The Relationship Between Smoking as a Modifiable Risk Factor and Chronic Complications on Elderly with Type 2 Diabetes Mellitus

Smoking is known as a variable that can be changed through a specific intervention activity. Recently in Indonesia, research related to chronic complication among elderly with type 2 Diabetes Mellitus (DM) was not available. This research has objective in exploring the risk of smoking towards chronic complication among elderly with type 2 DM. This research was using Riset Kesehatan Dasar (Riskesdas) in 2007. Riskesdas is a representative Indonesia Health Survey. 1,565 elderly (aged 60++ years) with type 2 DM have selected by random. 70-80% of the elderly have Chronic Complications and 32.11% of the sample is smokers. The elderly who smoke more than 24 cigarettes per day have risk 2.5 (95% CI, 1.54-3.97), smoker 1-12 cigarettes per day, and smoker 13-24 cigarettes per day have risk 1.3 and 1.6 respectively to get chronic complication compared with those who do not smoke, controlled by age, obesity, and physical activity. The proportion of smokers among elderly with type 2 DM is high, most of them are low education, low socioeconomic status, lack of access to the health services, low of physical activity, and low consume vegetables and fruit. Smoking increases the risk of chronic complication of type 2 DM

The Effect of Medical Check-up and Basic Physical Activities Daily Living: Panel Study on Among Indoesian Elderly 1993-2000

In the 21st Century, Indonesia becomes the fourth biggest ageing country in the World as reported by the Second World Assembly on Ageing (2002). The Indonesian Household Health Survey (2001) reported 88,9% of the elderly suffered from disability (including mild disability). In the US health services, medical check-up had significantly reduced disability from 22,1% in 1984 to 16% in 2002 (DHHS, 2003).The study has aims to confirm the relationship between medical check-up and basic physical activities daily living among elderly in Indonesia. Data used the Indonesian Family Life Survey. Those who were 55 years or older and active in 1993 were included for the study. In total, 1,541 were sampled. Multilevel logistic regression analyses were applied for modeling basic physical activities daily living. Among the sample, there were 1464 (89,54 %) in 2000 still active on basic physical activities daily living, and giving an incidence rate of 3.2% per year for limitation on basic physical activities daily living. This rate indicates that in a year, out of every 100 active elderly in Indonesia, between three and four elderly would have developed limited physical activity. The multivariate analysis showed that there were significant effects of medical check-up on maintaining in basic physical activities daily living among elderly (OR=1,85; 95% CI: 1,64 – 2,13). This suggests that elderly with routine medical check-up would have a chance to maintain their ability to perform daily activity almost twice compared to those who did not receive routine medical check-up

Determinan Komplikasi Kronik Diabetes Melitus pada Lanjut Usia

Indonesia menghadapi jumlah penduduk lanjut usia (lansia) yang semakin meningkat dan diikuti oleh peningkatan frekuensi penyakit tidak menular kronis atau multimorbiditas. Penelitian ini bertujuan untuk mengetahui prevalensi dan faktor yang berhubungan komplikasi kronis pada lansia penderita diabetes melitus. Penelitian ini menggunakan data Riset Kesehatan Dasar (Riskesdas) Tahun 2007 dengan desain cross sectional representatif Indonesia dan metode cluster 2 tahap untuk pengambilan sampel. Sampel adalah 1.565 lansia penderita diabetes melitus. Metode analisis yang digunakan meliputi analisis deskriptif dan multivariat. Hasil analisis menunjukkan bahwa prevalensi komplikasi kronis pada lansia adalah sekitar 73,1%, dengan hipertensi sebagai komplikasi terbanyak. Berdasarkan analisis multivariat diketahui pula bahwa faktor-faktor yang berhubungan dengan komplikasi diabetes adalah usia, jenis kelamin, obesitas, merokok, dan aktivitas fisik dan faktor utama yang berhubungan adalah merokok (OR = 2,48). Hasil penelitian menyarankan program untuk mencegah kesakitan dan komplikasi diabetes pada lansia perlu ditingkatkan. Saat ini program Kementerian Kesehatan Republik Indonesia yaitu CERDIK meliputi cek kesehatan secara berkala, enyahkan asap rokok, rajin berolahraga, diet sehat kalori seimbang, istirahat yang cukup dan kendalikan stres perlu diperluas. Indonesia faces a growing number of elderly people is increasing, with increasing elderly, not infectious diseases increase chronic or multimorbidity, there by the study has aims to explore the prevalence of Chronic Complications on elderly with diabetes mellitus and related factors. The research used data from National Basic Health Research 2007. National Basic Health Research is a cross-sectional design survey, two stage cluster method for sampling. The result is shown that the prevalence of chronic complication on the elderly with diabetes mellitus is 73.1%. Hypertension disease is the most of chronic complication that has been frequent appeared on elderly with diabetes mellitus. Based on multivariate analysis revealed to diabetes mellitus complication related with age, gender, obesity, smoking, and physical activity. The study purposes to emphasize of prevention and promotion program such as CERDIK program from Ministry of Health, Republic of Indonesia. The CERDIK program has many intervention programs, for example, reducing smoking, delegating regularly exercise, balancing healthy-diet calorie, resting and taking control of stress

Kehamilan yang Tidak Diinginkan dan Berat Badan Lahir Bayi

Berat badan lahir dianggap faktor penentu yang paling penting dari kesehatan dan kelangsungan hidup anak. Penelitian ini bertujuan untuk mempelajari besar risiko kehamilan tidak diinginkan terhadap berat bayi berdasarkan persepsi ibu di Indonesia tahun 2010 beserta faktor-faktor perancunya. Penelitian ini merupakan penelitian analitik dengan menggunakan data sekunder dari Riset Kesehatan Dasar tahun 2010. Namun, studi ini memiliki variabel dari hasil kehamilan sehingga memungkinkan menggunakan desain penelitian kohort retrospektif. Berdasarkan hasil analisis multivariat ditemukan bahwa ibu yang mengalami kehamilan tidak diinginkan berisiko melahirkan bayi dengan berat badan lahir rendah (BBLR) yang didasarkan pada persepsi ibu sekitar 1,27 kali lebih besar daripada ibu yang mengalami kehamilan diinginkan setelah dikontrol oleh usia ibu, usia kehamilan, frekuensi periksa kehamilan di pelayanan antenatal dan jumlah pil zat besi. Pada model probabilitas, risiko ibu dalam melahirkan BBLR pada kelompok kehamilan tidak diinginkan (4,42%), kelompok kehamilan diinginkan (3,52%) dengan kondisi usia ibu yang tidak berisiko (20 - 34 tahun), usia kehamilan cukup bulan, frekuensi pelayanan antenatal adekuat minimal 4 kali dan pil zat besi minimal 90 hari.Birth weight is considered to be one of the most important determinants of health and child survival. Therefore, this study aimed to study to explore the risk of unintended pregnancy on infant weight based on the perception of the mother in Indonesia in 2010 along with the risk of the counfonders. This study is analytical research and used data from Indonesia Basic Health Survey. This study had a variable pregnancy outcomes, therefore a retrospective cohort study design was performed in this study. Based on the multivariable analysis was found the risk ratio gave low birth weight on mothers who experiences unintended pregnancy 1,27 times compared mothers who have experienced desired pregnancy after adjustment by age of mother, age of pregnancy, antenatal care and the amount of iron tablets. The probability derived giving birth to LBW babies in mothers during her intended pregnancy is 4.42% compared 3.52% among mothers with desired pregnancy with certain conditions, such as age group (20 - 34 years), adequate of pregnancy age, four times antenatal care frequency, and adequate of the amount of zinc tablets minimum in 90 days

Trigliserida Sebagai Faktor Prognosis Untuk Hipertensi Tidak Terkendali Pada Wanita Pasca Menopause Di Kota Bogor, Tahun 2014

Further analysis aimed to determine the new cut-off correlation between blood triglyceride levels withuncontrolled hypertension among 888 postmenopausal women from two-year follow up of the cohort studyin Bogor. Uncontrolled hypertension was defined as the average of systolic and diastolic are >140mmHgand >90mmHg consecutively with no underlying diseases and systolic is >130mmHg with co-morbidityat the end of 2-year follow up. The covariate variables included demography, behavior and biologicalfactors. The new triglyceride\u27s cut off was determined by ROC curve with 65% sensitivity and 68%specificity. Data were analyzed with multiple logistic regression. Blood triglyceride level significantlycorrelated with uncontrolled hypertension (p=0.007) after adjusted with LDL, postprandial blood sugarand sodium intake. Triglyceride levels of 108-149mg/dl resulted in OR of 1.54 (95% CI 0.95 to 2.48),150-199mg/dl showed OR of 2.04 (95% CI 1.06 to 3.93) and level of >200 indicated an OR 2.1 (95% CI1.02 to 4.30) compared to normal level (<108mg/dl). Triglyceride level of 108mg/dl is a new cut-off todetermine uncontrolled hypertension in postmenopausal women in the study area. Blood triglyceride\u27slevel can be used as a prognostic factor for hypertensive patients to monitor blood pressure increment

The state of health in Indonesia's provinces, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Analysing trends and levels of the burden of disease at the national level can mask inequalities in health-related progress in lower administrative units such as provinces and districts. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to analyse health patterns in Indonesia at the provincial level between 1990 and 2019. Long-term analyses of disease burden provide insights on Indonesia's advance to universal health coverage and its ability to meet the United Nations Sustainable Development Goals by 2030. Methods We analysed GBD 2019 estimated cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 286 causes of death, 369 causes of non-fatal health loss, and 87 risk factors by year, age, and sex for Indonesia and its 34 provinces from 1990 to 2019. To generate estimates for Indonesia at the national level, we used 138 location-years of data to estimate Indonesia-specific demographic indicators, 317 location-years of data for Indonesia-specific causes of death, 689 location-years of data for Indonesia-specific non-fatal outcomes, 250 location-years of data for Indonesia-specific risk factors, and 1641 location-years of data for Indonesia-specific covariates. For subnational estimates, we used the following source counts: 138 location-years of data to estimate Indonesia-specific demographic indicators; 5848 location-years of data for Indonesia-specific causes of death; 1534 location-years of data for Indonesia-specific non-fatal outcomes; 650 location-years of data for Indonesia-specific risk factors; and 16 016 location-years of data for Indonesia-specific covariates. We generated our GBD 2019 estimates for Indonesia by including 1 915 207 total source metadata rows, and we used 821 total citations. Findings Life expectancy for males across Indonesia increased from 62·5 years (95% uncertainty interval 61·3–63·7) to 69·4 years (67·2–71·6) between 1990 and 2019, a positive change of 6·9 years. For females during the same period, life expectancy increased from 65·7 years (64·5–66·8) to 73·5 years (71·6–75·6), an increase of 7·8 years. There were large disparities in health outcomes among provinces. In 2019, Bali had the highest life expectancy at birth for males (74·4 years, 70·90–77·9) and North Kalimantan had the highest life expectancy at birth for females (77·7 years, 74·7–81·2), whereas Papua had the lowest life expectancy at birth for males (64·5 years, 60·9–68·2) and North Maluku had the lowest life expectancy at birth for females (64·0 years, 60·7–67·3). The difference in life expectancy for males between the highest-ranked and lowest-ranked provinces was 9·9 years and the difference in life expectacy for females between the highest-ranked and lowest-ranked provinces was 13·7 years. Age-standardised death, YLL, and YLD rates also varied widely among the provinces in 2019. High systolic blood pressure, tobacco, dietary risks, high fasting plasma glucose, and high BMI were the five leading risks contributing to health loss measured as DALYs in 2019. Interpretation Our findings highlight that Indonesia faces a double burden of communicable and non-communicable diseases that varies across provinces. From 1990 to 2019, Indonesia witnessed a decline in the infectious disease burden, although communicable diseases such as tuberculosis, diarrhoeal diseases, and lower respiratory infections have remained a main source of DALYs in Indonesia. During that same period, however, all-ages death and disability rates from non-communicable diseases and exposure to their risk factors accounted for larger shares of health loss. The differences in health outcomes between the highest-performing and lowest-performing provinces have also widened since 1990. Our findings support a comprehensive process to revisit current health policies, examine the root causes of variation in the burden of disease among provinces, and strengthen programmes and policies aimed at reducing disparities across the country. Funding The Bill & Melinda Gates Foundation and the Government of Indonesia. Translation For the Bahasa Indonesia translation of the abstract see Supplementary Materials section

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic