Household Income Research Articles

Can AI-powered avatars replace human trainers? An empirical test of synthetic humanlike spokesperson applications

Purpose This study aims to investigate the effectiveness of widely adopted but under-studied synthetic humanlike spokespersons (SHS) compared to organic human spokespersons in workplace training videos. The primary aim is to evaluate whether employees will rate training videos more negatively when they perceive their trainer to be synthetic such as those videos made with the AI-powered tools Synthesia or HeyGen. Results suggest that while ratings are more negative when the viewer perceives syntheticness, the change is only mild across most measures deployed here. When measures were calculated by using actual modality and not perceived modality, no significant change in rating was found. This study deployed three measures: actual knowledge transfer, perceived effectiveness and brand impression. It is guided by a convergence of AI Literacy Theory, the Technology Acceptance Model and the Theory of Reasoned Action. Design/methodology/approach Over 250 professionals assessed the effectiveness of training videos in a 2 × 2 trial design. Participants were randomly assigned to view one of four training videos featuring either a synthetic or organic spokesperson for a fictional business. After watching the video, participants answered Likert-scale survey questions and multiple-choice quiz-style questions to provide comparative measurements of actual knowledge transfer effectiveness, perceived effectiveness, brand impression and the effectiveness of the synthetic deception. The study used both ANOVA and multiple regression analyses to control for potential confounding variables and ensure the robustness of the findings. Findings The results indicate no significant differences between SHS and organic human spokespersons in terms of actual effectiveness (quiz scores), perceived effectiveness or brand impression, based on actual modality comparisons. However, when respondents perceived syntheticness, the avatar triggered the negative uncanny valley phenomenon and slightly decreased overall scores in perceived effectiveness and brand impression. Notably, more than half of respondents did not detect that the SHS was synthetic. Demographic variables such as gender, age or household income had no significant impact on the results. Practical implications Organizations can justifiably consider incorporating SHS into their training programs, leveraging these synthetic agents to deliver cost-effective and scalable learning solutions. The findings suggest that SHS can be used effectively for goals such as actual knowledge transfer without compromising training quality, and that other perceptual goals may be within reach as well. This may offer a viable alternative to traditional, organic human spokespersons, opening up new opportunities for enhancing training efficiency and accessibility across various industries. Originality/value Synthetic avatars, as outlined here, are a demonstrably effective new option in the array of available learning technologies. They are being adopted en masse but without significant study of their effectiveness. This research provides foundational quantitative assessments designed to address that gap in the literature and practice. The data presented here is highly valuable for practitioners and scholars interested in cutting-edge learning tools. Given the rapid advancement of technology, this study provides an important benchmark for evaluating future improvements in these tools. Furthermore, it offers actionable recommendations for integrating AI-powered avatars into professional development, enhancing understanding of the roles advanced technologies play in educational and training programs.

Is poor self-rated health associated with higher caries experience in adults? The HUNT4 Oral Health Study

Introduction: The association between lower socioeconomic status and a higher risk of dental caries is well established, but the independent association between general health status and dental caries on a population level is less investigated. The aim of this study was to assess the association between self-rated general health and caries experience in an adult Norwegian population and to assess if the associations were modified by age and sex. Methods: Data was collected as part of the Trøndelag Health Study (HUNT4) conducted 2017-2019 and a randomly selected subsample (20%) were invited for the HUNT4 Oral Health Study. This cross-sectional study included 4,880 dentate participants aged 19-94 years (response rate 67%). Participants underwent clinical and radiographic oral examinations and caries experience was measured by numbers of decayed (DT), missing (MT), and filled teeth (FT), DMFT index. The DT component consisted of primary and secondary caries in dentine, cavitated root caries and remaining roots. Questionnaires were used to assess self-rated general health and socioeconomic position, denoted by education, household income and employment status. Associations between self-rated health and caries experience (DMFT) and components (DT, MT, and FT) were assessed using negative binomial regression models. Ratios of means (RMs) with 95% confidence intervals (CI) for the associations were estimated, adjusting for socioeconomic position. Results: Individuals with poor self-rated general health had a 29% higher mean number of MT (RM 1.29 (95%CI 1.13-1.46)), a 22% higher mean number of DT (RM 1.22 (95%CI 1.07-1.39)), and a 7% higher mean number of DMFT (RM 1.07 (95%CI 1.04-1.11)) than individuals reporting very good health. Age stratified analyses presented a more pronounced association between self-rated health and caries experience for individuals below the age of 55 years than for those 55 years or older. Similarly, the association was more evident for women, with significantly higher mean values for DMFT, MT and FT among women reporting poor health. Conclusions: The present study demonstrated an independent association between poor self-rated health and a higher burden of caries experience, adjusted for education, income and employment status. The association was stronger for women and individuals below the age of 55 years. These findings add new evidence in understanding caries inequalities through self-rated health.

