Multivariate Logit Model Research Articles

Features of extreme pollution and its influencing factors: evidence from China.

Extreme pollution has become a significant environmental problem in China in recent years, which is hazardous to human health and daily life. Noticing the importance of investigating the causes of extreme pollution, this paper classifies cities across China into eight categories (four groups plus two scenarios) based on the generalized extreme value (GEV) distribution using hourly station-level concentration data, and a series of multi-choice models are employed to assess the probabilities that cities fall into different categories. Various factors such as precursor pollutants and socio-economic factors are considered after controlling for meteorological conditions in each model. It turns out that concentration, concentration, and population density are the top three factors contributing most to the log ratios. Moreover, in both left- and right-skewed cases, the influence of a one-unit increase of concentration on the relative probability of cities falling into different groups shows an increasing trend, while those of concentration show a decreasing trend. At the same time, the higher the extreme pollution level, the bigger the effect of and concentrations on the probability of cities falling into normalized scenarios. The multivariate logit model is used for prediction and policy simulations. In summary, by analyzing the influences of various factors and the heterogeneity of their influence patterns, this paper provides valuable insights in formulating effective emission reduction policies.

Association between weight-adjusted waist index and bone mineral density in adolescents

The negative effects of obesity and excess body fat on bone mineral density (BMD) have been widely reported. As opposed to waist circumference (WC) or body mass index (BMI), weight-adjusted waist index (WWI) is a superior method for assessing obesity. WWI also indicates centripetal obesity independently of the weight of the individual. An investigation of WWI and adolescents’ BMD was conducted in this study. The National Health and Nutrition Examination Survey (NHANES) 2011–2018 provided the data for this cross-sectional investigation. In this study, weighted multivariate logit models were employed to assess the correlation between teenage BMD and WWI. Additionally, we conducted interaction tests and subgroup analysis. Through multivariate linear regression, we discovered that WWI was negatively linked with lumbar, trunk, and total BMD but not pelvis BMD in this study, which included 6828 subjects. We found that each unit increase in WWI resulted in a lumbar BMD decline of 0.04 g/cm2 (95%CI −0.04, −0.04), a trunk BMD decrease of 0.03 g/cm2 (95%CI −0.03, −0.02), and a total BMD decrease of 0.02 g/cm2 (95%CI −0.02, −0.02). In conclusion, in US teenagers, there were negative connections discovered between WWI and lumbar, trunk, and total BMD, but not pelvis BMD.

Material, Psychological, and Behavioral Financial Hardship Among Lesbian, Gay, and Bisexual Cancer Survivors in the United States.

Driven by anti-LGBTQ+ stigma, emerging literature suggests that lesbian, gay, and bisexual (LGB) cancer survivors experience financial hardship (FH) more frequently than heterosexual survivors. However, few studies have used nationally representative samples to estimate this inequity. National Health Interview Survey data from 2019 to 2022 were pooled and weighted. Outcomes included material, psychological, and behavioral FH. The behavioral domain was further broken down into subdomains including medical care, prescription medications, and mental health care. Multivariable logit models controlling for a variety of factors were used to generate LGB and heterosexual predicted probabilities and differential effects for each FH outcome. Stratified estimates were generated by sex and age groups. A total of N = 374 LGB and N = 12,757 heterosexual cancer survivors were included in this analysis. In adjusted analyses, LGB cancer survivors had significantly higher material (19%, 95% CI, 15 to 24 v 12%, 95% CI, 11 to 13; P = .004), psychological (44%, 95% CI, 38 to 51 v 37%, 95% CI, 36 to 38; P = .035), and behavioral (23%, 95% CI, 18 to 28 v 13%, 95% CI, 13 to 14; P < .0001) FH than heterosexual survivors. LGB cancer survivors also had higher medical behavioral (11%, 95% CI, 7 to 15 v 7%, 95% CI, 6 to 7; P = .030), prescription medication behavioral (14%, 95% CI, 10 to 19 v 10%, 95% CI, 9 to 10; P = .032), and mental health behavioral (9%, 95% CI, 6 to 13 v 3%, 95% CI, 3 to 4; P < .0001) FH than heterosexual survivors. Stratified estimates revealed young LGB cancer survivors had the highest probability of each outcome (material: 31%, 95% CI, 23 to 40; psychological: 58%, 95% CI, 50 to 66; behavioral: 45%, 95% CI, 36 to 53). In this nationally representative analysis, LGB cancer survivors experience substantial inequities in all FH outcomes. It is crucial that future FH interventional work should prioritize populations at the highest risk of FH, such as LGB cancer survivors.

Analyzing market basket data through sparse multivariate logit models

AbstractUsing multivariate logit models, we analyze purchases of product categories made by individual households. We introduce a sparse multivariate logit model that considers only a subset of all two-way interactions. A combined forward and backward selection procedure based on a cross-validated performance measure excludes about 74 % of the possible two-way interactions. We also specify random coefficient versions of both the non-sparse and the sparse model. The fact that the random coefficient models lead to better values of the Bayesian information criterion demonstrates the importance of latent heterogeneity. The random coefficients sparse model attains the best statistical performance if we consider model complexity and offers a better interpretability. We investigate the cross-purchase effects of household segments derived from this random coefficient model. As additional interpretation aid we cluster categories and category pairs by integer programming. We demonstrate what the best performing sparse model implies for cross-selling by product recommendations and store layout. The sparse model leads to managerial implications with respect to the effects of advertising in local newspapers and flyers that are as a rule close to those implied by its non-sparse counterpart.

Malnutrition in Argentine preschoolers: 2005-2019

In low- and middle-income countries, studies on children's health focus primarily on their nutritional status, especially the presence of malnutrition. Child malnutrition is a major public health problem in Argentina. The objective of this research is to study the determinants and evolution of young children’s nutritional status in Argentina at the national level, and at different socioeconomic levels, between 2005 and 2019. We use data from the 2004-05 and 2018-19 National Survey of Nutrition and Health (ENNyS1 and ENNyS2). We use multivariate logit models, including household risk factors for childhood malnutrition, to estimate the likelihood of the occurrence of stunting and overweight in Argentinian children aged 24 to 60 months. Our results show that the prevalence of overweight among preschoolers has increased significantly between 2005 and 2019, from just below 10%, still a medium prevalence level, to more than 13%, a high prevalence level. The prevalence of overweight increased between 2005 and 2019 at all socioeconomic levels. The prevalence of stunting has not significantly changed in almost 14 years, remaining at around 7%, a low level. Except for the Cuyo region, which is close to the intermediate level, stunting prevalence in all regions remains between 5 and 8%. Understanding the determinants and evolution of young children’s nutritional status is key to implementing policies aimed at improving childhood nutrition.

Population under Stress: The Coping Mechanisms of Lebanese Adults in Times of Intermingling Crises and Their Relationship with Stress.

The Lebanese population has faced numerous stressors due to multiple crises in the past four years. This study aims to measure the perceived stress of the Lebanese population, identify the coping mechanisms being used, and determine whether they are associated with their stress levels. A cross-sectional study of 205 individuals randomly selected from Beirut was conducted. Frequency distribution, descriptive analysis, and multivariable cumulative logit models were used to determine the associations between coping mechanisms and perceived stress. Our results indicated that 95.4% of our population had moderate to high perceived stress levels. Problem-focused coping was the most adopted mechanism and was associated with a statistically significant lower stress level, whereas avoidant coping was associated with a statistically significant higher stress level. Our study can pave the way for raising awareness on the importance of managing stress with adaptive coping mechanisms.

