Prognostic value of resting heart rate in predicting undiagnosed diabetes in adults: Korean National Health and Nutrition Examination Survey 2008-2018.

BACKGROUND AND AIM: Although resting heart rate (RHR) is associated with prevalence and incidence of diabetes, whether it is associated with undiagnosed diabetes is still unclear. We aimed to investigate whether the RHR is associated with the prevalence of undiagnosed diabetes in a large Korean national dataset. METHODS AND RESULTS: The Korean National Health and Nutrition Examination Survey data from 2008 to 2018 were used. After screening, 51,637 participants were included in this study. The odds ratios and 95% confidence intervals (CIs) for undiagnosed diabetes were calculated using multivariable-adjusted logistic regression analyses. Analyses showed that participants with a RHR of ≥90 bpm showed a 4.00- (95% CI: 2.77-5.77) and 3.21-times (95% CI: 2.01-5.14) higher prevalence of undiagnosed diabetes for men and women, respectively, than those with a RHR of <60 bpm. The linear dose-response analyses showed that each 10-bpm increment in RHR was associated with a 1.39- (95% CI: 1.32-1.48) and 1.28-times (95% CI: 1.19-1.37) higher prevalence of undiagnosed diabetes for men and women, respectively. In the stratified analyses, the positive association between RHR and the prevalence of undiagnosed diabetes was tended to be stronger among those who were younger (age: <40 years) and lean (BMI: <23 kg/m2). CONCLUSIONS: Elevated RHR was significantly associated with a higher prevalence of undiagnosed diabetes in Korean men and women, independent of demographic, lifestyle, and medical factors. Accordingly, the value of RHR as a clinical indicator and health marker, especially in reducing the prevalence of undiagnosed diabetes, is suggestible.

Extensive evaluation and classification of low-cost dust sensors in laboratory using a newly developed test method.

An extensive evaluation of low-cost dust sensors was performed using an exponentially decaying particle concentration. A total of 264 sensors including 27 sensors with light-emitting diodes (LEDs) and 237 sensors with laser lighting sources were tested. Those tested sensors were classified into 4 groups based on the deviation from the reference data obtained by a reference instrument. The response linearities of all the tested samples for PM1 , PM2.5 , and PM10 were in excellent agreement with the reference instrument, except a few samples. For the measurements of PM1 and PM2.5 , the lighting source, that is, LED or laser, did not show any significant difference in overall sensor performance. However, LED-based sensors did not perform well for PM10 measurements. The 32, 24, and 16% of all the tested sensors for PM1 , PM2.5 , and PM10 measurement, respectively, are in the category of Class 1 (reference instrument reading ± 20%) requirement. The performance of the low-cost dust sensors for PM10 measurement was relatively less satisfactory.