Next Article in Journal
Effects of CaCl2 Treatment Alleviates Chilling Injury of Loquat Fruit (Eribotrya japonica) by Modulating ROS Homeostasis
Previous Article in Journal
Optimization and Development of Ready to Eat Chocolate Coated Roasted Flaked Rice as Instant Breakfast Food
Previous Article in Special Issue
Human Exposure to Toxic Metals (Al, Cd, Cr, Ni, Pb, Sr) from the Consumption of Cereals in Canary Islands
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Energy Content and Nutrient Profiles of Frequently Consumed Meals in Singapore

by
Penny Liu Qing Yeo
1,
Xinyan Bi
1,
Michelle Ting Yun Yeo
1 and
Christiani Jeyakumar Henry
1,2,*
1
Clinical Nutrition Research Centre (CNRC), Singapore Institute of Food and Biotechnology Innovation (SIFBI), Agency for Science, Technology and Research (A*STAR), 14 Medical Drive, Singapore 117599, Singapore
2
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599, Singapore
*
Author to whom correspondence should be addressed.
Foods 2021, 10(7), 1659; https://doi.org/10.3390/foods10071659
Submission received: 16 June 2021 / Revised: 8 July 2021 / Accepted: 8 July 2021 / Published: 19 July 2021

Abstract

:
Singapore is a multi-ethnic country with a great variety of traditional ethnic cuisines. In this modern society where there is an increasing prevalence of obesity, it is important to know the nutritional content and energy density of our foods. However, there have been little data on the nutritional content of our local foods. The energy density and nutrient content of 45 commonly consumed meals by three ethnic groups in Singapore (Chinese, Malay, and Indian) were assessed in this study. Chinese, Malay, and Indian cuisines had an average energy density of 661, 652, and 723 kJ/100 g, respectively. Moreover, the macronutrient content is different between the different ethnic groups. Compared to Chinese and Malay cuisines, Indian cuisine contained lower protein but higher fat and carbohydrate content (p = 0.03). From the mineral analysis of the ethnic foods, we found out that Chinese cuisines contain significantly higher sodium (average of 238 mg/100 g) than Malay cuisines (p = 0.006) and Indian cuisines (p = 0.03). Knowing the caloric density and nutrition content of local ethnic foods may aid hawkers and government officials in developing healthier options to tackle Singapore’s obesity epidemic.

Graphical Abstract

1. Introduction

In modern society, there has been an exponential increase in obesity due to the changes in diet and “nutrition transition”. This consists of the increase in consumption of fat, meat, added sugars, and bigger portion sizes, as well as the decrease in physical activity [1]. This global epidemic is particularly visible in affluent nations, such as Singapore, where the incidence of obesity is steadily increasing [2]. The proportion of obese and overweight adults aged 18 and 69 years was 8.7% and 36.2%, respectively, in 2017, as compared to 8.6% and 34.3%, respectively, in 2013 [3].
Singapore is a microcosm of Asia where three broad ethnicities corresponding to the major population centers in Asia are present, namely the Chinese (East Asians), the Malays (Southeast Asians), and the Indians (South Asians) [4]. Street food and foods created by tiny local businesses, known as hawker centers or Kopitiam in the local language, are popular venues for locals to have breakfast, lunch, and supper, as they are in many other Southeast Asian nations. From the Food Forward Trends Report Singapore in 2019 [5], the proportion of Singaporeans eating out is higher (61%) compared to the past years. Hawker center and fast food are listed as one of the top three eating out options in Singapore.
However, there is insufficient information on the caloric content of local ethnic foods, with the majority of the information dating back many years and based on bomb calorimetry and Atwater conversion factors [6]. We recently employed a new instrument called the Calorie AnswerTM to determine the calorie content of various foods [7,8]. Our results showed that this near-infrared spectroscopy (NIR) is rapid and reliable for a diverse range of foods [7].
Obesity is recognized to be a major risk factor for a variety of ailments, including cancer, heart disease, and diabetes mellitus, which are among the top 10 diseases afflicting Singaporeans [9,10]. Diet-related disorders, such as high blood pressure, are also affecting Singaporeans, which is linked to a higher salt consumption [11]. The intake of sodium by Singaporeans has increased over the years to 9 g, which has exceeded the recommended daily intake of 5 g [12]. In addition, minerals are needed by the body to ensure the internal systems function efficiently. Therefore, the dietary mineral intake must be monitored to maintain physical health. However, there are limited data on the mineral composition of local ethnic cuisines in Singapore.
Data on the nutritional content of these local ethnic foods are critical for determining nutrient intake, giving dietary recommendations, and avoiding illnesses. Therefore, the objective of the study is to analyze the energy density, macronutrient content (fat, protein, and carbohydrates), and mineral content (Na23, Mg24, Al27, K39, Ca40, Mn55, Fe56, Cu63, Zn66) of 45 local ethnic cuisines commonly consumed in Singapore.

2. Materials and Methods

2.1. Sample Preparation

Local food samples were purchased from a local food court (Kopitiam, Singapore). There were, in total, 45 local food samples from different ethnic groups that were used for analysis: Chinese food (n = 15), Malay food (n = 15), and Indian food (n =15). To achieve a smooth, consistent texture, all of the samples were homogenized in a kitchen blender (BL 480, Kenwood, United Kingdom). The samples were then put into 6 tubes, 3 for Calorie Answer analysis, and 3 for inductively coupled plasma mass spectroscopy (ICP-MS) analysis. For the ICP-MS analysis, the samples were kept in a −20 °C freezer. The samples were analyzed using the procedure and techniques described previously. The foods are described in Tables S1–S3.

