目的 了解兰州市2020年18岁以下中小学生超重和肥胖情况,以及超重、肥胖与血压偏高检出率之间的关系,为更好预防兰州市中小学生超重、肥胖和血压偏高提供基础数据和科学依据.方法 依据《2020年全国学生常见病和影响因素监测与干预方案工作手册》,选取兰州市城郊12所中小学,筛选18岁以下中小学生,计算不同性别、不同地区、不同年龄组的超重、肥胖检出率及血压偏高率.采用Logistic回归分析中小学生超重、肥胖与血压偏高的关系.结果 本次共调查4 036人,其中超重568人、超重率14.07％,肥胖506人、肥胖率12.54％,血压偏高495人、血压偏高率12.26％;超重检出率男生(15.80％)高于女生(12.22％),差异有统计学意义(x2=10.722,P＜0.05);肥胖检出率男生(15.28％)高于女生(9.60％),差异有统计学意义(x2=29.632,P＜0.05);血压偏高检出率男生(15.04％)高于女生(9.29％),差异有统计学意义(x2=30.930,P＜0.05);超重检出率城镇(16.74％)高于郊区(10.63％),差异有统计学意义(x2=30.689,P＜0.05);肥胖检出率城镇(15.91％)高于郊区(8.18％),差异有统计学意义(x2=53.990,P＜0.05);血压偏高检出率郊区(16.93％)高于城镇(8.66％),差异有统计学意义(x2=63.179,P＜0.05);血压偏高率体重正常组10.06％、超重组16.02％、肥胖组20.95％;调整年龄、性别和地区后,超重组和肥胖组血压偏高风险是正常组的2.025倍(95％CI:1.540～2.663)和3.488倍(95％CI:2.651～4.589).结论 兰州市中小学生肥胖和超重检出率较高,超重和肥胖是血压偏高的危险因素;家庭和学校应积极干预儿童青少年体重增长,提早预防高血压.

目的 了解甘肃省中小学生近视现状及影响因素,为区域学生近视防控工作提供参考依据.方法 分层整群抽取武威市小学4～6年级、初中和高中学生共3554名为研究对象,进行视力检查和问卷调查.采用χ2检验和Logistic回归分析近视影响因素.结果 3554名学生的近视率为77.2%.多因素Logistic回归分析结果显示,中学生、女生、住校生、平均每天作业时长≥2 h、父亲近视、母亲近视、父母亲均近视是近视的危险因素,OR值[95%CI]分别为1.776[1.527,2.066]、1.224[1.031,1.454]、2.732[1.947,3.835]、1.225[1.013,1.482]、2.431[1.893,3.123]、2.411[1.867,3.115]、4.244[3.054,5.897](均P<0.05);做眼保健操、眼睛距离书本>30 cm、老师提醒注意读写姿势、每天睡眠时间≥8 h是保护因素,OR值[95%CI]分别为 0.826[0.721,0.945]、0.839[0.762,0.923]、0.882[0.787,0.990]、0.685[0.548,0.856](均P<0.05).结论 甘肃省中小学生近视率较高,应家校联合,通过采取作业减负、充足睡眠等多项干预措施加强近视防控.

目的 分析2011-2021年武威市流行性腮腺炎的流行特征,并利用自回归积分滑动平均模型(auto regressive integrated moving average model,ARIMA)预测其短期发病趋势,为流行性腮腺炎的预防和控制措施的制订提供理论支撑.方法 收集2011-2021年武威市流行性腮腺炎发病资料进行流行病学特征分析,并利用R 4.1.0建立ARIMA模型,预测其短期发病趋势.结果 2011-2021年武威市流行性腮腺炎报告发病数4441例,年均发病率8.90/10万,发病群体以学生为主,共报告病例3 193例(71.90％);发病男性多于女性,性别比为1.70∶1;5～＜20岁年龄组发病数最多,共报告病例3515例(79.15％);报告发病数居首位的为凉州区(48.61％);报告年均发病率最高为古浪县(48.69/10万).发病呈现明显的季节性双峰分布,主峰为11月至次年1月,共报告病例1 470例(33.10％);次高峰为4-5月,共报告病例951例(21.41％).模型构建结果显示,ARIMA(2,1,0)(0,0,1)12为最优模型,其参数MASE为 0.326,RMSE为 1.337,MAE为-8.052,AIC为417.270,BIC 为 428.386.模型预测结果显示,预测值与观测值整体趋势变化一致,绝对误差平均值为0.25,相对误差平均值为0.42.结论 2011-2021年武威市流行性腮腺炎发病呈下降趋势,建立的ARIMA模型拟合程度较高,发病群体主要是学生,应做好学校卫生,加强学校流行性腮腺炎疫情监测.

