Living in Rural and Urban Areas of New Caledonia: Impact on Food Consumption, Sleep Duration and Anthropometric Parameters Among Melanesian Adolescents

Abstract

Background:
Food consumption, sleep duration and overweight were assessed in rural and urban Melanesian adolescents.

Methods:
A cross-sectional survey of 312 rural and 104 urban adolescents (11-16 years old) was conducted. Food intakes were assessed by a 26-item food frequency questionnaire and then categorised into the number of serves from each of the three recommended Pacific food groups (energy foods, protective foods, bodybuilding foods), with two additional categories for foods and drinks to be avoided i.e., processed foods and sugary drinks. Number of food serves were compared with the guidelines of 50% serves from energy foods, 35% serves from protective foods and 15% serves from bodybuilding foods. Sleep duration as hours per day was self-reported and body mass index (BMI) was calculated from measured weight and height.

Results:
Approximately 17.9% of rural and 26.9% of urban adolescents met the guidelines for energy foods; 61.5% rural and 69.2% urban met the serves for protective foods and 88.5% and 94.2% met the serves for bodybuilding foods. Less than 6.4% rural and 1.9% urban adolescents avoided processed foods but 61.5% rural and 56.7% urban avoided sugary beverages. Sleep duration for school days was below the international recommendations and did not significantly differ between rural and urban groups: respectively, 8.16 ± 1.10 and 8.31 ± 1.29 h. Overweight/obesity percentage was 38.1% for rural and 31.7% for urban adolescents.

Conclusions:
Although traditional foods, including protective food, are still part of the adolescents' diet, low consumption of the energy food group and high consumption of processed food occurs regardless of location. As poor eating habits and insufficient sleep may contribute to overweight/obesity, educational nutrition programs should target these lifestyle variables.

Full text

nutrients
Article
Living in Rural and Urban Areas of New Caledonia:
Impact on Food Consumption, Sleep Duration and
Anthropometric Parameters Among
Melanesian Adolescents
Olivier Galy 1, * , Emilie Paufique 1, Akila Nedjar-Guerre 1, Fabrice Wacalie 1,
Guillaume Wattelez 1, Pierre-Yves Le Roux 1, Solange Ponidja 1, Paul Zongo 1,
Christophe Serra-Mallol 2, Margaret Allman-Farinelli 3and Stéphane Frayon 1
1Interdisciplinary Laboratory for Research in Education, EA 7483, University of New Caledonia,
Avenue James Cook, 98800 Nouméa, New Caledonia; emilie.paufique@etudiant.unc.nc (E.P.);
akila.nedjar-guerre@unc.nc (A.N.-G.); fabrice.wacalie@unc.nc (F.W.); guillaume.wattelez@unc.nc (G.W.);
pierre-yves.le-roux@unc.nc (P.-Y.L.R.); solange.ponidja@unc.nc (S.P.); lopops1070@hotmail.fr (P.Z.);
stephanefrayon@hotmail.com (S.F.)
2CERTOP—University of Toulouse Jean Jaurès, 5 Allée Antonio Machado, 31058 Toulouse, France;
christophe.serra-mallol@univ-tlse2.fr
3Charles Perkins Centre, The University of Sydney, Camperdown, NSW 2006, Australia;
margaret.allman-farinelli@sydney.edu.au
*Correspondence: olivier.galy@unc.nc; Tel.: +687-290-545
Received: 15 February 2020; Accepted: 15 June 2020; Published: 10 July 2020


Abstract:
Background: Food consumption, sleep duration and overweight were assessed in rural
and urban Melanesian adolescents. Methods: A cross-sectional survey of 312 rural and 104 urban
adolescents (11–16 years old) was conducted. Food intakes were assessed by a 26-item food frequency
questionnaire and then categorised into the number of serves from each of the three recommended
Pacific food groups (energy foods, protective foods, bodybuilding foods), with two additional
categories for foods and drinks to be avoided i.e., processed foods and sugary drinks. Number of
food serves were compared with the guidelines of 50% serves from energy foods, 35% serves from
protective foods and 15% serves from bodybuilding foods. Sleep duration as hours per day was
self-reported and body mass index (BMI) was calculated from measured weight and height. Results:
Approximately 17.9% of rural and 26.9% of urban adolescents met the guidelines for energy foods;
61.5% rural and 69.2% urban met the serves for protective foods and 88.5% and 94.2% met the serves
for bodybuilding foods. Less than 6.4% rural and 1.9% urban adolescents avoided processed foods
but 61.5% rural and 56.7% urban avoided sugary beverages. Sleep duration for school days was
below the international recommendations and did not significantly differ between rural and urban
groups: respectively, 8.16
±
1.10 and 8.31
±
1.29 h. Overweight/obesity percentage was 38.1% for
rural and 31.7% for urban adolescents. Conclusions: Although traditional foods, including protective
food, are still part of the adolescents’ diet, low consumption of the energy food group and high
consumption of processed food occurs regardless of location. As poor eating habits and insufficient
sleep may contribute to overweight/obesity, educational nutrition programs should target these
lifestyle variables.
Keywords:
food habits; nutrition behaviour; ethnicity; lifestyle; adolescents; sustainable
development; Pacific
Nutrients 2020,12, 2047; doi:10.3390/nu12072047 www.mdpi.com/journal/nutrients

Nutrients 2020,12, 2047 2 of 14
1. Introduction
Pacific Island Countries and Territories (PICTs) have been undergoing a brutal socioeconomic
transition over the past 70 years. Pacific cultures have been exposed to a military presence during
and after World War II [
1
], the development of centralised political rule, monetisation of economic
systems and increased trade globalisation. Clearly, a lifestyle transition has been underway, and a
diet once based on fresh seafood, vegetables and tubers has shifted to include canned meat or fish,
oil, sugar, rice and processed foods [
2
]. At the same time, daily activity, which was once based on
fishing and agriculture, has shifted to more sedentary activities that have had a major impact on
health [
3
]. More recently, the mechanisation and digitisation of environments have also influenced
daily behaviour and activity, including physical activity and sleep duration. Indeed, when sleep
is less than optimal, energy expenditure is affected: sleep-deprived individuals are prone to feel
sleepy and tired in the daytime, thus preferring sedentary activities to physical activities, which then
lowers the energy expenditure [
4
]. Sleep deprivation negatively impacts metabolism, with rises in
the hunger hormone ghrelin and increases in energy intake, particularly poor-nutrient energy-dense
foods, as reported in Western populations [
5
–
8
]. These combined lifestyle variables are the root cause
(but not unique) of noncommunicable diseases, and the young Pacific population is extremely exposed.
The prevalence of overweight and obesity is very high in New Caledonian adolescents (from 36% to
43%, depending on age and the reference used to assess overweight) [
9
–
11
], and this is particularly
the case for Melanesians. Indeed, a recent study showed that the prevalence of overweight/obesity
was higher in 11 to 16-year-old Melanesian and Polynesian adolescents than in Caucasian adolescents,
respectively, 38.2%, 30.4% and 21.3% [12].
In New Caledonia, where per capita income is much higher than in other PICTs [
13
], small-scale
family farming is the predominant form of the agricultural system, particularly in the Loyalty Islands
and Northern Province, inhabited mostly by the Melanesian people. In Melanesian culture, family
farming remains prevalent [
14
], although sometimes household members leave the tribe to seek work
in towns. Agricultural activities, hunting and fishing remain strong, despite the proliferation of
development hubs, rising education levels and improved living conditions [
15
,
16
]. Nevertheless,
young people continue to be exposed to new food environments and have thus enlarged their food
choices and diversified their eating habits in both positive and negative ways [
17
]. Emergent food
environments in low-to-middle-income countries have created conditions that facilitate the choice
of lower-cost, less-healthy, more energy-dense foods, which may lead to overweight and obesity as
access to healthy foods diminishes [
18
]. The Pacific Guidelines for Healthy Living provide advice
about diet, physical activity, smoking and alcohol. These guidelines outline the proportions of foods to
be consumed from three ‘healthy’ food groups (energy, protective and bodybuilding) and indicate the
foods that should be limited. Water is the beverage of choice and sugar-sweetened beverages (SSBs)
should be avoided [
19
]. Comparing food intakes with these guidelines can yield valuable insight
into the food environments that these Pacific communities are experiencing [
19
]. In New Caledonia,
another way to gain insight into the effects of the ongoing lifestyle transition might be to determine the
proportion of ‘healthy foods’ versus ‘limited foods’ consumed by adolescents living in rural versus
urban areas. In this context, ‘healthy food’ consumption can be defined as eating a variety of fresh
local foods from the three food groups in the appropriate amounts each day (energy: 50% of food,
protective: 35% and bodybuilding: 15%) and limiting food and beverages high in salt, sugar and fat.
This means that imported processed food/drinks from the food industry should only be eaten in small
amounts. Recent studies have demonstrated that the lifestyles of New Caledonian adolescents have
undergone striking changes, characterised by a preference for highly processed drinks like SSBs [
20
],
breakfast skipping [
21
] and relatively low physical activity [
22
]. These changes may have contributed
to the prevalence of overweight and obesity in Melanesian adolescents, especially those living in rural
areas, although no study has yet investigated this hypothesis. Yet Melanesian girls from rural areas
were found to be less physically active than their urban counterparts [
10
], and this may result in the
higher prevalence of overweight and obesity as previously observed for body fat mass with 27.5%

Nutrients 2020,12, 2047 3 of 14
and 23.9% in rural and urban adolescents of similar age [
10
]. In addition, sleep behaviour is widely
associated with overweight and obesity, and several associated factors, like the influence of media at
home in the evening and school transport in isolated areas, impact sleep duration [
23
]. We therefore
hypothesised that food consumption, with the respective contributions of ‘healthy food’ and ‘limited
food’, and sleep duration would differ according to the living environment (i.e., urban and rural) of the
Melanesian adolescents and have an impact on anthropometric parameters.
This study aimed to assess food consumption, sleep duration and anthropometric parameters of
Melanesian adolescents living in rural and urban areas in New Caledonia to provide baseline measures
as the Pacific region undergoes transition.
2. Materials and Methods
2.1. Data Collection and Participants
This research is part of a community-based food culture project underway in New Caledonia and
its provinces: Northern Province, Southern Province and Loyalty Islands. All differ substantially in
terms of ethnic distribution, socioeconomic status and urbanisation. The ethnic groups are as follows:
Melanesian: 39.0%, European: 34.4%, Polynesian: 10.0%, Asian: 2.7% and other groups 14.1% [
13
].
The Melanesian community is distributed as follows: 77.0% live in rural areas and 23.0% in urban
areas [
13
]. Forty percent of the public schools are in rural areas (n=13) and 60% in urban areas
(n=20) [
13
]. The criteria for selecting the schools for this study were (1) location (rural and urban),
(2) sufficient school size (n>200) and (3) the agreement of the school’s principal. Five schools were
eligible in Southern Province (urban area), two in Northern Province (one on each coast) and only one
in Loyalty Islands (Lifou Island). Participating classes were then randomly drawn from within these
eligible schools. The school and participant selection processes are more fully described elsewhere [
24
].
We gathered data from July 2018 to April 2019 from 1060 adolescents from the community-based
food culture project, 11 to 16 years old from several ethnic community. In the current study, only
Melanesian adolescents were considered, providing a final sample of 416 Melanesian adolescents
representing 39.2% of the total sample and reflecting the percentage of Melanesians in the New
Caledonian population [13].
We obtained informed written consent from all parents before their children entered the study.
The research met the legal requirements and the Declaration of Helsinki, and the protocol was approved
by the Ethics Committee of the University of New Caledonia: CCE 2018-06 001.
2.2. Measures
2.2.1. Anthropometric Parameters
A trained staffcollected the anthropometric data in the school nurse’s office. A portable stadiometer
(Leicester Tanita HR 001, Tanita Corporation, Tokyo, Japan) measured height to the nearest 0.1 cm.
Weight was assessed to the nearest 0.1 kg using a scale (Tanita HA 503, Tanita Corporation, Tokyo,
Japan), with the adolescents wearing light clothing. From these measurements, body mass index (BMI)
was calculated as follows BMI =weight [kg]/([height [m])2.
We used the International Obesity Task Force (IOTF) criteria for children to define the adolescents
as thin (underweight), normal weight, overweight or obese. The IOTF criteria provide BMI cut-offs for
weight status based on BMI values according to age and sex [25].
2.2.2. Sociodemographic Characteristics
The adolescents used an anonymous survey tool to report ethnicity, and the ethnic groups
were categorised following the recommendations from the report on New Caledonia [
26
] by the
Institut National de la Sant
é
Et de la Recherche M
é
dicale (INSERM; National Institute of Health
and Medical Research). Three SES categories were determined based on the National Statistics

