Anxiety and depression symptoms and associated care seeking behaviors among ever- married women of reproductive age in Bangladesh: Assessing the role of women’s empowerment

Anxiety and depression symptoms and associated care seeking behaviors among ever- married women of reproductive age in Bangladesh: Assessing the role of women’s empowerment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Anxiety and depression symptoms and associated care seeking behaviors among ever- married women of reproductive age in Bangladesh: Assessing the role of women’s empowerment Somaya Mostarin, Md. Mehedi Hasan, Md. Faisal Kabir, Md. Tariqujjaman, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8548772/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 Purpose To examine the association of women’s empowerment with anxiety, depression and associated care-seeking behaviors among ever-married women of reproductive age in Bangladesh. Methods We analyzed nationally representative Bangladesh Demographic and Health Survey data collected in 2022. Survey-based Women’s Empowerment (SWPER) Index was used to define women’s empowerment in three domains: “Attitude towards violence”, “Social independence” and “Decision-making”. Mental health disorders include symptoms of anxiety and depression, measured respectively using the Generalized Anxiety Disorder-7 scale and the Patient Health Questionnaire. Multivariable binary logistic regression analysis was performed to explore the association. Results Of 19987 women, 19.5% had anxiety, 4.9% depression, 21.1% any symptom, 4.2% concurrent symptoms, and 11.9% sought mental health care. Women with low empowerment had significantly greater prevalence of mental health disorders than their counterparts. Compared to women with high empowerment, women’s low empowerment in “Attitude towards violence” was associated with greater odds of anxiety (AOR 1.69, 95% CI 1.36–2.09), depression (1.59, 1.07–2.31), any mental health symptoms (1.64, 1.32–2.03), their co-occurrences (1.73, 1.19–2.51), and associated care-seeking (2.44, 1.92–3.1). Low empowered women in “Social independence” domain were significantly more likely to experience anxiety (1.27, 1.12–1.44), any symptoms (1.2, 1.07–1.35), and their co-occurrences (1.34, 1.01–1.79). Conversely, empowerment in “decision-making” domain did not exhibit a statistically significant relationship with either mental health symptoms but with care-seeking behaviors. Conclusions Mental health disorders are high among women in Bangladesh and is linked with their low empowerment. Targeted interventions covering women with low empowerment might help address mental health burden in Bangladesh. Anxiety Depression Mental Health Women Empowerment Bangladesh Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Mental health disorders, particularly anxiety and depression, represent a critical global health challenge, disproportionately affecting women in low- and middle-income countries (LMICs)(Maitra et al. 2015 ). Women in these settings face heightened vulnerability due to the complex interplay of socio-economic, cultural, and systemic barriers (Malhotra and Shah 2015 ). These disorders severely impair daily functioning, quality of life, and overall wellbeing (Berghöfer et al. 2020 ), underscoring the urgent need to identify potential determinants and implement targeted interventions. The determinants of mental health problems among women in LMICs are multifaceted, including poverty, gender-based violence, limited access to education and healthcare, and sociocultural norms that restrict women’s autonomy (Lund et al. 2018 ). Women’s empowerment has emerged as a potential mitigating factor, offering pathways to address these limitations (Fielding and Lepine 2017 ). Women’s empowerment is a multidimensional construct encompassing the ability to make strategic life decisions, access resources, and exercise agency in decision-making (Kabeer 1999 ). It has increasingly been recognized as a critical determinant of positive health outcomes, including mental health (Fielding and Lepine 2017 ). Empowered women are more likely to control health-related decisions, access healthcare services, and allocate resources for their well-being (Malapit et al. 2019 ). Several studies demonstrate that higher empowerment is associated with improved mental health outcomes across LMICs, by enhancing women’s health care seeking behavior (Yount et al. 2014 ; Ewerling et al. 2020 ; Shawon et al. 2024 ). This agency can significantly improve mental health outcomes and increase the utilization of mental health services when needed. The burden of anxiety and depression in LMICs is substantial (Patel and Prince 2010 ). Studies have consistently demonstrated an inverse association between women’s empowerment and mental health disorders in these settings (Yount et al. 2014 ; Scott et al. 2018 ). In Bangladesh, the prevalence of mental health disorders among adults ranges from 6.5% and 31%, with women exhibiting greater vulnerability (Hossain et al. 2014 ). A rural study reported a psychiatric disorder prevalence of 16.5%, with depressive and anxiety disorders accounting for 8% and 5%, respectively (Monawar Hosain et al. 2007 ). Another study revealed a depression prevalence of 16.1%, disproportionately affecting women (19%) compared to men (12.9%) (Zaman 2006 ). Despite this, women are less likely to seek mental health care (WHO 2007; Giasuddin et al. 2012 ). Gender inequalities, reflected in Bangladesh’s 71st position out of 146 countries on the Global Gender Gap Index, exacerbate these disparities (UNDP Bangladesh 2022 ). Addressing these inequalities and examining the nexus of empowerment and mental health is vital for designing effective interventions. This study amis to explore the association of women’s empowerment, anxiety, depression and care-seeking behaviors, thereby informing policies that address these critical mental health needs. MATERIALS AND METHODS Data This study utilised the most recent nationally representative cross-sectional data from 2022 Bangladesh Demographic and Health Survey (BDHS). As the ninth iteration of the national survey, the BDHS 2022 aimd to provide updated demographic and health statistics of women and children, focusing on fertility preferences, childhood mortality, family planning awareness and usage, maternal and child health, breastfeeding practices, nutritional status, newborn care, women’s empowerment, noncommunicable diseases, mental health, and accessibility of health and family planning services. The survey was conducted under the authority of the National Institute of Population Research and Training (NIPORT), supported by the Medical Education and Family Welfare Division, the Ministry of Health and Family Welfare, and the Government of Bangladesh. Financial assistance was provided by the Government of Bangladesh and the United States Agency for International Development (USAID), implementation assistance by Mitra and Associates, and technical assistance from Inner City Fund (ICF) and International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). The BDHS 2022 obtained informed consent prior to data collection. Detailed information on the BDHS 2022 is available elsewhere (National Institute of Population Research and Training (NIPORT) and ICF 2022 ). This dataset, anonymized and devoid of identifiers, was accessed for this study with appropirtae authorization. Survey procedure The BDHS 2022 sampling frame was developed by the Bangladesh Bureau of Statistics (BBS) based on the 2011 population census. The sampling process followed a two-stage stratified design. In the first stage, 675 enumeration areas (EAs) were selected, with 237 EAs in urban and 438 in rural settings, using probability proportional to size. A complete household listing for each EA was then conducted to create a sampling frame for the second stage. In the second stage, 45 households were systematically selected from each EA to ensure robust estimates for urban and rural areas as well as for each of the eight divisions in Bangladesh. A total of 30,330 households were selected, of which 30,149 were occupied. Successful interviews were conducted in 30,018 households, yielding a near-perfect response. Of these, 30,358 ever-married women aged 15–49 years were eligible for individual interviews, with a final response rate of 99%. Further procedural details are outlined in the BDHS 2022 report (National Institute of Population Research and Training (NIPORT) and ICF 2022 ). Participants The study population comprised ever-married women of reproductive age (15–49 years) residing in both rural and urban areas of Bangladesh. Measurements Outcomes For the first time, the 2022 BDHS introduced comprehensive mental health modules. Primary outcomes include symptoms of anxiety, symptoms of depression, co-occurrence of anxiety and depression symptoms, and healthcare-seeking behavior for mental health concerns. Anxiety symptoms were assessed using the validated Generalized Anxiety Disorder-7 (GAD-7) scale (Spitzer et al. 2006 ), consisting of seven items rated on a 4-point Likert scale. Scores ranged from 0 to 21, with a threshold of ≥ 6 indicating anxiety symptoms. Depressive symptoms were evaluated using the Patient Health Questionnaire-9 (PHQ-9), a widely used tool based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria for major depressive disorder (Kroenke et al. 2001 ). The PHQ-9 comprises nine items, each rated on the same 4-point Likert scale as the GAD-7. Scores ranged from 0 to 27, with ≥ 10 indicating depressive symptoms. To identify the presence of any mental health symptoms, respondents reporting either anxiety symptoms (GAD-7 score ≥ 6) or depressive symptoms (PHQ-9 score ≥ 10) were included, as well as those who reported the use of medication prescribed by a healthcare provider for mental health issues. Co-occurrence of both anxiety and depressive symptoms was determined as meeting the thresholds for both GAD-7 and PHQ-9 simultaneously. Healthcare-seeking behaviour was defined as binary response (Yes/No) to whether the respondent sought care for mental health symptoms within the past two weeks. Exposure Women’s empowerment was measured using the Survey-based Women’s Empowerment (SWPER) index, a validated tool comprising three domains: 1) attitude towards violence, 2) social independence, and 3) decision-making (Ewerling et al. 2017 , 2020 ). The SWPER index employs principal component analysis (PCA) to calculate doman-specific scores based on 14 itemsClick or tap here to enter text.. Scores were categorized into tertiles to classify empowerment level as low, medium, or high (Ewerling et al. 2020 ). Covariates Based on the available resources including existing