03582nas a2200625   4500000000100000008004100001653001000042653001100052653001100063653000900074653000900083653001500092653002200107653001600129653001700145653002000162653001700182653001600199653002000215653002800235653004200263653002400305653003300329653002600362653002000388653001600408653003200424653002700456653002400483653001500507653005100522653002800573653003600601653001900637653002800656653002300684653003500707653002300742100001800765700001800783700001300801700001800814700001800832700001800850700001600868700001900884700001600903700001900919700001500938245010300953300001201056490000801068520186601076022001402942       2017                            d10aAdult10aFemale10aHumans10aAged10aMale10aOdds Ratio10aTreatment Outcome10aMiddle Aged10aRisk Factors10aRisk Assessment10aTime Factors10aAge Factors10aNew South Wales10aCardiovascular Diseases10aRandomized Controlled Trials as Topic10aGuideline Adherence10aPractice Guidelines as Topic10aMultivariate Analysis10aLogistic Models10aSex Factors10aDecision Support Techniques10aHealthcare Disparities10aPrimary Health Care10aQueensland10aHydroxymethylglutaryl-CoA Reductase Inhibitors10aAntihypertensive Agents10aPlatelet Aggregation Inhibitors10aAnticoagulants10aChi-Square Distribution10aDrug Prescriptions10aPractice Patterns, Physicians'10aPrimary Prevention1 aWoodward Mark1 aPatel Anushka1 aD Peiris1 aRedfern Julie1 aUsherwood Tim1 aBrieger David1 aHyun Karice1 aSullivan David1 aHarris Mark1 aLyford Marilyn1 aMacmahon S00aGender inequalities in cardiovascular risk factor assessment and management in primary healthcare.  a492-4980 v1033 a<p>
<b>OBJECTIVES: </b>To quantify contemporary differences in cardiovascular disease (CVD) risk factor assessment and management between women and men in Australian primary healthcare services.
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<b>METHODS: </b>Records of routinely attending patients were sampled from 60 Australian primary healthcare services in 2012 for the Treatment of Cardiovascular Risk using Electronic Decision Support study. Multivariable logistic regression models were used to compare the rate of CVD risk factor assessment and recommended medication prescriptions, by gender.
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<b>RESULTS: </b>Of 53 085 patients, 58% were female. Adjusting for demographic and clinical characteristics, women were less likely to have sufficient risk factors measured for CVD risk assessment (OR (95% CI): 0.88 (0.81 to 0.96)). Among 13 294 patients (47% women) in the CVD/high CVD risk subgroup, the adjusted odds of prescription of guideline-recommended medications were greater for women than men: 1.12 (1.01 to 1.23). However, there was heterogeneity by age (p &lt;0.001), women in the CVD/high CVD risk subgroup aged 35-54 years were less likely to be prescribed the medications (0.63 (0.52 to 0.77)), and women in the CVD/high CVD risk subgroup aged ≥65 years were more likely to be prescribed the medications (1.34 (1.17 to 1.54)) than their male counterparts.
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<b>CONCLUSIONS: </b>Women attending primary healthcare services in Australia were less likely than men to have risk factors measured and recorded such that absolute CVD risk can be assessed. For those with, or at high risk of, CVD, the prescription of appropriate preventive medications was more frequent in older women, but less frequent in younger women, compared with their male counterparts.
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<b>TRIAL REGISTRATION NUMBER: </b>12611000478910, Pre-results.
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  a1468-201X