Method and system for evaluating infant development state based on intestinal flora and application

Abstract

The invention relates to a divisional application with the application number of 202411328371.2, discloses a method and system for evaluating the growth and development state of 0-6-year-old children based on intestinal flora and application, and belongs to the field of development evaluation of 0-6-year-old children, and the development state to be evaluated comprises one or more of neuropsychological development, skin, excrement, crying and screaming and night sleep; the method comprises the following steps: acquiring intestinal flora information of a to-be-predicted target population; the intestinal flora information comprises relative abundance information of flora significantly related to the corresponding development state; the intestinal flora information is input into a pre-constructed prediction evaluation model, evaluation results output by the prediction evaluation model are obtained, and the quantification results correspond to different development states. According to the method, near and long-term neuropsychological development, skin, excrement, crying and screaming conditions and night sleep indexes of the children are predicted through intestinal flora of the children, target spots capable of reference improvement are provided, bad development results possibly existing in the future can be found in time, and prevention and improvement are carried out in time.

Description

[0001] The present application is a divisional application of a Chinese application with the application number 202411328371.2, the application date of September 23, 2024, and the invention name of "Method, system and application for evaluating the development state of infants and young children based on intestinal flora". TECHNICAL FIELD

[0002] The present application relates to the field of 0-6-year-old children development evaluation, in particular to a method, system and application for evaluating the growth and development state of 0-6-year-old children based on intestinal flora. BACKGROUND

[0003] There are about 10 14 microorganisms in the human body, most of which parasitize in the human intestinal tract, and the microorganisms in the human intestinal tract play an important role in individual nutritional metabolism, immunity, and physiological function regulation. The period of 0-6 years old is an important window period for the establishment of individual intestinal flora, which has a great influence on the establishment and maturation of future intestinal flora. The biggest feature of the intestinal flora of 0-6-year-old children is instability, great individual difference, and easy to be affected by external factors.

[0004] Although the intestinal flora of 0-6-year-old children has great differences, after birth, the intestinal flora of infants and young children has certain regularity from the initial colonization to the subsequent evolution process. At present, the generally accepted development mode of intestinal microorganisms of infants and young children is that facultative anaerobes colonize in the early stage, continuously consume the oxygen in the intestine, and when the intestine becomes an anaerobic environment, strict anaerobes begin to colonize in the intestine of infants and young children. With the gradual growth of infants and young children, the intestinal flora develops from low diversity and low complexity to high diversity and complexity, which usually takes three to four years. The intestine is the digestive and absorptive organ of the human body and also the largest immune organ of the human body. During the colonization process of intestinal flora in early life, it affects the development of individuals in early life to some extent.

[0005] Feeding mode affects intestinal flora and short-term and long-term health, the World Health Organization and the United Nations Children's Fund recommend that mothers should insist on exclusive breastfeeding for the first 6 months after the birth of infants. Breast milk has rich nutrients that can meet the energy and nutrients necessary for early growth and development of children, and also has various oligosaccharides and prebiotics that can regulate the composition of intestinal flora of infants and young children, improve the immunity of children, and reduce the risk of infectious diseases.

[0006] Neuropsychological development, skin, stool, crying, night sleep, and other indicators are used to evaluate the healthy development of children from various dimensions, and the influencing factors of the indicators are diversified. At present, the observation of these indicators mainly relies on external discovery, ignoring the relationship between changes in children's bodies and clinical manifestations.

[0007] Therefore, the present application is proposed. SUMMARY

[0008] OBJECTIVE

[0009] In order to overcome the above-mentioned defects, the present application aims to provide a method, system and application for evaluating the growth and development state of children aged 0-6 years old. The present application increases the angle of health evaluation of the growth and development state of children aged 0-6 years old by establishing the intestinal flora change curve and reference range of children aged 0-6 years old.

[0010] SOLUTION

[0011] In order to achieve the object of the present application, the technical solution adopted by the present application is as follows:

[0012] In a first aspect, the present application provides a method for evaluating the growth and development state of children aged 0-6 years old, wherein the development state to be evaluated includes one or more of neuropsychological development, skin, stool, crying, and night sleep; the method comprises the following steps:

[0013] Obtaining intestinal flora information of a target population to be predicted; the intestinal flora information includes relative abundance information of flora significantly related to the corresponding development state;

[0014] Inputting the intestinal flora information into a pre-constructed prediction and evaluation model to obtain an evaluation result output by the prediction and evaluation model, wherein the evaluation result includes a quantitative result of the corresponding development state, and the quantitative result corresponds to different development states.

[0015] The prediction and evaluation model is obtained by multivariate regression calculation according to the screened corresponding intestinal flora information significantly related to the development state to be evaluated.

[0016] Further, the prediction and evaluation model includes several prediction and evaluation sub-models distinguished according to age and the development state to be evaluated; the selection of the prediction and evaluation sub-model is based on age and the development state to be evaluated, and the corresponding intestinal flora information significantly related to the corresponding age range and the development state to be evaluated is input for prediction and evaluation; and / or,

[0017] The intestinal flora information is obtained by detection in a fecal sample of the target population to be predicted.

[0018] Further, the construction method of the prediction and evaluation model comprises:

[0019] Gut microbiota information from several samples across multiple regions was obtained. This gut microbiota information, combined with clinical information, was used to establish a gut microbiota database for children aged 0-6 years. Gut microbiota information included relative abundance at the phylum, family, and genus levels. Clinical information included age and developmental status. Developmental status information included neuropsychological development, skin condition, stool characteristics, crying patterns, and one or more sleep patterns at night. The developmental status information was quantified, including: scoring the neuropsychological development questionnaire based on skin disease, stool characteristics, crying patterns, and the number of awakenings during nighttime sleep.

[0020] The data in the database were grouped by age, and then further grouped according to the relative abundance of the bacterial community within each group. The average relative abundance of each bacterial species was used as the boundary to divide the data into a high abundance group and a low abundance group. The mean values ​​of the quantitative developmental status information of the high abundance group and the low abundance group were calculated respectively. The mean values ​​of the two groups were compared to obtain the difference fold and significance analysis was performed.

[0021] The bacteria that are significantly related to clinical information were selected as independent variables, and the scores or assignments of clinical information of children aged 0-6 years were selected as dependent variables. Random seeds were set for each age group, and the data were randomly divided into training set and validation set according to the proportion. Linear regression calculation was performed on the training set to obtain a linear prediction model of the relationship between the microbiota and clinical information of children aged 0-6 years. The model was then tested using the validation set.

[0022] Multiple linear regression models are obtained based on the random seed number. Based on the obtained models, the range of model coefficients is summarized, and the average value is used as the model coefficient to obtain a predictive evaluation model. Based on the predicted clinical information of children aged 0-6 years, the developmental status of children aged 0-6 years is evaluated.

[0023] Furthermore, the construction of the gut microbiota database for children aged 0-6 years includes: collecting fecal samples from children aged 0-6 years, sequencing and analyzing them using 16S amplicon sequencing technology to obtain sequencing data corresponding to the gut microbiota of children aged 0-6 years, denoising and aggregating the sequencing data to obtain basic taxonomic units (OTUs), annotating the taxonomic units to obtain the composition of the gut microbiota of children aged 0-6 years, and merging the gut microbiota information and clinical information according to the sample number to establish the gut microbiota database for children aged 0-6 years.

[0024] Furthermore, noise reduction includes: Reads splicing and filtering, followed by OTUs clustering.

[0025] Furthermore, when the developmental state to be assessed is neuropsychological development, the microbiota significantly associated with neuropsychological development includes several age-related microbial groups as follows (1) to (3):

[0026] (1) Staphylococcus (Staphylococcus), Ligilactobacillus (Ligilactobacillus), Ruminococcus. torques group (Ruminococcus torques); optionally, the child is aged 0 days to 4 months;

[0027] (2) Veillonella (Veillonella), Prevotella (Prevotella); optionally, the child is aged 5 months to 12 months;

[0028] (3) TM7x (TM7x), Weissella (Weissella), Devosia (Devosia), Bradyrhizobium (Bradyrhizobium), Atopobium (Atopobium), Glutamicibacter (Glutamicibacter), Cupriavidus (Cupriavidus), Lachnospiraceae_FCS020_group (Lachnospiraceae FCS020 group), RB41 (universal unit RB41); optionally, the child is aged 13 months to 6 years;

[0029] Alternatively, when the development state to be evaluated is skin, the flora significantly associated with skin includes several bacterial collections (i) to (ii) below, which are age-dependent:

[0030] (i) Clostridium_sensu_stricto_1 (Clostridium sensu stricto 1), Brevundimonas (Brevundimonas), Subdoligranulum (Subdoligranulum), Faecalibacterium (Faecalibacterium); the child is aged 0 days to 4 months;

[0031] (ii) Bifidobacterium (Bifidobacterium), Bacillus (Bacillus);

[0032] Alternatively, when the development state to be evaluated is stool properties, the flora significantly associated with stool properties includes several bacterial collections (i) to (iv) below, which are age-dependent:

[0033] i) Staphylococcus (Staphylococcus), Veillonella (Veillonella), Parabacteroides (Parabacteroides), Dialister (Dialister), Haemophilus (Haemophilus); optionally, the child is aged 0 to 15 days;

[0034] ii) Lachnospira, Flavonifractor, Agathobacter, Phascolarctobacterium; optionally, child age 16 days - 30 days;

[0035] iii) Clostridium_sensu_stricto_1, Bacteroides, Parabacteroides, Akkermansia, Citrobacter, Bilophila, Epulopiscium, Phascolarctobacterium, Collinsella, Sarcina; optionally, child age 31 days - 4 months;

[0036] iv) Escherichia.Shigella, Clostridium_sensu_stricto_1, Staphylococcus, Bacteroides, Bacillus, Erysipelatoclostridium, Subdoligranulum, Dialister, Epulopiscium, Ruminococcus. torques group, CAG.56, Sellimonas; optionally, child age 5 months - 6 years;

[0037] Alternatively, the bacterial community significantly associated with crying when the developmental state to be assessed is crying is 1)

[0038] of the age of the child:

[0039] 1) Erysipelatoclostridium, Klebsiella, Citrobacter; optionally, child age 8 days - 15 days;

[0040] 2) Staphylococcus (Staphylococcus), Rothia (Rothia), Phascolarctobacterium (Phascolarctobacterium), Ruminococcus (Ruminococcus); optionally, the child is aged between 16 days and 30 days;

[0041] 3) Acinetobacter (Acinetobacter), Enhydrobacter (Enhydrobacter), Aeromonas (Aeromonas), Ligilactobacillus (Ligilactobacillus), Veillonella (Veillonella), Megasphaera (Megasphaera), Prevotella (Prevotella), Fusobacterium (Fusobacterium), Lactobacillus (Lactobacillus), Flavonifractor (Flavonifractor), Lachnospiraceae_NK4A136_group (Lachnospiraceae_NK4A136_group), Fusicatenibacter (Fusicatenibacter), Ruminococcus (Ruminococcus), Eubacterium. hallii group (Eubacterium. hallii group), Actinomyces (Actinomyces), Atopobium (Atopobium); optionally, the child is aged between 31 days and 4 months;

[0042] Alternatively, when the developmental state to be assessed is night sleep, the microbiota significantly associated with night sleep includes several bacterial collections associated with age as follows a) to d):

[0043] a) Parabacteroides (Parabacteroides);

[0044] b) Lactobacillus (Lactobacillus), Phascolarctobacterium (Phascolarctobacterium);

[0045] c) Stenotrophomonas, Enterococcus, Prevotella, Lactobacillus, Bilophila, Flavonifractor, Sutterella, Ruminococcus. torques group, un identified Chloroplast, Fusicatenibacter, Dorea, Proteus, Myroides;

[0046] d) Staphylococcus, Enterobacter, Prevotella_9, Erysipelatoclostridium, Coprococcus, Fusobacterium, Flavonifractor, Sutterella, Lachnoclostridium, Actinomyces, Anaerostipes, Eubacterium. fissicatena group, Negativicoccus, Allisonella.

[0047] Further, the method of grouping by age includes: 0-7 days, 8-15 days, 16-30 days, 31 days-4 months, 5 months-12 months, 13 months-24 months, 25 months-36 months, 37 months-6 years old.