2.2. Standards and Reagents

Analytical and trace-metal grade reagents were utilized throughout. The Mili-Q IQ-7000 (Merck KGaA, Darmstadt, Germany) water purification system was used to provide high quality deionized water (resistivity > 18.2 M). Prior to use, all glassware and plasticware were cleaned by soaking for 48 h in a 10% (v/v) HNO3 solution, then rinsing with ultrapure water and drying. The dilution of 10 µg/mL (Bi209, Tb159, In115, Y89, Ge74, Ge72, Sc45, Li6) Internal Standard Mix solution (Agilent Technologies, Santa Clara, CA, USA) was required for the internal standard solution. The calibration curves were made using a 10 µg/mL and 100 µg/mL custom mix multi-element ICP-MS standard (HPS, North Charleston, SC, USA), as well as a 1000 µg/mL mineral element ICP-MS standard solution (HPS, North Charleston, SC, USA) (ICP-AM-17 Mineral Calibration Standard, HPS, North Charleston, SC, USA).

2.3. NIR Spectroscopy and Analysis

The homogenized samples were then put in cylindrical sample cells (with an internal diameter of 50 mm and a depth of 10 mm for solid samples) and tested in triplicates. For all samples, the Prepared Food settings were used. For solid samples, the reflectance mode was applied, and the reference reflectance data were analyzed using a calcium-carbonate-filled cell. Calorie AnswerTM (CA-HM, JWP, Hirakawa, Japan) was used to collect near-infrared (NIR) spectra of homogenized samples throughout a wavelength range of 1100–2200 nm, with a resolution of 7.5 nm and a data interval of 2 nm. A halogen lamp served as the radiation source, while an acousto-optic tunable filter (ATOF) served as a wavelength sensor and light-receiving sensors served as light detectors. To increase accuracy, the integrated computer program (CA-HM Measurement Application Software, JWP, Hirakawa, Japan) was programed to scan each triplicated component 10 times, then averaged to obtain a mean spectrum. After converting the data to log 1/R, the calorie density for each sample was determined using regression formulas preprogramed in the software. Each measurement took roughly 5 min to analyze (including time for calibration). The procedures used were elaborated intensively by Lau, et al. [7].

2.4. ICP-MS Mineral Analysis

A CEM MARS6 Microwave Digestor System with an iPrep 12 vessels rotor (CEM, Matthews, NC, USA) was utilized to digest the local food samples. Each Teflon vessel contained 0.25 g of sample, followed by 10 mL of HNO3 (Fisher Chemical, Waltham, MA, USA). The mixture was heated to 210 °C in 15 min and then held for another 15 min. After cooling, sample solutions were diluted to 50 mL with 5% HNO3 and 0.5% HCl in decontaminated 50 mL skirted centrifuge tubes. Of these 12 vessels, ten were samples, one was blank, and one was a spiked sample from the same digestion batch. In each digesting operation, this arrangement was retained. Duplicates of each sample were digested. The 7900 ICP-MS analyzer (Agilent Technologies, Hachioji, Japan) with the Ultra High Matrix Introduction (UHMI) option was used to perform inductively coupled plasma-mass spectrometry (ICP-MS) analysis. A MicroMist nebulizer, quartz spray chamber, and quartz torch with a 2.5 mm internal diameter injector were utilized during the experiment. The interface cones used had a platinum tip. The plasma was created using high quality (99.9997%) argon (Air Liquide, Singapore, Singapore). The following were the parameters of the ICP-MS instrument: 1550 W RF power, 10 mm sampling depth, 0.90 L/min carrier gas. The samples, which were kept in 50/15 mL tubes, were delivered by an Agilent SP4 auto-sampler. Internal standards were used: Sc45, Ge72, Y89, In115, and Bi209. Using the tuning solution (1 g/L Ce, Co, Li, Mg, Tl, Y in 2% HNO3) for the ICP-MS (Agilent Technologies; Santa Clara, CA, USA), the instrument was set for optimal signal sensitivity and stability. Triplicates of each analysis were performed.

2.5. Method Validation and Statistical Analysis

The ICP-MS analytical technique was derived from an Agilent application note [13]. To validate the method, 9 of the 45 local foods were used to run a spike recovery test to measure the elements tested. The average recoveries were presented in Tables S4–S6. Excellent spike recoveries were achieved, with most elements being 95–105% recovered. These foods were ranked from the highest to the lowest energy content (per 100 g). The mean and standard deviation (SD) are used to express the results.
The values of Ca44 were converted to Ca40 using the atomic abundance of the Ca element. The formula is as follows:
C a 40   m i n e r a l   c o n c e n t r a t i o n   ( p p m ) = C a 44   m i n e r a l   c o n c e n t r a t i o n   ( p p m ) × 96.94 % 2.09 %

