Parents’ son preference, childhood adverse experience and mental health in old age: Evidence from China

Child Abuse & Neglect 93 (2019) 249–262

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Parents’ son preference, childhood adverse experience and mental health in old age: Evidence from China Qing Wanga, John A. Rizzob, Hai Fangc, a b c

T

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Shandong Multicenter Research Platform for Health Care Big Data, School of Public Health, Shandong University, Jinan, Shandong, 250012, China Department of Preventive Medicine, State University of New York at Stony Brook, Stony Brook, NY 11790, USA China Center for Health Development Studies, Peking University, 38 Xueyuan Road, Beijing, 100083, China

A R T IC LE I N F O

ABS TRA CT

Keywords: Mental health Son preference Adverse childhood experience China

Background: Son preference is an enduring phenomenon in China and may often be related to childhood adverse experiences. According to a life-course perspective, adverse experiences during a childhood period may have a long-term effect on mental health in later age. However, little is known about this relationship between parents’ son preference, childhood adverse experiences and adulthood mental health in China. Objective: The study aims to evaluate the association of parents’ son preference and individual mental health in old age in China. The mediating role of childhood adverse experiences was also estimated. Participants and setting: The China Health and Retirement Longitudinal Study (CHARLS) 2015 combined with CHARLS life history survey was analyzed (N = 11,666). Methods: Mental health was measured by a shortened modification of the Center for Epidemiologic Studies Depression scale including seven items, and higher scores indicated worse mental health status. A four-step mediating model was applied. Results: Respondents growing in families with son preference had on average 0.75 (P < 0.001) points higher on the mental health scale than their counterparts, and the effects were consistent for both males and females. Childhood adverse experiences measured by physical maltreatment, emotional adverse experiences and witnesses of inter-parent violence mediated the relationship between parents’ son preference and individual adulthood mental health by 47.87%. For females, physical maltreatment and emotional adverse experiences explained the most parts of health effects of parents’ son preference, whereas witnesses of inter-parent violence was the most influential mediator for males. Conclusion: Parents’ son preference led to adverse childhood experiences, which influenced mental health in adulthood.

1. Introduction Son preference refers to an enduring phenomenon that a family prefers for sons (Das Gupta et al., 2003). Sons are more valued than daughters in the eyes of parents with son preference (Festini & De, 2004). Thus, parents with son preference may unfairly allocate their scarce time, energy, and resources by investing more in sons in comparison with daughters (Das Gupta et al., 2003; Echávarri & Husillos, 2016; Kugler & Kumar, 2017). Son preference exists in many countries, particularly in Asia, the Middle East and

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Corresponding author. E-mail address: [email protected] (H. Fang).

https://doi.org/10.1016/j.chiabu.2019.05.012 Received 3 July 2018; Received in revised form 16 February 2019; Accepted 16 May 2019 Available online 23 May 2019 0145-2134/ © 2019 Published by Elsevier Ltd.

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North Africa (Koolwal, 2007; Lin, Liu, & Qian, 2014; Oster, 2009; Rohlfs, Reed, & Yamada, 2010; Rossi & Rouanet, 2015). China has manifested preference for sons and discrimination against daughters for centuries (Das Gupta et al., 2003). Such behavior stems primarily from a patriarchal kin-ship system in which men continue the family name, receive the family inheritance and are responsible for ancestor worship, and is often aggravated by risky economic and social environments—sons offer financial supports to aged parents; in the past, they were also needed to carry out farm work (Das Gupta et al., 2003). Empirical studies utilized both objective and subjective measures to indicate son preference of parents. Behavioral/objective measures, for example, the time of breast-feeding (Graham, Larsen, & Xu, 1998); mothers’ use of health care (Chen, Xie, & Liu, 2007) were applied in previous literatures, while most of the recent literatures chose subjective measures, for example, the ideal proportion of sons (Koolwal, 2007; Lin & Adserà, 2013; Lin, 2009); a self-reported variable whether or not their parents had a preference for sons (Das Gupta et al., 2003; Echávarri & Husillos, 2016; Kugler & Kumar, 2017); a respondent’s willingness to bear another sibling and noted how the response differed by the sex of existing children (Clark, 2000). It is well-understood that parents’ son preference does often result in childhood adverse experiences among daughters, particularly when family resources are constrained. Parents with a preference for sons constrain daughters’ opportunities, and more severely, maltreatment to daughters and sex-selective abortion occur along with son preference (Das Gupta et al., 2003; Kugler & Kumar, 2017; Echávarri & Husillos, 2016). However, it has been argued that Chinese parents may exert stricter physical disciplines on their sons than daughters in order to motivate their sons to achieve greater academic, social, and moral attainments, as sons are better qualified to carry the family name and to provide financial supports to their aged parents (Wong et al., 2009). Corporal punishments by parents are found to be more frequent among sons than daughters. Therefore, son preference may also possibly result in adverse experiences for sons (Tang, 2006). It has been well-established that childhood adverse experiences, especially childhood maltreatment is associated with poor health outcomes at later age, such as depressive or anxiety problems, poor physical health-related indices, and socially-unacceptable behavior (Bellis et al., 2014; Bentley, 2012; Cicchetti, 2013; Fox, Perez, Cass, Baglivio, & Epps, 2015; Mersky, Topitzes, & Reynolds, 2013; Sareen et al., 2013; Schulz et al., 2017; Widom, Czaja, Kozakowski, & Chauhan, 2017). Similar associations are also found in countries with high tolerant levels for childhood adverse experiences and high preference for sons, including China, Philippine, Saudi Arabia, Korea (Almuneef, Qayad, Aleissa, & Albuhairan, 2014; Chen & Dunne, 2006; Kim, 2017; Lau, Chan, Lam, Choi, & Lai, 2003; Ramiro, Madrid, & Brown, 2010; Tang, 2006; Wong et al., 2009). The resulting health issues include substance abuse, suicide, poorer physical health, and/or depression. Given the consistent pairwise association of parents’ son preference, childhood adverse experiences and adulthood health, it is reasonable to believe that parents’ son preference affects individual mental health in older age and childhood adverse experiences within families is a mediator of this relationship between the two factors. However, empirical studies are scarce about it. Thus, using a nationally representative data in China, this study aims to estimate the relationship between son preference and adulthood mental health as well as the role of childhood adverse experiences. Considering the potential gender heterogeneity resulting from son preference, our analysis will also be stratified by males and females. By pointing out the adverse side of son preference, we suggest some ways to cultivate supporting environment so that the negative effects of son preference on life-cycle mental health are diminished and the development of children and their mental health at later age is improved. 2. Methods 2.1. Data This study uses data from the China Health and Retirement Longitudinal Study (CHARLS) 2015 combined with CHARLS life history survey, which is similar to the Health and Retirement Study in the U.S (Zhao, Hu, Smith, Strauss, & Yang, 2014). The CHARLS is a nationally representative sample of people aged 45 years old and above using stratified four-stage cluster sampling. In the first stage, 150 county-level units (rural counties and urban districts) were randomly selected from a sampling frame containing all county-level units in China, but excluded those in Tibet, in proportion to their population sizes (PPS). Within each county-level unit, three primary sampling units (PSUs) (administrative villages in rural areas or neighborhoods in urban areas) were randomly selected by PPS. Within each PSU, 24 households with members aged 45 years old and above were randomly selected. The member, aged 45 years old and above, and his or her spouse (if present) were interviewed face-to-face in each household. The Institutional Review Board at Peking University approved the survey. The first CHARLS national wide data were collected in 2011 and were followed every two years. The CHARLS 2015 was the third (latest) wave, which covered an extensive range of information, such as demographic characteristics, socioeconomic status, health status, insurance, and health care utilization. The life history sample surveyed in 2014 included family information, health history, wealth history, work history and education history of all live respondents in the first two waves. Based on individual ID, 12,880 respondents in the CHARLS 2015 were matched with the life history sample. After we excluded 1,214 respondents with missing values of mental health measures and son preferences, there were 11,666 respondents available for statistical analyses. 2.2. Data analytic procedures Descriptive statistics including percentages for categorical variables and means with standard deviations for continuous variables in the entire sample and by gender and son preference were reported. We hypothesized that the association between parents’ son preference and individual adulthood mental health was mediated by 250

