A comprehensive survey analysis focusing on the effect of living literacy on residential environment and health recognition under COVID ‐19 in Japan
2022; Wiley; Volume: 32; Issue: 10 Linguagem: Inglês
10.1111/ina.13136
ISSN1600-0668
AutoresTakashi Kawasaki, Koki Kikuta, Motoya Hayashi, Michiko Bando, Kenichi Hasegawa, Takao Sawachi,
Tópico(s)Smoking Behavior and Cessation
ResumoIndoor AirVolume 32, Issue 10 e13136 ORIGINAL ARTICLEOpen Access A comprehensive survey analysis focusing on the effect of living literacy on residential environment and health recognition under COVID-19 in Japan Takashi Kawasaki, Corresponding Author Takashi Kawasaki sakitaka0826@eis.hokudai.ac.jp Graduate School of Engineering, Hokkaido University, Sapporo, Japan Correspondence Takashi Kawasaki, Graduate School of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido, 060-8628, Japan. Email: sakitaka0826@eis.hokudai.ac.jpSearch for more papers by this authorKoki Kikuta, Koki Kikuta orcid.org/0000-0002-4407-4154 Faculty of Engineering, Hokkaido University, Sapporo, JapanSearch for more papers by this authorMotoya Hayashi, Motoya Hayashi Faculty of Engineering, Hokkaido University, Sapporo, JapanSearch for more papers by this authorMichiko Bando, Michiko Bando Department of Environmental Health, National Institute of Public Health, Wako, JapanSearch for more papers by this authorKenichi Hasegawa, Kenichi Hasegawa Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo, JapanSearch for more papers by this authorTakao Sawachi, Takao Sawachi President, Building Research Institute, Tsukuba, JapanSearch for more papers by this author Takashi Kawasaki, Corresponding Author Takashi Kawasaki sakitaka0826@eis.hokudai.ac.jp Graduate School of Engineering, Hokkaido University, Sapporo, Japan Correspondence Takashi Kawasaki, Graduate School of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido, 060-8628, Japan. Email: sakitaka0826@eis.hokudai.ac.jpSearch for more papers by this authorKoki Kikuta, Koki Kikuta orcid.org/0000-0002-4407-4154 Faculty of Engineering, Hokkaido University, Sapporo, JapanSearch for more papers by this authorMotoya Hayashi, Motoya Hayashi Faculty of Engineering, Hokkaido University, Sapporo, JapanSearch for more papers by this authorMichiko Bando, Michiko Bando Department of Environmental Health, National Institute of Public Health, Wako, JapanSearch for more papers by this authorKenichi Hasegawa, Kenichi Hasegawa Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo, JapanSearch for more papers by this authorTakao Sawachi, Takao Sawachi President, Building Research Institute, Tsukuba, JapanSearch for more papers by this author First published: 24 October 2022 https://doi.org/10.1111/ina.13136AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Appropriate knowledge and actions of residents in housing are expected to reduce health effects, defined as "living literacy." With the spread of COVID-19 and the diversification of lifestyles, a quantitative evaluation of a comprehensive model that includes living literacy in the housing environment is required. In this study, the author conducted two web-based surveys of approximately 2000 different households in Japan during the summer of 2020 and winter of 2021, and a statistical analysis based on the survey results. As a result, ventilation by opening windows was observed as a new resident behavior trend under COVID-19. In addition, structural equation modeling using the survey samples confirmed the certain relationship between living literacy and subjective evaluation of the indoor environment and health effects in both periods. Practical Implications This study identified the impact of occupants' knowledge and in-home behaviors on indoor environment and health assessments. Under COVID-19 in Japan, opening windows was a measure that many people practiced, suggesting that a certain level of behavioral change occurred in the homes due to social demands. The subjective recognition of several health effects that can occur within the housing was found to change depending on the level of knowledge and countermeasure behavior of the occupants. More attention should be paid to the involvement of detailed personal lifestyle habits regarding changes in health status. 