Child Abuse & Neglect 144 (2023) 106340

Contents lists available at ScienceDirectChild Abuse & Neglect
journal homepage: www.elsevier.com/locate/chiabuneg

Association between adverse childhood experiences and marital
status among Japanese older adults
Hanayo Matsukura a, Yui Yamaoka a, Yusuke Matsuyama a, Katsunori Kondo b, c,Takeo Fujiwara a, *a

Department of Global Health Promotion, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, M&D Tower 16F
1-5-45 Yushima, Bunkyo-Ku, Tokyo 113-8510, Japanb
Department of Social Preventive Medical Sciences, Center for Preventive Medical Sciences, Chiba University, 1-33 Yayoicho, Inage Ward, Chiba
263-8522, Japanc
Department of Gerontological Evaluation, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430,
Morioka-cho, Obu City, Aichi 474-8511, JapanA R T I C L E I N F O

A B S T R A C T

Keywords:
Adverse childhood experiences
Marital status
Psychosocial well-being

Background: Marital status is a well-known social determinant of health. Adverse childhood ex­periences (ACEs) affect attachment, critical to establishing and maintaining intimate relation­
ships, such as marital status.
Objective: This study examined the association between ACEs and marital status among older
Japanese adults.
Participants and setting: This research used data from a nationwide population-based study among
functionally independent people aged 65 and above in Japan.
Methods: ACEs were assessed by self-reported questionnaires on the following experiences before
18 years old: parental death, parental divorce, parental mental disease, exposure to intimate
partner violence, physical abuse, psychological neglect, psychological abuse, and poverty. Marital
status was asked as currently having a spouse (including common-law marriage), widowed,
divorced, or unmarried. Associations between the total number of ACEs and marital status wereanalyzed by multinomial logistic regression.
Results: Three or more ACEs showed higher risks of being widowed, divorced, or unmarried.
Psychological neglect led to higher divorce risks among males (RRR, 95%CI = 1.41, 1.13–1.76)
and females (RRR, 95%CI = 1.56, 1.28–1.89). Childhood poverty showed higher risks of un­
married among males (RRR, 95%CI = 1.25, 1.02–1.53) and females (RRR, 95%CI = 1.41,
1.18–1.69). Association between ACEs and divorce risks showed gender differences (RRR, 95%CIof having three or more ACEs in males: 2.19, 1.66–2.90; in females: 3.45, 2.71–4.38; p forinteraction = 0.034).
Conclusions: ACEs showed higher risks of being widowed, divorced, and unmarried among older
Japanese people. Policy to tackle ACEs and research investigating how ACEs, attachment, andrelationship quality influence marital status are required to promote well-being in later life.

* Corresponding author at: Department of Global Health Promotion, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo
113-8519, Japan.
E-mail address: fujiwara.hlth@tmd.ac.jp (T. Fujiwara).
https://doi.org/10.1016/j.chiabu.2023.106340
Received 26 July 2022; Received in revised form 19 May 2023; Accepted 30 June 2023
Available online 17 July 2023
0145-2134/© 2023 The Authors.
Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Child Abuse & Neglect 144 (2023) 106340

