Infant and early childhood dietary predictors of overweight at age 8 years in the CAPS population

BACKGROUND/OBJECTIVES: Programs to address obesity are a high priority for public policy especially for young children. Research into dietary determinants of obesity is challenging but important for rational planning of interventions to prevent obesity, given that both diet and energy expenditure influence weight status. We investigated whether early life dietary factors were predictive of weight status at 8 years in a cohort of Australian children. SUBJECTS/METHODS: We used data from the Childhood Asthma Prevention Study-a birth cohort at high risk of asthma. Dietary data (3-day weighed food records) were collected at 18 months and height, weight and waist circumference were collected at 8 years. We assessed the relationship between dietary predictor variables and measures of adiposity using linear regression. RESULTS: Intakes of protein, meat and fruit at age 18 months were positively associated with measures of adiposity at age 8 years, namely, body mass index and/or waist circumference. We also showed a significant negative relationship between these measures of adiposity at 8 years and intake at 18 months of dairy foods as a percent of total energy, and intake of energy dense cereal-based foods such as cookies and crackers. CONCLUSIONS: This birth cohort study with rigorous design, measures and analyses, has shown a number of associations between early dietary intake and subsequent adiposity that contribute to the growing evidence base in this important field.National Health and Medical Research Council of AustraliaHjärt- och LungfondenSvenska LäkarsällskapetManuscrip

Breastfeeding, asthma, and allergy : a tale of two cities

BACKGROUND: The effect of breastfeeding duration on subsequent asthma and allergy remains the subject of much controversy. OBJECTIVE: To investigate whether differences in study design or disease-related exposure modification were the cause of the differences in study findings. METHOD: The data from two cohorts, the Childhood Asthma Prevention Study (CAPS) from Australia and the Barn Allergi Miljo Stockholm cohort from Sweden, which had reported different findings on the association between breastfeeding and asthma, were combined. For this analysis, the definitions for breastfeeding, asthma, and allergy were harmonized. Subjects were included if they had at least one parent with wheeze or asthma and had a gestational age of more than 36 wks (combined n = 882). The risk of disease-related exposure modification was assessed using survival analysis. RESULTS: Breastfeeding reduced the risk of asthma at 4/5 and 8 yrs of age in children with a family history of asthma. The effect was stronger in the Swedish cohort. Breastfeeding had no effect on the prevalence of sensitization to inhaled allergens in this cohort with a family history of asthma but was a risk factor for sensitization to cow's milk, peanuts, and eggs in the CAPS cohort at 4/5 yrs and in the combined cohort at 8 yrs. There was no evidence to support the existence of disease-related exposure modification in either cohort. CONCLUSION: These findings point to the importance of harmonization of features of study design, including subject selection criteria and variable definitions, in resolving epidemiological controversies such as those surrounding the impact of breastfeeding on asthma and allergic sensitization.National Health and Medical Research Council of AustraliaStockholm County CouncilHjärt- och LungfondenThe Swedish Asthma and Allergy AssociationVetenskapsrådetThe Centre for Allergy research Karolinska InstitutetManuscrip

Prospective validation of a checklist to predict short-term death in older patients after emergency department admission in Australia and Ireland

Abstract Background Emergency departments (EDs) are pressured environment where patients with supportive and palliative care needs may not be identified. We aimed to test the predictive ability of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist to flag patients at risk of death within 3 months who may benefit from timely end-of-life discussions. Methods Prospective cohorts of >65-year-old patients admitted for at least one night via EDs in five Australian hospitals and one Irish hospital. Purpose-trained nurses and medical students screened for frailty using two instruments concurrently and completed the other risk factors on the CriSTAL tool at admission. Postdischarge telephone follow-up was used to determine survival status. Logistic regression and bootstrapping techniques were used to test the predictive accuracy of CriSTAL for death within 90 days of admission as primary outcome. Predictability of in-hospital death was the secondary outcome. Results A total of 1,182 patients, with median age 76 to 80 years (IRE-AUS), were included. The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% confidence interval [CI] = 7.7–8.6) versus 5.7 (95% CI = 5.1–6.2) and Irish mean of 7.7 (95% CI = 6.9–8.5) versus 5.7 (95% CI = 5.1–6.2). The model with Fried frailty score was optimal for the derivation (Australian) cohort but prediction with the Clinical Frailty Scale (CFS) was also good (areas under the receiver-operating characteristic [AUROC] = 0.825 and 0.81, respectively). Values for the validation (Irish) cohort were AUROC = 0.70 with Fried and 0.77 using CFS. A minimum of five of 29 variables were sufficient for accurate prediction, and a cut point of 7+ or 6+ depending on the cohort was strongly indicative of risk of death. The most significant independent predictor of short-term death in both cohorts was frailty, carrying a twofold risk of death. CriSTAL's accuracy for in-hospital death prediction was also good (AUROC = 0.795 and 0.81 in Australia and Ireland, respectively), with high specificity and negative predictive values. Conclusions The modified CriSTAL tool (with CFS instead of Fried's frailty instrument) had good discriminant power to improve certainty of short-term mortality prediction in both health systems. The predictive ability of models is anticipated to help clinicians gain confidence in initiating earlier end-of-life discussions. The practicalities of embedding screening for risk of death in routine practice warrant further investigation

