Analysis of heat stress and heat wave in the four metropolitan cities of India in recent period

Heat stress induces a three-phase thermoregulatory response in different hot and humid environments in rats

As global warming intensifies, heat waves occur more frequently around the world. Heat stress from hot and humid environments poses a significant threat to human health. It can cause a significant increase in core body temperature (CBT), and even lead to life-threatening heat stroke. Extremely high CBT is considered the most important clinical symptom and prognostic indicator of heat stroke. To study it, we implanted temperature-monitoring capsules into the abdominal cavities of rats to measure their CBT values. The rats were then exposed to different hot and humid environments to monitor the resultant changes in their CBTs. The results showed that heat stress could induce a three-phase thermoregulatory response in rats under different conditions. A temperature plateau was observed as part of the three-phase thermoregulatory response, at a similar CBT across different conditions. The duration of this plateau can reflect the thermotolerance of rats in hot and humid environments. The third stage of the three-phase thermoregulatory response reflects the pathogenesis of heat stroke, which may present the key stage of heat injury. Moreover, a certain range of humidity did not affect the thermoregulatory responses of rats, but exerted a significant impact once a certain threshold was reached. In this study, the CBTs of the rats in different environments were monitored to characterize their thermoregulatory responses under heat stress. In particular, the discovery of the plateau phase and humidity threshold may help to better understand the effects of high temperature and humidity conditions on living organisms.

The Self-Reported Human Health Impacts of Disaster on People in India: A Cross-Sectional Analysis of the Longitudinal Aging Study India

INTRODUCTION

The human health impacts of disaster are predicted to increase in frequency and severity due to the effects of climate change. This has impacts on all nations, but understanding disaster-related health impacts in highly populous nations, such as India, will help to inform risk preparedness and reduction measures for large proportions of the global population.

PROBLEM

Disaster-related human health impacts in India were examined via the use of survey data to inform risk reduction.

METHODS

A cross-sectional analysis of Wave 1 (2017-2018) data from the Longitudinal Aging Study India (LASI) was conducted to explore the impact of both natural and human-induced disasters on the self-reported health of people 45 years and above, as well as their partners (irrespective of age). Descriptive statistics, chi square tests of association, odds ratio, and logistic regression were used to analyze the data by socio-demographics, geographic location, and health concern type.

RESULTS

Out of a total 72,250 respondents, 2,301 (3.5%) reported disaster-related health impacts, of which 90.1% were significant. Rural residents and those with no education were more likely to be affected. Droughts were most commonly responsible for affecting human health (41.7%), followed by floods (24.0%). Two-thirds of the sample reported psychological trauma and one-in-five experienced chronic illness.

DISCUSSION

The LASI study presents an important first understanding of the self-reported human health impacts of disasters, both natural and human-induced in India. Findings indicate social determinants such as education level and rurality impact risk of disaster-related health impacts, while mental health concerns represent the biggest disaster-related health concern.

CONCLUSION

Future waves of LASI should be examined to determine if human health impacts are increasing due to the effects of climate change, as well as the vulnerability of an aging cohort.

Association between sleep quality, sleep duration, and physical frailty among adults aged 50 years and older in India

BACKGROUND

Considering the significant growth in India's aging population, it is imperative to identify factors associated with frailty among older Indians. This study examined the association between sleep quality, sleep duration, and physical frailty among older adults in India. Moreover, we examined whether the associations between sleep quality, sleep duration, and physical frailty varied by gender.

METHODS

In this secondary analysis, we used data from the 2015 wave 2 of the Study on Global Aging and Adult Health (WHO-SAGE) in India, comprising a sample of 6,512 older adults aged 50 years and above. Pre-frailty and frailty were assessed using the modified version of the frailty phenotype developed by Fried and colleagues. Sleep was assessed by self-reported quality and duration. Multinomial and multivariable logistic regression models were used to examine the associations between sleep quality, sleep duration, and physical frailty (including its components), as well as to explore the moderating effect of gender.

