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Relationship between Food Composition and Its Cold/Hot Properties: A Statistical Study

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Abstract

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.
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Relationship between Food Composition and Its Cold/Hot Properties: A Statistical
Study
Aiying Xie, Hanwen Huang, Fanbin Kong
PII: S2666-1543(20)30024-7
DOI: https://doi.org/10.1016/j.jafr.2020.100043
Reference: JAFR 100043
To appear in: Journal of Agriculture and Food Research
Received Date: 30 December 2019
Revised Date: 20 April 2020
Accepted Date: 22 April 2020
Please cite this article as: A. Xie, H. Huang, F. Kong, Relationship between Food Composition
and Its Cold/Hot Properties: A Statistical Study, Journal of Agriculture and Food Research, https://
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Cold, plain, hot
Macronutrients,
micronutrients,
water, energy,
bioactive
compounds
Eastern view of
food properties
Western view of f
ood
properties
Title: Relationship between Food Composition and Its Cold/Hot Properties: A Statistical Study
1
Aiying Xie
1
, Hanwen Huang
2
, Fanbin Kong
3,*
2
1. College of Animal Science. Southwest University. Chongqing. China.
3
2. College of Public Health. The University of Georgia. Athens. GA. U.S.A.
4
3. Department of Food Science & Technology. The University of Georgia. Athens. GA.
5
30622. U.S.A. Email: fkong@uga.edu
6
7
Relationship between Food Composition and Its Cold/Hot Properties: A Statistical Study
8
Aiying Xie, Hanwen Huang, Fanbin Kong
9
Abstract:
10
Food cold/hot properties are one of the basic principles of traditional Chinese medicine
11
(TCM) and have been used as a basis to make healthy food choices in oriental countries for
12
thousands of years. It is of great interest to know how the cold/hot properties are related to food
13
nutritional composition. In this study, 179 foods in different categories (cold, plain, and hot)
14
were identified from the literature. Their compositional data were obtained from USDA and
15
Chinese food composition databases. The contents of 32 nutritional components and calorie were
16
used through ANOVA and multivariate analysis to evaluate the most important variables
17
affecting food warming and cooling characteristics, and the interaction effect of different
18
components on food properties. Mathematical equations were derived to correlate the component
19
variables and the probability of the food being cold/hot. The results indicate vitamins (B6, folate,
20
and VA) are among the most important influencing factors. Logit functions were developed to
21
evaluate the hot and cold characteristics of a food based on its compositional data. The obtained
22
information from this study is expected to enhance the understanding of the link between food
23
composition and its cold/hot properties which may provide another method to evaluate the food
24
diet and their health effect.
25
Keywords: Food cold/hot properties; Food composition; Correlation study; Logit functions
26
27
1. Introduction
28
For decades, people have realized that isolation and supplementation of compounds may
29
not effectively capture the benefits of functional foods [1]. Therefore, green and whole foods are
30
getting more and more popular among consumers. As is well known, modern nutrition science
31
emphasizes the analytical and quantitative characterization of foods, focusing on the amount and
32
composition of carbohydrates, fat, protein, vitamins, minerals, and trace elements. While in TCM,
33
the ancient oriental philosophy developed the qualitative, holistic concept of yin and yang and
34
five element theory to describe the role of food in human health. In TCM, food is used just like a
35
medicine and can have both promoting and impeding effects on human health development
36
depending on the type of food and the characteristics of the human body [2]. Cold/hot properties
37
of food are one of the core elements in the basic theories of TCM [3]. Foods are classified into
38
cold, cool, warm and hot according to their effect on the body: those can raise the body’s inner
39
heat, improve the circulation and nourish the energy of body are warm or hot foods; while those
40
can calm the blood, clear toxins and reduce heat, conversely, cold or cool foods [4]. The ancient
41
Chinese medical text "Yellow Emperor’s Classic of Internal Medicine " suggests that cold
42
symptoms should be treated by heat, and hot symptoms should be treated by cold. According to
43
this principle, regulating the body can be done by consuming foods with certain hot/cold
44
properties to achieve a balance and maintain a healthy state.