evidence(Shawon et al. 2024 ), we included various sociodemographic characteristics as covariates in this study. These covariates include respondent’s age in years (15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49), current employment status (Unemployed/Employed), media exposure (No/Yes), husband’s education status (no formal education, primary, secondary and higher), number of living children (no child, 1, 2, 3, and 4+), household size (< 4, 4, 5, 6 and 7+), religion (Muslim, Non-Muslim), place of residence (Urban, Rural), administrative division (Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur and Sylhet), and household wealth index (Poorest, Poorer, Middle, Richer and Richest). The 2022 BDHS constructed the wealth index using PCA based on household assets. Statistical analysis Descriptive statistics were used to summarize the prevalence of mental health symptoms, empowerment levels, and participant characteristics, reported as frequencies, weighted percentages, and 95% confidence intervals (CIs). Bivariate analysis using the Chi-square (χ2) test identified associations between mental health outcomes, SWPER domains, and covariates. We performed multivariable binary logistic regression analyses to assess the association between empowerment and dichotomous mental health outcomes, with results preented as adjusted odds ratios (AORs) and 95% CIs. variables with a p-value < 0.20 in bivariate analysis were included as covariates. We excluded education from the final model due to its inclusion in SWPER domains. Analyses accounted for the hierarchical BDHS sampling design, adjustment of complex survey design using “svyset” while data analysis in Stata statistical software (version 18). RESULTS Sample characteristics Analysis included 19,987 ever-married women of reproductive age. Among them, 8.6% were adolescents aged 15–19 years and 13.7% had no formal education, 68% unemployed and 42.1% had no exposure to media. Most women (71.5%) resided in rural areas despite uniform distribution across wealth quintiles. The geographical distribution of the women spanned across various administrative divisions, with representation ranging from 5.8% in Sylhet to 25.4% in Dhaka (Table 1 ). Empowerment in the “attitude towards violence” domain was high for 85.4% of women and 59.5% in the “decision-making” domain while only 16.9% demonstrated high empowerment in the “social independence” domain (Table 1 ). Table 1 Background characteristics Frequency Percentage Exposures Women's attitude to violence Low empowerment 678 3.9% Medium empowerment 1,934 10.7% High empowerment 16,342 85.4% Women's social independence Low empowerment 7,998 43.3% Medium empowerment 7,507 39.8% High empowerment 3,449 16.9% Women's decision-making Low empowerment 2,827 14.2% Medium empowerment 5,049 26.4% High empowerment 11,078 59.5% Covariates Women's age in years 15–19 1,635 8.6% 20–24 3,233 16.4% 25–29 3,539 17.6% 30–34 3,438 17.2% 35–39 3,362 16.7% 40–44 2,561 12.7% 45–49 2,219 10.8% Women's education No formal education 2,721 13.7% Primary 5,207 26.0% Secondary 9,136 46.7% Higher 2,923 13.5% Current employment status No 13,812 68.0% Yes 6,175 32.0% Media exposure No 8,353 42.1% Yes 11,634 57.9% Wealth index Poorest 3,588 17.9% Poorer 3,914 20.1% Middle 3,989 20.6% Richer 4,149 20.9% Richest 4,347 20.4% Residence Urban 7,007 28.5% Rural 12,980 71.5% Administrative Division Barishal 2,117 6.0% Chattogram 2,983 18.7% Dhaka 3,028 25.4% Khulna 2,602 11.9% Mymensingh 2,156 7.6% Rajshahi 2,546 13.1% Rangpur 2,399 11.4% Sylhet 2,156 5.8% {Table 1 will be placed here} Prevalence of anxiety and depression Anxiety symptoms were reported by 19.5% and depressive symptoms by 4.9% of women. Co-occurrence of symptoms was present in 4.2% of women while 21.1% exhibited at least one mental health symptom. Only 11.9% of women sought mental health care (Fig. 1 ). We found large variations in the distribution of each symptoms of anxiety ( Figure S1 ) and depression ( Figure S2 ). Prevalence of mental health symptoms increased with age and was highest among rural, less wealthy, and less media-exposed women, with litte variations for care-seeking behaviours ( Table S1 ). {Figure 1 will be placed here} Association between women’s empowerment and mental health disorders The prevalence of mental health symptoms and associated care-seeking behaviours exhibited a negative association with increasing empowerment of women. Compared to women with high empowerment, women with low empowerment in all three domains had a higher prevalence of anxiety (27.4% vs 17.7%), depression (7% vs. 4.4%), any mental health symptoms (28.7% vs. 19.2%), their co-occurrences (6.5% vs. 3.7%), and associated care-seeking (23.1% vs 10.8%). Similarly, low empowered women in “Social independence” domain had greater prevalene of anxiety (20.7% vs. 15.5%), depression (5.1% vs. 3.8%), any mental health symptoms (22.3% vs. 17.6%) and co-occurrence of mental health symptoms (4.4% vs. 2.9%). Conversely, highly empowered women in “Decision-making” had high prevalence of anxiety (19.4% vs 16.1%) and any symptomatic mental health disorders (20.9% vs 17.9%) (Fig. 2 ). {Figure 2 will be placed here} The adjusted logistic regression analysis revealed that women who exhibited low or medium level of empowerment in the “attitude towards violence” domain were more likely than women with high empowerment to experience anxiety (low empowerment: AOR 1.69, 95% CI 1.36–2.09; medium empowerment: AOR 1.33, 95% CI 1.15–1.53), depression (low empowerment: AOR 1.59, 95% CI 1.07–2.31; medium empowerment: AOR 1.37, 95% CI 1.09–1.71), presence of any mental health symptoms (low empowerment: AOR 1.64, 95% CI 1.32–2.03; medium empowerment: AOR 1.38, 95% CI 1.21–1.58), their co-occurrences (low empowerment: AOR 1.73, 95% CI 1.19–2.51), and associated care-seeking (low empowerment: AOR 2.44, 95% CI 1.92–3.1; medium empowerment: AOR 1.45, 95% CI 1.21–1.73). Furthermore, less empowered women in “Social independence” domain were significantly more likely to experience anxiety (low vs high empowerment: AOR 1.27, 95% CI 1.12–1.44; medium vs high empowerment: AOR 1.18, 95% CI 1.04–1.34), any mental health symptoms (low vs high empowerment: AOR 1.2, 95% CI 1.07–1.35), and their co-occurrences (low vs high empowerment: AOR 1.34, 95% CI 1.01–1.79; medium vs high empowerment: AOR 1.32, 95% CI 1.0-1.74). Conversely, empowerment in the “decision-making” domain did not exhibit a statistically significant relationship with either mental health symptoms but with women’s behaviors to seek care for mental health (medium vs high empowerment: AOR 1.23, 95% CI 1.07–1.42) (Fig. 3 ). {Figure 3 will be placed here} DISCUSSION This study demonstrate that over one in five ever-married Bangladeshi women experience at least one mental health symptom, with anxiety being a predonminant contributor, highlighting the pervasive nature of mental health challenges within this population. Women with low levels of empowerment were at elevated risk of experiencing mental health symptoms and were more likely to seek mental health care. This indicates that empowerment influences not only mental health outcomes but also care-seeking behaviors. However, empowerment in specific domains, such as “social independence” or “decision-making”, did not exhibit a statistically significant association with mental health symptoms, their interactions, or care-seeking practices. This lack of association underpin the multidimensional nature of empowerment, suggesting that certain aspects alone may not suffice to influence mental health outcomes. A nuanced understanding of empowerment is essential to designing interventions that effectively enhance mental health and facilitate service utilization. The observed prevalence of anxiety aligns with national estimates from Bangladesh (Hasan et al. 2021 ) and Nepal (Shawon et al. 2024 ), while the prevalence of depression closely mirror the global estimates, with approximately 6% of women affected by depressive disorders (Global Health Data Exchange (GHDx)). However, discrepancies were noted when compared to the 2021 Global Burden of Disease estimates, which report anxiety and depression prevalence rates of 4.4% and 6.8%, respectively, among women (Seattle: Institute for Health Metrics and Evaluation). These deviations may be attributed to differences in study populations: global estimates encompass diverse demographics, wherreas this study focuses exclusively on ever-married women of reproductive age. Furthermore, global data often aggregate findings from countries with varying socioeconomic and cultural contexts, which may mask localized variations. The findings that over 21% of Bangladeshi women experienced at least one mental health symptoms- compared to the global estimates of one in eight individuals (Global Health Data Exchange (GHDx))- highlights the heightened mental health burden in this population, necessitating urgent need for targeted mental health services and support systems. Care-seeking for mental health symptoms was remarkably low, with only 11.9% of women reporting seeking care. This is consistent with findings from other LMICs (Rathod et al. 2017 ). Cultural attitudes, stigma, and structural barriers play critical roles in shaping help-seeking behaviors for mental illness. Factors such as cultural beliefs, religious practice, fear of of adverse consequences, and failial dynamics significantly impede mental health service utilization (Mantovani et al. 2017 ). Additionally, resource constraints, including financial and institutional barriers, exacerbate the issue, particularly for women and underprivileged populations (Srivastava 2012 ; Malhotra and Shah 2015 ; Ewerling et al. 2020 ). However, education enhances women's participation in social and economic spheres, leading to women empowerment and better care seeking practice(Reshi et al.). Educated and empowered women are more likely to navigate healthcare systems, overcome stigma, and advocate for their own mental health needs, leading to higher care-seeking behaviors (Giasuddin et al. 2012 ; Straiton and Myhre 2017 ; Shawon et al. 2024 ). Women with medium to low levels of empowerment in domains such as “attitude towards violence” or “social independence” were more susceptible to mental health disorders and exhibited lower rates of care-seeking compared to highly empowered women. These findings suggest that enhancing women’s empowerment could serve as a protective factor against mental health disorders in Bangladeshi women. Past research in similar settings corroborates the protective role of empowerment on mental health (Shawon et al. 2024 ). Factors such as financial dependency, restricted decision-making autonomy, interpersonal violence, and