在三个不同的国家对终身大麻开始和终身常规烟草吸烟的双重研究
Stephanie Zellers1, Jenny van Dongen2, Hermine H M Maes3
1Institute for Molecular Medicine Finland, University of Helsinki, P.O. Box 20, Helsinki, 00014, Finland. stephanie.zellers@helsinki.fi.
Behavior genetics
|July 30, 2024
概括
遗传和环境因素是常规吸烟和大麻使用同时发生的基础. 这些行为是由于共同的遗传和环境影响而联系在一起的,在不同国家之间存在差异.
科学领域:
- 行为遗传学 行为遗传学
- 精神病学流行病学 精神病学流行病学
- 药物使用研究研究 药物使用研究
背景情况:
- 经常一起观察到经常吸烟和大麻消费.
- 了解这些行为的共同遗传和环境影响至关重要.
研究的目的:
- 调查对常规吸烟启动 (RSI) 和大麻启动 (CI) 的变异和共变的遗传和环境贡献.
- 检查这些因素在不同社会规范和立法的国家之间有何差异.
主要方法:
- 分析来自荷兰,芬兰和美国的双胞胎数据 (N=21,617).
- 两变值模型被用来评估遗传和环境相关性.
- 模型按性别和国家分层,以探索变异.
主要成果:
- 显著的遗传和常见的环境因素影响RSI和CI.
- 在RSI和CI之间发现了高的表型,遗传和环境相关性.
- 流行率和相关性强度因国家而异,差异很大,表明异质性.
结论:
- 由于共同的遗传和环境因素,经常吸烟和大麻的开始是相关的.
- 这些行为背后的遗传结构显示了跨国异质性.
- 社会规范和立法可能会影响这些物质使用行为的流行和关联.
相关概念视频
Longitudinal Research
11.9K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.9K
Observational Studies
8.4K
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
8.4K
Statistical Methods for Analyzing Epidemiological Data
342
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:
342
Behavioral Genetics and Its Designs
347
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
347
Longitudinal Studies
151
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
151
Criteria for Causality: Bradford Hill Criteria - II
264
The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
264


