psychosocial risk factors for stroke 2012

7/30/2019 Psychosocial Risk Factors for Stroke 2012

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RESEARCH PAPER

Is psycho-physical stress a risk factor for stroke?A case-control study

Jose Antonio Egido,1 Olga Castillo,1 Beatriz Roig,1 Isabel Sanz,1

Maria Rosa Herrero,1

Maria Teresa Garay,1

Ana Mara Garcia,1

Manuel Fuentes,2

Cristina Fernandez2

ABSTRACTBackground Chronic stress is associated withcardiovascular diseases, but the link with stroke has notbeen well established. Stress is influenced by life-stylehabits, personality type and anxiety levels. We sought toevaluate psycho-physical stress as a risk factor forstroke, while assessing gender influences.Methods Case-control study. Cases: patients (n150)aged 18e65, admitted consecutively to our Stroke Unit

with the diagnosis of incident stroke. Controls: (n

300)neighbours (paired with case 65 years) recruited fromthe census registry. Study variables: socio-demographiccharacteristics, vascular risk factors, psychophysicalscales of H&R (Holmes & Rahe questionnaire of lifeevents), ERCTA (Recall Scale of Type A Behaviour), SF12(QoL scale), GHQ28 (General Health Questionnaire).Statistical analyses included conditional multiple logisticregression models.Results Mean age was 53.8 years (SD: 9.3). Comparedwith controls, and following adjustment for confoundingvariables, significant associations between stroke andstress were: H&R values >150 OR3.84 (95% CI 1.91to 7.70, p24) OR2.23 (95%

CI 1.19 to 4.18, p0.012); mental SF12 (values >50)OR0.73 (95% CI 0.39 to 1.37, p0.330); psychologicalSF12 (values >50) OR0.66 (95% CI 0.33 to 1.30,p0.229), male gender OR9.33 (95% CI 4.53 to 19.22,p

6 months. The patient can be consid-ered as suffering from an adjustment disorder if

clinically significant emotional or behaviouralsymptoms result.5 6

Psycho-physical stress can produce neuro-vegetative effects that predispose to psychosomaticdiseases.7 8 Several studies highlight stress asan independent risk factor in cardiovasculardiseases9e13 but there is a dearth of in-depth studiesevaluating the psycho-physical bases of stress andstroke.14e16

Psychophysical stress derives from situations thatmodulate factors such as personality type, quality-of-life (QoL), levels of anxiety or depression and otherenvironmental factors including social- and work-status, family responsibilities, and cultural level.17

These factors have not been fully assessed, to date.The objective of the present study was to eval-

uate, in a multimodal standardised approach, theassociation of psychophysical stress on stroke ina population


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We did not pair for gender because one objective of the study wasto assess the influence of gender. Control individuals whoreported a personal history of stroke were excluded from thestudy. If a selected control did not respond, refused to participateor was ineligible because of prior stroke, a second or a third age-matched control living in the neighbourhood was invited.

The control individuals were identified by an external clinicalresearch organisation using a random door-to-door search for

individuals fulfilling the inclusion criteria. The clinical researchorganisation was blinded with respect to gender and clinical data.

Amanual of operations was used to standardise data collection.

Study variablesVariables related with psychophysical stress were based on thecombined quantitative scores of the 4 scales used:< Questionnaire of life events of H&R consisting of 40 items

corresponding to stressful experiences lived over the previousyear. A score >300 constitutes the high-risk group with an80% probability of suffering an illness in the near future. Anintermediate-risk of 50% is a score between 150 and 300, thelow-risk of 30% corresponds to a score 8 on thisscale are considered pathological.20

< QoL scale (SF-12) provides a profile of general health statuswith reference to the previous month. Consisting of 12 itemsderived from eight dimensions of the SF36 questionnaire, itassesses physical function, social function, physical role,emotional role, mental health, vitality, body pain, generalhealth. These dimensions are summed as mental and physicalcomponents. A low QoL is defined as a value lower than themedian scores of the control group of individuals.21

14.4 g/day.23 Tobacco consumption wasestablished according to the WHO as: non-smoker, ex-smokerand current smoker. This last group includes habitual smokersand occasional smokers.24 Obstructive sleep apnoea syndromewas evaluated on the Epworth scale which measures the diurnalsomnolence that reflects the poor quality of night-time sleep.Scores up to 13 indicate light somnolence, up to 19 indicate

moderate and>

24 indicate severe somnolence.

25

The socio-demographic variables included age, gender, civil status,

education level, number of children, tobacco consumption,beverages or relaxation-inducing substances (coffee, tea, energydrinks containing cola-caffeine and taurine derivatives, sleepingtablets, anti-depressants, recreational drugs). The intakefrequencies were: never, 2/day.

The questionnaires were self-administered. Socio-demographic data and clinical history were recorded by theinterviewer using the same standardised format in cases and

controls. The interviews were conducted in the hospital duringthe first week following the stroke. Control individuals wereassessed in a face-to-face interview.

Quality control and ethical issuesThe agency identifying the control individuals and members ofthe investigation team underwent quality control testing toguarantee the validity of the information.

The study was approved by the ethics committee of the studycentre. Written informed consent was obtained from all theparticipants prior to inclusion into the study. Data were codifiedso as to maintain patient and control individuals anonymity.

STATISTICAL ANALYSESSample size was calculated for a confidence level a error of 5%,a power of 80%, an estimated proportion of exposure of controlsof 32.4%,26 an OR of 1.8, and with a case-control ratio of 1:2.The sample size calculation indicated 150 cases and 300 controls.

Qualitative variables are expressed with their frequencydistributions and quantitative variables as means and SD.

Univariate conditional logistic regression analyses wereapplied to assess relationships between categorical variables andstroke. The magnitude of association was evaluated using theOR and 95%CI. Interactions between gender and each of thescales used in the study were evaluated while introducing aninteraction term into the model. An adjusted logistic conditional

regression model was applied to each measurement scale ofpsychophysical stress.

Adjustment was with those variables which, in the univariateanalyses, showed a level of statistical significance of p


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calculated, and none were statistically significant. The data wereprocessed with the STATA V.9.0 (STATA Corp LP, Texas, USA)statistical package.

RESULTSConsecutive case recruitment continued until the number ofcases meeting the study entry requirements (n150) wasachieved. Of the 223 cases evaluated in this process, 73 were

excluded because of: comprehension deficit (n22, 30.1%),previous stroke (n19, 26%), refusal to participate (n11,15.1%), not domiciled in Madrid (n10, 13.7%), cognitivedeterioration (n5, 6.8%), psychiatric problems (n3, 4.1%),death (n3, 4.1%). The mean age of the patients was 53.8 years(69.3) and that of the control group was 53.6 years (69.6).

The socio-demographic and clinical characteristics of thegroup of patients included in the study were compared withthose who were excluded. Statistically significant differenceswere found only in the distribution of the civil status variable(singles included 36 (24%) vs 26 (40%) in the excluded group;p0.022) and the severity of stroke event (19 (24%) TACI ofthose included vs 27 (40.9%) of the 73 who had been excluded

(p9.

From our database we selected pairs of cases and controls whowere recorded as being employed at the time of the study. There-analysis showed that the significance was maintained

between gender and the diagnosis of stroke (OR5.4; 95% CI 2.5to 11.7; p14.4 g/day), DM, HT,hypercholesterolaemia, clinically diagnosed angina and/ormyocardial infarction, previously diagnosed alterations incardiac rhythm, and Epworth scale ($9). Figure 2 summarisesthe results of the multivariate analyses for each of the scalesused. A score of$150 in the H&R scale and a score of>24 in theERCTA scales is significantly related to the presence of stroke.The patients with scores >50 in the psychophysical SF12 scalehad a significantly lower frequency of stroke. Followingadjustment for potential confounding factors, the score on theGHQ28 scale was not related to stroke.

Finally, the conditional logistic regression model was adjustedby introducing the psychosocial variables of stress (except theGHQ28) adjusted for the potential confounding factors identifiedin the previous analysis. The factors that were independentlyrelated to stroke were: a score $150 on the H&R scale, a score of>24 on the ERCTA scale, masculine gender, consumption ofenergy drinks more than twice a day, type of smoker, alterationsin cardiac rhythm, and a score$9 on the Epworth scale (table 3).

BEHAVIOURAL FACTORS AND STRESS

The relationships between the consumption of tobacco, alcoholand physical activity versus ERCTA and the H&R scales withrespect to cases and controls were assessed. We did not observe,in the univariate analysis, any of these factors being significantin relation to the levels of stress in cases evaluated by thesescales. Further, modification of the effect of reduction in theeffect of these three factors on stress (between cases andcontrols) following the introduction of the interaction term intothe models of logistic regression indicated no statisticallysignificant differences.

DISCUSSIONStudy results and literature perspective

The grade of stress under which an individual lives is infl

uencedby several socio-cultural factors.27e30 In the present study

Table 1 Clinical characteristics of the cases

Characteristic n (%)

Stroke aetiology

Ischaemic 135 (90)

Hemorrhagic 15 (10)

Classification

TACI 19 (14.1)

PACI 23 (17)

LACI 40 (29.6)

POCI 19 (14.1)

TIA 49 (25.2)

Hemorrhagic aetiology

HT 13 (86.7)

Anticoagulants 0 (0)

Cavernoma 1 (6.7)

Other 1 (6.7)

Ischaemic aetiology

Cardioembolic 40 (29.6)

Atherothrombotic 17 (12.5)

Indeterminate 42 (31.1)

Lacunar 32 (23.7)

Unusual 4 (2.9)

Stroke severity

CSA 6-10 120 (80)

CSA 0.5-6 30 (20)

mRS 0-1-2 69 (46)

mRS 3-4-5 81 (54)

CSA, Canadian Score on Admission; HT, hypertension; LACI, lacunar infarct; mRS,Rankin Score on Admission; PACI, partial anterior circulation infarct; POCI, posterior

circulation infarct; TACI, total anterior circulation infarct; TIA, transient ischaemic attack.

Egido JA, Castillo O, Roig B, et al. J Neurol Neurosurg Psychiatry (2012). doi:10.1136/jnnp-2012-302420 3 of 7

Cerebrovascular disease

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various dimensions of validated scales were applied, and theresults are coherent in terms of relationship of stroke withstress. Other studies have evaluated stress with a single-itemquestionnaire.31 The INTERSTROKE study,32 which is thelargest case-control study dealing with known and emergingrisks factor across different countries and races, showed anassociation between psychosocial stress (and depression) withstroke. However, it only applied an isolated combined measureof general stress in the home and in the workplace over theprevious year. Conversely, we used a multimodal approachbecause psycho-physical stress derives from different situationsthat modulate such factors as personality type, QoL, anxietylevels, and other environmental factors. Further, in the INTER-STROKE study, for those patients unable to communicatesufficiently to complete the study questionnaire, proxy respon-dents were used. As we had found (see Methods, above) and ashas been previously reported,18 this approach is not valid inassessing responses to psychological questions.

Individuals having lived under stressful conditions in theprevious year (H&R scale) were, following adjustment, 3.8-foldmore likely to suffer a stroke compared to controls. Otherauthors have also proposed that psychosocial stress derived fromstressful life events increase the risk of cerebral infarct inhypertensive individuals.28

Patterns of behaviour can reflect the capacity to adapt toa stressful life. We found that individuals with high levels ofcompetitiveness and aggression (ERCTA scale >24) are,following adjustment, 2.2-fold more likely to suffer a strokecompared with controls.

For the GHQ28 psychosocial scale, those persons whopresented signs of depression had 22% higher likelihood ofhaving a stroke (albeit this did not reach statistical significance).

The Caerphilly study15 concluded that middle-aged men withsymptoms of psychological distress have a threefold higherlikelihood of dying from a stroke. The level of distress and thedepression symptoms associated with stress have somaticrepercussions such as HT30 and are also associated with poorlife-style choices such as low physical activity, tobacco habit,alcoholism and poor dietary habits.33 However, we did notobserve that any of the behavioural factors were related to stressin our cases and controls. Over the past year, the prevalence ofmental disturbance in Spain has been estimated as 8.48% of theadult population.34 The lack of statistical significance withrespect to the GHQ28 scale may be related to the high grade ofstress in our control population, which was greater than

expected and would require a larger sample size for a moredetailed investigation.

Table 2 Sociodemographic and lifestyle characteristics of thecases and controls

Controls CasesOR (95%CI) p Valuen (%) n (%)

Demographic

Gender

Female 191 (63.7) 34 (22.7) 1

Ma le 10 9 (36 .3) 116 (77.3) 6.7 4 (3.98 to 11.42 ) 2 c ups/day 10 (3.3) 2 (1.3) 0.2 6 (0.05 to 1.28) 0.1 0

Consumption of energy drinks

No 178 (59.5) 58 (38.7) 1

1e2 units/day 111 (37.1) 71 (47.3) 1.80 (1.20 to 2.72) 0.005

>2 uni ts/day 10 (3.3) 21 ( 14) 6.68 (2.76 to 16.19)


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In the multivariate analysis of values derived from eachscale, in relation to generic aspects of QoL, the individualswho had a better QoL (SF12 >50) had, following adjustment,half the likelihood of suffering a stroke compared to controls.

As such, we observed a protector effect of QoL reflected inthis scale. Poor socio-cultural conditions of the population,such as unfavourable housing conditions together with a lowsocio-cultural level, can generate high stress levels whichplay a significant role in the aetiology of cardiovasculardiseases.2 7 3 5 Conversely, stress has been shown to be associ-ated with material advantage, and which showed a spuriousprotector effect.36 In our study sample, following adjustmentfor the stress scales, the statistical significance was lost in boththese components of QoL assessment. This effect is produced,principally, by the H&E scale. In our study, in order to mini-mise the effect of environmental factors, a study sampleselection criterion was that the control individuals lived in thesame census district as the cases. As such, factors such as

education level, social conditions including civil status,number of children, family load, and influence of environmentare very similar.

With respect to work status, the number of individuals beingactively employed was much greater in cases than in controls,but this variable lost its statistical significance in multivariateanalysis. We recorded active employment but, unlike a previous

report,37 we did not evaluate the quality nor the grade of stressin the specific employment environment.

Study limitations

To evaluate the bias implied in non-response, we compared thecharacteristics of the individuals included in the study withthose who had been excluded. We observed that there were nostatistically significant differences in demographic characteris-tics between the two groups, except for civil status and extent ofthe stroke. To achieve the highest level of response possible, allsubjects in the study were individually contacted. However, wewere not able to exclude completely all those with specificpsychological attitudes that could influence non-response.

The exclusion of those patients who, due to their severity ofdisease or aphasia, were not able to respond on their own to thequestionnaire implies a bias in selection. Approximately 40% ofthose not included presented with extensive stroke, of whom,half had severe aphasia. Hence, these data cannot be extrapo-

lated to this type of patient. However, other authors havestudied this group of patients and observed an important asso-ciation between stress and fatal stroke.14 In our study, half of thecases presented a severe disability, and in 14% of patients withclinical infarct we observed a higher grade of stress (as measuredon the H&R scale). Hence, exclusion of more severe patientswould tend to minimise the effect of stress.

Figure 1 Relationship of the psycho-physical stress and quality-of-life scaleswith ictus between males and females.GHQ, general health questionnaire.

Figure 2 Multiple conditionalregression models: stress scales effecton stroke. Logarithm scale: OR 95% CI.N371. *adjusted for: gender, energydrinks intake, Epworth scale score.**adjusted for: gender, energy drinksintake, smoke category, hypertension,arrhythmia, Epworth scale score.***adjusted for: gender, energy drinksintake, smoke category, arrhythmia,Epworth scale score. GHQ, generalhealth questionnaire.





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Some of the risk factors associated with stroke were self-reported and this can produce a differential classification bias.The association of stress with stroke could be influenced by thestress due to the stroke itself, and this implies a bias in thedifferential classification, but only in the stroke group. However,the scales assess the patient with respect to the period before thestroke, depending on the design and validation of each scale.Conversely, the scales with significant results are the conse-quence of objective outcomes such as the H&R scale of stressfullife19 and of the behaviour type pattern22 and, as such, are lessinfluence by a possible bias in the patients recall of events andconditions.

It is reasonable to expect that stroke diagnosis and itstreatment can change the patients psycho-physical status and

life-style habits. The resulting bias can induce an artificialassociation in a cross-sectional setting. For example, strokepatients are more likely to quit smoking, which results inselection bias and an underestimation of smoking effect amongcurrent smokers together with an overestimation of effectamong ex-smokers. In our study we had no means of excludingthis possible bias.

Dealing with a hospitalised patient population carries its ownlimitation in relation to the external validity of the results. Thestroke patient sample in our study had similar characteristics asany other hospitalised population with this diagnosis. Theseincluded distribution, type of stroke, risk factors and severity,a high proportion of ischaemic stroke of principally cardi-

oembolic and indeterminate aetiology, and a small proportion ofhemorrhagic stroke caused by HT.

We selected a limited age range in order to reduce the otherconfounding vascular disease risk factors and to assess the effectof stress due to employment. As such, our results cannot beextrapolated to other age groups.

Gender, stress and strokeThere were more women in the control population sample andreflect the data provided by Spanish National Institute of

Statistics. Gender differences in employment rates were onlyaround 10%.38 Hence, based on the results obtained in ourpopulation, gender does not appear to affect the relationshipbetween stress and stroke.

CONCLUSIONSPsycho-physical stress factors related to stressful life-style andtype A personality are associated with stroke, independently ofother risk factors and unhealthy life-style. We did not observegender having a significant effect on these findings of psycho-physical stress and stroke. Addressing the influence of psycho-physical factors on stroke could constitute an additionaltherapeutic line in the primary prevention of stroke in the at-riskpopulation and, as such, warrants further investigation.

Contributors JAE, OC, BR, IS, MRH, MTG, MF and CF: Design of the study andpatient care. OC, BR, IS, MRH, MTG: data collection. OC, BR, IS, MRH, MTG, MF andCF: questionnaire design. MF and CF: statistical analysis. JAE, MF and CF: manuscriptpreparation. OC, BR, IS, MRH, MTG, AMG: input in drafting the manuscript. JAE is theoverall guarantor of validity of the study.

Funding This study was funded, in part, by a grant from the Health ResearchFoundation [Fondo Investigacion Sanitaria; FIS PI7/0124] within the European RegionalDevelopment Fund [Fondo Europeo de Desarrollo Regional; FEDER].

Competing interests None.

Patient consent Obtained.

Ethics approval Ethics approval was provided by ethics committee Hospital ClnicoSan Carlos.

Provenance and peer review Not commissioned; externally peer reviewed.

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Table 3 Multivariate analysis: Relationship of each assessmentscales and lifestyle habits with stroke (N371)

Variable OR 95% CI p Value

H&R

50 0.73 (0.39 to 1.37) 0.33

SF-12 physical

#50 1

>50 0.66 (0.33 to 1.30) 0.23

Gender

Male 9.33 (4.53 to 19.22) 2 times/day 2.63 (1.30 to 5.31) 0.007

Smoker category

Never smoked 1

Current smoker 2.08 (1.01 to 4.27) 0.05

Ex-smoker 2.35 (1.07 to 5.12) 0.03

Alteration in cardiac rhythm

No

Yes 3.18 (1.19 to 8.51) 0.02

Epworth

0e9

9e24 2.83 (1.03 to 7.78) 0.04

ERCTA, Recall Scale of Type A Behaviour; GHQ, general health questionnaire; H&R,Holmes and Rahe.

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doi: 10.1136/jnnp-2012-302420published online August 27, 2012J Neurol Neurosurg Psychiatry

Jose Antonio Egido, Olga Castillo, Beatriz Roig, et al.stroke? A case-control studyIs psycho-physical stress a risk factor for

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