Diversity assessment device, diversity assessment method, and diversity assessment program

Abstract

The objective is to provide a diversity assessment device, a diversity assessment method, and a diversity assessment program that can assess food diversity while considering nutrient diversity by evaluating the diversity of ingested foods based on clusters that classify foods. [Solution] Based on food component data, a food classification is set by classifying the target specified foods according to nutrients using a clustering method, data on the intake status of specified foods included in a meal classified according to the food classification is obtained, and a dietary diversity score is calculated for the specified food intake status data.

Description

Technical Field

[0001] The present invention relates to a diversity evaluation device, a diversity evaluation method, and a diversity evaluation program.

Background Art

[0002] Patent Documents 1-7 disclose techniques for classifying foods according to nutrients.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Patent Document 3

Patent Document 4

Patent Document 5

Patent Document 6

Patent Document 7

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the conventional inventions, there has been a problem that the existing classification does not sufficiently consider nutrients and is not suitable for evaluating the diversity of nutrients to be ingested.

[0005] The present invention has been made in view of the above-mentioned problems, and aims to provide a diversity evaluation device, a diversity evaluation method, and a diversity evaluation program that can evaluate the diversity of foods that are consumed, taking into account the diversity of nutrients, by evaluating the diversity of foods consumed based on clusters that classify foods. [Means for solving the problem]

[0006] To solve the above-mentioned problems and achieve the objective, a diversity evaluation device comprising a memory unit and a control unit is provided, wherein the memory unit comprises a diversity evaluation memory means for storing food component data in which the nutrients of each food are set, and the control unit comprises a setting means for setting a food classification by classifying a predetermined target food according to the nutrients based on the food component data using a clustering method, an acquisition means for acquiring predetermined food intake status data by classifying the predetermined target food contained in a meal according to the food classification, and a calculation means for calculating a dietary diversity score based on the predetermined food intake status data.

[0007] Furthermore, in the diversity evaluation device according to the present invention, the target predetermined food is characterized in that it is a predetermined food whose frequency of appearance on the dinner table is equal to or greater than a standard value.

[0008] Furthermore, in the diversity evaluation device according to the present invention, the predetermined food is characterized in that it is a vegetable.

[0009] Furthermore, in the diversity evaluation device according to the present invention, the calculation means is characterized in that it calculates the dietary diversity score using a scoring method with respect to the predetermined food intake status data.

[0010] Furthermore, in the diversity evaluation device according to the present invention, the calculation means is characterized in that it calculates the dietary diversity score using the scoring method with respect to the frequency of the food classification set in the predetermined food intake status data.

[0011] Furthermore, in the diversity evaluation device according to the present invention, the scoring method is characterized by being either Foodgroup-based indicators or Dietaryguidelines-based indicators.

[0012] Furthermore, in the diversity evaluation device according to the present invention, the scoring method is characterized by being FVS, DDS, DVS, QUANTIDD, Berryindex, or healthyfooddiversity.

[0013] Furthermore, in the diversity evaluation device according to the present invention, the food classification is characterized in that it includes at least one of the following: classification by differences in the color of the food, classification by differences in the form of the food, and classification by differences in the aroma of the food.

[0014] Furthermore, in the diversity evaluation device according to the present invention, the food classification is characterized by including at least one of the following: dark green vegetables, dark red or yellow vegetables, light green vegetables, light yellow or white vegetables, light brown vegetables, legumes including bean vegetables, and spice vegetables.

[0015] Furthermore, in the diversity evaluation device according to the present invention, the meal is characterized in that it is a user's meal, a meal corresponding to an arbitrary recipe, or a packaged meal.

[0016] Furthermore, in the diversity evaluation device according to the present invention, the acquisition means is characterized in that it acquires data on the intake status of predetermined foods, which are classified according to the food classification, in which predetermined foods included in the user's meals for one meal, one day, seven days, two weeks, or one month.

[0017] Furthermore, in the diversity evaluation device according to the present invention, the acquisition means is characterized in that it acquires the user's meal data and, based on the meal data, acquires predetermined food intake status data, which classifies the predetermined target food contained in the user's meal according to the food classification.

[0018] Further, in the diversity evaluation device according to the present invention, the acquisition means is characterized by acquiring, as the predetermined food intake situation data, a check result of the food classification check tool by the user.

