profile of mental disorders among the elderly united arab emirates population: sociodemographic...

INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY

Int J Geriatr Psychiatry 2004; 19: 344–351.

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/gps.1101

Profile of mental disorders among the elderly UnitedArab Emirates population: sociodemographic correlates

Rafia Ghubash1,2, Omer El-Rufaie1*, Taoufik Zoubeidi3, Qasim M. Al-Shboul2 and Sufyan M. Sabri1

1Department of Psychiatry, Faculty of Medicine and Health Sciences, UAE University, Al-Ain, UAE2Department of Family & Community Medicine, College of Medicine and Medical Sciences, Arabian Gulf University,Manama, Kingdom of Bahrain3Department of Statistics, Faculty of Business and Economics, UAE University, UAE

SUMMARY

Objectives To investigate the prevalence, nature and sociodemographic correlates of mental disorders among the elderlyUnited Arab Emirates (UAE) population.Study subjects and sample UAE nationals aged 60 years or more, were recruited from within a random sample of house-holds representing the UAE national population, irrespective of the age of individuals in each household.Research Instruments (i) Geriatric Mental State Interview (GMS-A3): an Arabic version, using the AGECAT for ana-lysis; (ii) A short questionnaire for relevant sociodemographic data.Procedure Purposely trained, Arabic speaking interviewers visited the targeted sample households to interview study sub-jects at their homes.Results The total number of screened subjects was 610: 166 (27.2%) in Al-Ain; 286 (46.9%) in Dubai and 158 (25.9%) inRas Al-Khaimah. There were 347 (56.9%) male subjects and 263 (43.1%) female subjects. The mean age of the interviewedsubjects was 68.6 (SD 8.3). The commonest diagnostic entities at the AGECAT syndrome case level were depression(20.2%), anxiety (5.6%), hypochondriasis (4.4%) and organic, mostly cognitive impairment with or without dementia(3.6%). Organic syndrome caseness, as an independent entity, showed significant correlation only to older age, while therest of the mental disorders showed significant correlation with female gender, insufficient income and being single, sepa-rated, divorced or widowed.Conclusion The GMS-AGECAT package proved to be a useful tool for psychiatric assessment among the elderly in thisArabian culture. The prevalence rates of mental disorders among the elderly UAE population were, more or less, within thesame range reported by other comparable worldwide studies. Copyright # 2004 John Wiley & Sons, Ltd.

key words— Geriatric Mental State Interview (GMS-A3); AGECAT; United Arab Emirates (UAE); mental disorders;old age

INTRODUCTION

Elderly people are at a particular risk of sufferingfrom dementia, depression and other psychiatric dis-orders. Estimates of the prevalence of mental disor-

ders among the elderly show considerable variationsamong the studied samples (Kay and Bergman,1980; Henderson and Kay, 1984; Copeland et al.,1987a). It is probable that the methodological proce-dures adopted in the various studies account for muchof the variations.

Psychiatric research in the Gulf Region, in particu-lar, and in the Arab world in general, is relativelyscanty in comparison with the Western world andother developed countries. Studies of psychiatricmorbidity among the elderly population in thisgeographic region are even more scanty. Among otherobjectives, this study is intended to establish

Received 7 October 2003Copyright # 2004 John Wiley & Sons, Ltd. Accepted 8 January 2004

*Correspondence to: Professor O. El-Rufaie, Department ofPsychiatry and Behavioural Sciences, Faculty of Medicine andHealth Sciences UAE University, P.O. Box 17666, Al-Ain, UnitedArab Emirates. Tel: 00971-3-7039442. Fax: 00971-3-7672995.E-mail: [email protected]

Contract/grant sponsor: Sheikh Hamdan Bin Rashid Al MaktoumAward; contract/grant number: MRG-17/1999–2000.

preliminary base-line data on the mental health of theelderly UAE population. Over the last three to fourdecades the UAE society has been evolving over aperiod of rapid urbanisation, socio-economicadvancement, modernisation and change in the qual-ity of life. Many western qualities and ways of lifehave been introduced. It is inevitable that the integrityof both the nucleus and extended families will beaffected by such quick and dramatic change. The shiftin the family set up, and the society as a whole, fromconservative Islamic society, governed to a greatextent by the Bedouin values and culture to modernsophisticated life with Western rhythm and style, willinevitably reflect in various ways on the elderly peo-ple’s welfare, health and prosperity.

