Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: a pooled analysis of 96 population-based studies with 331 288 participants.

BACKGROUND: Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA1c. We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions. METHODS: We used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT ≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori. FINDINGS: Population prevalence of diabetes based on FPG-or-2hOGTT was correlated with prevalence based on FPG alone (r=0·98), but was higher by 2-6 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42·8% of age-sex-survey groups and higher in another 41·6%; in the other 15·6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA1c-based prevalences was partly related to participants\u27 age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8% (95% CI 51·3-54·3%) and a pooled specificity of 99·74% (99·71-99·78%) compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30·5% (28·7-32·3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA1c versus FPG. INTERPRETATION: Different biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA1c-based definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucose-based test. FUNDING: Wellcome Trust, US National Institutes of Health

A century of trends in adult human height

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Differences in Risk Factor of Cardiovascular Disease Risk on Rural and Urban Population

Cardiovascular disease is a global threat. This study aimed to obtain a description of cardiovascular disease pattern among rural and urban population in Ponorogo. Two locations were chosen to represent rural and urban area through cluster sampling. Cross sectional study design was chosen with a sample size of 350 respondents. The research instrument was adopted from WHO STEPS. Difference in prevalence between the two clusters were analyzed with χ2 test, with α=0.05. The result showed that the prevalence smoking and alcohol consumption among males were higher in rural than urban population (p= 0.04 and p=0.012 respectively). The prevalence of unhealthy fruit consumption was higher in both sexes from rural population (p =0.025 and p=0.012). Hypertension was higher among rural female compared to female living in urban area (p=0.024)

The Risk Factor That Affect Children Diarrhea in the Island of Java 2013 (Riskesdas 2013 Data Analysis)

Diarrhea is the biggest cause of infant and child death in Indonesia. In 2013, Indonesian Ministry of Health stated that children diarrhea incidence was still high and rated as public health problem accounting for 6.7 per cent. Two of five provinces with the highest incidence of infant diarrhea in Indonesia was located in the island of Java, even though Java has the biggest achievement in infant and child healthcare coverage as well as the physical quality of drinking water and improved sanitation over the national. Based on these facts, the purpose of this study was to identify risk factors that affect the incidence of children diarrhea in Java 2013. Binary logistic regression was used to statistical analysis with incidence of children diarrhea as response variable while the explanatory variables are age, nutritional status, level maternal education, maternal age, maternal behavior of washing hands, access to sources of drinking water, access to sanitation facilities and household density. The source of data was Riskesdas 2013. The results of this study showed that all the explanatory variables: age, nutritional status, maternal education level, maternal age, maternal behavior of washing hands, access to sources of drinking water, access to sanitation facilities and household density significantly affect the incidence of children diarrhea

Smoking as a Risk Factor of Periodontal Disease

Background. Smoking is a cause of disease in humans is indeed a disease which can be prevented. Nicotine in cigarettes can damage the immune response system and causes constriction of blood vessels, including the blood vessels in the tissues surrounding the tooth. Narrowing of blood vessels, can form a favorable environment for the growth of bacteria that cause periodontal disease. The aim of research to determine whether there is a relationship between smoking and periodontal disease.Methods: the study design is a cross sectional, data retrieved from the secondary data Riskesdas 2013. Samples are household members aged ≥ 15 years with the number of 722 329 people.Results: There was a significant association between smoking and periodontal disease, with a value of p = 0.000 (p <0.05), this means that there is a significant relationship where OR = 4.434 (95%, CI: 4.156-4.731), the meaning that respondents who were 4.43 times to have periodontal diseases (unhealthy periodontal tissues) as compared to not-smoking.Conclusion: In this studi reported the smoking is a risk factor for the periodontal disease, where smoking were four times more likely to have periodontal diseases as compared to not-smoking. (Health Science Journal of Indonesia 2016;7(2):107-112

Risk-sensitive investment in a finite-factor model

A new jump diffusion regime-switching model is introduced, which allows for linking jumps in asset prices with regime changes. We prove the existence and uniqueness of the solution to the risk-sensitive asset management criterion maximisation problem in this setting. We provide an ODE for the optimal value function, which may be efficiently solved numerically. Relevant probability measure changes are discussed in the appendix. The approach of Klebaner and Lipster (2014) is used to prove the martingale property of the relevant density processes.Comment: 23 pages, 1 figur

Analysis of Factors Affecting on Risk Management of Wheat Production Among Wheat Farmers (Razavieh Region, Khorasan-E-Razavi Province, Iran)

The main purpose of this study was to analyze the Factors Affecting on risk management in wheat production among farmers of Razavieh region (Khorasan-E-Razavi province, Iran). Statistical population of the study was 1520 farmers that they had water cultivation. By using of stratified proportional random sampling 156 respondents were selected from 8 villages. For the calculation of the risk-aversion coefficient degree among farmers, the Safety First Rule model was used. The findings revealed that the dominant respondents (65%) were risk-averse. The results of exploratory factorial analysis showed that five factors determined about 74.267 % from total variance for wheat farmers' risk management that consist of: economy & marketing management factor, planting management factor, harvest management factor, infrastructure management of farming and risk-sharing management factor. From among of the above mentioned factors, the most important factor of risk management in study region was factor of economy & marketing management.Wheat farmers, Risk-aversion, Risk management, Drought, Agricultural extension, Farm Management, Risk and Uncertainty, GA, IN,

Factor Models for Portofolio Credit Risk

This paper gives a simple introduction to portfolio credit risk models of the factor model type. In factor models, the dependence between the individual defaults is driven by a small number of systematic factors. When conditioning on the realisation of these factors the defaults become independent. This allows to combine a large degree of analytical tractability in the model with a realistic dependency structure.Default Risk, Portfolio Models

Developing a pressure ulcer risk factor minimum data set and risk assessment framework

AIM: To agree a draft pressure ulcer risk factor Minimum Data Set to underpin the development of a new evidenced-based Risk Assessment Framework.BACKGROUND: A recent systematic review identified the need for a pressure ulcer risk factor Minimum Data Set and development and validation of an evidenced-based pressure ulcer Risk Assessment Framework. This was undertaken through the Pressure UlceR Programme Of reSEarch (RP-PG-0407-10056), funded by the National Institute for Health Research and incorporates five phases. This article reports phase two, a consensus study.DESIGN: Consensus study.METHOD: A modified nominal group technique based on the Research and Development/University of California at Los Angeles appropriateness method. This incorporated an expert group, review of the evidence and the views of a Patient and Public Involvement service user group. Data were collected December 2010-December 2011.FINDINGS: The risk factors and assessment items of the Minimum Data Set (including immobility, pressure ulcer and skin status, perfusion, diabetes, skin moisture, sensory perception and nutrition) were agreed. In addition, a draft Risk Assessment Framework incorporating all Minimum Data Set items was developed, comprising a two stage assessment process (screening and detailed full assessment) and decision pathways.CONCLUSION: The draft Risk Assessment Framework will undergo further design and pre-testing with clinical nurses to assess and improve its usability. It will then be evaluated in clinical practice to assess its validity and reliability. The Minimum Data Set could be used in future for large scale risk factor studies informing refinement of the Risk Assessment Framework