Nutrients 2020,12, 2047 4 of 14
Socio-Economic Classification [
27
]: managerial and professional occupations (high), intermediate
occupations (medium), and routine and manual occupations (low). We referred to the latest census in
New Caledonia [
13
] and a European standard to determine the degrees of urbanisation [
28
]: Noumea
and its suburbs were classified as urban and the other areas were classified as rural.
2.2.3. Food Frequency Questionnaire (FFQ)
The short FFQ was adapted from the validated version of the FFQ for Aboriginal and Torres
Strait Islanders by Gwynn et al. [
29
], in the absence of a validated FFQ for New Caledonia. Minor
modifications were made by the research team to include foods identified as important in the diet
of Melanesian adolescents [
19
] (Table 1). For example, tubers such as cassava, yams and taro are
consumed rather than white potatoes, and a common snack food is reconstituted noodle soup, e.g.,
Maggi noodles. The FFQ contains 26 questions on food and beverage intake with additional questions
on the purchase of food on the journey to and from school and at the school canteen.
For each participant, we calculated the number of serves for each of the following ten food
categories: (1) cereals (bread, pasta and rice); (2) vegetables and legumes (all varieties excluding
tubers); (3) fruit (all varieties including dried); (4) dairy (milk, yoghurt and cheese); (5) fats/oils (butter);
(6) red meat, pork, fish, poultry and eggs; (7) water; (8) SSBs; (9) extra foods high in salt or sugar
or saturated fat (french fries, salty processed meats, chocolate and confectionary, cakes, pastries and
biscuits); and (10) other (tubers such as cassava, yams, taro, sweet potato; noodle soup; take-away
food and breakfast cereals). To gain a global understanding of how well the food consumption in
rural and urban areas met the Pacific guidelines, the above ten food categories were condensed to
the three main food groups for the Pacific communities, plus limited foods, limited beverages and
water [
19
] as described in Table 1. These groups are: (1) energy foods (cereals and tubers), which
should comprise 50% of the food intake corresponding to a minimum of 6 serves per day; (2) protective
foods (vegetables, fruits), which should comprise 35% of food intake corresponding to a minimum of
5 serves per day; (3) bodybuilding foods (red meat, pork, fish, poultry and eggs, dairy and legumes),
which should comprise 15% of all foods corresponding to a minimum of 1.5 serves per day; (4) limited
foods (extra foods high in salt or sugar or saturated fat); (5) limited beverages (SSBs); and (6) water.
It should be noted that extra foods and other foods like noodle soup with Maggi sauce, cakes and
confectionary, as well as SSBs, are not recommended, but the number of serves of these was calculated.

Nutrients 2020,12, 2047 5 of 14
Table 1.
Dietary intake extracted from Gwynn’s FFQ [
29
] was analysed using the Pacific Food Group
Guidelines from the South Pacific Community [19].
Pacific Guidelines
Food Groups Main Nutrients Provided Food Question Extracted from Gwynn’s FFQ
Energy
Carbohydrates
Vitamins
Dietary fibre
Bread
How often do you eat bread (piece)? This
includes baguette bread, baby bread,
coconut bread, sandwich bread, etc.
Pasta and rice How often do you eat pasta or rice?
Tubers
How often do you eat tubers (cassava, yam,
taro, sweet potato, etc.)?
Protective
Vitamins
Minerals
Dietary fibre
Phytochemicals
Antioxidant
Vegetables
How often do you usually eat vegetables
per day (for example, salad, green beans,
cabbage, carrots, tomatoes, etc.)? This
includes all fresh, frozen and
canned vegetables.
Fruits
How often do you eat fruits per day (for
example, papaya, banana, mango, orange,
apple, etc.)? This includes all fresh, dried,
frozen and canned fruits.
Bodybuilding
Proteins and essential amino acids
Vitamins
Minerals
Fatty acids
Fibre (from dried beans and nuts)
Lentils, beans How often do you eat lentils, split peas or
dried beans?
Milk
What is the total amount of milk you
generally drink each day? Take into
account all types of milk (brick, powder,
milk consumed with cereals, etc.)
Cheese How often do you eat cheese?
Yoghurt How often do you eat yoghurt?
Red meat
How often do you eat red meat (such as
beef, deer or lamb)? This includes all steaks,
ribs, roasts, minced meat, stirfries
and stews.
White meat How often do you eat white meat
like chicken?
Fish How often do you eat fish?
Pork How often do you eat pork?
Eggs How often do you eat eggs?
Limited beverage SSB How many sweetened drinks do you
usually drink (juice, soda, lemonade)?
Limited food
Butter
How often do you eat your bread with
butter or margarine
(for example, Meadowlea)?
Canned meat
How often do you eat canned meat (corned
beef, ouaco beef, etc.)?
Deli meats How often do you eat cold cuts, sausages,
pâté, canned ham?
French fries How often do you eat french fries?
Salty snacks
How often do you eat potato chips or other
salty snacks (Twisties, Doritos, etc.)?
Sweeties How often do you eat confectionery
(lollipops, chocolate etc.)?
Sweet foods How often do you eat sweet foods such as
sweet biscuits, cake or pastries?
Breakfast cereals How often do you eat breakfast cereals?
Noodle soup
How often do you usually eat noodle soup
(bowl of soup, Maggi soup, Yum Yum
soup, etc.)?
Take-away food
How often do you eat meals such as
hamburgers, pizzas, fries from places
selling take-away food?
Water Water
How much water do you usually drink
each day? It can be tap water or bottled
water (a small bottle =two glasses).

Nutrients 2020,12, 2047 6 of 14
2.2.4. Sleep
The sleep duration was determined with the following four questions: ‘What time do you fall
asleep on school days?’, ‘What time do you fall asleep on the weekend?’, ‘What time do you wake
up in the school week?’ and ‘What time do you wake up on the weekend?’ There were 13 available
categories for the time an adolescent might fall asleep from ‘Around 9 pm or before’ to ‘Around
3 am or later’ with a 30-min interval between each category. There were 15 available categories for
the wake-up time from ‘Around 5 am or before’ to ‘Around midday or later’ with a 30-min interval
between each category. Answers were converted to numerical values by using the median value of
the time interval in the categorised answer or by using 30 min before (respectively after) for the first
(respectively the last) category. The final sleep duration was the difference between the wake-up time
and the falling-asleep time.
First, answers about sleeping duration during the school week and the weekend were separately
processed and then both factors were combined to get a total sleeping duration for the full week
as follows:
Sleep (Total Week)=
5
×Sleep (Week days)+
2
×Sleep (weekend)
. Sleep durations were
determined according to the recommendations from Hirshkowitz et al. [
23
] about sleeping, with a
threshold of 9 h 30 min for these 11- to 16-year-old adolescents.
2.3. Statistics
Analyses were conducted using R 3.5.1. [
30
], with an accepted type I error probability set at
α=
0.05. We tested the differences between adolescents living in rural and urban areas for each
parameter. For categorical parameters, the
χ2
test was performed when Cochran’s rule was verified,
otherwise Fisher’s exact test was used. For numerical parameters, Student’s t-test of means equality
was used when the assumption of variance equality was not rejected after an F test to compare
variances, otherwise the Welch test of means equality was used. The sample size (both in rural and
urban Melanesian adolescents) authorised these two parametric tests.
The percentages of adolescents meeting the dietary guidelines for each of the Pacific food groups
(energy: 6 serves/day, protective: 5 serves/day, bodybuilding: 1.5 serves/day) was calculated in the
whole sample and according to sex, weight status and the living area. The differences in proportions
between rural and urban adolescents meeting the guidelines were tested with the
χ2
test when
Cochran’s rule was verified and otherwise with the Fisher’s exact test.
3. Results
3.1. SES, Anthropometry and Sleep Duration
The descriptive data, both overall and by sex, are presented in Table 2. The sample of 204 boys
and 212 girls was all within the age range of 11 to 16 years. The breakdown of SES was: 11.8% high
status, 11.3% intermediate status and 76.2% low status.
The percentage of overweight or obesity was 38.1% for rural and 31.7% for urban adolescents.
No significant differences emerged between adolescents living in rural and urban areas, both in girls
and boys. No other significant differences in demographic characteristics, such as place of residence or
SES, were found.
Sleep duration in the school week or the weekend did not differ between rural and urban groups.
However, average sleep duration was substantially below the international recommendations (9.50 h
per night) [23] in both living areas, with 8.34 and 8.55 h per night in rural and urban areas.

Nutrients 2020,12, 2047 7 of 14
Table 2.
Anthropometric (weight, height, weight status) and sociodemographic characteristics (SES) and sleep duration according to the adolescents’ living area (rural
or urban) and sex. Numbers represent ‘Mean (Standard deviation)’ for the numerical variables (Age, Anthropometry and Sleep duration) and ‘Size (%)’ for the
categorical variables (SES, Weight status and Meals). Statistical significance was noted in the p-value column.
Whole Sample Female Male
Rural
(n=312)
Urban
(n=104) p-Value Rural
(n=167)
Urban
(n=45) p-Value Rural
(n=145)
Urban
(n=59) p-Value
Subjects [Mean (sd)] Age (months) 160.52
(15.21)
156.63
(12.60) 0.011 162.16
(14.22)
156.73
(11.68) 0.020 158.64
(16.11)
156.56
(13.36) 0.381
SES [n(%)]
Higher 35 (11.2%) 14 (13.4%)
0.060
17 (10.2%) 4 (8.9%)
0.401
18 (12.4%) 10 (17.0%)
0.110
Intermediate 29 (9.3%) 18 (17.3%) 17 (10.2%) 8 (17.8%) 12 (8.3%) 10 (17.0%)
Lower 245 (78.5%) 72 (69.2%) 131 (78.4%) 33 (73.3%) 114 (78.6%) 39 (66.1%)
Anthropometry
[Mean (sd)]
Height (cm) 156.5 (8.9) 157.3 (8.9) 0.417 156.7 (7.2) 157.0 (5.3) 0.762 156.2 (10.5) 157.5 (11.0) 0.427
Weight (kg) 54.4 (14.4) 54.1 (14.0) 0.846 55.4 (13.2) 55.4 (11.6) 1.000 53.3 (15.7) 53.1 (15.6) 0.942
Weight status [n(%)] Underweight and Normal 193 (61.9%) 71 (68.3%) 0.290 98 (58.7%) 29 (64.4%) 0.597 95 (65.5%) 42 (71.2%) 0.537
Overweight and obese 119 (38.1%) 33 (31.7%) 69 (41.3%) 16 (35.6%) 50 (34.5%) 17 (28.8%)
Sleep duration
[Mean (sd)]
Weekday (h/day) 8.16 (1.10) 8.31 (1.29) 0.302 8.15 (1.11) 8.29 (1.26) 0.459 8.18 (1.09) 8.32 (1.32) 0.427
Weekend (h/day) 8.80 (1.69) 8.84 (1.99) 0.854 8.96 (1.63) 9.01 (2.02) 0.854 8.61 (1.74) 8.70 (1.98) 0.740
All week (h/week) 58.40 (7.03) 59.21 (8.46) 0.380 58.65 (7.22) 59.47 (8.35) 0.516 58.12 (6.81) 59.02 (8.61) 0.475
Meals [n(%)]
Lunch at school 205 (65.7%) 96 (92.3%)
<0.001
108 (64.7%) 43 (95.6%)
<0.001
97 (66.9%) 53 (89.8%)
<0.001
No lunch at school 15 (4.8%) 8 (7.7%) 6 (3.6%) 2 (4.4%) 9 (6.2%) 6 (10.2%)
In boarding school 92 (29.5%) 0 (0.0%) 53 (31.7%) 0 (0.0%) 39 (26.9%) 0 (0.0%)

Nutrients 2020,12, 2047 8 of 14
3.2. Food Consumption and Frequency on School Days
Food consumption for the energy, protective and bodybuilding groups did not significantly differ
between the rural and urban adolescents (Figure 1). The extra and other foods defined as limited and
SSBs showed no differences, with high consumption observed for those living in both rural and urban
areas (Table 3and Figure 1). The average contribution of the food groups for the rural and urban
adolescents was, respectively: energy: 22% and 23%, protective: 32% and 30% and bodybuilding:
19% and 20% (Figure 1). Moreover, the percentage of limited food averaged 21% and limited drinks
reached 6% for both rural and urban Melanesian adolescents. We also assessed the percentage of the
sample meeting the Pacific guidelines for the three food groups (using number of serves compared
with recommended daily intake) and found no differences between rural and urban adolescents for the
whole sample, the underweight and normal-weight subgroup, or the overweight and obese subgroup
(Table 3). Most adolescents met the Pacific guidelines for bodybuilding foods. 61.5% of rural and
69.2% of urban adolescents consumed sufficiently protective foods including fruits and vegetables.
The recommended intake for the energy group was only achieved by 18.0% of rural and 26.9% of urban
adolescents. Less than 10% of these adolescents avoided limited foods and those in urban areas who
were normal or underweight all consumed these foods, with none totally avoiding them. More than
half the adolescents managed to avoid SSBs.
Nutrients 2020, 12, x FOR PEER REVIEW 8 of 14
3.2. Food Consumption and Frequency on School Days
Food consumption for the energy, protective and bodybuilding groups did not significantly
differ between the rural and urban adolescents (Figure 1). The extra and other foods defined as
limited and SSBs showed no differences, with high consumption observed for those living in both
rural and urban areas (Table 3 and Figure 1). The average contribution of the food groups for the
rural and urban adolescents was, respectively: energy: 22% and 23%, protective: 32% and 30% and
bodybuilding: 19% and 20% (Figure 1). Moreover, the percentage of limited food averaged 21% and
limited drinks reached 6% for both rural and urban Melanesian adolescents. We also assessed the
percentage of the sample meeting the Pacific guidelines for the three food groups (using number of
serves compared with recommended daily intake) and found no differences between rural and urban
adolescents for the whole sample, the underweight and normal-weight subgroup, or the overweight
and obese subgroup (Table 3). Most adolescents met the Pacific guidelines for bodybuilding foods.
61.5% of rural and 69.2% of urban adolescents consumed sufficiently protective foods including fruits
and vegetables. The recommended intake for the energy group was only achieved by 18.0% of rural
and 26.9% of urban adolescents. Less than 10% of these adolescents avoided limited foods and those
in urban areas who were normal or underweight all consumed these foods, with none totally
avoiding them. More than half the adolescents managed to avoid SSBs.
Figure 1. Food group proportions (percentages) and structure (yellow for energy group; green for
protective group, orange for bodybuilding group, red for limited food and red and white dots for
limited drinks) of rural (n = 312, middle column) and urban (n = 104, right column) adolescents
compared with the Pacific guidelines (left column) [19]. Data are expressed in percentages (%) per
day.
Figure 1.
Food group proportions (percentages) and structure (yellow for energy group; green for
protective group, orange for bodybuilding group, red for limited food and red and white dots for
limited drinks) of rural (n=312, middle column) and urban (n=104, right column) adolescents
compared with the Pacific guidelines (left column) [
19
]. Data are expressed in percentages (%) per day.

