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Zhiyu Qian, Edoardo Beatrici, Quoc-Dien Trinh, Adam S Kibel, Stacy Loeb, Hari S Iyer, Alexander P Cole, Climate change perception and its association with cancer screening intent, JNCI: Journal of the National Cancer Institute, Volume 116, Issue 4, April 2024, Pages 618–622, https://doi.org/10.1093/jnci/djad237
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Abstract
As the climate crisis deepens, its adverse effects on human health are becoming evident, including impacts on cancer pathogenesis and treatment. This study explored the link between individuals’ awareness of the health impacts of climate change and interest in cancer screening. Using the 2021 Health Information National Trends Survey, our study demonstrated a statistically significant association between recognition of climate change as a personal health threat and interest in cancer screening. Although the study’s retrospective nature and self-reported data pose some limitations, these findings signal a promising avenue for future research on the intersection of climate and cancer risk. This research supports the development of public health interventions that incorporate components of environmental health literacy alongside cancer screening efforts.
As the climate crisis escalates, its impacts on human health are increasingly evident. Although a good deal of research has focused on environmental and economic consequences, a growing body of work is exploring its health implications, including cancer risks (1-5). The links between cancer and climate change are both direct and indirect. Ozone depletion and environmental contaminants linked to climate change elevate cancer risks, and extreme weather events disrupt health-care systems, affecting cancer care (4,6,7). Co–risk factors, such as meat consumption and sedentary lifestyles, are also climate related (8,9). As Rublee et al. (10) noted, climate change mitigation and adaptation is indeed cancer control and prevention.
Emerging research is examining how climate perceptions affect health behaviors, including cancer prevention (11). These behaviors include adaptations to climate change, such as building health systems that are sustainable and resilient to extreme weather events as well as embracing dietary and lifestyle changes that offer mutual benefits for both cancer prevention and climate mitigation (eg, plant-based dietary patterns and active commuting) (12). This approach to dual-purpose interventions resonates with existing research that highlights the positive impact of climate change mitigation and adaptation on overall human health (13).
This study explored the public’s understanding of climate change and its impact on cancer screening intentions. We hypothesized that lower climate awareness would correlate with reduced interest in cancer screening.
The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for cross-sectional studies. Data were sourced from the 2021 Health Information National Trends Survey (HINTS), a nationally representative survey administered by the National Cancer Institute that collects information about health behaviors and beliefs. The 2021 HINTS dataset (released May 2023), being the first year to incorporate climate change awareness, presents a unique opportunity to investigate the relationship between environmental consciousness and cancer-preventive health behaviors (14).
The study population comprised adults who completed the HINTS survey in 2021. Participants with missing data were excluded. The predictor variable categorized each respondent’s self-reported perception of climate change’s harm to their health (“no harm” or “a little harm” vs “some harm” or “a lot of harm”). The outcome measure assessed their interest in cancer screening for the next year. This measure was dichotomized into 2 categories (“not at all” and “a little” vs “somewhat” and “very”).
Age, sex at birth, self-reported race and ethnicity, education level, annual income, insurance coverage, marital and employment status, urban or rural residency, and smoking status were included and adjusted for in subsequent multivariable analyses. Descriptive statistics were calculated for all variables across the HINTS cohort. The Pearson χ2 test compared the baseline characteristics of each variable, and a multivariable logistic regression estimated the adjusted odds ratio between climate change awareness and interest in cancer screening. A sensitivity analysis was conducted that focused on respondents aged 50 to 70 years to align with the age ranges that most United States Preventive Services Task Force cancer screening guidelines recommend. Significance levels were set at a P value of .05. Analysis was performed using Stata, version 17 (StataCorp LP, College Station, TX). The study was performed under a general institutional review board protocol for using anonymized, publicly available surveys.
The baseline characteristics of our cohort are shown in Table 1. Unweighted proportions are presented in Supplementary Table 1 (available online). Just under half of the participants (46%) believed that climate change will either cause “no” or only “a little” harm to their health, while the majority (54%) anticipated that climate change will inflict “some” or “a lot” of harm. In bivariate analysis, a statistically significant correlation was observed between screening interest and participant perception of climate change’s impact on health (P < .001). Younger individuals and female respondents were more likely to report that climate change would harm their health, as were those with higher educational attainment.
Baseline characteristics of the study cohort overall and stratified by self-reported perception of the health impacts of climate change (weighed proportions)
. | How much do you think climate change will harm your health?a . | . | |||
---|---|---|---|---|---|
. | Not at all, % . | A little, % . | Some, % . | A lot, % . | P . |
Total | 0.24 | 0.23 | 0.32 | 0.22 | |
Age group, y | .002 | ||||
18-34 | 0.16 | 0.24 | 0.32 | 0.28 | |
35-49 | 0.22 | 0.24 | 0.32 | 0.21 | |
50-64 | 0.28 | 0.23 | 0.31 | 0.18 | |
65-74 | 0.26 | 0.19 | 0.33 | 0.22 | |
≥75 | 0.31 | 0.22 | 0.30 | 0.17 | |
Sex assigned at birth | <.001 | ||||
Male | 0.29 | 0.22 | 0.31 | 0.19 | |
Female | 0.19 | 0.23 | 0.33 | 0.25 | |
Race and ethnicity | .002 | ||||
Hispanic | 0.17 | 0.22 | 0.33 | 0.27 | |
Non-Hispanic Black | 0.17 | 0.25 | 0.34 | 0.24 | |
Non-Hispanic White | 0.27 | 0.21 | 0.33 | 0.19 | |
Other | 0.16 | 0.30 | 0.26 | 0.27 | |
Employment status | .07 | ||||
Employed | 0.22 | 0.24 | 0.33 | 0.21 | |
Not employed | 0.27 | 0.21 | 0.30 | 0.23 | |
Marital status | .04 | ||||
Single | 0.20 | 0.21 | 0.34 | 0.26 | |
Married/partnered | 0.26 | 0.24 | 0.31 | 0.20 | |
Divorced/widowed/separated | 0.25 | 0.24 | 0.33 | 0.19 | |
Education level | .001 | ||||
High school or less | 0.26 | 0.25 | 0.31 | 0.17 | |
Some college/post–high school training | 0.27 | 0.23 | 0.28 | 0.22 | |
College graduate | 0.20 | 0.21 | 0.36 | 0.24 | |
Postgraduate | 0.17 | 0.18 | 0.39 | 0.26 | |
Income level | .28 | ||||
$0 to $34 999 | 0.26 | 0.21 | 0.30 | 0.23 | |
$35 000 to $74 999 | 0.19 | 0.23 | 0.36 | 0.21 | |
$75 000 to $199 999 | 0.24 | 0.24 | 0.31 | 0.22 | |
≥$200 000 | 0.26 | 0.18 | 0.32 | 0.23 | |
Urban or rural residence status | <.001 | ||||
Metro (>1 million people) | 0.18 | 0.22 | 0.34 | 0.26 | |
Metro (250 000 to 1 million people) | 0.29 | 0.22 | 0.29 | 0.20 | |
Metro (<250 000) | 0.29 | 0.29 | 0.28 | 0.15 | |
Nonmetro | 0.33 | 0.24 | 0.29 | 0.15 | |
Current smoker | .36 | ||||
No | 0.24 | 0.22 | 0.32 | 0.22 | |
Yes | 0.19 | 0.28 | 0.29 | 0.23 | |
Interest in cancer screening | <.001 | ||||
Not at all | 0.29 | 0.25 | 0.27 | 0.18 | |
A little | 0.22 | 0.27 | 0.31 | 0.19 | |
Somewhat | 0.21 | 0.22 | 0.35 | 0.22 | |
Very | 0.15 | 0.20 | 0.34 | 0.31 |
. | How much do you think climate change will harm your health?a . | . | |||
---|---|---|---|---|---|
. | Not at all, % . | A little, % . | Some, % . | A lot, % . | P . |
Total | 0.24 | 0.23 | 0.32 | 0.22 | |
Age group, y | .002 | ||||
18-34 | 0.16 | 0.24 | 0.32 | 0.28 | |
35-49 | 0.22 | 0.24 | 0.32 | 0.21 | |
50-64 | 0.28 | 0.23 | 0.31 | 0.18 | |
65-74 | 0.26 | 0.19 | 0.33 | 0.22 | |
≥75 | 0.31 | 0.22 | 0.30 | 0.17 | |
Sex assigned at birth | <.001 | ||||
Male | 0.29 | 0.22 | 0.31 | 0.19 | |
Female | 0.19 | 0.23 | 0.33 | 0.25 | |
Race and ethnicity | .002 | ||||
Hispanic | 0.17 | 0.22 | 0.33 | 0.27 | |
Non-Hispanic Black | 0.17 | 0.25 | 0.34 | 0.24 | |
Non-Hispanic White | 0.27 | 0.21 | 0.33 | 0.19 | |
Other | 0.16 | 0.30 | 0.26 | 0.27 | |
Employment status | .07 | ||||
Employed | 0.22 | 0.24 | 0.33 | 0.21 | |
Not employed | 0.27 | 0.21 | 0.30 | 0.23 | |
Marital status | .04 | ||||
Single | 0.20 | 0.21 | 0.34 | 0.26 | |
Married/partnered | 0.26 | 0.24 | 0.31 | 0.20 | |
Divorced/widowed/separated | 0.25 | 0.24 | 0.33 | 0.19 | |
Education level | .001 | ||||
High school or less | 0.26 | 0.25 | 0.31 | 0.17 | |
Some college/post–high school training | 0.27 | 0.23 | 0.28 | 0.22 | |
College graduate | 0.20 | 0.21 | 0.36 | 0.24 | |
Postgraduate | 0.17 | 0.18 | 0.39 | 0.26 | |
Income level | .28 | ||||
$0 to $34 999 | 0.26 | 0.21 | 0.30 | 0.23 | |
$35 000 to $74 999 | 0.19 | 0.23 | 0.36 | 0.21 | |
$75 000 to $199 999 | 0.24 | 0.24 | 0.31 | 0.22 | |
≥$200 000 | 0.26 | 0.18 | 0.32 | 0.23 | |
Urban or rural residence status | <.001 | ||||
Metro (>1 million people) | 0.18 | 0.22 | 0.34 | 0.26 | |
Metro (250 000 to 1 million people) | 0.29 | 0.22 | 0.29 | 0.20 | |
Metro (<250 000) | 0.29 | 0.29 | 0.28 | 0.15 | |
Nonmetro | 0.33 | 0.24 | 0.29 | 0.15 | |
Current smoker | .36 | ||||
No | 0.24 | 0.22 | 0.32 | 0.22 | |
Yes | 0.19 | 0.28 | 0.29 | 0.23 | |
Interest in cancer screening | <.001 | ||||
Not at all | 0.29 | 0.25 | 0.27 | 0.18 | |
A little | 0.22 | 0.27 | 0.31 | 0.19 | |
Somewhat | 0.21 | 0.22 | 0.35 | 0.22 | |
Very | 0.15 | 0.20 | 0.34 | 0.31 |
Weighted percentages were calculated across each row.
Baseline characteristics of the study cohort overall and stratified by self-reported perception of the health impacts of climate change (weighed proportions)
. | How much do you think climate change will harm your health?a . | . | |||
---|---|---|---|---|---|
. | Not at all, % . | A little, % . | Some, % . | A lot, % . | P . |
Total | 0.24 | 0.23 | 0.32 | 0.22 | |
Age group, y | .002 | ||||
18-34 | 0.16 | 0.24 | 0.32 | 0.28 | |
35-49 | 0.22 | 0.24 | 0.32 | 0.21 | |
50-64 | 0.28 | 0.23 | 0.31 | 0.18 | |
65-74 | 0.26 | 0.19 | 0.33 | 0.22 | |
≥75 | 0.31 | 0.22 | 0.30 | 0.17 | |
Sex assigned at birth | <.001 | ||||
Male | 0.29 | 0.22 | 0.31 | 0.19 | |
Female | 0.19 | 0.23 | 0.33 | 0.25 | |
Race and ethnicity | .002 | ||||
Hispanic | 0.17 | 0.22 | 0.33 | 0.27 | |
Non-Hispanic Black | 0.17 | 0.25 | 0.34 | 0.24 | |
Non-Hispanic White | 0.27 | 0.21 | 0.33 | 0.19 | |
Other | 0.16 | 0.30 | 0.26 | 0.27 | |
Employment status | .07 | ||||
Employed | 0.22 | 0.24 | 0.33 | 0.21 | |
Not employed | 0.27 | 0.21 | 0.30 | 0.23 | |
Marital status | .04 | ||||
Single | 0.20 | 0.21 | 0.34 | 0.26 | |
Married/partnered | 0.26 | 0.24 | 0.31 | 0.20 | |
Divorced/widowed/separated | 0.25 | 0.24 | 0.33 | 0.19 | |
Education level | .001 | ||||
High school or less | 0.26 | 0.25 | 0.31 | 0.17 | |
Some college/post–high school training | 0.27 | 0.23 | 0.28 | 0.22 | |
College graduate | 0.20 | 0.21 | 0.36 | 0.24 | |
Postgraduate | 0.17 | 0.18 | 0.39 | 0.26 | |
Income level | .28 | ||||
$0 to $34 999 | 0.26 | 0.21 | 0.30 | 0.23 | |
$35 000 to $74 999 | 0.19 | 0.23 | 0.36 | 0.21 | |
$75 000 to $199 999 | 0.24 | 0.24 | 0.31 | 0.22 | |
≥$200 000 | 0.26 | 0.18 | 0.32 | 0.23 | |
Urban or rural residence status | <.001 | ||||
Metro (>1 million people) | 0.18 | 0.22 | 0.34 | 0.26 | |
Metro (250 000 to 1 million people) | 0.29 | 0.22 | 0.29 | 0.20 | |
Metro (<250 000) | 0.29 | 0.29 | 0.28 | 0.15 | |
Nonmetro | 0.33 | 0.24 | 0.29 | 0.15 | |
Current smoker | .36 | ||||
No | 0.24 | 0.22 | 0.32 | 0.22 | |
Yes | 0.19 | 0.28 | 0.29 | 0.23 | |
Interest in cancer screening | <.001 | ||||
Not at all | 0.29 | 0.25 | 0.27 | 0.18 | |
A little | 0.22 | 0.27 | 0.31 | 0.19 | |
Somewhat | 0.21 | 0.22 | 0.35 | 0.22 | |
Very | 0.15 | 0.20 | 0.34 | 0.31 |
. | How much do you think climate change will harm your health?a . | . | |||
---|---|---|---|---|---|
. | Not at all, % . | A little, % . | Some, % . | A lot, % . | P . |
Total | 0.24 | 0.23 | 0.32 | 0.22 | |
Age group, y | .002 | ||||
18-34 | 0.16 | 0.24 | 0.32 | 0.28 | |
35-49 | 0.22 | 0.24 | 0.32 | 0.21 | |
50-64 | 0.28 | 0.23 | 0.31 | 0.18 | |
65-74 | 0.26 | 0.19 | 0.33 | 0.22 | |
≥75 | 0.31 | 0.22 | 0.30 | 0.17 | |
Sex assigned at birth | <.001 | ||||
Male | 0.29 | 0.22 | 0.31 | 0.19 | |
Female | 0.19 | 0.23 | 0.33 | 0.25 | |
Race and ethnicity | .002 | ||||
Hispanic | 0.17 | 0.22 | 0.33 | 0.27 | |
Non-Hispanic Black | 0.17 | 0.25 | 0.34 | 0.24 | |
Non-Hispanic White | 0.27 | 0.21 | 0.33 | 0.19 | |
Other | 0.16 | 0.30 | 0.26 | 0.27 | |
Employment status | .07 | ||||
Employed | 0.22 | 0.24 | 0.33 | 0.21 | |
Not employed | 0.27 | 0.21 | 0.30 | 0.23 | |
Marital status | .04 | ||||
Single | 0.20 | 0.21 | 0.34 | 0.26 | |
Married/partnered | 0.26 | 0.24 | 0.31 | 0.20 | |
Divorced/widowed/separated | 0.25 | 0.24 | 0.33 | 0.19 | |
Education level | .001 | ||||
High school or less | 0.26 | 0.25 | 0.31 | 0.17 | |
Some college/post–high school training | 0.27 | 0.23 | 0.28 | 0.22 | |
College graduate | 0.20 | 0.21 | 0.36 | 0.24 | |
Postgraduate | 0.17 | 0.18 | 0.39 | 0.26 | |
Income level | .28 | ||||
$0 to $34 999 | 0.26 | 0.21 | 0.30 | 0.23 | |
$35 000 to $74 999 | 0.19 | 0.23 | 0.36 | 0.21 | |
$75 000 to $199 999 | 0.24 | 0.24 | 0.31 | 0.22 | |
≥$200 000 | 0.26 | 0.18 | 0.32 | 0.23 | |
Urban or rural residence status | <.001 | ||||
Metro (>1 million people) | 0.18 | 0.22 | 0.34 | 0.26 | |
Metro (250 000 to 1 million people) | 0.29 | 0.22 | 0.29 | 0.20 | |
Metro (<250 000) | 0.29 | 0.29 | 0.28 | 0.15 | |
Nonmetro | 0.33 | 0.24 | 0.29 | 0.15 | |
Current smoker | .36 | ||||
No | 0.24 | 0.22 | 0.32 | 0.22 | |
Yes | 0.19 | 0.28 | 0.29 | 0.23 | |
Interest in cancer screening | <.001 | ||||
Not at all | 0.29 | 0.25 | 0.27 | 0.18 | |
A little | 0.22 | 0.27 | 0.31 | 0.19 | |
Somewhat | 0.21 | 0.22 | 0.35 | 0.22 | |
Very | 0.15 | 0.20 | 0.34 | 0.31 |
Weighted percentages were calculated across each row.
