Prevalence of depression and anxiety among elderly primary care patients in Palestine

Prevalence of depression and anxiety among elderly primary care patients in Palestine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence of depression and anxiety among elderly primary care patients in Palestine Bessan Maraqa, Zaher Nazzal, barlant alutt, ekram rishmawi, suha hamshari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2195431/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Depression and anxiety are common mental health disorders among the elderly worldwide. In this study, we estimated the prevalence of depression and anxiety and related risk factor among elderly attending PHC centers in Palestine. Methods: A cross-sectional study was conducted on a sample size of 380 participants aged ≥60 attending PHC centers in West Bank, using an interviewer-administered questionnaire. We used the Geriatric Depression Scale-15 and the Geriatric Anxiety Scale to screen for depression and anxiety, respectively.We analyzed data using descriptive and analytical statistics and employed logistic regression model to identify predictors of depression and anxiety. Results : The prevalence of depression and anxiety was 41.1% and 39.2%, respectively. Eldely people living in rural areas (aOR 2.6, 95%CI: 1.7-4.2), uneducated (aOR 2.9, 95%CI: 1.4-6.1), and without monthly income (aOR 3.4, 95%CI: 1.5-7.6) were more likely to have depression. On the other hand, anxiety is independently assosciated with living in rural areas (aOR 1.9, 95%CI: 1.2-3.0) and having non-communicable diseases (aOR 2.0, 95%CI: 1.1-3.5). Conclusion: Depression and anxiety are common in Palestine, a developing country with a lack of elderly-related services. This should be emphasized at the national and regional levels where geriatric health care services are scarce. Such information is required by policymakers and external funding agencies in order to develop future agendas Depression Anxiety Elderly Primary health Introduction Nowadays, the average individual can foresee living well into their sixties and beyond. People over 60 years of age are a growing proportion of the general population. In 2019, the global population of adults aged 60 and over topped one billion. The forecast estimates 1.4 billion people in 2030 and 2.1 billion in 2050.[1] Healthy aging is critical for reaping the full benefits of increased longevity.[2] While elderly individuals in the developed world have slightly better health than previous generations, good health later in life is not fairly distributed. Mental health is an important part of living well.care services are still below optimal in low to middle-income countries. According to World Health Organization 15% of adults 60 and older suffer a mental disorder.[3] A recent pooled analysis of depression prevalence among the elderly revealed an average predicted prevalence of 31.7% (95%CI 27.9, 35.6). In the subgroup analysis, the pooled prevalence was higher in developing countries, reaching almost 40.8%. Older women, single, divorced or widowed, education level (low or nonexistent), family's history of significant life events (such as a family death), and her physical health (diabetes or heart disease) are all risk factors.[4] Anxiety is also an issue in the elderly. Community samples revealed up to 15% suffered from anxiety, while clinical settings showed 28%. It was significantly higher in terms of anxiety symptoms, ranging between 15% and 52.3% in population samples and 15% to 56% in clinical samples.[5] Diagnosing anxiety symptoms may be more challenging in older adults, as anxiety symptoms may be misinterpreted for physical illness symptoms.[6] Health care practitioners often underdiagnose mental health illnesses, and the stigma associated with these conditions inhibits people from getting help. NEED citation. Few studies evaluate common mental disorders among older ages in Arab countries. The stigma associated with the significant societal implications of mental disorders might be one barrier to diagnosis and treatment.[7] In Palestine, clinicians do not have screening guidelines and rarely use screening instruments. NEED citation. However, numerous visits to primary health care centers (PHC) with physical symptoms are indicators of mental health problems that frequently goes untreated.[8] In Palestine, more than a third of the population is comprised of individuals aged sixty and over..[9] While those over 60 account for only 5% of the Palestinian population, they head one in every six households and account for 13% of the labour force. The poverty rate for individuals living in households headed by an older person are much higher than in other households, 32% versus 29%.[10] Additionally, Palestine has unique challenges with movement restrictions due to the Occupation, and a scarcity of mental health services.[11] The purpose of this study is to determine the prevalence of depression and anxiety among elderly adults presenting PHC in the Occupied West Bank and factors that influence those mental health diagnoses. Methods Design and Study population We conducted a cross-sectional study using an interview-administered questionnaire. Adults aged 60 years and older who attended the three main PHC centers in the West Bank of Palestine were asked to participation between February to July 2021. The sample size was 380, as calculated by Epi Info 6.0, at an 80% power level and a 95% confidence level. [12] Measures: The questionnaire consisted of 3 sections: 1) sociodemographic and medical history such as age, sex, residency, educational level, house setting, professional status, source of income and history of chronic medical conditions such as hypertension, diabetes mellitus, cancer, and ischemic heart disease based on previous medical evaluations and diagnosis. 2) A shorter form of the Geriatric Depression Scale to assess depression (GDS-15). This diagnostic measure is designed exclusively for identifying depression in older adults. The scale consists of 15 items that can be answered yes or no. The GDS score ranges from 0 to 15, with 0 indicating no depression, 5-8 indicating mild depression, 9-11 indicating moderate depression, and 12-15 indicating severe depression.[13]–[15] Depression was suggested by a cut-off value of six or higher. [13], [14] 3) The Geriatric Anxiety Scale (GAS) assessed anxiety. This self-report screening and assessment tool is specifically designed for older adults. It consists of 25 scoreable items that assess experienced anxiety symptoms. A total anxiety score is computed by adding the self-reported ratings on items 1-25, with higher scores indicating greater anxiety levels. A total score of 0-11 indicates minimal anxiety symptoms, 12-21 indicates mild anxiety symptoms, 22-27 indicates moderate anxiety symptoms, and scores of 28 and higher exhibit severe anxiety symptoms.[16], [17] To categorize anxiety into two groups, a cut-off score of 16 was chosen based on the literature. Those with a score greater than 16 were termed anxious, while those with a score less than or equal to 16 were classified as not anxious.[18] Arabic versions of both have a very high/excellent level of reliability.