Anthropometric measurements in Canadian children: a scoping review.
Patton, Ian T. ; McPherson, Amy C.
The use of anthropometric measurements (comparative measurement of
the human body) is a well-established practice for many clinical
purposes including screening and health risk assessment. (1) This is
particularly useful in the paediatric population as these measurements
can be used to track growth rate and identify abnormal growth trends.
(2) The most commonly utilized of these measurements is Body Mass Index
(BMI) which is calculated using the height and weight of the individual
(kg/[m.sup.2]). (3) Both the Canadian Paediatric Society and the
Dietitians of Canada recommend the screening of BMI for children above
the age of 2. (2)
Canada is a diverse country with a variety of unique settings from
rural to urban to northern/Arctic. Health care is delivered at the
provincial and territorial level and each region is composed of unique
environments and populations; therefore it is important to have
representation from all regions when considering the health of the
nation. (4) In a recent report, Dr. Kellie Leitch acknowledged that
Canadian children and youth, while fortunate in many ways, are poorly
ranked among key indicators of health including obesity, when compared
to other developed countries. (4) Of the world's 21 wealthiest
countries, Canada ranks 12th in regards to child wellbeing. (5) More
recently an update on this report has placed Canada at 17th out of the
29 wealthiest countries in regards to child wellbeing and an alarming
27th in regards to health. (6) These poor rankings highlight the need
for Canadians to focus on child health and closely monitor our progress.
This begins by understanding the forms of measurement being used and
investigating methods to improve the screening and monitoring of child
health. Canadian children have a unique health profile and need to be
investigated independently from other children. (4) In the case of
weight-based concerns such as obesity, there are clear regional
differences across the country. (7-9)
The current trend of increasing BMI in children has generated a
great deal of attention due to its links with a variety of negative
health outcomes, such as cardiovascular disease and diabetes. (10,11)
Some provinces have developed strategies and mandates to address the
obesity problem; Ontario, for example, recently released a report
focusing on childhood obesity in the province, and included a variety of
recommendations to reach their ambitious target of reducing childhood
obesity by 20% in 5 years. (12) Therefore, with the growing attention
placed on childhood obesity, (13) anthropometrics, specifically BMI,
have become of great importance. (14,15) Canadian guidelines recommend
using the World Health Organization's growth charts as reference,
(2) which consider a child between 2 and 19 years of age who has a BMI
below 3rd percentile as underweight, a BMI below the 85th percentile as
normal weight, 85th-97th centile as overweight or > 97th centile as
obese. (16) These categories are used as a proxy for body fat which is
associated with varying health risks. (17,18) It is however important to
note that there are "healthy" children with BMI calculations
that identify them as unhealthy. (3,14,19,20) For example, varying
growth rates could lead to a child having a higher weight than their
peers but not an advanced amount of body fat which would warrant the
"unhealthy" label. (3,14) Likewise, there are individuals
whose BMI falls in the "healthy" range, who are at greater
risk for poor health outcomes due to factors such as poor nutrition,
sedentary behaviours and negative environmental influences. A heavy
focus on BMI can cause some individuals to be misclassified and thus
fail to be provided with the most appropriate advice. (21,22) BMI
classification serves to exaggerate between-group differences (normal
weight vs. overweight) and severely downplays the potential individual
differences within each group, making the assumption that all within the
group are homogenous. (22) The current practice of using
population-level data (BMI classification) in a clinical setting is
problematic as it oversimplifies the screening and care of the patient.
