Zero-inflated Negative Binomial Regression Models Research Articles

Getting groceries during the pandemic: How transit remained important despite the rise of e-delivery

BackgroundWe model the use of public transit to reach grocery stores and the use of online delivery services to get groceries, before and during the COVID-19 pandemic among people who used transit regularly prior to the crisis. MethodsWe draw upon a panel survey of pre-pandemic transit riders in Vancouver and Toronto. We conduct multivariable two-step tobit regression models that predict the likelihood of a respondent using transit as their primary mode for getting groceries before the pandemic (step 1) and then during the pandemic (step 2). Models are conducted for two survey waves, May 2020 and March 2021. We also conduct zero-inflated negative binomial regression models predicting the frequency respondents ordered groceries online. ResultsTransit riders over the age of 64 were more likely to use transit to reach groceries before the pandemic and more likely to continue to do so during the pandemic (wave 1, OR, 1.63; CI, 1.24–2.14; wave 2, OR, 1.35; CI, 1.03–1.76). Essential workers were more likely to continue using transit to reach groceries during the pandemic (wave 1, OR, 1.33; CI, 1.24–1.43; wave 2, OR, 1.18; CI, 1.06–1.32). Walking distance to the nearest grocery store was positively associated with using transit to get groceries pre-pandemic (wave 1, OR, 1.02; CI, 1.01–1.03; wave 2, OR, 1.02; CI, 1.01–1.03), and in May 2020 (wave 1, OR 1.01; (1.00–1.02). During the pandemic, people who stopped using transit to get groceries were less likely to have made zero online grocery purchases (wave 1, OR, 0.56; CI, 0.41–0.75; wave 2, OR, 0.62; CI, 0.41–0.94). DiscussionPeople still physically commuting to work were more likely to still use transit to get groceries. Among transit riders, older adults and those living far walking distances from grocery stores are more likely to use transit to get groceries. Older transit riders and those with higher incomes were also more likely to use grocery delivery services, while female, Black, and immigrant riders were less likely to do so.

The association between proton pump inhibitor use and risk of post-hospitalization acute kidney injury: a multicenter prospective matched cohort study

BackgroundProton Pump Inhibitors (PPI) are among the most commonly used drugs to treat acid-related gastrointestinal disorders in the USA. Although PPI use has been linked to acute interstitial nephritis, the side effects of post-hospitalization acute kidney injury (AKI) and the progression of kidney disease still are controversial. We conducted a matched cohort study to examine the associations between PPI use and the side effects, especially in post-hospitalization AKI.MethodsWe investigated 340 participants from the multicenter, prospective, matched-cohort ASSESS-AKI study, which enrolled participants from December 2009 to February 2015. After the baseline index hospitalization, follow-up visits were conducted every six months, and included a collection of self-reported PPI use by participants. Post-hospitalization AKI was defined as the percentage increase from the nadir to peak inpatient SCr value was ≥ 50% and/or absolute increase ≥ 0.3 mg/dL in peak inpatient serum creatinine compared with baseline outpatient serum creatinine. We applied a zero-inflated negative binomial regression model to test the relationship between PPI use and post-hospitalization AKI. Stratified Cox proportional hazards regression models also were conducted to examine the association between PPI use and the risk of progression of kidney disease.ResultsAfter controlling for demographic variables, baseline co-morbidities and drug use histories, there was no statistically significant association between PPI use and risk of post-hospitalization AKI (risk ratio [RR], 0.91; 95% CI, 0.38 to 1.45). Stratified by AKI status at baseline, no significant relationships were confirmed between PPI use and the risk of recurrent AKI (RR, 0.85; 95% CI, 0.11 to 1.56) or incidence of AKI (RR, 1.01; 95% CI, 0.27 to 1.76). Similar non-significant results also were observed in the association between PPI use and the risk of progression of kidney diseases (Hazard Ratio [HR], 1.49; 95% CI, 0.51 to 4.36).ConclusionPPI use after the index hospitalization was not a significant risk factor for post-hospitalization AKI and progression of kidney diseases, regardless of the AKI status of participants at baseline.

Health service utilization among women veterans who report eating disorder symptoms.

