Physiological Daily Inhalation Rates for Free-Living Individuals Aged 1 Month to 96 Years,Using Data from Doubly Labeled Water Measurements: A Proposal for Air Quality Criteria,Standard Calculations and Health Risk Assessment

Reported disappearance rates of oral doses of doubly labeled water (²H₂O and H₂ ¹⁸O) in urine, monitored by gas-isotope-ratio mass spectrometry for an aggregate period of over 30,000 days and completed with indirect calorimetry and nutritional balance measurements, have been used to determine physiological daily inhalation rates for 2210 individuals aged 3 weeks to 96 years. Rates in m³/kg-day for healthy normal-weight individuals (n = 1252) were higher by 6 to 21% compared to their overweight/obese counterparts (n = 679). Rates for healthy normal-weight males and females drop by about 66 to 75% within the course of a lifetime. Infants and children between the age of 3 weeks to less than 7 years inhale 1.6 to 4.3 times more air (0.395 ± 0.048 to 0.739 ± 0.071 m³/kg-day, mean ± S.D., n = 581) than adults aged 23 to 96 years (0.172 ± 0.037 to 0.247 ± 0.039 m³/kg-day, n = 388). The 99th percentile rate of 0.725 m³/kg-day based on measurements for boys aged 2.6 to less than 6 months is recommended for air quality criteria and standard calculation for non-carcinogenic compounds pertaining to individuals of any age or gender (normality confirmed using the Shapiro-Wilk test, p ≥ 0.05). This rate is 2.5-fold more protective than the daily inhalation estimate of 0.286 m³/kg-day published by the Federal Register in 1980 (i.e., 20 m³/day for a 70-kg adult). It ensures that very few newborns aged 1 month and younger, less than 1% of infants aged 2.6 to less than 6 months and of course no older individuals up to 96 years of age inhale more toxic chemicals than associated safe doses which are not anticipated to result in any adverse effects in humans, when air concentration reaches the resulting air quality criteria and standard values. This rate is also protective for underweight, overweight, and obese individuals. Finally, as far as newborns are concerned, a rate of 0.956 m³/kg-day based on the 99th percentile estimates is recommended for short-term criteria and standard calculations for toxic chemicals that yield adverse effects over instantaneous to short-term duration.     

Are all distributions of risk with the same 95thpercentile equally acceptable?

When evaluating a probabilistic health risk assessment, say at a hazardous waste site, risk managers need a risk management policy that distinguishes an acceptable distribution of risks to individuals in a population from an unacceptable one. If a risk manager decides that the distribution of risk for the status quo is unacceptable, then a risk assessor needs a way to compute cleanup targets, i.e., the risk assessor needs a policy statement against which to estimate distributions of exposure point concentrations which, if engineered at a site, will achieve an acceptable distribution of risk. Some regulatory agencies base acceptability on whether the 95^th percentile of the risk distribution falls at or below a given value, without considering the behavior of the rest of the distribution. As regulatory agencies adopt risk management policies for use with probabilistic risk assessments, we recommend that they base their new policies on two simultaneously binding constraints‐one on an upper percentile and one on the arithmetic mean of the distribution of risk‐in addition to other non‐risk criteria.     

Probability Density Functions Describing 24-Hour Inhalation Rates For Use in Human Health Risk Assessments

A Monte Carlo simulation was undertaken to estimate the amount of air inhaled over a typical 24-hour period by six age groups of Canadians. The objective of the simulation was to derive probability density functions that could be used to describe inhalation rates in probabilistic health risk assessments involving airborne contaminants. The six age groups considered were those typically employed in human health risk assessments in Canada: infants (aged 0 to 6 months), toddlers (aged 7 months to 4 years), children (aged 5 to 11 years), teenagers (aged 12 to 19 years), adults (aged 20 to 59 years), and seniors (aged 60 years and older). The resulting distributions are considered equally applicable to Americans as Canadians, however, since the study relied heavily on time-activity information gathered in the USA. Existing time-activity and breathing rate studies were reviewed in order to define random variables describing probable durations that North Americans spend at various levels of activity and their probable inhalation rates while at each level of activity. These random variables were combined in a Monte Carlo simulation to empirically generate probability density functions describing 24-hour inhalation rates for each age group. The simulation suggested that most age groups' 24 hour inhalation rates can be represented with log-normal probability density functions. Arithmetic mean values and standard deviations for these distributions are as follows: approximately 9.3 ± 2.4?m³/day for toddlers; 14.6 ± 3.0?m³/day for children; 15.8 ± 3.7?m³/day for teenagers; 16.2 ± 3.8?m³/day for adults; and 14.2 ± 3.3?m³/day for seniors. The distribution of infants' 24-hour inhalation rates was found to be better represented by a normal distribution than a log-normal distribution. The mean and standard deviation for the infants' normal distribution are 2.1 ± 0.58?m³/day. Inhalation rates were also estimated separately for male and female toddlers, children, teenagers, adults and seniors. These estimates suggested that males inhale on average 8% to 27% more air than females of the same age. Because infants' activity patterns and minute volumes did not appear to be strongly correlated with gender, a single probability density function was deemed satisfactory to describe male and female infants' 24-hour inhalation rates.     

Impact of Random Variables Probability Distribution on Public Health Risk Assessment from Contaminated Soil

Probabilistic methods are now being applied increasingly to public health risk assessment instead of the deterministic, conservative, point estimates. An essential part of the probabilistic methods is the selection of probability distribution functions to represent the uncertainty of the random variables considered. We study the effect of selection of different probability distribution functions on the probabilistic outcome using the first-order reliability method (FORM). An example of cancer risk resulting from dermal contact with benzo(a)pyrene (BaP)-contaminated soil is given. Cancer potency factor, soil concentration, and fraction of skin area exposed were assigned normal, lognormal, and uniform probability distribution functions, and the effect of probability of exceeding a target risk level (termed the probability of failure) and sensitivity measures were studied. We investigated the question: what happens when one assumes different distribution shapes with the same mean and standard deviation? The results indicate that the selection of a probability distribution function for the random variables had a moderate impact on the probability of failure when the target risk is at the 50th percentile level, while the impact was much larger for a 95th target risk percentile. We conclude that the probability distribution will have a large impact because in most cases the regulatory threshold risk is at the tail end of the risk distribution. The impact of the distributions on probabilistic sensitivity, however, showed a reversed trend, where the impact was slightly more appreciable for the 50th percentile than for the 95th percentile. The selection of distribution shape did not, however, alter the order of probabilistic sensitivity of the basic random variables.     

A modeling procedure to predict cancer risks associated with inhalable oil dust from Kuwait oil lakes

A model was constructed to estimate cancer risks associated with PM₁₀‐bound polycydic aromatic hydrocarbons (PAHs) from Kuwait oil lakes. The design of the risk model was based on a conceptual “chain of events”; leading from levels of PAH compounds in oil lakes, erosion of oil dust and input into the atmosphere, to contaminant concentration in air, to actual human exposure in residential areas. Uncertainties in the “chain of events”; model were addressed using Monte Carlo techniques. To identify the exposure duration of concern [duration beyond which risk becomes unacceptable (i.e. Risk > 10^‐6)], four exposure durations were tested 10, 20, 40, 70 years. 40 years was identified to be the exposure duration of concern based on the 95th percen‐tile of the risk distribution. As a result, the acceptability of risk was specified in terms of a single constraint on the 95^th percentile of the risk distribution evaluated after 40 years of exposure: 0 < Risk (40 y)₀.₉₅ ≤ 10^‐6. Based on this constraint, it was estimated that a removal rate of 217, 793.27 m³/year to be an adequate action for risk management. The northern oil lakes were identified as the lakes of most concern when inhalation exposures are considered.     

