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EpiCast Report: Bipolar Disorder - Epidemiology Forecast to 2024

EpiCast Report: Bipolar Disorder - Epidemiology Forecast to 2024

Summary

Bipolar disorder, also known as bipolar depression or manic depression, is a psychological disorder that presents with severe shifts in mood from one extreme to another. The mood swings occur in a cyclic or periodic pattern that includes feelings of emotional highs (mania or hypomania) and lows (depression). In between episodes of mood swings, patients typically return to their regular state of being. During a manic or depressive episode, the disease can be debilitating, severely affecting a person’s ability to perform on the job or maintain good relationships with other people.

In 2014, there were 13,808,283 12-month and 23,140,488 lifetime total prevalent cases of bipolar disorder in the 8MM. In 2014, of the lifetime total prevalent cases, 52.15% were cyclothymic disorder, 24.58% bipolar I, and 23.27% bipolar II. GlobalData epidemiologists forecast that there will be approximately 14,703,622 12-month and 24,616,577 lifetime total prevalent cases of bipolar disorder in 2024.

In this report, GlobalData epidemiologists provide the forecast for the 12-month and lifetime total prevalent cases (both diagnosed and undiagnosed) of bipolar disorder spectrum in the 8MM. GlobalData epidemiologists sourced robust data based on national and international epidemiological studies and strong regional level studies. Age- and sex-specific rates were used whenever available. GlobalData epidemiologists used a consistent disease definition as well as consistent forecast methodology across all the 8MM to allow for a meaningful comparison among them.

Scope

  • The Bipolar EpiCast Report provides an overview of the risk factors, comorbidities, and global trends for bipolar spectrum disorder in the eight major markets (8MM) (US, France, Germany, Italy, Spain, UK, Japan, and Canada). It includes a 10-year epidemiological forecast for both 12-month and lifetime total prevalent cases of bipolar I, bipolar II, and cyclothymic disorder segmented by sex and age in these markets.
  • The bipolar epidemiology report is written and developed by Masters- and PhD-level epidemiologists.
  • The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 8MM.
Reasons to buy

The Bipolar EpiCast report will allow you to -
  • Develop business strategies by understanding the trends shaping and driving the global bipolar market.
  • Quantify patient populations in the global bipolar market to improve product design, pricing, and launch plans.
  • Organize sales and marketing efforts by identifying the sex and age groups that present the best opportunities for bipolar therapeutics in each of the markets covered.
  • Identify the subtype of bipolar disorder spectrum most important to your market plans.


1 Table of Contents
1.1 List of Tables
1.2 List of Figures
2 Introduction
2.1 Catalyst
2.2 Related Reports
2.3 Upcoming Related Reports
3 Epidemiology
3.1 Disease Background
3.2 Risk Factors and Comorbidities
3.3 Global Trends
3.4 Forecast Methodology
3.4.1 Sources Used
3.4.2 Sources Not Used
3.4.3 Forecast Assumptions and Methods
3.5 Epidemiological Forecast of Bipolar Disorder (2014-2024)
3.5.1 12-Month Total Prevalent Cases of Bipolar Spectrum Disorder
3.5.2 12-Month Total Prevalent Cases of Bipolar I
3.5.3 12-Month Total Prevalent Cases of Bipolar II
3.5.4 12-Month Total Prevalent Cases of Cyclothymic Disorder
3.5.5 Lifetime Total Prevalent Cases of Bipolar Spectrum Disorder
3.5.6 Age-Specific 12-Month Total Prevalent Cases of Bipolar I
3.5.7 Age-Specific 12-Month Total Prevalent Cases of Bipolar II
3.5.8 Age-Specific 12-Month Total Prevalent Cases of Cyclothymic Disorder
3.5.9 Sex-Specific 12-Month Total Prevalent Cases of Bipolar I
3.5.10 Sex-Specific 12-Month Total Prevalent Cases of Bipolar II
3.5.11 Sex-Specific 12-Month Total Prevalent Cases of Cyclothymic Disorder
3.5.12 Age-Standardized 12-Month Total Prevalence of Bipolar Spectrum Disorder
3.6 Discussion
3.6.1 Epidemiological Forecast Insight
3.6.2 Limitations of the Analysis
3.6.3 Strengths of the Analysis
4 Appendix
4.1 Bibliography
4.2 Physicians and Specialists Included in this Study
4.3 About the Authors
4.3.1 Epidemiologists
4.3.2 Reviewers
4.3.3 Global Director of Therapy Analysis and Epidemiology
4.3.4 Global Head of Healthcare
4.4 About GlobalData
4.5 About EpiCast
4.6 Disclaimer
1.1 List of Tables
Table 1: Risk Factors and Comorbidities for Bipolar Disorder
Table 2: 8MM, Sources Used to Forecast the 12-Month Total Prevalent Cases of Bipolar Disorder I
Table 3: 8MM, Sources Used to Forecast the Lifetime Total Prevalent Cases of Bipolar Disorder I
Table 4: 8MM, Sources Used to Forecast the 12-Month Total Prevalent Cases of Bipolar Disorder II
Table 5: 8MM, Sources Used to Forecast the Lifetime Total Prevalent Cases of Bipolar Disorder II
Table 6: 8MM, Sources Used to Forecast 12-Month Total Prevalent Cases of Cyclothymic Disorder
Table 7: 8MM, Sources Used to Forecast Lifetime Total Prevalent Cases of Cyclothymic Disorder
Table 8: 8MM, 12-Month Total Prevalent Cases of Bipolar Spectrum Disorder Summary, Both Sexes, Ages ≥13 Years, N (Row %), 2014
Table 9: 8MM, 12-Month Total Prevalent Cases of Bipolar I, Both Sexes, Ages ≥13 Years, 2014-2024
Table 10: 8MM, 12-Month Total Prevalent Cases of Bipolar II, Both Sexes, Ages ≥13 Years, 2014-2024
Table 11: 8MM, 12-Month Total Prevalent Cases of Cyclothymic Disorder, Both Sexes, Ages ≥13 Years, 2014-2024
Table 12: 8MM, Lifetime Total Prevalent Cases of Bipolar Spectrum Disorder Summary, Both Sexes, Ages ≥13 Years, N (Row %), 2014
Table 13: 8MM, Age-Specific 12-Month Total Prevalent Cases of Bipolar I, Both Sexes, Ages ≥13 Years, N (Row %), 2014
Table 14: 8MM, Age-Specific 12-Month Total Prevalent Cases of Bipolar II, Both Sexes, Ages ≥13 Years, N (Row %), 2014
Table 15: 8MM, Age-Specific 12-Month Total Prevalent Cases of Cyclothymic Disorder, Both Sexes, Ages ≥13 Years, N (Row %), 2014
Table 16: 8MM, Sex-Specific 12-Month Total Prevalent Cases of Bipolar I, Ages ≥13 Years, N (Row %), 2014
Table 17: 8MM, Sex-Specific 12-Month Total Prevalent Cases of Bipolar II, Ages ≥13 Years, N (Row %), 2014
Table 18: 8MM, Sex-Specific 12-Month Total Prevalent Cases of Cyclothymic Disorder, Ages ≥13 Years, N (Row %), 2014
Table 19: High-Prescribing Physicians (Non-KOLs) Surveyed, By Country
1.2 List of Figures
Figure 1: 8MM, 12-Month Total Prevalent Cases of Bipolar I, Both Sexes, Ages ≥13 Years, 2014-2024
Figure 2: 8MM, Bipolar II 12-Month Total Prevalent Cases, Both Sexes, Ages ≥13 Years, 2014-2024
Figure 3: 8MM, 12-Month Total Prevalent Cases of Cyclothymic Disorder, Both Sexes, Ages ≥13 Years, 2014-2024
Figure 4: 8MM, Age-Specific 12-Month Total Prevalent Cases of Bipolar I, Both Sexes, 2014
Figure 5: 8MM, Age-Specific 12-Month Total Prevalent Cases of Bipolar II, Both Sexes, 2014
Figure 6: 8MM, Age-Specific 12-Month Total Prevalent Cases of Cyclothymic Disorder, Both Sexes, 2014
Figure 7: 8MM, Sex-Specific 12-Month Total Prevalent Cases of Bipolar I, Ages ≥13 Years, 2014
Figure 8: 8MM, Sex-Specific 12-Month Total Prevalent Cases of Bipolar II, Ages ≥13 Years, 2014
Figure 9: 8MM, Sex-Specific 12-Month Total Prevalent Cases of Cyclothymic Disorder, Ages ≥13 Years, 2014
Figure 10: 8MM, Age-Standardized 12-Month Total Prevalence of Bipolar Spectrum Disorder, Men, Ages ≥13 Years, 2014
Figure 11: 8MM, Age-Standardized 12-Month Total Prevalence of Bipolar Spectrum Disorder, Women, Ages ≥13 Years, 2014

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