(22) This highlights the need to explore the options of supplementing
BMI data in detail. British children have their BMI measured through the
Child Measurement Programme, despite the warning from the National
Screening Committee. The committee suggested that the BMI measurement
not go ahead in children as they were not convinced that they were doing
more good than harm. (23) Nicholls points out that BMI classification in
isolation is simplistic and does not represent well the health of a
child. (22) He also states that a heavy focus on BMI classification can
promote the unintended harm of increased weight bias and discrimination,
which is of great concern to children. (22)
Regular anthropometric tracking in children is a valuable tool in
prevention, diagnosis and treatment of many conditions, including excess
fat mass. (21) A rich set of growth trend data provides health care
practitioners with valuable information about abnormal rates and sudden
fluctuations in growth which could highlight items for a health care
practitioner to explore in more detail. (14) However, caution should be
taken to not exaggerate the importance on any singular measurement, as
there are always limitations. (24) The value of BMI when used at an
individual level or in a special population (children with disabilities,
for example) has been questioned as it provides minimal information
about the health of that individual patient and fails to identify causes
of weight-based concerns such as diabetes or cardiovascular disease.
(3,21-23) For example, one study suggested that the use of BMI in
children could underestimate the importance and effect of socio-economic
factors such as parental education and poverty. (25) BMI itself is
designed as a means of simplification of data for the purpose of
studying population trends. As such, the misuse of BMI creates the risk
of oversimplifying the very complex issue of obesity. (22) Obesity is a
health condition that has many interacting contributors, and the full
complexity of the issue is not yet known. Current systems of
anthropometric measurement and classification do not provide an accurate
reflection of the severity of weight-based health. (3) Some even suggest
that a heavy focus on BMI can be detrimental to the patient through
potential adoption of risky weight loss methods, eating disorders and
weight bias. (19,20,22,26)
A new screening tool for children could potentially utilize a
combination of anthropometric measurements as well as assessments of
health behaviours and history in order to provide the health care
practitioner with a well-rounded and individualized picture of the
health needs of an individual child. While BMI is certainly the most
popular and most reported form of anthropometric measurement, there is a
variety of different measurements that can potentially be utilized in
conjunction with or separately from BMI. The development of such a tool
begins with the identification of the current forms of anthropometric
measurement available and the gaps in the literature surrounding them.
The results of this review will inform future research into the
development of a novel health screening tool for Canadian children, The
Healthy Body Scorecard.
Research question
The current study utilizes scoping review methodology, as scoping
reviews are designed to examine the extent and range of research
available in an identified research area, and to identify gaps in the
literature. (27,28) Although they have been criticized for not being as
rigorous as systematic reviews, (29) they are, in fact, a distinct
entity and can be conducted with differing levels of detail, ranging
from a brief count of the number of articles on a topic to a more
comprehensive mapping of the available literature and findings. (30,31)
The scoping review approach utilized in the current study was one that
identified current research, highlighted methods of anthropometric
measurement used for Canadian children, and identified gaps in the
literature. The research questions were: 1) What anthropometric measures
are being utilized with Canadian children and how prevalent are these
measures in published research? And, 2) What gaps in the literature
exist?
METHODOLOGY
Search strategies
Infants under the age of 2 years are involved in a rapid and
irregular state of growth, making it very difficult to accurately
categorize them in standardized growth charts. (2,12,21) Growth
measurement of Canadian children between the ages of 2 and 18 years has
been highlighted as an important part of primary health care. (2)
Therefore, studies in this review included Canadian children between 2
and 18 years of age.
The online databases Medline and PubMed and CINAHL were used to
search English-language journal articles from the last decade
(2002-2012) in order to focus on current literature. A set of keywords
and subject headings were used for the initial search, including:
Anthropometry, anthropometric measurement, body height, weight, body
mass index, growth and growth curve, combined with the terms
children/child and Canada. The reference lists of identified articles
were also screened for additional resources. A secondary search was
conducted once key topic areas were identified, including: Waist
circumference, leg-length-to-height ratio, waist-to-hip ratio,
waist-to-height ratio, skinfold thickness, girth, body composition,
obesity, and adipose tissue, again all combined with the terms
children/child and Canada. Only studies that utilized objectively
measured anthropometric methodologies were included.
RESULTS
The initial search identified 605 items to be screened. Review of
abstracts reduced the number of articles to be retrieved to 87.
Application of the inclusion and exclusion criteria to full-text
articles resulted in 50 studies being included in the current review
(Table 1). Studies ranged from nationally representative data to small
subpopulation studies and included a variety of age ranges that fell
within this review's 2-18 year old threshold.
Anthropometric measurement
The studies used a variety of different measurements (Table 1).
Body mass index calculation was by far the most collected form of
anthropometric measurement, with 88% (n = 44) of studies utilizing the
method. Over half of the studies (n = 28) examined BMI alone. Waist
circumference (WC) was the next most popular form of measurement, with
20% (n = 10) of studies collecting WC measurements. Blood pressure and
body fat percentage (measured using bio-electric impedance or sum of 5
skinfolds) were utilized by 10% (n = 4) and 12% (n = 5) of studies,
respectively. Another 2 studies observed waist-to-height ratio. (32,33)
Waist-to-hip ratio and skinfold calipers (sum of 5 skinfolds) had a
single study represent the measurement methods. (32,34) Another single
study utilized leg length and sitting height measurements for the
purpose of assessing physical maturity. (35)
Population characteristics
While 6 studies reported measurement of nationally representative
data from large-scale studies, the remaining inclusions in this review
were spread across varying subpopulations. For example, 8 (16%) of the
included studies were targeted specifically at Inuit or First Nations
(FN) populations. Of the 50 studies included in this review, 4 (8%)
directly targeted Caucasian-only populations. Many of the studies
focused on small and very specific subpopulations, such as congenital
heart disease patients, (36) or hockey players. (37) One of the larger
studies included in the review (which had a sample of 6,392)
specifically targeted the first generation (child and parents born
outside of Canada) immigrant and second generation (child born inside
Canada with at least one parent born outside Canada) immigrant
population. (38)
Sample size
The 50 included studies in the current review represent a total
sample size of 67,051 Canadian children. The 6 studies that are from
nationally representative samples account for 47% of the total sample
population for the review. The single study that addressed the immigrant
population represented 9.5% of the overall sample size. The 9 studies
focused on FN populations that were incorporated into the review
represented 2.5% of the total sample size.
Each of the identified forms of anthropometric measurement
represented different percentages of the total sample population for the
review (Table 2). For example, BMI measurement was collected in 94% of
the sample population. The second most popular form of measurement was
waist circumference, which was reported for 13% of the sample.
Waist-to-height ratio was measured in 3% of the sample. The remaining
forms of measurement reported each represented 2% or less of the total
sample population of the review.
DISCUSSION
The research using anthropometric measurement in Canadian children
is heavily skewed towards the collection of BMI measurements. This is
not surprising due to the simplicity of the measurement and analysis of
BMI: of all possible anthropometric measurements, the height and weight
collection used in the BMI calculation is likely to be the least
invasive of all and requires the least amount of expertise to acquire
accurate results. (3) Furthermore, it should be noted that BMI
measurement is the recommended clinical measurement for this age group.
(2) This is evident in the research as 28 of the 50 studies solely
examined BMI. However, simplicity does not always equate to the best
choice, as BMI does have limitations. (3,15,21) While BMI has been shown
to be useful in identifying population trends and disease risk, the use
of height and weight measurements on the individual level do not provide
sufficient information on which to base medical screening alone. (3,15)
For example, BMI fails to account for many important variables, such as
lean tissue mass, fat distribution, and health behaviours, that are
linked to poor health outcomes. (3,14,19,20)
The inclusion of a wide variety of anthropometric measurements
aside from BMI shows that there are other simple and useful data
collection methods that can be utilized in conjunction with BMI to
provide a rich data set. Waist circumference has gained popularity
across all populations as it provides insight into distribution of
adipose tissue in the body. (39-41) This can be particularly useful in
the Aboriginal population as they have been shown to be affected
differently than other Canadians by adiposity. (34,42,43) This review,
however, clearly identifies a gap in research using measurements such as
waist circumference, hip-to-waist ratio and leg-length-to-height ratio.
