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目的 探讨利用健康物联网技术的健康管理平台在大型企业工作场所员工健康管理中的应用.方法 根据员工健康体检资料,从符合入选条件的员工中,通过自愿报名筛选出126人,其中男性97人,女性29人,年龄26~59岁,平均(43.7±6.1)岁.通过佩戴个人可穿戴运动能耗监测设备康动仪、登录健康管理平台和使用健康监测一体机来监测干预对象的运动、体重、体质指数、脂肪量、肌肉量、收缩压、舒张压、总胆固醇、三酰甘油、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)、尿酸、空腹血糖等指标,通过3个月的强化管理对比前后的健康数据.计量资料用均数±标准差表示,干预前后健康指标的比较采用配对样本t检验.结果 经过3个月的健康管理干预,参研者的体重[(74.90±9.95)kg,(71.77±9.57)kg]、体质指数[(25.94±2.65)kg/m2,(24.96±2.55)kg/m2]、脂肪量[(21.30±4.31)kg,(18.89±4.23)kg]、肌肉量[(49.78±7.12)kg,(49.07±6.97)kg]、收缩压[(129.72±11.16)mmHg(1 mmHg=0.133 kPa),(118.32±10.50)mmHg]、舒张压[(89.10±8.28)mmHg,(76.94±7.57)mmHg]、胆固醇[(5.16±0.85)mmol/L,(4.96±0.90)mmol/L]、三酰甘油[(1.72±0.92)mmol/L,(1.43±0.64)mmol/L]、血尿酸[(353.00±85.33)μmol/L,(345.00±73.01)μmol/L]均有下降趋势,差异具有统计学意义(t=10.92、11.03、6.75、5.56、4.23、3.99、4.26、3.46、1.98,P均<0.05);HDL-C[(1.20±0.24)mmol/L,(1.28±0.25)mmol/L]有所上升,差异具有统计学意义(t=-4.62,P<0.05),LDL-C[(2.54±0.52)mmol/L,(2.66±0.58)mmol/L]略有上升,但差异无统计学意义(t=-3.03,P>0.05);血糖[(5.05±0.73)mmol/L,(5.02±0.79)mmol/L]下降,但差异无统计学意义(t=0.14,P>0.05).结论 通过应用健康物联网技术,对工作场所员工开展有针对性的健康管理干预,可以帮助员工培养科学的运动习惯、纠正不健康的膳食习惯,健康指标得到改善,探索出了一种新型的企业员工健康管理方法,推荐在大型企业的海内外项目等工作场所中推广应用.

Objective To study the application of Internet of Things, wireless health monitor all-in-one machine, health management platform, energy consumption monitoring in employee health management. Methods Enrollment criteria were set based on employees' health examination data, 126 employees were enrolled in this study voluntarily, 97 were male, and 29 were female. The age was from 26 to 59 years, the average age was 43.7 ± 6.1 years. Using motion energy consumption monitor, wireless health monitor all-in-one machine and health management platform, employee's exercise, body weight, body mass index, fat and muscle mass, systolic blood pressure, diastolic blood pressure, cholesterol, triglyceride, low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), uric acid, fasting blood glucose etc. were monitored. Data were collected for before and after 3 months intensive intervention. Results After 3 month of intensive intervention, body weight ( (74.90 ± 9.95) kg, (71.77 ± 9.57) kg), body mass index ((25.94 ± 2.65) kg/m2, (24.96 ± 2.55) kg/m2), fat mass ((21.30 ± 4.31) kg, (18.89 ± 4.23) kg), muscle mass ((49.78 ± 7.12) kg, (49.07 ± 6.97) kg), systolic pressure ((129.72 ± 11.16) mmHg(1 mmHg=0.133 kPa), (118.32 ± 10.50) mmHg), diastolic blood pressure ((89.10 ± 8.28) mmHg, (76.94 ± 7.57) mmHg), cholesterol ((5.16±0.85) mmol/L, (4.96±0.90) mmol/L), triglyceride ((1.72±0.92) mmol/L, (1.43±0.64) mmol/L), uric acid ((353.00 ± 85.33) μmol/L, (345.00 ± 73.01) μmol/L) were decreased with statistical significance (t=10.92, 11.03, 6.75, 5.56, 4.23, 3.99, 4.26, 3.46, 1.98, P<0.05); and the value of HDL-C ((1.20 ± 0.24) mmol/L, (1.28 ± 0.25) mmol/L) increased significantly (t=-4.62, P<0.05); the value of LDL-C((2.54 ± 0.52) mmol/L, (2.66±0.58) mmol/L) increased and fast blood glucose ((5.05±0.73) mmol/L, (5.02±0.79) mmol/L) decreased, but there was no significant difference(t=-3.03, 0.14 respectively, P>0.05). Conclusion Health Internet of Things can help employees to develop scientific exercise habits , to correct unhealthy diet habits, and improve health. It will provide a new option for enterprise employee health management and can be recommended for health management programs by large enterprises with domestic and abroad projects.