[0019] Further, in the diversity evaluation device according to the present invention, the clustering method is characterized by including at least one of cluster analysis, principal component analysis, and factor analysis.

[0020] Further, in the diversity evaluation device according to the present invention, the control unit further includes evaluation output means for outputting at least one of recipe proposal data, vegetable recommendation data, product recommendation data, service recommendation data, and seasoning recommendation data for the user based on the diet diversity score.

[0021] Further, in the diversity evaluation device according to the present invention, the frequency of appearance at the dinner table is the number of appearances per 100 dinner tables, 500 dinner tables, 1000 dinner tables or 10000 dinner tables, or per 100 households, 500 households, 1000 households or 10000 households.

[0022] Further, the diversity evaluation method according to the present invention is a diversity evaluation method for causing a diversity evaluation device including a storage unit and a control unit to execute. The storage unit includes diversity evaluation storage means for storing food component data in which nutrients of each food are set. The setting step of setting a food classification in which a predetermined food to be targeted is classified according to the nutrients by a clustering method based on the food component data, which is executed in the control unit; an acquisition step of acquiring predetermined food intake situation data in which the predetermined food included in the meal is classified according to the food classification; and a calculation step of calculating a diet diversity score for the predetermined food intake situation data.

[0023] In addition, the diversity evaluation method according to the present invention is characterized in that a food classification is set by classifying a predetermined food to be targeted according to the nutrients by a clustering method based on food component data in which nutrients of each food are set.

[0024] Further, the diversity evaluation program according to the present invention is a diversity evaluation program for causing a diversity evaluation device including a storage unit and a control unit to execute. The storage unit includes diversity evaluation storage means for storing food component data in which nutrients of each food are set. In the control unit, a setting step of setting a food classification obtained by classifying a predetermined food to be targeted according to the nutrients by a clustering method based on the food component data, an acquisition step of acquiring predetermined food intake situation data obtained by classifying the predetermined food to be targeted included in a meal according to the food classification, and a calculation step of calculating a diet diversity score for the predetermined food intake situation data are executed.

[0025] Further, the diversity evaluation program according to the present invention is a diversity evaluation program for causing a diversity evaluation device including a control unit to execute. In the control unit, a setting step of setting a food classification obtained by classifying a predetermined food to be targeted according to the nutrients by a clustering method based on food component data in which nutrients of each food are set is executed.

Effects of the Invention

[0026] According to this invention, it is possible to roughly classify vegetables by color based on the nutrient trends contained in 48 types of vegetables that frequently appear on the dinner table. Furthermore, according to this invention, by using cluster analysis, it is possible to group similar data from individual data. Furthermore, according to this invention, by using hierarchical cluster analysis, it is possible to achieve vegetable classification based on nutritional evidence. Furthermore, according to this invention, by using principal component analysis, it is possible to classify vegetables by aggregating data with many variables to create principal components (for example, by extracting the main features of vegetable nutrient data) and then performing cluster analysis. Furthermore, according to this invention, by using factor analysis, it is possible to classify vegetables based on common factors by aggregating observed variables (nutrient data) into a small number of latent variables (factors). Furthermore, according to this invention, by being able to evaluate vegetable diversity, it is possible to contribute to the further health of consumers. [Brief explanation of the drawing]

[0027] [Figure 1] Figure 1 is a block diagram showing an example of the configuration of the diversity evaluation device in this embodiment. [Figure 2] Figure 2 is a flowchart showing an example of the diversity evaluation process in this embodiment. [Figure 3] Figure 3 shows an overview of the diversity evaluation process in this embodiment. [Figure 4] Figure 4 shows an example of vegetable classification in this embodiment. [Figure 5] Figure 5 shows an example of vegetable classification in this embodiment. [Figure 6] Figure 6 shows an example of vegetable classification in this embodiment. [Figure 7] Figure 7 shows an example of a vegetable classification check tool in this embodiment. [Figure 8] Figure 8 shows an example of a dietary diversity score in this embodiment. [Figure 9] Figure 9 shows an example of the scoring method in this embodiment. [Figure 10] Figure 10 shows an example of propensity score matching in this embodiment. [Figure 11] Figure 11 shows an example of basic statistics on vegetable quantity and diversity in this embodiment. [Modes for carrying out the invention]

[0028] Embodiments of the present invention will be described in detail with reference to the drawings. However, the present invention is not limited to these embodiments.

