表紙:1型糖尿病(T1D):疫学予測(~2033年)
市場調査レポート
商品コード
1599072

1型糖尿病(T1D):疫学予測(~2033年)

Type 1 Diabetes: Epidemiology Forecast to 2033


出版日
発行
GlobalData
ページ情報
英文 69 Pages
納期
即納可能 即納可能とは
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=146.99円
1型糖尿病(T1D):疫学予測(~2033年)
出版日: 2024年11月13日
発行: GlobalData
ページ情報: 英文 69 Pages
納期: 即納可能 即納可能とは
GIIご利用のメリット
  • 全表示
  • 概要
  • 図表
  • 目次
概要

当レポートでは、主要7市場(米国、フランス、ドイツ、イタリア、スペイン、英国、日本)における1型糖尿病(T1D)について調査分析し、1型糖尿病の危険因子や併存疾患、過去の動向、2033年までの疫学的予測などの情報を提供しています。

目次

第1章 1型糖尿病(T1D):エグゼクティブサマリー

  • カタリスト
  • 関連レポート
  • 今後のレポート

第2章 疫学

  • 疾患の背景
  • 危険因子と合併症
  • 世界の過去の動向
  • 主要7市場の予測手法
  • T1Dの疫学的予測(2023年~2033年)
    • T1Dの患者数
    • T1Dの患者数:年齢別
    • T1Dの患者数:性別
    • T1Dの患者数:BMIカテゴリ別
    • 低血糖の発症を経験したT1Dの患者数
    • 脆弱型糖尿病を伴うT1Dの患者数
    • DKAの発症を経験したT1Dの患者数
    • 膵臓移植の対象となるT1Dの患者数
    • CKDを伴うT1Dの患者数
    • CVDを伴うT1Dの患者数
    • HLA-DQ8をコードする遺伝子を1つ以上持つT1Dの患者数
    • T1Dの総患者数
  • 議論
    • 疫学的予測の考察
    • COVID-19の影響
    • 分析の限界
    • 分析の強み

第3章 付録

図表

List of Tables

  • Table 1: Summary of newly added data types
  • Table 2: Summary of updated data types
  • Table 3: Diagnostic tests commonly used for T1D
  • Table 4: Risk factors and comorbidities for T1D

List of Figures

  • Figure 1: 7MM, diagnosed prevalent cases of T1D, all ages, both sexes, N, 2023 and 2033
  • Figure 2: 7MM, total prevalent cases of T1D, all ages, both sexes, N, 2023 and 2033
  • Figure 3: 7MM, diagnosed prevalence of T1D, men and women, %, all ages, 2023
  • Figure 4: 7MM, total prevalence of T1D, men and women, %, all ages, 2023
  • Figure 5: 7MM, sources used and not used to forecast the diagnosed prevalent cases of T1D
  • Figure 6: 7MM, sources used to forecast the diagnosed prevalent cases of T1D segmented by BMI category
  • Figure 7: 7MM, sources used and not used to forecast the diagnosed prevalent cases of T1D that experienced hypoglycemia
  • Figure 8: 7MM, source used to forecast the diagnosed prevalent cases of T1D with brittle diabetes
  • Figure 9: 7MM, sources used and not used to forecast the diagnosed prevalent cases of T1D that experienced DKA
  • Figure 10: 7MM, sources used to forecast the diagnosed prevalent cases of T1D that are eligible for a pancreas transplant
  • Figure 11: 7MM, sources used and not used to forecast the diagnosed prevalent cases of T1D with CKD
  • Figure 12: 7MM, sources used and not used to forecast the diagnosed prevalent cases of T1D with CVD
  • Figure 13: 7MM, sources used to forecast the diagnosed prevalent cases of T1D with at least one gene encoding for HLA-DQ8
  • Figure 14: 7MM, sources used to forecast the total prevalent cases of T1D
  • Figure 15: 7MM, diagnosed prevalent cases of T1D, N, both sexes, all ages, 2023
  • Figure 16: 7MM, diagnosed prevalent cases of T1D by age, N, both sexes, 2023
  • Figure 17: 7MM, diagnosed prevalent cases of T1D by sex, N, all ages, 2023
  • Figure 18: 7MM, diagnosed prevalent cases of T1D by BMI category, N, both sexes, all ages, 2023
  • Figure 19: 7MM, diagnosed prevalent cases of T1D that experienced hypoglycemic events, N, both sexes, all ages, 2023
  • Figure 20: 7MM, diagnosed prevalent cases of T1D with brittle diabetes, N, both sexes, all ages, 2023
  • Figure 21: 7MM, diagnosed prevalent cases of T1D that experienced DKA, N, both sexes, all ages, 2023
  • Figure 22: 7MM, diagnosed prevalent cases of T1D eligible for pancreas transplantation, N, both sexes, >=20 years, 2023
  • Figure 23: 7MM, diagnosed prevalent cases of T1D with CKD, N, both sexes, all ages, 2023
  • Figure 24: 7MM, diagnosed prevalent cases of T1D with CVD, N, both sexes, all ages, 2023
  • Figure 25: 7MM, diagnosed prevalent cases of T1D with at least one gene encoding for HLA-DQ8, N, both sexes, all ages, 2023
  • Figure 26: 7MM, total prevalent cases of T1D, N, both sexes, all ages, 2023
目次
Product Code: GDHCER328-24

T1D, formally referred to as insulin-dependent diabetes or juvenile diabetes, is a chronic autoimmune disease that predominantly develops in childhood and young adulthood and accounts for approximately 5-10% of all diabetes cases. It is caused by the body's immune system destroying pancreatic beta cells, which are responsible for producing a hormone that regulates blood sugar levels called insulin (Mobasseri et al., 2020). If T1D is left untreated, blood sugar levels increase, which can damage the pancreas and other organs (Mayo Clinic, 2024). As T1D is a chronic condition, it has a significant impact on the physical, psychological, and social wellbeing of patients.

Scope

  • The Type 1 Diabetes Epidemiology Report and Model provide an overview of the risk factors, comorbidities, and the global and historical trends of type 1 diabetes (T1D) in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan).
  • The report includes a 10-year epidemiology forecast for T1D, segmented by age, sex, body mass index (BMI) (underweight/normal [BMI <25kg/m2], overweight [BMI 25-30kg/m2], and obese [BMI >=30kg/m2]), hypoglycemic events (hypoglycemic and severe hypoglycemic events), brittle diabetes, diabetic ketoacidosis (DKA) events, and having at least one gene encoding for HLA-DQ8 for men and women of all ages. Additionally, the report also provides a 10-year epidemiological forecast for the diagnosed prevalent cases of T1D eligible for pancreas transplantation, with chronic kidney disease (CKD), and with cardiovascular disease (CVD) for men and women over 20 years old. The report also includes total prevalent cases of T1D for men and women of all ages.

Reasons to Buy

The T1D Epidemiology series will allow you to -

  • Develop business strategies by understanding the trends shaping and driving the global T1D markets.
  • Quantify patient populations in the global T1D markets to improve product design, pricing, and launch plans.
  • Organize sales and marketing efforts by identifying the age groups, sex, BMI groups, disease conditions and genetic groups that present the best opportunities for T1D therapeutics in each of the markets covered.
  • Understand magnitude of the T1D population by age, sex, BMI groups, associated disease conditions, pancreas transplant eligibility, and genetic groups.

Table of Contents

Table of Contents

  • About GlobalData

1 Type 1 Diabetes (T1D): Executive Summary

  • 1.1 Catalyst
  • 1.2 Related reports
  • 1.3 Upcoming reports

2 Epidemiology

  • 2.1 Disease background
  • 2.2 Risk factors and comorbidities
  • 2.3 Global and historical trends
  • 2.4 7MM forecast methodology
    • 2.4.1 Sources
    • 2.4.2 Forecast assumptions and methods
    • 2.4.3 Forecast assumptions and methods: diagnosed prevalent cases of T1D - 7MM
    • 2.4.4 Forecast assumptions and methods: diagnosed prevalent cases of T1D
    • 2.4.5 Diagnosed prevalent cases of T1D segmented by BMI
    • 2.4.6 Diagnosed prevalent cases of T1D that experienced hypoglycemic events
    • 2.4.7 Diagnosed prevalent cases of T1D with brittle diabetes
    • 2.4.8 Diagnosed prevalent cases of T1D that experienced DKA events
    • 2.4.9 Diagnosed prevalent cases of T1D eligible for pancreas transplantation
    • 2.4.10 Diagnosed prevalent cases of T1D with CKD
    • 2.4.11 Diagnosed prevalent cases of T1D with CVD
    • 2.4.12 Diagnosed prevalent cases of T1D with at least one gene encoding for HLA-DQ8
    • 2.4.13 Forecast assumptions and methods: total prevalent cases of T1D
  • 2.5 Epidemiological forecast for T1D (2023-33)
    • 2.5.1 Diagnosed prevalent cases of T1D
    • 2.5.2 Age-specific diagnosed prevalent cases of T1D
    • 2.5.3 Sex-specific diagnosed prevalent cases of T1D
    • 2.5.4 Diagnosed prevalent cases of T1D by BMI category
    • 2.5.5 Diagnosed prevalent cases of T1D that experienced hypoglycemic events
    • 2.5.6 Diagnosed prevalent cases of T1D with brittle diabetes
    • 2.5.7 Diagnosed prevalent cases of T1D that experienced DKA events
    • 2.5.8 Diagnosed prevalent cases of T1D eligible for pancreas transplantation
    • 2.5.9 Diagnosed prevalent cases of T1D with CKD
    • 2.5.10 Diagnosed prevalent cases of T1D with CVD
    • 2.5.11 Diagnosed prevalent cases of T1D with at least one gene encoding for HLA-DQ8
    • 2.5.12 Total prevalent cases of T1D
  • 2.6 Discussion
    • 2.6.1 Epidemiological forecast insight
    • 2.6.2 COVID-19 impact
    • 2.6.3 Limitations of the analysis
    • 2.6.4 Strengths of the analysis

3 Appendix

  • 3.1 Bibliography
  • 3.2 About the Authors
    • 3.2.1 Epidemiologist
    • 3.2.2 Reviewers
    • 3.2.3 Vice President of Disease Intelligence and Epidemiology
    • 3.2.4 Global Head of Pharma Research, Analysis and Competitive Intelligence
  • Contact Us