Mental Health Consequences of Riverbank Erosion: Examining Anxiety and PTSD Among Affected Communities in Southwestern Bangladesh

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Zawadul Karim, Md. Al-Mamun, Masuma Parvin, Maliha Azad Eva, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6042886/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Natural disasters, including tropical cyclones, tidal surges, and riverbank erosion, pose severe environmental and socio-economic challenges. Among these, riverbank erosion has emerged as a critical issue in Bangladesh, leading to both physical displacement and psychological distress. Despite its far-reaching consequences, limited research has examined the mental health impacts of riverbank erosion, particularly in relation to anxiety and post-traumatic stress disorder (PTSD). This cross-sectional study investigates the prevalence and determinants of anxiety and PTSD among communities affected by riverbank erosion in the southwestern region of Bangladesh, specifically in Gabura Union, located in the Shyamnagar sub-district of Satkhira District. The study was conducted between May and July 2024, using a multistage stratified sampling strategy. A total of 385 residents, aged 12 to 65 years, who have lived in the area for more than 15 years and have no previous diagnosed mental disorders, were surveyed. Among these, 280 were exposed to severe riverbank erosion, while 105 were not. Data were collected using valid scales for PTSD (PCL-5) and anxiety (GAD-7), and key risk factors, such as loss of livestock, displacement, and social support, were also assessed. Findings reveal that 63.63% of participants experienced anxiety, while 69.87% exhibited symptoms of PTSD, with significantly higher prevalence among those directly impacted by erosion. Vulnerability was particularly pronounced among middle-aged individuals (30–49 years), those from joint families, illiterate individuals, and those earning less than 10,000 Taka per month. The erosion-induced devastation resulted in 63.57% of respondents losing livestock and 64.65% experiencing displacement, exacerbating risks of PTSD, anxiety, insomnia, and suicidal ideation. However, social support played a crucial role in mitigating psychological distress. The study underscores the urgent need for targeted mental health interventions and social assistance programs to support affected populations. Policy measures should focus on enhancing resilience through community-based mental health care and sustainable social protection strategies. Riverbank erosion PTSD anxiety mental health displacement Bangladesh Figures Figure 1 Figure 2 Figure 3 1. Introduction A disaster is characterized as a significant disruption of a community's or society's normal functions, leading to considerable losses and impacts on individuals, property, or the environment that exceed the affected community's capacity to address with its available resources (UNISDR, 2009). Disasters primarily fall into two categories: Natural and human made disasters. Natural disasters arise from natural phenomena, such as storms, tidal waves, riverbank erosion and tropical storms (Saeed & Gargano, 2022 ). Asia is perhaps the most disaster-prone region globally. A primary cause attributed to the elevated frequency of disasters in Asia is its geographical position (Kokai et al., 2004 ). Among south Asia, it is especially South Asia that bears a disproportionate amount of the weight of natural disasters (Global Report on Internal Displacement, 2017 ). In south Asia, Bangladesh is one of the most vulnerable nations to natural disasters due to its geographical and geophysical position, which puts it at increasing risk from the consequences of climate change (Islam et al. ,2021). This region experiences a rise in the occurrence of other hydro-meteorological coastal disasters, such as river bank erosion, waterlogging, and saline intrusion in the soil (Rakib et al. ,2019). Consequences of natural disasters on Bangladesh is immensely dangerous (Karim et al. ,2024). At the very least once per year, the nation is confronted with a natural disaster. People are frequently more susceptible to being affected by climate-related disasters because of their frequency, unpredictability, and uncertainties over their livelihoods, as well as the location and pattern of their settlements (Maurya, 2019 ; Uddin & Haque, 2012 ). Among natural disasters, riverbank erosion is one of the prominent natural disasters of Bangladesh (Hasnat et al. ,2020; Islam & Rashid, 2011 ). Bangladesh is a riverine country in Southeast Asia, a low-lying nation, has about 700 rivers and streams that run into the Bay of Bengal (Hamid, 2009 ; Islam & Rashid,2012), where natural disasters like river bank erosion frequently occur due to its geographical location, terrain features, numerous rivers, and monsoonal climate (Wahiduzzaman & Yeasmin, 2022 ). Riverbank erosion is intensified in certain regions by elevated tides, vigorous winds, and substantial waves mostly in rainy seasons in Bangladesh (Uddin and Basak, 2012 ). Conversely, due to the sluggish water flow in delta regions, riverbank erosion may occur at any season (Kaiser, 2023 ). There are about 2400 km of riverbanks in Bangladesh (Hasnat et al. ,2020). The Bangladeshi River Management Board predicts that roughly 1200 km of riverbanks erode each year (Akter et al. , 2019). A significant population in this region resides adjacent to the rivers and is thus more susceptible to bank erosion (Das et al., 2017 ). Almost 30–40% of the country's people live in places near rivers that are likely to be washed away by erosion (Paul et al. ,2021). In recent years, riverbank erosion has escalated by ten to twenty times in Bangladesh due to climate change and unanticipated human interference (Uddin and Basak, 2012 ). Hence, River bank erosion is paramount environmental disaster in Bangladesh (Islam et al. ,2011; Rahman et al., 2022 ). Khatun et al. ( 2020 ) projected that if the trend of escalating the severity and frequency of catastrophes caused by nature persists, about 30,366,230 households in Bangladesh will be impacted by such events by 2030. The repercussions of extreme weather events not only drive migration and displacement but also affect the immediate determinants of both physical and mental health (Smith et al., 2022 ). 1.1 Effects of disasters on mental health The effects of disasters on health have been extensively examined within scientific circles. Natural disasters impact millions globally, both physically and psychologically, with extensive and potentially enduring impacts (Makwana, 2019 ; WHO,2019). It is predominantly unforeseen, resulting in victims experiencing shock (Makwana, 2019 ). Following which victims might induce a condition of hopelessness and trauma in themselves. This traumatic event affects the functioning lives of victims and results in developing Post traumatic stress disorder (Hackbarth et al. ,2012; Makwana, 2019 ). Udomratn and Pichet (2008) provides a comprehensive examination of natural disasters in Asia. This study indicates that the prevalence of post-traumatic stress disorder and its symptoms among Asian survivors following a natural disaster range from 8.6–57.3%. The incidence of post-traumatic stress disorder is common disorder among survivors of natural disaster (Udomratn and Pichet, 2008). PTSD is most commonly observed alongside anxiety, sadness, and other behavioral and psychological disorders following natural disasters (Makwana, 2019 ). So, increased anxiety is also concern for the victims of natural disasters (Rehdanz et al., 2015 ). Similar to other natural disasters, riverbank erosion has the same severe effect over people’s mental health. It was found that significant psychological distress was experienced by women in Bangladesh due to riverbank erosion (Keya and Harun ,2007). Similarly, the prevalence of depression, anxiety and stress was significantly higher among the people who were exposed to riverbank erosion due to losing various kinds of assets (such as house, land, livestock, etc.), and took narcotics to remove their stress/tension/frustration (Hossain et al., 2021a ). Simultaneously, it has numerous adverse effects on residents, such as diminished academic achievement, health issues, and reduced social and financial standing (Alam et al. ,2020). Along with that riverbank erosion in Bangladesh contributes to livelihood unpredictability, including socio-economic instability, poverty, sickness, and significant mental health issues (Alam et al. ,2020). It has resulted in heightened levels of worry, stress, and depression among the majority of responders (SarzamArobi et al. , 2019). and 8.75% respondents have suicidal ideation, 62% showed insomnia due to the damage following river bank erosion (Kaiser, 2023 ). To cope with adversities, Individuals employ problem-solving and emotional coping strategies to acclimate to unfamiliar environments, simultaneously, social connections may provide significant resilience or the ability to withstand unpleasant situations (SarzamArobi et al. , 2019). 1.2 Present study In light of the existing research, it is apparent that numerous studies have been conducted in Bangladesh regarding riverbank erosion, albeit mental health related work is limited. Most of these studies concentrate on the socio-economic ramifications for the victims of riverbank erosion. Only a limited number of studies have examined the correlation between riverbank erosion and mental health factors. Vulnerable mental health outcomes, such as the development of post-traumatic stress disorder and elevated anxiety levels, have not been thoroughly investigated. Moreover, most of the studies followed qualitative methods, therefore, scale-based study to measure exact intensity of mental health outcomes due to riverbank erosion is missing. Furthermore, there is a lack of research focusing on the southern region of Bangladesh concerning the impact of riverbank erosion on mental health. Assuming the need to conduct research, which will give shed of light to the research gap regarding riverbank erosion and Bangladesh. Therefore, the main objective of this study is to know the impact of riverbank erosion in developing significant mental health vulnerabilities like PTSD, anxiety in south-western region of Bangladesh. 2. Methods This study adhered cross-sectional survey research design to conduct the research. 2.1 Study area The study was carried out in a coastal union of Bangladesh named Gabura union. The Gabura Union (see Fig. 1 ) is situated adjacent to the mangrove forest 'Sundarbans' in the Shyamnagar sub-district of Satkhira District. This Territory is surrounded by the Sundarbans mangrove forest on two sides. Two rivers traverse the study area: the Kopataska river flows along the north-western side, while the Kholpetua River meanders along the south-eastern side (Alam et al. ,2015). Figure-1 Gabura was chosen as the study site due to its status as one of the most impacted unions in the severely afflicted region of Satkhira, resulting from the detrimental effects of natural disasters like river bank erosion (Rakib et al., 2019 ). 2.2 Respondents of the study To comprehend the pattern of riverbank erosion of that, we delineated the present embankment condition by traversing the study region. To understand more precisely about the impact of riverbank erosion, we procured data from two groups of people. Data was collected from 385 residents aged between 12 to 65 years living permanently in this area for more than 15 years and having no previous diagnosed mental disorders. Among 385 participants, 280 participants were selected in exposed group (who are mostly impacted by river bank erosion) and 105 participants were selected in non-exposed group (who weren’t impacted by river bank erosion).Selection of people in exposed group is done based on following consideration (i) living river bank erosion prone area in Gabura union for more than 15 years (ii) Have been impacted severely due to river bank erosion(loss of house, livestock etc (iii) Having no previous diagnosed mental disorders. Simultaneously, Selection of people in non-exposed group is done based on following consideration (i) living non river bank erosion prone area (ii) Haven’t been impacted severely due to riverbank erosion. 2.3 Sampling procedure and methods From the end of May to the middle of July 2024, 385 respondents were randomly selected from our study locations. Study participants are selected using a multistage stratified sampling strategy for data. This process begins with the identification of coastal regions, along with their susceptibility that are vulnerable to riverbank erosion. The second step is to randomly select villages from the chosen Gabura union. Lastly, affected and non-affected members of the communities in the sampled areas are selected using random sampling. The study locations in Gabura union were selected using a simple random selection approach to guarantee that participants were from varied socio-economic backgrounds, ages, and occupations. In order to determine sample size, Cochran’s ( 1977 ) most popular approach was used which we followed for the computation. The formula is \(\:\:n\:=\:\left[Z2P\right(1-P\left)\right]/d2\) . Accordingly, we have used p = 0.5 and a 95% confidence level (i.e., at least 5% precision) for setting the reliable and valid scale of confidence level, with the 95% confidence level representing Z values of 1.96 in the normal table. Moreover, a 5% margin of error has been projected. Based on these determinations, the sample size of this study was 385. A sample size of 385 people is deemed sufficient to detect significant impact if riverbank erosion over people’s mental health. 2.4 Study measurement Outcome variables While measuring the mental health status of selected areas, three mental state such as PTSD and Anxiety were measured using valid scales. Therefore, PTSD and Anxiety are considered as outcome variables in this study. Post traumatic stress disorder Post-traumatic stress disorder (PTSD) is a condition that arises in certain individuals following exposure to a traumatic, frightening, or perilous incident (Resick et al., 2012 ). To assess PTSD symptoms, PCL-5 scale was used which is a 20-item self-report measure (Weathers et al., 2013 ). PCL-5 is a 5- point Likert scale ranging from 0 to 4 (0 = Not at all 1 = A little bit 2 = Moderately 3 = Quite a bit and 4 = Extremely) where total severity score ranging between 0 and 80. The current investigation employed a cut-off score of ≥ 33 to identify possible PTSD (Weathers et al., 2013 ).Bangla adapted version of this scale is used in this study to measure PTSD (Islam et al., 2022b ). Anxiety Anxiety is a physiological reaction to a perceived threat, instigated by a person's beliefs, emotions, and ideas, and is marked with apprehensive emotions and tension (Park et al. ,2009). To assess anxiety, seven-item Generalized Anxiety Disorder (GAD-7) scale was used which was developed by Spitzer (Spitzer et al., 2006 ). This scale consists of 7 items questions having a four-point Likert scale ranging from 0 (“Not at all”) to 3 (“Nearly every day”). A cutoff score of ≥ 10 was utilized as a screening criterion for moderate to extremely severe anxiety, facilitating the assessment of anxiety presence among the people who took part in this study (Spitzer et al., 2006 ). This study used Bangla adapted version (Redwan et al., 2020 ) of this scale. Risk Factor /Predictor Variable The prominent predictor (risk factor) of mental health state (PTSD and Anxiety) is whether an individual is exposed or non-exposed to riverbank erosion. In this investigation, the term exposed denoted that the interviewed person experienced severe damage due to riverbank erosion. In addition to the exposed status of river bank erosion, the variable included few risk factors like Loss of livestock (Yes/No), Drinking water problem (yes/No), Received social support (Yes/No), Displacement (Yes/No), Persistent suicidal thought (Yes/No), Continuous worry (Yes/No). Along with that, there was a paramount risk factor that elucidated the level of disruption (Minimal, Moderate, Severe) experienced by an individual due to riverbank erosion. 2.5 Data tabulation and statistical analysis A substantial quantity of information and data was collected from the field investigation. The individuals who were interviewed were given the explicit assurance that their comments would be handled with the utmost discretion or confidentiality. The researcher and the person conducting the interview would be the only ones who were allowed to use the questionnaires. A comprehensive assessment of data and information was performed prior to analysis. IBM's SPSS 26 (Statistical Package for the Social Sciences) was utilized for the analysis of coded, screened, and cleaned data. To achieve the objectives outlined for the study, the researchers employed statistical analyses including descriptive statistics, chi squared test, independent sample t test and One-way Anova analysis according to the characteristics of the data. 2.6 Ethical consideration While conducting a study, social researchers must consider the rights of the people involved (Baker et al., 2016 ). Consequently, researchers must consider the ethical implications of their studies. This study was reviewed and approved by the Institutional Review Board (IRB) of the Department of Psychology, Gopalganj Science and Technology University (GSTU)-8100, Bangladesh (Approval Number: GSTU/SOC/IRB/2024/029). All procedures performed in this study involving human participants adhered to the ethical standards of the IRB at GSTU and the 1964 Helsinki Declaration (World Medical Association, 2013 ) and its later amendments or comparable ethical standards. Throughout this study, ethical standards were meticulously maintained at all stages. Respondents were provided with a comprehensive explanation about the objectives of the study. Before the conversation began, every single person gave their verbal agreement after receiving adequate information. This study adhered rigorously to all ethical standards, guaranteeing that no individuals suffered harm because of their participation. 3. Results Table-1 depicts the prevalence of PTSD and anxiety in exposed group and non-exposed group with riverbank erosion. Among 385 individuals, there were 280 (72.72%) people who were exposed to river bank erosion, while 105 (27.27%) were included in non-exposed group. Overall rates of PTSD and anxiety were 69.87% and 63.63%. (see Table 1). Table 1 and table 2 showed that a higher prevalence of post-traumatic stress disorder (PTSD) and anxiety was seen in the exposed group, which had been adversely impacted by river bank erosion, compared to the non-exposed group (PTSD: 91.4% versus 12.38%, P < .001; Anxiety: 85% versus 6.7%, P < .001) (see table 2 ). Among 385 participants, proportion of males (68.05%) are higher than female (31.94%) Most of the females were housewife (16.88%). In exposed group (280), mostly males (73.6%) and 26.4% females participated in this study. On the other hand, there were 53.3% male and 46.7% female who participated in non-exposed group. There are five different age groups in this study. Respondents with age group 30–49 (54.28%) were higher than other age groups. The lowest number of respondents came from the 12–17 age group (7.53%). Among participants, most them are illiterate (83.90%), come from joint family (66.23%) and do numerous work for living like fishing, honey collecting, doing household, business work etc. Only 9.51% of respondents were educated following which 4.1% were students. Due to its geographical location, respondents mostly were daily worker (25.71%) and fisherman (24.93%) (see table 3 ). Most participants (68.31%) were from the lower class and earned 1-10k taka (74.80%) monthly. It was found that affected respondents had lower income as 73.2% of exposed group members reported a monthly income of 1-10k taka. In addition, most non-exposed participants earned 11-30k taka per month. Thus, 54.3% of non-exposed respondents were middle class (see table 3 ). A chi-squared test was performed to know the associations of outcome variables such as PTSD, anxiety with socio-demographic factors, which is depicted in table − 4. It was depicted that the proportion of PTSD and anxiety was higher to male participants compared to female participants (PTSD: 74.4% versus 60.2%, P = 0.145; and Anxiety: 68.7% versus 53.7%, P = 0.146). Prevalence of PTSD and anxiety was increased with the age, mostly people having middle age (30–49) showed significantly higher PTSD (p < 0.001) and anxiety. In terms of education, illiterate people showed higher prevalence rate of PTSD and anxiety (PTSD: 74.0% versus 48.4%, P = 0.205; and Anxiety: 68.4% versus 40.3%, P = 0.215).Moreover ,participants who are fisherman showed higher PTSD symptoms (84.4%) compared to other counterparts and participants who are daily worker showed higher proportion of anxiety symptoms (77.8%).Simultaneously, people who belongs from middle class, had lower monthly income (< 10k) and lived in joint family showed higher level of PTSD and anxiety symptoms (see table 4 ). In Table-5,we have found that 63.57% participants lost their livestock things ( death of cows, goats) due to river bank erosion and showed higher PTSD and anxiety than participants who didn’t lost their livestock properties (PTSD : M = 46.82 versus 41.96, SD = 9.64 versus 12.24, 95% CI ,t(278) = 3.44, p < .001 : Anxiety : M = 10.97versus 10.06, SD = 2.54 versus 3.28, 95% CI ,t(278) = 2.40, p < .001) . Because of river bank erosion, 64.65% participants in exposed group witnessed their displacement ( lost their house and living in government’s place) and demonstrated higher rate of PTSD and anxiety ( PTSD : M = 47.31 versus 40.91, 95% CI ,t(278) = 4.54, p < .001), ( Anxiety : M = 11.11 versus 9.78, 95% CI ,t(278) = 3.79, p < .001).Following the devastating effect of river bank erosion,68.7% participants having continuous worry regarding their damage showed elevated PTSD and anxiety (PTSD : M = 47.56 versus 39.58, 95% CI ,t(278) = 6.06, p < .001 :Anxiety : M = 11.26 versus 9.30, 95% CI ,t(278) = 5.57, p < .001) . Having witnessed all of these, Figure-2 showed that 37.14% of respondents elucidated about their suicidal thought while confronting those impediments following riverbank erosion. Individuals who got suicidal thought had an extreme level of PTSD (PTSD: M = 51.23 versus 41.40, 95% CI ,t(278) = 8.44, p < .001) and Anxiety ( Anxiety : M = 11.84 versus 9.93, 95% CI ,t(278) = 5.5, p < .001) than people having no suicidal thought (see Fig. 2 and table 5 ). Only 32.85% respondents receive social support in exposed group and it is evident that participant who got social support showed less symptoms of PTSD and anxiety (PTSD: M = 42.76 versus 46.17, 95% CI, t (278) =-2.48, p < .001), (Anxiety: M = 10.07 versus 10.92, 95% CI, t (278) =-2.34, p < .001) (see table 5 ). A one-way between groups analysis of variance (ANOVA) was used to investigate the level of disruption (Minimal, Moderate, Severe) over affected people due to riverbank erosion on perceived PTSD and anxiety among exposed group of riverbank erosion. There was a statistically significant difference at the p < .05 level in PTSD and anxiety scores for the three groups: (PTSD: F (2,277) = 28.74, P = 0.20; Anxiety: F (2,277) = 23.90, P = 0.173). Post-hoc comparisons using the Tukey HSD test indicated that severe disruption groups showed highest proportion of PTSD and anxiety and groups with minimal disruption showed least proportion of PTSD and anxiety (PTSD:M = 37.50 versus 45.45 versus 51.22, SD = 10.93 versus 9.77 versus 9.43; Anxiety: M = 9.03 versus 10.56 versus 12.34, SD = 2.73 versus 2.38 versus 3.17) (see table 6 ). 4. Discussions This study examines the impact of riverbank erosion on affected communities in the southwestern region of Bangladesh. Findings highlight a significant association between riverbank erosion and the development of PTSD and anxiety. Additionally, key risk factors such as loss of livestock, suicidal ideation, and persistent worry are prevalent among victims, further exacerbating their psychological distress. This study underscores the significant mental health burden of riverbank erosion in the southwestern region of Bangladesh. Our findings reveal a notably higher prevalence of PTSD and anxiety among individuals exposed to riverbank erosion compared to non-exposed populations (see Fig. 3 ). These results align with previous studies conducted in Bangladesh (SarzamArobi et al., 2019) and other countries (Doherty & Clayton, 2011 ; Munro et al., 2017 ), which have consistently reported that exposure to environmental disasters increases psychological distress. Consistent with prior research (SarzamArobi et al., 2019; Hossain et al., 2021a ; Kaiser, 2023 ), our findings confirm that severe exposure to riverbank erosion significantly heightens the risk of developing PTSD, anxiety, depression, and insomnia. A key contributing factor to these psychological vulnerabilities is the loss of essential assets, such as homes, land, and livestock, which exacerbates economic insecurity and emotional distress. Similar patterns were observed in past studies, where disaster-induced displacement and property loss were strongly linked to heightened mental health risks (Hossain et al., 2021a ; Mahmud et al., 2021 ). Gender differences in mental health responses to disasters have been widely documented. While previous studies indicate that women exhibit higher levels of PTSD, depression, and anxiety following natural disasters (Hossain et al., 2021a ; Mahmud et al., 2021 ), our findings suggest that males demonstrated a higher proportion of PTSD and anxiety symptoms post-riverbank erosion. This contrast may stem from the unique socio-economic pressures placed on men as primary earners in disaster-affected households. Further investigation is necessary to understand the nuanced gender-specific mental health impacts of riverbank erosion. Age and educational status were also significant determinants of PTSD and anxiety. Middle-aged individuals (30–49 years) exhibited the highest levels of distress, a trend similarly observed in previous studies (Chandra Das et al., 2022 ; Yeshaw & Mossie, 2017 ). Additionally, our findings confirm that illiterate individuals are more susceptible to PTSD and anxiety than their educated counterparts, supporting evidence from Chandra Das et al. ( 2022 ) and Hoffmann & Blecha ( 2020 ). However, this contradicts Asghari et al. ( 2008 ), who argued that mental health outcomes are not necessarily linked to education level. These discrepancies suggest that education may interact with other socio-economic factors to influence psychological resilience in disaster settings. Household structure and economic status further influenced mental health outcomes. Individuals from joint families reported higher PTSD and anxiety symptoms, consistent with Hossain et al. ( 2021b ), who found that living in large households amplifies mental health stressors in disaster-affected regions. Furthermore, lower-income individuals (earning ≤ 10,000 Taka per month) exhibited significantly greater PTSD and anxiety symptoms than those earning above this threshold. This finding aligns with previous research (Hossain et al., 2021a ; Rahman & Gain, 2020 ), which suggests that financial stability serves as a protective factor against disaster-related psychological distress. Notably, fishermen and daily laborers faced the highest PTSD and anxiety levels, paralleling findings from Hossain et al. ( 2021a ), where economically vulnerable groups, such as housewives and daily workers, were disproportionately affected. Livestock loss emerged as a critical factor in exacerbating mental health distress. Participants who lost livestock exhibited significantly higher PTSD and anxiety symptoms compared to those who did not experience such losses. This finding mirrors previous studies (Moyna et al., 2024 ; Nayna Schwerdtle et al., 2021 ), which reported that the destruction of livelihood assets heightened psychological distress among disaster survivors. Likewise, individuals displaced due to home loss demonstrated increased PTSD and anxiety levels, consistent with studies conducted in Bangladesh (Hossain et al., 2021a ), Norway among migrants (Teodorescu et al., 2012 ), and the British Isles among flood-affected populations (Munro et al., 2017 ). An overwhelming 68.5% of participants reported persistent worry following riverbank erosion, exacerbating PTSD and anxiety symptoms. This aligns with previous studies in Bangladesh, which highlighted excessive worry as a common post-disaster psychological response (Hossain et al., 2021a ; Mostafizur Rahman et al., 2023 ). Moreover, suicidal ideation was alarmingly prevalent, with 37.14% of affected individuals contemplating suicide. Those with suicidal thoughts exhibited significantly higher PTSD and anxiety symptoms, echoing findings from previous disaster-related studies that linked trauma exposure to hopelessness, grief, and increased suicide risk (Ozdemir et al., 2015; Tasdik Hasan et al., 2020 ). To further analyze the association between disaster impact and psychological distress, we conducted a one-way ANOVA, which revealed that PTSD and anxiety levels varied significantly across different levels of disruption. Individuals who experienced severe disruption due to riverbank erosion exhibited the highest PTSD and anxiety symptoms, supporting existing evidence that greater disaster exposure correlates with higher mental health risks (Boden et al., 2015 ; Saeed & Gargano, 2022 ). This trend was also observed in moderate disruption groups, who exhibited higher PTSD and anxiety levels than those with minimal disruption, reinforcing the dose-response relationship between disaster exposure and psychological distress. Finally, social support emerged as a crucial mitigating factor. Individuals who received social support reported lower PTSD and anxiety symptoms compared to those without support, consistent with findings from McGuire et al. ( 2018 ) and Mostafizur Rahman et al. ( 2023 ). These results emphasize the importance of community-based interventions, mental health support systems, and targeted policies to address the psychological consequences of riverbank erosion. 5. Policy recommendations Natural catastrophes pose a significant threat to Bangladesh’s healthcare system, which is now unprepared to handle an influx of patients. When it comes to mental health treatment, Bangladesh's national adaptation plans fall short. There are no guidelines or budget details regarding how to proceed with the impact of natural disasters in coastal regions. As a result, we witnessed the health consequences of natural catastrophes on multiple levels, from the personal to the societal to the institutional. The findings of this study underscore the need for urgent local-level policy interventions to address the mental health crisis faced by communities affected by riverbank erosion. Despite national recognition of climate-induced displacement, localized mental health strategies remain insufficient. Considering resource constraints and the existing administrative framework in Bangladesh, the following feasible policy measures are recommended, with examples to illustrate potential success: 1. Integrating Mental Health Services into Local Health Systems Riverbank erosion-affected communities often face immense psychological distress, which must be addressed at the local level. Integrating mental health services into local health systems will be key. For instance, the Upazila Health Complexes (UHCs) and Union Health and Family Welfare Centers (UHFWCs) should incorporate mental health screenings and provide psychosocial support as part of their routine services. Community health workers (CHWs) and local doctors can be trained to provide psychological first aid in these areas. A relevant example can be seen in Jashore district, where the Shushilan NGO has worked with UHCs to integrate mental health care for displaced populations due to riverbank erosion. 