Interviews are reported in which heterosexual women construct unmarried status as a temporary stage, preparatory to marriage, or the consequence of failure to maintain heterosexual relationships. Remaining single in later life is constructed as a threat, and older single women are constructed as lonely and isolated. Women construct themselves as responsible for the ending of past relationships, and report having been held to account in this way by significant others. It is argued that these accounts reflect the discourses of heterosexual romantic quest, and the gendered division of emotional labour in marriage. Participants' accounts are characterized by heterosexism and ageism, and the authors discuss issues of collusion with these in the collection of data.
Social support appears to be a key factor mediating the psychosocial impact in women with polycystic ovary syndrome. Healthcare providers should consider running such support groups or referring patients to them. Providing social support may alleviate distress and improve self-management.
Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, P interaction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; P interaction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, P interaction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; P interaction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.
We examined the effects of metformin on diabetes prevention and the subgroups that benefited most over 15 years in the Diabetes Prevention Program (DPP) and its follow-up, the Diabetes Prevention Program Outcomes Study (DPPOS). RESEARCH DESIGN AND METHODS During the DPP (1996-2001), adults at high risk of developing diabetes were randomly assigned to masked placebo (n = 1,082) or metformin 850 mg twice daily (n = 1,073). Participants originally assigned to metformin continued to receive metformin, unmasked, in the DPPOS (2002-present). Ascertainment of diabetes development was based on fasting or 2-h glucose levels after an oral glucose tolerance test or on HbA 1c. Reduction in diabetes incidence with metformin was compared with placebo in subgroups by hazard ratio (HR) and rate differences (RDs). RESULTS During 15 years of postrandomization follow-up, metformin reduced the incidence (by HR) of diabetes compared to placebo by 17% or 36% based on glucose or HbA 1c levels, respectively. Metformin's effect on the development of glucose-defined diabetes was greater for women with a history of prior gestational diabetes mellitus (GDM) (HR 0.59, RD 24.57 cases/100 person-years) compared with parous women without GDM (HR 0.94, RD 20.38 cases/100 person-years [interaction P = 0.03 for HR, P = 0.01 for RD]). Metformin also had greater effects, by HR and RD, at higher baseline fasting glucose levels. With diabetes development based on HbA 1c , metformin was more effective in subjects with higher baseline HbA 1c by RD, with metformin RD 21.03 cases/100 person-years with baseline HbA 1c <6.0% (42 mmol/mol) and 23.88 cases/100 person-years with 6.0-6.4% (P = 0.0001). CONCLUSIONS Metformin reduces the development of diabetes over 15 years. The subsets that benefitted the most include subjects with higher baseline fasting glucose or HbA 1c and women with a history of GDM.
Across the Diabetes Prevention Program (DPP) follow-up, cumulative diabetes incidence remained lower in the lifestyle compared with the placebo and metformin randomized groups and could not be explained by weight. Collection of self-reported physical activity (PA) (yearly) with cross-sectional objective PA (in follow-up) allowed for examination of PA and its long-term impact on diabetes prevention. RESEARCH DESIGN AND METHODS Yearly self-reported PA and diabetes assessment and oral glucose tolerance test results (fasting glucose semiannually) were collected for 3,232 participants with one accelerometry assessment 11-13 years after randomization (n 5 1,793). Mixed models determined PA differences across treatment groups. The association between PA and diabetes incidence was examined using Cox proportional hazards models. RESULTS There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight). The effect of PA was greater (12% decrease) among participants less active at baseline (<7.5 MET-h/week) (n 5 1,338) (0.88 [0.83, 0.93]; P < 0.0001), with stronger findings for lifestyle participants. Lifestyle had higher cumulative PA compared with metformin or placebo (P < 0.0001) and higher accelerometry total minutes per day measured during follow-up (P 5 0.001 and 0.047). All associations remained significant with the addition of weight in the models. CONCLUSIONS PA was inversely related to incident diabetes in the entire cohort across the study, with cross-sectional accelerometry results supporting these findings. This highlights the importance of PA within lifestyle intervention efforts designed to prevent diabetes and urges health care providers to consider both PA and weight when counseling high-risk patients.
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