Method and system for determining optimal control concentration threshold value of atmospheric pollution based on resident health effect

Abstract

The embodiment of the invention provides a method and system for determining an optimal control concentration threshold value of atmospheric pollution based on a resident health effect, and belongs to the technical field of environmental health early warning. The method comprises the steps of firstly obtaining baseline information of a research object; collecting health and disease data and atmospheric pollution exposure data according to the baseline information; matching and integrating the baseline information, the health and disease data and the atmospheric pollution exposure data to obtain a research and analysis database; analyzing according to the research analysis database to obtain feedback data under different assumed air quality standards; and obtaining the optimal control concentration threshold value of the atmospheric pollution according to the feedback data. Technical support can be provided for formulating air quality standards and public health policies.

Description

Technical Field

[0001] The present application relates to the field of environmental health early warning technology, and in particular to a method and system for determining an optimal control concentration threshold of air pollution based on residents' health effects. Background Art

[0002] Current research evidence suggests that most air pollutants exhibit a nearly linear dose-response relationship with adverse health outcomes; that is, no specific concentration threshold exists, making it difficult to establish appropriate concentration standards based on this relationship. Furthermore, existing systems lack data quality, timeliness, multi-pollutant synergistic effects, assessment of long-term health impacts, and regional variations, limiting the accuracy and applicability of early warning systems. Their high cost and complexity also restrict their widespread application in resource-limited settings. These deficiencies undermine the effectiveness of early warning systems and their effectiveness in protecting public health. Summary of the Invention

[0003] The main purpose of the embodiments of the present application is to provide a method and system for determining the optimal control concentration threshold of air pollution based on the health effects of residents.

[0004] The technical solution adopted by the present invention is:

[0005] In one aspect, an embodiment of the present invention provides a method for determining an optimal control concentration threshold for air pollution based on resident health effects. The method for determining an optimal control concentration threshold for air pollution based on resident health effects includes the following steps:

[0006] Obtain baseline information of research subjects;

[0007] Based on the baseline information, collect health and disease data and air pollution exposure data;

[0008] Matching and integrating the baseline information, the health and disease data, and the air pollution exposure data to obtain a research and analysis database;

[0009] Analyze the research and analysis database to obtain feedback data under different assumed air quality standards;

[0010] According to the feedback data, the optimal control concentration threshold of air pollution is obtained.

[0011] Furthermore, obtaining baseline information of the research subjects includes the following steps:

[0012] Identify the research subjects;

[0013] According to the research subject, obtaining the baseline information of the research subject through anonymization processing;

[0014] The baseline information includes lifestyle information, physical condition information, and residential address information.

[0015] Furthermore, the collecting of health and disease data and air pollution exposure data based on the baseline information includes the following steps:

[0016] Analyze lifestyle information and physical condition information based on the baseline information, and simultaneously obtain health and disease data; the health and disease data include: death, chronic non-communicable diseases;

[0017] Based on the baseline information, the residential address information is analyzed and combined with the air pollution monitoring data to evaluate the long-term air pollutant exposure concentrations of the research subjects to obtain the air pollution exposure data.

[0018] Furthermore, matching and integrating the baseline information, the health and disease data, and the air pollution exposure data to obtain a research and analysis database includes the following steps:

[0019] Removing abnormal and missing data from the baseline information, the health and disease data, and the air pollution exposure data, unifying the data format and data measurement units, and completing data cleaning;

[0020] The cleaned baseline information, health and disease data, and air pollution exposure data of each research subject are matched and integrated to obtain a research analysis database.

[0021] Furthermore, the analysis is performed based on the research and analysis database to obtain feedback data under different assumed air quality standards, including the following steps:

[0022] The analysis was conducted based on the research analysis database, and the Cox proportional hazards regression model was nested using a distributed lag nonlinear model to calculate the hazard ratio of long-term air pollution exposure to health outcomes;

[0023] Based on the risk ratios, the absolute risk reduction was calculated;

[0024] Based on the absolute risk reduction values, combined with baseline mortality and population size, the number of deaths reduced under different assumed air quality standards was calculated;

[0025] The number of deaths reduced is used as feedback data.

