Food evaluation method regarding cognitive functions

Abstract

To provide an evaluation method which enables provision of information regarding, for example, whether food under evaluation is related to cognitive functions.SOLUTION: An evaluation method according to an embodiment involves evaluating food from the point of view of cognitive functions using a value(s) of the amount(s) of at least one amino acid selected from Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Arg, Ala, Asp, Glu, Gly, Pro, Ser, SAA, AAA, and BCAA in food, or a value(s) of an expression derived using the value(s) of the amount(s) and the expression including a variable(s) to be assigned with the value(s) of the amount(s).SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an evaluation method, a calculation method, a prevention method, an evaluation device, a calculation device, a prevention device, an evaluation program, a calculation program, a prevention program, a recording medium, an evaluation system, a prevention system, and a terminal device. [Background technology]

[0002] As the aging of society accelerates, the number of dementia patients is expected to increase. It is estimated that the number of dementia patients will exceed 10 million by 2050. Once dementia develops, recovery from symptoms such as the decline in cognitive function, known as the core symptom, is not expected. For this reason, prevention before the onset of dementia is extremely important. Furthermore, research into Alzheimer's disease (AD) is revealing that changes in the brain begin more than 20 years before the onset of AD. This research shows the importance of prevention at younger ages.

[0003] Risk factors related to the onset of dementia include genetic background such as the ApoE4 gene and lifestyle-related diseases such as diabetes and hypertension. Furthermore, lifestyle habits such as smoking, social participation, decreased frequency of going out, and dietary content are also said to be related to the onset of dementia. In particular, regarding the relationship between dietary content and the onset of dementia or cognitive function, there are reports that a high protein intake reduces the risk of mild cognitive impairment, which is a precursor to dementia (Non-Patent Document 1) and that the protein intake and cognitive function of elderly people show a positive correlation (Non-Patent Document 2). Therefore, protein intake is considered to be an important factor related to the onset of dementia or cognitive function. Furthermore, the effects of dietary melatonin and tryptophan intake on improving cognitive function have been examined (Non-Patent Document 3). In addition, there are reports that lysine intake improves cognitive function in healthy people (Patent Document 1), reports suggesting the effect of L-arginine or lysine intake on the improvement of AD or anxiety-like symptoms (Non-Patent Documents 4-7), and reports suggesting the improvement of tyrosine intake on the improvement of working memory decline and cognitive decline (Non-Patent Document 8). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] European Patent No. 2367547(A1) [Non-patent literature]

[0005] [Non-Patent Document 1] J. Alzheimers Dis. 32(2) 329-339(2012) [Non-Patent Document 2] Am. J. Clin. Nutr. 65(1) 20-29(1997) [Non-Patent Document 3] Anglo Food Industry Hi-Tech 22 (4) 23-24 (2011) [Non-Patent Document 4] The American Journal of Medicine 108 (5) 439 (2000 Apr 1) [Non-Patent Document 5] Neuropsychiatric Disease and Treatment 6 707-710 (2010) [Non-Patent Document 6] Biomedical Research 28 (2) 85-90 (2007) [Non-Patent Document 7] J. Nutr. 132 (12) 3744-3746 (2002) [Non-Patent Document 8] Amino Acids 45 (5) 1035-1045 (2013) Summary of the Invention [Problem to be solved by the invention]

[0006] However, some of the above reports do not have sufficient preventive or improving effects on cognitive decline, and some require verification of their effectiveness. Therefore, it is difficult to say that any component that has sufficient preventive or improving effects on cognitive decline, is highly safe, and can be taken continuously has been found. Furthermore, the relationship between amino acid intake from food and cognitive function has not yet been clarified.

[0007] The present invention aims to provide an evaluation method, calculation method, evaluation device, calculation device, evaluation program, calculation program, recording medium, evaluation system, and terminal device that can provide information on whether the food to be evaluated is related to cognitive function, for example, a method for preventing cognitive decline, a prevention device, prevention program, recording medium, prevention system, and terminal device that can provide information for preventing cognitive decline, and an evaluation method, calculation method, evaluation device, calculation device, evaluation program, calculation program, recording medium, evaluation system, and terminal device that can provide reliable information that can be useful in knowing the state of cognitive function. [Means for solving the problem]

[0008] The present inventors have conducted intensive research to solve the above problems, and have found a correlation between clinical evaluation indices for cognitive function and information on amino acids in food, thereby completing the present invention.

[0009] In order to solve the above-mentioned problems and achieve the object, the evaluation method of the present invention is characterized by including an evaluation step of evaluating the food from the perspective of cognitive function using the amount value of at least one amino acid selected from 21 types of amino acids (Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Arg, Ala, Asp, Glu, Gly, Pro, Ser, SAA, AAA and BCAA) in a food, or the value of the formula calculated using a formula including variables into which the value of the amount is substituted and the value of the amount.

[0010] In this specification, various amino acids are mainly represented by abbreviations, but their formal names are as follows: (Abbreviation) (Formal name) AAA Aromatic amino acids (Tyrosine and Phenylalanine) Ala Alanine Arg Arginine Asparagine Asp Aspartic acid and Asparagine BCAA Branched-chain amino acids (Isoleucine, Leucine and Valine) Cys Cystine Gln Glutamine Glu Glutamic acid and Glutamine Gly Glycine His Histidine Isoleucine Leu Leucine Lysine Methionine Phe Phenylalanine Proline SAA Sulfur-containing amino acids (Methionine and Cystine) Ser Serine Thr Threonine Trp Tryptophan Tyr Tyrosine Val Valine

[0011] Furthermore, the evaluation method of the present invention is characterized in that in the evaluation step, the value of the amount of at least one amino acid selected from Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Ala, Asp, Pro, Ser, SAA, AAA and BCAA in the food, or the value of the formula calculated using a formula including variables into which the value of the amount is substituted and the value of the amount, is used.

[0012] Furthermore, the evaluation method of the present invention is characterized in that in the evaluation step, the value of the amount of at least one amino acid selected from Ile, Leu, Tyr, Trp, Val, Ser, AAA and BCAA in the food is used, or the value of the formula calculated using a formula including variables into which the value of the amount is substituted and the value of the amount.

[0013] Furthermore, the evaluation method of the present invention is characterized in that in the evaluation step, the value of the amount of at least one amino acid selected from Lys, Phe, Thr and Ala in the food is used, or the value of the formula calculated using a formula including variables into which the value of the amount is substituted and the value of the amount.

[0014] The evaluation method according to the present invention is further characterized in that the food corresponds to breakfast, lunch or dinner.

[0015] In the evaluation method according to the present invention, the evaluation step is executed in a control unit of an information processing device including a control unit.

[0016] The calculation method of the present invention is also characterized by including a calculation step of calculating the value of a formula for evaluating the food from the perspective of cognitive function, the formula including an amount value of at least one amino acid among the 21 types of amino acids in a food and a variable into which the amount value is substituted.

[0017] In the calculation method according to the present invention, the calculation step is executed in a control unit of an information processing device including a control unit.

[0018] Furthermore, the evaluation device of the present invention is characterized in that it is an evaluation device equipped with a control unit, and the control unit is equipped with evaluation means for evaluating the food from the perspective of cognitive function using a value of the amount of at least one amino acid among the 21 types of amino acids in a food, or a value of the formula calculated using a formula including a variable into which the value of the amount is substituted and the value of the amount.

[0019] In addition, the evaluation device of the present invention is communicatively connected to a terminal device via a network, and the control unit further comprises a data receiving means for receiving information for calculating the value of the amount, the value of the amount calculated using the information, or the value of the formula calculated using the information, and a result sending means for sending the result obtained by the evaluation means to the terminal device, and the evaluation means is characterized in that (1) when the information is received by the data receiving means, it executes a process of calculating the value of the amount using the received information, or a process of calculating the value of the amount using the received information and calculating the value of the formula using the calculated value of the amount and the formula, and evaluates the food from the perspective of cognitive function using the value of the amount or the value of the formula obtained by the process, and (2) when the value of the amount or the value of the formula is received by the data receiving means, it evaluates the food from the perspective of cognitive function using the received value of the amount or the value of the formula.

[0020] Furthermore, the calculation device according to the present invention is characterized in that it is a calculation device comprising a control unit, and the control unit comprises a calculation means for calculating a value of a formula for evaluating the food from the viewpoint of cognitive function, the formula including an amount value of at least one amino acid among the 21 types of amino acids in a food and a variable into which the amount value is substituted.

[0021] In addition, the evaluation program of the present invention is an evaluation program to be executed in an information processing device equipped with a control unit, and is characterized in that it includes an evaluation step, to be executed in the control unit, of evaluating the food from the perspective of cognitive function using the amount value of at least one amino acid among the 21 types of amino acids in a food, or an equation including a variable into which the value of the amount is substituted, and the value of the equation calculated using the value of the amount.

[0022] Furthermore, the calculation program of the present invention is a calculation program to be executed in an information processing device having a control unit, and is characterized in that it includes a calculation step of calculating a value of a formula for evaluating the food from the perspective of cognitive function, the formula including an amount value of at least one amino acid among the 21 types of amino acids in a food and a variable into which the amount value is substituted, to be executed in the control unit.

[0023] The recording medium according to the present invention is a computer-readable recording medium having the evaluation program or the calculation program recorded therein. Specifically, the recording medium according to the present invention is a non-transitory computer-readable recording medium, and is characterized in that it contains programmed instructions for causing an information processing device to execute the evaluation method or the calculation method.

[0024] Further, an evaluation system according to the present invention is an evaluation system configured by connecting an evaluation device equipped with a control unit and a terminal device equipped with a control unit via a network so as to be able to communicate with each other, wherein the control unit of the terminal device comprises result receiving means for receiving a result of evaluation of a food from the viewpoint of cognitive function transmitted from the evaluation device, and the control unit of the evaluation device comprises data receiving means for receiving information for calculating an amount value of at least one amino acid among the 21 types of amino acids in the food, the value of the amount calculated using the information, or the value of the formula calculated using an equation including a variable into which the value of the amount is substituted and the value of the amount; The food processing device is characterized in that it comprises: (1) an evaluation means, when the information is received, for calculating the value of the amount using the received information, or a process for calculating the value of the amount using the received information and calculating the value of the formula using the calculated value of the amount and the formula, and evaluating the food from the perspective of cognitive function using the value of the amount or the value of the formula obtained by the process; (2) an evaluation means, when the value of the amount or the value of the formula is received by the data receiving means, for evaluating the food from the perspective of cognitive function using the received value of the amount or the value of the formula; and a result transmission means for transmitting the result obtained by the evaluation means to the terminal device.

[0025] Furthermore, a terminal device according to the present invention is a terminal device equipped with a control unit, the control unit being equipped with a result acquisition means for acquiring a result of evaluating a food from the perspective of cognitive function, the result being a result of evaluating the food from the perspective of cognitive function using a value of the amount of at least one amino acid among the 21 types of amino acids in the food, or a value of the formula calculated using an equation including a variable into which the value of the amount is substituted and the value of the amount.

[0026] Moreover, the terminal device according to the present invention is communicatively connected to an evaluation device that performs the evaluation via a network, and the result acquisition means receives the results transmitted from the evaluation device.

[0027] Furthermore, the method for preventing cognitive decline according to the present invention is characterized by including a calculation step of calculating the amount of at least one of the amino acids Lys, Phe, Thr and Ala in a food from information related to the food associated with a user; a determination step of determining whether each value calculated in the calculation step reaches a threshold value; a search step of searching for information on foods that contain a large amount of amino acids corresponding to values ​​determined in the determination step to not reach the threshold value; and a provision step of providing the information on foods searched for in the search step to the user as information for preventing cognitive decline.

[0028] Furthermore, the method for preventing cognitive decline according to the present invention is characterized in that the calculation step, the determination step, the search step and the provision step are executed in a control unit of an information processing device equipped with a control unit.

[0029] Furthermore, the preventive device of the present invention is a preventive device equipped with a control unit, and the control unit is characterized in that it comprises: a calculation means for calculating the amount of at least one of the amino acids Lys, Phe, Thr and Ala in a food based on information about the food linked to a user; a determination means for determining whether each value calculated by the calculation means reaches a threshold value; a search means for searching for information about foods that contain a large amount of amino acids corresponding to values ​​determined by the determination means to not reach the threshold value; and a provision means for providing the information about foods searched for by the search means to the user as information for preventing cognitive decline.

[0030] In addition, the prevention device of the present invention is communicatively connected to a terminal device via a network, the control unit further includes a data receiving means for receiving information regarding food associated with the user, and the providing means transmits the information regarding the food to the terminal device.

