Ground-Level Ozone Exposure and Type 2 Diabetes Incidence: An Ecological Study of Environmental and Social Determinants

Abstract

Ambient air pollution causes 4.2 million premature deaths annually. Ozone (O₃), a secondary pollutant, is prevalent in urban areas with high transportation/industrial emissions. Chronic exposure to ozone is associated with cardiovascular and respiratory diseases and with metabolic disorders, such as type-2 diabetes (T2D). This study examined the relationship between chronic exposure to ground-level ozone, socioeconomic status, and T2D incidence. We found a significant positive correlation between ozone exposure and the T2D incidence in Israel’s urban population (municipalities with ≥20,000 residents). Univariate and multivariate linear regression analyses revealed that exposure to ground-level ozone significantly contributed to the T2D morbidity, mostly in ages ≥ 45 years. Our results emphasize the relationship between chronic ozone exposure and T2D in Israel’s unique heterogeneous populations and highlight health risks associated with ozone exposure. While socioeconomic status is a significant determinant of T2D, as shown in the current study, our findings suggest that environmental factors, such as exposure to ground-level ozone, exert independently potent effects. This emphasizes the need to consider both socioeconomic and environmental factors in public health strategies. Stricter air quality regulations and targeted public health interventions are essential, particularly in high-ozone areas. Reducing ambient ozone levels could also help mitigate the T2D burden, particularly among vulnerable populations.

1. Introduction

Air pollution, a significant environmental concern, comprises a complex mixture of gases, particles, and biological molecules that may critically impact human health [1]. Annually, 6.7 million to 8.8 million people die prematurely worldwide due to exposure to air pollution [2], with 4.2 million of them as a result of exposure to ambient air pollution [3]. Notably, more than 90% of the global population breathes air that contains pollutants at levels exceeding the World Health Organization’s (WHO’s) guideline limits, especially in low- and middle-income countries [4]. Ground-level ozone (O₃), formed by photochemical reactions between NOx and VOCs in sunlight, significantly contributes to urban air pollution [5,6,7].

The health impacts of exposure to air pollution in general [8,9,10] and particularly to ozone are extensive [11,12,13]. High ozone levels are linked to compromised lung function [14,15] and respiratory conditions, such as asthma and chronic bronchitis [13,14]. Beyond these immediate effects, chronic exposure to ozone has been associated with more insidious health concerns, including cardiovascular diseases [11,15].

Recent studies suggest that ozone exposure may play a role in metabolic disorders, including associations with glucose intolerance and hyperlipidemia, which are precursors to diabetes [16,17]. As glucose intolerance often indicates pre-existing diabetes, recent studies have also been focusing on exploring the association between elevated ozone exposure and the incidence of diabetes, suggesting a complex interaction between environmental factors and glucose metabolism [18,19,20].

Several studies have provided initial support for a positive and robust association between long-term exposure to ozone and diabetes. This association has been observed among African American women living in 56 metropolitan areas across the United States [21,22], as well as among adults in China [19]. Long-term exposure to elevated ozone levels may increase the risk of type 2 diabetes (T2D) [23]. For example, it was found that individuals engaging in high levels of outdoor physical activity are particularly vulnerable to developing T2D when exposed to elevated ozone levels [24]. Additionally, a recent study revealed that daily ozone exposure during pregnancy increases the risk of developing Gestational Diabetes Mellitus (GDM). Reducing ambient ozone pollution may reduce the burden of both diseases [18]. Complementing these human studies, animal model studies have also provided critical insights into the mechanisms by which ozone contributes to diabetes, demonstrating that ozone exposure induces oxidative stress, inflammation, and impaired insulin sensitivity in rodents, which are factors known to increase the diabetes risk [25,26].

Socioeconomic status (SES), a multidimensional construct encompassing factors such as income, education, and occupation, profoundly influences individuals’ health trajectories [27,28,29]. This influence extends to environmental exposure, where SES can modulate both the likelihood and severity of exposure to environmental hazards, thereby exacerbating health disparities [30].

SES significantly influences health outcomes in the context of environmental exposure to ozone. Low-income areas often experience higher air pollution levels, including increased ozone exposure [31], leading to increased health risks, such as respiratory diseases and childhood asthma-related hospitalizations [32,33]. Similarly, during the COVID-19 pandemic, chronic air pollution exposure and low SES were associated with higher morbidity rates in the Israeli population [34].

A low SES is also associated with increased diabetes incidence [35]. Several key factors contribute to this association, including excessive weight and obesity [36]; racial differences, with a particularly high rate of T2D found among low SES African-Americans [37]; and economic transition, urbanization, and globalization, which have negative effects on lifestyle and diet [38]. Socioeconomic factors, such as illiteracy, unemployment, and low economic status, have also been linked to increased diabetes prevalence [39]. These findings highlight the complex interplay between biological, social, and environmental factors in shaping diabetes disparities.

Despite growing global evidence, few studies have examined the combined effects of ozone and SES on diabetes in a small, demographically diverse country like Israel. The ozone thresholds in Israel are higher than the WHO and EU (European Union) standards [40], making the population uniquely vulnerable.

This ecological study aimed to examine the relationships between chronic population-level exposure to ground-level ozone, the individual SES of residents, and the incidence of T2D in Israel. Based on the existing literature, we hypothesized that exposure to ground-level ozone would positively correlate with the incidence of T2D in the Israeli population. We assumed that this correlation would remain significant also when controlling for the SES. This study represents a pioneering effort to test this hypothesis at the municipal level in Israel, which involved analyzing data that encompassed the majority of the Israeli population. Employing univariate and multivariate linear regression models, this research meticulously accounted for a range of confounding factors to ensure robust and reliable findings. The original results underscore the critical importance of air pollution mitigation as a cornerstone for effective public health management. While additional epidemiological investigations are warranted to further validate these findings, the insights gained from this study provide a valuable foundation for evidence-based policymaking in public health.

2. Materials and Methods

2.1. Data Collection

The Israeli Central Bureau of Statistics (CBS) website [41] provides demographic information on all 280 Israeli cities and municipalities. To ensure sufficient data on T2D, we focused exclusively on municipalities with at least 20,000 residents. The resulting data pool included a total of 81 municipalities (ranging from small towns with a population ≥ 20,000 residents to the largest city with 936,000 residents). The following demographic and health data were collected:

(a)

A city’s 2017 socioeconomic cluster value. This value is determined by using a CBS socioeconomic index, ranging from 1—the lowest socioeconomic ranking to 10—the highest socioeconomic ranking. A municipality’s socioeconomic index includes 14 components related to demography, education, employment, and standard of living. The 14 index components are as follows:

Demography:

1.

Median age.

2.

Dependency ratio (ratio between working-age population (20–64) and dependents (0–19 and 65+)).

3.

Percentage of households with four or more children.

Education:

4.

Average years of schooling (ages 25–54).

5.

Percentage of individuals with an academic degree (ages 27–54).

Employment and Benefits:

6.

Percentage of individuals with income from employment (ages 25–54).

7.

Percentage of women (ages 25–54) with no income from employment.

8.

Percentage of employed individuals earning more than twice the average wage.

9.

Percentage of employed individuals earning below the minimum wage.

10.

Percentage of individuals aged 20+ receiving income support or old-age/survivors’ allowance.

Standard of Living:

11.

Average monthly income per capita.

12.

Average number of privately owned vehicles per 100 residents aged 17+.

13.

Average vehicle license fee (used as an estimate of vehicle value).

14.

Average number of days spent abroad per person.

(b)

Standardized rate of T2D per 1000 people for the entire Israeli population (general population’s T2D rate) between the years 2017 and 2019.

(c)

Standardized rate of T2D patients per 100,000 people aged ≥ 45 (rate of T2D among the adults aged ≥ 45 population) between the years 2017 and 2019.

The T2D data were downloaded from the CBS website [42]. These data were collected from all of Israel’s health maintenance organizations (HMOs), analyzed and summarized by the Israel Center for Disease Control (ICDC), and included patients who met the following criteria: (a) at least one glycated hemoglobin (HbA1c) test result above 6.5% in the past year; (b) purchase of at least three prescriptions for antidiabetic drugs in different months within the past year; and (c) blood glucose levels ≥ 200 mg/dL in two tests conducted at least one month apart in the past year.

A hybrid model, provided by the Israeli Ministry of Environmental Protection (IMoEP) was used to calculate the estimated population exposure to different air pollutants. The model is based on two sources of information: (a) the CHIMERE model [43], which provides hourly forecasts of different air pollutants at a spatial resolution of 3 km (covering the entire area of Israel), and (b) air pollution measurements obtained from an air-quality-monitoring network. We focused on the average ozone concentrations in both 2017 and 2019. Next, the weighted mean of the population ozone exposure was calculated per municipality by extracting the pollutants’ average concentrations in the areas attributed to the municipality in the aforementioned years [41,44]. Raw data on SES, ground ozone level, and diabetes prevalence per municipality can be found in Table S1.

2.2. Statistical Analyses

Since the distribution of ozone levels was non-linear, Spearman’s rank correlation was employed to assess the associations between the ozone levels and T2D morbidity. This non-parametric approach is robust to outliers and makes no assumptions about the normality of the data. To address potential biases related to the ecological fallacy, we performed additional Spearman correlations to evaluate the associations between ozone levels, T2D incidence, and population characteristics (population size and the percentage of young individuals aged 0–17 years), as well as heart disease incidence.

Next, we employed univariate linear regressions to evaluate the effect of the population-weighted ozone exposure with T2D morbidity.

Finally, we employed multivariate linear regressions to evaluate the independent associations of a municipality’s socioeconomic cluster value and the population-weighted ozone exposure with T2D morbidity. This regression analysis allows us to estimate the adjusted effect of ozone exposure on T2D morbidity after accounting for the influence of SES. The multivariate linear regressions formulas were as follows:

$$Y \left(\mathrm{T}2\mathrm{D} \mathrm{m}\mathrm{o}\mathrm{r}\mathrm{b}\mathrm{i}\mathrm{d}\mathrm{i}\mathrm{t}\mathrm{y}\right)={\beta }_0+{\beta }_{1 }\ast \mathrm{s}\mathrm{o}\mathrm{c}\mathrm{i}\mathrm{o}\mathrm{e}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{c} \mathrm{c}\mathrm{l}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{e}\mathrm{r}+{\beta }_2\ast \mathrm{O}\mathrm{z}\mathrm{o}\mathrm{n}\mathrm{e} \mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{l}\mathrm{s}$$

For each model, we calculated the statistical significance, root mean square error (RMSE), R², Cohen’s f² values, and the coefficient/p-value of each parameter. Additionally, to understand the relative contribution of each parameter (in the multivariate linear regressions), independent variables were normalized using min–max normalization.

All statistical analyses were performed using Python (version 3.9.13).

3. Results

This study examined the associations between the chronic exposure of a population to ground-level ozone, its SES (based on The Israeli CBS socioeconomic cluster index), and the incidence of T2D in Israel. The ozone concentrations in 2017 ranged between 55.8 and 95.9 µg/m³ (standard deviation (sd) of 9.02 µg/m³) and in 2019 between 57.1 and 94.8 µg/m³ (sd = 7.9 µg/m³).

The Spearman correlation analysis revealed positive correlations between the exposure to ozone and the T2D morbidity in 2017 and 2019: in 2017, the ozone and general population T2D rate (r = 0.4)/adults aged ≥ 45 years T2D rate (r = 0.43), and in 2019, the ozone and general population T2D rate (r = 0.41)/adults aged ≥ 45 years T2D rate (r = 0.4) (all p-values < 0.001) (Figure 1).

The additional correlations examined to rule out potential bias revealed no significant associations between T2D incidence and population variables (population size and the percentage of young individuals aged 0–17 years). However, a moderate statistically significant correlation was observed between T2D incidence and heart disease incidence (r = 0.51, p < 0.0001 for the general population; r = 0.68, p < 0.0001 for adults aged ≥ 45 years). This finding aligns with the well-established relationship between heart disease and diabetes, as extensively discussed in the literature [45].

Similarly, no significant correlations were identified between the ozone levels and the aforementioned population variables. However, mild but statistically significant correlations were observed between ozone levels and heart disease incidence (r = 0.39, p = 0.002 for 2017; r = 0.28, p = 0.01 for 2019). These correlations may have stemmed from the significant association between ozone exposure and heart disease, as shown here.

Univariate linear regressions further emphasized the positive effect of exposure to ozone on T2D morbidity in both years and both analyzed populations. All linear regression models were statistically significant, with the root mean square error (RMSE) being smaller than the morbidity standard deviations (

Table 1. Univariate linear regressions to predict T2D morbidity based on exposure to average concentrations of ground-level ozone in 2017 and 2019.