目的 了解甘肃省兰州市农村住宅室内环境甲醛污染情况及影响因素,为防控该地区农村室内甲醛污染提供一定的理论依据.方法 于2019年10月(秋季)和12月(冬季)分别检测兰州市榆中县连塔镇薛家营村20户农村住宅客厅和卧室室内空气中甲醛浓度、温度及相对湿度,并进行住宅特征问卷调查.结果 46个检测点的甲醛超标率为13.04％,其中卧室(8.70％)和客厅(17.39％)差异无统计学意义(x2=0.192,P=0.662),冬季甲醛超标率(27.27％)高于秋季(0.00％),差异有统计学意义(x2=5.315,P=0.021).近两年装修过的房屋室内甲醛超标率(66.67％)高于未装修房屋(5.00％)(Fisher确切概率法,P=0.014).结论 兰州市农村住宅室内环境存在甲醛污染情况,冬季和房屋近两年有装修是造成甲醛浓度超标的影响因素.

采用整群随机抽样方法,对兰州市18家公立医院2 989名医护人员进行职业紧张因素及其工作相关肌肉骨骼疾患(WMSDs)发生情况调查,采用x2检验、Mantel-Haenszel趋势检验、Pearson相关及Logistic回归进行统计分析.结果显示,医护人员WMSDs发生率为37.04％,患有≥2种WMSDs疾病的569人(19.04％),发生率最高的是颈椎病(22.68％),其次是腰肌劳损(13.35％)和颈肩肌肉酸痛(12.71％).WMSDs患病情况与年龄、文化程度、工龄、职称、岗位、月收入、每周工作时间、过度承诺及付出-回报失衡情况成正相关;与户籍和所在科室成负相关.工龄＜15年、每周工作时间＞40 h、付出-回报失衡及高水平过度承诺状态是发生WMSDs的危险因素(P＜0.01).

目的 探究某市中小学生视力现状及其影响因素,为学生近视防控提供科学的理论依据.方法 采用分层整群抽样方法抽取某市12所中小学校3 392名学生为调查对象,开展视力检查和影响因素的问卷调查.使用SPSS 25.0统计软件开展单因素分析和多因素Logistic回归分析.结果 2020年9-10月共调查3 392名学生,近视检出率为62.38％;其中,女生(67.38％)高于男生(57.45％),城区学生(72.16％)高于郊区(50.39％),差异均有统计学意义(P＜0.05);家长提醒读写姿势越频繁,近视检出率越高,差异有统计学意义(P＜0.05).单因素分析结果显示,课间休息场所(x2=49.617)、家长提醒读写姿势(x2=37.581)、近距离用眼时长(x2=138.001)、每天在校做眼保健操频率(x2=73.402)、夜间看电子屏幕(x2=55.644)、不良姿式看电子屏幕(x2=95.780)、父母近视情况(x2=85.795)、夜间学习使用光源(x2=22.353)与中小学生近视相关,差异均有统计学意义(P＜0.05).多因素Logistic回归分析结果显示,课间休息去户外活动(OR=0.73,95％CI:0.62～0.86)、近距离用眼15～29min休息1次(OR=0.69,95％CI:0.56～0.87)是视力不良的保护因素;近距离用眼超过60 min(OR=1.38,95％CI:1.07～1.76)、偶尔(OR=1.25,95％CI:1.03～1.53)、经常(OR=1.59,95％CI:1.15～2.18)、总是(OR=2.45,95％CI:1.25～4.80)不良姿势看电子屏幕、父亲有近视史(OR=2.00,95％CI:1.61～2.48)或者父母均近视(OR=2.46,95％CI:1.89～3.19)是学生患近视的危险因素.结论 学生视力受不良用眼行为和姿势、用眼时长以及遗传因素的影响,学校与家庭应督促学生多去户外活动,养成良好的读写姿势和用眼习惯,及时缓解用眼疲劳,降低中小学生近视发生率.

BackgroundPolycyclic aromatic hydrocarbons (PAHs) are one of the most widely distributed and harmful organic pollutants in the atmosphere. ObjectiveTo investigate the distribution characteristics and composition sources of PAHs in the atmosphere of two districts of Lanzhou from 2019 to 2020 and evaluate the health risks of PAHs via inhalation to different populations. MethodsThe PAHs concentrations in two urban areas (Chengguan District and Xigu District) of Lanzhou City from January 2019 to December 2020 were regularly monitored. Mann-Whitney U test was used to compare differences in target pollutant concentrations between the two areas. Diagnostic ratio method and principal component analysis were adopted for source identification. Incremental lifetime cancer risk (ILCR) model was applied to evaluate the health risks of PAHs. ResultsThe M (P25, P75) PAHs concentrations in Chengguan District and Xigu District were 24.04 (14.59, 41.81) ng·m−3 and 25.97 (18.59, 42.56) ng·m−3, respectively, with no significant difference (Z=−0.970, P>0.05). As to seasonal distribution, most PAHs monomer concentrations in Chengguan District were higher than those in Xigu District in summer, and the concentrations of benzo[a]anthracene and benzo[g,h,i]perylene in Chengguan District were also higher than those in Xigu District in spring and autumn (P<0.05), but there were no significant differences in PAHs monomer concentrations between the two urban areas in winter (P>0.05). Ring number of PAHs exhibited seasonal fluctuations. In winter and spring, the highest proportions in Chengguan District and Xigu District were both 4-ring PAHs (37.32%-41.73%, 35.20%-39.66%), and in summer and autumn, the highest proportions were both 2- and 3-ring PAHs (39.38%-49.54%, 47.17%-51.23%). The results of diagnostic ratio method revealed mixed atmospheric PAHs sources in the two urban areas, including fossil fuel, coal, and biomass combustion. The results of principal component analysis showed that the cumulative contribution rate of the four principal component factors reached 79.54%. Principal component 1 included phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, and benzo[a]pyrene; principal component 2 included acenaphthene and dibenzo[a,h]anthracene; principal component 3 was fluorene; principal component 4 was naphthalene. The results of health risk assessment showed that the ILCR values of adult males, adult females, and children in Chengguan District were 2.30×10−6, 2.16×10−6, and 1.73×10−6, respectively; and those in Xigu District were 1.58×10−6, 1.48×10−6, and 1.19×10−6, respectively; all were greater than 10−6. ConclusionPAHs pollution exists in the atmosphere of the two urban areas of Lanzhou City, mainly comes from mixed sources of fossil fuels, coal, and biomass burning, and may pose potential carcinogenic risks to the population.

BackgroundAir pollutants PM2.5 and its adsorbed metal elements are important factors affecting public health.ObjectiveTo explore the distribution characteristics and sources of metal elements in atmospheric PM2.5 in Lanzhou from 2019 to 2020, and to assess the health risks of metal elements to different groups of residents through inhalation.MethodsFrom January 2019 to December 2020 in two districts of Lanzhou City (Chengguan District and Xigu District), regular PM2.5 and metal elements [antimony (Sb), aluminum (Al), arsenic (As), beryllium (Be), cadmium (Cd), chromium (Cr), mercury (Hg), lead (Pb), manganese (Mn), nickel (Ni), selenium (Se), and thallium (Tl)] were regularly monitored, and their concentrations were described by the median (M) and 25th and 75th percentiles (P25, P75) as not following a normal distribution (because the detection rates of the five elements Be, Cr, Hg, Ni, and Se were less than 70%, the five elements were not included in subsequent analysis), and then compared with the secondary concentration limits in the Ambient Air Quality Standards (GB 3095-2012). The differences between the medians of the two groups were compared by the Mann-Whitney U rank sum test, and the differences among the medians of multiple groups were compared by the Kruskal-Wallis H rank sum test; the enrichment factor (EF) method and principal component analysis were used to evaluate the pollution degree of the metals and their sources; the health risks of five non-carcinogenic metals (Sb, Al, Pb, Mn, and Tl) and two carcinogenic metals (As and Cd) in PM2.5 were evaluated by hazard index (HI) and hazard quotient (HQ) using the incremental lifetime cancer risk (LCR) model and the non-carcinogenic risk assessment model, respectively.ResultsThe PM2.5 concentrations [M (P25, P75)] in Lanzhou City were 38.50 (26.00, 65.00) and 41.00 (29.00, 63.10) μg·m−3 in 2019 and 2020, respectively, and the difference was not statistically significant (Z=−0.989, P > 0.05). The average levels of the metal elements from high to low were: Al > Pb > Mn > As > Cd > Sb > Tl, and the annual average concentration of each metal element in 2019 was higher than that in 2020 (P<0.05). The M ( P25, P75) of PM2.5 concentrations in Chengguan and Xigu districts were 52.98 (17.00, 61.00) and 55.40 (17.00, 67.00) μg·m−3, respectively, with no statistically significant differences (P<0.05); the concentrations of Sb and Al in Chengguan District were lower than those in Xigu District (P<0.05), and the concentrations of other metal elements were not different between the two areas (P>0.05). There were seasonal differences in the concentrations of PM2.5 and seven metal elements in Lanzhou City (except PAl=0.007, the other Ps < 0.001). The results of the enrichment factor method showed that the EF values of the six metals (Sb, Al, As, Cd, Pb and Tl) were all greater than 1. Among them, except As, the EF values of other metal elements were all greater than 10, and the EF values of Al and Cd were both greater than 100. The results of principal component analysis showed that the variance contributions of the three principal components were 45.61%, 24.22%, and 14.42%, and the cumulative contribution reached 84.25%. The principal component 1 included Pb, As, Cd, and Sb, the principal component 2 included Al and Mn, and the principal component 3 contained Tl. The non-carcinogenic risks of the five metals were, in descending order, Al > Mn > Pb > Tl > Sb, among which the HQ values of the remaining four metals were less than 1 for adults and children, except the HQ value of Al for adults, which was greater than 1. The ILC values of carcinogenic metal As for adult males, adult females, and children were 2.68×10−5, 2.51×10−5, and 1.45×10−5, respectively; the ILC values of carcinogenic metal Cd for adult males, adult females, and children were 1.53×10−6, 1.43×10−6, and 8.26×10−7, respectively.ConclusionThere is pollution of atmospheric PM2.5 and its adsorbed metal elements in Lanzhou. As and Cd elements may pose potential carcinogenic risks to the residents.

BackgroundBecause of high working intensity, high responsibility, and unexpected situations, health care workers may suffer great work pressure, which may lead to health damage. ObjectiveTo explore the self-rated health status and its influencing factors such as demographic and occupational-related factors of medical staff in Lanzhou. MethodsIn-service medical staff were selected by using cluster random sampling method from 18 public hospitals in Lanzhou City and were investigated with a self-made questionnaire and the Self-rated Health Measurement Scale (SRHMS). SRHMS includes 48 items in 10 dimensions, which are divided into three sub-scales of physical health, mental health, and social health, and another independent dimension is overall health. The scores were converted into a percentage scale and expressed as the percentage of measured score to full score; a higher score indicated better health, and >70% was considered good health status. t test, Kruskal-Wallis H test, and Spearman correlation were used to analyze the scores of SRHMS and the demographic and occupational-related factors affecting the scores of physical, mental, and social health sub-scales. ResultsA total of 2989 valid questionnaires were recovered. There were statistically significant differences in total score and the scores of physical, mental, and social health among medical staff of different age, educational background, length of service, and weekly working hours groups (P < 0.05). The percentage of total score to full score in the medical staff was 71.41%, but the scores of physical, mental, and social health sub-scales and total scale of selected participants were all lower than the corresponding domestic norms (t=−3.323, −12.283, −7.157, −9.659, P < 0.05); the percentage of psychological symptoms and negative emotions in mental health scale to full score was the lowest, only 58.39%. Educational background, length of service, and weekly working hours were negatively correlated with physical health score (r=−0.061, −0.060, −0.165, P < 0.05); professional title was positively correlated with mental health score (r=0.045, P < 0.05), while educational background and weekly working hours were negatively correlated with it (r=−0.051, −0.172, P < 0.05). Monthly income, professional title, and length of service were positively correlated with social health score (r=0.040, 0.049, 0.071, P < 0.05), while educational background and weekly working hours were negatively correlated with it (r=−0.038, −0.110, P < 0.05). ConclusionThe self-rated health status of selected medical staff in Lanzhou is generally good, but lower than that of the norm, especially the mental health score is the lowest. The self-rated health score of total scale is correlated with education, length of service, professional title, and working time per week.

Objective:To establish and validate a nomogram prediction model for acute ischemic stroke in patients aged 60 years and over with type 2 diabetes mellitus (T2DM).Methods:A retrospective analysis was performed on 445 T2DM patients hospitalized in the Department of Geriatrics and Neurology, Lanzhou University Second Hospital from January 2018 to August 2021. Patients were divided into modeling group and validation group according to 3∶1 ratio. A total of 334 patients treated from January 2018 to August 2020 were selected as the modeling group. We screened for the best predictors of acute ischemic stroke in elderly T2DM patients by Lasso regression. The R software was used to construct the nomogram model. The Bootstrap method was used to internal verification, and to draw receiver operating characteristic (ROC) curve. The C-index was calculated to evaluate the predictive performance of the nomogram model. A total of 111 elderly T2DM patients from September 2020 to August 2021 were enrolled as the validation group, external verification of the nomogram model. The calibration curves were drawn and C-index, brier score, calibration intercept and calibration slope were calculated.Results:In the modeling group, Lasso combined with logistic regression analysis showed that diabetes mellitus with hypertension course(OR=1.05, 95%CI 1.01-1.10), systolic blood pressure (OR=2.40, 95%CI 1.74-3.40), high monocyte to high-density lipoprotein-cholesterol ratio (OR=1.34, 95%CI 1.14-1.58), free triiodothyronine (OR=0.36, 95%CI 0.20-0.64), carotid artery plaque area (OR=1.45, 95%CI 1.19-1.79), degree of intracranial arterial stenosis (OR=4.77, 95%CI 2.60-9.81) were the best predictors of acute ischemic stroke in elderly T2DM patients. ROC curve results showed that the C-index of the modeling group was 0.862 (95%CI 0.824-0.900), internal verification was carried out by Bootstrap method, the C-index corrected to 0.852 (95%CI 0.812-0.895), the sensitivity was 80.1%, and the specificity was 76.1%. The C-index of external validation was 0.867 (95%CI 0.803-0.932), the sensitivity was 82.0%, and the specificity was 75.4%. The Brier-score was 0.149, the calibration intercept was -0.149, and the calibration slope was 1.096.Conclusions:The nomogram prediction model constructed in this study has good discrimination and calibration, which has good value for early prediction of acute ischemic stroke in elderly patients with T2DM.

目的 分析甘肃省兰州市某城区采暖期和非采暖期居民住宅室内PM2.5的污染特征,探讨采暖期和非采暖期居室内PM2.5的影响因素.方法 2018年8月-2019年3月,选取兰州市某城区住宅27户,监测其采暖期和非采暖期室内PM2.5浓度,并对居室特征开展问卷调查以获取相关数据,利用Mann-Whitney U检验对不同居室特征下室内PM2.5浓度进行单因素分析,用逐步多元线性回归模型进行多因素分析探讨室内PM2.5浓度的可能影响因素.结果 某城区居民住宅采暖期和非采暖期室内PM2.5浓度分别为223.4(136.8～317.2)μg/m3和99.6(62.1～144.8)μg/m3,且采暖期和非采暖期室内PM2.5浓度差异有统计学意义(U=107.000,P＜0.05).单因素分析结果显示,采暖期房屋年限(U=44.000)、居住楼层(U=38.000)和室内是否使用空调(U=31.000),室内PM2.5浓度差异有统计学意义(均P＜0.05);多因素分析结果显示,房屋年限、是否使用中央空调是采暖期室内PM2.5浓度的影响因素,而居住楼层、是否使用中央空调是非采暖期室内PM2.5浓度的影响因素.结论 甘肃省兰州市某城区居民住宅采暖期室内PM2.5污染较严重,房屋年限、居住楼层和使用中央空调可能是影响室内PM2.5浓度的因素.

目的 了解兰州市孕妇的碘营养状况,为兰州市重点人群科学补碘提供依据.方法 采用多阶段随机抽样的方法抽区,兰州市各区县的孕妇作为研究对象,收集孕妇尿样和家中食用盐,采用《尿中碘的砷铈催化分光光度测定方法》(WS/T 107-2016)测定尿液样品中的碘含量,采用《制盐工业通用试验方法碘的测定》(GB/T 13025.7-2012)测定孕妇碘盐含量.结果 本次调查的兰州市800名孕妇的碘盐平均水平为(26.09±4.30)mg/kg,碘盐覆盖率为99.75％(798/800),碘盐合格率为93.36％(745/798),合格碘盐食用率为93.13％(745/800),不同县(区)间盐碘含量差异有统计学意义(F=20.06,P＜0.01);兰州市800名孕妇的尿碘中位数为166.75(105.51,253.98)μg/L,低于150 μg/L的占40.00％(320/800),适宜占 34.38％(275/800),在 250～499 μg/L 占 23.12％(185/800),过量占 2.50％(20/800).各县(区)同孕期孕妇尿碘水平的差异无统计学意义(H=0.31,P＞0.05),各县(区)不同孕期尿碘水平的构成差异无统计学意义(x2=6.63,P＞0.05).结论2020年兰州市孕妇碘营养总体适宜,应加强孕期宣传教育和对重点人群碘营养状况的动态监测,提高孕期的碘营养水平,指导科学补碘.

目的 探讨2型糖尿病(T2DM)合并非酒精性脂肪性肝病(NAFLD)患者肝纤维化与胰岛素抵抗(IR)的关系.方法 收集2018年12月至2020年1月就诊于兰州大学第二医院的T2DM患者298例,依据腹部超声检查结果,分为单纯T2DM组(n=81)及T2DM合并NAFLD组(n =217).收集两组病史资料及馒头餐糖耐量试验结果,计算稳态模型胰岛素抵抗指数(HOMA-IR)、胰岛素动态分泌敏感性评估指数(ISImatsuda)及胰岛素敏感指数(ISI).依据NAFLD肝纤维化评分(NFS)将T2DM合并NAFLD患者分为排除纤维化亚组(n=69)、不确定亚组(n=86)及纤维化亚组(n=62),比较各组间IR程度.应用Logistic回归分析影响肝纤维化发展的因素.ROC曲线分析HOMA-IR、ISImatsuda对患者肝纤维化的诊断价值.结果 相比于单纯T2DM组,合并NAFLD组患者的HOMA-IR升高,ISImatsuda、ISI则下降(P均＜0.01);合并NAFLD患者中,肝纤维化亚组HOMA-IR(11.96±4.66)高于不确定亚组(9.74±4.16)和排除纤维化亚组(6.21±2.99),ISImatsuda、ISI低于其他两组,差异均有统计学意义(P均＜0.01).Logistic回归分析显示,高HOMA-IR是影响T2DM合并NAFLD患者肝维化的危险因素(P＜0.01),而高ISImatsuda为延缓肝纤维化的保护性因素(P＜0.05).ROC曲线分析提示HOMA-IR取最佳截断值为9.895时,诊断T2DM合并NAFLD患者发生肝纤维化的敏感度为75.8％,特异度为71.6％,ROC曲线下面积为0.738.结论 IR是促进肝纤维化进展的危险因素,改善胰岛素敏感性可能是延缓肝纤维化的治疗靶标.

血糖波动即血糖变异性,是指血糖在一定时间内于高峰和低谷之间变化的非稳定状况,主要包括短期和长期血糖波动.老年糖尿病患者血糖波动的特点主要有血糖波动幅度大、与低血糖紧密关联、存在性别差异、与HbA1C密切相关.血糖波动与缺血性脑卒中发生、预后的关系可以概括为氧化应激和炎症反应.临床研究证实,血糖波动可增加卒中发生风险,加重卒中严重程度,与卒中不良预后相关;基础研究证实血糖变异性大比持续高糖危害更大,可以促进细胞凋亡、使活性氧自由基生成增多、内皮细胞功能障碍.关注老年糖尿病患者血糖波动,可以为加强缺血性脑卒中的一、二级预防提供新思路.

ObjectiveTo investigate the effect of serum C-peptide level on the progression of liver fibrosis in patients with type 2 diabetes mellitus (T2DM) and nonalcoholic fatty liver disease (NAFLD). MethodsA total of 484 patients with T2DM who were admitted to Department of Geriatrics, The Second Hospital of Lanzhou University, from December 2018 to July 2020 were enrolled, and according to the results of abdominal ultrasound examination, they were divided into simple T2DM group with 107 patients and T2DM+NAFLD group with 377 patients. According to NAFLD fibrosis score, the patients with T2DM and NAFLD were divided into fibrosis exclusion subgroup （T2DM+F0） with 136 patients, uncertain subgroup (T2DM+F1) with 146 patients, and fibrosis subgroup (T2DM+F2) with 95 patients. Medical history data and laboratory markers were collected. The chi-square test was used for comparison of categorical data; the t-test or the Mann-Whitney U test was used for comparison of continuous data, and a one-way analysis of variance or the Kruskal-Wallis H test was used for comparison between multiple groups; a logistic regression analysis was used to explore the risk factors for the progression of liver fibrosis; the receiver operating characteristic (ROC) curve was used to analyze the clinical value of serum C-peptide in predicting and diagnosing the progression of liver fibrosis. ResultsCompared with the simple T2DM group, the T2DM+NAFLD group had a significant increase in C-peptide level (Z=-6.040,P＜0.001); compared with the T2DM+F1 and T2DM+F0, the T2DM+F2 had significantly higher C-peptide level ［2.89 (1.84-3.77) vs 1.97 (1.12-2.65)/1.87 (1.25-2.68), H=36.023,P＜0.001) and rate of fasting C-peptide (56.84% vs 23.29%/24.27%, χ2=37.583,P＜0001). The logistic regression analysis showed that C-peptide (OR=1.435, 95% confidence interval: 1.227~1.678， P＜0.001) was a risk factor for liver fibrosis in patients with T2DM and NAFLD, and the ROC curve analysis also showed that C-peptide had great significance in predicting liver fibrosis in such patients, with an area under the ROC curve of 0.814, a sensitivity of 642%, a specificity of 897%, and a Youden index of 0.539 at the optimal cut-off value of 2.405 ng/ml. ConclusionC-peptide is an independent risk factor for the progression of liver fibrosis in patients with T2DM and NAFLD.

在糖尿病患者的管理中,血糖监测是了解血糖控制情况的根本,血糖水平则是评估治疗个体反应及安全性的关键。血糖监测技术在不断发展,用于评价血糖管理效果的指标也逐渐增多。葡萄糖目标范围内时间是新兴血糖评价指标,因其可为临床医师及患者提供更多有关血糖管理方面的信息而备受关注。目前,葡萄糖目标范围内时间与糖尿病并发症及其他血糖管理指标相关性方面的探讨相对较多,因此,该文拟对相关研究进展作一综述。

目的 探讨工业区居民砷、铅、镉的内暴露水平及影响因素.方法 采用随机整群分层方法抽取兰州市工业区常住居民135人进行问卷调查,尿及血中砷、铅、镉的含量检测.两组间比较采用Mann-Whitney U检验,多组间比较采用Kruskal-Wallis H检验;尿、血中重金属水平相关性分析采用Spearman等级相关.结果 研究对象尿砷、尿铅、尿镉的几何均数分别为14.17μg/L、0.81μg/L、0.22μg/L;与儿童比较,成人尿铅、尿镉水平较高;与不吸烟者比较,吸烟者尿镉的水平较高(P<0.05).血砷、血铅、血镉几何均数分别为0.92μg/L、18.43μg/L、0.49μg/L;与儿童比较,成人血砷、血铅和血镉的水平均较高(P<0.05);与不吸烟者比较,吸烟者血铅和血镉的水平均较高(P<0.05).尿砷和血砷、尿铅和血铅、尿镉和血镉的水平均呈正相关(P<0.05).结论 工业区居民砷、铅、镉的内暴露水平存在年龄差异,吸烟也有影响;3种重金属的尿、血水平呈正相关.

目的 分析兰州市2015-2017年重点职业病监测结果.方法 对2015-2017年兰州市重点职业病监测情况进行描述与对比分析.结果 2015-2017年报告的重点职业病人数占总职业病人数89.92％.2017重点职业病危害因素监测岗位数高于2015年和2016年,煤尘(煤矽尘)、矽尘和噪声岗位超标率下降,苯岗位超标率增加.2015-2017年个案卡收集率差异具有统计学意义(P＜0.05).2015年职业禁忌证检出率高于2016和2017年(P＜0.05),2017年疑似职业病检出率低于2015和2016年(P＜0.05).2015-2017年接触苯和噪声的劳动者疑似职业病检出率、职业禁忌证检出率和专项指标检出率差异具有统计学意义(P＜0.05),接触煤尘(煤矽尘)和矽尘疑似职业病和专项指标检出率差异具有统计学意义(P＜0.05).总工龄收集率和苯接触的劳动者血常规指标收集率较低.2015-2017年兰州市工伤保险待遇落实率37.21％.结论 2015-2017年3年期间兰州市重点职业病监测工作得到了加强,但监测范围以及工作服务体系仍需进一步提高.

T2DM是目前发病率最高的代谢性疾病之一,是遗传和/或环境因素造成的慢性病,口服降糖药物是常用的治疗方法.二甲双胍、阿卡波糖通过影响肠道菌群丰度变化及其代谢产物短链脂肪酸产生,以改善血糖水平.本文就降糖药物对T2DM患者肠道菌群及其代谢产物的影响进行综述.

Objective To examine drinking water intake and daily life water usage among urban adult residents in Lanzhou city of Gansu province and to provide basic data for estimating domestic water-related exposure parameters for health risk assessment. Methods A total of 1 236 residents aged 18 years and older were randomly selected with stratified multistage cluster sampling from four urban districts in Lanzhou for a questionnaire survey during July – August and December, 2017. Information on drinking water intake and dermal exposure parameter-related to water usage were collected and analyzed. Results The medians of direct, indirect, and total drinking water intake were 1 650 mL/d, 394 mL/d and 2 142 mL/d among the respondents, respectively; the three medians differed significantly by gender, age, and body mass index (BMI) groups and the median for indirect drinking water intake was significantly different among the respondents with various occupations (P Conclusion Gender, age, BMI and occupation may influence drinking water intake and daily life water usage among adult urban residents in Lanzhou city.