Livelihood disruption and psychological distress following the 2024 flash flood in Bangladesh
Sample profile
The majority of the respondents were male, accounting for 94.85% of the total sample (Table 2). It is reflective of the occupational characteristics in the region, where the most common livelihoods, particularly those affected by the flood, tend to be dominated by males. As the study specifically targeted these predominant livelihood activities, such as agro-fishery, business, and wage labor, which are traditionally male-dominated, the gender composition of the sample reflects the nature of these occupations. Most participants (57.43%) were aged between 36 and 55 years, while only 1.87% were aged 18–25. A large proportion (97.66%) were married. Regarding education, over half (54.39%) had completed up to non-SSC education, followed by 27.60% with SSC education, and a smaller percentage were illiterate (7.49%) or had more than SSC education (10.52%). In the context of this study, SSC refers to the Secondary School Certificate. It is a public examination taken by students in Bangladesh at the end of their 10th grade. The SSC is a significant milestone in Bangladesh’s education system, marking the completion of secondary education. Students who pass this examination are awarded the SSC certificate, which is required for further education, such as enrolling in higher secondary school (HSC) or vocational training. It is one of the key educational qualifications for young people in Bangladesh.
In terms of occupation, most respondents were involved in agro-fishery (44.44%), with other significant groups working in business (22.22%), wage labor (20.35%), and as employees (12.98%). The monthly income distribution showed that nearly half (49.24%) earned less than BDT 15,000, 46.67% earned between BDT 15,000 and BDT 29,999, and a small proportion (4.09%) earned more than BDT 30,000. Participants were from three upazilas: Fulgazi (34.27%), Sonagazi (34.04%), and Chhagalnaiya (31.7%). Most lived with their families (98.6%), and 85.26% had vulnerable family members. In this study, housing types were categorized into three groups, Kacha, Semi-pucca, and Pucca, based on construction quality and materials, which reflect residents’ socioeconomic status and vulnerability in flood-prone areas. Kacha houses, typically built with mud, bamboo, or thatch, are temporary and highly susceptible to flooding and other natural hazards, often indicating limited financial capacity. Pucca houses are constructed with durable materials like brick and concrete, offering greater resistance to environmental stress, and are more common among economically secure households. Semi-pucca houses combine elements of both, often featuring a brick or concrete base with less durable walls or roofs, providing moderate resilience. The prevalence of chronic disease and disability was low, with 91.93% reporting no chronic disease and 98.25% reporting no disability. In this study, chronic diseases refer to long-term health conditions that typically last for a year or more, require ongoing medical attention, or limit daily functioning. The study aimed to capture a broad range of such conditions that may increase participants’ vulnerability to flood-related impacts. Common examples include diabetes, hypertension, asthma, arthritis, heart disease, chronic respiratory conditions, and kidney disease. These illnesses can hinder individuals’ ability to respond to and recover from disasters by limiting mobility, increasing healthcare needs, and requiring continuous disease management. In this study, disability is defined as a broad range of physical, sensory, cognitive, or mental health impairments that may limit an individual’s ability to carry out daily activities or participate fully in social and economic life. The focus was on disabilities that could affect a person’s capacity to respond to and cope with flood-related challenges. Examples include physical impairments (e.g., mobility limitations, paralysis) and sensory disabilities (e.g., visual or hearing impairments). These forms of disability, recognized by both health and social systems, can significantly shape individual resilience and vulnerability in disaster contexts.
Flood-related information
The findings reveal a comprehensive picture of the respondents’ exposure, vulnerability, and experiences during the 2024 flash flood in the Feni district (Table 3). A significant majority (77.66%) reported no prior experience with flooding, underscoring the unprecedented nature of this disaster for most individuals. It aligns with the Rapid Needs Assessment report, which noted that 95% of the population in Fulgazi and Feni Sadar Upazilas were severely affected, with 90% of shelters submerged under water depths of 3–7 feet44. Despite 84.68% of respondents perceiving their residences as moderately safe, only 0.12% considered them completely safe, reflecting systemic infrastructural vulnerabilities. Alarmingly, 89% lacked resources to protect themselves, paralleling findings in Noakhali, where similar resource shortages were reported45.