Exposure to Ozone in	Population	Model p-Value	Intercept Beta (p)	Ozone Beta (p)	R2	RMSE	Standard Deviation
2017	General population	<0.01	15.40 (0.32)	0.67 (<0.01)	0.11	17.3	18.2
2017	Adults (ages ≥ 45)	<0.01	−18.97 (0.63)	1.73 (<0.01)	0.11	44.2	46.7
2019	General population	<0.01	6.53 (0.71)	0.79 (<0.01)	0.12	17.2	18.2
2019	Adults (ages ≥ 45)	<0.01	−25.10 (0.58)	1.77 (<0.01)	0.08	44.7	46.7

).

Multivariate linear regressions revealed that the socioeconomic cluster had a negative effect on the T2D morbidity (higher socioeconomic clusters significantly correlated with the lower T2D incidence), while the exposure to ozone had a positive effect (populations with higher exposure had higher T2D incidence) in all the tested models. All multivariate linear regression models were statistically significant, with the root mean square error (RMSE) smaller than the morbidity standard deviations. Cohen’s f² values (0.61 to 1.23) show very large effect sizes of the predictors (

Table 2. Multivariate linear regressions to predict T2D morbidity based on socioeconomic cluster and exposure to average concentrations of ground-level ozone in 2017 and 2019.

Exposure to Ozone in	Population	Model p-Value	Intercept Beta (p)	Socioeconomic Cluster Beta (p)	Ozone Beta (p)	R2 (f2)	RMSE	Standard Deviation
2017	General population	<0.01	88.2 (<0.01)	−48.0 (<0.01)	1.05 (0.87)	0.55 (1.23)	12.4	18.2
2017	Adults (ages ≥ 45)	<0.01	148.5 (<0.01)	−97.2 (<0.01)	16.6 (0.45)	0.39 (0.64)	37.0	46.7
2019	General population	<0.01	88.4 (<0.01)	−48.1 (<0.01)	0.69 (0.93)	0.55 (1.23)	12.4	18.2
2019	Adults (ages ≥ 45)	<0.01	154.1 (<0.01)	−100.8 (<0.01)	6.65 (0.76)	0.38 (0.61)	37.2	46.7

). Of note, linear regressions utilized to predict T2D morbidity based exclusively on socioeconomic cluster (without the variable of exposure to ozone) resulted in models with higher p-values, emphasizing the statistically significant contribution that the ozone exposure had on morbidity (Figure 2).

4. Discussion

4.1. Associations Between the Ozone Concentrations and the Incidence of Type 2 Diabetes

The association between exposure to various air pollutants and the incidence of T2D has been reported in the literature. For example, in 2018, Alderete and his colleagues showed that increased exposure to air pollutants, such as particulate matter (PM) and nitrogen dioxide (NO₂), contributed to metabolic dysfunction and T2D etiology [46]. Additionally, a borderline significant association between long-term exposure to traffic-related air pollution and confirmed cases of diabetes, particularly in nonsmokers and physically active individuals, was previously reported [47]. Recently, it was shown that exposure to NO₂, SO₂, CO, and ozone significantly increase diabetes-related hospitalizations, especially among women and older adults [48].

In this study, we observed a significant positive correlation between exposure to ground-level ozone and the incidence of T2D in the Israeli population (Figure 1). Exposure to ground-level ozone also contributed to the multivariable models’ predictions of T2D morbidity, primarily in adults aged 45 and above. These results align with findings that older individuals are more vulnerable due to age-related declines in pulmonary and immune function, which may amplify ozone’s systemic effects [6]. Previous studies conducted in Israel have reported high ozone levels that are regularly measured during the summer months, across both inland and mountainous regions. Back trajectory analysis of air masses responsible for these elevated levels elucidated that the ozone precursors originated from the industry and transportation emissions at the densely populated Israeli coastline [41,49], unlike much larger countries, where ozone hotspots are often localized around megacities [7]. The positive correlation between ozone exposure and T2D morbidity (Figure 1), and the positive effect found in the univariate and multivariate linear regressions (Table 1 and Table 2), align with previous findings in the literature, which highlight the health risks associated with ozone exposure [16,17,18,19,21,22,23,24]. These previous findings provided initial support for a positive association between long-term exposure to ozone and the incidence of T2D. This association has been observed across various regions, ethnicities and age groups, including African American women in the US, adults in China, residents of North Africa and the Middle East, as well as in a recently publish meta-analysis [13,18,19,21,22]. Furthermore, a similar impact was reported among Taiwanese adults aged 30 to 50 years old, where for every 3.3 ppb increase in ozone, the hazard ratio (HR) for the incidence of T2D was 1.093 (An HR greater than 1 indicates an increased risk). In this case, a 3.3 ppb rise in ozone was associated with a 9.3% increased risk of T2D [50].

Although associations between ozone exposure and T2D incidence can be found in different regions and countries around the globe, Israel’s arid climate and high solar radiation accelerate photochemical ozone formation, potentially intensifying ozone metabolic disruptions compared with temperate regions [41,49]. In Israel, as reported in the results section, ozone concentrations in 2017 and 2019 were between 55.8 and 95.9 µg/m³ and between 57.1 and 94.8 µg/m³, respectively. The Israeli environmental threshold for ozone exposure (8 h average) is higher than the EU, USA, and WHO thresholds, with 140 µg/m³ compared with 120, 138, and 100 µg/m³, respectively [40]. Additionally, differences in the ozone-monitoring density, urban spatial structure, and population demographics between Israel and other countries may contribute to the observed heterogeneity. For example, Israel’s relatively high density of air quality monitors and its urban planning patterns may reduce exposure misclassification compared with studies in larger, less densely monitored countries. All in all, regional differences in climate, urbanization, regulatory frameworks, and social structure must be considered when interpreting and comparing findings across studies.

The current study extended the body of knowledge by demonstrating the effects of ground-level ozone on the incidence of T2D in a unique demographic context—the Israeli population—and reinforced the notion that ozone is a critical environmental health hazard. Future research should prioritize longitudinal studies to clarify the dose–response relationship and evaluate mitigation strategies.

4.2. Type 2 Diabetes, Ground-Level Ozone Exposure, Socioeconomic Status, and Environmental Health Policy Recommendations

Our study, encompassing for the first time the entire Israeli urban population (population in municipalities ≥ 20,000 residents), corroborates prior evidence linking chronic ozone exposure and T2D, and emphasizes these associations in the uniquely heterogeneous Israeli population. Given the ecological nature of our study and the restricted literature evidence on a global population scale, further studies targeting diverse population groups (race, age, SES, health background etc.) are necessary to validate this link.

Our findings, when multivariate linear regressions revealed that lower socioeconomic clusters had higher T2D morbidity levels (Table 2 and Figure 2), also contribute to the understanding of the intersection between environmental health and SES. While SES is a significant determinant of health outcomes, as evidenced by its influence on T2D prevalence, our findings suggest that environmental factors, such as ground-level ozone exposure, are independently potent determinants of health. This highlights the importance of considering both socioeconomic and environmental factors in public health strategies, as was established by previous research on air pollution, SES, and other morbidities [34,51,52,53].

A holistic strategy for air pollution mitigation and public health enhancement is urgently needed. This strategy should include the following steps: reducing NOx and VOCs emissions from industrial and transport activities; reducing transport emissions by stricter vehicle emission regulations, incentives for low-emission technologies, and the promotion of electric vehicles; reducing industrial emissions by the adoption of cleaner best available technologies (BATs), as supported by regulatory policies enforcing stricter emission limits and control systems; transitioning to renewable energy can further mitigate emissions, with governments investing in renewable infrastructure and offering tax incentives or subsidies to accelerate adoption; implementing municipal low-emission zones, restricting traffic during high-ozone periods, promoting public transportation, and increasing urban green spaces to reduce ozone levels while enhancing citizen well-being; continuous monitoring through ground-based and satellite technology is essential for understanding ozone dynamics and assessing the effectiveness of policies; public education campaigns are crucial to raise awareness about relevant risks and encourage informed actions, such as using air quality apps or indoor air purifiers.

As a low SES may induce higher exposure levels due to residents living in close vicinity to industrial centers, main congested roads, or in poorly ventilated indoor environments [6], special care should be provided to protecting these weakened populations, focusing especially on young children, the elderly, and pregnant women.

