|Year : 2021 | Volume
| Issue : 2 | Page : 137-142
Estimation of sodium intake using spot urine samples in urban South Indian set up: A cross sectional study
Aman Jain, Smita S Sonoli, Reshma D Channashetti
Departments of Biochemistry, KLE Academy of Higher Education and Research Centre, JNMC, Belagavi, Karnataka, India
|Date of Submission||05-Nov-2020|
|Date of Decision||31-Mar-2021|
|Date of Acceptance||03-Apr-2021|
|Date of Web Publication||08-Jan-2022|
Dr. Reshma D Channashetti
Department of Biochemistry, KLE Academy of Higher Education and Research Centre, JNMC, Belagavi, Karnataka
Source of Support: None, Conflict of Interest: None
BACKGROUND AND OBJECTIVE: Obesity has been linked with various factors and one of them is the amount of sodium intake by an individual. Spot urine examination is an accepted method of sodium estimation which is accurate, patient compliant and reliable. Hence, the study plans to assess the sodium intake by analyzing spot urinary sodium in normal, overweight, and obese individuals and also to compare and correlate urinary sodium with body mass index (BMI) and waist-hip ratio (WHR).
MATERIALS AND METHODS: A cross-sectional study was conducted on 90 individuals grouped into normal, overweight, and obese categories in an urban set up. The Kawasaki formula was used to estimate urinary sodium excretion per day. Comparison between the BMI, WHR, and sodium intake per day for all the categories were done using ANOVA. Pearson's correlation coefficient was calculated to find the correlation between the sodium intake per day, BMI and WHR. A P < 0.05 was considered as statistically significant.
RESULTS: Total sodium intake per day by obese individuals was 316.69 ± 170.86 (mEq/day) with the P = 0.0645 using Kawasaki formula. According to Kruskal–Wallis test, there was no statistical difference between values of sodium intake between normal, overweight, and obese categories (P > 0.05). However, significant positive correlation was noted between BMI and sodium intake (P < 0.05) and that of WHR and sodium intake (P < 0.05).
CONCLUSION: Sodium intake was positively correlated with the indices of obesity (BMI and WHR) and was found to be an independent risk factor for obesity.
Keywords: Body mass index, Kawasaki formula, obesity, sodium chloride, urine biomarker, waist-hip ratio
|How to cite this article:|
Jain A, Sonoli SS, Channashetti RD. Estimation of sodium intake using spot urine samples in urban South Indian set up: A cross sectional study. BLDE Univ J Health Sci 2021;6:137-42
|How to cite this URL:|
Jain A, Sonoli SS, Channashetti RD. Estimation of sodium intake using spot urine samples in urban South Indian set up: A cross sectional study. BLDE Univ J Health Sci [serial online] 2021 [cited 2022 Jul 2];6:137-42. Available from: https://www.bldeujournalhs.in/text.asp?2021/6/2/137/335319
Sodium is an essential nutrient in the human body since it regulates various homeostatic functions, i.e., osmotic equilibrium, blood pressure, etc. Sodium chloride accounts for majority of dietary sodium intake, as it is used as a seasoning and preservative, with processed foods being the largest contributor. However, like every coin has two sides, excessive sodium intake has its own set of consequences. It has long been known to expose an individual to increased risk of cardiovascular morbidity and mortality, particularly by increasing the blood pressure and hence causing hypertension. Reducing the salt intake in population is one of the more efficient and cost-effective ways to reduce the burden of cardiovascular diseases which will ultimately result in a major improvement in public health., Recent observational studies highlights a possible relationship between sodium and obesity independent of higher caloric intake.,, Biological plausibility of this link has to be explored; high levels of sodium are associated with increased adipocyte mass and insulin sensitivity in rats and increased insulin resistance and prevalence of metabolic syndrome in humans., These observations and known facts directs to a need for extensive evaluation of the association between sodium and obesity. It would help in a more complete understanding of the effects of reduced sodium intake beyond treating traditional cardiovascular diseases.
