Factors Influencing Sex Differences in Poststroke Functional Outcome
Background and Purpose—Our objective was to identify factors that contribute to or modify the sex difference in poststroke functional outcome.
Methods—Ischemic strokes (n=439) were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) Project (2008–2011). Data were ascertained from interviews (baseline and 90 days post stroke) and medical records. Functional outcome was measured as an average of 22 activities of daily living (ADL)/instrumental ADL items (range, 1–4; higher scores worse function). Tobit regression was used to estimate sex differences and to identify confounding and modifying factors.
Results—Fifty-one percent were women. Median age was 71 (interquartile range, 59–80) years in women and 64 (interquartile range, 56–77) years in men. Median ADL/instrumental ADL score at 90 days was 2.7 (interquartile range, 1.8–3.6) in women and 2.0 (interquartile range, 1.3–3.1) in men (P<0.01); this difference remained after age-adjustment (P<0.001). Factors contributing to higher ADL/instrumental ADL scores in women included prestroke function, marital status, prestroke cognition, nursing home residence, stroke severity, history of stroke/transient ischemic attack, and body mass index; prestroke function was the largest contributor. Stroke severity modified the sex difference in outcome such that differences were apparent for mild to moderate but not severe strokes. After adjustment, women still had significantly worse functional outcome than men.
Conclusions—These findings yield insight into possible strategies and subgroups to target to reduce the sex disparity in stroke outcome; demographics and prestroke and clinical factors explained only 41% of the sex difference in stroke outcome highlighting the need for future research to identify modifiable factors that contribute to sex differences.
Causes of poorer functional outcomes after stroke in women than in men are unknown.1 Previous studies have simultaneously included all potential explanatory variables in multivariable models to measure adjusted sex differences in stroke outcome, precluding an understanding of which specific factors contribute to worse outcomes in women. This is crucially important because it is the identification of specific factors that could lead to interventions to reduce sex disparities in stroke outcomes. Furthermore, studies have not considered whether certain factors modify sex differences in functional outcome, which could identify subgroups that might be targeted to reduce sex disparities. Our objective was to identify specific factors that contribute to or modify sex differences in poststroke 90-day functional outcome.
Data were from the BASIC Project (2008–2011), a population-based stroke surveillance study.2 Stroke cases participated in baseline (≈47% conducted during hospitalization) and outcome interviews (≈90 days after stroke). Patients unable to answer orientation questions had a proxy interview. Data were collected from baseline interviews (demographics, prestroke modified Rankin Scale, prestroke cognitive status [Informant Questionnaire on Cognitive Decline in the Elderly]) and medical records (insurance, prestroke nursing home residence, body mass index, risk factors, comorbidities, stroke severity, and quality of care). First documented National Institutes of Health Stroke Scale was abstracted or calculated using previously validated methods.3 A prestroke comorbidity index was created by summing risk factors and comorbidities (range, 0–15). To measure quality of care, we created a binary defect-free score, which indicated a patient received all stroke performance measures (n=6) he/she was eligible to receive. Functional outcome was assessed as the average of 7 activities of daily living (ADL) and 15 instrumental ADL living (IADL); ADL/IADL score ranged from 1 (no difficulty) to 4 (can only do with help).
Tobit regression was used to assess the association between sex and ADL/IADL. We first generated a model that included sex and age. Each potential confounder was then added to this model and the estimated sex effects before and after inclusion of the variable were compared. If the sex coefficient changed by ≥5%, the variable was considered a confounder. The final model included sex, age, race-ethnicity, and confounders. Age and body mass index were modeled linearly; initial National Institutes of Health Stroke Scale required a quadratic term. We investigated interactions between sex and all other variables and included them in the final model if significant (P<0.10). We conducted 3 sensitivity analyses: (1) we included a variable for proxy use in our final model; (2) we reran the final model considering ADL and IADL subscales as separate outcomes; (3) we considered the effect of loss to follow-up by modeling the probability of missing outcome as dependent on the outcome itself.
All patients or their surrogate provided written informed consent, and the study was approved by the Institutional Review Boards at the University of Michigan and local hospitals.
A total of 644 of 913 patients with ischemic strokes (71%) agreed to an interview. There was no sex difference in age-adjusted 90-day mortality (P=0.50). After excluding deaths, 439 of 552 eligible patients (80%) completed the 90-day interview, with no sex difference in loss to follow-up (P=0.80). A total of 399 (91%) had complete data. Women were more likely than men to have a proxy at baseline (P=0.001) and outcome (P=0.029). The Table includes sex differences in select baseline characteristics. Median ADL/IADL score at 90 days was 2.7 (interquartile range, 1.8–3.6) in women and 2.0 (interquartile range, 1.3–3.1) in men (Table I in the online-only Data Supplement). After age-adjustment, women scored 0.40 points higher than men scored on the ADL/IADL score (95% confidence interval, 0.19–0.61). Prestroke modified Rankin Scale, prestroke nursing home residence, history of stroke/transient ischemic attack, stroke severity, marital status, body mass index, and prestroke Informant Questionnaire on Cognitive Decline in the Elderly contributed to poorer functional outcome in women (Figure). Demographics and confounders explained ≈41% of the sex effect (Table II in the online-only Data Supplement). An interaction between sex and initial National Institutes of Health Stroke Scale was found (P=0.061; Figure I in the online-only Data Supplement); women scored 0.40 points higher on the ADL/IADL score than men (95% confidence interval, 0.18–0.63) at the mean National Institutes of Health Stroke Scale (6). No other interactions were noted. Sensitivity analyses suggested minimal effect of proxy use and loss to follow-up (Figure II in the online-only Data Supplement), and that sex differences were more pronounced for IADLs than for ADLs (data not shown).
Women had significantly worse functional outcomes than men even after adjustment; but the most important factor attenuating the difference was prestroke function. Prevention efforts aimed at maintaining functional status in aging women could improve their stroke outcomes. Pre-existing functional limitations may also impact effectiveness of poststroke rehabilitation,4 further substantiating the importance of maintaining physical well-being in elderly women.
Other factors that contributed to worse functional outcome in women included marital status, nursing home residence, prestroke Informant Questionnaire on Cognitive Decline in the Elderly, history of stroke/transient ischemic attack, body mass index, and stroke severity, most of which are not amenable to intervention at stroke onset. Women were more likely to be widowed, which was associated with poorer outcome; the negative effect of being widowed could be because of increased social isolation, a risk factor for poor poststroke functional outcome.5 The detrimental effects of social isolation could be amenable to intervention; however, interventions focused on increasing social support in patients with stroke have largely been unsuccessful.6,7 Newer technologies, including social media, may provide a means of reaching socially isolated women with stroke but this requires additional research.8
Stroke severity modified the sex difference in functional outcome. The finding of no sex difference among those with severe strokes is intuitive because presumably severe stroke will result in poor outcome regardless of other factors. Causes of the sex difference in outcome in mild to moderately severe stroke population are unclear, but given adjustment for demographics, prestroke, and clinical factors explained only 41% of the sex difference in outcome, poststroke factors, such as rehabilitation and depression, may be relevant and prove to be important intervention targets for reducing stroke disability in women.
There are limitations to this work. Differential reporting by sex may exist for some ADL/IADLs although we used a composite measure that should minimize this effect. Prestroke factors were ascertained after stroke, which could lead to measurement error. We did not have data on stroke subtype although we accounted for severity such that differences in severity by subtype were captured. Our results are model dependent. The study is focused on one predominantly Mexican American community in south Texas. Thus, results may not be generalizable.
These findings yield insight into possible strategies and subgroups to target to reduce the sex disparity in stroke outcome; because demographics and prestroke and clinical factors explained less than half of the sex disparity, it highlights the need for future research to identify modifiable factors that contribute to sex differences in stroke outcome.
Sources of Funding
This study was funded by National Institutes of Health R01NS38916.
Drs Lisabeth and Morgenstern are funded by National Institutes of Health R01NS38916. The other authors report no conflicts.
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.114.007985/-/DC1.
- Received October 31, 2014.
- Revision received October 31, 2014.
- Accepted November 20, 2014.
- © 2015 American Heart Association, Inc.
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