Strengths and limitations of this study
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The study employs a cross-sectional design, allowing for the assessment of associations between food insecurity, dietary intake and mental health among underserved urban populations.
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Including diverse low-income urban areas improves the generalisability of findings across various underserved populations.
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The study’s cross-sectional nature restricts the capacity to infer causal relationships between dietary intake and mental health outcomes.
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The lack of longitudinal data limits the analysis of trends and changes in food security and mental health over time.
Introduction
The relationship between food insecurity and psychological health has represented a significant public health concern in recent years.1 Psychological disorders are recognised for their complex aetiology, with contributing factors ranging from genetic predisposition to environmental stressors.2 Growing attention has been paid to the social determinants of mental health, particularly in low- and middle-income countries (LMICs) where vulnerable populations face a myriad of challenges.3 Globally, food insecurity is a major public health issue that affects millions of people, particularly in LMICs.4 Among these populations, underserved settlements represent a group that is particularly at risk due to their precarious living conditions, economic instability and lack of access to essential services.5 6
Food insecurity, defined as the lack of reliable access to sufficient, affordable and nutritious food, is a pervasive issue in underserved settlements, especially in developing countries like Bangladesh.7 Underserved settlements often rely on unstable and informal employment, leading to inconsistent income and subsequent difficulties in meeting basic needs, including food.8 The relationship between food insecurity and mental health is increasingly recognised, with studies showing that food insecurity can exacerbate stress, anxiety and depressive symptoms.9 This is particularly concerning in underserved urban settlements, where food insecurity rates are often significantly higher than in other areas.10
The global prevalence of food insecurity has risen due to factors such as climate change, economic crises, political instability and the COVID-19 pandemic.11 According to the WHO, approximately 864 million people worldwide face food insecurity, with many living in developing countries, particularly in underserved settlements.12 These areas, characterised by overcrowding, poor infrastructure and limited access to basic services, are hotspots of extreme poverty. The combination of food insecurity and stressful living conditions contributes to higher rates of anxiety and depression.13 Research highlights a bidirectional relationship, where food insecurity worsens mental health, in turn, hinders individuals’ ability to secure food.14 This creates a vicious cycle, especially in urban slums, where multiple risks to mental well-being are prevalent.9 15 Importantly, nutritional quality significantly impacts mental health. Poor diets, often linked to food insecurity, are associated with higher risks of depression and anxiety.16 17 In underserved areas, diets are typically limited to cheap, energy-dense, nutrient-poor foods, lacking essential nutrients like omega-3 fatty acids, vitamins and minerals, all crucial for brain function.18 Studies show that individuals with poor dietary intake are more prone to mental health disorders.19 In Bangladesh, where rice and low-cost carbohydrates dominate, protein and micronutrient deficiencies are widespread, particularly among the poor, contributing to the high rates of anxiety and depression in underserved populations.20 21
Food insecurity is a significant issue in Bangladesh, especially in urban underserved settlements where rapid urbanisation, poverty and high population density exacerbate the challenges of accessing adequate nutrition.22 People living in informal neighbourhood often struggle with unstable employment, low wages and rising food prices, making it difficult to afford a healthy diet.23 Bangladesh has one of the fastest-growing urban populations globally, with over 1 million people living in those areas, often in extreme poverty.24 Studies show that food insecurity rates in the above-mentioned areas range from 43% to 52%.23 25 Additionally, food insecurity in these areas is closely linked to mental health disorders, with anxiety and depression being prevalent among the urban poor.26 27
The connection between food insecurity, poor dietary intake and mental health is a growing public health concern, especially in those underserved urban settlements where the population is at a heightened risk for both physical and mental health problems.17 28 Understanding the extent of these associations in these communities in Bangladesh is crucial for developing targeted interventions. In Bangladesh, studies such as that by Hijol et al have begun to document the mental health challenges faced by these particular populations, though much remains to be explored in terms of the specific pathways through which food insecurity and diet affect mental health.13 This study aims to fill this gap, providing valuable insights that could inform public health interventions in similar settings. The purpose of this study was to examine the relationship between food insecurity, dietary intake and mental health, specifically focusing on anxiety and depression among people living in these areas in Bangladesh. By exploring these links, the study highlights the need for integrated approaches addressing both mental health and food security in vulnerable populations. It will contribute to the understanding of social determinants of mental health in LMICs, offering valuable insights for public health interventions. The findings will inform policymakers, health professionals and community organisations on strategies to reduce the negative effects of food insecurity on mental health.
