Background: Understanding how bone (BM), lean (LM) and fat mass (FM) develop through childhood, puberty and adolescence is vital since it holds key information regarding current and future health. Our study aimed to determine how BM, LM and FM track from prepuberty to early adulthood in girls and what factors are associated with intra-and inter-individual variation in these three tissues.

SUMMARYThis cross-sectional study aimed to investigate whether body fat distribution, physical activity levels and dietary intakes are associated with insomnia and/or obstructive sleep apnea among overweight middleaged men. Participants were 211 Finnish men aged 30-65 years. Among the 163 overweight or obese participants, 40 had insomnia only, 23 had obstructive sleep apnea only, 24 had comorbid insomnia and obstructive sleep apnea and 76 were without sleep disorder. The remaining 48 participants had normal weight without sleep disorder. Fat mass, levels of physical activity and diet were assessed by dual-energy X-ray densitometry, physical activity questionnaire and 3-day food diary, respectively. Among the overweight participants, we found that: (i) groups with sleep disorders had higher fat mass in trunk and android regions than the group without sleep disorder (P = 0.048-0.004); (ii) the insomnia-only group showed a lower level of leisure-time physical activity (436.9 versus 986.5 MET min week À1 , P = 0.009) and higher intake of saturated fatty acids (14.8 versus 12.7 E%, P = 0.011) than the group without sleep disorder; and (iii) the comorbid group had a lower level of leisure-time physical activity (344.4 versus 986.5 MET min week À1 , P = 0.007) and lower folate intake (118.9 versus 152.1 lg, P = 0.002) than the group without sleep disorder, which were independent of body mass index. The results suggest that central obesity is associated with insomnia and/or obstructive sleep apnea. In addition, low levels of leisure-time physical activity and poor dietary intakes are related to insomnia or comorbid insomnia and obstructive sleep apnea among overweight men. IN TROD UCTI ONSleep disorders such as insomnia and obstructive sleep apnea (OSA) have become a significant health issue worldwide. The prevalence of insomnia has been estimated as 6-7% among the US and European populations (Ohayon, 2002;Wittchen et al., 2011), while more than 30% of the population may suffer at least one symptom related to insomnia (Ohayon, 2002). In Finland, the prevalence of diagnosed insomnia is 11.7%, which is 1.5-2 times higher than other European countries (Ohayon and Partinen, 2002). OSA is another sleep disorder with increasing prevalence, which affects 3-17% American adults in different age and gender groups, and is most observed commonly among men from middle to old age (Peppard et al., 2013). The prevalence of OSA is approximately 8% among Finnish population (Kronholm et al., 2009). Insomnia and OSA also often exist as comorbidity (Luyster et al., 2010).An increasing number of studies have shown the association between obesity and sleep disorders. One study Sleep and body fat suggests that obese individuals are 50% more likely to suffer insomnia than participants of normal weight, thus obesity is regarded as a risk factor for insomnia (Singareddy et al., 2012). The association between obesity and OSA is more widely recognized (Punjabi, 2008). More than two-thirds of individuals with OSA are obese (Punjabi, 2008;Vgontzas et...

ObjectiveTo identify serum biomarkers through metabolomics approach that distinguishes physically inactive overweight/obese women with metabolic syndrome from those who are metabolically healthy, independent of body weight and fat mass.MethodsWe applied nuclear magnetic resonance spectroscopy-based profiling of fasting serum samples to examine the metabolic differences between 78 previously physically inactive, body weight and fat mass matched overweight/obese premenopausal women with and without MetS. MetS was defined as the presence of at least three of the following five criteria: waist circumference ≥88 cm, serum triacylglycerol ≥1.7 mmol/L, and high density lipoprotein cholesterol (HDL-C) <1.30 mmol/L, blood pressure ≥ 130/85 mmHg and fasting glucose ≥5.6 mmol/L). Principal component analysis was used to reduce the large number of correlated variables to fewer uncorrelated factors.ResultsTwo metabolic factors were associated with MetS independent of BMI, fat mass, waist circumference and physical activity/fitness. Factor comprising branched-chain amino acids (BCAA) and aromatic amino acids (AAA) and orosomucoid was associated with all clinical risk factors (p < 0.01 for all).ConclusionTwo metabolic factors distinguish overweight/obese women with metabolic syndrome from those who are metabolically healthy independent of body weight, fat mass and physical activity/fitness. In particular, factor comprising BCAA, AAA and orosomucoid seems auspicious biomarker determining metabolic health as it was associated with all clinical risk factors. Further research is needed to determine the public health and clinical significance of these results in terms of screening to identify those at greatest cardio-metabolic risk for whom appropriate intervention strategies should be developed.

The aim of this study was to investigate whether overweight/obese women in metabolic disorder group (MDG, n = 27) differ in their gut microbiota composition from overweight/obese women in non‐metabolic disorder group (NMDG, n = 47) and normal weight women group (NWG, n = 11). Gut microbiota was profiled from fecal samples by 16S rRNA fluorescence in situ hybridization and flow cytometry in 85 premenopausal women. Body composition was measured by bioimpedance, and dietary intakes were collected via food diaries. Standard procedures were used to assess plasma glucose, serum insulin, lipids, and inflammatory status. We found that the proportion of bacteria belonging to Eubacterium rectale‐Clostridium coccoides group, indicating efficient energy harvest from nutrients in gut, was higher in MDG compared to NMDG and NWG, while no difference was found between NMDG and NWG. The proportion of Eubacterium rectale‐Clostridium coccoides group correlated positively with weight, BMI, total fat, fat mass percentage (FM%), visceral fat area, and serum triglycerides, and negatively with high‐density lipoprotein (HDL). Our results indicate that certain members of Eubacterium rectale‐Clostridium coccoides group are associated with obesity‐related MDs not obesity per se.

Objective: To investigate the long-term effects of duration of postpartum lactation on maternal body composition and risk for cardio-metabolic disorders in later life. Design: Retrospective study. Body composition was measured using dual-energy X-ray absorptiometry and serum glucose, insulin and lipids were analysed using enzymatic photometric methods 16-20 years after the last pregnancy. Medical history and lifestyle factors were collected via a self-administered questionnaire. Detailed information regarding weight change patterns during each pregnancy was obtained from personal maternity tracking records. Setting: City of Jyväskylä and surroundings in Central Finland. Subjects: Two hundred and twelve women (mean age 48, range 36-60 years). Results: At 16-20 years after their last pregnancy, women who had breast-fed for less than 6 months had higher total body fat mass and fat mass percentage, particularly in the android region (46?5 (SD 8?2) %) than mothers who had breast-fed for longer than 6 months (39?0 (SD 10?2) %) or for longer than 10 months (38?4 (SD 10?9) %, P , 0?01). These differences were independent of pre-pregnancy weight and BMI, menopausal status, smoking status, level of education, participation in past and present leisure-time physical activity, and current dietary energy intake. Higher body fat mass was also associated with higher fasting serum glucose concentration and insulin resistance, TAG, LDL cholesterol and total cholesterol concentrations, as well as higher systolic and diastolic blood pressure (P , 0?05 for all). Conclusions: Short duration of breast-feeding may induce weight retention and fat mass accumulation, resulting in increased risk of cardio-metabolic disorders in later life.

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Objective We explored the relationship between urinary incontinence (UI) and depression or anxiety. Methods We searched the Cochrane Library, Embase, and PubMed for articles on the association between depression, anxiety, and UI. We calculated pooled 95% confidence intervals (CIs) and odds ratios (ORs). Results Twelve articles (31,462 participants) were included. The UI group had significantly higher depression and anxiety levels than the non-UI group (OR = 1.73, 95%CI: 1.64–1.82, I2 = 75.5%). In subgroup analysis, depression and anxiety were significantly higher in participants with UI than in those without UI (OR = 1.95, 95%CI: 1.82–2.10, I2 = 64.3% and OR = 1.54, 95%CI: 1.43–1.65, I2 = 59.2%, respectively).  In subgroup analysis by age, participants with UI had significantly higher depression and anxiety, regardless of age, than the non-UI group (OR = 1.59, 95%CI: 1.29–1.95, I2 = 59.1% and OR = 1.98, 95%CI: 1.62–2.43, I2 = 75.5%, respectively). Conclusion Patients with UI had significantly higher depression and anxiety levels than those without UI. Depression and anxiety were higher in patients with UI than in those without UI, regardless of age. Larger sample sizes and more high-quality studies are needed to validate our findings.

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