Describe health service utilization in women veterans with eating disorder symptoms and characterize the nature of mental health services received. Women veterans (N = 191) in a northeastern Veterans Health Administration region completed the Eating Disorders Examination Questionnaire. Health service utilization was then observed for 5 years across multiple domains (i.e., mental health, primary care, telephone consultations, emergency services); negative binomial or zero-inflated negative binomial regression models (mental health) estimated the relative impact of reported eating disorder symptoms on health service utilization. After adjusting for the effects of age and body mass index, higher eating disorder symptoms were associated with higher primary care, mental health services, and telephone consultations. Eating disorder diagnoses were infrequent across the sample. Women veterans with higher self-reported eating disorder symptoms evidence higher health service utilization across common healthcare domains. Encounter data suggest that eating disorder symptoms are rarely identified or clinically addressed by providers. Existing mental health visits may represent an opportunity for selective screening for eating disorder symptoms, particularly among women who evidence known risk factors. This study reveals that women veterans with higher levels of eating disorder symptoms (e.g., dietary restriction, poor body image) use more primary care, mental health, and telephone consultations than others, but may not receive services that target disordered eating. Opportunities may exist to better identify eating disorder symptoms in the context of existing mental health visits, or potentially to combine treatment for eating disorder symptoms into their mental health care.

Organizational Agility and Communicative Actions for Responsible Innovation: Evidence from manufacturing firms in South Korea

Responsible Innovation (RI) has increasingly attracted attention in academic research and business practice for UN Sustainable Development Goals (SDGs). Especially, the UN Economic and Social Commission for Asia and the Pacific (UNESCAP) highlights RI as a key concept to address how to institutionalize and organize action programs to solve grand challenges. However, we know little about the determinants of organizing RI in business. By applying agile management and stakeholder theory, this study proposes the critical organizational factors to implement RI, namely: Organizational Agility and Communicative Actions. Based on the large-scale data analysis of 13,234 South Korean manufacturing firms during the period between 1999 and 2019, this paper investigates whether and how organizational factors can affect RI in the Asian context, using the zero-inflated negative binomial regression model. Findings show that well-organized agile management and communicative actions with stakeholders are essential to enhance RI performance in a holistic view. This study contributes to the recently emerging field of RI and offers novel theoretical and practical implications for academics and practitioners regarding the underlying mechanism of organizing RI.

Spatial distribution and determinants of childhood vaccination refusal in the United States.

Parental refusal and delay of childhood vaccination has increased in recent years in the United States. This phenomenon challenges maintenance of herd immunity and increases the risk of outbreaks of vaccine-preventable diseases. We examine US county-level vaccine refusal for patients under five years of age collected during the period 2012-2015 from an administrative healthcare dataset. We model these data with a Bayesian zero-inflated negative binomial regression model to capture social and political processes that are associated with vaccine refusal, as well as factors that affect our measurement of vaccine refusal. Our work highlights fine-scale socio-demographic characteristics associated with vaccine refusal nationally, finds that spatial clustering in refusal can be explained by such factors, and has the potential to aid in the development of targeted public health strategies for optimizing vaccine uptake.

Comparing the Travel Behavior of Older Users Between Station-Based and Dockless Bike Sharing Systems

As the population worldwide continues to age, providing improved mobility services for older people becomes increasingly crucial. In recent years, the maturation of bike sharing has led older people to progressively incorporate it into their everyday lives. In this study, station-based bike sharing (SBBS) and dockless bike sharing (DBS) are investigated in relation to older population mobility. This research relies on the fusion of multiple data sources, including SBBS and DBS trip records, point of interest (POI), and meteorological conditions in Nanjing, China. A zero-inflated negative binomial regression model is used to compare the travel behaviors among various age groups with the exposure variable. SBBS outperforms DBS in relation to age equity, while diverse travel behavior patterns are exhibited between the age groups. Although younger users are the majority of users, older users travel more frequently than younger users in bike sharing services. Also, older users are more likely to use shared bikes near the religious and health POIs, as well as in higher population density areas. This study provides beneficial insights into the transport equity and service improvement of bike sharing systems.

