Rural-Urban Disparity of Mental Health Symptoms Among Cancer Patients in Bangladesh: Results from a Multinomial Logistic Regression Model

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Ahedulla, Soptonwita Saha, Shafiul Azam Shakil, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6976895/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Discover Public Health → Version 1 posted 11 You are reading this latest preprint version Abstract Background Cancer can trigger distinct emotional reactions and difficulties for individuals, spanning from anxiety and depression to coping with treatment-related stressors. Geographic location can also influence access to mental health resources, cultural impacts on views, and available support systems for cancer patients. It is crucial to recognise these complexities when crafting mental health interventions and support approaches. Therefore, we investigated anxiety and depression prevalence among patients by cancer sites, stages, residence, and other associated factors. Methods This cross-sectional study was conducted at a leading cancer-specialised hospital in Bangladesh from April to June 2023. The Hospital Anxiety and Depression Scale (HADS) was used to assess depressive and anxious symptoms, and scores above 11 out of 21 were considered severe symptoms that need clinical concern. Subsequently, a multinomial regression model, adjusting for confounders, was applied to identify potential risk factors associated with different levels of anxiety and depression. Results Of 516 cancer patients, 63% were females, averaging 51.14 years (standard deviation 12.28). Of them, 10% reported severe anxiety, and 23% reported severe depression. Patients with head & neck cancer reported high levels of severe anxiety and depression. The level of severe anxiety increased with the cancer stage, being 3.18 times higher for advanced-stage patients compared to early-stage patients (relative risk ratio [RRR]: 3.18, 95% confidence interval [CI] = 1.57–6.42). Similarly, severe depression in advanced-stage patients was 8.25 times higher compared to early-stage patients (RRR: 8.25, 95% CI = 4.24–16.05). Despite similar anxiety levels, patients living in rural areas had 2.37 times more severe depression than those living in urban areas (RRR: 2.37, 95% CI = 1.37–4.11). Conclusions Cancer patients in rural areas are disproportionately affected by severe mental health issues. Patients with advanced-stage cancer and those with head & neck cancer are at particularly high risk of severe mental health symptoms. It is essential to ensure these patients receive the needed mental health support alongside a tailored treatment plan. Cancer disparity mental health anxiety depression disparity multinomial regression cancer stage Figures Figure 1 Introduction Cancer is a crucial contributor to disease burden worldwide and disproportionately affects low- and middle-income countries (LMICs) [ 1 ]. According to the International Agency for Research on Cancer (IARC), 20 million people were newly diagnosed with cancer and almost 10 million people died of it globally in 2022 [ 2 ]. The disease is predicted to double in incidence by 2070 worldwide, with the greatest increase in LMICs [ 3 ]. [ 2 ] Cancer is not just a physical illness but a major cause of psychological discomfort in individuals with cancer. Psychological illnesses such as depression, anxiety are well-recognised comorbidities for cancer patients that can happen at diagnosis, during treatment, or afterward [ 4 , 5 ]. Approximately one-third of cancer patients suffer from mental disorders, particularly depression and anxiety[ 6 ] and their rates are generally higher in LMICs compared to upper-income nations [ 7 , 8 ]. Recent systematic review of 94 studies shows psychiatric illnesses, such as anxiety and depression, affect approximately 10% and 20% of cancer patients, respectively [ 7 ]. Another review of 40 studies from LMICs found that 18% of cancer patients experience anxiety, while 21% suffer from depression disorders [ 8 ]. A growing body of literature reports that in cancer patients, anxiety and depression are likely to be influenced by multiple factors, including age, sex, residence, and economic conditions [ 7 – 10 ]. Similarly, clinical factors, such as cancer type and stage, have a profound impact on psychiatric illnesses [ 11 , 12 ]. The damage caused by cancer itself, and treatments such as various therapy, surgery and other treatments often result in both physical and psychological impairments [ 13 , 14 ]. Some studies highlighted discrepancies in mental health among cancer patients by geographical location[ 15 , 16 ] and it has resulted in a growing interest in evaluating these aspects in cancer patients. Hence, the research community is keenly interested in assessing these factors for quality cancer care, which may vary depending on where the patient lives. Bangladesh, a low- and middle-income country in South Asia with a population of over 170 million, reported 167,256 new cancer cases and 116,598 cancer-related deaths in 2022 [ 17 ]. This high incidence of cancer and the significant number of deaths highlight the challenges in managing cancer care in the country, where one-third of cancer patients experience severe financial burdens due to their treatment [ 18 ]. Psychological issues are still highly stigmatized in Bangladeshi society, leading many individuals to suffer mental health distress without seeking help [ 19 ]. While psychological support is a crucial component of cancer care, data are still limited in the context of Bangladesh. Against this backdrop, this study aimed to systematically examine the prevalence of anxiety and depression across different cancer types, disease stages, geographic regions, and other relevant demographic and clinical factors. Methods Study design and participants We conducted a cross-sectional study among cancer patients were receiving treatment at the outpatient department of the National Institute of Cancer Research & Hospital Dhaka, Bangladesh. The study hospital is the country’s only tertiary care specialised cancer hospital, offering multidisciplinary cancer care. Between April and June 2023, we recruited individuals diagnosed with cancer from the outpatient departments through a simple random sampling technique. Face-to-face interviews were conducted after obtaining written consent from participants. The sample comprised patients older than 18, receiving treatment in outpatient settings and whose had no apparent cognitive deficit. We excluded patients who were critically ill at the time of the interview and had a psychiatric history. Potential participants were asked whether they had ever been diagnosed with a mental health issue, and interviewers verified this information by consulting their caregivers. Data collection In a pilot study, 20 patients were tested on their understanding of relevant techniques and potential troublesome situations of interviews. We made necessary corrections based on the pilot study’s outcomes and used the final version of the questionnaire. A group of health professionals collected 516 completed data through face-to-face interviews. Before interviewing the patients, data collectors explained the study's objectives and goals, along with the risks and discomforts of the questions, and the benefits of the research. It was made clear to the respondents that participation in the study was entirely voluntary. The face-to-face interview took place one person at a time, to ensure privacy. Each questionnaire was checked for accuracy and completeness. The patients were informed that their data would be kept confidential, and any reporting would be done as a group with no identifying information. Measures Anxiety and depression assessment scale Participants were assessed for depressive and anxious symptoms using the frequently used and validated Hospital Anxiety and Depression Scale (HADS) [ 20 ]. The HADS instrument is a 14-question questionnaire that asks the patients about the degree of applicability of each item (question), using a 4-point Likert scale. Patients’ response ranges from 0 to 3, where 0 means “often” and 3 means “very seldom” or from “not at all” to “most of the time.” The subscale totals range from 0 to 21. We define severe symptoms as clinical concerns ranging from 11 to 21. Clinical characteristics Participants’ clinical characteristics included cancer sites and stage (early stage: I & II vs advanced stage: III & IV). Pathological diagnostic reports or current relevant treatment were used to determine the type of cancer site and patient stage. The most reported diagnosed cancer sites were categorised as oral, breast, blood, pancreas, liver, lung, brain, throat, cervical, and other cancer sites (e.g., eye, skin, bone, penile, ovarian). Sociodemographic characteristics The following sociodemographic variables were considered: sex (male vs female), age (in years), height (in inches), weight (in kilograms), marital status (never married, married, and widowed/divorced), schooling (no education, primary, secondary, higher secondary and tertiary), occupational status (not employed, employed, and housewife) and residence (urban vs rural). Statistical analysis Data were analyzed using R 3.6.2. Analyses of descriptive statistics were performed and reported as proportions and percentages for categorical variables. A multinomial regression model was fitted to examine the association of sociodemographic and clinical variables with anxiety and depression among cancer patients. The model’s multinomial regression coefficient was exponentiated and presented as relative risk ratios (RRR) along with corresponding 95% confidence intervals (CI). Here, RRR is the ratio of the proportion of an outcome (depression or anxiety) in the rural residency to the probability of an outcome in the urban residency. Results A total of 516 adult patients were interviewed. Of those, 63% were female, 78% were over 40, 63% had normal weight and 66% lived in rural areas. In addition, 46% had no education and 44% were unemployed. Moreover, 36% had breast cancer, 61% had early-stage disease, and 45% were diagnosed within 1 to 2 years of the data collection period (Table 1 ). Table 1 Patient’s background characteristics and their anxiety and depression level (n = 516). Characteristics N (%) Anxiety P value Depression P value No/mild Moderate Severe No/mild