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Article

The Social Distribution of Climate Change Risk Perception: Unraveling Intersectional Patterns of Concern in the United States

by
Musabber Ali Chisty
1,2,3
1
Department of Sociology, University of Colorado Boulder, Boulder, CO 80309, USA
2
Natural Hazards Center, Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO 80309, USA
3
Institute of Disaster Management and Vulnerability Studies, University of Dhaka, Dhaka 1000, Bangladesh
Climate 2026, 14(2), 58; https://doi.org/10.3390/cli14020058
Submission received: 20 January 2026 / Revised: 13 February 2026 / Accepted: 14 February 2026 / Published: 16 February 2026
Versions Notes

Abstract

The escalating frequency and severity of extreme weather events globally have underscored the critical importance of addressing anthropogenic climate change. Countries that contribute disproportionately to global warming relative to their population size bear an urgent responsibility to mitigate climate risks. However, effecting substantive policy change requires a broad public consensus to compel legislative action, a process fundamentally dependent on risk perception. It is theorized that individuals, households, and communities with higher levels of climate change risk perception are more inclined to adopt mitigation behaviors and support collective action. Such perception, however, varies considerably across social dimensions. This study aims to examine how sociodemographic factors shape climate change risk perception among Americans and how intersectionality reveals nuanced patterns beyond single-axis analysis. Using data from the 2023 National Survey of Health Attitudes, the analysis demonstrates that gender, race/ethnicity, educational attainment, religiosity, marital status, and geographic region serve as strong predictors of climate risk perception. Further intersectional analysis reveals that individuals with multiple marginalized social identities, such as race, gender, and socioeconomic status, perceive climate risk distinctly from those without such compounded identities. The study concludes that effective climate communication and policy interventions must prioritize sociodemographic diversity and integrate an intersectional lens to address differential vulnerabilities and perceptions equitably.

1. Introduction

While the most severe consequences of climate change are disproportionately borne by underdeveloped and developing nations, significant concern about its effects is also prevalent within developed nations [1,2,3]. Research on climate change risk perception in the United States has yielded reassuring results, indicating widespread public awareness of global warming and its adverse consequences [4,5]. Elevated risk perception regarding climate change is evident among residents of nations across the economic spectrum, including high-income (e.g., Germany, UK), middle-income (e.g., Brazil, India), and low-income (e.g., Bangladesh, Pakistan) countries. This trend suggests that the dissemination of climate change information is effectively raising global awareness [6,7,8]. However, research also indicates that different determinants and factors are associated with the level of climate change risk perception [9].
Regions continuously impacted by climate change, such as South Asia, Southeast Asia, and small island nations, consistently demonstrate higher levels of public risk perception. One reason for this elevated risk perception is the direct experience of negative consequences in daily life [10,11,12,13]. Conversely, in industrially developed nations like Australia, the United States, and France, high public risk perception is primarily driven by robust media coverage, widespread knowledge dissemination, and a strong sense of self-efficacy [4,14,15,16]. But why is it important to perceive the risk of climate change? Research indicates that a higher level of climate change risk perception and a deeper understanding of its impacts among citizens positively influence both support for climate policies and the adoption of individual and household-level actions [17,18,19,20,21,22].
Given that people perceive the risks of climate change and understand its importance, the focus must now shift to the factors that determine the level of this perception. From a sociological perspective, global studies indicate that socio-demographic characteristics are significant indicators for assessing why risk perception varies among individuals [23,24,25]. Research examining climate change risk perception through a socio-demographic lens remains limited in the United States. The existing literature strongly recommends continued study in this area to enhance the efficacy of household and community-level practices for climate change adaptation and mitigation [19,26,27,28]. However, these studies are often limited by a singular approach, analyzing variables individually rather than examining the complex interplay between multiple socio-demographic factors that shape risk perception. To address this gap, our study employed an intersectional framework. The primary objective was to assess climate change risk perception from a socio-demographic perspective and to examine how the intersection of these factors shapes perception levels.

2. Theoretical Framework

A substantial body of research has focused on quantifying climate change risk perception among national populations. Scholars, primarily from psychology and social science, due to the topic’s psychological nature, have successfully developed and operationalized numerous models to assess the public perception of climate-related risks. These efforts have been crucial in standardizing the assessment process [29,30]. For the current study, we want to operationalize three definitions of perception, risk perception, and climate change risk perception as part of a broader theoretical framework. Perception is the active mental process of selecting, organizing, and interpreting sensory information and experiences to form a coherent understanding of one’s environment [31]. Risk perception is the subjective judgment people make about the characteristics, severity, and likelihood of a potential threat, which is influenced by psychological, social, cultural, and institutional factors rather than by objective statistical analysis alone [32]. Climate change risk perception is the degree to which an individual or group recognizes, understands, and feels concerned about the potential dangers and adverse consequences associated with global climate change, including its environmental, economic, and social impacts [33,34]. Researchers have developed comprehensive models to assess climate change risk perception, integrating a range of indicators across cognitive, experiential, socioeconomic, attitudinal, and behavioral dimensions. Given the variation in assessment methodologies and contextual differences across regions, researchers have recommended conducting distinct, country-specific climate change risk perception assessments [35,36,37,38]. With such a theoretical background, this study focused on assessing climate change risk perception of the U.S. population.
While a body of scholarship has examined climate change risk perception among the U.S. population exploring various social, cultural, economic, and demographic determinants, a critical methodological limitation persists. The predominant approach within this literature has been to analyze these sociodemographic variables in isolation [19,35,39,40,41]. Consequently, there remains a significant gap in the application of an intersectional framework capable of interrogating how interlocking systems of power and compound identities concurrently structure and shape differential perceptions of climate risk. To implement an intersectional framework in this study, we need to review the intersectionality theory first. Coined by legal scholar Kimberlé Crenshaw, intersectionality theory posits that multiple sociodemographic identity markers, notably race, gender, and class, are not independent but rather interact synergistically to create unique modes of differential experience and systemic disadvantage. This framework elucidates how these interlocking systems of power and privilege produce heightened social vulnerability and susceptibility for certain individuals, even within broader shared demographic categories [42,43,44,45]. A substantial body of scholarly work has since expanded upon and operationalized Crenshaw’s foundational concept of intersectionality, applying its theoretical framework to a diverse array of disciplinary contexts. The core premise of this theory contends that effective policies, plans, and programs must move beyond universal, one-size-fits-all approaches to instead account for the heterogeneity within seemingly homogeneous groups. Intersectionality provides the critical analytical tool necessary to deconstruct how overlapping and interdependent social identities compound to shape unique lived experiences, perceptions, and vulnerabilities [46,47,48,49]. In this current study, we used an intersectional framework to review how intersectional sociodemographic identities shape climate change risk perception in the U.S.

3. Data and Methods

3.1. Data

Since 2013, the Robert Wood Johnson Foundation has been trying to develop a measurement to assess health and well-being outcome in the U.S. In 2015, with the assistance of the RAND Corporation, Santa Monica, CA, USA, the National Survey of Health Attitudes (NSHA) was introduced for field-level study. In the 2023 survey, there were 5 different domains under which data were clustered. These are social determinants of health and disparities; government roles, including levels of government in health promotion, illness care, etc.; change agent and action on health; health relative to other social issues and priorities; and perceptions of the role of personal responsibility. Under the social determinants of health domain, the NSHA included items to assess people’s perception about climate change and how it should be tackled [50]. In this current study, the 2023 NSHA public use data were used to assess Americans’ climate change risk perception. The public use version of the data is available through the Inter-university Consortium for Political and Social Research (ICPSR) data repository [51]. The final analytic sample consisted of 5620 respondents after removing cases with missing data and non-responses. According to a data summary report by the RAND Corporation, this sample is nationally representative. The survey comprised 37 questions, some of which included sub-questions and required approximately 19 to 20 min to complete [50].

3.2. Variables

3.2.1. Dependent Variable

This study operationalizes climate change risk perception as a unidimensional dependent variable, constructed from five items measured on a 4-point Likert scale (1 = Strongly Agree to 4 = Strongly Disagree). The question in the survey was “How much do you agree or disagree with each of the following statements?”. The five items in Table 1 were statements for this question with the Likert scale responding options. The absence of a neutral midpoint facilitated clearer analytical distinctions (Table 1). Prior to analysis, items were reverse-coded to ensure consistent directionality. The factorability of the five items was assessed prior to dimension reduction. The Kaiser–Meyer–Olkin (KMO) measure verified the sampling adequacy for the analysis, with an overall value of 0.90, classified as “meritorious” according to conventional thresholds. Individual KMO values for all items were well above 0.80, ranging from 0.88 to 0.92. Bartlett’s test of sphericity was significant (χ2 (10) = 28,000, p < 0.001), indicating that the correlation matrix was factorable.
Principal factor analysis (PFA) was used to examine the underlying structure of the scale. Based on Kaiser’s criterion (eigenvalue > 1), one dominant factor was retained. This factor had an eigenvalue of 3.95 and accounted for approximately 79% of the common variance. All five items loaded strongly onto the single factor, with loadings ranging from 0.87 to 0.91, confirming a robust unidimensional structure (see Table 1). The internal consistency of the scale was excellent, as indicated by a Cronbach’s alpha of 0.95.
A composite climate change risk perception score was created for each participant by averaging the five items, resulting in a continuous scale score that served as the dependent variable in subsequent analyses. The composite index was created by computing the arithmetic mean of the five items for each respondent. Averaging, rather than summing, was used to preserve the original scale metric and to allow the composite score to remain interpretable within the 1–4 response range. This approach also ensures that each indicator contributes equally to the overall climate change risk score, preventing any single item from disproportionately influencing the composite measure.
C l i m a t e   R i s k   I n d e x i = 1 5   ∑ j = 1 5 X i j
where:
-
Xij = reverse-coded response of respondent I on item j;
-
The index ranges from 1 to 4;
-
Higher values indicate higher perceived risk;
-
Each item contributes equally to the composite score.

3.2.2. Independent Variable and Covariates

As part of the intersectionality framework, the main independent variable of this study was gender. The study focused on exploring whether climate change risk perception differed based on the gender of the respondent. In the data, gender was recorded dichotomously (1 = Female, 0 = Male). Gender was specified as the primary independent variable because prior research has consistently documented gendered differences in climate risk perception and environmental concern [52]. These differences are theoretically grounded in socialization processes, unequal exposure to environmental risks, and structural inequalities that shape how individuals interpret and respond to climate-related threats [53,54,55]. Positioning gender as the main independent variable allows the analysis to assess whether these patterned differences persist after accounting for other relevant sociodemographic factors.
To implement the intersectional framework, the study also included several covariates. These covariates helped to assess whether gender is the main reason for variation in climate change risk perception or whether other factors can explain the changes in the scale. One important covariate was race/ethnicity. The study collected the responses at a nominal level. However, for analysis purposes, the study created a dummy variable and isolated the Non-Hispanic African American group from the rest of the responses, where the coding was 1 = Non-Hispanic African American, 0 = Others.
The rest of the covariates were dichotomous in nature, such as:
-
Marital status (1 = Single, 0 = Married);
-
Education (1 = Have a college degree, 0 = Do not have a college degree);
-
Religion in life (1 = Not important, 0 = Important);
-
Census region (1 = Northeast, 2 = Midwest, 3 = South, 4 = West; for analysis, a dummy variable was created where 1 = Northeast, 0 = Others);
-
Chronic health condition (1 = Yes, 0 = No);
-
Community wellbeing (1 = Poor, 0 = Good).

3.3. Analysis

The study included descriptive statistics at the percentage level for all variables to gather an overall perspective. Also, the variables were included in a bivariate test to assess whether the responses differed based on the gender of the respondents. A Pearson chi-square test was performed as part of the bivariate analysis. StataNow/BE 18.5 for Mac was used for statistical analysis of this paper.
Secondly, as part of the advanced analysis and to complete the study objective, an Ordinary Least Squares (OLS) model was used to assess the association between the climate change risk perception scale and the independent variable and covariates. In the first part of the OLS, an unadjusted model was used for each independent variable and covariate. For further analysis, an adjusted model was run to see whether the association between the dependent variable (the climate change risk perception index) and the independent variable (gender) changes or not based on the adjustment of covariates.
Following the OLS model, the study employed an intersectional analytical approach to examine how overlapping social identities jointly influence the outcome of interest. The analysis was conducted using interaction terms within a regression framework, allowing for the effects of one social characteristic to vary depending on the presence of another. Specifically, two-way interactions between key sociodemographic factors were included to capture these combined effects. After estimating the regression models, predicted margins and marginal effects were computed to interpret the interaction results, providing a nuanced understanding of how intersecting identities shape the outcome. This method enables the identification of patterns that may be obscured when only main effects are considered, ensuring a more comprehensive understanding of social inequality and its influence on the studied phenomenon. By integrating interaction terms and examining conditional effects, this approach operationalizes intersectionality quantitatively, offering rigorous insight into the multiplicative influence of social positions.

3.4. Ethics Statement

The study utilized the public-use version of the 2023 National Survey of Health Attitudes (NSHA), available through the ICPSR repository. As the author did not collect any primary data, the study was exempt from requiring ethical approval from an Institutional Review Board (IRB). All usage adhered to the ICPSR guidelines for secondary data analysis. The sole requirement, proper citation of the dataset, was strictly followed throughout the research and referencing process.

4. Results

4.1. Description of the Sociodemographic Characteristics

Table 2 presents the sociodemographic composition of the analytic sample, stratified by gender. Bivariate associations were evaluated using Pearson chi-square tests, with multiple indicators demonstrating statistically significant variation across gender categories.
Female respondents were significantly more likely to identify as Non-Hispanic African American (χ2 = 14.42, p < 0.01). Pronounced disparities were observed in educational attainment, with a higher proportion of male respondents holding a college degree (χ2 = 22.35, p < 0.001). Substantial differences were also evident in the role of religion, with females more frequently attributing importance to religion (χ2 = 94.70, p < 0.001). Health and community context also differed significantly by gender: females reported higher prevalence of chronic health conditions (χ2 = 8.15, p < 0.01) and poor community well-being (χ2 = 12.83, p < 0.01).
No statistically significant differences were detected in marital status or geographic distribution across census regions. The sample was predominantly Non-Hispanic White (50.4%), with comparable gender representation across most demographic strata.
These results affirm systematic sociodemographic patterning by gender, underscoring the methodological importance of controlling for these covariates and supporting the application of an intersectional framework in subsequent analyses of climate risk perception.

4.2. Climate Change Risk Perception Models

Table 3 presents the unadjusted and adjusted regression coefficients from Ordinary Least Squares (OLS) models predicting climate change risk perception. In both models, all independent variables demonstrated statistically significant associations with the risk perception index.
The unadjusted models estimated the bivariate association between each independent variable and the risk perception index. All variables were significantly associated with higher risk perception (p < 0.001). Female gender (β = 0.21, SE = 0.03), African American race (β = 0.28, SE = 0.03), identifying as single (β = 0.17, SE = 0.03), holding a college degree (β = 0.15, SE = 0.03), reporting religion as not important (β = 0.31, SE = 0.03), residing in the Northeast census region (β = 0.17, SE = 0.03), having a chronic health condition (β = 0.09, SE = 0.03), and reporting poor community well-being (β = 0.14, SE = 0.03) were all positively associated with the outcome.
The adjusted model, which included all covariates simultaneously, revealed how these associations persist when controlling for other sociodemographic factors. The positive association between female gender and risk perception strengthened slightly (β = 0.25, SE = 0.02), suggesting that controlling for confounding variables more clearly isolates the effect of gender. Similarly, coefficients for African American race (β = 0.32, SE = 0.03) and importance of religion (β = 0.35, SE = 0.03) increased in magnitude, indicating robust independent effects. Conversely, the coefficients for marital status, census region, and community well-being attenuated in the adjusted model, suggesting that part of their bivariate association is mediated by other variables in the model.
These findings demonstrate that multiple social, demographic, and geographic factors independently contribute to climate change risk perception, supporting an intersectional approach to understanding public perception of climate-related threats.

4.3. Intersectional Analysis

Finally, interaction-based regression analysis and marginal effects were estimated to examine how intersecting social identities shape climate change risk perception (Table 4 and Table 5). This approach moves beyond additive effects to model the lived experience of individuals holding multiple identities simultaneously.
The OLS regression results in Table 4 revealed both the main effects of sociodemographic characteristics and the intersectional effects with gender. Individually, gender, race, religion, marital status, and education were all significantly associated with climate change risk perception. Notably, the interaction terms indicate that the effect of these characteristics varies depending on gender. For example, the negative coefficient for African American females (−0.19, p < 0.01) suggests that while being African American or female individually is associated with higher climate threat perception, the combination slightly reduces the overall effect relative to what would be expected based on the main effects alone. Similarly, the interaction between female and non-religious status (−0.14, p < 0.01) indicates a moderated effect, where non-religious females perceive somewhat lower climate risk compared to the additive expectation from the main effects. Other interactions, such as female with a college degree or female never married, were not statistically significant, suggesting that for these identities, gender did not meaningfully modify the association with climate threat perception.
Table 5, which reports the predicted margins, provides a more interpretable view of these intersectional patterns. The marginal effects illustrate the combined outcomes for specific identity groups. For instance, African American females showed the highest predicted climate threat perception (3.27), exceeding both African American males (3.16) and females from other racial groups (3.02). This indicates that despite the negative interaction coefficient, the overall climate threat perception remains elevated for this group relative to many other groups. Similarly, females with no college degree (2.98) and females with a college degree (3.19) have higher predicted scores than their male counterparts, reinforcing the overall heightened perception among women. The marginal effects for religious and marital status also show similar patterns: non-religious females (3.22) perceived higher climate risk than religious females (2.94), and never-married females (3.14) showed slightly higher perception than males in comparable marital categories.
These empirical results indicate that climate risk perception is not uniform across interaction-based sociodemographic identities, but instead fluctuates in both positive and negative directions. While main effects highlight overall differences, the interaction terms and marginal effects reveal that overlapping social positions, particularly combinations of gender with race or religion, modify these perceptions. The results underscore the importance of examining multiple social identities simultaneously, as additive analyses would overlook these conditional patterns. Overall, women, especially those from minority racial or non-religious backgrounds, exhibit higher climate change risk perception, reflecting the compounded influence of intersecting social positions.

5. Discussion

Understanding climate change risk perception in the United States is critically important from both global and national policy perspectives. Although the U.S. comprises only 5% of the world’s population, it accounts for approximately 25% of historical global greenhouse gas emissions. This disproportionate contribution to atmospheric carbon levels confers upon the U.S. an outsized ethical and practical responsibility to mitigate climate change [35]. Elevated climate change risk perception among the general public serves two critical functions, particularly within high-income, politically influential nations. First, heightened public concern exerts substantive pressure on governmental bodies, increasing the likelihood of adopting and implementing rigorous climate mitigation policies, such as carbon pricing, renewable energy investments, and stricter emissions regulations. Second, individuals within economically secure communities are better positioned to undertake and sustain adaptive and mitigative actions at the household and local level, such as adopting energy-efficient technologies, supporting sustainable infrastructure, and engaging in conservation behaviors, when they perceive climate risks as salient and urgent [34,39,56,57]. Thus, understanding and fostering climate risk perception is not merely an academic exercise but a strategic imperative for catalyzing both top-down policy change and bottom-up behavioral shifts in key contexts.
The results indicate that gender is a significant sociodemographic predictor of climate change risk perception. Female participants expressed substantially higher concern regarding climate change and its associated environmental and health impacts than their male counterparts. This association remained statistically significant even after adjusting for other sociodemographic variables, underscoring the robustness of gender as an independent factor in shaping risk perception.
Several theoretical propositions may explain this observed gender gap. A prominent explanation is rooted in ecofeminist theory, which posits that women often maintain a closer relationship with the environment due to socially and culturally assigned roles. For instance, in many underdeveloped regions, women bear primary responsibility for gathering natural resources such as firewood and securing food from local ecosystems, roles that heighten their dependence on and awareness of environmental conditions. This lived experience may foster a deeper perception of climate-related risks compared to men, whose daily activities may less directly involve resource dependence and environmental interaction [58,59]. Furthermore, research indicates that women often experience disproportionate impacts from climate-related hazards due to structural socioeconomic vulnerabilities and culturally ingrained barriers. These include unequal access to resources, limited mobility, and gendered social roles that increase their exposure and sensitivity to environmental shocks. Consequently, women tend to exhibit greater vigilance and concern regarding the future consequences of climate change compared to men [60,61,62,63]. Studies focusing on gender aspects of environmental and climate risk perception presented that parents, both females and males, worry about climate change more than non-parents [64,65]. One study showed that female parents were more concerned about climate risk than males [66]. Researchers also accounted that women of reproductive age were worried about climate crises and frequently took steps to reduce their environmental footprint through actions like minimizing waste production, ensuring environmental conservation, and adopting eco-friendly lifestyles [67]. These behaviors of reproductive-age women are highly correlated with their roles as caregivers and concerns about their future children and families [68,69,70]. The current study’s statistical findings align with established literature indicating that women report significantly higher perceptions of climate change risks than men.
Race and ethnicity remain strong predictors of variation in climate change risk perception. Studies attribute this trend to historical marginalization and ongoing environmental injustices, which lead racial and ethnic minorities in the U.S. to perceive climate risks as significantly higher. Research has established that these communities, including Non-Hispanic Black and Hispanic populations, consistently report elevated risk perceptions compared to racial majorities [71,72,73,74]. This heightened awareness is a rational response to systemic disparities and greater vulnerability to environmental hazards, fostering a more urgent understanding of the need for climate change mitigation. The integration of gender with race through an intersectional lens reveals a compounded effect on climate change risk perception. Previous literature indicates that socioeconomically disadvantaged women of color report elevated concerns regarding environmental risks and climate change [75,76,77,78]. The current study corroborates these findings through statistical analysis, demonstrating that race functions as both a singular predictor and a key intersecting factor that when combined with female gender, significantly increases the probability of higher climate change risk perception.
The relationship between religiosity, religious affiliation, and climate change risk perception has emerged as a critical area of inquiry within the environmental social sciences. This discourse was profoundly shaped by Lynn White, Jr.’s 1967 seminal essay, “The Historical Roots of Our Ecological Crisis”. White argued that Western Christianity, particularly its interpretations of the Genesis creation narrative advocating for human dominion over nature, established a theological foundation that encouraged the exploitation of the natural world and thus bears a deep historical responsibility for the anthropogenic ecological crisis. This provocative thesis sparked decades of scholarly debate and research into how religious beliefs, both as systems of meaning and as sources of ethical injunction, shape environmental attitudes, behaviors, and risk perceptions [79,80]. Despite ongoing efforts by many faith-based institutions to promote environmental stewardship, a negative association between certain religious beliefs and climate change risk perception persists in the literature [81,82,83,84]. For example, Zaleha and Szasz presented that conservative Christians do not believe in climate change, and American Christians have a lower level of environmental concern than non-Christians [85]. Previously, Clements and colleagues corroborated these findings, identifying a significant negative association between conservative Christian affiliation and support for climate change mitigation policies in the United States [86]. A study conducted in the Middle East found that individuals who self-identified as Muslim and expressed support for Islamist governance demonstrated lower levels of concern regarding climate change and environmental issues [87]. Research confirms that religious importance significantly shapes climate change attitudes and behaviors, though its effects vary across traditions and interpretations [88]. This study’s findings align with previous research, indicating that individuals who attribute less importance to religion in their lives report higher levels of awareness and concern regarding climate change compared to their more religious counterparts. Furthermore, intersectional analysis revealed that participants embodying multiple marginalized identities, specifically, women who assigned lower importance to religion, perceived climate change risks more strongly than other groups.
Educational attainment emerged as a robust predictor of heightened climate change risk perception in this study [37,89,90]. Respondents with tertiary degrees, including university students and graduates, demonstrated significantly greater concern regarding climate-related threats compared to individuals possessing only secondary-level education or lower [91,92]. Indeed, both global and national studies consistently demonstrated that individuals with higher levels of educational attainment exhibited significantly stronger risk perception regarding climate change and expressed greater concern about its adverse consequences [93,94,95,96]. It was further revealed that highly educated women express greater concern regarding the climate crisis and perceive higher risks associated with climate change than men with low educational attainment [97]. The present study’s findings align with the existing literature, confirming that educational attainment serves as a significant predictor of climate change concern. Participants holding a college degree demonstrated substantially higher levels of climate change awareness and perceived risk compared to those without tertiary education. However, in terms of the interaction effect, education showed a limited impact on climate risk perception while interacting with gender. Though there was a modest impact of education and gender identities together on the climate risk perception outcome, education amplified gender differences rather than attenuating them. These findings complicate simplistic narratives that education universally increases environmental concern. Rather, education interacts with social position, producing divergent effects across demographic groups.
One of the main limitations of this study was the use of secondary survey data to measure climate change risk perception. This approach makes it difficult to address “why” questions based on the quantitative data alone, as it lacks the contextual depth that field-level case studies or interviews could provide. Furthermore, the survey captured perceptions at a single point in time, which may not account for changes in awareness or attitudes in response to evolving climate events or media coverage. Also, though the survey is nationally representative, certain subpopulations may be underrepresented, limiting the applicability of findings to all communities.

Policy and Practice Recommendations

Develop Intersectional Public Communication Campaigns: Federal and state agencies should move beyond one-size-fits-all climate messaging. Communication strategies should be co-developed with and tailored to specific communities, particularly women of color and religious groups, reflecting their unique values, concerns, and cultural contexts to effectively elevate risk perception and catalyze engagement. Through these special campaigns, vulnerable groups with intersectional identities will become more aware of climate risk. Also, these groups can contribute as resource persons in similar campaigns to improve communities’ climate risk perception.
Integrate Climate Education into Diverse Faith-Based and Community Settings: Support initiatives that partner with faith leaders and community organizations to reframe climate action through lenses of stewardship, justice, and protection. This can help bridge the gap between scientific consensus and diverse belief systems, building trust and motivating behavior change within skeptical communities. As non-religious persons or persons with low religious importance in life showed improved climate risk perception, the religious population is missing something. Including religious leaders in climate risk communication strategies through education programs can fill this gap.
Target Resource Allocation to Empower the Most Vulnerable and Aware: Policy should recognize that elevated risk perception often coincides with heightened vulnerability. Direct funding and resources toward communities that are both highly aware and disproportionately at risk, such as African American women, for locally led adaptation projects, green infrastructure, and climate resilience programs, transforming their awareness into actionable protection. Without access to resources, higher climate risk perception will not result in mitigation and adaptation actions. Thus, equity-based resource allocation is required for improved climate risk management.
Mandate Inclusive and Representative Climate Planning: Legislators should require that climate policy boards, planning committees, and grant-awarding bodies include representatives from the communities most affected by climate change, ensuring that policies are not only informed by intersectional risk perception but are also equitable in their implementation and benefits. Access to decision-making platforms will also result in improving climate risk knowledge and perception. Vulnerable communities will learn more about climate risks to present their needs in the planning process to reduce their vulnerabilities.
Advance Community-Engaged Mixed-Methods Research: Federal and state agencies should fund and prioritize community-engaged qualitative research alongside quantitative surveys to uncover the social, cultural, and structural drivers of climate risk perception and preparedness among intersecting sociodemographic groups. Such mixed-methods approaches can strengthen evidence-based policy design by grounding interventions in lived experiences and contextual realities that large-scale data alone cannot capture.

6. Conclusions

This research demonstrates that climate change risk perception in the United States is unevenly distributed, shaped by the interplay of sociodemographic factors such as gender, race, religiosity, and educational attainment. The findings reveal a nuanced landscape of vulnerability and privilege: structurally marginalized groups, particularly women of color, exhibit heightened climate awareness, likely reflecting lived experiences with disproportionate environmental risks. In contrast, individuals with lower educational attainment or certain religious affiliations show reduced perception of climate threats, highlighting how worldview, knowledge, and access to information influence environmental engagement.
These results underscore that climate risk perception is not purely a matter of individual cognition or exposure but is deeply intertwined with social, cultural, and institutional contexts. Patterns of awareness reflect historical inequities, socialization, and differential access to environmental knowledge, suggesting that public engagement strategies must be tailored to these intersecting factors. Overall, this study emphasizes the importance of integrating social justice perspectives into climate communication and policy, recognizing that effective climate action depends on understanding who perceives risk, why, and under what social conditions.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data Availability Statement

Data are available through the ICPSR data repository https://doi.org/10.3886/ICPSR39205.v1 (accessed on 20 August 2025).

