Change in employment status and its causal effect on suicidal ideation and depressive symptoms: A marginal structural model with machine learning algorithms.

OBJECTIVE: This study aimed to assess the causal effect of a change in employment status on suicidal ideation and depressive symptoms by applying marginal structural models (MSM) with machine-learning (ML) algorithms. METHODS: We analyzed data from the 8-15th waves (2013-2020) of the Korean Welfare Panel Study, a nationally representative longitudinal dataset. Our analysis included 13 294 observations from 3621 participants who had standard employment at baseline (2013-2019). Based on employment status at follow-up year (2014-2020), respondents were classified into two groups: (i) maintained standard employment (reference group), (ii) changed to non-standard employment. Suicidal ideation during the past year and depressive symptoms during the past week were assessed through self-report questionnaire. To apply the ML algorithms to the MSM, we conducted eight ML algorithms to build the propensity score indicating a change in employment status. Then, we applied the MSM to examine the causal effect by using inverse probability weights calculated based on the propensity score from ML algorithms. RESULTS: The random forest algorithm performed best among all algorithms, showing the highest area under the curve 0.702, 95% confidence interval (CI) 0.686-0.718. In the MSM with the random forest algorithm, workers who changed from standard to non-standard employment were 2.07 times more likely to report suicidal ideation compared to those who maintained standard employment (95% CI 1.16-3.70). A similar trend was observed in the analysis of depressive symptoms. CONCLUSIONS: This study found that a change in employment status could lead to a higher risk of suicidal ideation and depressive symptoms.

Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial.

Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigations will help us understand the role of these factors in seasonal variation in health outcomes and further identify currently unknown or unmeasured risk factors. This tutorial illustrates a statistical procedure for examining the seasonality of health outcomes and their changes, after adjusting for potential environmental drivers by assessing and comparing shape, timings and size. We recommend a three-step procedure, each carried out and compared before and after adjustment: (i) inspecting the fitted seasonal curve to determine the broad shape of seasonality; (ii) identifying the peak and trough of seasonality to determine the timings of seasonality; and (iii) estimating the peak-to-trough ratio and attributable fraction to measure the size of seasonality. Reporting changes in these features on adjusting for potential drivers allows readers to understand their role in seasonality and the nature of any residual seasonal pattern. Furthermore, the proposed approach can be extended to other health outcomes and environmental drivers.

Seasonal variation in mortality and the role of temperature: a multi-country multi-city study.

BACKGROUND: Although seasonal variations in mortality have been recognized for millennia, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature. METHODS: We compiled daily data on all-cause, cardiovascular and respiratory mortality, temperature and indicators on location-specific characteristics from 719 locations in tropical, dry, temperate and continental climate zones. We fitted time-series regression models to estimate the amplitude of seasonal variation in mortality on a daily basis, defined as the peak-to-trough ratio (PTR) of maximum mortality estimates to minimum mortality estimates at day of year. Meta-analysis was used to summarize location-specific estimates for each climate zone. We estimated the PTR with and without temperature adjustment, with the differences representing the seasonal effect attributable to temperature. We also evaluated the effect of location-specific characteristics on the PTR across locations by using meta-regression models. RESULTS: Seasonality estimates and responses to temperature adjustment varied across locations. The unadjusted PTR for all-cause mortality was 1.05 [95% confidence interval (CI): 1.00-1.11] in the tropical zone and 1.23 (95% CI: 1.20-1.25) in the temperate zone; adjusting for temperature reduced the estimates to 1.02 (95% CI: 0.95-1.09) and 1.10 (95% CI: 1.07-1.12), respectively. Furthermore, the unadjusted PTR was positively associated with average mean temperature. CONCLUSIONS: This study suggests that seasonality of mortality is importantly driven by temperature, most evidently in temperate/continental climate zones, and that warmer locations show stronger seasonal variations in mortality, which is related to a stronger effect of temperature.

Geographical Variations of the Minimum Mortality Temperature at a Global Scale: A Multicountry Study.

