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Abstract

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. What this paper adds
  7. References

Aim  The aim of this study was to evaluate the impact of pre- and perinatal factors on the risk of developing attention-deficit–hyperactivity disorder (ADHD).

Method  We investigated the medical history of 237 children (206 male; 31 female) from Malmö, Sweden born between 1986 and 1996 and in whom a diagnosis of ADHD (Diagnostic and Statistical Manual of Mental Disorders-IIIR or IV) was subsequently made at the Department of Child and Adolescent Psychiatry, Lund University, and a reference group of 31 775 typically developing children from Malmö using data from the Swedish Medical Birth Register.

Results  The results of multiple logistic regression analysis revealed that ADHD was significantly associated with a young maternal age (odds ratio [OR] for 5y increase 0.87; 95% confidence interval [CI] 0.76–0.99), maternal smoking (OR 1.35; 95% CI 1.14–1.60), maternal birthplace in Sweden (OR 2.04; 95% CI 1.45–2.94), and preterm birth <32 weeks (OR 3.05; 95% CI 1.39–6.71), and a male predominance (OR 6.38; 95% CI 4.37–9.32). Apgar scores at 5 minutes below 7 were significantly associated with ADHD in the univariable analysis (OR 2.60; 95% CI 1.15–5.90). The population-attributable fraction of ADHD caused by the perinatal factors studied was estimated to be 2.8%.

Interpretation  The results indicate that the studied factors constitute weak risk factors for developing ADHD.

Abbreviation
MBR

 Medical Birth Register

Attention-deficit–hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects about 4 to 7% of school-age children.1 Although genetic factors are considered to be most important in the aetiology of ADHD, shared and non-shared environmental factors have been estimated to account for between 10% and 25% of the statistical variance in twin ADHD scores.2 For example, many studies have shown that maternal smoking during pregnancy has a significant association with ADHD.3 A case–control study by Mick et al.4 using perinatal data obtained from parent interviews found that low birthweight was associated with a diagnosis of ADHD. Case–control studies by Botting et al.5 using data collected at birth supported this finding. However, in their case–control study with perinatal data collected at birth, O’Callaghan et al.6 could not find any association between low birthweight and ADHD. Similarly, Milberger et al.7 used perinatal data from parent interviews in their case–control study and failed to show an association between low birthweight and ADHD. Whitaker et al.8 performed a follow-up study of children aged 6 years who had a low birthweight and who had undergone cranial ultrasound. Neither low birthweight nor low gestational age increased the risk of ADHD independent of ultrasound findings.

Other possible risk factors for ADHD that have emerged from different studies are toxaemia, eclampsia, poor maternal health, maternal age, duration of labour, fetal stress, and antepartum haemorrhage.9 In a case–control study in 1990 utilizing retrospective data, Barkley et al.10 failed to find an association between ADHD and any pregnancy or birth complications, including low birthweight.

The findings in different studies have been contradictory, and study methodologies vary in controlling for confounding variables, sample sizes, and data gathering.7 Few studies have been made on population-based samples using data gathered at the time of delivery. A study involving all clinical participants in a geographic area and a population-based reference group without a diagnosis may provide information that makes it possible to estimate the relative strength of both different risk and protective factors.

In our study, we examined the Swedish Medical Birth Register (MBR), which contains obstetric data on most children born in Sweden. Obstetric data are recorded in the Swedish MBR by physicians and nurses at the time of delivery.

The aims of this study were to identify relevant pre- and perinatal risk and protective factors for ADHD and to estimate the extent to which pre- and perinatal factors affect the risk of developing ADHD.

Method

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. What this paper adds
  7. References

