Diabetes & Metabolic Syndrome: Clinical Research & Reviews 7 (2013) 191–197

Original Article

Pregnancy complications, mental health-related problems and type 2diabetes mellitus in Malaysian women

Syed Shahzad Hasan a,*, Kaeshaelya Thiruchelvam b, Syed Imran Ahmed b,Alexandra M. Clavarino a, Abdullah A. Mamun c, Therese Kairuz a

a The University of Queensland, 20 Cornwall Street, Woolloongabba 4102, Queensland, Australiab International Medical University, Jalan Jalil Perkasa 19, 57000 Bukit Jalil, Kuala Lumur, Malaysiac The University of Queensland, Herston Road, Herston 4006, Queensland, Australia

A R T I C L E I N F O

Keywords:

Type 2 diabetes mellitus

Depression

Anxiety

Malaysian

Women

A B S T R A C T

Aims: The aim of this study was to investigate the association between pregnancy complications, mental

health-related problems, and type 2 diabetes mellitus (T2DM) in Malaysian women.

Materials and methods: A case–control study of women with T2DM (n = 160) matched by age range to

controls without T2DM (n = 160). Data were collected in the Negeri Sembilan and PutraJaya regions in

Malaysia, from two hospital outpatient clinics, PutraJaya Hospital and Tuanku Jaa’far Hospital Seremban,

and one health clinic at Seremban. Validated, interviewer-administered questionnaires were used to

obtain the data. The unadjusted and adjusted estimates were calculated using the Mantel–Haenszel

method.

Results: Neither depression (RR 0.74, 95% CI: 0.39–1.41) nor anxiety (RR 1.00, 95% CI: 0.53–1.88)

symptoms increased the risk of T2DM significantly. However, gestational diabetes (RR 1.35, 95% CI:

1.02–1.79), and �3 pregnancies (RR 1.39, 95% CI: 1.08–1.79) were significant risk factors for the

development of T2DM. T2DM was not a significant risk factor for either depression (RR 1.26, 95% CI:

0.91–1.74) or anxiety symptoms (RR 1.13, 95% CI: 0.59–2.19).

Conclusion: In this study, T2DM is not a significant risk factor for depression and anxiety; similarly,

neither are depression and anxiety significant risk factors for T2DM. Although prevalence of depression

and anxiety is not alarming, the findings reported here should alert clinicians to screen and treat anxiety

and depression in people with diabetes and also note the importance of monitoring women with

complications in pregnancy for risk of later T2DM.

� 2013 Diabetes India. Published by Elsevier Ltd. All rights reserved.

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jo ur n al h o mep ag e: www .e lsev ier . c om / loc ate /d s x

1. Introduction

Diabetes mellitus (DM) is a chronic, inherited or acquireddisease that causes the pancreas to produce insufficient insulinresulting in an increased blood glucose concentration [1]. TheInternational Diabetes Federation (IDF) estimated that there were366 million diabetics worldwide in 2011 and the number isprojected to rise to 552 million by 2030 [2]. It is expected to shiftto the South East Asia Region by 2025, with an estimatedprevalence of 13.5%, affecting 145 million people [3]. In Malaysia,

* Corresponding author. Tel.: +61 469378163.

E-mail addresses: shahzad.syed@uqconnect.edu.au (S.S. Hasan),

kaeshaelya@hotmail.com (K. Thiruchelvam), imra_ahmed@imu.edu.my

(S.I. Ahmed), a.clavarino@sph.uq.edu.au (A.M. Clavarino),

mamun@sph.uq.edu.au (A.A. Mamun), t.kairuz@pharmacy.uq.edu.au (T. Kairuz).

1871-4021/$ – see front matter � 2013 Diabetes India. Published by Elsevier Ltd. All r

http://dx.doi.org/10.1016/j.dsx.2013.10.023

a middle-income, developing country located in the South EastAsia Region, the prevalence of DM has doubled over the pastdecade [4]. The National Health and Morbidity Survey I (NHMS-I)conducted in 1986, reported a 6.3% prevalence of DM amongadults aged �35 years whereas between 1996 and 2006, amongadults aged �30 years, the prevalence rose to 8.3% and 14.9%respectively, [4,5]. WHO estimates a total of 2.48 million diabeticsin Malaysia by 2030 [4]. DM is more prevalent in women after theage of 65 years, although below this age prevalence worldwide issimilar among men and women [6]. In developing countries suchas China, Brazil, and Egypt, DM is more prevalent among women,regardless of age [7].

