Can slide positivity rates predict malaria transmission?

Background: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China. Methods: Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. Results: The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (beta = 1.244, p = 0.000) alone and combination (SPR, beta = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates. Conclusion: SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

The association between pterygium and conjunctival ultraviolet autofluorescence : The Norfolk Island Eye Study

Purpose: To investigate the association between conjunctival ultraviolet autofluorescence (UVAF), a biomarker of ocular ultraviolet radiation (UVR) exposure, and prevalent pterygium. Methods: We conducted a cross-sectional study on Norfolk Island, South Pacific. All permanent residents aged ‡15 were invited to participate. Participants completed a sun exposure questionnaire and underwent autorefraction and slit lamp biomicroscope examination. Area of conjunctival UVAF (sum of temporal ⁄ nasal area in right and left eyes) was determined using computerized methods. Multivariate logistic and linear regression models were used to estimate the associations with pterygia and UVAF, respectively. Results: Of 641 participants, 70 people (10.9%) had pterygium in one or both eyes, and prevalence was higher in males (15.0% versus 7.7%, p = 0.003). Significant independent associations with pterygium in any eye were UVAF (per 10 mm2) [odds ratio (OR) 1.16, 95% confidence interval (CI) 1.16–1.28, p = 0.002], tanning skin phenotype (OR 2.17,1.20–3.92, p = 0.010) and spending more than three-quarters of the day outside (OR 2.22, 1.20–4.09, p = 0.011). Increasing quartile of UVAF was associated with increased risk of pterygium following adjustment of age, sex and time outdoors (pTrend = 0.002). Independent associations with increasing UVAF (per 10 mm2) were decreasing age, time outdoors, skin type and male gender (all p < 0.001). UVAF area correlated well with the duration of outdoor activity (pTrend < 0.001). Conclusion: Pterygium occurs in approximately one-tenth of Norfolk Islanders. Increasing conjunctival UVAF is associated with prevalent pterygia, confirming earlier epidemiological, laboratory and ray-tracing studies that pterygia are associated with UVR. Protection from the sun should be encouraged to reduce the prevalence of pterygium in the community.

Air pollution, temperature and pediatric influenza in Brisbane, Australia

Previous studies have demonstrated the importance of weather variables in influencing the incidence of influenza. However, the role of air pollution is often ignored in identifying the environmental drivers of influenza. This research aims to examine the impacts of air pollutants and temperature on the incidence of pediatric influenza in Brisbane, Australia. Lab-confirmed daily data on influenza counts among children aged 0-14years in Brisbane from 2001 January 1st to 2008 December 31st were retrieved from Queensland Health. Daily data on maximum and minimum temperatures for the same period were supplied by the Australian Bureau of Meteorology. Winter was chosen as the main study season due to it having the highest pediatric influenza incidence. Four Poisson log-linear regression models, with daily pediatric seasonal influenza counts as the outcome, were used to examine the impacts of air pollutants (i.e., ozone (O3), particulate matter≤10μm (PM10) and nitrogen dioxide (NO2)) and temperature (using a moving average of ten days for these variables) on pediatric influenza. The results show that mean temperature (Relative risk (RR): 0.86; 95% Confidence Interval (CI): 0.82-0.89) was negatively associated with pediatric seasonal influenza in Brisbane, and high concentrations of O3 (RR: 1.28; 95% CI: 1.25-1.31) and PM10 (RR: 1.11; 95% CI: 1.10-1.13) were associated with more pediatric influenza cases. There was a significant interaction effect (RR: 0.94; 95% CI: 0.93-0.95) between PM10 and mean temperature on pediatric influenza. Adding the interaction term between mean temperature and PM10 substantially improved the model fit. This study provides evidence that PM10 needs to be taken into account when evaluating the temperature-influenza relationship. O3 was also an important predictor, independent of temperature.

