Objective To explore the correlation between different body mass indexes and incidence of digestive carcinoma.Methods The retrospective cohort study was conducted.The data of 95 177 participants (75 909 males and 19 268 females) aged (51± 12)years with the range of 18-98 years who participated health examination at the Kailuan General Hospital,Kailuan Linxi Hospital,Kailuan Zhaogezhuang Hospital,Kailuan Tangjiazhuang Hospital,Kailuan Fan' gezhuang Hospital,Kailuan Jinggezhuang Hospital,Kailuan Lyujiatuo Hospital,Kailuan Linnancang Hospital,Kailuan Qianjiaying Hospital,Kailuan Majiagou Hospital and Kailuan Branch Hospital from July 2006 to December 2015 were collected.According to definition of body mass indexes from Chinese guideline for prevention and control of adult overweight and obesity,all the 95 177 participants were allocated into the 3 groups,including 37 660 with BMI＜24 kg/m2 in the normal BMI group,39 793 with with 24 kg/m2 ≤BMI＜ 28 kg/m2 in the overweight group and 17 724 with BMI≥28 kg/m2 in the obesity group.All participants received the same-order health examinations by the fixed team of doctors in 2006,2008,2010,2012 and 2014 at the same place.Epidemiological investigation,anthropometric parameters and biochemical indicators were collected.Observation indicators:(1) comparisons of clinical characteristics among the 3 groups;(2) incidence of digestive carcinoma in the participants;(3) risk factors analysis affecting new-onset digestive carcinoma;(4) comparisons of the fitting degree of BMI on new-onset digestive carcinoma model;(5) stratified analysis of risk factors affecting new-onset digestive carcinoma at different locations.Measurement data with normal distribution were represented as Mean±SD,and comparisons among groups were analyzed using the one-way ANOVA.Measurement data with skewed distribution were described as M (range),and comparisons among groups were analyzed using the Kruskal-Wallis test.Count data were described as case number and percentage,and comparisons among groups were analyzed using the chi-square test.The cumulative incidence was calculated by the Kaplan-Meier method,and comparisons of incidences among groups were done by the Log-rank test.The incidences of digestive carcinomain patients with different BMI were calculated by person-year incidence (incidence density).The hazard ratio (HR) and 95％ confidence interval (CI) of different BMI (continuous variable and classification variable) on new-onset digestive carcinoma were estimated by the COX proportional hazards regression models.Restrictive cubic spline regression was used to calculate the dose-response relation between the continuous variable and the risks of digestive carcinoma.The fitting degree of BMI on new-onset digestive carcinoma model was calculated by the likelihood ratio test and akaike information criterion (AIC).Results (1) Comparisons of clinical characteristics among the 3 groups:age,sex (male),systolic pressure,diastolic pressure,waistline,total cholesterol (TC),triglyceride (TG),fasting plasma glucose (FPG),C reactive protein,cases with smoking,drinking,physical exercise,positive HBsAg,high salt intake,malignant tumor in immediate family were (51± 13)yeas,28 607,(125±20) mmHg (1 mmHg=0.133 kPa),(80± 11) mmHg,(81±9) cm,(4.9± 1.1) mmol/L,1.05 mmol/L(range,0.75-1.49 mmol/L),(5.3±1.6) mmol/L,0.58 mmol/L (range,0.20-1.60 mmol/L),11 962,6 845,5 676,711,.3 640,1 298 in the normal BMI group and (52±12)years,32 928,(133±21) mmHg,(85±11) mmHg,(89±8)cm,(5.0±1.2) mmol/L,1.39 mmol/L (range,0.99-2.08 mmol/L),(5.6± 1.7)mmol/L,0.84 mmol/L (range,0.33-2.07 mmol/L),12 364,7 413,6 322,839,4 401,1 463 in the overweight group and (51 ± 12) years,14 374,(139 ± 21) mmHg,(88 ± 12) mmHg,(96 ± 9) cm,(5.1 ± 1.2) mmol/L,1.67 mmol/L (range,1.18-2.51 mmol/L),(5.7± 1.8) mmol/L,1.22 mmol/L (range,0.53-2.82 mmol/L),5 092,2 818,2 847,355,2 235,704 in the obesity group,showing statistically significant differences among groups (F=90.60,x2 =576.34,F=2 768.38,3 570.80,22 319.30,256.99,x2 =9 108.21,F=507.11,x2 =3 219.47,52.78,64.38,13.36,0.76,130.39,9.74,P＜0.05).