ICBDSR Report 2024

South America ECLAMC, 2015 to 2020

total births in the 6-year period: 330,135 (livebirths: 326,000)
average births per year: 55,020 (livebirths: 54,330)
terminations of pregnancy legal in country: Other
data include terminations of pregnancy: No
source structure: Hospital based

ECLAMC operates in 20 hospitals in Uruguay, Chile, Argentina, Brazil, Bolivia, Peru, Paraguay, Venezuela and Colombia

A word from the program

The ECLAMC program is hospital-based and currently includes 20 active hospitals in Latin America, from Uruguay, Chile, Argentina, Brazil, Bolivia, Peru, Paraguay, Venezuela and Colombia.
The ECLAMC, in operation since 1967, works as clinical and epidemiological investigation of developmental congenital anomalies in Latin America.As a surveillance system, ECLAMC systematically assesses fluctuations in the frequencies of the different malformations, and when an alarm for an epidemic is raised for a given malformation, time period, or area, it is mobilized to identify its origin and cause.
The ECLAMC operates as a voluntary agreement among professionals dedicated to the study of congenital malformations in Latin American hospitals. Members collaborate and agree on a set of operational rules and procedures that ensure data standards necessary for the harmonization of data across different hospitals.
Despite the lack of funding support, collaborating pediatricians in the active hospitals are highly engaged, enhancing data quality, which is assessed using data quality indicators.

Selected data highlights

The following tables highlight selected sets of congenital anomalies, each with a specific focus. Because of ECLAMC’s integrated structure across multiple countries (without country breakdown), the report does not include country-specific projections and estimates on case numbers and prevalence.

Top Ten

Here are the program’s top ten conditions by frequency, selected among those with significant clinical and public health impact. These are the conditions that one is more likely to encounter in the population under surveillance and impact the largest number of individuals and their families.

Condition	Cases	Yearly Avg	Prevalence
Top 10 Conditions by Frequency
among specific diagnoses with major health impact, South America ECLAMC, 2015-2020 shown are total cases for the reporting period, yearly average cases, and prevalence per 10,000
Hydrocephaly	763	127	23.1
Down syndrome	717	120	21.7
Cleft lip with or without cleft palate	568	95	17.2
Spina bifida	395	66	12.0
Gastroschisis	319	53	9.7
Microtia	236	39	7.1
Anorectal atresia/stenosis	209	35	6.3
Cystic kidney	175	29	5.3
Esophageal atresia	157	26	4.8
Diaphragmatic hernia	148	25	4.5
Note: not considered here are microcephaly, undescended testis, and unspecified conditions. However, microcephaly and undescended testis are included in the full table below. The green bar visually compares the prevalence (rows) relative to the most common condition in the table.

Notable Seven

These conditions exemplify the impact of congenital anomalies on morbidity and mortality. For example, neural tube defects and critical congenital heart disease, when combined, account for approximately half of all infant deaths associated with congenital anomalies.

For several of these conditions, modifiable risk factors are well established, and primary prevention, if implemented appropriately, works. This implication is unpacked in a later section (‘what if scenario’).

	Program	Percent liveborn	Prevalence per 10,000
Seven highly impactful conditions
selected on the basis of high morbidity and mortality, and potential for primary prevention South America ECLAMC, 2015-2020
Neural tube defects (NTD)
Neural tube defects, total	100	84	18.3
Spina bifida	66	94	12.0
Anencephaly	19	46	3.4
Orofacial
Cleft lip with or without cleft palate	95	91	17.2
Cleft palate without cleft lip	22	93	3.9
Heart
Tetralogy of Fallot	10	98	1.8
Hypoplastic left heart syndrome	8	89	1.4
Transposition of great vessels	6	97	1.0
Note: the green bar visually compares the prevalence (rows) relative to the most common condition in the table.

The full table

This more expansive set of major congenital anomalies, internal and external, includes most conditions of significant clinical and public health impact. A more detailed view of Trisomy 21 (Down syndrome) is included in a later section. Note: a child with multiple anomalies will be counted in all pertinent rows.

	All births			Livebirths
Selected congenital conditions by system
number of cases and prevalence (prev) per 10,000, for all births and livebirths South America ECLAMC, 2015-2020
	Cases	Prev	95% CI	Cases	Prev	95% CI
Neural tube defects (NTD)
Neural tube defects, total	603	18.3	16.8 - 19.8	506	15.5	14.2 - 16.9
Spina bifida	395	12.0	10.8 - 13.2	373	11.4	10.3 - 12.6
Anencephaly	113	3.4	2.8 - 4.1	52	1.6	1.2 - 2.0
Encephalocele	95	2.9	2.3 - 3.5	81	2.5	1.9 - 3.0
Other brain
Hydrocephaly	763	23.1	21.5 - 24.8	715	21.9	20.3 - 23.5
Microcephaly	324	9.8	8.8 - 10.9	304	9.3	8.3 - 10.4
Holoprosencephaly	23	0.7	0.4 - 1.0	13	0.4	0.2 - 0.6
Eye and Ear
Microtia	236	7.1	6.3 - 8.1	223	6.8	5.9 - 7.7
Microphthalmos	47	1.4	1.0 - 1.9	38	1.2	0.8 - 1.5
Anophthalmos	24	0.7	0.5 - 1.1	21	0.6	0.4 - 0.9
Anotia	13	0.4	0.2 - 0.7	12	0.4	0.2 - 0.6
A/microtia, unspec.	12	0.4	0.2 - 0.6	11	0.3	0.1 - 0.5
Orofacial
Cleft lip with or without cleft palate	568	17.2	15.8 - 18.7	519	15.9	14.6 - 17.3
Cleft palate without cleft lip	130	3.9	3.3 - 4.7	121	3.7	3.1 - 4.4
Choanal atresia bilateral	8	0.2	0.1 - 0.5	8	0.2	0.1 - 0.4
Heart
Tetralogy of Fallot	58	1.8	1.3 - 2.3	57	1.7	1.3 - 2.2
Hypoplastic left heart syndrome	47	1.4	1.0 - 1.9	42	1.3	0.9 - 1.7
Transposition of great vessels	34	1.0	0.7 - 1.4	33	1.0	0.7 - 1.4
Coarctation of aorta	27	0.8	0.5 - 1.2	21	0.6	0.4 - 0.9
Gastrointestinal
Anorectal atresia/stenosis	209	6.3	5.5 - 7.2	183	5.6	4.8 - 6.4
Esophageal atresia	157	4.8	4.0 - 5.6	145	4.4	3.7 - 5.2
Small intestinal atresia/stenosis	75	2.3	1.8 - 2.8	74	2.3	1.8 - 2.8
Genitourinary
Undescended testis	382	11.6	10.4 - 12.8	371	11.4	10.2 - 12.5
Cystic kidney	175	5.3	4.5 - 6.1	162	5.0	4.2 - 5.7
Indeterminate sex	91	2.8	2.2 - 3.4	71	2.2	1.7 - 2.7
Renal agenesis	38	1.2	0.8 - 1.6	24	0.7	0.4 - 1.0
Hypospadias	23	0.7	0.4 - 1.0	23	0.7	0.4 - 1.0
Bladder exstrophy	11	0.3	0.2 - 0.6	10	0.3	0.1 - 0.5
Epispadias	10	0.3	0.1 - 0.6	10	0.3	0.1 - 0.5
Limb
Limb deficiency, total	188	5.7	4.9 - 6.6	165	5.1	4.3 - 5.8
Limb deficiency, unspec.	118	3.6	3.0 - 4.3	93	2.9	2.3 - 3.4
Polydactyly preaxial	81	2.5	1.9 - 3.0	80	2.5	1.9 - 3.0
Limb deficiency, preaxial	20	0.6	0.4 - 0.9	18	0.6	0.3 - 0.8
Limb deficiency, mixed	17	0.5	0.3 - 0.8	14	0.4	0.2 - 0.7
Limb deficiency, transverse	14	0.4	0.2 - 0.7	12	0.4	0.2 - 0.6
Limb deficiency, intercalary	10	0.3	0.1 - 0.6	9	0.3	0.1 - 0.5
Limb deficiency, axial	5	0.2	0.0 - 0.4	4	0.1	0.0 - 0.3
Limb deficiency, postaxial	4	0.1	0.0 - 0.3	4	0.1	0.0 - 0.3
Abdominal
Gastroschisis	319	9.7	8.6 - 10.8	299	9.2	8.1 - 10.2
Diaphragmatic hernia	148	4.5	3.8 - 5.3	144	4.4	3.7 - 5.1
Omphalocele	98	3.0	2.4 - 3.6	77	2.4	1.8 - 2.9
Omphalocele/Gastroschisis, unspec.	45	1.4	1.0 - 1.8	35	1.1	0.7 - 1.4
Prune belly sequence	8	0.2	0.1 - 0.5	6	0.2	0.0 - 0.3
Chromosomal
Down syndrome	717	21.7	20.2 - 23.4	652	20.0	18.5 - 21.5
Trisomy 18	44	1.3	1.0 - 1.8	35	1.1	0.7 - 1.4
Trisomy 13	26	0.8	0.5 - 1.2	19	0.6	0.3 - 0.8
Note a dash (-) indicates data not available or not provided

Program Comment

The program leads provide their insights on data, operations, and recent achievements. Their interpretation of the data is particularly valuable because of their local experience and knowledge.

Currently, the program includes 20 active hospital, fewer than in the past. This decrease is mainly due to retiring pediatricians from the cohort of ECLAMC hospital champions. Because ECLAMC is primarily sustained by collaborating pediatricians from hospitals working directly with the program, when one of them retires often the hospital stops reporting to ECLAMC. Incorporating new hospitals has been difficult, mainly because reporting is unpaid work and there is no funding from ECLAMC to support it. On the other hand, because collaborating pediatricians in the active hospitals are highly engaged, data quality is high, as also indicated by data quality indicators. At the central program level, coding has slowed due to lack of personel, leading to some categories having more than usual unspecified cases.

Down syndrome (trisomy 21)

By far the most common chromosomal anomaly, Down syndrome is known to occur more frequently (has a higher risk of occurrence) in births of women with higher maternal age

This pattern is universally observed, provided there is no significant bias toward missing pregnancies with Down syndrome in older women (e.g., because of unreported pregnancy terminations)

	All cases			Livebirths
Down syndrome, overall and by maternal age
separately for all births and livebirths, prevalence per 10,000 (Poisson exact confidence intervals) South America ECLAMC, 2015-2020
	Cases	Prev	95% CI	Cases	Prev	95% CI
All maternal ages	717	21.7	20.2 - 23.4	652	20.0	18.5 - 21.5
< 20 years	35	7.2	5.0 - 10.0	35	7.2	4.8 - 9.6
20 to 24	60	7.0	5.4 - 9.0	55	6.4	4.7 - 8.1
25 to 29	68	8.3	6.5 - 10.6	61	7.5	5.6 - 9.4
30 to 34	90	14.3	11.5 - 17.6	79	12.6	9.8 - 15.3
35 to 39	222	57.6	50.3 - 65.7	206	53.5	46.2 - 60.8
40 to 44	209	182.0	158.1 - 208.4	187	162.8	139.7 - 186.0
45+ years	30	367.2	247.7 - 524.2	27	330.5	207.9 - 453.1
Age unspec.	3	-	-	2	-	-
Age unspec. = maternal age unknown or unspecified

Down syndrome - maternal age pyramid

Because of the relation between prevalence of Down syndrome and maternal age, the maternal age distribution in the population is a major determinant of the number of conceptions with Down syndrome in the population.

For programs that have maternal age specific data, one can compare the maternal-age ‘pyramid’ for all births in the population with that of births with Down syndrome. Typically, the distribution is skewed, with a relative excess of births with Down syndrome among the more advanced maternal age groups.

Down syndrome - birth rates matter

Despite the considerably higher risk (rates) of Down syndrome in mothers over 40 or 45 years, these age groups contribute comparatively fewer affected births than younger age groups. This is because birth rates matter: fewer births in the more advanced age groups mean fewer cases overall from those age groups.

A Pareto chart helps highlight the cumulative contribution of different age groups to the total number of cases. This information can help inform strategies for testing and counseling.