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Borick, C.P.; Rabe, B.G. Personal Experience, Extreme Weather Events, and Perceptions of Climate Change. In Oxford Research Encyclopedia of Climate Science; Oxford University Press: Oxford, UK, 2017. [Google Scholar] [CrossRef]
  2. Krosnick, J.A.; Holbrook, A.L.; Lowe, L.; Visser, P.S. The Origins and Consequences of democratic citizens’ Policy Agendas: A Study of Popular Concern about Global Warming. Clim. Chang. 2006, 77, 7–43. [Google Scholar] [CrossRef]
  3. Walker, I.; Greenhill, M.; Leviston, Z. Australian Attitudes to Climate Change and Adaptation: 2010–2014; CSIRO: Perth, Australia, 2015. [Google Scholar] [CrossRef]
  4. Bradley, G.L.; Babutsidze, Z.; Chai, A.; Reser, J.P. The role of climate change risk perception, response efficacy, and psychological adaptation in pro-environmental behavior: A two nation study. J. Environ. Psychol. 2020, 68, 101410. [Google Scholar] [CrossRef]
  5. Weber, E.U.; Stern, P.C. Public understanding of climate change in the United States. Am. Psychol. 2011, 66, 315–328. [Google Scholar] [CrossRef] [PubMed]
  6. Brechin, S.R.; Bhandari, M. Perceptions of climate change worldwide. WIREs Clim. Chang. 2011, 2, 871–885. [Google Scholar] [CrossRef]
  7. Frondel, M.; Simora, M.; Sommer, S. Risk Perception of Climate Change: Empirical Evidence for Germany. Ecol. Econ. 2017, 137, 173–183. [Google Scholar] [CrossRef]
  8. Paniello-Castillo, B.; Döring, S.; Dryhurst, S.; Di Baldassarre, G.; Raffetti, E. Risk perception of climate change and global crises: Influences of socio-economic drivers and political orientations. Humanit. Soc. Sci. Commun. 2025, 12, 967. [Google Scholar] [CrossRef]
  9. Fasolin, G.N.; Spektor, M.; Marques, R.; Camargo, J. Determinants of climate change risk perception in Latin America. Nat. Commun. 2025, 16, 6887. [Google Scholar] [CrossRef]
  10. Abidoye, B.O.; Kurukulasuriya, P.; Mendelsohn, R. South-east Asian farmer perceptions of climate change. Clim. Chang. Econ. 2017, 8, 1740006. [Google Scholar] [CrossRef]
  11. Aswani, S.; Vaccaro, I.; Abernethy, K.; Albert, S.; De Pablo, J.F.-L. Can Perceptions of Environmental and Climate Change in Island Communities Assist in Adaptation Planning Locally? Environ. Manag. 2015, 56, 1487–1501. [Google Scholar] [CrossRef]
  12. Kim, S.Y.; Wolinsky-Nahmias, Y. Cross-National Public Opinion on Climate Change: The Effects of Affluence and Vulnerability. Glob. Environ. Politics 2014, 14, 79–106. [Google Scholar] [CrossRef]
  13. Sovacool, B.K. Perceptions of climate change risks and resilient island planning in the Maldives. Mitig. Adapt. Strat. Glob. Chang. 2012, 17, 731–752. [Google Scholar] [CrossRef]
  14. Akerlof, K.; DeBono, R.; Berry, P.; Leiserowitz, A.; Roser-Renouf, C.; Clarke, K.-L.; Rogaeva, A.; Nisbet, M.C.; Weathers, M.R.; Maibach, E.W. Public Perceptions of Climate Change as a Human Health Risk: Surveys of the United States, Canada and Malta. Int. J. Environ. Res. Public Health 2010, 7, 2559–2606. [Google Scholar] [CrossRef] [PubMed]
  15. Pidgeon, N. Climate Change Risk Perception and Communication: Addressing a Critical Moment? Risk Anal. 2012, 32, 951–956. [Google Scholar] [CrossRef] [PubMed]
  16. Pidgeon, N. Public understanding of, and attitudes to, climate change: UK and international perspectives and policy. Clim. Policy 2012, 12, S85–S106. [Google Scholar] [CrossRef]
  17. Cologna, V.; Kotcher, J.; Mede, N.G.; Besley, J.; Maibach, E.W.; Oreskes, N. Trust in climate science and climate scientists: A narrative review. PLoS Clim. 2024, 3, e0000400. [Google Scholar] [CrossRef]
  18. Dietz, T.; Gardner, G.T.; Gilligan, J.; Stern, P.C.; Vandenbergh, M.P. Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions. Proc. Natl. Acad. Sci. USA 2009, 106, 18452–18456. [Google Scholar] [CrossRef]
  19. Leiserowitz, A. Climate Change Risk Perception and Policy Preferences: The Role of Affect, Imagery, and Values. Clim. Chang. 2006, 77, 45–72. [Google Scholar] [CrossRef]
  20. Lorenzoni, I.; Nicholson-Cole, S.; Whitmarsh, L. Barriers perceived to engaging with climate change among the UK public and their policy implications. Glob. Environ. Chang. 2007, 17, 445–459. [Google Scholar] [CrossRef]
  21. Nelson, L.K.; Cullen, A.C.; Koehn, L.E.; Harper, S.; Runebaum, J.; Bogeberg, M.; Strawn, A.; Levin, P.S. Understanding perceptions of climate vulnerability to inform more effective adaptation in coastal communities. PLoS Clim. 2023, 2, e0000103. [Google Scholar] [CrossRef]
  22. Ofori, B.Y.; Ameade, E.P.K.; Ohemeng, F.; Musah, Y.; Quartey, J.K.; Owusu, E.H. Climate change knowledge, attitude and perception of undergraduate students in Ghana. PLoS Clim. 2023, 2, e0000215. [Google Scholar] [CrossRef]
  23. García-del-Amo, D.; Mortyn, P.G.; Reyes-García, V. Local reports of climate change impacts in Sierra Nevada, Spain: Sociodemographic and geographical patterns. Reg. Environ. Chang. 2023, 23, 14. [Google Scholar] [CrossRef] [PubMed]
  24. Haq, S.M.A.; Ahmed, K.J. Does the perception of climate change vary with the socio-demographic dimensions? A study on vulnerable populations in Bangladesh. Nat. Hazards 2017, 85, 1759–1785. [Google Scholar] [CrossRef]
  25. Weber, E.U. What shapes perceptions of climate change? WIREs Clim. Chang. 2010, 1, 332–342. [Google Scholar] [CrossRef]
  26. Binelli, C.; Loveless, M.; Schaffner, B.F. Explaining Perceptions of Climate Change in the US. Political Res. Q. 2023, 76, 365–380. [Google Scholar] [CrossRef]
  27. Gilbert, C.; Lachlan, K. The climate change risk perception model in the United States: A replication study. J. Environ. Psychol. 2023, 86, 101969. [Google Scholar] [CrossRef]
  28. Mase, A.S.; Gramig, B.M.; Prokopy, L.S. Climate change beliefs, risk perceptions, and adaptation behavior among Midwestern U.S. crop farmers. Clim. Risk Manag. 2017, 15, 8–17. [Google Scholar] [CrossRef]
  29. Salas Reyes, R.; Nguyen, V.M.; Schott, S.; Berseth, V.; Hutchen, J.; Taylor, J.; Klenk, N. A Research Agenda for Affective Dimensions in Climate Change Risk Perception and Risk Communication. Front. Clim. 2021, 3, 751310. [Google Scholar] [CrossRef]
  30. Van Der Linden, S. On the relationship between personal experience, affect and risk perception:The case of climate change. Eur. J. Soc. Psychol. 2014, 44, 430–440. [Google Scholar] [CrossRef]
  31. Garner, W.R.; Hake, H.W.; Eriksen, C.W. Operationism and the concept of perception. Psychol. Rev. 1956, 63, 149–159. [Google Scholar] [CrossRef]
  32. Sjöberg, L. The Methodology of Risk Perception Research. Qual. Quant. 2000, 34, 407–418. [Google Scholar] [CrossRef]
  33. Xie, B.; Brewer, M.B.; Hayes, B.K.; McDonald, R.I.; Newell, B.R. Predicting climate change risk perception and willingness to act. J. Environ. Psychol. 2019, 65, 101331. [Google Scholar] [CrossRef]
  34. van der Linden, S. The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model. J. Environ. Psychol. 2015, 41, 112–124. [Google Scholar] [CrossRef]
  35. Leiserowitz, A.A. American Risk Perceptions: Is Climate Change Dangerous? Risk Anal. 2005, 25, 1433–1442. [Google Scholar] [CrossRef] [PubMed]
  36. Tranter, B. The Great Divide: Political Candidate and Voter Polarisation over Global Warming in Australia. Aust. J. Politics Hist. 2013, 59, 397–413. [Google Scholar] [CrossRef]
  37. Lee, T.M.; Markowitz, E.M.; Howe, P.D.; Ko, C.-Y.; Leiserowitz, A.A. Predictors of public climate change awareness and risk perception around the world. Nat. Clim. Chang. 2015, 5, 1014–1020. [Google Scholar] [CrossRef]
  38. Villacis, A.H.; Alwang, J.R.; Barrera, V. Linking risk preferences and risk perceptions of climate change: A prospect theory approach. Agric. Econ. 2021, 52, 863–877. [Google Scholar] [CrossRef]
  39. Grover, H.; Brody, S.D.; Vedlitz, A. Understanding climate change risk perception in the USA. Int. J. Glob. Warm. 2017, 13, 113. [Google Scholar] [CrossRef]
  40. Leiserowitz, A.A. Day After Tomorrow: Study of Climate Change Risk Perception. Environ. Sci. Policy Sustain. Dev. 2004, 46, 22–39. [Google Scholar] [CrossRef]
  41. Fletcher, J.; Higham, J.; Longnecker, N. Climate change risk perception in the USA and alignment with sustainable travel behaviours. PLoS ONE 2021, 16, e0244545. [Google Scholar] [CrossRef]
  42. Chisty, M.A.; Dola, S.E.A.; Khan, N.A.; Rahman, M.M. Intersectionality, vulnerability and resilience: Why it is important to review the diversifications within groups at risk to achieve a resilient community. Contin. Resil. Rev. 2021, 3, 119–131. [Google Scholar] [CrossRef]
  43. Cho, S.; Crenshaw, K.W.; McCall, L. Toward a Field of Intersectionality Studies: Theory, Applications, and Praxis. Signs J. Women Cult. Soc. 2013, 38, 785–810. [Google Scholar] [CrossRef]
  44. Crenshaw, K. Demarginalizing the Intersection of Race and Sex: A Black Feminist Critique of Antidiscrimination Doctrine, Feminist Theory and Antiracist Politics. Univ. Chic. Leg. Forum 1989, 1989, 139–167. [Google Scholar]
  45. Crenshaw, K.W. Race, Reform, and Retrenchment: Transformation and Legitimation in Antidiscrimination Law. Harv. Law Rev. 1988, 101, 1331–1387. [Google Scholar] [CrossRef]
  46. Aguilar, D.D. From Triple Jeopardy to Intersectionality: The Feminist Perplex. Comp. Stud. South Asia Afr. Middle East 2012, 32, 415–428. [Google Scholar] [CrossRef]
  47. Williams, J.C. Double Jeopardy? An Empirical Study with Implications for the Debates over Implicit Bias and Intersectionality. Harv. J. Law Gend. 2014, 37, 185–241. [Google Scholar]
  48. Bello, B.G.; Mancini, L. Talking about intersectionality. Interview with Kimberlé W. Crenshaw. In Sociologia Del Diritto; Milano University Press: Milan, Italy, 2016; pp. 11–21. [Google Scholar] [CrossRef]
  49. Cwiak, C.L. Teaching Intersectionality: Conceptualizing Layered Vulnerability To Advance Social Equity And Resilience. J. Secur. Intell. Resil. Educ. 2023, 17, 1–13. [Google Scholar]
  50. Chandra, A.; Bugliari, D.; May, L.W.; Weilant, S.; Nelson, C.; Martin, L.T.; Yeung, D.; Miller, C. 2023 National Survey of Health Attitudes; Description and Top-Line Summary Data; RAND Corporation: Santa Monica, CA, USA, 2024; Available online: www.rand.org/t/RRA3303-1 (accessed on 20 August 2025).
  51. Chandra, A. National Survey of Health Attitudes, [United States], 2023: Version 1 2024; ICPSR—Interuniversity Consortium for Political and Social Research: Ann Arbor, MI, USA, 2024. [Google Scholar] [CrossRef]
  52. Brown, G.D.; Largey, A.; McMullan, C. The impact of gender on risk perception: Implications for EU member states’ national risk assessment processes. Int. J. Disaster Risk Reduct. 2021, 63, 102452. [Google Scholar] [CrossRef]
  53. Wester, M.; Alfaro, E.S.; Lama, P.D. Gender Differences in Risk Perception: A Review. In Oxford Research Encyclopedia of Natural Hazard Science; Oxford University Press: Oxford, UK, 2024. [Google Scholar]
  54. Partey, S.T.; Dakorah, A.D.; Zougmoré, R.B.; Ouédraogo, M.; Nyasimi, M.; Nikoi, G.K.; Huyer, S. Gender and climate risk management: Evidence of climate information use in Ghana. Clim. Chang. 2020, 158, 61–75. [Google Scholar] [CrossRef]
  55. Henwood, K.L.; Anne Parkhill, K.; Pidgeon, N.F. Science, technology and risk perception: From gender differences to the effects made by gender. Equal. Oppor. Int. 2008, 27, 662–676. [Google Scholar] [CrossRef]
  56. Wang, C.; Geng, L.; Rodríguez-Casallas, J.D. How and when higher climate change risk perception promotes less climate change inaction. J. Clean. Prod. 2021, 321, 128952. [Google Scholar] [CrossRef]
  57. Lujala, P.; Lein, H.; Rød, J.K. Climate change, natural hazards, and risk perception: The role of proximity and personal experience. Local Environ. 2015, 20, 489–509. [Google Scholar] [CrossRef]
  58. Momsen, J.H. Gender Differences in Environmental Concern and Perception. J. Geogr. 2000, 99, 47–56. [Google Scholar] [CrossRef]
  59. Echavarren, J.M. The Gender Gap in Environmental Concern: Support for an Ecofeminist Perspective and the Role of Gender Egalitarian Attitudes. Sex Roles 2023, 89, 610–623. [Google Scholar] [CrossRef]