45
It is reasonable to think that there might exist a relationship between the cold/hot nature of
46
food and its nutritional composition, and a study on such relationships should enhance our
47
understanding of food effects on human health. Some studies about the material basis of the food
48
cold/hot properties were conducted by researchers in Chinese herbal medicine [9, 10, 11, 12],
49
while very limited studies were done by food scientists. A few papers were published in recent
50
years focusing on the relationship between the food cold/hot property and different components
51
including mineral element [13, 14], protein [11], carbohydrate [12, 14, 15], fat [14, 16],
52
vitamins, dietary fiber, and water [17]. But the study was not found in literature about the effect
53
of caffeine and phenolic compounds, which are important functional/bioactive components and
54
may significantly contribute to the hot/cold characteristics of the food. Besides, different
55
components may interact with each other, i.e. they may synergistically enhance the hot/cold
56
properties, or counteract with each other to lessen their effect on the human body, but such
57
studies were not found in the literature. Furthermore, the classification of cold/hot food in
58
previous studies was mostly based on one or two reference literature, while cold/hot
59
categorization for the same food often differs in different publications. For example, Mango is
60
labeled cool in the Encyclopedia of Chinese Diet [18], while plain in Compilation of Chinese
61
Herbal Medicine (Second Edition) [19]. Goose meat is labeled plain in Encyclopedia of Chinese
62
Diet [18], while cool in Shi Liao Ben Cao [20], and warm in Sui Xi Ju Yin Shi Pu [21]. The
63
confusing information also emphasize the necessity to conduct a systematic and comprehensive
64
investigation of the food hot/cold properties and their composition.
65
Therefore, the aims of the present study were 1) to statistically determine the impact of
66
various food components, including macro- and micronutrients, functional compounds, and their
67
interactions, on food hot/cold properties; and 2) to develop a mathematical model for predicting
68
the food hot/cold characteristics from the composition data. A thorough literature review was
69
conducted to identify typical foods in the three categories: cold, hot and plain. The detailed
70
food composition data were obtained from USDA Food Composition Databases (2015-2016),
71
Chinese food composition (2002 and 2004), and other literature. Both ANOVA and Multivariate
72
analyses were conducted to reveal the correlation among various food components and the
73
hot/cold properties, as well as the interaction among different components. Mathematical
74
equations were derived to relate the most important components and the level of hot and cold
75
characteristics, which can be used to predict any food products by imputing the composition data
76
into the equation. The obtained information from this study is expected to increase understanding
77
to the food hot/cold properties as related to their composition, which may provide another
78
method to evaluate food diet and the health effect.
79
80
2. Materials and methods
81
2.1 Food selection
82
A thorough literature review was conducted, covering most available literature in food
83
hot/cold properties, to identify commonly recognized foods in the three categories: cold, plain,
84
and warm. The literature included Yin Shan Zheng Yao [22], Shiliao Bencao [19], Encyclopedia
85
of Chinese diet [18], Great Dictionary of Chinese Medicine (2nd edition) [23], Foods Ben Cao
86
Gang Mu [24]Sui Xi Ju Yin Shi Pu [21], Compilation of Chinese Herbal Medicine Second
87
Edition [19], Xin Xiu Ben Cao [25], and Qian Jin Fang [26]. In total, 179 foods (67 cold + 60
88
plain + 52 hot) were identified and used for the statistical analysis. Table 1 shows the list of
89
foods in each category.
90
Table1. List of cold, plain and hot foods used in the study
91
Cold food
Crawfish
Zizania latifolia
Porphyra
Herba houttuyniae
Kiwifruit
Grapefruit
Millet, raw
Lard oil
Persimmons
Corbiculaflumine
Coix seed
Momordica grosvenori
Melons, casaba
Clam
Oranges
Apples
Pomelo
Bamboo shoots
Pears
Strawberries
Purslane
