Relationship between Food Composition and Its Cold/Hot Properties: A Statistical
Aiying Xie, Hanwen Huang, Fanbin Kong
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Received Date: 30 December 2019
Revised Date: 20 April 2020
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Cold, plain, hot
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Title: Relationship between Food Composition and Its Cold/Hot Properties: A Statistical Study
, Hanwen Huang
, Fanbin Kong
1. College of Animal Science. Southwest University. Chongqing. China.
2. College of Public Health. The University of Georgia. Athens. GA. U.S.A.
3. Department of Food Science & Technology. The University of Georgia. Athens. GA.
30622. U.S.A. Email: email@example.com
Relationship between Food Composition and Its Cold/Hot Properties: A Statistical Study
Aiying Xie, Hanwen Huang, Fanbin Kong
Food cold/hot properties are one of the basic principles of traditional Chinese medicine
(TCM) and have been used as a basis to make healthy food choices in oriental countries for
thousands of years. It is of great interest to know how the cold/hot properties are related to food
nutritional composition. In this study, 179 foods in different categories (cold, plain, and hot)
were identified from the literature. Their compositional data were obtained from USDA and
Chinese food composition databases. The contents of 32 nutritional components and calorie were
used through ANOVA and multivariate analysis to evaluate the most important variables
affecting food warming and cooling characteristics, and the interaction effect of different
components on food properties. Mathematical equations were derived to correlate the component
variables and the probability of the food being cold/hot. The results indicate vitamins (B6, folate,
and VA) are among the most important influencing factors. Logit functions were developed to
evaluate the hot and cold characteristics of a food based on its compositional data. The obtained
information from this study is expected to enhance the understanding of the link between food
composition and its cold/hot properties which may provide another method to evaluate the food
diet and their health effect.
Keywords: Food cold/hot properties; Food composition; Correlation study; Logit functions
For decades, people have realized that isolation and supplementation of compounds may
not effectively capture the benefits of functional foods . Therefore, green and whole foods are
getting more and more popular among consumers. As is well known, modern nutrition science
emphasizes the analytical and quantitative characterization of foods, focusing on the amount and
composition of carbohydrates, fat, protein, vitamins, minerals, and trace elements. While in TCM,
the ancient oriental philosophy developed the qualitative, holistic concept of yin and yang and
five element theory to describe the role of food in human health. In TCM, food is used just like a
medicine and can have both promoting and impeding effects on human health development
depending on the type of food and the characteristics of the human body . Cold/hot properties
of food are one of the core elements in the basic theories of TCM . Foods are classified into
cold, cool, warm and hot according to their effect on the body: those can raise the body’s inner
heat, improve the circulation and nourish the energy of body are warm or hot foods; while those
can calm the blood, clear toxins and reduce heat, conversely, cold or cool foods . The ancient
Chinese medical text "Yellow Emperor’s Classic of Internal Medicine " suggests that cold
symptoms should be treated by heat, and hot symptoms should be treated by cold. According to
this principle, regulating the body can be done by consuming foods with certain hot/cold
properties to achieve a balance and maintain a healthy state.
It is reasonable to think that there might exist a relationship between the cold/hot nature of
food and its nutritional composition, and a study on such relationships should enhance our
understanding of food effects on human health. Some studies about the material basis of the food
cold/hot properties were conducted by researchers in Chinese herbal medicine [9, 10, 11, 12],
while very limited studies were done by food scientists. A few papers were published in recent
years focusing on the relationship between the food cold/hot property and different components
including mineral element [13, 14], protein , carbohydrate [12, 14, 15], fat [14, 16],
vitamins, dietary fiber, and water . But the study was not found in literature about the effect
of caffeine and phenolic compounds, which are important functional/bioactive components and
may significantly contribute to the hot/cold characteristics of the food. Besides, different
components may interact with each other, i.e. they may synergistically enhance the hot/cold
properties, or counteract with each other to lessen their effect on the human body, but such
studies were not found in the literature. Furthermore, the classification of cold/hot food in
previous studies was mostly based on one or two reference literature, while cold/hot
categorization for the same food often differs in different publications. For example, Mango is
labeled cool in the Encyclopedia of Chinese Diet , while plain in Compilation of Chinese
Herbal Medicine (Second Edition) . Goose meat is labeled plain in Encyclopedia of Chinese
Diet , while cool in Shi Liao Ben Cao , and warm in Sui Xi Ju Yin Shi Pu . The
confusing information also emphasize the necessity to conduct a systematic and comprehensive
investigation of the food hot/cold properties and their composition.
Therefore, the aims of the present study were 1) to statistically determine the impact of
various food components, including macro- and micronutrients, functional compounds, and their
interactions, on food hot/cold properties; and 2) to develop a mathematical model for predicting
the food hot/cold characteristics from the composition data. A thorough literature review was
conducted to identify typical foods in the three categories: cold, hot and plain. The detailed
food composition data were obtained from USDA Food Composition Databases (2015-2016),
Chinese food composition (2002 and 2004), and other literature. Both ANOVA and Multivariate
analyses were conducted to reveal the correlation among various food components and the
hot/cold properties, as well as the interaction among different components. Mathematical
equations were derived to relate the most important components and the level of hot and cold
characteristics, which can be used to predict any food products by imputing the composition data
into the equation. The obtained information from this study is expected to increase understanding
to the food hot/cold properties as related to their composition, which may provide another
method to evaluate food diet and the health effect.
2. Materials and methods
2.1 Food selection
A thorough literature review was conducted, covering most available literature in food
hot/cold properties, to identify commonly recognized foods in the three categories: cold, plain,
and warm. The literature included Yin Shan Zheng Yao , Shiliao Bencao , Encyclopedia
of Chinese diet , Great Dictionary of Chinese Medicine (2nd edition) , Foods Ben Cao
Gang Mu ，Sui Xi Ju Yin Shi Pu , Compilation of Chinese Herbal Medicine Second
Edition , Xin Xiu Ben Cao , and Qian Jin Fang . In total, 179 foods (67 cold + 60
plain + 52 hot) were identified and used for the statistical analysis. Table 1 shows the list of
foods in each category.
Table1. List of cold, plain and hot foods used in the study
Wheat bran, crude
Soy sauce Mung seeds
White granlated sugar
Hot chili, red
Vinegar, red wine
Verum Canola oil
Squash, winter, acorn
2.2 Food composition data sources
The food composition data were obtained from Chinese Food Composition (2002, 2004), and
United States Department of Agriculture (USDA) Food Composition Databases (2015-2016). pH
and phenolic contents of food were obtained from related literature [27, 28]. Due to lack of
enough data, 5 components/attributes ("Sugars", "Iodine", "Vitamin D", "Vitamin K”, "trans
-fatty acids") were not included in the analysis. Finally, there were 33 variables included in the
analysis, as shown below (unit shown in parenthesis):
Water (g/100 g), Energy (kcal/100 g), Protein (g/100 g), Total lipid (g/100 g), Carbohydrate
(g/100 g), Fiber (mg/100 g), Ash (mg/100 g), Calcium (mg/100 g), Fe (mg/100 g), Mg (mg/100
g), P (mg/100 g), K (mg/100 g), Na (mg/100 g), Zn (mg/100 g), Se (µg/100 g), Cu (mg/100 g),
Mn (mg/100 g), Vitamin C (mg/100 g), Thiamin (mg/100 g), Riboflavin (mg/100 g), Vitamin B6
(mg/100 g), Folate (µg/100 g),Vitamin B12(µg/100 g), Vitamin A (µg/100 g), Vitamin E (µg/100
g), Lipids (g/100 g), Total saturated fatty acids (g/100 g), Total monounsaturated fatty acids
(g/100 g), Total polyunsaturated fatty acids (g/100 g), Cholesterol (mg/100 g), Caffeine (mg/100
g), Phenolic compounds (mg/100 g), and pH.
2.3 Statistical analysis
Analysis of variance (ANOVA) and multivariate ordinal regression model were carried out
using software R Version 3.1.2 to determine the most important variables (components) affecting
food cold/hot properties. ANOVA was used to analyze the mean differences of each individual
variable among cool, plain, and hot groups. Multivariate ordinal regression considered cool,
plain, and hot as 3 ordered levels and fitted all variables together into a regression model such
that the interaction among variables can be included. Missing data were replaced by the mean of
the observed ones for the similar foods.
3.1 ANOVA analysis
Correlation analysis was conducted using ANOVA analysis to reveal the impact of each
variable among the three groups (cool, plain and hot) on the hot/cold properties. The result is
shown in Table 2. Among the 33 variables, 14 were found significant including 6 vitamins (B6,
folate, B12, VE, niacin, and VC), 3 minerals (Mn, P, and K), energy substances (carbohydrate,
protein), water, and fiber. As shown in Table 2, B6, folate, water, B12 and Mn are the most
significant factors (p<0.01) among all the variables.
Table 2. The result of ANOVA analysis
Variables Cold/hot property p-values
B6 hot 0.00145
Folate cold 0.00497
Water cold 0.00505
B12 cold 0.00526
Mn hot 0.00795
Energy hot 0.01894
Carbohydrate hot 0.02556
Protein hot 0.02634
VE hot 0.03377
P hot 0.05266
K hot 0.05329
Niacin hot 0.05600
VC hot 0.07948
Fiber hot 0.08524
In addition, Table 2 shows that B12, water and folate contribute to cold nature of food; while
B6, Mn, energy, carbohydrate, protein, VE, P, K, niacin, and VC make food warm.
Fatty acids, such as saturated, monounsaturated, and polyunsaturated fatty acids, cholesterol,
phenolic and pH were also analyzed, using the available data, and none of these variables was
3.2 Multivariate analysis
Table 3. Result of multivariate analysis
Variables Cold/heat property p-values
Folate cold <0.0001
B6 hot 0.00258
Ca hot 0.00868
lipid hot 0.00958
VA hot 0.01553
Caffeine hot 0.03467
The result of multivariate analysis is shown in Table 3. Six variables were significant, and half of
these variables were vitamins (B6, folate, and VA). Notably, folate and B6 were significant
variables from both ANOVA and multivariate analysis. The results implied that vitamins have an
important effect on the cold/hot properties of foods.
3.3 Interactions analysis
Based on the previous studies [10, 17, 29, 30, 31, 32, 33, 34], interaction analysis was conducted
on the following variables: water, energy, fiber, caffeine, Ca, K, P, Fe, Mg, Cu, Zn, Mn, Niacin,
VE, VC, B6, B12, and folate. The results indicated that significant interactions existed
between folate and VA, and between B6 and caffeine.
3.4 Regression models to relate food composition and its hot/cold properties
The final fitted regression equations are
Logit (cold) = 0.1598 + 0.0339664*Folate - 0.0342311*B6 - 0.0160967*Ca 145
- 0.0264716*Lipids - 0.0151448*VA - 0.2100914*Caffeine (Eq. 1) 146
Logit (cold + plain) = 2.1068 + 0.0339664*Folate - 0.0342311*B6 - 0.0160967*Ca 147
- 0.0264716* Lipids - 0.0151448*VA- 0.2100914*Caffeine (Eq. 2) 148
The first equation can be used to obtain the probability of a food to be cold, and the second
equation provides the probability of a food to be cold or plain. It can be seen that increasing
folate makes the food colder while increasing B6, Ca, lipid, VA and caffeine make it hotter.
When other constituents remain constant, increasing the content of folate in food by one unit, the
estimated odds of food cold increases by e
.=1.03455 times. When increasing B6, Ca,
Lipid, VA and caffeine, the estimated odds of food cold decreases (OR values < 1).
If the probability of a food to be cold, plain or hot is P
=1 (Eq. 3)
) = EXP (logit (cold)) (Eq. 4)
=EXP (logit (cold + plain)) (Eq. 5)
Using the above equations (1 to 5) , the probability of a food to be in any group can be obtained.
Therefore, one can predict the type of a food nature (cold, plain or hot) by its content of folate,
B6, Ca, lipid, VA and caffeine.