  60. Riechard, D.E.; Peterson, S.J. Perception of Environmental Risk Related to Gender, Community Socioeconomic Setting, Age, and Locus of Control. J. Environ. Educ. 1998, 30, 11–19. [Google Scholar] [CrossRef]
  61. Ergun, S.J.; Karadeniz, Z.D.; Rivas, M.F. Climate change risk perception in Europe: Country-level factors and gender differences. Humanit. Soc. Sci. Commun. 2024, 11, 1573. [Google Scholar] [CrossRef]
  62. Carlton, S.J.; Jacobson, S.K. Climate change and coastal environmental risk perceptions in Florida. J. Environ. Manag. 2013, 130, 32–39. [Google Scholar] [CrossRef]
  63. Bord, J.; O’Connor, R.E. The Gender Gap in Environmental Attitudes: The Case of Perceived Vulnerability to Risk. Soc. Sci. Q. 1997, 78, 830–840. [Google Scholar]
  64. Ekholm, S. Swedish mothers’ and fathers’ worries about climate change: A gendered story. J. Risk Res. 2020, 23, 288–296. [Google Scholar] [CrossRef]
  65. Ekholm, S.; Olofsson, A. Parenthood and Worrying About Climate Change: The Limitations of Previous Approaches. Risk Anal. 2017, 37, 305–314. [Google Scholar] [CrossRef]
  66. Ergun, S.J.; Khan, M.U.; Rivas, M.F. Factors affecting climate change concern in Pakistan: Are there rural/urban differences? Environ. Sci. Pollut. Res. 2021, 28, 34553–34569. [Google Scholar] [CrossRef]
  67. Amin, S.M.; El-Sayed, M.M.; Abo-Hatab, T.A.E.; El-Monshed, A.H.; Atta, M.H.R. Empowering Women for a Changing Climate: Exploring the Role of Environmental Literacy in Shaping Risk Perception and Climate Capability in Reproductive-Age Women. Public Health Nurs. 2025, 42, 1813–1825. [Google Scholar] [CrossRef] [PubMed]
  68. Girardi, G.; Bremer, A.A. Effects of Climate and Environmental Changes on Women’s Reproductive Health. J. Women’s Health 2022, 31, 755–757. [Google Scholar] [CrossRef] [PubMed]
  69. Amin, S.M.; El-Monshed, A.H.; Khedr, M.A.; Awad, A.G.E.; Atta, M.H.R. The Association between Emotional Responses to Climate Change, Antenatal Anxiety and Maternal–Fetal Attachment in Primigravida Women. J. Adv. Nurs. 2025, 81, 8242–8255. [Google Scholar] [CrossRef] [PubMed]
  70. Asteria, D.; Herdiansyah, H.; Apriana, I.W.A. Women’s Environmental Literacy As Social Capital In Environmental Management For Environmental Security of Urban Area. IOP Conf. Ser. Earth Environ. Sci. 2016, 30, 012014. [Google Scholar] [CrossRef]
  71. Adeola, F.O. Nativity and Environmental Risk Perception: An Empirical Study of Native-Born and Foreign-Born Residents of the USA. Hum. Ecol. Rev. 2007, 14, 13–25. [Google Scholar]
  72. Burger, J.; Myers, O.; Boring, C.S.; Dixon, C.; Lord, C.; Ramos, R.; Shukla, S.; Gochfeld, M. Perceptions of general environmental problems, willingness to expend federal funds on these problems, and concerns regarding the Los Alamos national laboratory: Hispanics are more concerned than Whites. Environ. Res. 2004, 95, 174–183. [Google Scholar] [CrossRef]
  73. Greenberg, M.R. Concern about Environmental Pollution: How Much Difference Do Race and Ethnicity Make? A New Jersey Case Study. Environ. Health Perspect. 2005, 113, 369–374. [Google Scholar] [CrossRef]
  74. Finucane, M.L.; Slovic, P.; Mertz, C.K.; Flynn, J.; Satterfield, T.A. Gender, race, and perceived risk: The “white male” effect. Health Risk Soc. 2000, 2, 159–172. [Google Scholar] [CrossRef]
  75. Macias, T. Environmental risk perception among race and ethnic groups in the United States. Ethnicities 2016, 16, 111–129. [Google Scholar] [CrossRef]
  76. Flynn, J.; Slovic, P.; Mertz, C.K. Gender, Race, and Perception of Environmental Health Risks. Risk Anal. 1994, 14, 1101–1108. [Google Scholar] [CrossRef]
  77. Gilbert, C.; Lachlan, K. Media Effects, Emotion, and Race: Extending the Climate Change Risk Perception Model in the United States. Environ. Commun. 2025, 19, 1–21. [Google Scholar] [CrossRef]
  78. Elias, T.; Dahmen, N.S.; Morrison, D.D.; Morrison, D.; Morris, D.L. Understanding Climate Change Perceptions and Attitudes Across Racial/Ethnic Groups. Howard J. Commun. 2019, 30, 38–56. [Google Scholar] [CrossRef]
  79. White, L. The Historical Roots of Our Ecologic Crisis. Science 1967, 155, 1203–1207. [Google Scholar] [CrossRef] [PubMed]
  80. Konisky, D.M. The greening of Christianity? A study of environmental attitudes over time. Environ. Politics 2018, 27, 267–291. [Google Scholar] [CrossRef]
  81. Guth, J.L.; Green, J.C.; Kellstedt, L.A.; Smidt, C.E. Faith and the Environment: Religious Beliefs and Attitudes on Environmental Policy. Am. J. Political Sci. 1995, 39, 364. [Google Scholar] [CrossRef]
  82. Smith, N.; Leiserowitz, A. American evangelicals and global warming. Glob. Environ. Chang. 2013, 23, 1009–1017. [Google Scholar] [CrossRef]
  83. Tsimpo, C.; Wodon, Q. Faith Affiliation, Religiosity, and Attitudes Towards the Environment and Climate Change. Rev. Faith Int. Aff. 2016, 14, 51–64. [Google Scholar] [CrossRef]
  84. Haluza-DeLay, R. Religion and climate change: Varieties in viewpoints and practices. WIREs Clim. Chang. 2014, 5, 261–279. [Google Scholar] [CrossRef]
  85. Zaleha, B.D.; Szasz, A. Why conservative Christians don’t believe in climate change. Bull. At. Sci. 2015, 71, 19–30. [Google Scholar] [CrossRef]
  86. Clements, J.M.; Xiao, C.; McCright, A.M. An Examination of the “Greening of Christianity” Thesis Among Americans, 1993–2010. Sci. Study Relig. 2014, 53, 373–391. [Google Scholar] [CrossRef]
  87. Mazaheri, N. Faith in Science: Religion and Climate Change Attitudes in the Middle East. Glob. Environ. Politics 2024, 24, 52–75. [Google Scholar] [CrossRef]
  88. Morrison, M.; Duncan, R.; Parton, K. Religion Does Matter for Climate Change Attitudes and Behavior. PLoS ONE 2015, 10, e0134868. [Google Scholar] [CrossRef] [PubMed]
  89. Morote, Á.-F.; Sebastiá-Álcaraz, R.; Ferrero-Punzano, S.M.; Miguel-Revilla, D.; Moreno-Vera, J.R.; Rodríguez-Pizzinato, L.A.; García, Ó.J. Climate Change, Education, Training, and Perception of Pre-Service Teachers. Soc. Sci. 2025, 14, 236. [Google Scholar] [CrossRef]
  90. Bentley, R.A.; Horne, B.D. Perceptible climate warming amplifies how education increases climate concern in the US. npj Clim. Action 2025, 4, 12. [Google Scholar] [CrossRef]
  91. Sun, Y.; Han, Z. Climate Change Risk Perception in Taiwan: Correlation with Individual and Societal Factors. Int. J. Environ. Res. Public Health 2018, 15, 91. [Google Scholar] [CrossRef]
  92. Fang, S.-C.; Yu, T.-Y. A Risk Perception Model of Climate Change for University Students. J. Balt. Sci. Educ. 2015, 14, 339–350. [Google Scholar] [CrossRef]
  93. Bruine De Bruin, W.; Dugan, A. On the differential correlates of climate change concerns and severe weather concerns: Evidence from the World Risk Poll. Clim. Chang. 2022, 171, 33. [Google Scholar] [CrossRef]
  94. Shi, J.; Visschers, V.H.M.; Siegrist, M.; Arvai, J. Knowledge as a driver of public perceptions about climate change reassessed. Nat. Clim. Chang. 2016, 6, 759–762. [Google Scholar] [CrossRef]
  95. Poortinga, W.; Whitmarsh, L.; Steg, L.; Böhm, G.; Fisher, S. Climate change perceptions and their individual-level determinants: A cross-European analysis. Glob. Environ. Chang. 2019, 55, 25–35. [Google Scholar] [CrossRef]
  96. Simpson, N.P.; Andrews, T.M.; Krönke, M.; Lennard, C.; Odoulami, R.C.; Ouweneel, B.; Steynor, A.; Trisos, C.H. Climate change literacy in Africa. Nat. Clim. Chang. 2021, 11, 937–944. [Google Scholar] [CrossRef]
  97. Selm, K.R.; Peterson, M.N.; Hess, G.R.; Beck, S.M.; McHale, M.R. Educational attainment predicts negative perceptions women have of their own climate change knowledge. PLoS ONE 2019, 14, e0210149. [Google Scholar] [CrossRef]
Table 1. Factor loadings and uniqueness for the climate change risk perception index.
Table 1. Factor loadings and uniqueness for the climate change risk perception index.
ItemsFactor LoadingKMO
Climate change impacts of public health0.870.90
Climate change is harming/will harm my community0.870.91
Business should do more to address climate change0.900.89
Communities should do more to address climate change0.910.88
The government should do more to address climate change0.890.92
Eigenvalue3.95
Cronbach’s alpha0.95
Kaiser–Meyer–Olkin (KMO) measure0.90
Table 2. Sociodemographic description (n = 5620).
Table 2. Sociodemographic description (n = 5620).
IndicatorsGenderPearson Chi-Square
Male (%)Female (%)Total (n)
Race/Ethnicity
Non-Hispanic White25.0525.37283414.42 **
Non-Hispanic African American8.7011.321125
Hispanic10.6810.891212
Non-Hispanic Asian and Pacific Islanders2.882.78318
Non-Hispanic Others1.091.25131
Marital
Never married12.4612.9714290.26
Others35.9438.634191
Education
Have a college degree21.9820.21237122.35 ***
Don’t have a college26.4231.393249
Religion in Life
Not important25.5320.57259194.70 ***
Important22.8631.033029
Census region
Northeast8.178.709485.06
Midwest8.709.651031
South18.8121.02237
West12.7112.261404
Chronic health conditions
Yes24.3427.9029368.15 **
No24.0623.702684
Community well-being
Poor7.219.5294012.83 **
Good41.1942.084680
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table 3. Climate change risk perception index models.
Table 3. Climate change risk perception index models.
Independent VariablesCoefficients
(SE)
Unadjusted Model		Coefficients
(SE)
Adjusted Model
Gender (Female)0.21 ***
(0.03)		0.25 ***
(0.02)
Race (African American)0.28 ***
(0.03)		0.32 ***
(0.03)
Marital status (Never married)0.17 ***
(0.03)		0.11 ***
(0.03)
Education (College degree)0.15 ***
(0.03)		0.19 ***
(0.03)
Religion in life (Not important)0.31 ***
(0.03)		0.35 ***
(0.03)
Census region (Northeast)0.17 ***
(0.03)		0.12 ***
(0.03)
Chronic health condition (Yes)0.09 ***
(0.03)		0.09 ***
(0.03)
Community wellbeing (Poor)0.14 ***
(0.03)		0.09 **
(0.03)
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table 4. Intersectional identities and climate change risk perception (OLS model).
Table 4. Intersectional identities and climate change risk perception (OLS model).
Independent VariablesCoefficients
(SE)
Gender (Female)0.36 ***
(0.04)
Race (African American)0.44 ***
(0.05)
African American female−0.19 **
(0.06)
Religion in life (Not important)0.43 ***
(0.04)
Female with religion non-importance−0.14 **
(0.05)
Marital status (Never married)0.13 **
(0.04)
Never married female−0.04
(0.06)
Education (College degree)0.16 ***
(0.04)
Female with a college degree0.04
(0.05)
Constant2.43 ***
(0.03)
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table 5. Intersectional identities and climate change risk perception (marginal effect model).
Table 5. Intersectional identities and climate change risk perception (marginal effect model).
Independent VariablesMargin
(SE)
Male from other racial groups2.72 ***
(0.02)
African American male3.16 ***
(0.04)
Female from other racial groups3.02 ***
(0.02)
African American female3.27 ***
(0.04)
Male with religion importance2.62 ***
(0.03)
Male with religion non-importance3.04 ***
(0.02)
Female with religion importance2.94 ***
(0.02)
Female with religion non-importance3.22 ***
(0.03)
Male with other marital status2.77 ***
(0.02)
Never married male2.91 ***
(0.04)
Female with other marital status3.05 ***
(0.03)
Never married female3.14 ***
(0.04)
Male with no college degree2.74 ***
(0.02)
Male with a college degree2.91 ***
(0.03)
Female with no college degree2.98 ***
(0.02)
Female with a college degree3.19 ***
(0.03)
* p < 0.05, ** p < 0.01, *** p < 0.001.
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Chisty, M.A. The Social Distribution of Climate Change Risk Perception: Unraveling Intersectional Patterns of Concern in the United States. Climate 2026, 14, 58. https://doi.org/10.3390/cli14020058

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Chisty, M. A. (2026). The Social Distribution of Climate Change Risk Perception: Unraveling Intersectional Patterns of Concern in the United States. Climate, 14(2), 58. https://doi.org/10.3390/cli14020058

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