(2) Incidence of digestive carcinoma in the participants:all the 95 177 participants were followed up for 845 085 person-year,1 215 were diagnosed as new-onset digestive carcinoma,with a total person-year incidence of 1.44 thousand person / year.Of 1 215 patients,413 had colorectal-anal cancer,306 had liver cancer,234 had gastric cancer,113 had esophageal cancer,91 had the pancreatic cancer,36 had gallbladder carcinoma or cholangiocarcinoma,25 had intestinal cancer.Three patients had intestinal cancer complicated with colorectal-anal cancer.The person-year incidence of digestive carcinoma was 1.46 thousand person / year,1.37 thousand person / year and 1.53 thousand person / year in the normal BMI group,overweight group and obesity group,respectively.The cumulative incidences of digestive carcinoma in the normal BMI,overweight,obesity group were respectively 11.8‰,10.1‰ and 12.1‰,showing a statistically significant difference among 3 groups (x2=6.13,P＜0.05).There was no statistically significant difference between the normal BMI group and obesity group (x2 =1.07,P＞0.05),and statistically significant differences between the overweight group and normal BMI group and obesity group,respectively (x2=3.90,4.10,P ＜ 0.05).(3) Risk factors analysis affecting new-onset digestive carcinoma.Results of COX proportional hazards regression models showed that continuous BMI was not related factor affecting new-onset digestive carcinoma after adjustment of age,gender,systolic pressure,TC,TG,FPG,smoking,drinking,physical exercise,positive HBsAg,high salt intake,malignant tumor in immediate family (HR=0.99,95％CI:0.98-1.01,P＞0.05).After adding BMI as classification variable in the COX model,risk of new-onset digestive carcinoma in the overweight group was reduced compared with normal BMI group (HR =0.88,0.88,95％CI:0.78-1.01,0.77-0.98,P＜0.05) and risk of new-onset digestive carcinoma in the obesity group was not affected (HR=1.03,1.04,95％CI:0.88-1.20,0.89-1.22,P＞0.05).Results of restrictive cubic spline regression showed a "U" shaped relationship between BMI and incidence risk of digestive carcinoma and the lowest incidence of digestive carcinoma in patients with BMI as 25-27 kg/m2.(4) Comparisons of the fitting degree of BMI on new-onset digestive carcinoma model:multivariate model was constructed after adding risk factors of age,gender,systolic pressure,TC,TG,FPG,smoking,drinking,physical exercise,positive HBsAg,high salt intake,malignant tumor in immediate family,and-2Log L and AIC were 27 175.05 and 27 203.05 for the multivariate model.Then BMI variable was added into the multivariate model,and the-2Log L and AIC of the multivariate model+BMI model were 27 169.53 and 27 201.53,respectively,with a statistically significant difference compared with normal BMI group (x2 =5.52,P＜0.05).(5) Stratified analysis of risk factors affecting new-onset digestive carcinoma at different locations.Results of COX proportional hazards regression models showed risks of new-onset digestive carcinoma in the overweight and obesity groups were reduced compared with normal BMI group (HR=0.57,0.42,95％CI:0.38-0.84,0.23-0.79,P＜0.05) in the esophageal cancer model.Risks of new-onset digestive carcinoma in the overweight group were reduced compared with normal BMI group (HR=0.72,95％CI:0.55-0.93,P＜0.05) and risk of new-onset digestive carcinoma in the obesity group was not affected (HR=1.10,95％CI:0.82-1.47,P＞0.05) in the liver cancer model.Conclusions Participants in the overweight group have the lowest incidence of digestive carcinoma,especially in the esophageal cancer and liver cancer model.Incidence of digestive carcinoma is the lowest with BMI as 25-27 kg/m2.

