Archives of Academic Emergency Medicine. 2021; 9(1): e36 https://doi.org/10.22037/aaem.v9i1.1208 REV I EW ART I C L E Cardiovascular Diseases in Natural Disasters; a Systematic Review Javad Babaie1,2,3, Yousef Pashaei asl1,4, Bahman Naghipour5, Gholamreza Faridaalaee6,7,8∗ 1. Department of Health Policy & Management, Tabriz University of Medical Sciences, Tabriz, Iran. 2. Tabriz Health Services Management Research Center,Tabriz University of Medical Sciences, Tabriz, Iran. 3. Iranian Center of Excellence in Health Management, Tabriz University of Medical Sciences, Tabriz, Iran. 4. Department of Health Services Management, School of Health Management and information Sciences, Iran University of Medical Sciences, Tehran, Iran. 5. Department of Anaesthesiology and Intensive Care, Tabriz University of Medical Sciences, Tabriz, Iran. 6. Emergency Medicine Research Team, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. 7. Department of Emergency Medicine, Maragheh University of Medical Sciences, Maragheh, Iran. 8. Disaster Research Team, Tabriz University of Medical Sciences, Tabriz, Iran. Received: March 2021; Accepted: March 2021; Published online: 4 May 2021 Abstract: Introduction: As a result of destruction and lack of access to vital infrastructures and mental stress, disasters intensify cardiovascular diseases (CVDs) and hence management of CVDs becomes more challenging. The aim of this study is investigating incidence and prevalence of CVDs, morbidity and mortality of CVDs, treatment and management of CVDs at the time of natural disasters. Methods: In the present systematic review, the arti- cles published in English language until 28. 11. 2020, which studied CVDs in natural disasters were included. The inclusion criteria were CVDs such as myocardial infarction (MI), acute coronary syndrome (ACS), hyper- tension (HTN), pulmonary edema, and heart failure (HF) in natural disasters such as earthquake, flood, storm, hurricane, cyclone, typhoon, and tornado. Results: The search led to accessing 4426 non-duplicate records. Finally, the data of 104 articles were included in quality appraisal. We managed to find 4, 21 and 79 full text articles, which considered cardiovascular diseases at the time of flood, storm, and earthquake, respectively. Conclusion: Prevalence of CVD increases after disasters. Lack of access to medication or lack of medication adjustment, losing home blood pressure monitor as a result of destruction and physical and mental stress after disasters are of the most significant challenges of controlling and managing CVDs. By means of quick establish- ment of health clinics, quick access to appropriate diagnosis and treatment, providing and access to medication, self-management, and self-care incentives along with appropriate medication and non-medication measures to control stress, we can better manage and control cardiovascular diseases, particularly hypertension. Keywords: Natural disasters; Earthquakes; Floods; Cardiovascular Diseases; Hypertension; Acute Coronary Syndrome Cite this article as: Babaie J, Pashaei asl Y, Naghipour B, Faridaalaee Gh. Cardiovascular Diseases in Natural Disasters; a Systematic Review. Arch Acad Emerg Med. 2021; 9(1): e36. 1. Introduction Over recent years, the number of disasters and their costs has been increasing and is 6 times higher compared with the first ∗Corresponding Author: Gholamreza Faridaalaee; Department of Emer- gency Medicine, Tabriz University of Medical Sciences, Daneshgah Street, Tabriz, Iran. Tel: +98-4133829540, Email: faridaalaee@tbzmed.ac.ir, grf.aalae@yahoo.com. ORCID: https://orcid.org/0000-0002-9990-4936. half of the last century (1-3). For instance, about 324 disasters with 141 million casualties occurred only in 2014 (4). In addi- tion to destroying homes, roads, drinking water system, elec- tricity and gas system, and causing other economic damages, disasters lead to an increase in the incidence of commu- nicable diseases, non-communicable diseases (NCDs), and trauma (5). NCDs were the leading cause of mortality and morbidity in the world over the last century and their inci- dence and prevalence have an increasing trend. It is expected that incidence and prevalence of NCDs increase at the time This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem J. Babaie et al. 2 of disasters and the people present in the disaster area be more vulnerable to NCDs (6, 7). Cardiovascular diseases (CVDs) is the main category of NCDs whose incidence and prevalence have an increasing trend due to changing life style and aging population (8-10). NCDs leads to 40 million deaths in the world each year and like other NCDs, incidence and prevalence of CVDs increases af- ter disasters (9). As a result of destruction and lack of access to vital infrastructures such as homes, health centers, med- ication and also causing physical and mental stress, disas- ters intensify CVDs and hence management of cardiovascu- lar diseases faces a fundamental challenge (10-13). The aim of this systematic review study is investigation of incidence and prevalence of CVDs, morbidity and mortality of CVDs, and treatment and management of CVDs, at the time of nat- ural disasters. 2. Methods This is a systematic review based on PRISMA protocol. In this study, PICO is defined as: P, which stands for problem or population, is individuals with cardiovascular diseases, (I) is natural disasters, (C) comparing normal situation, and the (O) outcome is prevalence, treatment, and management of CVDs. 2.1. Eligibility Criteria In the present study, the articles published in English lan- guage until 28. 11. 2020, which studied CVDs in natural disasters were included. The inclusion criterion was study of CVDs such as myocardial infarction (MI), acute coronary syndrome (ACS), hypertension (HTN), arrhythmia such as atrial fibrillation (AF), ventricular tachycardia (VT), ventricu- lar fibrillation (VF), and paroxysmal supraventricular tachy- cardia (PSVT), pulmonary edema, and heart failure (HF) in natural disasters such as earthquake, flood, storm, hurricane, cyclone, typhoon, and tornado. The articles published in the form of abstract as a poster, conference proceeding, com- mentary, editorial, and case report were excluded. In this study, volcano and climate changes were not included. Simi- larly, man-made disasters were excluded and not reviewed. 2.2. Search Strategy In order to achieve the purpose of the present study, search items and their related key terms were selected by means of using MeSH and EMtree databases, consulting with expert specialists, searching the titles and abstracts of the related articles under supervision of a specialist and researcher in emergency medicine and a health management in disasters Ph.D. An extensive search in electronic databases including Medline, Web of Science, Embase, and Scopus until 28. 11. 2020 was done. Search strategy in Medline database is pre- sented in table 1. 2.3. Study Selection and Data Collection Process and Outcome Appraisal In this study, all articles published in English language, which studied CVDs in natural disasters, were included. Screen- ing of the articles was done based on inclusion and exclu- sion criteria. First, abstracts of the articles were read by two independent researchers. Then, after selecting the eligible articles, full texts of the articles were evaluated. Afterwards, the full text was considered in accordance with inclusion and exclusion criteria and eligible articles were selected. Sum- marizing the articles and recording the data in the checklist along with final quality control was performed by two inde- pendent individuals. Any discrepancy in views was resolved through discussion between two parties or by means of con- sulting a third researcher. The articles were summarized us- ing a checklist, which has been designed based on PRISMA statement (14). In this systematic review, outcome appraisal was prevalence, treatment, and management of CVDs in nat- ural disasters. Data related to first author and year of publi- cation, being peer reviewed, obtaining ethical or publication committee approval, definition of the outcome, expression of exclusion criteria, presence of a control group, and expres- sion of statistical method were extracted. 2.4. Statistical analysis Data analyses were done in a descriptive way. All the articles were summarized and categorized based on the considered variables. 2.5. Ethics Since systematic review studies consider the previously pub- lished studies and the research is not directly done on human or animal, there is no need for ethical approval. 3. Results 3.1. Study Selection and Study Characteristics The search led to 4426 non-duplicate records. 4,199 abstracts were excluded as they were not related to the purpose of our study. Also, 115 studies were case report, letter to edi- tor or Correspondence, review articles, abstracts presented at the conferences and non-English, all of which were excluded from the study. 112 article abstracts were eligible and hence necessary measures to provide their full text were taken. Also, six full text articles were studied but since they did not meet our criteria, they were excluded. We were not able to the find full text of two articles. They were not even accessible in the journal archive. Finally, the data of 104 articles were included in quality control appraisal. We managed to find 4, 21 and 79 full text articles, which considered cardiovascular diseases at This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 3 Archives of Academic Emergency Medicine. 2021; 9(1): e36 the time of flood, storm, and earthquake, respectively. The selection process and PRISMA diagram are shown in Fig- ure 1. Due to the variety of our included articles, based on natural disasters, we grouped the included articles into 3 cat- egories including storm (hurricane, typhoon, Cyclone and Tornadoes), flood, and Earthquake. 3.2. Quality control of study and risk of Bias The included articles were qualitatively considered. The qualitative review results of flood, storm (hurricane, cyclone, typhoon, and tornadoes), and earthquake are presented in Table 2, 3, and 4, respectively. 3.3. CVDs in Flooded Areas Prevalence of CVDs increases after flood. Diseases like AF, PSVT, ACS, severe CHF, cardiopulmonary arrest, and AMI un- dergo a remarkable increase in the first week and then de- crease. The second wave of increase in the number of CVDs is also observed in the 7th week (15). Existence of negative experiences such as loss of property, physical work, financial problems, alcohol use, and perceived distress in the long run can lead to hypertension (16). Nevertheless, some studies in- dicated that despite the increasing prevalence of CVDs after flood, such an increase is not statistically significant (17) and when confounding factors are excluded from the study, in- crease in the prevalence of CVD is not observed (18). 3.4. CVDs in Storm area (hurricane, Typhoon, Cyclone and Tornado) Prevalence of CVDs including HTN, AMI, and fatality caused by CVDs increase after hurricane (19-24). In the areas ex- tremely affected by the hurricane, the rate of CVDs, partic- ularly HTN, is high (23, 25). Unemployment, drug abuse, smoking, temporary housing life, and lack of health insur- ance are among the risk factors of increase in the prevalence of CVDs, particularly AMI (20-22, 26). After hurricane, CVDs obviously increase in women over 45 years of age; however, in the 6-month follow-up, no increase is observed (27). In terms of circadian and septadian rhythms, studies indicated that within 3 years, and in some studies within 6-10 years, after hurricane, the rate of CVDs increased only on the evenings and weekends. However, on the following morning and the first day of the week, a considerable decrease is observed in the prevalence of AMI (2, 21, 22). Since tornado has a small volume and does not take more than some minutes, it does not cause increase in cardiovascular diseases (28). At the time of evacuation, some patients forget to take their medication out of their home and some of them run out of medication or cannot obtain them and lack of medication makes them unable to control their HTN and hence uncon- trolled HTN increases (29, 30). The issue is so prevalent and 48.4% of those who are taken to shelters lack medication, most of whom are male and have no health insurance (31). Also, about 10% of the patients, who are taken to shelter, have chest pain and require emergent treatment (31). After hurricane, adherence to medication regimen decreases, par- ticularly in individuals over 65 years of age and non-whites, (26), which causes more uncontrolled HTN in these individ- uals in comparison with those who have higher adherence to antihypertensive drugs (29). However, after one year and in the second year after hurricane, adherence to medication re- turns to its previous state (32). The other factor leading to higher and uncontrolled HTN is stress (33); particularly in the elderly, it causes an increase in CVDs and lack of con- trolled HTN (34, 35). Reasons for such stress factors include lower capability of coping with disaster, more damage to liv- ing place, stress of living after hurricane, increase in separa- tion from friends and family, fewer visits to friends and fam- ily, loss of property and relatives (33). Medication request rate is higher in patients with CVDs in comparison with other diseases. Although only 11% of the complaints belong to the patients with CVDs, 52% of the requests for medication are for CVDs (36). Also, 55.6% of the individuals, who live in shel- ter, suffer from chronic diseases like HTN, diabetes, hyper- cholesterolemia, pulmonary diseases, and mental disorders (31). The amounts of medication required for chronic dis- eases and CVDs make up a high percentage of the medica- tion required during hurricane, which are 68% and 39%, re- spectively (37). Temporary reduction in access to health care centers leads to a decrease in the number of patients refer- ring for primary care after reopening of the centers and as a result more uncontrolled HTN can be observed (28). To improve the quality of health care services, the following points are recommended (30): 1. Having electronic health records, which enables the treatment staff to have access to the history of patients, prescribe the previous drugs of the pa- tient appropriately and quickly, and to better control chronic diseases upon emergencies. 2. Electronic health records backup. 3. Appropriate storage of medications 4. All mem- bers of healthcare provider team should be aware of the plan and their own roles, and 5. For times when telephone and in- ternet disconnect, there should be a backup communication system. 6. Appropriate relationship between donors and re- lief teams. Since during such disasters, drugs and medical equipment are donated, there is not much assurance as to their being intact and appropriately preserved. Even, some of them are unsuitable and inapplicable. Hence, those who intend to donate drugs and medical equipment should have a direct relationship with healthcare provider team. 7. Self- management of the patients for chronic diseases should be encouraged and reinforced. 8. There should be an effective communication plan between the individuals and healthcare providers. 9. All the stresses should be controlled (30). This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem J. Babaie et al. 4 3.5. Earthquake So far, numerous earthquakes have occurred. Out of these earthquakes, the Great East Japan earthquake in 2011 with the magnitude of 9 on Richter scale was one of the most se- vere ones, which caused triple disasters (38). In addition to its own causalities, it caused tsunami whose casualties were like those of intense flooding. On the other hand, Fukushima Daiichi Nuclear Power Plant was damaged, which caused leakage of radioactive materials (38). Hence, the studies re- lated to this earthquake will be run in two separate parts: The earthquake, and the surrounding area of the Fukushima Daiichi Nuclear Power Plant, which was damaged after the Great East Japan earthquake, is discussed separately. Based on the studies performed after the earthquake, prevalence of CVDs such as HTN, ACS, AMI, IHD, HF, VF, sustained or non- sustained VT, and cardiomyopathy and other