Modeling red-light running behavior using high-resolution event-based data: a finite mixture modeling approach

To effectively reduce the number of red-light violations and crashes, it is crucial to explore RLR behavior at local intersections, understand the contributing factors, and identify the riskiest intersections by estimating RLR frequency. In this study, a finite mixture modeling method was utilized to understand the contributing factors to RLR behavior and estimate this violating behavior. To develop the RLR estimation models, performance metrics and signal phasing data were collected from the Automated Traffic Signal Performance Measures (ATSPMs) system in two jurisdictions in Arizona: Pima County and the Town of Marana. The results from calibrated models showed that an increase in traffic flow, intersection delay, number of approach lanes, and split failure is associated with an increase in the likelihood of observing red-light violations. In addition, it was found that an increase in cycle length is associated with a decrease in the likelihood of observing the red-light violation. The results of comparing the proposed RLR estimation method with several conventional methods, the Poisson Generalized Linear Model (PGLM), Zero-inflated Poisson Regression Model (ZIPM), and Zero-inflated Negative Binomial Regression Model (ZINB) showed the proposed method outperforms all the models in terms of both model fit and accuracy. The application of the proposed method could be used to analyze the intersections with the highest number of red-light violations. Furthermore, the presented transferability results can be advantageous to transportation agencies within Arizona and urban areas with similar characteristics by providing insight into which model specifications may provide the best RLR estimation accuracy.

Spatial and racial covid-19 disparities in U.S. nursing homes

In many parts of the world nursing home residents have experienced a disproportionate risk of exposure to COVID-19 and have died at much higher rates than other groups. There is a critical need to identify the factors driving COVID-19 risk in nursing homes to better understand and address the conditions contributing to their vulnerability during public health crises. This study investigates the characteristics associated with COVID-19 cases and deaths among residents in U.S. nursing homes from 2020 to 2021, with a focus on geospatial and racial inequalities. Using data from the Centers for Medicare and Medicaid Services and LTCFocus, this paper uses zero-inflated negative binomial regression models, Kruskal-Wallis tests, and Local Moran's I to generate statistical and geospatial results. Our analysis reveals that majority Hispanic facilities have alarmingly high COVID-19 cases and deaths, suggesting that these facilities have the greatest need for policy improvements in staffing and financing to reduce racial inequalities in nursing home care. At the same time we also detect COVID-19 hot spots in rural areas with predominately White residents, indicating a need to rethink public messaging strategies in these areas. The top states with COVID-19 hot spots are Kentucky, Pennsylvania, Illinois, and Oklahoma. This research provides new insights into the socio-spatial contexts and inequities that contribute to the vulnerability of nursing home residents during a pandemic.

Use of historical remote monitoring data to determine predictors of CPAP non-compliance in patients with OSA.

Continuous positive airway pressure (CPAP) is the gold standard treatment for obstructive sleep apnoea. This study aimed to use complete usage data collected remotely from modern CPAP devices to identify compliance trends and clinical predictors of CPAP usage. Group usage data were analysed for a large cohort at a single tertiary sleep-centre before a detailed review of a 90-day reporting window for each patient was conducted. Individual data were collected for a smaller cohort of patients including demographics, past medical history and diagnostic sleep study results. A zero-inflated negative binomial regression model was used to determine associations between patient characteristics and usage days. Of 6450 patients who wereprescribed CPAP and included in the initial service analysis, 476 patients wereincluded in the sub-group. Complete usage data revealed that 46% of patients were fully compliant with CPAP therapy. Compliance fell from 55 to 46% by day 90 and remained at this rate going forward. Significant predictors of CPAP non-compliance included being in the lowest quartile of Index of Multiple Deprivation scores (most deprived) compared with the highest quartile (least deprived) (p = .005), and less severe oxygen desaturation index (ODI) on diagnosis (p = .03). Complete usage data show that compliance at day 90 appears to be a good indicator of future CPAP usage. Predictors of CPAP non-compliance may include lower socioeconomic status, and lower ODI.

