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Communications Earth & Environment volume 5, Article number: 687 (2024)
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Sea level rise affects the long-term psychological health of coastal communities. However, research on long-term and seasonal impacts on vulnerable communities’ psychological health is limited. Here, we explore the effect of sea-level rise on the psychological health of the coastal population in Satkhira and Khulna districts of southwest Bangladesh across two seasons: before monsoon (March to April) and post-monsoon months (October to November) in 2021. We leveraged the longitudinal research that involved 1144 participants. We collected data on psychological health using established scales for distress, depression, anxiety, and stress and also measured environmental factors and resource losses. Results indicate that psychological health, particularly distress, depression, anxiety, and stress, increased during the post-monsoon months in communities more vulnerable to sea-level rise. Highly vulnerable communities showed increased psychological distress post-monsoon. Environmental stressors and resource loss escalated during the post-monsoon period, especially in moderate and highly vulnerable communities. Our findings emphasize the urgent need for targeted support and resilience-building interventions in affected communities to alleviate the psychological health impacts of sea-level rise.
Sea-level rise (SLR) due to climate change is a major concern for coastal communities worldwide. The rate of SLR has increased from an average of 2.5 mm per year in the 1990s to ~3.4 mm in recent years, with predictions estimating a rise between 26 and 77 cm by 21001. This phenomenon threatens the well-being of nearly 600 million people living in vulnerable coastal regions2. SLR induces several environmental problems, such as coastal flooding, agricultural damage, and saltwater intrusion, which adversely affect public health and disrupt daily life3,4.
For instance, saltwater intrusion compromises drinking water quality and agricultural productivity5,6, while flooding leads to property damage, soil erosion, and crop destruction7,8,9, significantly impacting both community assets and individual psychological health10,11. Individuals in developing nations, who often depend on natural resources, are particularly susceptible to these challenges, facing heightened risks of psychological distress12,13. Factors like displacement, loss of cultural heritage, economic instability, and threats to food and water security are known to precipitate psychoterratic disorders14, which are psychological health issues caused by environmental changes15,16,17.
Research highlights the severe psychological impacts of SLR on coastal communities18. For example, Kabir et al. 19 conducted a cross-sectional survey with 1200 participants from coastal communities in Bangladesh, finding that SLR-induced environmental stressors were associated with increased psychological health issues, including distress, depression, anxiety, and stress. The study highlighted that the perceived loss of resources among participants may mediate the effects of SLR on psychological health. Similarly, Asugeni et al. 20 examined psychological health concerns related to SLR among residents of East Malaita in the Solomon Islands, where 98% of participants (56 out of 57) reported negative psychological impacts from SLR, such as fear and worry, underscoring the urgent need to address the psychological health dimensions of climate change in coastal areas.
However, the interpretability of these findings is compromised by confounding factors inherent in cross-sectional studies. For example, Kabir et al. 19 noted that socioeconomic status could be a confounding factor, with a higher percentage of individuals living below the poverty line in communities more vulnerable to SLR. This suggests that observed psychological distress in these communities could be influenced by socioeconomic disparities rather than SLR vulnerability alone.
To establish the effects of SLR as separated from socioeconomic and other confounding factors, longitudinal studies are necessary. Despite growing evidence of the long-term mental health impacts of disasters21, no existing research has longitudinally examined the psychological impacts of SLR. Thus, this study embarked on a longitudinal assessment of coastal communities in Bangladesh, beginning with initial data collection between March and April 2021, prior to the monsoon season. The study region (detailed in the following sections) experiences significant climatic and environmental challenges, including SLR and heavy rainfall during the monsoon season (June–October), leading to riverbank erosion, loss of agricultural land, and increased soil salinity due to flooding, which exacerbates the psychological strain among coastal populations22,23,24,25,26. Following the pre-monsoon data collection, which was reported by Kabir et al. 19, follow-up observations were conducted in the post-monsoon period (October–November 2021, 7 months after the pre-monsoon data collection) to understand the seasonal variations in psychological health risks associated with SLR.
