摘要
目的 分析<50岁男性血清PSA水平的影响因素. 方法 2006年9月至2008年11月健康检查<50岁男性6808例.分别测量身高、体质量,并计算体质量指数(BMI),检测血清PSA水平.将人群按年龄分为10岁～、20岁～、30岁～和40～49岁4组,按WHO亚太地区BMI水平分级标准分为消瘦(BMI<18.5 kg/m~2)、正常(BMI 18.5～22.9 kg/m~2)、超重(BMI 23.0～24.9kg/m~2)、肥胖(BMI 25.0～29.9 kg/m~2)、极度肥胖(BMI≥30.0 kg/m~2)5组.方差分析比较各年龄组和各BMI组人群PSA水平差异.并进行Spearman相关性分析. 结果 6808例平均年龄(39.2±7.0)岁,平均BMI指数(25.6±4.7)kg/m~2,平均PSA(0.89±0.56)ng/ml.单因素方差分析表明:10岁～年龄组PSA水平与其他3个年龄组间差异有统计学意义(P<0.01),其他3个年龄组问差异无统计学意义.各年龄组按照BMl分组比较,除10岁～组外,其余3组中随BMI增加,PSA水平降低,差异有统计学意义(P<0.01).相关性分析结果 显示年龄与PSA呈显著正相关(P<0.0001),BMI与PSA呈显著负相关(P<0.0001). 结论 男性青春期PSA变化明显,20～50岁间PSA增长缓慢,PSA水平与BMI呈负相关关系,在青年人群中评价PSA结果 应考虑上述影响因素.
Abstract
Objective To analyse the correlation of age and BMI with prostate-specific antigen (PSA)in male younger than 50 years of age. Methods The routine health examination data of 6808 males, younger than 50 years of age, were collected and reviewed. The height and weight were measured, so as to calculate the body mass index (BMI). Serum PSA was also examined. Eligible men were classified into age groups spanning 10 years. BMI was categorized as normal (BMI 18. 5 - 22. 9) , overweight (BMI 23. 0-24. 9), obese (BMI 25. 0 - 29. 9) , and very obese (BMI≥30. 0) according to the re-defined World Health Organization criterion for the Asia Pacific Region. PSA levels were stratified by age and BMI category. Results The mean age was (39. 2±7. 0)years, mean BMI (25. 6± 4. 7)kg/m~2 and mean PSA (0. 89±0. 56)ng/ml for the whole population. The PSA level in 10 - 19 age group was significantly lower than the other three groups (P<0. 01) and no significant difference was found among the other three groups. The BMI had negative correlated with PSA even when comparing in sub-age groups, except the 10-19 age group. Spearman analysis also found PSA had significant positive correlation with age and negative correlation with BMI. Conclusions Serum PSA level changes significantly with age in adolescence whereas quite slowly between 20-50 years of age. BMI has negative influence on PSA in male younger than 50 years of age.
NETL
NSTL
维普
万方数据