RESULTS

66.8% of older Indians were pre-frail, while 25.2% were frail. Relative to those with good sleep quality, older adults with poor sleep quality had significantly higher odds of frailty [AOR: 2.79; CI: 1.37-5.66]. Compared to those receiving the recommended age-appropriate 7-8 h of sleep, older adults sleeping ≥ 9 h reported a significantly lower likelihood of both pre-frailty [AOR: 0.73; CI: 0.57-0.93] and frailty [AOR: 0.68; CI: 0.51-0.91]. Analysis of specific components of frailty showed that older adults with long sleep had lower odds of exhaustion [AOR: 0.86; CI: 0.73-1.00] compared to those with age-appropriate sleep duration. Moreover, frailty was more pronounced in older men with poor sleep quality and short sleep duration (< 7 h/night) than in older women with similar sleep patterns. Poor sleep quality was not linked to any of the frailty components in older women; however, in older men, it was associated with exhaustion [AOR: 4.28; CI: 2.28-8.06], weak grip strength [AOR: 2.31; CI: 1.46-3.67], and low physical activity [AOR: 2.81; CI: 1.10-7.21].

CONCLUSION

The findings indicate potential associations between sleep quality, sleep quantity, and physical frailty among older Indians. Poor sleep quality was associated with frailty, yet long sleep duration was associated with a lower prevalence of frailty, independent of sleep quality. Moreover, the prevalence of frailty associated with poor sleep quality and shorter sleep duration was more pronounced among older Indian men than women, underscoring the need for targeted interventions to address sleep-related concerns in this demographic.

Enhancing the city-level thermal environment through the strategic utilization of urban green spaces employing geospatial techniques

Smart urban planning needs to have a multicriteria-based approach to prevent the deteriorating local thermal climate. Maximizing the cooling potential using the available grey infrastructure would be the utmost priority of future smart cities. Remote sensing and GIS can be the appropriate tools to develop a climate-resilient urban planning framework. Studies are needed to include different features of vertical and horizontal landscaping to mitigate heat stress and enhance liveability at the city level. With this goal, the current work outlined a holistic approach to efficiently using green spaces with minimal reconstruction. The problem of regional climate threat was evaluated with urban heat island characterization. Moran's I clustering identified nearly 12% of the study area to be under considerable heat stress during summer days. Multiple techniques, such as mapping local climate zones, segment mean shift-based roof extraction, vegetation index computation, solar azimuth-based green wall site selection, etc., were applied to formulate solutions and provide an integrated method for city-level environment enhancement. A considerable area was identified as most suitable for green roof cover, and it was also computed that the transition towards green roof at only these locations may bring down the maximum heat island intensity by 0.74 °C. Additionally, solar zenith, illumination effect, and building height information were combined to create a distinct method where vertical plantation would flourish exceptionally. A rigorous assessment of more than 130 urban green spaces further quantified the relation between landscape geometry and cooling effect to provide optimum green space designs for future urban planning.

Spatiotemporal link between El Niño Southern Oscillation (ENSO), extreme heat, and thermal stress in the Asia-Pacific region

Climate change is closely monitored and numerous studies reports increasing air temperature and weather extremes across the globe. As a direct consequence of the increase of global temperature, the increased heat stress is becoming a global threat to public health. While most climate change and epidemiological studies focus on air temperature to explain the increasing risks, heat strain can be predicted using comprehensive indices such as Universal Thermal Climate Index (UTCI). The Asia-Pacific region is prone to thermal stress and the high population densities in the region impose high health risk. This study evaluated the air temperature and UTCI trends between 1990 and 2019 and found significant increasing trends for air temperature for the whole region while the increases of UTCI are not as pronounced and mainly found in the northern part of the region. These results indicate that even though air temperature is increasing, the risks of heat stress when assessed using UTCI may be alleviated by other factors. The associations between El Niño Southern Oscillation (ENSO) and heat stress was evaluated on a seasonal level and the strongest regional responses were found during December-January (DJF) and March-May (MAM).

Metabolomics analysis to interpret changes in physiological and metabolic responses to chronic heat stress in Pekin ducks

Heat stress (HS) is a major environmental threat that affects duck production in subtropical and tropical regions, especially in summer. This study aimed to evaluate the physiological and metabolic responses of Pekin ducks to chronic HS conditions via liquid chromatography-mass spectrometry (LC-MS) using a paired-fed (PF) experimental design. On the basis of equivalent feed intake (HS vs. PF), HS significantly reduced growth performance and the percentage of leg and breast muscles, however, markedly increased the percentage of abdominal fat and breast skin fat. Serum metabolomics results revealed that heat-stressed ducks showed enhanced glycolysis and pentose phosphate pathways, as demonstrated by higher glucose 6-phosphate and 6-phogluconic acid levels in the PF vs. HS comparison. HS decreased hepatic mRNA levels of mitochondrial fatty acid β-oxidation-related genes (MCAD and SCAD) compared to the PF group, resulting in acetylcarnitine accumulation in serum. Moreover, HS elevated the concentrations of serum amino acids and mRNA levels of ubiquitination-related genes (MuRF1 and MAFbx) in the skeletal muscle and amino acid transporter-related genes (SLC1A1 and SLC7A1) and gluconeogenesis-related genes (PCK1 and PCase) in the liver compared to the PF group. When compared to the normal control group (NC), HS further decreased growth performance, but it elevated the abdominal fat rate. However, increased mRNA levels of ubiquitination-related genes and serum amino acid accumulation were not observed in the HS group compared to the NC group, implying that reduced feed intake masked the effect of HS on skeletal muscle breakdown and is a form of protection for the organism. These results suggest that chronic HS induces protein degradation in the skeletal muscle to provide amino acids for hepatic gluconeogenesis to provide sufficient energy, as Pekin ducks under HS conditions failed to efficiently oxidise fatty acids and ketones in the mitochondria, leading to poor growth performance and slaughter characteristics.

Excess Mortality Risk Due to Heat Stress in Different Climatic Zones of India

India is at a high risk of heat stress-induced health impacts and economic losses owing to its tropical climate, high population density, and inadequate adaptive planning. The health impacts of heat stress across climate zones in India have not been adequately explored. Here, we examine and report the vulnerability to heat stress in India using 42 years (1979-2020) of meteorological data from ERA-5 and developed climate-zone-specific percentile-based human comfort class thresholds. We found that the heat stress is usually 1-4 °C higher on heatwave (HW) days than on nonheatwave (NHW) days. However, the stress on NHW days remains considerable and cannot be neglected. We then showed the association of a newly formulated India heat index (IHI) with daily all-cause mortality in three cities - Delhi (semiarid), Varanasi (humid subtropical), and Chennai (tropical wet and dry), using a semiparametric quasi-Poisson regression model, adjusted for nonlinear confounding effects of time and PM2.5. The all-cause mortality risk was enhanced by 8.1% (95% confidence interval, CI: 6.0-10.3), 5.9% (4.6-7.2), and 8.0% (1.7-14.2) during "sweltering" days in Varanasi, Delhi, and Chennai, respectively, relative to "comfortable" days. Across four age groups, the impact was more severe in Varanasi (ranging from a 3.2 to 7.5% increase in mortality risk for a unit rise in IHI) than in Delhi (2.6-4.2% higher risk) and Chennai (0.9-5.7% higher risk). We observed a 3-6 days lag effect of heat stress on mortality in these cities. Our results reveal heterogeneity in heat stress impact across diverse climate zones in India and call for developing an early warning system keeping in mind these regional variations.

Frequency dominates intensity of future heat waves over India

Future changes in heat wave characteristics over India have been analyzed using Coordinated Regional Climate Downscaling Experiments (CORDEX) for South Asia (SA) regional climate model simulations for mid-term (2041-2060) and long-term (2081-2099) future under the representative concentration pathway (RCP) 4.5 and RCP 8.5 emission scenarios, respectively. SMHI_CSIRO-MK3.6 was found to be the best model in simulating heat wave trend over India for historical period. Future projections show a four-to-seven-fold increase in heat wave frequency for mid-term and long-term future under RCP 4.5 scenario, and five-to-ten-fold increase under RCP 8.5 scenario with increase in frequency dominating intensity in both the scenarios. Northwestern, Central, and South-central India emerged as future heat wave hotspots with largest increase in the south-central region. This high-resolution regional future projection of heat wave occurrence will serve as a baseline for developing transformational heat-resilient policies and adaptation measures to reduce potential impact on human health, agriculture, and infrastructure.

