Hubungan Pengetahuan, Sikap, dan Perilaku Tentang Karies Gigi terhadap Indeks Dmf-t pada Siswa SD Kelas VI di Daerah Kumuh dan Tidak Kumuh Kecamatan Penjaringan Jakarta Utara

In Indonesia town people are being increase almost twofold. Than many people have to stay in the slum areas. The health of teeth and mouth service in health centres (puskesmas) is given toothache for low income people and specially for anxious people to toothache. The percentage of the toothache, pulpitis and periapical membrane diseases for people took the fourth rank from nine non contagious diseases at Kecamatan Penjaringan are 2.9% in 1999. The objectives of the research were to determine the relations of knowledge, attitude, and behavior aspect about dental caries with DMF-T index. The other objecllves were to determine the classification of slum and non­ slum areas regarding the knowledge, attitude, and behavtor about caries on the elementary school students 6th class. Results by simple linear regression showed that DMF-T index were influenced by variables of knowledge (p = 0.041). Results by multiple linear regression showed that DMF-T index is influenced by variable of knowledge and attitude about dental (p knowledge = 0.010 and p attitude = 0.046). Results by t test proved there were the significant differences in the knowledge and attitude between elementary school students 6th class in the slum and non-slum area (p knowledge= 0.001 and p attitude= 0.029). Dental healthy of elementary school students 6th class were mfluenced by knowledge. If the variables of knowledge, attitude, and behavior were analyzed together, just variables of knowledge and attitude that influenced caries dentis (DMF-T index). The classification slum and non-slum areas influenced the knowledge and attitude of the students about dental caries

Analisis Kesesuaian Klaim dengan Realitas Pembayaran Ppk Rujukan dalam Jaminan Kesehatan Masyarakat Miskin

The main goal of health development in lndonesia is providing quality health care and assuring community access to equal health services for all citizen (universal coverage). In assuring the access to health services for the poor. Ministry of Health has launched special health insurance program for the poor (Askeskin). PT Askes was assigned by MOH to manage this program. Therefore, it is very important to improve facilities and management capabilities of health insurance administering bodies and health care providers. These include, improvement in case management, hospital accounting system, medical record, etc. This will be very useful for verification process and reducing the fraud and abuse. This study was conducted in order to provide valuable input for the Improvement of financing mechanism and payment system of referral providers in health insurance program for the poor (Askeskin). The objectives of this study are to calculate hospital claim on case management of Askeskin members and its real payment by PT Askes and to calculate the differences between claim and reimbursement (real payment) based on hospital components. The study design is cross-sectional. A Stratified Random Sampling method was conducted to select the study sites based on Human Development Index (HOI) and Fiscal Capacity (refers to Ministry of Finance Data) of district and city. Districts and cities were then classified into high, middle, or low level. The 3 selected study sites were: Kampar District (HPI 34,1) in Riau Province which represent high HOI; North Bengkulu District (HPI: 30.4) in Bengkulu province which represent middle HOI, and Pontianak City (HPI: 27.7) in West Kalimantan Province which represent low HOI. The results show that tariff agreement of case management for Askeskin members was not in accordance with local real condition. Therefore, clear operational and technical Askeskin guidelines are needed to gain similar perception between PT Askes and health care providers· beside Improvement of socialization activities to the community. The amount of differences between claim and reimbursement varied among study sites. The difference was influenced by following factors: (1) existed guidelines that were not suitable with local specific real demand and (2) disparity among hospital facilities. Hospital with limited facility has difficulty to refer patient to another closed hospital which doesn't have contract with PT Askes. Furthermore, in some cases hospital with good facility cannot optimalize using their advanced equipment for treatment, because not stated in the contract with PT Askes. Contract review, tariff adjustment, and re-negotiation between hospitals and PT Askes should be encouraged to provide better services for Askeskin members

Benefit Monitoring and Evaluation (Bme): a Case Study

Theoretically, the ultimate benefits of health development projects are reflected as increased incomes or tangible improvements in quality of life. They will only be forth coming if services provided by project have more direct effect for those who use the services. However the effects of health programs might be direct or indirect so that they are difficult to be measured comparing with other sectors. The study team conducted a study on Benefit Monitoring and Evaluation (BME) by using The Rural Health and Population Project (ADB Ill-Loan No.1299-lno) as objective of the study. The study was conducted in the year 2000, however, the results of this study is relevant to be published due to it is difficult to find the references, which showed the experiences of the BME study in the health sector. The prime objective of the Rural Health and Population Project was to assist the Government in raising the health status of the population and reducing total fertility rates through the improvement of quality, relevance, efficiency and effectiveness of community-based rural health and family planning (FP) delivery system. The Project adopted the following three strategic initiatives: (1) to change the role and orientation of the district hospital; (2) to improve community-based rural health, nutrition and FP service delivery and capabilities; and (3) to strengthen the organization and management at district level. To examine the extent, to which these reforms through the project implementation have intended benefits and effects, both individually and collectively, the evaluation team conducted a study to evaluate the progress on the field implementation of these reforms in the area of the project. The evaluation of benefits of projects will be conducted, whether or not the benchmarks of benefit monitoring was adequately documented when the project is prepared. The study team using a conceptual model called a Logical Framework (LF) a set of cause-and-effect relationship through which resources provided through the project are transformed so they contribute to achieving the objective of the intervention, and assumptions about external factors which affect these relationships. ALF enables one to describe a project in terms of three sequential relationships: inputs to outputs, outputs to effects and effects to impact. Assessment was used benchmark that information available in the project documents. Addition primary and secondary data needed was collected in the locations of the project. The study identified three group or stakeholders which have benefits of the projects; (1) the local authority; (2) The health provider; (3) the community or recipients. By using the benchmark which available in the regularly reporting and recording system the benefits of the project was assessed as; (1) no benefit; (2} minimal benefit; (3) and optimal benefit. Results of the study showed that (1) the local authority in general have optimal benefit, however several activities have minimal benefits; (2) the health providers have minimal benefit, some showed have no benefit, it is only improvement of medical services have an optimal benefit; (3) the community or recipients almost have optimal benefit

Risiko Penyakit Jantung pada Perokok Peserta Program Jamkesmas

Background: For years heart disease prevalence have increased. Results of Basic Health Research (known as riset Kesehatan Oasar-Riskesdas) 2007 showed that heart disease is the second major cause of death after stroke inmortality cases in Indonesia. As a matter of fact, other researches results indicate that smoking as a risk factor for heart disease and most of smoker are poor people. Indonesian government guarantees the poor to get free medical treatment through Jamkesmas program (social assistance program in health sector for the poor). In 2007 Cipto Mangunkusumo National Hospital (RSCM) noted that 60% of heart disease patients treated in this hospital is poor. The trends of cases and government budget to control heart disease are always increasing. Objective of this study was to know smoker prevalence, food consumption and activity for participants JAMKESMAS and also to know risk factor of heart disease for them Methods: Cross sectional was utilized as the study design The Riskesdas and Susenas 2007 data was used in this research. All research variables had been analyzed in univariat, bivariat (X2 test) and multivariat (logistic regression) by using a complex sample in SPSS v16. Results: The results shows that smokers Jamkesmas are most in aged 3-4 years do enough physical activities, and less eating fruits and vegetables, 1.8% of Jamkesmas smokers had diagnosed heart disease by health personnel. Based on statistical analysis, physical activity, fruit and vegetable consumption, smoking, gender and age is risk factor of heart disease

Identifikasi Wilayah dengan Permasalahan Kesehatan Anak Balita di Provinsi Jawa Timur

Background: Government Regulation no. 38 year 2007 about the distribution of governmental power between central, provincial and district/town was one reference for government. Despite of decentralization was expected to remain the relevance from the administration. Meanwhile, to view the performance or measured the success of development held by local districts, especially in the field of health has issued the Ministerial Regulation Rl No. 741/Menkes/Per/VII/2008 on Minimum Service Standards (SPM) in the Health Sector which is an effort to accelerate the achievement of the MDGs in 2015. Child health problems focused on the decline in mortality because even the trend was declining but the achievement is still rae from target, particularly the MDGs in 2015, either RPJPM or Minimum Service Standards (SPM). When in handling found of resource limitation, it is necessary to scale the priority to handle with the regional approach or program. The objective of the study is to know distribution areas and offers an alternative method of diagnosing the area of Children under 5 health problems so that it shows children under 5 priority areas. Methods: The data for this analysis from a survey called RISKESDAS 2007 with sample unit is children under 5. Variables used are; state of poor and malnutrition, the completed Immunization coverage, posyandu utilization, morbidity (diarrhea, pneumonia and TB), clean and healthy lifestyle. lack of clean water, lack of sanitation in the districts of East in Java. Results: This result is several thematic maps when it is overlay; find the two districts in the eastern part is relatively problematic area among the districts and other towns in East Java. Key words: Spatial analysis, children under 5 health, East Jav

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017

BackgroundPast research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries.MethodsWe reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).FindingsIn 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).InterpretationInjuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.</jats:sec