THE ASSOCIATION OF SEASON OF BIRTH WITH CHILD … · THE ASSOCIATION OF SEASON OF BIRTH WITH CHILD...

THE ASSOCIATION OF SEASON OF BIRTH WITH CHILD INTERNALIZING PROBLEMS

by

FRED W. GREER

(Under the direction of Roy P. Martin)

ABSTRACT

The study investigated the relationship between children’s season of birth and their

development of internalizing problems. This research builds on previous studies that have

examined season of birth effects for nervous system disorders, schizophrenia, mental retardation

and learning disabilities. The sample consisted of 2,619 elementary school students between the

ages of 5 and 12 years who participated in a grant project (Project ACT Early). Using the

Behavior Assessment System for Children (BASC; Reynolds & Kamphaus, 1992), classroom

teachers rated each student on their behavioral adjustment. Five scales from the BASC

instrument were examined in this study: Anxiety, Depression, Somatization, Withdrawal, and the

Internalizing Problems Composite.

Chi-square tests of independence were used to assess the association between which half

of the year were born (Spring/Summer or Fall/Winter) and whether they had extreme scores on

one of the five BASC scales (above the 75th percentile). These analyses were conducted for the

overall population, by sex, and by age-group (5 to 8 years, 9 to 12 years).

It was postulated that births for high-scoring children would be greater in the Spring/Summer

than other times of the year.

Statistically significant effects were found for high-score children on the Anxiety scale

and Internalizing Problems composite. The peak birth period for these subjects was during the

Spring/Summer period as expected. Analyses of the data according to sex identified statistically

significant effects among females on these same scales, also with the frequency of births cresting

in the Spring/Summer period.

INDEX WORDS: Season of birth, Anxiety, Internalizing, Seasonal variation, Birth pattern,

Risk factor, Project ACT Early, BASC


by

FRED W. GREER

A.B., The University of Georgia, 1986

M.A., The University of Georgia, 1992

A Dissertation Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree

DOCTOR OF PHILOSOPHY

ATHENS, GEORGIA

2005

© 2005

Fred Warren Greer

All Rights Reserved


by

FRED W. GREER

Major Professor: Roy Martin

Committee: Randy Kamphaus Thomas Hébert

Arthur Horne Electronic Version Approved: Maureen Grasso Dean of the Graduate School The University of Georgia May 2005

iv

DEDICATION

For Chris

v

ACKNOWLEDGEMENTS

Completion of this dissertation would not have been possible without the assistance of so

many people. Among them, I wish to thank my major professor, Dr. Roy Martin, for his

thoughtful guidance and patience. I am as well grateful for the easy cooperation and detailed

attention rendered by each member of my committee: Dr. Randy Kamphaus, Dr. Andy Horne,

and Dr. Thomas Hébert. Additionally, the value of Dr. Stefan Dombrowski’s thoughts during

my initial writing of the proposal should also be recognized, as should Dr. Jan Hinson’s feedback

that contributed to successful revisions in its final stages.

While working toward my doctorate, I have benefited enormously from the friendly

support of those with whom I’ve worked. Certainly I must thank the teachers, staff, and

students of Rutland Psychoeducational Services for the experience I enjoyed with them during

my internship. I am particularly owing to my internship supervisor, Dr. Harvey Gayer, for his

direction of my efforts while providing me the opportunity to develop my own perspective on

assessment and intervention. Moreover, I am grateful for the steady and energetic

encouragement Dr. Gayer has given over the course of my training and the writing of my

dissertation.

Various staff members of the University of Georgia deserve my thanks for their

assistance in helping me toward realizing my goals. The Department of Educational

Psychology’s Demetrius Smith was always ready to help explain paperwork and remind me of

deadlines.

vi

I am especially thankful of the support of my family throughout my doctoral program.

Even as they have been there for me throughout my life, my father, mother, sister, and

grandmother have provided assurance to every step on this course in my career.

vii

TABLE OF CONTENTS ACKNOWLEDGEMENTS……………………………………………………………....v LIST OF TABLES…………………………………………………………………..….viii LIST OF FIGURES………………………………………………………………………ix CHAPTER

1 INTRODUCTION……………………………………………………………1

2 REVIEW OF THE LITERATURE………………………………………......5

3 METHODS………………………………………………………………….22

4 RESULTS…………………………………………………………………...28

5 DISCUSSION…………………………………………………………….…49

REFERENCES….…………………………………………………………………..54

APPENDIX…………………………………………………………………………62

viii

LIST OF TABLES

Page

Table 1: Contingency Table to Test Season of Birth Effect upon Internalizing Disorder….27

Table 2: Number of Births by Month and Sex………………………………………….. 29

Table 3: Descriptive Statistics on BASC Internalizing Scales by Sex…………………. 30

Table 4: Overall Population Above and Below the 75th Percentile Cutscore…………... 32

Table 5: Observed Frequencies for Half-Year Split, by BASC Scale and Sex…………. 34

Table 6: Chi-Square Test of Independence, Half-Year Splits…………………………… 35

Table 7: Descriptive Statistics for Younger Children, by BASC Scale and Sex………... 36

Table 8: Descriptive Statistics for Older Children, by BASC Scale and Sex………….... 37

Table 9: Observed Frequencies for Younger Children: Half-Year Split, by BASC Scale and

Sex…………………………………………………………………………... 39

Table 10: Observed Frequencies for Older Children: Half-Year Split, by BASC Scale and

Sex……………………………………………………………………………….. 40

Table 11: Chi-Square Test of Independence for Younger Children, Half-Year Splits by

Sex……………………………………………………………………………….. 41

Table 12: Chi-Squared Test of Independence for Older Children, Half-Year Splits by

Sex……………………………………………………………………………….. 42

Table 13: Descriptive Statistics for BASC Internalizing Scales by Age Group……….... 63

Table 14: Chi-Square Tests of Independence, Age Group by Half-Year Split……….… 64

Table 15: Chi-Square Tests of Independence, Age Group by Season…………………... 65

Table 16: Chi-Square Tests of Independence, Age Group by Month……………..…….. 66

ix

LIST OF FIGURES

Page

Figure 1: Percentage of Children (Male and Female) Rated as High on Anxiety Born During

Each Season……………………………………………………………............... 44

Figure 2: Percentage of Children (Male and Female) Rated as High on Depression Born During

Each Season……………………………………………………………............... 45

Figure 3: Percentage of Children (Male and Female) Rated as High on Somatization Born

During Each Season…………………………………………...…………............. 46

Figure 4: Percentage of Children (Male and Female) Rated as High on Withdrawal Born During

Each Season……………………………………………………………................ 47

Figure 5: Percentage of Children (Male and Female) Rated as High on Internalizing Problems

Born During Each Season……………...…………………………….................... 48

Figure 6: Percentage of Children (Younger and Older) Rated as High on Anxiety Born During

Each Season……………………………………………………………................ 69

Figure 7: Percentage of Children (Younger and Older) Rated as High on Depression Born

During Each Season…………………………...………………………….............. 70

Figure 8: Percentage of Children (Younger and Older) Rated as High on Somatization Born

During Each Season……………………………………...……………….............. 71

Figure 9: Percentage of Children (Younger and Older) Rated as High on Withdrawal Born

During Each Season……………………………...……………………….............. 72

Figure 10: Percentage of Children (Younger and Older) Rated as High on Internalizing

Problems Born During Each Season……………………………………...……... 73

1

CHAPTER 1

Introduction

The search for the origin of psychopathology has been the subject of thousands of

research articles. Some studies focus on the implications of evolutionary theory and the influence

of genetic effects on the risk for psychopathology. Others look to the environmental variables

that play roles in the development of psychopathology. With few exceptions, however, nearly all

current theories acknowledge that behavior issues from the interplay of environment and

organism. The central nervous system (CNS) is at the nexus of this relationship.

It has been hypothesized that deviations from the normal operation of the CNS can

contribute to an individual’s dysfunctional behavior, including psychopathology. Developmental

anomalies of the CNS may underlay some abnormal CNS functions. Threats to the proper

development of the CNS structure, then, can affect physiological, morphological, biochemical,

and neurological mechanisms that contribute to CNS activity and are of interest to the student of

psychopathology.

The array of known environmental risks to fetal development is varied and of

undetermined size. The field of embryology refers to any such threat by the term teratogen,

signifying “monster maker” (A fusion of the Greek tera, meaning “monster” and geni, meaning

“growth”, the word originally denoted any prenatal disturbance causing the development of

grossly abnormal or deformed offspring). Research literature currently employs teratogen in an

expanded sense, referring to traumatic events or factors that initiate maldevelopment of the

2

nervous system that may underlie neurobehavioral disorders, including psychopathology (Mays

& Ward, 2003).

The effects of teratogens upon development depend upon the form of insult (mechanical

trauma, toxin, malnutrition, etc.), intensity (physical force, maternal blood alcohol level,

radiation dose, etc.), duration (momentary, repeated, persistent, etc.), and time of incidence

during the developmental process (Mayes & Ward, 2003). Teratogenic insult can range in effect

from death of the organism, to gross malformation of CNS structures, to consequences of lesser

degree, such as mental retardation. The outcomes of exposure to teratogens of a certain

magnitude are readily observed and related to their source. Teratogenic exposure at lower

intensities, or shorter durations, however, may yield subtle, difficult to detect, effects.

While the identity and extent of postnatal risk factors have become more clearly

understood, a mature comprehension of what and how prenatal factors affect future

psychopathology is yet to emerge. For example, poverty, under stimulation, malnutrition, and

physical abuse are childhood stressors that have been linked to risk for development of a variety

of psychological disorders. The identity of prenatal teratogens is less known, however. It is

suspected that the vulnerability of the organism during its prenatal development is greater than

after birth (Anderson, Northam, Hendy & Wrennall, 2001). Hence, factors that may present a

negligible risk to postnatal development may have more serious effects in the early stages of

neurodevelopment.

Research has shown that the timing of an insult to the central nervous system is a major

factor in determining the type and degree of any resultant altering of neural development (Mayes

& Ward, 2003). That is to say, critical periods exist during which the CNS is more susceptible to

3

deleterious effect of trauma or exposure to environmental variables (e.g. toxins, malnutrition,

radiation, etc.).

Some environmental variables are more prevalent at different times of the year, however.

For example, weather, insect-borne illnesses, diet, and photoperiods vary with the seasons.

These annual cyclical patterns present the opportunity to observe fluctuations in the influence of

these factors on overall development. Studies examining these patterns of influence have formed

a body of research literature sometimes referred to as season of birth research (Pasamanick &

Knobloch, 1958; Dalén, 1975; Castrogiovanni, Iapichino, Pacchierotti, Pierraccini, 1998).

Fetal exposure to perturbations such as hyperthermia and maternal infection has been

shown to have teratogenic effects on central nervous system development (Hunter, 1984;

Milunsky, et al., 1992). The timing and degree of gestational insult has varying developmental

influence over the course of a pregnancy (Aylward, 1997). Some research suggests

(Dombrowski, 2000) that environmental variables affecting nervous system development during

the second trimester may contribute to later development of psychological disorders, including

emotional problems. The incidence of seasonally varying phenomena with potentially

perturbational effects on prenatal child development has been associated with a heightened rate

of births of individuals who later present emotional behavior problems and psychopathology

(Gortmaker, Kagan, Caspi, & Silva, 1997; Pulver, et al., 1992).

Purpose

This study builds on previous studies that have examined season of birth effects for

nervous system disorders, schizophrenia, mental retardation and learning disabilities by

investigating the link between season of birth and the potential for occurrence of internalizing

problems such as social withdrawal, depression and anxiety. This research is intended to

4

examine if there are associations between the period of birth and later incidence of internalizing

behavior problems. A large sample of elementary school students comprised the pool of

research participants. The Behavior Assessment System for Children (Reynolds & Kamphaus,

1992), a rating scale for the report of an array of childhood psychological, social, and behavior

problems, was used to obtain data on internalizing problems of children. Analyses examined

monthly birth distributions for the children who had extreme scores on internalizing measures.

These analyses were done separately for each sex, and African-American and European-

American children. It was hypothesized that birthrates of these extreme-scoring children would

be higher in the spring and summer than during other times of the year.

5

CHAPTER 2

Review of the Literature

Season of birth research has been most extensively conducted in relation to birth patterns

of individuals diagnosed with schizophrenia. This review of the literature investigates this area

of research, its expansion to include broader areas of psychopathology, and the various

perturbations that may present teratogenic risks. First, however, an overview of

neurodevelopment and its relevance to psychopathology is presented.

Prenatal neurodevelopment

If the risk for development of psychopathology fluctuates according to the time of year an

individual is born, then it is reasonable to examine the processes that could introduce such a

threat during prenatal development. A physiological diathesis for psychopathology may be

established during prenatal central nervous system (CNS) development, a period when the

emerging neural structures and network are most vulnerable to insult.

Human CNS development begins within the development of the neural tube of the fetus

during early gestation, near the 40th day of embryonic life (Anderson, et al., 2001). At this time,

the period of cell proliferation known as cortical neurogenesis begins generating around 250,000

cells per minute (Papalia & Olds, 1992) until it largely ceases in the sixth month of gestation.

Once neurogenesis is complete, the creation of new neurons can never resume. The consequent

irreplaceability of neurons, then, gives significance to the injury or death of any cells in the CNS.

In addition to cortical neurogenesis, gestational CNS development includes the processes

of cell migration and differentiation. Cell migration involves the movement of neurons from the

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location of their genesis to their eventual permanent position in the CNS. The major period of

migration occurs between the 8th and 16th week of gestation, after which the process slows and

ceases at the 25th week (Kuzniecky, 1994).

Once neurons arrive at their ultimate destinations, they begin to differentiate, that is, to

develop into the specialized units specific to their role in the CNS. Development of the cell

soma, formation of axons and dendrites, establishment of synaptic connections, and selective cell

deaths adapt neurons to their functions. This maturation of neurons continues following birth

(Anderson, et al., 2001).

Postnatal neurodevelopment

The preponderance of research concerning neurodevelopmental pathology focuses on the

prenatal period, when the organism is particularly vulnerable to environmental teratogens. While

less susceptible to gross developmental errors, the ongoing development of the CNS is still

subject to disruption following birth. Postnatal development of the brain includes three

additional processes that are pertinent to the present study: dentritic arborisation, myelination,

and synaptogenesis. These aspects of CNS development concern the elaboration of the brain’s

neural network and enhancement of its functioning.

Dendritic arborisation involves the growth of narrowing appendages (dendrites) away

from the soma of nerve cells, thereby increasing the surface areas available for receiving

incoming information. Although this process may begin during the 25th to 30th week of

gestation, the majority of arborisation occurs postnatally with peak growth taking place between

5 and 21 weeks following birth (Becker, Armstrong, Chan, & Wood, 1984).

Myelination is the coiling growth of the myelin sheath over the axon, the outgoing

conduit for signals in transmission to the next neuron along the nerve path. This fatty matter

7

provides an insulation for nerves that increases the speed and efficiency of their transmission of

information. Myelination primarily occurs during the postnatal period, but its most rapid

development is found during the first three years of life and slower growth continues into

adolescence (Jernigan, & Tallal, 1990; Kinney, Brody, Kloman, & Gilles, 1988).

The development of the junctions between neurons (synapses), the process of

synaptogenesis begins in the second trimester as the cell migration phase draws to a close

(Molliver, Kostovic, & Van der Loos, 1973). The greatest period of development occurs

following birth, however. Unlike the neurodevelopmental processes previously discussed,

synaptogenesis seems to be largely invulnerable to environmental insults (Goldman-Rakic,

Bourgeois, & Rakic, 1997).

Teratogenic vulnerability

The term “teratogen” refers to any of the traumatic events or factors that initiate

maldevelopment of the nervous system that may underlie neurobehavioral disorders. Early

studies in neurodevelopmental teratology focused on grosser effects, such as physical

deformities, abnormal growths, major organ dysfunction, and death. The study of fetal exposure

to methyl mercury and radiation, for example, revealed clear teratogenic insults during some of

the emerging field’s initial research (Butcher, 1985). Teratogenic effects are not always so overt,

however, and researchers have expanded their investigations into more subtle effects of

environmental perturbations. Thereby, studies have come to gather on the identification of

teratogens and determination of their effects over periods of low and prolonged exposure (Mayes

& Ward, 2003).

The risks for neurological and psychiatric aftereffects from insults to the fetus were

highlighted fifty years ago by the research of Pasamanick and Knobloch (1965) and others.

8

Pregnancy and birthing complications have been associated with disorders such as cerebral palsy

(Lilienfeld & Pasamanick, 1955), epilepsy (Lilienfeld & Pasamanick, 1955), reading disability

(Kawl & Pasamanick, 1958), and hyperactivity and disorganized behaviors (Rogers, Lilienfeld,

& Pasamanick, 1955). This research also indicated that prenatal and parturitional insults tended

to affect the central nervous system in particular and could yield a continuum of negative

outcomes ranging from mild psychobehavioral deficits to death. The researchers came to refer to

the incidence of such outcomes as “reproductive casualty” (Pasamanick & Knobloch, 1965).

Most processes of neurodevelopment are subject to insults that threaten reproductive

casualty. Interference by environmental perturbations can alter the scheduled course of

development such that permanent disorders arise out of the subsequent abnormal CNS growth

and maturational processes. As Pennington (2002) describes:

Such mutations not only affect neuronal migration and lamination in a specific brain

structure but also alter neural connectivity more widely and presumably alter the

computational properties of neural networks. Hence, there is a resolution to the apparent

paradox of how a seemingly small, early change in brain development can have major

effects despite the sometimes impressive plasticity of the developing brain given a later

(and larger) acquired lesion. (p.xxx)

One of these developmental errors, disordered cell migration, for example, may result in

distribution of cells to wrong locations (Rayport, 1992) or abnormal concentrations of cells into

tight clusters (Kuzniecky, 1994). Dyslexia, schizophrenia, and deformed cerebral cortex are

among the disorders that have been associated with cell migration error (Geschwind, &

Galaburda, 1985; Weinberger, 1987; & Capone, 1996). Additionally, intellectual disability,

9

attention problems, and impaired processing speed have been linked to disruption of the

myelination process (van der Knapp, et al., 1991).

The type and intensity of insult naturally have implications for the nature of

neurodevelopmental pathology (e.g. radiation, mechanical trauma, and chemical toxins of

varying levels pose differing outcomes). Research has come to recognize, too, the existence of

general principles that govern the vulnerability of the developing CNS to insults and the degree

of abnormalities that may follow (Anderson, et al., 2001).

Aylward (1997), who estimates that developmental perturbations affect 25 percent of

conceptions, posits that the emergent structures are most vulnerable during the period of their

most rapid growth. Related to this idea, it is suggested that the timing of insult during certain

critical phases of neurodevelopment may have greater implications for outcomes than the nature

of the insult. It is thought, too, that the more prolonged a structure’s development, the more

subject it is to teratogenic insult; hence, the brain protracted developmental period makes it the

organ most susceptible to teratogenic insult.

The integrity of CNS development rests on the careful sequencing and timing of complex

processes, several of which have been mentioned. It is in the second trimester that much of the

prenatal CNS developmental neural pathways and network are formed. Near mid-gestation

(around week 20) both neurogenesis and cell migration are in full swing, a period that also sees

the onset of synaptogenesis (Anderson, et al., 2001).

In addition to general developmental errors of the CNS, disrupted functioning of specific

structures could have potential consequences for development of psychopathology. The

hypothalamus and limbic system contribute to the regulation of emotion, and the subcortical

limbic structures “profoundly influence affective behavior, including endocrine, autonomic,

10

arousal, and skeletomotor responses” (Devinsky & D’Esposito, 2004). Experimental stimulation

of the amygdala, for instance, “causes mild to moderate anxiety, terror, anger, a feeling of

"someone is behind me," paranoia, and visceral sensations” (Gloor, 1992). The idea of

neurodevelopmental disorder in these structures as a contributor to psychopathology has support

in data from magnetic resonance imaging that may link developmental errors in the amygdala

complex with bipolar disorder (Olsen, Bogerts, Coffman, Schwartzkopf, & Nasrallah, 1990;

Nasrallah, 1991).

Season of birth research

With knowledge of CNS development and its vulnerability to teratogens during critical

periods, researchers have begun to link the occurrence of developmental disorders to individuals’

season of birth. The perturbations posing risks to CNS development are continuously present

throughout the year. Cyclical amplification of these perturbations, however, may present

corresponding fluctuations in the incidence of negative neurodevelopmental outcomes. Season

of birth research, then, explores the possibility that birth patterns of individuals presenting with a

set of psychological problems can give insight into the identity and effects of teratogens

contributing to the risk for psychopathology.

The significance of season of birth to individuals’ behavior and emotions has been of

interest for centuries and may be seen in the origination of natal astrology by ancient Greeks

(Tester, 1987). The scientific examination of the relationship of season of birth to individual

characteristics, however, is a relatively recent occurrence. Huntington’s (1938) study of

intelligence and health marks one of the earlier efforts to apply scientific methods to the

association of individual differences and season of birth. Since then, the field has steadily

grown. A subset of this research has been devoted to the relation of season of birth to the risk

11

for psychopathology. Data collected in dozens of countries has now contributed to over 250

published studies considering this association, particularly as it relates to schizophrenia (Torrey,

Miller, Rawlings, & Yolken, 1997).

Schizophrenia Birth Patterns

An overview of the literature reveals that a considerable portion of season of birth studies

identify an excess of winter and early spring births of individuals diagnosed with schizophrenia,

between 5 and 15 percent more than expected by chance (Bradbury & Miller, 1985). Other

researchers have found birth peaks occurring later in the year. Kirkpatrick, Castanedo, and

Vazquez-Barquero (2002), for example, found an excess of births in the May to August period in

northern Spain, and a second study (Kirkpatrick, Tek, Alladyce, Morrison, & McCreadie, 2002)

revealed a similar pattern among Scottish subjects. This research indicates associations of

schizophrenic birth patterns with a variety of suspected cyclically occurring perturbations.

Maternal viral infection has been the focus of many of these studies.

Many, though not all, researchers have found an association between the rise and

subsidence of influenza epidemics and the season of birth patterns for schizophrenia (Adams,

Kendell, Hare, & Munk-Jorgensen, 1993; Andreasen, 1997; Boyd, Pulver, & Stewart, 1986;

Livingston, Adam, & Bracha, 1993). Data in these studies show increases in births of subjects

with schizophrenia starting approximately three months after the onset of influenza epidemics.

This suggests that some teratogenic insult may have been sustained during the critical

development period of the second trimester. It is yet, however, unclear what mechanism might

be at work as a result of any maternal viral infection. Flu symptoms, such as fever and nausea,

immune system response, and influenza treatment have been proposed as possibilities

12

(Dombrowski, Martin, & Huttunen, 2003; Lynberg, Khoury, Lu, & Cocian, 1994, as cited in

Takei, & O’Callaghan, 1995).

In addition to influenza, prenatal exposure to poliovirus has been related to the later

development of schizophrenia (Suvisaari, Haukka, Tanskanen, Hovi, & Lönnqvist, 1999; Torrey,

Rawlings, & Waldman, 1988, as cited by Suvisaari, Haukka, Tanskanen, Hovi, & Lönnqvist,

1999). Other researchers, however, have found no relationship between poliovirus exposure and

season of birth patterns (Watson, Kucula, Tilleskjor, & Jacobs, 1984, as cited by Suvisaari,

Haukka, Tanskanen, Hovi, & Lönnqvist, 1999).

Malnutrition is a known contributor to neurodevelopmental defects, and its relationship to

increased risk for developing schizophrenia has been shown in studies following the Dutch

famine in the latter days of the Second World War. Research on the birth cohort from this period

shows fetal exposure to the famine yielded significantly increased risk for development of

schizophrenia (Brown & Susser, 2003).

The importance of nutrition during gestation is well established. Gravid malnutrition can

lead to fetal development problems affecting every aspect of the organism. Nutritional deficits

have been considered as possible contributors to season of birth patterns (de Sauvage Nolting,

1954, as cited in Castrogiovanni, 1998; Torrey, Torrey, & Peterson, 1977, as cited in

Castrogiovanni, 1998) because of changes in diet that result in deficiencies of vitamins.

Researchers are now gaining an understanding of the mechanisms by which dietary and

nutritional deficiencies may compromise the development of the neural systems involved in

emotional regulation. New information in this area is coming from the field of epigenetics, the

study of heritable traits not involving alteration of the gene sequence.

13

A recent epigenetic study (Waterland & Jirtle, 2003) identified a mechanism in mice by

which maternal nutrition can effect permanent changes in the functioning of an offspring’s

genes. Researchers supplemented the diets of gravid yellow agouti mice with folic acid, B12,

choline, and betaine and found that this nutrient combination activated a trigger for a gene

determining hair color and predisposition for obesity, diabetes, and cancer. This direct link

between nutrition and epigenetic developmental outcomes in mice suggests that human genes

determining biological risks for psychopathology are also subject to nutritional teratogens.

The risk for developing schizophrenia has a significant heritable component, but not all

schizophrenics have a familial history of the disorder. Because season of birth patterns are

thought to be due to environmental variables, researchers have looked for distinctions between

schizophrenia probably brought about by genetics from that of a teratogenic etiology. With this

in mind, investigators have examined data on eye tracking dysfunction (ETD), one of several

comorbid conditions to which those with schizophrenia are vulnerable and which occurs at a

higher than normal rate among their relatives, both with and without schizophrenia. A 1999

study found that schizophrenics without ETD were significantly more likely to be born in months

of extreme temperature (hot or cold) than those with ETD (Kinney, Levy, Yurgelun-Todd,

Holzman, & Lajonchere, 1999). This suggests that seasonal birth excesses for schizophrenic

individuals are unlikely due to genetic factors operating independently of the environment. A

recent study lends additional support to this idea by finding no relationship between

schizophrenic individuals’ birth month and their siblings’ risk for developing schizophrenia

(Suvisaari, Haukka, & Lönnqvist, 2004).

Cyclical Events & Seasonal Birth Patterns

14

In exploring the relationship of season of birth to psychopathology, it is useful to look at

other birth phenomena that also exhibit patterns across the year. The crests and troughs of birth

patterns related to some phenomena are similar to those for mental disorders and may result from

shared environmental influences. Researchers have examined variables such as diet, climate,

work activities, and incidence of holidays as possible influences on the development of these

patterns.

The rate of births for the general population is not constant throughout the year and often

shows an annual seasonal pattern. Identifying these birth rate patterns lends context for the

interpretation of the birth seasonality of individuals with psychopathology. Recognition of ebbs

and rises in overall births is, of course, essential to detection of excessive proportions of births

among those with psychopathology. Moreover, research shows that birth rate patterns frequently

differ between ethnic groups and regions, and examination of this literature may assist in

resolving inconsistencies among the hundreds of published season of birth studies conducted

around the world.

In the southern United States, the lowest numbers of births occur in the April to May

period for both European-Americans and Nonwhites. The same nadir in births can be seen

among Nonwhites in northern states, but the pattern is more pronounced in the southern states

(Lam & Miron, 1994). Seasonal patterns in Israel, as well as the Delhi, Maharashtra, and Punjab

regions of India, are similar to those of the American south. The pattern of births is quite

different in western Europe, where the highest, not the lowest, numbers of births occur in the

spring. Within Europe, the amplitude of this pattern increases progressively from the

Mediterranean to Scandinavia (Lam & Miron, 1994; Levine, 1994). Interestingly, the latitudinal

positions of these regions generally correspond with the patterns of their birth rates; the southern

15

United States, Israel, Delhi, and Punjab all lay along the 30th parallel, whereas the majority of

Europe rests between the 40th and 60th parallels.

Although the exact significance of geographical latitude to seasonal birth patterns is

undetermined, some have looked to regional temperature differences for an explanation. Baker

and Lester (1986) compared May and November birth rates in the 48 coterminous U.S. states for

a five-year period and found a ratio varying from 0.85 in Louisiana to 1.12 for Washington and

Oregon. These results are consistent with the findings of other studies that identified low birth

rate in May in hot southern regions in comparison with the cooler northern areas (Lam & Miron,

1994; Levine, 1994). The researchers cited the contrast, for example, of the May/November

birth ratio of 0.73 in Singapore with that of 1.30 in Sweden.

Short-term increases in ambient temperature have been associated with lowered birth

rates nine months later in France, the southern United States, and rural Bangladesh. The most

well defined patterns of birthrate seasonality are found in zones of extreme summer heat. This

may be attributable, in part, to the known negative effect of high temperature on sperm

production and motility. These seasonal patterns have shifted somewhat during the past twenty

years, however. Even though the general rise and fall of birth numbers remained constant, the

peaks and troughs grew less pronounced. In Louisiana and Georgia, for example, the mean

annual low point for births during the 1942 to 1968 period fell in May, when the number of

births was 10 to 20 percent lower than the overall monthly average for the same period. Between

1969 and 1988, however, the amplitude of birth peaks and troughs diminished, with the low

point of European-American births approximately 5 to 9 percent lower than the overall monthly

average. This may be due to the advent of widespread use of air conditioning and the reduction

of outdoor and agricultural jobs during this period. Although Nonwhite birth patterns showed a

16

decrease in amplitude from the 1942 to 1968 period as well, it was only slight, perhaps a

reflection of less access to air conditioning or a slower transition to indoor work environments

(Lam & Miron, 1994).

When looking for environmental factors that vary with regularity over the passage of the

year, seasonal changes in daylength quickly come to mind. Photoperiod affects reproduction

(Foster, Ebling, Claypool, & Wood, 1989) and body weight (Bartness & Wade, 1985) in many

mammals. It has been hypothesized that such biochemical responses to length of daylight

exposure may be a contributory factor in some season of birth patterns for some individuals

(Gortmaker, et al., 1997).

Martin and Kimlin’s (unpublished manuscript) study of vitamin D as a possible influence

on season of birth patterns of neurodevelopment offers a connection between research regarding

nutrition and daylength. Vitamin D is produced by skin exposure to the ultraviolet (UV)

radiation in sunlight and is thought to contribute to the development and function of the nervous

system. Martin and Kimlin hypothesized that subnormal levels of maternal vitamin D may

increase the risk for mental retardation, a condition diagnosed for an excess of individuals born

in the August to November period and for fewer than expected in the winter months. Data

analysis established a relationship between births of children with mental retardation and the

amount of available UV radiation during the first and second months of gestation. These

findings open the way to further research into the influence of UV radiation on other season of

birth phenomena, such as internalizing disorders.

If regular annual events such as transitions in temperature and photoperiod bear upon

seasonal birth patterns, it may be anticipated that the patterns observed in the northern

hemisphere would be reversed below the equator: in other words, displaced by six months. This,

17

in fact, appears to be the case in South Africa, where the greatest number of births for both

European-Africans and Black-Africans occurs in September, a difference of about a half-year

from the birth peak in Europe. Australia and New Zealand also experience September peaks,

though Australia has another, slightly greater, peak in March (Lam & Miron, 1994).

Some southern hemisphere studies, however, have found little or no season of birth

effects. McGrath and Welham (1999), for instance, conducted a meta-analysis of four studies of

southern hemisphere populations and found small, non-significant differences in seasonal birth

patterns for individuals diagnosed with schizophrenia. The authors proposed that if season of

birth “acts as a proxy marker for fluctuating non-genetic risk-modifying factors for

schizophrenia…[then] in the Southern Hemisphere these factors may be weaker, less prevalent,

less regular, and/or may be modified by other confounding or modifying variables.”

The season of birth research regarding other cyclical meteorological phenomena has been

limited as yet. A 2001 report by de Messias, Cordeiro, Sampaio, Bartko, and Kilpatrick found an

association between monthly rainfall and the number of schizophrenic births three months later.

This finding is particularly compelling, because its data were drawn from northeastern Brazil, a

tropical region with little temperature change year round but offering distinct and extreme annual

wet and dry seasons.

Another meteorological phenomenon, geomagnetic storms, was investigated by Kay

(2004), who found that the birth data from six of eight schizophrenia studies negatively

correlated with indices of geomagnetic storm activity. Previous research has often found scant

evidence of season of birth patterns in equatorial and tropical zones (McGrath & Welham, 1999;

Parker, Mahendran, Koh, & Machin, 2000); therefore this study may guide future investigators

to include precipitation in their studies analyses of data. These results, like those of the Brazilian

18

study, remain unique until replicative investigation is conducted. They are important indicators,

however, of directions for future research.

Internalizing disorders

The preponderance of season of birth research has concerned schizophrenia, but attention

has also been directed to the examination of other forms of psychopathology. Internalizing

problems, the subject of the present study, have been the subject of a portion of this research.

Though far fewer internalizing problem studies exist than in schizophrenia-related birth research,

investigators have uncovered similar birth patterns and perturbation associations.

Some research has found seasonal patterns in the birth months of anxiety disorders. A

study of 843 subjects diagnosed with panic disorder (PD) found peaks in September and

December birth months (Castrogiovanni, Iapichino, Pacchierotti, & Pieraccini, 1999). This

pattern was consistent among patients having only a PD diagnosis and those with comorbid

disorders. This study found no significant variation in the birth month distribution among 1,181

subjects with other psychiatric diagnoses.

Penas-Lledo, Santos, Leal, and Waller (2003) found excess births for those with anorexia

in the June through August period. Anorexia has a high comorbidity with anxiety disorders, at

rates estimated as high as 73 percent (Toner, Garfinkel, & Garner, 1988, as cited in Wilson,

Heffernan, & Black, 1996). Those with acute anorexia have been reported to have comorbid

depression at a rate estimated between 21 and 91 percent (Kaye, Weltzen, & Hsu, 1993, as cited

in Wilson, et al., 1996).

In a review of season of birth research concerning affective disorders, Castrogiovanni, et

al., (1998) cite studies that consistently found an excess of winter/spring births and deficits in the

September to November period among patients with bipolar disorder. Similar season of birth

19

patterns have also been found among individuals with unipolar disorder. A study of 4,393 Irish

subjects diagnosed with the affective disorder found a significant excess of the individuals were

born in the spring and a significant deficit were born in the autumn (Clarke, et al., 1998).

At least one study has also linked maternal viral exposure to increased incidence of

internalizing disorders. Machón, Mednick, and Huttunen (1997) found within a Finnish

population that exposure to an influenza epidemic during the second trimester of gestation

increased the risk for development of major affective disorder in adulthood.

Season of birth effects have been found in age and method of suicide. A British study

(Salib, 2002) found a significant excess among 502 suicides for those individuals born in May.

Chotai, Renberg, and Jacobsson (1999) examined the 1,457 suicides that occurred between 1952

and 1993 in a region of Sweden. Analysis revealed that subjects younger than 45 years were

more likely to have been born during the February to April period. The investigators conducting

the Swedish study considered suicide as an indicator of internalizing problems. The periods of

elevated suicide are consistent with season of birth patterns related to fluctuations among

individuals’ levels of cerebrospinal fluid (CSF) monamine metabolites. Significantly low levels

of these metabolites have been found among patients diagnosed with mood, anxiety, and

adjustment disorders who were born in the February to April period (Chotai, & Åsberg, 1999).

Unusually low levels of these metabolites indicate a correspondingly low production of

serotonin, dopamine, and norepinephrine, a circumstance associated with depression. This study

is notable for its incorporation of medical data, an element largely missing from season of birth

research due to the expense and difficulty in obtaining such data from large numbers of subjects.

If suicide is a marker for depression and other affective disorders, then the risk for these

psychopathologies may be indicated in infant growth problems. Barker, Osmond, Rodin, Fall,

20

and Winter (1995) found an association between suicide and low weight gain during infancy. A

study of over 11,000 children between ages 6 and 24 months revealed that those born in the three

months following the year’s coldest months were at significantly greater risk for being below the

fifth percentile in weight (Frank, et al., 1996). The Barker, et al. study notes that patients with

depression have been found to have abnormal secretion of growth hormone and abnormalities in

the hypothalamus, which is thought to be programmed for hormonal secretions during gestation.

Although neuropsychologists have recently come to view the role of the hypothalamus in

emotion as less pivotal than in the past (Gainotti, 2000), its abnormal functioning may signal the

presence of developmental errors elsewhere in the CNS.

Because the majority of research programs are found in the nations of the North

American and European continents, the majority of season of birth studies have consequently

examined human populations in the northern hemisphere. With limited data from the southern

hemisphere, few have addressed the question of whether the opposite seasonal cycles of the

hemispheres present correspondingly inverse patterns of births for individuals with internalizing

problems.

One of the studies examining this question is that of Gortmaker, et al. (1997), who

compared U.S. and New Zealand populations and found an association between daylength during

pregnancy and shy offspring. Children whose gestation was centered during the interval of five

months with the shortest photoperiods (winter) were disproportionately likely to develop traits of

excessive shyness. In America, members of this group were 1.52 times more likely to be

considered shy than those whose gestation centered in months with longer lengths of daylight.

The New Zealand children who gestated during the span of winter months stood a similar 1.69

times greater chance of being rated as inhibited in comparison to those children exposed to

21

longer photoperiods en utero. The authors of the study estimated that the risk attributable to

gestation in shorter photoperiods was associated with approximately one of ever five cases of

extreme shyness in children.

Another study examined an Australian population for relationships between region of

gestation, internalizing symptoms and birth month. Joiner, Pfaff, Acres, and Johnson (2002)

examined data collected from residents of Australia, some of whom were born in that the

southern hemisphere and others who were born in the northern hemisphere. The researchers

found that subjects who were in utero in the southern hemisphere during that region’s flu peak

showed a higher degree of suicidal and depressive symptoms than other subjects who were in

gestation in the southern hemisphere. Likewise, those Australians who had been in utero in the

northern hemisphere’s peak flu season showed a greater level of suicidal and depressive

symptoms. The September to November period of high internalizing births for southern

hemisphere represents a six-month difference from the March to May birth peak of the northern

hemisphere in this study, suggesting the presence of a seasonal prenatal risk for depressive and

suicidal symptoms.

As stated earlier, the research concerning the season of birth of those with psychological

disorders remains an emerging field of study. The literature is diffuse and often inconsistent, yet

some patterns are beginning to appear for birth periods of increase risk. The present study is an

attempt to contribute to this growing body of research.

22

CHAPTER 3

Methods

Sample

Data studied in this investigation were obtained from 2,619 children between the ages of

5 and 12 years, who participated in Project ACT Early (ACT Early website:

http://www.coe.uga.edu/actearly/index.html). The project, funded by the U.S. Department of

Education, was designed to “understand the ecological context of risk in elementary school and

to help teachers acquire effective classroom strategies to intervene early in children's school

careers” (http://www.coe.uga.edu/actearly/index.html).

The ACT Early sample consists of 1,306 males (49.9%) and 1,313 females (50.1%).

Students receiving full-time special education services were not included in the study. The

sample to be analyzed is ethnically diverse. The majority of the students are from African-

American (848 students, 32.4%) or European-American backgrounds (560 students, 21.4%).

Other racial groups are present in smaller numbers. These include 62 (2.4%) Hispanic students,

41 (1.6%) Asian-American students, 30 (1.1%) Multi-racial students. Forty-one percent of the

sample (1076 students) did not provide race information.

Instrumentation

Emotional and behavioral problems of the sample children were assessed via the

Behavior Assessment System for Children (BASC; Reynolds & Kamphaus, 1992). The BASC

manual (Reynolds & Kamphaus, 1992) provides reliability estimates for the TRS-P and TRS-C

forms. The TRS-P reliablity estimates are: Anxiety = .84; Depression = .85; Somatization = .79;

http://www.coe.uga.edu/actearly/index.html

http://www.coe.uga.edu/actearly/index.html

23

Withdrawal = .92; Internalizing Problems = 86, for the TRS-C these are: Anxiety = .87;

Depression = .88; Somatization = .70; Withdrawal = .86; Internalizing Problems = 85. The

internal consistencies for the TRS-P and TRS-C are also reported for both the TRS-P (Anxiety =

.66; Depression = .77; Somatization = .67; Withdrawal = .84; Internalizing Problems = 82) and

the TRS-C (Anxiety = .74; Depression = .85; Somatization = .80; Withdrawal = .79;

Internalizing Problems = 89). These data indicate appropriate reliabilities for research purposes.

For purposes of the current study, elementary school teachers provided ratings of their

students using the Teacher Rating Scale – Child (TRS-C) and Teacher Rating Scale – Preschool

(TRS-P) forms. For each child, teachers provided ratings on a four-point Likert scale. The

resultant data are aggregated into 14 behavioral and social skills scales. Three of these scales

measure behaviors associated with internalizing disorders: Depression, Anxiety, Somatization.

These three internalizing scales have the same operational definition for both the TRS-P and

TRS-C forms.

The BASC scales are designed for individual interpretation. The instrument, however,

also yields composite scores for various domains of social-emotional behavior. The Depression,

Anxiety, and Somatization scales can be aggregated to form the Internalizing Problems

composite score. The fourth scale under examination in the present study, Withdrawal, is not

part of the BASC Internalizing Problems domain. The Withdrawal scale measures the

inclination to avoid social contact and was not highly related to other internalizing scales (some

socially withdrawn children experience no internalizing problems). It was, however, of interest

given the finding of a season of birth effect for shyness.

24

Methods

As a component of the ACT Early project, BASC questionnaires were distributed to the

homeroom teachers of students in four public elementary schools in Athens-Clarke County,

Georgia. These data were collected from the teachers during the fall and spring over a six-year

period.

The BASC manual (Reynolds & Kamphaus, 1992) designates a T-score of 60 as the

threshold for an at-risk level of behavior problems on its subscales and composite scales. The

present study, however, is not concerned with the clinical diagnosis of individual psychosocial

behaviors; rather, it is exploratory in nature and concerned with broad patterns across a research

population. Therefore, a lower cut score was used for selecting subjects for inclusion in groups

designated as having concerning levels of problems. Individual students were considered to

exhibit notable internalizing behaviors if any of their BASC scores on a particular subscale was

at or above the 75th percentile for the research population.

The hypotheses investigated are as follows:

Hypothesis 1: There will be a higher proportion of children with Depression scale scores at

or above the 75th percentile who were born in the spring and summer than during the fall and

winter.

Hypothesis 2: There will be a higher proportion of children with Anxiety scale scores at or

above the 75th percentile who were born in the spring and summer than during the fall and

winter.

Hypothesis 3: There will be a higher proportion of children with Somatization scale scores at


winter.

25

Hypothesis 4: There will be a higher proportion of children with Withdrawal scale scores at


winter.

Hypothesis 5: There will be a higher proportion of children with Internalizing Composite

scores at or above the 75th percentile who were born in the spring and summer than during

the fall and winter.

To address the hypotheses, the following steps were taken. First, students with scores at

or above the 75th percentile (P75) on the BASC TRS-C and TRS-P were noted. The frequency of

births per month for these students were compared to the frequency of births of students below

the cut score. Next, the students in the two groups (>75th percentile, ≤ 75th percentile) were

compared using a chi-square analysis test of independence. To test the hypothesis, the analysis

was carried out based on data in a 2 x 2 contingency table. Table 1 provides an example of the

contingency table and the categories was used in the testing.

It was expected that the frequency of students in cell D will be disproportionally high and

the frequency in cell B would be disproportionally low, compared to cells A and C, resulting in a

significant chi-square value. These analyses were investigated by gender and age range to

determine if seasonal birth patterns differed for males and females, or for younger (ages 5 to 7

years) and older (age 8 to 12 years) children.

Follow up analysis at the seasonal level (resulting in a 4 x 2 frequency table) and at the

monthly level (resulting in a 12 x 2 frequency table) were also be calculated. These analyses

helped determine if births during a particular season, or month, or series of months, were

disproportionally high for children above the 75th percentile cut score on each of the five

measures (anxiety, depression, somatization, Internalizing aggregate, and social withdrawal).

26

Seasons were defined as follows: Winter – January, February, March; Spring – April, May, June;

Summer – July, August, September; Fall – October, November, December.

It is noted that tests for the follow-up hypotheses followed the same sequencing as with

the intital hypotheses and also employed the 75th percentile as the cutoff score to identify

children with internalizing problems. Additionally, the set of analyses were conducted seperately

for males and females, and for older and younger age ranges, to determine gender effects of

season of birth on internalizing problems.

27

Table 1

Contingency Table to Test Season of Birth Effect upon Internalizing Disorder

Internalizing Scores

Low (<P75) High (≥ P75)

Birth Period

Fall, Winter A B

Spring Summer C D

28

CHAPTER 4

Results

To assess the possible impact of season of birth upon students judged to have high levels

of internalizing disorders, it is important to have a sizeable number of students who were born

during each month. Table 2 presents the distributions of births of all children, divided by month

of birth. Gender, by month of birth, is also included. Inspection of Table 2 indicates that data

from more than 200 students are available for each month of birth. This distribution affords a

sufficient number of children with extreme scores to test the hypotheses of interest in this study.

This study examined the possible associations between birth month and internalizing

behaviors. The sample size available for analysis was sufficient to examine this relationship

according to participants’ sex. Patterns of greater portions of spring and summer births of

children were observed for the entire sample as well as for each sex.

Descriptives

A total of five internalizing scales from the BASC were investigated. Descriptive

information for each of the scales is provided in Table 3. As seen in Table 3, most TRS-P and

TRS-C scores are close to the normed mean of 50 and standard deviation of 10. Considering the

results by gender, there are minor fluctuations by sex.

29

Table 2

Number of Births by Month and Sex

Month Male Female Total

January 134 86 220

February 102 102 204

March 95 111 206

April 114 105 219

May 105 121 226

June 90 124 214

July 117 138 255

August 104 117 221

September 104 103 207

October 113 96 209

November 112 98 210

December 116 112 228

Total 1,306 1,313 2,619

30

Table 3

Descriptive Statistics on BASC Internalizing Scales

Variable Mean Std. Dev. Min. Max.

Anxiety Total Sample 47.49 9.70 37 107

Male 47.79 9.69 37 104

Female 47.20 9.71 37 107

Depression Total Sample 48.88 10.05 37 113

Male 49.74 10.50 37 113

Female 48.03 9.52 37 105

Somatization Total Sample 48.19 10.01 40 98

Male 47.22 8.65 40 90

Female 49.17 11.13 40 98

Withdrawal Total Sample 48.29 10.28 35 106

Male 48.38 10.49 35 106

Female 48.19 10.08 35 100

Internalizing Total Sample 47.76 9.75 35 108

Composite Male 47.83 9.45 35 108

Female 47.69 10.05 35 98

31

Cut scores

It was necessary to quantitatively define the members of the data set to be regarded as

“at-risk” for the purpose of this study. BASC scores at or above P75 for the research population

were considered indicative of notably troubling behavior. All participants scores were ranked in

order to identify the third quartile point (P75) for each scale. The t-score equaling the 75th

percentile point on each scale served as the cut-score for identifying children presenting an at-

risk level of behavior problems. The cut scores for the five internalizing scales under study, as

well as counts of children above and below the 75th percentile level, are shown in Table 4.

Tests of Hypotheses

At the outset, a series of chi-square tests of independence were used to determine if a

relationship between season of birth and internalizing disorders could be identified.

Hypotheses 1-5 assert that there will be a higher proportion of children born in the

Spring/Summer period than in the Fall/Winter period who are viewed as having BASC subscale

scores ≥75th percentile. These hypotheses differ in that the dependent variables relate to different

BASC scales in each of 1 through 5.

The data set was split into two groups for the initial analysis. Participants were divided

according to which half of the year they were born. One group consisted of those born in the

Spring/Summer period, defined as spanning the months from April to September, inclusive. The

Fall/Winter group was formed by subjects born in the months from October to March, inclusive.

Table 5 presents frequency information for the four categories described in Table 3.

32

Table 4

Overall Population Above and Below the 75th Percentile Cutscore

BASC Scale t-score at P75 N < P75 N ≥ P75

Anxiety All 52 1870 (71.4%) 749 (28.6%)

Male 52 910 (69.7%) 396 (30.3%)

Female 52 960 (73.1%) 353 (26.9%)

Depression All 54 1888 (72.1%) 731 (27.9%)

Male 54 897 (68.7%) 409 (31.3%)

Female 51 903 (68.8%) 410 (31.2%)

Somatization All 51 1825 (69.7%) 794 (30.3%)

Male 51 943 (72.2%) 363 (27.8%)

Female 55 983 (74.9%) 330 (25.1%)

Withdrawal All 54 1964 (75.0%) 655 (25.0%)

Male 55 976 (94.7%) 330 (25.3%)

Female 51 885 (67.4%) 428 (32.6%)

Internalizing

Composite

All 52 1905 (72.7%) 714 (27.3%)

Male 52 954 (73.0%) 352 (27.0%)

Female 52 951 (72.4%) 362 (27.6%)

33

Higher than expected births during this phase were observed for high-score children on the

Anxiety scale and the Internalizing Problems Composite in overall samples. Also, more high-

score females on the Anxiety and Depression scales were born in Spring/Summer than expected.

Separate chi-square tests of independence were conducted for the overall population,

males, and females. Results of this test are provided in Table 6. The final column of the table

identifies the portion of the year containing the largest difference. It is noted that alpha levels of

below .05 denoted statistically significant results. However, because this is an exploratory study,

resultant probability values between .05 and .10 were also noted.

Results of the analyses showed a significant relationship between season of birth and

scores at or above the 75th percentile for two variables: Anxiety and the Internalizing Composite.

Investigating the relationships by gender showed a statistically significant relationship for

females’ Anxiety scores and a marginal difference was noted for the females’ Depression scores.

While many of the tests did not show statistically significant results, it is noted that all except

one test showed elevated scores in the intended direction.

In order to better understand these patterns, the data were separated into additional

sections by splitting the divided males and females into older and younger groups. Descriptive

information for these four catagories of children is presented in Tables 7 and 8.

34

Table 5

Observed Frequencies for Half-Year Split, by BASC Scale and Sex

Variable Split Fall/Winter

Score < P75

Fall/Winter

Score ≥ P75

Spring/Summer

Score < P75

Spring/Summer

Score ≥ P75

Anxiety All 939 (912) 338 (365) 931 (958) 411 (384)

Male 480 192 430 204

Female 459 (452) 146 (163) 501 (518) 207 (190)

Depression All 927 350 961 381

Male 459 213 438 196

Female 468 (457) 137 (148) 523 (534) 185 (174)

Somatization All 900 377 925 417

Male 488 184 455 189

Female 412 193 470 238

Withdrawal All 971 306 993 349

Male 508 164 463 171

Female 463 142 530 178

Internalizing

Composite

All 952 (929) 325 (348) 953 (976) 389 (366)

Male 502 170 452 182

Female 450 155 501 207

Note: Values in parentheses are expected values; expected values are reported for any test where p≤ .10.

35

Table 6

Chi-Square Test of Independence, Half Year Split (Spring/Summer, Winter/Fall)

Variable Split Χ2 Df P Peak

Anxiety All 5.539 1 .019* Spring/Summer

Male 2.007 1 .157 Spring/Summer

Female 4.325 1 .038* Spring/Summer

Depression All .314 1 .575 Spring/Summer

Male .093 1 .761 Fall/Winter

Female 3.617 1 .057† Spring/Summer

Somatization All .745 1 .388 Spring/Summer

Male .118 1 .731 Spring/Summer

Female 2.368 1 .124 Spring/Summer

Withdrawal All 1.457 1 .227 Spring/Summer



Internalizing

Composite

All 4.127 1 .042* Spring/Summer



Note: * = p < .05; † = p < .10

36

Table 7 Descriptive Statistics for Younger Children, by BASC Scale and Sex Variable Group Mean Std. Dev. Min. Max.

Anxiety Male 49.99 10.10 37 104

Female 49.84 10.66 37 107

Depression Male 49.74 10.69 37 100

Female 48.85 10.35 37 95

Somatization Male 48.26 9.82 40 90

Female 50.07 11.61 40 90

Withdrawal Male 48.51 11.00 35 96

Female 48.68 10.26 35 100

Internalizing Male 49.07 10.30 35 108

Composite Female 49.38 11.13 35 97

Note: Sample size for males = 571; Sample size for females = 550.

37

Table 8 Descriptive Statistics for Older Children, by BASC Scale and Sex Variable Group Mean Std. Dev. Min. Max.

Anxiety Male 46.08 9.00 34 99

Female 45.29 8.84 39 105

Depression Male 49.73 10.35 41 113

Female 47.44 8.84 41 105

Somatization Male 46.41 7.52 52 85

Female 48.51 10.73 42 98

Withdrawal Male 48.27 10.11 39 106

Female 47.85 9.93 39 100

Internalizing Male 46.88 8.62 39 97

Composite Female 46.47 9.01 39 98

Note: Sample size for males = 735; Sample size for females = 763.

38

Table 9 reports frequency information for younger children. Examination of the scores

above the 75th percentile shows higher numbers of births in Spring/Summer for many of the

scales. However, Table 11 did not report statistically significant differences between the scores.

Only one scale, Anxiety, where the alpha level <.10, showed more high-score younger females

than expected born in Spring/Summer.

Table 10 reports frequency information for older children. As seen in Table 12, there

were no significant differences from the expected for children in the older age group.

Data trends can be difficult to discern amid tabled test results. Therefore, birth season

statistics for the population were graphed for each BASC scale and are presented in Figures 1-7.

These are shown as percentages in order to simplify comparison between scales. For each BASC

scale, the number of participants with scores ≥P75 born in each season was stated as a percentage

of all high-score children. The derived figures create plotting points for another graph line for

comparing observed proportions with the expected. Separate graph lines for males and females

were created in the same manner.

The graph for Anxiety shows births of high-score females rising above the baseline of

births to a pronounced peak in the Spring period. Anxious males show a less discernable pattern

across the seasons, having a softer crest in births during the Summer period.

On the Depression scale, a peak in births of high-score females clearly occurs in the

Spring period and their nadir can be as easily observed for the Fall. The birth pattern for males

appears opposite, albeit to a somewhat more muted degree of amplitude from

39

Table 9

Observed Frequencies for Younger Children: Half-Year Split, by BASC Scale and Sex


Score < P75

Fall/Winter

Score ≥ P75

Spring/Summer

Score < P75

Spring/Summer

Score ≥ P75

Anxiety Male 181 103 170 117

Female 177 (162) 83 (94) 179 (188) 117 (108)

Depression Male 194 90 198 89

Female 193 61 207 89

Somatization Male 200 84 192 95

Female 163 91 189 107

Withdrawal Male 216 68 204 83

Female 189 65 208 88

Internalizing Male 201 83 188 99

Composite Female 174 80 192 104

Note: Values in parentheses are expected values; expected values are reported for any test where p≤ .10.

40

Table 10 Observed Frequencies for Older Children: Half-Year Split, by BASC Scale and Sex


Score < P75

Fall/Winter

Score ≥ P75

Spring/Summer

Score < P75

Spring/Summer

Score ≥ P75

Anxiety Male 299 89 260 87

Female 288 63 322 90

Depression Male 265 123 240 107

Female 275 76 316 96

Somatization Male 288 100 263 84

Female 249 102 281 131

Withdrawal Male 292 96 259 88

Female 274 77 322 90

Internalizing Male 301 87 264 83

Composite Female 276 75 309 103

41

Table 11 Chi-square Tests of Independence for Younger Children, Half-Year Splits by Sex


Anxiety Male 1.220 1 .269 Fall/Winter


Depression Male 0.031 1 .864 Spring/Summer


Somatization Male 0.824 1 .364 Spring/Summer


Withdrawal Male 1.817 1 .178 Spring/Summer


Internalizing Male 1.825 1 .177 Spring/Summer

Composite Female 0.813 1 .367 Spring/Summer

42

Table 12 Chi-square Tests of Independence for Older Children, Half-Year Splits by Sex


Anxiety Male 0.064 1 .801 Spring/Summer


Depression Male 0.458 1 .499 Fall/Winter


Somatization Male 0.239 1 .625 Fall/Winter


Withdrawal Male 0.037 1 .847 Spring/Summer

Female 0.001 1 .975 Fall/Winter

Internalizing Male 0.231 1 .631 Spring/Summer

Composite Female 1.398 1 .237 Spring/Summer

43

the baseline of births from the entire cohort. The line for the combined-sex group of high-score

subjects heels close to the baseline, a reflection of the opposing trends for males and females.

High-score females on the Somatization scale continue the presentation of a noticeable

peak in births for the Spring period. Here, however, the elevation of births for females continues

above the expected rate into the Summer period and falls sharply in the Fall and Winter periods.

Males show their opposite, but more subdued, crest in the Fall and have their lowest percent of

births in the Spring period. The overall group of high-score subjects roughly adheres to the

baseline of births.

The Spring peak in births for high-score females is noticeable again on the Withdrawal

scale. The highest percent of male births is found in the Summer period and the lowest in

Spring, however the male pattern is rather more restricted than that of the females. Births for

both males and females show a similar rise and decline as the baseline for the Summer and Fall

periods, and the line for the overall group of high-score subjects largely follows that of the

expected across the year.

As with all previous scales, females show their peak in percent of births in the Spring

period on the Internalizing Problems composite. High-score male births are highest in the

Summer period, though the amplitude of the peak, just as before, is not as great as that for

females. The line for the overall group of high-score individuals rises above the baseline at a

modest level that is approximately the same for the Spring as Fall period.

44

Winter Spring Summer Fall

Season

20.00

22.00

24.00

26.00

28.00

30.00

32.00

34.00

Perc

ent o

f Birt

hs

BaselineMaleFemale

Male

Baseline

Female

Figure 1 Percentage of Children (Male and Female) Rated as High on Anxiety Born During Each Season

45


Season

15.00

20.00

25.00

30.00

35.00

Perc

ent o

f Birt

hs

BaselineMaleFemale

Baseline

Male

Female

Figure 2 Percentage of Children (Male and Female) Rated as High on Depression Born During Each Season

46

Fall Spring Summer Winter

Season

22.00

23.00

24.00

25.00

26.00

27.00

28.00

29.00

Perc

ent o

f Birt

hs

BaselineMaleFemale

Male

Baseline

Female

Figure 3 Percentage of Children (Male and Female) Rated as High on Somatization Born During Each Season

47


Season

20.00

22.50

25.00

27.50

30.00

32.50

35.00

Perc

ent o

f Birt

hs

BaselineMaleFemale

Male

Baseline

Female

Figure 4 Percentage of Children (Male and Female) Rated as High on Withdrawal Born During Each Season

48


Season

20.00

22.00

24.00

26.00

28.00

30.00

32.00

Perc

ent o

f Birt

hs

BaselineMaleFemale

Male

Baseline

Female

Figure 5

Percentage of Children (Male and Female) Rated as High on Internalizing Problems Born

During Each Season

49

CHAPTER 5

Discussion

Summary of results

The purpose of this study was to investigate the relationship between season of birth and

the presence of internalizing problems among children. Five BASC subscales were investigated:

Anxiety, Depression, Somatization, Withdrawal, and the Internalizing Scales Composite. Data

were provided by elementary school teachers using the BASC TRS-C or TRS-P form, thus

allowing for an investigation of the relationship between season of birth and internalizing

disorders within the context of school. A sample of 2,619 students was used in the current study.

Children with scores on these five scales that were at or above the 75th percentile were

designated as having a score above a level of concern. Chi-square tests of independence assessed

the level of relationship between period of birth and the internalizing scales scores. Further,

relationship effects were investigated by sex and age group to determine if there were any

patterns that were stronger for one sex than the other and if such patterns were equally present

among older and younger children.

When data were divided into half year birth periods, chi–square independence tests

revealed statistically significant effects for students scoring high on the Anxiety scale and

Internalizing Problems composite, supporting Hypothesis 2 and 5. The peak birth period for

these subjects was during the Spring/Summer period as expected. Analyses of the data

according to sex identified statistically significant effects among females on these same scales,

also with the crest of births falling in the Spring/Summer period. After splitting boys and girls

50

into older and younger groups, it was found that data for Spring/Summer born younger females

approached significance for Anxiety.

To illustrate the trends observed in the data, graphs were created to show the

relationships between season of birth and the percentages of births observed. Ten graphs were

developed, one for each internalizing variable tested and examining results by sex and age group.

The plots showed differences in observed birth levels for students with internalizing problems

above a level of concern for the overall group, males, and females. This series was repeated for

age groups. Expected birth information was plotted for comparison, and all information was

transferred into percentages to allow for comparison across groups.

Over the set of graphs, information showed distinct elevations during summer/spring for

females as well as for the total sample. Additionally, the increases of births with internalizing

problems over the spring season could be identified. For the set of graphs, the highest peak

information was seen in the spring, suggesting a relationship between season of birth and the

presence of elevated ratings of internalizing disorders.

Theoretical and practical implications

Many of the tests showed statistically significant results for girls; graphs clearly showed

differences between girls with elevated internalizing behavior scores from expected levels. The

recurring peak of internalizing problems across the BASC scales for females around the April to

July period is similar to that found by Sunderman (2000).

Internalizing problems are often considered to be more prevalent in girls (Macfarlane,

Allen, & Honzik, 1954). For example, higher numbers of girls suffer from anxiety disorders,

depression, and eating disorders (which are thought to be strongly related to anxiety) than do

boys (Achenbach, Howell, Quay, & Conners, 1991). The research suggests that not only do girls

51

show greater occurrence of internalizing problems, but also the results of the current study

suggest that these disorders are even more prevalent in girls born during the spring/early summer

months.

There may be other factors influencing the results of the present study. Teachers

provided ratings on each participant involved in this research. Based on the current literature that

internalizing problems are more prevalent with females, teachers may be looking for these

occurrences in girls more than boys. This expectation may result in higher ratings. Additionally,

the majority of teachers in the tested elementary schools are female. Perhaps female teachers are

more ‘in tune’ to these behaviors in girls and can more easily identify and recognize their

internalizing problems than those of boys.

While boys may feel the same emotions (worried, sad, fearful, nervous, etc.), their affect

may be expressed differently than by girls. For example, due to peer pressure at school, a boy

may not cry when depressed, but may act out or hit another child and the aggressive act is

recorded. Thus, the behavior, while stemming from negative mood, could be taken as an

aggression or social problem.

The trend of a spring/summer rise in births found this study are consistent with patterns

found in some previous research (Kirkpatrick, Castanedo, & Vazquez-Barquero, 2002;

Kirkpatrick, Tek, Alladyce, Morrison, & McCreadie, 2002; Penas, et al., 2003). The peak birth

periods identified in this study differ from those found by certain other researchers, however, in

that they crest approximately one month later than among other subjects (Bradbury & Miller,

1985; Castrogiovanni, et al., 1998; Gortmaker, et al., 1997).

It is not possible to identify the cause of the birth patterns found in this study. Even so,

because the trend of increased high internalizing births occurs during the spring and summer,

52

certain suspected risk factors attract attention. Those subjects born in the April to July period

were in their second trimester of gestation from approximately December to March. During this

vulnerable phase of CNS development, they would have been at greater risk of exposure to

wintertime upper respiratory infections, short photoperiod, and reduced UV radiation, all of

which have been suggested as teratogenic factors (Adams, Kendall, Hare, & Munk-Jorgensen,

1993; Gortmaker, et al., 1997; Martin & Kimlin, unpublished paper) on the fetus.

Without a clear etiology for increased internalizing problems, creating a preventive plan

is admittedly difficult. The birth trends identified by this study, however, recommend attention

to the array of risks that may contribute to a biological susceptibility to internalizing problems.

This study lends support to the body of literature addressing the importance of prenatal care and

education of mothers-to-be regarding their own health and exposure to suspected and known

teratogens.

It will be key to expand awareness of birth trends for internalizing behaviors. An

increased consciousness among parents, teachers, and caretakers that there are relationships

between birth season and the presence of internalizing problems could increase vigilance for

early signs of problem behaviors. Alerted parents, teachers, doctors, psychologists, and others

responsible for spring/summer born children may be more attentive to the emergence of

internalizing disorders at an early stage, when treatment is more likely to be successful.

Limitations

This study had several limitations. First, the data were provided solely by classroom

teachers. While this allows for a unique look at internalizing disorders in the classroom, teachers

are largely restricted to seeing students in this one environment. Further, internalizing symptoms

53

are often a private matter not easily observed by others. Future studies may be strengthened by

accumulating data from other sources (e.g., mothers, fathers, siblings, doctors) and using the data

to replicate as well as to triangulate the results.

As noted, this study investigated children in one context – school. While school is clearly

an important arena to assess behavior of children between the ages of 4 and 12, it is recognized

that this environment is different from the home environment or any other setting where

children’s behavior may be slightly, or even markedly, different. For example, children may be

shy at school due to situational or peer factors, while they may be more outgoing and expressive

in a more comfortable setting. Children may act differently in all of these different contexts, and

ratings concerning a child’s behavior may vary depending upon the context. Future studies

could be strengthened by analyzing ratings of children’s behavior in different environments to

achieve a well-rounded picture of behavior.

This study investigated the relationship between season of birth patterns and the presence

of internalizing disorders within the elementary school context. Patterns of behavior were found

to vary for children born in the spring and summer months. Females with a higher level of

internalizing behaviors were especially more likely to have been born in the spring/summer

period. The information presented here helps to understand the broad and complex nature of

child development by investigating the relationship of behavior to developmental factors that

occur before birth. Children, parents, doctors, teachers, psychologists, and others may be

assisted by the illumination of season of birth fluctuations that present serious health

implications. Further, the information is useful to mothers as they seek prenatal care to reduce

the risk of insult to CNS development.

54

References

ACT Early Project (n.d). Retrieved February 12, 2004 from http://www.coe.uga.edu/dev/actearly/act/index.html.

Achenbach, T. M., Howell, C. T., Quay, H. C., & Conners, C. K. (1991). National survey of

problems and competencies among four- to sixteen-year-olds. Monographs of the Society for Research in Child Development, 56 (3, Serial No. 255).

Adams, W., Kendell, R.E., Hare, E. H., & Munk-Jorgensen, P. (1993). Epidemiological

evidence that maternal influenza contributes to the etiology of schizophrenia – An analysis of Scottish, English, and Danish data. British Journal of Psychiatry, 163, 522-534.

Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology:

A clinical approach. Philadelphia: Taylor & Frosuire. Andreasen, N. C. (1997). Linking mind and brain in the study of mental illnesses: a project for

scientific psychopathology. Science, 275, 1586-1592 Aylward, G. P. (1997). Infant and early childhood neuropsychology. New York: Plenum. Baker, G. & Lester, D. (1986). Seasonal births, academic achievement and psychopathology

(suicide and homicide): A regional analysis. Psychological Reports, 59, 742. Barker, D. J. P., Osmond, C., Rodin, I, Fall, C. H. D., & Winter, P.D. (1995). Low weight gain in

infancy and suicide later in life. British Medical Journal, 311, 1203. Bartness, T. J., & Wade, G. N. (1985). Photoperiodic control of seasonal body weight cycles in

hamsters. Neuroscience and Biobehavioral Reviews, 9, 599-612. In Gortmaker, S. L., Kagan, J., Caspi, A., & Silva, P. (1997). Daylength during pregnancy and shyness in children: Results from northern and southern hemispheres. Developmental Psychobiology, 31:107-114.

Becker, L., Armstrong, D., Chan, F., & Wood, M. (1984). Dendritic development in human

occipital cortical neurons. Developmental Brain Research, 13, 117-124, in Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Boyd, J. H., Pulver, A. E., & Stewart, W. (1986). Season of birth: Schizophrenia and bipolar

disorder. Schizophrenia Bulletin, 12, 173-186.

http://www.coe.uga.edu/dev/actearly/act/index.html

55

Bradbury, T. N., & Miller, G. A. (1985). Season of birth and schizophrenia: A review of evidence, methodology, and etiology. Psychological Bulletin, 3, 569-594.

Brown, A. S., & Susser, E. S. (2003). Prenatal factors for schizophrenia. In D. Cicchetti, & E.

F. Walker (Eds.). Neurodevelopmental mechanisms in psychopathology (pp. 84-110). New York: Cambridge University Press.

Butcher, R. E. (1985). A historical perspective on behavioral teratology. Neurobehavior,

teratology, & toxicology, 7, 537-540. In Mays, L. C. & Ward, A. (2003). “Principles of Neurobehavioral Teratology” in Neurodevelopmental Mechanisms in Psychopathology. New York: Cambridge University Press.

Capone, G. (1996). Human brain development. In A Capute & P. Accardo (Eds.),

Developmental disabilities in infancy and childhood: Vol. 1. Neurodevelopmental diagnosis and treatment (2nd ed., pp. 25-75). Baltimore: Paul H. Brookes. In Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Castrogiovanni, P., Iapichino, S., Pacchierotti, C., Pierraccini, F. (1998). Season of birth in

psychiatry: A review. Neuropsychobiology, 37, 175-181. Castrogiovanni, P., Iapichino, S., Pacchierotti, C., Pierraccini, F. (1999). Season of birth in panic

disorder. Neuropsychobiology, 40, 177-182. Chotai, J., Åsberg, M. (1999). Variations in csf monoamine metabolites according to season of

birth. Neuropsychobiology, 39, 57-62. Chotai, J., Renberg, E. S., & Jacobsson, L. (1999). Season of birth associated with the age and

method of suicide. Archives of Suicide Research, 5, 245-254. Cicchetti, D., & Cannon, T. D. (1999). Neurodevelopmental processes in the ontogenesis and

epigenesis of psychopathology. Developmental and Psychopathology, 11, 375-393. Clarke, M., Keogh, F., Murphy, P.T., Morris, M., Larkin, C. Walsh, D., O’Callaghan, E. (1998).

Seasonality of births in affective disorder in and Irish population. European Psychiatry, 13: 353-358).

Dalén, P. (1975). Season of Birth: A study of schizophrenia and other mental disorders. New

York: North American Elsevier Publishing Company, Inc. Devinsky, O. & D’Esposito, M. (2004). Neurology of cognitive and behavioral disorders. New

York: Oxford University Press. Dombrowski, S. C. (2000). Association between maternal fever during pregnancy and infant,

preschool, and child temperament. Dissertation Abstractions International, 60(11-B), 5810.

56

Dombrowski, S., Martin, R. P., & Huttunen, M. O. (2003). Association between maternal fever

and psychological/behavior outcomes: A hypothesis. Birth Defects Research Part A: Clinical and Molecular Teratology, 67, 905-910.

Foster, D. L., Ebling, F. I. P., Claypool, L. E., & Wood, R. I. (1989). Photoperiodic timing of

puberty in sheep. In S. M. Reppert (Ed.), Research in perinatal medicine (IX): Development of circadian rhythmicity and photoperiodism in mammals. Ithaca, New York: Perinatology Press, in Gortmaker, S. L., Kagan, J., Caspi, A., & Silva, P. (1997). Daylength during pregnancy and shyness in children: Results from northern and southern hemispheres. Developmental Psychobiology, 31:107-114.

Frank, D. A., Roos, N., Meyers, A., Napoleone, M., Peterson, K., Cather, A., & Cupples, L. A.

(1996). Seasonal variation in weight-for-age in a pediatric emergency room. Public Health Reports, 111, 366-371.

Gainotti, G. (2000). Neuropsychological theories of emotion. In J. C. Borod (Ed.), The

neuropsychology of emotion (pp. 214-236). New York: Oxford University Press. Geschwind, N., & Galaburda, A. (1985). Cerebral lateralisation: Biological mechanisms,

associations and pathology: I. A hypothesis and a program for research. Archives of Neurology, 44, 194-198. In Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Gloor, P. (1992). Role of the amygdala in temporal lobe epilepsy. In Aggleton, J. P. (Ed.) The

amygdala: Neurobiological aspects of emotion, memory, and mental dysfunction. New York: Wiley-Liss.

Goldman-Rakic, P. S., Bourgeois, J., & Rakic, P. (1997). Synaptic substrate of cognitive

development: Life-span analysis of synaptogenesis in the prefrontal cortex of the non-human primate. In N. Krasnegor, G. Lyon, & P. S. Goldman-Rakic (Eds.), Development of the prefrontal cortex: Evolution, neurology, and behavior (pp. 9-26). Baltimore: Brookes. In Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Gortmaker, S. L., Kagan, J., Caspi, A., & Silva, P. (1997). Daylength during pregnancy and

shyness in children: Results from northern and southern hemispheres. Developmental Psychobiology, 31:107-114.

Hunter, A. G. (1984). Neural tube defects in eastern Ontario and western Quebec: Demographic

and family data. American Journal of Medical Genetics, 19, 45-63. Huntington, E. (1938). Season of birth. New York: Wiley. In Baker, G. & Lester, D. (1986).

Seasonal births, academic achievement, and psychopathology (suicide and homicide): a regional analysis. Psychological Reports, 59, 742.

57

Jernigan, T. L., & Tallal, P. (1990). Late childhood changes in brain morphology observable

with MRI. Developmental Medicine and Child Neurology, 3, 379-385. Joiner, T. E., Pfaft, J. J., Acres, J. G., & Johnson, F. (2002). Birth month and suicidal and

depressive symptoms in Australians born in the southern vs. the northern hemisphere. Psychiatry Research, 112, 89-92.

Kawl, A. & Pasamanick, B. (1958). The association of factors of pregnancy with the

development of reading disorders in childhood. Journal of the American Medical Association, 162, 105.

Kay, R. W. (2004). Schizophrenia and season of birth: relationship to geomagnetic storms.

Schizophrenia Research, 66, 7-20. Kaye, W. H., Weltzen, T. E., & Hsu, L. K. G. (1993). Relationship between anorexia nervosa

and obsessive compulsive behaviors. Psychiatric Annals, 23, 365-373. Kinney, D. K., Levy, D. L., Yurgelun-Todd, D. A., Holzman, P. S., Lajonchere, C. M. (1999).

Eye-tracking dysfunction and birth-month weather in schizophrenia. Journal of Abnormal Psychology

Kinney, H. C., Brody, B. A., Kloman, A. S., & Gilles, F. H. (1988). Sequence of central nervous

system myelination in human infancy: II. Patterns of myelination in autopsied infants. Journal of Neuropathology and Experimental Neurology, 47, 217-234, in Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Kirkpatrick, B., Castanedo, S. H., & Vazquez-Barquero, J. L. (2002). Summer birth and deficit

schizophrenia: Cantabria, Spain. Journal of Nervous and Mental Disease, 190, 526-532. Kirkpatrick, B., Tek, C., Allardyce, J., Morrison, G., McReadie, R. G. (2002). Summer birth and

deficit schizophrenia in Dumfries and Galloway, Southwestern Scotland. American Journal of Psychiatry, 159,1382-1387.

Kuzniecky, R. (1994). Magnetic resonance imaging in developmental disorders of the cerebral

cortex. Epilepsia, 35, S44-S56. Lam, D. A., Miron, J.A. (1994). Global patterns of seasonal variation in human fertility. In

Campbell, K. L., & Wood, J. W. (Vol. Eds.) Annals of the New York Academy of Sciences: Volume 709, Human reproductive ecology: Interactions of environment, fertility, and behavior (pp. 9-27). New York: New York Academy of Sciences.

Levine, R. J. (1994). Male factors contributing to the seasonality of human reproduction. In

Campbell, K. L., & Wood, J. W. (Vol. Eds.) Annals of the New York Academy of

58

Sciences: Volume 709, Human reproductive ecology: Interactions of environment, fertility, and behavior (pp. 29-45). New York: New York Academy of Sciences.

Lilienfeld, A. & Pasamanick, B. (1955). The association of maternal and fetal factors in the

development of cerbral palsy and epilepsy. American Journal of Obstetrics and Gynecology, 70, 557-569.

Livingston, R. Adam, B. S., Bracha, H. S., (1993). Season of birth and neurodevelopmental

disorders: Summer birth is associated with dyslexia. Journal of American Academy of Child and Adolescent Psychiatry, 32, 612-616.

Lynberg, M. C., Khoury, M. J., Lu, X., & Cocian, T. (1994) Maternal flu, fever, and the risk of

neural tube defects: A population-based case-control study. American Journal of Epidemiology, 140, 244-255.

Macfarlane, J. W., Allen, L., & Honzik, M. P. (1954). A developmental study of the behavior

problems of normal children between twenty-one months and fourteen years. Berkeley, CA: University of California Press.

McGrath, J. J., Welham, J. L. (1999). Season of birth and schizophrenia: A systematic review

and meta-analysis of data from the southern hemisphere. Schizophrenia Research, 25, 237-242.

Machon, R. A., Mednick, S. A., & Huttunen, M. O. (1997). Adult major affective disorder after

prenatal exposure to an influenza epidemic. Archives of General Psychiatry, 54, 322-328.

Martin, R. P. & Kimlin, M. G. (2002). Season of birth and mental retardation: Is there a vitamin

D connection? (unpublished manuscript). Mays, L. C. & Ward, A. (2003). “Principles of Neurobehavioral Teratology” in D. Cicchetti &

E. F. Walker (Eds.) Neurodevelopmental Mechanisms in Psychopathology. New York: Cambridge University Press.

de Messias, E. L. M., Cordeiro, N. F., Sampaio, J. J. C., Bartko, J. J., & Kilpatrick, B. (2001).

Schizophrenia and season of birth in a tropical region: relationship to rainfall. Schizophrenia Research, 48, 227-234.

Milunsky, A., Ulcickas, M., Rothman, K. J., Willet, W., Jick, S., & Jick, H. (1992). Maternal

heat exposure and neural tube defects. Journal of the American Medical Association, 268, 882-885.

Molliver, M. E., Kostovic, I., & Van der Loos, H. (1973). The development of synapses in

cerebral cortex in the human fetus. Brain Research, 50, 403-407, in Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

59

Nasrallah, H. A. (1991). Neurodevelopmental aspects of bipolar affective disorder. Biological

Psychiatry, 29, 1-2. In Machon, R. A., Mednick, S. A., & Huttunen, M. O. (1997). Adult major affective disorder after prenatal exposure to an influenza epidemic. Archives of General Psychiatry, 54, 322-328.

Olsen, S. C., Bogerts, B., Coffman, J. A., Schwarzkopf, S. B.,& Nasrallah, H. A. (1990). Medial-

temporal and ventricular abnormalities by MRI: Comparing major psychoses. Biological Psychology, 27, 59A-60A. In Machon, R. A., Mednick, S. A., & Huttunen, M. O. (1997). Adult major affective disorder after prenatal exposure to an influenza epidemic. Archives of General Psychiatry, 54, 322-328.

Papalia, D., & Olds, S. (1992). Human development. New York: McGraw-Hill, in Anderson,

V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Parker, G., Mahendran, R., Koh, E. S, Machin, D. (2000). Season of birth in schizophrenia: No

latitude at the equator. British Journal of Psychiatry, 176, 68-71. Pasamanick, B., & Knobloch, H. (1958). Seasonal variation in complications of pregnancy.

Obstetrics and Gynecology, 12, 110-112. Pasamanick, B., & Knobloch, H. (1965). Retrospective studies on the epidemiology of

reproductive casualty: Old and new. Merrill-Palmer Quarterly, 11, 7-43. Penas-Lledo, E. M., Santos, L. R., Leal, F. J. V., & Waller, G. (2003). Pattern of birth in

restrictive and bulemic eating disorders. Eating Behaviors, 3, 325-328. Pennington, B. F. (2002). The development of psychopathology: Nature and nurture. New

York: The Guilford Press. Pulver, A. E., Liang, K. Y., Hendricks-Brown, C., Wolyniec, P., McGrath, J., Adler, L., Tam, D.,

Carpenter, W. T., Childs, B. (1992). Risk factors schizophrenia, season of birth, gender, and familial risk. British Journal of Psychiatry, 160, 65-71.

Rayport, S. G. (1992). Cellular and molecular biology of the neuron. In S. C. Yudofsky & R. E.

Hales (Eds.), American Psychiatric Press textbook of neuropsychiatry (2nd ed.) (pp. 3-28). Washington D.C.: American Psychiatric Association.

Reynolds, C. R., Kamphaus, R. W. (1998). Behavior assessment system for children manual.

Circle Pines Minnesota: American Guidance System. Rogers, M. E., Lilienfeld, A. M., Pasamanick, B. (1955). Prenatal and prenatal factors in the

development of childhood behavior disorders. Neurology, 102, 157.

60

Salib, E. (2002). Month of birth and suicide: An exploratory study. International Journal of Psychiatry in Clinical Practice, 6, 39-44.

Sunderman, D. A. O. (2000). Relation of month of birth to behavior problems in early

childhood. Unpublished doctoral dissertation. University of Georgia, Athens. de Sauvage Nolting, W. J. J. (1954). The relation between schizophrenic and related disorders

and the month of birth. Nederlands Tijdschrift Geneeskunde, 79, 528. Suvisaari, J. M., Haukka, J. K., & Lönnqvist, J. K. (2004). No association between season of

birth of patients with schizophrenia and risk of schizophrenia among their siblings. Schizophrenia Research, 66, 1-6.

Suvisaari, J. M., Haukka, J. K., Tanskanen, A. J., & Lönnqvist, J. K. (1999). Decline in the

incidence of schizophrenia in Finnish cohorts born from 1954 to 1965. Archives of General Psychiatry, 56, 733-740.

Suvisaari, J. M., Haukka, J. K., Tanskanen, A. J., Hovi, T., & Lönnqvist J. K. (1999).

Association between prenatal exposure to poliovirus infection and adult schizophrenia. American Journal of Psychiatry, 156, 1100-1102.

Takei, N., & O’Callaghan, E. (1995). Reply to the comments on Takei et al.: Prenatal exposure

to influenza and the risk of mental retardation. European Archives of Psychiatry and Clinical Neuroscience, 245, 260-266.

Tester, S. J. (1987). A history of western astrology. Wolfeboro, NH: Boydell Press. Toner, B. B., Garfinkel, P. E., & Garner, D. M. (1988). Affective and anxiety disorders in the

long-term follow-up of anorexia nervosa. International Journal of Psychiatry in Medicine, 18, 357-364.

Torrey, E. F., Miller, J., Rawlings, R., Yolken, R. H. (1997). Seasonality of births in

schizophrenia and bipolar disorder: A review of the literature. Schizophrenia Research, 28, 1-38.

Torrey, E. F., Rawlings, R., & Waldman, I. N. (1988). Schizophrenic births and viral diseases in

two states. Schizophrenia Research, 1, 73-77. Torrey, E. F., Torrey, B. B., Peterson, M. R. (1977). Seasonality of schizophrenic births in the

United States. Archives of General Psychiatry, 34, 1065-1070. Van der Knapp, M., Valk, J., Bakker, C., Schoonfeld, M., Faberm, J., et al. (1991). Myelination

as an expression of the functional maturity of the brain. Developmental Medicine and Child Neurology, 33, 849-857. In Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

61

Watson, C. G., Kucula, T., Tilleskjor, C., & Jacobs, L. (1984). Schizophrenic birth seasonality

in relation to the incidence of infectious diseases and temperature extremes. Archives of General Psychiatry, 41, 85-90.

Weinberger, D. (1987). Implications of normal brain development for the pathogenesis of

schizophrenia. Archives of General Psychiatry, 44, 660-669. In Anderson, V., Northam, E. Hendy, J., & Wrennall, J. (2001). Developmental Neuropsychology: A clinical approach. Philadelphia: Taylor & Frosuire.

Wilson, G. T., Heffernan, K., Black, C. M. D. (1996). Eating disorders, In E. J. Mash & R. A.

Barkley (Eds.) Child Psychopathology. New York: The Guilford Press. Waterland, R. A. & Jirtle, R. L. (2003). Transposable elements: Targets for early nutritional

effects on epigenetic gene regulation. Molecular and Cellular Biology, 23, 5293-5300

62

Appendix

In addition to examining the data for birth patterns for all students and for each sex,

supplementary analyses were conducted with the cohort divided by age. The younger half of the

participants was comprised of children between the ages of 5 and 7 years, inclusive. The older

children ranged from ages 8 to 12 years. The chi-square tests for independence applied to the

previous data groups were performed just as before.

Table 13 provides descriptive information for the older and younger subject groups in

comparison to that of the overall cohort. Both groups appear similar in the distribution of their

scores. The greatest difference between the two is found in the older group having a mean four

points lower than that of the younger group on the Anxiety scale.

Analysis of the data by age began with chi-square tests of independence for the

participants according to which half of the year they were born. Those with birthdates in April

through September were placed in the Spring/Summer group, and those born from October

through March were set into the Fall/Winter group. Separate chi-square tests of independence

were performed for the older and younger child groups. The results of these analyses are

provided in Table 14.

The results of the chi-square tests of independence showed a significant relationship between

season of birth and scores at or above the 75th percentile on the Anxiety scale for both older and

younger children, just as had been found for the overall group of subjects. The peak surplus of

births was found in the Summer/Spring period on all scales, except for older children on the

Depression scale, who showed a peak in the Fall/Winter period. This is similar to the to the

pattern found in the analysis of the data by sex, wherein all peaks were found in the

63

Table 13 Descriptive Statistics for BASC Internalizing Scales by Age Group

Variable Mean Std. Dev. Min. Max.

Anxiety Total Sample 47.49 9.70 37 107

Younger 49.92 10.38 37 107

Older 45.68 8.74 39 105

Depression Total Sample 48.88 10.05 37 113

Younger 49.30 10.53 37 100

Older 48.57 9.68 41 113

Somatization Total Sample 48.19 10.01 40 98

Younger 49.15 10.77 40 90

Older 47.48 9.349 42 98

Withdrawal Total Sample 48.29 10.28 35 106

Younger 48.59 10.63 35 100

Older 48.06 10.02 39 106

Internalizing Total Sample 47.76 9.75 35 108

Composite Younger 49.22 10.71 35 108

Older 46.67 8.82 39 98

64

Table 14

Chi-Square Tests of Independence, Age Group by Half-Year Split (Spring/Summer, Fall/Winter)

Split χ2 Df P Peak

Anxiety All 5.539 1 .019* Spring/Summer

Younger 4.671 1 .031* Spring/Summer

Older 4.480 1 .034* Spring/Summer

Depression All .314 1 .575 Spring/Summer

Younger .820 1 .365 Spring/Summer

Older .006 1 .936 Fall/Winter

Somatization All .745 1 .388 Spring/Summer

Younger 1.075 1 .300 Spring/Summer

Older .184 1 .668 Spring/Summer

Withdrawal All 1.457 1 .227 Spring/Summer



Internalizing

Composite

All 4.127 1 .042* Spring/Summer



Note: * = p < .05, statistical significance

65

Table 15

Chi-Square Tests of Independence, Age Group by Season

Split χ2 Df P Peak

Anxiety All 9.162 3 .027* Spring

Younger 7.518 3 .057 Summer

Older 8.556 3 .036* Spring

Depression All 1.038 3 .792 Spring


Older 1.121 3 .772 Spring

Somatization All .907 3 .824 Spring


Older .969 3 .809 Spring

Withdrawal All 2.290 3 .514 Spring


Older 2.800 3 .424 Winter

Internalizing

Composite

All 4.229 3 .239 Summer


Older 1.899 3 .594 Spring

Note: * = p < .05, statistical significance

66

Table 16

Chi-Square Tests of Independence, Age Group by Month

Split χ2 Df P Peak

Anxiety All 10.934 11 .449 April

Younger 13.180 11 .282 July

Older 11.998 11 .364 June

Depression All 12.188 11 .350 July

Younger 9.458 11 .580 July

Older 14.090 11 .228 June

Somatization All 12.147 11 .353 June

Younger 8.073 11 .707 August

Older 8.594 11 .659 June

Withdrawal All 8.274 11 .689 June

Younger 9.830 11 .546 September

Older 11.997 11 .364 February

Internalizing

Composite

All 11.071 11 .437 July

Younger 12.856 11 .303 October

Older 11.749 11 .383 June

67

Spring/Summer period, except for males on the Depression scale, who likewise peaked in the

Fall/Winter period.

Next, individuals were separated into four groups for analysis according to the season in

which they were born. Chi-square tests of independence were conducted using 4 x 2

contingency tables for the older and younger groups of children. The results of these tests are

presented in Table 15.

Analysis of the Anxiety scale yielded statistically significant results for the older

children. For all scales, younger children had birth surpluses in the Summer period. Older

children had peak surpluses in the Spring period on all but the Withdrawal scale, for which there

was a Winter peak in birth numbers.

Members of the younger and older groups were next assembled by month of birth for

analysis on 12 x 2 contingency tables. The results of these chi-square tests of independence are

presented in Table 16.

No indications of statistical significance were found among the results of the series of

chi-square tests of independence for month of birth by age group. The large majority of peak

birth surpluses fell in the spring and summer months. Only the older children on the Withdrawal

scale and the younger children on the Internalizing Composite were exceptions, with their

respective February and October peaks.

The birth patterns of younger and older children varies little from that of the overall high-

score group combined on the Anxiety scale. Whether divided by age or taken together, the peak

percent of births occurs in the Spring period. It is particularly noticable in Figure 6 that Spring is

the only season for which births exceed the line of expectation, a suggestion of the peak’s

significance.

68

Figure 7 for the Depression scale shows the younger group and overall high-score group

to share a peak in percent of births in the Summer period. Older children, however, are seen to

have the greatest percent of births in the Fall, the season in which the percent of births in the

younger group is at its nadir. The percent of births of the younger, older, and overall high-score

group are near the level of expectation in the Spring period.

Figure 8 for Somatization reveals opposite birth patterns for the younger and older high-

score subjects. Younger children have their peak in percent of births in the Spring period and a

secondary level above the baseline in the Winter. The highest percent of older children are born

in the Fall and have a lower point above the line of expectation in the Summer period. Together

these groups’ birth patterns yield a line that approximates that of the baseline.

On the Withdrawal scale, the birth pattens of the younger and older children are similar to

that of these two groups combined as well as that of the total research population, as seen in

Figure 9. The younger group shows marginally greater deviation from the line of expectation

with a modest rise above the baseline in Summer, followed by a sharper decline below expected

births in the Fall period. Even so, all these patterns are generally unremarkable.

On Figure 10, younger children showed a peak in percent of births for the Spring period

on the Internalizing Composite. A Summer excess of births generally equal in amplitude is

noted for the older group of children.

69


Season

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Figure 6 Percentage of Children (Younger and Older) Rated as High on Anxiety Born During Each Season

70


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Figure 7 Percentage of Children (Younger and Older) Rated as High on Depression Born During Each Season

71


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Figure 8 Percentage of Children (Younger and Older) Rated as High on Somatization Born During Each Season

72


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Figure 9 Percentage of Children (Younger and Older) Rated as High on Withdrawal Born During Each Season

73


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Figure 10 Percentage of Children (Younger and Older) Rated as High on Internalizing Problems Born During Each Season

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