BACKGROUND: Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale. METHODS: We collected data from 658 communities in 43 countries under different climates. We estimated temperature-mortality associations to derive the MMT for each community using Poisson regression with distributed lag nonlinear models. We investigated the variation in MMT by climatic zone using a mixed-effects meta-analysis and explored the association with climatic and socioeconomic indicators. RESULTS: The geographical distribution of MMTs varied considerably by country between 14.2 and 31.1 °C decreasing by latitude. For climatic zones, the MMTs increased from alpine (13.0 °C) to continental (19.3 °C), temperate (21.7 °C), arid (24.5 °C), and tropical (26.5 °C). The MMT percentiles (MMTPs) corresponding to the MMTs decreased from temperate (79.5th) to continental (75.4th), arid (68.0th), tropical (58.5th), and alpine (41.4th). The MMTs indreased by 0.8 °C for a 1 °C rise in a community's annual mean temperature, and by 1 °C for a 1 °C rise in its SD. While the MMTP decreased by 0.3 centile points for a 1 °C rise in a community's annual mean temperature and by 1.3 for a 1 °C rise in its SD. CONCLUSIONS: The geographical distribution of the MMTs and MMTPs is driven mainly by the mean annual temperature, which seems to be a valuable indicator of overall adaptation across populations. Our results suggest that populations have adapted to the average temperature, although there is still more room for adaptation.

Gender differences in under-reporting hiring discrimination in Korea: a machine learning approach.

OBJECTIVES: This study was conducted to examine gender differences in under-reporting hiring discrimination by building a prediction model for workers who responded "not applicable (NA)" to a question about hiring discrimination despite being eligible to answer. METHODS: Using data from 3,576 wage workers in the seventh wave (2004) of the Korea Labor and Income Panel Study, we trained and tested 9 machine learning algorithms using "yes" or "no" responses regarding the lifetime experience of hiring discrimination. We then applied the best-performing model to estimate the prevalence of experiencing hiring discrimination among those who answered "NA." Under-reporting of hiring discrimination was calculated by comparing the prevalence of hiring discrimination between the "yes" or "no" group and the "NA" group. RESULTS: Based on the predictions from the random forest model, we found that 58.8% of the "NA" group were predicted to have experienced hiring discrimination, while 19.7% of the "yes" or "no" group reported hiring discrimination. Among the "NA" group, the predicted prevalence of hiring discrimination for men and women was 45.3% and 84.8%, respectively. CONCLUSIONS: This study introduces a methodological strategy for epidemiologic studies to address the under-reporting of discrimination by applying machine learning algorithms.

Early Chronic Memantine Treatment-Induced Transcriptomic Changes in Wild-Type and Shank2-Mutant Mice.

Shank2 is an excitatory postsynaptic scaffolding protein strongly implicated in autism spectrum disorders (ASDs). Shank2-mutant mice with a homozygous deletion of exons 6 and 7 (Shank2-KO mice) show decreased NMDA receptor (NMDAR) function and autistic-like behaviors at juvenile [∼postnatal day (P21)] and adult (>P56) stages that are rescued by NMDAR activation. However, at ∼P14, these mice show the opposite change - increased NMDAR function; moreover, suppression of NMDAR activity with early, chronic memantine treatment during P7-21 prevents NMDAR hypofunction and autistic-like behaviors at later (∼P21 and >P56) stages. To better understand the mechanisms underlying this rescue, we performed RNA-Seq gene-set enrichment analysis of forebrain transcriptomes from wild-type (WT) and Shank2-KO juvenile (P25) mice treated early and chronically (P7-21) with vehicle or memantine. Vehicle-treated Shank2-KO mice showed upregulation of synapse-related genes and downregulation of ribosome- and mitochondria-related genes compared with vehicle-treated WT mice. They also showed a transcriptomic pattern largely opposite that observed in ASD (reverse-ASD pattern), based on ASD-related/risk genes and cell-type-specific genes. In memantine-treated Shank2-KO mice, chromatin-related genes were upregulated; mitochondria, extracellular matrix (ECM), and actin-related genes were downregulated; and the reverse-ASD pattern was weakened compared with that in vehicle-treated Shank2-KO mice. In WT mice, memantine treatment, which does not alter NMDAR function, upregulated synaptic genes and downregulated ECM genes; memantine-treated WT mice also exhibited a reverse-ASD pattern. Therefore, early chronic treatment of Shank2-KO mice with memantine alters expression of chromatin, mitochondria, ECM, actin, and ASD-related genes.

Mosquito abundance in relation to extremely high temperatures in urban and rural areas of Incheon Metropolitan City, South Korea from 2015 to 2020: an observational study.