[0048] Further, the clinical information includes neuropsychological development, skin, stool, crying condition or night sleep;

[0049] The prediction model formula of the intestinal flora information and the neuropsychological development includes one or more of the following formulas (1)-(3):

[0050] (1) When the child is 0 days-4 months old, the prediction formula of neuropsychological development is:

[0051] h = (51.0705-52.7283) + (-540.3316-54.9656) x Staphylococcus-

[0052] (3599.8924~2076.5719) x Ligilactobacillus + (127.5668~3359.586) x

[0053] Ruminococcus. torques_group;

[0054] Alternatively, h = 51.9239-249.4833 x Staphylococcus - 2448.8087 x Ligilactobacillus + 1394.1283 x Ruminococcus. torques_group;

[0055] wherein Staphylococcus is the relative abundance of Staphylococcus, Ligilactobacillus is the relative abundance of Ligilactobacillus, and Ruminococcus. torques_group is the relative abundance of Ruminococcus. torques_group;

[0056] (2) When the child is aged 5 months to 12 months, the formula for predicting neuropsychological development is:

[0057] h = (55.2745~56.409) - (34.2045~26.1645) x Veillonella + (794.7139~2787.5344) x Prevotella;

[0058] Alternatively, h = 55.8377-30.5745 x Veillonella + 1188.1085 x Prevotella;

[0059] wherein Veillonella is the relative abundance of Veillonella, and Prevotella is the relative abundance of Prevotella;

[0060] (3) When the child is aged 13 months to 6 years, the formula for predicting neuropsychological development is:

[0061] h = (49.9123-52.6285) + (2343.7701-4663.8371) x TM7x + (-60.5126-3457.3805) x Weissella + (3641.8351-4855.5426) x Devosia + (1378.1606-2869.502) x Bradyrhizobium + (866.0322-3817.5774) x Atopobium + (1370.5024-4909.5865) x Glutamicibacter - (11328.4011-6658.3515) x Cupriavidus + (1408.4641-2853.6566) x Lachnospiraceae_FCS020_group + (2431.4707-4358.3283) x RB41;

[0062] Optionally, h = 51.0569 + 3311.0714 x TM7x + 857.1083 x Weissella + 4384.629 x Devosia + 2224.3299 x Bradyrhizobium + 1831.3744 x Atopobium + 2466.8918 x Glutamicibacter - 9012.034 x Cupriavidus + 2119.8855 x Lachnospiraceae_FCS020_group + 3757.0831 x RB41;

[0063] wherein, TM7x is the relative abundance of TM7x genus, Weissella is the relative abundance of Weissella genus, Devosia is the relative abundance of Devosia genus, Bradyrhizobium is the relative abundance of Bradyrhizobium genus, Atopobium is the relative abundance of Atopobium genus, Glutamicibacter is the relative abundance of Glutamicibacter genus, Cupriavidus is the relative abundance of Cupriavidus genus, Lachnospiraceae_FCS020_group is the relative abundance of Lachnospiraceae_FCS020_group;

[0064] and / or, the intestinal flora information and the prediction model formula of the skin include one or several of the following formulas (i)-(ii):

[0065] (i) when the age of the child is 0-4 months, the formula for predicting the skin is:

[0066] h = (0.0659-0.0894) + (0.2965-0.4306) x Clostridium_sensu_stricto_1 + (298.8977-432.2361) x Brevundimonas + (1.6479-2.5646) x Subdoligranulum - (21.6623-5.945) x Faecalibacterium;

[0067] Optionally h = 0.0794 + 0.3781 x Clostridium_sensu_stricto_1 + 354.1341 x Brevundimonas + 2.0446 x Subdoligranulum - 12.0461 x Faecalibacterium;

[0068] wherein Clostridium_sensu_stricto_1 is the relative abundance of Clostridium sensu stricto, Brevundimonas is the relative abundance of Brevundimonas, Subdoligranulum is the relative abundance of Subdoligranulum, and Faecalibacterium is the relative abundance of Faecalibacterium;

[0069] (ii) for children aged 5 months to 6 years, the formula for predicting the skin is:

[0070] h = (0.1305-0.1715) - (0.2813-0.2075) x Bifidobacterium + (135.426-160.0824) x Bacillus;

[0071] Optionally h = 0.148 - 0.2464 x Bifidobacterium + 150.5487 x Bacillus;

[0072] wherein Bifidobacterium is the relative abundance of Bifidobacterium and Bacillus is the relative abundance of Bacillus;

[0073] and / or the predictive model formulae of the gut microbiota information and the stool properties comprise one or several of the following formulae i) to iv):

[0074] i) for children aged 0 to 15 days, the formula for predicting the stool properties is:

[0075] h = (2.5624-2.6469) - (2.6623-0.8585) x Staphylococcus - (4.0757-3.3154) x Veillonella - (2.3037-1.444) x Parabacteroides + (8.4342-535.3406) x Dialister - (3.8718-3.0043) x Haemophilus;

[0076] x Haemophilus;

[0077] Alternatively h = 2.6152 - 1.1958 x Staphylococcus - 3.6283 x Veillonella - 1.8468 x

[0078] Parabacteroides + 152.3533 x Dialister - 3.5718 x Haemophilus;

[0079] where Staphylococcus is the relative abundance of Staphylococcus, Veillonella is the relative abundance of Veillonella, Parabacteroides is the relative abundance of Parabacteroides, Dialister is the relative abundance of Dialister, and Haemophilus is the relative abundance of Haemophilus;

[0080] ii) For children aged 16-30 days, the formula to predict stool consistency is:

[0081] h = (2.3114-2.4241) + (2.4508-683.2421) x Lachnospira + (2.3546-12.7348) x Flavonifractor - (405.4702-62.5708) x Agathobacter - (13.1682-9.6822) x

[0082] Phascolarctobacterium;

[0083] Alternatively h = 2.3783 + 182.608 x Lachnospira + 8.5137 x Flavonifractor - 122.2349 x Agathobacter - 11.4688 x Phascolarctobacterium;

[0084] wherein Lachnospira is the relative abundance of the genus Lachnospira, Flavonifractor is the relative abundance of the genus Flavonifractor, Agathobacter is the relative abundance of the genus Agathobacter, and Phascolarctobacterium is the relative abundance of the genus Phascolarctobacterium;

[0085] iii) For children aged 31 days to 4 months, the formula to predict stool consistency is:

[0086] h = (2.3441-2.441) + (-0.1699-0.0419) x Clostridium_sensu_stricto_1 +

[0087] (0.0728-0.2473) x Bacteroides + (1.7218-2.1934) x Parabacteroides + (1.2942-3.6235) x Akkermansia + (-0.5946-2.7963) x Citrobacter + (-11.0145-21.6328) x Bilophila-

[0088] (1.8488-1.354) x Epulopiscium + (6.8497-11.2683) x Phascolarctobacterium +

[0089] (2.3211-5.0496) x Collinsella - (221.8181-121.729) x Sarcina.

[0090] Alternatively h = 2.3775 - 0.0542 x Clostridium_sensu_stricto_1 + 0.1665 x Bacteroides + 1.9577 x Parabacteroides + 2.7415 x Akkermansia + 1.8706 x Citrobacter + 1.9948 x Bilophila - 1.6425 x Epulopiscium + 8.7979 x Phascolarctobacterium + 3.2822 x Collinsella - 165.6212 x Sarcina.

[0091] wherein Clostridium_sensu_stricto_1 is the relative abundance of strict Clostridium 1, Bacteroides is the relative abundance of Bacteroides, Parabacteroides is the relative abundance of Parabacteroides, Akkermansia is the relative abundance of Akkermansia, Citrobacter is the relative abundance of Citrobacter, Bilophila is the relative abundance of Bilophila, Epulopiscium is the relative abundance of Epulopiscium, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, Sarcina is the relative abundance of Sarcina;

[0092] iv) For children aged 5 months to 6 years, the formula for predicting stool form is:

[0093] h = (2.9053-3.0947) - (1.0973-0.7369) x Escherichia. Shigella - (0.4223-0.3035) x Clostridium_sensu_stricto_1 - (15.7456-14.3356) x Staphylococcus + (0.3984-0.5591) x Bacteroides - (399.5418-60.4927) x Bacillus - (1.4938-0.4026) x Erysipelatoclostridium

[0094] (12.6503-8.9228) x Subdoligranulum + (22.3406-24.9229) x Dialister - (104.8873-77.8148) x Epulopiscium + (-0.347-7.5903) x Ruminococcus. torques_group - (458.5554-407.3394) x CAG.56 + (218.2145-397.8098) x Sellimonas;

[0095] Optionally, h = 2.9704 - 0.8727 x Escherichia.Shigella - 0.3608 x Clostridium_sensu_stricto_1 - 14.9315 x Staphylococcus + 0.4969 x Bacteroides - 203.9802 x Bacillus - 0.9976 x Erysipelatoclostridium - 10.9023 x Subdoligranulum + 24.0384 x Dialister - 93.5327 x Epulopiscium + 2.4099 x Ruminococcus._torques_group - 427.6705 x CAG.56 + 333.3722 x Sellimonas

[0096] Ruminococcus._torques_group - 427.6705 x CAG.56 + 333.3722 x Sellimonas

[0097] wherein, Escherichia.Shigella is the relative abundance of Escherichia-Shigella, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium_sensu_stricto_1, Staphylococcus is the relative abundance of Staphylococcus, Bacteroides is the relative abundance of Bacteroides, Bacillus is the relative abundance of Bacillus, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Subdoligranulum is the relative abundance of Subdoligranulum, Dialister is the relative abundance of Dialister, Epulopiscium is the relative abundance of Epulopiscium, Ruminococcus._torques_group is the relative abundance of Ruminococcus._torques_group, CAG.56 is the relative abundance of CAG.56, and Sellimonas is the relative abundance of Sellimonas;

[0098] And / or, the prediction model formula of the intestinal flora information and the crying condition includes one or several of the following formulas 1) to 3):

[0099] 1) When the child is 8 days to 15 days old, the formula for predicting the crying condition is:

[0100] h = (1.6702-1.8308) + (1.5851-2.4425) x Erysipelatoclostridium - (1.5395-1.1238) x Klebsiella - (20.1973-8.7767) x Citrobacter

[0101] Optionally h = 1.7244 + 1.8593 x Erysipelatoclostridium - 1.2836 x Klebsiella - 12.9963 x

[0102] Citrobacter;

[0103] wherein Erysipelatoclostridium is the relative abundance of the genus Erysipelatoclostridium, Klebsiella is the relative abundance of the genus Klebsiella, and Citrobacter is the relative abundance of the genus Citrobacter;

[0104] 2) For children aged 16 days to 30 days, the formula for predicting crying is:

[0105] h = (1.5075-1.5779) + (-0.9539-38.2314) x Staphylococcus - (111.3334-14.6111) x Rothia - (15.6307-9.5096) x Phascolarctobacterium - (7.9704-5.5118) x Ruminococcus;

[0106] Optionally h = 1.5331 + 20.0659 x Staphylococcus - 42.3019 x Rothia - 13.2372 x

[0107] Phascolarctobacterium - 6.9779 x Ruminococcus;

[0108] wherein Staphylococcus is the relative abundance of the genus Staphylococcus, Rothia is the relative abundance of the genus Rothia, Phascolarctobacterium is the relative abundance of the genus Phascolarctobacterium, and Ruminococcus is the relative abundance of the genus Ruminococcus;

[0109] 3) For children aged 31 days to 4 months, the formula for predicting crying is:

[0110] h = (1.4678~1.5216) + (-1.2963~3.8134) * Acinetobacter - (147.9583~82.5599) * Enhydrobacter + (214.5577~611.1134) * Aeromonas - (61.6441~45.7525) * Ligilactobacillus - (1.5492~1.1626) * Veillonella + (0.3757~2.8055) * Megasphaera - (26.169~226.5171) * Prevotella - (31.1451~28.1141) * Fusobacterium - (1.1191~0.486) * Lactobacillus - (1.2058~0.9898) * Flavonifractor - (215.1284~112.9927) * Lachnospiraceae_NK4A136_group - (2.2375~8.3244) * Fusicatenibacter - (179.0185~49.5399) * Ruminococcus - (477.6953~262.9145) * Eubacterium._hallii_group - (88.7991~73.9559) * Actinomyces + (160.468~224.39) * Atopobium;

[0111] h = 1.4959 + 1.279 * Acinetobacter - 117.4994 * Enhydrobacter + 394.8747 * Aeromonas - 54.0312 * Ligilactobacillus - 1.3707 * Veillonella + 1.3511 * Megasphaera + 62.6096 * Prevotella - 30.0045 * Fusobacterium - 0.7988 * Lactobacillus + 0.6225 * Flavonifractor - 167.8314 * Lachnospiraceae_NK4A136_group + 3.1171 * Fusicatenibacter - 109.4375 * Ruminococcus - 89.6414 * Eubacterium._hallii_group - 82.0443 * Actinomyces + 199.7983 * Atopobium;

[0112] Wherein, Acinetobacter is the relative abundance of Acinetobacter, Enhydrobacter is the relative abundance of Enhydrobacter, Aeromonas is the relative abundance of Aeromonas, Ligilactobacillus is the relative abundance of Ligilactobacillus, Veillonella is the relative abundance of Veillonella, Megasphaera is the relative abundance of Megasphaera, Prevotella is the relative abundance of Prevotella, Fusobacterium is the relative abundance of Fusobacterium, Lactobacillus is the relative abundance of Lactobacillus, Flavonifractor is the relative abundance of Flavonifractor, Lachnospiraceae_NK4A136_group is the relative abundance of Lachnospiraceae NK4A136 group, Fusicatenibacter is the relative abundance of Fusicatenibacter, Ruminococcus is the relative abundance of Ruminococcus, Eubacterium._hallii_group is the relative abundance of Eubacterium hallii group, Actinomyces is the relative abundance of Actinomyces, Atopobium is the relative abundance of Atopobium;

[0113] And / or, the prediction model formula of the intestinal flora information and the night sleep condition includes one or several of the following formulas a) ~ d):

[0114] a) When the age of the child is 0 days ~ 15 days, the formula of the night sleep condition is:

[0115] h = (1.667 ~ 1.7575) + (2.0551 ~ 3.3078) x Parabacteroides;

[0116] Optionally, h = 1.7084 + 2.5764 x Parabacteroides;

[0117] Wherein, Parabacteroides is the relative abundance of Parabacteroides;

[0118] b) When the age of the child is 16 days ~ 30 days, the formula of the night sleep condition is:

[0119] h = (1.9871 ~ 2.1135) - (36.0173 ~ 5.136) x Lactobacillus + (19.9734 ~ 35.2859) x Phascolarctobacterium;

[0120] Optionally, h = 2.0218 - 12.0345 x Lactobacillus + 26.0639 x Phascolarctobacterium;

[0121] wherein Lactobacillus is the relative abundance of the genus Lactobacillus, and Phascolarctobacterium is the relative abundance of the genus Phascolarctobacterium;

[0122] c) for children aged 31 days to 4 months, the formula for night sleep is:

[0123] h = (2.1063-2.153) + (485.8899-703.2182) x Stenotrophomonas - (1.1099-0.9931) x Enterococcus + (45.4132-142.3935) x Prevotella - (3.0807-2.7328) x Lactobacillus + (6.9523-27.6025) x Bilophila + (-0.4976-4.8429) x Flavonifractor + (3.4943-6.1713) x Sutterella + (7.1024-12.505) x Ruminococcus_torques_group - (405.374-222.0575) x unidentified_Chloroplast + (0.0185-4.2892) x Fusicatenibacter + (232.9549-397.3759) x Dorea - (3.843-2.5359) x Proteus - (126.278-76.0815) x Myroides;

[0124] h = 2.1267 + 580.5244 x Stenotrophomonas - 1.0646 x Enterococcus + 76.9896 x Prevotella - 2.9066 x Lactobacillus + 16.0708 x Bilophila + 0.7412 x Flavonifractor + 4.4946 x Sutterella + 8.8728 x Ruminococcus_torques_group - 280.1981 x unidentified_Chloroplast + 1.3007 x Fusicatenibacter + 310.8906 x Dorea - 3.3466 x Proteus - 98.8985 x Myroides;

[0125] h = 2.1267 + 580.5244 x Stenotrophomonas - 1.0646 x Enterococcus + 76.9896 x Prevotella - 2.9066 x Lactobacillus + 16.0708 x Bilophila + 0.7412 x Flavonifractor + 4.4946 x Sutterella + 8.8728 x Ruminococcus_torques_group - 280.1981 x unidentified_Chloroplast + 1.3007 x Fusicatenibacter + 310.8906 x Dorea - 3.3466 x Proteus - 98.8985 x Myroides;

[0126] Wherein, Stenotrophomonas is the relative abundance of Stenotrophomonas, Enterococcus is the relative abundance of Enterococcus, Prevotella is the relative abundance of Prevotella, Lactobacillus is the relative abundance of Lactobacillus, Bilophila is the relative abundance of Bilophila, Flavonifractor is the relative abundance of Flavonifractor, Sutterella is the relative abundance of Sutterella, Ruminococcus._torques_group is the relative abundance of Ruminococcus. Torques group, unidentified Chloroplast is the relative abundance of unidentified Chloroplast, Fusicatenibacter is the relative abundance of Fusicatenibacter, Dorea is the relative abundance of Dorea, Proteus is the relative abundance of Proteus, Myroides is the relative abundance of Myroides;

[0127] d) The formula for night sleep condition when the child is 5 months to 6 years old is:

[0128] h = (1.8273-1.8898) + (5.8052-7.3144) x Staphylococcus - (5.3856-1.5202) x

[0129] Enterobacter + (1.744-9.8407) x Prevotella_9 + (-1.5188-0.2748) x Erysipelatoclostridium + (-2.1975-30.4482) x Coprococcus - (66.6501-15.2271) x Fusobacterium + (-0.8691-4.0197) x Flavonifractor + (5.4952-9.5591) x Sutterella + (3.2347-5.8771) x Lachnoclostridium +

[0130] (53.2421-66.6003) x Actinomyces + (124.4522-194.2467) x Anaerostipes +

[0131] (6.1294-71.2023) x Eubacterium. fissicatena group - (158.923-76.3152) x Negativicoccus + (112.5601-779.4042) x Allisonella;

[0132] Optionally h = 1.8537 + 6.6401 x Staphylococcus - 2.9561 x Enterobacter + 4.1107 x Prevotella_9 - 0.5677 x Erysipelatoclostridium + 8.9717 x Coprococcus - 29.4941 x Fusobacterium + 1.7762 x Flavonifractor + 7.6957 x Sutterella + 4.7329 x Lachnoclostridium + 61.5478 x Actinomyces + 164.25 x Anaerostipes + 37.7456 x Eubacterium._fissicatena_group - 121.676 x Negativicoccus + 403.4906 x Allisonella;

[0133] wherein Staphylococcus is the relative abundance of Staphylococcus, Enterobacter is the relative abundance of Enterobacter, Prevotella_9 is the relative abundance of Prevotella_9, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Coprococcus is the relative abundance of Coprococcus, Fusobacterium is the relative abundance of Fusobacterium, Flavonifractor is the relative abundance of Flavonifractor, Sutterella is the relative abundance of Sutterella, Lachnoclostridium is the relative abundance of Lachnoclostridium, Actinomyces is the relative abundance of Actinomyces, Anaerostipes is the relative abundance of Anaerostipes, Eubacterium._fissicatena_group is the relative abundance of Eubacterium._fissicatena_group, Negativicoccus is the relative abundance of Negativicoccus, and Allisonella is the relative abundance of Allisonella.

[0134] In a second aspect, there is provided a system for evaluating the growth and development state of a child aged 0-6 years, applied to the method of any one of the first aspect, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.

[0135] In a third aspect, there is provided use of the method of the first aspect, or the system of the second aspect, in the preparation of a product for evaluating the growth and development state of a child aged 0-6 years.

[0136] Advantages

[0137] The development level of the child is evaluated through the information of neuropsychological development, skin, stool, crying, night sleep, etc., which is the monitoring of the development result index of the child, that is, the difference in the clinical performance of infant health caused by the internal development of the intestinal flora of the child, and the present application predicts the neuropsychological development, skin, stool, crying, night sleep index of the child in the near and long term through the intestinal flora of the child, provides a target that can be referred to for improvement, can timely find the possible adverse development result in the future, and timely prevent and improve. DETAILED DESCRIPTION

[0138] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0139] In addition, in order to better illustrate the present application, numerous specific details are given in the specific embodiments below. A person of ordinary skill in the art should understand that the present application can also be implemented without some specific details. In some embodiments, the raw materials, elements, methods, means, and the like that are well known to a person of ordinary skill in the art are not described in detail, so as to highlight the main idea of the present application.

[0140] Unless otherwise explicitly indicated, in the entire specification and claims, the term "comprise" or its variants such as "contain" or "include" and the like will be understood to include the stated element or component, but not exclude other elements or components.

[0141] The applicant launched a mother and infant nutrition cohort study project in China in 2014, which is a long-term tracking project in multiple representative areas. The project established a multi-point multi-center prospective mother and infant nutrition cohort in 7 provinces and cities, 8 diet circles, and 15 points. 3766 mothers and infants were enrolled. At the time points of the seventh day, the fifteenth day, the first month, the second month, the third month, the fourth month, the fifth month, the sixth month, the eighteenth month, the twenty-fourth month, the thirtieth month, the thirty-sixth month, the fourth year, the fifth year, and the sixth year, samples were collected, and 28354 biological samples such as breast milk, feces, and urine were collected. Among them, 737 fecal samples of breastfed children aged 0-6 years were collected, and a 0-6 intestinal microbiome database of breastfed children aged 0-6 years was established.

[0142] For the research method of intestinal flora, mainly rely on the use of sequencing technology, to the intestinal flora marker gene (16S rRNA V3V4 region) sequencing, using bioinformatics technology to process the sequencing results, using related theory, to summarize the data, realize the observation of intestinal flora.

[0143] The relative abundance of the present application represents the relative proportion of a certain microbial taxon in the whole microbial community. It is usually expressed in percentage, and the calculation method is to divide the relative abundance of a certain taxon (its relative quantity in a sample) by the total number of microorganisms and multiply by 100%. This is a common way to describe the composition of microorganisms. For example, the relative abundance of a bacterium is the proportion of the bacterium in the total abundance of bacteria detected in the sample.

[0144] The present application first establishes the change trend of intestinal flora of children aged 0-6 years according to the collected data of children aged 0-6 years, plans the change range of intestinal flora of children aged 0-6 years at different time nodes of Chinese children after birth, and establishes the standardized evaluation index of the development state of intestinal flora of children aged 0-6 years. Further explore the correlation between intestinal flora and development indicators, select a group of marker flora, evaluate the physical development state of children aged 0-6 years by evaluating the relative abundance of each bacterium in the marker flora group, and achieve the purpose of predicting the development state of children by using intestinal flora.

[0145] In a first aspect, the present application provides a method for evaluating the growth and development state of children aged 0-6 years, wherein the development state to be evaluated includes one or more of neuropsychological development, skin, stool, crying, and night sleep; the method comprises the following steps:

[0146] Obtaining intestinal flora information of the target population to be predicted; the intestinal flora information includes relative abundance information of flora significantly related to the corresponding development state;

[0147] Inputting the intestinal flora information into a pre-constructed prediction and evaluation model to obtain an evaluation result output by the prediction and evaluation model, wherein the evaluation result includes a quantitative result of the corresponding development state, and the quantitative result corresponds to different development states.

[0148] The prediction and evaluation model is obtained by multiple regression calculation according to the selected intestinal flora information significantly related to the development state to be evaluated.

[0149] Further, the prediction and evaluation model includes a plurality of prediction and evaluation sub-models distinguished according to age and the development state to be evaluated; the selection of the prediction and evaluation sub-models is based on age and the development state to be evaluated, and the corresponding intestinal flora information significantly related to the corresponding age and the development state to be evaluated is inputted for prediction and evaluation; and / or,

[0150] The intestinal flora information is obtained by detection of a fecal sample of the target population to be predicted.

