Preterm birth characteristics and outcomes in Portugal, between 2010 and 2018: a cross‐sectional sequential study

Received: 19 July 2022 | Revised: 23 November 2022 | Accepted: 29 December 2022 DOI: 10.1002/hsr2.1054 ORIGINAL RESEARCH Preterm birth characteristics and outcomes in Portugal, between 2010 and 2018—A cross‐sectional sequential study Cecília Elias 1,2 |Paulo Jorge Nogueira 2,3,4,5,6 |Paulo Sousa 3 1 Unidade de Saúde Publica Francisco George, ACES Lisboa Norte, ARSLVT, Lisboa, Portugal 2 EPI Task‐Force FMUL, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal 3 NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, CHRC, NOVA University Lisbon, Lisbon, Portugal 4 Instituto de Medicina Preventiva e Saúde Pública, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal 5 Área Disciplinar Autónoma de Bioestatística (Laboratório de Biomatemática), Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal 6 Instituto de Saúde Ambiental, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal Correspondence Cecília Elias, Unidade de Saúde Publica Francisco George, ACES Lisboa Norte, ARSLVT, Lisboa, Portugal. Email: [email protected] Funding information The present publication was funded by Fundação Ciência e Tecnologia, IP national support through CHRC, Grant/Award Number: UIDP/04923/2020 Abstract Introduction: According to the World Health Organization, 11% of all children are born prematurely, representing 15 million births annually. An extensive analysis on preterm birth, from extreme to late prematurity and associated deaths, has not been published. The authors characterize premature births in Portugal, between 2010 and 2018, according to gestational age, geographic distribution, month, multiple gestations, comorbidities, and outcomes. Methods: A sequential, cross‐sectional, observational epidemiologic study was conducted, and data were collected from the Hospital Morbidity Database, an anonymous administrative database containing information on all hospitalizations in National Health Service hospitals in Portugal, and coded according to the ICD‐9‐CM (International Classification of Diseases), until 2016, and ICD‐10 subsequently. Data from the National Institute of Statistics was utilized to compare the Portuguese population. Data were analyzed using R software. Results: In this 9‐year study, 51.316 births were preterm, representing an overall prematurity rate of 7.7%. Under 29 weeks, birth rates varied between 5.5% and 7.6%, while births between 33 and 36 weeks varied between 76.9% and 81.0%. Urban districts presented the highest preterm rates. Multiple births were 8× more likely preterm and accounted for 37%–42% of all preterm births. Preterm birth rates slightly increased in February, July, August, and October. Overall, respiratory distress syndrome (RDS), sepsis, and intraventricular hemorrhage were the most common morbidities. Preterm mortality rates varied significantly with gestational age. Conclusion: In Portugal, 1 in 13 babies was born prematurely. Prematurity wasmorecommoninpredominantlyurban districts, a surprise finding that warrants further studies. Seasonal preterm variation rates also require further analysis and modelling to factor in heat waves and low temperatures. A decrease in the case rate of RDS and sepsis was observed. Compared with previously published results, preterm mortality per gestational age decreased; however, further improvements are attainable in comparison with other countries. Health Sci. Rep. 2023;6:e1054. wileyonlinelibrary.com/journal/hsr2 | 1of13 https://doi.org/10.1002/hsr2.1054 This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. © 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC. KEYWORDS gestational age, morbidities, mortality, multiple, prematurity, urban–rural 1|INTRODUCTION According to theWorld Health Organization (WHO), an estimated 11% of all children are born prematurely, representing 15 million births annually. 1 Prematurity is the most important cause of hospitalization in newborn children, the leading cause of death during the neonatal period, and the second cause of death in children under 5. 2 Prematurity causes are multifactorial. Prematurity can be associated with spontaneous labor at an early gestational age resulting from several factors such as maternal characteristics, lifestyle, uterine anatomy and infection, 3 or can be caused by iatrogenic labor when, in specific clinical circumstances, a decision is taken to deliver a newborn at an early gestational age. 4 Multiple pregnancies are also an important risk factor for prematurity. 5,6 A seasonality pattern in preterm birth has also been reported, with preterm birth peaks occurring in the Summer or Winter months. 7 Other morbidity and mortality outcomes vary significantly with prematurity; in particular, extreme prematurity survival is significantly connected to gestational age. 8 In Portugal, in 2016, according to the National Institute of Statistics (INE), 6.801 premature births occurred, corresponding to 7.8% of all births. 9 According to Organisation for Economic Co‐operation and Development (OECD), Portugal has the fifth highest proportion of children born with low weight, 8.9%, significantly superior to the OECD average of 6.5% in 2015. 10 A National Very Low Birth Weight Registration (RNMBP) was implemented in Portugal in 1994. 11 This database includes the prenatal, perinatal, and postnatal data associated with the premature birth of extremely and very low birth weight (VLBW) children in Portugal. According to the RNMBP data, between 2005 and 2012, there were no survivors from births at 22 weeks of gestational age, and an inverse relationship between gestational age and death: 87%, 70%, 43%, and 30% at 23, 24, 25, and 26 weeks, respectively, making gestational age the most important risk factor for death. A sustained reduction in preterm deaths was reported between 1996 and 2012, particularly a decrease from 27% to 15% in preterm deaths with a birth weight under 1500 g. 12 Prematurity is considered a major cause of mortality and morbidity, and survivors are at increased risk of cognitive delay, cerebral palsy, ophthalmologic and auditory disease, and overall decreased health. 13 To the authors' knowledge, an extensive analysis on preterm birth characteristics, from extreme to late prematurity and associated deaths, has not been published. In this study, the authors characterize premature births in Portugal, between 2010 and 2018, according to gestational age, birth weight, multiple gestations, comorbidities, and outcomes. 2|METHODS 2.1 |Design study To analyze premature births, the authors conducted a sequential, cross‐sectional, observational epidemiologic study. 2.2 |Data Data were collected from the BDMH (Hospital Morbidity Database), an anonymous administrative database containing demographic information, diagnosis, and procedures of all the hospitalizations in Portugal, and coded according to the ICD‐9‐CM (International Classification of Diseases) until 2016 and ICD‐10 subsequently. Data from the National Institute of Statistics was utilized to compare the Portuguese population. Data were statistically analyzed using R software (R Core Team, 2018). Descriptive statistics were performed and statistical analysis using one‐sample χ 2 test, Pearson's correlation, Fisher–Freeman–Halton exact test, and linear‐by‐linear association tests were utilized. Linear regression was algo performed to compare quantitative variables. Statistical significance was considered when p< 0.05. 2.3 |Outcomes All the children born at National Health Service (NHS) hospitals, in Portugal, between 2010 and 2018 were included in our study, and premature births were analyzed subsequently. Prematurity was defined as birth before 37 weeks (36 +6 weeks of gestation), extreme preterm as birth before 28 weeks (27 +6 ), adapted extreme prematurity as birth before 29 weeks (28 +6 weeks of gestation), late prematurity as birth between 34 weeks and 36 +6 , and adapted late prematurity as birth between 33 and 36 +6 weeks. The adapted extreme preterm groups were created due to gestational age aggregation in ICD‐9‐CM, meaning preterm data on gestational age was combined in 25–26, 27–28, 29–30, 31–32, 33–34, and 35–36 weeks from 2010 to 2016. Birth weight was analyzed from a variable that presents birth weight in gram, so these were not derived from ICD coding. Low birth weight was defined as <2500 g and very low birth weight as <1500 g. Comorbidities such as necrotizing enteritis (NEC) (77751, 77752, 77753, 7775, P771, P772, P773, P779), respiratory distress syndrome (RDS) (769, P220), sepsis (77181, P360, P361, P362, P363, P364, P365, P368, P369) intraventricular hemorrhage (IVH) (77211, 77212, 77213, 77214, P520, P521, P5221, P5222, P523, P524, P525, P526, P528, P529), and retinopathy of prematurity (ROP) (H351, H3510, H3511, H3512, H3513, H3514, 2of13 | ELIAS ET AL. 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License H3515, H3516, H3517) were defined according to ICD‐9andICD‐10. Due to coding limitations outcomes such as late sepsis or specific ROP stages were not possible to obtain. Deaths were analyzed according to the variable DSP (destination after hospital discharge), with Code 20 (death) referring exclusively to the event of death during the inpatient stay associated with birth. Preterm infants not coded for a specific gestational age were excluded from analysis requiring this information. 2.4 |Ethics The study utilized an anonymous secondary database; therefore, no ethical approval was required. 3|RESULTS 3.1 |Prematurity Between 2010 and 2018, there were 668,171 births at SNS hospitals in Portugal. Of these, 51,316 were preterm, representing an overall prematurity rate of 7.7%, and annual prematurity rates varying from 7.3% to 8.0%. A nonhomogeneous pattern across years was observed but no clear trend emerged in total preterm analysis and according to sex (Table 1and Figure 1). A decrease in the absolute number of preterm births was observed and was partnered with an overall birth decrease, maintaining the preterm birth rates at similar levels. Low weight was observed in 61,608 births, yielding a yearly low birth rate varying from 8.9% to 9.5%, values consistently higher than preterm birth rates. A very low birth was observed in 8750 births, corresponding to 1.3% of all births. A total of 3,305 births occurred before 29 weeks (7.6% of preterm births), and compared among years; these remained stable throughout the study. A total of 38,930 births occurred between weeks 33 and 36 +6 , corresponding to 89.4% of the preterm births presenting an increasing trend from 76.9% in 2010 to 81.0% of all preterm births. 3.2 |Sex Prematurity was consistently more frequent in the male sex in all years, corresponding to 52% of preterm birth (Table 2). 3.3 |Gestational age Globally, preterm births varied yearly from 7.3% to 8.0% of all births. In 2017, extremely preterm birth was 4.0% preterm births and late TABLE 1 Total births, preterm births, low birth weight births, and very low birth weight births, in absolute and relative value (per 100 births), by year, between 2010 and 2018 at SNS hospitals in Portugal. Year 2010 2011 2012 2013 2014 2015 2016 2017 2018 Total pValue Births n84,480 87,023 75,170 68,379 66,310 69,167 73,717 73,356 70,569 668,171 <0.001 a 0.068 b Preterm births n6301 6352 5877 5384 5120 5515 5825 5681 5261 51316 <0.001 a % 7.5 7.3 7.8 7.9 7.7 8.0 7.9 7.7 7.5 7.7 0.716 b Male (n,%) n3228 3350 3073 2732 2777 2834 3060 3001 2803 26,858 0.007 c % 51 53 52 51 54 51 53 53 53 52 0.061 d Low birth weight n7514 8121 6837 6326 6110 6547 6707 6929 6517 61,608 0.002 c % 8.9 9.3 9.1 9.3 9.2 9.5 9.1 9.4 9.2 9.2 0.019 d Very low birth weight n1068 1419 1002 830 806 880 946 949 850 8750 <0.001 c % 1.3 1.6 1.3 1.2 1.2 1.3 1.3 1.3 1.2 1.3 <0.001 d a One‐sample χ 2 test. b Pearson's correlation. c Fisher–Freeman–Halton exact test. d Linear‐by‐linear association test. ELIAS ET AL. | 3of13 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 2010 2011 2012 2013 2014 2015 2016 2017 2018 Preterm