2. Capacity Building for Local Government and Community Volunteers Local governance structures such as Union Parishads and Union Disaster Management Committees (UDMCs) should be trained to address mental health needs in the aftermath of disasters. For example, the Cyclone Preparedness Program (CPP) in the coastal regions has trained volunteers to provide immediate support during cyclones. These volunteers could be further trained in psychosocial support to recognize signs of PTSD and anxiety among the affected population. This could be modeled after the Community Mental Health Program in Cox’s Bazar, where community-based volunteers were trained to identify and assist individuals dealing with mental health issues post-displacement. 3. Establishing Mobile Mental Health Units in High-Risk Areas To reach remote and hard-to-reach populations affected by riverbank erosion, mobile mental health units can provide immediate psychological support. This model has been successfully implemented by BRAC in rural parts of Bangladesh, where mobile health clinics were deployed to address both physical and mental health needs of people displaced by flooding. These mobile units could visit coastal areas affected by riverbank erosion on a rotational basis, offering counseling, therapy, and referrals to specialized mental health services. 4. Strengthening Social Safety Nets for Disaster-Affected Families Financial instability exacerbates mental health issues in disaster-affected areas. Strengthening social safety nets and offering livelihood support can reduce anxiety and stress. For example, the Government of Bangladesh’s Vulnerable Group Development (VGD) program, which provides food and cash support to vulnerable communities, could be expanded to include mental health services for those displaced by riverbank erosion. Additionally, cash-for-work programs, like the one implemented in Khulna’s disaster-affected areas, could provide income and a sense of stability to those recovering from displacement. 5. Enhancing Community Resilience through Participatory Planning Community resilience is a critical factor in improving mental health outcomes. Participatory planning in disaster-prone areas should involve local residents in identifying their mental health needs and shaping policies. The Local Climate and Health Task Forces, which could be established in each Union Parishad, would allow affected communities to collaborate with local health departments and NGOs to design interventions that directly meet their needs. This approach has already shown success in Barisal, where communities actively participated in disaster preparedness and mental health initiatives, significantly improving the resilience of vulnerable populations. 6. Developing Sustainable Infrastructure to Prevent Displacement Displacement due to riverbank erosion is a significant cause of mental health issues in affected communities. Developing sustainable infrastructure such as climate-resilient housing can reduce displacement and its psychological impacts. For example, in Khulna, the Shushilan NGO has been working on eco-friendly embankments and sustainable housing solutions to mitigate the impacts of riverbank erosion. Similarly, partnerships between local governments and NGOs can be scaled up to build flood-resistant homes and embankments in erosion-prone regions, decreasing displacement rates and improving mental well-being. 6. Strengths and Limitations The study integrates numerical data to quantify the effects of riverbank erosion on mental health while also examining the socio-economic and environmental factors contributing to psychological distress. The use of quantitative data allows for precise estimates of PTSD and anxiety prevalence, providing a robust foundation for policy recommendations. Moreover, the study likely involves extensive engagement with local populations, ensuring their participation in the research process and enhancing the applicability of findings to affected communities. The results are expected to inform evidence-based interventions aimed at improving resilience and mental well-being among those impacted by erosion-induced displacement. However, research in isolated coastal regions, particularly areas vulnerable to riverbank erosion, presents logistical challenges, including restricted access, language barriers, and cultural sensitivities. These factors may affect data quality and completeness, potentially limiting the generalizability of findings. Future studies should explore mixed-method approaches to address these limitations and further contextualize the psychological impacts of climate-induced displacement. 7. Conclusion Riverbank erosion is one of the most noteworthy natural disasters that Bangladesh endured in recent years. Within the realm of science, the consequences of natural disasters on people's health have been the subject of substantial research. The physical and psychological effects of natural catastrophes are felt by millions of people all over the world, and these effects can be significant and potentially long-lasting. The impact of riverbank erosion in developing PTSD and anxiety wasn’t studied in Bangladesh. Hence, this study is carried out in the southwest region of Bangladesh to investigate the effect of riverbank erosion on the development of substantial mental health vulnerabilities, such as PTSD and anxiety. We have found that the prevalence of PTSD and anxiety were significantly higher among individuals affected by riverbank erosion. Along with that, middle aged individuals who came from joint families, age range between 30 to 49, illiterate and have monthly income below 10 thousand taka showed higher proportion of PTSD and anxiety. Following the devastating impact of riverbank erosion, people witnessed severe damage like losing livestock things, homeland and houses which make them vulnerable to developing PTSD, anxiety, insomnia and suicidal ideation. While coping with those impediments, social support was found significantly impactful to diminish the impact of riverbank erosion. The study's findings are expected to provide evidence-based suggestions and policy implications to enhance the mental well-being of those affected by riverbank erosion. Numerous initiatives like providing mental health care services and social support should be taken to minimize the post-natural disaster effect. Declarations Authors Statement: Contributor’s CREDiT statements for each Author MZK: Conceptualization and design, acquisition of data, analysis and interpretation of data, drafting the manuscript, and Approval of the version of the manuscript to be published. MA-M: Conceptualization and design, Acquisition of data, analysis and interpretation of data, revising the manuscript critically for important intellectual content, Approval of the version of the manuscript to be published. MP: Supervision, Analysis and interpretation of data, drafting the manuscript, Approval of the version of the manuscript to be published. MAE: Acquisition of data, analysis and interpretation of data, drafting the manuscript, Approval of the version of the manuscript to be published. AK: Validation, Conceptualization and design, revising the manuscript critically for important intellectual content, and Approval of the version of the manuscript to be published. Data Availability The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Funding Statement This study did not receive any specific funding. The authors declare that there were no financial relationships or conflicts of interest that could have influenced the study design, data collection, analysis, interpretation, writing of the manuscript, or the decision to submit it for publication. Provenance and peer review Not commissioned; externally peer reviewed. Data availability statement The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Disclosure The authors of the paper are not involved in any conflicts of interest. The authors of this research communication do not have any financial or personal relationships with other individuals or organizations that could potentially bias their work. Acknowledgments The authors express their heartfelt gratitude to the entire research team for their collective efforts and unwavering dedication throughout the study. Additionally, first author would like to express his sincere gratitude to his supervisors, Masuma Parvin , and Abul Kalam for their invaluable guidance and support throughout the research process, particularly in conducting this study. Special recognition is due to the lead Author, Md. Al-Mamun (Researcher at BIGD, BRAC University), whose exceptional passion for research and expertise in the field have been instrumental in the conception and completion of this work. His commitment to producing impactful research is deeply appreciated. Finally, the Authors also extend their sincere thanks to the editors and anonymous reviewers for their insightful comments and constructive suggestions, which have significantly enriched the quality and rigor of this manuscript. Disclosure The Authors of the paper are not involved in any conflicts of interest. Authors of this research communication does not have any financial or personal relationships with other individuals or organizations that could potentially bias their work. Transparency statement Md. Al-Mamun affirms that this manuscript is an honest, accurate, and transparent account of the study being reported, that no important aspects of the study have been omitted and that any discrepancies from the study as planned (and, if relevant, registered) have been explained. ORCID iD Md. Zawadul Karim: https://orcid.org/0009-0004-0656-5907 Md. Al-Mamun: https://orcid.org/0000-0002-4133-757X Maliha Azad Eva:https://orcid.org/0009-0007-3543-9450 Masuma Parvin: https://orcid.org/0000000293079429 Abul Kalam: https://orcid.org/0009-0006-8372-1840 References Akhter S, Eibek KU, Islam S, Towfiqul Islam AR, Md., Chu R, Shuanghe S (2019) Predicting spatiotemporal changes of channel morphology in the reach of Teesta River, Bangladesh using GIS and ARIMA modeling. 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Neuropsychiatr Dis Treat 13:2803–2812. https://doi.org/10.2147/NDT.S150444 Tables Table 1: Descriptive statistics of developing PTSD and Anxiety among exposed group and non-exposed group of riverbank erosion Characteristics Total(overall) 385 (100%) Exposed groups 280 (72.72%) Non exposed groups 105 (27.27%) Post traumatic stress disorder Normal 116 (30.12%) 24 (8.6%) 92 (87.61%) Symptoms present 269 (69.87%) 256 (91.4%) 13 (12.38%) Anxiety Normal 140 (36.36%) 42 (15%) 98 (93.3%) Symptoms present 245 (63.63%) 238 (85%) 7 (6.7%) Table-2: Mean difference of PTSD and Anxiety scores between exposed group and non-exposed group of riverbank erosion score Exposure status with River bank erosion N Mean SD t PTSD Yes 280 45.05 10.90 17.47* No 105 23.95 9.55 Anxiety Yes 280 10.64 2.87 15.06* No 105 5.98 2.22 **P<.001 *P<.05 Table-3: Descriptive analysis of demographic characteristics of both exposed and non-exposed group of riverbank erosion Characteristic Type Total(385) Exposed group (280) Non-exposed group (105) Gender Male 262 (68.05%) 206 (73.6%) 56 (53.3%) Female 123(31.94%) 74 (26.4%) 49 (46.7%) age 12-17 29 (7.53%) 17 (6.1%) 12(11.4%) 18-29 68 (17.66%) 42 (15%) 26(24.8%) 30-49 209 (54.28%) 173 (61.8) 36(34.3%) 50-64 43 (11.16%) 28 (10%) 15(14.3%) 65-above 36 (9.3%) 20 (7.1%) 16(25.2%) Education Educated 62 (9.51%) 33(11.8%) 29(27.6%) Illiterate 323 (83.90%) 247(88.2%) 76(72.4%) Profession Daily worker 99 (25.71%) 88 (31.4%) 11 (10.5%) Honey collector 52 (13.50%) 33 (11.8% 19 (18.1% Fisherman 96 (24.93%) 82 (29.3%) 14 (13.3%) Businessman 57 (14.80%) 27 (9.6%) 30 (28.6%) Housewife 65 (16.88%) 43 (15.4%) 22 (21%) student 16 (4.1%) 7 (2.5%) 9 (8.6%) Family type Nuclear 132 (34.28%) 82 (29.3%) 50 (47.6%) Joint Family 255 (66.23%) 198 (70.7%) 55 (52.4%) Monthly income 1-10k taka 228 (74.80%) 205 (73.2%) 23 (21.9%) 11-20k taka 81 (21.03%) 42 (15%) 39 (37.1%) 21-30k taka 56 (14.54%) 20 (7.1%) 36 (34.3%) 31k-above taka 20(5.19%) 13 (4.6%) 7 (6.7%) Social Class Lower class 263 (68.31%) 215 (76.8%) 48 (45.7%) Middle class 121 (31.42%) 64 (22.9%) 57(54.3%) Higher class 1 (.25%) 1 (.4%) 0(0%) Table-4: Bivariate distribution of PTSD and anxiety with socio-demographic factors Characteristic PTSD χ 2-value (p-value) Anxiety χ 2-value (p-value) No Yes No Yes Gender Male 67(25.6%) 195 (74.4%) 8.09 (0.145) 82(31.3%) 180 (68.7%) 8.21 (0.146) Female 49(39.8%) 74(60.2%) 57 (46.3%) 66 (53.7%) age 12-17 16(55.17%) 13 (44.82%) 24.75 (<0.001) 17 (58.6%) 12(41.4%) 21.29 (0.235) 18-29 30(44.11%) 38 (55.88%) 34(50%) 34(50%) 30-49 43(20.57%) 166 (79.42%) 57 (27.3%) 152(72.7%) 50-64 14(32.55%) 29 (53.48%) 14 (32.6%) 29(67.4%) 65-above 13(36.11%) 23 (63.88%) 17 (47.2%) 19(52.8%) Education Educated 32(51.6%) 30(48.4%) 16.20 (0.205) 37(59.7%) 25(40.3%) 17.80 (0.215) Illiterate 84(26.0%) 239 (74.0%) 102(31.6%) 221(68.4%) Profession Daily worker 22(22.2%) 77 (77.8%) 31.615 (0.287) 22 (22.2%) 77 (77.8%) 29.70 (0.278) Honey collector 18 (34.6%) 34 (65.4%) 20 (38.5%) 32 (61.5% Fisherman 15(15.6%) 81 (84.4%) 28 (29.2%) 68 (70.8%) Businessman 25(43.9%) 32 (56.1%) 27 (20.6%) 30 (36.4%) Housewife 25(38.5%) 40 (61.5%) 29 (44.6%) 36 (55.4%) student 11(68.8%) 5 (31.3%) 13 (81.3%) 3 (18.8%) Family type Nuclear 55(41.7%) 77 (58.3%) 12.70 (0.182) 64 (48.5%) 68 (51.5%) 13.34 (0.186) Joint Family 61(24.1%) 192 (75.9%) 75 (29.6%) 178 (74.4%) Monthly income 1-10k taka 41(18.0%) 187 (82.0%) 53.87 (0.374) 51 (22.4%) 177(77.6%) 55.59 (0.363) 11-20k taka 38 (46.9%) 43 (53.1%) 46 (56.8%) 35 (43.2%) 21-30k taka 34 (60.7%) 22 (39.3%) 35 (62.5%) 21 (37.5%) 31k-above taka 3 (15%) 17 (85%) 7 (35%) 13 (65%) Social Class Lower class 46 (41.1%) 66 (58.9%) 11.61 (0.174) 53(47.3%) 59 (52.7%) 10.65 (0.166) Middle class 69(25.4%) 203 (74.6%) 85(31.3%) 187(68.8%) Higher class 1(100%) 0 (0.0%) 1(100%) 0 (0.0%) Table-5: Mean difference of risk factors of river bank erosion in PTSD and Anxiety scores among exposed groups of river bank erosion Risk Factor Response (280) Exposed Group PTSD Anxiety M SD t M SD t Loss of livestock (death of cows, goats) Yes (178) (63.57%) 46.82 9.64 3.44* 10.97 2.54 2.40* No (102) (36.42%) 41.96 12.24 10.06 3.28 Received social support Yes (92) 32.85% 42.76 11.23 -2.48* 10.07 2.98 -2.34* No (188) 67.14% 46.17 10.58 10.92 2.77 Displacement Yes (181) 64.65% 47.31 9.44 4.54** 11.11 2.61 3.79** No (99) 35.36% 40.91 12.14 9.78 3.10 Persistent suicidal thought due to damage/loss Yes (104) 37.14% 51.23 8.78 8.44** 11.84 2.92 5.5** No (176) 62.8% 41.40 10.39 9.93 2.58 Continuous worry about the damage Yes (192) 68.57% 47.56 9.86 6.05** 11.26 2.69 5.57** No (88) 31.42% 39.58 11.08 9.30 2.77 **P<.001 *P<.05 Table-6: Means, standard deviations, and one way analysis of variance of PTSD and Anxiety in terms of level of disruption due to riverbank erosion Measure Exposed Group (280) F (2,277) Eta square Post- Hoc Level of Disruption Minimal (59) Moderate (158) Severe (63) M SD M SD M SD PTSD 37.50 10.93 45.45 9.77 51.22 9.43 28.74* 0.20 3>2>1 Anxiety 9.03 2.73 10.56 2.38 12.34 3.17 23.90* 0.173 3>2>1 **P<.001 *P<.05 Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 11 May, 2025 Reviewers invited by journal 03 Apr, 2025 Editor invited by journal 28 Feb, 2025 Editor assigned by journal 18 Feb, 2025 First submitted to journal 16 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Zawadul Karim","email":"","orcid":"","institution":"Rights Jessore","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Zawadul","lastName":"Karim","suffix":""},{"id":437783512,"identity":"2173c21c-52e4-4262-b579-ba7495a0757a","order_by":1,"name":"Md. Al-Mamun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYFCCBAjFLwEX4WGQwK4UTYvkDJK1GNwgVotuewLrhp85h/OMb/c+/PCzjUGev4H34A18WszOPGC72bvtcLHZnePGkr1tDIYzDvAlW+DVciOB7QbvtsOJ226kMUgztjEwbmDgMcPrMJCWm3+BWjbPSGP+DdRiT5SW2yBbNkiksYFsSSSs5czDttuy29ITZ9w5xmbZc04iecZhQn45nnzs5ttt1on9s9uYb/wos7Htb+/FH2IMDIwNyDygk5jxqx8Fo2AUjIJRQAQAAL9lS1ZW29jUAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4133-757X","institution":"BRAC Institute of Governance and Development","correspondingAuthor":true,"prefix":"","firstName":"Md.","middleName":"","lastName":"Al-Mamun","suffix":""},{"id":437783513,"identity":"23fb46ca-2e45-4664-9f86-809db2a0682b","order_by":2,"name":"Masuma Parvin","email":"","orcid":"","institution":"BSMRSTU: Bangabandhu Sheikh Mujibur Rahman Science and Technology University","correspondingAuthor":false,"prefix":"","firstName":"Masuma","middleName":"","lastName":"Parvin","suffix":""},{"id":437783514,"identity":"811a8be3-014c-4210-97f5-7c419a05c2ff","order_by":3,"name":"Maliha Azad Eva","email":"","orcid":"","institution":"Khulna University","correspondingAuthor":false,"prefix":"","firstName":"Maliha","middleName":"Azad","lastName":"Eva","suffix":""},{"id":437783515,"identity":"20042a3b-becf-4060-bdf5-9892db013d64","order_by":4,"name":"Abul Kalam","email":"","orcid":"","institution":"BSMRSTU: Bangabandhu Sheikh Mujibur Rahman Science and Technology University","correspondingAuthor":false,"prefix":"","firstName":"Abul","middleName":"","lastName":"Kalam","suffix":""}],"badges":[],"createdAt":"2025-02-16 19:43:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6042886/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6042886/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81933201,"identity":"0740b4e9-4149-4732-a000-258144c88b34","added_by":"auto","created_at":"2025-05-05 05:38:29","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":132612,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSelected study site’s map (\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eadapted from Islam et al.,2022a\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6042886/v1/7938bbb0fa405dd6f1d33186.jpg"},{"id":81933143,"identity":"8a7b9543-f031-407a-b41f-e0dfbba8fc04","added_by":"auto","created_at":"2025-05-05 05:38:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56772,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eGraphical representation of the prevalence rate of suicidal thought and worry among affected people\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6042886/v1/fc2caa6051f64edc27746c8b.png"},{"id":81936253,"identity":"9f8747d1-dd8e-4199-be4c-4150d5b23be5","added_by":"auto","created_at":"2025-05-05 06:07:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68988,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eGraphical representation of proportion of PTSD and Anxiety\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6042886/v1/2e0852769a454d771222ec5a.png"},{"id":81936256,"identity":"44c68b64-44e6-441a-8e5e-866a352c6d4e","added_by":"auto","created_at":"2025-05-05 06:07:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2105736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6042886/v1/febdb367-6e12-4688-bfec-f682599bbcb7.pdf"}],"financialInterests":"","formattedTitle":"Mental Health Consequences of Riverbank Erosion: Examining Anxiety and PTSD Among Affected Communities in Southwestern Bangladesh","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eA disaster is characterized as a significant disruption of a community's or society's normal functions, leading to considerable losses and impacts on individuals, property, or the environment that exceed the affected community's capacity to address with its available resources (UNISDR, 2009). Disasters primarily fall into two categories: Natural and human made disasters. Natural disasters arise from natural phenomena, such as storms, tidal waves, riverbank erosion and tropical storms (Saeed \u0026amp; Gargano, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAsia is perhaps the most disaster-prone region globally. A primary cause attributed to the elevated frequency of disasters in Asia is its geographical position (Kokai et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Among south Asia, it is especially South Asia that bears a disproportionate amount of the weight of natural disasters (Global Report on Internal Displacement, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In south Asia, Bangladesh is one of the most vulnerable nations to natural disasters due to its geographical and geophysical position, which puts it at increasing risk from the consequences of climate change (Islam \u003cem\u003eet al.\u003c/em\u003e,2021). This region experiences a rise in the occurrence of other hydro-meteorological coastal disasters, such as river bank erosion, waterlogging, and saline intrusion in the soil (Rakib \u003cem\u003eet al.\u003c/em\u003e,2019). Consequences of natural disasters on Bangladesh is immensely dangerous (Karim \u003cem\u003eet al.\u003c/em\u003e,2024). At the very least once per year, the nation is confronted with a natural disaster. People are frequently more susceptible to being affected by climate-related disasters because of their frequency, unpredictability, and uncertainties over their livelihoods, as well as the location and pattern of their settlements (Maurya, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Uddin \u0026amp; Haque, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong natural disasters, riverbank erosion is one of the prominent natural disasters of Bangladesh (Hasnat \u003cem\u003eet al.\u003c/em\u003e,2020; Islam \u0026amp; Rashid, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Bangladesh is a riverine country in Southeast Asia, a low-lying nation, has about 700 rivers and streams that run into the Bay of Bengal (Hamid, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Islam \u0026amp; Rashid,2012), where natural disasters like river bank erosion frequently occur due to its geographical location, terrain features, numerous rivers, and monsoonal climate (Wahiduzzaman \u0026amp; Yeasmin, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Riverbank erosion is intensified in certain regions by elevated tides, vigorous winds, and substantial waves mostly in rainy seasons in Bangladesh (Uddin and Basak, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Conversely, due to the sluggish water flow in delta regions, riverbank erosion may occur at any season (Kaiser, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). There are about 2400 km of riverbanks in Bangladesh (Hasnat \u003cem\u003eet al.\u003c/em\u003e,2020). The Bangladeshi River Management Board predicts that roughly 1200 km of riverbanks erode each year (Akter \u003cem\u003eet al.\u003c/em\u003e, 2019). A significant population in this region resides adjacent to the rivers and is thus more susceptible to bank erosion (Das et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Almost 30\u0026ndash;40% of the country's people live in places near rivers that are likely to be washed away by erosion (Paul \u003cem\u003eet al.\u003c/em\u003e,2021). In recent years, riverbank erosion has escalated by ten to twenty times in Bangladesh due to climate change and unanticipated human interference (Uddin and Basak, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHence, River bank erosion is paramount environmental disaster in Bangladesh (Islam \u003cem\u003eet al.\u003c/em\u003e,2011; Rahman et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Khatun et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) projected that if the trend of escalating the severity and frequency of catastrophes caused by nature persists, about 30,366,230 households in Bangladesh will be impacted by such events by 2030. The repercussions of extreme weather events not only drive migration and displacement but also affect the immediate determinants of both physical and mental health (Smith et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Effects of disasters on mental health\u003c/h2\u003e \u003cp\u003eThe effects of disasters on health have been extensively examined within scientific circles. Natural disasters impact millions globally, both physically and psychologically, with extensive and potentially enduring impacts (Makwana, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; WHO,2019). It is predominantly unforeseen, resulting in victims experiencing shock (Makwana, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Following which victims might induce a condition of hopelessness and trauma in themselves. This traumatic event affects the functioning lives of victims and results in developing Post traumatic stress disorder (Hackbarth \u003cem\u003eet al.\u003c/em\u003e,2012; Makwana, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Udomratn and Pichet (2008) provides a comprehensive examination of natural disasters in Asia. This study indicates that the prevalence of post-traumatic stress disorder and its symptoms among Asian survivors following a natural disaster range from 8.6\u0026ndash;57.3%. The incidence of post-traumatic stress disorder is common disorder among survivors of natural disaster (Udomratn and Pichet, 2008). PTSD is most commonly observed alongside anxiety, sadness, and other behavioral and psychological disorders following natural disasters (Makwana, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). So, increased anxiety is also concern for the victims of natural disasters (Rehdanz et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilar to other natural disasters, riverbank erosion has the same severe effect over people\u0026rsquo;s mental health. It was found that significant psychological distress was experienced by women in Bangladesh due to riverbank erosion (Keya and Harun ,2007). Similarly, the prevalence of depression, anxiety and stress was significantly higher among the people who were exposed to riverbank erosion due to losing various kinds of assets (such as house, land, livestock, etc.), and took narcotics to remove their stress/tension/frustration (Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Simultaneously, it has numerous adverse effects on residents, such as diminished academic achievement, health issues, and reduced social and financial standing (Alam \u003cem\u003eet al.\u003c/em\u003e,2020).\u003c/p\u003e \u003cp\u003eAlong with that riverbank erosion in Bangladesh contributes to livelihood unpredictability, including socio-economic instability, poverty, sickness, and significant mental health issues (Alam \u003cem\u003eet al.\u003c/em\u003e,2020). It has resulted in heightened levels of worry, stress, and depression among the majority of responders (SarzamArobi \u003cem\u003eet al.\u003c/em\u003e, 2019). and 8.75% respondents have suicidal ideation, 62% showed insomnia due to the damage following river bank erosion (Kaiser, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To cope with adversities, Individuals employ problem-solving and emotional coping strategies to acclimate to unfamiliar environments, simultaneously, social connections may provide significant resilience or the ability to withstand unpleasant situations (SarzamArobi \u003cem\u003eet al.\u003c/em\u003e, 2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Present study\u003c/h2\u003e \u003cp\u003eIn light of the existing research, it is apparent that numerous studies have been conducted in Bangladesh regarding riverbank erosion, albeit mental health related work is limited. Most of these studies concentrate on the socio-economic ramifications for the victims of riverbank erosion. Only a limited number of studies have examined the correlation between riverbank erosion and mental health factors. Vulnerable mental health outcomes, such as the development of post-traumatic stress disorder and elevated anxiety levels, have not been thoroughly investigated. Moreover, most of the studies followed qualitative methods, therefore, scale-based study to measure exact intensity of mental health outcomes due to riverbank erosion is missing. Furthermore, there is a lack of research focusing on the southern region of Bangladesh concerning the impact of riverbank erosion on mental health. Assuming the need to conduct research, which will give shed of light to the research gap regarding riverbank erosion and Bangladesh. Therefore, the main objective of this study is to know the impact of riverbank erosion in developing significant mental health vulnerabilities like PTSD, anxiety in south-western region of Bangladesh.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Methods","content":"\u003cp\u003eThis study adhered cross-sectional survey research design to conduct the research.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eThe study was carried out in a coastal union of Bangladesh named Gabura union. The Gabura Union (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is situated adjacent to the mangrove forest 'Sundarbans' in the Shyamnagar sub-district of Satkhira District. This Territory is surrounded by the Sundarbans mangrove forest on two sides. Two rivers traverse the study area: the Kopataska river flows along the north-western side, while the Kholpetua River meanders along the south-eastern side (Alam \u003cem\u003eet al.\u003c/em\u003e,2015).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure-1\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGabura was chosen as the study site due to its status as one of the most impacted unions in the severely afflicted region of Satkhira, resulting from the detrimental effects of natural disasters like river bank erosion (Rakib et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Respondents of the study\u003c/h2\u003e \u003cp\u003eTo comprehend the pattern of riverbank erosion of that, we delineated the present embankment condition by traversing the study region. To understand more precisely about the impact of riverbank erosion, we procured data from two groups of people. Data was collected from 385 residents aged between 12 to 65 years living permanently in this area for more than 15 years and having no previous diagnosed mental disorders. Among 385 participants, 280 participants were selected in exposed group (who are mostly impacted by river bank erosion) and 105 participants were selected in non-exposed group (who weren\u0026rsquo;t impacted by river bank erosion).Selection of people in exposed group is done based on following consideration (i) living river bank erosion prone area in Gabura union for more than 15 years (ii) Have been impacted severely due to river bank erosion(loss of house, livestock etc (iii) Having no previous diagnosed mental disorders. Simultaneously, Selection of people in non-exposed group is done based on following consideration (i) living non river bank erosion prone area (ii) Haven\u0026rsquo;t been impacted severely due to riverbank erosion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sampling procedure and methods\u003c/h2\u003e \u003cp\u003eFrom the end of May to the middle of July 2024, 385 respondents were randomly selected from our study locations. Study participants are selected using a multistage stratified sampling strategy for data. This process begins with the identification of coastal regions, along with their susceptibility that are vulnerable to riverbank erosion. The second step is to randomly select villages from the chosen Gabura union. Lastly, affected and non-affected members of the communities in the sampled areas are selected using random sampling. The study locations in Gabura union were selected using a simple random selection approach to guarantee that participants were from varied socio-economic backgrounds, ages, and occupations. In order to determine sample size, Cochran\u0026rsquo;s (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) most popular approach was used which we followed for the computation.\u003c/p\u003e \u003cp\u003eThe formula is\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:n\\:=\\:\\left[Z2P\\right(1-P\\left)\\right]/d2\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAccordingly, we have used p\u0026thinsp;=\u0026thinsp;0.5 \u003cem\u003eand a\u003c/em\u003e 95% confidence level (i.e., at least 5% precision) for setting the reliable and valid scale of confidence level, with the 95% confidence level representing Z values of 1.96 in the normal table. Moreover, a 5% margin of error has been projected. Based on these determinations, the sample size of this study was 385. A sample size of 385 people is deemed sufficient to detect significant impact if riverbank erosion over people\u0026rsquo;s mental health.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Study measurement\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eOutcome variables\u003c/strong\u003e \u003cp\u003eWhile measuring the mental health status of selected areas, three mental state such as PTSD and Anxiety were measured using valid scales. Therefore, PTSD and Anxiety are considered as outcome variables in this study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePost traumatic stress disorder\u003c/strong\u003e \u003cp\u003ePost-traumatic stress disorder (PTSD) is a condition that arises in certain individuals following exposure to a traumatic, frightening, or perilous incident (Resick et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). To assess PTSD symptoms, PCL-5 scale was used which is a 20-item self-report measure (Weathers et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). PCL-5 is a 5- point Likert scale ranging from 0 to 4 (0\u0026thinsp;=\u0026thinsp;Not at all 1\u0026thinsp;=\u0026thinsp;A little bit 2\u0026thinsp;=\u0026thinsp;Moderately 3\u0026thinsp;=\u0026thinsp;Quite a bit and 4\u0026thinsp;=\u0026thinsp;Extremely) where total severity score ranging between 0 and 80. The current investigation employed a cut-off score of \u0026ge;\u0026thinsp;33 to identify possible PTSD (Weathers et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).Bangla adapted version of this scale is used in this study to measure PTSD (Islam et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAnxiety\u003c/strong\u003e \u003cp\u003eAnxiety is a physiological reaction to a perceived threat, instigated by a person's beliefs, emotions, and ideas, and is marked with apprehensive emotions and tension (Park \u003cem\u003eet al.\u003c/em\u003e,2009). To assess anxiety, seven-item Generalized Anxiety Disorder (GAD-7) scale was used which was developed by Spitzer (Spitzer et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This scale consists of 7 items questions having a four-point Likert scale ranging from 0 (\u0026ldquo;Not at all\u0026rdquo;) to 3 (\u0026ldquo;Nearly every day\u0026rdquo;). A cutoff score of \u0026ge;\u0026thinsp;10 was utilized as a screening criterion for moderate to extremely severe anxiety, facilitating the assessment of anxiety presence among the people who took part in this study (Spitzer et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This study used Bangla adapted version (Redwan et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) of this scale.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRisk Factor /Predictor Variable\u003c/strong\u003e \u003cp\u003eThe prominent predictor (risk factor) of mental health state (PTSD and Anxiety) is whether an individual is exposed or non-exposed to riverbank erosion. In this investigation, the term exposed denoted that the interviewed person experienced severe damage due to riverbank erosion. In addition to the exposed status of river bank erosion, the variable included few risk factors like Loss of livestock (Yes/No), Drinking water problem (yes/No), Received social support (Yes/No), Displacement (Yes/No), Persistent suicidal thought (Yes/No), Continuous worry (Yes/No). Along with that, there was a paramount risk factor that elucidated the level of disruption (Minimal, Moderate, Severe) experienced by an individual due to riverbank erosion.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data tabulation and statistical analysis\u003c/h2\u003e \u003cp\u003eA substantial quantity of information and data was collected from the field investigation. The individuals who were interviewed were given the explicit assurance that their comments would be handled with the utmost discretion or confidentiality. The researcher and the person conducting the interview would be the only ones who were allowed to use the questionnaires. A comprehensive assessment of data and information was performed prior to analysis. IBM's SPSS 26 (Statistical Package for the Social Sciences) was utilized for the analysis of coded, screened, and cleaned data. To achieve the objectives outlined for the study, the researchers employed statistical analyses including descriptive statistics, chi squared test, independent sample t test and One-way Anova analysis according to the characteristics of the data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Ethical consideration\u003c/h2\u003e \u003cp\u003eWhile conducting a study, social researchers must consider the rights of the people involved (Baker et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Consequently, researchers must consider the ethical implications of their studies. This study was reviewed and approved by the Institutional Review Board (IRB) of the Department of Psychology, Gopalganj Science and Technology University (GSTU)-8100, Bangladesh (Approval Number: GSTU/SOC/IRB/2024/029). All procedures performed in this study involving human participants adhered to the ethical standards of the IRB at GSTU and the 1964 Helsinki Declaration (World Medical Association, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and its later amendments or comparable ethical standards.\u003c/p\u003e \u003cp\u003e Throughout this study, ethical standards were meticulously maintained at all stages. Respondents were provided with a comprehensive explanation about the objectives of the study. Before the conversation began, every single person gave their verbal agreement after receiving adequate information. This study adhered rigorously to all ethical standards, guaranteeing that no individuals suffered harm because of their participation.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eTable-1 depicts the prevalence of PTSD and anxiety in exposed group and non-exposed group with riverbank erosion. Among 385 individuals, there were 280 (72.72%) people who were exposed to river bank erosion, while 105 (27.27%) were included in non-exposed group. Overall rates of PTSD and anxiety were 69.87% and 63.63%. (see Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1 and table 2 showed that a higher prevalence of post-traumatic stress disorder (PTSD) and anxiety was seen in the exposed group, which had been adversely impacted by river bank erosion, compared to the non-exposed group (PTSD: 91.4% versus 12.38%, P\u0026thinsp;\u0026lt;\u0026thinsp;.001; Anxiety: 85% versus 6.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;.001) (see \u003cem\u003etable 2\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eAmong 385 participants, proportion of males (68.05%) are higher than female (31.94%) Most of the females were housewife (16.88%). In exposed group (280), mostly males (73.6%) and 26.4% females participated in this study. On the other hand, there were 53.3% male and 46.7% female who participated in non-exposed group. There are five different age groups in this study. Respondents with age group 30\u0026ndash;49 (54.28%) were higher than other age groups. The lowest number of respondents came from the 12\u0026ndash;17 age group (7.53%). Among participants, most them are illiterate (83.90%), come from joint family (66.23%) and do numerous work for living like fishing, honey collecting, doing household, business work etc. Only 9.51% of respondents were educated following which 4.1% were students. Due to its geographical location, respondents mostly were daily worker (25.71%) and fisherman (24.93%) (see \u003cem\u003etable 3\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eMost participants (68.31%) were from the lower class and earned 1-10k taka (74.80%) monthly. It was found that affected respondents had lower income as 73.2% of exposed group members reported a monthly income of 1-10k taka. In addition, most non-exposed participants earned 11-30k taka per month. Thus, 54.3% of non-exposed respondents were middle class (see \u003cem\u003etable 3\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eA chi-squared test was performed to know the associations of outcome variables such as PTSD, anxiety with socio-demographic factors, which is depicted in table \u0026minus;\u0026thinsp;4. It was depicted that the proportion of PTSD and anxiety was higher to male participants compared to female participants (PTSD: 74.4% versus 60.2%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.145; and Anxiety: 68.7% versus 53.7%, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.146). Prevalence of PTSD and anxiety was increased with the age, mostly people having middle age (30\u0026ndash;49) showed significantly higher PTSD (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and anxiety. In terms of education, illiterate people showed higher prevalence rate of PTSD and anxiety (PTSD: 74.0% versus 48.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.205; and Anxiety: 68.4% versus 40.3%, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.215).Moreover ,participants who are fisherman showed higher PTSD symptoms (84.4%) compared to other counterparts and participants who are daily worker showed higher proportion of anxiety symptoms (77.8%).Simultaneously, people who belongs from middle class, had lower monthly income (\u0026lt;\u0026thinsp;10k) and lived in joint family showed higher level of PTSD and anxiety symptoms (see \u003cem\u003etable 4\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eIn Table-5,we have found that 63.57% participants lost their livestock things ( death of cows, goats) due to river bank erosion and showed higher PTSD and anxiety than participants who didn\u0026rsquo;t lost their livestock properties (PTSD : M\u0026thinsp;=\u0026thinsp;46.82 versus 41.96, SD\u0026thinsp;=\u0026thinsp;9.64 versus 12.24, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;3.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 : Anxiety : M\u0026thinsp;=\u0026thinsp;10.97versus 10.06, SD\u0026thinsp;=\u0026thinsp;2.54 versus 3.28, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;2.40, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) .\u003c/p\u003e\n\u003cp\u003eBecause of river bank erosion, 64.65% participants in exposed group witnessed their displacement ( lost their house and living in government\u0026rsquo;s place) and demonstrated higher rate of PTSD and anxiety ( PTSD : M\u0026thinsp;=\u0026thinsp;47.31 versus 40.91, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;4.54, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), ( Anxiety : M\u0026thinsp;=\u0026thinsp;11.11 versus 9.78, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;3.79, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).Following the devastating effect of river bank erosion,68.7% participants having continuous worry regarding their damage showed elevated PTSD and anxiety (PTSD : M\u0026thinsp;=\u0026thinsp;47.56 versus 39.58, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;6.06, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 :Anxiety : M\u0026thinsp;=\u0026thinsp;11.26 versus 9.30, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;5.57, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) .\u003c/p\u003e\n\u003cp\u003eHaving witnessed all of these, Figure-2 showed that 37.14% of respondents elucidated about their suicidal thought while confronting those impediments following riverbank erosion. Individuals who got suicidal thought had an extreme level of PTSD (PTSD: M\u0026thinsp;=\u0026thinsp;51.23 versus 41.40, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;8.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and Anxiety ( Anxiety : M\u0026thinsp;=\u0026thinsp;11.84 versus 9.93, 95% CI ,t(278)\u0026thinsp;=\u0026thinsp;5.5, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) than people having no suicidal thought (see Fig. 2 \u003cem\u003eand table 5\u003c/em\u003e). Only 32.85% respondents receive social support in exposed group and it is evident that participant who got social support showed less symptoms of PTSD and anxiety (PTSD: M\u0026thinsp;=\u0026thinsp;42.76 versus 46.17, 95% CI, t (278) =-2.48, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), (Anxiety: M\u0026thinsp;=\u0026thinsp;10.07 versus 10.92, 95% CI, t (278) =-2.34, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) (see \u003cem\u003etable 5\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eA one-way between groups analysis of variance (ANOVA) was used to investigate the level of disruption (Minimal, Moderate, Severe) over affected people due to riverbank erosion on perceived PTSD and anxiety among exposed group of riverbank erosion. There was a statistically significant difference at the p\u0026thinsp;\u0026lt;\u0026thinsp;.05 level in PTSD and anxiety scores for the three groups: (PTSD: F (2,277)\u0026thinsp;=\u0026thinsp;28.74, P\u0026thinsp;=\u0026thinsp;0.20; Anxiety: F (2,277)\u0026thinsp;=\u0026thinsp;23.90, P\u0026thinsp;=\u0026thinsp;0.173). Post-hoc comparisons using the Tukey HSD test indicated that severe disruption groups showed highest proportion of PTSD and anxiety and groups with minimal disruption showed least proportion of PTSD and anxiety (PTSD:M\u0026thinsp;=\u0026thinsp;37.50 versus 45.45 versus 51.22, SD\u0026thinsp;=\u0026thinsp;10.93 versus 9.77 versus 9.43; Anxiety: M\u0026thinsp;=\u0026thinsp;9.03 versus 10.56 versus 12.34, SD\u0026thinsp;=\u0026thinsp;2.73 versus 2.38 versus 3.17) (see \u003cem\u003etable 6\u003c/em\u003e).\u003c/p\u003e"},{"header":"4. Discussions","content":"\u003cp\u003eThis study examines the impact of riverbank erosion on affected communities in the southwestern region of Bangladesh. Findings highlight a significant association between riverbank erosion and the development of PTSD and anxiety. Additionally, key risk factors such as loss of livestock, suicidal ideation, and persistent worry are prevalent among victims, further exacerbating their psychological distress.