European Journal of Pediatrics
https://doi.org/10.1007/s00431-022-04604-7

ORIGINAL ARTICLE

Analysis of spot urine biomarkers and association with body weightin Japanese elementary schoolchildren
Nozomi Takemoto1 · Jasmine Millman1 · Tsugumi Uema1 · Fusae Yamakawa1 · Shiki Okamoto1 · Mari Mori2 ·Hideki Mori3 · Koshi Nakamura4 · Yukio Yamori3 · Hiroaki Masuzaki1
Received: 24 February 2022 / Revised: 17 August 2022 / Accepted: 29 August 2022
© The Author(s) 2022

Abstract
Childhood obesity is rapidly increasing worldwide and is largely the consequence of adoption of unhealthy diets excessive incalories and salt (NaCl) as well as devoid in pivotal micronutrients such as potassium (K) and magnesium (Mg). Educationbased programs aiming to encourage healthy food knowledge and behaviors are crucial at a young age, and for this purpose, convenient ways to assess daily dietary intake are warranted. We therefore attempted to evaluate the dietary intake of
Okinawan schoolchildren in Japan by analyzing a series of biomarkers in morning spot urine samples and explore whether
these biomarkers correlate with body weight and a series of metabolic parameters. We enrolled 98 third-grade elementary
schoolchildren in Okinawa, Japan. Morning spot urine samples were collected and analyzed using high-performance liquid
chromatography (HPLC) to assess dietary intake. We found that estimated daily NaCl intake was higher in obese/overweightchildren as compared to healthy-weight children (p = 0.0001). There was also a significant positive correlation between bodymass index (BMI) and NaCl intake (Spearman) (ρ = 0.45, p < 0.0001) and a negative correlation between BMI and Mg/
Cr (ρ =  −0.27, p = 0.01). Furthermore, Na/K ratio was higher in samples collected on Monday (weekend) as compared tosamples collected on Thursday or Friday (weekday) (p < 0.0001).
Conclusion: Via the use of morning spot urine analyses, our results show that NaCl intake was associated with obesity,and Mg excretion negatively correlated with BMI in Japanese schoolchildren, highlighting the potential role of these micronutrients in maintaining a healthy body weight.
What is Known:•Overweight and obesity are largely due to excessive consumption of calories and positively correlated with salt (NaCl) intake.
•Spot urine methods are convenient for assessing the nutritional needs and targeting prevention programs in children.
What is New:
•Utilizing morning spot urine analyses, estimated NaCl intake is positively correlated and Mg/Cr negatively correlated with BMI in Okinawan
schoolchildren.
•As estimated via morning spot urine samples, a greater proportion of children likely exceeds the recommended NaCl intake on the weekend
as compared to weekday.

Keywords Spot urine · Salt · Magnesium · Body mass index · Obesity
Communicated by Peter de Winter* Jasmine Millman
Jasmine.f.millman@gmail.com

2

Department of Health Management, School of HealthStudies, Tokai University, Kanagawa, Japan* Tsugumi Uema
ma2.ky8.26@gmail.com

3

Institute for World Health Development, Mukogawa
Women’s University, Hyogo, Japan* Hiroaki Masuzaki
hiroaki@med.u-ryukyu.ac.jp

4

Department of Public Health and Hygiene, Graduate Schoolof Medicine, University of the Ryukyus, Okinawa, Japan

1

Division of Endocrinology, Diabetes and Metabolism,
Hematology, Rheumatology, Second Department of Internal
Medicine), Graduate School of Medicine, Universityof the Ryukyus, 207 Uehara, Nishihara, Okinawa 903‑0215, Japan

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European Journal of Pediatrics

Abbreviations
BMI	Body mass index
BP	Blood pressureUN	Urea nitrogen
Cr	Creatinine
CRP	C-reactive protein
HPLC	High-performance liquid chromatography
Iso	Isoflavones
K	Potassium
Mg	Magnesium
Na	Sodium
NaCl	Sodium chloride (salt)
SD	Standard deviation
Tau	Taurine
TNF-α	Tumor necrosis factor-alphaWHO	World Health Organization