Urine biomarker (24-h urine sample, spot urine sample) data tends to capture all the sources of sodium intake which an individual often cannot recall and hence are more accurate than the dietary recall method. Accurate estimation of dietary salt intake is often inaccurate because it is difficult to estimate the amount of salt added during cooking, amount of food left in plate and the amount of salt in water. The measurement of 24-h urinary sodium excretion is the preferred method, as it is the gold standard. However, it can be expensive and cumbersome as it is dependent on various factors such as willingness of the person and shows person to person variability. In addition, 24-h urine excretion method does not account for electrolyte loss other than that through kidneys, for example, through sweat. Therefore, even 24-h urine collection method underestimates sodium intake to an extent. Recently, it has been brought to light that the spot sample, carried out in the morning after overnight fasting, was closely related to the 24-h sample. Collection of spot urine samples offer a considerably cheaper alternative but has not been studied extensively for use in measuring sodium intake. Patient compliance to this method is also expected to be more when compared to 24-h urine collection method.
Few studies have tried to establish a relationship between obesity and sodium intake taking into consideration 24-h urine sample, through 24-h urinary sodium levels. Although morning spot urinary sodium levels also give same results. Kawasaki formula is one of the most accurate formulas which utilizes spot urinary sodium to estimate 24-h sodium intake by an individual. It takes the spot creatinine concentration as a measure of urine concentration. To the best of our knowledge, no study has been done using any antecedent spot urine sodium analysis in obese patients. Thus, the current study embarks on estimating dietary sodium intake using spot urine samples in normal, overweight, and obese individuals with the help of the Kawasaki formula. Furthermore, the study also aims at comparing and drawing a correlation between urinary sodium, body mass index (BMI), and waist-hip ratio (WHR). By doing so the study aspires to determine the feasibility and validity of dietary sodium intake in spot urine samples as a potential risk factor for obesity.
| Materials and Methods|| |
Community-based cross-sectional study was conducted over a period of 2 months (June 2015–July 2015) on 90 individuals selected by random sampling at the urban health center in Belgaum, Karnataka, India. Study participants were then categorized into three groups of normal, over-weight, and obese, with 30 individuals in each. The minimal sample size required for the comparison of three groups, factoring in a type I error of 0.05 and power of 80%, and anticipating a medium effect size, the number of participants for each group was estimated to be 28. Therefore, the sample size was taken as 30 each for normal, overweight and obese categories. The samples were analyzed in the National Accreditation Board for Testing and Calibration Laboratories (NABL) accredited HI-TECH Biochemistry laboratory. In each of the three groups, ages of the participants ranged between 35 and 45 years. Patients with no previous history of hypertension and/or diabetes mellitus and availability of recently collected samples were included in the study. While the presence of kidney disease, hypertension and/or diabetes mellitus, obesity resulting from endocrinal disorders constituted the exclusion criteria.
Method of data collection
Institutional ethical committee clearance was obtained on May 27, 15 from Institution Ethics Committee on Human subject's research. People willing to participate in the study and who fit into our inclusion criteria were identified and written informed consent was taken from them. Their height and weight measurements were taken according to the World Health Organization (WHO) classification of BMI for Asian population.
Height was measured with a non-elastic tape to the nearest centimeter. The measurement of subject's body height was done with their back against the wall with the help of ruler.
Weight was measured with a portable electronic balance that was kept on a firm horizontal surface to the nearest 0.1 kg. The electric balance was switched on 30 min prior to calibration every day, and was calibrated by measuring and recording standard weights across the range of the scale. BMI was calculated using Quetelet's index. Once subgrouped into obese, overweight and normal weight, waist circumference (WC) and hip circumference (HC) were measured following standard protocol and then WHR was calculated.
WC was measured using non-elastic measuring tape as the smallest circumferences of the natural waist at minimal respiration.
Hip circumference was taken at the widest part of the buttocks. Measurements were made to the nearest 0.1 cm.
A labeled wide mouth universal sterile container was given to each participant. They were instructed to collect about 5–10 ml of 8-h overnight fasting midstream urine sample in the morning. The container was collected from them the following morning and was taken to NABL accredited HI-TECH biochemistry laboratory for the estimation of sodium and creatinine values.
