A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery

The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.

Disease mapping using Bayesian hierarchical models

description and analysis of geographically indexed health data with respect to demographic, environmental, behavioural, socioeconomic, genetic, and infectious risk factors (Elliott andWartenberg 2004). Disease maps can be useful for estimating relative risk; ecological analyses, incorporating area and/or individual-level covariates; or cluster analyses (Lawson 2009). As aggregated data are often more readily available, one common method of mapping disease is to aggregate the counts of disease at some geographical areal level, and present them as choropleth maps (Devesa et al. 1999; Population Health Division 2006). Therefore, this chapter will focus exclusively on methods appropriate for areal data...

Association of hearing impairment and subsequent driving mobility in older adults

- Purpose of the study Hearing impairment (HI) is associated with driving safety (e.g., increased crashes and poor on-road driving performance). However, little is known about HI and driving mobility. This study examined the longitudinal association of audiometric hearing with older adults’ driving mobility over three years. - Design and Methods Secondary data analyses were conducted of 500 individuals (63-90 years) from the Staying Keen in Later Life (SKILL) study. Hearing (pure tone average of 0.5, 1, and 2 kHz) was assessed in the better hearing ear and categorized into normal hearing <25 dB HL; mild HI 26-40 dB HL; or moderate and greater HI>41 dB HL. The Useful Field of View Test (UFOV) was used to estimate the risk for adverse driving events. MANCOVA compared driving mobility between HI levels across time, adjusting for age, sex, race, hypertension, and stroke. Adjusting for these same covariates, Cox regression analyses examined incidence of driving cessation by HI across three years. - Results Individuals with moderate or greater HI performed poorly on the UFOV, indicating increased risk for adverse driving events (p<.001). No significant differences were found among older adults with varying levels of HI for driving mobility (ps>.05), including driving cessation rates (p=.38), across time. - Implications Although prior research indicates older adults with HI may be at higher risk for crashes, they may not modify driving over time. Further exploration of this issue is required to optimize efforts to improve driving safety and mobility among older adults.

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.

Genetic influences on handedness: data from 25,732 Australian and Dutch twin families

Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.

Sitting-time and 9-year all-cause mortality in older women

Background Studies of mid-aged adults provide evidence of a relationship between sitting-time and all-cause mortality, but evidence in older adults is limited. The aim is to examine the relationship between total sitting-time and all-cause mortality in older women. Methods The prospective cohort design involved 6656 participants in the Australian Longitudinal Study on Women's Health who were followed for up to 9 years (2002, age 76–81, to 2011, age 85–90). Self-reported total sitting-time was linked to all-cause mortality data from the National Death Index from 2002 to 2011. Cox proportional hazard models were used to examine the relationship between sitting-time and all-cause mortality, with adjustment for potential sociodemographic, behavioural and health confounders. Results There were 2003 (30.1%) deaths during a median follow-up of 6 years. Compared with participants who sat <4 h/day, those who sat 8–11 h/day had a 1.45 times higher risk of death and those who sat ≥11 h/day had a 1.65 times higher risk of death. These risks remained after adding sociodemographic and behavioural covariates, but were attenuated after adjustment for health covariates. A significant interaction (p=0.02) was found between sitting-time and physical activity (PA), with increased mortality risk for prolonged sitting only among participants not meeting PA guidelines (HR for sitting ≥8 h/day: 1.31, 95% CI 1.07 to 1.61); HR for sitting ≥11 h/day: 1.47, CI 1.15 to 1.93). Conclusions Prolonged sitting-time was positively associated with all-cause mortality. Women who reported sitting for more than 8 h/day and did not meet PA guidelines had an increased risk of dying within the next 9 years.

Impact of malnutrition on 12-month mortality following acute hip fracture

Background Studies investigating the relationship between malnutrition and post-discharge mortality following acute hip fracture yield conflicting results. This study aimed to determine whether malnutrition independently predicted 12-month post-fracture mortality after adjusting for clinically relevant covariates. Methods An ethics approved, prospective, consecutive audit was undertaken for all surgically treated hip fracture inpatients admitted to a dedicated orthogeriatric unit (November 2010–October 2011). The 12-month mortality data were obtained by a dual search of the mortality registry and Queensland Health database. Malnutrition was evaluated using the Subjective Global Assessment. Demographic (age, gender, admission residence) and clinical covariates included fracture type, time to surgery, anaesthesia type, type of surgery, post-surgery time to mobilize and post-operative complications (delirium, pulmonary and deep vein thrombosis, cardiac complications, infections). The Charlson Comorbidity Index was retrospectively applied. All diagnoses were confirmed by the treating orthogeriatrician. Results A total of 322 of 346 patients were available for audit. Increased age (P = 0.004), admission from residential care (P < 0.001), Charlson Comorbidity Index (P = 0.007), malnutrition (P < 0.001), time to mobilize >48 h (P < 0.001), delirium (P = 0.003), pulmonary embolism (P = 0.029) and cardiovascular complication (P = 0.04) were associated with 12-month mortality. Logistic regression analysis demonstrated that malnutrition (odds ratio (OR) 2.4 (95% confidence interval (CI) 1.3–4.7, P = 0.007)), in addition to admission from residential care (OR 2.6 (95% CI 1.3–5.3, P = 0.005)) and pulmonary embolism (OR 11.0 (95% CI 1.5–78.7, P = 0.017)), independently predicted 12-month mortality. Conclusions Findings substantiate malnutrition as an independent predictor of 12-month mortality in a representative sample of hip fracture inpatients. Effective strategies to identify and treat malnutrition in hip fracture should be prioritized.