[0031] In addition, the preventive program of the present invention is a preventive program to be executed in an information processing device equipped with a control unit, and is characterized in that it includes a calculation step for calculating the amount of at least one of amino acids Lys, Phe, Thr and Ala in a food linked to a user from information about the food, the amount of the amino acid Lys, Phe, Thr and Ala in the food from information about the food linked to the user, a determination step for determining whether each value calculated in the calculation step reaches a threshold value, a search step for searching for information about foods that contain a large amount of amino acids corresponding to values ​​determined in the determination step to not reach the threshold value, and a provision step for providing the information about the food searched for in the search step to the user as information for preventing cognitive decline.

[0032] The recording medium according to the present invention is a computer-readable recording medium having the prevention program recorded therein. Specifically, the recording medium according to the present invention is a non-transitory computer-readable recording medium, and is characterized in that it includes programmed instructions for causing an information processing device to execute the prevention method.

[0033] Furthermore, the preventive system according to the present invention is a preventive system configured by connecting a preventive device having a control unit and a terminal device having a control unit via a network so as to be able to communicate with each other, wherein the control unit of the terminal device comprises a data receiving means for receiving information regarding food transmitted from the preventive device, and the control unit of the preventive device comprises: a data receiving means for receiving information regarding food associated with a user, a calculation means for calculating an amount of at least one amino acid selected from Lys, Phe, Thr and Ala in the food from the information regarding the food associated with the user received by the data receiving means, a determination means for determining whether each value calculated by the calculation means reaches a threshold value, a search means for searching for information regarding foods that contain a large amount of amino acids corresponding to values ​​determined by the determination means to not reach the threshold value, and a provision means for transmitting the information regarding foods searched for by the search means to the terminal device as information for preventing cognitive decline.

[0034] Furthermore, the terminal device of the present invention is characterized in that it is a terminal device equipped with a control unit, the control unit having a data acquisition means for acquiring information regarding food, and the information regarding food is searched information regarding foods that contain a large amount of amino acids corresponding to the amount of at least one of the amino acids Lys, Phe, Thr and Ala in the food calculated from information regarding the food linked to the user, the amount being determined to not reach a threshold value, and is provided as information for preventing cognitive decline.

[0035] In addition, the terminal device of the present invention is communicatively connected via a network to a prevention device that performs the calculation, the judgment, the search, and the provision, and the data acquisition means receives information regarding the food transmitted from the prevention device.

[0036] The evaluation method of the present invention is also characterized by including an evaluation step of evaluating the state of cognitive function of the subject using the amount value of at least one amino acid among the 21 types of amino acids in food ingested by the subject, or the value of the formula calculated using an equation including a variable into which the amount value is substituted and the amount value.

[0037] In the evaluation method according to the present invention, the evaluation step is executed in a control unit of an information processing device including a control unit.

[0038] In addition, the calculation method of the present invention is characterized by including a calculation step of calculating the value of an equation for evaluating the state of cognitive function, the equation including an amount value of at least one amino acid among the 21 types of amino acids in food ingested by the subject to be evaluated and a variable into which the amount value is substituted.

[0039] The calculation method according to the present invention is characterized in that it is executed by a control unit of an information processing device having a control unit.

[0040] Furthermore, the evaluation device of the present invention is characterized in that it is an evaluation device equipped with a control unit, and the control unit is equipped with an evaluation means for evaluating the state of cognitive function of the subject to be evaluated using a value of the amount of at least one amino acid among the 21 types of amino acids in food ingested by the subject to be evaluated, or a value of the formula calculated using an equation including a variable into which the value of the amount is substituted and the value of the amount.

[0041] In addition, the evaluation device of the present invention is communicatively connected to a terminal device via a network, and the control unit further comprises a data receiving means for receiving information about the food ingested by the subject to be evaluated (corresponding to an example of information for calculating the value of the amount), the value of the amount calculated using the information, or the value of the formula, and a result transmitting means for transmitting the result obtained by the evaluation means to the terminal device, and the evaluation means is characterized in that (1) when the information is received by the data receiving means, it executes a process of calculating the value of the amount using the received information, or a process of calculating the value of the amount using the received information and calculating the value of the formula using the calculated value of the amount and the formula, and evaluates the state of the cognitive function of the subject to be evaluated using the value of the amount or the value of the formula obtained by the process, and (2) when the data receiving means receives the value of the amount or the value of the formula, it evaluates the state of the cognitive function of the subject to be evaluated using the received value of the amount or the value of the formula.

[0042] Furthermore, the calculation device according to the present invention is characterized in that it is a calculation device equipped with a control unit, and the control unit is equipped with a calculation means for calculating the value of an equation for evaluating a state of cognitive function, the equation including an amount value of at least one amino acid among the 21 types of amino acids in food ingested by the subject to be evaluated and a variable into which the amount value is substituted.

[0043] Furthermore, the evaluation program of the present invention is an evaluation program to be executed in an information processing device having a control unit, and is characterized in that it includes an evaluation step, to be executed in the control unit, of evaluating the state of cognitive function of the subject to be evaluated using the amount value of at least one amino acid among the 21 types of amino acids in food ingested by the subject to be evaluated, or an equation including a variable into which the amount value is substituted, and the value of the equation calculated using the amount value.

[0044] Furthermore, the calculation program of the present invention is a calculation program to be executed in an information processing device having a control unit, and is characterized in that, to be executed in the control unit, it includes a calculation step of calculating the value of an equation for evaluating the state of cognitive function, the equation including an amount value of at least one amino acid among the 21 types of amino acids in food ingested by the subject to be evaluated, and a variable into which the amount value is substituted.

[0045] The recording medium according to the present invention is a computer-readable recording medium having the evaluation program or the calculation program recorded therein. Specifically, the recording medium according to the present invention is a non-transitory computer-readable recording medium, and is characterized in that it contains programmed instructions for causing an information processing device to execute the evaluation method or the calculation method.

[0046] Further, an evaluation system according to the present invention is an evaluation system configured by connecting an evaluation device having a control unit and a terminal device having a control unit via a network so as to be able to communicate with each other, wherein the control unit of the terminal device comprises a result receiving means for receiving an evaluation result of a state of cognitive function transmitted from the evaluation device, and the control unit of the evaluation device comprises a data receiving means for receiving information on a food ingested by an evaluation subject, a value of an amount of at least one amino acid among the 21 types of amino acids in the food calculated using the information, or a value of the formula calculated using an equation including a variable into which the value of the amount is substituted and the value of the amount; and and (2) when the data receiving means receives the value of the quantity or the value of the formula, executing a process of calculating the value of the quantity using the received information, or a process of calculating the value of the quantity using the received information and calculating the value of the formula using the calculated value of the quantity and the formula, and evaluating the state of the cognitive function of the subject to be evaluated using the value of the quantity or the value of the formula obtained in the process; and (3) when the data receiving means receives the value of the quantity or the value of the formula, evaluating the state of the cognitive function of the subject to be evaluated using the received value of the quantity or the value of the formula, and a result transmitting means transmitting the result obtained by the evaluation means to the terminal device.

[0047] Furthermore, a terminal device according to the present invention is a terminal device equipped with a control unit, the control unit having a result acquisition means for acquiring a result of evaluating the state of cognitive function, the result being a result of evaluating the state of cognitive function of the subject to be evaluated using a value of the amount of at least one amino acid among the 21 types of amino acids in food ingested by the subject to be evaluated, or a value of the formula calculated using an equation including a variable into which the value of the amount is substituted and the value of the amount.

[0048] Moreover, the terminal device according to the present invention is communicatively connected to an evaluation device that performs the evaluation via a network, and the result acquisition means receives the results transmitted from the evaluation device. Effect of the Invention

[0049] According to the present invention, for example, it is possible to provide information on whether the food to be evaluated is related to cognitive function. In addition, according to the present invention, it is possible to provide information for preventing cognitive function decline. In addition, according to the present invention, it is possible to provide highly reliable information that can be used as a reference for knowing the state of cognitive function. [Brief description of the drawings]

[0050] [Figure 1] FIG. 1 is a diagram showing the basic principle of the first embodiment. [Diagram 2] FIG. 2 is a diagram showing the basic principle of the second embodiment. [Diagram 3] FIG. 3 is a diagram showing an example of the overall configuration of the present system. [Figure 4] FIG. 4 is a diagram showing another example of the overall configuration of the present system. [Diagram 5] FIG. 5 is a block diagram showing an example of the configuration of the evaluation device 100 of this system. [Figure 6] FIG. 6 is a diagram showing an example of information stored in the amino acid-related data file 106a. [Figure 7] FIG. 7 is a diagram showing an example of information stored in the index state information file 106b. [Figure 8] FIG. 8 is a diagram showing an example of information stored in the designated index state information file 106c. [Figure 9] FIG. 9 is a diagram showing an example of information stored in the formula file 106d1. [Figure 10] FIG. 10 is a diagram showing an example of information stored in the evaluation result file 106e. [Figure 11] FIG. 11 is a block diagram showing the configuration of the evaluation unit 102d. [Figure 12] FIG. 12 is a block diagram showing an example of the configuration of a client device 200 of this system. [Figure 13] FIG. 13 is a block diagram showing an example of the configuration of the database device 500 of this system. [Figure 14] FIG. 14 is a diagram showing quantiles for each of a number of parameters (amino acid intake, etc.). [Figure 15] FIG. 15 is a diagram showing the relationship between the values ​​of each group of a plurality of parameters (such as amino acid intake) and the score of logical memory I (immediate recall) of each of the plurality of parameters (such as amino acid intake). [Figure 16] FIG. 16 is a diagram showing the relationship between the values ​​of each group of a plurality of parameters (such as amino acid intake) and the score of logical memory II (delayed recall) of each of the plurality of parameters (such as amino acid intake). [Figure 17] FIG. 17 shows the results of multiple regression analysis using WAIS-R (knowledge) 8 years later as the outcome. [Figure 18] FIG. 18 shows the results of multiple regression analysis using WAIS-R (knowledge) 8 years later as the outcome. [Figure 19] FIG. 19 shows the results of evaluation by AIC of a multivariate amino acid regression equation using multiple amino acids extracted by the stepwise method and a single variable amino acid regression equation using one amino acid. [Figure 20] FIG. 20 shows the results of evaluation by AIC of a multivariate amino acid regression equation using multiple amino acids extracted by the stepwise method and a single variable amino acid regression equation using one amino acid. [Figure 21] FIG. 21 shows the evaluation results by AIC for an amino acid two-variable regression equation using two types of amino acids composed of the amino acid used in the amino acid single-variable regression equation with the lowest AIC and the amino acid with the lowest correlation with the amino acid used in the amino acid single-variable regression equation with the lowest AIC, and an amino acid single-variable regression equation using one type of amino acid. [Figure 22] FIG. 22 shows the results of logistic regression evaluating the odds ratio of MMSE scores of 27 points or less 8 years later for two groups: a group whose daily amino acid intake corresponds to the T1 group and a group whose daily amino acid intake does not correspond to the T1 group. [Figure 23] FIG. 23 shows the ranges of daily intakes of amino acids for which the odds ratios were significant in FIG. 21 in the T1 group by sex. [Figure 24] FIG. 24 shows the possible ranges for maximum intakes for the first quintile of each amino acid. [Diagram 25] FIG. 25 shows the possible ranges for maximum intakes for the first quintile of each amino acid. [Figure 26] FIG. 26 is a diagram showing the range of required amounts of amino acids that can be estimated from dietary reference intakes. [Figure 27] FIG. 27 shows the possible ranges for maximum intakes for the first quintile of each amino acid. [Figure 28] FIG. 28 shows the possible ranges for maximum intakes for the first quintile of each amino acid. [Figure 29] FIG. 29 shows the results of covariance analysis between quartile groups of amino acid scores for breakfast, lunch, and dinner and logical memory II (delayed recall). [Diagram 30] FIG. 30 shows the estimated values ​​of logical memory II (delayed recall) scores by each model, divided into quartile groups of the lunch amino acid score. [Diagram 31] FIG. 31 shows the results of a comparison test in which the quartile groups of the amino acid scores for lunch were divided into two groups. [Diagram 32] FIG. 32 is a diagram showing quantiles in each quartile of the amino acid scores for lunch. [Diagram 33] FIG. 33 shows the possible range of maximum amino acid scores for each quantile of amino acid scores for each lunch. [Diagram 34] FIG. 34 shows the possible range of maximum amino acid scores for each quantile of amino acid scores for each lunch. [Diagram 35] FIG. 35 is a diagram showing the results of logistic regression evaluating the odds ratio of an MMSE score of 27 points or less after four tests for two groups, a group whose breakfast amino acid score corresponds to the T1 group and a group whose breakfast amino acid score does not correspond to the T1 group. [Diagram 36]FIG. 36 is a graph showing the ranges of amino acid scores for breakfast in which the odds ratios are significant in FIG. 35, by gender, in the T1 group. [Figure 37] FIG. 37 shows the possible range for the maximum first quartile of amino acid scores for breakfast. [Figure 38] FIG. 38 shows the possible range for the maximum first quartile of amino acid scores for breakfast. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0051] Hereinafter, an embodiment (first embodiment) of the evaluation method, calculation method, and prevention method according to the present invention, and an embodiment (second embodiment) of the evaluation device, calculation device, prevention device, evaluation method, calculation method, prevention method, evaluation program, calculation program, prevention program, recording medium, evaluation system, prevention system, and terminal device according to the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to these embodiments.

[0052] [First embodiment] [1-1. Overview of the first embodiment] Here, an overview of the first embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the basic principle of the first embodiment.

[0053] First, amino acid-related data on the amount of at least one of the 21 amino acids in food is obtained (step S11). In this specification, the term "food" includes meals (menus), ingredients, and compositions containing amino acids. Here, the term "meal" is not limited to a single meal (e.g., breakfast, lunch, or dinner), but may be a meal for a certain period (e.g., three days, one week, or one month), and may be a meal tendency, eating habit, or eating (dietary) pattern of a user (e.g., a group such as a family (family unit) or an individual such as a family member). In addition, it does not matter whether the meal was actually consumed by the user. In addition, the amount may include, for example, the content, intake amount, amino acid score, or amino acid score (sufficiency rate). Here, the amino acid score is an index for evaluating the content ratio of essential amino acids in food, and for example, the closer the value is to 100, the higher the quality of the protein contained in the food.Specifically, the concept of amino acid score includes: 1) the value of the lowest amino acid (first limiting amino acid) when comparing the ratio of essential amino acids in each food protein with the standard essential amino acid pattern (for example, the amino acid standard value proposed by FAO / WHO / UNU in 1985); 2) the Protein Digestibility Corrected Amino Acid Score (PDCAAS) corrected by the digestibility of the protein (see “Protein quality evaluation: report of the Joint FAO / WHO Expert Consultation, Bethesda, Md., USA 4-8 December 1989”, FAO food and nutrition paper; 51, Food and Agriculture Organization of the United Nations, 1991”); and 3) the Digestible Indispensable Amino Acid Score (DIAAS) corrected by the digestibility of each essential amino acid (digestibility up to the ileum) (see “Dietary protein quality evaluation in human nutrition: report of an FAO (See "FAO Food and Nutrition Paper, 92, Food and Agriculture Organization of the United Nations, 2013" (Food and Agriculture Organization of the United Nations, 2013)) and so on. Here, the amino acid score (sufficiency rate) refers to the ratio of each amino acid to the standard amino acid (for example, the amino acid standard value proposed by FAO / WHO / UNU in 1985).

[0054] The quantity value may be calculated from information about food, for example. The information about food may be, for example, 1) a photo of a meal or ingredients, 2) purchase data (e.g., POS (Point Of Sales) data, etc.) or electronic payment data about a meal or ingredients that make up a meal, 3) text information about the description of the meal (e.g., input using an electronic device such as a smartphone or tablet terminal), or 4) information about a dish selected by a user in a state where a screen including multiple options (e.g., "pork cutlet" and "shabu-shabu" classified into the option selected by the user in a screen including multiple options (e.g., "Japanese food", "Western food", "Chinese food", etc.) related to a genre of food is displayed on a monitor of an electronic device such as a smartphone or tablet terminal, the screen including multiple options (e.g., "Japanese food", "Western food", "Chinese food", etc.) related to a dish selected by a user (e.g., ingredients used in the dish and their amounts (e.g., weights, etc.), etc.). For example, when the information on food is a photograph of the meal (specifically, photographs of meals for several days), the amount value may be determined from the photograph of the meal based on a method such as the 3-day meal weighing method (Imai Tomoko et al., Effectiveness of Photographing in a 3-Day Meal Record Survey, Journal of the Japanese Society for Food and Nutrition, 2009, 20(3):203-210). Also, when the information on food is purchase data (such as data provided by a retailer's POS system), the amount of amino acids, etc. in the foodstuffs estimated on the assumption that the purchased food was consumed as a meal, or a value calculated by correcting this value, may be calculated, and the evaluation may be performed using the calculated value.

[0055] Next, the food is evaluated from the viewpoint of cognitive function using the amount value contained in the amino acid related data acquired in step S11 (step S12). Here, the cognitive function may be, for example, the cognitive function of the user at the time of ingestion of the food or the cognitive function of the user from the time of ingestion of the food. Evaluating the food from the viewpoint of cognitive function means, for example, evaluating whether the food to be evaluated is related to a person's cognitive function (specifically, whether the food to be evaluated has a possibility (risk) of lowering a person's cognitive function, etc.). In addition, when evaluating, for example, information such as the ratio or difference between the intake amounts of Lys, Phe, Thr, and Ala and the intake thresholds of Lys, Phe, Thr, and Ala shown in Example 6 may be used, and information on the minimum value or summary statistics (average value, etc.) of these four types of values ​​may also be used.

[0056] As described above, according to the first embodiment, it is possible to provide information as to whether or not the food to be evaluated is related to cognitive function, for example.

[0057] The evaluation may be performed by calculating the value of a formula using a formula that includes a value of the quantity and a variable into which the value is substituted.

[0058] Furthermore, the value of the quantity may be treated as the result of the evaluation (the same applies to the value of the expression). The value of the quantity may be converted, for example, using the following method, and the converted value may be treated as the result of the evaluation (the same applies to the value of the expression). Furthermore, the value of the quantity in this specification may be the value of the quantity itself, or may be a value after the value of the quantity is converted (the same applies to the value of the expression). The conversion method will now be described. Note that the following description focuses on the conversion of the value of the quantity, but the same applies to the value of the expression. In order to make the range of the amount value fall within a predetermined range (e.g., 0.0 to 1.0, 0.0 to 10.0, 0.0 to 100.0, or -10.0 to 10.0, etc.), for example, the amount value may be converted by adding, subtracting, multiplying, or dividing any value, converting the amount value using a predetermined conversion method (e.g., exponential conversion, logarithmic conversion, angular conversion, square root conversion, probit conversion, reciprocal conversion, Box-Cox conversion, or power conversion, etc.), or by combining these calculations on the amount value. For example, the value of an exponential function with the amount value as the exponent and Napier's number as the base (specifically, the value of p / (1-p) when the natural logarithm ln(p / (1-p)) when the probability p of the cognitive function evaluation index value being a predetermined value is defined is equal to the amount value) may be further calculated, and the value of the calculated exponential function divided by the sum of 1 and the value (specifically, the value of the probability p) may be further calculated. The quantity value may also be converted so that the converted value under a particular condition is a particular value, for example, the quantity value may be converted so that the converted value is 5.0 when the specificity is 80% and the converted value is 8.0 when the specificity is 95%. In addition, the distribution of the quantity values ​​may be normalized, and then the quantity values ​​may be standardized so that the average is 50 and the standard deviation is 10. These conversions may be performed according to gender or age.

[0059] Also, position information regarding the position of a predetermined mark on a predetermined ruler that is visibly displayed on a display device such as a monitor or a physical medium such as paper may be generated using the value of the quantity or the converted value if the value is converted, and the generated position information may be determined to be the result of the evaluation (the same applies to the value of an equation). Note that the predetermined ruler is used for the evaluation, and is, for example, a ruler with a scale that shows at least the scales corresponding to the upper and lower limits of the "range in which the value of the quantity or the converted value can be taken, or a part of the range" (the same applies to the value of an equation). Also, the predetermined mark is something that corresponds to the value of the quantity or the converted value, and is, for example, a circle or a star (the same applies to the value of an equation).

[0060] In addition, when the value of the quantity is lower than a predetermined value (such as the mean ± 1SD, 2SD, 3SD, N quantile, N percentile, or a cutoff value recognized for clinical significance), or is equal to or higher than a predetermined value, the above evaluation may be performed (similar to the value of the formula). In this case, a standard deviation may be used instead of the value of the quantity itself (similar to the value of the formula). For example, when the standard deviation is less than the mean value -2SD (standard deviation < 30) or when the standard deviation is higher than the mean value + 2SD (standard deviation > 70), the above evaluation may be performed (similar to the value of the formula).

[0061] In addition, the food to be evaluated may be qualitatively evaluated as to whether it is related to a person's cognitive function. For example, the food to be evaluated may be classified into one of a plurality of categories defined by at least considering the degree of relatedness to cognitive function using "amount value and one or more preset thresholds" or "amount value, a formula including a variable into which the value is substituted, and one or more preset thresholds". The plurality of categories may include a category for belonging to objects with high relatedness, a category for belonging to objects with low relatedness, and a category for belonging to objects with medium relatedness. The plurality of categories may also include a category for belonging to objects with high relatedness and a category for belonging to objects with low relatedness. The amount value or the value of the formula may be converted by a predetermined method, and the converted value may be used to classify the food to be evaluated into one of a plurality of categories.

[0062] The formula used in the evaluation may be in any form, but may be, for example, in the form shown below. Linear models such as multiple regression equations based on the least squares method, linear discriminants, principal component analysis, and canonical discriminant analysis Generalized linear models such as maximum likelihood logistic regression and Cox regression -Generalized linear mixed model that considers random effects such as individual differences and facility differences in addition to generalized linear models · Equations created by cluster analysis such as K-means and hierarchical cluster analysis Formulas based on Bayesian statistics such as MCMC (Markov Chain Monte Carlo), Bayesian Networks, and Hierarchical Bayesian methods - Formulas created by class classification such as support vector machines and decision trees Formulas created using methods that do not fall into the above categories, such as fractional formulas An equation that can be expressed as a sum of different forms of equations

[0063] The formula used in the evaluation may be prepared, for example, by the method described in International Publication No. WO 2004 / 052191 or International Publication No. WO 2006 / 098192, both of which are international applications filed by the present applicant. Formulas obtained by these methods can be suitably used for the evaluation.

[0064] Here, in the multiple regression equation, multiple logistic regression equation, canonical discriminant function, etc., a coefficient and a constant term are added to each variable, and these coefficients and constant terms may be real numbers, more preferably, values ​​within the range of the 99% confidence interval of the coefficients and constant terms obtained for performing the various classifications from the data, and even more preferably, values ​​within the range of the 95% confidence interval of the coefficients and constant terms obtained for performing the various classifications from the data. In addition, the value of each coefficient and its confidence interval may be multiplied by a real number, and the value of the constant term and its confidence interval may be added, subtracted, multiplied, or divided by any real constant. When a logistic regression equation, a linear discriminant, a multiple regression equation, etc. are used for evaluation, linear transformation (addition of a constant, constant multiplication) and monotonically increasing (decreasing) transformation (for example, logit transformation, etc.) do not change the evaluation performance and are equivalent to the one before the transformation, so the one after these transformations may be used.

[0065] A fractional expression is one in which the numerator is expressed as the sum of the variables A, B, C, ... and / or the denominator is expressed as the sum of the variables a, b, c, .... Fractional expressions also include sums of fractional expressions of this type, α, β, γ, ... (such as α + β). Fractional expressions also include divided fractional expressions. The variables used in the numerator and denominator may each have an appropriate coefficient. The variables used in the numerator and denominator may also be duplicated. Each fractional expression may have an appropriate coefficient. The values ​​of the coefficients of each variable and the values ​​of the constant terms may be real numbers. Although the positive / negative sign of the correlation between a given fractional formula and one in which the numerator variable and denominator variable have been swapped will generally be reversed, the correlation between them is maintained and the evaluation performance can be considered to be equivalent, so fractional formulas also include those in which the numerator variable and denominator variable have been swapped.

[0066] When making the evaluation, in addition to the value of the quantity, information on the following items, for example, may be used. Furthermore, the formula used when making the evaluation may further include, in addition to the variable into which the value of the quantity is substituted, one or more variables into which values ​​related to the items listed below, for example, are substituted. The five major nutrients (carbohydrates, proteins, lipids, minerals and vitamins) -Multiple nutrients divided into five major nutrients -Three food groups defined by the food classification method called the three color food groups (food groups classified as "red," "yellow," and "green") - Six food groups (groups 1 to 6) defined by the food classification method called basic food groups Attribute information (e.g., age, sex, or family structure), physical information (e.g., height, weight, muscle mass, body fat mass, clinical test results, vital signs, metabolite concentrations, etc.), health information (e.g., information related to health, etc.), survey information on diet or lifestyle (e.g., survey results on diet or lifestyle concerns, etc.), behavioral information (e.g., digital data on the number of steps, walking speed, voice, gaze, or facial expressions, etc.)