The economic impact was severe, with nearly all respondents (99.3%) experiencing income loss due to the flood. It is consistent with reports highlighting damaged markets and disrupted livelihoods across affected districts44,45. However, only 42.22% received socioeconomic support during the event, highlighting gaps in relief distribution mechanisms. The absence of early warning systems (98.25%) and dissemination mechanisms (93.22%) further exacerbated vulnerabilities, echoing findings from other studies emphasizing the critical role of timely warnings in disaster preparedness46.
Flood duration varied, but most respondents (82.57%) faced inundation for 7–10 days, with nearly all houses affected (99.88%). Access to necessities was severely disrupted—92.28% lacked safe drinking water, and 85.5% faced food scarcity during the flood. These findings align with assessments from Feni town, where water sources were destroyed and food stocks depleted47. Despite these challenges, 80% evacuated to shelters, although overcrowding likely compounded health risks.
Health impacts were multifaceted: while personal injuries were reported by only 1.87%, disease contraction affected 8.65%, and illness within families impacted 36.26%. These figures are consistent with reports of emerging waterborne diseases in flood-affected areas due to damaged sanitation facilities44. The findings underscore the intersection between physical health risks and systemic failures in sanitation and hygiene infrastructure.
Psychological distress
The assessment of psychological distress among the respondents revealed a concerning level of mental health burden following the 2024 flash flood in the Feni district. As shown in Table 4, only a very small proportion of participants (0.58%) were likely to be well, while the vast majority exhibited varying degrees of psychological distress. Over 85% of participants exhibited moderate to severe symptoms of distress, with 41.06% likely suffering from severe disorders. It aligns with broader observations from disaster-affected regions, where rapid-onset floods often lead to significant mental health challenges due to factors like limited forewarning, disruption of livelihoods, and loss of social support10,48,49,50,51,52. Approximately 13.69% were likely to have a mild mental disorder, 44.67% were likely to have a moderate disorder, and a striking 41.06% were likely to have a severe disorder. The distress levels in Feni mirror global patterns observed in post-disaster scenarios. The findings emphasize an urgent need for targeted mental health support and community-based interventions. Lessons from other regions suggest that protective measures like social support networks and accessible healthcare can mitigate long-term impacts.
Associated factors
Table 5 (see supplementary file) and Table 6 present the results of the simple and multiple regression analyses, respectively, identifying several key factors significantly associated with livelihood impacts (Model I) and psychological impacts (Model II) resulting from flash floods in the Feni district. Logistic regression was employed for Model I, while linear regression was used for Model II. Respondents with non-SSC level education had significantly higher odds of livelihood disruption compared to illiterate individuals (aOR = 3.47, 95% CI: 1.47–7.91). It suggests that partial education may not provide sufficient skills or resources to mitigate flood impacts. Individuals might lack the vocational or technical skills needed for flood mitigation and recovery, which is important to reduce the impact of the flood53. It also indicates that the education level influences flood preparedness and resilience. For instance, a study in the Tanguar Haor region found that education significantly affects flood preparedness, with individuals having higher education levels being better equipped to handle flood situations54.
In terms of occupation, those involved in business (aOR = 0.32, 95% CI: 0.18–0.56) and employed individuals (aOR = 0.12, 95% CI: 0.05–0.25) were significantly less likely to experience livelihood impacts compared to those in agro-fishery. It suggests that diversification away from agriculture can enhance resilience. It was reported that agricultural wages declined by 5% in flood-prone areas and 14% in severely exposed areas during the 1998 extreme floods in Bangladesh55. Long-term impacts were more severe, with wage losses persisting for over five years. Another study conducted after the flash flood in Cox’s Bazar, Bangladesh, found that poverty and precarious livelihoods exacerbated the impacts, forcing affected households to take loans, sell assets, and migrate56. Another study conducted in the southeast of Bangladesh found that the farmers faced the highest relative flood damage costs (35% of income), followed by fishermen (32%)57. A study in West Bengal highlights challenges such as limited access to resources and social constraints affecting agricultural labourers’ ability to diversify into higher-value occupations58. A study considered the Sylhet Haor Basin of Bangladesh, where flash floods severely affected agricultural livelihoods, prompting many to shift to non-agricultural occupations59..
Households with a monthly income of BDT 30,000–49,999 had significantly lower odds of livelihood impact (aOR = 0.14, 95% CI: 0.03–0.43) than those earning BDT 15,000–29,999. It underscores the protective effect of higher income against flood-related disruptions. It is consistent with research indicating that higher income levels enable better preparedness and recovery from floods. For example, in the Jamuna floodplain of Bangladesh, households with higher incomes were better able to cope with and adapt to flooding events60. Income inequality exacerbates vulnerability; policies promoting equality could reduce flood damage costs.
Residence in Sonagazi Upazila was associated with a notably higher likelihood of livelihood disruption (aOR = 11.66, 95% CI: 5.51–27.15) compared to Chhagalnaiya. It highlights the role of geographic location in flood vulnerability. Chronic illness was a strong predictor, with individuals reporting chronic disease showing a dramatically increased risk (aOR = 87.84, 95% CI: 14.58–788.21) relative to the ‘maybe’ category. It emphasizes the compounded vulnerability faced by individuals with health issues during floods. While specific studies on chronic illness and flood impact are limited, research indicates that health challenges exacerbate the difficulties in coping with flood events, especially among the rural poor7. Additionally, having access to safe drinking water during the flood was associated with reduced odds of livelihood impact (aOR = 0.47, 95% CI: 0.23–0.97), while experiencing food scarcity during the flood significantly increased the likelihood of impact (aOR = 2.64, 95% CI: 1.52–4.55).
In Model II, several factors were significantly associated with psychological distress among flood-affected individuals in the Feni district (Table 6). Individuals aged 26–55 years experienced significantly higher levels of distress compared to the 18–25 age group, with β coefficients ranging from 1.77 to 1.88. A systematic review of post-natural hazard mental health in Bangladesh identified age as a significant demographic factor influencing mental health outcomes, noting that middle-aged individuals often face increased responsibilities and stressors during disasters9. Research shows that psychological distress tends to decline with age, particularly from early adulthood to older age. However, middle-aged adults often report higher distress levels due to exposure to specific stressors, such as work crises or negative social relationships61. Middle adulthood is associated with unique psychosocial challenges, such as economic precarity, caregiving responsibilities, and chronic stress exposure, which may explain elevated distress in this group62.
Unmarried respondents reported significantly lower levels of psychological distress than their married counterparts (β = −1.90, 95% CI: −3.28 to −0.52). Research has shown that marital status is significantly correlated with depression, with married individuals often experiencing higher levels of stress and anxiety during disasters due to concerns about family safety and well-being9.
Education was inversely associated with psychological distress; those with non-SSC (β = −1.16), SSC (β = −1.38), and more than SSC education (β = −1.90) reported significantly less distress than illiterate individuals. Studies have demonstrated that individuals with lower levels of education exhibit higher levels of mental health symptoms, including anxiety and depression, during and after natural hazards9. Lower education is often associated with reduced health literacy, limited access to preventive care, and higher baseline stress—all of which may amplify disaster-related anxiety and depression.
Residence in Sonagazi Upazila was associated with higher psychological distress (β = 1.29, 95% CI: 0.74 to 1.83), and those living with family also reported higher distress levels (β = 3.39, 95% CI: 1.64 to 5.14). Studies highlight caregiver burden and amplified stress when managing family safety during disasters63.
Chronic illness showed a significant inverse association; individuals without chronic disease (β = −2.44) and those with chronic disease (β = −2.30) both reported lower levels of distress compared to those uncertain about their chronic disease status. Generally, health-related factors, including physical injury and disability during natural hazards, are associated with increased mental health problems. The lower distress levels among individuals with chronic illness in our study may warrant further investigation to understand the underlying causes.
