Fritz, M. (2025). Beyond the heat: The mental health toll of temperature and humidity in India. arXiv preprint arXiv:2503.08761.

Introduction

Climate change isn't just about rising temperatures—it's increasingly recognized as a significant threat to human health. While much research has focused on physical health impacts like heat stroke and cardiovascular disease, the mental health consequences have received comparatively little attention, particularly in low- and middle-income countries (LMICs) that are most vulnerable to climate change.

The research paper by Manuela Fritz from TUM School of Social Science and Technology and the University of Passau addresses this critical knowledge gap by investigating how extreme heat affects mental health in India. What sets this study apart is its consideration of humidity alongside temperature—a crucial factor that significantly amplifies the physiological stress of heat but is often overlooked in climate-health research.

India presents an ideal setting for this research. The country already experiences high temperatures and humidity levels, which climate models predict will worsen. Additionally, India faces a growing burden of mental health disorders with limited access to treatment and care, making the potential climate-mental health connection particularly relevant for public health planning.

The Research Gap

Previous research on heat's health effects has primarily focused on mortality and physical morbidity. When studies have examined mental health impacts, they've typically:

Concentrated on high-income countries rather than LMICs
Measured temperature alone without accounting for humidity
Focused on long-term mechanisms rather than short-term physiological effects
This gap is significant because:

People in LMICs often have greater occupational exposure to heat (outdoor work, manual labor)
These regions typically have less access to adaptive technologies like air conditioning
Humid heat is physiologically more dangerous than dry heat at the same temperature

The author explains that high wet-bulb temperature (a measure combining temperature and humidity) impairs the body's cooling mechanism—sweating—which may trigger physiological stress responses that affect mental health. At extreme wet-bulb temperatures, even healthy individuals in shade with adequate water cannot regulate body temperature, leading to potentially fatal conditions.

Methodology

The study employs a comprehensive approach that combines multiple high-quality datasets:

Mental Health Data: From the WHO Study on Global Ageing and Adult Health (SAGE) surveys in India, providing self-reported depression and anxiety symptoms.
Climate Data: From NASA's GLDAS Noah Land Surface Model, providing temperature, humidity, air pressure, and wind speed measurements.
Additional Environmental Factors: Including rainfall data from the Indian Meteorological Department and air pollution (PM2.5) from NASA MERRA-2.

The research design exploits the quasi-random timing of survey implementation across different regions of India, treating the variation in heat exposure as exogenous. The key advantage of this approach is that it allows for causal inference rather than mere correlation.

The author uses wet-bulb temperature as the primary heat measure, calculated using:

$\begin{gathered}T_{wb}=T\cdot\arctan[0.151977\cdot(RH\%+8.313659)^{1/2}]+\\\arctan(T+RH\%)-\arctan(RH\%-1.676331)+\\0.00391838\cdot(RH\%)^{3/2}\cdot\arctan(0.023101\cdot RH\%)-\\\\4.686035\end{gathered}$

Where T is temperature in Celsius and RH% is relative humidity percentage.

To analyze the relationship between heat and mental health, the study employs:

A temperature bin regression approach to estimate the effect of additional days in different temperature ranges
Binary heatwave indicators based on consecutive days exceeding specific temperature thresholds
Controls for individual characteristics, household factors, weather variables, and various fixed effects

Temperature‐Bin Regression Model

The main empirical specification decomposes the past 30 days’ exposure into a set of temperature bins. Specifically, the model can be written as:

$Mental_{idc}= \sum_{t=1,t \neq reference}^9 \alpha_t Wetbulb_{tdc} + \beta X_{idc} + \gamma Z_{dc} + \delta_{ym} +ζ_s + \eta_z + \epsilon_{idc}$

Here,
• $Mental_{idc}$ represents the mental health outcome (e.g., a binary indicator for severe/extreme depression or a continuous score) for individual i interviewed on day d in PSU (primary sampling unit) c.
• $Wetbulb_{tdc}$ denotes the number of days (within the past 30 days preceding the survey) in which the wet bulb temperature fell within temperature range (or “bin”) t; the bins are typically set at intervals of 1.5°C, and one of the central bins (e.g., days with temperatures between 21°C–22.5°C) is used as the reference group.
• $X_{idc}$ includes individual and household controls such as age, gender, years of education, marital status, chronic conditions, and asset or housing characteristics.
• $Z_{dc}$ represents other weather controls (like rainfall deviation, average wind speed, air pollution concentrations) and also controls for the long-run average wet bulb temperature and its variation over the 30-day period.
• $\delta_{ym},ζ_s$ , and $\eta_z$ are fixed effects for year-month, state, and climate zone (based on the Köppen-Geiger classification), respectively, capturing time-invariant and regional unobserved heterogeneity.
• $\epsilon_{idc}$ is an error term.

This specification allows the researcher to capture the non-linear relationship between varying levels of heat (combined with humidity) and mental health outcomes by determining how additional days in specific temperature bins affect the probability of experiencing severe depression symptoms.

Binary Heatwave Indicator Regression Model

In addition to the temperature-bin approach, the study also formulates a regression model that uses a binary indicator for experiencing a heatwave. The heatwave indicator is defined as 1 if the individual was exposed to two or more consecutive days with the wet bulb temperature exceeding a certain threshold (e.g., >27°C), and 0 otherwise. The model takes the form:

$Mental_{idc} = \theta · Heatwave_{>27,dc} + \beta X_{idc} + \kappa Z_{dc} + \lambda_{ym} + \mu_{s}+ \nu_z + \epsilon_{idc}$

Where:
• $Heatwave_{>27,dc}$ is the binary variable indicating the presence of a heatwave (e.g., two or more consecutive days with wet bulb temperatures above 27°C) in the past 30 days.
• The remaining terms ( $X_{idc},Z_{dc},\lambda_{ym}, \mu_{s}, \nu_z$ ) are analogous to those described above, representing individual weather controls and fixed effects.

Both models utilize a rich set of controls and fixed effects to isolate the causal impact of recent heat exposure (as characterized by the wet bulb temperature) on mental health outcomes. The temperature-bin model allows for capturing non-linear and threshold effects, while the binary heatwave model simplifies the interpretation into “exposed” versus “not exposed” to prolonged extreme heat.

Key Findings

The study reveals several important findings:

Heat Increases Depression Risk: Exposure to a heatwave in the 30 days preceding the survey increases the probability of suffering from severe or extreme depression by 24% at the extensive margin (exposure to any heatwave) and by 6% at the intensive margin (one additional heat day).

Humidity Matters: When only dry-bulb temperature is considered (ignoring humidity), the effects are consistently smaller or disappear completely. This crucial finding underscores the importance of incorporating humidity when assessing heat-related health risks.

Depression vs. Anxiety: Interestingly, heat exposure significantly affects depression but shows no consistent effect on anxiety symptoms. This suggests different pathways of impact for various mental health conditions.

Protective Effect of Mental Health Programs: The District Mental Health Program (DMHP) in India appears to mitigate the adverse mental health effects of heat exposure, demonstrating that targeted interventions can reduce climate vulnerability.

Potential Mechanisms: Increased conflict and tension during hot periods may be one channel through which extreme temperatures drive deterioration of mental health. The effects are stronger during agricultural seasons for rural populations, suggesting that continued exposure to heat through outdoor, physically demanding activities amplifies mental health impacts.

Vulnerable Populations
Not all populations are equally affected by heat exposure. The study identifies several vulnerable groups:

Working Individuals: People who are employed show stronger negative mental health effects from heat exposure, likely due to occupational heat exposure and reduced work capacity.

Rural Populations: Rural residents experience more significant mental health impacts, particularly during agricultural seasons, suggesting that outdoor work and limited access to cooling technologies increase vulnerability.

Less Educated Individuals: Those with lower educational attainment show stronger effects, possibly reflecting less adaptable employment and living conditions.

Younger Adults: Contrary to some expectations, the study finds that heat effects on mental health are larger for younger cohorts (below age 50) rather than the elderly. This may relate to work patterns and outdoor exposure.

These findings on differential vulnerability provide important nuance for targeted public health interventions and climate adaptation planning.

Policy Implications
The research yields several important implications for policy:

Climate-Mental Health Integration: Mental health considerations should be explicitly incorporated into climate change adaptation strategies and health system planning.

Humidity-Based Risk Assessment: Heat warning systems and public health advisories should account for humidity alongside temperature, potentially using wet-bulb temperature as a more accurate measure of heat stress.

Targeted Interventions: Resources should be directed toward protecting the most vulnerable populations identified in the study.

Strengthening Mental Health Services: Expanding programs like the DMHP could help mitigate climate-related mental health impacts.

Adaptation Technologies: Increasing access to cooling technologies and climate-adapted housing could reduce heat exposure, particularly for vulnerable groups.

Occupational Protections: Labor policies should account for the mental health impacts of occupational heat exposure, potentially including mandatory rest periods during extreme heat.

Monitoring Systems: Long-term surveillance of climate and mental health indicators is needed to track changing patterns of risk as the climate continues to warm.

Conclusion
This groundbreaking study establishes a causal link between extreme heat—particularly humid heat—and mental health deterioration in India. By demonstrating that wet-bulb temperature is a more relevant measure than dry-bulb temperature alone, the research advances our understanding of climate-health interactions in significant ways.

The findings highlight the often-overlooked mental health dimension of climate change, with particular relevance for developing countries that will bear the brunt of climate impacts. As global temperatures continue to rise, addressing these mental health effects becomes increasingly urgent.

The study also offers hope by identifying protective factors—such as India's District Mental Health Program—that can reduce vulnerability. This suggests that with appropriate planning and resource allocation, societies can mitigate some of the mental health consequences of an increasingly hot and humid world.

For researchers, the study points to the importance of incorporating humidity in climate-health analyses and considering differential vulnerability across population groups. For policymakers, it underscores the need to integrate mental health considerations into climate adaptation strategies and to strengthen mental health services as a climate resilience measure.

As the planet continues to warm, understanding and addressing the full spectrum of climate change impacts—including those on mental health—will be essential for protecting human wellbeing in the challenging decades ahead.

Relevant Citations
Carleton, T. A. (2017). Crop-damaging temperatures increase suicide rates in India.Proceedings of the National Academy of Sciences, 114(33):8746–8751.

This study provides important context by examining the link between heat and mental health in India, specifically focusing on suicide rates. It is particularly relevant as it highlights the impact of heat on a severe mental health outcome in the same geographical context as the user-provided paper.
Pailler, S. and Tsaneva, M. (2018). The effects of climate variability on psychological well-being in India.World Development, 106:15–26.

This citation is highly relevant as it directly investigates the effects of climate variability on mental well-being in India, using self-reported measures. The focus on India makes it directly comparable to the user-provided paper, and the use of self-reported measures adds another layer of relevance.
Thompson, R., Hornigold, R., Page, L., and Waite, T. (2018). Associations between high ambient temperatures and heat waves with mental health outcomes: A systematic review.Public Health, 161:171–191.

This systematic review offers a comprehensive overview of the existing literature on the association between high temperatures and mental health outcomes. It is important for understanding the broader scientific landscape surrounding the topic and placing the user-provided study's findings within the context of existing research.
Obradovich, N., Migliorini, R., Paulus, M. P., and Rahwan, I. (2018). Empirical evidence of mental health risks posed by climate change.Proceedings of the National Academy of Sciences, 115(43):10953–10958.

This research presents empirical evidence on the mental health risks associated with climate change. It's relevant to the user-provided paper due to its focus on the broader mental health implications of climate change and the methodological approach of using empirical data.

【文献解读】Beyond the Heat: The Mental Health Toll of Temperature and Humidity in India