Childhood Abuse and Cognitive Function in a Large Cohort of Middle-Aged Women

Abstract

Cognitive function at middle age is of particular public health interest, as it strongly predicts later dementia. Children who have experienced abuse subsequently have worse cognitive function than those who have not. However, it remains unclear whether the association of abuse with cognitive function persists into middle age. In 2014–2016, 14,151 women ages 49–69 years who had previously responded to a childhood abuse questionnaire completed a cognitive battery. In models adjusted for childhood socioeconomic status and head trauma, combined physical, emotional, and sexual abuse was associated with lower scores on both Learning/Working Memory (severe abuse, lower scores similar to that observed in women 4.8 years older in our data) and Psychomotor Speed/Attention (severe abuse, lower scores similar to that observed in women to 2.9 years older in our data). Adjustment for adulthood socioeconomic status and health factors (e.g., smoking, hypertension) slightly attenuated associations. In exploratory analyses further adjusted for psychological distress, associations were attenuated. Women exposed versus unexposed to childhood abuse had poorer cognitive function at mid-life. Associations were particularly strong for learning and working memory and were not accounted for by adulthood health factors. Childhood abuse should be investigated as a potential risk factor for cognitive decline and dementia in old age.

Keywords

childhood sexual abuse cognitive development cohort studies emotional/psychological maltreatment psychopathology public health

Cognitive function at middle age and older is of particular public health interest, as it is a strong predictor of subsequent dementia (Crooks et al., 2008; Elias et al., 2000; Kawas et al., 2003; Linn et al., 1995; Tierney et al., 2005), as well as a risk factor for decline in physical functioning (Elovainio et al., 2009) and death (Sabia et al., 2010). Lower cognitive function in later life is also associated with poorer health in a wide variety of domains (Hartanto et al., 2019; Shah et al., 2013; Wu et al., 2008), possibly because it is associated with poorer medication management (Stilley et al., 2010), medication non-adherence (Chodosh et al., 2004; Stilley et al., 2010), lower healthcare literacy (Lee & Son, 2018), and poorer health-related coping (Kim & Kang, 2016). Childhood abuse is a common early life stressor that has been linked to reduced cognitive function. US national surveys report high lifetime occurrence of childhood physical abuse (18.1%), emotional abuse (23.9%), and sexual abuse (26.6% for females, 5.1% for males) (Finkelhor et al., 2014, 2015).

Evidence from human and animal studies indicates that dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis resulting from abuse (e.g., elevated glucocorticoids) affects brain development (Ehlert, 2013). Child maltreatment reduces hippocampus volume, increases amygdala volume, and causes alterations to the corpus callosum and neocortex (Teicher et al., 2016). These brain regions play central roles in memory, attention, emotional regulation, language, calculation, spatial reasoning, and sensory perception (Huang et al., 2015). Numerous studies of children and adolescents have found that prior experience of childhood abuse is associated with deficits in working memory, verbal episodic memory, intelligence, processing speed, and executive function (Kavanaugh et al., 2017; Masson et al., 2015; R.-Mercier et al., 2018; Su et al., 2019), with few contradictory studies (Dunn et al., 2016). However, it is largely unknown whether lower cognitive function associated with childhood abuse persists into middle age (35–65 years) or later (>65 years).

In addition to the possibility that lower cognitive function that developed in childhood may persist into adulthood, differences in cognitive function by childhood abuse exposure may also emerge in adulthood, due to adulthood exposure to cognitive risk factors. Childhood abuse leads to emotional dysregulation, poor self-esteem, ineffective coping, diminished social competence, poor self-efficacy, and impulsivity, as well as physiological dysregulation in hormonal stress response, the serotonin and oxytocin systems, and immune function (De Bellis & Zisk, 2014; Hallowell et al., 2019; McCrory et al., 2019; Sachs-Ericsson et al., 2011). Partly as a result, childhood abuse is associated with adulthood risk factors for poor cognitive function, including lower socioeconomic status (Zielinski, 2009), smoking (Debette et al., 2011; Jun et al., 2008), high body mass index (BMI) (Anstey et al., 2011), low physical activity (Felitti et al., 1998), diabetes (Gregg et al., 2000; Rich-Edwards et al., 2010), high blood pressure (Riley et al., 2010), heart disease (Lang et al., 2008; Rich-Edwards et al., 2012) and stroke (Rich-Edwards et al., 2012). Thus, it possible that lower adulthood socioeconomic status or worse adulthood health and health behaviors in persons exposed to childhood abuse could lead to cognitive decline in middle and old age, regardless whether childhood cognitive function was altered.

Studies of adults have generally found lower cognitive function in persons exposed to childhood neglect, but have not found differences in cognitive function among those exposed to physical or sexual abuse, although studies have been limited by inadequate assessments of abuse, low prevalence of reported abuse (likely reflecting inadequate assessment), or lack of measurement of abuse severity (Danese et al., 2017; Geoffroy et al., 2016; Nikulina & Widom, 2013). Only three studies have examined cognitive function in older middle age (50–65 years) or old age (>65 years) in association with childhood abuse. The largest study, the Irish Longitudinal Study on Ageing (n = 6,912), measured multiple aspects of cognitive function (e.g., visual memory, executive function) in association with retrospectively reported childhood sexual abuse and found better global cognitive function and immediate word recall in participants who reported childhood sexual abuse versus those who did not, and no differences in other cognitive measures (Feeney et al., 2013). However, possible reporting bias was suggested by the unexpected association of abuse with higher childhood and adulthood socioeconomic status, which may be due to greater willingness to acknowledge abuse among persons with higher socioeconomic status in this sample, particular as participants were not asked about specific acts, but rather were asked to characterize their experiences as “abuse” (e.g., “were you ever sexually abused by either of your parents?”). A second study, using a random sample of Canadians (n = 1,282), reported a prevalence of only 2% of either sexual abuse or severe physical abuse (n_exposed = 26) and found no differences in cognitive function by abuse history (Ritchie et al., 2009, 2011). Finally, a study of Aboriginal and Torres Strait Islander Australians ages 60–92 years (n = 296), found an association of abuse exposure, assessed by a composite abuse measure, with higher risk of dementia and Alzheimer’s disease (Radford et al., 2017).

In the present study, we addressed limitations in the existing literature, including few studies of older persons, inadequate measures of abuse, and lack of assessment of potentially mediating health-related factors. We used data from a large cohort of women at ages 49–69 years, with validated, multi-item measures of childhood abuse that capture a range of abuse severity. We examined the association of childhood physical, emotional, and sexual abuse with several domains of cognitive function, including simple psychomotor reaction time, attention, working memory, executive function, and learning. These domains are commonly affected in aging and in Alzheimer’s Disease, the most common form of dementia, thus are of particular relevance to our aging cohort.

We further investigated whether a possible association of childhood abuse with cognitive function was partly accounted for by adulthood socioeconomic status or adulthood cognition-related health factors, including smoking, body mass index (BMI), physical activity, and physician-diagnosed history of diabetes, high blood pressure, myocardial infarction, and stroke. Childhood abuse may also be associated with lower cognitive function in middle and old age due to risk factors that co-occur with or precede abuse (Danese et al., 2017), including low parental educational attainment, low childhood socioeconomic status, and childhood head trauma. We therefore conducted analyses adjusted for these factors, as well as sensitivity analyses restricted to participants with high childhood socioeconomic status.

In addition, psychological distress, including depression and posttraumatic stress disorder (PTSD), has been associated with lower cognitive function (Diniz et al., 2013; Sumner et al., 2017), and is more prevalent in persons exposed to childhood abuse (Lindert et al., 2014). However, the relation between psychological distress and cognitive function in adulthood is complex, as risk of distress is greater in persons with lower cognitive function or cognitive decline (David et al., 2008; Gilbertson et al., 2006; Kremen et al., 2007). In addition, depression, PTSD, and reduced cognitive function could be common consequences of child-abuse-related brain alterations (Saleh et al., 2017). Finally, there is evidence that depression is an early indicator, or prodromal feature, of cognitive decline leading to dementia (Bennett & Thomas, 2014; Brommelhoff et al., 2009). We therefore conducted exploratory analyses examining the association of childhood abuse with cognitive function further adjusted for adulthood depression and PTSD symptoms, and separately among women who did not have probable depression or PTSD symptoms.

We hypothesized that childhood abuse would be associated with worse cognitive function, and that women exposed to the most severe abuse, especially women who experienced high levels of physical, emotional, and sexual abuse, would have the poorest cognitive function.