[0067] Furthermore, the subject of evaluation is not limited to food, and may be, for example, a user. For example, when the subject of evaluation is a user, the state of the user's cognitive function (for example, the state of cognitive function at the time of ingestion of food or the state of cognitive function in the future from the time of ingestion of food, etc.) may be evaluated using the value of the amount (for example, calculated using information about the food) of at least one amino acid among the 21 types of amino acids in food (for example, one serving or a certain period of food) ingested by the user, or the value of the formula including a variable into which the value is substituted and the value of the formula calculated using the value.

[0068] In addition, the method for preventing cognitive decline according to the present embodiment may include calculating the amount of at least one amino acid selected from Lys, Phe, Thr, and Ala in a food from information about the food associated with the user, determining whether each calculated value reaches a threshold (e.g., a threshold set for each amino acid), searching for information about foods that contain a large amount of an amino acid corresponding to a value determined not to reach the threshold (e.g., foods that contain an amino acid corresponding to the value in an amount equal to or greater than the difference between the threshold and the value), and providing the searched information about the food to the user as information for preventing cognitive decline. That is, the method for preventing cognitive decline according to the present embodiment may be considered to correspond to a method for providing information for preventing cognitive decline. Here, "preventing cognitive decline" is not limited to preventing cognitive decline, but also includes, for example, maintaining cognitive function, preventing dementia, maintaining brain function, or maintaining brain health. In addition, in the calculation in the method for preventing cognitive decline according to the present embodiment, for example, at least one of the values ​​of the amount of at least one amino acid among Lys, Phe, Thr, Ala, Leu, Tyr, Trp, Val, Ser, SAA, BCAA, Ile and AAA in food and the value of the amino acid score of food (e.g., breakfast equivalent, etc.) may be calculated. Here, the value of the amount of at least one amino acid among Lys, Phe, Thr, Ala, Leu, Tyr, Trp, Val, Ser, SAA, BCAA, Ile and AAA includes, for example, the values ​​of the intake of Leu, Tyr, Trp, Val, Ser, SAA and BCAA shown in Example 3 and at least one value of the amino acid score (sufficiency rate) of Ile, Leu, Trp, Val and AAA shown in Example 3.

[0069] [Second embodiment] [2-1. Overview of the second embodiment] Here, an overview of the second embodiment will be described with reference to FIG. 2. FIG. 2 is a diagram showing the basic principle of the second embodiment. In the description of the second embodiment, explanations that overlap with the first embodiment may be omitted. In particular, a case in which the value of a formula or a value after conversion thereof is used when performing the evaluation is described here as an example, but for example, a value of a quantity or a value after conversion thereof may also be used.

[0070] The control unit performs the evaluation by calculating the value of a formula using a formula stored in advance in the storage unit, the formula including the amount value and a variable into which the value is substituted (step S21). This makes it possible to provide information on, for example, whether the food to be evaluated is related to cognitive function.

[0071] In addition, the control unit may use the evaluation results obtained in step S21 (e.g., evaluation results of dietary content from the perspective of relevance to cognitive function) to generate information that leads to improvement of eating habits in accordance with the evaluation results (e.g., information on a balanced diet or information on suggested menus and ingredients) or information on solutions in accordance with the evaluation results (e.g., information on dietary advice, home delivery service meal kits, or supplements), and provide (transmit) the generated information to, for example, an information processing device owned by the requester.

[0072] In addition, the control unit may use the evaluation results obtained in step S21 to generate information that leads to or is related to insurance premium calculations or insurance product development at the insurance company, and provide (transmit) the generated information to, for example, an information processing device owned by the client.

[0073] In addition, the control unit may use the evaluation results obtained in step S21 to generate information regarding a health program linked to a person's attribute information (e.g., age, sex, or family composition), a person's behavioral information (e.g., digital data regarding the number of steps, walking speed, voice, gaze, or facial expression), or physical information (e.g., height, weight, muscle mass, body fat mass, clinical test results, vital signs, metabolite concentration information, or health-related information), or information regarding a fitness program, and provide (transmit) the generated information to, for example, an information processing device owned by the client.

[0074] In addition, the control unit may combine the evaluation results obtained in step S21 with, for example, information regarding the individual's attribute information (e.g., age, sex, or family composition), the individual's eating tendencies, the individual's eating habits, the individual's eating pattern, or the individual's preferences, to generate information personalized for the individual, and provide (transmit) the generated information to, for example, an information processing device owned by the client.

[0075] Furthermore, the control unit may use the evaluation results obtained in step S21 to evaluate future cognitive function, risk of disease associated with cognitive function, risk of change in physical condition such as becoming bedridden, risk of behavioral change, or life expectancy.

[0076] The control unit may also calculate the amount of at least one amino acid from Lys, Phe, Thr, and Ala in a food from information related to the user, determine whether each calculated value reaches a threshold (e.g., a threshold set for each amino acid), search for information related to foods that contain a large amount of an amino acid corresponding to a value determined not to reach the threshold (e.g., foods that contain an amount of an amino acid corresponding to the value that is equal to or greater than the difference between the threshold and the value), and provide the user with the searched information related to the food as information for preventing cognitive decline. For example, the control unit may provide (transmit) the information related to the food to an information processing device owned by the user.

[0077] The formula used in step S21 may be one created based on the formula creation process (steps 1 to 4) described below. Here, an overview of the formula creation process will be described. Note that the process described here is merely an example, and the formula creation method is not limited to this.

[0078] First, the control unit creates a candidate formula (e.g., y=a1x1+a2x2+···+anxn, y: index data, xi: amino acid-related data, ai: constant, i=1,2,···,n) based on a predetermined formula creation method from index state information (which may be information from which data containing missing values ​​or outliers has been removed in advance) that includes amino acid-related data and index data related to the values ​​of cognitive function assessment indexes and that is previously stored in the memory unit (step 1).

[0079] In step 1, multiple candidate formulas may be created from the index state information by using multiple different formula creation methods (including those related to multivariate analysis such as principal component analysis, discriminant analysis, support vector machine, multiple regression analysis, Cox regression analysis, logistic regression analysis, k-means method, cluster analysis, and decision tree). Specifically, multiple groups of candidate formulas may be created simultaneously in parallel using multiple different algorithms for the index state information. For example, discriminant analysis and logistic regression analysis may be performed simultaneously using different algorithms to create two different candidate formulas. In addition, the index state information may be converted using a candidate formula created by performing principal component analysis, and a discriminant analysis may be performed on the converted index state information to create a candidate formula. This allows the formula optimal for the evaluation to be created in the end.

[0080] Here, the candidate formula created using principal component analysis is a linear formula including each variable that maximizes the variance of all amino acid-related data. The candidate formula created using discriminant analysis is a high-order formula (including exponential and logarithmic) including each variable that minimizes the ratio of the sum of variances in each group to the variance of all amino acid-related data. The candidate formula created using support vector machine is a high-order formula (including kernel function) including each variable that maximizes the boundary between groups. The candidate formula created using multiple regression analysis is a high-order formula including each variable that minimizes the sum of distances from all amino acid-related data. The candidate formula created using Cox regression analysis is a linear model including a log hazard ratio, and is a linear formula including each variable and its coefficient that maximizes the likelihood of the model. The candidate formula created using logistic regression analysis is a linear model that represents the log odds of probability, and is a linear formula including each variable that maximizes the likelihood of the probability. The k-means method is a method of searching k neighbors of each amino acid-related data, defining the group to which the most neighboring points belong as the group to which the data belongs, and selecting the variable that best matches the group to which the input amino acid-related data belongs. Cluster analysis is a method of clustering (grouping) points that are closest to each other among all amino acid-related data. A decision tree is a method of ranking variables and predicting groups of amino acid-related data from the possible patterns of variables with higher rankings.

[0081] Returning to the explanation of the formula creation process, the control unit verifies (cross-validates) the candidate formulas created in step 1 based on a predetermined verification method (step 2). The candidate formulas are verified for each candidate formula created in step 1. In step 2, at least one of the discrimination rate, sensitivity, specificity, information criterion, ROC_AUC (area under the receiver characteristic curve), etc. of the candidate formula may be verified based on at least one of the bootstrap method, hold-out method, N-fold method, leave-one-out method, etc. This makes it possible to create a candidate formula with high predictability or robustness that takes into account index state information and evaluation conditions.

[0082] Here, the discrimination rate is the rate at which the evaluation method according to the present embodiment correctly evaluates the evaluation target whose true state is negative (e.g., foods with low relevance to cognitive function) as negative and correctly evaluates the evaluation target whose true state is positive (e.g., foods with high relevance to cognitive function) as positive. The sensitivity is the rate at which the evaluation method according to the present embodiment correctly evaluates the evaluation target whose true state is positive as positive. The specificity is the rate at which the evaluation method according to the present embodiment correctly evaluates the evaluation target whose true state is negative as negative. The Akaike information criterion is a standard that indicates the degree to which observed data matches a statistical model in the case of regression analysis, etc., and the model with the smallest value defined by "-2 x (maximum logarithmic likelihood of statistical model) + 2 x (number of free parameters of statistical model)" is judged to be the best. ROC_AUC is defined as the area under the receiver characteristic curve (ROC), which is a curve created by plotting (x, y) = (1 - specificity, sensitivity) on a two-dimensional coordinate system, and the ROC_AUC value is 1 for perfect discrimination, with the closer this value is to 1 the higher the discrimination ability. Predictability is the average of the discrimination rate, sensitivity, and specificity obtained by repeatedly verifying the candidate formula. Robustness is the variance of the discrimination rate, sensitivity, and specificity obtained by repeatedly verifying the candidate formula.

[0083] Returning to the explanation of the formula creation process, the control unit selects a combination of amino acid-related data included in the index state information used when creating the candidate formula by selecting variables of the candidate formula based on a predetermined variable selection method (step 3). In step 3, the selection of variables may be performed for each candidate formula created in step 1. This allows the variables of the candidate formula to be appropriately selected. Then, step 1 is executed again using the index state information including the amino acid-related data selected in step 3. In step 3, the variables of the candidate formula may be selected based on at least one of the stepwise method, the best path method, the local search method, and the genetic algorithm from the verification result in step 2. In addition, the best path method is a method of selecting variables by sequentially reducing the variables included in the candidate formula one by one and optimizing the evaluation index given by the candidate formula.

[0084] Returning to the explanation of the formula creation process, the control unit repeatedly executes the above-mentioned steps 1, 2, and 3, and creates a formula to be used in evaluation by selecting a candidate formula to be used in evaluation from among multiple candidate formulas based on the verification results accumulated thereby (step 4). Note that the selection of the candidate formula may involve, for example, selecting the optimal one from among candidate formulas created using the same formula creation method, or selecting the optimal one from among all candidate formulas.

[0085] As described above, in the formula creation process, the processes related to the creation of candidate formulas, the verification of the candidate formulas, and the selection of variables for the candidate formulas are systematized (systemized) in a series of flows and executed based on the index state information, thereby making it possible to create a formula that is optimal for the evaluation. In other words, in the formula creation process, amino acid-related data is used in multivariate statistical analysis, and a variable selection method and cross-validation are combined to select an optimal and robust set of variables, thereby extracting a formula with high evaluation performance.

[0086] [2-2. Configuration of the second embodiment] Here, the configuration of the evaluation system according to the second embodiment (hereinafter, sometimes referred to as the present system) will be described with reference to Figs. 3 to 14. Note that the present system is merely an example, and the present invention is not limited thereto. In particular, here, a case in which the value of a formula or its converted value is used when performing the evaluation is described as an example, but, for example, a value of a quantity or its converted value may also be used.

[0087] First, the overall configuration of the present system will be described with reference to FIG. 3 and FIG. 4. FIG. 3 is a diagram showing an example of the overall configuration of the present system. FIG. 4 is a diagram showing another example of the overall configuration of the present system. As shown in FIG. 3, the present system is configured by connecting an evaluation device 100 that performs the evaluation and a user's client device 200 (corresponding to a terminal device of the present invention) that provides an example of information about food, such as a photograph of a meal or ingredients or text information about a description of the meal content, and receives the evaluation result, etc., so that they can communicate with each other via a network 300. Here, in the system configuration shown in FIG. 3, the client device 200 may calculate a value of an amount using a photograph of a meal or ingredients or text information about a description of the meal content, and provide the calculated value. Also, in the system configuration shown in FIG. 3, the client device 200 may calculate a value of an amount using a photograph of a meal or ingredients or text information about a description of the meal content, and calculate a value of the calculated amount using a preset formula including a variable into which the calculated amount value and the value are substituted, and provide the value of the calculated formula.

[0088] In this system, the client device 200 that is the source of the data used for evaluation and the client device 200 that is the recipient of the evaluation results may be separate. As shown in FIG. 4, this system may be configured by connecting the evaluation device 100, the user's client device 200 that receives the evaluation results, and a retail store's POS system 400 that provides purchase data, which is an example of information about food, via a network 300 so that they can communicate with each other. Here, the POS system 400 is a general one used in the retail industry, etc. In the system configuration shown in FIG. 4, the POS system 400 may further have a function of calculating a quantity value using the purchase data and providing the calculated value.

[0089] In addition, the system configuration shown in FIG. 3 or FIG. 4 may further include a database device 500 (not shown in FIGS. 3 and 4) that stores index state information used when creating a formula by the evaluation device 100, formulas used in evaluation, etc.

[0090] Next, the configuration of the evaluation device 100 of this system will be described with reference to Fig. 5 to Fig. 11. Fig. 5 is a block diagram showing an example of the configuration of the evaluation device 100 of this system, and conceptually shows only the parts of the configuration that are related to the present invention.

[0091] The evaluation device 100 is composed of a control unit 102 such as a CPU (Central Processing Unit) that controls the evaluation device in an overall manner, a communication interface unit 104 that communicatively connects the evaluation device to a network 300 via a communication device such as a router and a wired or wireless communication line such as a dedicated line, a memory unit 106 that stores various databases, tables, files, etc., and an input / output interface unit 108 that connects to an input device 112 and an output device 114, and each of these units is communicatively connected via an arbitrary communication path.

[0092] The communication interface unit 104 mediates communication between the evaluation device 100 and the network 300 (or a communication device such as a router). That is, the communication interface unit 104 has a function of communicating data with other terminals via a communication line.

[0093] The input / output interface unit 108 is connected to an input device 112 and an output device 114. Here, the output device 114 may be a monitor (including a home television), a speaker, or a printer (hereinafter, the output device 114 may be referred to as a monitor 114). The input device 112 may be a keyboard, a mouse, a microphone, or a monitor that cooperates with a mouse to realize a pointing device function.

[0094] The memory unit 106 is a storage means, and may be, for example, a memory device such as a random access memory (RAM) or a read only memory (ROM), a fixed disk device such as a hard disk, a flexible disk, an optical disk, etc. The memory unit 106 records computer programs for cooperating with an operating system (OS) to give instructions to a CPU to perform various processes. As shown in the figure, the memory unit 106 stores an amino acid-related data file 106a, an index state information file 106b, a specified index state information file 106c, a formula-related information database 106d, and an evaluation result file 106e.

[0095] The amino acid-related data file 106a stores amino acid-related data related to quantity values. FIG. 6 is a diagram showing an example of information stored in the amino acid-related data file 106a. As shown in FIG. 6, the information stored in the amino acid-related data file 106a is configured by associating identification data for uniquely identifying an evaluation target with amino acid-related data. Here, in FIG. 6, the amino acid-related data is treated as a numerical value, i.e., a continuous scale, but the amino acid-related data may be a nominal scale or an ordinal scale. In the case of a nominal scale or an ordinal scale, an arbitrary numerical value may be assigned to each state for analysis. Also, information on the above items may be combined with the amino acid-related data.

[0096] The index state information file 106b stores index state information used when creating a formula. FIG. 7 is a diagram showing an example of information stored in the index state information file 106b. As shown in FIG. 7, the information stored in the index state information file 106b is configured by mutually associating identification data, index data (T) related to cognitive function evaluation indexes (index T1, index T2, index T3, etc.), and amino acid related data. Here, in FIG. 7, the index data and amino acid related data are treated as numerical values ​​(i.e., continuous scale), but the index data and amino acid related data may be nominal scale or ordinal scale. In the case of a nominal scale or ordinal scale, analysis may be performed by giving an arbitrary numerical value to each state.

[0097] The designated index status information file 106c stores index status information designated by the designation unit 102b described later. Fig. 8 is a diagram showing an example of information stored in the designated index status information file 106c. As shown in Fig. 8, the information stored in the designated index status information file 106c is configured by associating individual numbers, designated index data, and designated amino acid related data with each other.

[0098] The formula-related information database 106d is composed of a formula file 106d1 that stores formulas created by a formula creation unit 102c (described later). The formula file 106d1 stores formulas used in evaluation. Fig. 9 is a diagram showing an example of information stored in the formula file 106d1. As shown in Fig. 9, the information stored in the formula file 106d1 is composed of ranks, formulas, thresholds corresponding to each formula creation method, and verification results of each formula (e.g., the value of each formula), which are mutually associated with each other.

[0099] The evaluation result file 106e stores the evaluation results obtained by the evaluation unit 102d described later. Fig. 10 is a diagram showing an example of information stored in the evaluation result file 106e. The information stored in the evaluation result file 106e is configured by associating identification data, amino acid-related data, and evaluation results (for example, a formula value calculated by a calculation unit 102d1 described later, a converted value obtained by a conversion unit 102d2 described later, position information generated by a generation unit 102d3 described later, or a classification result obtained by a classification unit 102d4 described later, etc.) with each other.

[0100] The control unit 102 has an internal memory for storing control programs such as an OS, programs that define various processing procedures, required data, etc., and executes various information processing based on these programs. As shown in the figure, the control unit 102 is roughly divided into an acquisition unit 102a, a designation unit 102b, a formula creation unit 102c, an evaluation unit 102d, a result output unit 102e, and a transmission unit 102f. The control unit 102 may perform data processing such as removal of data with missing values, removal of data with many outliers, and removal of variables with many data with missing values ​​on the index state information and amino acid-related data.

[0101] The acquiring unit 102a acquires information (specifically, information on food, amino acid-related data, index state information, formula, etc.). For example, the acquiring unit 102a may acquire information by receiving information (specifically, information on food, amino acid-related data, index state information, formula, etc.) transmitted from the client device 200, the POS system 400, or the database device 500 via the network 300. The acquiring unit 102a may receive data used for evaluation transmitted from a client device 200 different from the client device 200 to which the evaluation result is transmitted. For example, in the case where the evaluation device 100 includes a mechanism (including hardware and software) for reading information recorded on a recording medium, the acquiring unit 102a may acquire information by reading information (specifically, information on food, amino acid-related data, index state information, formula, etc.) recorded on the recording medium via the mechanism.

[0102] The designation unit 102b designates the index data and amino acid-related data to be targeted when creating a formula.

[0103] The equation creation unit 102c creates an equation based on the index state information acquired by the acquisition unit 102a and the index state information designated by the designation unit 102b. When an equation is stored in advance in a predetermined storage area of ​​the storage unit 106, the equation creation unit 102c may create an equation by selecting a desired equation from the storage unit 106. The equation creation unit 102c may create an equation by selecting a desired equation from another computer device (e.g., database device 500) that has equations stored in advance and downloading the equation.

[0104] The evaluation unit 102d performs the evaluation by calculating the value of the formula using a formula obtained in advance (e.g., a formula created by the formula creation unit 102c or a formula obtained by the acquisition unit 102a) and an amount value obtained in advance (e.g., an amount value included in the amino acid-related data obtained by the acquisition unit 102a or an amount value calculated by the evaluation unit 102d). The evaluation unit 102d may perform the evaluation by using the amount value or a value obtained by converting the amount value.

[0105] Here, the configuration of the evaluation unit 102d will be described with reference to Fig. 11. Fig. 11 is a block diagram showing the configuration of the evaluation unit 102d, and conceptually shows only the parts of the configuration related to the present invention. The evaluation unit 102d further includes a calculation unit 102d1, a conversion unit 102d2, a generation unit 102d3, and a classification unit 102d4.

[0106] The calculation unit 102d1 calculates the value of an equation using an equation including a quantity value and a variable into which the value is substituted. The calculation unit 102d1 may calculate the quantity value using information about food (e.g., purchase data transmitted from the POS system 400, photos of meals and ingredients transmitted from the client device 200, or text information about the description of the meal transmitted from the client device 200). The evaluation unit 102d may store the value calculated by the calculation unit 102d1 in a predetermined storage area of ​​the evaluation result file 106e as the evaluation result.

[0107] The conversion unit 102d2 converts the value of the formula calculated by the calculation unit 102d1, for example, using the conversion method described above. The evaluation unit 102d may store the value converted by the conversion unit 102d2 in a predetermined storage area of ​​the evaluation result file 106e as the evaluation result. The conversion unit 102d2 may convert the value of the quantity, for example, using the conversion method described above.

[0108] The generating unit 102d3 generates position information on the position of a predetermined mark on a predetermined ruler that is visibly shown on a display device such as a monitor or a physical medium such as paper, using the value of the formula calculated by the calculating unit 102d1 or the value converted by the converting unit 102d2 (which may be the value of the quantity or the value converted from the value). The evaluating unit 102d may store the position information generated by the generating unit 102d3 in a predetermined storage area of ​​the evaluation result file 106e as the evaluation result.

[0109] The classification unit 102d4 classifies the evaluation object into one of the multiple categories using the value of the formula calculated by the calculation unit 102d1 or the value converted by the conversion unit 102d2 (which may be the value of the quantity or the converted value of the quantity).

[0110] The result output unit 102e outputs to the output device 114 the processing results of each processing unit in the control unit 102 (including the evaluation result obtained by the evaluation unit 102d) and the like.

[0111] The transmitting unit 102f transmits information such as the evaluation result, information on food, quantity values, and formula values ​​to the client device 200, and transmits information such as the formula and evaluation result created by the evaluation device 100 to the database device 500. The transmitting unit 102f may transmit the evaluation result to a client device 200 different from the client device 200 that is the source of the data used for the evaluation.

[0112] Next, the configuration of client device 200 will be described with reference to Fig. 12. Fig. 12 is a block diagram showing an example of the configuration of client device 200, and conceptually shows only the parts of the configuration that are related to the present invention.

[0113] The client device 200 is composed of a control unit 210, a ROM 220, a HD (Hard Disk) 230, a RAM 240, an input device 250, an output device 260, an input / output IF 270, and a communication IF 280, and these units are communicably connected via any communication path. The client device 200 may be based on, for example, a known information processing terminal such as a personal computer, a workstation, a home game device, an Internet TV, a PHS (Personal Handyphone System) terminal, a mobile terminal, a mobile communication terminal, a PDA (Personal Digital Assistant), a smartphone, or a tablet terminal.

[0114] The input device 250 is a keyboard, a mouse, a microphone, etc. The monitor 261 described later also realizes a pointing device function. The output device 260 is an output means for outputting information received via the communication IF 280, and includes a monitor (including a home television) 261. In addition, the output device 260 may be provided with a speaker, etc. The input / output IF 270 is connected to the input device 250 and the output device 260. The client device 200 may further include an imaging device such as a camera.

[0115] The communication IF 280 communicably connects the client device 200 and the network 300 (or a communication device such as a router).

[0116] The control unit 210 includes a transmission unit 211 and a reception unit 212. The transmission unit 211 transmits information such as photos of meals, ingredients, etc., which are examples of information about food, or text information about the meal contents, to the evaluation device 100 via the communication IF 280. The reception unit 212 receives information such as the evaluation results, information about food, quantity values, and formula values ​​transmitted from the evaluation device 100 via the communication IF 280.

[0117] The control unit 210 may realize all or any part of the processing performed by the control unit with a CPU and a program that is interpreted and executed by the CPU. A computer program for giving instructions to the CPU in cooperation with the OS and performing various processing is recorded in the ROM 220 or the HD 230. The computer program is executed by being loaded into the RAM 240, and constitutes the control unit 210 in cooperation with the CPU. The computer program may also be recorded in an application program server connected to the client device 200 via any network, and the client device 200 may download all or any part of the computer program as necessary. Also, all or any part of the processing performed by the control unit 210 may be realized by hardware such as wired logic.

[0118] Here, the control unit 210 may include an evaluation unit 210a (including a calculation unit 210a1, a conversion unit 210a2, a generation unit 210a3, and a classification unit 210a4) having the same functions as the evaluation unit 102d included in the evaluation device 100. For example, when the evaluation unit 210a receives a value of an amount or a value of an expression from the evaluation device 100, the conversion unit 210a2 may convert the received value, the generation unit 210a3 may generate position information corresponding to the received value or the converted value, and the classification unit 210a4 may classify the evaluation target into one of the multiple categories using the received value or the converted value. Also, for example, when the evaluation unit 210a receives a value after conversion of a value of an amount or a value of an expression from the evaluation device 100, the generation unit 210a3 may generate position information corresponding to the received value, and the classification unit 210a4 may classify the evaluation target into one of the multiple categories using the received value. Also, for example, when the evaluation unit 210a receives a quantity value, an expression value, or a converted value and location information from the evaluation device 100, the classification unit 210a4 may classify the evaluation target into one of a plurality of categories using the received values.

[0119] Next, the network 300 of this system will be described with reference to Figures 3 and 4. The network 300 has a function of connecting the evaluation device 100, the client device 200, the POS system 400, and the database device 500 (not shown in Figures 3 and 4) so ​​that they can communicate with each other, and is, for example, the Internet, an intranet, or a LAN (Local Area Network) (including both wired and wireless networks). In addition, network 300 may be a VAN (Value-Added Network), a personal computer communication network, a public telephone network (including both analog and digital), a leased line network (including both analog and digital), a CATV (Community Antenna TeleVision) network, a mobile circuit-switched network or a mobile packet-switched network (including the IMT (International Mobile Telecommunication) 2000 system, the GSM (registered trademark) (Global System for Mobile Communications) system, or the PDC (Personal Digital Cellular) / PDC-P system, etc.), a radio paging network, a local wireless network such as Bluetooth (registered trademark), a PHS network, or a satellite communication network (including CS (Communication Satellite), BS (Broadcasting Satellite), or ISDB (Integrated Services Digital Broadcasting), etc.).

[0120] Next, the configuration of the database device 500 of this system will be described with reference to Fig. 13. Fig. 13 is a block diagram showing an example of the configuration of the database device 500 of this system, and conceptually shows only the parts of the configuration that are related to the present invention.

[0121] The database device 500 has a function of storing index state information used when creating an equation in the evaluation device 100 or the database device itself, an equation created in the evaluation device 100, an evaluation result in the evaluation device 100, etc. As shown in Fig. 13, the database device 500 is composed of a control unit 502 such as a CPU that controls the database device in an overall manner, a communication interface unit 504 that communicatively connects the database device to the network 300 via a communication device such as a router and a wired or wireless communication circuit such as a dedicated line, a storage unit 506 that stores various databases, tables, files (e.g., files for Web pages), etc., and an input / output interface unit 508 that connects to an input device 512 and an output device 514, and these units are communicatively connected via any communication path.

[0122] The memory unit 506 is a storage means, and may be, for example, a memory device such as a RAM or ROM, a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like. The memory unit 506 stores various programs and the like used for various processes. The communication interface unit 504 mediates communication between the database device 500 and the network 300 (or a communication device such as a router). That is, the communication interface unit 504 has a function of communicating data with other terminals via a communication line. The input / output interface unit 508 is connected to an input device 512 and an output device 514. Here, the output device 514 may be a monitor (including a home television), a speaker, or a printer. The input device 512 may be a keyboard, a mouse, a microphone, or a monitor that cooperates with a mouse to realize a pointing device function.

[0123] The control unit 502 has an internal memory for storing control programs such as an OS, programs defining various processing procedures, required data, etc., and executes various information processing based on these programs. As shown in the figure, the control unit 502 is roughly equipped with a transmission unit 502a and a reception unit 502b. The transmission unit 502a transmits various information such as index state information and equations to the evaluation device 100. The reception unit 502b receives various information such as equations and evaluation results transmitted from the evaluation device 100.

[0124] In this description, an example has been given in which the evaluation device 100 executes the processes from obtaining amino acid-related data and the like, calculating formula values, classifying the evaluation targets into categories, and transmitting the evaluation results, while the client device 200 receives the evaluation results. However, when the client device 200 is provided with the evaluation unit 210a, the calculation of the amount value or formula value, conversion of the amount value or formula value, generation of position information, and classification of the evaluation targets into categories may be appropriately shared between the evaluation device 100 and the client device 200.

[0125] Furthermore, the prevention system according to the second embodiment may be constructed based on, for example, this system. Specifically, the evaluation device 100 includes a determination unit that determines whether the amount value calculated by the calculation unit 102d1 reaches a threshold value, and a search unit that searches for information on foods that contain a large amount of amino acids corresponding to the amount value determined by the determination unit to not reach the threshold value, thereby making it possible to realize information processing that is composed of the following processes A1 to A6. Process A1: The acquisition unit 102a acquires information about food associated with the user. Process A2: The calculation unit 102d1 calculates the amount value from the acquired information on the food. Process A3: The determination unit determines whether the calculated amount reaches a threshold value. Process A4: The search unit searches for information on foods that contain a large amount of the amino acid corresponding to the amount determined by the determination unit to not reach the threshold value. Process A5: The transmission unit 102f transmits the information on food searched for by the search unit to the client device 200 as information for preventing cognitive decline. Process A6: The client device 200 receives the information about food transmitted from the evaluation device 100.

[0126] [2-3. Other embodiments] The evaluation device, calculation device, prevention device, evaluation method, calculation method, prevention method, evaluation program, calculation program, prevention program, recording medium, evaluation system, prevention system, and terminal device of the present invention may be embodied in various different embodiments within the scope of the technical idea described in the claims, in addition to the second embodiment described above.

[0127] Furthermore, among the processes described in the second embodiment, 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 using known methods.

[0128] In addition, the processing procedures, control procedures, specific names, registered data for each process, information including parameters such as search conditions, screen examples, and database configurations shown in the above documents and drawings can be changed as desired unless otherwise specified.

[0129] Moreover, with regard to the evaluation device 100, the components shown in the figures are merely functional concepts, and the evaluation device 100 does not necessarily have to be physically configured as shown in the figures.

[0130] For example, the processing functions of the evaluation device 100, particularly the processing functions performed by the control unit 102, may be realized in whole or in part by a CPU and a program interpreted and executed by the CPU, or may be realized as hardware using wired logic. The program is recorded in a non-transient computer-readable recording medium including programmed instructions for causing an information processing device to execute the evaluation method or calculation method according to the present invention, and is mechanically read by the evaluation device 100 as necessary. That is, a computer program for giving instructions to the CPU in cooperation with the OS and performing various processes is recorded in the storage unit 106 such as a ROM or HDD (Hard Disk Drive). This computer program is executed by being loaded into a RAM, and constitutes a control unit in cooperation with the CPU.

[0131] In addition, this computer program may be stored in an application program server connected to the evaluation device 100 via any network, and it is also possible to download all or part of it as necessary.

[0132] The evaluation program or calculation program according to the present invention may be stored in a non-transitory computer-readable recording medium, or may be configured as a program product. Here, the term "recording medium" includes any "portable physical medium" such as a memory card, a Universal Serial Bus (USB) memory, a Secure Digital (SD) card, a flexible disk, a magneto-optical disk, a ROM, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable and Programmable Read Only Memory (EEPROM) (registered trademark), a Compact Disc Read Only Memory (CD-ROM), a Magneto-Optical disk (MO), a Digital Versatile Disk (DVD), and a Blu-ray (registered trademark) Disc.

[0133] Moreover, a "program" is a data processing method written in any language or description method, and may be in any form, such as source code or binary code. Note that a "program" is not necessarily limited to a single configuration, but also includes a distributed configuration as multiple modules or libraries, and a program that works with a separate program, such as an OS, to achieve its function. Note that the specific configuration and reading procedure for reading a recording medium in each device shown in the embodiments, as well as the installation procedure after reading, may use well-known configurations and procedures.

[0134] The various databases etc. stored in the memory unit 106 are storage means such as 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 etc. used for various processes and providing websites.

[0135] The evaluation device 100 may be configured as an information processing device such as a known personal computer or a workstation, or may be configured as the information processing device to which any peripheral device is connected. The evaluation device 100 may be realized by installing software (including a program or data) that realizes the evaluation method or calculation method of the present invention in the information processing device.

[0136] Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the drawings, and all or part of them can be functionally or physically distributed and integrated in any unit according to various additions or functional loads. In other words, the above-mentioned embodiments can be implemented in any combination, or the embodiments can be implemented selectively. EXAMPLES

[0137] A total of 2162 men and women (1069 men and 1093 women) aged 40 to 86 years old from June 2004 to June 2006 were surveyed. Photographs of the meals actually consumed on each day of the three consecutive days (two weekdays and one holiday) during the period were obtained from the subjects. A nutritionist then calculated each person's nutritional intake (specifically, the daily intake of each of the 22 types of amino acids (Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Arg, Ala, Asp, Glu, Gly, Pro, Ser, Hydroxyproline, SAA, AAA, and BCAA)) based on the three-day food weighing method (Imai Tomoko et al., Effectiveness of Photographing in a Three-Day Food Record Survey, Journal of the Japanese Society for Food and Living, 2009, 20(3):203-210.). The daily intake of each of the 22 amino acids was then classified into tertiles by gender, and three groups were generated, T1, T2, and T3, in ascending order of intake. The tertiles of T1, T2, and T3 for the daily intake of each amino acid are shown in FIG. 14. For example, for Ile, the intake of men in the T1 group was 1154.9 mg / day or more and less than 2881.2 mg / day, and the intake of women in the T1 group was 1146.7 mg / day or more and less than 2436.3 mg / day.

[0138] The mean score and standard error of the logical memory I (immediate recall) of the WMS-R Wechsler Memory Scale, which is one of the cognitive function indicators administered to the subjects during the period, were calculated for each group.

[0139] In addition, an analysis of variance was performed on the previously prepared models 1, 2, 3, and 4, and the presence or absence of significant differences between the three groups was evaluated at a significance level of 5% on both sides (whether or not there is a statistically significant difference in at least one of the three groups). In addition, a trend test was performed with adjustments using the same variables as in models 1 to 4 of the analysis of variance, and the presence or absence of significant differences between the three groups was evaluated at a significance level of 5% on both sides (whether or not a significant slope was observed when regression was examined in the order of intake of the three groups). The evaluation results are shown in Figure 15.

[0140] Here, model 1 is a model adjusted for each of the 22 types of amino acids by age, sex, BMI, years of education, CES-D (The Center for Epidemiologic Studies Depression Scale) which is a depression index, smoking history, employment status, whether or not living alone, whether or not having myocardial infarction, whether or not having hypertension, whether or not having hyperlipidemia, whether or not having ischemic heart disease, and whether or not having diabetes. Specifically, model 1 is a model composed of 14 explanatory variables, and the 14 explanatory variables are the intake group (T1, T2 or T3) of one of the 22 types of amino acids, age, sex, BMI, years of education, CES-D, smoking history, employment status, whether or not living alone, whether or not having myocardial infarction, whether or not having hypertension, whether or not having hyperlipidemia, whether or not having ischemic heart disease, and whether or not having diabetes. Model 2 is a model composed of 15 explanatory variables, in which lipid intake is added as an explanatory variable to model 1. Model 3 is a model composed of 15 explanatory variables, in which energy intake is added as an explanatory variable to model 1. Model 4 is a model consisting of 15 explanatory variables, in which protein intake was added as an explanatory variable to Model 1.

[0141] In the results of Model 1 shown in Figure 15, a significant association was observed for all amino acids except for Hydroxyproline, indicating that the daily intake of 21 types of amino acids, excluding Hydroxyproline, from the 22 types of amino acids, is associated with cognitive function (immediate regenerative ability).

[0142] In the results of model 2 shown in Figure 15, a significant association was observed between Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Pro, Ser, Asp, SAA, AAA and BCAA, so it was found that the daily intake of these 17 kinds of amino acids is related to cognitive function (immediate regenerative ability) even in the same situation of lipid intake in the subject. In addition, since lipid intake and animal protein are thought to be correlated, it was suggested that the daily intake of these 17 kinds of amino acids is related to cognitive function (immediate regenerative ability) even in the same situation of animal protein intake in the subject.

[0143] In the results of Model 3 shown in Figure 15, significant associations were observed for Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Ala, Asp, Pro, Ser, SAA, AAA and BCAA, indicating that the daily intake of these 18 amino acids is associated with cognitive function (immediate regenerative ability) even when the energy intake in the subjects is the same.

[0144] In the results of Model 4 shown in Figure 15, significant associations were observed for Ile, Leu, Lys, Met, Tyr, Thr, Trp, Val, SAA, AAA and BCAA, indicating that the daily intake of these 11 types of amino acids is associated with cognitive function (immediate regenerative ability) even when the protein intake in the subjects was the same.

[0145] The results of Model 1 show that the content of amino acids in the diet is related to cognitive function (immediate regeneration), and the results of Models 2 to 4 show that the quality of amino acids in the diet is related to cognitive function (immediate regeneration). (In Model 2, the amount of lipid intake is significantly related to cognitive function under the same conditions, in Model 3, the amount of energy intake is significantly related to cognitive function under the same conditions, in other words, in Model 4, even under the same conditions of protein intake, a significant association between amino acids and cognitive function is observed, so that the proportion of amino acids that make up protein is important in the association between diet and cognitive function.) In addition, for amino acids that were related to cognitive function, the score of cognitive function (immediate regeneration) also increased as the intake of amino acids increased, suggesting that a higher intake is better. In addition, the usefulness of setting a threshold value in the range between the minimum value and the maximum value, as in the quantile shown in Figure 14, and expressing and categorizing the intake as a group was also suggested. EXAMPLES

[0146] The logical memory I (immediate recall) of the WMS-R Wechsler Memory Test used as the cognitive function index in Example 1 was replaced with the logical memory II (delayed recall) of the WMS-R Wechsler Memory Test, which is one of the cognitive function indexes, and the same evaluation as in Example 1 was performed. The evaluation results are shown in FIG.

[0147] In the results of Model 1 shown in Figure 16, a significant association was observed for all amino acids except for Hydroxyproline, indicating that the daily intake of 21 types of amino acids, excluding Hydroxyproline, from the 22 types of amino acids, is associated with cognitive function (delayed recall ability).

[0148] In the results of model 2 shown in Figure 16, a significant correlation was observed between Ile, Leu, Lys, Met, Phe, Tyr, Thr, Trp, Val, His, Pro, SAA, AAA and BCAA, indicating that the daily intake of these 14 amino acids is related to cognitive function (delayed regeneration ability) even when the subjects have the same lipid intake. In addition, since lipid intake and animal protein are thought to be correlated, it was suggested that the daily intake of these 14 amino acids is related to cognitive function (immediate regeneration ability) even when the subjects have the same animal protein intake.

[0149] In the results of Model 3 shown in Figure 16, significant associations were observed for Ile, Leu, Lys, Met, Phe, Tyr, Thr, Trp, Val, His, Asp, Pro, Ser, SAA, AAA and BCAA, indicating that the daily intake of these 16 amino acids is associated with cognitive function (delayed recall ability) in the subjects, even when the energy intake is the same.

[0150] In the results of Model 4 shown in Figure 16, significant associations were observed for Ile, Leu, Lys, Phe, Tyr, Thr, Trp, Val, His, Pro, SAA, AAA and BCAA, indicating that the daily intake of these 13 types of amino acids is associated with cognitive function (delayed recall ability) even when the protein intake in the subjects was the same.

[0151] The results of Model 1 show that the content of amino acids in the diet is related to cognitive function (delayed recall ability), and the results of Models 2 to 4 show that the quality of amino acids in the diet is related to cognitive function (delayed recall ability) (Model 2 shows that the intake of amino acids in the diet is significantly related to cognitive function under the same lipid intake, Model 3 shows that the intake of energy, and Model 4 shows that the intake of protein is significantly related to cognitive function under the same protein intake. In other words, considering Model 4 as an example, even under the same protein intake, amino acids are significantly related to cognitive function, so the proportion of amino acids that make up protein is important in the relationship between diet and cognitive function). In addition, for amino acids that were related to cognitive function, the score of cognitive function (delayed recall ability) also increased as the intake of amino acids increased, suggesting that a higher intake is better. In addition, the usefulness of setting a threshold value in the range between the minimum value and the maximum value, as in the quantile shown in Figure 14, and expressing and categorizing the intake as a group was also suggested. EXAMPLES

[0152] A total of 1,330 men and women (663 men and 667 women) aged 40 to 82 years old from May 2002 to May 2004 were surveyed. Photographs of the meals actually consumed on each of the three consecutive days (two weekdays and one holiday) during the period were obtained from the subjects. A nutritionist then used the photographs to determine each person's nutritional intake (specifically, the daily intake of each of the 22 amino acids and the daily amino acid score (sufficiency rate) of each of the nine amino acids (Ile, Leu, Lys, Thr, Trp, Val, His, SAA, and AAA) relative to the amino acid reference values ​​proposed by FAO / WHO / UNU in 1985) based on the three-day dietary weighing method.

[0153] Scores from the WAIS-R Adult Intelligence Scale (Knowledge), a commonly used method for assessing cognitive ability, were obtained from the subjects between July 2010 and July 2012.

[0154] The score of the WAIS-R Adult Intelligence Test (knowledge) was used as the objective variable, and the daily intake of each of the 22 types of amino acids and the daily amino acid score (sufficiency rate) of each of the 9 types of amino acids were used as explanatory variables. An analysis was performed using a linear regression model (specifically, Models 1 to 4 below) to examine the relationship between the amino acid intake and amino acid score (sufficiency rate) and future cognitive function indexes. The evaluation results are shown in Figures 17 and 18.

[0155] Here, model 1 is a model in which the daily intake of the 22 kinds of amino acids and the daily amino acid score (sufficiency rate) of the 9 kinds of amino acids are adjusted for age, sex, BMI, years of education, CES-D, presence or absence of history of hypertension, presence or absence of history of dyslipidemia, presence or absence of history of diabetes, and presence or absence of history of stroke. Specifically, model 1 is a model consisting of 10 explanatory variables, and the 10 explanatory variables are one of the daily intake of the 22 kinds of amino acids and the 9 kinds of daily amino acid scores (sufficiency rate), age, sex, BMI, years of education, CES-D, presence or absence of history of hypertension, presence or absence of history of dyslipidemia, presence or absence of history of diabetes, and presence or absence of history of stroke. Model 2 is a model consisting of 11 explanatory variables, in which lipid intake is added as an explanatory variable to model 1. Model 3 is a model in which energy intake is added as an explanatory variable to model 1. Model 4 is a model in which protein intake is added as an explanatory variable to model 1.

[0156] In the results of Model 4 shown in FIG. 17, significant results were obtained for Leu, Tyr, Trp, Val, Ser, SAA and BCAA, indicating that the daily intake of these seven amino acids is associated with future cognitive function (WAIS-R Adult Intelligence Scale (Knowledge)) in the subjects with the same protein intake.

[0157] In the results of models 1, 2, 3, and 4 shown in FIG. 18, it was found that the daily amino acid scores (sufficiency rate) of Ile, Leu, Trp, Val, and AAA were associated with future cognitive function (WAIS-R Adult Intelligence Scale (Knowledge)).

[0158] These results indicate that the amino acid content and quality of dietary amino acids are related to future cognitive function (WAIS-R Adult Intelligence Scale (Knowledge)) (model 2 shows that dietary amino acid intake is significantly related to cognitive function when lipid intake is the same, model 3 shows that energy intake is the same, and model 4 shows that protein intake is the same; in other words, considering model 4 as an example, there is a significant association between amino acids and cognitive function even when protein intake is the same, indicating that the proportion of amino acids that make up protein is important in the association between diet and cognitive function). EXAMPLES

[0159] We examined whether the use of information on two or more amino acids in the diet would increase the association with logical memory I (immediate recall) compared to the use of information on one amino acid in the diet. Using the same data as in Example 1 (specifically, the daily intake of the 22 amino acids and the score of logical memory I (immediate recall)), we selected amino acids for each of models 1 to 4 described in Example 1 using a stepwise method with a p-value of the variable selection criterion of 0.2, to create models using two or more amino acids corresponding to each of the models 1 to 4. The association with logical memory I was evaluated using Akaike's information criterion (AIC) for the models using two or more amino acids selected by the stepwise method and the model using one amino acid. For the models using one amino acid, the one with the smallest AIC value was adopted. The evaluation results are shown in FIG. 19. In all of models 1 to 4, the AIC of the models using two or more types of amino acids was smaller than the AIC of the model with the smallest AIC using one type of amino acid, indicating that using information on two or more types of amino acids in the diet results in a greater correlation with logical memory I than when using information on one type of amino acid in the diet. EXAMPLES

[0160] We examined whether the use of information on two or more amino acids in the diet would result in a greater association with logical memory II (delayed recall) than the use of information on one amino acid in the diet. Using the same data as in Example 2 (specifically, the daily intake of the 22 amino acids and the score for logical memory II (delayed recall)), we selected amino acids using a stepwise method with a variable selection criterion p-value of 0.2 for each of models 1 to 4 described in Example 2, and created models using two or more amino acids corresponding to each of the models 1 to 4. We evaluated the association with logical memory II using AIC for models using two or more amino acids selected by the stepwise method and models using one amino acid. The evaluation results are shown in FIG. 20. Models 1 to 3 could not be compared because no amino acids were selected by the stepwise method. In model 4, the AIC of the model using two or more amino acids was smaller than the AIC of the model using one amino acid with the smallest AIC, indicating that the use of information on two or more amino acids in the diet would result in a greater association with logical memory II than the use of information on one amino acid in the diet.

[0161] In addition, since no amino acids were selected by the stepwise method for models 1 to 3, the relevance to logical memory II was evaluated by AIC for the model obtained by adding the amino acid with the lowest correlation coefficient with the amino acid used to the model with the smallest AIC using one type of amino acid. The evaluation results are shown in FIG. 21. In all of models 1 to 4, the AIC of the model using two types of amino acids was smaller than the AIC of the model with the smallest AIC using one type of amino acid, suggesting the possibility that the relevance to logical memory II is higher by using information on two or more types of amino acids in a meal than by using information on one type of amino acid in a meal. EXAMPLES

[0162] The study involved 427 men and women (205 men and 222 women) aged between 60 and 82 years old between May 2002 and May 2004 who scored above 27 on the Mini-Mental State Examination (MMSE), an index of cognitive function, administered during the same period. Food was weighed and recorded on the meals actually consumed on each of the three consecutive days (two weekdays and one holiday) during the same period, and photographs of the meals before and after consumption were obtained from the subjects. A registered dietitian then coded each food based on the food composition table from the three-day food records and photos, calculated each person's nutritional intake over the three days, and calculated the average daily nutritional intake (specifically, the daily intake of each of the 22 amino acids (Ile, Leu, Lys, Met, Cys, Phe, Tyr, Thr, Trp, Val, His, Arg, Ala, Asp, Glu, Gly, Pro, Ser, Hydroxyproline, SAA, AAA, and BCAA)). The calculated daily intake of each of the 22 amino acids was then classified into quartiles by gender, and four groups were created, T1, T2, T3, and T4, in descending order of intake.

[0163] The MMSE scores obtained from the subjects were re-administered from July 2010 to July 2012, about 8 years after the aforementioned period, and the binary data indicating "27 points or less" or "higher than 27 points" were used as the objective variable. The binary data indicating whether the daily intake of the target amino acid corresponds to the T1 group, age, sex, BMI, years of education, CES-D, whether or not there is a history of hypertension, whether or not there is a history of dyslipidemia, whether or not there is a history of ischemic heart disease, whether or not there is a history of diabetes, whether or not there is a history of stroke, and daily protein intake were used as explanatory variables. Logistic regression was performed for each of the 22 amino acids, and the relationship between the daily intake of each of the 22 amino acids and the re-administered MMSE was examined. The evaluation results are shown in Figure 22. Significant odds ratios were obtained for Lys, Phe, Thr, and Ala, indicating that the daily intake of these four amino acids is related to future cognitive decline. In addition, the range of daily intakes (minimum and maximum intakes) of these four amino acids in the T1 group is shown in Figure 23. The daily intakes of these four amino acids that correspond to the T1 group (Lys: 4099 mg / day or less for men and 3353 mg / day or less for women, Phe: 3053 mg / day or less for men and 2596 mg / day or less for women, Thr: 2601 mg / day or less for men and 2183 mg / day or less for women, Ala: 3294 mg / day or less for men and 2688 mg / day or less for women) significantly increase the risk of future cognitive decline, so it was found that an intake higher than the maximum intake of the T1 group shown in Figure 23 is important.

[0164] The standard deviation, which indicates the variability of the data in the T1 group, was 546 mg / day for Lys, 349 mg / day for Phe, 313 mg / day for Thr, and 414 mg / day for Ala. If we assume that the data are normally distributed around the maximum intake of the T1 group observed this time, 95% of the data would be included in the range of the maximum intake of the T1 group observed this time ±1.96 × standard deviation. Therefore, it was considered appropriate to set the threshold within the range considered as the maximum intake of the T1 group shown in Figure 24. For Lys, the thresholds should be set at 3,029 mg / day or more and less than 5,170 mg / day for men and 2,282 mg / day or more and less than 4,423 mg / day for women; for Phe, the thresholds should be set at 2,369 mg / day or more and less than 3,737 mg / day for men and 1,912 mg / day or more and less than 3,280 mg / day for women; for Thr, the thresholds should be set at 1,988 mg / day or more and less than 3,215 mg / day for men and 1,570 mg / day or more and less than 2,797 mg / day for women; and for Ala, the thresholds should be set at 2,482 mg / day or more and less than 4,105 mg / day for men and 1,877 mg / day or more and less than 3,500 mg / day for women, and it is considered desirable to consume more than these thresholds. In addition, if we consider the case where the data is normally distributed with the maximum intake of group T1 observed this time as the center, it is considered that 68% of the data falls within the range of the maximum intake of group T1 observed this time ± the standard deviation, and therefore it was considered appropriate to set the threshold within the range considered as the maximum intake of group T1 shown in Figure 25.For Lys, the thresholds should be set at 3553 mg / day or more and less than 4645 mg / day for men and 2807 mg / day or more and less than 3899 mg / day for women; for Phe, the thresholds should be set at 2704 mg / day or more and less than 3402 mg / day for men and 2247 mg / day or more and less than 2945 mg / day for women; for Thr, the thresholds should be set at 2288 mg / day or more and less than 2914 mg / day for men and 1870 mg / day or more and less than 2496 mg / day for women; and for Ala, the thresholds should be set at 2880 mg / day or more and less than 3708 mg / day for men and 2274 mg / day or more and less than 3102 mg / day for women, and it is considered desirable to consume more than these thresholds.

