18 resultados para Data linkage

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Objectives
To determine whether excessive and often inappropriate or dangerous psychotropic drug dispensing to older adults is unique to care homes or is a continuation of community treatment.

Design
Population-based data-linkage study using prescription drug information.

Setting
Northern Ireland's national prescribing database and care home information from the national inspectorate.

Participants
Two hundred fifty thousand six hundred seventeen individuals aged 65 and older.

Measurements
Prescription information was extracted for all psychotropic drugs included in the British National Formulary (BNF) categories 4.1.1, 4.1.2, and 4.2.2 (hypnotics, anxiolytics, and antipsychotics) dispensed over the study period. Repeated cross-sectional analysis was used to monitor changes in psychotropic drug dispensing over time.

Results
Psychotropic drug use was higher in care homes than the community; 20.3% of those in care homes were dispensed an antipsychotic in January 2009, compared with 1.1% of those in the community. People who entered care had higher use of psychotropic medications before entry than those who did not enter care, but this increased sharply in the month of admission and continued to rise. Antipsychotic drug dispensing increased from 8.2% before entry to 18.6% after entering care (risk ratio (RR) = 2.26, 95% confidence interval (CI)=1.96–2.59) and hypnotic drug dispensing from 14.8% to 26.3% (RR=1.78, 95% CI=1.61–1.96).

Conclusion
A continuation of high use before entry cannot wholly explain the higher dispensing of psychotropic drugs to individuals in care homes. Although drug dispensing is high in older people in the community, it increases dramatically on entry to care. Routine medicine reviews are necessary in older people and are especially important during transitions of care.

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Objectives. We compared the mental health risk to unpaid caregivers bereaved of a care recipient with the risk to persons otherwise bereaved and to nonbereaved caregivers.

Methods. We linked prescription records for antidepressant and anxiolytic drugs to characteristics and life-event data of members of the Northern Ireland Longitudinal Study (n = 317 264). Using a case-control design, we fitted logistic regression models, stratified by age, to model relative likelihood of mental health problems, using the proxy measures of mental health–related prescription.

Results. Both caregivers and bereaved individuals were estimated to be at between 20% and 50% greater risk for mental health problems than noncaregivers in similar circumstances (for bereaved working-age caregivers, odds ratio = 1.41; 95% confidence interval = 1.27, 1.56). For older people, there was no evidence of additional risk to bereaved caregivers, though there was for working-age people. Older people appeared to recover more quickly from caregiver bereavement.

Conclusions. Caregivers were at risk for mental ill health while providing care and after the death of the care recipient. Targeted caregiver support needs to extend beyond the life of the care recipient.


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Research on admissions to care homes for older people has paid more attention to individual and social characteristics than to geographical factors. This paper considers rural-urban differences in household composition and admission rates. Cohort: 51,619 people aged 65 years or older at the time of the 2001 Census and not living in a care home, drawn from a data linkage study based on c.28% of the Northern Ireland population.Living alone was less common in rural areas; 25% of older people in rural areas lived with children compared to 18% in urban areas. Care home admission was more common in urban (4.7%) and intermediate (4.3%) areas than in rural areas (3.2%). Even after adjusting for age, sex, health and living arrangements, the rate of care home admission in rural areas was still only 75% of that in urban areas.People in rural areas experience better family support by living as part of two or three generation households. Even after accounting for this difference, older rural dwellers are less likely to enter care homes; suggesting that neighbours and relatives in rural areas provide more informal care; or that there may be differential deployment of formal home care services.

