Childhood adversities and mid-late depressive symptoms over the life course: Evidence from the China health and retirement longitudinal study

Journal of Affective Disorders 245 (2019) 668–678

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Research paper

Childhood adversities and mid-late depressive symptoms over the life course: Evidence from the China health and retirement longitudinal study Fan Tiana, Steven Siyao Mengb, Peiyuan Qiua,c,

T

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a

West China School of Public Health, Sichuan University, Chengdu, China Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14642, USA c West China Research Center for Rural Health Development, Sichuan University, Chengdu, China b

ARTICLE INFO

ABSTRACT

Keywords: Childhood adversity Depressive symptoms Life course Chinese mid-aged and elderly

Background: The cumulative effect of childhood adversities on depressive symptoms in later life is well documented. However, there is a dearth of accurate information about this effect among Chinese population. The aim of this study is to examine the cumulative effect of childhood adversities on mid-late depressive symptoms in the Chinese population. Methods: Data were drawn from the China Health and Retirement Longitudinal Study (CHARLS). We included 17,425 respondents aged 45 and over, and retrospectively collected information of childhood adversities. The depressive symptoms were assessed using a 10-item Center for Epidemiologic Studies Depression Scale (CES-D). A structural equation model was employed for analysis. Results: Parental mental health problems had a direct effect on mid-late depressive symptoms (β = 0.180, P < 0.001). Lack of friends showed direct effect on mid-late depressive symptoms (β = 0.118, P < 0.001) and indirect effect through low SES and poor health status in mid-late life (β = 0.054, P < 0.001). Poor health status, child neglect and abuse, and low SES in childhood had an indirect effect on mid-late depressive symptoms (β = 0.128, β = 0.040, β = 0.098, P < 0.001). Limitations: Limitations of this study include recall bias on life course data collection, absence of adolescent data, limited construction of latent variables. Conclusions: These findings are crucial for preventing childhood adversities and subsequently reducing the prevalence of depression. Moreover, the indirect effects of childhood adversities suggest that early intervention and resource mobilization can circumvent some of the long-term mental health consequences.

1. Introduction Depression is now recognized as one of the most prominent health problems (Santini et al., 2015). The World Health Organization (WHO) estimated that in 2015, the total number of people with depression had exceeded 300 million globally. China had become the second main contributor to the global burden of depression, with total cases exceeding 54.8 million (WHO, 2017). Moreover, in the context of rapidly increasing ageing population worldwide, depression in late life raises considerable concern in both developed and developing countries (Gertner et al., 2017; Moussavi et al., 2007; Ni et al., 2017), with reported prevalence ranged from 4.7% and 16% (Blazer, 2003). Lei (Lei et al., 2014) reported that 30% of men and 45% of women aged 45 and over had depressive symptoms using baseline data of the China Health and Retirement Longitudinal Study (CHARLS), suggesting

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depression in mid-late life of Chinese people is a significant problem. The cause in depression is believed to be a combination of biological, psychological, and social factors (Urrea and Pedraza, 2000). Many cross-sectional studies found that risk factors for depression included female gender, functional impairment, chronic disease, socioeconomic status, unemployment, psychological trauma, or any other stressful life events, and so on (Lei et al., 2014; Li et al., 2016; Wagenaar et al., 2012; Waris et al., 2007). Some retrospective and prospective studies also found that early life adverse events, such as family history of depression, family disruption, death of parent, physical or emotional neglect, psychological, physical and sexual abuse were related to higher prevalence of later depression. (Betts, 2014; Gonzalez et al., 2012; Kessler et al., 2010; Najman et al., 2010; Raposo et al., 2014) Later on, researchers suggested that depression should be studied in the context of individual life courses (Colman and Ataullahjan, 2010).

Corresponding author at: West China School of Public Health, Sichuan University, No. 17, 3 section, South Renmin Road, Chengdu, Sichuan 610041,China E-mail address: [email protected] (P. Qiu).

https://doi.org/10.1016/j.jad.2018.11.028 Received 6 August 2018; Received in revised form 12 October 2018; Accepted 3 November 2018 Available online 06 November 2018 0165-0327/ © 2018 Elsevier B.V. All rights reserved.

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Fig. 1. Hypothesized structural equation model (SEM). Note: SES: socio-economic status.

Several studies reported that exposure to childhood adverse events was a powerful predictor for lifetime depressive symptoms (Chapman et al., 2004; Raposo et al., 2014; Yang and Lou, 2016). The effect of childhood adversities in these studies can be explained by the cumulative inequality (CI) theory, which suggests that early exposure to stressful events increase the risk of adulthood disadvantages, either in health or finance, and these disadvantages become more apparent as people age (Ferraro and Shippee, 2009). CI theory creatively incorporates the core principles from the cumulative disadvantage and life course theories and provides insight into the study aging and accumulation of inequality (Ferraro and Shippee, 2009). Considering that structural equation model (SEM) is able to incorporate multiple interacting factors longitudinally and identify the complex causal chains leading to disease, it is proper to apply SEM to the life course study. Therefore, in our study, we aim to use SEM techniques to examine the cumulative effect of childhood adversities on depressive symptoms in mid-late life based on the Chinese population and assess how the effect are mediated by influential factors of the casual chain. Under the framework of CI theory, we propose a theoretical SEM model (Fig. 1) in

the context of China, which includes five aspects of childhood adversities and other potential risk factors that might be associated with depression. We hypothesized that: (1) Parental mental health problems show a direct relationship with depressive symptoms in mid-late life. According to CI theory, familial factors including genetic transmission and shared living environment could have significant and long-lasting effects on offspring health outcomes (Ferraro and Shippee, 2009). Children of parents with persistent psychological distress have higher risk of depressive disorder during their childhood and adolescence (Ensminger et al., 2003). A 30-year follow-up study also demonstrated that offspring of depressed parents remained at greater risk for depression associated morbidity and mortality in their middle life compared with those of non-depressed parents (Weissman et al., 2016). Thus, we hypothesized a direct relationship between parental mental health and offspring depressive symptoms. (2) Child neglect and abuse have both direct and indirect effects on mid-late life depressive symptoms, with indirect effects mediated through low SES 669

