To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×10⁻¹¹) and MSRA (WC, P = 8.9×10⁻⁹). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×10⁻⁸). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity. Here, we describe a meta-analysis of genome-wide association data from 38,580 individuals, followed by large-scale replication (in up to 70,689 individuals) designed to uncover variants influencing anthropometric measures of central obesity and fat distribution, namely waist circumference (WC) and waist–hip ratio (WHR). This work complements parallel efforts that have been successful in defining variants impacting overall adiposity and focuses on the visceral fat accumulation which has particularly strong relationships to metabolic and cardiovascular disease. Our analyses have identified two loci (TFAP2B and MSRA) associated with WC, and a further locus, near LYPLAL1, which shows gender-specific relationships with WHR (all to levels of genome-wide significance). These loci vary in the strength of their associations with overall adiposity, and LYPLAL1 in particular appears to have a specific effect on patterns of fat distribution. All in all, these three loci provide novel insights into human physiology and the development of obesity.

Background: Older adults may use wearable devices for various reasons, ranging from monitoring clinically relevant health metrics or detecting falls to monitoring physical activity. Little is known about how this population engages with wearable devices, and no qualitative synthesis exists to describe their shared experiences with long-term use. Objective: This study aims to synthesize qualitative studies of user experience after a multi-day trial with a wearable device to understand user experience and the factors that contribute to the acceptance and use of wearable devices. Methods: We conducted a systematic search in CINAHL, APA PsycINFO, PubMed, and Embase (2015-2020; English) with fixed search terms relating to older adults and wearable devices. A meta-synthesis methodology was used. We extracted themes from primary studies, identified key concepts, and applied reciprocal and refutational translation techniques; findings were synthesized into third-order interpretations, and finally, a “line-of-argument” was developed. Our overall goal was theory development, higher-level abstraction, and generalizability for making this group of qualitative findings more accessible. Results: In total, we reviewed 20 papers; 2 evaluated fall detection devices, 1 tested an ankle-worn step counter, and the remaining 17 tested activity trackers. The duration of wearing ranged from 3 days to 24 months. The views of 349 participants (age: range 51-94 years) were synthesized. Four key concepts were identified and outlined: motivation for device use, user characteristics (openness to engage and functional ability), integration into daily life, and device features. Motivation for device use is intrinsic and extrinsic, encompassing many aspects of the user experience, and appears to be as, if not more, important than the actual device features. To overcome usability barriers, an older adult must be motivated by the useful purpose of the device. A device that serves its intended purpose adds value to the user’s life. The user’s needs and the support structure around the device—aspects that are often overlooked—seem to play a crucial role in long-term adoption. Our “line-of-argument” model describes how motivation, ease of use, and device purpose determine whether a device is perceived to add value to the user’s life, which subsequently predicts whether the device will be integrated into the user’s life. Conclusions: The added value of a wearable device is the resulting balance of motivators (or lack thereof), device features (and their accuracy), ease of use, device purpose, and user experience. The added value contributes to the successful integration of the device into the daily life of the user. Useful device features alone do not lead to continued use. A support structure should be placed around the user to foster motivation, encourage peer engagement, and adapt to the user’s preferences.

Article published by the Endocrine Society Article published by the Endocrine Society

