Will a Rising Tide Sink All Boats? Examining the Unequal Distribution and Health Impact of Extreme Weather Events

Abstract

Background: Climate change is intensifying and poses an increased threat to health. However, limited attention has been paid to the social patterning of exposure to extreme weather events, specifically among socially marginalized communities such as people with disabilities, LGBTQ people, those in rural areas, and racialized minorities.

Methods: Data from the 2023 California Health Interview Survey, a survey of California adults, were used to examine if exposure to any extreme weather events varied across a range of sociodemographic and health-related characteristics (e.g., sexual orientation, race/ethnicity, gender, rurality, have any health conditions), and if these exposures to these weather-related events were associated with physical or mental health impacts for anyone in the household. Multivariable logistic regression models were used.

Results: Respondents who identified as American Indian or Alaska Native, bisexual and pansexual, lower income, completed some college or more, living in rural areas, had a health condition, having experienced psychological distress, or had a disability had higher odds of reporting that someone in their household had experienced an extreme weather event. In terms of health harm from weather events, bisexual people, pansexual people, transgender people, people with disabilities, people with health conditions, and those living in rural areas were more likely to experience harm.

Discussion: Human-fueled climate change is set to have devastating impacts on health in the coming decades. This study suggests that these impacts will disproportionately fall on structurally marginalized communities.

BACKGROUND

Overview of climate change: heat waves, fires, and floods

Climate change is intensifying the frequency and severity of extreme weather events, including heat waves, wildfires, and floods, with significant consequences across the United States and on global scales.¹ In California, these climate-related hazards have become increasingly pronounced, as rising temperatures exacerbate droughts, fuel record-breaking wildfires, and increase risk for a mega flood in the region.² From 1972 to 2018, the incidence of wildfires increased 5-fold, and in the past century, the California coast has seen an increase of 8 inches in sea level.³ The state’s vulnerability is amplified by its dense urban populations, high levels of economic inequality, and a reliance on agriculture that faces existential threats from shifting climate patterns.⁴ California is predicted to experience warming of 3°C–5°C and sea level rise by up to 3 meters (9.8 feet) by the century’s end, contingent on emission reductions, worsening hydrological extremes like droughts, and wildfire risk.⁶ Assessments by the State of California predict that sea level rise will consume 31%–67% of beaches in Southern California if no adaptations are implemented.⁵ These trends are accompanied by critical biodiversity impacts, as rising temperatures impact regional hydrology patterns, expand environmental boundaries for pathogens to thrive, and create uninhabitable and unpredictable living conditions.⁶

Although extensive research has quantified the biophysical environmental impacts of these events,⁷ less attention has been paid to the uneven distribution of exposure across social groups. Socially marginalized communities—including low-income populations, disabled individuals, and racially minoritized peoples—are particularly vulnerable due to historical patterns of segregation, infrastructure disparities, and limited access to adaptive resources such as cooling centers and transportation during heat waves.⁸ The concentration of extreme weather burdens in these populations raises urgent questions about social inequality in climate risk.⁹

Socially patterned health impacts of exposure to climate change events

Social vulnerability studies indicate that health impacts from climate change also disproportionately affect structurally disadvantaged populations. For instance, exposure to heat-island effects in urban areas, where impervious surfaces dominate and tree cover is sparse, is more prevalent in low-income and minority neighborhoods.¹⁰ Similarly, wildfire smoke and the mental health stress associated with repeated climate disasters contribute to rising rates of anxiety, post-traumatic stress disorder, and respiratory conditions in these communities.¹¹ Research on disaster recovery highlights systemic inequities: following Hurricane Katrina, African American evacuees housed in shelters faced heightened physical and emotional stress due to limited access to health care, housing, and evacuation resources, underscoring the compounded vulnerabilities of marginalized groups.¹² More broadly, people of color disproportionately experience the health impacts of climate change.¹³

Theoretical approaches to understand the inequitable health impacts of climate change have been drawn from multiple frameworks, including environmental justice, social determinants of health, and critical sociology. Nevertheless, gaps remain in integrating these frameworks with health outcomes, particularly in understanding how structural inequities compound climate-related vulnerabilities.¹⁴ One theory not typically applied to understand the impacts of climate change is minority stress theory (MST). Originally developed to understand how stress impacts the health of sexual minorities,¹⁵ it has been extended to understand how stress impacts other marginalized groups.¹⁶ Briefly, MST argues that chronic social and environmental stressors can negatively impact health, if they exceed resources available to cope with them.¹⁷ Some of these stressors stem from being part of a marginalized community (i.e., racism, ableism, transphobia, and so on) and the efforts people undertake to cope with these (i.e., concealing identity, anticipating rejection, and so on) although others are not directly linked to being marginalized (i.e., broader social conditions). Applied to climate change, climate-related events are understood as additional contextual stressors that marginalized people have to deal with, on top of stress stemming from their marginalized status. Further, coping resources available to marginalized people may be limited because of the systemic barriers that they face, which can be heighten as a result of climate-related events. To date, MST has had limited application in understanding how the stressors of climate change interact with the stressors of holding a marginalized identity.¹⁸ We expand on this application not only to understand the vulnerabilities of structurally marginalized communities, including (but not limited to) LGBTQ individuals.

