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Previous research demonstrates various associations between depression, cardiovascular disease (CVD) incidence and mortality. Differences between studies may occur as a result of different methodologies.
This work investigated the impact of using two different methods to measure depression and two different methods of analysis to establish relationships.
The work investigated the association between depression, CVD incidence (CVDI) and mortality from coronary heart disease (MCHD), smoking related conditions (MSRC), and all causes (MALL), in a major population study using depression measured from a validated scale and a depression measure derived by factor analysis, and analyses based on continuous data and grouped data.
Data from the PRIME Study (N=9,798 men) on depression and ten year CVD incidence and mortality were analysed using Cox proportional hazards models.
Using continuous data, no relationships with CVDI were found, but both measures of depression resulted in the emergence of positive associations between depression and mortality (MCHD, MSRC, MALL). Using grouped data, no associations with CVDI or MCVD were found, and associations between the measure derived from factor analysis and MSRC and MALL were also lost. Positive associations were only found between depression measured using validated items, MSRC and MALL.
These data demonstrate a possible association between depression and mortality but detecting this association is dependent on the methodology used. Different findings based on methodology present clear problems for the determination of relationships. The differences here suggest the preferential use of validated scales and suggest against over-reduction via factor analysis and grouping.
A longstanding issue in the field of nutrition is the potential inaccuracy of methods traditionally used for dietary assessment (i.e. food diaries and food frequency questionnaires). It is possible to overcome the limitations and biases of these techniques by combining them with analytical measurements in human biofluids. Metabolomic technologies are gaining popularity as nutritional tools due to their capacity to measure metabolic responses to external stimuli, such as the ingestion of certain foods. This project performed both LC-MS and 1H-NMR metabolomic profiling on serum samples collected as part of the NICOLA study (Northern Irish Cohort for the Longitudinal Study of Aging) in order to discover novel dietary biomarkers. A dietary validation cohort (NIDAS) was incorporated within NICOLA, involving 45 males and 50 females, aged 50 years and over. Participants provided detailed dietary data (4-day food diary) and blood samples at two time-points, six months apart. Serum samples were processed on two analytical platforms. 1H-NMR spectra were acquired using a Bruker 600 MHz Ascent coupled to a TCI cryoprobe and processed using Bayesil (University of Alberta, Canada). A Waters TQ-S coupled with an Acquity I-class UPLC was used in combination with a targeted commercially available kit (AbsoluteIDQ p180 kit, Biocrates). Mass spectra obtained were processed with MetIDQ and verified using MassLynx (v4.1). Data were tested for normality, and metabolite concentrations were correlated with recorded dietary intake of each food type using SPSS. Additional tests (PCA, PLS-DA, ROC Curves) were performed on MetaboAnalyst 4.0 (University of Alberta, Canada). More than 50 statistically significant (P < 0.05) food-metabolite correlations were detected, 15 of which remained significant after eliminating potential confounding from sex, age and BMI. The strongest correlations were between fruit consumption and acetic acid, and between dairy consumption and certain glycerophospholipids (e.g. LysoPC aa C20:3). Stratifying the cohort by gender yielded further correlations, including PC ae C38:2 (dairy; males), PC aa C34:4 (dairy; females), PC aa C36:4 (dairy; females) and trans-4-Hydroxyproline (meat; males). A number of potential blood-based food biomarkers were detected, many of which are gender-specific, and some are corroborated by previously published studies. However, further validation work is required. For example, biological plausibility needs to be established, and the findings need to be reproduced in other cohorts to demonstrate their applicability in larger and more diverse populations. These results contribute greatly to the ongoing efforts to discover and validate reliable nutritional biomarkers as an objective and unbiased measurement of food intake.