Cerebrospinal fluid glucose and lactate: age-specific reference values and implications for clinical practice

Cerebrospinal fluid (CSF) analysis is an important tool in the diagnostic work-up of many neurological disorders, but reference ranges for CSF glucose, CSF/plasma glucose ratio and CSF lactate based on studies with large numbers of CSF samples are not available. Our aim was to define age-specific reference values. In 1993 The Nijmegen Observational CSF Study was started. Results of all CSF samples that were analyzed between 1993 and 2008 at our laboratory were systematically collected and stored in our computerized database. After exclusion of CSF samples with an unknown or elevated erythrocyte count, an elevated leucocyte count, elevated concentrations of bilirubin, free hemoglobin, or total protein 9,036 CSF samples were further studied for CSF glucose (n = 8,871), CSF/plasma glucose ratio (n = 4,516) and CSF lactate values (n = 7,614). CSF glucose, CSF/plasma glucose ratio and CSF lactate were age-, but not sex dependent. Age-specific reference ranges were defined as 5–95^th percentile ranges. CSF glucose 5^th percentile values ranged from 1.8 to 2.9 mmol/L and 95^th percentile values from 3.8 to 5.6 mmol/L. CSF/plasma glucose ratio 5^th percentile values ranged from 0.41 to 0.53 and 95^th percentile values from 0.82 to 1.19. CSF lactate 5^th percentile values ranged from 0.88 to 1.41 mmol/L and 95^th percentile values from 2.00 to 2.71 mmol/L. Reference ranges for all three parameters were widest in neonates and narrowest in toddlers, with lower and upper limits increasing with age. These reference values allow a reliable interpretation of CSF results in everyday clinical practice. Furthermore, hypoglycemia was associated with an increased CSF/plasma glucose ratio, whereas hyperglycemia did not affect the CSF/plasma glucose ratio.     

Severe Obesity and Cardiometabolic Risk in Children: Comparison from Two International Classification Systems

Objectives

There is no agreed-upon definition for severe obesity (Sev-OB) in children. We compared estimates of Sev-OB as defined by different cut-points of body mass index (BMI) from the Centers for Disease Control and Prevention (CDC) or the World Health Organization (WHO) curves and the ability of each set of cut-points to screen for the presence of cardiometabolic risk factors.

Research Design and Methods

Cross-sectional, multicenter study involving 3,340 overweight/obese young subjects. Sev-OB was defined as BMI ≥99^th percentile or ≥1.2 times the 95^th percentile of the CDC or the WHO curves. High blood pressure, hypertriglyceridemia, low High Density Lipoprotein -cholesterol and impaired fasting glucose were considered as cardiometabolic risk factors.

Results

The estimated prevalence of Sev-OB varied widely between the two reference systems. Either using the cut-point ≥99^th percentile or ≥1.2 times the 95^th percentile, less children were defined as Sev-OB by CDC than WHO (46.8 vs. 89.5%, and 63.3 vs. 80.4%, respectively p<0.001). The CDC 99^th percentile had lower sensitivity (58.5 vs 94.2), higher specificity (57.6 vs 12.3) and higher positive predictive value (34.4 vs 28.9) than WHO in identifying obese children with ≥2 cardiometabolic risk factors. These differences were mitigated using the 1.2 times the 95^th percentile (sensitivity 73.9 vs. 88.1; specificity 40.7 vs. 22.5; positive predictive value 32.1 vs. 30.1). Substantial agreement between growth curves was found using the 1.2 times the 95^th percentile, in particular in children ≤10 years.

Conclusions

Estimates of Sev-OB and cardiometabolic risk as defined by different cut-points of BMI are influenced from the reference systems used. The 1.2 times the 95^th percentile of BMI of either CDC or WHO standard has a discriminatory advantage over the 99^th percentile for identifying severely obese children at increased cardiometabolic risk, particularly under 10 years of age.     

Height at Late Adolescence and Incident Diabetes among Young Men

Background

Short stature was suggested as a risk factor for diabetes onset among middle age individuals, but whether this is the case among young adults is unclear. Our goal was to assess the association between height and incident diabetes among young men.

Methods and Findings

Incident diabetes was assessed among 32,055 men with no history of diabetes, from the prospectively followed young adults of the MELANY cohort. Height was measured at two time points; at adolescence (mean age 17.4±0.3 years) and grouped according to the US-CDC percentiles and at young adulthood (mean age 31.0±5.6 years). Cox proportional hazards models were applied. There were 702 new cases of diabetes during a mean follow-up of 6.3±4.3 years. There was a significant increase in the crude diabetes incidence rate with decreasing adolescent height percentile, from 4.23 cases/10⁴ person-years in the <10^th percentile group to 2.44 cases/10⁴ person-years in the 75^th≤ percentile group. These results persisted when clinical and biochemical diabetes risk factors were included in multivariable models. Compared to the 75^th≤ percentile group, height below the 10^th percentile was associated with a hazard ratio (HR) of 1.64 (95%CI 1.09–2.46, p = 0.017) for incident diabetes after adjustment for age, body mass index (BMI), fasting plasma glucose, HDL-cholesterol and triglyceride levels, white blood cells count, socioeconomic status, country of origin, family history of diabetes, sleep quality and physical activity. At age 30 years, each 1-cm decrement in adult height was associated with a 2.5% increase in diabetes adjusted risk (HR 1.025, 95%CI 1.01–1.04, p = 0.001).

Conclusions

Shorter height at late adolescence or young adulthood was associated with an increased risk of incident diabetes among young men, independent of BMI and other diabetes risk factors.     

Normative references of heart rate variability and salivary alpha-amylase in a healthy young male population

Background

This study aimed to present normative reference values of heart rate variability and salivary alpha-amylase in a healthy young male population with a particular focus on their distribution and reproducibility.

Methods

The short-term heart rate variability of 417 young healthy Japanese men was studied. Furthermore, salivary alpha-amylase was measured in 430 men. The average age of the subjects were 21.9 years with standard deviation of 1.6 years. Interindividual variations in heart rate variability indices and salivary alpha-amylase levels were plotted as histograms. Data are presented as the mean, median, standard deviation, coefficient of variation, skewness, kurtosis, and fifth and 95th percentiles of each physiological index.

Results

Mean recorded values were heart period 945.85 ms, log-transformed high frequency component 9.84 ln-ms², log-transformed low frequency component 10.42 ln-ms², log-transformed low frequency to high frequency ratio 0.58 ln-ratio, standard deviation of beat-to-beat interval 27.17 ms and root mean square of successive difference 37.49 ms. The mean value of raw salivary alpha-amylase was 17.48 U/mL, square root salivary alpha-amylase 3.96 sqrt[U/mL] and log-transformed salivary alpha-amylase 2.65 ln[U/mL]. Log-transformed heart rate variability indices exhibited almost symmetrical distributions; however, time-domain indices of heart rate variability (standard deviation of beat-to-beat interval and root mean square of successive difference) exhibited right-skewed (positive skewness) distributions. A considerable right-skewed distribution was observed for raw salivary alpha-amylase. Logarithmic transformation improved the distribution of salivary alpha-amylase, although square root transformation was insufficient. The day-to-day reproducibility of these indices was assessed using intraclass correlation coefficients. Intraclass correlation coefficients of most heart rate variability and salivary indices were approximately 0.5 to 0.6. Intraclass correlation coefficients of raw salivary markers were approximately 0.6, which was similar to those of heart rate variability; however, log transformation of the salivary markers did not considerably improve their reproducibility. Correlations between sympathetic indicators of heart rate variability and salivary alpha-amylase were not observed.

Conclusion

Because the sample population examined in this study involved limited age and gender variations, the present results were independent of these factors and were indicative of pure interindividual variation.     

Monitoring of mycotoxin biomarkers in the Czech Republic

AFM₁ was determined in 72 (72%) samples of human urine, range 19-6064 pg/g creatinine, mean 367 pg/g creatinine, median 158 pg/g creatinine and 90% percentile 755 pg/g creatinine in 1997. AFM₁ was determined in 46 (43.8%) samples of human urine, range 21-19219 pg/g creatinine, mean 414 pg/g creatinine, median 96 pg/g creatinine and 90% percentile 415 pg/g creatinine in 1998. OTA was determined in 2077 (94.2%) samples of human serum, range 0.1–13.7 μg/L, mean 0.28 μg/L, median 0.2 μg/L and 90% percentile 0.5 μg/L in 1994–2002. OTA was determined in 12 (40%) samples of human kidneys, range 0.1–0.2 μg/kg, mean 0.07 μg/kg, and median 0.05 μg/kg in 2001. Presented at the 26^th Mykotoxin-Workshop in Herrsching, Germany, May 17–19, 2004.     

Probabilistic Risk Assessment and Risk Mapping of Sediment Metals in Sydney Harbour Embayments

Sediment metal concentrations in embayments of Sydney Harbour, acquired from the literature and from samples collected for this study, were used to generate contaminant probability density distributions using AQUARISK. The sediment metal concentrations often exceeded Australia's interim sediment quality guidelines. Similarly, estuarine spiked sediment toxicity test literature provided adverse biotic effects concentration data to generate species sensitivity distributions using AQUARISK. Although the harbor is subject to other inorganic and organic contamination, we have used sediment metals to demonstrate an approach for ecological risk mapping and environmental management prioritization. Sufficient spiked sediment toxicity test data were found for only three metals—Cd, Cu, and Zn—and some tests were likely to overestimate toxicity. The estimates of the hazardous concentration to 5% of species (the 50th percentile of the 95% species protection level) were 5, 12, and 40 mg/kg DW of total sediment metal for Cd, Cu, and Zn, respectively. These values were generally low when compared with the interim sediment quality guidelines due to the overestimation of toxic effects in the literature data. The parameters for the species sensitivity distributions have been combined with the measured sediment metal concentrations in Homebush Bay to generate risk maps of the estimated species impact for each metal as well as for all three metals collectively assuming proportional additivity. This has demonstrated the utility of comparing contaminants on a consistent scale—ecological risk.     

Heart Rate and Systolic Blood Pressure Variability in the Time Domain in Patients with Recent and Long-Standing Diabetes Mellitus

Diabetes Mellitus (DM) affects the cardiovascular response of patients. To study this effect, interbeat intervals (IBI) and beat-to-beat systolic blood pressure (SBP) variability of patients during supine, standing and controlled breathing tests were analyzed in the time domain. Simultaneous noninvasive measurements of IBI and SBP for 30 recently diagnosed and 15 long-standing DM patients were compared with the results for 30 rigorously screened healthy subjects (control). A statistically significant distinction between control and diabetic subjects was provided by the standard deviation and the higher moments of the distributions (skewness, and kurtosis) with respect to the median. To compare IBI and SBP for different populations, we define a parameter, α, that combines the variability of the heart rate and the blood pressure, as the ratio of the radius of the moments for IBI and the same radius for SBP. As diabetes evolves, α decreases, standard deviation of the IBI detrended signal diminishes (heart rate signal becomes more “rigid”), skewness with respect to the median approaches zero (signal fluctuations gain symmetry), and kurtosis increases (fluctuations concentrate around the median). Diabetes produces not only a rigid heart rate, but also increases symmetry and has leptokurtic distributions. SBP time series exhibit the most variable behavior for recently diagnosed DM with platykurtic distributions. Under controlled breathing, SBP has symmetric distributions for DM patients, while control subjects have non-zero skewness. This may be due to a progressive decrease of parasympathetic and sympathetic activity to the heart and blood vessels as diabetes evolves.     

Visual vs Fully Automatic Histogram-Based Assessment of Idiopathic Pulmonary Fibrosis (IPF) Progression Using Sequential Multidetector Computed Tomography (MDCT)

Objectives

To describe changes over time in extent of idiopathic pulmonary fibrosis (IPF) at multidetector computed tomography (MDCT) assessed by semi-quantitative visual scores (VSs) and fully automatic histogram-based quantitative evaluation and to test the relationship between these two methods of quantification.

Methods

Forty IPF patients (median age: 70 y, interquartile: 62-75 years; M:F, 33:7) that underwent 2 MDCT at different time points with a median interval of 13 months (interquartile: 10-17 months) were retrospectively evaluated. In-house software YACTA quantified automatically lung density histogram (10^th-90^th percentile in 5^th percentile steps). Longitudinal changes in VSs and in the percentiles of attenuation histogram were obtained in 20 untreated patients and 20 patients treated with pirfenidone. Pearson correlation analysis was used to test the relationship between VSs and selected percentiles.

Results

In follow-up MDCT, visual overall extent of parenchymal abnormalities (OE) increased in median by 5 %/year (interquartile: 0 %/y; +11 %/y). Substantial difference was found between treated and untreated patients in HU changes of the 40th and of the 80th percentiles of density histogram. Correlation analysis between VSs and selected percentiles showed higher correlation between the changes (Δ) in OE and Δ 40^th percentile (r=0.69; p<0.001) as compared to Δ 80^th percentile (r=0.58; p<0.001); closer correlation was found between Δ ground-glass extent and Δ 40^th percentile (r=0.66, p<0.001) as compared to Δ 80^th percentile (r=0.47, p=0.002), while the Δ reticulations correlated better with the Δ 80^th percentile (r=0.56, p<0.001) in comparison to Δ 40^th percentile (r=0.43, p=0.003).