This research is anchored in the conservation of resources (COR) theory27,28, which posits that perceived threats to resources (such as financial, social, and personal resources) can trigger psychological distress. The Theory enables an examination of vulnerability to climate change from psychological perspectives, considering the interplay of social, psychological, and physical factors. Vulnerability assessments are crucial for identifying and mitigating risks, shaped by the interactions between societal structures and physical hazards29,30,31. Several studies, including those by Freedy32 and Benevolenza et al. 33, have substantiated a connection between resource loss and psychological distress, emphasizing the role of environmental degradation. Rudolphi34 further illuminated the relevance of COR theory in the climate change context, exploring connections between environmentally induced resource loss and psychological health challenges. The current research aims to extend these findings by examining the longitudinal pattern of psychological distress in communities facing SLR.
Currently, there is a limited amount of information regarding how SLR negatively affects psychological health among the world’s most vulnerable populations. Many researchers recommend empirical work in this space, as diverse communities must increasingly contend with the myriad challenges associated with climate change11,35,36,37,38. The Asia-Pacific region, accommodating >56% of the global population and nearly two-thirds of the world’s impoverished individuals, is particularly vulnerable to SLR1. Within this region, Bangladesh emerges as a specific case, given its unique geographical characteristics, high poverty rate, and high reliance on agriculture39. With ~53% of its coastal region currently grappling with salinity issues, primarily due to SLR, the country experiences significant resource losses, including lives, property, and developmental setbacks, particularly in its coastal zone39.
The primary goal of the current study is to determine the longitudinal patterns of psychological status (distress, depression, anxiety, and stress symptoms) among coastal communities in Bangladesh, to examine the relationship between environmental stressors and psychological health. Further, we seek to ascertain whether changes in resource loss mediate the relationship between SLR-induced environmental stressors and shifts in psychological wellbeing. Previous studies have offered an indication of the potential mediating role of resource loss. The current research adopts a longitudinal approach to investigate these associations. This study incorporates geo-spatial mapping of environmental vulnerability to examine how SLR-induced stressors evolve over time, especially during the critical periods preceding and following the monsoon season in the coastal regions, when vulnerabilities are notably exacerbated40. Furthermore, this research examines the role of resilience as a potential protective factor against the psychological toll of SLR. Resilience, defined by the ability to adapt effectively to challenging conditions, emerges as a pivotal determinant of how individuals respond to climatic hazards in prior research41.
This study examines several hypotheses: Psychological health deteriorates after the monsoon season, particularly in communities most vulnerable to SLR (H1). The degree of environmental stressors increases after the monsoon season, with a more pronounced effect in vulnerable communities (H2). An increased sense of resource loss is evident after the monsoon season, particularly in communities vulnerable to SLR (H3). The deterioration of psychological health from pre-monsoon to post-monsoon is associated with an increase in environmental stressors, mediated by an increase in resource loss (H4). In addition to these hypotheses, the study seeks to explore the potential influence of COVID-19 anxiety on the participants, given that this anxiety was prevalent at the time of data collection.
As presented in Tables 1, 2 and Fig. 1, there was a marked increase in psychological distress, depression, anxiety, and stress reported post-monsoon compared to pre-monsoon. A significant interaction between phase and vulnerability was noted for psychological distress, depression, and anxiety. For instance, highly vulnerable communities exhibited a notable increase in psychological distress post-monsoon (b = 4.635, SE = 0.441, p < 0.001) compared to their low-vulnerability counterparts. A similar trend was observed in moderate-vulnerability communities (b = 2.597, SE = 0.437, p < 0.001), as shown in Fig. 1, Panel A. However, this interaction was not significant for stress, thus, partially supporting H1.
A Psychological distress, B depression, C anxiety, D stress, E environmental stressor, F resource loss, G covid-19 anxiety and H resilience.
Investigation of H2 and H3 revealed an increase in environmental stressors during post-monsoon, particularly prominent in moderate (b = 4.478, SE = 0.798, p < 0.001) and highly vulnerable (b = 5.757, SE = 0.329, p < 0.001) communities compared to low-vulnerable communities (Fig. 1, Panel E), supporting H2. Regarding resource loss, a significant uptick was reported post-monsoon both in moderate (increase by 16.693 points, SE = 1.330, p < 0.001) and highly vulnerable communities (increase by 19.054 points, SE = 1.334, p < 0.001), corroborating H3 (Fig. 1, Panel F).
When examining COVID-19 anxiety and resilience, a general increase in anxiety levels was noted in the post-monsoon period. This increase was more pronounced among the residents of coastal communities with low and moderate vulnerability compared to those with high (Fig. 1, Panel G), a deviation from trends observed in other psychological health measures. In contrast, resilience tended to decrease after the monsoon season but was reported at significantly greater levels in moderate (b = −17.928, SE = 2.943, p < 0.001) and highly vulnerable communities (b = −20.641, SE = 2.947, p < 0.001) than low vulnerable communities.
