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

Abstract

The invention 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 to-be-evaluated development state 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

Technical Field

[0001] The present invention relates to the field of development assessment of children aged 0 to 6 years old, and in particular to a method, system and application for assessing the growth and development status of children aged 0 to 6 years old based on intestinal flora. Background Art

[0002] The human body consists of about 10 14 There are many microorganisms in the human intestine, most of which are parasitic in the human intestine. The microorganisms in the human intestine play an important role in the individual's nutritional metabolism, immunity, and physiological function regulation. The 0-6-year-old childhood is an important window period for the establishment of individual intestinal flora, which has a great influence on the establishment and maturity of the future intestinal flora. The biggest characteristics of the intestinal flora of children aged 0-6 are instability, variability, large individual differences, and susceptibility to external factors.

[0003] Although there are large differences in the intestinal flora of children aged 0 to 6 years, there is a certain regularity in the intestinal flora of infants and young children from the initial colonization to the subsequent continuous evolution after birth. At present, it is generally believed that the development pattern of intestinal microorganisms in infants and young children is that facultative anaerobes colonize in the early stage and continuously consume oxygen in the intestine. When the intestine becomes an anaerobic environment, strict anaerobes begin to colonize the intestines of infants and young children. As infants and young children grow up, the intestinal flora slowly develops from low diversity and low complexity at the beginning to high diversity and complexity. This process usually takes three to four years. The intestine is the digestive and absorptive organ of the human body, and it is also the largest immune organ of the human body. The colonization of intestinal flora in early life affects the development of individuals in early life to a certain extent.

[0004] Feeding methods affect intestinal flora and short- and long-term health. The World Health Organization and UNICEF recommend that mothers should insist on exclusive breastfeeding for the first 6 months after the baby is born. Breast milk is rich in nutrients that can meet the energy and nutrition necessary for children's early growth and development. It also contains a variety of oligosaccharides and prebiotics, which can regulate the composition of infants' intestinal flora, improve children's immunity, and reduce the risk of infectious diseases.

[0005] Indicators such as neuropsychological development, skin, bowel movements, crying, and night sleep assess children's healthy development from various dimensions. The factors that influence the indicators are diverse. Currently, the observation of these indicators is mainly through in vitro discoveries, while ignoring the relationship between changes in children's bodies and clinical manifestations.

[0006] Therefore, this invention is proposed. Summary of the invention

[0007] Purpose of the Invention

[0008] To overcome the above shortcomings, the purpose of the present invention is to provide a method, system and application for evaluating the growth and development status of children aged 0 to 6 years old. The present invention increases the perspective of health assessment of the in vivo development status of children aged 0 to 6 years old by establishing a change curve and reference range of intestinal flora of children aged 0 to 6 years old.

[0009] Solution

[0010] To achieve the purpose of the present invention, the technical solution adopted by the present invention is as follows:

[0011] In a first aspect, the present invention provides a method for evaluating the growth and development status of children aged 0 to 6 years old, wherein the development status to be evaluated includes one or more of neuropsychological development, skin, defecation, crying, and night sleep; the method comprises the following steps:

[0012] Obtaining intestinal flora information of the target population to be predicted; the intestinal flora information includes relative abundance information of flora significantly associated with the corresponding developmental state;

[0013] Inputting the intestinal flora information into a pre-built prediction and evaluation model to obtain an evaluation result output by the prediction and evaluation model, the evaluation result including: a quantitative result of a corresponding developmental state, wherein the quantitative result corresponds to different developmental states;

[0014] Among them, the predictive evaluation model is obtained through multivariate regression calculation based on the corresponding intestinal flora information that is significantly correlated with the developmental status to be evaluated.

[0015] Furthermore, the prediction and evaluation model includes several prediction and evaluation sub-models differentiated according to age and developmental status to be evaluated; the prediction and evaluation sub-models are selected according to age and developmental status to be evaluated, and corresponding intestinal flora information significantly related to the corresponding age group and developmental status to be evaluated is input for prediction and evaluation; and / or,

[0016] The intestinal flora information is obtained by detecting stool samples of the target population to be predicted.

[0017] Furthermore, the method for constructing the prediction and evaluation model includes:

[0018] Obtain intestinal flora information of several samples from multiple regions, merge intestinal flora information and clinical information to establish an intestinal flora database for children aged 0 to 6 years old, intestinal flora information includes relative abundance information of flora at the phylum, family, and genus levels, and clinical information includes age and developmental status information; developmental status information includes one or more of neuropsychological development, skin, stool, crying, and night sleep; quantify the developmental status information, including: scoring of neuropsychological development questionnaires, scoring based on whether or not there is a skin disease, scoring based on stool characteristics, scoring based on crying, and scoring based on the number of awakenings during night sleep;

[0019] The data in the database were grouped by age, and then grouped again according to the relative abundance of the flora within the group. The average value of the relative abundance of each bacterium was used as the boundary to divide the data into a high-abundance group and a low-abundance group. The means of the quantitative developmental status information of the high-abundance group and the low-abundance group were calculated respectively. The means of the two groups were compared to obtain the difference multiple and perform significance analysis.

[0020] Select bacteria significantly correlated with clinical information as independent variables, and the scores or assignments of clinical information of children aged 0 to 6 years old as dependent variables. Set the random seeds for each age group, randomly divide the data into training set and validation set in proportion, perform linear regression calculation on the training set, obtain the linear prediction model of bacterial flora and clinical information of children aged 0 to 6 years old, and test it with the validation set.

[0021] According to the number of random seeds, multiple linear regression models were obtained. Based on the multiple models obtained, the range of model coefficients was summarized, and the average value was used as the calculation model coefficient to obtain a predictive evaluation model. According to the predicted clinical information of children aged 0 to 6 years old, the developmental status of children aged 0 to 6 years old was evaluated.

[0022] Furthermore, the construction of the intestinal flora database of children aged 0 to 6 years old includes: collecting feces of children aged 0 to 6 years old, sequencing and analyzing them through 16S amplicon sequencing technology to obtain sequencing data corresponding to the intestinal flora of children aged 0 to 6 years old, denoising and aggregating the sequencing data to obtain basic classification units OTUs, annotating the classification units with species to obtain the composition of the intestinal flora of children aged 0 to 6 years old, merging the intestinal flora information and clinical information according to the sample number, and establishing a intestinal flora database for children aged 0 to 6 years old.

[0023] Furthermore, noise reduction includes: reads splicing and filtering, and then OTUs clustering.

[0024] Furthermore, when the developmental state to be evaluated is neuropsychological development, the bacterial flora significantly associated with neuropsychological development includes the following bacterial collections (1) to (3) that are related to age:

[0025] (1) Staphylococcus, Ligilactobacillus, Ruminococcus._torques_group; Optionally, the child is aged between 0 days and 4 months;

[0026] (2) Veillonella and Prevotella; optionally, the child is between 5 and 12 months old;

[0027] (3) TM7x (TM7x), Weissella, Devosia, Bradyrhizobium, Atopobium, Glutamicibacter, Cupriavidus, Lachnospiraceae_FCS020_group, RB41; Optionally, the child is aged between 13 months and 6 years;

[0028] Alternatively, when the developmental state to be evaluated is the skin, the bacterial flora significantly associated with the skin includes the following bacterial collections (i) to (ii) that are associated with age:

[0029] (i) Clostridium_sensu_stricto_1 (Clostridium sensu_stricto_1), Brevundimonas (Brevundimonas), Subdoligranulum (Subdoligranulum), Faecalibacterium (Faecalibacterium); children aged 0 days to 4 months;

[0030] (ii) Bifidobacterium, Bacillus;

[0031] Alternatively, when the developmental status to be evaluated is stool characteristics, the bacterial flora significantly associated with stool characteristics includes the following bacterial collections i) to iv) that are related to age:

[0032] i) Staphylococcus, Veillonella, Parabacteroides, Dialister, Haemophilus; Optionally, children aged 0 to 15 days;

[0033] ii) Lachnospira, Flavonifractor, Agathobacter, Phascolarctobacterium; Optionally, the child is aged between 16 and 30 days;

[0034] iii) Clostridium_sensu_stricto_1 (strict Clostridium 1), Bacteroides, Parabacteroides, Akkermansia, Citrobacter, Bilophila, Epulopiscium, Phascolarctobacterium, Collinsella, Sarcina; Optionally, the child is aged between 31 days and 4 months;

[0035] iv) Escherichia.Shigella, Clostridium_sensu_stricto_1, Staphylococcus, Bacteroides, Bacillus, Erysipelatoclostridium, Subdoligranulum, Dialister, Epulopiscium, Ruminococcus._torques_group, CAG.56, Sellimonas; Optionally, the child is aged between 5 months and 6 years;

[0036] Alternatively, when the developmental state to be evaluated is crying, the bacterial flora significantly associated with crying includes the following bacterial collections 1) to 3) that are related to age:

[0037] 1) Erysipelatoclostridium, Klebsiella, Citrobacter; Optionally, children aged 8 to 15 days;

[0038] 2) Staphylococcus, Rothia, Phascolarctobacterium, Ruminococcus; Optionally, children aged 16 to 30 days;

[0039] 3) Acinetobacter, Enhydrobacter, Aeromonas, Ligilactobacillus, Veillonella, Megasphaera, Prevotella, Fusobacterium, Lactobacillus, Flavonifractor, Lachnospiraceae_NK4A136_group, Fusicatenibacter, Ruminococcus, Eubacterium._hallii_group, Actinomyces, Atopobium; Optionally, the child is 31 days to 4 months old;

[0040] Alternatively, when the developmental state to be evaluated is the nighttime sleep condition, the bacterial flora significantly associated with the nighttime sleep condition includes the following bacterial collections a) to d) associated with age:

[0041] a) Parabacteroides (Parabacteroides);

[0042] b) Lactobacillus (Lactobacillus), Phascolarctobacterium (Phascolarctobacterium);

[0043] c) Stenotrophomonas, Enterococcus, Prevotella, Lactobacillus, Bilophila, Flavonifractor, Sutterella, Ruminococcus_torques_group, unidentified_Chloroplast, Fusicatenibacter, Dorea, Proteus, Myroides;

[0044] d) Staphylococcus, Enterobacter, Prevotella_9, Erysipelatoclostridium, Coprococcus, Fusobacterium, Flavonifractor, Sutterella, Lachnoclostridium, Actinomyces, Anaerostipes, Eubacterium._fissicatena_group, Negativicoccus, Allisonella.

[0045] Furthermore, methods of grouping by age include: 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, and 37 months-6 years.

[0046] Furthermore, clinical information included neuropsychological development, skin, bowel movements, crying conditions, or nighttime sleep;

[0047] The prediction model formula of intestinal flora information and neuropsychological development includes one or more of the following formulas (1) to (3):

[0048] (1) When children are between 0 days and 4 months old, the formula for predicting neuropsychological development is:

[0049] h=(51.0705~52.7283)+(-540.3316~54.9656)×Staphylococcus-(3599.8924~2076.5719)×Ligilactobacillus+(127.5668~3359.586)×Ruminococcus._torques_group;

[0050] Alternatively h = 51.9239-249.4833×Staphylococcus-2448.8087×Ligilactobacillus+1394.1283×Ruminococcus._torques_group;

[0051] Among them, Staphylococcus is the relative abundance of Staphylococcus, Ligilactobacillus is the relative abundance of Lactobacillus, and Ruminococcus._torques_group is the relative abundance of Ruminococcus._torques_group;

[0052] (2) When children are between 5 and 12 months old, the formula for predicting neuropsychological development is:

[0053] h=(55.2745~56.409)-(34.2045~26.1645)×Veillonella+(794.7139~2787.5344)×Prevotella;

[0054] Optionally h = 55.8377-30.5745×Veillonella+1188.1085×Prevotella;

[0055] Among them, Veillonella is the relative abundance of Veillonella, and Prevotella is the relative abundance of Prevotella;

[0056] (3) When children are between 13 months and 6 years old, the formula for predicting neuropsychological development is:

[0057] h=(49.9123~52.6285)+(2343.7701~4663.8371)×TM7x+(-60.5126~3457.3805)×Weis sella+(3641.8351~4855.5426)×Devosia+(1378.1606~2869.502)×Bradyrhizobium+

[0058] (866.0322~3817.5774)×Atopobium+(1370.5024~4909.5865)×Glutamicibacter-

[0059] (11328.4011~6658.3515)×Cupriavidus+(1408.4641~2853.6566)×

[0060] Lachnospiraceae_FCS020_group+(2431.4707~4358.3283)×RB41;

[0061] Alternatively h = 51.0569 + 3311.0714 × TM7x + 857.1083 × Weissella + 4384.629 × Devosia + 2224.3299 × Bradyrhizobium + 1831.3744 × Atopobium + 2466.8918 × Glutamicibacter-9012.034 ×

[0062] Cupriavidus+2119.8855×Lachnospiraceae_FCS020_group+3757.0831×RB41;

[0063] Among them, TM7x is the relative abundance of TM7x, Weissella is the relative abundance of Weissella, Devosia is the relative abundance of Devosia, Bradyrhizobium is the relative abundance of Bradyrhizobium, Atopobium is the relative abundance of Atopobium, Glutamicibacter is the relative abundance of Glutamicibacter, Cupriavidus is the relative abundance of Pseudomonas aeruginosa, Lachnospiraceae_FCS020_group is the relative abundance of Lachnospiraceae FCS020 group;

[0064] And / or, the prediction model formula of intestinal flora information and skin includes one or more of the following formulas (i) to (ii):

[0065] (i) When children are between 0 days and 4 months old, the formula for predicting skin is:

[0066] 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;

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

[0068] Among them, Clostridium_sensu_stricto_1 is the relative abundance of the strict Clostridium genus, Brevundimonas is the relative abundance of the Monosperma genus, Subdoligranulum is the relative abundance of the rare Micrococcus genus, and Faecalibacterium is the relative abundance of the Faecalibacterium genus;

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

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

[0071] Alternatively, h = 0.148-0.2464×Bifidobacterium+150.5487×Bacillus;

[0072] Among them, Bifidobacterium is the relative abundance of Bifidobacterium, and Bacillus is the relative abundance of Bacillus;

[0073] And / or, the prediction model formula of intestinal flora information and stool characteristics includes one or more of the following formulas i) to iv):

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

[0075] h=(2.5624~2.6469)-(2.6623~0.8585)×Staphylococcus-(4.0757~3.3154)×Veillonella-(2.30 37~1.444)×Parabacteroides+(8.4342~535.3406)×Dialister-(3.8718~3.0043)×Haemophilus;

[0076] Alternatively h = 2.6152-1.1958×Staphylococcus-3.6283×Veillonella-1.8468×

[0077] Parabacteroides+152.3533×Dialister-3.5718×Haemophilus;

[0078] Among them, 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;

[0079] ii) For children aged 16 to 30 days, the formula for predicting stool characteristics is:

[0080] h=(2.3114~2.4241)+(2.4508~683.2421)×Lachnospira+(2.3546~12.7348)×Flavonifractor-(405.4702~62.5708)×Agathobacter-(13.1682~9.6822)×Phascolarctobacterium;

[0081] Alternatively h = 2.3783 + 182.608 × Lachnospira + 8.5137 × Flavonifractor - 122.2349 ×

[0082] Agathobacter-11.4688×Phascolarctobacterium;

[0083] Among them, Lachnospira is the relative abundance of Lachnospira, Flavonifractor is the relative abundance of Flavonoids, Agathobacter is the relative abundance of Eubacterium rectale, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium;

[0084] iii) For children aged 31 days to 4 months, the formula for predicting stool characteristics is:

[0085] h=(2.3441~2.441)+(-0.1699~0.0419)×Clostridium_sensu_stricto_1+(0.0728~0.2473)×Bacteroides+(1.7218~2.1934)×Parabacteroides+(1.2942~3.6235)×Akkermansia+

[0086] (-0.5946~2.7963)×Citrobacter+(-11.0145~21.6328)×Bilophila-(1.8488~1.354)×

[0087] Epulopiscium+(6.8497~11.2683)×Phascolarctobacterium+(2.3211~5.0496)×Collinsella-

[0088] (221.8181~121.729)×Sarcina;

[0089] Alternatively h = 2.3775-0.0542×Clostridium_sensu_stricto_1+0.1665×Bacteroides+1.9577×Parabacteroides+2.7415×Akkermansia+1.8706×Citrobacter+1.9948×Bilophila-1.6425×

[0090] Epulopiscium+8.7979×Phascolarctobacterium+3.2822×Collinsella-165.6212×Sarcina;

[0091] Among them, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium 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 Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, and Sarcina is the relative abundance of Epulopiscium;

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

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

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

[0095] Optionally, h = 2.9704 - 0.8727 × Escherichia.Shigella - 0.3608 × Clostridium_sensu_stricto_1 - 14.9315 × Staphylococcus + 0.4969 × Bacteroides - 203.9802 × Bacillus - 0.9976 ×

[0096] Erysipelatoclostridium - 10.9023 × Subdoligranulum + 24.0384 × Dialister - 93.5327 ×

[0097] Epulopiscium + 2.4099 × Ruminococcus._torques_group - 427.6705 × CAG.56 + 333.3722 × Sellimonas;

[0098] Among them, Escherichia.Shigella is the relative abundance of Escherichia coli-Shigella, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium 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 Erysipelothrix, 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, CAG.56 is the relative abundance of the common unit CAG.56, and Sellimonas is the relative abundance of Sellimonas;

[0099] And / or, the prediction model formula of intestinal flora information and crying condition includes one or more of the following formulas 1) to 3):

[0100] 1) When the child is 8 to 15 days old, the formula for predicting crying is:

[0101] h=(1.6702~1.8308)+(1.5851~2.4425)×Erysipelatoclostridium-(1.5395~1.1238)×Klebsiella-(20.1973~8.7767)×Citrobacter;

[0102] Alternatively h = 1.7244 + 1.8593 × Erysipelatoclostridium - 1.2836 × Klebsiella - 12.9963 × Citrobacter;

[0103] Among them, Erysipelatoclostridium is the relative abundance of Erysipelothrix, Klebsiella is the relative abundance of Klebsiella, and Citrobacter is the relative abundance of Citrobacter;

[0104] 2) When the child is between 16 and 30 days old, the formula for predicting crying is:

[0105] 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;

[0106] Alternatively h = 1.5331 + 20.0659 × Staphylococcus - 42.3019 × Rothia - 13.2372 ×

[0107] Phascolarctobacterium-6.9779×Ruminococcus;

[0108] Among them, Staphylococcus is the relative abundance of Staphylococcus, Rothia is the relative abundance of Roseburia, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, and Ruminococcus is the relative abundance of Ruminococcus;

[0109] 3) When children are between 31 days and 4 months old, the formula for predicting crying is:

[0110] h=(1.4678~1.5216)+(-1.2963~3.8134)×Acinetobacter-(147.9583~82.5599)×

[0111] Enhydrobacter+(214.5577~611.1134)×Aeromonas-(61.6441~45.7525)×Ligilactobacillus-

[0112] (1.5492~1.1626)×Veillonella+(0.3757~2.8055)×Megasphaera+(-26.169~226.5171)×Prev otella-(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)×

[0113] Eubacterium._hallii_group-(88.7991~73.9559)×Actinomyces+(160.468~224.39)×Atopobium;

[0114] Alternatively h = 1.4959 + 1.279 × Acinetobacter - 117.4994 × Enhydrobacter + 394.8747 ×

[0115] 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;

[0116] Among them, Acinetobacter is the relative abundance of Acinetobacter, Enhydrobacter is the relative abundance of Aquatic Bacillus, Aeromonas is the relative abundance of Aeromonas, Ligilactobacillus is the relative abundance of Lactobacillus, 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. =The relative abundance of Bacillus is shown in Table 1. 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, Actinomyces is the relative abundance of Actinomyces, and Atopobium is the relative abundance of Atopobium.

[0117] And / or, the prediction model formula of intestinal flora information and night sleep conditions includes one or more of the following formulas a) to d):

[0118] a) For children aged 0 to 15 days, the formula for nighttime sleep is:

[0119] h=(1.667~1.7575)+(2.0551~3.3078)×Parabacteroides;

[0120] Alternatively h = 1.7084 + 2.5764 × Parabacteroides;

[0121] Among them, Parabacteroides is the relative abundance of Parabacteroides;

[0122] b) For children aged 16 to 30 days, the formula for nighttime sleep is:

[0123] h=(1.9871~2.1135)-(36.0173~5.136)×Lactobacillus+(19.9734~35.2859)×

[0124] Phascolarctobacterium;

[0125] Alternatively, h = 2.0218-12.0345×Lactobacillus+26.0639×Phascolarctobacterium;

[0126] Among them, Lactobacillus is the relative abundance of Lactobacillus, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium;

[0127] c) For children aged 31 days to 4 months, the formula for nighttime sleep is:

[0128] h=(2.1063~2.153)+(485.8899~703.2182)×Stenotrophomonas-(1.1099~0.9931)×Enterococcus+(45.4132~142.3935)×Prevotella-(3.0807~2.7328)×Lactobacillus+

[0129] (6.9523~27.6025)×Bilophila+(-0.4976~4.8429)×Flavonifractor+(3.4943~6.1713)×Sutterella+(7.1024~12.505)×Ruminococcus._torques_group-(405.374~222.0575)×

[0130] unidentified_Chloroplast+(0.0185~4.2892)×Fusicatenibacter+(232.9549~397.3759)×Dorea-(3.843~2.5359)×Proteus-(126.278~76.0815)×Myroides;

[0131] Alternatively h = 2.1267 + 580.5244 × Stenotrophomonas - 1.0646 × Enterococcus + 76.9896 ×

[0132] Prevotella-2.9066×Lactobacillus+16.0708×Bilophila+0.7412×Flavonifractor+4.4946×

[0133] Sutterella+8.8728×Ruminococcus._torques_group-280.1981×unidentified_Chloroplast+1.3007×Fusicatenibacter+310.8906×Dorea-3.3466×Proteus-98.8985×Myroides;

[0134] Among them, 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, and Myroides is the relative abundance of Myroides;

[0135] d) For children aged 5 months to 6 years old, the formula for nighttime sleep is:

[0136] h=(1.8273~1.8898)+(5.8052~7.3144)×Staphylococcus-(5.3856~1.5202)×Enterobacter+(1.744~9.8407)×Prevotella_9+(-1.5188~0.274 8)×Erysipelatoclostridium+(-2.1975~30.4482)×Coprococcus-(66.6501~15.2271)×Fusobacterium+(-0.8691~4.0197)×Flavonifractor+

[0137] (5.4952~9.5591)×Sutterella+(3.2347~5.8771)×Lachnoclostridium+(53.2421~66.6003)×Actinomyces+(124.4522~194.2467)×Anaerostipes+(6.1294~71.2023)×

[0138] Eubacterium._fissicatena_group-(158.923~76.3152)×Negativicoccus+(112.5601~779.4042)×Allisonella;

[0139] Alternatively h = 1.8537 + 6.6401 × Staphylococcus - 2.9561 × Enterobacter + 4.1107 ×

[0140] Prevotella_9-0.5677×Erysipelatoclostridium+8.9717×Coprococcus-29.4941×

[0141] Fusobacterium+1.7762×Flavonifractor+7.6957×Sutterella+4.7329×Lachnoclostridium+61.5478×Actinomyces+16 4.25×Anaerostipes+37.7456×Eubacterium._fissicatena_group-121.676×Negativicoccus+403.4906×Allisonella;

[0142] Among them, 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 Erysipelothrix, 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 anaerobic Corynebacterium, Eubacterium._fissicatena_group is the relative abundance of the fissured Brevibacterium group, Negativicoccus is the relative abundance of the negative coccus, and Allisonella is the relative abundance of the Allisonella.

[0143] In a second aspect, a system for evaluating the growth and development status of children aged 0 to 6 years old is provided, which is applied to any method described in 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 described in the first aspect when executing the program.

[0144] In a third aspect, there is provided an application of the method described in the first aspect or the system described in the second aspect in the preparation of a product for evaluating the growth and development status of children aged 0 to 6 years old.

[0145] Beneficial Effects

[0146] Evaluating a child's developmental level through information such as neuropsychological development, skin, bowel movements, crying, and sleep at night is a monitoring of the child's developmental outcome indicators, that is, there are differences in the clinical manifestations of infant health caused by the child's intrinsic development such as the intestinal flora. The present invention predicts the child's short- and long-term neuropsychological development, skin, bowel movements, crying, and sleep at night indicators through the child's intestinal flora, provides targets for reference and improvement, and can promptly discover possible adverse developmental outcomes in the future, and promptly prevent and improve them. DETAILED DESCRIPTION

[0147] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0148] In addition, in order to better illustrate the present invention, numerous specific details are provided in the specific embodiments below. It should be understood by those skilled in the art that the present invention can also be implemented without certain specific details. In some embodiments, raw materials, elements, methods, means, etc. well known to those skilled in the art are not described in detail, so as to highlight the main purpose of the present invention.

[0149] Unless explicitly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising”, etc., will be understood to include the stated elements or components but not to exclude other elements or components.

[0150] The applicant launched a maternal and infant nutrition cohort study project in my country in 2014, which was a long-term follow-up project across multiple representative regions. The project established a multi-point, multi-center, prospective maternal and infant nutrition cohort across 7 provinces, cities, 8 food circles, and 15 points, with 3,766 mothers and infants enrolled. Samples were collected at the seventh day, fifteenth day, first month, second month, third month, fourth month, fifth month, sixth month, eighteenth month, twenty-fourth month, thirtieth month, thirty-sixth month, fourth year, fifth year, and sixth year, and 28,354 biological samples such as breast milk, feces, and urine were collected. A total of 737 fecal samples of children aged 0 to 6 years old who were breastfed were collected, and a 0-6-year-old intestinal microbiome database of breastfed children aged 0 to 6 years old was established.

[0151] The research method of intestinal flora mainly relies on the use of sequencing technology to sequence the intestinal flora marker genes (V3V4 region of 16SrRNA), use bioinformatics technology to process the sequencing results, and use relevant theories to summarize the data to achieve observation of intestinal flora.

[0152] The relative abundance of the present invention indicates the relative proportion of a certain microbial taxon in the entire microbial community. It is usually expressed as a percentage, and the calculation method is to divide the relative abundance of a certain taxon (its relative number 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.

[0153] The present invention first establishes the trend of intestinal flora changes in children aged 0-6 years old based on the collected data of children aged 0-6 years old, plans the range of intestinal flora changes in Chinese children aged 0-6 years old at different time points after birth, and establishes standardized intestinal flora development status evaluation indicators for children aged 0-6 years old. Further explore the relationship between intestinal flora and development indicators, screen out a group of marker flora, and evaluate the physical development status of children aged 0-6 years old by evaluating the relative abundance of each bacteria in the marker flora group, so as to achieve the purpose of using intestinal flora to predict the development status of children.

[0154] In a first aspect, the present invention provides a method for evaluating the growth and development status of children aged 0 to 6 years old, wherein the development status to be evaluated includes one or more of neuropsychological development, skin, defecation, crying, and night sleep; the method comprises the following steps:

[0155] Obtaining intestinal flora information of the target population to be predicted; the intestinal flora information includes relative abundance information of flora significantly associated with the corresponding developmental state;

[0156] Inputting the intestinal flora information into a pre-built prediction and evaluation model to obtain an evaluation result output by the prediction and evaluation model, the evaluation result including: a quantitative result of a corresponding developmental state, wherein the quantitative result corresponds to different developmental states;

[0157] Among them, the predictive evaluation model is obtained through multivariate regression calculation based on the corresponding intestinal flora information that is significantly correlated with the developmental status to be evaluated.

[0158] Furthermore, the prediction and evaluation model includes several prediction and evaluation sub-models differentiated according to age and developmental status to be evaluated; the prediction and evaluation sub-models are selected according to age and developmental status to be evaluated, and corresponding intestinal flora information significantly related to the corresponding age group and developmental status to be evaluated is input for prediction and evaluation; and / or,

[0159] The intestinal flora information is obtained by detecting stool samples of the target population to be predicted.

[0160] Furthermore, the method for constructing the prediction and evaluation model includes:

[0161] Obtain intestinal flora information of several samples from multiple regions, merge intestinal flora information and clinical information to establish an intestinal flora database for children aged 0 to 6 years old, intestinal flora information includes relative abundance information of flora at the phylum, family, and genus levels, and clinical information includes age and developmental status information; developmental status information includes one or more of neuropsychological development, skin, stool, crying, and night sleep; quantify the developmental status information, including: scoring of neuropsychological development questionnaires, scoring based on whether or not there is a skin disease, scoring based on stool characteristics, scoring based on crying, and scoring based on the number of awakenings during night sleep;

[0162] The data in the database were grouped by age, and then grouped again according to the relative abundance of the flora within the group. The average value of the relative abundance of each bacterium was used as the boundary to divide the data into a high-abundance group and a low-abundance group. The means of the quantitative developmental status information of the high-abundance group and the low-abundance group were calculated respectively. The means of the two groups were compared to obtain the difference multiple and perform significance analysis.

[0163] Select bacteria significantly correlated with clinical information as independent variables, and the scores or assignments of clinical information of children aged 0 to 6 years old as dependent variables. Set the random seeds for each age group, randomly divide the data into training set and validation set in proportion, perform linear regression calculation on the training set, obtain the linear prediction model of bacterial flora and clinical information of children aged 0 to 6 years old, and test it with the validation set.

[0164] According to the number of random seeds, multiple linear regression models were obtained. Based on the multiple models obtained, the range of model coefficients was summarized, and the average value was used as the calculation model coefficient to obtain a predictive evaluation model. According to the predicted clinical information of children aged 0 to 6 years old, the developmental status of children aged 0 to 6 years old was evaluated.

[0165] Among them, the questionnaire score of neuropsychological development refers to the score of communication ability obtained according to the test questionnaire Ages & Stages Questionnaires (ASQ) for children of different ages, which reflects the children's ability to understand language signals and their ability and willingness to express verbally. The way to obtain data: Professional personnel use ASQ questionnaires of different age groups to evaluate children of corresponding ages, and then use the corresponding software to calculate the total score according to the ASQ questionnaire scoring principle. The scoring results of all children are summarized according to different ASQ classifications. This time, the ASQ communication score is mainly used as the evaluation data, which is paired with the children's own flora data one by one. According to the relative abundance of the flora, the ASQ score is divided into two groups, and the difference multiple calculation and t test are performed to obtain the difference multiple and p value of the two groups. The flora with statistical significance is selected as the independent variable, and the ASQ communication score is used as the dependent variable for multivariate linear regression calculation. The sample data is brought into the regression model to obtain the valuation, which can be considered as a prediction of the ASQ score.

[0166] Among them, scoring based on whether or not a child has a skin disease refers to whether the child has skin diseases such as dermatitis and urticaria. The child is registered based on whether or not the child has a skin disease, and the score for skin diseases is set to 1, and the score for not having skin diseases is set to 0. This assessment focuses on the possibility of children developing skin diseases (dermatitis, urticaria). The intestinal flora is affected by external factors. When a child suffers from a skin disease, the child's intestinal flora will change accordingly. We establish the relationship between the intestinal flora and children's skin diseases, and use the intestinal flora to predict the possibility of children developing skin diseases, so as to prevent the occurrence of skin diseases in a timely manner. The valuation score calculated using the model can be understood as a risk assessment score. The closer the score is to 1, the higher the risk of illness. The method of obtaining data is to consult the mothers of children at different ages about the children's recent illnesses, mainly about whether the children suffer from skin diseases such as dermatitis and urticaria. The children are registered based on whether they are ill or not, and the illness is set as 1 and the non-illness is set as 0. The illness status and the child's intestinal flora information are merged, and the groups are grouped according to the abundance of the flora. A t-test is performed on the indicator values ​​of the two groups, and the differential bacteria with a p-value less than 0.05 are calculated. The differential bacteria are used as the independent variable and the illness or not is used as the dependent variable. Multiple regression calculations are performed, and the result is a numerical result calculated according to the formula. The valuation score can be understood as a risk assessment score. The closer the score is to 1, the higher the risk of illness.

[0167] Scoring of stool characteristics, night sleep conditions, and crying: The establishment process of these three detection indicators is similar. The indicators are divided according to different types and assigned scores. The scoring principles are as shown in the table. At different ages of children, children's stool characteristics, night sleep conditions, and crying conditions are investigated through questionnaires. The collected scales are summarized and the summarized data are merged with the microbial data. According to the relative abundance of each bacteria in the microbial community is higher / lower than the average relative abundance, they are divided into high and low groups. According to the high and low groups, the summary scores are subjected to difference multiples and t tests to obtain the difference multiples and p values. Bacteria with p values ​​less than 0.05 are selected as independent variables, and the indicator scores are used as dependent variables for multiple regression calculations. Sample information is put into the model for calculation to obtain a predicted score, which can be considered as a tendency. For example, if the predicted score of a is 1.7, it is considered that he is more inclined to the result of 2. Refer to the table below for the relationship between score tendencies.

[0168] The scoring principles are shown in Table 1:

[0169] Table 1. Scoring principles for stool characteristics, nighttime sleep, and crying

[0170]

[0171] The actual trait tendency relationship corresponding to the score estimated by the model is:

[0172] When the estimated score is 0≤x<1.5, the corresponding trait is scored as 1;

[0173] When the estimated score is 1.5≤x<2.5, the corresponding trait is scored as 2;

[0174] When the estimated score is 2.5≤x<3.5, the corresponding trait is scored 3;

[0175] When the estimated score is 3.5≤x<4.5, the corresponding trait is scored as 4;

[0176] When the estimated score is 4.5≤x, the corresponding trait is scored 5.

[0177] Furthermore, the construction of the intestinal flora database of children aged 0 to 6 years old includes: collecting feces of children aged 0 to 6 years old, sequencing and analyzing them through 16S amplicon sequencing technology to obtain sequencing data corresponding to the intestinal flora of children aged 0 to 6 years old, denoising and aggregating the sequencing data to obtain basic classification units OTUs, annotating the classification units with species to obtain the composition of the intestinal flora of children aged 0 to 6 years old, merging the intestinal flora information and clinical information according to the sample number, and establishing a intestinal flora database for children aged 0 to 6 years old.

[0178] Furthermore, noise reduction includes: reads splicing and filtering, and then OTUs clustering.

[0179] A possible implementation example is as follows:

[0180] (1) The collected samples were processed by performing double-end sequencing of the library based on the Illumina NovaSeq sequencing platform using 16S amplicon sequencing technology to obtain sequencing data corresponding to the intestinal flora of children aged 0 to 6 years. The offline data were denoised and aggregated on the qiime 2 platform to obtain the basic taxonomic units (OTUs). The taxonomic units were annotated with species based on the existing biological level annotators to obtain the composition of the intestinal flora of children aged 0 to 6 years. The composition of the flora was presented in the format of relative abundance.

[0181] (2) The data of all breast-fed samples (including the intestinal flora composition and clinical information table of children aged 0 to 6 years) were read in using R studio software, and the samples were merged according to their unique numbers. The clinical information and intestinal flora composition information were merged together to establish a database of exclusively breast-fed children aged 0 to 6 years. The samples were divided according to different time points, and eight categories were designed: 0 to 7 days (stage 1), 8 to 15 days (stage 2), 16 to 30 days (stage 3), 31 days to 4 months (stage 4), 5 months to 12 months (stage 5), 13 months to 24 months (stage 6), 25 months to 36 months (stage 7), and 37 months to 6 years (stage 8).

[0182] (2) Based on the database obtained in (1), according to the above time classification mode, each group was subjected to the following operations: the relative abundance of the microbiota in the group was further divided into groups higher than the average and lower than the average, and the height and weight information of the high abundance group and the low abundance group were compared to obtain the difference multiple; in addition, a t test was performed to obtain the p value. It was found that some microbiota were associated with clinical manifestations.

[0183] (3) The results calculated in (2) were further screened, and bacteria with a p-value less than 0.05 were selected, which were defined as having a significant correlation with the height and weight information of children aged 0 to 6 years. Grouping was performed according to the grouping method in (1), and a random seed was set. For each time group, data were randomly selected, and 80% of the samples in each group were used as the prediction set. The height and weight of children aged 0 to 6 years were linearly regressed using the bacterial flora to obtain a linear model of bacterial flora and clinical manifestations. The remaining 20% ​​of the samples were used as the test set, and the root mean square error and R of the model were calculated by using the ten-fold cross-validation method. 2 , mean absolute error. Multiple linear regression models are obtained according to the number of random seeds. Based on the obtained multiple models, the range of model coefficients is summarized, and the average value is used as the calculation model coefficient to calculate the obtained model, model evaluation results and value range.

[0184] Furthermore, when the developmental state to be evaluated is neuropsychological development, the bacterial flora significantly associated with neuropsychological development includes the following bacterial collections (1) to (3) that are related to age:

[0185] (1) Staphylococcus, Ligilactobacillus, Ruminococcus._torques_group; Optionally, the child is aged between 0 days and 4 months;

[0186] (2) Veillonella and Prevotella; optionally, the child is between 5 and 12 months old;

[0187] (3) TM7x (TM7x), Weissella, Devosia, Bradyrhizobium, Atopobium, Glutamicibacter, Cupriavidus, Lachnospiraceae_FCS020_group, RB41; Optionally, the child is aged between 13 months and 6 years;

[0188] Alternatively, when the developmental state to be evaluated is the skin, the bacterial flora significantly associated with the skin includes the following bacterial collections (i) to (ii) that are associated with age:

[0189] (i) Clostridium_sensu_stricto_1 (Clostridium sensu_stricto_1), Brevundimonas (Brevundimonas), Subdoligranulum (Subdoligranulum), Faecalibacterium (Faecalibacterium); children aged 0 days to 4 months;

[0190] (ii) Bifidobacterium, Bacillus;

[0191] Alternatively, when the developmental status to be evaluated is stool characteristics, the bacterial flora significantly associated with stool characteristics includes the following bacterial collections i) to iv) that are related to age:

[0192] i) Staphylococcus, Veillonella, Parabacteroides, Dialister, Haemophilus; Optionally, children aged 0 to 15 days;

[0193] ii) Lachnospira, Flavonifractor, Agathobacter, Phascolarctobacterium; Optionally, the child is aged between 16 and 30 days;

[0194] iii) Clostridium_sensu_stricto_1 (strict Clostridium 1), Bacteroides, Parabacteroides, Akkermansia, Citrobacter, Bilophila, Epulopiscium, Phascolarctobacterium, Collinsella, Sarcina; Optionally, the child is aged between 31 days and 4 months;

[0195] iv) Escherichia.Shigella, Clostridium_sensu_stricto_1, Staphylococcus, Bacteroides, Bacillus, Erysipelatoclostridium, Subdoligranulum, Dialister, Epulopiscium, Ruminococcus._torques_group, CAG.56, Sellimonas; Optionally, the child is aged between 5 months and 6 years;

[0196] Alternatively, when the developmental state to be evaluated is crying, the bacterial flora significantly associated with crying includes the following bacterial collections 1) to 3) that are related to age:

[0197] 1) Erysipelatoclostridium, Klebsiella, Citrobacter; Optionally, children aged 8 to 15 days;

[0198] 2) Staphylococcus, Rothia, Phascolarctobacterium, Ruminococcus; Optionally, children aged 16 to 30 days;

[0199] 3) Acinetobacter, Enhydrobacter, Aeromonas, Ligilactobacillus, Veillonella, Megasphaera, Prevotella, Fusobacterium, Lactobacillus, Flavonifractor, Lachnospiraceae_NK4A136_group, Fusicatenibacter, Ruminococcus, Eubacterium._hallii_group, Actinomyces, Atopobium; Optionally, the child is 31 days to 4 months old;

[0200] Alternatively, when the developmental state to be evaluated is the nighttime sleep condition, the bacterial flora significantly associated with the nighttime sleep condition includes the following bacterial collections a) to d) associated with age:

[0201] a) Parabacteroides (Parabacteroides);

[0202] b) Lactobacillus (Lactobacillus), Phascolarctobacterium (Phascolarctobacterium);

[0203] c) Stenotrophomonas, Enterococcus, Prevotella, Lactobacillus, Bilophila, Flavonifractor, Sutterella, Ruminococcus_torques_group, unidentified_Chloroplast, Fusicatenibacter, Dorea, Proteus, Myroides;

[0204] d) Staphylococcus, Enterobacter, Prevotella_9, Erysipelatoclostridium, Coprococcus, Fusobacterium, Flavonifractor, Sutterella, Lachnoclostridium, Actinomyces, Anaerostipes, Eubacterium._fissicatena_group, Negativicoccus, Allisonella.

[0205] Furthermore, clinical information included neuropsychological development, skin, bowel movements, crying conditions, or nighttime sleep;

[0206] The prediction model formula of intestinal flora information and neuropsychological development includes one or more of the following formulas (1) to (3):

[0207] (1) When children are between 0 days and 4 months old, the formula for predicting neuropsychological development is:

[0208] h=(51.0705~52.7283)+(-540.3316~54.9656)×Staphylococcus-(3599.8924~2076.5719)×Ligilactobacillus+(127.5668~3359.586)×Ruminococcus._torques_group;

[0209] Among them, Staphylococcus is the relative abundance of Staphylococcus, Ligilactobacillus is the relative abundance of Lactobacillus, and Ruminococcus._torques_group is the relative abundance of Ruminococcus._torques_group;

[0210] (2) When children are between 5 and 12 months old, the formula for predicting neuropsychological development is:

[0211] h=(55.2745~56.409)-(34.2045~26.1645)×Veillonella+(794.7139~2787.5344)×Prevotella;

[0212] Among them, Veillonella is the relative abundance of Veillonella, and Prevotella is the relative abundance of Prevotella;

[0213] (3) When children are between 13 months and 6 years old, the formula for predicting neuropsychological development is:

[0214] h=(49.9123~52.6285)+(2343.7701~4663.8371)×TM7x+(-60.5126~3457.3805)×Weis sella+(3641.8351~4855.5426)×Devosia+(1378.1606~2869.502)×Bradyrhizobium+

[0215] (866.0322~3817.5774)×Atopobium+(1370.5024~4909.5865)×Glutamicibacter-

[0216] (11328.4011~6658.3515)×Cupriavidus+(1408.4641~2853.6566)×

[0217] Lachnospiraceae_FCS020_group+(2431.4707~4358.3283)×RB41;

[0218] Among them, TM7x is the relative abundance of TM7x, Weissella is the relative abundance of Weissella, Devosia is the relative abundance of Devosia, Bradyrhizobium is the relative abundance of Bradyrhizobium, Atopobium is the relative abundance of Atopobium, Glutamicibacter is the relative abundance of Glutamicibacter, Cupriavidus is the relative abundance of Pseudomonas aeruginosa, Lachnospiraceae_FCS020_group is the relative abundance of Lachnospiraceae FCS020 group;

[0219] Optionally, the prediction model formula of intestinal flora information and neuropsychological development includes one or more of the following formulas (1) to (3):

[0220] (1) When children are between 0 days and 4 months old, the formula for predicting neuropsychological development is:

[0221] h=51.9239-249.4833×Staphylococcus-2448.8087×Ligilactobacillus+1394.1283×

[0222] Ruminococcus._torques_group;

[0223] (2) When children are between 5 and 12 months old, the formula for predicting neuropsychological development is:

[0224] h=55.8377-30.5745×Veillonella+1188.1085×Prevotella;

[0225] (3) When children are between 13 months and 6 years old, the formula for predicting neuropsychological development is:

[0226] h=51.0569+3311.0714×TM7x+857.1083×Weissella+4384.629×Devosia+2224.3299×Bradyrhizobium+1831.3744×Atopobium+2466.8918×Glutamicibacter-9012.034×

[0227] Cupriavidus+2119.8855×Lachnospiraceae_FCS020_group+3757.0831×RB41;

[0228] The root mean square error, R 2 , the mean absolute error is shown in Table 2.

[0229] Table 2. Root mean square error and R of the prediction model formula for intestinal flora information and neuropsychological development 2 , mean absolute error

[0230]

[0231] Furthermore, the prediction model formula of intestinal flora information and skin includes one or more of the following formulas (i) to (ii):

[0232] (i) When children are between 0 days and 4 months old, the formula for predicting skin is:

[0233] 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;

[0234] Among them, Clostridium_sensu_stricto_1 is the relative abundance of the strict Clostridium genus, Brevundimonas is the relative abundance of the Monosperma genus, Subdoligranulum is the relative abundance of the rare Micrococcus genus, and Faecalibacterium is the relative abundance of the Faecalibacterium genus;

[0235] (ii) For children aged 5 months to 6 years, the formula for predicting skin is:

[0236] h=(0.1305~0.1715)-(0.2813~0.2075)×Bifidobacterium+(135.426-160.0824)×Bacillus;

[0237] Among them, Bifidobacterium is the relative abundance of Bifidobacterium, and Bacillus is the relative abundance of Bacillus;

[0238] Optionally, the prediction model formula of intestinal flora information and skin includes one or more of the following formulas (i) to (ii):

[0239] (i) When children are between 0 days and 4 months old, the formula for predicting skin is:

[0240] h=0.0794+0.3781×Clostridium_sensu_stricto_1+354.1341×Brevundimonas+2.0446×Subdoligranulum-12.0461×Faecalibacterium;

[0241] (ii) For children aged 5 months to 6 years, the formula for predicting skin is:

[0242] h=0.148-0.2464×Bifidobacterium+150.5487×Bacillus;

[0243] The root mean square error, R 2, the mean absolute error is shown in Table 3.

[0244] Table 3. Root mean square error and R of the prediction model formula for intestinal flora information and skin 2 , mean absolute error

[0245]

[0246] Furthermore, the prediction model formula of intestinal flora information and stool characteristics includes one or more of the following formulas i) to iv):

[0247] i) For children aged 0 to 15 days, the formula for predicting stool characteristics is:

[0248] h=(2.5624~2.6469)-(2.6623~0.8585)×Staphylococcus-(4.0757~3.3154)×Veillonella-(2.30 37~1.444)×Parabacteroides+(8.4342~535.3406)×Dialister-(3.8718~3.0043)×Haemophilus;

[0249] Among them, 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;

[0250] ii) For children aged 16 to 30 days, the formula for predicting stool characteristics is:

[0251] h=(2.3114~2.4241)+(2.4508~683.2421)×Lachnospira+(2.3546~12.7348)×Flavonifractor-(405.4702~62.5708)×Agathobacter-(13.1682~9.6822)×Phascolarctobacterium;

[0252] Among them, Lachnospira is the relative abundance of Lachnospira, Flavonifractor is the relative abundance of Flavonoids, Agathobacter is the relative abundance of Eubacterium rectale, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium;

[0253] iii) For children aged 31 days to 4 months, the formula for predicting stool characteristics is:

[0254] h=(2.3441~2.441)+(-0.1699~0.0419)×Clostridium_sensu_stricto_1+(0.0728~0.2473)×Bacteroides+(1.7218~2.1934)×Parabacteroides+(1.2942~3.6235)×Akkermansia+

[0255] (-0.5946~2.7963)×Citrobacter+(-11.0145~21.6328)×Bilophila-(1.8488~1.354)×

[0256] Epulopiscium+(6.8497~11.2683)×Phascolarctobacterium+(2.3211~5.0496)×Collinsella-

[0257] (221.8181~121.729)×Sarcina;

[0258] Among them, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium 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 Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, and Sarcina is the relative abundance of Epulopiscium;

[0259] iv) For children aged 5 months to 6 years, the formula for predicting stool characteristics is:

[0260] h=(2.9053~3.0947)-(1.0973~0.7369)×Escherichia.Shigella-(0.4223~0.3035)×Clostridium_sensu_stricto_1-(15.7456~14.33 56)×Staphylococcus+(0.3984~0.5591)×Bacteroides-(399.5418~60.4927)×Bacillus-(1.4938~0.4026)×Erysipelatoclostridium-

[0261] (12.6503~8.9228)×Subdoligranulum+(22.3406~24.9229)×Dialister-(104.8873~77.8148)×Epulopiscium+(-0. 347~7.5903)×Ruminococcus._torques_group-(458.5554~407.3394)×CAG.56+(218.2145~397.8098)×Sellimonas;

[0262] Among them, Escherichia.Shigella is the relative abundance of Escherichia coli-Shigella, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium 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 Erysipelothrix, 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 torso, CAG.56 is the relative abundance of the general unit CAG.56, and Sellimonas is the relative abundance of Sellimonas.

[0263] Optionally, the prediction model formula of intestinal flora information and stool characteristics includes one or more of the following formulas i) to iv):

[0264] i) For children aged 0 to 15 days, the formula for predicting stool characteristics is:

[0265] h=2.6152-1.1958×Staphylococcus-3.6283×Veillonella-1.8468×Parabacteroides+152.3533×Dialister-3.5718×Haemophilus;

[0266] ii) For children aged 16 to 30 days, the formula for predicting stool characteristics is:

[0267] h=2.3783+182.608×Lachnospira+8.5137×Flavonifractor-122.2349×Agathobacter-11.4688×Phascolarctobacterium;

[0268] iii) For children aged 31 days to 4 months, the formula for predicting stool characteristics is:

[0269] h=2.3775-0.0542×Clostridium_sensu_stricto_1+0.1665×Bacteroides+1.9577×

[0270] Parabacteroides+2.7415×Akkermansia+1.8706×Citrobacter+1.9948×Bilophila-1.6425×

[0271] Epulopiscium+8.7979×Phascolarctobacterium+3.2822×Collinsella-165.6212×Sarcina;

[0272] iv) When children are between 5 months and 6 years old, the formula for predicting stool characteristics is:

[0273] h=2.9704-0.8727×Escherichia.Shigella-0.3608×Clostridium_sensu_stricto_1-14.9315×Staphylococcus+0.4969×Bacteroides-20 3.9802×Bacillus-0.9976×Erysipelatoclostridium-10.9023×Subdoligranulum+24.0384×Dialister-93.5327×Epulopiscium+2.4099×

[0274] Ruminococcus._torques_group-427.6705×CAG.56+333.3722×Sellimonas.

[0275] The root mean square error, R 2 , the mean absolute error is shown in Table 4.

[0276] Table 4. Root mean square error and R of the prediction model formula for intestinal flora information and stool characteristics 2 , mean absolute error

[0277]

[0278] Furthermore, the prediction model formula of intestinal flora information and crying condition includes one or more of the following formulas 1) to 3):

[0279] 1) When the child is 8 to 15 days old, the formula for predicting crying is:

[0280] h=(1.6702~1.8308)+(1.5851~2.4425)×Erysipelatoclostridium-(1.5395~1.1238)×Klebsiella-(20.1973~8.7767)×Citrobacter;

[0281] Among them, Erysipelatoclostridium is the relative abundance of Erysipelothrix, Klebsiella is the relative abundance of Klebsiella, and Citrobacter is the relative abundance of Citrobacter;

[0282] 2) When the child is between 16 and 30 days old, the formula for predicting crying is:

[0283] 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;

[0284] Among them, Staphylococcus is the relative abundance of Staphylococcus, Rothia is the relative abundance of Roseburia, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, and Ruminococcus is the relative abundance of Ruminococcus;

[0285] 3) When children are between 31 days and 4 months old, the formula for predicting crying is:

[0286] h=(1.4678~1.5216)+(-1.2963~3.8134)×Acinetobacter-(147.9583~82.5599)×

[0287] Enhydrobacter+(214.5577~611.1134)×Aeromonas-(61.6441~45.7525)×Ligilactobacillus-

[0288] (1.5492~1.1626)×Veillonella+(0.3757~2.8055)×Megasphaera+(-26.169~226.5171)×Prev otella-(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)×

[0289] Eubacterium._hallii_group-(88.7991~73.9559)×Actinomyces+(160.468~224.39)×Atopobium;

[0290] Among them, Acinetobacter is the relative abundance of Acinetobacter, Enhydrobacter is the relative abundance of Aquatic Bacillus, Aeromonas is the relative abundance of Aeromonas, Ligilactobacillus is the relative abundance of Lactobacillus, 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. =The relative abundance of Bacillus is shown in Table 1. 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, Actinomyces is the relative abundance of Actinomyces, and Atopobium is the relative abundance of Atopobium.

[0291] Preferably, the prediction model formula of intestinal flora information and crying condition includes one or more of the following formulas 1) to 3):

[0292] 1) When the child is 8 to 15 days old, the formula for predicting crying is:

[0293] h=1.7244+1.8593×Erysipelatoclostridium-1.2836×Klebsiella-12.9963×Citrobacter;

[0294] 2) When the child is between 16 and 30 days old, the formula for predicting crying is:

[0295] h=1.5331+20.0659×Staphylococcus-42.3019×Rothia-13.2372×

[0296] Phascolarctobacterium-6.9779×Ruminococcus;

[0297] 3) When children are between 31 days and 4 months old, the formula for predicting crying is:

[0298] h=1.4959+1.279×Acinetobacter-117.4994×Enhydrobacter+394.8747×Aeromonas-54.0312×Ligilactobacillus-1.3707×Veillonell a+1.3511×Megasphaera+62.6096×Prevotella-30.0045×Fusobacterium-0.7988×Lactobacillus+0.6225×Flavonifractor-167.8314×

[0299] Lachnospiraceae_NK4A136_group+3.1171×Fusicatenibacter-109.4375×Ruminococcus-89.6414×Eubacterium._hallii_group-82.0443×Actinomyces+199.7983×Atopobium;

[0300] The root mean square error, R 2 , the mean absolute error is shown in Table 5.

[0301] Table 5. Root mean square error and R of the prediction model formula for intestinal flora information and crying status 2 , mean absolute error

[0302]

[0303] Furthermore, the prediction model formula of the intestinal flora information and the night sleep condition includes one or more of the following formulas a) to d):

[0304] a) For children aged 0 to 15 days, the formula for nighttime sleep is:

[0305] h=(1.667~1.7575)+(2.0551~3.3078)×Parabacteroides;

[0306] Among them, Parabacteroides is the relative abundance of Parabacteroides;

[0307] b) For children aged 16 to 30 days, the formula for nighttime sleep is:

[0308] h=(1.9871~2.1135)-(36.0173~5.136)×Lactobacillus+(19.9734~35.2859)×

[0309] Phascolarctobacterium;

[0310] Among them, Lactobacillus is the relative abundance of Lactobacillus, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium;

[0311] c) For children aged 31 days to 4 months, the formula for nighttime sleep is:

[0312] h=(2.1063~2.153)+(485.8899~703.2182)×Stenotrophomonas-(1.1099~0.9931)×Enterococcus+(45.4132~142.3935)×Prevotella-(3.0807~2.7328)×Lactobacillus+

[0313] (6.9523~27.6025)×Bilophila+(-0.4976~4.8429)×Flavonifractor+(3.4943~6.1713)×Sutterella+(7.1024~12.505)×Ruminococcus._torques_group-(405.374~222.0575)×

[0314] unidentified_Chloroplast+(0.0185~4.2892)×Fusicatenibacter+(232.9549~397.3759)×Dorea-(3.843~2.5359)×Proteus-(126.278~76.0815)×Myroides;

[0315] Among them, 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, and Myroides is the relative abundance of Myroides;

[0316] d) For children aged 5 months to 6 years old, the formula for nighttime sleep is:

[0317] h=(1.8273~1.8898)+(5.8052~7.3144)×Staphylococcus-(5.3856~1.5202)×Enterobacter+(1.744~9.8407)×Prevotella_9+(-1.5188~0.274 8)×Erysipelatoclostridium+(-2.1975~30.4482)×Coprococcus-(66.6501~15.2271)×Fusobacterium+(-0.8691~4.0197)×Flavonifractor+

[0318] (5.4952~9.5591)×Sutterella+(3.2347~5.8771)×Lachnoclostridium+(53.2421~66.6003)×Actinomyces+(124.4522~194.2467)×Anaerostipes+(6.1294~71.2023)×

[0319] Eubacterium._fissicatena_group-(158.923~76.3152)×Negativicoccus+(112.5601~779.4042)×Allisonella;

[0320] Among them, 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 Erysipelothrix, 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 anaerobic Corynebacterium, Eubacterium._fissicatena_group is the relative abundance of the fissured Brevibacterium group, Negativicoccus is the relative abundance of the negative coccus, and Allisonella is the relative abundance of the Allisonella.

[0321] Preferably, the prediction model formula of intestinal flora information and nighttime sleep conditions includes one or more of the following formulas a) to d):

[0322] a) For children aged 0 to 15 days, the formula for nighttime sleep is:

[0323] h=1.7084+2.5764×Parabacteroides;

[0324] b) For children aged 16 to 30 days, the formula for nighttime sleep is:

[0325] h=2.0218-12.0345×Lactobacillus+26.0639×Phascolarctobacterium;

[0326] c) For children aged 31 days to 4 months, the formula for nighttime sleep is:

[0327] 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×

[0328] Ruminococcus._torques_group-280.1981×unidentified_Chloroplast+1.3007×

[0329] Fusicatenibacter+310.8906×Dorea-3.3466×Proteus-98.8985×Myroides;

[0330] d) For children aged 5 months to 6 years old, the formula for nighttime sleep is:

[0331] h=1.8537+6.6401×Staphylococcus-2.9561×Enterobacter+4.1107×Prevotella_9-0.5677×Erysipelatoclostridium+8.9717×Coprococcus-29.4941×Fusobacterium+1.7762×

[0332] Flavonifractor+7.6957×Sutterella+4.7329×Lachnoclostridium+61.5478×Actinomyces+164.25×Anaerostipes+37.7456×Eubacterium._fissicatena_group-121.676×Negativicoccus+403.4906×Allisonella;

[0333] The root mean square error, R 2 , the mean absolute error is shown in Table 6.

[0334] Table 6. Root mean square error and R of the prediction model formula for intestinal flora information and night sleep status 2 , mean absolute error

[0335]

[0336]

[0337] The linear model established by using the training set and the validation set is shown in terms of root mean square error, R 2 , mean absolute error, where the root mean square error is the square root of the average error between the model prediction value and the actual value. The smaller the value, the better the model. 2Indicates the explanatory power of the independent variable on the dependent variable. The closer the value is to 1, the stronger the explanatory power of the model; the mean absolute error is the average absolute error between the model's predicted value and the actual value. The smaller the value, the better the model.

[0338] The above results show that the model formula obtained by the present invention has good prediction performance.

[0339] The specific test examples are as follows:

[0340] Test Case 1: Neuropsychological Prediction

[0341] Three samples aged 31 days to 4 months were randomly selected, and the relative abundance of bacterial genera related to neuropsychology in this age group was substituted into the corresponding formula:

[0342] h=51.9239-249.4833×Staphylococcus-2448.8087×Ligilactobacillus+1394.1283×

[0343] Ruminococcus._torques_group;

[0344] The model prediction value was calculated and evaluated according to the prediction value specification. The results are shown in Table 7. It was found that the model evaluation status was close to the actual status of the child, which proved that the model fit was good and the microbiota could be used to predict the ASQ3 questionnaire score.

[0345] Table 7. Comparison of neuropsychological questionnaire scores and model prediction results

[0346] index 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 value 51.5863 44.2838 45.2965 Difference (questionnaire score - model prediction value) -1.5863 0.7162 -0.2965 .

[0347] Test Example 2: Crying State Prediction

[0348] Three samples from 16 to 30 days old were randomly selected, and the relative abundance of specific bacterial genera related to crying in this age group was substituted into the corresponding formula:

[0349] h=1.5331+20.0659×Staphylococcus-42.3019×Rothia-13.2372×

[0350] Phascolarctobacterium-6.9779×Ruminococcus;

[0351] The model prediction value was calculated and evaluated according to the prediction value specification. The results are shown in Table 8. It was found that the model evaluation status was the same as the child's actual status, which proved that the model fit was good and the microbiota could be used to evaluate the crying status.

[0352] Table 8. Comparison of actual crying status and predicted results

[0353] index Sample 1 Sample 2 Sample 3 Actual score of crying state 1 2 2 Staphylococcus 0 0 0.00270636 Rothia 0 0 0 Phascolarctobacterium 0.00135318 0 0 Ruminococcus 0.073071719 0 0 Model prediction value 1.005300538 1.5331 1.587405549 Judgment result value (the tendency result value obtained based on the predicted value) 1 2 2 .

[0354] Test Example 3: Sleep State Prediction

[0355] Three samples aged 31 days to 4 months were randomly selected, and the relative abundance of bacterial genera related to the sleep state of this age group was substituted into the corresponding formula:

[0356] 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×

[0357] Fusicatenibacter+310.8906×Dorea-3.3466×Proteus-98.8985×Myroides;

[0358] The model prediction value was calculated and evaluated according to the prediction value specification. The results are shown in Table 9. It was found that the model evaluation status was the same as the child's actual status, which proved that the model fit was good and the microbiota could be used to evaluate the sleep status.

[0359] Table 9. Comparison of actual sleep status and predicted results

[0360]

[0361]

[0362] Test Example 4: Stool Characteristics Prediction

[0363] Three samples from 8 to 15 days old were randomly selected, and the relative abundance of specific bacterial genera related to the stool characteristics of this age group was substituted into the corresponding formula:

[0364] h=2.6152-1.1958×Staphylococcus-3.6283×Veillonella-1.8468×Parabacteroides+152.3533×Dialister-3.5718×Haemophilus;

[0365] The model prediction value was calculated and evaluated according to the prediction value specification. The results are shown in Table 10. It was found that the model evaluation status was the same as the child's actual status, which proved that the model fit was good and the microbiota could be used to evaluate the sleep status.

[0366] Table 10. Comparison of actual status and predicted results of stool characteristics

[0367] index Sample 1 Sample 2 Sample 3 Actual score of stool consistency 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 value 1.89777 2.60553 1.87571 Judgment result value (the tendency result value obtained based on the predicted value) 2 3 2 .

[0368] Test case 5: Skin prediction

[0369] Three samples aged 31 days to 4 months were randomly selected, and the relative abundance of skin-related bacteria in this age group was substituted into the corresponding formula:

[0370] 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;

[0371] The model prediction value was calculated and evaluated according to the prediction value specification. The results are shown in Table 11. It was found that the model evaluation status was the same as the child's actual status, which proved that the model fit was good and the evaluation of skin problems using the microbiome could be realized.

[0372] Table 11. Comparison of actual skin condition and predicted results

[0373] index 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 value 0.23579121 0.72163397 0.75818809 Judgment result value (the tendency result value obtained based on the predicted value) 0 1 1 .

[0374] The above results show that the prediction and evaluation formula of the present invention has a good model fitting effect, can achieve accurate prediction of neuropsychological development, skin, bowel movements, crying, sleep at night, etc., and has good evaluation value.

[0375] It has been verified that the fitting effects of other model formulas are also good.

[0376] In a second aspect, a system for evaluating the growth and development status of children aged 0 to 6 years old is provided, which is applied to any method described in 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 described in the first aspect when executing the program.

[0377] In a third aspect, there is provided an application of the method described in the first aspect or the system described in the second aspect in the preparation of a product for evaluating the growth and development status of children aged 0 to 6 years old.

[0378] The beneficial effects of the present invention include:

[0379] 1. The data used in the embodiments of the present invention are all from children aged 0 to 6 years old in China, and all of them are breastfed. The clinical cohort covers multiple regions in China, with a long tracking time and rich data content, which is more suitable as an indicator measurement for children aged 0 to 6 years old in China.

[0380] 2. The current evaluation of infant health is mainly based on developmental indicators such as neuropsychological development, skin, bowel movements, crying, and nighttime sleep, as well as neuropsychological development indicators such as language, movement, and problem-solving ability, and health indicators such as whether the infant is ill and the type of disease, but it is difficult to evaluate the health level of the infant's internal development. The present invention adds a perspective for evaluating the health of the internal development status of children aged 0 to 6 years old by establishing a change curve and reference range of the intestinal flora of children aged 0 to 6 years old.

[0381] 3. Evaluating the child's development level through information such as neuropsychological development, skin, bowel movements, crying, and sleep at night is a monitoring of the child's developmental outcome indicators. That is, there are differences in the clinical manifestations of infant health caused by the child's internal development such as the intestinal flora. The intestinal flora of the child is used to predict the child's short- and long-term neuropsychological development, skin, bowel movements, crying, and sleep at night, providing targets for reference and improvement, which can discover possible adverse developmental outcomes in the future and prevent and improve them in time.

[0382] 4. The intestinal flora is in a state of constant dynamic change and stability. External intervention has an impact on the composition of the flora. The intestinal flora of children aged 0 to 6 years old is more susceptible to external influences. It is difficult to explain the final outcome of the child's development caused by the impact of different factors on the intestinal flora of children. According to the flora reference standard provided by the present invention, the adverse development of the intestinal flora can be discovered in time to change the adverse outcome.

[0383] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the growth and development status of children aged 0 to 6 years old based on intestinal flora, characterized in that: The developmental status to be evaluated includes one or more of neuropsychological development, skin, defecation, crying, and nighttime sleep; the method includes the following steps: Obtaining intestinal flora information of the target population to be predicted; the intestinal flora information includes relative abundance information of flora significantly associated with the corresponding developmental state; Inputting the intestinal flora information into a pre-built prediction and evaluation model to obtain an evaluation result output by the prediction and evaluation model, the evaluation result including: a quantitative result of a corresponding developmental state, wherein the quantitative result corresponds to different developmental states; Among them, the predictive evaluation model is obtained through multivariate regression calculation based on the corresponding intestinal flora information that is significantly correlated with the developmental status to be evaluated.

2. The method according to claim 1, characterized in that The prediction and evaluation model includes several prediction and evaluation sub-models distinguished according to age and developmental status to be evaluated; the prediction and evaluation sub-models are selected according to age and developmental status to be evaluated, and the corresponding intestinal flora information significantly related to the corresponding age group and developmental status to be evaluated is input for prediction and evaluation; and / or, The intestinal flora information is obtained by detecting stool samples of the target population to be predicted.

3. The method according to claim 1, characterized in that The methods for constructing the prediction and evaluation model include: Obtain intestinal flora information of several samples from multiple regions, merge intestinal flora information and clinical information to establish an intestinal flora database for children aged 0 to 6 years old, intestinal flora information includes relative abundance information of flora at the phylum, family, and genus levels, and clinical information includes age and developmental status information; developmental status information includes one or more of neuropsychological development, skin, stool, crying, and night sleep; quantify the developmental status information, including: scoring of neuropsychological development questionnaires, scoring based on whether or not there is a skin disease, scoring based on stool characteristics, scoring based on crying, and scoring based on the number of awakenings during night sleep; The data in the database were grouped by age, and then grouped again according to the relative abundance of the flora within the group. The average value of the relative abundance of each bacterium was used as the boundary to divide the data into a high-abundance group and a low-abundance group. The means of the quantitative developmental status information of the high-abundance group and the low-abundance group were calculated respectively. The means of the two groups were compared to obtain the difference multiple and perform significance analysis. Bacteria significantly correlated with clinical information were selected as independent variables, and the scores or assignments of clinical information of children aged 0 to 6 years old were selected as dependent variables. Random seeds were set for each age group, and the data were randomly divided into training sets and validation sets in proportion. The training sets were subjected to multivariate linear regression calculations to obtain a linear prediction model of bacterial flora and clinical information of children aged 0 to 6 years old, which was tested on the validation set. According to the number of random seeds, multiple linear regression models were obtained. Based on the multiple models obtained, the range of model coefficients was summarized, and the average value was used as the calculation model coefficient to obtain a predictive evaluation model. According to the predicted clinical information of children aged 0 to 6 years old, the developmental status of children aged 0 to 6 years old was evaluated.

4. The method according to claim 3, characterized in that: The construction of the intestinal flora database of children aged 0 to 6 years old includes: collecting feces of children aged 0 to 6 years old, sequencing and analyzing them through 16S amplicon sequencing technology to obtain sequencing data corresponding to the intestinal flora of children aged 0 to 6 years old, denoising and aggregating the sequencing data to obtain the basic classification units OTUs, annotating the classification units to species, and obtaining the composition of the intestinal flora of children aged 0 to 6 years old. The intestinal flora information and clinical information are merged according to the sample number to establish the intestinal flora database of children aged 0 to 6 years old.

5. The method according to claim 4, characterized in that Noise reduction includes: Reads were spliced ​​and filtered, and then OTUs were clustered.

6. The method according to any one of claims 1 to 5, characterized in that: When the developmental status to be evaluated is neuropsychological development, the bacterial flora significantly associated with neuropsychological development includes the following bacterial collections (1) to (3) that are related to age: (1) Staphylococcus, Ligilactobacillus, Ruminococcus._torques_group; (2) Veillonella, Prevotella; (3)TM7x, Weissella, Devosia, Bradyrhizobium, Atopobium, Glutamicibacter, Cupriavidus, Lachnospiraceae_FCS020_group, RB41; Alternatively, when the developmental state to be evaluated is the skin, the bacterial flora significantly associated with the skin includes the following bacterial collections (i) to (ii) that are associated with age: (i) Clostridium_sensu_stricto_1, Brevundimonas, Subdoligranulum, Faecalibacterium; (ii) Bifidobacterium, Bacillus; Alternatively, when the developmental status to be evaluated is stool characteristics, the bacterial flora significantly associated with stool characteristics includes the following bacterial collections i) to iv) that are related to age: 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 developmental state to be evaluated is crying, the bacterial flora significantly associated with crying includes the following bacterial collections 1) to 3) that are related to age: 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; Alternatively, when the developmental state to be evaluated is the nighttime sleep condition, the bacterial flora significantly associated with the nighttime sleep condition includes the following bacterial collections a) to d) associated with age: 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.

7. The method according to claim 2, characterized in that The age grouping methods include: 0-7 days, 8-15 days, 16-30 days, 31 days to 4 months, 5 months to 12 months, 13 months to 24 months, 25 months to 36 months, and 37 months to 6 years.

8. The method according to claim 7, characterized in that Clinical information included neuropsychological development, skin, bowel movements, crying, or nighttime sleep; The prediction model formula of intestinal flora information and neuropsychological development includes one or more of the following formulas (1) to (3): (1) When children are between 0 days and 4 months old, the formula for predicting neuropsychological development is: h=(51.0705~52.7283)+(-540.3316~54.9656)×Staphylococcus-(3599.8924~2076.5719)×Ligilactobacillus+(127.5668~3359.586)×Ruminococcus._torques_group; Among them, Staphylococcus is the relative abundance of Staphylococcus, Ligilactobacillus is the relative abundance of Lactobacillus, and Ruminococcus._torques_group is the relative abundance of Ruminococcus._torques_group; (2) When children are between 5 and 12 months old, the formula for predicting neuropsychological development is: h=(55.2745~56.409)-(34.2045~26.1645)×Veillonella+(794.7139~2787.5344)×Prevotella; Among them, Veillonella is the relative abundance of Veillonella, and Prevotella is the relative abundance of Prevotella; (3) When children are between 13 months and 6 years old, the formula for predicting neuropsychological development is: h=(49.9123~52.6285)+(2343.7701~4663.8371)×TM7x+(-60.5126~3457.38 05)×Weissella+(3641.8351~4855.5426)×Devosia+(1378.1606~2869.502)× Bradyrhizobium+(866.0322~3817.5774)×Atopobium+(1370.5024~4909.5865)× Glutamicibacter-(11328.4011~6658.3515)×Cupriavidus+(1408.4641~2853.6566)×Lachnospiraceae_FCS020_group+(2431.4707~4358.3283)×RB41; Among them, TM7x is the relative abundance of TM7x, Weissella is the relative abundance of Weissella, Devosia is the relative abundance of Devosia, Bradyrhizobium is the relative abundance of Bradyrhizobium, Atopobium is the relative abundance of Atopobium, Glutamicibacter is the relative abundance of Glutamicibacter, Cupriavidus is the relative abundance of Pseudomonas aeruginosa, Lachnospiraceae_FCS020_group is the relative abundance of Lachnospiraceae FCS020 group, RB41 is the relative abundance of the general unit RB41; And / or, the prediction model formula of intestinal flora information and skin includes one or more of the following formulas (i) to (ii): (i) When children are between 0 days and 4 months old, the formula for predicting skin is: 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; Among them, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium stricto, Brevundimonas is the relative abundance of the genus Brevundimonas, Subdoligranulum is the relative abundance of the genus Subdoligranulum, and Faecalibacterium is the relative abundance of the genus Faecalibacterium; (ii) For children aged 5 months to 6 years, the formula for predicting skin is: h=(0.1305~0.1715)-(0.2813~0.2075)×Bifidobacterium+(135.426-160.0824)×Bacillus; Among them, Bifidobacterium is the relative abundance of Bifidobacterium, and Bacillus is the relative abundance of Bacillus; And / or, the prediction model formula of intestinal flora information and stool characteristics includes one or more of the following formulas i) to iv): i) For children aged 0 to 15 days, the formula for predicting stool characteristics is: h=(2.5624~2.6469)-(2.6623~0.8585)×Staphylococcus-(4.0757~3.3154)×Veillonell a-(2.3037~1.444)×Parabacteroides+(8.4342~535.3406)×Dialister-(3.8718~3.0043) ×Haemophilus; Among them, 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) For children aged 16 to 30 days, the formula for predicting stool characteristics is: h=(2.3114~2.4241)+(2.4508~683.2421)×Lachnospira+(2.3546~12.7348)×Flavonifractor-(405.4702~62.5708)×Agathobacter-(13.1682~9.6822)× Phascolarctobacterium; Among them, Lachnospira is the relative abundance of Lachnospira, Flavonifractor is the relative abundance of Flavonoids, Agathobacter is the relative abundance of Eubacterium rectale, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium; iii) For children aged 31 days to 4 months, the formula for predicting stool characteristics is: h=(2.3441~2.441)+(-0.1699~0.0419)×Clostridium_sensu_stricto_1+(0.0728~0.2473)×Bact eroides+(1.7218~2.1934)×Parabacteroides+(1.2942~3.6235)×Akkermansia+(-0.5946~2.7963 )×Citrobacter+(-11.0145~21.6328)×Bilophila-(1.8488~1.354)×Epulopiscium+(6.8497~11.2683)×Phascolarctobacterium+(2.3211~5.0496)×Collinsella-(221.8181~121.729)×Sarcina; Among them, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium 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 Phascolarctobacterium, Collinsella is the relative abundance of Collinsella, and Sarcina is the relative abundance of Epulopiscium; iv) When children are between 5 months and 6 years old, the formula for predicting stool characteristics is: h=(2.9053~3.0947)-(1.0973~0.7369)×Escherichia.Shigella-(0.4223~0.3035)×Clostridium_sensu_stricto_1-(15.74 56~14.3356)×Staphylococcus+(0.3984~0.5591)×Bacteroides-(399.5418~60.4927)×Bacillus-(1.4938~0.4026)×Erysipe latoclostridium-(12.6503~8.9228)×Subdoligranulum+(22.3406~24.9229)×Dialister-(104.8873~77.8148)×Epulopisc ium+(-0.347~7.5903)×Ruminococcus._torques_group-(458.5554~407.3394)×CAG.56+(218.2145~397.8098)×Sellimonas; Among them, Escherichia.Shigella is the relative abundance of Escherichia coli-Shigella, Clostridium_sensu_stricto_1 is the relative abundance of Clostridium 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 Erysipelothrix, 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, CAG.56 is the relative abundance of the common unit CAG.56, and Sellimonas is the relative abundance of Sellimonas; And / or, the prediction model formula of intestinal flora information and crying condition includes one or more of the following formulas 1) to 3): 1) When the child is 8 to 15 days old, the formula for predicting crying is: h=(1.6702~1.8308)+(1.5851~2.4425)×Erysipelatoclostridium-(1.5395~1.1238)×Klebsiella-(20.1973~8.7767)×Citrobacter; Among them, Erysipelatoclostridium is the relative abundance of Erysipelothrix, Klebsiella is the relative abundance of Klebsiella, and Citrobacter is the relative abundance of Citrobacter; 2) When the child is between 16 and 30 days old, the formula for predicting crying 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; Among them, Staphylococcus is the relative abundance of Staphylococcus, Rothia is the relative abundance of Roseburia, Phascolarctobacterium is the relative abundance of Phascolarctobacterium, and Ruminococcus is the relative abundance of Ruminococcus; 3) When children are between 31 days and 4 months old, the formula for predicting crying 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-(88.7991~73.9559)×Actinomyces+(160.468~224.39)×Atopobium; Among them, Acinetobacter is the relative abundance of Acinetobacter, Enhydrobacter is the relative abundance of Aquatic Bacillus, Aeromonas is the relative abundance of Aeromonas, Ligilactobacillus is the relative abundance of Lactobacillus, 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 Flavonoids, 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, Actinomyces is the relative abundance of Actinomyces, and Atopobium is the relative abundance of Atopobium; And / or, the prediction model formula of intestinal flora information and night sleep conditions includes one or more of the following formulas a) to d): a) For children aged 0 to 15 days, the formula for nighttime sleep is: h=(1.667~1.7575)+(2.0551~3.3078)×Parabacteroides; Among them, Parabacteroides is the relative abundance of Parabacteroides; b) For children aged 16 to 30 days, the formula for nighttime sleep is: h=(1.9871~2.1135)-(36.0173~5.136)×Lactobacillus+(19.9734~35.2859)×Phascolarctobacterium; Among them, Lactobacillus is the relative abundance of Lactobacillus, and Phascolarctobacterium is the relative abundance of Phascolarctobacterium; c) For children aged 31 days to 4 months, the formula for nighttime sleep is: h=(2.1063~2.153)+(485.8899~703.2182)×Stenotrophomonas-(1.1099~0.9931)×Enterococcus+(45.4132~142.3935)×Prev otella-(3.0807~2.7328)×Lactobacillus+(6.9523~27.6025)×Bilophila+(-0.4976~4.8429)×Flavonifractor+(3.4943~6.1 713)×Sutterella+(7.1024~12.505)×Ruminococcus._torques_group-(405.374~222.0575)×unidentified_Chloroplast+(0 .0185~4.2892)×Fusicatenibacter+(232.9549~397.3759)×Dorea-(3.843~2.5359)×Proteus-(126.278~76.0815)×Myroides; Among them, 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 the genus Myroides; d) For children aged 5 months to 6 years old, the formula for nighttime sleep is: h=(1.8273~1.8898)+(5.8052~7.3144)×Staphylococcus-(5.3856~1.5202)× Enterobacter+(1.744~9.8407)×Prevotella_9+(-1.5188~0.2748)×Erysipelatoclostridium+(-2.1975~30.4482)×Coprococcus-(66.6501~15.2271)×Fusobacterium+(-0.86 91~4.0197)×Flavonifractor+(5.4952~9.5591)×Sutterella+(3.2347~5.8771)×Lachnoclostridium+(53.2421~66.6003)×Actinomyces+(124.4522~194.2467)×Anaerostipes+ (6.1294~71.2023)×Eubacterium._fissicatena_group-(158.923~76.3152)× Negativicoccus+(112.5601~779.4042)×Allisonella; Among them, 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 Erysipelothrix, 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 the genus Lachnoclostridium, Actinomyces is the relative abundance of the genus Actinomyces, Anaerostipes is the relative abundance of anaerobic Corynebacterium, Eubacterium._fissicatena_group is the relative abundance of the fissicatena group, Negativicoccus is the relative abundance of the genus Negativicoccus, and Allisonella is the relative abundance of the genus Allisonella.

9. A system for evaluating the growth and development status of children aged 0 to 6, applied to the method according to any one of claims 1 to 8, characterized in that: The method comprises 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 according to any one of claims 1 to 8 when executing the program.

10. Use of the method according to any one of claims 1 to 8 or the system according to claim 9 in preparing a product for evaluating the growth and development status of children aged 0 to 6 years old.

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