Introduction
The prevalence of childhood obesity has been swiftly
increasing worldwide. Recent global estimates suggest thatapproximately 340 million children and adolescents aged
5–19 years are classified as overweight or obese [1], withseveral studies reporting that approximately 40–50% ofobese children go onto develop obesity later in adulthood[2–4], putting this group at an elevated risk for developing
type 2 diabetes and related cardiometabolic diseases laterin life [5].
Although Japan has experienced a relatively low prevalence of obesity compared to other developed countries,
Okinawa, a prefecture in the southernmost part of Japan,
once renowned as being home to some of the healthiest andlongest living people in the world, is now facing a stark
increase in obesity and metabolic diseases in both adults
and children [6]. This undesirable trend has resulted in an
expedition decline in life expectancy in Okinawan people[7]. According to the School Health Survey Japan, approximately 9.2% of 8-year-old boys and girls in Okinawa areobese [8], which is considerably higher compared to thenational average of 8.2% (boy) and 6.9% (girl) [9]. Reasonsfor such an alarming figure largely stem from westernizationof the food culture, with increased availability and consumption of energy-dense, high salt– (sodium chloride, NaCl)containing foods such as fried foods and pastries and displacement of the traditional Okinawan diet naturally abundant in micronutrient-rich plant foods such as seaweeds,
sweet potato, soy products, and moderate amounts of fishand seafood [7].
Excessive intake of NaCl is one of the main dietaryfactors diving increases in high blood pressure and cardiovascular diseases [10], with its intake found to be

13

positively correlated with BMI independent of energy
intake in adults [11]. Currently, Japanese people typically consume ~10 g per day of NaCl, more than twice asmuch as the upper 5 g daily limit advised by the World
Health Organization [12, 13]. Along with reducing NaCl,
increasing intake of micronutrients such as potassium andmagnesium can also positively impact blood pressure
and associated disease risks [14]. Given that obesity andrelated diseases often start to develop in early childhood,methods that accurately capture dietary intake profile andare easy to implement are warranted for assessing thenutritional needs and appropriately targeting prevention
programs.
Although accurate execution of dietary records and foodfrequency questionnaire methods require both skilled professionals and participant’s cooperation, assessment of biomarkers in urine offers a convenient and reliable alternative
to assess dietary intake of specific nutrients, especially asa public health strategy [12]. In this context, we aimed toassess urinary biomarkers associated with nutrient intake
utilizing morning spot urine samples of Okinawan elementary schoolchildren and explore the potential links withobesity.

Methods
Study design and participants
The present study was carried out in a cross-sectional fashion, recruiting in 231 third-grade elementary schoolchildren,
8–9 years old, from two elementary schools in Okinawa prefecture, Japan, from November 2019 to January 2020. A
total of 98 children (49 boys and 49 girls) were enrolled andasked to provide spot urine samples at four time points aswell as measuring anthropometric indices and blood pressure. Exclusion criteria were as follows: (1) presence ofacute or chronic kidney disease and or (2) bronchial asthma
and the relevant regular use of corticosteroids for the treatment. None of the children met the exclusion criteria. However, we excluded 17 children (5 boys and 12 girls) who
provided only one sample across the four time points. Consequently, the remaining 81 children (44 boys and 37 girls)
were considered eligible study participants and included in
the subsequent analyses.
Ethics approval was obtained by the Ryukyu University
Human Research Ethics Committee (approval number: 360,
25 October 2019). Written informed consent was obtained
from all participants and their parent (or legal guardians).
This study was carried out in accordance with the Helsinki
Declaration.

European Journal of Pediatrics

Assessment of a series of biomarkers in urine
Spot urine samples were collected on Monday mornings
to assess weekend eating habits, and Thursday or Friday
mornings to assess weekday eating habits. Urine samples
were collected over a total of four time points: 1st, Monday
November 2019; 2nd, Thursday or Friday, November 2019;
3rd, Monday January and 2020; and 4th, Thursday or Friday,
November 2020.
Each spot urine sample was collected in 10-mL tubes atparticipants’ home, brought to each school and stored at a
4 °C. Samples were then transferred into either an 8-mL
tubes or 1-mL tube. Eight-mL samples were stored at 4 °C
and 1-mL samples were stored at −80 °C. Eight-mL tube
samples were sent to FALCO Biosystems, Ltd. (Tokyo,
Japan) to determine the level of pH, urea nitrogen (UN),creatinine (Cr), sodium (Na), potassium (K), and magnesium(Mg). One-mL tube samples were sent to Mukogawa Women’s University (Hyogo, Japan) for analyses of isoflavones(Iso) and taurine (Tau) by HPLC. Briefly, HPLC analyses
were performed to assess the urinary value of the common
dietary isoflavonoids including daidzein, genistein, andglycitein as previously described, and the sum of daidzein,
genistein, glycitein, and equol was calculated as the total
concentration of Iso [15, 16]. Salt intake (NaCl [g/day]) was
estimated using Tanaka et al.’s equation [17].

Measurements of anthropometric indices and bloodpressure
Body height and weight were measured, and body massindex (BMI) was computed as weight (kg) per the squareof height (m). BMI values were converted to age-adjusted
and sex-adjusted BMI z-scores from WHO References 2007[18]. According to the WHO BMI-for-age growth charts,
children were classified as underweight (less than −2SD),
normal weight (−2SD to less than 1SD), overweight (1SD,
equivalent to BMI 25 kg/m2 at 19 years, to less than 2SD) or
obese (over 2SD, equivalent to BMI 30 kg/m2 at 19 years).
Blood pressure (BP) was measured in the seated position
using an automatic manometer (HBP-1300, Omron Healthcare Co., Ltd, Kyoto, Japan) on three separate occasions overthe course of the study by trained researchers.

Statistical analysis
For participants providing multiple urine samples, we calculated the average of concentration of specific biomarkers
from 1st to 3rd urine samples on Monday to assess weekend dietary intake (A), and the average of concentrationof specific biomarkers from 2nd to 4th urine samples oneither Thursday or Friday to assess weekday dietary intake(B). For participants providing a single urine sample oneither 1st or 3rd time point, as well as on either 2nd or 4thtime point, the concentration of specific urinary biomarkers from the single urine sample was used for (A) and (B),respectively. Taken together, we used the average of (A)and (B) as the result of specific urinary biomarkers and
NaCl.
Data regarding subject characteristics are presented collectively as well as separately for boys and girls. Urinary
biomarkers were also compared between healthy weight
and obese/overweight children and are shown. Data areexpressed as mean ± standard deviation or median and 25thand 75th percentiles. Unpaired t-test was used for normal
distribution data, while Wilcoxon test was used for skewed
distribution data. Spearman’s rank correlation coefficientswere used to assess correlations between each urinary
biomarker and BMI. A similar correlation method was
performed as a sensitivity analysis utilizing participants’urine samples that were collected across all of four time
points. Finally, biomarkers in urine samples were compared
between weekend and weekday to examine whether variation of eating habits may be potentially influenced by school
lunch or “Kyushoku.”
All probability values were two-tailed, and the significance level was set at p < 0.05. All statistical analyses werecarried out using standard software packages (JMP pro version 15; SAS Institute Inc., Cary, NC, USA).

Results
Characteristics of study participants
The average weight of the children was 29.4 ± 5.5 kg, andthe average height was 131.6 ± 5.8 cm, respectively. No statistical differences in parameters were observed between
boys and girls (Table 1). According to BMI z-score, 4 boys
were classed as obese, and 6 boys and 3 girls were classed
as overweight. There were no participants classed as underweight. However, some urinary biomarkers reflecting dietaryintake showed statistically significant differences between
boys and girls, including Na/Cr (boys 124.2 mEq/gCr versus
girls 109.0 mEq/gCr, p = 0.01) and K/Cr (boys 28.5 mEq/
gCr versus girls 23.8 mEq/gCr, p = 0.0085) (Table 2).