Methods
Study design and setting
This cross-sectional study was conducted in selected urban underserved settlements of Khulna Division in Bangladesh from November 2023 to December 2023. The slums were chosen based on population density and socioeconomic characteristics, ensuring a representative sample of the urban poor.
Study population and sample size determination
The study targeted adult residents (aged 18 years and above) living in the discussed areas. Participants were selected using a multistage random sampling technique. Initially, those areas within the Khulna Division (Jashore, Narail, Khulna, Jhinaidaha and Kushtia) were listed and stratified by district using a random sampling method. Subsequently, five districts were randomly selected for the study. Within each selected district, designated areas were listed, and specific areas were randomly selected. In the third stage, a simple random sampling technique was applied to select households within each cluster. Inclusion criteria included permanent residency in these areas for at least 6 months, willingness to participate and the ability to provide informed consent. Exclusion criteria were individuals with mental health conditions, including intellectual disability, developmental delay, autism or any other condition that could interfere with the interview process and those unwilling to provide informed consent.
The sample size was calculated using a formula for cross-sectional studies, considering the estimated prevalence of anxiety and depression among slum populations (Cochran, 1977): n=Z2×P(1−P)/e2 where n=sample size, Z=Z-value (1.96 for 95% confidence level), P=estimated prevalence of food insecurity (assumed to be 50% due to lack of precise data), e=margin of error (4%). Using this formula, the calculated sample size was approximately 600 households. To account for potential non-responses, an additional 10% was added, resulting in a minimum final target of 660 households. Finally, a total of 749 households completed the assessments.
Data collection procedures
Data were collected from participants through face-to-face interviews. Interviews were conducted in participants’ homes, ensuring privacy and confidentiality. We employed four personnel with academic backgrounds in Nutrition and Food Technology. Prior to data collection, they received two days of training covering research methods, survey instruments, procedures for obtaining informed consent and data collection techniques. The principal investigator, along with two co-investigators, supervised the team to ensure that households and participants were selected appropriately in accordance with the sampling design, thereby enhancing the study’s quality. All survey tools and consent forms were translated into the local language (Bengali) and subsequently back-translated into English to ensure accuracy. The survey questionnaire was divided into three sections: (1) personal profile, including sociodemographic and socioeconomic characteristics; (2) household food security and dietary intake and (3) mental health status-related items. A pretested, structured questionnaire was employed to assess household food insecurity, dietary diversity and mental health, incorporating standardised tools such as the Household Food Insecurity Access Scale (HFIAS), the Household Dietary Diversity Score (HDDS), the Generalised Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9). To ensure content validity and clarity, the questionnaire was reviewed by subject matter experts. It was then pretested among 40 randomly selected slum households that were excluded from the final study sample. The pilot testing assessed the tool’s reliability and comprehensibility, resulting in minor revisions to enhance clarity and cultural relevance. Cronbach’s alpha values >0.7 confirmed the internal consistency of the key sections prior to the commencement of full-scale data collection.
Instruments and measures
Food insecurity
Food insecurity was assessed using HFIAS, a widely used and validated tool for measuring food insecurity in resource-constrained settings.29 The HFIAS includes nine items that capture the degree of food access problems experienced by households over the past 30 days. The cumulative scores for the nine HFIAS items, ranging from 0 to 27, reflect the household’s level of food insecurity, with higher scores indicating greater food insecurity and lower scores representing higher food security. In this study, households categorised as mildly and moderately food insecure were combined into a single group labelled ‘mild-to-moderate food insecurity’. Consequently, the dataset included three household categories: food secure, mild-to-moderately food insecure and severely food insecure. The HFIAS has demonstrated high sensitivity and specificity in accurately classifying food insecurity status in diverse populations. The HFIAS has demonstrated strong psychometric properties across various settings, with reported sensitivity ranging from 83% and specificity ranging from 92%, depending on the population and reference standard used in validation studies. These metrics suggest that the HFIAS is both a sensitive and specific tool for identifying food-insecure households in low-income, South Asian settings. Its robust sensitivity and specificity make it suitable for both research and programmatic contexts where accurate classification of food insecurity status is essential.
Dietary intake
Dietary intake data were collected using a 24-hour dietary recall method adapted for the Bangladeshi context. Trained field workers conducted interviews with participants to record all foods and beverages consumed in the previous 24 hours. Dietary diversity was calculated based on the number of food groups consumed, following The Food and Agriculture Organisation of the United Nations’s Minimum Dietary Diversity Indicator.30 The HDDS was calculated using a minimum consumption of at least half a serving of one food from each of the mentioned food group. A score of 1 was given for each food group consumed, and the maximum score was 12. Cut-off points for household dietary diversity category are lowest dietary diversity (≤3 food groups), medium dietary diversity (4–5 food groups) and high dietary diversity (≥6 food groups). Moreover, Food Frequency Questionnaire (FFQ) assessed participants’ intake of major food groups, including cereals, roots and tubers, vegetables, fruits, meats, eggs, fish/sea foods, legumes, nuts and seeds, milk and milk products, fried foods, sweets, spices and beverage items over the past 7 days. Frequencies of consumption were recorded in four categories: always (more than 4 days/weeks), sometimes (3–4 days/weeks), rarely (1–2 days/weeks), never. The combination of 24-hour recall and FFQ improved the sensitivity (ability to correctly identify those with poor dietary diversity) and specificity (ability to correctly identify those with adequate dietary diversity) of dietary diversity assessment. This triangulated approach reduces recall bias and increases the accuracy of dietary intake data, enabling more precise classification of households’ diversity status.
Anxiety and depression
Anxiety and depression levels were measured using GAD-7 and PHQ-9, respectively. Both tools are validated screening instruments that have been widely used in global mental health research, including in low-income settings. The GAD-7 consists of 7 items, and the PHQ-9 consists of 9 items, with scores categorised as minimal, mild, moderate and severe for anxiety and depression, respectively.31 32 We further classified the participants as having anxiety and depression (if they reported having a total score of ≥10), which indicated possible major anxiety and depression, with a sensitivity of 80% and specificity of 92%.33 We found the reliability of the scale among the participants acceptable.
Other covariates
Several sociodemographic factors were collected as potential confounders, including gender (male/female), age (20–30, >30–40 and >40 years), employment status, occupation, education level (illiterate, primary, and secondary and above), occupation (farmer, day labourer, serviceman/maid, businessman, and others), family income per month (<10 000 BDT, 10 000–15 000 BDT, >15 000–20 000 BDT, and >20 000 BDT), number of family members (≤4/>4), marital status (unmarried/married), duration in slums (<5 years, 5–15 years, and >15 years) and multimorbidity (no/yes) were collected through pre-coded questionnaire.
Statistical analysis
Data were analysed using Stata. Descriptive statistics were used to summarise the sociodemographic characteristics, levels of food insecurity, dietary intakes and prevalence of anxiety and depression. Two separate multivariable logistic regression models were conducted to explore the food insecurity and dietary intake associated with anxiety and depression among the participants. All independent variables were tested for multicollinearity prior to their inclusion in the regression analysis, and no significant multicollinearity was detected between any of the variables. Adjustments were made for potential confounders, including district, age, gender, level of education, family income, family member, marital status, duration in slums and multimorbidity status. Adjusted ORs with 95% CIs were calculated to determine the strength of these associations. A p value of <0.05 was considered statistically significant.
Patient and public involvement
None.
Results
Table 1 illustrates the sociodemographic factors of people living in the study areas. Almost more than half of the respondents were women (52.7%), about 49.1% of respondents had no education, and very few had higher education (17.5%). The majority of respondents were aged 20–30 years (55.4%) and worked as day labourers (38.2%). About 42.5% of the respondents had a monthly family income of 10 000–15 000 BDT, whereas 98% of the respondents were married. The majority of the participants had multimorbidity (62.7%), inadequate quality of food (94.5%) and insufficient food intake (88.4%). Nearly 68% reported that they stayed for more than 15 years in slums. In addition, 22.1% and 74.6% of respondents had severe food insecurity and mild to moderate food insecurity, respectively, and 44.5% had low HDDS. Nearly 57.1% and 57.9% of respondents had suffered from anxiety and depression, respectively.
Sociodemographic factors of slum dwellers
Tables 2 and 3 show that Khulna district’s respondents were more likely to have anxiety (76.7%) than Jashore district respondents (60.7%), and depression was more prevalent in Kushtia (73.3%) than Jashore (62.3%) (p<0.001 and p<0.001). In addition to that, anxiety and depression were significantly (p<0.015 and p<0.034) more prevalent among over 40 age respondents (63.8% and 62.9%) than those aged below 20 (44.9% and 42.9%). Female respondents suffered more anxiety and depression (59.7% and 58.5%) than male respondents (54.2% and 57.2%). Anxiety and depression (61.0% and 62.5%) were significantly (p<0.035 and p<0.031) higher in people with family income of 10 000–15000 BDT than with income above 15 000 BDT (50.4% and 53.9%). Furthermore, the study showed that the respondents whose family members were <4 or 4 suffered more anxiety (58.2%) than those whose family members were >4. Inversely, depression (61.4%) was more relevant among the respondents whose family members were >4 (p<0.043 and p<0.038).
Characteristics of respondents based on anxiety status (n=749)
Characteristics of respondents based on depression status (n=749)
Figure 1 shows the distribution of the study population according to dietary intake. About 92.6%, 53.6%, 61.3% and 58.1% of respondents always take cereals, root tubers, fats and oils/fried foods and spices. Nearly 44.2% of respondents sometimes take vegetables. Around 75.3%, 53.5%, 37.3%, 38.7%, 73.6% and 63.7% of respondents had never taken fruits, meats, fish/seafood, legumes/nuts/seeds, milk and milk products and sweets. Rarely, 36.4% of respondents eat eggs.
Distribution of study population according to dietary intakes.
The multivariate logistic model revealed that Khulna and Kushtia respondents had 3.01 and 1.51 times increased odds of being anxious (OR: 3.01, 95% CI 1.62 to 5.59 and OR: 1.51, 95% CI 1.33 to 2.74), and 2.11 and 2.01 times increased odds of being depressed (OR: 2.11, 95% CI 1.13 to 3.93 and OR: 2.01, 95% CI 1.07 to 3.79), as compared with Jashore district respondents (table 4). Moreover, the odds of having anxiety were 2.15 times and 2.98 times higher among ages 31–40 years and above 40 years (OR: 2.15, 95% CI 1.17 to 4.78 and OR: 2.98, 95% CI 1.27 to 6.97), and the odds of having depression were 2.59 times higher among ages over 40 years (OR: 2.59, 95% CI 1.10 to 6.12), as compared with below 21 years participants. Respondents with monthly family income <10000 BDT were 2.59 and 2.92 times more likely to experience anxiety and depression than their peers. Respondents with multimorbidity status (1.69 times), inadequate quality of food (2.71 times and 2.52 times) and insufficient food intake (1.24 times and 1.71 times) had higher odds of anxiety and depression than their peers, respectively.
Multivariate logit regression model results for the determinants of anxiety and depression
Respondents who had low HDDS and severe food insecurity were associated with higher odds of anxiety (1.71 times and 2.64 times) and depression (1.55 times and 2.43 times), respectively. The respondents who always consumed roots and tubers, fruits, fish/seafood, legumes/nuts/seeds, spices/ condiments/beverages (0.61 times, 0.58 times, 0.59 times, 0.57 times and 0.48 times) were less likely to experience anxiety than those who never consumed those food groups, respectively. Again, respondents who always consumeed roots and tubers, fruits, fish/seafood, legumes/nuts/seeds and spices/ condiments/beverages (0.37 times, 0.35 times, 0.74 times, 0.73 times and 0.57 times) were less likely to experience depression than those who never consumed those food groups. Again, respondents who occasionally consumed meat were also less likely to experience anxiety (0.37 times) and depression (0.49 times) than their peers. The respondents who rarely consumed vegetables and eggs were more likely to experience anxiety (1.49 times and 1.47 times) and depression (1.86 times and 1.54 times) than their peers.
Discussion
The multivariate logistic regression model reveals significant associations between district, age, gender, income, dietary diversity and food security with anxiety and depression among respondents. This study’s findings highlight the complexity of mental health issues, particularly anxiety and depression, in the context of socioeconomic and dietary factors in Bangladesh’s rural regions.
The results indicate an unambiguous geographical disparity in mental health outcomes. Respondents from Khulna had significantly higher odds of both anxiety and depression than those from Jashore, with similar trends observed in Kushtia. The elevated risks in these regions might be due to variations in socioeconomic conditions, healthcare access and environmental stressors such as food insecurity. These findings align with previous research highlighting how regional disparities can affect mental health outcomes, with marginalised populations often experiencing higher psychological distress.34–36 Age was also found to be a significant predictor of both anxiety and depression, with individuals aged 31–40 and above 40 years showing higher odds of anxiety. Older participants (over 40 years) were also more likely to experience depression. The increased burden of anxiety and depression among older adults could be attributed to factors such as greater economic strain, the cumulative burden of multimorbidities and reduced social support networks.37 Socioeconomic status, particularly monthly family income, was strongly associated with anxiety and depression. Participants from households earning less than 10 000 BDT per month were significantly more likely to suffer from both anxiety and depression, compared with those earning more. These findings are consistent with global evidence linking low income and financial stress to poor mental health outcomes.38 Income inequality exacerbates stress, especially in rural areas where poverty limits access to healthcare, education and adequate nutrition.39 We found that respondents with multimorbidity had higher odds of depression, highlighting the link between chronic physical health conditions and mental health.40 The coexistence of chronic diseases and mental health conditions, such as depression, is well established. A review study found that contributing factors include physical pain, diminished quality of life and social isolation, all of which can lead to significant psychological distress.41
Importantly, respondents suffering from food insecurity were particularly vulnerable, with severe food insecurity associated with a higher risk of anxiety and depression. This finding aligns with previous research linking food insecurity with increased mental health risks, as insufficient access to food heightens emotional distress and worries about survival.26 27 42 Food insecurity acts as a chronic stressor, affecting not only physical health through inadequate nutrition but also may affect mental health by increasing uncertainty and anxiety about access to food.43 The high prevalence of food insecurity in these regions, particularly among low-income households, could exacerbate mental health disparities.44 Moreover, individuals reporting inadequate food quality and insufficient food intake had significantly increased odds of psychological distress like anxiety and depression. Food insecurity is a recognised predictor of poor mental health, frequently serving as a stressor that intensifies symptoms of anxiety and depression.45
Dietary diversity was found to significantly impact mental health outcomes. Individuals with lower HDDS were more likely to experience symptoms of anxiety and depression, highlighting the essential link between diet quality and mental well-being. Limited dietary diversity, often resulting from food insecurity, can lead to nutritional deficiencies that negatively impact both cognitive function and emotional well-being.46
The current analysis has found that respondents who always consumed fruits, roots and tubers, fish, legumes/nuts/seeds, spices/condiments and beverages (particularly tea and coffee) were associated with a reduced risk of mental health disorders, including anxiety and depression. Several previous studies align with a growing body of literature that emphasises the critical role of diet in maintaining mental health.47–49 These foods are abundant in vitamins, minerals, polyphenols, fibre and antioxidants that are known to reduce systemic inflammation and oxidative stress—two key mechanisms linked to the development of mood disorders.50 51 Furthermore, moderate consumption of animal-sourced foods such as meat, fish and seafood was associated with lower experience of mental well-being. This study was similar to the previous studies.49 52 53 It is evident that high-quality protein and essential nutrients like omega-3 fatty acids, iron, vitamin B12 and zinc, all of which play crucial roles in brain function and neurotransmitter synthesis.54 55 Notably, omega-3 fatty acids found in fish have been particularly associated with lower levels of depressive symptoms.56 Surprisingly, in this study, individuals who rarely consumed eggs and vegetables exhibited higher odds of anxiety and depression. While this may reflect a broader pattern of overall poor diet quality, it also aligns with research highlighting the role of micronutrient deficiencies—common among those with low egg and vegetable intake—in contributing to mood disorders. Eggs provide essential nutrients such as choline, selenium and B vitamins, which are important for brain health.57 However, some studies have shown a significant association between egg consumption and psychological disorders.57 58
Implications for public health
The findings of the study have significant policy implications for public health, nutrition and social welfare strategies. First, addressing food insecurity as a critical factor influencing mental health in slum communities can guide policymakers to prioritise food assistance programmes. Policies including food relief, free food hubs, and food subsidies that ensure regular and adequate access to nutritious food in low-income areas can reduce the prevalence of mental health disorders such as anxiety and depression. Second, integrating mental health services within community-based primary healthcare facilities in underserved areas is crucial. By training local healthcare workers to screen for and address mental health issues, public health policies can become more inclusive, ensuring early detection and intervention for those suffering from food-related mental health conditions. Furthermore, the study highlights the need for dietary education and counselling within underserved populations, promoting affordable and nutritious dietary practices. Government and non-governmental organisations can collaborate to launch nutrition awareness campaigns that are culturally and economically appropriate for these vulnerable communities. Lastly, this study reinforces the necessity of a multisectoral approach in tackling underserved health challenges, where policies related to food security, mental health and urban development are aligned to create a sustainable impact. Policymakers must also consider long-term solutions, such as income support programmes and vocational training, to address the underlying socioeconomic factors contributing to food insecurity. Overall, the study emphasises the importance of creating health and social policies that recognise the intersection between food security and mental health, thereby enhancing the quality of life for underserved dwellers in developing countries.
Strengths and weaknesses
The study addresses the critical issue of food insecurity and its association with anxiety and depression, which is highly relevant in the context of public health, particularly in urban underserved settlements of developing countries like Bangladesh. By concentrating on underserved dwellers, a marginalised and underserved population, the study provides crucial insights into the mental health and nutritional challenges of a demographic often overlooked in academic research. The cross-sectional design allows for the examination of a broad spectrum of variables, including dietary intake and mental health, making the study more inclusive in its approach. The findings may provide a basis for public health interventions aimed at improving food security and mental health outcomes, especially in low-income urban settings. This study adds to the growing body of knowledge about the interconnectedness of mental health and nutrition, particularly in resource-limited settings.
The cross-sectional nature of the study limits its ability to establish causality between food insecurity, dietary intake and mental health outcomes. Longitudinal studies would be more effective in understanding the direction of these relationships. The study may also suffer from self-report bias, as the data on dietary intake and mental health symptoms were collected through self-reported questionnaires, which can lead to under-reporting or over-reporting. Another limitation is the potential lack of control for confounding variables, such as access to healthcare services, substance use, family support or other social support systems, which could have a significant influence on both food insecurity and mental health. Additionally, findings may not be fully generalisable beyond the specific urban informal settlements settings of Bangladesh, given the unique socioeconomic and cultural conditions of the study population.
Conclusion
This cross-sectional study underscores the significant association between food insecurity, dietary intake and mental health disorders, particularly anxiety and depression, among underserved populations in Bangladesh. Our findings suggest that food insecurity and inadequate dietary intake may be linked to an increased risk of anxiety and depression in these vulnerable communities. The elevated prevalence of mental health issues in underserved areas appears to correlate with limited access to nutritious food, highlighting a potential cyclical relationship between poverty, nutrition and psychological well-being. Addressing food insecurity and improving dietary quality in these populations is crucial for mitigating the mental health burden. Interventions focusing on both food access and mental health services are essential for breaking this cycle. Future research should explore longitudinal impacts and the effectiveness of integrated food and mental health interventions to support better the health and well-being of underserved populations in developing nations like Bangladesh.
Data availability statement
Data are available upon reasonable request.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and was approved. Ethical approval was obtained from the Ethical Review Committee of the Faculty of Biological Science and Technology, Jashore University of Science and Technology, Bangladesh (reference number: ERC/FBST/JUST/2023-182). Participants gave informed consent to participate in the study before taking part.
Acknowledgments
All the authors wish to express their gratitude to the participants who volunteered for this study.