\u003c/p\u003e \u003cp\u003eThis study underscores the significant mental health burden of riverbank erosion in the southwestern region of Bangladesh. Our findings reveal a notably higher prevalence of PTSD and anxiety among individuals exposed to riverbank erosion compared to non-exposed populations (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These results align with previous studies conducted in Bangladesh (SarzamArobi et al., 2019) and other countries (Doherty \u0026amp; Clayton, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Munro et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which have consistently reported that exposure to environmental disasters increases psychological distress.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eConsistent with prior research (SarzamArobi et al., 2019; Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Kaiser, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), our findings confirm that severe exposure to riverbank erosion significantly heightens the risk of developing PTSD, anxiety, depression, and insomnia. A key contributing factor to these psychological vulnerabilities is the loss of essential assets, such as homes, land, and livestock, which exacerbates economic insecurity and emotional distress. Similar patterns were observed in past studies, where disaster-induced displacement and property loss were strongly linked to heightened mental health risks (Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Mahmud et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGender differences in mental health responses to disasters have been widely documented. While previous studies indicate that women exhibit higher levels of PTSD, depression, and anxiety following natural disasters (Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Mahmud et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), our findings suggest that males demonstrated a higher proportion of PTSD and anxiety symptoms post-riverbank erosion. This contrast may stem from the unique socio-economic pressures placed on men as primary earners in disaster-affected households. Further investigation is necessary to understand the nuanced gender-specific mental health impacts of riverbank erosion.\u003c/p\u003e \u003cp\u003eAge and educational status were also significant determinants of PTSD and anxiety. Middle-aged individuals (30\u0026ndash;49 years) exhibited the highest levels of distress, a trend similarly observed in previous studies (Chandra Das et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yeshaw \u0026amp; Mossie, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, our findings confirm that illiterate individuals are more susceptible to PTSD and anxiety than their educated counterparts, supporting evidence from Chandra Das et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Hoffmann \u0026amp; Blecha (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, this contradicts Asghari et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), who argued that mental health outcomes are not necessarily linked to education level. These discrepancies suggest that education may interact with other socio-economic factors to influence psychological resilience in disaster settings.\u003c/p\u003e \u003cp\u003eHousehold structure and economic status further influenced mental health outcomes. Individuals from joint families reported higher PTSD and anxiety symptoms, consistent with Hossain et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e), who found that living in large households amplifies mental health stressors in disaster-affected regions. Furthermore, lower-income individuals (earning\u0026thinsp;\u0026le;\u0026thinsp;10,000 Taka per month) exhibited significantly greater PTSD and anxiety symptoms than those earning above this threshold. This finding aligns with previous research (Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Rahman \u0026amp; Gain, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which suggests that financial stability serves as a protective factor against disaster-related psychological distress. Notably, fishermen and daily laborers faced the highest PTSD and anxiety levels, paralleling findings from Hossain et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e), where economically vulnerable groups, such as housewives and daily workers, were disproportionately affected.\u003c/p\u003e \u003cp\u003eLivestock loss emerged as a critical factor in exacerbating mental health distress. Participants who lost livestock exhibited significantly higher PTSD and anxiety symptoms compared to those who did not experience such losses. This finding mirrors previous studies (Moyna et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nayna Schwerdtle et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which reported that the destruction of livelihood assets heightened psychological distress among disaster survivors. Likewise, individuals displaced due to home loss demonstrated increased PTSD and anxiety levels, consistent with studies conducted in Bangladesh (Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e), Norway among migrants (Teodorescu et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and the British Isles among flood-affected populations (Munro et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAn overwhelming 68.5% of participants reported persistent worry following riverbank erosion, exacerbating PTSD and anxiety symptoms. This aligns with previous studies in Bangladesh, which highlighted excessive worry as a common post-disaster psychological response (Hossain et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Mostafizur Rahman et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, suicidal ideation was alarmingly prevalent, with 37.14% of affected individuals contemplating suicide. Those with suicidal thoughts exhibited significantly higher PTSD and anxiety symptoms, echoing findings from previous disaster-related studies that linked trauma exposure to hopelessness, grief, and increased suicide risk (Ozdemir et al., 2015; Tasdik Hasan et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo further analyze the association between disaster impact and psychological distress, we conducted a one-way ANOVA, which revealed that PTSD and anxiety levels varied significantly across different levels of disruption. Individuals who experienced severe disruption due to riverbank erosion exhibited the highest PTSD and anxiety symptoms, supporting existing evidence that greater disaster exposure correlates with higher mental health risks (Boden et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Saeed \u0026amp; Gargano, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This trend was also observed in moderate disruption groups, who exhibited higher PTSD and anxiety levels than those with minimal disruption, reinforcing the dose-response relationship between disaster exposure and psychological distress. Finally, social support emerged as a crucial mitigating factor. Individuals who received social support reported lower PTSD and anxiety symptoms compared to those without support, consistent with findings from McGuire et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Mostafizur Rahman et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These results emphasize the importance of community-based interventions, mental health support systems, and targeted policies to address the psychological consequences of riverbank erosion.\u003c/p\u003e"},{"header":"5. Policy recommendations","content":"\u003cp\u003eNatural catastrophes pose a significant threat to Bangladesh\u0026rsquo;s healthcare system, which is now unprepared to handle an influx of patients. When it comes to mental health treatment, Bangladesh's national adaptation plans fall short. There are no guidelines or budget details regarding how to proceed with the impact of natural disasters in coastal regions. As a result, we witnessed the health consequences of natural catastrophes on multiple levels, from the personal to the societal to the institutional. The findings of this study underscore the need for urgent local-level policy interventions to address the mental health crisis faced by communities affected by riverbank erosion. Despite national recognition of climate-induced displacement, localized mental health strategies remain insufficient. Considering resource constraints and the existing administrative framework in Bangladesh, the following feasible policy measures are recommended, with examples to illustrate potential success:\u003c/p\u003e\n\u003ch3\u003e1. Integrating Mental Health Services into Local Health Systems\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRiverbank erosion-affected communities often face immense psychological distress, which must be addressed at the local level. Integrating mental health services into local health systems will be key. For instance, the Upazila Health Complexes (UHCs) and Union Health and Family Welfare Centers (UHFWCs) should incorporate mental health screenings and provide psychosocial support as part of their routine services. Community health workers (CHWs) and local doctors can be trained to provide psychological first aid in these areas. A relevant example can be seen in Jashore district, where the Shushilan NGO has worked with UHCs to integrate mental health care for displaced populations due to riverbank erosion.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e2. Capacity Building for Local Government and Community Volunteers\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eLocal governance structures such as Union Parishads and Union Disaster Management Committees (UDMCs) should be trained to address mental health needs in the aftermath of disasters. For example, the Cyclone Preparedness Program (CPP) in the coastal regions has trained volunteers to provide immediate support during cyclones. These volunteers could be further trained in psychosocial support to recognize signs of PTSD and anxiety among the affected population. This could be modeled after the Community Mental Health Program in Cox\u0026rsquo;s Bazar, where community-based volunteers were trained to identify and assist individuals dealing with mental health issues post-displacement.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e3. Establishing Mobile Mental Health Units in High-Risk Areas\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo reach remote and hard-to-reach populations affected by riverbank erosion, mobile mental health units can provide immediate psychological support. This model has been successfully implemented by BRAC in rural parts of Bangladesh, where mobile health clinics were deployed to address both physical and mental health needs of people displaced by flooding. These mobile units could visit coastal areas affected by riverbank erosion on a rotational basis, offering counseling, therapy, and referrals to specialized mental health services.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e4. Strengthening Social Safety Nets for Disaster-Affected Families\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFinancial instability exacerbates mental health issues in disaster-affected areas. Strengthening social safety nets and offering livelihood support can reduce anxiety and stress. For example, the Government of Bangladesh\u0026rsquo;s Vulnerable Group Development (VGD) program, which provides food and cash support to vulnerable communities, could be expanded to include mental health services for those displaced by riverbank erosion. Additionally, cash-for-work programs, like the one implemented in Khulna\u0026rsquo;s disaster-affected areas, could provide income and a sense of stability to those recovering from displacement.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e5. Enhancing Community Resilience through Participatory Planning\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eCommunity resilience is a critical factor in improving mental health outcomes. Participatory planning in disaster-prone areas should involve local residents in identifying their mental health needs and shaping policies. The Local Climate and Health Task Forces, which could be established in each Union Parishad, would allow affected communities to collaborate with local health departments and NGOs to design interventions that directly meet their needs. This approach has already shown success in Barisal, where communities actively participated in disaster preparedness and mental health initiatives, significantly improving the resilience of vulnerable populations.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e6. Developing Sustainable Infrastructure to Prevent Displacement\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDisplacement due to riverbank erosion is a significant cause of mental health issues in affected communities. Developing sustainable infrastructure such as climate-resilient housing can reduce displacement and its psychological impacts. For example, in Khulna, the Shushilan NGO has been working on eco-friendly embankments and sustainable housing solutions to mitigate the impacts of riverbank erosion. Similarly, partnerships between local governments and NGOs can be scaled up to build flood-resistant homes and embankments in erosion-prone regions, decreasing displacement rates and improving mental well-being.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"6. Strengths and Limitations","content":"\u003cp\u003eThe study integrates numerical data to quantify the effects of riverbank erosion on mental health while also examining the socio-economic and environmental factors contributing to psychological distress. The use of quantitative data allows for precise estimates of PTSD and anxiety prevalence, providing a robust foundation for policy recommendations. Moreover, the study likely involves extensive engagement with local populations, ensuring their participation in the research process and enhancing the applicability of findings to affected communities. The results are expected to inform evidence-based interventions aimed at improving resilience and mental well-being among those impacted by erosion-induced displacement.\u003c/p\u003e \u003cp\u003eHowever, research in isolated coastal regions, particularly areas vulnerable to riverbank erosion, presents logistical challenges, including restricted access, language barriers, and cultural sensitivities. These factors may affect data quality and completeness, potentially limiting the generalizability of findings. Future studies should explore mixed-method approaches to address these limitations and further contextualize the psychological impacts of climate-induced displacement.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eRiverbank erosion is one of the most noteworthy natural disasters that Bangladesh endured in recent years. Within the realm of science, the consequences of natural disasters on people's health have been the subject of substantial research. The physical and psychological effects of natural catastrophes are felt by millions of people all over the world, and these effects can be significant and potentially long-lasting. The impact of riverbank erosion in developing PTSD and anxiety wasn\u0026rsquo;t studied in Bangladesh. Hence, this study is carried out in the southwest region of Bangladesh to investigate the effect of riverbank erosion on the development of substantial mental health vulnerabilities, such as PTSD and anxiety. We have found that the prevalence of PTSD and anxiety were significantly higher among individuals affected by riverbank erosion. Along with that, middle aged individuals who came from joint families, age range between 30 to 49, illiterate and have monthly income below 10 thousand taka showed higher proportion of PTSD and anxiety. Following the devastating impact of riverbank erosion, people witnessed severe damage like losing livestock things, homeland and houses which make them vulnerable to developing PTSD, anxiety, insomnia and suicidal ideation. While coping with those impediments, social support was found significantly impactful to diminish the impact of riverbank erosion. The study's findings are expected to provide evidence-based suggestions and policy implications to enhance the mental well-being of those affected by riverbank erosion. Numerous initiatives like providing mental health care services and social support should be taken to minimize the post-natural disaster effect.