How are we diagnosing cardiometabolic risk in primary care settings?
OBJECTIVE
To assess attitudes, barriers and practices of clinicians in assessing and treating cardiometabolic risk in overweight adults.


METHODS
In 2006, primary care physicians and mid-level practitioners in Montana were surveyed (N=430).


RESULTS
Most primary care clinicians (95%) recognized the clinical benefit of weight loss, but many cited patient motivation (87%), lack of support services (61%), and lack of time (58%) as barriers. Over 80% identified obesity, hypertension, abnormal lipids, history of gestational diabetes, and family history as indications for diabetes screening. Most clinicians used fasting glucose (89%), random glucose (58%), and A1c (42%) as initial screens for diabetes. To confirm the diagnosis, the majority of respondents used A1c testing (80%) or fasting glucose (64%). Approximately one-quarter used the diagnosis pre-diabetes (26%), but just over half (52%) used alternative diagnoses of glucose intolerance. Sixty-five percent used the diagnosis of metabolic syndrome. Of those using metabolic syndrome, mid-level practitioners were more likely than physicians to assess waist circumference (49% vs. 63%).


CONCLUSIONS
Despite citing significant barriers, clinicians routinely assessed cardiometabolic risk with diabetes screening, but relatively few reported using the diagnosis pre-diabetes. Metabolic syndrome was used commonly to diagnose overweight adults at risk for diabetes and cardiovascular disease.
Gohdes
Dorothy
D
Asthma, Cardiovascular Health, and Diabetes Section, Chronic Disease Prevention and Health Promotion Bureau, Montana Department of Public Health and Human Services, Helena, MT 59620-2951, USA.
Amundson
Helen
H
Oser
Carrie S
CS
Helgerson
Steven D
SD
Harwell
Todd S
TS
D001291:Attitude of Health Personnel; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000191:economics / Q000209:etiology* / Q000517:prevention & control; D003376:Counseling; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis* / Q000191:economics / Q000209:etiology / Q000628:therapy; D005260:Female; D005951:Glucose Tolerance Test; D006442:Glycated Hemoglobin / Q000378:metabolism; D019538:Health Care Surveys; D007722:Health Knowledge, Attitudes, Practice; D006297:Health Services Accessibility; D006801:Humans; D007349:Insurance, Health, Reimbursement; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis* / Q000191:economics / Q000209:etiology / Q000628:therapy; D008875:Middle Aged; D009009:Montana; D009042:Motivation; D050177:Overweight / Q000150:complications* / Q000191:economics / Q000628:therapy; D010342:Patient Acceptance of Health Care; D010818:Practice Patterns, Physicians'; D011236:Prediabetic State / Q000175:diagnosis* / Q000191:economics / Q000209:etiology / Q000628:therapy; D011237:Predictive Value of Tests; D011320:Primary Health Care / Q000191:economics; D018570:Risk Assessment; D012307:Risk Factors; D011795:Surveys and Questionnaires; D055105:Waist Circumference
D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human