3. Results

The energy density and the macronutrient content of the selected foods were determined and reported for 100 g edible portion, as presented in Table 1 (Chinese cuisine), Table 2 (Malay cuisine), and Table 3 (Indian cuisine).
The foods were listed from the highest to the lowest energy density for each ethnic group. The average energy density of Chinese, Malay, and Indian cuisines was 661, 652, and 723 kJ/100 g, respectively, as in Figure 1a. For Chinese cuisine, steamed white chicken rice had the highest energy density (789 kJ/100 g), while dumpling you mian had the lowest energy density (496 kJ/100 g) (Table 1). For Malay cuisine, ayam penyet had the highest energy density (849 kJ/100 g), while mee rebus had the lowest energy density (472 kJ/100 g) (Table 2). For Indian cuisine, egg prata with chicken curry had the highest energy density (782 kJ/100 g), while vegetarian set meal (biryani rice) had the lowest energy density (521 kJ/100 g) (Table 3). Figure 1b,c show that the macronutrient compositions and the mineral contents of local ethnic foods were remarkably different between different ethnic groups.
Figures S1–S3 show the mineral distributions of the foods consumed by different ethnic groups. Our results suggested that local ethnic foods are high in Na, K, and Ca. Figure S1 shows that, for Chinese cuisine, economical mee goreng (per portion, same below) had the highest amount of sodium (1575 mg), and laska had the highest amount of magnesium (90 mg), potassium (251 mg), calcium (1236 mg), manganese (1.15 mg), and iron (2.89 mg). Figure S2 shows that, for Malay cuisine, mee rebus had the highest amount of sodium (1170 mg), goreng pisang had the highest amount of magnesium (94.5 mg) and manganese (2.07 mg), nasi ambang chicken had the highest amount of potassium (574 mg) and iron (3.78 mg), and tahu goreng set had the highest amount of calcium (1129 mg). Figure S3 shows that, for Indian cuisine, naan set had the highest amount of sodium (1219 mg), chapati set with potato marsala had the highest amount of magnesium (99.5 mg) and potassium (729 mg), vegetable biryani had the highest amount of calcium (677 mg), and poori set had the highest amount of manganese (2.37 mg) and iron (5.21 mg). Variations in local ethnic meals and recipes are assumed to be related to a variety of factors, including processing and farming conditions, as well as varied ingredients and cooking methods. As shown in Figure 1c, Chinese cuisine has a relatively high sodium content compared to other ethnic cuisines (p < 0.05). This may be due to Chinese cuisines using seasonings, such as soya sauce and monosodium glutamate (MSG), to season their food.

4. Discussion

Local ethnic foods are the main meals consumed in Singapore, and with more Singaporeans eating out, this may contribute to higher energy intake and higher sodium intake, which increases the risk of obesity and associated diseases. Since the research relating to diet and health is constantly evolving, appropriate dietary guidelines have been implemented to help Singaporeans adopt healthier food eating habits. The dietary guidelines include having a varied diet, and the foods chosen should be low in fat, especially saturated fat, low in salt, and low in sugar, replacing refined grains with whole grains, eating more fruit and vegetables each day. In recent years, there is also an increasing culture of dining out among Singaporeans from a recent 2018 Nielsen survey. The percentage of Singaporeans eating out is constantly increasing, from 51% in 2015 to 55% in 2019, on a weekly basis. Moreover, dining out meals generally deliver large portions that can lead to a substantially higher energy intake. Therefore, reducing portion size is one of the key requirements of moderating food intake. The first prerequisite for such action is the need to know the individual energy density of various local ethnic foods. In meeting this requirement, we are presenting for the first time a comprehensive list of energy density and nutrient content of various local ethnic foods.
The recommended daily allowances for the different macronutrients and micronutrients are shown in Tables S7–S9 [14]. Table 4, Table 5 and Table 6 show the macronutrient content with the %RDA of the commonly consumed Chinese, Malay, and Indian cuisines, respectively. Following the Recommended Dietary Guidelines 2003 for Adult Singaporeans, all the local ethnic foods, if eaten for all three meals, will exceed the recommended guidelines for energy contribution (%) of macronutrients to total energy intake [15]. Table 4 shows one serving of laska consumed in a day contributes to 34–43% of the caloric intake, 60–73% of protein intake, 35–45% of fat intake, and 27–35% of carbohydrates intake. From the National Nutrition Survey 2010, it was shown that 60% of Singaporeans exceeded the daily recommendation for energy and total fat [16]. This is also reflected in the National Nutrition Survey in 2018 that more Singaporeans are consuming more fat in their diet, from 31% in 2010 to 35% in 2018 [12]. It also states that protein intake was also mostly adequate, with over 80% of Singaporeans achieving the daily protein intake recommendation [12].
Local ethnic foods in Kopitiam or hawker centers can be considered “unhealthy” foods due to their high amount of sodium, MSG, and fat. Mineral contents were assessed in addition to macronutrients, since they are known to have a significant role in metabolism and tissue function. The local ethnic foods consumed in Singapore were found to be high in macro-elements, like sodium, potassium, magnesium, and calcium, but deficient in trace elements, like copper, iron, manganese, and zinc, according to this study. Table 7, Table 8 and Table 9 show the percentage of the mineral content of the different ethnic foods with comparison to the recommended intake.
Sodium is essential for the control of blood pressure and stimulation of muscles and nerves. It is an electrolyte that controls the extracellular amount of fluid in the body and is needed for hydration. Excessive consumption of dietary salt and sodium-containing substances, like monosodium glutamate (MSG), has been linked to high blood pressure, making it a risk factor for cardiovascular illnesses [17]. The daily sodium consumption requirement is 2.4 g; thus, salt intake should not exceed 6 g per day [18]. From Table 7, Table 8 and Table 9, we can see that the %RDA of one serving of local ethnic food is around 34–46% of the recommended daily intake. This can be better illustrated from one serving of economic noodles (the highest sodium meal), which has 79% of the daily sodium intake advised. From the National Nutrition Survey 2018, it is also evident that Singaporeans are consuming too much salt, with an average daily intake of 9 g [12]. To counter the high sodium foods, high potassium foods can be consumed, as there is abundant evidence that a reduction in dietary sodium and an increase in potassium intake decreases blood pressure and reduces the chances of hypertension, morbidity, and mortality from cardiovascular diseases [19,20].
Calcium is important to prevent osteoporosis and for bone development [21,22]. The recommended dietary intake of calcium for adults should be 1000 mg/day [23]. The consumption of one serving of laska already exceeds the recommended daily level of calcium intake by 124%. In addition, the amount of calcium that can be absorbed varies with an individual’s vitamin D status [24].
Iron insufficiency is the most frequent micronutrient deficit worldwide [25,26]. It is required for many proteins and enzymes, especially hemoglobin to prevent anemia. The recommended dietary intake of iron for adult males aged 18 and above is 8 mg/day. Adult women between ages 18 and 59 require 18 mg/day, while women above 60 require 8 mg/day. In Singapore, one in every two women could be suffering from iron deficiency but they are not aware of it. From the analysis, the average iron content in the local ethnic foods was found to be 1.3 mg/100 g, which is very low. From Table 7, Table 8 and Table 9, we can see that the average %RDA is from 7–29%, with Indian food having a higher average compared to other ethnic groups. Its bioavailability is poor and it is influenced by dietary variables that might either enhance or decrease its availability [27].

5. Conclusions

The energy density and the nutrition composition of 45 popular consumed local ethnic cuisines in Singapore were assessed. Indian ethnic cuisine has the highest average energy density of 723 kJ/100 g. This is due to the higher fat and carbohydrate content in Indian cuisine as compared to the Chinese and Malay cuisines. From the ICP-MS analysis, the mineral content of the local ethnic cuisines differs greatly. Overall, Chinese cuisine has the highest amount of sodium in their local ethnic foods. This may be due to the seasonings used to season the food. In addition to the dietary advice and guidelines by the government agencies, the validated data of energy density and macronutrient contents of the local ethnic foods will serve as an important tool in reviewing or setting new dietary guidelines in mitigating health disorders, as well as maintaining sustainable human health in Singapore.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/foods10071659/s1, Table S1: Description of selected commonly consumed Chinese local food, Table S2: Description of selected commonly consumed Malay local food, Table S3: Description of selected commonly consumed Indian local food, Table S4: Spike Recovery of Chinese Ethnic Local Food (Fried Carrot Cake), Table S5: Spike Recovery of Malay Ethnic Local Food (Ayam Penyet), Table S6: Spike Recovery of Indian Ethnic Local Food (Mutton Briyani), Table S7: Recommended daily allowances of iron, sodium, Table S8: Recommended daily allowances of calcium in adults, Table S9: Recommended daily allowances of macronutrients for adults, Figure S1: Mineral contents of the commonly consumed Chinese cuisines (calculated based on portion size). (a) Sodium; (b) Magnesium; (c) Potassium; (d) Calcium; (e) Manganese; (f) Iron, Figure S2: Mineral contents of the commonly consumed Malay cuisines (calculated based on portion size), (a) Sodium; (b) Magnesium; (c) Potassium; (d) Calcium; (e) Manganese; (f) Iron, Figure S3: Mineral contents of the commonly consumed Indian cuisines (calculated based on portion size), (a) Sodium; (b) Magnesium; (c) Potassium; (d) Calcium; (e) Manganese; (f) Iron.

Author Contributions

Conceptualization, C.J.H.; methodology, P.L.Q.Y., M.T.Y.Y. and X.B.; validation, P.L.Q.Y., M.T.Y.Y. and X.B.; formal analysis, P.L.Q.Y., M.T.Y.Y. and X.B.; investigation, P.L.Q.Y. and M.T.Y.Y.; writing—original draft preparation, P.L.Q.Y. and X.B.; writing—review and editing, P.L.Q.Y., X.B. and C.J.H.; supervision, C.J.H.; project administration, C.J.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research is funded by A*STAR BMRC (Biomedical Research Council) by the following grant, IAF-PP (HBMS Domain): H17/01/a0/A11 Food Structure Engineering for Nutrition and Health-CNRC Core Funds.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

