Are gluten free foods healthier than non-gluten free foods? An evaluation of supermarket products in Australia

Abstract

Despite tremendous growth in the consumption of gluten-free (GF) foods, there is a lack of evaluation of their nutritional profile and how they compare with non-GF foods. The present study evaluated the nutritional quality of GF and non-GF foods in core food groups, and a wide range of discretionary products in Australian supermarkets. Nutritional information on the Nutrition Information Panel was systematically obtained from all packaged foods at four large supermarkets in Sydney, Australia in 2013. Food products were classified as GF if a GF declaration appeared anywhere on the product packaging, or non-GF if they contained gluten, wheat, rye, triticale, barley, oats or spelt. The primary outcome was the ‘Health Star Rating’ (HSR: lowest score 0·5; optimal score 5), a nutrient profiling scheme endorsed by the Australian Government. Differences in the content of individual nutrients were explored in secondary analyses. A total of 3213 food products across ten food categories were included. On average, GF plain dry pasta scored nearly 0·5 stars less (
P
< 0·001) compared with non-GF products; however, there were no significant differences in the mean HSR for breads or ready-to-eat breakfast cereals (
P
≥ 0·42 for both). Relative to non-GF foods, GF products had consistently lower average protein content across all the three core food groups, in particular for pasta and breads (52 and 32 % less,
P
< 0·001 for both). A substantial proportion of foods in discretionary categories carried GF labels (e.g. 87 % of processed meats), and the average HSR of GF discretionary foods were not systematically superior to those of non-GF products. The consumption of GF products is unlikely to confer health benefits, unless there is clear evidence of gluten intolerance.

Full text

Are gluten-free foods healthier than non-gluten-free foods? An evaluation of
supermarket products in Australia
Jason H. Y. Wu
1
*, Bruce Neal
1,2,3
, Helen Trevena
1
, Michelle Crino
1
, Wendy Stuart-Smith
4
,
Kim Faulkner-Hogg
5
, Jimmy Chun Yu Louie
4,6
and Elizabeth Dunford
1
1
The George Institute for Global Health, Sydney Medical School, University of Sydney, Level 10, King George V Building,
83-117 Missenden Road, Camperdown, Sydney, NSW 2050, Australia
2
The School of Public Health, Faculty of Medicine, Epidemiology and Biostatistics, Imperial College of Science,
Technology and Medicine, Praed Street, Norfolk Place, London W2 1PG, UK
3
The Royal Prince Alfred Hospital, Camperdown, NSW 2050, Australia
4
Discipline of Nutrition and Metabolism, School of Molecular Bioscience, University of Sydney, New South Wales, Australia
5
Allergy Unit, Royal Prince Alfred Hospital, Camperdown and Food4me Private Practice, New South Wales, Australia
6
School of Molecular Bioscience and Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, University of
Sydney, New South Wales, Australia
(Submitted 11 January 2015 – Final revision received 18 April 2015 – Accepted 13 May 2015)
Abstract
Despite tremendous growth in the consumption of gluten-free (GF) foods, there is a lack of evaluation of their nutritional profile and how
they compare with non-GF foods. The present study evaluated the nutritional quality of GF and non-GF foods in core food groups, and a
wide range of discretionary products in Australian supermarkets. Nutritional information on the Nutrition Information Panel was system-
atically obtained from all packaged foods at four large supermarkets in Sydney, Australia in 2013. Food products were classified as GF if a
GF declaration appeared anywhere on the product packaging, or non-GF if they contained gluten, wheat, rye, triticale, barley, oats or spelt.
The primary outcome was the ‘Health Star Rating’ (HSR: lowest score 0·5; optimal score 5), a nutrient profiling scheme endorsed by the
Australian Government. Differences in the content of individual nutrients were explored in secondary analyses. A total of 3213 food
products across ten food categories were included. On average, GF plain dry pasta scored nearly 0·5 stars less (P,0·001) compared with
non-GF products; however, there were no significant differences in the mean HSR for breads or ready-to-eat breakfast cereals (P$0·42 for
both). Relative to non-GF foods, GF products had consistently lower average protein content across all the three core food groups, in particular
for pasta and breads (52 and 32 % less, P,0·001 for both). A substantial proportion of foods in discretionary categories carried GF labels
(e.g. 87 % of processed meats), and the average HSR of GF discretionary foods were not systematically superior to those of non-GF products.
The consumption of GF products is unlikely to confer health benefits, unless there is clear evidence of gluten intolerance.
Key words: Gluten: Nutrient profiling: Food labels
Health effects of gluten have received increasing attention
both in medical research and popular media, and remain
highly controversial
(1 – 3)
. People with diagnosed coeliac
disease require a lifelong strictly gluten-free (GF) diet
(4)
.In
addition to coeliac disease patients, it has been hypothesised
that a substantial proportion of the population may be
gluten intolerant (non-coeliac gluten sensitivity), and could
benefit from reducing gluten in their diet
(5)
. However, clinical
evidence for the existence of such conditions and other pur-
ported adverse health effects of gluten remain inconsistent
(6)
.
Nevertheless, there is growing popular perception that GF
foods are healthier, and in recent years, there has been a
dramatic increase in demand and consumption of GF foods
in many Western countries. For example, nearly one-third of
adults in the USA have expressed interest in avoiding or cut-
ting down on gluten in their diets, and sales of GF foods
reached approximately $10 billion in 2013, with most of the
increased demand for GF foods from those without clinically
diagnosed coeliac disease
(3,7)
. A rapid growth in the sale of
GF foods has also been observed in the UK
(8)
.
Despite the tremendous rise in popularity and consumption
of GF foods, there is a lack of evaluation of their nutritional
profile and how they compare with non-GF foods. Such an
assessment is important for several reasons. Gluten-containing
*Corresponding author: J. H. Y. Wu, fax þ61 2 9993 4501, email jwu1@georgeinstitute.org.au
Abbreviations: GF, gluten-free; HSR, Health Star Rating; NIP, Nutrition Information Panel; RTE, ready-to-eat.
British Journal of Nutrition, page 1 of 7 doi:10.1017/S0007114515002056
qThe Authors 2015
British Journal of Nutrition

grains such as wheat, rye and barley are important sources of
nutrients. Staple foods that traditionally contain these grains
are core to the diet of many countries, and consumed by
large proportions of the population
(9)
. There are concerns
that removal or substitution of these grains from GF products
with other ingredients could adversely affect nutrient intake in
those consuming a GF diet
(10,11)
. Furthermore, consumers may
perceive GF products as healthier than non-GF foods, and
food companies may market them as such and charge a
premium price
(12,13)
. This may occur even when the foods
concerned are energy-rich, nutrient-poor discretionary
products such as cakes and biscuits
(12 – 14)
. For most food
categories, it is unclear whether GF products contain
comparable, higher or lower levels of sugar, salt and saturated
fat relative to non-GF products.
To address these gaps in knowledge, we conducted an
evaluation of the nutritional quality of GF foods in core food
groups and a wide range of discretionary product categories
available in Australian supermarkets in 2013, and compared
their nutritional profile with non-GF products.
Methods
Design and data
Nutritional information for each food product was obtained
from the Nutrition Information Panel (NIP), and data were col-
lected using previously described methods
(15,16)
. Briefly,
between July and December 2013, NIP data were systemati-
cally obtained from all packaged food products available for
sale at four large supermarket stores (Coles, Woolworths,
ALDI and IGA) in Sydney, New South Wales, Australia.
Where exactly the same product was for sale in more than
one supermarket, it was recorded only once. Where the
same product was presented in different pack sizes, only
one entry was recorded. For each food product, the manufac-
turer, brand and product name, nutrient content per 100g as
appeared on the NIP, and gluten status were recorded (see
below). Data were entered into The George Institute’s
branded food composition database according to standardised
procedures
(17)
. Likewise, data were verified according to a
defined quality assurance protocol and workflow, which
includes screening for outliers and missing values, checking
data entry accuracy by two study personnel independently,
and resolving queries and discrepancies by review of the orig-
inal NIP data, consultation between the research personnel,
review of the manufacturer’s website, or follow-up with the
manufacturer directly.
Product categories included
The staple food categories that we included were those typi-
cally containing gluten and comprised breads, ready-to-eat
(RTE) breakfast cereals and dry plain pasta. These are import-
ant contributors to energy intake in typical Western diets
including Australia, and are part of the core foods
recommended by the Australian Dietary Guidelines
(9,18)
. Like-
wise, we evaluated multiple categories of discretionary foods
including those that utilise large quantities of gluten-contain-
ing grains (cereal bars, cake mixes/cakes and sweet biscuits)
as well as others that typically include smaller quantities and
for which GF alternatives are often available (ice cream,
corn and potato chips, cured meats, sausages and hot dogs,
and sugar-based confectioneries). Food categories were also
selected if they contained at least twenty GF and twenty
non-GF products to allow meaningful comparison and statisti-
cal inference between the nutritional composition of GF and
non-GF foods.
Determination of gluten status
A product was classified as GF if a GF declaration appeared on
the NIP, or anywhere else on the product packaging. A pro-
duct was coded as non-GF if it contained any of the following
ingredients: gluten; wheat; rye; triticale; barley; oats; or spelt.
Glucose syrup derived from wheat was considered to be a GF
ingredient. We excluded from analyses the food products that
did not carry a GF label, but were determined to be likely GF
based on inspection of the ingredient list.
Outcomes
The primary outcome used to compare the nutritional quality
of GF v. non-GF products was the ‘Health Star Rating’ (HSR)
system, a voluntary nutrient profiling scheme endorsed by
the Australian Government with the aim of helping consumers
to choose healthier foods
(19)
. The HSR system rates a product
between 0·5 and 5 stars (increasing in 1/2-star increments,
with more stars indicating higher nutritional quality). The
number of stars for a food product is calculated based on an
algorithm that takes into account the quantity of specific
food components and the estimated overall healthiness of
the product. Details of the HSR algorithm are provided in
the Supplementary material (available online). In secondary
analyses, we also explored differences in the content of
energy (kJ), saturated fat, total sugars, Na, protein and dietary
fibre per 100 g between GF and non-GF products. Australian
law does not require mandatory labelling of fibre content as
part of the NIP, so we restricted the analysis of fibre to only
those food products with available information.
Statistical analyses
Data are presented as means and standard deviations. Sum-
mary data for energy and nutrients were presented per 100 g
of each food. Differences in mean HSR and nutrient content
between GF and non-GF products were assessed by linear
regression analysis. A two-sided Pvalue of ,0·05 was
considered as statistically significant. Statistical analyses were
conducted using Stata 13.1 (Stata Corporation).
Results
A total of 3213 food products across ten food categories were
included in the analyses. The top three manufacturers of GF
and non-GF products and the number of products in each
J. H. Y. Wu et al.2
British Journal of Nutrition

category are provided in online Supplementary Table S1. The
number of products ranged from 154 for corn and potato
chip products to 550 for sweet biscuits. In almost all of
the food categories, the majority of products were non-GF
(percentage of GF products 10–36 %), with the only exception
being cured meats, sausages and hot dogs for which most
(87 %) of the products were labelled as ‘GF’. For non-GF pro-
ducts, the top three manufacturers were mainly large inter-
national food manufacturers (e.g. Kellogg and Mondelez) or
major Australian supermarket retailers selling their own
brand (e.g. Woolworths and Coles). Conversely, GF products
came from a more diverse group of manufacturers, and the
leading companies were mostly different across product
categories.
The mean HSR and nutrient content of GF v. non-GF
products in the core food groups are summarised in Table 1.
On average, GF plain dry pasta scored nearly 0·5 stars less
(95 % CI 20·38, 0·57, P,0·001) compared with non-GF pro-
ducts; however, there were no significant differences in the
mean HSR for breads or RTE breakfast cereals (P$0·42 for
both). Relative to non-GF foods, GF products had consistently
lower average protein content across all the three core food
groups, in particular for plain dry pasta and breads (52 and
32 % less, P,0·001 for both). The contents of total energy,
Na, saturated fat and total sugars were similar between GF
and non-GF core foods. While GF breads had significantly
higher mean dietary fibre content (2·2 g/100 g, P,0·001), the
opposite was true for RTE breakfast cereals (Fig. 1).
HSR were similar for four out of the seven discretionary
food groups assessed, including cereal bars, cake mixes/
cakes, sweet biscuits, and cured meats, sausages and hot
dogs (Table 2). Consistent with this observation, there were
no clear patterns of differences in the content of individual
nutrients between GF and non-GF products in these food cat-
egories (Table 2 and see online Supplementary Fig. S1). These
foods were generally high in Na, saturated fat and sugar con-
tent and often exhibited reciprocal changes in the levels of
these nutrients. For example, while GF cake mixes and
cakes had lower saturated fat levels compared with non-GF
products (by 2·1 g/100 g, P¼0·001), they had higher total
sugar levels (by 8·1 g/100 g, P,0·001), resulting in similar
mean total energy (1469 v. 1501 kJ/100 g). In the remaining
three discretionary food categories examined (ice cream,
corn and potato chips, and sugar-based confectioneries), GF
products had significantly higher HSR (mean difference
0·2–0·8 stars, P#0·01 for both), which were largely driven
by lower mean levels of saturated fat (ice cream and corn
and potato chips) or total sugars (ice cream and sugar-based
confectioneries) and therefore energy density (all the three
product categories).
Discussion
Based on a large cross-sectional survey, our data show that GF
products in the core food categories had overall similar nutri-
tional profiles compared with non-GF products, with the
notable exception being that GF products had lower average
protein levels. Furthermore, while GF products had slightly
Table 1. Nutritional profile of gluten-free (GF) v. non-GF core food categories
(Mean values and standard deviations)
Nutrient content (per 100 g)
Health Star
Rating (stars) Energy (kJ) Na (mg)
Saturated fat
(g) Protein (g) Total sugars (g)
Product types nPercentage of all products Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD
Plain dry pasta 303
GF 46 15·2 3·9 0·3 1362 382 33·8 46·2 0·4 0·5 6·1 2·3 1·4 1·4
Non-GF 257 84·8 4·4 0·3 1508 57 25·1 48·6 0·5 0·3 12·6 1·4 2·0 1·5
Difference in mean* 20·5 2146 8·7 20·1 26·5 20·6
P†,0·001 ,0·001 0·28 0·16 ,0·001 0·02
Breads 537
GF 54 10·1 3·5 0·7 1096 355 524 435 1·1 1·1 6·2 4·8 3·6 3·1
Non-GF 483 89·9 3·5 0·8 1159 248 485 219 1·5 2·2 9·1 2·1 3·7 4·8
Difference in mean* 0 263 39 20·4 22·9 20·1
P† 0·46 0·10 0·27 0·12 ,0·001 0·88
RTE breakfast cereals 339
GF 73 21·5 3·8 0·7 1612 213 154 175 1·7 1·8 9·0 3·0 15·2 8·5
Non-GF 266 78·5 3·9 0·8 1618 145 165 174 1·6 1·4 10·4 3·1 17·7 9·3
Difference in mean* 20·1 26211 0·1 21·4 22·5
P†0·42 0·78 0·63 0·56 0·001 0·04
RTE, ready-to-eat.
* Calculated as follows: mean GF group2mean non-GF group.
† Differences in mean nutrient content between GF and non-GF products were assessed by linear regression analysis.
Gluten-free v. non-gluten-free foods 3
British Journal of Nutrition

better average nutritional profiles compared with their non-GF
counterparts in several discretionary food categories, the over-
all quality of these products remained poor with typically high
levels of sugar, saturated fat and salt.
Gluten is an important part of traditional cereal-based foods
such as bread and pasta because it confers desirable functional
(e.g. strengthening the structure of bread) and sensory (e.g.
improved mouthfeel) characteristics important to food manu-
facturers and consumers
(20)
. To compensate for the absence of
gluten, GF products are developed using a wide variety and
mixture of GF flour, fibre, hydrocolloids and enzymes
(21)
,
and concerns have been raised regarding the nutritional pro-
file of GF products. For example, prior surveys of a limited
number of GF products have suggested frequent dependence
on substitute ingredients with low fibre content
(22,23)
. It has
also been speculated that GF products may contain more
sugar and fat to improve palatability, with the concern that
this could result in higher energy intake and weight gain
(24)
.
A key finding from our analyses of nearly 1200 core foods is
the lower average protein content of GF products, which
suggests that carbohydrate-rich, but protein-poor ingredients
such as maize starch, white rice flour, potato starch or tapioca
starch are likely to have been used as substitutes in these food
categories. As such ingredients are often also very low in vita-
mins and minerals, our findings highlight the need for future
studies to examine the levels of these nutrients in GF core
foods. The present results do not support the contention
that GF core foods are consistently lower in fibre content or
that the nutritional quality of GF foods is seriously adversely
influenced by the addition of saturated fat or sugar.
Breads, RTE breakfast cereals and pasta are important
sources of nutrients in the Australian population, with the
most recent Australian Health Survey reporting that approxi-
mately two-thirds and one-third of the population consumed
breads and RTE breakfast cereals on the day of assessment
(9)
.