Diastolic Dysfunction and the Risk of Stroke and Major Bleeding

BACKGROUND: Left ventricular diastolic dysfunction (DD) is associated with adverse cardiovascular outcomes including atrial fibrillation. Whether DD is independently associated with incident stroke and transient ischemic attack (TIA) and with bleeding events is not known. We performed this observational cohort analysis to examine the impact of DD on the risk of stroke/TIA and major bleeding. METHODS: Patients who underwent at least 1 cardiac echocardiogram and were followed for at least 3 months were included in this study. Patients with a prior history of stroke, TIA, or major bleeding, as determined by International Classifications of Diseases codes, were excluded. Smart key-phrase search was applied to echocardiographic reports to classify patients into 4 groups based on the most severe DD assessment. Patients in whom the presence of DD could not be determined were excluded. The final study cohort was followed to the end point of hospital admission for stroke/TIA and major bleeding, and independent predictors of these events were evaluated using the multivariable Cox proportional hazards method. RESULTS: The final study cohort (age, 56±18 years; 56% women) had 96 702 patients with no DD and 18 164, 5881, and 1340 patients with DD grades I, II, and III, respectively. Over a median follow-up of 3.4 years, 2938 (2.4%) patients were hospitalized for stroke/TIA and 5567 (4.6%) for major bleeding. After adjusting for age, the CHA 2 DS 2 -VASc score, chronic kidney disease, use of antiplatelet agents, use of anticoagulation agents, the year of echocardiographic testing, household income, and history of atrial fibrillation, DD remained a strong predictor of incident stroke/TIA (hazard ratio, 1.22 per grade increase in DD [95% CI, 1.16–1.29]; P <0.001) and major bleeding (hazard ratio, 1.20 per grade increase in DD [95% CI, 1.16–1.25]; P <0.001). CONCLUSIONS: DD is independently associated with a higher risk of cerebrovascular accidents and major bleeding. DD should be considered when counseling patients regarding their risk profile and management options.

Importance of Community Context in Understanding Substance Use Among Adolescents With Allegations of Maltreatment

This study examined the association between community disadvantage and substance use among adolescents referred to child protective services (CPS) and the interaction role of race/ethnicity in the association between community disadvantage and adolescent substance use. Findings revealed that higher county-level alcohol/drug mortality rates were associated with a higher risk of substance use across non-Hispanic Black, non-Hispanic white, and Hispanic adolescents. An interaction test showed that the association between county-level alcohol/drug mortality rates and risk of substance use was particularly stronger for non-Hispanic Black adolescents compared to non-Hispanic white adolescents. However, county-level vacant housing rates and low median household income did not show a significant association with adolescent substance use across all racial/ethnic groups. Results suggest that practitioners should screen for community-level substance risk levels to prevent substance use among historically marginalized racial-ethnic adolescents involved in CPS.

