This study employed a cross-sectional survey design to assess the impact of the 2022 flash flood on men’s mental health in two flood-prone Upazilas of Bangladesh, Ajmiriganj and Dharmapasha. We utilized the Depression, Anxiety, and Stress Scale-21 (DASS-21) to evaluate mental health conditions. A structured questionnaire was administered through face-to-face interviews to collect data on mental health status and associated sociodemographic and flood-related variables. Descriptive statistics and multiple linear regression analyses were applied to examine the association between mental health conditions and various risk factors. Ethical approval for the study was obtained from the Institutional Review Board of Khulna University.

This cross-sectional study examined the impact of the 2022 floods on two remote Upazilas of Bangladesh: Ajmiriganj and Dharmapasha. Figure 1 shows the locations of these Upazilas, with Ajmiriganj situated in the Habiganj District and Dharmapasha in Sunamganj. The rising water levels of the Khowai, Kushiyara-Kalni rivers, and haors (a type of wetland found in northeastern Bangladesh and parts of India. It is a large, bowl-shaped depression that fills with water during the monsoon season, creating a unique ecosystem. These areas are prone to seasonal flooding, which can have significant impacts on agriculture and livelihoods. Haors are vital for biodiversity, but their floods can be devastating to communities living in or near them) inundating the low-lying areas of Ajmiriganj in Habiganj District. Haors are large, bowl-shaped depressions that fill with water during the monsoon season, creating unique ecosystems. While vital for biodiversity, these areas are prone to seasonal flooding, which can severely impact agriculture and local livelihoods.

In 2022, the floods not only submerged vast areas but also cut off communication and electricity supplies to neighboring areas for several days. The floodwaters severely affected Dharmapasha Upazila, trapping people and damaging road infrastructure. Ajmiriganj Upazila has a population of 114,265, with 56,615 men and 57,650 women, covering a total area of 223.98 km² (27). The male literacy rate in Ajmiriganj is 39.5%, while the female literacy rate is 34.7% for individuals aged seven and older (27). Men in this Upazila primarily work in agriculture, while many women either stay at home or are not employed outside the household. Dharmapasha Upazila has a population of 243,464, with 122,300 men and 121,164 women, and covers an area of 531.00 km² (28). The literacy rate in Dharmapasha is 29.2%, with 30.6% of men and 27.7% of women being literate (27). The majority of residents in both Upazilas rely on agriculture for their livelihood.

The 2022 flash floods in Habiganj District affected 83,390 individuals, with Ajmiriganj being the hardest-hit area (29). The total economic loss in the district was estimated at 5000 million Bangladeshi Taka (approximately 47 million USD), with the most significant losses in infrastructure, education, livestock, agriculture, and fisheries. Most of Ajmiriganj, including its roads, was submerged, leading to a prolonged school closure (30). Similarly, the floods in Dharmapasha submerged around 965 hectares of agricultural land, leading to significant financial losses for local farmers (31). The overall damage to crops in Sunamganj District, including Dharmapasha, amounted to one billion Bangladeshi Taka (approximately nine million USD) (32). Road closures and power disruptions further exacerbated the difficulties faced by flood victims in Dharmapasha Upazila (33).

We conducted a structured survey using face-to-face interviews in the local Bengali language to ensure clarity and comprehension, particularly for illiterate respondents. The questionnaire consisted of closed-ended and Likert-scale questions, including the DASS-21 instrument (34), to assess depression, anxiety, and stress levels. The survey also gathered sociodemographic information, previous flood experiences, and perceptions of flood safety.

The survey was conducted in July–August 2022, after the floodwaters had receded enough to allow access to affected areas. However, some regions were still in recovery, and the flood had a significant impact on the data collection process. Many roads remained damaged or submerged, requiring the research team to use boats and alternative routes to reach certain villages. Some participants were initially hesitant to participate due to their ongoing struggles with property loss, income disruptions, and health concerns. To address these challenges, we collaborated with local community leaders who helped facilitate participant engagement. Despite these difficulties, the survey team successfully conducted in-person interviews, ensuring that responses were gathered from a diverse group of flood-affected individuals.

Seven items comprise each subscale of DASS-21. It was used in various research (35–37). On a four-point Likert scale, 0 means “Did not apply to me at all,” 1 means “Applied to me to some degree, or some of the time-Sometimes,” 2 means “Applied to me to a considerable degree, or a good part of the time-Often,” and 3 means “Applied to me very much or most of the time-Almost always.” Participants had to describe symptoms from the previous week. Add and double the applicable item scores for depression, stress, and anxiety to get the scores. For DASS-21 scores, there are five cutoff points: normal, mild, moderate, severe, and extremely severe (Table 1). The DASS helps measure symptom severity and therapy response.

The questionnaire’s final version (in KoboToolbox) incorporates comments from a preliminary survey of certain research participants. Early survey responses were not included in the final study. Cronbach’s alphas are more than 0.80 in all three of the pretested DASS sections, indicating reliability. Current alpha values are close to previous authors’ standards (34). If the value of Cronbach’s alpha exceeds 0.60, then the survey’s internal consistency is considered reliable (38, 39). The questionnaire has four main components. In the first part, we covered demographics (age, marital status, education, location, housing type, occupation, vulnerable family member, and chronic condition). We asked, “How do you perceive your current social life?” concerning social satisfaction. Respondents were questioned in the third part about their past flood experiences prior to the 2022 flood., if their current location was safe from flooding, if they had been injured or ill from the recent flash flood if they had lost a family member, and if they had income problems. This research examined if the flood damaged property. We utilized participant demographics and flood data as independent variables. We anticipated these factors would affect all three DASS components. We then asked DASS-21 questions. Self-reported questionnaires were initially developed (34). Most participants were illiterate or uneducated. We asked questions to get self-reported answers. In certain research, DASS-21 was utilized in face-to-face interviews (40–42). We utilized a tested Bengali form of DASS-21 (43). In our earlier study, we used this tool successfully with the general community during COVID-19 (36). Participants understood our questions. We’ve worked with these participants (44). Our pilot survey also enhanced question clarity.

Participants for this study were selected using a combination of convenience and snowball sampling techniques. Initially, we approached adult male residents (aged 18 years or older) from Ajmiriganj and Dharmapasha Upazilas who had been directly affected by the 2022 flash flood. The first participant was identified through community contacts and local key informants. Following this, snowball sampling was used, where each respondent was asked to refer other potential participants who met the study criteria. In the convenience sampling technique, participants were selected based on their availability and willingness to participate. This method facilitated quick data collection from those directly affected by the flood. In the case of the snowball sampling technique, initial participants referred other potential respondents from their social networks, ensuring a broader representation of affected individuals. The sample size was determined using Krejcie and Morgan’s (45) table, which provides an established guideline for selecting an appropriate number of respondents. For a population exceeding 10,000 individuals, a sample size of 384 participants is deemed statistically adequate. To enhance reliability and account for potential non-responses, we increased the sample size to 452 participants.

Data analysis was conducted using R software (version 4.2.2) and Python (version 2.7) (46, 47), following a two-step regression approach. First, simple linear regression (bivariate analysis) was performed, where each independent variable was tested separately against the three mental health outcomes—depression, anxiety, and stress—to identify significant associations (p < 0.05). In the second step, multiple linear regression (multivariate analysis) was conducted, incorporating only those variables that were statistically significant in the bivariate analysis. Three separate multiple linear regression models were developed, with depression, anxiety, and stress as the respective dependent variables. Each model included selected sociodemographic and flood-related factors as independent variables to assess their associations with mental health conditions. The results were reported using beta coefficients (β), confidence intervals (CI), and p-values to determine statistical significance.

An ethical certification committee associated with Khulna University in Bangladesh has approved this research (Ref. No. KUECC-2022/06/16) after reviewing our objectives and method. This study followed the Declaration of Helsinki and its revisions regarding human subject usage (48). Informed consent was obtained from all participants. For those who were illiterate, consent was verbally explained in Bengali, and their agreement was documented with their permission.

Table 2 presents the sociodemographic data of the study participants. Approximately 33% of the sample population was between 36 and 55 years old, followed by 24% in the 18–35 age group, with the remaining participants spread across other age groups. The majority (94%) of participants were married. A significant portion of the population was illiterate or had not completed secondary school, which aligns with the low male literacy rates reported in previous Upazila data (27). Our findings, similar to prior research (49), confirm that men in this area tend to have higher education levels than women. Previous studies indicated that 74% of women in these Upazilas are uneducated (49). Most participants lived in semi-pucca dwellings, and more than half of them were employed as agricultural farmers or fishermen.

Table 3 summarizes the flood-related facts and impacts. A significant number of participants had experienced floods before the 2022 event. Around 55% of participants considered their homes vulnerable to flooding, which is consistent with the regular flooding in these areas (50). They are generally well aware of local flood risks. The 2022 flash flood caused injuries to 13 and 10% of participants’ families. Furthermore, 92% of participants or their families lost income due to the flood, and 95% reported damage to their property. It aligns with a similar report detailing the impacts of the 2022 floods in the region (51). Despite these hardships, most participants received financial and social assistance during the flood event.

The findings presented in Figure 2 shed light on the mental health status of the research participants, focusing on levels of depression, anxiety, and stress. The mean scores for depression (19.96 ± 8.19), anxiety (14.51 ± 8.6), and stress (22.12 ± 8.98) indicate significant psychological distress among the respondents. Table 4 further highlights the severe psychological impact of the flood. Approximately 24 and 23% of participants experienced severe or extremely severe depression, respectively, pointing to a significant number of individuals struggling with depressive symptoms. Around 33% of participants reported severe anxiety, indicating a high prevalence of anxiety-related distress among men. Additionally, 20 and 16% of respondents experienced severe or extremely severe stress, respectively, further illustrating the widespread stress among participants in the aftermath of the flood.

These findings are consistent with previous studies on men’s mental health following natural disasters such as floods. Cultural values of stoicism and self-reliance may discourage men from seeking mental health support, potentially exacerbating their suffering (52, 53). The high prevalence of severe mental health symptoms among men underscores the urgent need for targeted mental health treatments and support services in disaster-affected areas.

Men may also experience additional stress due to their societal roles as providers and caretakers. The loss of livelihoods, displacement, or struggles to meet family responsibilities can further strain their mental well-being (53). As a result, men in disaster-affected regions may experience depression, anxiety, stress, and PTSD. Our findings align with broader disaster mental health literature, which suggests that men and women experience psychological distress differently. Women typically exhibit higher rates of PTSD, depression, and anxiety due to heightened emotional processing of trauma. In contrast, men are more likely to manifest stress through externalizing behaviors, such as substance use and avoidance. The high levels of severe depression and anxiety observed in this study reinforce the need for targeted mental health interventions that consider gender-specific coping mechanisms and barriers to seeking psychological support.

A different study on women’s mental health post-disaster found higher levels of depression, anxiety, and stress compared to the results in this study (49). While men may not experience mental health difficulties as severely as women, their challenges also require attention for the sake of community resilience. In countries with entrenched gender equality through legislative frameworks, research suggests that both men and women should face similar disaster-related mental health outcomes (54). For instance, the 2007 Tewkesbury floods and the 2008 Morpeth floods in the UK demonstrated that men and women may experience both common and distinct gendered impacts from disasters (54). Similarly, the English National Study on Flooding and Health found that women had comparable risks of depression and anxiety as men (55). After Hurricane Katrina, 15% of men in the affected areas reported depression (56). In some cases, men expressed feelings of fear and referred to the floods as “very severe” (54).

Table 5 outlines the Disaster-Related Adjustment and Stress (DAS) factors. In line with the method used in this study, only statistically significant variables were included in the simple linear regression analysis. Significant variables included age group, education, marital status, housing type, occupation, chronic disease, social satisfaction, prior flood experience, flood safety ratings, income loss due to the flood, property damage in the 2022 flood, and receiving social and economic support during the flood. Multiple linear regression analyses indicated that depression was significantly associated with age, marital status, housing type, occupation, flood safety ratings, and property damage in the 2022 flood.

Participants in the 36–45 age group, unmarried individuals, those living in pucca (brick) houses, those engaged in business activities or employed in government or private sectors, and individuals who rated their areas as moderately safe from flooding and had not suffered property damage were less likely to experience depression than those in the over-55 age group, married individuals, those residing in kacha (temporary) houses, and those working as fishermen or farmers, particularly if they perceived their areas as unsafe from floods or had experienced property damage in previous floods, including the 2022 event.

Anxiety was found to be associated with marital status, education, housing type, occupation, and flood safety ratings. Unmarried participants, those with less than secondary school education, those living in pucca houses, businesspeople, and those who rated their areas as moderately safe from flooding reported lower levels of anxiety compared to married individuals, those with no formal education, those residing in kacha houses, and those working in agriculture or fishing, particularly in areas rated as unsafe.

Stress was associated with all anxiety-related factors. Unmarried participants, those with less than secondary education, those living in pucca houses, businesspeople, government or private employees, and those living in moderately safe locations were less likely to experience stress compared to married individuals, those with no formal education, those residing in kacha houses, and those involved in agriculture or fishing, particularly in unsafe areas.

The impact of sociodemographic factors on mental health post-floods is clear. These factors significantly affect mental health outcomes in the aftermath of disasters. Floods, due to their recurring nature and severity, can exacerbate mental health problems, especially among vulnerable groups, such as people with low incomes (57). These communities, often dependent on agriculture or fishing, suffer significant losses of livelihoods, which compounds mental health distress. Flooding is one of the most damaging agricultural disasters, leading to crop failure and decreased productivity (58, 59). It also disrupts water quality and habitat structures, which adversely affect fishing (60, 61). Thus, the mental health challenges observed in our study can be attributed to the destruction of livelihoods caused by the 2022 floods.

Identifying these key sociodemographic characteristics allows authorities, public health professionals, and disaster management experts to better target interventions for vulnerable populations. Understanding the root causes of mental health disorders is crucial. Older individuals may have experienced multiple disasters over time, leading to increased mental health concerns (62, 63). Older people are particularly vulnerable to the impacts of disasters, often facing increased risks due to diminished physical health and social isolation (64, 65). Research suggests that older adults are more likely to suffer from mental health problems in the wake of a disaster (66–69).

The DAS factors also reveal the role of inadequate education, housing quality, and the safety of living environments in shaping mental health outcomes. Mental illness places a heavy burden on individuals, families, and communities (70). Low socioeconomic status is linked to higher rates of mental health issues (71). The mismatch between demands and available resources often triggers stress responses. People with low incomes face greater health risks yet lack the resources to mitigate them (72). Limited response resources in poor communities increase vulnerability to stress, conflict, and hazardous conditions (73), leading to long-term mental health consequences.

Illiterate individuals may be less aware of disaster risks and less able to respond effectively (74). Studies show that education plays a critical role in enhancing resilience and mental health post-disasters (75–77). Nations with higher levels of income and education typically experience fewer losses during disasters (78). It raises questions about whether financial stress contributes to mental health problems in low-income populations or whether education plays a more significant role in fostering resilience (79). Education can improve awareness of disaster risks, disaster preparedness, and access to resources (75). In contrast, inadequate disaster response, especially in flood-prone areas, may lead to increased mental health symptoms. Different regions experience varying levels of flood damage depending on housing quality and the vulnerability of exposed elements (80). Participants living in kacha houses, for example, were found to have higher levels of depression, anxiety, and stress compared to those living in pucca houses, likely due to the hazardous conditions associated with kacha housing.

Overall, our findings demonstrate that the mental health issues experienced by participants are directly related to the losses suffered during the 2022 floods. As loss from disasters can exacerbate mental health challenges, it is crucial to prioritize both disaster risk mitigation and post-disaster mental health care. The mental health impacts of floods are significantly influenced by community resilience. Resilient communities tend to experience fewer mental health problems post-flood (81). Several factors, such as traumatic events, disruptions to daily life, the loss of loved ones, and the destruction of homes and assets, can contribute to the increase in mental health issues (82).

Based on our findings, we propose the following recommendations for local and national governments, as well as disaster management and public health authorities, to mitigate the mental health impact of floods: