臺灣博碩士論文加值系統

背景：隨著全球暖化，國際社會相當重視極端氣候造成的健康危害，尤其是脆弱的易感族群以及遭受氣溫劇烈變化的地區。自從1994年巴西的研究以來，越來越多的研究指出妊娠糖尿病盛行率具有季節性，夏季有較高的盛行率，而近期的研究更發現其與大氣溫度亦具有相關性。台灣位處熱帶與亞熱帶交錯處，有關大氣溫度與妊娠糖尿病盛行率相關性之研究仍屬有限，而國外研究雖然顯示高溫季節妊娠糖尿病盛行率較高，但針對日均溫度高低或同一天內溫差變化大小與妊娠糖尿病診斷發生間的相關性研究也很有限。
目的：探討台灣第二妊娠期環境氣溫暴露與妊娠糖尿病診斷發生風險之間是否具相關性，並分析此相關性是否會隨著產婦年齡、原始國籍與社會經濟地位不同而有所差異。
方法：本研究為全人口的回溯性世代研究設計，使用「衛生福利部衛生福利資料科學中心」之全人口健保與出生通報資料，納入2013-2014年所有經歷分娩之孕婦，分析其於妊娠糖尿病診斷日（或懷孕第27週第1天）所在之季節與前35日每日氣溫與與每日高低溫差之平均值。妊娠糖尿病盛行率並以世界衛生組織2000年標準人口進行年齡標準化，以連結點迴歸（joinpoint regression）找尋盛行率與平均氣溫關係是否存在轉折點，再以單變量與多變量邏輯斯迴歸搭配廣義估計方程式，經控制潛在干擾因子（人口學、生產特性與社會經濟地位等）後，計算不同季節、氣溫與溫差之下，妊娠糖尿病診斷發生風險之勝算比及其95%信賴區間，並納入交互作用項，檢定潛在效果修飾因子的顯著性。
結果：2013-2014年研究樣本共371,131產婦人次，當中於懷孕期間有妊娠糖尿病診斷共有43,538產婦人次（11.73%）。妊娠糖尿病年齡標準化盛行率以夏季與秋季較高（13.04%與12.63%），冬季與春季較低（11.63%與11.53%），且隨著暴露指標日前35天平均日均溫上升而上升，在日均溫達28°C以上時，上升的幅度更為明顯。多變量迴歸分析發現：相較於冬季，夏季與秋季發生妊娠糖尿病診斷之調整後勝算比顯著較高，分別為1.05（95%信賴區間：1.04-1.07）與1.04（95%信賴區間：1.04-1.07）。另外，日均溫與妊娠糖尿病診斷之關係並非呈線性關係，利用連結點迴歸找出關係轉折點並區分成兩段線性分析，溫度區間為14-27°C時，平均日均溫之勝算比為1.03（95%信賴區間：1.02-1.03），28-30°C時，平均日均溫之勝算比則大幅增加為1.54（95%信賴區間：1.48-1.60）。此外，妊娠糖尿病盛行率則是與日溫差平均值呈現線性的負相關，平均日溫差每增加1°C，妊娠糖尿病盛行率下降10%（調整後勝算比0.90，95%信賴區間：0.87-0.92）。雖然年齡與均溫，以及社經地位與均溫及溫差之交互作用均達到統計顯著性，不過分層分析顯示：年齡、社經地位、以及孕婦原生國籍別對溫度、溫差與妊娠糖尿病間相關性之效果修飾作用並不明顯。
結論：本研究發現：季節、均溫與溫差與台灣妊娠期婦女妊娠糖尿病診斷發生的風險有關，於夏季、高溫之下妊娠糖尿病診斷發生風險將提升，超過28°C之後風險將會更加明顯；另一方面，溫差增加則是會降低妊娠糖尿病診斷的發生。

SUMMARY
Recent studies have found the association between prevalence of gestational diabetes mellitus (GDM) and daily temperature. On the basis of these literatures, the aim of this study was to examine the association between the identical factors in Taiwan, a sub-tropic country. This was a population-based retrospective cohort study with Birth Notification database 2013 to 2014, and the National Health Insurance (NHI) program to investigate the prevalence of GDM. Multivariate unconditional logistic regression analysis with generalized estimation equation was used to estimate the adjusted odds ratio (aOR) and 95% confidence interval (CI) of GDM. In all women (n=371,131) who gave birth in 2013 and 2014, 43538(11.7%) had a GDM diagnosis during pregnancy. The age-standardized prevalence of GDM was higher in summer (13.04%) and fall (12.63%), but lower in winter (11.63%) and spring (11.53%), and also steadily raised with increasing temperature from 14°C to 30°C, with a noticeable rise after 28°C. After controlling for potential confounders, summer and fall were associated with a significantly higher risk of GDM diagnosis, with an adjusted OR [95% CI] of 1.05 [1.04–1.07] and 1.04 [1.02–1.06], with reference to winter. The adjusted OR [95% CI] in 14°C to 27°C was 1.03[1.02-1.03], but in 28°C to 30°C was 1.54[1.48-1.60]. The principal conclusion was that season and temperature conferred an increased risk of GDM in Taiwan. A significant dose–gradient effect of temperature on GDM was noted in mothers living in sub-tropic regions; and the association became stronger after 28°C.
Key words：Gestational diabetes mellitus, Temperature, Seasonal variation, Cohort studies, Epidemiologic studies
BACKGROUND
The impact of climate variability on health, especially susceptible populations and regions, has become increasingly importan given the global warming over the past century. After the first Brazil study published in 1994, several studies found a seasonal clustering of gestational diabetes mellitus (GDM) with a significantly higher prevalence noted in summer. Furthermore, recent studies have found the association between prevalence of GDM and daily temperature, or daily temperature difference. Although the climate of Taiwan is warmer than most countries around the world, no study that explored this issue in Taiwan. Moreover, it is in dispute whether the screen of GDM should be covered in National Health Insurance (NHI).
OBJECTIVES
This study aimed to investigate the association of ambient temperature with prevalence of GDM in Taiwan, a sub-tropic country. Furthermore, our study attempted to evaluate whether maternal age, birth country or socioeconomic status may interact with temperature on the risk of GDM.
METHODS
This was a population-based retrospective cohort study with Birth Notification database 2013 to 2014, and the NHI program to investigate the prevalence of GDM in Taiwan. The average daily temperature over a 35-day period prior to GDM diagnosis or the first day of the 27th gestational week was used to indicate exposure. The prevalence of GDM was standardized by using the WHO 2000 standard population. We performed joinpoint regression to assess whether there is a threshold for the putative temperature and GDM relationship. Multivariate unconditional logistic regression analyses with generalized estimation equation were further performed to estimate the adjusted odds ratio (aOR) and 95% confidence interval (CI) of GDM.
RESULTS
Between 2013 and 2014, there were 371,131 women who gave birth, and among them 43,538 (11.7%) women had a diagnosis of GDM during pregnancy. The age-standardized prevalence of GDM was higher in summer (13.04%) and fall (12.63%), but lower in winter (11.63%) and spring (11.53%). The prevalence of GDM also steadily raised with increasing temperature from 14°C to 30°C, with a noticeable rise after 28°C. After controlling for potential confounders, summer and fall were associated with a significantly higher risk of GDM diagnosis, with an adjusted OR [95% CI] of 1.05 [1.04–1.07] and 1.04 [1.02–1.06], with reference to winter. Additionally, an increase of 1°C was associated with a 4% higher risk of being diagnosed as GDM( adjusted OR [95% CI] was 1.04[1.04-1.04] ). If we classified the temperature into two group according to the outcome of joinpoint regression, the adjusted OR [95% CI] in 14°C to 27°C was 1.03[1.02-1.03], but in 28°C to 30°C was 1.54[1.48-1.60].
CONCLUSIONS
Our study found that season and temperature conferred an increased risk of GDM in Taiwan. A significant dose–gradient effect of temperature on GDM was noted in mothers living in sub-tropic regions; and the association became stronger after 28°C. On the other hand, maternal age and socioeconomic status interacted with temperature on the risk of GDM. Findings from our study may help formulate prenatal care programs that may effectively manage the GDM of pregnant women.

目錄
摘要 II
誌謝 VII
第壹章 前言 1
第一節 研究背景 1
第二節 研究目的 1
第三節 研究假設 2
第貳章 文獻回顧 3
第一節 妊娠糖尿病介紹 3
第二節 溫度與疾病的關係 15
第三節 溫度與妊娠糖尿病的關係 17
第叁章 研究設計 22
第一節 資料來源 22
第二節 研究設計 22
第三節 研究對象與病例定義 23
第四節 妊娠日期之界定方法以及大氣溫度之暴露評估 23
第五節 其他影響妊娠糖尿病之危險因子定義 25
第六節 統計分析 27
第肆章 研究結果 29
第一節 研究對象特徵描述 29
第二節 研究期間氣象參數描述 29
第三節 盛行率描述 30
第四節 各氣象參數與妊娠糖尿病診斷發生之勝算比 31
第五節 交互作用描述 31
第伍章 討論 34
第一節 研究主要發現 34
第二節 與過去研究比較 35
第三節 研究結果之重要性 39
第四節 研究優勢與限制 40
第陸章 結論與建議 44
第柒章 參考文獻 45