Forecasting Electric Vehicle Adoption in the USA Using Machine Learning Models

Electric vehicles (Electric Vehicles) are at the vanguard of the global dispensation to sustainable transportation, depicting a pivotal step toward diminishing greenhouse gas emissions and reliance on fossil fuels. Notwithstanding, the adoption of Electric Vehicles has been growing in the USA, but their future remains at a crossroads. The objective of the research is to design and execute machine learning models capable of providing accurate predictions of future trends in electric vehicle adoption in the USA. The dataset gathered for analyzing EV adoption in the USA comprises data across three primary categories: environmental data, economic indicators, and policy-related data. The economic indicators include household income, fuel prices, electricity rates, and lithium battery costs that affect EV purchasing power obtained from the U.S. Census Bureau and the U.S. Energy Information Administration (EIA). Environmental data include greenhouse gas emissions and air quality indices from the EPA, providing information on regional environmental conditions that might affect EV attractiveness. Other policy data included federal and state incentives such as tax credits, rebates, and EV infrastructure data, collected from the U.S. Led by the U.S. Department of Energy's Alternative Fuels Data Center and the Energy Laboratory, additional EV sales trends were pulled from databases of the automotive industry. In this research project, credible and proven machine learning models were employed, most notably, Linear Regression, Random Forest, and XG-Boost. The performance of the models was tested for EV adoption prediction by considering a few important metrics: Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R²). From the model performance metrics presented, the Gradient Boosting Regressor and Random Forest models performed far better by a big margin than Linear Regression. The prediction models, particularly, the Random Forest regressors and Gradient Boosting regressors demonstrated incredible forecasting of electric vehicle adoption. The model works excellently on the premise that historical data with relevant features can be utilized to gain some valuable insight into future trends. Policy-makers interested in stimulating the wider use of electric vehicles can ensure that targeted policies address both current barriers and future demands. Results of this analysis suggest incentives, such as tax credits, rebates, and subsidies, are some of the most common actions to reduce the upfront cost of an EV, a key circumventing factor in the choice that many consumers face.

Financial assets and mental health over time

Financial, material, and social assets are core drivers of access to salutary resources. However, there is a paucity of research about how non-income financial assets shape mental health. We explore the relation of financial assets with symptoms of depression and of anxiety using a nationally representative, longitudinal survey of U.S. adults fielded annually from 2020 to 2023 (n = 1,296 unique participants). We used multivariable logistic regression models to estimate the association of financial assets and financial stress separately and together with symptoms of depression (PHQ-9 > 9), anxiety (GAD-7 > 9), and their co-occurrence, controlling for demographic indicators and year fixed effects. We found, first, that adults with <$5,000 in accrued financial assets reported over two times the odds of positive screen for depression, anxiety, and co-occurring depression and anxiety, respectively, as adults with ≥$100,000 in financial assets. Second, when controlling for accrued financial assets, annual household income was not associated with symptoms of anxiety. Third, the gap in positive screen for depression between household financial assets groups stayed consistent and did not differ significantly over the study period. Annual income alone does not capture the influence of all financial assets on mental health.

Patients’ perspective and practices of heart failure recurrence prevention in Yancheng City

Effective self-management is essential for patients with heart failure, but many struggle with acquiring the necessary skills. Given the complexity of heart failure management and the importance of patient adherence to prescribed regimens, this study aims to investigate the knowledge, attitudes, and practices (KAP) concerning the prevention of heart failure recurrence among patients. A cross-sectional study was conducted at the Third People’s Hospital of Yancheng City from September 1, 2023, to December 31, 2023, employing a self-administered KAP questionnaire. The study included 421 heart failure patients, of whom 230 (54.6%) were male. Median scores for knowledge, attitudes, and practices were 12.00 [10.00, 13.00] (possible range: 1–18), 20.00 [19.00, 21.00] (possible range: 5–25), and 16.00 [15.00, 17.00] (possible range: 5–22), respectively. Pearson’s correlation analysis indicated a positive correlation between knowledge and attitude scores (r = 0.183, P < 0.001), as well as between knowledge and practice scores (r = 0.169, P < 0.001). A higher attitude score was significantly associated with a higher practice score (r = 0.245, P < 0.001), as supported by structural equation modelling. Multivariate logistic regression revealed that attitude score (OR = 1.238), suburban residence (OR = 2.524), monthly household income exceeding 5000 RMB (OR = 3.539), BMI less than 20 kg/m2 (OR = 2.155, P = 0.029), BMI between 20 and 24 kg/m2 (OR = 2.387), and BMI between 25 and 29 kg/m2 (OR = 4.063) were independently linked to proactive practices (all P < 0.05). Additionally, Structural Equation Modelling (SEM) elucidated the intricate relationship between sociodemographic factors and KAP dimensions. Despite positive attitudes and proactive prevention efforts, heart failure patients exhibit a knowledge gap. Tailored educational interventions by healthcare providers could effectively bridge this gap, leveraging patients’ positive attitudes and proactive behaviours to reinforce preventive measures.