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and poor health status in mid-late life. Based on CI theory, in addition to social economic status and societal structures, early-life adverse experiences or events can also impact later life outcomes for individuals (Ferraro and Shippee, 2009). People with a history of childhood abuse are more likely to suffer from trauma-associated symptoms such as personality disorders, substance abuse, posttraumatic stress disorder, chronic physical conditions, depression and suicidal ideations (Gonzalez et al., 2012; Herrenkohl et al., 2013; Levitan et al., 2003). Furthermore, neglect and interparental violence in the household have both been linked to depression and health impairments (Herrenkohl et al., 2013; Hovens et al., 2010). In the US, Zielinski (Zielinski, 2009) found that child neglect and abuse significantly increased the rates of unemployment, poverty and Medicaid usage, indicating a long-term impact on victims’ socioeconomic well-being. More importantly, mid-late life SES have been shown to be associated with depressive symptoms among elderly people (Lei et al., 2014). A meta-analysis concluded that health status in old age, especially in respect to chronic disease, was significantly associated with increased depression (Huang et al., 2010). As such, it is reasonable to test two hypothesized pathways to mid-late depressive symptoms: a direct pathway through childhood neglect and abuse, and an indirect pathway through low SES and poor health status in mid-late life as a consequence of childhood trauma. (3) Poor health status in childhood can directly and indirectly influence mid-late life depressive symptoms, with indirect effects mediated through poor health status in mid-late life. A range of early physical health problems in early life, such as asthma, prematurity, cancer, chronic illness and pain, have been found associated with depression (Jens et al., 2010; Raposa et al., 2014). Furthermore, poor childhood health can have a profound contribution to health deterioration later in life. Thus, we aim to examine the direct and indirect influence of poor health status in childhood on late depressive symptoms. (4) Low SES in childhood is indirectly associated with depressive symptoms in mid-late life. It has been reported that SES in childhood is a reliable predictor for the development of depression later in life (Gilman et al., 2003; Najman et al., 2010; Reading, 2004). This can be explained by the CI theory in that familial factors plays a critical role in shaping one's life course (Ferraro and Shippee, 2009). In terms of SES, intergenerational transmission of disparities is well documented. Children from socioeconomically disadvantaged families are more likely to remain in lower SES later in life (Reading, 2004). Meanwhile, lower SES, regarded as a chronic stressor, is highly correlated with limited social resources, worse health outcomes and increased adverse events in one's lifetime (Colman and Ataullahjan, 2010). Taken together, we hypothesize that lower SES in childhood will affect SES in adulthood, which is a strong risk factor for mid-late life depressive symptoms. (5) Lack of friends in childhood is directly and indirectly associated with depressive symptoms in mid-late life, with indirect associations through low SES in later life. Friendship is a major component of social relationships. Marver (Marver et al., 2017) found that impaired friendship predicted greater risk of suicide attempts, and the effect was largely explained by self-reported depression severity. Teo's study also demonstrated that high-quality social relationships were protective against depression (Teo et al., 2013). In addition, sociologists demonstrated that social relationships emerging from an early age and developed throughout life have long-lasting effects on health. Individuals with a high level of engagement in social relationships tend to be healthier than those with lower involvement (Umberson and Montez, 2010). Therefore, we intend to test the direct impact of friendship on depressive symptoms in mid-late life and its indirect impact on depression in later life though SES.

(6) Poor health status and low SES in mid-late life are tightly interwoven. Large amounts of empirical evidence have supported a consistent interconnection between SES and health (Anderson and Armstead, 1995; Marmot, 1995; Zimmer and Kwong, 2004). Zimmer (Zimmer and Kwong, 2004) found that socioeconomic status is positively correlated with chronic conditions, such as cardiovascular disease. In turn, individuals with health problems have relatively higher risk of being exposed to financially unstable environments (Jiang et al., 2012; Smith, 1999). Therefore, we intend to verify the interconnection between low SES and poor health in mid-late life. In addition to the direct and indirect risk factors for depression mentioned above, we have also proposed some correlations between childhood adversities, which can be found in Fig. 1. 2. Methods 2.1. Participants The data were drawn from the third and fourth wave of the China Health and Retirement Longitudinal Study (CHARLS), which is a nationally representative longitudinal survey of the residents aged 45 and older in China. Samples were obtained via multi-stage stratified sampling and the final samples fell within 150 counties of 28 provinces across China. More detailed description of the study design and sampling procedure can be found in the cohort profile of CHARLS (Zhao et al., 2014). The third wave of CHARLS, conducted in 2014, is a special survey in that it retrospectively collected the life history information of all longitudinal samples. The data include residence and relocation history, childhood history, education history, health and health care history and so on. It should be noted that childhood period in this data was defined as before 16 years old. The fourth wave conducted in 2015 was a regular follow-up investigation, which included demographic information, health status and functioning, health care and insurance, socio-economic status and so on. Thus, we matched the individuals of wave 3 and wave 4 based on their individual ID so that we can trace the childhood experience. Overall, 20,948 and 21,789 individuals were interviewed in wave 3 and wave 4 respectively. Respondents under the age of 45 or had missing value on depression questionnaire were exclude, and if depression questionnaire items were answered by proxy respondents, respondents were also excluded from the analysis. After matching and exclusion, we finally included 17,425 respondents. 2.2. Measurement 2.2.1. Assessments of depression Depressive symptoms were examined by the 10-item Center for Epidemiologic Studies Depression Scale (CES-D) short form, which has been widely used in many countries. The questionnaire includes 10 items in total and requires respondents to recall what they have felt and behaved during the last week. Responses to each item were rated using a 4-point scale varying from ‘Rarely or none of the time (less than 1 day)’ (0) to ‘Most or all of the time (5–7 days)’ (3). For items about negative emotions such as “I felt fearful”, we scored the answers from 0 for rare to 3 for most or all of the time. As for items about positive emotions such as “I felt hopeful about the future”, the score was reversed with 0 for all the time and 3 for rare. Therefore, a higher total score indicated a higher severity of depression and cut-off score for depressive symptoms was greater than or equal to 10 (Andresen et al., 1994). The Cronbach's α for CES-D-10 was 0.797 in this study.

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2.2.2. Assessments of childhood adversities 2.2.2.1. Socioeconomic status (SES). Childhood SES in this study was assessed by six indicators: education of female and male dependents, occupation of female and male dependents, food availability and selfreport family's financial situation. Education level included six categories from four-year college and above to illiteracy. Parental occupation included three categories: non-agricultural, farming and unemployment. Because many Chinese elders experienced the Great Famine in their childhood, we use the ‘enough food’ indicator to measure the family's SES. The self-report family financial situation was rated on a 5-point scale (1 = a lot better than other family to 5 = a lot worse than other family).

cardiovascular disease. The self-report health status was rated on a 5point scale from ‘1 = very good’ to ‘5 = very poor’. The remaining items include three common and prominent chronic diseases among Chinese elders, all of which were dichotomous. 2.3. Statistical analysis The hypothesized model showed in Fig. 1 was examined by a Structural Equation Modelling (SEM) approach. Based on the model results, we reconstructed the model by removing non-significant associations and re-assessing the model fitness. All analyses were conducted with MPlus 7.4 (Muthén and Muthén, 2012). Considering all included variables were either binary or ordered, the model was assessed using the weighted least squares means and variance adjusted estimation (WLSMV), which default using pairwise present approach to missing data to maximize the utility of the available data (Asparouhov and Muthén, 2010). According to the parameter estimate method, we reassessed each model using the following indices of fit: root mean square error of approximation (RMSEA) <0.08, comparative fit index (CFI) >0.90, and Tucker-Lewis index (TLI) >0.90. The x2 value should have been reported as a fit index, but we excluded it as this index was overly sensitive to sample size and tended to be too huge with large sample sizes. We also used standardized regression coefficients relative to endogenous and exogenous latent variables. Moreover, as the CHARLS adopted a multi-stage stratified sampling method, all analyses including descriptive analyses and SEM were weighted using individual sample weights adjusted for non-response in order to provide estimates representative of the population in China.

2.2.2.2. Child neglect and abuse. Child neglect refers to failure by a child's caregiver in meeting a child's physical, emotional, educational, or medical needs. Child abuse refers to all forms of physical and emotional maltreatment, and sexual abuse (Gateway, 2015). In our study, child neglect and abuse were measured as a latent variable using nine indicators: the frequency of adequate affection and love, the level of care that female dependent give, parental preference for other siblings, the frequency of quarrel and relationship between your parents, the frequency of domestic violence, the frequency of family members’ abuse including male dependents, female dependents and siblings. For each indicator, a higher score refers to a higher exposure to child neglect and abuse. 2.2.2.3. Lack of friends. Lack of friends in childhood was evaluated by three indicators: the frequency of loneliness, the frequency of having a group of friends, and presence of a good friend. The first two indicators used a 4-point scale ranging from ‘Often’, ‘Sometimes’, ‘Not very often’ and ‘Never’. And the last indicator was dichotomous.

Table 1 Demographic characteristics (weighted).

2.2.2.4. Parental mental health problems. We measured mental health problems in the parents using frequency of nervousness or anxiety, the frequency of upset mood or panic, and whether parents showed consistent signs of sadness or depression. The first two indicators used a 4-point scale (1 = a little of the time to 4 = most of the time) and the last indicator was dichotomous. 2.2.2.5. Poor health status. We assessed the childhood health status of individuals using 5 items, including their health status compared with other children of the same age, whether they missed school due to health problems, whether they were bedridden, whether they were hospitalized for a month or more and whether they were hospitalized more than three times over any given year. Except the first item, which was evaluated on a 5-point scale (1 = much healthier to 5 = much less healthy), the rest were all dichotomously coded (1 = yes and 0 = no). 2.2.3. Assessments of socioeconomic status (SES) in mid-late life Traditionally, SES was comprised of three indicators: family financial status, education level and living region. In most cases, ‘family financial status’ refers to the income index such as annual household income. However, due to the privacy and complexity of income and expense, it's usually hard to accurately collect the real information. Thus, researchers proposed the asset-based measures by constructing an asset index to evaluate the family SES (Bartholomew et al., 2002; Howe et al., 2008). In this study, we adopted the Principal Components Analysis (PCA) to calculate asset index. According to the asset index, we divided our respondents into 5 levels of ‘familial financial status’. Education was divided into six categories from four-year college and above to illiteracy and living region had two categories including urban and rural areas. 2.2.4. Assessments of poor health status in mid-late life Health status in mid-late life comprised of four items: self-report health status, and presence of disability, hypertension, diabetes and

Variable

Total sample (n = 17,425) x¯ ± SE / n (%)

95% CI

Age, Mean Age Aged 45–55 Aged 55–65 Aged 65–75 Aged 75+ Gender Male Female Education Illiteracy Elementary Middle Senior Three-year college Four-year college and above Living region Rural Urban Family financial situation I II III IV V Hypertension Diabetes Heart problems Self-report health status Very good Good Fair Poor Very poor Depression, Mean Depression

63.31 ± 0.14 16,570 4743(29.14) 4689(27.59) 4686(27.41) 2452(15.86) 17,410 8246(47.27) 9164(52.73) 17,417 3650(19.64) 7037(37.86) 4463(26.55) 1841(12.36) 277(2.09) 149(1.50) 17,359 12,446(62.69) 4913(37.31) 10,319 2070(19.63) 2079(19.37) 2046(19.03) 2147(20.85) 1977(21.13) 3728(21.36) 927(5.43) 1926(10.91) 16,828 2039(12.51) 1978(12.25) 8500(51.04) 3809(21.47) 502(2.73) 7.62 ± 0.07 5565(31.02)

63.04–63.58 – 28.03–30.25 26.65–28.54 26.47–28.35 15.00–16.72 – 46.17–48.37 51.63–53.83 – 18.84–20.44 36.84–38.88 25.53–27.57 11.53–13.18 1.73–2.45 1.14–1.86 – 61.47–63.91 36.09–38.53 – 18.45–20.80 18.26–20.47 17.94–20.11 19.79–21.91 19.90–22.35 20.51–22.22 4.99–5.87 10.31–11.51 – 11.65–13.36 11.55–12.95 49.95–52.14 20.66–22.29 2.46–3.00 7.49–7.75 30.09–31.96

Note: SE, standard error; CI, confidence interval.

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3. Results

3.2. Structural equation modeling

3.1. Demographic characteristics

The confirmatory factor analysis for the measuring model based on the theoretical framework indicated an appropriate factor structure with good model fit: CFI = 0.901; TLI = 0.894; RMSEA = 0.024. All factor loadings from the latent variables to observed variables were significant. The initial SEM was successfully identified but two hypothesized paths were not significant: from poor health status in childhood to depressive symptoms in mid-late life (P = 0.294) and from low SES in mid-late life to depressive symptoms in later life (P = 0.163). The hypothesized correlation between low SES in childhood and childhood neglect and abuse was also refuted (P = 0.176). We subsequently deleted the insignificant pathways and re-assessed each model. After that, we also found the path from childhood neglect and abuse to mid-late life depressive symptoms was not significant (P = 0.058). We deleted this pathway and obtain the final model (see Fig. 2). The fit indices of final model improved (CFI = 0.927;

Weighted statistics and frequency distributions of respondent characteristics are presented in Table 1. The total sample comprised of 17,425 respondents, of whom 52.73% were female. Average age was 63.31 (95% CI = 63.04–63.58) years, and primary respondents have low education level. About two-thirds of sampled population live in rural area and half of respondents reported a fair health status. In terms of depression, the average score of CES-D was 7.62 (95% CI = 7.49–7.75), and 31.02% of respondents were predicted to have depressive symptoms based on the cut-off value. Other summary information about childhood adversities of total sample and between respondents with and without depression were showed in Table A1 and Table A2.

Fig. 2. Final model with standardized path coefficients and significant level (N = 17,425).Note: SES: socio-economic status. Fit statistics: comparative fit index (CFI) = 0.927; Tucker–Lewis index (TLI) = 0.922; root mean square error of approximation (RMSEA) = 0.020 (90% CI = 0.019–0.020). ⁎⁎⁎P < 0.001; ⁎⁎P < 0.01; *P < 0.05. 672

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Table 2 Path coefficients and standard errors for the final SEM model (N = 17,425). Path Independent variable

Dependent variable

Final model β1

SE1

β2

SE2

P

Low SES in childhood Lack of friends in childhood Child neglect and abuse Poor health status in mid-late life Poor health status in childhood Child neglect and abuse Low SES in mid-late life Age Gender Lack of friends in childhood Parental mental health problems in childhood Poor health status in mid-late life

Low SES in mid-late life Low SES in mid-late life Low SES in mid-late life Low SES in mid-late life Poor health status in mid-late life Poor health status in mid-late life Poor health status in mid-late life Depressive symptoms in mid-late life Depressive symptoms in mid-late life Depressive symptoms in mid-late life Depressive symptoms in mid-late life Depressive symptoms in mid-late life

0.487 0.373 −0.460 0.468 0.095 0.103 0.094 0.005 −0.274 0.150 0.180 1.864

0.021 0.029 0.058 0.101 0.014 0.022 0.013 0.001 0.016 0.021 0.016 0.197

0.579 0.319 −0.174 0.146 0.229 0.125 0.303 0.073 −0.193 0.118 0.180 0.534

0.019 0.022 0.019 0.026 0.023 0.023 0.024 0.013 0.011 0.016 0.015 0.017

<0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

Note: SES: socio-economic status. β, path coefficient; SE, standard error; 1, unstandardized parameter; 2, standardized parameter. Table 3 Standardized direct effect, indirect and total effect of the childhood adversities on mid-late depressive symptoms (N = 17,425). Variable

Standardized direct effects

Standardized indirect effects

Standardized total effects

Age Gender Low SES in childhood Lack of friends in childhood Child neglect and abuse Poor health status in childhood Parental mental health problems in childhood Poor health status in mid-late life Low SES in mid-late life

0.073 −0.193⁎⁎⁎ – 0.118⁎⁎⁎ – – 0.180⁎⁎⁎ 0.534⁎⁎⁎ –

– – 0.098⁎⁎⁎ 0.054⁎⁎⁎ 0.040⁎⁎ 0.128⁎⁎⁎ – 0.025⁎⁎⁎ 0.169⁎⁎⁎

0.073⁎⁎⁎ −0.193⁎⁎⁎ 0.098⁎⁎⁎ 0.172⁎⁎⁎ 0.040⁎⁎ 0.128⁎⁎⁎ 0.180⁎⁎⁎ 0.558⁎⁎⁎ 0.169⁎⁎⁎

⁎⁎⁎

Note: SES: socio-economic status ⁎⁎⁎ P < 0.001 ⁎⁎ P < 0.01 *P < 0.05.

TLI = 0.922; RMSEA = 0.020 (90% CI = 0.019–0.020)). All path coefficients in the final model were standard and significant. Within the final model, parental mental health problems was significantly associated with depressive symptoms in mid-late life (β = 0.180, SE = 0.015). Lack of friends in childhood was associated with more severe depressive symptoms (β = 0.118, SE = 0.016) and significantly indicated a low SES in mid-late life (β = 0.319, SE = 0.022). Additionally, child neglect and abuse was associated with poor health status (β = 0.125, SE = 0.023) and low SES in mid-late life (β = −0.174, SE = 0.019). Poor health status in childhood significantly predicted a poor health status in later life (β = 0.229, SE = 0.023), which was strongly associated with severe depressive symptoms in mid-late life (β = 0.534, SE = 0.017). We also found that SES in childhood had significant influence on the late life SES (β = 0.579, SE = 0.019) and increased age and female gender were both significantly associated with severe depressive symptoms (β = 0.073, SE = 0.013; β = −0.193, SE = 0.022). Table 2 summarizes the standard path coefficients for the final model. Standardized direct and indirect effects of childhood adversities on mid-late life depressive symptoms were reported in Table 3. It has been demonstrated that poor health status in mid-late life has the largest effect on depressive symptoms (β = 0.558, SE = 0.018). Parental mental health had the third largest total effect on mid-late life depressive symptoms after the total effect of gender (β = 0.180, SE = 0.015). Lack of friends had both direct (β = 0.118, SE = 0.016) and indirect (β = 0.054, SE = 0.006) effect on depressive symptoms, with the indirect effects through low SES and poor health status in midlate life. Lack of friends also contributed a relatively high total effect on depressive symptoms (β = 0.172, SE = 0.016). Child neglect and abuse have no direct effect on depressive symptoms but contribute to poor health status and low SES in mid-late life (β = 0.040, SE = 0.013). Low

SES in childhood had an indirect effect on depressive symptoms through low SES and poor health status in mid-late life (β = 0.098, SE = 0.010). In addition, Table 4 summarized the correlations of five latent variables of childhood adversities. 4. Discussion As far as we know, this study is the first to explore cumulative effect of childhood adversities on later depressive symptoms based on a representative sample of Chinese people. The results of this study have confirmed that the cumulative effect of childhood adversities on midlate depressive symptoms. Five aspects of childhood adversities, including parental mental health problems, poor health status, child neglect and abuse, low SES and lack of friends were all significantly associated with depressive symptoms in middle-aged and elderly life, either in a direct or indirect way. Furthermore, we found that these associations were significantly mediated through poor health and low SES in mid-late life. Echoing our hypothesis and prior studies, children of parents with mental health problems had an increased risk of developing depressive symptoms in later life. Weissman et al. (1997a,b, 2016) repeatedly investigated the risk of psychopathology, morbidity, and mortality in offspring of depressed parents from birth to adulthood using an European Caucasian cohort, and recent findings suggested that the offspring of depressed parents were approximately three times more susceptible to developing depression after 30-year followed-up compared to control. Similarly, Kessler et al. (2010) reported results from WHO World Mental Health Surveys and demonstrated parental mental illness was a significantly predictor for the mental disorders of offspring at each stage in life. The transmission of mental health illness from one generation to another could be rationally explained by the CI theory 673

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Table 4 Correlations of five latent variable of childhood adversities (N = 17,425). Latent variable Parental mental health problems Parental mental health problems Parental mental health problems Low SES Low SES Low SES Child neglect and abuse

Poor health status Lack of friends Child neglect and abuse Parental mental health problems Poor health status Lack of friends Poor health status

γ1

SE1

γ2

SE2

P

0.096 0.113 0.055 0.192 0.030 0.215 0.025

0.007 0.008 0.005 0.009 0.009 0.011 0.003

0.281 0.288 0.317 0.354 0.081 0.502 0.212

0.020 0.017 0.019 0.014 0.023 0.017 0.020

<0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

Note: SES: socio-economic status. γ, correlation coefficient; SE, standard error; 1, unstandardized parameter; 2, standardized parameter.

which proposes that familial factors have an enduring effect on offspring health outcomes (Ferraro and Shippee, 2009). Children living with parents with mental health illness may not only be influenced by negative emotions in the household such as fear, anxiety and depression, but also by maladaptive behaviours of their parents including substance abuse, domestic violence, neglect and suicide. At the same time, these children often fail to obtain adequate health care and emotional affection from their parents and tend to be a poor health status or more vulnerable to stressors in life. Long-term exposure to negative emotions, adverse behaviours and neglect can shape one's depressive personality, which can have life-long consequences. Consistent with our hypothesis, lacking friends in childhood has direct and indirect effects on depressive symptoms in mid-late life, with indirect effects mediated through low SES and poor health status in mid-late life. As Reisman postulated, limited friendship was a major diagnostic indicator for a range of psychiatric disorders (Reisman, 1985). A recent longitudinal cohort study found that highquality social relationships including friendship predicted lower risk of depressive symptoms in later life (Teo et al., 2013). It also has been extrapolated that social relationships developed since childhood can either foster cumulative advantage or disadvantage in health over one's lifetime (Umberson and Montez, 2010). We consider that a good friendship directly associates with children’ happiness, life satisfaction, self-esteem and self-confidence, which all have beneficial effects on coping mechanisms with events in life. For example, children often share their feelings with friends and seek support in times of trouble. To some extent, friendship can compensate for inadequate love and care from family. As such, a good friendship could be thought to a protective factor buffering the effects of life stress by enhancing individual's coping abilities. Additionally, we found that lack of friends increased susceptibility to low SES and poor health in mid-late life, which subsequently increased the likelihood of depressive symptoms in mid-late life. This phenomenon could be explained by the strong correlation between poor SES and lack of friends in childhood. Due to the intergenerational transmission of SES, children of a family with high SES had access to a better life condition and higher education, and more likely to acquire a high SES in their later life. This association also has been proved from our final model In this study, we did not find a direct association between child neglect or abuse and depressive symptoms in mid-late life as shown in previous studies (Spinhoven et al., 2010). However, we did observe an indirect total effect of child neglect and abuse on mid-life depressive symptoms through poor health status and low SES in late life. Although direct effects on depressive symptoms are insignificant, child neglect and abuse increase susceptibility for low SES and poor health status in mid-late life, which are both risk factors for depressive symptoms. Moreover, large amounts of studies have provided supports for the association between child neglect abuse and disadvantaged SES or adverse health outcomes in later life (Gonzalez et al., 2012; Horwitz et al., 2001). A prospective study indicated that subjects with a history of physical abuse as a child were susceptible to depression and chronic pain conditions (Gonzalez et al., 2012). Furthermore, Zielinski (Zielinski, 2009) found that victims of child neglect and abuse have

Table A1 Summary statistics of respondent childhood history (weighted). Variable

Low SES in childhood Education of female dependent Four-year college and above Three-year college Senior Middle Elementary Illiteracy Education of male dependent Four-year college and above Three-year college Senior Middle Elementary Illiteracy Occupation of female dependent Non-agricultural Farming Unemployment Occupation of male dependent Non-agricultural Farming No job Enough Food Family's financial situation A lot better off than others Somewhat better off than others Same as others Somewhat worse off than others A lot worse off than others Child neglect and abuse Enough affection Often Sometimes Not very often Never Enough care A lot Some A little Not at all Partiality of female dependent, Not at all strict A little strict Somewhat strict Very strict Partiality of male dependent Not at all strict A little strict Somewhat strict Very strict Relationship between your parents Excellent Very good Good Fair

Total sample (n = 17,425) n (%)

95% CI

16,623 17(0.16) 4(0.02) 120(1.06) 226(1.46) 1825(12.35) 14,431(84.95) 16,041 106(0.79) 47(0.37) 447(3.10) 832(5.87) 5496(35.10) 9113(54.77) 16,933 1028(8.92) 14,453(82.45) 1452(8.63) 16,558 3169(23.06) 13,256(76.17) 133(0.77) 5538(33.79) 17,321 198(1.43) 1417(9.34) 8825(50.99) 2761(15.77) 4120(22.48)

– 0.06–0.26 0–0.05 0.73–1.38 1.24–1.69 11.51–13.19 84.04–85.85 – 0.60–0.98 0.24–0.50 2.62–3.57 5.10–6.63 34.03–36.18 53.63–55.92 – 8.15–9.69 81.57–83.33 8.10–9.15 – 22.05–24.07 75.16–77.19 0.62–0.92 32.71–34.87 – 1.09–1.76 8.53–10.14 49.89–52.09 14.92–16.63 21.60–23.35

16,492 10,087(59.30) 2915(18.40) 1952(12.23) 1538(10.06) 16,524 9251(54.89) 3514(21.40) 2666(16.91) 1093(6.81) 16,505 13,768(82.43) 813(5.27) 1514(9.79) 410(2.51) 16,049 13,735(84.67) 777(5.43) 1198(7.91) 339(2.00) 15,806 3612(22.51) 5088(32.95) 2901(17.78) 3693(23.51)

– 58.19–60.41 17.45–19.36 11.52–12.95 9.35–10.77 – 53.79–55.98 20.56–22.24 15.96–17.85 6.24–7.38 – 81.52–83.34 4.72–5.81 9.07–10.51 2.16–2.87 – 83.81–85.52 4.86–6.00 7.25–8.56 1.75–2.24 – 21.61–23.41 31.79–34.10 17.00–18.56 22.56–24.47

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Table A1 (continued)

Table A1 (continued)

Variable

Total sample (n = 17,425) n (%)

95% CI

Variable

Total sample (n = 17,425) n (%)

95% CI

Poor Quarrel of your parents Never Not very often Sometimes Often Father beat up your mother Never Not very often Sometimes Often Mother beat up your father Never Not very often Sometimes Often Siblings abuse Never Not very often Sometimes Often Female abuse Never Not very often Sometimes Often Male abuse Never Not very often Sometimes Often Lack of friends in childhood Lonely due to no friends Never Not very often Sometimes Often Having a group of friends Never Not very often Sometimes Often Having a good friend Parental mental Health problems Female nervousness A little of the time Some of the time Good part of the time Most of the time Male nervousness A little of the time Some of the time Good part of the time Most of the time Female upset A little of the time Some of the time Good part of the time Most of the time Male upset A little of the time Some of the time Good part of the time Most of the time Female depression Never A little of the time Some of the time Most of the time All the time Male depression Never

512(3.25) 15,561 7039(43.82) 4920(32.54) 2750(18.26) 852(5.37) 15,347 12,118(79.28) 1939(12.69) 1015(6.27) 275(1.77) 15,440 14,599(94.56) 592(3.87) 191(1.14) 58(0.43) 17,040 14,243(83.08) 1705(10.22) 894(5.32) 198(1.39) 16,483 7619(44.82) 4835(30.30) 3316(20.32) 713(4.56) 16,110 9364(57.28) 3989(25.68) 2263(14.02) 494(3.02)

2.90–3.60 – 42.71–44.94 31.39–33.68 17.29–19.24 4.91–5.84 – 78.26–80.29 11.78–13.59 5.73–6.80 1.49–2.05 – 93.89–95.23 3.24–4.49 0.95–1.32 0.24–0.62 – 82.12–84.03 9.43–11.01 4.80–5.83 0.99–1.78 – 43.73–45.91 29.19–31.40 19.35–21.29 4.05–5.07 – 56.12–58.44 24.59–26.77 13.17–14.87 2.68–3.36

A little of the time Some of the time Most of the time All the time Poor health in childhood Health status Much healthier Somewhat healthier About average Somewhat less healthy Much less healthy Miss school due to health problems Confined to bed due to health problems Hospitalized for a month or more Hospitalized more than three times over one year

460(2.64) 557(3.53) 636(3.99) 153(0.91)

2.38–2.90 3.14–3.91 3.55–4.44 0.75–1.07

17,316 2902(17.20) 3215(18.63) 8942(50.92) 1376(8.47) 881(4.78) 684(3.93) 974(5.56) 371(2.05) 185(0.96)

– 16.33–18.06 17.84–19.43 49.82–52.02 7.77–9.16 4.34–5.23 3.55–4.30 5.11–6.00 1.81–2.28 0.81–1.12

17,017 13,431(80.04) 1436(8.16) 1089(6.21) 1061(5.59) 17,121 11,102(66.24) 2219(12.37) 1529(8.68) 2271(12.72) 9023(54.99)

– 79.24–80.84 7.60–8.72 5.71–6.71 5.22–5.96 – 65.25–67.23 11.73–13.00 8.12–9.24 12.00–13.44 53.93–56.06

16,094 10,608(66.53) 2661(16.48) 1611(9.81) 1214(7.19) 15,562 11,120(71.95) 2212(14.07) 1310(8.57) 920(5.41) 15,899 11,264(71.50) 2359(14.56) 1357(8.37) 919(5.56) 15,337 11,934(78.41) 1873(12.00) 912(5.87) 618(3.72) 15,706 12,446(80.00) 822(5.38) 982(5.99) 1138(6.70) 318(1.93) 15,157 13,351(88.93)

– 65.50–67.56 15.66–17.30 9.13–10.48 6.70–7.67 – 70.94–72.96 13.32–14.82 7.83–9.30 5.00–5.82 – 70.51–72.49 13.83–15.29 7.68–9.07 5.08–6.05 – 77.48–79.33 11.31–12.69 5.23–6.51 3.37–4.07 – 79.14–80.86 4.83–5.92 5.51–6.47 6.20–7.20 1.66–2.20 – 88.29–89.57

Note: SES: socio-economic status. CI, confidence interval.

Table A2 The prevalence of childhood adversities among depression and non-depression group. Variable

SES in childhood Education of female dependent, N(%) Illiteracy Elementary Middle Senior Three-year college Four-year college and above Education of male dependent, N(%) Illiteracy Elementary Middle Senior Three-year college Four-year college and above Occupation of female dependent, N(%) No job Farming Non-agricultural Occupation of male dependent, N(%) No job Farming Non-agricultural Enough Food, N(%) No Yes Family's financial situation, N(%) A lot worse off than others Somewhat worse off than others Same as others Somewhat better off than others A lot better off than others

Sample (n = 17,425) Depression non-depression (n = 5565) (n = 11,860)

x2/ P

50.262(< 0.001) 4752(32.93) 469(25.70) 52(23.01) 33(27.50) 1(25.00) 3(17.65)

9679(67.07) 1356(74.30) 174(76.99) 87(72.50) 3(75.00) 14(82.35) 46.572(< 0.001)

3068(33.67) 1642(29.88) 227(27.28) 110(24.61) 9(19.15) 30(28.30)

6045(66.33) 3854(70.12) 605(72.72) 337(75.39) 38(80.85) 76(71.70) 69.086(< 0.001)

444(30.58) 4730(32.73) 209(20.33)

1008(69.42) 9723(67.27) 819(79.67)

46(34.59) 4413(33.29) 808(25.50)

87(65.41) 8843(66.71) 2361(74.50)

4152(35.38) 1374(24.81)

7585(64.62) 4164(75.19)

1672(40.58)

2448(59.42)

952(34.48)

1809(65.52)

2515(28.50) 349(24.63)

6310(71.50) 1068(75.37)

46(23.23)

152(76.77)

72.095(< 0.001)

193.040(< 0.001) 239.543(< 0.001)

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Table A2 (continued) Variable

Child neglect and abuse Enough affection, N(%) Often Sometimes Not very often Never Enough care, N(%) A lot Some A little Not at all Mother favors other siblings, N(%) Not at all strict A little strict Somewhat strict Very strict Father favors other siblings, N(%) Not at all strict A little strict Somewhat strict Very strict Relationship between your parents, N(%) Excellent Very good Good Fair Poor Quarrel between your parents, N(%) Never Not very often Sometimes Often Father beat up your mother, N(%) Never Not very often Sometimes Often Mother beat up your father, N(%) Never Not very often Sometimes Often Siblings abuse, N(%) Never Not very often Sometimes Often Female abuse, N(%) Never Not very often Sometimes Often Male abuse, N(%) Never Not very often Sometimes Often Friendship in childhood Lonely due to no friends, N(%) Often Sometimes Not very often Never Having a group of friends, N(%) Often

Table A2 (continued) Sample (n = 17,425) Depression non-depression (n = 5565) (n = 11,860)

3190(31.62) 898(30.81) 652(33.40) 546(35.50)

6897(68.38) 2017(69.19) 1300(66.60) 992(64.50)

2961(32.01) 1021(29.06) 891(33.42) 420(38.43)

6290(67.99) 2493(70.94) 1775(66.58) 673(61.57)

4346(31.57) 247(30.38) 485(32.03) 190(46.34)

9422(68.43) 566(69.62) 1029(67.97) 220(53.66)

4320(31.45) 237(30.50) 423(35.31) 151(44.54)

9415(68.55) 540(69.50) 775(64.69) 188(55.46)

1057(29.26) 1404(27.59) 960(33.09) 1390(37.64) 221(43.16)

2555(70.74) 3684(72.41) 1941(66.91) 2303(62.36) 291(56.84)

2130(30.26) 1492(30.33) 960(34.91) 382(44.84)

4909(69.74) 3428(69.67) 1790(65.09) 470(55.16)

3641(30.05) 686(35.38) 405(39.90) 137(49.82)

8477(69.95) 1253(64.62) 610(60.10) 138(50.18)

4568(31.29) 232(39.19) 84(43.98) 25(43.10)

10,031(68.71) 360(60.81) 107(56.02) 33(56.90)

4451(31.25) 576(33.78) 343(38.37) 107(54.04)

9792(68.75) 1129(66.22) 551(61.63) 91(45.96)

2331(30.59) 1504(31.11) 1121(33.81) 320(44.88)

5288(69.41) 3331(68.89) 2195(66.19) 393(55.12)

2964(31.65) 1246(31.24) 741(32.74) 196(39.68)

6400(68.35) 2743(68.76) 1522(67.26) 298(60.32)

2

x /P

12.954(0.0047)

37.194(< 0.001)

40.930(< 0.001)

33.240(< 0.001)

142.887(< 0.001)

91.420(< 0.001)

100.609(< 0.001)

33.139(< 0.001)

66.711(< 0.001)

68.013(< 0.001)

15.535(0.0014)

294.200(< 0.001) 536(50.52) 472(43.34) 530(36.91) 3926(29.23)

525(49.48) 617(56.66) 906(63.09) 9505(70.77)

905(39.85)

1366(60.15)

192.708(< 0.001)

676

Variable

Sample (n = 17,425) Depression non-depression (n = 5565) (n = 11,860)

Sometimes Not very often Never Having a good friend, N (%) No Yes Parental mental health problems Female nervousness, N (%) A little of the time Some of the time Good part of the time Most of the time Male nervousness, N(%) A little of the time Some of the time Good part of the time Most of the time Female upset, N(%) A little of the time Some of the time Good part of the time Most of the time Male upset, N(%) A little of the time Some of the time Good part of the time Most of the time Female depression, N (%) Never A little of the time Some of the time Most of the time All the time Male depression, N(%) Never A little of the time Some of the time Most of the time All the time Health in childhood Health status, N(%) Much healthier Somewhat healthier About average Somewhat less healthy Much less healthy Miss school due to health problems, N (%) No Yes Confined to bed due to health problems, N (%) No Yes Hospitalized for a month or more, N(%) No Yes Hospitalized more than three times over one year, N(%) No Yes

618(40.42) 810(36.50) 3176(28.61) 1387(49.41)

911(59.58) 1409(63.50) 7926(71.39) 9023(52.7)

2830(34.95) 2677(29.67)

5267(65.05) 6346(70.33)

x2/ P

54.578(< 0.001)

245.009(< 0.001) 2983(28.12) 947(35.59) 684(42.46) 529(43.57)

7625(71.88) 1714(64.41) 927(57.54) 685(56.43)

3227(29.02) 774(34.99) 570(43.51) 395(42.93)

7893(70.98) 1438(65.01) 740(56.49) 525(57.07)

3094(27.47) 901(38.19) 625(46.06) 441(47.99)

8170(72.53) 1458(61.81) 732(53.94) 478(52.01)

3394(28.44) 745(39.78) 440(48.25) 291(47.09)

8540(71.56) 1128(60.22) 472(51.75) 327(52.91)

3439(27.63) 351(42.70) 425(43.28) 616(54.13) 165(51.89)

9007(72.37) 471(57.30) 557(56.72) 522(45.87) 153(48.11)

3882(29.08) 215(46.74) 262(47.04) 367(57.70) 70(45.75)

9469(70.92) 245(53.26) 295(52.96) 269(42.30) 83(54.25)

736(25.36) 918(28.55) 2884(32.25) 540(39.24) 458(51.99)

2166(74.64) 2297(71.45) 6058(67.75) 836(60.76) 423(48.01)

5275(31.66) 269(39.33)

11,384(68.34) 415(60.67)

5095(31.24) 427(43.84)

11,214(68.76) 547(56.16)

5368(31.73) 154(41.51)

11,549(68.27) 217(58.49)

5435(31.79) 86(46.49)

11,664(68.21) 99(53.51)

185.028(< 0.001)

379.943(< 0.001)

297.616(< 0.001)

525.147(< 0.001)

271.616(< 0.001)

17.740(< 0.001) 67.107(< 0.001)

15.967(< 0.001)

18.195(< 0.001)

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significantly higher rates of unemployment, poverty and Medicaid usage, and remained an cumulative inequality on socioeconomic wellbeing. Our study also found a significant positive indirect association between poor health status in childhood and depressive symptoms in midlate life, which was mediated by mid-late poor health status. Though inconsistent with our initial hypothesis of a direct association, the indirect effects can be explained by poor childhood health condition developing over time into chronic diseases later on in life, which is strongly associated with depressive symptoms. At the same time, it is worth noting that poor health status in midlate life has the largest total effect on depressive symptoms. A large body of empirical evidence have consistently reported that chronic illnesses, pain, and disability significantly influence psychosocial wellbeing and increase risks of depression (Katon and Sullivan, 1990; Moussavi et al., 2007). In our study, we found poor SES in mid-late life had a positive association with poor health status, which in turn was positively associated with depressive symptoms. In general, socioeconomic status has broad implications regarding people's lives, including access to health resource, social support, opportunity for success, likelihood of encountering multiple adversities and capacity of coping with stressful life events (Nurius et al., 2017). Socioeconomically disadvantaged groups have fewer material resources to buffer or deal with life stressors and are more likely to suffer from physical or psychological problems as a result.

Limitations This study has several limitations that should be noted. First, as cross-sectional data, the wave 4 of CHARLS was collected retrospectively, which may introduce recall bias. Second, due to the data availability, our study only included adverse events in childhood, but not during adolescence, which is equally important. Third, the latent variables constructed from available data may be limited in capturing the full dimensionality and interconnectedness of the constructs. Finally, it is worth noting that some children with a history of adverse events may have passed away from other complications before reaching the age of 45, which may cause selection bias. Declarations of interest None. Contributors Fan Tian was involved in extracting data, doing data synthesis, interpreting results, and writing article. Steven Siyao Meng was involved in interpreting results and revising the article. Peiyuan Qiu assisted with data synthesis, results interpretation, and article drafting and revising. All authors approved the final submitted version. Funding source

4.1. Limitations

This study was funded by China Medical Board (no.14-198).

This study has several limitations that should be noted. First, as cross-sectional data, the wave 4 of CHARLS was collected retrospectively, which may introduce recall bias. Second, due to the data availability, our study only included adverse events in childhood, but not during adolescence, which is equally important. Third, the latent variables constructed from available data may be limited in capturing the full dimensionality and interconnectedness of the constructs. Fourth, considering all the data were self-reported by respondents, it inevitably introduced reporting bias since depressed respondents were more likely to report negative events and some indicators like self-reported health may be biased. Finally, it is worth noting that some children with a history of adverse events may have passed away from other complications before reaching the age of 45, which may cause selection bias.

Acknowledgments The data used in this paper are from China Health and Retirement Longitudinal Study (CHARLS), funded by the National Institute on Aging (NIA)in the USA (grant nos. 1-R21-AG031372-01, 1-R21AG033675-01-A1, 1-R01-AG037031-01, and 1-R01-AG037031-03S1), the National Natural Science Foundation of China (grant nos. 70773002, 70910107022, and 71130002), and the World Bank (grant no. 7159234). Financial support from the China Medical Board (no. 14198) is also acknowledged. References Anderson, N.B., Armstead, C.A., 1995. Toward understanding the association of socioeconomic status and health: A new challenge for the biopsychosocial approach. Psychosom. Med. 57, 213. Andresen, E.M., Malmgren, J.A., Carter, W.B., Patrick, D.L., 1994. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale). Am. J. Prev. Med. 10, 77. Asparouhov, T., Muthén, B.O., 2010. Weighted least squares estimation with missing data. Mplustechnical Append. retrieved from http://www.statmodel.com/download/ GstrucMissingRevision.pdf. Bartholomew, D.J., Steele, F., Moustaki, I., Galbraith, J.I., 2002. The Analysis and Interpretation of Multivariate Data For Social Scientists. Chapman & Hall/CRC. Betts, K., 2014. Early Life Course Determinants of Psychopathology. Post-traumatic Stress Disord. Blazer, D.G., 2003. Depression in late life: Review and commentary. J. Gerontol. Med. Sci. 58A, 249–265. Chapman, D.P., Whitfield, C.L., Felitti, V.J., Dube, S.R., Edwards, V.J., Anda, R.F., 2004. Adverse childhood experiences and the risk of depressive disorders in adulthood. J. Affect. Disord. 82, 217–225. Colman, I., Ataullahjan, A., 2010. Life course perspectives on the epidemiology of depression. Can. J. Psychiatry 55, 622–632. Ensminger, M.E., Hanson, S.G., Riley, A.W., Juon, H.S., 2003. Maternal psychological distress: adult sons’ and daughters’ mental health and educational attainment. J. Am. Acad. Child Adolesc. Psychiatry 42, 1108–1115. Ferraro, K.F., Shippee, T.P., 2009. Aging and cumulative inequality: how does inequality get under the skin? Gerontologist 49, 333–343. Gateway, C.W.I., 2015. Acts of omission: An overview of child neglect. Child Welf. Inf. Gatew. Gertner, A., Domino, M., Dow, W., 2017. Risk factors for late-life depression and correlates of antidepressant use in Costa Rica: Results from a nationally-representative longitudinal survey of older adults. J. Affect. Disord. 208, 338–344. Gilman, S.E., Kawachi, I., Fitzmaurice, G.M., Buka, L., 2003. Socio-economic status,

5. Conclusions This study explored multiple pathways from five aspects of childhood adversities including parental mental health problems, poor health status, child neglect and abuse, low SES, and lack of friends to depressive symptoms in mid-late life among Chinese population. The results revealed that all the five factors were directly or indirectly associated with mid-late life depressive symptoms. From the life course perspective, childhood adversities unlikely exist in isolation but interconnect with each other, jointly influencing the depressive symptoms in mid-late life. Meanwhile, early inequality could develop along multiple axes and finally diffuse to some life domains in later life such as health status and SES. These findings are crucial for the development of integrated practices and deployment of available resources to prevent childhood adversities, subsequently reducing the prevalence of depression. Improvements in legislation, governmental or non-governmental social services and health care services are necessary to reduce the long-term burden of adverse childhood events. Moreover, some aspects of childhood adversities indirectly associated depressive symptoms through intermediary problems such as poor health status and low SES in mid-late life, which suggests that early intervention and resource mobilization can circumvent some of the long-term mental health consequences. 677

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