Logit Link Function Research Articles

Estimation of small area proportions under a bivariate logistic mixed model

A variety of data is of geographic interest but is not available at a small area level from large-scale national sample surveys. Small area estimation can be used to estimate parameters of target variables to detailed geographical scales based on relationships between the target variables and relevant auxiliary information. Small area estimation of proportions is a topic of great interest in many fields of study, where binary variables are diffused, such as in labour force, business, and social exclusion surveys. The univariate generalised mixed model with logit link function is widely adopted in this context. The small area estimation literature has shown that multivariate small area estimators, where correlations among response variables are taken into account, provide more efficient estimates than the traditional univariate approaches. However, the estimation problem of multivariate proportions has not been studied yet. In this article, we propose a bivariate small area estimator of proportions based on a bivariate generalised mixed model with logit link function. A simulation study and an application are presented to evaluate the good properties of the bivariate estimator compared to its univariate setting. We found that the extent of the improved efficiency of the bivariate over the univariate approach is associated with the degree of correlation of the area-specific random effects and the intraclass correlation, whereas it is not strongly related to the area sample size.

The role of the ICU liaison nurse services on anxiety in family caregivers of patients after ICU discharge during COVID-19 pandemic: a randomized controlled trial

BackgroundWith the onset of the COVID-19 pandemic and the need to maintain social distancing and changes in wards' structure, families no longer access the routine support they received during the hospitalization of their patients in the ICU. This study aimed to determine the effects of ICU liaison nurse services on the anxiety in patients’ family caregivers after ICU discharge during the COVID-19 pandemic.MethodsThis randomized controlled trial was performed in western Iran from February 2020, to March 2021. Sixty subjects were selected from the family caregivers of the patients transferred from the ICU and were randomly assigned to the control (n = 30) and the intervention groups (n = 30). The control group received routine transfer care. In the intervention group, liaison nurse services were offered in 4 dimensions: patient support, family support, training, support of the ward’s staff, and the evaluation of the destination ward. The participants’ anxiety was measured using the Spielberger State Anxiety Inventory immediately after the patient transfer and 6 h after admission to the general ward. Data analyzed with SPSS V16, descriptive and inferential statistics, including Chi-square test, Mann–Whitney test, Wilcoxon test, and Generalized Linear Model with cumulative logit link function. Results were reported at a 0.05 significance level.ResultsA statistically significant difference was observed in baseline anxiety levels (P = 0.035) and age group (P < 0.001) between the intervention and control groups. After moderating baseline anxiety levels, the age group, and marital status, the impact of the intervention was significant (X2 = 10.273, df = 1, P < 0.001), meaning that the intervention could reduce the relative chances of developing higher levels of anxiety by 92.1% (OR: 0.08, 95%CI: 0.017–0.373, P < 0.001).ConclusionsThis study confirmed the positive impact of nursing services on reducing anxiety in family caregivers during the COVID-19 pandemic. It is recommended to use these services, especially during the COVID-19 condition, to facilitate the patient transfer, support the patient's family, and reduce the health care gap between the ICU and the ward.

Surveillance Program of Clinical Samples for Polio and Non-Polio Enteroviruses in the Slovak Republic during the 1958-2020 Period.

Enteroviruses (EVs) are associated with a wide spectrum of diseases involving various organs. Our aim was to give a historical overview of the genesis of clinical sample processing for EVs in the Slovak Republic (SR) during the 1958–2020 period, within the framework of the World Health Organization (WHO) polio program. Further, analyses were made of the data obtained from the archives of processed clinical sample surveillance using statistical methods. We used generalized additive models (GAM) with binomial distribution and logit link functions and an autoregressive moving average (ARMA) to analyze the data obtained during this 63-year period. Our results show trends in the composition of EV strains circulating in the population. Furthermore, statistically significant increasing trends of the non-polio enteroviruses (NPEVs) were observed over the studied time, represented by echoviruses (E) and coxsackieviruses A and B (CVA and CVB), with a cyclical pattern of occurrence. The most prevalent serotype over this period was CVB5, which became significantly more prevalent after 2000. While PVs, CVB1, and CVB3 were present in the second half of the studied period, CVA10, CVA16, E3, E25, and E30 appeared more frequently.

Behavioural Risk for HIV, Hepatitis B, and Hepatitis C Infections among a Population of Drug Users and Injectors across Four Regions in Ghana.

Background Blood borne infections such as HIV, Hepatitis B (HBV), and Hepatitis C (HCV) are of great importance to governments and their implementing partners, especially among people who use drugs (PWUD) and people who inject drugs (PWID). Prevalence and determinants of HIV, HBV, and HCV among PWUD and PWID in Ghana are not well established, the significance of this study. Method This assessment was a cross-sectional study implemented via the respondent driven sampling approach. A team of community advisory boards that comprised former users, current users, and civil society organizations were constituted to help in the implementation of the study. The study was conducted in four regions in Ghana. The assessment was based on a representation of populations of PWID and PWUD from the four regions. Efforts were made by the team to ensure adequate representation of women where feasible. A quantitative questionnaire was developed and used to obtain information on the respondents' sociodemographics, sexual behavior, substance use, and biological characteristics. The prevalence of HIV, HBV, and HCV among PWID and PWUD was determined using blood samples. First response and oral quick test for confirmation of HIV positivity were carried out, while SD bioline was used to test for the presence of HBV and HBC. Data were analyzed using the Bayesian generalized linear model via the binomial family of distributions under the logit link function with weak Cauchy and Normal distribution as prior. Results A total of 323 PWUD and PWID participants were interviewed across four regions of Ghana. The overall median age of the respondents was 36 (28, 43) years. The prevalence of HIV, HBV, and HCV infection in the study was 2.5%, 4.6%, and 5.9%, respectively. The prevalence of HIV, HBV, and HCV among drug users was 2.5% (95% CI: 0.7%–4.2%), 4.1% (95% CI: 1.8%–6.2%), and 6.7% (95% CI: 3.9%–9.4%), respectively. Most drug injectors and users started using and injecting drugs at ages less than 20 years and between 20 and 29 years, respectively. Drug users who identified themselves as part of the general population were 66% less likely to be tested HIV positive (POR = 0.34, CrI: 0.12–0.81) compared to sex workers. Part time employment respondents had fivefold odds (POR = 5.50, CrI: 1.20–16.16) of being HBV positive as against full-time employment. Conclusion Most of the injectors and users started drugs at an early age. Drug users and injectors are at higher risk of these infections because of associated risky sexual behaviors and risky injection practices. Harm reduction programs to help addicts who are willing to quit the practice are recommended.

On outliers detection and prior distribution sensitivity in standard skew-probit regression models

Regression models with probit and logit link functions are the most frequently used for binary response variables. However, traditional approaches may not be adequate when data are unbalanced. This paper deals with standard skew-probit regression models. Parameters were estimated through a new Bayesian approach which consists of the use of Hamiltonian Monte Carlo (HMC) and the original likelihood function. Simulation studies assessed the efficiency of the estimation method and the sensitivity of prior distributions for parameters related to asymmetry calculating the RMSE (root mean square error). The proposed estimation method was compared when used for detecting outliers. The results show that the proposed method is more efficient than INLA and is successful in the recovery of true parameter values. The sensitivity study enabled the proposal of a new prior distribution configuration for the asymmetry parameter, and the randomized quantile residual proved to be more suitable for detecting outliers. The methodology was applied to a diabetes dataset towards illustrating the results.

Sine-Weibull Geometric Mixture and Nonmixture Cure Rate Models with Applications to Lifetime Data

In this study, two new distributions are developed by compounding Sine-Weibull and zero-truncated geometric distributions. The quantile and ordinary moments of the distributions are obtained. Plots of the hazard rate functions of the distributions show that the distributions exhibit nonmonotonic failure rates. Also, plots of the densities of the distributions show that they exhibit decreasing, skewed, and approximately symmetric shapes, among others. Mixture and nonmixture cure rate models based on these distributions are also developed. The estimators of the parameters of the cure rate models are shown to be consistent via simulation studies. Covariates are introduced into the cure rate models via the logit link function. Finally, the performance of the distributions and the cure rate and regression models is demonstrated using real datasets. The results show that the developed distributions can serve as alternatives to existing models for survival data analyses.

Signal intensity of lateral meniscal allografts deteriorates over time: a longitudinal MRI analysis during a minimum follow-up of 8years.