[0029] [1. Configuration of the diversity evaluation device 100] The diversity evaluation device 100 according to this embodiment can be configured by functionally or physically distributing and integrating units of any type (either standalone or system-type). In this embodiment, an example of the configuration of the diversity evaluation device 100 will be described with reference to Figure 1. Figure 1 is a block diagram showing an example of the configuration of the diversity evaluation device 100 in this embodiment.

[0030] In Figure 1, the diversity evaluation device 100 may be a personal computer or an information processing device such as a workstation. The diversity evaluation device 100 comprises a control unit 102, a storage unit 106, and an input / output unit 112, and each part of the diversity evaluation device 100 is connected to communicate via any communication path. The diversity evaluation device 100 is connected to other devices to communicate with each other via the network 300.

[0031] The input / output unit 112 may have the function of performing data input / output (I / O). Here, the input / output unit 112 may be, for example, a key input unit, a touch panel, a control pad (e.g., a touch pad and a game pad), a mouse, a keyboard, and a microphone. The input / output unit 112 may also be a display unit that displays (input / output) information such as application software (e.g., a display, monitor, and touch panel made of liquid crystal or organic EL). The input / output unit 112 may also be an audio output unit that outputs audio information as audio (e.g., a speaker). The input / output unit 112 may also be an image input unit that records images (still images and videos) captured by an image sensor such as a CCD image sensor or a CMOS image sensor as digital data (e.g., a camera). The input / output unit 112 may also be a fingerprint sensor, a camera usable for iris recognition or facial recognition (e.g., an infrared camera), and / or a biosensor such as a vein sensor.

[0032] The memory unit 106 stores various databases, tables, and / or files. The memory unit 106 also stores computer programs that work in cooperation with the OS (Operating System) to give instructions to the CPU (Central Processing Unit) to perform various processes. For example, RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), and / or SSD (Solid State Drive) can be used as the memory unit 106. The memory unit 106 may also store image data recorded by the input / output unit 112, data received via the network 300, and / or input data entered via the input / output unit 112. Functionally, the memory unit 106 includes a diversity evaluation database 106a.

[0033] The diversity assessment database 106a stores diversity assessment data related to the assessment of dietary diversity. Here, the diversity assessment database 106a may also store food component data that sets the nutrients of each food. Here, the food component data may be from the Standard Tables of Food Composition in Japan.

[0034] The control unit 102 is a CPU or the like that comprehensively controls the diversity evaluation device 100. The control unit 102 has an internal memory for storing control programs such as the OS, programs that define various processing procedures, required data, etc., and executes various information processing based on these stored programs. Functionally, the control unit 102 comprises a setting unit 102a, an acquisition unit 102b, a calculation unit 102c, and an evaluation output unit 102d.

[0035] The setting unit 102a sets the food classification. Here, the setting unit 102a may set the food classification by classifying the target predetermined foods according to their nutrients using a clustering method based on food component data in which the nutrients of each food are set. The predetermined foods may also be vegetables. Furthermore, the food classification may include at least one of the following: dark green vegetables, dark red or yellow vegetables, light green vegetables, light yellow or white vegetables, light brown vegetables, legumes including bean vegetables, and spice vegetables. Furthermore, the clustering method may include at least one of cluster analysis, principal component analysis, and factor analysis.

[0036] The acquisition unit 102b acquires data on the intake status of specified foods, classified according to their food classification. Here, the acquisition unit 102b may acquire data on the intake status of specified foods, classified according to their food classification, that are included in a meal. The specified foods may also be specified foods whose frequency of appearance on the table is above a standard value. The meal may be the user's meal, a meal corresponding to an arbitrary recipe, or a packaged meal. The acquisition unit 102b may also acquire data on the intake status of specified foods, classified according to their food classification, that are included in the user's meals for one meal, one day, seven days, two weeks, or one month.

[0037] Furthermore, the acquisition unit 102b may acquire the user's meal data and, based on said meal data, acquire predetermined food intake status data by classifying the target predetermined foods included in the user's meals according to food classification. Also, the acquisition unit 102b may acquire the results of the user's check against the food classification check tool as predetermined food intake status data. Furthermore, the table appearance frequency may be 100 tables, 500 tables, 1000 tables or 10000 tables, or the number of appearances per 100 households, 500 households, 1000 households or 10000 households.

[0038] The calculation unit 102c calculates a dietary diversity score. Here, the calculation unit 102c may calculate a dietary diversity score for predetermined food intake data. Alternatively, the calculation unit 102c may calculate a dietary diversity score for predetermined food intake data using a scoring method. Alternatively, the calculation unit 102c may calculate a dietary diversity score for the frequency of food classifications set in predetermined food intake data using a scoring method. The scoring method may be Food group-based indicators (FGIs), Dietary guidelines-based indicators (DGIs), or Other indicators (OIs). The scoring method may also be Food Variety Score (FVS), Dietary Diversity Score (DDS), Dietary Variety Score (DVS), Quantitative Index for Dietary Diversity (QUANTIDD), Berry index, or healthy food diversity.

[0039] The evaluation output unit 102d outputs data related to the evaluation of dietary diversity (display, audio output, or print output). Here, the evaluation output unit 102d may output at least one of the following to the user based on the dietary diversity score: recipe suggestion data, vegetable recommendation data, product recommendation data, service recommendation data, and seasoning recommendation data. The evaluation output unit 102d may also output the dietary diversity score.

[0040] [2. Diversity Assessment Process] An example of the diversity evaluation process according to this embodiment will be described with reference to Figures 2 to 11. Figure 2 is a flowchart showing an example of the diversity evaluation process in this embodiment.

[0041] As shown in Figure 2, the setting unit 102a sets a food classification by classifying vegetables according to their nutrients using a clustering method, based on food component data in which the nutrients of each food stored in the diversity evaluation database 106a (Step SA-1).

[0042] Then, the acquisition unit 102b acquires vegetable intake data, which classifies the vegetables included in the user's meals over seven days according to their food classification (step SA-2).

[0043] Then, the calculation unit 102c calculates a dietary diversity score using a scoring method based on the frequency of each food classification set in the vegetable intake data (step SA-3).

[0044] Then, the evaluation output unit 102d displays recipe suggestion data for the user on the input / output unit 112 based on the dietary diversity score (step SA-4), and terminates the process.

[0045] Now, with reference to Figure 3, an overview of the diversity evaluation process in this embodiment will be described. Figure 3 is a diagram showing an overview of the diversity evaluation process in this embodiment.

[0046] As shown in Figure 3, this embodiment proposes a system that uses consumer meal data as input and processes it with a recommendation algorithm to suggest recipes that promote dietary diversity. Furthermore, as shown in Figure 3, in this embodiment, the dietary diversity score may be calculated by taking into account the age, gender, family structure, cooking frequency, and preferences set in the user data.

[0047] Furthermore, an example of the development of a vegetable classification check tool in this embodiment will be described with reference to Figures 4 to 7. Figures 4 to 6 show an example of vegetable classification in this embodiment. Figure 7 shows an example of a vegetable classification check tool in this embodiment.

[0048] As shown in Figure 4, in this embodiment, based on data from the Standard Tables of Food Composition in Japan, 48 types of vegetables that appear at least once per 1000 meals were selected for analysis. Excluding biotin, iodine, celem, chromium, and molybdenum, which have many unmeasured values, and including water, an important source of nutrients for vegetables, 27 items listed in the Food Composition Table were used as variables, and hierarchical cluster analysis was performed to establish seven clusters (vegetable classifications). Here, as shown in Figure 5, in this embodiment, seven vegetable classifications were established based on the color, aroma, and form of the vegetables. Furthermore, as shown in Figure 6, it can be seen that the seven vegetable classifications have distinctive nutritional characteristics.

[0049] As shown in Figure 7, in this embodiment, a "7-vegetable classification check tool" is created based on the cluster analysis results, primarily classifying vegetables by color.

[0050] In this embodiment, using the check tool shown in Figure 7, consumers are asked to answer questions about the frequency of their intake of each vegetable group by marking the corresponding cell with a circle. For each vegetable group, 1 point is assigned if they ate it 2-3 days or more per week, and 0 points if they ate it a few times a month or less. Based on the total points for the seven vegetable groups, a dietary diversity score for one consumer is calculated. Specifically, in this embodiment, for each vegetable group, 1 point is assigned if an O is assigned to any of the following: "ate it almost every day," "ate it 4-5 days a week," or "ate it 2-3 days a week," and 0 points are assigned if an O is assigned to any of the following: "ate it a few times a month," "hardly ever ate it," or "don't know."

[0051] Now, with reference to Figure 8, an example of a dietary diversity score in this embodiment will be described. Figure 8 is a diagram showing an example of a dietary diversity score in this embodiment.

[0052] As shown in Figure 8, in this embodiment, the scores for "dark green vegetables," "dark red or yellow vegetables," "light green vegetables," "light yellow or white vegetables," "light brown vegetables," "bean vegetables," and "spice vegetables" (each assigned 0 or 1 point) are totaled, and a score distributed in the range of 0 to 7 points is calculated as the dietary diversity score.

[0053] Here, as shown in Figure 8, when a dietary diversity score was calculated using data from a web survey (men and women aged 20-70, N=10,000) obtained in March 2024, with a criterion of 1 point for eating "2-3 days a week" or more, the scores of the survey participants were distributed without being biased towards 0 or 7 points. Therefore, it was confirmed that in this embodiment, by setting the criterion for eating frequency to "2-3 days a week," it is possible to calculate a score suitable for evaluating the dietary diversity (diversity of vegetables consumed) of the participants.

[0054] Furthermore, an example of the scoring method in this embodiment will be described with reference to Figure 9. Figure 9 is a diagram showing an example of the scoring method in this embodiment.

[0055] As shown in Figure 9, in this embodiment, various methods can be used to evaluate dietary diversity. For evaluating vegetable diversity by vegetable group, FGIs (e.g., DVS or DDS) or DGIs (e.g., healthy food diversity) can be used (scores are calculated based on the number of vegetable groups consumed at a specified frequency or higher). When evaluating vegetable diversity that takes into account not only vegetable groups but also the intake of each vegetable group, OIs (e.g., QUANTIDD or Berry index) can be used.

[0056] Furthermore, the background of this embodiment will be explained with reference to Figures 10 and 11. Figure 10 is a diagram showing an example of propensity score matching in this embodiment. Figure 11 is a diagram showing an example of basic statistics for vegetable quantity and diversity in this embodiment.

[0057] In recent years, several reports have shown a correlation between not only the quantity of vegetables consumed, but also vegetable diversity and the risk of lifestyle-related diseases. Furthermore, as shown in Figure 10, in this embodiment, after adjusting for background factors between the two groups, a t-test was conducted between vegetable intake / vegetable diversity and subjective well-being, and it was confirmed that there is a correlation between vegetable intake / vegetable diversity and subjective well-being. Also, as shown in Figure 11, in this embodiment, when the subjective vegetable intake of users was evaluated, only 43% of users felt the need to eat vegetables, but felt that they were eating enough. When the vegetable diversity score of users was evaluated, it was confirmed that diversity could be determined by asking about the frequency of intake at least once every 2-3 days. Therefore, in this embodiment, we focused on vegetable diversity and developed a tool to evaluate the quality (diversity) of vegetables.

[0058] Thus, the tool in this embodiment can recommend vegetables, seasoning products, and meal recipes (menus). Furthermore, the tool in this embodiment can be used in conjunction with the applicant's tools (for example, "Eat Well" or "Nutritional Balance Evaluation Tool") to recommend a "well-balanced meal."

[0059] Furthermore, the tool in this embodiment can be used as a sales promotion tool to promote the product, can be used to promote improved nutritional literacy among consumers regarding vegetable intake, and can be used as a tool to monitor behavioral changes in consumers' vegetable intake.

[0060] [3. Other Embodiments] In addition to the embodiments described above, the present invention may be implemented in various different embodiments within the scope of the technical idea described in the claims.

[0061] For example, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods.

[0062] Furthermore, the processing procedures, control procedures, specific names, information including parameters such as registration data and search conditions for each process, screen examples, and database configuration shown in this specification and in the drawings may be changed at will unless otherwise specified.

