Zero-inflated Poisson Regression Models Research Articles

Investigating interaction effects of social risk factors and exposure to air pollution on pediatric lymphoma cancer in Georgia, United States

Childhood cancer constitutes a major cause of death in children. In a recent study of the Georgia Cancer Registry, joint exposures to environmental and social/behavioral stressors were associated with spatial clustering of lymphomas and reticuloendothelial neoplasms among the 159 counties in Georgia, USA. The present study aims to further investigate these associations on a more granular level. Bayesian Poisson and zero-inflated Poisson regression models with spatial and non-spatial variance structures were utilized to investigate whether county-specific cancer patterns may be explained by single or combinations of social stressors and ambient air pollution while adjusting for confounding and accounting for overfitting using differences in expected log predictive densities. While we did not find associations between lymphoma rates and social variables, air pollution, or their interactions, our proposed analysis workflow can serve as a blueprint for future studies investigating dependencies in regression models that feature combinations of unobserved and observed dependency structures.

Double robust semiparametric weighted M-estimators of a zero-inflated Poisson regression with missing data in covariates

Frequently, the covariates in the linear predictors of a zero-inflated Poisson regression model are prone to missingness. When the missing data process is at random, the naive estimator and the inverse probability weighted estimator of the model parameter are known to be biased or less efficient. Hence, we propose four different semiparametric double robust weighting M-estimators of a zero-inflated Poisson model. In particular, these estimators differ in term of the nature and the combination of the nuisance components in the estimating equation. The Nadaraya kernel and the generalized additive models are the two smoothing approaches used to estimate the nuisance parameters in step 1. Each estimator in step 2 is a solution to a specific M-estimating equation which requires two distinct nonparametric nuisance components including the selection probability and the augmentation term. The resulting semiparametric weighted M-estimators are double robust and relatively more efficient than their parametric counterpart and related inverse probability weighted estimators. We examine the performance of the proposed estimators by conducting a simulation study and exploring a road traffic dataset. Overall, the performance of the proposed estimators is satisfactory and potential for various extensions.

Handheld Cellphone Use and Risky Driving in Adolescents

Handheld cellphone use while driving is associated with increased motor vehicle crash risk among adolescents. To examine the association of handheld cellphone use while driving with kinematic risky driving (KRD) events-hard braking and rapid acceleration-in adolescent drivers. Adolescents aged 16.50 to 17.99 years licensed 365 days or less in Pennsylvania were eligible to participate in this cross-sectional study. Enrollment occurred from July 29, 2021, to June 6, 2022. Participants downloaded a smartphone telematics cellphone app to record driving data for 60 days. Trip characteristics, including frequency, length, and duration; presence of speeding; frequency and duration of handheld cellphone use; time of day; and presence of precipitation. Kinematic risky driving events per 100 miles driven. Zero-inflated Poisson regression models examined whether individual characteristics and trip characteristics were associated with KRD. Incidence rate ratios were computed. Of 405 adolescents who responded to recruitment, 151 enrolled, 140 completed study procedures, and 119 with 12 360 trips were included in the analytic sample (60 female participants [50.4%]; mean [SD] age, 17.2 [0.4] years). Adolescents drove a mean (SD) of 103.8 (65.7) trips, 565.0 (487.3) miles, and 25.1 (19.3) hours. Adolescents had minimal night trips (1.5% [192]), and few trips with precipitation present (9.0% [1097]). Speeding occurred in 43.9% (5428) of the trips and handheld cellphone use occurred in 34.1% (4214) of the trips. Kinematic risky driving events occurred in 10.9% (1358) of the trips at a rate of 2.65 per 100 miles. In adjusted models, increased KRD events were associated with handheld cellphone use (incidence rate ratio [IRR], 2.62; 95% CI, 1.53-4.48), speeding (IRR, 2.12; 95% CI, 1.06-4.26), and minutes driving (IRR, 1.02; 95% CI, 1.01-1.02). Trips at night, precipitation presence, licensure for less than 6 months, and sex were not associated with increased KRD events. In this cross-sectional study of adolescent drivers, trips with handheld cellphone use and speeding were associated with higher rates of KRD, while individual characteristics were not. The findings suggest that smartphone telematics apps provide an opportunity to observe behaviors as well as surveil changes due to intervention efforts.

