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Prelacteal is foods given to newborns before breastfeeding is established or before breast milk comes out, one of the effects of prelacteal feeding practice is to increase mortality in infants. Efforts to reduce the behavior of prelacteal feeding practice is by implementing Early Initiation of Breastfeeding. Where one of the benefits of implementing EIB is stimulate the release of breast milk. This study uses data from the Indonesian Demographic and Health Survey on 2017 which aims to determine the correlation between the implementation of EIB with prelacteal feeding practice among newborns after being controlled by covariate variables (age, education, occupation, economic status, region of residence, frequency of Antenatal Care visits, birth attendants, type of delivery, and birthweight). The study design used was cross sectional with a total sample of 1,728 respondents. Data analysis used multiple logistic regression. The results showed that there was a correlation between the implementation of IMD with prelacteal feeding practice among newborns in Indonesia on 2017 (ρ-value = 0.0001) with an OR value of 5.20, which means that respondents who did not implement EIB had a 5.20 times more likely to do prelacteal feeding practice among newborns after being controlled by variables the region of residence and type of delivery. The recommendations of this research are technical guidelines and implementation guidelines of existing policies so that these regulations can be implemented by the regions.
The population of Indonesia from 2010-2017 continues to increase from 238 million to 261 million in 2017 with a population growth rate of 1.34% per year and maternal mortality rate is 359 per 100,000 live births. The percentage of drop out of family planning participation is 34% and the percentage of married women aged 15-49 with unmet need for family planning is 11% . This study aims to analyze the determinants of the choice type of contraception in women of childbearing age. Variables observed were age, education, work status, domicile, economic status, number of children, gender of children, place of family planning services, and ownership of national health insurance (JKN) women of childbearing age. The data used are Susenas Data (National Socio- Economic Survey) in 2017 and analyzed using multivariate logistic regression. The results explain that the variables of maternal age, education, work status, domicile, economic status, number of children, gender of children, place of family planning services, and ownership of national health insurance (JKN) influence the choice of birth control methods for women of childbearing age in Indonesia. From the results of this finding, it is expected that the government will be able to improve the health education movement for women of childbearing age to be willing to use family planning and increase the number of trained personnel, especially village midwives
ABSTRAK Penurunan Angka Kematian Ibu (AKI) hingga mencapai 102 per 100.000 kelahiran hidup di tahun 2015 sulit dicapai. Peningkatan penolong persalinan oleh tenaga kesehatan merupakan upaya pendekatan untuk mencapai target tersebut. Chen et al menyatakan densitas tenaga kesehatan per 1000 penduduk kurang dari 2,5 akan sulit mencapai persentase persalinan oleh tenaga kesehatan lebih dari 80%. Penelitian ini ditujukan untuk mengetahui hubungan antara densitas bidan dan persentase persalinan oleh bidan di Jawa Barat, Jawa Tengah, Jawa Timur, dan Banten. Desain penelitian adalah cross sectional menggunakan data gabungan Susenas 2010 dan Potensi Desa 2011 dengan unit analisis 107 kabupaten/kota. Hasil analisis menunjukkan ukuran yang paling baik dalam menjelaskan hubungan antara densitas bidan dan persentase persalinan oleh bidan adalah jumlah bidan per 10.000 penduduk dibandingkan jumlah bidan per luas wilayah dan persentase desa memiliki bidan. Peningkatan jumlah bidan per 10.000 penduduk dapat meningkatkan persentase persalinan oleh bidan sebesar 4,1% setelah dikontrol oleh densitas dokter dan provinsi, dengan R2 0,38. Sedangkan peningkatan jumlah bidan per 10.000 penduduk dapat meningkatkan persentase persalinan oleh bidan pada kuintil pengeluaran rendah sebesar 6,0% setelah dikontrol oleh densitas dokter, dengan R2 0,11.<><> ABSTRACT Decreasing Maternal Mortality Rate (MMR) up to 102 per 100000 live births in 2015 is difficult to achieve. An approaching effort to achieve these targets is by increasing skilled birth attendant. Chen et al declared the density of health workers per 1000 population less than 2.5, will be difficult to reach the percentage of skilled birth attendant more than 80%. This study is aimed to determine the relationship between density of midwives and percentage of births by midwives in West Java, Central Java, East Java, and Banten. This research used secondary data from Susenas 2010 and Podes 2011, with cross-sectional study design. Unit of analysis covers 107 districts / cities. The results showed that number of midwives per 10,000 population describes the relationship between density of midwives and percentage of births by midwives better than number of midwives per area and percentage of village which has midwives. The increasing number of midwives per 10,000 population can increase the percentage of births by midwives by 4.1% after controlling the density of doctors and province (R2 0.38). While increasing number of midwives per 10,000 population can increase the percentage of births by midwives at lower quintiles by 6.0% after being controlled by the density of physicians (R2 0.11).
Penyakit ginjal kronis merupakan penyebab kematian nomor 12 pada tahun 2017 dan diprediksi menjadi penyebab kematian nomor 5 pada tahun 2040. Berdasarkan data SKI 2023, prevalensi penyakit ginjal kronis di Indonesia adalah 0,18%. Walaupun relatif relatif kecil, masalah yang dihadapi adalah deteksi dini risiko dari faktor risiko penyakit ginjal kronis. Permasalahan penanganan penyakit ginjal kronis di Indonesia adalah kurangnya edukasi mengenai deteksi dini penyakit ginjal kronik serta faktor risikonya kepada masyarakat. Berdasarkan permasalahan ini, dilakukan penelitian untuk melihat faktor-faktor penyebab ginjal kronis di Indonesia. Penelitian dilakukan dengan menggunakan data SKI 2023 dengan jumlah sampel sebanyak 22639 individu. Penelitian ini dilakukan dengan uji kai kuadrat dan dilanjutkan dengan regresi logistik. Dari hasil regresi logistik yang dilakukan didapatkan hasil bahwa variabel yang menjadi faktor terbesar penyebab penyakit ginjal kronis adalah diabetes ( p-value = 0,008 ; OR = 4.792 (1,52-15,14)). Karena hasil penelitian menunjukkan diabetes sebagai faktor terbesar penyebab penyakit ginjal kronis, maka peneliti menyarankan bahwa terdapat dua fokus kebijakan yang dapat dilakukan. Pertama untuk penderita diabetes dalam hal pengontrolan penyakit, dan kedua kepada orang sehat dalam hal skrining dan deteksi dini serta promosi kesehatan untuk penerapan pola hidup sehat.
Chronic kidney disease was the 12th leading cause of death in 2017 and is predicted to be the fifth leading cause of death in 2040. Based on SKI 2023 data, the prevalence of chronic kidney disease in Indonesia is 0.18%. Although relatively small, the problem faced is early detection of the risk of chronic kidney disease risk factors. The problem of handling chronic kidney disease in Indonesia is the lack of education regarding the early detection of chronic kidney disease and its risk factors to the community. Based on this problem, a study was conducted to see the factors causing kidney chronicity in Indonesia. The study was conducted using SKI 2023 data with a sample size of 22,639 individuals. This study was conducted using the chi-square test and continued with logistic regression. From the results of the logistic regression, it was obtained that the variable that was the most significant factor causing chronic kidney disease was diabetes (p-value = 0.008; OR = 4.792 (1.52-15.14)). Because the results of the study showed diabetes as the most significant factor causing chronic kidney disease, the researcher suggested that there were two policy focuses that could be implemented. Firstly, for people with diabetes in terms of disease control, and secondly, for healthy people in terms of screening and early detection as well as health promotion for implementing a healthy lifestyle.