Ethnic Differences in Body Composition and Obesity Related Risk Factors: Study in Chinese and White Males Living in China

The purpose of this cross-sectional observational study was to identify ethnic differences in body composition and obesity-related risk factors between Chinese and white males living in China. 115 Chinese and 114 white male pilots aged 28–63 years were recruited. Fasting body weight, height and blood pressure were measured following standard procedures. Whole-body and segmental body composition were measured using an 8-contact electrode bioimpedance analysis (BIA) system. Fasting serum glucose, fasting plasma total cholesterol (TC), high-density lipoprotein (HDL) cholesterol, and triglycerides (TG) were assessed using automatic biochemistry analyzer. After adjusting for age and body mass index (BMI), Chinese males had significantly higher percentage of body fat (PBF) both with respect to whole body (Chinese: 23.7%±0.2% vs. Whites: 22.4%±0.2%) and the trunk area (Chinese: 25.0%±0.3% vs. Whites: 23.2%±0.3%) compared to their white counterparts. At all BMIs, Chinese males had significantly higher fasting glucose levels (Chinese: 5.7±1.0 mmol/L vs. Whites: 5.2±1.0 mmol/L) but lower high-density lipoprotein levels (Chinese: 0.8±1.0 mmol/L vs. Whites: 1.0±1.0 mmol/L) than white males. In addition, a marginally significantly higher diastolic blood pressure was found among Chinese men than that among white men (Chinese: 80±1.0 mmHg vs. Whites: 77±1.0 mmHg). Chinese males had more body fat and a greater degree of central fat deposition pattern than that seen in white males in the present study. Furthermore, data on blood pressure, fasting glucose and blood lipids suggest that Chinese men may be more prone to obesity-related risk factors than white men

Remote Cardiovascular Hypertension Program Enhanced Blood Pressure Control During the COVID‐19 Pandemic

Background The COVID‐19 pandemic disrupted traditional health care; one fallout was a drastic decrease in blood pressure (BP) assessment. We analyzed the pandemic's impact on our existing remote hypertension management program's effectiveness and adaptability. Methods and Results This retrospective observational analysis evaluated BP control in an entirely remote management program before and during the pandemic. A team of pharmacists, nurse practitioners, physicians, and nonlicensed navigators used an evidence‐based clinical algorithm to optimize hypertensive treatment. The algorithm was adapted during the pandemic to simplify BP control. Overall, 1256 patients (605 enrolled in the 6 months before the pandemic shutdown in March 2020 and 651 in the 6 months after) were a median age of 63 years old, 57% female, and 38.2% non‐White. Among enrolled patients with sustained hypertension, 51.1% reached BP goals. Within this group, rates of achieving goal BP improved to 94.6% during the pandemic from 75.8% prepandemic (P<0.0001). Mean baseline home BP was 141.7/81.9 mm Hg during the pandemic and 139.8/82.2 prepandemic, and fell ≈16/9 mm Hg in both periods (P<0.0001). Maintenance during the pandemic was achieved earlier (median 11.8 versus 19.6 weeks, P<0.0001), with more frequent monthly calls (8.2 versus 3.1, P<0.0001) and more monthly home BP recordings per patient (32.4 versus 18.9, P<0.0001), compared with the prepandemic period. Conclusions A remote clinical management program was successfully adapted and delivered significant improvements in BP control and increased home BP monitoring despite a nationally observed disruption of traditional hypertension care. Such programs have the potential to transform hypertension management and care delivery

Obesity-related risk factors in different ethnic groups adjusted for age and BMI.

<p>Continuous variables are given as mean values with their standard errors.</p><p>BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FG, fasting glucose; TC, total cholesterol; TG, triglyceride; HDL, high-density lipoprotein.</p><p>Analysis of covariance (ANCOVA) adjusted for age (single years) and BMI (continuous).</p><p>*Mean values were significantly different between Chinese men and white men (<i>P</i><0.05).</p

Body composition in different ethnic groups adjusted for age and BMI.

<p>Continuous variables are given as mean values with their standard errors.</p><p>BMI, body mass index, FM, fat mass, FFM, fat-free mass, TFM, trunk FM.</p><p>Analysis of covariance (ANCOVA) adjusted for age (single years) and BMI (continuous).</p><p>*Mean values were significantly different between Chinese men and White men (<i>P</i><0.05).</p

Characteristics of subjects in different ethnic groups.

<p>Continuous variables are given as mean values with their standard deviations.</p><p>BMI, body mass index, FM, fat mass, FFM, fat-free mass, BI, bioelectrical impendence.</p><p>Two-tailed T-test was applied to compare the differences between Chinese men and White men.</p