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Journal of Peking University (Health Sciences) ›› 2024, Vol. 56 ›› Issue (2): 230-238. doi: 10.19723/j.issn.1671-167X.2024.02.005

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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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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

CLC Number: 

  • R749.4

Figure 1

Flowchart of samples"

Table 1

Conceptual basis of health lifestyles"

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

Figure 2

The potential mechanisms of the relationship between SES and depression of Chinese older adults SES, socioeconomic status; X, the independent variable “social economic status”; Y, the dependent variable “depression status”; M1, the mediating variable “digital participation”; M2, the mediating variable “health lifestyle”; a1, a2, a3, b1, and b2, relationship between variables."

Table 2

Sociodemographic and health-related characteristics of older adults"

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

Table 3

Mediating role of digital participation and health lifestyle between SES and depression (regression analysis)"

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

Table 4

Mediating role of digital participation and health lifestyle between SES and depression (KHB)"

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

Figure 3

The mechanisms of the relationship between socioeconomic status and depression of Chinese older adults in the digital age"

Table 5

Mediating role of digital participation and health lifestyle between SES and depression: Robustness test (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

Table 6

Mediating role of digital participation and health lifestyle between SES and depression: Robustness test (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
1 Phelan JC , Link BG , Tehranifar P .Social conditions as fundamental causes of health inequalities: Theory, evidence, and policy implications[J].J Health Soc Behav,2010,51(Suppl):S28-S40.
2 Cockerham WC .Health lifestyle theory and the convergence of agency and structure[J].J Health Soc Behav,2005,46(1):51-67.
doi: 10.1177/002214650504600105
3 de Vogli R , Gimeno D , Kivimaki M .Socioeconomic inequalities in health in 22 European countries[J].New Engl J Med,2008,359(12):1290-1291.
doi: 10.1056/NEJMc081414
4 van Doorslaer E , Koolman X .Explaining the differences in income-related health inequalities across European countries[J].Health Econ,2004,13(7):609-628.
doi: 10.1002/hec.918
5 Meyer IH , Schwartz S , Frost DM .Social patterning of stress and coping: Does disadvantaged social statuses confer more stress and fewer coping resources[J].Soc Sci Med,2008,67(3):368-379.
doi: 10.1016/j.socscimed.2008.03.012
6 王甫勤.社会经济地位、生活方式与健康不平等[J].社会,2012,32(2):125-143.
7 黄洁萍, 尹秋菊.社会经济地位对人口健康的影响——以生活方式为中介机制[J].人口与经济,2013,(3):26-34.
8 袁迎春.不平等的再生产: 从社会经济地位到健康不平等——基于CFPS2010的实证分析[J].南方人口,2016,31(2):1-15.
9 Jones IR , Papacosta O , Whincup PH , et al.Class and lifestyle "lock-in" among middle-aged and older men: A multiple correspondence analysis of the British regional heart study[J].Sociol Health Ill,2011,33(3):399-419.
doi: 10.1111/j.1467-9566.2010.01280.x
10 唐丹, 张琨, 亓心茹.互联网使用对老年人社会网络及孤独感的影响: 基于用途的分析[J].人口研究,2022,46(3):88-101.
11 Cotten SR , Ford G , Ford S , et al.Internet use and depression among older adults[J].Comput Hum Behav,2012,28(2):496-499.
doi: 10.1016/j.chb.2011.10.021
12 Confortin SC , Giehl MWC , Antes DL , et al.Positive self-rated health in the elderly: A population-based study in the South of Brazil[J].Cad Saude Publica,2015,31(5):1049-1060.
doi: 10.1590/0102-311X00132014
13 Gracia E , Herrero J .Internet use and self-rated health among older people: A national survey[J].J Med Internet Res,2009,11(4):e49.
doi: 10.2196/jmir.1311
14 王宇.智能手机使用对老年人主观健康的影响研究——基于2016年中国老年社会追踪调查(CLASS)数据[J].人口与发展,2020,26(6):65-75.
15 李志光, 贾仓仓.互联网使用对中老年人心理健康的影响: 异质性特征与作用机制检验[J].江苏社会科学,2021,(6):72-79.
16 杜鹏, 马琦峰, 和瑾, 等.互联网使用对老年人心理健康的影响研究——基于教育的调节作用分析[J].西北人口,2023,44(2):1-13.
17 Chang SJ , Im EO .A path analysis of Internet health information seeking behaviors among older adults[J].Geriatr Nurs,2014,35(2):137-141.
doi: 10.1016/j.gerinurse.2013.11.005
18 Wang YN , Song YT , Zhu YR , et al.Association of eHealth literacy with health promotion behaviors of community-dwelling older people: The chain mediating role of self-efficacy and self-care ability[J].Int J Env Res Pub Health,2022,19(10):6092.
doi: 10.3390/ijerph19106092
19 Nakagomi A , Shiba K , Kawachi I , et al.Internet use and subsequent health and well-being in older adults: An outcome-wide analysis[J].Comput Hum Behav,2022,130,107156.
doi: 10.1016/j.chb.2021.107156
20 Peng YI , Chan YS .Do internet users lead a healthier lifestyle?[J].J Appl Gerontol,2020,39(3):277-284.
doi: 10.1177/0733464818785797
21 阮航清, 陈功.中国老年人与收入相关的健康不平等及其分解——以北京市为例[J].人口与经济,2017,(5):84-94.
22 赵晓航, 阮航清.中国成年人抑郁症状的社会经济梯度研究——基于"中国家庭追踪调查"2014年和2016年数据[J].北京社会科学,2019,(8):34-47.
23 伍小兰, 李晶, 王莉莉.中国老年人口抑郁症状分析[J].人口学刊,2010,(5):43-47.
24 李甲森, 马文军.中国中老年人抑郁症状现状及影响因素分析[J].中国公共卫生,2017,33(2):177-181.
25 丁志宏, 王妍.使用互联网会降低老年人的抑郁水平吗?[J].兰州学刊,2023,(2):148-160.
26 Zheng X , Guo C .Strengthening systematic research on aging: Reflections from an omics perspective[J].China CDC Wkly,2022,4(39):875-878.
doi: 10.46234/ccdcw2022.181
27 张韵, 梁宏.社会经济地位与老年人生活方式: 低水平的"收敛"与高水平的"发散"[J].人口研究,2021,45(3):114-128.
28 Briggs R , Carey D , O'Halloran AM , et al.Validation of the 8-item centre for epidemiological studies depression scale in a cohort of community-dwelling older people: data from The Irish Longitudinal Study on Ageing (TILDA)[J].Eur Geriatr Med,2018,9(1):121-126.
doi: 10.1007/s41999-017-0016-0
29 Zhan HJ , Feng XT , Luo BZ .Placing elderly parents in institutions in urban China: A reinterpretation of filial piety[J].Res Aging,2008,30(5):543-571.
doi: 10.1177/0164027508319471
30 骆琪, 阎国光.社会经济地位对老年人健康影响的实证检验[J].统计与决策,2012,(13):91-94.
31 齐良书, 王诚炜.健康状况与社会经济地位: 基于多种指标的研究[J].中国卫生经济,2010,29(8):47-50.
32 Wu XG , Treiman DJ .The household registration system and social stratification in China: 1955-1996[J].Demography,2004,41(2):363-384.
doi: 10.1353/dem.2004.0010
33 程云飞, 李姝, 熊晓晓, 等."数字鸿沟"与老年人自评健康——以北京市为例[J].老龄科学研究,2018,6(3):14-25.
34 张未平, 范君晖.老年数字鸿沟的社会支持体系构建[J].老龄科学研究,2019,7(2):63-70.
35 李路路, 王煜."健康"作为生活方式的模式: 机会结构和个体能动性的双重建构——基于潜类别分析的研究[J].江苏社会科学,2018,(5):70-81.
36 Sun YJ , Xu LZ , Ma ZH , et al.Health-related risky behaviors and their risk factors in adolescents with high-functioning autism[J].World J Clin Cases,2021,9(22):6329-6342.
doi: 10.12998/wjcc.v9.i22.6329
37 Zhang L , Bi XY , Ding ZH .Health lifestyles and Chinese oldest-old's subjective well-being-evidence from a latent class analysis[J].Bmc Geriatrics,2021,21(1):206.
doi: 10.1186/s12877-021-02121-0
38 唐丹.城乡因素在老年人抑郁症状影响模型中的调节效应[J].人口研究,2010,34(3):53-63.
39 柳士顺, 凌文辁.多重中介模型及其应用[J].心理科学,2009,32(2):433-435.
40 温忠麟, 叶宝娟.中介效应分析: 方法和模型发展[J].心理科学进展,2014,22(5):731-745.
41 Preacher KJ , Hayes AF .Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models[J].Behav Res Methods,2008,40(3):879-891.
doi: 10.3758/BRM.40.3.879
42 Breen R , Karlson KB , Holm A .Total, direct, and indirect effects in Logit and probit models[J].Sociol Methods Res,2013,42(2):164-191.
doi: 10.1177/0049124113494572
43 Kohler U , Karlson KB , Holm A .Comparing coefficients of nested nonlinear probability models[J].Stata J,2011,11(3):420-438.
doi: 10.1177/1536867X1101100306
44 程开明.结构方程模型的特点及应用[J].统计与决策,2006,(10):22-25.
45 Cotten SR , Ford G , Ford S , et al.Internet use and depression among retired older adults in the United States: A longitudinal analysis[J].J Gerontol B Psychol Sci Soc Sci,2014,69(5):763-771.
doi: 10.1093/geronb/gbu018
46 王雪辉, 彭聪.老年人社会经济地位对健康的影响机制研究——兼论生活方式、公共服务和社会心理的中介效应[J].中国卫生政策研究,2020,13(3):21-30.
47 薛新东, 葛凯啸.社会经济地位对我国老年人健康状况的影响——基于中国老年健康影响因素调查的实证分析[J].人口与发展,2017,23(2):61-69.
48 杨梦瑶, 李知一, 李黎明.互联网使用与老年人的心理健康——基于两级数字不平等的视角[J].人口与发展,2022,28(6):132-147.
49 Dannefer D .Cumulative advantage/disadvantage and the life course: Cross-fertilizing age and social science theory[J].J Gerontol B Psychol Sci Soc Sci,2003,58(6):S327-S337.
doi: 10.1093/geronb/58.6.S327
50 Yates S , Kirby J , Lockley E .Digital Media Use: Differences and inequalities in relation to class and age[J].Sociol Res Online,2015,20(4):1-21.
doi: 10.5153/sro.3810
51 杜本峰, 王旋.老年人健康不平等的演化、区域差异与影响因素分析[J].人口研究,2013,37(5):81-90.
52 赵万里, 谢榕.数字不平等与社会分层: 信息沟通技术的社会不平等效应探析[J].科学与社会,2020,10(1):32-45.
53 Norman CD , Skinner HA .eHealth literacy: Essential skills for consumer health in a networked world[J].J Med Internet Res,2006,8(2):e9.
doi: 10.2196/jmir.8.2.e9
54 Hall AK , Bernhardt JM , Dodd V , et al.The digital health divide: Evaluating online health information access and use among older adults[J].Health Educ Behav,2015,42(2):202-209.
doi: 10.1177/1090198114547815
55 Suka M , Odajima T , Okamoto M , et al.Relationship between health literacy, health information access, health behavior, and health status in Japanese people[J].Patient Educ Couns,2015,98(5):660-668.
doi: 10.1016/j.pec.2015.02.013
56 陆杰华, 韦晓丹.老年数字鸿沟治理的分析框架、理念及其路径选择——基于数字鸿沟与知沟理论视角[J].人口研究,2021,45(3):17-30.
57 王元超, 王夏雨.互联网对个人健康的积极影响及其形成机制: 社会关系网络的作用[J].华东理工大学学报(社会科学版),2022,37(1):66-80.
58 赵建国, 刘子琼.互联网使用对老年人健康的影响[J].中国人口科学,2020,(5):14-26.
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