Depression and anxiety are two common, co-morbid, modifi-able conditions associated with DM [8,9] and recent studies havefound that they are implicated in later-onset DM [10,11]. Anxietyand depression are more common among females and thosesuffering from diabetes, the target population in our study [12,13].

ights reserved.

S.S. Hasan et al. / Diabetes & Metabolic Syndrome: Clinical Research & Reviews 7 (2013) 191–197192

Several longitudinal studies from developed countries suggest thatthe association between depression and DM is reciprocal orbidirectional [14,15]. However, the relationship between depres-sion and diabetes seems stronger, with depression appearing tolead to diabetes more commonly than diabetes leading todepression [15,16]. Although there has been less focus on anxiety,a meta-analysis reported an increased prevalence of anxietysymptoms and generalized anxiety disorders (GAD) amongdiabetics [11].

Pregnancy-related factors such as gestational diabetes mellitus(GDM), preeclampsia, hypertension, are also reported to beassociated with the development of T2DM [17,18]. In the UnitedStates (US), between 5% and 10% of women with GDM are found tohave diabetes immediately after pregnancy, and have a 35–60%chance of developing diabetes in the next 10–20 years [19]. Theepidemiological data also suggest an association between GDMand T2DM with insulin resistance being suggested as a pathogeniclinkage [17]. A meta-analysis reported that the risk of subsequentT2DM was increased about 3-fold after gestational hypertensionand about 4-fold after severe preeclampsia [18].

Depression co-morbid with physical illness has been found tointensify the distress and disability normally associated with manymedical conditions [21,22]. A decrease in physical functioning hasbeen associated with depression, and either can amplify the effectsof the other; they are considered synergistic [23–25]. Longitudinaland case–control studies examining pregnancy complicationsassociated with modifiable mental health conditions (depressionand anxiety) and T2DM among middle-aged women in developingcountries are limited. The primary aim of this study was todetermine the association between pregnancy-related events,mental health conditions (depression and anxiety) and T2DMamong women in Malaysia.

2. Materials and methods

2.1. Study design and population

This case–control study involved women with diabetes(cases) matched to women without T2DM (control group) inthe same age range. Both groups comprised women aged 35–75years who had delivered at least one live singleton baby in thepast that neither died nor was adopted prior to leaving thehospital. Each case was a woman with a known diagnosis ofT2DM; the controls were women with no known diagnosis ofT2DM, the diagnosis of diabetes or absence of diabetes wasconfirmed by medical records. Women diagnosed with T1DMduring the last pregnancy and T2DM prior to the last pregnancywere excluded. Face-to-face interviews with women with T2DMwere carried out in outpatient clinics at PutraJaya Hospital inPutraJaya, Tuanku Jaa’far Hospital and Seremban Health Clinic,both in Negeri Sembilan. The control subjects were healthyfriends or unrelated family members (no blood relation for e.g. inlaws) of people with DM.

The validated English version of the study questionnaires weretranslated into the Malay language (Bahasa Melayu) with forward/backward translation conceptual as stipulated by the WHO [28].The sample size was estimated based on the actual and predictedprevalence of women with diabetes in Malaysia in 2010 and 2030,i.e. 11.6% and 13.8%, respectively. Assuming a 5% margin of errorand a 95% confidence interval using the extrapolated prevalence in2012, a sample size of 160 diabetics was calculated [29–31]. For thecase group, every second diabetic patient on the respectivepatients’ list at the clinic sites was recruited; verbal or writtenconsent was obtained from participants who met the inclusioncriteria. The control participants were recruited using the samecriteria, except for the presence of T2DM.

2.2. Measurement of outcomes

Two instruments were used to classify participants withdepression or anxiety symptoms: Delusions Symptoms StatesInventory (DSSI), the Center for Epidemiological Studies Depres-sion Scale-10 (CES-D 10). The information about the presence ofdepression and anxiety symptoms was collected in two parts.Firstly, depression and anxiety symptoms present before thediagnosis of T2DM, around the time of last pregnancy, werecollected retrospectively from medical records, to examinetheir role in causing T2DM. Secondly, anxiety and depressionwere assessed at the time of this study among using the DSSI andCES-D 10.

2.2.1. The Delusions Symptoms States Inventory (DSSI)

One of the advantages of using the DSSI instrument is that itcovers both depression and anxiety. The DSSI instrument wasmainly used to cover anxiety symptoms in this study. The DSSI is a14 item measure was developed for use with community samplesand has been validated against clinical samples with diagnosedmental illness [32–34]. The DSSI has been found to correlate well,and shares items with, other established symptoms scales such asthe Edinburgh Postnatal Depression Scale (EPDS) and the HospitalAnxiety/Depression Scale (HADS) [35,36]. The DSSI contains 14symptoms; 7 for depression and 7 for anxiety. Participants in thisstudy were classified as anxious or depressed when they scored 4or more and as non-anxious or non-depressed when they scored 4or less out of a maximum score of 7. The DSSI was found to bereliable (Cronbach alpha = 0.69).

2.2.2. The Center for Epidemiological Studies Depression CES-D 10

The Center for Epidemiological Studies Depression 10 Scale(CES-D 10) is a brief self-report screening tool for depressivesymptoms derived from the validated 20-item CES-D 20 Scale [37].The shorter form contains 10 depression items and is easier andquicker to administer in clinical and non-clinical settings. It hasbeen shown to have reliability and validity comparable to thestandard 20-item CES-D instrument and is considered a goodinstrument for screening depression in older adults [38], andpatients with T2DM [39]. The CES-D 10 uses a zero-to-threeresponse scale, with total symptom severity scores ranging from 0(no depression) to 30 (severe depression) [40]. Participants in thisstudy were categorized as depressed if they scored 11 or more onthe CES-D 10 scale. The CES-D-10 was found to be reliable(Cronbach alpha = 0.70).

There was significant positive correlation (r = 0.288, p = 0.001)between the two sections of DSSI used to examine depression andanxiety symptoms. validated English version of the study used toidentify depression symptoms, DSSI-Depression and CES-D 10,were also noted to have a significant positive correlation (r = 0.419,p = 0.001) suggesting that as depression symptoms on the DSSIscale increased, depression symptoms on the CES-D-10 scale alsoincreased.

2.3. Assessment of T2DM

Data on T2DM was collected through a self-administeredquestionnaire, where women were asked ‘‘Have you EVER beentold by a doctor that you have diabetes (high blood sugars)?’’ withresponse options ‘‘yes’’ or ‘‘no.’’ Subjects were categorized ashaving T2DM if they had been told by a physician they haddiabetes. This information was further confirmed by patients’medication records, fasting plasma glucose (FPG) greater than orequal to 7.0 mmol/l, and random plasma glucose (RPG) greaterthan or equal to 11.1 mmol/l. Subjects were not recruited if datawere missing on their fasting glucose levels. We also categorized

S.S. Hasan et al. / Diabetes & Metabolic Syndrome: Clinical Research & Reviews 7 (2013) 191–197 193

diabetics based on the duration of T2DM: 0–5 years, 6–10 years,and >10 years.

2.4. Measurement of exposures

Women were asked ‘‘Have you EVER been told by a doctor thatyou have gestational DM, gestational hypertension, pre-eclamp-sia?’’ with response options ‘‘yes’’ or ‘‘no.’’ The information aboutpregnancy-related factors (GDM, gestational hypertension, pre-eclampsia) was further confirmed by patients’ medical records.Depression, anxiety and T2DM were also used as exposures.

