CN116973435A - Evaluation method and application of breast milk mineral elements - Google Patents
Evaluation method and application of breast milk mineral elements Download PDFInfo
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- 235000020256 human milk Nutrition 0.000 title claims abstract description 82
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- 239000002366 mineral element Substances 0.000 title claims abstract description 43
- 238000011156 evaluation Methods 0.000 title claims abstract description 11
- 238000000034 method Methods 0.000 claims abstract description 20
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- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 20
- 239000007789 gas Substances 0.000 claims description 18
- 239000011701 zinc Substances 0.000 claims description 14
- 238000001095 inductively coupled plasma mass spectrometry Methods 0.000 claims description 12
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Abstract
The invention relates to an evaluation method and application of breast milk mineral elements, which are carried out according to the following steps: (1) Collecting a breast milk sample, and collecting breast milk information corresponding to the breast milk sample at the same time of collecting the breast milk sample, wherein the breast milk information comprises mother basic information, infant basic information, meal intake information and infant feeding information; (2) preprocessing a breast milk sample to obtain a sample to be detected; (3) Measuring the mineral element content in a sample to be measured, combining the mineral element content with breast milk information, and establishing a model of mineral elements in breast milk; (4) And calculating the content level of the corresponding mineral element in the breast milk according to the model evaluation. The method can effectively establish a dynamic regression model, and can effectively judge the content level of mineral elements in breast milk according to the dietary condition of a mother, thereby realizing the evaluation of the mineral supply amount of the breast milk, and simultaneously feeding back the lack or excessive elements in the mineral of the breast milk to give related dietary advice in the dietary advice.
Description
Technical Field
The invention mainly relates to the field of breast milk evaluation, in particular to an evaluation method and application of breast milk mineral elements.
Background
Breast milk is the most ideal natural food for infants, contains abundant mineral substances, plays an important role in normal physiological functions and growth and development of infants, and is a necessary micronutrient for infants.
For example, sodium participates in regulating the volume and osmotic pressure of extracellular fluid, maintaining acid-base balance and normal blood pressure, maintaining the stress of neuromuscular, and the like, and 0-6 month old infant sodium is mainly from breast milk sodium. Iron is primarily involved in oxygen transport and in the process of organizing respiratory chain transport in the body; is involved in the composition of hemoglobin, myoglobin and cytochromes, and maintains the normal hematopoietic function of infants. However, there is a potential toxic effect on cells when in excess. Marginal or mild iron deficiency is often neglected without any clinical symptoms, 0-6 month old infant iron is mainly from breast milk iron. Copper is involved in maintaining normal hematopoiesis in infants, maintaining the integrity of the central nervous system, and is involved in the composition of copper protein and various enzymes, and has effects of promoting bone, vascular and skin health and resisting oxidation. Microcytic hypopigmentation anemia can occur during the deficiency, and 0-6 months infants mainly derive copper from breast milk. Zinc is a trace element necessary to maintain normal growth, cognitive performance, wound healing, taste and immune regulation of the body and the functioning of over 200 metalloenzymes. Marginal or mild zinc deficiency is often neglected because of the absence of any clinical symptoms, 0-6 month old infant zinc is mainly from breast milk zinc. The world health organization recommends that infants should be fed with pure breast milk for the first 6 months after birth, and the important difference of breast milk is that the nutrients have higher absorption and utilization rate compared with milk and infant formula milk powder, which is helpful for promoting the development and perfection of the immune system functions of newborns and infants. However, most breast milk components vary significantly in terms of lactation period, diet, region, etc. In the prior art, the lactating mother cannot directly obtain the breast milk energy and mineral nutrient intake at regular time or in a fixed quantity, so that the nutritional requirements of infants 0-6 months old on most mineral substances are met, the occurrence of excessive and deficiency of certain mineral nutrient elements of the infants fed by the lactating mother is avoided, the breast feeding rate is improved, and the technical problem to be solved in the prior art is urgent.
In view of this, the present invention has been made.
Disclosure of Invention
The invention aims to provide a method for simply and quickly evaluating the content level of mineral elements in breast milk.
In order to achieve the above object, the present invention provides a method for evaluating mineral elements of breast milk and application thereof, comprising the steps of:
(1) Collecting a breast milk sample, and collecting breast milk information corresponding to the breast milk sample at the same time of collecting the breast milk sample, wherein the breast milk information comprises mother basic information, infant basic information, meal intake information and infant feeding information;
(2) Pretreating a breast milk sample to obtain a sample to be tested;
(3) Measuring the mineral element content in a sample to be measured, combining the mineral element content with breast milk information, and establishing a model of mineral elements in breast milk;
(4) And calculating the content level of the corresponding mineral element in the breast milk according to the model evaluation.
Preferably or alternatively, the mineral elements include elemental sodium, elemental zinc, elemental copper, and elemental iron.
Preferably or alternatively, the pretreatment method in step (2) is: adding concentrated nitric acid and hydrogen peroxide into the breast milk sample, digesting at constant temperature, cooling, heating to remove acid, and fixing the volume to obtain the sample to be measured.
Preferably or alternatively, the temperature of the constant temperature digestion is 150-170 ℃ and the digestion time is 4-5h.
Preferably or alternatively, the determination of the mineral element content in the sample to be measured in step (3) is carried out using inductively coupled plasma mass spectrometry.
Preferably or alternatively, the parameters of the inductively coupled plasma mass spectrometry are: 9 Be＞2000cps、 115 In＞40000cps、 238 U＞30000cps、 220 Bkgd（background）≤3cps、 156 CeO/ 140 Ce≤0.025、Ce ＋＋ 140Ce is less than or equal to 0.03, the gas flow of the atomizer, the auxiliary gas flow and the plasma gas flow are respectively 0.92, 1.20 and 18.00L/min, the ICP radio frequency power is 1600W, the voltage of the simulation stage and the voltage of the pulse stage are respectively-1800V and 1100V, and a dynamic reaction mode is adopted.
The invention also provides application of the method for evaluating the breast milk mineral elements in the fields of nutritional consultation and diet suggestion.
The method can effectively establish a dynamic regression model, and can effectively judge the content level of mineral elements in the breast milk according to the dietary condition of the mother, thereby realizing the evaluation of the mineral supply amount of the breast milk, so as to infer whether the mineral supply amount of the breast milk meets the growth requirement of infants, avoid the risk of excessive intake and deficiency, prevent certain diseases, feed back the deficient or excessive elements in the mineral of the mother, and give related dietary suggestions in the dietary suggestions.
Drawings
FIG. 1 is a graph of the AUC corresponding to the model of example 2;
FIG. 2 is a graph of the AUC corresponding to the model of example 3;
FIG. 3 is a graph of the corresponding AUC of the model of example 4;
fig. 4 is a graph of AUC corresponding to the model of example 5.
Detailed Description
The following describes specific embodiments of the present invention in detail. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
The experimental methods used in the following examples are conventional methods unless otherwise specified.
Materials, reagents and the like used in the examples described below are commercially available unless otherwise specified.
Example 1
In this embodiment, a method for collecting and preprocessing a breast milk sample is provided.
The method for collecting the breast milk sample comprises the following steps:
the method is characterized in that the breast milk samples are collected at a uniform time point, the physical indexes of lactates from which all the breast milk samples are derived are normal, and the infants are delivered at full term (38-42 weeks of gestation) without congenital or genetic diseases.
Lactating women need to empty one breast in the morning between 6:00 and 7:00 a.m. after which whole milk is collected from one breast (previously empty) in the morning between 9:00 and 11:00 a.m.. Mixing whole milk, packaging into 1mL sterile freezing tube, and storing in-80deg.C ultra-low temperature refrigerator.
In the process of collecting the breast milk sample, information collection is carried out simultaneously, and breast milk information corresponding to the breast milk sample is collected, wherein the breast milk information comprises mother basic information, infant basic information, meal intake information and infant feeding information.
Wherein, the mother basic information comprises name, age, delivery mode, milk time, height, weight, breast milk sample (front section, rear section, whole milk).
The infant basic information includes name, date of birth, length, weight, sex, length of birth and weight of birth.
The diet recording information is filled in the intake conditions of various main and auxiliary foods by a diet review method, and the intake conditions of foods are recorded according to nine major categories of meat, fruits, vegetables, fish and shrimp, eggs, milk, cereals and potatoes, miscellaneous beans, soybeans, nuts and grease by referring to the second edition of Chinese national institute of nutrition.
The infant feeding information includes the number of breasts, the amount of breast milk intake, and the time of lactation.
Accurately weighing 1.00g of collected breast milk sample from a single source, adding 4mL of concentrated nitric acid and 2mL of hydrogen peroxide solution into a digestion inner tank, covering an inner cover, screwing a stainless steel jacket, placing into a constant-temperature drying box, carrying out heat preservation reaction for 4-5h at 150-170 ℃ to enable the breast milk sample to be completely digested, taking out, cooling to room temperature, taking out digestion liquid from the digestion inner tank, removing acid until the residual liquid is about 0.5mL at 100 ℃ on a temperature-controlled electric plate, transferring into a constant volume centrifuge tube, washing the digestion tank for 3-4 times, combining the washing liquid and the digestion liquid after acid removal, fixing the volume to 25mL, shaking uniformly, and filtering to obtain the sample to be measured.
Example 2
The sample to be tested prepared in the manner of example 1 was measured by inductively coupled plasma mass spectrometry and the sodium content of the breast milk sample was obtained.
The parameters of inductively coupled plasma mass spectrometry were: 9 Be＞2000cps、 115 In＞40000cps、 238 U＞30000cps、 220 Bkgd（background）≤3cps、 156 CeO/ 140 Ce≤0.025、Ce ＋＋ 140Ce is less than or equal to 0.03, the gas flow of the atomizer, the auxiliary gas flow and the plasma gas flow are respectively 0.92, 1.20 and 18.00L/min, the ICP radio frequency power is 1600W, the voltage of the simulation stage and the voltage of the pulse stage are respectively-1800V and 1100V, and a dynamic reaction mode is adopted.
The reaction gas A is ammonia gas, the reaction gas B is oxygen gas, and the units of the reaction gas A and the reaction gas B are mL/min:
| element(s) | Quality number (amu) | Mode | Reaction gas A | Reaction gas B | Quadrupole rod parameters Rpq of reaction cell |
| Na | 22.9898 | DRC | 0.6 | 0.0 | 0.6 |
。
After 394 samples are measured by the method, 341 samples are randomly selected, correlation analysis is carried out on mineral element data of the samples and Y scores corresponding to the samples through SPSS25 statistical software, mineral elements with the lowest significance difference at a 95% confidence level (p < 0.05) are selected, and a data model is established through single-factor variance analysis and multiple linear regression analysis.
The SPSS analysis results are shown in the following table:
| Na | B | significance sig |
| Lactation time | -0.112 | 0.000 |
| Vegetables | -0.008 | 0.006 |
| Fish and shrimp | 0.007 | 0.044 |
| Milk | -0.011 | 0.024 |
| Cereal potatoes and miscellaneous beans | 0.003 | 0.048 |
| Constant value | 25.991 | 0.000 |
。
According to the table, the built data model is Y Na -0.112 x lactation time-0.008 x vegetables +0.007 x fish and shrimp-0.011 x milk +0.003 x cereal potatoes +25.991.
Wherein the unit of each type of food is the gram number of the food intake in 24 hours, and the lactation time is the number of days of post-natal time of the lactating mother.
Statistics of Y for each sample Na The value sets the dimension and the results are shown in the following table:
| dimension(s) | Y Na |
| 0 | -1.7727 |
| 25% | 13.7036 |
| 50% | 18.1754 |
| 75% | 22.2958 |
| 100% | 37.5733 |
。
Y calculated by the model Na The value is brought into the dimension table to obtain the level of the mineral element Na of the breast milk sample in the whole lactating mother, and when the level is too low, such as lower than 25%, timely diet and nutrition intervention measures of the lactating mother can be suggested.
The resulting model was validated with the 53 remaining samples out of the 394 samples assayed as the validation set. Model calculated Y Na The corresponding dimension of the content level is the correct result in accordance with the dimension of the actual measured content of sodium in the sample. AUC curves were also plotted for this model, as shown in figure 1.
The data correlation coefficient (r=0.505, significance value P < 0.05) used above, proved by a verification set, provided a model accuracy of 76.61%. And combining with an AUC curve graph, the model has good accuracy.
Example 3
The sample to be tested prepared in the manner of example 1 was measured by inductively coupled plasma mass spectrometry and the iron element content of the breast milk sample was obtained.
The parameters of inductively coupled plasma mass spectrometry were: 9 Be＞2000cps、 115 In＞40000cps、 238 U＞30000cps、 220 Bkgd（background）≤3cps、 156 CeO/ 140 Ce≤0.025、Ce ＋＋ /140Ce≤0.03, wherein the gas flow of the atomizer, the auxiliary gas flow and the plasma gas flow are respectively 0.92, 1.20 and 18.00L/min, the ICP radio frequency power is 1600W, the voltage of the simulation stage and the voltage of the pulse stage are respectively-1800V and 1100V, and a dynamic reaction mode is adopted.
The reaction gas A is ammonia gas, the reaction gas B is oxygen gas, and the units of the reaction gas A and the reaction gas B are mL/min:
| element(s) | Quality number (amu) | Mode | Reaction gas A | Reaction gas B | Quadrupole rod parameters Rpq of reaction cell |
| Fe | 55.9349 | DRC | 0.6 | 0.0 | 0.6 |
。
After 131 samples are measured, 80 samples are randomly selected, correlation analysis is carried out on mineral element data of the samples and Y scores corresponding to the samples through SPSS25 statistical software, mineral elements with the lowest significance difference at a 95% confidence level (p < 0.05) are selected, and a data model is established through single-factor variance analysis and multiple linear regression analysis.
The SPSS analysis results are shown in the following table:
| Fe | B | significance sig |
| Livestock meat | -0.112 | 0.044 |
| Fruits and the like | -0.178 | 0.046 |
| Eggs and eggs | 0.464 | 0.004 |
| Milk | -0.316 | 0.014 |
| Constant value | 493.277 | 0.000 |
。
According to the table, the built data model is Y Fe -0.152 x livestock meat-0.178 x fruits +0.464 x eggs-0.316 x milk +493.277.
Wherein the unit of each type of food is the gram of the food intake for 24 hours.
Statistics of Y for each sample Fe The value sets the dimension and the results are shown in the following table:
| dimension(s) | Y Fe |
| 0 | 246.962 |
| 25% | 387.4216 |
| 50% | 447.0794 |
| 75% | 478.71005 |
| 100% | 716.8564 |
。
Y calculated by the model Fe The value is brought into the dimension table to obtain the level of the mineral element Fe in the whole lactating mother of the breast milk sample, and when the level is too low, such as lower than 25%, timely diet and nutrition intervention measures of the lactating mother can be suggested.
The obtained model was verified using the remaining 51 samples out of the 131 samples measured as a verification set. Model calculated Y Fe The corresponding dimension of the content level is the correct result in accordance with the dimension of the actual measured content of iron in the sample. Simultaneously drawing AUC curves for the modelAs shown in fig. 2.
The data correlation coefficient (r=0.562, significance value P < 0.05) used above was verified by the verification set to provide a model accuracy of 73.08%. And combining with an AUC curve graph, the model has good accuracy.
Example 4
The sample to be tested prepared in the manner of example 1 was measured by inductively coupled plasma mass spectrometry to obtain the copper element content of the breast milk sample.
The parameters of inductively coupled plasma mass spectrometry were: 9 Be＞2000cps、 115 In＞40000cps、 238 U＞30000cps、 220 Bkgd（background）≤3cps、 156 CeO/ 140 Ce≤0.025、Ce ＋＋ 140Ce is less than or equal to 0.03, the gas flow of the atomizer, the auxiliary gas flow and the plasma gas flow are respectively 0.92, 1.20 and 18.00L/min, the ICP radio frequency power is 1600W, the voltage of the simulation stage and the voltage of the pulse stage are respectively-1800V and 1100V, and a dynamic reaction mode is adopted.
The reaction gas A is ammonia gas, the reaction gas B is oxygen gas, and the units of the reaction gas A and the reaction gas B are mL/min:
| element(s) | Quality number (amu) | Mode | Reaction gas A | Reaction gas B | Quadrupole rod parameters Rpq of reaction cell |
| Cu | 62.9298 | DRC | 0.3 | 0.0 | 0.6 |
。
After 276 samples are measured, 212 of the samples are randomly selected to carry out correlation analysis on mineral element data of the samples and Y scores corresponding to the samples through SPSS25 statistical software, mineral elements with the lowest significance difference at a 95% confidence level (p < 0.05) are selected, and a data model is established through single-factor variance analysis and multiple linear regression analysis.
The SPSS analysis results are shown in the following table:
| Cu | B | significance sig |
| Lactation time | -0.233 | 0.000 |
| Vegetables | -0.008 | 0.014 |
| Milk | -0.019 | 0.002 |
| Oils and fats | 0.200 | 0.046 |
| Cereal potatoes and miscellaneous beans | 0.006 | 0.005 |
| Constant value | 50.666 | 0.000 |
。
According to the table, the built data model is Y Cu = -0.233 x lactation time-0.008 x vegetables-0.019 x milk +0.200 x oil +0.006 x cereal potatoes +50.666.
Wherein the unit of each type of food is the gram number of the food intake in 24 hours, and the lactation time is the number of days of post-natal time of the lactating mother.
Statistics of Y for each sample Cu The value sets the dimension and the results are shown in the following table:
| dimension(s) | Y Cu |
| 0 | -1.4647 |
| 25% | 25.107225 |
| 50% | 35.9905 |
| 75% | 47.893275 |
| 100% | 62.1252 |
。
Y calculated by the model Cu The value is brought into the dimension table to obtain the level of the mineral element Cu in the whole lactating mother of the breast milk sample, and when the level is too low, such as lower than 25%, timely diet and nutritional intervention measures of the lactating mother can be suggested.
The resulting model was validated with the remaining 64 samples of the 276 samples measured as a validation set. Model calculated Y Cu The corresponding dimension of the content level is the correct result in accordance with the dimension of the actual measured content of copper in the sample. AUC curves were also plotted for this model, as shown in fig. 3.
The data correlation coefficient (r=0.865, significance value P < 0.05) used above was verified by the verification set to provide a model accuracy of 83.96%. And combining with an AUC curve graph, the model has good accuracy.
Example 5
The sample to be tested prepared in the manner of example 1 was measured by inductively coupled plasma mass spectrometry to obtain the zinc element content of the breast milk sample.
The parameters of inductively coupled plasma mass spectrometry were: 9 Be＞2000cps、 115 In＞40000cps、 238 U＞30000cps、 220 Bkgd（background）≤3cps、 156 CeO/ 140 Ce≤0.025、Ce ＋＋ 140Ce is less than or equal to 0.03, the gas flow of the atomizer, the auxiliary gas flow and the plasma gas flow are respectively 0.92, 1.20 and 18.00L/min, the ICP radio frequency power is 1600W, the voltage of the simulation stage and the voltage of the pulse stage are respectively-1800V and 1100V, and a dynamic reaction mode is adopted.
The reaction gas A is ammonia gas, the reaction gas B is oxygen gas, and the units of the reaction gas A and the reaction gas B are mL/min:
| element(s) | Quality number (amu) | Mode | Reaction gas A | Reaction gas B | Quadrupole rod parameters Rpq of reaction cell |
| Zn | 65.9260 | DRC | 0.3 | 0.0 | 0.6 |
。
After 397 samples are measured, 283 of the samples are randomly selected, correlation analysis is carried out on mineral element data of the samples and Y scores corresponding to the samples through SPSS25 statistical software, mineral elements with the lowest significance difference at a 95% confidence level (p < 0.05) are selected, and a data model is established through single-factor variance analysis and multiple linear regression analysis.
The SPSS analysis results are shown in the following table:
| Zn | B | significance sig |
| Stage numbering | -32.702 | 0.000 |
| Vegetables | -0.060 | 0.026 |
| Fish and shrimp | 0.104 | 0.003 |
| Milk | 0.103 | 0.036 |
| Constant value | 347.320 | 0.000 |
。
According to the table, the built data model is Y Zn = (-32.702 ×stage number-0.060×vegetables+0.104×fish and shrimp+0.103×milk+ 347.320) ×10 -3 。
Wherein, the unit of each type of food is the gram of the intake of the food in 24 hours, and the stage number is obtained in the following way: the collected breast milk samples are divided into 1 (0-5 d after birth), 2 (6-15 d after birth), 3 (16-30 d after birth), 4 (31-60 d after birth), 5 (61-90 d after birth), 6 (91-135 d after birth) and 7 (136-180 d after birth) according to the post-natal time of the lactating mother and numbering the same.
Statistics of Y for each sample Zn The value sets the dimension and the results are shown in the following table:
| dimension(s) | Y Zn |
| 0 | 0.0260159 |
| 25% | 0.159 |
| 50% | 0.2180168 |
| 75% | 0.25966295 |
| 100% | 0.4761785 |
。
Y calculated by the model Zn The value is brought into the dimension table to obtain the level of the mineral element Zn in the whole lactating mother of the breast milk sample, and when the level is too low, such as lower than 25%, timely diet and nutrition intervention measures of the lactating mother can be suggested.
The obtained model was verified using 114 samples remaining from the 397 samples measured as a verification set. Model calculated Y Zn The corresponding dimension of the content level and the real zinc in the sampleThe dimensions to which the inter-assay content belongs are consistent and are the correct results. AUC curves were also plotted for this model, as shown in fig. 4.
The data correlation coefficient (r=0.541, significance value P < 0.05) used above was verified by the verification set to provide a model accuracy of 75.11%. And combining with an AUC curve graph, the model has good accuracy.
From the above, the method can effectively establish a dynamic regression model, and can effectively judge the content level of mineral elements in the breast milk according to the dietary condition of the mother, thereby realizing the evaluation of the mineral substance supply amount of the breast milk so as to infer whether the mineral substance supply amount of the breast milk meets the growth requirement of infants, avoid the excessive intake risk and deficiency, prevent certain diseases, feed back the lack or excessive elements in the mineral substance of the breast milk and give related dietary suggestions in the dietary suggestions.
The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present invention within the scope of the technical concept of the present invention, and all the simple modifications belong to the protection scope of the present invention.
Moreover, any combination of the various embodiments of the invention can be made without departing from the spirit of the invention, which should also be considered as disclosed herein.
Claims (7)
1. A method for evaluating a mineral element of breast milk, comprising the steps of:
(1) Collecting a breast milk sample, and collecting breast milk information corresponding to the breast milk sample at the same time of collecting the breast milk sample, wherein the breast milk information comprises mother basic information, infant basic information, meal intake information and infant feeding information;
(2) Pretreating a breast milk sample to obtain a sample to be tested;
(3) Measuring the mineral element content in a sample to be measured, combining the mineral element content with breast milk information, and establishing a model of mineral elements in breast milk;
(4) And calculating the content level of the corresponding mineral element in the breast milk according to the model evaluation.
2. The method of evaluating a breast milk mineral element according to claim 1, wherein the mineral element includes sodium element, zinc element, copper element, and iron element.
3. The method for evaluating a breast milk mineral element according to claim 1, wherein the pretreatment method in step (2) is: adding concentrated nitric acid and hydrogen peroxide into the breast milk sample, digesting at constant temperature, cooling, heating to remove acid, and fixing the volume to obtain the sample to be measured.
4. A method of assessing a mineral element of breast milk according to claim 3, wherein the temperature of the constant temperature digestion is 150-170 ℃ and the digestion time is 4-5 hours.
5. The method for evaluating a mineral element in breast milk according to claim 1, wherein the determination of the mineral element content in the sample to be measured in step (3) is performed by inductively coupled plasma mass spectrometry.
6. The method of claim 5, wherein the parameters of inductively coupled plasma mass spectrometry are: 9 Be＞2000cps、 115 In＞40000cps、 238 U＞30000cps、 220 Bkgd（background）≤3cps、 156 CeO/ 140 Ce≤0.025、Ce ＋＋ 140Ce is less than or equal to 0.03, the gas flow of the atomizer, the auxiliary gas flow and the plasma gas flow are respectively 0.92, 1.20 and 18.00L/min, the ICP radio frequency power is 1600W, the voltage of the simulation stage and the voltage of the pulse stage are respectively-1800V and 1100V, and a dynamic reaction mode is adopted.
7. Use of the method according to any one of claims 1-6 in the field of nutritional counseling and meal advice.
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