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2023年7月 第38卷 第7期11
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下背痛对中国人群健康负担的影响趋势分析及预测模型构建

Trend analysis and prediction model construction of the impact of low back pain on the health burden in the Chinese population

来源期刊: 广州医药 | 843-856 发布时间:2026-07-20 收稿时间:2026/8/20 17:52:18 阅读量:19
作者:
关键词:
下背痛疾病负担趋势分析驱动因素ARIMA模型预测
low back paindisease burdentrend analysisdriving factorsARIMA model prediction
DOI:
10. 20223 / j. cnki. 1000-8535. 2026. 07. 007
收稿时间:
2026-01-28 
修订日期:
 
接收日期:
 
引用总数:
0  
       目的 探究1990—2023年中国人群下背痛(LBP)疾病负担,并预测2024—2040年LBP疾病负担发展趋势,为公共卫生政策制定提供数据支撑。方法 基于GBD2023数据库,采用Joinpoint模型、分解分析(decomposition analysis)量化我国LBP负担变化趋势,最后通过ARIMA(autoregressive integrated moving average model)模型预测未来趋势。结果 2023年我国LBP患病人数达9 532.40万人,发病人数为4 138.36万人,伤残调整生命年(DALYs),虽然患病人数、发病人数及DALYs绝对数较1990年显著增长,但年龄标准化率(ASR)均呈显著下降趋势(AAPC依次为-0.90%、-0.84%、-0.89%)。分解分析表明,人口年龄结构是我国LBP疾病负担增长的主要正向驱动因素,流行病学趋势变化对患病率和DALYs起关键抑制作用,且存在明显性别差异。ARIMA模型预测显示,2024—2040年男性和女性LBP相关ASR将持续下降,但我国女性LBP负担仍高于男性。结论 我国LBP负担沉重,受人口结构、性别差异、行为与职业等多方面因素影响,未来需通过分人群、分职业精准干预及多部门协同,持续降低疾病负担。

     Objective To explore the characteristics of disease burden of low back pain(LBP) in the Chinese population from 1990 to 2023,and predict its development trend from 2024 to 2040,so as to provide data support for the formulation of public health policies.Methods Based on the Global Burden of Disease Study 2023(GBD 2023) database,the Joinpoint model and decomposition analysis were adopted to quantify the changing trend of LBP burden in China.The autoregressive integrated moving average(ARIMA) model was used to predict the future trend,with the data for prediction stratified by gender and age group.Results In 2023,the number of LBP patients in China reached 95.3240 million,the number of incident cases was 41.3836 million,and the disability-adjusted life years(DALYs) were 10.6359 million person-years.Although the absolute numbers of prevalent cases,incident cases,and DALYs increased significantly compared with 1990,the age-standardized rates(ASRs) all showed a significant downward trend(average annual percentage changes were -0.90%,-0.84%,and -0.89%,respectively).Decomposition analysis revealed that population age structure was the primary positive driving factor for the growth of LBP disease burden in China,while changes in epidemiological trends played a key inhibitory role in prevalence and DALYs,with significant gender differences.ARIMA model prediction indicated that the LBP-related ASRs would continue to decrease in both males and females from 2024 to 2040,but the LBP burden in females would remain higher than that in males in China.Conclusions The baseline burden of LBP in China is heavy,affected by multiple factors such as population structure,gender differences,behavioral and occupational factors.In the future,targeted interventions for specific populations and occupations,as well as multi-sectoral collaboration,are needed to continuously reduce the disease burden.
       下背痛(low back pain,LBP)作为以腰背部至臀部区域疼痛为核心表现的常见症状,疼痛性质多为钝痛、酸痛,常在外力负荷、不良姿势等因素下加重。其病因常涉及脊柱退变、肌肉劳损、骨质疏松等问题,严重时可导致活动受限甚至残疾[1-2]
       从全球视角看,LBP已成为重大公共卫生挑战。全球疾病负担研究(Global Burden of Disease Study,GBD)作为多国合作的持续性研究,为量化疾病健康损失提供了权威框架。据GBD数据显示,至2020年,全球工作年龄人群LBP患病例数已增至6.19亿,较1990年增长超过60%,且长期稳居全球致残原因首位[3]。在中国,LBP流行态势同样严峻,人口增长与老龄化等因素仍推动疾病负担绝对数值攀升[4]
       GBD数据库涵盖发病率、患病率和DALYs等多维度指标及长期时序数据,为疾病负担趋势分析与驱动因素提供了关键支撑。尚未有研究利用其最新数据开展针对我国的精细化趋势预测。因此,本研究基于GBD 2023数据库数据,系统分析1990—2023年我国LBP疾病负担,并对未来负担情况进行预测,为公共卫生政策提供更有针对性的资料,为降低LBP健康损害与社会成本提供数据支撑和决策参考。

1 资料与方法

1.1 数据来源

       本研究所用数据均通过https://ghdx.healthdata.org/gbd-2023在线获取。GBD数据库系统整合了各国人口数据、流行病学调查研究等,是全球研究人员全面了解特定疾病的数据资源平台[5-6]。本研究提取1990—2023年我国人群LBP相关数据,包括患病人数、发病人数、伤残调整生命年(disability-adjusted life years,DALYs)及年龄标化率(age-standardized rate,ASR),数据按性别、年龄组等进行整理。所有数据处理与统计分析均采用R4.4.1软件完成。

1.2 统计分析

       1.2.1 Joinpoint回归模型 采用Joinpoint Regression Program 5.1.0软件分析1990—2023年我国人群LBP疾病负担的时间趋势。该模型通过识别趋势变化中的转折点(joinpoint),将整个研究时段划分为多个连续的线性趋势段,进而计算各趋势段的年度变化百分比(annual percent change,APC)及全时段的平均年度变化百分比(average annual percent change,AAPC),并以95%不确定性区间(uncertainty interval,UI)评估统计显著性。AAPC>0提示指标呈上升趋势,AAPC<0提示呈下降趋势,P<0.05为差异有统计学意义。通过该模型明确LBP疾病负担的长期演变特征、关键转折节点及不同时段的变化强度[7]
       1.2.2 分解分析 采用分解分析方法,量化1990—2023年我国LBP疾病负担(患病人数、发病人数及DALYs)变化的驱动因素。分解模型将总变化量分解为三个贡献因子:①人口规模变化效应;②人口年龄结构变化效应;③流行病学趋势变化效应。通过计算各因子的贡献值及贡献度,明确不同因素对LBP疾病负担变化的相对重要性,为制定干预策略提供依据[8]
       1.2.3 自回归积分移动平均模型(autoregressive integrated moving average model,ARIMA) 构建ARIMA模型预测2024—2040年我国人群LBP疾病负担趋势。模型构建流程如下:①对1990—2023年LBP年龄标化患病率(age-standardized prevalence rate,ASPR)、年龄标化发病率(age-standardized incidence rate,ASIR)、年龄标化DALYs率(age-standardized disability-adjusted life years rate,ASDR)时间序列数据进行平稳性检验;②基于自相关函数和偏自相关函数确定模型阶数;③通过Akaike信息准则和Bayesian信息准则筛选最优模型,优先选择AIC和BIC值最小的模型;④对最优模型进行残差检验,验证模型拟合效果;⑤基于拟合优度良好的ARIMA模型,预测未来17年LBP疾病负担的趋势及95%预测区间(95% confidence interval,95%CI[9]

2 结 果

2.1 1990—2023年我国LBP疾病负担现状及变化趋势

       2023年我国LBP患病人数达9 532.40万例,ASPR为4 929.78/10万人年;发病人数4 138.36万例,ASIR为2 164.80/10万人年;DALYs数为1 063.59万例,ASDR为551.92/10万人年。与1990年数据相比(表1),核心负担指标绝对数均呈增长态势,但ASR均表现为显著下降趋势:ASPR[AAPC=-0.90%,95%UI(-0.95,-0.84)]、ASIR[AAPC=-0.84%,95%UI(-0.89,-0.79)]、ASDR[AAPC=-0.89%,95%UI(-0.95,-0.83)](表1)。女性上述各指标的AAPC下降幅度均显著大于男性(均P<0.001)(图1)。各年龄段女性LBP患病、发病及DALYs的计数绝大部分多于男性(各年龄段对比均P<0.05),55~59岁为高峰(图2A-C)。40岁前男女LBP的ASPR、ASIR及ASDR水平相近且较低;40岁后女性标准化率快速上升并持续高于男性,85岁左右达峰值后略回落,但仍显著高于同年龄段男性(图3A-C)。

表1  1990及2023年中国下背痛的患病、发病、伤残调整生命年情况及1990—2023年变化趋势

项目

性别

绝对计数(万例/万人年)(95%UI

 

年龄标准化率(/10万)(95%UI

 

AAPC%)(95%UI

1990

2023

 

1990

2023

 

AAPC

P

患病

总体

6863.63
(5981.68, 7745.74)

9532.40
(8362.51, 10777.88)

 

6636.60
(5778.62,7462.02)

4929.78
(4304.39,5494.10)

 

-0.90
(-0.95,-0.84)

0.001

男性

2662.01
(2313.53, 3019.47)

3754.48
(3266.37, 4233.78)

 

5007.32
(4392.70,5623.80)

3991.71
(3485.97,4444.85)

 

-0.69
(-0.74,-0.64)

0.001

女性

4201.62
(3663.13, 4732.70)

5777.92
(4984.86, 6516.50)

 

8246.61
(7136.33,9281.41)

5857.13
(5102.95,6576.59)

 

-1.03
(-1.09,-0.97)

0.001

发病

总体

2998.91
(2633.59, 3341.89)

4138.36
(3641.72, 4652.04)

 

2859.73
(2532.11,3187.09)

2164.80
(1926.65,2383.57)

 

-0.84
(-0.89,-0.79)

0.001

男性

1197.97
(1050.00, 1339.16)

1647.89
(1442.55, 1858.63)

 

2225.22
(1956.98,2491.25)

1772.18
(1570.07,1961.50)

 

-0.69
(-0.74,-0.64)

0.001

女性

1800.94
(1585.96, 2008.68)

2490.47
(2189.55, 2805.13)

 

3495.05
(3087.94,3888.27)

2555.41
(2278.44,2817.75)

 

-0.94
(-0.99,-0.89)

0.001

伤残调整生命年

总体

773.24
(543.86, 1047.70)

1063.59
(752.04, 1471.57)

 

740.83
(525.01,1010.60)

551.92
(388.90,750.82)

 

-0.89
(-0.95,-0.83)

0.001

男性

302.65
(212.15, 412.79)

422.85
(296.36, 583.39)

 

563.52
(397.47,769.53)

450.10
(314.92,611.07)

 

-0.68
(-0.74,-0.62)

0.001

女性

470.60
(331.71, 640.08)

640.74
(454.53, 882.80)

 

917.48
(650.90,1250.58)

653.03
(462.34,886.10)

 

-1.02
(-1.09,-0.96)

0.001

注:AAPC,average annual percentage change,年度平均变化百分比。 

20260824165742_3912_thumb.png
图 1   基于 Joinpoint 回归模型的 1990—2023 年中国下背痛疾病负担分析
      注:A、B和C分别为总体、男性和女性下背痛年龄标准化患病率;D、E和F分别为总体、男性和女性下背痛年龄标准化发病率;G、H
和I分别为总体、男性和女性下背痛年龄标准化DALYs率;DALYs,disability-adjusted life years,伤残调整生命年;APC,annual percentage change,年度变化百分比;*APC在该段时间内变化显著(P<0.05)。

20260824165919_8042.png
图 2 
2023 年中国下背痛分年龄段患病例数、发病例数和 DALYs 例数
       注:(A)分年龄段患病例数;(B)分年龄段发病例数;(C)分年龄段DALYs例数。

20260824170018_1101.png
图 3
  2023 年中国下背痛分年龄段年龄标准化患病率、发病率和 DALYs 率
       注:(A)分年龄段年龄标准化患病率;(B)分年龄段年龄标准化发病率;(C)分年龄段年龄标准化DALYs率。

2.2 疾病负担变化的驱动因素

       分解分析结果表明,人口年龄结构是推动我国LBP患病、发病及DALY增长的首要正向驱动因素,贡献度分别为136.22%、259.52%和136.14%(表2),且存在明显性别差异(因贡献度为推导值,无统一统计检验方法计算P值,故通过效应量对比量化差异):在患病和DALY层面:女性人口年龄结构的贡献度(148.65%、149.23%)均高于男性(116.36%、116.07%);在发病层面:男性人口年龄结构的贡献度(1 278.35%)显著高于女性(283.19%)。人口规模对LBP患病和DALYs呈正向贡献,贡献度分别为60.41%和62.18%,但对发病呈显著负向抑制作用(贡献度为-381.94%),且男性负向贡献度的绝对值为女性的2.17倍,性别差异明显。流行病学趋势变化对LBP患病和DALYs均表现为负向抑制作用,贡献度分别为-96.63%、-98.32%,女性抑制贡献度的绝对值较男性高出1.2~1.5个百分点(图4A-C)。

表2 分解分析中国下背痛的人口规模、人口年龄结构、流行病学趋势变化贡献占比

疾病负担指标

性别

人口年龄结构(%)

人口规模(%)

流行病学趋势变化(%)

伤残调整生命年

总体

136.14

62.18

-98.32

116.07

56.96

-73.03

149.23

66.79

-116.02

发病

总体

259.52

-381.94

222.42

1278.35

-1951.76

773.41

283.19

-476.5

293.31

患病

总体

136.22

60.41

-96.63

116.36

55.45

-71.81

148.65

64.76

-113.41

 


20260824170209_1078.png

图 4  1990—2023 年中国下背痛疾病负担的分解分析
注:(A)患病;(B)发病;(C)DALYs,伤残调整生命年。

2.3 2023—2040年我国LBP疾病负担预测(ARIMA模型预测)

       ARIMA模型预测结果显示,2024—2040年我国男性、女性LBP的年龄相关疾病负担指标均呈持续下降趋势,基于模型95%CI判断,性别间降幅的95%CI无重叠,存在实际公共卫生意义的差异。男性ASPR从2023年3 991.71/10万人年降至2040年3 335.23/10万人年,降幅达16.4%;ASIR由1 772.18/10万人年降至1 465.00/10万人年,下降17.3%;其中ASIR降幅最为显著(图5A、C、E)。女性ASIR从2 555.41/10万人年降至2 304.95/10万人年,下降9.8%;ASDR由653.03/10万人年降至554.35/10万人年,降幅15.1%,以ASDR降幅最为突出(图5B、D、F);男性ASPR、ASIR降幅分别为女性的1.67倍、1.77倍,女性ASDR降幅为男性的1.22倍,性别间降幅差异特征明确。
20260824170342_8275_thumb.png
图 5   未来 17 年(2024—2040 年)中国下背痛年龄标准化患病率、发病率和 DALYs 率的趋势预测
       注:A和B分别为男性和女性下背痛年龄标准化患病率;C和D分别为男性和女性下背痛年龄标准化发病率;E和F分别为男性和女性下
背痛年龄标准化DALYs率。红实线代表1990—2023年LBP患病率、发病率和DALYs率的真实趋势;黄色虚线和阴影区域分别代表预测值及
其95%CI

3 讨 论

       本研究结果显示,1990—2023年间,我国LBP的ASPR、ASIR及ASDR均呈现显著下降趋势,然而疾病负担依然沉重,2023年患病人数高达9 532.40万例,DALYs达1 063.59万。分解分析进一步剖析了背后的驱动力量:人口年龄结构是推动疾病负担增长的最主要正向因素(对患病、发病、DALYs的贡献率均超过136%),而流行病学趋势变化则对患病和DALYs起到了关键的抑制作用(贡献率约为-97%至-98%)。ARIMA模型预测,至2040年,各指标ASR将继续稳步下降。
       LBP的发生并非单一因素作用,可能是多种风险因素共同作用的结果。尽管宏观上ASIR呈下降趋势,但2023年高达4 138.36万例的发病人数,提示个体层面的风险暴露依然普遍。长期久坐与不良姿势是当前LBP的高危因素[10-11],久坐会导致腰背部肌肉持续紧张,腰椎间盘压力长期处于较高水平[12],加速椎间盘退变,诱发疼痛[13]。有椎间盘突出病史者,LBP复发率高于无病史人[14]。而肌肉力量不足会导致腰椎稳定性下降,引发疼痛[15]。此外,长期处于寒冷环境,会导致腰背部血管痉挛,增加LBP发病概率[16-17]。此外,肥胖也是我国LBP流行的重要因素[18],BMI每增加5%,LBP的风险就会增加35%[19]。针对这些因素精准干预,可能是进一步扭转发病率趋势的关键。
       不同职业人群是LBP疾病负担分布中的重要部分[20-21]。体力型职业(如搬运工)的腰椎高负荷[22]、久坐或久站职业(如职员、教师)的持续静态负荷[11,23],都易导致腰椎生物力学的失衡,引发LBP。因此,职业防护至关重要,需通过微观的职业健康管理来缓解宏观的人口结构压力。
       研究结果还揭示了一个值得深思的现象,1990—2023年间,女性在ASPR、ASIR和ASDR的下降幅度均大于男性,但疾病负担依然严峻。2023年女性的ASPR、ASIR和ASDR均显著高于男性,特别是40岁以后差距更为明显,预测至2040年,此差距依然存在。这种差异可能由于性别特异性风险因素:一是妊娠期女性腰椎前凸角度增加,腰背部负荷较孕前增大,从而引起LBP[24-25];此外,LBP的发生风险随怀孕次数增加而提高[26]。二是绝经后女性雌激素水平骤降,引起骨密度下降,且下降速度快于男性,导致LBP[27];另外,骨质疏松会导致腰椎椎体强度下降,易出现压缩性骨折,诱发LBP[28-29]。这些因素共同导致女性,尤其是中老年女性,在DALYs和日常活动受限比例上处于显著劣势。未来的干预措施可以重点考虑这一方向。
       本研究的分解分析指出,人口年龄结构是LBP负担增长的主要推动力,我国人口老龄化进程正成为LBP疾病负担上升的重要组成部分[30]。分解分析显示了人口老龄化在LBP负担增长中的重要地位(对患病、DALYs的贡献率均超过136%)。随着年龄增长,腰椎退变累积,导致LBP发病率升高[31];同时,老年人群腰背部肌肉萎缩,导致腰椎稳定性显著降低,易诱发LBP[15,32-33]。老年LBP并非单纯的疼痛问题,也影响老年人的自理能力,并产生更多的家庭与社会成本[34]。尽管预测显示ASDR未来将持续下降,但我国社会快速老龄化的进程[4],意味着LBP患病人群的绝对数量可能继续攀升,应对老龄化带来的LBP危机,是未来公共卫生需要重视的一个重要方面。
       1990—2023年,我国LBP患病人数等负担指标持续上升,但年龄标准化率显著下降。医疗进步与健康意识提升发挥了积极作用,然而个体风险暴露仍普遍。人口年龄结构是LBP负担增长的核心驱动因素,而流行病学趋势变化对患病和DALYs起明显抑制作用,且其影响存在明显的性别差异。ARIMA模型预测显示,2024—2040年男女LBP相关年龄标准化指标将持续下降,但女性负担仍高于男性,性别特异性因素是主要原因。综上所述,我国LBP疾病负担是多因素交织的结果,未来干预需多维度考量、多部门协同,以确保我国LBP疾病负担持续下降。
       本研究仍存在一定局限性:第一,研究数据均来源于GBD 2023数据库。该数据库中下背痛的患病率、发病率等指标均基于全球多源数据整合与模型估算获得,存在固有估算误差;且数据库中针对中国人群的本土化流行病学调查数据占比有限,部分指标可能与我国实际流行情况存在偏差。第二,本研究采用ARIMA模型开展疾病负担趋势预测,该模型依托时间序列历史数据规律构建,对未来人口结构突变、社会经济模式转型等结构性变化的适应能力有限,若未来出现重大公共卫生政策干预、居民生活方式大幅改变等突发情况,模型预测结果的准确性可能受到影响。第三,研究未单独纳入政策干预、区域经济发展差异、医疗资源可及性、不同职业防护措施落实情况等因素。上述因素可通过改变居民下背痛风险暴露水平、早期诊疗效率等,间接影响疾病负担的发展趋势。未能纳入这些因素可能导致对驱动因素的探讨不够全面。第四,本研究聚焦全国层面的下背痛疾病负担分析,未开展分城乡、分区域的精细化研究,因此难以反映我国不同经济发展水平地区下背痛负担的分布特征与差异。 
       后续研究可结合我国本土化的下背痛流行病学横断面调查和队列研究数据对结果进行校正,以提升其真实性。同时,可开展分城乡、分区域、分职业的下背痛疾病负担研究,明确不同特征人群的负担差异,为制定更具针对性的防控策略提供数据支撑。

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