
浏览全部资源
扫码关注微信
Data Center of Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China
赵玉凤,E-mail: snowmanzhao@163.com
收稿:2025-08-03,
修回:2025-11-13,
录用:2025-11-14,
纸质出版:2025-11-30
移动端阅览
马鹏珍,庞华鑫,沈翊康,等.中国老年人体圆指数变迁轨迹及其影响因素:一项基于CLHLS队列的归因分析[J].陆军军医大学学报,2025,47(22):2858-2867.DOI:10.16016/j.2097-0927.202508006.
MA P Z,PANG H X,SHEN Y K,et al.Trajectory of changes in body roundness index of elderly people in China and its influencing factors: an attribution analysis based on CLHLS cohort[J].J Army Med Univ,2025,47(22):2858-2867.DOI:10.16016/j.2097-0927.202508006.
马鹏珍,庞华鑫,沈翊康,等.中国老年人体圆指数变迁轨迹及其影响因素:一项基于CLHLS队列的归因分析[J].陆军军医大学学报,2025,47(22):2858-2867.DOI:10.16016/j.2097-0927.202508006. DOI:
MA P Z,PANG H X,SHEN Y K,et al.Trajectory of changes in body roundness index of elderly people in China and its influencing factors: an attribution analysis based on CLHLS cohort[J].J Army Med Univ,2025,47(22):2858-2867.DOI:10.16016/j.2097-0927.202508006. DOI:
目的
2
基于中国老年健康影响因素跟踪调查(Chinese longitudinal healthy longevity survey,CLHLS)平台数据构建2011—2018年中国老年人体圆指数(body roundness index,BRI)变化的轨迹模型,并分析不同BRI轨迹的影响因素。
方法
2
本研究基于CLHLS平台中的纵向队列数据,运用组别轨迹模型分析(Group-based Trajectory Model,GBTM)构建2011、2014、2018年三波符合研究标准的调查对象BRI的纵向变化轨迹;并运用无序多分类logistic回归分析不同BRI轨迹的影响因素。
结果
2
共有2 512个有效样本被纳入分析,GBTM拟合的中国老年人BRI轨迹最优分组为3组,分别为低水平增长轨迹模型、中等水平增长轨迹模型、高水平增长轨迹模型。性别、受教育年限、居住地、是否与配偶同住、有无退休金、睡眠质量、是否存在吸烟史、是否存在饮酒史、是否一直锻炼、进食水果频率、进食盐腌蔬菜频率、“水果+蛋白质”饮食模式在不同BRI轨迹组中分布差异有统计学意义(
P
<
0.05);无序多分类Logistic回归分析发现,以低水平增长轨迹模型为参照:男性、有吸烟史的人群更不易表现为中、高增长水平的BRI轨迹;有退休金的老年人更易表现为中、高增长水平的BRI轨迹;有饮酒史的人更容易表现为中等平稳增长水平的BRI轨迹;受教育年限
>
10的人更不容易表现为高水平增长的BRI轨迹,城市居民、经常进食水果以及盐腌蔬菜的人更容易表现为高水平增长的BRI轨迹。
结论
2
2011—2018年中国老年人BRI变化轨迹可分为3组,性别、居住地、受教育年限等多个因素或影响其轨迹走向,需提前关注并采取措施提升老年生活质量。对策 建议有关部门将BRI纳入老年健康监测核心指标,建立高危人群动态管理机制,实施精准化生活方式干预与健康指导。
Objective
2
To construct a trajectory model for the changes in body roundness index (BRI) of elderly people in China from 2011 to 2018 based on the data derived from Chinese Longitudinal Healthy Longevity Survey (CLHLS)
and analyze the influencing factors of different BRI trajectories.
Methods
2
Based on the longitudinal cohort data from the CLHLS platform
group-based trajectory model (GBTM) analysis was used to construct longitudinal change trajectories of 3 waves of BRI (2011
2014
and 2018) that meet our research criteria. Unordered multinomial logistic regression analysis was employed to identify the influencing factors of different BRI trajectories.
Results
2
A total of 2 512 valid samples were included in the analysis. The BRI trajectory of Chinese elderly people fitted by GBTM was optimally grouped into low-
medium-
and high-level growth trajectory models. There were statistically significant differences among different BRI trajectory groups in gender
length of education
resident place
living with spouse
retirement pension
sleep quality
smoking history
drinking history
continuous exercise
frequency of fruit consumption
frequency of salt-preserved vegetables consumption
and “fruit+protein” dietary patterns (
P
<
0.05). Disordered multiclass logistic regression analysis found that
using the low-level growth trajectory model as a reference
males and those with a history of smoking were less likely to exhibit moderate to high growth levels of BRI trajectories; Elderly people with retirement pensions were more likely to exhibit a moderate to high growth level of BRI trajectory; People with a history of alcohol consumption were more likely to exhibit a moderate steady growth level of BRI trajectory; People with longer than 10 years of education were less likely to exhibit a high level of growth in the BRI trajectory
while urban residents and those who frequently consumed fruits and salted vegetables were more likely to exhibit a
high level of growth in the BRI trajectory.
Conclusion
2
The trajectory of BRI changes among elderly people in China from 2011 to 2018 can be divided into 3 groups
which are influenced by multiple factors such as gender
resident place
and length of education. It is necessary to pay attention to and make measures in advance to improve the quality of life in the elderly.
Countermeasures
It is advisable to incorporate BRI as a core indicator in elderly health monitoring systems
establish a dynamic management mechanism for high-risk populations
and implement precision-targeted lifestyle interventions and health guidance.
杜鹏 , 吴赐霖 . 从长寿大国迈向长寿强国: 基于百岁老人的中国长寿水平分析 [J]. 人口研究 , 2024 , 48 ( 3 ): 3 - 19 .
DU P , WU C L . China’s longevity levels from the perspective of centenarians [J]. Popul Res , 2024 , 48 ( 3 ): 3 - 19 .
NEELAND I J , LIM S , TCHERNOF A , et al . Metabolic syndrome [J]. Nat Rev Dis Primers , 2024 , 10 ( 1 ): 77 . DOI: 10.1038/s41572-024-00563-5 http://dx.doi.org/10.1038/s41572-024-00563-5 .
LV Y B , ZHANG Y , LI X W , et al . Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study [J]. Eur Heart J , 2024 , 45 ( 24 ): 2145 - 2154 . DOI: 10.1093/eurheartj/ehae206 http://dx.doi.org/10.1093/eurheartj/ehae206 .
李嘉丽 , 刘璠 , 柯立鑫 , 等 . 1990 —2021年全球与中国60 岁及以上人群肥胖的疾病负担: 趋势分析与模型预测 [J/OL]. 中国全科医学 , 2025 : 1 - 10 . ( 2025-08-21 ). https://kns.cnki.net/kcms/detail/13.1222.R.20250820.1451.002.html https://kns.cnki.net/kcms/detail/13.1222.R.20250820.1451.002.html .
LI J L , LIU F , KE L X , et al . Disease burden of obesity among individuals aged 60 and above globally and in China from 1990 to 2021: trend analysis and model-based projection [J/OL]. Chin Gen Pract , 2025 : 1 - 10 . ( 2025-08-21 ). https://kns.cnki.net/kcms/detail/13.1222.R.20250820.1451.002.html https://kns.cnki.net/kcms/detail/13.1222.R.20250820.1451.002.html .
耿小亮 , 汤逢源 , 谭港锐 , 等 . 中国老年人超重和肥胖流行趋势及影响因素分析 [J]. 卫生软科学 , 2025 , 39 ( 5 ): 76 - 82 . DOI: 10.3969/j.issn.1003-2800.2025.05.014 http://dx.doi.org/10.3969/j.issn.1003-2800.2025.05.014 .
GENG X L , TANG F Y , TAN G R , et al . Analysis of prevalence trends and influencing factors of overweight and obesity among Chinese older adults [J]. Soft Sci Health , 2025 , 39 ( 5 ): 76 - 82 . DOI: 10.3969/j.issn.1003-2800.2025.05.014 http://dx.doi.org/10.3969/j.issn.1003-2800.2025.05.014 .
张翼飞 , 石娟 , 许悦宁 . 内脏脂肪在肥胖诊断及其合并症预测中的应用现状及展望 [J]. 诊断学理论与实践 , 2025 , 24 ( 1 ): 7 - 13 . DOI: 10.16150/j.1671-2870.2025.01.002 http://dx.doi.org/10.16150/j.1671-2870.2025.01.002 . [
ZHANG Y F , SHI J , XU Y N . Current applications and prospects of visceral fat in obesity diagnosis and comorbidity prediction [J]. J Diagn Concepts Pract , 2025 , 24 ( 1 ): 7 - 13 . DOI: 10.16150/j.1671-2870.2025.01.002 http://dx.doi.org/10.16150/j.1671-2870.2025.01.002 .
TIAN Y , JIANG C M , WANG M , et al . BMI, leisure-time physical activity, and physical fitness in adults in China: results from a series of national surveys, 2000-14 [J]. Lancet Diabetes Endocrinol , 2016 , 4 ( 6 ): 487 - 497 . DOI: 10.1016/S2213-8587(16)00081-4 http://dx.doi.org/10.1016/S2213-8587(16)00081-4 .
THOMAS D M , BREDLAU C , BOSY-WESTPHAL A , et al . Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model [J]. Obesity , 2013 , 21 ( 11 ): 2264 - 2271 . DOI: 10.1002/oby.20408 http://dx.doi.org/10.1002/oby.20408 .
WANG J N , WU M Y , WU S L , et al . Relationship between body roundness index and the risk of heart failure in Chinese adults: the Kailuan cohort study [J]. ESC Heart Fail , 2022 , 9 ( 2 ): 1328 - 1337 . DOI: 10.1002/ehf2.13820 http://dx.doi.org/10.1002/ehf2.13820 .
LI Y , HE Y M , YANG L , et al . Body roundness index and waist-hip ratio result in better cardiovascular disease risk stratification: results from a large Chinese cross-sectional study [J]. Front Nutr , 2022 , 9 : 801582 . DOI: 10.3389/fnut.2022.801582 http://dx.doi.org/10.3389/fnut.2022.801582 .
ZHANG X Q , MA N , LIN Q S , et al . Body roundness index and all-cause mortality among US adults [J]. JAMA Netw Open , 2024 , 7 ( 6 ): e2415051 . DOI: 10.1001/jamanetworkopen.2024.15051 http://dx.doi.org/10.1001/jamanetworkopen.2024.15051 .
CHEN Y F , GAO Y , CHEN Y X , et al . Association between dietary patterns and all-cause mortality in the Chinese old: analysis of the Chinese longitudinal healthy longevity survey cohort [J]. Nutrients , 2024 , 16 ( 11 ): 1605 . DOI: 10.3390/nu16111605 http://dx.doi.org/10.3390/nu16111605 .
NAGIN D S , JONES B L , ELMER J . Recent advances in group-based trajectory modeling for clinical research [J]. Annu Rev Clin Psychol , 2024 , 20 ( 1 ): 285 - 305 . DOI: 10.1146/annurev-clinpsy-081122-012416 http://dx.doi.org/10.1146/annurev-clinpsy-081122-012416 .
KANDALA N B , STRANGES S . Geographic variation of overweight and obesity among women in Nigeria: a case for nutritional transition in sub-Saharan Africa [J]. PLoS One , 2014 , 9 ( 6 ): e101103 . DOI: 10.1371/journal.pone.0101103 http://dx.doi.org/10.1371/journal.pone.0101103 .
MUNYOGWA M J , MTUMWA A H . The prevalence of abdominal obesity and its correlates among the adults in Dodoma Region, Tanzania: a community-based cross-sectional study [J]. Adv Med , 2018 , 2018 : 6123156 . DOI: 10.1155/2018/6123156 http://dx.doi.org/10.1155/2018/6123156 .
FILOZOF C , GONZALEZ C , SEREDAY M , et al . Obesity prevalence and trends in Latin-American countries [J]. Obes Rev , 2001 , 2 ( 2 ): 99 - 106 . DOI: 10.1046/j.1467-789x. 2001.00029.x http://dx.doi.org/10.1046/j.1467-789x.2001.00029.x .
CHEN Y J , PENG Q , YANG Y , et al . The prevalence and increasing trends of overweight, general obesity, and abdominal obesity among Chinese adults: a repeated cross-sectional study [J]. BMC Public Health , 2019 , 19 ( 1 ): 1293 . DOI: 10.1186/s12889-019-7633-0 http://dx.doi.org/10.1186/s12889-019-7633-0 .
CARRERAS-TORRES R , JOHANSSON M , HAYCOCK P C , et al . Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank [J]. BMJ , 2018 , 361 : k1767 . DOI: 10.1136/bmj.k1767 http://dx.doi.org/10.1136/bmj.k1767 .
TUCCI S A . Phytochemicals in the control of human appetite and body weight [J]. Pharmaceuticals , 2010 , 3 ( 3 ): 748 - 763 . DOI: 10.3390/ph3030748 http://dx.doi.org/10.3390/ph3030748 .
JUNG P , JUNG S , SOO K , et al . The effect of alcohol drinking on metabolic syndrome and obesity in koreans: big data analysis [J]. Int J Environ Res Public Health , 2022 , 19 ( 9 ): 4949 . DOI: 10.3390/ijerph19094949 http://dx.doi.org/10.3390/ijerph19094949 .
ALI N , MOHANTO N C , NURUNNABI S M , et al . Prevalence and risk factors of general and abdominal obesity and hypertension in rural and urban residents in Bangladesh: a cross-sectional study [J]. BMC Public Health , 2022 , 22 ( 1 ): 1707 . DOI: 10.1186/s12889-022-14087-8 http://dx.doi.org/10.1186/s12889-022-14087-8 .
徐聪 . 赣南地区超重肥胖流行特征及干预效果研究 [D]. 赣州 : 赣南医科大学 , 2024 . DOI: 10.27959/d.cnki.ggnyx.2024.000064 http://dx.doi.org/10.27959/d.cnki.ggnyx.2024.000064 .
XU C . The epidemiological characteristics of overweight and obesity in southern Gannan and its intervention effect [D]. Ganzhou : Gannan Medical University , 2024 . DOI: 10.27959/d.cnki.ggnyx.2024.000064 http://dx.doi.org/10.27959/d.cnki.ggnyx.2024.000064 .
谢思思 . 赣南地区糖尿病前期流行现况及人群筛查策略研究 [D]. 赣州 : 赣南医学院 , 2023 . DOI: 10.27959/d.cnki.ggnyx.2023.000081 http://dx.doi.org/10.27959/d.cnki.ggnyx.2023.000081 .
XIE S S . Prevalence of pre-diabetes mellitus and populations screening strategies in the south of Jiangxi [D]. Ganzhou : Gannan Medical College , 2023 . DOI: 10.27959/d.cnki.ggnyx.2023.000081 http://dx.doi.org/10.27959/d.cnki.ggnyx.2023.000081 .
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621