types of mor- tality increase after the earthquake (39-79). The rate of CVD outbreak in the regions more impacted and more damaged by the earthquake is higher than other areas. Fatal MI had a significant increase in high impact areas; however, in low impact areas its rate was not different from that of before the earthquake (80). Also, in high impact areas, higher rate of De- compensated HF and AMI is observed, particularly among women and the elderly and those who had to abandon their home (81, 82). Impact of the earthquake on CVDs is not permanent and af- ter a period, the incidence rate of CVDs returns to its nor- mal state. The earthquake not only has not had any remark- able impact on long-term prognosis in 30 years, but also has not had any midterm impact on CVDs in 4 years after earth- quake in the affected area (83, 84). Some studies indicate that this impact was even less than this and after a few weeks, there was no increase in observed incidence and prevalence of ACS and HTN (43, 47, 51, 59, 76, 85-89). Some studies even express that incidence of CVDs in the first week of the earthquake had a remarkable increase and after that this in- crease is less observed (43, 90). The less severe earthquakes are, the sooner the return to previous state takes place (40, 85). Conversely, the more severe earthquakes are, the more damage there will be; hence, the increase in incidence of CVDs will last longer and the return to baseline state will oc- cur later; like in Sichuan earthquake with the magnitude of 8 on the Richter scale, where intense destruction occurred and 5 million people were displaced (43, 44, 62, 91, 92). In New Zealand, two earthquakes occurred with an interval of 6 months. The first one was 7.1 on the Richter scale and an increase in CVDs was observed for 3 weeks. However, in the second one with the magnitude of 6.3 on the Richter scale an increase in CVDs was observed for 2 weeks (43). In the less intense earthquakes the rate of CVDs was significantly high only for 3 days; like the two earthquakes that occurred in Thessaloniki, Greece, on 19th and 20th of 1978 with the mag- nitude of 5.2 and 6.4 on the Richter scale, respectively (93). The other factor impacting the incidence of CVDs is distance from the center of the earthquake. The observed incidence of CVDs such as HTN was lower among those who lived more than 50 km away from the center of the earthquake (51). Blood pressure (BP) increases in the people with chronic dis- eases such as renal failure (94, 95). Other risk factors of in- crease in BP and uncontrolled BP in the people who live in shelters include being over 55 years old, history of having HTN, and having insomnia. Hence, in addition to taking their previous medication regularly, they probably need to increase their previous medication (83). The time, at which the earthquake takes place, is another fac- tor affecting the incidence rate of CVDs. For instance, Loma Prieta earthquake, in 1989, took place at 5:04 pm in San Fran- cisco. The magnitude of the earthquake was 7 on the Richter scale. In comparison with the days before or after the earth- quake or in comparison with the same day in 1990, on the day of Loma Prieta earthquake, there was not any statistically remarkable increase observed in AMI admission in San Fran- cisco area. Northridge, Los Angeles, earthquake in 1994 oc- curred at 4:31 am and there was a 110% increase in the rate of AMI admission in Los Angeles on the day of the earthquake in comparison with the mean admission rate over 7 years before the earthquake. Sudden death rate also increased. Therefore, severe emotional stress resulting from sudden wake-up stress affects the increase in AMI. And if there is less stress, AMI risk is lower as well (96, 97). In fact, stress plays a pivotal role in increase in incidence of CVDs, which mostly happens because of mental stresses such as losing property and relatives (39, 47, 49, 51, 56, 85, 98). Also, in some studies, white coat is thought to be one of the factors affecting stress and increasing BP after the earthquake (87). In some other studies, signs of depression at the time of admission remarkably predict the risk of re- hospitalization for IHD (44). Mental stress resulting from heavy work leads to increase in the incidence of HTN after the earthquake. Disaster staff, who work in the quaked area, face the risk of increasing HTN if they have a heavy workload (99). Even, ordinary government employees showed a higher rate of increase in HTN in the quaked area. In this study, the average time of monthly extra work of ordinary employees in March, 2011, was 10 times more than public people in the previous March. Therefore, after the earthquake Blood Pres- sure of government employees should be controlled and if re- quired treatment should be prescribed (75, 100). Also, circa- dian rhythm changes play a role in increasing fatality result- ing from CVDs, which occurred more in the elderly at night and in the morning, but no increase in fatality was observed between 11 am and 11 pm (101). Age, family history of BP, obesity, sleep disorder, waist to hip ratio, high blood sugar, This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 5 Archives of Academic Emergency Medicine. 2021; 9(1): e36 and high-salt food are other factors that affect the increase in incidence of HTN and uncontrolled HTN after the earth- quake (47, 62, 101, 102). One of the other reasons for uncontrolled Blood Pressure is discontinuity of antihypertensive drugs, which happens be- cause of various reasons. In the people with psychological problems, the risk of stopping using antihypertensive drugs is higher (103). One of the cases with different results is a study carried out in New Zealand. In this study, after two earthquakes, there was no increase observed in ventricular arrhythmia (104). An- other study expressed that through stimulating sympathetic nerve, earthquake leads to increase in HR and cardiac mor- tality. However, in the individuals over 60 years of age, stimu- lation of sympathetic nerve system was blunt (52). In another study, it was said that individuals who lose their residence and live in temporary residence areas, can control their BP as good as the people who live at their own home. However, in- dividuals, particularly the elderly, who live at their own home, indicate increase in BP on winter mornings. Similarly, as to the individuals who do not have any changes in their BP medicine, increase in BP was observed, the researcher did not explain the reasons, though (105). 3.6. Fukushima Area after the Great East Japan Earthquake Areas within 20 km of Fukushima nuclear power plant were determined as high-risk and restricted areas due to nuclear radiations more than 20 mSv per year. Almost all of the res- idents had to evacuate their homes (106, 107). From 20-30 km of the nuclear plant was determined as area prepared for evacuation at the time of emergency. The areas within 30 km of the plant were determined as deliberate evacuation areas (106). Incidence of HTN, tachycardia, MI, AF, and the deaths related to CVDs was higher in the individuals who had to abandon their homes (107-113). CVDs risk was higher than normal range within 2 years after the incident (111). However, some studies indicated that incidence of AMI was higher than the surrounding areas only until one month after the incident (107). Other studies held that there was no remarkable dif- ference in the prevalence of AMI before and after the earth- quake in Fukushima area (114). Stress is a leading factor in increasing the risk of CVDs and hence, a higher rate of CVD is observed in individuals with depression and PTSD (115) and there is a higher increase in the prevalence of CVDs because of psychological stresses like losing property, relatives or job (115, 116). Other risk factors include: previous CVD, being female, being 40-90 years old, obesity, being alcoholic and having dinner late at night (111, 115, 117). After the earthquake, a higher incidence of AF is observed in men compared to other groups (109). In comparison between evacuees and non-evacuees, there was no difference or little difference in term of increase in BP (106). 3.7. Special Groups In a study on pregnant women, it was indicated that those who were in their 3rd trimester of pregnancy at the time of in- cident and stress more commonly had pregnancy HTN (118). In children under 15years of age, within 1 year of the inci- dent, increase in incidence of HTN is observed (119). It has also been reported that within 4 years of the incident, in- crease in incidence of HTN in children is observed. In a study on the impacts of great east JAPAN earthquake on the BP of the injured children, it was indicated that the children who went through more stressful incidents like tsunami waves, corpse of their relatives or friends, fire waves or separation from their parents, higher BP was observed. Of these chil- dren, those who witnessed fire waves indicated higher dias- tolic BP (120). 3.8. Management of CVDs One of the important measures to take in order to decrease the risk of CVDs is to strengthen buildings before the earth- quake happens. It can be claimed that the less destruction in building, the lower the risk of CVDs (42). So as to prevent and treat CVDs, controlling stress is an- other paramount issue that should be taken into account. Over this period, decrease in stress and coronary risk factors may decrease mortality resulting from Coronary Heart Dis- ease (CHD) after a main EQ (48). Prescription of tranquilizers and anti-depression medication can help control HTN and their prescription may even be essential (121). After crises, it is more likely that patients stop taking drugs, encouraging hypertensive patients to start taking drugs again may help re- duce CVD risk (122). After the earthquake, changing the patients’ antihyperten- sive drugs is another important measure that leads to better control of HTN. Data show that after earthquake, paying spe- cial attention to BP level and treatment modifications can be important not only immediately, but also for some months after the earthquake (70). Studies showed that patients who were under treatment of α-blocker or β-blocker or renin- angiotensin inhibitor either did not show any change in their BP level or there was little increase (79). Supplying a morning home blood pressure measuring device to control morning home blood pressure is essential for pre- venting CVDs’ side effects (123). Due to many reasons such as losing morning home blood pressure equipment, dam- age to other equipment, or anxiety caused by vast destruc- tion, most of the patients were not able to measure morn- ing home blood pressure (123). In patients who lived in a shelter, precise control of BP until 4 years was possible us- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem J. Babaie et al. 6 Figure 1: PRISMA flow diagram. ing an automatic home sphygmomanometer and web-based information and communications technology (ICT- technol- ogy) (124). Controlling BP, nutrition, and personal hygiene can decrease HF as well (102). Timely and appropriate intervention is another factor that can help reduce due to CVDs. Complications like HF can oc- cur less under the condition that patients are immediately admitted for AMI and the treatment begins quickly (125). Also immediate admission and intervention improves pri- mary function of PCI (125). 4. Discussion In this systematic review study, incidence and prevalence of CVDs, morbidity and mortality of CVDs, and treatment and management of CVDs, were investigated. Prevalence of CVDs increases after disasters. This increase directly depends on the intensity of the damage to the disaster area. The most import reason for such an increase are stresses like losing home and relatives and friends, disconnection with friends and relatives, losing job and joblessness, and lack of consis- tency following the incident. Also, high-risk individuals like the elderly are more susceptible. However, using appropri- ate medication and non-medication measures in terms of stress, it is possible to decrease prevalence of CVDs. Quick establishment of health clinic and access to appropriate and quick treatment within a few months after disaster is of other measures that can help control CVDs. Such measures like providing and providing access to medication, consulting to change dose or type of medication, and encouraging self- management and self-care can help decrease these compli- cations to minimum. Similarly, it is essential to pay atten- tion to special populations like pregnant women, particularly within their third trimester of pregnancy and children under 15. In a review study, Kazuomi Kario et al., 2012, studied the effects of 2011 Great East Japan earthquake and Hanshin- Awaji earthquake on CVDs. This study probed into in-clinic and off-clinic HTN, potential mechanism of HTN in disas- ters, and management of these diseases. The results indi- cated that BP increases after earthquake and complications related to lifestyle, like stressful factors such as bad qual- ity of sleep, and complications related to activity, such as lack of physical movement after earthquake, can lead to bi- ological rhythm disorders. Aldosterone and cortisone in- crease in biological rhythm disorders and consequently sym- pathetic nerve is stimulated, which leads to increase in the use of salt and hence HTN. In this study, controlling use of salt along with establishing a quiet sleeping condition, being away from stress, appropriate physical activity, and having self-management to prevent obesity are mentioned as im- portant factors to control HTN (126). Similarly, in our study, controlling stress, encouraging self- care and self-management, and providing BP measuring de- vice to facilitate self-care and self-management are taken to be important factors to control HTN. But, in the study done by Kazumi, providing BP measuring device to facilitate self- care is not mentioned (126). In 2015 and 2016 a guideline titled disaster medicine for CVD was published by Japanese Circulation Society (12). This guideline includes a number of issues like water and food hygiene, salt and sugar reg- imen, instructions for healthy sleep and providing sound sleep and, if needed, controlling sleeplessness through med- ication, treating depression, appropriate psychological sup- port, resorting to appropriate diagnostic methods to con- trol CVDs and treat them, and making sure the medication is taken at home to manage and control CVDs (12). Results of this study as well as the clinical guide is consistent with our study, which accentuates controlling stress and provid- ing sound sleep, following a special diet, providing healthy food to the individuals affected by disaster, prescribing med- ication for sleeplessness, changing HTN medication, control- ling risk factors of CVDs, and quickly treating newly-admitted patients or the intensified cases already admitted (12). Re- sults of the study by Errol D et al. are also consistent with our study. That study has also mentioned stress in the dis- aster area, financial stress resulting from losing job and not having insurance, lack of access to healthy food, salty and high-carbohydrate food, and disconnection with the health system and health service providers as some factors that lead to difficulty in controlling HTN during the hurricane (127). The study has recommended some solutions, like having a list (can be electronic) of medications, presenting data re- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 7 Archives of Academic Emergency Medicine. 2021; 9(1): e36 lated to complications of not using medication (before disas- ter), having enough supply of medication, providing appro- priate access to medication during disaster, and appropriate control of stress (127). In a systematic review study in 2019, Farzad Gohardehi et al. probed into HTN and diabetes after disasters. Like our study, they indicated that prevalence of HTN remarkably increases after disasters (3). 