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Prevalence of abnormal general movements in three-month-old infants
Early Human Development 85 (2009) 399–403
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Early Human Development j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e a r l h u m d ev
Prevalence of abnormal general movements in three-month-old infants Hylco Bouwstra a, Geerteke R. Dijk-Stigter b, Hedwig M.J. Grooten c, Femke E.M. Janssen-Plas d, Alice J. Koopmans d, Christien D. Mulder b, Ans van Belle e, Mijna Hadders-Algra a,⁎ a
Department of Paediatrics — Developmental Neurology, University Medical Center Groningen, Groningen, The Netherlands Ouder- en Kindzorg, Icare, Meppel, The Netherlands Thuiszorg & GGD Groningen, Groningen, The Netherlands d Thuiszorg De Friese Wouden, Drachten, The Netherlands e Thuiszorg Het Friese Land, Leeuwarden, The Netherlands b c
a r t i c l e
i n f o
Article history: Received 4 November 2008 Received in revised form 22 December 2008 Accepted 12 January 2009 Keywords: General movements Well baby clinic Neurodevelopment Infant Prevalence
a b s t r a c t Background: The quality of general movements (GMs) is a sensitive tool to measure neurodevelopmental condition in early infancy. No information is available on prevalence rates of abnormal GMs in the general population. Objective: To assess the prevalence of abnormal GMs in the general population of three-month-old infants and to evaluate the association of abnormal GM quality with medical and social risk factors. Method: We recruited 535 infants in six well baby clinics in The Netherlands. GMs were video-taped at the corrected age of 2 to 4 months. GM-quality was assessed by two persons unaware of the infant's history. GMquality was classified as normal optimal (NO), normal suboptimal (SO), mildly abnormal (MA) and definitely abnormal (DA). Only the last category implies clinically relevant dysfunction. Social, perinatal and postnatal characteristics were collected and their association with DA and abnormal (DA + MA) GMs were evaluated by means of univariate and logistic regression analyses. Results: GM-quality could be assessed reliably in 455 infants (85%). Seventeen infants (3.7%) showed DA GMs and 113 (25%) MA GMs. DA GMs were associated with preterm birth and smoking during pregnancy; abnormal (DA + MA) GMs with preterm birth, a relatively low level of paternal profession and urban living conditions. These factors explained between 3% and 7% of variance. Conclusion: The study indicates that the prevalence of definitely abnormal GMs in the general population is 3.7% and that of mildly abnormal GMs 25%. The clinically relevant definitely abnormal GMs were associated with preterm birth and smoking during pregnancy. © 2009 Elsevier Ireland Ltd. All rights reserved.
1. Introduction During the last decade it became increasingly clear that the assessment of the quality of general movements (GMs) provides valuable information regarding the neurological condition of the fetus and young infant. Numerous studies have shown that the quality of GMs reflects the integrity of the central nervous system [1]. GMs are endogenously generated spontaneous movements of the fetus and young infant in which all parts of the body participate. Around 4 months post-term age GMs get increasingly rare as the infant gets more involved in voluntary motor activity. GMs have agespecific expressions which are characteristic for early fetal life,
Abbreviations: GM, general movement; NO, normal optimal; SO, normal suboptimal; MA, mildly abnormal; DA, definitely abnormal. ⁎ Corresponding author. University Medical Center Groningen, Developmental Neurology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands. Tel.: +31 50 3614247; fax: +31 50 3619158 E-mail address: [email protected] (M. Hadders-Algra). 0378-3782/$ – see front matter © 2009 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.earlhumdev.2009.01.003
preterm age, the term period and the final phase of so-called ‘fidgety’ GMs [2]. Fidgety GMs are present between 2 and 4 months post-term. They are characterized by a continuous flow of small and elegant movements occurring irregularly all over the body. The quality of GMs is primarily determined by the degree of movement variation and movement complexity and to a lesser extent by movement fluency. This is true for each GM-phase. The quality of GMs forms a continuum which ranges from highly variable, complex, and fluent movements to highly stereotyped, simple and non-fluent movements. GM-quality can be classified into four categories: two forms of normal GMs (normal-optimal and normal-suboptimal GMs) and two forms of abnormal GMs (mildly and definitely abnormal GMs; Table 1) [3]. The reliability and validity of the GM-method is good [1,4]. The quality of GMs during the fidgety phase has the best predictive power for future neurodevelopmental outcome [1]. Multiple studies of high risk infants have demonstrated that definitely abnormal GMs at fidgety GM age predict with high accuracy neurological disorders, such as cerebral palsy (CP) and that mildly abnormal GMs are related to minor neurological dysfunction and behavioural problems at school age [1,5–
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H. Bouwstra et al. / Early Human Development 85 (2009) 399–403
Table 1 Classification of the quality of GMs [3]. Classification of GM-quality
Complexity
Variation
Fluency
Significance in terms of brain function
Normal-optimal GMs Normal-suboptimal GMs Mildly abnormal GMs Definitely abnormal GMs
+++ ++ + ±/−
+++ ++ + ±/−
+ − − −
Excellent Typical Non-optimal Dysfunction
GM-complexity = spatial variation: The infant actively produces frequent changes in movement direction of the participating body parts. The changes in movement direction are brought about by continuously varying combinations of flexion–extension, abduction–adduction and endorotation–exorotation of the participating joints. GM-variation = temporal variation: Across time, the infant produces continuously new movement patterns, i.e., the infants has an apparently infinite movement repertoire. GM-fluency: presence of smooth, supple and graceful movements. Fluency in particular points to the velocity profile of the movements, which is characterized by gradual accelerations and decelerations. +++ = abundantly present, ++ = sufficiently present, + = present, but insufficiently, ± = minimally present, − = absent.
