The science and art of molecular epidemiology

作者
Martha L. Slattery
出处
期刊:Journal of Epidemiology and Community Health [BMJ]
卷期号:56 (10): 728-729 被引量:11
标识
DOI:10.1136/jech.56.10.728
摘要

This paper details some of the issues surrounding the growing field of molecular epidemiology Epidemiology is both a science and an art. The science of epidemiology entails applying classic epidemiological methods to understanding the distribution of diseases in populations. The art of epidemiology is interpreting the findings. Molecular epidemiology provides new opportunities for epidemiologists and other medical researchers to understand diseases and make public health recommendations for disease prevention and treatment. The value of molecular epidemiological studies, in terms of providing information that can be used to improve the health of populations, depends on how well both the science and the art are applied. Molecular epidemiology, an area of epidemiology that is somewhat ambiguous, encompasses utilisation of biomarkers and genetics as tools to define both exposures (factors that are inherited) and outcomes (factors that are acquired). As noted by Porta and colleagues,1 there are an increasing number of published articles with molecular epidemiology as a key word. Molecular epidemiology has been applied to many diseases, although a large percentage of published studies have focused on cancer. Within the cancer arena, most molecular epidemiological studies involving genetics have examined inherited genetic variants or polymorphisms. These genetic variants are exposures, a host characteristic, that may independently or through combination with other diet, lifestyle, or environmental exposures change disease risk. While the hope was that these studies would explain some of the inconsistent diet and lifestyle associations reported in the literature, many have added their own element of confusion.2–8 Evaluation of acquired tumour mutations as a disease end point with diet, lifestyle, and environmental exposure data can provide information about specific disease pathways. The central issue in the review by Porta and colleagues1 was classification of genetic mutations in tumours and appropriate inferences from this classification. Despite the growing …

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Friday完成签到,获得积分10
刚刚
乐观山水发布了新的文献求助10
2秒前
土豆完成签到,获得积分10
3秒前
3秒前
慈祥的又菱应助xixi626采纳,获得10
3秒前
xiadiandong发布了新的文献求助10
4秒前
wxx771510625完成签到 ,获得积分10
4秒前
4秒前
77完成签到,获得积分10
5秒前
5秒前
赵琪发布了新的文献求助10
5秒前
6秒前
6秒前
共享精神应助七七采纳,获得10
6秒前
酷波er应助飘逸谷蕊采纳,获得10
7秒前
7秒前
7秒前
Akim应助科研通管家采纳,获得10
7秒前
英俊的铭应助科研通管家采纳,获得30
7秒前
7秒前
7秒前
CodeCraft应助科研通管家采纳,获得10
8秒前
8秒前
酷波er应助科研通管家采纳,获得10
8秒前
77发布了新的文献求助10
8秒前
247793325发布了新的文献求助10
9秒前
9秒前
小二郎应助明亮的嚣采纳,获得10
10秒前
赵琪完成签到,获得积分10
10秒前
Sylar发布了新的文献求助10
11秒前
gyj发布了新的文献求助10
11秒前
Kmong发布了新的文献求助10
11秒前
xupeng发布了新的文献求助10
12秒前
虚幻又菡完成签到,获得积分10
12秒前
南风未眠完成签到,获得积分10
14秒前
坚强哑铃发布了新的文献求助10
15秒前
搜集达人应助贪玩夏蓉采纳,获得10
16秒前
lu发布了新的文献求助10
16秒前
xupeng完成签到,获得积分10
17秒前
ale应助乐观山水采纳,获得10
18秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Evidence Summary. Injection (subcutaneous):op- timal administration 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7499643
求助须知:如何正确求助?哪些是违规求助? 9090387
关于积分的说明 19391588
捐赠科研通 7109645
什么是DOI,文献DOI怎么找? 3250611
关于科研通互助平台的介绍 2420035
邀请新用户注册赠送积分活动 2236520