Prevalence of preterm birth according to birth weight group: a
          systematic review

Systematic review of the Brazilian literature published from 1990 to 2012, to identify studies with primary collection of data on birth weight and gestational age. Twelve studies were selected and contributed for tabulations of preterm prevalence according to 100 g birth weight categories. These results were combined using sex-specific fractional polynomial equations and the resulting curves were compared with results from the Live Birth Information System for the years 2000, 2005, 2010 and 2011.

RESULTS

For all birth weight categories, preterm prevalence estimates based on primary studies had a higher prevalence than those of the the Live Birth Information System. The prevalence reported by the Live Birth Information System was of 7.2% in 2010, about 38.0% lower than the estimated prevalence of 11.7% obtained with the correctional equation.

CONCLUSIONS

Information reported by the Live Birth Information System on preterm prevalence does not reflect the true magnitude of the problem in Brazil, and should not be used without the correction factors proposed in the present analyses.

Infant, Premature; Infant, Low Birth Weight; Prevalence; Birth Certificates; Review

Correspondence
: Mariangela Freitas da Silveira - Rua Marechal Deodoro, 1160 3° Piso Centro - 96020-220 Pelotas, RS, Brasil - E-mail: maris.sul@terra.com.br

This study was supported by the Brazilian Ministry of Health, General Coordination of Information and Epidemiological Analysis, Department of Health Surveillance (Contract no. BR/CNT/1200975.001, 2012) and by the Brazil Office of the United Nations Fund for Children (Contract no. 43127038, 2012).

The authors declare that there are no conflict of interests.

SCIMAGO INSTITUTIONS RANKINGS

Departamento Materno-Infantil . Faculdade de Medicina . Universidade Federal de Pelotas. Pelotas, RS, Brasil Universidade Federal de PelotasBrasilPelotas, RS, Brasil Departamento Materno-Infantil . Faculdade de Medicina . Universidade Federal de Pelotas. Pelotas, RS, Brasil

Programa de Pós-Graduação em Epidemiologia. Universidade Federal de Pelotas. Pelotas, RS, BrasilUniversidade Federal de PelotasBrasilPelotas, RS, Brasil Programa de Pós-Graduação em Epidemiologia. Universidade Federal de Pelotas. Pelotas, RS, Brasil

Departamento de Puericultura e Pediatria. Faculdade de Medicina de Ribeirão Preto. Universidade de São Paulo. São Paulo, SP, Brasil Universidade de São PauloBrasilSão Paulo, SP, Brasil Departamento de Puericultura e Pediatria. Faculdade de Medicina de Ribeirão Preto. Universidade de São Paulo. São Paulo, SP, Brasil

Departamento de Saúde Pública. Universidade Federal do Maranhão. São Luís, MA, BrasilUniversidade Federal do MaranhãoBrasilSão Luís, MA, Brasil Departamento de Saúde Pública. Universidade Federal do Maranhão. São Luís, MA, Brasil

Departamento de Nutrição. Faculdade de Saúde Pública . Universidade de São Paulo. São Paulo, SP, BrasilUniversidade de São PauloBrasilSão Paulo, SP, Brasil Departamento de Nutrição. Faculdade de Saúde Pública . Universidade de São Paulo. São Paulo, SP, Brasil

Programa de Pós-Graduação em Saúde Coletiva. Universidade Federal de Santa Catarina. Florianópolis, SC, BrasilUniversidade Federal de Santa CatarinaBrasilFlorianópolis, SC, Brasil Programa de Pós-Graduação em Saúde Coletiva. Universidade Federal de Santa Catarina. Florianópolis, SC, Brasil

Australian Research Centre for Population Oral Health. University of Adelaide. Adelaide, AustraliaUniversity of AdelaideAustraliaAdelaide, Australia Australian Research Centre for Population Oral Health. University of Adelaide. Adelaide, Australia

Universidade Federal de Sergipe. Aracaju, SE, BrasilUniversidade Federal de SergipeBrasilAracaju, SE, Brasil Universidade Federal de Sergipe. Aracaju, SE, Brasil

