The objective of this study was to develop a new method named the "one-week salt estimation method" that could estimate an individual's salt intake and the sources of salt in the diet, and to evaluate this new method with a 24-h urine collection. The new method estimates salt intake from: (1) household cooking by weighing the family salt container and other high-salt condiments or sauces at the beginning and end of a week; (2) processed food according to established China food composition figures; and (3) cafeteria or restaurant meals using the results of previous studies. Consumption of salt additives and major salt contained foods and salt intake related eating habits were collected using a structured simple seven-day questionnaire. In order to validate the method, we studied 37 individuals from 11 families using the new method and 26 of these participants collected seven concurrent 24-h urine samples. The average salt intake for the 26 participants was 15.6+/-5.5 g/person/day (mean+/-standard deviation) by the 24-h urine collection and 13.7+/-6.5 g/person/day by the new method. The difference was 1.8+/-4.2 g/day/person (p=0.037). The Pearson correlation coefficient was 0.762 (p<0.001) and the partial correlation coefficient was 0.771 (p<0.001) when adjusted for family code. Bland-Altman Plot showed the average of the difference between the two methods was -1.83, with 95% limits of -10.1 to 6.5 g/person/day. The new method showed that 43.7% of salt intake came from household cooking (33.5% from cooking salt, 10.2% from other condiments and sauces), 12.9% from processed food, and 43.4% from eating out. In conclusion, despite its limitations of underestimating salt intake, the "one-week salt estimation method" is easier for people to implement and is likely to provide useful information that highlights the excessively high intake of salt and its sources, and in turn is helpful in guiding dietary salt reduction.
AD - The George Institute for Global Health at Peking University Health Science Center, Level 18, Tower B, Horizon Tower, 6, Zhichun Road, Haidian District, 100088 Beijing, China. zhang.lu@imicams.ac.cn.The objective of this study was to develop a new method named the "one-week salt estimation method" that could estimate an individual's salt intake and the sources of salt in the diet, and to evaluate this new method with a 24-h urine collection. The new method estimates salt intake from: (1) household cooking by weighing the family salt container and other high-salt condiments or sauces at the beginning and end of a week; (2) processed food according to established China food composition figures; and (3) cafeteria or restaurant meals using the results of previous studies. Consumption of salt additives and major salt contained foods and salt intake related eating habits were collected using a structured simple seven-day questionnaire. In order to validate the method, we studied 37 individuals from 11 families using the new method and 26 of these participants collected seven concurrent 24-h urine samples. The average salt intake for the 26 participants was 15.6+/-5.5 g/person/day (mean+/-standard deviation) by the 24-h urine collection and 13.7+/-6.5 g/person/day by the new method. The difference was 1.8+/-4.2 g/day/person (p=0.037). The Pearson correlation coefficient was 0.762 (p<0.001) and the partial correlation coefficient was 0.771 (p<0.001) when adjusted for family code. Bland-Altman Plot showed the average of the difference between the two methods was -1.83, with 95% limits of -10.1 to 6.5 g/person/day. The new method showed that 43.7% of salt intake came from household cooking (33.5% from cooking salt, 10.2% from other condiments and sauces), 12.9% from processed food, and 43.4% from eating out. In conclusion, despite its limitations of underestimating salt intake, the "one-week salt estimation method" is easier for people to implement and is likely to provide useful information that highlights the excessively high intake of salt and its sources, and in turn is helpful in guiding dietary salt reduction.
PY - 2015 SN - 2072-6643 (Electronic)