Objectives: The study aimed to document the association between intussusception in Indian children and meteorological parameters and examine regional variations.
Design: A bidirectional (retrospective and prospective) surveillance between July 2010 and September 2017.
Setting: At 20 hospitals in India, retrospective case record review during July 2010 and March 2016 and prospective surveillance during April 2016 and September 2017 were performed.
Participants: 2161 children aged 2-24 months with first intussusception episode were included.
Interventions: The monthly mean meteorological parameters (temperature, sunshine, rainfall, humidity and wind speed) for the study sites were collected.
Methods: The association between monthly intussusception cases and meteorological parameters was examined at pooled, regional and site levels using Pearson () and Spearman's rank-order () correlation, factorial analysis of variance, and Poisson regression or negative binomial regression analyses.
Results: The intussusception cases were highest in summer and lowest in autumn seasons. Pearson correlation analysis showed that temperature (=0.056; p<0.05), wind speed (=0.134; p<0.01) and humidity (=0.075; p<0.01) were associated with monthly intussusception cases. Spearman's rank-order correlation analysis found that temperature (=0.049; p<0.05), wind speed (=0.096; p<0.01) and sunshine (=0.051; p<0.05) were associated with monthly intussusception cases. Poisson regression analysis resulted that monthly intussusception case was associated with rising temperature (North region, p<0.01 and East region, p<0.05), sunshine (North region, p<0.01), humidity (East region, p<0.01) and wind speed (East region, p<0.01). Factorial analysis of variance revealed a significant seasonal difference in intussusception cases for pooled level (p<0.05), 2-6 months age group (p<0.05) and North region (p<0.01). Significant differences in intussusception cases between summer and autumn seasons were observed for pooled (p<0.01), children aged 2-6 months (p<0.05) and 7-12 months (p<0.05).
Conclusions: Significant correlations between intussusception cases and temperature, humidity, and wind speed were observed at pooled and regional level in India. A peak in summer months was noted, which may be used for prediction, early detection and referral for appropriate management of intussusception.
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http://dx.doi.org/10.1136/bmjopen-2020-043687 | DOI Listing |
Sensors (Basel)
January 2025
College of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China.
Precipitable water vapor (PWV) is an important indicator to characterize the spatial and temporal variability of water vapor. A high spatial and temporal resolution of atmospheric precipitable water can be obtained using ground-based GNSS, but its inversion accuracy is usually limited by the weighted mean temperature, Tm. For this reason, based on the data of 17 ground-based GNSS stations and water vapor reanalysis products over 2 years in the Hong Kong region, a new model for water vapor inversion without the Tm parameter is established by deep learning in this paper, the research results showed that, compared with the PWV information calculated by the traditional model using Tm parameter, the accuracy of the PWV retrieved by the new model proposed in this paper is higher, and its accuracy index parameters BIAS, MAE, and RMSE are improved by 38% on average.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Programa de Pós Graduação Em Ciências Ambientais, Centro de Engenharias, Universidade Federal de Pelotas, Rua Benjamin Constant, 989, Porto, Pelotas, RS, 96010020, Brazil.
The PM/PM ratio is a metric used to distinguish the primary sources of particulate matter (PM) within a given environment. Higher ratios often indicate significant contributions from anthropogenic sources, while smaller ratios suggest a substantial influence from natural origins. However, various contextual factors can influence this ratio.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, 21944, Saudi Arabia.
This paper presents a novel approach to modeling and controlling a solar photovoltaic conversion system(SPCS) that operates under real-time weather conditions. The primary contribution is the introduction of an uncertain model, which has not been published before, simulating the SPCS's actual functioning. The proposed robust control strategy involves two stages: first, modifying the standard Perturb and Observe (P&O) algorithm to generate an optimal reference voltage using real-time measurements of temperature, solar irradiance, and wind speed.
View Article and Find Full Text PDFPLoS One
January 2025
Crop Research Institute, Prague, Ruzyně, Czech Republic.
The assessment of human perception of the thermal environment is becoming highly relevant in the context of global climate change and its impact on public health. In this study, we aimed to evaluate the suitability of the use of four frequently used thermal comfort indices (thermal indices)-Wet Bulb Global Temperature (WGBT), Heat Index (HI), Physiologically Equivalent Temperature (PET), and Universal Thermal Climate Index (UTCI)-to assess human thermal comfort perception in three large urban parks in Central Europe, using Prague, the capital of the Czech Republic, as a case study. We investigated the relationship between the four indices and the thermal perception of park visitors, while taking into account the effect of the sex, age, and activity of the respondents and the week-time and daytime of their visit (assessed parameters).
View Article and Find Full Text PDFSci Rep
January 2025
College of New Energy and Environment, Jilin University, Changchun, 130012, China.
Land use and land cover changes (LULCC) alter local surface attributes, thereby modifying energy balance and material exchanges, ultimately impacting meteorological parameters and air quality. The North China Plain (NCP) has undergone rapid urbanization in recent decades, leading to dramatic changes in land use and land cover. This study utilizes the 2020 land use and land cover data obtained from the MODIS satellite to replace the default 2001 data in the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model.
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