BACKGROUND: Climate change increasingly impacts health, particularly of rural populations in sub-Saharan Africa due to their limited resources for adaptation. Understanding these impacts remains a challenge, as continuous monitoring of vital signs in such populations is limited. Wearable devices (wearables) present a viable approach to studying these impacts on human health in real time.
OBJECTIVE: The aim of this study was to assess the feasibility and effectiveness of consumer-grade wearables in measuring the health impacts of weather exposure on physiological responses (including activity, heart rate, body shell temperature, and sleep) of rural populations in western Kenya and to identify the health impacts associated with the weather exposures.
METHODS: We conducted an observational case study in western Kenya by utilizing wearables over a 3-week period to continuously monitor various health metrics such as step count, sleep patterns, heart rate, and body shell temperature. Additionally, a local weather station provided detailed data on environmental conditions such as rainfall and heat, with measurements taken every 15 minutes.
RESULTS: Our cohort comprised 83 participants (42 women and 41 men), with an average age of 33 years. We observed a positive correlation between step count and maximum wet bulb globe temperature (estimate 0.06, SE 0.02; P=.008). Although there was a negative correlation between minimum nighttime temperatures and heat index with sleep duration, these were not statistically significant. No significant correlations were found in other applied models. A cautionary heat index level was recorded on 194 (95.1%) of 204 days. Heavy rainfall (>20 mm/day) occurred on 16 (7.8%) out of 204 days. Despite 10 (21%) out of 47 devices failing, data completeness was high for sleep and step count (mean 82.6%, SD 21.3% and mean 86.1%, SD 18.9%, respectively), but low for heart rate (mean 7%, SD 14%), with adult women showing significantly higher data completeness for heart rate than men (2-sided t test: P=.003; Mann-Whitney U test: P=.001). Body shell temperature data achieved 36.2% (SD 24.5%) completeness.
CONCLUSIONS: Our study provides a nuanced understanding of the health impacts of weather exposures in rural Kenya. Our study\'s application of wearables reveals a significant correlation between physical activity levels and high temperature stress, contrasting with other studies suggesting decreased activity in hotter conditions. This discrepancy invites further investigation into the unique socioenvironmental dynamics at play, particularly in sub-Saharan African contexts. Moreover, the nonsignificant trends observed in sleep disruption due to heat expose the need for localized climate change mitigation strategies, considering the vital role of sleep in health. These findings emphasize the need for context-specific research to inform policy and practice in regions susceptible to the adverse health effects of climate change.

BACKGROUND: Some studies have found hot temperatures to be associated with exacerbations of schizophrenia, namely psychoses. As climate changes faster in Northern countries, our understanding of the association between temperature and hospital admissions (HA) for psychosis needs to be deepened.
OBJECTIVE: 1) Among adults diagnosed with schizophrenia, measure the relationship between mean temperatures and HAs for psychosis during summer. 2) Determine the influence of individual and ecological characteristics on this relationship.
METHODS: A cohort of adults diagnosed with schizophrenia (n = 30,649) was assembled using Quebec\'s Integrated Chronic Disease Surveillance System (QICDSS). The follow-up spanned summers from 2001 to 2019, using hospital data from the QICDSS and meteorological data from the National Aeronautics and Space Administration\'s (NASA) Daymet database. In four geographic regions of the province of Quebec, a conditional logistic regression was used for the case-crossover analysis of the relationship between mean temperatures (at lags up to 6 days) and HAs for psychosis using a distributed lag non-linear model (DLNM). The analyses were adjusted for relative humidity, stratified according to individual (age, sex, and comorbidities) and ecological (material and social deprivation index and exposure to green space) factors, and then pooled through a meta-regression.
RESULTS: The statistical analyses revealed a statistically significant increase in HAs three days (lag 3) after elevated mean temperatures corresponding to the 90th percentile relative to a minimum morbidity temperature (MMT) (OR 1.040; 95% CI 1.008-1.074), while the cumulative effect over six days was not statistically significant (OR 1.052; 95% IC 0.993-1.114). Stratified analyses revealed non statistically significant gradients of increasing HAs relative to increasing material deprivation and decreasing green space levels.
CONCLUSIONS: The statistical analyses conducted in this project showed the pattern of admissions for psychosis after hot days. This finding could be useful to better plan health services in a rapidly changing climate.

Nighttime heat is an important factor in heat-health outcomes, though nighttime heat exposure and its impacts are poorly understood. We assessed overnight heat in indoor (n = 12) and outdoor (n = 3) living spaces in Knoxville, Tennessee, using iButton Hygrochrons in August 2021. Indoor sleep spaces, all of which were air conditioned, reported a variety of overnight conditions. Indoor sleep spaces were both warmer and cooler than outdoor temperatures overnight, and some participants noted having physical health effects of overnight heat in their homes. Downtown outdoor sleep spaces, including a park and encampment, exhibited an urban heat island signal, staying warmer than other outdoor areas. Future research should focus on the intensity and length of the overnight recovery period for individuals and how that affects heat-health outcomes, especially after being exposed to daytime heat. Specifically, do homes reach a cool enough temperature for recovery, and do outdoor sleeping spaces offer a long enough and cool enough period for recovery? We provide some recommendations for such future studies, including (1) focus on purposeful sampling, (2) use deliberate sensor placement for representative results, (3) prepare for participant drop-off due to non-compliance and technological problems, and (4) strategically gather demographic information.

OBJECTIVE: To investigate the association between ambient temperature and preterm birth (PTB) and to estimate the population attributable fraction (PAF) of PTBs due to low and high temperatures.
METHODS: Time-stratified case-crossover design.
METHODS: Japan (46 prefectures, excluding Okinawa), 2011-2020.
METHODS: 214 050 PTBs registered in the Japan Perinatal Registry Network database among 1 908 168 singleton live births.
METHODS: A quasi-Poisson regression model with a distributed lag nonlinear model was employed to assess the associations between daily mean temperature and PTBs for a lag of 0-27 days in each prefecture. A random effects meta-analysis was conducted by combining effect estimates from the 46 prefectures to estimate pooled relative risks (RRs). The PAFs of the PTBs due to below or above the mean of the 46 median temperatures (16.0°C) were calculated.
METHODS: Preterm singleton live births.
RESULTS: The association between daily mean temperature and PTB risk exhibited a U-shaped curve. The adjusted RRs were 1.15 (95% confidence interval [CI] 1.05-1.25) at the mean of the 1st percentiles (0.8°C) and 1.08 (95% CI 1.00-1.17) at the mean of the 99th percentiles (30.2°C) of 46 prefectures, with 16.0°C as the reference temperature. Approximately 2.3% (95% CI 0.6-4.0) of PTBs were attributable to low temperatures.
CONCLUSIONS: Both low and possibly high temperatures were associated with an increased risk of PTBs. These findings may help to inform preventive measures for pregnant women.

The management of the thermal environment to which dogs are exposed should be included in strategies to improve their welfare. An online questionnaire was administered to 624 owners of Siberian Husky dogs residing in Brazil, with the objective of assessing their perceptions regarding their dogs\' capacity to adapt to heat, and its association with the owners\' routine care. Owners who believed that dogs are low-heat-tolerant animals were more likely to report heat response behaviors from their dogs. Overall, owners reported walk with their dogs during early morning, late afternoon and nighttime. They also reported solar radiation as the primary criteria for determining the time to walk with their dogs. However, owners who reported walking with their dogs at noon mentioned time availability as their primary criteria. In conclusion, owners perceive Siberian Husky dogs living in Brazil as being poorly adapted to heat, and this perception appeared to influence their positive attitudes towards protecting their dogs from heat stress by choosing to walk them during times with less solar exposure. However, the lack of time for owners to walk with their dogs during cooler periods can still be a risk factor in exposing the animals to extreme hot conditions.

Crop yields are adversely affected by climate change; therefore, it is crucial to develop climate adaptation strategies to mitigate the impacts of increasing climate variability on the agriculture system to ensure food security. As one of the largest potato-producing provinces in Canada, Prince Edward Island (PEI) has recently experienced significant instability in potato production. PEI\'s local farmers and stakeholders are extremely concerned about the prospects for the future of potato farming industries in the context of climate change. This study aims to use the Decision Support System for Agrotechnology Transfer (DSSAT) potato model to simulate future potato yields under the Coupled Model Intercomparison Project Phase 6 (CMIP6) climate scenarios (including SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The study evaluates the combined effects of changing climatic conditions at local scales (i.e., warming temperature and changing precipitation patterns) and increasing carbon dioxide (CO2) concentration in the atmosphere. The results indicate future significant declines in potato yield in PEI under the current farming practices. In particular, under the high-emission scenarios (e.g., SSP3-7.0 and SSP5-8.5), the potato yield in PEI would decline by 48% and 60% in the 2070s and by 63% and 80% by 2090s; even under the low-emission scenarios (i.e., SSP1-1.9 and SSP1-2.6), the potato yield in PEI would still decline by 6-10%. This implies that it is important to develop effective climate adaptation measures (e.g., adjusting farming practices and introducing supplemental irrigation plans) to ensure the long-term sustainability of potato production in PEI.

BACKGROUND: Despite the substantial disease burden caused by nervous system diseases, few studies have examined the association between ambient temperature and nervous system diseases, especially during cold seasons. Evidence for specific disease subgroups such as Alzheimer\'s and Parkinson\'s is also lacking.
OBJECTIVE: This study examined the association between short-term changes in ambient temperature and nervous system diseases-related mortality in ten Japanese prefectures from 1 January 2010 to 31 December 2019.
METHODS: A two-stage analysis based on a time-stratified case-crossover study design was conducted. A conditional quasi-Poisson regression model with a distributed lag non-linear model for temperature was applied followed by a multivariate random-effects meta-analysis to obtain average associations. Mortality due to all and cause-specific nervous system diseases (major neurodegenerative diseases, Alzheimer\'s, and Parkinson\'s) were analyzed, with consideration for sex and age (0-84 and 85+ years old) subgroups.
RESULTS: We analyzed 162,315 death cases due to nervous system diseases. Cold was associated with all categories of nervous system diseases-related mortality, but not heat. The estimated relative risks for cold, obtained by comparing the 2.5th percentile of daily mean temperature distribution to the minimum mortality temperature (MMT), were 1.43 (95 % CI: 1.28-1.60), 1.37 (95 % CI: 1.17-1.59), 1.53 (95 % CI: 1.07-2.01), and 1.54 (95 % CI: 1.13-2.10) for all nervous system diseases, major neurodegenerative diseases, Alzheimer\'s, and Parkinson\'s, respectively. These associations were also observed in the sex and age subgroups in general but without evidence of effect modification. Heat (the 97.5th percentile of daily mean temperature distribution vs. MMT) was associated with Parkinson\'s disease-related mortality among those aged 85 years and over.
CONCLUSIONS: Cold was associated with an increased risk of nervous system disease-related mortality. The effect of heat was not observed, except for mortality among the elderly aged 85 years and older with Parkinson\'s disease.

Heat-related mortality is an increasingly important public health burden that is expected to worsen with climate change. In addition to long-term trends, there are also interannual variations in heat-related mortality that are of interest for efficient planning of health services. Large-scale climate patterns have an important influence on summer weather and therefore constitute important tools to understand and predict the variations in heat-related mortality.
UNASSIGNED: In this article, we propose to model summer heat-related mortality using seven climate indices through a two-stage analysis using data covering the period 1981-2018 in two metropolitan areas of the province of Québec (Canada): Montréal and Québec. In the first stage, heat attributable fractions are estimated through a time series regression design and distributed lag nonlinear specification. We consider different definitions of heat. In the second stage, estimated attributable fractions are predicted using climate index curves through a functional linear regression model.
UNASSIGNED: Results indicate that the Atlantic Multidecadal Oscillation is the best predictor of heat-related mortality in both Montréal and Québec and that it can predict up to 20% of the interannual variability.
UNASSIGNED: We found evidence that one climate index is predictive of summer heat-related mortality. More research is needed with longer time series and in different spatial contexts. The proposed analysis and the results may nonetheless help public health authorities plan for future mortality related to summer heat.

A genome-wide association study (GWAS) was performed in six environments to identify major or consistent alleles responsible for wheat yield traits in Australia and North China where rainfed farming system is adopted. A panel of 228 spring wheat varieties were genotyped by double digest restriction-site associated DNA genotyping-by-sequencing. A total of 223 significant marker-trait association (MTAs) and 46 candidate genes for large- or consistent-effect MTAs were identified. The results were compared with previous studies based on a mini-review of 23 GWAS analyses on wheat yield. A phenomenon seldom reported in previous studies was that MTAs responsible for the trait tended to cluster together at certain chromosome segments, and many candidate genes were in the form of gene clusters. Although linkage disequilibrium (LD) might contribute to the co-segregation of the regions, it also suggested that marker-assisted selection (MAS) or transgenic method targeting a single gene might not be as effective as MAS targeting a larger genomic region where all the genes or gene clusters underlying play important roles.

Since the 2003 heatwave in Europe, evidence has been rapidly increasing on the association between extreme temperature and all-cause mortality. Little is known, however, about cause-specific cardiovascular mortality, effect modification by air pollution and aircraft noise, and which population groups are the most vulnerable to extreme temperature. We conducted a time-stratified case-crossover study in Zurich, Switzerland, including all adult cardiovascular deaths between 2000 and 2015 with precise individual exposure estimates at home location. We estimated the risk of 24,884 cardiovascular deaths associated with heat and cold using distributed non-linear lag models. We investigated potential effect modification of temperature-related mortality by fine particles, nitrogen dioxide, and night-time aircraft noise and performed stratified analyses across individual and social characteristics. We found increased risk of mortality for heat (odds ratio OR = 1.28 [95% confidence interval: 1.11-1.49] for 99th percentile of daily Tmean (24 °C) versus optimum temperature at 20 °C) and cold (OR = 1.15 [0.95-1.39], 5th percentile of daily Tmean (-3 °C) versus optimum temperature at 20 °C). Heat-related mortality was particularly strong for myocardial infarctions and hypertension related deaths, and among older women (>75 years). Analysis of effect modification also indicated that older women with lower socio-economic position and education are at higher risk for heat-related mortality. PM2.5 increased the risk of heat-related mortality for heart failure, but not all-cause cardiovascular mortality. This study provides useful information for preventing cause-specific cardiovascular temperature-related mortality in moderate climate zones comparable to Switzerland.