北京市6~18岁儿童青少年LMS法体脂百分位数参考值分析

采用LMS法拟合北京市6~18岁儿童青少年体脂率百分位数参考值曲线,为进一步制订儿童青少年体脂率肥胖判定标准及儿童青少年肥胖的监测提供参考依据.方法 在北京地区抽取7 435名6~18岁儿童青少年,采用生物电阻抗方法(BIA,Inbody230)对北京市7 435名6~18岁儿童青少年进行身体成分测定,应用LMS chartmaker软件分别拟合男女生体脂率随年龄变化的百分位数曲线图.以P3,P10,P15,P20,P25,P50,P75,P80,P85,P90,P97作为参考曲线.结果 6~12岁儿童青少年在相同年龄段内男女生体脂率性别差异较小,但13~18岁男女生体脂率存在性别差异(P值均<0.01).百分位数曲线显示,6~11岁男生体脂率随年龄缓慢增长,11 ~ 15岁明显下降,15岁以后保持平稳状态,而女生体脂率在6~18岁呈现随年龄增长而持续增长的趋势.结论 用LMS方法构建的体脂率百分位数曲线可正确反映儿童青少年生长发育的规律.普及LMS方法对于制订与健康体质相关的儿童青少年百分位数标准具有重要意义.     

用LMS法建立西安市0～18岁儿童青少年身高百分位数曲线

目的　年龄别百分位数曲线是生长标准的最科学的表现形式,本文研究一种适用于各种分布,能更精确描述这些基本参数随年龄变化的曲线平滑方法。　方法　采用LMS(λ—中位数—变异系数) 法对西安市0～18 岁儿童青少年身高百分位数进行拟合。　结果　计算了城男、城女、乡男、乡女的年龄别λ( L) ,中位数( M) ,变异系数(S) 值,给出了各组的百分位数曲线图。　结论　LMS 法用于拟合身高百分位数,结果非常满意     

上海市儿童青少年腰围百分位数值及曲线

目的 建立适合上海市儿童青少年生长发育特点的年龄别腰围、腰围指数的百分位数及曲线,为科学评价儿童青少年生长发育水平及中心性肥胖的防治提供参考.方法 以2010年上海市学生体质健康调研的7 ～18岁中小学生14 301名为样本,应用国际通用的LMS法分性别建立年龄别腰围、腰围指数正常值及百分位数曲线.结果 腰围百分位数曲线随年龄增长呈递增趋势,符合儿童青少年生长发育规律;腰围指数的P50百分位数曲线具有明显性别差异,7 ～12岁男生逐年上升,且高于女生,自13岁开始经交叉后低于女生.获得上海市7 ～18岁儿童青少年男女年龄别腰围、腰围指数百分位数(P5,P10,P15,P50,P85,P95,P95)及曲线.结论 儿童青少年年龄别腰围、腰围指数百分位数存在地区、性别差异.本研究所获得的百分位数及曲线可为进一步研究儿童青少年中心性肥胖提供基本数据.     

生长曲线偏度系数-中位数-变异系数法不同软件实现方法的比较

目的探讨不同软件对生长曲线偏度系数-中位数-变异系数(LMS)法的实现方法,优选适合基层使用的统计方法。方法使用包头市定期体检正常婴儿的3、6、9和12月龄头围数据,分别应用SAS、R、STATA和SPSS软件包进行生长曲线的LMS拟合,并从方便程度、难易程度、界面、结果展示及更新维护等4个方面对几种软件的使用效果进行评价。结果使用不同软件分别实现了生长曲线LMS的计算和绘图,绘制的包头市婴儿的头围生长曲线的各百分位数值结果一致。从操作步骤、难易程度、操作界面、操作选项、更新维护、软件成本和结果展示来看,R软件更具优势。结论在常用生长曲线LMS的计算和绘图方面,与SAS、STATA和SPSS软件相比,R软件综合了各软件的优点,比较适于基层妇幼保健工作者使用。     

上海市7～18岁学生体质指数百分位数参考值研究

目的采用偏度-中位数-变异系数(LMS)法拟合上海市7~18岁学生体质指数(BMI)百分位数参考值曲线,为儿童青少年肥胖监测提供参考依据。方法采用分层随机整群抽样法在上海市抽取15 259名7~18岁学生,测量身高和体重,应用LMS Chartmaker软件分别拟合男女生BMI随年龄变化的百分位数曲线图。以P_3、P_5、P_(10)、P_(15)、P_(25)、P_(50)、P_(75)、P_(85)、P_(90)、P_(95)、P_(97)作为参考曲线。结果随着年龄增长,男、女生BMI均呈增长趋势;男生BMI在各年龄段均高于女生。上海市男、女生各年龄组BMI的P_(50)均高于全国水平,BMI的P_(85)和P_(95)前期基本与全国水平持平,后期则高于全国水平。百分位数曲线显示,男生自9岁开始进入BMI增长高峰,12岁之后增长缓慢,18岁曲线仍呈一定的上升;女生自10岁开始进入BMI增长高峰,14岁之后增长缓慢,16岁以后曲线趋于平稳。结论用LMS法构建的BMI百分位数曲线能直观反映儿童青少年生长发育的规律;上海市儿童青少年BMI高于全国水平。     