Australian baby boomers switched to more environment friendly modes of transport during the global financial crisis

The global financial crisis (GFC) in 2008 rocked local, regional, and state economies throughout the world. Several intermediate outcomes of the GFC have been well documented in the literature including loss of jobs and reduced income. Relatively little research has, however, examined the impacts of the GFC on individual level travel behaviour change. To address this shortcoming, HABITAT panel data were employed to estimate a multinomial logit model to examine mode switching behaviour between 2007 (pre-GFC) and 2009 (post-GFC) of a baby boomers cohort in Brisbane, Australia—a city within a developed country that has been on many metrics the least affected by the GFC. In addition, a Poisson regression model was estimated to model the number of trips made by individuals in 2007, 2008, and 2009. The South East Queensland Travel Survey datasets were used to develop this model. Four linear regression models were estimated to assess the effects of the GFC on time allocated to travel during a day: one for each of the three travel modes including public transport, active transport, less environmentally friendly transport; and an overall travel time model irrespective of mode. The results reveal that individuals were more likely to switch to public transport who lost their job or whose income reduced between 2007 and 2009. Individuals also made significantly fewer trips in 2008 and 2009 compared to 2007. Individuals spent significantly less time using less environmentally friendly transport but more time using public transport in 2009. Baby boomers switched to more environmentally friendly travel modes during the GFC.

The influence of maternal infant feeding practices and beliefs on the expression of food neophobia in toddlers

Food neophobia is a highly heritable trait characterized by the rejection of foods that are novel or unknown and potentially limits dietary variety, with lower intake and preference particularly for fruits and vegetables. Understanding non-genetic (environmental) factors that may influence the expression of food neophobia is essential to improving children’s consumption of fruits and vegetables and encouraging the adoption of healthier diets. The aim of this study was to examine whether maternal infant feeding beliefs (at four months) were associated with the expression of food neophobia in toddlers and whether controlling feeding practices mediated this relationship. Participants were 244 first-time mothers (M = 30.4, SD = 5.1 years) allocated to the control group of the NOURISH randomized controlled trial. The relationships between infant feeding beliefs (Infant Feeding Questionnaire) at four months and controlling child feeding practices (Child Feeding Questionnaire) and food neophobia (Child Food Neophobia Scale) at 24 months were tested using correlational and multiple linear regression models (adjusted for significant covariates). Higher maternal Concern about infant under-eating and becoming underweight at four months was associated with higher child food neophobia at two years. Similarly, lower Awareness of infant hunger and satiety cues was associated with higher child food neophobia. Both associations were significantly mediated by mothers’ use of Pressure to eat. Intervening early to promote positive feeding practices to mothers may help reduce the use of controlling practices as children develop. Further research that can further elucidate the bi-directional nature of the mother-child feeding relationship is still required.

Environmental, personal, and genetic determinants of response to vitamin D supplementation in older adults

CONTEXT AND OBJECTIVE: Suboptimal vitamin D status can be corrected by vitamin D supplementation, but individual responses to supplementation vary. We aimed to examine genetic and nongenetic determinants of change in serum 25-hydroxyvitamin D (25(OH)D) after supplementation. DESIGN AND PARTICIPANTS: We used data from a pilot randomized controlled trial in which 644 adults aged 60 to 84 years were randomly assigned to monthly doses of placebo, 30 000 IU, or 60 000 IU vitamin D3 for 12 months. Baseline characteristics were obtained from a self-administered questionnaire. Eighty-eight single-nucleotide polymorphisms (SNPs) in 41 candidate genes were genotyped using Sequenom MassArray technology. Serum 25(OH)D levels before and after the intervention were measured using the Diasorin Liaison platform immunoassay. We used linear regression models to examine associations between genetic and nongenetic factors and change in serum 25(OH)D levels. RESULTS: Supplement dose and baseline 25(OH)D level explained 24% of the variability in response to supplementation. Body mass index, self-reported health status, and ambient UV radiation made a small additional contribution. SNPs in CYP2R1, IRF4, MC1R, CYP27B1, VDR, TYRP1, MCM6, and HERC2 were associated with change in 25(OH)D level, although only CYP2R1 was significant after adjustment for multiple testing. Models including SNPs explained a similar proportion of variability in response to supplementation as models that included personal and environmental factors. CONCLUSION: Stepwise regression analyses suggest that genetic variability may be associated with response to supplementation, perhaps suggesting that some people might need higher doses to reach optimal 25(OH)D levels or that there is variability in the physiologically normal level of 25(OH)D.

The relationship between number of fruits, vegetables, and noncore foods tried at age 14 months and food preferences, dietary intake patterns, fussy eating behavior, and weight status at age 3.7 years

Objective We examined whether exposure to a greater number of fruits, vegetables, and noncore foods (ie, nutrient poor and high in saturated fats, added sugars, or added salt) at age 14 months was related to children’s preference for and intake of these foods as well as maternal-reported food fussiness and measured child weight status at age 3.7 years. Methods This study reports secondary analyses of longitudinal data from mothers and children (n=340) participating in the NOURISH randomized controlled trial. Exposure was quantified as the number of food items (n=55) tried by a child from specified lists at age 14 months. At age 3.7 years, food preferences, intake patterns, and fussiness (also at age 14 months) were assessed using maternal-completed, established questionnaires. Child weight and length/height were measured by study staff at both age points. Multivariable linear regression models were tested to predict food preferences, intake patterns, fussy eating, and body mass index z score at age 3.7 years adjusting for a range of maternal and child covariates. Results Having tried a greater number of vegetables, fruits, and noncore foods at age 14 months predicted corresponding preferences and higher intakes at age 3.7 years but did not predict child body mass index z score. Adjusting for fussiness at age 14 months, having tried more vegetables at age 14 months was associated with lower fussiness at age 3.7 years. Conclusions These prospective analyses support the hypothesis that early taste and texture experiences influence subsequent food preferences and acceptance. These findings indicate introduction to a variety of fruits and vegetables and limited noncore food exposure from an early age are important strategies to improve later diet quality.

Cord blood 25-hydroxyvitamin D and fetal growth in the China-Anhui birth cohort study

We determined the association of cord blood 25-hydroxyvitamin D [25(OH)D] with birth weight and the risk of small for gestational age (SGA). As part of the China-Anhui Birth Cohort (C-ABC) study, we measured cord blood levels of 25(OH)D in 1491 neonates in Hefei, China. The data on maternal sociodemographic characteristics, health status, lifestyle, birth outcomes were prospectively collected. Multiple regression models were used to estimate the association of 25(OH)D levels with birth weight and the risk of SGA. Compared with neonates in the lowest decile of cord blood 25(OH)D levels, neonates in four deciles (the fourth, fifth, sixth and seventh deciles) had significantly increased birth weight and decreased risk of SGA. Multiple linear regression models showed that per 10 nmol/L increase in cord blood 25(OH)D, birth weight increased by 61.0 g (95% CI: 31.9, 89.9) at concentrations less than 40 nmol/L, and then decreased by 68.5 g (95% CI: −110.5, −26.6) at concentrations from 40 to 70 nmol/L. This study provides the first epidemiological evidence that there was an inverted U shaped relationship between neonatal vitamin D status and fetal growth, and the risk of SGA reduced at moderate concentration.

Positive associations of serum Perfluoroalkyl substances with uric acid and hyperuricemia in children from Taiwan

To investigate the risk of hyperuricemia in relation to Perfluoroalkyl substances (PFASs) in children from Taiwan, 225 Taiwanese children aged 12-15 years were recruited from 2009 to 2010. Linear and logistic regression models were employed to examine the influence of PFASs on serum uric acid levels. Findings revealed that eight of ten PFASs analyses were detected in > 94% of the participants' serum samples. Multivariate linear regression models revealed that perfluorooctanic acid (PFOA) was positively associated with serum uric acid levels (β=0.1463, p<0.05). Of all the PFASs analyses, only PFOA showed a significant effect on elevated levels of hyperuricemia (aOR=2.16, 95%CI: 1.29-3.61). When stratified by gender, the association between serum PFOA and uric acid levels was only evident among boys (aOR=2.76, 95%CI: 1.37-5.56). In conclusion, PFOA was found to be associated with elevated serum levels of uric acid in Taiwanese children, especially boys. Further research is needed to elucidate these links.

Damping structure selection in nonlinear ship manoeuvring models

This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stochastic models, which is postulated based on previous work in the literature. Then a nested test of hypothesis problem is considered. The testing reduces to a recursive comparison of two competing models, for which optimal tests in the Neyman sense exist. The method yields a preferred model structure and its initial parameter estimates. Alternatively, the method can give a reduced set of likely models. Using simulated data we study how the selection method performs when there is both uncorrelated and correlated noise in the measurements. The first case is related to instrumentation noise, whereas the second case is related to spurious wave-induced motion often present during sea trials. We then consider the model structure selection of a modern high-speed trimaran ferry from full scale trial data.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Temperature variation between neighboring days and mortality: a distributed lag non-linear analysis

Objectives To investigate whether a sudden temperature change between neighboring days has significant impact on mortality. Methods A Poisson generalized linear regression model combined with a distributed lag non-linear models was used to estimate the association of temperature change between neighboring days with mortality in a subtropical Chinese city during 2008–2012. Temperature change was calculated as the current day’s temperature minus the previous day’s temperature. Results A significant effect of temperature change between neighboring days on mortality was observed. Temperature increase was significantly associated with elevated mortality from non-accidental and cardiovascular diseases, while temperature decrease had a protective effect on non-accidental mortality and cardiovascular mortality. Males and people aged 65 years or older appeared to be more vulnerable to the impact of temperature change. Conclusions Temperature increase between neighboring days has a significant adverse impact on mortality. Further health mitigation strategies as a response to climate change should take into account temperature variation between neighboring days.

Rank regression for analyzing ordinal qualitative data for treatment comparison

Ordinal qualitative data are often collected for phenotypical measurements in plant pathology and other biological sciences. Statistical methods, such as t tests or analysis of variance, are usually used to analyze ordinal data when comparing two groups or multiple groups. However, the underlying assumptions such as normality and homogeneous variances are often violated for qualitative data. To this end, we investigated an alternative methodology, rank regression, for analyzing the ordinal data. The rank-based methods are essentially based on pairwise comparisons and, therefore, can deal with qualitative data naturally. They require neither normality assumption nor data transformation. Apart from robustness against outliers and high efficiency, the rank regression can also incorporate covariate effects in the same way as the ordinary regression. By reanalyzing a data set from a wheat Fusarium crown rot study, we illustrated the use of the rank regression methodology and demonstrated that the rank regression models appear to be more appropriate and sensible for analyzing nonnormal data and data with outliers.

Rank regression analysis of correlated water quality data from South East Queensland

With growing population and fast urbanization in Australia, it is a challenging task to maintain our water quality. It is essential to develop an appropriate statistical methodology in analyzing water quality data in order to draw valid conclusions and hence provide useful advices in water management. This paper is to develop robust rank-based procedures for analyzing nonnormally distributed data collected over time at different sites. To take account of temporal correlations of the observations within sites, we consider the optimally combined estimating functions proposed by Wang and Zhu (Biometrika, 93:459-464, 2006) which leads to more efficient parameter estimation. Furthermore, we apply the induced smoothing method to reduce the computational burden. Smoothing leads to easy calculation of the parameter estimates and their variance-covariance matrix. Analysis of water quality data from Total Iron and Total Cyanophytes shows the differences between the traditional generalized linear mixed models and rank regression models. Our analysis also demonstrates the advantages of the rank regression models for analyzing nonnormal data.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.