Mediating Effect of Metabolic Diseases on the Relationship Between Dietary Inflammatory Index (DII) and Cataract Prevalence: A Structural Equation Modeling Study

Abstract

Background/Objectives: Aging increases the risk of metabolic diseases, such as diabetes, hypertension, dyslipidemia, and obesity, which may contribute to cataract development. This study examined whether metabolic diseases mediate the relationship between the dietary inflammatory index (DII) and cataract prevalence using structural equation modeling (SEM). Methods: Data were obtained from 9260 individuals aged 40 and older who participated in the 8th Korea National Health and Nutrition Examination Survey (KNHANES 2019–2021). DII scores, calculated from 24 h dietary recall, reflect the inflammatory potential of the diet, with higher scores indicating a more pro-inflammatory profile. SEM was applied to assess mediation effects, and analyses were conducted using SPSS 29.0 and AMOS 29.0. Results: Among the participants, 1853 individuals (20.0%) were diagnosed with cataracts, and the mean DII was 1.5 ± 2.8. In the high DII group, the risk of hypertension (β = 0.077, p < 0.001) and dyslipidemia (β = 0.033, p = 0.001) increased significantly. Hypertension (β = 0.187, p < 0.05), diabetes mellitus (β = 0.132, p < 0.05), dyslipidemia (β = 0.108, p < 0.05), and obesity (β = 0.025, p < 0.05) had direct effects on cataract prevalence. Diabetes 0.002 (p < 0.05), hypertension 0.014 (p < 0.05), and dyslipidemia 0.004 (p < 0.05) also showed significant indirect effects. Conclusions: Metabolic diseases mediate the relationship between DII and cataracts. Managing inflammation and metabolic health may reduce cataract risk.

1. Introduction

In Korea, advancements in medical technology and improvements in living standards have led to an increase in average life expectancy, resulting in a steady rise in the middle-aged and elderly population. According to data from Statistics Korea, the proportion of individuals aged 65 and older was 15.7% in 2020 and increased to 19.2% in 2024 [1]. At the same time, the middle-aged population is also growing, and the prevalence of metabolic diseases such as diabetes [2], hypertension, dyslipidemia, and obesity has been increasing from middle age onward. Additionally, among individuals aged 65 and older, the prevalence of both metabolic diseases and age-related eye diseases has been rising. According to Statistics Korea, the proportion of people with at least one chronic disease was 19.7% in 2019 and increased to 20.5% in 2020 [3].

Middle age is a period of progressive aging, during which the risk of developing metabolic diseases may increase if lifestyle habits are not properly managed [4]. The increasing prevalence of metabolic diseases and age-related eye diseases not only affects individual health but also leads to a decline in quality of life [5]. Some studies suggest that inflammatory responses triggered by unhealthy lifestyle habits contribute to an increased risk of metabolic diseases [6] which, in turn, further promote oxidative stress and inflammation in the body [6]. In particular, poor dietary habits and lack of physical activity can lead to metabolic diseases such as diabetes [7], hypertension [8], dyslipidemia [9], and obesity [10]. These conditions weaken the body’s antioxidant defense system, promote excessive production of reactive oxygen species (ROS), and ultimately cause oxidative damage. Oxidative stress damages cells and tissues, activates inflammatory responses, and sustains a state of chronic inflammation [11]. This vicious cycle not only accelerates metabolic disorders but is also closely linked to diseases caused by oxidative stress, such as cataracts. Therefore, understanding the mechanisms underlying the interaction between inflammation, metabolic diseases, and cataracts is essential.

Age-related eye diseases include cataracts, glaucoma, macular degeneration, and diabetic retinopathy, with cataracts being the most common. The development of cataracts is influenced by factors such as ultraviolet (UV) exposure [12], smoking [13], alcohol consumption [14], and quality of life [5]. Oxidative stress is also known to play a key role in the prevalence of cataracts [11]. It is a critical factor in the onset and progression of cataracts, as it causes continuous oxidative damage to the eye’s lens, leading to inflammation. Prolonged inflammatory responses have been reported to contribute to cataract development [11]. Some research suggests that the antioxidant nutrients vitamins C and E play a crucial role in protecting the eye from oxidative damage caused by UV exposure [15]. Antioxidants help neutralize ROS, reduce oxidative damage, and support eye health [10]. Therefore, ensuring adequate antioxidant nutrient intake among middle-aged and older adults is essential for cataract prevention, emphasizing the need for practical dietary strategies to promote sufficient antioxidant consumption.