8]. It should be kept in mind that a mildly abnormal quality of GMs as an isolated risk factor is a poor predictor of an infant's neurodevelopmental outcome. In other words, mildly abnormal GMs do not imply a mildly abnormal nervous system, but rather a normal but nonoptimally functioning nervous system (Table 1). Suboptimal GMquality can be regarded as the typical GM-quality shown by most infants born at term [9]. Normal-optimal GMs are relatively rare; their occurrence is associated with breastfeeding [10]. The assessment of the quality of GMs can help to predict neurological disorders in high risk populations of infants, especially when combined with other neurodevelopmental assessments or imaging techniques [1,11,12]. Another important application of GM-assessment is the evaluation of neurological outcome in groups of infants with specific problems or the effect of prenatal or early postnatal intervention, such as the effect of prenatal and postnatal nutrition [9,10] or the effect of in vitro fertilization (Middelburg et al, personal communication) [13]. For adequate interpretation of the data in the latter type of studies information on the prevalence of mildly and definitely abnormal GMs is a prerequisite. However, currently no data are available on the prevalence of abnormal GMs in the general population. Therefore, the aim of the present study is to determine the prevalence of mildly and definitely abnormal GMs at fidgety GM age in a representative group of infants visiting well-baby clinics in the northern part of The Netherlands. Well-baby clinics provide a scheduled assessment of children's nutritional and medical needs which is performed by public health physicians and their assistants. The Dutch well-baby clinics neatly cover the country thereby providing an unique network of public health care available for every child. The known high visit rate (90%) irrespective of ethnicity allowed us to study a representative sample of Dutch infants at one of the fixed ages of assessment, i.e. at 3 months [13]. A secondary aim of our study is to evaluate the relationship between the sociodemographic and perinatal characteristics and the quality of GMs at fidgety age.
gave informed consent and the study was approved by the Ethics Committee of the Groningen University Hospital. Spontaneous motility in supine position of each infant was videorecorded during 5 min under standardized conditions. The child was dressed in a nappy and was lying on a mattress in a quiet room. The aim was to record the infant's motility at three months corrected age in an active wakeful behavioural state without interference of other persons or presence of toys. GM-quality of all infants was assessed by two persons who were unaware of the infant's history during the assessment. The quality of GMs was classified according to Hadders-Algra et al. [14]. This means that four classes of GM-quality were distinguished: normal-optimal GMs (NO; abundant variation and complexity, fluent), normalsuboptimal GMs (SO; sufficiently variable and complex, non-fluent), mildly abnormal GMs (MA; insufficiently variable and complex, nonfluent) and definitely abnormal GMs (DA; variation and complexity virtually absent, non-fluent; Table 1). The interobserver reliability was good (kappa 0.82; CI 0.62–1.0; n = 30 videos) which is consistent with findings reported previously [14]. In case of disagreement, findings were discussed until agreement was reached. 2.1. Statistics Statistical analyses were performed using the statistical package for social sciences (SPSS 14; SPSS Inc., Chicago, IL). The analysis focused on the influence of social and pre-, peri- and postnatal characteristics on abnormal GMs. Besides univariate statistical analyses with Chi-square, Mann Whitney and t-test, logistic regression analysis was applied to determine which factors were the major determinants of DA GMs and of abnormal (MA + DA) GMs. Factors were only entered into the model if the univariate association with GM quality reached a p-value b0.10. Differences with p-levels b0.05 were considered statistically significant (two tailed). 3. Results In 455 infants (85% of the study population) a video-recording was obtained which allowed for the assessment of the quality of GMs. A major reason that the quality of GMs could not be assessed was that the infant was too old, i.e. was older than 17 weeks corrected age (Table 2), which means that GM-activity had been largely replaced by goal directed activity. Social and perinatal characteristics of infants whose movement quality was not eligible for analysis differed slightly from those who were included: excluded infants were less often born preterm (p = 0.05) and their fathers were better educated (p = 0.04). 3.1. Prevalence of abnormal GMs The distribution of the quality of GMs is shown in Fig. 1. Most infants (72%) showed normal GMs, of whom 14% showed the perfect optimal GMs and the remaining 58% normal-suboptimal GMs.