Bayesian spatio-temporal analysis of dengue transmission in Lao PDR

Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People’s Democratic Republic (Lao PDR). This study aimed to describe spatial–temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE). The association between monthly dengue occurrences and environmental and climate variations was investigated using a multivariable Zero-inflated Poisson regression model developed in a Bayesian framework. The study analyzed a total of 72,471 dengue cases with an incidence rate of 174 per 100,000 population. Each year, incidence peaked from June to September and a large spike was observed in 2019. The Bayesian spatio-temporal model revealed a 9.1% decrease (95% credible interval [CrI] 8.9%, 9.2%) in dengue incidence for a 0.1 unit increase in monthly normalized difference vegetation index at a 1-month lag and a 5.7% decrease (95% CrI 5.3%, 6.2%) for a 1 cm increase in monthly precipitation at a 6-month lag. Conversely, dengue incidence increased by 43% (95% CrI 41%, 45%) for a 1 °C increase in monthly mean temperature at a 3-month lag. After accounting for covariates, the most significant high-risk spatial clusters were detected in the southern regions of Lao PDR. Probability analysis highlighted elevated trends in 45 districts, emphasizing the importance of targeted control strategies in high-risk areas. This research underscores the impact of climate and environmental factors on dengue transmission, emphasizing the need for proactive public health interventions tailored to specific contexts in Lao PDR.

Application of longitudinal multilevel zero inflated Poisson regression in modeling of infectious diseases among infants in Ethiopia

BackgroundIn sub-Saharan African countries, preventable and manageable diseases such as diarrhea and acute respiratory infections still claim the lives of children. Hence, this study aims to estimate the rate of change in the log expected number of days a child suffers from Diarrhea (NOD) and flu/common cold (NOF) among children aged 6 to 11 months at the baseline of the study.MethodologyThis study used secondary data which exhibit a longitudinal and multilevel structure. Based on the results of exploratory analysis, a multilevel zero-inflated Poisson regression model with a rate of change in the log expected NOD and NOF described by a quadratic trend was proposed to efficiently analyze both outcomes accounting for correlation between observations and individuals through random effects. Furthermore, residual plots were used to assess the goodness of fit of the model.ResultsConsidering subject and cluster-specific random effects, the results revealed a quadratic trend in the rate of change of the log expected NOD. Initially, low dose iron Micronutrient Powder (MNP) users exhibited a higher rate of change compared to non-users, but this trend reversed over time. Similarly, the log expected NOF decreased for children who used MNP and exclusively breastfed for six months, in comparison to their counterparts. In addition, the odds of not having flu decreased with each two-week increment for MNP users, as compared to non-MNP users. Furthermore, an increase in NOD resulted in an increase in the log expected NOF. Region and exclusive breastfeeding also have a significant relationships with both NOD and NOF.ConclusionThe findings of this study underscore the importance of commencing analysis of data generated from a study with exploratory analysis. The study highlights the critical role of promoting EBF for the first six months and supporting children with additional food after six months to reduce the burden of infectious diseases.

The relative effectiveness of a high-dose quadrivalent influenza vaccine versus standard-dose quadrivalent influenza vaccines in older adults in France: a retrospective cohort study during the 2021–2022 influenza season

ObjectivesHigh-dose quadrivalent influenza vaccine (HD-QIV) was introduced during the 2021/2022 influenza season in France for adults aged ≥65 years as an alternative to standard-dose quadrivalent influenza vaccine (SD-QIV). The aim of this study is to estimate the relative vaccine effectiveness of HD-QIV vs. SD-QIV against influenza-related hospitalizations in France. MethodsCommunity-dwelling individuals aged ≥65 years with reimbursed influenza vaccine claims during the 2021/2022 influenza season were included in the French national health insurance database. Individuals were followed up from vaccination day to 30 June 2022, nursing home admission or death date. Baseline socio-demographic and health characteristics were identified from medical records over the five previous years. Hospitalizations for influenza and other causes were recorded from 14 days after vaccination until the end of follow-up. HD-QIV and SD-QIV vaccinees were matched using 1:4 propensity score matching with an exact constraint on age group, sex, week of vaccination, and region. Incidence rate ratios were estimated using zero-inflated Poisson or zero-inflated negative binomial regression models. ResultsWe matched 405 385 HD-QIV to 1 621 540 SD-QIV vaccinees. HD-QIV was associated with a 23.3% (95% CI, 8.4–35.8) lower rate of influenza hospitalizations compared with SD-QIV (69.5/100 000 person years vs. 90.5/100 000 person years). Post-matching, we observed higher rates in the HD-QIV group for hospitalizations non-specific to influenza and negative control outcomes, suggesting residual confounding by indication. DiscussionHD-QIV was associated with lower influenza-related hospitalization rates vs. SD-QIV, consistent with existing evidence, in the context of high SARS-CoV-2 circulation in France and likely prioritization of HD-QIV for older/more comorbid individuals.

Urban landscape pattern mainly drives the early epidemic distribution of dengue fever in Hangzhou, China

ContextA new dengue fever (DF) epidemic in Hangzhou, China has placed a serious burden on the urban sustainable development. However, the key drivers of DF epidemic are still unclear, especially the effects of urban landscape patterns.ObjectivesIn the present study, the spatial relationships between DF epidemic and urban landscape attributes in Hangzhou were investigated based on the framework and approach of landscape epidemiology.MethodsThe landscape indices of green space, waterbody, and built-up area were calculated based on land cover and land use (LULC) data. Population density, road density, GDP, and property price were used to represent socioeconomic conditions. The densities of social gathering places (SGPs) such as restaurants, malls, services, entertainment, traditional markets, and parks were recorded. A geographically weighted zero-inflated poisson regression (GWZIPR) model was applied to analyze the effects of LULC patterns, socioeconomic conditions, and SGPs on the risk of DF epidemics. An additional ZIPR-LASSO algorithm was used to explore the dominant drivers of spatial patterns of DF risk to construct the optimal model.ResultsDF cases were mainly clustered in central Hangzhou. Landscape patterns involving LULC and SGPs played a more important role in DF epidemic than the socioeconomic conditions. Among these factors, the total area of built-up area had the greatest effect to DF risk. Furthermore, property price, density of entertainment and services could better explain the spatial variation of DF risk in Hangzhou.ConclusionsOverall, the contribution of landscape patterns to the DF epidemic was more important than socioeconomic conditions within the urban region, especially in the new epidemic region. These findings revealed the key role of landscape epidemiology in public health management and landscape governance to improve the urban sustainable development and human well-being.

Tobacco Exposures are Associated With Healthcare Utilization and Healthcare Costs in Pregnant Persons and Their Newborn Babies.

Identifying healthcare utilization and costs associated with active and passive smoking during pregnancy could help improve health management strategies. Data are from the Newborn Epigenetics STudy (NEST), a birth cohort enrolled from 2005 to 2011 in Durham and adjacent counties in North Carolina, United States. Participants included those for whom prenatal serum samples were assayed and for whom administrative data were obtainable (N = 1045). Zero-inflated poisson regression models were used to assess associations between cotinine, adjusted for covariates (eg, race and ethnicity, age at delivery, cohabitation status, and education), and health care utilization outcomes. Generalized linear regression models were used to estimate average total charges. Simulation models were conducted to determine the economic benefits of reducing secondhand smoke and smoking during pregnancy. Increasing levels of cotinine were positively associated with parent's number of emergency department (ED) visits (coefficient[b] = 0.0012, standard error [SE] = 0.0002; p < .001), the number of ICU hours (b = 0.0079, SE = 0.0025; p = .002), time spent in the ICU (b = 0.0238, SE = 0.0020, p < .001), and the number of OP visits (b = 0.0003, SE = 0.0001; p < .001). For infants, higher cotinine levels were associated with higher number of ED (b = 0.0012, SE = 0.0004; p = .005), ICU (b = 0.0050, SE = 0.001; p < .001), and OP (b = 0.0006, SE = 0.0002; p < .001) visits and longer time spent in the ED (b = 0.0025, SE = 0.0003; p < .001), ICU (b = 0.0005, SE = 0.0001; p < .001), and IP (b = 0.0020, SE = 0.0002; p < .001). Simulation results showed that a 5% reduction in smoking would correspond to a potential median cost savings of $150 533 from ED visits of parents and infants. Our findings highlight the importance of smoke exposure cessation during pregnancy to reduce health care utilization and costs for both parents and infants. This study reinforces the importance of reducing smoking and secondhand smoke exposure during pregnancy. Focusing on expanding cessation services to this group could help reduce morbidities observed within this population. Furthermore, there is the potential for healthcare cost savings to healthcare systems, especially for those with high delivery numbers. These cost savings are represented by potential reductions in ED, OP, and ICU hours and visits.

Participation and Persistence in High School Elective Music Ensembles

In this study, we examined demographic patterns of participation and persistence in high school elective music ensembles. We extend prior research that has only compared music and non-music students by explicitly modeling persistence across multiple years of ensemble enrollment. The research draws on data from the High School Longitudinal Study of 2009 and employs a zero-inflated Poisson regression model to analyze the data. This hurdle model, suitable for count data with a large number of zero observations, allows us to jointly examine factors related to enrolling in at least 1 year of a music ensemble (moving from 0 years to 1 year of music) and those factors related to accruing additional years of music ensemble enrollment (moving beyond 1 year to multiple years). We found that family socioeconomic status, birth-assigned sex, academic achievement, shared parent/student outside arts event attendance, and out-of-school arts engagement were significant predictors of both students’ music participation and persistence. By examining persistence, we add important nuance to the prior research examining demographic predictors of elective high school music enrollment, particularly for issues of birth-assigned sex and socioeconomic status in the choral context.

Predicting the multivariate zero-inflated counts: A novel model averaging method under Pearson loss.

Excessive zeros in multivariate count data are often observed in scenarios of biomedicine and public health. To provide a better analysis on this type of data, we first develop a marginalized multivariate zero-inflated Poisson (MZIP) regression model to directly interpret the overall exposure effects on marginal means. Then, we define a multiple Pearson residual for our newly developed MZIP regression model by simultaneously taking heterogeneity and correlation into consideration. Furthermore, a new model averaging prediction method is introduced based on the multiple Pearson residual, and the asymptotical optimality of this model averaging prediction is proved. Simulations and two empirical applications in medicine are used to illustrate the effectiveness of the proposed method.

Modeling clustered count data using mixed effect discrete Weibull regression model with cubic splines

This paper investigates the use of mixed-effect discrete Weibull (DW) regression model with cubic splines for clustered count data. DW regression model can be used for both over and under-dispersed data thus, it can be an appropriate choice for researchers to use without having the risk to violate assumptions for using a particular model distribution. We used a cubic spline function to model the non-linear relationship between the outcome variable and the covariate. The proposed model is applied to a clustered dataset from the eighth Korean National Health and Nutrition Examination Survey (KNHANES VIII) from 2019 to assess the factors influencing the amount of alcohol drink in 17 different regions. We compared the results with our proposed model with those of Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial regression models in the presence of spline function. The results show that using DW regression model with cubic spline gives the best fit. We also held a simulation study to investigate the performance and the robustness of DW with a spline function. It turns out that DW regression model with a spline function can flexibly model clustered count data with various dispersion and data with many zeros.

Long-term effects of childhood difficulties on depressive symptoms among older adults: Role of adulthood income and income satisfaction.

This study examines how childhood difficulties are associated with late-life depression. Using the concept of agency within the structure of the life course perspective, this study investigates how subjective income satisfaction in adulthood plays a role in the relationship between adulthood objective income and late-life depressive symptoms among older adults who have experienced childhood difficulties. Using data from two waves (2006, 2021) of the Korean Welfare Panel Study (N = 1822), we identified respondents with and without childhood difficulties, and performed a series of hierarchical zero-inflated Poisson regression models. Childhood difficulties (β, 0.07; 95% confidence interval [CI], 0.04-0.11), adulthood low income (β, 0.17; 95% CI, 0.13-0.21), and low income satisfaction (β, 0.16; 95% CI, 0.12-0.21) are associated with an increased level of depressive symptoms in late life. In the context of the association between objective income level and late-life depressive symptoms, the buffering effect of income satisfaction in adulthood was found among the respondents who had experienced childhood difficulties (β, 0.22; 95% CI, 0.09-0.34). Childhood difficulties are a critical risk factor impacting late-life psychological well-being. How an individual subjectively evaluates his or her economic status in adulthood plays a major role in mitigating the negative impact of childhood difficulties on late-life health inequality. Interventions to reduce the risk of childhood difficulties and their negative long-lasting impact may alleviate individuals' exposure to depression in late life. Geriatr Gerontol Int 2024; 24: 246-252.

Evaluating the Performance of Mixed Zero-Inflated Poisson Regression Models with Time-dependent and Time-independent Covariates

One of the issues that researchers may encounter in count data is having many zeros. One of the solutions to model these data is using zero-inflated Poisson (ZIP) regression models. Recently, researchers have started to model longitudinal count data with time-dependent covariates. However, it has not been considered whether a model with time-dependent covariates provides a better fit than a model with time-independent covariates. In this paper, the fit between a mixed ZIP model with time-dependent covariates and a mixed ZIP model with time-independent covariates is compared using simulation. Using the deviance information criterion as a measure of fit, we found that the model with time-dependent covariates exhibits a better fit than the model with time-independent covariates. KEYWORDS correlated data, count data, excess zeros, longitudinal, mixed models, model fit

