In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Example Input: Context: This study examines the prevalence and correlates of self-reported premenstrual symptoms among a large, population-based sample of reproductive age, active-duty women.', 'Data were obtained from a combined dataset of two large-scale mail surveys designed to represent the total force. Subjects included in the present study were 6026 active-duty women of all branches of military service stratified by service, paygrade group, race/ethnicity, and location. A multivariate approach is used to evaluate the interrelationships among psychosocial and lifestyle correlates of premenstrual symptoms or pain after controlling for demographic differences in women who reported premenstrual symptoms or pain during the past 3 months (cases) and those who did not (controls).', 'Premenstrual symptoms were reported by nearly 2 of every 3 reproductive age women. Women reporting premenstrual symptoms were more likely to report other symptoms of menstrual dysfunction, two or more current medical conditions, migraines, and healthcare provider visits in the past year. After controlling for the protective effects of taking Depo-Provera (Upjohn, Kalamazoo, MI) and ever being pregnant, younger age, trying to lose weight, heavier drinking, poorer self-perceived health, and overall job stress were the most significant predictors of premenstrual symptoms. The greatest risk factor was a high level of job stress, with an almost 3-fold increase in risk relative to those without symptoms.\Question: Does psychosocial and lifestyle correlate of premenstrual symptoms among military women?
Example Output: Work stress may mediate the relationship among depression and premenstrual symptoms. Further research is needed to elucidate the biological interrelationships among work stress, hormonal function, and premenstrual symptomatology.

Example Input: Context: To evaluate the relationship between pro-atherogenic biomarkers and epicardial adipose tissue (EAT) thickness in patients with cardiovascular risk factors.', 'Plasma nitric oxide (NO), soluble intercellular adhesion molecule-1 and malondialdehyde (MDA) levels, EAT thickness, flow-mediated dilation (FMD) and carotid intima media thickness (CIMT) were determined in patients aged >18 years who were referred for echocardiography for heart ischemia or non-ischemic diseases. Cardiovascular risk factors (Framingham score [FS]20) were weighted.', 'Hypertension, dyslipidaemia and type 2 diabetes mellitus were prevalent (55% of 40 patients). Patients with FS20 (n=21) showed significantly higher EAT and CIMT values. Globally, MDA, CIMT, age, waist circumference, high-density lipoprotein cholesterol (HDL-C) and FS were associated with EAT thickness. EAT was significantly associated with NO in patients with FS20. Significant differences in EAT thickness were found between patients stratified by NO value, FMD, age, smoking status, dyslipidaemia, type 2 diabetes mellitus and FS. An EAT-associated atherogenic risk (CIMT1mm) model was statistically significant when MDA and type 2 diabetes mellitus were included.\Question: Are pro-atherogenic mediators and subclinical atherogenesis related to epicardial adipose tissue thickness in patients with cardiovascular risk?
Example Output: EAT thickness was associated with MDA, CIMT, age, waist circumference, HDL-C and FS globally, but with NO only in patients with FS20. EAT may be used to identify vascular damage stage, possibly influenced by MDA and type 2 diabetes mellitus.

Example Input: Context: To assess disability more efficiently with less burden on the patient, the National Institutes of Health has developed the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function-an instrument based on item response theory and using computer adaptive testing (CAT). Initially, upper and lower extremity disabilities were not separated and we were curious if the PROMIS Physical Function CAT could measure upper extremity disability and the Quick Disability of Arm, Shoulder and Hand (QuickDASH).', 'We aimed to find correlation between the PROMIS Physical Function and the QuickDASH questionnaires in patients with upper extremity illness. Secondarily, we addressed whether the PROMIS Physical Function and QuickDASH correlate with the PROMIS Depression CAT and PROMIS Pain Interference CAT instruments. Finally, we assessed factors associated with QuickDASH and PROMIS Physical Function in multivariable analysis.', 'A cohort of 93 outpatients with upper extremity illnesses completed the QuickDASH and three PROMIS CAT questionnaires: Physical Function, Pain Interference, and Depression. Pain intensity was measured with an 11-point ordinal measure (0-10 numeric rating scale). Correlation between PROMIS Physical Function and the QuickDASH was assessed. Factors that correlated with the PROMIS Physical Function and QuickDASH were assessed in multivariable regression analysis after initial bivariate analysis.', 'There was a moderate correlation between the PROMIS Physical Function and the QuickDASH questionnaire (r=-0.55, p<0.001). Greater disability as measured with the PROMIS and QuickDASH correlated most strongly with PROMIS Depression (r=-0.35, p<0.001 and r=0.34, p<0.001 respectively) and Pain Interference (r=-0.51, p<0.001 and r=0.74, p<0.001 respectively). The factors accounting for the variability in PROMIS scores are comparable to those for the QuickDASH except that the PROMIS Physical Function is influenced by other pain conditions while the QuickDASH is not.\Question: Does the PROMIS physical function correlate with the QuickDASH in patients with upper extremity illness?
Example Output:
The PROMIS Physical Function instrument may be used as an upper extremity disability measure, as it correlates with the QuickDASH questionnaire, and both instruments are influenced most strongly by the degree to which pain interferes with achieving goals.