The analysis also examined the moderating effect of gender. Results from this analysis reported in Supplementary Table 2A show that women generally experience greater negative impacts from monsoons and community vulnerabilities compared to men. However, this pattern did not consistently appear across response variables.
Table 3 reports the results from mediational analyses related to Hypothesis 4. The findings revealed significant total effects of environmental stressors on psychological distress (b = 0.085, p = 0.014), depression (b = 0.194, p = 0.001), anxiety (b = 0.090, p = 0.041), and stress (b = 0.084, p = 0.046). These results substantiated the initial segment of H4, confirming the association between increased environmental stressors and aggravated psychological health from pre- to post-monsoon reports. Moreover, observed significant indirect effects for all outcome variables supported the latter part of H4, indicating that an increased sense of resource loss mediates the relationship between the rise in environmental stressors and a decline in psychological health.
This study used a longitudinal design to understand the association between SLR and psychological health among coastal communities in Bangladesh. The results showed significant increases in distress, depression, stress, and anxiety, which were especially pronounced in the post-monsoon season. These psychological effects were highly prevalent in communities at highest risk of SLR. The findings underscored that an escalation in environmental stress correlates with deteriorating psychological health, an association mediated by an increase in resource loss. Drawing upon the Conservation of Resources theory27,42, this study provides the first longitudinal evidence supporting the applicability of the Theory to assess psychological distress, depression, anxiety, and stress in coastal communities facing SLR. The findings suggested that the severity of existing psychological health risks may be exacerbated among coastal populations during the post-monsoon season. The findings point to the critical need for policymakers and practitioners to address not only the direct effects of SLR on mental health but also to devise strategies aimed at mitigating resource loss from environmental hazards. Effective interventions should prioritize strengthening community environmental resilience, protecting infrastructure, enhancing livelihood opportunities, bolstering social networks, and integrating mental health support into climate adaptation strategies43,44. This underscores the necessity of addressing the complex interplay between environmental changes and mental health in policy formulation and practice.
Additionally, this research observed a notable decrease in resilience following the monsoon season, especially in communities identified as moderate to highly vulnerable to SLR. Environmental stressors elicited by SLR, such as saline intrusion, coastal flooding, and agricultural damage, emerged as potent determinants compromising resilience, particularly in susceptible populations45. This aligns with the existing literature that resilience is negatively correlated with resource loss46 and environmental stressors, possibly because of local environmental contexts25. For example, the unique geography or climate of a place could make the impact of these stressors more severe, affecting the community’s capacity for recovery. This notion aligns with past studies showing that losing resources and facing environmental stress can weaken resilience25,45,46, possibly influenced by the environmental characteristics of each location.
The research revealed that women experienced greater psychological distress, anxiety, and stress due to monsoons and community vulnerabilities compared to men, although no significant gender differences were noted for depressive symptoms. This contrasts with international literature that generally reports higher depression rates among women47. Women face specific threats related to climate change and disasters, often exacerbated by patriarchal norms, restricted autonomy, and limited economic options, particularly in rural and coastal areas48,49,50. However, substantial evidence supports the potential for innovation in climate change mitigation through women’s leadership50,51. These findings underscore the need for gender-responsive policies and greater inclusion of women in decision-making roles for climate adaptation.
Intriguingly, the findings indicated a greater increase in COVID-19 anxiety among the respondents from low and moderately vulnerable coastal communities compared to those in highly vulnerable areas. This contrasts with earlier studies indicating that individuals living in unstable conditions without adequate social support were more likely to experience COVID-19-related anxiety disorders52,53,54. It appeared that in highly vulnerable coastal communities, the immediate threat of environmental stressors may overshadow concerns related to the COVID-19 pandemic, resulting in higher COVID-19 anxiety in less vulnerable, but more densely populated communities located further inland.
