Objective: To determine whether subgroups of patients with MDD stratified according to the A/W criterion had a different degree of genetic overlap with obesity-related traits (body mass index [BMI] and levels of C-reactive protein [CRP] and leptin).

Design, Setting, and Patients: This multicenter study assembled genome-wide genotypic and phenotypic measures from 14 data sets of the Psychiatric Genomics Consortium. Data sets were drawn from case-control, cohort, and population-based studies, including 26 628 participants with established psychiatric diagnoses and genome-wide genotype data. Data on BMI were available for 15 237 participants. Data were retrieved and analyzed from September 28, 2015, through May 20, 2017.

Main Outcomes and Measures: Lifetime DSM-IV MDD was diagnosed using structured diagnostic instruments. Patients with MDD were stratified into subgroups according to change in the DSM-IV A/W symptoms as decreased or increased.

Results: Data included 11 837 participants with MDD and 14 791 control individuals, for a total of 26 628 participants (59.1% female and 40.9% male). Among participants with MDD, 5347 (45.2%) were classified in the decreased A/W and 1871 (15.8%) in the increased A/W subgroups. Common genetic variants explained approximately 10% of the heritability in the 2 subgroups. The increased A/W subgroup showed a strong and positive genetic correlation (SE) with BMI (0.53 [0.15]; P = 6.3 × 10-4), whereas the decreased A/W subgroup showed an inverse correlation (-0.28 [0.14]; P = .06). Furthermore, the decreased A/W subgroup had a higher polygenic risk for increased BMI (odds ratio [OR], 1.18; 95% CI, 1.12-1.25; P = 1.6 × 10-10) and levels of CRP (OR, 1.08; 95% CI, 1.02-1.13; P = 7.3 × 10-3) and leptin (OR, 1.09; 95% CI, 1.06-1.12; P = 1.7 × 10-3).

DESIGN: Prospective cohort study.

SETTING: England, Wales and Scotland.

PARTICIPANTS: 17 781 postmenopausal women from the UK Women's Cohort Study.

PRIMARY OUTCOME MEASURE: Incident cases of malignant breast cancers (International Classification of Diseases (ICD) 9 code 174 and ICD 10 code C50).

RESULTS: From 282 277 person-years follow-up, there were 946 incident breast cancer cases with an incidence rate of 3.35 per 1000 women. Body mass index (HR: 1.04; 95% CI: 1.02 to 1.07), blouse size (HR: 1.10; 1.03 to 1.18), waist circumference (HR: 1.07; 1.01 to 1.14) and skirt size (HR: 1.14;1.06 to 1.22) had positive associations with postmenopausal breast cancer after adjustment for potential confounders. Increased weight over adulthood (HR: 1.02; 1.01 to 1.03) was also associated with increased risk for postmenopausal breast cancer.

METHODS: A total of 1319 Malaysian adults participated in this cross-sectional online survey. Information on anthropometric data including body weight and height, and lifestyle behaviours including eating pattern, physical activity, and sleep pattern were self-reported by the respondents. A multivariable generalised linear mixed model was used to assess the associations between lifestyle behaviours and body weight changes with adjustment of confounding factors; namely, age, sex, ethnicity, and body weight status before MCO.

RESULTS: During MCO, 41.2% of the respondents perceived that their eating patterns were healthier, but 36.3% reduced their physical activities, and 25.7% had a poorer sleep quality. Further, the proportion of adults who reported having lose weight (32.2%) was almost similar to those who reported having gained weight (30.7%). Lifestyle behaviours including less frequent practice of healthy cooking methods and lunch skipping were associated with weight gain, while less frequent consumption of high fat foods, more frequent physical activity, and good sleep latency were associated with lower risk of weight gain. In contrast, practicing healthy eating concept, skipped lunch, and more frequent physical activity were significantly associated with weight loss.

Methods: A total of 380 women who had used the same contraceptive method for at least twelve months were recruited in this study. Covariance analysis was done to compare the weight gain between hormonal and non-hormonal contraceptive users, while studying the same confounders [age, household income, number of pregnancies, and baseline body mass index (BMI)].

Results: Hormonal methods were more commonly used. The mean weight gain among hormonal users (adjusted mean 2.85, 95% CI 2.45, 3.24) was significantly higher than non-hormonal users (adjusted mean 0.46, 95% CI -0.73, 1.65; p-value <0.001), after controlling for age, household income, number of pregnancies, and baseline BMI.

METHODS: This was a prospective cohort study of 452 pregnant women recruited from 3 health clinics in a southern state of Peninsular Malaysia. PA levels at the first, second, and third trimester were assessed using the Pregnancy Physical Activity Questionnaire. GDM was diagnosed at 24-28 weeks of gestation following the Ministry of Health Malaysia criteria. Group-based trajectory modeling was used to identify PA trajectories. Three multivariate logistic models were used to estimate the odds of trajectory group membership and GDM.

RESULTS: Two distinct PA trajectories were identified: low PA levels in all intensity of PA and sedentary behavior (Group 1: 61.1%, n = 276) and high PA levels in all intensity of PA as well as sedentary behavior (Group 2: 38.9%, n = 176). Moderate and high intensity PA decreased over the course of pregnancy in both groups. Women in group 2 had significantly higher risk of GDM in two of the estimated logistic models. In all models, significant associations between PA trajectories and GDM were only observed among women with excessive gestational weight gain in the second trimester.