Compared with those who perceived no harm from climate change, respondents who thought climate change would cause some harm or a lot of harm had greater interest in cancer screening in adjusted models (Table 2). The magnitude of this effect increased in size with greater recognition of the health impacts of climate change: There were 73% higher odds of reporting interest in cancer screening among those who thought that climate change would harm their health “some” (adjusted odds ratio = 1.73, 95% confidence interval = 1.26 to 2.38); there were 84% higher odds of having interest in cancer screening in those who thought climate change would harm their health “a lot” (adjusted odds ratio = 1.84, 95% confidence interval = 1.27 to 2.65). Additional independent predictors of interest in cancer screening are summarized in Table 2. Sensitivity analysis with respondents aged 50 to 70 years showed consistent results (Supplementary Table 2, available online).
Multivariable logistic regression for independent predictors of interest in having a cancer screening test in the next yeara
. | Odds ratio . | 95% Confidence interval . | P . | |
---|---|---|---|---|
How much do you think climate change will harm your health? | ||||
Not at all | (Referent) | |||
A little | 1.24 | 0.90 to 1.70 | .18 | |
Some | 1.73 | 1.26 to 2.38 | <.001 | |
A lot | 1.84 | 1.27 to 2.65 | <.001 | |
Age group, y | ||||
18-34 | (Referent) | |||
35-49 | 1.58 | 1.06 to 2.34 | .02 | |
50-64 | 2.23 | 1.65 to 3.02 | <.001 | |
65-74 | 1.82 | 1.14 to 2.89 | .01 | |
≥75 | 1.60 | 1.00 to 2.56 | .05 | |
Sex assigned at birth | ||||
Male | (Referent) | |||
Female | 1.72 | 1.39 to 2.13 | <.001 | |
Race and ethnicity | ||||
Hispanic | 2.15 | 1.49 to 3.10 | <.001 | |
Non-Hispanic Black | 1.66 | 1.19 to 2.30 | <.001 | |
Non-Hispanic White | (Referent) | |||
Others | 1.36 | 0.84 to 2.21 | .21 | |
Employment status | ||||
Employed | (Referent) | |||
Not employed | 1.15 | 0.84 to 1.57 | .38 | |
Marital status | ||||
Single | (Referent) | |||
Married/partnered | 1.23 | 0.96 to 1.59 | .10 | |
Divorced/widowed/separated | 0.95 | 0.69 to 1.31 | .76 | |
Education level | ||||
High school or less | (Referent) | |||
Some college/post–high school training | 1.41 | 0.99 to 1.99 | .05 | |
College graduate | 1.67 | 1.12 to 2.51 | .01 | |
Postgraduate education | 1.83 | 1.22 to 2.72 | <.001 | |
Income level | ||||
$0 to $34 999 | (Referent) | |||
$35 000 to $74 999 | 1.06 | 0.75 to 1.49 | .72 | |
$75 000 to $199 999 | 1.00 | 0.69 to 1.44 | .98 | |
≥$200 000 | 0.94 | 0.56 to 1.58 | .81 | |
Urban or rural residence status | ||||
Metro (>1 million people) | (Referent) | |||
Metro (250 000 to 1 million people) | 0.84 | 0.63 to 1.13 | .25 | |
Metro (<250 000) | 0.79 | 0.50 to 1.24 | .30 | |
Nonmetro | 0.77 | 0.53 to 1.10 | .15 | |
Current smoker | ||||
No | (Referent) | |||
Yes | 0.89 | 0.63 to 1.27 | .52 |
. | Odds ratio . | 95% Confidence interval . | P . | |
---|---|---|---|---|
How much do you think climate change will harm your health? | ||||
Not at all | (Referent) | |||
A little | 1.24 | 0.90 to 1.70 | .18 | |
Some | 1.73 | 1.26 to 2.38 | <.001 | |
A lot | 1.84 | 1.27 to 2.65 | <.001 | |
Age group, y | ||||
18-34 | (Referent) | |||
35-49 | 1.58 | 1.06 to 2.34 | .02 | |