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Accurate address information from health service providers is fundamental for the effective delivery of health care and population monitoring and screening. While it is currently used in the production of key statistics such as internal migration estimates, it will become even more important over time with the 2021 Census of UK constituent countries integrating administrative data to enhance the quality of statistical outputs. Therefore, it is beneficial to improve understanding of the accuracy of address information held by health service providers and factors that influence this. This paper builds upon previous research on the social geography of address mismatch between census and health service records in Northern Ireland. It is based on the Northern Ireland Longitudinal Study; this is a large data linkage study including about 28 per cent of the Northern Ireland population, which is matched between the census (2001, 2011) and Health Card Registration System maintained by the Health and Social Care Business Service Organisation (BSO). This research compares address information from the Spring 2011 BSO download (Unique Property Reference Number, Super Output Area) with comparable geographic information from the 2011 Census. Multivariate and multilevel analyses are used to assess the individual and ecological determinants of match/mismatch between geographical information in both data sources to determine if the characteristics of the associated people and places are the same as the position observed in 2001. It is important to understand if the same people are being inaccurately geographically referenced in both Census years or if the situation is more variable.

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Objectives
To investigate individual, household and country variation in consent to health record linkage.

Study Design and Setting
Data from 50,994 individuals aged 16-74 years recruited to wave 1 of a large UK general purpose household survey (January 2009 – December 2010) were analysed using multi-level logistic regression models.

Results
Overall, 70.7% of respondents consented to record linkage. Younger age, marriage, tenure, car ownership and education were all significantly associated with consent, though there was little deviation from 70% in subgroups defined by these variables. There were small increases in consent rates in individuals with poor health when defined by self-reported long term limiting illness (adjusted OR 1.11; 95%CIs 1.06, 1.16), less so when defined by General Health Questionnaire score (adjusted OR=1.05; 95%CIs 1.00, 1.10), but the range in absolute consent rates between categories was generally less than 10%. Larger differences were observed for those of non-white ethnicity who were 38% less likely to consent (adjusted OR 0.62; 95%CIs 0.59, 0.66). Consent was higher in Scotland than England (adjusted OR 1.17; 95%CIs 1.06, 1.29) but lower in Northern Ireland (adjusted OR 0.56; 95%CIs 0.50, 0.63).

Conclusion
The modest overall level of systematic bias in consent to record linkage provides reassurance for record linkage potential in general purpose household surveys. However, the low consent rates amongst non-white ethnic minority survey respondents will further compound their low survey participation rates. The reason for the country-level variation requires further study.

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The main hallmark of diabetic nephropathy is elevation in urinary albumin excretion. We performed a genome-wide linkage scan in 63 extended families with multiple members with type II diabetes. Urinary albumin excretion, measured as the albumin-to-creatinine ratio (ACR), was determined in 426 diabetic and 431 nondiabetic relatives who were genotyped for 383 markers. The data were analyzed using variance components linkage analysis. Heritability (h2) of ACR was significant in diabetic (h2=0.23, P=0.0007), and nondiabetic (h2=0.39, P=0.0001) relatives. There was no significant difference in genetic variance of ACR between diabetic and nondiabetic relatives (P=0.16), and the genetic correlation (rG=0.64) for ACR between these two groups was not different from 1 (P=0.12). These results suggested that similar genes contribute to variation in ACR in diabetic and nondiabetic relatives. This hypothesis was supported further by the linkage results.

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Prior family and adoption studies have suggested a genetic relationship between schizophrenia and schizotypy. However, this has never been verified using linkage methods. We therefore attempted to test for a correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. The Irish study of high-density schizophrenia families comprises 270 families with at least two members with schizophrenia or poor-outcome schizoaffective disorder (n = 637). Non-psychotic relatives were assessed using the structured interview for schizotypy (n = 746). A 10-cM multipoint, non-parametric, autosomal genomewide scan of schizophrenia was performed in Merlin. A scan of a quantitative trait comprising ratings of DSM-III-R criteria for schizotypal personality disorder in non-psychotic relatives was also performed. Schizotypy logarithm of the odds (LOD) scores were regressed onto schizophrenia LOD scores at all loci, with adjustment for spatial autocorrelation. To assess empirical significance, this was also carried out using 1000 null scans of schizotypy. The number of jointly linked loci in the real data was compared to distribution of jointly linked loci in the null scans. No markers were suggestively linked to schizotypy based on strict Lander Kruglyak criteria. Schizotypy LODs predicted schizophrenia LODs above chance expectation genome wide (empirical P = 0.04). Two and four loci yielded nonparametric LOD (NPLs) > 1.0 and > 0.75, respectively, for both schizophrenia and schizotypy (genome-wide empirical P = 0.04 and 0.02, respectively). These results suggest that at least a subset of schizophrenia susceptibility genes also affects schizotypy in non-psychotic relatives. Power may therefore be increased in molecular genetic studies of schizophrenia if they incorporate measures of schizotypy in non-psychotic relatives.