These types of measurements provide information with regard to mass
distribution and growth trends that are potentially useful for health
screening and should be explored in more detail. Therefore, future
studies should be designed to collect other appropriate and simple
measurements, which will result in rich data sets. Growth data that go
beyond height and weight could allow health care practitioners and
researchers to identify abnormal growth patterns as well as provide an
opportunity to explore relationships between measures and health
outcomes in greater detail. This may enable greater accuracy in
identifying health issues and unhealthy behaviours, as well as highlight
the issues that need greater attention in regard to children's
growth and development.
While a good portion of this review is based on nationally
representative data (50% of the entire sample) from large-scale studies,
there are still some important gaps in the review studies in terms of
population representation. Particularly, FN populations are
underrepresented at only 2.5% of the sample. First Nations represent a
unique and important population with health trends that differ
considerably from the national norm. (44-48) Statistics also show FN
populations to have higher rates of obesity and related co-morbidities
compared to the rest of the country, which could be for a number of
reasons. (44,46) The use of waist circumference measurement in this
population may provide insight into the fat mass distribution and the
severity of weight-based health issues. Interestingly, 4 of the 9
studies addressing the First Nations population included the measurement
of waist circumference. This review, however, failed to identify any FN
research that utilized other valuable forms of measurement, such as
leg-length-to-height ratio and hip-to-waist ratio. It would therefore be
beneficial for future research in this population to address the gaps
identified in this review for the purpose of better understanding the
usefulness of these measurements in this population.
Geographically, the review identified some key characteristics. The
majority of the studies took place in Ontario and Quebec. This is likely
due to the large population base as well as the number of large research
centres and universities in these two provinces. While all regions of
the country are accounted for by the 6 nationally representative
studies, the remaining studies included in the review identified some
areas that lack attention in the literature. Specifically, Manitoba
populations had not been represented individually outside of the
nationally representative data. Furthermore, other regions such as
British Columbia and the Maritimes are under-represented. It would be
valuable to be able to compare all of the various forms of
anthropometric measurement across the different regions to nationally
representative data, particularly when developing cross-Canada
guidelines.
Limitations
For feasibility reasons, all of the searches and study inclusion
decisions were performed by a single researcher. Systematic review
methodology requires study inclusion decisions to be conducted by two
separate investigators, to ensure that only evidence meeting strict
criteria is considered. (49) However, scoping reviews take a more
inclusive approach, aiming to include all information that has relevance
to a specific topic. (23,24) Therefore, single reviewer studies have
been successfully completed in scoping reviews where the inclusion and
exclusion criteria are not complex. (50)
Only published studies were included in this review, a noted
limitation of many types of literature reviews. (23)
CONCLUSION
The purpose of this review was to identify the forms of
anthropometric measurement currently in use for the Canadian child and
youth population. The variety of measurements identified in this review
reflect the range of measures available for studying the growth trends
of Canadian children. The secondary purpose of this review was to
identify any gaps in the literature with regard to the measurements,
geographic location and sample population. All of the identified forms
of anthropometric measurement aside from BMI would benefit from greater
attention in future research. In order to strengthen the findings of
future research, researchers should take the opportunity to collect
other simple anthropometric measurements such as waist circumference,
hip circumference and leg length. This would allow for a greater
understanding of the reliability of these methods as well as growth
trends in children and the link to health outcomes. While a large
portion of the sample was nationally representative, efforts should be
made to utilize the anthropometric measurements in all regions in order
to allow for regional comparisons. Furthermore, specific attention needs
to be focused on collecting anthropometric data from First Nations
children, as they were under-represented in the studies included in this
review.