Arrowhead
Syrup, Cane
Malan
Ferns
Salt
Rabbit
Radishes
Bitter gourd
Mulberries
Horse meat
Wheat bran, crude
Cucumber
Seaweed, kelp
Frog
Tea, green
Blood ,duck
Asparagus
Eggplant
Peppermint, fresh
Margarya Watermelon
Carambola,
(starfruit)
Tomatoes
Crab, dungeness
Lotus root
Soybeans sprouted
Oil, sesame
Crab, blue
Mung sprouted
Chufa
Milk
Egg, duck
Celery
Towel gourd
Meat, buffalo
Egg
Butter
Mangos
Soy sauce Mung seeds
Portunus
trituberculatus
Mollusks, octopus
Banana
Tofu
Swamp cabbage
Oyster
Plain food
Alfalfa
Crucian
Corn
Figs
Dolichos sinensis
Pork
Carrots
Chrysanthemum, garland
Hazelnuts
Milk, human
Mushrooms shiitake
Taro
Beans, kidney
pigeon
Mushrooms, oyster
Agaric
Peanuts
Quail, meat
White fungus
Licorioce
Peas
Honey
Quail egg
Cabbage, savoy
Rice
Peanut oil
Abalone
Chrysanthemum flower
Vigna umbellata
Coconut meat
Lotus seeds
Fish, carp
Ginkgo nuts
Grapes
Beans, black
Goose
Butter fish
Yam
Sunflower seed
Beef
Mandarin fish
Pineapple
Goji berries
Plum
Silverfish
Raspberries
Ass meat
White granlated sugar
Black carp
Potatoes
Duck, meat
Perch
Oliver
Cabbage (pe
-
tsai)
Sweet potato
Hyacinth
-
beans
Yellow beans
Chestnuts
Turtle
Sturgeon
Hot food
Liquor
Apricots, raw
Pumpkin
Deer meat
Goat
Sugars, brown
Chives
Chicken
Ginger
Mustard greens
Leeks
Eel
Cinnamon
Papayas
Potherb
Garlic, raw
Green pepper
Bayberry
Pine nuts
Syrups, malt
Hot chili, red
Coconut water
Pistachio nuts
Cloves, ground
Pepper, black
Jackfruit
Rice, glutinous
Coffee, brewed
Soy oil
Tangerines
Sorghum flour
Vinegar, red wine
Alcoholic red
Peaches
Egg, goose
Maltose
Cherries
Guavas
Carp
Mustard
Curry powder
Toona sinensis
Sheep milk
Prickly pepper
Cinnamomum
Verum Canola oil
Caraway seed
Squash, winter, acorn
Mytilide
Aristichths
Salmo playcephalus
Black
-
bone chicken
2.2 Food composition data sources
92
The food composition data were obtained from Chinese Food Composition (2002, 2004), and
93
United States Department of Agriculture (USDA) Food Composition Databases (2015-2016). pH
94
and phenolic contents of food were obtained from related literature [27, 28]. Due to lack of
95
enough data, 5 components/attributes ("Sugars", "Iodine", "Vitamin D", "Vitamin K”, "trans
96
-fatty acids") were not included in the analysis. Finally, there were 33 variables included in the
97
analysis, as shown below (unit shown in parenthesis):
98
Water (g/100 g), Energy (kcal/100 g), Protein (g/100 g), Total lipid (g/100 g), Carbohydrate
99
(g/100 g), Fiber (mg/100 g), Ash (mg/100 g), Calcium (mg/100 g), Fe (mg/100 g), Mg (mg/100
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),
101
Mn (mg/100 g), Vitamin C (mg/100 g), Thiamin (mg/100 g), Riboflavin (mg/100 g), Vitamin B6
102
(mg/100 g), Folate (µg/100 g),Vitamin B12(µg/100 g), Vitamin A (µg/100 g), Vitamin E (µg/100
103
g), Lipids (g/100 g), Total saturated fatty acids (g/100 g), Total monounsaturated fatty acids
104
(g/100 g), Total polyunsaturated fatty acids (g/100 g), Cholesterol (mg/100 g), Caffeine (mg/100
105
g), Phenolic compounds (mg/100 g), and pH.
106
2.3 Statistical analysis
107
Analysis of variance (ANOVA) and multivariate ordinal regression model were carried out
108
using software R Version 3.1.2 to determine the most important variables (components) affecting
109
food cold/hot properties. ANOVA was used to analyze the mean differences of each individual
110
variable among cool, plain, and hot groups. Multivariate ordinal regression considered cool,
111
plain, and hot as 3 ordered levels and fitted all variables together into a regression model such
112
that the interaction among variables can be included. Missing data were replaced by the mean of
113
the observed ones for the similar foods.
114
115
3. Result
116
3.1 ANOVA analysis
117
Correlation analysis was conducted using ANOVA analysis to reveal the impact of each
118
variable among the three groups (cool, plain and hot) on the hot/cold properties. The result is
119
shown in Table 2. Among the 33 variables, 14 were found significant including 6 vitamins (B6,
120
folate, B12, VE, niacin, and VC), 3 minerals (Mn, P, and K), energy substances (carbohydrate,
121
protein), water, and fiber. As shown in Table 2, B6, folate, water, B12 and Mn are the most
122
significant factors (p<0.01) among all the variables.