We compared antibiotic prescribing to older people in different settings to inform antibiotic stewardship interventions. We used data linkage to stratify individuals aged 65 years and over in Northern Ireland, 1st January 2012–31st December 2013, by residence: community dwelling, care home dwelling or ‘transitioned’ if admitted to a care home. The odds of being prescribed an antibiotic by residence were analysed using logistic regression, adjusting for patient demographics and selected medication use (proxy for co-morbidities). Trends in monthly antibiotic prescribing were examined in the 6 months pre- and post-admission to the care home. The odds of being prescribed at least one antibiotic were twofold higher in care homes compared with community dwellers (adjusted odds ratio 2.05, 95% CI 1.93–2.17). There was a proportionate increase of 51.5% in the percentage prescribed an antibiotic on admission, with a monthly average of 23% receiving an antibiotic in the 6 months post admission. While clinical need likely accounts for some of the observed antibiotic prescribing in care homes we cannot rule out more liberal prescribing, given the twofold difference between care home residents and their community dwelling peers having accounted for co-morbidities. The appropriateness of antibiotic prescribing in the care home setting should be examined.
This study uses simulation over real and artificial networks to compare the eventual adoption outcomes of network interventions, operationalized as idealized contagion processes with different sets of seeds. While the performance depends on the details of both the network and behaviour adoption mechanisms, interventions with seeds that are central to the network are more effective than random selection in the majority of simulations, with faster or more complete adoption throughout the network. These results provide additional theoretical justification for utilizing relevant network information in the design of public health behavior interventions.
Food group guideline adherence is vital to prevent obesity and diabetes. Various studies have demonstrated that environmental variables influence food intake behaviour. In the present study we examined the effect of a portion design plate with food group portion guidelines demarcated by coloured lines (ETE Plate™). A two-group quasi-experimental design was used to measure proportions of carbohydrate, vegetable and protein portions and user experience in a hospital staff lounge setting in Singapore. Lunch was served on the portion design plate before 12.15 hours. For comparison, a normal plate (without markings) was used after 12.15 hours. Changes in proportions of food groups from 2 months before the introduction of the design plate were analysed in a stratified sample at baseline (859 subjects, all on normal plates) to 1, 3 and 6 months after (in all 1016 subjects on the design plate, 968 subjects on the control plate). A total of 151 participants were asked about their experiences and opinions. Between-group comparisons were performed using t tests. Among those served on the portion design plate at 6 months after its introduction, the proportion of vegetables was 4·71 % (P < 0·001) higher and that of carbohydrates 2·83 % (P < 0·001) lower relative to the baseline. No significant change was found for proteins (−1·85 %). Over 6 months, we observed different change patterns between the different food group proportions. While participants were positive about the portion design plate, they did not think it would influence their personal behaviour. A portion design plate might stimulate food group guideline adherence among hospital staff and beyond.
The quality of prenatal maternal mental health, from psychological stress and depressive symptoms to anxiety and other nonpsychotic mental disorders, profoundly affects fetal neurodevelopment. Despite the evidence for the influence of positive mental well-being on health, there is, to our knowledge, no research examining the possible effects of positive antenatal mental health on the development of the offspring. Using exploratory bifactor analysis, this prospective study (n = 1,066) demonstrated the feasibility of using common psychiatric screening tools to examine the effect of positive maternal mental health. Antenatal mental health was assessed during 26th week of pregnancy. The effects on offspring were assessed when the child was 12, 18, and 24 months old. Results showed that positive antenatal mental health was uniquely associated with the offspring's cognitive, language and parentally rated competences. This study shows that the effects of positive maternal mental health are likely to be specific and distinct from the sheer absence of symptoms of depression or anxiety.
Using an interdisciplinary model of financial planning, we investigated the factors contributing to perceived adequacy of retirement savings among Hong Kong workers by replicating a previous study of American and Dutch workers. The model was also tested for age differences in the way in which the variables operated within the model. These questions were examined using data from a phone survey conducted with 999 Hong Kong workers in 2012. We examined three psychological factors (future time orientation, goal clarity and financial knowledge), three social support variables (early learning from parents, spousal support and friend support) and three institutional factors (quality of employer pensions, trust in banks and fund managers, and trust in the government), as well as retirement savings planning activity and perceived retirement savings adequacy. Path analyses were used to test the model for the whole sample and separately for younger (N=437) and older (N=562) workers. Although a few age differences were found in the path analyses, the model was found to be useful in explaining the factors contributing to retirement savings planning and practices. Finally, we discuss how our findings differ from those of prior studies, and we assess their theoretical and practical implications.