Methods of estimation
The spot urine samples collected were processed using Ion Selective Electrode by Roche diagnostic Analyzer and Jaffe's method based SIEMENS Dimension auto analyzer for estimating urinary sodium and urinary creatinine, respectively. Predicted 24-h urinary creatinine (PRCr) (mg/day) in samples was calculated by the following equation.
+7.39×Height(cm)-79.90 for Males.
+5.09×Height(cm)-74.50 for females.
The calculated values were substituted in the Kawasaki formula to find out urinary sodium excretion per day
Data analysis was done using software package of social sciences (SPSS) trial version 16 in an Excel sheet. All the numerical values were summarized as mean ± standard deviation with P < 0.05 considered as level of significance. Chi-square test was done for the male/female ratio. Comparison between the means obtained for BMI, WHR and sodium intake per day for the three categories, i.e., normal, over-weight and obese was done using ANOVA. Pearson's correlation coefficient was derived to see for the correlation between the sodium intake per day, BMI and WHR.
| Results|| |
The current study monitored 90 individuals aged between 35 and 45 years for an association between dietary sodium intake detected via spot urine samples and obesity. Out of the 90 individuals enrolled, a male preponderance of 56 individuals over 34 females was observed.
Although age was found to be an insignificant factor, but a significant difference was found in the gender distribution across the study groups with X22 = 6.334 and P = 0.0421 as presented in [Table 1]. ANOVA analysis of BMI (kg/m2), WHR (WC/HC) and sodium intake per day (mEq/day) of the three groups revealed a significant association of BMI (P < 0.0001) and WHR (P < 0.0114) with obesity.
BMI was significantly higher in overweight and obese individuals as compared to normal individuals (P < 0.0001). WHR also changed significantly among the three categories (P < 0.05). Post hoc Tukey honestly significant difference test demonstrated that mean of WHR of overweight (P = 0.0238) and obese individuals (P = 0.0263) were significantly different from normal weight individuals however WHR of obese individuals did not significantly differ from that of overweight individuals (P = 0.9991). However, there was no statistical difference between values of sodium intake between the three categories, i.e., normal weight, overweight, and obese (P > 0.05).
On deriving “r” value with the help of Pearson's correlation coefficient, BMI and WHR correlated positively with sodium intake [Table 2]. [Figure 1] provides a graphical representation of the strong positive correlation of sodium intake with significant BMI and WHR variables.
|Table 2: Pearson's correlation coefficient in sodium intake versus body mass index; versus waist-hip ratio|
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|Figure 1: Comparison of salt intake between normal, overweight and obese categories|
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| Discussion|| |
With over 1.9 billion overweight adults and 650 million individuals grappling with obesity globally, understanding the root of this metabolic dysfunction is crucial. In a populous country such as India, obesity prevalence rates of 11.8%–31.3%, impose an inordinate medical and financial burden on the public expenditure. Therefore, critical analysis of the causes and its effects constitute the need of the hour. Salt is the major contributor of sodium to our body. High sodium intake is one of the risk factors for the development of overweight and obesity related disorders and comorbidities like hypertension, cardiovascular disorders, etc. Existing literature pertaining to sodium intake among populations mostly revolve around 24 h urinary sodium extraction method. Considering the absence of a study explicative of the salient association between sodium intake and obesity especially among the Indian population, the need for this study was felt. Hence, this study set out to evaluate the potential of dietary sodium intake estimated by spot urine samples as a risk factor for obesity, while taking into account the BMI and WHR.
The studies done in western population have shown that sodium intake acted as an independent risk factor for obesity.,,, In the present study, with the shift of category from normal weight to overweight to obese, there was an increase in sodium intake estimation values. However, statistical significance could not be achieved. This trend between sodium intake of normal, over-weight and obese individuals could be due to the small sample size of our study. Healthy lifestyle habits encompassing diet and exercise inculcated by the urban population studied, owing to greater awareness could have also played a role. Voluntary reductions in dietary sodium intake, or low-calorie diet and loss of sodium through sweat during routine exercise have been shown to have a positive influence in balancing sodium levels.,
Association of demographic characteristics such as age and gender with dietary sodium intake showed varied results. Age was not found to influence dietary sodium intake, while gender was observed to be a significant factor. Higher dietary sodium intake was noticed among males in the normal and overweight categories; however, among the obese category an equivalence of genders was seen. These findings are in consonance with the observations of Li et al. who reported that age did not show any notable variance, in contrast to gender wherein higher urinary sodium levels were more prevalent among males than females. A review article by Cogswell et al. also echoes a similar finding of increased urinary sodium excretion in males compared to females on investigating 13 prospective cohort studies.
