体重指数、体表面积对中老年女性股骨骨密度的影响

目的了解体重指数(BMI)、体表面积(BS)对中老年女性股骨近端骨密度的影响。方法①采用美国LUNAR公司的EXPERT-XL双能X线骨密度仪测定成都地区女性健康体检者421例,按年龄分成两组40~59岁、60~80岁组;测量部位包括股骨颈(Neck)、大转子(Troch)、Wards区、股骨干(shaft)、全髋(total)。②不同年龄组分别按BMI大小分成3组BMI≤20kg/m2,(20~25)kg/m2,≥25kg/m2;BS大小分成3组大体表面积组(LBSG),中体表面积组(IBSG),小体表面积组(SBSG)。③结果用SPSS12.0统计软件处理,体重指数、体表面积与股骨近端各部位骨密度用spearson相关分析,不同年龄组、不同BMI、BS组间比较用方差分析。结果①体重指数、体表面积与股骨骨密度呈正相关,r=0.122~0.424(P<0.005);②不同年龄组股骨近端骨密度均为BMI≤20kg/m2组IBSG>SBSG,差异有统计学意义。结论体重指数(BMI)、体表面积(BS)均是影响股骨近端骨密度的重要因素,低BMI、BS中老年女性应注意骨质疏松诊断、防治。     

体重质量指数与557例绝经后妇女骨密度变化的关系研究

目的 了解不同的年龄绝经后妇女不同体重质量指数(BMI)与不同部位骨密度(BMD)的关系。方法 来自门诊健康体检的557名绝经后妇女(肝肾等疾病除外),年龄范围50~78岁。用双能X线吸收法(DEXA)测定腰椎(L2-4)、股骨颈、Ward's三角及Troch等部位的BMD,同时计算BMI。根据BMI将研究对象分为3组:低体重组(BMI≤20 kg／m2)、正常体重组(25≥BMI>20 kg/m2)及超重组(BMI>25 kg/m2)。根据年龄又分为3组(50-,60-,70~78岁),用方差分析的方法进行各组间均数的统计学分析。结果不同BMI组总体不同部位的BMD方差分析比较有极显著意义P<0.01,高BMI组的BMD均值明显增高;进一步对同一年龄组不同BMI组的不同部位的BMD均值比较,各组之间均有显著性差异(P<0.01),特别是低体重组的骨密度明显低于其他两组BMI组的BMD。结论BMI与绝经后妇女的骨密度有显著相关,但低体重的绝经后妇女作为骨折的危险人群应受到更多的关注:对于超重的绝经后妇女,通过增加体重的方式增加BMD是危险的,因为超重与高血压、冠心病、糖尿病、心肌梗死及中风有一定的关系;通过其他途径:如年轻时加强运动、多饮牛奶、不盲目减肥等,提高妇女峰值骨含量是非常重要的。     

身高、体重、体重指数对绝经后妇女全身骨密度的影响

目的 探讨绝经后妇女骨密度（BMD）与身高、体重、体重指数（BMI）的关系。方法 对南京地区50岁以上绝经后妇女794人，按身高、体重和BMI，将受检者分为3组：低体重组，正常体重组和超体重组，采用双能X线骨密度（DEXA）测定受检者腰椎2-4、股骨上端及全身MBD。结果 腰椎、股骨和全身MBD随体重、BMI增加而增高。各组间腰椎、股骨和全身MBD均有显著差异（P〈0．01）。身高、体重、BMI与腰椎、股骨及全身的BMD呈正相关。体重比身高、BMI与BMD相关性好。结论 体重对绝经后妇女BMD影响较身高和BMI大，低体重是发生骨质疏松（OP）的危险因素之一，对低体重（BMI≤20kg／m^2）绝经后妇女采取适当措施防治OP，以免发生骨折。     

身高、体重及体重指数对辽宁地区正常中老年人骨矿含量的影响

目的　调查分析身高、体重及体重指数 (BMI)对辽宁地区正常中老年人群骨矿含量的影响。方法　在辽宁地区年龄在 40～ 79岁的中老年人群中随机抽样 173 1例 ,除外可能导致继发性骨质疏松症的各种疾病 ,应用美国lunar公司生产的双能X线骨密度仪 ,分别测试受试者的腰椎及股骨上段的骨密度 (BMD) ,全部资料输入微机 ,用SPSS软件进行统计学处理。结果　身高与腰椎及股骨上段的BMD相关性较差 (r=0 0 87～ 0 197,P <0 0 5 ) ,体重与腰椎及股骨上段的BMD相关性较好(r=0 2 2 6～ 0 3 5 2P <0 0 1)。体重指数与腰椎的相关性最好 ,其次是大转子。腰椎及股骨颈的BMD在超体重组 (BMI>2 5kg/m2 )明显大于低体重组 (BMI≤ 19kg/m2 ) ,其差异有显著性 ,该特点在腰椎最为明显。结论　体重是影响中老年人骨矿含量的重要因素。对低体重的中老年人 (BMI≤ 19kg/m2 )可作为骨质疏松症的易发人群 ,及时监测BMD ,早期预防及治疗     

成都市中老年健身女性体成分指标与骨密度和骨代谢指标的相关性研究

目的探讨体重、体重指数(BMI)等体成分指标对中老年健身运动女性骨密度的影响及体成分指标与骨代谢指标、骨密度指标的关系。方法94例成都市城区健身运动女性根据BMI不同分为三组:低体重组(BMI≤20kg/m2)、正常体重组(20kg/m225kg/m2),采用Osteospace超声骨密度仪测定跟骨的BUA、SOS、STI骨密度指标;全自动生化分析仪测定血清AKP含量;应用放射免疫法测定血清hCT、BGP、IL-6、E2、TNF含量。应用方差分析和偏相关方法进行统计学处理。结果不同BMI组的体重、体重指数、瘦体重和体脂百分比差异显著,低体重组T-score与正常体重组、超重组比较有极显著差异;低体重组SOS、STI骨密度指标显著低于正常体重组;BUA、SOS、STI骨密度指标与体重、体重指数、瘦体重和体脂百分比呈正相关,与hCT、IL-6、TNF、BGP、AKP呈正相关,与E2呈负相关。低体重组骨量减少、骨质疏松发生率最高。结论体重、体重指数等体成分指标是影响中老年健身运动女性BMD的重要因素,保持体重有利于防止骨丢失和预防骨质疏松发生。     

体重、体重指数、腰围、腰臀比对绝经后2型糖尿病患者骨密度的影响

目的 探讨体重、体重指数(body mass index,BMI)、腰围、腰臀比等指标对绝经后2型糖尿病患者骨密度的影响.方法 采用双能X线骨密度仪测量162例绝经后2型糖尿病患者不同部位的骨密度,按年龄分两组(A组:＜60岁;B组:≥60岁),同一年龄段按体重指数各分为两组(L-BMI组:BMI＜25 kg/m~2;H-BMI组:BMI≥25 kg/m~2)进行分析.结果 H-BMI组多部位骨密度明显高于L-BMI组(P＜0.05或P＜0.01).年龄与骨密度呈负相关,体重与骨密度呈正相关.结论 体重及体重指数均与骨密度相关,其中体重是影响绝经后妇女骨密度的重要因素.     

青少年强直性脊柱炎早期年龄、身高、体重、体重指数与腰椎骨量、骨密度的相关性初步分析

目的研究青少年强直性脊柱炎(Ankylosing spondylitis,AS)早期年龄、身高、体重、体重 指数(BMI)与腰椎骨矿含量(L1-4 BMC、L2-4 4BMC)、腰椎面积骨密度(L1-4 BMD、L2-4 BMD)、腰椎体积表观骨密度(L1-4 BMAD、L2-4 BMAD)之间的相关性,旨在初步探讨我国青少年AS早期骨量、骨密度的重要相关因素及评价指标.方法选择男性青少年AS早期患者31例,统计AS患者年龄(y)、身高(cm)、体重(kg)、BMI(kg/m2)、病程(mon)及ESR(mm/h)等变量,应用DPX-IQ双能X线骨密度仪(DEXA)检测L1-4BMC、L2-4 4BMC、L1-4BMD和L2-4BMD,计算L1-4BMAD和L2-4 BMAD(BMAD=BMC/面积3/2,g/cm3);采用相关和回归分析研究多因素相关性.结果年龄、身高、体重、BMI、病程、ESR、L1-4 BMC、L2-4 BMC、L1-4BMD、L2-4BMD、L1-4BMAD和L2-4BMAD的变量值分别为(17.56±2.01)y、(168.52±8.59)cm、(56.13±12.72)kg、(19.65±3.42)kg/m2、(19.61±12.39)mon、(21.71±10.04)mm/h、(52.16±12.17)g、(41.29±9.59)g、(0.971±0.139)g/cm2、(0.984±0.142)g/cm2、(0.1332±0.0146)g/m3和(0.1527±0.0173)g/m3.双因素相关分析初步证实AS早期ESR增高(51.61%AS患者ESR≥20mm/h)且与腰椎骨量、骨密度呈负相关(r=-0.509～-0.424、P=0.003～0.018).多因素回归分析表明仅体重因素进入L1-4BMD(R=-0.657,P=0.000)、L2-4BMD(R=0.620,P=0.000)、L1-4 BMAD(R=0.551,P=0.001)和L2-4BMAD(R=0.510,P=0.003)回归疗程;另一方面,身高因素成为L1-4 BMC(R=0.676,P=0.000)和L2-4BMC(R=0.673,P=0.000)主要相关因素而被纳入其回归方程.结论身高和体重即成为青少年AS早期骨量及骨密度的重要相关因素.此时期重视发挥二因素对腰椎骨矿含量和骨密度的正相关作用,将对于减缓青少年AS早期骨量丢失及AS相关性骨质疏松症有积极意义.     

年龄、身高、体重、体重指数对福州地区中老年男性骨密度的影响

目的调查分析年龄、身高、体重及体重指数（Body Mass Index,BMI)对福州地区中老年男性人 群腰椎、股骨颈、ward’s区和大转子骨密度的影响。方法在福州地区进行随机抽样338例中老年男 性,采用双能载线骨密度仪检测腰椎、股骨颈、ward’s区和大转子骨密度,记录年龄,测量身高、体重,计算出体重指数。应用SPSS19.0统计软件进行年龄、身高、体重、BMI与各部位骨密度Pearson相关 分析及组间单因素方差分析（AN0VA )。结果中老年男性的年龄与股骨颈和ward ''区骨密度相关 十分显著,高龄组（S75岁）骨密度明显低于低龄组（<60岁）;中老年男性的身高与腰椎、股骨颈、和大转子骨密度显著相关,身高170 cm以上组人群具有较高骨密度;中老年男性的体重、BMI与腰 椎、大转子骨密度显著相关,低体重组（<60噪早）及低BMI组（BMI<19 )骨密度明显更低,差异具有显 著性意义。结论年龄、身高、体重和体重指数是影响福州地区中老年男性骨密度的重要因素,低体重 指数的老年男性骨密度较低,应及时检测骨密度,以早期诊断和防治骨质疏松症。     

南宁地区成年女性骨密度与年龄、体重指数关系的研究

目的 研究南宁地区成年女性骨密度(BMD)与年龄、体重指数(BMI)之间关系.方法 采用双能X线骨密度仪测量384例年龄20～87岁的女性腰椎正位和股骨近端的BMD;分别按年龄和BMI分组,分析各年龄组和各BMI组BMD和骨质疏松(OP)检出率的变化.结果 ①腰椎和股骨近端骨峰值均出现在30～39岁组;50岁后BMD明显降低,70岁后再次出现BMD降低加速.②OP在50岁后明显增加,并以每增加10岁OP增加20%以上的速度发展,80岁后OP发生率近100%.③与正常BMI和超BMI组相比,低BMI组BMD显著降低,OP显著增高.结论 南宁地区成年女性BMD峰值在30～39岁;绝经后、年龄70岁以上和低BMI是OP发生危险因素.     

成年女性体表面积与不同骨骼部位骨密度关系及其患骨质疏松的风险

目的调查成年女性体表面积（BS）与不同骨骼部位骨密度（BMD）之间的关系,及BS大小不同的受试者各骨骼部位患骨质疏松的风险.方法用双能X线骨密度仪测量3418例成年女性腰椎后前位、侧位及髋部和前臂BMD.结果BS与不同骨骼部位的BMD呈显著性正相关（r=0.114～0.373,P=0.000）,但与腰椎侧位体积BMD（vBMD）不相关.以身高、体重、体重指数（BMI）、体表面积（BS）作为自变量,以BMD作为因变量的多元逐步回归分析显示：影响后前位腰椎、髋部和前臂BMD的最重要的变量是BS.按BS大小将该人群分为3组：大体表面积组（LBSG）、中等体表面积组（IBSG）和小体表面积组（SBSG）.各骨骼部位的BMD按BS大小呈递增变化（腰椎侧位除外）：LBSG＞IBSG＞SBSG;而骨质疏松的患病率和发病风险向相反的方向变化：LBSG＜IBSG＜SBSG.结论成年女性BS与BMD的关系超过身高和体重.用面积BMD表达时,BS较大者BMD较高和患骨质疏松的风险较小,BS较小者BMD较低和患骨质疏松的风险较大.用vBMD表达时,这些差异缩小甚至消失.     

中年妇女年龄、月经状态、体重指数及体力活动对机体组成及脂肪分布的影响

目的 研究中年妇女年龄、月经状态、体重指数(body mass index,BMI)及体力活动对机体组成及脂肪分布的影响. 方法 横断面收集于北京协和医院体检中心体检的健康妇女,利用经过效度和信度检验的国际体力活动问卷短卷中文版调查研究对象的体力活动情况,利用双能X线吸收法(DEXA)测定机体组成及脂肪分布情况. 结果 共收集到162例妇女资料,年龄40～62岁、(52.81±5.31)岁.多元线性回归分析结果显示,全身脂肪组织百分比与BMI(标准化偏回归系数b=0.70)、月经状态(b=0.19,生育期赋值1,绝经过渡期赋值2,绝经后赋值3,下同)呈正相关,而与体力活动能量消耗呈负相关(b=-0.17),回归方程的决定系数R2-0.55.全身无脂肪组织含量(fat-free tissue)与BMI呈正相关(b=0.61)、与月经状态呈负相关(b=-0.14),回归方程的决定系数R2=0.39.躯干脂肪/全身脂肪比值与BMI(b=0.32)、月经状态(b=0.30)呈正相关,回归方程的决定系数R2=0.20.校正了BMI、月经状态及体力活动的影响后,年龄与全身脂肪组织百分比、全身无脂肪组织含量、躯干脂肪/全身脂肪比值均无明显相关性. 结论 月经状态对机体组成及脂肪分布具有独立影响,随着生殖衰老的进展,脂肪组织增加且趋于中心性分布,机体无脂肪组织含量降低.而年龄本身与机体组成及脂肪分布无直接关系.中年妇女应增加体力活动,保持适当的体重以降低绝经对脂肪组织所造成的不利变化.     

绝经后妇女骨密度、体重指数、体脂和雌激素分泌的关系

目的　调查分析绝经后妇女骨密度、体重指数、体脂和雌激素分泌之间的关系。方法　上海市区 5 0～ 70岁社区绝经后女性健康志愿者共 4 5 7例 ,进行身高体重、腰椎和股骨颈骨密度的测定、腰椎和髋部脂肪成分的检测 ,以及随机选取 118例志愿者进行血清雌激素的测定。所有资料输入电脑 ,应用SPSS软件进行统计分析。结果　非骨质疏松 (Non OP)组中体重指数与腰椎和股骨颈骨密度的相关系数分别为 0 . 5 3和 0 . 5 4 ,骨质疏松 (OP)组分别为 0 .33和 0 . 33;Non OP组中体重指数与腰椎和髋部体脂的相关系数分别为 0. 2 1和 0 . 0 92 ,OP组分别为 0 . 72和 0 .2 7;Non OP组的血清雌激素浓度与体脂呈弱相关 ,OP组血清雌激素浓度与体脂无关。Non- OP组中体重指数大于OP组 ,体脂低于OP组 ,但无统计学意义。经体重指数校正后 ,体脂 (即体脂 /体重指数 ,亦即体脂在体重中所占的比重 ) ,OP组体脂明显大于Non -OP组 (P <0 . 0 5 )。结论　体重是影响绝经后妇女骨密度的重要因素 ,体脂在体重中的比重增加会降低绝经后妇女的骨密度 ,这种体脂的增加与雌激素可能无关。绝经后妇女应在不增加体脂的前提下 ,适当增加体重来预防骨质疏松症的发生。     

Association between body mass index,body height,and the prevalence of spinal deformities

Background contextThe most common spinal deformities among adolescents are adolescent idiopathic scoliosis (AIS; 2%–3% prevalence) and Scheuermann kyphosis (SK; 1%–8% prevalence). Both are believed to have a genetic influence in their etiology. The association between body mass index (BMI) and body stature and their possible association to spinal deformities is uncertain.Study designA cross-sectional prevalence study.PurposeTo examine the prevalence of all adolescent spinal deformities according to the extent of their severity as well as their possible association to BMI and body height.Outcome measuresSubjects diagnosed as having spinal deformities were classified into one of three severity groups; “Mild,” “Intermediate,” or “Severe,” according to their curve scoliosis or kyphosis measurement with a standing X-ray.MethodsThe data for this study were derived from a medical database containing records of 17-year-old male and female patients before their recruitment into mandatory military service. Information on the disability codes associated with spinal deformities according to the Regulations of Medical Fitness Determination was retrieved. Logistic regression models were used to assess the association between the BMI and body height to various degrees of spinal deformities by severity.ResultsThe study cohort included 829,791 consecutive subjects, of whom 103,249 were diagnosed with spinal deformities (76% were mild in degree). The prevalence of spinal deformities was significantly greater among the underweight male and female patients (p<.001). Increased BMI had a protective effect for developing spinal deformities. The odds ratios for severe spinal deformities were greater compared with mild spinal deformities in the underweight groups. The risk for developing spinal deformities increased significantly with height for both genders (p<.001).ConclusionsAn association between height and the risk for spinal deformities by severity was found for all height groups. Below normal BMI is associated with severity of spinal deformities, whereas above-normal BMI apparently has a protective effect. Body height is also positively associated with the severity of spinal deformities.     

Weight,body composition,and bone density in postmenopausal women

Associations of body weight and body composition with bone mineral density (BMD) were examined in 261 postmenopausal women. BMD, body fat, and body nonfat soft tissue (NFST) were measured by dual-energy X-ray absorptiometry (DXA). A height-independent BMD variable (HIBMD) was calculated to correct for differences among individuals in bone thickness, a dimension that is ignored by DXA scanners. HIBMD was calculated as BMD divided by height at the spine and femoral neck, and BMD divided by the square root of height at the total body. Weight, fat, and nonfat soft tissue were all positively correlated with both BMD and HIBMD, but the magnitudes of regression and correlation coefficients were lower when HIBMD was the dependent variable. The weight-independent associations of body composition with HIBMD were examined by including weight and % NFST together in linear models. In these analyses, weight was positively associated with HIBMD at all three skeletal sites (r=0.22–0.26, P<0.05), % NFST was not associated with HIBMD at the spine or femoral neck (r=0.01–0.02), and there was only a weak inverse correlation of % NFST with total body BMD (r=-0.12, P<0.05). These findings are consistent with those of previous studies demonstrating positive associations between body weight and BMD. In addition, they demonstrate that once bone thickness and body weight are taken into account, body composition appears to have little if any independent effect on bone density at the skeletal sites measured. This finding is consistent with the hypothesis that the protective effect of body weight is brought about predominantly through its mechanical force on the skeleton.     

Assessment of total body water and lean body mass from anthropometry, Watson formula, creatinine kinetics, and body electrical impedance compared with antipyrine kinetics in peritoneal dialysis patients

Background. Indirect methods such as anthropometry (A), Watson formula (W), creatinine kinetics (CK), and body electrical impedance (BEI) are increasingly applied to determine total body water (TBW) and lean body mass (LBM) in dialysis patients. These methods share the disadvantage that they have been validated for healthy men only. We studied which of these four commonly applied methods can best be used routinely in CAPD patients. Methods. TBW estimates obtained from A, W, CK, and BEI were compared with those obtained by a gold standard (antypirine distribution volume, ADV) in eight CAPD patients. In addition, several BEI equations to derive lean body mass (LBM) were compared with LBM estimated by ADV in order to determine which equation is the most valuable for the assessment of LBM by BEI in CAPD patients. Results. TBW as ADV was 41.4±6.6 (mean±SD) L. TBW estimated by W, A and CK underestimated ADV by a mean±SD of 2.3±13, 5±8.4 and 12.3±10.9% respectively. TBW as measured by BEI overestimated ADV by 2.5±8.8%. The correlation coefficients between ADV-TBW and TBW estimated by the indirect methods were r=0.88 (A), r=0.87 (BEI), r=0.82 (CK), and 0.68 (W). LBM estimated by ADV was 56.7±8.9 (mean±SD) kg; LBM by different BEI equations ranged from 49.9±7 to 58.1±10.7 kg. The correlation coefficient between LBM by ADV and LBM according to the various BEI equations ranged from 0.81 to 0.93. Conclusions. A and BEI: can be used to estimate TBW, but the considerable SD (or inaccuracy) makes individual predictions hazardous. Considering the correlation coefficients and difference between LBM by ADV and LBM according to different BEI equations, Deurenberg's formula can be advocated for use in the estimation of LBM by BEI.     

Estimates of body water,fat-free mass,and body fat in patients on peritoneal dialysis by anthropometric formulas

BACKGROUND: Anthropometric formulas that are used to estimate body water in peritoneal dialysis patients can also be used to estimate fat-free mass and body fat. Evaluation of body composition by the anthropometric formulas rests on two assumptions: (1) fat contains no water, and (2) the water content of the fat-free mass is constant (72%). METHODS: We compared estimates of body water, fat-free mass, and body fat by anthropometric formulas to estimates employing dilution of tracer substances to measure body water and standard methods to analyze body composition in studies performed on peritoneal dialysis patients. We also analyzed the potential errors of the estimates of body composition by the formulas. RESULTS: Estimates of the average body composition provided by the anthropometric formulas agreed with estimates provided by the standard methods. However, these formulas have the potential of introducing large errors when estimating body composition in individuals differing from the average subject, either because the anthropometric formulas do not account for major determinants of body composition, such as physical exercise, nutrition, and catabolic illness, or because these formulas systematically overestimate body water in subjects who are obese or experiencing volume excess. CONCLUSION: Anthropometric formulas currently in existence can provide only approximations of body composition and may be the sources of large errors in evaluating body composition in peritoneal dialysis patients. The potential errors include estimates of body water. These errors may alter the interpretation of urea kinetic studies in certain categories of peritoneal dialysis patients (e.g., obese subjects).     

绝经后女性体质量指数、体成分与骨密度的变化特征及关系

目的 探讨绝经后女性年龄、体质量指数（body mass index, BMI）及体成分的变化特征及与骨质疏松症之间的关系。方法 选取广州中医药大学第三附属医院2019年12月–2021年1月门诊收集的98名绝经后女性的体成分及骨密度资料,根据受试者的年龄和BMI分组,比较各年龄组及各BMI组的体成分差别,通过Spearman分析年龄、BMI及体成分对骨质疏松情况的影响,利用多元线性回归研究整体骨密度和整体骨矿含量的影响因素。结果 各个年龄组的整体骨密度（P＜0.001）及整体骨矿含量（P＜0.05）随年龄增加而下降,而各个BMI组的整体骨矿含量（P＜0.05）、整体肌肉质量（P＜0.001）、整体脂肪质量（P＜0.001）随BMI增加而增加。Spearman相关分析显示,随着年龄增加（P=0.005,r=0.281）,骨质疏松程度越严重;而随着BMI（P=0.019,r= – 0.237）、整体骨矿含量（P＜0.001,r= – 0.719）、肌肉质量（P=0.014,r= – 0.249）和脂肪质量（P=0.013,r= – 0.249）的增加,患骨质疏松的程度越轻。多元线性回归分析结果显示,年龄与绝经后女性整体骨密度（P=0.002,B= – 0.004）及整体骨矿含量呈负相关（P=0.000,B= – 0.013）;而整体肌肉质量（P=0.018,B=0.022）和整体脂肪质量（P=0.037,B=0.027）则与绝经后女性整体骨矿含量呈正相关。结论 年龄是绝经后女性患骨质疏松症的危险因素,而BMI、肌肉质量和脂肪质量是保护因素,有助于提高整体骨密度和整体骨矿含量。     

Philosophy,technical principles,selection, and indication in body contouring surgery

The experiences of almost three decades of performing various types of body contouring surgery, in both pre- and postlipoplasty periods, using many different techniques are described. Contouring surgery for such body areas as the abdomen, flanks, inner and outer thighs, and buttocks is discussed in detail.