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Received: April 30, 2013
Accepted: September 17, 2013
Ian T. Patton, PhD, (1) Amy C. McPherson, PhD CPsychol, AFBPsS (2)
Author Affiliations
(1.) Dalla Lana School of Public Health, University of Toronto,
Toronto, ON
(2.) Holland Bloorview Kids Rehabilitation Hospital, Bloorview
Research Institute, Toronto, ON
Correspondence: Ian Patton, 114 Martin Rd., Bowmanville, ON L1C
3N4, Tel: 289927-5576, E-mail: ian.patton@utoronto.ca
Acknowledgements: The authors acknowledge the funding support for
this work through Mitacs and The Sandbox Project.
Conflict of Interest: None to declare.
Table 1. Review Articles
Author Year Measures Age Range
(years)
Hayek et al. (45) 2012 Height, weight, BMI 2-5
Melka et al. (51) 2012 Height, weight, BMI, 12-18
blood pressure
Shields et al. (52) 2011 Height, weight, BMI 6-11
Twells & Newhook (53) 2011 Height, weight, BMI 0-5
Maximova et al. (38) 2011 Height, weight, BMI 9-12
Woodruff et al. (54) 2010 Height, weight, BMI 10-12
Khalil et al. (42) 2010 Height, weight, BMI,
waist circumference, 9-18
body fat % (BI)
Herman et al. (55) 2009 Height, weight, BMI 7-18
Downs et al. (56) 2009 Height, weight, BMI 8-12
Dubois et al. (57) 2007 Height, weight, BMI 3-5
Spence et al. (58) 2008 Height, weight, BMI 3-5
Dubois et al. (59) 2007 Height, weight, 0-5
weight for height
Sherar et al. (37) 2007 Height, weight, 14-15
sitting height
Galloway (60) 2006 Height, weight, BMI 7-14
Shields (61) 2005 Height, weight, BMI 2-17
Thompson et al. (62) 2005 Height, weight, BMI 7-17
Nakano et al. (46) 2005 Height, weight, BMI 10-12
Stefan et al. (36) 2005 Height, weight, BMI 2-14
Hay et al. (63) 2004 Body fat % (BI) 8-14
Smith et al. (64) 2002 Height, weight, BMI 4-14
Hajna et al. (32) 2012 BMI, waist-height 9-13
ratio, waist-hip
ratio, waist girth,
hip girth
Danyliw et al. (65) 2011 Height, weight, BMI 10-13
Kakinami et al. (66) 2012 BMI, blood pressure 9-16
Chaput et al. (33) 2012 BMI, waist to height 5-10
ratio
Tomlin et al. (34) 2012 BMI, waist 9-13
circumference,
sum-of-5 skinfolds
Pausova et al. (67) 2012 Body fat% (BI), 12-18
blood pressure
Liu et al. (68) 2012 BMI, 9-14
leg-length-to-height
ratio
Panagiotopoulos 2011 BMI, waist 0-18
et al. (69) circumference
Bilinski et al. (70) 2011 Height, weight, BMI 8-13
Chaput et al. (71) 2011 BMI, waist 5-10
circumference
Larouche et al. (72) 2011 BMI, waist 8-12
circumference
Spence et al. (73) 2012 Height, weight, BMI 4-5
Johnston et al. (74) 2011 Height, weight, BMI 9-11
Katzmarzyk et al. (75) 2007 Height, weight, BMI 6-18
Katzmarzyk (76) 2004 Waist circumference 11-18
Downs et al. (56) 2008 Height, weight, BMI, 9-12
waist circumference
Syme et al. (77) 2009 Height, weight, BMI, 12-18
waist circumference,
body fat % (BI)
Moffat et al. (78) 2005 Height, weight, BMI 6-10
Anderson et al. (31) 2010 Height, weight, BMI, 8-16
waist circumference
Paradis et al. (79) 2010 Height, weight, BMI, 6-19
blood pressure
Mirwald et al. (35) 2002 Height, weight, BMI, 8-16
sitting height, leg
length, leg-length-
to-sitting-height-
ratio
Banach et al. (80) 2007 Height, weight, BMI 9 yrs
Verret et al. (81) 2010 Height, weight, BMI 7-12
Stock et al. (82) 2007 Height, weight, BMI, 4-13
heart rate
St. John et al. (83) 2008 Height, weight, BMI 7-17
Haque et al. (84) 2006 Height, weight, BMI 6-17
He et al. (85) 2006 Height, weight, BMI 6-13
Larouche et al. (86) 2011 Height, weight, BMI, 8-12
waist circumference
Pabayo et al. (87) 2010 Height, weight, BMI 4-8
(Z-score)
He et al. (88) 2004 Height, weight, BMI 2-6
Author Sample Location Special
Size Population
Hayek et al. (45) 296 Arctic First Nations
communities
Melka et al. (51) 598 Quebec French Canadian
Shields et al. (52) 854 Canada Nationally
representative
Twells & Newhook (53) 1026 Newfoundland
Maximova et al. (38) 6392 Quebec Immigrants
Woodruff et al. (54) 405 Ontario
Khalil et al. (42)
125 Quebec First Nations
Herman et al. (55) 374 Canada
Downs et al. (56) 201 Quebec First Nations
Dubois et al. (57) 1549 Quebec
Spence et al. (58) 501 Alberta
Dubois et al. (59) 354 Quebec
Sherar et al. (37) 281 Saskatchewan Hockey players
Galloway (60) 504 Ontario Rural
Shields (61) 8661 Canada Nationally
representative
Thompson et al. (62) 1653 Nova Scotia
Nakano et al. (46) 216 Canadian First Nations
Arctic/Yukon
Stefan et al. (36) 110 Ontario Congenital
heart disease
patients
Hay et al. (63) 206 Ontario Caucasian
Smith et al. (64) 101 Ontario First Nations
Hajna et al. (32) 1570 Ontario
Danyliw et al. (65) 10,038 Canada Nationally
representative
Kakinami et al. (66) 2466 Quebec
Chaput et al. (33) 550 Quebec Caucasian,
obese parent
Tomlin et al. (34) 148 British First Nations
Columbia
Pausova et al. (67) 499 Quebec Caucasian
Liu et al. (68) 1166 Ontario
Panagiotopoulos 231 British
et al. (69) Columbia
Bilinski et al. (70) 99 Saskatchewan Rural
Chaput et al. (71) 550 Quebec
Larouche et al. (72) 315 Ontario
Spence et al. (73) 1730 Alberta
Johnston et al. (74) 305 Alberta
Katzmarzyk et al. (75) 7081 Canada Nationally
representative
Katzmarzyk (76) 3064 Canada Nationally
representative
Downs et al. (56) 178 Quebec First Nations
Syme et al. (77) 425 Quebec
Moffat et al. (78) 261 Ontario 3 varying
communities
Anderson et al. (31) 416 Saskatchewan First Nations
Paradis et al. (79) 2079 Canada Nationally
representative
Mirwald et al. (35) 152 Saskatchewan
Banach et al. (80) 1497 Ontario
Verret et al. (81) 70 Quebec Boys, Attention
deficit and
Stock et al. (82) 232 British hyperactivity
Columbia disorder
St. John et al. (83) 2296 Nova Scotia
Haque et al. (84) 801 Ontario Northern Ontario
He et al. (85) 1570 Ontario
Larouche et al. (86) 315 Ontario
Pabayo et al. (87) 1170 Quebec
He et al. (88) 1370 Ontario
Table 2. Percent Representation of Measurement Methods
(N = 67,051)
Measurement N Percentage of
sample population
BMI 63,282 94%
Waist circumference 8592 13%
Body fat percentage 756 1%
Weight for height 354 0.50%
Sitting height 433 0.60%
Waist-to-height ratio 2120 3%
Hip-to-waist ratio 1570 2%
Hip girth 1570 2%
Skinfold 148 0.20%
Leg-length-to-height ratio 1166 2%
Leg-length-to-sitting-height ratio 152 0.20%