Departamento de Pediatria. Faculdade de Medicina. Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, BrasilUniversidade Federal do Rio de JaneiroBrasilRio de Janeiro, RJ, Brasil Departamento de Pediatria. Faculdade de Medicina. Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brasil

Departamento de Ginecologia e Obstetrícia. Faculdade de Medicina. Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brasil Universidade Federal do Rio de JaneiroBrasilRio de Janeiro, RJ, BrasilDepartamento de Ginecologia e Obstetrícia. Faculdade de Medicina. Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brasil

Escola Nacional de Saúde Pública. Fundação Oswaldo Cruz. Rio de Janeiro, RJ, BrasilFundação Oswaldo CruzBrasilRio de Janeiro, RJ, BrasilEscola Nacional de Saúde Pública. Fundação Oswaldo Cruz. Rio de Janeiro, RJ, Brasil

Escritório do Brasil. Fundo das Nações Unidas para a Infância. Brasília, DF, BrasilEscritório do Brasil. Fundo das Nações Unidas para a Infância. Brasília, DF, BrasilBrasilBrasília, DF, BrasilEscritório do Brasil. Fundo das Nações Unidas para a Infância. Brasília, DF, Brasil

Coordenação Geral de Informação e Análise Epidemiológica. Secretaria de Vigilância em Saúde. Ministério da Saúde do Brasil. Brasília, DF, BrasilMinistério da Saúde do BrasilBrasilBrasília, DF, BrasilCoordenação Geral de Informação e Análise Epidemiológica. Secretaria de Vigilância em Saúde. Ministério da Saúde do Brasil. Brasília, DF, Brasil

Programa de Pós-Graduação em Saúde e Comportamento. Universidade Católica de Pelotas. Pelotas, RS, BrasilUniversidade Católica de PelotasBrasilPelotas, RS, BrasilPrograma de Pós-Graduação em Saúde e Comportamento. Universidade Católica de Pelotas. Pelotas, RS, Brasil

Figures | Tables

Figures (4)
Tables (4)

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Figure 1
. Prevalence of preterm birth in males (A) and female (B) according to categories of birth weight (each dot represents the result of a study). Brazil, 1993-2011.

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Figure 2
Fractional polynomials and 95% confidence interval for the probability of preterm birth in male and female categories according to birth weight, obtained by weighted analysis of the 12 studies. Brazil, 1993-2011.

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Figure 3
. Prevalence of preterm births in males according to categories of birth weight, comparing the results of the current study with data from the Information System on Live Births (SINASC) in different years. Brazil, 2000, 2005, 2010, 2011.

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Figure 4
. Prevalence of preterm births in females according to categories of birth weight, comparing the results of the current study with data from the Information System on Live Births (SINASC) in different years. Brazil, 2000, 2005, 2010, 2011.

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Table
. Characteristics of the studies included in the analysis, 1990-2012.

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Annex 1
. Prevalence of preterm births by birth weight groups in Brazilian studies. Male. Brazil, 1993-2011.

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Annex 2
. Prevalence of preterm births by birth weight groups in Brazilian studies. Female. Brazil, 1993-2011.

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Annex 3.
Correction factors for the prevalence of preterm births by birth weight groups. Brazil, 1993-2011.

Figure 1 . Prevalence of preterm birth in males (A) and female (B) according to categories of birth weight (each dot represents the result of a study). Brazil, 1993-2011.

Figure 2 Fractional polynomials and 95% confidence interval for the probability of preterm birth in male and female categories according to birth weight, obtained by weighted analysis of the 12 studies. Brazil, 1993-2011.

Figure 3 . Prevalence of preterm births in males according to categories of birth weight, comparing the results of the current study with data from the Information System on Live Births (SINASC) in different years. Brazil, 2000, 2005, 2010, 2011.

Figure 4 . Prevalence of preterm births in females according to categories of birth weight, comparing the results of the current study with data from the Information System on Live Births (SINASC) in different years. Brazil, 2000, 2005, 2010, 2011.

Table . Characteristics of the studies included in the analysis, 1990-2012.

Author, year and place of publication	Description of the sample	Number of births	Method used to estimate gestational age^a	% preterm births	% low birth weight

Horta et al, ¹¹11 . Horta BL, Barros FC, Halpern R, Victora CG. Baixo peso ao nascer em duas coortes de base populacional no Sul do Brasil. Cad Saude Publica . 1996;12(Supl 1):S27-31. DOI:10.1590/S0102-311X1996000500005 https://doi.org/10.1590/S0102-311X199600... 1993, Pelotas, RS	Study of all births in all maternity hospitals in the city throughout the year	5,249	LMP	7.5	9.6
Bettiol et al, ⁷7 . Bettiol H, Rona RJ, Chinn S, Goldani M, Barbieri MA. Factors associated with preterm births in southeast Brazil: a comparison of two birth cohorts born 15 years apart. Paediatr Perinat Epidemiol . 2000;14(1):30-8. DOI:10.1046/j.1365-3016.2000.00222.x https://doi.org/10.1046/j.1365-3016.2000... 1994, Ribeirao Preto, SP	Study of all births in all maternity hospitals in the city for five months	2,846	LMP, regression model used to impute GA for unknown values	13.3	12.3
Silva et al, ²³23 . Silva AAM, Coimbra LC, Silva RA, Alves MTSSB, Lamy Filho F, Lamy ZC, et al. Perinatal health and mother-child health care in the municipality of São Luís, Maranhão State, Brazil. Cad Saude Publica . 2001;17(6):1413-23. DOI:10.1590/S0102-311X2001000600025 https://doi.org/10.1590/S0102-311X200100... 1997-1998, Sao Luís, MA	Study of a systematic sample of hospital births throughout the year	2,487	LMP, regression model used to impute GA for unknown values	13.9	9.6
Rondo et al, ²¹21 . Rondo PH, Ferreira RF, Nogueira F, Ribeiro MC, Lobert H, Artes R. Maternal psychological stress and distress as predictors of low birth weight, prematurity and intrauterine growth retardation. Eur J Clin Nutr . 2003;57(2):266-72. DOI:10.1038/sj.ejcn.1601526 https://doi.org/10.1038/sj.ejcn.1601526... 1997-2000, Jundiaí, SP	Study of newborns in a cohort of pregnant women attending antenatal care	865	LMP, US, Capurro	4.2	6.5
Lunardelli et al, ¹⁵15 . Lunardelli AN, Peres MA. Is there an association between periodontal disease, prematurity and low birth weight? A population-based study. J Clin Periodontol . 2005;32(9):938-46. DOI:10.1111/j.1600-051X.2005.00759.x https://doi.org/10.1111/j.1600-051X.2005... 2003, Itajaí, SC	Study of newborns from a group of women selected after exclusion criteria (age, disease, number of teeth) for five months in maternity hospitals	449	LMP	7.1	5.5
Barros et al, ³3 . Barros AJD, Santos IS, Victora CG, Albernaz EP, Domingues MR, Timm IK, et al. Coorte de nascimentos de Pelotas, 2004: metodologia e descrição. Rev Saude Publica . 2006;40(3):402-13. DOI:10.1590/S0034-89102006000300007 https://doi.org/10.1590/S0034-8910200600... 2004, Pelotas, RS	Study of all births in all maternity hospitals in the city throughout the year	4,231	LMP, US	15	10
Gurgel et al, ¹⁰10 . Gurgel RQ, Nery AMDG, Almeida MLD, Oliveira ERR, Lima DDF, Bettiol H, et al. Características das gestações, partos e recém-nascidos da região metropolitana de Aracaju, Sergipe, Brasil. Rev Bras Saude Mater Infant . 2009;9(2):167-77. DOI:10.1590/S1519-38292009000200006 https://doi.org/10.1590/S1519-3829200900... 2005, Aracaju, SE	Study of all births in all maternity hospitals in the city in four consecutive months	4,746	LMP, Capurro	7.7	7.2
Silva et al, ²⁴24 . Silva AAM, Silva LM, Barbieri MA, Bettiol H, Carvalho LM, Ribeiro VS, et al. The epidemiologic paradox of low birth weight in Brazil. Rev Saude Publica . 2010;44(5):767-75. DOI:10.1590/S0034-89102010005000033 https://doi.org/10.1590/S0034-8910201000... 2010, Sao Luís, MA	Study of a systematic sample of hospital births throughout the year	5,149	LMP, regression model used to impute GA for unknown values	12.9	8.6
Bettiol et al, ⁷7 . Bettiol H, Rona RJ, Chinn S, Goldani M, Barbieri MA. Factors associated with preterm births in southeast Brazil: a comparison of two birth cohorts born 15 years apart. Paediatr Perinat Epidemiol . 2000;14(1):30-8. DOI:10.1046/j.1365-3016.2000.00222.x https://doi.org/10.1046/j.1365-3016.2000... 2010, Ribeirao Preto, SP	Study of all births in all maternity hospitals in the city throughout the year	7,716	LMP regression model used to impute GA for unknown values	14.0	9.5
Ledo et al,^b2010, Rio de Janeiro, RJ	Study of births in maternity school for a year	2,716	LMP	11.3	10.0
Intergrowth, ²⁵25 . Silveira MF, Barros FC, Sclowitz IK, Domingues MR, Mota DM, Fonseca SS, et al. Implementation of the INTERGROWTH-21st Project in Brazil. BJOG : an international journal of obstetrics and gynaecology. 2013;120 Suppl 2:81-6. 2011-2012, Pelotas, RS	Study of all births in all maternity hospitals in the city over 15 months	6,109	LMP, US, physical examination	14.8	12.4
Leal et al, ¹⁴14 . Leal MC, Silva AAN, Dias MAB, Gama SGN, Rattner D, Moreira ME, Theme Filha MM, et al. Birth in Brazil: national survey into labour and birth. Reprod Health . 2012;9:15. DOI:10.1186/1742-4755-9-15 https://doi.org/10.1186/1742-4755-9-15... 2011-2012, Nascer no Brasil, Brazil	National study in 191 cities over 18 months	23,940	LMP	12.5	8.5

LMP: last menstruation period; US: ultrasound ; GA: gestational age

^aSeveral studies used more than one method of assessing gestational age, but the results discussed here are based primarily on the date of last menstruation, complementary methods being used when this information was not available or was inaccurate.

^bData not published.

Annex 1 . Prevalence of preterm births by birth weight groups in Brazilian studies. Male. Brazil, 1993-2011.

Lower limit (g)	Upper limit (g)	Sao Luís	Sao Luís	Jundiaí	Ribeirao Preto	Ribeirao Preto	Rio de Janeiro	Pelotas	Pelotas	Itajaí	Pelotas	Aracaju	Mean

		2010	1997	1997	2010	1994	2010	1993	2004	2003	2011	2005

0	499						1.00				1.00	1.00	1.00
500	599	1.00			1.00	1.00	1.00	1.00	1.00		1.00	1.00	1.00
600	699	1.00	1.00		1.00	1.00	1.00		1.00		1.00	1.00	1.00
700	799		1.00				1.00		1.00		1.00	1.00	1.00
800	899	1.00	1.00		1.00	1.00	1.00	1.00	1.00		1.00	1.00	1.00
900	999	1.00	1.00		1.00	1.00	1.00	1.00	1.00		1.00	1.00	1.00
1,000	1,099	0.80	1.00		1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	0.98
1,100	1,199	1.00	1.00	1.00	0.83	1.00	1.00	1.00	1.00		1.00	1.00	0.98
1,200	1,299	1.00	1.00		1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
1,300	1,399	0.50	1.00	1.00	1.00	0.86	1.00	1.00	1.00	1.00	1.00		0.94
1,400	1,499	0.86	1.00		0.86	1.00	1.00	0.67	1.00	1.00	1.00	1.00	0.94
1,500	1,599	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00		1.00		1.00
1,600	1,699				0.92	0.67	1.00	0.80	1.00		1.00	1.00	0.91
1,700	1,799	0.75	0.75		0.83	0.89	1.00	1.00	1.00		1.00	1.00	0.91
1,800	1,899	0.71	0.75	0.66	0.86	1.00	0.86	0.93	1.00	1.00	0.86	0.60	0.84
1,900	1,999	0.90	0.83	1.00	0.92	0.73	0.83	0.90	1.00		1.00	1.00	0.91
2,000	2,099	0.89	0.33		0.76	0.80	0.25	0.82	0.63		0.81	0.38	0.63
2,100	2,199	0.60	0.50	0.60	0.73	0.69	0.37	0.76	0.69	1.00	0.85	0.40	0.65
2,200	2,299	0.44	0.35	0.75	0.72	0.76	0.56	0.50	0.60	0.00	0.81	0.57	0.55
2,300	2,399	0.63	0.30	0.50	0.64	0.59	0.23	0.48	0.61	1.00	0.61	0.20	0.53
2,400	2,499	0.50	0.28	0.00	0.46	0.41	0.46	0.42	0.34	0.25	0.52	0.32	0.36
2,500	2,599	0.33	0.31	0.25	0.45	0.28	0.41	0.26	0.37	0.00	0.39	0.22	0.30
2,600	2,699	0.19	0.13	0.13	0.30	0.37	0.33	0.19	0.28	0.17	0.34	0.21	0.24
2,700	2,799	0.15	0.20	0.06	0.23	0.09	0.19	0.13	0.22	0.00	0.21	0.05	0.14
2,800	2,899	0.19	0.06	0.11	0.18	0.06	0.12	0.10	0.13	0.08	0.15	0.12	0.12
2,900	2,999	0.14	0.17	0.00	0.09	0.05	0.04	0.09	0.18	0.19	0.09	0.03	0.10
3,000	3,099	0.07	0.10	0.03	0.08	0.11	0.08	0.12	0.13	0.00	0.04	0.04	0.07
3,100	3,199	0.07	0.09	0.03	0.06	0.06	0.06	0.05	0.08	0.00	0.02	0.05	0.05
3,200	3,299	0.10	0.10	0.00	0.05	0.10	0.03	0.07	0.11	0.05	0.03	0.05	0.06
3,300	3,399	0.06	0.07	0.00	0.06	0.04	0.01	0.06	0.07	0.00	0.01	0.04	0.04
3,400	3,499	0.09	0.05	0.00	0.06	0.05	0.04	0.02	0.03	0.07	0.00	0.04	0.04
3,500	3,599	0.06	0.16	0.00	0.02	0.00	0.00	0.02	0.01	0.00	0.00	0.02	0.03
3,600	3,699	0.03	0.03	0.00	0.06	0.08	0.01	0.02	0.01	0.00	0.01	0.04	0.03
3,700	3,799	0.04	0.02	0.00	0.01	0.03	0.06	0.00	0.01	0.00	0.00	0.05	0.02
3,800	3,899	0.05	0.08	0.00	0.03	0.00	0.02	0.00	0.00	0.00	0.00	0.00	0.02
3,900	3,999	0.00	0.00	0.00	0.01	0.00	0.00	0.00	0.03	0.00	0.01	0.00	0.00
4,000+		0.01	0.00	0.00	0.00	0.00	0.01	0.02	0.00	0.00	0.01	0.02	0.01

Blank cells indicate no data.

Annex 2 . Prevalence of preterm births by birth weight groups in Brazilian studies. Female. Brazil, 1993-2011.

Lower limit (g)	Upper limit (g)	Sao Luís	Sao Luís	Jundiaí	Ribeirao Preto	Ribeirao Preto	Rio de Janeiro	Pelotas	Pelotas	Itajaí	Pelotas	Aracaju	Mean

		2010	1997	1997	2010	1994	2010	1993	2004	2003	2011	2005

0	499	1.00					1.00		1.00		1.00	1.00	1.00
500	599	1.00			1.00				1.00		1.00		1.00
600	699	1.00	1.00		1.00	1.00	1.00		1.00		1.00	1.00	1.00
700	799	1.00			1.00	1.00	1.00	1.00	1.00		1.00	1.00	1.00
800	899	1.00	1.00		1.00		100	1.00	1.00		1.00		1.00
900	999	1.00	1.00		1.00	1.00			1.00		1.00	1.00	1.00
1,000	1,099	1.00	1.00		1.00	1.00	1.00	1.00			1.00	1.00	1.00
1,100	1,199	0.75	1.00		1.00	0.80		1.00	1.00		1.00	1.00	0.94
1,200	1,299	1.00	1.00		0.92	1.00	1.00	1.00	1.00	1.00	1.00	0.67	0.87
1,300	1,399	1.00	1.00		0.89	0.80	1.00	1.00	1.00		1.00	1.00	0.97
1,400	1,499	1.00	1.00	1.00	0.92	1.00	100	1.00	1.00	1.00	1.00	1.00	0.99
1,500	1,599	1.00	1.00	0.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	0.91
1,600	1,699	0.83			0.93	1.00	0.67	1.00	1.00		0.92		0.91
1,700	1,799	0.90	1.00	1.00	1.00	0.86	1.00	1.00	1.00		0.88	0.67	0.93
1,800	1,899	0.82	0.75		0.79	0.50	0.67	0.82	0.93	1.00	0.88	1.00	0.82
1,900	1,999	1.00	0.80	0.50	0.90	0.77	1.00	0.94	1.00		0.91	0.00	0.78
2,000	2,099	0.58	0.77	0.66	0.78	0.46	0.75	0.81	0.88	0.00	0.87	0.43	0.63
2,100	2,199	0.62	0.45	0.00	0.86	0.61	0.83	0.43	0.67	0.00	0.82	0.46	0.52
2,200	2,299	0.44	0.36	0.50	0.45	0.38	0..44	0.57	0.53	0.00	0.48	0.35	0.41
2,300	2,399	0.51	0.15	000	0.51	0.29	0.41	0.41	0.38	0.50	0.48	0.36	0.36
2,400	2,499	0.39	0.36	0.00	0.42	0.31	0.26	0.33	0.42	1.00	0.45	0.19	0.38
2,500	2,599	0.17	0.19	0.10	0.25	0.20	0.17	0.19	0.28	0.00	0.39	0.16	0.19
2,600	2,699	0.16	0.21	0.12	0.18	0.14	0.20	0.23	0.19	0.22	0.24	0.16	0.18
2,700	2,799	0.10	0.16	0.00	0.12	0.09	0.14	0.10	0.21	0.20	0.21	0.03	0.12
2,800	2,899	0.07	0.16	0.03	0.13	0.09	0.09	0.07	0.17	0.00	0.15	0.04	0.09
2,900	2,999	0.10	0.10	0.00	0.07	0.09	0.08	0.07	0.15	0.08	0.06	0.04	0.07
3,000	3,099	0.12	0.10	0.00	0.08	0.07	0.07	0.08	0.07	0.00	0.02	0.02	0.06
3,100	3,199	0.05	0.11	0.00	0.06	0.10	0.02	0.07	0.07	0.00	0.03	0.04	0.05
3,200	3,299	0.10	0.07	0.00	0.08	0.06	0.00	0.04	0.03	0.00	0.01	0.06	0.04
3,300	3,399	0.04	0.10	0.02	0.06	0.03	0.05	0.03	0.05	0.00	0.00	0.03	0.04
3,400	3,499	0.07	0.08	0.00	0.04	0.05	0.01	0.01	0.06	0.00	0.01	0.03	0.03
3,500	3,599	0.04	0.10	0.00	0.01	0.04	0.00	0.02	0.02	0.13	0.00	0.03	0.03
3,600	3,699	0.03	0.05	0.00	0.05	0.05	0.00	0.03	0.04	0.00	0.01	0.01	0.02
3,700	3,799	0.00	0.03	0.00	0.04	0.02	0.05	0.01	0.03	0.22	0.00	0.03	0.04
3,800	3,899	0.03	0.04	0.00	0.02	0.00	0.00	0.02	0.00	0.00	0.00	0.04	0.01
3,900	3,999	0.00	0.00	0.00	0.08	0.00	0.00	0.00	0.00	0.00	0.02	0.03	0.01
4,000+		0.01	0.00	0.00	0.03	0.00	0.00	0.01	0.00	0.00	0.00	0.04	0.01

Blank cells indicate no data.

