COVID-19 pandemic modifies temperature and heat-related illness ambulance transport association in Japan: a nationwide observational study

Background During the COVID-19 pandemic, several illnesses were reduced. In Japan, heat-related illnesses were reduced by 22% compared to pre-pandemic period. However, it is uncertain as to what has led to this reduction. Here, we model the association of maximum temperature and heat-related illnesses in the 47 Japanese prefectures. We specifically examined how the exposure and lag associations varied before and during the pandemic. Methods We obtained the summer-specific, daily heat-related illness ambulance transport (HIAT), exposure variable (maximum temperature) and covariate data from relevant data sources. We utilized a stratified (pre-pandemic and pandemic), two-stage approach. In each stratified group, we estimated the 1) prefecture-level association using a quasi-Poisson regression coupled with a distributed lag non-linear model, which was 2) pooled using a random-effects meta-analysis. The difference between pooled pre-pandemic and pandemic associations was examined across the exposure and the lag dimensions. Results A total of 321,655 HIAT cases was recorded in Japan from 2016 to 2020. We found an overall reduction of heat-related risks for HIAT during the pandemic, with a wide range of reduction (10.85 to 57.47%) in the HIAT risk, across exposure levels ranging from 21.69 °C to 36.31 °C. On the contrary, we found an increment in the delayed heat-related risks during the pandemic at Lag 2 (16.33%; 95% CI: 1.00, 33.98%). Conclusion This study provides evidence of the impact of COVID-19, particularly on the possible roles of physical interventions and behavioral changes, in modifying the temperature-health association. These findings would have implications on subsequent policies or heat-related warning strategies in light of ongoing or future pandemics.

Age, Sex, and Race/Ethnicity Associations between Fat Mass and Lean Mass with Bone Mineral Density: NHANES Data

Rising rates of obesity and osteoporosis have public health implications; hence, understanding the relationships between body composition (fat mass (FM) and lean mass (LM)) and bone mineral density (BMD) is important. The purpose of this study is to investigate these associations in a large representative sample. A cross-sectional analysis was conducted using National Health and Nutrition Examination Survey participants (n = 1717, age 44.1 ± 14.2 years) who had complete dual energy x-ray absorptiometry (total BMD g/cm2, FM kg, and LM kg) and covariate data. Hierarchical linear regression models were fitted, controlling for demographic and behavioral covariates. Stratum-specific models were fitted by race, sex, and age group. Significant negative associations were found for FM and BMD (β = −0.003) and significant positive associations for LM and BMD (β = 0.007). Stratum-specific analyses by race were consistent between groups, while variations in negative association magnitudes were seen in FM for sex (males β = −0.005 vs. females β = −0.002) and age (under 45 years of age β = −0.005 vs. 45 years and older β = −0.002). Consistent positive linear associations in total and stratum-specified models between LM and BMD could suggest a potential mechanical influence on bone health. The biological mechanisms driving the magnitude variations between FM and BMD by sex and age require more investigation.

Lack of Association of Elder Mistreatment With Mortality

Background Prior research is limited and inconsistent on the degree to which elder mistreatment (EM) is associated with mortality. This study uses data from a 10-year, prospective, population-based study of EM to determine the adjusted effects of EM on older adult mortality, after controlling for other health and socioeconomic covariates. Methods The New York State Elder Mistreatment Prevalence Study conducted a random-sample telephone survey of older adults (n = 4 156) in 2009 (Wave 1). The current study employs EM and covariate data from Wave 1 and data on mortality status through Wave 2 (2019). EM was operationalized both as experiencing EM and as severity of EM. The survey measured overall EM and separate subtypes (emotional, physical, and financial abuse, and neglect). Results The hypothesis was not supported that abused and neglected older people would have higher rates of death over the study. Individuals who were victims of EM were no more likely to die over the following 10 years, compared with those who were not mistreated, after controlling for covariates. Furthermore, the severity of EM, as measured by the frequency of mistreatment behaviors, also was not associated with mortality risk. Conclusions The finding that self-reported EM did not raise the risk of earlier death in this sample is encouraging. Future research should work to identify factors that may moderate the relationship between EM and mortality, such as social support/isolation, quality of family relationships, or involvement with formal support service systems.

