Body odor risk calculation method, calculation apparatus, calculation program, calculation system, and method for presenting countermeasures against body odor occurrence risk

Abstract

To provide a body odor risk calculation method, a calculation apparatus, a calculation program, and a calculation system enabling calculation of the risk of occurrence of body odor of a subject or enabling presentation of countermeasures, as well as to provide a method for presenting countermeasures against body odor occurrence risk according to the risk of body odor occurrence.SOLUTION: A body odor risk calculation system 10 includes a body odor risk calculation apparatus 100, a storage unit 200, and a display unit 220. The body odor risk calculation apparatus 100 includes a detection unit 120 that detects a microbiota from a sample acquired from an object such as a human body, and a calculation unit 140 that calculates a risk of body odor occurrence based on bacteria included in the detected microbiota. The detection unit 120 amplifies the acquired microbiota by PCR, performs 16S rRNA microbiota analysis with a sequencer, and estimates bacterial species and copy number. The calculation unit 140 is, for instance, a computer configured to implement and execute, as a computer program, at least a part of the body odor risk calculation method.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a body odor risk calculation method, a calculation device, a calculation program, a calculation system, and a method for presenting measures to deal with the risk of body odor occurrence, which provide information on the risk of body odor occurrence. [Background technology]

[0002] A conventional method is known in which the normal skin flora of multiple subjects is measured, a correlation diagram between the abundance ratio of Corynebacteria and skin parameters is created in advance as a population, and this is used to measure the normal skin flora of each individual subject, and the abundance ratio of Corynebacteria is compared with the correlation diagram to predict skin texture and wrinkles (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-62887 Summary of the Invention [Problem to be solved by the invention]

[0004] However, because the relationship between normal skin flora and body odor was unknown, it was not possible to calculate the risk of body odor or to suggest measures to deal with body odor.

[0005] The present invention has been made in consideration of at least one of these problems, and aims to provide a body odor risk calculation method, calculation device, calculation program, and calculation system that can calculate a subject's risk of body odor occurrence or present countermeasures, as well as a body odor occurrence risk countermeasure presentation method that presents countermeasures based on the risk of body odor occurrence. [Means for solving the problem]

[0006] The present invention provides a body odor risk calculation method, calculation device, calculation program, and calculation system that can calculate a subject's risk of body odor occurrence or present countermeasures, as well as a body odor occurrence risk countermeasure presentation method that presents countermeasures based on the risk of body odor occurrence.

[0007] Specific embodiments of the present invention are as follows: [Invention 1] to [Invention 10], but are not limited to these. [Invention 1] A detection step of detecting bacterial flora from a skin resident bacterial flora sample obtained from a subject; a calculation step of calculating the risk of body odor occurrence based on bacteria contained in the detected bacterial flora; A method for calculating the risk of body odor generation, including: [Invention 2] the detecting step includes detecting the genus Corynebacterium or the genus Anaerobic Corynebacterium, and Propionibacterium acnes contained in the sample; the calculating step calculates a risk of body odor occurrence based on the Corynebacterium genus or the Anaerobic Coccus genus and the Propionibacterium acnes; The calculation method described in Invention 1. [Invention 3] The calculation method according to Invention 2, wherein the calculation step calculates that the risk of body odor occurrence is high when the abundance ratio of the Propionibacterium acnes in the bacterial flora is less than a first threshold value and the logarithmic value of the copy number of the genus Corynebacteria is equal to or greater than a second threshold value or the logarithmic value of the copy number of the genus Anaerobic Coccus is equal to or greater than a third threshold value, and / or the calculation step calculates that the risk of body odor occurrence is low when the abundance ratio of the Propionibacterium acnes in the bacterial flora is equal to or greater than a first threshold value and the logarithmic value of the copy number of the genus Corynebacteria is less than the second threshold value or the logarithmic value of the copy number of the genus Anaerobic Coccus is less than a third threshold value. [Invention 4] The calculation method according to Invention 2 or 3, wherein the calculation step calculates that the risk of body odor generation is medium when the abundance ratio of Propionibacterium acnes in the bacterial flora is less than a first threshold value and the logarithmic value of the copy number of the genus Corynebacteria is less than a second threshold value or the logarithmic value of the copy number of the genus Anaerobic Coccus is less than a third threshold value, and / or the calculation step calculates that the risk of body odor generation is medium when the abundance ratio of Propionibacterium acnes in the bacterial flora is equal to or greater than a first threshold value and the logarithmic value of the copy number of the genus Corynebacteria is equal to or greater than a second threshold value or the logarithmic value of the copy number of the genus Anaerobic Coccus is equal to or greater than a third threshold value. [Invention 5] The calculation method according to Invention 3 or 4, wherein the second threshold is determined based on the copy number of the Corynebacterium genus and the odor intensity of the sole odor. [Invention 6] The calculation method according to Invention 3 or 4, wherein the third threshold is determined based on the copy number of the Anaerobic Bacteria and the odor intensity of the sour odor. [Invention 7] A method for presenting measures to deal with body odor risk, which presents measures to deal with body odor based on the risk of body odor occurrence calculated using the method for calculating the risk of body odor occurrence according to any one of inventions 1 to 6. [Invention 8] a detection unit for detecting bacterial flora contained in a sample obtained from the body; a calculation unit that calculates the risk of body odor occurrence based on the bacteria contained in the detected bacterial flora; Body odor risk calculation device. [Invention 9] a detection step for detecting the bacterial flora in a sample obtained from the body; a calculation step of calculating the risk of body odor occurrence based on bacteria contained in the detected bacterial flora; A computer-executable body odor generation risk calculation program comprising: [Invention 10] a detection unit for detecting bacterial flora contained in a skin resident bacterial flora sample obtained from a subject; a calculation unit that calculates the risk of body odor occurrence based on bacteria contained in the detected bacterial flora; a display unit that displays the occurrence risk; a memory unit that stores data used to calculate the risk of body odor occurrence; A body odor generation risk calculation system comprising: [Effects of the Invention]

[0008] According to the present invention, there are provided a body odor risk calculation method, calculation device, calculation program, and calculation system capable of calculating a subject's risk of body odor occurrence, as well as a body odor occurrence risk countermeasure presentation method that presents countermeasures based on the risk of body odor occurrence. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a schematic diagram showing an example of a body odor risk calculation system according to the present invention. [Figure 2] 1 is a graph showing the relationship between Corynebacterium spp. and Propionibacterium acnes and foot odor. [Figure 3] 1 is a graph showing the relationship between the genus Anerococcus and Propionibacterium acnes and foot odor. [Figure 4] 10 is a flowchart illustrating an example of a body odor risk calculation process. DETAILED DESCRIPTION OF THE INVENTION

[0010] A body odor risk calculation system 10 according to one embodiment of the present invention will be described. Referring to Fig. 1, the body odor risk calculation system 10 mainly comprises a body odor risk calculation device 100 (hereinafter also referred to as a calculation device), a storage unit 200, and a display unit 220.

[0011] The body odor risk calculation device 100 mainly comprises a detection unit 120 that detects bacterial flora from a sample obtained from a body, for example, a human body, and a calculation unit 140 that calculates the risk of body odor occurrence based on the bacteria contained in the detected bacterial flora.

[0012] The detection unit 120 amplifies the acquired bacterial flora by PCR and performs 16S rRNA bacterial flora analysis using a sequencer. That is, the 16S rRNA gene contained in the DNA obtained from the sample is analyzed, and the gene sequence is compared with known gene sequences to estimate the bacterial species corresponding to the gene sequence and the copy number of that bacterial species.

[0013] The calculation unit 140 is, for example, a computer, which implements and executes at least a part of a body odor generation risk calculation method described below as a computer program.

[0014] The storage unit 200 is electrically connected to the calculation device 100, for example, a hard disk for recording data, or is connected via a network, for example, a data server, and stores data used to calculate the risk of body odor generation, i.e., a plurality of threshold values described below. The threshold values will be described later. The storage unit 200 may be provided inside the calculation device 100.

[0015] Display unit 220 is a device such as a display electrically connected to calculation device 100 or a tablet connected via a network, and displays the risk of body odor generation and / or countermeasures described below. Display unit 220 may also be provided in calculation device 100.

[0016] Next, we will explain the threshold value. The inventors classified the axillary odor of 94 subjects into six levels of odor intensity, from 0 to 5, by sensory evaluation, and obtained samples of resident skin flora and skin gas from 62 subjects who had an odor intensity ranging from 4 to 2.

[0017] The resident skin flora was amplified by PCR and then analyzed for 16S rRNA gene expression to determine the proportion of bacterial species present in all subjects. The bacteria with the top 20 bacterial copy numbers were analyzed and used as the bacterial flora composition ratio. Regarding odor intensity, the odor intensity of each of 25 odor components was determined for skin gas collected from the subjects' skin. The odors were then divided into multiple odor categories, and the odor intensity was calculated for each odor category. Odor intensity was calculated by logarithmically summing the odor scale for each odor category based on the Weber-Pfiffner law. The odor scale (m / h, Odor level) was calculated using the following formula: Odor level=E / Odor threshold where E is the emission flux (ng / (cm 2 h), Odor threshold (ng / m 3 ) odor classifications include, for example, foot odor consisting of butanal, isovaleric aldehyde, valeric aldehyde, butyric acid, isovaleric acid, and valeric acid, and sour odor consisting of acetic acid and propionic acid; the classification names do not limit the location of the odor. Multivariate analysis was then performed on the odor intensity and bacterial composition ratio for each odor component or odor category to investigate and explore correlations between odor intensity and bacterial composition ratio. Results indicated that for sour odors, a higher composition ratio or copy number of the genus Anaerobic Coccus increased the odor intensity. For sour odors, a higher composition ratio or copy number of the genus Corynebacterium increased the odor intensity. Furthermore, for both sour and sour odors, a higher composition ratio of Propionibacterium acnes decreased the odor intensity of both sour and sour odors. Details of the correlations are shown in Table 1. Missing values were handled using the pairwise method. [Table 1]

[0018] This led to the discovery that the genus Anaerobic Odor may be the main cause of sour odor, the genus Corynebacterium may be the main cause of foot odor, and that Propionibacterium acnes is an odor-suppressing factor for both armpit and foot odor.

[0019] Furthermore, we investigated the important factors of the axillary bacterial flora as explanatory (predictor) variables for the intensity of sour odor and foot odor. Using partition analysis based on regression trees (JMP ver. 17), we examined variables that may be related to each odor intensity, using the bacterial flora abundance ratio or bacterial copy number as explanatory variables. We found that for foot odor intensity, the logarithm of the copy number of Corynebacterium genus was 4.2, and for sour odor intensity, the logarithm of the copy number of Anaerobic Bacteria genus was 3.7. For the above two odor intensities, the bacterial flora composition ratio (abundance ratio) of Propionibacterium acnes was used as the benchmark, with 1% as the benchmark. The odor intensities could be divided into two groups based on their high and low odor intensity.

[0020] Figure 2 shows boxplots showing the relationship between odor intensity and the logarithm of the copy number of Corynebacterium genus less than 4.2 and 4.2 or more for samples where the presence rate of Propionibacterium acnes was less than 1% and 1% or more.

