During the past decade, interest in the documentation of neuromotor development to support a systematic approach to clinical practice and research has been growing. This interest has resulted in increased demand for standardized assessment tools.1–3 Standardized neuromotor assessments are important to describe early motor development, particularly to measure and monitor the rapid and extensive changes that occur during the first years of life.3 Standardized neuromotor assessment tools are used routinely in the United States, Canada, and Europe, where most of the available assessment tools were developed. The use of these instruments is not routine in other countries because of economic, language, and cultural barriers, as well as a lack of specific training in the use of these standardized assessments.
The psychometric properties of a test, such as interrater and intrarater reliabilities and the concurrent validity, can be influenced by culture-specific elements.4 As a result, direct generalization of the content of a neuromotor assessment to other cultures may not be appropriate because the standardized age norms developed in one country may not be suitable as a reference for the interpretation of the results in another, as in the case of Brazil.5,6 Therefore, the use of imported assessment tools should be preceded by efforts to develop an accurate translation, to analyze the possible cross-cultural differences, and, if needed, to gather reference data for the culture in which the assessment will be used.5,6
The Alberta Infant Motor Scale (AIMS), which is a Canadian gross motor developmental assessment, has been used across different continents (North and South America, Europe, Asia, and Oceania). Researchers in Brazil have used the scale extensively. The instrument is used for different purposes: to characterize gross motor development in infants born healthy and at term and in infants born preterm; to assess the influence of different risk factors on early motor milestone acquisition; and as an outcome measure for intervention studies.
According to Santos et al,7 among the tests that can be used to assess early gross motor development, the AIMS is most often cited in Brazilian studies. Researchers using the AIMS in Brazil have assessed its concurrent validity and reliability8,9; characterized motor development in infants born full-term,10–13 preterm,14–16 and with low birth weight7; and assessed infants small for their gestational age.17 The AIMS has also been used to assess the influence of child-rearing practices,18 to examine the need to use corrected gestational age,19 and to compare oral and gross motor achievement.20 The AIMS is also used to assess the motor function of infants, both those born full-term and those born preterm,21 and to follow the motor development of infants in early intervention programs, including those born preterm22 and children with Down syndrome.23 Although no age reference values for the AIMS have been published for Brazilian children, the test has been integrated into research and clinical practice.
The AIMS has sound psychometric properties, such as high intrarater and interrater reliability and good to high degrees of concurrent validity. The AIMS is also easy to administer, low in cost, and requires minimal resources; these qualities may account for its widespread use. Despite these qualities, in only 2 countries, the Netherlands and Greece, have researchers compared the gross motor development of full-term infants with the Canadian reference values.24,25 Researchers in the Netherlands also compared data from infants born preterm with Canadian values.26 The results have been inconsistent. Greek infants showed a gross motor developmental pattern similar to the Canadian values, but Dutch children scored below Canadian values in both the full-term and preterm groups.
In Brazil, 2 research groups have examined Brazilian infants using the AIMS, one reported in 2004 with infants born preterm23 and the other in 2012 with infants born preterm and full-term.27 Both groups found that the motor performance of Brazilian infants was inferior to the Canadian norms. Data from the latter Saccani and Valentini27 study were collected almost at the same time as this study, and although they evaluated a considerable number of infants (795), their data are representative of a southern state, where higher economic standards of living may limit the extent to which the results could be generalized to the entire Brazilian infant population. As Brazil has major climatic, cultural, and economic differences from south to north that may influence children's development, other studies are needed. The aim of this study was to further examine the adequacy of the original Canadian reference values for use with Brazilian infants. Data were collected in a central state, Minas Gerais, which is—on the basis of the United Nations' Human Development Index (HDI)28—considered to be representative of the country's population diversity. The research questions were as follows: (1) Does gross motor development differ significantly between Brazilian and Canadian infants as measured by the AIMS? (2) Does gross motor development differ significantly among groups with respect to sex, economic status, and the HDI?
A cross-sectional study of gross motor development in 660 Brazilian infants (330 girls), aged from 0 to 18 months who were born healthy and at full-term, was conducted in a Brazilian metropolitan city, Belo Horizonte. The data were collected between 2009 and 2011. The infants were recruited from private pediatric clinics, private day care centers, and public health services. Gross motor development was measured using the AIMS. Written consent was obtained from the parents. The Ethics Review Committee of Universidade Federal de Minas Gerais (ETIC 640/08) and of Prefeitura de Belo Horizonte-MG (CAAE 0016.0.410.203-100) approved this study. Both the publisher and an author of the AIMS provided permission to translate the AIMS score sheet into Portuguese.
Infants were included if they were between 0 and 18 months old, were born full-term (>37 weeks), had a birth weight greater than 2.5 kg, with no gestational and delivery complications, and had no cardiac, respiratory, or neurological problems. Infants were excluded if they had a problem that could affect their motor development or were on long-term medication.
To characterize the sample population, the sex (male/female), gestational age (weeks), birth weight (kg), height, head circumference (cm), and Apgar score (0-10) at the 1st and 5th minutes were recorded. Children with Apgar scores below 7 were not included in the sample. The HDI was used as a measure of life expectancy, literacy, education, and standards of living.28 The HDI ranges from 0 to 1 and the values are divided into 4 subcategories: low (0-0.499), medium (0.5-0.799), high (0.8-0.899), and very high (9 to 1). Because Brazil as well as Belo Horizonte have high average HDI scores of 0.81 and 0.80, respectively, infants in this study were grouped into the following subcategories: 36% as medium (0.787-0.788), 26% as medium-high (0.789-0.835), and 38% as high (0.836-0.914) according to the distribution among live births in the 2000 Brazilian census. Besides the HDI, which is a group estimate by region, the Brazilian Criteria for Economical Classification (ABEP)29 questionnaire was used to classify the socioeconomic status of each child's family. The results of this questionnaire are categorized in 5 levels: A (scores 25-34), B (scores 17-24), C (scores 11-16), D (scores 6-10), and E (scores 0-5). The lower the score, the more economically disadvantaged the family.
Measurement of Gross Motor Development
The AIMS is a performance-based, norm-referenced observational measure of infant gross motor development from 0 to 18 months. The scale has 58 items divided into 4 subscales: prone (21 items), supine (9 items), sitting (12 items), and standing (16 items). Each item includes a description of the body weight distribution, the postural components, and the active movements the examiner must observe to assign a grade of “pass” for an infant's performance on each item. Children were undressed and observed individually for 20 to 30 minutes in the presence of at least one of the parents (if the child was at home) or the caretaker (if the child was at a day care). The child had to be awake and active during the assessment. After observing the infant's spontaneous movements, the examiner completed the AIMS score sheet. Each examination was video recorded for confirmation of the score, when needed. First, the examiner determined the least and most mature observed items in each of the 4 positions, thus determining the windows within which every item in each position must be scored. Each item inside the window was scored on a dichotomous scale as observed (1 point) or not observed (0 point). Items below the window were assigned 1 point, and items above the window were considered to be a fail. The sum of the item scores produces the total raw score, ranging from 0 to 58, which can be converted to a percentile rank on the basis of monthly levels (from 0 to 19). Three trained pediatric therapists—2 physical therapists and 1 occupational therapist-–assessed all the infants. Interrater reliability was determined before data collection, with the observation and independent scoring of 10 children, yielding intraclass correlation coefficients of 0.93 to 0.97, indicating highly congruent results among the 3 examiners.
The infants were divided into 18 groups according to age in months at the time of assessment. The Shapiro–Wilk test for normality was used to determine whether the data were normally distributed. For each month of age, the mean AIMS score, standard deviation, and confidence intervals were calculated, and the Student t test was used to compare the mean AIMS scores from our study with the reference values of the original Canadian population.30 The effect sizes were calculated using G*Power 3.1 and were classified as small, moderate, or large according to Cohen's criteria for standardized differences in means, using the thresholds 0.20, 0.50, and 0.80, respectively.31 The binominal test was used to compare the percentile ranks (5th, 10th, 25th, 50th, 75th, and 90th) for the first 14 months only because all percentile curves tended to converge to the same value from this point onwards.
Because a normal distribution was not present in some months, nonparametric tests were used to compare the scale rankings for sex and between the 3 HDI ranges and the 5 categories of the ABEP questionnaire. The Mann-Whitney test was used to compare sex. For the HDI and ABEP questionnaire, the Kruskal–Wallis test was used to compare multiple categories. All statistical analyses were conducted using the PASW program, version 18, and the R program, version 2.13.0. The α level for statistical significance was set at 0.05.
Characteristics of Participants
A total of 660 infants were included in the sample. General sample characteristics are presented in Table 1. The economic status distribution according to the ABEP questionnaire was as follows: 41.8% (A), 13.7% (B), 35.8% (C), 8.4% (D), and 0.3% (E).
Brazilian Versus Canadian Scores for AIMS
The mean, standard deviation, and mean difference (95% confidence interval) for the AIMS total scores for the 660 Brazilian infants compared with the original Canadian sample, aged 0 to 18 months, is shown in Table 2. Statistically significant differences were found between the Brazilian and Canadian infants for the age groups 0 to less than 1 month (P = .045; d = 0.43), 1 to less than 2 months (P = .021; d = 0.39), 4 to less than 5 months (P = .000; d = 0.8), 5 to less than 6 months (P = .001; d = 0.4) and 10 to less than 11 months (P = .009; d = 0.47). The Brazilian infants showed lower mean scores for all age groups except for the 0 to less than 1-month group, in which the Brazilian infants had higher mean scores. Figure 1 shows the mean AIMS score curves for Brazilian and Canadian infants.
AIMS percentile ranks for the Brazilian infants throughout the first 14 months are presented in Table 3. Statistically significant differences were found scattered in all percentile values, with the highest number of differences in the 75th percentile curve (1-<2, 2-<3, 4-<5, 5-<6, 10-<11, 11-<12, and 13-<14 monthly age groups). Statistically significant differences were also found in the 5th percentile at 9 to less than 10 and 10 to less than 11 months of age; the 10th percentile at 4 to less than 5, 9 to less than 10, and 10 to less than 11 months of age; the 25th percentile at 4 to less than 5, 5 to less than 6, and 11 to less than 12 months of age; the 50th percentile at 4 to less than 5 and 5 to less than 6 months of age; and the 90th percentile at 10 to less than 11, 11 to less than 12, and 13 to less than 14 months of age. Figure 2 shows the distribution of AIMS percentile ranks for the Brazilian and Canadian infants from 0 to 18 months.
No significant sex differences were found in the AIMS scores for the age groups except for age 12 months to less than 13 months, in which girls presented higher scores (P = .047). For the HDI, significant differences were observed only at 13 months to less than 14 months, in which the medium HDI group had higher scores than the high HDI group (P = .006). No statistically significant differences were found in the AIMS scores for all age groups on the ABEP socioeconomic classification.
This study with Brazilian infants compared monthly gross motor development from 0 to 18 months with the AIMS reference values that were derived from Canadian subjects. The results showed that Brazilian infants born full-term presented an almost similar course of gross motor development for age groups and percentile ranks compared with the AIMS Canadian reference values. No significant differences were found in our sample between sexes with the exception of one age group (12-<13 months), in which the girls presented higher scores.
Although we found differences between the Canadian and Brazilian data sets in the mean AIMS scores in 5 of 17 age groups, the mean difference was quite small, less than 1 point, for the 0 to less than 1 and 1 to less than 2 months' age groups. The differences found in the first 2 months could be related to the small number of AIMS test items that were available for the first 3 months after birth. Considering the total score, a difference of only 1 point in these age groups could be enough to explain the results of this study.
At ages of 4 months to less than 5 months, 5 months to less than 6 months, and 10 months to less than 11 months, the differences reached values of 3.2, 1.9, and 2.3 points and deserve special attention, as the effect size for 4 months to less than 5 months was also large. Clinically, the age bands 4 months to less than 5 months and 5 months to less than 6 months are critical for the early detection of motor delay and to direct decisions regarding referral for treatment. Differences in gross motor development in these age groups could be related to parent practices, such as the use of the supine position to avoid or prevent sudden infant death syndrome. The relationship between the use of the prone and supine positions and the rate of gross motor development is well documented in the literature.32,33 Formiga et al22 showed that Brazilian parents actually avoid the use of the prone position even if the child is awake. This could be a reason for the differences in scores between Brazilian and Canadian infants and should be investigated in future studies.
The difference found in the total score at 10 months to less than 11 months could be explained by both the psychometric characteristics of the AIMS and intrinsic motor development characteristics. Using Rasch analysis to investigate the hierarchy of item difficulty calibration for the AIMS, Liao and Campbell34 revealed that starting at 9 months, gaps instead of small increments in the continuum of item difficulty are present. Indeed, at the high end of the scale, fewer items are available, actually just the standing position ones, which results in less precision in measurement. The gaps or bigger increments in item difficulty, from 1 standing position item to the next mean more unpredictable variance, may have contributed to the differences found in this study. From a clinical perspective, an infant who does not progress from 1 item to the next could have a motor ability that is close to the item passed, close to the item failed, or anywhere between the 2 (gap unmeasured). However, Bartlett35 reported that infants who scored low on the AIMS at 10 months of age did not necessarily score low on the AIMS at 15 months or on the Peabody Developmental Motor Scale at 18 months, showing that motor development is not continuous. Both conditions lead to variation in individual scores that could have contributed to the total score differences observed at 10 months to less than 11 months.
Although it would be relevant to determine whether specific items of the AIMS show discrepancies (variance) that could possibly have led to differences observed in the total scores at specific months (ie, 4, 5, 6, and 10 months), this analysis was not possible because specific data on the mean age that infants acquire the 58 skills of the AIMS are not available in the AIMS manual. This could be considered a limitation of this study. As a result, only the percentile curves were used to assess whether to set new reference values for Brazilian infants from 0 to 18 months.
Comparison of the AIMS percentiles using the binominal tests shows that Brazilian infants, with a few exceptions, follow a course that is very similar to that of Canadian infants. Significant differences were found between groups scattered in some ages and percentile ranks, but they are most frequent at the 75th percentile (6 age groups). Although the 75th percentile is important for characterizing motor development, it is not clinically important to identify motor development delay. As discussed by Darrah et al,36 2 different percentile cut-off points of the AIMS are used to identify infants with atypical motor development: the 10th percentile at 4 months and the 5th percentile at 8 months.
Significant differences were found in the age groups of 9 months to less than 10 months and 10 months to less than 11 months at the 5th percentile and in the 4 months to less than 5 months group at the 10th percentile. Descriptive analysis indicates that 3 of the 50 infants in the 9 months to less than 10 months group (6%) and 5 of the 50 infants in the 10 months to less than 11 months group (9.4%) fell within the 5th percentile. For the 4 months to less than 5 months group, 4% of infants were below the 10th percentile. In the 4 months to less than 5 months group, the point differences were minor (1.6 points). Despite this, it is noteworthy that a change in 1 point in the total score can change the percentile rank substantially in the younger and older age groups.37 Considering that the recommended AIMS cut-off points for diagnosing or predicting motor delay are at 4 months and 8 months and since we found significant differences between Canadian and Brazilian infants at the 10th percentile at 4 months, we recommend the use of the percentile curves of this study (Figure 3) when assessing healthy full-term infants in Brazil.
Even though healthy full-term Brazilian infants in some age groups show an apparent delay in motor development when compared with infants in the normative Canadian sample, the results corroborate those of other Brazilian and international studies. In Brazil, Lopes et al13 assessed 70 infants from birth to 6 months and found that Brazilian infants presented lower percentiles than the AIMS normative values, with most of the Brazilian infants falling at or below the 25th percentile. In a study similar to ours that included 795 infants born preterm or full-term aged 0 to 18 months from the south of Brazil, Saccani and Valentini27 reported that Brazilian infants scored lower in 13 of 18 age groups than the Canadian group, whereas in our study we found difference in only 5 age groups. Another similarity to the study results by Saccani and Valentini27 is that sex did not seem to be an issue for early gross motor development, as differences were found in only 1 age group in each study, with an advantage for the females at age 12 months to less than 13 months in this study and at age 14 months in the study by Saccani and Valentini. This study, using a sample whose HDI is similar to the country's mean, adds to the work by Saccani and Valentini,27 as both support the need to use Brazilian reference values for making clinical decisions.
Motor development studies in different countries with infants who were healthy and born full-term using the AIMS showed varying results. Although Greek infants (n = 424) aged 0 to 18 months showed a similar developmental curve compared with the Canadian reference values, Dutch infants (n = 100) aged 0 to 12 months showed lower scores.25,24 These differences could be related to parenting practices, environmental stimuli, or cultural and socioeconomic influences; however, no study examined these variables. It is also noteworthy that the Dutch study had a sample size of only 100 children.
Surprisingly, the socioeconomic status, as measured with the HDI and ABEP, showed statistically significant differences only at the age of 13 to less than 14 months, in which the medium HDI group had higher AIMS scores than the high HDI group. Belo Horizonte's HDI is 0.8 and Brazil's HDI is 0.813 (HDI-2009), both classified as high. On the basis of the HDI, Belo Horizonte can be considered to be representative of Brazil, and therefore the results of this study can be generalized to the Brazilian population, which should be confirmed with further studies.
At this point, we suggest that both the mean AIMS total scores and the percentile curves presented in this study should be used with Brazilian infants. Even though we found that the socioeconomic status of the families did not influence the rate of gross motor development, because Brazil is a large country with great cultural diversity, specific regional characteristics may influence parenting practices and affect the rate of motor development. Consequently, future studies should include data from different regions of the country. Combining data sets and conducting collaborative studies would lead to a more representative sample of the country's diversity. Finally, it should be noted that, because the AIMS reference data were collected more than 20 years ago, it would be interesting to compare our recent Brazilian data with updated Canadian reference data.
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