To identify sociodemographic and metabolic correlates of weight categories in postmenopausal women.

Methods

The Women's Health Initiative enrolled 161 808 postmenopausal women ages 50-79. We included those free of cardiovascular disease (CVD) and with CVD risk factors and biomarkers (n = 19 412). Normal weight was defined as a BMI ≥18.5 and <25 kg/m² and waist circumference <88 cm and overweight/obesity as a BMI ≥25 kg/m² or waist circumference ≥88 cm. Metabolically healthy was based on <2 and metabolically unhealthy ≥2 traits: triglycerides ≥150 mg/dl, systolic blood pressure (BP) ≥130 mmHg or diastolic BP ≥85 mmHg or antihypertensives or diuretics, fasting glucose ≥100 mg/dl or diabetes medication, and high-density lipoprotein cholesterol <50 mg/dl. Polytomous multinomial logistic regression with generalized link logit function provided the odds of metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUHNW), metabolically healthy overweight/obese (MHO), and metabolically unhealthy overweight/obese (MUHO) according to demographic and risk factor measures.

Results

Among the 19 412 postmenopausal women, 2369 (12.2%) participants had prevalent diabetes. Advanced age was associated with an increased odds of MUHNW as compared with the MHNW after adjusting for covariates [odds ratio (OR) 1.04, P < 0.0001]. Black/African American ethnicity was associated with a decreased odds of MUHNW (OR 0.64, P < 0.0001) and MUHO (OR 0.77, P = 0.0004), while an increased odds for MHO (OR 1.50, P < 0.0001) as compared with White MHNW.

Conclusions

Advanced age and ethnicity are important indicators of metabolic weight categories among postmenopausal women.

OBJECTIVE: To determine the relationship of metabolic weight categories with incident diabetes mellitus (DM) in postmenopausal women. METHODS: The Womens Health Initiative (WHI) enrolled 161,808 postmenopausal women aged 50 to 79 years. We included those with cardiovascular disease (CVD) biomarkers and free of CVD and prevalent DM (n = 17,043) at baseline. Normal weight was defined as a body mass index (BMI) ≥18.5 and <25 kg/m, and waist circumference (WC) <88 cm and overweight/obesity as a BMI ≥25 kg/m or WC ≥88 cm. Metabolically healthy was based on <2 and metabolically unhealthy ≥2 traits of the following: triglycerides ≥150 mg/dL, systolic blood pressure (BP) ≥130 mm Hg or diastolic BP ≥85 mm Hg, or antihypertensives or diuretics, fasting glucose ≥100 mg/dL or DM medication, and high-density lipoprotein cholesterol <50 mg/dL. Cox regression was performed to determine the risk of incident DM among metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUHNW), metabolically healthy overweight/obese (MHO), and metabolically unhealthy overweight/obese (MUHO). RESULTS: Among our sample, 2,253 (13.3%) participants developed DM over a mean ± standard deviation follow-up time of 15.6 ± 3.4 years. Compared with MHNW (n = 162 incident DM cases), an increased risk of incident DM was observed in MUHNW (n = 102 cases) (hazard ratio [HR] 2.24, 95% confidence interval [CI] 1.74-2.88, P < 0.0001), MHO (n = 624 cases) (HR 1.68, 95% CI 1.40-2.00, P < 0.0001), and MUHO (n = 1,365 cases) (HR 4.51, 95% CI 3.82-5.35, P < 0.0001). CONCLUSIONS: Among postmenopausal women, MUHNW and MHO confer an approximate doubling in the risk and MUHO more than a four-fold increased risk for developing DM.

Many studies have reported that heavy substance use is associated with impaired response inhibition. Studies typically focused on associations with a single substance, while polysubstance use is common. Further, most studies compared heavy users with light/non-users, though substance use occurs along a continuum. The current mega-analysis accounted for these issues by aggregating individual data from 43 studies (3610 adult participants) that used the Go/No-Go (GNG) or Stop-signal task (SST) to assess inhibition among mostly "recreational" substance users (i.e., the rate of substance use disorders was low). Main and interaction effects of substance use, demographics, and task-characteristics were entered in a linear mixed model. Contrary to many studies and reviews in the field, we found that only lifetime cannabis use was associated with impaired response inhibition in the SST. An interaction effect was also observed: the relationship between tobacco use and response inhibition (in the SST) differed between cannabis users and non-users, with a negative association between tobacco use and inhibition in the cannabis non-users. In addition, participants' age, education level, and some task characteristics influenced inhibition outcomes. Overall, we found limited support for impaired inhibition among substance users when controlling for demographics and task-characteristics.