1 INTRODUCTION In modern residential life, the role played by occupants in maintaining and improving their health is as significant as that of housing performance and facility performance. To maintain a good indoor environment in a house, it is essential for residents themselves to have appropriate knowledge and to practice effective behaviors. This ability of residents can be interpreted as a kind of literacy and is the area on which this study will focus. Health literacy is one such capacity of the health parties. Health literacy is defined as "the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions."1 The Institute of Medicine takes the view that the health literacy that people possess is the result of the interaction of social and cultural backgrounds and personal factors.2 In addition, low levels of health literacy have been shown to be significantly related to prevalence, and its lack has been considered problematic.3 While the importance of health literacy is well recognized and applied in a variety of ways, divergent views exist regarding its specific definition and framework. Sørensen et al. discuss the scope and conceptual aspects of health literacy, suggesting the existence of several levels and different dimensions with respect to health literacy and presenting an integrated model of it.4 Others present a conceptual model with two views that understand health literacy as either a "risk" in clinical care or an "asset" in public health.5 Some studies have focused on lifestyle as such a health risk or health promotion factor. In particular, the relationship between lifestyle habits such as alcohol consumption, smoking, and physical activity and chronic diseases has been reported.6, 7 It is commonly believed that health literacy or lifestyle is influenced by social context, and studies have shown that people's socioeconomic status (SES) influences health through the mediation of health literacy or lifestyle.8, 9 In this study, health literacy was applied to residential living, and "living literacy" was defined as "the degree of knowledge of appropriate behavior and residential living of residents within their homes." The hypothesized model in this study is shown in Figure 1. Similar to health effects, living literacy is influenced by internal and external factors. Internal factors refer mainly to psychological characteristics according to individual principles and preferences. External factors include learning through education and social demands. The behavior and perceptions of such subjects may change with life-stage transformations. For example, behavioral changes during a woman's gestational period and the perception of the environment as a major factor for a healthy pregnancy at the level of consciousness have been reported.10 FIGURE 1Open in figure viewerPowerPoint Research hypothesis model The concept of health interventions like living literacy, which is the focus of this study, has already been examined in relation to health problems caused mainly by environmental pollutants. Joyce et al. in their study of risk factors related to infant allergy and asthma examined mothers' avoidance behavior and level of knowledge of environmental risk factors.11 Recent studies have also suggested that control of the indoor residential environment may be an effective means of addressing serious health problems related to childhood asthma.12, 13 Cultivation of living literacy is one of the guidelines for healthy living that residents should aim for under more diverse lifestyles. This study aims to quantitatively evaluate the relationship between living literacy, indoor environment, and health effects through a web survey in Japan. Kishi et al.14 conducted a nationwide survey of indoor environmental conditions in Japanese houses from 2003 to 2004. In their survey, Kishi et al. confirmed that indoor humidity, odor, and air stagnation indices were associated with the risk of Sick House Syndrome (SHS) in dwelling units. Hasegawa et al.15 also conducted a web-based survey of the same scale in 2018, showing associations between housing performance and home occupants' behavior and knowledge of indoor environmental problems (e.g., condensation, mold, and odor). In this study, based on a large-scale survey conducted by Hasegawa et al.15 in Japan in the past, a web-based survey was conducted from April to August 2020 (hereinafter referred to as "summer") and from October 2020 to February 2021 (hereinafter referred to as "winter"). The period covered by the survey is the initial stage of the spread of COVID-19 in Japan. It is necessary to focus on the short-term behavioral changes of residents and clarify the details of these changes. Based on the survey results, the author will conduct a statistical analysis of the relationships among the factors involved in the hypothetical model (Figure 1), especially those indicated in orange, and examine the model using structural equation modeling (SEM). 2 METHODS 2.1 Data collection In this study, two surveys were conducted using the web-based questionnaire method, one in the summer and the other in the winter. Note that the subjects of the summer and winter surveys were not necessarily the same; they were recruited randomly from the survey agency's registrants. The target respondents for both surveys were approximately 2000 persons (aged 20–60 years old). The number of requests from the survey agency was 128 098 s (summer) and 137 123 s (winter), and the collection rate was about 1.5% for both. The target population was families (excluding single-person households) that had lived in the same house for at least 3 years and whose family composition had not changed for at least 2 years. In addition, to determine household energy consumption in the survey, respondents were required to know their electricity rates for a specific period of time. For the summer survey, only households with an air conditioner in the house were included. Survey participants were screened and then equalized by gender, age, and region (Hokkaido, Akita, Miyagi, Tokyo, Osaka, Kochi, Nagasaki, and Okinawa) as much as possible (final sample size: summer n = 2116 and winter n = 2181). 2.2 Questionnaires The questionnaire consisted of approximately 50 questions in total. The questions consisted of seven items: respondent attributes, housing attributes, facilities, knowledge, indoor environment, lifestyle, and COVID-19. Questions on respondent attributes included questions on gender, age, family structure, smoking, and medical history ("asthma," "atopic dermatitis," "dry eyes," "pollinosis," "hay fever," "allergic rhinitis," "allergic conjunctivitis," "food allergy," "SHS (Sick House Syndrome)," "MCS (Multiple Chemical Sensitivity)," "hypertension," and "diabetes"). Questions regarding housing attributes included housing type, year of construction, history of residence (years), region, and building renovation (Table 1). The questions related to facilities include those related to ventilation and air-conditioning systems. Knowledge questions are about information on environmental indicators, knowledge about SHS, knowledge about heat stroke (in summer), and knowledge about bathing accidents (in winter). Questions related to the indoor environment include questions on condensation, mold, dust mites, odor, cold, and humidity. Lifestyle questions are about equipment usage, cleaning frequency, and preventive measures (condensation, mold, mites, odor, heat stroke, and bathing accidents); COVID-19 questions are about COVID-19 measures, ventilation, changes in time and number of people at home, and changes in electricity rates. TABLE 1. Characteristics of respondents Characteristics Summer n = 2116 Winter n = 2181 Characteristics Summer n = 2116 Winter n = 2181 n (%) n (%) n (%) n (%) Gender Type of house Male 981 (46.4) 1012 (46.4) Detached house 1147 (54.2) 1169 (53.6) Female 1135 (53.6) 1169 (53.6) Apartment/condominium 969 (45.8) 1012 (46.4) Age Year of construction 20–29 177 (8.4) 205 (9.4) Before 1985 399 (18.9) 446 (20.4) 30–39 487 (23.0) 477 (21.9) 1986–1995 445 (21.0) 459 (21.0) 40–49 526 (24.9) 534 (24.5) 1996–2003 459 (21.7) 455 (20.9) 50–59 468 (22.1) 477 (21.9) 2004–2013 527 (24.9) 505 (23.2) 60–69 458 (21.6) 488 (22.4) After 2014 286 (13.5) 316 (14.5) Rising children (year <20) Years lived in Yes 758 (35.8) 1090 (50.0) 3 to <5 322 (15.2) 275 (12.6) Smoking 5 to 10 1300 (61.4) 1393 (63.9) Symptoms Region Asthma 79 (3.7) 98 (4.5) Hokkaido 271 (12.8) 318 (14.6) Atopic dermatitis 89 (4.2) 87 (4.0) Akita 245 (11.6) 255 (11.7) Dry skin 58 (2.7) 46 (2.1) Miyagi 273 (12.9) 285 (13.1) Dry eye 116 (5.5) 113 (5.2) Tokyo 278 (13.1) 286 (13.1) Pollinosis 235 (11.1) 252 (11.6) Osaka 272 (12.9) 265 (12.2) Allergic rhinitis 218 (10.3) 208 (9.5) Kochi 274 (12.9) 264 (12.1) Allergic conjunctivitis 38 (1.8) 32 (1.5) Nagasaki 258 (12.2) 269 (12.3) Food allergies 31 (1.5) 42 (1.9) Okinawa 245 (11.6) 239 (11.0) SBS 3 (0.1) 3 (0.1) Building remodeling (within 3 years) MCS 4 (0.2) 3 (0.1) Yes 261 (12.3) 238 (10.9) High blood pressure 295 (13.9) 293 (13.4) Diabetes 104 (4.9) 106 (4.9) In developing the survey questionnaire, several past surveys on the residential indoor environment in Japan were used as references.16-19 2.3 Statistical analysis In the statistical analysis, the chi-square test and logistic regression analysis used in Chapters 3 and 4 were performed in BellCurve for Excel (Social Survey Research Information Co., Ltd.). SEM in Chapter 5 was conducted in IBM SPSS AMOS 27 (IBM Japan, Ltd.). Binomial logistic regression analysis on symptoms associated with heat stroke and bathing employed a variable reduction method (standard p-value = 0.20). Variables to be entered as explanatory variables were examined in advance for their association with the objective variable, and appropriate variables were extracted. 3 LIVING LITERACY UNDER COVID-19 The widespread use of COVID-19 has significantly changed people's lives, and it can be inferred that the impact of this change has extended to the behavior of individuals in their residences. This chapter focuses on the behavior of Japanese residents and their indoor environment in the COVID-19 environment. According to the Japanese Ministry of Health, Labor, and Welfare, the first infected person in Japan occurred on January 16, 2020. During the summer survey, the number of cases exceeded 1500 in August 2020. Since then, there have been multiple peaks of infection spread in the country, and during the winter survey, there was a day in January 2021 when the number of cases exceeded 8000. Since the winter survey, the infection has continued to spread further, and the results of this survey report the initial stage of COVID-19 in Japan. With the spread of COVID-19, people's working and schooling patterns changed significantly. Figure 2 shows the increase in the number of people at home and the time spent at home obtained from the survey results for the summer and winter periods. However, the summer and winter surveys cover different sample groups. Comparisons are made with the same period of the previous year and show the average number of persons in a household whose home time increased, as well as the average increase in home time per person. The survey results show that home time increased by approximately 2–3 h per person. This may have impacted the comprehensive survey and increased the opportunities for residents to look at their indoor environment. FIGURE 2Open in figure viewerPowerPoint Increase in the number of people and hours at home 3.1 Countermeasures 3.1.1 Overview and characteristics The following section presents the overall results (Table 2) and the relationship between the COVID-19 countermeasure level implemented and personal attributes (Table 3) about the infection control measures implemented in the houses. Questions regarding countermeasures were multiple answerable (hereafter referred to as "MA" in the figures and tables), and similar questions were employed in the summer and winter surveys. The COVID-19 measure levels were divided into four tiers, depending on the number of the nine measures implemented. "None" (the number of measures = 0), "Low" (1–3), "Middle" (4–6), and "High" (7–9). In Table 2, more than 90% of the residents indicated that they wash their hands and gargle, suggesting that they are highly conscious of not bringing viruses into their residences when they return home. In addition, about half of the residents indicated that they "increase the amount of ventilation," meaning a heightened awareness of ventilation that has not been seen in conventional infection control measures. Regarding Table 3, a comparison by gender revealed that women took more measures than men in both the summer and winter surveys (p < 0.001). In addition, the summer survey showed a statistically significant relationship between the number of measures implemented and the area of residence (p < 0.001). Details are shown in Figure 3. Tokyo and Hokkaido, where many countermeasures were implemented, were the areas that showed a significant increase in the number of new positive cases during the summer survey, confirming that the difference in crisis awareness associated with the spread of infection affected the behavior of residents. Thus, the influence of social conditions on resident behavior is one of the characteristics of living literacy under COVID-19 conditions. TABLE 2. COVID-19 measures (MA) Variables Summer n = 2116 Winter n = 2181 n (%) n (%) Using disinfectant to clean the room 664 (31.4) 687 (31.5) Washing hands and gargling 1957 (92.5) 1962 (90.0) Careful to control temperature 388 (18.3) 345 (15.8) Careful to control humidity 517 (24.4) 344 (15.8) Increasing ventilation 1012 (47.8) 1006 (46.1) Decreasing ventilation 29 (1.4) 29 (1.3) Using an air purifier 562 (26.6) 511 (23.4) Wearing a mask even indoors 181 (8.6) 150 (6.9) Careful with food and beverages 480 (22.7) 514 (23.6) Other 22 (1.0) 25 (1.1) Nothing 85 (4.0) 128 (5.9) TABLE 3. Pearson's chi-square test on characteristics and COVID-19 measure level Attributes COVID-19 measure level Summer (p-value) Winter (p-value) Gender p < 0.001** p < 0.001** Age 0.755 0.612 Smoking habits 0.312 0.127 Type of house 0.141 0.457 Year of construction 0.550 0.047* Years lived in 0.060 0.284 Region p < 0.001** 0.219 Note: **p < 0.01, *p < 0.05. FIGURE 3Open in figure viewerPowerPoint COVID-19 measure level and region (summer) 3.1.2 Ventilation For COVID-19 countermeasures in residences, it was important to ensure ventilation volume, and ideally, the operation of normal ventilation systems should be intensified, and doors and windows should be opened when necessary.20 Therefore, the current survey focused on ventilation, particularly the operation of ventilation systems and the opening of windows, to investigate the actual conditions. Table 4 shows ways to increase ventilation in homes. Note that only those who responded "increase ventilation" in the above COVID-19 measure (Table 2) were included in the survey. In setting the options, the respondents were asked to consider those that would increase ventilation by intensifying the operation of the ventilation system and those that would open windows. For those that would open windows, they were asked about the frequency and direction of the ventilation. Residents who increased ventilation through the enhanced operation of the ventilation system accounted for about 30% of the total respondents in both surveys. Regarding window opening, the most common pattern was to always open windows from two directions, which accounted for more than 40% of the total respondents in the summer survey. Table 5 shows how windows are opened during cooling (summer) and heating (winter). In both periods, "regularly open windows" was the most common pattern, and even in winter, when the outside temperature drops rapidly, many residents kept their windows open while heating. TABLE 4. How to increase ventilation (MA) Variables Summer n = 1012 Winter n = 1006 n (%) n (%) Enhancing the ventilation system 282 (27.9) 290 (28.8) Regularly open a window in one direction 161 (15.9) 190 (18.9) Always try to open a window in one direction 140 (13.8) 125 (12.4) Regularly open a window in two directions 306 (30.2) 328 (32.6) Always try to open a window in two directions 441 (43.6) 348 (34.6) Other 7 (0.7) 7 (0.7) TABLE 5. Opening the window while cooling/heating Variables Summer n = 2060 Winter n = 1983 n (%) n (%) Regularly open a window 908 (44.1) 1053 (53.1) Always try to open a window 448 (21.7) 306 (15.4) Always close the windows 683 (33.2) 595 (30.0) Not using air conditioning 21 (1.0) 29 (1.5) The above description of the ventilation situation in the COVID-19 environment shows that the ventilation awareness of the occupants has increased compared to the pre-COVID-19 environment. Although this change may be temporary, this is an example of how the spread of COVID-19 has led to different occupant behavior than in the past. 3.2 Relevance to the indoor environment This section of the analysis focuses on the indoor environment and the opening of windows, which was a trend in this COVID-19 measure. First, the indoor environment of the respondents to this survey is summarized. Figure 4 shows the incidence of problems related to the indoor environment (for the last year at the time of response). Figure 5 shows the implementation rate of countermeasures for indoor environmental problems. Regarding the implementation of countermeasures, the number of residents who have implemented at least one of the options listed was tabulated. FIGURE 4Open in figure viewerPowerPoint Problems related to the indoor environment FIGURE 5Open in figure viewerPowerPoint Measures for problems related to the indoor environment Regarding Figure 4, compared to the results of the survey by Kishi et al.,14 the incidence of condensation, mold, and odor in residences nationwide was similar to that before COVID-19. Regarding Figure 5, it was found that more than half of the occupants took some measures to address problems related to the indoor environment in all categories. Figure 6 shows the relationship between the occurrence of mold and measures taken by ventilation in the COVID-19 environment. According to the analysis results, households experiencing problems related to the indoor environment tend to be more likely to implement measures through ventilation. This tendency was similar in comparison to the occurrence of other indoor environmental problems. Regarding residents' countermeasure behavior and problems related to the indoor environment, Hasegawa et al.15 explained that the more residents implement countermeasures, the more strongly their awareness of problems related to the indoor environment is expressed, and the same tendency is likely to be observed in the results of the present survey. These detailed causal relationships are dealt with in Chapter 5. FIGURE 6Open in figure viewerPowerPoint Mold occurrence and ventilation for COVID-19 measures 4 RECOGNITION OF HEALTH EFFECTS The increased health effects associated with deteriorating indoor environments are a severe issue, and research has been conducted on the relationship between various indoor environmental issues and health. For example, since Strachan et al.21, 22 reported its association with respiratory health problems, with regard to dampness and mold in housing, a link to various health effects (asthma, allergic rhinitis, and respiratory infections) has been implicated.23, 24 Concerning indoor temperatures, conditions that are either too high or too low have been found to lead to poorer health effects.25, 26 In addition, airborne Volatile Organic Compounds (VOCs), especially aromatic and aliphatic compounds, have been reported to be associated with increased asthma symptoms.27 This chapter discusses the relationship between health problems in housing and the indoor environment and living literacy. The health problems addressed in this study will be physical ailments that occur only inside the house, heat stroke (summer), and physical ailments related to bathing (winter), the incidence of which increases in each study period. 4.1 Physical conditions in housing The survey asked about symptoms occurring in the house (headache and dizziness/sore, itchy, flickering eyes/cough, sore throat/hives, skin irritation, itchy skin/runny nose, congestion/feeling tired, and nauseous/hypersensitivity to odors) from seven symptom groups. Multiple answers were allowed for each question. In the analysis, the occurrence of indoor environmental problems (condensation/mold/tick/odor) and the reported data of symptoms were subjected to a chi-square test to confirm statistical significance (Table 6). TABLE 6. Physical condition in housing and indoor environment Physical condition in housing Condensation Mold Tick Odor Summer Summer Summer Summer n (%) p-value n (%) p-value n (%) p-value n (%) p-value Headache and dizziness 65 (7.2) ** 67 (8.8) ** 32 (13.7) ** 33 (15.7) ** Sore, itchy, flickering eyes 63 (7.0) ** 56 (7.4) ** 26 (11.2) ** 29 (13.8) ** Cough, sore throat 23 (2.6) 25 (3.3) ** 15 (6.4) ** 11 (5.2) ** Hives, skin irritation, itchy skin 58 (6.5) ** 57 (7.5) ** 33 (14.2) ** 36 (17.1) ** Runny nose, congestion 58 (6.5) ** 55 (7.2) ** 28 (12.0) ** 23 (11.0) ** Feeling tired, nauseous 36 (4.0) * 34 (4.5) ** 22 (9.4) ** 22 (10.5) ** Hypersensitivity to odors 6 (0.7) 6 (0.8) 5 (2.1) ** 6 (2.9) ** Physical condition in housing Winter Winter Winter Winter n (%) p-value n (%) p-value n (%) p-value n (%) p-value Headache and dizziness 70 (7.0) * 86 (8.2) ** 31 (12.0) ** 45 (11.8) ** Sore, itchy, flickering eyes 68 (6.8) 77 (7.3) ** 29 (11.2) ** 42 (11.0) ** Cough, sore throat 54 (5.4) ** 60 (5.7) ** 26 (10.1) ** 38 (10.0) ** Hives, skin irritation, itchy skin 46 (4.6) * 56 (5.3) ** 28 (10.9) ** 30 (7.9) ** Runny nose, congestion 109 (11.0) ** 110 (10.5) ** 43 (16.7) ** 61 (16.0) ** Feeling tired, nauseous 36 (3.6) ** 35 (3.3) ** 15 (5.8) ** 24 (6.3) ** Hypersensitivity to odors 33 (3.3) ** 33 (3.1) * 11 (4.3) * 26 (6.8) ** * p < 0.05 ** p < 0.01. The statistical analysis confirmed an increase in declarations with the deterioration of the indoor environment for many symptoms. These data show a statistically significant relationship, implying that physical discomfort in the housing is strongly influenced by the deterioration of the indoor environment. 4.2 Risk factors of heat stroke symptoms Heat stroke caused by raised body temperature is one of the health problems that require attention, especially during the summer season when room temperatures in housing are elevated. In general, it is recommended to keep room temperature below 28°C by actively using air conditioners and fans to prevent heat stroke. In COVID-19 environments, appropriate ventilation is recommended while cooling equipment is in use.20 On the other hand, Hatakeyama et al.28 noted in Japan, COVID-19 preventive measures such as home requests and the use of counseling services may be associated with reduced exposure to heat. This study conducted a statistical analysis of the occurrence of heat stroke in residences in the COVID-19 environment and its contributing factors based on the survey results. For the risk analysis related to heat stroke, the results of the summer survey were referred to. 4.2.1 Severity and personal attributes For the severity of heat stroke, the author cited the Environmental Health Manual for Heat Stroke29 of the Ministry of the Environment and classified the eight symptoms asked in the question into three categories (Table 7). TABLE 7. Severity of heat stroke symptom Symptoms n (%) Severity I Dizziness 116 (5.5) Flushed skin 92 (4.3) Muscle cramps 42 (2.0) Severity II Sluggishness, nausea 94 (4.4) Alteration in sweating 96 (4.5) Severity III High body temperature 63 (3.0) Unconsciousness 9 (0.4) Disorientation 11 (0.5) Table 8 shows heat stroke symptoms and respondent characteristics. In determining severity, the severity category was determined by referring to the most severe symptoms reported by the respondents. Significant relationships were found between age, region, and reported heat stroke symptoms. Regarding age, it was confirmed that younger people were more likely to report heat stroke symptoms. However, according to the Fire and Disaster Management Agency, more than half of the emergency medical evacuees in Japan from June to September 2020 due to heat stroke were elderly people (65 years and older). This is thought to be because the elderly are
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