This section examines descriptive statistics including the mean, range, and skewness for child physical health measures. These measures demonstrate unique characteristics of child physical health in the CGS neighbourhoods. Table 4.1 demonstrates the descriptive statistics for measures of the
dependent variable.
Table 4.1 Descriptive Statistics for Child Physical Health
N Range Minimu m Maximu m Mean Std. Deviation Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic
Std. Error Percentage of children not on track 21 28.70 6.30 35.00 16.3238 7.44721 1.171 .501 Subdomain: physical readiness 21 17.00 .00 17.00 4.4579 3.96437 1.956 .501 Subdomain: physical independence 21 28.34 .00 28.34 7.6844 6.72685 1.801 .501
Subdomains gross & fine motor skills
21 31.43 .00 31.43 12.7718 7.75167 .901 .501
There are 21 CGS neighbourhoods included in this study. The range demonstrates that there is quite a wide difference of scores for each measure. The percentage of children not on track has a range of 28.70
%. Physical readiness for the school day has the smallest range of scores (17.0%), and gross & fine motor skills has the widest range of score (31.43%). This shows that child physical health scores in the CGS neighbourhoods have significant variance, with some neighbourhoods having a very low percentage of children not on track as well as some neighbourhoods with a very high percentage of children not on track. Figure 4.1 provides a visual representation of the varying scores for the percentage of children not on track by neighbourhood.
Figure 4.1 Percentage of Children Not on Track by Neighbourhood
Figure 4.1 illustrates the differences between neighbourhoods in terms of children who are not on track for physical health. The Flour Mill and Donovan have the highest percentage of at risk children (35%), and Rural Valley East has the lowest (6.30%). This demonstrates a child physical health gradient because there is a select few neighbourhoods with much higher percentages of children who are not on track. When the subdomains are examined in terms of the distribution of at risk children, there are differences between the sub-domains. Figure 4.2 and 4.3 show differences in the distribution of scores between the sub-domains of child physical health. Figure 4.2 shows the distribution of scores for children meeting few/no developmental expectations for physical readiness for the school day, and
figure 4.3 shows the distribution of scores for children meeting few/no developmental expectations for gross/fine motor skills.
Figure 4.2 Physical Readiness for the School Day by Neighbourhood
Figure 4.3 Gross and Fine Motor Skills Scores by Neighbourhood
Figure 4.2 shows how there are major differences in scores by neighbourhood for physical readiness for the school day. Flour Mill and Donovan is has the highest percentage (17.0%), followed by Minnow Lake
(11.9%). For this sub-domain, there are more neighbourhoods with low percentages, with a select few neighbourhoods who have a significantly higher concentration of children not meeting the
developmental expectations for physical readiness for the school day. Figure 4.3 also demonstrates the wide range of scores between CGS neighbourhoods. However, the distribution of scores do not follow the same pattern. This means neighbourhoods experiencing high percentages of children not meeting developmental expectations for gross/fine motor skills are not the same neighbourhoods experiencing high percentages in other domains. For gross/fine motor skills, Lively has the highest percentage of children meeting few/no developmental expectations (31.43%) followed by Coniston and Falconbridge (26.56%). This indicates that 1) there is a wide range of scores for child physical health in CGS
neighbourhoods, and 2) the distribution of child physical health scores in the CGS neighbourhoods varies depending on what the measurement is. This is important because the same children who are at risk for physical readiness for the school day may not be the same children who are at risk for gross and fine motor skills. This indicates that each domain of child physical health needs to be analyzed separately even though all three domains compromise the total percentage of children who are in the bottom 25th percentile of scores. If neighbourhoods are experiencing different levels of risk for different measures, then there are different variables within those neighbourhoods that are increasing the risk of poor child physical health and wellbeing.
4.1.1 Neighbourhood Skewness
Besides the large and varying ranges, there is also skewness in the distribution of scores by neighbourhood. The subdomains physical readiness and physical independence demonstrate a large skewness. Figure 4.4 illustrates how the physical readiness scores are positively skewed.
Figure 4.4 demonstrates there is a large number of neighbourhoods with the same value of scores. The mean scores for physical readiness is low (4.45 %). This means the average percentage of children meeting few/no developmental expectations for physical readiness is relatively low, but there are select neighbourhoods with a much higher percentage. The distribution of scores for this domain clusters towards the bottom of the distribution. This has implications for the bivariate and multivariate analyses. Table 4.2 summarizes how the dependent variables are distributed including the range of scores, the skewness and kurtosis of the distribution, and the Shapiro-Wilk test which measures the normality of the distribution (or lack thereof). A Shapiro-Wilk test score of p<.05 means that the cases have a statistically significant (not random) distribution and violates the assumption that the data is normally distributed (Hair, Black, Babin, Anerson, & Tatham, 2006).
Table 4.2 Dependent Variable Distribution Scores
Dependent Variable Range Skewness Kurtosis Shapiro-Wilk Test
% of at risk children 28.70% 1.171 .758 .014
Physical readiness 17.00% 1.956 4.36 .001
Physical independence 28.34% 1.801 3.68 .001
Gross/Fine Motor Skills 31.43% .901 .448 .062
Table 4.2 demonstrates that all of the dependent variable measures have a varying range, are negatively skewed, are outside of the expected range of skewness and kurtosis (except for gross/fine motor skills) and the Shapiro-Wilk test demonstrates the data is not normally distributed due to the skewness and kurtosis. Due to the fact that the dependent variables measured in this study are not normally distributed, the data analysis will include results that are adjusted for non-normalcy.