Role of Maternal Adverse Childhood Experiences on Infant Neglect: A Multi-Perspective Approach

Abstract

We explored the intergenerational transmission effects of maternal adverse childhood experiences (ACEs) and infant neglect from multiple perspectives. The study included a sample of postpartum mothers and infants (N = 550) from the outpatient child health care department of a tertiary hospital in Jinan, Shandong Province, China. Our investigation followed three main lines of inquiry. First, the association of overall maternal ACEs with infant neglect was estimated. Secondly, the cumulative and independent effects of maternal ACEs on infant neglect were explored using the Adverse Childhood Experience Questionnaire-Revised (ACEQ-R) with 14 types of ACEs. Finally, the different patterns of 14 maternal ACEs were identified, and the association between the different patterns and infant neglect was explored. There were three main findings. First, infants born to mothers with ACEs experienced higher levels of neglect compared to those born to mothers without ACEs. Second, infants born to mothers with three or more subtypes of ACEs experienced the greatest levels of neglect, with maternal childhood physical neglect emerging as a particularly influential factor. Third, infants in the “median maternal ACEs” and “high maternal neglect and poor peer relationship” groups experienced more severe neglect than those in the “low maternal ACEs” group. These results suggest that early life experiences substantially shape future parenting behaviors, such as infant neglect.

Keywords

neglect child abuse bullying

Neglect, the most common form of maltreatment (Dubowitz, 2007; Hussey et al., 2006), refers to specific incidents and a repeated pattern of failure by a parent or other caregiver to ensure the development and well-being of a child. In 2015, 26.0% of children in China experienced neglect (Fang et al., 2015), which was higher than the prevalence of other types of maltreatment. Although incidents of child neglect are not uncommon, the problem has been disproportionately understudied compared to child abuse (Stoltenborgh et al., 2013). Researchers in family and child development are often surprised to learn that the consequences associated with child neglect are at least as severe as those associated with abuse (Gilbert et al., 2009; Humphreys et al., 2020). Relative to physically abused children, neglected children exhibit lower cognitive and learning abilities, increased social withdrawal, limited peer interactions, and heightened internalizing problems (Hildyard & Wolfe, 2002). Given the high rates and severe consequences of child neglect, many researchers have called for more careful investigations of this subtype of maltreatment.

The neglect of the youngest children (ages 0–1) is an area that has received scarce attention. For infants, neglect signifies more severe adversity, as neglect in this sensitive period may disrupt neuronal architecture and limit overall brain growth (De Bellis, 2005), altering their lifelong developmental trajectories (Rayce et al., 2017). Furthermore, due to their immature systems (Lyons-Ruth et al., 2017), infants rely more heavily on caregivers for fundamental care than older children. As a result, neglect during infancy can be not only devastating but pose life-threatening risks. Public health interventions aimed at early prevention of neglect, starting in infancy, are necessary to protect children’s health.

Maternal ACEs and Infant Neglect

Identifying the causes and risk factors that influence vulnerability to neglect is crucial for effectively implementing preventive measures. Given that mothers are typically the primary source of nutrition and the closest caregivers for infants, maternal characteristics are likely to have the most direct and profound impact on infants. Having a mother who has been maltreated is the single most important risk factor for subsequent child maltreatment (Assink et al., 2018; Gilbert & Lacey, 2021), a phenomenon known as the “intergenerational cycle” of trauma. In addition, the early experiences of infants and their caregivers are associated with similar negligent patterns in later parenting, especially among women; women who grew up in adverse environments (e.g., with child maltreatment) put their children at a higher risk of experiencing similar adverse environments than those who did not. Therefore, some scholars theorize that maternal childhood adversity could be a key risk factor for early infant neglect. However, to our knowledge, only one study (Dym Bartlett & Easterbrooks, 2015) has explored the association between maternal childhood maltreatment and infant neglect in young mothers (<21 years at childbirth). That study found that infants born to mothers who had experienced multiple types of maltreatment in childhood were more likely to be neglected than children whose mothers had not been maltreated. To explore this phenomenon more carefully, it is imperative to consider more detailed and broader types of maternal childhood adversity.

The adverse childhood experiences (ACEs) study reached a milestone in medical research by linking childhood experiences of abuse, neglect, and family dysfunction to future outcomes (Felitti et al., 1998). The extended ACEs assessed by ACEQ-R scale include a wide range of adversities, including emotional abuse, physical abuse, sexual assault, emotional neglect, physical neglect, mother treated violently, parental separation or divorce, household substance abuse, household mental illness, incarcerated household members, peer victimization, peer isolation/rejection, exposure to community violence, and low socioeconomic status (Finkelhor et al., 2015). These ACEs represent chaotic environments characterized by extreme daily instability, disorder, and lack of temporal and structural regularity (Lotto et al., 2021).

Comprehensive Perspectives

This study conducted a comprehensive assessment to understand the critical role of maternal childhood maltreatment in the risk of infant neglect. We explored the intergenerational transmission effects of adverse maternal childhood experiences and infant neglect from various perspectives.

First, the study estimated the association of overall maternal ACEs with child neglect by exploring whether infants born to mothers with ACEs experienced more neglect than those born to mothers without ACEs using the multiple linear regression. To yield more purified estimates of the relationships, adjustments for potential confounding factors were made using propensity score (PS) matching, which could separate the study design from outcome analysis and was accepted as a method to prevent actual or suspected bias by researchers (Benedetto et al., 2018). However, considering that PS matching would lose a lot of sample information to achieve an optimal matching effect, it was used as a complement to multiple linear regression analyses in this study.

Second, we explored the cumulative and independent effects of 14 types of maternal ACEs on infant neglect from a variable-centered perspective. ACEs studies have found evidence of a dose-response relationship between ACEs and adverse outcomes (Evans et al., 2013; Lacey et al., 2020). For example, young adults exposed to three or more ACEs had an over 15-fold increase in suicidal ideation compared to their peers exposed to zero ACE (Wang et al., 2019). These findings support the cumulative risk models, in which multiple exposures trigger worse developmental consequences than single exposures. This is the most important reason for studying exposure to childhood ACEs (Evans et al., 2013). Another reason for studying exposure to multiple risk factors is that studies on the effects of a single risk factor may generate bias in the estimates of developmental effects, particularly if a single risk factor is associated with one or more other risk factors (Evans et al., 2013). In terms of intervention, studying exposure to multiple risk factors could be beneficial in targeting interventions effectively. Identifying children with multiple risk factors is likely to reveal vulnerable individuals who should be given the highest priority for interventions (Evans et al., 2013). However, cumulative effects implicitly assume that the ACEs have the same impact on outcomes (Renner et al., 2020). For example, childhood physical neglect has the same impact on development as childhood emotional neglect and thus can obscure meaningful information about the relative importance of particular types of victimized mothers and their relationship to infant neglect. Exploring the independent effects of ACEs could complement the limitations of the cumulative effects.

Third, different patterns of maternal ACEs were identified using a people-centered approach, latent class analysis (LCA). The study then investigated the association between different patterns of maternal ACEs and infant neglect. The cumulative and independent effects from a variable-centered perspective, ignored the potential clustering of ACEs (Lacey & Minnis, 2020). Service providers would benefit from being able to identify which subgroups of maternal ACEs have the strongest associations with infant neglect. Fluke et al. (2005) pointed out that the variable-centered approach helps identify groups at risk of recurrent child maltreatment; however, isolating groups with similar trajectories might provide more valuable information. LCA allows researchers to explore ACE clusters in population samples and their differential associations with key predictors or outcomes (e.g., infant neglect; Lacey & Minnis, 2020). Several studies have identified different ACE patterns in their study populations. For example, Lacey et al. (2020) identified four ACE classes using data from the Avon Longitudinal Study of Parents and Children (ALSPAC): “Low ACEs” (81.1%), “Maternal mental health problems” (10.3%), “Maternal mental health problems and physical abuse” (6.3%), and “Parental conflict, mental health problems and emotional abuse” (2.4%).

Current Study

The aim of this study was to explore the intergenerational transmission effects of maternal ACEs and infant neglect from different perspectives. Thus, we formulated the following four hypotheses:

H1 Infants born to mothers with ACEs will experience more neglect than those born to mothers without ACEs.

H2 There will be a cumulative effect of maternal ACEs on infant neglect.

H3 The types of ACEs related to childhood maltreatment will account for the strongest association with infant neglect.

H4 Maternal ACE subtypes will be associated with infant neglect.

Methods

Participants and Procedures

This quantitative cross-sectional observational study was conducted between October 2020 and October 2021. The participants in the study comprised postpartum mothers and infants recruited from the outpatient department of the child health care department at a tertiary hospital in Jinan, Shandong Province, China. The study utilized the following inclusion criteria: (1) mothers who were within the first year postpartum; (2) mothers’ age ≥18 years and infants’ age ≤1 year; (3) singleton birth in the previous pregnancy; (4) gestational weeks at delivery ≥37 weeks; (5) spontaneous pregnancy without assisted reproductive technology; and (6) mothers could speak, write, communicate, and understand the information in the questionnaire. The following exclusion criteria were applied: (1) mothers with severe physical or mental diseases; (2) mothers who declined to participate in the research; or (3) infants diagnosed with severe physical diseases or congenital diseases. Of the 600 participants we approached, 583 agreed to participate in the questionnaire survey (response rate: 97.17%). After excluding incomplete or incorrectly completed questionnaires, 550 valid questionnaires were obtained. Before beginning the formal investigation, the investigator informed all participants of the study’s content, aim, potential risks, and benefits. The Ethics Committee of the authors’ school approved the study protocol (2020-R-025).

Sample Size

In the multivariate linear regression, the specified parameters included a medium effect size (f ²) of 0.15, a statistical power of 90%, a significance level of 0.05, and an estimated number of 23 predictor variables. G*power calculated the minimum sample size as 202; the minimum sample size required to account for an approximately 10% non-response rate (the proportion of responses in a survey for which the surveyor was unable to obtain valid information) was 237. A minimum sample size of 300 empirically was required to identify the optimal number of latent class models. Considering an approximately 10% non-response rate, the minimum sample size was 334 (Nylund-Gibson & Choi, 2018). Random forest regression has a high tolerance for missing values and the advantage of being implemented in small samples. Thus, the study required a minimum sample size of 334, meaning our 550 samples were more than adequate.

Measures

Infant Neglect

The severity of neglect in infants over the past month was assessed using the Chinese version (Mao et al., 2023) of Arimoto and Tadaka’s (2021) Signs of Neglect in Infants Assessment Scale (SIGN). In this study, nurses from the outpatient department of the child health care department observed and collected relevant information on infant neglect from mothers when the infant came for a physical examination. The SIGN had three dimensions: lack of basic supervisory care, child underdevelopment, and lack of emotional behavior. The respondents rated 14 items using a 3-point Likert scale (0 = never, 1 = once, 2 = two or more times). A higher score indicated more serious neglect. The scale had good reliability and validity in the original study, with the Cronbach’s α of the total score and each dimension of SIGN greater than .8, and the GFI = .947, AGFI = .921, CFI = .959, RMSEA = .057 (Arimoto & Tadaka, 2021). In this study, Cronbach’s alpha coefficient was .848.

Maternal ACEs

The maternal ACEs were measured using the Adverse Childhood Experience Questionnaire-Revised (ACEQ-R; Finkelhor et al., 2015), which listed 14 ACEs: (1) emotional abuse, (2) physical abuse, (3) sexual assault, (4) emotional neglect, (5) physical neglect, (6) mother treated violently, (7) parental separation or divorce, (8) household substance abuse, (9) household mental illness, (10) incarcerated household members, (11) peer victimization, (12) peer isolation/rejection, (13) exposure to community violence, and (14) low socioeconomic status. The mother’s experiences with the 14 items, as follows, were scored: yes = 1, no = 0. A higher total ACEQ-R scores indicated the presence of multiple types of ACEs. Wang et al. (2018) validated the Chinese version of the ACEQ-R. The Cronbach’s alpha coefficient of the scale in this study was .722.

Covariates

The following demographic information was obtained from the participants: maternal age, maternal body mass index (BMI), baby’s age, maternal parity, maternal occupation, household income, maternal education level, parental support from older parents, and whether they experienced breastfeeding difficulty.

Statistical Analyses

Statistical analyses were conducted using IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA), R version 4.1.3 (R Core Team, 2018), and Mplus, Version 8.3 (Muthén & Muthén, 1998–2017). A two-tailed significance level of 5% was set for all statistical tests. Descriptive statistics, including frequencies (percentages) and mean ± standard deviations, were used to describe the distribution of the participants’ demographic characteristics. Missing data were addressed through multiple imputations using R 4.1.3. All analyses controlled for the participants’ demographic characteristics, including maternal age, maternal BMI, baby’s age, maternal parity, maternal occupation, household income, maternal education level, parental support from older parents, and whether they experienced breastfeeding difficulty.

Assessing the Association of Overall Maternal ACEs With Infant Neglect

First, a multiple linear regression model was conducted to explore the association between overall maternal ACEs and infant neglect, while the independent variable was a dichotomous variable (0 = without ACEs, 1 = with ACEs). Next, we adjusted for potential confounding factors using PS matching to obtain more accurate estimates of the relationships. Specifically, we used PS matching to adjust for maternal age, maternal BMI, baby’s age, maternal parity, maternal occupation, household income, maternal education level, parental support from older parents, and breastfeeding difficulty, and the logistic regression with ACEs (with or without) as the dependent variable was conducted, with the caliper value (defined as the acceptable range for PS differences between two individuals, with a larger caliper value allowing for a broader range of successful matches) set at 0.003. Utilizing a 1:1 matching aimed to achieve the most balanced mean covariate values between the two groups; evidence shows that 1:1 matching reduces bias in the estimated effect more effectively than 1: n matching (Austin, 2010).

Assessing the Cumulative and Independent Effects of 14 Types of Maternal ACEs on Infant Neglect

To assess the cumulative effect, the multiple linear regression analysis was performed using the cumulative total scores (continuous variable) and cumulative categorical index (categorical variable) as the independent variables and infant neglect as the dependent variable. We calculated the cumulative total ACE scores and categorical indices by summing the number of ACEs (continuous variable: 0–14; categorical variable: 0, 1, 2, 3+). To assess the independent effect (infant neglect as the dependent variable and 14 types of maternal ACEs as the independent variables), multiple linear regression and random forest models were performed. Multivariable (MV) models are the most common approach for identifying the strength of the relationships between these variables. However, given the possible nonlinear relationship between maternal ACEs and infant neglect (Tung et al., 2020), as well as the potential multicollinearity between different types of ACEs (Herrenkohl & Herrenkohl, 2009; Renner et al., 2020), MV models’ ability to detect a valid association may be compromised. Therefore, random forests were employed to evaluate the relative contributions of different types of maternal ACEs to infant neglect as a complement to MV models. As a machine learning method, the random forest technique has some unique advantages, including not considering multicollinearity between independent variables and not requiring a linear relationship between independent and dependent variables (De Francesco et al., 2021). Random forest models were executed with parameters set at 10 for mtry and 1,000 for ntree. The percentage of increase in mean squared error (%IncMSE) was used to measure the importance of the different maternal ACEs (higher %IncMSE values indicate higher importance). Additionally, because random forests cannot provide significance estimates, it was necessary to combine MV models with random forests to assess the independent impact of ACEs on infant neglect comprehensively. Given that only one mother reported the experience of household substance abuse, this type of ACE was therefore excluded from the independent effect analysis.

Assessing the Association Between Different Patterns Maternal ACEs and Infant Neglect

LCA was employed to identify the different patterns of maternal ACEs, applying the Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted Bayesian information criterion (aBIC) to select the optimal class solution (lower values indicate a better model fit; Burnham & Anderson, 2004). Entropy values greater than 0.80 indicate good classification discrimination; the closer the value is to 1.00, the better (Berlin et al., 2014). The significant values of the Vuong–Lo–Mendell–Rubin likelihood ratio test (LMRT) and the bootstrapped likelihood ratio test were employed to evaluate whether the k-class solution was superior to the k-1 class (Nylund et al., 2007). After determining the optimal class solution, the relationship between potential patterns of ACEs and infant neglect was explored.

Results

Sample Characteristics

Table 1 presents the sample’s demographic characteristics. Overall, most of the infants were 10–12 months old (54.50%), and most of the mothers were 25–34 years old (74.00%), multipara (54.90%), and had a bachelor’s degree or above (63.09%). Regarding the other characteristics, 145 mothers (26.40%) did not work outside the home; 360 (65.50%) of the mothers had a household income of more than 6,000 Chinese Yuan (CNY) per month; 480 mothers (87.30%) had parental support from older parents; and 122 (22.20%) mothers experienced breastfeeding difficulty.

Table1.

Characteristics of the Study Variables (N = 550).

Characteristics	n	%
Baby’s age, month
0–3	45	8.20
4–6	84	15.30
7–9	120	21.80
10–12	300	54.50
Unknown/missing	1	0.20
Maternal age (years)
≤24	33	6.00
25–29	192	34.90
30–34	215	39.10
≥35	103	18.70
Unknown/missing	7	1.30
Maternal body mass index
Underweight	52	9.50
Normal	302	54.90
Overweight	120	21.80
Obese	36	6.50
Unknown/missing	40	7.30
Maternal parity
Primipara	248	45.10
Multipara	302	54.90
Maternal occupation
Yes	373	67.80
No	145	26.40
Unknown/missing	32	5.80
Maternal education level
High school or less	198	36.00
Undergraduate or above	347	63.09
Unknown/missing	5	0.91
Household income, month (CNY)
<6,000*	175	31.80
≥6,000	360	65.50
Unknown/missing	15	2.70
Breastfeeding difficulty
Not difficult	424	77.10
Difficult	122	22.20
Unknown/missing	4	0.70
Parental support from older parents
Yes	480	87.30
No	67	12.20
Unknown/missing	3	0.50
Maternal ACEs, kinds
0	406	73.8
1+	144	26.2
SIGN (no. of kinds)
0	98	17.82
1	115	20.91
2	178	32.36
3	159	28.91

Note. SIGN = Signs of Neglect in Infants Assessment Scale.

6000 CNY = approximately 836 USD.

Assessing the Association of Overall Maternal ACEs With Infant Neglect

Multivariate Regression

After adjusting for sociodemographic characteristics, mothers with maternal ACEs were more likely to indicate that they were neglecting their infants (B = 2.168, p < .001).

PS Matching

There were 550 and 194 participants before and after PS matching, respectively. After PS matching, the variables baby’s age, maternal age, maternal BMI, maternal parity, maternal occupation, maternal education level, household income, breastfeeding difficulty, and parental support from older parents were statistically similar between the ACEs and non-ACEs groups (see Supplemental A). After PS matching, mothers with maternal ACEs were more likely to indicate that they were neglecting their infants (B = 2.268, p < .001), even after we controlled for the propensity score (B = 2.267, p < .001; see Table 2 and Supplemental B).

Table 2.

Relationship Between the Maternal Adverse Childhood Experiences and Infant Neglect Global Scores After PSM (n = 194).

Dependent Variable	B	Beta	t	p
SIGN
Model1*	2.268	.255	3.662	<.001
Model2*	2.267	.255	3.727	<.001

Note. SIGN = Signs of Neglect in Infants Assessment Scale.

PS score was not controlled in Model 1 and controlled in Model 2.

Assessing the Cumulative and Independent Effects of 14 Types of Maternal ACEs on Infant Neglect

Cumulative Effect

When the model used the ACE cumulative total scores as an independent variable, each unit increase in the global ACE scores was significantly related to a 0.892 unit change in infant neglect (B = 0.892, p < .001). Likewise, when the model used the ACEs cumulative categorical index as an independent variable, mothers with one subtype of ACE were no more likely to report infant neglect than those without ACEs. Compared to mothers without any ACEs, the magnitudes of increase in the infant neglect scores for mothers with only one subtype of ACE, two subtypes of ACEs, and three or more subtypes of ACEs were 0.613, 3.182, and 3.546, respectively; the increase in mothers with only one subtype of ACE was not significant (see Table 3 and Supplemental C).