Participants

From the register of diagnosis at the Department of Child and Adolescent Psychiatry in the city of Malmö we could identify 419 children born in the period 1978 to 2001 who were subsequently clinically diagnosed as having ADHD according to the Diagnostic and Statistical Manual of Mental Disorders (DSM). Almost every child with a formal diagnosis of ADHD was assessed at the Department of Child and Adolescent Psychiatry by 10 experienced clinicians using DSM criteria (DSM-III-R11 before 1994 and DSM-IV12 from 1994 onwards). Age at the time of diagnosis varied between 5 and 17 years, with most children being diagnosed between the ages of 8 and 12 years. Very few children were diagnosed with ADHD in Malmö in the period 1978 to 1986, as ADHD was not fully recognized by the Swedish child psychiatry service during this period. Furthermore, assessment procedures were not very reliable before the 1990s. As we found so few diagnoses of ADHD among children born before 1986, and as we were uncertain if we could rely on these early diagnoses, children born before 1986 were excluded. As the diagnosis of ADHD is seldom made in children of preschool age, we identified few children with a diagnosis born after 1996 (the study was initiated in 2005). Thus, children born after 1996 were also excluded. Using the personal identification number of each individual, the reference group was linked to the Swedish MBR in order to obtain demographic and obstetric information. Individuals for whom no linkage was possible (e.g. children who were born abroad) or children who were born in Sweden but outside Malmö were not included in the final analysis. The reference group was identified from the Swedish MBR and consisted of all individuals whose mothers were living in Malmö during the study period and who were not included in the case group. The result of the case and reference group selection procedure is shown in Figure 1.

image

Figure 1.  Flow chart of the case and reference group selection procedure. ADHD, attention-deficit–hyperactivity disorder.

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The MBR contains medical information on nearly all deliveries in Sweden (coverage about 99%).13 Standardized record forms are used at all antenatal clinics, delivery units, and paediatric examinations of newborn infants. Copies of these forms are sent to the National Board of Health, where they are computerized. Nearly all pregnant women receive free antenatal care. The MBR is annually linked with Statistics Sweden to obtain information on, among other things, the infant’s identification numbers, date of death, and parental citizenship.

Intrauterine growth was evaluated in accordance with the national fetal weight-based growth standard14 and expressed in SD scores according to gestational age. Infants with a birthweight of more than 2SD below the expected weight for gestational age were classified as small, whereas infants weighing more than 2SD above the expected weight were considered large.

Maternal parity was defined as the number of previously born children at birth of the study child.

This study was approved in 2005 by the Regional Ethical Review Board in Lund (register number Ö49–2005).

Statistical analysis

Odds ratios (ORs) and 95% confidence intervals (CIs) for ADHD were calculated using multiple logistic regression analyses (Gauss; Aptech Systems Inc., Maple Valley, WA, USA; http://www.aptech.com). All possible risk factors for ADHD that were investigated are listed in Table I.

Table I.   Maternal and infant characteristics and perinatal risk factors by study group
 ADHD group (n=237), n (%)Reference group (n=31 775), n (%)
  1. ADHD, attention-deficit–hyperactivity disorder.

Year of birth
 1986–198723 (10)5239 (16)
 1988–199084 (35)8920 (28)
 1991–199388 (37)9022 (28)
 1994–199642 (18)8594 (27)
Maternal age (y)
 Mean (SD)27.4 (5.2)28.1 (5.1)
  <209 (4)1052 (3)
  20–2470 (30)7088 (22)
  25–2984 (35)11 685 (37)
  30–3447 (20)8183 (26)
  35–3920 (8)3209 (10)
  40+7 (3)558 (2)
Maternal smoking status
 Not known8 (3)1026 (3)
 Non-smoking143 (62)22 532 (73)
 <10 cigarettes/day41 (18)4834 (16)
 ≥10 cigarettes/day45 (20)3383 (11)
Mother born outside Sweden38 (16)9169 (29)
Number among siblings
 Not known4 (2)585 (2)
 Only child36 (15)4270 (13)
 First child, younger sibling(s)83 (35)11 006 (35)
 Middle child42 (18)5497 (17)
 Last-born child, older sibling(s)72 (30)10 417 (33)
Twins6 (2)835 (3)
Males206 (87)16 210 (51)
Gestational age (wks)
 Not known0 (0)22 (0)
 <327 (3)262 (1)
 32–369 (4)1660 (5)
 37–41203 (86)27 541 (87)
 42+18 (8)2290 (7)
Pre-eclampsia10 (4)878 (3)
Delivery mode
 Vaginal, no instrument200 (84)27 512 (87)
 Elective Caesarean section10 (4)850 (3)
 Emergency Caesarean section12 (5)2124 (7)
 Vacuum extraction/forceps15 (6)1289 (4)
Apgar score at 5min
 01 (0)138 (0)
 1–66 (2)315 (1)
 7+230 (97)31 322 (99)
Birthweight
 <2500g15 (6)1576 (5)
 2500–4000g192 (81)25 356 (80)
 >4000g30 (13)4843 (15)
SD scores (birthweight)
 <−2 (small for gestational age)14 (6)1612 (5)
 −2 to –1.147 (20)5664 (18)
 −1 to 1150 (63)20 007 (63)
 1.1 to 221 (9)3407 (11)
 >2SD (large for gestational age)5 (2)1085 (3)

