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  • Author: Qiao Wang x
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Eduardo Salazar, Mayank Gupta, Meynard Toledo, Qiao Wang, Pavan Turaga, James M. Parish and Matthew P. Buman

Obstructive sleep apnea (OSA) is an under-diagnosed risk factor for several adverse health outcomes. The gold standard diagnostic test for OSA is laboratory-based polysomnography (PSG). Portable sleep monitoring has been studied as an alternative for patients lacking access to PSG. This study aimed to assess the validity of the Zephyr BioHarness 3 (BH3), a chest-worn activity monitor that records movement, electrocardiography, and respiratory parameters, to identify apnea events in patients suspected of OSA. Patients (N = 18) underwent single-night laboratory-based PSG while wearing the BH3. PSG data were scored in 30-second epochs by PSG technicians. PSG and BH3 data were sampled and analyzed using three sets of features with a radial basis function support vector machine and three-layer neural networks: (1) apnea events were identified second by second using 5-second windows of raw BH3 data (sensitivity = 48.0 ± 8.7%, specificity = 75.6 ± 3.0%, accuracy = 74.4 ± 2.7%); (2) apnea events were identified second by second using mean, median, and variance values of 5-second windows of BH3 data (sensitivity = 54.7 ± 17.3%, specificity = 66.5 ± 12.1%, accuracy = 66.0 ± 10.9%); and (3) apnea events were identified second by second using phase-space transformation of BH3 data (sensitivity = 68.4 ± 9.0%, specificity = 81.5 ± 2.7%, accuracy = 80.9 ±2.5% for τ = 60; sensitivity = 64.0 ± 7.9%, specificity = 81.8 ± 2.5%, accuracy = 81.0 ± 2.3% for τ = 70). The BH3 may be useful for patients suspected of OSA without timely access to PSG.

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Jie Liang, Shuang-Shuang Tian, Nan Qiao, Cong Wang, Jian-Jun Huang, Chen-Ming Sun, Hai-Xia Zhang, Yan Cui, Hui Wang, Xiao-Meng Liu, Shu-Hong Xu, Hongwei Guan and Tong Wang

Objective:

This study aimed to investigate the relationship between metabolic syndrome (MetS) and physical activity (PA) in different domains among male coal miners of Shanxi Province in China.

Method:

The study was conducted from July 2013 to December 2013. A two-stage stratified cluster sampling method was used. Data regarding the general information of participants were collected by well-trained interviewers. MetS was defined according to IDF criteria. Self-reported PA was obtained with the IPAQ and categorized into three tertiles of intensity levels across occupation, transportation, household, and leisure-time domains. Univariate and multiple logistic regression analysis were applied to compute the odds ratios and their 95% confidence interval (CI).

Results:

A total of 3076 males aged 18–65 years old were recruited in this cross-sectional study. The prevalence of MetS was 40.5% in the study subjects. The percentages of vigorous-intensity PA in MetS and non-MetS groups were 70.07% and 62.92%, respectively. Participants spent most of their time on occupation (2034 MET-min/w) and transportation (693MET-min/w) domains. Higher-intensity levels in occupation domains were significantly associated with lower risk of MetS (OR: 0.759, 95% CI: 0.633–0.911; OR: 0.627, 95% CI: 0.516–0.762).

Conclusions:

Across four types of workers, the relationships between PA domains and MetS were different. For underground and underground auxiliary workers, the negative relationship was found between occupation PA and MetS. For office workers, the negative relationship was found between household PA and MetS. For ground workers, only leisure-time PA had positively related to MetS.