and Low Weight Births Preterm Births Low Birth Weight 0 1000 2000 3000 4000 5000 6000 7000 2010 2011 2012 2013 2014 2015 2016 2017 2018 Extreme, Late and All Preterm Births Extreme Preterm Late Preterm All Preterm FIGURE 1 (Left) Preterm and low weight births per year and (right) extreme, late, and total preterm births per year, between 2010 and 2018, at SNS hospitals in Portugal. TABLE 2 Preterm births by gestational week in relative and absolute terms, total births with known gestational week per year between 2010 and 2018, and extreme and late preterm birth between 2017 and 2018, in Portugal. Gestational age in weeks Total2010 2011 2012 2013 2014 2015 2016 2017 2018 <23 22 <24 15 27 27 27 23 16 18 0.0 0.0 176 0.2 0.4 0.5 0.5 0.4 0.3 0.3 10 9 23 0.2 0.2 24 24 48 46 43 33 27 39 49 43 34 362 0.8 0.7 0.7 0.6 0.5 0.7 0.8 0.8 0.6 25 41 43 25–26 121 122 127 93 118 102 112 0.7 0.8 982 26 1.92 1.92 2.16 1.73 2.30 1.85 1.92 57 46 1.0 0.9 27 74 73 27–28 200 234 175 165 141 160 173 1.3 1.4 1590 28 3.2 3.7 3.0 3.1 2.8 2.9 3.0 103 92 1.8 1.7 29 145 94 29–30 357 332 312 253 259 303 272 2.6 1.8 2664 30 5.7 5.2 5.3 4.7 5.1 5.5 4.7 195 142 3.4 2.7 31 217 214 31–32 637 633 551 493 520 515 549 3.8 4.1 4957 32 10.1 10.0 9.4 9.2 10.2 9.3 9.4 313 315 5.5 6.0 4of13 | ELIAS ET AL. 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License preterm births 70.2%. Unsurprisingly, there was an increase in the absolute and relative birth rates with increasing gestational age. In 2018, for example, 0.2% (n= 11) of preterm births were infants with less than 24 weeks, and 56.5% (n= 2970) were between 35 and 36 weeks. For most of the years, a small proportion of the preterm births were not coded for a specific gestational age and were excluded from analysis requiring this information. 3.4 |District distribution In absolute value, preterm births occurred mainly in large urban districts such as Lisbon (n= 12,859, 27.0%), Porto (n= 9580, 20.1%), and Setubal (n= 4803, 10.1%) and the lowest counts were observed in rural districts such as Portalegre, Guarda e Bragança. Considering preterm births from total births, large urban centers maintained an increased rate than the national average (7.7%)—in the Porto district, 8.6%, and in the Lisbon district, 8.2%, of births were preterm. The lowest preterm birth rates, under 5.5%, were observed in mainly rural districts such as Portalegre and Beja. Castelo Branco, an interior and mainly rural district, also reported preterm birth rates of 8.3%. 3.5 |Monthly preterm births Overall, preterm births were slightly more frequent in February, July, August, and October, corresponding to 7.9%–8.0% of all preterm births. In contrast, extreme preterm birth rates were more common in July at 9.4% and August at 9.7%. 3.6 |Multiple births A total of 19,975 were multiple births, corresponding to 3.0% of all births and between 2.8% and 3.4% of births per year. Between 97.0% and 99.1% were twins, and the remaining triplets or more. Preterm multiples corresponded to 1.8%–2.2% of all births yearly and importantly corresponded to 35.3%– 42.2% of all preterm births. In addition to this, 61.2%–68.4% of multiple pregnancies were associated with premature birth. In 2017, 2.0% of multiples were born preterm and 39.7% were late preterm. Under 29 weeks, preterm multiple births rates appear to present a slight increase over the 9‐year analysis (Table 3and Figure 2). TABLE 2 (Continued) Gestational age in weeks Total2010 2011 2012 2013 2014 2015 2016 2017 2018 33 488 456 33–34 1348 1316 1273 1167 1135 1228 1283 8.6 8.7 11,235 34 21.4 20.7 21.7 21.7 22.2 22.3 22.0 786 755 13.8 14.4 35 1181 1121 35–36 3233 3380 3077 2923 2741 2980 3195 20.8 21.3 27,695 36 51.3 53.2 52.4 54.3 53.5 54.0 54.8 2006 1858 35.3 35.3 Total 5959 6090 5585 5154 4964 5343 5651 5661 5254 43,702 Preterm under 29 weeks (n,%) 384 429 372 318 309 317 352 433 391 3305 6.4 7.0 6.7 6.2 6.2 5.9 6.2 7.6 7.4 7.6 Extreme preterm (n,%) 227 207 4.0 3.9 33–36 weeks preterm (n,%) 4581 4696 4350 4090 3876 4208 4478 4461 4190 38,930 