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Fig. 1. (A) Direct relationship between son preference and adulthood mental health (B) Relationship between son preference and adulthood mental health mediated by childhood adverse experiences.

childhood adverse experiences in the family, and was examined using a four-step regression approach summarized in Fig. 1 (Cerin & Mackinnon, 2009). The four-step method tested a direct path between son preference and adulthood mental health, and then examined how much this association was reduced by adjusting for childhood adverse experiences. To be specific, step 1: an Ordinary Least Square (OLS) model was applied to test whether parents’ son preference significantly influenced individual adulthood mental health in the absence of childhood adverse experiences and explain the extent to which parents’ son preferences influence mental health in older age (see (c) in Fig. 1) (Lei, Sun, Strauss, Zhang, & Zhao, 2014). Mental health as the dependent variable in the regression was measured by a shortened modification of the Center for Epidemiologic Studies Depression (CES-D) scale including seven items. The seven items were evaluated as follows: (1) “was bothered by things,” (2) “had trouble keeping mind on tasks,” (3) “felt depressed,” (4) “felt everything he/she did was an effort,” (5) “felt fearful,” (6) “restless sleep,” and (7) “felt lonely.” Their frequencies in experiencing such symptoms in the previous week before the survey were encoded from 1 to 4: 1 = none or rarely; 2 = some or little; 3 = occasionally or a moderate amount; and 4 = most or all of the time, with summed scores ranging from 7-28. Higher scores indicate more depressive disorders and therefore worse mental health. The validity and reliability of this shortened CES-D scale had been proved in China (Lam, Tse, Gandek, & Fong, 2005; Lee, 2009). In our study sample, CES-D was also demonstrated to have high internal consistency (Cronbach’s alpha = 0.78) and validity (Kaiser–Meyer– Olkin = 0.86). If the Cronbach’s alpha and Kaiser–Meyer–Olkin test values exceed the recommended level of 0.70, data are often considered to be highly reliable (Koh et al., 2006). Our key independent variable was parents’ son preference, based on the question “Did your guardian prefer boys to girls?” If the answer was very much or somewhat, it was coded as 1, otherwise, 0. Following Lei et al. (2014), an OLS model was applied. Step 2: since childhood adverse experiences were measured by binary variables, Logistic models were used to test if parents’ son preference significantly affected childhood adverse experiences (see (a) in Fig. 1). The dependent variable was childhood adverse experiences within families including 3 binary indicators: physical maltreatment, adverse emotional experiences, and witnesses of inter-parental violence during childhood. A history of exposure to physical maltreatment was obtained in response to the following question: “When you were growing up, did your guardian ever hit you? Was that often, sometimes, rarely, or never?” A response of often or sometimes was defined as physical maltreatment. Following the rule of Chapman et al. (2004), respondents had emotionally adverse experiences in the childhood family environments if they responded 3 or 4 to either of the following questions: “How would you rate your relationship with your female/ male guardian when you were growing up? 1. very good, 2. good, 3. fair, 4. poor”; “How much love and affection did your female guardian give you? 1. often, 2. sometimes, 3. rarely; 4. never”; “How much effort did your female guardian put into watching over you? 1. a lot, 2. some, 3. a little, 4. none”; “How strict was your female/male guardian with the rules for you? 1. not at all strict; 2. a little strict; 3. somewhat strict; 4. very strict”; “Did your female/male guardian treat your siblings better than you? 1. not at all; 2. a little; 3. somewhat; 4. very”. Witness of inter-parental violence was based on the CHARLS questions “When you were growing up, did your parents often beat up each other? Was that often, sometimes, rarely, or never?” A respondent was considered to witness inter-parental violence if his or her answers were “sometimes” or “more often”. Step 3: childhood adverse experiences had a significant unique effect on adulthood mental health using the OLS model (see (b) in Fig. 1). In this step, the continuous variable of adulthood mental health was the dependent variable with childhood adverse experiences as the key independent variable. Step 4: the effect of parents’ son preference on adulthood mental health shrank upon the addition of childhood adverse experiences to the OLS model of the first step (see (cc’) in Fig. 1). The measures of parents’ son preference on adulthood mental health were similar to those in step 1. Demographic, adulthood and childhood socioeconomic measures were controlled in all the models (a, b, c and cc'). Demographic variables included two binary variables of gender (reference group: female), marital status (reference group: married with spouse present (common-law marriage was considered married); unmarried includes single, divorced, and separate), and a continuous variable of age. Adulthood socioeconomic status was measured by two categorical variables including occupations, and educational attainments (Cohen, Janickideverts, Chen, & Matthews, 2010). On the base of self-reported job descriptions, occupations were classified into four categories: professionals and managers, farmers and manual workers, self-employed, and the non-employed, with the non-employed as the reference group (Chen et al., 2015). Educational attainments were constructed to measure general or vocational education, which was categorized into four levels: no formal education, primary school, junior high school, and senior high school and above, 251

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with no formal education serving as the reference group. Childhood socioeconomic status was captured by two category variables, which were parent’s education and household financial status during their childhood period. Both the father and mother’s educational attainments were categorized into three levels: illiterate, elementary school, and high school or above. In addition, respondents were asked to classify household financial status before his or her 17 years old into 3 categories: worse than others, same as others, and better than others. Odd ratios and 95% confidence intervals (CI) were reported for Logistic estimation. Coefficients and 95% CI were reported for OLS estimation. Separate models were run by gender. All regression models were weighted using sample weights to correct for the multistage stratified sampling design and non-response issue. The weights were proportional to the inverse-probability of participation at the individual level to enhance generalizability to the source population. This study mainly measured mental health on a continuous basis rather than a threshold dichotomously distinguishing “good” from “poor” for the following two reasons. First, it was hard to define the optimal threshold-point separating good from poor mental health in self-reported responses (Cole & Tembo, 2011). Second, it was more reasonable to evaluate the functional impairment of mental health using symptom burdens instead of a cut-off point between good and poor (Rucci et al., 2003). A dimensional scale provided information to accurately describe common mental disorders, specifically in China, where people preferred to accept the somatic disorder associated with depression instead of psychological sickness (Kleinman, Goldman, Snow, & Korol, 2010). In addition, as a robust check, mental health on a threshold basis was also analyzed. A categorical variable for CES-D was created based on a usual cut-off point of 12 (Rucci et al., 2003). The variable equaled 1 if CES-D was higher than 12, and 0 otherwise, and then a Logistic model was used. Furthermore, an alternative measure of emotionally adverse experiences was constructed as a robust check. A summed score of the items on emotionally adverse experiences was calculated to measure emotionally adverse experiences, with lower scores indicating fewer emotionally adverse experiences in childhood. The results for the main results and robust check results were very consistent. Due to the space limitation, results as robust check were not included in the paper and could be requested from authors. Mediation statistics, including the indirect effect and total effect, were obtained using a modified version of the user-written STATA “binary_mediation’’ command, and bias-adjusted 95% CIs were derived using bootstrapping methods. Statistical analyses were performed using STATA 14.0. 3. Results Table 1 shows the descriptive statistics for the entire study sample and by gender and son preference status. The average age of the respondents was 61 (std. dev. 9.30) and 49 percent were male, with the majority being married (88 percent). Over 35 percent had high school education or above, and 16 percent of occupations were professionals and managers. As for childhood socioeconomic status, a majority of their parents were illiterate (58 percent for fathers; 88 percent for mothers); 39 percent considered their household financial status during their childhood period as “better than others”. The mean of mental scores was 12 (std. dev. 5.07). 11 percent experienced son preference during their childhood period and 29 percent experienced physical maltreatment, 35 percent experienced emotional maltreatment, and 9 percent witnessed inter-parents violence. For respondents exposed to son preference, the ratio of having adverse childhood experiences and ill mental health status was higher than those reporting that parents didn’t have son preference. Table 2 shows the association of parents’ son preference and individual adulthood mental health by OLS estimation. Respondents growing in families with son preference had on average 0.75 points higher on the CES-D scale than their counterparts (P < 0.001). The results by males and females were similar. Both males and females growing up with parents having son preference were associated with poor adulthood mental health (males: 0.81, P-value < 0.001; females: 0.69, P-value < 0.001). Table 3 presents the association of adverse childhood experiences and adulthood mental health. When only one type of adverse childhood experiences was included, respondents exposed to physical maltreatment, emotional maltreatment and witnesses of interparents violence in their childhood had on average 0.86 (P < 0.001), 0.62 (P < 0.001) and 1.22 (P < 0.001) points higher on the CES-D scale than their counterparts, respectively. As the three types of adverse childhood experiences were controlled simultaneously, physical maltreatment, emotional maltreatment and witnesses of inter-parents violence increased the CES-D scale by 0.71 (P < 0.001), 0.45 (P < 0.001), and 0.91 (P < 0.001). The adulthood mental health effects of adverse childhood experiences stratified by gender were consistent with the results from the entire study sample. Table 4 shows the association of parents’ son preference and adverse childhood experience measured by physical maltreatment, emotional maltreatment and witnesses of inter-parents violence. Parents’ son preference increased the likelihood of physical maltreatment, emotional maltreatment and inter-parents violence by 281% (P < 0.001), 330% (P < 0.001) and 322% (P < 0.001). For both males and females, parents’ son preference was positively related to physical maltreatment, emotional maltreatment and witnesses of inter-parents violence. Table 5 shows the association of parents’ son preference and individual adulthood mental health adjusting for adverse childhood experiences. The effects were consistent but smaller than the effects without controlling for adverse childhood experiences for the entire sample, female and male samples. Table 6 presents the indirect effect of childhood adverse experiences from parents’ son preference to individual adulthood mental health. Proportions of total effects mediated by adverse childhood experience were 47.87 percent, 58.69 percent and 33.38 percent for all the respondents, female and male samples, respectively. Among the adverse childhood experiences, physical maltreatment played the most important role for the entire sample and females (1.6 percent /3.5 percent = 46.26 percent, P < 0.001), while, for 252

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Table 1 Descriptive statistics. All (N = 11666)

Female

Male

Growing in a family without son preference (N = 5,162)

Growing in a family with son preference (N = 821)

Growing in a family without son preference (N = 5269)

Growing in a family with son preference (N = 414)

Mental health score (mean/std.dev.)

12.27 (5.07)

13.13 (5.29)

13.87 (5.62)

11.21 (4.53)

11.86 (4.86)

Son preference (%) No Yes

89.41 10.59

100 0

0 100

100 0

0 100

80.37 19.63

54.20 45.80

66.79 33.21

54.35 45.65

70.90 29.10

36.55 63.45

64.30 35.70

48.56 51.44

92.68 7.32

79.39 20.61

92.46 7.54

83.68 16.32

23.26 19.00 23.09 34.65

35.34 20.30 19.37 24.99

34.10 18.39 17.90 29.60

10.93 18.14 27.39 43.54

8.21 14.73 25.12 51.93

27.76 45.33

32.58 49.03

35.81 41.41

21.92 43.08

25.83 35.51

10.48 16.43

8.16 10.23

10.48 12.30

12.41 22.58

14.98 23.67

60.89(9.30)

60.09(9.46)

59.73(9.22)

61.77(9.03)

62.14(9.66)

Gender (%) Female Male

51.29 48.71

100 0

100 0

0 100

0 100

Marital status (%) Married Unmarried

87.52 12.48

84.41 15.59

85.38 14.62

90.68 9.32

90.34 9.66

Childhood socioeconomic status Father education (%) Illiterate 58.25 Primary school 21.15 High school and above 20.60

59.09 19.35 21.56

52.57 21.07 26.43

58.49 22.66 18.85

56.28 24.40 19.32

Mother education (%) Illiterate Primary school High school and above

88.17 5.46 6.37

86.36 5.72 7.92

88.61 5.45 5.94

88.16 5.56 6.28

37.04 53.45 9.51

42.38 44.95 12.67

40.48 52.02 7.50

36.72 50.48 12.80

Childhood maltreatment (%) Physical maltreatment No 71.47 Yes 28.53 Emotional adverse experience No 64.71 Yes 35.29 Witness of inter-parental violence No 91.28 Yes 8.72 Socioeconomic status Education (%) No formal education Primary school Junior high school Senior High school and above Occupation (%) Non-employed Farmers or manual workers Self-employed Professionals and managers Age (mean/std.dev.)

88.24 5.48 6.28

Financial situation before age 17 (%) Worse off than others 38.96 Same as them 52.10 Better off than others 8.94

males, witnesses of inter-parents violence were the most important factor to explain the effect of son preference on mental health status in older age (0.8 percent/1.7 percent = 44.84 percent, P < 0.001). 4. Discussion Using a nationally representative data, this study applied a four-step model to estimate the association of parents’ son preference, adverse childhood experiences, and individual adulthood mental health. As expected, we found a positive association of son preference and poor adulthood mental health status, after controlling for a variety of demographics, family background, and other 253

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Table 2 Association of son preference and adulthood mental health by OLS. VARIABLES

Son preference No Yes Demographic Age Gender Female Male Marital status Unmarried Married Education No formal education Primary school Junior high school Senior high school and above Occupation Non-employed Farmers or manual workers Self-employed Professionals and managers Father education Illiterate Primary school High school and above Mother education Illiterate Primary school High school and above Financial situation before age 17 Worse off than others Same as them Better off than others

All Coef (Std.error)

Female Coef (Std.error)

Male Coef (Std.error)

Reference 0.747*** (0.175)

Reference 0.691*** (0.226)

Reference 0.806*** (0.267)

−1.168*** (0.407)

−1.227** (0.593)

−1.072** (0.544)

Reference −1.046*** (0.173)

Reference −0.980*** (0.233)

Reference −1.211*** (0.262)

Reference −0.110 (0.179) −0.519*** (0.172) −1.316*** (0.173)

Reference −0.191 (0.235) −0.406* (0.233) −1.505*** (0.237)

Reference 0.173 (0.282) −0.362 (0.264) −0.967*** (0.263)

Reference 0.360*** (0.134) −0.129 (0.195) −0.872*** (0.177)

Reference 0.562*** (0.181) −0.055 (0.301) −0.831*** (0.321)

Reference 0.098 (0.199) −0.255 (0.257) −0.974*** (0.220)

Reference −0.036 (0.130) 0.001 (0.153)

Reference −0.170 (0.197) 0.149 (0.232)

Reference 0.040 (0.167) −0.144 (0.178)

Reference 0.182 (0.265) −0.122 (0.214)

Reference −0.154 (0.390) −0.022 (0.322)

Reference 0.465 (0.328) −0.209 (0.264)

Reference −1.032*** (0.112) −1.444*** (0.184)

Reference −1.400*** (0.170) −1.730*** (0.280)

Reference −0.691*** (0.142) −1.147*** (0.226)

Reference 1.369*** (0.114)

Robust standard errors in parentheses. *** p < 0.01. ** p < 0.05. * p < 0.1.

characteristics. Parents’ son preference did not only result in adulthood ill mental health status for females, but also had a negative influence for male mental health at later age. Furthermore, the four-step model showed that childhood adverse experiences mediated the relationship between parents’ son preference and adulthood mental health status. Childhood experiences mediated 48 percent of son preference effects on adulthood mental health. Physical and emotional maltreatment explained the majority of indirect effects of adverse childhood experiences on the association between son preference and mental health in adulthood for females, whereas witnesses of inter-parent violence mediated the biggest part of this association for males. The negative influence of parents’ son preference on sons might be side effects 254

255

Father education Illiterate Primary school

Professionals and managers

Self-employed

Occupation Non-employed Farmers or manual workers

Senior high school and above

Junior high school

Education No formal education Primary school

Marital status Unmarried Married

Gender Female Male

Demographic Age

Witness of inter-parental violence No Yes

Emotional adverse experience No Yes

Childhood adverse experience Physical maltreatment No Yes

VARIABLES

Reference −0.034

Reference 0.331** (0.134) −0.140 (0.200) −0.894*** (0.177)

Reference −0.132 (0.179) −0.553*** (0.172) −1.337*** (0.173)

Reference −1.023*** (0.174)

Reference 1.511*** (0.114)

−0.933** (0.408)

Reference 0.863*** (0.118)

Reference −0.071

Reference 0.343*** (0.132) −0.124 (0.193) −0.881*** (0.175)

Reference −0.150 (0.179) −0.538*** (0.171) −1.334*** (0.172)

Reference −1.077*** (0.174)

Reference 1.453*** (0.113)

−1.031** (0.405)

Reference 0.623*** (0.109)

Reference −0.059

Reference 0.278** (0.140) −0.169 (0.202) −0.959*** (0.183)

Reference −0.152 (0.189) −0.512*** (0.183) −1.336*** (0.182)

Reference −1.030*** (0.185)

Reference 1.326*** (0.119)

−1.055** (0.423)

Reference 1.222*** (0.195)

Reference −0.077

Reference 0.296** (0.140) −0.172 (0.203) −0.967*** (0.181)

Reference −0.153 (0.188) −0.529*** (0.180) −1.341*** (0.180)

Reference −1.021*** (0.184)

Reference 1.412*** (0.118)

−0.945** (0.421)

Reference 0.914*** (0.198)

Reference 0.450*** (0.113)

Reference 0.713*** (0.125)

Coef (Std.error)

Reference −0.160

Reference 0.546*** (0.179) −0.075 (0.300) −0.841*** (0.312)

Reference −0.183 (0.235) −0.457** (0.232) −1.504*** (0.236)

Reference −0.975*** (0.234)

−0.943 (0.581)

Reference 1.067*** (0.187)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Female

All

Table 3 Association of childhood adverse experiences and adulthood mental health by OLS.

Reference −0.187

Reference 0.546*** (0.180) −0.065 (0.300) −0.840*** (0.316)

Reference −0.214 (0.235) −0.432* (0.232) −1.512*** (0.237)

Reference −1.054*** (0.234)

−1.070* (0.592)

Reference 0.576*** (0.165)

Coef (Std.error)

Reference −0.157

Reference 0.501*** (0.186) −0.168 (0.310) −0.888*** (0.327)

Reference −0.272 (0.246) −0.370 (0.247) −1.476*** (0.246)

Reference −0.958*** (0.247)

−1.073* (0.613)

Reference 1.072*** (0.280)

Coef (Std.error)

Reference −0.166

Reference 0.519*** (0.186) −0.190 (0.310) −0.894*** (0.316)

Reference −0.244 (0.245) −0.413* (0.241) −1.496*** (0.244)

Reference −0.959*** (0.247)

−1.006* (0.603)

Reference 0.710** (0.288)

Reference 0.371** (0.171)

Reference 0.953*** (0.200)

Coef (Std.error)

Reference 0.038

Reference 0.060 (0.203) −0.263 (0.267) −1.006*** (0.225)

Reference 0.107 (0.284) −0.406 (0.268) −1.027*** (0.266)

Reference −1.166*** (0.264)

−0.907 (0.558)

Reference 0.700*** (0.146)

Coef (Std.error)

Male

Reference −0.009

Reference 0.083 (0.195) −0.242 (0.251) −0.984*** (0.216)

Reference 0.109 (0.282) −0.383 (0.264) −1.006*** (0.262)

Reference −1.173*** (0.261)

−0.979* (0.538)

Reference 0.662*** (0.137)

Coef (Std.error)

Reference −0.039

Reference 0.014 (0.211) −0.233 (0.270) −1.085*** (0.232)

Reference 0.105 (0.306) −0.421 (0.287) −1.052*** (0.284)

Reference −1.204*** (0.278)

−0.863 (0.567)

Reference 1.092*** (0.263)

Reference 0.503*** (0.144)

Reference 0.528*** (0.153)

Coef (Std.error)

(continued on next page)

Reference −0.015

Reference −0.008 (0.210) −0.247 (0.270) −1.082*** (0.230)

Reference 0.138 (0.305) −0.425 (0.287) −1.059*** (0.283)

Reference −1.216*** (0.279)

−1.033* (0.565)

Reference 1.358*** (0.262)

Coef (Std.error)

Q. Wang, et al.

Child Abuse & Neglect 93 (2019) 249–262

Reference −0.987*** (0.111) −1.347*** (0.180)

Financial situation before age 17 Worse off then others Reference Same as them −0.957*** (0.113) Better off than others −1.371*** (0.180)

Robust standard errors in parentheses. *** p < 0.01. ** p < 0.05. * p < 0.1.

High school and above

Reference 0.151 (0.252) −0.142 (0.212) Reference −0.998*** (0.118) −1.363*** (0.190)

Reference 0.255 (0.270) −0.062 (0.217) Reference −0.932*** (0.118) −1.325*** (0.185)

Reference 0.230 (0.261) −0.102 (0.214)

(0.134) −0.067 (0.154)

Reference −1.301*** (0.170) −1.663*** (0.271)

Reference −0.180 (0.366) −0.052 (0.319)

(0.197) 0.166 (0.229)

(0.130) −0.028 (0.152)

(0.131) −0.001 (0.152)

(0.135) −0.058 (0.156)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Female

All

Reference 0.206 (0.262) −0.128 (0.212)

Mother education Illiterate Primary school

High school and above

VARIABLES

Table 3 (continued)

Reference −1.349*** (0.170) −1.649*** (0.274)

Reference −0.197 (0.376) −0.046 (0.319)

(0.198) 0.127 (0.230)

Coef (Std.error)

Reference −1.346*** (0.178) −1.589*** (0.288)

Reference −0.093 (0.399) −0.002 (0.325)

(0.204) 0.154 (0.236)

Coef (Std.error)

Reference −1.257*** (0.177) −1.548*** (0.278)

Reference −0.136 (0.373) −0.057 (0.323)

(0.203) 0.153 (0.233)

Coef (Std.error)

Reference −0.631*** (0.144) −1.062*** (0.228)

Reference 0.524 (0.334) −0.200 (0.262)

(0.170) −0.165 (0.177)

Coef (Std.error)

Male

Reference −0.649*** (0.140) −1.026*** (0.227)

Reference 0.442 (0.309) −0.225 (0.261)

(0.166) −0.180 (0.176)

Coef (Std.error)

Reference −0.680*** (0.149) −1.165*** (0.234)

Reference 0.533 (0.331) −0.102 (0.266)

(0.173) −0.280 (0.180)

Coef (Std.error)

Reference −0.641*** (0.150) −1.126*** (0.232)

Reference 0.515 (0.322) −0.123 (0.264)

(0.173) −0.293 (0.180)

Coef (Std.error)

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Table 4 Association of son preference and childhood adverse experiences by Logistic model. VARIABLES

Son preference No Yes

Demographic Age

Gender Female Male

Marital status Unmarried Married

Education No formal education Primary school

Junior high school

Senior high school and above Occupation Non-employed Farmers or manual workers Self-employed

Professionals and managers Father education Illiterate Primary school

High school and above Mother education Illiterate Primary school

High school and above

All

Female

Male

PM OR (95%CI)

EAE OR (95%CI)

WIV OR (95%CI)

PM OR (95%CI)

EAE OR (95%CI)

WIV OR (95%CI)

PM OR (95%CI)

EAE OR (95%CI)

WIV OR (95%CI)

Reference 2.813*** (2.411 3.282)

Reference 3.299*** (2.838 3.835)

Reference 3.224*** (2.672 3.890)

Reference 3.457*** (2.848 4.197)

Reference 4.270*** (3.538 5.153)

Reference 3.344*** (2.635 4.243)

Reference 1.931*** (1.533 2.431)

Reference 1.992*** (1.585 2.504)

Reference 2.994*** (2.186 4.102)

0.502*** (0.327 0.770)

0.538*** (0.371 0.780)

1.120 (0.619 2.028)

0.463*** (0.269 0.796)

0.735 (0.453 1.192)

0.949 (0.430 2.094)

0.552* (0.282 1.082)

0.366*** (0.207 0.645)

1.364 (0.552 3.370)

Reference 0.576*** (0.514 0.645)

Reference 0.811*** (0.729 0.903)

Reference 1.085 (0.910 1.294)

Reference 0.893 (0.769 1.037) (0.327 0.770)

Reference 1.078 (0.937 1.241) (0.371 0.780)

Reference 1.040 (0.818 1.322) (0.619 2.028)

Reference 0.941 (0.766 1.157) (0.269 0.796)

Reference 1.164 (0.967 1.401) (0.453 1.192)

Reference 0.962 (0.709 1.305) (0.430 2.094)

Reference 0.829* (0.665 1.032) (0.282 1.082)

Reference 1.029 (0.828 1.278) (0.207 0.645)

Reference 1.179 (0.785 1.769) (0.552 3.370)

Reference

Reference

Reference

Reference

Reference

Reference

Reference

Reference

Reference

1.076 (0.932 1.242) 1.207** (1.031 1.414) 1.079 (0.932 1.249)

1.094 (0.956 1.253) 0.978 (0.848 1.128) 0.940 (0.819 1.080)

1.007 (0.802 1.265) 1.004 (0.795 1.268) 0.988 (0.777 1.257)

0.955 (0.785 1.163) 1.151 (0.924 1.435) 1.073 (0.874 1.317)

0.938 (0.784 1.122) 0.993 (0.822 1.199) 1.023 (0.848 1.235)

1.115 (0.845 1.472) 1.087 (0.797 1.483) 1.020 (0.734 1.416)

1.269** (1.005 1.602) 1.322** (1.040 1.682) 1.164 (0.924 1.466)

1.316** (1.049 1.652) 0.979 (0.783 1.224) 0.902 (0.725 1.123)

0.850 (0.563 1.283) 0.896 (0.609 1.316) 0.899 (0.609 1.327)

Reference 1.032 (0.907 1.174) 1.137 (0.908 1.423) 1.052 (0.871 1.270)

Reference 0.965 (0.861 1.083) 1.126 (0.923 1.374) 1.030 (0.869 1.221)

Reference 1.365*** (1.123 1.659) 1.477*** (1.110 1.967) 1.455*** (1.111 1.905)

Reference 1.036 (0.879 1.222) 1.100 (0.825 1.467) 1.085 (0.796 1.479)

Reference 0.959 (0.830 1.109) 1.305* (0.992 1.717) 1.028 (0.787 1.342)

Reference 1.395*** (1.089 1.787) 1.652** (1.103 2.475) 1.230 (0.812 1.864)

Reference 1.025 (0.836 1.258) 1.172 (0.838 1.640) 1.045 (0.805 1.358)

Reference 0.981 (0.815 1.180) 1.013 (0.763 1.344) 1.014 (0.801 1.284)

Reference 1.368* (0.990 1.891) 1.349 (0.894 2.036) 1.642** (1.120 2.408)

Reference 1.003 (0.879 1.144) 1.036 (0.901 1.192)

Reference 1.201*** (1.061 1.360) 1.134* (0.993 1.295)

Reference 0.957 (0.784 1.169) 1.029 (0.836 1.268)

Reference 0.946 (0.783 1.144) 0.925 (0.752 1.137)

Reference 1.159* (0.978 1.373) 1.143 (0.950 1.374)

Reference 0.745* (0.555 1.001) 0.930 (0.706 1.226)

Reference 1.059 (0.887 1.265) 1.153 (0.956 1.389)

Reference 1.255*** (1.056 1.491) 1.130 (0.941 1.357)

Reference 1.228 (0.934 1.616) 1.214 (0.891 1.654)

Reference 0.924 (0.695 1.230) 1.143 (0.912 1.433)

Reference 1.335** (1.003 1.779) 1.183 (0.962 1.455)

Reference 0.947 (0.632 1.419) 0.900 (0.615 1.316)

Reference 1.049 (0.672 1.636) 1.223 (0.873 1.712)

Reference 1.381* (0.953 2.000) 1.261 (0.952 1.670)

Reference 0.790 (0.459 1.361) 0.901 (0.545 1.488)

Reference 0.830 (0.589 1.170) 1.061 (0.789 1.427)

Reference 1.264 (0.831 1.921) 1.086 (0.808 1.460)

Reference 1.046 (0.597 1.832) 0.861 (0.483 1.535)

Financial situation before age 17

(continued on next page) 257

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Table 4 (continued) VARIABLES

Worse off than others Same as them

Better off than others

All

Female

Male

PM OR (95%CI)

EAE OR (95%CI)

WIV OR (95%CI)

PM OR (95%CI)

EAE OR (95%CI)

WIV OR (95%CI)

PM OR (95%CI)

EAE OR (95%CI)

WIV OR (95%CI)

Reference

Reference

Reference

Reference

Reference

Reference

Reference

Reference

Reference

0.652*** (0.584 0.726) 0.771**

0.866*** (0.782 0.959) 0.838*

0.733*** (0.626 0.858) 0.526***

0.650*** (0.556 0.760) 0.775

0.775*** (0.672 0.895) 0.807

0.653*** (0.523 0.815) 0.351***

0.655*** (0.563 0.761) 0.776*

0.976 (0.848 1.123) 0.879

0.860 (0.684 1.082) 0.850

(0.628 0.946)

(0.697 1.007)

(0.372 0.743)

(0.571 1.052)

(0.625 1.042)

(0.232 0.531)

(0.596 1.012)

(0.681 1.136)

(0.513 1.410)

95% CI in parentheses. PM: Physical maltreatment. EAE: Emotional Adverse Experience. WIV: Witness of inter-parents violence. *** p < 0.01. ** p < 0.05. * p < 0.1.

such as maltreatment related to tough love, and witnesses of inter-parent violence due to educational ideology. This is the first study to quantify the relationship between parents’ son preference and adulthood ill mental health and the role of adverse childhood experiences in China. This study extended the analyses of son preference to a life-course influence. In addition, this study answered the question to what extent and how son preference is related to adulthood mental health in China. In addition, we stratified our analyses by gender. Our results not only supported the bad influence of parents’ son preference on females, but also brought the adverse impacts of parents’ son preference to males. Our findings shed light on the implementation of public policies to enhance individuals’ mental health. Mental health issues had been the most important health risks in China. China accounted for 17 percent of the global mental, neurological, and substance use disorder burden in 2013 (Charlson, Baxter, Cheng, Shidhaye, & Whiteford, 2016). Mental health profoundly influenced the elderly's quality of life and significantly increased their uses of health and social services (Dening & Barapatre, 2004; Unalan, Gocer, Basturk, Baydur, & Ozturk, 2015). Health policy and interventions were needed to avert this burden in China. The result that childhood adverse experiences affected adulthood mental health implied that policy interventions on mental health promotion should work throughout the entire life course, beginning from childhood. An integrated health policy is highly recommended to pursue the premise of maximizing health across the life course, especially in China where the likelihood of having adverse experiences in their childhood period is fairly high. Those growing with adverse experiences may be vulnerable to ill mental health, thus mental health intervention or policy should be tailored to focus on these people. In addition, mental health interventions should take effects to deal with son preference issues, which may also exert bad influence over children’s life-long mental health. According to CHARLS, 11 percent of responders’ parents have son preference. By removal of son preference, which is the negative factor of child development, life-cycle mental health could be improved significantly. Despite years of efforts, the prevalence of son preference is not altered by government controls such as caring for girls campaign and onechild-policy (Li & Cooney, 1993). Apart from culture-roots and population policies, the Chinese government may consider enhancing the welfare of old people in China since son preference may partly result from the concern that a girl moves out with her husband's family when she gets married and she thus cannot look after her own parents when they become old. Right now, many old people in Chinese rural areas don’t have pension or limited pension to make ends meet. There are some limitations in the study. First, we excluded 1,214 respondents with missing values. Among them, 1,086 respondents didn’t report one and more questions on mental health scores, and the rest of 128 respondents didn’t report if they were exposed to son preference during their childhood. Such deletion may potentially affect our analysis results. But the distribution of mental health in the study sample was similar to that in a review on depression symptoms in China, so the missing values might be random (Li, Xu, Nie, Zhang, & Wu, 2014). Second, our work on childhood status in CHARLS relied on a retrospective self-evaluation of household financial status for a respondent when he or she was a child up to 17 years old. This variable might be subjective. Selfreported childhood health status was potentially related to household financial status when a participant was a child. However, due to data limitation, we didn’t have objective indicators for household financial status in childhood. Third, our measurements on childhood adverse experiences were limited and crude. Although there were some scales associated with adverse childhood experiences (e.g. childhood emotional maltreatment), they were unavailable due to data limitations of CHARLS. The study aimed to examine the role of childhood maltreatment as a mediator between son preference and adulthood mental health. We found that parents’ son preference led to adverse childhood experiences, which influenced mental health in adulthood. In order to improve life-long mental health, son preference issues should be changed through culture and population interventions, along with economic supports for the aged. 258

259

Professionals and managers

Self-employed

Occupation Non-employed Farmers or manual workers

Senior high school and above

Junior high school

Education No formal education Primary school

Marital status Unmarried Married

Gender Female Male

Demographic Age

Witness of inter-parental violence No Yes

Emotional adverse experience No Yes

Childhood adverse experience Physical maltreatment No Yes

Son Preference No Yes

VARIABLES

Reference 0.367*** (0.134) −0.137 (0.199) −0.883***

Reference −0.097 (0.178) −0.536*** (0.171) −1.318*** (0.172)

Reference −1.004*** (0.173)

Reference 1.454*** (0.115)

−1.025** (0.407)

Reference 0.790*** (0.118)

Reference 0.579*** (0.175)

Reference 0.366*** (0.133) −0.134 (0.193) −0.873***

Reference −0.120 (0.179) −0.515*** (0.170) −1.305*** (0.172)

Reference −1.057*** (0.173)

Reference 1.397*** (0.114)

−1.086*** (0.406)

Reference 0.551*** (0.109)

Reference 0.592*** (0.176)

Reference 0.313** (0.140) −0.174 (0.202) −0.952***

Reference −0.108 (0.188) −0.490*** (0.181) −1.317*** (0.180)

Reference −1.009*** (0.183)

Reference 1.270*** (0.119)

−1.142*** (0.421)

Reference 1.115*** (0.196)

Reference 0.658*** (0.182)

Reference 0.321** (0.140) −0.175 (0.203) −0.963***

Reference −0.109 (0.188) −0.500*** (0.179) −1.314*** (0.179)

Reference −0.996*** (0.183)

Reference 1.372*** (0.119)

−1.019** (0.419)

Reference 0.860*** (0.199)

Reference 0.404*** (0.114)

Reference 0.677*** (0.126)

Reference 0.431** (0.181)

Coef (Std.error)

Reference 0.574*** (0.179) −0.056 (0.301) −0.827***

Reference −0.153 (0.234) −0.428* (0.231) −1.497*** (0.235)

Reference −0.931*** (0.232)

−1.045* (0.580)

Reference 0.971*** (0.194)

Reference 0.442* (0.230)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Female

All

Reference 0.567*** (0.181) −0.068 (0.302) −0.832***

Reference −0.184 (0.235) −0.406* (0.232) −1.506*** (0.236)

Reference −0.999*** (0.233)

−1.201** (0.592)

Reference 0.454*** (0.169)

Reference 0.537** (0.230)

Coef (Std.error)

Table 5 Association of son preference, childhood adverse experiences and adulthood mental health by Logistic model.

Reference 0.538*** (0.186) −0.150 (0.310) −0.872***

Reference −0.237 (0.245) −0.353 (0.243) −1.480*** (0.245)

Reference −0.912*** (0.244)

−1.164* (0.609)

Reference 0.960*** (0.289)

Reference 0.610** (0.238)

Coef (Std.error)

Reference 0.539*** (0.186) −0.172 (0.310) −0.887***

Reference −0.213 (0.244) −0.388 (0.240) −1.487*** (0.243)

Reference −0.903*** (0.245)

−1.079* (0.602)

Reference 0.681** (0.292)

Reference 0.302* (0.172)

Reference 0.927*** (0.204)

Reference 0.301 (0.243)

Coef (Std.error)

Reference 0.098 (0.203) −0.271 (0.266) −0.998***

Reference 0.149 (0.283) −0.389 (0.266) −0.993*** (0.265)

Reference −1.183*** (0.263)

−0.970* (0.556)

Reference 0.660*** (0.144)

Reference 0.720*** (0.266)

Coef (Std.error)

Male

Reference 0.102 (0.197) −0.252 (0.251) −0.974***

Reference 0.136 (0.282) −0.352 (0.263) −0.944*** (0.262)

Reference −1.213*** (0.261)

−0.904* (0.539)

Reference 0.648*** (0.138)

Reference 0.701*** (0.265)

Coef (Std.error)

Reference 0.038 (0.211) −0.254 (0.270) −1.088***

Reference 0.174 (0.304) −0.364 (0.285) −0.988*** (0.282)

Reference −1.222*** (0.278)

−0.919 (0.567)

Reference 1.013*** (0.257)

Reference 0.493*** (0.144)

Reference 0.495*** (0.153)

Reference 0.619** (0.265)

Coef (Std.error)

(continued on next page)

Reference 0.018 (0.211) −0.272 (0.271) −1.086***

Reference 0.209 (0.303) −0.375 (0.285) −1.001*** (0.281)

Reference −1.235*** (0.278)

−1.106* (0.566)

Reference 1.260*** (0.256)

Reference 0.731*** (0.265)

Coef (Std.error)

Q. Wang, et al.

Child Abuse & Neglect 93 (2019) 249–262

Reference −1.017*** (0.112) −1.427*** (0.182)

260

Robust standard errors in parentheses. *** p < 0.01. ** p < 0.05. * p < 0.1.

High school and above

Financial situation before age 17 Worse off than others Reference Same as them −0.973*** (0.113) Better off than others −1.398*** (0.181)

Reference −0.061 (0.129) −0.015 (0.153) Reference 0.149 (0.255) −0.148 (0.213)

Reference −0.036 (0.130) 0.003 (0.152)

Reference −1.004*** (0.117) −1.382*** (0.190)

Reference 0.220 (0.272) −0.080 (0.217)

Reference −0.043 (0.134) −0.051 (0.156)

Reference −0.946*** (0.117) −1.339*** (0.186)

Reference 0.196 (0.263) −0.114 (0.215)

Reference −0.058 (0.134) −0.056 (0.154)

(0.181)

Reference −1.322*** (0.170) −1.676*** (0.273)

Reference −0.177 (0.369) −0.059 (0.321)

Reference −0.159 (0.196) 0.173 (0.229)

(0.312)

(0.176)

(0.177)

(0.183)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Coef (Std.error)

Female

All

Reference 0.183 (0.264) −0.138 (0.213)

Mother education Illiterate Primary school

High school and above

Father education Illiterate Primary school

VARIABLES

Table 5 (continued)

Reference −1.379*** (0.170) −1.718*** (0.277)

Reference −0.178 (0.381) −0.046 (0.321)

Reference −0.184 (0.198) 0.137 (0.231)

(0.317)

Coef (Std.error)

Reference −1.355*** (0.177) −1.581*** (0.289)

Reference −0.095 (0.401) −0.016 (0.328)

Reference −0.139 (0.204) 0.159 (0.236)

(0.326)

Coef (Std.error)

Reference −1.283*** (0.176) −1.543*** (0.279)

Reference −0.142 (0.374) −0.065 (0.326)

Reference −0.142 (0.203) 0.167 (0.233)

(0.316)

Coef (Std.error)

Reference −0.647*** (0.144) −1.110*** (0.226)

Reference 0.482 (0.336) −0.208 (0.263)

Reference 0.033 (0.169) −0.161 (0.177)

(0.225)

Coef (Std.error)

Male

Reference −0.686*** (0.141) −1.126*** (0.224)

Reference 0.424 (0.310) −0.231 (0.262)

Reference 0.004 (0.165) −0.165 (0.177)

(0.217)

Coef (Std.error)

Reference −0.687*** (0.149) −1.219*** (0.232)

Reference 0.473 (0.332) −0.115 (0.267)

Reference 0.000 (0.173) −0.271 (0.180)

(0.231)

Coef (Std.error)

Reference −0.648*** (0.150) −1.168*** (0.230)

Reference 0.460 (0.322) −0.130 (0.264)

Reference −0.025 (0.173) −0.286 (0.180)

(0.232)

Coef (Std.error)

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Table 6 Indirect effect of childhood adverse experiences.

Total indirect effect Physical maltreatment Emotional adverse experience Witness of inter-parental violence Total effect Proportion of total effect mediate

All

Female

Male

0.027*** (0.022–0.032) 0.010 0.009 0.008 0.056*** (0.039–0.074) 47.87%

0.035*** (0.023–0.046) 0.016 0.011 0.008 0.059*** (0.033–0.085) 58.69%

0.017*** (0.011–0.022) 0.006 0.005 0.008 0.051*** (0.023–0.076) 33.38%

*** p < 0.01.

Funding This paper was supported by the National Natural Science Foundation of China No. 71372013 for Hai Fang and No. 71503059 for Qing Wang; the Research Funds of Liaoning Economic and Social Development (No. 2019lslktyb-064) and China Postdoctoral Science Foundation (No. 2018M620384) for Qing Wang. Competing interests The authors declare that they have no competing interests. Availability of data and material This study used open-access data from the China Health and Retirement Longitudinal Study, which could be downloaded from http://charls.ccer.edu.cn/zh-CN. Acknowledgements We would like to acknowledge the China Health and Retirement Longitudinal Study team for providing data and the training of using the dataset. References Almuneef, M., Qayad, M., Aleissa, M., & Albuhairan, F. (2014). Adverse childhood experiences, chronic diseases, and risky health behaviors in Saudi Arabian adults: A pilot study. Child Abuse & Neglect, 38(11), 1787–1793. Bellis, M. A., Hughes, K., Leckenby, N., Jones, L., Baban, A., Kachaeva, M., et al. (2014). Adverse childhood experiences and associations with health-harming behaviours in young adults: Surveys in eight eastern European countries. Bulletin of the World Health Organization, 92(9), 641–655. Bentley, T. (2012). A prospective investigation of physical health outcomes in abused and neglected children: New findings from a 30-year follow-up. American Journal of Public Health, 102(6), 1135. Cicchetti, D. (2013). Annual research review: Resilient functioning in maltreated children—Past, present, and future perspectives. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 54(4), 402–422. Chen, J. Q., & Dunne, M. P. (2006). Child maltreatment in China. World perspectives on child abuse. Chicago: ISPCAN. 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. Journal of Affective Disorder, 82(2), 217–225. Chen, J., Xie, Z., & Liu, H. (2007). Son preference, use of maternal health care, and infant mortality in rural China: 1989–2000. Population Studies, 61(2), 161–183. Clark, S. (2000). Son preference and sex composition for children: Evidence from India. Demography, 37(1), 95–108. Cole, S. M., & Tembo, G. (2011). The effect of food insecurity on mental health: Panel evidence from rural Zambia. Social Science & Medicine, 73(7), 1071–1079. Cohen, S., Janickideverts, D., Chen, E., & Matthews, K. A. (2010). Childhood socioeconomic status and adult health. Annals of the New York Academy of Sciences, 1186(1), 37–55. Chen, M., Wu, Y., Narimatsu, H., Li, X., Wang, C., Luo, J., et al. (2015). Socioeconomic status and physical activity in Chinese adults: A report from a community-based survey in Jiaxing, China. PloS One, 10(7), e0132918. Cerin, E., & Mackinnon, D. P. (2009). A commentary on current practice in mediating variable analyses in behavioural nutrition and physical activity. Public Health Nutrition, 12(8), 1182–1188. Charlson, F. J., Baxter, A. J., Cheng, H., Shidhaye, R., & Whiteford, H. A. (2016). The burden of mental, neurological, and substance use disorders in China and India: A systematic analysis of community representative epidemiological studies. Lancet, 388(10042), 376–389. Dening, T., & Barapatre, C. (2004). Mental health and the ageing population. The Journal of the British Menopause Society, 10(2), 49. Das Gupta, M., Jiang, Z., Li, B., Xie, Z., Chung, W., & Bae, H.-O. K. (2003). Why is son preference so persistent in east and south Asia? A cross-country study of china, India and the Republic of Korea. The Journal of Development Studies, 40(2), 153–187. Echávarri, R., & Husillos, J. (2016). The missing link between parents’ preferences and daughters’ survival: The moderator effect of societal discrimination. World Development, 78(17), 372–385. Festini, F., & De, M. M. (2004). Twenty five years of the one child family policy in China. Journal of Epidemiology and Community Health, 58(5), 358–360. Fox, B. H., Perez, N., Cass, E., Baglivio, M. T., & Epps, N. (2015). Trauma changes everything: Examining the relationship between adverse childhood experiences and serious, violent and chronic juvenile offenders. Child Abuse & Neglect, 46, 163–173. Graham, M. J., Larsen, U., & Xu, X. (1998). Son Preference in Anhui Province, China. International Family Planning Perspectives, 24(2), 72–77. Koh, E. T., Leong, K. P., Tsou, I. Y. Y., Lim, V. H., Pong, L. Y., Chong, S. Y., et al. (2006). The reliability, validity and sensitivity to change of the Chinese version of sf-36 in oriental patients with rheumatoid arthritis. Rheumatology, 45(8), 1023–1028.

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