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Article

http://ajp.psychiatryonline.org

Malnutrition at Age 3 Years and Externalizing Behavior

Problems at Ages 8, 11, and 17 Years

Jianghong Liu, Ph.D.

Adrian Raine, D.Phil.

Peter H. Venables, Ph.D., D.Sc.

Sarnoff A. Mednick, Ph.D.,

Objective: Poor nutrition is thought to predispose to externalizing behavior problems, but to date there appear to have been no prospective longitudinal studies testing this hypothesis. This study assessed whether 1) poor nutrition at age 3 years predisposes to antisocial behavior at ages 8, 11, and 17 years, 2) such relationships are independent of psychosocial adversity, and 3) IQ mediates the relationship between nutrition and externalizing behavior problems.

Method: The participants were drawn from a birth cohort (N=1,795) in whom signs of malnutrition were assessed at age 3 years, cognitive measures were assessed at ages 3 and 11 years, and antisocial, aggressive, and hyperactive behavior was assessed at ages 8, 11, and 17 years.

Results: In relation to comparison subjects (N=1,206), the children with malnutrition signs at age 3 years (N=353) were more aggressive or hyperactive at age 8 years, had more externalizing problems at age 11, and had greater conduct disorder and excessive motor activity at age 17. The results were independent of psychosocial adversity and were not moderated by gender. There was a dose-response relationship between degree of malnutrition and degree of externalizing behavior at ages 8 and 17. Low IQ mediated the link between malnutrition and externalizing behavior at ages 8 and 11.

Conclusions: These results indicate that malnutrition predisposes to neurocognitive deficits, which in turn predispose to persistent externalizing behavior problems throughout childhood and adolescence.  The findings suggest that reducing early malnutrition may help reduce later antisocial and aggressive behavior.

(Am J Psychiatry 2004; 161:2005–2013)

Despite decades of research into social and biological

risk factors for childhood aggression, surprisingly little is

known about the role of malnutrition in contributing to

the development of childhood externalizing behavior (1,

2). Although deficiency in nutrition has been rarely studied

in relation to externalizing behavior, several studies

have demonstrated the effects of related factors, including

food additives, hypoglycemia, and, more recently, cholesterol

(2–4), on human behavior. In addition, epidemiological

studies have shown associations between increased

aggressive behavior and vitamin and mineral deficiency

(5, 6). Several authors have also claimed links between

iron-deficient anemia or low zinc level and externalizing

behavior in childhood (7, 8). More recently, the male offspring

of nutritionally deprived pregnant women were

found to have 2.5 times the normal rate of antisocial personality

disorder in adulthood (9). Effects were found for

severe malnutrition during the first and second trimesters

of pregnancy, but not the third trimester. Despite these

findings, the research literature on malnutrition and externalizing

behavior problems remains both limited and

controversial (2, 10).

If malnutrition is linked to antisocial behavior, as some

suggest, a key question concerns the mechanism of action.

One possible, but so far untested, hypothesis is that early

malnutrition predisposes to antisocial behavior because

malnutrition impairs neurocognitive functioning, which in

turn predisposes to externalizing behavior problems. There

is now compelling evidence that externalizing behavior

problems are characterized by lower IQ (11–14), and furthermore,

there is evidence that these early neurocognitive

deficits predict the onset of antisocial behavior (1, 15, 16).

In addition, there is increasing evidence that malnutrition

predisposes to lower IQ (17, 18). We recently observed that

malnutrition at age 3 was related to lower IQ at age 3 and

age 11 in a large longitudinal study in Mauritius (19), while

similar findings have also been observed by others (17, 20).

Despite the plausibility of the malnutrition-externalizing

hypothesis, we know of no empirical tests of it to date.

Research on nutrition and antisocial behavior has five

important limitations. First, there are simply very few

studies that have assessed the relationship between nutritional

deficits and externalizing behavior. Second, with

the exception of the prenatal study by Neugebauer et al.

(9), studies have not investigated prospectively the effect

of early nutrition on later aggressive behavior; it is possible,

for example, that antisocial behavior in the child could

produce parental neglect and malnutrition, rather than

vice versa. Third, there have been few, if any, studies on the

relation between nutritional deficits and aggression in fe2006

Am J Psychiatry 161:11, November 2004

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males as well as males. Fourth, to our knowledge, the possibility

of mediating mechanisms, such as neurocognitive

deficits, have not been tested. Fifth, prior studies have

rarely controlled for the confounding effects of psychosocial

adversity.

In this study we used longitudinal data from Mauritius

in order to begin to address these gaps in the literature by

testing the following hypotheses: 1) poor nutrition at age 3

years predisposes to antisocial behavior at ages 8, 11, and

17 years, 2) such relationships are independent of early

psychosocial adversity, and 3) IQ mediates the nutritionantisocial

relationship. If controlling for childhood intelligence

abolishes the relationship between early malnutrition

and later externalizing behavior problems, this would

provide evidence for the role of intelligence as a significant

mediating mechanism (21).

Method

Participants

Participants were drawn from a birth cohort of 1,795 children

from the island of Mauritius, which lies off the coast of Africa. On

the basis of vaccination records, all children born in 1969 and 1970

in two main towns on the island were recruited into the study between

September 1972 and August 1973 when they were 3 years

old. The two towns (Vacoas and Quatre Bornes) were chosen because

they were representative of the ethnic distribution of the

whole island. The sample consisted of both boys (51.4%) and girls

(48.6%). The ethnic distribution was as follows: Indian, 68.7%;

Creole (African origin), 25.7%; and other (Chinese, English, and

French), 5.6%. Census data for the island as a whole indicated 66%

Indian, 29% Creole, and 5% other, indicating that the study largely

achieved its goal of representing the ethnicity of the population. In

keeping with previous work on this population (14, 22), the data

analyses were restricted to Indians and Creoles because of the

small number of subjects in the “other” ethnic category. Oral informed

consent was obtained from the mothers of the participants

in the early phases and from the participants themselves in

the age 17 phase. Early research activities were conducted according

to the principles outlined in the Declaration of Helsinki (23),

which prevailed in 1972, when the research was initiated, while research

activities in later years were conducted according to principles

outlined in the Belmont Report (24). Institutional review

board approval for the later research phases and retrospective

data analyses was obtained from the University of Southern California

and from the University of California, Los Angeles.

Signs of Malnutrition at Age 3

At age 3 years, four early signs of malnutrition (19) were assessed

in a clinical examination of 1,559 of the children. Assessments

of the children were conducted with a structured protocol

by local pediatricians who had received their medical training in

Europe. All assessments were conducted at the research unit. The

four signs were as follows:

Angular stomatitis. Cracking in the lips and corners of the

mouth is predominantly a sign of riboflavin deficiency (vitamin

B2) but also reflects niacin deficiency (25, p. 97). The base rate for

angular stomatitis in the sample was 7.0%.

Hair dyspigmentation. This condition reflects protein malnutrition

(26) and is found in tropical regions, particularly in Africa

(26), where children’s hair takes on a reddish-orange color. The

base rate for red hair in the sample was 6.8%.

Sparse, thin hair. This indicator is a sign of protein-energy

malnutrition in particular (27, 28) and malnutrition in general

(29). Protein reduction impairs hair growth, while zinc and iron

deficiency can also lead to thin hair. The base rate for this symptom

in the sample was 5.8%.

Anemia. Anemia was indicated by a low hemoglobin level,

which reflects iron deficiency. Hemoglobin level was assessed

from a laboratory test of blood drawn from the child. Anemia was

defined as a hemoglobin level below 8.5 g/dl. This definition of

anemia was consistent with medical practice in Mauritius in the

early 1970s. The base rate in this sample was 17.0%.

Definition of malnutrition. A participant was defined as suffering

from nutritional deficits if at least one of the four preceding

indicators was present; 22.6% of the assessed children met this

definition. A participant with no indicator present was classified

as having relatively normative nutrition; 77.4% fit this category.

To assess for a dose-response relationship between malnutrition

and externalizing behavior, each subject for whom behavior data

were available was categorized into one of four groups: no malnutrition

(N=766 at age 8, N=807 at age 11, N=422 at age 17), one indicator

of malnutrition (N=160 at age 8, N=172 at age 11, N=90 at

age 17), two indicators (N=45 at age 8, N=50 at age 11, N=25 at age

17), or three indicators (N=10 at age 8, N=13 at age 11, N=4 at age

17). Because only two individuals had all four nutrition indicators,

this category could not be included in the dose-response

analyses. Children thought to have potentially significant medical

problems of any kind (including malnutrition, scabies, and parasitic

worm) were referred to appropriate agencies for treatment

(30), but neither these referrals nor the treatment outcomes were

recorded or coded.

Intelligence and Cognitive Ability at Ages 3 and 11

Age 3. Measures of total cognitive ability were derived from six

subtests of the Boehm Test of Basic Concepts—Preschool Version

(14, 31, 32), which assesses basic verbal and visual-spatial concepts

that are fundamental for early school achievement. Full details

of measurement, factor structure, reliability, and validity in

this sample are given elsewhere (14, 31). Data were available for

1,260 subjects.

Age 11. Estimates of full-scale IQ were assessed at age 11 years

by using seven subtests of the WISC (33). The similarities and

digit span subtests were used to form an estimate of verbal IQ,

while the block design, object assembly, coding, mazes, and picture

completion subtests were used to form an estimate of performance

IQ. Data were available on 1,260 subjects for the preceding

three measures.

Psychosocial Adversity at Ages 3 and 11

The age 3 index of psychosocial adversity (14, 22) was based on

nine psychosocial variables assessed by social workers who visited

the homes of the children at age 3 years (see reference 34 for

full details). The index was created along lines similar to those described

by Rutter (35) and Moffitt (36). A total adversity score was

created by adding one point for each of the following nine variables:

father uneducated, mother uneducated, semiskilled or unskilled

parental occupation, single parent status, separation from

parents, large family size, poor health of mother, teenage mother,

and overcrowded home. Complete data for this construct were

available for 1,795 participants.

The age 11 psychosocial adversity index (14, 19, 22) was based

on 14 variables assessed by social workers who visited the homes

of the children at age 11 years. A total adversity score was created

by adding one point for each of the following 14 variables: living

in rented accommodation, house without electricity or water,

child with neither good toys nor good books, no television, poor

housing, father uneducated, mother uneducated, parent psychiAm

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atrically ill, parent physically ill, teenage mother (age 19 or

younger when child was born), single parent status, separation

from both parents, five or more siblings, and overcrowded home

(five or more family members per room). Complete data were

available on 1,272.

Externalizing Behavior Problems

Age 8. Externalizing behavior was assessed by teacher ratings

with the Children’s Behavior Questionnaire (37); see earlier reports

(14, 22, 38) for full details of reliability and validity. Briefly, a

factor analysis of this scale produced a factor of “aggression-hyperactivity”

(38), with the four-item aggression scale having an

internal reliability (coefficient alpha) of 0.79 and the six-item hyperactivity

scale having a reliability of 0.64. Complete data were

available for 1,130 participants on the aggression measure and for

1,128 on the hyperactivity measure.

Age 11. Externalizing behavior was assessed from parental ratings

using the three externalizing subscales (aggression, delinquency,

hyperactivity) of the Child Behavior Checklist (39), with

item content common across boys and girls (22). The internal reliability

values (coefficient alpha) for the scales were as follows: 0.72

for aggression, 0.66 for delinquency, 0.57 for hyperactivity, and 0.84

for total externalizing problems. Construct validity data are provided

elsewhere (22, 34). Data were available for 1,206 children.

Age 17. Externalizing behavior was assessed by parent and

teacher ratings using the Revised Behavior Problem Checklist

(40); full details of reliability and validity have presented elsewhere

(14, 22). All four checklist subscales that reflect externalizing

behavior problems were included in the analyses: conduct

disorder, socialized aggression, excessive motor activity, and attention

problems. Complete data were available for 608 subjects.

Representativeness of Groups

Complete data on both the malnutrition and externalizing behavior

variables were available on 982 subjects at age 8, 1,044 at age

11, and 541 at age 17. Those with and without complete data at

each age were compared on gender and ethnicity, variables that

were available on all subjects at age 3. Results of these analyses are

shown in Table 1. There was a statistically significant overrepresentation

of Indians at all ages among the participants with complete

data and an overrepresentation of boys at age 11. Consequently,

ethnicity and gender were entered into the subsequent analyses in

order to assess their roles as moderator effects or confounds.

Statistical Analyses

In the comparisons of the malnourished and normal groups,

separate analyses were conducted for each of the three ages (8, 11,

and 17 years). To test for overall effects of malnutrition on externalizing

behavior problems, we conducted a multivariate analysis

of variance (MANOVA) on all dependent variables for each age

(e.g., hyperactivity, aggression, and delinquency at age 11). Univariate

F tests were then used to assess which specific subcomponents

of externalizing behavior were associated with malnutrition.

IQ and social adversity at ages 3 and 11 were identified as

potential mediators, i.e., variables accounting for a significant

portion of the relationship between the predictor (malnutrition)

and the outcome variable (externalizing behavior) (21). To test for

the mediating effects of cognition and psychosocial adversity,

these variables were each entered separately as covariates in the

MANOVAs. Gender and ethnicity were identified as potential

moderators, i.e., factors that may reduce or enhance the influence

of malnutrition on externalizing behavior, as indicated by an interaction

between the independent variable (malnutrition) and a

factor (gender, ethnicity) (21). To assess for moderating effects of

gender and ethnicity, we entered these variables as factors in the

MANOVA alongside the nutrition grouping. Any interactions were

broken down by stratifying on the moderator variable and conducting

two-way MANOVAs to test for simple interactions (41).

These in turn were broken down by tests of simple main effects.

To test for a dose-response relationship between degree of malnutrition

and degree of externalizing behavior problems, we constructed

four levels of the grouping factor (none, one, two, and

three malnutrition indicators), repeated the preceding MANOVAs

and univariate ANOVAs, and conducted tests for linear trends to

assess for a linear fit between degree of malnutrition and degree

of externalizing behavior. Two-tailed tests of significance with an

alpha set at 0.05 were used throughout.

Results

Detailed results of both the multivariate and univariate

F tests of the effects of malnutrition on externalizing behavior

at all three ages, including moderator and mediator

effects, are shown in Table 2.

Externalizing Behavior Problems at Age 8

Effect of malnutrition. A MANOVA on the two dependent

variables (aggression and hyperactivity) indicated a

main group effect (Table 2), demonstrating that the malnourished

children had higher overall externalizing behavior

scores. Univariate F tests indicated that the malnourished

group had significantly higher scores on both

hyperactivity and aggression (Figure 1, Table 2).

Mediators. The malnourished children were more likely

to have lower cognitive ability at age 3 than the normal

children and were more likely to suffer psychosocial adversity

at age 3 than the normal children (Table 3). Consequently,

it is possible that poor cognition or greater

psychosocial adversity could mediate the main effect of

malnutrition on externalizing behavior. This possibility

was tested by entering cognitive and adversity measures

separately as covariates in the preceding MANOVA.

The main effect of malnutrition was abolished after we

controlled for cognitive ability, indicating that cognitive

ability mediates the link between malnutrition and externalizing

behavior. In contrast, after we controlled for age 3

psychosocial adversity, the main effect of malnutrition remained

significant (Table 2), indicating that the relation-

TABLE 1. Ethnicity and Gender of Subjects With and Without

Complete Follow-Up Data Among 1,559 Children in

Mauritius Whose Nutritional Status Was Assessed at Age 3

Age at Follow-Up,

Ethnicity,

and Gender

Percent With Indian Ethnicity

or Male Gendera Analysis

Subjects With

Complete Data

Subjects With

Missing Data

÷2

(df=1) p

Age 8

Indian ethnicity 74.5 67.6 9.98 0.002

Male gender 51.2 52.5 0.30 0.59

Age 11

Indian ethnicity 74.6 66.9 12.37 0.001

Male gender 54.1 48.7 5.11 0.03

Age 17

Indian ethnicity 76.4 69.2 9.32 0.002

Male gender 53.1 51.2 0.55 0.46

a Percentages are based on the number of subjects at each follow-up

with complete or missing data.

2008 Am J Psychiatry 161:11, November 2004

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ship between malnutrition and externalizing behavior

was independent of psychosocial adversity.

Creoles were more likely to be malnourished than Indians

(Table 3). After we controlled for ethnicity by entering

it as a covariate, the effect of malnutrition on externalizing

behavior remained significant (Table 2).

Moderators. There were no interactions between nutrition

grouping and gender. However, there was a significant

interaction between ethnicity and nutrition grouping. In

order to clarify this two-way interaction, the sample was

stratified by race and one-way MANOVAs were conducted

separately on Creoles and Indians. The multivariate results

indicated that in both groups, malnutrition was significantly

associated with externalizing problems. For Creoles

there was a significant effect of malnutrition on externalizing

behavior (F=3.67, df=2, 236, p<0.03). Univariate F tests

indicated that malnourished Creoles had significantly

higher scores than normal Creoles on aggression (F=7.37,

TABLE 2. Results of Multivariate and Univariate Tests of the Effect of Malnutrition at Age 3 on Externalizing Behavior at

Ages 8, 11, and 17 Among Children in Mauritius

Age at Follow-Up, Type of Analysis,

and Behavior Variablea

Moderator Effects

Main Effect of Malnutrition

Gender-by-Malnutrition

Interaction

Race-by-Malnutrition

Interaction

N F df p F df p F df p

Age 8 982

Multivariate 5.63 2, 979 0.004 1.62 2, 975 0.24 3.47 2, 932 0.04

Univariate

Aggression 4.68 1, 980 0.04 1.63 2, 975 0.24 4.58 2, 933 0.04

Hyperactivity 11.28 1, 980 0.001 0.42 2, 976 0.52 0.06 2, 933 0.82

Age 11 1,044

Multivariate 4.18 3, 1042 0.006 1.19 3, 1037 0.31 1.50 3, 994 0.21

Univariate

Aggression 2.67 1, 1042 0.11 1.95 1, 1039 0.16 4.25 1, 996 0.04

Delinquency 2.10 1, 1042 0.15 0.18 1, 1039 0.67 3.22 1, 996 0.08

Hyperactivity 12.53 1, 1042 0.001 1.88 1, 1039 0.17 0.81 1, 996 0.37

Age 17 541

Multivariate 5.35 4, 536 0.001 1.34 4, 533 0.25 0.53 4, 514 0.72

Univariate

Conduct disorder 10.07 1, 539 0.002 0.12 1, 536 0.73 0.81 1, 517 0.37

Motor excess 6.11 1, 539 0.02 3.75 1, 536 0.053 0.12 1, 517 0.73

Attention problems 0.31 1, 539 0.58 0.50 1, 536 0.48 0.96 1, 517 0.06

Socialized aggression 0.63 1, 539 0.43 0.00 1, 536 0.98 0.01 1, 517 0.91

a At age 8, externalizing behavior was assessed with the Children’s Behavior Questionnaire. At age 11, externalizing behavior was assessed with

the Child Behavior Checklist. At age 17, externalizing behavior was assessed with the Revised Behavior Problem Checklist.

b Analyses of the follow-up at age 8 used the ratings of psychosocial adversity and cognitive ability at age 3. Analyses of the follow-ups at ages

11 and 17 used the ratings at age 11.

FIGURE 1. Scores for Externalizing Behaviors at Ages 8, 11, and 17 Among Children in Mauritius Who Were or Were Not

Malnourished at Age 3

a Number of subjects assessed at age 3.

4.0

3.0

2.0

1.0

3.5

2.5

1.5

0.5

0.0

Aggression Hyperactivity Aggression Hyperactivity Delinquency Conduct

disorder

Motor

excess

Attention

problems

Socialized

aggression

Score on Scale From Children’s

Behavior Questionnaire

Age 8 Age 11 Age 17

Comparison

subjects (N=1,206)a

Malnourished

children (N=353)a

6

4

2

5

3

1

0

Score on Scale From Child Behavior Checklist

12

8

6

4

2

10

11

9

7

5

3

1

0

Score on Scale From Revised

Problem Behavior Checklist

Am J Psychiatry 161:11, November 2004 2009

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df=1, 237, p<0.008), but the effect for hyperactivity was not

significant (F=2.92, df=1, 237, p=0.09). For Indians, there

was a significant effect of malnutrition on externalizing behavior

(F=3.43, df=2, 695, p<0.04), with higher scores for

externalizing behavior among the malnourished Indians

than among the normal Indians. Univariate F tests indicated

that malnourished Indians had significantly higher

scores than normal Indians on hyperactivity (F=4.85, df=1,

696, p<0.03), but the effect for aggression was not significant

(F=0.15, df=1, 696, p=0.70). Consequently, these analyses

indicate that malnutrition is more likely to predispose

Creole children to aggression at age 8 but predispose Indian

children to hyperactivity at age 8.

Externalizing Behavior Problems at Age 11

Effect of malnutrition. As shown in Table 2, the overall

MANOVA indicated a main effect of malnutrition on externalizing

behavior scores at age 11 years. The univariate F

tests showed a significant effect of malnutrition on hyperactivity

but not on aggression or delinquency (Figure 1).

Mediators. As shown in Table 3, the malnourished children

had lower cognitive ability at age 11 than the nonmalnourished

children. After we controlled for cognitive

ability, the main effect of nutritional status was abolished,

indicating a mediating effect of low cognitive ability. Although

the malnourished and comparison children did

not differ significantly on adverse psychosocial backgrounds

at age 11, the difference approached significance.

Consequently, to ensure that adversity did not mediate the

findings, the age 11 total psychosocial adversity score was

entered as a covariate in the preceding MANOVA. The

main group effect remained significant.

Moderators. Multivariate results indicated that there were

no significant moderator effects for gender at all ages and no

moderator effects for ethnicity at ages 11 and 17, although

ethnicity was a significant moderator at age 8 (Table 2).

Externalizing Behavior Problems at Age 17

Effect of malnutrition. A MANOVA conducted on conduct

disorder, motor excess, attention problems, and socialized

aggression showed a significant overall main effect

of malnutrition (Table 2). Univariate F tests showed that

the malnourished group had significantly higher scores on

conduct disorder and motor excess but not on attention

problems or socialized aggression (Figure 1, Table 2).

Mediators. After age 11 cognitive ability was entered as a

covariate, the main effect of malnutrition remained significant.

The main group effect also remained significant after

we controlled for age 11 psychosocial adversity (Table 2).

Moderators. There was no significant moderator effect

for gender or ethnicity (Table 2).

Dose-Response Relationships

Dose-response relationships between malnutrition and

externalizing behavior are depicted in Figure 2. MANOVAs

indicated a significant main effect of the degree of malnutrition

on externalizing behavior at age 8 (F=2.53, df=6,

1954, p=0.02), and the linear term was also significant for

both aggression (F=5.92, df=1, 977, p<0.02) and hyperactivity

(F=11.96, df=1, 977, p<0.001). At age 17, there was

also a main effect of the degree of malnutrition (F=2.44,

df=12, 1608, p<0.004) and significant linear trends for conduct

disorder (F=10.14, df=1, 537, p<0.002) and motor excess

(F=8.58, df=1, 537, p<0.004). For age 11, the main effect

of nutrition was nonsignificant (F=1.84, df=9, 3114, p=

0.06), although the linear term was significant for hyperactivity

(F=9.19, df=1, 1038, p<0.002). Univariate F tests

showed significant group differences for age 8 hyperactivity

(F=4.60, df=3, 977, p<0.003), age 11 hyperactivity (F=

4.36, df=3, 1038, p<0.005), age 17 conduct disorder (F=

3.53, df=3, 537, p<0.02), and age 17 motor excess (F=2.95,

df=3, 537, p<0.04). The results of all other univariate tests

(i.e., on aggression at age 8, aggression and delinquency at

age 11, and attention problems and socialized aggression

at age 17) were nonsignificant (p>0.11).

In order to assess whether poor cognition mediated the

preceding dose-response relationships, the tests were repeated

after we entered the cognitive measures as covariates.

All effects of nutrition were abolished (age 8: F=1.14,

df=6, 1488, p=0.34; age 17: F=1.69, df=12, 1401, p=0.07), indicating

a mediating role of poor neurocognitive functioning.

Discussion

Key Findings

One key finding of this study is that malnutrition at age

3 years is associated with higher scores for externalizing

behavior problems at ages 8, 11, and 17. A second key find-

Mediator Effects

Psychosocial Adversity

at Age 3 or 11b

Cognitive Ability

at Age 3 or 11b

F df p F df p

4.49 2, 976 0.02 1.58 2, 746 0.21

4.05 1, 977 0.05 1.37 1, 747 0.24

8.97 1, 977 0.003 3.15 1, 747 0.08

4.04 3, 1002 0.007 1.40 3, 973 0.24

2.84 1, 1004 0.10 1.32 1, 975 0.25

2.32 1, 1004 0.13 0.35 1, 975 0.55

12.14 1, 1004 0.001 3.79 1, 975 0.05

3.91 4, 480 0.004 3.69 4, 467 0.006

5.59 1, 483 0.02 4.45 1, 470 0.21

3.55 1, 483 0.06 1.25 1, 470 0.26

0.53 1, 483 0.47 1.16 1, 470 0.28

1.56 1, 483 0.21 1.64 1, 469 0.20

2010 Am J Psychiatry 161:11, November 2004

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ing is that the relationship between malnutrition and externalizing

behavior was not found to be an artifact of psychosocial

adversity but was instead mediated by cognitive

ability, indicating that malnutrition predisposes children

to a lower IQ, which in turn predisposes them to externalizing

behavior problems. These conclusions are supported

by the finding of dose-response relationships between degree

of malnutrition and degree of externalizing behavior

problems at ages 8 and 17, relationships that were again

found to be mediated by low IQ. To our knowledge, these

are the first findings to show prospectively that malnutrition

assessed in the early postnatal years is associated with

externalizing behavior problems from childhood to late

adolescence and also to show the mediating effects of cognitive

ability. These findings in turn have potential implications

for public health attempts to prevent the occurrence

of externalizing behavior problems in children and

adolescents.

The robustness of the findings is indicated in several

ways. First, malnutrition predisposed to externalizing behavior

problems across several ages from childhood (age

to late adolescence (age 17). Second, externalizing behavior

problems were measured by three different instruments

at the three different ages, indicating that the findings were

replicated across sources and were largely invariant to the

nature of measurement (42). Third, the fact that gender

and ethnicity did not moderate the multivariate findings at

ages 11 and 17 indicates that the nutrition-externalizing relationship

is not specific to one gender or ethnic grouping,

although it should be noted that at age 8 malnutrition was

more likely to predispose to aggression in Creoles and to

hyperactivity in Indians. It is possible that malnutrition

predisposes to a general disinhibitory tendency and that

broad cultural differences influence the precise manifestations

of such disinhibition at a behavioral level. Fourth, the

fact that dose-response relationships were found at ages 8

and 17 confirms and extends the findings based on comparisons

of the malnourished and nonmalnourished children,

although it is noted that the dose-response effect at

age 11 was not statistically significant (p=0.06). For these

reasons, we believe that the findings cannot be easily attributed

to chance and that, instead, they reflect a reliable

relationship between early malnutrition and later externalizing

behavior problems.

TABLE 3. Demographic and Cognitive Measures at Ages 8, 11, and 17 Among Children in Mauritius Who Were or Were Not

Malnourished at Age 3

Age at Follow-Up

and Variable

Malnourished Not Malnourished

Percent of Ethnic

or Gender Group Mean SD N

Percent of Ethnic

or Gender Group Mean SD

Analysis

N ÷2 t df p

Age 8 216 766

Ethnicity 7.67 1 0.006

Creole 28.0 72.0

Indian 19.5 80.5

Gender 0.82 1 0.40

Male 23.1 76.9

Female 20.7 79.3

Psychosocial adversity

score at age 3a 2.21 1.35 1.83 1.31 3.80 978 0.001

Cognitive ability score

at age 3b 96.51 14.20 100.44 15.25 2.84 748 0.005

Age 11 1,044 762

Ethnicity 0.45 1 0.54

Creole 24.0 76.0

Indian 22.0 78.0

Gender 0.10 1 0.78

Male 22.3 77.7

Female 23.2 76.8

Psychosocial adversity

score at age 11c 2.02 1.49 1.80 1.52 1.87 1005 0.07

Cognitive ability score

(IQ) at age 11 95.88 15.58 101.27 14.36 4.80 976 0.001

Age 17 541 1,265

Ethnicity 0.07 1 0.80

Creole 22.8 77.2

Indian 21.6 78.4

Gender 0.13 1 0.76

Male 22.3 77.7

Female 23.2 76.8

Psychosocial adversity

score at age 11 2.13 1.52 1.87 1.54 1.55 484 0.12

Cognitive ability score

(IQ) at age 11 94.37 16.57 99.46 15.56 2.92 471 0.004

a Range=0–9; 9=greatest severity.

b Higher scores indicate greater cognitive ability.

c Range=0–14; 14=greatest severity.

Am J Psychiatry 161:11, November 2004 2011

LIU, RAINE, VENABLES, ET AL.

http://ajp.psychiatryonline.org

Nutrition, Brain Development,

and Externalizing Behavior

A critical question concerns the mechanism by which

malnutrition predisposes to later externalizing behavior

problems. We hypothesize that early malnutrition negatively

affects brain growth and development and that

brain impairments predispose to antisocial and violent

behavior by affecting cognitive functions. The indicators

of malnutrition in this study reflect deficits in protein (red

hair, sparse/thin hair), iron (low hemoglobin level), and

zinc (red hair, sparse/thin hair). There is extensive experimental

evidence in animals both that zinc and protein deficiency

impairs brain development (8, 43–45) and that

protein, iron, and zinc deficiency predisposes to aggression

(45–47). In humans, zinc deficiency during pregnancy

has been linked to impaired DNA, RNA, and protein synthesis

during brain development as well congenital brain

abnormalities (48). There is also evidence in humans that

antisocial behavior is related to protein deficiency (9) and

iron-deficient anemia (7). Consequently, protein, iron,

and zinc deficiencies may contribute to the brain impairments

that have been found in aggressive adult offenders

and that in turn are thought to predispose to aggressive

antisocial behavior (3, 15, 46, 49).

While early malnutrition could thus relatively directly predispose

to externalizing behavior problems by impairing

brain mechanisms such as those in the prefrontal cortex

that are thought to regulate emotion and inhibit impulsive

aggressive behavior (for example, see reference 50), malnutrition

could also predispose to externalizing behavior problems

more indirectly by impairing cognitive functioning,

which in turn predisposes to externalizing behavior problems.

The findings from the present study provide partial

(but not total) support for this possibility. Cognitive functioning

was established as a mediator for the malnutritionexternalizing

relationship at ages 8 and 11 years in that controlling

for the effect of IQ on externalizing behavior abolished

the malnutrition-externalizing relationship. Poor cognitive

ability has been found consistently to predispose to

externalizing behavior problems (51). Nevertheless, support

for this cognitive explanation of the malnutrition-externalizing

relationship is not entirely complete. While mediating

effects were observed at ages 8 and 11 and while poor cognition

mediated the dose-response relationship at age 17, it

did not mediate overall differences between the malnourished

and comparison groups in age 17 externalizing behavior,

possibly because of the 6-year gap between the assessments

of IQ (age 11) and externalizing behavior (age 17).

Clinical Implications and Limitations

Externalizing behavior problems are important predisposing

factors in later adult violent offenses (52), and violence

prevention and protection from victimization have

become two of the most pressing issues facing society today

(52, 53). One recent double-blind, placebo-controlled,

randomized experimental trial showed that supplementation

of adult prisoners’ diet with vitamins, minerals, and

essential fatty acids significantly reduced antisocial and

violent behavior in prison (54). Although dietary interventions

for adults may prove helpful in reducing antisocial

and violent behavior, identification of early risk factors for

childhood and adolescent aggression is a critically important

first step for developing successful prevention

programs for such adult violence. Because nutrition is a

FIGURE 2. Dose-Response Relationships Between Number of Malnutrition Indicators at Age 3 and Externalizing Behaviors

at Ages 8, 11, and 17 Among Children in Mauritiusa

a Four indicators of malnutrition were assessed: angular stomatitis, hair dyspigmentation, sparse/thin hair, and anemia.

4.0

2.0

1.0

1.5

0.5

3.5

2.5

3.0

0.0

Score on Scale From Children’s

Behavior Questionnaire

Age 8 (N=982) Age 11 (N=1,044) Age 17 (N=541)

12

11

10

8

6

4

2

9

7

5

3

1

0

Score on Scale From Revised

Problem Behavior Checklist

0 1 2 3 0 1 2

Number of Malnutrition Indicators

3 0 1 2 3

6

4

2

5

3

1

0

Score on Scale From Child Behavior Checklist

Motor excess

Conduct disorder

Delinquency

Hyperactivity

Aggression

2012 Am J Psychiatry 161:11, November 2004

MALNUTRITION AND EXTERNALIZING BEHAVIOR

http://ajp.psychiatryonline.org

malleable factor, it may be more practical and easier to

prevent externalizing behavior through better early nutrition

targeting at-risk populations than more complex and

expensive psychosocial manipulations. The fact that several

studies that have included the promotion of early nutrition

as part of a larger prevention program have met

with success (55, 56) argues for further attention to early

malnutrition as a predisposing factor in externalizing behavior

among children. It is possible, however, that malnutrition

at age 3 years is correlated with poor prenatal

malnutrition and that prenatal, rather than postnatal, interventions

for malnutrition may be most effective (9, 55).

Finally, three potential limitations of the study should

be acknowledged. First, the findings suggest but do not

prove that early malnutrition predisposes to later externalizing

behavior. Randomized, controlled designs that

manipulate nutritional intake and evaluate diet in children

are needed to support the role of nutrition as an etiological

factor in externalizing behavior. Nevertheless, the

fact that interventions that indirectly manipulate nutrition

have been found to reduce later conduct disorder (55,

56) suggests that a possible etiological role of malnutrition

in externalizing behavior should not be discounted. Second,

because nutrition was assessed at only one time

point (age 3 years) this study could not ascertain whether

the effects on externalizing behavior were produced by

transient malnutrition (i.e., the first 3 years only), by more

sustained malnutrition, extending beyond the third year,

or by maternal malnutrition during pregnancy (9). Third,

there are cultural, ethnic, and social differences between

Mauritius and the United States that highlight the importance

of replicating the present findings in Europe and the

United States. Nevertheless, the current findings from

Mauritius may be a good model for externalizing problems

in underserved subpopulations of American society,

particularly since food insufficiency is relatively common

in poor rural areas of the United States and has been associated

with poor behavioral functioning in low-income

children in American inner cities (57, 58).

Received June 10, 2003; revision received Dec. 2, 2003; accepted

Jan. 19, 2004. From the Social Science Research Institute and the Department

of Psychology, University of Southern California; and the Department

of Psychology, University of York, York, U.K. Address reprint

requests to Dr. Raine, Department of Psychology, University of Southern

California, Los Angeles, CA 90089-1061; raine@usc.edu (e-mail).

Supported by a predoctoral fellowship award (F31 NR-07518) and

postdoctoral fellowship (F32 NR-08661) from the National Institute of

Nursing Research to Dr. Liu; an NIMH Independent Scientist Award

(K02 MH-01114), a grant from the Borchard Foundation, and a grant

from NIMH (RO1 MH-46435) to Dr. Raine; grants from the Medical Research

Council, Leverhulme Trust, and Mental Health Foundation to

Dr. Venables; an NIMH Research Scientist Award to Dr. Mednick (5

K05 MH-00619); and a grant from the Ministry of Health of the Mauritian

government.

The authors thank Marie-Clare Calambay, Meena Calinghen,

Athene Chiriaca, Cyril Dalais, Fazila Dinally, Devi Jaganathen, Goorah

Rajah, and Charles Yip Tong for help in data collection and scoring.

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Harmful pesticides found in everyday food products
By Andrew Schneider
Seattlepi, 1/30/2008 

Read full study here

Government promises to rid the nation’s food supply of brain-damaging pesticides aren’t doing the job, according to the results of a yearlong study that carefully monitored the diets of a group of local children.

The peer-reviewed study found that the urine and saliva of children eating a variety of conventional foods from area groceries contained biological markers of organophosphates, the family of pesticides spawned by the creation of nerve gas agents in World War II.

When the same children ate organic fruits, vegetables and juices, signs of pesticides were not found.

“The transformation is extremely rapid,” said Chensheng Lu, the principal author of the study published online in the current issue of Environmental Health Perspectives.

“Once you switch from conventional food to organic, the pesticides (malathion and chlorpyrifos) that we can measure in the urine disappears. The level returns immediately when you go back to the conventional diets,” said Lu, a professor at Emory University’s School of Public Health and a leading authority on pesticides and children.

Within eight to 36 hours of the children switching to organic food, the pesticides were no longer detected in the testing.

The subjects for his testing were 21 children, ages 3 to 11, from two elementary schools and a Montessori preschool on Mercer Island.

The community has double the median national income, but the wealth of Mercer Island made no difference in the outcome, he said.

“We are confident that if we did the same study in poor communities, we would get the same results,” he said. The study is being repeated in Georgia.

The study has not yet linked the pesticide levels to specific foods, but other studies have shown peaches, apples, sweet bell peppers, nectarines, strawberries and cherries are among those that most frequently have detectable levels of pesticides.

Measuring the harm

Lu is quick to point out that there is no certainty that the pesticides measured in this group of children would cause any adverse health outcomes. However, he added that a recent animal study demonstrated that persistent cognitive impairment occurred in rats after chronic dietary exposure to chlorpyrifos.

Death or serious health problems have been documented in thousands of cases in which there were high-level exposures to malathion and chlorpyrifos. But a link between neurological impairments and repeated low-level exposure is far more difficult to determine.

“There’s a large underpinning of animal research for organophosphate pesticides, and particularly for chlorpyrifos, that points to bad outcomes in terms of effects on brain development and behavior,” Dr. Theodore Slotkin, a professor of pharmacology and cancer biology at Duke University in North Carolina, said in the April 2006 Environmental Health Perspectives.

Lu says more research must be done into the harm these pesticides may do to children, even at the low levels found on food.

“In animal and a few human studies, we know chlorpyrifos inhibits an enzyme that transmits a signal in the brain so the body can function properly. Unfortunately, that’s all we know.”

Not many chemicals, including pharmaceutical products, were designed specifically to kill mammals, which was genesis of organophosphates.

“It is appropriate to assume that if we — human beings — are exposed to (this class of) pesticides, even though it’s a low-level exposure on a daily basis, there are going to be some health concerns down the road,” said Lu, who is on the Environmental Protection Agency’s pesticide advisory panel.

The EPA says it eliminated the use of organophosphates on many crops and imposed numerous restrictions on the remaining organophosphate pesticide uses.

Congressional concern that children were being harmed by excessive exposure to pesticides led to the unanimous passage of the Food Quality Protection Act. At its heart was a requirement that by 2006, the EPA complete a comprehensive reassessment of the 9,721 pesticides permitted for use and determine the safe level of pesticide residues permitted for all food products.

“As a result, the amount of these pesticides used on kids’ foods (has undergone) a 57 percent reduction,” said Jonathan Shradar, the EPA’s spokesman.

But that’s not nearly enough to prevent birth defects and neurological problems, said Chuck Benbrook, chief scientist of the Organic Center, a nationwide, nonprofit, food research organization.

“The pesticide limits that EPA permits are far, far too high to say they’re safe. And, the reduction that EPA cites in the U.S. has been accompanied by a steady increase in pesticide-contaminated imported foods, which are capturing a growing share of the market,” he said.

Yet the EPA continues to insist that “dietary exposures from eating food crops treated with chlorpyrifos are below the level of concern for the entire U.S. population, including infants and children.”

That statement is “not supported by science,” Benbrook said.

“Given the almost daily reminders that children are suffering from an array of behavioral, learning, neurological problems, doesn’t it make sense to eliminate exposures to chemicals known to trigger such outcomes like chlorpyrifos?” he asked.

What to do

While the gut reaction of some parents might be to limit the consumption of fresh produce or switch completely to organic food, Lu cautions not to make the wrong decision.

“It is vital for children to consume significantly more fresh fruits and vegetables than is commonly the case today,” he says, citing such problems as juvenile diabetes and obesity.

“Nor is our purpose to promote the consumption of organic food, although our data clearly demonstrate that food grown organically contains far less pesticide residues.”

Lu says an all-organic diet is not necessary. He has two sons, 10 and 13, and he estimates that about 60 percent of his family’s diet is organic.

“Consumers,” he says, “should be encouraged to buy produce direct from the farmers they know. These need not be just organic farmers, but conventional growers who minimize their use of pesticides.”

Understanding how fruits and vegetables grow can help guide the consumer, he says.

For example, organic strawberries probably are worth the money because they are a tender-fleshed fruit grown close to the dirt, so more pesticides are needed to fight insects and bugs from the soil. He adds apples and spinach to his list.

“It may also be money-smart to choose conventionally grown broccoli because it has a web of leaves surrounding the florets, resulting in lower levels of pesticide residue,” Lu says.

He is greatly concerned about one finding from the study.

“Overall pesticide (marker) levels in urine samples were even higher in the winter months, suggesting children may have consumed fruits and vegetables that are imported. The government needs to ensure that imported food comply with the standards we impose on domestic produce,” he said.

Dangerous science

Chlorpyrifos, made by Dow Chemical Co., is one of the most widely used organophosphate insecticides in the United States and, many believe, the world.

For years, millions of pounds of the chemical insecticide were used in schools, homes, day care centers and public housing, and studies show that children were often exposed to enormously high doses. Just as the EPA was ready to ban the product, which analysts said would have damaged Dow’s overseas sales, the company “voluntarily” removed it from the home market. Yet, with few exceptions, the agricultural uses continued.

The EPA’s Web site is a study in contradictions when it comes to chlorpyrifos.

At one section, it “acknowledged the special susceptibility and sensitivity of children to developmental and neurological effects from exposure to chlorpyrifos.”

But in another section, the agency reports that infants and children face no risk from eating food crops treated with chlorpyrifos. However, the agency doesn’t say how it reached that conclusion. There is no agreement of how much of the neurotoxin is too much.

Benbrook said the EPA has refused orders from Congress to study the cumulative developmental risk to children from low-dose exposures.

“Perhaps we can rest assured that EPA has protected us adults from acute insecticide poisoning risk, but our kids are on their own,” Benbrook said. 

http://www.publicbroadcasting.net/kunr/news.newsmain/article/0/0/1647855/Nevada.Newsline/Dietary.SupplementsBonnie

Workshop on Micronutrient Treatment and Research for Mental Health

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• Hear and discuss case presentations.
• Learn about practical applications for your practice, with Teresa Kolpak, Expert.
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• Learn about conducting research in clinical practice with Dr. Bonnie Kaplan, Ph.D.
• Come, share, and ask questions!

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Low levels of these important chemicals are extremely common in the general public and is due to innumerable lifestyle, environmental, and dietary factors.  People with low levels may suffer from one or more of the following conditions: obesity, depression, anxiety, fibromyalgia, chronic fatigue, insomnia, attention deficit, learning disorders, panic attacks, migraines, pms, menopausal symptoms, digestive complaints and many more. Selective serotonin re-uptake inhibitors (SSRIs) and other drugs working on the neurotransmitter biochemistry such as Prozac, Zoloft, Effexor, Celexa, Wellbutrin, etc. are currently some of the most commonly prescribed drugs. 

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