隨著穿戴裝置技術的提升，人們的身體狀態已能被追蹤，保險公司開始推出外溢型保單 (Wellness Incentive Insurance Policy) 使被保險人達到預定的運動目標時，可獲得保費回饋來達到健康激勵效果。然而，研究運動強度對死亡率的影響需長期且大規模的醫學研究數據，保險公司無法在短時間內取得資料，對保戶的死亡率與回饋金額精算。因此這類型商品目前是參考同業損率與回饋比例制定，缺乏系統且科學的估計與定價方式。
本研究以統合性分析方法，收集50篇運動強度與死亡率具高度關聯性的研究。根據受試者的運動強度劑量，以代謝當量 (METs) 將樣本分為三個水平，建立一套評估運動強度對死亡率影響的計算模型。研究結果發現，與低運動強度相比，中運動強度的死亡風險降低39%，而高運動強度的死亡風險降低達47%，並依上述統合性分析結果計算出各運動強度組的年化死亡率。
基於死亡率計算結果，本研究對不同運動強度設計現金回饋的保費方案。發現目前保險公司提供的回饋金額度顯著低於本模型的計算結果，表示業者有相當程度的空間能透過增加回饋金來激勵保戶規律運動，降低群體死亡風險的同時也增加民眾購買外溢型保單的意願。

With wearables enabling activity tracking, insurers have introduced wellness incentive policies offering premium rebates for achieving exercise goals. However, accurately pricing such policies requires large-scale data on the relationship between exercise intensity and mortality risk, which insurers lack, currently relying on industry benchmarks lacking scientific rigor.
This meta-analysis of 50 studies established a model assessing mortality risk across exercise intensity levels, measured in metabolic equivalents (METs). Findings indicate moderate and high intensities reduce mortality risk by 39% and 47% respectively compared to low intensity. Calculated annualized mortality rates highlight a significant gap between current rebate amounts and model estimates.
Model estimates substantially diverge from current rebate amounts, highlighting significant potential for insurers to increase rebates as an incentive for regular exercise, concurrently reducing mortality risk and driving consumer adoption of wellness incentive policies.

目錄
第一章 緒論 1
第二章 文獻回顧 2
2-1 運動與死亡率關係與統合分析優勢 2
2-2 外溢型保單 3
第三章 資料整理與文獻篩選 4
3-1 資料來源與篩選 4
3-2 運動強度分級標準 4
3-3 資料整理 5
3-4 運動強度等級重新分類 8
3-5 文獻之敘述性統計 8
第四章 研究方法與實證分析 12
4-1 模型設定 12
4-2 參數估計 12
4-2-1研究內變異量 13
4-2-2 研究間變異量 15
4-2-3計算總外溢效果 15
4-2-4死亡率估算 16
4-4 實證結果分析 17
4-4-1分析方法 17
4-4-2統合性分析結果 17
4-4-3實證分析總結 21
第五章 外溢型保單設計與定價 22
5-1 保單設計的概念與架構 22
5-2 外溢型保單訂價 22
5-3 與先前文獻之比較 26
第六章、結論 28
6-1 研究結果 28
6-2 研究限制 29
參考文獻 30

中文部分
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