Number Of Infant Mortality Research Articles

Parameter Estimation and Hypothesis Testing of Multivariate Poisson Inverse Gaussian Regression

Multivariate Poisson regression is used in order to model two or more count response variables. The Poisson regression has a strict assumption, that is the mean and the variance of response variables are equal (equidispersion). Practically, the variance can be larger than the mean (overdispersion). Thus, a suitable method for modelling these kind of data needs to be developed. One alternative model to overcome the overdispersion issue in the multi-count response variables is the Multivariate Poisson Inverse Gaussian Regression (MPIGR) model, which is extended with an exposure variable. Additionally, a modification of Bessel function that contain factorial functions is proposed in this work to make it computable. The objective of this study is to develop the parameter estimation and hypothesis testing of the MPIGR model. The parameter estimation uses the Maximum Likelihood Estimation (MLE) method, followed by the Newton–Raphson iteration. The hypothesis testing is constructed using the Maximum Likelihood Ratio Test (MLRT) method. The MPIGR model that has been developed is then applied to regress three response variables, i.e., the number of infant mortality, the number of under-five children mortality, and the number of maternal mortality on eight predictors. The unit observation is the cities and municipalities in Java Island, Indonesia. The empirical results show that three response variables that are previously mentioned are significantly affected by all predictors.

Identifying the most influential risk factors of frequent infant mortality in Iraq

Nowadays, frequent Infant Mortality for the married women are prevailing in Iraq. It may be also considered as a risky phenomenon in developing countries. It is the loss of an infant after viability. The estimated number is 2.5 million deaths occurring in the first month of life in 2017 alone. On the other hand, the survival rates of newborn infants reflect the quality of pregnancy care provided during work and viability and the infrastructure for the infant care in the different regions and countries of the world. Numerous risk factors are causing this phenomenon. Logistic regression is a statistical technique can be used to express the association between the number of infant mortality and the risk factors cause it. It helps to select the most influential risk factors for this case. The aim of this study is to use logistic regression to examine the association between biological, behavioral and lifestyle risk factors and the number of infant mortality, and to identify the most influential risk factors affected it. A simple random sample is drawn with size of 200 persons that consists of all mothers who visit the primary health care centers in Babylon province in year 2018. Seventeen risk factors are representing biological, behavioral and lifestyle factors of women under the study. The results of fitting binary and ordinal logistic regressions with all seventeen risk factors show that four risk factors show a significance effect on the dependent variable. Consequently, a stepwise logistic regression was fitted, and ordinal logistic regression model has fitted. Nevertheless, there are no much differences between the results of these models with different methods of fitting. All results show that husbands working has two times more likely to exhibit infant mortality than Husbands not working. Increasing age at marriage and woman weight were associated with an increased likelihood of exhibiting infant mortality, but increasing number of hours of women's sleeping was associated with a reduction in the likelihood of exhibiting infant mortality.

Modeling of infant mortality in west sulawesi using zero inflated poisson regression method

The number of infant deaths, one of which can be reflected in the Infant Mortality Rate (IMR) is one indicator to determine the development of a country’s development. The AKB target in the 2015-2019 National Medium-Term Development Plan is 24 deaths per 1,000 live births. Based on the SDKI 2017, the IMR value in West Sulawesi is 42 deaths per 1,000 live births. Factors suspected of affecting infant mortality in West Sulawesi are not only in the health but also in socio-economic fields. Data on the number of infant mortality in West Sulawesi is a data count that contains a value of 0. Therefore, the analysis used is Zero Inflated Poisson (ZIP) Regression to determine what factors influence infant mortality in West Sulawesi. The results of the ZIP regression analysis showed that the best model with the smallest AIC and AICc is 324,3407 and 326,7407 were models with a combination of the variables of the percentage of active maternal and child health services, percentage of society with good drinking water adequate access and percentage of society with proper sanitation access. The variable that has a significant effect on the log model is the percentage of active maternal and child health services, percentage of society with good drinking water adequate access and percentage of society with proper sanitation access. In the variable logit model that is influential is the percentage of active maternal and child health services.

Karakteristik Ibu dan Faktor Risiko Kejadian Kematian Bayi di Kabupaten Banjarnegara

Latar Belakang: Kabupaten Banjarnegara pada tahun 2012 menjadi Kabupaten dengan angka kematian bayi (AKB) tertinggi di Provinsi Jawa tengah. Dalam lima tahun terakhir angka kematian bayi sudah mengalami penurunan namun belum signifikan. Tujuan penelitian ini adalah untuk menganalisis karakteristik ibu dan beberapa faktor risiko yang berhubungan dengan kejadian kematian bayi di kabupaten Banjarnegara. Metode: Penelitian ini merupakan penelitian survei dengan pendekatan kasus kontrol dengan jumlah kelompok kasus 47 ibu dan kelompok kontrol 47 ibu. Sampel diambil secara purposive dengan kriteria inklusi kelompok kasus yaitu ibu yang mempunyai bayi meninggal sebelum berusia 24 hari di tahun 2017 dan tercatat di puskesmas Punggelan dan pejawaran. Data primer diambil dengan menggunakan kuesioner dengan teknik wawancara tatap muka. Data sekunder diambil dari buku catatan KIA ibu. Data dianalisis dengan menggunakan uji Chi-Square.Hasil: Dari hasil penelitian didapatkan bahwa faktor risiko yang berhubungan dengan kejadian kematian bayi di Kabupaten Banjarnegara adalah komplikasi persalinan, riwayat anemia, berat bayi lahir rendah, asfiksia, kelainan kongenital, dan bayi lahir prematur. Sedangkan umur ibu pengetahuan ibu, Pendidikan ibu, Paritas, Jarak kehamilan, berat badan ibu, lingkar lengan atas ibu, riwayat penyakit kronik ibu, perdarahan, hipertensi, penolong persalinan, tidak berhubungan secara signifikan dengan kejadian kematian bayi. Diharapkan dari hasil penelitian ini petugas kesehatan dapat mencegah faktor risiko yang berhubungan dengan kematian bayi dengan cara menganjurkan dan mengunjungi ibu hamil untuk melakukan ANC tepat waktu dan lengkap termasuk pemberian tablet Fe kepada ibu dan memonitornya melalui petugas surveilance KIA.Kata Kunci: kematian bayi, faktor risiko, karakteristik ibu hamil

Risk Factors of Perinatal Death Age 0-28 Days at RSD dr. Soebandi Jember

Abstract
 Perinatal deaths are babies who die at <28 days of birth. According to WHO, there are 2.7 million perinatal deaths worldwide in 2015. In 2016, the number of infant mortality at Jember is 50.19 per 1000 live births and become the second rank in Jawa Timur after Probolinggo. Infant mortality has been associated by maternal, gestational and neonatal factors. The aim of this study is to determine the risk factors of perinatal death age 0-28 days in RSD dr. Soebandi Kabupaten Jember. This research was analytic observasional with case control design doing in RSD dr. Soebandi Kabupaten Jember. The samples were 65 cases and 65 controls. Data analysis was done by Chi-square test and Fisher’s exact test with significance value < 0,05. The results showed APGAR Score (p <0.001, OR = 6.51), birth weight (p <0.001, OR = 9.66), body length (p <0.001 OR = 5.07), gestational age (p = 0.002; OR = 2.92), congenital anomalies (p = 0.013; OR = -) and maternal age (p = 0.001; OR = 4.51) were risk factors for perinatal death 0-28 days in RSD dr. Soebandi Kabupaten Jember. 
 Keywords: perinatal deaths, neonatal factors, maternal factors, gestational factors.

Mother Behavior Prefer Untrained Traditional Birth Attendant As Labor Support Person At Tembilahan Hulu Public Health Center Districts On 2016

Background: Maternal Mortality Rate (MMR) is one indicator of health development in Indonesia. Deliveries by health personnel to be very important in efforts to reduce maternal mortality. Coverage of births attended by skilled health personnel at health centers Tembilahan Hulu has yet to reach the target of 90%. Target Health Center Tembilahan Hulu is 80% but reached only 45%. The number of maternal deaths in health centers Hulu 2016 Tembilahan 1 case and the number of infant mortality as much as 5 case, one cause of death is handled by TBAs.
 Objective: to know the mother's behavior in selecting birth attendants in health centers working area Tembilahan Hulu.
 Design: Qualitative research, to obtain in-depth information about how the Mother Behavior in Choosing Auxiliary Power Delivery at Puskesmas Tembilahan Hulu 2016.
 Methods: This study used a qualitative descriptive method, which is an approach to research that revealed certain social situations to describe reality correctly, formed by words based on the techniques of collecting and analyzing relevant data obtained from the natural situation.
 Results and Discussion: Research shows that mothers choose birth attendants decision is closely linked to the knowledge, attitudes, social culture, access to health services, family support.
 Conclusions: The behavior of mothers in selecting birth attendant is still a lot to TBAs compared to the health worker / midwife.