180 research outputs found

    Trust in Technology: An Empirical Examination of the Construct

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    In this study, we examine trust in the technology itself. We introduce and distinguish between trusting beliefs, trust in a technology vendor, and willingness to depend on a technology. Empirically, we integrate these constructs into existing innovation diffusion research and examine these constructs’ relationship with the ease of use (EOU), perceived usefulness (PU) and intention to explore technology. Our analysis suggests that (1) trusting belief in technology have a direct effect on EOU and PU, (2) trusting belief in a vendor influenced willingness to depend on a technology and (3) willingness to depend on a technology has a direct effect on PU and a mediated effect on intention to explore. Implications for research and practice are offered

    Sitting Time and Waist Circumference Are Associated With Glycemia in U.K. South Asians: Data from 1,228 adults screened for the PODOSA trial

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    OBJECTIVE-To investigate the independent contributions of waist circumference, physical activity, and sedentary behavior on glycemia in South Asians living in Scotland. RESEARCH DESIGN AND METHODS-Participants were 1,228 (523 men and 705 women) adults of Indian or Pakistani origin screened for the Prevention of Type 2 Diabetes and Obesity in South Asians (PODOSA) trial. All undertook an oral glucose tolerance test, had physical activity and sitting time assessed by International Physical Activity Questionnaire, and had waist circumference measured. RESULTS-Mean +/- SD age and waist circumference were 49.8 +/- 10.1 years and 99.2 +/- 10.2 cm, respectively. One hundred ninety-one participants had impaired fasting glycemia or impaired glucose tolerance, and 97 had possible type 2 diabetes. In multivariate regression analysis, ay (0.012 mmol.L-1.year [95% CI 0.006-0.017]) and waist circumference (0.018 mmol.L-1.cm(-1) [0.012-0.024]) were significantly independently associated with fasting glucose concentration, and age (0.032 mmol.L-1.year(-1) [0.016-0.049]), waist (0.057 mmolL(-1).cm(-1) [0.040-0.074]), and sitting time (0.097 mmol.L-1.h(-1).day(-1) [0.036-0.158]) were significantly independently associated with 2-h glucose concentration. Vigorous activity time had a borderline significant association with 2-h glucose concentration (-0.819 mmol.L-1.h(-1).day-1 [-1.672 to 0.034]) in the multivariate model. CONCLUSIONS-These data highlight an important relationship between sitting time and 2-h glucose levels in U.K. South Asians, independent of physical activity and waist circumference. Although the data are cross-sectional and thus do not permit firm conclusions about causality to be drawn, the results suggest that further study investigating the effects of sitting time on glycemia and other aspects of metabolic risk in South Asian populations is warrante

    Discovery and fine-mapping of loci associated with MUFAs through trans-ethnic meta-analysis in Chinese and European populations

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    MUFAs are unsaturated FAs with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels are associated with cardiometabolic disorders, including CVD, T2D, and metabolic syndrome (MS). Previous genome-wide association studies (GWASs) have identified seven loci for plasma and erythrocyte palmitoleic and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential functional variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in more than 15,000 participants of Chinese and European ancestry. We identified novel genome-wide significant associations for vaccenic acid at FADS1/2 and PKD2L1 [log(10)(Bayes factor). >= 8.07] and for gondoic acid at FADS1/2 and GCKR [log(10)(Bayes factor) >= 6.22], and also observed improved fine-mapping resolutions at FADS1/2 and GCKR loci. The greatest improvement was observed at GCKR, where the number of variants in the 99\% credible set was reduced from 16 (covering 94.8 kb) to 5 (covering 19.6 kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of PKD2L1, FADS1/2, GCKR, and HIF1AN with palmitoleic acid and of FADS1/2 and LPCAT3 with oleic acid in the Chinese-specific GWAS and the trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were in unsaturated FA metabolism and signaling pathways.(jl) Our findings provide novel insight into the genetic basis relevant to MUFA metabolism and biology.Infrastructure for the CHARGE Consortium was supported in part by the National Heart, Lung, and Blood Institute grant HL105756. The NHAPC study was supported by the major project of the Ministry of Science and Technology of China (2016YFC1304903) and the National Natural Science Foundation of China (81471013, 30930081, 81170734, and 81321062). The ARIC Study was carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C and grants R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. Infrastructure was partly supported by grant UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. The CARDIA study was conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201300025C and HHSN268201300026C), Northwestern University (HHSN268201300027C), University of Minnesota (HHSN268201300028C), Kaiser Foundation Research Institute (HHSN268201300029C), and Johns Hopkins University School of Medicine (HHSN268200900041C). CARDIA is also partially supported by the Intramural Research Program of the National Institute on Aging. Genotyping of the CARDIA participants was supported by National Human Genome Research Institute grants U01-HG-004729, U01-HG-004446, and U01-HG-004424. Statistical analyses and FA measures were funded by National Heart, Lung, and Blood Institute grant R01-HL-084099 (M.F.). The CHS was supported by National Heart, Lung, and Blood Institute contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086; and National Heart, Lung, and Blood Institute grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and R01HL085710, with additional contribution from the National Institute of Neurological Disorders and Stroke. Additional support was provided through National Institute on Aging grant R01AG023629. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences CTSI grant UL1TR000124 and the National Institute of Diabetes and Digestive and Kidney Diseases Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The HPFS and NHS were supported by National Institutes of Health research grants UM1 CA186107, R01 HL034594, UM1 CA167552, R01 HL35464, HL60712, and CA055075; National Heart, Lung, and Blood Institute career development award R00HL098459; American Diabetes Association research grant 1-12-JF-13; and American Heart Association grant 11SDG7380016. The MESA study and MESA SHARe were supported by National Heart, Lung, and Blood Institute contracts N01-HC-95159 through N01-HC-95169 and RR-024156. Funding for MESA SHARe genotyping was provided by National Heart, Lung, and Blood Institute contract N02HL64278. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences CTSI grant UL1TR000124 and the National Institute of Diabetes and Digestive and Kidney Diseases Diabetes Research Center grant DK063491 (Southern California Diabetes Endocrinology Research Center).; The GOLDN study was funded by National Heart, Lung, and Blood Institute grants U01HL072524 and HL54776. The InCHIANTI baseline (1998-2000) was supported as a ``targeted project (ICS110.1/RF97.71) by the Italian Ministry of Health and in part by National Institute on Aging contracts 263 MD 9164 and 263 MD 821336. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.S