Associations Between Sleep Health and Child Behavior at Age 6 Years in the INSIGHT Study

ABSTRACT Objective: Suboptimal sleep is associated with disruptive behaviors in childhood. We evaluate associations of mean and variability (SD) of sleep duration, quality, and timing with emotion regulation, impulsivity, and prosocial and antisocial behavior in children. Methods: Intervention Nurses Start Infants Growing on Healthy Trajectories, a randomized controlled trial designed for obesity prevention, compared a responsive parenting intervention delivered in the first 2.5 years after birth with a home safety control group. At age 6 years, children wore an actigraphy device for 7 days and participated in behavioral tasks evaluating behavioral control, emotion regulation, and prosocial and antisocial behaviors. Separate linear regression models examined associations between sleep and behavioral variables, adjusting for study group, child sex, and household income. Moderation analysis investigated whether the study group moderated relationships between sleep and positive age-appropriate behavior. Results: Children (N = 143, age 6.7 ± 0.3 years) were predominantly non-Hispanic White (95%). Mean actigraphic sleep duration, quality, and timing were not associated with behavioral variables. By contrast, greater variability in sleep onset timing was associated with greater impulsivity (B = 0.85, p = 0.004) and poorer emotion regulation (B = −0.65, p = 0.01). Greater variability in sleep midpoint timing was associated with greater impulsivity (B = 0.80, p = 0.03). The study group moderated the effect of sleep onset variability on behavior; only the home safety control group exhibited a significant negative relationship between variability in sleep onset timing and emotion regulation (B = −1.28, p = 0.0002). Conclusion: Findings support the importance of consistency in sleep timing and how this may play a greater role in children's behavioral and emotional outcomes than mean actigraphic sleep duration and quality.

Balancing the cart: Milk, plant‐based alternatives and nutrient availability in New Zealand households

AbstractMilk is a near‐universal source of essential nutrients and contributes significantly to global nutrient availability. Global demand for milk continues to rise, driven by population growth, rising household incomes and favourable consumption patterns. Plant‐based alternatives (PBAs) to milk seek to cater to the preferences of a share of consumers regarding sustainability, lifestyle or health‐related matters (e.g. allergies and lactose intolerance). Though popular, PBAs do not stand as suitable nutritional substitutes for milk. These considerations emphasise the complex relationships between nutritional content and consumer preferences. This paper estimates a demand system for milk and PBAs in the New Zealand (NZ) market. We explore patterns of complementarity or substitutability between standard milk, reduced‐fat milk and organic milk, and an aggregate group of PBAs. We use these results to calculate nutrient elasticities and assess changes in nutrient availability in response to prices and expenditure variations. We estimate a Quadratic Almost Ideal Demand System using purchase records for 2460 NZ households in 2021. We find that demand for standard milk does not show any substitutional relationship with PBAs. On the contrary, increases in the PBAs price lead households to switch towards standard milk, thereby increasing the availability of essential nutrients. That is, in the case of price increases, milk effectively offsets the reduction in essential nutrients as households switch away from PBAs, but PBAs cannot offset any reduction in essential nutrients as households do not find them to be adequate substitutes for milk.

Move out of the land: certification and migration in China

Abstract Motivated by the emphasis on securing property rights as an important tool for the efficient allocation of resources, including land and labour, we use three rounds of China Rural Household Panel Survey data to assess the impact of a land certification programme (LCP) on the labour and land allocation in rural China. We find that the LCP results in increased rural–urban migration, more active land rental markets, as well as higher household income and consumption in rural China. These effects vary with age and are larger for younger individuals and households with heads aged 50 years or younger. Improving property rights could be a central task for the Chinese government to tackle issues related to labour and land misallocation.

Digital divide and digital engagement in small business owners: an examination of survey data

ABSTRACT This paper examines the digital divide among Small Business Owners (SBO). Most of the existing literature has focused on the digital divide among individuals and communities with little attention given to SBOs. This paper uses the Resources and Appropriation (RA) theory to explore the digital divide in SBOs. Data is analyzed from a survey of residents in the seventh-largest city in the US. The analysis indicates that many characteristics of the digital divide persist when comparing SBOs. However, when controlling for factors such as digital engagement, business characteristics, and expected revenue, demographic variables like race, ethnicity, education, gender, age, and household income did not significantly affect the level of digital engagement or expected revenue of SBOs. The findings support RA theory by demonstrating that access and the reasons for using the Internet play a crucial role among SBOs. The results emphasize the need to create opportunities for minority-owned small businesses to thrive in the digital age.

Contribution of wildlife tourism in improving local communities’ livelihood in Burunge Wildlife Management Area in Tarangire Manyara Ecosystem, Tanzania

The overall objective of this study was to assess the role of wildlife tourism in improving the livelihood of communities in Burunge Wildlife Management Area (BWMA) by focusing on the economic and the socio-cultural roles. Data were obtained through household questionnaire, focus group discussions, and key informant interviews in three study villages. The data were analyzed using the Statistical Package for Social Science (SPSS) version 26 and Microsoft Excel. The findings revealed that wildlife tourism operations in the three villages associated with BWMA have generated significant benefits. Several economic and socio-cultural livelihood indicators in the study villages were significantly impacted by wildlife tourism activities. Wildlife tourism appears to have a considerable impact on increasing household incomes, but a relatively lesser impact on reducing agricultural production, which is the economic mainstay for many households in the Babati district. In terms of socio-cultural livelihood indicator, wildlife tourism operation seem to have a significant (x2 = 191.613, df = 8, N = 117 and p < 0.0001) impact in raising the profile and fame of the villages, while having a lesser impact on the erosion of local customs and culture, as most of the villagers continue to uphold their cultural practices. These findings suggest that wildlife tourism in the WMAs can improve people's standard of living and strengthen cultural values. The study recommends full consideration of socio-economic and cultural values of the communities at individual level by the potential stakeholders including policy makers. This will enhance the achievement of sustainable conservation in WMAs and community development through wildlife tourism activities.

Association of neighborhood-level disadvantage beyond individual sociodemographic factors in patients with or at risk of knee osteoarthritis

ObjectiveLower socioeconomic status (SES) is a risk factor for poorer pain-related outcomes. Further, the neighborhood environments of disadvantaged communities can create a milieu of increased stress and deprivation that adversely affects pain-related and other health outcomes. Socioenvironmental variables such as the Area Deprivation Index, which ranks neighborhoods based on socioeconomic factors could be used to capture environmental aspects associated with poor pain outcomes. However, it is unclear whether the ADI could be used as a risk assessment tool in addition to individual-level SES.MethodsThe current study investigated whether neighborhood-level disadvantage impacts knee pain-related outcomes above sociodemographic measures. Participants were 188 community-dwelling adults who self-identified as non-Hispanic Black or non-Hispanic White and reported knee pain. Area Deprivation Index (ADI; measure of neighborhood-level disadvantage) state deciles were derived for each participant. Participants reported educational attainment and annual household income as measures of SES, and completed several measures of pain and function: Short-form McGill Pain Questionnaire, Western Ontario and McMaster Universities Osteoarthritis Index, and Graded Chronic Pain Scale were completed, and movement-evoked pain was assessed following the Short Physical Performance Battery. Hierarchical linear regression analyses were used to assess whether environmental and sociodemographic measures (i.e., ADI 80/20 [80% least disadvantaged and 20% most disadvantaged]; education/income, race) were associated with pain-related clinical outcomes.ResultsLiving in the most deprived neighborhood was associated with poorer clinical knee pain-related outcomes compared to living in less deprived neighborhoods (ps < 0.05). Study site, age, BMI, education, and income explained 11.3–28.5% of the variance across all of the individual pain-related outcomes. However, the ADI accounted for 2.5–4.2% additional variance across multiple pain-related outcomes.ConclusionThe ADI accounted for a significant amount of variance in pain-related outcomes beyond the control variables including education and income. Further, the effect of ADI was similar to or higher than the effect of age and BMI. While the effect of neighborhood environment was modest, a neighborhood-level socioenvironmental variable like ADI might be used by clinicians and researchers to improve the characterization of patients’ risk profile for chronic pain outcomes.