Researchers have proposed different theories to explain food cold and hot properties of food
from their nutrition and chemical components perspectives. In the TCM, it has been widely
believed that the cold/hot properties of food is derived from the constituents the food contained
. Network pharmacology, metabolomics, and chemical informatics were used to study the
possible molecular mechanisms relating to the different biological effects of the cold and hot
TCM group and discovered significant correlation between the cold and hot TCM group and
their active components [6, 8]. It was reported that compounds associated with cold nature
contain more aliphatic rings than the other groups while compounds associated with hot nature
were on average of lower molecular weight with more aromatic ring systems than other groups
. Other researchers using statistical analysis found that dietary fiber, Mg, Cu are related to
the cold nature of food while water, proteins, fat, carbohydrate, iron, Se, and Zn contribute to hot
In this study, 179 cold, plain and hot foods were identified from the literature, and their
composition data were used to analyze the correlation between the cold/hot nature and their
chemical composition. To our knowledge, this study covered the most varieties of foods as
compared with similar studies in the literature. The results of this study confirmed that the
cold/hot properties of foods are largely dependent on their compositions (Table 1). Specifically,
energy substances include protein, carbohydrate and lipids significantly contribute to hot nature
of food, as they mainly provide energy to maintain body function. This result is consistent with
previous studies [10, 14, 17]. Feng et al. (11) used HPLC to analyze the amino acid content of
different foods and found that the average amino acid content in the hot foods is 32% higher than
the cold food. It was recognized that consumption of the energy substances could promote heat
production of the body [35, 36] and potentially increase body temperature [37, 38]. However, not
all the hot food can cause a change of body temperature .
It was reported that mineral elements significantly affect food cold/hot properties (7, 29, 31), and
the cold/hot property is closely related to the oxidation potential of the elements/chemical
compounds in the food. Anions of the elements such as Fe, Co, Ni, and Cu contribute to cold
property, while cations of the elements such as Ti, Cr, Mo, and Zn contribute to hot property .
In our study, Mn, Ca, P, and K significantly contribute to hot. Among them, Ca, Mn, and K
belong to the fourth period in the periodic table of elements with high oxidation potential. Other
studies reported similar effect of Mn [29, 31] and K  on food hot property. However, one
studies reported that Ca and P contribute to cold . The reason may be related to the different
forms of the elements. It was found that for different foods, the influence of the same element is
dependent on its existing form [9, 17]. For example, Ca has different existing forms in milk and
spinach with the former having higher bioavailability than the later. In this case, even if the
content of Ca is the same, the impact on the human body may be different.
Vitamins are important for human health; and most of them come from food. Our study
indicated that 6 vitamins play a significant role in the cold/hot nature of food, in which niacin,
VA contribute to hot, while folate, B6, and B12 contribute to cold. Similar results were
reported by Zhang (17) who found that VC and VE contribute to the hot property of food.
Water is important for food cold/hot properties [18, 24]. In this study, water was found to
contribute to the cold property. Although this result is in line with most of the previous studies,
one study suggested that water contributes to hot property . A previous study has also
analyzed how the state of water in food influenced cold/hot properties . Dietary fiber can be
subdivided into soluble dietary fiber and insoluble dietary fiber, which have different effects on
the body. In this study, fiber was found to contribute to hot, but other studies suggested that it
contributes to cold [9, 17]. The results of this study also indicated that caffeine significantly
contributes to the hot property of food.
In the literature, inconsistent results were reported from different studies on the cold/hot
properties of the same components, which is likely because the raw data used for analysis came
from different sources. For example, the food compositional data in this study were obtained
from USDA Food Composition Databases (2015-2016) and Chinese Food Composition (2002,
2004), while the raw data in Zhang’s study  were exclusively obtained from Chinese Food
Composition (2002). Also, the different cold/hot classification of the same food in the literature
may be also because of the different growing environment and processing conditions [2, 40, 41].
Therefore, detailed information is needed to explain the inconsistent or conflicting results
reported in different studies. In this study, the model (Eq. 1 & 2) were derived to assess the
probability of food being cold, plain or hot, which could be used as a simple method to evaluate
food cold/hot nature with their composition data.
Results of ANOVA and multivariate analysis indicated that 18 food components have significant
effects on cold/hot property, including B6, Folate, Water, B12, Mn, Energy, Carbohydrate,
Protein, VE, P, K, Niacin, VC, Fiber, Ca, Lipid, VA, and Caffeine. Seven of them are vitamins,
which suggested that vitamins play an important role in food cold/hot properties. Caffeine was
found to make food hot suggesting that functional components are also important factors.
Significant interaction effects of some components were found. Mathematical equations derived
from this study provide another method to predict food cooling and warming effect based on
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• ANOVA and multivariate analysis indicated that 18 food components have significant
effects on cold/hot property of food.
• Vitamins play an important role in food cold/hot properties.
• Folate contributes to cold property of food.
• Mathematical equations were derived to predict food cooling and warming effect based
on their composition.
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