Anthropometric indices and urinary biomarkers
Table 3 shows anthropometric indices and blood pressurecomparing healthy weight with obese/overweight children.
Statistically significant differences were observed not only
for weight, but also for height (healthy weight: 130.8 cm

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European Journal of Pediatrics
Table 1  Characteristics of thestudy participants

Height (cm)Weight (kg)BMI (kg/m2)
BMI z-scorea
Obese (n)bOverweight (n)c
Underweight (n)dSystolic BP (mmHg)
Diastolic BP (mmHg)

Total (n = 81)

Boys (n = 44)

Girls (n = 37)

p value131.6 ± 5.8
29.4 ± 5.5
16.9 ± 2.2
0.16 ± 1.0490
104 ± 957 ± 6

131.6 ± 6.1
30.1 ± 6.4
17.2 ± 2.6
0.3 ± 1.146
0
105 ± 957 ± 7131.7 ± 5.5
28.6 ± 4.0
16.4 ± 1.6-0.05 ± 0.8030103 ± 957 ± 6

0.93
0.21
0.10
0.09

0.32
0.70

Values are shown as mean ± standard deviation (SD). Unpaired t-test was used to compare each characteristic in each sex groupa
BMI values were converted to age-adjusted and sex-adjusted BMI z-score according to WHO 2007 references [18]bcdTable 2  Urine biomarkers andestimated salt (NaCl) intake inboys and girls

Obese: > +2SD (equivalent to BMI 30 kg/m2 at 19 years)

Overweight: > +1SD (equivalent to BMI 25 kg/m2 at 19 years)
Underweight: < −2sdpH
UN (mg/dL)
Cr (mg/dL)
Na/Cr (mEq/gCr)
K/Cr (mEq/gCr)
Mg/Cr (mEq/gCr)
NaCl (g/day)
Na/K
Iso/Cr (nmol/mgCr)
Tau/Cr (nmol/mgCr)

Total (n = 81)

Boys (n = 44)

Girls (n = 37)

p value

6.0 (5.875–6.25)
1234.8 ± 271.0
120.7 ± 37.8
118.2 (93.0–156.3)
25.5 (21.5–38.5)
13.7 (11.7–16.2)
5.0 (4.3–5.9)
4.6 (3.7–6.4)
Total (n = 75)
19.1 (10.3–34.6)
762.5 (550.0–1040.4)

6.0 (5.875–6.26)
1269.8 ± 284.9
114.3 ± 36.6
124.2 (98.4–174.4)
28.5 (22.9–42.1)
13.7 (11.3–17.0)
5.1 (4.3–6.4)
4.6 (3.7–6.2)
Boys (n = 42)
18.2 (10.1–37.4)
737.8 (497.1–985.3)

6.0 (5.8125–6.4375)
1193.2 ± 251.0
128.3 ± 6.3
109.0 (78.8–131.1)
23.8 (20.6–29.6)
13.4 (11.9–15.7)
4.6 (4.3–5.6)
4.6 (3.6–6.4)
Girls (n = 33)
19.8 (11.2–32.7)
766.7 (569.4–1065.1)

0.68
0.21
0.10
0.01
<0.01
0.99
0.07
0.95
p value
0.75
0.41

Values are presented as median (25th and 75th percentiles) or mean ± standard deviation (SD). Wilcoxon
test or unpaired t-test was used to compare each characteristic in each sex groupversus obese/overweight: 135.7 cm, p = 0.0053) (Table 3).
However, blood pressure levels were apparently similar for
healthy weight and obese/overweight children. NaCl intake
was significantly different between healthy weight andobese/overweight children (healthy weight: 4.7 g/day versus obesity/overweight:6.0 g/day, p = 0.0001) (Table 4). As
illustrated in Fig. 1, there was a positive correlation between
BMI and NaCl (ρ = 0.45, p < 0.0001) (Fig. 1a) and a negative correlation between BMI and urinary Mg/Cr (ρ =  −0.27,
p = 0.01) (Fig. 1b).
When performing a sensitivity analysis using only biomarker data from subjects’ urine samples that were collectedacross all four time points (n = 42), a moderate positive correlation between BMI and NaCl (ρ = 0.61, p < 0.0001) andslightly negative correlation between BMI and urinary Mg/
Cr (ρ =  −0.23, p = 0.14) were found.

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Table 3  Characteristics of obese/overweight and healthy-weight children
Obese/overweight (n = 13)
Height (cm)Weight (kg)BMI (kg/m2)
BMI z-scorea
Systolic BP (mmHg)
Diastolic BP (mmHg)

135.7 ± 4.0
38.7 ± 4.9
21.0 ± 1.7
1.9 ± 0.6
106 ± 958 ± 6

Healthyweight(n = 68)130.8 ± 5.8
27.6 ± 3.4
16.1 ± 1.2−0.2 ± 0.7
104 ± 957 ± 6p value

<0.01
<0.01
<0.01
<0.01
0.41
0.68

Values are shown as mean ± standard deviation (SD). Unpaired t-test
was used to compare each characteristic in each weight groupa

BMI values were converted to age-adjusted and sex-adjusted BMI
z-score according to WHO 2007 references [18]European Journal of Pediatrics
Table 4  Selected urine
biomarkers and estimatedsalt (NaCl) intake in obese/
overweight and healthy-weightchildrenpH
UN (mg/dL)
Cr (mg/dL)
Na/Cr (mEq/gCr)
K/Cr (mEq/gCr)
Mg/Cr (mEq/gCr)
NaCl (g/day)
Na/K
Iso/Cr (nmol/mgCr)
Tau/Cr (nmol/mgCr)

Obese/overweight (n = 13)

Healthy-weight (n = 68)

p value

6.0 (5.625–6.0)
1301.6 ± 316.1
122.6 ± 34.4
108.7 (91.1–159.8)
38.9 (23.5–43.1)
12.4 (10.8–14.0)
6.0 (5.4–7.3)
4.2 (3.4–5.2)
Obese/overweight (n = 13)
13.9 (10.0–20.4)
596.0 (482.5–956.9)

6.0 (5.875–6.25)
1222.1 ± 262.2
120.4 ± 38.7
119.6 (92.0–159.2)
25.1 (21.4–34.1)
13.9 (11.8–17.0)
4.7 (4.2–5.5)
4.7 (3.8–6.5)
Healthy-weight (n = 62)
20.1(10.5–35.4)
778.6 (579.3–1041.4)

0.01
0.33
0.85
0.72
0.07
0.06
<0.01
0.11
p value
0.21
0.22

Values are presented as median (25th and 75th percentiles) or mean ± standard deviation (SD). Wilcoxon
test or unpaired t-test was used to compare each characteristic in each weight group

Fig. 1  Spearman’s rank correlation coefficient showing
significant correlations between
BMI and estimated salt intake(a), and between BMI and urine
Mg/Cr concentration (b), as
evaluated by spot urine analyses

Table 5  Selected urine
biomarkers and estimated salt
(NaCl) intake on weekend andweekdaypH
UN (mg/dL)
Cr (mg/dL)
Na/Cr (mEq/gCr)
K/Cr (mEq/gCr)
Mg/Cr (mEq/gCr)
NaCl (g/day)
Na/K
Iso/Cr (nmol/mgCr)
Tau/Cr (nmol/mgCr)

Weekend (n = 81)

Weekday (n = 81)

p value

6.0 (6.0–6.5)
1250.8 ± 291.8
123.1 ± 42.9
130.6 (89.7–173.1)
24.1 (17.3–34.7)
14.9 (10.9–16.9)
5.2 (4.3–6.2)
5.4 (3.9–7.3)
Weekend (n = 75)
12.5 (5.7–28.9)
716.3 (422.6–1026.1)

6.0 (5.75–6.25)
1218.9 ± 344.5
118.3 ± 43.1
107.6 (79.7–139.4)
26.8 (221.3–38.4)
13.4 (11.2–15.5)
4.8 (4.0–5.6)
3.8 (2.9–5.0)
Weekday (n = 75)
21.5 (12.1–36.6)
781.0 (525.8–1028.4)

0.09
0.53
0.48
0.02
0.06
0.21
0.10
<0.01
p value<0.01
0.32

Values are presented as median (25th and 75th percentiles) or mean ± standard deviation (SD). Wilcoxon
test or unpaired t-test was used to compare each characteristic in groups as classified according to sample
collection time points

13European Journal of Pediatrics
Fig. 2  Distribution of the valueof estimated salt intake on
weekend (a) and on weekday(b), as evaluated by spot urine
analyses and calculated using
Tanaka et al.’s equation [17]Measurement of urinary biomarkers across time
pointsBoth Na/Cr excretion level and Na/K ratio were significantly
elevated in weekend as opposed to weekday samples (Na/Cr:
130.6 mEq/gCr versus 107.6 mEq/gCr, p < 0.0001), (Na/K:
5.4 versus 3.8, p < 0.0001), and Iso/Cr excretion level was
significantly lower in weekend as compared to weekday samples (12.5 nmol/mgCr versus 21.5 nmol/mgCr, p = 0.0047)(Table 5). Although there were no statistically significant
differences in estimated NaCl intake between weekend andweekday samples, the percentage of participants with NaCl
intake estimated at ≥ 5 g/day was apparently greater in weekend as compared to weekday samples (weekend 54% versus
weekday 38%) (Fig. 2).

Discussion
The present study showed a moderately significant positive
correlation between NaCl intake and BMI, and a slightly
significant negative correlation between Mg/Cr excretion
and BMI in Okinawan schoolchildren. Research in pooledurine samples in humans has demonstrated that Na concentration reflects salt intake, K concentration reflects
the intake of vegetables and fruits, and Mg concentrationreflects the intake of unrefined whole grains such as brown
rice, seeds, and seaweeds [19–21]. Although 24-h urine
collection has been the standard that accurately captures
the profile of dietary intake, in recent years, it has beenreported that highly reproducible results can be obtainedwith spot urine collection and analytic methodologies[17, 22–24]. Based on these notions, in the present studyof spot urine analyses, we did observe a number of significant differences in measurements of specific urinary
biomarkers and estimated dietary micronutrient intakes in

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Okinawan schoolchildren when considering gender, BMI,
and weekend versus weekday sampling. Regarding genderdifferences, boys showed a significantly higher value of
urinary Na/Cr and K/Cr than girls. These results are inagreement with a larger sized study which recruited 766
Italian boys and 658 girls aged 6–18 years at National
Health Service Centers across 10 regions, and 24-h urine
collection found that boys across all developmental ages
showed a significantly higher value of estimated NaCl andK intakes than girls [20]. As the children in our study
were of pre-pubescent age, it is unlikely that such a genderdimorphism is due to sexual development or subsequent
influence of sex hormones, but presumably more so a consequence of the increased amount of food boys consume
as compared to girls [25].
When stratified subjects according to BMI in spot urine
analyses, we observed significantly lower urine pH and significantly higher estimated NaCl intake in obese/overweightchildren compared to healthy weight children. In support ofthis, a cross-sectional study employing 5430 Japanese subjects using fasting single spot urine found that subjects withcomponents of the Metabolic Syndrome were significantly
associated with lower urine pH [26]. On top of this, 524
children (aged 6–17 years) in the Dortmund Nutritional andAnthropometric Longitudinally Designed (DONALD) Studyin Germany also reported a significant inverse relationshipwith fat mass and urinary pH [27]. Concerning the elevated
NaCl intake in obese/overweight children observed in ourstudy, this is in line with a number of previous studies showing that NaCl intake is higher in obese and overweight adults
as well as children [28–32].
Following on from this point, the level of estimated
NaCl intake in spot urine analyses was positively associated with BMI in Okinawan schoolchildren. This finding
is consistent with a number of previous larger, populationbased studies in adults showing that NaCl excretion wasEuropean Journal of Pediatrics

positively associated with body weight as well as central
obesity even after controlling for energy intake [33–35].
Other previous studies also observed the same results inchildren [36, 37]. Specifically, a large study with 1738
boys aged 10–18 years from the Korea National Health andNutrition Examination found that subjects in the highest
quartile for urinary sodium excretion to urinary gravity
specific ratio (a representative for sodium intake) showedsignificantly higher body weight, BMI, and waist circumference among groups [37]. Also, a cross-sectional studyof 374 Iranian children aged 11–18 years found that 24-h
urinary Na/K ratio showed significantly positive associations with value of waist circumference and percentage ofbody fat even after adjusting for sugar sweetened beverage
consumption or calorie intake [36]. Although our study
cannot rule out the possibility that estimated higher NaCl
intake in children with higher BMI is due to increased
consumption of highly processed, energy dense foods, aline of plausible mechanisms has been proposed regarding the independent relationship between NaCl intake andoverweight/obesity. Firstly, high NaCl intake is associatedwith increased urinary cortisol [38, 39] also in children[40]. Mechanism-oriented studies in mice show that high
NaCl intake can stimulate aldose reductase–fructokinase
pathway in both liver and hypothalamus, causing endogenous fructose production, subsequent leptin resistance,and hyperphagia, resulting in obesity [41]. Such a mechanism has been commonly observed in humans with healthy
subjects consuming diets high NaCl, prone to developing type 2 diabetes and non-alcoholic fatty liver disease(NAFLD) [41].
Noticeably, we found that the Mg excretion levelsin spot urine were inversely associated with BMI in
Okinawan schoolchildren. These findings are also supported by previous population-based studies indicatingthat lower intake of Mg is associated with higher BMI[42–44]. Although there has not been enough data inchildren linking urinary excretion level of Mg with bodyweight, lower levels of serum Mg were shown to be significantly lower in both obese children and adolescents compared to healthy weight controls [45]. Several mechanisms
are postulated as to how lower levels of Mg in urine samples may potentially relate with increased body weight.
Firstly, Mg deficiency is tightly linked with an increasein a number of inflammatory markers including CRP and
TNF-α in obese humans [46]. Mechanism-oriented studies
in animals showed that Mg deficiency leads to an inflammatory response primarily via increasing intracellular calcium, which in turn causes priming of immune cells suchas leukocytes and macrophages, resulting in a variety of
inflammatory responses [47]. In addition, Mg is crucial
for regulating several key enzymes involved in glucose

metabolism [48]. In particular, Mg deficiency increases
anaerobic metabolites such as lactate within adipocytes,
leading to an increased triglyceride storage and insulin
resistance in adipose tissue [49, 50].
Intriguingly in the present study, a significant increasein urinary sodium and Na/K ratio as well as a significant
decrease in level of urinary isoflavones was observed in
the weekend compared to the weekday in spot urine samples. In support of our data, a study of Japanese preschool
children employing spot urine collection found that the
Na excretion level as well as Na/K ratio was significantly
higher on the weekend compared to the weekday [51].
Similarly, a cross-sectional study of Australian schoolchildren assessing electrolyte intake by 24-h urine discovered that NaCl intake was roughly 1.0 g/day higher
on non-school days versus school days [52]. Regarding
the analysis of other measured biomarkers in urine, weekend Iso excretion levels in our study were comparable toprevious studies in Japanese preschool children reportingthat mean Iso intakes range between 12 mg/d and 14 mg/d[53]. This notion raises a possibility that weekday Iso levels are significantly higher due to the inclusion of school
lunch or “Kyushoku” featuring isoflavone-rich soy foods
in Japan, thereby contributing to overall improved dietquality [54]. In contrast, our study in spot urine samples
observed no statistically significant differences in taurine
excretion levels, a validated biomarker of taurine-rich seafood and fish intake, between weekend and weekday samples. These findings may be a reflection of the substantial
lack of seafood and fish featured in the diets of Okinawan
schoolchildren both during the weekday including school
lunches and also on weekends. In fact, a study assessing
seafood intake as measured by urinary excretion of Tau inschoolchildren in mainland Japan showed that Tau/Cr level
was higher compared to levels observed in our study [23].
There are a couple of limitations in the present study.
Firstly, without collection of dietary intake data using
validated assessment tools, we are unable to report on
the intercorrelations among urinary biomarkers, dietaryintake, and level of obesity. However, it should be notedthat our results are well consistent with previous studies
that employed urine analyses in combination with validated dietary intake assessment tools [43, 44, 54]. Secondly, as this study was cross-sectional, causal inference
cannot be assumed regarding the temporal link between
obesity and intake of specific micronutrients, and also,
limited number of subjects reduced the power of the study.
Finally, our study population was comprised of children
residing in the southern island community of Japan with adistinctly different climate and culture compared to otherJapanese communities and therefore should be taken thispoint into consideration.

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European Journal of Pediatrics

Conclusion
In Okinawan schoolchildren, high dietary intake of NaCl andlow intake of Mg as estimated by spot urine analyses were significantly associated with body weight, suggesting a pivotal roleof dietary electrolyte intake in the management of healthy bodyweight. Also, the lower dietary intake of NaCl on weekdays
as opposed to weekends may suggest the positive influence ofweekday school lunches in this population group. Overall, ourresults open up a potentially fresh avenue to expand food-based
education programs in schoolchildren at the risk of obesity,
further supporting the significance of Japanese school lunch inhelping to improve the overall diet quality of children.
Acknowledgements We thank the board of education of Okinawa prefecture for introducing two elementary schools and third-grade elementary schoolteachers and nursing teachers for their enthusiastic support.
We are grateful to T. Ikematsu, Y. Inamine, M. Hirata, and C. Noguchi
for secretarial assistance.
Authors’ contributions All authors contributed to the study conception anddesign. Material preparation and data collection were performed by Nozomi
Takemoto, Fusae Yamakawa, and Tsugumi Uema. Analysis of samples
was conducted by Mari Mori and Hideki Mori. Statistical analyses were
performed by Nozomi Takemoto and Fusae Yamakawa under the supervision of Koshi Nakamura. The first draft of the manuscript was written
by Nozomi Takemoto and Jasmine Millman. Nozomi Takemoto, Jasmine
Millman, Tsugumi Uema, and Hiroaki Masuzaki reviewed and edited thefinal manuscript. Shiki Okamoto, Yukio Yamori, and Hiroaki Masuzaki
supervised the study. All authors read and approved the final manuscript.
Funding This work was supported in part by the Health problem-solving
support project of the Well-being Agency of Okinawa (2019–2020).
Availability of data and material The datasets generated during and/or
analyzed during the current study are available from the corresponding
authors on reasonable request.
Code availability Not applicable.

Declarations
Ethics approval This study was performed in line with the principles of
the Declaration of Helsinki. Approval was granted by the Ethics Committee of the University of the Ryukyus (25 October 2019, approval
number: 360).
Consent to participate Witten informed consent was obtained from theparents of children who participated in the study.
Consent for publication Not applicable.
Competing interests The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as longas you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are

13

included in the article's Creative Commons licence, unless indicatedotherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view acopy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/.

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