Background: Globally, it was estimated that over 650 million adults 18 years old and older were obese in 2016. It is an increasing global health challenge with a significant health and economic impact. Thus, understanding geographic and socioeconomic disparities in obesity among adults is crucial. Methods: We combined geospatial and quantitative analyses to assess the disparity in obesity across 514 districts in Indonesia. We used the Basic Health Survey (Riskesdas) 2018 for obesity data and the World Bank database for socioeconomic data. Dependent variables included obesity prevalence among all adults (18+ years), males, females, young adults (18–24 years), adults (25–59 years), and older adults (60+ years). Results: We found significant geographic and socioeconomic disparities in adult obesity in Indonesia. In terms of region, districts in Java and Bali had a significantly higher prevalence of obesity than those in Papua, Maluku, and Nusa Tenggara. Districts in Java had 29%, 32%, 60%, and 28% higher prevalence of obesity among all adults, female adults, young adults, and adults. By income, compared to the poorest ones, most affluent districts had a significantly higher prevalence of obesity; they had a 36%, 39%, 34%, 42%, 33%, and 73% higher prevalence of obesity among all adults, males, females, young adults, adults, and older adults. Similarly, by education, compared to the least educated ones, the most educated districts had a significantly higher prevalence of obesity; they had a 34%, 42%, 29%, 36%, and 80% higher prevalence of obesity among all adults, males, females, adults, and older adults. Conclusions: There are significant disparities in adult obesity among 514 districts in Indonesia. Efforts by policymakers and stakeholders are needed to reduce obesity among adults, especially within districts with high prevalence.
The utilization of traditional health services and the use of traditional medicine in Indonesia is still high. There are socio-cultural-natural resources connection in the use of traditional health services and traditional medicine. This study examines Basic Health Research (Riskesdas) 2018 data relating to Indonesia's top ten provinces' relative position, whose community exercises self-traditional health practices and utilizing traditional health services. The analysis was conducted by using PCA-Biplots. Results showed similarities between North Maluku-Maluku-West Papua; Central Sulawesi-South Sulawesi-East Nusa Tenggara-Papua; Special Region of Yogyakarta-Central Java-East Java; South Kalimantan-Banten, while the others were scattered. The utilization of TOGA had a positive correlation with the utilization of traditional medicines. The result of variable diversity identification showed that the community utilizes traditional health services (83.29%) was higher than community exercising self-traditional health practices (73.19%). Actively monitoring, improving information sharing, and educating people on traditional medicine applications, particularly non-communicable disease issues, should be done according to traditional medicine variables' main characteristics in the region. Traditional medicine should serve promotive and preventive health initiatives, as its efficacy in therapeutic use is still debatable. Abstrak Pemanfaatan pelayanan Kesehatan tradisional (yankestrad) dan penggunaan obat tradisional masih cukup banyak. Terdapat keterkaitan sosial, budaya, dan sumber daya alam dalam pemanfaatan yankestrad dan penggunaan pengobatan tradisional lokal. Penelitian ini menganalisis posisi relatif 10 besar provinsi di Indonesia yang melakukan upaya kestrad sendiri dan memanfaatkan yankestrad berdasarkan data Riskesdas 2018. Analisis posisi relatif dalam artikel ini adalah PCA-Biplot. Hasil analisis menunjukkan pola pengelompokan kemiripan sebagai berikut: Malut-Maluku-Pabar; Sulteng-Sulsel-NTT-Papua; DIY-Jateng-Jatim; Kalsel-Banten, dan lainnya tersebar. Variabel pemanfaatan TOGA, semakin positif variabel, maka diikuti oleh pemanfaatan obat tradisional yang semakin baik. Hasil identifikasi keragaman variabel pada pengelompokan 10 besar provinsi dengan masyarakat memanfaatkan yankestrad (83,29%) mempunyai nilai lebih tinggi daripada masyarakat melakukan upaya kestrad sendiri (73,19%). Pemerintah melalui dinas terkait harus melakukan pemantauan, pemberian informasi dan edukasi pengobatan tradisional khususnya untuk penyakit tidak menular dengan penyesuaian terhadap karakteristik pemanfaatan pengobatan tradisional di wilayah tersebut.
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.
Program Rujuk Balik (PRB) merupakan program yang berpotensi memberi banyak manfaat bagi peserta BPJS Kesehatan yang menderita penyakit kronis. Kajian ini bertujuan mengkaji proses pelaksanaan PRB Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan. Data diperoleh dengan panduan wawancara terstruktur yang ditanyakan kepada manajemen BPJS Kesehatan, penanggung jawab PRB di Puskesmas dan Rumah Sakit serta penanggung jawab apotek yang bekerjasama dengan BPJS Kesehatan. Identifikasi kendala proses pelaksanaan PRB menggunakan pendekatan sistem, sedangkan pendekatan Root Cause Analysis digunakan untuk mencari penyebab yang mendasarinya. Hasil penelitian menengarai masalah utama pelaksanaan PRB adalah 1) ketersediaan obat PRB di Puskesmas terbatas, 2) penumpukan pasien di Fasilitas Kesehatan Rujukan Tingkat Lanjut (FKRTL) sehingga waktu tunggu memanjang, 3) notifikasi status pasien “potensi PRB†pada program VCLAIM di FKRTL cenderung diabaikan, 4) rendahnya kepatuhan tenaga medis di FKRTL dalam melengkapi form rujuk balik, dan 5) sosialisasi mekanisme PRB kepada masyarakat masih kurang. Penyebab dasar timbulnya masalah ini adalah tidak adanya metode evaluasi dan sumber daya manusia dari BPJS yang secara khusus melakukan proses pengawasan dan evaluasi berkala. Direkomendasikan kepada BPJS agar menugaskan staf khusus untuk memantau PRB secara berkesinambungan dan menyeluruh, serta bersama kolegium profesional kedokteran untuk segera menyusun standar ketentuan pasien stabil setiap penyakit yang termasuk dalam PRB.
<b>Introduction:</b> COVID-19 spreads quickly, especially in densely populated countries like Indonesia. Understanding transmission factors can support in reducing transmission rates. The purpose of this study is to analyze the various factors that may contribute to the transmission of COVID-19 in Indonesia, especially in the first wave of pandemic.<br /> <b>Methods: </b>This was a cross sectional study design. The sample was selected from the new all record data or the database for recording COVID-19 cases at the health office at the research location by online system. The research was conducted in seven districts and cities across three provinces to obtain an overview of transmission in each regional characteristic. The number of samples was as high as 2,010, with confirmed cases and close contacts in Banda Aceh City, Aceh Besar District, Semarang City, Magelang District, Ternate City, South Halmahera District, and Tidore Islands City. Data analysis was done descriptively and were analyzed using Chi-square and logistic regression with SPSS software.<br /> <b>Results: </b>The multivariate analysis shows that five dominant factors the risk of COVID-19 transmission, there are, age, employment status, activities outside the home, medical history, and vaccination status. Age group of 20-39 years (odds ratio [OR]=1.6-1.7; 95% confidence interval [CI] 1.07-2.71), working of employment status (OR=1.51; 95% CI 1.10-2.07), have a comorbid in medical history (OR=2.39; 95% CI 1.67-3.4), have activities outside home (OR=1.82, 95% CI 1.39-2.39), and have not been vaccinated of COVID-19 (OR=3.03; 95% CI 3.37-3.87) were significantly related with an increased risk of COVID-19 transmission.<br /> <b>Conclusions: </b>productive age,<b> </b>work and activities outside the home, having comorbidities, and not having received COVID-19 vaccination are all risk factors for COVID-19 exposure. Eliminating all of these factors at the same time will undoubtedly be difficult. As a result, cross-sectoral collaboration is needed to control the spread of COVID-19 at the community and individual levels, as well as to support policy interventions to accelerate the elimination of COVID-19 cases.
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