BACKGROUND: Despite concerns regarding increasingly frequent and intense heat waves due to global warming, there is still a lack of information on the effects of extremely high temperatures on the adult abundance of mosquito species that are known to transmit vector-borne diseases. This study aimed to evaluate the effects of extremely high temperatures on the abundance of mosquitoes by analyzing time series data for temperature and mosquito abundance in Incheon Metropolitan City (IMC), Republic of Korea, for the period from 2015 to 2020. METHODS: A generalized linear model with Poisson distribution and overdispersion was used to model the nonlinear association between temperature and mosquito count for the whole study area and for its constituent urban and rural regions. The association parameters were pooled using multivariate meta-regression. The temperature-mosquito abundance curve was estimated from the pooled estimates, and the ambient temperature at which mosquito populations reached maximum abundance (TMA) was estimated using a Monte Carlo simulation method. To quantify the effect of extremely high temperatures on mosquito abundance, we estimated the mosquito abundance ratio (AR) at the 99th temperature percentile (AR99th) against the TMA. RESULTS: Culex pipiens was the most common mosquito species (51.7%) in the urban region of the IMC, while mosquitoes of the genus Aedes (Ochlerotatus) were the most common in the rural region (47.8%). Mosquito abundance reached a maximum at 23.5 °C for Cx. pipiens and 26.4 °C for Aedes vexans. Exposure to extremely high temperatures reduced the abundance of Cx. pipiens mosquitoes {AR99th 0.34 [95% confidence interval (CI) 0.21-0.54]} to a greater extent than that of Anopheles spp. [AR99th 0.64 (95% CI 0.40-1.03)]. When stratified by region, Ae. vexans and Ochlerotatus koreicus mosquitoes showed higher TMA and a smaller reduction in abundance at extreme heat in urban Incheon than in Ganghwa, suggesting that urban mosquitoes can thrive at extremely high temperatures as they adapt to urban thermal environments. CONCLUSIONS: We confirmed that the temperature-related abundance of the adult mosquitoes was species and location specific. Tailoring measures for mosquito prevention and control according to mosquito species and anticipated extreme temperature conditions would help to improve the effectiveness of mosquito-borne disease control programs.

Respiratory function declines in children with asthma associated with chemical species of fine particulate matter (PM2.5) in Nagasaki, Japan.

BACKGROUND: The differential effects of PM2.5 fractions on children's lung function remain inconclusive. This study aimed to examine whether lung function in asthmatic children was associated with increased PM2.5 fractions in urban areas in Nagasaki prefecture, Japan, where the air pollution level is relatively low but influenced by transboundary air pollution. METHODS: We conducted a multiyear panel study of 73 asthmatic children (boys, 60.3%; mean age, 8.2 years) spanning spring 2014-2016 in two cities. We collected self-measured peak expiratory flow (PEF) twice a day and daily time-series data for PM2.5 total mass and its chemical species. We fitted a linear mixed effects model to examine short-term associations between PEF and PM2.5, adjusting for individual and time-varying confounders. A generalized linear mixed effects model was also used to estimate the association for worsening asthma defined by severe PEF decline. Back-trajectory and cluster analyses were used to investigate the long-range transboundary PM2.5 in the study areas. RESULTS: We found that morning PEFs were adversely associated with higher levels of sulfate (- 1.61 L/min; 95% CI: - 3.07, - 0.15) in Nagasaki city and organic carbon (OC) (- 1.02 L/min; 95% CI: - 1.94, - 0.09) in Isahaya city, per interquartile range (IQR) increase at lag1. In addition, we observed consistent findings for worsening asthma, with higher odds of severe PEF decline in the morning for sulfate (odds ratio (OR) = 2.31; 95% CI: 1.12, 4.77) and ammonium (OR = 1.73; 95% CI: 1.06, 2.84) in Nagasaki city and OC (OR = 1.51; 95% CI: 1.06, 2.15) in Isahaya city, per IQR increase at lag1. The significant chemical species were higher on days that could be largely attributed to the path of Northeast China origin (for sulfate and ammonium) or both the same path and local sources (for OC) than by other clusters. CONCLUSIONS: This study provides evidence of the differential effects of PM2.5 fractions on lung function among asthmatic children in urban areas, where the Japanese national standards of air quality have been nearly met. Continuous efforts to promote mitigation actions and public awareness of hazardous transboundary air pollution are needed to protect susceptible children with asthma.

Seasonality of mortality under a changing climate: a time-series analysis of mortality in Japan between 1972 and 2015.

BACKGROUND: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. METHODS: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. RESULTS: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: - 1.24 to 1.48), respectively. CONCLUSION: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.

Bayesian semiparametric mixed effects models for meta-analysis of the literature data : An application to cadmium toxicity studies.

We propose Bayesian semiparametric mixed effects models with measurement error to analyze the literature data collected from multiple studies in a meta-analytic framework. We explore this methodology for risk assessment in cadmium toxicity studies, where the primary objective is to investigate dose-response relationships between urinary cadmium concentrations and ß2 -microglobulin. In the proposed model, a nonlinear association between exposure and response is described by a Gaussian process with shape restrictions, and study-specific random effects are modeled to have either normal or unknown distributions with Dirichlet process mixture priors. In addition, nonparametric Bayesian measurement error models are incorporated to flexibly account for the uncertainty resulting from the usage of a surrogate measurement of a true exposure. We apply the proposed model to analyze cadmium toxicity data imposing shape constraints along with measurement errors and study-specific random effects across varying characteristics, such as population gender, age, or ethnicity.

Robust and distributed neural representation of action values.

Studies in rats, monkeys, and humans have found action-value signals in multiple regions of the brain. These findings suggest that action-value signals encoded in these brain structures bias choices toward higher expected rewards. However, previous estimates of action-value signals might have been inflated by serial correlations in neural activity and also by activity related to other decision variables. Here, we applied several statistical tests based on permutation and surrogate data to analyze neural activity recorded from the striatum, frontal cortex, and hippocampus. The results show that previously identified action-value signals in these brain areas cannot be entirely accounted for by concurrent serial correlations in neural activity and action value. We also found that neural activity related to action value is intermixed with signals related to other decision variables. Our findings provide strong evidence for broadly distributed neural signals related to action value throughout the brain.

Nonparametric Bayesian functional two-part random effects model for longitudinal semicontinuous data analysis.

Longitudinal semicontinuous data, characterized by repeated measures of a large portion of zeros and continuous positive values, are frequently encountered in many applications including biomedical, epidemiological, and social science studies. Two-part random effects models (TPREM) have been used to investigate the association between such longitudinal semicontinuous data and covariates accounting for the within-subject correlation. The existing TPREM is, however, limited to incorporate a functional covariate, which is often available in a longitudinal study. Moreover, the existing TPREM typically assumes the normality of subject-specific random effects, which can be easily violated when there exists a subgroup structure. In this article, we propose a nonparametric Bayesian functional TPREM to assess the relationship between the longitudinal semicontinuous outcome and various types of covariates including a functional covariate. The proposed model also relaxes the normality assumption for the random effects through a Dirichlet process mixture of normals, which allows for identifying an underlying subgroup structure. The methodology is illustrated through an application to social insurance expenditure data collected by the Korean Welfare Panel Study and a simulation study.

Comparison of climatic factors on mosquito abundance at US Army Garrison Humphreys, Republic of Korea.

INTRODUCTION: A number of studies have been conducted on the relationship between the distribution of mosquito abundance and meteorological variables. However, few studies have specifically provided specific ranges of temperatures for estimating the maximum abundance of mosquitoes as an empirical basis for climatic dynamics for estimating mosquito-borne infectious disease risks. METHODS: Adult mosquitoes were collected for three consecutive nights/week using Mosquito Magnet® Independence® model traps during 2018 and 2019 at US Army Garrison (USAG) Humphreys, Pyeongtaek, Gyeonggi Province, Republic of Korea (ROK). An estimate of daily mean temperatures (provided by the Korea Meteorological Administration) were distributed at the maximum abundance for selected species of mosquitoes using daily mosquito collection data after controlling for mosquito ecological cycles and environmental factors. RESULTS: Using the Monte-Carlo simulation, the overall mosquito population abundance peaked at 22.7°C (2.5th-97.5th: 21.7°C-23.8°C). Aedes albopictus, vector of Zika, chikungunya, dengue fever and other viruses, abundance peaked at 24.6°C (2.5th-97.5th, 22.3°C-25.6°C), while Japanese encephalitis virus (JEV) vectors, e.g., Culex tritaeniorhynchus and Culex pipiens, peaked at 24.3°C (2.5th-97.5th: 21.9°C-26.3°C) and 22.6°C (2.5th-97.5th: 21.9°C-25.2°C), respectively. Members of the Anopheles Hyrcanus Group, some of which are vivax malaria vectors in the ROK, abundance peaked at 22.4°C (2.5th-97.5th: 21.5°C-23.8°C). CONCLUSION: The empirical mean temperature ranges for maximum abundance were determined for each mosquito species collected at USAG Humphreys. These data contributed to the identification of relative mosquito abundance patterns for estimating mosquito-borne disease risks and developing and implementing disease prevention practices.

Health Effects of Asian Dust: A Systematic Review and Meta-Analysis.

BACKGROUND: Potential adverse health effects of Asian dust exposure have been reported, but systematic reviews and quantitative syntheses are lacking. OBJECTIVE: We reviewed epidemiologic studies that assessed the risk of mortality, hospital admissions, and symptoms/dysfunction associated with exposure to Asian dust. METHODS: We performed a systematic search of PubMed and Web of Science to identify studies that reported the association between Asian dust exposure and human health outcomes. We conducted separate meta-analyses using a random-effects model for mortality and hospital admissions for a specific health outcome and assessed pooled estimates for each lag when at least three studies were available for a specific lag. RESULTS: We identified 89 studies that met our inclusion criteria for the systematic review, and 21 studies were included in the meta-analysis. The pooled estimates (percentage changes) of mortality from circulatory and respiratory causes for Asian dust days vs. non-Asian dust days were 2.33% [95% confidence interval (CI): 0.76, 3.93] increase at lag 0 and 3.99% (95% CI: 0.08, 8.06) increase at lag 3, respectively. The increased risk for hospital admissions for respiratory disease, asthma, and pneumonia peaked at lag 3 by 8.85% (95% CI: 0.80, 17.55), 14.55% (95% CI: 6.74, 22.94), and 8.51% (95% CI: 2.89, 14.44), respectively. Seven of 12 studies reported reduced peak expiratory flow, and 16 of 21 studies reported increased respiratory symptoms associated with Asian dust exposure. There were substantial variations between the studies in definitions of Asian dust, study designs, model specifications, and confounder controls. DISCUSSION: We found evidence of increased mortality and hospital admissions for circulatory and respiratory events. However, the number of studies included in the meta-analysis was not large and further evidences are merited to strengthen our conclusions. Standardized protocols for epidemiological studies would facilitate interstudy comparisons. https://doi.org/10.1289/EHP5312.

Nonlinear temperature-suicide association in Japan from 1972 to 2015: Its heterogeneity and the role of climate, demographic, and socioeconomic factors.

It has been reported that suicide is associated with ambient temperature; however, the heterogeneity in this association and its underlying factors have not been extensively investigated. Therefore, we investigated the spatial and temporal variation in the temperature-suicide association and examined climatic, demographic, and socioeconomic factors that may underlie such heterogeneity. We analyzed the daily time-series data for the suicide counts and ambient temperature, which were collected for the 47 prefectures of Japan from 1972 to 2015, using a two-stage analysis. In the first stage, the prefecture-specific temperature-suicide association was estimated by using a generalized linear model. In the second stage, the prefecture-specific associations were pooled, and key factors explaining the spatial and temporal variation were identified by using mixed effects meta-regression. Results showed that there is an inverted J-shape nonlinear association between temperature and suicide; the suicide risk increased with temperature but leveled off above 24.4 °C. The nationwide relative risk (RR) for the maximum suicide temperature versus 5th temperature percentile (2.9 °C) was estimated as 1.26 (95% CI: 1.22, 1.29). The RRs were larger for females than for males (1.32 vs. 1.22) and larger for elderly people (≥65 y) than for the non-elderly (15-64 y) (1.51 vs. 1.18). The RRs were larger for rural prefectures, which are characterized by smaller population, higher proportions of females and elderly people, and lower levels of financial capability and the proportion of highly educated people. The RRs were also larger in colder and less humid prefectures. These findings may help in understanding the potential mechanism of the temperature-suicide association and projecting the future risk of suicide under climate change.

Temporal Trend of Aedes albopictus in Local Urban Parks of the Republic of Korea.

Aedes albopictus (Skuse) was first reported in the Republic of Korea in 1941 (Suwon, Gyeonggi Province). Recently, a mosquito-monitoring program was established in response to the potential development of autochthonous infections of dengue, chikungunya, and Zika viruses, to identify the regional characteristics of Ae. albopictus in Suwon. Daily collections of adult mosquitoes were conducted using Blackhole UV-LED traps and BG-Sentinel traps baited with octenol, carbon dioxide or both at five sites in Suwon (Sungkyunkwan University, Manseok, Seoho, Olympic, and Jungang parks) from 1 July to 1 November 2016. Based on the ecological cycle of mosquitoes, an estimated association between the daily mean temperatures [2 wk prior to the collection date (lag 2 wk)] and relative population abundance were developed using a generalized linear model. The overall proportion of female mosquitoes collected from all traps was 88.3%. Higher female trap indices were observed for mosquitoes collected at BG-Sentinel traps. Additionally, the BG-sentinel trap was more effective collecting Ae. albopictus. Culex pipiens (Coquillett) was the most frequently collected mosquito using UV-LED traps, followed by Ae. vexans nipponii (Theobald), Ochlerotatus koreicus (Edwards), Cx. inatomi (Kamimura and Wada), and members of the Anopheles Hyrcanus Group. Within a certain temperature range, daily mean temperatures 2 wk prior to the collection period was significantly associated with a maximum abundance of Ae. albopictus (P < 0.05) at 26.2°C (95% confidence interval: 24.3-29.4°C). The BG-Sentinel trap is an effective trap for monitoring relative population abundance of Ae. albopictus, and trap catches are significantly correlated with daily mean temperatures.

Publisher Correction: Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model.

Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r > 0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r > 0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.

Suicide and Ambient Temperature: A Multi-Country Multi-City Study.

BACKGROUND: Previous literature suggests that higher ambient temperature may play a role in increasing the risk of suicide. However, no multi-country study has explored the shape of the association and the role of moderate and extreme heat across different locations. OBJECTIVES: We examined the short-term temperature-suicide relationship using daily time-series data collected for 341 locations in 12 countries for periods ranging from 4 to 40 y. METHODS: We conducted a two-stage meta-analysis. First, we performed location-specific time-stratified case-crossover analyses to examine the temperature-suicide association for each location. Then, we used a multivariate meta-regression to combine the location-specific lag-cumulative nonlinear associations across all locations and by country. RESULTS: A total of 1,320,148 suicides were included in this study. Higher ambient temperature was associated with an increased risk of suicide in general, and we observed a nonlinear association (inverted J-shaped curve) with the highest risk at 27°C. The relative risk (RR) for the highest risk was 1.33 (95% CI: 1.30, 1.36) compared with the risk at the first percentile. Country-specific results showed that the nonlinear associations were more obvious in northeast Asia (Japan, South Korea, and Taiwan). The temperature with the highest risk of suicide ranged from the 87th to 88th percentiles in the northeast Asian countries, whereas this value was the 99th percentile in Western countries (Canada, Spain, Switzerland, the UK, and the United States) and South Africa, where nearly linear associations were estimated. The country-specific RRs ranged from 1.31 (95% CI: 1.19, 1.44) in the United States to 1.65 (95% CI: 1.40, 1.93) in Taiwan, excluding countries where the results were substantially uncertain. DISCUSSION: Our findings showed that the risk of suicide increased with increasing ambient temperature in many countries, but to varying extents and not necessarily linearly. This temperature-suicide association should be interpreted cautiously, and further evidence of the relationship and modifying factors is needed. https://doi.org/10.1289/EHP4898.

Interactive Effect of Diurnal Temperature Range and Temperature on Mortality, Northeast Asia.

BACKGROUND: The diurnal temperature range (DTR) represents temperature variability within a day and has been reported as a potential risk factor for mortality. Previous studies attempted to identify the role of temperature in the DTR-mortality association, but results are inconclusive. The aim of this study was to investigate the interactive effect of temperature and DTR on mortality using a multicountry time series analysis. METHODS: We collected time series data for mortality and weather variables for 57 communities of three countries (Taiwan, Korea, and Japan) in Northeast Asia (1972-2012). Two-stage time series regression with a distributed lag nonlinear model and meta-analysis was used to estimate the DTR-mortality association changing over temperature strata (six strata were defined based on community-specific temperature percentiles). We first investigated the whole population and then, the subpopulations defined by temperature distribution (cold and warm regions), sex, and age group (people <65 and ≥65 years of age), separately. RESULTS: The DTR-mortality association changed over temperature strata. The relative risk (RR) of mortality for 10°C increase in DTR was larger for high-temperature strata compared with cold-temperature strata (e.g., = 1.050; 95% confidence interval [CI] = 1.040, 1.060 at extreme-hot stratum and RR = 1.040; 95% CI = 1.031, 1.050 at extreme-cold stratum); extreme-hot and -cold strata were defined as the days with daily mean temperature above 90th and below 10th percentiles each community's temperature distribution. Such increasing pattern was more pronounced in cold region and in people who were 65 years or older. CONCLUSIONS: We found evidence that the DTR-related mortality may increase as temperature increases.