scholarly journals Corrigendum to “A simple nomogram for identifying individuals at high risk of undiagnosed diabetes in rural population” [Diabet. Res. Clin. Pract. 180 (2021) 109061]

2021 ◽  
pp. 109184
Author(s):  
Tran Quang Binh ◽  
Pham Tran Phuong ◽  
Nguyen Thanh Chung ◽  
Bui Thi Nhung ◽  
Do Dinh Tung ◽  
...  
Keyword(s):  
High Risk ◽  
Rural Population ◽  
Undiagnosed Diabetes

A simple nomogram for identifying individuals at high risk of undiagnosed diabetes in rural population

2021 ◽  
pp. 109061
Author(s):  
Tran Quang Binh ◽  
Pham Tran Phuong ◽  
Nguyen Thanh Chung ◽  
Bui Thi Nhung ◽  
Do Dinh Tung ◽  
...  
Keyword(s):  
High Risk ◽  
Rural Population ◽  
Undiagnosed Diabetes

Prediabetes, undiagnosed diabetes and diabetes risk in Italy in 2017–2018: results from the first National screening campaign in community pharmacies

2021 ◽  
Author(s):  
P Brunetti ◽  
L Baldessin ◽  
S Pagliacci
Keyword(s):  
High Risk ◽  
Diabetes Risk ◽  
World Health ◽  
Undiagnosed Diabetes ◽  
Community Pharmacies ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Health Organization ◽  
Very High

Abstract Background Effective policies for diabetes prevention remain urgent. We conducted a mass screening campaign in Italy to identify subjects potentially having undiagnosed diabetes, prediabetes or at diabetes risk. Methods This cohort study was conducted in community pharmacies joining the unitary National federation of pharmacy holders (Federfarma) and participating in the 7-day screening campaign ‘DiaDay’ in 2017–2018. Capillary blood glucose levels and the risk of developing diabetes in 10 years (through the Finnish Diabetes Risk Score) were assessed. Results 145 651 volunteers aged ≥20 years without known diabetes were screened at 5671 community pharmacies in 2017 and 116 097 at 5112 in 2018. Overall, 3.6% had glucose values suggestive of undiagnosed diabetes; under fasting conditions (N = 94 076), 39.9% and 16.4% had values suggestive of prediabetes by the American Diabetes Association and the World Health Organization criteria, respectively. Of those without diabetes (N = 252 440), 19.2% had scores compatible with a high risk (1:3) and 2.7% with a very high risk (1:2) of developing the disease; in the prediabetes group, the risk rose with higher impaired fasting glucose values. Conclusions DiaDay, the first National screening campaign, highlights the need to screen the population and the key role of the pharmacist both in screening activities and education promotion.

scholarly journals Prevalence of diagnosed diabetes and associated risk factors: Evidence from the large-scale surveys in India

2017 ◽  
Vol 05 (01) ◽  
pp. 028-036 ◽  
Author(s):  
Saddaf Akhtar ◽  
Preeti Dhillon
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Large Scale ◽  
Multinomial Logistic Regression ◽  
Local Level ◽  
Diabetes Prevalence ◽  
World Health ◽  
Undiagnosed Diabetes ◽  
Newly Diagnosed ◽  
Associated Risk Factors

Abstract Context: India has observed the most devastating increases in the burden of diabetes in the contemporary era. However, so far, the comparable prevalence of diabetes is only available for limited geography. Aims: The present paper provides comparable estimates of diabetes prevalence in states and districts of India and examines the associated risk factors with newly diagnosed and self-reported diabetes. Setting and Design: The study uses clinical, anthropometric, and biochemical data from District Level Household and Facility Survey (2012–2013) and Annual Health Survey (2014). Subjects and Methods: The paper analyses the information on glucose level of the blood sample and defines diabetes as per the World Health Organization (1999) criteria. It applies multinomial logistic regression to identify the risk factors of diabetes. Results: The study estimates 7% adults with diabetes in India, with a higher level in urban (9.8%) than in the rural area (5.7%), a higher proportion of males (7.1%) than females (6.8%). Widowed, older persons, and persons with high blood pressure have very high risk of both diagnosed and self-reported diabetes. Comparing to Hindus, Muslims and Christians have higher, and Sikhs have less risk of diabetes. Further, corresponding to general caste, scheduled castes, and other backward classes have a high risk of newly diagnosed but the lower risk of self-reported diabetes. Conclusions: The list of districts and states with alarming diabetes prevalence is the valuable information for further programs and research. A significant population with undiagnosed diabetes reflects an urgent need to strengthen the diagnostics at the local level and for those who need them most.