Objective To explore the predictive value of combined application of the different obesity measures on incident gallstone disease (GD) and find the optimal combination.Methods The retrospective cohort study was conducted.The data of 88 947 participants who participated in health examination at the Kailuan General Hospital,Kailuan Linxi Hospital,Kailuan Zhaogezhuang Hospital,Kailuan Tangjiazhuang Hospital,Kailuan Fan'gezhuang Hospital,Kailuan Jinggezhuang Hospital,Kailuan Lyujiatuo Hospital,Kailuan Linnancang Hospital,Kailuan Qianjiaying Hospital,Kailuan Majiagou Hospital and Kailuan Branch Hospital from July 2006 to December 2015 were collected.All participants received the same-order health examinations by the fixed team of doctors in 2006,2008,2010,2012 and 2014 at the same place.Epidemiological investigation,anthropometric parameters and biochemical indicators were collected.Observation indicators:(1) comparisons of general data between 2 genders;(2) incidence of GD;(3) risk factors analysis of the different obesity measures affecting incident GD;(4) comparisons of the fitting degree and predictive value of combined application of the different obesity measures on incident GD model.Measurement data with normal distribution were represented as (x)±s,and comparisons between groups were analyzed using the t test.Measurement data with skewed distribution were described as M (P25,P75),and comparisons between groups were analyzed using the rank sum test.Comparisons of count data were analyzed using the chi-square test.The incidences of GD between 2 genders were calculated by person-year of follow-up.The hazard ratio (HR) and 95％ confidence interval (CI) of the different obesity measures on incident GD were estimated by the COX proportional hazard model.The fitting degree of different combination of obesity measures on incident GD model was calculated by the likelihood ratio test and akaike information criterion (AIC).Results (1) Comparisons of general data between 2 genders:of 88 947 participants,age,body mass index (BMI),waist circumference (WC),systolic pressure,diastolic pressure,total cholesterol (TC),triglyceride (TG),fasting plasma glucose (FPG),cases with diabetes,hypertension,smoking,drinking and physical exercise were respectively (51± 12) years old,(25±3) kg/m2,(88± 10) cm,(132±20) mmHg (1mmHg=0.133 kPa),(84± 12) mmHg,(4.95± 1.16) mmol/L,1.18 mmol/L (0.81 mmol/L,1.74 mmol/L),(5.5±1.6)mmol/L,6 223,31 816,26 993,15 779,11 063 in male participants and (49± 11)yearsold,(25±4)kg/m2,(83±11)cm,(124±21)mmHg,(7911)mmHg,(4.98±1.08)mmol/L,1.30 mmol/L (0.92 mmol/L,2.00 mmol/L),(5.3±1.6)mmol/L,1 409,5 866,248,87,2 450 in female participants,with statistically significant differences [t=587.20,894.27,1 064.97,813.49,986.22,630.97,H(x2)=642.39,t=452.87,x2=35.10,1 205.40,9 619.42,4 901.75,84.82,P＜0.05].(2) Incidence of GD:88 947 participants were followed up for 713 345 person-year,4 291 participants had incident GD,with a total person-year incidence of 6.02 thousand person / year.The total follow-up time,cases with incident GD and person-year incidence were respectively 562 821 person-year,3 268,5.81 thousand person / year in male participants and 150 524 person-year,1 023,6.80 thousand person / year in female participants.(3) Risk factors analysis of the different obesity measures affecting incident GD:the results of COX proportional hazard model:in male participants,adjusted for age,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,BMI was associated with increased risk of incident GD (HR=1.35,1.63,95％CI:1.24-1.46,1.48-1.80,P＜0.05);WC was associated with increased risk of incident GD (HR=1.27,1.53,95％CI:1.15-1.40,1.39-1.67,P＜0.05);waist-to-height ratio (WHtR) was associated with increased risk of incident GD (HR=1.20,1.44,95％CI:1.09-1.32,1.31-1.58,P＜0.05).In female participants,BMI was associated with increased risk of incident GD (HR=1.35,1.77,95％CI:1.16-1.56,1.49-2.10,P＜0.05);WC was associated with increased risk of incident GD (HR=1.38,1.72,95％CI:1.15-1.66,1.44-2.07,P＜0.05);WHtR was associated with increased risk of incident GD (HR=1.34,1.71,95％CI:1.12-1.61,1.43-2.04,P＜0.05).(4) Comparisons of the fitting degree and predictive value of combined application of the different obesity measures on incident gallstone diseases model:multi-factor model of male participants was constructed after adding risk factors of age,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,and-2log L and AIC were 71 257 and 71 275.Then BMI,WC,WHtR,BMI+WC,BMI+WHtR,WC+WHtR and BMI+WC+ WHtR were respectively added into the multi-factor model,and-2log L and AIC were respectively 71 156 and 71 178,71 170 and 71 192,71 197 and 71 219,71 134 and 71 160,71 132 and 71 162,71 170 and 71 196,71 132 and 71 162.The minimal mode of AIC was multi-factor model+BMI+WC,with a difference of 123 compared with multi-factor model of-2log L,showing a statistically significant difference (x2 =123.00,P＜ 0.05).The multi-factor model of female participants was constructed after adding risk factors of age,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,and-2log L and AIC were 19 612 and 19 630.Then BMI,WC,WHtR,BMI+WC,BMI+WHtR,WC+WHtR and BMI+WC+WHtR were respectively added into the multi-factor model,and-2log L and AIC were respectively 19 568 and 19 590,19 575 and 19 597,19 574 and 19 596,19 558 and 19 584,19 557 and 19 583,19 571 and 19 597,19 556 and 19 586.The minimal mode of AIC was multi-factor model+BMI+WHtR,with a difference of 55 compared with multi-factor model of-2log L,showing a statistically significant difference (x2 =55.00,P＜0.05).Conclusions The increased BMI,WC and WHtR are independent risk factors for incident GD,no matter the gender.In males,the combination of BMI and WC can improved the predictive value of the incident GD,while in females,BMI and WHtR are the best combination for predicting incident GD.

Objective To explore the relationship between alcohol consumption and new-onset cholelithiasis.Methods The retrospective cohort study was conducted.The data of 77 755 participants who participated health examination at the Kailuan General Hospital,Kailuan Linxi Hospital,Kailuan Zhaogezhuang Hospital,Kailuan Tangjiazhuang Hospital,Kailuan Fan'gezhuang Hospital,Kailuan Lyujiatuo Hospital,Kailuan Jinggezhuang Hospital,Kailuan Linnancang Hospital,Kailuan Qianjiaying Hospital,Kailuan Majiagou Hospital and Kailuan Branch Hospital from June 2006 to December 2015 were collected.According to definition of alcohol consumption from literature,all the 77 755 participants were allocated into the 5 groups,including 50 695 with never drinking in the never group,3 154 with alcohol withdrawal time≥ 1 year in the past group,12 410 with light drinking in the light group,1 606 with moderate drinking in the moderate group and 9 890 with heavy drinking in the heavy group.All participants received the same-order health examinations by the fixed team of doctors in 2006,2008,2010,2012 and 2014 at the same place.Epidemiological investigation,anthropometric parameters and biochemical indicators were collected.Observation indicators:(1) comparisons of clinical characteristics among the 5 groups;(2) incidence of cholelithiasis;(3) risk factors analysis affecting new-onset cholelithiasis;(4) comparisons of the fitting degree of alcohol consumption on new-onset cholelithiasis model.Measurement data with normal distribution were represented as (x)±s,and comparisons among groups were analyzed using the one-way ANOVA.The pairwise comparison and homogeneity of variance were done using the least significance difference (LSD) test.Heterogeneity of variance was analyzed by the Dunnett's T3 test.Measurement data with skewed distribution were described as M (Q),and comparisons among groups were analyzed using the rank sum test.Comparisons of count data were analyzed using chi-square test.The cumulative incidence of new-onset cholelithiasis was calculated by the Kaplan-Meier method,and comparisons of incidences among groups were done by the Log-rank test.The hazard ratio (HR) and 95％ confidence interval (CI) of different intakes of alcohol on new-onset cholelithiasis were estimated by the COX proportional hazards regression models.The fitting degree of alcohol consumption on new-onset cholelithiasis model was calculated by the likelihood ratio test and akaike information criterion (AIC).Results (1) Comparisons of clinical characteristics among the 5 groups:male,age,systolic pressure,diastolic pressure,body mass index (BMI),total cholesterol (TC),triglyceride (TG),fasting plasma glucose (FPG) and waistline and cases with diabetes,hypertension,smoking and physical exercise were respectively 33 406,(51±12)years,(130±21) mmHg (1mmHg=0.133 kPa),(83± 12)mmHg,(25±4)kg/m2,(4.93±1.13)mmol/L,1.26 mmol/L (0.90-1.88 mmol/L),(5.5±1.7)mmol/L,(86±10) cm,4 538,21 773,5 873,6 140 in the never group and 3 077,(56±12) years,(134±22)mmHg,(85±12)mmHg,(25± 3) kg/m2,(4.93 ± 1.21) mmol/L,1.29 mmol/L (0.91-1.90 mmol/L),(5.6 ± 1.8) mmol/L,(89 ±9)cm,420,1 652,856,856 in the past group and 11 859,(46±12)years,(127±19)mmHg,(82±11)mmHg,(25±3)kg/m2,(4.89± 1.15) mmol/L,1.30 mmol/L (0.89-2.01 mmol/L),(5.4± 1.4) mmol/L,(87±9)cm,891,4294,2 186,2 186 in the light group and 1 585,(58±11)years,(134±22)mmHg,(84±11)mmHg,(25±3)kg/m2,(5.06±1.21)mmoL/L,1.23 mmoL/L (0.85-1.82 mmol/L),(5.5±1.7) mmol/L,(88±9)cm,159,762,591,591 in the moderate group and 9 868,(52±9) years,(135±21)mmHg,(86±12)mmHg,(25±3)kg/m2,(5.18±1.21)mmoL/L,1.36 mmol/L (0.92-2.19 mmol/L),(5.5±1.5)mmoL/L,(88±9) cm,819,4 900,2 183,2 183 in the heavy group,showing statistically significant differences among groups [x2 =9 989.71,F=869.28,F=254.13,195.97,27.52,112.63,H(x2) =154.09,F=11.92,63.37,x2 =128.17,656.31,23 561.80,656.31,P＜0.05].(2) Incidence of cholelithiasis:all 77 755 participants were observed for (6.8±2.1)years,3 757 were diagnosed as new-onset cholelithiasis,with a cumulative incidence of new-onset cholelithiasis of 4.5％.The cumulative incidences of new-onset cholelithiasis in the never,past,light,moderate and heavy groups were respectively 5.1％,4.9％,3.7％,3.4％ and 3.3％,showing a statistically significant difference among groups (x2=83.14,P＜0.05).The cumulative incidence of new-onset cholelithiasis in the never group was significantly different from that in the past,light,moderate and heavy groups (x2 =18.34,40.58,45.41,48.44,P＜0.05).The cumulative incidence of new-onset cholelithiasis in the past group was significantly different from that in the light,moderate and heavy groups (x2 =18.72,20.47,25.41,P＜0.05).There were statistically significant differences in the cumulative incidence of new-onset cholelithiasis among the light,moderate and heavy groups (x2=8.47,12.41,P＜0.05) and no statistically significant difference between the moderate and heavy groups (x2=0.85,P＞0.05).(3) Risk factors analysis affecting new-onset cholelithiasis:results of COX proportional hazards regression models showed that risks of new-onset cholelithiasis in the light,moderate and heavy groups were reduced compared with never group after adjustment of gender,age,TC,TG,BMI,hypertension,diabetes,smoking and physical exercise (HR=0.88,0.82,0.73,95％CI:0.79-0.98,0.76-0.89,0.64-0.83,P＜0.05).(4) Comparisons of the fitting degree of alcohol consumption on newonset cholelithiasis model:multivariate model was constructed after adding risk factors of gender,age,BMI,TG,TC,hypertension,diabetes mellitus,smoking and physical exercise,and-2Log L and AIC were 76 331.83 and 76 353.83 for the multivariate model.Then drinking variable was added into multivariate model,and the-2Log L and AIC of the multivariate model+drinking model were 76 307.86 and 76 337.86,respectively,with statistically significant differences (x2=23.97,P＜0.05).Conclusion Alcohol consumption is an independent protective factor for new-onset cholelithiasis,and the risk of cholelithiasis is decreased with increasing alcohol intake.

Objective:To investigate the current situation of medical social worker supervision in Shanghai, for reference to promote the high-quality development of medical social work.Methods:From June to July 2022, a questionnaire survey was conducted on the in-service medical social workers in all medical institutions with medical social work departments or posts in Shanghai. The questionnaire mainly included demographic information, current status of supervision implementation, and effectiveness of supervision. The data were analyzed descriptively with t test for comparison between groups and the Pearson test was for correlation analysis. Results:A total of 99 medical social workers were included in this study, 65 had received supervision, and medical institutions where 58 people located had established the supervision system. The average scores of actual and expected supervisory support received by medical social workers were 3.71 and 4.20 respectively, and the mean burnout level score was 32.91. The effect of establishing a supervision institutions on burnout was statistically significant ( P<0.05) and actual access to supervision support was negatively associated with burnout ( P<0.05). Conclusions:The overall situation of medical social work supervision in Shanghai was positive, but the demand for supervision was not fully satisfied; Supervision had a positive impact on reducing the burnout level. It is suggested that medical social work should further strengthen the cultivation of supervisory talents, promote the construction of supervisory systems, and improve the quality of supervision.