An Empirical Study on Physical Subhealth Risk Perception: A Physical Examination Data of Tertiary Grade-A Hospitals in Anhui Province, China

Background Physical subhealth directly correlates to people's work effectiveness and quality of life, so subhealth prevention has become an urgent medical problem. Methods A random sampling method was used to conduct a questionnaire survey of physical examinees from June to September, 2019. In total, 770 people participated in our study. The Pearson correlation and multiple stepwise regression analysis were used to explore the relationship among demographic variables, physical subhealth, and risk perception. Also, this study used a two-way interaction moderated multiple regression approach to examine the moderating effects of demographic variables on physical subhealth and risk perception. Results The risk perception level was negatively associated with physical health. Age, education level, and subhealth proportion in the work unit all significantly and positively influence physical health, whereas living place, subhealth duration, and marital status negatively influence physical health. Living place, average annual household income, number of employees in the work unit, and subhealth proportion in the work unit significantly and positively influence the risk perception, and only age negatively influences the risk perception. The number of children had a moderating effect on physical subhealth and risk perception (Interaction coefficient α = −0.3, P < 0.05). Conclusions To achieve the overall improvement of public health, relevant management departments can provide targeted interventions for the public with different levels of risk perception. Also, the physical subhealth of the public can be addressed by encouraging the public to attach importance to education, improving the public living environment to build a livable city, strengthening psychological guidance and intervention for couples heading toward divorce to reduce the divorce rate, focusing on the health of work unit employees and regularly organizing employees to attend medical checkups, and actively responding to the national policy of family planning.


Introduction
In 2006, the Clinical Guidelines of Chinese Medicine on subhealth, issued by the China Association of Chinese Medicine [1], pointed out that subhealth refers to a state of human body between unhealthy and healthy. A subhealthy person shows symptoms of decreased vitality, function, and adaptability within a certain period but does not meet the clinical or subclinical diagnostic criteria of modern medicine's defned diseases. Tis condition is also known as a "grey state" or "third state." Subhealth includes symptoms such as physical fatigue, psychological anxiety, depression, and decline of social adaptability, which seriously afect people's quality of life. Te process of body life is the mutual transformation of health, subhealth, and disease. Without timely intervention, subhealth will lead to the occurrence of diseases [2]. A study pointed that only 5% of the global population were in a complete health state, 20% were in a disease state, and the remaining 75% were in subhealth status [3]. Individual physical subhealth is a global public health problem that needs to be solved urgently.

Te Relationship between Physical Subhealth and Risk
Perception. Risk perception, which refects people's cognition and intuitive judgment of risk [4], is studied in the feld of psychology [5]. Risk perception is one of the core elements of health behavior theories; those theories point out that people exposed to risk are motivated to stop unhealthy behaviors and adopt healthy behaviors to avoid negative consequences [6]. For example, the health belief model [7,8] takes susceptibility and severity to disease as pretest factors of whether an individual adopts healthy behaviors, where the cognition of susceptibility to disease and severity is the risk perception. Te protective motivation theory [9,10] explains why health behaviors occur from the perspective of motivation, in which risk perception plays a central role. Te level of risk perception afects the behavioral lifestyle of the public [11], while lifestyle is one of the most important factors infuencing health status. Positive risk perception attitudes of the public play a key role in driving individual adaptive behavior and are a precondition for the public to make healthier lifestyle choices, participate in health screenings, and adhere to health care [12]. People with higher risk perception levels are more likely to resist unhealthy behaviors and adopt healthy lifestyle habits, which helps to increase their level of self-protection against risks and reduce health threats due to various risks [13,14].

Current Study. Domestic and international scholars
have carried out numerous studies on subhealth, but those research eforts mainly focused on the diagnosis [2], infuencing factors [15], and treatment options [16] of subhealth, while there was a relative lack of research on the prevention of subhealth. Many studies exploring risk perception have pointed out that demographic variables are signifcantly related to risk perception and risk reduction behaviors. For example, relevant studies showed that risk behavior decreases with the increase of age [17], the level of risk perception in women was higher than that in men [18], education level was negatively correlated with risk perception level [19], and higher income will reduce the occurrence of risk behavior [20].
Tis study explores the infuencing factors of physical subhealth from a new perspective of risk perception, analyzes the mechanism of action between risk perception and physical subhealth, and discusses the moderating efects of demographic variables and related control variables on physical subhealth and risk perception. Tis work provides a theoretical basis for reducing public subhealth risk and provides a judgment basis for health warnings. Tus, based on the previous research, we propose the following hypothesis.

Study Design and Study
Population. Tis was a crosssectional study performed in four grade-A hospital physical examination centers in Anhui Province to obtain data on physical subhealth and risk perceptions of physical examinees. Te study period was from June to September, 2019. Anhui's economy has been developing rapidly in recent years, and its comprehensive strength has been steadily improved. With the booming economy, the pressure on people in all areas is also increasing, and the public's health status has attracted much attention. Tis study selected examinees at physical examination centers as the research participants and explored the relationship between the public risk perception level and physical subhealth status. Participants were excluded if they did not give verbal consent prior to the start of the questionnaire or refused to cooperate with this study while the questionnaire was in progress. Participants who gave verbal consent to participate in this study before questionnaires were selected, thereby ensuring that participants were voluntarily agreeing to participate in the study. In this study, a total of 785 questionnaires were collected from physical examinees by our random sampling method, and 770 valid questionnaires were obtained after excluding invalid questionnaires, yielding a response rate of 98%.

Ethical Approval and Consent.
Our study was approved by the Ethics Committee of Anhui Medical University (No. 20190463). Human rights and ethics issues were taken into consideration when the survey was designed. To save participants' time, verbal informed consent was obtained from each participant following a detailed explanation about the purpose of the study. For participants under the age of 18, verbal informed consent was obtained from their parents or legal guardians. Participation in the study was voluntary and anonymous, and the participants' information was kept completely confdential. All procedures performed in studies involving human participants were in accordance with the Declaration of Helsinki.

Measures Used.
Te survey was administered by researchers assisted by undergraduate students majoring in health management, master of health management students, professional lecturers, and associate professors. Tis research team was trained before distributing the questionnaires. We collected the data through the following three tools: Te frst two items cover the dimension of health knowledge: "I am more knowledgeable about subhealth than the people around me" and "I regularly browse and read health newsletters, exam-related websites, and subhealth-related brochures." Four items cover trust selection, asking about trustworthy agents: doctors at local community hospitals; doctors in provincial and municipal hospitals; provincial or national public health administrators; and experts/scholars at medical research institutions. Four more items concern information channels: "I obtain subhealth-related information through an Internet search (Baidu and Soso);" "I obtain subhealth related information through related hospital websites;" "I need to search for more information about subhealth;" and "I will compare this information with other relevant information." Five items cover risk perception: total presence of subhealth indicators in an individual's body; subhealthy physical symptoms that I fear are a threat to my quality of life; subhealthy symptoms in my body and I feel anxious and scared; "Do you think the occurrence of subhealth is related to the individual's behavioral habits?;" and "Do you think the occurrence of subhealth is related to the degree of integrity of an individual's family structure?." Te social groups' dimension concerns the fnal three items: family members; social networks (QQ, WeChat, and Weibo); and friends, relatives, neighbors, and colleagues. Using Likert's 5grade scoring standard, each item has fve options, namely, "totally disagree," "basically disagree," "neither agree nor disagree," "basically agree," and "fully agree," which scored 1-5 points, respectively. Te total score of this fve-dimensional scale ranged from 18 to 90. Te higher the score, the better the individual's competence of physical subhealth risk perception.

Questionnaire on Demographic
Variables. Te questionnaire included parts for gathering demographic data about the participants (gender, age, education level, years of working, living place, marital status, number of children, and average annual household income) and control variables data (self-assessment of health, subhealth duration, number of employees in the work unit, and subhealth proportion in the work unit). Te variables are formatted as shown in Table 1.  [22], we compiled a questionnaire to collect individual subhealth clinical data. Specifcally, participants were asked if they had the following clinical symptoms that lasted for three months or longer. Te clinical symptoms covered in the questionnaire include short-term knee pain symptoms; gastrointestinal and liver abnormalities (e.g., nausea in the morning, palpitations, hunger, and similar symptoms); cardiac abnormalities (e.g., shortness of breath, arrhythmia, snoring, sexual dysfunction, and similar symptoms); stool abnormalities (e.g., alternating diarrhea and constipation and long-term chronic diarrhea); and painless abnormalities (e.g., painless neck mass, painless hematuria, and similar symptoms). For each item, clinical manifestation options are divided into three categories "No," "Yes," and "No idea," which scored 1, −1, and 0 points, respectively. Te score of this questionnaire ranged from −5 to 5. Te closer the score is to 5, the healthier the individual's body. Te closer the score is to −5, the more severe the subhealth condition is.

Statistical
Analysis. EpiData 3.1 software was used to establish the database and double input data. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were calculated on the participants' demographic data using SPSS 23.0. Heatmap analysis of physical subhealth and risk perception data was performed using Python-3.8.6. Te Pearson correlation coefcients were used to analyze the correlation among physical subhealth, risk perception, demographic variables, and related control variables. Factor analysis was used to test for multicollinearity, and multiple linear stepwise regression analysis was used to explore the efects of demographic variables and control variables on physical subhealth and risk perception. Two-way interactions in moderated multiple regression were used to test the moderating efect of demographic variables and control variables on physical subhealth and risk perception. Diferences are considered to be statistically signifcant when P < 0.05.  Table 2.

Te Efect of Risk Perception Level on Physical Subhealth/
Health. In this study, two variables, physical subhealth risk perception level and clinical manifestations of physical subhealth, were used to collect data from physical examinees through a cross-sectional survey. Python-3.8.6 software was used to analyze the data of physical subhealth status and risk perception level. We found that a few physical examinees had a poor risk perception level, but most of them had a good risk perception level. As the risk perception level increased, the rate of physical subhealth status tended to increase and then decrease, peaking at the "good" risk perception level (except when the physical subhealth score was 2, which peaked at the "general" risk perception level). Te details are shown in Figure 2. Te results suggested that there was an efect of the public's risk perception level on physical health status. Note. 5, 4, 3, 2, 1, 0, −1, −2, −3, −4, and −5 represent the physical health scores of the physical examinees. Te closer the score is to 5, the lower the risk of subhealth and the better the health status. Te closer the score is to −5, the higher the subhealth risk and the worse the health status. Te risk perception score is divided into four levels according to the quartiles method [23]: 18-35, 36-53, 54-71, and 72-90. We use "poor," "general," "good," and "excellent" to represent the risk perception levels. "Poor" indicates the score on the risk perception scale is 18-35, with "general" indicating 36-53, "good" indicating 54-71, and "excellent" indicating 72-90.

Correlations among the Study Variables.
Based on the clinical manifestations and risk perception sample data for physical subhealth, Pearson's correlations were calculated among the study variables, as shown in Figure 3. Te results showed the correlations among physical subhealth, risk perception, demographic variables, and control variables.
From Figure 3, it can be seen that physical subhealth was negatively correlated with the living place, marital status, average annual household income, subhealth duration, and physical subhealth risk perception level (P < 0.05). Te risk perception level was positively correlated with the education level, living place, average annual household income, subhealth duration, number of employees in the work unit, and subhealth proportion in the work unit (P < 0.05), and negatively correlated with age (P < 0.05). Tere will be a multicollinearity problem when the correlation coefcient is more than 0.9, and there may be a problem when the correlation coefcient is over 0.8 [24], so 0.6 is the baseline for an acceptable correlation coefcient [25]. In this study, only the correlation coefcient between age and working years and that between age and number of children exceeded 0.6, and both correlation coefcients were 0.66. We conducted a multicollinearity test on all data. Te larger the variance infation factor (VIF), the greater the problem of multicollinearity. More specifcally, multicollinearity is not a problem when the tolerance value is greater than 0.10 and the variance infation factors (VIFs) are less than 10. In our study, the lowest tolerance value was 0.354 and the highest VIF was 2.829. Accordingly, multicollinearity does not appear to be a signifcant problem in our dataset.

Regression Analysis.
Te multiple stepwise regression model for physical subhealth and risk perception level on the demographic characteristic variables and control variables is provided in Table 3.
It can be seen from Table 3 that age, education level, and the subhealth proportion in the work unit had a signifcant positive infuence on the physical health (P < 0.05), while the living place, marital status, and subhealth duration signifcantly and negatively infuenced the physical health of the examinees (P < 0.05). Te living place, average annual Average annual household income Less than 30,000 yuan � 1; 30,000 to 60,000 yuan � 2; 60,000 to 100,000 Yuan � 3; 100,000 to 200,000 yuan � 4; more than 200,000 yuan � 5 Self-assessment of health More serious than sub-health � −2, sub-health � −1, unclear � 0, and health � 1 Subhealth duration Less than 3 months � 1, 3 to 6 months � 2, 6 months to 1 year � 3, less than 2 years � 4, more than 3 years � 5 Number of employees in the work unit Freelance � 1, less than 50 � 2, 50 to 150 � 3, 150 to 500 � 4, more than 500 � 5 Subhealth proportion in the work unit 10% � 1, 30% � 2, 50% � 3, 70% � 4, more than 90% � 5 household income, number of employees in the work unit, and subhealth proportion in the work unit had a signifcant positive infuence on the level of risk perception (P < 0.05), while age had a signifcant negative infuence on the level of risk perception (P < 0.05). Te results in Figure 2 partially supported Hypothesis 1: Te risk perception level has an impact on physical subhealth.
Te results in Figure 3 showed that there is a signifcant negative correlation between physical health and risk perception level. Terefore, Hypotheses 1 and 2 are partially supported. Figure 3 and Table 3 supported Hypotheses 3 and 4. Some demographic variables and control variables have signifcant efects on physical subhealth and risk perception.

Moderating Efects among the Study Variables.
We used two-way interactions in a moderated multiple regression to explore the moderating efect of demographic variables and control variables on physical subhealth and the risk perception level (Table 4). Te results showed that among the abovementioned variables, only the number of children of physical examinees had a signifcant moderating efect on physical subhealth and risk perception level (P < 0.05). Te specifc moderating efciencies are shown in Figure 4.
As shown in Figure 4, the risk perception level of physical examinees with more children and higher health level was signifcantly lower than those with fewer children. Te risk perception level was higher in families with fewer  Figure 2: Heatmap of the distribution of physical subhealth rate in diferent risk perception levels (%).
children than in families with more children. Te poorer the level of physical health, the higher the level of risk perception. Meanwhile, the diference between the two groups of samples was small, the possible reason was that our study only considered the impact of the number of children on the physical health and risk perception level of the physical examinees, and did not consider the age of the children. Te family burden of the children of diferent ages was diferent. Te age of the children in this study may be relatively similar, so the diference between the two samples was small.

Discussion
Te purpose of this study was to explore the relationships between risk perception level, demographic characteristics, and physical subhealth among physical examinees. Furthermore, the roles of demographic variables as moderators in the relationship between risk perception level and physical subhealth were investigated. From Figure 3, it can be seen that the physical health status and the risk perception level of the study participants were signifcantly and negatively correlated. On the one hand, when the risk perception level of the study participants increased above the normal level, they became more worried about their health, which further caused psychological anxiety and tension [26]. Physical subhealth is often an outward manifestation of psychological subhealth. More psychological pressure can lead to the growth of negative emotions [27]. Studies have found that anxiety and depression can reduce the subjective sense of health of the public, increase the degree of physical and mental discomfort of the public [28], and take their physical health into a low-quality state. On the other hand, as physical subhealth deepens, the public's internal anxiety and worry can raise the risk perception level. Based on these results, we put forward the following suggestions. First, decision-makers should pay attention to public mental health and correctly guide public risk perception. For groups with low levels of physical subhealth risk perception, leaders should target and push physical subhealth prevention knowledge through technology software or programs such as WeChat applets and relative health APPs to improve the public's physical subhealth perception level. For groups with high levels of risk perception, information about physical health checkups and health care knowledge should be publicized.
Te study results show that age, education level, and subhealth proportion in the work unit all signifcantly and R1 stands for physical subhealth status; R2 stands for physical subhealth risk perception level; R3 stands for gender; R4 stands for age/years; R5 stands for education level; R6 stands for years of working; R7 stands for living place; R8 stands for marital status; R9 stands for number of children; R10 stands for average annual household income; R11 stands for self-assessment of health; R12 stands for subhealth duration; R13 stands for number of employees in the work unit; and R14 stands for subhealth proportion in the work unit.
positively infuence physical health, whereas living place, subhealth duration, and marital status negatively infuence physical health. One of the possible reasons for the results is that most of the physical examinees in this study are under 45 years of age (83%); fewer are elderly. With the improvement of living standards, contemporary young people are more concerned about their health, so it is understandable that age has a positive efect on physical health in this study. Later, the scope of the study participants could be expanded to increase the data for the elderly group. A second possible reason is that the study participants with higher education level mainly focus on their own and family's quality of life and are more willing to spend money and time to buy health care products or exercise, so they have a relatively better physical health status. So, we encourage the public to attach importance to education. A third possible reason is that the higher the subhealth proportion in the work unit of the study participants, the more  risks the study participants perceive, and they will take various measures to improve their health status actively. A fourth possible reason is that people living in second-tier developed cities have a more stressful and faster life and encounter serious environmental pollution, both of which lead to poorer physical health. Terefore, we propose to improve the public living environment to build a livable city. A ffth possible reason is that divorce has become more common in recent years, unhappy marital status (e.g., divorce) and discordant family life indirectly induced physical subhealth conditions due to psychological imbalance, negative emotions, and increased stress [29]; our results are consistent with the studies of Lopez et al. [30]. Based on this, it is recommended that the relevant marriage laws should be improved and the implementation of a divorce cooling-of period should be implemented. We must strengthen psychological guidance and intervention for couples heading toward divorce to reduce the divorce rate. A sixth possible reason is that when the body is in a subhealthy state for a long time without intervention or treatment, the subhealthy condition will gradually worsen and even evolve into a disease. Based on this logic, our result is consistent with Bo-Yang's research to a certain extent [2]. Of course, other possible reasons cannot be ruled out.
Our analysis of the results shows that the living place, average annual household income, number of employees in the work unit, and subhealth proportion in the work unit signifcantly and positively infuence the risk perception level, and only age negatively infuences the risk perception level. One possible reason is that the older the study participants, the greater their life experience and exposure, the better their ability to handle risk, and the lower their physical subhealth risk perception level. Another possible reason is that when people have a more prosperous and developed place of living, a higher household income, and a higher quality of life, then they are more concerned about their health, so they have a higher level of physical subhealth risk perception. Terefore, it is recommended that social resources should be allocated rationally to reduce the gap between the rich and the poor. Yet another possible reason is that more employees in the work unit, higher the subhealth proportion in the work unit indicating a higher number of subhealthy people in the work unit. Tis will bring psychological panic and anxiety to the study participants. In those conditions, they will worry more about their health status and the level of physical subhealth risk perception will gradually increase. We should focus on the health of work unit employees and regularly organize employees to attend medical checkups.
Our results show that the number of children of physical examinees had a signifcant moderating efect on the relationship of physical subhealth and risk perception level. Te risk perception level of physical examinees with more children and higher health level was signifcantly lower than those with fewer children, and the risk perception levels were higher in families with fewer children than in families with more children. A possible reason for the moderation is that examinees with more children and better health spend more time and energy on their children and pay less attention to their own physical health, so it is understandable that the risk perception level of examinees with more children and better health is signifcantly lower. A second possible reason is that families with fewer children typically have a lower level of economic pressure than families with more children, so they have more energy and fnancial resources to spend on their own health management. Also, they are often more sensitive to information about their own health status, and once they perceive a change in their health status, they will quickly take countermeasures, so it is not difcult to understand that families with fewer children have a higher level of risk perception. A third possible reason is that when the physical health status of the examinees is poor, their psychological burden will increase, and poor health will also trigger internal panic and anxiety, so the risk perception level of the examinees is correspondingly higher. Te number of children in a family is related to China's population policy. China's family planning policy was in force for decades and attracted great attention from the public. Te policy has made a remarkable contribution to reduce China's fertility rate, control the total population, and avoid the negative problems caused by overpopulation, but China also needs to face up to the series of problems it brought, such as the accelerated process of population aging and the serious imbalance of the sex ratio at birth [31]. With the continuous development of the economy and society, the progress of medical and health services, and the improvement of people's living standards, China's population is aging [32]. In response to the increasing average age of its population, China has implemented a comprehensive twochild policy to adjust the demographic structure and slow down the aging trend, but the implementation of the policy did not trigger a birth boom among pregnant women of the right age in China. Cha et al. [33] found that after the implementation of the "comprehensive two-child" policy in China, the second-child fertility rate among women of childbearing age did not increase, but remained at a low level, mainly because women of childbearing age in China perceive risks such as high fnancial pressure, high cost of raising children, unattended children, and impact on work and career development [34,35]. How to coordinate responses to the aging population and the "comprehensive  two-child" policy requires the support and cooperation of relevant government departments. It can also contribute to the development of our public physical health by, for example, promoting the national policy of better prenatal and postnatal care.

Conclusion
Tis study investigated how the risk perception level and demographic characteristics afect physical subhealth among physical examinees. Te results showed that the risk perception level and average annual household income were signifcantly and negatively correlated with the physical subhealth status of the medical examiners. Te poorer the level of physical health, the higher the level of risk perception. Te level of risk perception had the opposite efect on physical subhealth. Age, education level, living place, marital status, subhealth duration, and subhealth proportion in the work unit were direct infuences on physical subhealth. Te risk perception level and average annual household income were indirect factors that infuenced the physical subhealth status of the examinees. Te moderating efect of the number of children on physical subhealth status and risk perception level was signifcant. Based on this, we suggest that the overall improvement of public health can be achieved by enhancing public literacy and education level, improving the housing and living environment to build a livable city, strengthening psychological guidance and intervention for couples heading toward divorce to reduce the divorce rate, encouraging the public to attend regular medical check-ups, allocating social resources rationally to avoid unreasonable wage increases, disseminating the national policy on better prenatal and postnatal care, and enhancing the public's awareness of physical health care.

Data Availability
Te data and materials in the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest
Te authors declare that they have no conficts of interest.