Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never ...been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios.
This study had three aims:
) Compare the range in projected impacts that arises from using different adaptation modeling methods;
) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios;
) recommend modeling method(s) to use in future impact assessments.
We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty.
The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty.
Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.
Climate change and rapid population ageing are significant public health challenges. Understanding which health problems are affected by temperature is important for preventing heat and cold-related ...deaths and illnesses, particularly in the elderly. Here we present a systematic review and meta-analysis on the effects of ambient hot and cold temperature (excluding heat/cold wave only studies) on elderly (65+ years) mortality and morbidity.
Time-series or case-crossover studies comprising cause-specific cases of elderly mortality (n=3,933,398) or morbidity (n=12,157,782) were pooled to obtain a percent change (%) in risk for temperature exposure on cause-specific disease outcomes using a random-effects meta-analysis.
A 1°C temperature rise increased cardiovascular (3.44%, 95% CI 3.10–3.78), respiratory (3.60%, 3.18–4.02), and cerebrovascular (1.40%, 0.06–2.75) mortality. A 1°C temperature reduction increased respiratory (2.90%, 1.84–3.97) and cardiovascular (1.66%, 1.19–2.14) mortality. The greatest risk was associated with cold-induced pneumonia (6.89%, 20–12.99) and respiratory morbidity (4.93% 1.54–8.44). A 1°C temperature rise increased cardiovascular, respiratory, diabetes mellitus, genitourinary, infectious disease and heat-related morbidity.
Elevated risks for the elderly were prominent for temperature-induced cerebrovascular, cardiovascular, diabetes, genitourinary, infectious disease, heat-related, and respiratory outcomes. These risks will likely increase with climate change and global ageing.
•Heat and cold exposure elevates elderly risk of cardiovascular and cerebrovascular deaths and respiratory deaths and morbidity.•Climate change and ageing will likely increase the risk of diabetes, renal, infectious disease and heat-induced morbidity.•Temperature risks for elderly populations in Africa, Middle East, Asia and South America are under-represented.
We applied a rigorous search strategy on three relevant databases following the PRISMA protocol. The search retrieved 18 mortality, and 30 morbidity publications eligible for meta-analysis, representing 3,933,398 deaths and 12,157,782 morbidity cases. Robust risk estimates were calculated for a wide range of temperature-sensitive health outcomes in the elderly. Temperature was found to significantly elevate cerebrovascular, cardiovascular, diabetes, genitourinary, and especially respiratory mortality or morbidity risks in the elderly. This study highlights considerable adverse health risks from temperature exposure in a large vulnerable population and provides impetus for climate change policy to address these risks.
Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of ...aggregated insights into how wearables have been used in health research.
In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.
We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.
We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations-wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).
Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.
As the epidemiological transition progresses throughout sub-Saharan Africa, life lived with diseases is an increasingly important part of a population’s burden of disease. The burden of disease of ...climate-sensitive health outcomes is projected to increase considerably within the next decades. Objectively measured, reliable population health data is still limited and is primarily based on perceived illness from recall. Technological advances like non-invasive, consumer-grade wearable devices may play a vital role in alleviating this data gap and in obtaining insights on the disease burden in vulnerable populations, such as heat stress on human cardiovascular response. The overall goal of this study is to investigate whether consumer-grade wearable devices are an acceptable, feasible and valid means to generate data on the individual level in low-resource contexts. Three hundred individuals are recruited from the two study locations in the Nouna health and demographic surveillance system (HDSS), Burkina Faso, and the Siaya HDSS, Kenya. Participants complete a structured questionnaire that comprises question items on acceptability and feasibility under the supervision of trained data collectors. Validity will be evaluated by comparing consumer-grade wearable devices to research-grade devices. Furthermore, we will collect demographic data as well as the data generated by wearable devices. This study will provide insights into the usage of consumer-grade wearable devices to measure individual vital signs in low-resource contexts, such as Burkina Faso and Kenya. Vital signs comprising activity (steps), sleep (duration, quality) and heart rate (hr) are important measures to gain insights on individual behavior and activity patterns in low-resource contexts. These vital signs may be associated with weather variables—as we gather them from weather stations that we have setup as part of this study to cover the whole Nouna and Siaya HDSSs—in order to explore changes in behavior and other variables, such as activity, sleep, hr, during extreme weather events like heat stress exposure. Furthermore, wearable data could be linked to health outcomes and weather events. As a result, consumer-grade wearables may serve as a supporting technology for generating reliable measurements in low-resource contexts and investigating key links between weather occurrences and health outcomes. Thus, wearable devices may provide insights to better inform mitigation and adaptation interventions in these low-resource settings that are direly faced by climate change-induced changes, such as extreme weather events.
ObjectivesQuantify the risk of mental health (MH)-related emergency department visits (EDVs) due to heat, in the city of Curitiba, Brazil.DesignDaily time series analysis, using quasi-Poisson ...combined with distributed lag non-linear model on EDV for MH disorders, from 2017 to 2021.SettingAll nine emergency centres from the public health system, in Curitiba.Participants101 452 EDVs for MH disorders and suicide attempts over 5 years, from patients residing inside the territory of Curitiba.Main outcome measureRelative risk of EDV (RREDV) due to extreme mean temperature (24.5°C, 99th percentile) relative to the median (18.02°C), controlling for long-term trends, air pollution and humidity, and measuring effects delayed up to 10 days.ResultsExtreme heat was associated with higher single-lag EDV risk of RREDV 1.03(95% CI 1.01 to 1.05—single-lag 2), and cumulatively of RREDV 1.15 (95% CI 1.05 to 1.26—lag-cumulative 0–6). Strong risk was observed for patients with suicide attempts (RREDV 1.85, 95% CI 1.08 to 3.16) and neurotic disorders (RREDV 1.18, 95% CI 1.06 to 1.31). As to demographic subgroups, females (RREDV 1.20, 95% CI 1.08 to 1.34) and patients aged 18–64 (RREDV 1.18, 95% CI 1.07 to 1.30) were significantly endangered. Extreme heat resulted in lower risks of EDV for patients with organic disorders (RREDV 0.60, 95% CI 0.40 to 0.89), personality disorders (RREDV 0.48, 95% CI 0.26 to 0.91) and MH in general in the elderly ≥65 (RREDV 0.77, 95% CI 0.60 to 0.98). We found no significant RREDV among males and patients aged 0–17.ConclusionThe risk of MH-related EDV due to heat is elevated for the entire study population, but very differentiated by subgroups. This opens avenue for adaptation policies in healthcare: such as monitoring populations at risk and establishing an early warning systems to prevent exacerbation of MH episodes and to reduce suicide attempts. Further studies are welcome, why the reported risk differences occur and what, if any, role healthcare seeking barriers might play.
Weather, climate, and climate change are affecting human health, with scientific evidence increasing substantially over the past two decades, but with very limited research from low- and ...middle-income countries. The health effects of climate change occur mainly because of the consequences of rising temperatures, rising sea levels, and an increase in extreme weather events. These exposures interact with demographic, socio-economic, and environmental factors, as well as access to and the quality of health care, to affect the magnitude and pattern of risks. Health risks are unevenly distributed around the world, and within countries and across population groups. Existing health challenges and inequalities are likely to be exacerbated by climate change. This narrative review provides an overview of the health impacts of weather, climate, and climate change, particularly on vulnerable regions and populations in sub-Saharan Africa and South Asia, and discusses the importance of protecting human health in a changing climate; such measures are critical to reducing poverty and inequality at all scales. Three case summaries from the INDEPTH Health and Demographic Surveillance Systems highlight examples of research that quantified associations between weather and health outcomes. These and comparable surveillance systems can provide critical knowledge to increase resilience and decrease inequalities in an increasingly warming world.
High ambient air temperatures in Africa pose significant health and behavioral challenges in populations with limited access to cooling adaptations. The built environment can exacerbate heat ...exposure, making passive home cooling adaptations a potential method for protecting occupants against indoor heat exposure.
We are conducting a 2-year community-based stratified cluster randomized controlled trial (cRCT) implementing sunlight-reflecting roof coatings, known as "cool roofs," as a climate change adaptation intervention for passive indoor home cooling. Our primary research objective is to investigate the effects of cool roofs on health, indoor climate, economic, and behavioral outcomes in rural Burkina Faso. This cRCT is nested in the Nouna Health and Demographic Surveillance System (HDSS), a population-based dynamic cohort study of all people living in a geographically contiguous area covering 59 villages, 14305 households and 28610 individuals. We recruited 1200 participants, one woman and one man, each in 600 households in 25 villages in the Nouna HDSS. We stratified our sample by (i) village and (ii) two prevalent roof types in this area of Burkina Faso: mud brick and tin. We randomized the same number of people (12) and homes (6) in each stratum 1:1 to receiving vs. not receiving the cool roof. We are collecting outcome data on one primary endpoint - heart rate, (a measure of heat stress) and 22 secondary outcomes encompassing indoor climate parameters, blood pressure, body temperature, heat-related outcomes, blood glucose, sleep, cognition, mental health, health facility utilization, economic and productivity outcomes, mosquito count, life satisfaction, gender-based violence, and food consumption. We followed all participants for 2 years, conducting monthly home visits to collect objective and subjective outcomes. Approximately 12% of participants (n = 152) used smartwatches to continuously measure endpoints including heart rate, sleep and activity.
Our study demonstrates the potential of large-scale cRCTs to evaluate novel climate change adaptation interventions and provide evidence supporting investments in heat resilience in sub-Saharan Africa. By conducting this research, we will contribute to better policies and interventions to help climate-vulnerable populations ward off the detrimental effects of extreme indoor heat on health.
German Clinical Trials Register (DRKS) DRKS00023207. Registered on April 19, 2021.
Temperature, precipitation, relative humidity (RH), and Normalized Different Vegetation Index (NDVI), influence malaria transmission dynamics. However, an understanding of interactions between ...socioeconomic indicators, environmental factors and malaria incidence can help design interventions to alleviate the high burden of malaria infections on vulnerable populations. Our study thus aimed to investigate the socioeconomic and climatological factors influencing spatial and temporal variability of malaria infections in Mozambique.
We used monthly malaria cases from 2016 to 2018 at the district level. We developed an hierarchical spatial-temporal model in a Bayesian framework. Monthly malaria cases were assumed to follow a negative binomial distribution. We used integrated nested Laplace approximation (INLA) in R for Bayesian inference and distributed lag nonlinear modeling (DLNM) framework to explore exposure-response relationships between climate variables and risk of malaria infection in Mozambique, while adjusting for socioeconomic factors.
A total of 19,948,295 malaria cases were reported between 2016 and 2018 in Mozambique. Malaria risk increased with higher monthly mean temperatures between 20 and 29°C, at mean temperature of 25°C, the risk of malaria was 3.45 times higher (RR 3.45 95%CI: 2.37-5.03). Malaria risk was greatest for NDVI above 0.22. The risk of malaria was 1.34 times higher (1.34 1.01-1.79) at monthly RH of 55%. Malaria risk reduced by 26.1%, for total monthly precipitation of 480 mm (0.739 95%CI: 0.61-0.90) at lag 2 months, while for lower total monthly precipitation of 10 mm, the risk of malaria was 1.87 times higher (1.87 1.30-2.69). After adjusting for climate variables, having lower level of education significantly increased malaria risk (1.034 1.014-1.054) and having electricity (0.979 0.967-0.992) and sharing toilet facilities (0.957 0.924-0.991) significantly reduced malaria risk.
Our current study identified lag patterns and association between climate variables and malaria incidence in Mozambique. Extremes in climate variables were associated with an increased risk of malaria transmission, peaks in transmission were varied. Our findings provide insights for designing early warning, prevention, and control strategies to minimize seasonal malaria surges and associated infections in Mozambique a region where Malaria causes substantial burden from illness and deaths.
Mobile health (mHealth) interventions hold promise for addressing the epidemic of noncommunicable diseases (NCDs) in low- and middle-income countries (LMICs) by assisting healthcare providers ...managing these disorders in low-resource settings. We aimed to systematically identify and assess provider-facing mHealth applications used to screen for, diagnose, or monitor NCDs in LMICs. In this systematic review, we searched the indexing databases of PubMed, Web of Science, and Cochrane Central for studies published between January 2007 and October 2019. We included studies of technologies that were: (i) mobile phone- or tablet-based, (ii) able to screen for, diagnose, or monitor an NCD of public health importance in LMICs, and (iii) targeting health professionals as users. We extracted disease type, intervention purpose, target population, study population, sample size, study methodology, technology stage, country of development, operating system, and cost. Our initial search retrieved 13,262 studies, 315 of which met inclusion criteria and were analyzed. Cardiology was the most common clinical domain of the technologies evaluated, with 89 publications. mHealth innovations were predominantly developed using Apple's iOS operating system. Cost data were provided in only 50 studies, but most technologies for which this information was available cost less than 20 USD. Only 24 innovations targeted the ten NCDs responsible for the greatest number of disability-adjusted life years lost globally. Most publications evaluated products created in high-income countries. Reported mHealth technologies are well-developed, but their implementation in LMICs faces operating system incompatibility and a relative neglect of NCDs causing the greatest disease burden.
Background
Although climate change is one of the biggest global health threats, individual-level and short-term data on direct exposure and health impacts are still scarce. Wearable electronic ...devices (wearables) present a potential solution to this research gap. Wearables have become widely accepted in various areas of health research for ecological momentary assessment, and some studies have used wearables in the field of climate change and health. However, these studies vary in study design, demographics, and outcome variables, and existing research has not been mapped.
Objective
In this review, we aimed to map existing research on wearables used to detect direct health impacts and individual exposure during climate change–induced weather extremes, such as heat waves or wildfires.
Methods
We conducted a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework and systematically searched 6 databases (PubMed MEDLINE, IEEE Xplore, CINAHL EBSCOhost, WoS, Scopus, Ovid MEDLINE, and Google Scholar). The search yielded 1871 results. Abstracts and full texts were screened by 2 reviewers (MK and IM) independently using the inclusion and exclusion criteria. The inclusion criteria comprised studies published since 2010 that used off-the-shelf wearables that were neither invasive nor obtrusive to the user in the setting of climate change–related weather extremes. Data were charted using a structured form, and the study outcomes were narratively synthesized.
Results
The review included 55,284 study participants using wearables in 53 studies. Most studies were conducted in upper–middle-income and high-income countries (50/53, 94%) in urban environments (25/53, 47%) or in a climatic chamber (19/53, 36%) and assessed the health effects of heat exposure (52/53, 98%). The majority reported adverse health effects of heat exposure on sleep, physical activity, and heart rate. The remaining studies assessed occupational heat stress or compared individual- and area-level heat exposure. In total, 26% (14/53) of studies determined that all examined wearables were valid and reliable for measuring health parameters during heat exposure when compared with standard methods.
Conclusions
Wearables have been used successfully in large-scale research to measure the health implications of climate change–related weather extremes. More research is needed in low-income countries and vulnerable populations with pre-existing conditions. In addition, further research could focus on the health impacts of other climate change–related conditions and the effectiveness of adaptation measures at the individual level to such weather extremes.
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