5. Limitations In this study, non-English articles were excluded, which re- sulted in losing some data. 6. Conclusion Prevalence of CVDs increases after disasters. Lack of access to medication or lack of medication adjustment, losing home BP monitor device as a result of destruction, and physical and mental stress after disasters are of the most significant chal- lenges of controlling and managing CVDs. By means of quick establishment of health clinic, providing quick access to ap- propriate diagnosis and treatment, providing access to med- ication, and self-management and self-care incentives, along with appropriate medication and non-medication measures to control stress, we can better manage and control cardio- vascular diseases, particularly hypertension. 7. Declarations 7.1. Conflict of interest There is no conflict of interest 7.2. Acknowledgements All authors thank Tabriz University of Medical Sciences for supporting this study. 7.3. Funding and supports There is no funding. 7.4. Authors’ contributions Yousef Pashaei asl, Bahman Naghipour and Gholamreza Fari- daalaee: abstract reading and Data extraction. 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Downloaded from: http://journals.sbmu.ac.ir/aaem 13 Archives of Academic Emergency Medicine. 2021; 9(1): e36 Table 1: Medline search strategy Database Search terms MEDLINE (PubMed) 1) “Cardiovascular Diseases”[Mesh] OR “Pulmonary Edema”[Mesh] OR “Hypertension”[Mesh] OR “Acute Coronary Syndrome”[Mesh] OR “Myocardial Ischemia”[Mesh] OR “Coronary Disease”[Mesh] OR “Conges- tive heart failure”[Mesh] OR “Coronary Diseases”[tiab] OR “Myocardial Ischemias”[tiab] OR “Ischemic Heart Diseases”[tiab] OR “Ischemic Heart Disease”[tiab] OR “Chronic heart Diseases”[tiab] OR “Chronic heart Dis- eases”[tiab] OR “Hypertension”[tiab] OR “High Blood Pressure”[tiab] OR “High Blood Pressures”[tiab] OR “Acute Coronary Syndrome”[tiab] OR “Acute Coronary Syndromes”[tiab] OR “Coronary Artery Disease”[tiab] OR “cardiac disease”[tiab] OR “Congestive heart failure”[tiab] OR “Pulmonary Edema”[tiab] OR “Pulmonary Edemas”[tiab] “Myocardial Ischemia”[tiab] OR “Cardiovascular disease”[tiab] OR “Cardiac Disease”[tiab] OR “Cardiac Diseases” OR “Cardiac Disorder”[tiab] 2) “Earthquake”[Mesh] OR ”Floods”[Mesh] OR ”Cyclonic Storms”[Mesh] OR ”Tornadoes”[Mesh] OR ”Natural Disasters”[Mesh] OR ”Disasters”[Mesh] OR “Earthquake” [tiab] OR “Catastrophic Flooding” [tiab] OR “Catas- trophic Flooding”[tiab] OR “Floods”[tiab] OR “Cyclonic Storms”[tiab] OR “Cyclonic Storm”[tiab] OR “Cy- clone”[tiab] OR “Cyclones”[tiab] OR “Hurricanes”[tiab] OR “Hurricane”[tiab] OR “Tropical Storm”[tiab] OR “Tropical Storms”[tiab] OR “Typhoons”[tiab] OR “Typhoon”[tiab] OR “Tornadoes”[tiab] OR “Tornado”[tiab] OR “Tornados”[tiab] OR “Catastrophic”[tiab] OR “Natural Disasters”[tiab] OR “Natural Disaster”[tiab] 3) 1 &2 Table 2: Quality assessment and risk of bias in flood High risk of bias: × James N. Jana Yasuhiro Alain low risk of bias: p Logue 1980 Obrová 2014 Nagayoshi 2015 Vanasse 2016 Publication in peer-review journal p p p p Description of patient group p p p p Description of control group p p p p Ethics approval × × × p Informed consent × × × × Specified main outcome p p p p Specified secondary outcome p p p p Description of statistical analysis p p p p Conflict of interest status × × × × This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem J. Babaie et al. 14 Table 3: Quality assessment and risk of bias in storm First author and publication year Storm name and event year Type of study Publication in peer- review journal Description of patient group Exclusion criteria Ethics approval Mentioned type of study Specified main outcome Description of statistical analysis Conflict of interest status Lisa A. Hendrick- son 1997 Hurricane Iniki 1992 C.S p p p × × p p × Michael A. Jhung 2007 Hurricane Katrina 2005 C.S p p × × × p × × Erica Howe 2008 Hurricane Katrina 2005 C.S p p × p p p p × P. Gregg Gree- nough 2008 Hurricane Katrina 2005 C.S p p × p p p p p MA Krousel- Wood 2008 Hurricane Katrina 2005 C.S p p p × p p p × T Islam 2008 Hurricane Katrina 2005 CO p p p p p p p × Sandeep Gautam 2009 Hurricane Katrina 2005 O p p p p p p p p Martha I. Arrieta 2009 Hurricane Katrina 2005 Q p p × × p p p p Erin Stanley 2011 Hurricane Katrina 2005 C.S p p p × p p p × Nathan McKin- ney 2011 4 Florida Hurricane 2004 C.S p p × × × p p × Zhen Jiao 2012 Hurricane Katrina 2005 CO p p p × p p p × Matthew N. Pe- ters 2013 Hurricane Katrina 2005 CO p p p p p p p p Matthew N. Pe- ters 2014 Hurricane Katrina 2005 CO p p p × p p p p Joel N. Swerde 2014 Hurricane Sandy 2012 C.S p p p p × p p × Federico Silva Palacios 2015 tornado in Joplin 2011 C.S p p × × × p p × Linda Meta Mob- ula 2016 Typhoon Haiyan 2013 O p p × p p p p × Aaron Baum 2019 Hurricane Sandy 2012 CO p p p p p p p p John C. Moscona 2019 Hurricane Katrina 2005 CO p p p p p p p × Zachary Lenane 2019 Hurricane Katrina 2005 CO p p × p p p p p Ninon A. Bec- quart 2019 Hurricane Katrina 2005 C.S p p × × × p p p Hsin-I Shih 2020 Typhoon Morakot 2009 C.C p p × p p p - p C.C= case-control, CO= cohort study, C.S= Cross Sectional study, O= observational study, Q=qualitative study High risk of bias: ×, Low risk of bias: p This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 15 Archives of Academic Emergency Medicine. 2021; 9(1): e36 Table 4: Quality assessment and risk of bias in earthquake First author and year of publication name of Earthquake and year of event Type of study Publication in peer-review journal Description of patient group Description of control group Exclusion criteria Ethics approval Specified main outcome Description of statistical analysis Conflict of interest status Kleakatsouyanni 1986 Greece 1978 C.S p p ? p × p p × MaurizioTrevisan 1986 Italy 1980 Lo p p p p × p p × MaurizioTrevisan 1992 Italy 1980 Lo p p ? × × p p × Annette J Dobson 1991 Newcastle 1987 C.S p p ? p × p p × Jonathan Leor 1996 Northridge 1994 C.S p p ? p × p p × Komei Saito 1997 Hanshin-Awaji 1995 Ob p p p p × p p × Robert A. Kloner 1997 Northridge 1994 C.S p p p × × p p × Shunji Suzuki 1997 Hanshin- Awaji 1995 Ob p p ? × × p p × Junichi Minnmi 1997 Hanshin- Awaji 1995 C.S p p × × × p p × Kazuomi Kario 1997 Hanshin- Awaji 1995 C.S p p × × p p p × Kazuomi Kario 1997 Hanshin-Awaji 1995 C.S p p p p × p p × Haroutune K. Armenian 1998 Armenia 1988 CO p p p × × p p × David L. Brown 1999 Loma Prieta 1989 Northridge 1994 C.S p p p p × p p × SusanH.Bland 2000 Italy 1983-4 Co p p ? × × p p × Keiko Ogawa 2000 Hanshin- Awaji 1995 C.S p p ? × × p p × Kazuomi Kario 2001 Hanshin-Awaji 1995 Ob p p ? p × p p × Lian-Yu Lin 2001 Taiwan 1999 Ob p p p p × p p × Kyuzi Kamoi 2006 Niigata, Japan 2004 Ob p p ? × × p p × Masahito Sato 2006 Mid-Niigata 2004 C.S p p ? × × p p × Yucheng Chen 2009 Sichuan 2008 C.D p p ? × p p p p Xiao Qiang Zhang 2009 Sichuan 2008 C.S p p p × p p p p Masayuki Tsuchida 2009 Noto Peninsula 2007 Ob p p ? × × p p × I Nakagawa 2009 Niigata Chuetsu 2004 C.S p p p × p p p p Tomoko Azuma 2010 Mid-Niigata 2004 Ob p p p p × p p p Kaisen Huang 2011 Sichuan 2008 Co p p p p p p p p Huang Kai-sen 2011 Sichuan 200 Co p p ? p p p p × Simona Sofia 2012 L’Aquila 2009 C.S p p p × p p p p Makoto Nakano 2012 Great East Japan 2011 C.S p p ? × × p p × Motoyuki Nakamura 2012 Great East Japan 2011 Ob p p p p p p p × Tatsuo Aoki 2012 Great East Japan 2011 C.S p p p p p p p p Kenichi Tanaka 2012 Great East Japan 2011 Ob p p ? p p p p p Tatsuo Aoki 2013 Great East Japan 2011 C.S p p ? × p p p × Satoshi Konno 2013 Great East Japan 2011 Co p p p × p p p p Paolo Giorgini 2013 L’Aquila 2009 Ob p p p p × p p p L. Petrazzi 2013 L’Aquila 2009 C.S p p ? × × p p p Christina Chan 2013 Christchurch 2010, 2011 C.S p p p p p p p × Hitoshi Murakami 2013 Great East Japan 2011 C.S p p p p p p p p Akihiro Nakamura 2013 Great East Japan 2011 Ob p p p p p p p p Eiji Nozaki 2013 Great East Japan 2011 C.S p p ? × p p p × Hiroyuki Yamauchi 2013 Great East Japan 2011 Ob - - ? p p p p p Kimio Watanabe 2013 Great East Japan 2011 Ob p p ? p × p p p X.-C. SUN 2013 Sichuan 2008 C.S p p ? × × p p × Christina Chan 2014 Christchurch 2010 Co p p ? × p p p p Takayoshi Yamaki 2014 Great East Japan 2011 C.S p p ? × p p p × Tomonori Itoh 2014 Great East Japan 2011 Ob p p p × p p p p This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem J. Babaie et al. 16 Table 4: Quality assessment and risk of bias in earthquake First author and year of publication name of Earthquake and year of event Type of study Publication in peer-review journal Description of patient group Description of control group Exclusion criteria Ethics approval Specified main outcome Description of statistical analysis Conflict of interest status Yoshihiro Tani 2014 Great East Japan 2011 C.S p p p p p p p p Kenichi Tanaka 2014 Great East Japan 2011 Ob p p ? p p p p × Akihiro Nakamura 2014 Great East Japan 2011 C.S p p p × p p p p Kiyotaka Hao 2014 * Great East Japan 2011 RCT p p p × p p p p Fumitaka Tanaka 2015 Great East Japan 2011 Ob p p p p p p p × Yukihiko kawasaki 2014 Great East Japan 2011 Ob p p p × × p p p Masanobu Niiyama 2014 Great East Japan 2011 C.S p p p p p p p × Masafumi Nishizawa 2015 Great East Japan 2011 Co p p p × × p p p Misa Takegami 2015 Hanshin-Awaji 1994 AND Great East Japan 2011 C.S p p ? p p p p p Hitoshi Suzuki 2015 Great East Japan 2011 C.S p p p × p p p p Yukihiko kawasaki 2015 Great East Japan 2011 Ob p p p p p p p p Reiichiro Tanaka 2016 Great East Japan 2011 C.S p p ? p p p p p Kaisen Huang 2016 Sichuan 2008 C.S p p p × × p p × Chuanwei Li 2016 Sichuan 2008 Ob p p ? p p p p p Tetsuya Ohira 2016 Great East Japan 2011 Co p p p p p p p × Motoyuki Nakamura 2016 Great East Japan 2011 Co p p × × p p p p Na Li 2017 Tangshan 1976 Ob p p p p p p p p Naoki Nakaya 2017 Great East Japan 2011 C.S p p ? × p p p p Masafumi Nishizawa 2017 Great East Japan 2011 Co p p × × p p × p Motoyuki Nakamura 2017 Great East Japan 2011 Ob p p p × p p p p Satoshi Miyata 2017 Great East Japan 2011 Co p p p p p p p p Tetsuya Ohira 2017 Great East Japan 2011 Ob p p p × × p p p Andrea M Teng 2017 Christchurch 2010, 2011, 7.1 , 6.3 Co p p p p p p p × Satoshi Konno 2017 Great East Japan 2011 Co p p × × p p p p Wen Zhang 2017 Great East Japan 2011 C.S p p ? × p p p p Masato Nagai 2018 Great East Japan 2011 Co p p p p p p p p Christina Chan 2019 Christchurch 2010, 2011, 7.1 , 6.3 Ob p p ? × p p p × Mai Takiguchi 2019 Great East Japan 2011 Co p p p p p p p p Satoshi Hoshide 2019 Great East Japan 2011 Ob p p ? × p p p × Masahiro Watanabe 2019 Great East Japan 2011 Co p p p × p p p p Masafumi Nishizawa 2019 Great East Japan 2011, Ob p p p × p p p p Mimang Tembe 2019 Nepal 2015, C.S p p ? × p p p × Hyo Kyozuka 2020 Great East Japan 2011, Ob p p ? p p p p p Toshiki Sanoh 2020 Great East Japan 2011 Ob p p ? p p p p p C.C= case-control, CO= cohort study, C.S= Cross Sectional study, Lo= Longitudinal O= observational study, Q=qualitative study, Randomized Clinical Trial= RCT. * Only 1 RCT exist, High risk of bias: ×, Low risk of bias: p This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem Introduction Methods Results Discussion Limitations Conclusion Declarations References