H. Matsukura et al.

1. Introduction
Marital status is an essential social determinant of health. As early as the 19th century, it was reported that health and mortality
outcomes for married individuals were better than those who were unmarried (Farr, 1859; Hu & Goldman, 1990). The benefits ofmarriage were empirically identified by various health-related indicators in systematic reviews (Ikeda et al., 2007; Sommerlad et al.,2018; Wang et al., 2020). For example, a systematic review of individuals born between 1897 and 1939 in Europe, Asia, Brazil, and the
US identified a lower risk of dementia for married compared to those who were never married or widowed (Sommerlad et al., 2018).
Moreover, mortalities of cancer, cardiovascular disease, and coronary heart disease were associated with being unmarried in in­dividuals aged between 42.1 and 73.2 years old in 1997 and 2018 across 21 studies in Europe, Asia, and North America (Wang et al.,2020). A similar pattern was also found in Japan, showing higher mortality risks in unmarried individuals (Ikeda et al., 2007). Even if
people get married, poor marital functioning directly influences allostatic load, including immune, endocrine, cardiovascular, andneurosensory functioning (Kiecolt-Glaser & Newton, 2001). Those in stressful marriages showed poorer health than those in nonstressful marriages and divorced (Burman & Margolin, 1992; Williams, 2003), and the effects of long-term marital strain on healthbecome more significant over time (Umberson et al., 2006).
Among the determinants of marital status, attachment is one of the most critical. Notably, emotional ties such as trust, love, andmutual respect, developed through attachment (Bailey et al., 2015), are essential to maintaining a marriage (Karimi et al., 2019).
Bowlby developed the attachment theory, proposing that children need a secure base to develop attachment relationships with theircaregivers (Bowlby, 1969). As a result of the experiences with their caregivers, children develop an internal working model (Bowlby,
1969, 1976) of self, others, and relationships that make the way to deal with stress or threat (Bowlby, 1982; Waters et al., 2002). To be
more specific, a lack of consistent and reliable attachment relationships adversely affects psychosocial development (Bowlby, 1969,
1976; Lieberman et al., 2011), eventually resulting in a lack of self-worth being loved and a lack of trust in others (Bowlby, 1969, 1976;
Cyr et al., 2010; Huynh et al., 2022). Later, Bowlby (1980) developed a hypothesis to interpret trauma survivors’ psychologicalmechanism named defensive exclusion (Bowlby, 1980). Traumatized individuals eliminate clues that are evocative to the individual’s
attached figures due to psychological pains, which results in two cognitive/behavioral patterns: 1) the individual’s behavioral system
is deactivated, and 2) the individual attributes bad situations to others then repeats the behavior (Bowlby, 1980). Previous studies
showed consistent findings with this hypothesis. Adults with avoidant and ambivalent styles tend to avoid intimate relationships andreject the need for close relationships (Feeney & Noller, 1990; Mikulincer & Erev, 1991). Other studies also showed that individuals
with childhood trauma experience a higher risk of dysfunctional relationships (DiLillo et al., 2009).
Adverse childhood experiences (ACEs) are parental loss, child maltreatment, and family dysfunction during childhood (Felitti et al.,1998). ACEs are recognized as a fundamental determinant of well-being throughout life from multi dimensions, including psycho­social, behavioral, and physiological functioning. For example, a higher number of ACEs is associated with the probability of disor­ganized attachment (Murphy et al., 2014), lower psychosocial functioning in marital relationships (Mosley-Johnson et al., 2019),
higher risk behavior such as heavy drinking, drug use, and suicide attempts (Merrick et al., 2017), and higher mortality (Bellis et al.,2014; Brown et al., 2009; Rod et al., 2020). The extensive literature examined the quality of marital relationships’ oversight influenceof ACEs (Shonkoff & Garner, 2012). Although ACEs are known to interrelate and co-occur, many studies focused on specific types of
ACEs in intimate relationships (Dong et al., 2004). There is a scarcity of research that systematically examines the association between
ACEs and marital status, specifically among older adults.
A population-based survey in the US, which included 29,229 individuals whose average age was 48 years old from five states, foundsignificant associations between higher ACEs and a higher probability of divorce or separation and lower probabilities of married or
widowed (Font & Maguire-Jack, 2016). Another study, which included 17,530 men and 23,978 women aged 18 to 54 from 13 states,
found that people with more ACEs were likelier to be unmarried couples or experience divorce or separation (Anderson, 2017).
However, these two studies included relatively younger respondents. Also, Anderson (2017) dropped widowed individuals from theanalysis, and Font and Maguire-Jack (2016) merged widowed and married; therefore, these studies might not sufficiently capture
respondents’ marital status, resulting in an underestimation of the association between ACEs and marital status.
Sex or gender differences matter in marriage life. Empirically, men enjoy more excellent health benefits from marriage than women(Ben-Shlomo et al., 1993; Gove, 1973). Saxbe et al. (2008) identified that sex differences were linked to cortisol levels; higher
satisfaction levels with marriage showed a more robust basal cortisol cycle for women. Regarding gender, in general, women expe­
rience less access to income, wealth, time, and low status in the household (Doyal, 2003), and Wanic and Kulik (2011) hypothesizedthat lower status in marital relationships for women increases the risk of adverse consequences in marriage. Thus, there is a need toanalyze the factors with stratification by gender.
The Japan Gerontological Evaluation Study (JAGES), which targets older adults aged 65 and above without functional dependence
across Japan, assessed ACEs and marital status. Using this data set, marital status is more accurate compared to the previous studies.
Based on the above, this study examines the following hypothesis among older people in Japan: 1) there are cumulative effects of ACEs
on marital status, i.e., the risks of being widowed, divorced, and unmarried, 2) each ACE has a differential impact on the marital statusof older adults, and 3) these associations differ by gender.
2. Methods
2.1. Sample
This study used data from the Japan Gerontological Evaluation Study (JAGES), a nationwide population-based survey conducted in2

Child Abuse & Neglect 144 (2023) 106340

H. Matsukura et al.

2013 and 2016. The JAGES investigated the social determinants of health among individuals aged 65 and older whose activities ofdaily life have been independent since 2003 by mailing self-reported questionnaires (Kondo et al., 2018). The data used in this study
were sampled from 30 municipalities in 14 prefectures in 2013 and from 40 in 18 in 2016 in Japan. The target population size was
193,694 for the questionnaire in 2013 and 276,469 in 2016. Of the target populations, there were 137,736 respondents (response rate
= 71.1 %) in 2013 and 194,352 respondents (response rate = 69.5 %) in 2016. The surveys excluded those who needed functional
support. Hence, the data comprised 128,239 respondents in 2013 and 180,021 in 2016. ACEs were asked in a randomly selected
sample by self-reported questionnaires, about one-fifth of the total sample in 2013 (n = 25,656/128,239) and one-eighth of the total
sample in 2016 (n = 22,129/180,021). The present analysis was conducted after setting the following exclusion criteria: 1) those who
did not completely answer the questions on ACEs; 2) those who did not answer about marital status; 3) those who answered “other” inmarital status; and 4) those who did not answer about their sex. We found those who participated in both surveys in 2013 and 2016.
This study excluded 2013, as marital status might have changed during the three years (N = 1957). Finally, the analytic sample
comprised 39,738 respondents (20,135 in 2013 and 19,603 in 2016). Supplemental Fig. 1 shows the Flowchart of the samples foranalysis.
2.2. Measurements
In the JAGES, marital status was asked using the following answer items: 1) having a spouse (including common-law marriage), 2)
being widowed, 3) being divorced, 4) never married, and 5) others. This study correspondingly named 1) married, 2) widowed, 3)
divorced, and 4) unmarried as marital status, excluding respondents who answered “other.”With regards to ACEs, JAGES in 2013 asked about the following experiences that occurred before 18 years old (yes/no responses):
1) parental death, 2) parental divorce, 3) parental mental disease, 4) exposure to intimate partner violence (IPV), 5) physical abuse, 6)
psychological neglect, 7) psychological abuse, and 8) childhood poverty (Amemiya et al., 2019; Tani et al., 2019; Tani et al., 2020).
The JAGES in 2016 added the questionnaire of if their parent passed away because of war and if their parent died for other reasons.
Therefore, this paper made a variable as “parental loss” for the participants of JAGES in 2016 if they experienced either/both cases ofparental bereavement due to war and/or the other reasons for the analysis. Although the original ACEs study by Felitti et al. (1998) did
not include childhood poverty, a recent ACEs study considered childhood poverty an ACE (Hughes & Tucker, 2018). This study
calculated the total number of ACEs and categorized them as zero, one, two, and three or more for further analysis.
Age was also asked via the questionnaire and categorized as 65 to 69 years old, 70 to 74 years old, 75 to 79 years old, and 80 years
old or above. Socioeconomic status (SES), marital status, and ACEs seem inextricable to link one another. For example, individuals
with high SES tend to postpone marriage and childrearing, but groups with low SES tend to give birth before marriage and are lesslikely never to marry (Karney, 2021). Also, several studies identified that ACEs are associated with later economic outcomes (Currie &Widom, 2010; Mersky & Topitzes, 2010), job performance (Anda et al., 2004), and educational attainment in later life (Mersky &Topitzes, 2010). Thus, education and occupation were considered mediators of the association between ACEs and marital status. The
number of years of formal education year was asked in the following categories: 1) shorter than six years, 2) six to nine years, 3) ten to
12 years, 4) 13 years or longer, and 5) others. For further analysis, we collapsed the education as nine years or shorter (the compulsory
education period is nine years in Japan), ten to 12 years (high school), 13 years or longer (college), and others. Missing values of theeducation period and the answer of “others” were treated as dummy variables. The occupation was classified as non-manual, manual,and not employed by asking, “What was the longest occupation you were in?” Non-manual includes professional/engineering occu­
pation and administrative posts; manual includes clerical work, sales/service, general work, agriculture, forestry/fisheries, selfemployment, and other; and not employed includes never worked. This study treated missing values of occupation as dummy
variables.
2.3. Ethics
The JAGES protocol was approved by the Ethics Committee in Research of Human Subjects at Nihon Fukushi University (No. 1314),
in Research of Human Subjects at the National Center for Geriatrics and Gerontology (No.992), and Chiba University Faculty of
Medicine (No. 2493).
2.4. Analysis
First, demographic variables, proportions of each ACE and the number of ACEs, and current marital status were described bygender. Second, we examined the proportions of having other ACEs for each type of ACE. Then, multinomial logistic regression wasused to analyze the association between ACEs and marital status. This study examined the associations using three models: 1) the crude
model, 2) Model 1, which adjusted age, and 3) Model 2, which adjusted age, education, and occupation. To examine if gender modifies
the effect of cumulative ACEs on marital status, an interaction term of ACE and gender was entered into the model. In addition, thisstudy analyzed the association of each ACE with marital status by multinomial logistic regression stratified by gender. All statisticalanalyses were conducted via Stata/MP version 16.1 (STATA Corp., College Station, TX, USA). The level of statistical significance wasset at p < 0.05 (two-tailed).
3Child Abuse & Neglect 144 (2023) 106340

H. Matsukura et al.

3. Results
Table 1 shows the demographic characteristics of the study participants by gender. In the sample, 53.6 % were female, and theaverage age was 73.8 (SD = 6.16) years old (30.3 % were 65–69 years old, and 19.1 % were 80 years old and above). Regarding thenumber of years of formal education, males obtained significantly more extended education periods than females (30.1 % of males
received 13 or longer years of education, while only 18.5 % of females did). With regards to occupation, “not employed” individuals
were 9.5 % for females and 1.3 % for males, and a significantly higher percentage of non-manual workers were seen in males (37.1 %)than in females (11.4 %). Males showed a significantly higher percentage of experiencing ACEs both in any ACEs and the number ofACEs. The most prevalent ACE was poverty, and then parental death and psychological neglect followed. Most respondents were
married (87.1 % for males and 61.5 % for females), followed by widowed (7.3 % for males and 31.4 % for females), divorced (3.2 % formales and 4.4 % for females), and unmarried (2.5 % for males and 2.6 % for females).
Table 2 shows the concurrence of ACEs. Physical abuse showed the highest concurrence of other ACEs for males and females (94.4% and 96.0 %, respectively). However, more than half of individuals who experienced physical abuse were affected by other types ofACEs, such as psychological neglect (51.9 % for males and 54.3 % for females), psychological abuse (49.6 % for males and 60.9 % forfemales), and poverty (78.0 % for males and 76.8 % for females). Although poverty was the most prevalent among all ACEs at 50.8 %for males and 37.9 % for females, it showed the lowest percentage of coincidence of other ACEs.
Table 3 illustrates the association between the number of ACEs and marital status for males and females. For both genders, three ormore ACEs showed significantly high relative risk ratios (RRRs) of widowed, divorced, and unmarried (Table 3). Having three or more
ACEs was more likely to be widowed among older adults (RRR, 95 % confidence interval [95 % CI] for male: 1.47, 1.20–1.81; forfemale: 1.35, 1.17–1.55) in the crude model. The significant associations remained after adjusting covariates in model 2 in bothgenders. Looking at the details of being divorced, RRRs were higher in females than males. For example, the RRRs of being divorced
with three or more ACEs were 2.34 (95 % CI: 1.79–3.07) for males while 3.52 (95 % CI: 2.78–4.45) for females in the crude model, andsuch a pattern was found in all models. Higher ACEs score showed higher RRRs of being unmarried for both genders. The RRRs of being
unmarried with three or more ACEs were higher in males (RRR, 95%CI: 2.52, 1.88–3.38) than in females (1.86, 1.32–2.63) in the crude
model. However, the RRRs of being unmarried in Model 2 became similar for males (RRR, 95%CI: 2.27, 1.67–3.09) for females (2.24,
1.58–3.17). There were dose-response relationships between cumulative ACEs and the risk of being widowed, divorced, and unmarriedin both males and females (p for trend <0.05). As a result of adding the interaction of gender on the association between cumulative
ACEs and marital status in Model 2, the risk of being divorced was modified by gender when the number of ACEs reaches three or more
(RRR, 95%CI:1.48, 1.03–2.12; p for interaction = 0.034).
Tables 4 and 5 illustrate the association between each ACE and marital status for males and females. Interestingly, no ACEs wereassociated with the significantly higher risk of being widowed for both genders in Model 2. The RRRs of being divorced by each ACE
Table 1
Demographic characteristics of the study participants.
Male
Age

Education period

Occupation

ACEs

Number of ACEs

Marital status

65–69 years old
70–74 years old
75–79 years old
80+ years old
9 years or shorter10 to 12 years
13 or longer years
Other and missing
Non-manual
ManualNot employed
Missing
Parental deathParental divorce
Parental mental disease
Exposure to IPV
Physical abuse
Psychological neglect
Psychological abuse
Poverty01
23+
Married
Widow
Divorce
Unmarried

FemaleP-value

N

%

N

%

5714
5272
4033
3413
5941
6786
5542
163
6835
10,139
234
1224
5066
506
193
816
337
2665
1093
9371
6055
6928
3913
1536
16,045
1339
584
464

31.0
28.6
21.9
18.5
32.2
36.8
30.1
0.9
37.1
55.0
1.3
6.6
27.5
2.8
1.1
4.4
1.8
14.5
5.9
50.8
32.9
37.6
21.2
8.3
87.1
7.3
3.2
2.5

6342
6126
4682
4156
8072
8990
3939
305
2429
14,340
2016
2521
5411
440
149
698
151
2094
1039
8081
9223
7583
3425
1075
13,112
6694
942
558

29.8
28.8
22.0
19.5
37.9
42.2
18.5
1.4
11.4
67.3
9.5
11.8
25.4
2.1
0.7
3.3
0.7
9.8
4.9
37.9
43.3
35.6
16.1
5.1
61.5
31.4
4.4
2.6

4

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

H. Matsukura et al.

Table 2
Relationships of ACEs (N = 18,432 for males and N = 21,306 for females).
Number (%)

Exposed to another ACE (%)
Parental
Parental
Mentaldeath
divorcedisease5066 (27.5%)506(2.7%)
193(1.0%)
816(4.4%)
337(1.8%)
2665 (14.5%)
1093 (5.9%)
59371 (50.8%)

182(3.6%)
182(36.0%)
105(54.4%)
217(26.6%)
116(34.4%)
808(30.3%)
322(29.5%)
3170(33.8%)

5411 (25.4%)

113(2.1%)
113(25.7%)
69 (46.3%)
166(23.8%)
52 (34.4%)
564(26.9%)
284(27.3%)
2670(33.0%)

13(8.7%)
57(8.2%)
21(13.9%)
99(4.7%)
64(6.2%)
258(3.2%)

33(4.0%)
23(6.8%)
52(2.0%)
41(3.8%)
141 (1.5%)

69(1.3%)
13(3.0%)

24(3.4%)
8(5.3%)
28(1.3%)
30(2.9%)
98(1.2%)

Physicalabuse

Psychologicalneglect

Psychologicalabuse

Poverty

Additional
ACEs (%)

217(4.3%)
73(14.4%)
33(17.1%)

116(2.3%)
36(7.1%)
23(11.9%)
162 (19.9%)808(16.0%)
171(33.8%)
52(26.9%)
306(37.5%)
175(51.9%)

322(6.4%)
66(13.0%)
41(21.2%)
245(30.0%)
167(49.6%)
462(17.3%)

3170(62.6%)
370(73.1%)
141(73.1%)
635(77.8%)
263(78.0%)
1736(65.1%)
764(69.9%)

3491 (68.9%)

2670(49.3%)
258(58.6%)
98(65.8%)
479(68.6%)
116(76.8%)
1110(53.0%)
640(61.6%)

3012(55.7%)
332(74.5%)
132(88.6%)
588(84.2%)
145(96.0%)
1424(68.0%)
851(81.9%)
3996(49.5%)

162(48.1%)
306(11.5%)
245(22.4%)
635(6.8%)

166(3.1%)
57(13.0%)
24(16.1%)

61(40.4%)
196(9.4%)
187(18.0%)
479(5.9%)

175(6.6%)
167 (15.3%)
263 (2.8%)52(1.0%)
21(4.8%)
8(5.4%)
61(8.7%)

82(3.9%)
92(8.9%)
116(1.4%)

462(42.3%)
1736(18.5%)

564(10.4%)
99(22.5%)
28(18.8%)
196(28.1%)
82(54.3%)

424(40.8%)
1110(13.7%)

764(8.2%)

284(5.3%)
64(14.6%)
30(20.1%)
187(26.8%)
92(60.9%)
424(20.3%)

1039(7.9%)

444(87.8%)
177(91.7%)
737(90.3%)
318(94.4%)
2041(76.6%)
933(85.4%)
4978 (53.1%)

Child Abuse & Neglect 144 (2023) 106340

440(2.1%)
149(0.7%)
698(3.3%)
151(0.7%)
2094(9.8%)
1039(4.9%)
8081 (37.9%)25(13.0%)
73(9.0%)
36(10.7%)
171(6.4%)
66(6.0%)
370(4.0%)

105(2.1%)
25(4.9%)

Exposure to
IPVH. Matsukura et al.

Table 3
Association between ACEs and marital status by gender (N = 18,432 for males and N = 21,306 for females).
Marital status (reference: married)
Widow

Male

0
1

6

2
3+
Female01
23+

Divorce

Unmarried

Crude

Model1Model2

Crude

Model 1Model 2

Crude

Model 1Model 2

RRR
(95%CI)

RRR(95%CI)

RRR(95%CI)

RRR(95 % CI)

RRR
(95 % CI)

RRR
(95 % CI)

RRR
(95 % CI)

RRR
(95 % CI)

RRR
(95 % CI)

ref.
1.13
(0.99–1.29)
1.21(1.04–1.41)
1.47(1.20–1.81)
ref.
1.08
(1.01–1.16)
1.13(1.03–1.23)
1.35(1.17–1.55)

ref.
1.11
(0.97–1.28)
1.15(0.98–1.35)
1.51(1.22–1.86)
ref.
1.05
(0.97–1.13)
1.11(1.01–1.22)
1.49(1.29–1.73)

ref.
1.06
(0.92–1.22)
1.06(0.90–1.24)
1.34(1.08–1.65)
ref.
1.00
(0.93–1.07)
1.03(0.94–1.13)
1.35(1.16–1.57)

ref.
1.21
(0.98–1.49)
1.30(1.02–1.64)
2.34(1.79–3.07)
ref.
1.32
(1.12–1.54)
1.70(1.41–2.05)
3.52(2.78–4.45)

ref.
1.23
(1.00–1.52)
1.35(1.06–1.71)
2.36(1.80–3.10)
ref.
1.33
(1.13–1.56)
1.72(1.42–2.07)
3.54(2.80–4.48)

ref.
1.19
(0.97–1.47)
1.28(1.00–1.63)
2.19(1.66–2.90)
ref.
1.30
(1.11–1.53)
1.66(1.37–2.02)
3.45(2.71–4.38)

ref.
1.10
(0.87–1.39)
1.33(1.02–1.73)
2.52(1.88–3.38)
ref.
1.04
(0.85–1.26)
1.26(0.99–1.60)
1.86(1.32–2.63)

ref.
1.18
(0.93–1.50)
1.53(1.17–1.99)
2.73(2.03–3.67)
ref.
1.03
(0.85–1.26)
1.27(1.00–1.61)
1.93(1.37–2.72)

ref.
1.10
(0.87–1.41)
1.36(1.04–1.78)
2.27(1.67–3.09)
ref.
1.11
(0.91–1.35)
1.41(1.10–1.80)
2.24(1.58–3.17)

Model1: adjusted for age; Model2 adjusted for age, educational period, and occupation.
Bold letters represent significant results (* p < 0.05, ** p< 0.01, *** p< 0.001).
Child Abuse & Neglect 144 (2023) 106340

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H. Matsukura et al.

tend to be higher for females than males, and the type of ACEs with a significant association is more diverse for females. Parental death,
psychological abuse, and poverty were significantly more likely to experience divorce only in females. In contrast, parental divorce andpsychological neglect were significant risk factors for divorce in both genders. Regarding unmarried status, poverty was a significant
common risk factor in both genders. Psychological neglect remained significant only for males, even after adjusting covariates and allother ACEs.
4. Discussion
This study examined the association between ACEs and marital status among functionally independent older Japanese. Overall, we
found the following things: 1) three or more ACEs were associated with the risk of being widowed, and the accumulated effects of ACEs
matter to becoming widowed rather than none of the specific types of ACEs has the independent effect, 2) childhood poverty was
associated with the risk of being divorced only for females, and females had a greater risk of being divorced when having three or more
ACEs than males, and 3) unmarried status was associated with having three or more ACEs and childhood poverty in both genders.
Regarding the risk of widowhood, the outcomes imply that the impact of each ACE is small and not specific, but multiple ACEs
could lead to the risk of widowhood in both males and females. Even though females are more likely to become widowed than males,
this study confirmed that both males and females with three or more ACEs are more likely to become widowed than those without
ACEs. In addition, individuals with a higher number of ACEs might experience a higher risk of being widowed because individuals
exposed to ACEs significantly tend to choose partners with ACEs (Andersson et al., 2021), and a higher number of ACEs is associatedwith premature mortality (Bellis et al., 2014; Brown et al., 2009).
Why individuals with ACEs match each other can be considered from two aspects. First, child maltreatment is associated with
insecure attachment styles (Baer & Martinez, 2006), and when getting married, people select their mate to sustain initial attachment
security (Bartholomew, 1990). In this view, attachment rather than ACEs is the hidden reason. Another is assortative mating theories,
which propose that individuals choose partners having their similarities (Trombello et al., 2015), convince that people having similar
backgrounds might be attracted to each other.
Marital quality mediates the association between childhood abuse and positive/negative affective symptoms (Fitzgerald & Ber­thiaume, 2021), and insecure attachment style mediates the association between childhood maltreatment and lower quality intimate
relationships (Shahab et al., 2021). Further, insecure individuals showed decreased commitment and trust and increased perception of
cost overtime (Keelan et al., 1994). Given these, accumulated stress caused by a high marital strain might eventually lead towidowhood. Further study is required to examine how mediating factors, including attachment, marital quality, subsequent adverse
health effects due to ACES for themselves and their partners, and its interactive effects between them influence higher risks ofwidowhood throughout the marriage.
This study found new knowledge in the association between a specific type of ACEs and the risk of divorce. To the best of ourknowledge, the association between childhood poverty and being divorced for females had not been reported; however, prior studies
back up this outcome. Parents facing financial strain experience wide-ranging difficulty and are more likely to use parenting practices
that lack warmth, which develop insecure attachment (Ho et al., 2022; Laraia et al., 2006; Stansfeld et al., 2008). Also, financial strain
Table 4
Relative risk ratios of widowed, divorced, and unmarried by each ACE for males (N = 18,432).
Marital status (reference: married)
ACEs

Parental deathParental divorce
Parental mental disease
Exposure to IPV
Physical abuse
Psychological neglect
Psychological abuse
Poverty

Widow

Divorce

Unmarried

Bivariate

Model1Model2

Bivariate

Model1Model2

Bivariate

Model1Model2

RRR

RRR

RRR

RRR

RRR

RRR

RRR

RRR

RRR

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

1.30
1.15–1.46
0.85
0.58–1.23
1.29
0.78–2.14
1.04
0.79–1.37
1.08
0.71–1.62
1.20
1.03–1.39
1.13
0.90–1.43
1.09
0.98–1.22

1.13
1.00–1.27
0.92
0.63–1.34
1.29
0.77–2.16
1.17
0.89–1.55
1.03
0.68–1.58
1.11
0.95–1.30
1.12
0.89–1.41
1.04
0.92–1.16

1.12
0.99–1.27
0.87
0.59–1.27
1.24
0.74–2.08
1.15
0.85–1.54
0.91
0.58–1.43
1.10
0.93–1.29
1.07
0.84–1.37
1.01
0.90–1.14

1.16
0.97–1.39
1.93
1.31–2.84
1.75
0.92–3.34
1.75
1.27–2.42
2.00
1.26–3.18
1.61
1.31–1.97
1.48
1.10–2.00
1.20
1.01–1.41

1.18
0.98–1.42
1.79
1.22–2.64
1.64
0.86–3.13
1.61
1.16–2.23
1.85
1.16–2.95
1.55
1.26–1.90
1.42
1.05–1.92
1.14
0.96–1.35

1.16
0.96–1.39
1.53
1.03–2.28
1.32
0.69–2.56
1.29
0.90–1.84
1.27
0.75–2.13
1.41
1.13–1.76
1.11
0.79–1.55
1.04
0.87–1.24

1.09
0.88–1.34
2.01
1.32–3.07
1.76
0.86–3.61
1.90
1.34–2.70
1.63
0.93–2.86
1.82
1.46–2.27
1.73
1.26–2.38
1.42
1.18–1.72

1.10
0.89–1.36
1.63
1.06–2.51
1.44
0.69–2.98
1.55
1.09–2.21
1.35
0.76–2.40
1.71
1.36–2.15
1.60
1.15–2.20
1.35
1.11–1.64

1.04
0.84–1.29
1.34
0.87–2.09
1.20
0.57–2.51
1.23
0.83–1.81
0.81
0.43–1.52
1.55
1.22–1.97
1.29
0.90–1.83
1.25
1.02–1.53

Model1: adjusted age, occupation, education, Model2: Model1+ all ACEs.
Bold letters represent significant results (* p < 0.05, ** p< 0.01, *** p< 0.001).
7

Child Abuse & Neglect 144 (2023) 106340

H. Matsukura et al.

Table 5
Relative risk ratios of being widowed, divorced, and unmarried by each ACE for females (N = 21,306).
Marital status (reference: married)
Widow
ACEs

Parental deathParental divorce
Parental mental disease
Exposure to IPV
Physical abuse
Psychological neglect
Psychological abuse
Poverty

Divorce

Unmarried

Bivariate

Model1Model2

Bivariate

Model1Model2

Bivariate

Model1Model2

RRR

RRR

RRR

RRR

RRR

RRR

RRR

RRR

RRR

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

95%CI

1.21
1.13–1.30
0.89
0.71–1.11
1.00
0.70–1.44
0.94
0.79–1.12
1.48
1.04–2.10
1.09
0.98–1.22
1.01
0.88–1.16
1.08
1.02–1.15

1.02
0.95–1.10
1.18
0.93–1.50
1.03
0.70–1.51
1.24
1.03–1.48
1.58
1.09–2.30
1.07
0.96–1.19
1.14
0.98–1.32
1.05
0.99–1.13

1.02
0.95–1.09
1.14
0.90–1.44
0.96
0.65–1.42
1.16
0.96–1.40
1.38
0.94–2.04
1.05
0.94–1.18
1.05
0.90–1.24
1.04
0.97–1.11

1.25
1.13–1.30
3.21
2.39–4.32
1.43
0.72–2.84
1.97
1.48–2.61
3.09
1.79–5.32
1.93
1.61–2.32
2.27
1.80–2.86
1.44
1.26–1.64

1.23
1.06–1.43
3.10
2.30–4.18
1.40
0.70–2.80
1.90
1.43–2.53
2.98
1.72–5.15
1.91
1.59–2.30
2.22
1.76–2.80
1.39
1.21–1.59

1.20
1.03–1.39
2.57
1.89–3.50
0.96
0.48–1.95
1.31
0.96–1.78
1.29
0.71–2.32
1.56
1.28–1.89
1.60
1.23–2.06
1.23
1.07–1.42

0.96
0.78–1.17
1.50
0.90–2.50
1.98
0.91–4.32
1.43
0.95–2.16
2.27
1.04–4.95
1.24
0.94–1.62
1.71
1.23–2.36
1.30
1.10–1.54

0.95
0.77–1.16
1.62
0.97–2.72
1.79
0.77–4.12
1.57
1.04–2.38
2.52
1.15–5.53
1.37
1.04–1.79
1.74
1.25–2.41
1.47
1.23–1.76

0.90
0.73–1.11
1.39
0.83–2.34
1.61
0.73–3.55
1.18
0.77–1.83
1.53
0.67–3.51
1.16
0.87–1.55
1.40
0.98–2.00
1.41
1.18–1.69

Model1: adjusted age, occupation, education, Model2: Model1+ all ACEs.
Bold letters represent significant results (* p < 0.05, ** p< 0.01, *** p< 0.001).

during childhood increases the sensitivity to stress and influences trust, especially in close relationships (Miller et al., 2011; Pearlin
et al., 2005), and only women with childhood financial strain feel lower levels of happiness in the context of marital strain (Upenieks &Liu, 2022).
With regards to other types of ACEs, the following are consistent findings with prior studies: there was a dose-response relationshipbetween the number of ACEs and the risk of being divorced (Anderson, 2017; Font & Maguire-Jack, 2016), and there were associations
between divorce risks and psychological neglect and parental divorce (Anderson, 2017; Colman & Widom, 2004; Font & Maguire-Jack,
2016). Inconsistent findings were found in parental death, physical abuse, and psychological abuse. Parental bereavement was
associated with higher separation rates in females and males (Høeg et al., 2018), but females only in this study. In addition, females had
higher divorce risks if they experienced combined childhood violence (Anderson, 2017), or no associations between childhood
violence and the risk of divorce (Font & Maguire-Jack, 2016). However, this study identified that females with childhood psycho­
logical abuse were more likely to divorce.
Relationships with the mother and the father and the child’s gender influence development of attachment and behaviors in close
relationships. Children form attachment relationships with their mother and father differently, showing that father’s parenting
practices predict versatile variation in infant-father attachment security (Cox et al., 1992). Further, selection of intimate partner isassociated with opposite-sex parent’s caregiving style (Collins & Read, 1990). The prior study described that around 70 % was paternal
death among parental bereavement (Høeg et al., 2018), while the survey used in this study did not ask which parent passed away.
Considering the historical backgrounds that the participants were raised during/after the World War II, the percentage of father’s
death is considered to be much higher than mother’s death, and such difference might affect the different outcomes (Fujiwara et al.,2023). The inconsistent outcomes of childhood violence might be due to females’ versatile attachment, which was developed via therelationships with their fathers. Further study is required to examine how specific type of ACE influences the development of emotional
functioning and attachment lead to divorce, considering parental sex difference and stratifying males and females.
Although the dose-response relationship between cumulative ACEs and unmarried risk was consistent with a prior study (Font &Maguire-Jack, 2016), the types of ACEs differ. This study found that higher risks of unmarried were associated with childhood poverty
in males and females and psychological neglect in males only; however, any ACEs or child abuse were not associated with nevermarried in prior studies (Anderson, 2017; Colman & Widom, 2004). The fiscal pressure in the family of origin is associated withfinancial hardships in later life (Donnellan et al., 2009), and couples in low SES are likely never to marry (Karney, 2021). Psychologicalneglect is directly related to avoidant attachment (Höltge et al., 2023), which brings social isolation and less involvement in romantic
relationships, especially for males (Colman & Widom, 2004; May et al., 2022). Childhood poverty affects holistic human develop­
mental aspects, such as physical, psychological, emotional, cognitive functioning (Yoshikawa et al., 2012), and intimate relationships
throughout life, as we found in this study. Therefore, it should be emphasized that policy development and implementation to tackle
childhood poverty and evaluation of its effects on later well-being in intimate relationships must be inevitable.
Different patterns of associations between ACEs and marital status between males and females can be explained through brain
mechanisms. For example, a recent study found interacting effects of ACEs and sex on brain morphology: females with either threat (i.
e., the presence of unexpected inputs such as trauma) or deprivation (i.e., the absence of expected inputs) had smaller grey mattervolume in a region where the processing of emotions interplays than those without such experiences, while males who experienced
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H. Matsukura et al.

deprivation did smaller than those who experienced threat (Everaerd et al., 2016). Also, females are more accurate in recognizing
fearful facial expressions compared to males, using sex-specific brain circuits (Weisenbach et al., 2014). Such evidence may imply thatfemales are more vulnerable to emotional processing and developing attachment relationships when exposed to diverse ACEs (boththreat and deprivation). Hence, all professionals in intimate relationships should pay more attention to ACEs and their differential
effects on sex for further effective intervention/prevention strategies.
Several limitations should be mentioned before the conclusion. Firstly, the current findings may not apply to different circum­
stances and younger generations because most of the participants in this study were born during/after World War II, and the meaningof marriage differed from the current pattern. Several recent studies make categories related to other adverse experiences such as war
and natural disasters (e.g., Johnson et al., 2020), but this study did not; therefore, the outcomes might have been different if there wereother variables of different kinds of ACEs. In addition, marriage had been viewed as an expectation and obligation due to family beliefs
in East Asia, including Japan (Bumpass et al., 2009; Rindfuss et al., 2004). The social norm has changed; the individual choice has
become more welcomed (Arnett et al., 2014). Such societal change is seen in the statistics; arranged marriages took up more than halfin the 1950s while it decreased to only a few percent by the early 21st century (Arnett et al., 2014). Therefore, future study needs totarget young or middle-age adulthood to see the effects of ACEs on marital status in the current context. Secondly, information bias,
especially recall bias on ACEs, might have influenced the findings, though a previous study reported that retrospective recall of ACEs
showed good validity (Hardt & Rutter, 2004). Thirdly, this study excluded those who answered “other” for marital status, whereinthose who remarried or divorced multiple times might be included. Fourthly, although we focused on older adults of 65 years or above,
survival effect, those with higher ACEs were more likely to die before 65. Thus, the association between ACEs and marital status may
have been underestimated.
In conclusion, a higher number of ACEs is associated with being widowed, divorced, and unmarried in older Japanese adults.
Therefore, policy to tackle ACEs and further research examining how ACEs, attachment, and couple relationships are related and how
they influence marital status is required to promote well-being in later intimate relationships.
Supplementary data to this article can be found online at https://doi.org/10.1016/j.chiabu.2023.106340.
Financial disclosure
The authors have no financial relationships relevant to this article to disclose. This study used data from the JAGES, which was
supported by Grant-in-Aid for Scientific Research (15H01972, 15H04781, 15H05059, 15K03417, 15K03982, 15K16181, 15K17232,
15K18174, 15K19241, 15K21266, 15KT0007, 15KT0097, 16H05556, 16K09122, 16K00913, 16K02025, 16K12964, 16K13443,
16K16295, 16K16595, 16K16633, 16K17256, 16K17281, 16K19247, 16K19267, 16K21461, 16K21465, 16KT0014, 17K04305,
17K04306, 25253052, 25713027, 26285138, 26460828, 26780328, 18H03018, 18H04071, 18H03047, 18H00953, 18H00955,
18KK0057, 19H03901, 19H03915, 19H03860, 19K04785, 19K10641, 19K11657, 19K19818, 19K19455, 19K24060, 19K20909,
20H00557, 21K19635, 21H03153) from JSPS (Japan Society for the Promotion of Science); Health Labour Sciences Research Grants(H26-Choju-Ippan-006, H27-Ninchisyou-Ippan-001, H28- Choju-Ippan-002, H28- Ninchisyou-Ippan-002, H30-Kenki-Ippan-006, H29Chikyukibo-Ippan-001, H30-Jyunkankinado-Ippan-004, 19FA1012, 19FA2001, 21FA1012, 22FA2001, 22FA1010), Research project
on health and welfare promotion for the elderly from the Ministry of Health, Labour and Welfare, Japan; the Research and Devel­
opment Grants for Longevity Science from Japan Agency for Medical Research and Development (AMED) (JP18dk0110027,
JP18ls0110002, JP18le0110009, JP20dk0110034, JP21lk0310073, JP21dk0110037, JP22lk0310087), the Research Funding forLongevity Sciences from National Center for Geriatrics and Gerontology (24-17, 24-23, 29-42, 30-30, 30-22, 20-19, 21-20); Open
Innovation Platform with Enterprises, Research Institute and Academia (OPERA, JPMJOP1831) from the Japan Science and Tech­
nology (JST); a grant from the Japan Foundation For Aging and Health (J09KF00804), a grant from Innovative Research Program on
Suicide Countermeasures (1-4), a grant from Sasakawa Sports Foundation, a grant from Japan Health Promotion & Fitness Foundation,a grant from Chiba Foundation for Health Promotion & Disease Prevention, the 8020 Research Grant for fiscal 2019 from the
8020Promotion Foundation (adopted number: 19-2-06), grants from Meiji Yasuda Life Foundation of Health and Welfare. Also, thiswork was supported by JST SPRING, Grant Number JPMJSP 2120. The views and opinions expressed in this article are those of theauthors and do not necessarily reflect the official policy or position of the respective funding organizations.
Declaration of competing interest
The authors have no conflict of interest to disclose.
Data availability
Data are from the JAGES study. All enquiries are to be addressed at the data management committee via e-mail: dataadmin.
ml@jages.net.
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