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علیّت در اپیدمیولوژی مطالب اصلی مورد بحث:
ارتباط و انواع آن در اپیدمیولوژی ارتباط علیّتی و انواع آن در اپیدمیولوژی انواع مدل های علیّت در اپیدمیولوژی معیارهای قضاوت درباره علیّت
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What is a Cause? Something which has an effect (or Difference).
An event, condition, characteristic (or a combination) which plays an important role/regular/predicable change in occurrence of the outcome (e.g. smoking and lung cancer)
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Characteristics of a cause
Must precede the effect 2. Can be either host or environmental factors (e.g., characteristics, conditions, actions of individuals, events, natural, social or economic phenomena) 3. Positive (presence of a causative exposure) or negative (lack of a preventive exposure)
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ارتباط و علیت (Association & Causation)
ارتباط: همراهي قوي دو متغير (مثلاً بیماری و عامل مورد نظر) به اندازه اي كه نتوان آن را فقط به شانس نسبت داد و بيش از آنچه از شانس انتظار مي رود، با هم اتفاق بيفتند. Note: Association is not equal to causation. If the rooster crows at the break of dawn, then the rooster caused the sun to rise?!!!
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علت لازم و کافی Necessary and sufficient cause
Necessary cause: "A causal factor whose presence is required for the occurrence of the effect”. Sufficient cause: A causal factor whose presence is not required for the occurrence of the effect”. Any given cause may be necessary, sufficient, both, neither
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از همبستگی تا علیّت ساختگی غیر مستقیم مستقیم «علیّتی» انواع رابطه:
رابطه علیّتی یک به یک رابطه علیّتی چند عاملی
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اثر مستقل یا اثر تقويت كننده اي ( Independent or synergistic effect)
سیگار سرطان ریه آزبستوز سرطان ریه آلودگی هوا سرطان ریه سیگار + آزبستوز + آلودگی هوا سرطان ریه
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مدل های علیّت در اپیدمیولوژی
مدل مثلث اپیدمیولوژی مدل چرخ مدل شبکه علیّت
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The Epidemiology Triangle
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Host Factors ویژگی های فردی مؤثر بر مواجهه، حساسیت و یا پاسخ فرد به عامل بیماری زا سن، جنس، ژنتیک، نژاد، قومیت، مذهب، وضعیت تأهل، وضعیت اقتصادی- اجتماعی، عادات و رفتارها، ساختار آناتومیک و عملکرد فیزیولوژیک بدن، وضعیت ایمنولوژیک و تغذیه، ابتلا به بیماری های دیگر، مصرف دارو و ...
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Environmental factors
عوامل محیطی مؤثر بر عامل بیماریزا و شانس مواجهه میزبان با عامل بیماریزا عوامل فیزیکی: درجه حرارت، رطوبت، سروصدا عوامل بیولوژیک: ناقل های بیماری ها عوامل اقتصادی- اجتماعی: ازدحام جمعیت، دسترسی به خدمات بهداشتی، بهسازی محیط
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Agent factors عوامل بیولوژیک: میکرو ارگانیسم ها عوامل تغذیه ای: نقص یا زیادی مواد مغذی عوامل فیزیکی: تروما، پرتوها عوامل شیمیایی: داروها، مونوکسید کربن، سموم
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Biological Environment
The Wheel of Causation Social Environment Biological Environment Host (human) Genetic Core Physical Environment
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Web of Causation (Spider web)
social organization phenotype behaviour microbes Disease genes environment Unknown factors workplace
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Web of Causation - CHD CHD stress genetic susceptibility medications
smoking lipids CHD gender physical activity Unknown factors inflammation blood pressure 15
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Time for a break, Be happy
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Causal "guidelines" suggested by Sir AB Hill (1965)
Temporality Strength of the association Consistency Biological gradient Experiment Plausibility Coherence Specificity Analogy Sir Austin Bradford Hill( )
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1. Temporality The causal factor must precede the disease in time.
This is the only one of Hill's criteria that everyone agrees with. Prospective studies do a good job establishing the correct temporal relationship between an exposure and a disease.
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2. Strength of the association
Strong associations are more likely to be causal because they are unlikely to be due entirely to bias and confounding. Example: RR of lung cancer in smokers vs. non-smokers = 9 RR of lung cancer in heavy vs. non-smokers = 20 Weak associations may be causal but it is harder to rule out bias and confounding.
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3. Consistency The association is observed repeatedly in different persons, places, times, and circumstances. Replicating the association in different samples, with different study designs, and different investigators gives evidence of causation. Note: Sometimes there are good reasons why study results differ. For example, one study may have looked at low level exposures while another looked at high level exposures.
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4. Biological Gradient A “dose-response” relationship between exposure and disease. Example: Lung cancer death rates rise with the number of cigarettes smoked. Some exposures might not have a "dose-response" effect but rather a "threshold effect" below which these are no adverse outcomes.
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5. Experiment Investigator-initiated intervention that modifies the exposure through prevention, treatment, or removal should result in less disease. Example: Smoking cessation programs result in lower lung cancer rates. Provides strong evidence for causation, but most epidemiologic studies are observational.
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6/7. Plausibility / Coherence
Biological or social model exists to explain the association. Association does not conflict with current knowledge of natural history and biology of disease. Example: Cigarettes contain many carcinogenic substances.
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8. Specificity A single exposure should cause a single disease. This is a hold-over from the concepts of causation that were developed for infectious diseases. There are many exceptions to this. When present, specificity, does provide evidence of causality, but its absence does not preclude causation.
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9. Analogy Has a similar relationship been observed with another exposure and/ or disease? Example: Effects of Alcohol on the fetus provide analogy for effects of similar substances on the fetus.
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Thank you for your kind attention
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