; 95% CI: 1.09 to 1.54; P = 0.003).
Table 2.
Association between food insecurity (FI) and vision impairment among older adults (≥ 50 years) in six low- and middle-incomes countries using multivariable logistic regression by country
|
China |
Ghana |
India |
Mexico |
Russia |
South Africa |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FS | FI | FS | FI | FS | FI | FS | FI | FS | FI | |||
| Crude | 1 | 1.38 (0.88 to 2.17) | 1 | 1.11 (0.92 to 1.34) | 1 | 1.47 (1.25 to 1.73) ** | 1 | 1.03 (0.8 to 1.34) | 1 | 1.47 (1.14 to 1.89) ** | 1 | 1.35 (1.08 to 1.69) ** |
| Adjusted† | 1 | 1.22 (0.75 to 1.97) | 1 | 0.90 (0.74 to 1.11) | 1 | 1.31 (1.09 to 1.57) ** | 1 | 1.08 (0.82 to 1.43) | 1 | 1.25 (0.95 to 1.64) | 1 | 1.29 (1.02 to 1.64) * |
| Participants/Cases (n) | 11504/1274 | 156/23 | 2230/264 | 1872/243 | 4987/801 | 1048/230 | 1458/239 | 570/96 | 2572/495 | 363/94 | 2164/258 | 880/136 |
| Near vision impairment | ||||||||||||
| Crude | 1 | 1.36 (0.99 to 1.88) | 1 | 1.07 (0.93 to 1.22) | 1 | 1.03 (0.91 to 1.19) | 1 | 1.15 (0.95 to 1.40) | 1 | 1.26 (1 to 1.57) * | 1 | 1.33 (1.13 to 1.40) ** |
| Adjusted† | 1 | 1.26 (0.90 to 1.75) | 1 | 1.06 (0.91 to 1.23) | 1 | 1.02 (0.88 to 1.18) | 1 | 1.06 (0.86 to 1.30) | 1 | 1.19 (0.94 to 1.50) | 1 | 1.30 (1.09 to 1.54) ** |
| Participants/Cases (n) | 11504/4087 | 156/67 | 2230/600 | 1872/528 | 4987/2127 | 1048/457 | 1458/572 | 570/243 | 2572/1012 | 363/163 | 2164/721 | 880/352 |
a. Food security; b. Food insecurity; *: p <0.05; **p <0.01; † Adjusted-model: adjusted for age, gender, wealth quintiles based on income, tobacco use, alcohol use in the past 30 days, presence diabetes and hypertension, physi-cal activity, BMI and level of education.
The results from all countries indicated that the prevalence of distance and near vision impairment was the highest among Russian individuals experiencing food insecurity (Figure 1 & Supplemental Figure 1).
Figure 1.
Prevalence of distance vision impairment (VI) by food insecurity (FI) status (secure or insecure) among older adults (≥ 50 years) in six low- and middle-incomes countries
The country-wise association between food insecurity and distance and near vision impairment is presented in Figure 2 & Figure 3. Pooled analyses across all countries revealed a significant association between food insecurity and distance (OR: 1.16; 95% CI: 1.01 to 1.33; P = 0.04) and near (OR: 1.12; 95% CI: 1.02 to 1.22; P = 0.01) vision impairment, with a between-country heterogeneity of 46.30% and 25.99%, respectively.
Figure 2.
Country-wise association between distance vision impairment and food insecurity status among older adults estimated by multivariable logistic regression
Figure 3.
Country-wise association between near vision impairment and food insecurity status among older adults (≥ 50 years) using multivariable logistic regression
Subgroup analyses for gender and age are provided in the supplemental material (Figures 2, 3, 4 & 5). There was no evidence of a statistically significant difference between the subgroups (P > 0.05).
Discussion
The present study found that food insecurity was associated with distance vision impairment in India and South Africa, while near vision impairment was associated with food insecurity in South Africa. The prevalence of distance and near vision impairment was higher among food insecure individuals across all included countries, with the highest prevalence of food insecurity found among individuals with vision impairment in Russia. Finally, pooled results across all countries demonstrated that food insecurity was associated with distance and near vision impairment.
Food insecurity was associated with a greater odds of vision impairment in India and South Africa. India is known as the largest underserved population whereby individuals live below poverty in dense low-income settlements (16). Food insecurity is a visible reality in India resulting in increased vulnerability to a wide spectrum of unfavorable health outcomes (16, 17). India has one-fifth of the world's population and the yields of rice and wheat in India provide nearly adequate amounts for consumption for the population in India. However, when all macronutrients (i.e., carbohydrates, protein, and fat) are considered, there are not enough food sources available to the population to meet nutritional requirements. In addition, food insecurity in India is driven by gender inequality, unequal distribution and low purchasing power (18). Findings from surveys have suggested that up to 80 percent of some regions in South Africa could be categorized as moderately or severely food insecure due to price policies, restricted endemic agriculture and rural—urban food transfer limitations (19, 20). Food insecurity can result in undernutrition or over nutrition by affecting health status either directly or indirectly. Food insecurity is related to adverse physical and mental health, disordered eating behaviors, macronutrient and micronutrient deficiencies, lower hemoglobin, lower serum albumin, and vitamin A deficiency (21), which may indicate possible mechanisms for the effects of food insecurity on visual impairment.
Although food insecurity in Ghana reflects general poverty in the population (22), there was no evidence of a significant association between food insecurity and vision impairment in present study. Similarly, Mexico has a high prevalence of food insecurity, which may be an independent risk factor for the development of depression, obesity, stress, type 2 diabetes and hypertension (23). However, an association between food insecurity and visual impairment was not found in Mexico in the present study. Furthermore, China experiences the most serious natural disasters with annual grain losses of more than 7% of its total grain production, which have the potential to cause food security disruptions in this population. Ultimately, there is limited data available on the associations between food insecurity and visual impairment in these countries, which warrants further investigations.
The greatest prevalence of distance and near vision impairment in individuals experiencing food insecurity was found in Russia. In Russia, food insecurity differs compared to other countries as the concern is not necessarily related to insufficient availability or supply of resources within the country, but rather is often a result of inadequate access or unhealthy food choices due to socioeconomic status and poverty (24). Population growth, climate change, and the availability of water resources and lands can also influence food insecurity and its related complications (25).
Food insecurity may impair vision through various pathways. Older adults often experience chronic health conditions which tend to be accompanied by increased financial needs due to greater healthcare and food expenditures to meet medical and nutritional recommendations. These households may be at higher risk of food insecurity (26). It is reasonable to suggest that individuals experiencing food insecurity may skip meals, reduce daily food intake, and may consume low quality diets including foods high in salt, sugar or saturated fats. These factors may result in food insecurity, but also may contribute to the development or deterioration of chronic complications that can cause vision-related diseases including cataract, macular degeneration, and diabetic retinopathy (10, 27, 28, 29). Furthermore, individuals experiencing food insecurity and poor-quality diets have a greater risk of diabetes and hypertension, which is a potential risk factor for vision impairment through increased inflammatory and oxidative stress products (10, 30, 31, 32, 33). Food insecurity is also characterized by increased stress and dietary pattern variation which stimulates immune system and incite inflammation (34), which is another possible pathway involved in the pathogenesis of vision impairment in individuals experiencing food insecurity.
In line with our findings, prior research has found that food insecurity was associated with a greater risk of vision impairment. In a representative sample of the United States older adult population, vision impairment was associated with food security status in a dose-response pattern. This study found that individuals with very poor food security status had a greater risk of self-reported vision impairment and objectively assessed vision impairment (10). These findings align with results from the present study indicating a significant association between food insecurity and visual impairment (10). However, the association appears to be weaker in the present study. A potential explanation may be the use of different criteria to evaluate food insecurity and vision impairment in the present study compared to the previous study in the US population (10).
Many factors may affect the prevalence of food insecurity and vision impairment, which remain not fully understood. Vision impairment may be accompanied by nutritional deprivation via low mobility and functional status, which can cause difficulties with shopping and food preparation (35, 36). Furthermore, vision impairment may cause food insecurity due to challenges with social services and healthcare affordability and accessibility (e.g. online platforms for direction and transportation) (37). For instance, food insecurity may be directly associated with missing eye examinations in a diabetic patients, which can exacerbate visual impairment (38). In fact, it is possible that vision impairment and food insecurity have a two-way relationship highlighting the potential for reverse causality or simultaneity in the observed associations. Kumar et al. found a significant association between visual impairment and food insecurity in a dose-response manner (39). Furthermore, Muurinen and colleagues demonstrated that elderly residents with vision complications had a higher risk of malnutrition (35).
The present study has several strengths and limitations that should be considered. The study is novel as it is one of few studies that has evaluated the association between food insecurity status and distance and near vision impairment. The study had a large sample size increasing the power of the analysis and incorporated data from six low- and middle-income countries improving the generalizability of the findings while considering the individual associations in each country. However, these findings were derived from cross-sectional data which did not allow us to analyze the temporal association between vision impairment and food insecurity. Therefore, definite conclusions about cause-effect relationships cannot be established. Another limitation of this study is that we used two independent questions to evaluate food insecurity rather than a validated questionnaire such as the USDA Food Security Survey 10-item Module. Future research evaluating longitudinal associations are needed to elucidate these relationships and the possible mechanisms contributing to the findings.
Conclusion
The present study found that food insecurity was associated with both distance and near vision impairment in older adults aged 50 years or older. These findings highlight the importance of alternative food policies and interventions targeted at reducing food insecurity are essential in vulnerable households.
Acknowledgments
This article uses data from the WHO Study on Global Ageing and Adult Health (SAGE). SAGE is supported by the U.S. National Institute on Aging through Interagency Agreements OGHA 04034785, YA1323-08-CN-0020, Y1-AG-1005-01 and through research grants R01-AG034479 and R21-AG034263.
Ethical standards
We used secondary analysis of datasets from Study on global AGEing and adult health (SAGE).
Conflict of interest
The authors declare no conflicts of interest.
Electronic Supplementary Material
Supplementary material is available in the online version of this article at https://doi.org/10.1007/s12603-023-1903-1.
Supplementary material, approximately 383 KB.
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