123
Table 2. The result of ANOVA analysis
124
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
125
In addition, Table 2 shows that B12, water and folate contribute to cold nature of food; while
126
B6, Mn, energy, carbohydrate, protein, VE, P, K, niacin, and VC make food warm.
127
Fatty acids, such as saturated, monounsaturated, and polyunsaturated fatty acids, cholesterol,
128
phenolic and pH were also analyzed, using the available data, and none of these variables was
129
found significant.
130
3.2 Multivariate analysis
131
Table 3. Result of multivariate analysis
132
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
133
The result of multivariate analysis is shown in Table 3. Six variables were significant, and half of
134
these variables were vitamins (B6, folate, and VA). Notably, folate and B6 were significant
135
variables from both ANOVA and multivariate analysis. The results implied that vitamins have an
136
important effect on the cold/hot properties of foods.
137
3.3 Interactions analysis
138
Based on the previous studies [10, 17, 29, 30, 31, 32, 33, 34], interaction analysis was conducted
139
on the following variables: water, energy, fiber, caffeine, Ca, K, P, Fe, Mg, Cu, Zn, Mn, Niacin,
140
VA
,
VE, VC, B6, B12, and folate. The results indicated that significant interactions existed
141
between folate and VA, and between B6 and caffeine.
142
3.4 Regression models to relate food composition and its hot/cold properties
143
The final fitted regression equations are
144
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
149
equation provides the probability of a food to be cold or plain. It can be seen that increasing
150
folate makes the food colder while increasing B6, Ca, lipid, VA and caffeine make it hotter.
151
When other constituents remain constant, increasing the content of folate in food by one unit, the
152
estimated odds of food cold increases by e
0.0339664
.=1.03455 times. When increasing B6, Ca,
153
Lipid, VA and caffeine, the estimated odds of food cold decreases (OR values < 1).
154
If the probability of a food to be cold, plain or hot is P
1
, P
2
, P
3
, respectively,
155
Then
156
P
1
+P
2
+P
3
=1 (Eq. 3)
157
P
1
/ (P
2
+P
3
) = EXP (logit (cold)) (Eq. 4)
158
(P
2
+P
3
)/P
3
=EXP (logit (cold + plain)) (Eq. 5)
159
Using the above equations (1 to 5) , the probability of a food to be in any group can be obtained.
160
Therefore, one can predict the type of a food nature (cold, plain or hot) by its content of folate,
161
B6, Ca, lipid, VA and caffeine.
162
163
4. Discussion
164
Researchers have proposed different theories to explain food cold and hot properties of food
165
from their nutrition and chemical components perspectives. In the TCM, it has been widely
166
believed that the cold/hot properties of food is derived from the constituents the food contained
167
[5]. Network pharmacology, metabolomics, and chemical informatics were used to study the
168
possible molecular mechanisms relating to the different biological effects of the cold and hot
169
TCM group and discovered significant correlation between the cold and hot TCM group and
170
their active components [6, 8]. It was reported that compounds associated with cold nature
171
contain more aliphatic rings than the other groups while compounds associated with hot nature
172
were on average of lower molecular weight with more aromatic ring systems than other groups
173
[42]. Other researchers using statistical analysis found that dietary fiber, Mg, Cu are related to
174
the cold nature of food while water, proteins, fat, carbohydrate, iron, Se, and Zn contribute to hot
175
[17].
176
In this study, 179 cold, plain and hot foods were identified from the literature, and their
177
composition data were used to analyze the correlation between the cold/hot nature and their
178
chemical composition. To our knowledge, this study covered the most varieties of foods as
179
compared with similar studies in the literature. The results of this study confirmed that the
180
cold/hot properties of foods are largely dependent on their compositions (Table 1). Specifically,
181
energy substances include protein, carbohydrate and lipids significantly contribute to hot nature
182
of food, as they mainly provide energy to maintain body function. This result is consistent with
183
previous studies [10, 14, 17]. Feng et al. (11) used HPLC to analyze the amino acid content of
184
different foods and found that the average amino acid content in the hot foods is 32% higher than
185
the cold food. It was recognized that consumption of the energy substances could promote heat
186
production of the body [35, 36] and potentially increase body temperature [37, 38]. However, not
187
all the hot food can cause a change of body temperature [17].