To evaluate the serial change of magnetic resonance imaging (MRI) signal intensity (SI) of lateral meniscal allografts in a long-term period of > 8years and to determine whether the SI change adversely affected clinical outcomes. Thirty-three lateral meniscal allograft transplantation (LMAT) patients with MRI taken > 8years after surgery were included. The allograft was assessed using MRI at five serial time points (1, 2-4, 4-6, 6-8, and > 8years after surgery), based on the following grading system: grade 1, globular increased SI not adjacent to the articular surface; grade 2, linear SI within the meniscus; and grade 3, increased SI extended to the articular surface. MRI evaluation was performed for three locations of the allograft (anterior horn, mid-body, and posterior horn), and the serial changes of allograft SI at each location were analyzed using the generalized estimating equation (GEE) with cumulative logit link function. The patients were classified according to SI change at each location (stationary group and deterioration group), and the two groups were compared in terms of clinical outcomes using the Lysholm score. The mean follow-up duration was 9.2 ± 1.2years. During that period, SI of the allograft deteriorated over time, regardless of the location (anterior horn, p = 0.034; mid-body, p = 0.002; posterior horn, p < 0.001). The amount of SI deterioration at each location of the graft differed with a borderline significance (p = 0.050, GEE), and the proportion of grade 3 SI was higher at the posterior horn (36.4%) than at the other locations at the last follow-up (p < 0.001, chi-square test). However, no significant differences in the Lysholm scores were found between the stationary group and the deterioration group at all locations. SI of the meniscal allograft deteriorated over time at all locations during the long-term follow-up. Deterioration of the graft was more prominent at the posterior horn than at the other locations. SI deterioration did not adversely affect the clinical outcomes, which should be interpreted with caution, considering the small sample size of this study. In the prognosis of lateral MAT, SI deterioration at the posterior horn is a more determining factor than that at the other part of the allograft. Therefore, SI at the posterior horn needs to be examined with special concern. III.

Proportional odds model for identifying spatial inter-seasonal propagation of meteorological drought

Drought is probably the most multifaceted environmental disaster that results from a precipitation deficiency. It perhaps has directly and indirectly potential effects on people's lives, the economy, and other environmental resources worldwide. However, for reducing the potential negative impacts of drought, the understanding and information about seasonal drought frequency and persistence are crucial for drought early warning and mitigations policies. Therefore, the current research examines the selected stations' seasonal meteorological drought frequency and persistence. For this purpose, ordinal outcomes of the current research are modelled under the set of cumulative Logit Models (CLM). The estimation of the CLM is made from the logit link function. Further, the Brant Test (BT) is used to check the parallel line assumptions. The BT substantiates that the odds ratios are the same across the several drought classes. Thereby the POM is a ubiquitous choice for the current analysis. Therefore, the Proportional Odds Model (POM) is utilized to compute the odds and Probability of Drought Persistence (PDP) in varying seasons (March, April, May (Spring); June, July, August (Summer); September, October, November (Autumn); December, January, February (Winter). Further, Standardized Precipitation Index (SPI) for a certain time scale (i.e. three-month time scale SPI-3) is mainly utilized in POM. Amid SPI and various seasons, the relationship is found significant at a 5% significance level in various stations, including Murree, Rawalpindi, Sialkot, Sargodha, Faisalabad, Bahawalnagar, Bahawalpur, Mianwali, Jhelum Multan, Khanpur, and Lahore. The potential of the current research is substantiated by twelve meteorological stations in a certain province of Punjab, Pakistan. The current research outcomes provide the direction to dynamically identify the spatial interseasonal propagation of meteorological drought. Moreover, the obtained results can be helpful in making useful policies for the early warning system, drought risk assessment, and management, and formulating the drought-reducing plans.

Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves.

Most item response theory (IRT) models for dichotomous responses are based on probit or logit link functions which assume a symmetric relationship between the probability of a correct response and the latent traits of individuals taking a test. This assumption restricts the use of those models to the case in which all items behave symmetrically. On the other hand, asymmetric models proposed in the literature impose that all the items in a test behave asymmetrically. This assumption is inappropriate for great majority of tests which are, in general, composed of both symmetric and asymmetric items. Furthermore, a straightforward extension of the existing models in the literature would require a prior selection of the items' symmetry/asymmetry status. This paper proposes a Bayesian IRT model that accounts for symmetric and asymmetric items in a flexible but parsimonious way. That is achieved by assigning a finite mixture prior to the skewness parameter, with one of the mixture components being a point mass at zero. This allows for analyses under both model selection and model averaging approaches. Asymmetric item curves are designed through the centred skew normal distribution, which has a particularly appealing parametrization in terms of parameter interpretation and computational efficiency. An efficient Markov chain Monte Carlo algorithm is proposed to perform Bayesian inference and its performance is investigated in some simulated examples. Finally, the proposed methodology is applied to a data set from a large-scale educational exam in Brazil.

