背景:
氣喘與第一型糖尿病的發生，皆是基因與環境因子交互作用所致的結果，隨著世界各地的氣喘及第一型糖尿病之發生率皆呈現上升趨勢，有越來越多的研究探討環境中各種因子是否為導致發生率上升的原因。其中包括了衛生假說（hygiene hypothesis），其理論基礎在於：當暴露於環境微生物中，人體內的共生菌會與其作用，此時能夠刺激免疫系統，促進人體免疫系統的成熟，並且有助於第一型與第二型輔助性T細胞的發展。然而，並非所有過去的研究都支持衛生假說；為此，本研究以兒童氣喘及第一型糖尿病與自體免疫有關之疾病為對象，針對衛生假說再次進行研究驗證。
目的:
本研究將探討台灣的孩童居住地區畜牧場密度、嬰幼兒期使用抗生素的次數，以及搬家頻率等三個環境因素與氣喘及第一型糖尿病（僅前兩者環境因素）發生風險間之相關性。
方法:
第一部分（氣喘）採世代追蹤研究，使用全民健康保險資料之2000年百萬人承保抽樣歸人檔，此部分的出生世代將被定義為：出生日期介於1998年1月1日與2000年12月31日之間者，暴露期間界定為出生後的四年內（零歲至滿三歲），追蹤時間為滿三歲日至2013年12月31日，排除條件為:滿三歲前死亡、退出全民健康保險者，或已發生氣喘者。本研究藉由全民健康保險資料之綜合就醫地來推估樣本居住地區，並據此，來進行樣本居住地畜牧場密度與搬家頻率的評估，本研究也藉由全民健康保險資料之門診處方醫令明細檔，和住院醫療費用醫令清單明細檔中，所有種類的抗生素（ATC code: J01），來評估研究對象嬰幼兒期使用抗生素的頻率。氣喘的界定是根據國際疾病分類臨床修正第九版（International Classification of Disease, Ninth Revision, Clinical Modification,ICD-9-CM）之定義，若主次診斷診斷碼為“493.X”或”493.XX”。此部分分析將以Cox proportional hazard model，在控制潛在干擾因子後，估計前述衛生假說相關因子與氣喘發生風險之風險對比值（adjusted hazard ratio, aHR）及其95%信賴區間（Confidence Interval, CI）。
第二部分（第一型糖尿病）採病例對照研究法，使用2003-2011年全人口糖尿病人資料，病例組為2003-2011年間於重大傷病檔中診斷為250.x1 or 250.x3，且重大傷病登錄年齡在6歲以下兒童。排除條件為第一型糖尿病登錄前（回溯至1997/1/1）沒有第一型糖尿病病史者。對照組為來源為健保承保檔，經匹配病例組年齡、性別、與登錄年代後，以簡單不重複的隨機選取之非第一型糖尿病兒童（病例/對照 1/4），病例組與對照組個案將回溯至出生，檢視其0-6歲期間居住地畜牧場密度與搬家的暴露情形。此部份分析將採用條件式邏輯斯迴歸分析估計勝算比及其95%信賴區間。
結果：
本研究第一部分最後納入研究分析之個案為28,516名兒童，追蹤至2013年12月31日止，平均追蹤人年數為13.09人年，總追蹤人年數為373526.211人年，追蹤期間發生氣喘總人數為5,545人，在調整潛在干擾因子後發現：兒童出生後4年內皆居住於農牧場密度較高地區，以及使用抗生素的頻率多寡都與發生氣喘的風險無顯著相關，校正風險對比值分別為0.96（95% CI: 0.83-1.14），與0.98（95% CI: 0.87-1.10）。不過，本研究發現：相較於兒童出生後4年內未搬家者，搬家次數達3次之兒童其罹患氣喘的風險顯著高出23%（aHR=1.23, 95% CI: 1.06-1.43），且呈現顯著劑量反應關係（trend test P <0.001）。
本研究第二部分共納入了443名罹患第一型糖尿病之兒童為病例組個案，以及1,772名未罹患第一型糖尿病之兒童為對照組個案，在調整潛在干擾因子後，兒童居住於農牧場密度較高的地區，與搬家次數都與6歲以前發生第一型糖尿病之風險無顯著相關，不過兒童居住於較高農牧場密度地區，傾向與發生第一型糖尿病的風險有正相關性，校正勝算比為1.05（95% CI: 0.82-1.34），但並沒有達到顯著統計上的意義，而在搬家次數方面，若兒童搬家次數越多，也傾向與第一型糖尿病之發生風險間有正相關性，校正勝算比為1.14（95% CI: 0.87-1.48）、1.32（95% CI: 0.98-1.79）、與1.22（95% CI: 0.82-1.81），但也沒有達到統計上的顯著意義。
結論:
本研究第一部分發現兒童的搬家次數越多，其罹患氣喘之風險越高，呈現顯著劑量反應關係，但抗生素使用與農場密度則是與氣喘發生無顯著相關。另外，農牧場密度與搬家頻率則是與第一型糖尿病發生風險間無顯著的相關。本研究的數據並未支持衛生假說。

SUMMARY
Asthma and Type 1 Diabetes Mellitus (T1DM) have been considered to result from the interaction between human genes and environment exposure. When the increasing incidence of asthma and T1DM worldwide, many of research considered certain environment factors as potential causes of both conditions. The hygiene hypothesis is among the major hypotheses. The theoretical basis of the hygiene hypothesis is that when exposed to environmental microorganisms, the symbiotic bacteria in the human body will interact with it. As a result, it can stimulate the immune system, promote the maturation of the human immune system, and help the type 1 and type 2 helper cells development. However, not all past study findings supported the hygiene hypothesis. For this reason, this study puts a foucus on children's asthma and type 1 diabetes, both are autoimmunity related diseases, and attempts to falsify the hygiene hypothesis. Our study firstly aimed to assess the associations of farm density of living area, number of antibiotic prescriptions, and moving frequency in the first 4 years of life with risk of asthma in Taiwan’s child population. Data were retrieved from the Longitudinal Health Insurance Database 2000 (LHID 2000). The birth cohort included a sample of live births from 1998 to 2000 and the environmental exposure was assessed for the first 4 years of life. This part included 28,516 children, all study subjects were then followed to December 31, 2013. The mean follow-up time was 13.09 years. The total follow-up time was 373526.211 person-years. During the follow-up, 5,546 children were diagniosed to have asthma. According to Cox regression model after adjustment for potential confounders, we found that higher farm density had an adjusted hazard ratio (aHR) of 0.96 (95% CI: 0.83-1.14). Antibiotic exposure more than four times was associated with an aHR at 0.98 (95% CI: 0.87-1.10). A significant association between moving for three times and asthma with an aHR at 1.23 (95% CI: 1.06-1.43); and the relationship between moving frequency and asthma showed a linear trend ( P <0.001), indicating a significant dose-response relationship. The second aims of ours study was to assess the associations of farm density of living areas and moving frequency with risk of T1DM. This was a case-control design. Data were retrieved from Diabetes Mellitus Health Database and Registry for Catastrophic Illness Patients. Children with a diagnosis of T1DM between 2003 and 2011 under six years old were selected as the T1DM cases and the non-T1DM controls were randomly selected from the general population by matching cases on year of T1DM registration, age and sex, with a case/control ratio of 1/4. We finally included 443 cases with T1DM and 1,772 matched controls. According to conditional logistic regression analysis after adjustment for potential confounders, we found that higher farm density was associated with an adjusted odds (aOR) of 1.05 (95% CI: 0.82-1.34). Moving frequency more than three times was associated with an aOR of 1.22 (95% CI: 0.82-1.81). In conclusion, despite potential for exposure misclassification and incomplete adjustment for potential confounders, our study generally provides no support for the hygiene hypothesis.

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