Riječ uredništva

BACKGROUND: Methods for estimating air pollutant exposures for epidemiological studies are becoming more complex in an effort to minimise exposure error and its associated bias. While land use regression (LUR) modelling is now an established method, there has been little comparison between LUR and other recent, more complex estimation methods. Our aim was to develop a LUR model to estimate intra-city exposures to nitrogen dioxide (NO2) for a Sydney cohort, and to compare those with estimates from a national satellite-based LUR model (Sat-LUR) and a regional Bayesian Maximum Entropy (BME) model. METHODS: Satellite-based LUR and BME estimates were obtained using existing models. We used methods consistent with the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to develop LUR models for NO2 and NOx. We deployed 46 Ogawa passive samplers across western Sydney during 2013/2014 and acquired data on land use, population density, and traffic volumes for the study area. Annual average NO2 concentrations for 2013 were estimated for 947 addresses in the study area using the three models: standard LUR, Sat-LUR and a BME model. Agreement between the estimates from the three models was assessed using interclass correlation coefficient (ICC), Bland-Altman methods and correlation analysis (CC). RESULTS: The NO2 LUR model predicted 84% of spatial variability in annual mean NO2 (RMSE: 1.2 ppb; cross-validated R2: 0.82) with predictors of major roads, population and dwelling density, heavy traffic and commercial land use. A separate model was developed that captured 92% of variability in NOx (RMSE 2.3 ppb; cross-validated R2: 0.90). The annual average NO2 concentrations were 7.31 ppb (SD: 1.91), 7.01 ppb (SD: 1.92) and 7.90 ppb (SD: 1.85), for the LUR, Sat-LUR and BME models respectively. Comparing the standard LUR with Sat-LUR NO2 cohort estimates, the mean estimates from the LUR were 4% higher than the Sat-LUR estimates, and the ICC was 0.73. The Pearson's correlation coefficients (CC) for the LUR vs Sat-LUR values were r = 0.73 (log-transformed data) and r = 0.69 (untransformed data). Comparison of the NO2 cohort estimates from the LUR model with the BME blended model indicated that the LUR mean estimates were 8% lower than the BME estimates. The ICC for the LUR vs BME estimates was 0.73. The CC for the logged LUR vs BME estimates was r = 0.73 and for the unlogged estimates was r = 0.69. CONCLUSIONS: Our LUR models explained a high degree of spatial variability in annual mean NO2 and NOx in western Sydney. The results indicate very good agreement between the intra-city LUR, national-scale sat-LUR, and regional BME models for estimating NO2 for a cohort of children residing in Sydney, despite the different data inputs and differences in spatial scales of the models, providing confidence in their use in epidemiological studies

Estimating the contribution of subclinical tuberculosis disease to transmission: An individual patient data analysis from prevalence surveys.

BACKGROUND: Individuals with bacteriologically confirmed pulmonary tuberculosis (TB) disease who do not report symptoms (subclinical TB) represent around half of all prevalent cases of TB, yet their contribution to Mycobacterium tuberculosis (Mtb) transmission is unknown, especially compared to individuals who report symptoms at the time of diagnosis (clinical TB). Relative infectiousness can be approximated by cumulative infections in household contacts, but such data are rare. METHODS: We reviewed the literature to identify studies where surveys of Mtb infection were linked to population surveys of TB disease. We collated individual-level data on representative populations for analysis and used literature on the relative durations of subclinical and clinical TB to estimate relative infectiousness through a cumulative hazard model, accounting for sputum-smear status. Relative prevalence of subclinical and clinical disease in high-burden settings was used to estimate the contribution of subclinical TB to global Mtb transmission. RESULTS: We collated data on 414 index cases and 789 household contacts from three prevalence surveys (Bangladesh, the Philippines, and Viet Nam) and one case-finding trial in Viet Nam. The odds ratio for infection in a household with a clinical versus subclinical index case (irrespective of sputum smear status) was 1.2 (0.6-2.3, 95% confidence interval). Adjusting for duration of disease, we found a per-unit-time infectiousness of subclinical TB relative to clinical TB of 1.93 (0.62-6.18, 95% prediction interval [PrI]). Fourteen countries across Asia and Africa provided data on relative prevalence of subclinical and clinical TB, suggesting an estimated 68% (27-92%, 95% PrI) of global transmission is from subclinical TB. CONCLUSIONS: Our results suggest that subclinical TB contributes substantially to transmission and needs to be diagnosed and treated for effective progress towards TB elimination. FUNDING: JCE, KCH, ASR, NS, and RH have received funding from the European Research Council (ERC) under the Horizon 2020 research and innovation programme (ERC Starting Grant No. 757699) KCH is also supported by UK FCDO (Leaving no-one behind: transforming gendered pathways to health for TB). This research has been partially funded by UK aid from the UK government (to KCH); however, the views expressed do not necessarily reflect the UK government's official policies. PJD was supported by a fellowship from the UK Medical Research Council (MR/P022081/1); this UK-funded award is part of the EDCTP2 programme supported by the European Union. RGW is funded by the Wellcome Trust (218261/Z/19/Z), NIH (1R01AI147321-01), EDTCP (RIA208D-2505B), UK MRC (CCF17-7779 via SET Bloomsbury), ESRC (ES/P008011/1), BMGF (OPP1084276, OPP1135288 and INV-001754), and the WHO (2020/985800-0)

Cellular and molecular mechanisms of immunomodulation in the brain through environmental enrichment

Recent studies on environmental enrichment (EE) have shown cytokines, cellular immune components [e.g., T lymphocytes, natural killer (NK) cells], and glial cells in causal relationship to EE in bringing out changes to neurobiology and behavior. The purpose of this review is to evaluate these neuroimmune mechanisms associated with neurobiological and behavioral changes in response to different EE methods. We systematically reviewed common research databases. After applying all inclusion and exclusion criteria, 328 articles remained for this review. Physical exercise (PE), a form of EE, elicits anti-inflammatory and neuromodulatory effects through interaction with several immune pathways including interleukin (IL)-6 secretion from muscle fibers, reduced expression of Toll-like receptors on monocytes and macrophages, reduced secretion of adipokines, modulation of hippocampal T cells, priming of microglia, and upregulation of mitogen-activated protein kinase phosphatase-1 in central nervous system. In contrast, immunomodulatory roles of other enrichment methods are not studied extensively. Nonetheless, studies showing reduction in the expression of IL-1β and tumor necrosis factor-α in response to enrichment with novel objects and accessories suggest anti-inflammatory effects of novel environment. Likewise, social enrichment, though considered a necessity for healthy behavior, results in immunosuppression in socially defeated animals. This has been attributed to reduction in T lymphocytes, NK cells and IL-10 in subordinate animals. EE through sensory stimuli has been investigated to a lesser extent and the effect on immune factors has not been evaluated yet. Discovery of this multidimensional relationship between immune system, brain functioning, and EE has paved a way toward formulating environ-immuno therapies for treating psychiatric illnesses with minimal use of pharmacotherapy. While the immunomodulatory role of PE has been evaluated extensively, more research is required to investigate neuroimmune changes associated with other enrichment methods.Gaurav Singhal, Emily J. Jaehne, Frances Corrigan and Bernhard T. Baun

Exploring the development and heterogeneity of childhood diseases including asthma, allergy and obesity in the Childhood Asthma Prevention Study

This thesis presents a body of work exploring the development and heterogeneous nature of common childhood diseases: asthma, allergic disease and obesity. Statistical models, which increase in complexity from a linear regression model to finite mixture models including a growth mixture model, latent class analysis and a latent transition analysis, were used to examine risk factors and define latent subgroups of these childhood diseases. This thesis utilises data from the first 11.5 years of the Childhood Asthma Prevention Study (CAPS), a birth cohort recruited on the basis of having a first degree relative with asthma. Five research papers form the body of this thesis. In conclusion, this thesis has used data from an established birth cohort in innovative ways, by applying simple and complex statistical models, to provide new insights into the development and heterogeneity of asthma, allergy and obesity. The results of this research have contributed to the literature on asthma, allergy and obesity by identifying specific subgroups within each of these childhood diseases that may benefit from increased monitoring and a targeted intervention or treatment. This work demonstrates the potential for finite mixture models to be applied to other complex heterogeneous diseases

Performance of the LACE index to predict 30-day hospital readmissions in patients with chronic obstructive pulmonary disease

Background and objective: Patients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (COPD) have a high 30-day hospital readmission rate, which has a large impact on the health care system and patients’ quality of life. The use of a prediction model to quantify a patient’s risk of readmission may assist in directing interventions to patients who will benefit most. The objective of this study was to calculate the rate of 30-day readmissions and evaluate the accuracy of the LACE index (length of stay, acuity of admission, co-morbidities, and emergency department visits within the last 6 months) for 30-day readmissions in a general hospital population of COPD patients. Methods: All patients admitted with a principal diagnosis of COPD to Liverpool Hospital, a tertiary hospital in Sydney, Australia, between 2006 and 2016 were included in the study. A LACE index score was calculated for each patient and assessed using receiver operator characteristic curves. Results: During the study period, 2,662 patients had 5,979 hospitalizations for COPD. Four percent of patients died in hospital and 25% were readmitted within 30 days; 56% of all 30-day readmissions were again due to COPD. The most common reasons for readmission, following COPD, were heart failure, pneumonia, and chest pain. The LACE index had moderate discriminative ability to predict 30-day readmission (C-statistic =0.63). Conclusion: The 30-day hospital readmission rate was 25% following hospitalization for COPD in an Australian tertiary hospital and as such comparable to international published rates. The LACE index only had moderate discriminative ability to predict 30-day readmission in patients hospitalized for COPD