Air pollution exposure intervention evaluation method and system for cardiovascular disease high-risk groups

Abstract

The invention provides an air pollution exposure intervention evaluation method and system for cardiovascular disease high-risk groups, and relates to the technical field of big data analysis processing, and the method comprises the steps: screening to-be-evaluated queue groups, and collecting the personal information, disease follow-up information and air pollution exposure concentration to be intervened of the to-be-evaluated queue groups; inputting the personal information and disease follow-up visit information of the to-be-evaluated queue population to a corresponding cardiovascular disease onset risk prediction model, obtaining the onset risk of each to-be-evaluated object through evaluation, and identifying a cardiovascular disease high-risk population; according to the cardiovascular disease incidence information, constructing a cardiovascular disease incidence intervention evaluation microscopic simulation model, setting scenes corresponding to different air pollution exposure concentrations to be intervened, and quantitatively evaluating the influence of different scenes on the cardiovascular disease incidence risk of cardiovascular disease high-risk groups to obtain an air pollution exposure intervention evaluation result.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis and processing, and in particular to an air pollution exposure intervention evaluation method and system for people at high risk of cardiovascular disease. Background Art

[0002] This section is intended to provide a background or context for embodiments of the present invention. No description herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] At present, a large number of studies have reported on the damage of long-term exposure to atmospheric pollutants such as PM2.5 and air pollution to human health, especially the impact on the incidence and mortality of cardiovascular diseases. People at high risk of cardiovascular disease may increase their risk of cardiovascular disease under long-term exposure to air pollution. Using air purifiers and wearing masks can effectively reduce the exposure level of air pollution. However, there is currently a lack of simple algorithms to quantitatively evaluate the beneficial effects of air pollution exposure intervention on people at high risk of cardiovascular disease. Therefore, the existing technology has the following main deficiencies: In the past, the effect of air pollution exposure intervention was evaluated through traditional epidemiological intervention field surveys such as randomized controlled trials, which consumed a lot of manpower and financial resources; previous evaluation methods did not take into account the vulnerable population of cardiovascular disease, thereby underestimating the intervention effect in special populations.

[0004] In summary, due to the above-mentioned limitations of the air pollution exposure intervention evaluation method, there is an urgent need for a technical solution that can overcome the above-mentioned defects, improve the air pollution exposure intervention evaluation method, and support the promotion and application of intervention measures. Summary of the invention

[0005] In order to solve the problems existing in the prior art, the present invention proposes an air pollution exposure intervention evaluation method and system for people at high risk of cardiovascular disease.

[0006] In a first aspect of an embodiment of the present invention, a method for evaluating air pollution exposure intervention for a high-risk population for cardiovascular disease is proposed, the method comprising:

[0007] Screening the cohort population to be evaluated, collecting personal information, disease follow-up information, and proposed intervention air pollution exposure concentration of the cohort population to be evaluated;

[0008] Based on different gender groups, cardiovascular disease risk prediction models corresponding to preset time periods are established respectively, and the personal information and disease follow-up information of the cohort population to be evaluated are input into the corresponding cardiovascular disease risk prediction model, and the risk of each subject to be evaluated is obtained through evaluation; wherein, if the risk of developing disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease, if the risk of developing disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease, and if the risk of developing disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease are obtained;

[0009] According to the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation was constructed, and different scenarios corresponding to the proposed intervention air pollution exposure concentrations were set. The impact of different scenarios on the cardiovascular disease risk of the high-risk group of cardiovascular disease was quantitatively evaluated to obtain the air pollution exposure intervention evaluation results.

[0010] In a second aspect of an embodiment of the present invention, an air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease is proposed, the system comprising:

[0011] An information collection module is used to screen the population of the cohort to be evaluated, and collect personal information, disease follow-up information, and proposed intervention air pollution exposure concentration of the population of the cohort to be evaluated;

[0012] The risk assessment module is used to establish cardiovascular disease risk prediction models corresponding to preset time periods based on different gender groups, input the personal information and disease follow-up information of the cohort to be evaluated into the corresponding cardiovascular disease risk prediction model, and obtain the risk of each subject to be evaluated after evaluation; wherein, if the risk of developing disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease; if the risk of developing disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease; if the risk of developing disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease are obtained;

[0013] The air pollution exposure intervention evaluation module is used to construct a micro-simulation model for cardiovascular disease incidence intervention evaluation based on the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, set different scenarios corresponding to the proposed intervention air pollution exposure concentrations, quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of the high-risk group of cardiovascular disease, and obtain the air pollution exposure intervention evaluation results.

[0014] In a third aspect of an embodiment of the present invention, a computer device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements an air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease when executing the computer program.

[0015] In a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is proposed, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, an air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease is implemented.

[0016] In a fifth aspect of an embodiment of the present invention, a computer program product is proposed, which includes a computer program, and when the computer program is executed by a processor, an air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease is implemented.

[0017] The air pollution exposure intervention evaluation method and system for people at high risk of cardiovascular disease proposed in the present invention screens a cohort of people to be evaluated, collects personal information, disease follow-up information and proposed air pollution exposure concentration of the cohort of people to be evaluated; establishes cardiovascular disease risk prediction models corresponding to preset time periods based on different gender groups, inputs the personal information and disease follow-up information of the cohort of people to be evaluated into the corresponding cardiovascular disease risk prediction models, and obtains the risk of each object to be evaluated after evaluation; wherein, if the risk of disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease, if the risk of disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease, and if the risk of disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and obtains the high-risk group, medium-risk group and low-risk group for cardiovascular disease. group and low-risk group; according to the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation is constructed, and different scenarios corresponding to the proposed intervention air pollution exposure concentrations are set to quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of people at high risk of cardiovascular disease, and obtain the air pollution exposure intervention evaluation results. The overall solution innovatively connects the cardiovascular disease risk prediction model with the micro-simulation model considering competing risks in series, first identifies the high-risk group of cardiovascular disease, and further uses algorithms to quantitatively evaluate the health benefits of the high-risk group of cardiovascular disease after reducing air pollution exposure, realizes the air pollution exposure intervention evaluation of people at high risk of cardiovascular disease, improves the processing efficiency of intervention evaluation, improves the intervention effect, and provides strong technical support for environmental science. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 It is a flow chart of an air pollution exposure intervention evaluation method for a high-risk population for cardiovascular disease according to an embodiment of the present invention.

[0020] Figure 2 It is a schematic diagram of a process for assessing the risk of disease according to an embodiment of the present invention.

[0021] Figure 3 It is a schematic diagram of the conversion relationship between disease development states according to an embodiment of the present invention.

[0022] Figure 4 It is a flowchart of quantitative evaluation according to an embodiment of the present invention.

[0023] Figure 5 It is a schematic diagram of the architecture of an air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease according to an embodiment of the present invention.

[0024] Figure 6 It is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0026] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0027] According to an embodiment of the present invention, an air pollution exposure intervention evaluation method and system for people at high risk of cardiovascular disease are proposed, which relate to the technical field of big data analysis and processing.

[0028] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0029] Figure 1FIG. 1 is a flow chart of an air pollution exposure intervention evaluation method for a high-risk population for cardiovascular disease according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0030] S101, screening the population of the cohort to be evaluated, and collecting personal information, disease follow-up information, and proposed intervention air pollution exposure concentration of the population of the cohort to be evaluated;

[0031] S102, establishing cardiovascular disease risk prediction models corresponding to preset time periods based on different gender groups, inputting personal information and disease follow-up information of the cohort to be evaluated into the corresponding cardiovascular disease risk prediction model, and obtaining the risk of each subject to be evaluated after evaluation; wherein, if the risk of developing is within the first numerical range, the subject is classified as a high-risk group for cardiovascular disease; if the risk of developing is within the second numerical range, the subject is classified as a medium-risk group for cardiovascular disease; if the risk of developing is within the third numerical range, the subject is classified as a low-risk group for cardiovascular disease, and a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease are obtained;

[0032] S103, based on the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group for cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation is constructed, different scenarios corresponding to the proposed intervention air pollution exposure concentrations are set, and the effects of different scenarios on the cardiovascular disease incidence risk of the high-risk group for cardiovascular disease are quantitatively evaluated to obtain the air pollution exposure intervention evaluation results.

[0033] The present invention collects population baseline information, cardiovascular disease incidence, and air pollutant exposure concentration, uses the COX proportional risk model to establish a cardiovascular disease incidence prediction model, identifies high-risk populations, and further constructs a micro-simulation model. By setting different air pollution exposure concentration reduction scenarios, the effect of reducing air pollution exposure on the incidence of cardiovascular disease is quantitatively evaluated. The overall solution connects the cardiovascular disease incidence risk prediction model with the vascular disease incidence intervention evaluation micro-simulation model in series, simulates different air pollutant concentration reduction scenarios, evaluates the effects of different intervention measures on the risk of cardiovascular disease, and provides a basis for formulating effective air pollution intervention measures; through effective air pollution intervention, the incidence and mortality of cardiovascular diseases can be reduced, the health management of people at high risk of cardiovascular diseases can be improved, and the impact of air pollution on public health can be reduced.

[0034] In order to explain more clearly the air pollution exposure intervention evaluation method for the above-mentioned high-risk groups for cardiovascular disease, each step is explained in detail below.

[0035] In one embodiment, for S101, a cohort population to be evaluated is screened, and personal information, disease follow-up information, and proposed air pollution exposure concentration for intervention of the cohort population to be evaluated are collected.

[0036] Specifically, the cohort population to be evaluated includes at least a population without the disease and a population with cardiovascular disease;

[0037] The personal information of the cohort population to be evaluated includes at least age, gender, income level, urban or rural residence, height, weight, blood pressure, heart rate, waist circumference, smoking history, family history of cardiovascular disease, history of atrial fibrillation, history of diabetes, blood sugar, and blood lipids; the disease follow-up information includes at least the incidence of cardiovascular disease during the preset follow-up period, and the incidence of cardiovascular disease includes at least the time of diagnosis and the type of disease;

[0038] The proposed intervention air pollution exposure concentrations include at least the exposure concentrations of PM2.5 and O3.

[0039] In practical application scenarios, it is first necessary to select a suitable population sample as the survey object. The sample can be the general population or a population with a high risk of cardiovascular disease. When selecting a sample, it is necessary to consider the representativeness of the sample and the purpose of the study to ensure the applicability and validity of the results.

[0040] At the beginning of the study, a series of health and demographic information about the subjects is collected. Collecting baseline data of the target population can improve the rationality and accuracy of subsequent analysis and evaluation. The collected data includes at least:

[0041] Age, gender: basic demographic characteristics.

[0042] Income level, urban / rural residence: indicators of socioeconomic status that may influence health behaviors and access to resources.

[0043] Height, weight, blood pressure, heart rate, waist circumference: body measurements and health indicators associated with cardiovascular disease risk.

[0044] Smoking history, family history of cardiovascular disease, history of atrial fibrillation, history of diabetes: lifestyle and genetic factors, these are important risk factors for cardiovascular disease.

[0045] Blood sugar and blood lipids: metabolic indicators, closely related to the risk of cardiovascular disease.

[0046] Disease follow-up data are collected to assess long-term health outcomes, including:

[0047] The incidence of cardiovascular diseases: including the time of diagnosis and the specific type of disease.

[0048] The above data provide strong data support for assessing the incidence of cardiovascular disease and the accuracy of prediction models.

[0049] In one embodiment, for S102, cardiovascular disease risk prediction models corresponding to preset time periods are established based on different gender groups, and the personal information and disease follow-up information of the cohort population to be evaluated are input into the corresponding cardiovascular disease risk prediction model, and the risk of each object to be evaluated is obtained through evaluation; wherein, if the risk of disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease, if the risk of disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease, and if the risk of disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease are obtained.

[0050] refer to Figure 2 , is a schematic diagram of a process for assessing the risk of disease according to an embodiment of the present invention. Figure 2 As shown, the specific method is:

[0051] S201, using the proportional regression risk model, establish cardiovascular disease risk prediction models corresponding to the preset duration in different gender groups; among them, variables whose discriminant improvement index is greater than the preset index and variables whose probability of the observed statistic is less than the set probability value when the null hypothesis is true are respectively included in the cardiovascular disease risk prediction model, and the predictive ability of the model is evaluated by goodness of fit test and C statistic;

[0052] Specifically, based on the collected data, variables related to the incidence of cardiovascular diseases were selected, such as age, gender, income level, urban or rural residence, height, weight, blood pressure, heart rate, waist circumference, smoking history, family history of cardiovascular disease, history of atrial fibrillation, history of diabetes, blood sugar, blood lipids, etc.

[0053] The COX proportional hazard model was used to build models for men and women respectively. The basic form of the COX model is:

[0054] h(t,X)=h0(t)exp(β1X1+β2X2+...+β p X p );

[0055] h(t,X) is the hazard rate function at time t and covariate X, h0(t) is the baseline hazard rate function, exp(β1X1+β2X2+...+β p X p ) is the risk ratio, which contains the p term, indicating the effect of the covariate on the risk. The model parameters β1, β2, …, β p , select appropriate variables to enter the model, and perform stepwise regression to optimize the model.

[0056] When selecting variables, you can consider the integrated discriminant improvement index and P value. The integrated discriminant improvement index (IDI) is a measure of the performance of a prediction model, especially when comparing two models (for example, a baseline model and a model with new variables added). The IDI measures the average improvement of the new model in predicting the probability of an event relative to the baseline model. If the IDI is greater than 6%, it means that the new model has a significant improvement in predictive ability relative to the baseline model.

[0057] The P value is a statistic used in hypothesis testing to measure the probability of the observed statistic or a more extreme situation occurring when the null hypothesis is true. The null hypothesis usually indicates that there is no effect or no difference. For example, when comparing two groups of data, the null hypothesis is usually that there is no difference between the two groups. The smaller the P value, the smaller the probability of the observed data or more extreme data occurring when the null hypothesis is true, thus providing more evidence to reject the null hypothesis.

[0058] The goodness-of-fit test and C statistic can be further used to evaluate the predictive ability of the model.

[0059] The goodness of fit test can be a chi-square test (such as the Hosmer-Lemeshow chi-square test) to assess whether the difference between the model's predicted values ​​and the actual values ​​is significant. The test divides the sample into multiple groups (usually based on deciles of predicted probability) and then compares the number of events observed in each group with the expected number of events. If the model has good predictive ability, the number of events observed should be close to the expected number of events, and the chi-square statistic should be close to 0. If the P value of the chi-square test is large (usually greater than 0.05), it indicates that there is no significant difference between the model's predicted values ​​and the actual values, and the model fits well.

