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Background The two-stage design has become a standard tool in environmental epidemiology to model multi-location data. However, its standard form is rather inflexible and poses important limitations for modelling complex risks associated with environmental factors. In this contribution, we illustrate multiple design extensions of the classical two-stage method, all implemented within a unified analytic framework. Methods We extended standard two-stage meta-analytic models along the lines of linear mixed-effects models, by allowing location-specific estimates to be pooled through flexible fixed and random-effects structures. This permits the analysis of associations characterised by combinations of multivariate outcomes, hierarchical geographical structures, repeated measures, and/or longitudinal settings. The analytic framework and inferential procedures are implemented in the R package mixmeta. Results The design extensions are illustrated in examples using multi-city time series data collected as part of the National Morbidity, Mortality and Air Pollution Study (NMMAPS). Specifically, four case studies demonstrate applications for modelling complex associations with air pollution and temperature, including non-linear exposure–response relationships, effects clustered at multiple geographical levels, differential risks by age, and effect modification by air conditioning in a longitudinal analysis. Conclusions The definition of several design extensions of the classical two-stage design within a unified framework, along with its implementation in freely-available software, will provide researchers with a flexible tool to address novel research questions in two-stage analyses of environmental health risks.

Reliable estimates of future health impacts due to climate change are needed to inform and contribute to the design of efficient adaptation and mitigation strategies. However, projecting health burdens associated to specific environmental stressors is a challenging task because of the complex risk patterns and inherent uncertainty of future climate scenarios. These assessments involve multidisciplinary knowledge, requiring expertise in epidemiology, statistics, and climate science, among other subjects. Here, we present a methodologic framework to estimate future health impacts under climate change scenarios based on a defined set of assumptions and advanced statistical techniques developed in time-series analysis in environmental epidemiology. The proposed methodology is illustrated through a step-by-step hands-on tutorial structured in well-defined sections that cover the main methodological steps and essential elements. Each section provides a thorough description of each step, along with a discussion on available analytical options and the rationale on the choices made in the proposed framework. The illustration is complemented with a practical example of study using real-world data and a series of R scripts included as Supplementary Digital Content; http://links.lww.com/EDE/B504, which facilitates its replication and extension on other environmental stressors, outcomes, study settings, and projection scenarios. Users should critically assess the potential modeling alternatives and modify the framework and R code to adapt them to their research on health impact projections.

Melanoma represents an important public health problem, due to its high case-fatality rate. Identification of individuals at high risk would be of major interest to improve early diagnosis and ultimately survival. The aim of this study was to evaluate whether variants predicted melanoma risk independently of at-risk phenotypic characteristics. Data were collected within an international collaboration - the M-SKIP project. The present pooled analysis included data on 3,830 single, primary, sporadic, cutaneous melanoma cases and 2,619 controls from seven previously published case-control studies. All the studies had information on gene variants by sequencing analysis and on hair color, skin phototype, and freckles, ie, the phenotypic characteristics used to define the red hair phenotype. The presence of any variant was associated with melanoma risk independently of phenotypic characteristics (OR 1.60; 95% CI 1.36-1.88). Inclusion of variants in a risk prediction model increased melanoma predictive accuracy (area under the receiver-operating characteristic curve) by 0.7% over a base clinical model ( =0.002), and 24% of participants were better assessed (net reclassification index 95% CI 20%-30%). Subgroup analysis suggested a possibly stronger role of in melanoma prediction for participants without the red hair phenotype (net reclassification index: 28%) compared to paler skinned participants (15%). The authors suggest that measuring the genotype might result in a benefit for melanoma prediction. The results could be a valid starting point to guide the development of scientific protocols assessing melanoma risk prediction tools incorporating the genotype.