[0026] Furthermore, the research analysis database was analyzed and a distributed lag nonlinear model was used to nest the Cox proportional hazard regression model to calculate the hazard ratio of long-term air pollution exposure to health outcomes. The formula used included:

[0027]

[0028]

[0029] Among them, h0(t) is the baseline risk function, t is the time node, L is the maximum lag time, f(x t-l ,l) is the cross basis function, β l is the risk coefficient corresponding to the lag time l, HR is the risk ratio of long-term air pollution exposure to health outcomes; f(x 1,t-l ,l) is the cumulative cross-base value of exposure level x1 at the lag time, f(x 0,t-l ,l) is the cumulative cross-base value of the reference level x0 at the lag time.

[0030] Furthermore, the absolute risk reduction value is calculated based on the risk ratio, and the formula used includes:

[0031]

[0032] Where ARR is the absolute risk reduction; λ0 is the baseline mortality rate; and Δc is the change in pollutant concentration per unit.

[0033] Furthermore, the absolute risk reduction value is combined with the baseline mortality rate and population size to calculate the number of deaths reduced under different assumed air quality standards. The formula used includes:

[0034]

[0035] Where N is the population size under the current air quality standard, and t' is the time frame.

[0036] On the other hand, an embodiment of the present invention further provides a system for determining an optimal control concentration threshold of air pollution based on resident health effects, which is used to implement the method for determining an optimal control concentration threshold of air pollution based on resident health effects as described above. The system for determining an optimal control concentration threshold of air pollution based on resident health effects includes:

[0037] The data collection module is used to collect baseline information of the research subjects and, through a cohort study design, to collect health and disease data of the research subjects during the follow-up period;

[0038] Data processing module, used to perform data cleaning, matching, and integration, and to establish a research and analysis database;

[0039] The data analysis and feedback module is used to evaluate the chronic health effects of long-term exposure to air pollutants on the population and to analyze and calculate the optimal control concentration threshold for air pollution.

[0040] On the other hand, an embodiment of the present invention also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method for determining the optimal control concentration threshold of air pollution based on the health effects of residents as described above.

[0041] The embodiments of this application include at least the following beneficial effects: This application provides a method and system for determining the optimal control concentration threshold for air pollution based on resident health effects. The present invention can obtain baseline information on research subjects; based on this baseline information, collect health and disease data and air pollution exposure data; match and integrate the baseline information, health and disease data, and air pollution exposure data to generate a research and analysis database; analyze the research and analysis database to obtain feedback data under different assumed air quality standards; and, based on this feedback data, determine the optimal control concentration threshold for air pollution. This invention can provide technical support for the formulation of air quality standards and public health policies. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is a schematic diagram of a method for determining an optimal control concentration threshold of air pollution based on residents' health effects provided by an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of the process modules of a system for determining the optimal control concentration threshold of air pollution based on residents' health effects provided by an embodiment of the present invention;

[0044] Figure 3 This is a schematic diagram showing the number of resident deaths that can be reduced by reducing the concentration by one unit under different potential concentration standards provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0046] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0047] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0049] Before explaining the embodiments of the present application in detail, some of the nouns and terms involved in the embodiments of the present application are first explained. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0050] 1) Cox proportional hazards regression model, a survival analysis model used to analyze the relationship between event time and predictor variables;

[0051] 2) hazard ratio (HR), a relative risk index used to measure the ratio of the hazard functions of two groups of individuals;

[0052] 3) Absolute risk reduction (ARR), which is an indicator used to measure the absolute difference in the probability of an event occurring between two groups of individuals, reflecting the actual effect of the intervention;

[0053] 4) Distributed lag nonlinear model (DLNM), a statistical model used to analyze nonlinear effects and time lag effects in exposure-response relationships.

