Trends and Influencing Factors of Complementary Feeding Practices in Niger: An Analysis of National Surveys From 2000 – 2018

Objectives To examine the trends and influencing factors of suboptimal complementary feeding (CF) practices among children aged 6–23 months in Niger using national data from 2000 to 2018. Methods Using data from the 2000 Multiple Indicator Cluster Survey, 2012 Demographic and Health Surveys (DHS), and 2018 Standardized Monitoring and Assessment of Relief and Transitions survey in Niger, the trends and predictors of WHO-UNICEF CF indicators including timely introduction of complementary foods (INTRO), minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD) were estimated. Using the most completed data in CF and influencing factors (available from 2012 DHS), multilevel logistic regression models were applied to identify factors at the individual, household and community levels that were associated with meeting INTRO, MMF, MDD, and MAD. Results The weighted proportion of children aged 6–8 months meeting INTRO increased from 56.0% in 2000 to 84.4% in 2018. The weighted proportion of children meeting MMF (51.3% to 77.9%), MDD (9.8% to 14.2%), and MAD (5.6% to 10.9%) also increased between 2012 - 2018. At the individual level, children with mothers who were employed had higher odds of meeting all four indicators as compared to those whose mothers were unemployed. Older child age and maternal exposure to media were significantly associated with higher odds of meeting MMF, MDD, and MAD. Maternal education and child birth weight greater or smaller than average (reference) were positively associated with the odds of meeting MMF and MAD, and antenatal iron supplementation and currently breastfeeding were positively associated with the odds of achieving MDD and MAD. At the household level, the odds of meeting MMD and MAD were higher among children from wealthier households. At the community level, the odds of meeting INTRO and MMF were higher among children from communities with greater access to health services. Conclusions Despite the improvement in CF practices since 2000, only 10% of children from 6–23 months received minimum acceptable diets. Factors associated with CF were distributed across individual, household and community levels, suggesting the need for multi-level strategies to improve child nutrition in Niger. Funding Sources UNICEF West and Central Africa Regional Office (Grant # 43279190).

Longitudinal Associations of Stroke With Cognitive Impairment Among Older Adults in the United States: A Population-Based Study

Objective: The aim of this study was to explore the longitudinal associations of stroke with cognitive impairment in older US adults.Method: The data used in this longitudinal analysis were extracted from the National Health and Aging Trends Study (NHATS) from 2011 to 2019. Univariate and multivariable Cox proportional hazards regression models were used to estimate the longitudinal association of stroke with cognitive impairment. The multivariable model was adjusted by demographic, physical, and mental characteristics, and the complex survey design of NHATS was taken into consideration.Results: A total of 7,052 participants with complete data were included. At the baseline, the weighted proportion of cognitive impairment was 19.37% (95% CI, 17.92–20.81%), and the weighted proportion of the history of stroke was 9.81% (95% CI, 8.90–10.72%). In univariate analysis, baseline stroke history was significantly associated with cognitive impairment in the future (hazard ratio, 1.746; 95% CI, 1.461–2.088), and the baseline cognitive impairment was significantly associated with future report of stroke (hazard ratio, 1.436; 95% CI, 1.088–1.896). In multivariable model, stroke was also significantly associated with cognitive impairment (hazard ratio, 1.241; 95% CI, 1.011–1.522); however, the reverse association was not significant (hazard ratio, 1.068; 95% CI, 0.788–1.447). After the data from proxy respondents were excluded, in the sensitive analyses, the results remained unchanged.Conclusion: Older adults in the United States who suffered strokes are more likely to develop cognitive impairment as a result in the future than those who have not had strokes. However, the reverse association did not hold. Furthermore, the study suggests that it is necessary to screen and take early intervention for cognitive impairment in stroke survivors and prevent the incidence of stroke by modifying risk factors in the general population with rapidly growing older US adults.

Synthesising Residential Electricity Load Profiles at the City Level Using a Weighted Proportion (Wepro) Model

It is important to understand residential energy use as it is a large energy consumption sector and the potential for change is of great importance for global energy sustainability. A large energy-saving potential and emission reduction potential can be achieved, among others, by understanding energy consumption patterns in more detail. However, existing studies show that it requires many input parameters or disaggregated individual end-uses input data to generate the load profiles. Therefore, we have developed a simplified approach, called weighted proportion (Wepro) model, to synthesise the residential electricity load profile by proportionally matching the city’s main characteristics: Age group, labour force and gender structure with the representative households profiles provided in the load profile generator. The findings indicate that the synthetic load profiles can represent the local electricity consumption characteristics in the case city of Amsterdam based on time variation analyses. The approach is in particular advantageous to tackle the drawbacks of the existing studies and the standard load model used by the utilities. Furthermore, the model is found to be more efficient in the computational process of the residential sector’s load profiles, given the number of households in the city that is represented in the local profile.

Are Vapers More Susceptible to COVID-19 Infection?

BackgroundCOVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a global pandemic in March 2020. Electronic cigarette use (vaping) rapidly gained popularity in the US in recent years. Whether electronic cigarette users (vapers) are more susceptible to COVID-19 infection is unknown.MethodsUsing integrated data in each US state from the 2018 Behavioral Risk Factor Surveillance System (BRFSS), United States Census Bureau and the 1Point3Acres.com website, generalized estimating equation (GEE) models with negative binomial distribution assumption and log link functions were used to examine the association of weighted proportions of vapers with number of COVID-19 infections and deaths in the US.ResultsThe weighted proportion of vapers who used e-cigarettes every day or some days ranged from 2.86% to 6.42% for US states. Statistically significant associations were observed between the weighted proportion of vapers and number of COVID-19 infected cases as well as COVID-19 deaths in the US after adjusting for the weighted proportion of smokers and other significant covariates in the GEE models. With every one percent increase in weighted proportion of vapers in each state, the number of COVID-19 infected cases increase by 0.3139 (95% CI: 0.0554 –0.5723) and the number of COVID-19 deaths increase by 0.3705 (95% CI: 0.0623 – 0.6786) in log scale in each US state.ConclusionsThe positive associations between the proportion of vapers and the number of COVID-19 infected cases and deaths in each US state suggest an increased susceptibility of vapers to COVID-19 infections and deaths.

Research on Risk Avoidance and Coordination of Supply Chain Subject Based on Blockchain Technology

Based on the influence of block chain technology on information sharing among supply chain participants, mean-CVaR (conditional value at risk) is used to characterize retailers’ risk aversion behavior, while a Stackelberg game is taken to study the optimal decision-making of manufacturers and retailers during decentralized and centralized decision-making processes. Finally, the mean-CVaR-based revenue-sharing contract is used to coordinate the supply chain and profit distribution. The research shows that, under the condition of decentralized decision-making, when the retailer’s optimal order quantity is low, it is an increasing function of the weighted proportion and the risk aversion degree, while, when the retailer’s optimal order quantity is high, it is an increasing function of the weighted proportion, and has nothing to do with the risk aversion degree. The manufacturer’s blockchain technology application degree is a reduction function of the weighted proportion. When the retailer’s order quantity is low, the manufacturer’s blockchain technology application degree is a decreasing function of risk aversion, while, when the retailer’s order quantity is high, the manufacturer’s blockchain technology application is independent of risk aversion. The profit of the supply chain system under centralized decision-making is higher than that of decentralized decision-making. The revenue sharing contract can achieve the coordination of the supply chain to the level of centralized decision-making. Through blockchain technology, transaction costs among members of the supply chain can be reduced, information sharing can be realized, and the benefits of the supply chain can be improved. Finally, the specific numerical simulation is adopted to analyze the weighted proportion, risk aversion and the impact of blockchain technology on the supply chain, and verify the relevant conclusions.