Fleming Mwashako Mwalugho
Sheffield Hallam
Research
Introduction
High sodium content is a global issue. Most countries have enacted laws to help curb the sodium content in food. However, some of the enactments are not fully enforced exposing the food industry to high food sodium especially in processed food and in certain cuisines. It is now established that high salt content leads to an increase in blood pressure and greatly increases the risk for cardiovascular diseases. According to (Du et al., 2022) cardiovascular diseases are one of the leading causes of death in most western countries accounting for more than 30% of the deaths. It is widely accepted that the consumption of high sodium foods is above the Food Standard Agency (FSA) recommended levels in the United Kingdom.
The WHO targets a 30% of salt reduction by 2025 with an adult consumption recommendation of fewer than 5 grams of salt per day. The United Kingdom set a target to reduce salt content for more than 85% of food categories ten years ago and this resulted in more than 20% reduction in high blood pressure and cardiovascular disease-related deaths. In China, intake of sodium is very high ranging from 12-14g/d, this is accompanied by the increase in the consumption of sauces like soy sauce which account for the highest rates, and processed food that also has high sodium content. This is also witnessed in the UK where most urban populations indulge in foreign cuisines. In developed countries, it is estimated that processed foods account for more than 75% of the salt consumed (Tan et al., 2019). Studies have shown that Chinese food, ingredients, and accompaniments in the United Kingdom contain higher levels of sodium than recommended by the FSA 2024 (Tan et al., 2019). Further in a study that was conducted in 2017 most UK products met the FSA standards but only 13% of Chinese products met the recommended FSA standards for sauces and Ingredients. Studies have demonstrated that it is possible to reduce salt content in Chinese food. Following the enactment of policies in past on salt regulation in the UK, there is a substantial decrease in the sodium content in Chinese cuisines this is in comparison to china where the same products are consumed. The most important strategy in reducing salt consumption is identifying the amount of salt consumed and how it is consumed. The aim of the study was to establish the sodium content in Chinese meal components, ingredients, and sauces and to determine if they are in line with the FSA 2024 standards. The final report provides actual values of salt content and helps in reviewing targets and informing consumer decisions. This was achieved by systematically collecting data on sodium levels on the UK processed Chinese products and comparing the sodium values against the UK FSA 2024 standard on salt content.
Literature review
He & MacGregor (2018) in a research on the relationship between high salt intake and cardiovascular diseases propose that a high level of sodium in food is highly detrimental and takes a toll on the life of a person. They explain that high sodium in foods increases the risk of hypertension which is dangerous, especially for people with comorbidities. The above argument is further supported by Bandy et al (2021) in research on U.K food safety and sodium levels found that high sodium levels increased the risk of cardiovascular diseases, hypertension, renal diseases, and stroke by 55% in a sample population of 1045 on a study conducted between 2019 and 2021. A study conducted by (Barton et al., 2011) raised blood pressure accounted for 47% of strokes and this is linked to evidence that high consumption levels of salt consumed in diets is the leading cause for high blood pressure.
Elsewhere Rippin et al., (2019) in a research on the effects of high sodium levels in energy foods in the UK by use of urinary sodium surveys, also found that the risk of hypertension and stroke was increased by 49% in a study sample size of 2200 drawn from various age groups. Additionally, the study also revealed, that 76% of the sodium taken was drawn from processed foods. The above therefore creates the need to investigate sodium levels in foods in the UK if they are in line with the F.S.A 2024 standards.
Antúnez et al., (2019) in a research on the F.S.A guidelines and standards on foods, explains various standards. Among the main findings is that there are various subcategories of targets to be met by food manufacturers by 2024. For instance, slices of bacon are set at 1035 sodium (2.59g of sodium) per 100 grams of bacon and 430mg sodium (1.08g sodium) per 100 grams of sausages. Tan et al., (2019) in research on the same, support the above findings by further giving more targets as set out by the F.S.A. further, the author lists and explains the targets like meat pies with a target of 370 mg sodium (0.93 sodium) per 100 gram of meat pie and standard of 320mg sodium (0.8g salt) for meat-based pasties by 2024.