[0165] In addition, in the "Dietary Reference Intakes for Japanese (2015 edition)" (Ministry of Health, Labor and Welfare website https: / / www.mhlw.go.jp / stf / seisakunitsuite / bunya / kenkou_iryou / kenkou / eiyou / syokuji_kijyun.html), "amino acid requirement (mg / kg body weight / day) relative to protein requirement (g / kg body weight / day)" is shown as the estimated average requirement of essential amino acids. When the body weight of the analysis group in Example 6 was calculated, the average value was 57.3 kg and the standard deviation was 9.1 kg. Therefore, considering the range of the average value ± 1.96 × standard deviation, the amino acid requirement in the body weight range of 39 kg to 75 kg was calculated. The calculation results are shown in Figure 26. Since there is a possibility that nutritional guidance will be provided comprehensively, including nutrients other than amino acids, in the field of nutritional guidance, it is considered possible to change the lower limit value shown in Figure 24 to the value shown in Figure 26 for Lys and Thr. For example, for Lys, it was considered desirable to set the threshold value in the range of 3029 mg / day or more and less than 5170 mg / day for men from FIG. 24, but considering the situation of nutritional guidance and taking into account the information in FIG. 26, it is also possible to set the threshold value by combining the values ​​in FIG. 24, 25, and 26, such as in the range of 1170, 1719, or 2250 mg / day or more and 4099 or less than 5170 mg / day. Note that Phe is not described as a single amino acid in the "Dietary Reference Intakes for Japanese (2015 Edition)," but the required amount of AAA (aromatic amino acid) including Phe is described. Therefore, for Phe, if the AAA value of 975, 1433, or 1875 mg / day shown in FIG. 26 is taken, at least the required amount of Phe is met, so it is also possible to set the threshold value by combining the values ​​in FIG. 24, 25, and 26, such as substituting this AAA value as the lower limit of Phe. In addition, taking into consideration the range of the mean ± standard deviation (the range that contains 68% of the data in the case of normal distribution), the amino acid requirements for those with body weights in the range of 48 kg to 66 kg were calculated. The calculation results are shown in FIG.Considering the range of the mean ± standard deviation as the basis, the values ​​shown in Figure 26 may be used as the lower limit of the amino acid requirement, as in the case of the mean ± 1.96 × standard deviation described above. Figures 27 and 28 show the results of correcting the results of Figures 24 and 25 with an average body weight of 57.3 kg. These values ​​corrected by body weight may be used as threshold values. EXAMPLES

[0166] The subjects were 2122 men and women (1054 men and 1068 women) aged 40 to 85 years old from June 2004 to June 2006. The subjects were given a record sheet on which the food was weighed and recorded for each meal actually consumed during three consecutive days (two weekdays and one holiday) during the period, and photos taken before and after the consumption were obtained. A registered dietitian coded the obtained three-day meal record sheet and photos based on the food composition table, calculated each person's nutritional intake for the three days, and calculated the average nutritional intake per day (specifically, the amino acid scores for breakfast, lunch, and dinner). The amino acid scores for breakfast, lunch, and dinner obtained were then classified into quartiles by gender, and four groups were generated, T1, T2, T3, and T4, in descending order of intake. In this embodiment, the amino acid score refers to the protein digestibility corrected amino acid score (PDCAAS).

[0167] A covariance analysis was performed on a model (Model 1) in which the score of logical memory II (delayed recall) of the WMS-R Wechsler Memory Test, which is one of the cognitive function indicators administered to the subject during the period, was used as the objective variable, and the explanatory variables were the quartile group of the amino acid score of breakfast, the quartile group of the amino acid score of lunch, the quartile group of the amino acid score of dinner, age, sex, BMI, years of education, CES-D, smoking history, employment status, whether or not living alone, whether or not having had a stroke, whether or not having hypertension, whether or not having dyslipidemia, whether or not having ischemic heart disease, and whether or not having diabetes. In addition, the three explanatory variables, the quartile group, are set to a value that means that the score corresponds to the T1 group, a value that means that the score corresponds to the T2 group, a value that means that the score corresponds to the T3 group, or a value that means that the score corresponds to the T4 group. A covariance analysis was also performed on Model 2, in which daily lipid intake was added as an explanatory variable to Model 1, Model 3, in which daily energy intake was added as an explanatory variable to Model 1, and Model 4, in which daily protein intake was added as an explanatory variable to Model 1. The evaluation results are shown in Figures 29 and 30. Figure 29 shows that significant results were obtained in the amino acid score of lunch, and Figure 30 shows that as the amino acid score of lunch increases, the score of Logical Memory II also increases.

[0168] In addition, for the quartile groups of amino acid scores for lunch, (1) comparisons were made between the "T1 group" and the "T2 to T4 groups", (2) comparisons between the "T1 and T2 groups" and the "T3 and T4 groups", and (3) comparisons between the "T1 to T3 groups" and the "T4 group", and the significance of the statistical hypothesis tests for each comparison was examined. The results of the examination are shown in Figure 31, and the range of amino acid scores for lunch for the T1 to T4 groups is shown in Figure 32. In the comparison of (2), significant differences were observed in models 1 to 3, and in the comparison of (3), significant differences were observed in models 1 to 4. Therefore, it is considered desirable to consume an amino acid score for lunch that is equal to or higher than the maximum amino acid score of the T2 group (85.7 (86) or higher for men, 86.9 (87) or higher for women) or equal to or higher than the maximum amino acid score of the T3 group (96.3 (96) or higher for men, 96.4 (96) or higher for women).

[0169] The standard deviation, which indicates the dispersion of the data, was 13.8 for the "T1 group and T2 group" in the comparison of (2), and 15.4 for the "T1 group to T3 group" in the comparison of (3). Therefore, if we consider that the data is normally distributed around the quantile observed this time, 95% of the data is considered to be included in the range of the quantile observed this time ±1.96 × standard deviation, and therefore it is considered appropriate to set the threshold within the range of the amino acid score shown in Figure 33. Based on the results of the comparison of (2), the threshold of the amino acid score of lunch for men should be set in the range of 58.7 (59) or more and 100 or less, and the threshold of the amino acid score of lunch for women should be set in the range of 59.9 (60) or more and 100 or less. Based on the results of the comparison of (3), the threshold of the amino acid score of lunch for men should be set in the range of 66.1 (66) or more and 100 or less, and the threshold of the amino acid score of lunch for women should be set in the range of 66.2 (66) or more and 100 or less, and it is considered desirable to consume more than these thresholds. In addition, if we consider the case where the data is normally distributed around the quantile observed this time, 68% of the data is expected to fall within the range of the quantile observed this time ± the standard deviation, and therefore it is considered appropriate to set the threshold within the amino acid score range shown in Figure 34. Based on the results of the comparison in (2), the threshold amino acid score for men's lunch should be set in the range of 71.9 (72) or more and 99.5 (100) or less, and the threshold amino acid score for women should be set in the range of 73.1 (73) or more and 100 or less, and based on the results of the comparison in (3), the threshold amino acid score for men's lunch should be set in the range of 80.9 or more and 100 or less, and the threshold amino acid score for women should be set in the range of 81.0 (81) or more and 100 or less, and it is considered desirable to consume more than these thresholds. EXAMPLES

[0170] The subjects were 418 men and women (202 men, 216 women) aged 60 to 82 years old from May 2002 to May 2004, and had a cognitive function index MMSE score of more than 27 points during the period. The subjects were given a record sheet on which the food was weighed and recorded, and photographs of the food before and after intake for each meal actually consumed for three consecutive days (two weekdays and one holiday) during the period. A registered dietitian then coded the obtained three-day meal record sheet and photographs based on a food composition table, calculated each person's nutritional intake for the three days, and calculated the average nutritional intake per day (specifically, the amino acid scores for breakfast, lunch, and dinner). The amino acid scores for breakfast, lunch, and dinner were then classified into tertiles by gender, and three groups, T1, T2, and T3, were generated in descending order of intake. In this embodiment, the amino acid score refers to the protein digestibility corrected amino acid score (PDCAAS).

[0171] The binary data, meaning "27 points or less" or "higher than 27 points", obtained from the MMSE scores administered to the subjects again between July 2006 and July 2008, about four years after the aforementioned period, were used as the objective variable, and the binary data of whether the amino acid score of breakfast corresponds to the T1 group or not, the binary data of whether the amino acid score of lunch corresponds to the T1 group or not, the binary data of whether the amino acid score of dinner corresponds to the T1 group or not, age, sex, BMI, years of education, CES-D, history of hypertension, history of ischemic heart disease, history of dyslipidemia, history of diabetes, history of stroke, and daily protein intake were used as explanatory variables (Model 1). Logistic regression was performed to examine the association between the amino acid scores of breakfast, lunch, and dinner and the repeated MMSE. Logistic regression was also performed on model 2, which added daily fat intake as an explanatory variable to model 1, model 3, which added daily energy intake as an explanatory variable to model 1, and model 4, which added daily protein intake as an explanatory variable to model 1, to examine the association between the amino acid scores of breakfast, lunch, and dinner and the MMSE that was performed again. The evaluation results are shown in Figure 35. A significant odds ratio was obtained for the binary data of whether the amino acid score of breakfast corresponds to the T1 group, indicating that the amino acid score of breakfast is related to future cognitive decline. In addition, the range of the amino acid score of breakfast in the T1 group (minimum score and maximum score) is shown in Figure 36. Since the amino acid score of breakfast corresponds to the T1 group significantly increases the risk of future cognitive decline, it was found that a breakfast amino acid score higher than the maximum amino acid score of the T1 group shown in Figure 36 (90.3 (90) for men, 88.9 (90) for women) is important.

[0172] The standard deviation, which indicates the dispersion of the data, was 12.0 for the breakfast amino acid score. If the data were to be normally distributed around the quantile observed this time, 95% of the data would be included in the range of the quantile observed this time ±1.96 × standard deviation. Therefore, it was considered appropriate to set the threshold within the range of the amino acid score shown in FIG. 37. For the amino acid score of a men's breakfast, the threshold would be set to a range of 66.8 (67) or more and 100 or less, and for the amino acid score of a women's breakfast, the threshold would be set to a range of 65.4 (66) or more and 100 or less, and it would be desirable to consume more than the threshold. In addition, if the data were to be normally distributed around the quantile observed this time, 68% of the data would be included in the range of the quantile observed this time ±standard deviation. Therefore, it was considered appropriate to set the threshold within the range of the amino acid score shown in FIG. 38. For the amino acid score of a men's breakfast, the threshold would be set to a range of 78.3 (78) or more and 100 or less, and for the amino acid score of a women's breakfast, the threshold would be set to a range of 76.9 (77) or more and 100 or less, and it would be desirable to consume more than the threshold. [Industrial Applicability]

[0173] INDUSTRIAL APPLICABILITY As described above, the present invention can be widely implemented in many industrial fields, particularly in the fields of pharmaceuticals, food, medicine, etc., and is extremely useful. [Explanation of symbols]

[0174] 100 Evaluation device (including calculation device) 102 Control section 102a Acquisition Department 102b Specified part 102c Expression Creation Section 102d Evaluation Section 102d1 Calculation part 102d2 Converter 102d3 Generation part 102d4 Classification section 102e Result output section 102f Transmitter 104 Communication interface section 106 Storage section 106a Amino acid related data file 106b Index status information file 106c Specified index status information file 106d type related information database 106d1 Formula File 106e Evaluation result file 108 Input / Output Interface Section 112 Input Devices 114 Output Device 200 Client device (terminal device (information communication terminal device)) 300 Network 400 POS System 500 Database device

Claims

[Claim 1] an evaluation step of evaluating said food in terms of cognitive function using values ​​of the amounts in the food of at least one amino acid of Met, Cys, SAA, AAA and BCAA, or values ​​of said formula calculated using a formula comprising variables into which the values ​​of said amounts are substituted and said values ​​of said amounts; An evaluation method characterized by:

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