We would like to thank Steven Pang from Agilent Technologies for his assistance with the method development for the ICP-MS analysis.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bhurosy, T.; Jeewon, R. Overweight and Obesity Epidemic in Developing Countries: A Problem with Diet, Physical Activity, or Socioeconomic Status? Sci. World J. 2014, 2014, 7. [Google Scholar]
  2. Yoon, K.H.; Lee, J.H.; Kim, J.W.; Cho, J.H.; Choi, Y.H.; Ko, S.H.; Zimmet, P.; Son, H.Y. Epidemic obesity and type 2 diabetes in Asia. Lancet 2006, 368, 1681–1688. [Google Scholar] [CrossRef]
  3. National Population Health Survey 2016/2017. Available online: https://www.moh.gov.sg/resources-statistics/reports/national-population-health-survey-2016-17 (accessed on 8 July 2021).
  4. Phan, T.P.; Alkema, L.; Tai, E.S.; Tan, K.H.X.; Yang, Q.; Lim, W.Y.; Teo, Y.Y.; Cheng, C.Y.; Wang, X.; Wong, T.Y.; et al. Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore. BMJ Open Diabetes Res. Care 2014, 2, e000012. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Shandwich, W. Asian Pacific Food Forward Trends Report II. Available online: http://13.251.163.42/wp-content/uploads/2019/02/FoodForwardTrends.pdf (accessed on 8 July 2021).
  6. Health Promotion Board. Energy & Nutrient Composition of Food. Available online: https://focos.hpb.gov.sg/eservices/ENCF/ (accessed on 8 July 2021).
  7. Lau, E.; Goh, H.J.; Quek, R.; Lim, S.W.; Henry, J. Rapid estimation of the energy content of composite foods: The application of the Calorie Answer™. Asia Pac. J. Clin. Nutr. 2016, 25, 18–25. [Google Scholar] [PubMed]
  8. Quek, Y.-C.R.; Goh, H.-J.; Henry, C.J. Energy Density of Locally Consumed Foods in Singapore: A Comparative Study amongst Chinese, Malays and Indians. Malays. J. Nutr. 2019, 25, 171–184. [Google Scholar] [CrossRef]
  9. Foo, L.L.; Vijaya, K.; Sloan, R.A.; Ling, A. Obesity prevention and management: Singapore’s experience. Obes. Rev. 2013, 14, 106–113. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. Goh, L.G.; Pang, J. Obesity in Singapore, Prevention and Control. Singap. Fam. Physician 2012, 38, 8–13. [Google Scholar]
  11. Foo, L. Snacking Smart. HealthHub Singapore, 2018, 46–47. Available online: https://www.healthhub.sg/live-healthy/1117/snacking-smart (accessed on 8 July 2021).
  12. National Nutrition Survey 2018 Shows Gradual Improvements in Singaporeans’ Dietary Habits. Available online: https://www.hpb.gov.sg/article/national-nutrition-survey-2018-shows-gradual-improvements-in-singaporeans-dietary-habits (accessed on 8 July 2021).
  13. Kazuhiro, S.; Junichi, T.; Ed, M. 5991-4556EN: Application of the Agilent 7900 ICP-MS with Method Automation function for the routine determination of trace metallic components in food CRMs. Agil. Technol. 2014, 1–9. Available online: https://www.agilent.com/cs/library/applications/5991-4556EN_AppNote7900_ICP-MS_food_CRMs.pdf (accessed on 14 July 2019).
  14. Healthhub. Recommended Dietary Allowances for Normal Healthy Persons in Singapore. Available online: https://www.healthhub.sg/live-healthy/192/recommended_dietary_allowances (accessed on 8 July 2021).
  15. Health Promotion Board. Dietary Guidelines 2003 for Adult Singaporeans (18–65 Years); Health Promotion Board: Singapore, 2003.
  16. Health Promotion Board. Report of the National Nutrition Survey 2010; Health Promotion Board: Singapore, 2010.
  17. Meneton, P.; Jeunemaitre, X.; de Wardener, H.E.; MacGregor, G.A. Links between dietary salt intake, renal salt handling, blood pressure, and cardiovascular diseases. Physiol. Rev. 2005, 85, 679–715. [Google Scholar] [CrossRef] [PubMed]
  18. WHO. Guideline: Sodium Intake for Adults and Children; World Health Organization (WHO): Geneva, Switzerland, 2012. [Google Scholar]
  19. Whelton, P.K.; He, J. Health effects of sodium and potassium in humans. Curr. Opin. Lipidol. 2014, 25, 75–79. [Google Scholar] [CrossRef] [PubMed]
  20. He, F.J.; MacGregor, G.A. Salt, blood pressure and cardiovascular disease. Curr. Opin. Cardiol. 2007, 22, 298–305. [Google Scholar] [CrossRef] [PubMed]