Modeling driver’s braking and steering behavior along horizontal curves of two-lane rural highways for ADAS applications

Objective Drivers continuously manipulate the vehicle’s steering and pedals (throttle, brake) while driving. Inadequate or excessive manipulation leads to crashes, possibly leading to injuries. An Advanced Driving Assistance System (ADAS) can warn drivers of inadequate or excessive manipulation to avert risky situations. Such systems evolve continuously and need more road infrastructure inputs for better driving assistance. Rural highways showcased more fatalities than urban counterparts, with more road departure crashes along horizontal curves than straight sections. Hence, the present study explores drivers’ braking and steering behavior along the horizontal curves of two-lane rural highways and proposes a suitable runoff risk model. Methods Sixty-eight drivers participated in a driving simulator study, where they drove along fifty-two horizontal curves in free-flow conditions. Typical five brake and three steering measures found in past studies were evaluated. Based on data distribution of brake and steering measures, Tobit and mixed-effects multiple linear regression models were developed to understand the association of these measures with the approach speed and geometric parameters of horizontal curves. Further, a generalized linear mixed runoff (road departure) risk model with a logit link function was developed to identify the effective measures among all brake and steering variables. Results The brake and steering measures were significantly associated with the approach speed and the geometric parameters such as curve radius, gradient, and turn type (left or right). Further, the runoff risk analysis revealed a significant effect of braking distance (BD) and standard deviation of steering wheel position (SDSWP). The interaction between BD and SDSWP was significant, suggesting that the runoff risk increased with SDSWP; however, it decreased with BD. Conclusions The runoff risk intensified with higher steering instability along horizontal curves, while it can be reduced with effective brake pedal usage. The study suggests better usage of brakes than steering before entering the curve. It potentially reduces the vehicle speed, thus ensuring more time to perceive the curve and help reduce the driver’s steering instability. The models developed in this study can be used in the ADAS systems upon validation with the field observations.

Effects of an herbal diet, diet x boar line and diet x genotype interactions on skin lesions and on growth performance in post-weaning pigs using a cross-classified experiment

The aims of the present study were to assess the effect of an herbal diet (HD; basal diet plus a supplement with chicory herbs) on production traits and lesions scores in post weaning pigs, and to study possible boar x diet and genotype x diet interactions considering the two feeding groups HD and control (CON). In this regard, a cross-classified research design was implemented, aiming on an equal number of boar offspring in both groups HD and CON. Grouping of piglets (993 crossbred piglets from 14 different Piétrain boars sire to German Landrace or German Edelschwein sows) was done after weaning, and the feeding experiment was conducted in post-weaning period up to the pig age of nine weeks. Studied traits included the post-weaning weight (PWW) at the age of nine week 9, average daily gain (ADG) considering the period from weaning until week 9 and a skin lesion score (LS) at week 9. Herbal diet effects and sire x diet effects were inferred via linear models for Gaussian distributed PWW and ADG, and via generalized linear mixed models with a logit link function for categorical LS. Possible genotype x diet interactions were proved in multiple-trait models via Gibbs sampling, by defining same traits recorded either in CON and HD as different traits, i.e., post-weaning weight control (PWWCON) and post-weaning weight herbal diet (PWWHD), average daily gain control (ADGCON) and average daily gain herbal diet (ADGHD), and lesion score control (LSCON) and lesion score herbal diet (LSHD). The dietary treatment had no significant effect (P > 0.05) on PWW and ADG. The dietary treatment significantly (P < 0.05) influenced the behavior of the pigs, with a lower and favorable LS score for the pigs allocated to HD. Significant sire x diet interactions were identified for LS, PWW and ADG. Pearson correlations between estimates for sire effects from both diets CON and HD (i.e., the sire x diet effect) were 0.84 for PWW, 0.71 for ADG and 0.56 for LS. Genetic correlations smaller than 0.80 between PWWCON and PWWHD, ADGCON and ADGHD, and LSCON and LSHD indicate genotype x diet interactions, especially for the functional and low heritability LS. Hence, re-rankings of sires according to their estimated breeding values (EBV) were observed in both environments CON and LD, displaying smaller genetic and EBV variations for LS in the HD group. The HD dietary supplement contributed to fewer skin lesions, probably due to the favorable effect on pig behavior, but a more pronounced genetic differentiation seems to be possible in the more challenging CON environment. Generally, the results from the present study indicate the importance of genotype x feeding interactions for pig breeding, suggesting specific boars for different feeding environments.

Dengue Seroprevalence and Factors Associated with Dengue Seropositivity in Petaling District, Malaysia.

Dengue virus (DENV) infection is a major public health concern, posing huge economic and disease burdens globally. In Malaysia, the incidence of DENV infections has increased significantly over the years. Nevertheless, the passive surveillance mechanism applied may not capture the actual magnitude of DENV infection. There was also a paucity of community-based studies exploring DENV seroprevalence. This study aimed to determine the DENV seroprevalence and the associated factors among the urban population in Petaling district, Malaysia. A population-based cross-sectional study was conducted from 18 August to 26 October 2018 with 533 participants recruited. Blood samples were collected and analysed for DENV seropositivity using a composite reference standard comprised of three dengue serological tests. Associated factors were identified by fitting Generalised Linear Mixed Models with binomial error structure and logit link function. DENV seroprevalence obtained was 79.0% (95% CI: 75.2–82.4%). The age-specific DENV seroprevalence showed an increasing trend with advancing age, from 22.7% (95% CI: 9.6–45.0%) for those aged below five years old to 94.9% (95% CI: 81.3–98.7%) for those aged ≥60 years old. Only age group and house level were found to be significant factors associated with DENV seropositivity. The odds of being DENV seropositive generally increased with age, from 13.43 (95% CI: 2.77–65.22) for the 5–9 years old age group to 384.77 (95% CI: 39.27–3769.97) for the ≥60 years old age group, as compared to those aged below 5 years old. For house level, those who lived on the first and second floor (OR: 8.98, 95% CI: 3.16–25.12) and the third floor and above (OR: 4.82, 95% CI: 1.89–12.32) had greater odds of being DENV seropositive compared to those living on the ground floor. This study demonstrated the persistently high DENV seroprevalence among the urban population in Petaling district, which could be useful to evaluate dengue control measures taken and estimate more accurate disease incidence. The associated factors with DENV seropositivity identified could also contribute to undertaking more targeted preventive and control measures.

Anatomy Nights: An international public engagement event increases audience knowledge of brain anatomy.

Anatomy Nights is an international public engagement event created to bring anatomy and anatomists back to public spaces with the goal of increasing the public's understanding of their own anatomy by comparison with non-human tissues. The event consists of a 30-minute mini-lecture on the anatomy of a specific anatomical organ followed by a dissection of animal tissues to demonstrate the same organ anatomy. Before and after the lecture and dissection, participants complete research surveys designed to assess prior knowledge and knowledge gained as a result of participation in the event, respectively. This study reports the results of Anatomy Nights brain events held at four different venues in the UK and USA in 2018 and 2019. Two general questions were asked of the data: 1) Do participant post-event test scores differ from pre-event scores; and 2) Are there differences in participant scores based on location, educational background, and career. We addressed these questions using a combination of generalized linear models (R's glm function; R version 4.1.0 [R Core Team, 2014]) that assumed a binomial distribution and implemented a logit link function, as well as likelihood estimates to compare models. Survey data from 91 participants indicate that scores improve on post-event tests compared to pre-event tests, and these results hold irrespective of location, educational background, and career. In the pre-event tests, participants performed well on naming structures with an English name (frontal lobe and brainstem), and showed signs of improvement on other anatomical names in the post-test. Despite this improvement in knowledge, we found no evidence that participation in Anatomy Nights improved participants' ability to apply this knowledge to neuroanatomical contexts (e.g., stroke).

Diet Quality and Sleep Characteristics in Midlife: The Bogalusa Heart Study

ObjectivesThe objective of this study was to determine the cross-sectional relationship between diet quality and multiple sleep outcomes in the Bogalusa Heart Study (BHS). MethodsThis cross-sectional study included 824 midlife participants of the 2013–2016 BHS visit (mean age 48 years, 30% Black). Diet was assessed with a validated food frequency questionnaire and dietary patterns (Alternate Healthy Eating Index [AHEI] 2010, Healthy Eating Index 2015, and Alternate Mediterranean). Insomnia risk, sleep apnea risk, and healthy sleep pattern scores were measured with validated questionnaires. Generalized estimating equations with a logit link function were used to estimate the odds ratio (OR) of high risk of insomnia, sleep apnea, and having a healthy sleep pattern across quintiles (Q) and per standard deviation (SD) increase in dietary pattern scores controlling for body mass index (BMI), socioeconomic status, and other potential confounders. Interactions by race, sex, and education were explored. ResultsHigher diet quality as measured by AHEI 2010 was associated with decreased odds of being high risk for sleep apnea after controlling for demographic, socioeconomic, health, and lifestyle factors (OR [95% confidence interval (CI)] Q5 vs. Q1: 0.38 [0.22, 0.65], per SD increase: 0.80 [0.67, 0.95], p-trend: 0.003). This association was stronger among women compared to men (OR [95% CI] per SD increase women: 0.69 [0.55, 0.86], men: 1.01 [0.74, 1.39], p-interaction = 0.01) and in those with higher education compared to those with less education (OR [95% CI] per SD increase high education: 0.67 [0.51, 0.87], low education: 0.94 [0.74, 1.20], p-interaction = 0.03). There were no associations among other dietary patterns or for insomnia risk or healthy sleep pattern in fully adjusted models. ConclusionsHigher diet quality is associated with decreased odds of sleep apnea risk in a biracial cohort from a semi-rural, low-income community in the southeastern United States. If confirmed in prospective studies, these results have public health implications for the prevention of chronic disease. Funding SourcesNational Heart, Lung, And Blood Institute of the National Institutes of Health.

1154-P: Leisure-Time Physical Activity Environment and Odds of Glycemic Control over Time among Veterans with New-Onset Type 2 Diabetes

Physical activity is protective against type 2 diabetes (T2D) incidence and supports T2D management. Access to local facilities such as gyms and parks enables leisure-time physical activity (LTPA) . We examined associations between T2D patients’ access to LTPA facilities and parks and whether repeated A1C follow-up tests were within a desired range. We analyzed data on 271,5 patients from the Veterans Administration Diabetes Risk Cohort who developed T2D from 2008-2018. We measured an A1C test as in-range if 5.0-7.0 (&amp;lt;80 years of age) or 5.0-8.5 (≥80 years of age) , density of facilities within street network buffers, and population-weighted distance to the closest 7 parks. We used generalized estimating equations with a logit link function to predict the log odds of an in-range vs. out-of-range A1C test. We tested environment-by-time interactions, controlling for individual and neighborhood demographics and baseline A1C. On average, patients were 60 years of age, male (95%) , white (71%) , and had A1C tests during follow-up. Higher facility density, but not park distance, was narrowly associated with lower odds ofan in-range A1C test (ORdensity=.99, 95% CI=.98, 1.0) . As years since T2D diagnosis increased, the odds of an in-range A1C test decreased (ORtime=.88, 95% CI=.88, .88) . For those living in higher facility density, the odds of an in-range A1C decreased over time by only a slightly lower factor than for those living in lower facility density (P&amp;lt;.0 for interaction term) . For those living farther from parks, the odds of an in-range A1C decreased over time by only a slightly higher factor than for those living closer to parks (P=.001) . As odds of in-range A1C tests decline over time, broader access to facilities and parks may not soften the decline since the modified effects were clinically negligible. Viable interventions for maintaining healthy A1C after diagnosis may include efforts to both increase access to and promote the use of the LTPA environment. Disclosure S.L.Orstad: None. P.M.Lopez: None. S.Adhikari: Research Support; Johnson &amp; Johnson. D.C.Lee: None. R.Kanchi: None. M.D.Schwartz: None. F.Alemi: None. B.Elbel: None. L.Thorpe: None. Funding This study was funded by the Centers for Disease Control and Prevention (5 U01DP006299-02-00; PI: Lorna Thorpe)

Exploring complementary and competitive relations between non-communicable disease services and other health extension programme services in Ethiopia: a multilevel analysis

BackgroundEthiopia has recently revitalised its health extension programme (HEP) to address the rising burden of non-communicable diseases (NCDs). We examined the effects of existing essential HEP services on the uptake...

Melanoma with peripheral globules: Clinical and dermatoscopic features

The morphology and biology of nevi with peripheral globules are well known, whereas those of melanomas with peripheral globules remain unclear. Comparing the dermatoscopic characteristics of nevi and melanomas with peripheral globules. A total of 401 melanocytic lesions with peripheral globules were included in this retrospective study. Dermatoscopic patterns and structures, including those of peripheral globules, were evaluated. A generalized estimating equation model with a binomial distribution dependent variable and logit link function was fitted to the dataset to identify features with the highest odds of differentiating melanoma from nevi. Of the 401 lesions, 179 (44.64%) were excised, 41 (10.22%) of which were melanomas. Melanomas were most common in the lower extremities (P<.01), with a disorganized pattern, whereas melanocytic nevi were most common on the trunk, with an organized pattern. In addition, the presence of blotches, atypical dots and globules, or atypical vessels was associated with melanomas (P<.01). The retrospective design of the study may have caused an inclusion bias. Melanocytic lesions displaying peripheral globules are at the greatest risk of melanoma if located on the lower extremity and if lesions reveal any of the following structures: blotch, atypical dots and globules, or atypical vessels.

First test-day postcalving risk factors for clinical mastitis in southern Chile dairy farms: A retrospective cohort study

We conducted a retrospective cohort study to evaluate risk factors associated with clinical mastitis in dairy cows in southern Chile between the first milk test after calving to 200 d in milk (DIM). Data from 8,772 cows were collected from June 2017 to November 2019 on 10 dairy farms selected by convenience in southern Chile. Data were analyzed using a multivariable mixed logistic regression using a manual backward selection process with logit link function and farm as a random effect. The dependent variable was clinical mastitis between the first milking sample collected by monthly milk sampling program up to 200 DIM. Days in milk, fat, urea, parity, season, and somatic cell counts were statistically associated with clinical mastitis in the first 200 d in milk. Cows with higher than average milk yield, parity, urea, and somatic cell count were at greater odds of being diagnosed with clinical mastitis compared with their respective referents. In contrast, higher milk fat was associated with lower odds of clinical mastitis. Significant interactions between days in milk with season and parity were observed, where for every 5-d increase in DIM, the odds of clinical mastitis decreased by different proportions depending on the interaction. Identified risk factors for clinical mastitis using first monthly milk sampling data can help dairy farmers in Chile implement herd-level mastitis prevention and control measures.

Evaluation of clinically relevant changes in the lung clearance index in children with cystic fibrosis and healthy controls

BackgroundThe limits of reproducibility of the lung clearance index (LCI) are higher in children with cystic fibrosis (CF) compared with healthy children, and it is currently unclear what defines a...

Association of Antibiotic Use during the First 6 Months of Life with Body Mass of Children.

In this study, our objective was to assess the association of body mass in preschool children with the use of antibiotics within 6 months after birth. National administrative databases were used to examine all children born between 2008 and 2009 in Korea. Exposure was defined as the use of systemic antibiotics during the first 6 months of age. The observed outcomes were stunting (height for age [HFA] z score < −2.0), short stature (HFA z score < −1.64), overweight (body mass index [BMI] for age z score ≥ 1.04), and obesity (BMI for age z score ≥ 1.64), and the children’s height and body weight were measured from three to six years of age. To balance characteristics between the antibiotic user and non-user groups, propensity score matching was performed. The outcomes were evaluated using a generalized estimation equation with the logit link function. Analysis of antibiotic use by children during the first 6 months of life indicated there were 203,073 users (54.9%) and 166,505 non-users (45.1%). After PS matching, there were 72,983 antibiotic users and 72,983 non-users. Antibiotic use was significantly associated with stunting (aOR = 1.198, 95% CI = 1.056 to 1.360) and short stature (aOR = 1.043, 95% CI = 1.004 to 1.083), and had significant negative association with HFA z score (weighted β = −0.023). The use of an antibiotic for 14 days or more had a marked association with stunting. Antibiotic use was also associated with overweight, obesity, and increased BMI for age z score. Antibiotic use during the first 6 months of life increased the risk of stunting, short stature, overweight, and obesity in preschool children.