Heat Exposure and Cause-Specific Hospital Admissions in Spain: A Nationwide Cross-Sectional Study.

BACKGROUND: More frequent and intense exposure to extreme heat conditions poses a serious threat to public health. However, evidence on the association between heat and specific diagnoses of morbidity is still limited. We aimed to comprehensively assess the short-term association between cause-specific hospital admissions and high temperature, including the added effect of temperature variability and heat waves and the effect modification by humidity and air pollution. METHODS: We used data on cause-specific hospital admissions, weather (i.e., temperature and relative humidity), and air pollution [i.e., fine particulate matter with aerodynamic diameter ≤2.5µm (PM2.5), fine particulate matter with aerodynamic diameter ≤10µm (PM10), NO2, and ozone (O3)] for 48 provinces in mainland Spain and the Balearic Islands between 1 January 2006 and 31 December 2019. The statistical analysis was performed for the summer season (June-September) and consisted of two steps. We first applied quasi-Poisson generalized linear regression models in combination with distributed lag nonlinear models (DLNM) to estimate province-specific temperature-morbidity associations, which were then pooled through multilevel univariate/multivariate random-effect meta-analysis. RESULTS: High temperature had a generalized impact on cause-specific hospitalizations, while the added effect of temperature variability [i.e., diurnal temperature range (DTR)] and heat waves was limited to a reduced number of diagnoses. The strongest impact of heat was observed for metabolic disorders and obesity [relative risk (RR) = 1.978; 95% empirical confidence interval (eCI): 1.772, 2.208], followed by renal failure (1.777; 95% eCI: 1.629, 1.939), urinary tract infection (1.746; 95% eCI: 1.578, 1.933), sepsis (1.543; 95% eCI: 1.387, 1.718), urolithiasis (1.490; 95% eCI: 1.338, 1.658), and poisoning by drugs and nonmedicinal substances (1.470; 95% eCI: 1.298, 1.665). We also found differences by sex (depending on the diagnosis of hospitalization) and age (very young children and the elderly were more at risk). Humidity played a role in the association of heat with hospitalizations from acute bronchitis and bronchiolitis and diseases of the muscular system and connective tissue, which were higher in dry days. Moreover, heat-related effects were exacerbated on high pollution days for metabolic disorders and obesity (PM2.5) and diabetes (PM10, O3). DISCUSSION: Short-term exposure to heat was found to be associated with new diagnoses (e.g., metabolic diseases and obesity, blood diseases, acute bronchitis and bronchiolitis, muscular and connective tissue diseases, poisoning by drugs and nonmedicinal substances, complications of surgical and medical care, and symptoms, signs, and ill-defined conditions) and previously identified diagnoses of hospital admissions. The characterization of the vulnerability to heat can help improve clinical and public health practices to reduce the health risks posed by a warming planet. https://doi.org/10.1289/EHP13254.

Ambient temperature and risk of cardiovascular and respiratory adverse health outcomes: a nationwide cross-sectional study from Spain.