188
It was reported that mineral elements significantly affect food cold/hot properties (7, 29, 31), and
189
the cold/hot property is closely related to the oxidation potential of the elements/chemical
190
compounds in the food. Anions of the elements such as Fe, Co, Ni, and Cu contribute to cold
191
property, while cations of the elements such as Ti, Cr, Mo, and Zn contribute to hot property [7].
192
In our study, Mn, Ca, P, and K significantly contribute to hot. Among them, Ca, Mn, and K
193
belong to the fourth period in the periodic table of elements with high oxidation potential. Other
194
studies reported similar effect of Mn [29, 31] and K [32] on food hot property. However, one
195
studies reported that Ca and P contribute to cold [31]. The reason may be related to the different
196
forms of the elements. It was found that for different foods, the influence of the same element is
197
dependent on its existing form [9, 17]. For example, Ca has different existing forms in milk and
198
spinach with the former having higher bioavailability than the later. In this case, even if the
199
content of Ca is the same, the impact on the human body may be different.
200
Vitamins are important for human health; and most of them come from food. Our study
201
indicated that 6 vitamins play a significant role in the cold/hot nature of food, in which niacin,
202
VC, VE
,
VA contribute to hot, while folate, B6, and B12 contribute to cold. Similar results were
203
reported by Zhang (17) who found that VC and VE contribute to the hot property of food.
204
Water is important for food cold/hot properties [18, 24]. In this study, water was found to
205
contribute to the cold property. Although this result is in line with most of the previous studies,
206
one study suggested that water contributes to hot property [17]. A previous study has also
207
analyzed how the state of water in food influenced cold/hot properties [39]. Dietary fiber can be
208
subdivided into soluble dietary fiber and insoluble dietary fiber, which have different effects on
209
the body. In this study, fiber was found to contribute to hot, but other studies suggested that it
210
contributes to cold [9, 17]. The results of this study also indicated that caffeine significantly
211
contributes to the hot property of food.
212
In the literature, inconsistent results were reported from different studies on the cold/hot
213
properties of the same components, which is likely because the raw data used for analysis came
214
from different sources. For example, the food compositional data in this study were obtained
215
from USDA Food Composition Databases (2015-2016) and Chinese Food Composition (2002,
216
2004), while the raw data in Zhang’s study [17] were exclusively obtained from Chinese Food
217
Composition (2002). Also, the different cold/hot classification of the same food in the literature
218
may be also because of the different growing environment and processing conditions [2, 40, 41].
219
Therefore, detailed information is needed to explain the inconsistent or conflicting results
220
reported in different studies. In this study, the model (Eq. 1 & 2) were derived to assess the
221
probability of food being cold, plain or hot, which could be used as a simple method to evaluate
222
food cold/hot nature with their composition data.
223
224
5. Conclusions
225
Results of ANOVA and multivariate analysis indicated that 18 food components have significant
226
effects on cold/hot property, including B6, Folate, Water, B12, Mn, Energy, Carbohydrate,
227
Protein, VE, P, K, Niacin, VC, Fiber, Ca, Lipid, VA, and Caffeine. Seven of them are vitamins,
228
which suggested that vitamins play an important role in food cold/hot properties. Caffeine was
229
found to make food hot suggesting that functional components are also important factors.
230
Significant interaction effects of some components were found. Mathematical equations derived
231
from this study provide another method to predict food cooling and warming effect based on
232
their composition.
233
234
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Highlights
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.
We wish to confirm that there are no known conflicts of interest associated with this publication and
there has been no significant financial support for this work that could have influenced its outcome.
We confirm that the manuscript has been read and approved by all named authors and that there are
no other persons who satisfied the criteria for authorship but are not listed.
We further confirm that the order of authors listed in the manuscript has been approved by all of us.
We confirm that we have given due consideration to the protection of intellectual property associated
with this work and that there are no impediments to publication, including the timing of publication,
with respect to intellectual property. In so doing we confirm that we have followed the regulations of
our institutions concerning intellectual property.
We understand that the Corresponding Author is the sole contact for the Editorial process (including
Editorial Manager and direct communications with the office). He/she is responsible for communicating
with the other authors about progress, submissions of revisions and final approval of proofs.
We confirm that we have provided a current, correct email address which is accessible by the
Corresponding Author.
... Xie et al. [37] 2020 United States of America, China ...
... Regression methods are a powerful tool in statistics that are widely used to predict the values of dependent variables using information concerning independent variables. Three papers [21,25,37] reported applying regression methods to the FCDB. Two papers [25,37] related concepts from traditional Chinese medicine to food composition. ...
... Three papers [21,25,37] reported applying regression methods to the FCDB. Two papers [25,37] related concepts from traditional Chinese medicine to food composition. All foods in traditional Chinese medicine are categorised into the four natures: cold, cool, warm, and hot. ...
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Evidence-based knowledge of the relationship between foods and nutrients is needed to inform dietary-based guidelines and policy. Proper and tailored statistical methods to analyse food composition databases (FCDBs) could assist in this regard. This review aims to collate the existing literature that used any statistical method to analyse FCDBs, to identify key trends and research gaps. The search strategy yielded 4238 references from electronic databases of which 24 fulfilled our inclusion criteria. Information on the objectives, statistical methods, and results was extracted. Statistical methods were mostly applied to group similar food items (37.5%). Other aims and objectives included determining associations between the nutrient content and known food characteristics (25.0%), determining nutrient co-occurrence (20.8%), evaluating nutrient changes over time (16.7%), and addressing the accuracy and completeness of databases (16.7%). Standard statistical tests (33.3%) were the most utilised followed by clustering (29.1%), other methods (16.7%), regression methods (12.5%), and dimension reduction techniques (8.3%). Nutrient data has unique characteristics such as correlated components, natural groupings, and a compositional nature. Statistical methods used for analysis need to account for this data structure. Our summary of the literature provides a reference for researchers looking to expand into this area.
... A study exploring factors influencing food choices of Chinese university students living in the USA reported that participants tended to eat more "yin" foods in the summer, more "yang" food in winter [44]. Moreover, participants believed that some food (e.g., herbs, garlic, ginger, swallow saliva, white fungus) had either healing or damaging properties [40,49,50]. ...
... TCM has a unique cultural influence on Chinese people's dietary behaviours. While individuals may have different levels of knowledge of TCM [49], many generally believe in the concept of achieving a nutritional "balance of yin and yang", despite the categorisation of yin/cold and yang/hot foods being inconsistent in different publications [50]. For example, mango is labelled "cool" in the Encyclopaedia of Chinese Diet, while it is regarded as "plain" in the Compilation of Chinese Herbal Medicine [50]. ...
... While individuals may have different levels of knowledge of TCM [49], many generally believe in the concept of achieving a nutritional "balance of yin and yang", despite the categorisation of yin/cold and yang/hot foods being inconsistent in different publications [50]. For example, mango is labelled "cool" in the Encyclopaedia of Chinese Diet, while it is regarded as "plain" in the Compilation of Chinese Herbal Medicine [50]. ...
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Determinants of food choice in Chinese populations have not been systematically synthesised using a cultural lens. This study reviewed qualitative studies exploring food choice determinants of both Chinese mainlanders and Chinese immigrants living in Western countries. Ovid Medline, CINAHL Plus, Web of Science, ProQuest, and China National Knowledge Infrastructure database (CNKI) were searched from database inception to 1 April 2021. Studies were included if they involved qualitative research methods, were written in English or Chinese, investigated the factors influencing food choices, and targeted Chinese mainlanders or Chinese immigrants living in Western countries. Twenty-five studies (24 in English, 1 in Chinese) were included, involving 2048 participants. Four themes were identified; (1) the principles of traditional Chinese medicine (TCM), (2) perceptions of a healthy diet in Chinese culture (e.g., regular eating, eating in moderation, and emphasis on food freshness), (3) the desire to maintain harmony in families/communities, and (4) physical/social environmental factors all significantly influenced Chinese people’s food choices. It is important to acknowledge these factors when developing culturally appropriate nutrition programs for promoting health in Chinese mainlanders and Chinese immigrants.
... It should be noted that some findings were contradictory. For example, Xie et al. (2020) reported that Zhang (2006) identified water to be correlated with a 'hot' label (Zhang 2006), whereas multiple other sources suggest the opposite; as does also 'yin/yang' theory. Hence it is more plausible that water belongs to the 'cool' category. ...
... In addition, other conflicting findings include those for fiber, iron, and vitamin C (with all three being coded twice as 'cooling,' and once as 'heating'); and manganese, retinol, and vitamin A (with one coding each for 'cooling,' and 'heating'). Possible explanations for discrepancies with respect to compositions and 'hot' and 'cold' labeling were provided by both Liu et al. (2012) and Xie et al. (2020). Liu et al. (2012) suggested that the loss of electrons from minerals may result in a 'cold' nature, whereas when electrons are gained, energy is released, and a 'hot' nature is exhibited. ...
... Consequently, different ionization potentials may occur under differing conditions. Xie et al. (2020) similarly postulated that different elemental forms in foods, or bioavailabilities, may result in differing physiological effects. For example, soluble and insoluble fiber may have different properties and hence may explain differing 'hot' and 'cold' associations. ...
Chapter
Ancient scholars across cultures have postulated that by being less potent versions of herbs, food plays a substantive role in the maintenance of health and treatment of disease. A commonality among these traditional medical systems is in relation to the ‘heating’ and ‘cooling’ properties of foods. In this chapter, ‘hot’ and ‘cold’ classifications of foods are explored, along with ways to optimize health and combat disease. Scientific evaluations of ‘hot’ and ‘cold’ properties are also reviewed in relation to chemical compositions and physiological impacts. A broad scoping Google Scholar search was conducted to identify relevant articles. Scientific evaluations were heterogeneous and of mixed quality. Nonetheless some evidence supported the traditional ‘hot’ and ‘cold’ classifications. Overall, ‘heating’ foods were associated with metabolism and sympathetic nervous system enhancement via increased proportions of caffeine, carbohydrate, protein, fat, and calories; as well as greater oxidation potential; vasodilatory and pro-inflammatory effects; and higher acidity and aromatic compound content. ‘Cooling’ foods were contrastly found to be higher in water, fiber, alkalinity, and aliphatic compounds; as well as associated with anti-inflammatory, and detoxification (elimination) processes. With the potential to specifically tailor diets to suit individual needs, further high-quality research to substantiate traditional food classifications is warranted.
... The concept of food nature is known not only in TPM, but also in the traditional medicine of the Indian, European, Arabic, Roman, Greek, and Chinese cultures [21].The concept of natural food, however, is not entirely intuitive for word scientists, but research in this field is growing. Recently, some studies have analyzed foods based on this concept and have revealed that the nutrients of foods may be one of the distinguishing factors for categorizing their cold-hot properties [22,23]. A previous study showed that hot-natured foods have beneficial effects on improving the clinical score of MS through an immunomodulatory mechanism [24]. ...
... A study by Chunhong Liu et al. evaluated 284 foods according to their cold or hot nature, suggesting that the nutrients of foods could be one of the distinguishing factors for categorizing their cold or hot essence [22]. Another multivariate analysis found that 18 food components had major effects on the cold or hot properties of foods [23]. In this study, cold-natured foods included cold-natured meats (cow and veal meat, hen and chicken, fish/seafood, canned tuna, hamburgers, sausages, bologna, and pizza), cold-natured fruits (watermelon, apricot, cherries, peach, nectarine, greengage, grapefruit, orange, tangerine, pomegranate, plum, and strawberry), and additives (chips, cheese balls, sugar, salt, etc.). ...
... The current study showed that some cold-natured foods can increase the risk of MS. The exploration of potential mechanisms is difficult, but recent Chinese studies have shown that low levels of antioxidants or vitamins (B6; folate) may contribute to the cold essence of certain foods [23,37]. This finding is in agreement with recent studies indicating that deficiencies in folate, vitamin B12, and other vitamins might contribute to the progression of MS. ...
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Introduction It remains a matter of debate whether traditional concepts regarding the nature of food affect the development and progression of multiple sclerosis (MS).To date, there are limited studies that have investigated the association between MS and dietary patterns based on the categories of food nature (hot, cold, or balanced) defined in traditional medicine. Method This case-control study was conducted from October 2019 to February 2020. In total, 60 patients diagnosed with MS within the preceding 6 months and referred to our neurology outpatient clinic were included in our case group. The control group included 180 patients who were referred to the same center for general or orthopedic surgery. Dietary intake was assessed in both groups through a reliable and valid semi-quantitative food frequency questionnaire. Data were assessed using principal component analysis. Results The mean age of the participants was 44.9 ± 17.33 years. The analysis showed that four food patterns were distinguished (eigenvalue > 1), namely “additives and cold-natured foods”, “hot and balanced foods and nuts”, “dairy and legumes”, and “hot and balanced starches”. These food patterns explained 57.8% of the total variance. After adjusting all confounding factors, individuals in the highest quartile and medium quartile of “additives and cold-natured foods” had an elevated MS risk compared with the lowest quartile (OR = 7.21, 95%CI = 2.01–12.38 and OR = 3.37, 95%CI = 1.02–11.35, respectively). Furthermore, individuals in the highest quartile of the “hot and balanced foods and nuts” group were protected against MS compared with its lowest quartile (OR = 0.28, 95%CI = 0.08–0.90). Moreover, a protective effect against MS was seen in the highest quartile of the “hot and balanced starches” group relative to its lowest quartile (OR = 0.34, 95%CI = 0.12–0.98). No significant association was found between “dairy and legumes” and the risk of MS. Conclusion This study revealed that dietary patterns based on the traditional concept of food nature might be associated with the risk of developing MS. This represents the first work in this area, so further research is recommended.