A daily high-resolution (1 km) human thermal index collection over the North China Plain from 2003 to 2020

Human-perceived temperature (HPT) describes the joint effects of multiple climatic factors such as temperature and humidity. Extreme HPT events may reduce labor capacity and cause thermal discomfort and even mortality. These events are becoming more frequent and more intense under global warming, posing severe threats to human and natural systems worldwide, particularly in populated areas with intensive human activities, e.g., the North China Plain (NCP). Therefore, a fine-scale HPT dataset in both spatial and temporal dimensions is urgently needed. Here we construct a daily high-resolution (~1 km) human thermal index collection over NCP from 2003 to 2020 (HiTIC-NCP). This dataset contains 12 HPT indices and has high accuracy with averaged determination coefficient, mean absolute error, and root mean squared error of 0.987, 0.970 °C, and 1.292 °C, respectively. Moreover, it exhibits high spatiotemporal consistency with ground-level observations. The dataset provides a reference for human thermal environment and could facilitate studies such as natural hazards, regional climate change, and urban planning.

Variability of heat stress using the UrbClim climate model in the city of Seville (Spain): mitigation proposal

Climate change is creating an increase in temperatures, which is harming the quality of life of people all over the world, particularly those with minimal financial resources. While 30% of the world's population is now vulnerable to extreme heat, estimates show that ratio will rise to 74% in the next 20 years, according to forecasts. Using the UrbClim climate model, this study examines the space-time variability of the heat stress index (HI) in different local climate zones (LCZs), as well as how heat wave conditions might affect this index based on land use and land cover. To that end, Seville, in Southern Spain, was investigated during the summer of 2017, when it had four heat waves. The following indices were considered for each urban sub-area: Normalized Difference Vegetation, Proportion Vegetation, Normalized Difference Built, and Urban Index. The goal is to conduct a statistical analysis of the link between the aforementioned elements and the heat stress index in order to recommend mitigation and resilience techniques. Our findings showed that compact and industrial LCZs (2, 3, and 10) are less resistant to HI than open and rural regions (5, 6, B, D, and G), which are more resistant to HI due to higher vegetation rates. The heat wave condition exacerbates the HI in all LCZs. As a result, initiatives such as enhancing open space, increasing green space, or using green roofs and façades might alleviate heat stress and improve people's quality of life.

The 2022 Summer record-breaking heatwave and health information-seeking behaviours: an infodemiology study in Mainland China

INTRODUCTION

Heatwave is a major global health concern. Many countries including China suffered a record-breaking heatwave during the summer of 2022, which may have a significant effect on population health or health information-seeking behaviours but is yet to be examined.

METHODS

We derived health information-seeking data from the Baidu search engine (similar to Google search engine). The data included city-specific daily search queries (also referred to Baidu Search Index) for heat-sensitive diseases from 2021 to 2022, including heatstroke, hospital visits, cardiovascular diseases and diabetes, respiratory diseases, mental health and urological diseases. For each city, the record-breaking heatwave days in 2022 were matched to days in the same calendar month in 2021.

RESULTS

The 2022 record-breaking heatwave hit most cities (83.64%) in Mainland China. The average heatwave duration was 13 days and the maximum temperature was 3.60°C higher than that in 2021 (p<0.05). We observed increased population behaviours of seeking information on respiratory diseases (RR=1.014, 95% CI: 1.008 to 1.020), urological diseases (RR=1.011, 95% CI: 1.006 to 1.016) and heatstroke (RR=1.026, 95% CI: 1.016 to 1.036) associated with the heatwave intensity in 2022 (per 1°C increase). The heatwave duration in 2022 (per 1 day increase) was also associated with an increase in seeking information on cardiovascular diseases and diabetes (RR=1.003, 95% CI: 1.002 to 1.004), urological diseases (RR=1.005, 95% CI: 1.002 to 1.008), mental health (RR=1.009, 95% CI: 1.006 to 1.012) and heatstroke (RR=1.038, 95% CI: 1.032 to 1.043). However, there were substantial geographical variations in the effect of the 2022 heatwave intensity and duration on health information-seeking behaviours.

CONCLUSION

This infodemiology study suggests that the 2022 summer unprecedented heatwave in Mainland China has significantly increased population demand for health-related information, especially for heatstroke, urological diseases and mental health. Population-based research of real-time disease data is urgently needed to estimate the negative health impact of the exceptional heatwave in Mainland China and elsewhere.