Associations between screen viewing at 2 and 3.5 years and drawing ability at 3.5 years among children from the French nationwide Elfe birth cohort

The effect of screen viewing on children’s cognitive development has been of concern among parents and researchers. This study investigated the association between children screen time, as reported by parents, and drawing ability, and the confounding effects of socioeconomic characteristics (such as parental education, household income, migration status) and children’s competing activities (such as drawing practice, extracurricular activity, outdoor time, sleep time, time playing with parents). Participants included 7577 children aged 3.5 years (50% girls) who underwent the Draw-a-person test (McCarthy score [range = 0–12 points]) in the French nationwide Elfe birth cohort, initiated in 2011. Sex-stratified zero-inflated Poisson regression models were used. Increased screen time was associated with a higher likelihood to obtain a null score in boys (OR 1.15, 95% CI 1.07–1.23) and girls (1.13 [1.03–1.24]) and a lower score in girls only (β = − 0.02, 95% CI − 0.04; − 0.01). After adjusting for SES, associations were no longer observed, indicating that the association between screen time and drawing abilities was confounded by socioeconomic characteristics.

Determinants of fertility in Nigeria: An analysis of recent data

Abstract: Despite the continuous decline in fertility since the 1950s, several African nations, including Nigeria, have continued to experience population growth. Previous research has concentrated on how socioeconomic and fertility-related factors influence fertility outcomes in developing countries. It is crucial to understand the dynamics of fertility in Nigeria, a country with rapid population growth, to lower the total fertility rate (TFR), particularly in regions prone to rapid population expansion, which in turn affects the rate of development. This study sought to examine the factors influencing fertility outcomes in Nigeria. Using zero-inflated Poisson regression models, this study examined recent data from the 2018 Nigeria Demographic and Health Survey (NDHS) to determine the factors with the greatest influence on fertility in the country. The findings indicate that the sociodemographic and economic characteristics of women influence their fertility. In addition, proximate factors such as contraceptive use, marital status, and abortion were also significantly associated with fertility. Recommendations are made to the government, policymakers, and local stakeholders to maintain a national policy for citizens and development that aims to improve the education of young girls and extend their ages at first sex (and, consequently, their ages at first birth) through extended schooling. Finally, greater emphasis should be placed on promoting knowledge of the use of contraceptives.

Prediction of Tuberculosis in Iraq Using A ZIPR Model

In this article, the ZeroInflated Poisson Regression model (ZI-PRM) was used to predict the number of tuberculosis patients by estimating the model using the maximum likelihood method and compared with Poisson regression model (PRM). The results showed that the ZIPRM best represented TB data from PRM. The PRM showed that the importance of some variables, although they were not significant as a cause of the TB data. The ZIP model indicates that there will be more TB cases in 2027 than there were in 2023. These findings point to an improvement in the nation's health status.

New antipsychotic prescription and recurrent infections among adult sepsis survivors: A population-based cohort study.

Antipsychotic agents, which may increase the risk of infection through dopaminergic dysregulation, are prescribed to a fraction of patients following critical illness. We compared the rate of recurrent sepsis among patients who filled a prescription for antipsychotics with high- or low-D2 affinity. Population-based cohort with active comparator design. We included sepsis survivors older than 65 years with intensive care unit admission and new prescription of antipsychotics in Ontario 2008-2019. The primary outcome were recurrent sepsis episodes within 1 year of follow-up. Patients who filled a prescription within 30 days of hospital discharge for high-D2 affinity antipsychotics (e.g., haloperidol) were compared with patients who filled a prescription within 30 days of hospital discharge for low-D2 affinity antipsychotics (e.g., quetiapine). Multivariable zero-inflated Poisson regression models with robust standard errors adjusting for confounding at baseline were used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI). Overall, 1879 patients filled a prescription for a high-D2, and 1446 patients filled a prescription for a low-D2 affinity antipsychotic. Patients who filled a prescription for a high-D2 affinity antipsychotic did not present a higher rate of recurrent sepsis during 1 year of follow-up, compared with patients who filled a prescription for a low-D2 affinity antipsychotic (IRR: 1.12; 95% CI: 0.94, 1.35). We did not find conclusive evidence of a higher rate of recurrent sepsis associated with the prescription of high-D2 affinity antipsychotics (compared with low-D2 affinity antipsychotics) by 1 year of follow-up in adult sepsis survivors with intensive care unit admission.