 
表目錄
表2- 1、國際妊娠糖尿病診斷標準整理 61
表2- 2、妊娠糖尿病與氣象參數之相關性文獻整理 62
表3- 1、氣象測站資訊 64
表3- 2、查爾森共病指標內容 66
表4- 1、研究對象特徵描述 67
表4- 2、台灣各地理區域於研究期間（2012-2014）四季之每日溫濕度參數統計表 69
表4- 3、研究對象於不同觀察區間內之氣象觀測值 71
表4- 4、研究期間(2012-2014)各氣象觀測值之皮爾森相關係數 72
表4- 5、研究期間(2012-2014)暴露指標日前不同期間之平均日均溫之皮爾森相關係數 73
表4- 6、研究期間（2012-2014）暴露指標日前不同期間之平均日溫差之皮爾森相關係數 74
表4- 7、研究期間月份別以及季節別妊娠糖尿病盛行率其95%信賴區間 75
表4- 8、平均日均溫別妊娠糖尿病盛行率及其95%信賴區間 76
表4- 9、平均日溫差別妊娠糖尿病盛行率及其95%信賴區間 77
表4- 10、研究對象特性分析(以產婦原始國籍分組)1 78
表4- 11、日均溫別與妊娠糖尿病盛行率及其95%信賴區間(以產婦原始國籍分層) 80
表4- 12、日溫差別與妊娠糖尿病盛行率及其95%信賴區間(以產婦原始國籍分層) 82
表4- 13、日均溫別與妊娠糖尿病盛行率及其95%信賴區間(以生產年齡分層) 83
表4- 14、日溫差與妊娠糖尿病盛行率及其95%信賴區間(以生產年齡分層) 85
表4- 15、日均溫與妊娠糖尿病盛行率及其95%信賴區間(以健保投保金額分層) 86
表4- 16、溫差與妊娠糖尿病盛行率及其95%信賴區間(以健保投保金額分類) 90
表4- 17、季節與妊娠糖尿病診斷之邏輯斯迴歸分析 92
表4- 18、平均日均溫與妊娠糖尿病診斷之邏輯斯迴歸分析 95
表4- 19、平均日溫差與妊娠糖尿病診斷之邏輯斯迴歸分析 98
表4- 20、氣象參數與妊娠糖尿病診斷發生之國籍別勝算比1 101
表4- 21、氣象參數與妊娠糖尿病診斷發生之母親生產年齡別勝算比1 102
表4- 22、氣象參數與妊娠糖尿病診斷發生之健保投保金額別勝算比1 103

 
圖目錄
圖3、資料擷取流程圖 105
圖4- 1、2012/06/01-2014/12/31台灣四大地理區域平均氣象參數折線圖 107
圖4- 2、2012/06/01-2014/12/31台灣四大區域平均氣象參數期間（前7、14、21、28與35天）平均折線圖 109
圖4- 3、月份別妊娠糖尿病粗盛行率及其95%信賴區間 110
圖4- 4、月份別年齡標準化妊娠糖尿病盛行率其95%信賴區間 111
圖4- 5、季節別妊娠糖尿病粗盛行率及其95%信賴區間 112
圖4- 6、季節別年齡標準化妊娠糖尿病盛行率及其95%信賴區間 113
圖4- 7、以joinpoint regression 分析季節與妊娠糖尿病粗盛行率之關係圖 114
圖4- 8、以joinpoint regression 分析季節與年齡標準化妊娠糖尿病盛行率之關係圖 115
圖4- 9、平均日均溫別妊娠糖尿病粗盛行率及其95%信賴區間 116
圖4- 10、平均日均溫別年齡標準化妊娠糖尿病盛行率及其95%信賴區間 117
圖4- 11、以joinpoint regression 分析平均日均溫與妊娠糖尿病粗盛行率之關係圖 118
圖4- 12、以joinpoint regression 分析平均日均溫與年齡標準化妊娠糖尿病盛行率之關係圖 119
圖4- 13、平均日溫差別妊娠糖尿病粗盛行率及其95%信賴區間 120
圖4- 14、平均日溫差別年齡標準化妊娠糖尿病盛行率及其95%信賴區間 121
圖4- 15、以joinpoint regression 分析平均日溫差與妊娠糖尿病粗盛行率之關係圖 122
圖4- 16、以joinpoint regression 分析平均日溫差與年齡標準化妊娠糖尿病盛行率之關係圖 123
圖4- 17、平均日均溫別妊娠糖尿病粗盛行率及其95%信賴區間（以產婦原始出生國籍分層） 124
圖4- 18、平均日均溫別年齡標準化妊娠糖尿病盛行率及其95%信賴區間（以產婦原始出生國籍分層） 125
圖4- 19、平均日溫差別妊娠糖尿病粗盛行率及其95%信賴區間（以產婦原始出生國籍分層） 126
圖4- 20、平均日溫差別年齡標準化妊娠糖尿病盛行率及其95%信賴區間（以產婦原始出生國籍分層） 127
圖4- 21、平均日均溫別妊娠糖尿病粗盛行率及其95%信賴區間（以產婦生產年齡分層） 128
圖4- 22、平均日溫差別妊娠糖尿病盛行率及其95%信賴區間（以產婦生產年齡分層） 129
圖4- 23、平均日均溫別妊娠糖尿病粗盛行率及其95%信賴區間（以產婦健保投保金額分層） 130
圖4- 24、平均日均溫別年齡標準化妊娠糖尿病盛行率及其95%信賴區間（以產婦健保投保金額分層） 131
圖4- 25、平均日溫差別妊娠糖尿病粗盛行率及其95%信賴區間（以產婦健保投保金額分層） 132
圖4- 26、平均日溫差別年齡標準化妊娠糖尿病盛行率及其95%信賴區間（以產婦健保投保金額分層） 133

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