The specific aim of this study was to investigate theprevalence, nature and pertinent sociodemographiccorrelates of mental disorders among the elderlyUAE population. In this study the broad spectrum ofmental disorders in the elderly were investigated.Cognitive impairment and depression among theelderly have been extensively studied but other psy-chiatric disorders, including anxiety states, were notadequately investigated. The fact that the elderly areamongst the heaviest consumers of anxiolytics(Skegg et al., 1977; Catalan et al., 1988; Lindesayet al., 1989), is suggestive of the significance of anxi-ety and other neurotic disorders among this sector ofthe population (Lindesay et al., 1989). This is why weopted to investigate a wider range of mental disordersamong the elderly, rather than restricting the study todepression and cognitive impairment.

METHOD

Study sample

Study subjects were UAE nationals aged 60 years ormore. Due to the high illiteracy rate among the elderlyin this area, many of them do not know their exact

age. The study interviewers were trained to cross-validate the age stated by subjects with particularimportant events in their lifetime, and by informationfrom close reliable relatives.

The study sample was provided by the CentralDepartment of Statistics, Ministry of Planning, AbuDhabi. It consists of a random sample of 2000 house-holds representing UAE local population irrespectiveof the age of the individuals in each household. Thesame sample was also used for the purpose of anotherchild psychiatry study scheduled to be carried outsimultaneously with this study. The sampling framewhich was based on the UAE 1995 population censuswas also updated in 1998 to take into account the for-mation of new citizen households. Both the compila-tion of the sample frame and the drawing of the mastersample were supervised by two sampling experts fromthe United Nations Statistical Office. The master sam-ple was designed as a two-stage, stratified, clustersample of approximately 4000 citizen households in210 primary sampling units (PSUs). The PSUs consistof census enumeration areas in urban sectors and vil-lages in rural sectors. The PSUs were stratified into sixsize categories, according to the number of citizenhouseholds per PSU. A cluster of PSUs was thenselected from each stratum. The sampling schemegave equal probability of selection to each household.For the purpose of this study 843 households wereselected for screening. These households representthe population of two out of the seven Emirates, i.e.Dubai and Ras-Al-Khaimah, in addition to the popula-tion of Al-Ain, which constitutes the Eastern region ofa third Emirate, i.e. Abu Dhabi. The sample included843 households which were selected by randomlychoosing approximately half the households withinPSUs of the master sample that were located in thethree Emirates. Institutions were not included in thissampling procedure. Further details regarding thestudy sample are presented in Table 1.

Table 1. Sample sizes and response rates at various levels

Al-Ain Dubai Ras-Al-Khaimah Total

Households in the original sample frame 192 418 233 843Households without potential subjects (60 yrs or more) 45 121 75 241Total number of households which accepted to take part and 132 257 158 547subjects were screenedHouseholds, with potential subjects, which apologized 15 (10.2%) 40 (13.5%) 4 (2.5%) 59 (9.7%)from participationNumber of subjects interviewed* 166 (27.2%) 286 (46.9%) 158 (25.9%) 610 (100%)Subjects apologized from within agreeable households 4 (2.4%) 12 (4.0%) 1 (0.6%) 17 (2.7%)

*In some households more than one subject were interviewed.

mental disorders among elderly uae population 345

Copyright # 2004 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2004; 19: 344–351.

Case definition and research instruments

A short preliminary questionnaire. For recordingbasic socio-demographic data not included in theGMS-A3, schedule.

Geriatric Mental State Interview (GMS-A3). TheGeriatric Mental State Interview (GMS), a standar-dised, semi-structured interview for examining andrecording the mental state in elderly subjects. The firstversion was developed in 1976 (Copeland et al.,1976). Later, shortened versions were developed(GMS-6, GMS-A1, GMS-A3). The reliability andvalidity of the GMS have been established in in-patient, out-patient and community samples. Studiesestablished consistently high level of agreementbetween psychiatrists and non-psychiatrist raters.The schedule was translated and validated in over17 languages.

