With the widespread application of cloud computing,big data,the Internet of Things,mobile internet,artifi-cial intelligence,blockchain,and edge computing in healthcare,hospital information systems have been developing rapidly.As hospital business systems increase and data interaction becomes more frequent,hospital data security faces increasingly greater risks in the new situation of digital transformation,leading to stricter requirements for data security.This article analyzes the cur-rent status of data security in the healthcare industry and the security challenges it faces.Based on the characteristics of new tech-nologies in the current situation,several security strategies are proposed for medical and health institutions to improve their data security capabilities.

With the widespread application of cloud computing,big data,the Internet of Things,mobile internet,artifi-cial intelligence,blockchain,and edge computing in healthcare,hospital information systems have been developing rapidly.As hospital business systems increase and data interaction becomes more frequent,hospital data security faces increasingly greater risks in the new situation of digital transformation,leading to stricter requirements for data security.This article analyzes the cur-rent status of data security in the healthcare industry and the security challenges it faces.Based on the characteristics of new tech-nologies in the current situation,several security strategies are proposed for medical and health institutions to improve their data security capabilities.

To explore the best measurement of waist circumference related with intra-abdominal fat area evaluated by magnetic resonance imaging ( MRI). Totally 207 participants aged 20-60 years were enrolled. Waist circumference were measured at the levels of navel ( WC1) and the midpoint between costal brim and iliac cest (WC2). Intra-abdominal fat area was evaluated by MRI scan. Intra-abdominal fat area was significantly higher in men than in women [(132. 17 ± 59. 49 vs 70. 56 ± 35. 33)cm2 , P<0. 01]. Pearson correlation analysis showed that WC1 and WC2 were positively correlated with intra-abdominal fat area (r = 0. 779, r = 0. 809, both P<0. 01). Multiple linear stepwise regression analysis demonstrated that WC1 and WC2 were independently associated with intra-abdominal fat area(β=0. 553, R2 =0. 714, P<0. 01; β = 0. 603, R2 = 0. 735, P<0. 01). All of the two different measurements of waist circumference parameters may reflect intra-abdominal fat area, while WC1 seems to be the simpler one.

Objective To investigate the relationship between intra-abdominal fat area(IAFA)in male with abdominal obesity and glycometabolism related indicators. Methods Ninety-four obesity males,aged from 21 to 62 years old,were selected as our subjects. They were divided into abdominal obesity group(n = 70)and non-abdominal obesity group( n = 24). The general information of all subjects was recorded. The indexes of height,weight,waist circumference,hip circumference,body mass index(BMI)were measured. The fasting oral glucose tolerance test was performed. The levels of blood glucose(0,1,2 h)and insulin(0,1,2 h)were measured,and insulin resistance index was calculated. MRI measurement was applied to calculate the IAFA. Compared the difference between the two groups in term of the level of blood glucose,insulin and insulin resistance index,and analyzed the correlation between glycometabolism related indicators and IAFA. Results BMI,waist circumference,hip circumference,insulin resistance index and IAFA in abdominal obesity group were (28. 67 ± 4. 20)kg/ m2 ,(99. 75 ± 4. 07)cm,(104. 42 ± 7. 62)cm,2. 60 ± 1. 80,(153. 06 ± 53. 23)cm2 respectively,higher than those in non-abdominal obesity group((21. 80 ± 1. 97)kg/ m2 ,(79. 50 ± 10. 05)cm, (91. 86 ± 4. 49)cm,1. 52 ± 0. 73,(71. 78 ± 25. 48)cm2 ),and the differences were statistically significant(t= - 7. 704,- 9. 583,- 7. 618,- 2. 877,- 7. 184,P < 0. 05). The level of blood glucose at 0,1,2 h of patient in abdominal obesity group were(5. 89 ± 1. 36)mmol/ L,(10. 55 ± 3. 07)mmol/ L,and(8. 41 ± 3. 63) mmol/ L,higher than that in non-abdominal obesity group((5. 29 ± 0. 53)mmol/ L,(8. 76 ± 1. 96)mmol/ L, (6. 54 ± 1. 50)mmol/ L). Meanwhile,The insulin at 0,1,2 h of man in abdominal obesity group were(9. 71 ± 5. 05)mU/ L,(83. 29 ± 64. 51)mU/ L,(63. 56 ± 21. 09)mU/ L),significantly higher than those in non-abdominal obesity group((6. 42 ± 2. 96)mU/ L,(33. 00 ± 19. 82)mU/ L,(63. 56 ± 21. 09)mU/ L),and the differences were significant( t = - 2. 098,- 2. 671;- 2. 447,- 3. 010;- 3. 784,- 3. 089;P < 0. 05). The IAFA in abdominal obesity was positively correlated with age,BMI,waist circumference,hip circumference,blood glucose(0,1,2 h)insulin(0,2 h)and insulin resistance index(r = 0. 254,0. 533,0. 521,0. 615,0. 245,0. 315, 0. 294,0273,0. 249,0. 225,P < 0. 05 ). After adjustment for confounding factors,age( x1 ),abdominal circumference(x2)and insulin resistance index(x3)were related to IAFA(y = 1. 369x1 + 4. 472x2 + 25. 072x3- 333. 626). Conclusion Compared with patients with non-abdominal obesity,the IAFA of patient with abdominal obesity with abdominal fat area size is associated with insulin resistance.