|Year : 2020 | Volume
| Issue : 4 | Page : 393-397
Salt intake among women in an Urban resettlement colony of Delhi
P Aparna1, Harshal Ramesh Salve2, Anand Krishnan3, Lakshmy Ramakrishnan4, Sanjeev Kumar Gupta3, Baridalyne Nongkynrih3
1 Junior Resident, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Associate Professor, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
3 Professor, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
4 Professor, Cardiac Biochemistry, All India Institute of Medical Sciences, New Delhi, India
|Date of Submission||25-Aug-2019|
|Date of Decision||02-Oct-2019|
|Date of Acceptance||21-Oct-2020|
|Date of Web Publication||11-Dec-2020|
Centre for Community Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110 029
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Monitoring of population salt intake is essential for compliance with the WHO target of a 30% relative reduction in mean population salt intake. Objective: This study was conducted to estimate the daily salt intake and find the associated variables among adult women in an urban resettlement colony of Delhi. Methods: In this community-based cross-sectional study, 426 women aged 20–59 years from an urban resettlement colony were randomly selected. Sociodemographic details, anthropometric measurements, blood pressure, and morning spot urine samples were obtained. INTERSALT equation was used to estimate the 24-h salt intake from spot urine sodium. Association of salt intake with related variables was studied using t-test/analysis of variance, and P < 0.05 was considered to be significant. Results: A total of 426 women participated in the study, and 381 participants' urine samples could be collected. The study participants' mean age (standard deviation [SD]) was 34.5 (9.4) years. The mean salt intake (SD, 95% confidence interval) of the participants calculated using the INTERSALT equation was 7.6 (1.7, 7.5–7.8) g/day. The salt intake was significantly associated with educational status, occupation, marital status, socioeconomic status, blood pressure, and waist circumference. Waist circumference was found to have a significant positive linear relationship with daily salt intake. Conclusion: The daily salt intake of this population was well above the recommendation and had a positive linear relationship with waist circumference. Reduction in daily salt intake is a must to control the epidemic of hypertension.
Keywords: Hypertension, India, salt intake, sodium, spot urine
|How to cite this article:|
Aparna P, Salve HR, Krishnan A, Ramakrishnan L, Gupta SK, Nongkynrih B. Salt intake among women in an Urban resettlement colony of Delhi. Indian J Public Health 2020;64:393-7
|How to cite this URL:|
Aparna P, Salve HR, Krishnan A, Ramakrishnan L, Gupta SK, Nongkynrih B. Salt intake among women in an Urban resettlement colony of Delhi. Indian J Public Health [serial online] 2020 [cited 2021 Jan 21];64:393-7. Available from: https://www.ijph.in/text.asp?2020/64/4/393/303099
| Introduction|| |
Sodium is an essential element consumed in the form of dietary salt, required for the normal human physiology. However, high salt intake is associated with high blood pressure and its consequences such as cardiovascular disease and stroke., In India, hypertension is a key risk factor for leading causes of death such as ischemic heart disease and stroke. Excessive salt intake is also known to cause gastric cancer, obesity, osteoporosis, and chronic kidney disease.
The global action plan for prevention and control of noncommunicable disease has identified a reduction of salt intake by 30%, reduction in raised blood pressure by 25% to achieve a 25% reduction in premature mortality from noncommunicable diseases by the year 2025. The WHO has recommended a salt intake of <5 g per day for adults.
A systematic review done in India, which included studies from 1986 to 2014, showed overall mean weighted salt intake to be 10.98 g/day (95% confidence interval [CI]: 8.57–13.40). Few studies done in the recent past reported a mean salt intake almost double the recommendation.,, These studies used different methods to estimate the salt intake such as the 24-h dietary recall, 24-h urine sodium, and spot urine sodium. Although multiple nonconsecutive 24-h urine sodium is considered the gold standard, its limitations such as high participant burden leading to low response rate or insufficient sample collection make it an unlikely first choice in low-resource settings.,, Spot urine sodium is known to be a convenient and affordable alternative to 24-h urine collection to estimate the population salt intake. A study conducted in India also showed that methods based on spot urine samples can be used to estimate population salt intake, and the INTERSALT (International Study of Salt and Blood Pressure) equation gives a reasonable estimate for the same using morning spot urine sample.
Knowing the population salt intake is a necessity to plan a program at the national level to reduce salt intake. India is a country with diverse dietary practices owing to socioeconomic and cultural factors. Due to this diversity, our salt consumption also varies. Data on salt intake are sparse in our country. Hence, this study was conducted to estimate the mean salt intake and study its association with related variables among women in a resettlement colony of urban Delhi.
| Materials and Methods|| |
Study design and sampling
This was a community-based cross-sectional study conducted in an urban resettlement colony of South-East Delhi, Dakshinpuri Extension, in Ambedkar Nagar. It included women of the age 20–59 years and residents of the colony for a minimum of 6 months. The Health Management and Information System database which contains the details of the residents of Dakshinpuri Extension provided a list of participants from 6 of its blocks, which formed our sampling frame.
The sample size was calculated using standard deviation (SD) of the mean from the systematic review done in India. The sample size was calculated using the formula, n = (Z1-a/22SD2)/d2, where Z is the standard normal deviate (which is 1.96 at 5% alpha error), SD is the SD, and d is the absolute precision (taken as 0.12). After considering a nonresponse rate of 10% and rounding off, we arrived at a sample size of 450. Simple random sampling was done using Microsoft Excel, and 450 participants were selected. A list was made where the selected participants were sorted block wise. The participants with known history of heart or kidney failure, stroke, and liver disease; pregnant or lactating women; those who were recently started on diuretics (<2 weeks); and those with any disease that alters their dietary habits were excluded.
From October 2017 to December 2017, the investigator collected the data. The 450 participants' houses were visited, and participants were interviewed with a pretested, semi-structured questionnaire with sociodemographic details. The Updated Kuppuswamy Scale was used to classify the participants based on their socioeconomic status. This was followed by recording of blood pressure with a calibrated standard blood pressure monitor (Omron HEM7121), weight by a calibrated digital weighing machine (Equinox), height, and waist circumference with a constant tension tape. After this, the participants were handed over a sterile urine culture bottle for collection of early morning urine sample the next day.
Urine collection and laboratory analysis
The participants were instructed to collect their fasting morning midstream urine sample of about 5 ml and store it in a cool place away from sunlight. If the participant was menstruating, her urine sample was collected next week. In case the participants forgot to collect the sample, they were approached everyday till the sample could be collected or the participants refused, whichever was earlier.
Four milliliters of urine was transferred from the culture bottle through a pipette to 2 prelabeled storage vials. The rest of the urine was discarded appropriately. The two vials of 2 ml each urine were kept in a storage box kept in a vaccine carrier and stored at 2–8 degree centigrade. These samples were transported the same day evening to the laboratory.
Out of the selected sample of 450 participants, three were ineligible (pregnant/lactating) and five had moved out. Of the remaining 442 participants, 11 were not available during the three visits made and five refused to take part, giving a response rate of 96.4% (426) for participation. About 86% (381) of the participants gave the urine sample, and the others either refused to give the sample or the sample could not be collected after four visits.
The urine analysis was conducted at the laboratory of the Department of Cardiac Biochemistry, AIIMS, New Delhi. Urine sodium and potassium were estimated by indirect ion-selective electrode method in auto-analyzer Beckman Coulter AU 680. Urine creatinine was estimated by Jaffe's method in auto-analyzer ROCHE Modular P.
Urine sodium and potassium values were obtained in mEq/L, and urine creatinine was obtained in mg/dL. These values were used for the calculation of 24-h urine sodium using the INTERSALT equation, which is one of the equations used to estimate 24-h urine sodium using the spot urine sodium and is found to provide a reasonable estimate of mean population sodium intake. Apart from urine sodium, this equation uses variables such as urine potassium and creatinine, body mass index (BMI), and age for 24-h sodium estimation. The 24-hour mean urine sodium estimate obtained with this equation in milligram was multiplied with 2.54 to obtain daily salt intake in milligram.
2.54 × 23× (5.07 + [0.34 × spot Na (mmol/L)] - [2.16 × spot Cr (mmol/L)] - [0.09 × spot K (mmol/L)] + [2.39 × BMI (kg/m2)] + [2.35 × age (years)]– [0.03 × age2 (years)]).
As a part of internal quality control, every 10th sample was stored at zero degree centigrade for retesting. These were retested, and the correlation coefficient was calculated.
Mean salt intake was expressed in gram per day. SD and 95% CI were also reported. Bivariable analysis was done between mean salt intake and associated variables, namely education, occupation, marital status, socioeconomic status, blood pressure, and waist circumference, using t-test and analysis of variance, and a P < 0.05 was considered statistically significant. Multivariable linear regression was done to find the association between daily salt intake and related variables.
This study was in compliance with the Helsinki Declaration. Ethical clearance was obtained from the Institutional Ethics Committee with reference number IECPG-228/23.08.2017. Participant information sheet was read out to each participant, and written consent was taken.
| Results|| |
The interview schedule was administered to a total of 426 participants, and urine sample could be collected from 381 participants, which was the final sample size. The mean age (SD) of the participants in the study was 34.9 (9.4) years, and majority of them were between 20 and 39 years. About three-fourths of the participants were currently married. A little more than half of the participants belonged to nuclear families. About 78% of the participants were educated up to high school certificate or more. Majority of the participants were homemakers only. About 43% of the participants belonged to lower middle class [Table 1].
|Table 1: Distribution of participants by sociodemographic factors (n=381)|
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None of the participants reported smoking or consuming alcohol. One-third of the participants were overweight, nearly 20% of them were obese, and 60% of the participants had abdominal obesity. About one-fourth of the participants (n = 96) had normal blood pressure and 31.8% (n = 121) were hypertensives.
The mean urine sodium, potassium, and creatinine in the early morning urine samples were found to be 114.3 mEq/L, 33.4 mEq/L, and 76.2 mg/dL, respectively, and their distribution was not normal, as summarized in [Table 2].
|Table 2: Urinary sodium, potassium, and creatinine in the spot sample (n=381)|
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The mean daily salt intake (SD) calculated using the INTERSALT equation was 7.6 (1.7) g. The samples (10%) that were retested showed excellent correlation with the first test values.
In bivariable analysis to compare the mean salt intake across categories of various variables, a significant difference was seen in the categories of education status, occupation, marital status, socioeconomic status, blood pressure, and waist circumference, which is shown in [Table 3].
|Table 3: Bivariable analysis between daily salt intake (spot urine sodium) and associated variables (n=381)|
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A multivariable linear regression was run to predict daily salt intake from educational status, marital status, occupation, socioeconomic score, average systolic blood pressure, average diastolic blood pressure, and waist circumference. These variables statistically significantly predicted daily salt intake, F (7, 336) = 22.45, P < 0.001, R-squared = 0.319. Among the predictor variables, waist circumference added statistically significantly to the prediction, P < 0.001, as shown in [Table 4].
|Table 4: Multivariable linear regression between salt intake (g) and related variables (n=381)|
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| Discussion|| |
Salt intake of the population
The mean salt intake of the study population based on morning spot urine sodium was found to be 7.6 g/day (SD 1.7, 95% CI: 7.5–7.8). This value is above the WHO recommendation of <5 g/day. The study conducted by Johnson et al. used 24-h urine sodium and estimated the mean salt intake to be 7.69 g/day (95% CI: 6.54–8.84) among women in Delhi and Haryana region. This study reported that the salt intake was higher in slum regions followed by rural region and least in urban region. In the slum region of Delhi and Haryana, this study found the mean salt intake to be 8.96 g/day (95% CI: 7.66–10.26) among both men and women. Considering that our study was done in an urban resettlement colony, our estimate is closer to these figures. This observation is similar to our study even though our study used the spot urine sodium to estimate the salt intake, thereby reinforcing the claim that spot urine sodium can give an estimation of the mean salt intake of the population.,
The mean salt intake reported by other studies done in India and internationally is higher compared to our study.,, The difference in the intake can be due to our study population being women. Studies have shown lesser salt intake among women compared to men., However, the mean salt intake of this population is well above the recommendation.
It has been established that the major contribution to the daily salt intake in developing countries is discretionary salt. To decrease the intake of salt in the population, we need to focus on cutting down the discretionary salt use. A study by Ravi et al. in South India showed pulse-based dishes, cereal-based dishes, and vegetable-based dishes to be the major contributors to daily salt intake. Hence, cutting down salt usage in staple food plays an important role. The use of low-sodium salt may prove to be beneficial, however, its availability is to be regulated as it is contraindicated in patients with renal disease, cardiac problems, and diabetes and patients on potassium-sparing diuretics and painkillers. Awareness needs to be created regarding its availability and contraindications among both the health-care professional and the general public.
Association between daily salt intake and related variables
There was a significant difference in the mean salt intake of various classes of socioeconomic scale, with higher socioeconomic status having a lesser intake as seen in another study. This may also be the reason for lesser salt intake in urban areas.
There was a significant difference in the mean salt intake of abdominally obese and nonobese participants. The salt intake among the normotensives, prehypertensives, and hypertensives was also significantly different from hypertensives consuming more salt than the normotensives.
Waist circumference had a significant positive linear relationship with daily salt intake after adjusting for other variables, as proved earlier., In multiple linear regression, no significant linear relationship was observed between blood pressure and salt intake, which is not surprising as it is a common finding in studies of this kind due to measurement errors., These errors can be due to the actual errors in the measurement of either salt intake or blood pressure and diurnal variation of blood pressure. The educational status seemed to have no effect on the daily salt intake, as seen in Johnson et al.'s study. The daily salt intake was also found to be not related to the marital status, occupation, and socioeconomic score of the participants after controlling for other variables. This study being cross-sectional, doesn't reflect the exact association between these variables.
The effect of age, weight, and height on daily salt intake could not be assessed as these variables were part of the INTERSALT equation used to estimate the 24-h urine sodium.
These findings stress the need for strong national policies to control the salt level of the population. It is to be supplemented by behavioral changes instilled in the population by health-care providers and IEC activities.
As spot urine sodium was used to estimate the daily salt intake, our estimate cannot be applied at the individual level. However, with a good sample size, we arrived at the mean population sodium intake.
| Conclusion|| |
The mean population salt intake among the women of this urban resettlement colony was above the WHO recommendation of daily salt intake and was associated with educational status, occupation, marital status, socioeconomic status, blood pressure, and waist circumference. Waist circumference was found to have a significant positive linear relationship with daily salt intake. Almost 30% of this population was found to be hypertensive. This calls for intervention at both individual and population levels to reduce the salt intake and prevent its consequences.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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