Conclusions

There is a relevant and fully automatically measurable difference at MDCT in VSs and in histogram analysis at one year follow-up of IPF patients, whether treated or untreated: Δ 40^th percentile might reflect the change in overall extent of lung abnormalities, notably of ground-glass pattern; furthermore Δ 80^th percentile might reveal the course of reticular opacities.     

Inhalation Rates for Risk Assessments Involving Construction Workers in Canada

A Monte Carlo simulation was performed to generate probability density distributions describing hourly inhalation rates of male and female construction workers. Ranges of oxygen uptake and ventilation rates reported in the literature for various construction trades were manipulated in a simulation to generate hourly inhalation rates for male construction workers. The resulting inhalation rates can be represented by a log normal distribution with mean ± standard deviation of 1.40 ± 0.51 m³/h. Hourly inhalation rates for female construction workers were scaled from those of their male counterparts using relative awake-time inhalation rates of men and women of the general public. Female construction workers' inhalation rates can be represented by a log normal distribution with a mean ± standard deviation of 1.25 ± 0.66 m³/h. If the nature of the work is well understood, male and female construction workers' hourly inhalation rates can be scaled according to the construction trade. Construction trade-specific scaling factors were developed and range from 0.78 for electricians to 1.11 for ironworkers.     

Variability in Growth Characteristics of Different E. coli O157:H7 Isolates, and its Implications for Predictive Microbiology

In growth experiments 75 clinical isolates of Escherichia coli O157:H7 were studied for the variability in seven growth characteristics: minimum, optimum and maximum growth temperature, minimum and optimum pH, minimum water activity and optimum specific growth rate. With these characteristics, growth can be predicted for any given set of conditions (temperature, acidity and water activity), when the gamma model is used as predictive microbiology model. The optimum specific growth rate of the 75 strains, as conceptually defined by the model, had a mean value of 4.71 (ln[emsp4 ](count)/h), with a standard deviation of 0.39. It could not be shown that the mean optimum specific growth rate differs significantly per strain, so the variability found will predominantly be the result of other sources of variation. In contrast, the experimental results suggest that the differences in minimum temperature of growth may be partially strain specific. As variability in growth is crucial for quantitative risk assessment, the results were implemented in the gamma model. Predictions at three sets of growth conditions were compared with predictions of the Pathogen Modeling Program (PMP) (USDA) and some published experimental results. This comparison showed that growth rates higher than those published and outside the 95% confidence interval predicted by the PMP are feasible. Although it needs further development and additional tests, our approach offers a promising strategy to predict the variability in growth.     

Associations of Blood Pressure with Body Composition among Afro-Caribbean Children in Barbados

Despite complex presentation of adult hypertension and a concomitant obesity epidemic, little is known about overweight in relation to blood pressure among Caribbean children. We examined blood pressure in relation to body size in a cross-sectional study of 573 Barbadian children aged 9–10 years (2010-2011).The United States normative blood pressure percentiles were used to identify children with high (≥ 95^th percentile) or high normal blood pressure (90^th – 95^th percentile). The World Health Organization body mass index cut-off points were used to assess weight status.

Major findings

Thirty percent of children were overweight/obese. Percentage fat mass differed between girls (20.4%) and boys (17.72%) (p< 0.05). Mean systolic blood pressure among girls was 106.11 (95% CI 105.05, 107.17) mmHg and 105.23 (104.09, 106.38) for boys. The percentages with high or high-normal mean systolic blood pressurewere14.38% (10.47, 18.29) for girls and 8.08% (4.74, 11.41) for boys. Height and body mass index were independent correlates of systolic and diastolic blood pressure. Mean systolic blood pressure was related to lean mass but not fat mass, while diastolic blood pressure was associated with fat mass index and overweight.

Principal conclusion

One third of 9-10 year old children in Barbados were overweight/obese and 12% had elevated mean systolic blood pressure. BP was related to body size. These findings signal potential adverse trends in weight gain and BP trends for children growing up in the context of a country that has recently undergone rapid economic transition.     

Estimation of microbial contamination of food from prevalence and concentration data: application to Listeria monocytogenes in fresh vegetables

A normal distribution and a mixture model of two normal distributions in a Bayesian approach using prevalence and concentration data were used to establish the distribution of contamination of the food-borne pathogenic bacteria Listeria monocytogenes in unprocessed and minimally processed fresh vegetables. A total of 165 prevalence studies, including 15 studies with concentration data, were taken from the scientific literature and from technical reports and used for statistical analysis. The predicted mean of the normal distribution of the logarithms of viable L. monocytogenes per gram of fresh vegetables was -2.63 log viable L. monocytogenes organisms/g, and its standard deviation was 1.48 log viable L. monocytogenes organisms/g. These values were determined by considering one contaminated sample in prevalence studies in which samples are in fact negative. This deliberate overestimation is necessary to complete calculations. With the mixture model, the predicted mean of the distribution of the logarithm of viable L. monocytogenes per gram of fresh vegetables was -3.38 log viable L. monocytogenes organisms/g and its standard deviation was 1.46 log viable L. monocytogenes organisms/g. The probabilities of fresh unprocessed and minimally processed vegetables being contaminated with concentrations higher than 1, 2, and 3 log viable L. monocytogenes organisms/g were 1.44, 0.63, and 0.17%, respectively. Introducing a sensitivity rate of 80 or 95% in the mixture model had a small effect on the estimation of the contamination. In contrast, introducing a low sensitivity rate (40%) resulted in marked differences, especially for high percentiles. There was a significantly lower estimation of contamination in the papers and reports of 2000 to 2005 than in those of 1988 to 1999 and a lower estimation of contamination of leafy salads than that of sprouts and other vegetables. The interest of the mixture model for the estimation of microbial contamination is discussed.     

Variance in Brain Volume with Advancing Age: Implications for Defining the Limits of Normality

Background

Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.

Materials and Methods

We acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer’s disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.

Results

In both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5^th percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects.

Conclusions

While more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.     

Estimation of Microbial Contamination of Food from Prevalence and Concentration Data: Application to Listeria monocytogenes in Fresh Vegetables

A normal distribution and a mixture model of two normal distributions in a Bayesian approach using prevalence and concentration data were used to establish the distribution of contamination of the food-borne pathogenic bacteria Listeria monocytogenes in unprocessed and minimally processed fresh vegetables. A total of 165 prevalence studies, including 15 studies with concentration data, were taken from the scientific literature and from technical reports and used for statistical analysis. The predicted mean of the normal distribution of the logarithms of viable L. monocytogenes per gram of fresh vegetables was −2.63 log viable L. monocytogenes organisms/g, and its standard deviation was 1.48 log viable L. monocytogenes organisms/g. These values were determined by considering one contaminated sample in prevalence studies in which samples are in fact negative. This deliberate overestimation is necessary to complete calculations. With the mixture model, the predicted mean of the distribution of the logarithm of viable L. monocytogenes per gram of fresh vegetables was −3.38 log viable L. monocytogenes organisms/g and its standard deviation was 1.46 log viable L. monocytogenes organisms/g. The probabilities of fresh unprocessed and minimally processed vegetables being contaminated with concentrations higher than 1, 2, and 3 log viable L. monocytogenes organisms/g were 1.44, 0.63, and 0.17%, respectively. Introducing a sensitivity rate of 80 or 95% in the mixture model had a small effect on the estimation of the contamination. In contrast, introducing a low sensitivity rate (40%) resulted in marked differences, especially for high percentiles. There was a significantly lower estimation of contamination in the papers and reports of 2000 to 2005 than in those of 1988 to 1999 and a lower estimation of contamination of leafy salads than that of sprouts and other vegetables. The interest of the mixture model for the estimation of microbial contamination is discussed.     

Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City,northeastern China, 2007–2018

BackgroundHemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS.ObjectiveHuludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City.MethodsOur researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors.ResultsDuring the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5^th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5^th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5^th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5^th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level.ConclusionsOur study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.