caregiving responsibilities negatively impact women’s mental health (Lund et al. 2018 ). Moreover, societal expectations and familial conflicts, particularly with in-laws, exacerbate mental health challenges (Koly et al. 2022 ). Interventions promoting social independence, characterized by access to education, knowledge, and equitable resources, could significantly improve mental health outcomes among women (Ewerling et al. 2020 ). Contrary to previous studies (Rungreangkulkij et al. 2019 ), empowerment in the domain of “decision-making” did not exhibit a substantial influence on mental health symptoms. This finding reinforces the need to address empowerment as a multidimensional construct, with tailored interventions targeting specific domains to foster holistic well-being and improve care-seeking behaviours. Enhanced social capital and decision-making power related to pregnancy, parenting, and financial matters have been linked to better mental health outcomes(Alipour et al. 2018 ; Scott et al. 2020 ) and greater care-seeking behaviours (Shawon et al. 2024 ). Expanding mental health interventions to encompass women with low empowerment across all domains could have far-reaching impacts on mentla health and overall wellbeing. Future research should investigate the frequency of mental health symptoms of care-seeking patterns across varying levels of empowerment within each SWPER domain to identify high-risk groups. Understanding these dynamics will inform the development of targeted interventions and support systems for women. Comprehensive research is essential to guide policy formulation, program planning, and service delivery, ultimately mitigating the social and economic consequences of mental illness and addressing health disparities (World Health Organization (WHO) 2001 ; Global Forum for Health Research 2004 ; Saraceno and Saxena 2004 ; Global Forum for Health Research and Yvo Nuyens 2005 , 2008; Patel and Prince 2010 ; Donkoh et al. 2024 ). The absence of independent mental health strategies in many LMICs, with 25% of the World Health Organization member nations not have such a policy or plan (Saxena et al. 2006 ), as highlighted by the Mental Health Atlas 2020, emphasizes the need for evidence-based policy development. Currently, only 8% of Commonwealth countries reference within-country data in mental health policy formulation, reflecting a broader issue of underutilization of available evidence (Omar et al. 2010 ; Williamson et al. 2015 ; World Health Organization 2021 ). Moreover, current evidence is frequently not fully used in crafting policies in LMICs (Omar et al. 2010 ; Bhugra et al. 2018 ). Strengthening mental health research and translating findings into actionable policies will be pivotal in reducing the burden of mental health disorders, particularly among vulnerable populations. To our knowledge, this is the first study to assess the influence of women’s empowerment across multiple domains in mental health outcomes in Bangladesh. This study provides critical insights into the national burden of mental health and its association across different domains of empowerment, utilizing the SWPER index- a robust, cross-culturally validated tool for measuring empowerment. The analyses, based on nationally representative data, offers reliable estimates of mental health burden and its relationship with empowerment after adjusting for potential confounders and survey design (Anik et al. 2021 ). However, the SWPER index has limitations, including its exclusive applicability only to partnered or married women and its exclusion of certain critical empowerment variables, including the ownership of assets. Additionally, the reliance on self-reported data may introduce recall bias. While the cross-sectional design precludes causal inferences, it enables valuable exposure-outcome associations commonly explored in public health research (Tariqujjaman et al. 2022 ; Hasan et al. 2023 ). Finally, the burden estimation needs to be interpreted with cautions as this estimated for ever-married women and hence may not represent all women. CONCLUSION Overall, the burden of mental health disorders is high among ever-married women of reproductive age in Bangladesh and is associated with low level of empowerment. These findings underscore the need for targeted interventions to enhance eompowerment of women towards addressing mental health disorders. Targeted interventions covering women with low empowerment might help address mental health burden in Bangladesh. Declarations Author Contribution Conceptualization: SM and MMH; Data curation: MMH; Formal analysis: MMH; Methodology: SM and MMH; Visualization: MMH; Investigation: SM and MMH; Supervision: AAM and MMH; Validation: MT, MLK; Writing—original draft: SM, MFK, MMH; Writing - review and editing: MT, MBL, RBI, MAAJ, AA, SYH, TH, HRM and AAM; All authors reviewed the manuscript. Acknowledgement The authors would like to thank the DHS Program for making the 2022 Bangladesh Demographic and Health Survey data publicly available for analysis. We also thank the participants of the DHS. Data Availability We accessed this publicly available the 2022 Bangladesh Demographic and Health Survey dataset via this link: https://dhsprogram.com/data/ References Alipour Z, Kheirabadi GR, Kazemi A, Fooladi M (2018) The most important risk factors affecting mental health during pregnancy: A systematic review. Eastern Mediterranean Health Journal 24:549–559 Anik AI, Ghose B, Rahman MM (2021) Relationship between maternal healthcare utilisation and empowerment among women in Bangladesh: Evidence from a nationally representative cross-sectional study. BMJ Open 11:. https://doi.org/10.1136/bmjopen-2021-049167 Berghöfer A, Martin L, Hense S, et al (2020) Quality of life in patients with severe mental illness: a cross-sectional survey in an integrated outpatient health care model. Quality of Life Research 29:2073–2087. https://doi.org/10.1007/s11136-020-02470-0 Bhugra D, Pathare S, Joshi R, et al (2018) A review of mental health policies from Commonwealth countries. International Journal of Social Psychiatry 64:3–8. https://doi.org/10.1177/0020764017745108 Donkoh IE, Aboagye RG, Okyere J, et al (2024) Association between the survey-based women’s empowerment index (SWPER) and intimate partner violence in sub-Saharan Africa. Reprod Health 21:. https://doi.org/10.1186/s12978-024-01755-8 Ewerling F, Lynch JW, Victora CG, et al (2017) The SWPER index for women’s empowerment in Africa: development and validation of an index based on survey data. Lancet Glob Health 5:e916–e923. https://doi.org/10.1016/S2214-109X(17)30292-9 Ewerling F, Raj A, Victora CG, et al (2020) SWPER Global: A survey-based women’s empowerment index expanded from Africa to all low- and middle-income countries. J Glob Health 10:. https://doi.org/10.7189/JOGH.10.020434 Fielding D, Lepine A (2017) Women’s Empowerment and Wellbeing: Evidence from Africa. Journal of Development Studies 53:826–840. https://doi.org/10.1080/00220388.2016.1219345 Giasuddin NA, Chowdhury NF, Hashimoto N, et al (2012) Pathways to psychiatric care in Bangladesh. Soc Psychiatry Psychiatr Epidemiol 47:129–136. https://doi.org/10.1007/s00127-010-0315-y Global Forum for Health Research (2004) Some networks in priority research areas: mental and neurological health. In: The 10/90 report on health research 2003–2004. Geneva: Global Forum for Health Research Global Forum for Health Research and Yvo Nuyens (2005) No development without research: a challenge for research capacity strengthening. Geneva: Global Forum for Health Research Global Health Data Exchange (GHDx) Institute of Health Metrics and Evaluation. In: 2022 Hasan MM, Asif CA Al, Barua A, et al (2023) Association of access to water, sanitation and handwashing facilities with undernutrition of children below 5 years of age in Bangladesh: Evidence from two population-based, nationally representative surveys. BMJ Open 13:. https://doi.org/10.1136/bmjopen-2022-065330 Hasan MT, Anwar T, Christopher E, et al (2021) The current state of mental healthcare in Bangladesh: part 1 – an updated country profile. BJPsych Int 18:78–82. https://doi.org/10.1192/bji.2021.41 Hossain MD, Ahmed HU, Chowdhury WA, et al (2014) Mental disorders in Bangladesh: A systematic review. BMC Psychiatry 14:. https://doi.org/10.1186/s12888-014-0216-9 Kabeer N (1999) Resources, Agency, Achievements: Reflections on the Measurement of Women’s Empowerment. Dev Change 30:435–464. https://doi.org/10.1111/1467-7660.00125 Koly KN, Tasnim Z, Ahmed S, et al (2022) Mental healthcare-seeking behavior of women in Bangladesh: content analysis of a social media platform. BMC Psychiatry 22:. https://doi.org/10.1186/s12888-022-04414-z Kroenke K, Spitzer RL, Williams JBW (2001) The PHQ-9. J Gen Intern Med 16:606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x Lund C, Brooke-Sumner C, Baingana F, et al (2018) Social determinants of mental disorders and the Sustainable Development Goals: a systematic review of reviews. Lancet Psychiatry 5:357–369 Maitra S, Brault MA, Schensul SL, et al (2015) An Approach to Mental Health in Low- and Middle-Income Countries: A Case Example from Urban India. Int J Ment Health 44:215–230. https://doi.org/10.1080/00207411.2015.1035081 Malapit H, Quisumbing A, Meinzen-Dick R, et al (2019) Development of the project-level Women’s Empowerment in Agriculture Index (pro-WEAI). World Dev 122:675–692. https://doi.org/10.1016/j.worlddev.2019.06.018 Malhotra S, Shah R (2015) Women and mental health in India: An overview. Indian J Psychiatry 57:205–211 Mantovani N, Pizzolati M, Edge D (2017) Exploring the relationship between stigma and help-seeking for mental illness in African-descended faith communities in the UK. Health Expectations 20:373–384. https://doi.org/10.1111/hex.12464 Monawar Hosain GM, Chatterjee N, Ara N, Islam T (2007) Prevalence, pattern and determinants of mental disorders in rural Bangladesh. Public Health 121:18–24. https://doi.org/10.1016/j.puhe.2006.06.018 National Institute of Population Research and Training (NIPORT) and ICF (2022) Bangladesh Demographic and Health Survey 2022: Final Report. . Dhaka, Bangladesh, and Rockville, Maryland, USA Omar MA, Green AT, Bird PK, et al (2010) Mental health policy process: a comparative study of Ghana, South Africa, Uganda and Zambia Patel V, Prince M (2010) Global mental health: A new global health field comes of age. JAMA 303:1976–1977 Rathod S, Pinninti N, Irfan M, et al (2017) Mental Health Service Provision in Low- and Middle-Income Countries. Health Serv Insights 10 Reshi IA, Sudha DT, Dar SA Multidiciplinary Output Research For Actual and International Issue |MORFAI JOURNAL WOMEN’S ACCESS TO EDUCATION AND ITS IMPACT ON THEIR EMPOWERMENT: A COMPREHENSIVE REVIEW Rungreangkulkij S, Kaewjanta N, Kabkumba C, Kotnara I (2019) Online): 2581-6187 49 Somporn Rungreangkulkij, Netchanok Kaewjanta, Chompoonoot Kabkumba, and Ingkata Kotnara Saraceno B, Saxena S (2004) Bridging the mental health research gap in low- and middle-income countries. Acta Psychiatr Scand 110:1–3 Saxena S, Paraje G, Sharan P, et al (2006) The 10/90 divide in mental health research: Trends over a 10-year period. British Journal of Psychiatry 188:81–82. https://doi.org/10.1192/bjp.bp.105.011221 Scott K, Beckham SW, Gross M, et al (2018) What do we know about community-based health worker programs? A systematic review of existing reviews on community health workers. Hum Resour Health 16 Scott S, Arrieta A, Kumar N, et al (2020) Multidimensional predictors of common mental disorders among Indian mothers of 6- To 24-month-old children living in disadvantaged rural villages with women’s self-help groups: A cross-sectional analysis. PLoS One 15:. https://doi.org/10.1371/journal.pone.0233418 . Seattle: Institute for Health Metrics and Evaluation GBD Results Tool. In: Global Health Data Exchange . In: 2019 Shawon MSR, Hossain FB, Ahmed R, et al (2024) Role of women empowerment on mental health problems and care-seeking behavior among married women in Nepal: secondary analysis of nationally representative data. Arch Womens Ment Health 27:527–536. https://doi.org/10.1007/s00737-024-01433-5 Spitzer RL, Kroenke K, Williams JBW, Löwe B (2006) A Brief Measure for Assessing Generalized Anxiety Disorder. Arch Intern Med 166:1092. https://doi.org/10.1001/archinte.166.10.1092 Srivastava K (2012) Women and mental health: Psychosocial perspective. Ind Psychiatry J 21:1. https://doi.org/10.4103/0972-6748.110938 Straiton ML, Myhre S (2017) Learning to navigate the healthcare system in a new country: a qualitative study. Scand J Prim Health Care 35:352–359. https://doi.org/10.1080/02813432.2017.1397320 Tariqujjaman M, Hasan MM, Mahfuz M, et al (2022) Association between Mother’s Education and Infant and Young Child Feeding Practices in South Asia. Nutrients 14:. https://doi.org/10.3390/nu14071514 UNDP Bangladesh (2022) Gender Equality Strategy 2023- 2026 WHO MoHFWDB 2007 (2007) WHO-AIMS report on mental health system in Bangladesh Williamson A, Makkar SR, McGrath C, Redman S (2015) How can the use of evidence in mental health policy be increased? A systematic review. Psychiatric Services 66:783–797 World Health Organization (2021) Mental Health ATLAS 2020. Geneva: World Health Organization World Health Organization (WHO) (2001) The World Health Report 2001. Mental Health: New Understanding, New Hope. Geneva: World Health Organization Yount KM, Dijkerman S, Zureick-Brown S, VanderEnde KE (2014) Women’s empowerment and generalized anxiety in minya, egypt. Soc Sci Med 106:185–193. https://doi.org/10.1016/j.socscimed.2014.01.022 Zaman MM (2006) Prevalence, medical care, awareness and attitude towards mental illness in Bangladesh (2008) Mental Health Global Action Programme: scalling up care for mental, neurological and substance use disorders. Geneva: World Health Organization Additional Declarations No competing interests reported. Supplementary Files SupplementaryWomenempowermentandmentalhealthinBangladeshSPPE.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 18 May, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 05 Feb, 2026 Submission checks completed at journal 12 Jan, 2026 First submitted to journal 08 Jan, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8548772","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596293895,"identity":"608295a1-12cd-4a7d-a5dc-093b479195ce","order_by":0,"name":"Somaya Mostarin","email":"","orcid":"","institution":"National Institute of Prevention and Social Medicine","correspondingAuthor":false,"prefix":"","firstName":"Somaya","middleName":"","lastName":"Mostarin","suffix":""},{"id":596293899,"identity":"9b97681c-d5e3-43f8-a73d-112a0d6a9d55","order_by":1,"name":"Md. Mehedi Hasan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYFCCBDYwxQ8m2UjRItlAshaDA8Rq0W1PYHvw449dnvGN5A0MH8oOM/DPSMCvxezMA3bD3rbkYrMbaQWMM84dZpC4QUjLjQQ2Cd4G5sRtN3IMmHnbDjMwEKNF8s+f+sTNM4Ba/gK1yBOjRZqH7XDiBgmgFkagFgOCWs48bJOWbTueOOPMs4KDPefSeQzPPCCg5XjyMck3f6oT+9uTNz74UWYtJ3ecgC0MDIwNMBY4angIqUcBBiSpHgWjYBSMgpEDAFshRmLa8edcAAAAAElFTkSuQmCC","orcid":"","institution":"The University of Queensland","correspondingAuthor":true,"prefix":"","firstName":"Md.","middleName":"Mehedi","lastName":"Hasan","suffix":""},{"id":596293900,"identity":"c37b90a5-da56-42f7-9955-78a8a04b3542","order_by":2,"name":"Md. Faisal Kabir","email":"","orcid":"","institution":"North South University","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Faisal","lastName":"Kabir","suffix":""},{"id":596293905,"identity":"5da96573-13ce-4019-a2b7-af806dca8895","order_by":3,"name":"Md. Tariqujjaman","email":"","orcid":"","institution":"International Centre for Diarrhoeal Disease Research","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"","lastName":"Tariqujjaman","suffix":""},{"id":596293907,"identity":"973f35cd-effd-4d1c-8b62-105293abaf79","order_by":4,"name":"Md. Lutful Kader","email":"","orcid":"","institution":"The University of Dhaka","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Lutful","lastName":"Kader","suffix":""},{"id":596293910,"identity":"ad2a51db-554e-4e93-9c6a-26c5cd9120b8","order_by":5,"name":"Mushfika Binte Latif","email":"","orcid":"","institution":"York University","correspondingAuthor":false,"prefix":"","firstName":"Mushfika","middleName":"Binte","lastName":"Latif","suffix":""},{"id":596293912,"identity":"89b4af92-6b4e-4fc7-8313-cb9c11fb5153","order_by":6,"name":"Raisha Binte Islam","email":"","orcid":"","institution":"The University of Dhaka","correspondingAuthor":false,"prefix":"","firstName":"Raisha","middleName":"Binte","lastName":"Islam","suffix":""},{"id":596293913,"identity":"729252e2-5c75-474e-9b47-792df2aa6fa7","order_by":7,"name":"Md. Akib Al-Zubayer","email":"","orcid":"","institution":"Khulna University","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Akib","lastName":"Al-Zubayer","suffix":""},{"id":596293921,"identity":"42a00283-9a8a-4ee1-bd61-8f483576a82b","order_by":8,"name":"Amina Anjum","email":"","orcid":"","institution":"National Institute of Prevention and Social Medicine","correspondingAuthor":false,"prefix":"","firstName":"Amina","middleName":"","lastName":"Anjum","suffix":""},{"id":596293932,"identity":"7799fc8d-cc3c-47b0-a82b-f7ae0108cf4e","order_by":9,"name":"Samima Yasmin Hira","email":"","orcid":"","institution":"The University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Samima","middleName":"Yasmin","lastName":"Hira","suffix":""},{"id":596293933,"identity":"be925408-8c21-4b16-afa3-77e0176356b5","order_by":10,"name":"Tanvir Hayder","email":"","orcid":"","institution":"The University of Dhaka","correspondingAuthor":false,"prefix":"","firstName":"Tanvir","middleName":"","lastName":"Hayder","suffix":""},{"id":596293936,"identity":"a1d0426d-4c55-4adf-a566-13aa620e97bc","order_by":11,"name":"Hassan Rushekh Mahmood","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Hassan","middleName":"Rushekh","lastName":"Mahmood","suffix":""},{"id":596293957,"identity":"eeb89486-8ffd-4137-86b1-27cb31c79799","order_by":12,"name":"Abdullah Al Mamun","email":"","orcid":"","institution":"The University of Queensland","correspondingAuthor":false,"prefix":"","firstName":"Abdullah","middleName":"Al","lastName":"Mamun","suffix":""}],"badges":[],"createdAt":"2026-01-08 08:23:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8548772/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8548772/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103613035,"identity":"024eabae-55a7-484e-aee0-a464915863d7","added_by":"auto","created_at":"2026-02-27 16:12:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38852,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of anxiety and depression and associated care-seeking practices among women of reproductive age in Bangladesh\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8548772/v1/95428adbd83adbdb8172e8e1.png"},{"id":103613037,"identity":"913eb43d-be6f-40df-a6bb-42f630fcd65c","added_by":"auto","created_at":"2026-02-27 16:12:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":240286,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of mental health disorders by level of women’s empowerment\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e WE= Women empowerment, *** p-value\u0026lt;0.001, ** p-value\u0026lt;0.01, * p-value\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8548772/v1/cdeefec9e9274ec4244a8090.png"},{"id":104399471,"identity":"925d3429-2d41-4556-81b9-ffd62c8cc639","added_by":"auto","created_at":"2026-03-11 12:06:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":185292,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between women’s empowerment and prevalence of anxiety, depression and associated care-seeking behaviors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e AOR= Adjusted Odds Ratio, *** p-value\u0026lt;0.001, ** p-value\u0026lt;0.01, * p-value\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e†\u003c/sup\u003eResults were adjusted for women’s age, current employment status, media exposure, wealth index, residence and division.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e‡\u003c/sup\u003eResults were adjusted for women’s age, wealth index, residence and division.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e§\u003c/sup\u003eResults were adjusted for women’s age, current employment status, residence and division.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8548772/v1/9cc434b518b9f9a20bef2993.png"},{"id":104407560,"identity":"060fdc8f-fea6-4778-aa25-bb2dca2192db","added_by":"auto","created_at":"2026-03-11 12:38:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1244424,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8548772/v1/d2cf6eb2-2cca-4e6a-bfa3-0dadc2a4cce1.pdf"},{"id":103613038,"identity":"91998dff-dc71-498d-b799-321ce7ea8157","added_by":"auto","created_at":"2026-02-27 16:12:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":130851,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryWomenempowermentandmentalhealthinBangladeshSPPE.docx","url":"https://assets-eu.researchsquare.com/files/rs-8548772/v1/95b4806e8e450ade8a5db6cd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anxiety and depression symptoms and associated care seeking behaviors among ever- married women of reproductive age in Bangladesh: Assessing the role of women’s empowerment","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMental health disorders, particularly anxiety and depression, represent a critical global health challenge, disproportionately affecting women in low- and middle-income countries (LMICs)(Maitra et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Women in these settings face heightened vulnerability due to the complex interplay of socio-economic, cultural, and systemic barriers (Malhotra and Shah \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These disorders severely impair daily functioning, quality of life, and overall wellbeing (Bergh\u0026ouml;fer et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), underscoring the urgent need to identify potential determinants and implement targeted interventions. The determinants of mental health problems among women in LMICs are multifaceted, including poverty, gender-based violence, limited access to education and healthcare, and sociocultural norms that restrict women\u0026rsquo;s autonomy (Lund et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Women\u0026rsquo;s empowerment has emerged as a potential mitigating factor, offering pathways to address these limitations (Fielding and Lepine \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWomen\u0026rsquo;s empowerment is a multidimensional construct encompassing the ability to make strategic life decisions, access resources, and exercise agency in decision-making (Kabeer \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). It has increasingly been recognized as a critical determinant of positive health outcomes, including mental health (Fielding and Lepine \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Empowered women are more likely to control health-related decisions, access healthcare services, and allocate resources for their well-being (Malapit et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Several studies demonstrate that higher empowerment is associated with improved mental health outcomes across LMICs, by enhancing women\u0026rsquo;s health care seeking behavior (Yount et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ewerling et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shawon et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This agency can significantly improve mental health outcomes and increase the utilization of mental health services when needed.\u003c/p\u003e \u003cp\u003eThe burden of anxiety and depression in LMICs is substantial (Patel and Prince \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Studies have consistently demonstrated an inverse association between women\u0026rsquo;s empowerment and mental health disorders in these settings (Yount et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In Bangladesh, the prevalence of mental health disorders among adults ranges from 6.5% and 31%, with women exhibiting greater vulnerability (Hossain et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). A rural study reported a psychiatric disorder prevalence of 16.5%, with depressive and anxiety disorders accounting for 8% and 5%, respectively (Monawar Hosain et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Another study revealed a depression prevalence of 16.1%, disproportionately affecting women (19%) compared to men (12.9%) (Zaman \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Despite this, women are less likely to seek mental health care (WHO 2007; Giasuddin et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGender inequalities, reflected in Bangladesh\u0026rsquo;s 71st position out of 146 countries on the Global Gender Gap Index, exacerbate these disparities (UNDP Bangladesh \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Addressing these inequalities and examining the nexus of empowerment and mental health is vital for designing effective interventions. This study amis to explore the association of women\u0026rsquo;s empowerment, anxiety, depression and care-seeking behaviors, thereby informing policies that address these critical mental health needs.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData\u003c/h2\u003e \u003cp\u003eThis study utilised the most recent nationally representative cross-sectional data from 2022 Bangladesh Demographic and Health Survey (BDHS). As the ninth iteration of the national survey, the BDHS 2022 aimd to provide updated demographic and health statistics of women and children, focusing on fertility preferences, childhood mortality, family planning awareness and usage, maternal and child health, breastfeeding practices, nutritional status, newborn care, women\u0026rsquo;s empowerment, noncommunicable diseases, mental health, and accessibility of health and family planning services. The survey was conducted under the authority of the National Institute of Population Research and Training (NIPORT), supported by the Medical Education and Family Welfare Division, the Ministry of Health and Family Welfare, and the Government of Bangladesh. Financial assistance was provided by the Government of Bangladesh and the United States Agency for International Development (USAID), implementation assistance by Mitra and Associates, and technical assistance from Inner City Fund (ICF) and International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). The BDHS 2022 obtained informed consent prior to data collection. Detailed information on the BDHS 2022 is available elsewhere (National Institute of Population Research and Training (NIPORT) and ICF \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This dataset, anonymized and devoid of identifiers, was accessed for this study with appropirtae authorization.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSurvey procedure\u003c/h3\u003e\n\u003cp\u003eThe BDHS 2022 sampling frame was developed by the Bangladesh Bureau of Statistics (BBS) based on the 2011 population census. The sampling process followed a two-stage stratified design. In the first stage, 675 enumeration areas (EAs) were selected, with 237 EAs in urban and 438 in rural settings, using probability proportional to size. A complete household listing for each EA was then conducted to create a sampling frame for the second stage. In the second stage, 45 households were systematically selected from each EA to ensure robust estimates for urban and rural areas as well as for each of the eight divisions in Bangladesh. A total of 30,330 households were selected, of which 30,149 were occupied. Successful interviews were conducted in 30,018 households, yielding a near-perfect response. Of these, 30,358 ever-married women aged 15\u0026ndash;49 years were eligible for individual interviews, with a final response rate of 99%. Further procedural details are outlined in the BDHS 2022 report (National Institute of Population Research and Training (NIPORT) and ICF \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe study population comprised ever-married women of reproductive age (15\u0026ndash;49 years) residing in both rural and urban areas of Bangladesh.\u003c/p\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eFor the first time, the 2022 BDHS introduced comprehensive mental health modules. Primary outcomes include symptoms of anxiety, symptoms of depression, co-occurrence of anxiety and depression symptoms, and healthcare-seeking behavior for mental health concerns.\u003c/p\u003e \u003cp\u003eAnxiety symptoms were assessed using the validated Generalized Anxiety Disorder-7 (GAD-7) scale (Spitzer et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), consisting of seven items rated on a 4-point Likert scale. Scores ranged from 0 to 21, with a threshold of \u0026ge;\u0026thinsp;6 indicating anxiety symptoms.\u003c/p\u003e \u003cp\u003eDepressive symptoms were evaluated using the Patient Health Questionnaire-9 (PHQ-9), a widely used tool based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria for major depressive disorder (Kroenke et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The PHQ-9 comprises nine items, each rated on the same 4-point Likert scale as the GAD-7. Scores ranged from 0 to 27, with \u0026ge;\u0026thinsp;10 indicating depressive symptoms.\u003c/p\u003e \u003cp\u003eTo identify the presence of any mental health symptoms, respondents reporting either anxiety symptoms (GAD-7 score\u0026thinsp;\u0026ge;\u0026thinsp;6) or depressive symptoms (PHQ-9 score\u0026thinsp;\u0026ge;\u0026thinsp;10) were included, as well as those who reported the use of medication prescribed by a healthcare provider for mental health issues.\u003c/p\u003e \u003cp\u003eCo-occurrence of both anxiety and depressive symptoms was determined as meeting the thresholds for both GAD-7 and PHQ-9 simultaneously.\u003c/p\u003e \u003cp\u003eHealthcare-seeking behaviour was defined as binary response (Yes/No) to whether the respondent sought care for mental health symptoms within the past two weeks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eExposure\u003c/h2\u003e \u003cp\u003eWomen\u0026rsquo;s empowerment was measured using the Survey-based Women\u0026rsquo;s Empowerment (SWPER) index, a validated tool comprising three domains: 1) attitude towards violence, 2) social independence, and 3) decision-making (Ewerling et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe SWPER index employs principal component analysis (PCA) to calculate doman-specific scores based on 14 itemsClick or tap here to enter text.. Scores were categorized into tertiles to classify empowerment level as low, medium, or high (Ewerling et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eBased on the available resources including existing evidence(Shawon et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), we included various sociodemographic characteristics as covariates in this study. These covariates include respondent\u0026rsquo;s age in years (15\u0026ndash;19, 20\u0026ndash;24, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;39, 40\u0026ndash;44 and 45\u0026ndash;49), current employment status (Unemployed/Employed), media exposure (No/Yes), husband\u0026rsquo;s education status (no formal education, primary, secondary and higher), number of living children (no child, 1, 2, 3, and 4+), household size (\u0026lt;\u0026thinsp;4, 4, 5, 6 and 7+), religion (Muslim, Non-Muslim), place of residence (Urban, Rural), administrative division (Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur and Sylhet), and household wealth index (Poorest, Poorer, Middle, Richer and Richest). The 2022 BDHS constructed the wealth index using PCA based on household assets.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize the prevalence of mental health symptoms, empowerment levels, and participant characteristics, reported as frequencies, weighted percentages, and 95% confidence intervals (CIs). Bivariate analysis using the Chi-square (χ2) test identified associations between mental health outcomes, SWPER domains, and covariates. We performed multivariable binary logistic regression analyses to assess the association between empowerment and dichotomous mental health outcomes, with results preented as adjusted odds ratios (AORs) and 95% CIs. variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.20 in bivariate analysis were included as covariates. We excluded education from the final model due to its inclusion in SWPER domains. Analyses accounted for the hierarchical BDHS sampling design, adjustment of complex survey design using \u0026ldquo;svyset\u0026rdquo; while data analysis in Stata statistical software (version 18).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSample characteristics\u003c/h2\u003e \u003cp\u003eAnalysis included 19,987 ever-married women of reproductive age. Among them, 8.6% were adolescents aged 15\u0026ndash;19 years and 13.7% had no formal education, 68% unemployed and 42.1% had no exposure to media. Most women (71.5%) resided in rural areas despite uniform distribution across wealth quintiles. The geographical distribution of the women spanned across various administrative divisions, with representation ranging from 5.8% in Sylhet to 25.4% in Dhaka (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Empowerment in the \u0026ldquo;attitude towards violence\u0026rdquo; domain was high for 85.4% of women and 59.5% in the \u0026ldquo;decision-making\u0026rdquo; domain while only 16.9% demonstrated high empowerment in the \u0026ldquo;social independence\u0026rdquo; domain (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBackground characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eExposures\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen's attitude to violence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen's social independence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen's decision-making\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh empowerment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCovariates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen's age in years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen's education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent employment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13,812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedia exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdministrative Division\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarishal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChattogram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhulna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMymensingh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRajshahi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRangpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSylhet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e{Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e will be placed here}\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of anxiety and depression\u003c/h2\u003e \u003cp\u003eAnxiety symptoms were reported by 19.5% and depressive symptoms by 4.9% of women. Co-occurrence of symptoms was present in 4.2% of women while 21.1% exhibited at least one mental health symptom. Only 11.9% of women sought mental health care (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We found large variations in the distribution of each symptoms of anxiety (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) and depression (\u003cb\u003eFigure S2\u003c/b\u003e). Prevalence of mental health symptoms increased with age and was highest among rural, less wealthy, and less media-exposed women, with litte variations for care-seeking behaviours (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e{Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e will be placed here}\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between women\u0026rsquo;s empowerment and mental health disorders\u003c/h2\u003e \u003cp\u003eThe prevalence of mental health symptoms and associated care-seeking behaviours exhibited a negative association with increasing empowerment of women. Compared to women with high empowerment, women with low empowerment in all three domains had a higher prevalence of anxiety (27.4% vs 17.7%), depression (7% vs. 4.4%), any mental health symptoms (28.7% vs. 19.2%), their co-occurrences (6.5% vs. 3.7%), and associated care-seeking (23.1% vs 10.8%). Similarly, low empowered women in \u0026ldquo;Social independence\u0026rdquo; domain had greater prevalene of anxiety (20.7% vs. 15.5%), depression (5.1% vs. 3.8%), any mental health symptoms (22.3% vs. 17.6%) and co-occurrence of mental health symptoms (4.4% vs. 2.9%). Conversely, highly empowered women in \u0026ldquo;Decision-making\u0026rdquo; had high prevalence of anxiety (19.4% vs 16.1%) and any symptomatic mental health disorders (20.9% vs 17.9%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e{Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e will be placed here}\u003c/p\u003e \u003cp\u003eThe adjusted logistic regression analysis revealed that women who exhibited low or medium level of empowerment in the \u0026ldquo;attitude towards violence\u0026rdquo; domain were more likely than women with high empowerment to experience anxiety (low empowerment: AOR 1.69, 95% CI 1.36\u0026ndash;2.09; medium empowerment: AOR 1.33, 95% CI 1.15\u0026ndash;1.53), depression (low empowerment: AOR 1.59, 95% CI 1.07\u0026ndash;2.31; medium empowerment: AOR 1.37, 95% CI 1.09\u0026ndash;1.71), presence of any mental health symptoms (low empowerment: AOR 1.64, 95% CI 1.32\u0026ndash;2.03; medium empowerment: AOR 1.38, 95% CI 1.21\u0026ndash;1.58), their co-occurrences (low empowerment: AOR 1.73, 95% CI 1.19\u0026ndash;2.51), and associated care-seeking (low empowerment: AOR 2.44, 95% CI 1.92\u0026ndash;3.1; medium empowerment: AOR 1.45, 95% CI 1.21\u0026ndash;1.73). Furthermore, less empowered women in \u0026ldquo;Social independence\u0026rdquo; domain were significantly more likely to experience anxiety (low vs high empowerment: AOR 1.27, 95% CI 1.12\u0026ndash;1.44; medium vs high empowerment: AOR 1.18, 95% CI 1.04\u0026ndash;1.34), any mental health symptoms (low vs high empowerment: AOR 1.2, 95% CI 1.07\u0026ndash;1.35), and their co-occurrences (low vs high empowerment: AOR 1.34, 95% CI 1.01\u0026ndash;1.79; medium vs high empowerment: AOR 1.32, 95% CI 1.0-1.74). Conversely, empowerment in the \u0026ldquo;decision-making\u0026rdquo; domain did not exhibit a statistically significant relationship with either mental health symptoms but with women\u0026rsquo;s behaviors to seek care for mental health (medium vs high empowerment: AOR 1.23, 95% CI 1.07\u0026ndash;1.42) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e{Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e will be placed here}\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study demonstrate that over one in five ever-married Bangladeshi women experience at least one mental health symptom, with anxiety being a predonminant contributor, highlighting the pervasive nature of mental health challenges within this population. Women with low levels of empowerment were at elevated risk of experiencing mental health symptoms and were more likely to seek mental health care. This indicates that empowerment influences not only mental health outcomes but also care-seeking behaviors. However, empowerment in specific domains, such as \u0026ldquo;social independence\u0026rdquo; or \u0026ldquo;decision-making\u0026rdquo;, did not exhibit a statistically significant association with mental health symptoms, their interactions, or care-seeking practices. This lack of association underpin the multidimensional nature of empowerment, suggesting that certain aspects alone may not suffice to influence mental health outcomes. A nuanced understanding of empowerment is essential to designing interventions that effectively enhance mental health and facilitate service utilization.\u003c/p\u003e \u003cp\u003eThe observed prevalence of anxiety aligns with national estimates from Bangladesh (Hasan et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Nepal (Shawon et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), while the prevalence of depression closely mirror the global estimates, with approximately 6% of women affected by depressive disorders (Global Health Data Exchange (GHDx)). However, discrepancies were noted when compared to the 2021 Global Burden of Disease estimates, which report anxiety and depression prevalence rates of 4.4% and 6.8%, respectively, among women (Seattle: Institute for Health Metrics and Evaluation). These deviations may be attributed to differences in study populations: global estimates encompass diverse demographics, wherreas this study focuses exclusively on ever-married women of reproductive age. Furthermore, global data often aggregate findings from countries with varying socioeconomic and cultural contexts, which may mask localized variations. The findings that over 21% of Bangladeshi women experienced at least one mental health symptoms- compared to the global estimates of one in eight individuals (Global Health Data Exchange (GHDx))- highlights the heightened mental health burden in this population, necessitating urgent need for targeted mental health services and support systems.\u003c/p\u003e \u003cp\u003eCare-seeking for mental health symptoms was remarkably low, with only 11.9% of women reporting seeking care. This is consistent with findings from other LMICs (Rathod et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Cultural attitudes, stigma, and structural barriers play critical roles in shaping help-seeking behaviors for mental illness. Factors such as cultural beliefs, religious practice, fear of of adverse consequences, and failial dynamics significantly impede mental health service utilization (Mantovani et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, resource constraints, including financial and institutional barriers, exacerbate the issue, particularly for women and underprivileged populations (Srivastava \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Malhotra and Shah \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ewerling et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, education enhances women's participation in social and economic spheres, leading to women empowerment and better care seeking practice(Reshi et al.). Educated and empowered women are more likely to navigate healthcare systems, overcome stigma, and advocate for their own mental health needs, leading to higher care-seeking behaviors (Giasuddin et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Straiton and Myhre \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Shawon et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWomen with medium to low levels of empowerment in domains such as \u0026ldquo;attitude towards violence\u0026rdquo; or \u0026ldquo;social independence\u0026rdquo; were more susceptible to mental health disorders and exhibited lower rates of care-seeking compared to highly empowered women. These findings suggest that enhancing women\u0026rsquo;s empowerment could serve as a protective factor against mental health disorders in Bangladeshi women. Past research in similar settings corroborates the protective role of empowerment on mental health (Shawon et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Factors such as financial dependency, restricted decision-making autonomy, interpersonal violence, and caregiving responsibilities negatively impact women\u0026rsquo;s mental health (Lund et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Moreover, societal expectations and familial conflicts, particularly with in-laws, exacerbate mental health challenges (Koly et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Interventions promoting social independence, characterized by access to education, knowledge, and equitable resources, could significantly improve mental health outcomes among women (Ewerling et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContrary to previous studies (Rungreangkulkij et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), empowerment in the domain of \u0026ldquo;decision-making\u0026rdquo; did not exhibit a substantial influence on mental health symptoms. This finding reinforces the need to address empowerment as a multidimensional construct, with tailored interventions targeting specific domains to foster holistic well-being and improve care-seeking behaviours. Enhanced social capital and decision-making power related to pregnancy, parenting, and financial matters have been linked to better mental health outcomes(Alipour et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and greater care-seeking behaviours (Shawon et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Expanding mental health interventions to encompass women with low empowerment across all domains could have far-reaching impacts on mentla health and overall wellbeing.\u003c/p\u003e \u003cp\u003eFuture research should investigate the frequency of mental health symptoms of care-seeking patterns across varying levels of empowerment within each SWPER domain to identify high-risk groups. Understanding these dynamics will inform the development of targeted interventions and support systems for women. Comprehensive research is essential to guide policy formulation, program planning, and service delivery, ultimately mitigating the social and economic consequences of mental illness and addressing health disparities (World Health Organization (WHO) \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Global Forum for Health Research \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Saraceno and Saxena \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Global Forum for Health Research and Yvo Nuyens \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, 2008; Patel and Prince \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Donkoh et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The absence of independent mental health strategies in many LMICs, with 25% of the World Health Organization member nations not have such a policy or plan (Saxena et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), as highlighted by the Mental Health Atlas 2020, emphasizes the need for evidence-based policy development. Currently, only 8% of Commonwealth countries reference within-country data in mental health policy formulation, reflecting a broader issue of underutilization of available evidence (Omar et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Williamson et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; World Health Organization \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, current evidence is frequently not fully used in crafting policies in LMICs (Omar et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bhugra et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Strengthening mental health research and translating findings into actionable policies will be pivotal in reducing the burden of mental health disorders, particularly among vulnerable populations.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first study to assess the influence of women\u0026rsquo;s empowerment across multiple domains in mental health outcomes in Bangladesh. This study provides critical insights into the national burden of mental health and its association across different domains of empowerment, utilizing the SWPER index- a robust, cross-culturally validated tool for measuring empowerment. The analyses, based on nationally representative data, offers reliable estimates of mental health burden and its relationship with empowerment after adjusting for potential confounders and survey design (Anik et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, the SWPER index has limitations, including its exclusive applicability only to partnered or married women and its exclusion of certain critical empowerment variables, including the ownership of assets. Additionally, the reliance on self-reported data may introduce recall bias. While the cross-sectional design precludes causal inferences, it enables valuable exposure-outcome associations commonly explored in public health research (Tariqujjaman et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hasan et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Finally, the burden estimation needs to be interpreted with cautions as this estimated for ever-married women and hence may not represent all women.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOverall, the burden of mental health disorders is high among ever-married women of reproductive age in Bangladesh and is associated with low level of empowerment. These findings underscore the need for targeted interventions to enhance eompowerment of women towards addressing mental health disorders. Targeted interventions covering women with low empowerment might help address mental health burden in Bangladesh.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization: SM and MMH; Data curation: MMH; Formal analysis: MMH; Methodology: SM and MMH; Visualization: MMH; Investigation: SM and MMH; Supervision: AAM and MMH; Validation: MT, MLK; Writing—original draft: SM, MFK, MMH; Writing - review and editing: MT, MBL, RBI, MAAJ, AA, SYH, TH, HRM and AAM; All authors reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank the DHS Program for making the 2022 Bangladesh Demographic and Health Survey data publicly available for analysis. We also thank the participants of the DHS.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eWe accessed this publicly available the 2022 Bangladesh Demographic and Health Survey dataset via this link: https://dhsprogram.com/data/\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlipour Z, Kheirabadi GR, Kazemi A, Fooladi M (2018) The most important risk factors affecting mental health during pregnancy: A systematic review. Eastern Mediterranean Health Journal 24:549\u0026ndash;559\u003c/li\u003e\n\u003cli\u003eAnik AI, Ghose B, Rahman MM (2021) Relationship between maternal healthcare utilisation and empowerment among women in Bangladesh: Evidence from a nationally representative cross-sectional study. BMJ Open 11:. https://doi.org/10.1136/bmjopen-2021-049167\u003c/li\u003e\n\u003cli\u003eBergh\u0026ouml;fer A, Martin L, Hense S, et al (2020) Quality of life in patients with severe mental illness: a cross-sectional survey in an integrated outpatient health care model. Quality of Life Research 29:2073\u0026ndash;2087. https://doi.org/10.1007/s11136-020-02470-0\u003c/li\u003e\n\u003cli\u003eBhugra D, Pathare S, Joshi R, et al (2018) A review of mental health policies from Commonwealth countries. International Journal of Social Psychiatry 64:3\u0026ndash;8. https://doi.org/10.1177/0020764017745108\u003c/li\u003e\n\u003cli\u003eDonkoh IE, Aboagye RG, Okyere J, et al (2024) Association between the survey-based women\u0026rsquo;s empowerment index (SWPER) and intimate partner violence in sub-Saharan Africa. Reprod Health 21:. https://doi.org/10.1186/s12978-024-01755-8\u003c/li\u003e\n\u003cli\u003eEwerling F, Lynch JW, Victora CG, et al (2017) The SWPER index for women\u0026rsquo;s empowerment in Africa: development and validation of an index based on survey data. Lancet Glob Health 5:e916\u0026ndash;e923. https://doi.org/10.1016/S2214-109X(17)30292-9\u003c/li\u003e\n\u003cli\u003eEwerling F, Raj A, Victora CG, et al (2020) SWPER Global: A survey-based women\u0026rsquo;s empowerment index expanded from Africa to all low- and middle-income countries. J Glob Health 10:. https://doi.org/10.7189/JOGH.10.020434\u003c/li\u003e\n\u003cli\u003eFielding D, Lepine A (2017) Women\u0026rsquo;s Empowerment and Wellbeing: Evidence from Africa. Journal of Development Studies 53:826\u0026ndash;840. https://doi.org/10.1080/00220388.2016.1219345\u003c/li\u003e\n\u003cli\u003eGiasuddin NA, Chowdhury NF, Hashimoto N, et al (2012) Pathways to psychiatric care in Bangladesh. Soc Psychiatry Psychiatr Epidemiol 47:129\u0026ndash;136. https://doi.org/10.1007/s00127-010-0315-y\u003c/li\u003e\n\u003cli\u003eGlobal Forum for Health Research (2004) Some networks in priority research areas: mental and neurological health. In: The 10/90 report on health research 2003\u0026ndash;2004. Geneva: Global Forum for Health Research\u003c/li\u003e\n\u003cli\u003eGlobal Forum for Health Research and Yvo Nuyens (2005) No development without research: a challenge for research capacity strengthening. Geneva: Global Forum for Health Research\u003c/li\u003e\n\u003cli\u003eGlobal Health Data Exchange (GHDx) Institute of Health Metrics and Evaluation. In: 2022\u003c/li\u003e\n\u003cli\u003eHasan MM, Asif CA Al, Barua A, et al (2023) Association of access to water, sanitation and handwashing facilities with undernutrition of children below 5 years of age in Bangladesh: Evidence from two population-based, nationally representative surveys. BMJ Open 13:. https://doi.org/10.1136/bmjopen-2022-065330\u003c/li\u003e\n\u003cli\u003eHasan MT, Anwar T, Christopher E, et al (2021) The current state of mental healthcare in Bangladesh: part 1 \u0026ndash; an updated country profile. BJPsych Int 18:78\u0026ndash;82. https://doi.org/10.1192/bji.2021.41\u003c/li\u003e\n\u003cli\u003eHossain MD, Ahmed HU, Chowdhury WA, et al (2014) Mental disorders in Bangladesh: A systematic review. BMC Psychiatry 14:. https://doi.org/10.1186/s12888-014-0216-9\u003c/li\u003e\n\u003cli\u003eKabeer N (1999) Resources, Agency, Achievements: Reflections on the Measurement of Women\u0026rsquo;s Empowerment. Dev Change 30:435\u0026ndash;464. https://doi.org/10.1111/1467-7660.00125\u003c/li\u003e\n\u003cli\u003eKoly KN, Tasnim Z, Ahmed S, et al (2022) Mental healthcare-seeking behavior of women in Bangladesh: content analysis of a social media platform. BMC Psychiatry 22:. https://doi.org/10.1186/s12888-022-04414-z\u003c/li\u003e\n\u003cli\u003eKroenke K, Spitzer RL, Williams JBW (2001) The PHQ-9. J Gen Intern Med 16:606\u0026ndash;613. https://doi.org/10.1046/j.1525-1497.2001.016009606.x\u003c/li\u003e\n\u003cli\u003eLund C, Brooke-Sumner C, Baingana F, et al (2018) Social determinants of mental disorders and the Sustainable Development Goals: a systematic review of reviews. Lancet Psychiatry 5:357\u0026ndash;369\u003c/li\u003e\n\u003cli\u003eMaitra S, Brault MA, Schensul SL, et al (2015) An Approach to Mental Health in Low- and Middle-Income Countries: A Case Example from Urban India. Int J Ment Health 44:215\u0026ndash;230. https://doi.org/10.1080/00207411.2015.1035081\u003c/li\u003e\n\u003cli\u003eMalapit H, Quisumbing A, Meinzen-Dick R, et al (2019) Development of the project-level Women\u0026rsquo;s Empowerment in Agriculture Index (pro-WEAI). World Dev 122:675\u0026ndash;692. https://doi.org/10.1016/j.worlddev.2019.06.018\u003c/li\u003e\n\u003cli\u003eMalhotra S, Shah R (2015) Women and mental health in India: An overview. Indian J Psychiatry 57:205\u0026ndash;211\u003c/li\u003e\n\u003cli\u003eMantovani N, Pizzolati M, Edge D (2017) Exploring the relationship between stigma and help-seeking for mental illness in African-descended faith communities in the UK. Health Expectations 20:373\u0026ndash;384. https://doi.org/10.1111/hex.12464\u003c/li\u003e\n\u003cli\u003eMonawar Hosain GM, Chatterjee N, Ara N, Islam T (2007) Prevalence, pattern and determinants of mental disorders in rural Bangladesh. Public Health 121:18\u0026ndash;24. https://doi.org/10.1016/j.puhe.2006.06.018\u003c/li\u003e\n\u003cli\u003eNational Institute of Population Research and Training (NIPORT) and ICF (2022) Bangladesh Demographic and Health Survey 2022: Final Report. . Dhaka, Bangladesh, and Rockville, Maryland, USA\u003c/li\u003e\n\u003cli\u003eOmar MA, Green AT, Bird PK, et al (2010) Mental health policy process: a comparative study of Ghana, South Africa, Uganda and Zambia\u003c/li\u003e\n\u003cli\u003ePatel V, Prince M (2010) Global mental health: A new global health field comes of age. JAMA 303:1976\u0026ndash;1977\u003c/li\u003e\n\u003cli\u003eRathod S, Pinninti N, Irfan M, et al (2017) Mental Health Service Provision in Low- and Middle-Income Countries. Health Serv Insights 10\u003c/li\u003e\n\u003cli\u003eReshi IA, Sudha DT, Dar SA Multidiciplinary Output Research For Actual and International Issue |MORFAI JOURNAL WOMEN\u0026rsquo;S ACCESS TO EDUCATION AND ITS IMPACT ON THEIR EMPOWERMENT: A COMPREHENSIVE REVIEW\u003c/li\u003e\n\u003cli\u003eRungreangkulkij S, Kaewjanta N, Kabkumba C, Kotnara I (2019) Online): 2581-6187 49 Somporn Rungreangkulkij, Netchanok Kaewjanta, Chompoonoot Kabkumba, and Ingkata Kotnara\u003c/li\u003e\n\u003cli\u003eSaraceno B, Saxena S (2004) Bridging the mental health research gap in low- and middle-income countries. Acta Psychiatr Scand 110:1\u0026ndash;3\u003c/li\u003e\n\u003cli\u003eSaxena S, Paraje G, Sharan P, et al (2006) The 10/90 divide in mental health research: Trends over a 10-year period. British Journal of Psychiatry 188:81\u0026ndash;82. https://doi.org/10.1192/bjp.bp.105.011221\u003c/li\u003e\n\u003cli\u003eScott K, Beckham SW, Gross M, et al (2018) What do we know about community-based health worker programs? A systematic review of existing reviews on community health workers. Hum Resour Health 16\u003c/li\u003e\n\u003cli\u003eScott S, Arrieta A, Kumar N, et al (2020) Multidimensional predictors of common mental disorders among Indian mothers of 6- To 24-month-old children living in disadvantaged rural villages with women\u0026rsquo;s self-help groups: A cross-sectional analysis. PLoS One 15:. https://doi.org/10.1371/journal.pone.0233418\u003c/li\u003e\n\u003cli\u003e. Seattle: Institute for Health Metrics and Evaluation GBD Results Tool. In: Global Health Data Exchange . In: 2019\u003c/li\u003e\n\u003cli\u003eShawon MSR, Hossain FB, Ahmed R, et al (2024) Role of women empowerment on mental health problems and care-seeking behavior among married women in Nepal: secondary analysis of nationally representative data. Arch Womens Ment Health 27:527\u0026ndash;536. https://doi.org/10.1007/s00737-024-01433-5\u003c/li\u003e\n\u003cli\u003eSpitzer RL, Kroenke K, Williams JBW, L\u0026ouml;we B (2006) A Brief Measure for Assessing Generalized Anxiety Disorder. Arch Intern Med 166:1092. https://doi.org/10.1001/archinte.166.10.1092\u003c/li\u003e\n\u003cli\u003eSrivastava K (2012) Women and mental health: Psychosocial perspective. Ind Psychiatry J 21:1. https://doi.org/10.4103/0972-6748.110938\u003c/li\u003e\n\u003cli\u003eStraiton ML, Myhre S (2017) Learning to navigate the healthcare system in a new country: a qualitative study. Scand J Prim Health Care 35:352\u0026ndash;359. https://doi.org/10.1080/02813432.2017.1397320\u003c/li\u003e\n\u003cli\u003eTariqujjaman M, Hasan MM, Mahfuz M, et al (2022) Association between Mother\u0026rsquo;s Education and Infant and Young Child Feeding Practices in South Asia. Nutrients 14:. https://doi.org/10.3390/nu14071514\u003c/li\u003e\n\u003cli\u003eUNDP Bangladesh (2022) Gender Equality Strategy 2023- 2026\u003c/li\u003e\n\u003cli\u003eWHO MoHFWDB 2007 (2007) WHO-AIMS report on mental health system in Bangladesh\u003c/li\u003e\n\u003cli\u003eWilliamson A, Makkar SR, McGrath C, Redman S (2015) How can the use of evidence in mental health policy be increased? A systematic review. Psychiatric Services 66:783\u0026ndash;797\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (2021) Mental Health ATLAS 2020. Geneva: World Health Organization\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (WHO) (2001) The World Health Report 2001. Mental Health: New Understanding, New Hope. Geneva: World Health Organization\u003c/li\u003e\n\u003cli\u003eYount KM, Dijkerman S, Zureick-Brown S, VanderEnde KE (2014) Women\u0026rsquo;s empowerment and generalized anxiety in minya, egypt. Soc Sci Med 106:185\u0026ndash;193. https://doi.org/10.1016/j.socscimed.2014.01.022\u003c/li\u003e\n\u003cli\u003eZaman MM (2006) Prevalence, medical care, awareness and attitude towards mental illness in Bangladesh\u003c/li\u003e\n\u003cli\u003e(2008) Mental Health Global Action Programme: scalling up care for mental, neurological and substance use disorders. Geneva: World Health Organization\u003c/li\u003e\n\u003c/ol\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":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Anxiety, Depression, Mental Health, Women Empowerment, Bangladesh","lastPublishedDoi":"10.21203/rs.3.rs-8548772/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8548772/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo examine the association of women\u0026rsquo;s empowerment with anxiety, depression and associated care-seeking behaviors among ever-married women of reproductive age in Bangladesh.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analyzed nationally representative Bangladesh Demographic and Health Survey data collected in 2022. Survey-based Women\u0026rsquo;s Empowerment (SWPER) Index was used to define women\u0026rsquo;s empowerment in three domains: \u0026ldquo;Attitude towards violence\u0026rdquo;, \u0026ldquo;Social independence\u0026rdquo; and \u0026ldquo;Decision-making\u0026rdquo;. Mental health disorders include symptoms of anxiety and depression, measured respectively using the Generalized Anxiety Disorder-7 scale and the Patient Health Questionnaire. Multivariable binary logistic regression analysis was performed to explore the association.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 19987 women, 19.5% had anxiety, 4.9% depression, 21.1% any symptom, 4.2% concurrent symptoms, and 11.9% sought mental health care. Women with low empowerment had significantly greater prevalence of mental health disorders than their counterparts. Compared to women with high empowerment, women\u0026rsquo;s low empowerment in \u0026ldquo;Attitude towards violence\u0026rdquo; was associated with greater odds of anxiety (AOR 1.69, 95% CI 1.36\u0026ndash;2.09), depression (1.59, 1.07\u0026ndash;2.31), any mental health symptoms (1.64, 1.32\u0026ndash;2.03), their co-occurrences (1.73, 1.19\u0026ndash;2.51), and associated care-seeking (2.44, 1.92\u0026ndash;3.1). Low empowered women in \u0026ldquo;Social independence\u0026rdquo; domain were significantly more likely to experience anxiety (1.27, 1.12\u0026ndash;1.44), any symptoms (1.2, 1.07\u0026ndash;1.35), and their co-occurrences (1.34, 1.01\u0026ndash;1.79). Conversely, empowerment in \u0026ldquo;decision-making\u0026rdquo; domain did not exhibit a statistically significant relationship with either mental health symptoms but with care-seeking behaviors.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eMental health disorders are high among women in Bangladesh and is linked with their low empowerment. Targeted interventions covering women with low empowerment might help address mental health burden in Bangladesh.\u003c/p\u003e","manuscriptTitle":"Anxiety and depression symptoms and associated care seeking behaviors among ever- married women of reproductive age in Bangladesh: Assessing the role of women’s empowerment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 16:12:04","doi":"10.21203/rs.3.rs-8548772/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"274401195374640957572889016509137722824","date":"2026-05-18T08:36:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T12:20:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-05T07:22:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-12T08:32:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Social Psychiatry and Psychiatric Epidemiology","date":"2026-01-08T08:06:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9bb6ca64-88d1-4659-b98d-b373caf97afe","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"274401195374640957572889016509137722824","date":"2026-05-18T08:36:40+00:00","index":21,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T16:12:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 16:12:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8548772","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8548772","identity":"rs-8548772","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}