Life Expectancy is a tool for evaluating government performance in improving the welfare of the population in general, and improving health status in particular. Research on life expectancy is necessary, as life expectancy is an important indicator of health and economic development. The research aims to make the modeling of life expectancy of men and women in Indonesia based on health variables that exist in susenas 2016. This research is a research of secondary data with multiple linear regression analysis. There were 17 predictor variables analyzed for female AHH and 13 predictor variables for male AHH. Most of the variables are health variables. there are only 2 variables of all variables were signifi cant to female AHH. there are only 4 variables were signifi cant to male AHH The regression model shows that AHH has a higher constant than the male AHH. The results show that the variables that give signifi cant effect to the female AHH were the percentage of people who ever been hospitalized, Toddler age 0–2 year was still breastfed and the household using the toilet facility. For male AHH the signifi cant variables are Toddler age 0–2 year was still breastfed, household using the toilet facility, and residents using health insurance for inpatient and outpatient. Abstrak Angka Harapan Hidup (AHH) merupakan alat untuk mengevaluasi kinerja pemerintah dalam meningkatkankesejahteraan penduduk pada umumnya, dan meningkatkan derajat kesehatan pada khususnya. Penelitian mengenai AHH sangat diperlukan, mengingat Angka Harapan Hidup merupakan indikator penting pembangunan kesehatan dan ekonomi. Penelitian bertujuan untuk membuat pemodelan AHH laki-laki dan perempuan di Indonesia berdasarkan variabel yang ada di susenas 2016. Penelitian ini merupakan penelitian data sekunder dengan analisis regresi linier berganda. Terdapat 17 variabel prediktor yang dianalisis untuk AHH perempuan dan 13 variabel prediktor untuk AHH laki-laki. Sebagian besar variabel merupakan variabel kesehatan. Dari variabel tersebut hanya 3 variabel prediktor yang signifi kan terhadap AHH perempuan dan 4 variabel yang signifi kan terhadap AHH laki-laki. Model regresi menunjukkan AHH perempuan mempunyai konstanta yang lebih besar daripada AHH laki-laki. Hasil penelitian menunjukkan bahwa variabel yang memberi pengaruh signifi kan terhadap AHH perempuan adalah persentase penduduk yang pernah rawat inap, Baduta masih ASI dan rumah tangga yang menggunakan fasilitas buang air besar (BAB). Untuk AHH laki-laki variabel yang signifi kans adalah Baduta masih ASI, rumah tangga yang menggunakan fasilitas buang air besar (BAB),serta penduduk yang menggunakan jaminan kesehatan untuk rawat inap dan rawat jalan.
The 2018 Basic Health Research (Riskesdas) shows that the proportion of mental emotional disorders has increased compared to Risksesdas 2013 (9.8% from 6%), so that it has the potential to become a mental disorder that needs complex handling. The use of basic medicines for mental disorders in primary health care is limited due to the lack of competent and authorized health worker, besides the availability of medicines is very low. Research on Medicinal Plans and Herbs/Riset Tanaman Obat dan Jamu (Ristoja) has been carried out since 2012 and has resulted in successfully identifying more than 4,000 species of medicinal plants. One of them is a medicinal plant that is empirically used to overcome mental emotional disorders. Ristoja is an ethnomedicine study that needs further investigation. The research aims to prioritize/rank potential of medicinal plants for mental emotional disorders. The study analyzed secondary data of Ristoja in 2012, 2015, and 2017. Data were selected using the Weighted Product (WP) method to assess the priority of medicinal plants to be carried out in the next stage of research. Subsequent analysis of the WP method is used to determine the peringkat of medicinal plants. The results of the analysis show that of the 22 plants that caried out a literature search, there were only 9 medicinal plants that had the potential for mental emotional disorders, and were a priority for research. These plants are 1) Moringa oleifera (Kelor); 2) Sesbania grandiflora (Turi); 3) Spondias mombin (Yellow mombin); 4) Mimosa pudica (Putri malu); 5) Ocimum tenuiflorum (Lampes); 6) Basilicum polystachyon (Sangket); 7) Cocos nucifera (Kelapa); 8) Citrus aurantiifolia (Jeruk limau); 9) Caesalpinia sappan (Secang). These plants mostly work to suppress the central nervous system. Plants that have entered piority for mental disorders, can be performed pharmacologically and acute toxicity tests, in accordance with the stages of the development of traditional medicine in Indonesia. Abstrak Data Riset Kesehatan Dasar (Riskesdas) tahun 2018 menunjukkan proporsi gangguan mental emosional mengalami peningkatan dibanding Riskesdas 2013 (9,8% dari 6%), sehingga berpotensi menjadi gangguan jiwa yang perlu penanganan kompleks. Penggunaan obat dasar gangguan mental di pelayanan kesehatan primer dibatasi karena kurangnya petugas kesehatan yang kompeten dan berwenang, selain itu ketersediaan obat sangat rendah. Riset Tanaman Obat dan Jamu (Ristoja) dilakukan sejak tahun 2012 dan telah berhasil mengidentifikasi lebih dari 4.000 spesies tumbuhan obat, salah satunya adalah tumbuhan untuk mengatasi gangguan mental emosional. Ristoja merupakan studi etnomedisin yang perlu diteliti lebih lanjut. Penelitian bertujuan untuk melakukan prioritas/ peringkat tumbuhan obat berpotensi untuk gangguan mental emosional. Penelitian menganalisis data sekunder Ristoja tahun 2012, 2015, dan 2017. Data diseleksi menggunakan metode Weighted Product (WP) untuk menilai prioritas tumbuhan obat yang akan dilakukan penelitian pada tahap berikutnya. Analisis selanjutnya metode WP digunakan untuk menentukan peringkat tumbuhan obat. Hasil analisis menunjukkan bahwa dari 22 tumbuhan yang dilakukan penelusuran literatur, hanya ada 9 tumbuhan yang berpotensi untuk gangguan mental emosional, serta menjadi prioritas untuk dilakukan penelitian. Tumbuhan tersebut adalah:1) Moringa oleifera (Kelor); 2) Sesbania grandiflora (Turi); 3) Spondias mombin (Yellow mombin); 4) Mimosa pudica (Putri malu); 5) Ocimum tenuiflorum (Lampes); 6) Basilicum polystachyon (Sangket); 7) Cocos nucifera (Kelapa); 8) Citrus aurantiifolia (Jeruk limau); 9) Caesalpinia sappan (Secang). Tumbuhan tersebut sebagian besar bekerja menekan sistem saraf pusat. Tumbuhan yang sudah masuk prioritas untuk gangguan mental, dapat dilakukan uji farmakologi dan toksisitas akut, sesuai dengan tahapan pengembangan obat tradisional di Indonesia.
Compounding plants into health ingredients is a promotive-preventive-based health culture, which was identified in the Research on Medicinal Plants and Herbs (Ristoja). The regeneration of traditional healers who mastered herbal formulation is not going well, documentation must be carried out for better knowledge transfer process. This study documented the traditional use of plants to preserve health and fatigue, using data from Ristoja 2012, 2015 and 2017, obtained from the National Institute of Health Research and Development (Indonesian Ministry of Health), data were analyzed descriptively. The data inventory includes grouping of species-family, plant parts, method, frequency, and duration of use, cultivation/non-cultivation, origin, and method of obtaining plants. The results show that the ingredients to preserve health and relieve fatigue have a large diversification, namely 33 families and 60 species. The most widely used are from families Zingiberaceae and Myrtaceae; species Z. officinale, C. domestica, C. xanthorrhiza, P. guajava, S. aromaticum, and S. Polyantum; parts of plant leaves (71,7%) and roots (38,3%;, originally from yards, forests, and fields/gardens; mostly consumed once/day (76,7%). Plants that have been used as ingredients to preserve health and relieve fatigue have several mechanism of action, such as antioxidant, anti-inflammatory, analgesic, glycemic control, blood pressure control, and others.
This study aims to group provinces in Indonesia based on the prevalence of communicable and non-communicable diseases (CDs and NCDs) for disease control efforts. The results of grouping can find out the priority of communicable and non-communicable disease control areas based on seven variables related to infectious diseases and ten variables related to NCDs based on Basic Health Research 2018. A Multidimensional Scaling (MDS) technique was used as the analytical strategy. The MDS analysis resulted in four groups of provinces based on the prevalence of CDs and NCDs. Provincial groups with the highest prevalence of infectious diseases (group 2) were NTT, Central Kalimantan, Maluku, West Papua, and Papua. Provincial groups with the highest NCDs prevalence (group 3) were Bangka Belitung, DKI Jakarta, DI Yogyakarta, East Kalimantan, North Kalimantan, and North Sulawesi. The two groups of provinces were the priority groups in controlling CDs and NCDs. The focus of communicable disease control is URI, hepatitis, malaria, and filariasis in the highest priority groups of provinces with the highest prevalence of infectious diseases. In groups of provinces with the highest NCDs prevalence, the NCD control should focus on asthma, cancer, diabetes, heart disease, hypertension, stroke, chronic renal failure, and joint disease. Further research is suggested adding risk factor analysis variables for CDs and NCDs using the MDS method to help provides a more comprehensive picture of regional groupings. Coordination between central and local governments is needed to accelerate efforts to control CDs and NCDs in priority area groups. Abstrak Tujuan penelitian ini adalah melakukan pengelompokan provinsi di Indonesia berdasarkan prevalensi penyakit menular (PM) dan penyakit tidak menular (PTM) dalam upaya pengendalian penyakit. Hasil pengelompokan dapat diketahui prioritas wilayah pengendalian PM dan PTM berdasarkan tujuh variabel terkait PM dan 10 variabel terkait PTM dari Riset Kesehatan Dasar (Riskesdas) 2018. Jenis penelitian ini adalah cross-sectional menggunakan data sekunder Riskesdas 2018. Analisis pengelompokan provinsi menggunakan Multidimensional Scaling (MDS). Analisis MDS menghasilkan empat kelompok provinsi berdasarkan prevalensi PM dan PTM. Kelompok provinsi dengan prevalensi PM tertinggi (kelompok 2) adalah NTT, Kalimantan Tengah, Maluku, Papua Barat dan Papua. Kelompok propinsi dengan prevalensi PTM tertinggi (kelompok 3) adalah Bangka Belitung, DKI Jakarta, DI Yogyakarta, Kalimantan Timur, Kalimantan Utara, dan Sulawesi Utara. Kedua kelompok provinsi ini merupakan kelompok provinsi prioritas dalam pengendalian PM dan PTM. Pada kelompok provinsi dengan PM tertinggi, fokus pengendalian PM adalah ISPA, hepatitis, malaria dan filariasis. Fokus pengendalian untuk PTM adalah asma, kanker, diabetes, penyakit jantung, hipertensi, stroke, gagal ginjal kronis, dan penyakit sendi. Penelitian selanjutnya disarankan menambahkan variabel analisis faktor risiko PM dan PTM dengan menggunakan metode MDS untuk membantu memberi gambaran yang lebih lengkap pada pengelompokan wilayah. Diperlukan koordinasi sinergi antara pemerintah pusat dan daerah untuk percepatan upaya pengendalian PM dan PTM di kelompok wilayah prioritas.
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