2. Methods All 605 three-month-old infants visiting six well baby clinics in the Northern part of The Netherlands in the year 2001 were eligible for the study. Two well baby clinics were situated in a city (Leeuwarden and Heerenveen), two in semi rural areas (Haren and Winsum) and two in a rural region (Surhuisterveen and Smilde). Eighty-eight percent of the parents (n = 535) allowed their infant to participate in the study. Infants whose primary caregiver did not master the Dutch language were excluded from the study as language difficulties interfered with the collection of background information. At enrolment standardized information was collected on a wide range of social, and pre-, peri- and postnatal conditions by means of parental interview and from medical records. The parents
Table 2 Number of infants excluded from analysis. Excluded from analysis
Number (% of study population, n = 535)
Age of assessment too high (≥17 weeks) Insufficient quality of video-recording Inadequate behavioural state Crying Sleeping and not moving Insufficient amount of GMs due to goal-directed-behaviour in infants b17 weeks Recording too short for assessment Total number of infants excluded from analysis
57 (11%)
16 (3%) 1 (0.2%) 4 (7%) 2 (4%) 80 (15%)
H. Bouwstra et al. / Early Human Development 85 (2009) 399–403
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Table 4 Multivariate analysis of explaining factors of abnormal quality of GMs. Definitely abnormal
Abnormal (MA + DA)
Explained variance 2.8% Factors Age at investigation in weeks Preterm birth (b 37 weeks) Smoking during pregnancy Lower paternal profession Living area Semi rural area Rural area
Fig. 1. The distribution of the quality of GMs of 3-month old infants visiting general well-baby clinics (n = 455).
Explained variance 6.9%
Standardized coefficient (95% CI)
p
Standardized coefficient (95% CI)
p
–
–
0.87 (0.7–1.0)
0.07
0.02
2.6 (1.0–6.4)
0.05
4.5 (1.3–15.2) 4.9 (1.8–13.8)
a
0.002 –
–
–
–
1.9 (1.1–3.3)b
0.03
– –
– –
0.4 (0.2–0.7)c 0.5 (0.3–0.9)c
0.002 0.03
A standardized coefficient of N 1 means a higher risk for abnormal GMs. a Maternal smoking throughout pregnancy (1 or more cigarette per day). b Relatively low paternal profession: not requiring an university or vocational college education. c When compared to living in an urban area.
Twenty-five percent of infants showed mildly abnormal GMs and seventeen infants (3.7%) had definitely abnormal GMs.
factors related to definitely abnormal GMs and to abnormal (DA + MA) GMs explained only 2.8% and 6.9% of the variance (Table 4).
3.2. Associated factors
4. Discussion
Univariate analysis revealed that the occurrence of definitely abnormal GMs (n = 17) was associated with maternal and paternal smoking during pregnancy, a lower gestational age, preterm birth and a lower birthweight (Table 3). The presence of abnormal (MA + DA) GMs was associated with a lower gestational age, preterm birth, a lower birth weight, not being breastfed for 3 months, a lower paternal education and living in an urban area (Table 3). Multivariate analysis indicated that abnormal (MA + DA) GMs were explained by preterm birth (b37 weeks; p = 0.05), a relatively low level of paternal profession (p = 0.03) and living in a rural or semi rural area (respectively p = 0.03 and p = 0.002). Definitely abnormal GMs were explained by preterm birth (p = 0.02) and smoking during pregnancy (p = 0.002). Note that the models on the
We determined the prevalence of abnormal quality of GMs in a representative population of three-month-old infants (n = 455): 3.7% had definitely abnormal and 25% mildly abnormal GMs. An abnormal quality of (DA or DA + MA) GMs was related to preterm birth, maternal smoking during pregnancy, a lower level of paternal profession and an urban background. A limitation of our study is that we did not assess all infants eligible: parents of 70 (12%) infants did not allow their infant to participate and GMs of another 80 (13%) infants could not be assessed on the basis of an inappropriate age or behavioural state. This might imply that we did not study a representative selection of the general population. However, important social and perinatal characteristics, such as parental education, paternal smoking, living
Table 3 Social and obstetrical characteristics associated with abnormal (DA or DA + MA) quality of GMs. Characteristics
Smoking during pregnancya No smoking n (%) Paternal smoking during pregnancy No smoking n (%) Gestational age in week Mean ± SD Premature birth b 37 weeks n (%) Birthweight in g Mean ± SD Infant was breastfed at least until 3 months n (%) High profession partnerb n (%) Living area Urban n (%) Semi rural n (%) Rural n (%)
Normal GM-quality
Abnormal GM-quality
Missing
p-values
n (%)
Normal vs abnormal
Definitely abnormal vs NO/SO/ MA
NO + SO
MA + DA
DA
n = 325
n = 130
n = 17
283 (88%)
106 (83%)
10 (59%)
5 (1%)
NS
p = 0.004
243 (76%)
94 (74%)
9 (53%)
8 (2%)
NS
p = 0.04
39.6 ± 1.7
39.0 ± 2.4
37.6 ± 3.4
3 (1%)
0.003
16 (5%)
16 (13%)
4 (24%)
3 (1%)
p = 0.005
p = 0.03
3496 ± 553
3339 ± 707
3059 ± 1015
8 (2%)
p = 0.01
p = 0.01
179 (56%)
57 (45%)
4 (25%)
8 (2%)
p = 0.02
NS
100 (36%)
24 (23%)
3 (27%)
71 (16%)
p = 0.02
NS
84 (26%) 123 (38%) 118 (36%)
55 (42%) 20 (23%) 45 (35%)
6 (35%) 6 (35%) 5 (29%)
None q q
p = 0.001 p = 0.003 NS
NS q q
NS = not significant. a Maternal smoking throughout pregnancy (1 or more cigarette per day). b Relatively high paternal profession: requiring a university or vocational college education.