For the purpose of this study the GMS-A3,designed mainly for community studies, was used.It is the most recent version for the full range of men-tal illnesses (183 items). It seeks to establish symp-toms experienced by the subjects in the four weeksbefore the interview. Diagnoses were made by meansof a computer-assisted system, the Automated Geria-tric Examination for Computer Assisted Taxonomy(AGECAT). The AGECAT was also developed byCopeland et al. (1986) as a computerised systemwhich could be applied to data derived from theGMS by grouping the symptoms to form a patternrecognised by a psychiatrist as illness, usually identi-fied as syndrome case (Copeland et al., 1986;Copeland et al., 1987b). The AGECAT diagnosticsystem is divided into a number of logical stages. Itbrings together items from the GMS and other sche-dules into symptom components, which are then con-densed to form eight diagnostic clusters. Each clusterconsists of groups representing symptoms importantfor diagnosis. Scores on each group determine thelevel of diagnostic confidence for each subject oneach diagnostic cluster. The diagnostic clustersinclude organic, schizophrenic, manic, depressive(psychotic and neurotic), hypochondrical, obses-sional, phobic and anxious. In the second stage thelevels are compared across clusters so as to determinewhether or not the symptoms rank as a syndromecase. All clusters with diagnostic confidence level of3, 4 and 5 represent syndrome case levels, while 1 and2 sub-case levels. When a subject reaches the caselevel in several syndromes, then the AGECAT willselect one of these as the overall diagnosis, which isreferred to as ‘diagnostic syndrome’. For the purposeof this study we report cases as identified by the

AGECAT at the syndrome case level. This mayresult in over-diagnosis of cases which may notlead to psychiatric intervention if judged by a psy-chiatrist. However, there is evidence of agreementbetween psychiatrists and AGECAT diagnoses forboth institutionally based and community basedsubjects (Copeland et al., 1986; Copeland et al.,1987b).

Translation and training of interviewers

One Arabic speaking doctor and seven arabic speak-ing nurses, were recruited as interviewers for thisstudy. All of them had previous experience with com-munity psychiatric research.

The Egyptian translation of the GMS-A3 into Ara-bic was used. The bilingual psychiatrist who led thegroup of translators, and one of his colleagues wereinvited to train our interviewers on the methods ofadministration. During the training videotaped andlive interviews, simulated and real patients, wereused. The training emphasised conveying the exactoriginal meaning of each item and the standardisationof administration.

Procedure

In each of Al-Ain, Dubai and Ras-Al-Khaimah, thesimultaneous child psychiatry study team, using thesame sampling frame, visited households accordingto the sample frame map. An additional assignmentfor the team was to report, for the purpose of thisstudy, about presence of subjects 60 years or overwithin each household visited. Households withpotential study subjects (60 years or over) were vis-ited by a representative of this study to deliver a letterwhich explained the nature of the study and requestedconsent to participate.

A team of two interviewers visited each household,usually late in the afternoon and normally after atelephone call. After summarising the nature of thestudy and ensuring consent both the sociodemo-graphic questionnaires and the Arabic version of theGMS-A3 were administered.

Statistical analysis

Data was entered in the AGECAT computerized diag-nostic system. The system analyzed the data into anumber of logical stages: first symptoms componentsthen symptom clusters. The outcome of the lattertogether with the socio-economic variables werecoded, re-entered and analyzed using the Statistical

346 r. ghubash ET AL.


Package for Social Sciences (SPSS). The inter-raterreliability was assessed using 40 subjects. Each pairof our four pairs of interviewers assessed ten subjects.Each interviewer recorded his own findings indepen-dently. Calculation of the inter-rater reliability wasbased on the chance-corrected agreement coefficientAC1 (Gwet, 2001), which avoids the well-knownweaknesses of the Kappa coefficient (Cohen, 1968).The values of AC1 range between 0 and 1, where 1represent a perfect agreement while a 0 representsno agreements beyond those made by chance. Thechi-squared test was used to determine the socio-demographic variables that were significantly corre-lated to mental disorder syndrome cases. Simplelogistic regression analysis was used to assess theindividual effect of the variables on syndrome case-ness. The level p< 0.05 was considered to be thecut-off value for significance.

RESULTS

Statistical analysis revealed high levels of agree-ment among the interviewers in all the studied syn-drome cases. The mean and range of AC1 over thefour pairs of interviewers were: 0.86 (0.77–1) fororganic syndrome caseness, 0.92 (0.9–1) for schizo-phrenic syndrome caseness, 1 (1–1) for manic syn-drome caseness, 0.89 (0.77–1) for depressivesyndrome caseness, 0.97 (0.89–1) for hypochondria-sis syndrome caseness, 0.94 (0.88–1) for phobic syn-drome caseness, and 0.83 (0.66–1) for anxietysyndrome caseness.

The sample size in the three research cites and theresponse rate at the levels of the households and indi-vidual subjects are presented in Table 1. A range ofrelevant sociodemographic data (except for the occu-pational status) is presented in Table 2. None of thefemales interviewed had a regular occupation. Outof 347 men, 104 (30%) were working at the time ofinterview. Among those, 55 (53%) were unskilledlabourers, ten (10%) were in business or trade andthe rest were distributed in small proportion in otherjobs, including skilled labour (4.8%), army and police(3.8%), clerical (3.8%), professionals (2.9%), tea-chers (1%) and fishermen (1%). The diagnostic enti-ties as identified by AGECAT, at the syndrome caselevel are presented in Table 3. Comorbidity of hypo-chondriasis with anxiety, depression and comorbidanxiety and depression was investigated further more.The results are outlined in Table 4. An additionalfurther analysis was also performed for the categoryof organic syndrome caseness, by estimating the pre-valence among the sample population aged 65 or

more, which turned out to be 5.1%, in comparisonto 3.6% for those aged 60 or more (Table 3).

Simple logistic regressions between each of fivepertinent variables and caseness in each of the eightcategories of mental disorders show that gender, mar-ital status, and income sufficiency were significantlycorrelated with mental disorder. A stepwise logisticregression was also fitted between the same groupof variables and caseness in each of the mental disor-ders categories. Again, gender, marital status, andincome sufficiency showed statistically significantcorrelation (Table 5). To assess the association ofthe same variables with organic syndrome caseness(as an independent entity, without comorbidity withother mental disorder), simple logistic regressionswere fitted with each of the variables. Except forage, none of the variables had a significant correlation(Table 6).

DISCUSSION

The overall response rate among the sample house-holds, with potential subjects, was 90.3%. Amongindividual subjects the response rate was even betterat 97.3%. The sample screened, 610 subjects out of843 households, appears to be smallish. This was aninevitable consequence of the fact that, due to finan-cial and other constraints, we limited our screening toonly two Emirates and a region of a third one, out ofthe total seven Emirates in the country.

The commonest identified AGECAT syndromecase categories among the entire sample were depres-sion (20.2%), anxiety (5.6%), hypochondriasis (4.4%)and organic (3.6%). This is in conformity with theresults of other relevant studies in identifying depres-sion and organic, mostly cognitive impairment, asconsistently common mental health problems amongthe elderly. Also the prevalence rate of anxiety disor-der immediately follows these two conditions in manystudies. However, the identification of hypocondriasisin a small proportion among our syndrome cases,appears to be related to the psychometric propertiesof the GMS, which is designed to generate this entity,rather than an indication of the clinical significance ofhypochondriasis as an independent diagnostic entityamong the sample. A significant finding in this regard,was the firm association and comorbidity betweenhypochondriasis in one hand, and anxiety, depressionor comorbid anxiety and depression on the other hand(Table 4).

Organic, mostly cognitive impairment with orwithout dementia, was estimated as 3.6%. A similarfigure of 3.5% was reached in an Indian community



Table 2. Relevant economic and sociodemographic data

Al-Ain Dubai Ras-Al-Khaimah Totaln (%) n (%) n (%) n (%)

GenderMale 100 (60.2) 147 (51.4) 100 (63.3) 347 (56.9)Female 66 (39.8) 139 (48.6) 58 (36.7) 263 (43.1)

Age groups60–69 96 (57.8) 173 (60.5) 89 (56.3) 358 (58.7)70–79 42 (25.3) 79 (27.6) 48 (30.4) 169 (27.7)80–89 21 (12.7) 28 (9.8) 17 (10.8) 66 (10.8)90 and above 7 (4.2) 6 (2.1) 4 (2.5) 17 (2.8)Mean 68.84 67.90 69.41 68.55Median 65.00 65.00 68.00 65.00SD 8.96 7.83 8.32 8.29

Personal monthly incomeLess than 5000 Dhs* 59 (35.5) 188 (65.7) 120 (75.9) 367 (60.2)5000–9999 Dhs 58 (34.9) 41 (14.3) 32 (20.3) 131 (21.5)10000–14999 Dhs 8 (4.8) 19 (6.6) 1 (0.6) 28 (4.6)15000–19999 Dhs 1 (0.6) 2 (0.7) 1 (0.6) 4 (0.7)More than 20000 Dhs 0 (0.0) 6 (2.1) 0 (0.0) 6 (1.0)Unreported 40 (24.1) 30 (10.5) 4 (2.5) 74 (12.1)

Income sufficiency, according to individual subjectsExcellent 60 (36.1) 51 (17.8) 18 (11.4) 129 (21.1)Acceptable 86 (51.8) 173 (60.5) 101 (63.9) 360 (59.0)Not sufficient 16 (9.6) 61 (21.3) 36 (22.8) 113 (18.5)Unreported 4 (2.4) 1 (0.3) 3 (1.9) 8 (1.3)

Marital statusSingle 1 (0.6) 1 (0.3) 0 (0.0) 2 (0.3)Married 118 (71.1) 174 (60.8) 107 (67.7) 399 (65.4)Divorced 7 (4.2) 12 (4.2) 1 (0.6) 20 (3.3)Widowed 38 (22.9) 98 (34.3) 50 (31.6) 186 (30.5)Unreported 2 (1.2) 1 (0.3) 0 (0.0) 3 (0.5)

Family (household) compoundHusband and/or wife and their children 72 (43.4) 152 (53.1) 109 (69.0) 333 (54.6)Extended family 60 (36.1) 84 (29.4) 37 (23.4) 181 (29.7)Extended family and others 25 (15.1) 34 (11.9) 11 (7.0) 70 (11.5)Living alone 7 (4.2) 14 (4.9) 0 (0.0) 21 (3.4)Unreported 2 (1.2) 2 (0.7) 1 (0.6) 5 (0.8)

EducationIlliterate 141 (84.9) 233 (81.5) 138 (87.3) 512 (83.9)Elementary 19 (11.4) 40 (14.0) 17 (10.8) 76 (12.5)Preparatory 3 (1.8) 6 (2.1) 2 (1.3) 11 (1.8)Secondary 2 (1.2) 3 (1.0) 0 (0.0) 5 (0.8)University 1 (0.6) 4 (1.4) 0 (0.0) 5 (0.8)Post graduate 0 (0.0) 0 (0.0) 1 (0.6) 1 (0.2)

*US Dollar¼ 3.68 Dirhams.

Table 3. Diagnostic entities at the syndrome case level in Al-Ain, Dubai and Ras-Al-Khaimah

Al-Ain (n¼ 166) Dubai (n¼ 286) Ras-Al-Khaimah (n¼ 158) Total (n¼ 610)n (%) n (%) n (%) n (%)

Organic 6 (3.6) 12 (4.2) 4 (2.5) 22 (3.6)Schizophrenia 0 (0.0) 1 (0.3) 3 (1.9) 4 (0.7)Mania 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)Depression 19 (11.4) 84 (29.4) 20 (12.7) 123 (20.2)Obsession 1 (0.6) 7 (2.4) 3 (1.9) 11 (1.8)Hypochondriasis 5 (3.0) 15 (5.2) 7 (4.4) 27 (4.4)Phobia 0 (0.0) 1 (0.3) 0 (0.0) 1 (0.2)Anxiety 2 (1.2) 24 (8.4) 8 (5.1) 34 (5.6)



study, also using the GMS (Bhatnagar and Frank,1997). However, the estimate of 3.6% tends to be inthe lower border, in comparison to the estimates ofmost other comparable studies. A large Liverpoolsample of subjects aged over 65 years, also usingthe GMS, determined a prevalence rate of 5.2% atthe diagnostic syndrome level (Copeland et al.,1987a). A prevalence rate of 4.6% of cognitiveimpairment was determined in another UK study,using CARE organic brain syndrome scale (Lindesayet al., 1989). However, it should be noted that the sub-jects of this study were younger than those in the pre-vious studies. The entry age to our study was 60 years(mean age 68.6) while the entry age for the other stu-dies was 65. This was substantiated by computing theprevalence among those aged 65 or more within oursample, which turned out to be 5.1%. Evidence is wellestablished that the prevalence of all types of cogni-tive impairment, including dementias, increases with

age (Graham et al., 1997) and probably with no gen-der differences (Fichter et al., 1995). This was alsoconfirmed by our finding that age was the only vari-able, among others, to demonstrate significant corre-lation with organic syndrome caseness (Table 6).

The AGECAT syndrome depression among theentire study sample was 20.2%. This appears to berelatively higher than the prevalence estimated incomparable studies. In Copeland and colleaguesLiverpool study the overall AGECAT depressionwas 11.3% (Copeland et al., 1987a), while in aTaiwan community study using the GMS, depressiveneurosis was 15.3%, and major depression was 5.9%(Chong et al., 2001). A range from 5 to 19% wasdetermined among elderly people in black and ethnicminorities in the UK (McCracken et al., 1997). ACanadian study of elderly community residents,determined 11.4% as AGECAT depression (Newmanet al., 1998). It may be interesting to note that theAGECAT depression in our Al-Ain sample was11.4%, in Ras-Al-Khaimah 12.7%, in Dubai 29.4%and the overall prevalence was 20.2%. The prevalencerate of depression was within the same range in bothAl-Ain and Ras-Al-Khaimah, while significantlyhigher in Dubai. The result of hierarchical logicregression between depression syndrome caseness inthe three sites, after controlling for age, marital statusand income sufficiency, confirmed the clinical signif-icance of the elicited difference between Dubai andthe other two regions. This is suggestive of the need

Table 4. Comorbidity of hypochondriasis with anxiety, depressionand comorbid anxiety and depression

Diagnostic entity From the Comorbidity withtotal sample hypochondriasis

n (%) n (%)

Anxiety 34 (5.6) 7 (20.6)Depression 123 (20.2) 16 (13.0)Comorbid anxiety 30 (4.9) 7 (23.3)and depression

Table 5. Correlation of the group of subjects with identified caseness in any of the range of mental disorders, with five pertinent variables(n¼ 155)

Variable Non-syndrome cases Syndrome cases p-value Odds ration (%) n (%)

GenderMale 275 (79.3) 72 (20.7)Female 180 (68.4) 83 (31.6) 0.003 1.8

Age groups60–74 354 (76.5) 109 (23.5)75–84 79 (71.2) 32 (28.8) 1.385 and above 22 (61.1) 14 (38.9) 0.088 2.4

Marital statusCurrently married 318 (79.7) 81 (20.3)Currently single, divorced, separated, widowed 135 (64.1) 73 (35.1) 0.000 2.1

Income sufficiencyExcellent 109 (84.5) 20 (15.5)Acceptable 273 (75.8) 87 (24.2) 1.7Not sufficient 66 (58.4) 47 (41.6) 0.000 3.8

EducationIlliterate 377 (73.6) 135 (26.4)Less than secondary 70 (80.5) 17 (19.5)Secondary and above 8 (72.7) 3 (27.3) 0.400

p-values computed simple logistic regression.



for further rigorous research to identify the factorsbehind this observation. Perhaps, the fast rhythm ofchange in all aspects of life in urban Dubai comparedto the rural and simpler life style in other two places,may contribute, directly or indirectly, to this finding.

The total prevalence rate of anxiety in this studywas 5.6%. Again this is higher than the rates reportedin similar studies, especially those using the GMS/AGECAT package. The Copeland et al. New Yorkand London comparative study determined by farsmaller rates for all range of neuroses (Copelandet al., 1987b). Another community study, also usingthe same methodology, in a sample of elderly Asianimmigrants living in the UK, made an estimate of4% for anxiety neurosis among the studied sample(Bhatnagar and Frank, 1997). However, there is accu-mulating evidence suggesting that anxiety and anxi-ety disorders are not prominent health problems inold age. A relatively recent German study indicatedthat the prevalence rate of anxiety in the youngerold (70–84 yrs) was 4.3%, while in the older old(85–103 yrs) was 2.3%. There were more phobicsymptoms in the younger age group, and femalesshowed significantly higher anxiety (Schaub andLinden, 2000). Further more, the extremely low rateof phobic disorder reported in this study, comparedto other relevant studies, may be related to the natureof the phobic questions in the GMS which mayexclude some fears if they are thought to be normalfor elderly people. It is also claimed that clinical anxi-

ety among the elderly seems to be confined to thosewho also suffer clinical depression (Yohannes et al.,2000). It is argued that aging is associated with intrin-sic reduction in the susceptibility to anxiety anddepression, and this was attributed to the possibilityof reduced emotional responsiveness, increased emo-tional control and psychological immunisation tostressful life events in old age (Jorm, 2000). For con-firming the validity of the comparison made betweenour anxiety estimates and the estimates of other citedrelevant studies, it is crucial to take into considerationthe level of severity used to discriminate between syn-drome caseness and non-caseness, so as to match thediagnostic confidence level of 3 or more criteria usedin this study.

A comparison was made between the groups withidentified mental disorders (syndrome cases) withthe group without evidence for mental disorder(non-syndrome cases), in relation to five variables(Table 5). Mental disorders were significantly higheramong the female compared to the male subjects.This is consistent with the findings of similar studies(Catalan et al., 1988; Yohannes et al., 2000). Marriedsubjects living with their spouses were compared withthe single, divorced, separated or widowed, i.e. livingalone. In conformity with other relevant publishedworks, there was significant increase of mental disor-ders among those living alone (Baker et al., 1996). Oncomparing income sufficiency, as reported by thesubjects themselves, there was significant increase of

Table 6. Correlation of organic syndrome caseness with five pertinent variables (n¼ 11)

Variable Non-organic syndrome cases Organic syndrome cases p-value Odds ration (%) n (%)

GenderMale 340 (98.0) 7 (2.0)Female 259 (98.5) 4 (1.5) 0.648

Age groups60–74 460 (99.4) 3 (0.6)75–84 107 (96.4) 4 (3.6) 5.785 and above 32 (88.9) 4 (11.1) 0.001 19.2

Marital statusCurrently married 393 (98.5) 6 (1.5)Currently single, divorced, separated, widowed 203 (97.6) 5 (2.4) 0.434

Income sufficiencyExcellent 128 (99.2) 1 (0.8)Acceptable 351 (97.5) 9 (2.5)Not sufficient 112 (99.1) 1 (0.9) 0.360

EducationIlliterate 501 (97.9) 11 (2.1)Less than secondary 87 (100.0) 0 (0.0)Secondary and above 11 (100.0) 0 (0.0) 0.143

p-values computed using simple logistic regression.



mental disorder among those who had reported insuf-ficient income. There was no significant correlationbetween the level of education and the occurrenceof mental disorder in old age. Apparently the associa-tion of last two variables, income and education, withmental disorder among the elderly was not researchedenough to make a meaningful comparison.

Although the Arabic version of the GMS-A3 usedin this study proved to be feasible for use among oursample, the main drawback was the long time neededfor administration. It took each interviewer about 60–75 minutes to interview a study subject. However, asthe study progressed, the time needed diminished asthe interviewers gained experience and mastered thetechnique of application. Perhaps, a drawback to theAGECAT diagnoses was in connection with the cate-gory of organic syndrome caseness which, theoreti-cally, includes all degrees of cognitive impairment,with and without dementia, in addition to otherorganic brain dysfunctions. The fact that the GMS-AGECAT package is not designed to identify inde-pendent diagnostic entities of dementia or cognitiveimpairment is a limitation to this particular researchmethodology.

ACKNOWLEDGEMENT

The authors would like to express their sincere thanksto the Sheikh Hamdan Bin Rashid Al MaktoumAward for Medical Sciences who supported this pro-ject by the research grant (MRG-17/1999–2000).Authors would like also to thank Dr Emad HamdiGhoz and Dr Youserya Amin for their continuousadvice, and Mr D. Ranganathan for preparation ofthe manuscript.

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profile of mental disorders among the elderly united arab emirates population: sociodemographic...

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