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Article

Climate Change Anxiety Among Individuals with and Without Chronic Illnesses: The Roles of Exposure, Awareness, and Coping Strategies

by
Yaira Hamama-Raz
1,* and
Shiri Shinan-Altman
2
1
School of Social Work, Ariel University, Ariel 40700, Israel
2
The Louis and Gabi Weisfeld School of Social Work, Bar-Ilan University, Ramat Gan 5290002, Israel
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(13), 6034; https://doi.org/10.3390/su17136034
Submission received: 29 May 2025 / Revised: 27 June 2025 / Accepted: 30 June 2025 / Published: 1 July 2025
(This article belongs to the Special Issue Climate Change, Biodiversity and Sustainability)
Review Reports Versions Notes

Abstract

Climate change poses a significant threat to individuals with chronic illnesses, yet research on the psychological effects of climate change among this population remains scarce. This study’s aim was to compare levels of climate change anxiety among individuals without chronic illnesses, with cardiovascular disease, and with respiratory disease, and to examine the roles of exposure, awareness, and coping strategies in predicting anxiety. A cross-sectional survey was conducted among 522 Israeli adults recruited from a national online panel, including groups with and without chronic illnesses. Participants completed self-report questionnaires assessing climate change exposure, awareness, coping strategies, and anxiety. Analyses revealed that individuals with cardiovascular disease reported higher levels of climate change anxiety than those without a chronic illness or with respiratory disease. Across groups, greater climate change exposure and greater use of problem-focused coping were associated with higher climate change anxiety, whereas meaning-focused coping and awareness were not significant predictors. Additionally, climate change exposure predicted anxiety only among participants with respiratory disease. These findings underscore the differential psychological impact of climate change based on health status, highlighting the need for targeted interventions to address climate change anxiety among vulnerable populations.

1. Introduction

Climate change poses a growing threat to public health, not only through its direct environmental consequences—such as extreme heat, air pollution, and natural disasters—but also through its disproportionate impact on individuals living with chronic illnesses [1]. Among those most at risk are individuals with cardiovascular and respiratory conditions, whose underlying health vulnerabilities increase their sensitivity to climate-related stressors [2,3,4,5]. Exposure to elevated temperatures, poor air quality, and unpredictable weather patterns can exacerbate symptoms, raise hospitalization rates, and elevate mortality risk among these populations [6].
Although the physical health consequences of climate change have been widely studied, less attention has been paid to its psychological effects, particularly among individuals with chronic illnesses. One emerging construct is climate change anxiety, defined as persistent worry about the harmful consequences of climate change, often accompanied by helplessness, fear, or frustration [7,8]. Research on this topic remains limited among vulnerable populations. A notable exception is a recent multi-national study that assessed climate change anxiety in 1266 individuals with asthma across four Arab countries [9]. Findings indicated that climate change anxiety was more prevalent among middle-aged participants, those with longer disease duration, and individuals with prior hospitalizations. However, Atta and colleagues’ study [9] focused only on respiratory disease and did not compare subgroups or examine contributing psychosocial mechanisms. This lack underscores the need to investigate how different types of chronic illnesses, such as cardiovascular versus respiratory conditions, may be uniquely associated with climate change anxiety and to explore the role of psychological and contextual factors, such as perceived exposure, climate change awareness, and coping strategies, in shaping these emotional responses.
Broader research has shown that climate change anxiety is positively associated with both direct exposure to extreme weather events such as heatwaves, floods, or air pollution, and indirect exposure, including media coverage and awareness of climate-related risks [10,11]. In particular, individuals with greater climate change awareness often report higher anxiety, especially when they perceive limited personal control or coping capacity [12,13,14]. These effects may be stronger among people with chronic illnesses, who face a dual burden of heightened environmental vulnerability and perceived threat [15]. As Cianconi and colleagues [16] emphasized, climate change affects psychological functioning through both acute and chronic stress mechanisms and disproportionately impacts populations with pre-existing vulnerabilities, including medical and socioeconomic disadvantages.
To understand emotional responses to climate threats, it is important to consider individual coping processes. In this study, we adopted the transactional model of stress and coping developed by Lazarus and Folkman [17], which conceptualizes stress as a dynamic interaction between person and environment. According to this framework, individuals engage in primary appraisal (assessing threat or harm) and secondary appraisal (evaluating their coping resources). Stressful experiences arise when perceived demands exceed available coping capacities, triggering various coping efforts, both cognitive and behavioral [17].
Importantly, the impact of these coping mechanisms is complex and sometimes paradoxical. Problem-focused and meaning-focused coping have both been linked to greater emotional distress among general populations [18,19,20], whereas de-emphasizing (i.e., de-emphasizing the seriousness of climate change) coping has been associated with lower climate-related worry, particularly among adolescents [21]. However, it remains unclear how these coping responses operate among individuals with chronic illnesses, particularly those with cardiovascular or respiratory conditions, who may experience unique appraisals and constraints. According to Van Susteren and Al-Delaimy [22], psychological responses to climate change, including anxiety, grief, and trauma, require deeper exploration in clinical contexts, especially among vulnerable patients already facing chronic stressors due to long-term health conditions.
Taken together, despite increased scholarly interest in climate change anxiety, little research has examined how different chronic illness groups emotionally respond to climate threats. These populations not only face heightened physiological risk but also greater psychological vulnerability due to increased exposure and their perceived vulnerability [23]. Moreover, integrative reviews have stressed the need to better understand the psychological consequences of climate change across diverse populations, especially those with fewer psychological or medical resources to cope [16]. To the best of our knowledge, no prior study has systematically compared individuals with different types of chronic illness in relation to climate change anxiety, nor examined how psychological factors such as exposure, awareness, and coping may differentially predict anxiety across these groups.
To address these gaps, we had the following three primary aims: (1) to compare levels of climate change anxiety among individuals without chronic illnesses, individuals with cardiovascular disease, and individuals with respiratory disease; (2) to examine whether exposure, awareness, and coping strategies predicted climate change anxiety; and (3) to explore whether these predictors interacted with health status by testing group-by-variable interactions in regression analyses.
Based on the literature, we proposed the following hypotheses:
H1. 
Individuals with chronic illness (cardiovascular or respiratory) would report higher levels of climate change anxiety than those without chronic illness.
H2. 
Individuals with respiratory disease would report higher levels of climate change anxiety than individuals with cardiovascular disease, due to the more immediate impacts of air pollution and heat [2].
H3. 
Across all groups, higher climate change awareness, greater exposure, and more frequent use of problem-focused and meaning-focused coping would be associated with higher climate change anxiety, whereas greater use of de-emphasizing coping would be associated with lower anxiety.

