Identifying Sex-Specific Differences in Young-Onset Metabolic Syndrome Using Primary Care Electronic Medical Record.

Objectives: To apply a case definition to a Northern Alberta-based primary care practice population and to assess the sex-specific characteristics of young-onset metabolic syndrome (MetS). Design: We carried out a cross-sectional study to identify and estimate the prevalence of MetS using electronic medical record (EMR) data and perform descriptive comparative analyses of demographic and clinical characteristics between males and females. Setting: Northern Alberta Primary Care Research Network (NAPCReN) consists of EMR patient data from 77 physicians among 18 clinics. Participants: Patients with one or more clinic visit between 2015 and 2018, between 18 and 40 years old, residing in Northern Alberta. Main Outcome Measures: Comparison of prevalence in MetS between sexes as well as sex-specific distribution of MetS characteristics [body mass index (BMI), fasting blood glucose, glycated hemoglobin, triglycerides, and high-density lipoprotein cholesterol (HDL-C), presence of hypertension, and presence of diabetes]. Results: Of 15,766 patients, 4.4% (n = 700) had young-onset MetS based on recorded data, prevalence was nearly twice as high in males (6.1%, n = 354) compared with females (3.5%, n = 346). The most prevalent risk factor for MetS consisted of having an elevated BMI for both females (90.9%) and males (91.5%). In the presence of MetS, more females had lower HDL-C [68.2% females (F) vs. 52.5% males (M)], and higher prevalence of diabetes (21.4% F vs. 9.0% M), whereas more males had hypertriglyceridemia (60.4% F vs. 79.7% M) and hypertension (12.4% F vs. 15.8% M). Females also had consistently higher percentages of absent laboratory data compared with males when identified as having MetS and BMI ≥25 kg/m2. Conclusions: Males have nearly twice the prevalence of young-onset MetS compared with females, with notable sex-specific differences in the manifestation of MetS, although we suspect that this is partially due to underreporting where the absence of anthropomorphic and laboratory investigations point to a lack of testing. Sex-specific screening for MetS, especially among young females of childbearing years, is important for downstream prevention.

Feasibility of identifying and describing the burden of early-onset metabolic syndrome in primary care electronic medical record data: a cross-sectional analysis.

BACKGROUND: The prevalence of metabolic syndrome is growing worldwide, yet remains underinvestigated in Canadian young adults. We sought to explore the use of a harmonized case definition specific to early-onset metabolic syndrome and determine its feasibility in assessing the prevalence of metabolic syndrome among electronic medical record (EMR) data of young adults in Northern Alberta. METHODS: We conducted a cross-sectional study using a sample of EMR data from young adult patients aged 18-40 years and residing in Northern Alberta, who had an encounter with a participating primary care clinic between June 29, 2015, and June 29, 2018. Physical examination, laboratory investigation and disease diagnosis data were collected. A case definition and algorithm were developed to assess the feasibility of identifying metabolic syndrome, including measures for body mass index (BMI), blood pressure (BP), dysglycemia, hypertriglyceridemia, high-density lipoprotein cholesterol, diabetes and hypertension. RESULTS: Among 15 766 young adults, the case definition suggested the prevalence of metabolic syndrome was 4.4%, 95% confidence interval (CI) 4.1%-4.7%. The most frequent 3-factor combination (41.6%, 95% CI 37.9%-45.3%) of metabolic syndrome criteria consisted of being overweight or obese, having elevated BP and hypertriglyceridemia. Half of metabolic syndrome cases (51.3%, 95% CI 47.6%-55.0%) were missing measures for fasting blood glucose, and one-fifth were missing a hemoglobin A1c (HbA1c) level. Notably, most young adults with a BMI of 25 or greater were missing HbA1c (68.7%, 95% CI 67.6%-69.8%), fasting blood glucose (84.0%, 95% CI 83.2%-84.8%) and triglyceride testing (79.0%, 95% CI 78.1%-79.9%). INTERPRETATION: We have shown that our case definition is feasible in identifying early-onset metabolic syndrome using EMR data; however, the degree of missing data limits the feasibility in assessing prevalence. Further investigation is required to validate this case definition for metabolic syndrome in the EMR data, which may involve comparing this definition to other validated metabolic syndrome case definitions.