Table 3.

Association between Cumulative ACEs Categorical Index and Infant Neglect Global scores (N = 550).

Number of ACEs*	B	SE	t	p
1	0.613	0.519	1.183	.238
2	3.182	0.618	5.148	<.001
3+	3.546	0.631	5.616	<.001

Note. ACEs = adverse childhood experiences.

With the absence of adversity as a reference.

Independent Effect

In the multiple linear regression model, physical neglect (B = 2.409, p = .013) and exposure to community violence (B = 2.335, p = .034) were positively associated with infant neglect (see Table 4 and Supplemental D). We performed random forest regression models on the five sets of data after multiple imputations using the mean of squared residuals and R² as metrics to select the best model for the variable importance measure analysis; the smaller mean of squared residuals and larger R² indicate a better model fit; see Supplemental E). The results showed that peer isolation/rejection, physical neglect, physical abuse, emotional neglect, and exposure to community violence had strong contributions to infant neglect, especially peer isolation/rejection and physical neglect. Combining the results of the MV model, maternal childhood experiences of physical neglect exhibited the closest association with infant neglect within this sample. In addition, this study found that breastfeeding difficulty had a large contribution to infant neglect. Figure 1 shows the maternal ACEs sorted according to their importance.

Table 4.

Independent Effect of Maternal ACEs on Infant Neglect (N = 550).

Maternal ACEs	B	SE	t	p
Emotional abuse	0.301	0.570	0.527	.598
Physical abuse	1.645	1.020	1.613	.107
Sexual assault	3.495	2.225	1.571	.117
Emotional neglect	1.172	0.729	1.608	.109
Physical neglect	2.409	0.968	2.490	.013
Mother treated violently	−2.108	1.277	−1.651	.099
Parental separation or divorce	−1.271	1.601	−0.794	.427
Household mental illness	1.389	1.044	1.330	.184
Incarcerated household member	0.913	1.747	0.523	.601
Peer victimization	0.636	1.319	0.482	.630
Peer isolation/rejection	1.190	0.709	1.679	.094
Exposure to community violence	2.335	1.100	2.123	.034
Low socioeconomic status	0.589	0.771	0.764	.445

Note. ACEs = adverse childhood experiences.

Associations Between the Maternal ACE Patterns and Infant Neglect

After fitting LCA models with one to three classes, we selected a three-class solution, as this model showed the best fit (see Supplemental F). Figure 2 shows the clusters of maternal ACE subtypes within each class among mothers. Class 1 (N = 22/550, 4.0%) was characterized by a high probability of emotional and physical neglect and peer isolation or rejection, termed the “high maternal neglect and poor peer relationship” group. Class 2 (N = 71/550, 12.9%) was characterized by a median probability of all the different maternal ACEs and designated as the “median maternal ACEs” group. The largest group, class 3 (N = 457/550, 83.1%), was characterized by a low probability of all the different maternal ACEs, identified as the “low maternal ACEs” group.

We conducted multivariate linear regression analyses to examine the relationship between the different subtypes and infant neglect (see Table 5 and Supplemental G). With the “low maternal ACEs” group as the reference, the magnitudes of increase in the infants’ neglect global scores for the “median maternal ACEs” and “high maternal neglect and poor peer relationship” groups were 2.417 and 4.447, respectively.

Table 5.

Association Between Different Maternal ACE Subtypes and Infant’s Neglect Global Scores (N = 550).

ACE Subtypes	B	SE	t	p
Median maternal ACEs group*	2.417	0.484	4.997	<0.001
High maternal neglect and poor peer relationship group	4.447	0.853	5.215	<0.001

Note. ACEs = adverse childhood experiences.

With the “low maternal ACEs” group as a reference.

Discussion

Summary of Main Findings

Our study, the first to examine the association between maternal ACEs and infant neglect from different perspectives, produced three primary findings, discussed in detail below: (1) infants born to mothers with ACEs experienced more neglect than those born to mothers without ACEs; (2) infants born to mothers with three or more subtypes of ACEs experienced the most neglect, both the multivariate linear and random forest models showed that maternal childhood physical neglect exhibited the closest association with infant neglect, and (3) applying LCA to the ACEs data revealed that mothers in the “median maternal ACEs” and “high maternal neglect and poor peer relationship” groups engaged in high levels of infant neglect than mothers in the “low maternal ACEs” group.

Relationship Between Overall Maternal ACEs and Infant Neglect

Infants born to mothers with ACEs demonstrated a higher prevalence of neglect compared to those born to mothers without ACEs, supporting the “intergenerational cycles” of the trauma paradigm. It may be that maternal ACEs, such as having a history of maternal childhood abuse, might impair the ability to show empathy and sensitivity (Mielke et al., 2016). An infant’s distress might also trigger maternal fear responses re-experienced as conflicting feelings and emotions, resulting in a hostile or helpless response to the infant’s needs that manifests as neglect (Amos et al., 2011). ACEs are particularly prominent during particular life stages, such as the perinatal period. The intimate nature of perinatal experiences associated with pregnancy, childbirth, and lactation can trigger memories of early traumatic experiences (Chamberlain et al., 2019). Mothers with ACEs are more likely to face multiple socioeconomic challenges, including unwanted pregnancy (Drevin et al., 2020), perinatal depression (Abe et al., 2022), and interactions with the justice system (Dierkhising et al., 2013), which could expose infants to adverse environments from birth, resulting in increased neglect.

Cumulative and Independent Effects of 14 Types of Maternal ACEs on Infant Neglect

The infant neglect scores reflected varying effects among the different ACEs, both cumulatively and individually. The cumulative scores helped us determine the dose-response relationship of the ACEs. As an independent field, childhood adversity can reveal the unequal association of different ACEs with infant neglect. For example, the multivariate linear model and random forest model showed that maternal childhood physical neglect exhibited the closest association with infant neglect. This evidence suggests that we cannot truly understand cumulative childhood adversity as just a series of identical adverse experiences. This study supported the homotypic transmission of child maltreatment—that is, the maintenance of specific types of child maltreatment practices (Lotto et al., 2021). For example, mothers who suffered neglect as children were more likely to practice the same harmful parenting practices with their children. The opposite, heterotypic transmission, refers to when someone who suffered a particular type of maltreatment in childhood later perpetrates a different type of maltreatment on their own children. Our findings suggest that mitigating types of ACEs that practitioners and policymakers have traditionally considered high priorities, such as physical neglect, could reduce the intergenerational transmission of trauma.

The findings of this study indicated that childhood peer isolation may increase the risk of infant neglect. Mother’s childhood experience of peer isolation or rejection might influence the construction of her social support system, correlating with lower levels of social support in adulthood. A recent review highlighted the buffering effect of social support on child maltreatment. Enhancing social support had the potential to mitigate the intergenerational transmission of neglect, ultimately decreasing the risk of infant victimization in the home environment (Scheuplein et al., 2023). Moreover, the study found that breastfeeding difficulty had a large contribution to infant neglect. Breastfeeding has the potential to enhance maternal responsiveness through the stimulation of oxytocin release, a hormone linked to decreased anxiety, improved mood, and a dampened physiological stress response (Strathearn et al., 2009). Mothers facing breastfeeding contraindications or susceptibility to feeding challenges may experience heightened physiological stress responses, influencing their interaction and emotional communication with their infants, potentially resulting in infant neglect.

Associations Between the Different Maternal ACE Patterns and Infant Neglect

Using LCA, three different patterns (groups) of maternal ACEs were identified: “high maternal neglect and poor peer relationship” group, “median maternal ACEs,” and “low maternal ACEs”. Mothers in the “median maternal ACEs” and “high maternal neglect and poor peer relationship” groups exhibited higher levels of infant neglect than those in the “low maternal ACEs” group. Studies applying LCA to ACEs data always find a low ACEs class (Lacey et al., 2020). However, we found a unique class characterized by high levels of neglect and high levels of peer bullying, which were correlated with the highest increase in infant neglect levels, emphasizing that the combination of maternal childhood neglect and peer isolation/rejection might increase the risk of infant neglect.

Limitations

The measures of maternal ACEs were limited to retrospective self-reports, as we could not follow mothers prospectively during their childhoods; thus, there might have been some recall bias. However, some studies have found that adults’ retrospective recall of early life experiences was reliable (Dube et al., 2004). Second, the measurement of infant neglect was collected by different nurses without an inter-rater reliability test. Third, this study recruited all the participants from a single tertiary hospital in Jinan, Shandong Province, China, whose patients were mostly in a relatively high socioeconomic cohort. Thus, the findings might not be generalizable to women in other cities or provinces, in other socioeconomic situations, or in demographics where abuse is more (or less) common. Fourth, as with all ACEs studies, the present research cannot make causal claims. Fifth, we did not collect information on factors such as whether the mother had a partner involved in raising the child or whether the child experienced colic. These variables could potentially be associated with or impact child neglect.

Conclusions

This study focused on neglect during infancy and examined the association between maternal ACEs and infant neglect from different perspectives. The findings supported the view that early life experiences significantly affect the individuals’ well-being and future parenting behaviors; ACEs often perpetuate the cycle of trauma. Understanding how maternal ACEs can impact infant neglect could help us develop support programs for mothers who were victimized as children (especially those who experienced physical neglect and peer isolation/rejection) to help them heal so they can raise the next generation of children with healthier parenting practices. In addition, formulating intervention programs to alleviate physical neglect in the current generation and diminish the risk factors responsible for it, such as that stemming from financial constraints, has the potential to reduce the perpetuation of intergenerational trauma. Importantly, transitioning to parenthood during the perinatal period provides a unique life-course opportunity for improving health and relationships. Understanding which positive perinatal forces could break the vicious cycle of intergenerational trauma should be an essential focus for future research.

Supplemental Material

sj-docx-1-jiv-10.1177_08862605241248437 – Supplemental material for Role of Maternal Adverse Childhood Experiences on Infant Neglect: A Multi-Perspective Approach

Supplemental material, sj-docx-1-jiv-10.1177_08862605241248437 for Role of Maternal Adverse Childhood Experiences on Infant Neglect: A Multi-Perspective Approach by Xuan Zhang, Yiping Xiao, Fangxiang Mao, Zhaojuan Xu and Fenglin Cao in Journal of Interpersonal Violence

Footnotes

Author Contributions

Fenglin Cao contributed to the design of the study. Xuan Zhang carried out the manuscript preparation and analysis of data. Yiping Xiao performed the analysis of data and interpreted the data. Fangxiang Mao and Zhaojuan Xu carried out the data collection and interpreted the data. All the authors have approved the final draft.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Surface Project of the National Natural Science Foundation of China (Grant Number: 32071084) and the Fundamental Research Funds for the Central Universities (Grant Number: 2022JC016).

ORCID iDs

Fangxiang Mao

Fenglin Cao

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Xuan Zhang, PhD, is a postdoctoral researcher at the School of Nursing and Rehabilitation, Shandong University. Her research focused on perinatal mental problems and their relationship with maternal and children’s health. She is interested in exploring the mechanism of maternal mental health problems using an intervention study design.

Yiping Xiao, Bachelor of Science, is a postgraduate student at the School of Nursing and Rehabilitation, Shandong University. Her research focused on the relationship between maternal stress and children’s health. She is interested in exploring the risk prediction model of the neurodevelopment disorders among infant using a cohort study design.

Fangxiang Mao, PhD candidate, is a postgraduate student of Erasmus Medical Center. Her research focused on perinatal mental problems, child maltreatment, and their relationship with maternal and children’s health. She is interested in exploring the mechanism of maternal and children’s mental health problems by using data mining

Zhaojuan Xu, Master of Medicine, head of the nurse in the pediatric department of the Second Hospital of Shandong University, has worked in the department for more than 20 years and had rich clinical practices and experiences. She is interested in exploring the way of providing care of high quality to mothers and their infants.

Fenglin Cao, PhD, is a professor at the School of Nursing and Rehabilitation, Shandong University. Her research focused on perinatal mental problems and their relationship with maternal and children’s health. With support from multidisciplinary collaboration, she has established a systematic research frame, which combines birth cohorts, experimental labs, and intervention protocols together.

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