[0054] Before describing the method and system of the present invention for determining the optimal control concentration threshold of air pollution based on the health effects of residents, it is necessary to clearly state that this application follows the principle of privacy protection when processing data. In particular, all data of the research subjects involved in the present invention, including but not limited to baseline information or health and disease data collected through cohort study design, such as gender, age, smoking, drinking, body mass index, physical activity, hypertension, coronary heart disease, stroke, etc., are strictly obtained and used with the explicit authorization and consent of the research subjects.

[0055] The present invention makes full use of population health data and environmental data to calculate the number of residents' deaths that can be reduced by each unit reduction in concentration under different assumed concentration standards, and compares the number of residents' deaths that can be reduced by each unit reduction in concentration under several assumed concentration standards. Taking into account cost and feasibility, the largest value is the recommended standard; the present invention provides technical support for the formulation of air quality standards and public health policies.

[0056] The embodiments of the present invention are further described below with reference to the accompanying drawings.

[0057] On the one hand, the embodiment of the present invention provides a method for determining the optimal control concentration threshold of air pollution based on the health effect of residents, referring to Figure 1 The method for determining the optimal control concentration threshold of air pollution based on residents' health effects includes the following steps:

[0058] S100, obtain baseline information of research subjects;

[0059] S200. Based on baseline information, collect health and disease data and air pollution exposure data;

[0060] S300, match and integrate baseline information, health and disease data, and air pollution exposure data to obtain a research and analysis database;

[0061] S400, analyzing according to the research and analysis database to obtain feedback data under different assumed air quality standards;

[0062] S500: Obtaining an optimal control concentration threshold for air pollution based on feedback data.

[0063] S100 disclosed in the embodiment of the present invention obtains baseline information of the research subject, including the following steps:

[0064] S110, determine the research subjects;

[0065] S120, obtaining baseline information of the research subject through anonymization processing according to the research subject;

[0066] S130. Baseline information includes lifestyle information, physical condition information, and residential address information.

[0067] S200 disclosed in the embodiment of the present invention collects health and disease data and air pollution exposure data based on baseline information, including the following steps:

[0068] S210. Based on the baseline information, analyze the lifestyle information and physical condition information, and obtain health and disease data; health and disease data include: death, chronic non-communicable diseases;

[0069] S220. Based on the baseline information, the residential address information is analyzed and combined with the air pollution monitoring data to evaluate the long-term air pollutant exposure concentration of the research subjects to obtain air pollution exposure data.

[0070] As an optional implementation method, the embodiment of the present invention adopts a cohort study design and selects a representative population as the research subjects. The inclusion criteria of the research subjects are clarified, such as age range, residential area, health status, etc. Research subjects that do not meet the conditions are excluded, such as individuals who have serious diseases or missing data at baseline. The data sources of this embodiment are: baseline information, health and disease data of the research subjects are obtained through face-to-face interviews, telephone interviews or online questionnaires, including demographic information, such as gender, age, residential address information (for matching air pollution exposure data); lifestyle information, such as smoking status (such as whether smoking, smoking amount, smoking years), drinking status (such as whether drinking, drinking frequency, drinking amount), physical activity level (such as exercise frequency, exercise type); physical condition information, such as body mass index (BMI), past medical history (such as diabetes, hypertension, coronary heart disease, stroke, etc.).

[0071] S300 disclosed in the embodiment of the present invention matches and integrates baseline information, health and disease data, and air pollution exposure data to obtain a research and analysis database, including the following steps:

[0072] S310. Remove abnormal and missing data from baseline information, health and disease data, and air pollution exposure data, unify data formats and data measurement units, and complete data cleaning;

[0073] S320. Match and integrate the cleaned baseline information, health and disease data, and air pollution exposure data of each research subject to obtain a research analysis database.

[0074] As an optional implementation, the present invention standardizes data formats and units of measurement (e.g., age is standardized as years in years, and smoking volume is standardized as "packs per year"), checks data integrity and consistency, excludes outliers (e.g., age outside a reasonable range), and fills in or excludes missing data to ensure data quality. The personal information of the research subjects is anonymized to ensure data security. The acquired baseline information is matched and integrated with health outcome data and air pollution exposure data to form a structured research and analysis database to facilitate subsequent data analysis and modeling.

[0075] S400 disclosed in the embodiment of the present invention performs analysis based on the research and analysis database to obtain feedback data under different assumed air quality standards, including the following steps:

[0076] S410. Analyze the research analysis database and use the distributed lag nonlinear model nested in the Cox proportional hazards regression model to calculate the hazard ratio of long-term air pollution exposure to health outcomes;

[0077] S420. Calculate the absolute risk reduction value based on the risk ratio;

[0078] S430. Based on the absolute risk reduction, combined with baseline mortality and population size, calculate the number of deaths reduced under different assumed air quality standards;

[0079] S440. Use the number of deaths reduced as feedback data.

[0080] As an optional implementation, the present invention uses other health outcome data as feedback, such as disease incidence, hospitalization rate, medical expenses, etc., to reflect the impact of air pollution on health. The following are the relevant method steps:

[0081] The Cox proportional hazards regression model was used to analyze the relationship between long-term air pollution exposure and various health outcomes (such as respiratory diseases, cardiovascular and cerebrovascular diseases, and hospitalization events).

[0082] Based on the hazard ratio (HR) and baseline health outcome incidence, the absolute risk reduction values ​​under different assumed air quality standards were calculated;

[0083] Based on the absolute risk reduction (ARR), combined with the baseline incidence of health outcomes and population size, the health benefits (such as the reduction in the number of respiratory diseases and hospitalizations) under different assumed air quality standards were calculated;

[0084] The calculated health benefit data are used as feedback data to evaluate the health benefits of different assumed air quality standards, such as the reduction in the number of respiratory diseases (such as asthma and chronic obstructive pulmonary disease), the reduction in the number of cardiovascular and cerebrovascular diseases (such as myocardial infarction and stroke), the reduction in the number of hospitalizations (reflecting the impact of air pollution on the burden of medical resources), and the reduction in medical expenses (estimated reduction in medical expenses based on the reduction in the number of diseases and hospitalizations).

[0085] S410 disclosed in the embodiment of the present invention performs analysis based on the research and analysis database, and uses a distributed lag nonlinear model nested in a Cox proportional hazards regression model to calculate the hazard ratio of long-term air pollution exposure to health outcomes. The formula used includes:

[0086]

[0087]

[0088] Among them, h0(t) is the baseline risk function, t is the time node, L is the maximum lag time, f(xt-l ,l) is the cross basis function, β l is the risk coefficient corresponding to the lag time l, HR is the risk ratio of long-term air pollution exposure to health outcomes; f(x 1,t-l ,l) is the cumulative cross-base value of exposure level x1 at the lag time, f(x 0,t-l ,l) is the cumulative cross-base value of the reference level x0 at the lag time.

[0089] S420 disclosed in the embodiment of the present invention calculates the absolute risk reduction value based on the risk ratio, and the formula used includes:

[0090]

[0091] Where ARR is the absolute risk reduction; λ0 is the baseline mortality rate; and Δc is the change in pollutant concentration per unit.

[0092] S430 disclosed in the embodiment of the present invention calculates the number of deaths reduced under different assumed air quality standards based on the absolute risk reduction value, combined with the baseline mortality rate and population size. The formula used includes:

[0093]

[0094] Where N is the population size under the current air quality standard, and t' is the time frame.

[0095] On the other hand, an embodiment of the present invention further provides a system for determining an optimal control concentration threshold of air pollution based on resident health effects, which is used to implement the method for determining an optimal control concentration threshold of air pollution based on resident health effects as described above. The system for determining an optimal control concentration threshold of air pollution based on resident health effects includes:

[0096] The data collection module is used to collect baseline information of the research subjects and, through a cohort study design, to collect health and disease data of the research subjects during the follow-up period;

[0097] Data processing module, used to perform data cleaning, matching, and integration, and to establish a research and analysis database;

[0098] The data analysis and feedback module is used to evaluate the chronic health effects of long-term exposure to air pollutants on the population and to analyze and calculate the optimal control concentration threshold for air pollution.

[0099] As an optional implementation, this embodiment utilizes a cohort study design. The data collection module first collects baseline information on study subjects. Based on their residential addresses, each subject's average annual exposure to air pollution is assessed. Follow-up visits record the subjects' health and disease information. The data analysis and feedback module assesses the chronic health effects of long-term exposure to air pollution. Furthermore, based on different assumed concentration thresholds, the number of deaths that could be avoided for each unit reduction in air pollution concentration is calculated. The highest of these values ​​is then compared to determine the optimal control concentration threshold for air pollution.

[0100] As an optional implementation, refer to Figure 2 , the embodiment of the present invention provides a data collection module, a data processing module and a data analysis and feedback module;

[0101] In the data collection module, baseline information data of the research subjects are collected, and through the cohort study design, health and disease data of the research subjects during the follow-up period are collected;

[0102] The residential address information of the study subjects in the baseline information was used to evaluate the long-term air pollutant exposure data of each study subject and calculate the annual average air pollution exposure concentration;

[0103] The data processing module cleans, matches and integrates the collected data to establish a research and analysis database.

[0104] The data analysis and feedback module evaluates the chronic health effects of long-term exposure to air pollutants on the population and analyzes and calculates the optimal control concentration threshold for air pollution.

[0105] Optionally, the baseline information data of the research subjects include: gender, age, smoking, drinking, body mass index, and physical activity;

[0106] Health and disease data include: death, diabetes, hypertension, coronary heart disease, stroke, etc.;

[0107] Air pollution exposure data include: atmospheric fine particulate matter PM 2.5 .

[0108] Optionally, clean the data in the data collection module to remove abnormal and missing data, and unify the data format and data measurement units;

[0109] The data from the data collection module are matched and integrated, and the baseline information data, health and disease data, and air pollution exposure data of each research subject are matched and integrated to form a structured research analysis database for data analysis.

[0110] Optionally, a data analysis and feedback module is used to assess the chronic health effects of long-term exposure to air pollution on the population:

[0111] The hazard ratios (HRs) and 95% confidence intervals (CIs) of long-term air pollution exposure for health outcomes were calculated using a distributed lag nonlinear model (DLNM) nested in a Cox proportional hazard regression model. The hazard ratios (HRs) at different concentrations were calculated as follows:

[0112]

[0113] Among them, h0(t) is the baseline risk function, t is the time node, L is the maximum lag time, f(x t-l ,l) is the cross basis function, β l is the coefficient corresponding to the lag time l.

[0114]

[0115] Where L is the maximum lag time, f(x 1,t-l ,l) is the cumulative cross-base value of exposure level x1 at the lag time, f(x 0,t-l ,l) is the cumulative cross-base value of the reference level x0 at the lag time.

[0116] Optionally, the data analysis and feedback module includes calculating the absolute risk reduction (ARR) using the obtained formula:

[0117]

[0118] Where λ0 is the baseline mortality rate, β l is the risk coefficient lagged by one day, and Δc is the change in the concentration of the pollutant per unit.

[0119] Optionally, the data analysis and feedback module includes further calculating the number of deaths reduced using the obtained formula:

[0120]

[0121] Where λ0 is the baseline mortality rate under a specific air quality standard, N is the population size under the current air quality standard, t' is the time horizon, and β l is the risk coefficient lagged by one day, and Δc is the change in the concentration of the pollutant per unit.

[0122] Optionally, the data analysis and feedback module includes using the obtained formula to set the Δc concentration change to 1, and the number of deaths reduced can be obtained as follows:

[0123]

[0124] Where λ0 is the baseline mortality rate under a specific air quality standard, N is the population size under the current air quality standard, t' is the time horizon, and βl is the risk coefficient lagged by 1 day.