Abstract TMP96: Clear Thrombectomy Score: An Index to Estimate Probability of Good Functional Outcome Following Endovascular Treatment in the Late Window for Anterior Circulation Occlusion

Background: Endovascular thrombectomy (EVT) has established efficacy across a wide range of patient age, radiological findings, and clinical features. However, EVT may be less effective in extreme scenarios (e.g., large established infarction in later treatment windows), where there are currently limited data. Methods: A heterogeneous, multinational observational cohort (CLEAR registry) of consecutive adult patients ≥18 years old who underwent EVT for acute occlusion (2014-2022) of the internal carotid or proximal middle cerebral (M1 or M2) arteries was queried (n=64 sites). A high-fidelity model for predicting good functional outcome at 90 days (return to pre-stroke modified Rankin Scale [mRS] or mRS 0-2 after EVT) was developed using a binary, multivariable logit model with adaptive double lasso adjustment, which was validated using 5-fold cross validation and 1000 bootstrap sampling for confidence intervals. Results: At the time of the analysis, we evaluated 2953 patients from the registry treated with EVT, of which 1855 (63%) had complete covariate data for inclusion. The median National Institutes of Health Stroke Scale (NIHSS) score was 15 (IQR 9-20), with 14.0% having a pre-stroke mRS &gt;2, 8.3% having a NIHSS &lt;6, and 17.8% having an Alberta Stroke Program Early Computed Tomography Scale (ASPECTS) score ≤6. A good functional outcome occurred in 813 (43.8%) patients. Independent predictors of the primary outcome, with points allocated toward the final score, included younger age, higher ASPECTS, lower NIHSS, and time from last known well to arterial puncture. The areas under the curve for derivation and validation cohorts were 0.72 (95% CI 0.70-0.75) and 0.74 (95% CI 0.71-0.80), respectively. Discussion: The CLEAR thrombectomy score provides a simple, validated means of predicting good functional outcome following late-window, anterior circulation thrombectomy using routinely acquired clinical and imaging data. External validation is warranted.

A study of automobile market structure prediction based on multivariate logit model with embedded Newton's method

In order to deeply understand the factors that consumers focus on when choosing models with different technological routes, and to predict the structure of the future automobile market accordingly, a multivariate logit model incorporating Newton's method of optimization is used, which is able to accurately measure the weights of the various factors that influence the process of choosing models by consumers, in order to reflect the degree of heterogeneity of consumers' preferences for these factors, and to predict the future market share of the different technological routes on the basis of this model. Based on this, it predicts the share of different technological routes in the future market. The results of this study show that when choosing a vehicle of different technological routes, convenience of replenishment is the most important factor, with a preference weight of 0.39. In contrast, the imitation coefficient has the lowest preference weight of 0.11, which suggests that consumers are more likely to take into account their personal experience rather than the choices made by others in their vehicle purchasing decisions. In addition, in the prediction of future technological routes in the automobile market, it is also found that by 2025, consumers' tendency to choose new energy vehicles will be more than 50%, and by 2030, the proportion will be more than 70%. Meanwhile, the market share of sales of traditional fuel vehicles is expected to fall to 17% by 2035.

Endogeneity of marketing variables in multicategory choice models

A regressor is endogenous if it is correlated with the unobserved residual of a model. Ignoring endogeneity may lead to biased coefficients. We deal with the omitted variable bias that arises if firms set marketing variables considering factors (demand shocks) that researchers do not observe. Whereas publications on sales response or brand choice models frequently take the potential endogeneity of marketing variables into account, multicategory choice models provide a different picture. To consider endogeneity in multicategory choice models, we follow a two-step Gaussian copula approach. The first step corresponds to an individual-level random coefficient version of the multivariate logit model. We analyze yearly shopping data for one specific grocery store, referring to 29 product categories. If the assumption of a Gaussian correlation structure is met, the copula approach indicates the endogeneity of a category-specific marketing variable in about 31% of the categories. The majority of marketing variables rated as endogenous are positively correlated with the omitted variable, implying that ignoring endogeneity leads to an overestimation of the coefficients of the respective marketing variable. Finally, we investigate whether taking endogeneity into account by the copula approach leads to different managerial implications. In this regard, we demonstrate that for our data ignoring endogeneity often suggests a level of marketing activity that is too high.

Millers on Hazard Analysis Critical Control Point (HACCP) for Aflatoxin Control in Maize; A Case in Kiambu County, Kenya.

Food safety management implementation is vital in food industries. Hazard Analysis Critical Control Points (HACCP) implementation in maize millers help in identifying aflatoxin hazards, prevent, reduce or eliminate them. Knowledge, attitude and practices (KAP) towards HACCP on aflatoxin determine the safety of the end product from its contamination. The main objective was to determine KAP on HACCP in Kiambu county maize millers in aflatoxin control. Clustering and systematic sampling methods were used to sample the 30 maize millers. 150 questionnaire respondents were selected randomly from the milling sub-sections. Multivariate probit model and multinomial logit model were used as the analytical framework for evaluating KAP. 60% of the respondents were male, 34% had completed university and 80% of the respondents from management section had completed university while dispatch section respondents had the lowest education level. HACCP average knowledge was 57.5%, 74.43% being highest from management section. HACCP attitude mean score was 3.326, management section showing more positivity with a mean of 3.633. Sufficient training and recruitment of food safety related experts across all sub- section would improve KAP towards aflatoxin reduction to the maize flour.

The impact of employment loss on mentally unhealthy days among LGBTQ+ cancer survivors during the COVID-19 pandemic: Findings from the OUT National Survey.

Lesbian, Gay, Bisexual, Transgender, Queer, and all other sexual and gender minority (LGBTQ+) populations made up 7.1% of the US population in 2021. LGBTQ+ cancer survivors face a variety of economic and mental health disparities; however, the determinants of poor mental health among LGBTQ+ cancer survivors are understudied. This analysis utilized the OUT National Survey which consists of N=2233 LGBTQ+ cancer survivors (complete cases). Multivariable negative binomial and logit regression models were used to generate predicted values, predicted probabilities, and average marginal effects (AME) to assess the association between COVID-19 related employment loss and mentally unhealthy days (MUDs) and frequent mental distress among LGBTQ+ cancer survivors. Predicted values and marginal effects were generated with interaction terms (demographics interacted with employment loss) to explore the heterogeneity of the effect of employment loss among LGBTQ+ sub-populations. In bivariate analyses employment loss was associated with a higher number of MUDs (10.3, SD=9.9 vs. 8.4, SD=9.6; p-value<0.001) and frequent mental distress (34% vs. 26%; p-value=0.001). AME from a multivariable negative binomial model revealed that employment loss was associated with 1.42 more MUDs (95%CI: 0.33-2.86). Demographic factors such as some sexual orientations, cis-female and non-binary gender, younger age, and a current cancer diagnosis were also associated with significant expected increases in the number of MUDs. Whenassessing the heterogeneity of the effect of employment loss some sub-populations experienced changes in the number of MUDs that pushed them overthe threshold of frequent mental distress while others did not. Furthermore, identifying with multiple sexual orientations (AME: 0.19, 95%CI: 0.11-0.27), cis-female and non-binary genders (AME: 0.07, 95%CI: 0.2-0.12; AME:0.18, 95%CI: 0.07-0.28), American Indian and Alaska Native race (AME: 0.17, 95%CI: 0.03-0.31), and a current cancer diagnosis (AME: 0.14, 95%CI: 0.09-0.19) were associated with an increase in the probability of experiencing frequent mental distress. COVID-19 related employment loss negatively impacted the mental health of LGBTQ+ cancer survivors. LGBTQ+ specific supportive services as well as equity-based employment and income interventions are needed.

Comparison of primary payer in cancer registry and discharge data.

To determine agreement between variables capturing the primary payer at cancer diagnosis across the Pennsylvania Cancer Registry (PCR) and statewide facility discharge records (Pennsylvania Health Care Cost Containment Council [PHC4]) for adults younger than 65 years, and to specifically examine factors associated with misclassification of Medicaid status in the registry given the role of managed care. Cross-sectional analysis of the primary cancer cases among adults aged 21 to 64 years in the PCR from 2010 to 2016 linked to the PHC4 facility visit records. We assessed agreement of payer at diagnosis (Medicare, Medicaid, private, other, uninsured, unknown) across data sources, including positive predictive value (PPV) and sensitivity, using the PHC4 records as the gold standard. The probability of misclassifying Medicaid in registry was estimated using multivariate logit models. Agreement of payers was high for private insurance (PPV, 89.7%; sensitivity, 83.6%), but there was misclassification and/or underreporting of Medicaid in the registry (PPV, 80%; sensitivity, 58%). Among cases with "other" and "unknown" insurance, 73.8% and 62.1%, respectively, had private insurance according to the PHC4 records. Medicaid managed care was associated with a statistically significant increase of 12.6 percentage points (95% CI, 9.4-15.8) in the probability of misclassifying Medicaid enrollment as private insurance in the registry. Findings suggest caution in conducting and interpreting research using insurance variables in cancer registries.

Factors Associated with Maternal Healthcare Utilization Before and After Delivery Among Migrant Pregnant Women in China: An Observational Study.

Effective healthcare utilization throughout pregnancy is essential in protecting mother and child health, but the maternal healthcare utilization and its associated factors among migrant women are still underexplored. The data came from the 2018 China Migrants Dynamic Survey. Our analysis included 6337 pregnant migrant women. Prenatal healthcare utilization comprises receiving at least 5 antenatal care (ANC) times and establishing the maternal health record within the first 12 weeks of pregnancy. Postnatal healthcare utilization refers to whether an individual received a postpartum visit and a physical health examination within 28 days and 42 days following delivery. A multivariate binary logit model was employed to investigate the factors related to maternal healthcare utilization. 67.15% of the 6337 participants establishedhealth records within the first 12 weeks of pregnancy, and 88.35% receivedat least five ANC visits. 76.88% and 84.20% of migrant pregnant women received a postpartum visit and a health examination respectively. Age was positively correlated with receiving at least five ANC visits (OR:1.245, 95% CI: 1.038-1.493), a postpartum visit within 28 days (OR: 1.272, 95% CI: 1.107-1.460) and a physical examination within 42 days after delivery (OR=1.174, 95% CI: 1.002-1.376). Education, household income, health insurance and maternal health education were positively associated with prenatal and postnatal healthcare utilization (P<0.05). Number of Children negatively correlated with ANC times (OR: 0.742, 95% CI: 0.613-0.898) and receiving health examination after delivery (OR: 0.720, 95% CI: 0.610-0.849). There is still potential for improvement in the maternal healthcare utilization, particularly in postnatal healthcare. Strengthening the follow-up, focusing on those who are younger, have lower socioeconomic status, and are members of ethnic minorities, and continuing to strengthen maternal health education for them can promote the maternal healthcare utilization before and after delivery.

Determinants of the European Sovereign Debt Crisis: Application of Logit, Panel Markov Regime Switching Model and Self Organizing Maps.

The study aims to empirically identify the determinants of the debt crisis that occurred within the framework of 15 core EU member countries (EU-15). Contrary to previous empirical studies that tend to use event-based crisis indicators, our study develops a continuous fiscal stress index to identify the debt crises in the EU-15 and employs three different estimation techniques, namely self-organizing map, multivariate logit and panel Markov regime switching models. Our estimation results show first that the study correctly identifies the time and the length of the debt crisis in each EU-15-member country. Empirical results then indicate, via three different models, that the debt crisis in the EU-15 is the consequence of deterioration of both financial and macroeconomic variables such as nonperforming loans over total loans, GDP growth, unemployment rates, primary balance over GDP, and cyclically adjusted balance over GDP. Furthermore, variables measuring governance quality, such as voice and accountability, regulatory quality, and government effectiveness, also play a significant role in the emergence and the duration of the debt crisis in the EU-15.

Financial hardship differences by LGBTQ+ status among assigned female at birth adolescent and young adult cancer survivors: a mixed methods analysis.

Adolescent and young adult (AYA) cancer survivors are at an elevated risk of financial hardship. However, financial hardship among LGBTQ+ AYAs has not been widely explored. Thus, we used qualitative and quantitative survey data from the Horizon Study cohort to assess financial hardship of AYAs by LGBTQ+ status. Multivariable logit models, predicted probabilities, average marginal effects or differences in predicted probabilities (AME) and 95% confidence intervals (CI) were used to assess the association of LGBTQ+ status and two components of financial hardship: material and psychological. Qualitative content analysis of an open-ended survey question about financial sacrifices was used to describe the third component of financial hardship, behavioral. Among 1,635 participants, 4.3% self-identified as LGBTQ+. Multivariable logit models controlling for demographic factors revealed that LGBTQ+ AYAs had an 18-percentage point higher probability of experiencing material financial hardship (95%CI 6-30%) and a 14-percentage point higher probability of experiencing psychological financial hardship (95%CI 2-26%) than non-LGBTQ+ AYAs. Controlling for economic factors attenuated the association of LGBTQ+ status with psychological financial hardship (AME = 11%; 95%CI -1-23%), while the material financial hardship association remained statistically significant (AME = 14%; 95%CI 3-25%). In the qualitative analysis, LGBTQ+ AYAs frequently reported educational changes and costs (e.g., quitting school), unpaid bills and debt (e.g., medical debt, taking on credit card debt), as well as changes in housing and poor housing conditions (e.g., moving into less expensive house). LGBTQ + targeted and tailored interventions are needed to move toward equity for LGBTQ+ AYAs-an overlooked minority population.

Improving provider and client communication around family planning in Togo: Results from a cross-sectional survey.

Previous research has shown that clients are better able to achieve their reproductive intentions when family planning (FP) services meet their needs and they have satisfying client provider interactions. There are several areas of quality provider-client communication, including providers taking a complete reproductive history of their clients to best gauge their needs, communication around alternative FP methods and side effects captured in the method information index, and communication around sexually transmitted infections and HIV risk as it relates to FP choices. This study examines data from a clinic-based intervention in Togo that focuses on strengthening health provider counseling related to FP, including improving in these three areas of provider-client communication. A clustered sampling approach was used to select 650 FP clients from 23 intervention facilities and 235 clients from 17 control facilities in the Lomé and Kara districts of Togo. The FP clients' interactions with providers were observed and clients exit interviews were conducted in December 2021. For each communication area measured through client interviews and observations, principal components analysis and Cronbach's alpha scores were used to ensure that the individual components could be indexed. Outcomes variables based on an index of sub-questions were then created for those who had fulfilled each of the components within an index. Multivariate multilevel mixed-effects logit models accounted for clients nested within facilities and included independent variables capturing client demographic and facility variables. Multivariate results show that all three outcome variables representing the three provider-client communication areas were statistically significantly better for FP clients in intervention clinics versus control clinics (p<0.05). The results speak to the emphasis that the Togo Ministry of Health has placed on building the provider capacity to provide quality counseling and administration of FP methods and working to assist in achieving health programming goals through well-designed interventions.

Prevalence of and risk factors for microscopic and submicroscopic malaria infections in pregnancy: a systematic review and meta-analysis

Malaria infections during pregnancy can cause adverse birth outcomes, yet many infections are undetected by microscopy. We aimed to describe the epidemiology of submicroscopic malaria infections in pregnant women in Asia, the Americas, and Africa using aggregated and individual participant data (IPD). For this systematic review and meta-analysis, studies (published Jan 1, 1997 to Nov 10, 2021) with information on both microscopic and submicroscopic infections during pregnancy from Asia, the Americas, or Africa, identified in the Malaria-in-Pregnancy Library, were eligible. Studies (or subgroups or study groups) that selected participants on the basis of the presence of fever or a positive blood smear were excluded to avoid selection bias. We obtained IPD (when available) and aggregated data. Estimates of malaria transmission intensity and sulfadoxine-pyrimethamine resistance, matched by study location and year, were obtained using publicly available data. One-stage multivariable logit and multinomial models with random intercepts for study site were used in meta-analysis to assess prevalence of and risk factors for submicroscopic infections during pregnancy and at delivery. This study is registered with PROSPERO, number CRD42015027342. The search identified 87 eligible studies, 68 (78%) of which contributed to the analyses. Of these 68 studies, 45 (66%) studies contributed IPD (48 869 participants) and 23 (34%) studies contributed aggregated data (11 863 participants). During pregnancy, median prevalence estimates were 13·5% (range 0·0-55·9, 66 substudies) for submicroscopic and 8·0% (0·0-50·6, 66 substudies) for microscopic malaria. Among women with positive Plasmodium nucleic acid amplification tests (NAATs), the median proportion of submicroscopic infections was 58·7% (range 0·0-100); this proportion was highest in the Americas (73·3%, 0·0-100), followed by Asia (67·2%, 36·4-100) and Africa (56·5%, 20·5-97·7). In individual patient data analysis, compared with women with no malaria infections, those with submicroscopic infections were more likely to present with fever in Africa (adjusted odds ratio 1·32, 95% CI 1·02-1·72; p=0·038) but not in other regions. Among women with NAAT-positive infections in Asia and the Americas, Plasmodium vivax infections were more likely to be submicroscopic than Plasmodium falciparum infections (3·69, 2·45-5·54; p<0·0001). Risk factors for submicroscopic infections among women with NAAT-positive infections in Africa included older age (age ≥30 years), multigravidity, and no HIV infection. During pregnancy, submicroscopic infections are more common than microscopic infections and are associated with fever in Africa. Malaria control in pregnancy should target both microscopic and submicroscopic infections. Bill & Melinda Gates Foundation through the Worldwide Antimalarial Resistance Network.

Willingness to pay for electronic transaction levy: empirical evidence from Ghana

PurposeIn countries where the electronic levy (e-levy) has been implemented, one question that resonates with the populace is, “how much would you want to pay for e-levy per transaction?” In response, varied perspectives have been shared with no convergence. Against this background, this study seeks to estimate people's willingness to pay (WTP) for electronic transaction levy in Ghana, while analysing the associated determinants.Design/methodology/approachThis study relies on a survey of 2,810 respondents obtained from February 9 to 16, 2022 in Ghana. A multivariate logit model was estimated with its marginal effects. Further, a robustness check was undertaken using the linear probability model to validate the results.FindingsWith respect to the sample, the authors find evidence that approximately 46% of the respondents are not willing to pay any amount per transaction for the e-levy. Second, about 21% of the respondents are willing to pay Ghs0.5% as e-levy per transaction. Furthermore, about 10% of the respondents are willing to pay 1% per transaction as e-levy. Those who indicated that they would pay rates above 1% (specifically, 1.50%–1.75%) per transaction are less than 5%. For flat rates, approximately 10% of the respondents were willing to pay Ghs5 per month for all transactions above Ghs100. All others who are interested in other flat rates together are less than 5% of the respondents. The key statistically significant determinants of the probability that an individual would be willing to pay for the e-levy are also provided. This study recommends a comprehensive dialogue between the government and all stakeholders to reach a reasonable conclusion on an acceptable e-levy rate and by extension, implementation strategies.Originality/valueTo the best of the researchers' knowledge, this is the first empirical study that estimates individuals' willingness to pay for e-levy on electronic transactions in a developing country.