[0021] When the presence rate of Propionibacterium acnes is less than 1%, samples with a logarithmic value of the copy number of the genus Corynebacterium of 4.2 or more are shown in the leftmost box plot (hereinafter referred to as group 1 in Figure 2). The number of samples (N number) in group 1 is 41. When the presence rate of Propionibacterium acnes is 1% or more, samples with a logarithmic value of the copy number of the genus Corynebacterium of 4.2 or more are shown in the second box plot from the left (hereinafter referred to as group 2 in Figure 2). The number of samples (N number) in group 2 is 5. When the presence rate of Propionibacterium acnes is less than 1%, samples with a logarithmic value of the copy number of the genus Corynebacterium of less than 4.2 are shown in the third box plot from the left (hereinafter referred to as group 3 in Figure 2). The number of samples (N number) in group 3 is 4. When the proportion of Propionibacterium acnes present was 1% or higher, samples with a logarithmic value of the Corynebacterium copy number of less than 4.2 were shown as the boxplot on the far right (hereinafter referred to as Group 4 in Figure 2). The number of samples in Group 4 (N number) was 12. In each boxplot, the black horizontal line in the box indicates the median odor intensity, and the circle indicates the mean.

[0022] When comparing odor intensity between these groups, Group 1, in which the proportion of Propionibacterium acnes was less than 1% and the logarithm of the Corynebacterium copy number was 4.2 or greater, had a significantly higher foot odor intensity than Group 4, in which the proportion of Propionibacterium acnes was 1% or greater and the logarithm of the Corynebacterium copy number was less than 4.2 (p=0.0037).Furthermore, Group 1 tended to have a higher foot odor intensity than Group 2, in which the proportion of Propionibacterium acnes was 1% or greater and the logarithm of the Corynebacterium copy number was 4.2 or greater, and Group 3, in which the proportion of Propionibacterium acnes was less than 1% and the logarithm of the Corynebacterium copy number was less than 4.2 (p=0.090 and p=0.064, respectively).

[0023] From the above, it was found that the risk of odor was highest when the presence rate of Propionibacterium acnes was less than 1% and the logarithm of the copy number of Corynebacterium spp. was 4.2 or higher (Group 1), and the risk of odor was lowest when the presence rate of Propionibacterium acnes was 1% or higher and the logarithm of the copy number of Corynebacterium spp. was less than 4.2 (Group 4). The risk of odor was considered to be moderate when the presence rate of Propionibacterium acnes was 1% or higher and the logarithm of the copy number of Corynebacterium spp. was 4.2 or higher (Group 2), and when the presence rate of Propionibacterium acnes was less than 1% and the logarithm of the copy number of Corynebacterium spp. was less than 4.2 (Group 3).

[0024] In this embodiment, based on the odor intensity obtained based on the abundance ratio of Propionibacterium acnes and the logarithm of the copy number of Corynebacterium genus, a first threshold value of 1% was determined as the abundance ratio of Propionibacterium acnes (described below), and a second threshold value of 4.2 was determined as the logarithm of the copy number of Corynebacterium genus (described below). In other words, the second threshold value was determined based on the copy number of Corynebacterium genus and the odor intensity of the sole odor.

[0025] Figure 3 shows box plots showing the relationship between odor intensity and the logarithm of the copy number of the genus Acne in samples where the proportion of Propionibacterium acnes was less than 1% and 1% or more, respectively, and where the logarithm of the copy number of the genus Acne in samples where the copy number was less than 3.7 and 3.7 or more.

[0026] When the presence rate of Propionibacterium acnes is less than 1%, samples with a logarithmic value of the copy number of the genus Anaerococcus of 3.7 or more are shown in the leftmost box plot (hereinafter referred to as group 1 in Figure 3). The number of samples (N number) in group 1 is 33. When the presence rate of Propionibacterium acnes is 1% or more, samples with a logarithmic value of the copy number of the genus Anaerococcus of 3.7 or more are shown in the second box plot from the left (hereinafter referred to as group 2 in Figure 3). The number of samples (N number) in group 2 is 5. When the presence rate of Propionibacterium acnes is less than 1%, samples with a logarithmic value of the copy number of the genus Anaerococcus of less than 3.7 are shown in the third box plot from the left (hereinafter referred to as group 3 in Figure 3). The number of samples (N number) in group 3 is 12. When the proportion of P. acnes present was 1% or higher, samples with a logarithmic value of the copy number of the genus Anaerobic Coliforme less than 3.7 were shown as the boxplot on the far right (hereinafter referred to as group 4 in Figure 3). The number of samples in group 4 (N number) was 11. Missing values were handled using the listwise method.

[0027] When comparing odor intensities between these groups, Group 4, in which the proportion of Propionibacterium acnes was 1% or more and the logarithm of the copy number of Anaerococcus was less than 3.7, had significantly lower sour odor intensity than Group 1, in which the proportion of Propionibacterium acnes was less than 1% and the logarithm of the copy number of Anaerococcus was 3.7 or more, and Group 2, in which the proportion of Propionibacterium acnes was 1% or more and the logarithm of the copy number of Anaerococcus was 3.7 or more (p=0.0007, p=0.020, respectively).Furthermore, Group 4 tended to have lower sour odor intensity than Group 3, in which the proportion of Propionibacterium acnes was less than 1% and the logarithm of the copy number of Anaerococcus was less than 3.7 (p=0.12).

[0028] From the above, it was found that the risk of odor was highest when the presence rate of P. acnes was less than 1% and the logarithm of the copy number of the Anaerobic genus was 3.7 or higher (group 1), and the risk of odor was lowest when the presence rate of P. acnes was 1% or higher and the logarithm of the copy number of the Anaerobic genus was less than 3.7 (group 4). Based on the results of the above intergroup analysis and partition analysis, the risk of odor was considered to be medium when the presence rate of P. acnes was 1% or higher and the logarithm of the copy number of the Anaerobic genus was 3.7 or higher (group 2), and when the presence rate of P. acnes was less than 1% and the logarithm of the copy number of the Anaerobic genus was less than 3.7 (group 3).

[0029] In this embodiment, based on the odor intensity obtained based on the abundance ratio of Propionibacterium acnes and the logarithmic value of the copy number of the genus Anaerobic Coli, a first threshold value of 1% was determined as the abundance ratio of Propionibacterium acnes (described below), and a logarithmic value of the copy number of the genus Anaerobic Coli (described below) of 3.7 was determined as the third threshold value (described below). In other words, the third threshold value was determined based on the copy number of the genus Anaerobic Coli and the odor intensity of the sour odor.

[0030] Based on the above, a method for calculating the risk of body odor generation according to one embodiment of the present invention will now be described. Figure 4 is a flowchart showing the method for calculating the risk of body odor generation.

[0031] First, in step S1, a bacterial flora is obtained from a test subject. The test subject or a tester collects the bacterial flora from the test subject's armpit or sole using a collection device. The collected bacterial flora is also called a skin resident bacterial flora sample.

[0032] In the next step S2, the obtained bacterial flora is amplified by PCR and subjected to 16S rRNA analysis using a sequencer. The bacterial species and copy number contained in the sample are estimated from the DNA obtained from the sample using the sequence of the 16S rRNA gene possessed by the bacteria. That is, the copy numbers of Corynebacterium and Anaerococcus, as well as the proportion of Propionibacterium acnes in the bacterial flora, are determined. Step S2 constitutes at least a part of the detection step.

[0033] In the next step S3, it is determined whether the proportion of Propionibacterium acnes flora is less than 1%. If it is less than 1%, the process proceeds to step S4. If it is not less than 1%, that is, if it is 1% or more, the process proceeds to step S5.

[0034] In step S4, it is determined whether the logarithm of the copy number of Corynebacterium is 4.2 or more, or whether the logarithm of the copy number of Anaerobic Bacteria is 3.7 or more, where 4.2 constitutes the second threshold and 3.7 constitutes the third threshold. If the logarithm of the copy number of the genus Corynebacterium is 4.2 or more, and if the logarithm of the copy number of the genus Anaerobic bacteria is 3.7 or more, the process proceeds to step S41. In step S41, the risk of odor generation is calculated to be high, and output to display unit 220. Display unit 220 displays that the risk of odor generation is high. In step S4, if the logarithm of the copy number of the genus Corynebacterium is not 4.2 or more, i.e., less than 4.2, and if the logarithm of the copy number of the genus Anaerobic bacteria is not 3.7 or more, i.e., less than 3.7, the process proceeds to step S42. In step S42, the risk of odor generation is calculated to be medium, and output to display unit 220. Display unit 220 displays that the risk of odor generation is medium.

[0035] In step S5, it is determined whether the logarithm of the copy number of the genus Corynebacterium is 4.2 or more, or whether the logarithm of the copy number of the genus Anaerobic Coliform is 3.7 or more. If the logarithm of the copy number of the genus Corynebacterium is 4.2 or more, or if the copy number of the genus Anaerobic Coliform is 3.7 or more, the process proceeds to step S42. In step S42, the risk of odor generation is calculated to be medium, and this is output to display unit 220. Display unit 220 displays that the risk of odor generation is medium.

[0036] In step S5, if the logarithm of the copy number of the genus Corynebacterium is not 4.2 or more, i.e., less than 4.2, and if the logarithm of the copy number of the genus Anaerobic Bacteria is not 3.7 or more, i.e., less than 3.7, the process proceeds to step S51. In step S51, the risk of odor generation is calculated to be low, and output to display unit 220. Display unit 220 displays that the risk of odor generation is low.

[0037] Then, the process ends. Note that steps S3, S4, S41, S42, S5, and S51 constitute at least a part of the calculation step.

[0038] Furthermore, it is also possible to present measures to deal with body odor based on the risk of body odor calculated using the body odor risk calculation method. This method is a method for presenting measures to deal with body odor risk, and the measures include various medicines and their prescription methods, or methods for caring for areas where body odor occurs, such as the skin, and these are presented to the subject. An example of a measure will be described below.

[0039] The body odor risk calculation device 100 presents, in other words, displays on the display device 220, techniques to be taken in the morning, afternoon, and evening according to the risk of odor generation.

[0040] For example, when the calculation unit 140 calculates that the risk of the subject developing axillary odor is high, it suggests applying an anti-armpit odor agent (such as a balm-type agent containing a disinfectant and astringent and having a tight fit) in the morning, suggesting the use of an antiperspirant sheet and / or reapplication of an anti-armpit odor agent in the daytime, and suggesting the use of a body soap containing a disinfectant ingredient and / or skin care for the armpit area in the evening.

[0041] When the calculation unit 140 calculates that the subject's risk of developing odor is medium, it suggests applying an anti-armpit odor agent (spray type or roll-on type, etc.) in the morning, suggesting the use of an antiperspirant sheet and / or reapplication of an anti-armpit odor agent in the daytime, and suggesting skin care for the armpit area in the evening.

[0042] When the calculation unit 140 calculates that the risk of the subject developing odor is low, it suggests applying an anti-armpit odor agent (spray type or roll-on type, etc.) in the morning, suggests using an antiperspirant sheet as needed during the day, and does not suggest it at night.

[0043] According to this embodiment, a body odor risk calculation method, calculation device, calculation program, and calculation system capable of calculating a subject's risk of body odor occurrence, as well as a body odor occurrence risk countermeasure presentation method for presenting countermeasures based on the risk of body odor occurrence, are obtained.

[0044] At least a part of the body odor generation risk calculation method and the body odor generation risk countermeasure presentation method is realized as a computer program, and the computer program can be stored in, for example, a non-volatile recording medium.

[0045] The sizes of the components shown in the specification and drawings are merely examples and are not limited to these. Furthermore, the materials of the components are merely examples and are not limited to these.

[0046] Although embodiments of the present invention have been described herein with reference to the accompanying drawings, it will be apparent to those skilled in the art that modifications may be made in the structure and relationship of the parts without departing from the scope and spirit of the invention as described. [Explanation of symbols]

[0047] 10 Body odor risk calculation system 100 Body odor risk calculation device 120 Detector 140 Calculation Department 200 Storage section 220 Display section

Claims

1. A detection step of detecting bacterial flora from a skin resident bacterial flora sample obtained from a subject; a calculation step of calculating the risk of body odor occurrence based on bacteria contained in the detected bacterial flora; A method for calculating the risk of body odor generation, including:

2. the detecting step includes detecting the genus Corynebacterium or the genus Anaerobic Corynebacterium, and Propionibacterium acnes contained in the sample; the calculating step calculates a risk of body odor occurrence based on the Corynebacterium genus or the Anaerobic Coccus genus and the Propionibacterium acnes; The calculation method according to claim 1 .

3. 3. The calculation method according to claim 2, wherein the calculation step calculates that the risk of body odor occurrence is high when the abundance ratio of the Propionibacterium acnes in the bacterial flora is less than a first threshold value and the logarithmic value of the copy number of the Corynebacteria genus is equal to or greater than a second threshold value or the logarithmic value of the copy number of the Anaerobic Oxidant is equal to or greater than a third threshold value; and / or the calculation step calculates that the risk of body odor occurrence is low when the abundance ratio of the Propionibacterium acnes in the bacterial flora is equal to or greater than a first threshold value and the logarithmic value of the copy number of the Corynebacteria genus is less than a second threshold value or the logarithmic value of the copy number of the Anaerobic Oxidant is less than a third threshold value.

4. 3. The calculation method according to claim 2, wherein the calculating step calculates that the risk of body odor occurrence is medium when the abundance ratio of the Propionibacterium acnes in the bacterial flora is less than a first threshold value and the logarithmic value of the copy number of the Corynebacteria genus is less than a second threshold value or the logarithmic value of the copy number of the Anaerobic genus is less than a third threshold value; and / or the calculating step calculates that the risk of body odor occurrence is medium when the abundance ratio of the Propionibacterium acnes in the bacterial flora is equal to or greater than a first threshold value and the logarithmic value of the copy number of the Corynebacteria genus is equal to or greater than a second threshold value or the logarithmic value of the copy number of the Anaerobic genus is equal to or greater than a third threshold value.

5. The calculation method according to claim 3 or 4, wherein the second threshold is determined based on the copy number of the Corynebacterium genus and the odor intensity of the sole odor.

6. The calculation method according to claim 3 or 4, wherein the third threshold is determined based on the copy number of the genus Anaerobic Bacteria and the odor intensity of the sour odor.

7. A method for suggesting measures to deal with body odor risk, which suggests measures to deal with body odor based on the risk of body odor occurrence calculated using the method for calculating the risk of body odor occurrence according to any one of claims 1 to 4.

8. a detection unit for detecting bacterial flora contained in a skin resident bacterial flora sample obtained from a subject; a calculation unit that calculates the risk of body odor occurrence based on the bacteria contained in the detected bacterial flora; Body odor risk calculation device.

9. a detection step for detecting the bacterial flora in a sample obtained from the body; a calculation step of calculating the risk of body odor occurrence based on bacteria contained in the detected bacterial flora; A computer-executable body odor generation risk calculation program comprising:

10. a detection unit for detecting bacterial flora contained in a skin resident bacterial flora sample obtained from a subject; a calculation unit that calculates the risk of body odor occurrence based on bacteria contained in the detected bacterial flora; a display unit that displays the occurrence risk; a memory unit that stores data used to calculate the risk of body odor occurrence; A body odor generation risk calculation system comprising:

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