  21. WHO; Food and Agriculture Organization of the United Nations. Vitamin and Mineral Requirements in Human Nutrition, 2nd ed.; Report of a joint FAO/WHO expert consulation/Bangkok; FAO: Rome, Italy; WHO: Geneva, Switzerland, 2004. [Google Scholar]
  22. WHO; Global Strategy on Diet, Physical Activity and Health. Obesity and overweight. 57th Health Assembly. Provisional Agenda, Item 12.6. A57/9; WHO: Geneva, Switzerland; FAO: Rome, Italy, 2004. [Google Scholar]
  23. IOM (Institute of Medicine). Dietary Reference Intakes for Calcium and Vitamin D; The National Academies Press: Washington, DC, USA, 2011. [Google Scholar]
  24. Allen, L.H. Calcium bioavailability and absorption: A review. Am. J. Clin. Nutr. 1982, 35, 783–808. [Google Scholar] [CrossRef] [PubMed]
  25. Dahdouh, S.; Grande, F.; Espinosa, S.N.; Vincent, A.; Gibson, R.; Bailey, K.; King, J.; Rittenschober, D.; Charrondière, U.R. Development of the FAO/INFOODS/IZINCG Global Food Composition Database for Phytate. J. Food Compos. Anal. 2019, 78, 42–48. [Google Scholar] [CrossRef] [PubMed]
  26. Ferguson, E.L.; Watson, L.; Berger, J.; Chea, M.; Chittchang, U.; Fahmida, U.; Khov, K.; Kounnavong, S.; Le, B.M.; Rojroongwasinkul, N.; et al. Realistic Food-Based Approaches Alone May Not Ensure Dietary Adequacy for Women and Young Children in South-East Asia. Matern. Child Health J. 2019, 23, 55–66. [Google Scholar] [CrossRef] [PubMed]
  27. Fairweather-Tait, S.J. The importance of trace element speciation in nutritional sciences. Fresenius J. Anal. Chem. 1999, 363, 536–540. [Google Scholar] [CrossRef]
Figure 1. Comparisons of (a) energy density, (b) macronutrient content, and (c) mineral content between the different ethnic cuisines.
Figure 1. Comparisons of (a) energy density, (b) macronutrient content, and (c) mineral content between the different ethnic cuisines.
Foods 10 01659 g001
Table 1. Energy and macronutrient content of the commonly consumed Chinese cuisines.
Table 1. Energy and macronutrient content of the commonly consumed Chinese cuisines.
Name of Chinese Local FoodPortion Size (g)Calories (kJ/100 g)Protein (g/100 g)Fat (g/100 g)Carbohydrate (g/100 g)
Steamed Chicken Rice412789 ± 139.3 ± 0.17.4 ± 0.321.2 ± 0.9
Roasted Chicken Rice285768 ± 98.3 ± 0.26.3 ± 0.623.4 ± 1.0
Char Kuay Teow362762 ± 154.0 ± 0.66.3 ± 0.227.4 ± 0.5
Yang Zhou Fried Rice388746 ± 235.8 ± 0.24.9 ± 0.227.7 ± 1.5
Fried Carrot Cake271732 ± 89.0 ± 0.711.5 ± 0.38.9 ± 0.1
Sin Chew Bee Hoon386689 ± 136.6 ± 0.45.2 ± 0.122.7 ± 0.4
Minced Meat Mee Pok383677 ± 58.3 ± 0.36.9 ± 0.216.6 ± 0.3
Economical Mee Goreng350677 ± 223.5 ± 0.42.2 ± 0.231.9 ± 1.7
Lor Mai Kai354646 ± 124.2 ± 0.51.7 ± 0.830.6 ± 1.5
Laska577639 ± 98.0 ± 0.45.3 ± 0.118.3 ± 0.6
Ban Mian Dry311621 ± 116.7 ± 0.64.0 ± 0.221.3 ± 1.1
Steamed Chicken Noodle367600 ± 710.8 ± 0.43.3 ± 0.317.4 ± 0.7
Fried Hokkien Mee328569 ± 185.5 ± 0.31.5 ± 0.225.1 ± 0.7
Char Siew Wanton Noodle335502 ± 87.9 ± 0.71.6 ± 0.218.4 ± 0.7
Dumpling You Mian761496 ± 155.5 ± 0.42.6 ± 0.218.2 ± 1.4
Values are expressed as mean ± SD. To convert energy to kcal/100 g, divide by 4.184.
Table 2. Energy and macronutrient content of the commonly consumed Malay cuisines.
Table 2. Energy and macronutrient content of the commonly consumed Malay cuisines.
Name of Malay Local FoodPortion Size (g)Calories (kJ/100 g)Protein (g/100 g)Fat (g/100 g)Carbohydrate (g/100 g)
Ayam Penyet425849 ± 98.9 ± 0.29.0 ± 0.121.7 ± 0.7
Nasi Kampung Goreng405798 ± 117.1 ± 0.27.1 ± 0.224.6 ± 0.8
Nasi Lemak395785 ± 109.2 ± 0.39.0 ± 0.217.7 ± 1.0
Ikan Penyet274765 ± 147.8 ± 0.77.0 ± 0.222.2 ± 0.8
Nasi Ambang630733 ± 59.2 ± 0.57.2 ± 0.618.3 ± 1.7
Goreng Pisang415733 ± 20.4 ± 0.35.6 ± 0.230.9 ± 0.2
Tahu Goreng402690 ± 910.3 ± 0.49.9 ± 0.38.8 ± 0.9
Mee Soto281640 ± 59.2 ± 0.32.9 ± 0.220.3 ± 0.5
Mee Bandung466622 ± 77.5 ± 0.35.2 ± 0.018.1 ± 0.2
Mee Bakso435611 ± 85.7 ± 0.72.2 ± 0.125.9 ± 0.6
Lotong269593 ± 108.2 ± 0.36.6 ± 0.212.4 ± 0.5
Mee Siam566590 ± 04.9 ± 0.02.7 ± 0.024.3 ± 0.0
Kentang Ball with Rice Cube424490 ± 115.4 ± 0.53.9 ± 0.315.1 ± 0.2
Soto Ayam693481 ± 196.2 ± 0.81.5 ± 0.319.1 ± 0.3
