Pengembangan Alat Skrining dan Model Estimasi Berat Janin Usia 35-40 Minggu

Abstract

The first thousand days of life (1000 HPK) is the crucial for baby’s growth and development starting from conception until two years of age (24 months). During this period, fulfillment of adequate nutrition is very important for fetal growth and development. If the mother has undernutrition status, it will cause nutritional and health problems and affecting the pregnancy outcome. One of the consequences of undernutrition during pregnancy is low birth weight (LBW). In Indonesia, the prevalence of LBW has decreased from year to year. However, some provinces in Indonesia still have LBW prevalence above the national prevalence, one of them is North Maluku Province. The infant mortality rate (IMR) in Indonesia by 2020 decreased from the previous year. Unfortunately, over 50% Indonesian provinces have IMR above the national average, including North Maluku Province which is the province with the sixth highest IMR in Indonesia. Most of the IMR occurs during the neonatal period (0-28 days), and the most common cause of neonatal death in Indonesia is LBW. Because there still high negative effects caused by LBW, it is important for creating strategies to reduce the LBW prevalence in Indonesia, mainly in the areas with limited health facilities and services. Moreover, it is also necessary to monitor fetal growth during pregnancy for identifying the fetal growth pattern. Unfortunately, neither screening tools nor fetal growth charts are available in maternal and child health booklet (MCH), which is as a media for monitoring antenatal care (ANC). Therefore, this research aimed to develop a screening tool with scoring system that can be easily implemented in all ANC facilities. In addition, due to the latest recommendations for the minimum ANC visits and program for distributing 10.000 USG to community health centers (Puskesmas) in Indonesia, this research also aimed to develop a fetal growth chart 35-40 weeks and hopefully with this growth chart can provide information regarding fetal growth and intervention before delivery. This research was conducted with combination of retrospective cohort and cross-sectional designs. The North Maluku Province was chosen as research location because it is the second largest prevalence of LBW in Indonesia (Ministry of Health 2018). Besides, it also has prevalence of LBW with birth length <48 cm above the national average, and as one of the priority provinces for intervention to reduce stunting. The research location was carried out at a private hospital in Ternate City. The selection of the hospital was based on the completeness of the ultrasound data during ANC, namely fetal biometry consisting of biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL). The inclusion criteria of subject were nulliparous or multiparous, having ANC visit and giving birth at the same hospital, having complete medical records, and giving normal or LBW babies. Subjects with multiple pregnancies, breech babies, and comorbidities such as diabetes mellitus type 2 and hypertension were not included in this study. The minimum subject for developing a screening tool were 30 subjects per group of LBW and normal babies, while for chart development, it should be minimum 100 subjects/gestational age. Research Ethics Permitted was obtained from the Health Research Ethics Commission, Faculty of Medicine, Hasanuddin University: 785/UN4.6.5.31/PP3/2022. Data were processed and analyzed by univariate, bivariate and multivariate analysis (multiple logistic and linear regression). Before developing screening tool and fetal growth chart, the collected data were divided into two, namely training dataset (to build the model) and testing dataset (to validate the model). Validation model was applied to the chosen model by calculating the mean error (ME), mean absolute percentage prediction error (MAPE), median absolute percentage prediction error (MEDAPE), and the number of estimates within 5%, 10%, and 20% of the actual birth weight. Maternal weight gain during pregnancy was also analyzed in relation to nutritional status, anemia status, baby anthropometry, and Apgar scores. The results showed that maternal gestational weight gain was not associated to nutritional status, but it associated to maternal anemia status, birth weight, birth length, head circumference, chest circumference, and Apgar score. The variables of the chosen model for estimating fetal weight consisted of fetal biometry (LK and LP) variabels and maternal characteristics (height) (Model III). The model was formed from subjects who gave birth and had their last ultrasound in the same week (35-40 weeks). Results showed that Model III has less error than other models or existing models in estimating fetal weight, so Model III was used to develop fetal growth charts based on gestational age of 35-40 weeks. The next step for developing growth chart was analysing the Model III and gestational age using regression. The results showed that Quadratic Model was the best model for developing growth charts aged 35-40 weeks by less error and had the highest R2-adjusted value. The comparison of actual birth weight and the 50th percentile value from the proposed model and existing formulas, showed that the proposed model had predicted fetal weight almost same as the actual birth weight, although slightly overestimated. On the other hand, in existing formulas, there were certain formulas that can be underestimate or overestimate in predicting fetal weight at a given gestational age. For example, the predicted fetal weight from Stirnemann formula at 40 weeks of gestation was close to the actual birth weight, but under 40 weeks of gestation, the predicted fetal weight tend to underestimate. This research concluded that the screening tool for predicting the risk of LBW can be easily applied to all ANC facilities by health workers. In addition, the fetal growth chart also had less error in predicting fetal weight based on gestational age of 35-40 weeks compare to existing growth chart. It can be concluded that the screening tool can be used in the health sector during ANC visit for detecting the risk of LBW babies. On the other hand, the fetal growth chart 35-40 weeks can help provide information about estimated fetal weight for pregnant women and can improve the quality of ANC. By this screening tool and growth chart, it can give intervention as early as possible for pregnant women with high risk of LBW baby. Furthermore, it can also support the government programs and improve the quality of life of human resources in the future. Keywords: chart, fetal, LBW, model, screening