Factors associated with Macrosomia in public hospitals of Mekelle City, Northern Ethiopia: A multi-center study
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| Pubblicato in: | PLoS One vol. 20, no. 6 (Jun 2025), p. e0325541 |
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| Autore principale: | |
| Altri autori: | , , , , , |
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Public Library of Science
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| 003 | UK-CbPIL | ||
| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0325541 |2 doi | |
| 035 | |a 3215590101 | ||
| 045 | 2 | |b d20250601 |b d20250630 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Gebretinsae Alem Hagos | |
| 245 | 1 | |a Factors associated with Macrosomia in public hospitals of Mekelle City, Northern Ethiopia: A multi-center study | |
| 260 | |b Public Library of Science |c Jun 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a BackgroundMacrosomia, defined as a birth weight ≥4,000 grams, is linked to increased risks of cesarean delivery, postpartum hemorrhage, and neonatal morbidity, posing significant challenges in resource-limited regions like Northern Ethiopia., However, in Northern Ethiopia, evidence about the factors that lead to macrosomia is scarce. This study aimed to assess the factors associated with delivery of a macrosomic baby in public hospitals in Mekelle city, Northern Ethiopia.MethodA hospital-based, unmatched case control study design was implemented on 276 samples (184 controls and 92 cases) among newborns delivered in public hospitals of Mekelle City from February 21, 2020, to June 20, 2020. Cases and controls were selected using consecutive and systematic random sampling techniques, respectively. Data were collected using a structured questionnaire and a checklist and analyzed using SPSS. After describing the variables, bivariate and multivariable logistic regression models were employed to see the association between the factors and macrosomia. P < 0.05 was used to determine the statistical significance.ResultThe multivariable model identified five factors that are significantly associated with macrosomia. As the age of the mother increases by one year, the odds of macrosomia were found to increase by 12% (AOR = 1.12, 95% CI: 1.02 to 1.23). As well, for each one-kilogram weight gain during pregnancy, the odds of macrosomia increased by 36% (AOR = 1.36, 95% CI: 1.12 to 1.65). And, one unit increment in body mass index was found to increase the odds of macrosomia by 26% (AOR = 1.26, 95% CI: 1.06 to 1.50). Likewise, the male sex of the newborn and history of macrosomia were found to increase the chance of macrosomia by 2.66 (AOR = 2.66, 95% CI: 1.08 to 6.56) and 3.59-fold (AOR = 3.59, 95% CI: 1.62 to 7.95), respectively.ConclusionIn this study, the risk of macrosomia was found to be higher for male newborns, older mothers, greater weight gain during pregnancy, higher body mass index, and mothers with a history of macrosomia. This study has found both modifiable and non-modifiable risk factors of macrosomia. Policymakers should integrate preconception counselling and health education about the modifiable risk factors of macrosomia, such as weight gain during pregnancy. Big emphasis should be given to the male fetus and pregnant mothers with advanced age and history of macrosomia. | |
| 651 | 4 | |a Ethiopia | |
| 651 | 4 | |a Mekelle Ethiopia | |
| 653 | |a Fetuses | ||
| 653 | |a Hemorrhage | ||
| 653 | |a Population | ||
| 653 | |a Neonates | ||
| 653 | |a Pregnancy | ||
| 653 | |a Regression models | ||
| 653 | |a Morbidity | ||
| 653 | |a Regression analysis | ||
| 653 | |a Age | ||
| 653 | |a Health facilities | ||
| 653 | |a Hospitals | ||
| 653 | |a Births | ||
| 653 | |a Body mass index | ||
| 653 | |a Random sampling | ||
| 653 | |a Sampling techniques | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Mothers | ||
| 653 | |a Sampling methods | ||
| 653 | |a Medical history | ||
| 653 | |a Statistical sampling | ||
| 653 | |a Body weight | ||
| 653 | |a Body size | ||
| 653 | |a Males | ||
| 653 | |a Sociodemographics | ||
| 653 | |a Cesarean section | ||
| 653 | |a Gestational diabetes | ||
| 653 | |a Risk factors | ||
| 653 | |a Data collection | ||
| 653 | |a Birth weight | ||
| 653 | |a Newborn babies | ||
| 653 | |a Maternal mortality | ||
| 653 | |a Bivariate analysis | ||
| 653 | |a Babies | ||
| 653 | |a Social | ||
| 700 | 1 | |a Mekuria Kassa Nerea | |
| 700 | 1 | |a Edris Abdu Debesay | |
| 700 | 1 | |a Mengistu Hagazi Tequare | |
| 700 | 1 | |a Hiluf Ebuy Abraha | |
| 700 | 1 | |a Yohannes Tesfay Abebe | |
| 700 | 1 | |a Mohamedawel Mohamedniguss Ebrahim | |
| 773 | 0 | |t PLoS One |g vol. 20, no. 6 (Jun 2025), p. e0325541 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3215590101/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3215590101/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3215590101/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |