男性新生儿血红蛋白正常参考值与中国地理因素

目的:为制定中国男性新生儿血红蛋白正常参考值的统一标准提供科学依据。方法:收集了中国78个单位用氰化高铁血红蛋白(HiCN)法测定的5169例男性新生儿血红蛋白正常参考值,运用相关分析和回归分析的方法,研究了其与地理因素的关系。结果:发现男性新生儿血红蛋白正常参考值与中国地理因素之间有很显著的相关关系(F=17.93)。用逐步回归分析的方法推导出了一个回归方程:Y=156.8+0.01670X1+0.4140X3-0.008596X5±25.1。结论:如果知道了中国某地的地理因素,就可以用回归方程估算这个地区的血红蛋白正常参考值。依据血红蛋白正常参考值与地理因素的依赖关系把中国分为青藏区、西南区、西北区、东南区、华北区、东北区等六个区。     

中年女性红细胞计数正常参考值与地理因素的相关分析

目的：为制定中国中年女性红细胞计数正常参考值的统一标准提供科学依据.方法：收集了中国331个单位用显微镜计数法测定的41003例中年女性红细胞计数正常参考值,运用相关分析和回归分析的方法,研究了其与八个地理因素的关系.结果：发现中年女性红细胞计数正常参考值与中国地理因素之间有很显著的相关关系（F=364.76,P=0.000）.用逐步回归分析的方法推导出了一个回归方程：Y^=4.184＋0.0002421X1-0.02921X4＋0.0002582X7＋0.08144X8±0.47.结论：如果知道了中国某地的地理因素,就可以用回归方程计算这个地区的红细胞计数正常参考值.依据红细胞计数正常参考值与地理因素的依赖关系,把中国分为八个区.     

中国健康中老年女性红细胞压积参考值（温氏法）与地理因素的关系

为制定中国健康中老年女性红细胞压积参考值（温氏法）的统一标准提供科学依据。方法分析了３１２个单位１５６０８例健康中老年女性的红细胞压积参考值（温氏法）与５项地理因素的关系。结果发现随着海拔高度的逐渐增大,红细胞压积参考值也逐渐的增大;用数学回归的方法推导出了一个多元回归方程。结论可以依据红细胞压积参考值（温氏法）与地理因素的依赖关系把中国分为青藏区、西南区、西北区、东南区、华北区、东北区等６个区。     

基于偏最小二乘回归的中国青春期男性肺活量参考值与地理因素的关系

目的：为制定中国青春期男性肺活量参考值的统一标准提供科学依据.方法：搜集了中国用肺量计法测定72个单位的213881例健康青春期男性肺活量参考值.运用相关分析的方法研究了其与海拔高度（X_1）,年日照时数（X_2）,年平均相对湿度（X_3）,年平均气温（X_4）,年降水量（X_5）,气温年较差（X_6）,年平均风速（X_7）的关系.结果：发现青春期男性肺活量参考值与地理因素之间有显著的相关关系.用偏最小二乘回归分析的方法建立了青春期男性肺活量参考值与地理因素的回归模型：Y=3024.77-0.131640X_1＋0.022388X_2＋2.381548X_3-1.344117X_4-0.030850X_5＋7.881706X_6＋39.820870X_7±557.93,并用Arcgis软件中的空间差值内插出中国青春期男性肺活量参考值的空间趋势分布图.结论：知道中国某地的地理因素,就可用此模型估算该地区青春期男性肺活量参考值,同时也可用空间趋势图直观的得到中国任何地方的青春期男性肺活量参考值.     

The Relationship Between the Reference Value of Erythrocyte Sedimentation Rate and Geographical Factors

In order to provide a scientific basis for a unified standard of the reference value of erythrocyte sedimentation rate (ESR) in China, the reference value of healthy people's ESR has been collected. The relationship between the reference value of ESR and geographical factors is examined in this paper. Altitude is the most important factor affecting the reference value of ESR, which decreases with increasing altitude; the relationship is quite significant. The method of stepwise regression analysis was used to deduce two regression equations: ₁=12.08-0.00222X₁+0.00114X₅ ± 2.95, ₂=18.81-0.00323X₁+0.239X₄ ± 4.70. If the geographical factor value of a particular area in China is known, the reference value of ESR of Chinese people can be calculated by means of the regression equations. Furthermore, the dependence on geographical factors in China can be classified as six districts: Qingzang, Southwest, Northwest, Southeast, North and Northeast.     

Reference values for erythrocyte sedimentation rate of middlescent people as a function of altitude

The purpose of this paper is to provide a scientific basic for a unified standard for the reference value of middlescent people's erythrocyte sedimentation rate (ESR) in China. ESR measurements for healthy middlescent people were collected according to the Wintrobe method and the relationship between the reference value of middlescent people's ESR and altitude was tested in this paper It was found that the reference value of middlescent people's ESR decreases when the altitude gradually increases, and the relationship is quite significant. Univariate regression analysis was used to deduce two regression equations: Y1 = 13.14-0.00245X +/- 2.98 (males) and: Y2 = 22.00-0.00397X +/- 4.85 (females). If the altitude value of a particular area of China is known, the reference value of middlescent people's ESR can be calculated by means of these regression equations. Furthermore, depending on the altitude, China can be divided into three biogeographic districts: Qingzang District, Central District, and Eastern District.     

Sister-chromatid exchange in childhood in relation to age and sex

Small children have been found to have a lower SCE/cell than adults and in recent reports females have had higher SCEs/cell than males. We here describe the relationship between SCE/cell and age and sex in 46 girls and 39 boys with an age range of 1.4-19.2 years and 2.6-18.7 years, respectively. For the calculation a transformation y = (sum SCE)1/2 + (sum SCE + 1)1/2 was used. The best fit to our material was represented by the equation y = b0 + b1 X log age. A common slope (b1) could be used for the boys and girls. This slope was significantly different from zero (P less than 0.0005). The levels of the regression lines for the two sexes were different (P = 0.0006). The girls had a 0.55-0.7 higher SCE/cell than the boys, depending on age. The following equations were found: Girls: y = 22.49 + 6.53 X log age. Boys: y = 21.11 + 6.53 X log age. By this model 43% of the variation in y could be explained. As a consequence of the result it is absolutely essential, when planning studies of children, to use age-matched groups to decrease the variability of the test system.     

Predicting running velocity at blood lactate threshold from running performance tests in adolescent boys

The purpose of this study was to investigate the relationship between running velocity at blood lactate threshold (VLT) and running performance (50 m, 40 s and 5 min) in boys aged 14 years at puberty (n = 30) and young men aged 16-20 years (n = 39), and to examine the possibility of predicting VLT from running performances in boys during adolescence. Special attention was also paid as to whether these parameters are related to bone maturity in boys at puberty. After allowing for chronological age, height, weight and fat content, all the running performances were positively correlated to bone maturity in non-active boys at puberty. In contrast, VLT was negatively correlated to bone maturity. In spite of these results, VLT was significantly related to performance in the 5 min run in both the boys and the young men. However, the correlation coefficient for the former was significantly lower than that for the latter. The 5 min and 40 s runs were selected by stepwise regression analysis for predicting VLT in the two groups. The same predictor was selected from the combined data from both groups using the following equation: VLT(m X min-1) = 124 - 0.83 X 40 s run(m) + 0.202 X 5 min run(m). The correlation between actual and estimated VLT, and the standard error of the estimate of this formula were 0.726 and - 5 + 15 m X min-1 in the boys, and 0.880 and 4 + 11 m X min-1 in the young men, respectively. This formula was similar in precision to the formulae obtained from the data in each individual group.(ABSTRACT TRUNCATED AT 250 WORDS)     

中国青年人全血比粘度参考值与地理因素的关系

为制定中国青年人全血比粘度参考值的标准提供科学依据,收集了中国各地用毛细管法测定的健康青年人全血比粘度参考值,并对其与地理因素的关系进行了研究,发现海拔高度是影响青年人全血比粘度参考值最主要的因素,随着海拔高度的逐渐增大,青年人全血比粘度参考值也在逐渐的增大,相关性很显著。用逐步回归分析的方法推导出了２个回归方程。如果知道了中国某地的地理因素,就可以用这２回归方程估算这个地区的青年人全血比粘度参考     

通过骨盆外测量推算中骨盆径的一元和多元回归方程

本文以126例生育年龄非妊娠女工的髂结节间径、髂前上棘间径、大转子间径及坐骨结节间径为自变量估计因变量中骨盆横径,求出多元回归方程:=—6.89+0.05x_1+0.12x_2+0.23x_3+0.77x_4;以骶耻外径和骨盆倾斜度为自变量估计因变量中骨盆矢径,其回归方程为:=6.09+0.39x_1-0.05x_2。对两方程进行方差分析,其F值分别为4.069和8.26,均具高度显著性,可以应用于临床对中骨盆径的估计以取代X线测量法。     

基于地理因素的健康中老年(40-65)P_aO_2参考值预测研究

动脉血氧分压(P_aO_2)参考值是医学诊治的重要指标,并随地理因素的变化而变化.鉴于各地参考值的不同,本文从地理因素角度出发,利用各地的各项地理因素指标,与各地的健康中老年动脉血氧分压参考值建立相关分析和回归分析,以此建立较为精确的预测模型,用以验证已知地区和预测未知地区的参考值.其建立的预测模型为医学参考值的制定提供了新的方法,并促进了地理资源的实践发展.     

中国汉族男性腰椎的身高推断

本文研究了中国汉族男性腰椎的测量及腰椎推断身高的方法。测量指标有 :椎体前高、椎体后高、椎体上矢径、椎体下矢径、椎体上横径、椎体下横径、椎体中部横径、椎孔矢状径、椎孔横径、左侧椎弓根厚度。将各腰椎的测量数据与身高进行了相关分析并建立了中国汉族男性腰椎推断身高的回归方程。本研究所建立的方程 ,可以用于中国汉族男性腰椎的身高推断。     

Estimating height from arm span measurement in Malawian children

Arm span and standing height were measured in 289 boys and 337 girls aged 6-15 years who were free from physical deformities which can affect stature or arm span. The arm span exceeded height in all age groups of boys and in older girls. At the age of 7, 11 and 12 years girls were significantly taller than the boys and had longer arm span while at the age of 15 years, the trend was opposite. The mean difference between the two anthropometric parameters for boys was 5.45 +/- 4.21 cm (t = 3.556, p < 0.001) and for girls was 4.94 +/- 4.96 cm (t = 3.542, p < 0.001). Correlation coefficient between height and arm span measurements for Malawian boys was 0.983 and for girls was 0.986. Height, arm span and height-arm span difference increased with age of children while height to arm span ratio decreased. The gender difference in height-arm span differences was only significant at the age of 15 years. Multiple regression and cross validation were performed. Height of Malawian children of both sexes can be estimated from equation: Height (cm) = 15.756 + (0.168 x age) + (0.839 x arm span) (SEE = 0.760, R2 = 0.988).     

Prediction of Body Fat by Anthropometry in Older Chinese People

Objective: To derive regression equations for fat percentage by using simple anthropometric measurements applicable in normal and immobile (cannot stand or walk) older people. Research Methods and Procedures: The study population comprised 352 females and 261 males, apparently well and community‐dwelling, aged 69 to 82 years. Fifty‐one females and 27 males were recruited for external validation. Body weight, standing height, arm span, triceps and biceps skinfold thicknesses (SFTs), and midarm circumference were measured. The reference method of total body fat percentage was dual‐energy X‐ray densitometry. Predictive equations for fat percentages were derived by stepwise multiple linear regression on anthropometric indices and gender. Results: Upper‐limb SFTs, body mass index, and gender yielded the more predictive equation. The SEE was 4.1% weight. There was a significant trend of underestimation in overweight subjects, especially in females. The equation using SFTs and midarm circumference was less reliable but more applicable to older immobile people and those with significant kyphoscoliosis. Conclusions: The combination of body mass index and upper‐limb SFTs gives reliable prediction of fat percentages in older Chinese people, except in the obese.     

欧美杨杂交种'中嘉8'净光合速率与若干生态因子的相关分析

本文利用DPS数据处理系统,采用多元逐步回归及通径分析方法,得出欧美杨杂交种‘中嘉8’(Populusdeltoides CL.‘Zhongjia 8’)在6月和9月净光合速率与生态因子的关系。结果表明,‘中嘉8’在6月晴天净光合速率呈单峰曲线,其最主要影响因子为光合有效辐射PAR(X1),二者极显著相关,净光合速率日变化最优方程为:Y=17.8271 0.0108X1-0.2185X2;9月晴天净光合速率呈双峰曲线,影响光合速率日变化的最主要因子为空气CO2浓度Ca(X4),净光合速率日变化最优方程为:Y=5.2915-0.0030X1 0.3414X3-0.0216X4。统计分析表明,采用多元逐步回归及通径分析应用于统计光合速率与生态因子的相关关系,较二元变量的相关分析更为科学合理。     

红火蚁饵剂药瓶瓶盖孔洞设计与出药量的关系

红火蚁Solenopsis invicta Buren是一种对人类健康、生态环境等具有严重危害的重大入侵害虫,毒饵诱杀是防控红火蚁的重要手段.在采用人工撒施方法时,如何避免药剂浪费或不足仍需研究.本文研究了红火蚁饵剂药瓶瓶盖出药量与瓶盖上孔洞直径、孔洞数量和施药方式的关系,为红火蚁饵剂施药装置选择合适的孔洞直径、孔洞数量和施药方式提供理论依据.研究发现,在倾倒施药处理下,孔洞直径为3.0、4.0、5.0、6.0和7.0mm时,出药量与孔洞直径有显著的线性关系,线性方程依次为Z =0.02X-0.004、Z=0.007X-0.007、Z =0.015X-0.02、Z =0.026X+0.025和Z=0.097X-0.094(Z代表出药量,X代表孔洞数量),即孔洞越多,倾倒的出药量越多.施药方式为倾倒时,出药量与孔洞直径和孔洞数量有显著的线性关系,线性方程为Z=0.008X+0.106Y-0.464(Z代表出药量,X代表孔洞数量,Y代表孔洞直径),即出药量随孔洞数量或孔洞直径增加而增多.在撒播施药处理下,当孔洞直径为3.0 mm时,撒播的出药量与孔洞数量的线性关系不显著.当孔洞直径为4.0、5.0、6.0和7.0mm时,出药量与孔洞直径和孔洞数量有显著的线性关系,线性方程依次为Z=0.006X+0.037、Z =0.013X+0.018、Z=0.02X+0.093、Z=0.06X+0.03(Z代表出药量,X代表孔洞数量),即孔洞越多,撒播的出药量越多;撒播的出药量与孔洞直径和孔洞数量有显著的线性关系,线性方程为Z =0.006X+0.087Y-0.335(Z代表出药量,X代表孔洞数量,Y代表孔洞直径),即出药量随着孔洞数量或孔洞直径增加而增多.因此,厂家可参考上述线性方程,根据产品物理性状、有效施用剂量在毒饵瓶瓶盖上选择相应的孔洞直径和孔洞数量.     

泉州湾河口湿地主要红树植物叶面积测算

植物叶面积的测算对于评价生态系统初级生产力具有重要意义.本研究分别选用“最大叶长”、“最大叶宽”以及“最大叶长×最大叶宽”等指标,利用不同类型的线性或非线性回归方程,对泉州湾河口湿地主要红树植物秋茄、桐花树和白骨壤的叶面积进行测算,从而确定各自最佳拟合回归方程.结果表明:二元非线性回归方程Y=0.7297X10.8698 X2.11600、幂指数方程Y=0.9740X0.9634和Y=0.7773X 0.9954分别为秋茄、桐花树和白骨壤叶面积的最佳拟合回归方程.进一步的0-1回归检验和相对误差值分析显示,以上回归方程均能精确地估算各自的叶面积,其中,白骨壤叶面积测算更为精确.     

老年前期人红细胞压积参考值与中国地理因素的关系

运用相关分析和回归分析的方法,研究了老年前期人红细胞压积参考值与地理因素的关系,结果表明海拔高度是影响红细胞压积参考值最主要的因素。     

水稻品种抗虫特征次生物质及其对白背飞虱种群的抑制作用

应用高效液相色谱(HPLC)技术,对具有不同白背飞虱抗性水平的5个水稻品种25个样品中13个特征次生物质色谱峰进行了测定,并运用主成分分析和多元回归分析,建立了抗白背飞虱种群增长的预测模型:Y=152.0762+0.7749X4-13.1806X9-14.4265X10。检验结果表明,白背飞虱种群增长指数与特征峰面积之间极显著相关(r=0.9999,P=0.0058),其中峰4、峰9、峰10对应的次生化合物可能是影响水稻对白背飞虱抗性水平的主要抗原次生化合物;抗原特征峰面积总值与白背飞虱种群增长指数具有显著的相关性,拟合的线性回归方程为:Y=82.7086-2.3476X。因此,利用高效液相色谱法测定抗原特征次生物质,可以简捷、快速地测定大田白背飞虱种群在栽培品种上的发生动态,即间接估计该品种的抗虫性。此外,采用种群生命表技术与干扰作用控制指数IIPC值评价水稻品种对白背飞虱种群消长的影响,结果显示,中感品种籼小占、粤农占、小农占I总值分别为9.280、6.030、6.603,中抗虫品种粳籼89为3.689,而感虫品种双桂I为29.789,表明中抗虫品种对白背飞虱种群的抑制作用仍十分明显,而这种抑制作用主要表现在第二世代上。     

Modeling pulmonary and CNS O(2) toxicity and estimation of parameters for humans.

The power expression for cumulative oxygen toxicity and the exponential recovery were successfully applied to various features of oxygen toxicity. From the basic equation, we derived expressions for a protocol in which PO(2) changes with time. The parameters of the power equation were solved by using nonlinear regression for the reduction in vital capacity (DeltaVC) in humans: %DeltaVC = 0.0082 x t(2)(PO(2)/101.3)(4.57), where t is the time in hours and PO(2) is expressed in kPa. The recovery of lung volume is DeltaVC(t) = DeltaVC(e) x e(-(-0.42 + 0.00379PO(2))t), where DeltaVC(t) is the value at time t of the recovery, DeltaVC(e) is the value at the end of the hyperoxic exposure, and PO(2) is the prerecovery oxygen pressure. Data from different experiments on central nervous system (CNS) oxygen toxicity in humans in the hyperbaric chamber (n = 661) were analyzed along with data from actual closed-circuit oxygen diving (n = 2,039) by using a maximum likelihood method. The parameters of the model were solved for the combined data, yielding the power equation for active diving: K = t(2) (PO(2)/101.3)(6.8), where t is in minutes. It is suggested that the risk of CNS oxygen toxicity in diving can be derived from the calculated parameter of the normal distribution: Z = [ln(t) - 9.63 +3.38 x ln(PO(2)/101.3)]/2.02. The recovery time constant for CNS oxygen toxicity was calculated from the value obtained for the rat, taking into account the effect of body mass, and yielded the recovery equation: K(t) = K(e) x e(-0.079t), where K(t) and K(e) are the values of K at time t of the recovery process and at the end of the hyperbaric oxygen exposure, respectively, and t is in minutes.