Receiving socioeconomic support was also associated with reduced psychological distress (β = −0.65, 95% CI: −1.09 to −0.20). The association between receiving socioeconomic support and reduced psychological distress aligns with findings that social support is a critical factor in mitigating mental health issues during disasters64. Access to financial assistance and community support networks can alleviate stress and promote resilience64,65..
The early warning had a strong positive association with psychological distress (β = 3.93, 95% CI: 2.19 to 5.67), and the perception of having no early warning dissemination mechanism significantly increased distress levels (β = 2.93, 95% CI: 2.01 to 3.86) compared to those who rated the system as insufficient. Access to safe drinking water during the flood was protective (β = −1.26, 95% CI: −2.03 to −0.49). The protective effect of access to safe drinking water during floods on psychological distress is supported by studies highlighting the importance of essential resources in mitigating mental health issues during disasters9.
Interestingly, individuals who were physically injured during the flood experienced significantly less psychological distress (β = −2.94, 95% CI: −4.43 to −1.46), while those who became ill due to the flood had higher distress levels (β = 1.46, 95% CI: 0.64 to 2.27). Finally, having a family member injured during the 2024 flood was strongly associated with reduced psychological distress (β = −3.61, 95% CI: −4.37 to −2.85). The association of having a family member injured during the 2024 flood with reduced psychological distress is unexpected. Typically, the loss or injury of family members during disasters is linked to higher levels of depression and anxiety. This discrepancy suggests the need for further research to explore coping mechanisms and cultural factors influencing these outcomes.
Limitations and strengths
Despite offering essential insights, this study has several limitations that warrant consideration.
First, the study used a single binary question to measure livelihood disruption. While this approach provides a broad overview, it may not fully capture the complex and multifaceted nature of livelihood impacts. Different livelihoods (e.g., agriculture, fishing, wage labor) may have been affected in various ways, and a more detailed set of questions could provide a richer understanding of the specific challenges faced by respondents. Future research could benefit from using more granular and multi-dimensional questions to explore the particular types of livelihood disruptions. Second, the cross-sectional nature of the study limits the ability to infer causal relationships between flood exposure and the observed outcomes of livelihood and mental health. Longitudinal follow-up would be more effective in capturing the progression of psychological distress and recovery of livelihood over time. Third, the purposive sampling strategy, although practical in post-disaster settings, may have introduced selection bias that potentially overrepresents those who are more accessible or more severely affected, thereby limiting the generalizability of the results to the broader population. Fourth, this study relied on self-reported data, particularly concerning psychological distress, which could be subject to recall bias. However, to mitigate this, we collected data shortly after the flood, thereby reducing the likelihood that participants would inaccurately recall their experiences. By gathering data promptly, we aimed to capture the immediate psychological and livelihood impacts, which enhances the reliability of the findings and provides a more accurate representation of the event’s immediate effects. Additionally, crucial confounding variables, such as pre-existing mental health conditions, coping strategies, and access to mental health or relief services before the disaster, were not fully captured. Finally, the geographic focus on the Feni District restricts the study’s applicability to other flood-prone regions in Bangladesh or areas with different environmental, infrastructural, and cultural contexts.
Nonetheless, the study possesses several key strengths. It addresses a significant research gap by jointly examining the effects of flash flooding on both livelihoods and mental health in a highly vulnerable region. The use of a widely validated tool, K10, enhances reliability and facilitates meaningful comparisons with other research. The large sample size improves the statistical robustness of the findings and supports subgroup analyses across diverse sociodemographic characteristics. Moreover, the study identifies multiple determinants- such as education, occupation, income, location, and access to basic needs—that can guide targeted interventions and inform disaster risk reduction strategies. By shedding light on the dual burden of economic and psychological distress following a sudden-onset disaster, this research provides a valuable foundation for developing holistic response frameworks and strengthening community resilience in Bangladesh and similar settings.
Recommendations
Based on the findings of this study, several actionable recommendations can be proposed to enhance disaster preparedness, livelihood resilience, and mental health support for flood-affected communities in Bangladesh:
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