On the Calculation of the Prevalence of Transsexualism

On the Calculation of the Prevalence of Transsexualism Prof. Femke Olyslager 1, Ph. D, and Prof. em. Lynn Conway 2 1 Department of Information Technology, Ghent University, Ghent, Belgium 2 Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA 1/11

Introduction • Introductory remark: – Only male-to-female transsexualism is discussed here! • The key-question: “What are the chances that my child is transsexual? ” = “The prevalence of transsexualism. ” • Observation: – Literature(1): P = 1 in 11, 900 – In discrepancy with simple sanity-checks!(2) • Actions: – Analyse the old reports on prevalence – Develop a mathematical framework – Derive commensurable prevalence numbers (1) A. Bakker et al. , “The prevalence of transsexualism in the Netherlands, ” Acta Psych. Scand. , 1993. (2) L. Conway, “How frequently does transsexualism occur? , ” Lynn. Conway. com, 2001. 2/11

Deriving prevalence • • How was prevalence derived? # patients receiving treatment P= total population Problem A: – E. g. the Netherlands(1, 2): 1980 P = 1 in 45, 000 1983 1 in 26, 000 1986 1 in 18, 000 1990 1 in 11, 900 “Prevalence increases over time, as more patients treated. ” • Problem B: – Who is counted? Those satisfying TS definition, those on hormone therapy, those having SRS, . . . ? “Leads to incommensurable numbers. ” (1) A. Bakker et al. , “The prevalence of transsexualism in the Netherlands, ” Acta Psych. Scand. , 1993. (2) P. L. E. Eklund et al. , “Prevalence of transsexualism in the Netherlands, ” Brit. J. Psych. , 1988. 3/11

Deriving prevalence • Types of prevalence: – – – • P(TS) = the prevalence of transsexualism P(SH) = the prevalence of transsexual people who have sought help P(HT) = the prevalence of those on hormone therapy P(ST) = the prevalence of those who have socially transitioned P(SRS) = the prevalence of those who have undergone SRS Inequalities (in general): P(TS) > P(SH) > P(HT) > P(SRS) or: P(TS) > P(SH) > P(ST) > P(HT) > P(SRS) – Allows e. g. to derive P(HT) from P(SRS) if P(SRS)/P(HT) is known – Provides lower bounds for P(TS) 4/11

Deriving prevalence • Suppose transsexuality were visible at birth: • # transsexual babies per year # births per year Suppose transsexuality is always identified at some point in life: P(TS) = # identified individuals per year # births per year – Assumes constant demographics – Assumes regime situation for # identified individuals • Correction for non-constant demographics: P(TS) = # identified individuals per year # births per year L years ago L = average of identification • Note: This is a different from recurring conditions such as the flu, where: P(flu) = # flu cases per year duration flu in days x total population 365 5/11

Inherent vs. active prevalence • “Inherent” prevalence: – P(TSI) = 1 in 4, 000 & population = 4, 000 • 1, 000 identified transsexuals? No! – Age of identification L = 35 years & life expectancy E = 70 years • 500 identified transsexuals! • “Active” prevalence: P(TSA) = • # identified individuals total population Relation between “active” and “inherent” prevalence: _ E L P(TSA) = x P(TSI) E L = average of identification E = life expectancy 6/11

An example • Prevalence as given in Bakker et. al. (1): P(HT in Bakker et. al. (1)) = • 507 patients in 1976 - 1990 = 1 in 11, 900 6, 019, 546 males > 15 years Inherent prevalence: – 34 new patients annually (1, 2) – Average to start HT: L = 32 years – Male births in 1990 – 32 = 1958 (3): 120, 000 # new HT per year 34 = = 1 in 3, 500 # births per year L years ago 120, 000 Active prevalence: P(HTI) = • – If life expectancy E = 75 years, then P(HTA) = E _ E L x P(HTI) = 75 _ 75 32 x 34 = 1 in 6, 200 120, 000 (1) A. Bakker et al. , “The prevalence of transsexualism in the Netherlands, ” Acta Psych. Scand. , 1993. (2) P. L. E. Eklund et al. , “Prevalence of transsexualism in the Netherlands, ” Brit. J. Psych. , 1988. (3) Central bureau for statistics in the Netherlands, http: //www. cbs. nl. 7/11

Other methods • Other methods to estimate the prevalence of transsexualism: “triangulations and sanity-checks” • Example 1: Fellows of the IEEE(1) – 5, 500 Fellows (mostly males) – 3 Fellows had SRS – Estimate: P(SRSA) = 3 = 1 in 1, 800 5, 500 – If P(SRSA) = 1 in 11, 900 then only 1. 6% chance to have 3 cases (1) IEEE: Institute for Electrical and Electronics Engineers. 8/11

Other methods • Example 2: SRS surgeries on US residents(1) – Over 1, 500 SRS on US residents = over 1, 000 SRS in US + over 500 SRS elsewhere – 2, 000 US male births per year P(SRSI) = # SRS per year 1, 500 > > 1 in 1, 300 # births per year 2, 000 – Since P(TSI) > P(SHI) > P(HTI) > P(SRSI): P(TSI) > 1 in 500 (1) L. Conway, “How frequently does transsexualism occur? , ” Lynn. Conway. com, 2001. 9/11

Other methods • Example 3: estimates based on Thai Kathoey – Counting Kathoey (1): 6 per 1, 000 P(STA) = 6 = 1 in 167 1, 000 – Demographic profile of Kathoey (2): 27. 7% of Kathoey had SRS P(SRSA) = 0. 277 x P(STA) = 1 in 600 – Average of SRS L = 24. 1 years & Life expectancy E = 73 years P(SRSI) = 73 x P(SRSA) = 1 in 400 73 _ 24. 1 – Demographic profile of Kathoey (2): 48. 3% of Kathoey who had no SRS want SRS P(TSI) = 1 in 200 (1) S. Winter, “Counting Kathoey, ” Transgender Asia papers, 2002. (2) S. Winter, “Thai Transgenders in focus, Demographics, Transitions and Identities, ” IJT, 2006. 10/11

Conclusions • Past reports failed to answer the key question: “What are the chances that my child is transsexual? ” • Analysis of past reports: P(SRSI) = 1 in 4, 500 to 1 in 2, 000 • P(TSI) = 1 in 2, 000 to 1 in 1, 000 Estimates from more recent reports: P(TSI) = 1 in 500 Transsexuality is not that uncommon! Important for transgender health care and recognition by society! • Further reading (draft hardcopies available from authors): F. Olyslager and L. Conway, “On the Calculation of the Prevalence of Transsexualism, ” submitted to the International Journal of Transgenderism. 11/11