Mee Rebus582472 ± 53.7 ± 0.42.4 ± 0.819.0 ± 1.4
Values are expressed as mean ± SD. To convert energy to kcal/100 g, divide by 4.184.
Table 3. Energy and macronutrient content of the commonly consumed Indian cuisines.
Table 3. Energy and macronutrient content of the commonly consumed Indian cuisines.
Name of Indian Local FoodPortion Size (g)Calories (kJ/100 g)Protein (g/100 g)Fat (g/100 g)Carbohydrate (g/100 g)
Original Appam3441042 ± 112.9 ± 0.65.4 ± 0.647.1 ± 0.6
Egg Appam304884 ± 174.2 ± 0.46.4 ± 0.334.7 ± 0.3
Roti Prata246869 ± 62.5 ± 0.56.2 ± 0.335.5 ± 0.5
Egg Prata with Chicken Curry477782 ± 137.7 ± 0.57.1 ± 0.523.1 ± 1.2
Boneless Mutton Biryani459728 ± 88.7 ± 0.08.9 ± 0.514.7 ± 1.1
Poori Set474715 ± 136.6 ± 0.26.8 ± 0.121.0 ± 0.9
Marsala Thosai569714 ± 137.0 ± 0.56.9 ± 0.220.2 ± 0.3
Naan 597697 ± 75.2 ± 0.83.9 ± 0.427.5 ± 1.3
Chapatti Set with Potato336695 ± 56.0 ± 0.66.1 ± 0.221.8 ± 0.8
Putu Mayam193678 ± 41.8 ± 0.42.6 ± 0.232.8 ± 0.4
Chapatti Set with Potato Marsala603652 ± 144.5 ± 0.43.2 ± 0.227.2 ± 0.7
Idli Set389639 ± 96.1 ± 0.16.5 ± 0.617.4 ± 1.7
Egg Thosai325623 ± 87.5 ± 0.35.7 ± 0.517.0 ± 1.1
Vegetable Biryani640595 ± 64.2 ± 1.15.6 ± 0.618.8 ± 2.0
Veg Set Meal (Biryani Rice)513521 ± 113.6 ± 0.53.2 ± 0.520.3 ± 1.2
Values are expressed as mean ± SD. To convert energy to kcal/100 g, divide by 4.184.
Table 4. Energy and macronutrient content and the %RDA of the commonly consumed Chinese cuisines.
Table 4. Energy and macronutrient content and the %RDA of the commonly consumed Chinese cuisines.
Name of Local FoodCalories (kcal)%RDA (Men)% RDA (Women)Protein (g)%RDA (Men)% RDA (Women)Fat (g)%RDA (Men)% RDA (Women)Carbohydrates (g)%RDA (Men)% RDA (Women)
Steamed Chicken Rice77830%38%3850%61%3035%45%8822%29%
Roasted Chicken Rice52420%26%2431%38%1821%27%6717%22%
Char Kuay Teow65925%32%1519%23%2326%33%9925%32%
Yang Zhou Fried Rice47518%23%2330%36%1922%28%10728%35%
Fried Carrot Cake47518%23%2532%39%3136%46%246%8%
Sin Chew Bee Hoon63524%31%2634%41%2023%30%8823%29%
Minced Meat Mee Pok62024%30%3242%51%2631%39%6416%21%
Economical Mee Goreng56622%28%1216%20%89%11%11229%37%
Lor Mai Kai54721%27%1519%24%67%9%10828%35%
Laska88134%43%4660%73%3035%45%10627%35%
Ban Mian Dry46218%23%2127%34%1315%19%6617%22%
Steamed Chicken Noodle52720%26%4052%64%1214%18%6416%21%
Fried Hokkien Mee44617%22%1824%29%56%7%8221%27%
Char Siew Wanton Noodle40215%20%2735%42%56%8%6216%20%
Dumpling You Mian90335%44%4255%67%2023%29%13936%45%
Average59323%29%2735%43%1821%26%8522%28%
Table 5. Energy and macronutrient content and the %RDA of the commonly consumed Malay cuisines.
Table 5. Energy and macronutrient content and the %RDA of the commonly consumed Malay cuisines.
Name of Local FoodCalories (kcal)%RDA (Men)% RDA (Women)Protein (g)%RDA (Men)% RDA (Women)Fat (g)%RDA (Men)% RDA (Women)Carbohydrates (g)%RDA (Men)% RDA (Women)
Ayam Penyet86233%42%3850%60%3844%56%9224%30%
Nasi Kampung Goreng77230%38%2938%46%2933%42%10026%33%
Nasi Lemak74129%36%3647%58%3541%52%7018%23%
Ikan Penyet50219%25%2128%34%1922%28%6116%20%
Nasi Ambang Chicken110443%54%5876%93%4653%67%11530%38%
Goreng Pisang72728%36%22%3%2327%34%12833%42%
Tahu Goreng Set66426%33%4154%66%4046%58%359%12%
Mee Bandung69327%34%3546%56%2428%36%8422%28%
Mee Bakso63524%31%2532%39%911%14%11329%37%
Lotong38115%19%2229%35%1821%26%339%11%
Mee Siam79831%39%2836%44%1517%22%13835%45%
Mee Soto40616%20%2634%41%89%12%5715%19%
Kentang Ball with Rice Cube49619%24%2330%37%1719%25%6416%21%
Soto Ayam79731%39%4356%68%1012%15%13334%43%
Mee Rebus65525%32%2128%34%1416%21%11128%36%
Average68226%33%3039%48%2327%34%8923%29%
Table 6. Energy and macronutrient content and the %RDA of the commonly consumed Indian cuisines.
Table 6. Energy and macronutrient content and the %RDA of the commonly consumed Indian cuisines.
Name of Local FoodCalories (kcal)%RDA (Men)% RDA (Women)Protein (g)%RDA (Men)% RDA (Women)Fat (g)%RDA (Men)% RDA (Women)Carbohydrates (g)%RDA (Men)%RDA (Women)
Original Appam94136%46%2736%44%2023%29%16442%54%
Egg Appam64225%31%1215%19%1922%28%10627%35%
Roti Prata51120%25%68%10%1518%22%8722%29%