We observed a certain positive correlation between BMI and sodium intake (P < 0.05) and between WHR and sodium intake (P < 0.05). Previous studies have reported that increasing intakes of sodium (salt) obligatorily produce a progressive increase in thirst. The progressive increase in the average intake of salt explains the observed concomitant increase in the intake of beverages which, in turn, has caused a marked net increase in the intake of calories during the same period. The use of different measures of body size (BMI and WHR) and their similar positive correlation with obesity lends credibility to this research. Although fairly accurate, overnight fasting spot urine samples are yet to be established as an equally accurate method as 24-h urine sample method to determine the sodium intake of an individual which could have caused the results to vary from the trend observed with other studies, i.e., positive correlation between sodium intake between normal weight, overweight, and obese individuals. Furthermore, the reverse situation cannot be ruled out, i.e., obesity related metabolic syndrome could cause more urinary sodium excretion in an individual. The findings of this study could have been further enhanced by a parallel comparison of dietary sodium intake estimated using 24h urine samples and spot urine samples. Incorporating a lifestyle survey enquiring about the frequency and intensity of physical exercise practiced, if any and general dietary preferences of participants could have ruled out confounding factors.
Immediate outcome of the study
Sodium intake was positively correlated to BMI and WHR, i.e., as sodium intake increased among individuals, a concomitant increase in BMI and WHR was observed (measures of obesity).
Intermediate outcome of the study
Studies with larger sample size will endorse our study. In the present scenario, test for estimation of sodium intake is not prescribed routinely even for hypertensive patients. Also, patient compliance needs to be kept in mind. Newer and more accurate patient friendly techniques for estimation of sodium intake need to be developed so that a consultant can take into account a patient's sodium level when he visits an outpatient clinic. Further studies need to check the credibility of spot urinary sodium measurement as a measure of sodium intake and try if serially monitored spot urine samples, for example, overnight fasting spot urine samples for 7 continuous days of a week can provide better results.
Long term outcome of the study
If the relationship between sodium intake and risk for developing obesity is established independent of other factors, the same can be suggested to the governing body (WHO) and local government scan take up the necessary measures for the moderation of the sodium in preservatives and other food items.
In this study, sodium intake was measured indirectly by the estimation of its excretion in overnight fasting spot urine samples. Males were found to consume elevated levels of sodium in their diet in comparison to females. Sodium intake was positively and significantly correlated with the indices of obesity (BMI and WHR) and was found to be an independent risk factor for obesity.
| Conclusion|| |
Sodium intake was estimated indirectly by measuring sodium and creatinine concentrations in overnight fasting spot urine samples and substituting the values in Kawasaki formula. This method was used because it is non-cumbersome and has better patient compliance compared to dietary recall, which is often considered vague and inaccurate. The measurement of 24-h urinary sodium excretion is the gold standard. However, it is expensive and willingness of the person is a concern. Sodium intake was positively and significantly correlated with the indices of obesity (BMI and WHR) and was found to be an independent risk factor for obesity, but statistical significance could not be achieved. Further studies can be taken up with larger sample size to establish the significance.
We would like to thank all the participated students for their cooperation.
Financial support and sponsorship
ICMR Funded STS project.
Conflict of interest
There are no conflicts of interest.
| References|| |
Soetan AK, Olaiya CO, Oyewole OE. The importance of mineral elements for humans, domestic animals and plants: A review. Afr J Food Sci 2010;4:200-22.
Ainsworth P, Plunkett A. Reducing salt in snack products. In: Kilcast D, Angus F, editors. Reducing Salt in Foods: Practical Strategies. Cambridge, UK: Woodhead P; 2007. p. 296-315.