In order to determine the final multiple logistic regression model, the following steps were taken: first, the best logistic model for each investigated variable (linear, quadratic, or divided into designed class variables) was determined by investigating the level of significance and goodness of fit according to the Hosmer–Lemeshow test. Second, variables with p values below 0.20 in the final univariate models were initially included in the multivariable model and excluded if the p values exceeded 0.20 in the multivariable analysis.

In the multivariable model, year of birth was controlled for using class variables divided into 2- or 3-year periods (1986–1987, 1988–1990, 1991–1993 [reference], and 1994–1996). Maternal age was best expressed as a linear continuous variable. Maternal smoking was entered as a semicontinuous variable with 1=no smoking, 2=smoking less than 10 cigarettes per day, and 3=smoking 10 cigarettes per day or more. If the smoking information was not available (in 3.2% of all records – see Table I), it was replaced by the mean (1.38 on the semicontinuous scale) in the multivariable analysis. Birthweight was entered into the analyses as SD scores (birthweight for gestational age) and was best expressed as a linear continuous variable (see Results). If information on birthweight SD scores was unavailable (0.1%, reference group only), the SD score was replaced by the mean (0). The other evaluated possible risk factors were entered as simple class variables in the multiple or univariate models. For each model, the number of investigated factors never exceeded one-tenth of the number of individuals with ADHD.

Two designed dichotomous variables were created to evaluate the overall influence of the perinatal factors on the genesis of ADHD. The first ‘overall perinatal factor’ was regarded as present if the child was born before 37 weeks of pregnancy, weighed <2500g at birth, had an Apgar score at 5 minutes below 7, and was either small or large for gestational age. Otherwise, the ‘overall perinatal factor’ was regarded as absent. Similarly, the second ‘specific perinatal factor’ was regarded as being present if the child was born before 32 weeks of pregnancy or had an Apgar score at 5 minutes below 7, and was otherwise regarded as being absent.

Results

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. What this paper adds
  7. References

The basic demographic characteristics of the children with ADHD and reference children are shown in Table I. As evident from the table, fewer children in the group with ADHD than in the reference group were born either early or late within the study period. This fact makes it necessary to consider year of birth when designing the final analysis. The mothers of children with ADHD were significantly younger and were more often smokers than the mothers of children in the reference group. A significant negative association was found between ADHD and maternal age (entered as a linear continuous variable), and a significant positive association was found between ADHD and maternal smoking (entered as a semicontinuous variable; see Method). These estimates did not change more than marginally in the multivariable analysis (Table II). Other factors that were found to be significant independent risk factors for ADHD were gestational age below 32 weeks, Apgar score at 5 minutes below 7, and male sex (Table II). Furthermore, a negative association between ADHD and maternal birth outside Sweden was found. No associations were found between ADHD and twinning, moderate preterm birth (between 32 and 36 gestational weeks), and the index child’s number among siblings.

Table II.   Risk or protective factors for having a diagnosis of attention-deficit–hyperactivity disorder. Only risk factors with p values below 0.20 are shown. Estimate and 95% confidence intervals (CIs) obtained by simple and multiple logistic regression analysis respectively, are shown
 Univariate estimateMultiple modela
OR95% CIOR95% CI
  1. aModel including all the specified factors in the column. bEntered as a semicontinuous variable (1=non-smoking, 2=smoking 1–9 cigarettes/day, 3=smoking >10 cigarettes/day). OR, odds ratio.

Maternal age (5y increase)0.860.76–0.980.870.76–0.99
Mother born outside Sweden0.470.33–0.670.490.34–0.69
Maternal smokingb1.431.22–1.691.351.14–1.60
Year of birth
 1986–19870.450.28–0.710.410.26–0.65
 1988–19900.970.71–1.300.910.67–1.22
 1991–1993Reference Reference 
 1994–19960.500.35–0.720.550.38–0.79
<32 weeks of gestation3.341.56–7.173.051.39–6.71
Apgar score at 5min, 1–62.601.15–5.902.170.93–5.06
Male sex6.384.37–9.316.384.37–9.32

In the univariate analysis there was a slight indication of an association between elective caesarean sections or vacuum extraction/forceps delivery and ADHD (p=0.14 and p=0.08 respectively). In the preliminary multivariable analysis (including all variables with p<0.20 in the univariate analysis), there was no sign of any association between delivery mode and ADHD (p=0.23 for elective caesarean section and p=0.24 for vacuum extraction/forceps). Thus, the variables on delivery mode were never added to the final multiple model. A possible association between pre-eclampsia and ADHD was indicated in the univariate analysis (p=0.16). However, in all models, including information on Apgar score and gestational length, no suggestion of any independent association between pre-eclampsia and ADHD was found. Even though second-grade models were tested, it was revealed that in the current data set, the birthweight SD scores variable was best entered to the models as a linear continuous variable. In the univariate analysis, there was an indication of a negative association between increasing SD scores and ADHD (p=0.13). However, when SD scores were included in a multiple model (in which maternal smoking and maternal age were included), the p value increased to 0.5. Thus, SD scores never entered the final multiple model.

In order to evaluate the overall impact of obstetric risk factors on the aetiology of ADHD, birth before 37 weeks of pregnancy, Apgar score at 5 minutes below 7, small for gestational age, and large for gestational age were combined into a designed dichotomous variable. The OR, adjusted for sex, year of birth, maternal age, and maternal smoking, was 1.01 (0.70–1.45; p=0.97). If, instead, the two variables that were found to be independent risk factors for ADHD in the current study (Apgar score below 7 and very preterm birth before 32wks) were combined, the adjusted OR (with 95% CI) was 2.68 (95% CI 1.45–4.97). However, only 11 out of the 237 children (4.6%) with ADHD had any of these risk factors. With the overall risk of 0.7% for ADHD in the current study, the OR of 2.68 corresponds to a number needed to harm of 84, and the population-attributable fraction caused by perinatal factors was estimated to be 2.8%.

Discussion

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. What this paper adds
  7. References

The following factors were found to have significant associations with a diagnosis of ADHD: young maternal age, maternal smoking during pregnancy, maternal birthplace in Sweden, child born before week 32 of pregnancy, male sex (as expected), and Apgar score below 7 at 5 minutes after delivery.

A population-based study in Malmö found a frequency of ADHD among children aged between 5 years 6 months and 10 years of about 4%.15 In the present study, the frequency of ADHD was about 0.7%. As the problem has been that of underdiagnosing, and as assessment methods have been good, it may be that the children who have been diagnosed have been accurately assessed but that they represent only one-fifth of all the children with ADHD. Children with ADHD not identified should constitute no more than 4 to 5% of the children in the reference group. We had a sex bias, typical of clinical samples, with six times more males than females. In Sweden, the diagnosis of deficits in attention, motor control, and perception has been used; this diagnosis can be translated in DSM terms as indicating children who have both ADHD and developmental coordination disorder.16 About half of the children with ADHD in our study were also diagnosed as having deficits in attention, motor control, and perception.

Both young and old mothers are considered to belong to an obstetric risk group according to clinical experience and research.17 We found a significant statistical association between a clinical childhood diagnosis of ADHD and young age of the mother. We could also detect a trend towards increased risk among the oldest mothers, although this association was not statistically significant.

Several previous studies have identified smoking in pregnancy as a risk factor for the development of ADHD.3 In studies of twins in which adjustments for genetic risk have been made, maternal smoking during pregnancy has been found to have a true environmental effect on ADHD symptoms, but a recent study by Thapar et al.18 involving children born using assisted reproductive technologies found no significant association between ADHD and smoking if the mother and child were genetically unrelated. Our study shows that maternal smoking during pregnancy is a significant risk factor. To determine if this factor represents a true environmental effect or if it is a consequence of the genetic risk factor, further research is needed – either more studies like that of Thapar et al.18 utilizing children born with the aid of assisted reproductive technologies or studies in which comparisons can be made between children with different degrees of heredity for ADHD.

According to Bhutta et al.,19 children of low birthweight have a threefold increased risk of developing ADHD, and Mick et al.4 have proposed that 13.8% of all cases of ADHD can be attributed to low birthweight. We did not find any significant association between birthweight and ADHD, but this may be because the statistical power of the study was too low. The strength of the association between birthweight and ADHD increased when smoking during pregnancy was introduced in the regression model, which is interesting as smoking during pregnancy has a known association with low birthweight.

Preterm birth has been described as a risk factor for the development of ADHD,7 and we found that the prevalence of ADHD was higher among children born before week 32 of gestational age than among term-born children. In other studies, pre-eclampsia has been shown to be a risk factor for ADHD.20 In our sample there was a non-significant tendency for an association between maternal pre-eclampsia and ADHD.

We found that having a mother born in another country was a relative protective factor (OR<1; thus, statistically, a protective factor from developing ADHD). In another study from Malmö concerning perinatal risk and protective factors for developing autism spectrum disorders,21 having a mother born in another country was found to be a risk factor for developing autistic syndrome but a protective factor for developing Asperger syndrome. A possible explanation for the finding that having a mother born in another country is a relative protective factor for Asperger syndrome and ADHD could be that immigrant families are less inclined to seek help from child psychiatry, and as these conditions are milder than autistic syndrome, it may be the case that affected individuals are less likely come into contact with child psychiatry and to be diagnosed. This hypothesis is supported by statistics from the Department of Child and Adolescent Psychiatry in Malmö, which show that the proportion of families seeking help from child psychiatry is lower in the areas of Malmö with a high proportion of immigrants than in those areas with very few immigrant families. This might be explained by cultural factors and difficulties with integration, causing some immigrant families to have less confidence in Swedish child psychiatry services. However, some professionals also believe that ADHD-like behaviour may be explained by social and cultural adjustment problems.

In our study, the population-attributable fraction caused by the perinatal factors studied was estimated to be 2.8%, which is less than estimates made by several other researchers.2

The incidence of birth complications in Europe and the United States is now very low since the dramatic improvements in obstetric care that occurred at the end of the twentieth century; however, it remains high in many developing countries.22 Earlier work, such as the studies by Knobloch and Pasamanick,23 were conducted at a time when concepts such as minimal brain damage still were in use and the incidence of birth complications such as neonatal asphyxia was high. Neonatal encephalopathy following perinatal asphyxia can affect the striatum, which hypothetically might lead to symptoms of ADHD.24 Marlow et al.25 found that moderate but not mild neonatal encephalopathy leads to a significantly increased frequency of hyperactivity in children of school age. In many developing countries the rates of child mortality are still very high, and intrapartum hypoxia and birth asphyxia are widely regarded as major causes of morbidity and mortality in these countries.26 In Europe and the United States, the survival of extremely preterm infants has continued to improve.27 Most recent studies do not indicate that improved survival is associated with increased neonatal morbidity.27 These data suggest that perinatal risk factors associated with the development of ADHD may be of less clinical urgency in countries such as Sweden.

Limitations

In this study, we had to rely on clinical diagnoses of ADHD, which are not as reliable as research diagnoses. As the sample was large, smaller aberrations caused by individuals not being diagnosed with ADHD would only moderately weaken the statistical associations that we have studied because the prevalence of ADHD among the children in the reference group would be very low (certainly <5%). A limitation of our study is that data on socioeconomic status, family dysfunction, and abuse were not available for analysis. Although the statistical power seems good, it might not be high enough to detect some relevant associations.

What this paper adds

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. What this paper adds
  7. References
  • • 
    Previous studies of perinatal factors affecting the risk of developing ADHD have mostly involved referred individuals and retrospective obstetric data. This study utilizes data gathered at the time of birth in a population-based representative sample.
  • • 
    This study has comparatively good statistical power.
  • • 
    The results indicate that the studied perinatal risk factors are rather weak compared with previous claims.

References

  1. Top of page
  2. Abstract
  3. Method
  4. Results
  5. Discussion
  6. What this paper adds
  7. References
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