Egg Prata89134%44%3748%59%3439%50%11028%36%
Boneless Mutton Biryani79931%39%4052%64%4147%60%6717%22%
Poori Set81131%40%3141%50%3237%47%10026%33%
Marsala Thosai97137%48%4052%63%3945%58%11530%38%
Naan Set99538%49%3141%50%2327%35%16442%54%
Chapati Set with Potato55822%27%2027%32%2124%30%7319%24%
Putu Mayam31212%15%45%6%56%7%6316%21%
Chapati Set with Potato Marsala94136%46%2736%44%2023%29%16442%54%
Idli Set59423%29%2431%38%2529%37%6817%22%
Egg Thosai48419%24%2432%39%1921%27%5514%18%
Vegetable Biryani91135%45%2735%43%3641%53%12031%39%
Veg Set Meal64625%32%1924%30%1719%24%10427%34%
Average73428%36%2532%39%2428%36%10427%34%
Table 7. Mineral content and the %RDA of the commonly consumed Chinese cuisines.
Table 7. Mineral content and the %RDA of the commonly consumed Chinese cuisines.
FoodAmount of Na (mg)% RDAAmount of Ca (mg)% RDAAmount of Fe (mg)% RDA(Men)% RDA(Women)
Steamed Chicken Rice63832%1127113%1.6521%9%
Roasted Chicken Rice48924%93093%0.284%2%
Char Kuay Teow92946%40841%2.1727%12%
Yang Zhou Fried Rice104652%17217%0.7810%4%
Fried Carrot Cake42721%24525%1.6320%9%
Sin Chew Bee Hoon93247%54154%1.5419%9%
Minced Meat Mee Pok104152%18418%1.5319%9%
Economical Mee Goreng157579%25025%0.79%4%
Lor Mai Kai115458%17017%0.719%4%
Laska138069%1236124%2.8936%16%
Ban Mian Dry75538%26727%0.628%3%
Steamed Chicken Noodle62531%28428%0.739%4%
Fried Hokkien Mee86143%20721%0.9812%5%
Char Siew Wanton Noodle73137%21221%0.678%4%
Dumpling You Mian108654%81281%1.5219%8%
Average91146%47047%115%7%
Table 8. Mineral content and the %RDA of the commonly consumed Malay cuisines.
Table 8. Mineral content and the %RDA of the commonly consumed Malay cuisines.
FoodAmount of Na (mg)% RDAAmount of Ca (mg)% RDA Amount of Fe (mg)% RDA (Men)%RDA (Women)
Ayam Penyet41521%35235%1.2716%7%
Nasi Kampung Goreng74637%27227%1.2115%7%
Nasi Lemak45923%45946%1.9725%11%
Ikan Penyet39020%90891%0.557%3%
Nasi Ambang Chicken91946%1002100%3.7847%21%
Goreng Pisang49825%36136%0.8310%5%
Tahu Goreng Set57329%1129113%2.0125%11%
Mee Bandung62531%32933%1.418%8%
Mee Bakso73437%23423%0.8711%5%
Lotong31216%40340%0.8110%5%
Mee Siam115658%39940%2.2628%13%
Mee Soto79840%15916%0.8411%5%
Kentang Ball with Rice Cube49125%53153%2.1227%12%
Soto Ayam81141%31532%1.3917%8%
Mee Rebus117059%45345%1.1615%6%
Average67334%48749%119%8%
Table 9. Mineral content and the %RDA of the commonly consumed Indian cuisines.
Table 9. Mineral content and the %RDA of the commonly consumed Indian cuisines.
FoodAmount of Na (mg)%RDAAmount of Ca (mg)% RDAAmount of Fe (mg)% RDA (Men)% RDA (Women)
Original Appam34017%77.58%1.0313%6%
Egg Appam25413%20020%1.5219%8%
Roti Prata61731%17918%0.749%4%
Egg Prata105753%51652%2.8636%16%
Boneless Mutton Biryani86843%36837%1.8423%10%
Poori Set87744%39940%5.2165%29%
Marsala Thosai99950%31632%3.4143%19%
Naan Set121961%53754%2.9937%17%
Chapati Set with Potato86243%27528%2.0225%11%
Putu Mayam1859%23.52%0.7710%4%
Chapati Set with Potato Marsala104352%39540%4.8360%27%
Idli Set40820%18619%2.3329%13%
Egg Thosai88844%21922%1.6220%9%
Vegetable Biryani110055%67768%1.9224%11%
Veg Set Meal102151%28729%1.5419%9%
Average78339%31031%229%13%
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Yeo, P.L.Q.; Bi, X.; Yeo, M.T.Y.; Henry, C.J. Energy Content and Nutrient Profiles of Frequently Consumed Meals in Singapore. Foods 2021, 10, 1659. https://doi.org/10.3390/foods10071659

AMA Style

Yeo PLQ, Bi X, Yeo MTY, Henry CJ. Energy Content and Nutrient Profiles of Frequently Consumed Meals in Singapore. Foods. 2021; 10(7):1659. https://doi.org/10.3390/foods10071659

Chicago/Turabian Style

Yeo, Penny Liu Qing, Xinyan Bi, Michelle Ting Yun Yeo, and Christiani Jeyakumar Henry. 2021. "Energy Content and Nutrient Profiles of Frequently Consumed Meals in Singapore" Foods 10, no. 7: 1659. https://doi.org/10.3390/foods10071659

APA Style

Yeo, P. L. Q., Bi, X., Yeo, M. T. Y., & Henry, C. J. (2021). Energy Content and Nutrient Profiles of Frequently Consumed Meals in Singapore. Foods, 10(7), 1659. https://doi.org/10.3390/foods10071659

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop