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. 2021 Dec 2;16(12):e0260408. doi: 10.1371/journal.pone.0260408

Estimation of sodium consumption by novel formulas derived from random spot and 12-hour urine collection

Pitchaporn Sonuch 1, Surasak Kantachuvesiri 2,3,*, Prin Vathesatogkit 4, Raweewan Lappichetpaiboon 3, Worawan Chailimpamontri 3, Nintita Sripaiboonkij Thokanit 5, Wichai Aekplakorn 6
Editor: Dulce Elena Casarini7
PMCID: PMC8639059  PMID: 34855776

Abstract

The gold standard for estimating sodium intake is 24h urine sodium excretion. Several equations have been used to estimate 24h urine sodium excretion, however, a validated formula for calculating 24h urine sodium excretion from 12h urine collection has not yet been established. This study aims to develop novel equations for estimating 24h urine sodium excretion from 12h and random spot urine collection and also to validate existing spot urine equations in the Thai population. A cross-sectional survey was carried out among 209 adult hospital personnel. Participants were asked to perform a 12h daytime, 12h nighttime, and a random spot urine collection over a period of 24 hours. The mean 24h urine sodium excretion was 4,055±1,712 mg/day. Estimated urine sodium excretion from 3 different equations using random spot urine collection showed moderate correlation and agreement with actual 24h urine sodium excretion (r = 0.54, P<0.001, ICC = 0.53 for Kawasaki; r = 0.57, P<0.001, ICC = 0.44 for Tanaka; r = 0.60, P<0.001, ICC = 0.45 for INTERSALT). Novel equations for predicting 24h urine sodium excretion were then developed using variables derived from 12h daytime urine collection, 12h nighttime urine collection, random spot urine collection, 12h daytime with random spot urine collection, and 12h nighttime with random spot urine collection which showed strong correlation and agreement with actual measured values (r = 0.88, P<0.001, ICC = 0.87; r = 0.83, P<0.001, ICC = 0.81; r = 0.67, P<0.001, ICC = 0.62; r = 0.90, P<0.001, ICC = 0.90; and r = 0.83, p<0.001, ICC = 0.82 respectively). Bland-Altman plots indicated good agreement between predicted values and actual 24h urine sodium excretion using the new equations. Newly derived equations from 12h daytime and 12h nighttime urine collection with or without casual spot urine collection were able to accurately predict 24h urine sodium excretion.

Introduction

Noncommunicable diseases (NCDs), such as cardiovascular disease (CVD), cancer, diabetes, and chronic respiratory diseases are the leading causes of death worldwide [1]. In Thailand, the top two causes of mortality are ischemic heart disease (IHD) and stroke. Over the past decade, the mortality rate has increased by 50% for IHD (from 21 to 32 per 100,000 population) and has more than doubled for stroke (from 21 to 48 per 100,000 population) [2]. Sodium is an essential nutrient for humans, but excessive sodium consumption is causally associated with high blood pressure [3]. Dietary sodium consumption of greater than the recommended daily amount of 5 grams of salt or 2,000 mg of sodium is a major risk factor for CVD-related mortality [4].

In 2010, the global mean sodium intake was 3.95 g/day (95% CI 3.89 to 4.01). This was nearly twice the WHO recommended limit of 2 g/day and equivalent to 10.06 (9.88–10.21) g/day of salt. Intakes were highest in East Asia, Central Asia and Eastern Europe (mean>4.2 g/day) and in Central Europe and Middle East/North Africa (3.9–4.2 g/day) [5]. In the UK and other developed nations, hypertension and its vascular complications were more common in ethnically African and South-Asian communities compared with Europeans [6, 7]. One important racial difference between ethnic groups is salt sensitivity and significantly suppressed activity of the renin–angiotensin–aldosterone system in African-origin hypertensive patients. As a consequence of this, they are more sensitive to a low-salt diet. There is also evidence that renin suppression is common in Japanese and Chinese hypertensive patients [8]. As demonstrated in a systematic review, sodium reduction from a high sodium intake level (201 mmol/day) to a level of 66 mmol/day resulted in a decrease in SBP/DBP of 1/0 mmHg in white participants with normotension and a decrease in SBP/DBP of 5.5/2.9 mmHg in white participants with hypertension. A few studies showed that the effects in black and Asian populations were greater [9].

Robust data on sodium consumption in the Thai population is limited [10]. Available studies are limited by method of measurement, selection bias and poor sampling. An estimate from a 24-hour dietary recall from the Thai national health examination survey IV, done in 2009, reported a daily sodium intake of 3264.5 mg/day [11]. However, this information may be subject to information bias due to over or under-reporting. A small study done in 200 patients, used 24-hour urine collection, the gold standard for estimating sodium intake, and reported a sodium intake of 2,955 mg per day. Other studies were done in small, non-representative samples such as hypertensive patients or patients with kidney disease [12, 13]. A recent study, the first nationally representative population-based survey using 24-hour urinary analyses indicated that dietary sodium consumption among Thai adults was 3,636 mg/day [14]. While national efforts in sodium reduction are underway, regular and accurate measurement of sodium intake is instrumental in monitoring progression towards goals of NCDs prevention and control [1].

There are several methods for assessment of sodium consumption including food frequency questionnaires, dietary recall, and 24-hour urine collection [15]. In general, 24-hour urine collection is regarded as the gold standard and is the most validated method for assessing sodium intake, as 90% of ingested sodium is excreted in the urine [16]. However, 24-hour urine collection is burdensome for participants and often results in incomplete data. Alternative methods have been derived to overcome this drawback, such as estimation of 24-hour urine sodium from spot urine collection [17]. Another study suggested that 12-hour urine collection at night may be more feasible and more reliable, as creatinine clearance correlated well with 24-hour urine samples [18], and 12-hour urine collection at night can be used to estimate 24-hour urine sodium excretion [19].

The purpose of our study was to validate previously published spot urine equations for predicting 24-hour urine sodium excretion using the Kawasaki, Tanaka, and INTERSALT equations (S1 Table) [20–22], and to establish novel formulas incorporating 12-hour urine collection and casual spot urine collection to predict 24-hour urine sodium excretion in Thai adults. More feasible methods and validated equations will be extremely beneficial for surveillance of sodium intake at the population level.

Methods

Study design and population

A cross-sectional survey was carried out among Ramathibodi Hospital personnel. All adults (male and female) over 18 years of age provided informed consent to participate in the study. Calculation of sample size was based on N4studies application (S1 Fig) [23]. The total number of subjects required for estimation of mean urine sodium of 3,600 and SD of 1,722 mg [14] for hospital personnel was 195. The study was conducted during July 2019 –September 2019. Participants who had a history of end stage renal disease, heart failure, cirrhosis, those who were started on a diuretic within 2 weeks, pregnant or breastfeeding women, those on contraceptive pills, women during menstruation and those unable to provide informed consent were excluded from the study. Details of the study were provided and informed consent was obtained from the participants. Participants collected 12-hour urine during the daytime, 12-hour urine during the nighttime, and a random spot urine collection. In addition, blood pressure was monitored, treatment and control of hypertension was assessed. The protocol was approved for ethics clearance by the Ethics Committee of Mahidol University.

Data collection

Collection of demographics was carried out using a questionnaire. Data collected included age, sex, occupation, medical history and behavior related to dietary salt intake. Physical examination included measurement of height, weight, systolic and diastolic blood pressure. Physical measurements were taken immediately after the completion of demographic and behavioral information questionnaires. Blood pressure was taken by automatic blood pressure monitoring machine, Omron HEM-7130-L, after 15 minutes of rest, once participants had completed the questionnaire. Three blood pressure readings were recorded and calculated as mean systolic and diastolic blood pressure.

Each participant received two 3-liter containers for the 12-hour urine collections, one small container for spot urine collection, measuring cups and instructions on how to collect urine. After waking up, the first morning void was discarded. The participants were asked to collect all urine starting from the second void over a period of 12-hour during daytime. Then a 12-hour night time was collected until next morning including first morning urine. Participants were required to take note of the timing and the volume of urine collected with each void in the logbook provided. Participants were asked to randomly collect a spot urine during 12-hour collection using the small container. The urine samples were processed by the central laboratory of Ramathibodi Hospital for determination of urine volume, sodium, potassium and creatinine excretion.

Complete urine collection was defined as: total urine volume higher than 500 ml from 24-hour collection or not less than 250 ml from 12-hour collection and creatinine excretion more than 0.98 g/day for males and more than 0.72 g/day for females. Creatinine excretion was calculated using Roche/Hitachi cobas c laboratory system.

Statistical analysis

Data analysis was carried out using STATA software, version 16.0. The results were expressed as mean ± standard deviation. Pearson correlation coefficient and Intraclass correlation coefficient (ICC) were calculated to assess the correlation between actual 24-hour urine sodium excretion and estimated 24-hour sodium using the Kawasaki, Tanaka and INTERSALT formulas (S1 Table). Student’s t-test was used to compare two means and ANOVA test was used for comparison of three means or more. Multivariate linear regression analysis was used to create novel prediction equations for estimated 24-hour urine sodium excretion. The models incorporated multiple variables including age, height, weight, body mass index (BMI), urine sodium excretion, urine potassium excretion and urine creatinine excretion. Five novel equations estimating 24-hour urine sodium excretion were derived from: 1) 12-hour daytime urine collection, 2) 12-hour nighttime urine collection, 3) random spot urine collection, 4) 12-hour daytime collection with random spot urine collection, and 5) 12-hour nighttime collection with random spot urine collection. The models were analyzed separately for males and females. Pearson correlation coefficient and Intraclass correlation coefficient (ICC) were used to analyze the correlation between actual 24-hour urine sodium excretion and the estimated values calculated from the novel equations. The Bland-Altman method was used to estimate bias and agreement between equations. Statistical power was calculated based on an expected minimum R2 value of 0.6, a sample size of at least 85, and a 0.05 alpha error. With 8 predictors, the power of the test was equal to 1.0.

Results

Two hundred and fifty-two participants were recruited (Fig 1). After excluding those with incomplete urine collection based on volume and urine creatinine, those with incomplete data collection, and those who were pregnant, two hundred and nine individuals were included in the analysis. The mean age was 34.1 ± 10.8 years. There were more women (59.3%) than men (40.7%). Approximately 19.1% were hypertensives which was defined as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg or current use of antihypertensive drugs with previous diagnosis of hypertension. In participants with hypertension, the number of patients receiving antihypertensive drugs were as follows: RAAS blockage 13 (Azilsartan 1, Enalapril 8, Losartan 4), calcium channel blocker 8 (Amlodipine 4, Manidipine 3, Lercanidipine 1), beta-blocker 2 (carvedilol 1, propranolol 1), hydralazine 1 and HCTZ 1. About 97.6% reported eating out at least one meal per day at different places such as restaurants (83.7%), shop/street food (79.4%), convenience stores (74.6%), and others (12.0%) (Table 1).

Fig 1. Flow diagram of participants included in the study.

Fig 1

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Table 1. Demographic data and clinical characteristic of the study population (N = 209).

Selected Characteristics Mean ± SD, (%)
Age (years) 34.1 ± 10.8
Sex
 • Male 85 (40.7%)
 • Female 124 (59.3%)
Occupation
 • Healthcare worker (HCW) 98 (46.9%)
 • Non-healthcare (non-HCW) 111 (53.1%)
Weight (kg) 66.1 ± 13.6
Height (cm) 164.5 ± 8.7
BMI (kg/m2) 24.4±4.8
BP (mmHg)
 • Systolic 118 ± 15
 • Diastolic 76 ± 10
Hypertension (previous diagnosis or current use of hypertensive medications or SBP≥140mmHg or DBP≥90mmHg) 40 (19.1%)
Other underlying diseases
  • Diabetic mellitus 8 (3.8%)
  • Dyslipidemia 26 (12.4%)
  • Chronic kidney disease 3 (1.4%)
  • Cardiovascular disease 4 (1.9%)
  • Others 24 (11.5%)
24-hour urine
  • Volume (ml) 2,139 ± 908
  • Sodium excretion (mg/24h) 4,055 ± 1,712
  • Potassium excretion (mg/24h) 1,666 ± 619
  • Creatinine excretion (mg/24h) 1,365 ± 439
  • Na/K ratio (mmol/mmol) 4.4 ± 1.9
Eating habits
  • Home cooking
   • 3 meals/day 5 (2.4%)
   • 0–2 meals/day 204 (97.6%)
  • Eating out
   • Convenience store 156 (74.6%)
   • Restaurant 175 (83.7%)
   • Shop/Street food 166 (79.4%)
   • Others 25 (12.0%)
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The mean sodium, potassium, and creatinine excretion from the 24-hour urine samples were 4,055 ± 1,712, 1,666 ± 619, and 1,365 ± 439 mg/day respectively. In subgroup analyses, urine sodium excretion in males was higher than in females, 4,307 ± 1,694 versus 3,882 ± 1,710 mg/day respectively (P = 0.078). Non-health care workers (non-HCWs) had significantly higher urine sodium excretion than HCWs, 4,442 ± 1,865 versus 3,617 ±1,406 mg/day respectively (P<0.001). Participants aged 30–44 years had the highest urine sodium excretion and significantly higher urine sodium excretion when compared to those aged 18–29 years, P<0.001. Moreover, those with hypertension had significantly higher urine sodium excretion than those without hypertension, 4,592 ± 1,998 versus 3,928 ± 1,618 mg/day respectively (P = 0.027) (Table 2).

Table 2. Urine excretion in subgroup population (N = 209).

Selected Characteristics (N) Mean ± SD, (%)
Volume (ml) Urine sodium excretion (mg/24h) Urine potassium excretion (mg/24h) Urine creatinine excretion (mg/24h) Urine Na/K ratio (mmol/mmol)
Age
 • 18–29 years (90) 1,983 ± 831 3,517 ± 1,310 1,590 ± 573 1,355 ± 383 4.1 ± 1.8
 • 30–44 years (80) 2,271 ± 1,015 4,593 ± 2,017 1,711 ± 676 1,414 ± 497 4.8 ± 2.1
 • 45–59 years (37) 2,260 ± 817 4,285 ±1,486 1,773 ± 599 1,308 ± 432 4.3 ± 1.6
 • ≥60 years (2) 1,668 ± 131 2,487 ± 102 1,295 ± 21 927 ±256 3.3 ± 0.1
P = 0.135 P<0.001* P = 0.308 P = 0.304 P = 0.055
Sex
 • Male (85) 2,108 ± 916 4,307 ± 1,694 1,679 ± 646 1,714 ± 410 4.8 ± 2.2
 • Female (124) 2,161 ± 905 3,882 ± 1,710 1,657 ± 602 1,126 ± 263 4.3 ± 1.7
P = 0.684 P = 0.078 P = 0.806 P<0.001* P = 0.030*
Blood pressure
 • Hypertension (40) 2,330 ± 793 4,592 ± 1,998 1,735 ± 625 1,406 ± 473 4.7 ± 1.8
 • Non-hypertension (169) 2,094 ± 929 3,928 ± 1,618 1,650 ± 618 1,356 ± 431 4.3 ± 1.9
P = 0.140 P = 0.027* P = 0.434 P = 0.516 P = 0.238
Occupation
 • HCW (98) 2,031 ± 981 3,617 ±1,406 1,646 ± 594 1,300 ± 374 4.0 ± 1.8
 • Non-HCW (111) 2,235 ± 831 4,442 ± 1,865 1,683 ± 642 1,423 ± 484 4.7 ± 2.0
P = 0.106 P<0.001* P = 0.666 P = 0.043* P = 0.007*
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Estimated 24-hour urine sodium excretion from spot urine collection using Kawasaki, Tanaka, and INTERSALT equations showed moderate correlation with actual 24-hour urine sodium excretion, r = 0.54, P<0.001, ICC = 0.53 (95%CI: 0.44 to 0.63); r = 0.57, P<0.001, ICC = 0.44 (95%CI: 0.34 to 0.55); and r = 0.60, P<0.001, ICC = 0.45 (95%CI: 0.35 to 0.56) respectively (Fig 2).

Fig 2.

Fig 2

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Correlation between the actual and the estimated equation 24 hours sodium excretion: (a) from Kawasaki equation, (b) from Tanaka equation, (c) from INTERSALT equation, (d) novel equation from 12-hour urine daytime collection, (e) novel equation from 12-hour urine nighttime collection, (f) novel equation from casual spot urine collection, (g) novel equation from 12-hour urine daytime collection with casual spot urine collection, (h) novel equation from 12-hour urine nighttime collection with casual spot urine collection.

Multiple linear regression analyses were performed to identify factors that correlated with urine sodium excretion (S2 Table). Urine sodium excretion measured from 12-hour and random spot urine collection and spot urine creatinine significantly correlated with 24-hour urine sodium excretion.

Investigators then derived novel equations for estimating 24-hour urine sodium excretion (Table 3). Equations that were derived from 12-hour urine daytime and 12-hour urine nighttime collection showed strong correlation with 24-hour urine sodium excretion (r = 0.88, P<0.001, ICC = 0.87 (95%CI: 0.83 to 0.90); r = 0.83, P<0.001, ICC = 0.81 (95%CI: 0.76 to 0.85 respectively), whereas the equation derived from casual spot urine samples showed moderate correlation, r = 0.67, P<0.001, ICC = 0.62 (95%CI: 0.53 to 0.70) (Fig 2). Furthermore, when spot urine collection was added to the equation, these novel equations showed extremely strong correlation with 24-hour urine sodium excretion [r = 0.90, P<0.001, ICC = 0.90 (95%CI: 0.87 to 0.92) for 12-hour urine daytime collection with spot urine collection equation, and r = 0.83, p<0.001, ICC = 0.82 (95%CI: 0.7 7 to 0.86) for 12-hour urine nighttime with spot urine collection equation]. The novel equations that were derived from 12-hour urine collections demonstrated stronger correlation compared to the equations that were derived from spot urine collection.

Table 3. Derived novel equation for estimating 24 hours urine sodium excretion.

Urine collection Gender Novel equation for estimated 24 hours urine sodium excretion (mg/day)
12-hour daytime urine
R 0.88, p<0.001
ICC 0.87 (95%CI: 0.83 to 0.90) 		Male 23*((Age*0.47)+(Wt*0.70)+(Ht*0.10)+(UNa daytime*1.07)-(UK daytime*0.10)+(UCr daytime*13.69)–9.54)
Female 23*((Age*0.69)+(Wt*0.96)-(Ht*0.01)+(UNa daytime*1.35)-(UK daytime*0.50)-(UCr daytime*35.64)–10.51)
12-hour nighttime urine
R 0.83, p<0.001
ICC 0.81 (95%CI: 0.76 to 0.85) 		Male 23*((Age*0.80)+(Wt*3.12)-(Ht*1.95)-(BMI*3.68)+(UNa nighttime*1.39)-(UK nighttime*1.07)-(UCr nighttime*34.05)+287.80)
Female 23*((Age*(-0.50))+(Wt*10.25)-(Ht*6.73)-(BMI*22.48)+(UNa nighttime*1.43)+(UK nighttime*0.26)-(UCr nighttime*50.48)+1092.97)
Casual spot urine
R 0.67, p<0.001
ICC 0.62 (95%CI: 0.53 to 0.70) 		Male 23*((Age*0.77)+(Wt*9.15)-(Ht*5.85)-(BMI*20.11)+(UNa spot*0.55)+(UK spot*0.19)-(UCr spot*0.41)+978.77)
Female 23*((Age*0.59)+(Wt*10.97)-(Ht*6.67)-(BMI*22.40)+(UNa spot*0.57)-(UK spot*0.08)-(UCr spot*0.44)+1068.44)
12-hour daytime urine with casual spot urine
R 0.90, p<0.001
ICC 0.90 (95%CI: 0.87 to 0.92) 		Male 23*((Age*0.15)+(BMI*1.74)+(UNa daytime*0.87)-(UK daytime*0.03)+(UCr daytime*39.17)+(UNa spot*0.20)+(UK spot*0.10)-(UCr spot*0.25)+25.71)
Female 23*((Age*0.67)+(BMI*1.32)+(UNa daytime*1.20)-(UK daytime*0.18)-(UCr daytime*7.51)+(UNa spot*0.34)-(UK spot*0.39)-(UCr spot*0.12)-2.14)
12-hour nighttime urine with casual spot urine
R 0.83, p<0.001
ICC = 0.82 (95%CI: 0.77 to 0.86) 		Male 23*((Age*0.31)+(BMI*5.26)+ (UNa nighttime*1.09)-(UK nighttime*1.01)-(UCr nighttime*0.80)+(UNa spot*0.26)+(UK spot*0.45)-(UCr spot*0.24)-43.74)
Female 23*((Age*(-0.63))+(BMI*2.76)+ (UNa nighttime*1.39)+(UK nighttime*0.05)-(UCr nighttime*39.65)+(UNa spot*0.08)+(UK spot*0.35)-(UCr spot*0.19)+41.92)
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Note: Age (years); Wt, weight (kg), Ht, height (cm), BMI, body mass index (kg/m2); UNa, urine sodium (mmol/12hr) from daytime and nighttime, UNa spot, spot urine sodium (mmol/L), UK, urine potassium (mmol/12hr) from daytime and nighttime, UK spot, spot urine potassium (mmol/L), UCr, urine creatinine (g/12hr) from daytime and nighttime, UCr spot, spot urine creatinine (mg/dL)

A Bland-Altman analysis was performed to determine the difference between actual 24-hour urine sodium excretion and estimated urine sodium from novel equations. Results indicated good agreement between estimates from novel equations and actual 24-hour urine sodium excretion, with biases of 6.45 mg/day for 12-hour urine daytime collection, -19.53 mg/day for 12-hour nighttime collection, -20.60 mg/day for casual spot urine collection, -6.06 mg/day for 12-hour urine daytime with spot urine collection, and -19.96 mg/day for 12-hour urine nighttime with spot urine collection. For random spot urine equation, Bland-Altman analysis showed biases of 655.05 mg/day for Kawasaki equation, -478.85 mg/day for Tanaka equation, and -1023.37 mg/day for INTERSALT equation (Fig 3).

Fig 3. Bland-Altman plot: The difference between 24-hour urine sodium excretion and estimated urine sodium from novel equations.

Fig 3

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The dashed middle line represents the mean difference or bias. The other two dashed lines represents the 95% limits of agreement of the mean difference ± 1.96 standard deviation.

Discussion

Previous studies have demonstrated correlation between 12-hour and 24-hour urine sodium and creatinine excretion [18, 19]. In addition, collecting urine during 12-hour periods may be more practical for subjects, hence may predict sodium intake more accurately. The objective of our study was to investigate this correlation and formulate novel equations for estimating 24-hour urine sodium excretion from 12-hour urine collection, and casual spot urine collection. We were able to demonstrate that novel equations derived from 12-hour urine daytime and 12-hour urine nighttime collection with and without spot urine collection can be used to estimate 24-hour urine sodium excretion with good correlation. These novel equations demonstrate better correlation with actual urine sodium excretion than previously validated equations calculated from spot urine collection (Kawasaki, Tanaka and INTERSALT). A 12-hour urine collection may be more representative of a 24-hour urine collection than a spot urine collection, which is limited by diurnal variation in sodium excretion and is dependent on the amount and timing of sodium intake [24, 25].

In our study, we investigated the validity of previous equations that have been used to estimate urine sodium excretion in the Thai population from a spot urine collection. The Kawasaki and Tanaka equations were chosen for validation in this study because these formulas were derived from studies done in Asian participants, the Kawasaki equation using second morning void and the Tanaka equation using casual spot urine collection at different times during the day [20, 21] INTERSALT was also selected since it was derived from a large international population [22].

Results from our study suggest high sodium and low potassium intake in the enrolled subjects which is associated with an increased risk of NCDs and CVD. WHO recommends maximum daily intake of 5 grams of salt or 2,000 mg of sodium and at least 3,510 mg of potassium [4, 26, 27]. In our study, participants with hypertension had significantly higher urine sodium excretion than normotensives, affirming the association between dietary salt intake and hypertension, which is well-established in literature [28, 29]. Therefore, reduction in sodium intake may significantly decrease blood pressure in the hypertensive group. In contrast, urine potassium excretion was not significantly different in both groups. Furthermore, urine sodium excretion varied by age, with age groups of 30–44 and 45–59 having higher urine sodium excretion than the others. In line with our previous national surveys, sodium intake was higher among young people consuming higher calorie intake and fast food [14]. Our study demonstrated that non-HCWs had significantly higher urine sodium excretion than HCWs suggesting more knowledge and awareness among HCWs leading to their lower salt intake. Studies have reported that in the general population, knowledge of the health impacts of high salt intake is low [30]. Individuals with higher knowledge and awareness of the salt content and impact were significantly associated with lower salt intake [31, 32]. However, further research on the better understanding of salt knowledge and behavior in the population might facilitate the planning and implementation of a low salt intake program. Urine creatinine excretion in non-HCWs was also significantly higher than HCWs. This could be due to higher body mass index in the group of non-HCWs (26.05±5.12 kg/m2 in non-HCW vs 22.64±3.45 kg/m2 in HCW, P<0.001) which affected urine creatinine excretion.

In participants with hypertension, some patients received antihypertensive drugs that may alter renal hemodynamics and sodium excretion. The administration of calcium-blocking drugs exerts a natriuretic response by exerting hemodynamic effects, as well as by acting directly on the proximal tubule and impairing sodium reabsorption in the distal tubule [33]. In contrast, beta-adrenergic antagonists have little or no clinical effect on glomerular filtration rate (GFR), urinary sodium or potassium excretion, free water clearance, or body fluid composition [34]. In animal models of salt sensitive hypertension, treatment with an angiotensin-converting-enzyme inhibitor (ACEI) or an angiotensin receptor blocker (ARB) effectively lowered blood pressure. In addition to lowering blood pressure, ACEI and ARB inhibition downregulated ENaC and suppressed sodium reabsorption in renal tubules [35]. However, in our study, since the dosages of the antihypertensives were stable for at least 2 weeks before entering the study, the effect of medications on spot urine sodium excretion and in turn, estimated urine sodium excretion will be trivial as patients are in a steady state. Furthermore, a prior study showed that medications such as diuretics and ACE inhibitor or angiotensin receptor blocker did not substantially affect the accuracy with which Na excretion was estimated by spot urine equation [36].

We validated various equations for predicting 24-hour urine sodium excretion from previously established equations and also formulated novel equations to estimated 24-hour urine sodium excretion in Thai participants. These new equations are derived from 12-hour urine collections to estimate 24-hour urine sodium excretion. They are robust and convenient for estimating sodium excretion and consumption in patients with uncontrolled hypertension. Furthermore, they provide a practical method to monitor sodium intake in clinical research or in epidemiological studies, especially in patients who work and can only collect urine for 12 hours at night time.

Strengths of this study include relatively complete and reliable urine samples. The main limitation is the study sample, which was hospital personnel, thereby limiting applicability to the general population. However, the study participants had similar characteristics to the general Thai population, therefore, the novel formulas for estimation of 24-hour urine sodium excretion should be applicable to the general Thai population with relatively good kidney function.

In summary, the newly derived equations from 12-hour urine daytime and 12-hour urine nighttime collection with or without casual spot urine collection may be applicable for estimation of 24-hour urine sodium excretion in the Thai population. This will be instrumental in the monitoring of sodium intake for NCDs prevention.

Supporting information

S1 Fig. N4studies application [23].

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Click here for additional data file. (3.5MB, tif)
S1 Table. Three methods to estimated 24 hours urine sodium excretion from spot urine sample [20–22].

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Click here for additional data file. (5.4MB, tif)
S2 Table. Multivariate linear regression analysis.

(TIF)

Click here for additional data file. (5.6MB, tif)
S1 Dataset

(XLSX)

Click here for additional data file. (104.5KB, xlsx)

Acknowledgments

We would like to thank Ananthaya Kunjang for technical support and Dr. Pitchaphon Nissaisorakarn for editing the manuscript.

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

This study was financially supported by the Thai Health Promotion Foundation. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Dulce Elena Casarini

27 Apr 2021

PONE-D-21-09293

Estimation of sodium consumption by novel formulas derived from random spot and 12-hour urine collection

PLOS ONE

Dear Dr. Kantachuvesiri, 

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

My observations to be answered:

- The study added new information to existing knowledge of Kawasaki, Tanaka, and Intersalt equations.

- In the introduction the authors made a literature revision, but there were no reported differences between handling of sodium in the Western, Eastern and Black populations.

-- In Methods is important to provide the calculation power performed for the inclusion of patients in the study.  The urine collection period was not described when the authors refer to the day or night period and also is important to know the start or end time of it. It is important describe the drugs that the volunteers normally received.

- The study analyzed other parameters in results as ages, gender, occupation, medical history, behavior towards dietary salt intake,  hypertension and other parameters that were described in results, however, such analyzes were a little out of the objective of the study. The drugs received by patients need to be discussed with regard to the influence on the handling of sodium.

- Figures need to be better worked, with better resolution.

- In the discussion, it would be important to emphasize the importance of the 12-hour urine collection findings in relation to the 24-hour urine in established calculations and its application in the future in the clinic.

- Native English proofreading is required

Please submit your revised manuscript by 20 days. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Dulce Elena Casarini, PhD, FAHA

Academic Editor

PLOS ONE

Additional Editor Comments:

The authors described in the manuscript equations/formulas to validated formula for predicting 24h urine sodium excretion from 12h urine collection. The study added new information to existing knowledge of Kawasaki, Tanaka, and Intersalt equations.

In the introduction the authors made a literature revision, but there were no reported differences between handling of sodium in the Western, Eastern and Black populations.

In Methods is important to provide the calculation power performed for the inclusion of patients in the study. The urine collection period was not described when the authors refer to the day or night period and also is important to know the start or end time of it. It is important describe the drugs that the volunteers normally received.

The study analyzed other parameters in results as ages, gender, occupation, medical history, behavior towards dietary salt intake, hypertension and other parameters that were described in results, however, such analyzes were a little out of the objective of the study. The drugs received by patients need to be discussed with regard to the influence on the handling of sodium.

Figures need to be better worked, with better resolution.

In the discussion, it would be important to emphasize the importance of the 12-hour urine collection findings in relation to the 24-hour urine in established calculations and its application in the future in the clinic.

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[This study was financially supported by the ThaiHealthPromotionFoundation.]

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: To authors

The current manuscript is interesting and important. It involves prediction about cardiovascular diseases in Thailand through getting sodium urine measurement. The authors carried out urine tests and created new formulas with correlation between former formulas by other researchers and the new formula.

My questions:

Methods

I have not found quotes about participants with heart failure or cirrhosis. These syndromes cause low perfusion, secondary hyperaldosteronism. It can interfere with renal sodium excretion.

Approximately 19 % were hypertensives, but I have also found no reports of the use of drugs that block the renin-angiotensin system in hypertensive volunteers. Could these medicines interfere with kidney sodium excretion?

I am not sure or I didn't pay attention when reading the manuscript. What was the exact moment when each participant performed the spot urine collection? Was it before, during or after the 12h urine collection?

Results

What statistical test did you use to compare urinary sodium excretion between HCW and non-HCW groups? And about comparison between age? And hypertesion vs. non-hypertension? Have you performed with the Student's t test?

Discussion

In my opinion, you should report the primary result found in the in the first paragraph in discussion of the manuscript

Authors must perform a detailed review of English.

Reviewer #2: Soumach's article and collaborators describe new equations to predict 24-hour urinary sodium excretion. With the equations proposed by the authors, the collection of 12-hour urine, whether collected during the day or night, associated or not with spot urine, correlates significantly with studies that investigated sodium excretion. The study of Soumach and collaborators adds information to existing knowledge.