    Comparing Respondent-Driven Sampling and Targeted Sampling Methods of Recruiting Injection Drug Users in San Francisco

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    The objective of this article is to compare demographic characteristics, risk behaviors, and service utilization among injection drug users (IDUs) recruited from two separate studies in San Francisco in 2005, one which used targeted sampling (TS) and the other which used respondent-driven sampling (RDS). IDUs were recruited using TS (n = 651) and RDS (n = 534) and participated in quantitative interviews that included demographic characteristics, risk behaviors, and service utilization. Prevalence estimates and 95% confidence intervals (CIs) were calculated to assess whether there were differences in these variables by sampling method. There was overlap in 95% CIs for all demographic variables except African American race (TS: 45%, 53%; RDS: 29%, 44%). Maps showed that the proportion of IDUs distributed across zip codes were similar for the TS and RDS sample, with the exception of a single zip code that was more represented in the TS sample. This zip code includes an isolated, predominantly African American neighborhood where only the TS study had a field site. Risk behavior estimates were similar for both TS and RDS samples, although self-reported hepatitis C infection was lower in the RDS sample. In terms of service utilization, more IDUs in the RDS sample reported no recent use of drug treatment and syringe exchange program services. Our study suggests that perhaps a hybrid sampling plan is best suited for recruiting IDUs in San Francisco, whereby the more intensive ethnographic and secondary analysis components of TS would aid in the planning of seed placement and field locations for RDS

    Genetic loci associated with plasma phospholipid N-3 fatty acids: A Meta-Analysis of Genome-Wide association studies from the charge consortium

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    Long-chain n-3 polyunsaturated fatty acids (PUFAs) can derive from diet or from α-linolenic acid (ALA) by elongation and desaturation. We investigated the association of common genetic variation with plasma phospholipid levels of the four major n-3 PUFAs by performing genome-wide association studies in five population-based cohorts comprising 8,866 subjects of European ancestry. Minor alleles of SNPs in FADS1 and FADS2 (desaturases) were associated with higher levels of ALA (p = 3×10-64) and lower levels of eicosapentaenoic acid (EPA, p = 5×10-58) and docosapentaenoic acid (DPA, p = 4×10-154). Minor alleles of SNPs in ELOVL2 (elongase) were associated with higher EPA (p = 2×10-12) and DPA (p = 1×10-43) and lower docosahexaenoic acid (DHA, p = 1×10-15). In addition to genes in the n-3 pathway, we identified a novel association of DPA with several SNPs in GCKR (glucokinase regulator, p = 1×10-8). We observed a weaker association between ALA and EPA among carriers of the minor allele of a representative SNP in FADS2 (rs1535), suggesting a lower rate of ALA-to-EPA conversion in these subjects. In samples of African, Chinese, and Hispanic ancestry, associations of n-3 PUFAs were similar with a representative SNP in FADS1 but less consistent with a representative SNP in ELOVL2. Our findings show that common variation in n-3 metabolic pathway genes and in GCKR influences plasma phospholipid levels of n-3 PUFAs in populations of European ancestry and, for FADS1, in other ancestries

    Fatty Acid Biomarkers of Dairy Fat Consumption and Incidence of Type 2 Diabetes: A Pooled Analysis of Prospective Cohort Studies

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    Background We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D). Methods and findings Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance±weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohortspecific 10th to 90th percentile range of 15:0 was 0.80 (0.73±0.87); of 17:0, 0.65 (0.59± 0.72); of t16:1n7, 0.82 (0.70±0.96); and of their sum, 0.71 (0.63±0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction \u3c 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist. Conclusions In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D
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