The dietary inflammatory index (DII) is a comprehensive measure that evaluates the impact of various foods and nutrients on inflammation in the body. It assesses the overall inflammatory potential of a diet by scoring foods based on their ability to promote or suppress inflammation [16]. A lower DII score, indicating a diet rich in anti-inflammatory foods, has been reported to help reduce inflammation and promote overall health [15]. Managing inflammation levels through dietary intake has been associated with the prevention of various chronic diseases [17]. Moreover, recent studies suggest that a higher DII is linked to an increased prevalence of age-related eye diseases [6,18]. Inflammatory dietary patterns may contribute to the development of metabolic diseases which, in turn, increase the risk of cataract formation. Therefore, managing inflammation levels in the body may be an essential strategy for preventing and managing both metabolic diseases and age-related eye conditions.

To date, studies on dietary intake and cataracts in Korea have primarily focused on analyzing nutrient intake in cataract patients or assessing cataract risk based on dietary factors. However, since cataracts are influenced by multiple factors, a more comprehensive analysis incorporating various contributing elements is necessary. In particular, there is a lack of research on the association between the DII and cataract prevalence mediated by metabolic diseases in Korean adults. Therefore, this study aims to examine whether DII influences cataract prevalence through metabolic diseases as mediators by utilizing data from the 8th Korea National Health and Nutrition Examination Survey (KNHANES 2019–2021) for individuals aged 40 years and older. To achieve this, a structural equation modeling (SEM) approach was applied to analyze these relationships.

2. Materials and Methods

2.1. Research Design and Hypotheses

This study utilized raw data from the 8th KNHANES (2019–2021) provided by the Korea Disease Control and Prevention Agency. The objective was to examine the mediating effects of metabolic diseases including diabetes, hypertension, dyslipidemia, and obesity in the association between the DII and cataract prevalence. This hypothesis is based on the premise that pro-inflammatory dietary patterns may promote systemic inflammation, thereby contributing to the development of metabolic disorders. These metabolic conditions are known to increase oxidative stress and accelerate cataract formation through oxidative damage. The proposed research model is illustrated in (Figure 1). Ethical approval was obtained from the Clinical Test Deliberation Commission of the In-stitutional Review Board at Wonkwang University, Iksan City, Korea (Approval No. WKIRB-202409-SB-063).

Hypotheses

H1: 

Higher DII will be associated with an increased risk of cataract prevalence.

H2: 

Higher DII will be associated with an increased risk of metabolic diseases.

H3: 

The presence of metabolic diseases will be associated with an increased risk of cataract prevalence.

H4: 

Metabolic diseases will mediate the relationship between DII and cataract prevalence.

2.2. Study Population

This study was analyzed using raw data from the eighth round of the KNHANES (2019–2021). Of the 22,559 people who participated in the survey in those years, 11,635 were middle-aged and older adults aged 40 to 80 years, including those with a total daily intake of less than 500 kcal and more than 5000 kcal (n = 147), those with current cancer (n = 708), and those with myocardial infarction and stroke (n = 374). Those with missing data on sociodemographic factors or body mass index, and those with missing data on glycated hemoglobin, fasting blood glucose, and systolic and diastolic blood pressure levels (n = 1146) were excluded, resulting in a final study population of 9260 subjects (3858 men and 5402 women). The study population selection process is shown in Figure 2.

2.3. Dietary Inflammatory Index (DII)

The DII was calculated using the scoring system developed by Shivappa et al. [16], based on a systematic literature review. This index quantifies the impact of various nutrients and foods on systemic inflammation and is constructed based on its association with inflammatory biomarkers, including IL-1β, IL-4, IL-6, IL-10, TNF-α, and Hs-CRP. Higher DII scores indicate a more pro-inflammatory diet and increased levels of systemic inflammation. To calculate the DII, 36 nutrients and 9 food items were analyzed using dietary intake data. Among the 45 potential components proposed in the original DII model, only 36 were available and used for the calculation in this study. The KNHANES provided intake data for energy, carbohydrates, protein, fat, saturated fat, dietary fiber, cholesterol, calcium, sodium, magnesium, iron, zinc, vitamin A, vitamin D, vitamin E, beta-carotene, thiamin, riboflavin, niacin, folate, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, n-3, and n-6 fatty acids, as well as pepper, onion, ginger, green tea, and black tea. Additionally, selenium, vitamin B6, and trans fatty acid intake were obtained from the National Standard Food Ingredient Database (ver. 10.2) [19], while flavonoid intake including flavones, flavonols, isoflavones, and flavanones was derived from the flavonoid composition data of the Rural Development Administration [20]. Components unavailable in domestic food composition databases or those lacking sufficient verification were excluded. Finally, DII scores were calculated by applying the effect scores assigned to each component, as proposed by Shivappa et al. [16].