p b 0.0005
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area, premature birth, birth weight and infant feeding practice of the infants studied were comparable to those of the general Dutch population [15,16]. Another limitation of our study is that we only had information on major characteristics of the infants' pre- and perinatal condition and their social background. This limitation is reflected in the low values of the explained variance of the models on abnormal GM-quality. The prevalence of definitely abnormal GMs was 3.7%, a prevalence which is considerably higher than the prevalence of CP which is around 2‰ [17]. The first studies on the predictive value of abnormal GMs indicated that definitely abnormal GMs at fidgety age were associated with a risk of CP of 85–90% [1,6]. However, these studies included many infants with severe brain lesions. Later studies on infants at risk for developmental disorders confirmed that infants with definitely abnormal GMs at fidgety age have a high risk for CP, but the level of risk varied between the studies [6,11,18–23]. The studies also indicated that infants with definitely abnormal GMs who did not develop CP often had minor neurological dysfunction and behavioural problems [1,18]. Our data suggest that the significance of definitely abnormal GMs in the general population might differ from that in populations at risk. This means that the predictive value of definitely abnormal GMs in the general population needs to be determined. Twenty-five percent of the infants showed mildly abnormal GMs, which is consistent with the rate found in a study on the effect of early nutrition in a group of 397 healthy full-term infants [9]. A mildly abnormal GM-quality, reflecting normal but non-optimal brain function, is associated with an increased risk for the development of minor neurological dysfunction and behavioural problems at school age [1,7,8,24,25]. However, the weakness of the association precludes the use of mildly abnormal GMs as single predictor of later problems. The relatively high rate of mildly abnormal GMs might be a reflection of the high rate of various ‘minor’ developmental disorders such as minor neurological dysfunction, developmental coordination disorder and attention-deficithyperactivity-disorder (ADHD) in children [26–29]. In our study, premature birth (b37 weeks) significantly increased the likelihood of a definitely and mildly abnormal GM-quality (Tables 3 and 4). It is getting increasingly clear that preterm birth is associated with white matter injury and adverse neurological outcome [30,31]. This association fits to the association between preterm birth and abnormal GMs as it was recently hypothesized that the neural substrate of abnormal GMs is dysfunction or damage of the transiently present cortical subplate and/or its efferent motor connections in the periventricular white matter [2,32]. We also found that maternal smoking during pregnancy was associated with the presence of definitely abnormal GMs. This finding once again underlines the adverse effect of maternal smoking on fetal brain development [33]. Interestingly the effect of maternal smoking on GM-quality was larger than that of birth weight and parental education. The presence of abnormal GMs was related in particular to socioeconomic parameters, i.e. paternal level of profession and urban living conditions. Socio-economic variables are complex parameters reflecting both nature, i.e. the parents' genetic constitution, and nurture, i.e. environmental conditions. Examples of the latter are pollution and nutrition. In this respect it is interesting to mention that prenatal longchain polyunsaturated fatty acid status is associated with GM-quality at three months and that the addition of these fatty acids to infant formula decreases the rate of mildly abnormal GMs [9,34]. In conclusion, our study indicates that the prevalence of definitely abnormal GMs in the general population at ‘fidgety’ GM age is 3.7% and that of mildly abnormal GMs 25%. Abnormal GMs were associated with premature birth, smoking during pregnancy, a lower level of paternal profession and living in an urban area, but these factors explained only a minor part of the variance. Future studies are needed to assess the predictive value of abnormal GMs in the general population.
Acknowledgements We kindly acknowledge the support of Marius De Konink, MD and Agnes De Groot-Hornstra, MD in the initial phases of the study. This research project was financially supported by Artsen Jeugdgezondheidszorg Nederland.