Abstract P266: Complex Patterns of Early Life Adversity Vary by Gender: Associations With Cardiometabolic Health and Pre-Heart Failure Among Hispanics/Latinos in the Midlife

Background: Early life adversities (ELA) are known risk factors for cardiovascular disease, but less understood is how distinct configurations of ELA impart differential risks for cardiometabolic health and heart failure (HF) in adulthood. Objective: To determine distinct profiles of ELA and assess whether there are associations between the resultant profiles and multiple indicators of cardiometabolic disease and pre-HF among Hispanic/Latino adults. Methods: Data from the Hispanic Community Health Study/Study of Latinos SCAS and ECHO-SOL (N=1143, mean age 55.9±0.4 years, 58.2% female) were used. Latent class analysis was used to identify the optimal number of classes characterizing ELA co-occurrence overall and by gender. Prevalent pre-HF was defined as systolic dysfunction (left ventricular (LF) ejection fraction &lt;50%/ global longitudinal strain &gt;15%) or diastolic dysfunction (≥ Grade 1) or LV remodeling (LV mass index &gt;115 for males, &gt;95 for females/ relative wall thickness &gt;0.42). Weighted multivariable logit models were used to examine associations. Results: The best fitting latent classes and characterization are shown in Figure 1. By gender, ELA profiles were associated with cardiometabolic factors. E.g., females with high adversity had greater odds of obesity than those with a low adversity (OR=2.27, 95% CI: 1.39 - 3.72). Alternatively, males experiencing household dysfunction had lower odds of high cholesterol than those with low adversity (OR=0.39, 95% CI: 0.19 - 0.80). Associations were not explained by age, childhood economic hardship, nativity, and Hispanic/Latino background. ELA profiles were not associated with pre-HF (e.g., high adversity OR=0.60, household dysfunction OR=0.75; all p&gt;0.05). Conclusions: Distinct patterns of ELA among Hispanic/Latino adults vary by gender; females experience more complex and varied patterns of adversity. Exposure to specific patterns of ELA were associated with several cardiometabolic outcomes, but no associations were found with any measures of pre-HF.

The impact of digital competence on telehealth utilization

ObjectivesTelehealth use has increased steadily since the mid-2000′s when technology shifted from voice-only systems to live video-conferencing and other technologies supported by broadband Internet. More recently, the COVID-19 pandemic has resulted in exponential growth in telehealth use. As telehealth systems become increasingly complex and gain widespread adoption, this study explores how users’ digital competences affect telehealth use. MethodsWe apply a series of multivariate logit models to a representative sample of California adults with Internet access surveyed in early 2021. We estimate the impact of self-reported digital competence–using items from the digital skills assessment scale–on a participant's likelihood of telehealth use during the COVID-19 pandemic as well as the likelihood to continue using telehealth beyond the pandemic. ResultsThe findings show that a one-unit increase in digital competence is associated with 72.8% greater odds of telehealth use (p <0.001) and 71.6% greater odds of willingness to continue using telehealth services beyond the pandemic (p<.01). We also found that greater social and economic capital generally were associated with increased odds of telehealth use. ConclusionsImproving access to telehealth will require solutions addressing both the first level (i.e., access to broadband and devices) and the second level (i.e., skills and attitudes towards the internet) of digital inequality. Policies and programs seeking to expand internet access must be coupled with investments in digital upskilling and training. Those with limited digital competence will face continued barriers in navigating telehealth systems, further exacerbating disparities in healthcare access and outcomes. Public Interest SummaryDigital competence is the ability and confidence to apply one's knowledge and skills to perform tasks through information technology, including computing devices and the internet. This study explores the relationship between digital competence and telehealth use among those with broadband internet access at home. Telehealth has become increasingly common due to its cost-effectiveness and accessibility for patients unable to visit healthcare facilities. Though the COVID-19 pandemic has contributed to a significant increase in telehealth use, it is expected that telehealth services will continue to expand after the pandemic subsides. In our analysis of California adults, a year into the pandemic, we find those with greater digital competence are more likely to have used telehealth during the pandemic. Further, among telehealth users, those with greater digital competence are more likely to continue using telehealth beyond the pandemic. Addressing disparities in healthcare access and outcomes will require improving potential users’ digital competence.