2.4. General Characteristics

In this study, the presence of cataracts was determined by participants answering yes or no to the question of whether a “cataract has been diagnosed by a doctor” in the raw data of the 8th KNHANES (2019–2021) provided by the Korea Centers for Disease Control and Prevention.

The study utilized survey data to collect information on participants’ sex, age, body mass index (BMI), marital status, alcohol consumption, smoking status, activity limitations, hypertension status, diabetes status, and dyslipidemia status. Marital status was categorized using the marital status variable. Individuals who reported being “married, cohabiting” were grouped as “cohabiting”, while those who responded, “married but separated”, “widowed”, or “divorced” were categorized as “living alone”. Smoking status was determined using the current cigarette smoking status variable. Participants who responded, “smoke daily” or “smoke occasionally” were classified as “current smokers”. Those who answered, “used to smoke but do not currently smoke” were classified as “former smokers”, while those who responded, “do not currently smoke”, “not applicable”, or “unknown” were categorized as “non-smokers”. Alcohol consumption was categorized based on the alcohol consumption frequency in the past year variable. Participants who answered, “not applicable” or “unknown, no response” were classified as “does not drink”. Those who reported “have not consumed alcohol in the past year” or “drink less than once per month” were categorized as “less than once per month”. Participants who reported drinking “once a month” or “2–4 times per month” were grouped as “1–4 times per month”. Those who answered “2–3 times per week” were classified as “2–3 times per week”, and those who reported “4 or more times per week” were categorized as “4 or more times per week”. Activity limitation was assessed using the activity limitation status variable. Participants who answered “no”, “not applicable (children)”, or “unknown, no response” were categorized as “able to perform activities”, while those who answered “yes” were classified as “unable to perform activities”. Hypertension, diabetes, and dyslipidemia status were each determined using their respective diagnosis variables. Participants who responded “yes” were classified as having the condition, while those who answered “no”, “not applicable” were classified as not having the condition.

2.5. Statistical Analysis

Statistical analyses were performed using SPSS version 29.0 and AMOS version 29.0 programs. To analyze participants’ characteristics based on cataract status, categorical variables were assessed using cross-tabulation analyses, while continuous variables were analyzed using a general linear model (GLM), and results are presented as n (%) or mean ± standard error (SE). DII was adjusted for total energy intake per 1000 kcal and categorized into tertiles for analysis. SEM was employed to examine the relationship between DII and cataract prevalence through metabolic diseases. The model fit was evaluated using absolute fit indices, including CMIN (χ²), GFI (goodness-of-fit index), RMR (root mean square residual), and RMSEA (root mean square error of approximation), as well as incremental fit indices, including NFI (normed fit index), IFI (incremental fit index), and CFI (comparative fit index). The significance of the hypothesized model was assessed using the p-value of the critical ratio (CR). To evaluate the significance of direct, indirect, and total effects, a bootstrapping procedure with 2000 resamples was conducted. Both percentile and bias-corrected confidence intervals were set at the 95% level. The maximum likelihood (ML) method was applied for bootstrapping.

3. Results

3.1. General Characteristics of Subjects by Cataracts

The general characteristics of participants aged 40 years and older are presented in (

Table 1. Demographic and clinical characteristics of study subjects according to cataract status.

Variable	Non-Cataract		Cataract		p-Value
Sex (n(%))					<0.001
Men	3167	(42.8) (1)	691	(37.3)
Women	4240	(57.2)	1162	(62.7)
Age (year)	57.0	±10.8 (2)	70.2	±8.5	<0.001
BMI (kg/m2)	24.1	±3.4	24.4	±3.3	0.003
Income					<0.001
Lowest	1249	(16.9)	762	(41.1)
Lower middle	1816	(24.5)	515	(27.8)
Upper middle	2035	(27.5)	325	(17.5)
Highest	2307	(31.1)	251	(13.5)
Education					<0.001
≤Elementary	1291	(17.4)	917	(49.5)
Middle school	850	(11.5)	297	(16.0)
High school	2554	(34.5)	392	(21.2)
≥University	2712	(36.6)	247	(13.3)
Marital status					<0.001
Living together	5933	(80.1)	1209	(65.2)
Alone	1474	(19.9)	644	(34.8)
Activity restriction					<0.001
Yes	496	(6.7)	292	(15.8)
No	6911	(93.3)	1561	(84.2)
Drinking					<0.001
Non-drinking	840	(11.3)	466	(25.1)
Less than once a month	2906	(39.2)	780	(42.1)
1–4 times a month	2131	(28.8)	340	(18.3)
2–3 times a week	1058	(14.3)	156	(8.4)
More than 4 time a week	472	(6.4)	111	(6.0)
Smoking					<0.001
Non-smoking	4489	(60.6)	1216	(65.6)
Past	1768	(23.9)	462	(24.9)
Current	1150	(15.5)	175	(9.4)
Hypertension	1959	(26.4)	944	(50.9)	<0.001
Diabetes mellitus	774	(10.4)	431	(23.3)	<0.001
Dyslipidemia	1590	(21.5)	662	(35.7)	<0.001
Obesity (BMI > 25 kg/m2)	2688	(36.3)	731	(39.4)	0.012
DII	0.9	±2.3	1.5	±2.8	<0.001

⁽¹⁾ N (%). ⁽²⁾ Mean ± SE. BMI, body mass index; DII, dietary inflammation index (ranges from −7.30~8.97).

). Among the total participants, 691 (37.3%) were men and 1162 (62.7%) were women (p < 0.001). The mean age of the cataract group was 70.2 ± 8.5 years. The proportions of current smokers (p < 0.001) and alcohol drinkers (p < 0.001) were both lower in the cataract group. In the cataract group, a lower level of household income and educational attainment was associated with a higher prevalence of cataracts (p < 0.001). Cataract prevalence was higher among individuals living alone and those with activity limitations (p < 0.001). In terms of disease status, the cataract group showed significantly higher prevalence of hypertension (p < 0.001), diabetes mellitus (p < 0.001), dyslipidemia (p < 0.001), and obesity (p = 0.012). The mean DII score ranged from -7.30 to 8.97. It was 1.5 ± 2.8 in the cataract group and 0.9 ± 2.3 in the non-cataract group, and significantly higher scores were observed among those with cataracts (p < 0.001).

3.2. DII and Cataracst: Mediating Effects of Metabolic Diseases

After adjusting the DII to 1000 kcal, the mediating effect of DII on the relationship between cataract prevalence and metabolic diseases was analyzed by dividing it into three groups: LOW, MID, and HIGH, shown in (Figure 3).

The model fit was evaluated using indices such as CMIN, GFI, and RMSEA. A model is considered to have an adequate fit if the GFI is above 0.90 and the RMSEA is below 0.08. The analysis results showed that all models had GFI values of 0.986 or higher and RMSEA values below 0.08, indicating that the research models demonstrated an overall acceptable fit. Additionally, the NFI was 0.880, the IFI was 0.881, and the CFI was 0.885, which were close to the threshold of >0.9, making them acceptable.

In the LOW DII group, hypertension β = −0.063 (p < 0.001), dyslipidemia β = −0.032 (p = 0.002), and obesity β = −0.024 (p = 0.023) had a negative effect on disease prevalence. In the MID DII group, there was no significant relationship with DII for any disease. In the HIGH DII group, hypertension β = 0.077 (p < 0.001) and dyslipidemia β = 0.033 (p = 0.001) had a positive effect on disease prevalence.

When analyzing the direct effects of metabolic diseases on cataract development, diabetes mellitus β = 0.132 (p< 0.05), hypertension β = 0.187 (p< 0.05), dyslipidemia β = 0.108 (p< 0.05), and obesity β = 0.025 (p< 0.05) were found. Of these, hypertension had the strongest direct association with cataract development, followed by diabetes and dyslipidemia.

The indirect effects of metabolic diseases on cataract prevalence by DII were significant negative indirect effects of −0.002 (p < 0.05) for diabetes, −0.012 (p < 0.05) for hypertension, −0.003 (p < 0.05) for dyslipidemia, and −0.001 (p < 0.05) for obesity in the LOW DII group. In the HIGH DII group, diabetes had a significant positive indirect effect of 0.002 (p < 0.05), for hypertension, 0.014 (p < 0.05), and dyslipidemia, 0.004 (p < 0.05).

4. Discussion

This study analyzed the mediating effect between DII and metabolic diseases on cataracts among adults aged 40 years and older using data from the 8th KNHANES (2019–2021). The results showed that in the LOW DII group, metabolic diseases had a significant negative indirect effect on cataract prevalence, whereas in the HIGH DII group, metabolic diseases had a significant positive indirect effect on cataract prevalence.

In this study, the analysis of the association between DII and metabolic diseases showed that in the LOW DII group, hypertension, dyslipidemia, and obesity had a significant negative (−) relationship, whereas in the HIGH DII group, diabetes, hypertension, and dyslipidemia had a significant positive (+) association. These findings suggest that an inflammatory diet may increase the risk of developing metabolic diseases. Previous research analyzing the relationship between an inflammatory diet and metabolic syndrome in Mexican adults found that individuals in the HIGH DII group had approximately twice the risk of developing hypertension, hypertriglyceridemia, and abdominal obesity compared to those in the LOW DII group [21]. Another study also reported that higher DII scores were associated with an increased risk of obesity, diabetes, and cardiovascular diseases [22]. These findings align with the results of the present study, where higher DII scores were associated with an increased prevalence of metabolic diseases, further reinforcing the strong link between DII and metabolic disease development.

The analysis of the impact of metabolic diseases on cataract prevalence in this study showed that hypertension, diabetes, and dyslipidemia were significantly associated with cataracts across all groups, with hypertension being the strongest risk factor. A previous study conducted in Bangladesh among adults aged 41 years and older found that the risk of developing cataracts was 4.64 times higher in those with obesity (BMI ≥ 25 kg/m²) and 3 times higher in those with dyslipidemia [23]. Similarly, a study conducted in Greece found that hypertension was the most significant risk factor for cataract prevalence among diabetes, hypertension, and dyslipidemia [24]. These findings align with the present study, reinforcing the strong association between metabolic diseases and cataract risk. Hypertension and dyslipidemia have been linked to the effects on ocular blood supply and lipid metabolism [25]. Hypertension is an increase in blood pressure caused by impaired vascular function, which can impede blood flow to the ocular tissues, reducing the supply of nutrients and oxygen to the lens [8]. This can lead to increased oxidative stress and promote the degeneration and clouding of lens proteins, which can increase the risk of developing cataracts [24]. Dyslipidemia is also characterized by abnormalities in lipid metabolism in the blood and can alter the structure and function of the lens cell membrane by promoting lipid peroxidation reactions in the lens, which can increase oxidative damage [9]. These mechanisms contribute to cataract formation, highlighting the importance of preventing and managing hypertension and dyslipidemia as key strategies for cataract prevention. In contrast, obesity did not show a significant impact compared to other metabolic diseases in this study. This may be due to the use of BMI as the sole measure of obesity, whereas previous studies have considered various indicators such as waist circumference and waist-to-hip ratio [23]. Research analyzing the relationship between visceral fat and metabolic diseases has shown that an increase in visceral fat is strongly associated with a higher risk of metabolic syndrome. Among obesity indicators, waist circumference has demonstrated the highest correlation with visceral fat, suggesting its importance as a key measure of abdominal obesity [26]. Based on these findings, future studies should consider alternative indicators such as waist circumference, waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), body fat percentage, and visceral fat area to better understand the relationship between obesity and cataract prevalence.

The results of this study suggest that DII influences cataract prevalence via metabolic disease. Diets high in DII are high in saturated fats, simple sugars, trans fats, and high sodium, which increase the production of pro-inflammatory cytokines (IL-6, TNF-α, CRP, etc.) in the body as a mechanism of inflammation [15]. Chronic inflammation triggered by such a diet induces oxidative stress, impairs metabolic function, and increases the risk of metabolic diseases. Metabolic disease is an important mediating factor in the prevalence of cataracts, with diabetes impairing vascular function due to elevated blood glucose concentrations, disrupting glucose metabolism in the lens and inducing oxidative stress [27]. This oxidative damage can cause protein denaturation and lens opacity, thereby accelerating cataract formation [7]. Visual impairment caused by protein denaturation and lens opacity, such as reduced visual acuity, visual field defects, and visual distortion, can lead to difficulties in daily life and significantly impact physical functioning and quality of life [5]. Hypertension also impairs blood flow, reducing the supply of oxygen and nutrients to ocular tissues [8,24]. Dyslipidemia leads to abnormalities in lipid metabolism in the blood, which increases lipid peroxidation reactions, which in turn induces oxidative stress, which can damage the lens cell membrane and increase the prevalence of cataracts [9,25]. Thus, it can be interpreted that a diet high in DII increases inflammation levels in the body, leading to the development of metabolic diseases, and these metabolic diseases mediate cataract development through oxidative stress and impaired blood flow.

This study used energy-adjusted DII values (per 1000 kcal intake) to account for differences in total energy intake among participants. The DII was categorized into tertiles, and SEM was used to analyze the mediating effect of metabolic diseases on the relationship between DII and cataract prevalence. As a result, cataract prevalence increased in the HIGH DII group, and the indirect effect of DII on cataract prevalence became significantly stronger when hypertension and dyslipidemia acted as mediators. These findings align with previous research, which has shown that higher DII levels increase the risk of metabolic diseases [17], and that these metabolic diseases, in turn, contribute to a higher risk of cataract development [28,29]. Previous studies have reported that anti-inflammatory dietary patterns, including fruits, vegetables, fatty fish, nuts, and olive oil, have beneficial effects on metabolic health [30]. In particular, the Mediterranean diet, rich in antioxidant and anti-inflammatory components, has been shown to reduce systemic inflammation and lower the risk of metabolic diseases [31,32]. These findings suggest that lowering DII may play a crucial role in not only preventing metabolic diseases but also reducing cataract risk. Based on these results, a structured anti-inflammatory diet may be particularly beneficial for individuals with metabolic conditions such as hypertension, diabetes, and dyslipidemia, contributing to cataract prevention and management.

This study differs from previous research in that it did not merely analyze simple associations but instead utilized SEM to examine the mediating effect of metabolic diseases on the relationship between DII and cataract prevalence. This study suggests a possible pathway through which DII may influence cataract prevalence via metabolic diseases, indicating that improving overall dietary habits may be a more effective strategy for preventing and managing both metabolic diseases and cataracts than focusing solely on individual conditions.

This study has several limitations. First, since the 24 h recall method was used to assess dietary intake, it may not accurately reflect usual eating habits or intake levels. Second, this study was conducted as a cross-sectional study using data from the KNHANES, which limits the ability to clearly establish a causal relationship between the DII and cataract prevalence because it was not possible to identify the time of the metabolic disease dietary survey and the time of cataract development. Therefore, a prospective cohort study with a follow-up period of at least 2 to 5 years is needed to evaluate the long-term effects of dietary patterns on the development of metabolic diseases and cataracts. Such studies may help clarify how changes in the DII affect the prevalence of cataracts. Third, this study analyzed people aged 40 and older; however, cataracts are generally an age-related eye disease with a sharp increase in prevalence after the age of 60. Future studies should consider age-stratified analyses to investigate potential variations in the relationship between DII, metabolic diseases, and cataract prevalence across different age groups. Despite these limitations, this study is significant as it is the first to analyze the mediating effect of metabolic diseases in the association between DII and cataract prevalence using large-scale national data. This study comprehensively examines their interrelationships, providing new insights into dietary inflammation and cataract risk.

5. Conclusions

This study demonstrated that individuals with a higher DII exhibited a significantly greater prevalence of cataracts, and that this association was significantly mediated by the presence of metabolic diseases, particularly hypertension and dyslipidemia. These findings suggest that pro-inflammatory dietary factors play a critical role not only in the development of various metabolic disorders but also in age-related ocular conditions such as cataracts, highlighting the importance of dietary strategies aimed at reducing systemic inflammation. Accordingly, modifying dietary patterns to lower the DII may serve as an effective preventive approach for both metabolic diseases and cataract development. In particular, an anti-inflammatory diet rich in fruits, vegetables, and antioxidants should be strongly recommended for middle-aged and older adults, and such dietary guidelines should be integrated into public health education campaigns and intervention programs to reduce the burden of chronic diseases.