Sheng CS, Liu M, Kang YY, Wei FF, Zhang L, Li GL, et al
. Prevalence, awareness, treatment and control of hypertension in elderly Chinese. Hypertens Res 2013;36:824-8.
Brown IJ, Tzoulaki I, Candeias V, Elliott P. Salt intakes around the world: Implications for public health. Int J Epidemiol 2009;38:791-813.
Bibbins-Domingo K, Chertow GM, Coxson PG, Moran A, Lightwood JM, Pletcher MJ, et al
. Projected effect of dietary salt reductions on future cardiovascular disease. N Engl J Med 2010;362:590-9.
Larsen SC, Ängquist L, Sørensen TI, Heitmann BL. 24h urinary sodium excretion and subsequent change in weight, waist circumference and body composition. PLoS One 2013;8:e69689.
Zhu H, Pollock NK, Kotak I, Gutin B, Wang X, Bhagatwala J, et al
. Dietary sodium, adiposity, and inflammation in healthy adolescents. Pediatrics 2014;133:e635-42.
Yi SS, Kansagra SM. Associations of sodium intake with obesity, body mass index, waist circumference, and weight. Am J Prev Med 2014;46:e53-5.
Fonseca-Alaniz MH, Takada J, Andreotti S, De Campos TB, Campaña AB, Borges-Silva CN, et al
. High sodium intake enhances insulin-stimulated glucose uptake in rat epididymal adipose tissue. Obesity 2008;16:1186-92.
Baudrand R, Campino C, Carvajal CA, Olivieri O, Guidi G, Faccini G, et al
. High sodium intake is associated with increased glucocorticoid production, insulin resistance and metabolic syndrome. Clin Endocrinol (Oxf) 2014;80:677-84.
Ortega RM, López-Sobaler AM, Ballesteros JM, Pérez-Farinós N, Rodríguez-Rodríguez E, Aparicio A, et al
. Estimation of salt intake by 24 h urinary sodium excretion in a representative sample of Spanish adults. Br J Nutr 2011;105:787-94.
Ji C, Sykes L, Paul C, Dary O, Legetic B, Campbell NR, et al
. Systematic review of studies comparing 24-hour and spot urine collections for estimating population salt intake. Rev Panam Salud Publica 2012;32:307-15.
Mente A, O'Donnell MJ, Dagenais G, Wielgosz A, Lear SA, McQueen MJ, et al
. Validation and comparison of three formulae to estimate sodium and potassium excretion from a single morning fasting urine compared to 24-h measures in 11 countries. J Hypertens 2014;32:1005-14.
WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-63.
Johnson C, Mohan S, Rogers K, Shivashankar R, Thout SR, Gupta P, et al
. Mean dietary salt intake in urban and rural areas in India: A population survey of 1395 persons. J Am Heart Assoc 2017;6:1-8.
Kawasaki T, Uezono K, Itoh K, Ueno M. Prediction of 24-hour urinary creatinine excretion from age, body weight and height of an individual and its application. Nihon Koshu Eisei Zasshi 1991;38:567-74.
Ahirwar R, Mondal PR. Prevalence of obesity in India: A systematic review. Diabetes Metab Syndr 2019;13:318-21.
Kang HJ, Jun DW, Lee SM, Jang EC, Cho YK. Low salt and low calorie diet does not reduce more body fat than same calorie diet: A randomized controlled study. Oncotarget 2018;9:8521-30.
Turner MJ, Avolio AP. Does replacing sodium excreted in sweat attenuate the health benefits of physical activity? Int J Sport Nutr Exerc Metab 2016;26:377-89.
Li CL, Wang HJ, Si QJ, Zhou J, Li KL, Ding Y. Association between urinary sodium excretion and coronary heart disease in hospitalized elderly patients in China. J Int Med Res 2018;46:3078-85.
Cogswell ME, Maalouf J, Elliott P, Loria CM, Patel S, Bowman BA. Use of urine biomarkers to assess sodium intake: Challenges and opportunities. Annu Rev Nutr 2015;35:349-87.
Karppanen H, Mervaala E. Sodium intake and hypertension. Prog Cardiovasc Dis 2006;49:59-75.
[Table 1], [Table 2]