19 research outputs found
Characteristics of people interviewed.
Diabetes and depression are both serious health conditions. While their relationship is bidirectional and each condition adversely affects outcomes for the other, they are treated separately. In low and middle income countries, such as Bangladesh and Pakistan, health systems are already stretched and the integration of diabetes and depression care is rarely a priority. Within this context through interviews with patients, healthcare workers and policy makers the study explored: lived experiences of people living with depression and diabetes, current practice in mental health and diabetes care and barriers and perspectives on integrating a brief psychological therapy into diabetes care. The findings of the study included: differing patient and practitioner understandings of distress/depression, high levels of stigma for mental health and a lack of awareness and training on treating depression. While it was apparent there is a need for more holistic care and the concept of a brief psychological intervention appeared acceptable to participants, many logistical barriers to integrating a mental health intervention into diabetes care were identified. The study highlights the importance of context and of recognising drivers and understandings of distress when planning for more integrated mental and physical health services, and specifically when adapting and implementing a new intervention into existing services.</div
COREQ (COnsolidated criteria for REporting Qualitative research) checklist completed for the reported study in the manuscript.
COREQ (COnsolidated criteria for REporting Qualitative research) checklist completed for the reported study in the manuscript.</p
Enrichment for coding variants amongst autosomal SNPs stratified between South Asians and the 1000 Genome populations (3A) and for specific functional classes of SNPs amongst South Asians compared to Europeans (3B).
<p>Enrichment is calculated compared to null hypothesis; P values are provided in <b>Table S6 and Table S7 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102645#pone.0102645.s021" target="_blank">File S1</a></b>.</p
Correlation between imputed and observed genotypes amongst South Asians, using phased or unphased genotypes from low coverage WGS, or using 1000 Genomes Project data.
<p>Results are shown as mean r<sup>2</sup> with genotypes observed from microarray data (<b>2A</b>) or high-coverage WGS (<b>2B</b>, WGS-28x).</p
Location of birth (1A) and principal components analysis (PCA, 1B) of the South Asians sequenced.
<p>The PCA plots shows results for all South Asians in the LOLIPOP study (SA - All, red circles), for South Asians sequenced (SA - NGS, black dots) and for HapMap2 populations.</p
Enrichment for stratified genetic variants at genetic loci associated with respective phenotype in genome-wide association studies.
<p>Inset the correlation between the enrichment for stratified SNPs at known genetic loci, and enrichment of stratified variants for SNPs associated with respective phenotype in genome-wide association studies. Further details are provided in <b>Table S10 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0102645#pone.0102645.s021" target="_blank">File S1</a></b>.</p
T2D prediction, glycemic genetic score.
<p>Forest plot of association between glycemic genetic score with incident T2D over a decade-long follow-up period, by ancestry. MESA (European and Asian ancestry) and the <i>G6PD</i> variant (rs1050828) in ARIC (European and African American) were not included in the discovery GWAS analysis. Effect estimates were combined in a fixed effects meta-analysis. Overall effect estimate: 1.05, 95% CI 1.04–1.06, <i>p</i> = 2.5 × 10<sup>−29</sup>. ARIC, Atherosclerosis Risk in Communities Study; ES, Effect Size; FHS, Framingham Heart Study; GWAS, genome-wide association study; G6PD, glucose-6-phosphate dehydrogenase; I-Squared, Higgin's I-squared statistic, a measure of heterogeneity; MESA, Multiethnic Study of Atherosclerosis; SCHS, Singapore Chinese Health Study; T2D, type 2 diabetes.</p
Reclassification of individuals with discordant T2D status based on prevailing diagnostic thresholds for FG and HbA1c before and after accounting for the effect of erythrocytic variants.
<p>Reclassification of individuals with discordant T2D status based on prevailing diagnostic thresholds for FG and HbA1c before and after accounting for the effect of erythrocytic variants.</p
Mean HbA1c of individuals at the bottom 5% and top 5% of the distribution of ancestry-specific genetic scores and rs1050828 by genotype.
<p>The difference in measured HbA1c of individuals at the bottom 5% and top 5% of the distribution of an ancestry-specific additive GS composed of all 60 variants (GS-Total), and the equivalent calculation for an ancestry-specific GS composed of up to 20 erythrocytic variants (GS-E). Far right of the figure shows the mean HbA1c by genotype for chromosome X rs1050828. AA men, African American men; AA women, African American women; HbA1c, glycated hemoglobin; GS, genetic scores.</p
T2D prediction, erythrocytic genetic score.
<p>Forest plot of association between erythrocytic genetic score with incident T2D over a decade-long follow-up period, by ancestry. MESA (European and Asian ancestry) and the <i>G6PD</i> variant (rs1050828) in ARIC (European and African American) were not included in the discovery GWAS analysis. Effect estimates were combined in a fixed effects meta-analysis. Overall effect estimate: 1.00, 95% CI 0.99–1.01, <i>p</i> = 0.60. ARIC, Atherosclerosis Risk in Communities Study; ES, Effect Size, FHS, Framingham Heart Study; GWAS, genome-wide association study; G6PD, glucose-6-phosphate dehydrogenase; I-Squared, Higgin's I-squared statistic, a measure of heterogeneity; MESA, Multiethnic Study of Atherosclerosis; SCHS, Singapore Chinese Health Study; T2D, type 2 diabetes.</p