The findings of this study are pertinent to the ongoing discourse on climate change’s psychological impacts, answering the call for empirical data to inform public policy55,56,57. By delineating mechanisms through which SLR contributes to psychological health in South Asia, this work illuminated long-term relationships between environmental stress, resource depletion, and psychological health. Thus, to address the psychological health risks exacerbated by SLR in vulnerable coastal regions of the Asia-Pacific, specific government policies and investments are critical. The Government of Bangladesh National Plan for Disaster Management58 does not currently include consideration of psychological support for at-risk communities or the role of psychological resilience in disaster risk reduction. Future policies should incorporate strategies focused on three main areas: first, resource conservation to mitigate the environmental impacts contributing to these psychological risks, second, development of place-based, community-led resilience initiatives, and third, the expansion of community-level psychological services to directly support individuals affected by these changes. This multifaceted approach aims to not only reduce the environmental drivers of psychological stress but also provide necessary psychological support to those in need. Such targeted actions align with the priorities of the Asia Pacific Disaster Mental Health Network59 and the World Health Organization Thematic Platform on Health Emergency and Hazard Risk Management60, underscoring the importance of a comprehensive strategy that includes both preventive measures and direct support services to tackle the complex challenges posed by climate change in high-risk areas.
Efficient psychological treatment models such as task shifting and peer support are essential for expanding psychological health services in high-risk areas61,62. These approaches, which involve training community members to provide basic mental health services and utilizing the support of individuals with shared experiences, are crucial for broadening access to mental health care. They ensure that services are more accessible, especially for higher-risk groups such as women and older adults19,62. The emphasis on evidence-based, culturally sensitive, and sustainable interventions highlights the need for mental health programs to be closely aligned with the specific needs and contexts of the communities they aim to serve59.
This study enriches our comprehension of the intricate interplay between climate change, with a focus on SLR, and the psychological wellbeing of coastal communities in South Asia. It presents unique evidence demonstrating how climatic events, like coastal flooding, amplify psychological distress, depression, and anxiety, especially within communities at an elevated risk of SLR. Significantly, this research contributes to the validation of the Conservation of Resources theory in a longitudinal design tailored to assessing this vulnerability at a community level. Observed patterns not only bolster theoretical foundations regarding environmental stress and resource loss as mediating variables but also illuminate their significant repercussions on psychological health. In terms of policy and practice, the findings on resource loss suggest that policymakers and practitioners should focus on preventing or reducing the loss of critical resources to mitigate psychological health issues in these communities. Consistent with Bangladesh’s National Plan for Disaster Management58, inclusive and participatory approaches are needed to identify key risks and priorities for community action. This could involve creating community-led practices that strengthen infrastructure against floods and salinity ingress, support social capital63, and ensure access to mental health services64. Understanding the direct link between resource loss and psychological health could lead to more effective and targeted interventions, emphasizing the need for comprehensive strategies that address both the environmental and psychological impacts of SLR on vulnerable populations.
Strengthening social connections within communities at risk of hazards can improve mental health and resilience after disasters65,66. For policymakers and practitioners, this means creating strategies that build these social networks and support systems, which can help people cope better with the psychological effects of environmental challenges like SLR. Enhancing social capital, such as community bonds, infrastructure that enables community interaction, and social support, is key to helping individuals and communities withstand and recover from these stressors63. Therefore, policy efforts should focus on strengthening community resilience through increased social support and collective action, aiding in the mental health recovery process in SLR-impacted areas58,60.
Several limitations must be noted. The two-wave longitudinal design, while providing temporal insights, falls short of fully elucidating the causal relationships among environmental stress, resource loss, and psychological health. Future studies employing a more expansive temporal framework could foster a more in-depth understanding. Additionally, the recent occurrence of tropical cyclones Amphan and Yaas might have influenced participants’ perceptions, potentially elevating reported levels of distress and resource loss. The proximity of these events to the study timeline might have amplified environmental stress and altered resilience perceptions. Sole reliance on self-reported measures also may have introduced potential biases. Future studies incorporating additional objective measures of environmental vulnerability could enhance the reliability and depth of the findings. This study primarily focused on the psychological effects of SLR, omitting other crucial aspects of climate change, such as heat stress. Addressing this limitation by incorporating these elements could offer a more holistic view of climate change’s impact on psychological well-being. The geographical focus on three distinct coastal communities in South Asia (more specifically in Bangladesh) may also limit the generalizability of the results. Expanding the scope to include a diverse range of communities across different geographical and cultural landscapes would be beneficial for future research. This study did not consider other influencing factors, like personal or family mental health history or past experiences with severe weather, which could give a more detailed understanding in future studies. Nevertheless, despite these limitations, this work laid a vital foundation for further exploration in this crucial area.
This research presents an empirical exploration of the psychological health implications of SLR within coastal communities. Through its longitudinal design, this work found that escalating environmental stressors, exacerbated by climate change, adversely influenced psychological distress, depression, anxiety, and stress. Notably, these effects were elevated following the monsoon season, especially in communities that were vulnerable to SLR. Resource loss served as a mediating factor in this association. These insights offer policymakers evidence to strategize long-term provisions for both local and national psychological health services. As climate change intensifies1, there is a pressing need to ensure that communities vulnerable to SLR have access to sustainable, targeted, and effective psychological interventions.
This research involved participants from the coastal communities in Satkhira and Khulna districts of southwest Bangladesh (Fig. 2), regions significantly impacted by SLR67. These areas are particularly vulnerable due to their geographical features, high poverty levels, reliance on agriculture, and high risk of frequent hazards like salinity intrusion and coastal flooding68. The study recruited individuals from those communities categorized by a recent Bangladesh Bureau of Statistics67 (BBS) report as high, moderate, or low vulnerability. The BBS report evaluated environmental vulnerability using hazard-specific data (e.g., flooding, coastal erosion, salinity intrusion) and an economic vulnerability index that included agricultural and other livelihood factors. In the studied region, changes in heat and humidity over time were minimal69, leading to the exclusion of these factors from the study. The average temperature during the study period ranged between 23 and 27 °C69.
Sampling location in southwest Bangladesh.
The communities of Gabura, Kamarkhola, and Naihati, situated 60, 93, and 120 km from the coastline, respectively, were chosen based on their varying vulnerability levels67,70. Geographic information system (GIS) data supported this selection, indicating significant risks of salinity ingress, coastal flooding, and agricultural damage, especially in Gabura and Kamarkhola. Gabura, being nearest to the Bay of Bengal, is the most affected by SLR and suffers from frequent floods, tidal surges, high salinity, land erosion, and waterlogging67,70,71. It comprises 6753 households within a 33 km² area, predominantly engaged in farming, fishing, petty trading (small-scale merchants selling goods in local markets), forest resource collection, and wage labor (employed in casual or irregular jobs, often in construction or agriculture)67,72. Kamarkhola and Naihati face moderate and low levels of impact from these environmental issues, respectively67,72. The economic activities in these areas are similar to those in Gabura67,72. The demographic details of these communities are further outlined in Supplementary Table 1.
The data collection targeted a 10% recruitment rate from each village within the Gabura, Kamarkhola, and Naihati communities, leading to a planned sample size of 100 individuals per village, totalling 400 participants per community and 1200 participants in total (Fig. 3). This approach aligned with the recommendations of Pollack et al. 73 and began with the purposive selection of villages, followed by a randomized recruitment process using voter lists from the Election Commission to ensure participant representativeness. Of the 1224 individuals approached, 1200 consented to participate. All participants provided consent after receiving a detailed explanation of the study’s purpose, potential risks, and benefits. The consent was obtained both verbally and in written form, ensuring that participants fully understood the terms of their involvement.
Study sampling strategy.
The data collection was conducted in two phases: pre-monsoon (March–April 2021)74 and post-monsoon (October–November 2021)75, with an initial cohort of 1200 participants. Ethics approvals were obtained from the human research ethics committees of Curtin University (approval number: HRE2020-0645) and Dhaka University (ref. no. 109/Biol. Scs.). Participants completed Bengali questionnaires in about 45 min each, with the data first recorded on paper and subsequently entered IBM SPSS (version 28). Six field researchers were employed to assist participants with questionnaire completion, ensuring clarity and understanding of the questions and aiding in accurate responses. This support was particularly crucial given the complex nature of the questions and the diverse literacy levels of the participants. The study observed a 4.7% attrition rate, resulting in 1144 participants completing both survey rounds. Attrition rates varied by community vulnerability: 7% in highly vulnerable communities (9% for males, 4% for females), 4% in moderately vulnerable communities (5% for males, 3% for females), and 3% in low vulnerability communities (3% for both males and females). The main reasons for attrition included migration for livelihood (25 in highly vulnerable, 14 in moderately vulnerable, and 9 in low vulnerable communities), death (2 each in high and moderate, none in low), and hospitalization (1 in high, 1 in moderate, and 2 in low). To address attrition, follow-up efforts were made through phone calls and visits. Small items like soap and toothpaste were provided to thank participants for their time.
To assess psychological issues, the study employed the Kessler psychological distress scale (K10) and the depression anxiety stress scale (DASS-21), both of which have been adapted and validated for the Bengali-speaking demographic76,77. The K10 was translated to ensure cultural and linguistic appropriateness, with its reliability and validity confirmed in Bangladesh, demonstrating good internal consistency (Cronbach’s alpha = 0.88) and test–retest reliability (0.82). It consists of 14 items rated on a five-point Likert scale (1 = ‘never’ to 5 = ‘always’), assessing emotional states over the past four weeks, asking questions like “In the last four weeks, how often did you feel inexplicably exhausted?” Scores are cumulative, with higher scores indicating greater distress. The DASS-21, also validated for use in Bangladesh77,78,79, consists of three subscales: Depression, Anxiety, and Stress—with each subscale comprising seven items. The Depression subscale measures self-devaluation, anhedonia, lack of interest, dysphoria, and hopelessness (e.g., “I couldn’t seem to experience any positive feeling at all”). The Anxiety subscale evaluates anxious feelings, situational anxiety, and physical symptoms (e.g., “I was aware of dryness in my mouth”). The Stress subscale identifies chronic non-specific arousal (e.g., “I found it hard to wind down”). Internal consistency for these subscales was high, with alpha values of 0.99 for Depression, 0.96 for Anxiety, and 0.97 for Stress. Responses are rated on a four-point Likert scale from 0 (not applicable) to 3 (almost always), and higher subscale scores suggest more severe symptoms.
Resilience was assessed using the protective factors for resilience scale (PFRS), validated for use in coastal communities80,81. The PFRS, developed by Harms82, is a self-report instrument consisting of 20 items: 10 items measure personal resources (e.g., “I believe in myself”), and 5 items each assess peer (e.g., “I feel that I belong with my friends”) and family and social resources (e.g., “my family are a source of strength for me”). Participants rated each item on a seven-point Likert scale from strongly disagree (1) to strongly agree (7). The Bengali version of the PFRS has been used to explore resilience in Bangladesh’s coastal communities facing climate change80,81. A summed score approach was applied, with higher scores indicating higher resilience factors. The Coronavirus Anxiety Scale (CAS) developed by Lee83, translated and validated in Bengali84, was used to assess COVID-19-related anxiety. This scale includes five items (e.g., “I had trouble falling or staying asleep because I was thinking about the coronavirus”), with responses ranging from 0 (not at all) to 4 (nearly every day over the last 2 weeks). Elevated scores on individual items and a high total scale score (≥9) may suggest significant symptoms that could necessitate further assessment and/or treatment83,84.
Environmental stressors related to SLR were assessed using the environmental stressor scale (ESS) and the resource loss scale (RLS)8,42,85. To ensure local contextual relevance, the ESS underwent a forward and backward translation process into Bengali. Furthermore, the scale’s internal consistency was confirmed with Cronbach’s alpha coefficients, which exceeded 0.70. The ESS includes twelve items, such as coastal flooding and salinity intrusion, each rated on a scale from 0 (not at all) to 4 (all the time), with higher scores indicating greater stress. The RLS, originally conceptualized by Hobfoll27 and refined in subsequent studies8,86, comprises 35 items across five domains: condition resources, basic object resources, object resources, energy resources, and personal characteristic resources. These domains cover a wide range of potential losses, including agricultural products, sea-oriented income, and access to essential services. Adapted to the Bangladeshi context, the RLS was subjected to a pilot study to ensure its appropriateness and underwent a translation process. It employs a five-point Likert scale (0 indicating no loss to 4 indicating extensive loss), and its construct validity was confirmed through exploratory factor analysis. The internal consistency of the RLS was verified with a Cronbach’s alpha exceeding 0.70.
Demographic variables such as age, gender, religion, marital status, and diverse income sources were also collected through the MacArthur socioeconomic status scale87 to assess the socioeconomic standing of participants within their local communities and the broader regional context, such as Bangladesh. Detailed psychometric information for ESS, RLS, and demographic measures is available in Supplementary Measures.
A linear mixed-effects model was employed, primarily chosen to account for clustering within participants and villages and to control variations among participants’ demographic characteristics. This model facilitated the examination of Hypotheses 1–3, enabling an assessment of differences in participants’ responses across seasons, particularly focusing on communities most vulnerable to SLR. For each outcome variable (e.g., psychological distress), a model was fitted that entered two responses from each participant and the vulnerability level of their communities (i.e., high, moderate, or low). The model incorporated an interaction term between the data collection phase (pre- and post-monsoon) and community vulnerability. To accommodate clustering effects, a random intercept for the village and a random slope for the data collection phase were incorporated into the model. The model also considered participants’ demographic attributes, including age, gender, religion, marital status, education, occupation, annual household income, number of dependent family members, and socioeconomic status on the community ladder. COVID-19 anxiety and resilience were also entered into the model. The fourth hypothesis posited that a deterioration in psychological health from pre-monsoon to post-monsoon would correlate with an increase in environmental stressors, with this relationship being mediated by a rise in resource loss. To investigate this, difference scores between pre-monsoon and post-monsoon responses for environmental stressors, psychological distress, and resource loss were calculated. Subsequently, a multilevel mediation analysis, utilizing the “ml_mediation” command of STATA (17 version) with 500 bootstrapped replications88, was employed to estimate the indirect, direct, and total effects, taking into consideration demographic variables (i.e., age, gender, religion, marital status, education, occupation, household income, dependent members, socioeconomic ladder) and COVID-19 anxiety as covariates.
This study identified missing data in approximately 1% of the dataset, primarily affecting variables related to psychological distress and environmental stressors.
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
The datasets of this study are publicly available in the figshare repository. The pre-monsoon data (1st dataset) can be accessed at https://doi.org/10.6084/m9.figshare.26325676.v1, and the post-monsoon data (2nd dataset) at https://doi.org/10.6084/m9.figshare.26325679.v2. These datasets are publicly accessible to ensure transparency and reproducibility of the research findings. Both datasets are referenced accordingly in the manuscript.
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Sincere gratitude is extended to local administration and field assistants from Khulna University, Bangladesh—Mr. Mohibbullah, Mr. Bocktiar Uddin, Mr. Shahriar Zaman, Mr. Asaduzzaman Nur, Mr. Sazidul Islam, and Mr. Rakib Hasan for their invaluable assistance during data collection. Funding details This research was part of Kabir’s Ph.D. work, funded by the Ministry of Science and Technology, Government of Bangladesh (Sponsor Number 12166). E.A.N. received support from a Curtin Research Fellowship in Australia. Neither funding body influenced the data collection, analysis, or decision to publish. No authors were paid by any pharmaceutical company or other agency to write this article. All authors had access to the data and took responsibility for submitting it for publication.
School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia
Sajjad Kabir, Elizabeth Newnham & Takeshi Hamamura
Jagannath University, Dhaka, Bangladesh
Sajjad Kabir
Curtin enAble Institute, Perth, Australia
Elizabeth Newnham
FXB Center for Health and Human Rights, Harvard University, Boston, MA, USA
Elizabeth Newnham
School of Earth and Planetary Sciences (EPS), Faculty of Science and Engineering, Curtin University, Perth, Australia
Ashraf Dewan
Department of Fisheries, University of Dhaka, Dhaka, Bangladesh
Md. Monirul Islam
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Sajjad Kabir contributed to the conceptualization, data curation, formal analysis, and investigation, and wrote the original draft of the manuscript. Takeshi Hamamura, Elizabeth A. Newnham, and Ashraf A. Dewan were involved in the conceptualization, provided supervision, and participated in the writing—review and editing of the manuscript. Islam provided resources by offering guidance on cultural and customary considerations during the data collection phase. All authors approved the final manuscript for publication.
Correspondence to Sajjad Kabir.
The authors declare no competing interests.
Ethical approval was sought and received from both Curtin University’s Human Research Ethics Committee (HRE2020-0645) and Dhaka University Research Ethics Committee (Ref. No. 109/Biol. Scs.), ensuring the process adhered to globally recognized ethical standards.
Communications Earth & Environment thanks Francis Vergunst, Paolo Cianconi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Martina Grecequet. A peer review file is available.
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Kabir, S., Newnham, E., Dewan, A. et al. Psychological health declined during the post-monsoon season in communities impacted by sea-level rise in Bangladesh. Commun Earth Environ 5, 687 (2024). https://doi.org/10.1038/s43247-024-01862-1
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