Model Prediksi Berat Lahir Bayi Berdasarkan Berat Badan Ibu Hamil

Sari, Maulia; Sudiarti, Trini

doi:10.21109/kesmas.v7i8.18

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…33 Pre-pregnancy weight and maternal weight gain in the first, second, and third trimesters have a moderate power relation and positive pattern. 34 Protein is important for fetal development because one of its roles is to form fetal cells and tissues. Protein consumption is increased during pregnancy to prevent protein deficiency and malnutrition.…”

Section: Discussionmentioning

confidence: 99%

Risk Factors Associated with Low Birth Weight

Rahfiludin¹,

Dharmawan²

2018

Kesmas: National Public Health Journal

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Neonatal deaths are associated with preterm birth complications. Preterm birth is also related to low birth weight (LBW), which can have multiple causes. The aim of this study was to analyze the risk factors associated with LBW. This was a cross-sectional study held in Bulu Primary Health Care, Temanggung, Central Java, Indonesia. The sample size required for this study was 69 based on the Slovin formula. Data were collected using questionnaires and semi-quantitative FFQ forms. Data on infant birth weight was taken from midwives’ delivery cohort records. Mid upper arm circumference (MUAC), hemoglobin level, blood pressure, maternal age, parity, nutritional intake, and serum transferrin receptor data were taken from the infant’s mother using a MUAC tape, automatic blood pressure monitor and blood laboratory analysis by Prodia. Data analysis procedures were carried out with quantitative methods. Descriptive statistics were analyzed as means and standard deviations. Inferential statistics used the chi-square test for bivariate analysis and binary logistic regression for multivariate analysis. The results of this study showed that mean infant birth weight was 2917.68 ± 374.673 kg. Inferential analysis showed that MUAC and pregnancy at a risky age are significant risk factors associated with LBW, while serum transferrin receptor levels, anemia, parity, energy and protein consumption levels, and systolic and diastolic blood pressure are nonsignificant risk factors. The probability of LBW in pregnant women with LILA under 23.5 cm and pregnancy at a risky age is 68.9%.

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Section: Discussionmentioning

confidence: 99%

Risk Factors Associated with Low Birth Weight

Rahfiludin¹,

Dharmawan²

2018

Kesmas: National Public Health Journal

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“…Pada trisemester pertama berat badan bayi berkisar antara 0,500 -2000 Gram. Kurangnya berat bayi pada trisemester pertama mempunyai pengaruh lebih besar terhadap berat lahir (10). Penyebab kurangnya berat badan bayi dapat dikarenakan karena ketidakcukupan konsumsi makanan pada ibu hamil.…”

Section: Pendahuluanunclassified

“…Hasil penelitian yang telah dilakukan janin yang mnegalami kekurangan gizi selama kehamilan semester pertama akan mengalami penurunan regulasi pertumbuhan, berat lahir yang kurang dengan tubuh janin yang kecil. Usia janin pada trisemester pertama merupakan tahapan pembentukan organ, sehingga apabila gizi dan makanan yang dikonsumsi oleh ibu hamil megalami kekurangan maka akan berpengaru pada perkembangan organ (10).…”

Section: Pendahuluanunclassified

Peningkatan Pengetahuan Obat Dan Gizi Selama Kehamilan Melalui Program Pendampingan

et al. 2019

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Central Java is one of the contributors to our maternal and infant mortality rates in Indonesia. This increase was partly due to the knowledge of pregnant women about nutritional needs at the time of assessment. The purpose of this research is to increase the knowledge of pregnant women about the adequacy of nutrition and the use of drugs during pregnancy. The method used was assistance for pregnant women by professionals in their fields in September Obgyn Doctors and Pharmacists and descriptive analysis through questionnaires before and then conducted activities. Assistance activities carried out for one day in preparation for preliminary pregnant women in Pudak Payung. Based on the results of research people do not understand the importance of adequate nutrition during the assessment seen from a baby's low weight at his age. After mentoring, the increase in knowledge and awareness of pregnant women increased by 97%. Abstrak Jawa tengah merupakan salah satu penyumbang angka kamatian ibu hamil dan bayi di Indonesia. Peningkatan tersebut salah satunya karena faktor pengetahuan ibu hamil mengenai kebutuhan gizi pada saat kehamilan. Tujuan dilakukan penelitian adalah meningkatkan pengetahuan ibu hamil akan kecukupan gizi dan penggunaan obat selama kehamilan. Metode yang digunakan adalah pendampingan pada ibu hamil oleh tenaga professional dibidangnya seperti Dokter Obgyn dan Apoteker dan analisa deskriptif melalui kuisioner sebelum dan sesudah dilakukan kegiatan. Kegiatan pendampingan dilakukan selama satu hari sebagai gambaran pendahuluan kondisi ibu hamil di Pudak Payung. Berdasarkan hasil penelitian masyarakat belum mengetahui akan pentingnya kecukupan gizi selama kehamilan dilihat dari berat badan bayi yang rendah pada usianya. Setelah dilakukan pendampingan peningkatan pengetahuan dan kesadaran ibu hamil meningkat sebesar 97%.

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Model Prediksi Berat Lahir Bayi Berdasarkan Faktor-Faktor Yang Mempengaruhi Di Puskesmas Kaluku Bodoa Tahun 2017-2018

Finandakasih¹,

Rosmah²,

Tiro³

2020

JKMM

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Salah satu indikator untuk menentukan derajat kesehatan suatu bangsa ditandai dengan tinggi rendahnya angka kematian ibu dan bayi, target Sustainable Development Goals (SDGs) dalam mengurangi angka kematian neonatal belum tercapai. Berat badan lahir rendah (BBLR) merupakan penyebab utama kematian prenatal. Tujuan penelitian ini untuk mengetahui model prediksi berat lahir bayi berdasarkan faktor-faktor yang mempengaruhi di Puskesmas Kaluku Bodoa tahun 2017-2018. Jenis penelitian ini adalah penelitian retrospektif. Populasi adalah seluruh bayi baru lahir di wilayah kerja Puskesmas Kaluku Bodoa pada bulan Februari tahun 2017 sampai bulan Februari 2018 yang berjumlah 1.223 bayi. Besar sampel adalah 142 bayi diperoleh berdasarkan teknik pengambilan sampel yaitu purposive sampling. Hasil penelitian menunjukkan model prediksi yang diperoleh dari analisis regresi linear berganda yaitu y = 1500,435 + 2,401X1 + 7,446X2 + 132,484X3 + 128,960X4 + 103,877X5 dimana : y = berat lahir bayi, X1 = berat badan ibu sebelum hamil, X2 = ukuran LILA, X3 = pertambahan berat badan trimester I, X4 = pertambahan berat badan trimester II, X5= pertambahan berat badan trimester III (R2 = 80%) dan semua asumsi regresi linear terpenuhi.

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Model Prediksi Berat Lahir Bayi Berdasarkan Berat Badan Ibu Hamil

Cited by 3 publications

References 8 publications

Risk Factors Associated with Low Birth Weight

Risk Factors Associated with Low Birth Weight

Peningkatan Pengetahuan Obat Dan Gizi Selama Kehamilan Melalui Program Pendampingan

Model Prediksi Berat Lahir Bayi Berdasarkan Faktor-Faktor Yang Mempengaruhi Di Puskesmas Kaluku Bodoa Tahun 2017-2018

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