Moderate Severe Sex 0.559 0.021 Male 191(37.00) 116(60.70) 53(27.70) 22(11.50) 38(19.90) 100(52.40) 53(27.70) Female 325(63.00) 203(62.50) 94(28.90) 28(8.60) 100(30.80) 154(47.40) 71(21.80) Age in years < 0.001 < 0.001 60 116(22.50) 57(49.10) 37(31.90) 22(19.00) 25(21.60) 53(45.70) 38(32.80) Marital status 0.058 0.058 Unmarried 11(2.10) 9(81.80) 1(9.10) 1(9.10) 9(81.80) 1(9.10) 1(9.10) Married 454(88.00) 280(61.70) 135(29.70) 39(8.60) 280(61.70) 135(29.70) 39(8.60) Divorced/ widowed 51(9.90) 30(58.80) 11(21.60) 10(19.60) 30(58.80) 11(21.60) 10(19.60) Schooling 0.807 0.051 No schooling 237(45.90) 142(59.90) 70(29.50) 25(10.50) 55(23.20) 120(50.60) 62(26.20) 1 to 5 years 105(20.30) 67(63.80) 27(25.70) 11(10.50) 22(21.00) 52(49.50) 31(29.50) 6 to 12 years 129(25.00) 78(60.50) 40(31.00) 11(8.50) 43(33.30) 62(48.10) 24(18.60) 12 + years 45(8.70) 32(71.10) 10(22.20) 3(6.70) 18(40.00) 20(44.40) 7(15.60) BMI 0.167 0.128 Normal weight 327(63.40) 191(58.40) 105(32.10) 31(9.50) 80(24.50) 165(50.50) 82(25.10) Underweight 74(14.30) 49(66.20) 16(21.60) 9(12.20) 18(24.30) 34(45.90) 22(29.70) Overweight/Obese 115(22.30) 79(68.70) 26(22.60) 10(8.70) 40(34.80) 55(47.80) 20(17.40) Residence 0.038 < 0.001 Rural 340(65.90) 198(58.20) 109(32.10) 33(9.70) 62(18.20) 195(57.40) 83(24.40) Urban 176(34.10) 121(68.80) 38(21.60) 17(9.70) 76(43.20) 59(33.50) 41(23.30) Employment 0.063 < 0.001 Employed 78(15.10) 55(70.50) 13(16.70) 10(12.80) 35(44.90) 25(32.10) 18(23.10) Not employed 226(43.80) 136(60.20) 65(28.80) 25(11.10) 34(15.00) 124(54.90) 68(30.10) Housewife 212(41.10) 128(60.40) 69(32.50) 15(7.10) 69(32.50) 105(49.50) 38(17.9) Cancer type 0.163 Breast 185(35.90) 114(61.60) 61(33.00) 10(5.40) 63(34.10) 92(49.70) 30(16.20) Cervical 54(10.50) 33(61.10) 15(27.80) 6(11.10) 13(24.10) 24(44.40) 17(31.50) Colorectal 37(7.20) 29(78.40) 5(13.50) 3(8.10) 8(21.60) 20(54.10) 9(24.30) Head & Neck 65(12.60) 46(70.80) 10(15.40 9(13.80) 15(23.10) 29(44.60) 21(32.30) Lung 94(18.20) 54(57.40) 31(33.00) 9(9.60) 18(19.10) 51(54.30) 25(26.60) Oral 29(5.60) 18(62.10) 8(27.60) 3(10.30) 7(24.10 13(44.80) 9(31.00) Other cancers 52(10.10) 25(48.10) 17(32.70) 10(19.20) 14(26.90) 25(48.10) 13(25.00) Cancer stage < 0.001 < 0.001 Early (I & II) 316 (61.20) 200(63.30) 98(31.00) 18(5.70) 109(34.50) 152(48.10) 55(17.40) Advanced (III & IV) 200 (38.80) 119(59.50) 49(24.50) 32(16.00) 29(14.50) 102(51.00) 69(34.50) Diagnosis (year) 0.002 0.317 2 years 95(18.40) 47(49.50) 33(34.70) 15(15.80) 28(29.50) 44(46.30) 23(24.20) Primary caregiver 0.011 0.463 Children 224(43.40) 119(53.10) 79(35.30) 26(11.60) 52(23.20) 116(51.80) 56(25.00) Spouse 247(47.90) 168(68.00) 58(23.50) 21(8.50) 70(28.30) 118(47.80) 59(23.90) Others 45(8.70) 32(71.10) 10(22.20) 3(6.70) 16(35.60) 20(44.40) 9(20.00) Note : BMI: body mass index; p-value: probability value Of 516 patients, 38% had anxiety, of which 28% had moderate and 10% had severe anxiety. Patient’s residence, cancer stage, years of diagnosis and primary caregiver were significantly (p-value < 0.05) associated with anxiety (Table 1 ). Similarly, 73% of patients had depression of which 50% had moderate and 23% had severe depression. Patients’ sex, age, year of diagnosis and primary caregivers were significantly (p-value < 0.05) associated with depression (Table 1 ). Figure 1 shows the level of anxiety and depression of patients at cancer sites. The highest level of moderate anxiety was found in patients with breast (33%) and lung cancer (33%) followed by cervical cancer (28%). On the other hand, patients with head & neck cancer (14%) had the highest level of severe anxiety followed by cervical cancer (11%). Patients with colorectal cancer had the highest level of moderate depression (54%) followed by breast cancer (50%). Meanwhile, patients with head & neck cancer had the highest level of severe depression (32%) followed by cervical cancer (31%) (Fig. 1 ). Table 2 shows the results of a multinomial logistic regression model for predicting moderate and severe anxiety and depression among cancer patients. Patients aged 40–59 and > 60, relative to patients aged < 40 had 3.26 times (RRR: 3.26, 95% CI = 1.04–10.19) and 10.80 times (RRR: 10.80, 95% CI = 3.09–37.74) the odds of severe anxiety compared to mild/no anxiety, respectively. Patients with advanced-stage cancer were 3.18 times more likely to develop severe anxiety than early-stage cancer patients (RRR: 3.18, 95% CI = 1.57–6.42). Table 2 Multinomial logistic regression model to understand associated factors on anxiety and depression Participants’ characteristics Anxiety Depression Moderate Severe Moderate Severe RRR 95% CI RRR 95% CI RRR 95% CI RRR 95% CI Sex (reference: female) Male 0.88 0.55–1.39 0.93 0.47–1.86 1.16 0.96–2.69 1.48 0.82–2.67 Age group (reference: <40 years) 40–59 years 2.25 1.26–4.02 3.26 1.04–10.19 1.90 1.08–3.34 2.87 1.39–5.91 60 + years 2.56 1.22–5.35 9.80 3.09–17.74 1.61 0.75–3.45 4.47 1.81–10.99 Residence (reference: urban) Rural 1.86 1.18–2.93 1.17 0.60–2.31 4.06 2.54–6.50 2.37 1.37–4.11 Primary caregiver (reference: children) Others 0.73 0.33–1.66 0.63 0.16–2.42 0.82 0.35–1.93 0.84 0.30–2.33 Spouse 0.70 0.44–1.11 0.76 0.38–1.54 0.89 0.53–1.52 0.99 0.54–1.82 Years of diagnosis (reference: 2 years 3.98 2.05–7.73 1.93 0.80–4.70 0.69 0.33–1.43 0.36 0.16–0.83 Cancer stage (reference: early stage) Advanced stage 0.64 0.39–1.03 3.18 1.57–6.42 3.48 1.92–6.30 8.25 4.24–16.05 Note : RRR: relative risk ratio; CI: confidence interval; Early stage: stage I &II; Advanced stage: stage III & IV. Bold faces reflect the significance at a 5% significance level. Middle-aged (40–59 years) and old patients (> 60 years) were 2.87 times (RRR: 2.87, 95% CI = 1.39–5.91) and 4.47 times (RRR: 4.47, 95% CI = 1.81–10.99) more likely to affected by severe depression compared to younger age groups (< 40 years), respectively. The risk of severe depression was 2.37 times higher among patients from rural communities compared to those from urban areas (RRR: 2.37, 95% CI = 1.37–4.11). Patients diagnosed with cancer more than two years ago were significantly less likely to experience severe depression compared to those diagnosed less than a year ago (RRR: 0.36, 95% CI = 0.16–0.83). The risk of severe depression in advanced cancer patients was 8.25 times higher than in early-stage cancer patients (RRR: 8.25, 95% CI = 4.24–16.05). Discussion Our study identified the prevalence of anxiety and depression among patients by cancer site, stage, and residence, as well as identified key risk factors. Overall, 38% of our study patients had anxiety and 73% had depression symptoms. This finding is higher than a review of 40 studies in similar settings, which found that 18% of cancer patients had anxiety, while 21% had depression [ 8 ]. This discrepancy might arise from variations in cancer site and stage, sociodemographic differences, methodological variations, and sample size. We also found that patients with head & neck cancer had the highest levels of severe anxiety and depression compared with other cancers. The results of previous studies support our findings that head & neck cancer patients are most vulnerable to mental illnesses [ 21 , 22 ]. When treating and enduring head & neck cancer, patients may experience difficulty swallowing, breathing, speaking, and even appearance defects compared to other cancers [ 22 ]. These complications not only reduce patients' quality of life but also result in various complex psychosocial challenges stemming from stigma, adjustment disorders, loneliness, and changes in body image due to surgery [ 9 , 21 ]. Hence, it is prudent to ensure that psychological screening and support become routine parts of oncology care. According to the regression model, patients with advanced cancer were three times and eight times more likely to suffer from severe anxiety and depression than those with early cancer, respectively. In line with our findings, previous studies reported that patients with advanced cancer were three to five times more likely to suffer from anxiety and depression than patients with early-stage cancer, respectively [ 23 , 24 ]. Some studies also demonstrate that mental illnesses typically become the most severe during the advanced or metastatic phase and less severe after treatment, but this may increase depending on the cancer prognosis [ 25 – 27 ]. One possible reason could be the requirement of advanced care, aggressive treatment, multiple rounds of therapies, and patients’ critical condition in advanced cancer [ 26 , 28 ]. In addition to offering more efficient treatment options and preventing disease progression, an early diagnosis significantly impacts managing healthcare costs which is also linked to physiological complications [ 26 ]. It is hypothesised that the majority of patients seek treatment when the disease reaches an advanced stage, making the possibility of recovery unlikely. Hence, there is an urgent need to strengthen the health system by ensuring the availability of cancer diagnostics technologies to facilitate early detection and management. It's evident that the burden of mental health illnesses is not evenly distributed across the population and may differ between rural and urban dwellers [ 29 , 30 ]. In line with a previous study finding [ 30 ], our study found that severe depression was two times higher for rural cancer patients compared to urban patients. There are several reasons why rural cancer patients experience more mental illnesses compared to urban patients. Firstly, centralized health centers are located in urban areas and equipped with skilled health personnel, so urban patients can access them quickly and achieve effective cancer treatment outcomes [ 16 ]. Such variations in cancer care or treatment can put rural cancer patients at risk of physical impairment, which can impact their mental health [ 29 ]. In addition, rural patients often have difficulty gaining access to cancer information, resulting in slower cancer diagnosis and disease progression, which has a severe impact on mental health [ 16 ]. Further, cancer diagnoses might be more difficult to discuss in rural areas due to social norms regarding disclosure of psychological or emotional problems, even to mental health professionals [ 16 ]. Future studies are required to fully understand the factors contributing to the geographical difference in the experience of mental illness among cancer patients in Bangladesh and similar settings. Policy recommendations This study’s findings highlight the need for targeted support for cancer patients, especially those with head and neck cancer, who face high levels of anxiety and depression. Findings also show anxiety and depression go hand in hand with cancer progression, highlighting the need for an awareness program for screening and public health policies to early detection before metastasis. What was strikingly evident from this study is that rural cancer patients are particularly vulnerable to higher rates of depression compared to their urban counterparts, highlighting a potential ‘cancer health disparity’. This suggests that the burden of cancer is greater for rural individuals in Bangladesh. Policymakers are recommended to ensure a broader spectrum of care that includes psycho-oncological care for screening and support become routine parts of the cancer treatment plan, particularly in rural areas. This comprehensive approach is crucial for improving cancer treatment outcomes throughout the disease trajectory. Strength and limitations Our study used standardized psychometric measures that were valid and reliable among the patients on target. The study took place at the National Institute of Cancer Research & Hospital, where all Bangladeshi hospitals refer their cancer patients, allowing the results to be generalized to all cancer patients in the country. Several limitations should be taken into account when interpreting our results. First, the direction of association between anxiety and depression and related factors could not be established due to the cross-sectional nature of the study. Second, some of the physical symptoms, which are part of the HADS symptoms list, may have been due to the cancer itself or its treatment rather than due to anxiety or depression. These may have an impact on the magnitude of depression or anxiety in this study. Experimental or longitudinal studies are recommended for the screening, assessment, and psychosocial support intervention of patients with cancer. Conclusions The disproportionate impact of severe mental health problems among cancer patients residing in rural areas highlights the urgent need for targeted intervention and support. Patients with advanced-stage cancer, and those grappling with specific cancer types, such as head & neck cancer, are particularly vulnerable to heightened mental health challenges. Understanding the nuanced factors contributing to the mental health burden in these populations is imperative for developing comprehensive support strategies. Factors like geographical location, cancer site and stage play crucial roles in shaping the mental health landscape for these individuals. Efforts to address these challenges should encompass clinical treatments and holistic support systems that consider the unique circumstances to improve the overall health of rural cancer patients. By acknowledging and addressing these specific needs, healthcare providers can contribute significantly to improving the overall well-being of cancer patients in rural areas. Abbreviations IARC: International Agency for Research on Cancer LMICs: Low- and Middle-Income Countries HADS: Hospital Anxiety and Depression Scale BMI: Body Mass Index CI: Confidence Intervals RRR: Relative risk ratio Declarations Ethics approval statements All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki Declaration. Each participant was informed about the purpose of the study, the voluntary nature of participation, data storage and security measures and gave informed consent prior to participating. Official permission was obtained from the respective authorities for data collection in the hospital. The ethics committee of North South University, Bangladesh approved the study protocol (Ref-2021/OR-NSU/IRB/0401). Clinical trial number: Not applicable Consent for publication Not applicable. Data availability statement The data used and/or analysed during the current study are available upon reasonable request from the corresponding author. Data are located in controlled access data storage at . Funding statement This research did not receive any funding from any agency in the public, commercial, or not-for-profit sectors. Conflict of interests The authors declare that they have no competing interests. Authors’ contributions SKC and AH conceived and designed the experiments. MA, SS, SAS, TB, and AS were involved in the data collection process. AH analysed the data. SMC and MA interpreted the results. SKC and MA prepared the draft manuscript. SKC, AS, SHS, TB, SKB, and AH edited and reviewed the manuscript. AH supervised the study. All authors contributed to the critical revision and approved the submitted version of the manuscript. 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Urban vs. rural differences in psychiatric diagnoses, symptom severity, and functioning in a psychiatric sample. PLoS One. 2023;18:e0286366. Gunn KM, Berry NM, Meng X, Wilson CJ, Dollman J, Woodman RJ, et al. Differences in the health, mental health and health-promoting behaviours of rural versus urban cancer survivors in Australia. Support Care Cancer. 2020;28:633–43. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Discover Public Health → Version 1 posted Editorial decision: Revision requested 29 Aug, 2025 Reviews received at journal 16 Aug, 2025 Reviews received at journal 11 Aug, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers agreed at journal 05 Aug, 2025 Reviewers invited by journal 05 Aug, 2025 Editor assigned by journal 26 Jun, 2025 Submission checks completed at journal 26 Jun, 2025 First submitted to journal 25 Jun, 2025 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. 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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-6976895","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497365429,"identity":"5ba964eb-a418-4bd6-96b1-f986d87aca6d","order_by":0,"name":"Samar Kishor Chakma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIiWNgGAWjYPCCBB4GCSD1AcSWAIscAIkS1sI4A8jkAWtJIKwFbDgzDzFa5NtPJ36uYEiTkZ/dfOyz7Q6bfHvp9oePeX/cYeBnzzHApsXgTO5myTMMOTwGd44lz849k2bZI3PG2Jgn4RmDZM8b7FoYcjdINjBU8BhI5Bgz57YdNuCRyGGT5kk4zGBwA7st8v1vN/8EaZGfAdRiCdaS/gysxR6HFoYbuduAtuTwMNwAamEEa0kwg9gigcMvN95us2wwSOMxuJGWzNjblmbAA9RrOCftMI/EmWcF2B2Wu/lmQ0WyvfyM5MMMP9tsDNhnpD988MbmsBx/e/IGrA6DBgIm4MGtfBSMglEwCkYBIQAAnHRbnCzR/24AAAAASUVORK5CYII=","orcid":"","institution":"North South University","correspondingAuthor":true,"prefix":"","firstName":"Samar","middleName":"Kishor","lastName":"Chakma","suffix":""},{"id":497365430,"identity":"db3cadff-8f64-465a-80ad-c55676ee67f7","order_by":1,"name":"Md. Ahedulla","email":"","orcid":"","institution":"National Institute of Preventive and Social Medicine","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"","lastName":"Ahedulla","suffix":""},{"id":497365431,"identity":"daa5459d-9342-49f3-82d7-15616106b4a8","order_by":2,"name":"Soptonwita Saha","email":"","orcid":"","institution":"National Institute of Preventive and Social Medicine","correspondingAuthor":false,"prefix":"","firstName":"Soptonwita","middleName":"","lastName":"Saha","suffix":""},{"id":497365432,"identity":"eb9d5213-0834-4eda-904b-013d7ab20710","order_by":3,"name":"Shafiul Azam Shakil","email":"","orcid":"","institution":"National Institute of Preventive and Social Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shafiul","middleName":"Azam","lastName":"Shakil","suffix":""},{"id":497365433,"identity":"1726ea34-e389-409d-bfdf-4e99ef94d9bc","order_by":4,"name":"Afsana Shormi","email":"","orcid":"","institution":"East West Medical College","correspondingAuthor":false,"prefix":"","firstName":"Afsana","middleName":"","lastName":"Shormi","suffix":""},{"id":497365434,"identity":"e642be7a-58ff-4372-8b4c-d9a39ba4d9c4","order_by":5,"name":"Tapos Biswas","email":"","orcid":"","institution":"Research Rats","correspondingAuthor":false,"prefix":"","firstName":"Tapos","middleName":"","lastName":"Biswas","suffix":""},{"id":497365435,"identity":"6ce87cec-45a5-4e26-8798-60b546e323b5","order_by":6,"name":"Sujal Kumar Bokshi","email":"","orcid":"","institution":"District Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sujal","middleName":"Kumar","lastName":"Bokshi","suffix":""},{"id":497365436,"identity":"8dbc6c18-5c12-4d37-a2ea-7c8b069c1fff","order_by":7,"name":"Sayed Hossain Sohag","email":"","orcid":"","institution":"BRB Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sayed","middleName":"Hossain","lastName":"Sohag","suffix":""},{"id":497365437,"identity":"0d29a543-7e1a-47ce-a871-2a3538fbe490","order_by":8,"name":"Ahmed Hossain","email":"","orcid":"","institution":"University of Sharjah","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Hossain","suffix":""}],"badges":[],"createdAt":"2025-06-25 17:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6976895/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6976895/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12982-025-01119-y","type":"published","date":"2025-11-21T15:58:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88776883,"identity":"91023c53-2ab6-4e52-a3fc-6f0d7181d4a5","added_by":"auto","created_at":"2025-08-11 10:10:16","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75747,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of anxiety and depression in cancer sites\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6976895/v1/4a0289ebdd7c3e047853ddd7.jpg"},{"id":96650340,"identity":"4877550b-ce60-4771-a717-b70b715d3b0b","added_by":"auto","created_at":"2025-11-24 16:11:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1355973,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6976895/v1/f1fb6185-8771-4524-8c32-cbf92bb52fec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rural-Urban Disparity of Mental Health Symptoms Among Cancer Patients in Bangladesh: Results from a Multinomial Logistic Regression Model","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer is a crucial contributor to disease burden worldwide and disproportionately affects low- and middle-income countries (LMICs) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the International Agency for Research on Cancer (IARC), 20\u0026nbsp;million people were newly diagnosed with cancer and almost 10\u0026nbsp;million people died of it globally in 2022 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The disease is predicted to double in incidence