76.9 77.1 77.9 79.4 78.1 78.8 79.2 78.8 79.7 89.1 Late preterm (n,%) 3973 3734 70.2 71.1 Total preterm 6301 6352 5877 5384 5120 5515 5825 5681 5261 51,316 Unknown gestational week (n,%) 342 262 292 230 156 172 174 20 7 7614 5.4 4.1 5.0 4.3 3.0 3.1 3.0 0.4 0.1 14.8 ELIAS ET AL. | 5of13 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE 3 Multiple births and preterm multiple births per year and proportion for all births between 2010 and 2018, in Portugal. Year Multiple births Twin births (n,%) Triplets or more (n,%) Preterm multiple births (n,%) Proportion of preterm multiples from all preterm (%) Proportion of preterm multiples from all multiples (%) Altered extreme preterm multiples births (n,%) Extreme preterm multiples births (n,%) Altered late preterm multiples birth (n,%) Late preterm multiples birth (n,%) 2010 2378 (2.8) 2344 (98.6) 34 (1.4) 1543 (1.8) 37.7 64.9 90 (3.8) 1072 (45.1) 2011 2450 (2.8) 2394 (97.7) 56 (2.3) 1630 (1.9) 38.6 66.5 104 (4.2) 1216 (49.6) 2012 2201 (2.9) 2182 (99.1) 19 (0.9) 1506 (2.0) 37.5 68.4 101 (4.6) 1077 (48.9) 2013 2006 (2.9) 1980 (98.7) 26 (1.3) 1330 (1.9) 37.3 66.3 92 (4.6) 959 (47.8) 2014 1996 (3.0) 1963 (98.3) 33 (1.7) 1321 (2.0) 39.0 66.2 105 (5.3) 939 (47.0) 2015 2326 (3.4) 2294 (98.6) 32 (1.4) 1541 (2.2) 42.2 66.3 78 (3.4) 1148 (49.4) 2016 2054 (2.8) 2003 (97.5) 51 (2.5) 1331 (1.8) 35.3 64.8 89 (4.3) 978 (47.6) 2017 2384 (3.2) 2335 (97.9) 49 (2.1) 1459 (2.0) 42.0 61.2 84 (5.8) 53 (2.3) 1089 (45.7) 947 (39.7) 2018 2180 (3.1) 2115 (97.0) 65 (3.0) 1378 (2.0) 41.4 63.2 85 (6.2) 68 (3.1) 979 (44.9) 856 (39.3) Total 19,975 19,610 365 13,039 828 9457 6of13 | ELIAS ET AL. 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 3.7 |Birth weight Between 2010 and 2018, mean preterm birth weights remained stable between 2126.8. and 2155.5 g. Extreme preterm birth weights varied between 885.8 and 948.6 g. Under 1000 g births preterm births varied between 5.1% and 6.4%, and approximately 30% of extremely preterm births had a birthweight under 1000 g (Table 4). 3.8 |Preterm complications and ventilation requirements Between 2010 and 2018, NEC cases varied between 24 (6.1%) and 44 (10.3%), RDS varied between 216 (55.2%) and 318 (74.1%), sepsis between 119 (30.4%) and 200 (46.6%), IVH between 88 (22.9%) and 141 (40.1%), Grade 3 and 4 IVH between 34 (8.7%) and 45 (12.6%), and ROP between 55 (14.1%) and 87 (20.3%). Regarding ventilation requirements, noninvasive ventilation was utilized between 165 (42.2%) and 221 (51.5%) and invasive ventilation between 170 (43.5%) and 265 (71.2%) (Table 5and Figure 3). 3.9 |Preterm deaths Overall, 976 deaths were reported in our study, a rate of 1.9% from all preterm births. Preterm deaths varied significantly according to gestational age. During the birth hospital episode, preterm deaths: at 24 weeks ranged from 48.5% (2015) to 75% (2016); between 27 and 0 500 1000 1500 2000 2500 3000 2010 2011 2012 2013 2014 2015 2016 2017 2018 Total and Preterm Mulple Births Mulples Births Preterm Mulple Births FIGURE 2 Total and preterm multiple births per year between 2010 and 2018 at SNS hospitals in Portugal. TABLE 4 Mean birth weight and standard deviation for preterm (in g), under 29 weeks preterm, and 33–36 weeks preterm babies, between 2010 and 2018, in Portugal. Year Birth weight <1000 g Preterm Under 29 weeks preterm Preterm 33–36 weeks Preterm Under 29 weeks preterm µSD µSD µSD n%n% 2010 2152.7 622.8 932.5 414.8 2364.1 455.8 322 5.1 127 2.0 2011 2134.0 650.1 948.6 452.7 2345.0 483.1 405 6.4 138 2.2 2012 2151.1 624.6 917.3 420.9 2365.6 453.9 348 5.9 112 1.9 2013 2151.6 606.6 918.1 386.5 2352.9 437.4 293 5.4 108 2.0 2014 2126.8 612.8 922.7 401.3 2338.7 451.6 271 5.3 101 2.0 2015 2130.5 605.9 930.3 406.2 2333.0 444.6 275 5.0 108 2.0 2016 2141.7 620.1 922.4 390.1 2350.5 467.0 329 5.6 106 1.8 2017 2151.9 627.9 874.8 283.2 2369.7 467.1 307 5.4 98 1.7 2018 2155.5 621.3 885.8 295.6 2365.4 464.3 269 5.1 98 1.9 Total 2144.0 621.3 916.9 383.5 2353.9 458.3 2819 996 ELIAS ET AL. | 7of13 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 28 weeks decreased to 10.5% (2010) and 14% (2018); and between 35 and 36 weeks, ranged from 0.1% to 0.2%. Between weeks 29 and 36, death rates decreased from 4.6% to 0.2%. In the yearly death analysis, a decreasing trend was observed in deaths of 31–32 and 33–34 weekers and no particular trend was evident for other gestational ages or overall trend. The mode day of death for total and extreme preterm was consistently Day 0 of life, whereas in late preterm, the same pattern was observed, but from 2015 onward, the mode varies between Days 2 and 6. A wide variation of the mean, median, and SD was observed for total, extreme, and late preterms (Tables 6and 7). 4|DISCUSSION Over the 9 years analyzed, at NHS hospitals in Portugal, 7.7% (n= 51.316) of all births were preterm, or 1 in 13 babies was born preterm, highlighting the magnitude of prematurity as a present‐day public health issue. These values are in line with other national results 14 and international studies. 1 Preterm birth rates were stable throughout our study; a decrease in overall births was associated with a decrease in preterm births rendering a preterm rate between 7.3% and 8.0%. Unsurprisingly, as reported in the literature, preterm births were more common in males. 15 Overall, preterm births under 29 weeks occurred in 0.48% of births and 6.1% of all preterm births. In 2017, our study reports an extreme preterm rate of 0.31% of all births and 4.0% of preterm births. International estimates show higher values than ours; extreme preterm births constitute around 0.42% of all births 16 and 0.55% of all births in the United Kingdom, in 2019. 17 In France, extreme preterm births constituted 5% of all preterm birth, 18 a higher value than the one we report. In 2017, preterm births between 34 and 36 completed weeks were 5.4% of all births and 69.9% of all preterm births. A multicentre Portuguese study on late preterm prevalence showed 5.4% of late singleton births between 34 and 36 weeks, which is in line with our national results. 19 Prematurity was more frequent in high‐density urban districts like Lisbon and Porto and some rural districts such as Castelo Branco and Bragança. The lowest prematurity rates were observed in rural districts like Beja and Portalegre. The authors expected urban districts to be associated with lower prematurity rates as studies have mainly shown an urban maternal residence associated with a longer gestation. 20,21 However, our results show the opposite. This finding is supported by Statistics Portugal (INE) data, where preterm births in Alentejo, a mainly rural region, are consistently inferior to the Lisbon Metropolitan region. A similar description has also been reported in Pennsylvania (USA), where rural preterm rates were lower than urban ones. 22 However, prematurity is multifactorial, and several risk factors may play a role as socioeconomic factors, maternal educational level, ethnicity, or access to health services, which our study did not analyze. 21 Other hypotheses to explain this asymmetry may be associated with other urban pregnancy vulnerabilities, cesarean section rates, or twinning rates in Portuguese urban centers. However, this detailed analysis is beyond the scope of this article, and future studies are required to ascertain the predominant factors associated with this result. Our analysis shows preterm births were more frequent during the Summer months, July and August, typically two extremely hot months in all of Portugal, and the winter month of February. Several countries have reported seasonality preterm rates with preterm peaks during Summer and or Winter months. 23,24 Greece, with a similar Mediterranean climate as Portugal, has reported these two TABLE 5 Preterm comorbidities (NEC, RDS, sepsis; IVH, ROP) and ventilation requirements per year between 2010 and 2018 at SNS hospitals in Portugal. 2010 2011 2012 2013 2014 2015 2016 2017 2018 Total pValue NEC 43 (11.2) 44 (10.3) 33 (8.9) 32 (10.1) 25 (8.1) 30 (9.5) 31 (8.8) 30 (6.9) 24 (6.1) 292 (8.8) <0.05 RDS 277 (72.1) 318 (74.1) 281 (75.5) 267 (84.0) 250 (80.9) 256 (80.8) 278 (79.0) 278 (64.2) 216 (55.2) 2421 (73.3) 0.07 Sepsis 168 (43.8) 200 (46.6) 169 (45.4) 163 (51.3) 146 (47.2) 149 (47.0) 157 (44.6) 159 (36.7) 119 (30.4) 1430 (43.3) <0.05 IVH 88 (22.9) 115 (26.8) 98 (26.3) 92 (28.9) 92 (29.8) 102 (32.2) 141 (40.1) 116 (26.8) 100 (25.6) 944 (28.6) 0.2 IVH Grade 3 and 4 53 (13.8) 54 (12.6) 44 (11.8) 37 (11.6) 36 (11.7) 54 (17.0) 72 (20.5) 45 (10.4) 34 (8.7) 429 (13.0) 0.7 ROP 85 (22.1) 87 (20.3) 77 (20.7) 77 (24.2) 84 (27.2) 79 (24.9) 92 (26.1) 81 (18.7) 55 (14.1) 717 (21.7) 0.98 NIMV 200 (52.1) 221 (51.5) 195 (52.4) 202 (63.5) 199 (64.4) 204 (64.4) 202 (57.4) 172 (39.7) 165 (42.2) 1760 (53.3) <0.05 Mechanical ventilation 254 (66.1) 284 (66.2) 265 (71.2) 225 (70.8) 207 (67.0) 233 (73.5) 230 (65.3) 215 (49.7) 170 (43.5) 2083 (63.0) <0.05 Ventilation option coded as other 28 (7.3) 38 (8.9) 33 (8.9) 29 (9.1) 27 (8.7) 26 (8.2) 48 (13.6) 117 (27.0) 133 (34.0) 479 (14.5) ‐ Abbreviations: IVH, intraventricular hemorrhage; NEC, necrotizing enteritis; NIMV, non invasive mechanical ventilation; RDS, respiratory distress syndrome; ROP, retinopathy of prematurity. 8of13 | ELIAS ET AL. 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License peaks and has shown models that include meteorological conditions to optimize preterm birth descriptions. 25 Further analysis on the seasonality of preterm births in Portugal is required, particularly with models to factor in heatwaves and low temperatures. Multiple birth rates varied from 2.8% to 3.4% of all births yearly, similar to results published in other countries 6,26 accounting for 37% to 42% of all preterm births analyzed. Over 97% of multiple births studied were twins and the remaining triplets. Between 61% and 68% of all multiple births were preterm. In contrast, the overall prematurity rate was 7.9%, which reflects an approximately eight times increase in premature births in multiple pregnancies, similar to what has been shown in other studies. 6 An increase in multiple gestations with associated preterm births has been widely recognized to be connected with increased maternal age and infertility treatment options. 27 As expected, comorbidities were frequent in extreme preterms: 73.3% were diagnosed with respiratory distress syndrome and 43.3% with sepsis, and in both cases, a statistically significant decrease in cases was observed throughout the study. RDS has been consistently recognized as the most common complication associated with prematurity. 28 Sepsis is documented as a frequent complication and a Swedish study reported sepsis in 66% of preterm infants under 27 weeks gestation, where we reported 43.3% under 29 weeks. 29 Necrotizing enterocolitis in developed countries is reported to occur in 5%–12% of VLBW infants. 28 In our analysis, we report 8.8% of preterms under 29 weeks, which is in keeping with the literature. 0.0 2.0 4.0 6.0 8.0 10.0 12.0 2010 2011 2012 2013 2014 2015 2016 2017 2018 NEC 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 2010 2011 2012 2013 2014 2015 2016 2017 2018 RDS 0.0 10.0 20.0 30.0 40.0 50.0 60.0 2010 2011 2012 2013 2014 2015 2016 2017 2018 Sepsis 0.0 10.0 20.0 30.0 40.0 50.0 2010 2011 2012 2013 2014 2015 2016 2017 2018 IVH Total IVH IVH Grade 3 and 4 0.0 5.0 10.0 15.0 20.0 25.0 30.0 2010 2011 2012 2013 2014 2015 2016 2017 2018 ROP 0.0 20.0 40.0 60.0 80.0 2010 2011 2012 2013 2014 2015 2016 2017 2018 Non Invasive and Invasive Mechanical Venlaon Non Invasive Mechanical Venlaon Mechanical Venlaon FIGURE 3 Preterm comorbidities (NEC, RDS, sepsis; IVH, ROP) and ventilation requirements per year between 2010 and 2018 at SNS hospitals in Portugal. IVH, intraventricular hemorrhage; NEC, necrotizing enteritis; RDS, respiratory distress syndrome; ROP, retinopathy of prematurity. ELIAS ET AL. | 9of13 23988835, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/hsr2.1054 by Cochrane Portugal, Wiley Online Library on [25/05/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License