Projecting and valuing climate change impacts on anxiety and depression in the contiguous USA: a damage function approach.

Warming of 1–6°C would produce hundreds of millions to over a billion excess annual anxiety symptom-days among US adults.

• Assuming present-day sociodemographics, 1–6°C warming would result in 401 million to 1.8 billion excess annual self-reported anxiety symptom-days.
• This represents a 5–23% increase from baseline.
• Baseline health data were drawn from 2015, and baseline climate was 2005.
• Estimates were derived by combining epidemiologically derived exposure-response relationships with projections from five CMIP6 climate models.

Warming of 1–6°C would produce hundreds of millions to over a billion excess annual depression symptom-days among US adults.

• Assuming present-day sociodemographics, 1–6°C warming would result in 329 million to 1.4 billion excess annual self-reported depression symptom-days.
• This also represents a 5–23% increase from baseline.
• Analyses covered both acute (short-term, over the past month) and chronic (multi-year average maximum temperature) exposures.

The economic value of excess anxiety and depression burden under 1–6°C warming reaches tens of billions of dollars annually.

• Corresponding annual values of excess anxiety burden are US$13 billion to $57 billion (2023 US dollars, undiscounted).
• Corresponding annual values of excess depression burden are US$11 billion to $47 billion (2023 US dollars, undiscounted).
• Economic valuation was based on health-related quality of life losses monetised using a scaled value per quality-adjusted life-year derived from the US EPA Value of a Statistical Life divided by quality-adjusted life expectancy.
• Valuation estimates were informed by fixed-effects regression analysis of Medical Expenditure Panel Survey 2018–21 data.

Per-person annual increases in anxiety and depression symptom-days are estimated at two to seven and one to six days, respectively, under 1–6°C warming.

• The study estimates an additional two to seven anxiety symptom-days per person-year across the general adult population.
• The study estimates an additional one to six depression symptom-days per person-year across the general adult population.
• These per-person estimates are derived under present-day sociodemographic scenarios.

Low-income subpopulations face substantially larger projected mental health burdens from climate warming.

• Low-income subpopulations are projected to experience four to 15 excess anxiety symptom-days per person-year under 1–6°C warming.
• Low-income subpopulations are projected to experience three to 14 excess depression symptom-days per person-year under 1–6°C warming.
• These burdens are approximately double to more than double those projected for the general adult population.
• Analyses were stratified by sex and income for acute temperature and precipitation exposures.

The greatest projected mental health impacts from climate warming are concentrated in the Appalachian region.

• The greatest impacts are projected to occur in Appalachia.
• The authors note that this region has restricted adaptive capacity due to economic hardship.
• The findings underscore the need for mental health investment in economically disadvantaged regions.

Using end-of-century (2095) sociodemographic projections substantially increases both estimated symptom-days and monetised impacts compared to present-day scenarios.

• Using 2095 sociodemographics resulted in an increase in symptom days of almost 30% compared to present-day sociodemographic scenarios.
• Using 2095 sociodemographics resulted in an increase in monetised impacts of almost 90% compared to present-day sociodemographic scenarios.
• Present-day sociodemographic scenario used 2022 data; end-of-century scenario used 2095 projections.

Baseline symptom-day incidence rates were estimated using negative binomial regression of BRFSS data spanning 2013–2023.

• Data from the US Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS) 2013–23 datasets were used to inform baseline symptom-day incidence rates.
• Regression analyses were stratified by month, state, sex, and age group.
• Sex-specific and age group-specific mental health difficulty day allocation ratios for anxiety and depression were estimated using the 2018 Depression and Anxiety Module for Oregon and Tennessee.
• Monte Carlo simulations were used to propagate uncertainty across health, climate, and valuation inputs.