Effects of puberty nutrition socioeconomic status
Discussion
In the last decades scholars debate on the effects of puberty, nutrition, socioeconomic status, geographical location , ethnicity etc on skeletal maturation and skeletal age in both genders. Age has also been indicated as one of the most essential factors for establishment of the identity of an individual and determination of the growth factors related to the individual .The question that is raised in multiple studies is whether the greulich and pyle atlas standards set in year 1959 are still applicable on our population and also the population used at that time is different to todays population. To answer these questions a multicentre longitudinal study needs to be undertaken (as suggested by Loder et al., 1993; Ontell et al., 1996) including children of all races and ethnicity and taking into account different geographical locations. As this set standard is used in very important fields of life like medical field for assessing growth abnormalities and response to treatments, forensic, criminal and legal cases for trafficking victims and illegal immigrants etc it is note worthy that this technique should be continuously checked and investigated especially in developing world.
Greulich and Pyle did not consider different races when standardizing the atlas for skeletal development of children and adolescents. Sutow et al. (1953) mentioned in a study about the effects of ethnicity causing retardation of skeletal age. He discussed racial differences to be among the causes of retardation of skeletal maturation among the Japanese children. He sought a sample of 898 children of the Japanese origin from San Francisco, California. They were aged between 5 and 18 years. Boys between 13 and 17 and girls between 10 and 17 showed comparative acceleration (Sutow, 1953). This was contrasted to Greulich’s 5-7 years age group (Gruelich, 1957). Sutow et al. (1953) attributed the trend to the fact that the children from the Japanese descendent did not have favorable environmental and nutritional conditions. It is, however, possible to alter the information regarding ethnicity in our study by considering the information that according to CSO (Ireland Central Statistics Office), Eurostat and CIA world fact book suggested that total population in Ireland is 4,581,269 in 2011 and 4,588,252 (preliminary) in 2012. There are different nationalities and ethnicities living in Ireland. 86.9% population is Irish, however the total white population (Irish and other white population from UK or EU countries) comprises of total of 94.3 % of all population. Ethnicities like Asians make up 1.9%, black 1.4%, others 0.9% and ethnicity not known is 1.6%.
Greulich andPyle did not consider different races when standardizing the atlas for skeletal development of children and adolescents. Sutow et al. (1953) mentioned in the study about the effects of ethnicity causing retardation of skeletal age. The opinion was that ethnicity is one of the strongest factors that contributes to the retardation of skeletal age. But information in regards to ethnic origin could be adjusted in our study by considering the information that according to CSO (Ireland Central Statistics Office), Eurostat and CIA world fact book suggested that total population in Ireland is 4,581,269 in 2011 and 4,588,252 (preliminary) in 2012.There are different nationalities and ethnicities living in Ireland. 86.9% population is Irish, however the total white population (Irish and other white population from UK or EU countries) comprises of total of 94.3 % of all population.
The current sample histograms (Figure 1) shows that majority of our study population shows a difference of under 12 months ( standard chosen to be 1 year due to the SD value advised by Greulich and Pyle to be 0.6 to 1.1 years). In 59 percent of the female children, the difference between skeletal age and chronological age is less than 5 months while in 31 percent of the female children the difference is found to be 5 to 10 months. Figure 2 shows that unlike the female children, 43 percent of males shows a difference of less than 5 months and 39 percent have difference between chronological and skeletal age of 5 to 10 months. The study of Hackman et al. (2012) and Paxton et al. (2012) showed an estimated 29 and 33 percent of females showing a difference of less than 5 months and 20 and 26 percent showed a difference of 5 to 10 months. In males less than 5 months difference was estimated in 26 and 27 percent and 5 to 10 months in 23 percent respectively ( NB_ values estimated at 5 and 10 months from histograms in their studies is due to the range presented on x-axis as ± 5, 10, 15 months etc ). Hence the difference observed in current study is comparatively lower as compared to the above two study results and also the current sample showed an over all 90 percent females and 82 percent males showing a difference of less than one year which is insignificant.
For the current study, the difference between skeletal and chronological age is found to be lesser than the previously attempted studies. The standard deviation for the entire sample was found to be 7.8 months (6.9 for females and 8.3 for males) whereas the range noted in the Greulich and Pyle for females was between 0.72 to 7.31 and males 0.6 to 13.0 months. This supports the clinical applicability of the Greulich and Pyle method for Irish children and adolescents and as most of the subjects are observed with a difference between skeletal and chronological age equal to 10 months, we can assume that the gap is not large enough to affect medical and surgical treatment. But still the gap is justified with the fact that maturation changes with respect to time. There is 0.22-0.66 years increase in skeletal maturation per decade (Himes, 1984). Only the lower end of this possible spectrum is achieved mainly in younger age groups in females and age group 0 and 2 years in males based on the findings of current study.
It is noted that skeletal maturation is gender specific and different in males and females respectively (Marshall et al., 1969 and 1970). This study found out that there has been a general mixed pattern for both under-aging and over-aging in both genders. The over-aging range from 0.59 to 5.56 months from the age 1 to 8 years in females shows that girls are overestimated. Also, it can be due to the fact that girls reach the stages of skeletal maturation earlier in comparison to the male population (Mito et al., 2002). For males over-aging ranged from 1.54 to 3.63 months in age groups 14 to 16 years and 18 years. The pattern for males has been consistent for under-aging from 3 to 9 years and 11 and 12 years old. This pattern of under-aging in males before puberty and overa-ging after puberty is seen in other studies conducted by Ontell et al. (1996), Koc et al. (2001), Büken et al. (2007), Nahid et al. (2010), Zafar et al. (2010) and Hackman et al. (2012). In both males and females 19 years showed an under-aging and could be due to the end of the atlas series at this age group. In comparison, the Hackman et al. (2012) study showed a general mixed pattern of under-aging and over-aging. It was seen that, for females, over-aging occurs at 1, 3, 6, 7 and 9-16 years old with over-aging from 0.20 to 5.73 months. They also indicated that, for males, there is a tendency of over-aging from the age of 0 to 2 years, same seen in our study in ages 0 and 2 years old. The tendency of under-aging between 3 to 8 years and 10 and 12 years, and over-aging between 14-16 years for males is seen in our study as well. The pattern of under-aging for males was also seen in the study conducted by Rikhasor et al. (1999) and Patil et al. (2011) from age groups 2 to 15 years and 4 to 15 years ranging from 0.3 to 1.1 years and more than 0.5 years. The reason stated was poor nutrition and ill health affecting the maturation of carpal bones.
The results in Table 5 showed that the correlation coefficient between skeletal and chronological age of both female and male subjects is 0.99. Büken et al. (2007) found high correlation with r = 0.88 for girls and r = 0.90 for males. The study indicated for both females and males a R2 value 0.98 and regression coefficient of 0.97 for females and 1.01 for males (p < 0.05) indicated by the first observer. The variance is high at 98% indicating that the relationship between the chronological and skeletal age is positive and highly correlated. Hackman et al. (2012) showed an R2 value of 0.93 and 0.94 with regression coefficient of 0.89 and 0.97 for females and males (p <0.001) respectively. The study found that the mean differences between chronological age and skeletal age in months where males had a mean difference of -1.24 with an over-age of 31.45 months and an under-age of -35.72 months as compared to the females who had mean difference of 0.99 with an over-age of 18.57 months and an under age of -24.57 months. Hackman and Black (2012) indicated that the differences between chronological age and skeletal age ranged from between an under-age of 37 months and an over-age of 31 months which was similar for both females and males. In the study of Rijn et al. (2000) the differences ranged from -30 to +32.4 and -26.4 to +30 months in girls and boys.
The study found out that the mean differences between chronological age and skeletal age in months where males had a mean difference of (-1.24) with an over-age of 31.45 months and an under-age of -35.72 months as compared to the females who had mean difference of (0.99) with an over-age of 18.57 months and an under age of -24.57 months. Hackman and Black (2012) indicated that the differences between chronological age and skeletal age ranged from between an under-age of 37 months and an over-age of 31 months which was similar for both females and males. The results of males in our study correlate well with the results of males in Hackman et al. (2012) study where nearly same under-aging and over-aging was seen. In the study of Rijn et al. (2000) the differences ranged from -30 to +32.4 and -26.4 to +30 months in girls and boys .The compatibility in results is seen only amongst males with an over-age of 30 months in their study and with an over-age of 31.45 months in our study respectively.
It is noted that skeletal maturation is gender specific and different in males and females respectively (Marshall et al., 1969 and 1970). In the current study, gender impact on the difference between chronological and skeletal ages is observed. This study found out that there has been a general mixed pattern for both under-aging and over-aging in both genders. The over-aging range from 0.59 to 5.56 months from the age 1 to 8 years in females, showing that girls are overestimated in early and middle childhood groups. As per Marshall et al. (1969 and 1970) girls are skeletally 4-6 weeks more mature than boys at birth and this pattern can be seen during childhood and adolescence age group but in the current sample the pattern is seen for the childhood age group only. Also it can be due to the fact that girls reach the stages of skeletal maturation earlier in comparison to the male population (Mito et al., 2002). For males over-aging ranged from 1.54 to 3.63 months in age groups 14 to 16 years and 18 years. The pattern for males has been consistent for under-aging from 3 to 9 years and 11 and 12 years old. This pattern of underaging in males before puberty and overaging after puberty is seen in other studies conducted by Ontell et al. (1996), Koc et al. (2001), Büken et al. (2007), Nahid et al. (2010), Zafar et al. (2010) and Hackman et al. (2012). In both males and females19 years showed an under-aging and could be due to the end of the atlas series at this age group. In comparison, the Hackman et al. (2012) study showed a general mixed pattern of under-aging and over-aging. It was seen that for females over-aging occurred at 1, 3, 6, 7 and 9-16 years old with over-aging from 0.20 to 5.73 months. They also indicated that for males there is a tendency of over-aging from the age of 0 to 2 years, same seen in our study in ages 0 and 2 years old. The tendency of under-aging between 3 to 8 years and 10 and 12 years, and overaging between 14-16 years is seen in our study as well. The pattern of under-aging for males was also seen in the study conducted by Rikhasor et al. (1999) and Patil et al. (2011) from age groups 2 to 15 years and 4 to 15 years ranging from 0.3 to 1.1 years and more than 0.5 years. The reason stated was poor nutrition and ill health affecting the maturation of carpal bones.
In our study this general pattern of under-estimation and over-estimation could be the result of the change of population and geographical location different from the one on which Greulich and Pyle study was based and also according to Schmeling et al. (2006) economic progress and modernization in medicine have an impact on the ossification of hand and wrist resulting in high ossification rates. Today Irish children are provided with better nutrition, meals are organised, there are better physical and psychosocial environment. Children are not prone to emotional stress and there has been profound awareness among masses about health and diseases. The differences amongst girls and boys can be also be due to the effect of puberty and genetics on skeletal maturation.. Girls enter puberty before boys with ages 11 years vs 13 years (Tanner et al.,1975) and complete pubertal stages earlier in comparison to boys who complete the puberty stages later (onset of growth spurt occurs later and slow progression to completion) and continue to show advanced bone age even after the girls have achieved skeletal maturity. In addition genetics has influence on skeletal maturation and its predisposition can range from 41 to 71% (Tanner, 1989; Sinclair, 1978). According to Arpenter and Laster (1993), after puberty skeletal age advanced in both females and males while in current sample, only in case of males this finding is supported, however in females it is supported only by age groups 12 years.
When four age cohorts were taken for both males and females it showed that in males an under-age of 18 months and an over age of 9 months was seen in ages 0 to 5 years and in females similar group was under-aged by 5 months, which is small compared to other age groups. This smaller range of under and over-aging is also seen in study conducted by Hackman et al. (2012) who appeared to have an under-age of 15 months and an over-age of 14 months in same age group (0-5 years). Studies conducted by Loder et al. (1993), Ontell et al. (1996), Rikhasor et al. (1999) and Mora et al. (2001) also agreed to smaller difference between chronological age and skeletal age in young age groups. This smaller difference noted in these younger cohorts could be due to the small gap of 3 months given in taking x-rays under one year of age followed by a gap of 3 and 6 months until the age of 5 years. However a gap of 12 months was given thereafter which could be contributing to the larger differences seen in older age groups.
The difference between mean chronological and skeletal age is of the order of 1 month. For females there is a difference of 0.99 months (95% CI -0.09, 2.08) and for males the difference is -1.24 (95% CI -2.36,-0.12).Based on the data collected, the difference for males is statistically significant (p < 0.05) whereas for females no significance was found. This may be due to the increased power to detect differences in the male population due to a larger proportion of this cohort being male (213 vs 158). Thus we can conclude that whatever differences exist between these measures is small. (NB – chronological age is a continuous measure – it can take any value – whereas the skeletal age is to the nearest 3 months). Another possibility could be that significant difference is found in the residual age in age cohort 19 years ( due to minimum number subjects in this group) which could be contributing to the above results seen in males. This difference may also be attributed due to the hormonal changes occuring before, at and after puberty affecting the skeletal maturation but at different ages in males and females. Rotham et al. (1978), Poole et al. (1982) and Gardner et al. (1986) emphasized on the use of confidence interval rather than p value to assess the differences. As p value can be significant due to larger sample size and non significant due to small sample sizes but the impact of these results can be important to note clinically. The Confidence interval in our study is noted to be small in both males and females.
The reliability and the accuracy of the Greulich and Pyle atlas method is not 100% because it brings out the mixed patterns of the difference between the chronological and skeletal age among both genders. Marco et al. (2011) in their study where they assessed the applicability of the Greulich and Pyle method in the assessment of the age for the Italian sample in the legal practice found out that the method was not 100% reliable in determine the true age of the study participants. They indicated that the true ages of the subjects were either over-estimated or under-estimated and therefore posing a challenge to the legal practice. But then one should be aware of the fact that in order to prove 100 % efficacy of the method of age assessment ideal situation is required where there is no deviation of the individuals from the population upon which the method of assessing the skeletal age is based. Considering this point our study have proved the adequacy of the Greulich and Pyle technique by showing 98% of the variation in the chronological age being interpreted on the basis of skeletal age for both subjects (p < 0.05).
All the outliers were included in the study as it is true representation of the data. The reason for the few outliers may be due to the systematic error on assessors part for example a bone can be over-aged or under-aged than its actual value causing variations in the results. However it should be noted that it is random and could increase the variation when being considered on its own but balancing the error when taken in group. The variability in assessing the skeletal age is lower for the carpal bones as compared to other bones of the hand-wrist (Thompson et al., 1973; Roche et al., 1976) This could increase the changeability of the skeletal ages noticed for these bones. The other possible reason could be that at the time of presenting to Emergency Department with trauma there might have been an underlying pathology which was not diagnosed or was not apparent at that point of time. But never the less our data proves that the Irish population access to nutrition and health system is satisfactory and the skeletal maturation is in line with the Greulich and Pyle atlas.
INTEROBSERVER AND INTRAOBSERVER RELIABILITY
This study revealed the there is a strong correlation between the intra-observer and inter-observer estimations for both females and males with correlation coefficient value of 0.99. The result also indicates that there is a significant association between the intra-observer and inter-observer estimations on both genders (p < 0.05). There is a satisfactory level of agreement between both the observers i.e. intra-observer and inter-observer which is in line with other studies which applied the Greulich and Pyle method (Ontell et al., 1996; Van Rijn et al., 2001; Garamendi et al., 2005; Lynnerup et al., 2008; Zafar et al., 2010; Tisè et al., 2011).
The intra-observer and inter-observer results for both females and males have R2 value of 0.98 and 0.99 (p < 0.05) respectively. There is a decrease in the reliability between the estimations by 1% and thus it is important to note that the decrease in the R2 value might be due to the inexperience of the first observer in comparison to second observer. Also the R2 value for first set of age estimation for both females and males is 0.98 and second time estimation for both females and males is 0.99. This is supported by the results of Hackman et al. (2012), where R2 value improved from 0.93 and 0.94 to 0.97 and 0.96 for both females and males respectively. Our study and the study of Hackman et al. (2012) confirms that accuracy is increased for first observer with experience. As it is worth noticing that with experience the accuracy in assessing the skeletal age is improved it would be not wrong to emphasize on the fact that this method should not be used for medical or forensic purposes by someone who has no knowledge of this method unless supervised by an experience practioner.
The result of this study is supported by Roche et al. (1970) who indicated that the there was a slight increase in the intra-observer reliability as compared with the inter-observer reliability due to the experience and the practice of the observer. The reliability between the two estimations, intra-observer and inter-observer has been found to be due to the accuracy levels of the observers and the experience between the two observers as supported by other studies conducted by koski et al. (1961) and Groell et al. (1999).
There was no statistically significant difference in means between the intra-observer and inter-observer estimations for both male and female subjects as seen by the t-test results.
RESTRICTIONS OF THE STUDY
There are two weaknesses of the current research. First the small sample size especially the age groups 0, 3 to 5 and 13 to 19 years old among the females where they showed a small number of x- rays in the study while in males the age groups 0, 1, 13, 15 and 19 years old had a smaller number of x-rays. However the age groups six to 12 years had the highest number of sample size. Second the study population was restricted on one area and region and therefore the results of this study cannot represent the entire country and cannot be simply correlated to other geographical, socio-economic or ethnical groups.
FUTURE RESEARCH
The present study focussed on the age estimation of the study participants between the age of 0 or from birth until the age of 19 years. Although the positive results from this study are linked and supported by other studies involved in the estimation of the skeletal age using the chronological age, it is important to indicate that more studies should be conducted in line with taking into consideration equal sample size among all age groups. This is because the sample size in this study was not equal among the study participants.
Another area of future research is where the difference between the skeletal and chronological age are discussed but are supported by the socio-demographic factors, environmental factors, genetic factors and even the geographical factors. This will bring out the difference between study participants in various regions and also highlight important areas where the Greulich and Pyle atlas technique can be effectively applied.
It is also important to note that this study can be replicated to other regions and areas to determine if the same results will be found or there will be significant difference between the results of the present study and that of the future results.
The future results should also be able to make sure that they demarcate the areas where the x-rays of both the left hand and the right hand are taken so that comparisons of the estimations can also be done depending on the area where the x-ray was taken.
CONCLUSION
It is in conclusion that the study agrees to the use of the Greulich and Pyle atlas method for medical and forensic purposes. Researchers and assessors are therefore encouraged by the study to put the atlas to work, even the more. From the study, for instance, it has been evinced that the Greulich and Pyle atlas is effective in the estimation of ages among children given that all the considerations provided are adhered to.
Current study has not found any evidence against the applicability of the Greulich and Pyle atlas on the basis of changes in specific bony maturation patterns despite of variability in maturation rates. Therefore the results of this study support the use of Greulich and Pyle method in the age estimation among the children of our country as long as differences notified in the current study are taken in to consideration.
References
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