by 2070 worldwide, with the greatest increase in LMICs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eCancer is not just a physical illness but a major cause of psychological discomfort in individuals with cancer. Psychological illnesses such as depression, anxiety are well-recognised comorbidities for cancer patients that can happen at diagnosis, during treatment, or afterward [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Approximately one-third of cancer patients suffer from mental disorders, particularly depression and anxiety[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and their rates are generally higher in LMICs compared to upper-income nations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Recent systematic review of 94 studies shows psychiatric illnesses, such as anxiety and depression, affect approximately 10% and 20% of cancer patients, respectively [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Another review of 40 studies from LMICs found that 18% of cancer patients experience anxiety, while 21% suffer from depression disorders [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA growing body of literature reports that in cancer patients, anxiety and depression are likely to be influenced by multiple factors, including age, sex, residence, and economic conditions [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Similarly, clinical factors, such as cancer type and stage, have a profound impact on psychiatric illnesses [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The damage caused by cancer itself, and treatments such as various therapy, surgery and other treatments often result in both physical and psychological impairments [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Some studies highlighted discrepancies in mental health among cancer patients by geographical location[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and it has resulted in a growing interest in evaluating these aspects in cancer patients. Hence, the research community is keenly interested in assessing these factors for quality cancer care, which may vary depending on where the patient lives.\u003c/p\u003e\u003cp\u003eBangladesh, a low- and middle-income country in South Asia with a population of over 170\u0026nbsp;million, reported 167,256 new cancer cases and 116,598 cancer-related deaths in 2022 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This high incidence of cancer and the significant number of deaths highlight the challenges in managing cancer care in the country, where one-third of cancer patients experience severe financial burdens due to their treatment [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Psychological issues are still highly stigmatized in Bangladeshi society, leading many individuals to suffer mental health distress without seeking help [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. While psychological support is a crucial component of cancer care, data are still limited in the context of Bangladesh. Against this backdrop, this study aimed to systematically examine the prevalence of anxiety and depression across different cancer types, disease stages, geographic regions, and other relevant demographic and clinical factors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eWe conducted a cross-sectional study among cancer patients were receiving treatment at the outpatient department of the National Institute of Cancer Research \u0026amp; Hospital Dhaka, Bangladesh. The study hospital is the country\u0026rsquo;s only tertiary care specialised cancer hospital, offering multidisciplinary cancer care. Between April and June 2023, we recruited individuals diagnosed with cancer from the outpatient departments through a simple random sampling technique. Face-to-face interviews were conducted after obtaining written consent from participants. The sample comprised patients older than 18, receiving treatment in outpatient settings and whose had no apparent cognitive deficit. We excluded patients who were critically ill at the time of the interview and had a psychiatric history. Potential participants were asked whether they had ever been diagnosed with a mental health issue, and interviewers verified this information by consulting their caregivers.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eIn a pilot study, 20 patients were tested on their understanding of relevant techniques and potential troublesome situations of interviews. We made necessary corrections based on the pilot study\u0026rsquo;s outcomes and used the final version of the questionnaire. A group of health professionals collected 516 completed data through face-to-face interviews. Before interviewing the patients, data collectors explained the study's objectives and goals, along with the risks and discomforts of the questions, and the benefits of the research. It was made clear to the respondents that participation in the study was entirely voluntary. The face-to-face interview took place one person at a time, to ensure privacy. Each questionnaire was checked for accuracy and completeness. The patients were informed that their data would be kept confidential, and any reporting would be done as a group with no identifying information.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eAnxiety and depression assessment scale\u003c/h2\u003e\u003cp\u003eParticipants were assessed for depressive and anxious symptoms using the frequently used and validated Hospital Anxiety and Depression Scale (HADS) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The HADS instrument is a 14-question questionnaire that asks the patients about the degree of applicability of each item (question), using a 4-point Likert scale. Patients\u0026rsquo; response ranges from 0 to 3, where 0 means \u0026ldquo;often\u0026rdquo; and 3 means \u0026ldquo;very seldom\u0026rdquo; or from \u0026ldquo;not at all\u0026rdquo; to \u0026ldquo;most of the time.\u0026rdquo; The subscale totals range from 0 to 21. We define severe symptoms as clinical concerns ranging from 11 to 21.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eClinical characteristics\u003c/h3\u003e\n\u003cp\u003eParticipants\u0026rsquo; clinical characteristics included cancer sites and stage (early stage: I \u0026amp; II vs advanced stage: III \u0026amp; IV). Pathological diagnostic reports or current relevant treatment were used to determine the type of cancer site and patient stage. The most reported diagnosed cancer sites were categorised as oral, breast, blood, pancreas, liver, lung, brain, throat, cervical, and other cancer sites (e.g., eye, skin, bone, penile, ovarian).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSociodemographic characteristics\u003c/h2\u003e\u003cp\u003eThe following sociodemographic variables were considered: sex (male vs female), age (in years), height (in inches), weight (in kilograms), marital status (never married, married, and widowed/divorced), schooling (no education, primary, secondary, higher secondary and tertiary), occupational status (not employed, employed, and housewife) and residence (urban vs rural).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData were analyzed using R 3.6.2. Analyses of descriptive statistics were performed and reported as proportions and percentages for categorical variables. A multinomial regression model was fitted to examine the association of sociodemographic and clinical variables with anxiety and depression among cancer patients. The model\u0026rsquo;s multinomial regression coefficient was exponentiated and presented as relative risk ratios (RRR) along with corresponding 95% confidence intervals (CI). Here, RRR is the ratio of the proportion of an outcome (depression or anxiety) in the rural residency to the probability of an outcome in the urban residency.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 516 adult patients were interviewed. Of those, 63% were female, 78% were over 40, 63% had normal weight and 66% lived in rural areas. In addition, 46% had no education and 44% were unemployed. Moreover, 36% had breast cancer, 61% had early-stage disease, and 45% were diagnosed within 1 to 2 years of the data collection period (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePatient\u0026rsquo;s background characteristics and their anxiety and depression level (n\u0026thinsp;=\u0026thinsp;516).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo/mild\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo/mild\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e191(37.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116(60.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(27.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(11.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(19.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100(52.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(27.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e325(63.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e203(62.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94(28.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28(8.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100(30.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154(47.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71(21.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge in years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121(23.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95(78.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(18.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(3.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50(41.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54(44.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(14.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e279(54.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167(59.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88(31.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24(8.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63(22.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e147(52.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(24.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116(22.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57(49.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(31.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(19.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(45.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(32.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(2.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(81.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(9.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(9.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(81.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(9.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(9.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e454(88.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e280(61.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135(29.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(8.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e280(61.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135(29.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(8.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced/ widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51(9.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(58.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(19.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(58.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(19.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSchooling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.051\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo schooling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e237(45.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e142(59.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70(29.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(10.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55(23.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e120(50.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62(26.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 to 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105(20.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67(63.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27(25.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(10.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(21.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52(49.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31(29.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 to 12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e129(25.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78(60.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40(31.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(8.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43(33.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62(48.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24(18.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(8.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(71.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(22.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(6.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(44.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(15.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e327(63.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e191(58.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105(32.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31(9.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80(24.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e165(50.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82(25.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e74(14.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49(66.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(12.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(24.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34(45.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22(29.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight/Obese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115(22.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79(68.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(22.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(8.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40(34.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55(47.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(17.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e340(65.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e198(58.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109(32.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33(9.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62(18.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e195(57.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83(24.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e176(34.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121(68.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(9.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76(43.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59(33.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41(23.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78(15.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55(70.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(16.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(12.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(44.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(32.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(23.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e226(43.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e136(60.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65(28.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(11.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34(15.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e124(54.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68(30.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e212(41.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e128(60.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(32.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(7.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(32.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105(49.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e185(35.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e114(61.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61(33.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(5.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63(34.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92(49.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30(16.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54(10.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33(61.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(27.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(11.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(24.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24(44.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(31.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eColorectal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(7.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(78.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(13.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(8.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(21.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(54.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(24.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHead \u0026amp; Neck\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65(12.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46(70.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(15.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(13.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(23.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(44.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(32.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94(18.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54(57.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31(33.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(9.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(19.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51(54.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(26.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(5.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(62.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(27.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(10.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(24.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(44.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(31.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther cancers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52(10.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(48.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(32.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(19.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(26.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(48.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(25.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarly (I \u0026amp; II)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e316 (61.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200(63.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98(31.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(5.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109(34.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e152(48.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55(17.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced (III \u0026amp; IV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e200 (38.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119(59.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49(24.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(16.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(14.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102(51.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(34.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis\u003c/strong\u003e (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.317\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e187(36.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e131(70.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(20.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(9.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(28.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83(44.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51(27.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 to 2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e234(45.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e141(60.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76(32.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(7.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57(24.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e127(54.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50(21.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95(18.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47(49.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33(34.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(15.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28(29.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(46.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(24.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary caregiver\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.463\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChildren\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e224(43.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119(53.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79(35.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(11.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52(23.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116(51.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56(25.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e247(47.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e168(68.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58(23.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(8.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70(28.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e118(47.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59(23.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(8.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(71.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(22.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(6.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(35.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(44.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: \u003cem\u003eBMI: body mass index; p-value: probability value\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOf 516 patients, 38% had anxiety, of which 28% had moderate and 10% had severe anxiety. Patient\u0026rsquo;s residence, cancer stage, years of diagnosis and primary caregiver were significantly (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) associated with anxiety (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Similarly, 73% of patients had depression of which 50% had moderate and 23% had severe depression. Patients\u0026rsquo; sex, age, year of diagnosis and primary caregivers were significantly (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) associated with depression (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the level of anxiety and depression of patients at cancer sites. The highest level of moderate anxiety was found in patients with breast (33%) and lung cancer (33%) followed by cervical cancer (28%). On the other hand, patients with head \u0026amp; neck cancer (14%) had the highest level of severe anxiety followed by cervical cancer (11%). Patients with colorectal cancer had the highest level of moderate depression (54%) followed by breast cancer (50%). Meanwhile, patients with head \u0026amp; neck cancer had the highest level of severe depression (32%) followed by cervical cancer (31%) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the results of a multinomial logistic regression model for predicting moderate and severe anxiety and depression among cancer patients. Patients aged 40\u0026ndash;59 and \u0026gt;\u0026thinsp;60, relative to patients aged\u0026thinsp;\u0026lt;\u0026thinsp;40 had 3.26 times (RRR: 3.26, 95% CI\u0026thinsp;=\u0026thinsp;1.04\u0026ndash;10.19) and 10.80 times (RRR: 10.80, 95% CI\u0026thinsp;=\u0026thinsp;3.09\u0026ndash;37.74) the odds of severe anxiety compared to mild/no anxiety, respectively. Patients with advanced-stage cancer were 3.18 times more likely to develop severe anxiety than early-stage cancer patients (RRR: 3.18, 95% CI\u0026thinsp;=\u0026thinsp;1.57\u0026ndash;6.42).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultinomial logistic regression model to understand associated factors on anxiety and depression\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eParticipants\u0026rsquo; characteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRRR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRRR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRRR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRRR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e (reference: female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u0026ndash;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.47\u0026ndash;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u0026ndash;2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u0026ndash;2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e (reference: \u0026lt;40 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u0026ndash;59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.26\u0026ndash;4.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.04\u0026ndash;10.19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.08\u0026ndash;3.34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.39\u0026ndash;5.91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.22\u0026ndash;5.35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.09\u0026ndash;17.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.75\u0026ndash;3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.81\u0026ndash;10.99\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e (reference: urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.18\u0026ndash;2.93\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60\u0026ndash;2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.54\u0026ndash;6.50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.37\u0026ndash;4.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary caregiver\u003c/strong\u003e (reference: children)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u0026ndash;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.16\u0026ndash;2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.35\u0026ndash;1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.30\u0026ndash;2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u0026ndash;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38\u0026ndash;1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.53\u0026ndash;1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.54\u0026ndash;1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears of diagnosis\u003c/strong\u003e (reference: \u0026lt;1 year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.38\u0026ndash;3.63\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.40\u0026ndash;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.91\u0026ndash;2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u0026ndash;1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;2 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.05\u0026ndash;7.73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u0026ndash;4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u0026ndash;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.16\u0026ndash;0.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer stage\u003c/strong\u003e (reference: early stage)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u0026ndash;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.57\u0026ndash;6.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.92\u0026ndash;6.30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.24\u0026ndash;16.05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: \u003cem\u003eRRR: relative risk ratio; CI: confidence interval; Early stage: stage I \u0026amp;II; Advanced stage: stage III \u0026amp; IV.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003cstrong\u003eBold faces\u003c/strong\u003e \u003cem\u003ereflect the significance at a 5% significance level.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eMiddle-aged (40\u0026ndash;59 years) and old patients (\u0026gt;\u0026thinsp;60 years) were 2.87 times (RRR: 2.87, 95% CI\u0026thinsp;=\u0026thinsp;1.39\u0026ndash;5.91) and 4.47 times (RRR: 4.47, 95% CI\u0026thinsp;=\u0026thinsp;1.81\u0026ndash;10.99) more likely to affected by severe depression compared to younger age groups (\u0026lt;\u0026thinsp;40 years), respectively. The risk of severe depression was 2.37 times higher among patients from rural communities compared to those from urban areas (RRR: 2.37, 95% CI\u0026thinsp;=\u0026thinsp;1.37\u0026ndash;4.11). Patients diagnosed with cancer more than two years ago were significantly less likely to experience severe depression compared to those diagnosed less than a year ago (RRR: 0.36, 95% CI\u0026thinsp;=\u0026thinsp;0.16\u0026ndash;0.83). The risk of severe depression in advanced cancer patients was 8.25 times higher than in early-stage cancer patients (RRR: 8.25, 95% CI\u0026thinsp;=\u0026thinsp;4.24\u0026ndash;16.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study identified the prevalence of anxiety and depression among patients by cancer site, stage, and residence, as well as identified key risk factors. Overall, 38% of our study patients had anxiety and 73% had depression symptoms. This finding is higher than a review of 40 studies in similar settings, which found that 18% of cancer patients had anxiety, while 21% had depression [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This discrepancy might arise from variations in cancer site and stage, sociodemographic differences, methodological variations, and sample size.\u003c/p\u003e\u003cp\u003eWe also found that patients with head \u0026amp; neck cancer had the highest levels of severe anxiety and depression compared with other cancers. The results of previous studies support our findings that head \u0026amp; neck cancer patients are most vulnerable to mental illnesses [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. When treating and enduring head \u0026amp; neck cancer, patients may experience difficulty swallowing, breathing, speaking, and even appearance defects compared to other cancers [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These complications not only reduce patients' quality of life but also result in various complex psychosocial challenges stemming from stigma, adjustment disorders, loneliness, and changes in body image due to surgery [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Hence, it is prudent to ensure that psychological screening and support become routine parts of oncology care.\u003c/p\u003e\u003cp\u003eAccording to the regression model, patients with advanced cancer were three times and eight times more likely to suffer from severe anxiety and depression than those with early cancer, respectively. In line with our findings, previous studies reported that patients with advanced cancer were three to five times more likely to suffer from anxiety and depression than patients with early-stage cancer, respectively [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Some studies also demonstrate that mental illnesses typically become the most severe during the advanced or metastatic phase and less severe after treatment, but this may increase depending on the cancer prognosis [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. One possible reason could be the requirement of advanced care, aggressive treatment, multiple rounds of therapies, and patients\u0026rsquo; critical condition in advanced cancer [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In addition to offering more efficient treatment options and preventing disease progression, an early diagnosis significantly impacts managing healthcare costs which is also linked to physiological complications [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. It is hypothesised that the majority of patients seek treatment when the disease reaches an advanced stage, making the possibility of recovery unlikely. Hence, there is an urgent need to strengthen the health system by ensuring the availability of cancer diagnostics technologies to facilitate early detection and management.\u003c/p\u003e\u003cp\u003eIt's evident that the burden of mental health illnesses is not evenly distributed across the population and may differ between rural and urban dwellers [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In line with a previous study finding [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], our study found that severe depression was two times higher for rural cancer patients compared to urban patients. There are several reasons why rural cancer patients experience more mental illnesses compared to urban patients. Firstly, centralized health centers are located in urban areas and equipped with skilled health personnel, so urban patients can access them quickly and achieve effective cancer treatment outcomes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Such variations in cancer care or treatment can put rural cancer patients at risk of physical impairment, which can impact their mental health [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In addition, rural patients often have difficulty gaining access to cancer information, resulting in slower cancer diagnosis and disease progression, which has a severe impact on mental health [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Further, cancer diagnoses might be more difficult to discuss in rural areas due to social norms regarding disclosure of psychological or emotional problems, even to mental health professionals [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Future studies are required to fully understand the factors contributing to the geographical difference in the experience of mental illness among cancer patients in Bangladesh and similar settings.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePolicy recommendations\u003c/h2\u003e\u003cp\u003eThis study\u0026rsquo;s findings highlight the need for targeted support for cancer patients, especially those with head and neck cancer, who face high levels of anxiety and depression. Findings also show anxiety and depression go hand in hand with cancer progression, highlighting the need for an awareness program for screening and public health policies to early detection before metastasis. What was strikingly evident from this study is that rural cancer patients are particularly vulnerable to higher rates of depression compared to their urban counterparts, highlighting a potential \u0026lsquo;cancer health disparity\u0026rsquo;. This suggests that the burden of cancer is greater for rural individuals in Bangladesh. Policymakers are recommended to ensure a broader spectrum of care that includes psycho-oncological care for screening and support become routine parts of the cancer treatment plan, particularly in rural areas. This comprehensive approach is crucial for improving cancer treatment outcomes throughout the disease trajectory.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eStrength and limitations\u003c/h2\u003e\u003cp\u003eOur study used standardized psychometric measures that were valid and reliable among the patients on target. The study took place at the National Institute of Cancer Research \u0026amp; Hospital, where all Bangladeshi hospitals refer their cancer patients, allowing the results to be generalized to all cancer patients in the country. Several limitations should be taken into account when interpreting our results. First, the direction of association between anxiety and depression and related factors could not be established due to the cross-sectional nature of the study. Second, some of the physical symptoms, which are part of the HADS symptoms list, may have been due to the cancer itself or its treatment rather than due to anxiety or depression. These may have an impact on the magnitude of depression or anxiety in this study. Experimental or longitudinal studies are recommended for the screening, assessment, and psychosocial support intervention of patients with cancer.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe disproportionate impact of severe mental health problems among cancer patients residing in rural areas highlights the urgent need for targeted intervention and support. Patients with advanced-stage cancer, and those grappling with specific cancer types, such as head \u0026amp; neck cancer, are particularly vulnerable to heightened mental health challenges. Understanding the nuanced factors contributing to the mental health burden in these populations is imperative for developing comprehensive support strategies. Factors like geographical location, cancer site and stage play crucial roles in shaping the mental health landscape for these individuals. Efforts to address these challenges should encompass clinical treatments and holistic support systems that consider the unique circumstances to improve the overall health of rural cancer patients. By acknowledging and addressing these specific needs, healthcare providers can contribute significantly to improving the overall well-being of cancer patients in rural areas.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIARC: International Agency for Research on Cancer\u003c/p\u003e\n\u003cp\u003eLMICs: Low- and Middle-Income Countries\u003c/p\u003e\n\u003cp\u003eHADS: Hospital Anxiety and Depression Scale\u003c/p\u003e\n\u003cp\u003eBMI: Body Mass Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI: Confidence Intervals\u003c/p\u003e\n\u003cp\u003eRRR: Relative risk ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the 1964 Helsinki Declaration. Each participant was informed about the purpose of the study, the voluntary nature of participation, data storage and security measures and gave informed consent prior to participating. Official permission was obtained from the respective authorities for data collection in the hospital. The ethics committee of North South University, Bangladesh approved the study protocol (Ref-2021/OR-NSU/IRB/0401). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used and/or analysed during the current study are available upon reasonable request from the corresponding author.\u0026nbsp;Data are located in controlled access data storage at\u0026nbsp;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any funding from any agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSKC and AH conceived and designed the experiments. MA, SS, SAS, TB, and AS were involved in the data collection process. AH analysed the data. SMC and MA interpreted the results. SKC and MA prepared the draft manuscript. SKC, AS, SHS, TB, SKB, and AH edited and reviewed the manuscript. AH supervised the study. All authors contributed to the critical revision and approved the submitted version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the patients who voluntarily participated in the study and the hospital authority for permitting data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, Harvey JD, et al. cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life years for 29 cancer groups from 2010 to 2019 a systematic analysis for the global burden of disease study 2019. JAMA Oncol. 2022;8:420\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024. \u003c/li\u003e\n\u003cli\u003eSoerjomataram I, Bray F. Planning for tomorrow: global cancer incidence and the role of prevention 2020\u0026ndash;2070. Nat Rev Clin Oncol. 2021;18:663\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eChang WH, Lai AG. Cumulative burden of psychiatric disorders and self-harm across 26 adult cancers. Nature Medicine. 2022 28:4. \u003c/li\u003e\n\u003cli\u003eMazor M, Paul SM, Chesney MA, Chen LM, Smoot B, Topp K, et al. Perceived stress is associated with a higher symptom burden in cancer survivors. Cancer. 2019;125:4509\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eWang Y, Duan Z, Ma Z, Mao Y, Li X, Wilson A, et al. Epidemiology of mental health problems among patients with cancer during COVID-19 pandemic. Translational Psychiatry. 