2.5. Measurement of confounders

The potential confounders and risk factors were identified onthe basis of their association with outcomes and on the basis of apriori knowledge [47–49]. Height (m) and weight (kg) measure-ments were obtained from participants’ medical records and usedto calculate body mass index (BMI) (kg/m2). BMI 30 or greater wasused as cut-off point to categorize participants as obese and non-obese as per WHO International Classification. The self-reportedinformation on level of physical activity (not at all, 1–2 times aweek, 3 or more times a week), alcohol consumption, and cigarettesmoking (non-smokers, past smokers and current smokers) werecollected from participants, while co-morbidities or medicalconditions other than T2DM were collected from medical records.

Menopausal status at the 21-y follow-up was considered on thebasis of a maternal report of her last period (i.e. the mother wasasked, ‘‘When did you have your last period?’’ with the followingoptions of response: ‘‘in the last month, last 3 months, between 3and 11 mo, or 12 months ago or before.’’). Mothers were also asked,in separate questions, whether they ever have had surgery toremove a uterus (hysterectomy) or one ovary. Combining thesequestions, menopausal status was defined as a regular period or nomenopause (i.e. had a period in the previous month), last period�12 month, last period 12 months ago, or last period before havinga hysterectomy or an ovary removed.

The physical health was examined using the physical compo-nent summary of the Short Form 12 of the Medical Outcomes Study(SF-12). SF-12 is a multipurpose survey instrument comprising 12questions, developed as a legitimate alternative to the SF-36. Thetwo scales (Physical and Mental Component Summary) provide aninsight to mental and physical health [41]. In this study, the SF-12was administered to obtain physical summary scale (PCS), withlower scores indicating greater disablement. The PCS scores werecalculated using the scores that range from 0 to 100. The mediansplit method was used to categorize participants where scores lessthan median indicate poor physical health (median = 75). Womenwere also asked ‘‘Have you EVER been told by a doctor that youhave sleep problem?’’ with response options ‘‘yes’’ or ‘‘no.’’Subjects were categorized as having sleep problem if they hadbeen told by a physician they had sleep problem.

This study was approved by the Ethics Committee at School ofPharmacy, The University of Queensland (Reg. No. 2011/14) and byInternational Medical University Research and Ethics Committee(Project ID No: B01/09-Res (04) 2012). The study was registeredwith National Medical Research Registry (NMRR), Ministry ofHealth Malaysia.

2.6. Statistical analysis

The data were analyzed using the Statistical Package for SocialSciences (SPSS)1 version 20 and STATA IC1 version 12, with asignificance level of �0.05. Descriptive statistics were used tocalculate percentages frequencies, means and standard deviations.The relationship between variables for categorical data was

performed using the x2 (Chi-Sq). Fisher Exact test was appliedin cases where sample size was small. Similarly, on occasionswhere we had less than 5 readings per cell for Chi-Sq, LikelihoodRatio test was applied. Comparisons between groups with normaldistribution were performed using the Student’s t-test. To verifythe existence of a correlation between instruments’ mean scores orother values, Pearson’s correlation test was used.

We presented our findings in a typical (simplified) case–controlstudy without matching format at individual confounder level. As ageneral rule, if an interaction was absent but confounding waspresent, summary (adjusted) measures of association werereported; stratum-specific (unadjusted) measures of associationwere reported if both were absent. However, for most of thefactors, we presented adjusted estimates, although for some wepresented both adjusted and unadjusted estimates. The stratum-specific odds ratios for diabetics and controls in addition to crudeodds ratios (ORs) were derived from a 2 � 2 contingency table.

The crude odds ratio is an unadjusted measure of theassociation in the aggregate form and it does not control forpossible confounding. Therefore, we used stratum-specific ORs andMantel and Haenszel (M–H) method to obtain relative risks (RRs),adjusted for the effects of confounders. The M–H method isillustrated, which represents a simple and useful tool to obtainestimates of association, adjusted for the effect of one or moreconfounders. This method is used to control for confounding in thecase where the confounding variables are categorical [50].

We therefore used the median split method to categorize theconfounders into binary groups. These binary groups includenumber of pregnancies and age at last pregnancy. As an estimatorof RR, ORMH = 1 under the null hypothesis of equal risks in exposedand unexposed subjects. If the value >1, the exposure is positivelyassociated with the disease that is it causes the disease, while if thevalue ranges between 0 and 1, the exposure plays some protectiverole [51,52].