AIMS: We assessed the association of temperature and temperature variability with cause-specific emergency hospitalizations and mortality from cardiovascular and respiratory diseases in Spain, as well as the effect modification of this association by individual and contextual factors. METHODS AND RESULTS: We collected data on health (hospital admissions and mortality), weather (temperature and relative humidity), and relevant contextual indicators for 48 Spanish provinces during 2004-2019. The statistical analysis was separately performed for the summer (June-September) and winter (December-March) seasons. We first applied a generalized linear regression model with quasi-Poisson distribution to estimate daily province-specific temperature-health associations, and then we fitted multilevel multivariate meta-regression models to the evaluate effect modification of the contextual characteristics on heat- and cold-related risks. High temperature increased the risk of mortality across all cardiovascular and respiratory diseases, with the strongest effect for hypertension (relative risk (RR) at 99th temperature percentile vs. optimum temperature: 1.510 [95% empirical confidence interval {eCI} 1.251 to 1.821]), heart failure (1.528 [1.353 to 1.725]), and pneumonia (2.224 [1.685 to 2.936]). Heat also had an impact on all respiratory hospitalization causes (except asthma), with similar risks between pneumonia (1.288 [1.240 to 1.339]), acute bronchitis and bronchiolitis (1.307 [1.219 to 1.402]), and chronic obstructive pulmonary disease (1.260 [1.158 to 1.372]). We generally found significant risks related to low temperature for all cardiovascular and respiratory causes, with heart failure (RR at 1st temperature percentile vs. optimum temperature: 1.537 [1.329 to 1.779]) and chronic obstructive pulmonary disease (1.885 [1.646 to 2.159]) exhibiting the greatest risk for hospitalization, and acute myocardial infarction (1.860 [1.546 to 2.238]) and pneumonia (1.734 [1.219 to 2.468]) for mortality. Women and the elderly were more vulnerable to heat, while people with secondary education were less susceptible to cold compared to those not achieving this educational stage. Results from meta-regression showed that increasing heating access to the highest current provincial value (i.e. 95.6%) could reduce deaths due to cold by 59.5% (57.2 to 63.5). CONCLUSION: Exposure to low and high temperatures was associated with a greater risk of morbidity and mortality from multiple cardiovascular and respiratory conditions, and heating was the most effective societal adaptive measure to reduce cold-related mortality.

Exposure to low and high temperatures increases the risk of morbidity and mortality from several cardiovascular and respiratory diseases, especially among the elderly. Increasing access to heating could substantially reduce cold-related mortality burden.

Ambient temperature and seasonal variation in inpatient mortality from respiratory diseases: a retrospective observational study.

Background: The seasonal fluctuation in mortality and hospital admissions from respiratory diseases, with a winter peak and a summer trough, is widely recognized in extratropical countries. However, little is known about the seasonality of inpatient mortality and the role of ambient temperature remains uncertain. We aimed to analyse the association between ambient temperature and in-hospital mortality from respiratory diseases in the provinces of Madrid and Barcelona, Spain. Methods: We used data on daily hospitalisations, weather (ie, temperature and relative humidity) and air pollutants (ie, PM2.5, PM10, NO2 and O3) for the Spanish provinces of Madrid and Barcelona during 2006-2019. We applied a daily time-series quasi-Poisson regression in combination with distributed lag non-linear models (DLNM) to assess, on the one hand, the seasonal variation in fatal hospitalisations and the contribution of ambient temperature, and on the other hand, the day-to-day association between temperature and fatal hospital admissions. The analyses were stratified by sex, age and primary diagnostic of hospitalisation. Findings: The study analysed 1 710 012 emergency hospital admissions for respiratory diseases (mean [SD] age, 60.4 [31.0] years; 44.2% women), from which 103 845 resulted in in-hospital death (81.4 [12.3] years; 45.1%). We found a strong seasonal fluctuation in in-hospital mortality from respiratory diseases. While hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures. When analysing the day-to-day association between temperature and in-hospital mortality, we only found an effect for high temperatures. The relative risk (RR) of fatal hospitalisation at the 99th percentile of the distribution of daily temperatures vs the minimum mortality temperature (MMT) was 1.395 (95% eCI: 1.211-1.606) in Madrid and 1.612 (1.379-1.885) in Barcelona. In terms of attributable burden, summer temperatures (June-September) were responsible for 16.2% (8.8-23.3) and 22.3% (15.4-29.2) of overall fatal hospitalisations from respiratory diseases in Madrid and Barcelona, respectively. Women were more vulnerable to heat than men, whereas the results by diagnostic of admission showed heat effects for acute bronchitis and bronchiolitis, pneumonia and respiratory failure. Interpretation: Unless effective adaptation measures are taken in hospital facilities, climate warming could exacerbate the burden of inpatient mortality from respiratory diseases during the warm season. Funding: European Research Council Consolidator Grant EARLY-ADAPT, European Research Council Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

Collider and reporting biases involved in the analyses of cause of death associations in death certificates: an illustration with cancer and suicide.

BACKGROUND: Mortality data obtained from death certificates have been studied to explore causal associations between diseases. However, these analyses are subject to collider and reporting biases (selection and information biases, respectively). We aimed to assess to what extent associations of causes of death estimated from individual mortality data can be extrapolated as associations of disease states in the general population. METHODS: We used a multistate model to generate populations of individuals and simulate their health states up to death from national health statistics and artificially replicate collider bias. Associations between health states can then be estimated from such simulated deaths by logistic regression and the magnitude of collider bias assessed. Reporting bias can be approximated by comparing the estimates obtained from the observed death certificates (subject to collider and reporting biases) with those obtained from the simulated deaths (subject to collider bias only). As an illustrative example, we estimated the association between cancer and suicide in French death certificates and found that cancer was negatively associated with suicide. Collider bias, due to conditioning inclusion in the study population on death, increasingly downwarded the associations with cancer site lethality. Reporting bias was much stronger than collider bias and depended on the cancer site, but not prognosis. RESULTS: The magnitude of the biases ranged from 1.7 to 9.3 for collider bias, and from 4.7 to 64 for reporting bias. CONCLUSIONS: These results argue for an assessment of the magnitude of both collider and reporting biases before performing analyses of cause of death associations exclusively from mortality data. If these biases cannot be corrected, results from these analyses should not be extrapolated to the general population.

Drivers of the time-varying heat-cold-mortality association in Spain: A longitudinal observational study.

BACKGROUND: A number of studies have reported reductions in mortality risk due to heat and cold over time. However, questions remain about the drivers of these adaptation processes to ambient temperatures. We aimed to analyse the demographic and socioeconomic drivers of the downward trends in vulnerability to heat- and cold-related mortality observed in Spain during recent decades (1980-2018). METHODS: We collected data on all-cause mortality, temperature and relevant contextual indicators for 48 provinces in mainland Spain and the Balearic Islands between Jan 1, 1980, and Dec 31, 2018. Fourteen contextual indicators were analysed representing ageing, isolation, urbanicity, heating, air conditioning (AC), house antiquity and ownership, education, life expectancy, macroeconomics, socioeconomics, and health investment. The statistical analysis was separately performed for the range of months mostly causing heat- (June-September) and cold- (October-May) related mortality. We first applied a quasi-Poisson generalised linear regression in combination with distributed lag non-linear models (DLNM) to estimate province-specific temperature-mortality associations for different periods, and then we fitted univariable and multivariable multilevel spatiotemporal meta-regression models to evaluate the effect modification of the contextual characteristics on heat- and cold-related mortality risks over time. FINDINGS: The average annual mean temperature has risen at an average rate of 0·36 °C per decade in Spain over 1980-2012, although the increase in temperature has been more pronounced in summer (0·40 °C per decade in June-September) than during the rest of the year (0·33 °C per decade). This warming has been observed, however, in parallel with a progressive reduction in the mortality risk associated to both hot and cold temperatures. We found independent associations for AC with heat-related mortality, and heating with cold-related mortality. AC was responsible for about 28·6% (31·5%) of the decrease in deaths due to heat (extreme heat) between 1989 and 1993 and 2009-2013, and heating for about 38·3% (50·8%) of the reductions in deaths due to cold (extreme cold) temperatures. Ageing (ie, proportion of population over 64 years) attenuated the decrease in cold-related mortality. INTERPRETATION: AC and heating are effective societal adaptive measures to heat and cold temperatures. This evidence holds important implications for climate change health adaptation policies, and for the projections of climate change impacts on human health.

Artificial intelligence exceeds humans in epidemiological job coding.

BACKGROUND: Work circumstances can substantially negatively impact health. To explore this, large occupational cohorts of free-text job descriptions are manually coded and linked to exposure. Although several automatic coding tools have been developed, accurate exposure assessment is only feasible with human intervention. METHODS: We developed OPERAS, a customizable decision support system for epidemiological job coding. Using 812,522 entries, we developed and tested classification models for the Professions et Catégories Socioprofessionnelles (PCS)2003, Nomenclature d'Activités Française (NAF)2008, International Standard Classifications of Occupation (ISCO)-88, and ISCO-68. Each code comes with an estimated correctness measure to identify instances potentially requiring expert review. Here, OPERAS' decision support enables an increase in efficiency and accuracy of the coding process through code suggestions. Using the Formaldehyde, Silica, ALOHA, and DOM job-exposure matrices, we assessed the classification models' exposure assessment accuracy. RESULTS: We show that, using expert-coded job descriptions as gold standard, OPERAS realized a 0.66-0.84, 0.62-0.81, 0.60-0.79, and 0.57-0.78 inter-coder reliability (in Cohen's Kappa) on the first, second, third, and fourth coding levels, respectively. These exceed the respective inter-coder reliability of expert coders ranging 0.59-0.76, 0.56-0.71, 0.46-0.63, 0.40-0.56 on the same levels, enabling a 75.0-98.4% exposure assessment accuracy and an estimated 19.7-55.7% minimum workload reduction. CONCLUSIONS: OPERAS secures a high degree of accuracy in occupational classification and exposure assessment of free-text job descriptions, substantially reducing workload. As such, OPERAS significantly outperforms both expert coders and other current coding tools. This enables large-scale, efficient, and effective exposure assessment securing healthy work conditions.

Work can expose us to health risks, such as asbestos and constant noise. To study these risks, job descriptions are collected and classified by experts to standard codes. This is time-consuming, expensive, and requires expert knowledge. To improve this coding, we created computer code based on Artificial Intelligence that can both automate this process and suggest codes to experts, who can then check and change it manually if needed. Our system outperforms both expert coders and other available tools. This system could make studying occupational health risks more efficient and accurate, resulting in safer work environments.

Suicide and All-Cause Mortality Within 1 Year After a Suicide Attempt in the VigilanS Cohort.

Objective: Obtaining better knowledge on the outcomes of patients who attempt suicide is crucial for suicide prevention. The aim of our study was to determine the causes of death 1 year after a suicide attempt (SA) in the VigilanS program, mortality rates, and risk factors associated with any cause of death and suicide.Methods: A prospective cohort of 7,406 people who had attempted suicide between January 1, 2017, and December 31, 2018, was included in the study. The vital status of each participant was sought, and the cause of death was established through a phone call to their general practitioner or psychiatrist. Second, the relationship between sociodemographic and clinical factors and death by suicide within 1 year of an SA was assessed using a multivariable Cox model.Results: At 1 year, 125 (1.7%) participants had died, 77 of whom died by suicide. Half of the deaths occurred within the first 4 months after an SA. Hanging (20.3%; 24/125) and self-poisoning (19.5%; 23/125) were the methods the most often used for suicide. We demonstrated that male sex (HR = 1.79 [1.13-2.82], P = .01) and being 45 years of age or older (between 45 and 64 years old, HR = 2.08 [1.21-3.56], P < .01; 65 years or older, HR = 5.36 [2.72-10.54], P < .01) were associated with a higher risk of death by suicide 1 year after an SA and that being younger than 25 years was associated with a lower risk (HR = 0.22 [0.07-0.76], P = .02).Conclusions: One out of 100 people who attempted suicide died by suicide within 1 year after an SA. Greater vigilance is required in the first months following an SA, especially for males older than 45 years.Trial Registration: ClinicalTrials.gov identifier: NCT03134885.

Reactive surveillance of suicides during the COVID-19 pandemic in France, 2020 to March 2022.

AIMS: Mitigation actions during the COVID-19 pandemic may impact mental health and suicide in general populations. We aimed to analyse the evolution in suicide deaths from 2020 to March 2022 in France. METHODS: Using free-text medical causes in death certificates, we built an algorithm, which aimed to identify suicide deaths. We measured its retrospective performances by comparing suicide deaths identified using the algorithm with deaths which had either a Tenth revision of the International Classification of Diseases (ICD-10) code for 'intentional self-harm' or for 'external cause of undetermined intent' as the underlying cause. The number of suicide deaths from January 2020 to March 2022 was then compared with the expected number estimated using a generalized additive model. The difference and the ratio between the observed and expected number of suicide deaths were calculated on the three lockdown periods and for periods between lockdowns and after the third one. The analysis was stratified by age group and gender. RESULTS: The free-text algorithm demonstrated high performances. From January 2020 to mid-2021, suicide mortality declined during France's three lockdowns, particularly in men. During the periods between and after the two first lockdowns, suicide mortality remained comparable to the expected values, except for men over 85 years old and in 65-84 year-old age group, where a small number of excess deaths was observed in the weeks following the end of first lockdown, and for men aged 45-64 years old, where the decline continued after the second lockdown ended. After the third lockdown until March 2022, an increase in suicide mortality was observed in 18-24 year-old age group for both genders and in men aged 65-84 years old, while a decrease was observed in the 25-44 year-old age group. CONCLUSIONS: This study highlighted the absence of an increase in suicide mortality during France's COVID-19 pandemic and a substantial decline during lockdown periods, something already observed in other countries. The increase in suicide mortality observed in 18-24 year-old age group and in men aged 65-84 years old from mid-2021 to March 2022 suggests a prolonged impact of COVID-19 on mental health, also described on self-harm hospitalizations and emergency department's attendances in France. Further studies are required to explain the factors for this change. Reactive monitoring of suicide mortality needs to be continued since mental health consequences and the increase in suicide mortality may be continued in the future with the international context.

Daylight saving time affects European mortality patterns.

Daylight saving time (DST) consists in a one-hour advancement of legal time in spring offset by a backward transition of the same magnitude in fall. It creates a minimal circadian misalignment that could disrupt sleep and homoeostasis in susceptible individuals and lead to an increased incidence of pathologies and accidents during the weeks immediately following both transitions. How this shift affects mortality dynamics on a large population scale remains, however, unknown. This study examines the impact of DST on all-cause mortality in 16 European countries for the period 1998-2012. It shows that mortality decreases in spring and increases in fall during the first two weeks following each DST transition. Moreover, the alignment of time data around DST transition dates revealed a septadian mortality pattern (lowest on Sundays, highest on Mondays) that persists all-year round, irrespective of seasonal variations, in men and women aged above 40.

Association of Daily Temperature With Suicide Mortality: A Comparison With Other Causes of Death and Characterization of Possible Attenuation Across 5 Decades.

Suicide is one of the leading causes of death in young adults in many Western countries. We examined the short-term association of temperature with cause-specific mortality, comparing suicide with other causes of death and describing possible attenuation of associations with temperature across decades. We considered all deaths that occurred in France between 1968 and 2016. For each cause of death, we conducted a 2-stage meta-analysis of associations with daily temperature. We stratified the association across time periods. A total of 502,017 deaths by suicide were recorded over 49 years. Temperature was monotonically associated with suicide mortality. The strongest association was found at lag 0 days. The relative risk of suicide mortality at the 99th (compared with the 1st) temperature percentile was 1.54 (95% confidence interval, 1.46, 1.63). Among all causes of death, suicide was the only cause displaying a monotonic trend with temperature and ranked seventh for heat-related mortality; 2 other causes of death implying the nervous system ranked third and fourth. Associations with temperature attenuated between the 1968-1984 and 1985-2000 periods for all-cause mortality and suicide mortality, without clear further attenuation in the 2001-2016 period. The robust short-term monotonic association between temperature and suicide risk could be considered in heat effects- and suicide-related prevention campaigns.