[0060] The C statistic (Concordance Statistic) is a measure of the predictive power of a model. It is calculated by comparing all possible pairs of observations (one positive and one negative). If the model predicts a higher probability of the positive than the negative, the pair is considered to be consistent. The value of the C statistic ranges from 0.5 (no predictive power) to 1 (perfect predictive power). C statistic values ​​greater than 0.7 are considered to have good predictive power, while values ​​greater than 0.8 are considered to be excellent predictive models.

[0061] S202, using the cardiovascular disease risk prediction model, inputting the personal information and disease follow-up information of the cohort population to be evaluated into the model, evaluating the cardiovascular disease risk of each subject to be evaluated over a preset period of time, and classifying the subjects to be evaluated whose assessed risk is greater than or equal to 10.0% as a high-risk group for cardiovascular disease, the subjects to be evaluated whose assessed risk is greater than or equal to 5.0% and less than 10% as a medium-risk group for cardiovascular disease, and the subjects to be evaluated whose risk is less than 5% as a low-risk group for cardiovascular disease, thereby obtaining a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease.

[0062] The preset period is 5 years or 10 years.

[0063] In one embodiment, for S103, based on the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group for cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation is constructed, and different scenarios corresponding to the proposed intervention air pollution exposure concentrations are set to quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of the high-risk group for cardiovascular disease, and obtain the air pollution exposure intervention evaluation results.

[0064] Specifically, the cardiovascular disease incidence intervention evaluation micro-simulation model is used to simulate the disease development process of the cohort population to be evaluated, wherein the disease development states contained in the micro-simulation model at least include not suffering from cardiovascular disease, suffering from cardiovascular disease, dying from cardiovascular disease, and dying from other causes of disease.

[0065] refer to Figure 3 , is a schematic diagram of the conversion relationship between disease development states according to an embodiment of the present invention. Figure 3 As shown, the transition probabilities between disease development states include: a first state transition probability P1 from not suffering from cardiovascular disease to suffering from cardiovascular disease, a second state transition probability P2 from not suffering from cardiovascular disease to dying from cardiovascular disease, a third state transition probability P3 from not suffering from cardiovascular disease to dying from other causes of disease, a fourth transition probability P4 from suffering from cardiovascular disease to suffering from cardiovascular disease, a fifth transition probability P5 from suffering from cardiovascular disease to dying from cardiovascular disease, a sixth transition probability P6 from suffering from cardiovascular disease to dying from other causes of disease, and a seventh transition probability P7 from suffering from cardiovascular disease to suffering from cardiovascular disease.

[0066] In one embodiment, reference Figure 4 , is a schematic diagram of a quantitative evaluation process of an embodiment of the present invention. Figure 4 As shown, the specific method is:

[0067] S401, using the cardiovascular disease risk prediction model to predict the first state transition probability P1 of the high-risk group, the medium-risk group and the low-risk group of cardiovascular disease at the first air pollution exposure concentration, respectively, and combining the second state transition probability P2 to the seventh state transition probability P7 to determine the incidence of cardiovascular disease at the first air pollution exposure concentration as a control group sample;

[0068] S402, setting the scenario of decreasing air pollution exposure concentration;

[0069] For example, for the actual air pollution exposure concentration, the 3 , 20 μg / m 3 scenarios of air pollution exposure concentrations.

[0070] S403, simulating the incidence of cardiovascular disease in a scenario where the air pollution exposure concentration decreases, and determining the first state transition probabilities P1' corresponding to the high-risk group, the medium-risk group, and the low-risk group of cardiovascular disease in different scenarios;

[0071] The calculation formula of the first state transition probability P1' corresponding to different scenarios is:

[0072]

[0073] Among them, P1' is the risk probability of cardiovascular disease for each subject to be evaluated after the simulated air pollution exposure concentration decreases, indicating the first state transition probability under different scenarios; P1 is the risk probability of cardiovascular disease for each subject to be evaluated at the first air pollution exposure concentration, indicating the first state transition probability at the first air pollution exposure concentration; X is the decreased concentration corresponding to the scenario of decreased air pollution exposure concentration; HR is the risk of cardiovascular disease for each increase in the set concentration of air pollution exposure concentration obtained by querying the data;

[0074] S404, according to the first state transition probability P1' corresponding to different scenarios, combined with the second state transition probability P2 to the seventh state transition probability P7, using the cardiovascular disease incidence intervention evaluation micro-simulation model to simulate the incidence of cardiovascular diseases after the air pollution exposure concentration is reduced as the experimental group sample;

[0075] S405, based on the control group samples and the experimental group samples, determine the number of cardiovascular disease cases prevented after reducing the air pollution exposure concentration in the high-risk group, medium-risk group and low-risk group for cardiovascular disease, and the number of people who need intervention for each prevented cardiovascular disease case; by comparing the differences in health benefits among the high-risk group, medium-risk group and low-risk group for cardiovascular disease after reducing the air pollution exposure concentration, quantitatively evaluate the protective effect of reducing the air pollution exposure concentration on the incidence of cardiovascular disease in the high-risk group for cardiovascular disease, and obtain the air pollution exposure intervention evaluation results.

[0076] It should be noted that, although the operations of the method of the present invention are described in a specific order in the above embodiments and the accompanying drawings, this does not require or imply that the operations must be performed in the specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0077] The air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease of the present invention is described below with reference to a specific embodiment.

[0078] 1. Collect data related to cardiovascular disease incidence prediction and air pollution exposure, including:

[0079] Identify the cohort population in which the intervention is to be evaluated, which can be a general cohort population or a special cohort focused on cardiovascular disease incidence;

[0080] The target population's baseline age, gender, income level, urban or rural residence, height, weight, blood pressure, heart rate, waist circumference, smoking history, family history of cardiovascular disease, history of atrial fibrillation, history of diabetes, blood sugar, and blood lipids were collected; as well as the incidence of cardiovascular disease in each person after 5 or 10 years of follow-up, including the time of diagnosis and specific type of disease.

[0081] Collect information on the long-term exposure concentration of air pollutants to be intervened by the population in the cohort to be evaluated. The air pollutants to be intervened may be PM2.5, O3, etc.

[0082] 2. Identify people at high risk of cardiovascular disease;

[0083] The COX proportional hazard model was used to establish a 5-year (or 10-year) cardiovascular disease incidence prediction model in different gender groups. Variables with a comprehensive discriminant improvement index of >6% and P<0.01 were included in the final incidence prediction model.

[0084] The Hosmer-Lemeshow chi-square test and C statistic were used to evaluate the predictive ability of the model. Since the cardiovascular risk prediction model in this method is only used to distinguish high-risk, medium-risk, and low-risk groups in the cohort to be evaluated, and is not used to promote other populations, no external validation is required.

[0085] The above-established cardiovascular disease risk prediction model was used to substitute the S1(2) data of the cohort population to be evaluated, and the 5-year (or 10-year) cardiovascular disease risk of each survey subject was evaluated. Based on the relevant information on cardiovascular disease risk assessment and management, survey subjects with an assessed risk of ≥10.0% were considered to be at high risk of cardiovascular disease, those with an assessed risk of 5.0% to 9.9% were considered to be at medium risk of cardiovascular disease, and those with a risk of <5% were considered to be at low risk of cardiovascular disease.

[0086] 3. Evaluate air pollution exposure interventions for high-risk populations;

[0087] For the high-risk, medium-risk and low-risk groups for cardiovascular disease distinguished as above, a micro-simulation model for the evaluation of cardiovascular disease incidence intervention was constructed. The risk calculation formulas were connected in series, and different air pollution exposure concentration exposure scenarios after intervention were set to quantitatively evaluate the protective effect of reducing air pollution exposure concentration on the incidence of cardiovascular disease in high-risk groups.

[0088] Constructing a cardiovascular disease intervention evaluation model:

[0089] A micro-simulation model that takes into account the competing risks of diseases is used to simulate the disease occurrence and development process of the cohort population, which is used to subsequently evaluate the impact of intervention measures to reduce air pollution exposure concentrations on the incidence of cardiovascular diseases in the population. The state transitions of the micro-simulation model include four states: no cardiovascular disease, cardiovascular disease, death from cardiovascular disease, and death from other causes. Figure 3 As shown, the exemplary P1-P7 represent the transition probabilities between different states, wherein P1 is derived from the above-mentioned cardiovascular disease risk calculation formula, and P2-P7 are converted from the estimated event rates in the cohort population to be evaluated or the event rates in the GBD database.

[0090] Assuming that the model cycle is 1 year and the simulation period is 5 years (or 10 years), by simulating the incidence of cardiovascular disease in the population before and after the reduction of air pollution exposure concentration in the next 5 years (or 10 years), the impact of intervention measures on the incidence of cardiovascular disease in high-risk populations is estimated, and the population intervention effect of reducing air pollution exposure concentration is evaluated.

[0091] Quantitative evaluation of the effect of reducing air pollution exposure concentration on the incidence of cardiovascular disease in high-risk populations:

[0092] The cohort survey subjects with predicted high-risk, moderate-risk, and low-risk of cardiovascular disease were used as the control group samples, with the cardiovascular disease risk probability P1 under the actual air pollution exposure concentration, combined with the estimated other state transition probabilities (P2-P7) in the cohort population and the incidence of cardiovascular disease when the air pollution exposure concentration of the population was not reduced.

[0093] Two scenarios of long-term exposure to air pollution are set to reduce concentration by 10 μg / m 3 , 20 μg / m 3 . The data show that the air pollution exposure concentration increases by 10μg / m 3 The risk of cardiovascular disease was reduced by 10 μg / m 3 or 20 μg / m 3 The risk probability P1' of cardiovascular disease for high-risk, medium-risk and low-risk subjects is calculated according to the following formula:

[0094]

[0095] Among them, P1' is the risk probability of cardiovascular disease for each subject to be evaluated after the simulated air pollution exposure concentration decreases, which represents the first state transition probability under different scenarios; P1 is the risk probability of cardiovascular disease for each subject to be evaluated at the first air pollution exposure concentration, which represents the first state transition probability at the first air pollution exposure concentration; X is the decrease concentration corresponding to the air pollution exposure concentration decrease scenario, and the set concentration is 10μg / m 3 or 20 μg / m 3 HR is the risk of cardiovascular disease for each increase in air pollution exposure concentration obtained through data query, and the set concentration is 10μg / m 3 .

[0096] Furthermore, P1' was combined with other estimated state transition probabilities (P2-P7) in the cohort population, and the micro-simulation model was used again to simulate the incidence of cardiovascular diseases after the population's air pollution exposure concentration was reduced. By comparing with the above scenarios, the number of preventable cardiovascular diseases in high-risk, medium-risk, and low-risk populations and the number of people needed to treat (NNT) for each case of cardiovascular disease prevented were calculated, respectively, to evaluate the impact of reduced air pollution exposure concentration on the incidence of cardiovascular diseases.

[0097] By comparing the differences in health benefits after reducing air pollution exposure concentrations among high-risk, medium-risk, and low-risk groups, the protective effect of reducing air pollution exposure concentrations on the incidence of cardiovascular diseases in high-risk groups was quantitatively evaluated.

[0098] The overall scheme of the present invention uses the COX proportional hazard model, combined with multiple factors such as gender, age, living habits and physiological indicators, to accurately identify the high-risk population for cardiovascular disease; the micro-simulation model and risk calculation formula are used to quantitatively evaluate the health benefits of the high-risk population for cardiovascular disease after reducing air pollution exposure, and the intervention evaluation effect is improved through model series connection. Further, by simulating different air pollutant concentration reduction scenarios, the impact of different intervention measures on the risk of cardiovascular disease is evaluated, providing a basis for formulating effective air pollution intervention measures; compared with traditional randomized controlled trials, this technical solution provides a simpler and more economical method to evaluate the effect of air pollution exposure intervention, reducing the consumption of manpower and financial resources. At the same time, this application focuses on the vulnerable population of cardiovascular disease, and can more accurately evaluate the intervention effect in special populations, thereby improving the pertinence and effectiveness of the intervention; the overall scheme provides scientific data support to help policy makers and public health experts formulate more effective air pollution control and cardiovascular disease prevention strategies, and provides new tools and methods for the study of the relationship between cardiovascular disease and air pollution, promoting scientific research in this field, and reducing the incidence and mortality of cardiovascular disease through effective air pollution intervention, and reducing the disease burden of society and individuals.

[0099] After introducing the method of the exemplary embodiment of the present invention, next, refer to Figure 5 An air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease according to an exemplary embodiment of the present invention is introduced.

[0100] The implementation of the air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease can refer to the implementation of the above method, and the repetitions will not be repeated. The terms "module" or "unit" used below can be a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived.

[0101] Based on the same inventive concept, the present invention also proposes an air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease, such as Figure 5 As shown, the system includes:

[0102] The information collection module 510 is used to screen the population of the to-be-assessed cohort, and collect personal information, disease follow-up information, and proposed intervention air pollution exposure concentration of the population of the to-be-assessed cohort;

[0103] The risk assessment module 520 is used to establish cardiovascular disease risk prediction models corresponding to preset time periods based on different gender groups, input the personal information and disease follow-up information of the cohort to be evaluated into the corresponding cardiovascular disease risk prediction model, and obtain the risk of each subject to be evaluated after evaluation; wherein, if the risk of developing disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease; if the risk of developing disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease; if the risk of developing disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and obtain a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease;

[0104] The air pollution exposure intervention evaluation module 530 is used to construct a cardiovascular disease incidence intervention evaluation micro-simulation model based on the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, set different scenarios corresponding to the proposed intervention air pollution exposure concentrations, quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of the high-risk group of cardiovascular disease, and obtain the air pollution exposure intervention evaluation results.

[0105] It should be noted that, although several modules of the air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules described above can be concretized in one module. Conversely, the features and functions of one module described above can be further divided into multiple modules to be concretized.

[0106] Based on the above invention concept, Figure 6 As shown, the present invention also proposes a computer device 600, including a memory 610, a processor 620, and a computer program 630 stored in the memory 610 and executable on the processor 620, wherein the processor 620 implements the aforementioned air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease when executing the computer program 630.

[0107] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the aforementioned air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease.

[0108] Based on the aforementioned inventive concept, the present invention proposes a computer program product, which includes a computer program, and when the computer program is executed by a processor, an air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease is implemented.

[0109] The air pollution exposure intervention evaluation method and system for people at high risk of cardiovascular disease proposed in the present invention screens a cohort of people to be evaluated, collects personal information, disease follow-up information and proposed air pollution exposure concentration of the cohort of people to be evaluated; establishes cardiovascular disease risk prediction models corresponding to preset time periods based on different gender groups, inputs the personal information and disease follow-up information of the cohort of people to be evaluated into the corresponding cardiovascular disease risk prediction models, and obtains the risk of each object to be evaluated after evaluation; wherein, if the risk of disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease, if the risk of disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease, and if the risk of disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and obtains the high-risk group, medium-risk group and low-risk group for cardiovascular disease. group and low-risk group; according to the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation is constructed, and different scenarios corresponding to the proposed intervention air pollution exposure concentrations are set to quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of people at high risk of cardiovascular disease, and obtain the air pollution exposure intervention evaluation results. The overall solution innovatively connects the cardiovascular disease risk prediction model with the micro-simulation model considering competing risks in series, first identifies the high-risk group of cardiovascular disease, and further uses algorithms to quantitatively evaluate the health benefits of the high-risk group of cardiovascular disease after reducing air pollution exposure, realizes the air pollution exposure intervention evaluation of people at high risk of cardiovascular disease, improves the processing efficiency of intervention evaluation, improves the intervention effect, and provides strong technical support for environmental science.

[0110] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of laws and regulations.

[0111] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] The present invention is described with reference to flowcharts and / or block diagrams of methods and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0113] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0115] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for evaluating air pollution exposure intervention for people at high risk of cardiovascular disease, characterized in that: The method includes: Screening the cohort population to be evaluated, collecting personal information, disease follow-up information, and proposed intervention air pollution exposure concentration of the cohort population to be evaluated; Based on different gender groups, cardiovascular disease risk prediction models corresponding to preset time periods are established respectively, and the personal information and disease follow-up information of the cohort population to be evaluated are input into the corresponding cardiovascular disease risk prediction model, and the risk of each subject to be evaluated is obtained through evaluation; wherein, if the risk of developing disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease, if the risk of developing disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease, and if the risk of developing disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease are obtained; According to the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation was constructed, and different scenarios corresponding to the proposed intervention air pollution exposure concentrations were set. The impact of different scenarios on the cardiovascular disease risk of the high-risk group of cardiovascular disease was quantitatively evaluated to obtain the air pollution exposure intervention evaluation results.

2. The air pollution exposure intervention evaluation method for high-risk populations of cardiovascular disease according to claim 1, characterized in that: Screen the cohort population to be evaluated, collect their personal information, disease follow-up information, and proposed intervention air pollution exposure concentration, including: The cohort population to be evaluated at least includes people without the disease and people with cardiovascular disease; The personal information of the cohort population to be evaluated includes at least age, gender, income level, urban or rural residence, height, weight, blood pressure, heart rate, waist circumference, smoking history, family history of cardiovascular disease, history of atrial fibrillation, history of diabetes, blood sugar, and blood lipids; the disease follow-up information includes at least the incidence of cardiovascular disease during the preset follow-up period, and the incidence of cardiovascular disease includes at least the time of diagnosis and the type of disease; The proposed intervention air pollution exposure concentrations include at least the exposure concentrations of PM2.5 and O3.

3. The air pollution exposure intervention evaluation method for high-risk populations of cardiovascular disease according to claim 1, characterized in that: Based on different gender groups, a cardiovascular disease risk prediction model corresponding to a preset time period is established, and the personal information and disease follow-up information of the cohort to be evaluated are input into the corresponding cardiovascular disease risk prediction model. After evaluation, the risk of each subject to be evaluated is obtained, including: A proportional regression risk model was used to establish cardiovascular disease risk prediction models corresponding to preset durations in different gender groups. Variables whose discriminant improvement index was greater than the preset index and variables whose observed statistical probability was less than the set probability value when the null hypothesis was true were included in the cardiovascular disease risk prediction model, and the goodness of fit test and C statistic were used to evaluate the predictive ability of the model. The cardiovascular disease risk prediction model is adopted, and the personal information and disease follow-up information of the cohort population to be evaluated are input into the model, and the cardiovascular disease risk of each object to be evaluated within a preset period of time is evaluated, and the objects to be evaluated whose assessed risk of occurrence is greater than or equal to 10.0% are divided into a high-risk group for cardiovascular disease, the objects to be evaluated whose assessed risk of occurrence is greater than or equal to 5.0% and less than 10% are divided into a medium-risk group for cardiovascular disease, and the objects to be evaluated whose risk of occurrence is less than 5% are divided into a low-risk group for cardiovascular disease, thereby obtaining a high-risk group, a medium-risk group and a low-risk group for cardiovascular disease.

4. The air pollution exposure intervention evaluation method for a high-risk population for cardiovascular disease according to any one of claims 1 to 3, characterized in that: The preset period is 5 years or 10 years.

5. The air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease according to claim 3, characterized in that: According to the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, a micro-simulation model for cardiovascular disease incidence intervention evaluation is constructed, and different scenarios corresponding to the proposed intervention air pollution exposure concentrations are set to quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of the high-risk group of cardiovascular disease. The air pollution exposure intervention evaluation results are obtained, including: The cardiovascular disease incidence intervention evaluation micro-simulation model is used to simulate the disease development process of the cohort population to be evaluated, wherein the disease development states contained in the micro-simulation model at least include not suffering from cardiovascular disease, suffering from cardiovascular disease, dying from cardiovascular disease and dying from other causes of disease, and the conversion probabilities between disease development states include: a first state conversion probability of not suffering from cardiovascular disease to suffering from cardiovascular disease, a second state conversion probability of not suffering from cardiovascular disease to dying from cardiovascular disease, a third state conversion probability of not suffering from cardiovascular disease to dying from other causes of disease, a fourth conversion probability of suffering from cardiovascular disease to suffering from cardiovascular disease, a fifth conversion probability of suffering from cardiovascular disease to dying from cardiovascular disease, a sixth conversion probability of suffering from cardiovascular disease to dying from other causes of disease, and a seventh conversion probability of suffering from cardiovascular disease to suffering from cardiovascular disease.

6. The air pollution exposure intervention evaluation method for people at high risk of cardiovascular disease according to claim 5, characterized in that: The method includes: The cardiovascular disease risk prediction model is used to predict the first state transition probability of the high-risk group, the medium-risk group and the low-risk group of cardiovascular disease under the first air pollution exposure concentration, respectively, and the second state transition probability to the seventh state transition probability are combined to determine the incidence of cardiovascular disease under the first air pollution exposure concentration as the control group sample; Set up scenarios for decreasing air pollution exposure concentrations; The incidence of cardiovascular disease was simulated in the scenario of decreasing air pollution exposure concentration, and the first state transition probability corresponding to the high-risk group, medium-risk group and low-risk group of cardiovascular disease in different scenarios was determined. The calculation formula is: Among them, P1' is the risk probability of cardiovascular disease for each subject to be evaluated after the simulated air pollution exposure concentration decreases, indicating the first state transition probability under different scenarios; P1 is the risk probability of cardiovascular disease for each subject to be evaluated at the first air pollution exposure concentration, indicating the first state transition probability at the first air pollution exposure concentration; X is the decreased concentration corresponding to the scenario of decreased air pollution exposure concentration; HR is the risk of cardiovascular disease for each increase in the set concentration of air pollution exposure concentration obtained by querying the data; According to the first state transition probabilities corresponding to different scenarios, combined with the second state transition probabilities to the seventh state transition probabilities, the cardiovascular disease incidence intervention evaluation micro-simulation model is used to simulate the incidence of cardiovascular diseases after the air pollution exposure concentration is reduced, as the experimental group samples; Based on the control group samples and the experimental group samples, the number of cardiovascular disease cases prevented in the high-risk group, medium-risk group and low-risk group for cardiovascular disease after reducing the air pollution exposure concentration, and the number of people required to intervene for each case of cardiovascular disease prevented were determined. By comparing the differences in health benefits among the high-risk group, medium-risk group and low-risk group for cardiovascular disease after reducing the air pollution exposure concentration, the protective effect of reducing the air pollution exposure concentration on the incidence of cardiovascular disease in the high-risk group for cardiovascular disease was quantitatively evaluated, and the air pollution exposure intervention evaluation results were obtained.

7. An air pollution exposure intervention evaluation system for people at high risk of cardiovascular disease, characterized in that: The system includes: An information collection module is used to screen the population of the cohort to be evaluated, and collect personal information, disease follow-up information, and proposed intervention air pollution exposure concentration of the population of the cohort to be evaluated; The risk assessment module is used to establish cardiovascular disease risk prediction models corresponding to preset time periods based on different gender groups, input the personal information and disease follow-up information of the cohort to be evaluated into the corresponding cardiovascular disease risk prediction model, and obtain the risk of each subject to be evaluated after evaluation; wherein, if the risk of developing disease is within the first numerical range, it is classified as a high-risk group for cardiovascular disease; if the risk of developing disease is within the second numerical range, it is classified as a medium-risk group for cardiovascular disease; if the risk of developing disease is within the third numerical range, it is classified as a low-risk group for cardiovascular disease, and a high-risk group, a medium-risk group, and a low-risk group for cardiovascular disease are obtained; The air pollution exposure intervention evaluation module is used to construct a micro-simulation model for cardiovascular disease incidence intervention evaluation based on the cardiovascular disease incidence information of the high-risk group, medium-risk group and low-risk group of cardiovascular disease, set different scenarios corresponding to the proposed intervention air pollution exposure concentrations, quantitatively evaluate the impact of different scenarios on the cardiovascular disease risk of the high-risk group of cardiovascular disease, and obtain the air pollution exposure intervention evaluation results.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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