For potential confounding, we compared the crude RR to theadjusted RR, with confounding confirmed when the crude RR andadjusted RR estimates differ. As far as literature is concerned thereis no statistical test for confounding, since confounding is a form ofsystematic error, and not random error. Therefore, the degree towhich confounding is present must remain a matter of judgment[51,52].

3. Results

3.1. Socio-demographic characteristics

A total of 320 participants (160 diabetics and 160 non diabetics)were interviewed, and the socio-demographic characteristics ofthose with diabetes and those without diabetes are summarized inTable 1. The median age at diagnosis of T2DM was 50 years (range:27–70); diabetics were slightly older than non diabetics, with amean difference in age of 7.0 � 1.83. The overall median age at lastpregnancy was 29 years; non diabetics = 30 years (range: 21–41) anddiabetics = 27.8 years (range: 18–44). All recruited diabetics devel-oped T2DM after their last pregnancy, about 22 (range: 9–26) yearson median. In both the diabetic and controls groups, most of theparticipants were Indians (48% versus 46%) and living in urban areas(89% versus 98%). Those with diabetes had lower educational andincome level than the controls (p < 0.05). None of the participantssmoked and only a few (<5) were consuming alcohol at the time ofstudy.

3.2. Pregnancy-related risk factors and risk of T2DM

Gestational diabetes was not significantly associated withhigher odds of T2DM (OR 2.26, 95 CI: 0.99–5.16), however, M–H

Table 1Socio-demographic characteristics of women (n = 320).

Variables Overall N = 320 n (%) Women with T2DM N = 160 n (%) Women without T2DM N = 160 n (%)

Age groups (years)*

35–44 52 (16.3) 18 (11.3) 34 (21.3)

45–54 133 (41.6) 39 (24.4) 94 (58.7)

55–64 93 (29.1) 70 (43.7) 23 (14.4)

�65 42 (13.1) 33 (20.6) 9 (5.6)

Ethnic groups*

Malay 62 (19.4) 52 (32.5) 13 (8.1)

Chinese 94 (29.4) 26 (16.2) 68 (42.5)

Indian 150 (46.9) 77 (48.1) 73 (45.6)

Indigenous/natives 11(3.4) 5 (3.1) 6 (3.8)

Geographical location

Urban 298 (93.1) 142 (88.8) 156 (97.5)

Rural 22 (6.9) 18 (11.2) 4 (2.5)

Highest level of education completed*

No formal education 14 (4.4) 14 (8.8) 0 (0.0)

Primary school 56 (17.5) 48 (30.0) 8 (5.0)

LCE/PMR/SRP (awarded after completing 9 years of schooling) 43 (13.4) 33 (20.6) 10 (6.2)

SPM/MCE/O’Level (lower secondary) 82 (25.6) 40 (25.0) 42 (26.2)

STPM/HSC/A-level (upper secondary) 19 (5.9) 5 (3.1) 14 (8.8)

Diploma 34 (10.6) 7 (4.4) 27 (16.9)

Bachelor degree 52 (16.2) 8 (5.0) 44 (27.5)

Post Graduate degree 20 (6.2) 5 (3.1) 15 (9.4)

Occupation*

Government employee 57 (17.8) 16 (10.0) 41 (25.6)

Non-government employee 58 (18.1) 17 (10.6) 41 (25.6)

Self employed 18 (5.6) 4 (2.5) 14 (8.8)

Homemakeryy 133 (41.6) 93 (58.1) 40 (25.0)

Retired/pensioner 38 (11.9) 29 (18.1) 9 (5.6)

Unemployedy 16 (5.0) 1 (0.6) 15 (9.4)

Monthly income*

No income 82 (25.6) 52 (32.5) 30 (18.8)

Less than RM2499 99 (31.0) 73 (45.5) 26 (16.2)

RM2500–RM4999 63 (19.7) 21 (13.0) 42 (26.3)

RM5000 or more 76 (23.7) 13 (8.0) 62 (38.7)

*p < 0.05; p-value obtained by Chi-square test.y Unemployed include both those able or unable to work and volunteers.yy Homemaker include either with or without allowance.

S.S. Hasan et al. / Diabetes & Metabolic Syndrome: Clinical Research & Reviews 7 (2013) 191–197194

method produced significant RRMH (RR 1.41, 95% CI: 1.06–1.86)which remained significant after adjustments for the effects ofpotential confounders. Women who had 3 or more pregnancies(OR 1.86, 95% CI: 1.16–2.98) and were more than 30 years of ageat last pregnancy (OR 2.64, 95% CI: 1.68–4.16) had increased

Table 2Association between pregnancy and mental health-related factors, and stratum-specifi

Factors Overall N = 320 n (%) Women with T2DM N

Pregnancy-related factors

No GDM* 292 (91.3) 141 (88.1)

GDM 28 (8.7) 19 (11.9)

No gestational hypertension 290 (90.6) 146 (91.3)

Gestational hypertension 30 (9.4) 14 (8.7)

No pre-eclampsia* 312 (97.5) 160 (100.0)

Pre-eclampsia 8 (2.5) 0 (0.0)

<3 pregnancies* 108 (33.7) 43 (26.9)

�3 pregnancies 212 (66.3) 117 (73.1)

�30 age at last pregnancy* 150 (46.9) 56 (35.0)

>30 age at last pregnancy 170 (53.1) 104 (65.0)

Mental health-related factors

Not depressed 304 (95.0) 154 (96.3)

Depressed 16 (5.0) 6 (3.7)

Not anxious 310 (96.9) 155 (96.9)

Anxious 10 (3.1) 5 (3.1)

GDM = gestational diabetes mellitus.* p < 0.05 based on Fisher exact test.y Statistical significance.

odds of T2DM (Table 2). Similarly M–H also found a significantassociation (Table 3). Depression (OR 0.58, 95% CI: 0.21–1.65),anxiety (OR 1.00, 95% CI: 0.28–3.52), and sleep problems (OR0.51, 95% CI: 0.21–1.24), diagnosed around the time pregnancywere not significantly associated with increased odds of T2DM

c odds of type 2 diabetes.

= 160 n (%) Women without T2DM N = 160 n (%) ORs (95% CI)

151 (94.4) 2.26 (0.99–5.16)

9 (5.6)

144 (90.0) 0.86 (0.41–1.83)

16 (10.0)

152 (95.0) 0.06y (0.003–0.98)

8 (5.0)

65 (40.6) 1.86y (1.16–2.98)

95 (59.4)

94 (58.7) 2.64y (1.68–4.16)

66 (41.3)

150 (93.7) 0.58 (0.21–1.65)

10 (6.3)

155 (96.9) 1.00 (0.28–3.52)

5 (3.1)

Table 3Association between mental health and pregnancy-related factors, and risk of type 2 diabetes, adjusted by the Mantel–Haenszel method for the effect of confounders.

Factors % Women

with T2DM

N = 160

Unadjusted

Effect Size

RR (95% CI)

Adjusted for

Anxiety RR

(95% CI)

Adjusted for

Sleep Problem

RR (95% CI)

Adjusted for

GDM RR

(95% CI)

Adjusted for

Obesity RR

(95% CI)

Adjusted for

Physical Activity

RR (95% CI)

Mental health-related factors

Not depressed 96.3 1.00 1.00 1.00 1.00 1.00 1.00

Depressed 3.7 0.74 (0.39–1.41) 0.71 (0.36–1.40) 0.83 (0.44–1.60) 0.71 (0.37–1.36) 0.75* (0.40–1.40) 0.72 (0.39–1.34)

Not anxious 96.9 1.00 1.00 1.00 1.00 1.00 1.00

Anxious 3.1 1.00 (0.53–1.88) 1.16y (0.60–2.22) 1.13 (0.58–2.20) 0.99 (0.54–1.85) 0.98 (0.54–1.81) 1.06 (0.57–1.95)

Pregnancy-related factors

No GDM 88.1 1.00 1.00 1.00 1.00 1.00 1.00

GDM 11.9 1.41* (1.06–1.86) 1.41* (1.06–1.86) 1.41* (1.06–1.85) 1.43*,y (1.09–1.87) 1.35* (1.02–1.77) 1.35* (1.02–1.79)

<3 Pregnancies 26.2 1.00 1.00 1.00 1.00 1.00 1.00

�3 Pregnancies 73.8 1.41* (1.08–1.84) 1.42* (1.08–1.85) 1.43* (1.10–1.86) 1.41* (1.08–1.83) 1.42* (1.09–1.84) 1.39* (1.08–1.79)

�30 age at pregnancy 64.4 1.00 1.00 1.00 1.00 1.00 1.00

>30 age at pregnancy 35.6 0.62* (0.49–0.79) 0.62* (0.49–0.79) 0.62* (0.49–0.79) 0.60* (0.46–0.76) 0.63* (0.50–0.80) 0.62* (0.49–0.78

GDM = gestational diabetes mellitus; RR = relative risk.y Adjusted for depression.* Statistically significant.

Table 4Association between type 2 diabetes, and risks of depression and anxiety, adjusted by the Mantel–Haenszel method for the effect of confounders.

Factors % Depressed

N = 26

Unadjusted

effect size

RR (95% CI)

Adjusted for

physical activity

RR (95% CI)

Adjusted for

menopause RR

(95% CI)

Adjusted for

comorbidities

RR (95% CI)

Adjusted for

obesity RR

(95% CI)

Adjusted for

sleep problem

RR (95% CI)

Adjusted for

anxiety RR

(95% CI)

Not diabetics 38.5 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Diabetics 61.5 1.26 (0.91–1.74) 1.67 (0.70–3.98) 1.41 (0.70–2.85) 4.6 (0.63–33.7) 1.63 (0.75–3.56) 1.81 (0.86–3.77) 1.52 (0.74–3.10)

% Anxious N = 32

Not diabetics 46.9 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Diabetics 53.1 1.13 (0.59–2.19) 1.23 (0.63–2.42) 1.10 (0.55–2.08) 0.98 (0.38–2.51) 1.12 (0.56–2.23) 1.29 (0.67–2.45) 0.96y (0.51–1.81)

y Adjusted for depression.

S.S. Hasan et al. / Diabetes & Metabolic Syndrome: Clinical Research & Reviews 7 (2013) 191–197 195

(Table 2). Similarly M–H also found an insignificant association(Table 3).

3.3. T2DM and risk of depression and anxiety symptoms

Symptoms of depression were uncommon among people withand without DM based on both DSSI (N = 10 versus N = 18) andCES-D (N = 10 versus N = 16) and this translated into an insignifi-cant association between T2DM and depression symptoms (RR1.26, 95% CI: 0.91–1.74) and remained insignificant after adjust-ments for the effects of confounders (Table 4). Similarly duration ofdiabetes (6–10 years = OR 0.50, 95% CI: 0.12–2.11 and >10years = OR 1.19, 95% CI: 0.21–6.80) did not increase the odds ofdepression significantly.

Participants with anxiety symptoms were slightly older (meanage: 44.5 � 5.9) than participants reporting symptoms of depression(mean age: 37.0 � 13.1). Anxiety symptoms were more frequentlyfound among people with DM (n = 34) than people without DM(n = 30). Similar to what we observed with depression symptoms,T2DM did not increase the risk of anxiety symptoms significantly (RR1.13, 95% CI: 0.59–2.19) (Table 4).

4. Discussion

To the best of our knowledge, the current study is the first toexplore the association between pregnancy, mental healthconditions and T2DM in Malaysian women. The findings of thisstudy were similar to those of NHMS III [4]; the majority ofdiabetics are Indians (�19.9%), followed by Malays (�11.9%) andChinese (�11.4%) [4]. Some studies indicate an inherent risk of DMamong Indians and phenotypic differences in the DM progressionrate [5,6,53]. People with DM were slightly older than peoplewithout DM suggesting that the age structures differ between the

two groups. The body’s ability to produce and use insulindeteriorates as one ages, placing older adults at an elevated riskof developing T2DM. The sharpest increase in the prevalence of DMoccurred after the age of 40 years. In this study, women in the 45–54 year age group had the highest proportion of T2DM. More than50% of the affected women in this study were of working age, thatis between 25 and 64 years which is common feature in developingcountries [54,55].

Women who developed symptoms of depression and anxiety,before the diagnosis of T2DM, around the time of the lastpregnancy were not significantly associated with increased oddsof T2DM. Both depression and diabetes can have extendedprodromal periods [16] and we believe the period of about 22years, which was the difference between median age atdiagnosis of depression and anxiety and median age at diagnosisof T2DM in this study, was adequate to indicate development ofT2DM. Previous studies came to different conclusions about therole of depression as a cause of diabetes [57,58]; Saydah et al.found no evidence to support an etiological relation betweendepression and diabetes [57], and a retrospective Scandinavianstudy published in 2004 also reported no overall relationbetween diabetes and depression [59]. However, a recentprospective large population-based study (2007) documentedthat individuals reporting symptoms of depression at baselinehad increased risk of T2DM development at 10-year follow-up[14]. Carnethon et al. found that if social factors such aseducation are taken into account, depression can predict anincreased incidence of diabetes [58]. It is reported that the linkbetween diabetes and depression does not solely result frompsychological distress resulting from the disease diagnosis [60].At the time of this study, the American Psychological Association(APA) guidelines do not support the view of a mood disordercaused by diabetes [61].

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In previous studies, there has been less focus on anxietycompared to depression in patients with T2DM. However, unlikedepression, anxiety was more commonly found among peoplewith DM (21.3%) than people without DM (18.8%) in this study. Thefinding is consistent with the World Mental Health Surveyconducted across 17 countries where the risk of mood and anxietydisorders was higher among individuals with diabetes relative tothose without [62]. Anxiety was more prevalent among themiddle-aged women as opposed to the younger or older age groupsin this study. This may be due to the fact that anxiety in the olderpeople is often underestimated because they are more likely toreport physical complaints rather than psychiatric symptoms [63].Anxiety is an episodic disorder and participants may have not hadanxiety attacks during the time of the study. We also notedsignificant positive correlation between anxiety and depressionsuggesting that as the depression symptoms increased, anxietysymptoms correspondingly increased. It is well established thatboth depression and anxiety go hand in hand and they are usuallydiagnosed together [63].

Among pregnancy-related factors, GDM, preeclampsia andnumber of pregnancies were found to increase the odds of T2DM inthis study. For any population and ethnic group, the risk of GDMindicates the underlying frequency of T2DM [17,64]. SimilarlyLeanne et al. found that women with GDM had an increased risk ofdeveloping T2DM compared with those without GDM [64].Although meta-analysis reported significant association betweenT2DM and gestational hypertension [18], the participating womenwith a history of gestational hypertension in this study were notassociated with increased risk of T2DM. Our findings also suggestthat the risk of developing T2DM is lower among those womenwho were pregnant at age more than 30 years.

5. Limitations

This study used self-report scales to assess depression andanxiety; although diagnosis of these disorders by a trained healthcare professional according to DSM-IV-based criteria would havebeen preferred, this was not possible. There may have beenparticipant recall bias which would be a systematic error resultingfrom lack of completeness of memory of past events or experienceswhich may have affected accuracy of self-reported information.

6. Conclusions

This study supports the hypothesis that T2DM is not asignificant risk factor for depression and anxiety symptoms.Anxiety symptoms were more commonly found among diabeticsthan depression symptoms. However, both depression andanxiety was not significantly associated with increased odds ofT2DM. This study also confirms previous findings that GDM andpreeclampsia are the important risk factors for T2DM. Althoughprevalence of depression and anxiety is not alarming, the findingsalert clinicians to screen and treat anxiety and depression inpeople with diabetes. Additional properly designed studies areneeded to establish the strength and direction of this relationshipin developing countries.

Authors’ contributions

All authors contributed to this paper.

Financial disclosure

None.

Conflict of interest statement

None.

Acknowledgements

We wish to extend our utmost gratitude to the administrativeassistance of the International Medical University PostgraduateOffice. The project was also supported by the Pharmacy Depart-ment of the PutraJaya Hospital and Tuanku Jaa’far Hospital, NegeriSembilan, and the Seremban Health Clinic, Negeri Sembilan.

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