... This concept is closely related to modern medicine, where most cancers and other degenerative diseases are caused by improper diet and nutritional deficiencies. Foods, like human nature, are divided into four categories cold, cool, warm, and hot according to their effects on the body [20]. Foods that can increase body heat, promote circulation, and boost body energy are warm; and those that can calm the blood, remove toxins and reduce calories, on the contrary, are cold foods [21,22]. ...
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ABSTRACT A better understanding of traditional medicine requires a more accurate comprehension of the philosophy and culture in which traditional medicine is rooted. From the perspective of traditional Chinese medicine, the effects of foods on human health are inseparable from temperament, mind, body, and environmental factors. The links between these components may not be explained clearly in modern medicine [1]. This article aims to review perspective of traditional and modern medicine on the nature of hot-cold food, to explain more clear the concepts of traditional medicine in this subject, subsequently to promote its global applicability. traditional medicine, four temperaments, nature of foods, hot & cold
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Saffron (Crocus sativus L.) belongs to the Iridaceae family. The stigma of saffron has been widely used as spice, medicinal plant, and food additive in the Mediterranean and Subtropical countries. Recently, attention has been paid to the identification of new sources of safe natural antioxidants for the food industry. The antioxidant activities of spices are mainly attributed to their phenolic and flavonoid compounds. Saffron is one of the spices believed to possess antioxidant properties, but information on its antioxidant activity and phenolic, flavonoids compound are rather limited, therefore this research was carried out to evaluate the antioxidant activity of saffron stigmas extracted with different solvents. The phenolic and flavonoid compounds of saffron were also examined using reversed phase (RP)-HPLC. Results showed that saffron stigma possess antioxidant activity. The free radical scavenging and ferric reducing power activities were higher for the methanolic extract of saffron stigma at a concentration of 300 μg/mL, with values of 68.2% and 78.9%, respectively, as compared to the corresponding boiling water and ethanolic extracts, but the activities were lower than those of antioxidant standards such as BHT and α-tocopherol. The obtained total phenolics value for methanolic saffron extract was 6.54 ± 0.02 mg gallic acid equivalent (GAE)/g dry weight (DW), and for total flavonoids, 5.88 ± 0.12 mg rutin equivalent/g DW, which were also higher than values obtained from the ethanolic and boiling water extracts. In addition, the RP-HPLC analyses indicated the presence of gallic acid and pyrogallol as two bioactive compounds. In summary, saffron stigmas showed antioxidant activity and methanol appeared to be the best solvent to extract the active components, among which the presence of gallic acid and pyrogallol might contribute towards the stigma's antioxidant properties. Hence, saffron stigma could be applied as a natural antioxidant source for industrial purposes.
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It is a common sense that chewing a mint leaf causes a cold feeling, while masticating a piece of ginger root is associated with a hot sensation. The Traditional Chinese Medicine has termed this phenomenon as cold and hot properties of herbs and applied them in treating certain human diseases successfully for thousands of years. Here, we have developed an Animal Thermotropism Behavior Surveillance System, and by using this device and other approaches, we not only verified the existence of, but also characterized and quantitated the cold and hot properties of medicinal herbs in animal behavioral experiments. The results suggested that the hot and cold properties of herbal drugs indeed correlated with the alteration of animal behavior in search for residence temperature.
Study on statistical pattern recognition model for relationship between cold-heat natures and Lipid based on GC-MS of 6 traditional Chinese medicine
  • Wang
The hypothesis of "four elements theory" of traditional Chinese medicine and its three elements theory
  • Ouyang
Cheminformatics study on molecular mechanism of cold/hot nature in TCM
  • Sun
Application of support vector machine in the study of the relationship between inorganic elements and properties of traditional Chinese Medicine
  • Liu