[0125] Optionally, the data analysis and feedback module uses the obtained formula to calculate the number of resident deaths that can be reduced for each unit concentration reduction under different assumed air quality standards, and compares the values ​​to determine the largest atmospheric pollutant concentration threshold, which is the most practical air quality standard.

[0126] As an optional implementation, the embodiment of the present invention starts from the data collection module to collect health information of residents in Hebei Province, Hunan Province, Zhejiang Province, Jiangxi Province, and Gansu Province, and simultaneously evaluates long-term exposure to atmospheric pollution concentrations to obtain the annual average PM 2.5 concentration; the data processing module is further used to clean, match, and integrate the collected data to establish the data set used in this embodiment; the baseline information data of the research subjects in this embodiment include: gender, age; the health outcome specifically refers to death; the air pollution specifically refers to the annual average PM 2.5 In the data analysis and feedback module of this embodiment, the death data of each province and specific PM 2.5 The proportion of the population exposed to the concentration is combined with the obtained HR value to calculate the number of residents who can be reduced by reducing the concentration by one unit.

[0127] At present, the PM2.5 specified in the ambient air quality standards implemented in my country 2.5 The secondary concentration limit is 35 μg / m 3 Based on this, this embodiment assumes that PM 2.5 The secondary concentration standards were reduced by 1 μg / m 3 , that is, from 35μg / m 3 Up to 20 μg / m 3 15 concentrations were set. Further, the long-term PM 2.5 The impact of exposure on the risk of death in the population was calculated by calculating the HR values ​​corresponding to the assumed standard concentrations. The number of deaths of residents that could be reduced by reducing the concentration by one unit was further calculated under different standard concentrations. The results are as follows: Figure 3 shown.

[0128] As an optional implementation, Figure 3 As shown, the embodiment of the present invention compares the number of residents' deaths that can be reduced by reducing the concentration by one unit under different assumed standard concentrations, and determines the standard concentration corresponding to the maximum value as the PM2.5 standard concentration of the province. 2.5 Long-term exposure concentration threshold. In some embodiments, the maximum number of deaths that can be reduced by reducing the concentration by one unit in different provinces is 25 μg / m 3 or 26 μg / m 3 Among them, Gansu, Hebei, and Zhejiang were at 26 μg / m 3The maximum value that can be avoided is 25μg / m in Hunan and Jiangxi. 3 The maximum value can be avoided when the number of people is high. Taking into account the situation in different provinces, this example determines 26μg / m 3 is the long-term exposure concentration threshold.

[0129] This invention leverages public health information and air pollution data, taking into account cost and feasibility, to accurately determine the potential concentration thresholds of air pollutants. This method involves calculating the number of deaths that can be avoided for each unit reduction in concentration under different hypothetical concentration standards, comparing the number of deaths averted under several hypothetical concentration standards, and then selecting the highest value that achieves the best health benefits, taking into account cost and feasibility, as the recommended standard. This invention provides technical support for the formulation of air quality standards and public health policies.

[0130] On the other hand, an embodiment of the present invention also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method of determining the optimal control concentration threshold of air pollution based on the health effects of residents as mentioned above.

[0131] Those skilled in the art will appreciate that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). As known to those skilled in the art, the term computer storage media is included in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data) and is volatile and non-volatile, removable, and non-removable. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0132] On the other hand, an embodiment of the present invention also provides a device for determining the optimal control concentration threshold of air pollution based on the health effect of residents, including a memory, a processor, and a computer program stored on the memory and runnable on the processor. When the processor executes the computer program, it implements the method for determining the optimal control concentration threshold of air pollution based on the health effect of residents as described above.

[0133] The processor and the memory can be connected via a bus or other means. The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0134] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A method for determining the optimal control concentration threshold of air pollution based on residents' health effects, characterized in that: The method for determining the optimal control concentration threshold of air pollution based on residents' health effects includes the following steps: Obtain baseline information of research subjects; Based on the baseline information, collect health and disease data and air pollution exposure data; Matching and integrating the baseline information, the health and disease data, and the air pollution exposure data to obtain a research and analysis database; Analyze the research and analysis database to obtain feedback data under different assumed air quality standards; According to the feedback data, the optimal control concentration threshold of air pollution is obtained.

2. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 1, characterized in that: The method of obtaining baseline information of the research subjects includes the following steps: Identify the research subjects; According to the research subject, obtaining the baseline information of the research subject through anonymization processing; The baseline information includes lifestyle information, physical condition information, and residential address information.

3. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 1, characterized in that: The collecting of health and disease data and air pollution exposure data based on the baseline information includes the following steps: Analyze lifestyle information and physical condition information based on the baseline information, and simultaneously obtain health and disease data; the health and disease data include: death, chronic non-communicable diseases; Based on the baseline information, the residential address information is analyzed and combined with the air pollution monitoring data to evaluate the long-term air pollutant exposure concentrations of the research subjects to obtain the air pollution exposure data.

4. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 1, characterized in that: The matching and integration of the baseline information, the health and disease data, and the air pollution exposure data to obtain a research and analysis database includes the following steps: Removing abnormal and missing data from the baseline information, the health and disease data, and the air pollution exposure data, unifying the data format and data measurement units, and completing data cleaning; The cleaned baseline information, health and disease data, and air pollution exposure data of each research subject are matched and integrated to obtain a research analysis database.

5. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 1, characterized in that: The analysis based on the research and analysis database to obtain feedback data under different assumed air quality standards includes the following steps: The analysis was conducted based on the research analysis database, and the Cox proportional hazards regression model was nested using a distributed lag nonlinear model to calculate the hazard ratio of long-term air pollution exposure to health outcomes; Based on the risk ratios, the absolute risk reduction was calculated; Based on the absolute risk reduction values, combined with baseline mortality and population size, the number of deaths reduced under different assumed air quality standards was calculated; The number of deaths reduced is used as feedback data.

6. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 5, characterized in that: The research analysis database was analyzed and the Cox proportional hazard regression model was nested using a distributed lag nonlinear model to calculate the risk ratio of long-term air pollution exposure to health outcomes. The formula used included: Among them, h0(t) is the baseline risk function, t is the time node, L is the maximum lag time, f(x t-l ,l) is the cross basis function, β l is the risk coefficient corresponding to the lag time l, HR is the risk ratio of long-term air pollution exposure to health outcomes; f(x 1,t-l ,l) is the cumulative cross-base value of exposure level x1 at the lag time, f(x 0,t-l ,l) is the cumulative cross-base value of the reference level x0 at the lag time.

7. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 5, characterized in that: The absolute risk reduction value is calculated based on the risk ratio, and the formula used includes: Where ARR is the absolute risk reduction; λ0 is the baseline mortality rate; and Δc is the change in pollutant concentration per unit.

8. The method for determining the optimal control concentration threshold of air pollution based on residents' health effects according to claim 5, characterized in that: The formula used to calculate the number of deaths reduced under different assumed air quality standards based on the absolute risk reduction value, combined with the baseline mortality rate and population size includes: Where N is the population size under the current air quality standard, and t' is the time frame.

9. A system for determining the optimal control concentration threshold of air pollution based on the health effect of residents, for implementing the method for determining the optimal control concentration threshold of air pollution based on the health effect of residents as claimed in any one of claims 1 to 8, characterized in that: The system for determining the optimal control concentration threshold of air pollution based on residents' health effects includes: The data collection module is used to collect baseline information of the research subjects and, through a cohort study design, to collect health and disease data of the research subjects during the follow-up period; Data processing module, used to perform data cleaning, matching, and integration, and to establish a research and analysis database; The data analysis and feedback module is used to evaluate the chronic health effects of long-term exposure to air pollutants on the population and to analyze and calculate the optimal control concentration threshold for air pollution.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to enable a computer to execute the method for determining the optimal control concentration threshold of air pollution based on residents' health effects as described in any one of claims 1 to 8.

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