scholarly journals Waist:height ratio: a superior index in estimating cardiovascular risks in Turkish adults

2013 ◽  
Vol 17 (10) ◽  
pp. 2246-2252 ◽  
Author(s):  
Reci Meseri ◽  
Reyhan Ucku ◽  
Belgin Unal
Keyword(s):  
Blood Pressure ◽  
High Risk ◽  
Risk Score ◽  
Framingham Risk Score ◽  
Undiagnosed Diabetes ◽  
Anthropometric Measurement ◽  
Cardiovascular Risks ◽  
Framingham Risk ◽  
Chd Risk ◽  
Diabetes Status

AbstractObjectiveTo determine the best anthropometric measurement among waist: height ratio (WHtR), BMI, waist:hip ratio (WHR) and waist circumference (WC) associated with high CHD risk in adults and to define the optimal cut-off point for WHtR.DesignPopulation-based cross-sectional study.SettingBalcova, Izmir, Turkey.SubjectsIndividuals (n 10 878) who participated in the baseline survey of the Heart of Balcova Project. For each participant, 10-year coronary event risk (Framingham risk score) was calculated using data on age, sex, smoking status, blood pressure, serum lipids and diabetes status. Participants who had risk higher than 10 % were defined as ‘medium or high risk’.ResultsAmong the participants, 67·7 % were female, 38·2 % were obese, 24·5 % had high blood pressure, 9·2 % had diabetes, 1·5 % had undiagnosed diabetes (≥126 mg/dl), 22·0 % had high total cholesterol and 45·9 % had low HDL-cholesterol. According to Framingham risk score, 32·7 % of them had a risk score higher than 10 %. Those who had medium or high risk had significantly higher mean BMI, WHtR, WHR and WC compared with those at low risk. According to receiver-operating characteristic curves, WHtR was the best and BMI was the worst indicator of CHD risk for both sexes. For both men and women, 0·55 was the optimal cut-off point for WHtR for CHD risk.ConclusionsBMI should not be used alone for evaluating obesity when estimating cardiometabolic risks. WHtR was found to be a successful measurement for determining cardiovascular risks. A cut-off point of ‘0·5’ can be used for categorizing WHtR in order to target people at high CHD risk for preventive actions.

scholarly journals Anthropometric Predictors of High Risk of Obstructive Sleep Apnea Syndrome in a Rural Population

2012 ◽  
Vol 19 (1) ◽  
pp. 7-16
Author(s):  
Otilia Niţă ◽  
Lidia Graur ◽  
Dana Popescu ◽  
Alina Popa ◽  
Laura Mihalache ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
High Risk ◽  
Obstructive Sleep Apnea Syndrome ◽  
Rural Population ◽  
Sleep Apnea Syndrome ◽  
Berlin Questionnaire ◽  
Height Ratio ◽  
Obstructive Sleep ◽  
Apnea Syndrome

Anthropometric Predictors of High Risk of Obstructive Sleep Apnea Syndrome in a Rural PopulationObjective. To evaluate which anthropometric parameter better predicts the high risk of obstructive sleep apnea syndrome (OSA) in a rural population. Material and Method. 254 subjects were enrolled. We measured weight, height, waist circumference (WC) and neck circumference (NC) and calculated body mass index (BMI), waist-to-height ratio (WHtR) and neck circumference/height ratio (NC/Height). The risk of OSA was assessed by using Berlin Questionnaire. Results. Subjects with high risk of OSA had a significant higher BMI, WC, WHtR, NC, and NC/Height. A higher percentage of those with large WC (≥80cm and ≥94cm for women and men, respectively) (p<0.001), WHtR ≥0.5 (p<0.001), NC ≥40cm (p=0.004), NC/Height ratio ≥0.23 (p=0.002) had a high risk of OSA. Using ROC curves of anthropometric parameters studied we found that WHtR was the best predictor for high risk of OSA, with AUC of 0.760, 95% CI: 0.699 to 0.815. Conclusions. WHtR was the best predictor for high risk of OSA as assessed by the Berlin Questionnaire.

EXERCISE ADHERENCE AND COMPLIANCE IN A HIGH RISK RURAL POPULATION

1998 ◽  
Vol 30 (Supplement) ◽  
pp. 97
Author(s):  
R. Yeater ◽  
I. Ullrich ◽  
S. Putnam ◽  
W G Hornsby
Keyword(s):  
High Risk ◽  
Rural Population ◽  
Exercise Adherence

A Mobile App for Identifying Individuals With Undiagnosed Diabetes and Prediabetes and for Promoting Behavior Change: 2-Year Prospective Study (Preprint)

2018 ◽  
Author(s):  
Angela YM Leung ◽  
Xin Yi Xu ◽  
Pui Hing Chau ◽  
Yee Tak Esther Yu ◽  
Mike KT Cheung ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Risk Group ◽  
Mobile App ◽  
Diabetes Risk ◽  
Undiagnosed Diabetes ◽  
Risk Level ◽  
Optimal Cutoff ◽  
Diabetes Risk Score

BACKGROUND To decrease the burden of diabetes in society, early screening of undiagnosed diabetes and prediabetes is needed. Integrating a diabetes risk score into a mobile app would provide a useful platform to enable people to self-assess their risk of diabetes with ease. OBJECTIVE The objectives of this study were to (1) assess the profile of Diabetes Risk Score mobile app users, (2) determine the optimal cutoff value of the Finnish Diabetes Risk Score to identify undiagnosed diabetes and prediabetes in the Chinese population, (3) estimate users’ chance of developing diabetes within 2 years of using the app, and (4) investigate high-risk app users’ lifestyle behavior changes after ascertaining their risk level from the app. METHODS We conducted this 2-phase study among adults via mobile app and online survey from August 2014 to December 2016. Phase 1 adopted a cross-sectional design, with a descriptive analysis of the app users’ profile. We used a Cohen kappa score to show the agreement between the risk level (as shown in the app) and glycated hemoglobin test results. We used sensitivity, specificity, and area under the curve to determine the optimal cutoff value of the diabetes risk score in this population. Phase 2 was a prospective cohort study. We used a logistic regression model to estimate the chance of developing diabetes after using the app. Paired t tests compared high-risk app users’ lifestyle changes. RESULTS A total of 13,289 people used the app in phase 1a. After data cleaning, we considered 4549 of these as valid data. Most users were male, and 1811 (39.81%) had tertiary education or above. Among them, 188 (10.4%) users agreed to attend the health assessment in phase 1b. We recommend the optimal value of the diabetes risk score for identifying persons with undiagnosed diabetes and prediabetes to be 9, with an area under the receiver operating characteristic curve of 0.67 (95% CI 0.60-0.74), sensitivity of 0.70 (95% CI 0.58-0.80), and specificity of 0.57 (95% CI 0.47-0.66). At the 2-year follow-up, people in the high-risk group had a higher chance of developing diabetes (odds ratio 4.59, P=.048) than the low-risk group. The high-risk app users improved their daily intake of vegetables (baseline: mean 0.76, SD 0.43; follow-up: mean 0.93, SD 0.26; t81=–3.77, P<.001) and daily exercise (baseline: mean 0.40, SD 0.49; follow-up: mean 0.54, SD 0.50; t81=–2.08, P=.04). CONCLUSIONS The Diabetes Risk Score app has been shown to be a feasible and reliable tool to identify persons with undiagnosed diabetes and prediabetes and to predict diabetes incidence in 2 years. The app can also encourage high-risk people to modify dietary habits and reduce sedentary lifestyle.

scholarly journals Identification of Multiple High-Risk Human Papillomavirus Infections in a Rural Population of Canatlan, Durango, Mexico

2020 ◽  
Vol 24 (6) ◽  
pp. 370-374
Author(s):  
Jesús Favela-Bueno ◽  
Rebeca Pérez-Morales ◽  
José Ramirez-Torres ◽  
Luisa Hernandez-Arteaga ◽  
Gerardo Alfonso Anguiano-Vega
Keyword(s):  
Human Papillomavirus ◽  
High Risk ◽  
Rural Population ◽  
Papillomavirus Infections
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