Traumatic brain injury (TBI) has been associated with dementia. The questions of whether the risk of dementia decreases over time after TBI, whether it is similar for different TBI types, and whether it is influenced by familial aggregation are not well studied. The cohort considered for inclusion comprised all individuals in Sweden aged ≥50 years on December 31, 2005 (n = 3,329,360). Diagnoses of dementia and TBI were tracked through nationwide databases from 1964 until December 31, 2012. In a first cohort, individuals diagnosed with TBI (n = 164,334) were matched with up to two controls. A second cohort consisted of subjects diagnosed with dementia during follow-up (n = 136,233) matched with up to two controls. A third cohort consisted of 46,970 full sibling pairs with discordant TBI status. During a mean follow-up period of 15.3 (range, 0–49) years, 21,963 individuals in the first cohort (6.3% with TBI, 3.6% without TBI) were diagnosed with dementia (adjusted odds ratio [OR], 1.81; 95% confidence interval [CI], 1.75–1.86). The association was strongest in the first year after TBI (OR, 3.52; 95% CI, 3.23–3.84), but the risk remained significant >30 years (OR, 1.25; 95% CI, 1.11–1.41). Single mild TBI showed a weaker association with dementia (OR, 1.63; 95% CI, 1.57–1.70) than did more severe TBI (OR, 2.06; 95% CI, 1.95–2.19) and multiple TBIs (OR, 2.81; 95% CI, 2.51–3.15). These results were in general confirmed in the nested case-control cohort. TBI was also associated with an increased risk of dementia diagnosis in sibling pairs with discordant TBI status (OR, 1.89; 95% CI, 1.62–2.21). A main limitation of the present study is the observational design. Thus, no causal inferences can be made based on the associations found. The risk of dementia diagnosis decreased over time after TBI, but it was still evident >30 years after the trauma. The association was stronger for more severe TBI and multiple TBIs, and it persisted after adjustment for familial factors.

Sarcopenia has been defined as age-related loss of muscle mass and function. The aim of this randomized controlled trial was to examine the effects of a 10-week instructor-led resistance training program on functional strength and body composition in men and women aged 70 years with pre-sarcopenia. Participants were randomized to either 10 weeks of a physical training regimen including optional nutritional supplementation (n = 36) or to a control group (n = 34) (ClinicalTrials.gov, no. NCT03297632). The main outcome was changes in the Short Physical Performance Battery (SPPB) score. Secondary outcomes included the Timed Up and Go test, chair sit-stand time, lean body mass, and fat mass. The intervention had no significant effect on SPPB in the total cohort (P = .18), when comparing changes in the intervention group with the control group. However, those given the intervention in the male subcohort increased 0.5 ± 0.4 (mean ± standard error for the difference) points in SPPB during follow-up (P = .02) compared to male controls. With respect to secondary outcomes, the intervention group decreased 0.9 ± 0.6 seconds in chair sit-stand time compared to controls (P = .01). Furthermore, the intervention resulted in significantly greater improvements for the training group than control group in all measures of body composition (P ≤ .01 for all). For example, lean body mass increased by a mean of 1147 ± 282 g (P < .001), and total fat mass decreased by a mean of 553 ± 225 g (P = .003), favoring the intervention group. The main finding of this intervention study is that an easy-to-use, functional resistance training program was effective in maintaining functional strength and increasing muscle mass in older adults with pre-sarcopenia.

Recent genome-wide association studies (GWAS) have identified multiple risk loci for common obesity (FTO, MC4R, TMEM18, GNPDA2, SH2B1, KCTD15, MTCH2, NEGR1 and PCSK1). Here we extend those studies by examining associations with adiposity and type 2 diabetes in Swedish adults. The nine single nucleotide polymorphisms (SNPs) were genotyped in 3885 non-diabetic and 1038 diabetic individuals with available measures of height, weight and body mass index (BMI). Adipose mass and distribution were objectively assessed using dual-energy X-ray absorptiometry in a sub-group of non-diabetics (n = 2206). In models with adipose mass traits, BMI or obesity as outcomes, the most strongly associated SNP was FTO rs1121980 (P < 0.001). Five other SNPs (SH2B1 rs7498665, MTCH2 rs4752856, MC4R rs17782313, NEGR1 rs2815752 and GNPDA2 rs10938397) were significantly associated with obesity. To summarize the overall genetic burden, a weighted risk score comprising a subset of SNPs was constructed; those in the top quintile of the score were heavier (+2.6 kg) and had more total (+2.4 kg), gynoid (+191 g) and abdominal (+136 g) adipose tissue than those in the lowest quintile (all P < 0.001). The genetic burden score significantly increased diabetes risk, with those in the highest quintile (n = 193/594 cases/controls) being at 1.55-fold (95% CI 1.21–1.99; P < 0.0001) greater risk of type 2 diabetes than those in the lowest quintile (n = 130/655 cases/controls). In summary, we have statistically replicated six of the previously associated obese-risk loci and our results suggest that the weight-inducing effects of these variants are explained largely by increased adipose accumulation.