This study analyzed data from 81 municipalities, representing the majority of Israel’s population. Given Israel’s compact geographical area and its long borders with five neighboring countries, international collaboration is crucial to address the transboundary movement of ozone precursors. Such cooperation can facilitate the development of shared strategies to effectively reduce the emissions of NOx and VOCs.

4.3. Research Strengths and Limitations and Policy Implications

Our findings suggest the need for stricter air quality regulations and targeted public health interventions, especially in areas with high ozone levels. Reducing ambient ozone pollution could be a crucial step in mitigating the burden of T2D, particularly in vulnerable populations. This goal could be achieved by addressing the above environmental health policy recommendations.

Overall, our findings align with the limited recent literature, which primarily focuses on regional or ethnic group scales. This study’s strengths included (a) the novel focus on all Israeli municipalities with ≥20,000 residents, comprising the majority (78%) of the highly ethnically and culturally diverse Israeli population; (b) the usage of the highly reliable databases of the Israeli CBS including health, socioeconomic, and demographic data, as well as the IMoEP air pollution exposure data for this study’s statistical analyses; and (c) the robustness of the results, as reflected by employing various statistical tools that all yielded consistent findings (Figure 1 and Figure 2).

This study, while robust and comprehensive, was not without limitations: (a) Given its ecological nature, this study pointed out correlations between T2D incidence and air pollution levels without indicating causation, for which further epidemiological research is needed. (b) The reliance on available data from specific years may not fully capture the dynamic relationship between ozone exposure and T2D incidence. Additionally, due to the unavailability of data at the municipal level, certain potential confounding factors—such as body mass index (BMI), smoking habits, dietary patterns, and levels of physical activity—could not be accounted for or analyzed in this study. Moreover, the T2D data lacked important details, such as sex and disaggregation into additional age groups, which limited the ability to conduct a more refined stratified analyses. Consequently, further epidemiological research is necessary to address these parameters and provide a more comprehensive understanding of the findings. (c) Since residents do not always spend their entire day in their city of residence, there might be some discrepancies between the actual air pollution exposure and the calculated exposure attributed to specific municipality residents. However, since the COVID-19 crisis and due to increasing global temperatures, an increasing number of people are working indoors or from home in air-conditioned environments; the extent to which this trend may have influenced our results remains uncertain. (d) Focusing on municipalities with ≥20,000 residents in Israel resulted in 81 municipalities. This relatively small sample size (n = 81) posed challenges to the statistical performance, which imposed constraints that limited the depth of this research investigation. (e) Variations in the SES within urban areas, specifically at the intra-municipal resolution, were not accounted for in this study due to the lack of access to high-resolution SES data. Consequently, the analysis could not be conducted at a finer spatial resolution.

Future research could benefit from a longitudinal approach, assessing changes over time and using a higher spatial resolution, or performing the analysis on individuals rather than municipalities. Additionally, exploring the specific mechanisms by which ozone contributes to diabetes development in humans could further elucidate this complex relationship and assist the scientific community to present policy makers research-based solutions for long-term air pollution, and more specifically, for ozone exposures. Following the anticipated implementation of a comprehensive policy for air pollution reduction, future research should also assist in monitoring and assessing the effectiveness of ozone reduction strategies in lowering T2D morbidity levels.

5. Conclusions

This study elucidated the complex interplay between chronic exposure to ground-level ozone, SES, and the incidence of T2D in Israel. Our major finding indicates a positive correlation between the chronic ozone exposure and the T2D morbidity, both in the general population and in adults aged ≥ 45 years old, residing in 81 municipalities (≥20,000 residents), even after controlling for SES. Multivariate linear regressions revealed that higher socioeconomic cluster (1 low–10 high) had a negative effect on T2D morbidity, while higher ozone chronic exposure had a positive effect on T2D morbidity. These findings indicate that ozone exposure may be a significant environmental risk factor for T2D, with potentially greater effects on populations with lower SES. Special care should be taken to protect these vulnerable population groups, focusing especially on young children, the elderly, and pregnant women. These findings underscore the vital need for integrating air quality management into T2D prevention strategies and addressing environmental health disparities through comprehensive municipal-, state-, and international-level public health policies. Future research should prioritize clarifying the biological mechanisms underlying this association, utilize higher-resolution data, and assess the effectiveness of holistic ozone reduction policies in mitigating T2D-associated morbidity.