2. Materials and Methods

2.1. Participants and Procedure

The current study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational research. Data were collected through a large, probability-based Israeli online panel consisting of over 100,000 members [24]. This panel comprises adults between the ages of 18 and 85 who have agreed to participate in survey-based research. Recruitment into the panel is ongoing and employs diverse online strategies to ensure broad representation. The panel provider, iPanel, complies with rigorous ethical and methodological standards as outlined by the World Association for Market, Social, and Opinion Research (ESOMAR). Data were collected during the winter of February 2025. Eligibility criteria specified that participants should be aged 18 or over, fluent in Hebrew, and able to give informed consent for this study. This study was approved by the first author’s university’s institutional review board (IRB; approval No. 20241226).
Sample size was calculated using G*Power 3.1 [25]. For an analysis of covariance (ANCOVA) with three groups and several covariates with a moderate–low effect size f = 0.15, α = 0.05, and power = 0.80, the minimum required sample size would be N = 432 participants. This sample size provides a power level of 0.99 for a regression analysis with moderate–low effect size f2 = 0.10, α = 0.05, and up to 20 predictors. We ensured more than sufficient statistical power with a final sample of 522 participants, including 277 participants who reported not having a chronic illness (53.1%), 133 who were diagnosed with a respiratory disease (25.5%), and 112 who were diagnosed with cardiovascular disease (21.5%). Table 1 presents the demographic characteristics of the total sample and the three study groups. About half of the participants were men (51.1%), and about half were women (48.9%), with an average age of about 50 years. About 72% of them were married or in a relationship, and about three-fourths of them had children (77.2%). Participants had about 15 years of education on average, and approximately three-fourths of the participants were employed (76.8%), with income levels ranging from below average (35.5%) to above average (36.7%). About half of the participants were secular (52.5%), and most of the others were traditional (30.5%). To assess the representativeness of our sample, we compared key demographic characteristics (e.g., gender, age, education, employment, and religiosity) with national population data provided by Israel’s Central Bureau of Statistics [26]. As shown in Supplementary Table S1, our sample closely approximated national distributions on several indicators, though some variation was expected due to the online recruitment format and study eligibility criteria.
In reference to group differences, our analysis yielded significant group differences. Whereas no demographic differences were found between those with a respiratory condition and those without a chronic illness, participants diagnosed with cardiovascular disease were more likely to be men and older than the others. Additionally, a higher percentage of them were married or widowed than in the other two groups, had more children, and were less likely to be employed.