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We conducted data-mining analyses of genome wide association (GWA) studies of the CATIE and MGS-GAIN datasets, and found 13 markers in the two physically linked genes, PTPN21 and EML5, showing nominally significant association with schizophrenia. Linkage disequilibrium (LD) analysis indicated that all 7 markers from PTPN21 shared high LD (r(2)>0.8), including rs2274736 and rs2401751, the two non-synonymous markers with the most significant association signals (rs2401751, P=1.10 × 10(-3) and rs2274736, P=1.21 × 10(-3)). In a meta-analysis of all 13 replication datasets with a total of 13,940 subjects, we found that the two non-synonymous markers are significantly associated with schizophrenia (rs2274736, OR=0.92, 95% CI: 0.86-0.97, P=5.45 × 10(-3) and rs2401751, OR=0.92, 95% CI: 0.86-0.97, P=5.29 × 10(-3)). One SNP (rs7147796) in EML5 is also significantly associated with the disease (OR=1.08, 95% CI: 1.02-1.14, P=6.43 × 10(-3)). These 3 markers remain significant after Bonferroni correction. Furthermore, haplotype conditioned analyses indicated that the association signals observed between rs2274736/rs2401751 and rs7147796 are statistically independent. Given the results that 2 non-synonymous markers in PTPN21 are associated with schizophrenia, further investigation of this locus is warranted.

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BACKGROUND: Published work assessing psychosocial stress (job strain) as a risk factor for coronary heart disease is inconsistent and subject to publication bias and reverse causation bias. We analysed the relation between job strain and coronary heart disease with a meta-analysis of published and unpublished studies. METHODS: We used individual records from 13 European cohort studies (1985-2006) of men and women without coronary heart disease who were employed at time of baseline assessment. We measured job strain with questions from validated job-content and demand-control questionnaires. We extracted data in two stages such that acquisition and harmonisation of job strain measure and covariables occurred before linkage to records for coronary heart disease. We defined incident coronary heart disease as the first non-fatal myocardial infarction or coronary death. FINDINGS: 30?214 (15%) of 197?473 participants reported job strain. In 1·49 million person-years at risk (mean follow-up 7·5 years [SD 1·7]), we recorded 2358 events of incident coronary heart disease. After adjustment for sex and age, the hazard ratio for job strain versus no job strain was 1·23 (95% CI 1·10-1·37). This effect estimate was higher in published (1·43, 1·15-1·77) than unpublished (1·16, 1·02-1·32) studies. Hazard ratios were likewise raised in analyses addressing reverse causality by exclusion of events of coronary heart disease that occurred in the first 3 years (1·31, 1·15-1·48) and 5 years (1·30, 1·13-1·50) of follow-up. We noted an association between job strain and coronary heart disease for sex, age groups, socioeconomic strata, and region, and after adjustments for socioeconomic status, and lifestyle and conventional risk factors. The population attributable risk for job strain was 3·4%. INTERPRETATION: Our findings suggest that prevention of workplace stress might decrease disease incidence; however, this strategy would have a much smaller effect than would tackling of standard risk factors, such as smoking. FUNDING: Finnish Work Environment Fund, the Academy of Finland, the Swedish Research Council for Working Life and Social Research, the German Social Accident Insurance, the Danish National Research Centre for the Working Environment, the BUPA Foundation, the Ministry of Social Affairs and Employment, the Medical Research Council, the Wellcome Trust, and the US National Institutes of Health.

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In 2004, the integrated European project GEHA (Genetics of Healthy Ageing) was initiated with the aim of identifying genes involved in healthy ageing and longevity. The first step in the project was the recruitment of more than 2500 pairs of siblings aged 90 years or more together with one younger control person from 15 areas in 11 European countries through a coordinated and standardised effort. A biological sample, preferably a blood sample, was collected from each participant, and basic physical and cognitive measures were obtained together with information about health, life style, and family composition. From 2004 to 2008 a total of 2535 families comprising 5319 nonagenarian siblings were identified and included in the project. In addition, 2548 younger control persons aged 50-75 years were recruited. A total of 2249 complete trios with blood samples from at least two old siblings and the younger control were formed and are available for genetic analyses (e.g. linkage studies and genome-wide association studies). Mortality follow-up improves the possibility of identifying families with the most extreme longevity phenotypes. With a mean follow-up time of 3.7 years the number of families with all participating siblings aged 95 years or more has increased by a factor of 5 to 750 families compared to when interviews were conducted. Thus, the GEHA project represents a unique source in the search for genes related to healthy ageing and longevity.

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Clear evidence exists for heritability of humanlongevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12-q22 (LOD = 2.95), chromosome 19p13.3-p13.11 (LOD = 3.76), and chromosome 19q13.11-q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed-effect meta-analysis approach, rs4420638 at the TOMM40/ APOE/APOC1 gene locus showed significant association with longevity (P-value = 9.6 × 10). By combined modeling of linkage and association, we showed that association of longevity with APOEe4 and APOEe2 alleles explain the linkage at 19q13.11-q13.32 with P-value = 0.02 and P-value = 1.0 × 10, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12-q22, and 19p13.3-p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.

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To determine if urban residence is associated with an increased risk of anxiety/depression independent of psychosocial stressors, concentrated disadvantage or selective migration between urban and rural areas, this population wide record-linkage study utilised data on receipt of prescription medication linked to area level indicators of conurbation and disadvantage. An urban/rural gradient in anxiolytic and antidepressant use was evident that was independent of variation in population composition. This gradient was most pronounced amongst disadvantaged areas. Migration into increasingly urban areas increased the likelihood of medication. These results suggest increasing conurbation is deleterious to mental health, especially amongst residents of deprived areas

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Retinitis pigmentosa (RP) is the most prevalent human retinopathy of genetic origin. Chromosomal locations for X-linked RP and autosomal dominant RP genes have recently been established. Multipoint analyses with ADRP and seven markers on the long arm of chromosome 3 demonstrate that the gene for rhodopsin, the pigment of the rod photoreceptors, cosegregates with the disease locus with a maximum lod score of approximately 19, implicating rhodopsin as a causative gene. Recent studies have indicated the presence of a point mutation at codon 23 in exon 1 of rhodopsin which results in the substitution of histidine for the highly conserved amino acid proline, suggesting that this mutation is a cause of rhodopsin-linked ADRP. This mutation is not present in the Irish pedigree in which ADRP has been mapped close to rhodopsin. Another mutation in the rhodopsin gene or in a gene closely linked to rhodopsin may be involved. Moreover, the gene in a second ADRP pedigree, with Type II late onset ADRP, does not segregate with chromosome 3q markers, indicating that nonallelic as well as perhaps allelic genetic heterogeneity exists in the autosomal dominant form of this disease.

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DNA from members of a three-generation pedigree of Irish origin, displaying an autosomal dominant simplex form of epidermolysis bullosa of the epidermolytic, simplex, or Koebner variety (EBS2), was analyzed for linkage with a set of markers derived from the long arm of chromosome 1. Two-point analysis revealed positive lod scores for five of these markers, AT3 (Z = 2.107, theta = 0), APOA2 (Z = 1.939, theta = 0.15), D1S66 (Z = 1.204, theta = 0), D1S13 (Z = 1.026, theta = 0.15), and D1S65 (Z = 0.329, theta = 0.15). Multilocus analysis, incorporating the markers D1S19, D1S16, D1S13, APOA2, D1S66, AT3, and D1S65, resulted in a lod score of 3 maximizing at AT3. These data strongly support previous tentative indications of linkage between EBS2 and genetic markers on the long arm of chromosome 1.