Nutrients 2020,12, 2047 9 of 14
Table 3.
Food frequency, food group consumption expressed in serves per week (with school meals according to each adolescent‘s living area: rural or urban) and sex.
Statistical significance was noted in the p-value column.
Whole Sample Female Male
Serves per Day
[Mean (sd)] % Meeting the Guidelines Serves per Day
[Mean (sd)] % Meeting the Guidelines Serves per Day
[Mean (sd)] % Meeting the Guidelines
Rural Urban Rural Urban p-Values Rural Urban Rural Urban p-Values Rural Urban Rural Urban p-Values
Whole sample
Energy group 4.06 (2.20) 4.56 (2.54) 18.0 26.9 0.067 4.04 (2.28) 4.08 (2.30) 19.2 20.0 1.000 4.07 (2.12) 4.92 (2.66) 16.6 32.2 0.022
Protective group 5.55 (2.30) 5.60 (2.06) 61.5 69.2 0.196 5.47 (2.28) 5.67 (2.09) 60.5 73.3 0.158 5.65 (2.33) 5.55 (2.05) 62.8 66.1 0.772
Bodybuilding group 3.51 (1.77) 3.87 (2.15) 88.5 94.2 0.133 3.27 (1.65) 3.40 (1.83) 86.2 91.1 0.535 3.79 (1.85) 4.23 (2.32) 91.0 96.6 0.277
Limited foods 4.01 (2.63) 4.41 (2.80) 6.4 1.9 0.129 4.07 (2.63) 4.20 (2.82) 4.8 4.4 1.000 3.95 (2.64) 4.58 (2.80) 8.3 0.0 0.020
Limited beverages 1.16 (1.22) 1.36 (1.37) 61.5 56.7 0.452 1.11 (1.19) 1.40 (1.37) 62.9 53.3 0.321 1.21 (1.25) 1.33 (1.37) 60.0 59.3 1.000
Water 3.14 (1.14) 3.39 (1.07) 2.99 (1.19) 3.11 (1.06) 3.30 (1.07) 3.61 (1.03)
Underweight and
normal weight
Energy group 4.10 (2.23) 4.71 (2.50) 18.1 28.1 0.108 3.88 (2.26) 4.09 (2.13) 16.3 17.2 1.000 4.32 (2.19) 5.14 (2.66) 20.0 35.7 0.080
Protective group 5.54 (2.36) 5.70 (2.12) 60.1 69.0 0.237 5.23 (2.31) 5.74 (2.24) 55.1 72.4 0.147 5.86 (2.39) 5.67 (2.06) 65.3 66.7 1.000
Bodybuilding group 3.53 (1.76) 3.81 (2.14) 89.1 94.4 0.292 3.25 (1.65) 3.07 (1.61) 85.7 89.7 0.813 3.83 (1.83) 4.32 (2.33) 92.6 97.6 0.452
Limited foods 4.32 (2.81) 4.55 (2.91) 6.2 0.0 0.041 4.26 (2.82) 4.21 (2.85) 6.1 0.0 0.335 4.38 (2.80) 4.78 (2.97) 6.3 0.0 0.177
Limited beverages 1.21 (1.29) 1.40 (1.35) 61.7 53.5 0.293 1.19 (1.25) 1.37 (1.37) 60.2 89.7 0.788 1.23 (1.34) 1.43 (1.36) 63.1 52.4 0.319
Water 3.09 (1.15) 3.39 (1.10) 2.91 (1.20) 3.17 (1.11) 3.27 (1.08) 3.54 (1.08)
Overweight
and obese
Energy group 3.99 (2.17) 4.23 (2.63) 17.7 24.2 0.547 4.28 (2.32) 4.07 (2.66) 23.3 25.0 1.000 3.60 (1.90) 4.37 (2.66) 10.0 23.5 0.216
Protective group 5.58 (2.20) 5.40 (1.93) 63.9 69.7 0.678 5.81 (2.20) 5.54 (1.84) 68.1 75.0 0.812 5.25 (2.17) 5.26 (2.06) 58.0 64.7 0.841
Bodybuilding group 3.47 (1.77) 4.00 (2.20) 87.4 93.9 0.457 3.29 (1.67) 3.99 (2.10) 87.0 93.8 0.742 3.72 (1.90) 4.01 (2.36) 88.0 94.1 0.669
Limited foods 3.52 (2.25) 4.12 (2.55) 6.7 6.1 1.000 3.80 (2.34) 4.17 (2.84) 2.9 12.5 0.328 3.13 (2.08) 4.08 (2.34) 12.0 0.0 0.325
Limited beverages 1.07 (1.09) 1.27 (1.40) 61.3 63.6 0.970 0.99 (1.10) 1.45 (1.41) 66.7 50.0 0.337 1.18 (1.08) 1.11 (1.42) 54.0 76.5 0.179
Water 3.21 (1.13) 3.39 (1.02) 3.11 (1.17) 3.00 (0.99) 3.36 (1.07) 3.76 (0.92)

Nutrients 2020,12, 2047 10 of 14
4. Discussion
By focusing on food consumption and sleep, this study confirmed an advanced transition in
one of the PICTs, New Caledonia. Both rural and urban Melanesian adolescents failed to meet
recommendations for the consumption of traditional energy sources and instead showed high
consumption of processed foods, although about three out of five avoided SSBs. Their sleep duration
was low, irrespective of the place of living. Overall, these behaviour patterns may have contributed to
the high rate of overweight and obesity in both rural and urban areas.
The Melanesian adolescents had retained some of the positive aspects of the traditional diet,
with 61.5% of the rural and 69.2% of the urban adolescents meeting the guidelines for the protective food
group with adequate daily serves (5.55 and 5.60 serves per day in rural and urban areas, respectively).
These findings contrast with the findings in Western countries like Australia, where many fail to meet
the national guidelines for fruit and vegetables (albeit 7–7.5 serves is recommended in Australia) [
31
],
and even in Fiji, where 60% of Melanesian adolescents fail to meet them [
26
]. In both rural and urban
areas, the adolescents more than met the daily serves for the bodybuilding group, which provides
the main sources of dietary protein and many micronutrients. However, rather than local traditional
sources of carbohydrate-rich foods, they tended to select snack foods and two out of five drank SSBs
whatever the living area. Moreover, we noted that water consumption is slightly lower in the rural
areas (3.14 serves/day) when compared with the urban areas (3.39 serves/day). We previously reported
on the high intake of SSBs and suggested such explanations as safety concerns about tap water and the
extensive marketing of these beverages [
20
]. However, the amount of limited beverages consumed
in the rural areas is also slightly lower on average (1.16 serves/day) when compared with the urban
areas (1.36 serves/day). The differences between the rural and urban areas in beverages consumption
(water and limited beverages) are not statistically significant but the urban adolescents seem to drink
more beverages than their rural counterparts, especially in girls (rural: 4.10 serves/day and urban:
4.51 serves/day). Studies on other Pacific islands have shown how changes in food and beverage
intakes have led to unbalanced diets and predisposed to malnutrition characterised by overweight and
obesity, with possible micronutrient deficiency [
32
]. Nevertheless, our findings for the Melanesian
adolescents of New Caledonia are described for the first time. Substitution of traditional food energy
sources with highly processed foods high in sugar, fat and salt are consistent with Western diets
consumed in countries where obesity is epidemic. These dietary changes might explain the high
percentage of overweight and obesity (38.1% for rural and 31.7% for urban adolescents) observed in
this study and those of other studies [10–12].
The pattern of lower consumption of ‘healthy food’ and higher consumption of ‘limited food’
of the Melanesians in the Pacific was apparent in both rural and urban dwellers. No differences were
found for most food categories based on location. This might be because the adolescents have lunchtime
meals prepared at school (part-time boarders) and some also have dinner at school (full-time boarders).
These meals have standardised food intakes across regions. Other students had easy access to shops
to purchase food on their way to and from school. The types of foods on offer are typically those
high in added sugar, saturated fat or salt that should be limited in diets, and yet almost three in five
Melanesian adolescents reported buying food in the morning journey and a little over half on the trip
home. Not only are limited foods easily accessible, but they are also extensively marketed, persuading
adolescents to purchase them despite their low dietary quality. The abandonment of recommended
food groups in favour of ‘extra’ foods that should be limited has long been recognised in neighbouring
countries like Australia, where as much as 40% of the energy in adolescent diets comes from these
foods [
33
]. Such food patterns may result in excessive energy intake (in the present case, corresponding
to 27% of daily food intake, Figure 1), which would lead to weight gain in children [
34
]. By replacing
more nutritious foods, ‘extra’ foods might also lead to marginal intakes of some micronutrients [
35
,
36
].
One explanation for the current pattern of dietary intake is the reduced place of family farming in
the community. Family farming has played a central role in the Melanesian community and has fed
populations for decades in both rural and urban areas (urban gardens) [
15
,
37
]. Yet, population growth

Nutrients 2020,12, 2047 11 of 14
and climate change together have weaken food safety (Sustainable Goal Development number 2)
and health (Sustainable Goal Development number 3) in the Pacific population [
3
]. Second, traditional
foods with higher-fibre content are now juxtaposed with modern highly processed foods and beverages
that are highly visible in the marketplace. Indeed, the socioeconomic transition in the Pacific region
has accelerated over the past few decades and is characterised by the integration of commercial and
processed foods into the traditional diet, with both contributing to food over-abundance for meals [
38
].
Third, both what time and how frequently meals or snacks are consumed need to be considered.
One review suggested that how many and when meals are consumed throughout the day are not as
important as how energy is distributed across the meals [
39
]. This suggests that the combination of
breakfast skipping [
21
] and the timing and frequency of meals and snacks might play a major role in
adolescent weight status.
As one of the lifestyle components, sleep duration during the school week and the weekend
was substantially below the international recommendations [
23
] (Table 2). Indeed, adolescents in
both rural and urban areas wake up very early, as school begins between 7 and 7.30 am. When
the school transport time is factored in, sleep duration is de facto reduced, with wake-up times
between 5 and 5.30 am—even before 5 am for some of these families. The rhythms observed during
a typical school day added to a contemporary lifestyle at home in the evening (media, screen time,
etc.,) may be additional influences on food consumption, as already observed in Vanuatu adults [
40
].
Moreover, media messages are known to influence eating behaviours in adolescents [
41
] and may lead
to eating disorders [
42
]. Childhood obesity has traditionally been ascribed to habits of high-calorie
eating and sedentary lifestyles. Importantly, more recent research suggests that sleep duration may
also have a role in the development of obesity, as sleep is crucially implicated in hormonal release,
metabolic changes and lifestyle, all factors that contribute to overweight and obesity [
43
]. The exact
mechanisms underlying the relationship between sleeping and overweight and obesity require further
elucidation [
44
], but the link between insufficient sleep and weight gain through high caloric intake
might involve increased ghrelin levels and decreased leptin levels, both of which stimulate appetite and
the intake of excessive food [45]. In addition, it has been shown that insufficient sleep can affect food
choices, resulting in lower protective food consumption and higher consumption of limited food and
drinks [
46
]. In adolescents with sedentary activities (media use), there are many more opportunities to
eat highly processed food and drinks. Not least, insufficient sleep impacts energy expenditure, with
sleep-deprived people feeling sleepy and tired in the daytime, prompting them to choose sedentary
activities over physical activity and exercise [4].
In the present context, the combined effects of unhealthy food behaviours, including increased
consumption of limited foods and daily snacking, and reduced sleeping time most likely contribute
to the high proportion of overweight and obesity in Melanesian adolescents across places of living.
It is clear that these behaviours will contribute to the development of chronic diseases among the
population over the long term.
Limitations and Strengths of the Study
As this study was cross-sectional, we cannot point to causal relationships or long-term trends.
However, we collected data directly in the participating schools: anthropometric measurements were
made by trained staffduring medical examinations, which ensured reliable assessments, and the
FFQ was completed on days when the researchers were present. Yet, as with all self-report dietary
assessments, bias may have been introduced by the participants due to recall difficulties and social
desirability in the reporting.
The short FFQ presents limitations regarding the interpretation of food intake. While it was
possible to group the food categories into the three recommended food groups, plus limited foods and
drinks and water, the questions were not exhaustive and may not have fully captured the diversity of
dietary intakes in a population undergoing nutritional transition. We did not quantitatively assess
the macronutrient and micronutrient intakes or the portion sizes for the serves. Future studies will

Nutrients 2020,12, 2047 12 of 14
therefore include other more comprehensive dietary assessment methods and further qualitative
assessment of food habits to permit a more comprehensive and powerful analysis of food behaviour
in Melanesian adolescents. In addition, the use of self-reported information for sleep time duration
does not inform the quality of sleep or the time of falling asleep, which might influence the global
sleep of these adolescents. Another important point is energy expenditure via objective measure of
accelerometery, which is known to have major impact on anthropometric parameters and could help
to better understanding of adolescents’ lifestyle. So, future directions needs to consider the place of
physical activity.
5. Conclusions
In both rural and urban areas, processed food is omnipresent in the diets of Melanesian adolescents,
although some of the traditional food patterns are nevertheless still present. Overall, sleep durations
are low whatever the place of living. These lifestyle factors may contribute to overweight and obesity,
which lead to chronic diseases and will thus have a major impact on the Melanesian population in the
coming decades. A more comprehensive approach to macro- and micronutrient intakes, combined with
the assessment of physical activity levels and other lifestyle and sociodemographic factors, is needed.
The findings could be used to enhance health education programs in the schools and for families
in New Caledonia and other Pacific communities and perhaps for policy to maintain the healthier
traditional food supply.
Author Contributions:
O.G., A.N.-G., G.W., C.S.-M., M.A.-F. and S.F. conceived and designed the study. O.G.,
E.P., A.N.-G., F.W., G.W., P.-Y.L.R., S.P., P.Z., C.S.-M., S.F. collected data. O.G., G.W., S.F. conducted the statistical
analyses and O.G., E.P., A.N.-G., F.W., G.W., C.S.-M., M.A.-F., S.F., P.-Y.L.R. drafted the manuscript. All authors
have read and agreed to the published version of the manuscript.
Funding: The Fondation NestléFrance supported this study.
Acknowledgments:
We thank the school teaching teams and administrative stafffor their help and support in our
investigations, especially the Department ‘Promotion de la sant
é
en milieu scolaire’ of the Vice-Rectorat of New
Caledonia. We would like to thank Seila Muliava, Oriane Pourcelot, Malia Lasalo, Jeremy Sechet, Eloise Vendegou.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
McLennan, A.K.; Ulijaszek, S.J. Obesity emergence in the Pacific islands: Why understanding colonial history
and social change is important. Public Health Nutr. 2015,18, 1499–1505. [CrossRef] [PubMed]
2.
The Global Syndemic of Obesity, Undernutrition and Climate Change: The Lancet Commission
Report—The Lancet. Available online: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)
32822-8/fulltext (accessed on 4 December 2019).
3.
Regional Framework for Accelerating Action on Food Security and Nutrition in Pacific SIDS.
Available online: https://sustainabledevelopment.un.org/content/documents/17753PacificFramework.pdf
(accessed on 19 June 2020).
4.
Chen, M.-Y.; Wang, E.K.; Jeng, Y.-J. Adequate sleep among adolescents is positively associated with health
status and health-related behaviors. BMC Public Health 2006,6, 59. [CrossRef] [PubMed]
5.
Markwald, R.R.; Melanson, E.L.; Smith, M.R.; Higgins, J.; Perreault, L.; Eckel, R.H.; Wright, K.P. Impact of
insufficient sleep on total daily energy expenditure, food intake, and weight gain. Proc. Natl. Acad. Sci. USA
2013,110, 5695–5700. [CrossRef] [PubMed]
6.
Chapman, C.D.; Benedict, C.; Brooks, S.J.; Birgir Schiöth, H. Lifestyle determinants of the drive to eat:
A meta-analysis. Am. J. Clin. Nutr. 2012,96, 492–497. [CrossRef] [PubMed]
7.
Benedict, C.; Brooks, S.J.; O’Daly, O.G.; Almen, M.S.; Morell, A.; Aberg, K.; Gingnell, M.; Schultes, B.;
Hallschmid, M.; Broman, J.-E. Acute sleep deprivation enhances the brain’s response to hedonic food stimuli:
An fMRI study. J. Clin. Endocrinol. Metab. 2012,97, E443–E447. [CrossRef]
8.
St-Onge, M.-P. Sleep–obesity relation: Underlying mechanisms and consequences for treatment. Obes. Rev.
2017,18, 34–39. [CrossRef]

Nutrients 2020,12, 2047 13 of 14
9.
Frayon, S.; Cherrier, S.; Cavaloc, Y.; Wattelez, G.; Lerrant, Y.; Galy, O. Relationship of body fat and body mass
index in young Pacific Islanders: A cross-sectional study in European, Melanesian and Polynesian groups.
Pediatric Obes. 2017,13, 357–364. [CrossRef]
10.
Zongo, P.; Frayon, S.; Antoine-Jonville, S.; Wattelez, G.; Le Roux, P.-Y.; Hue, O.; Galy, O. Anthropometric
Characteristics and Physical Fitness in Rural and Urban 11- to 16-Year-Old Melanesian Adolescents:
A Cross-sectional Study in New Caledonian Schools. Asia Pac. J. Public Health
2017
,29, 589–598. [CrossRef]
11.
Frayon, S.; Cavaloc, Y.; Wattelez, G.; Cherrier, S.; Touitou, A.; Zongo, P.; Yacef, K.; Caillaud, C.; Lerrant, Y.;
Galy, O. Body image, body dissatisfaction and weight status of Pacific adolescents from different ethnic
communities: A cross-sectional study in New Caledonia. Ethn. Health 2017,25, 1–16. [CrossRef]
12.
Frayon, S.; Cavaloc, Y.; Wattelez, G.; Cherrier, S.; Lerrant, Y.; Ashwell, M.; Galy, O. Potential for waist-to-height
ratio to detect overfat adolescents from a Pacific Island, even those within the normal BMI range. Obes. Res.
Clin. Pract. 2017,12, 351–357. [CrossRef]
13.
Broustet, D.; Rivoilan, P. ISEE Structure de la Population et
É
volutions; Institut de la Statistique et des Etudes
Economiques—Nouvelle-Calédonie: Nouvelle-Calédonie, France, 2014.
14.
Leblic, I. Ignames, interdits et anc
ê
tres en Nouvelle-Cal
é
donie. J. Soc. Oc
é
an.
2002
,114–115, 115–127.
[CrossRef]
15.
Bouard, S.; Apithy, L.; Guyard, S. Family Farming in Contemporary Kanak Society. In Diversity of
Family Farming around the World: Existence, Transformations and Possible Futures of Family Farms; Bosc, P.-M.,
Sourisseau, J.-M., Bonnal, P., Gasselin, P., Valette,
É
., B
é
li
è
res, J.-F., Eds.; Springer: Dordrecht, The Netherlands,
2018; pp. 285–296. ISBN 978-94-024-1617-6.
16.
Sabinot, C.; David, G.; Juncker, M.; Bouard, S.; Fossier, C.; Mallet, J.; Kombouare, F. P
ê
ches identitaires,
nourrici
è
res et commerciales dans les
é
cosyst
è
mes r
é
cifaux. In Nouvelle-Cal
é
donie: Archipel de Corail;
Payri, C., Ed.; IRD: Marseille, France, 2018; pp. 191–198.
17.
HLPE. Nutrition and Food Systems. A Report by the High Level Panel of Experts on Food Security and Nutrition of
the Committee on World Food Security; Committee on World Food Security: Rome, Italy, 2017; p. 152.
18.
FAO; IFAD; UNICEF; WFP; WHO. The State of Food Security and Nutrition in the World 2018. Building Climate
Resilience for Food Security and Nutrition; FAO: Rome, Italy, 2018.
19.
Anon. Pacifc Guidelines for Healthy Living: A Handbook for Health Professionals and Educators;
Pacific Community (SPC): Noumea, New Caledonia, 2017; 44p.
20.
Wattelez, G.; Frayon, S.; Cavaloc, Y.; Cherrier, S.; Lerrant, Y.; Galy, O. Sugar-Sweetened Beverage Consumption
and Associated Factors in School-Going Adolescents of New Caledonia. Nutrients
2019
,11, 452. [CrossRef]
[PubMed]
21.
Frayon, S.; Cherrier, S.; Cavaloc, Y.; Touitou, A.; Zongo, P.; Wattelez, G.; Yacef, K.; Caillaud, C.; Lerrant, Y.;
Galy, O. Nutrition behaviors and sociodemographic factors associated with overweight in the multi-ethnic
adolescents of New Caledonia. Ethn. Health 2017,24, 1–17. [CrossRef] [PubMed]
22.
Galy, O.; Yacef, K.; Caillaud, C. Improving Pacific Adolescents’ Physical Activity toward International
Recommendations: Exploratory Study of a Digital Education App Coupled with Activity Trackers.
JMIR mHealth uHealth 2019,7, e14854. [CrossRef] [PubMed]
23.
Hirshkowitz, M.; Whiton, K.; Albert, S.M.; Alessi, C.; Bruni, O.; DonCarlos, L.; Hazen, N.; Herman, J.;
Katz, E.S.; Kheirandish-Gozal, L. National Sleep Foundation’s sleep time duration recommendations:
Methodology and results summary. Sleep Health 2015,1, 40–43. [CrossRef] [PubMed]
24.
Frayon, S.; Cherrier, S.; Cavaloc, Y.; Wattelez, G.; Touitou, A.; Zongo, P.; Yacef, K.; Caillaud, C.; Lerrant, Y.;
Galy, O. Misperception of weight status in the pacific: Preliminary findings in rural and urban 11-to
16-year-olds of New Caledonia. BMC Public Health 2017,17, 25. [CrossRef] [PubMed]
25.
Cole, T.J.; Lobstein, T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and
obesity. Pediatric Obes. 2012,7, 284–294. [CrossRef]
26.
Hamelin, C.; Salomon, C.; Lert, F.; Vignier, N.; Bonenfant, S.; Kanieswski, N.; Carole, C. Situation
sociale et comportements de sant
é
des jeunes en Nouvelle-Cal
é
donie. In INSERM; H
ô
pital Paul Brousse:
Villejuif, France, 2008.
27.
Krieger, N. A Researcher’s Guide to the National Statistics Socio-Economic Classification; Palgrave Macmillan
Journals: Basingstoke, UK, 2003; ISBN 0197-5897.

Nutrients 2020,12, 2047 14 of 14
28.
The European Union Labour Force Survey—Methods and Definitions—2001 (Eurostat, Guidelines, Labour
Statistics, Survey). Available online: https://unstats.un.org/unsd/EconStatKB/KnowledgebaseArticle10230.
aspx (accessed on 4 December 2019).
29.
Gwynn, J.D.; Flood, V.M.; D’Este, C.A.; Attia, J.R.; Turner, N.; Cochrane, J.; Wiggers, J.H. The reliability and
validity of a short FFQ among Australian Aboriginal and Torres Strait Islander and non-Indigenous rural
children. Public Health Nutr. 2011,14, 388–401. [CrossRef]
30.
R: A Language and Environment for Statistical Computing. Available online: https://www.gbif.org/fr/tool/
81287/r-a-language-and-environment-for-statistical-computing (accessed on 4 December 2019).
31.
Australian Health Survey: Nutrition First Results—Food and Nutrients, 4364.0.55.007-2011-12.
Available online: https://www.abs.gov.au/ausstats/abs@.nsf/lookup/4364.0.55.007main+features12011-12
(accessed on 4 December 2019).
32.
Swinburn, B.A.; Kraak, V.I.; Allender, S.; Atkins, V.J.; Baker, P.I.; Bogard, J.R.; Brinsden, H.; Calvillo, A.;
Schutter, O.D.; Devarajan, R.; et al. The Global Syndemic of Obesity, Undernutrition, and Climate Change:
The Lancet Commission report. The Lancet 2019,393, 791–846. [CrossRef]
33.
Johnson, B.J.; Bell, L.K.; Zarnowiecki, D.; Rangan, A.M.; Golley, R.K. Contribution of Discretionary Foods
and Drinks to Australian Children’s Intake of Energy, Saturated Fat, Added Sugars and Salt. Children
2017
,
4, 104. [CrossRef]
34.
Swinburn, B.A.; Caterson, I.; Seidell, J.C.; James, W.P.T. Diet, nutrition and the prevention of excess weight
gain and obesity. Public Health Nutr. 2004,7, 123–146. [PubMed]
35.
Kant, A.K. Reported Consumption of Low-Nutrient-Density Foods by American Children and Adolescents:
Nutritional and Health Correlates, NHANES III, 1988 to 1994. Arch. Pediatr. Adolesc. Med.
2003
,157, 789–796.
[CrossRef] [PubMed]
36.
Webb, K.L.; Lahti-Koski, M.; Rutishauser, I.; Hector, D.J.; Knezevic, N.; Gill, T.; Peat, J.K.; Leeder, S.R.;
Team, C. Consumption of ‘extra’ foods (energy-dense, nutrient-poor) among children aged 16–24 months
from western Sydney, Australia. Public Health Nutr. 2006,9, 1035–1044. [CrossRef] [PubMed]
37.
Satterthwaite, D.; McGranahan, G.; Tacoli, C. Urbanization and its implications for food and farming.
Philos. Trans. R. Soc. B Biol. Sci. 2010,365, 2809–2820. [CrossRef] [PubMed]
38.
Serra-Mallol, C. Bien manger, c’est manger beaucoup: Comportements alimentaires et repr
é
sentations
corporelles àTahiti. Sci. Soc. Santé2008,26, 81–112.
39.
Newby, P.K. Are Dietary Intakes and Eating Behaviors Related to Childhood Obesity? A Comprehensive
Review of the Evidence. J. Law Med. Ethics 2007,35, 35–60. [CrossRef] [PubMed]
40.
Sun, C.; Pomer, A.; Dancause, K.N.; Chan, C.W.; Olszowy, K.M.; Silverman, H.; Lee, G.; Tarivonda, L.;
Taleo, G.; Regenvanu, R. Ownership of consumer electronics is associated with measures of adiposity during
health transition in Vanuatu. Am. J. Hum. Biol. 2017,29, e22928. [CrossRef]
41.
Eagle, L.; Bulmer, S.; De Bruin, A.; Kitchen, P.J. Exploring the link between obesity and advertising in New
Zealand. J. Mark. Commun. 2004,10, 49–67. [CrossRef]
42.
Becker, A.E.; Burwell, R.A.; Herzog, D.B.; Hamburg, P.; Gilman, S.E. Eating behaviours and attitudes
following prolonged exposure to television among ethnic Fijian adolescent girls. Br. J. Psychiatry
2002
,180,
509–514. [CrossRef]
43.
Sleep Duration and Obesity in Children: A Systematic Review and Meta-Analysis of Prospective Cohort
Studies—Li—2017—Journal of Paediatrics and Child Health—Wiley Online Library. Available online:
https://onlinelibrary.wiley.com/doi/full/10.1111/jpc.13434 (accessed on 4 December 2019).
44.
Li, L.; Zhang, S.; Huang, Y.; Chen, K. Sleep duration and obesity in children: A systematic review and
meta-analysis of prospective cohort studies. J. Paediatr. Child Health 2017,53, 378–385. [CrossRef]
45.
Bayon, V.; Leger, D.; Gomez-Merino, D.; Vecchierini, M.-F.; Chennaoui, M. Sleep debt and obesity. Ann. Med.
2014,46, 264–272. [CrossRef] [PubMed]
46.
Kjeldsen, J.S.; Hjorth, M.F.; Andersen, R.; Michaelsen, K.F.; Tetens, I.; Astrup, A.; Chaput, J.-P.; Sjödin, A.
Short sleep duration and large variability in sleep duration are independently associated with dietary risk
factors for obesity in Danish school children. Int. J. Obes. 2014,38, 32. [CrossRef] [PubMed]
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