The differences in protein content between GF and non-GF
core foods that we identified have also been reported by
others
(25)
. However, this difference is unlikely to have a
substantial impact on protein intake in those following a GF
diet if they also eat meat, dairy and egg products. Neverthe-
less, those who do not (e.g. vegans) could be particularly
affected, and education regarding alternative protein sources
(e.g. legumes and nuts) is important for this group.
There has been a dramatic increase in the demand for GF
products over the last several years, driven in part by a per-
ception that these products are healthier than their non-GF
counterparts
(2,3)
. A large number of discretionary products
that do not naturally contain gluten (e.g. processed meats
and corn and potato chips) and that now carry GF labelling
suggests that food manufacturers may be employing GF label-
ling as a tool to market discretionary food items. The average
nutritional qualities of GF discretionary foods were not sys-
tematically superior to those of non-GF products, although
some were better than their gluten-containing counterparts.
There is growing evidence that the ‘health halo’ effect
whereby products are labelled as ‘healthier’ (e.g. low fat)
can mislead consumers about elements such as energy content
and portion sizes, resulting in increased consumption
(26 – 29)
.
The effects of GF labelling on consumer perception and beha-
viour is not well established; however, there is a clear risk that
consumers could misconstrue GF status as an indicator of
healthiness. Another potential risk is that non-coeliac subjects
who choose to consume a GF diet may unnecessarily limit the
variety and adversely affect the quality of their diet, which
could have a substantial influence on health outcomes
(30)
.
Therefore, it is also important for future studies to assess the
overall dietary pattern (i.e. intake of specific foods such as
whole grains, fruits and vegetables) in populations consuming
a GF diet.
The present study has several strengths. Nutritional infor-
mation was collected using standardised methods with rigor-
ous quality control that reduced the likelihood of data
errors. We sampled a large number of products that enhanced
statistical power to assess differences in nutritional quality
between GF and non-GF products. The collection of packaged
foods from leading Australian retailers increased the relevance
of these findings to Australian consumers. Simultaneous
assessment of both core and discretionary food products pro-
vided novel insights into the nutritional quality of GF products
across diverse food domains that are consumed in significant
quantities by a large proportion of the population.
Potential limitations are the absence of ‘gold-standard’
chemical analysis to assess individual nutrients in the food
products and our reliance on the NIP. Prior independent
assessments of NIP data suggest that they are generally accu-
rate
(31)
. Our reliance on the NIP also meant that we were
unable to systematically evaluate the levels of other nutrients
of interest (e.g. folate, thiamin and Fe) that may differ between
GF and non-GF products
(22,23,32)
. Dietary fibre information
was available for only a subset of the products evaluated,
and therefore these results should be interpreted with caution.
We did not collect and compare the price of GF and non-GF
products; furthermore, as the present study examined pack-
aged foods from large supermarket chains in Australia, the
findings may not be generalisable to products found in
other types of food retailers or to other countries.
Breads
Plain dry pasta 26
n
87
41
321
62
228
RTE breakfast cereals
Dietary fibre (g/100 g)
0246810
*
*
12
Fig. 1. Dietary fibre levels of gluten-free (GF, A) and non-gluten-free (non-GF,
B) pasta, breads and ready-to-eat (RTE) breakfast cereal products. Products
were identified from four major supermarkets in Sydney, Australia in 2013,
and analyses were restricted to products with dietary fibre information
available on their Nutrition Information Panel. Values are means, with their
standard errors represented by vertical bars. * Mean value was significantly
different from that of non-GF products (P,0·05; linear regression).
J. H. Y. Wu et al.4
British Journal of Nutrition

Table 2. Nutritional profile of gluten-free (GF) v. non-GF discretionary food categories
(Mean values and standard deviations)
Nutrient content (per 100 g)
Health Star
Rating (stars) Energy (kJ) Na (mg)
Saturated fat
(g) Protein (g)
Total sugars
(g)
Product types nPercentage of all products Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD
Cereal bars 237
GF 60 25·3 2·6 0·9 1907 299 53·9 52·3 5·3 4·6 9·7 3·8 30·6 10·4
Non-GF 177 74·7 2·6 0·9 1765 224 135 105 6·0 4·0 8·1 3·4 25·9 7·5
Difference in mean* 0 142 281 20·7 1·6 4·7
P†0·75 ,0·001 ,0·001 0·31 0·002 ,0·001
Cake mixes/cakes 491
GF 59 12·0 1·7 0·8 1469 307 300 215 3·4 4·9 4·9 6·4 44·1 24·1
Non-GF 432 88·0 1·6 0·7 1501 290 319 200 5·5 4·6 4·6 1·3 36·0 13·5
Difference in mean* 0·1 232 219 22·1 0·3 8·1
P†0·65 0·43 0·50 0·001 0·47 ,0·001
Sweet biscuits 550
GF 63 11·5 1·2 0·7 1942 250 183 158 13·9 5·4 4·5 2·1 31·3 7·8
Non-GF 487 88·5 1·1 0·7 1978 200 240 127 11·7 5·6 5·8 1·5 33·4 10·7
Difference in mean* 0·1 236 257 2·2 21·3 22·1
P†0·85 0·22 0·002 0·005 ,0·001 0·16
Ice cream 217
GF 25 11·5 2·8 0·6 728 195 49·1 17·5 5·1 3·8 3·3 1·3 18·4 4·6
Non-GF 192 88·5 2·0 0·8 1073 284 70·4 35·7 8·9 4·7 3·6 1·1 23·6 3·7
Difference in mean* 0·8 2345 221·3 23·8 20·3 25·2
P†0·001 ,0·001 0·004 ,0·001 0·16 ,0·001
Corn and potato chips 154
GF 56 36·4 3·5 0·7 1996 186 596 457 4·0 3·7 6·0 2·1 3·0 2·6
Non-GF 98 63·6 2·8 0·7 2122 121 645 211 9·4 5·3 6·4 1·4 2·9 1·5
Difference in mean* 0·7 2126 249 25·4 20·4 0·1
P†,0·001 ,0·001 0·37 ,0·001 0·16 0·70
Cured meats, sausages and hot dogs 179
GF 156 87·2 1·4 0·9 1134 352 1056 496 8·5 3·7 18·0 5·5 0·9 0·5
Non-GF 23 12·9 1·4 0·8 1104 301 1005 347 7·0 3·0 16·6 3·9 0·9 0·2
Difference in mean* 0·1 30 51 1·5 1·4 0
P†0·87 0·70 0·63 0·06 0·23 0·72
Sugar-based confectioneries 206
GF 45 21·8 2·0 0·8 1380 198 51·9 102 2·0 3·3 3·4 2·9 38·8 31·9
Non-GF 161 78·2 1·8 0·5 1462 119 86·9 96 1·0 1·0 2·9 1·7 52·4 14·5
Difference in mean* 0·2 282 235 1·0 0·5 213·6
P†0·01 0·001 0·04 0·001 0·15 ,0·001
* Calculated as follows: mean GF group 2mean non-GF group.
† Differences in mean nutrient content between GF and non-GF products were assessed by linear regression analysis.
Gluten-free v. non-gluten-free foods 5
British Journal of Nutrition

In conclusion, the consumption of GF products is unlikely
to confer health benefits, unless there is clear evidence of coe-
liac disease, gluten intolerance or allergy to gluten-containing
grains. There is a moderate likelihood that GF labelling is
being used to infer healthiness for discretionary items, which
is unwarranted. Given the adverse health effects caused by
poor diets in Australia and other parts of the world, policy
initiatives should target increased consumption of core foods
such as whole grains, fruit and vegetables and reduced
consumption of discretionary foods (GF or otherwise) as a
public health priority.
Supplementary material
To view supplementary material for this article, please visit
http://dx.doi.org/10.1017/S0007114515002056
Acknowledgements
B. N. was supported by an Australian Research Council Future
Fellowship (DP100100295) and a National Health and Medical
Research Council (NHMRC) of Australia Senior Research
Fellowship (APP100311). He holds a NHMRC Program Grant
(APP1052555). B. N., J. H. Y. W. and M. C. work within a
NHMRC Centre for Research Excellence (APP1041020). H. T.
was supported by a postgraduate scholarship from the
NHMRC. E. D. was supported by a NHMRC Early Career
Fellowship.
The authors’ contributions are as follows: J. H. Y. W., B. N.
and E. D. contributed to the study concept and design; B. N.
obtained funding; J. H. Y. W. and E. D. conducted the
research, the acquisition of the data, and the statistical
analyses; J. H. Y. W. drafted the manuscript and had primary
responsibility for the final content. All authors interpreted
the data, critically revised the manuscript for important
intellectual content, and approved the final manuscript.
There are no conflicts of interest.
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