2.2. Measurements

Participants responded to a series of self-report instruments designed to assess sociodemographic characteristics; climate change exposure, awareness, and coping strategies; and climate change anxiety.
Demographic Data: Participants provided details on their gender, age (in years), type of residence (urban vs. rural), marital status (married, divorced, widowed, or single), number of children, total years of formal education, current employment status (full-time, part-time, self-employed, unemployed, retired, or stay-at-home parent), and level of religiosity (secular, traditional, or religious).
Health information included having a chronic disease (yes/no, and if “yes”, indicating which disease, i.e., respiratory, cardiovascular, or other).
Climate Change Exposure: Climate change exposure was assessed using a set of seven binary (yes/no) items developed by the authors, referencing participants’ exposure over the past year to common climate change-related phenomena in Israel. These included extreme heat waves, severe flooding, prolonged drought, sand and dust storms, intense rain and thunderstorms, wildfires or vegetation fires due to hot and dry conditions, and sudden or extreme temperature shifts (e.g., large swings between hot and cold days). The total summary score was calculated.
Climate Change Awareness: Climate change awareness was measured using the Climate Change Awareness (CCA) scale [27], comprising 13 items rated on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). An example item was “I am aware that floods will occur if world temperatures increase.” Higher average scores reflect greater awareness. The internal consistency of the original scale was α = 0.88 [27]; in the present study, Cronbach’s alpha was 0.90.
Climate Change Coping Strategies: Climate change coping was measured using Ojala’s [28] 15-item instrument, which assesses three distinct coping styles: problem-focused coping (three items, e.g., “I think about what I myself can do”), meaning-focused coping (six items, e.g., “I have faith in people engaged in environmental organizations”), and de-emphasizing climate change’s seriousness (six items, e.g., “I can’t be bothered to care about climate change”). Participants responded using a 5-point Likert scale ranging from 1 (not true at all) to 5 (completely true). Mean scores were calculated for each coping strategy. Reported internal consistency values in the original study were as follows: α = 0.76 (problem-focused), α = 0.76 (meaning-focused), and α = 0.75 (de-emphasizing). In the present study, internal consistency values were as follows: α = 0.80 (problem-focused), α = 0.66 (meaning-focused), and α = 0.72 (de-emphasizing).
Climate Change Anxiety: The 13-item Climate Change Anxiety Scale (CCAS) [7] was used to assess climate change anxiety. Items were rated on a scale from 1 (never) to 5 (almost always). A sample item was “Thinking about climate change makes it difficult for me to concentrate.” Higher scores indicate greater levels of climate-related anxiety. Internal consistency values were α = 0.87 in the original study and α = 0.93 in the current sample.

2.3. Statistical Analyses

Data were analyzed with SPSS version 29. Descriptive statistics were used for participants’ demographic and background characteristics, by group, and compared with chi-square analyses and Z tests for the comparison of independent proportions. Cronbach’s α was calculated for internal consistency. Climate change exposure was positively skewed (skewness = 0.76, SE = 0.11), as was climate change anxiety (skewness = 2.16, SE = 0.11). Both were logarithmically transformed. Associations between the background variables and the study variables were analyzed with Pearson correlations and t-tests to identify the variables that should be controlled for when assessing the study hypotheses. Group differences in the study variables were analyzed with ANCOVAs, controlling for gender, age, and years of education. Significant differences were interpreted with estimated marginal means. Next, Pearson correlations were calculated between the study variables, and a multiple linear regression was calculated for climate change anxiety. In order to assess fulfillment of basic assumptions of variable independence in the regression model, collinearity was examined via variance inflation factor (VIF) and the related condition index. A highly correlated independent variable was removed to avoid erroneous results that were due to collinearity and did not represent correct outcomes. Next, to assess the unique contributions of the study variables to climate change anxiety by group, the interactions between group and the study variables were entered as a final step in the regression analysis, using Hayes’ PROCESS procedure [29], model No. 1. In this model, variables were standardized, 5000 bootstrap samples were used, and 95% confidence intervals were defined. Significant interactions were interpreted with simple slopes.

3. Results

3.1. Descriptive Results

Most participants with a chronic illness reported generally good health (n = 159, 64.9%), with the rest reporting either bad or not so good health (n = 45, 18.4%) or excellent health (n = 41, 16.7%), and there were no meaningful group differences (χ2(2) = 5.98, p = 0.050). Participants reported having their chronic illness for a total average of 19.43 years (SD = 14.88, range 1–70), with a longer average period being reported by those with a respiratory condition (M = 21.98, SD = 15.76) than by those with cardiovascular disease (M = 16.46, SD = 13.24) (Z = 2.72, p = 0.007). Almost all participants with cardiovascular disease received medication (n = 106, 94.6%), compared with about 39.1% (n = 52) of those with a respiratory condition (Z = 9.05, p < 0.001).