Current study

This study examines how the mental and physical health impacts of climate change are socially patterned, with a particular focus on differential exposure and vulnerability across demographic groups in California. Informed by MST, we hypothesize that marginalized communities will be more likely to experience the harms of climate change.

METHODS

Data source

Data for this study come from the 2023 California Health Interview Survey (CHIS), a survey overseen by the UCLA Center for Health Policy Research. Data were collected between January 30, 2023, and December 18, 2023.¹⁹ This time period immediately follows two major weather disasters in 2022 that resulted in a billion or more dollars in losses (wildfires and droughts with accompanying heat waves) and also covers flooding in that occurred in 2023 that resulted in a billion dollars or more in losses.²⁰ The CHIS sampled noninstitutionalized adults, aged 18 and older, living in California. Address-based sampling was used to recruit households to complete the CHIS either over the phone or online.²¹ In cases where there were multiple adults in a household, one adult was randomly selected to participate in the CHIS. Respondents were compensated with financial incentives for their time.²² The CHIS was collected with Institutional Review Board approval.

The CHIS researchers imputed most missing data from responses, except in cases where the responses were given via a proxy respondent (i.e., someone answering on behalf of a respondent). Proxy interviews did not receive the full CHIS questionnaire, as proxies cannot reliably report on some details of the respondent’s life.

A total of 23,697 adults completed the 2023 CHIS. Two analytical samples were derived from this. The first excluded 16 people who completed the interview via proxy, resulting in a sample of 21,655. The second was limited to the 14,307 respondents who had experienced an extreme weather event in the past two years and did not complete the CHIS via proxy.

Variables

Dependent variables captured exposure to and impacts of extreme weather events. Respondents were asked if they or someone in their household had experienced specific extreme weather events in the past two years. This was used to create dichotomous variables capturing experience of weather events: (1) experienced any extreme weather event; (2) experienced an extreme heat wave; (3) experienced a wildfire; (4) experienced smoke from wildfire; and (5) experienced a flood, mudslides, or rising sea levels. Respondents were specifically asked if they or someone in their household had experienced: heat waves, wildfires, smoke from wildfires, and floods/rising sea levels/mudslides. Among those who had experienced extreme weather events, respondents were asked if they had experienced physical or mental harm from specific events. This resulted in six dichotomous variables: (1) experienced mental health harm due to weather event; (2) experienced mental health harm due to heat wave; (3) experienced mental health harm due to smoke from wildfire; (4) experienced physical health harm due to weather event; (5) experienced physical health harm due to heat wave; and (6) experienced physical health harm due to smoke from wildfire. Both physical and mental harm were not explicitly defined for the respondent, so they were free to interpret these as they wanted.

Independent variables of interest consisted of social identities, health and disability measures, socioeconomic status measures, housing/household characteristics, and health care access. Social identities and demographic characteristics were measured using categorical variables. These were as follows: (1) Race and ethnicity (White; Black; Hispanic/Latinx; American Indian or Alaska Native; Asian; and Other race or multiracial); (2) gender (male or female); (3) sexual orientation (heterosexual; gay, lesbian or homosexual; bi- or pansexual; and don’t know/other/prefer not to say); (4) gender identity (cisgender; or transgender or gender non-conforming); (5) Citizenship status (U.S.-born citizen; naturalized citizen; and non-citizen); and (6) age (18–39; 40–64; or 65 and older). Measures of socioeconomic status were household income as a % of the federal poverty level (FPL; under 100% of FPL; 100%–199% of FPL; and 200% and above FPL) and educational attainment (high school or less and some college or more). Housing and household characteristics were as follows: (1) family size (1 person; 2 people; and 3 or more people), (2) lives in urban or rural area, and (3) housing type (house; duplex; building with 3 or more units; and mobile home). Measures of health and disability were as follows: (1) health status (fair or poor health; and good, very good, or excellent health); (2) psychological distress in the past year (no or yes); (3) having a disability (no or yes); and (4) having a health condition (no or yes). Finally, current insurance status (not insured or insured) was used to capture access to health care. In all cases, reference groups for variables in analyses are the first groups noted in parentheses in the description above.

ANALYSES

All analyses were conducted using Stata 18 using jackknife replicate weights to account for the design of the CHIS. Univariate statistics were calculated for all variables. Logistic regressions using the full sample were used to calculate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) of experiencing weather events in the past two years, using all independent variables. For the subsample of people who had experienced a weather event, AORs and 95% CIs of physical and mental health harm outcomes were calculated, using all independent variables.

RESULTS

Table 1 shows the weighted sample characteristics of the full sample and subsample. Most Californians had someone in their household experience an extreme weather event in the past two years (61.3%). Among the subsample who had someone in their household experience an extreme weather event, physical health harm from the event was more common than mental health harm (27.02% vs. 23.54%).

Table 1.

Sample Characteristics, California Health Interview Survey 2023

	Full sample (N = 21,655)		Sample that experienced extreme weather event in past 2 years (N = 14,307)
%	SE	%	SE
Experienced any extreme weather event in past 2 years	61.3	0.42	—	—
Experienced a heat wave	50.76	0.46	—	—
Experienced a wildfire	12.14	0.27	—	—
Experienced smoke from wildfire	41.36	0.39	—	—
Experienced flood, mudslides, or rising sea levels	6.75	0.25	—	—
Experienced any physical health harm from extreme weather event in past 2 years	—	—	27.02	0.57
Experienced physical health harm from heat wave	—	—	13.53	0.35
Experienced physical health harm from smoke from fire	—	—	19.84	0.55
Experienced any mental health harm from extreme weather event in past 2 years	—	—	23.54	0.48
Experienced mental health harm from heat wave	—	—	14.88	0.41
Experienced mental health harm from smoke from fire	—	—	13.31	0.38
Variable
Race and Ethnicity
Non-Hispanic White	37.88	0.04	44.05	0.36
Hispanic/Latinx	37.91	0.03	34.89	0.42
Black or African American	5.5	0.01	4.81	0.22
American Indian or Alaska Native	0.42	0.04	0.59	0.06
Asian	16.38	0.4	13.4	0.29
Other race or multiracial	1.91	0.04	2.26	0.09
Gender
Male	48.97	0.03	49.21	0.32
Female	51.03	0.03	50.79	0.32
Sexual orientation
Heterosexual	84.43	0.39	83.61	0.44
Gay, lesbian, or homosexual	3.35	0.14	3.82	0.19
Bisexual or pansexual	5.12	0.22	6.53	0.3
Don’t know/other/prefer not to say	7.09	0.27	6.04	0.31
Gender identity
Cisgender	98.65	0.12	98.22	0.15
Transgender or gender non-conforming	1.35	0.12	1.78	0.15
Citizenship status
U.S.-born citizen	67	0.37	74.98	0.45
Naturalized citizen	19.63	0.33	15.15	0.36
Non-citizen	13.36	0.3	9.87	0.36
Age
18–39	38.57	0.02	41.11	0.46
40–64	38.71	0.03	38.16	0.44
65 and over	22.72	0.04	20.73	0.3
Household income
Under 100% of federal poverty level	14.62	0.35	12.39	0.43
100%–199% of the federal poverty level	15.82	0.36	14.29	0.45
200% and above the federal poverty level	69.56	0.42	73.32	0.63
Educational attainment
High school or less	36.28	0.04	31.46	0.44
Some college or more	63.72	0.04	68.54	0.44
Family size
1 person	35.92	0.43	36.7	0.51
2 people	34.26	0.47	33.3	0.55
3 or more people	29.82	0.42	30	0.49
Lives in urban or rural area
Urban	70.35	0.13	66.9	0.42
Rural	29.65	0.13	33.1	0.42
Housing type
House	64.66	0.35	67.03	0.53
Duplex	5.48	0.26	4.87	0.32
Building with 3 or more units	26.63	0.33	24.97	0.45
Mobile home	3.23	0.19	3.13	0.26
Health status
Good, very good, or excellent	81.75	0.48	83.11	0.56
Fair or poor	18.25	0.48	16.89	0.56
Health condition
No	55.88	0.49	55.01	0.63
Yes	44.12	0.49	44.99	0.63
Psychological distress in past year
No	86.11	0.39	83.07	0.52
Yes	13.89	0.39	16.93	0.52
Disability
No	19.16	0.43	20.63	0.56
Yes	80.84	0.43	79.37	0.56
Currently insured
No	5.38	0.25	4.36	0.35
Yes	94.62	0.25	95.64	0.35

SE, standard error

Table 2 shows differences in AORs of experiencing extreme weather events in the past two years. Respondents who were American Indian or Alaska Native (AOR = 2.61; 95% CI = 1.10, 6.17), bi- and pansexual (AOR = 1.55; 95% CI = 1.23, 1.94), in households 200% or above the FPL (AOR = 1.32; 95% CI = 1.14, 1.53), had completed some college or more (AOR = 1.37; 95% CI = 1.22, 1.53), living in rural areas (AOR = 1.40; 95% CI = 1.26, 1.56), had a health condition (AOR = 1.15; 95% CI = 1.04, 1.27), experienced psychological distress (AOR = 2.66; 95% CI = 1.42, 1.94), or had a disability (AOR = 1.19; 95% CI = 1.04, 1.35) were more likely to report that someone in their household had experienced an extreme weather event than their respective reference groups. Conversely, respondents who were Hispanic/Latinx (AOR = 0.69; 95% CI = 0.61, 0.78), Asian (AOR = 0.57; 95% CI = 0.49, 0.67), naturalized citizens (AOR = 0.59; 95% CI = 0.53, 0.65), noncitizens (AOR = 0.56; 95% CI = 0.48, 0.66), living in a duplex (AOR = 0.82; 95% CI = 0.68, 0.98), or living in a building with 3 or more units (AOR = 0.82; 95% CI = 0.74, 0.91) were less likely to report that someone in their household had experienced an extreme weather event than their respective reference groups. For individual weather events the pattern of results varied.

Table 2.

Odds of Experiencing Extreme Weather Event in the Past 2 Years (N = 21,655)

Variable	Experienced any weather event		Experienced an extreme heat wave		Experienced a wildfire		Experienced smoke from wildfire		Experienced flood, mudslides, or rising sea levels
AOR	95% CI	AOR	95% CI	AOR	95% CI	AOR	95% CI	AOR	95% CI
Race and Ethnicity
Non-Hispanic White	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Hispanic/Latinx	0.69	(0.61, 0.78)	0.97	(0.85, 1.10)	0.64	(0.53, 0.76)	0.54	(0.48, 0.61)	0.84	(0.70, 1.00)
Black or African American	0.49	(0.41, 0.60)	0.65	(0.53, 0.78)	0.71	(0.47, 1.08)	0.53	(0.43, 0.65)	0.39	(0.27, 0.57)
American Indian or Alaska Native	2.61	(1.10, 6.17)	1.25	(0.67, 2.33)	4.35	(1.98, 9.56)	2.42	(1.32, 4.44)	1.69	(0.77, 3.69)
Asian	0.57	(0.49, 0.67)	0.76	(0.66, 0.87)	0.54	(0.44, 0.66)	0.55	(0.48, 0.64)	0.49	(0.37, 0.65)
Other race or multiracial	1.03	(0.79, 1.35)	1.07	(0.86, 1.34)	0.80	(0.60, 1.06)	1.07	(0.83, 1.39)	0.96	(0.66, 1.41)
Gender
Male	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Female	0.97	(0.91, 1.05)	1.04	(0.97, 1.13)	0.89	(0.79, 1.00)	0.92	(0.85, 0.99)	1.19	(1.02, 1.39)
Sexual orientation
Heterosexual	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Gay, lesbian, or homosexual	1.18	(0.91, 1.52)	1.23	(0.99, 1.53)	0.79	(0.57, 1.11)	1.16	(0.94, 1.43)	0.77	(0.54, 1.09)
Bisexual or pansexual	1.55	(1.23, 1.94)	1.38	(1.08, 1.77)	0.96	(0.70, 1.32)	1.25	(1.02, 1.53)	1.34	(1.03, 1.73)
Don’t know/other/prefer not to say	0.96	(0.79, 1.18)	0.91	(0.75, 1.11)	0.86	(0.65, 1.14)	0.91	(0.73, 1.14)	0.74	(0.49, 1.12)
Gender identity
Cisgender	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Transgender or gender non-conforming	1.59	(0.92, 2.77)	1.89	(1.20, 2.96)	1.09	(0.69, 1.72)	1.35	(0.93, 1.97)	0.57	(0.32, 1.03)
Citizenship status
U.S.-born citizen	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Naturalized citizen	0.59	(0.53, 0.65)	0.65	(0.59, 0.72)	0.91	(0.74, 1.12)	0.55	(0.48, 0.62)	0.86	(0.66, 1.12)
Non-citizen	0.56	(0.48, 0.66)	0.63	(0.54, 0.74)	0.86	(0.65, 1.15)	0.52	(0.43, 0.63)	0.51	(0.35, 0.76)
Age
18–39	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
40–64	0.95	(0.83, 1.09)	0.91	(0.81, 1.02)	0.89	(0.76, 1.04)	0.98	(0.88, 1.08)	0.61	(0.50, 0.73)
65 and over	0.64	(0.55, 0.74)	0.59	(0.51, 0.67)	0.55	(0.45, 0.66)	0.62	(0.55, 0.70)	0.36	(0.28, 0.45)
Household income
Under 100% of federal poverty level	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
100%–199% of the federal poverty level	1.13	(0.95, 1.34)	1.12	(0.97, 1.29)	1.26	(1.00, 1.58)	1.14	(0.93, 1.38)	0.94	(0.70, 1.28)
200% and above the federal poverty level	1.32	(1.14, 1.53)	1.20	(1.03, 1.38)	1.15	(0.93, 1.41)	1.40	(1.21, 1.61)	0.95	(0.75, 1.21)
Educational attainment
High school or less	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Some college or more	1.37	(1.22, 1.53)	1.21	(1.07, 1.36)	1.32	(1.12, 1.57)	1.44	(1.29, 1.61)	1.20	(1.02, 1.42)
Family size
1 person	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
2 people	0.97	(0.87, 1.07)	0.95	(0.86, 1.04)	1.13	(0.97, 1.31)	0.99	(0.89, 1.09)	1.05	(0.85, 1.30)
3 or more people	1.06	(0.94, 1.14)	1.07	(0.96, 1.19)	1.00	(0.85, 1.18)	1.08	(0.97, 1.20)	0.91	(0.73, 1.12)
Lives in urban or rural area
Urban	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Rural	1.40	(1.26, 1.56)	1.45	(1.31, 1.61)	2.04	(1.80, 2.32)	1.28	(1.16, 1.42)	0.93	(0.78, 1.11)
Housing type
House	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Duplex	0.82	(0.68, 0.98)	0.84	(0.71, 0.98)	0.96	(0.73, 1.25)	0.72	(0.60, 0.86)	0.79	(0.56, 1.11)
Building with 3 or more units	0.82	(0.74, 0.91)	0.90	(0.82, 0.99)	0.68	(0.58, 0.79)	0.72	(0.64, 0.81)	0.75	(0.63, 0.89)
Mobile home	0.96	(0.70, 1.33)	1.10	(0.81, 1.51)	1.17	(0.86, 1.59)	0.94	(0.70, 1.26)	1.07	(0.73, 1.57)
Health status
Good, very good, or excellent	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Fair or poor	0.96	(0.84, 1.09)	0.98	(0.87, 1.10)	1.03	(0.87, 1.21)	0.95	(0.84, 1.07)	1.10	(0.90, 1.34)
Health condition
No	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Yes	1.15	(1.04, 1.27)	1.19	(1.08, 1.31)	1.01	(0.89, 1.15)	1.10	(1.00, 1.20)	1.05	(0.89, 1.22)
Psychological distress in past year
No	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Yes	1.66	(1.42, 1.94)	1.61	(1.39, 1.86)	1.42	(1.16, 1.74)	1.52	(1.32, 1.74)	1.37	(1.12, 1.67)
Disability
No	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Yes	1.19	(1.04, 1.35)	1.19	(1.05, 1.35)	1.34	(1.14, 1.58)	1.13	(1.00, 1.28)	1.20	(1.00, 1.43)
Currently insured
No	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Yes	1.24	(0.99. 1.56)	1.32	(1.05. 1.66)	1.21	(0.84, 1.76)	1.26	(0.96, 1.66)	0.86	(0.57, 1.28)

Significant associations in bold.

Ref, references; AOR, adjusted odds ratio; 95% CI, 95% confidence interval.

Table 3 shows differences in AORs of someone in the household experiencing physical health harm from extreme weather events. Respondents who were: bi or pan (AOR = 1.29; 95% CI = 1.05, 1.58), had completed some college or more (AOR = 1.40; 95% CI = 1.22, 1.60), living in rural areas (AOR = 1.17; 95% CI = 1.04, 1.31), living in a duplex (AOR = 1.41; 95% CI = 1.16, 1.72), had a health condition (AOR = 1.42; 95% CI = 1.25, 1.61), experienced psychological distress (AOR = 1.75; 95% CI = 1.49, 1.61), or had a disability (AOR = 1.41; 95% CI = 1.23, 1.61) were more likely to report physical health harm due to a weather event than their counterparts. Conversely, respondents who were: Latinx (AOR = 0.69; 95% CI = 0.61, 0.78), non-citizens (AOR = 0.56; 95% CI = 0.48, 0.66), or 65 and older (AOR = 0.73; 95% CI = 0.58, 0.90) were less likely to report physical health harm from extreme weather event than their counterparts. For individual weather events the pattern of results varied.

Table 3.

Odds of Experiencing Physical Health Harm From Extreme Weather Event (N = 14,307)

Variable	Health harmed due to any event		Health harmed due to heat wave		Health harmed due to smoke from fire
AOR	95% CI	AOR	95% CI	AOR	95% CI
Race and Ethnicity
Non-Hispanic White	Reference	Reference	Reference	Reference	Reference	Reference
Hispanic/Latinx	0.73	(0.62, 0.86)	0.95	(0.75, 1.19)	0.56	(0.47, 0.65)
Black or African American	1.17	(0.89, 1.55)	1.14	(0.74, 1.74)	1.02	(0.72, 1.45)
American Indian or Alaska Native	1.65	(0.65, 4.18)	2.15	(0.45, 10.35)	1.71	(0.58, 5.00)
Asian	0.87	(0.72, 1.05)	0.92	(0.73, 1.15)	0.84	(0.68, 1.03)
Other race or multiracial	0.83	(0.61, 1.12)	1.29	(0.86, 1.93)	0.63	(0.46, 0.84)
Gender
Male	Reference	Reference	Reference	Reference	Reference	Reference
Female	1.08	(0.97, 1.20)	1.07	(0.91, 1.25)	1.04	(0.93, 1.17)
Sexual orientation
Heterosexual	Reference	Reference	Reference	Reference	Reference	Reference
Gay, lesbian, or homosexual	1.03	(0.79, 1.34)	0.99	(0.69, 1.41)	0.91	(0.69, 1.18)
Bisexual or pansexual	1.29	(1.05, 1.58)	1.19	(0.90, 1.58)	1.28	(0.99, 1.67)
Don’t know/other/prefer not to say	0.72	(0.56, 0.93)	0.67	(0.48, 0.93)	0.85	(0.66, 1.10)
Gender identity
Cisgender	Reference	Reference	Reference	Reference	Reference	Reference
Transgender or gender non-conforming	1.46	(0.98, 2.18)	1.43	(0.91, 2.24)	0.93	(0.55, 1.55)
Citizenship status
U.S.-born citizen	Reference	Reference	Reference	Reference	Reference	Reference
Naturalized citizen	0.86	(0.71, 1.03)	1.20	(0.95, 1.53)	0.77	(0.64, 0.93)
Non-citizen	0.73	(0.59, 0.91)	0.98	(0.73, 1.33)	0.61	(0.44, 0.84)
Age
18–39	Reference	Reference	Reference	Reference	Reference	Reference
40–64	1.06	(0.91, 1.24)	0.84	(0.68, 1.04)	1.05	(0.90, 1.22)
65 and over	0.73	(0.58, 0.90)	0.60	(0.45, 0.79)	0.71	(0.57, 0.89)
Household income
Under 100% of federal poverty level	Reference	Reference	Reference	Reference	Reference	Reference
100%–199% of the federal poverty level	1.04	(0.82, 1.33)	0.85	(0.65, 1.12)	1.15	(0.86, 1.53)
200% and above the federal poverty level	0.87	(0.73, 1.04)	0.58	(0.46, 0.73)	1.23	(0.99, 1.53)
Educational attainment
High school or less	Reference	Reference	Reference	Reference	Reference	Reference
Some college or more	1.40	(1.22, 1.60)	1.14	(0.93, 1.39)	1.55	(1.33, 1.81)
Family size
1 person	Reference	Reference	Reference	Reference	Reference	Reference
2 people	1.08	(0.92, 1.27)	1.02	(0.82, 1.28)	1.11	(0.95, 1.30)
3 or more people	1.08	(0.93, 1.24)	1.10	(0.90, 1.35)	1.07	(0.92, 1.25)
Lives in urban or rural area
Urban	Reference	Reference	Reference	Reference	Reference	Reference
Rural	1.17	(1.04, 1.31)	1.08	(0.92, 1.25)	1.19	(1.03, 1.37)
Housing type
House	Reference	Reference	Reference	Reference	Reference	Reference
Duplex	1.41	(1.16, 1.72)	1.33	(0.92, 1.92)	1.08	(0.84, 1.38)
Building with 3 or more units	0.95	(0.81, 1.12)	1.25	(1.02, 1.53)	0.86	(0.72, 1.01)
Mobile home	1.30	(0.91, 1.86)	1.32	(0.78, 2.22)	1.27	(0.92, 1.75)
Health status
Good, very good, or excellent	Reference	Reference	Reference	Reference	Reference	Reference
Fair or poor	0.97	(0.84, 1.11)	1.04	(0.92, 1.23)	0.91	(0.79, 1.04)
Health condition
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.42	(1.25, 1.61)	1.52	(1.26, 1.82)	1.34	(1.17, 1.53)
Psychological distress in past year
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.75	(1.49, 2.06)	1.90	(1.53, 2.35)	1.48	(1.25, 1.76)
Disability
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.41	(1.23, 1.61)	1.64	(1.35, 1.99)	1.28	(1.10, 1.49)
Currently insured
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.21	(0.81, 1.80)	0.85	(0.52, 1.39)	1.83	(1.09, 3.08)

Significant associations in bold.

Table 4 shows differences in AORs of someone in the household experiencing mental health harm from extreme weather events. Respondents who were: women (AOR = 1.15; 95% CI = 1.02, 1.30), bi- and pansexual (AOR = 1.94; 95% CI = 1.54, 2.43), trans and gender non-conforming (AOR = 3.34; 95% CI = 2.28, 4.90), had completed some college or more (AOR = 1.52; 95% CI = 1.31, 1.76), living in rural areas (AOR = 1.18; 95% CI = 1.04, 1.34), experienced psychological distress (AOR = 2.25; 95% CI = 1.91, 2.66), or had a disability (AOR = 1.43; 95% CI = 1.21, 1.68) were more likely to report mental health harm due to a weather event than their counterparts. Conversely, respondents who were Latinx (AOR = 0.64; 95% CI = 0.54, 0.77), Black (AOR = 0.68; 95% CI = 0.49, 0.93), Asian (AOR = 0.64; 95% CI = 0.53, 0.79), non-citizens (AOR = 0.60; 95% CI = 0.44, 0.81), ages 40–64 (AOR = 0.82; 95% CI = 0.71, 0.94), or ages 65 and older (AOR = 0.58; 95% CI = 0.49, 0.69) were less likely to report mental health harm from extreme weather event than their counterparts. For individual weather events, the pattern of results varied.

Table 4.

Odds of Experiencing Mental Health Harm From Extreme Weather Event (N = 14,307)

Variable	Health harmed due to any event		Health harmed due to heat wave		Health harmed due to smoke from fire
AOR	95% CI	AOR	95% CI	AOR	95% CI
Race and Ethnicity
Non-Hispanic White	Reference	Reference	Reference	Reference	Reference	Reference
Hispanic/Latinx	0.64	(0.54, 0.77)	0.81	(0.68, 0.98)	0.55	(0.45, 0.67)
Black or African American	0.68	(0.49, 0.93)	0.88	(0.59, 1.32)	0.63	(0.37, 1.05)
American Indian or Alaska Native	1.98	(0.81, 4.85)	0.65	(0.35, 1.21)	2.99	(1.03, 8.63)
Asian	0.64	(0.53, 0.79)	0.71	(0.55, 0.91)	0.67	(0.53, 0.84)
Other race or multiracial	0.73	(0.56, 0.96)	0.67	(0.51, 0.89)	0.84	(0.60, 1.18)
Gender
Male	Reference	Reference	Reference	Reference	Reference	Reference
Female	1.15	(1.02, 1.30)	1.18	(1.01, 1.39)	0.94	(0.81, 1.08)
Sexual orientation
Heterosexual	Reference	Reference	Reference	Reference	Reference	Reference
Gay, lesbian, or homosexual	1.13	(0.84, 1.52)	1.18	(0.83, 1.66)	1.02	(0.71, 1.45)
Bisexual or pansexual	1.94	(1.54, 2.43)	1.57	(1.24, 2.00)	2.10	(1.65, 2.69)
Don’t know/other/prefer not to say	0.81	(0.63, 1.05)	0.95	(0.69, 1.30)	1.18	(0.89, 1.57)
Gender identity
Cisgender	Reference	Reference	Reference	Reference	Reference	Reference
Transgender or gender non-conforming	3.34	(2.28, 4.90)	2.63	(1.81, 3.83)	1.59	(1.00, 2.54)
Citizenship status
U.S.-born citizen	Reference	Reference	Reference	Reference	Reference	Reference
Naturalized citizen	0.98	(0.81, 1.18)	1.18	(0.93, 1.52)	0.96	(0.76, 1.22)
Non-citizen	0.60	(0.44, 0.81)	0.63	(0.42, 0.96)	0.51	(0.36, 0.73)
Age
18–39	Reference	Reference	Reference	Reference	Reference	Reference
40–64	0.82	(0.71, 0.94)	0.71	(0.59, 0.85)	0.96	(0.81, 1.51)
65 and over	0.58	(0.49, 0.69)	0.49	(0.39, 0.62)	0.70	(0.60, 0.83)
Household income
Under 100% of federal poverty level	Reference	Reference	Reference	Reference	Reference	Reference
100%–199% of the federal poverty level	0.79	(0.60, 1.05)	0.69	(0.51, 0.93)	0.93	(0.66, 1.30)
200% and above the federal poverty level	0.84	(0.70, 1.00)	0.70	(0.57, 0.86)	1.19	(0.91, 1.57)
Educational attainment
High school or less	Reference	Reference	Reference	Reference	Reference	Reference
Some college or more	1.52	(1.31, 1.76)	1.31	(1.08, 1.59)	1.77	(1.44, 2.19)
Family size
1 person	Reference	Reference	Reference	Reference	Reference	Reference
2 people	1.12	(0.95, 1.33)	1.10	(0.90, 1.34)	1.00	(0.82, 1.22)
3 or more people	1.09	(0.93, 1.27)	1.04	(0.86, 1.27)	1.05	(0.86, 1.28)
Lives in urban or rural area
Urban	Reference	Reference	Reference	Reference	Reference	Reference
Rural	1.18	(1.04, 1.34)	1.09	(0.91, 1.29)	1.21	(1.06, 1.39)
Housing type
House	Reference	Reference	Reference	Reference	Reference	Reference
Duplex	1.10	(0.87, 1.40)	1.20	(0.91, 1.60)	1.01	(0.73, 1.38)
Building with 3 or more units	1.05	(0.91, 1.21)	1.17	(1.00, 1.38)	0.90	(0.76, 1.06)
Mobile home	1.10	(0.78, 1.55)	0.84	(0.55, 1.27)	0.86	(0.55, 1.43)
Health status
Good, very good, or excellent	Reference	Reference	Reference	Reference	Reference	Reference
Fair or poor	1.06	(0.91, 1.24)	1.11	(0.90, 1.36)	1.02	(0.85, 1.24)
Health condition
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.10	(0.98, 1.25)	1.17	(1.02, 1.36)	1.03	(0.90, 1.17)
Psychological distress in past year
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	2.25	(1.91, 2.66)	2.23	(1.85, 2.68)	1.71	(1.37, 2.14)
Disability
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.43	(1.21, 1.68)	1.46	(1.19, 1.79)	1.32	(1.08, 1.60)
Currently insured
No	Reference	Reference	Reference	Reference	Reference	Reference
Yes	1.04	(0.71, 1.53)	0.95	(0.57, 1.60)	1.43	(1.05, 1.94)

Significant associations in bold.

DISCUSSION

The current study revealed two patterns of findings that are partially aligned with our MST-informed hypotheses: (1) exposure to extreme weather events is socially patterned, such that some marginalized groups have greater exposure (e.g., bi and pansexual individuals; people with disabilities; and American Indians and Alaska Natives); (2) the mental and physical health harms of extreme weather events disproportionately impact some socially marginalized groups. These disparities were more pronounced when examining mental health impacts of extreme weather events. Groups that experienced greater negative impacts included the following: bisexual, pansexual, transgender and gender non-conforming individuals; people living in rural areas; and those with existing health conditions or disabilities. Most of these associations were not previously examined in prior work with the CHIS.²³

Individuals with disabilities and health conditions were groups identified as more likely to both be exposed to climate events and experience health harm. Prior work has shown that people with disabilities and existing health conditions experience a myriad of physical and mental health impacts as a result of climate events,²⁴ with some studies showing inequitable trends such that health impacts are more common among people with disabilities.²⁵ This may be driven by several factors, including that disability can make evacuation more difficult, which is compounded by the limited support available to people with disabilities from government and nongovernment agencies.²⁶ As such, an equitable approach to addressing the impact of climate change must consider providing additional resources to people with disabilities. Resources could help people with disabilities be adequately equipped to mitigate the adverse impacts of climate change and navigate underlying structural ableism that creates built and social environments that disadvantage them in the first place.

This work revealed heightened vulnerability among groups that are not regularly highlighted in social epidemiological discourse on climate change, in particular findings for gender and sexual minorities. Specifically, we show that bi/pan individuals are more likely to report exposure to an extreme weather event and bi/pan and trans individuals were more likely to experience mental health impacts of climate events. This is consistent with MST that argues these groups deal with the stressors of homophobia and transphobia, on top of climate events, which could yield a level of stress beyond what available resources can address. However, most prior work on climate change has examined the factors that make LGBTQ people more vulnerable to the impacts of climate change (i.e., disasters forcing people out of the closet, bigotry, being blamed for natural disasters by religious communities, heteronormative assumptions by workers providing aid, destruction of LGBTQ spaces by disasters, and so on), but far less work has examined if (and how) LGBTQ people are more likely to be exposed to climate events and their impacts.²⁷ This increased exposure may be due to the fact that LGBTQ people are more likely to live in coastal, urban areas and in areas with poorer infrastructure²⁸ and may be more likely to experience homelessness due to factors like family rejection.²⁹ This contextualizes earlier work showing that LGBTQ individuals perceived greater threats from climate change and worry about climate change more than their cishet counterparts.³⁰ As such, this study highlights the unique needs of the LGBTQ community in the face of a growing climate crisis.

Importantly, there was nuance in associations we observed such that some marginalized groups were less likely to report exposure to or harm from climate events. For example, Hispanic/Latinx, Black, and non-citizen people were less likely to report mental health harm from climate events than White respondents, which is in contrast to prior work that broadly shows that people of color are more likely to be exposed to extreme weather events and experience harm.³¹ This may be due to the normalization of chronic, environmental stressors that racialized minority groups face on an everyday basis, thereby leading them to not appraise climate change events as particularly stressful in addition to interpersonal and structural racism or xenophobia. With regard to immigrants, there is a potentially complicated link with climate change, as people are increasingly migrating to the United States because of factors related to climate change in their countries of origin.³² Yet, in our findings, non-citizens were less likely to report experiencing a climate event and less likely to experience harm from climate events. Further, in contrast to prior work,³³ individuals with lower SES (household income and education) were less likely to experience any and specific extreme weather events (i.e., heat wave and smoke from wildfires), although sometimes also being less vulnerable to physical or mental health harm from some of these events. These findings may reflect the broader measures of harm from climate events that encapsulate the household, specifically, people may be forced into a new household in response to a climate event, and people of higher SES may be in a better position to take people into their homes after an event.

Findings should be interpreted with some limitations in mind. First, our measures of exposure to extreme climate events, and harm from them, were at the household level. Thus, the reports of harm reflect harm done to the homes of people with certain identities or social positions and reflect harm: (1) to the respondent; (2) household members; and (3) that is indirect or vicarious caused by witnessing harm in the household. Consistent with this, prior work has argued that harms from climate change come from both direct and indirect harm.³⁴ Second, data are cross-sectional so temporality cannot be established, which may be relevant if climate events lead to disability or other health conditions. Third, our data are specific to California residents whose geographic locations place them at risk for particular weather conditions that may be different from other locales. Fourth, some groups in the sample, like Black or non-heterosexual respondents, represent a small subgroup within the sample that may not be adequately powered to detect all differences. Finally, although CHIS collects data across the state of California, the publicly available data do not include geography, making it impossible to control for differential exposures to climate event due to physical location. Despite these limitations, this study adds to the limited work examining disparities in climate impacts in population-based studies and shows, in the same study, that people with disabilities, bi/pan, and transgender and gender non-conforming people are both more likely to experience climate events and more likely to suffer the negative health impacts from these.

Human-fueled climate change is set to devastate population health in the coming decades. This study suggests that these impacts will disproportionately fall on many structurally marginalized communities. As cross-sector initiatives attempt to mitigate the impacts of climate change, public health professionals must consider who is currently being left behind, so that we can strive for equity, even on a dying planet. This will be more pressing for some regions outside of the United States, which are projected to be more negatively impacted by climate change.³⁵

Footnotes

AUTHOR DISCLOSURE STATEMENT

No competing financial interests exist.

FUNDING INFORMATION

No funding was received for this article.

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