2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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 was more common in predominantly urban 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.

          Key points

          • Study question

            • What are the characteristics of preterm births in Portugal, according to gestational age, geographic distribution, seasonality, multiple gestation, and outcomes?

          • What is already known

            • 7.8% of all births in Portugal are preterm. Distinct prematurity urban–rural patterns have been reported in different regions worldwide. Several countries have reported a seasonal prematurity trend. Multiple births are a risk factor for prematurity. Prematurity outcomes are intrinsically related to gestational age.

          • What this study adds

            • One in 13 babies was born prematurely in Portugal. Under 29 weeks, birth rates varied between 5.5% and 7.6%, and between 33 and 36 weeks varied from 76.9% to 81.0%. Prematurity was more common in predominantly urban districts than rural ones, which was a surprising finding and warrants further studies. Seasonal preterm variation rates also require further analysis. Multiple births were eight times more likely to be preterm. A decrease in the case rate of RDS and sepsis was observed. Preterm mortality per gestational age improvements are attainable compared with other countries.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis

          Summary Background Preterm birth is the leading cause of death in children younger than 5 years worldwide. Although preterm survival rates have increased in high-income countries, preterm newborns still die because of a lack of adequate newborn care in many low-income and middle-income countries. We estimated global, regional, and national rates of preterm birth in 2014, with trends over time for some selected countries. Methods We systematically searched for data on preterm birth for 194 WHO Member States from 1990 to 2014 in databases of national civil registration and vital statistics (CRVS). We also searched for population-representative surveys and research studies for countries with no or limited CRVS data. For 38 countries with high-quality data for preterm births in 2014, data are reported directly. For countries with at least three data points between 1990 and 2014, we used a linear mixed regression model to estimate preterm birth rates. We also calculated regional and global estimates of preterm birth for 2014. Findings We identified 1241 data points across 107 countries. The estimated global preterm birth rate for 2014 was 10·6% (uncertainty interval 9·0–12·0), equating to an estimated 14·84 million (12·65 million–16·73 million) live preterm births in 2014. 12· 0 million (81·1%) of these preterm births occurred in Asia and sub-Saharan Africa. Regional preterm birth rates for 2014 ranged from 13·4% (6·3–30·9) in North Africa to 8·7% (6·3–13·3) in Europe. India, China, Nigeria, Bangladesh, and Indonesia accounted for 57·9 million (41×4%) of 139·9 million livebirths and 6·6 million (44×6%) of preterm births globally in 2014. Of the 38 countries with high-quality data, preterm birth rates have increased since 2000 in 26 countries and decreased in 12 countries. Globally, we estimated that the preterm birth rate was 9×8% (8×3–10×9) in 2000, and 10×6% (9×0–12×0) in 2014. Interpretation Preterm birth remains a crucial issue in child mortality and improving quality of maternal and newborn care. To better understand the epidemiology of preterm birth, the quality and volume of data needs to be improved, including standardisation of definitions, measurement, and reporting. Funding WHO and the March of Dimes.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Trends in Care Practices, Morbidity, and Mortality of Extremely Preterm Neonates, 1993-2012.

            Extremely preterm infants contribute disproportionately to neonatal morbidity and mortality.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000.

              Information about the distribution of causes of and time trends for child mortality should be periodically updated. We report the latest estimates of causes of child mortality in 2010 with time trends since 2000. Updated total numbers of deaths in children aged 0-27 days and 1-59 months were applied to the corresponding country-specific distribution of deaths by cause. We did the following to derive the number of deaths in children aged 1-59 months: we used vital registration data for countries with an adequate vital registration system; we applied a multinomial logistic regression model to vital registration data for low-mortality countries without adequate vital registration; we used a similar multinomial logistic regression with verbal autopsy data for high-mortality countries; for India and China, we developed national models. We aggregated country results to generate regional and global estimates. Of 7·6 million deaths in children younger than 5 years in 2010, 64·0% (4·879 million) were attributable to infectious causes and 40·3% (3·072 million) occurred in neonates. Preterm birth complications (14·1%; 1·078 million, uncertainty range [UR] 0·916-1·325), intrapartum-related complications (9·4%; 0·717 million, 0·610-0·876), and sepsis or meningitis (5·2%; 0·393 million, 0·252-0·552) were the leading causes of neonatal death. In older children, pneumonia (14·1%; 1·071 million, 0·977-1·176), diarrhoea (9·9%; 0·751 million, 0·538-1·031), and malaria (7·4%; 0·564 million, 0·432-0·709) claimed the most lives. Despite tremendous efforts to identify relevant data, the causes of only 2·7% (0·205 million) of deaths in children younger than 5 years were medically certified in 2010. Between 2000 and 2010, the global burden of deaths in children younger than 5 years decreased by 2 million, of which pneumonia, measles, and diarrhoea contributed the most to the overall reduction (0·451 million [0·339-0·547], 0·363 million [0·283-0·419], and 0·359 million [0·215-0·476], respectively). However, only tetanus, measles, AIDS, and malaria (in Africa) decreased at an annual rate sufficient to attain the Millennium Development Goal 4. Child survival strategies should direct resources toward the leading causes of child mortality, with attention focusing on infectious and neonatal causes. More rapid decreases from 2010-15 will need accelerated reduction for the most common causes of death, notably pneumonia and preterm birth complications. Continued efforts to gather high-quality data and enhance estimation methods are essential for the improvement of future estimates. The Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                cecilia.elias@proton.me
                Journal
                Health Sci Rep
                Health Sci Rep
                10.1002/(ISSN)2398-8835
                HSR2
                Health Science Reports
                John Wiley and Sons Inc. (Hoboken )
                2398-8835
                22 February 2023
                February 2023
                : 6
                : 2 ( doiID: 10.1002/hsr2.v6.2 )
                : e1054
                Affiliations
                [ 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
                Author notes
                [*] [* ] Correspondence Cecília Elias, Unidade de Saúde Publica Francisco George, ACES Lisboa Norte, ARSLVT, Lisboa, Portugal.

                Email: cecilia.elias@ 123456proton.me

                Author information
                http://orcid.org/0000-0002-3922-7152
                https://orcid.org/0000-0001-8316-5035
                https://orcid.org/0000-0001-9502-6075
                Article
                HSR21054
                10.1002/hsr2.1054
                9945543
                a98024f5-bd3b-4402-a1e2-ab385d82854d
                © 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ 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.

                History
                : 23 November 2022
                : 19 July 2022
                : 29 December 2022
                Page count
                Figures: 3, Tables: 7, Pages: 13, Words: 6713
                Funding
                Funded by: The present publication was funded by Fundação Ciência e Tecnologia, IP national support through CHRC
                Award ID: UIDP/04923/2020
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                February 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.5 mode:remove_FC converted:22.02.2023

                gestational age,morbidities,mortality,multiple,prematurity,urban–rural

                Comments

                Comment on this article