3.2. Group Differences

Prior to assessing group differences in the study variables, according to the first two hypotheses, their associations with the study variables were examined. Gender was associated with de-emphasizing the seriousness of climate change, such that male participants reported using these strategies (mean = 2.37, SD = 0.65) more than did female participants (mean = 2.23, SD = 0.62) (t(520) = 2.43, p = 0.015, d = 0.21). Age was negatively associated with exposure (r = −0.13, p = 0.003) and positively associated with awareness (r = 0.13, p = 0.003), problem-focused coping (r = 0.15, p < 0.001), meaning-focused coping (r = 0.15, p < 0.001), and climate change anxiety (r = 0.15, p < 0.001). Years of education were positively associated with exposure (r = 0.11, p = 0.012) and negatively associated with meaning-focused coping (r = −0.13, p = 0.003). To a small extent, years of education were negatively associated with climate change anxiety as well (r = −0.09, p = 0.040). Employment status had low variance (77% were employed) and was highly associated with age (p < 0.001), as most unemployed participants were older retired adults in the cardiovascular disease group. Other demographic variables had low variance as well or were not meaningfully associated with the study variables. In light of these associations, group differences in the study variables were examined while controlling for gender, age, and years of education. Employment status was not controlled for to avoid collinearity (VIF = 1.77).
To assess the first two hypotheses, Table 2 presents group differences in the study variables.
Results showed significant group differences for climate change anxiety, where participants with cardiovascular disease reported higher anxiety than participants with either a respiratory disease (p = 0.013) or without a chronic illness (p < 0.001). Reported climate change exposure was higher among participants with a respiratory disease than among participants with either cardiovascular disease (p = 0.028) or without a chronic illness (p = 0.003). Further, meaning-focused coping was higher among participants with cardiovascular disease or without a chronic illness than among participants with a respiratory disease (p = 0.001 and p = 0.004, respectively). No significant differences were found for climate change awareness, problem-focused coping strategies, or de-emphasizing the seriousness of climate change. Thus, the first study hypothesis, in which we claimed that individuals with a chronic illness (cardiovascular or respiratory) would report higher levels of climate change anxiety than those without a chronic illness, was partly supported. Participants with cardiovascular disease reported higher climate change anxiety than participants without a chronic illness, yet no difference was found for participants with a respiratory disease. The second study hypothesis, in which we claimed that individuals with a respiratory disease would report higher climate change anxiety than individuals with cardiovascular disease, was not supported. The opposite was found—participants with cardiovascular disease reported higher anxiety than participants with a respiratory disease. Similar results were found for climate change anxiety when controlling for exposure. Further, similar results were found when considering gender and age as concurrent characteristics of the cardiovascular disease and controlling for years of education only.

3.3. Associations with Climate Change Anxiety

Prior to assessing the third study hypothesis, Pearson correlations between the study variables can be seen in Table 3. Higher climate change exposure, higher climate change awareness, a greater use of problem-focused and meaning-focused coping strategies, and a lesser use of de-emphasizing the seriousness of climate change were associated with higher climate change anxiety. In addition, higher climate change exposure was associated with higher climate change awareness, a greater use of problem-focused coping strategies, and a lesser use of de-emphasizing the seriousness of climate change. Higher climate change awareness was associated with a greater use of problem-focused and meaning-focused coping strategies and a lesser use of de-emphasizing the seriousness of climate change.
It should be noted that de-emphasizing the seriousness of climate change was rather highly associated with climate change awareness (r = −0.58, p < 0.001). Indeed, both variables had rather high VIF values in a regression model (de-emphasizing VIF = 1.66, awareness VIF = 1.93), and a high condition index (index = 36.66) was found, indicating possible collinearity. Further, the negative association between de-emphasizing and climate change anxiety in the correlation matrix turned positive in the regression model (β = 0.09, p = 0.050), suggesting a suppressor variable. In order to verify the suppressor variable, another regression model was calculated showing that the contribution of “de-emphasizing coping” to climate change anxiety, beyond group, gender, age, and years of education, was indeed negative (β = −0.13, p = 0.002). Thus, de-emphasizing the seriousness of climate change was excluded from further analyses.
To assess the contribution of the study variables to climate change anxiety, in accordance with the third hypothesis, a multiple linear regression was calculated. The group was defined with effect coding as two variables, and gender, age, and years of education were controlled for. The results, shown in Table 4, reveal that 33% of the variance in climate change anxiety was explained in the model. Beyond group, gender, age, and years of education, greater climate change exposure and greater use of problem-focused strategies were associated with higher climate change anxiety. Climate change awareness and meaning-focused coping were not associated with climate change anxiety. Similar results were found when considering gender and age as concurrent characteristics of the cardiovascular disease and controlling for years of education only.
Thus, the third study hypothesis was partly supported: Namely, it was supported for climate change exposure and the use of problem-focused strategies but was not supported for climate change awareness or meaning-focused coping.
Finally, in order to assess the unique contributions of exposure, awareness, and coping strategies to climate change anxiety by group, the interactions between group and the study variables were entered as a final step in the regression analysis. These interactions were calculated using Hayes’ PROCESS procedure [28], model No. 1. Of all the interactions, the one between group and climate change exposure was significant, F(2, 510) = 3.04, p = 0.049. Its interpretation revealed a significant positive association between exposure and anxiety among participants with a respiratory condition (effect = 0.03, SE = 0.01, p = 0.008, 95%CI = 0.01, 0.05) and non-significant associations among participants with cardiovascular disease (effect = −0.01, SE = 0.01, p = 0.386, 95%CI = −0.03, 0.01) or without a chronic illness (effect = 0.01, SE = 0.01, p = 0.159, 95%CI = −0.01, 0.02). That is, higher exposure was associated with higher anxiety among participants with respiratory conditions, and no similar associations were detected for the other participants.

4. Discussion

The aim of the present study was to examine the psychological impact of climate change on individuals with chronic cardiovascular and respiratory conditions, as well as on those without a chronic illness, focusing on climate change anxiety and its predictors—exposure, awareness, and coping strategies. Despite the extensive documentation of physical health risks associated with climate change, its psychological effects on vulnerable populations remain underexplored, particularly regarding how coping mechanisms influence anxiety responses to environmental stressors [2,3]. The current study addressed this gap by assessing group-specific predictors of climate change anxiety, thus contributing to targeted intervention strategies for at-risk populations.
Our main findings indicate that cardiovascular disease is a salient factor in climate change anxiety, with participants in this group reporting heightened distress compared to those without a chronic illness or those with a respiratory condition. The unpredictable, episodic, and acute nature of cardiovascular events, such as heart attacks and strokes [30], can create a persistent sense of vulnerability and may intensify anticipatory anxiety (wherein individuals not only fear the immediate health impacts but also the long-term, cumulative effects of repeated exposure to climate-related stressors [16]), fostering hypervigilance to environmental triggers. This notion aligns with Lazarus and Folkman’s [17] model, which posits that perceived threat and lack of control are key determinants of psychological distress. In the context of cardiovascular disease, this model helps explain how individuals’ heightened sense of vulnerability to sudden, life-threatening events can perpetuate a cycle of anxiety and constant health monitoring. Although studies have indeed shown that even brief exposure to elevated temperatures or air pollution can significantly increase cardiovascular morbidity and mortality, underscoring the tangible health risks associated with climate change [5], this cohort’s sense of helplessness and lack of control seem to reinforce their state of constant alertness [31].
In contrast, respiratory conditions, despite being directly impacted by air quality and temperature fluctuations [32], did not elicit the same level of climate change anxiety. This discrepancy may stem from the chronic and more manageable nature of respiratory conditions [33,34], such as asthma and chronic obstructive pulmonary disease (COPD). Although these conditions are certainly sensitive to environmental factors, they are typically perceived as predictable and controllable through established management strategies, including medication adherence, indoor air quality management, and avoidance of high-exposure activities [1]. Additionally, individuals with respiratory conditions may have developed a sense of resilience through repeated exposure to respiratory triggers, fostering adaptive coping mechanisms that mitigate acute anxiety responses [35]. This perceived sense of control may act as a psychological buffer, reducing the likelihood of excessive worry even when individuals are confronted with severe weather or air pollution warnings. Nevertheless, the cumulative impact of long-term exposure to environmental pollutants can still pose a significant threat to respiratory health, potentially eroding coping resources over time and leading to increased vulnerability to chronic stress and anxiety [36].
In reference to climate change anxiety predictors, climate change exposure emerged as a significant predictor of climate change anxiety. This association underscores the potent psychological impact of direct encounters with extreme weather events, air pollution, and other environmental hazards, which may serve as continual reminders of escalating climate threats [37]. For individuals already managing chronic health conditions, such exposure may exacerbate feelings of vulnerability, as each environmental event not only threatens physical health but also serves as a tangible manifestation of climate change’s growing intensity. The cumulative nature of these stressors may further contribute to a sense of loss of control, as repeated exposure to unpredictable and severe environmental conditions can gradually erode coping resources, fostering a state of chronic hypervigilance and anticipatory anxiety [38].
Interestingly, the use of problem-focused coping strategies was also associated with heightened climate change anxiety, suggesting a potential paradox in how individuals attempt to manage climate-related threats. Typically conceptualized as an adaptive strategy involving active efforts to mitigate or eliminate stressors, problem-focused coping may inadvertently intensify distress when the perceived threat is vast, complex, and largely uncontrollable, as is the case with climate change [8,18]. This phenomenon may be particularly true for individuals with chronic illnesses, who already face limited personal resources and heightened vulnerability. When attempts to actively solve or control an overwhelming problem such as climate change prove ineffective, feelings of frustration, inadequacy, or failure can be exacerbated, thereby reinforcing anxiety rather than alleviating it. For cardiovascular patients, the emphasis on monitoring environmental conditions to prevent health crises may lead, as stated, to a state of hypervigilance, where each weather fluctuation or air quality alert is interpreted as a potential precursor to a severe health event. Similarly, respiratory patients who engage in constant monitoring of air quality indices may find themselves overwhelmed by the persistent perception of imminent danger, further entrenching a cycle of anxiety and threat sensitivity [5,39].
Contrary to expectations, neither climate change awareness nor meaning-focused coping was significantly associated with climate change anxiety, a finding that challenges conventional assumptions regarding the protective value of cognitive reframing and adaptive meaning-making. The lack of a significant relationship between awareness and anxiety may suggest that, in the context of chronic health conditions, mere knowledge of climate risks is insufficient to mitigate psychological distress. Instead, the pervasive and often uncontrollable nature of climate-related stressors may diminish the efficacy of cognitive coping strategies, as individuals struggle to reconcile their awareness of environmental threats with their limited capacity to prevent or mitigate such threats [18,40]. Additionally, the ineffectiveness of meaning-focused coping in reducing anxiety may indicate that attempts to find purpose or reinterpret climate threats are less relevant for those whose primary concern is the immediate and tangible risk to their health. For these individuals, the focus may shift from abstract meaning-making to urgent, problem-focused efforts aimed at immediate threat reduction. Moreover, meaning-focused strategies may even backfire in this context, as reframing an existential threat such as climate change in positive or purposeful terms could feel disingenuous or disconnected from the lived reality of chronic illness—thereby increasing emotional dissonance and undermining coping efficacy.

4.1. Limitations

The present study offers important insights into the psychological impact of climate change on individuals with chronic illnesses; however, several limitations should be noted. First, although the sample was drawn from a large, probability-based online panel, certain population subgroups—particularly older adults with limited digital literacy, individuals from lower socioeconomic backgrounds, and non-Hebrew speakers—may be underrepresented. This sampling bias may limit the generalizability of our findings to the broader Israeli population. Individuals who participate in online surveys may possess certain personal characteristics that distinguish them from those who do not engage in such panels. Furthermore, the cross-sectional design limits our ability to draw causal inferences, as it does not allow for establishing the temporal sequence between variables such as exposure and anxiety. For example, it remains unclear whether heightened anxiety leads to increased use of problem-focused strategies (e.g., environmental monitoring) or whether these strategies themselves elevate anxiety. Unmeasured factors, such as social support or economic status, may also have influenced the results but were not captured in this single-time assessment. Future research should adopt longitudinal designs to better understand how climate change anxiety evolves over time and in response to changing exposure or coping strategies. The reliance on self-report measures may also have introduced response biases; integrating objective data such as air quality indices or temperature fluctuations could provide a more comprehensive understanding of the relationship between climate change exposure and psychological distress. Additionally, expanding the focus to include other chronic conditions such as diabetes or autoimmune diseases may further clarify how different health vulnerabilities interact with climate-related stressors. Future studies could also examine the role of social support networks, as stronger support systems may foster more adaptive coping responses to climate threats. Finally, grouping diverse respiratory conditions such as asthma and COPD into a single category may have masked important differences in sensitivity to climate triggers, limiting the specificity of our findings. Future studies should consider more refined disease classifications.

4.2. Implications for Clinical Practice and Public Health Interventions

The findings of this study have several important implications for clinical practice and public health interventions aimed at mitigating climate change anxiety among individuals with chronic illnesses. For cardiovascular patients, targeted interventions that focus on reducing intense worry and promoting adaptive coping strategies may be particularly beneficial, given such patients’ heightened sensitivity to sudden environmental changes and the perceived unpredictability of cardiovascular crises. For individuals with respiratory conditions, strategies that focus on managing chronic exposure to air pollution and maintaining a sense of control over environmental triggers may help reduce ongoing stress and prevent the development of chronic anxiety. Additionally, public health campaigns should consider the distinct psychological responses associated with cardiovascular and respiratory conditions, emphasizing both immediate protective measures during extreme weather events and long-term coping strategies for managing environmental stressors. Incorporating mental health support into climate adaptation programs for vulnerable populations could further mitigate the psychological impact of climate change, promoting resilience and reducing the risk of persistent anxiety. These findings also support the development of multidisciplinary care models that integrate physical and mental health services for individuals with chronic illnesses affected by climate change. Moreover, community-based programs that provide accessible resources and psychoeducation can enhance individuals’ capacity to cope with climate-related stressors, particularly in underserved or high-risk populations.

5. Conclusions

This study underscores the importance of recognizing climate change anxiety as a significant concern for individuals with chronic health conditions. By identifying specific health vulnerabilities and their associations with exposure and coping strategies, the findings point to the need for targeted mental health interventions that address the distinct psychological challenges posed by climate change. Incorporating these insights into clinical practice and public health initiatives could mitigate the impact of environmental stressors on mental health, fostering resilience and adaptive coping among at-risk populations. Future research should continue to explore the mechanisms underlying these relationships, expanding the focus to include other chronic conditions and longitudinal assessments to capture the evolving impact of climate change. This study contributes to the literature by empirically examining climate-related psychological responses across distinct chronic illness groups, offering a clearer understanding of how health status influences emotional vulnerability. Further, it advances the field by bridging environmental psychology and health psychology, highlighting the need for integrated, condition-specific approaches to climate-related mental health care.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su17136034/s1. Table S1. Demographic comparison: study sample vs. Israeli population.

Author Contributions

Conceptualization, Y.H.-R. and S.S.-A.; methodology, Y.H.-R. and S.S.-A.; formal analysis, Y.H.-R. and S.S.-A.; investigation, Y.H.-R. and S.S.-A.; resources, Y.H.-R. and S.S.-A.; writing—original draft preparation, Y.H.-R. and S.S.-A.; writing—review and editing, Y.H.-R. and S.S.-A.; visualization, Y.H.-R. and S.S.-A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Ariel University (protocol code No. 20241226 and date of approval 26 December 2024).

Informed Consent Statement

Informed consent was obtained from all participants involved in this study.

Data Availability Statement

Data will be made available upon request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Demographic characteristics (N = 522).
Table 1. Demographic characteristics (N = 522).
VariableCategoriesTotal SampleNo Chronic Illness
(n = 277)		Respiratory Disease
(n = 133)		Cardio-Vascular Disease
(n = 112)		Difference
Gender, n (%)Male267 (51.1)130 (46.9)59 (44.4)78 (69.6)χ2(2) = 19.76
(p < 0.001)
Female255 (48.9)147 (53.1)74 (55.6)34 (30.4)
Age, mean (SD), range 49.25 (16.91), 20–7944.53 (15.06) a44.90 (15.47) a66.07 (11.38) bχ2(2) = 136.54
(p < 0.001)
Age category, n (%)20–35136 (26.1)88 (31.8)45 (33.8)3 (2.7)χ2(6) = 165.20
(p < 0.001)
36–50147 (28.2)100 (36.1)41 (30.8)6 (5.4)
50–65126 (24.1)59 (21.3)33 (24.8)34 (30.4)
66–80113 (21.6)30 (10.8)14 (10.5)69 (61.6)
Marital status, n (%)Single88 (16.9)54 (19.5)30 (22.6)4 (3.6)χ2(4) = 22.27
(p < 0.001)
Married, in a relationship374 (71.6)193 (69.7)93 (69.9)88 (78.6)
Divorced, widowed, other60 (11.5)30 (10.8)10 (7.5)20 (17.9)
Children, n (%)Yes403 (77.2)202 (72.9)96 (72.2)105 (93.8)χ2(2) = 22.21
(p < 0.001)
Number of children, mean (SD), range 2.20 (1.73),
0–11		1.97 (1.61) a2.04 (1.94) a2.95 (1.55) bχ2(2) = 31.70
(p < 0.001)
Years of education, mean (SD), range 14.79 (2.84), 8–2614.89 (2.80)14.55 (2.88)14.85 (2.90)χ2(2) = 1.13
(p = 0.567)
Employed, n (%)Yes401 (76.8)233 (84.1)112 (84.2)56 (50.0)χ2(2) = 57.60
(p < 0.001)
Income, n (%) (n = 510)Below average181 (35.5)101 (37.4)43 (32.8)37 (33.9)χ2(4) = 4.70
(p = 0.319)
Average142 (27.8)70 (25.9)34 (26.0)38 (34.9)
Above average187 (36.7)99 (36.7)54 (41.2)34 (31.2)
Religiosity, n (%)Secular274 (52.5)134 (48.4)73 (54.9)67 (59.8)χ2(4) = 4.86
(p = 0.302)
Traditional159 (30.5)92 (33.2)37 (27.8)30 (26.8)
Religious89 (17.0)51 (18.4)23 (17.3)15 (13.4)
Note: Different letters mark significant differences. SD = standard deviation.
Table 2. Differences between groups according to the study variables.
Table 2. Differences between groups according to the study variables.
Total
Mean (SD)
(N = 522)		No Chronic Illness
Mean (SD)
(n = 277)		Respiratory Disease
Mean (SD)
(n = 133)		Cardiovascular Disease
Mean (SD)
(n = 112)		F (2, 243)
(p) (η2)
Climate change anxiety1.31 (0.49)1.26 (0.46) a1.32 (0.47) a1.41 (0.51) b3.64 (p = 0.027)
(η2 = 0.014)
Climate change exposure1.95 (1.58)1.81 (1.53) b2.30 (1.63) a1.82 (1.51) b5.99 (p = 0.003)
(η2 = 0.023)
Climate change awareness3.48 (0.70)3.44 (0.71)3.56 (0.72)3.51 (0.63)1.94 (p = 0.145)
(η2 = 0.007)
Problem-focused coping2.37 (0.80)2.35 (0.77)2.37 (0.86)2.44 (0.80)0.15 (p = 0.857)
(η2 = 0.001)
Meaning-focused coping2.86 (0.55)2.88 (0.55) a2.72 (0.55) b2.94 (0.54) a4.70 (p = 0.009)
(η2 = 0.018)
De-emphasizing2.31 (0.64)2.32 (0.64)2.27 (0.70)2.33 (0.58)0.36 (p = 0.694)
(η2 = 0.001)
Note: Different letters mark significant differences. Ranges: climate change anxiety 1–4; climate change exposure 0–7; climate change awareness 1–5; and coping strategies 1–5. SD = standard deviation.
Table 3. Pearson correlations for the study variables (N = 522).
Table 3. Pearson correlations for the study variables (N = 522).
Variables123456
1. Climate change anxiety1
2. Climate change exposure0.16 ***1
3. Climate change awareness0.26 ***0.33 ***1
4. Problem-focused coping0.55 ***0.21 ***0.49 ***1
5. Meaning-focused coping0.26 ***0.010.27 ***0.40 ***1
6. De-emphasizing−0.13 **−0.30 ***−0.58 ***−0.36 ***−0.011
** p < 0.01, *** p < 0.001 Note. The Bonferroni criterion was applied, p = 0.003.
Table 4. Regression model for climate change anxiety (N = 522).
Table 4. Regression model for climate change anxiety (N = 522).
VariablesBSEΒp
Group (chronic illness vs. no chronic illness)0.030.010.110.008
Group (cardiovascular disease vs. respiratory disease)0.030.020.070.112
Gender (male)0.010.010.020.653
Age0.010.010.050.302
Years of education−0.010.01−0.110.005
Climate change exposure0.020.010.090.027
Climate change awareness0.010.010.040.413
Problem-focused coping0.090.010.53<0.000
Meaning-focused coping0.010.010.030.462
Adj. R2 = 0.33, F(9, 512) = 29.23, p < 0.001.
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Hamama-Raz, Y.; Shinan-Altman, S. Climate Change Anxiety Among Individuals with and Without Chronic Illnesses: The Roles of Exposure, Awareness, and Coping Strategies. Sustainability 2025, 17, 6034. https://doi.org/10.3390/su17136034

AMA Style

Hamama-Raz Y, Shinan-Altman S. Climate Change Anxiety Among Individuals with and Without Chronic Illnesses: The Roles of Exposure, Awareness, and Coping Strategies. Sustainability. 2025; 17(13):6034. https://doi.org/10.3390/su17136034

Chicago/Turabian Style

Hamama-Raz, Yaira, and Shiri Shinan-Altman. 2025. "Climate Change Anxiety Among Individuals with and Without Chronic Illnesses: The Roles of Exposure, Awareness, and Coping Strategies" Sustainability 17, no. 13: 6034. https://doi.org/10.3390/su17136034

APA Style

Hamama-Raz, Y., & Shinan-Altman, S. (2025). Climate Change Anxiety Among Individuals with and Without Chronic Illnesses: The Roles of Exposure, Awareness, and Coping Strategies. Sustainability, 17(13), 6034. https://doi.org/10.3390/su17136034

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