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Contents lists available at ScienceDirect
Early Human Development j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e a r l h u m d ev
Prevalence of abnormal general movements in three-month-old infants Hylco Bouwstra a, Geerteke R. Dijk-Stigter b, Hedwig M.J. Grooten c, Femke E.M. Janssen-Plas d, Alice J. Koopmans d, Christien D. Mulder b, Ans van Belle e, Mijna Hadders-Algra a,⁎ a
Department of Paediatrics — Developmental Neurology, University Medical Center Groningen, Groningen, The Netherlands Ouder- en Kindzorg, Icare, Meppel, The Netherlands Thuiszorg & GGD Groningen, Groningen, The Netherlands d Thuiszorg De Friese Wouden, Drachten, The Netherlands e Thuiszorg Het Friese Land, Leeuwarden, The Netherlands b c
a r t i c l e
i n f o
Article history: Received 4 November 2008 Received in revised form 22 December 2008 Accepted 12 January 2009 Keywords: General movements Well baby clinic Neurodevelopment Infant Prevalence
a b s t r a c t Background: The quality of general movements (GMs) is a sensitive tool to measure neurodevelopmental condition in early infancy. No information is available on prevalence rates of abnormal GMs in the general population. Objective: To assess the prevalence of abnormal GMs in the general population of three-month-old infants and to evaluate the association of abnormal GM quality with medical and social risk factors. Method: We recruited 535 infants in six well baby clinics in The Netherlands. GMs were video-taped at the corrected age of 2 to 4 months. GM-quality was assessed by two persons unaware of the infant's history. GMquality was classified as normal optimal (NO), normal suboptimal (SO), mildly abnormal (MA) and definitely abnormal (DA). Only the last category implies clinically relevant dysfunction. Social, perinatal and postnatal characteristics were collected and their association with DA and abnormal (DA + MA) GMs were evaluated by means of univariate and logistic regression analyses. Results: GM-quality could be assessed reliably in 455 infants (85%). Seventeen infants (3.7%) showed DA GMs and 113 (25%) MA GMs. DA GMs were associated with preterm birth and smoking during pregnancy; abnormal (DA + MA) GMs with preterm birth, a relatively low level of paternal profession and urban living conditions. These factors explained between 3% and 7% of variance. Conclusion: The study indicates that the prevalence of definitely abnormal GMs in the general population is 3.7% and that of mildly abnormal GMs 25%. The clinically relevant definitely abnormal GMs were associated with preterm birth and smoking during pregnancy. © 2009 Elsevier Ireland Ltd. All rights reserved.
1. Introduction During the last decade it became increasingly clear that the assessment of the quality of general movements (GMs) provides valuable information regarding the neurological condition of the fetus and young infant. Numerous studies have shown that the quality of GMs reflects the integrity of the central nervous system [1]. GMs are endogenously generated spontaneous movements of the fetus and young infant in which all parts of the body participate. Around 4 months post-term age GMs get increasingly rare as the infant gets more involved in voluntary motor activity. GMs have agespecific expressions which are characteristic for early fetal life,
Abbreviations: GM, general movement; NO, normal optimal; SO, normal suboptimal; MA, mildly abnormal; DA, definitely abnormal. ⁎ Corresponding author. University Medical Center Groningen, Developmental Neurology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands. Tel.: +31 50 3614247; fax: +31 50 3619158 E-mail address: [email protected] (M. Hadders-Algra). 0378-3782/$ – see front matter © 2009 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.earlhumdev.2009.01.003
preterm age, the term period and the final phase of so-called ‘fidgety’ GMs [2]. Fidgety GMs are present between 2 and 4 months post-term. They are characterized by a continuous flow of small and elegant movements occurring irregularly all over the body. The quality of GMs is primarily determined by the degree of movement variation and movement complexity and to a lesser extent by movement fluency. This is true for each GM-phase. The quality of GMs forms a continuum which ranges from highly variable, complex, and fluent movements to highly stereotyped, simple and non-fluent movements. GM-quality can be classified into four categories: two forms of normal GMs (normal-optimal and normal-suboptimal GMs) and two forms of abnormal GMs (mildly and definitely abnormal GMs; Table 1) [3]. The reliability and validity of the GM-method is good [1,4]. The quality of GMs during the fidgety phase has the best predictive power for future neurodevelopmental outcome [1]. Multiple studies of high risk infants have demonstrated that definitely abnormal GMs at fidgety GM age predict with high accuracy neurological disorders, such as cerebral palsy (CP) and that mildly abnormal GMs are related to minor neurological dysfunction and behavioural problems at school age [1,5–
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Table 1 Classification of the quality of GMs [3]. Classification of GM-quality
Complexity
Variation
Fluency
Significance in terms of brain function
Normal-optimal GMs Normal-suboptimal GMs Mildly abnormal GMs Definitely abnormal GMs
+++ ++ + ±/−
+++ ++ + ±/−
+ − − −
Excellent Typical Non-optimal Dysfunction
GM-complexity = spatial variation: The infant actively produces frequent changes in movement direction of the participating body parts. The changes in movement direction are brought about by continuously varying combinations of flexion–extension, abduction–adduction and endorotation–exorotation of the participating joints. GM-variation = temporal variation: Across time, the infant produces continuously new movement patterns, i.e., the infants has an apparently infinite movement repertoire. GM-fluency: presence of smooth, supple and graceful movements. Fluency in particular points to the velocity profile of the movements, which is characterized by gradual accelerations and decelerations. +++ = abundantly present, ++ = sufficiently present, + = present, but insufficiently, ± = minimally present, − = absent.
8]. It should be kept in mind that a mildly abnormal quality of GMs as an isolated risk factor is a poor predictor of an infant's neurodevelopmental outcome. In other words, mildly abnormal GMs do not imply a mildly abnormal nervous system, but rather a normal but nonoptimally functioning nervous system (Table 1). Suboptimal GMquality can be regarded as the typical GM-quality shown by most infants born at term [9]. Normal-optimal GMs are relatively rare; their occurrence is associated with breastfeeding [10]. The assessment of the quality of GMs can help to predict neurological disorders in high risk populations of infants, especially when combined with other neurodevelopmental assessments or imaging techniques [1,11,12]. Another important application of GM-assessment is the evaluation of neurological outcome in groups of infants with specific problems or the effect of prenatal or early postnatal intervention, such as the effect of prenatal and postnatal nutrition [9,10] or the effect of in vitro fertilization (Middelburg et al, personal communication) [13]. For adequate interpretation of the data in the latter type of studies information on the prevalence of mildly and definitely abnormal GMs is a prerequisite. However, currently no data are available on the prevalence of abnormal GMs in the general population. Therefore, the aim of the present study is to determine the prevalence of mildly and definitely abnormal GMs at fidgety GM age in a representative group of infants visiting well-baby clinics in the northern part of The Netherlands. Well-baby clinics provide a scheduled assessment of children's nutritional and medical needs which is performed by public health physicians and their assistants. The Dutch well-baby clinics neatly cover the country thereby providing an unique network of public health care available for every child. The known high visit rate (90%) irrespective of ethnicity allowed us to study a representative sample of Dutch infants at one of the fixed ages of assessment, i.e. at 3 months [13]. A secondary aim of our study is to evaluate the relationship between the sociodemographic and perinatal characteristics and the quality of GMs at fidgety age.
gave informed consent and the study was approved by the Ethics Committee of the Groningen University Hospital. Spontaneous motility in supine position of each infant was videorecorded during 5 min under standardized conditions. The child was dressed in a nappy and was lying on a mattress in a quiet room. The aim was to record the infant's motility at three months corrected age in an active wakeful behavioural state without interference of other persons or presence of toys. GM-quality of all infants was assessed by two persons who were unaware of the infant's history during the assessment. The quality of GMs was classified according to Hadders-Algra et al. [14]. This means that four classes of GM-quality were distinguished: normal-optimal GMs (NO; abundant variation and complexity, fluent), normalsuboptimal GMs (SO; sufficiently variable and complex, non-fluent), mildly abnormal GMs (MA; insufficiently variable and complex, nonfluent) and definitely abnormal GMs (DA; variation and complexity virtually absent, non-fluent; Table 1). The interobserver reliability was good (kappa 0.82; CI 0.62–1.0; n = 30 videos) which is consistent with findings reported previously [14]. In case of disagreement, findings were discussed until agreement was reached. 2.1. Statistics Statistical analyses were performed using the statistical package for social sciences (SPSS 14; SPSS Inc., Chicago, IL). The analysis focused on the influence of social and pre-, peri- and postnatal characteristics on abnormal GMs. Besides univariate statistical analyses with Chi-square, Mann Whitney and t-test, logistic regression analysis was applied to determine which factors were the major determinants of DA GMs and of abnormal (MA + DA) GMs. Factors were only entered into the model if the univariate association with GM quality reached a p-value b0.10. Differences with p-levels b0.05 were considered statistically significant (two tailed). 3. Results In 455 infants (85% of the study population) a video-recording was obtained which allowed for the assessment of the quality of GMs. A major reason that the quality of GMs could not be assessed was that the infant was too old, i.e. was older than 17 weeks corrected age (Table 2), which means that GM-activity had been largely replaced by goal directed activity. Social and perinatal characteristics of infants whose movement quality was not eligible for analysis differed slightly from those who were included: excluded infants were less often born preterm (p = 0.05) and their fathers were better educated (p = 0.04). 3.1. Prevalence of abnormal GMs The distribution of the quality of GMs is shown in Fig. 1. Most infants (72%) showed normal GMs, of whom 14% showed the perfect optimal GMs and the remaining 58% normal-suboptimal GMs.
2. Methods All 605 three-month-old infants visiting six well baby clinics in the Northern part of The Netherlands in the year 2001 were eligible for the study. Two well baby clinics were situated in a city (Leeuwarden and Heerenveen), two in semi rural areas (Haren and Winsum) and two in a rural region (Surhuisterveen and Smilde). Eighty-eight percent of the parents (n = 535) allowed their infant to participate in the study. Infants whose primary caregiver did not master the Dutch language were excluded from the study as language difficulties interfered with the collection of background information. At enrolment standardized information was collected on a wide range of social, and pre-, peri- and postnatal conditions by means of parental interview and from medical records. The parents
Table 2 Number of infants excluded from analysis. Excluded from analysis
Number (% of study population, n = 535)
Age of assessment too high (≥17 weeks) Insufficient quality of video-recording Inadequate behavioural state Crying Sleeping and not moving Insufficient amount of GMs due to goal-directed-behaviour in infants b17 weeks Recording too short for assessment Total number of infants excluded from analysis
57 (11%)
16 (3%) 1 (0.2%) 4 (7%) 2 (4%) 80 (15%)
H. Bouwstra et al. / Early Human Development 85 (2009) 399–403
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Table 4 Multivariate analysis of explaining factors of abnormal quality of GMs. Definitely abnormal
Abnormal (MA + DA)
Explained variance 2.8% Factors Age at investigation in weeks Preterm birth (b 37 weeks) Smoking during pregnancy Lower paternal profession Living area Semi rural area Rural area
Fig. 1. The distribution of the quality of GMs of 3-month old infants visiting general well-baby clinics (n = 455).
Explained variance 6.9%
Standardized coefficient (95% CI)
p
Standardized coefficient (95% CI)
p
–
–
0.87 (0.7–1.0)
0.07
0.02
2.6 (1.0–6.4)
0.05
4.5 (1.3–15.2) 4.9 (1.8–13.8)
a
0.002 –
–
–
–
1.9 (1.1–3.3)b
0.03
– –
– –
0.4 (0.2–0.7)c 0.5 (0.3–0.9)c
0.002 0.03
A standardized coefficient of N 1 means a higher risk for abnormal GMs. a Maternal smoking throughout pregnancy (1 or more cigarette per day). b Relatively low paternal profession: not requiring an university or vocational college education. c When compared to living in an urban area.
Twenty-five percent of infants showed mildly abnormal GMs and seventeen infants (3.7%) had definitely abnormal GMs.
factors related to definitely abnormal GMs and to abnormal (DA + MA) GMs explained only 2.8% and 6.9% of the variance (Table 4).
3.2. Associated factors
4. Discussion
Univariate analysis revealed that the occurrence of definitely abnormal GMs (n = 17) was associated with maternal and paternal smoking during pregnancy, a lower gestational age, preterm birth and a lower birthweight (Table 3). The presence of abnormal (MA + DA) GMs was associated with a lower gestational age, preterm birth, a lower birth weight, not being breastfed for 3 months, a lower paternal education and living in an urban area (Table 3). Multivariate analysis indicated that abnormal (MA + DA) GMs were explained by preterm birth (b37 weeks; p = 0.05), a relatively low level of paternal profession (p = 0.03) and living in a rural or semi rural area (respectively p = 0.03 and p = 0.002). Definitely abnormal GMs were explained by preterm birth (p = 0.02) and smoking during pregnancy (p = 0.002). Note that the models on the
We determined the prevalence of abnormal quality of GMs in a representative population of three-month-old infants (n = 455): 3.7% had definitely abnormal and 25% mildly abnormal GMs. An abnormal quality of (DA or DA + MA) GMs was related to preterm birth, maternal smoking during pregnancy, a lower level of paternal profession and an urban background. A limitation of our study is that we did not assess all infants eligible: parents of 70 (12%) infants did not allow their infant to participate and GMs of another 80 (13%) infants could not be assessed on the basis of an inappropriate age or behavioural state. This might imply that we did not study a representative selection of the general population. However, important social and perinatal characteristics, such as parental education, paternal smoking, living
Table 3 Social and obstetrical characteristics associated with abnormal (DA or DA + MA) quality of GMs. Characteristics
Smoking during pregnancya No smoking n (%) Paternal smoking during pregnancy No smoking n (%) Gestational age in week Mean ± SD Premature birth b 37 weeks n (%) Birthweight in g Mean ± SD Infant was breastfed at least until 3 months n (%) High profession partnerb n (%) Living area Urban n (%) Semi rural n (%) Rural n (%)
Normal GM-quality
Abnormal GM-quality
Missing
p-values
n (%)
Normal vs abnormal
Definitely abnormal vs NO/SO/ MA
NO + SO
MA + DA
DA
n = 325
n = 130
n = 17
283 (88%)
106 (83%)
10 (59%)
5 (1%)
NS
p = 0.004
243 (76%)
94 (74%)
9 (53%)
8 (2%)
NS
p = 0.04
39.6 ± 1.7
39.0 ± 2.4
37.6 ± 3.4
3 (1%)
0.003
16 (5%)
16 (13%)
4 (24%)
3 (1%)
p = 0.005
p = 0.03
3496 ± 553
3339 ± 707
3059 ± 1015
8 (2%)
p = 0.01
p = 0.01
179 (56%)
57 (45%)
4 (25%)
8 (2%)
p = 0.02
NS
100 (36%)
24 (23%)
3 (27%)
71 (16%)
p = 0.02
NS
84 (26%) 123 (38%) 118 (36%)
55 (42%) 20 (23%) 45 (35%)
6 (35%) 6 (35%) 5 (29%)
None q q
p = 0.001 p = 0.003 NS
NS q q
NS = not significant. a Maternal smoking throughout pregnancy (1 or more cigarette per day). b Relatively high paternal profession: requiring a university or vocational college education.
p b 0.0005
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area, premature birth, birth weight and infant feeding practice of the infants studied were comparable to those of the general Dutch population [15,16]. Another limitation of our study is that we only had information on major characteristics of the infants' pre- and perinatal condition and their social background. This limitation is reflected in the low values of the explained variance of the models on abnormal GM-quality. The prevalence of definitely abnormal GMs was 3.7%, a prevalence which is considerably higher than the prevalence of CP which is around 2‰ [17]. The first studies on the predictive value of abnormal GMs indicated that definitely abnormal GMs at fidgety age were associated with a risk of CP of 85–90% [1,6]. However, these studies included many infants with severe brain lesions. Later studies on infants at risk for developmental disorders confirmed that infants with definitely abnormal GMs at fidgety age have a high risk for CP, but the level of risk varied between the studies [6,11,18–23]. The studies also indicated that infants with definitely abnormal GMs who did not develop CP often had minor neurological dysfunction and behavioural problems [1,18]. Our data suggest that the significance of definitely abnormal GMs in the general population might differ from that in populations at risk. This means that the predictive value of definitely abnormal GMs in the general population needs to be determined. Twenty-five percent of the infants showed mildly abnormal GMs, which is consistent with the rate found in a study on the effect of early nutrition in a group of 397 healthy full-term infants [9]. A mildly abnormal GM-quality, reflecting normal but non-optimal brain function, is associated with an increased risk for the development of minor neurological dysfunction and behavioural problems at school age [1,7,8,24,25]. However, the weakness of the association precludes the use of mildly abnormal GMs as single predictor of later problems. The relatively high rate of mildly abnormal GMs might be a reflection of the high rate of various ‘minor’ developmental disorders such as minor neurological dysfunction, developmental coordination disorder and attention-deficithyperactivity-disorder (ADHD) in children [26–29]. In our study, premature birth (b37 weeks) significantly increased the likelihood of a definitely and mildly abnormal GM-quality (Tables 3 and 4). It is getting increasingly clear that preterm birth is associated with white matter injury and adverse neurological outcome [30,31]. This association fits to the association between preterm birth and abnormal GMs as it was recently hypothesized that the neural substrate of abnormal GMs is dysfunction or damage of the transiently present cortical subplate and/or its efferent motor connections in the periventricular white matter [2,32]. We also found that maternal smoking during pregnancy was associated with the presence of definitely abnormal GMs. This finding once again underlines the adverse effect of maternal smoking on fetal brain development [33]. Interestingly the effect of maternal smoking on GM-quality was larger than that of birth weight and parental education. The presence of abnormal GMs was related in particular to socioeconomic parameters, i.e. paternal level of profession and urban living conditions. Socio-economic variables are complex parameters reflecting both nature, i.e. the parents' genetic constitution, and nurture, i.e. environmental conditions. Examples of the latter are pollution and nutrition. In this respect it is interesting to mention that prenatal longchain polyunsaturated fatty acid status is associated with GM-quality at three months and that the addition of these fatty acids to infant formula decreases the rate of mildly abnormal GMs [9,34]. In conclusion, our study indicates that the prevalence of definitely abnormal GMs in the general population at ‘fidgety’ GM age is 3.7% and that of mildly abnormal GMs 25%. Abnormal GMs were associated with premature birth, smoking during pregnancy, a lower level of paternal profession and living in an urban area, but these factors explained only a minor part of the variance. Future studies are needed to assess the predictive value of abnormal GMs in the general population.
Acknowledgements We kindly acknowledge the support of Marius De Konink, MD and Agnes De Groot-Hornstra, MD in the initial phases of the study. This research project was financially supported by Artsen Jeugdgezondheidszorg Nederland.
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