Ditemukan 19 dokumen yang sesuai dengan query :: Simpan CSV
Ryan T. Demmer, Aleksandra M. Zuk, Michael Rosenbaum, Moïse Desvarieux
Abstrak:
Although prevalence and incidence of type 2 diabetes mellitus (T2DM) are reportedly increasing among adolescents, national data are lacking, particularly in regard to undiagnosed T2DM. To estimate the prevalence of diagnosed and undiagnosed T2DM among US adolescents, we analyzed a nationally representative cross-section of 11,888 adolescents aged 12-19 years who received a diabetes interview in the Continuous National Health and Nutrition Examination Survey during 1999-2010. Among them, a random subsample of 4,661 adolescents also had fasting blood samples collected. Persons who reported a previous diabetes diagnosis and were either taking no medication or taking an oral hypoglycemic agent (with or without insulin) were classified as having T2DM; persons who reported using insulin alone were classified as having type 1 diabetes. Undiagnosed diabetes was defined as a fasting plasma glucose concentration of ≥126 mg/dL and was assumed to be type 2. In the fasting subsample, 31 diabetes cases (types 1 and 2) were identified, representing a prevalence of 0.84% (weighted 95% confidence interval (CI): 0.51, 1.40) (276,638 cases; 95% CI: 134,255, 419,020). Estimates of the prevalences of type 1 and type 2 diabetes were 0.48% (95% CI: 0.23, 1.02) and 0.36% (95% CI: 0.20, 0.67), respectively, indicating that T2DM accounted for 43% of all cases. Further, undiagnosed T2DM prevalence was 0.12% (95% CI: 0.05, 0.31), representing 34% of T2DM cases (40,611 cases; 95% CI: 2,850, 78,373). T2DM accounts for approximately half of adolescent diabetes in the United States, and one-third of these cases are undiagnosed.
Read More
AJE Vol.178, No.7
Oxford : Oxford University Press, 2013
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Roy Nusa R.E.S.
AJPPTV Vol.4, No.1
Ciamis : Balitbangkes Depkes RI, 2012
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Mariana Lazo, Ruben Hernaez, Mark S. Eberhardt, Susanne Bonekamp, Ihab Kamel, Eliseo Guallar, Ayman Koteish, Frederick L. Brancati, Jeanne M. Clark
Abstrak:
Previous estimates of the prevalence of nonalcoholic fatty liver disease (NAFLD) in the US population relied on measures of liver enzymes, potentially underestimating the burden of this disease. We used ultrasonography data from 12,454 adults who participated in the Third National Health and Nutrition Examination Survey, conducted in the United States from 1988 to 1994. We defined NAFLD as the presence of hepatic steatosis on ultrasonography in the absence of elevated alcohol consumption. In the US population, the rates of prevalence of hepatic steatosis and NAFLD were 21.4% and 19.0%, respectively, corresponding to estimates of 32.5 (95% confidence interval: 29.9, 35.0) million adults with hepatic steatosis and 28.8 (95% confidence interval: 26.6, 31.2) million adults with NAFLD nationwide. After adjustment for age, income, education, body mass index (weight (kg)/height (m)²), and diabetes status, NAFLD was more common in Mexican Americans (24.1%) compared with non-Hispanic whites (17.8%) and non-Hispanic blacks (13.5%) (P = 0.001) and in men (20.2%) compared with women (15.8%) (P < 0.001). Hepatic steatosis and NAFLD were also independently associated with diabetes, with insulin resistance among people without diabetes, with dyslipidemia, and with obesity. Our results extend previous national estimates of the prevalence of NAFLD in the US population and highlight the burden of this disease. Men, Mexican Americans, and people with diabetes and obesity are the most affected groups.
Read More
AJE Vol.178, No.1
Oxford : Oxford University Press, 2013
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Asia-Pacific J. of Public Health (APJPH), Vol.24, No.6, Nov. 2012, hal. 1002-1012. ( ket. ada di bendel 2010 - 2012 )
[s.l.] :
[s.n.] :
s.a.]
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Anna Maria Sirait
MPPK Vol.23, No.3
Jakarta : Balitbangkes Kemenkes RI, 2013
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Mugi Wahidin; Promotor: Anhari Achadi; Kopromotro: Besral, Soewarta Kosen; Penguji: Atik Nurwahyuni, Mardiati Nadjib, Sudarto Ronoatmodjo, Ekowati Rahajeng; Masdalina Pane
Abstrak:
Read More
Latar belakang: Diabetes Melitus (DM) menjadi salah satu masalah kesehatan masyarakat terbesar di dunia dan di Indonesia yang menjadi target pengendalian secara global dan nasional. Penelitian tentang proyeksi beban DM dengan memasukkan pengaruh faktor risiko dan program pencegahan dan pengendalian DM di Indonesia sangat terbatas. Tujuan penelitian ini adalah untuk membuat model proyeksi beban penyakit Diabetes Melitus di Indonesia berdasarkan faktor risiko dan program pencegahan dan pengendalian DM. Metode: Penelitian ini merupakan penelitian kuantitatif non-experiment menggunakan desain cross sectional study melalui pembuatan model regresi linier ganda dan system dynamics. Model proyeksi prevalens baseline dibuat berdasarkan faktor risiko, program pencegahan dan pengendalian DM. Proyeksi sampai 2045 melibatkan dinamisasi faktor risiko dan program DM, proyeksi penduduk, case fatality rate DM, unit cost DM, standar tarif pemeriksaan gula darah, dan inflasi kesehatan. Faktor risiko termasuk overweight, obesitas sentral, obesitas, konsumsi makanan manis, konsumsi minuman manis, konsumsi makanan berlemak, kurang konsumsi buah dan sayur, kurang aktivitas fisik, hipertensi, dan merokok. Program DM meliputi rasio Posbindu PTM, Desa Ber Posbindu PTM, Pemeriksaan di Posbindu PTM, Puskesmas dengan Pelayanan Terpadu PTM, pemeriksaan rutin gula darah, standar pelayanan minimal (SPM) pelayanan kesehatan DM, dan SPM skrining usia produktif. Model dibuat berdasarkan data dari 205 kabupaten/kota di 33 provinsi di Indonesia. Proyeksi dibuat secara nasional, provinsi, dan kabupaten/kota berupa prevalens, kematian, biaya langsung, dan jumlah dan biaya skrining gula darah. Penelitian ini menggunakan data sekunder dari Riset Kesehatan Dasar (Riskesdas) 2007-2018, BPJS Kesehatan 2016-2020, program P2PTM 2016-2020, dan Pusdatin Kemkes 2019-2021. Unit analisis adalah kabupaten/kota. Hasil: Model proyeksi DM menggunakan regresi linier ganda dengan formula prevalensi DM = -2,212 + 0.216 prevalens overweight +0,017 prevalens obesitas + 0,112 prevalens obesitas sentral +0,019 prevalens konsumsi makanan berlemak – 0,001 Persentase Desa Ber-Posbindu PTM + 0,003 Persentasi Pandu PTM + 1,510 prevalensi rutin diperiksa gula darah – 0.012 cakupan SPM yankes DM + 0,008 cakupan SPM skrining usia produktif. Prevalensi DM di Indonesia diperkirakan meningkat dari 9,19% pada 2020 (18,69 juta kasus) menjadi 16,09% pada 2045 (40,7 juta kasus), naik 75,1% selama 25 tahun, atau 3% per tahun. Prevalensi DM akan lebih rendah menjadi 15,68% atau 39,6 juta kasus (berkurang 5,54%) pada 2045 jika dilakukan intervensi peningkatan cakupan desa ber-posbindu dan SPM yankes DM menjadi 100%, dan menjadi 9,22% atau 23,2 juta kasus (berkurang 42,69%) jika intervensi program tersebut ditambahkan dengan pencegahan laju faktor risiko (overweight, obesitas, obesitas sentral dan konsumsi makanan berlemak). Di tingkat provinsi dan kabupaten/kota, prevalensi dan jumlah kasus meningkat dan sangat bervariasi. Proyeksi jumlah kematian akibat DM di Indonesia meningkat dari 433.752 pada 2020 menjadi 944.468 pada 2045, naik 117% selama 25 tahun atau 4,7% per tahun. Kematian akibat strok pada DM meningkat dari 52,397 pada 2020 menjadi 114,092 pada 2045. Kematian akibat IHD pada DM meningkat dari 35.351 pada 2020 menjadi 76.974 pada 2045. Sedangkan kematian akibat penyakit ginjal kronik pada DM meningkat dari 29.061 pada 2020 menjadi 63.279 pada 2045. Jumlah kematian pada 2045 lebih rendah menjadi 919.206 jika dilakukan intervensi program dan menjadi 537.190 jika dilakukan intervensi program dan menahan laju faktor risiko. Jumlah kematian akibat DM dan komplikasinya di provinsi dan kabupaten/kota meningkat dan sangat bervariasi. Biaya langsung (direct cost) DM meningkat dari Rp 37,36 triliun pada 2020 menjadi Rp 81,38 triliun pada 2045, meningkat 117,76% selama 25 tahun atau 4,71% per tahun. Jika dilakukan intervensi peningkatan program maka dapat diturunkan menjadi Rp 79,31 triliun (berkurang 2,54%) dan menjadi Rp 46,53 triliun (berkurang 42,82%) jika intervensi ditambah menahan laju faktor risiko. Di tingkat provinsi dan kabupaten/kota, biaya langsung DM mengalami kenaikan dan bervariasi antara daerah. Jumlah penduduk berusia 15-39 tahun dengan obesitas dan usia 40 tahun ke atas yang perlu diskrining gula darah di Indonesia pada 2020 diperkirakan 116.387.801 menjadi 171.913.086 orang pada 2045, meningkat 47,8% selama 25 tahun atau 1,9% per tahun. Biaya skrining Rp 2,39 trilliun pada 2020 meningkat menjadi Rp 3,53 trilliun pada 2045. Di provinsi dan kabupaten/kota, jumlah dan biaya skrining meningkat dan bervariasi. Proyeksi DM di Indonesia dan aplikasi perhitungan proyeksi dapat dilihat di www.diabetes-ina.com. Hasil proyeksi sudah dinyatakan sudah baik setelah dibahas dengan para ahli dan mempunyai Mean Absolute Percentage Error (MAPE) sebesar 13% (baik) untuk proyeksi provinsi dan nasional serta 22% (layak) untuk proyeksi kabupaten/kota. Hasil penelitian ini dapat digunakan untuk bahan perencanaan SDM, skrining, dan biaya pengobatan DM di Indonesia baik tingkat pusat, provinsi, maupun kabupaten/kota.
Background: Diabetes Mellitus (DM) is one of the biggest public health problems in the world and in Indonesia which is targeted for control globally and nationally. Research on DM burden projection by including the influence of risk factors and DM prevention and control programs in Indonesia is very limited. The purpose of this study is to make a projection model of the burden of Diabetes Mellitus in Indonesia based on risk factors and DM prevention and control programs. Method: The study was a quantitative non-experiment study using cross sectional study design through the creation of multiple linear regression models and system dynamics. The baseline prevalence projection model is based on risk factors, DM prevention and control programs. Projections until 2045 involved the dynamization of risk factors and DM programs, population projections, DM case fatality rate, DM unit costs, tariffs standard of blood glucose screening, and health inflation. Risk factors included overweight, central obesity, obesity, consumption of sugary foods, consumption of sugary drinks, consumption of fatty foods, lack consumption of fruits and vegetables, lack of physical activity, hypertension, and smoking. The DM program included the ratio of NCD Post (Posbindu), percentage of Village had Posbindu, Examination at Posbindu, Puskesmas with Integrated NCD Services (Pandu), routine blood glucose checks, minimum service standards (SPM) of DM health services, and SPM of productive age screening. The model was created based on data from 205 districts/cities in 33 provinces in Indonesia. Projections was made nationally, provincially, and districts in terms of prevalence, mortality, direct costs, and the number and cost of blood glucose screening. This study used secondary data from Basic Health Research (Riskesdas) 2007-2018, BPJS Kesehatan 2016-2020, NCD programs 2016-2020, and Pusdatin Ministry of Health 2019-2021. The analysis unit is the district/city. Results: DM projection model using multiple linear regression with DM prevalence formula = -2.212 + 0.216 overweight prevalence + 0.017 obesity prevalence + 0.112 central obesity prevalence + 0.019 prevalence of fatty food consumption – 0.001 percentage of villages with Posbindu + 0.003 NCD integrated services percentage + 1.510 prevalence of routine blood glucose checks – 0.012 SPM coverage of DM services + 0.008 SPM of productive age screening coverage. The prevalence of DM in Indonesia is estimated to increase from 9.19% in 2020 (18.69 million cases) to 16.09% in 2045 (40.7 million cases), increase 75.1% over 25 years, or 3% per year. The prevalence of DM will be lower to 15.68% or 39.6 million cases (reduced by 5.54%) in 2045 if interventions are carried out to increase the coverage of Posbindu villages and SPM DM services to 100%, and to 9.22% or 23.2 million cases (reduced by 42.69%) if the program interventions are added with prevention of risk factor rates (overweight, obesity, central obesity and consumption of fatty foods). At the provincial and district/city levels, the prevalence and number of cases are increasing and vary greatly. The projected number of deaths due to DM in Indonesia increases from 433,752 in 2020 to 944,468 in 2045, increase 117% over 25 years or 4.7% per year. Deaths due to stroke among DM increases from 52,397 in 2020 to 114,092 in 2045. Deaths from IHD among DM increases from 35,351 in 2020 to 76,974 in 2045. Meanwhile, deaths from chronic kidney disease among DM increases from 29,061 in 2020 to 63,279 in 2045. The number of deaths in 2045 could be lower to 919,206 if program interventions are carried out and to 537,190 if program interventions are carried out and halt the rate of risk factors. The number of deaths due to DM and its complications in provinces and districts / cities is increasing and varies greatly. DM direct costs increased from Rp 37.36 trillion in 2020 to Rp 81.38 trillion in 2045, an increase of 117.76% over 25 years or 4.71% per year. If the program improvement intervention is carried out, it can be reduced to Rp 79.31 trillion (reduced by 2.54%) and to Rp 46.53 trillion (reduced by 42.82%) if the intervention is added to halt the rate of risk factors. At the provincial and district/city levels, DM direct costs have increased and vary between regions. The number of people aged 15-39 years with obesity and aged 40 years and above who need to be screened for blood glucose in Indonesia in 2020 is estimated at 116,387,801 to 171,913,086 people in 2045, an increase of 47.8% over 25 years or 1.9% per year. Screening costs of Rp 2.39 trillion in 2020 will increase to Rp 3.53 trillion in 2045. In provinces and districts, the number and cost of screening are increasing and varying. DM projections in Indonesia and projection calculation applications can be seen at www.diabetes-ina.com. The projection results have been declared good after discussion with experts and have an Absolute Mean Percentage Error (MAPE) of 13% (good) for provincial and national projections and 22% (feasible) for district/city projections. The results of this study can be used for human resource planning, screening, and DM treatment costs in Indonesia at the central, provincial, and district / city levels.
D-478
Depok : FKM-UI, 2023
S3 - Disertasi Pusat Informasi Kesehatan Masyarakat
☉
Paul Gustafson, Mark Gilbert, Michelle Xia, Warren Michelow, Wayne Robert, Terry Trussler, Marissa McGuire, Dana Paquette, David M. Moore, Reka Gustafson
Abstrak:
Venue sampling is a common sampling method for populations of men who have sex with men (MSM); however, men who visit venues frequently are more likely to be recruited. While statistical adjustment methods are recommended, these have received scant attention in the literature. We developed a novel approach to adjust for frequency of venue attendance (FVA) and assess the impact of associated bias in the ManCount Study, a venue-based survey of MSM conducted in Vancouver, British Columbia, Canada, in 2008-2009 to measure the prevalence of human immunodeficiency virus and other infections and associated behaviors. Sampling weights were determined from an abbreviated list of questions on venue attendance and were used to adjust estimates of prevalence for health and behavioral indicators using a Bayesian, model-based approach. We found little effect of FVA adjustment on biological or sexual behavior indicators (primary outcomes); however, adjustment for FVA did result in differences in the prevalence of demographic indicators, testing behaviors, and a small number of additional variables. While these findings are reassuring and lend credence to unadjusted prevalence estimates from this venue-based survey, adjustment for FVA did shed important insights on MSM subpopulations that were not well represented in the sample.
Read More
AJE Vol.177, No.10
Oxford : Oxford University Press, 2013
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Tiersa Vera Junita; Pembimbing: Helda; Penguji: Nurhayati Adnan, Ratna Djuwita, Robert M Sarangih
T-4734
Depok : FKM-UI, 2016
S2 - Tesis Pusat Informasi Kesehatan Masyarakat
☉
Sitti Chadijah ... [et al.]
MPPK Vol.24, No.1
Jakarta : Balitbangkes Kemenkes RI, 2014
Indeks Artikel Jurnal-Majalah Pusat Informasi Kesehatan Masyarakat
☉
Melyanty Toding Rante; Pembimbing: Mondastri Korib Sudaryo; Penguji: Ratna Djuwita, Adhi Dharmawan Tato
S-6528
Depok : FKM UI, 2011
S1 - Skripsi Pusat Informasi Kesehatan Masyarakat
☉