Some suggestions for improving the study

• I suggest that the specificity of the population studied is included in the title. Possibly, most (if not all) of the study participants were Eastern. It is known, for example, that black individuals have a distinct handling of sodium. Even in the introduction of the work the authors refer only to the sodium intake of the Thai population.

• Although the authors elegantly demonstrate that the proposed formulas predict and validate excretion in a shorter time (12 hours) it would not be important for the authors to evidence the gains in the use of these equations. The discussion of the benefit of using equations takes place in only one paragraph.

• How did the authors calculate the number of patients included in each group? Which test was used to calculate the sample?

• When the authors refer to the day or night period, the start or end time of the collection is not clear.

• Could the fact that patients answer the questionnaire while resting could not determine the increase in blood pressure?

• Antihypertensive drugs that alter renal hemodynamics (such as calcium channel blockers) or aldosterone secretion could not interfere with the results?

• The objectives of the work were related to the development of the equations. However, the work also makes comparations between ages, gender, the fact that patients are hypertensive or health professionals. The focus of the work seems to me scattered. It would be interesting, the correlation between 24-hour and 12-hour measurements in the different strata proposed by the authors.

• What was the statistical analysis software used by the authors?

• In equations, I think it should be sororded "UNa" instead of "Una". UK is capitalized

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Dec 2;16(12):e0260408. doi: 10.1371/journal.pone.0260408.r002

Author response to Decision Letter 0

24 May 2021

Response to Reviewer

- In the introduction the authors made a literature revision, but there were no reported differences between handling of sodium in the Western, Eastern and Black populations.

Ans: We have added the literature review in the introduction part as follows:

In 2010, the global mean sodium intake was 3.95 g/day (95% CI 3.89 to 4.01). This was nearly twice the WHO recommended limit of 2 g/day and equivalent to 10.06 (9.88–10.21) g/day of salt. Intakes were highest in East Asia, Central Asia and Eastern Europe (mean>4.2 g/day) and in Central Europe and Middle East/North Africa (3.9-4.2 g/day).(5) In the UK and other developed nations, hypertension and its vascular complications were more common in ethnically African and South-Asian communities compared with Europeans.(6,7) One important racial difference between ethnic groups is salt sensitivity and significantly suppressed activity of the renin–angiotensin–aldosterone system in African-origin hypertensive patients. As a consequence of this, they are more sensitive to a low-salt diet. There is also evidence that renin suppression is common in Japanese and Chinese hypertensive patients.(8) As demonstrated in a systematic review, sodium reduction from a high sodium intake level (201 mmol/day) to a level of 66 mmol/day resulted in a decrease in SBP/DBP of 1/0 mmHg in white participants with normotension and a decrease in SBP/DBP of 5.5/2.9 mmHg in white participants with hypertension. A few studies showed that the effects in black and Asian populations were greater.(9) (Paragraph2, Page3)

- In Methods is important to provide the calculation power performed for the inclusion of patients in the study.

Ans:

We have added a sentence describing the calculation of power in the statistical analysis section as follows: Power of test was assessed based on an expected minimum value of R squared of 0.6, sample size of at least 85, alpha error 0.05 and 6 predictors, the power of test was equal to 1.0. (Statistical analysis, Page7)

- The urine collection period was not described when the authors refer to the day or night period and also is important to know the start or end time of it.

Ans:

Regarding to urine collection period, the first morning void was discarded. A 12-hour urine daytime started from the second void and collected over a period of 12-hours, Then a 12-hour night time was collected until next morning including first morning urine. (Paragraph2, Page6)

- It is important describe the drugs that the volunteers normally received.

Ans: We have added the information on drug used and discussed in the discussion part as follows:

In subgroup of participants with hypertension, numbers of patients receiving antihypertensive drugs were followings RAAS blockage (Azilsartan 1, Enalapril 8, Losartan 4), calcium channel blocker (Amlodipine 4, Manidipine 3, Lercanidipine 1), beta-blocker (carvedilol 1, propranolol 1), hydralazine in 1 and HCTZ in 1. (Paragraph2, Page13)

- The study analyzed other parameters in results as ages, gender, occupation, medical history, behavior towards dietary salt intake, hypertension and other parameters that were described in results, however, such analyzes were a little out of the objective of the study. The drugs received by patients need to be discussed with regard to the influence on the handling of sodium

Ans:

In participants with hypertension, some patients received antihypertensive drugs that may alter renal hemodynamics and sodium excretion. The administration of calcium-blocking drugs exerts a natriuretic response by exerting hemodynamic effects, as well as by acting directly on the proximal tubule and impairing sodium reabsorption in the distal tubule.(30) In contrast, beta-adrenergic antagonists have little or no clinical effect on glomerular filtration rate (GFR), urinary sodium or potassium excretion, free water clearance, or body fluid composition.(31) In animal models of salt sensitive hypertension, treatment with an angiotensin-converting-enzyme inhibitor (ACEI) or an angiotensin receptor blocker (ARB) effectively lowered blood pressure. In addition to lowering blood pressure, ACEI and ARB inhibition downregulated ENaC and suppressed sodium reabsorption in renal tubules.(32) However, in our study, since the dosages of the antihypertensives were stable for at least 2 weeks before entering the study, the effect of medications on spot urine sodium excretion and in turn, estimated urine sodium excretion will be trivial as patients are in a steady state. Furthermore, a prior study showed that medications such as diuretics and ACE inhibitor or angiotensin receptor blocker did not substantially affect the accuracy with which Na excretion was estimated by spot urine equation.(33 (Paragraph2, Page13)

- Figures need to be better worked, with better resolution.

Ans:

We have revised the figures as suggested

- In the discussion, it would be important to emphasize the importance of the 12-hour urine collection findings in relation to the 24-hour urine in established calculations and its application in the future in the clinic.

Ans:

We added discussion on the importance of the new 12-hour urine equation and its application on page 14

- Native English proofreading is required

Ans:

Native English proofreading was performed

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (17.7KB, docx)

Decision Letter 1

Dulce Elena Casarini

24 Aug 2021

PONE-D-21-09293R1

Estimation of sodium consumption by novel formulas derived from random spot and 12-hour urine collection

PLOS ONE

Dear Dr. Kantachuvesiri

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The review was adequate and two small points would need to be reviewed, topics that are in line with those also highlighted by one of the referees:

-  the statistical analysis to Table 2 when the authors discuss age, 

-  in discussion explain the difference between HCW and non-HCW in excretions of sodium and creatinine. 

Please submit your revised manuscript by September 2nd, 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Dulce Elena Casarini, PhD, FAHA

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

All changes made were appropriate in this new version, and I suggest that the authors observe the note made by one of the referees about adding the statistical analysis to Table 2 when the authors discuss age. Regarding the discussion, the difference between HCW and non-HCW in sodium and creatinine excretions was not highlighted, which was also observed by one of the referees.

With these minor corrections the article is in the profile for publication.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

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Reviewer #1: Dear authors

The current manuscript is interesting and important. It involves prediction about cardiovascular diseases through getting urine sodium measurement.

All comments have been addressed.

Reviewer #2: The study by Sonouch and collaborators brings gains from its original version and is much better organized.

The article actually brings two studies, the first that discusses the sodium excretion of 209 Thai participants. The second is the design of equations that increase the correlation between urine collection for 12 hours (daytime or nighttime), associated or not with the isolated urine sample. The correlations when associated with the 12-hour sample when associated with the isolated sample present a high degree of correlation against the gold standard, which is the 24-hour sodium dosage.

Because the study is local, I strongly recommend that the study title contain this information. The stratified analysis of the information, verified in table 2, was a gain for the study, but the statistical analysis was lacking in the table when the authors discuss age. I also did not see in the article discussion why the difference between HCW and non-HCW in sodium and creatinine excretions.

I still believe that extrapolating mathematical behaviors in a small sample should be taken with caution. The authors do not demonstrate calculations the estimate of the necessary population.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Dec 2;16(12):e0260408. doi: 10.1371/journal.pone.0260408.r004

Author response to Decision Letter 1

21 Oct 2021

Response to Reviewer

1. The statistical analysis to Table 2 when the authors discuss age

Ans:

We have added ANOVA test was used for comparison of three means or more. (Paragraph1, Page7) and inserted P value in Table2.

2. In discussion explain the difference between HCW and non-HCW in excretions of sodium and creatinine.

Ans:

We have add discussion in Paragraph2, Page13

Furthermore, urine sodium excretion varied by age, with age groups of 30-44 and 45-59 having higher urine sodium excretion than the others. In line with our previous national surveys, sodium intake was higher among young people consuming higher calorie intake and fast food.(14) Our study demonstrated that non-HCWs had significantly higher urine sodium excretion than HCWs suggesting more knowledge and awareness among HCWs leading to their lower salt intake. Studies have reported that in the general population, knowledge of the health impacts of high salt intake is low.(30) Individuals with higher knowledge and awareness of the salt content and impact were significantly associated with lower salt intake.(31,32) However, further research on the better understanding of salt knowledge and behavior in the population might facilitate the planning and implementation of a low salt intake program. Urine creatinine excretion in non-HCWs was also significantly higher than HCWs. This could be due to higher body mass index in the group of non-HCWs (26.05±5.12 kg/m2 in non-HCW vs 22.64±3.45 kg/m2 in HCW, P<0.001) which affected urine creatinine excretion.

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Decision Letter 2

Dulce Elena Casarini

10 Nov 2021

Estimation of sodium consumption by novel formulas derived from random spot and 12-hour urine collection

PONE-D-21-09293R2

Dear Dr. Kantachuvesiri

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Dulce Elena Casarini, PhD, FAHA

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The authors answered all the last questions asked by the referees that improved the manuscript. This latest revision has been carefully done, and therefore the manuscript is accepted for publication.

Reviewers' comments:

The authors answered all the last questions asked by the referees that improved the manuscript. This latest revision has been carefully done, and therefore the manuscript is accepted for publication.

Acceptance letter

Dulce Elena Casarini

22 Nov 2021

PONE-D-21-09293R2

Estimation of sodium consumption by novel formulas derived from random spot and 12-hour urine collection

Dear Dr. Kantachuvesiri:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Dulce Elena Casarini

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. N4studies application [23].

    (TIF)

    Click here for additional data file. (3.5MB, tif)
    S1 Table. Three methods to estimated 24 hours urine sodium excretion from spot urine sample [20–22].

    (TIF)

    Click here for additional data file. (5.4MB, tif)
    S2 Table. Multivariate linear regression analysis.

    (TIF)

    Click here for additional data file. (5.6MB, tif)
    S1 Dataset

    (XLSX)

    Click here for additional data file. (104.5KB, xlsx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (17.7KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (13.9KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting information files.

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