When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum wear criterion using population-based accelerometer data, and explore the influence of gender and the purposeful inclusion of children with weekend data on reliability. Accelerometer data obtained during the age seven sweep of the UK Millennium Cohort Study were analysed. Children were asked to wear an ActiGraph GT1M accelerometer for seven days. Reliability coefficients(r) of mean daily counts/minute were calculated using the Spearman-Brown formula based on the intraclass correlation coefficient. An r of 1.0 indicates that all the variation is between- rather than within-children and that measurement is 100% reliable. An r of 0.8 is often regarded as acceptable reliability. Analyses were repeated on data from children who met different minimum daily wear times (one to 10 hours) and wear days (one to seven days). Analyses were conducted for all children, separately for boys and girls, and separately for children with and without weekend data. At least one hour of wear time data was obtained from 7,704 singletons. Reliability increased as the minimum number of days and the daily wear time increased. A high reliability (r = 0.86) and sample size (n = 6,528) was achieved when children with ≥ two days lasting ≥10 hours/day were included in analyses. Reliability coefficients were similar for both genders. Purposeful sampling of children with weekend data resulted in comparable reliabilities to those calculated independent of weekend wear. Quality control procedures should be undertaken before analysing accelerometer data in large-scale studies. Using data from children with ≥ two days lasting ≥10 hours/day should provide reliable estimates of physical activity. It's unnecessary to include only children with accelerometer data collected during weekends in analyses.

BackgroundThe beneficial effect of physical activity (PA) on mental health in adults is well established, but less is known about this relationship in children. We examine associations between objectively measured sedentary time, PA and mental health in 11-year-olds from the UK Millennium Cohort Study (MCS).MethodsLongitudinal data from MCS sweeps 4 (age 7) and 5 (age 11) were used (n=6153). Accelerometer data were collected at MCS4, and mental health was measured at MCS4 and MCS5 using subscales (peer, emotional, conduct, hyperactivity) of the Strengths and Difficulties Questionnaire (SDQ). Associations between mean daily PA minutes at different intensities (sedentary, light, moderate-to-vigorous) at MCS4 and SDQ outcomes at MCS5 (score range 0–10) were estimated using multiple linear regression models, adjusting for SDQ at MCS4 and individual and family characteristics, and stratified by gender.ResultsIn fully adjusted models, increased PA at MCS4 was associated with fewer peer problems in boys and girls at MCS5. For each additional 15 min in moderate-to-vigorous physical activity (MVPA), peer problems decreased −0.077 points (95% CI −0.133 to –0.022) in boys. For girls, light PA was associated with decreased peer problems (−0.071 points/30 min, 95% CI −0.130 to –0.013). Greater sedentary time was associated with more peer problems and fewer hyperactivity symptoms in boys and girls. Increased MVPA was associated with more conduct and hyperactivity problems in boys and more hyperactivity in girls.ConclusionsIncreased sedentary time is associated with more peer problems in children, and PA, generally, is beneficial for peer relations in children aged 11.

The regional disparity of heatwave-related mortality over a long period has not been sufficiently assessed across the globe, impeding the localisation of adaptation planning and risk management towards climate change. We quantified the global mortality burden associated with heatwaves at a spatial resolution of 0.5°×0.5° and the temporal change from 1990 to 2019. We collected data on daily deaths and temperature from 750 locations of 43 countries or regions, and 5 meta-predictors in 0.5°×0.5° resolution across the world. Heatwaves were defined as location-specific daily mean temperature ≥95th percentiles of year-round temperature range with duration ≥2 days. We first estimated the location-specific heatwave-mortality association. Secondly, a multivariate meta-regression was fitted between location-specific associations and 5 meta-predictors, which was in the third stage used with grid cell-specific meta-predictors to predict grid cell-specific association. Heatwave-related excess deaths were calculated for each grid and aggregated. During 1990 to 2019, 0.94% (95% CI: 0.68-1.19) of deaths [i.e., 153,078 cases (95% eCI: 109,950-194,227)] per warm season were estimated to be from heatwaves, accounting for 236 (95% eCI: 170-300) deaths per 10 million residents. The ratio between heatwave-related excess deaths and all premature deaths per warm season remained relatively unchanged over the 30 years, while the number of heatwave-related excess deaths per 10 million residents per warm season declined by 7.2% per decade in comparison to the 30-year average. Locations with the highest heatwave-related death ratio and rate were in Southern and Eastern Europe or areas had polar and alpine climates, and/or their residents had high incomes. The temporal change of heatwave-related mortality burden showed geographic disparities, such that locations with tropical climate or low incomes were observed with the greatest decline. The main limitation of this study was the lack of data from certain regions, e.g., Arabian Peninsula and South Asia. Heatwaves were associated with substantial mortality burden that varied spatiotemporally over the globe in the past 30 years. The findings indicate the potential benefit of governmental actions to enhance health sector adaptation and resilience, accounting for inequalities across communities.

Climate change has marked implications for the burden of infectious diseases. However, no studies have estimated future projections of climate change–related excess morbidity due to diarrhea according to climate change scenarios. We aimed to examine temperature-infectious gastroenteritis associations throughout Japan and project temperature-related morbidity concomitant with climate change for the 2090s. Weekly time series of average temperature and morbidity for infectious gastroenteritis cases in the period 2005-2015 were collated from the 47 Japanese prefectures. A two-stage time-series analysis was adopted to estimate temperature-infectious gastroenteritis relationships. Time series of present and future average daily temperature fluctuations were projected for the four climate change scenarios of representative concentration pathways (RCPs) according to five general circulation models. Excess morbidity for high and low temperatures and the net change in the period 1990–2099 were projected for each climate change scenario by assuming the absence of adaptation and population alterations. In the period 2005–2015, 11,529,833 infectious gastroenteritis cases were reported. There were net reductions in temperature-induced excess morbidity under higher emission scenarios. The net change in the projection period 2090-2099 in comparison with 2010–2019 was [Formula: see text] (95% empirical confidence interval [eCI]: [Formula: see text], 0.5) for RCP2.6, [Formula: see text] (95% eCI: [Formula: see text], [Formula: see text]) for RCP4.5, [Formula: see text] (95% eCI: [Formula: see text], [Formula: see text]) for RCP6.0, and [Formula: see text] (95% eCI: [Formula: see text], [Formula: see text]) for RCP8.5, and the higher the emissions scenario, the larger the estimates reductions. Spatial heterogeneity in the temperature-morbidity relationship was observed among prefectures (Cochran Q test, [Formula: see text]; [Formula: see text]). Japan may experience a net reduction in temperature-related excess morbidity due to infectious gastroenteritis in higher emission scenarios. These results might be because the majority of temperature-related diarrhea cases in Japan are attributable to viral infections during the winter season. Further projections of specific pathogen-induced infectious gastroenteritis due to climate change are warranted. https://doi.org/10.1289/EHP4731.

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. 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. 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. 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. 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.

Few studies have used empirical evidence of past adaptation to project temperature-related excess mortality under climate change. Here, we assess adaptation in future projections of temperature-related excess mortality by employing evidence of shifting minimum mortality temperatures (MMTs) concurrent with climate warming of recent decades. The study is based on daily non-external mortality and daily mean temperature time-series from 11 Spanish cities covering four decades (1978–2017). It employs distributed lag non-linear models (DLNMs) to describe temperature-mortality associations, and multivariate mixed-effect meta-regression models to derive city- and subperiod-specific MMTs, and subsequently MMT associations with climatic indicators. We use temperature projections for one low- and one high-emission scenario (ssp126, ssp370) derived from five global climate models. Our results show that MMTs have closely tracked mean summer temperatures (MSTs) over time and space, with meta-regression models suggesting that the MMTs increased by 0.73 °C (95%CI: 0.65, 0.80) per 1 °C rise in MST over time, and by 0.84 °C (95%CI: 0.76, 0.92) per 1 °C rise in MST across cities. Future projections, which include adaptation by shifting MMTs according to observed temporal changes, result in 63.5% (95%CI: 50.0, 81.2) lower heat-related excess mortality, 63.7% (95%CI: 30.2, 166.7) higher cold-related excess mortality, and 11.2% (95%CI: −5.5, 39.5) lower total temperature-related excess mortality in the 2090s for ssp370 compared to estimates that do not account for adaptation. For ssp126, assumptions on adaptation have a comparatively small impact on excess mortality estimates. Elucidating the adaptive capacities of societies can motivate strengthened efforts to implement specific adaptation measures directed at reducing heat stress under climate change.