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Updated: Jul 2, 2025

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

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PM2.5,植被密度和儿童癌症:一个基于德克萨斯州1995-2011年的病例控制注册表的研究

Lindsay A Williams1,2,3, David Haynes4, Jeannette M Sample1

  • 1Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.

Journal of the National Cancer Institute
|February 17, 2024
PubMed
概括

早期接触细颗粒物 (PM2.5) 会增加儿童癌症的风险. 绿色 (NDVI) 有混合效应,降低了某些癌症的风险,但增加了其他癌症的风险,突出了复杂的环境相互作用.

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Measuring Carbon Content in Airway Macrophages Exposed to Carbon-Containing Particulate Matters05:18

Measuring Carbon Content in Airway Macrophages Exposed to Carbon-Containing Particulate Matters

Published on: July 12, 2024

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Quantification of three DNA Lesions by Mass Spectrometry and Assessment of Their Levels in Tissues of Mice Exposed to Ambient Fine Particulate Matter12:15

Quantification of three DNA Lesions by Mass Spectrometry and Assessment of Their Levels in Tissues of Mice Exposed to Ambient Fine Particulate Matter

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相关概念视频

Cancer Prevention02:59

Cancer Prevention

Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
Some...
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Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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Criteria for Causality: Bradford Hill Criteria - I01:30

Criteria for Causality: Bradford Hill Criteria - I

The Bradford Hill criteria are a group of principles that provide a framework to determine a causal relationship between a specific factor and a disease. There are nine criteria that are pivotal in assessing causality in epidemiological studies. Here's a closer look at Strength, Consistency, Specificity, and Temporality criteria with definitions and examples:
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