[0151] Further, the construction method of the prediction and evaluation model comprises:

[0152] Obtaining intestinal flora information of several samples of multiple areas, combining the intestinal flora information and clinical information to establish a 0-6 year-old children intestinal flora database, the intestinal flora information includes the relative abundance information of flora at the door, department and genus level, and the clinical information includes age and development state information; the development state information includes one or several of neuropsychological development, skin, stool, crying condition and night sleep; the development state information is quantitatively processed, including: scoring the questionnaire of neuropsychological development, scoring according to whether suffering from skin disease, scoring according to the stool shape, scoring according to the crying condition, and scoring according to the number of waking up during night sleep;

[0153] Grouping the data in the database according to age, and grouping again according to the relative abundance of flora in the group, dividing into high abundance group and low abundance group with the average value of the relative abundance of each bacterium as the boundary, calculating the mean value of the quantified development state information of the high abundance group and the low abundance group respectively, comparing the mean values of the two groups to obtain the difference multiple, and performing significance analysis;

[0154] Selecting the bacteria significantly related to the clinical information as the independent variable, the score or score of 0-6 year-old children clinical information as the dependent variable, setting the random seed of each age group, randomly dividing the data into training set and validation set according to the proportion, calculating the linear regression of the training set to obtain the linear prediction model of the flora and the 0-6 year-old children clinical information, and testing by the validation set;

[0155] Obtaining multiple linear regression models according to the number of random seeds, inducing the model coefficient range according to the obtained multiple models, and using the average value as the calculation model coefficient to obtain the prediction evaluation model, and evaluating the development state of 0-6 year-old children according to the predicted 0-6 year-old children clinical information.

[0156] Among them, the score of the neuropsychological development questionnaire is the score of the communication ability obtained according to the Ages & Stages Questionnaires (ASQ) test questionnaire for the physical development, communication ability, limb movement, problem solving, personal and social interaction ability of children of different ages, reflecting the ability and willingness of children to understand language signals and express orally. The data is obtained in the following way: through professional personnel, using ASQ questionnaires of different ages, evaluating children of corresponding ages, then calculating the total score according to the ASQ questionnaire guidance scoring principle through corresponding software, summarizing the score results of all children according to different ASQ categories, this time mainly taking the ASQ communication score as the evaluation data, pairing with the children's own flora data, dividing the ASQ score into two groups according to the high and low of the relative abundance of flora, calculating the difference fold and t-test of the high and low two groups, obtaining the difference fold and p value of the high and low two groups, selecting the statistically significant flora as the independent variable, and the ASQ communication score as the dependent variable to calculate the multiple linear regression. The estimated value obtained by bringing the sample data into the regression model can be considered as a prediction of the ASQ score.

[0157] Among them, the score of the neuropsychological development questionnaire is the score of the communication ability obtained according to the Ages & Stages Questionnaires (ASQ) test questionnaire for the physical development, communication ability, limb movement, problem solving, personal and social interaction ability of children of different ages, reflecting the ability and willingness of children to understand language signals and express orally. The data is obtained in the following way: through professional personnel, using ASQ questionnaires of different ages, evaluating children of corresponding ages, then calculating the total score according to the ASQ questionnaire guidance scoring principle through corresponding software, summarizing the score results of all children according to different ASQ categories, this time mainly taking the ASQ communication score as the evaluation data, pairing with the children's own flora data, dividing the ASQ score into two groups according to the high and low of the relative abundance of flora, calculating the difference fold and t-test of the high and low two groups, obtaining the difference fold and p value of the high and low two groups, selecting the statistically significant flora as the independent variable, and the ASQ communication score as the dependent variable to calculate the multiple linear regression. The estimated value obtained by bringing the sample data into the regression model can be considered as a prediction of the ASQ score.

[0158] Regarding the scores for stool characteristics, nighttime sleep, and crying: The process for establishing these three indicators is similar. The indicators are categorized according to different types and assigned scores. The scoring principles are shown in the table. At different age stages, children's stool characteristics, nighttime sleep, and crying are surveyed using questionnaires. The collected questionnaires are summarized, and the summarized data is combined with the gut microbiota data. Based on the relative abundance of each bacterium in the microbiota being higher or lower than the average relative abundance, the children are divided into high and low groups. For each high-low group, a fold change test and a t-test are performed on the summarized scores to obtain the fold change and p-value. Bacteria with a p-value less than 0.05 are selected as independent variables, and the indicator scores are the dependent variable. A multiple regression calculation is performed, and the sample information is fed into the model to obtain a predicted score. This score can be considered a tendency. For example, if child a's predicted score is 1.7, then they are considered to be more inclined towards result 2. The scoring tendency relationship is shown in the table below.

[0159] The scoring principles are shown in Table 1:

[0160] Table 1. Scoring principles for stool characteristics, nighttime sleep, and crying.

[0161] Score Stool form Night sleep Crying 1 Stool watery 3-4 wakings per night Almost never cries 2 Stool runny 1-2 wakings per night Cries during feeding 3 Stool formed Good sleep at night Unexplained crying 4 Stool formed 5 Stool hard .

[0162] The actual trait tendency relationship corresponding to the scores predicted by the model is as follows:

[0163] When the predicted score is 0 ≤ x < 1.5, the corresponding trait with a score of 1 is:

[0164] When the predicted score is 1.5 ≤ x < 2.5, the corresponding trait is a score of 2.

[0165] When the predicted score is 2.5 ≤ x < 3.5, the corresponding trait is a score of 3;

[0166] When the predicted score is 3.5 ≤ x < 4.5, the corresponding trait is a score of 4.

[0167] When the predicted score is 4.5 ≤ x, the corresponding trait is a score of 5.

[0168] Furthermore, the construction of the gut microbiota database for children aged 0-6 years includes: collecting fecal samples from children aged 0-6 years, sequencing and analyzing them using 16S amplicon sequencing technology to obtain sequencing data corresponding to the gut microbiota of children aged 0-6 years, denoising and aggregating the sequencing data to obtain basic taxonomic units (OTUs), annotating the taxonomic units to obtain the composition of the gut microbiota of children aged 0-6 years, and merging the gut microbiota information and clinical information according to the sample number to establish the gut microbiota database for children aged 0-6 years.

[0169] Furthermore, noise reduction includes: Reads splicing and filtering, followed by OTUs clustering.

[0170] One possible implementation is as follows:

[0171] (1) Process the collected samples, obtain the sequencing data of the intestinal flora of children aged 0-6 years old by using 16s amplicon sequencing technology, double-end sequencing of the library based on illumina NovaSeq sequencing platform, denoise and aggregate the data in qiime 2 platform to obtain basic classification units OTUs, and annotate the classification units according to the existing biological level annotator to obtain the composition of the intestinal flora of children aged 0-6 years old. The composition of the flora is presented in the format of relative abundance;

[0172] (2) Use R studio software to read in the data of all breastfed samples (including the composition of the intestinal flora of children aged 0-6 years old and the clinical information table), merge according to the unique sample number, combine the clinical information and intestinal flora composition information together, and establish a database of breastfed children aged 0-6 years old. According to different time points, the samples are divided into eight categories: 0-7 days (stage 1), 8-15 days (stage 2), 16-30 days (stage 3), 31 days-4 months (stage 4), 5 months-12 months (stage 5), 13 months-24 months (stage 6), 25 months-36 months (stage 7), and 37 months-6 years old (stage 8).

[0173] (2) Based on the database obtained in (1), according to the above time classification mode, each group is operated as follows: the relative abundance of the flora in the group is re-grouped according to being higher than the average value and lower than the average value, the height and weight information of the high abundance group and the low abundance group is compared, and the difference multiple is obtained; in addition, t test is performed to obtain p value. It is found that part of the flora is related to the clinical performance.

[0174] (3) Further filter the results calculated in (2), select bacteria with p value less than 0.05, and define them as having significant correlation with the height and weight information of children aged 0-6 years old. According to the grouping method in (1), set a random seed, randomly select data for each time grouping, use 80% of the samples in each group as a prediction set, and use the flora to perform linear regression calculation on the height and weight of children aged 0-6 years old to obtain a linear model of the flora and the clinical performance. Use the remaining 20% of the samples as a test set, and calculate the root mean square error, R 2, mean absolute error. According to the number of random seeds, multiple linear regression models are obtained, according to the obtained multiple models, the model coefficient range is induced, and the average value is taken as the calculation model coefficient, and the calculated model, model evaluation results and value range.

[0175] Further, when the development state to be evaluated is neuro-psychological development, the flora significantly related to neuro-psychological development includes several bacterial collections related to age as follows (1) to (3):

[0176] (1) Staphylococcus, Ligilactobacillus, Ruminococcus. torques group; optionally, the child's age is 0 days to 4 months;

[0177] (2) Veillonella, Prevotella; optionally, the child's age is 5 months to 12 months;

[0178] (3) TM7x, Weissella, Devosia, Bradyrhizobium, Atopobium, Glutamicibacter, Cupriavidus, Lachnospiraceae_FCS020_group, RB41; optionally, the child's age is 13 months to 6 years;

[0179] Alternatively, when the development state to be evaluated is skin, the flora significantly related to skin includes several bacterial collections related to age as follows (i) to (ii):

[0180] (i) Clostridium sensu stricto 1, Brevundimonas, Subdoligranulum, Faecalibacterium; the child's age is 0 days to 4 months;

[0181] (ii) Bifidobacterium, Bacillus;

[0182] Alternatively, when the development state to be evaluated is stool characteristics, the flora significantly related to stool characteristics includes several bacterial collections related to age as follows i) to iv):

[0183] i) Staphylococcus, Veillonella, Parabacteroides, Dialister, Haemophilus; optionally, for children aged 0–15 days;

[0184] ii) Lachnospira, Flavonoids, Agathobacter, Phascolarctobacterium; optionally, for children aged 16 to 30 days;

[0185] iii) Clostridium sensu stricto 1, Bacteroides, Parabacteroides, Akkermansia, Citrobacter, Bilophila, Epulopiscium, Phascolarctobacterium, Collinsella, Sarcina; optionally, for children aged 31 days to 4 months;

[0186] iv) *Escherichia Shigella*, *Clostridium sensu stricto*, *Staphylococcus*, *Bacteroides*, *Bacillus*, *Erysipelatoclostridium*, *Subdoligranulum*, *Dialister*, *Epulopiscium*, *Ruminococcus torques*, CAG.56, *Sellimonas*; optionally, for children aged 5 months to 6 years.

[0187] Alternatively, when the developmental stage to be assessed is crying, the microbiota significantly associated with crying includes the following age-related microbiota: 1)

[0188] ~3) A collection of several bacteria:

[0189] 1) Erysipelatoclostridium (Erysipelotrichia), Klebsiella (Klebsiellaceae), Citrobacter (Citrobacter); optionally, the child is aged between 8 days and 15 days;

[0190] 2) Staphylococcus (Staphylococcaceae), Rothia (Rothiaceae), Phascolarctobacterium (Phascolarctobacteriaceae), Ruminococcus (Ruminococcaceae); optionally, the child is aged between 16 days and 30 days;

[0191] 3) Acinetobacter (Acinetobacter), Enhydrobacter (Enhydrobacter), Aeromonas (Aeromonadaceae), Ligilactobacillus (Ligilactobacillus), Veillonella (Veillonellaceae), Megasphaera (Megasphaera), Prevotella (Prevotellaceae), Fusobacterium (Fusobacteriaceae), Lactobacillus (Lactobacillaceae), Flavonifractor (Flavobacteriaceae), Lachnospiraceae_NK4A136_group (Lachnospiraceae), Fusicatenibacter (Fusicatenibacter), Ruminococcus (Ruminococcaceae), Eubacterium. hallii group (Eubacteriaceae), Actinomyces (Actinomycetaceae), Atopobium (Atopobiaceae); optionally, the child is aged between 31 days and 4 months;

[0192] Alternatively, when the developmental state to be assessed is the night sleep situation, the microbiota significantly associated with the night sleep situation comprises several bacterial collections associated with age as follows a) to d):

[0193] a) Parabacteroides (Parabacteroides);

[0194] b) Lactobacillus (Lactobacillaceae), Phascolarctobacterium (Phascolarctobacteriaceae);

[0195] c) Stenotrophomonas, Enterococcus, Prevotella, Lactobacillus, Bilophila, Flavonifractor, Sutterella, Ruminococcus. torques group, unidentified Chloroplast, Fusicatenibacter, Dorea, Proteus, Myroides;

[0196] d) Staphylococcus, Enterobacter, Prevotella_9, Erysipelatoclostridium, Coprococcus, Fusobacterium, Flavonifractor, Sutterella, Lachnoclostridium, Actinomyces, Anaerostipes, Eubacterium. fissicatena group, Negativicoccus, Allisonella.

[0197] Further, the clinical information includes neuro-psychological development, skin, stool, crying condition or night sleep;

[0198] The prediction model formula of the intestinal flora information and neuro-psychological development includes one or several of the following formulas (1) to (3):

[0199] (1) When the child age is 0 day to 4 months, the prediction formula of neuro-psychological development is:

[0200] h = (51.0705-52.7283) + (-540.3316-54.9656) x Staphylococcus

[0201] (3599.8924-2076.5719) x Ligilactobacillus + (127.5668-3359.586) x

[0202] Ruminococcus. _torques_group;

[0203] wherein Staphylococcus is the relative abundance of Staphylococcus, Ligilactobacillus is the relative abundance of Ligilactobacillus, and Ruminococcus. _torques_group is the relative abundance of Ruminococcus. _torques_group;

[0204] (2) When the child is aged 5 months to 12 months, the formula for predicting neuropsychological development is:

[0205] h = (55.2745-56.409) - (34.2045-26.1645) x Veillonella + (794.7139-2787.5344) x Prevotella;

[0206] wherein Veillonella is the relative abundance of Veillonella, and Prevotella is the relative abundance of Prevotella;

[0207] (3) When the child is aged 13 months to 6 years, the formula for predicting neuropsychological development is:

[0208] h = (49.9123-52.6285) + (2343.7701-4663.8371) x TM7x + (-60.5126-3457.3805) x Weissella + (3641.8351-4855.5426) x Devosia + (1378.1606-2869.502) x Bradyrhizobium + (866.0322-3817.5774) x Atopobium + (1370.5024-4909.5865) x Glutamicibacter - (11328.4011-6658.3515) x Cupriavidus + (1408.4641-2853.6566) x Lachnospiraceae_FCS020_group + (2431.4707-4358.3283) x RB41;

[0209] Wherein, TM7x is the relative abundance of TM7x genus, Weissella is the relative abundance of Weissella genus, Devosia is the relative abundance of Devosia genus, Bradyrhizobium is the relative abundance of Bradyrhizobium genus, Atopobium is the relative abundance of Atopobium genus, Glutamicibacter is the relative abundance of Glutamicibacter genus, Cupriavidus is the relative abundance of Cupriavidus genus, Lachnospiraceae_FCS020_group is the relative abundance of Lachnospiraceae_FCS020_group, and RB41 is the relative abundance of RB41 genus.

[0210] Optionally, the prediction model formula of the intestinal flora information and neuro-psychological development comprises one or more of the following formulas (1)-(3):

[0211] (1) When the child is aged from 0 days to 4 months, the prediction formula of neuro-psychological development is:

[0212] h = 51.9239-249.4833x Staphylococcus-2448.8087x Ligilactobacillus+1394.1283x Ruminococcus_torques_group;

[0213] (2) When the child is aged from 5 months to 12 months, the prediction formula of neuro-psychological development is:

[0214] h = 55.8377-30.5745x Veillonella+1188.1085x Prevotella;

[0215] (3) When the child is aged from 13 months to 6 years, the prediction formula of neuro-psychological development is:

[0216] h = 51.0569+3311.0714x TM7x+857.1083x Weissella+4384.629x Devosia+2224.3299x Bradyrhizobium+1831.3744x Atopobium+2466.8918x Glutamicibacter-9012.034x Cupriavidus+2119.8855x Lachnospiraceae_FCS020_group+3757.0831x RB41;

[0217] The root mean square error, R 2 , and the mean absolute error of the prediction model formula of the intestinal flora information and neuro-psychological development are shown in Table 2.

[0218] Table 2, root mean square error, R of prediction model formula of gut microbiota information and neuro-psychological development 2 , mean absolute error

[0219]

[0220] Further, the prediction model formula of gut microbiota information and skin includes one or several of the following formulae (i)-(ii):

[0221] (i) When the age of the child is 0 days-4 months, the formula for predicting the skin is:

[0222] h = (0.0659-0.0894) + (0.2965-0.4306) x Clostridium_sensu_stricto_1 + (0. 298.8977-432.2361) x Brevundimonas + (1.6479-2.5646) x Subdoligranulum - (21.6623-5.945) x Faecalibacterium;

[0223] (298.8977-432.2361) x Brevundimonas + (1.6479-2.5646) x Subdoligranulum - (21.6623-5.945) x Faecalibacterium;

[0224] (21.6623-5.945) x Faecalibacterium;

[0225] Wherein, Clostridium_sensu_stricto_1 is the relative abundance of strict Clostridium, Brevundimonas is the relative abundance of Brevundimonas, Subdoligranulum is the relative abundance of Subdoligranulum, and Faecalibacterium is the relative abundance of Faecalibacterium;

[0226] (ii) When the age of the child is 5 months-6 years, the formula for predicting the skin is:

[0227] h = (0.1305-0.1715) - (0.2813-0.2075) x Bifidobacterium + (135.426-160.0824) x Bacillus;

[0228] Wherein, Bifidobacterium is the relative abundance of Bifidobacterium, and Bacillus is the relative abundance of Bacillus;

[0229] Alternatively, the prediction model formula of gut microbiota information and skin includes one or several of the following formulae (i)-(ii):

[0230] (i) When the age of the child is 0 days-4 months, the formula for predicting the skin is:

[0231] h = 0.0794 + 0.3781 x Clostridium_sensu_stricto_1 + 354.1341 x Brevundimonas + 2.0446 x Subdoligranulum - 12.0461 x Faecalibacterium;

[0232] (ii) For children aged 5 months to 6 years, the formula for predicting the skin is:

[0233] h = 0.148 - 0.2464 x Bifidobacterium + 150.5487 x Bacillus;

[0234] The root mean square error, R 2 , and the mean absolute error of the above intestinal flora information and the prediction model formula of the skin are shown in Table 3.

[0235] Table 3, Root mean square error, R 2 , and mean absolute error of intestinal flora information and prediction model formula of the skin

[0236]

[0237] Further, the prediction model formula of the intestinal flora information and the stool property includes one or several of the following formulas i) to iv):

[0238] i) For children aged 0 to 15 days, the formula for predicting the stool property is:

[0239] h = (2.5624-2.6469) - (2.6623-0.8585) x Staphylococcus - (4.0757-3.3154) x Veillonella - (2.3037-1.444) x Parabacteroides + (8.4342-535.3406) x Dialister - (3.8718-3.0043)

[0240] x Haemophilus;

[0241] Wherein, Staphylococcus is the relative abundance of Staphylococcus, Veillonella is the relative abundance of Veillonella, Parabacteroides is the relative abundance of Parabacteroides, Dialister is the relative abundance of Dialister, and Haemophilus is the relative abundance of Haemophilus;

[0242] ii) For children aged 16 days to 30 days, the formula for predicting the stool property is:

[0243] h = (2.3114-2.4241) + (2.4508-683.2421) x Lachnospira + (2.3546-12.7348) x Flavonifractor - (405.4702-62.5708) x Agathobacter - (13.1682-9.6822) x

[0244] Phascolarctobacterium;

[0245] wherein Lachnospira is the relative abundance of the genus Lachnospira, Flavonifractor is the relative abundance of the genus Flavonifractor, Agathobacter is the relative abundance of the genus Agathobacter, and Phascolarctobacterium is the relative abundance of the genus Phascolarctobacterium;

[0246] iii) for children aged 31 days to 4 months, the formula to predict stool consistency is:

[0247] h = (2.3441-2.441) + (-0.1699-0.0419) x Clostridium_sensu_stricto_1 +

[0248] (0.0728-0.2473) x Bacteroides + (1.7218-2.1934) x Parabacteroides + (1.2942-3.6235) x Akkermansia + (-0.5946-2.7963) x Citrobacter + (-11.0145-21.6328) x Bilophila -

[0249] (1.8488-1.354) x Epulopiscium + (6.8497-11.2683) x Phascolarctobacterium +

[0250] (2.3211-5.0496) x Collinsella - (221.8181-121.729) x Sarcina;

[0251] wherein Clostridium_sensu_stricto_1 is the relative abundance of strict Clostridium 1, Bacteroides is the relative abundance of Bacteroides, Parabacteroides is the relative abundance of Parabacteroides, Akkermansia is the relative abundance of Akkermansia, Citrobacter is the relative abundance of Citrobacter, Bilophila is the relative abundance of Bilophila, Epulopiscium is the relative abundance of Epulopiscium, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, Sarcina is the relative abundance of Sarcina;

[0252] iv) For children aged 5 months to 6 years, the formula to predict stool form is:

[0253] h = (2.9053-3.0947) - (1.0973-0.7369) x Escherichia. Shigella - (0.4223-0.3035) x Clostridium_sensu_stricto_1 - (15.7456-14.3356) x Staphylococcus + (0.3984-0.5591) x Bacteroides - (399.5418-60.4927) x Bacillus - (1.4938-0.4026) x Erysipelatoclostridium

[0254] (12.6503-8.9228) x Subdoligranulum + (22.3406-24.9229) x Dialister - (104.8873-77.8148) x Epulopiscium + (-0.347-7.5903) x Ruminococcus. torques_group - (458.5554-407.3394) x CAG.56 + (218.2145-397.8098) x Sellimonas;

[0255] Escherichia.Shigella is the relative abundance of Escherichia-Shigella, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium_sensu_stricto_1, Staphylococcus is the relative abundance of Staphylococcus, Bacteroides is the relative abundance of Bacteroides, Bacillus is the relative abundance of Bacillus, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Subdoligranulum is the relative abundance of Subdoligranulum, Dialister is the relative abundance of Dialister, Epulopiscium is the relative abundance of Epulopiscium, Ruminococcus._torques_group is the relative abundance of Ruminococcus._torques_group, CAG.56 is the relative abundance of CAG.56, Sellimonas is the relative abundance of Sellimonas.

[0256] Optionally, the prediction model formula of the intestinal flora information and the stool property includes one or several of the following formulas i) to iv):

[0257] i) When the child's age is 0-15 days, the formula for predicting the stool property is:

[0258] h = 2.3775 - 0.0542 x Clostridium_sensu_stricto_1 + 0.1665 x Bacteroides + 1.9577 x

[0259] ii) When the child's age is 16 days-30 days, the formula for predicting the stool property is:

[0260] h = 2.3783 + 182.608 x Lachnospira + 8.5137 x Flavonifractor - 122.2349 x Agathobacter - 11.4688 x Phascolarctobacterium;

[0261] iii) When the child's age is 31 days-4 months, the formula for predicting the stool property is:

[0262] h = 2.3775 - 0.0542 x Clostridium_sensu_stricto_1 + 0.1665 x Bacteroides + 1.9577 x

[0263] Parabacteroides + 2.7415 x Akkermansia + 1.8706 x Citrobacter + 1.9948 x Bilophila - 1.6425 x Epulopiscium + 8.7979 x Phascolarctobacterium + 3.2822 x Collinsella - 165.6212 x Sarcina;

[0264] iv) For children aged 5 months to 6 years, the formula for predicting stool form is:

[0265] h = 2.9704 - 0.8727 x Escherichia. Shigella - 0.3608 x Clostridium_sensu_stricto_1 - 14.9315 x Staphylococcus + 0.4969 x Bacteroides - 203.9802 x Bacillus - 0.9976 x Erysipelatoclostridium - 10.9023 x Subdoligranulum + 24.0384 x Dialister - 93.5327 x Epulopiscium + 2.4099 x

[0266] Ruminococcus. torques_group - 427.6705 x CAG.56 + 333.3722 x Sellimonas.

[0267] The root mean square error, R 2 , and the mean absolute error of the above intestinal flora information and the prediction model formula of stool form are shown in Table 4.

[0268] Table 4, Root mean square error, R 2 , and mean absolute error of intestinal flora information and prediction model formula of stool form

[0269]

[0270] Further, the prediction model formula of intestinal flora information and crying condition includes one or more of the following formulas 1) to 3):

[0271] 1) For children aged 8 days to 15 days, the formula for predicting crying condition is:

[0272] h = (1.6702-1.8308) + (1.5851-2.4425) x Erysipelatoclostridium - (1.5395-1.1238) x Klebsiella - (20.1973-8.7767) x Citrobacter;

[0273] wherein Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Klebsiella is the relative abundance of Klebsiella, and Citrobacter is the relative abundance of Citrobacter;

[0274] 2) When the child is aged 16 days-30 days, the formula for predicting the crying condition is:

[0275] h = (1.5075-1.5779) + (-0.9539-38.2314) x Staphylococcus - (111.3334-14.6111) x Rothia - (15.6307-9.5096) x Phascolarctobacterium - (7.9704-5.5118) x Ruminococcus;

[0276] wherein Staphylococcus is the relative abundance of Staphylococcus, Rothia is the relative abundance of Rothia, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, and Ruminococcus is the relative abundance of Ruminococcus;

[0277] 3) When the child is aged 31 days-4 months, the formula for predicting the crying condition is:

[0278] h = (1.4678~1.5216) + (-1.2963~3.8134) x Acinetobacter - (147.9583~82.5599) x Enhydrobacter + (214.5577~611.1134) x Aeromonas - (61.6441~45.7525) x Ligilactobacillus - (1.5492~1.1626) x Veillonella + (0.3757~2.8055) x Megasphaera - (26.169~226.5171) x Prevotella - (31.1451~28.1141) x Fusobacterium - (1.1191~0.486) x Lactobacillus - (1.2058~0.9898) x Flavonifractor - (215.1284~112.9927) x Lachnospiraceae_NK4A136_group - (2.2375~8.3244) x Fusicatenibacter - (179.0185~49.5399) x Ruminococcus - (477.6953~262.9145) x Eubacterium._hallii_group - (88.7991~73.9559) x Actinomyces + (160.468~224.39) x Atopobium;

[0279] Wherein, Acinetobacter is the relative abundance of Acinetobacter, Enhydrobacter is the relative abundance of Enhydrobacter, Aeromonas is the relative abundance of Aeromonas, Ligilactobacillus is the relative abundance of Ligilactobacillus, Veillonella is the relative abundance of Veillonella, Megasphaera is the relative abundance of Megasphaera, Prevotella is the relative abundance of Prevotella, Fusobacterium is the relative abundance of Fusobacterium, Lactobacillus is the relative abundance of Lactobacillus, Flavonifractor is the relative abundance of Flavonifractor, Lachnospiraceae_NK4A136_group is the relative abundance of Lachnospiraceae NK4A136 group, Fusicatenibacter is the relative abundance of Fusicatenibacter, Ruminococcus is the relative abundance of Ruminococcus, Eubacterium._hallii_group is the relative abundance of Eubacterium hallii group, Actinomyces is the relative abundance of Actinomyces, Atopobium is the relative abundance of Atopobium;

[0280] Preferably, the prediction model formula of the intestinal flora information and the crying condition comprises one or several of the following formulas 1) to 3):

[0281] 1) When the child is 8 days to 15 days old, the formula for predicting the crying condition is:

[0282] h = 1.7244 + 1.8593 x Erysipelatoclostridium - 1.2836 x Klebsiella - 12.9963 x Citrobacter;

[0283] 2) When the child is 16 days to 30 days old, the formula for predicting the crying condition is:

[0284] h = 1.5331 + 20.0659 x Staphylococcus - 42.3019 x Rothia - 13.2372 x Phascolarctobacterium - 6.9779 x Ruminococcus;

[0285] 3) When the child is 31 days to 4 months old, the formula for predicting the crying condition is:

[0286] h = 1.4959 + 1.279 x Acinetobacter - 117.4994 x Enhydrobacter + 394.8747 x Aeromonas - 54.0312 x Ligilactobacillus - 1.3707 x Veillonella + 1.3511 x Megasphaera + 62.6096 x Prevotella - 30.0045 x Fusobacterium - 0.7988 x Lactobacillus + 0.6225 x Flavonifractor - 167.8314 x Lachnospiraceae_NK4A136_group + 3.1171 x Fusicatenibacter - 109.4375 x Ruminococcus - 89.6414 x Eubacterium. hallii_group - 82.0443 x Actinomyces + 199.7983 x Atopobium;

[0287] The root mean square error, R 2 , mean absolute error of the prediction model formula of the intestinal flora information and the crying situation are as shown in Table 5.

[0288] Table 5, the root mean square error, R 2 , mean absolute error of the prediction model formula of the intestinal flora information and the crying situation

[0289]

[0290] Further, the prediction model formula of the intestinal flora information and the night sleep situation includes one or several of the following formulas a) ~ d):

[0291] a) When the child is 0 days to 15 days old, the formula of the night sleep situation is:

[0292] h = (1.667 ~ 1.7575) + (2.0551 ~ 3.3078) x Parabacteroides;

[0293] Wherein, Parabacteroides is the relative abundance of Parabacteroides;

[0294] b) When the child is 16 days to 30 days old, the formula of the night sleep situation is:

[0295] h = (1.9871 ~ 2.1135) - (36.0173 ~ 5.136) x Lactobacillus + (19.9734 ~ 35.2859) x

[0296] Phascolarctobacterium;

[0297] wherein Lactobacillus is the relative abundance of the genus Lactobacillus, and Phascolarctobacterium is the relative abundance of the genus Phascolarctobacterium;

[0298] c) the formula for night sleep at the age of 31 days to 4 months of the child is:

[0299] h = (2.1063-2.153) + (485.8899-703.2182) x Stenotrophomonas - (1.1099-0.9931) x Enterococcus + (45.4132-142.3935) x Prevotella - (3.0807-2.7328) x Lactobacillus + (6.9523-27.6025) x Bilophila + (-0.4976-4.8429) x Flavonifractor + (3.4943-6.1713) x Sutterella + (7.1024-12.505) x Ruminococcus_torques_group - (405.374-222.0575) x unidentified_Chloroplast + (0.0185-4.2892) x Fusicatenibacter + (232.9549-397.3759) x Dorea - (3.843-2.5359) x Proteus - (126.278-76.0815) x Myroides;

[0300] wherein Stenotrophomonas is the relative abundance of the genus Stenotrophomonas, Enterococcus is the relative abundance of the genus Enterococcus, Prevotella is the relative abundance of the genus Prevotella, Lactobacillus is the relative abundance of the genus Lactobacillus, Bilophila is the relative abundance of the genus Bilophila, Flavonifractor is the relative abundance of the genus Flavonifractor, Sutterella is the relative abundance of the genus Sutterella, Ruminococcus_torques_group is the relative abundance of the genus Ruminococcus_torques_group, unidentified_Chloroplast is the relative abundance of the genus unidentified_Chloroplast, Fusicatenibacter is the relative abundance of the genus Fusicatenibacter, Dorea is the relative abundance of the genus Dorea, Proteus is the relative abundance of the genus Proteus, and Myroides is the relative abundance of the genus Myroides.

[0301] wherein Stenotrophomonas is the relative abundance of the genus Stenotrophomonas, Enterococcus is the relative abundance of the genus Enterococcus, Prevotella is the relative abundance of the genus Prevotella, Lactobacillus is the relative abundance of the genus Lactobacillus, Bilophila is the relative abundance of the genus Bilophila, Flavonifractor is the relative abundance of the genus Flavonifractor, Sutterella is the relative abundance of the genus Sutterella, Ruminococcus_torques_group is the relative abundance of the genus Ruminococcus_torques_group, unidentified_Chloroplast is the relative abundance of the genus unidentified_Chloroplast, Fusicatenibacter is the relative abundance of the genus Fusicatenibacter, Dorea is the relative abundance of the genus Dorea, Proteus is the relative abundance of the genus Proteus, and Myroides is the relative abundance of the genus Myroides.

[0302] d) For children aged 5 months to 6 years, the formula for night sleep is:

[0303] h = (1.8273-1.8898) + (5.8052-7.3144) x Staphylococcus - (5.3856-1.5202) x Enterobacter + (1.744-9.8407) x Prevotella_9 + (-1.5188-0.2748) x Erysipelatoclostridium + (-2.1975-30.4482) x Coprococcus - (66.6501-15.2271) x Fusobacterium + (-0.8691-4.0197) x Flavonifractor + (5.4952-9.5591) x Sutterella + (3.2347-5.8771) x Lachnoclostridium

[0304]

[0305] (53.2421-66.6003) x Actinomyces + (124.4522-194.2467) x Anaerostipes + (6.1294-71.2023) x Eubacterium. fissicatena group - (158.923-76.3152) x Negativicoccus + (112.5601-779.4042) x Allisonella

[0306]

[0307] ​​Wherein, Staphylococcus is the relative abundance of Staphylococcus, Enterobacter is the relative abundance of Enterobacter, Prevotella_9 is the relative abundance of Prevotella_9, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Coprococcus is the relative abundance of Coprococcus, Fusobacterium is the relative abundance of Fusobacterium, Flavonifractor is the relative abundance of Flavonifractor, Sutterella is the relative abundance of Sutterella, Lachnoclostridium is the relative abundance of Lachnoclostridium, Actinomyces is the relative abundance of Actinomyces, Anaerostipes is the relative abundance of Anaerostipes, Eubacterium._fissicatena_group is the relative abundance of Eubacterium._fissicatena_group, Negativicoccus is the relative abundance of Negativicoccus, and Allisonella is the relative abundance of Allisonella.

[0308] Preferably, the intestinal flora information and the prediction model formula of the night sleep condition include one or several of the following formulas a) ~ d):

[0309] a) When the age of the child is 0 days to 15 days, the formula of the night sleep condition is:

[0310] h = 1.7084 + 2.5764 x Parabacteroides;

[0311] b) When the age of the child is 16 days to 30 days, the formula of the night sleep condition is:

[0312] h = 2.0218 - 12.0345 x Lactobacillus + 26.0639 x Phascolarctobacterium;

[0313] c) When the age of the child is 31 days to 4 months, the formula of the night sleep condition is:

[0314] h = 2.1267 + 580.5244 * Stenotrophomonas - 1.0646 * Enterococcus + 76.9896 * Prevotella - 2.9066 * Lactobacillus + 16.0708 * Bilophila + 0.7412 * Flavonifractor + 4.4946 * Sutterella + 8.8728 * Ruminococcus_torques_group - 280.1981 * unidentified_Chloroplast + 1.3007 * Fusicatenibacter + 310.8906 * Dorea - 3.3466 * Proteus - 98.8985 * Myroides;

[0315] d) For children aged 5 months to 6 years, the formula for night sleep is:

[0316] h = 1.8537 + 6.6401 * Staphylococcus - 2.9561 * Enterobacter + 4.1107 * Prevotella_9 - 0.5677 * Erysipelatoclostridium + 8.9717 * Coprococcus - 29.4941 * Fusobacterium + 1.7762 * Flavonifractor + 7.6957 * Sutterella + 4.7329 * Lachnoclostridium + 61.5478 * Actinomyces + 164.25 * Anaerostipes + 37.7456 * Eubacterium_fissicatena_group - 121.676 * Negativicoccus + 403.4906 * Allisonella;

[0317] The root mean square error, R 2 , mean absolute error of the prediction model formula of the intestinal flora information and night sleep for children aged 5 months to 6 years are shown in Table 6.

[0318] Table 6, root mean square error, R 2 , mean absolute error of the prediction model formula of the intestinal flora information and night sleep

[0319]

[0320]

[0321] The linear model establishment effect calculated by the training set and the validation set is shown by the root mean square error, R2 Root Mean Square Error (RMSE) is the square root of the average error between the predicted value and the actual value of the model, and the smaller the value, the better the model. 2 R-squared (R2) represents the explanatory power of independent variables on dependent variables. The closer the value is to 1, the stronger the explanatory power of the model; and the smaller the value, the better the model.

[0322] The above results show that the model formula obtained by the present application has good prediction performance.

[0323] Specific tests are as follows:

[0324] Test Example 1: Neuropsychological prediction

[0325] Three samples of 31 days to 4 months were randomly selected, and the relative abundance of the genus related to neuropsychology in this age group was brought into the corresponding formula:

[0326] h = 51.9239 - 249.4833 Staphylococcus - 2448.8087 Ligilactobacillus + 1394.1283 Ruminococcus. Torques group;

[0327] The model prediction value was calculated, and the prediction value was evaluated according to the prediction value specification, and the results are shown in Table 7. It was found that the model evaluation state was similar to the actual state of the child, proving that the model fitting was good, and the prediction of the ASQ3 questionnaire score using the flora could be realized.

[0328] Table 7: Comparison of neuropsychological questionnaire scores and model prediction results

[0329] Indicator Sample 1 Sample 2 Sample 3 Questionnaire score 50 45 45 Staphylococcus 0.00135318 0.00405954 0 Ligilactobacillus 0 0.00270636 0.00270636 [Ruminococcus]_torques_group 0 0 0 Model prediction 51.5863 44.2838 45.2965 Difference (questionnaire score - model prediction) -1.5863 0.7162 -0.2965 .

[0330] Test Example 2: Crying state prediction

[0331] Three samples of 16 to 30 days were randomly selected, and the specific relative abundance of the genus related to the crying condition in this age group was brought into the corresponding formula:

[0332] h = 1.5331 + 20.0659 Staphylococcus - 42.3019 Rothia - 13.2372 Phascolarctobacterium - 6.9779 Ruminococcus;

[0333] The model prediction value is calculated, and the prediction value is evaluated according to the prediction value specification. The results are shown in Table 8. It is found that the model evaluation state is the same as the actual state of the child, proving that the model fitting is good, and the evaluation of the crying state by the bacterial flora can be realized.

[0334] Table 8, comparison of actual state and prediction results of crying situation

[0335]

[0336]

[0337] Test Example 3: Sleep state prediction

[0338] Three samples of 31 days to 4 months were randomly selected, and the specific relative abundance of the genus related to the sleep state of this age group was brought into the corresponding formula:

[0339] h = 2.1267 + 580.5244 x Stenotrophomonas - 1.0646 x Enterococcus + 76.9896 x Prevotella - 2.9066 x Lactobacillus + 16.0708 x Bilophila + 0.7412 x Flavonifractor + 4.4946 x Sutterella + 8.8728 x Ruminococcus. Torques group - 280.1981 x unidentified Chloroplast + 1.3007 x Fusicatenibacter + 310.8906 x Dorea - 3.3466 x Proteus - 98.8985 x Myroides

[0340] The model prediction value is calculated, and the prediction value is evaluated according to the prediction value specification. The results are shown in Table 8. It is found that the model evaluation state is the same as the actual state of the child, proving that the model fitting is good, and the evaluation of the crying state by the bacterial flora can be realized.

[0341] Table 9, comparison of actual state and prediction results of sleep situation

[0342] Indicator Sample 1 Sample 2 Sample 3 Actual score of sleep state 2 3 2 Stenotrophomonas 0 0 0 Enterococcus 0.00270636 0 0 Prevotella 0 0 0 Lactobacillus 0 0 0 Bilophila 0 0 0.00541272 Flavonifractor 0 0.01082544 0 Sutterella 0.02435724 0.01488498 0 [Ruminococcus]_torques_group 0 0.067658999 0 unidentified_Chloroplast 0.00135318 0 0 Fusicatenibacter 0.00135318 0 0 Dorea 0 0 0 Proteus 0 0 0 Myroides 0 0 0 Model prediction 1.855896476 2.801950614 2.213686741 Judgment result value (tendency result value obtained from prediction value) 2 3 2 .

[0343] Test Example 4: Stool shape prediction

[0344] Three samples of 8 to 15 days were randomly selected, and the specific relative abundance of the genus related to the stool shape of this age group was brought into the corresponding formula:

[0345] h = 2.6152 - 1.1958*Staphylococcus - 3.6283*Veillonella - 1.8468*Parabacteroides + 152.3533*Dialister - 3.5718*Haemophilus;

[0346] The model prediction value is calculated, and the prediction value is evaluated according to the prediction value specification, and the results are shown in Table 10, and it is found that the model evaluation state is the same as the actual state of the child, proving that the model fitting is good, and the evaluation of sleep state by using the flora can be realized.

[0347] Table 10, Comparison of actual state and prediction results of stool characteristics

[0348] Indicator Sample 1 Sample 2 Sample 3 Actual score of stool form 2 3 2 Staphylococcus 0.09472 0 0.00406 Veillonella 0 0 0.00135 Parabacteroides 0 0 0.39513 Dialister 0 0 0 Haemophilus 0.16915 0.00271 0 Model prediction 1.89777 2.60553 1.87571 Judgment result value (tendency result value obtained from prediction value) 2 3 2 .

[0349] Test Example 5: Skin prediction

[0350] Three samples of 31 days to 4 months were randomly selected, and the specific skin-related genus relative abundance of this age group was brought into the corresponding formula:

[0351] h = (0.0659-0.0894) + (0.2965-0.4306)*Clostridium_sensu_stricto_1 + (298.8977-432.2361)*Brevundimonas + (1.6479-2.5646)*Subdoligranulum - (21.6623-5.945)*Faecalibacterium;

[0352] The model prediction value is calculated, and the prediction value is evaluated according to the prediction value specification, and the results are shown in Table 11, and it is found that the model evaluation state is the same as the actual state of the child, proving that the model fitting is good, and the evaluation of sleep state by using the flora can be realized.

[0353] Table 11, Comparison of actual state and prediction results of skin

[0354] Indicator Sample 1 Sample 2 Sample 3 Skin problems 0 1 1 Clostridium_sensu_stricto_1 0.34776725 0.29364005 0.34641407 Brevundimonas 0 0 0 Subdoligranulum 0.0121786 0.25981056 0.26792964 Faecalibacterium 0 0 0 Model prediction 0.23579121 0.72163397 0.75818809 Judgment result value (tendency result value obtained from prediction value) 0 1 1 .

[0355] The above results show that the prediction and evaluation formula of the present application has good model fitting effect, and can realize accurate prediction of neuro-psychological development, skin, stool, crying condition, night sleep and the like, and has good evaluation value.

[0356] It has been verified that the fitting effect of other model formulas is also good.

[0357] In a second aspect, there is provided a system for evaluating the growth and development state of a child aged 0-6 years, applied to the method of any one of the first aspect, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.

[0358] In a third aspect, there is provided use of the method of the first aspect or the system of the second aspect in the preparation of a product for evaluating the growth and development state of a child aged 0-6 years.

[0359] The beneficial effects of the present application include:

[0360] 1. The data used in the embodiments of the present application are all from children aged 0-6 years in China, and all belong to breast-feeding, the clinical cohort covers multiple regions in China, the tracking time is relatively long, the data content is rich, and it is more suitable for being used as an index for measuring children aged 0-6 years in China.

[0361] 2. The current evaluation of the health level of infants is mainly through the development indicators of neuropsychological development, skin, stool, crying, night sleep, and the neuropsychological development indicators of language, action, problem solving ability, whether the child is sick and the type of disease, and other health status indicators, but it is difficult to evaluate the health level of the internal development of the infant. The present application increases the angle of health evaluation of the internal development state of children aged 0-6 years by establishing the intestinal flora change curve and reference range of children aged 0-6 years.

[0362] 3. Evaluating the development level of children through neuropsychological development, skin, stool, crying, night sleep and other information is a monitoring of the development result indicators of children, that is, there are differences in the clinical manifestations of infant health caused by the internal development of the intestinal flora of children, and the neuropsychological development, skin, stool, crying, night sleep indicators of children in the near and long term are predicted through the intestinal flora of children, providing a target point that can be referred to for improvement, which can find possible adverse development results in the future and prevent and improve in time.

[0363] 4. The intestinal flora is in a state of continuous dynamic change and maintenance, external intervention has an impact on the composition of the flora, and the intestinal flora of children aged 0-6 years is more susceptible to external influences. It is difficult to say the final outcome of child development caused by the influence of different factors on the intestinal flora of children, and the reference standard of the flora provided by the present application can timely find the possible adverse development of the intestinal flora and change the adverse outcome.

[0364] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for evaluating the growth and development state of children aged 0-6 years based on intestinal flora, characterized in that, The development state to be evaluated includes one or more of the following: stool, crying, and sleep at night; the method comprises the following steps: Obtaining intestinal flora information of a target population to be predicted; the intestinal flora information includes relative abundance information of flora significantly related to a corresponding development state; Inputting the intestinal flora information into a pre-constructed prediction and evaluation model to obtain an evaluation result output by the prediction and evaluation model; the evaluation result includes a quantitative result of the corresponding development state, and the quantitative result corresponds to different development states; The prediction and evaluation model is obtained by multiple regression calculation according to the screened corresponding intestinal flora information significantly related to the development state to be evaluated; When the development state to be evaluated is stool traits, the flora significantly related to the stool traits includes several bacterial collections related to age as follows: i) Staphylococcus, Veillonella, Parabacteroides, Dialister, Haemophilus; ii) Lachnospira, Flavonifractor, Agathobacter, Phascolarctobacterium; iii) Clostridium sensu stricto 1, Bacteroides, Parabacteroides, Akkermansia, Citrobacter, Bilophila, Epulopiscium, Phascolarctobacterium, Collinsella, Sarcina; iv) Escherichia. Shigella, Clostridium_sensu_stricto_1, Staphylococcus, Bacteroides, Bacillus, Erysipelatoclostridium, Subdoligranulum, Dialister, Epulopiscium, Ruminococcus. torques_group, CAG.56, Sellimonas; Alternatively, when the development state to be evaluated is crying, the flora significantly related to crying includes several bacterial collections related to age as follows: 1) Erysipelatoclostridium, Klebsiella, Citrobacter; 2) Staphylococcus, Rothia, Phascolarctobacterium, Ruminococcus; 3) Acinetobacter, Enhydrobacter, Aeromonas, Ligilactobacillus, Veillonella, Megasphaera, Prevotella, Fusobacterium, Lactobacillus, Flavonifractor, Lachnospiraceae_NK4A136_group, Fusicatenibacter, Ruminococcus, Eubacterium. hallii_group, Actinomyces, Atopobium; Or, when the development state to be evaluated is night sleep condition, the flora significantly related to the night sleep condition includes several bacterial collections a) ~ d) as follows: a) Parabacteroides; b) Lactobacillus, Phascolarctobacterium; c) Stenotrophomonas, Enterococcus, Prevotella, Lactobacillus, Bilophila, Flavonifractor, Sutterella, Ruminococcus. torques_group, unidentified_Chloroplast, Fusicatenibacter, Dorea, Proteus, Myroides; d) Staphylococcus, Enterobacter, Prevotella_9, Erysipelatoclostridium, Coprococcus, Fusobacterium, Flavonifractor, Sutterella, Lachnoclostridium, Actinomyces, Anaerostipes, Eubacterium. fissicatena_group, Negativicoccus, Allisonella.

2. The method of claim 1, wherein, The prediction evaluation model includes several prediction evaluation sub-models distinguished according to age and the development state to be evaluated; the selection of the prediction evaluation sub-model is based on age and the development state to be evaluated, and the corresponding intestinal flora information significantly related to the corresponding age range and the development state to be evaluated is input for prediction evaluation.

3. The method of claim 1, wherein, The intestinal flora information is obtained by detection in the fecal sample of the target population to be predicted.

4. The method of claim 1, wherein, The construction method of the prediction evaluation model includes: Obtaining intestinal flora information of a plurality of samples of a plurality of regions, combining the intestinal flora information and clinical information to establish an intestinal flora database of children aged 0-6 years old, the intestinal flora information including relative abundance information of flora at the level of door, department and genus, and the clinical information including age and development state information; the development state information including one or more of stool, crying and night sleep state information; the development state information is quantitatively processed, including: scoring according to stool shape, scoring according to crying, and scoring according to the number of awakenings during night sleep; Grouping the data in the database according to age, and grouping again according to the relative abundance of flora in the group, to divide into a high-abundance group and a low-abundance group with the average value of the relative abundance of each bacterium as the boundary, calculating the average value of the quantitatively processed development state information of the high-abundance group and the low-abundance group respectively, comparing the average values of the two groups to obtain a difference multiple, and performing significance analysis; Selecting bacteria significantly related to clinical information as independent variables, the score or score of the clinical information of children aged 0-6 years old as dependent variables, setting a random seed for each age group, randomly dividing the data into a training set and a validation set in proportion, performing multiple linear regression calculation on the training set to obtain a linear prediction model of the flora and the clinical information of children aged 0-6 years old, and testing by the validation set; Obtaining a plurality of linear regression models according to the number of random seeds, inducing the model coefficient range according to the plurality of models, taking the average value as the calculation model coefficient to obtain a prediction evaluation model, and evaluating the development state of children aged 0-6 years old according to the predicted clinical information of children aged 0-6 years old.

5. The method of claim 4, wherein, The construction of the intestinal flora database of children aged 0-6 years old includes: collecting the feces of children aged 0-6 years old, sequencing and analyzing by 16S amplicon sequencing technology to obtain sequencing data corresponding to the intestinal flora of children aged 0-6 years old, denoising and aggregating the sequencing data to obtain basic classification units OTUs, annotating the classification units to obtain the composition of the intestinal flora of children aged 0-6 years old, and combining the intestinal flora information and the clinical information according to the sample number to establish the intestinal flora database of children aged 0-6 years old.

6. The method of claim 5, wherein, The denoising includes: Reads splicing filtering and OTUs clustering.

7. The method according to any one of claims 1 to 6, characterized in that, When the development state to be evaluated is stool shape, the bacteria in set i) are children aged 0-15 days; the bacteria in set ii) are children aged 16 days-30 days; the bacteria in set iii) are children aged 31 days-4 months; and the bacteria in set iv) are children aged 5 months-6 years old; And / or, when the development state to be evaluated is crying, the bacteria in set 1) are children aged 8 days-15 days; the bacteria in set 2) are children aged 16 days-30 days; and the bacteria in set 3) are children aged 31 days-4 months; And / or, when the development state to be evaluated is night sleep, the bacteria in set a) are children aged 0 days-15 days; the bacteria in set b) are children aged 16 days-30 days; the bacteria in set c) are children aged 31 days-4 months; and the bacteria in set d) are children aged 5 months-6 years old.

8. The method of claim 7, wherein, The clinical information includes stool, crying or night sleep; The prediction model formulae of the intestinal flora information and the stool form include one or several of the following formulae i) to iv): i) When the child is 0 to 15 days old, the formula for predicting the stool form is: h = (2.5624-2.6469) - (2.6623-0.8585) x Staphylococcus - (4.0757-3.3154) x Veillonella - (2.3037-1.444) x Parabacteroides + (8.4342-535.3406) x Dialister - (3.8718-3.0043) x Haemophilus wherein Staphylococcus is the relative abundance of Staphylococcus, Veillonella is the relative abundance of Veillonella, Parabacteroides is the relative abundance of Parabacteroides, Dialister is the relative abundance of Dialister, and Haemophilus is the relative abundance of Haemophilus; ii) When the child is 16 to 30 days old, the formula for predicting the stool form is: h = (2.3114-2.4241) + (2.4508-683.2421) x Lachnospira + (2.3546-12.7348) x Flavonifractor - (405.4702-62.5708) x Agathobacter - (13.1682-9.6822) x Phascolarctobacterium wherein Lachnospira is the relative abundance of Lachnospira, Flavonifractor is the relative abundance of Flavonifractor, Agathobacter is the relative abundance of Agathobacter, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium; iii) When the child is 31 days to 4 months old, the formula for predicting the stool form is: h = (2.3441-2.441) + (-0.1699-0.0419) x Clostridium_sensu_stricto_1 + (0.0728-0.2473) x Bacteroides + (1.7218-2.1934) x Parabacteroides + (1.2942-3.6235) x Akkermansia + (-0.5946-2.7963) x Citrobacter + (-11.0145-21.6328) x Bilophila - (1.8488-1.354) x Epulopiscium + (6.8497-11.2683) x Phascolarctobacterium + (2.3211-5.0496) x Collinsella - (221.8181-121.729) x Sarcina wherein Clostridium_sensu_stricto_1 is the relative abundance of Clostridium sensu stricto 1, Bacteroides is the relative abundance of Bacteroides, Parabacteroides is the relative abundance of Parabacteroides, Akkermansia is the relative abundance of Akkermansia, Citrobacter is the relative abundance of Citrobacter, Bilophila is the relative abundance of Bilophila, Epulopiscium is the relative abundance of Epulopiscium, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, and Sarcina is the relative abundance of Sarcina. ​ ​ ​ ​ ​ wherein Clostridium_sensu_stricto_1 is the relative abundance of Clostridium sensu stricto 1, Bacteroides is the relative abundance of Bacteroides, Parabacteroides is the relative abundance of Parabacteroides, Akkermansia is the relative abundance of Akkermansia, Citrobacter is the relative abundance of Citrobacter, Bilophila is the relative abundance of Bilophila, Epulopiscium is the relative abundance of Epulopiscium, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, Sarcina is the relative abundance of Sarcina; iv) When the child is aged from 5 months to 6 years, the formula for predicting the stool form is: h = (2.9053-3.0947) - (1.0973-0.7369) x Escherichia. Shigella - (0.4223-0.3035) x Clostridium_sensu_stricto_1 - (15.7456-14.3356) x Staphylococcus + (0.3984-0.5591) x Bacteroides - (399.5418-60.4927) x Bacillus - (1.4938-0.4026) x Erysipelatoclostridium - (12.6503-8.9228) x Subdoligranulum + (22.3406-24.9229) x Dialister - (104.8873-77.8148) x Epulopiscium + (-0.347-7.5903) x Ruminococcus. torques_group - (458.5554-407.3394) x CAG.56 + (218.2145-397.8098) x Sellimonas; Wherein, Escherichia.Shigella is the relative abundance of Escherichia-Shigella, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium_sensu_stricto_1, Staphylococcus is the relative abundance of Staphylococcus, Bacteroides is the relative abundance of Bacteroides, Bacillus is the relative abundance of Bacillus, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Subdoligranulum is the relative abundance of Subdoligranulum, Dialister is the relative abundance of Dialister, Epulopiscium is the relative abundance of Epulopiscium, Ruminococcus._torques_group is the relative abundance of Ruminococcus._torques_group, CAG.56 is the relative abundance of CAG.56, Sellimonas is the relative abundance of Sellimonas; And / or, the prediction model formula of the intestinal flora information and the crying condition includes one or several of the following formulas 1)~3): 1) When the child is 8 days to 15 days old, the formula for predicting the crying condition is: h=(1.6702~1.8308)+(1.5851~2.4425)xErysipelatoclostridium-(1.5395~1.1238)Klebsiella-(20.1973~8.7767)Citrobacter; Wherein, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Klebsiella is the relative abundance of Klebsiella, and Citrobacter is the relative abundance of Citrobacter; 2) When the child is 16 days to 30 days old, the formula for predicting the crying condition is: h=(1.5075~1.5779)+(-0.9539~38.2314)Staphylococcus-(111.3334~14.6111)Rothia-(15.6307~9.5096)Phascolarctobacterium-(7.9704~5.5118)Ruminococcus; Wherein, Staphylococcus is the relative abundance of Staphylococcus, Rothia is the relative abundance of Rothia, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, and Ruminococcus is the relative abundance of Ruminococcus; 3) When the child is 31 days to 4 months old, the formula for predicting the crying condition is: ​ ​ h = (1.4678~1.5216) + (-1.2963~3.8134) * Acinetobacter + (-147.9583~82.5599) * Enhydrobacter + (214.5577~611.1134) * Aeromonas + (-61.6441~45.7525) * Ligilactobacillus + (-1.5492~1.1626) * Veillonella + (0.3757~2.8055) * Megasphaera + (-26.169~226.5171) * Prevotella + (-31.1451~28.1141) * Fusobacterium + (-1.1191~0.486) * Lactobacillus + (-1.2058~0.9898) * Flavonifractor + (-215.1284~112.9927) * Lachnospiraceae_NK4A136_group + (-2.2375~8.3244) * Fusicatenibacter + (179.0185~49.5399) * Ruminococcus + (-477.6953~262.9145) * Eubacterium._hallii_group + (160.468~224.39) * Actinomyces + (0.0000~0.0000) * Atopobium wherein, Acinetobacter is the relative abundance of Acinetobacter, Enhydrobacter is the relative abundance of Enhydrobacter, Aeromonas is the relative abundance of Aeromonas, Ligilactobacillus is the relative abundance of Ligilactobacillus, Veillonella is the relative abundance of Veillonella, Megasphaera is the relative abundance of Megasphaera, Prevotella is the relative abundance of Prevotella, Fusobacterium is the relative abundance of Fusobacterium, Lactobacillus is the relative abundance of Lactobacillus, Flavonifractor is the relative abundance of Flavonifractor, Lachnospiraceae_NK4A136_group is the relative abundance of Lachnospiraceae_NK4A136_group, Fusicatenibacter is the relative abundance of Fusicatenibacter, Ruminococcus is the relative abundance of Ruminococcus, Eubacterium._hallii_group is the relative abundance of Eubacterium._hallii_group, Actinomyces is the relative abundance of Actinomyces, Atopobium is the relative abundance of Atopobium. ​ ​ ​ ​ ​ And / or, the prediction model formula of the intestinal flora information and the night sleep condition comprises one or more of the following formulas a)~d): a) when the child age is 0 days~15 days, the formula of the night sleep condition is: h=(1.667~1.7575)+(2.0551~3.3078)XParabacteroides; Wherein, Parabacteroides is the relative abundance of Parabacteroides; b) when the child age is 16 days~30 days, the formula of the night sleep condition is: h=(1.9871~2.1135)-(36.0173~5.136)XLactobacillus+(19.9734~35.2859)XPhascolarctobacterium; Wherein, Lactobacillus is the relative abundance of Lactobacillus, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium; c) when the child age is 31 days~4 months, the formula of the night sleep condition is: h=(2.1063~2.153)+(485.8899~703.2182)XStenotrophomonas- (1.1099~0.9931)XEnterococcus+(45.4132~142.3935)XPrevotella- (3.0807~2.7328)XLactobacillus+(6.9523~27.6025)XBilophila+(-0.4976~4.8429)XFlavonifractor+(3.4943~6.1713)XSutterella+(7.1024~12.505)XRuminococcus._torques_group-(405.374~222.0575)Xunidentified_Chloroplast+ (0.0185~4.2892)XFusicatenibacter+(232.9549~397.3759)XDorea-(3.843~2.5359)XProteus-(126.278~76.0815)XMyroides; ​ Wherein, Stenotrophomonas is the relative abundance of Stenotrophomonas, Enterococcus is the relative abundance of Enterococcus, Prevotella is the relative abundance of Prevotella, Lactobacillus is the relative abundance of Lactobacillus, Bilophila is the relative abundance of Bilophila, Flavonifractor is the relative abundance of Flavonifractor, Sutterella is the relative abundance of Sutterella, Ruminococcus. Torques group is the relative abundance of Ruminococcus. Torques group, Unidentified Chloroplast is the relative abundance of Unidentified Chloroplast, Fusicatenibacter is the relative abundance of Fusicatenibacter, Dorea is the relative abundance of Dorea, Proteus is the relative abundance of Proteus, Myroides is the relative abundance of Myroides; d) The formula for night sleep when the child is 5 months to 6 years old is: h = (1.8273-1.8898) + (5.8052-7.3144) x Staphylococcus - (5.3856-1.5202) x Enterobacter + (1.744-9.8407) x Prevotella_9 + (-1.5188-0.2748) x Erysipelatoclostridium + (-2.1975-30.4482) x Coprococcus - (66.6501-15.2271) x Fusobacterium + (-0.8691-4.0197) x Flavonifractor + (5.4952-9.5591) x Sutterella + (3.2347-5.8771) x Lachnoclostridium + (53.2421-66.6003) x Actinomyces + (124.4522-194.2467) x Anaerostipes + (6.1294-71.2023) x Eubacterium. Fissicatena group - (158.923-76.3152) x Negativicoccus + (112.5601-779.4042) x Allisonella; h = (1.8273-1.8898) + (5.8052-7.3144) x Staphylococcus - (5.3856-1.5202) x Enterobacter + (1.744-9.8407) x Prevotella_9 + (-1.5188-0.2748) x Erysipelatoclostridium + (-2.1975-30.4482) x Coprococcus - (66.6501-15.2271) x Fusobacterium + (-0.8691-4.0197) x Flavonifractor + (5.4952-9.5591) x Sutterella + (3.2347-5.8771) x Lachnoclostridium + (53.2421-66.6003) x Actinomyces + (124.4522-194.2467) x Anaerostipes + (6.1294-71.2023) x Eubacterium. Fissicatena group - (158.923-76.3152) x Negativicoccus + (112.5601-779.4042) x Allisonella; ​ ​ ​ ​ ​ Wherein, Staphylococcus is the relative abundance of Staphylococcus, Enterobacter is the relative abundance of Enterobacter, Prevotella_9 is the relative abundance of Prevotella_9, Erysipelatoclostridium is the relative abundance of Erysipelatoclostridium, Coprococcus is the relative abundance of Coprococcus, Fusobacterium is the relative abundance of Fusobacterium, Flavonifractor is the relative abundance of Flavonifractor, Sutterella is the relative abundance of Sutterella, Lachnoclostridium is the relative abundance of Lachnoclostridium, Actinomyces is the relative abundance of Actinomyces, Anaerostipes is the relative abundance of Anaerostipes, Eubacterium._fissicatena_group is the relative abundance of Eubacterium._fissicatena_group, Negativicoccus is the relative abundance of Negativicoccus, Allisonella is the relative abundance of Allisonella.

9. A system for assessing the state of growth and development of a child aged 0-6 years, for use in the method of any one of claims 1-8, characterized in that, A computer program product comprising a memory, a processor and a computer program stored on the memory and loadable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 8 when running the program.

10. Use of the method according to any one of claims 1 to 8, or of the system according to claim 9, for the manufacture of a product for assessing the state of growth and development of a child of 0 to 6 years of age.

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