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The association between diurnal temperature range and clinic visits for upper respiratory tract infection among college students in Wuhan, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第2期29卷 2287-2297页

作者： Zhang, Faxue Wu, Chuangxin Zhang, Miaoxuan Zhang, Han Feng, Huan Zhu, Wei Wuhan Univ Sch Hlth Sci Dept Occupat & Environm Hlth Wuhan 430071 Peoples R China Wuhan Univ Sch Hlth Sci Dept Global Hlth Wuhan 430071 Peoples R China Hosp Wuhan Univ Wuhan 430072 Hubei Peoples R China Wuhan Univ Sch Hlth Sci Dept Epidemiol & Biostat Wuhan 430071 Peoples R China

The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 degrees C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.

关键词： Diurnal temperature range generalized additive model upper respiratory tract infection Outpatient visits

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Non-linear relations between life expectancy, socio-economic, and air pollution factors: a global assessment with spatial disparities

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第35期29卷 53306-53318页

作者： Pu, Haixia Wang, Shaobin Wang, Zhaolin Ran, Zimi Jiang, Mengyu Chongqing Technol & Business Univ Ctr Populat Dev & Policy Res Chongqing 400067 Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Res A11 Datun Rd Beijing 100101 Anwai Peoples R China Chongqing Technol & Business Univ Sch Publ Adm Chongqing 400067 Peoples R China Chongqing Key Lab Spatial Data Min & Big Data Int Chongqing Peoples R China Changchun Normal Univ Coll Geog Sci Changchun 130032 Peoples R China

Influential factors of socio-economic and air pollution on life expectancy (LE) show complexity. The investigations of non-linear functions of LE, socio-economic, and air pollution factors have not been largely conducted, and spatial and temporal differences of the linear or non-linear relations between LE and the influential factors have been obscured across countries in the world. In this study, the non-linear relations between LE and factors of per capita gross national income (GNI(pc)), urban population rate (UPR), and fine-particulate (PM2.5) were estimated from 2000 to 2015 by using a generalized additive model (GAM). The collected data included the 219 countries and regions with sufficient data and covers the period 2000-2015. The results demonstrate that at the global level, the GNI(pc) plays a stable and significant non-linear role in LE, while the non-linear relationships between UPR, PM2.5, and LE are not significant. The temporal variation was further investigated that the non-linear effect of PM2.5 on LE is gradually strengthened, and the non-linear effect of UPR on LE shows a weakened trend. However, GNI(pc) always plays a significantly non-linear role in the LE level. Furthermore, the spatial difference in the non-linear relations among different continents is detected. In sum, it cannot be ignored the non-linear effects of socio-economic and air pollution factors on LE at a global scale and across different continents.

关键词： Life expectancy at birth Social-economic factors Air pollution Spatial difference generalized additive model

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Data-driven modelling of joint debris flow release susceptibility and connectivity

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EARTH SURFACE PROCESSES AND LANDFORMS 2022年第11期47卷 2740-2764页

作者： Steger, Stefan Scorpio, Vittoria Comiti, Francesco Cavalli, Marco Eurac Res Inst Earth Observat Bolzano Italy Univ Modena & Reggio Emilia Dept Chem & Geol Sci Via Campi I-41125 Modena Italy Free Univ Bozen Bolzano Fac Sci & Technol Bolzano Italy Natl Res Council CNR IRPI Res Inst Geohydrol Protect Padua Italy

In mountain basins, sediment supply to the fluvial system occurs mainly through episodic geomorphic processes-such as debris flows and other landslide types-whose effectiveness is strongly influenced by the structural connectivity within a catchment. This paper presents a novel data-driven approach to identify and map areas that are simultaneously susceptible to debris flow initiation and structurally connected to the main channel network (i.e. relevant sediment source areas for predicting and mitigating flood hazards in the river channels). The presented approach comprises: (i) the visual interpretation, delineation, mapping and classification of event-specific connected and disconnected debris flow areas in three catchments of the Italian Alps;(ii) the development of data-driven debris flow release susceptibility models that are combined with quantitatively classified index of connectivity (IC) maps;and (iii) a thorough evaluation of the approach, including an assessment of its spatial transferability across the catchments. The main results show: (i) quantitative IC thresholds to discriminate connected from disconnected debris flow release areas;(ii) statistically well-performing and geomorphically plausible debris flow release susceptibility models for the three basins;(iii) diverse joint debris flow connectivity-susceptibility maps that allow identifying zones which are differently relevant in terms of debris flow connectivity. This work also highlights the spatial transferability of the approach, associated benefits and potential drawbacks, as well as the utmost importance of a thorough combined quantitative and qualitative (i.e. geomorphic plausibility) evaluation of the underlying results. The proposed approach is rather simple and requires few basic input data, and can therefore be applied over vast areas (e.g. to support regional-scale hazard assessments or sediment management plans).

关键词： debris flows generalized additive model index of connectivity sediment cascades South Tyrol spatial transferability

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Short-term impact of ambient temperature on the incidence of influenza in Wuhan, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第12期29卷 18116-18125页

作者： Li, Yanbing Wu, Jingtao Hao, Jiayuan Dou, Qiujun Xiang, Hao Liu, Suyang Wuhan Univ Sch Hlth Sci 115 Donghu Rd Wuhan 430071 Peoples R China Chinese Acad Med Sci Union Med Coll Sch Basic Med Peking Dept Epidemiol & BiostatInst Basic Med Sci Beijing 100005 Peoples R China Chinese Acad Med Sci Peking Union Med Coll Ctr Environm & Hlth Sci Beijing 100005 Peoples R China Harvard Univ Dept Biostat Cambridge MA 02138 USA

Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1, 2014, to December 31, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57 celcius. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4 days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.

关键词： Temperature Influenza generalized additive model Distributed lag nonlinear model Extreme Temperature effect Nonlinear relationship

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Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

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ECOLOGY AND EVOLUTION 2020年第12期10卷 5759-5784页

作者： Becker, Elizabeth A. Carretta, James, V Forney, Karin A. Barlow, Jay Brodie, Stephanie Hoopes, Ryan Jacox, Michael G. Maxwell, Sara M. Redfern, Jessica, V Sisson, Nicholas B. Welch, Heather Hazen, Elliott L. Ocean Associates Inc Natl Marine Fisheries Serv NOAA Southwest Fisheries Sci Ctr La Jolla CA 40404 USA Univ Calif Santa Cruz Inst Marine Sci Santa Cruz CA 95064 USA ManTech Int Corp Solana Beach CA 92075 USA NOAA Marine Mammal & Turtle Div Southwest Fisheries Sci Ctr Natl Marine Fisheries Serv La Jolla CA USA NOAA Marine Mammal & Turtle Div Southwest Fisheries Sci Ctr Natl Marine Fisheries Serv Moss Landing CA USA San Jose State Univ Moss Landing Marine Labs Moss Landing CA USA Southwest Fisheries Sci Ctr Environm Res Div Monterey CA USA Earth Syst Res Lab Phys Sci Div Boulder CO USA Univ Washington Sch Interdisciplinary Arts & Sci Bothell WA USA New England Aquarium Anderson Cabot Ctr Ocean Life Boston MA USA Old Dominion Univ Dept Biol Sci Norfolk VA USA

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted;most rely on presence-only data;and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km(2)) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991-2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.

关键词： boosted regression tree California Current cetacean generalized additive model habitat model species distribution model

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The role of infrastructure, socio-economic development, and food security to mitigate the loss of natural disasters

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第35期29卷 52412-52437页

作者： Khan, Muhammad Tariq Iqbal Anwar, Sofia Batool, Zahira Govt Coll Univ Dept Econ Faisalabad 38000 Pakistan Govt Coll Univ Dept Sociol Faisalabad 38000 Pakistan

This study shows the impact of risk (hazard, exposure, and vulnerability) and resilience (infrastructure, information and communication technology, institutional quality, food security, women empowerment, economic performance, human capital, emergency workforce, and social capital) indicators on losses due to natural disasters in 24 high-income, 24 upper-middle-income, 30 lower-middle-income, and 12 low-income countries from 1995 to 2019. It develops a new disaster risk index and disaster resilience index using standard index-making procedure (indicators selection, winsorization, normalization, aggregation). The generalized additive modeling was used to explore the non-linear relationship between response and explanatory variables. There exists a positive link between damage due to natural disasters and hazard index (all panels) and exposure index in high-income countries. The decrease in damage due to natural disasters was observed due to an increase in infrastructure (upper-middle-, lower-middle-, and low-income countries), information and communication technology (high-income countries), institutional quality (high-income countries), food security (high- and upper-middle-income countries), women empowerment (lower-middle-income countries), economic performance (high- and low-income countries), human capital (low-income countries), and emergency workforce (upper-middle and lower-middle-income countries). The governments should enhance disaster resilience through Sendai Framework, having seven targets and four priority areas to increase disaster resilience.

关键词： Disaster risk reduction generalized additive model Natural disasters Resilience Sendai framework Sustainable development

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The relationship between short-term PM2.5 exposure and outpatient visits for acne vulgaris in Chongqing, China: a time-series study

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第40期29卷 61502-61511页

作者： Li, Xiang Zhou, Lai-Xin Yang, Li-Li Huang, Xiao-Long Wang, Nan Hu, Yue-Gu Tang, En-Jie Xiao, Hua Zhou, Yu-Meng Li, Ya-Fei Lu, Yuan-Gang Cai, Tong-Jian Third Mil Med Univ Coll Prevent Med Dept Epidemiol Army Med Univ Chongqing 400038 Peoples R China Third Mil Med Univ Daping Hosp Dept Plast & Cosmet Surg Army Med Univ Chongqing 400042 Peoples R China Third Mil Med Univ Southwest Hosp Med Dept Army Med Univ Chongqing 400038 Peoples R China Third Mil Med Univ Xinqiao Hosp Dept Informat Army Med Univ Chongqing 400037 Peoples R China Third Mil Med Univ Xinqiao Hosp Med Dept Army Med Univ Chongqing 400037 Peoples R China

Many researches have reported the air pollution impacts, either long term or short term, on inflammatory skin diseases, but there are few studies on the relation between PM2.5 and acne vulgaris. To determine the correlation between short-term PM2.5 exposure and acne outpatient visits, data for 120,842 acne vulgaris outpatient visits between December 2013 and December 2019 were obtained from three large hospitals in Chongqing, China. Both single-pollutant models and two-pollutant models were established to explore the relationship between PM2.5 exposure and acne outpatient visits. The stratified analyses were conducted through two-sample z-tests to investigate the possible gender (male or female) and age (< 25 years or >= 25 years) differences in PM2.5 effects. The results demonstrated positive correlations between PM2.5 concentrations and acne outpatient visits. A 10 mu g/m(3) increase in PM2.5 concentration was associated with a 1.71% (95% CI: 1.06-2.36%) increase in acne outpatient visits at lag 0-7 day. Stratified analyses showed that PM2.5 effects were greater in individuals aged >= 25 years than those aged < 25 years, but no gender difference was found. In conclusion, short-term PM2.5 exposure was positively associated with the risk of acne outpatient visits, especially for people >= 25 years old.

关键词： Acne Skin health Particulate matter Air pollution generalized additive model Time-series analysis

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Reply to a letter to the editor regarding "The association between altitude and the prevalence of hypertension among permanent highlanders"

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HYPERTENSION RESEARCH 2023年第2期46卷 546-547页

作者： Zhang, Yuewen Chen, Weizhong Zeng, Ziqian Chengdu Med Coll Dept Epidmiol & Stat Chengdu Peoples R China

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A Statistical Non-Parametric data analysis for COVID-19 incidence data

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ISA TRANSACTIONS 2022年 130卷 675-683页

作者： Minu, R. I. Nagarajan, G. Sathyabama Inst Sci & Technol Chennai India SRM Inst Sci & Technol Chennai India

Background: The impact of COVID-19 on the Global scale is tremendously drastic. There are several types of research going on across the world simultaneously to understand and overcome this dire pandemic outbreak. This paper is purely a statistical study on a distinct set of datasets regarding COVID-19 in India. The motivation of this study is to provide an insight into the rapid growth of confirmed COVID-19 cases in ***: The rapid growth of COVID-19 cases in India started in March 2020. The main objective of this paper is to provide a solid statistical model for the policymaker to handle this kind of pandemic situation in the near future with nonlinear data. In this paper, the data was got from 1st April to 29th November 2020. To come up with a solid statistical model, various nonlinear data such as confirmed COVID-19 cases, maximum temperature, minimum temperature, the total population (state-wise), the total area in km2 (state-wise), and the total rural and urban population count (state-wise) have been analyzed. In this paper, six different generalized additive models (GAM) was identified after a thorough analysis of other researchers' (Xie and Zhu, 2020;Prata et al., 2020) ***: In all perspectives, the results were identified and analyzed. The GAM model regarding total COVID-19 confirmed cases, total population, and the total rural population provides the best average fit of R2 value of 0.934. As the population value is quite high, the author has concise it using logarithm to provide the best p-value of 0.000542 and 0.001407 for a relation between the total number of COVID-19 cases regarding the total population and total rural population respectively.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： COVID-19 India Population Rural population Temperature generalized additive model

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A method for determining groups in nonparametric regression curves: Application to prefrontal cortex neural activity analysis

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第7期19卷 6435-6454页

作者： Roca-Pardinas, Javier Ordonez, Celestino Machado, Luis Meira Vigo Univ Dept Stat & Operat Res Vigo 36310 Spain Oviedo Univ Geomat & Comp Graph Lab Dept Min Exploitat & Prospecting Mieres 33600 Spain Minho Univ Ctr Math P-4704553 Braga Portugal

generalized additive models provide a flexible and easily-interpretable method for uncovering a nonlinear relationship between response and covariates. In many situations, the effect of a continuous covariate on the response varies across groups defined by the levels of a categorical variable. When confronted with a considerable number of groups defined by the levels of the categorical variable and a factor-by-curve interaction is detected in the model, it then becomes important to compare these regression curves. When the null hypothesis of equality of curves is rejected, leading to the clear conclusion that at least one curve is different, we may assume that individuals can be grouped into a number of classes whose members all share the same regression function. We propose a method that allows determining such groups with an automatic selection of their number by means of bootstrapping. The validity and behavior of the proposed method were evaluated through simulation studies. The applicability of the proposed method is illustrated using real data from an experimental study in neurology.

关键词： clustering of regression curves factor-by-curve interaction generalized additive model multiple regression curves nonlinear regression number of groups

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