Knowledge · Epidemiology

How common is dysmelia, and how many children a year?

Two questions, two kinds of answer. Prevalence is a rate: how many children in 10,000 births are conceived with a condition, as measured by the registries that count them. Incidence is what that rate becomes when it meets a population: how many children a year a country can expect. The first part below gives the rates, condition by condition, each checked against its publication; the second turns them into numbers for every country, which you can filter.

Part 1 · Prevalence at birth

How common is each condition?

Two columns, two kinds of source. Orphanet gives each rare disease a prevalence class and, where available, a mean estimate; it is the reference for named syndromes. Population studies fill the gaps for the conditions Orphanet does not count (the amelias, polydactyly, syndactyly, brachydactyly) and cross-check the others. Every figure was checked against its original publication in September 2026.

How to read these figures: they describe births, not the number of persons living with a condition; ranges are Orphanet's prevalence classes; the named conditions do not add up to the total for limb reduction defects, because most limb differences are isolated deficiencies without a syndrome name. Rates also differ between populations and registries. None of this is medical advice.

Sources of the prevalence figures

1. Bermejo-Sánchez E, Cuevas L, Amar E, et al. Amelia: a multi-center descriptive epidemiologic study in a large dataset from the International Clearinghouse for Birth Defects Surveillance and Research, and overview of the literature. Am J Med Genet C Semin Med Genet. 2011;157C(4):288-304. doi.org/10.1002/ajmg.c.30319
2. Pakkasjärvi N, Syvänen J, Wiro M, Koskimies-Virta E. Amelia and phocomelia in Finland: characteristics and prevalences in a nationwide population-based study. Birth Defects Res. 2022;114(20):1427-1433. doi.org/10.1002/bdr2.2123
3. Vasluian E, van der Sluis CK, van Essen AJ, et al. Birth prevalence for congenital limb defects in the northern Netherlands: a 30-year population-based study. BMC Musculoskelet Disord. 2013;14:323. doi.org/10.1186/1471-2474-14-323
4. Chen ZY, Li WY, Xu WL, et al. The changing epidemiology of syndactyly in Chinese newborns: a nationwide surveillance-based study. BMC Pregnancy Childbirth. 2023;23:334. doi.org/10.1186/s12884-023-05660-z
5. Temtamy SA, Aglan MS. Brachydactyly. Orphanet J Rare Dis. 2008;3:15. doi.org/10.1186/1750-1172-3-15
6. Koskimies E, Lindfors N, Gissler M, Peltonen J, Nietosvaara Y. Congenital upper limb deficiencies and associated malformations in Finland: a population-based study. J Hand Surg Am. 2011;36(6):1058-1065. doi.org/10.1016/j.jhsa.2011.03.015
7. Pakkasjärvi N, Koskimies E, Ritvanen A, Nietosvaara Y, Mäkitie O. Characteristics and associated anomalies in radial ray deficiencies in Finland: a population-based study. Am J Med Genet A. 2013;161A(2):261-267. doi.org/10.1002/ajmg.a.35707
8. Syvänen J, Nietosvaara Y, Ritvanen A, Koskimies E, Kauko T, Helenius I. High risk for major nonlimb anomalies associated with lower-limb deficiency: a population-based study. J Bone Joint Surg Am. 2014;96(22):1898-1904. doi.org/10.2106/JBJS.N.00155
9. Klungsøyr K, Nordtveit TI, Kaastad TS, et al. Epidemiology of limb reduction defects as registered in the Medical Birth Registry of Norway, 1970-2016: population based study. PLoS One. 2019;14(7):e0219930. Cites the EUROCAT figure for Europe 2003-2012 (Morris et al., 2018). doi.org/10.1371/journal.pone.0219930
10. Shin YH, Baek GH, Kim YJ, Kim MJ, Kim JK. Epidemiology of congenital upper limb anomalies in Korea: a nationwide population-based study. PLoS One. 2021;16(3):e0248105. doi.org/10.1371/journal.pone.0248105
11. Orphanet. Orphadata, epidemiological data (product 9), release of 23 June 2026. Licence CC BY 4.0. www.orphadata.com/epidemiology/
12. Gordillo M, Vega H, Jabs EW. ESCO2 Spectrum Disorder. In: GeneReviews. University of Washington, Seattle. www.ncbi.nlm.nih.gov/books/NBK1153/

Part 2 · Incidence, year by year

How many children are conceived with it each year?

A prevalence is a rate; families and health services need a number. The world records about 132 million births a year across the 217 countries the World Bank counts, so the rate of 4.5 per 10,000 births that European registries measure for limb reduction defects works out at roughly 59,554 children a year worldwide. On the same arithmetic, polydactyly reaches about 111,167 a year and syndactyly 62,201, while amelia, the absence of a whole limb, comes to about 1,866. In a country the size of France, with 664,951 births a year, the same rates give 299 limb reduction defects and 9.4 children conceived with amelia.

These are expectations, not counts, and the distinction matters. Every rate in the table above was measured by a registry in Europe, Finland or the northern Netherlands, and applying it to births in Nigeria, India or Brazil assumes the rate is the same there, which no one has shown; where other registries have measured, the figures differ. Read the numbers below as the order of magnitude a health service should plan for, and as the reason a patient-owned registry is worth building: it turns an estimate into a consented, counted child who can be offered care.

Births: World Bank open data (CC BY 4.0): population SP.POP.TOTL and crude birth rate SP.DYN.CBRT.IN, most recent year with both. Read 2026-09-14, covering 2024. data.worldbank.org · Download the births data (JSON). Rates: the prevalence table above, with its sources; each is stated per 10,000 births in the selector. Expected cases = births × rate. A country whose expectation falls below one child a year is shown to one decimal: it means the condition is expected there less often than once a year, not never.

These figures say how often each condition occurs and how many children that means. What is known about why it occurs is set out in Causes of dysmelia, and what each condition is in Understanding dysmelia.