[14], [19] In this study, Cronbach alpha for depression items is 0.83 and anxiety items is 0.92, which shows excellent reliability. Analysis Plan The analysis was conducted using IBM SPSS Statistics for Windows, Version 20.0 (IBM Corp., Armonk, NY: IBM Corp). The demographic and clinical features of the subjects were described using descriptive statistics (means, standard deviations for continuous variables, and frequency distributions and proportions for categorical variables). Additionally, the chi-squared test and logistic regression were employed to determine any significant relationships between the groups. The level of significance was determined at p< 0.05. Ethical considerations All methods involving human participants in this study were conducted per ethical research standards. The study was conducted in conformity with the ethical norms of An-Najah National University (ANNU). The Ministry of Health approved authorization for the study to be conducted in PHC settings, and participants were approached and invited voluntarily to participate. Participants were assured of their confidentiality and anonymity. Results Of the 447 questionnaires distributed, 380 patients agreed to the interview, representing an 85% response rate. Just over half (52.1%) were male, most (76.6%) were married, two thirds (69.9) were between 60 and 70 years of age. Sociodemographics are presented in Table 1. Prevalence of depression and anxiety Among the participants, 156 [41.1% (95% CI: 36.1%-46.2%)] were found to have depression, with mild depression accounting for 28.4%, moderate depression accounting for 13.4%, and severe depression accounting for 6.3%. Anxiety was reported among 149 participants [39.2%, (95% CI: 34.3%-44.3%)] with mild anxiety accounting for 28.4%, moderate anxiety accounting for 13.4%, and severe anxiety accounting for 6.3%. How many had both depression and anxiety? We conducted bivariate analysis and the Chi-squared test to investigate the factors associated with depression and anxiety Older people living in rural areas, with a lower educational level, and were unemployed, and had no source of income were more likely to have depression (Table 2). In contrast, single female elderly who lived in rural areas, and had a lower educational level showed significantly higher anxiety levels. Furthermore, older people who live alone, are unemployed, have no income, or have a non-communicable disease have substantially greater anxiety levels (Table 3). Any data for patients with both depression and anxiety?? We conducted the multivariable analysis to explore variables independently related to depression and anxiety among the elderly. Older people living in rural areas were shown to be 2.6 times more likely to be depressed than those living in urban (p-value <0.001, aOR 2.6, 95%CI: 1.7-4.2), as did those with a lower educational level (p-value 0.004, aOR 2.9, 95%CI: 1.4-6.1) and those with no monthly income (p-value 0.003, aOR 3.4, 95%CI: 1.5-7.6). On the other hand, anxiety among older people was found to be independently associated with living in rural areas (p-value 0.007, aOR 1.9, 95%CI: 1.2-3.0) and among those with a non-communicable disease (p-value 0.026, aOR 2.0, 95%CI: 1.1-3.5) (Table 4). Discussion To our knowledge, this is the first study examining the prevalence of depression and anxiety in adults over 60 years seeking care in primary care centers in Palestine. Consistent with other studies, physical illness is a common risk factor for mental illness, particularly in the elderly. [20] In this context, we need to emphasize the importance of screening for anxiety and depression in PHC settings, especially when NCDs are present. , In our sample 41.1% suffer from depression, 39.2% from anxiety. These findings corroborate a meta-analysis that assessed the global prevalence of depression to be 31.7% and 40.7% in developing countries.[4] Research conducted in nearby Egypt reported a prevalence of depression and anxiety of 37.5% and 14.2%, respectively.[21] Health professionals should routinely assess for depression and anxiety among the elderly. Professional organizations in Palestine should adopt guidelines and policies to encourage assessing the elderly for the WHO guidelines . Policymakers and other key stakeholders should allocate resources to facilitate screening and treatment. Undiagnosed and untreated depression and anxiety can consume health care resources with unnecessary workups and testing for physical symptoms [3] establish effective control measures and offer routine geriatric care. On the other hand, in a financially impoverished country such as Palestine, such mental illnesses can impose a significant financial and institutional load on primary health care facilities. [22]. Our results for both anxiety and depression were surprising because the female gender and single status, which are considered risk factors[23], are not significant in our sample. Age, on the other hand, was not significantly associated with either anxiety or depression.This is likely due to local culture and traditions that value the elderly and encourage people, particularly women and unmarried women, to assist them financially and socially. Rural-urban differences in mental disorders have piqued the interest of researchers and policymakers involved in mental health care. Due to community ties and social isolation, city inhabitants may be more prone to depression than rural residents.[24] Inequalities of health care and access barriers could explain the apparent correlation between both anxiry and depression an rural and urban residence. In the relationship between depression and education, low education was significantly associated with depression in developing and developed countries. In contrast, income was not strongly related to depression in low- to middle-income countries, contradicting our findings.[25] This could indicate that educated individuals better understand the issue and are more likely to seek medical treatment early. While in terms of income, as previously stated, a significant proportion of Palestinian families frequently rely on retired older people financially, increasing pressure and the possibility of economic violence; of course, this association warrants further examination to ascertain the patterns implicit in these complex relationships. Our study limitations include , beginning with the global pandemic of COVID-19, which prevented the researchers and patients from accessing the primary health care centres. Nonetheless, we have a good response rate of 85 percent; participants' refusal to proceed with the interview was explained by a lack of time, tiredness, or simply a dislike of interacting with others. The nature of the participants' refusal was similar to that of the study participants. The social desirability bias could be expected in an interview-based questionnaire about sensitive objects because patients tend to answer positively to the questions, but we hypothesize that this may be minimal in our study because elderly people are fully aware of the consequences of their contribution, which may reflect in their quality of care. Finally, this is a cross-sectional study that measures the prevalence in a snapshot of time, and the prevalence may change over time. Conclusion Palestine is a developing country that lacks elderly-related services such as screening for the common diosredrs among eldely . Depression and anxiety are common and elderly patients in PHC centers should routinely be screened. Guidelines for screening should be adopted and clinicians trained to follow them. Interventions to prevent and manage depression should be developed. Campaings to educate the public about depression should be created. This should be emphasized at the national and regional levels where geriatric health care services are scarce. Such information is required by policymakers and external funding agencies in order to develop future agendas.. Referral systems for patients with moderate to severe depression and anxiety symptoms should be prioritized. Declarations Author Notes : Ethical Consideration and Consent to Participate All methods involving human participants in this study were conducted per ethical research standards. The study was conducted in conformity with the ethical norms of An-Najah National University (ANNU). The Ministry of Health approved authorization for the study to be conducted in PHC settings, and participants were approached and invited voluntarily to participate. Participants were assured of their confidentiality and anonymity This study was performed in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. It was approved by the Institutional Review Board (IRB) of An-Najah National University . Consent to participate: All subjects involved in the research were invited to participate voluntarily after the study's purpose as well as the risks and the benefits of participation were explained. Informed consent was obtained from all individual participants is included in the stud Consent for publication The authors consent to the publication of identifiable detail s in the Geraitric BMJ Journal,which may include any details within the article. Availability of data and materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Acknowledgments: We are grateful to the Palestinian Ministry of Health for assisting us in distributing and collecting questionnaires, and we are grateful to the Palestinian women who attend primary health care centers for responding to our questions. Conflict of interst: No potential conflict of interest was reported by the author (s). Author contribution : Beesan Maraqa: Designing the work, conducting data analyses and interpretations, drafting the work, and final approval of the published version. Zaher Nazzal: Analysis and interpretation of data, drafting of the work, final approval of the published version. Suha Hamshari: Designing the work, drafting the work, final approval of the published version, and agreement to be accountable for all aspects of the work, including ensuring that any questions about the work's accuracy or integrity are appropriately investigated and resolved. Barlant Alutt : Acquisition of data, drafting of the work, and final approval of the published version. Ekram Rishmawi : Acquisition of data, drafting of the work, and final approval of the published version. All authors contributed to the final manuscript's development and approval. Funding: No funding was received . References World Health Organization, “Ageing,” 2022. . World Health Organization, “Decade of Healthy Ageing,” 2020. World Health Organization, “Mental health of older adults,” 2017. . Y. Zenebe, B. Akele, M. W/Selassie, and M. Necho, “Prevalence and determinants of depression among old age: a systematic review and meta-analysis,” Ann. Gen. Psychiatry , vol. 20, no. 1, p. 55, 2021, doi: 10.1186/s12991-021-00375-x. C. Bryant, H. Jackson, and D. Ames, “The prevalence of anxiety in older adults: Methodological issues and a review of the literature,” J. Affect. Disord. , vol. 109, no. 3, pp. 233–250, 2008, doi: https://doi.org/10.1016/j.jad.2007.11.008. C. Andreescu and S. 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Tables Table 1: Sociodemographic characteristics of the studied sample (n=380) Variables Frequency (%) Age 60-64 years 147 38.7 65-70 years 118 31.1 >70 years 115 30.3 Gender Male 198 52.1 Female 182 47.9 Marital Status Married 291 76.6 Single 20 5.3 Widowed 69 18.2 Residency Urban 172 45.3 Rural 208 54.7 Educational Level Uneducated +primary school 157 41.3 Middle +high school 134 35.3 University 89 23.4 House setting Alone 40 10.5 Not alone 340 89.5 Professional status Employed 59 15.5 Retired 91 23.9 Not employed 230 60.5 Source of income No Income or social, or savings 55 14.5 From Family 148 38.9 Retirement salary or Private Job 177 46.6 Non-Communicable Disease (Yes) 298 87.4 Hypertension 205 53.9 Diabetes 161 57.6 IHD 102 26.8 Cancer 15 3.9 Table 2: Bivariate analysis of sociodemographic characteristics with depression Depression Variables Yes (n=156) No (n=224) P value* Age 60-64 years 64 (43.5%) 83 (56.5%) 65-70 years 64 (43.5%) 77 (65.3%) .243 >70 years 51 (44.3%) 64 (55.7%) Gender Male 74 (37.4%) 124 (62.8%) .128 Female 82 (45.1%) 100 (54.9%) Marital Status Married 112 (38.5%) 179 (61.5%) Single 44 (49.4%) 45 (50.6) .066 Residency Urban 46 (26.7%) 126 (73.3%) <.001 Rural 110 (52.9%) 98 (47.1%) Educational Level Uneducated +primary school 87 (55.4%) 70 (44.6%) Middle +high School 49 (36.6%) 85 (63.4%) <.001 University 20 (22.5%) 69 (77.5%) Living conditions Alone 22 (55.0%) 18 (45.0%) .058 Not alone 134 (39.4%) 206 (60.6%) Professional status Employed 16 (27.1%) 43 (72.9%) Retired 25 (27.5%) 66 (72.5%) <.001 Not employed 115 (50.0%) 115 (50.0%) Source of income No income /social /savings 115 (50.0%) 18 (32.7%) From Family 72 (48.6%) 76 (51.4%) <.001 Retirement salary or Private Job 77 (26.6%) 130 (73.4%) NCD † Yes 130 (43.6%) 168 (56.4%) No 2 6 (31.7%) 56 (68.3%) .052 *Chi-squared test, †,Non-Communicable Disease Table 3: Bivariate analysis of sociodemographic characteristics with anxiety Anxiety Variables Yes (n=149) No (n=231) P value Age 60-64 years 60(40.8%) 87(59.2%) 65-70 years 37(31.4%) 81 (68.6%) .084 >70 years 52(45.2%) 63(54.8) Gender Male 62(31.3%) 136(68.7%) .001 Female 87(47.8%) 95(52.2%) Marital Status Married 103(35.4%) 188 (64.4%) .006 Single 46(51.3%) 43 (48.3%) Residency Urban 50 (29.1%) 122 (70.9%) <.001 Rural 99 (47.6%) 109 (52.4%) Educational Level Uneducated +primary school 81 (51.6%) 76(48.4%) Middle +high School 44 (32.8%) 90 (67.2%) <.001 University 24 (27.0%) 65 (73.0%) Living conditions Alone 22 (55.0%) 18 (45.0%) .031 Not alone 127 (37.4%) 213 (62.6%) Professional status Employed 15 (25.4%) 44 (74.6%) Retired 25 (27.5%) 66 (72.5%) <.001 Not employed 109 (47.4%) 121 (52.6%) Source of income No income /social /savings 32 (58.2%) 23 (41.8%) From Family 68 (45.9%) 80 (54.1%) <.001 Retirement salary or Private Job 49 (27.7%) 128 (73.2%) NCD † Yes 129 (43.3%) 169 (56.7%) .002 No 20 (24.4%) 62 (75.6%) *Chi-squared test, †,Non-Communicable Disease Table 4. Multivariate model of factors independently associated with depression and anxiety. Depression Anxiety Variables P value Adjusted OR (95% CI) P value Adjusted OR (95% CI) Age (years) 60-64 years † 1 65-70 years .183 1.5 (.83-2.7) .055 .57(.33-1.1) >70 years .577 .84(.463-1.5) .657 .87 (.45-1.5) Sex Male† 1 1 Female .324 .75 (.43-1.3) .308 1.3(.77-2.9) Marital status Married † 1 Single .715 1.1 (.62-2.0) .411 1.3 (.72-2.2) Residence † Urban † 1 1 Rural <.001 2.6 (1.7-4.2) .007 1.9 (1.2-3.0) Educational level Uneducated or primary school .004 2.9 (1.4-6.1) .160 1.6 (.82-3.6) Middle or high School .210 1.5 (.77-3.1) .859 .94 (.48-1.9) University † 1 1 Professional status Employed † 1 1 Retired .350 1.5 (.65-3.4) .727 1.2(.51-2.6) Not employed .339 1.6 (.62-4.0) .411 1.5 (.59-3.6) Source of income No Income /social /savings .003 3.4 (1.5-7.6) .081 2.0 (0.9-4.4) From Family .244 1.5 (.76-2.9) .834 1.1 (.56-2.1) Retirement salary or Private Job † 1 1 NCD Yes .308 1.4(.75-2.5) .026 2.0 (1.1-3.5) No † 1 1 † Reference level , OR: odds ratio, CI: confidence interval, NCD: non-communicable diseases Additional Declarations No competing interests reported. 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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-2195431","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":148972978,"identity":"f7fbff68-6d77-4d28-a1b8-fda6efe9074b","order_by":0,"name":"Bessan Maraqa","email":"","orcid":"","institution":"Ministry of Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bessan","middleName":"","lastName":"Maraqa","suffix":""},{"id":148972979,"identity":"3ddaf421-dc43-4315-95e8-86ef668aa8c7","order_by":1,"name":"Zaher Nazzal","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zaher","middleName":"","lastName":"Nazzal","suffix":""},{"id":148972980,"identity":"3f95b485-4630-4f1d-8680-67fe95852ba0","order_by":2,"name":"barlant alutt","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"barlant","middleName":"","lastName":"alutt","suffix":""},{"id":148972981,"identity":"db8f6398-8f4d-48e0-b516-a8f046904659","order_by":3,"name":"ekram rishmawi","email":"","orcid":"","institution":"An-Najah National University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"ekram","middleName":"","lastName":"rishmawi","suffix":""},{"id":148972982,"identity":"f4b58011-24ca-470f-a9f8-fd846b62cb7f","order_by":4,"name":"suha hamshari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYFACHhBxgIGBmfkAiJMA5BkQq4UtgVQtDDxglYS1yDfwHvx0488defN2nm8PfsjY5TGwN2+TwKfF4ABfsnRu2zPDOYd5txv28CQXM/AcK8OvBege6dyGw4wzmHm3SfDwMCc2SOSY4dUi38Bj/Dvnz2H7Gcw8zyT/8NQnNsi/wa+F4QCPmXQO2+FEoBY2aR6ew0BbePBrMTjMY2ad23Y4eQYzm5m0DM/xxDaetGILvA5r7zG+DXSY7Qz+w88k3/ZUJ/azH954A6/DmJE5jD0MDGx4lWOCHySqHwWjYBSMghEBAMK3QzkdHbvEAAAAAElFTkSuQmCC","orcid":"","institution":"An-Najah National University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"suha","middleName":"","lastName":"hamshari","suffix":""}],"badges":[],"createdAt":"2022-10-23 10:44:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2195431/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2195431/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":35024154,"identity":"9770f6d9-ead1-427e-8ce5-10f313742759","added_by":"auto","created_at":"2023-03-30 07:14:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":454119,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2195431/v1/6313886e-23f0-4792-bf54-88f8f107b193.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence of depression and anxiety among elderly primary care patients in Palestine","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNowadays, the average individual can foresee living well into their sixties and beyond. People over 60 years of age are a growing proportion of the general population. In 2019, the global population of adults aged 60 and over topped one billion. The forecast estimates 1.4 billion people in 2030 and 2.1 billion in 2050.[1]\u0026nbsp;Healthy aging is critical for reaping the full benefits of increased longevity.[2]\u0026nbsp;While elderly individuals in the developed world have slightly better health than previous generations, good health later in life is not fairly distributed.\u003c/p\u003e\n\u003cp\u003eMental health is an important part of living well.care services are still below optimal in low to middle-income countries. According to World Health Organization 15% of adults 60 \u0026nbsp;and older suffer a mental disorder.[3]\u0026nbsp;A recent pooled analysis of depression prevalence among the elderly revealed an average predicted prevalence of 31.7% (95%CI 27.9, 35.6). In the subgroup analysis, the pooled prevalence was higher in developing countries, reaching almost 40.8%. Older women, single, divorced or widowed, education level (low or nonexistent), family\u0026apos;s history of significant life events (such as a family death), and her physical health (diabetes or heart disease) are all risk factors.[4]\u003c/p\u003e\n\u003cp\u003eAnxiety is also an issue in the elderly. Community samples revealed up to 15% suffered from anxiety, while clinical settings showed 28%. It was significantly higher in terms of anxiety symptoms, ranging between 15% and 52.3% in population samples and 15% to 56% in clinical samples.[5] Diagnosing anxiety symptoms may be more challenging in older adults, as anxiety symptoms may be misinterpreted for physical illness symptoms.[6]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealth care practitioners often underdiagnose mental health illnesses, and the stigma associated with these conditions inhibits people from getting help. NEED citation. Few studies evaluate common mental disorders among older ages in Arab countries. The stigma associated with the significant societal implications of mental disorders might be one barrier to diagnosis and treatment.[7] \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Palestine, clinicians do not have screening guidelines and rarely use screening instruments. NEED citation. However, numerous visits to primary health care centers (PHC) with physical symptoms are indicators of mental health problems that frequently goes untreated.[8]\u003c/p\u003e\n\u003cp\u003eIn Palestine, more than a third of the population is comprised of individuals aged sixty and over..[9] While those over 60 account for only 5% of the Palestinian population, they head one in every six households and account for 13% of the labour force. The poverty rate for individuals living in households headed by an older person are much higher than in other households, 32% versus 29%.[10] Additionally, Palestine has unique challenges with movement restrictions due to the Occupation, and a scarcity of mental health services.[11] The purpose of this study is to determine the prevalence of depression and anxiety among elderly adults presenting PHC in the Occupied West Bank and factors that influence those mental health diagnoses.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eDesign and Study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional study using an interview-administered questionnaire. Adults aged 60 years and older who attended the three main PHC centers in the West Bank of Palestine were asked to participation between February to July 2021. The sample size was 380, as calculated by Epi Info 6.0, at an 80% power level and a 95% confidence level.\u0026nbsp;[12]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Measures:\u003c/p\u003e\n\u003cp\u003eThe questionnaire consisted of 3 sections: 1) sociodemographic and medical history such as age, sex, residency, educational level, house setting, professional status, source of income and history of chronic medical conditions such as hypertension, diabetes mellitus, cancer, and ischemic heart disease based on previous medical evaluations and diagnosis. 2) A shorter form of the Geriatric Depression Scale to assess depression (GDS-15). This diagnostic measure is designed exclusively for identifying depression in older adults. The scale consists of 15 items that can be answered yes or no. The GDS score ranges from 0 to 15, with 0 indicating no depression, 5-8 indicating mild depression, 9-11 indicating moderate depression, and 12-15 indicating severe depression.[13]\u0026ndash;[15]\u0026nbsp;Depression was suggested by a cut-off value of six or higher.\u0026nbsp;[13], [14]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3) The Geriatric Anxiety Scale (GAS) assessed anxiety. This self-report screening and assessment tool is specifically designed for older adults. It consists of 25 scoreable items that assess experienced anxiety symptoms. A total anxiety score is computed by adding the self-reported ratings on items 1-25, with higher scores indicating greater anxiety levels. A total score of 0-11 indicates minimal anxiety symptoms, 12-21 indicates mild anxiety symptoms, 22-27 indicates moderate anxiety symptoms, and scores of 28 and higher exhibit severe anxiety symptoms.[16], [17]\u0026nbsp;To categorize anxiety into two groups, a cut-off score of 16 was chosen based on the literature. Those with a score greater than 16 were termed anxious, while those with a score less than or equal to 16 were classified as not anxious.[18]\u003c/p\u003e\n\u003cp\u003eArabic versions of both have a very high/excellent level of reliability.[14], [19]\u0026nbsp;In this study, Cronbach alpha for depression items is 0.83 and anxiety items is 0.92, which shows excellent reliability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis Plan\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe analysis was conducted using IBM SPSS Statistics for Windows, Version 20.0 (IBM Corp., Armonk, NY: IBM Corp). The demographic and clinical features of the subjects were described using descriptive statistics (means, standard deviations for continuous variables, and frequency distributions and proportions for categorical variables). Additionally, the chi-squared test and logistic regression were employed to determine any significant relationships between the groups. The level of significance was determined at p\u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods involving human participants in this study were conducted per ethical research standards. The study was conducted in conformity with the ethical norms of An-Najah National University (ANNU). The Ministry of Health approved authorization for the study to be conducted in PHC settings, and participants were approached and invited voluntarily to participate. Participants were assured of their confidentiality and anonymity.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 447 questionnaires distributed, 380 patients agreed to the interview, representing an 85% response rate. \u0026nbsp;Just over half (52.1%) were male, most (76.6%) were married, two thirds (69.9) were between 60 and 70 years of age. Sociodemographics are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of depression and anxiety\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the participants, 156 [41.1% (95% CI: 36.1%-46.2%)] were found to have depression, with mild depression accounting for 28.4%, moderate depression accounting for 13.4%, and severe depression accounting for 6.3%. Anxiety was reported among 149 participants [39.2%, (95% CI: 34.3%-44.3%)] with mild anxiety accounting for 28.4%, moderate anxiety accounting for 13.4%, and severe anxiety accounting for 6.3%. How many had both depression and anxiety?\u003c/p\u003e\n\u003cp\u003eWe conducted bivariate analysis and the Chi-squared test to investigate the factors associated with depression and anxiety Older people living in rural areas, with a lower educational level, and were unemployed, and had no source of income were more likely to have depression (Table 2).\u003c/p\u003e\n\u003cp\u003eIn contrast, single female elderly who lived in rural areas, and had a lower educational level showed significantly higher anxiety levels. Furthermore, older people who live alone, are unemployed, have no income, or have a non-communicable disease have substantially greater anxiety levels (Table 3).\u003c/p\u003e\n\u003cp\u003eAny data for patients with both depression and anxiety??\u003cbr\u003e\u0026nbsp;We conducted the multivariable analysis to explore variables independently related to depression and anxiety among the elderly. Older people living in rural areas were shown to be 2.6 times more likely to be depressed than those living in urban (p-value \u0026lt;0.001, aOR 2.6, 95%CI: 1.7-4.2), as did those with a lower educational level (p-value 0.004, aOR 2.9, 95%CI: 1.4-6.1) and those with no monthly income (p-value 0.003, aOR 3.4, 95%CI: 1.5-7.6). On the other hand, anxiety among older people was found to be independently associated with living in rural areas (p-value 0.007, aOR 1.9, 95%CI: 1.2-3.0) and among those with a non-communicable disease (p-value 0.026, aOR 2.0, 95%CI: 1.1-3.5) (Table 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first study examining the prevalence of depression and anxiety in adults over 60 years seeking care in primary care centers in Palestine. Consistent with other studies, physical illness is a common risk factor for mental illness, particularly in the elderly.\u0026nbsp;[20]\u0026nbsp;In this context, we need to emphasize the importance of screening for anxiety and depression in PHC settings, especially when NCDs are present. ,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our sample 41.1% suffer from depression, 39.2% from anxiety. These findings corroborate a meta-analysis that assessed the global prevalence of depression to be 31.7% and 40.7% in developing countries.[4]\u0026nbsp;Research conducted in nearby Egypt reported a prevalence of depression and anxiety of 37.5% and 14.2%, respectively.[21]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealth professionals should routinely assess for depression and anxiety among the elderly. Professional organizations in Palestine should adopt guidelines and policies to encourage assessing the elderly for the WHO guidelines . Policymakers and other key stakeholders should allocate resources to facilitate screening and treatment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUndiagnosed and untreated depression and anxiety can consume health care resources with unnecessary workups and testing for physical symptoms\u0026nbsp;[3]\u003c/p\u003e\n\u003cp\u003eestablish effective control measures and offer routine geriatric care. On the other hand, in a financially impoverished country such as Palestine, such mental illnesses can impose a significant financial and institutional load on primary health care facilities.\u0026nbsp;[22].\u003c/p\u003e\n\u003cp\u003eOur results for both anxiety and depression were surprising because the female gender and single status, which are considered risk factors[23], are not significant in our sample. Age, on the other hand, was not significantly associated with either anxiety or depression.This is likely due to local culture and traditions that value the elderly and encourage people, particularly women and unmarried women, to assist them financially and socially.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRural-urban differences in mental disorders have piqued the interest of researchers and policymakers involved in mental health care. Due to community ties and social isolation, city inhabitants may be more prone to depression than rural residents.[24]\u0026nbsp;Inequalities of health care and access barriers could explain the apparent correlation between both anxiry and depression an rural and urban residence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the relationship between depression and education, low education was significantly associated with depression in developing and developed countries. In contrast, income was not strongly related to depression in low- to middle-income countries, contradicting our findings.[25]\u0026nbsp;This could indicate that educated individuals better understand the issue and are more likely to seek medical treatment early. While in terms of income, as previously stated, a significant proportion of Palestinian families frequently rely on retired older people financially, increasing pressure and the possibility of economic violence; of course, this association warrants further examination to ascertain the patterns implicit in these complex relationships.\u003c/p\u003e\n\u003cp\u003eOur study limitations include , beginning with the global pandemic of COVID-19, which prevented the researchers and patients from accessing the primary health care centres. Nonetheless, we have a good response rate of 85 percent; participants\u0026apos; refusal to proceed with the interview was explained by a lack of time, tiredness, or simply a dislike of interacting with others. The nature of the participants\u0026apos; refusal was similar to that of the study participants. The social desirability bias could be expected in an interview-based questionnaire about sensitive objects because patients tend to answer positively to the questions, but we hypothesize that this may be minimal in our study because elderly people are fully aware of the consequences of their contribution, which may reflect in their quality of care. Finally, this is a cross-sectional study that measures the prevalence in a snapshot of time, and the prevalence may change over time.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePalestine is a developing country that lacks elderly-related services such as screening for the common diosredrs among eldely . Depression and anxiety are common and elderly patients in PHC centers should routinely be screened. Guidelines for screening should be adopted and clinicians trained to follow them. Interventions to prevent and manage depression should be developed. Campaings to educate the public about depression should be created. This should be emphasized at the national and regional levels where geriatric health care services are scarce. Such information is required by policymakers and external funding agencies in order to develop future agendas.. Referral systems for patients with moderate to severe depression and anxiety symptoms should be prioritized.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Notes :\u003c/strong\u003e\u003c/p\u003e\n\u003col start=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eEthical Consideration and Consent to Participate\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAll methods involving human participants in this study were conducted per ethical research standards. The study was conducted in conformity with the ethical norms of An-Najah National University (ANNU). The Ministry of Health approved authorization for the study to be conducted in PHC settings, and participants were approached and invited voluntarily to participate. Participants were assured of their confidentiality and anonymity\u003c/p\u003e\n\u003cp\u003eThis study was performed in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. It was approved by the Institutional Review Board (IRB) of An-Najah National University .\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAll subjects involved in the research were invited to participate voluntarily after the study\u0026apos;s purpose as well as the risks and the benefits of participation were explained. Informed consent was obtained from all individual participants is included in the stud\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eThe authors consent to the publication of identifiable detail\u003c/strong\u003e\u003cstrong\u003es in the Geraitric BMJ Journal,which may include any details within the article.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003col start=\"4\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u0026nbsp;Availability of data and materials\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWe are grateful to the Palestinian Ministry of Health for assisting us in distributing and collecting questionnaires, and we are grateful to the Palestinian women who attend primary health care centers for responding to our questions.\u003c/p\u003e\n\u003col start=\"6\"\u003e\n \u003cli\u003e\u003cstrong\u003eConflict of interst:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the author (s).\u003c/p\u003e\n\u003col start=\"7\"\u003e\n \u003cli\u003e\u003cstrong\u003eAuthor contribution :\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eBeesan Maraqa: Designing the work, conducting data analyses and interpretations, drafting the work, and final approval of the published version.\u003c/p\u003e\n\u003cp\u003eZaher Nazzal: Analysis and interpretation of data, drafting of the work, final approval of the published version.\u003c/p\u003e\n\u003cp\u003eSuha Hamshari: Designing the work, drafting the work, final approval of the published version, and agreement to be accountable for all aspects of the work, including ensuring that any questions about the work\u0026apos;s accuracy or integrity are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003eBarlant Alutt : \u0026nbsp; Acquisition of data, drafting of the work, and final approval of the published version.\u003c/p\u003e\n\u003cp\u003eEkram Rishmawi\u003cstrong\u003e\u0026nbsp;:\u0026nbsp;\u003c/strong\u003eAcquisition of data, drafting of the work, and final approval of the published version. \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the final manuscript\u0026apos;s development and approval.\u003c/p\u003e\n\u003col start=\"8\"\u003e\n \u003cli\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eNo funding was received .\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization, \u0026ldquo;Ageing,\u0026rdquo; 2022. .\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, \u0026ldquo;Decade of Healthy Ageing,\u0026rdquo; 2020.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, \u0026ldquo;Mental health of older adults,\u0026rdquo; 2017. .\u003c/li\u003e\n\u003cli\u003eY. Zenebe, B. Akele, M. W/Selassie, and M. Necho, \u0026ldquo;Prevalence and determinants of depression among old age: a systematic review and meta-analysis,\u0026rdquo; \u003cem\u003eAnn. Gen. Psychiatry\u003c/em\u003e, vol. 20, no. 1, p. 55, 2021, doi: 10.1186/s12991-021-00375-x.\u003c/li\u003e\n\u003cli\u003eC. Bryant, H. Jackson, and D. Ames, \u0026ldquo;The prevalence of anxiety in older adults: Methodological issues and a review of the literature,\u0026rdquo; \u003cem\u003eJ. Affect. Disord.\u003c/em\u003e, vol. 109, no. 3, pp. 233\u0026ndash;250, 2008, doi: https://doi.org/10.1016/j.jad.2007.11.008.\u003c/li\u003e\n\u003cli\u003eC. Andreescu and S. Lee, \u0026ldquo;Anxiety disorders in the elderly,\u0026rdquo; in \u003cem\u003eAdvances in Experimental Medicine and Biology\u003c/em\u003e, vol. 1191, Springer, 2020, pp. 561\u0026ndash;576.\u003c/li\u003e\n\u003cli\u003eS. M. Khaled, \u0026ldquo;Prevalence and potential determinants of subthreshold and major depression in the general population of Qatar,\u0026rdquo; \u003cem\u003eJ. Affect. Disord.\u003c/em\u003e, vol. 252, pp. 382\u0026ndash;393, Jun. 2019, doi: 10.1016/j.jad.2019.04.056.\u003c/li\u003e\n\u003cli\u003eZ. Nazzal, B. Maraqa, M. Abu Zant, L. Qaddoumi, and R. Abdallah, \u0026ldquo;Somatic symptom disorders and utilization of health services among Palestinian primary health care attendees: a cross-sectional study,\u0026rdquo; \u003cem\u003eBMC Health Serv. Res.\u003c/em\u003e, vol. 21, no. 1, pp. 1\u0026ndash;9, 2021, doi: 10.1186/s12913-021-06671-2.\u003c/li\u003e\n\u003cli\u003ePalestinian Ministry of Health, \u0026ldquo;Health Annual Report Palestine 2019,\u0026rdquo; Nablus, 2020.\u003c/li\u003e\n\u003cli\u003ePalestinian Central Bureau of Statistics, \u0026ldquo;The international day of older persons,\u0026rdquo; 2021.\u003c/li\u003e\n\u003cli\u003eM. Marie, B. Hannigan, and A. Jones, \u0026ldquo;Challenges for nurses who work in community mental health centres in the West Bank, Palestine.,\u0026rdquo; \u003cem\u003eInt. J. Ment. Health Syst.\u003c/em\u003e, vol. 11, p. 3, 2017, doi: 10.1186/s13033-016-0112-4.\u003c/li\u003e\n\u003cli\u003eA. G. Dean \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Epi Info : a word-processing, database, and statistics program for public health on IBM-compatible microcomputers.\u0026rdquo; Atlanta, Georgia : Centers for Disease Control and Prevention, p. Produced by the Division of Surveillance and Epide, 1995.\u003c/li\u003e\n\u003cli\u003eC. Shin \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Usefulness of the 15-item geriatric depression scale (GDS-15) for classifying minor and major depressive disorders among community-dwelling elders.,\u0026rdquo; \u003cem\u003eJ. Affect. Disord.\u003c/em\u003e, vol. 259, pp. 370\u0026ndash;375, Dec. 2019, doi: 10.1016/j.jad.2019.08.053.\u003c/li\u003e\n\u003cli\u003eM. Chaaya \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Validation of the Arabic version of the short Geriatric Depression Scale (GDS-15).,\u0026rdquo; \u003cem\u003eInt. psychogeriatrics\u003c/em\u003e, vol. 20, no. 3, pp. 571\u0026ndash;581, Jun. 2008, doi: 10.1017/S1041610208006741.\u003c/li\u003e\n\u003cli\u003eS. A. Greenberg, \u0026ldquo;The geriatric depression scale: Short form,\u0026rdquo; \u003cem\u003eAmerican Journal of Nursing\u003c/em\u003e, vol. 107, no. 10. Am J Nurs, pp. 60\u0026ndash;69, Oct. 2007, doi: 10.1097/01.NAJ.0000292204.52313.f3.\u003c/li\u003e\n\u003cli\u003eD. L. Segal, A. June, M. Payne, F. L. Coolidge, and B. Yochim, \u0026ldquo;Development and initial validation of a self-report assessment tool for anxiety among older adults: The Geriatric Anxiety Scale,\u0026rdquo; \u003cem\u003eJ. Anxiety Disord.\u003c/em\u003e, vol. 24, no. 7, pp. 709\u0026ndash;714, 2010, doi: https://doi.org/10.1016/j.janxdis.2010.05.002.\u003c/li\u003e\n\u003cli\u003eD. D. Callow \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;The Mental Health Benefits of Physical Activity in Older Adults Survive the COVID-19 Pandemic.,\u0026rdquo; \u003cem\u003eAm. J. Geriatr. psychiatry Off. J. Am. Assoc. Geriatr. Psychiatry\u003c/em\u003e, vol. 28, no. 10, pp. 1046\u0026ndash;1057, Oct. 2020, doi: 10.1016/j.jagp.2020.06.024.\u003c/li\u003e\n\u003cli\u003eJ. Gottschling, D. L. Segal, C. H\u0026auml;usele, F. M. Spinath, and G. Stoll, \u0026ldquo;Assessment of Anxiety in Older Adults: Translation and Psychometric Evaluation of the German Version of the Geriatric Anxiety Scale (GAS),\u0026rdquo; \u003cem\u003eJ. Psychopathol. Behav. Assess. 2015 381\u003c/em\u003e, vol. 38, no. 1, pp. 136\u0026ndash;148, Aug. 2015, doi: 10.1007/S10862-015-9504-Z.\u003c/li\u003e\n\u003cli\u003eS. Hallit, R. Hallit, D. Hachem, M. C. Daher Nasra, N. Kheir, and P. Salameh, \u0026ldquo;Validation of the Arabic version of the Geriatric Anxiety Scale among Lebanese population of older adults,\u0026rdquo; \u003cem\u003eJ. Psychopathol.\u003c/em\u003e, vol. 23, no. 1, pp. 26\u0026ndash;34, 2017.\u003c/li\u003e\n\u003cli\u003eC. Menta, L. W. Bisol, E. L. Nogueira, P. Engroff, and A. C. Neto, \u0026ldquo;Prevalence and correlates of generalized anxiety disorder among elderly people in primary health care,\u0026rdquo; \u003cem\u003eJ. Bras. Psiquiatr.\u003c/em\u003e, vol. 69, no. 2, pp. 126\u0026ndash;130, 2020, doi: 10.1590/0047-2085000000267.\u003c/li\u003e\n\u003cli\u003eD. Ahmed, I. H. El Shair, E. Taher, and F. Zyada, \u0026ldquo;Prevalence and predictors of depression and anxiety among the elderly population living in geriatric homes in Cairo, Egypt,\u0026rdquo; \u003cem\u003eJ. Egypt. Public Health Assoc.\u003c/em\u003e, vol. 89, no. 3, pp. 127\u0026ndash;135, Dec. 2014, doi: 10.1097/01.EPX.0000455729.66131.49.\u003c/li\u003e\n\u003cli\u003eJ.-O. Bock \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Impact of depression on health care utilization and costs among multimorbid patients--from the MultiCare Cohort Study,\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 9, no. 3, pp. e91973\u0026ndash;e91973, Mar. 2014, doi: 10.1371/journal.pone.0091973.\u003c/li\u003e\n\u003cli\u003eJ. S. Girgus, K. Yang, and C. V Ferri, \u0026ldquo;The Gender Difference in Depression: Are Elderly Women at Greater Risk for Depression Than Elderly Men?,\u0026rdquo; \u003cem\u003eGeriatr. (Basel, Switzerland)\u003c/em\u003e, vol. 2, no. 4, p. 35, Nov. 2017, doi: 10.3390/geriatrics2040035.\u003c/li\u003e\n\u003cli\u003eJ. L. Wang, \u0026ldquo;Rural-urban differences in the prevalence of major depression and associated impairment,\u0026rdquo; \u003cem\u003eSoc. Psychiatry Psychiatr. Epidemiol.\u003c/em\u003e, vol. 39, no. 1, pp. 19\u0026ndash;25, Jan. 2004, doi: 10.1007/S00127-004-0698-8.\u003c/li\u003e\n\u003cli\u003eE. Bromet \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Cross-national epidemiology of DSM-IV major depressive episode,\u0026rdquo; \u003cem\u003eBMC Med.\u003c/em\u003e, vol. 9, no. 1, p. 90, 2011, doi: 10.1186/1741-7015-9-90.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSociodemographic characteristics of the studied sample (n=380)\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e60-64 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e38.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e65-70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e31.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u0026gt;70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e52.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e47.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e76.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e45.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e54.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eUneducated +primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e41.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eMiddle +high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eUniversity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHouse setting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eAlone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eNot alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e89.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e15.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e23.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e60.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eNo Income \u0026nbsp;or social, or savings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eFrom Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e38.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eRetirement salary or Private Job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e46.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Communicable Disease\u0026nbsp;\u003c/strong\u003e\u003cem\u003e(Yes)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e87.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eHypertension\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e53.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e57.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eIHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"52.68817204301075%\"\u003e\n \u003cp\u003eCancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.56989247311828%\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\u0026nbsp;\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eBivariate analysis of sociodemographic characteristics with depression\u0026nbsp;\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"570\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.719298245614034%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"43.333333333333336%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.94736842105263%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u0026nbsp;\u003c/strong\u003e(n=156)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo \u0026nbsp;\u003c/strong\u003e(n=224)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e60-64 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e64 (43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e83 (56.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e65-70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e64 (43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e77 (65.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e.243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u0026gt;70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e51 (44.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e64 (55.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e74 (37.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e124 (62.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e.128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e82 (45.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e100 (54.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e112 (38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e179 (61.5%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e44 (49.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e45 (50.6)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e46 (26.7%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e126 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e110 (52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e98 (47.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eUneducated +primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e87 (55.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e70 (44.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eMiddle +high School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e49 (36.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e85 (63.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eUniversity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e20 (22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e69 (77.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiving conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eAlone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e22 (55.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e18 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eNot alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e134 (39.4%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e206 (60.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e16 (27.1%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e43 (72.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e25 (27.5%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e66 (72.5%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;115 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e115 (50.0%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eNo income /social /savings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e115 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e18 (32.7%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eFrom Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e72 (48.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e76 (51.4%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eRetirement salary or Private Job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e77 (26.6%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e130 (73.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNCD\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e130 (43.6%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e168 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"37.65323992994746%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.71628721541156%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e6 (31.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.71628721541156%\"\u003e\n \u003cp\u003e56 (68.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.914185639229423%\"\u003e\n \u003cp\u003e.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e*Chi-squared test, \u0026dagger;,Non-Communicable Disease\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eBivariate analysis of sociodemographic characteristics with anxiety\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"525\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"41.333333333333336%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u0026nbsp;\u003c/strong\u003e(n=149)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo \u0026nbsp;\u003c/strong\u003e(n=231)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e60-64 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e60(40.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e87(59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e65-70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e37(31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;81 (68.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u0026gt;70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e52(45.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;63(54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e62(31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e136(68.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e87(47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e95(52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e103(35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e188 (64.4%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e46(51.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e43 (48.3%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e50 (29.1%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e122 (70.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e99 (47.6%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e109 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eUneducated +primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e81 (51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e76(48.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eMiddle +high School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e44 (32.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e90 (67.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eUniversity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e24 (27.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e65 (73.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiving conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eAlone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e22 (55.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e18 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eNot alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e127 (37.4%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e213 (62.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e15 (25.4%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e44 (74.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e25 (27.5%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e66 (72.5%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e109 (47.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e121 (52.6%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eNo income /social /savings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e32 (58.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e23 (41.8%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eFrom Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e68 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e80 (54.1%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eRetirement salary or Private Job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e49 (27.7%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e128 (73.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNCD\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e129 (43.3%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e169 (56.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"42.285714285714285%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.61904761904762%\"\u003e\n \u003cp\u003e20 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.714285714285715%\"\u003e\n \u003cp\u003e62 (75.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.38095238095238%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e*Chi-squared test, \u0026dagger;,Non-Communicable Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eMultivariate model of factors independently associated with depression and anxiety.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"720\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.790568654646325%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"34.11927877947296%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDepression\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"35.09015256588072%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnxiety\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAdjusted OR (95% CI)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.5%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAdjusted OR (95% CI)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e60-64 years\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e65-70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.5 (.83-2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e.57(.33-1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u0026gt;70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e.84(.463-1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e.87 (.45-1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eMale\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e.75 (.43-1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1.3(.77-2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eMarried\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.1 (.62-2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.5%\"\u003e\n \u003cp\u003e1.3 (.72-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eUrban\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eRural\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e2.6 (1.7-4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1.9 (1.2-3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eUneducated or primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e2.9 (1.4-6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1.6 (.82-3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eMiddle or high School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.5 (.77-3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e.94 (.48-1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eUniversity\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eEmployed\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.5 (.65-3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1.2(.51-2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.6 (.62-4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1.5 (.59-3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eNo Income /social /savings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e3.4 (1.5-7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e2.0 (0.9-4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eFrom Family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.5 (.76-2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1.1 (.56-2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eRetirement salary or Private Job\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNCD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1.4(.75-2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e2.0 (1.1-3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.833333333333332%\"\u003e\n \u003cp\u003eNo\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"21.666666666666668%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cem\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eReference level\u003csup\u003e,\u0026nbsp;\u003c/sup\u003e\u003cstrong\u003eOR:\u0026nbsp;\u003c/strong\u003eodds ratio, \u003cstrong\u003eCI:\u0026nbsp;\u003c/strong\u003econfidence interval, \u003cstrong\u003eNCD:\u0026nbsp;\u003c/strong\u003enon-communicable diseases\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Depression, Anxiety, Elderly, Primary health","lastPublishedDoi":"10.21203/rs.3.rs-2195431/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2195431/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDepression and anxiety are common mental health disorders among the elderly worldwide. In this study, we estimated the prevalence of depression and anxiety and related risk factor among elderly attending PHC centers in Palestine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA cross-sectional study was conducted on a sample size of 380 participants aged ≥60 attending PHC centers in West Bank, using an interviewer-administered questionnaire. We used the Geriatric Depression Scale-15 and the Geriatric Anxiety Scale to screen for depression and anxiety, respectively.We analyzed data using descriptive and analytical statistics and employed logistic regression model to identify predictors of depression and anxiety.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The prevalence of depression and anxiety was 41.1% and 39.2%, respectively. Eldely people living in rural areas (aOR 2.6, 95%CI: 1.7-4.2), uneducated (aOR 2.9, 95%CI: 1.4-6.1), and without monthly income (aOR 3.4, 95%CI: 1.5-7.6) were more likely to have depression. On the other hand, anxiety is independently assosciated with living in rural areas (aOR 1.9, 95%CI: 1.2-3.0) and having non-communicable diseases (aOR 2.0, 95%CI: 1.1-3.5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Depression and anxiety are common in Palestine, a developing country with a lack of elderly-related services. This should be emphasized at the national and regional levels where geriatric health care services are scarce. Such information is required by policymakers and external funding agencies in order to develop future agendas\u003c/p\u003e","manuscriptTitle":"Prevalence of depression and anxiety among elderly primary care patients in Palestine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-07 23:29:32","doi":"10.21203/rs.3.rs-2195431/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbe26566-fa0a-428b-a4a2-e36d5b4f193f","owner":[],"postedDate":"November 7th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-30T07:14:38+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-07 23:29:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2195431","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2195431","identity":"rs-2195431","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}