[0063] Furthermore, with respect to the diversity evaluation device 100, etc., each component shown in the illustration is a functional concept and does not necessarily need to be physically configured as shown.

[0064] For example, the processing functions of the diversity evaluation device 100, particularly those performed in the control unit, may be implemented in whole or in part by a CPU and a program interpreted and executed by the CPU, or they may be implemented as wired logic hardware. The program is recorded on a non-temporary computer-readable recording medium containing programmed instructions for the information processing device to execute the processing described in this embodiment, and is read mechanically as needed. That is, a storage unit such as ROM or HDD (Hard Disk Drive) contains a computer program that works in cooperation with the OS to give instructions to the CPU and perform various processing tasks. This computer program is executed by being loaded into RAM and works in cooperation with the CPU to constitute the control unit.

[0065] Furthermore, this computer program may be stored on an application program server connected to the diversity evaluation device 100, etc., via any network 300, and it is possible to download all or part of it as needed.

[0066] Furthermore, the program for executing the processing described in this embodiment may be stored on a non-temporary computer-readable recording medium, or it may be configured as a program product. Here, "recording medium" includes any "portable physical medium" such as memory cards, USB (Universal Serial Bus) memory, SD (Secure Digital) cards, flexible disks, magneto-optical disks, ROMs, EPROMs (Erasable Programmable Read Only Memory), EEPROMs (Registered Trademark) (Electrically Erasable and Programmable Read Only Memory), CD-ROMs (Compact Disk Read Only Memory), MOs (Magneto-Optical disks), DVDs (Digital Versatile Disks), and Blu-ray (Registered Trademark) Discs.

[0067] Furthermore, "program" refers to a data processing method described in any language or writing method, regardless of its format, such as source code or binary code. Note that "program" is not necessarily limited to a single, monolithic structure; it also includes distributed structures consisting of multiple modules or libraries, and those that work in cooperation with other programs, such as an operating system, to achieve their functions. Regarding the specific configuration and reading procedures for reading the recording medium in each device shown in this embodiment, as well as the installation procedures after reading, well-known configurations and procedures can be used.

[0068] The various databases stored in the memory unit are memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and optical disks, and store various programs, tables, databases, and web page files used for various processes and website provision.

[0069] Furthermore, the diversity evaluation device 100 may be configured as a known personal computer or workstation or other information processing device, or as an information processing device to which any peripheral devices are connected. Alternatively, the diversity evaluation device 100 may be implemented by installing software (including programs or data, etc.) that enables the processing described in this embodiment onto the device.

[0070] Furthermore, the specific forms of distribution and integration of the devices are not limited to those shown in the figures, and all or part of them can be configured by functionally or physically distributing and integrating them in any unit according to various additions or functional loads. In other words, the embodiments described above may be implemented in any combination, or the embodiments may be implemented selectively. [Industrial applicability]

[0071] This invention is useful in various industries, including the food industry and the information processing industry. [Explanation of Symbols]

[0072] 100 Diversity Evaluation Device 102 Control Unit 102a Settings section 102b Acquisition Department 102c Calculation Unit 102d Evaluation Output Unit 106 Storage section 106a Diversity Assessment Database 112 Input / output section 300 Networks

Claims

1. A diversity evaluation device comprising a memory unit and a control unit, The aforementioned storage unit is A diversity evaluation storage means that stores food component data with defined nutrients for each food item. Equipped with, The control unit, A setting means for setting a food classification by classifying a predetermined food according to the nutrients using a clustering method based on the aforementioned food component data, An acquisition means for acquiring data on the intake status of specified foods, which are classified according to the food classification, and the specified foods included in a meal. A calculation means for calculating a dietary diversity score for the aforementioned predetermined food intake data, A diversity evaluation device characterized by being equipped with the following features.

2. The specified food items covered above are: The diversity evaluation device according to claim 1, characterized in that the specified food item has a frequency of appearance on the dinner table that is equal to or greater than a standard value.

3. The aforementioned specified food is The diversity evaluation device according to claim 1 or 2, characterized in that it is a vegetable.

4. The calculation means is The diversity evaluation device according to claim 1 or 2, characterized in that it calculates the dietary diversity score using a scoring method for the predetermined food intake data.

5. The calculation means is The diversity evaluation device according to claim 4, characterized in that it calculates the dietary diversity score using the scoring method for the frequency of the food classification set in the predetermined food intake data.

6. The aforementioned scoring method is, The diversity evaluation device according to claim 4, characterized in that it is a food group-based indicator or a dietary guidelines-based indicator.

7. The aforementioned scoring method is, The diversity evaluation device according to claim 4, characterized in that it is FVS, DDS, DVS, QUANTIDD, Berry index, or healthy food diversity.

8. The aforementioned food classification is, The diversity evaluation device according to claim 3, characterized in that it includes at least one of the following: classification by differences in the color of the food, classification by differences in the form of the food, and classification by differences in the aroma of the food.

9. The aforementioned food classification is, The diversity evaluation device according to claim 8, characterized in that it includes at least one of the following: dark green vegetables, dark red or yellow vegetables, light green vegetables, light yellow or white vegetables, light brown vegetables, legumes including bean vegetables, and spice vegetables.

10. The aforementioned meal was The diversity evaluation device according to claim 1 or 2, characterized in that it is a user's meal, a meal corresponding to an arbitrary recipe, or a commercially packaged meal.

11. The acquisition means is, The diversity evaluation device according to claim 10, characterized in that it acquires data on the intake status of predetermined foods, which are classified according to the food classification, in which the predetermined foods included in the meals of the user for one meal, one day, seven days, two weeks, or one month are included in the predetermined foods.

12. The acquisition means is, The diversity evaluation device according to claim 1 or 2, characterized in that it acquires user meal data and, based on said meal data, acquires data on the intake status of said predetermined foods, which are classified according to the food classification of the predetermined foods to be targeted in said meals of said user.

13. The acquisition means is, The diversity evaluation device according to claim 1 or 2, characterized in that it acquires the results of a user's check against a food classification check tool as predetermined food intake status data.

14. The aforementioned clustering method is The diversity evaluation device according to claim 1 or 2, characterized by including at least one of cluster analysis, principal component analysis, and factor analysis.

15. The control unit, An evaluation output means that outputs at least one of the following to the user based on the dietary diversity score: recipe suggestion data, vegetable recommendation data, product recommendation data, service recommendation data, and seasoning recommendation data. The diversity evaluation device according to claim 1 or 2, further comprising the above.

16. The frequency of appearance at the aforementioned dinner table is, The diversity evaluation device according to claim 2, characterized in that the number of occurrences is per 100 dining tables, 500 dining tables, 1,000 dining tables, or 10,000 dining tables, or per 100 households, 500 households, 1,000 households, or 10,000 households.

17. A diversity evaluation method to be performed by a diversity evaluation device comprising a memory unit and a control unit, The aforementioned storage unit is A diversity evaluation storage means that stores food component data with defined nutrients for each food item. Equipped with, The control unit is executed as follows: A setting step of setting a food classification by classifying the target food according to the nutrients using a clustering method based on the aforementioned food component data, A step of acquiring data on the intake status of specified foods, which are classified according to the food classification, and the specified foods included in the meal. A calculation step for calculating a dietary diversity score for the aforementioned predetermined food intake data, A diversity evaluation method characterized by including the following.

18. A method for evaluating diversity, characterized by setting a food classification by classifying a predetermined food according to its nutrients using a clustering method, based on food component data that sets the nutrients of each food.

19. A diversity evaluation program to be executed by a diversity evaluation device comprising a memory unit and a control unit, The aforementioned storage unit is A diversity evaluation storage means that stores food component data with defined nutrients for each food item. Equipped with, In the control unit, A setting step of setting a food classification by classifying the target food according to the nutrients using a clustering method based on the aforementioned food component data, A step of acquiring data on the intake status of specified foods, which are classified according to the food classification, and the specified foods included in the meal. A calculation step for calculating a dietary diversity score for the aforementioned predetermined food intake data, A diversity assessment program to enable implementation.

20. A diversity evaluation program to be executed by a diversity evaluation device equipped with a control unit, In the control unit, Setting step: Based on food component data in which the nutrients of each food are set, a clustering method is used to set a food classification that classifies the target specified food according to the said nutrients. A diversity assessment program to enable implementation.

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