Methods

Participants

The Nurses’ Health Study II enrolled 116,429 female U.S. nurses in 1989 and has followed them with biennial health questionnaires (Bao et al., 2016). In 2001, a supplemental violence questionnaire queried experiences of childhood abuse. From 2014 to 2016, 40,082 women who had returned the violence questionnaire and a follow-up questionnaire, and with known email addresses, were invited to complete an online cognitive battery. 14,151 women completed this assessment (35% response rate). Exposure to childhood abuse was similar in cognitive battery responders and non-responders: 22.9% of both responders and non-responders experienced severe physical/emotional abuse, and 9.2% of non-responders versus 9.8% of responders experienced moderately frequent or frequent sexual abuse. Prior comparisons of responders and non-responders to the cognitive battery have found them extremely similar in age, childhood and adulthood socioeconomic indictors, and health behaviors, including smoking, BMI, and physical activity (Sumner et al., 2017). The study protocol was approved by the institutional review board of the Brigham and Women’s Hospital. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Measures

Cognitive function

Cognitive function was measured in 2014–2016 using a self-administered online battery, the Cogstate Brief Battery (Fredrickson et al., 2010). The Cogstate Brief Battery is sensitive to cognitive impairment associated with aging and neurodegenerative conditions. Scores differentiate healthy persons from those with mild cognitive impairment and Alzheimer’s Disease (Lim et al., 2012; Maruff et al., 2009), and predict Alzheimer’s Disease pathology in non-cognitively impaired persons (Darby et al., 2011). The Cogstate Brief Battery includes four tasks designed to assess simple psychomotor reaction time, attention, working memory, learning, and executive function. Each Cogstate task involves a response to a playing card initially displayed face down on a green background. The Detection task, which captures reaction time and measures psychomotor function, requires the respondent to press the “Yes” key as soon as the card is turned face up. The Identification task, a choice reaction time task which measures visual attention, executive function, and vigilance, requires a “Yes” response if the card is red and a “No” response if the card is black. The One Card Learning task, which measures visual learning and memory, requires the respondent to press “Yes” if the card has appeared in the test previously and “No” if it has not. The One-back task, which measures working memory, attention, and executive function, requires the respondent to press “Yes” if the card is the same as the previous card. Following published guidelines (Hammers et al., 2012), we log₁₀ transformed mean response times for correct trials for the Detection, Identification, and One Back tasks, and arcsine transformed the square root of the proportion of correct responses for the One Card Learning task. We then standardized scores on individual tasks and summed the resulting z-scores to create two composite scores.

Research suggests that composites formed from scores on Cogstate tasks may be more sensitive measures of cognitive function than individual task scores (Lim et al., 2013; Maruff et al., 2013); this approach is consistent with neuropsychological models that highlight the benefit of using composite scores in clinical research (Crane et al., 2008; Nuechterlein et al., 2008). Following this prior work, the One Card Learning and One Back scores were summed to create a Learning/Working Memory composite, and the Detection and Identification scores were summed to create a Psychomotor Speed/Attention composite. The Cogstate has good test-retest reliability (coefficient of variation range = 0.01–0.09 for the 4 tasks) (Fredrickson et al., 2010), construct validity, and criterion validity (Hammers et al., 2012). The composite scores also have good test-retest reliability across 4 months (Learning/Working Memory, intra-class correlation [ICC] = 0.95; Psychomotor Speed/Attention, ICC = 0.90) (Maruff et al., 2013). The composite scores are sensitive indicators of early cognitive deficits (Maruff et al., 2009) and discriminate persons with mild cognitive impairment and Alzheimer’s Disorder from healthy controls with moderate-to-large differences (Maruff et al., 2013).

Childhood abuse

Childhood physical/emotional abuse up to age 11 was assessed in 2001 with 5 questions from the Physical/Emotional Abuse Subscale of the Childhood Trauma Questionnaire (Bernstein et al., 1994). Frequency of experiencing cruel punishments, being yelled and screamed at, insulted, punished with a belt or other hard object, and being hit so hard it left bruises or marks were queried. Responses were summed according to scoring recommendations for the measure, and the resulting continuous variable was divided approximately into quartiles to investigate a possible dose-response relation of severity of abuse with cognitive function (Straus, 1990). Childhood sexual abuse was ascertained with four questions from the Sexual Maltreatment Scale of the Conflict Tactics Scales (Straus et al., 1998), querying unwanted or forced sexual touching up to age 11 years and at ages 11–17 years. Each question has response options: 0: never, 1: once, and 2: more than once. Points were summed across responses. Women were considered to have no sexual abuse if they responded “never” to each question. One or two points was coded as “infrequent abuse,” 3–4 points as “moderately frequent abuse,” and ≥5 points was considered “frequent” sexual abuse. As children exposed to both physical/emotional and sexual abuse may have worse health outcomes than children exposed to a single type (Finkelhor et al., 2007), following prior work (Roberts et al., 2013), we summed the two measures to create a combined physical, emotional, and sexual abuse measure. Because few women were exposed to the most severe levels of abuse, we combined the top two categories to create a measure that ranged from 0: no abuse to 5: severe combined abuse.

Demographic and health factors

Childhood socioeconomic status indicators were assessed in 2005 and included parents’ education, occupation, and home ownership. Parents’ education in participant’s infancy was coded separately for mother and father as: <9 years of school, 1–3 years high school, 4 years high school, 1–3 years college, 4 or more years college. Parents’ occupation during participant’s infancy was coded separately for mother and father as: unskilled laborer or service, blue collar (sales, service, skilled worker, machine operator, or military), farming, professional or manager, or don’t know/missing (3.2%). Parents’ home ownership in participant’s infancy was coded as yes or no. Childhood head trauma was assessed in 2001 with the question, “Have you ever suffered from head trauma with loss of consciousness?” Age of occurrence was queried. We considered any loss of consciousness before age 20 as exposure to childhood head trauma.

For adulthood demographic and health factors, we included measurements closest to the time of the cognitive assessment. Adulthood socioeconomic status was measured with three variables. Participants reported their current perceived social standing in both the community and in the U.S. in 2001 (Giatti et al., 2012). Level of education completed by spouse/partner was queried in 1999 and coded as: <high school, high school, 2-year college, 4-year college, graduate school, not applicable, or missing (2.9%). Marital status was queried in 2013. Self-identified race/ethnicity was coded as White, Black/African-American, Asian, or other races. BMI was calculated in kg/m² from self-reported height in 1989 and weight in 2013. Self-reported weight has good validity in this cohort (Rimm et al., 1990). Smoking in 2013 was coded as never, former, or current. Physical activity in 2013 was calculated from self-reported time spent per week in 10 different activities (e.g, jogging, lap swimming) and was coded as <3, 3 to <9, 9 to <18, 18 to <27, or ≥27 metabolic equivalent hours per week (METS/week). History of physician-diagnosed type 2 diabetes, high blood pressure, myocardial infarction, and stroke was queried biennially, 1989–2013. Participants were considered to have a history of these disorders if they had ever endorsed them. Depressive symptoms were assessed in 2013 with the Center for Epidemiologic Studies Depression Scale (CESD-10) and dichotomized, with ≥10 symptoms indicating probable depression (Andresen et al., 1994). Current PTSD symptoms were assessed in 2008 with Breslau’s Short Screening Scale for DSM-IV PTSD (Breslau et al., 1999).

Analyses

We examined the association of demographic and health factors with combined childhood physical, emotional, and sexual abuse. Next, to ascertain the association of childhood abuse with cognitive function, we fit a generalized estimating equation with a normal distribution and an identity link with each of the Learning/Working Memory and Psychomotor Speed/Attention composites as dependent variables, with: 1) childhood physical/emotional abuse; 2) childhood sexual abuse; and 3) combined physical, emotional, and sexual abuse as independent ordinal variables in separate models. The reference groups were, respectively, women who had experienced: 1) the lowest quartile of physical/emotional abuse; 2) no sexual abuse; and 3) the lowest quartile of physical/emotional abuse and no sexual abuse. To test whether more abuse was associated with worse cognitive function across the range of abuse, we calculated tests of trend by fitting models with abuse as a continuous variable. The base model adjusted for age at cognitive assessment and race/ethnicity. A second model further adjusted for potential childhood confounders, including socioeconomic indicators, e.g. parents’ education, parents’ occupation, and parents’ home ownership, and childhood head trauma. To separately examine the extent to which adulthood socioeconomic status and health factors might account for a possible association between childhood abuse and cognitive function, we fit two additional models, further adjusted for: 1) indicators of adulthood socioeconomic status, including husband’s education, the perceived social standing scales, and marital status; and 2) adulthood socioeconomic status and BMI, smoking, and exercise, and history of high blood pressure, diabetes, and myocardial infarction. Finally, we fit a model with adulthood socioeconomic status, health factors, and depressive symptoms and PTSD symptoms, and separately estimated the association of child abuse with cognitive function in the subsample of women without probable depression or PTSD symptoms.

High childhood socioeconomic status is associated with cognitively-protective environmental factors, such as high-quality schools (Quinn, 2015), low exposure to environmental pollutants (Hajat et al., 2013), and cognitively enriched home environment (Sarsour et al., 2011). High socioeconomic status may also be protective against childhood adversities such as abuse. We therefore conducted additional analyses examining associations of child abuse with cognitive function restricted to women with high childhood socioeconomic status (defined as having a parent with a 4-year college degree, or a parent employed as a manager or professional).

As cognitive decline related to aging is a well-understood phenomenon, following other studies of environmental exposures (Power et al., 2011; Weuve et al., 2009), we also report associations of child abuse with cognitive function in terms of years of age. We estimated cognitive differences associated with one additional year of age by fitting separate models for Learning/Working Memory and Psychomotor Speed/Attention with age as the independent variable, adjusted for race. Next we divided the beta estimate associated with child abuse by the beta estimate associated with 1 year of age, separately for the two cognitive composites. Models were fit using PROC GENMOD in SAS 9.4.

Results

The sample was mostly white (97.7%), with a mean age of 61.2 years (range = 49–69 years). Women who experienced higher levels of childhood physical/emotional abuse were more likely to experience frequent sexual abuse. Among women who reported severe physical/emotional abuse, 14.4% reported frequent sexual abuse, compared to 1.4% of women who reported no physical/emotional abuse. Women exposed to childhood abuse were more likely to have indicators of lower socioeconomic status in both childhood and adulthood (Table 1). For example, only 13.2% of women with no combined physical, emotional, or sexual abuse had mothers with less than high school education, while 26.9% of women with severe abuse had mothers with less than high school education. Each indicator of adulthood socioeconomic status was lower in women exposed to severe abuse versus women unexposed to abuse (e.g., 29.6% of women with no abuse had husbands with <4 years of college education, versus 33.7% of women exposed to severe abuse). In addition, women who experienced childhood abuse were far more likely to report childhood head trauma (no abuse, 5.4% versus severe abuse, 13.7%).

Table 1.

Demographic and Health Factors by Combined Physical, Emotional, and Sexual Childhood Abuse, Nurses’ Health Study II, n = 13,984.

		0: no abuse	1	2	3	4	5: severe abuse
		n = 3,668	n = 3,102	n = 2,723	n = 2,630	n = 1,122	n = 739
Age at cognitive assessment (years)	Mean (SD)	61.2 (4.7)	61.2 (4.7)	61.1 (4.6)	61.1 (4.5)	61.3 (4.4)	61.3 (4.3)
Race
White	% (n)	98.5 (3,614)	98.2 (3,047)	97.8 (2,664)	97.3 (2,558)	97.3 (1,092)	94.3 (697)
Black	% (n)	0.2 (7)	0.4 (13)	0.7 (18)	0.7 (19)	0.5 (6)	2.2 (16)
Asian	% (n)	0.8 (31)	1.1 (35)	0.9 (24)	1.2 (32)	1.3 (15)	1.8 (13)
Parental education
Mother, <high school	% (n)	13.2 (483)	16.2 (501)	18.4 (502)	19.5 (513)	23.3 (261)	26.9 (199)
Father, <high school	% (n)	19.7 (722)	23.8 (737)	25.6 (697)	27.3 (717)	29.2 (328)	34.5 (255)
Parents owned home	% (n)	53.8 (1,972)	50.7 (1,573)	50.7 (1,380)	48.2 (1,268)	47.0 (527)	48.0 (355)
Parental occupation, unskilled laborer	% (n)	9.2 (336)	9.7 (302)	10.5 (286)	11.4 (301)	14.3 (160)	15.0 (111)
Childhood head trauma	% (n)	5.4 (197)	6.8 (212)	7.3 (198)	7.4 (195)	10.4 (117)	13.7 (101)
Perceived social standing in the US, 2001^†	% (n)	3.7 (1.2)	3.8 (1.3)	3.8 (1.2)	3.9 (1.3)	3.9 (1.3)	4.1 (1.4)
Perceived social standing in the community, 2001^†	% (n)	3.9 (1.5)	3.9 (1.5)	4.0 (1.5)	4.1 (1.6)	4.1 (1.6)	4.3 (1.7)
Husband’s education, <4 years college, 1999	% (n)	29.6 (1,087)	31.5 (977)	31.7 (862)	30.3 (797)	30.8 (346)	33.7 (249)
Currently married, 2013	% (n)	80.4 (2,949)	79.0 (2,452)	78.2 (2,129)	75.1 (1,976)	71.3 (800)	69.6 (514)
Body mass index, 2013	% (n)
<25 kg/m²	% (n)	46.0 (1,688)	45.4 (1,408)	43.4 (1,181)	41.2 (1,084)	37.3 (419)	34.1 (252)
25 to <30 kg/m²	% (n)	29.8 (1,093)	28.3 (878)	29.2 (796)	29.5 (777)	29.9 (336)	28.1 (208)
≥30 kg/m²	% (n)	22.8 (837)	25.3 (786)	26.3 (715)	28.0 (736)	30.9 (347)	36.3 (268)
Smoking, 2013	% (n)
Never	% (n)	71.0 (2,603)	68.4 (2,121)	66.3 (1,804)	60.9 (1,601)	59.1 (663)	56.0 (414)
Former	% (n)	26.3 (966)	28.4 (880)	30.8 (838)	35.1 (924)	36.6 (411)	39.4 (291)
Current	% (n)	2.6 (95)	3.2 (98)	2.9 (79)	3.9 (102)	4.3 (48)	4.5 (33)
Exercise, <3 metabolic equivalent hours, 2013 (METS)/week	% (n)	9.4 (345)	9.7 (302)	10.1 (275)	10.2 (269)	11.9 (134)	11.9 (88)
History of high blood pressure, 2013^†	% (n)	35.4 (1,300)	37.0 (1,149)	36.7 (999)	39.7 (1,044)	41.2 (462)	45.3 (335)
History of diabetes mellitus, 2013^†	% (n)	1.0 (36)	1.3 (40)	1.0 (28)	1.2 (32)	2.0 (23)	2.3 (17)
History of myocardial infarction, 2013^†	% (n)	6.0 (221)	6.7 (208)	6.7 (182)	6.5 (172)	9.7 (109)	9.6 (71)
History of stroke, 2013^†	% (n)	1.0 (37)	1.0 (31)	1.3 (36)	1.5 (40)	1.5 (17)	1.8 (13)

^† Perceived social standing indicates subjective social standing in the US and the community. Smaller values indicate higher social standing. Women were considered to have a history of high blood pressure, diabetes mellitus, myocardial infarction, or stroke prior to the cognitive testing if they reported these conditions on any of the biennial questionnaires, 1989–2013.

Women with versus without histories of childhood abuse had higher prevalence of cognition-related health risk factors in adulthood. For example, 36.3% of women severely abused had BMI ≥ 30 kg/m², indicating obesity, versus 22.8% of women with no abuse history (Table 1). Women with severe abuse versus those with no abuse had higher prevalence of smoking (4.5% versus 2.6%), low physical activity (11.9% versus 9.4%), and history of physician-diagnosed high blood pressure (45.3% versus 35.4%), diabetes (2.3% versus 1.0%), and myocardial infarction (9.6% versus 6.0%).

In models adjusted for age and race, moderate and severe physical/emotional abuse were associated with lower scores on the Learning/Working Memory composite (p-trend < 0.0001, Table 2, Model 1a). Further adjustment for childhood socioeconomic status and childhood head trauma slightly attenuated these associations, although they remained strong (age and race adjusted, β-estimate_{severe abuse}= −0.10, 95% CI = −0.14, −0.05; further adjusted, β-estimate_{severe abuse}= −0.09, 95% CI = −0.13, −0.05, p-trend < 0.0001, Table 2, Model 2a). Each additional year of age was associated with lower Learning/Working Memory scores (β-estimate = −0.03) and lower Psychomotor Speed/Attention scores (β-estimate = −0.04). In models adjusted for childhood socioeconomic status, severe physical/emotional abuse (the top quartile) was associated with a lower Learning/Working Memory score similar to that observed in women 3.3 years older. Moderate abuse (the third quartile) was associated with a lower score similar to that observed in women 1.6 years older. Childhood physical/emotional abuse was also associated with lower Psychomotor Speed/Attention scores, but this difference did not reach statistical significance (age and race adjusted, β-estimate = −0.03, 95% CI = −0.08, 0.03, p-trend = 0.08, Table 2, Model 1b). Further adjustment for adulthood socioeconomic status and health factors very slightly attenuated associations of child physical/emotional abuse with Learning/Working Memory, but did not change associations with Psychomotor Speed/Attention (Table 2, Models 3 & 4).

Table 2.

Association of Childhood Physical/Emotional Abuse With Cognitive Function in Middle Age (n = 13,992), Nurses’ Health Study II, 2014–2016^†.

		Physical/Emotional Abuse
Learning/working memory
	No abuse	Mild	Moderate	Severe	Test of trend
	n = 6,554	n = 2,887	n = 3,329	n = 1,222
	β coefficients
Model 1a: Age and race	0.0 [Ref]	0.01 (−0.02, 0.04)	−0.05 (−0.08, −0.02)**	−0.10 (−0.14, −0.05)***	p < 0.0001
Model 2a: + childhood factors^†	0.0 [Ref]	0.01 (−0.02, 0.04)	−0.04 (−0.07, −0.01)**	−0.09 (−0.13, −0.05)***	p < 0.0001
Model 3a: + adulthood socioeconomic indicators	0.0 [Ref]	0.01 (−0.02, 0.04)	−0.04 (−0.07, −0.01)**	−0.09 (−0.13, −0.05)***	p < 0.0001
Model 4a: + health factors	0.0 [Ref]	0.01 (−0.02, 0.04)	−0.04 (−0.07, −0.01)**	−0.09 (−0.13, −0.04)***	p < 0.0001
Model 5a: + psychological distress	0.0 [Ref]	0.01 (−0.02, 0.05)	−0.03 (−0.06, 0.00)	−0.05 (−0.10 −0.01)*	p = 0.01
Psychomotor speed/attention
	No abuse	Mild	Moderate	Severe	Test of trend
	n = 6,546	n = 2,882	n = 3,327	n = 1,217
	β coefficients
Model 1b: Age and race	0.0 [Ref]	−0.03 (−0.06, 0.01)	−0.03 (−0.07, 0.01)	−0.03 (−0.08, 0.03)	p = 0.08
Model 2b: + childhood factors^†	0.0 [Ref]	−0.02 (−0.06, 0.02)	−0.04 (−0.07, 0.00)	-0.03 (−0.08, 0.03)	p = 0.07
Model 3b: + adulthood socioeconomic indicators	0.0 [Ref]	−0.03 (−0.06, 0.01)	−0.03 (−0.07, 0.00)	−0.03 (−0.08, 0.03)	p = 0.10
Model 4b: + health factors	0.0 [Ref]	−0.03 (−0.07, 0.01)	−0.03 (−0.07, 0.00)	−0.03 (−0.08, 0.03)	p = 0.07
Model 5b: + psychological distress	0.0 [Ref]	−0.02 (−0.06, 0.02)	−0.02 (−0.06, 0.01)	0.00 (−0.06, 0.06)	p = 0.41

** p < 0.01, *** p < 0.001.

^† Childhood factors include mother’s occupation, father’s occupation, mother’s education, father’s education, parents’ home ownership in participant’s infancy and any head trauma with loss of consciousness before age 20 years. Adulthood socioeconomic indicators include husband’s education, marital status, and subjective social standing in the community and in the U.S. Health factors include smoking, BMI, physical activity, and history of physician-diagnosed hypertension, myocardial infarction, diabetes, and stroke.

Similarly, childhood moderately frequent and frequent sexual abuse were associated with lower scores on Learning/Working Memory (p-trend = 0.006) equivalent to 1.4 and 2.8 additional years of age, respectively, in models adjusted for age, race, and childhood socioeconomic status (Table 3, Model 2a). Further adjustment for childhood socioeconomic status did not notably alter associations, compared with the model adjusted only for age and race (age and race adjusted, β-estimate = −0.11, 95% CI = −0.17, −0.04; further adjusted, β-estimate = −0.10, 95% CI = −0.17, −0.04, Table 3, Model 1a). Sexual abuse was associated with lower Psychomotor Speed/Attention scores at borderline statistical significance (p-trend = 0.05, Table 3, Model 1b). Further adjustment for: 1) childhood socioeconomic status and head trauma, 2) adulthood socioeconomic status, and 3) adulthood cognition-related health factors slightly attenuated associations in women exposed to infrequent or moderately frequent abuse, but no attenuation was observed in women exposed to frequent sexual abuse (Table 3, Models 2, 3 & 4).

Table 3.

Association of Childhood Sexual Abuse With Cognitive Function in Middle Age (n = 13,982), Nurses’ Health Study II, 2014–2016^†.

		Sexual Abuse
Learning/working memory
	No abuse	Infrequent	Moderately frequent	Frequent	Test of trend
	n = 9,200	n = 3,406	n = 918	n = 458
Model 1a: Age and race	0.0 [Ref]	0.00 (−0.03, 0.03)	−0.06 (−0.11, −0.01)*	−0.11 (−0.17, −0.04)**	p = 0.001
Model 2a: + childhood factors	0.0 [Ref]	0.01 (−0.02, 0.03)	−0.05 (−0.10, −0.00)*	−0.10 (−0.17, −0.04)**	p = 0.006
Model 3a: + adulthood socioeconomic indicators	0.0 [Ref]	0.01 (−0.02, 0.03)	−0.05 (−0.10, −0.00)*	−0.10 (−0.17, −0.03)**	p = 0.008
Model 4a: + health factors	0.0 [Ref]	0.01 (−0.02, 0.04)	−0.05 (−0.09, −0.00)	−0.09 (−0.16, −0.03)**	p = 0.01
Model 5a: + psychological distress	0.0 [Ref]	0.02 (−0.01, 0.04)	−0.03 (−0.07, 0.02)	−0.05 (−0.11, 0.02)	p = 0.36
Psychomotor speed/attention
	No abuse	Infrequent	Moderately frequent	Frequent	Test of trend
	n = 9,186	n = 3,403	n = 917	n = 456
Model 1b: Age and race	0.0 [Ref]	−0.03 (−0.06, 0.01)	−0.04 (−0.10, 0.03)	−0.05 (−0.14, 0.03)	p = 0.05
Model 2b: + childhood factors^†	0.0 [Ref]	−0.02 (−0.06, 0.01)	−0.03 (−0.09, 0.03)	−0.05 (−0.14, 0.03)	p = 0.06
Model 3b: + adulthood socioeconomic indicators	0.0 [Ref]	−0.02 (−0.06, 0.01)	−0.03 (−0.09, 0.03)	−0.05 (−0.14, 0.03)	p = 0.07
Model 4b: + health factors	0.0 [Ref]	−0.02 (−0.06, 0.01)	−0.03 (−0.09, 0.03)	−0.05 (−0.13, 0.04)	p = 0.09
Model 5b: + psychological distress	0.0 [Ref]	−0.01 (−0.05, 0.02)	−0.02 (−0.08, 0.04)	−0.01 (−0.10, 0.07)	p = 0.46

** p < 0.01, *** p < 0.001.

^† Childhood factors include mother’s occuupation, father’s occupation, mother’s education, father’s education, parents’ home ownership in participant’s infancy, and head trauma with loss of consciousness before age 20 years. Adulthood socioeconomic indicators include husband’s education, and subjective social standing in the community and in the U.S. Health factors include smoking, BMI, physical activity, and history of physician-diagnosed hypertension, myocardial infarction, diabetes, and stroke. Models 4a and 5a do not include hypertension, since it is an effect modifier.

Combined childhood emotional, physical, and sexual abuse was associated with lower cognitive function on both composites in an approximately monotonic fashion, in models adjusted for age, race, and childhood socioeconomic status (p-trend < 0.001 for both, Figure 1; Supplemental Table 1, Model 2). For comparison, the Figure shows the association of one additional year of age with each composite. Severe combined abuse was associated with an effect equivalent to that observed in women 4.8 years older on the Learning/Working Memory composite (β-estimate = −0.13, 95% CI = −0.19, −0.07) and 2.9 years older on the Psychomotor Speed/Attention composite (β-estimate = −0.11, 95% CI = −0.18, −0.04). Adjustment for adulthood socioeconomic status and adulthood health very slightly attenuated associations of combined abuse with both the Learning/Working Memory and the Psychomotor Speed/Attention construct (Supplemental Table 1, Models 3 & 4).

Figure 1.

Association of combined physical, emotional, and sexual abuse with cognitive function in middle age (n = 13,975), adjusted for age, race, and childhood factors, Nurses’ Health Study II, 2014–2016. Associations of cognitive function with age were estimated in models adjusted for race.

In exploratory analyses further adjusted for adulthood depressive and PTSD symptoms, the association of physical/emotional abuse with Learning/Working Memory was attenuated yet remained statistically significant (severe abuse, β-estimate = −0.05, 95% CI = −0.10, −0.02, p < 0.05; p-trend = 0.01). The association of childhood sexual abuse with Learning/Working Memory was attenuated and no longer statistically significant. In analyses of combined physical, emotional, and sexual abuse, associations were attenuated but remained substantial (Learning/Working Memory: severe abuse, β-estimate = −0.08, 95% CI = −0.13, −0.02, p-trend = 0.004; Psychomotor Speed/Attention: severe abuse, β-estimate−0.07, 95% CI = −0.14, 0.01, p-trend = 0.01). In the subsample of women with no probable depression or PTSD symptoms (n = 8,331), child abuse was strongly associated with lower cognitive function (severe combined abuse, Learning/Working memory β-estimate = −0.09, 95% CI = −0.19, 0.00, p-trend = 0.008; Psychomotor Speed/Attention β-estimate = −0.13, 95% CI = −0.25, −0.01, p-trend=0.003, Supplemental Table 2).

In the sub-sample of women with high childhood socioeconomic status (defined as having a parent with a 4-year college degree, or a parent employed as a manager or professional, n = 5,498), associations of childhood abuse with cognitive function were similar to associations in the whole sample (severe combined abuse: Learning/Working Memory β-estimate = −0.14, 95% CI = −0.23, −0.04, p-trend < 0.0001; Psychomotor Speed/Attention β-estimate = −0.10, 95% CI = −0.22, 0.02, p-trend = 0.02).

Discussion

We found that women exposed to childhood physical, emotional, and sexual abuse had poorer cognitive function in mid-life than women without abuse exposure, with particularly strong associations with learning and working memory. We observed an approximately monotonic relationship, where women exposed to more severe abuse had lower cognitive function than women exposed to less severe abuse. Potential childhood confounders, including socioeconomic indicators and head trauma, accounted for very little of the association of abuse with cognitive function. Abuse also remained associated with lower cognitive function in the subset of women with college-educated or professional parents, suggesting that lower childhood socioeconomic status among women exposed to abuse was not driving the associations we found.

We examined a broad range of cognition-related health factors as possible mediators of the association between childhood abuse and cognitive function at middle age and found that these factors accounted for only a small part of the associations. In exploratory models further adjusted for adulthood psychological distress, associations of child abuse with cognitive function were greatly attenuated, although in the subsample of women with no significant distress, the association of abuse with cognitive function remained strong. We cannot determine from our study the extent to which: 1) child abuse causes distress that then leads to decreased cognitive function; or 2) distress and cognitive function are associated because they are common outcomes of child abuse; or 3) risk of distress is increased due to lower cognitive function in women who have experienced abuse. Nonetheless, findings in the subsample of women with no indicators of psychological distress suggest that other mechanisms aside from distress are also involved in the association.

Prior studies have similarly found poorer working memory in younger adults with child abuse histories. A meta-analysis of 17 studies (n = 1,416 persons with psychiatric disorders, mean age = 8–40 years) found the largest differences associated with childhood abuse were in working memory (g = −0.56), and the smallest in processing speed (g = −0.21), mirroring our results (R.-Mercier et al., 2018). While there is much overlap in brain regions that subserve different cognitive functions, some regions play larger roles in specific types of cognitive functions. For example, learning tasks are heavily dependent on temporal regions of the brain, while working memory and executive function (e.g., planning and coordination of actions) are more dependent on frontal cortical regions and the deeper brain structures that are linked to those, and the hippocampus contributes to both. Effects of exposures that adversely affect the brain can sometimes affect brain regions broadly, leading to more global effects on cognition. Studies examining brains of children exposed and unexposed to abuse suggest that child abuse affects many regions of the brain, including ones particularly relevant for working memory, like the prefrontal and cingulate cortices and the hippocampus, but also other regions like the temporal, parietal, and occipital lobes, amygdala, and cerebellum (De Brito et al., 2013; Hanson et al., 2010, 2012, 2013; Hart & Rubia, 2012; Teicher et al., 2012). In addition, it is not known whether brain differences related to abuse found in children persist into adulthood, as few studies have examined persons at middle age or older.

It is also possible that childhood abuse is an indicator of early life or genetic factors that lead to lower cognitive function. A study examining cognitive function at 38 years found that adjustment for maternal IQ (measured at child age 3 years) greatly attenuated the association of childhood abuse with cognitive function (Danese et al., 2017). These findings are also consistent with intergenerational transmission of childhood abuse, whereby both the mother and the child experience abuse and subsequent cognitive decrements.

Thus, childhood abuse and cognitive function in middle age may be associated through multiple pathways. First, the extreme psychological stress of childhood abuse may cause alterations to the developing brain that reduce cognitive function across the lifecourse (De Bellis, 2001; De Brito et al., 2013; Hanson et al., 2012, 2013). Second, higher prevalence of adulthood psychological distress in persons exposed to childhood abuse may lead to lower cognitive function. Third, exposure to childhood abuse and genetic risk for lower cognitive function may become correlated across generations, as parents with lower cognitive function may be more likely to be perpetrators of childhood abuse (Crandall et al., 2015; Deater-Deckard et al., 2012; Johnston et al., 2012; Mokrova et al., 2010) or children with poor cognitive function may be at elevated risk for abuse (Dubowitz et al., 2011; Jones et al., 2012; Spencer et al., 2005; Sullivan & Knutson, 2000).

Our study has several limitations. Our sample was comprised of female nurses who were predominantly white. Compared with the US population, our sample was better educated (Ryan & Bauman, 2016), less likely to smoke (Hasin & Grant, 2015), and less likely to be obese (Hales et al., 2020). Therefore, our results may not be generalizable. The response rate to the cognitive assessment was modest, although no substantive differences emerged in comparisons of responders and non-responders. Some potential adulthood mediators were collected several year prior to the cognitive assessments. Thus, we may have underestimated the extent to which adulthood factors, including socioeconomic status, health factors, depression, and PTSD, mediated the association of childhood abuse with cognitive function. Childhood abuse was queried retrospectively at ages 36–56 years; therefore, faulty recall may have lead to misclassification of abuse. However, we assessed cognitive function and childhood abuse 10 years apart, which would make priming unlikely. Thus, misclassification of abuse may be unrelated to later cognitive function; non-differential misclassification would typically bias associations toward the null hypothesis. Our study also has significant strengths. We used validated measures of child abuse in a large sample of middle-aged women. The childhood abuse measures captured sexual as well as physical and emotional abuse, and the spectrum of abuse from mild to severe. We accounted for multiple childhood and adulthood socioeconomic and health factors as potential confounders and mediators, and the cohort was large enough to enable us to examine associations in the stratum of women with high childhood SES.

We found the strongest associations between childhood abuse and the Learning/Working Memory composite. Lower scores on memory tests (Kawas et al., 2003; Tierney et al., 2005) and memory decline (Chen et al., 2001) have been particularly predictive of subsequent Alzheimer’s Disease diagnosis, compared with other cognitive measures, in prospective studies. In addition, the Cogstate working memory tasks best distinguished healthy controls from subjects with mild cognitive impairment and dementia in a validation study (Hammers et al., 2012). Together, these prior findings and the results of the present study suggest that childhood abuse should be investigated as a potential risk indicator for cognitive decline, mild cognitive impairment, and dementia in old age. Additionally, the causal structures underlying the association of childhood abuse with cognitive function, particularly regarding the role of psychological distress, must be better understood, to facilitate intervention and prevention.

Supplemental Material

Supplemental Material, sj-pdf-1-cmx-10.1177_1077559520970647 - Childhood Abuse and Cognitive Function in a Large Cohort of Middle-Aged Women

Supplemental Material, sj-pdf-1-cmx-10.1177_1077559520970647 for Childhood Abuse and Cognitive Function in a Large Cohort of Middle-Aged Women by Andrea L. Roberts, Jennifer A. Sumner, Karestan C. Koenen, Laura D. Kubzansky, Francine Grodstein, Janet Rich-Edwards and Marc G. Weisskopf in Child Maltreatment

Footnotes

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 and/or authorship of this article: National Institutes of Health (P30 ES000002, R01MH101269, U01 CA17672).

ORCID iD

Andrea L. Roberts

Supplemental Material

Supplemental material for this article is available online.

References

Andresen

E. M.

Malmgren

J. A.

Carter

W. B.

Patrick

D. L.

(1994). Screening for depression in well older adults: Evaluation of a short form of the CES-D (Center for epidemiologic studies depression scale). American Journal of Preventive Medicine, 10(2), 77–84. http://www.ncbi.nlm.nih.gov/pubmed/8037935

Anstey

K. J.

Cherbuin

Budge

Young

(2011). Body mass index in midlife and late-life as a risk factor for dementia: A meta-analysis of prospective studies. Obesity Reviews, 12(5), e426–437. https://doi.org/10.1111/j.1467-789X.2010.00825.x

Bao

Bertoia

M. L.

Lenart

E. B.

Stampfer

M. J.

Willett

W. C.

Speizer

F. E.

Chavarro

J. E.

(2016). Origin, methods, and evolution of the three nurses’ health studies. American Journal of Public Health, 106(9), 1573–1581. https://doi.org/10.2105/ajph.2016.303338

Bennett

Thomas

A. J.

(2014). Depression and dementia: Cause, consequence or coincidence? Maturitas, 79(2), 184–190. https://doi.org/10.1016/j.maturitas.2014.05.009

Bernstein

D. P.

Fink

Handelsman

Foote

Lovejoy

Wenzel

Sapareto

Ruggiero

(1994). Initial reliability and validity of a new retrospective measure of child abuse and neglect. American Journal of Psychiatry, 151(8), 1132–1136. https://doi.org/10.1176/ajp.151.8.1132

Breslau

Peterson

E. L.

Kessler

R. C.

Schultz

L. R.

(1999). Short screening scale for DSM-IV posttruamatic stress disorder. American Journal of Psychiatry, 156, 908–911.

Brommelhoff

J. A.

Gatz

Johansson

McArdle

J. J.

Fratiglioni

Pedersen

N. L.

(2009). Depression as a risk factor or prodromal feature for dementia? Findings in a population-based sample of Swedish twins. Psychology and Aging, 24(2), 373.

Chen

Ratcliff

Belle

S. H.

Cauley

J. A.

DeKosky

S. T.

Ganguli

(2001). Patterns of cognitive decline in presymptomatic alzheimer disease: A prospective community study. JAMA Psychiatry, 58(9), 853–858. https://doi.org/10.1001/archpsyc.58.9.853

Chodosh

Seeman

T. E.

Keeler

Sewall

Hirsch

S. H.

Guralnik

J. M.

Reuben

D. B.

(2004). Cognitive decline in high-functioning older persons is associated with an increased risk of hospitalization. Journal of the American Geriatrics Society, 52(9), 1456–1462. https://doi.org/10.1111/j.1532-5415.2004.52407.x

10.

Crandall

Deater-Deckard

Riley

A. W.

(2015). Maternal emotion and cognitive control capacities and parenting: A conceptual framework. Developmental Review, 36, 105–126.

11.

Crane

P. K.

Narasimhalu

Gibbons

L. E.

Pedraza

Mehta

K. M.

Tang

Manly

J. J.

Reed

B. R.

Mungas

D. M.

(2008). Composite scores for executive function items: demographic heterogeneity and relationships with quantitative magnetic resonance imaging. Journal of the International Neuropsychological Society, 14(5), 746–759.

12.

Crooks

V. C.

Lubben

Petitti

D. B.

Little

Chiu

(2008). Social network, cognitive function, and dementia incidence among elderly women. American Journal of Public Health, 98(7), 1221–1227. https://doi.org/10.2105/ajph.2007.115923

13.

Danese

Moffitt

T. E.

Arseneault

Bleiberg

B. A.

Dinardo

P. B.

Gandelman

S. B.

Houts

Ambler

Fisher

H. L.

Poulton

Caspi

(2017). The origins of cognitive deficits in victimized children: Implications for neuroscientists and clinicians. American Journal of Psychiatry, 174(4), 349–361. https://doi.org/10.1176/appi.ajp.2016.16030333

14.

Darby

D. G.

Brodtmann

Pietrzak

R. H.

Fredrickson

Woodward

Villemagne

V. L.

Fredrickson

Maruff

Rowe

(2011). Episodic memory decline predicts cortical amyloid status in community-dwelling older adults. Journal of Alzheimer’s Disease, 27, 627–637. https://doi.org/10.3233/JAD-2011-110818

15.

David

A. S.

Zammit

Lewis

Dalman

Allebeck

(2008). Impairments in cognition across the spectrum of psychiatric disorders: evidence from a Swedish conscript cohort. Schizophrenia Bulletin, 34(6), 1035–1041. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18441331

16.

De Bellis

M. D.

(2001). Developmental traumatology: The psychobiological development of maltreated children and its implications for research, treatment, and policy. Development and Psychopathology, 13(3), 539–564. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11523847

17.

De Bellis

M. D.

Zisk

(2014). The biological effects of childhood trauma. Child and Adolescent Psychiatric Clinics of North America, 23(2), 185–222. https://doi.org/10.1016/j.chc.2014.01.002

18.

De Brito

S. A.

Viding

Sebastian

C. L.

Kelly

P. A.

Mechelli

Maris

McCrory

E. J.

(2013). Reduced orbitofrontal and temporal grey matter in a community sample of maltreated children. Journal of Child Psychology and Psychiatry, 54(1), 105–112. https://doi.org/10.1111/j.1469-7610.2012.02597.x

19.

Deater-Deckard

Wang

Chen

Bell

M. A.

(2012). Maternal executive function, harsh parenting, and child conduct problems. Journal of Child Psychology and Psychiatry, 53(10), 1084–1091.

20.

Debette

Seshadri

Beiser

Himali

J. J.

Palumbo

Wolf

P. A.

DeCarli

(2011). Midlife vascular risk factor exposure accelerates structural brain aging and cognitive decline. Neurology, 77(5), 461–468. https://doi.org/10.1212/WNL.0b013e318227b227

21.

Diniz

B. S.

Butters

M. A.

Albert

S. M.

Dew

M. A.

Reynolds

C. F.

(2013). Late-life depression and risk of vascular dementia and Alzheimer’s disease: Systematic review and meta-analysis of community-based cohort studies. The British Journal of Psychiatry, 202(5), 329–335.

22.

Dubowitz

Kim

Black

M. M.

Weisbart

Semiatin

Magder

L. S.

(2011). Identifying children at high risk for a child maltreatment report. Child Abuse & Neglect, 35(2), 96–104. https://doi.org/10.1016/j.chiabu.2010.09.003

23.

Dunn

E. C.

Busso

D. S.

Raffeld

M. R.

Smoller

J. W.

Nelson

C. A.

Doyle

A. E.

Luk

(2016). Does developmental timing of exposure to child maltreatment predict memory performance in adulthood? Results from a large, population-based sample. Child Abuse & Neglect, 51, 181–191. https://doi.org/10.1016/j.chiabu.2015.10.014

24.

Ehlert

(2013). Enduring psychobiological effects of childhood adversity. Psychoneuroendocrinology, 38(9), 1850–1857.

25.

Elias

M. F.

Beiser

Wolf

P. A.

White

R. F.

D’Agostino

R. B.

(2000). The preclinical phase of Alzheimer disease: A 22-year prospective study of the Framingham cohort. JAMA Neurology, 57(6), 808–813. https://doi.org/10.1001/archneur.57.6.808

26.

Elovainio

Kivimäki

Ferrie

J. E.

Gimeno

De Vogli

Virtanen

Vahtera

Brunner

E. J.

Marmot

M. G.

Singh-Manoux

(2009). Physical and cognitive function in midlife: Reciprocal effects? A 5-year follow-up of the Whitehall II study. Journal of Epidemiology & Community Health, 63(6), 468–473.

27.

Feeney

Kamiya

Robertson

I. H.

Kenny

R. A.

(2013). Cognitive function is preserved in older adults with a reported history of childhood sexual abuse. Journal of Traumatic Stress, 26(6), 735–743.

28.

Felitti

V. J.

Anda

R. F.

Nordenberg

Williamson

D. F.

Spitz

A. M.

Edwards

Koss

M. P.

Marks

J. S.

(1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhood experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. https://doi.org/10.1016/s0749-3797(98)00017-8

29.

Finkelhor

Ormrod

R. K.

Turner

H. A.

(2007). Polyvictimization and trauma in a national longitudinal cohort. Development and Psychopathology, 19(1), 149–166. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17241488

30.

Finkelhor

Shattuck

Turner

H. A.

Hamby

S. L.

(2014). The lifetime prevalence of child sexual abuse and sexual assault assessed in late adolescence. Journal of Adolescent Health, 55(3), 329–333. http://doi.org/10.1016/j.jadohealth.2013.12.026

31.

Finkelhor

Turner

H. A.

Shattuck

Hamby

S. L.

(2015). Prevalence of childhood exposure to violence, crime, and abuse: Results from the national survey of children’s exposure to violence. JAMA Pediatrics, 169(8), 746–754.

32.

Fredrickson

Maruff

Woodward

Moore

Fredrickson

Sach

Darby

(2010). Evaluation of the usability of a brief computerized cognitive screening test in older people for epidemiological studies. Neuroepidemiology, 34(2), 65–75.

33.

Geoffroy

M. C.

Pinto Pereira

Power

(2016). Child neglect and maltreatment and childhood-to-adulthood cognition and mental health in a prospective birth cohort. Journal of the American Academy of Child and Adolescent Psychiatry, 55(1), 33–40.e33. https://doi.org/10.1016/j.jaac.2015.10.012

34.

Giatti

Camelo Ldo

Rodrigues

J. F.

Barreto

S. M.

(2012). Reliability of the MacArthur scale of subjective social status—Brazilian longitudinal study of adult health (ELSA-Brasil). BMC Public Health, 12, 1096. https://doi.org/10.1186/1471-2458-12-1096

35.

Gilbertson

M. W.

Paulus

L. A.

Williston

S. K.

Gurvits

T. V.

Lasko

N. B.

Pitman

R. K.

Orr

S. P.

(2006). Neurocognitive function in monozygotic twins discordant for combat exposure: relationship to posttraumatic stress disorder. Journal of Abnormal Psychology, 115(3), 484.

36.

Gregg

E. W.

Yaffe

Cauley

J. A.

Rolka

D. B.

Blackwell

T. L.

Narayan

K. M. V.

Cummings

S. R.

(2000). Is diabetes associated with cognitive impairment and cognitive decline among older women? JAMA Internal Medicine, 160(2), 174–180. https://doi.org/10.1001/archinte.160.2.174

37.

Hajat

Diez-Roux

A. V.

Adar

S. D.

Auchincloss

A. H.

Lovasi

G. S.

O’Neill

M. S.

Sheppard

Kaufman

J. D.

(2013). Air pollution and individual and neighborhood socioeconomic status: Evidence from the Multi-Ethnic Study of Atherosclerosis (MESA). Environmental Health Perspectives, 121(11–12), 1325–1333.

38.

Hales

Carroll

Fryar

Ogden

(2020). Prevalence of obesity and severe obesity among adults: United States, 2017–2018. Hyattsville.

39.

Hallowell

E. S.

Oshri

Liebel

S. W.

Liu

Duda

Clark

U. S.

Sweet

L. H.

(2019). The mediating role of neural activity on the relationship between childhood maltreatment and impulsivity. Child Maltreat, 24(4), 389–399. https://doi.org/10.1177/1077559519835975

40.

Hammers

Spurgeon

Ryan

Persad

Barbas

Heidebrink

Darby

Giordani

(2012). Validity of a brief computerized cognitive screening test in dementia. Journal of Geriatric Psychiatry and Neurology, 25(2), 89–99. https://doi.org/10.1177/0891988712447894

41.

Hanson

J. L.

Adluru

Chung

M. K.

Alexander

A. L.

Davidson

R. J.

Pollak

S. D.

(2013). Early neglect is associated with alterations in white matter integrity and cognitive functioning. Child Development, 84(5), 1566–1578.

42.

Hanson

J. L.

Chung

M. K.

Avants

B. B.

Rudolph

K. D.

Shirtcliff

E. A.

Gee

J. C.

Davidson

R. J.

Pollak

S. D.

(2012). Structural variations in prefrontal cortex mediate the relationship between early childhood stress and spatial working memory. Journal of Neuroscience, 32(23), 7917–7925.

43.

Hanson

J. L.

Chung

M. K.

Avants

B. B.

Shirtcliff

E. A.

Gee

J. C.

Davidson

R. J.

Pollak

S. D.

(2010). Early stress is associated with alterations in the orbitofrontal cortex: A tensor-based morphometry investigation of brain structure and behavioral risk. Journal of Neuroscience, 30(22), 7466–7472.

44.

Hart

Rubia

(2012). Neuroimaging of child abuse: A critical review. Frontiers in Human Neuroscience, 6(52). https://doi.org/10.3389/fnhum.2012.00052

45.

Hartanto

Yong

J. C.

Toh

W. X.

(2019). Bidirectional associations between obesity and cognitive function in midlife adults: A longitudinal study. Nutrients, 11(10), 2343.

46.

Hasin

D. S.

Grant

B. F.

(2015). The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) waves 1 and 2: Review and summary of findings. Social Psychiatry and Psychiatric Epidemiology, 50(11), 1609–1640. https://doi.org/10.1007/s00127-015-1088-0

47.

Huang

Song

Zhang

Jia

Xiao

(2015). Cognitive impairments associated with corpus callosum infarction: A ten cases study. International Journal of Clinical and Experimental Medicine, 8(11), 21991–21998. https://pubmed.ncbi.nlm.nih.gov/26885171 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724017/

48.

Johnston

Mash

E. J.

Miller

Ninowski

J. E.

(2012). Parenting in adults with attention-deficit/hyperactivity disorder (ADHD). Clinical Psychology Review, 32(4), 215–228.

49.

Jones

Bellis

M. A.

Wood

Hughes

McCoy

Eckley

Bates

Mikton

Shakespeare

Officer

(2012). Prevalence and risk of violence against children with disabilities: A systematic review and meta-analysis of observational studies. The Lancet, 380(9845), 899–907.

50.

Jun

H.-J.

Rich-Edwards

Boynton-Jarrett

Austin

S. B.

Frazier

A. L.

Wright

R. J.

(2008). Child abuse and smoking among young women: The importance of severity, accumulation, and timing. Journal of Adolescent Health, 43(1), 55–63.

51.

Kavanaugh

B. C.

Dupont-Frechette

J. A.

Jerskey

B. A.

Holler

K. A.

(2017). Neurocognitive deficits in children and adolescents following maltreatment: Neurodevelopmental consequences and neuropsychological implications of traumatic stress. Applied Neuropsychology: Child, 6(1), 64–78. https://doi.org/10.1080/21622965.2015.1079712

52.

Kawas

C. H.

Corrada

M. M.

Brookmeyer

Morrison

Resnick

S. M.

Zonderman

A. B.

Arenberg

(2003). Visual memory predicts Alzheimer’s disease more than a decade before diagnosis. Neurology, 60(7), 1089–1093. https://doi.org/10.1212/01.Wnl.0000055813.36504.Bf

53.

Kim

Y. J.

Kang

S. J.

(2016). Impact of cognitive function and cancer coping on quality of life among women with post-chemotherapy breast cancer. Korean Journal of Women Health Nursing, 22(3), 182–190. https://doi.org/10.4069/kjwhn.2016.22.3.182

54.

Kremen

W. S.

Koenen

K. C.

Boake

Purcell

Eisen

S. A.

Franz

C. E.

Tsuang

M. T.

Lyons

M. J.

(2007). Pretrauma cognitive ability and risk for posttraumatic stress disorder: A twin study. Archives of General Psychiatry, 64(3), 361–368. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17339525

55.

Lang

I. A.

Llewellyn

D. J.

Langa

K. M.

Wallace

R. B.

Huppert

F. A.

Melzer

(2008). Neighborhood deprivation, individual socioeconomic status, and cognitive function in older people: Analyses from the English longitudinal study of ageing. Journal of the American Geriatrics Society, 56(2), 191–198. https://doi.org/10.1111/j.1532-5415.2007.01557.x

56.

Lee

J. K.

Son

Y.-J.

(2018). Gender differences in the impact of cognitive function on health literacy among older adults with heart failure. International Journal of Environmental Research and Public Health, 15(12), 2711.

57.

Lim

Y. Y.

Ellis

K. A.

Harrington

Ames

Martins

R. N.

Masters

C. L.

Rowe

Savage

Szoeke

Darby

Maruff

The Aibl Research

(2012). Use of the cogstate brief battery in the assessment of Alzheimer’s disease related cognitive impairment in the Australian imaging, biomarkers and lifestyle (AIBL) study. Journal of Clinical and Experimental Neuropsychology, 34(4), 345–358. https://doi.org/10.1080/13803395.2011.643227

58.

Lim

Y. Y.

Pietrzak

R. H.

Ellis

K. A.

Jaeger

Harrington

Ashwood

Szoeke

Martins

R. N.

Bush

A. I.

Masters

C. L.

Rowe

C. C.

Villemagne

V. L.

Ames

Darby

Masters

C. L.

(2013). Rapid decline in episodic memory in healthy older adults with high amyloid-β. Journal of Alzheimer’s Disease, 33(3), 675–679.

59.

Lindert

von Ehrenstein

O. S.

Grashow

Gal

Braehler

Weisskopf

M. G.

(2014). Sexual and physical abuse in childhood is associated with depression and anxiety over the life course: Systematic review and meta-analysis. International Journal of Public Health, 59(2), 359–372. https://doi.org/10.1007/s00038-013-0519-5

60.

Linn

R. T.

Wolf

P. A.

Bachman

D. L.

Knoefel

J. E.

Cobb

J. L.

Belanger

A. J.

Kaplan

E. F.

D’Agostino

R. B.

(1995). The ‘preclinical phase’ of probable Alzheimer’s disease: A 13-year prospective study of the Framingham cohort. Archives of Neurology, 52(5), 485–490.

61.

Maruff

Lim

Y. Y.

Darby

Ellis

K. A.

Pietrzak

R. H.

Snyder

P. J.

Bush

A. I.

Szoeke

Schembri

Ames

Masters

C. L.

Ames

(2013). Clinical utility of the cogstate brief battery in identifying cognitive impairment in mild cognitive impairment and Alzheimer’s disease. BMC Psychology, 1(1), 30.

62.

Maruff

Thomas

Cysique

Brew

Collie

Snyder

Pietrzak

R. H.

(2009). Validity of the CogState brief battery: Relationship to standardized tests and sensitivity to cognitive impairment in mild traumatic brain injury, schizophrenia, and AIDS dementia complex. Archives of Clinical Neuropsychology, 24(2), 165–178. https://doi.org/10.1093/arclin/acp010

63.

Masson

Bussieres

E.-L.

East-Richard

R-Mercier

Cellard

(2015). Neuropsychological profile of children, adolescents and adults experiencing maltreatment: A meta-analysis. The Clinical Neuropsychologist, 29(5), 573–594.

64.

McCrory

Ogle

J. R.

Gerin

M. I.

Viding

(2019). Neurocognitive adaptation and mental health vulnerability following maltreatment: The role of social functioning. Child Maltreatment, 24(4), 435–451. https://doi.org/10.1177/1077559519830524

65.

Mokrova

O’Brien

Calkins

Keane

(2010). Parental ADHD symptomology and ineffective parenting: The connecting link of home chaos. Parenting: Science and Practice, 10(2), 119–135.

66.

Nikulina

Widom

C. S.

(2013). Child maltreatment and executive functioning in middle adulthood: A prospective examination. Neuropsychology, 27(4), 417.

67.

Nuechterlein

K. H.

Green

M. F.

Kern

R. S.

Baade

L. E.

Barch

D. M.

Cohen

J. D.

Essock

Fenton

W. S.

Frese

F. J. 3rd.

Gold

J. M.

Goldberg

Heaton

R. K.

Keefe

R. S.

Kraemer

Mesholam-Gately

Seidman

L. J.

Stover

Weinberger

D. R.

… Marder

S. R.

(2008). The MATRICS consensus cognitive battery, part 1: Test selection, reliability, and validity. American Journal of Psychiatry, 165(2), 203–213.

68.

Power

M. C.

Weisskopf

M. G.

Alexeeff

S. E.

Coull

B. A.

Spiro

Schwartz

(2011). Traffic-related air pollution and cognitive function in a cohort of older men. Environmental Health Perspectives, 119(5), 682–687. https://doi.org/10.1289/ehp.1002767

69.

Quinn

D. M.

(2015). Kindergarten Black–White test score gaps: Re-examining the roles of socioeconomic status and school quality with new data. Sociology of Education, 88(2), 120–139.

70.

R.-Mercier

Masson

Bussières

E.-L.

Cellard

(2018). Common transdiagnostic cognitive deficits among people with psychiatric disorders exposed to childhood maltreatment: A meta-analysis. Cognitive Neuropsychiatry, 23(3), 180–197. https://doi.org/10.1080/13546805.2018.1461617

71.

Radford

Delbaere

Draper

Mack

H. A.

Daylight

Cumming

Chalkley

Minogue

Broe

G. A.

(2017). Childhood stress and adversity is associated with late-life dementia in Aboriginal Australians. The American Journal of Geriatric Psychiatry, 25(10), 1097–1106.

72.

Rich-Edwards

J. W.

Mason

Rexrode

Spiegelman

Hibert

Kawachi

Jun

H. J.

Wright

R. J.

(2012). Physical and sexual abuse in childhood as predictors of early onset cardiovascular events in women. Circulation. https://doi.org/10.1161/circulationaha.111.076877

73.

Rich-Edwards

J. W.

Spiegelman

Lividoti Hibert

E. N.

Jun

H. J.

Todd

T. J.

Kawachi

Wright

R. J.

(2010). Abuse in childhood and adolescence as a predictor of type 2 diabetes in adult women. American Journal of Preventive Medicine, 39(6), 529–536. https://doi.org/S0749-3797(10)00509-X[pii]10.1016/j.amepre.2010.09.007

74.

Riley

E. H.

Wright

R. J.

Jun

H. J.

Hibert

E. N.

Rich-Edwards

J. W.

(2010). Hypertension in adult survivors of child abuse: observations from the Nurses’ Health Study II. Journal of Epidemiology and Community Health, 64(5), 413–418. https://doi.org/10.1136/jech.2009.095109

75.

Rimm

E. B.

Stampfer

M. J.

Colditz

G. A.

Chute

C. G.

Litin

L. B.

Willett

W. C.

(1990). Validity of self-reported waist and hip circumferences in men and women. Epidemiology, 1(6), 466–473. http://www.ncbi.nlm.nih.gov/pubmed/2090285

76.

Ritchie

Jaussent

Stewart

Dupuy

A.-M.

Courtet

Ancelin

M.-L.

Malafosse

(2009). Association of adverse childhood environment and 5-HTTLPR genotype with late-life depression. The Journal of Clinical Psychiatry, 70(9), 1281.

77.

Ritchie

Jaussent

Stewart

Dupuy

A.-M.

Courtet

Malafosse

Ancelin

M.-L.

(2011). Adverse childhood environment and late-life cognitive functioning. International Journal of Geriatric Psychiatry, 26(5), 503–510. https://doi.org/10.1002/gps.2553

78.

Roberts

A. L.

Lyall

Rich-Edwards

J. W.

Ascherio

Weisskopf

M. G.

(2013). Association of maternal exposure to childhood abuse with elevated risk for autism in offspring. JAMA Psychiatry, 70(5), 508–515. https://doi.org/10.1001/jamapsychiatry.2013.447

79.

Sabia

Guéguen

Marmot

M. G.

Shipley

M. J.

Ankri

Singh-Manoux

(2010). Does cognition predict mortality in midlife? Results from the Whitehall II cohort study. Neurobiology of Aging, 31(4), 688–695.

80.

Sachs-Ericsson

Medley

A. N.

Kendall-Tackett

Taylor

(2011). Childhood abuse and current health problems among older adults: The mediating role of self-efficacy. Psychology of Violence, 1(2), 106.

81.

Saleh

Potter

G. G.

McQuoid

D. R.

Boyd

Turner

MacFall

J. R.

Taylor

W. D.

(2017). Effects of early life stress on depression, cognitive performance and brain morphology. Psychological Medicine, 47(1), 171–181.

82.

Sarsour

Sheridan

Jutte

Nuru-Jeter

Hinshaw

Boyce

W. T.

(2011). Family socioeconomic status and child executive functions: The roles of language, home environment, and single parenthood. Journal of the International Neuropsychological Society, 17(1), 120–132.

83.

Shah

F. A.

Pike

Alvarez

Angus

Newman

A. B.

Lopez

Tate

Kapur

Wilsdon

Krishnan

J. A.

Hansel

Avdalovic

Fan

V. S.

Barr

R. G.

Yende

(2013). Bidirectional relationship between cognitive function and pneumonia. American Journal of Respiratory and Critical Care Medicine, 188(5), 586–592.

84.

Spencer

Devereux

Wallace

Sundrum

Shenoy

Bacchus

Logan

(2005). Disabling conditions and registration for child abuse and neglect: A population-based study. Pediatrics, 116(3), 609–613. https://doi.org/10.1542/peds.2004-1882

85.

Stilley

C. S.

Bender

C. M.

Dunbar-Jacob

Sereika

Ryan

C. M.

(2010). The impact of cognitive function on medication management: three studies. Health Psychology, 29(1), 50.

86.

Straus

M. A.

(1990). Measuring intrafamily conflict and violence: The Conflict Tactics (CT) Scales. In Straus

M. A.

Gelles

R. J.

(Eds.), Physical violence in American families (pp. 29–47). Transaction Publishers.

87.

Straus

M. A.

Hamby

S. L.

Finkelhor

Moore

D. W.

Runyan

(1998). Identification of child maltreatment with the parent-child conflict tactics scales: Development and psychometric data for a national sample of American parents. Child Abuse & Neglect, 22(4), 249–270. https://doi.org/S0145-2134(97)00174-9[pii]

88.

D’Arcy

Yuan

Meng

(2019). How does childhood maltreatment influence ensuing cognitive functioning among people with the exposure of childhood maltreatment? A systematic review of prospective cohort studies. Journal of Affective Disorders, 252, 278–293. https://doi.org/10.1016/j.jad.2019.04.026

89.

Sullivan

P. M.

Knutson

J. F.

(2000). Maltreatment and disabilities: A population-based epidemiological study. Child Abuse & Neglect, 24(10), 1257–1273. http://www.ncbi.nlm.nih.gov/pubmed/11075694

90.

Sumner

J. A.

Hagan

Grodstein

Roberts

A. L.

Harel

Koenen

K. C.

(2017). Posttraumatic stress disorder symptoms and cognitive function in a large cohort of middle-aged women. Depress Anxiety, 34(4), 356–366. https://doi.org/10.1002/da.22600

91.

Teicher

M. H.

Anderson

C. M.

Polcari

(2012). Childhood maltreatment is associated with reduced volume in the hippocampal subfields CA3, dentate gyrus, and subiculum. Proceedings of the National Academy of Sciences, 109(9), E563–E572. https://doi.org/10.1073/pnas.1115396109

92.

Teicher

M. H.

Samson

J. A.

Anderson

C. M.

Ohashi

(2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature Reviews Neuroscience, 17(10), 652.

93.

Tierney

M. C.

Yao

Kiss

McDowell

(2005). Neuropsychological tests accurately predict incident Alzheimer disease after 5 and 10 years. Neurology, 64(11), 1853–1859.

94.

Ryan

C. L.

Bauman

(2016). Educational attainment in the United States: 2015. US Department of Commerce, United States Census Bureau, 11. https://www.census.gov/library/publications/2016/demo/p20-578.html

95.

Weuve

Korrick

S. A.

Weisskopf

M. A.

Ryan

L. M.

Schwartz

Nie

Grodstein

(2009). Cumulative exposure to lead in relation to cognitive function in older women. Environmental Health Perspectives, 117(4), 574–580. https://doi.org/10.1289/ehp.11846

96.

Plassman

B. L.

Crout

R. J.

Liang

(2008). Cognitive function and oral health among community-dwelling older adults. The Journals of Gerontology: Series A, 63(5), 495–500.https://doi.org/10.1093/gerona/63.5.495

97.

Zielinski

D. S.

(2009). Child maltreatment and adult socioeconomic well-being. Child Abuse & Neglect, 33(10), 666–678. https://doi.org/10.1016/j.chiabu.2009.09.001

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.16 MB