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北京大学学报（医学版） ›› 2024, Vol. 56 ›› Issue (2): 230-238. doi: 10.19723/j.issn.1671-167X.2024.02.005

• 论著 • 上一篇    下一篇

数字融入和健康生活方式对社会经济状况与老年人抑郁关系的序列中介作用

汤华萌1,袁典琪1,王明星1,杨晗冰1,郭超1,2,*()   

  1. 1. 北京大学人口研究所，北京 100871
    2. 北京大学亚太经合组织健康科学研究院，北京 100871
  • 收稿日期:2023-06-21 出版日期:2024-04-18 发布日期:2024-04-10
  • 通讯作者: 郭超 E-mail:chaoguo@pku.edu.cn
  • 基金资助:
    国家自然科学基金(82103955);北京大学临床医学+X青年专项-中央高校基本科研业务费(7100604313)

Sequential mediating role of digital participation and health lifestyle in the relationship between socioeconomic status and depression of older adults

Huameng TANG1,Dianqi YUAN1,Mingxing WANG1,Hanbing YANG1,Chao GUO1,2,*()   

  1. 1. Institute of Population Research, Peking University, Beijing 100871, China
    2. APEC Health Science Academy (HeSAY), Peking University, Beijing 100871, China
  • Received:2023-06-21 Online:2024-04-18 Published:2024-04-10
  • Contact: Chao GUO E-mail:chaoguo@pku.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(82103955);the Fundamental Research Funds for the Central Universities: Peking University Clinical Medicine Plus X-Young Scholars Project(7100604313)

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摘要：

目的: 通过数字融入和健康生活方式的中介作用探索数字时代下社会经济状况与老年人抑郁关系的内部潜在作用机制。方法: 使用中国家庭追踪调查(China Family Panel Studies, CFPS)2020年数据，借助链式多重中介效应模型并构建健康生活方式的综合指标，运用KHB (The Karlson, Holm, and Breen)中介效应测度法检验健康生活方式和数字融入在社会经济状况与老年人抑郁之间的中介作用，计算中介作用比例，并进行结构方程模型等一系列稳健性检验。结果: 纳入分析的4 846位老年人平均年龄为(68.20±5.07)岁，其中48.06%为女性。KHB结果显示，数字融入和健康生活方式同时作为中介变量能够在社会经济地位与老年人抑郁之间起到中介作用(P < 0.000 1)，健康生活方式的中介作用占比大于数字融入。本研究主要发现三条社会经济状况与老年人抑郁的潜在作用路径，包括：(1)社会经济状况→数字融入→健康生活方式→抑郁，(2)社会经济状况→健康生活方式→抑郁，(3)社会经济状况中收入和城乡对抑郁的直接作用。结构方程模型检验证明本研究模型的整体拟合情况较好。结论: 数字时代下，社会经济状况除了直接作用、以生活方式为中介间接作用于老年人抑郁，还存在通过数字融入促进形成健康的生活方式进而降低抑郁风险的序列中介作用，提示我们应关注社会经济地位较差的老年人在数字时代下多重劣势状态的进一步累积。

关键词: 序列中介作用, 抑郁, 老年人, 健康生活方式, 数字鸿沟

Abstract:

Objective: To explore the potential mechanisms of the relationship between socioeconomic status (SES) and depression of Chinese older adults through the mediating role of digital participation and health lifestyle. Methods: Using the nationally representative data from the China Family Panel Studies in 2020, 4 846 participants aged 60 years and older were analyzed in our study. We explored the potential mechanisms of the relationship between SES and depression of Chinese older adults in the digital era through a chain multiple mediating effects model. The KHB (The Karlson, Holm, and Breen) method was used to analyze the mediating role of digital participation and health lifestyle and the proportion of mediating effect between the two was also calculated. A series of robustness tests were further conducted and the fit of the model was checked by structural equation modeling. Results: The mean age of the 4 846 older adults included in this study was (68.20±5.07) years, 48.06% of whom were female and 51.94% were male. The KHB results showed that both digital participation and health lifestyle could mediate the relationship between SES and depression of older adults (P < 0.000 1) and the mediating role of health lifestyle accounted for a greater proportion than digital participation. And our study mainly found three potential pathways of SES and depression of older adults, including: (1) SES → digital participation → health lifestyle → depression, (2) SES → health lifestyle → depression, and (3) SES → depression. Structural equation modeling tests proved the overall fit of the model in this study. Conclusion: Our findings showed that in the digital age, in addition to the direct relationship between SES and depression of older adults, and the health lifestyle as a mediator between the relationship, there is also a sequential mediating role of digital participation and health lifestyle to reduce the risk of depression. The findings suggest that we should pay more attention to the probability of the digital divide exacerbating health inequalities and socioeconomic inequalities accumulation in the digital age and promote the co-progress of digital literacy and health literacy among older adults.

Key words: Sequential mediating effects, Depression, Aged, Health lifestyle, Digital divide

中图分类号: 

  • R749.4

图1

样本流程图"

表1

健康生活方式的标准及依据"

Health-related behaviors Questions from CFPS Healthy lifestyle factors③
Smoking Have you smoked in the past month? No smoking
Drinking Have you been drinking more than 3 times a week for the past month? Drinking less than 3 times a week
Sleeping How many minutes do you usually sleep for a nap?In general, how many hours of sleep per day, excluding the nap? (If divided into weekdays and rest-days, the average is calculated based on two rest-days a week) Sleep duration (including nighttime and nap) of more than 5 h and less than 10 h per day①
Exercising How often did you exercise in the past 12 months? (2020) Exercise more than 3 times a week②
Diet Whether consuming protein in the past week?Whether consuming fruits and vegetables in the past week? Dietary structure with protein and vitamins

图2

数字时代下社会经济状况与老年人抑郁关系的潜在路径模型"

表2

老年人的社会人口及健康相关特征"

CharacteristicDigital participation (n=4 846)P value
No (n=3 756) Yes (n=1 090)
Covariates, n (%)
  Age group
    Aged 60 to 74 years 3 085 (82.14) 1 022 (93.76) < 0.000 1
    Aged 75 years and above 671 (17.86) 68 (6.24)
  Gender
    Female 1 869 (49.76) 460 (42.20) < 0.000 1
    Male 1 887 (50.24) 630 (57.80)
  Marriage status
    Not in marriage 672 (17.89) 135 (12.39) < 0.000 1
    In marriage 3 084 (82.11) 955 (87.61)
  Employment
    Employed 2 067 (55.03) 412 (37.80) 0.000 1
    Not 1 689 (44.97) 678 (62.20)
  Chronic disease
    No 2 636 (70.18) 765 (70.18) 0.999
    Yes 1 120 (29.82) 325 (29.82)
  Self-rated health
    Not good 1 690 (44.99) 373 (34.22) < 0.000 1
    Good 2 066 (55.01) 717 (65.78)
Independent variables
  Income, $\bar x \pm s$
    ln(In+1) 6.69±3.68 8.50±3.68 < 0.000 1
  Education, n (%)
    Primary school and below 2 470 (65.76) 245 (22.48) < 0.000 1
    Above primary school 1 286 (34.24) 845 (77.52)
  Living areas, n (%)
    Rural 2 111 (56.20) 306 (28.07) < 0.000 1
    Urban 1 645 (43.80) 784 (71.93)
Dependent variables, n (%)
    Depression 783 (20.85) 135 (12.39) < 0.000 1
    Healthy 2 973 (79.15) 955 (87.61)
Health lifestyle*
    Level, $\bar x \pm s$ 3.36±1.00 3.82±0.99 < 0.000 1

表3

数字参与和健康生活方式在社会经济地位与抑郁之间的中介效应分析(回归分析结果)"

ItemsDigital participation Health lifestyle Depression
OR 95%CI β 95%CI OR① 95%CI① OR② 95%CI②
SES
  Income 1.08*** 1.06-1.10 0.02*** 0.01-0.28 0.96*** 0.94-0.98 0.96*** 0.94-0.98
  Education 4.53*** 3.80-5.41 0.21*** 0.15-0.27 0.80* 0.67-0.96 0.89 0.74-1.07
  Living areas 2.06*** 1.73-2.46 0.26*** 0.20-0.31 0.64*** 0.55-0.76 0.70*** 0.59-0.83
Intermediary variables
  Digital participation 0.26*** 0.19-0.32 0.84 0.67-1.05
  Health lifestyle 0.77*** 0.70-0.83

表4

数字参与和健康生活方式在社会经济地位与抑郁之间的中介效应分析(KHB结果)"

ItemsM1+M2 M1 M2
Income Education Living areas Income Education Living areas Income Education Living areas
Total effect 0.956*** 0.796* 0.639*** 0.956*** 0.799* 0.642*** 0.957*** 0.798* 0.641***
Direct effect 0.964*** 0.892 0.701*** 0.959*** 0.845 0.658*** 0.963*** 0.859 0.692***
Indirect effect 0.992*** 0.892*** 0.911*** 0.997* 0.945* 0.976* 0.994*** 0.929*** 0.926***
Mediation proportion/% M1: 4.40M2: 13.95 M1: 18.24M2: 31.73 M1: 4.04M2: 16.71 5.95 25.01 5.51 14.46 32.75 17.22

图3

数字时代下社会经济状况与老年人抑郁关系的内部作用路径"

表5

数字参与和健康生活方式在社会经济地位与抑郁之间的中介作用：稳健性检验(KHB)"

ItemsM1+M2 M1 M2
Income Education Living areas Income Education Living areas Income Education Living areas
Total effect 0.956*** 0.801* 0.640*** 0.956*** 0.799* 0.642*** 0.956*** 0.803* 0.642***
Direct effect 0.961*** 0.865 0.668*** 0.959*** 0.843 0.657*** 0.959*** 0.826* 0.657***
Indirect effect 0.995** 0.927** 0.957*** 0.997* 0.948* 0.977* 0.997* 0.972*** 0.977**
Mediation proportion/% M1: 5.37M2: 5.03 M1: 12.51M2: 21.98 M1: 4.72M2: 5.09 5.59 24.01 5.27 5.57 12.88 5.24

表6

数字参与和健康生活方式在社会经济地位与抑郁之间的中介作用：稳健性检验(SEM)"

ItemsDigital participation Health lifestyle Depression
β 95%CI β 95%CI β 95%CI
SES
  Income 0.047*** 0.019 to 0.075 0.088*** 0.061 to 0.114 -0.066*** -0.093 to -0.038
  Education 0.200*** 0.171 to 0.230 0.134*** 0.105 to 0.163 -0.029 -0.059 to 0.001
  Living areas 0.027 -0.003 to 0.057 0.139*** 0.111 to 0.167 -0.094*** -0.122 to -0.065
Intermediary variables
  Digital participation 0.059*** 0.032 to 0.086 0.017 -0.010 to 0.044
  Health lifestyle -0.113*** -0.141 to -0.085
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