Evaluation of Multiple Imputation Approaches for Handling Missing Covariate Information in a Case-Cohort Study.

Background In case-cohort studies a random subcohort is selected from the inception cohort and acts as the sample of controls for several outcome investigations. Analysis is conducted using only the cases and the subcohort, with inverse probability weighting (IPW) used to account for the unequal sampling probabilities resulting from the study design. Like all epidemiological studies, case-cohort studies are susceptible to missing data. Multiple imputation (MI) has become increasingly popular for addressing missing data in epidemiological studies. It is currently unclear how best to incorporate the weights from a case-cohort analysis in MI procedures used to address missing covariate data.Method A simulation study was conducted with missingness in two covariates, motivated by a case study within the Barwon Infant Study. MI methods considered were: using the outcome, a proxy for weights in the simple case-cohort design considered, as a predictor in the imputation model, with and without exposure and covariate interactions; imputing separately within each weight category; and using a weighted imputation model. These methods were compared to a complete case analysis (CCA) within the context of a standard IPW analysis model estimating either the risk or odds ratio. The strength of associations, missing data mechanism, proportion of observations with incomplete covariate data, and subcohort selection probability varied across the simulation scenarios. Methods were also applied to the case study.Results There was similar performance in terms of relative bias and precision with all MI methods across the scenarios considered, with expected improvements compared with the CCA. Slight underestimation of the standard error was seen throughout but the nominal level of coverage (95%) was generally achieved. All MI methods showed a similar increase in precision as the subcohort selection probability increased, irrespective of the scenario. A similar pattern of results was seen in the case study.Conclusions How weights were incorporated into the imputation model had minimal effect on the performance of MI; this may be due to case-cohort studies only having two weight categories. In this context, inclusion of the outcome in the imputation model was sufficient to account for the unequal sampling probabilities in the analysis model.

Invited Commentary: Standards, Inputs, and Outputs—Strategies for Improving Data-Sharing and Consortia-Based Epidemiologic Research

Data-sharing improves epidemiologic research, but the sharing of data frustrates epidemiologic researchers. The inefficiencies of current methods and options for data-sharing are increasingly documented and easily understood by any study group that has shared its data and any researcher who has received shared data. In this issue of the Journal, Temprosa et al. (Am J Epidemiol. XXX(XX):XXX–XXX) describe how the Consortium of Metabolomics Studies (COMETS) developed and deployed a flexible analytical platform to eliminate key pain points in large-scale metabolomics research. COMETS Analytics includes an online tool, but its cloud computing and technology are the supporting rather than the leading actors in this script. The COMETS team identified the need to standardize diverse and inconsistent metabolomics and covariate data and models across its many participating cohort studies, and then developed a flexible tool that gave its member studies choices about how they wanted to meet the consortium’s analytical requirements. Different specialties will have different specific research needs and will probably continue to use and develop an array of diverse analytical and technical solutions for their projects. COMETS Analytics shows how important—and enabling—the upstream attention to data standards and data consistency is to producing high-quality metabolomics, consortia-based, and large-scale epidemiology research.

In-Service Reliability Assessment of Turbine Blade Thermal Barrier Coatings Based on a Novel Cumulative Damage Index Model

Thermal barrier coating (TBC) has been used widely on turbine blades to provide temperature and oxidation protection. With the turbine inlet temperature continuously increasing, TBCs have become more likely to oxide spallation, leading to premature failure of blade metal substrates. Thus, It is necessary to accurately evaluate the in-service reliability of TBCs for blade life assessment and engine operation safety. Nowadays, it is common to dynamically record aero-engine operating and performance data, called dynamic covariate data, which provides periodic snapshots for obtaining reliability information of engine components. Nevertheless, existing TBC life prediction models that pay adequate attention to dynamic covariate information are rare. This paper focuses on using limited failure samples with associated dynamic covariate data to make in-service reliability assessments of TBCs through a proposed cumulative damage index model. For the demonstration of the proposed approach, an integrated TBC life simulation approach has been introduced, which comprises engine performance, blade thermal, TBC damage, and damage accumulation models. The case study shows that the proposed cumulative damage index model based method provides more stable and accurate results than the traditional statistical method based on failure-time data.

Using randomized trial data to estimate effects of complex treatment regimens in real-world patients.

e18706 Background: Real-world patients often differ from trial participants in prognostic factors such as age, sex, and cancer substage. New methods combine covariate data from real-world patients (the “target population”) with outcome and covariate data from a trial to estimate treatment effects in the target population that take these differences into account. With some assumptions, these methods can also estimate outcomes under treatment regimens not studied in the trial such as “what if we only gave six cycles of chemotherapy?” or “what if patients all perfectly followed a protocol?” Methods: Data from the MOSAIC trial of 5-fluorouracil (5FU) vs oxaliplatin + 5FU (FOLFOX) were combined with covariate data from a target population of stage III colon cancer patients in the US Oncology Network meeting trial eligibility criteria. We used weighting and G-computation to estimate five-year mortality and treatment-related paresthesia risk in the target population for four regimens: treatment with up to 12 cycles of 5FU, if providers used their discretion on dose reductions and delays (5FU-MD); up to 12 cycles of FOLFOX with similar physician discretion (FOLFOX-MD); up to 6 cycles of FOLFOX, with providers perfectly following a strict and specific protocol of dose reductions and delays (6-cycle FOLFOX-P, “P” for “per protocol”); and up to 12 cycles of FOLFOX, following the same strict protocol (12-cycle FOLFOX-P). Results: Tablepresents five-year all-cause mortality and paresthesia risk under each regimen in the stage III target population estimated from the models built in trial participants. Paresthesia risk increased with cumulative oxaliplatin dose. Estimated 5-year mortality was lowest with 12-cycle FOLFOX-P. Conclusions: In a target population of US Oncology Network patients with stage III colon cancer, strict protocols of 12 cycles of FOLFOX were predicted to improve survival compared to strict 6-cycle FOLFOX regimens or less strict 12-cycle FOLFOX and 5FU regimens at the cost of substantial increases in side effects. While estimates of risk differences in 5-year mortality were imprecise, combining trial and real-world data and then using weights and G-computation allowed estimation of benefits and harms of multiple regimens in a clinically relevant patient population.[Table: see text]

The use of an impeller mowing conditioner during haymaking had no effects on feeding behavior, feed intake or performance of organic dairy cows

Impeller mowing conditioners are commonly used to speed up the drying process on the field, making forage preservation (haying, ensiling) less dependent on weather conditions. However, the effects of this technique on the nutritive value of the forage and dairy cows' responses have not been investigated yet. Each half of two fields of grass-dominated swards, first regrowth, was cut either with or without the use of an impeller mowing conditioner (experimental hay and control hay, respectively). Ceteris paribus conditions were guaranteed by the same cutting and wilting times (roughly 48 h), number of teddings, field pickup technique and barn-drying method. At the beginning of the feeding trial, 19 lactating Holstein cows were allocated to one of two groups, one control (nine cows) and one experimental group (10 cows) and were fed the respective forage plus a fixed amount of concentrate [3.6 kg d−1; dry matter (DM) basis]. After a 14-d adaptation period, data were collected over 21 consecutive days. Covariate data of cows were collected prior to the experimental feeding period, over a time span of 9 d, and included in the statistical model. Results revealed that control and experimental hay showed significant (P < 0.05) differences in the nutrient profile. However, the magnitude of these differences was not enough to affect intakes of hay (18.4 ± 0.29 kg DM d−1), total dietary energy or chewing activity, but did lead to a decreased intake of water-soluble carbohydrates and an increased crude protein intake, thus affecting ruminal nitrogen balance (P < 0.01). This resulted in a higher milk urea content [23.3 vs 17.9 mg (100 mL)−1; P < 0.01] in cows fed the experimental hay, whereas other milk performance parameters remained unaffected. In conclusion, the use of the impeller mowing conditioner did not affect the overall forage utilization by cows when the diet contained about 16% concentrate (DM basis). As this is the first study dealing with the effects of an impeller mowing conditioner on cows' responses, future research should consider investigating the effects of mowing conditioners when cows are fed only forage or diets with lower concentrate amounts.