50-64 | 2.23 | 1.65 to 3.02 | <.001 | |
65-74 | 1.82 | 1.14 to 2.89 | .01 | |
≥75 | 1.60 | 1.00 to 2.56 | .05 | |
Sex assigned at birth | ||||
Male | (Referent) | |||
Female | 1.72 | 1.39 to 2.13 | <.001 | |
Race and ethnicity | ||||
Hispanic | 2.15 | 1.49 to 3.10 | <.001 | |
Non-Hispanic Black | 1.66 | 1.19 to 2.30 | <.001 | |
Non-Hispanic White | (Referent) | |||
Others | 1.36 | 0.84 to 2.21 | .21 | |
Employment status | ||||
Employed | (Referent) | |||
Not employed | 1.15 | 0.84 to 1.57 | .38 | |
Marital status | ||||
Single | (Referent) | |||
Married/partnered | 1.23 | 0.96 to 1.59 | .10 | |
Divorced/widowed/separated | 0.95 | 0.69 to 1.31 | .76 | |
Education level | ||||
High school or less | (Referent) | |||
Some college/post–high school training | 1.41 | 0.99 to 1.99 | .05 | |
College graduate | 1.67 | 1.12 to 2.51 | .01 | |
Postgraduate education | 1.83 | 1.22 to 2.72 | <.001 | |
Income level | ||||
$0 to $34 999 | (Referent) | |||
$35 000 to $74 999 | 1.06 | 0.75 to 1.49 | .72 | |
$75 000 to $199 999 | 1.00 | 0.69 to 1.44 | .98 | |
≥$200 000 | 0.94 | 0.56 to 1.58 | .81 | |
Urban or rural residence status | ||||
Metro (>1 million people) | (Referent) | |||
Metro (250 000 to 1 million people) | 0.84 | 0.63 to 1.13 | .25 | |
Metro (<250 000) | 0.79 | 0.50 to 1.24 | .30 | |
Nonmetro | 0.77 | 0.53 to 1.10 | .15 | |
Current smoker | ||||
No | (Referent) | |||
Yes | 0.89 | 0.63 to 1.27 | .52 |
Within the logistic model, we dichotomized the variable “interest in cancer screening” into 2 categories: “Not at all” and “A little” vs “Somewhat” and “Very.”
Multivariable logistic regression for independent predictors of interest in having a cancer screening test in the next yeara
. | Odds ratio . | 95% Confidence interval . | P . | |
---|---|---|---|---|
How much do you think climate change will harm your health? | ||||
Not at all | (Referent) | |||
A little | 1.24 | 0.90 to 1.70 | .18 | |
Some | 1.73 | 1.26 to 2.38 | <.001 | |
A lot | 1.84 | 1.27 to 2.65 | <.001 | |
Age group, y | ||||
18-34 | (Referent) | |||
35-49 | 1.58 | 1.06 to 2.34 | .02 | |
50-64 | 2.23 | 1.65 to 3.02 | <.001 | |
65-74 | 1.82 | 1.14 to 2.89 | .01 | |
≥75 | 1.60 | 1.00 to 2.56 | .05 | |
Sex assigned at birth | ||||
Male | (Referent) | |||
Female | 1.72 | 1.39 to 2.13 | <.001 | |
Race and ethnicity | ||||
Hispanic | 2.15 | 1.49 to 3.10 | <.001 | |
Non-Hispanic Black | 1.66 | 1.19 to 2.30 | <.001 | |
Non-Hispanic White | (Referent) | |||
Others | 1.36 | 0.84 to 2.21 | .21 | |
Employment status | ||||
Employed | (Referent) | |||
Not employed | 1.15 | 0.84 to 1.57 | .38 | |
Marital status | ||||
Single | (Referent) | |||
Married/partnered | 1.23 | 0.96 to 1.59 | .10 | |
Divorced/widowed/separated | 0.95 | 0.69 to 1.31 | .76 | |
Education level | ||||
High school or less | (Referent) | |||
Some college/post–high school training | 1.41 | 0.99 to 1.99 | .05 | |
College graduate | 1.67 | 1.12 to 2.51 | .01 | |
Postgraduate education | 1.83 | 1.22 to 2.72 | <.001 | |
Income level | ||||
$0 to $34 999 | (Referent) | |||
$35 000 to $74 999 | 1.06 | 0.75 to 1.49 | .72 | |
$75 000 to $199 999 | 1.00 | 0.69 to 1.44 | .98 | |
≥$200 000 | 0.94 | 0.56 to 1.58 | .81 | |
Urban or rural residence status | ||||
Metro (>1 million people) | (Referent) | |||
Metro (250 000 to 1 million people) | 0.84 | 0.63 to 1.13 | .25 | |
Metro (<250 000) | 0.79 | 0.50 to 1.24 | .30 | |
Nonmetro | 0.77 | 0.53 to 1.10 | .15 | |
Current smoker | ||||
No | (Referent) | |||
Yes | 0.89 | 0.63 to 1.27 | .52 |
. | Odds ratio . | 95% Confidence interval . | P . | |
---|---|---|---|---|
How much do you think climate change will harm your health? | ||||
Not at all | (Referent) | |||
A little | 1.24 | 0.90 to 1.70 | .18 | |
Some | 1.73 | 1.26 to 2.38 | <.001 | |
A lot | 1.84 | 1.27 to 2.65 | <.001 | |
Age group, y | ||||
18-34 | (Referent) | |||
35-49 | 1.58 | 1.06 to 2.34 | .02 | |
50-64 | 2.23 | 1.65 to 3.02 | <.001 | |
65-74 | 1.82 | 1.14 to 2.89 | .01 | |
≥75 | 1.60 | 1.00 to 2.56 | .05 | |
Sex assigned at birth | ||||
Male | (Referent) | |||
Female | 1.72 | 1.39 to 2.13 | <.001 | |
Race and ethnicity | ||||
Hispanic | 2.15 | 1.49 to 3.10 | <.001 | |
Non-Hispanic Black | 1.66 | 1.19 to 2.30 | <.001 | |
Non-Hispanic White | (Referent) | |||
Others | 1.36 | 0.84 to 2.21 | .21 | |
Employment status | ||||
Employed | (Referent) | |||
Not employed | 1.15 | 0.84 to 1.57 | .38 | |
Marital status | ||||
Single | (Referent) | |||
Married/partnered | 1.23 | 0.96 to 1.59 | .10 | |
Divorced/widowed/separated | 0.95 | 0.69 to 1.31 | .76 | |
Education level | ||||
High school or less | (Referent) | |||
Some college/post–high school training | 1.41 | 0.99 to 1.99 | .05 | |
College graduate | 1.67 | 1.12 to 2.51 | .01 | |
Postgraduate education | 1.83 | 1.22 to 2.72 | <.001 | |
Income level | ||||
$0 to $34 999 | (Referent) | |||
$35 000 to $74 999 | 1.06 | 0.75 to 1.49 | .72 | |
$75 000 to $199 999 | 1.00 | 0.69 to 1.44 | .98 | |
≥$200 000 | 0.94 | 0.56 to 1.58 | .81 | |
Urban or rural residence status | ||||
Metro (>1 million people) | (Referent) | |||
Metro (250 000 to 1 million people) | 0.84 | 0.63 to 1.13 | .25 | |
Metro (<250 000) | 0.79 | 0.50 to 1.24 | .30 | |
Nonmetro | 0.77 | 0.53 to 1.10 | .15 | |
Current smoker | ||||
No | (Referent) | |||
Yes | 0.89 | 0.63 to 1.27 | .52 |
Within the logistic model, we dichotomized the variable “interest in cancer screening” into 2 categories: “Not at all” and “A little” vs “Somewhat” and “Very.”
Using cross-sectional data from the 2021 HINTS, our study is the first to explore the correlation between attitudes and beliefs about the health impacts of climate change and interest in cancer screening. Our data reveal a low national level of awareness concerning the health impacts of climate change. A disconnect persists between acknowledging climate change occurrence and recognizing its adverse effects on human health (15). Our finding that patients who do not seriously consider health impacts of climate change are less likely to express interest in cancer screening suggests a high-risk group that may greatly benefit from targeted interventions aimed simultaneously at both appreciation for natural environments and encouraging cancer awareness. Beyond broad interventions such as initiating public health policies, more localized strategies, such as using social media to spread awareness of health-related and climate-related issues—a potential solution supported by prior literature—can be employed to address this issue (16).
These key insights align with existing literature underscoring the role of perceived health threats in shaping health behaviors (17-19). Further, these data imply that there is a potential avenue for health education and promotion: Public health interventions could be enhanced by incorporating components of environmental health literacy to foster preventive behaviors. The campaign against tobacco-associated cancers serves as a pertinent model: Raising public awareness about the health and cancer risks of smoking played a crucial role in promoting policies and advocacy efforts to reduce smoking prevalence (20,21). For physicians and epidemiologists, the connection between climate-related weather events and cancer epidemiology and outcomes is evident. Yet, these results highlight a significant gap in the general population’s understanding of this connection.
We also observed notable differences in climate change awareness and interest in cancer screening across different racial and ethnic groups. For example, non-Hispanic Black and Hispanic respondents demonstrated significantly higher odds of expressing interest in cancer screening than non-Hispanic White individuals in univariable and adjusted analyses (Table 2). These findings were encouraging in light of observed disparities in cancer morbidity and mortality (22).
One possible explanation of the observed association is that individuals who are more aware of the potential health impacts of climate change may also be more overall health conscious. Higher health consciousness could potentially drive their interest in preventive health-care measures, such as cancer screening. Awareness of climate change impacts could also serve as a form of “ecological health literacy,” prompting individuals to take more proactive steps to protect their health in the face of environmental threats. This finding suggests a broader understanding of health that includes the potential effects of environmental changes. Finally, it is possible that the stress and anxiety associated with climate change awareness may motivate individuals to seek control where they can, leading them to engage in preventive health behaviors, such as cancer screening (23). Further studies are needed to understand how climate change awareness affects health behaviors. Health-care professionals could be key in spreading this knowledge. Incorporating climate change into medical education may be one way to enhance understanding of the link between climate change, planetary health, and cancer.
Although our study offers novel insights, limitations exist. The cross-sectional HINTS survey offers a single time-point snapshot, limiting causal inferences. The self-reported nature of climate change awareness and cancer screening interest could introduce social desirability bias. Our data solely recorded patient intent and did not confirm the actual completion of screening tests such as colonoscopy, Papanicolaou smears, or prostate-specific antigen testing. The lack of data on personal or familial cancer history, a potential influence on cancer screening attitudes, is another limitation. Despite adjustments, it is possible that an unmeasured or mismeasured factor, such as education, socioeconomic status, and political beliefs, could explain the persistent association between climate change awareness and intent to screen. Finally, generalizability could be affected by the exclusion of individuals with missing data, although the HINTS sample is nationally representative.
Our study elucidates a significant correlation between climate change health awareness and cancer screening independent of sociodemographic characteristics, thereby suggesting that those who lack environmental health literacy may also forego opportunities for cancer prevention. Although our results stem from retrospective survey–limiting causal inference, they indicate a promising direction for future research to explore and support awareness about the impacts of climate change on human health generally and on cancer care and prevention specifically. Enhancing environmental health literacy could support adherence to preventive health behaviors, thereby lessening the impacts of climate change on cancer outcomes.
Data availability
The dataset used in this study is publicly available at https://hints.cancer.gov/.
Author contributions
Zhiyu Qian, MD (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Writing—original draft; Writing—review & editing), Edoardo Beatrici, MD (Conceptualization; Writing—original draft; Writing—review & editing), Quoc-Dien Trinh, MD, MBA (Conceptualization; Investigation; Methodology; Project administration; Writing—review & editing), Adam Kibel, MD, MHCM (Conceptualization; Methodology; Writing—review & editing), Stacy Loeb, Md, MSc (Conceptualization; Investigation; Methodology; Writing—review & editing), Hari S. Iyer, ScD, MPH (Conceptualization; Formal analysis; Methodology; Software; Writing—review & editing), Alexander Putnam Cole, MD (Conceptualization; Investigation; Methodology; Supervision; Visualization; Writing—review & editing).
Funding
A.P.C. reports research funding from the Bruce A. Beal and Robert L. Beal surgical fellowship of the Brigham and Women’s Hospital Department of Surgery, from the Prostate Cancer Foundation and American Cancer Society (No. 23YOUN25), and from a Physician Research Award from the Department of Defense Congressionally Directed Medical Research Program (No. PC220342).
Conflicts of interest
Q.D.T. reports personal fees from Astellas, Bayer, and Janssen outside the submitted work. Q.D.T. reports research funding from the American Cancer Society, the Defense Health Agency, and Pfizer Global Medical Grants. A.P.C. reports research funding from the American Cancer Society and Pfizer Global Medical grants.
Acknowledgements
The funder had no role in the design of the study; the collection, analysis, or interpretation of the data; or the writing of the manuscript and decision to submit it for publication.