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors Statement: Contributor\u0026rsquo;s CREDiT statements for each Author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMZK: Conceptualization and design, acquisition of data, analysis and interpretation of data, drafting the manuscript, and Approval of the version of the manuscript to be published.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMA-M: Conceptualization and design, Acquisition of data, analysis and interpretation of data, revising the manuscript critically for important intellectual content, Approval of the version of the manuscript to be published.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMP: Supervision, Analysis and interpretation of data, drafting the manuscript, Approval of the version of the manuscript to be published.\u003c/p\u003e\n\u003cp\u003eMAE: Acquisition of data, analysis and interpretation of data, drafting the manuscript, Approval of the version of the manuscript to be published.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAK: Validation, Conceptualization and design, revising the manuscript critically for important intellectual content, and Approval of the version of the manuscript to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any specific funding. The authors declare that there were no financial relationships or conflicts of interest that could have influenced the study design, data collection, analysis, interpretation, writing of the manuscript, or the decision to submit it for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProvenance and peer review\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot commissioned; externally peer reviewed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors of the paper are not involved in any conflicts of interest. The authors of this research communication do not have any financial or personal relationships with other individuals or organizations that could potentially bias their work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their heartfelt gratitude to the entire research team for their collective efforts and unwavering dedication throughout the study. Additionally, first author would like to express his sincere gratitude to his supervisors,\u0026nbsp;\u003cem\u003eMasuma Parvin\u003c/em\u003e, and\u0026nbsp;\u003cem\u003eAbul Kalam\u003c/em\u003e for their invaluable guidance and support throughout the research process, particularly in conducting this study. Special recognition is due to the lead Author,\u0026nbsp;\u003cem\u003eMd. Al-Mamun\u003c/em\u003e (Researcher at BIGD, BRAC University), whose exceptional passion for research and expertise in the field have been instrumental in the conception and completion of this work. His commitment to producing impactful research is deeply appreciated. Finally, the Authors also extend their sincere thanks to the editors and anonymous reviewers for their insightful comments and constructive suggestions, which have significantly enriched the quality and rigor of this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Authors of the paper are not involved in any conflicts of interest. Authors of this research communication does not have any financial or personal relationships with other individuals or organizations that could potentially bias their work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransparency statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMd. Al-Mamun affirms that this manuscript is an honest, accurate, and transparent account of the study being reported, that no important aspects of the study have been omitted and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eORCID iD \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMd. Zawadul Karim: https://orcid.org/0009-0004-0656-5907\u003c/p\u003e\n\u003cp\u003eMd. Al-Mamun: https://orcid.org/0000-0002-4133-757X\u003c/p\u003e\n\u003cp\u003eMaliha Azad Eva:https://orcid.org/0009-0007-3543-9450\u003c/p\u003e\n\u003cp\u003eMasuma Parvin: https://orcid.org/0000000293079429\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbul Kalam: https://orcid.org/0009-0006-8372-1840\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkhter S, Eibek KU, Islam S, Towfiqul Islam AR, Md., Chu R, Shuanghe S (2019) Predicting spatiotemporal changes of channel morphology in the reach of Teesta River, Bangladesh using GIS and ARIMA modeling. 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\u003cp\u003e\u003cstrong\u003eTotal(overall)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e385 (100%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposed groups\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e280 (72.72%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon exposed groups\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e105 (27.27%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost traumatic stress disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.28%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.28%;\"\u003e\n \u003cp\u003e116 (30.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e24 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e92 (87.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.28%;\"\u003e\n \u003cp\u003e269 (69.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e256 (91.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e13 (12.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.28%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.28%;\"\u003e\n \u003cp\u003e140 (36.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e42 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e98 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptoms present\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.28%;\"\u003e\n \u003cp\u003e245 (63.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e238 (85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.96%;\"\u003e\n \u003cp\u003e7 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable-2: Mean difference of PTSD and Anxiety scores between exposed group and non-exposed group of riverbank erosion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"641\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003escore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposure status with\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRiver bank erosion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e45.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e10.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e17.47*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e23.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e9.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e10.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e15.06*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e**P\u0026lt;.001 *P\u0026lt;.05\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable-3: Descriptive analysis of demographic characteristics of both exposed and non-exposed group of riverbank erosion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"649\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal(385)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposed group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; (280)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-exposed group \u0026nbsp; \u0026nbsp; \u0026nbsp; (105)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e262 (68.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e206 (73.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e56 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e123(31.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e74 (26.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e49 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e12-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e29 (7.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e17 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e12(11.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e18-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e68 (17.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e42 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e26(24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e30-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e209 (54.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e173 (61.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e36(34.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e50-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e43 (11.16%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e28 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e15(14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e65-above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e36 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e20 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e16(25.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eEducated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e62 (9.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e33(11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e29(27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e323 (83.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e247(88.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e76(72.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProfession\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eDaily worker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e99 (25.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e88 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e11 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eHoney collector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e52 (13.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e33 (11.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e19 (18.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eFisherman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e96 (24.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e82 (29.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e14 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eBusinessman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e57 (14.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e27 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e30 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e65 (16.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e43 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e22 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003estudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e16 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e7 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e9 (8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFamily type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eNuclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e132 (34.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e82 (29.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e50 (47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eJoint Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e255 (66.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e198 (70.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e55 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e1-10k taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e228 (74.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e205 (73.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e23 (21.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e11-20k taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e81 (21.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e42 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e39 (37.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e21-30k taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e56 (14.54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e20 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e36 (34.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e31k-above taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e20(5.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e13 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e7 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Social Class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eLower class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e263 (68.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e215 (76.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e48 (45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eMiddle class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e121 (31.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e64 (22.9%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e57(54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eHigher class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e1 (.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e1 (.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e0(0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable-4: Bivariate distribution of PTSD and anxiety with socio-demographic factors\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e2-value\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(p-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e2-value\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(p-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e67(25.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e195 (74.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e8.09\u003c/p\u003e\n \u003cp\u003e(0.145)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e82(31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e180 (68.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e8.21\u003c/p\u003e\n \u003cp\u003e(0.146)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e49(39.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e74(60.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e57 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e66 (53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e12-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e16(55.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e13 (44.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e24.75\u003c/p\u003e\n \u003cp\u003e(\u0026lt;0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e17 (58.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e12(41.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e21.29\u003c/p\u003e\n \u003cp\u003e(0.235)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e18-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e30(44.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e38 (55.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e34(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e34(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e30-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e43(20.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e166 (79.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e57 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e152(72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e50-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e14(32.55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e29 (53.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e14 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e29(67.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e65-above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e13(36.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e23 (63.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e17 (47.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e19(52.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eEducated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e32(51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e30(48.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e16.20\u003c/p\u003e\n \u003cp\u003e(0.205)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e37(59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e25(40.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e17.80\u003c/p\u003e\n \u003cp\u003e(0.215)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e84(26.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e239 (74.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e102(31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e221(68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProfession\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eDaily worker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e22(22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e77 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e31.615\u003c/p\u003e\n \u003cp\u003e(0.287)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e22 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e77 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e29.70\u003c/p\u003e\n \u003cp\u003e(0.278)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eHoney collector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e18 (34.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e34 (65.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20 (38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e32 (61.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eFisherman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e15(15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e81 (84.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e28 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e68 (70.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eBusinessman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e25(43.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e32 (56.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e27 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e30 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e25(38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e40 (61.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e29 (44.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e36 (55.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003estudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e11(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e5 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e13 (81.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFamily type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eNuclear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e55(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e77 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e12.70\u003c/p\u003e\n \u003cp\u003e(0.182)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e64 (48.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e68 (51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e13.34\u003c/p\u003e\n \u003cp\u003e(0.186)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eJoint Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e61(24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e192 (75.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e75 (29.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e178 (74.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1-10k taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e41(18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e187 (82.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e53.87\u003c/p\u003e\n \u003cp\u003e(0.374)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e51 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e177(77.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e55.59\u003c/p\u003e\n \u003cp\u003e(0.363)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e11-20k taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e38 (46.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e43 (53.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e46 (56.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e35 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e21-30k taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e34 (60.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e22 (39.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e35 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e21 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e31k-above taka\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e17 (85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e13 (65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial Class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eLower class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e46 (41.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e66 (58.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11.61\u003c/p\u003e\n \u003cp\u003e(0.174)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e53(47.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e59 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e10.65\u003c/p\u003e\n \u003cp\u003e(0.166)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMiddle class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e69(25.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e203 (74.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e85(31.3%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e187(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eHigher class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable-5: Mean difference of risk factors of river bank erosion in PTSD and Anxiety scores among exposed groups of river bank erosion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResponse\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(280)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 421px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eExposed Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 224px;\"\u003e\n \u003cp\u003ePTSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eAnxiety\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLoss of livestock (death of cows, goats)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eYes (178)\u003c/p\u003e\n \u003cp\u003e(63.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e46.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e9.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e3.44*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e10.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.40*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eNo (102)\u003c/p\u003e\n \u003cp\u003e(36.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e41.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e12.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e10.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceived social support\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eYes (92)\u003c/p\u003e\n \u003cp\u003e32.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e42.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e11.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e-2.48*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e10.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e-2.34*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eNo (188)\u003c/p\u003e\n \u003cp\u003e67.14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e46.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e10.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDisplacement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eYes (181)\u003c/p\u003e\n \u003cp\u003e64.65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e47.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e9.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e4.54**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e11.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e3.79**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eNo (99)\u003c/p\u003e\n \u003cp\u003e35.36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e40.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e12.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e9.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersistent suicidal thought due to damage/loss\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eYes (104)\u003c/p\u003e\n \u003cp\u003e37.14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e51.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e8.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e8.44**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e11.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e5.5**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eNo (176)\u003c/p\u003e\n \u003cp\u003e62.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e41.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e10.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e9.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eContinuous worry about the damage\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eYes (192)\u003c/p\u003e\n \u003cp\u003e68.57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e47.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e9.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e6.05**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e11.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e5.57**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eNo (88)\u003c/p\u003e\n \u003cp\u003e31.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e39.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e11.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e**P\u0026lt;.001 *P\u0026lt;.05\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable-6: Means, standard deviations, and one way analysis of variance of PTSD and Anxiety in terms of level of disruption due to riverbank erosion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"636\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 393px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExposed Group (280)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(2,277)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEta square\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost- Hoc\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 393px;\"\u003e\n \u003cp\u003eLevel of Disruption\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMinimal (59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;(158)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp; Severe\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;(63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e37.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e10.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e45.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e9.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e51.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e9.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e28.74*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u0026gt;2\u0026gt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e9.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e10.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e12.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e23.90*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u0026gt;2\u0026gt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e**P\u0026lt;.001 *P\u0026lt;.05\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Riverbank erosion, PTSD, anxiety, mental health, displacement, Bangladesh","lastPublishedDoi":"10.21203/rs.3.rs-6042886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6042886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNatural disasters, including tropical cyclones, tidal surges, and riverbank erosion, pose severe environmental and socio-economic challenges. Among these, riverbank erosion has emerged as a critical issue in Bangladesh, leading to both physical displacement and psychological distress. Despite its far-reaching consequences, limited research has examined the mental health impacts of riverbank erosion, particularly in relation to anxiety and post-traumatic stress disorder (PTSD). This cross-sectional study investigates the prevalence and determinants of anxiety and PTSD among communities affected by riverbank erosion in the southwestern region of Bangladesh, specifically in Gabura Union, located in the Shyamnagar sub-district of Satkhira District. The study was conducted between May and July 2024, using a multistage stratified sampling strategy. A total of 385 residents, aged 12 to 65 years, who have lived in the area for more than 15 years and have no previous diagnosed mental disorders, were surveyed. Among these, 280 were exposed to severe riverbank erosion, while 105 were not. Data were collected using valid scales for PTSD (PCL-5) and anxiety (GAD-7), and key risk factors, such as loss of livestock, displacement, and social support, were also assessed. Findings reveal that 63.63% of participants experienced anxiety, while 69.87% exhibited symptoms of PTSD, with significantly higher prevalence among those directly impacted by erosion. Vulnerability was particularly pronounced among middle-aged individuals (30\u0026ndash;49 years), those from joint families, illiterate individuals, and those earning less than 10,000 Taka per month. The erosion-induced devastation resulted in 63.57% of respondents losing livestock and 64.65% experiencing displacement, exacerbating risks of PTSD, anxiety, insomnia, and suicidal ideation. However, social support played a crucial role in mitigating psychological distress. The study underscores the urgent need for targeted mental health interventions and social assistance programs to support affected populations. Policy measures should focus on enhancing resilience through community-based mental health care and sustainable social protection strategies.\u003c/p\u003e","manuscriptTitle":"Mental Health Consequences of Riverbank Erosion: Examining Anxiety and PTSD Among Affected Communities in Southwestern Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 05:38:18","doi":"10.21203/rs.3.rs-6042886/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-05-11T06:46:42+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-03T07:00:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Natural Hazards","date":"2025-02-28T17:09:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-18T09:54:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"Natural Hazards","date":"2025-02-16T14:42:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"39023f8e-7405-49de-959a-1e34c7c0b923","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T05:38:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-05 05:38:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6042886","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6042886","identity":"rs-6042886","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}