The effect of average temperature on suicide rates in five urban California counties, 1999-⁠2019: an ecological time series analysis.

BACKGROUND: Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. METHODS: Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. RESULTS: There were over 38,000 deaths by suicide in California's five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025-1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021-1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023-1.0153) were similar. CONCLUSION: This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

Substance-related poisoning hospitalizations and homelessness in Canada: a descriptive study. / Étude descriptive des liens entre les hospitalisations pour intoxication liée à la consommation de substances et l'itinérance au Canada.

INTRODUCTION: The objective of this analysis is to describe patient demographics, the context, characteristics and outcomes of a substance-related poisoning, and the recorded mental disorder of people with housing and those experiencing homelessness. METHODS: Hospitalization data for Canada (except Quebec) from 1 April 2019 to 31 March 2020 were retrieved from the Canadian Institute for Health Information (CIHI) Discharge Abstract Database using ICD-10-CA codes for up to 25 diagnoses for substance-related poisonings, homelessness status and other characteristics relevant to the patient's hospitalization. We compared the characteristics of people experiencing homelessness with those of people who were housed, and their substance-related poisoning hospitalizations, using chi-square, t tests and Fisher exact test. RESULTS: There was a higher proportion of males, younger individuals and people with recorded mental disorders among people experiencing homelessness hospitalized for a substance-related poisoning than among their housed counterparts. Substance-related poisonings among people experiencing homelessness were more likely to be accidental, involve opioids and stimulants (most frequently fentanyl and its analogues and heroin), result in lengthier hospitalizations and end with leaving the hospital against medical advice. CONCLUSION: These findings can be used to strengthen strategies and interventions to reduce substance-related harms in priority populations, particularly those experiencing homelessness.

A Dynamic Model of Opioid Overdose Deaths in Canada during the Co-Occurring Opioid Overdose Crisis and COVID-19 Pandemic.

With over 40,000 opioid-related overdose deaths between January 2016 and June 2023, the opioid-overdose crisis is a significant public health concern for Canada. The opioid crisis arose from a complex system involving prescription opioid use, the use of prescription opioids not as prescribed, and non-medical opioid use. The increasing presence of fentanyl and its analogues in the illegal drugs supply has been an important driver of the crisis. In response to the overdose crisis, governments at the municipal, provincial/territorial, and federal levels have increased actions to address opioid-related harms. At the onset of the COVID-19 pandemic, concerns emerged over how the pandemic context may impact the opioid overdose crisis. Using evidence from a number of sources, we developed a dynamic mathematical model of opioid overdose death to simulate possible trajectories of overdose deaths during the COVID-19 pandemic. This model incorporates information on prescription opioid use, opioid use not as prescribed, non-medical opioid use, the level of fentanyl in the drug supply, and a measure of the proportion deaths preventable by new interventions. The simulated scenarios provided decision makers with insight into possible trajectories of the opioid crisis in Canada during the COVID-19 pandemic, highlighting the potential of the crisis to take a turn for the worse under certain assumptions, and thus, informing planning during a period when surveillance data were not yet available. This model provides a starting point for future models, and through its development, we have identified important data and evidence gaps that need to be filled in order to inform future action.

Sensitivity and specificity of International Classification of Diseases algorithms (ICD-9 and ICD-10) used to identify opioid-related overdose cases: A systematic review and an example of estimation using Bayesian latent class models in the absence of gold standards.

OBJECTIVES: This study aimed to summarize validity estimates of International Classification of Diseases (ICD) codes in identifying opioid overdose (OOD) among patient data from emergency rooms, emergency medical services, inpatient, outpatient, administrative, medical claims, and mortality, and estimate the sensitivity and specificity of the algorithms in the absence of a perfect reference standard. METHODS: We systematically reviewed studies published before December 8, 2023, and identified with Medline and Embase. Studies reporting sufficient details to recreate a 2 × 2 table comparing the ICD algorithms to a reference standard in diagnosing OOD-related events were included. We used Bayesian latent class models (BLCM) to estimate the posterior sensitivity and specificity distributions of five ICD-10 algorithms and of the imperfect coroner's report review (CRR) in detecting prescription opioid-related deaths (POD) using one included study. RESULTS: Of a total of 1990 studies reviewed, three were included. The reported sensitivity estimates of ICD algorithms for OOD were low (range from 25.0% to 56.8%) for ICD-9 in diagnosing non-fatal OOD-related events and moderate (72% to 89%) for ICD-10 in diagnosing POD. The last included study used ICD-9 for non-fatal and fatal and ICD-10 for fatal OOD-related events and showed high sensitivity (i.e. above 97%). The specificity estimates of ICD algorithms were good to excellent in the three included studies. The misclassification-adjusted ICD-10 algorithm sensitivity estimates for POD from BLCM were consistently higher than reported sensitivity estimates that assumed CRR was perfect. CONCLUSION: Evidence on the performance of ICD algorithms in detecting OOD events is scarce, and the absence of bias correction for imperfect tests leads to an underestimation of the sensitivity of ICD code estimates.

RéSUMé: OBJECTIFS: Cette étude avait pour objectifs de recenser les estimations de la validité des codes de Classification Internationale des Maladies (CIM) à diagnostiquer les cas de surdose aux opioïdes (SDO) chez des patients en utilisant les données de salles d'urgence, services médicaux d'urgence, hospitalisations, soins ambulatoires, services administratifs, demandes de remboursement de frais médicaux, ainsi que de mortalité, et d'estimer la sensibilité et la spécificité d'algorithmes utilisant la CIM en l'absence d'un test de référence parfait. MéTHODES: Nous avons examiné systématiquement les études publiées avant le 8 décembre 2023, et identifiées dans Medline et Embase. Les études rapportant suffisamment de détails permettant de recréer un tableau 2 × 2 comparant les algorithmes de la CIM à un test de référence pour le diagnostic d'événements liés aux SDO ont été incluses. Les données d'une étude éligible ont été utilisées pour estimer, avec des modèles Bayésiens de classes latentes (MBCL), les distributions a posteriori de la sensibilité et de la spécificité de cinq algorithmes de la CIM-10 et du test imparfait de révision du rapport du coroner (RRC) dans la détection des décès liés aux opioïdes de prescription (DOP). RéSULTATS: Trois parmi les 1 990 études examinées ont été retenues. Les estimations rapportées de la sensibilité des codes CIM étaient faibles (variant de 25,0 % à 56,8 %) pour CIM-9 dans le diagnostic des événements liés aux SDO non-fatales dans une étude, et modérées (72 % à 89 %) pour CIM-10 dans le diagnostic des DOP dans une autre étude. La dernière étude incluse combinait des codes CIM-9 pour les cas non-fatals et fatals et CIM-10 pour les cas fatals et démontrait des estimations de sensibilité élevées (c.à.d. supérieures à 97 %). Les estimations de la spécificité étaient bonnes à excellentes dans les trois études. Les estimations de la sensibilité des algorithmes de la CIM-10 corrigées pour les erreurs de classification pour les décès liés aux opioïdes, obtenues à partir de nos MBCL, étaient systématiquement plus élevées que celles rapportées et qui supposaient que RRC était un test parfait. CONCLUSION: Les évidences sur la performance des algorithmes de la CIM dans la détection des cas de SDO sont rares, et l'absence de correction de biais pour des tests diagnostiques imparfaits conduit à une sous-estimation de la sensibilité des codes de la CIM.

Neonatal abstinence syndrome hospitalizations in Canada: a descriptive study.

OBJECTIVE: The objective of this paper is to describe the trend of newborn hospitalizations with neonatal abstinence syndrome (NAS) in Canada, between 2010 and 2020, and to examine severity indicators for these hospitalizations. METHODS: National hospitalization data (excluding Quebec) from the Canadian Institute for Health Information's Discharge Abstract Database, from January 2010 to March 2021, and Statistics Canada's Vital Statistics Birth Database were used. Analyses were performed to examine NAS hospitalizations by year and quarter, and by severity indicators of length of stay, Special Care Unit admission and status upon discharge. Severity indicators were further stratified by gestational age at birth. RESULTS: An increasing number and rate of NAS hospitalizations in Canada between 2010 (n = 1013, 3.5 per 1000 live births) and 2020 (n = 1755, 6.3 per 1000 live births) were identified. A seasonal pattern was observed, where rates of NAS were lowest from April to June and highest from October to March. Mean length of stay in acute inpatient care was approximately 15 days and 71% of NAS hospitalizations were admitted to the Special Care Unit. Hospitalizations for pre-term births with NAS had longer durations and greater rates of Special Care Unit admissions compared to term births with NAS. CONCLUSION: The number and rate of NAS hospitalizations in Canada increased during the study, and some infants required a significant amount of specialized healthcare. Additional research is required to determine what supports and education for pregnant people can reduce the incidence of NAS hospitalizations.

RéSUMé: OBJECTIF: Le présent article a pour but de décrire la tendance des hospitalisations de nouveau-nés atteints du syndrome d'abstinence néonatale (SAN) au Canada, entre 2010 et 2020, et d'examiner les indicateurs de gravité de ces hospitalisations. MéTHODE: Les données nationales sur les hospitalisations (à l'exclusion du Québec) provenant de la base de données sur les congés des patients de l'Institut canadien d'information sur la santé, de janvier 2010 à mars 2021, ainsi que la base de données sur les naissances des statistiques de l'état civil de Statistique Canada ont été utilisées. Des analyses ont été réalisées pour examiner les hospitalisations liées au SAN par année et par trimestre, et par indicateurs de gravité de la durée du séjour, de l'admission dans une unité de soins spéciaux et de l'état à la sortie de l'hôpital. Les indicateurs de gravité ont en outre été stratifiés en fonction de l'âge gestationnel à la naissance. RéSULTATS: Un nombre et un taux croissants d'hospitalisations liées au SAN au Canada entre 2010 (n=1 013, 3,5 pour 1 000 naissances vivantes) et 2020 (n=1 755, 6,3 pour 1 000 naissances vivantes) ont été identifiés. Une tendance saisonnière a été observée, où les taux de SAN étaient les plus bas d'avril à juin et les plus élevés d'octobre à mars. La durée moyenne du séjour en soins de courte durée était d'environ 15 jours et 71 % des hospitalisations liées au SAN ont été admises à l'unité de soins spéciaux. Les hospitalisations pour les accouchements prématurés de nouveau-nés atteints du SAN avaient des durées plus longues et des taux plus élevés d'admissions dans des unités de soins spéciaux par rapport aux naissances à terme de nouveau-nés atteints du SAN. CONCLUSION: Le nombre et le taux d'hospitalisations liées au SAN au Canada ont augmenté au cours de l'étude, et certains nourrissons nécessitent une quantité importante de soins spécialisés. Des recherches supplémentaires sont nécessaires pour déterminer quels soutiens et quelle éducation pour les personnes enceintes peuvent réduire l'incidence des hospitalisations liées au SAN.