Epidemiology of engagement in physical activity behaviors in people with epilepsy from National Health Interview Survey 2017

ObjectivePhysical activity (PA) participation may be beneficial for people with epilepsy (PWE) but has been discouraged due to a fear that it may induce seizures. Using data from the 2017 National Health Interview Survey, we aimed to describe current rates of PA sufficient to meet US PA Aerobic and Strength Training Guidelines (Aim #1), compare the average time PWE spend on aerobic activity and strength training activity (Aim #2), and compare rates of engagement with various types of PA (e.g., moderate, vigorous, strength training, and mind–body activities) among PWE to the general population (Aim #3). MethodsCross-sectional data (n = 26,728) were analyzed via logistic and zero-inflated Poisson regression models. PA participation was analyzed based on the US PA Guidelines (neither, strength training [≥2 times/wk], moderate to vigorous physical activity [MVPA; ≥ 150 min/wk], or both; Aim #1), time spent on activity/week (Aim #2), and activity participation (yes/no; Aim #3). Epilepsy status was coded as active epilepsy (doctor-diagnosed and either taking antiepileptic medication or had at least one seizure in 12 months; n = 335), inactive epilepsy (doctor-diagnosed, not taking antiepileptic medication nor had a seizure in 12 months; n = 213), and no history of epilepsy (n = 26,180). ResultsPeople with active epilepsy were more likely to report meeting neither (68 %, 95 % CI = 63–74 %) of the PA Guidelines compared to people with no history of epilepsy (59 %, 58–60 %). The mean duration of time reported on vigorous activity for people with inactive epilepsy was significantly higher than people with no history of epilepsy (p = 0.01). People with active epilepsy were 32–39 % less likely to report participating in any moderate or vigorous activity compared to people with no history of epilepsy. SignificanceThis study highlights activity disparities among PWE and the general population, indicating substantially lower activity and higher likelihood of inactivity in PWE, particularly active epilepsy.

Prescribed fires, smoke exposure, and hospital utilization among heart failure patients

BackgroundPrescribed fires often have ecological benefits, but their environmental health risks have been infrequently studied. We investigated associations between residing near a prescribed fire, wildfire smoke exposure, and heart failure (HF) patients’ hospital utilization.MethodsWe used electronic health records from January 2014 to December 2016 in a North Carolina hospital-based cohort to determine HF diagnoses, primary residence, and hospital utilization. Using a cross-sectional study design, we associated the prescribed fire occurrences within 1, 2, and 5 km of the patients’ primary residence with the number of hospital visits and 7- and 30-day readmissions. To compare prescribed fire associations with those observed for wildfire smoke, we also associated zip code-level smoke density data designed to capture wildfire smoke emissions with hospital utilization amongst HF patients. Quasi-Poisson regression models were used for the number of hospital visits, while zero-inflated Poisson regression models were used for readmissions. All models were adjusted for age, sex, race, and neighborhood socioeconomic status and included an offset for follow-up time. The results are the percent change and the 95% confidence interval (CI).ResultsAssociations between prescribed fire occurrences and hospital visits were generally null, with the few associations observed being with prescribed fires within 5 and 2 km of the primary residence in the negative direction but not the more restrictive 1 km radius. However, exposure to medium or heavy smoke (primarily from wildfires) at the zip code level was associated with both 7-day (8.5% increase; 95% CI = 1.5%, 16.0%) and 30-day readmissions (5.4%; 95% CI = 2.3%, 8.5%), and to a lesser degree, hospital visits (1.5%; 95% CI: 0.0%, 3.0%) matching previous studies.ConclusionsArea-level smoke exposure driven by wildfires is positively associated with hospital utilization but not proximity to prescribed fires.

Zero-Inflated Poisson Regression Modeling of Plant Protein Consumption

Summary This research fitted a discrete distribution for modeling count data. Specifically, Zero-Inflated Poisson (ZIP) regression was used to model plant protein consumption by 400 randomly sampled individuals in Wukari. The data was collected by questionnaire. The ZIP regression model was used based on its ability to model data with excess zeros present in the collected data. Variables considered and used for the analysis are Age, Body Mass Index, Blood Pressure, Occupation, Gender, Weight, Height, Body Reaction, and Consumption Class. The parameters of the ZIP model were estimated using the maximum likelihood estimation technique. The model was tested for Goodness of Fit (GoF) using deviance, scaled deviance, Pearson–χ 2 and scaled Pearson–χ 2 statistics. The results obtained showed that Age, Gender, and Reaction were significant at 5%, and the GoF tests revealed that the Zero-Inflated Poisson regression produces a good fit and is a good model for overcoming the overdispersion effect.