Menyanu, Russell & Charlton (2019) further in their discussion they expound more on the above standards by discussing several standards and their anticipated importance. Among the foods standards the writers discuss are the above and more such as pizza, soups, crisps, snacks and biscuits. Sampling the standards, the target for biscuits is 220 mg sodium (0.55g salt) and for children’s main meals is 685 mg sodium (1.71g salt) per 100 mg of their food. The authors further posit that the above targets are part of the campaign started in 2003 by the F.S.A to reduce salt intake to 6mg per day per person by 2024.
Zhang et al., (2020) in research on Chinese processed foods, argues that Chinese processed foods are among the most popular cuisines in the U.K. additionally the writer argues that Chinese foods are four-fold saltier and higher in sodium in the U.K. Tan et al., (2019) further agree with the above by discussing that Chinese foods have high salt levels with an average of 13 g per day. Additionally, he explains that Chinese products such as sauces account up to 6% of total salt levels.
He et al., (2018) in their research reaffirms the above findings through research on Chinese salt and sodium levels research conducted in 2018-2019. In the study findings, the Chinese cuisine had more salts than the U.K foods. Specifically, from the researcher’s findings on instant noodles, of 10 sampled, 4 had more salt levels as compared to 2 of the U.K noodles. Additionally, 8 out of 11 food groups in China had more salt and sodium content compared to the same sampled in the UK. On average the writer affirms that Chinese products mostly non-processed had 4.5 times more salt than those from U.K. The comparison was done largely on non-processed and large groups of processed foods with little focus on processed foods.
In the longitudinal study conducted by (Ni Mhurchu et al., 2010) there was high sodium content in the food served in UK households. More than 50% of the salt consumed was added as table salt (Ni Mhurchu et al., 2010). The other 50% was mainly salt added at the point of processing ready meals. With the increase in ready meal consumption, there has been a substantial increase in dietary sodium levels in the UK (Ni Mhurchu et al., 2010). The intake of Chinese food from supermarkets has also increased over time reducing the gains that were instituted by the FSA in 2004.
In the UK the FSA recommends the reduction of salt intake to 6 grams in adults, it is also estimated that 75% of salt intake is derived from the consumption of processed foods retailed in supermarkets such as Tesco and Sainsbury with 27.5% and 16% respectively. This project was aimed at assessing the salt content in Chinese food, sauces, ingredients, and accompaniments sold in the above supermarkets.
Methodology
Data collection
The chosen method for this study was a systematic sampling of main Chinese food from two outlets, Tesco and Sainsbury. The outlets were chosen based on the number of Chinese cuisines available on their menu. One of the advantages of using systematic sampling is its convenience and the ability to single out samples and access the desired sample size and characteristics (Elfil & Negida, 2017). However, this is limiting as it may not be representative of the entire population. Further, there was a risk of data manipulation which was countered by ensuring the data was collected randomly (Elfil & Negida, 2017)..
A systematic survey was conducted in Tesco and Sainsbury with a primary goal of establishing the mean average sodium concentration in the main Chinese cuisine categories that contribute to salt in the diet bearing in mind most Chinese food uses soy products and other refined oils (Diez-Simon et al., 2020). Data was collected to include mainly Chinese cuisines, however, there was data from Thai and Japanese cuisines that had similar formulations. The data include quality ranges from top middle and bottom, this also included chilled, frozen, and ambient cuisines from across all the categories. For each cuisine, the data also included the weight of the product, price, brand name, serving size, and the amount of salt/100g. Not all products had salt contents, therefore, those that had nil or missing data were rounded up to zero for consistency.
Data analysis
The data was collected and stored in an excel datasheet. It was then imported to the Statistical Package for Social Sciences (SPSS) version 26, where descriptive and inferential statistics were conducted. Out of the 49 observations surveyed, the Chinese ready meal was 82 % followed by the Chinese ready sauces which were 8% of the total product category, and lastly, the Japanese ready sauces and Thai ready meal sauces had 2% each. Descriptive statistics were used to measure the mean value, frequency, standard deviation, and median.
An independent t-test was used to investigate if the mean of the two unrelated groups statistically differed where Salt g/100g was used as the dependent variable and the product subcategory was used as the independent variable. Seven observations were used to conduct the T independent t-test which produced 46 observations as the degrees of freedom. The total number of observations in Tesco was 23 while the total number of observations in Sainsbury’s was 25.
ANOVA test was used to determine the analysis of variance where more Chinese products were selected (89%) as compared to other products from Japan and Thai cuisines. Further, the One-way ANOVA analysis involved three groups that include the complete Chilled meal, complete ambient meal, and complete frozen meal. The product subcategories were used as the independent variable and the Salt g/100g was used as the dependent variable. A subsequent post hoc test was done to detect any significant difference in means between the groups. The average salt content was measured against the FSA 2024 guidelines on sauce-based foods (≤6 g/100 g). (Reference)
Results
Below are the results as analyzed using the SPSS 26 statistical tool. They included descriptive and inferential analysis.
| Statistics | ||||||||
| Product category | Product sub-category | Outlets | Product Name | Brand name | Brand type | Quality range | ||
| N | Valid | 49 | 49 | 49 | 49 | 49 | 49 | 49 |
| Missing | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
Table 1.1: frequencies product category
The total number of valid observations was 49 with 0 missing values for all product categories.
| Product category | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Chinese ready meal | 42 | 85.7 | 85.7 | 85.7 |
| Chinese ready sauces | 4 | 8.2 | 8.2 | 93.9 | |
| Japanese ready sauces | 1 | 2.0 | 2.0 | 95.9 | |
| Japanese ready meals | 2 | 4.1 | 4.1 | 100.0 | |
| Total | 49 | 100.0 | 100.0 | ||
Table 1.2: frequencies product subcategory
There were four categories of Chinese cuisine processed foods products (n=4). There were 8.2% (n=4) Chinese ready sauces, 85.7% (n=42) Chinese ready meals, 4.1% (n=2) Japanese ready meal and 2% (n=1) Japanese ready sauces.
Table 1.3: product subcategories
| Product sub-category | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | chilled meal , complete | 27 | 55.1 | 55.1 | 55.1 |
| Ambient meal complete | 20 | 40.8 | 40.8 | 95.9 | |
| frozen meal complete | 2 | 4.1 | 4.1 | 100.0 | |
| Total | 49 | 100.0 | 100.0 | ||
There were three subcategories of the product which included Chilled meal, ambient meal, and frozen meal. There were 55.1% (n=27) Chilled meals, 40.8% (n=20) ambient meals, and 4.1% (n=2) frozen meals.
Table 1.3: frequencies_ Brand name
| Brand name | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | 1 | 25 | 51.0 | 51.0 | 51.0 |
| 2 | 24 | 49.0 | 49.0 | 100.0 | |
| Total | 49 | 100.0 | 100.0 | ||
There were two brand names included Sainsbury’s and Tesco. There were 25 Sainsbury’s outlets accounting for 51% and 24 Tesco outlets representing the other half.
Table 1.4: frequencies quality range
| Quality range | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Basic | 2 | 4.1 | 4.1 | 4.1 |
| Middle | 46 | 93.9 | 93.9 | 98.0 | |
| Top | 1 | 2.0 | 2.0 | 100.0 | |
| Total | 49 | 100.0 | 100.0 | ||
Across all products, 4.1% (n=2) were basic range quality, 93.9% (n=46) mid-range quality and 2% (n=1) top range quality product.
Table 2: independent T test _ product category
Group statistics
Independent sample t Test
| Group Statistics | ||||||||||||||||
| Brand name | N | Mean | Std. Deviation | Std. Error Mean | ||||||||||||
| Salt g/100g | 1 | 23 | 1.488696 | 1.9117681 | .3986312 | |||||||||||
| 2 | 24 | .971563 | .9326120 | .1903686 | ||||||||||||
|
Independent Samples Test |
||||||||||||||||
| Levene’s Test for Equality of Variances | t-test for Equality of Means | |||||||||||||||
| F | Sig. | t | df | Sig. (2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence Interval of the Difference | |||||||||
| Lower | Upper | |||||||||||||||
| Salt g/100g | Equal variances assumed | 4.027 | .051 | 1.186 | 45 | .242 | .5171332 | .4358778 | -.3607698 | 1.3950361 | ||||||
| Equal variances not assumed | 1.171 | 31.606 | .250 | .5171332 | .4417545 | -.3831310 | 1.4173973 | |||||||||
The independent T-test indicated a difference in the salt content t (46) =1.253, p=0.043. The salt g/100g did not differ significantly between Tesco branded products (M=1.49, SD=1.91) and Sainsbury’s branded products (M=0.97, SD=0.93).
Further, the independent sample t-test was run where Salt g/100g was used as the dependent variable while product-subcategory was used as the independent variable. The total number of observations in Tesco was 23 while the total number of observations in the Sainsbury’s is 25. The mean of Tesco is 1.49 with a standard deviation of 1.91, while the mean of is 0.0953 with a mean of 0.953 with a standard deviation of 0.918 (Refer to table 2).
Table 3: One-way Anova
| Descriptive | ||||||||
| Salt g/100g | ||||||||
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | ||
| Lower Bound | Upper Bound | |||||||
| chilled,meal ,complete | 27 | .994352 | .9232977 | .1776887 | .629107 | 1.359596 | .0800 | 4.6000 |
| Ambient meal complete | 18 | 1.645000 | 2.1124289 | .4979043 | .594514 | 2.695486 | .2000 | 8.0000 |
| frozen meal complete | 2 | .550000 | .0707107 | .0500000 | -.085310 | 1.185310 | .5000 | .6000 |
| Total | 47 | 1.224628 | 1.5003789 | .2188528 | .784100 | 1.665155 | .0800 | 8.0000 |
| ANOVA | |||||
| Salt g/100g | |||||
| Sum of Squares | df | Mean Square | F | Sig. | |
| Between Groups | 5.523 | 2 | 2.761 | 1.239 | .299 |
| Within Groups | 98.029 | 44 | 2.228 | ||
| Total | 103.552 | 46 | |||
Results for One-Way ANOVA for the measure of salt content g/100g
The Chilled meal, ambient meal and frozen meal identified were not significant F (2, 44) = 1.24, p = 0.299. The degree of freedom between the groups is 2, and the degree of freedom within the group is 45. The mean of the Chilled meal is 0.99g and the standard deviation is 0.923. The mean of the ambient meal is 1.65g and the standard deviation is 2.11.
The mean of the frozen meal was 0.55g and the standard deviation is 0.07. The sum of squares between the groups is 5.52 and the sum of squares within the group was 98.03. The p-value is 0.26 which is greater than 0.05 thus we fail to reject the null hypothesis and conclude there is no significant difference in the means of the salt content across the three product subcategories.
|
Multiple Comparisons |
||||||
| Dependent Variable: Salt g/100g | ||||||
| Tukey HSD | ||||||
| (I) Product sub-category | (J) Product sub-category | Mean Difference (I-J) | Std. Error | Sig. | 95% Confidence Interval | |
| Lower Bound | Upper Bound | |||||
| chilled,meal ,complete | Ambient meal complete | -.6506481 | .4541927 | .333 | -1.752284 | .450988 |
| frozen meal complete | .4443519 | 1.0938409 | .913 | -2.208740 | 3.097443 | |
| Ambient meal complete | chilled,meal ,complete | .6506481 | .4541927 | .333 | -.450988 | 1.752284 |
| frozen meal complete | 1.0950000 | 1.1125404 | .591 | -1.603447 | 3.793447 | |
| frozen meal complete | chilled,meal ,complete | -.4443519 | 1.0938409 | .913 | -3.097443 | 2.208740 |
| Ambient meal complete | -1.0950000 | 1.1125404 | .591 | -3.793447 | 1.603447 | |
A subsequent Tukey post hoc test demonstrated that the subcategories of the products were more likely to have a high salt content in the Ambient meal (M = 1.65, SD = 2.11) than in the chilled meal (M = 0.99, SD = 0.92). However, there were no significant differences in the amount of salt intake in Frozen meals (M = 0.54, SD = 0.06) and either Ambient meals or chilled meals.
Moreover, there was no significant difference between the three subcategories. There was no significant difference in the amount of salt in chilled meals and Ambient meals (p=0.33), there was no difference between the chilled milled and the Frozen meal (p=0.91) and there was no difference between Ambient meals and the Frozen meal (p=0.59).
Table 4: Salt
| Salt g/100g | ||
| Tukey HSDa,b | ||
| Product sub-category | N | Subset for alpha = 0.05 |
| 1 | ||
| frozen meal complete | 2 | .550000 |
| chilled,meal ,complete | 27 | .994352 |
| Ambient meal complete | 18 | 1.645000 |
| Sig. | .479 | |
| Means for groups in homogeneous subsets are displayed. | ||
| a. Uses Harmonic Mean Sample Size = 5.063. | ||
| b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. | ||
As represented in the table above, there is one subset. The Ambient meal (M = 1.645), chilled milled (M = 0.994) and frozen meal (M=0.55) fall under one subset. Therefore, the three conditions did not differ from each other.
Figure 1: histogram
Table 5: Pearson test
| Correlations | |||||||
| Product category | pack size g | Product retail price £ | Salt g/100g | salt grams per serving | Weight of serving g | ||
| Product category | Pearson Correlation | 1 | -.054 | -.048 | .192 | .229 | .109 |
| Sig. (2-tailed) | .713 | .745 | .197 | .126 | .476 | ||
| N | 49 | 49 | 49 | 47 | 46 | 45 | |
| pack size g | Pearson Correlation | -.054 | 1 | .201 | -.316* | -.005 | .272 |
| Sig. (2-tailed) | .713 | .166 | .031 | .974 | .071 | ||
| N | 49 | 49 | 49 | 47 | 46 | 45 | |
| Product retail price £ | Pearson Correlation | -.048 | .201 | 1 | -.069 | -.067 | -.052 |
| Sig. (2-tailed) | .745 | .166 | .646 | .659 | .733 | ||
| N | 49 | 49 | 49 | 47 | 46 | 45 | |
| Salt g/100g | Pearson Correlation | .192 | -.316* | -.069 | 1 | .473** | -.211 |
| Sig. (2-tailed) | .197 | .031 | .646 | .001 | .165 | ||
| N | 47 | 47 | 47 | 47 | 46 | 45 | |
| salt grams per serving | Pearson Correlation | .229 | -.005 | -.067 | .473** | 1 | .409** |
| Sig. (2-tailed) | .126 | .974 | .659 | .001 | .006 | ||
| N | 46 | 46 | 46 | 46 | 46 | 44 | |
| Weight of serving g | Pearson Correlation | .109 | .272 | -.052 | -.211 | .409** | 1 |
| Sig. (2-tailed) | .476 | .071 | .733 | .165 | .006 | ||
| N | 45 | 45 | 45 | 45 | 44 | 45 | |
| *. Correlation is significant at the 0.05 level (2-tailed). | |||||||
| **. Correlation is significant at the 0.01 level (2-tailed). | |||||||
The coefficient of correlation
According to the Pearson test table above, the coefficient of correlation between the product category and the salt was 0.192, between the product category and the salt in grams was 0.229 and between the weight of serving and the product category was 0.109. The coefficient of correlation between the pack size and the product retail price was 0.201, between the pack size and the weight of serving was 0.272. The coefficient of correlation between the product category and the pack size was -0.54. The coefficient of correlation between the product category and the product retail price was – 0.048. The coefficient of correlation between the salt and the pack size was -0.316, between pack size and salt grams per serving was -0.005. The coefficient of correlation between the pack size and the weight of serving was 0.272. The coefficient of correlation between the product retail price and the salt was 0.069, between product retail price and the salt per serving was -0.067.
Figure 2: scatter plot between the salt g/100g and the weight of serving g.
According to the figure above, the line depicts a negative slope thus there was an inverse relationship between the amount of salt and the pack size.
Figure 3. scatter plot between the salt g/100g and the weight of serving g.
According to the figure above, the line depicts a negative slope thus there was an inverse relationship between the amount of salt and the weight of serving.
DISCUSSION
CONCLUSION
The research provided a better view of the quantity of salt that was found in the products processed by Chinese and UK products. The aim of the study was to establish the sodium content in Chinese cuisine products and determine if they are in line with the F.S.A 2024 standards. There were two objectives of the study. Firstly, the study was to systematically collect data on sodium levels in processed Chinese products. Secondly, it was to compare the sodium values against the FSA standard on salt content. The research has revealed that Chinese products have a high salt content (g/100g) than in the UK. Therefore, Chinese foods are saltier than UK foods. This research will help the Chinese companies to know the required salt content g/ 100g and adhere to the F.S.A 2024 guidelines and standards on foods’ sodium (salt) content.
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