Annex 3. Correction factors for the prevalence of preterm births by birth weight groups. Brazil, 1993-2011.

Birth weight group (g)		Male		Female

		Prevalence (%)	95%CI	Prevalence (%)	95%CI

0	499	99.8	99.6;99.9	99.7	99.5;99.9
500	599	99.7	99.4;99.8	99.6	99.3;99.8
600	699	99.6	99.3;99.8	99.5	99.1;99.7
700	799	99.5	99.1;99.8	99.4	99.0;99.6
800	899	99.4	98.9;99.7	99.2	98.7;99.5
900	999	99.3	98.7;99.6	99.0	98.4;99.4
1,000	1,099	99.0	98.3;99.4	98.7	97.9;99.2
1,100	1,199	98.7	97.8;99.2	98.2	97.3;98.9
1,200	1,299	98.3	97.2;98.9	97.6	96.5;98.4
1,300	1,399	97.6	96.3;98.5	96.7	95.3;97.7
1,400	1,499	96.7	95.1;97.8	95.5	93.7;96.8
1,500	1,599	95.4	93.4;96.9	93.7	91.5;95.3
1,600	1,699	93.6	91.2;95.4	91.2	88.5;93.3
1,700	1,799	91.1	88.2;93.3	87.7	84.6;90.3
1,800	1,899	87.6	84.3;90.3	83.2	79.5;86.2
1,900	1,999	83.0	79.2;86.2	77.2	73.2;80.7
2,000	2,099	77.0	73.0;80.5	69.9	65.7;73.7
2,100	2,199	69.7	65.6;73.4	61.4	57.3;65.3
2,200	2,299	61.2	57.3;64.9	52.2	48.4;55.9
2,300	2,399	52.0	48.4;55.6	42.9	39.5;46.3
2,400	2,499	42.8	39.5;46.1	34.2	31.3;37.2
2,500	2,599	34.1	31.2;37.2	26.5	24.1;29.2
2,600	2,699	26.5	23.9;29.4	20.3	18.2;22.5
2,700	2,799	20.3	17.9;22.9	15.3	13.5;17.2
2,800	2,899	15.3	13.3;17.6	11.5	10.0;13.1
2,900	2,999	11.5	9.8;13.5	8.6	7.4;10.0
3,000	3,099	8.7	7.2;10.4	6.5	5.5;7.7
3,100	3,199	6.6	5.4;8.0	5.0	4.2;6.0
3,200	3,299	5.0	4.1;6.2	3.9	3.2;4.7
3,300	3,399	3.9	3.1;4.9	3.1	2.5;3.8
3,400	3,499	3.1	2.5;3.9	2.5	2.0;3.1
3,500	3,599	2.5	2.0;3.1	2.1	1.6;2.6
3,600	3,699	2.0	1.6;2.6	1.7	1.4;2.2
3,700	3,799	1.7	1.4;2.2	1.5	1.2;2.0
3,800	3,899	1.5	1.2;1.9	1.4	1.0;1.8
3,900	3,999	1.3	1.1;1.6	1.3	0.9;1.7
4,000	5,000	1.2	1.0;1.5	1.6	0.9;2.6

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Prevalence of preterm birth according to birth weight group: a systematic review

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[1] Correspondence
: Mariangela Freitas da Silveira - Rua Marechal Deodoro, 1160 3° Piso Centro - 96020-220 Pelotas, RS, Brasil - E-mail: maris.sul@terra.com.br