上海市儿童青少年肺功能百分位数参考值

建立符合上海市儿童青少年生长发育特点的肺活量参考值及曲线,为监测本地区儿童青少年功能水平变化提供参照.方法 以2014年上海市学生体质与健康调研6区15 421名7~18岁学生为样本,用偏度中位数—变异系数(LMS)法建立年龄别肺活量百分位数值及曲线.结果 随着年龄增长,男、女生肺活量呈上升趋势,在12岁之前差异不大,12岁之后差异逐渐增大,各年龄组均为男生高于女生(P值均<0.01).2014年上海市中小学生肺活量百分位数曲线随年龄增加呈增长趋势,各年龄组均高于全国同期水平,上海市儿童青少年肺活量百分位数存在性别差异.结论 儿童青少年肺活量百分位数曲线图为上海市儿童青少年功能水平测量提供了一种直观评价方式.     

上海市7~18岁儿童青少年身体形态长期变化趋势

了解上海市7~18岁儿童青少年2000--2014年身体形态指标的变化趋势,为儿童青少年生长发育监测提供理论依据.方法 从200-2014年上海市学生体质与健康调研数据中,抽取7~18岁儿童青少年为研究对象,运用LMS法拟合儿童青少年身高、体重主要百分位数值及曲线,并观察其变化趋势.结果 14年间,男生P5,P15,P5o,P85,P95身高平均增幅分别为3.5,3.4,3.2,3.1,3.1 cm,女生分别为2.6,2.5,2.3,2.3,2.4 cm;男生P5,P15,P50,P85,P95体重平均增幅分别为3.3,3.9,5.3,7.4,9.2 kg,女生分别为2.2,2.5,3.3,4.6,5.8 kg.男女生体重平均增长幅度均为高百分位数大于低百分位数,身高则是低百分位数大于高百分位数(P值均<0.01);不同群体的身高最大增幅的出现年龄均提前,城市男生、城市女生、郊区男生生长最大发育年龄提前,提前幅度表现为郊区男生(0.45)>城市女生(0.35》城市男生(0.26).结论 上海市儿童青少年身体形态正经历生长发育的长期变化趋势,需注意身高、体重不同百分位数人群增长特点.     

中国8个城市中学生腰围身高比值界值点和百分位数曲线

目的确定城市中学生腰围身高比值(WHtR)的界值点并制作WHtR的百分位数曲线图,为临床评价儿童青少年生长发育和防控心血管疾病提供参考。方法对北京、绍兴、广州、太原、哈尔滨、鄂州、重庆和贵阳8个城市28所中学的初一、初二、高一、高二学生11 307名进行人体测量。采用偏相关和受试者工作特征曲线分析方法,分析WHtR与心血管疾病危险因素的关联强度,确定WHtR的界值点;采用LMS法建立WHtR的百分位数曲线。结果与WHtR关联性最强的2个因素是收缩压和三酰甘油,男生WHtR与收缩压和三酰甘油的相关系数分别为0.32和0.16(P值均<0.01),女生的相关系数分别为0.23和0.09(P值均<0.01);用关联性最强的2个因素(性别年龄组P85)预测WHtR的界值点,男、女生分别为0.436和0.450。百分位数曲线显示,12～13岁男生WHtR各百分位数曲线普遍高于女生,14～18岁女生WHtR的各百分位数曲线普遍高于男生。男生从12岁以后WHtR的P50开始下降,15岁WHtRP50最低,16岁以后又开始增加;女生WHtRP5012岁开始相对平稳,15岁开始升高。结论 WHtR可考虑用于临床监测,用LMS方法制定的WHtR百分位数曲线可正确反映儿童青少年生长发育。     

中国大中城市汉族儿童青少年身高、体重和体质指数生长图表

【目的】制订中国大中城市汉族儿童青少年生长图表,为儿童期和青春期生长发育评价提供参考。【方法】应用Box-Cox幂指数(BCPE)分布模型,以三次样条函数平滑μ,σ,ν,τ参数曲线,拟合身高、体重和体质指数百分位数曲线。以虫行图、Q-检验估价拟合优度。【结果】根据最小AIC和GAIC(3)选择了各生长学指标BCPE模型μ,σ,ν,τ参数的自由度,拟合了百分位数曲线。【结论】BCPE分布模型适用于儿童青少年生长学指标平滑百分位数的估价,所制订的身高、体重和体质指数生长图表将有助于了解儿童青少年的生长发育状况。     

用LMS法建立西安市O～18岁人群体重百分位数曲线

目的年龄别百分位数是许多临床参考值的基本参数,本文研究一种适合于任意分布,能更精确描述这些基本参数随年龄变化的曲线平滑方法。方法采用LMS法建立西安市0～18岁人群青少年体重百分位数曲线。结果给出了各组的年龄别L,M,S曲线和百分位数曲线。结论该法用于西安市0～18岁人群体重百分位数曲线的拟合结果非常满意。     

5岁以下儿童手腕骨发育指数骨龄评价方法

【目的】 提出5岁以下婴幼儿骨龄评价方法。 【方法】 研究样本为《中国人手腕骨发育标准-中华05》研究中5岁以下组的2 468名(男1 245,女1 223)儿童,使用以概率单位法计算的TW3骨发育等级出现年龄为骨发育指数,采用LMS方法拟合手腕部桡尺、掌指骨(radius, ulna and short bones,RUS)、腕骨(carpal,CARP)(R+C)以及单独CARP的发育指数百分位数曲线。 【结果】 绘制出手腕部R+C和CARP法骨发育指数P₃、P₁₀、P₂₅、P₅₀、P₇₅、P₉₀、P₉₇评价图,拟合百分位数曲线下受试者例数的百分数与理论期望值相差在0.1%~2.3%之间。手腕骨发育速度存在明显的性别差异,男女R+C骨发育指数分别在1岁和0.5岁后、CARP发育指数分别在1.5岁和1岁后迅速增加,而且女童增加速度均明显大于男童。 【结论】 男女婴幼儿手腕部骨化中心在0.5岁后陆续出现,可参考使用R+C和CARP骨发育指数百分位数曲线图评价婴幼儿骨龄。     

Statistical methodology for constructing gestational age-related charts using cross-sectional and longitudinal data: The INTERGROWTH-21st project as a case study

Most studies aiming to construct reference or standard charts use a cross-sectional design, collecting one measurement per participant. Reference or standard charts can also be constructed using a longitudinal design, collecting multiple measurements per participant. The choice of appropriate statistical methodology is important as inaccurate centiles resulting from inferior methods can lead to incorrect judgements about fetal or newborn size, resulting in suboptimal clinical care. Reference or standard centiles should ideally provide the best fit to the data, change smoothly with age (eg, gestational age), use as simple a statistical model as possible without compromising model fit, and allow the computation of Z-scores from centiles to simplify assessment of individuals and enable comparison with different populations. Significance testing and goodness-of-fit statistics are usually used to discriminate between models. However, these methods tend not to be useful when examining large data sets as very small differences are statistically significant even if the models are indistinguishable on actual centile plots. Choosing the best model from amongst many is therefore not trivial. Model choice should not be based on statistical considerations (or tests) alone as sometimes the best model may not necessarily offer the best fit to the raw data across gestational age. In this paper, we describe the most commonly applied methodologies available for the construction of age-specific reference or standard centiles for cross-sectional and longitudinal data: Fractional polynomial regression, LMS, LMST, LMSP, and multilevel regression methods. For illustration, we used data from the INTERGROWTH-21^st Project, ie, newborn weight (cross-sectional) and fetal head circumference (longitudinal) data as examples.     

Worm plot: a simple diagnostic device for modelling growth reference curves

The worm plot visualizes differences between two distributions, conditional on the values of a covariate. Though the worm plot is a general diagnostic tool for the analysis of residuals, this paper focuses on an application in constructing growth reference curves, where the covariate of interest is age. The LMS model of Cole and Green is used to construct reference curves in the Fourth Dutch Growth Study 1997. If the model fits, the measurements in the reference sample follow a standard normal distribution on all ages after a suitably chosen Box-Cox transformation. The coefficients of this transformation are modelled as smooth age-dependent parameter curves for the median, variation and skewness, respectively. The major modelling task is to choose the appropriate amount of smoothness of each parameter curve. The worm plot assesses the age-conditional normality of the transformed data under a variety of LMS models. The fit of each parameter curve is closely related to particular features in the worm plot, namely its offset, slope and curvature. Application of the worm plot to the Dutch growth data resulted in satisfactory reference curves for a variety of anthropometric measures. It was found that the LMS method generally models the age-conditional mean and skewness better than the age-related deviation and kurtosis.     

Smooth centile curves for skew and kurtotic data modelled using the Box-Cox power exponential distribution

The Box-Cox power exponential (BCPE) distribution, developed in this paper, provides a model for a dependent variable Y exhibiting both skewness and kurtosis (leptokurtosis or platykurtosis). The distribution is defined by a power transformation Y(nu) having a shifted and scaled (truncated) standard power exponential distribution with parameter tau. The distribution has four parameters and is denoted BCPE (mu,sigma,nu,tau). The parameters, mu, sigma, nu and tau, may be interpreted as relating to location (median), scale (approximate coefficient of variation), skewness (transformation to symmetry) and kurtosis (power exponential parameter), respectively. Smooth centile curves are obtained by modelling each of the four parameters of the distribution as a smooth non-parametric function of an explanatory variable. A Fisher scoring algorithm is used to fit the non-parametric model by maximizing a penalized likelihood. The first and expected second and cross derivatives of the likelihood, with respect to mu, sigma, nu and tau, required for the algorithm, are provided. The centiles of the BCPE distribution are easy to calculate, so it is highly suited to centile estimation.This application of the BCPE distribution to smooth centile estimation provides a generalization of the LMS method of the centile estimation to data exhibiting kurtosis (as well as skewness) different from that of a normal distribution and is named here the LMSP method of centile estimation. The LMSP method of centile estimation is applied to modelling the body mass index of Dutch males against age.     

西安市城区2009年7~18岁儿童、青少年超重和肥胖流行病学调查

【目的】 了解西安市城区儿童、青少年超重和肥胖的发病情况。 【方法】 随机整群抽取西安市城区7~18岁中小学生13 994人,采用体质指数(body mass index,BMI)诊断超重和肥胖。采用三次样条对西安市7~18岁儿童青少年体重、身高和BMI百分位数进行拟合,将身高,体重P₅₀,及BMI的P₈₅、P₉₅百分位数值与2005年中国全国标准进行比较。 【结果】 西安市城区7~18岁中小学生超重总发病率为10.42%,男生和女生分别为11.85%和8.83%;肥胖总发病率为4.67%,男生和女生分别为4.92%和4.40%。男生身高P₅₀值在10~15岁(除12岁)比全国标准稍低,男女体重和女生身高P₅₀中位数与全国数值基本接近;男生BMI的P₈₅、P₉₅数值与2005年全国水平基本接近;女生P₈₅和P₉₅值在14岁以前与全国水平基本接近,15岁后有所减低。 【结论】 西安市中小学肥胖发病率在17年间增加了一倍,制定预防儿童超重和肥胖的有效措施势在必行。     

Smoothing reference centile curves: the LMS method and penalized likelihood.

Refence centile curves show the distribution of a measurement as it changes according to some covariate, often age. The LMS method summarizes the changing distribution by three curves representing the median, coefficient of variation and skewness, the latter expressed as a Box-Cox power. Using penalized likelihood the three curves can be fitted as cubic splines by non-linear regression, and the extent of smoothing required can be expressed in terms of smoothing parameters or equivalent degrees of freedom. The method is illustrated with data on triceps skinfold in Gambian girls and women, and body weight in U.S.A. girls.     

乌鲁木齐市维吾尔族和汉族7～18岁人群体重指数分类标准比较

目的探讨使用偏度-中位数-变异系数法（LMS法）建立并比较乌鲁木齐市7～18岁维吾尔族（维族）和汉族青少年超重、肥胖的体重指数（BMI）分类标准。方法采用分层整群抽样方法，调查新疆乌鲁木齐市7～18岁维、汉族中小学生9146人，绘制两民族7～18岁青少年年龄别、性别BMI百分位曲线，确定18岁时分别通过国际肥胖工作组（IOTF）和中国肥胖问题工作组（WGOC）成年人超重、肥胖标准的特殊百分位数曲线，由此获得两民族7～18岁人群超重和肥胖的界值标准。结果18岁时通过25及30kg／m^2的百分位曲线：维族男生为P94.46和P99.58，维族女生为P92.44和P99.64，汉族男生为P85.05和P97.26，汉族女生为P90.92和P99.03；通过24及28kg／m^2的百分位曲线维族男生为P90.54和P98.86，维族女生为P86.96和P98.77，汉族男生为P78.98和P94.72，汉族女生为P86.15和P97.56。结论BMI分布具有民族特异性；对维族青少年超重、肥胖筛检时建议参考使用该研究标准。     

配对四格表资料χ2检验在 SPSS 和 SAS 软件中的实现

目的：通过实例来介绍配对四格表资料的卡方检验在SPSS和SAS统计分析软件中如何操作,输出结果的区别及正确的解读,为临床及相关科研人员提供可以借鉴的方法。方法使用SPSS和SAS统计软件,对配对四格表资料的卡方检验进行操作和分析。结果本文以两种方法诊断肺癌的检测结果为例题,根据基本公式算得统计量χ2＝4．92,P＜0．05,得出两种诊断方法的诊断结果存在差异。在SPSS软件的分析结果中只有P值,SAS软件的分析结果可以给出统计量和P的确切值,但统计量χ2＝6．23,与基本公式计算的结果不同,经过自编程序运行后,我们得到了与基本公式相同的结果。结论 SPSS和SAS统计软件是医学统计学数据分析的常用教学软件,本文通过实例详解,得出在结果的输出方面两种软件有很大区别,但这并不影响我们得出相同的统计结论。 SPSS软件操作简便,SAS软件编程比较麻烦,以及SAS软件在处理此类资料上存在默认不校正的问题,因此,在实际应用中,我们可以根据情况自行选择。     

SHORT REPORT: Suitability of revised UK reference data for the assessment of nutritional status in 7-year-old children

Introduction: Nutritional assessment in clinical practice and epidemiology requires comparison of anthropometric measurements with appropriate reference data, but the reference data recommended for the UK are largely untested. The aim of the present study was to test the suitability of the ‘Revised UK 1990’ reference data for height, weight and body mass index (BMI) in a representative sample of 7-year-old children. Methods: Measurements made in 255 children in Edinburgh (n=123 girls; 132 boys) were compared with the ‘Revised UK 1990’ reference data using standard deviation (SD) scores. The proportion of children both expected and observed to fall below the 10th centile and above the 90th centile were calculated. Results: In boys, mean (±SD) scores were not significantly different from zero for height (?0.02±0.95), weight (0.07±1.01) and BMI (0.10±1.03), and there was good agreement between expected and observed frequencies <10th and >90th centiles for all three variables. In the girls, mean (±SD) scores did not differ significantly from zero: height (?0.08±0.91); weight (?0.18±0.98); BMI (?0.18±1.02), and there were no significant differences relative to the 10th and 90th centile cut-offs for height and BMI. Conclusion: This study supports the use of the currently recommended height, weight and BMI reference data to define under- and over-weight for height in children.     

Growth patterns of Qatari school children and adolescents aged 6-18 years

The study was conducted to analyze the patterns of growth in height and weight and the prevalence of over-weight among Qatari school children aged 6-18 years. Weights and heights of a cross-sectional sample of Qatari school children were measured. These children were selected randomly, in equal proportions of age and gender, from different schools from urban and semi-urban districts. Appropriate statistical procedures were performed to produce smooth percentile curves for boys and girls using a two-stage approach. Initial curve smoothing for selected major percentiles was accomplished by various paramet-ric and non-parametric procedures. In the second stage, a normalization procedure was used for creating z-scores that closely matched the smooth percentile curves. The height and weight results were compared with the international reference values of National Center for Health Statistics/Centers for Disease Control and Prevention (NCHS/CDC). The prevalence of over-weight was calculated using the new International Obesity Task Force (IOTF) reference. Of 7442 Qatari children studied, 50.3% were male and 49.7%' female. The mean values for height, weight, and body mass index (BMI) increased with the age for both boys and girls until the age of 18 years, except BMI, which stabilized at the age of 16-18 years at around 22.6 for boys and at 21.6 for girls. The growth patterns of the Qatari children, aged 6-18 years, appeared to be comparable with those of the NCHS/CDC reference. The weight-for-age centile curves of the Qatari boys tended to be superior to those of the NCHS/CDC reference until the age of 15 years, less so those of the Qatari girls. In contrast, the height-for-age centile curves of the Qatari children tended to deviate in a negative sense from the NCHS/CDC reference curves, for boys and girls from age around 11 years and 13 years respectively. The deviation of the smoothed median height-for-age curves from the reference in adolescence could most likely be attributed to a later maturation among the Qatari children. The prevalence of under-weight, over-weight, and obesity for the Qatari children was quite below the CDC and IOTF rates, except for girls aged 6-9 years. More males than females were over-weight or obese according to either the local, the CDC, or the IOTF reference, and the prevalence increased with age. A good percentage of the Qatari children was at risk of being over-weight, which needs more attention because the development of obesity results in different types of diseases associated with changes in body composition.