The Role of Household Structure and Composition in Influencing Complementary Feeding Practices in Ethiopia

While the household in which a child grows up is considered a critical environment that influences nutrition outcomes, there is little research examining the influence of household composition and structure on complementary feeding practices. This study examined the influence of household structure and composition on complementary feeding practices, using the Ethiopian Demographic and Health Survey (EDHS), 2000 to 2016. The composition variables were calculated from the attributes of household members (alters) and the structure variables from their kinship status. A multilevel mixed-effects regression model, specifying survey rounds as the random effect, was used to examine the association between household structure/composition and the Minimum Meal Frequency (MMF) and Minimum Dietary Diversity (MDD). The average Marginal Effects (MEs) were calculated to facilitate practical interpretation. Children of caregivers with a higher number of alters (degree), unique number of kinship category (effect size), closely related (constraint), and mixed-age alters (age diversity) seemed to increase the probability of meeting the MDD. Degree and effective size decreased the probability of meeting MMF, while constraint increased it. Overall, this study revealed some associations between household structure and composition and complementary feeding practices. Hence, complementary feeding interventions could be adapted to account for the household structure and composition variations.

Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany

Agricultural production is highly dependent on the weather. The mechanisms of action are complex and interwoven, making it difficult to identify relevant management and adaptation options. The present study uses random forests to investigate such highly non-linear systems for predicting yield anomalies in winter wheat at district levels in Germany. In order to take into account sub-seasonality, monthly features are used that explicitly take soil moisture into account in addition to extreme meteorological events. Clustering is used to show spatially different damage potentials, such as a higher susceptibility to drought damage from May to July in eastern Germany compared to the rest of the country. In addition, relevant heat effects are not detected if the clusters are not sufficiently defined. The variable with the highest importance is soil moisture in March, where higher soil moisture has a detrimental effect on crop yields. In general, soil moisture explains more yield variations than the meteorological variables. The approach has proven to be suitable for explaining historical extreme yield anomalies for years with exceptionally high losses (2003, 2018) and gains (2014) and the spatial distribution of these anomalies. The highest test R-squared (R2) is about 0.68. Furthermore, the sensitivity of yield variations to soil moisture and extreme meteorological conditions, as shown by the visualization of average marginal effects, contributes to the promotion of targeted decision support systems.

Marginal Effects of Multiple Years of Volunteering on Objective and Subjective Measures of Cognition

Volunteering is conducive to older Americans’ physical and mental health; however, the effect of volunteering on cognitive health is less studied. Using four waves (2010-2016) of the Health and Retirement Study, this study examined the incremental effect of volunteering engagement on older adults’ cognitive health. We included10,718 cognitively unimpaired, community-dwelling individuals aged 51+ in 2010 and were alive through 2016. Volunteering engagement was measured by the number of times respondents participated in volunteering throughout the four waves. Objective cognition was assessed using the Telephone Interview for Cognitive Status (TICS), a standardized test of cognitive functioning. The TICS score was further categorized into three statuses: “No impairment,” “Cognitive impairment no dementia (CIND),” and “Dementia.” Subjective cognition referred to self-rated memory on a 5-point Likert scale. With sampling weights, ordered logit regression was performed controlling for health-related variables (e.g., health conditions, depression), SES (e.g., income, assets), contextual features (e.g., neighborhood safety, urbanicity), and sociodemographics. The average marginal effects (AMEs) were produced. Results show that more volunteering engagement significantly reduced the likelihood of CIND or dementia (OR=0.88, p<0.001). Specifically, every one-time increase in volunteering increased the probability of remaining cognitively normal by 0.01 (p<0.001), whereas it decreased the probability of CIND by 0.008 (p<0.001) and dementia by 0.001 (p<0.001). For subjective cognition, there was no significant relationship with volunteering. Our findings address gaps in literature by adding evidence of the incremental health benefits of volunteering on cognitive functioning. Differences in the findings for subjective and objective cognition warrant further investigation.

Sustainable Careers: Reliability of Job Satisfaction Predictors for Employees Aged 50+. Evidence from Romanian Development Regions

In this paper, we analyze the determinants of job satisfaction for employees over the age 50 or more, using the latest SHARE-ERIC dataset (Wave 7) filtered for Romania (over 2000 records). After applying logistic regressions with average marginal effects, we obtained an overall and seven regional models which emphasize that a good atmosphere at the workplace and the deserved recognition received for the work done are the most reliable predictors of career satisfaction, confirmed in this order of importance by many other robustness checks. Particularly, in the case of respondents from the Western part of Romania, we found that meritocracy-based influence, namely deserved recognition, counts almost as much as the workplace atmosphere. For these individuals, previous educational performance and lifetime employment at a single job matter more than the previous dual-core on job satisfaction. Unexpectedly, the adults from central romania present a negative influence of life satisfaction on job satisfaction due to an unbalanced work-family vision of life. The locus of control has different effects on job satisfaction in south and south-western regions, while in the north-east, meaning in life is negatively influencing job satisfaction. Bridge employment exerts a negative influence on career satisfaction in the north-west, and in the South-East, and interpersonal trust has a positive effect.

A Robust Approach for Identifying the Major Components of the Bribery Tolerance Index

The paper aims to emphasize the advantages of several advanced statistical and data mining techniques when applied to the dense literature on corruption measurements and determinants. For this purpose, we used all seven waves of the World Values Survey and we employed the Naive Bayes technique in SQL Server Analysis Services 2016, the LASSO package together with logit and melogit regressions with raw coefficients in Stata 16. We further conducted different types of tests and cross-validations on the wave, country, gender, and age categories. For eliminating multicollinearity, we used predictor correlation matrices. Moreover, we assessed the maximum computed variance inflation factor (VIF) against a maximum acceptable threshold, depending on the model’s R squared in Ordinary Least Square (OLS) regressions. Our main contribution consists of a methodology for exploring and validating the most important predictors of the risk associated with bribery tolerance. We found the significant role of three influences corresponding to questions about attitudes towards the property, authority, and public services, and other people in terms of anti-cheating, anti-evasion, and anti-violence. We used scobit, probit, and logit regressions with average marginal effects to build and test the index based on these attitudes. We successfully tested the index using also risk prediction nomograms and accuracy measurements (AUCROC > 0.9).

Impacts of innovation in dental care delivery and payment in Medicaid managed care for children and adolescents

Background We evaluated a 14-county quality improvement program of care delivery and payment of a dental care organization for child and adolescent managed care Medicaid beneficiaries after 2 years of implementation. Methods Counties were randomly assigned to either the intervention (PREDICT) or control group. Using Medicaid administrative data, difference-in-difference regression models were used to estimate PREDICT intervention effects (formally, “average marginal effects”) on dental care utilization and costs to Medicaid, controlling for patient and county characteristics. Results Average marginal effects of PREDICT on expected use and expected cost of services per patient (child or adolescent) per quarter were small and insignificant for most service categories. There were statistically significant effects of PREDICT (p < .05), though still small, for certain types of service: Expected number of diagnostic services per patient-quarter increased by .009 units; Expected number of sealants per patient-quarter increased by .003 units, and expected cost by $0.06; Total expected cost per patient-quarter for all services increased by $0.64. These consistent positive effects of PREDICT on diagnostic and certain preventive services (i.e., sealants) were not accompanied by increases in more costly service types (i.e., restorations) or extractions. Conclusion The major hypothesis that primary dental care (selected preventive services and diagnostic services in general) would increase significantly over time in PREDICT counties relative to controls was supported. There were small but statistically significant, increases in differential use of diagnostic services and sealants. Total cost per beneficiary rose modestly, but restorative and dental costs did not. The findings suggest favorable developments within PREDICT counties in enhanced preventive and diagnostic procedures, while holding the line on expensive restorative and extraction procedures.

Co-Resident Grandparent: A Burden or a Relief? A Comparison of Gender Roles between Italians and Migrants

In the international literature, the principal task of grandparents is generally recognized as helping their children in providing childcare. Most of those studies analyzed grandparental childcare on the whole population, and few have focused on co-resident grandparent(s), which turns out to be an understudied topic in the European context. Further, most of them investigated the effect of childcare on grandparents’ health status. However, the elderly population can both provide and receive care. Using two Italian surveys released by the Italian National Institute of Statistics, the “Social Condition and Integration of Foreign Citizen (2011–2012)” and the “Multiscopo–Aspetti della vita quotidiana (2011)”, the study aims to analyze differences in grandparental childcare provided by co-resident grandparents between Italian and migrant households, considering both the role played by grandparents’ self-rated health (SRH) and gender. We identify four grandparents’ profiles by combining grandparents’ SRH and their attitude towards looking after their grandchild(ren). Subsequently, we apply multinomial logistic regressions, and we compute average marginal effects to facilitate results interpretations. Results display that migrant co-resident grandparents are less likely to declare bad SRH and no-childcare and are more likely to declare good SRH and to provide childcare than Italian grandparents. Moreover, when considering gender differences, the real role is revealed: we find that women have a higher probability to report poor health and care for their grandchild(ren) than men. Such findings illustrate that grandparents’ cohabitation decision is based upon the difference between their need for care and offer to care, and second, in addition to migrant status and SRH, gender is a determinant of grandparents’ childcare: women look after their grandchild(ren) more than men, whatever their health status.

Machine learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany

Agricultural production is highly dependent on the weather. The mechanisms of action are complex and interwoven, making it difficult to identify relevant management and adaptation options. The present study uses random forests to investigate such highly non-linear systems for predicting yield anomalies in winter wheat at district level in Germany. In order to take into account sub-seasonality, monthly features are used that explicitly take soil moisture into account in addition to extreme meteorological events. Clustering is used to show spatially different damage potentials, such as a higher susceptibility to drought damage from April to July in eastern Germany compared to the rest of the country. The variable that explains most differences is soil moisture in March, where higher soil moisture has a detrimental effect on crop yields. In general, soil moisture explains more yield variations than the meteorological variables, while the top 25 cm of soil moisture is a better yield predictor than the total soil column. The approach has proven to be suitable to explain historical extreme yield anomalies for years with exceptionally high losses (2003, 2018) and gains (2014) and the spatial distribution of these anomalies. The highest test R-square is about 0.70. Furthermore, the sensitivity of yield variations to soil moisture and extreme meteorological conditions, as shown by the visualisation of average marginal effects, contributes to the promotion of targeted decision support systems.

Anti-Smoking Media Campaigns and Disparities in Smoking Cessation in the United States, 2001-2015

Purpose: To evaluate sociodemographic differences in the relationship between state and national anti-smoking media campaigns and cessation behaviors among adult smokers in the U.S. Design: Repeated cross-sectional analysis. Setting: U.S. nationally representative survey of adults ages 18 and older, 2001-2015. Subjects: 76,278 year-ago smokers from the 2001-2015 Tobacco Use Supplement to the Current Population Survey. Measures: Area-level exposure to State-sponsored and “Tips from former smokers” anti-tobacco media campaigns was the primary predictor of this study. Outcome variables included: quit attempt in the past 12 months, past 30-day smoking cessation, and past 90-day smoking cessation among year-ago smokers. Analysis: We conducted modified Poisson regression models to examine the association between media campaign exposure and cessation behaviors. We also examined effect modification on the additive scale by sex, race/ethnicity, income, and education using average marginal effects. Results: Year-ago smokers with greater exposure to media campaigns were more likely to report 30-day (Prevalence Ratio [PR]: 1.18, CI: 1.03, 1.36) and 90-day cessation (PR: 1.18, CI: 1.00, 1.41) compared to respondents with less campaign exposure. We found no evidence of effect modification by sociodemographic variables. Conclusion: Exposure to anti-smoking media campaigns were associated with year-ago smokers’ cessation behaviors. However, there were no differences in the association by sex, race/ethnicity, income, or education, indicating that broadly focused media campaigns may be insufficient to reduce smoking cessation among priority populations, and thus health disparities generally.

Couple communication and contraception use in urban Senegal

Objectives: Couple communication about family planning has been shown to increase uptake of contraception. However, couple communication is often measured based solely on one partner’s report of communication. This research investigates the influence of couple-reported communication about family planning on current and future use of contraception using couple-level data. Methods: We used baseline data from the Measurement, Learning, and Evaluation (MLE) project collected through household surveys in 2011 from a cross-sectional representative sample of women and men in urban Senegal to conduct secondary data analysis. We used multivariable logit models to estimate the average marginal effects of couple communication about family planning on current contraception use and future intention to use contraception. Results: Couple communication about family planning reported by both partners was significantly associated with an increased likelihood of current use of contraception and with future intention to use contraception among non-contracepting couples. Couples where one partner reported discussing family planning had a 25% point greater likelihood of current contraception use than couples where neither partner reported discussing, while couples where both partners reported discussing family planning had a 56% point greater likelihood of current contraception use, representing more than twice the effect size. Among couples not using contraception, couples where one partner reported discussing family planning had a 15% point greater likelihood of future intention to use contraception than couples where neither partner reported discussing, while couples where both partners reported discussing family planning had a 38% point greater likelihood of future intention to use contraception. Conclusion: These findings underscore the importance of the inclusion of both partners in family planning programs to increase communication about contraception and highlight the need for future research using couple-level data, measures, and analysis.