Modified ridge-type estimator for the zero inflated negative binomial regression model

The Zero-inflated negative binomial (ZINB) regression models are commonly used for count data that shows an over-dispersion and extra zeros. Multicollinearity is considered to be a significant issue in the estimation of parameters in the ZINB regression model. Thus, to alleviate the negative effects of multicollinearity, a new estimator called ZINB modified ridge type (ZINBMRT) estimator is proposed. Furthermore, we proposed some new approaches to estimate the shrinkage parameters for the ZINBMRT estimator. A Monte Carlo simulation study and illustrative example are given to show the superiority of the proposed ZINBMRT estimator over some of the existing estimation methods. Based on the findings of simulation study and example, it is observed that the proposed ZINBMRT estimator under different suggested parameters give a better performance over the other competitive estimators.

Healthcare utilization among pre-frail and frail Puerto Ricans.

Frailty is associated with adverse health outcomes and greater healthcare utilization. Less is known about the relationship between frailty and healthcare utilization in Puerto Rico, where high rates of chronic conditions and limited healthcare may put this group at a higher likelihood of using healthcare resources. This study examined the association between pre-frailty and frailty with healthcare utilization at baseline and 4-year follow-up among a cohort of community dwelling Puerto Ricans living on the island. We examined data from 3,040 Puerto Ricans (mean age 70.6 years) from The Puerto Rican Elderly: Health Conditions (PREHCO) study between 2002-2003 and 2006-2007. We used a modified version of the Fried criteria defined as 3 or more of the following: shrinking, weakness, poor energy, slowness, and low physical activity. Pre-frailty was defined as 1-2 components. The number of emergency room visits, hospital stays, and doctor visits within the last year were self-reported. Zero-inflated negative binomial regression models were used for ER visits and hospital stays. Negative binomial models were used for doctor visits. Pre-frailty was associated with a higher rate of doctor visits with a rate ratio of 1.11 (95% CI = 1.01-1.22) at baseline. Frailty was associated with a higher rate of ER visits (1.48, 95% CI = 1.13-1.95), hospital stays (1.69, 95% CI = 1.08-2.65), and doctor visits (1.24, 95% CI = 1.10-1.39) at baseline. Pre-frailty and frailty were not associated with any healthcare outcomes at follow-up. Pre-frailty and frailty are associated with an increased rate of healthcare services cross-sectionally among Puerto Rican adults, which may cause additional burdens on the already pressured healthcare infrastructure on the island.

Association Between Frailty and Antiseizure Medication Tolerability in Older Adults With Epilepsy.

Frailty is an important aspect of biological aging, referring to the increased vulnerability of individuals with frailty to physical and psychological stressors. While older adults with epilepsy are an important and distinct clinical group, there are no data on frailty in this population. We hypothesize that frailty will correlate with the seizure frequency and especially the tolerability of antiseizure medications (ASMs) in older adults with epilepsy. We recruited individuals aged 60 years or older with active epilepsy from 4 Canadian hospital centers. We reported the seizure frequency in the 3 months preceding the interview, while ASM tolerability was quantified using the Liverpool Adverse Events Profile (LAEP). We applied 3 measures of frailty: grip strength as a measure of physical frailty, 1 self-reported score (Edmonton frail score [EFS]), and 1 scale completed by a healthcare professional (clinical frailty scale [CFS]). We also administered standardized questionnaires measuring levels of anxiety, depression, functional disability, and quality of life and obtained relevant clinical and demographic data. Forty-three women and 43 men aged 60-93 years were recruited, 87% of whom had focal epilepsy, with an average frequency of 3.4 seizures per month. Multiple linear regression and zero-inflated negative binomial regression models showed that EFS and CFS scores were associated with decreased ASM tolerability, each point increase leading to 1.83 (95% CI: 0.67-4.30) and 2.49 (95% CI: 1.27-2.39) point increases on the LAEP scale, respectively. Neither the EFS and CFS scores nor grip strength were significantly associated with seizure frequency. The EFS was moderately correlated with depression, anxiety, quality of life, and functional disability, demonstrating the best construct validity among the 3 tested measures of frailty. The EFS was significantly, both statistically and clinically, associated with ASM tolerability. It also showed multiple advantages in performance while assessing for frailty in older adults with epilepsy, when compared with the 2 other measures of frailty that we tested. Future studies must focus on what role the EFS during epilepsy diagnosis may play in ASM selection among older adults with epilepsy.

Patient-Reported Outcomes in Cancer Patients with HIV.

Elevated cancer-specific mortality in PWH has been demonstrated for non-AIDS-defining malignancies. However, additional clinical endpoints of interest, including patient-reported outcomes (PROs), have not been systematically examined in PWH and cancer. We evaluated differences in patient-reported symptomology between cancer patients with versus without HIV using data from 12,529 patients at the Moffitt Cancer Center, including 55 with HIV. The symptoms were assessed using the Edmonton Symptom Assessment Scale (ESAS), which asks patients to rank 12 symptoms on a scale of 1−10, with scores ≥7 considered severe. The responses across all questions were summed to create a composite score. Vital status through t July 2021 was determined through linkage to the electronic health record. PWH reported a higher composite ESAS score on average (44.4) compared to HIV-uninfected cancer patients (30.7, p-value < 0.01). In zero-inflated negative binomial regression models adjusted for cancer site, sex, and race, the composite ESAS scores and the count of severe symptoms were 1.41 times (95% CI: 1.13−1.77) and 1.45 times (95% CI: 1.09−1.93) higher, respectively, in cancer patients with HIV. Among PWH, higher ESAS scores were associated with mortality (p-value = 0.02). This is the first demonstration of uniquely poor PROs in PWH and cancer and suggests that patient symptom monitoring to improve clinical endpoints deserves further study.

Decline in dental caries experience among schoolchildren in Taiwan, 2012-2020.

This study investigated the association between the decline of the decayed, missing, and filled teeth (DMFT) index and several family-level and individual-level factors among 6- to 18-year-old Taiwanese children from 2012 to 2020. This study used data from the 2012 and 2020 Taiwan National Oral Health Survey of Children and Adolescents. Both surveys used similar methods and were performed in the same study age group. A structured questionnaire was used to collect data on parents' sociodemographic background; the number of children in the family; oral health-related knowledge, attitudes, and behaviours; and children's dietary habits. Dental caries was recorded through standardized oral examinations. Multivariable multilevel zero-inflated negative binomial regression models were used to determine the association between family-level and individual-level factors and the DMFT index from 2012 to 2020. A total of 10217 and 10436 schoolchildren completed the oral examinations and questionnaires in the 2012 and 2020 surveys, respectively. The adjusted mean DMFT index of 12-year-old Taiwanese schoolchildren in 2020 was 2.01, denoting a significant decline from 2.50 in 2012 (adjusted mean ratio=0.20, 95% confidence interval [CI]=0.17, 0.23, p < .0001). Furthermore, children who often consumed sugar-rich drinks had a significantly higher risk (mean ratio=1.05, 95% CI=1.01, 1.10) of having DMFT than those who seldom consumed such drinks (p=.017). In the period of 2012-2020, the DMFT index among Taiwanese children significantly declined. Children who often consumed sugar-rich drinks had a higher DMFT index than those who seldom consumed such drinks. Our findings are valuable to paediatricians, dentists, nutritionists, and public health policymakers.

Abstract 15002: Real-World Healthcare Resource Utilization Among US Patients With Atrial Fibrillation Receiving Dronedarone versus Ablation as 1st-Line Therapy

Introduction: Catheter ablation is used increasingly as a 1st-line (1L) alternative to antiarrhythmic drugs (AAD) including dronedarone in patients with atrial fibrillation (AF). Healthcare resource utilization (HCRU)-related costs with dronedarone vs 1L ablation are unknown. Methods: We conducted a retrospective, observational cohort study using Optum Clinformatics Data Mart® from Jan 2012-Jan 2022 among US adults with AF and no prior rhythm control therapy who received new AAD therapy with dronedarone (index: date of incident dronedarone fill) vs those who received 1L ablation, or a non-dronedarone AAD followed by ablation within 3 mo (index: date of first recorded ablation or AAD). Patients were required to have ≥24 mo of pre-index data, and ≥3 mo follow-up. Patients in the 1L ablation cohort were propensity score matched 2:1 to the dronedarone cohort. Mean payer costs per patient per month (PPPM) during the 24-mo post-index period were calculated for total HCRU, inpatient visits, emergency room (ER) visits, outpatient physicians’ office visits, and all outpatient visits, and compared by zero-inflated negative binomial (ZINB) regression model. Results: Post-matching, the dronedarone (n=1440) and 1L ablation (n=2253) cohorts had similar baseline characteristics (mean age at index: 68.4 vs 67.7 years; male: 57.7% vs 59.3%; mean time from AF diagnosis to index: 80.2 vs 91.6 days; Charlson comorbidity index: 2.3 vs 2.2; CHADS2-VASc score: 3.4 vs 3.2). Mean PPPM costs were lower with dronedarone vs 1L ablation for all-cause total HCRU, inpatient visits, any outpatient visit, ER visit, and outpatient office visit (Table). ZINB analyses showed significant cost differences for all-cause total HCRU and any outpatient visit events. Conclusion: In patients with AF and no prior rhythm control therapy, 1L dronedarone was associated with lower total HCRU and outpatient visit costs during 24-mo follow-up vs 1L ablation; future studies will assess cost-effectiveness.

Modelling the Relationship between Weather Variables and Yellow Stem Borer Population: A Count Data Modelling Approach

Aim: This study was conducted to model the relationship between discrete dependent variable (yellow stem borer population) and continuous weather variables.&#x0D; Data Description: The yellow stem borer (YSB) population and standard meteorological week (SMW) wise weather variables (temperature, relative humidity, rainfall and sunshine hours) data of Warangal centre (Telangana state) generated under All India Co-Ordinated Rice Improvement Project (AICRIP) from 2013-2021 were considered for the study. The YSB population were recorded daily using light trap with an incandescent bulb and are counted as weekly cumulative catches.&#x0D; Methodology: The weekly cumulative trapped YSB populations and weekly averages of climatological data were considered as inputs to the models under consideration. In this study the classical linear regression i.e. step-wise multiple linear regression and count regression models such as Poisson, negative binomial, zero inflated Poisson and zero inflated negative binomial regression models were employed.&#x0D; Result: The empirical results revealed that the zero inflated count regression models viz., zero inflated Poisson regression and zero inflated negative binomial regression models performed better compared to the classical linear regression, Poisson and negative binomial regression models, further the negative binomial regression model outperformed all models as it yielded lowest mean square error (MSE) and highest R2 values. The average percentage reduction in accuracy of zero-inflated negative binomial regression model over classical model was around 4 percent.&#x0D; Conclusion: Based on the results obtained in this study, it is concluded that the zero inflated models performs better compared to classical models as they are unable to handle the presence of excess zeroes, as a result provides more prediction error and lower R2 values. Further, the models developed in this study will be of great assistance in identifying the factors influencing occurrence of YSB population in rice.

Measles Disease Analysis in Bengkulu Province Using Zero Inflated Poisson Regression and Zero Inflated Negative Binomial Regression

Zero Inflated Poisson regression (ZIP) and Zero Inflated Negative Binomial (ZINB) regression were used if there was overdispersion and no multicollinearity in the data. This study aims to analyze measles in Bengkulu Province using the ZIP and ZINB regression models. Among them are selecting the best model, seeing the influential variables from the best model, and predicting the results of the best model. The data used is one dependent variable, namely the number of measles cases (Y) in each puskesmas and six independent variables (X) namely the percentage of measles immunization, the amount of malnutrition, the percentage of exclusive breastfeeding, the percentage of vitamin A, the percentage of proper sanitation, and the percentage of healthy house. The results of this study, the ZIP regression model formed is a discrete model for , namely ln()=-5.042-0.007X1-0.014X3+0.094X4 and a zero inflation model for , namely logit()= -3.656+0.101X4-0.054X6, while the ZINB regression model formed is a discrete model for , namely ln()=-9,289+0.120X4 and a zero inflation model for , namely logit()=- 17.841+0.205X4. The AIC value of the ZINB regression model is 255.249, which is smaller than the AIC value of the ZIP regression model of 331.467, so the ZINB regression model is better to use. The influential variable in this study is the percentage of vitamin A administered. There is not much difference between predicted results and the actual data.

Evaluación del tamaño y número de tubérculos de papa amarilla bajo diferentes densidades de siembra usando modelos cero inflados

A field study was carried out on the cultivation of the yellow diploid potato (Solanum tuberosum Phureja Group) to evaluate the influence of the planting density associated with distances between plants of 30, 40, and 50 cm and distances between the rows and paths of 100 cm on the tuber count with sizes less than 2 cm, 2-4 cm, 4-6 cm, and more than 6 cm. At the time of the harvest of the tubers, they were classified by size and respective count was made. The modelling of the counts was done by means of the usual negative binomial regression and by the inflated zeros option. The zero-inflated negative binomial regression models showed a significant effect of the sowing density on the tuber count in the sizes that were superior to 4 cm while the negative binomial model showed a significant effect it in the case of the sizes lower than 4 cm. The results on size and density are attributes of interest in both the agronomic management of this crop and in the industrial management of the tubers, so the relationship that we found can be adopted in both areas to generate the desired attributes of the crop for improving the production and guiding the process of industrialization.

The association between food insecurity and physical activity in adults with serious mental illness living in supportive housing

Rates of food insecurity are high among adults with serious mental illness (SMI); this population also engages in less physical activity than the general population. However, the relationship between food insecurity and physical activity in this group has not been explored. We examined food insecurity prevalence and its association with physical activity in 314 adults with SMI living in supportive housing in New York City and Philadelphia and enrolled in an institutional review board-approved randomized controlled trial of a Peer Group Lifestyle Balance (PGLB) program. We analyzed 2014 baseline survey data, including demographic data and self-reported food security, and four self-reported physical activity outcomes: any physical activity per week (yes/no) and 2) total, 3) moderate, or 4) vigorous physical activity minutes per week. A logistic regression model examined food security as a predictor of any physical activity; zero-inflated negative binomial regression models were used for the other three physical activity outcomes; demographic and clinical predictors were assessed for inclusion in models. Over half of participants (51.7%) reported low or very low levels of food security. Relationships between food insecurity and three physical activity measures (any physical activity, total weekly minutes, and moderate weekly minutes) were non-significant; those with lower food security were more likely to engage in vigorous physical activity. The high food insecurity prevalence highlights the importance of measuring and addressing food security in populations experiencing SMI; measuring physical activity is also important for tailored lifestyle recommendations. Future studies should examine longitudinal changes in food security and physical activity.

Streptococcus mutans carriage in the saliva of mothers and its association with dental caries and Streptococcus mutans carriage in the saliva of children between 6 and 30 months old in a low-income setting in Karachi, Pakistan.

Early childhood caries poses a significant health issue in children under 6 years old. It is determined that Streptococcus mutans is a primary etiological agent, likely to be transferred through maternal contact. To determine the association of maternal S. mutans counts with S. mutans counts in their children between 6 and 30 months of age, and to determine the maternal and child DMFT (decayed, missing, and filled teeth) indices. A community-based cross-sectional study was conducted in Karachi, Pakistan. A sample of 193 dyads of mother-children (6-30 months of age) was selected via purposive sampling. Saliva samples of the dyads were collected to assess S. mutans count. Caries assessment was performed for both using the DMFT index. A pretested questionnaire was used. The association of bottle-feeding, oral hygiene measures, and other factors with S. mutans counts in children were also explored. Zero-inflated negative binomial regression model at a 5% level of significance was applied using STATA version 12.0. Out of 193 children, 109 (56.47%) were males and 84 (43.52%) were females. The mean age of mothers and children was 29.4 ± 6.2 years and 19.54 ± 6.8 months, respectively. Maternal S. mutans counts were not statistically associated with child's S. mutans counts (Mean child's S. mutans count ratio: 1; 95% confidence interval [CI]: 1, 1.01; p = .882). Compared with children who were breastfed, S. mutans counts were higher in children who were bottle-fed (mean S. mutans count ratio= 4.85 [95% CI: 1.53, 15.41], p = .007). Age of mother and present caries status of mothers was significantly associated with the child's S. mutans count. No association between maternal S. mutans and child S. mutans was observed. However, maternal age, children who were breastfed, children who did not use pacifiers,and children with mothers who did not have caries, exhibited low S. mutans counts in their saliva.