CMIP6 models informed summer human thermal discomfort conditions in Indian regional hotspot

The frequency and intensity of extreme thermal stress conditions during summer are expected to increase due to climate change. This study examines sixteen models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) that have been bias-adjusted using the quantile delta mapping method. These models provide Universal Thermal Climate Index (UTCI) for summer seasons between 1979 and 2010, which are regridded to a similar spatial grid as ERA5-HEAT (available at 0.25° × 0.25° spatial resolution) using bilinear interpolation. The evaluation compares the summertime climatology and trends of the CMIP6 multi-model ensemble (MME) mean UTCI with ERA5 data, focusing on a regional hotspot in northwest India (NWI). The Pattern Correlation Coefficient (between CMIP6 models and ERA5) values exceeding 0.9 were employed to derive the MME mean of UTCI, which was subsequently used to analyze the climatology and trends of UTCI in the CMIP6 models.The spatial climatological mean of CMIP6 MME UTCI demonstrates significant thermal stress over the NWI region, similar to ERA5. Both ERA5 and CMIP6 MME UTCI show a rising trend in thermal stress conditions over NWI. The temporal variation analysis reveals that NWI experiences higher thermal stress during the summer compared to the rest of India. The number of thermal stress days is also increasing in NWI and major Indian cities according to ERA5 and CMIP6 MME. Future climate projections under different scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) indicate an increasing trend in thermal discomfort conditions throughout the twenty-first century. The projected rates of increase are approximately 0.09 °C per decade, 0.26 °C per decade, and 0.56 °C per decade, respectively. Assessing the near (2022-2059) and far (2060-2100) future, all three scenarios suggest a rise in intense heat stress days (UTCI > 38 °C) in NWI. Notably, the CMIP6 models predict that NWI could reach deadly levels of heat stress under the high-emission (SSP5-8.5) scenario. The findings underscore the urgency of addressing climate change and its potential impacts on human well-being and socio-economic sectors.

Gulf Cooperation Council countries' water and climate research to strengthen UN's SDGs 6 and 13

Clean water and sanitation and climate actions represent two of the seventeen United Nations Sustainable Development Goals (SDGs). Although challenging, the two goals can be achieved by 2030 through unconventional and innovative solutions. Scientific research related to clean water and sanitation (SDG 6) and urgent actions to combat climate change and its impacts (SDG 13) will help develop new technologies to support the two goals and can bridge the gap between practitioners and academia's to achieve sustainability. The Gulf Cooperation Council (GCC) countries are located in an arid region. Their water and climate research activities and outcomes may provide a good contribution toward achieving the two goals. This study used text mining and bibliometric methods to analyze water and climate research contributions to achieve SDGs 6 and 13 in GCC countries. Results revealed that there is an increase in research publications after 2016 in the areas of water and climate in the GCC countries involving a longstanding international collaboration with developed countries. Research topics were focused on wastewater treatment, contamination, heavy metal, groundwater, and climate change impacts. Under SDG 6, most of the publications were research articles (77.3%), followed by reviews (11.1%), and the rest were book chapters and conference papers. For SDG 13, 75.1% of the publications are research articles, 10.9% are conference papers, and 8% are reviews. The research outcomes in the GCC countries have clearly contributed to the development of water and climate strategies and international collaborations to achieve the two goals.

Hot weather hazard analysis over India

Heat waves are often termed as the silent killer and have become even more important as recent studies suggest that the heat wave have become second most devastating extreme weather events in terms of human deaths and losses. It is also been largely realised by scientific community that it is not just the high temperatures which are responsible for the gruesome effect of heat waves but several other meteorological parameters play a vital role in aggravating the impact and causing much more damages. In view of the above the attention of scientific community, weather forecasters as well as disaster managers has shifted to also take into account the different meteorological parameters like maximum and minimum temperatures, relative humidity, wind speed, duration/spell of heat waves and its intensity which are aggravating the impact of heat stress. In this background, this study is undertaken as an attempt to quantify the effect of different meteorological parameters on heat wave on different regions of India for different summer months (March, April, May and June). In this study the impact of individual meteorological parameter as well their cumulative effect is studied based on data of 30 years (1981-2010) for 300 stations. The effect of different meteorological parameters is identified for different months for different regions of the country. Also the cumulative scores are calculated for different regions considering different meteorological parameters, as a first initiative to perform heat hazard analysis and zonation over the entire country. This could serve as initial step for planning mitigation and adaptation strategies throughout the country. These scores as thresholds for different regions may be also useful for operational forecaster's for early impact based warning services as well as for the disaster managers, for taking effective and timely actions.