Assessing the Effectiveness of Climate-Smart Irrigation Practices in Improving Household Income Among Smallholder Maize Farmers in Botswana

Assessing the Effectiveness of Climate-Smart Irrigation Practices in Improving Household Income Among Smallholder Maize Farmers in Botswana

Analisis Tingkat Kesejahteraan Rumah Tangga Petani Padi di Desa Cadaskertajaya Kecamatan Telagasari Kabupaten Karawang

Agricultural development in rural areas not only increases production, but also increases people's income, opens up more job opportunities, and improves welfare. This research aims to analyze farmer household income, farmer household expenditure, and the level of welfare of rice farmer households in Cadaskertajaya Village, Telagasari District, Karawang Regency. The research method used is Mix Method, with primary and secondary data types. Primary data was collected through interviews using questionnaires from 47 rice farmers. Secondary data was obtained from the Central Statistics Agency, Karawang Regency Agricultural Service, Cadaskertajaya Village, and other institutions. Samples were taken using the proportional random sampling method, with the criteria being farmer owners and farm workers. Data analysis uses the Directorate of Land Use's criteria poverty line for household income, the Sayogyo criteria poverty line for household expenditure, and welfare indicators from BPS. The research results show that the average household income of rice farmers in Cadaskertajaya Village is IDR 34,582,351.69 per year and IDR 8,124,446.81 per capita per year. The household expenditure of rice farmers is IDR 25,380,255.32 per year and IDR 8,413,937.59 per capita per year. Based on the poverty line criteria of the Directorate of Land Use, 53.19% of farmers are not poor, and according to the Sayogyo criteria, 82.61% are not poor. The welfare level is calculated using 11 indicators from BPS, with the highest score being 33 and the lowest score being 27, which is still included in the high welfare category.

A cross-sectional study of the impact of stigma on quality of life in hemiplegic stroke patients following suicide attempts in nursing homes

To analyze the factors affecting stigma and quality of life in hemiplegic stroke patients following suicide attempts in nursing homes and to provide a theoretical basis for developing interventions in clinical care. General demographic information, the Stigma Scale for Chronic Illness (SSCI), and the Quality of Life Scale (SF-36) were used to investigate 259 patients with hemiplegia after stroke following nursing home suicide from January to April 2024. Univariate statistical analyses were performed to assess the impact of potential determinants on quality of life. Multiple regression models and stratified analyses with smoothed curve fitting were used for further evaluation. Multiple regression modeling showed that the factors influencing the quality of life in hemiplegic stroke patients following suicide attempts in nursing homes were stigma, Age, marital status, education, type of occupation, monthly household income, and duration of illness. The level of quality of life before unadjusted variables was strongly associated with high school and college education (β = 11.9, 95% CI: 8.2–15.6; P < 0.001), (β = 13.1, 95% CI: 9.2 -16.9; P < 0.001). After adjusting for confounders such as marital status (Married, Unmarried), Age (< 30, 30–40, 40–50, > 50) (β = 8.1, 95% CI: 4 .6–11.6; P < 0.0001). (β = 9.5, 95% CI: 6.0–13.1;P < 0.0001), the results were not significantly different. Curve fitting revealed threshold nonlinear associations between intrinsic and extrinsic stigma and quality of life, with quality of life decreasing as stigma increased. Conclusion Stigma is negatively correlated with the level of quality of life in hemiplegic stroke patients following suicide attempts in nursing homes. Different demographic profiles moderated patients’ quality of life levels, and effective psychological intervention strategies should be used to improve patients’ quality of life.

Economic reforms and consumption trends: A deep dive into Saudi Arabia’s economic evolution

This study examines the aggregate consumption function of Saudi Arabia from 2000 to 2022, focusing on identifying key determinants of household consumption and evaluating the impacts of disposable income, household wealth, government expenditure, interest rates, and oil revenues. the research uses advanced econometric methods, including the autoregressive distributed lag (ARDL) model and Johansen cointegration test, to analyze the relationships among these variables. the findings reveal that disposable income, household wealth, and government expenditure significantly and positively influence consumption, whereas interest rates show a negative correlation. oil revenues also play a critical role, reflecting the country’s economic reliance on oil. the study highlights the necessity for economic diversification to reduce the impact of oil price volatility on household income and consumption stability. The results offer crucial insights for policymakers, emphasizing the need for strategies that enhance household income and wealth, maintain robust public sector spending, and effectively manage interest rates. these findings also support the importance of consistent and predictable income sources for sustaining consumption. additionally, this study suggests directions for future research, including developing sophisticated forecasting models to predict consumption trends and exploring other influencing factors such as demographic shifts and technological progress.

Horizontal inequity in the use of mental healthcare in Australia.

For people experiencing mental health problems, timely access to high-quality healthcare is imperative for improving outcomes. However, limited availability of services, high out-of-pocket costs, insufficient health literacy and stigmatizing attitudes may mean people do not receive the necessary treatment. We analyze Australian longitudinal data to document the extent and predictors of horizontal inequity in mental healthcare use among people with a newly developed mild or moderate mental disorder. Importantly, we compare people with similar health, residing in the same area, thus controlling for differences in healthcare needs and availability of services. Results suggest that mental healthcare use is not significantly associated with household income or financial hardship. In contrast, we find significant inequities by educational attainment, with university graduates around 50% more likely to receive mental healthcare than high-school dropouts. These findings are robust across subsamples and alternative modeling approaches, including panel data models with individual fixed-effects. Additional explorations of the education gradient suggest a potential pathway through mental health-specific knowledge and attitudes.

Effects of Sustainable Agricultural Practices on Income and Environmental Sustainability of Small Farm Households in Rural Pakistan

Effects of Sustainable Agricultural Practices on Income and Environmental Sustainability of Small Farm Households in Rural Pakistan

Prenatal iodine intake and infant temperament in a multiethnic US cohort.

Maternal iodine plays a central role in fetal neurodevelopment. It is recommended that pregnant women consume sufficient levels of iodine to accommodate increased need for mother and fetus. We examined associations among prenatal dietary and supplemental iodine intake and infant temperament. The PRogramming of Intergenerational Stress Mechanisms (PRISM) study is an ongoing longitudinal pregnancy cohort. Data from 2011 to 2020 were used for this study. Women completed the Block98 FFQ ascertaining prenatal dietary and supplemental iodine intake and the Infant Behavior Questionnaire-Revised at infant age 6 months to ascertain infant temperament (Surgency/Extraversion, Negative Affectivity and Orienting/Regulation). USA. Mother-child dyads (n 892). Women were primarily Black/Hispanic Black (44 %) and non-Black Hispanic (35 %) with 46 % reporting household income < $25 000/year. Nearly half had an estimated average requirement (EAR) < 160 µg/d (49 % based on dietary intake; 43 % based on diet and supplements). Girls born to women with an EAR ≥ 160 µg/d compared to girls born to women below this level had higher unadjusted extraversion scores for dietary plus supplemental intake (β = 0·23 (0·13, 0·33)); decreased to β = 0·05 (-0·08, 0·19) after adjusting for covariates. Boys born to women with an EAR ≥ 160 µg/d (based on diet and supplements) as compared to boys born to women below this level had statistically non-significant higher unadjusted negative affective score (β = 0·06 (-0·08, 0·20)) that became significantly lower upon covariate adjustment (β = -1·66 (-1·97, -1·35)). A significant proportion of these women reported suboptimal prenatal iodine intake. Suboptimal prenatal iodine intake may have implications for child neurodevelopment evident as early as infancy.