Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-14T17:22:59.570Z Has data issue: false hasContentIssue false

Evaluating population salt reduction programmes worldwide: the risk of cutting corners!

Published online by Cambridge University Press:  04 December 2017

Francesco P Cappuccio*
Affiliation:
WHO Collaborating Centre for NutritionWarwick Medical SchoolThe University of WarwickGibbet Hill Road, Coventry CV4 7AL, UK
Lanfranco D'Elia
Affiliation:
Federico II University of Naples, Naples, Italy and WHO Collaborating Centre for Nutrition, Coventry, UK
Rights & Permissions [Opens in a new window]

Abstract

Type
Invited Commentary
Copyright
Copyright © The Authors 2017 

The question of how to assess salt intake in individuals and populations has been framed since the 1970s( Reference Liu, Dyer and Cooper 1 ). Salt intake is extremely variable between individuals as well as from day to day in the same person( Reference Liu, Cooper and McKeever 2 Reference Lerchl, Rakova and Dahlmann 4 ). Therefore, even a single measurement of the daily amount of Na excreted in the urine (often regarded as the ‘gold standard’) is inadequate for assessing the salt consumption of an individual( Reference Ji, Sykes and Paul 3 ). In a well-conducted physiological study, single 24 h urine collections at intakes ranging from 6 to 12 g salt/d were not suitable to detect a 3 g difference in individual daily salt intake( Reference Lerchl, Rakova and Dahlmann 4 ). Repeated measurements of 24 h urinary Na improve precision, suggesting multiple 24 h urine collections over time are necessary to assess a person’s salt intake( Reference Lerchl, Rakova and Dahlmann 4 ). However, the interest in using easier alternative methods has led to a renewed curiosity into the validation of methods based primarily on estimating 24 h urinary Na excretion (hence salt intake) from spot urine samples. In an original systematic review including 1 380 130 participants from twenty studies, spot, timed and overnight urine samples showed greater intra-individual and inter-individual variability than 24 h urine collections. There was a wide range of correlation coefficients between 24 h urine Na and other measures of Na excretion( Reference Ji, Sykes and Paul 3 ). Subsequently, numerous validation studies have been published, comparing 24 h urine collections v. estimates of daily Na excretion from spot urines extrapolated with the application of different formulas. From a variety of population analyses spot urines (irrespective of the formulas used to estimate daily consumption) lead to biased estimates of 24 h urinary Na excretion with overestimates at lower levels and underestimates at higher levels( Reference Cogswell, Wang and Chen 5 Reference Petersen, Wu and Webster 9 ), making these measures not suitable to assess an individual’s Na excretion (salt intake) in cross-sectional and prospective studies( Reference Campbell 10 ).

A different question has been put more recently as to whether we can estimate the average Na excretion for the population using spot urine samples, avoiding the burden of 24 h urinary collections in epidemiological settings( Reference Petersen, Wu and Webster 9 , Reference Huang, Crino and Wu 11 ). This question has become repeatedly common given the need to assess average population salt consumption and to monitor and evaluate intervention programmes of population salt reduction over time within the UN resolution and WHO action plan to reduce global CVD by 2025( 12 ).

The analysis of different South African population samples from various ethnic backgrounds (white, black, Indian), reported by Swanepoel et al. in this journal, is an important step forward( Reference Swanepoel, Schutte and Cockeran 13 ). It validates three formulas (Kawasaki, Tanaka and INTERSALT)( Reference Cogswell, Wang and Chen 5 , Reference Kawasaki, Itoh and Uezono 14 Reference Brown, Dyer and Chan 16 ) commonly used to estimate 24 h urinary Na excretion from spot urine samples against the direct measurements of Na excretion using a 24 h urine sample. The authors pooled data from three cross-sectional population studies in South Africa: the African-PREDICT study, including 470 black and white men and women aged 20–30 years; the Thusa-Bothle study, including 104 black women aged 35–65 years; and the KwaZulu-Natal study, including 107 Indian women aged 18–50 years. All three studies used common methodologies for collecting and analysing urine samples. Several measurements were considered: comparison of mean population Na excretions (estimated and measured); Bland–Altman plots( Reference Bland and Altman 17 ) to calculate the bias in the spot estimate v. the ‘gold standard’ (24 h urinary excretion); proportional bias by linear regression of the difference in estimates v. the mean; interclass correlation coefficients between estimated and measured Na; and sensitivity and specificity of estimated Na excretion to correctly classify the mean population Na excretion below the WHO’s recommended target of 2000 mg Na/d (5 g salt/d).

The search for validity in the framework of the global action plan is not so much to simply estimate the average population mean( Reference Petersen, Wu and Webster 9 ), or the proportion of the population with a salt intake ‘above’ a specific threshold( Reference Huang, Crino and Wu 11 ), since the majority of populations globally are above that threshold( Reference Powles, Fahimi and Micha 18 ). The validations of two alternative measures should be able to: (i) estimate the absolute difference in salt consumption between two time points (measuring the effectiveness of a population programme of salt reduction); and (ii) estimate the proportion of the population ‘below’ a threshold of 5 g salt/d.

Crude direct comparisons between population means by Swanepoel et al. indicated that the Kawasaki and Tanaka formulas overestimate urinary Na excretion compared with 24 h urinary Na, whereas the INTERSALT formula – in a couple of cases – underestimates it. However, the degree of bias obtained from the Bland–Altman plots and the proportional bias measured indicate that all three formulas fall short of an ideal scenario. Both the Kawasaki and the Tanaka formulas introduce a large negative bias (2242 and 837 mg Na, or 5·6 and 2·1 g salt, respectively) while the INTERSALT formula introduces a positive bias (161 mg Na or 0·4 g salt).

Furthermore, the proportional bias is the highest with the INTERSALT formula. As expected, interclass correlation coefficients are very low (the highest being 0·29 in white participants using the INTERSALT formula), even considering that the spot samples were not ‘independent’ of the 24 h samples. The important implication of these sets of results for policy is that all these formulas introduce a bias leading to a high degree of inaccuracy in the baseline estimation of population salt consumption, and, more importantly, do not enable them to detect small changes in population salt consumption over time ensuing from a salt reduction programme. For instance, the use of the Kawasaki or Tanaka formula would not have been able to detect the 1·4 g change in daily salt consumption in the 8-year UK national salt reduction programme, and a population change of 0·4 g – still an important change – could also be missed by the INTERSALT formula. The effectiveness of the population intervention would therefore be missed, with crucial implications for further political and industrial support to sustained salt reduction programmes and public health policies towards the ambitious, and yet achievable, WHO global target.

Swanepoel et al.’s analysis indicates that the sensitivity of all three formulas is high. This is not a very useful measure in the context of the evaluation of population salt reduction programmes. All countries in the world eat far more than the 5 g salt/d set by the WHO as target, and, even with successful short-term reductions, the proportion of those eating less than 5 g/d could still be very low despite successful reduction of mean levels. Specificity, on the other hand, is paramount. The specificity of all three formulas is <10 %, i.e. they are all unable to detect an increase in the proportion below the threshold. In other words, none of the formulas would be suitable to evaluate a population salt reduction programme accurately, even considering the single objective of measuring the proportion achieving target thresholds, with immediate risk to the continuation of the programme.

In conclusion, Swanepoel et al.’s analysis, while confirming the presence of biases and shortcomings in the use of spot urines to estimate population salt intake when compared with 24 h urine samples, is the first to acknowledge and discuss the important features required by a validation study to be able to inform public health recommendations for an effective evaluation and monitoring of long-term population salt reduction programmes. Spot urines are no substitute for 24 h urine collections in monitoring population salt reduction.

Acknowledgements

Financial support: This work received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. The work was carried out under the remit of the WHO Collaborating Centre for Nutrition (UNK-257). However, the publication does not necessarily represent the decisions or the stated policy of the WHO; and the designations employed and the presentation of material do not imply the expression of any opinion on the part of the WHO. Conflict of interest: None to declare. Authorship: F.P.C., critical appraisal of the original paper and commentary. L.D., critical appraisal of the original paper and commentary. Ethics of human subject participation: Not applicable.

References

1. Liu, K, Dyer, AR, Cooper, RS et al. (1979) Can overnight urine replace 24-hour urine collection to assess salt intake? Hypertension 1, 529536.Google Scholar
2. Liu, K, Cooper, R, McKeever, J et al. (1979) Assessment of the association between habitual salt intake and high blood pressure: methodological problems. Am J Epidemiol 110, 219226.Google Scholar
3. Ji, C, Sykes, L, Paul, C et al. (2012) Systematic review of studies comparing 24-h vs spot urine collections for estimating population salt intake. Rev Panam Salud Publica 32, 307315.Google Scholar
4. Lerchl, K, Rakova, N, Dahlmann, A et al. (2015) Agreement between 24-hour salt ingestion and sodium excretion in a controlled environment. Hypertension 66, 850857.Google Scholar
5. Cogswell, ME, Wang, C-Y, Chen, T-C et al. (2013) Validity of predictive equations for 24-h urinary sodium excretion in adults aged 18–39 y. Am J Clin Nutr 98, 15021513.Google Scholar
6. Wang, C-Y, Cogswell, ME, Loria, CM et al. (2013) Urinary excretion of sodium, potassium, and chloride, but not iodine, varies by timing of collection in a 24-hour calibration study. J Nutr 143, 12761282.Google Scholar
7. Ji, C, Miller, MA, Venezia, A et al. (2014) Comparisons of spot vs 24-h urine samples for estimating salt intake: validation study in two independent population samples of adults in Britain and Italy. Nutr Metab Cardiovasc Dis 24, 140147.Google Scholar
8. Mente, A, O’Donnell, MJ, Dagenais, G et al. (2014) 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 32, 10051015.Google Scholar
9. Petersen, KS, Wu, JH, Webster, J et al. (2017) Estimating mean change in population salt intake using spot urine samples. Int J Epidemiol 46, 15421550.Google Scholar
10. Campbell, N (2014) 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 32, 24992500.Google Scholar
11. Huang, L, Crino, M, Wu, JHY et al. (2016) Mean population salt intake estimated from 24-h urine samples and spot urine samples: a systematic review and meta-analysis. Int J Epidemiol 45, 239250.Google Scholar
12. World Health Organization (2013) WHO Global Action Plan for the Prevention and Control of Noncommunicable Diseases 2013–2020. Geneva: WHO.Google Scholar
13. Swanepoel, B, Schutte, AE, Cockeran, M et al. (2017) Monitoring the South African population’s salt intake: spot urine v. 24 h urine. Public Health Nutr. Published online: 10 November 2017. doi: 10.1017/S1368980017002683.Google Scholar
14. Kawasaki, T, Itoh, K, Uezono, K et al. (1993) A simple method for estimating 24 h urinary sodium and potassium excretion from second morning voiding urine specimen in adults. Clin Exp Pharmacol Physiol 20, 714.Google Scholar
15. Tanaka, T, Okamura, T, Miura, K et al. (2002) A simple method to estimate population 24-h urinary sodium and potassium excretion using a casual urine specimen. J Hum Hypertens 16, 97103.Google Scholar
16. Brown, IJ, Dyer, AR, Chan, Q et al. (2013) Estimating 24-hour urinary sodium excretion from casual urinary sodium concentrations in Western populations: the INTERSALT study. Am J Epidemiol 177, 11801192.Google Scholar
17. Bland, JM & Altman, DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8, 135160.Google Scholar
18. Powles, J, Fahimi, S, Micha, R et al. (2013) Global, regional and national sodium intakes in 1990 and 2010: a systematic analysis of 24h urinary sodium excretion and dietary surveys worldwide. BMJ Open 3, e003733.Google Scholar