2020;10:1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eMitchell AJ, Chan M, Bhatti H, Halton M, Grassi L, Johansen C, et al. Prevalence of depression, anxiety, and adjustment disorder in oncological, haematological, and palliative-care settings: a meta-analysis of 94 interview-based studies. Lancet Oncol. 2011;12:160\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eWalker ZJ, Xue S, Jones MP, Ravindran AV. Depression, anxiety, and other mental disorders in patients with cancer in low- and lower-middle-income countries: a systematic review and meta-analysis. JCO Glob Oncol. 202;7:1233-1250.\u003c/li\u003e\n\u003cli\u003eHammerm\u0026uuml;ller C, Hinz A, Dietz A, Wichmann G, Pirlich M, Berger T, et al. Depression, anxiety, fatigue, and quality of life in a large sample of patients suffering from head and neck cancer in comparison with the general population. BMC Cancer. 2021;21:1\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eYang YL, Liu L, Wang Y, Wu H, Yang XS, Wang JN, et al. The prevalence of depression and anxiety among Chinese adults with cancer: A systematic review and meta-analysis. BMC Cancer. 2013;13:1\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eGoerling U, Hinz A, Koch-Gromus U, Hufeld JM, Esser P, Mehnert-Theuerkauf A. Prevalence and severity of anxiety in cancer patients: results from a multi-center cohort study in Germany. J Cancer Res Clin Oncol. 2023;149:6371\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003evan Tuijl LA, Basten M, Pan KY, Vermeulen R, Portengen L, de Graeff A, et al. Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis. Cancer. 2023;129:3287\u0026ndash;99.\u003c/li\u003e\n\u003cli\u003eMohsin FM, Rahman MS, Shahjalal M. Prevalence and factors associated with malnutrition on patients with cancer in Bangladesh: a cross-sectional study. BMJ Public Health. 2024;2:e000337.\u003c/li\u003e\n\u003cli\u003eSinger S, Das-Munshi J, Br\u0026auml;hler E. Prevalence of mental health conditions in cancer patients in acute care-a meta-analysis. Annals of Oncology. 2009;21:925\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003evan der Kruk SR, Butow P, Mesters I, Boyle T, Olver I, White K, et al. Psychosocial well-being and supportive care needs of cancer patients and survivors living in rural or regional areas: a systematic review from 2010 to 2021. Supportive Care in Cancer. 2022;30:1021\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eBurris JL, Andrykowski M. Disparities in mental health between rural and nonrural cancer survivors: A preliminary study. Psychooncology. 2010;19:637\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eBangladesh Cancer Statistics. International Agency for Research on Cancer. Cancer Today. 2022.\u003c/li\u003e\n\u003cli\u003eShahjalal M, Dahal PK, Mosharaf MdP, Alam MM, Hawlader MDH, Mahumud RA. Economic burden of healthcare services on cancer survivors in Bangladesh. Cancer Rep. 2024;7.\u003c/li\u003e\n\u003cli\u003eFaruk O, Hasan Khan A, Uddin K, Chowdhury A, Jahan S, Chandra Sarker D, et al. Mental illness stigma in Bangladesh: Findings from a cross-sectional survey. Glob Ment Health (Camb). 2023;10:e59.\u003c/li\u003e\n\u003cli\u003eZigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand. 1983;67:361\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003ePichardo PFA, Desiato VM, Hellums RN, Altman KW, Purdy NC, Haugen T. Depression and anxiety in patients with head and neck cancer undergoing free flap reconstruction. Am J Otolaryngol. 2024;45:104044.\u003c/li\u003e\n\u003cli\u003eHammerm\u0026uuml;ller C, Hinz A, Dietz A, Wichmann G, Pirlich M, Berger T, et al. Depression, anxiety, fatigue, and quality of life in a large sample of patients suffering from head and neck cancer in comparison with the general population. BMC Cancer. 2021;21.\u003c/li\u003e\n\u003cli\u003eAyalew M, Deribe B, Duko B, Geleta D, Bogale N, Gemechu L, et al. Prevalence of depression and anxiety symptoms and their determinant factors among patients with cancer in southern Ethiopia: a cross-sectional study. BMJ Open. 2022;12:e051317.\u003c/li\u003e\n\u003cli\u003eNaser AY, Hameed AN, Mustafa N, Alwafi H, Dahmash EZ, Alyami HS, et al. Depression and anxiety in patients with cancer: a cross-sectional study. Front Psychol. 2021;12.\u003c/li\u003e\n\u003cli\u003ePitman A, Suleman S, Hyde N, Hodgkiss A. Depression and anxiety in patients with cancer. BMJ. 2018;361:k1415.\u003c/li\u003e\n\u003cli\u003eVodermaier A, Linden W, MacKenzie R, Greig D, Marshall C. Disease stage predicts post-diagnosis anxiety and depression only in some types of cancer. Br J Cancer. 2011;105:1814\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eNiedzwiedz CL, Knifton L, Robb KA, Katikireddi SV, Smith DJ. Depression and anxiety among people living with and beyond cancer: A growing clinical and research priority. BMC Cancer. 2019;19:1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eShahjalal M, Sultana M, Gow J, Hoque ME, Mistry SK, Hossain A, et al. Assessing health-related quality of life among cancer survivors during systemic and radiation therapy in Bangladesh: a cancer-specific exploration. BMC Cancer. 2023;23.\u003c/li\u003e\n\u003cli\u003eForrest LN, Waschbusch DA, Pearl AM, Bixler EO, Sinoway LI, Kraschnewski JL, et al. Urban vs. rural differences in psychiatric diagnoses, symptom severity, and functioning in a psychiatric sample. PLoS One. 2023;18:e0286366.\u003c/li\u003e\n\u003cli\u003eGunn KM, Berry NM, Meng X, Wilson CJ, Dollman J, Woodman RJ, et al. Differences in the health, mental health and health-promoting behaviours of rural versus urban cancer survivors in Australia. Support Care Cancer. 2020;28:633\u0026ndash;43.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cancer, disparity, mental health, anxiety, depression, disparity, multinomial regression, cancer stage","lastPublishedDoi":"10.21203/rs.3.rs-6976895/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6976895/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCancer can trigger distinct emotional reactions and difficulties for individuals, spanning from anxiety and depression to coping with treatment-related stressors. Geographic location can also influence access to mental health resources, cultural impacts on views, and available support systems for cancer patients. It is crucial to recognise these complexities when crafting mental health interventions and support approaches. Therefore, we investigated anxiety and depression prevalence among patients by cancer sites, stages, residence, and other associated factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis cross-sectional study was conducted at a leading cancer-specialised hospital in Bangladesh from April to June 2023. The Hospital Anxiety and Depression Scale (HADS) was used to assess depressive and anxious symptoms, and scores above 11 out of 21 were considered severe symptoms that need clinical concern. Subsequently, a multinomial regression model, adjusting for confounders, was applied to identify potential risk factors associated with different levels of anxiety and depression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf 516 cancer patients, 63% were females, averaging 51.14 years (standard deviation 12.28). Of them, 10% reported severe anxiety, and 23% reported severe depression. Patients with head \u0026amp; neck cancer reported high levels of severe anxiety and depression. The level of severe anxiety increased with the cancer stage, being 3.18 times higher for advanced-stage patients compared to early-stage patients (relative risk ratio [RRR]: 3.18, 95% confidence interval [CI]\u0026thinsp;=\u0026thinsp;1.57\u0026ndash;6.42). Similarly, severe depression in advanced-stage patients was 8.25 times higher compared to early-stage patients (RRR: 8.25, 95% CI\u0026thinsp;=\u0026thinsp;4.24\u0026ndash;16.05). Despite similar anxiety levels, patients living in rural areas had 2.37 times more severe depression than those living in urban areas (RRR: 2.37, 95% CI\u0026thinsp;=\u0026thinsp;1.37\u0026ndash;4.11).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eCancer patients in rural areas are disproportionately affected by severe mental health issues. Patients with advanced-stage cancer and those with head \u0026amp; neck cancer are at particularly high risk of severe mental health symptoms. It is essential to ensure these patients receive the needed mental health support alongside a tailored treatment plan.\u003c/p\u003e","manuscriptTitle":"Rural-Urban Disparity of Mental Health Symptoms Among Cancer Patients in Bangladesh: Results from a Multinomial Logistic Regression Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 10:02:11","doi":"10.21203/rs.3.rs-6976895/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-29T10:14:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-16T19:10:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T03:39:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186603566090032792336746662161647952814","date":"2025-08-06T03:33:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117697095747884367251944288625189986120","date":"2025-08-05T23:05:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166744184242961819867381039855907079534","date":"2025-08-05T19:12:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"153357323726082402500588240521540530121","date":"2025-08-05T19:09:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-05T19:06:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-27T01:17:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-27T01:16:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2025-06-25T16:52:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e98cbd29-7111-4566-8fce-68a6185a1344","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:06:25+00:00","versionOfRecord":{"articleIdentity":"rs-6976895","link":"https://doi.org/10.1186/s12982-025-01119-y","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2025-11-21 15:58:21","publishedOnDateReadable":"November 21st, 2025"},"versionCreatedAt":"2025-08-11 10:02:11","video":"","vorDoi":"10.1186/s12982-025-01119-y","vorDoiUrl":"https://doi.org/10.1186/s12982-025-01119-y","workflowStages":[]},"version":"v1","identity":"rs-6976895","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6976895","identity":"rs-6976895","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}