Extensive Set Of Covariates Research Articles

Propensity score-based analysis of long-term outcome of patients on HeartWare and HeartMate 3 left ventricular assist device support.

AimsLeft ventricular assist device therapy has become the cornerstone in the treatment of end‐stage heart failure and is increasingly used as destination therapy next to bridge to transplant or recovery. HeartMate 3 (HM3) and HeartWare (HVAD) are centrifugal continuous flow devices implanted intrapericardially and most commonly used worldwide. No randomized controlled trials have been performed yet. Analysis based on large registries may be considered as the best alternative but has the disadvantage of different standard of care between centres and missing data. Bias is introduced, because the decision which device to use was not random, even more so because many centres use only one type of left ventricular assist device. Therefore, we performed a propensity score (PS)‐based analysis of long‐term clinical outcome of patients that received HM3 or HVAD in a single centre.Methods and resultsBetween December 2010 and December 2019, 100 patients received HVAD and 81 patients HM3 as primary implantation at the University Medical Centre Utrecht. We performed PS matching with an extensive set of covariates, resulting in 112 matched patients with a median follow‐up of 28 months. After PS matching, survival was not significantly different (P = 0.21) but was better for HM3. The cumulative incidences for haemorrhagic stroke (P = 0.01) and pump thrombosis (P = 0.02) were significantly higher for HVAD patients. The cumulative incidences for major bleeding, ischaemic stroke, right heart failure, and driveline infection were not different between the groups. We found no interaction between the surgeon who performed the implantation and survival (P = 0.59, P = 0.78, and P = 0.89). Sensitivity analysis was performed, by PS matching without patients on preoperative temporary support resulting in 74 matched patients. This also resulted in a non‐significant difference in survival (P = 0.07). The PS‐adjusted Cox regression showed a worse but non‐significant (P = 0.10) survival for HVAD patients with hazard ratio 1.71 (95% confidence interval 0.91–3.24).ConclusionsSurvival was not significantly different between both groups after PS matching, but was better for HM3, with a significantly lower incidence of haemorrhagic stroke and pump thrombosis for HM3. These results need to be interpreted carefully, because matching may have introduced greater imbalance on unmeasured covariates. A multicentre approach of carefully selected centres is recommended to enlarge the number of matched patients.

The Impact of Caste: A Missing Link in the Literature on Stunting in India

India is home to some 120 million children under the age of 5, 36 percent of whom are chronically malnourished. The associated high prevalence of stunting has generated a stream of research explaining why chronic malnourishment in India is higher than in poorer countries of sub-Saharan Africa. Surprisingly, this body of research has overlooked a crucial feature of chronic malnourishment in India – that is, the difference in stunting incidence across caste and religious groups. A comparison by social categories reveals that not only are the height gaps between social groups in India two to three times larger than the India–Africa gap, but that children from the socio-economically dominant group, the upper caste Hindus, are even taller than their African counterparts. We find significant caste gaps in child height in samples that are balanced on an extensive set of covariates. We also show that height gaps are higher in areas where discrimination is more prevalent. Our results suggest that incorporating considerations of caste is essential to understanding the problem of chronic malnourishment in India today.

The Joint Effects of Loneliness and Depression on Mortality: Does Gender Matter?

Loneliness and depression are both associated with an increased risk of all-cause mortality among older adults. However, the evidence on the joint effect of loneliness and depression is scarce. Furthermore, previous research has rarely examined the modifying effects of gender. We investigated these questions using the Panel on Health and Aging of Singaporean Elderly, a nationally-representative cohort study of community-dwelling older Singaporean adults aged 60 and above, conducted in 2009 with two follow-up waves in 2011 and 2015 (N=4536). We operationalized six groups based on three categories of loneliness measured using the 3-item University of California, Los Angeles (UCLA) loneliness scale: always lonely, sometimes lonely, and never lonely; Two categories of depressive symptom scores were measured using the 11-item Center for Epidemiologic Studies Depression Scale (CES-D) scale: depressed and not depressed. Cox proportional hazards models were employed to estimate the mortality risks for each group, with an extensive set of covariates. Due to significant differences in the prevalence of loneliness and depression in different genders, we conducted gender-stratified analyses. Compared to being not depressed and never lonely, women who were depressed and sometimes lonely and who were not depressed but always lonely had a higher mortality risk. Men who were not depressed but sometimes lonely had a higher mortality risk. We conclude that loneliness appears to be the predominant construct in conferring excess mortality risk. Health policies and interventions addressing the factors common and unique to each gender may improve psychological well-being at older ages, thereby extending the lifespan.

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium

Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progression phenotypes that are potentially more responsive to interventions. We used publicly available data from the Foundation for the National Institutes of Health (FNIH) osteoarthritis (OA) Biomarkers Consortium, where radiographic (medial joint space narrowing of ≥0.7mm), and pain progression (increase of ≥9 Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC] points) were defined at 48 months, as four mutually exclusive outcome groups (none, both, pain only, radiographic only), along with an extensive set of covariates. We applied distance weighted discrimination (DWD), direction-projection-permutation (DiProPerm) testing, and clustering methods to focus on the contrast (z-scores) between those progressing by both criteria ("progressors") and those progressing by neither ("non-progressors"). Using all observations (597 individuals, 59% women, mean age 62 years and BMI 31kg/m2) and all 73 baseline variables available in the dataset, there was a clear separation among progressors and non-progressors (z=10.1). Higher z-scores were seen for the magnetic resonance imaging (MRI)-based variables than for demographic/clinical variables or biochemical markers. Baseline variables with the greatest contribution to non-progression at 48 months included WOMAC pain, lateral meniscal extrusion, and serum N-terminal pro-peptide of collagen IIA (PIIANP), while those contributing to progression included bone marrow lesions, osteophytes, medial meniscal extrusion, and urine C-terminal crosslinked telopeptide type II collagen (CTX-II). Using methods that provide a way to assess numerous variables of different types and scalings simultaneously in relation to an outcome of interest enabled a data-driven approach that identified key variables associated with a progression phenotype.

Part-time employment and worker health in the United States

A growing body of research has highlighted the consequences of part-time employment for workers’ health and well-being. However, these studies have yielded inconsistent results and relied on cross-sectional data. In addition, relatively little empirical research has explored whether the effect of working part-time on health varies by gender, particularly in the United States. Using longitudinal data from three waves of the General Social Survey panel (2010–2012–2014), our study examined the association between part-time employment and perceived health among U.S employees, and whether this association varied by gender. The results showed that part-time workers were less likely to report poor self-rated health than full-time workers, especially among males. The pattern of results was consistent across empirical approaches—including generalized estimating equations and random effects models, with an extensive set of covariates. Taken together, these findings suggest that for U.S. employees, working part-time appears to be beneficial or at least not detrimental to perceived health, which warrants further investigation.

Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA

We analyze 20,660 transactions of single family detached houses sold in 2003 and 2004 in the city of Los Angeles, CA, to estimate the value of urban trees, irrigated grass, and non-irrigated grass areas. To deal with spatial autocorrelation and unobserved neighborhood characteristics, we contrast two models: a geographically weighted regression model, and a Cliff–Ord model with spatial lags in the dependent variable, the exogenous variables, and the disturbances as well as submarket fixed effects and an extensive set of covariates. We find that Angelenos like lawns: over 88% of the properties examined would gain value with additional irrigated grass on their parcel, and even more (89%) in their neighborhood. Although more non-irrigated grass/bare soil on parcels typically hurts property values, it often has the opposite effect at the neighborhood level. Moreover, additional parcel trees would decrease the value of almost 40% of the properties examined and they would have only a small positive impact on most of the others. By contrast, additional neighborhood trees would slightly increase the value of over 97% of the properties analyzed. This suggests that while Los Angeles residents may want additional trees, they are unwilling to pay for them. These results have implications for urban tree planting programs that rely primarily on private property owners.

The Effect of an Employer Health Insurance Mandate on Health Insurance Coverage and the Demand for Labor: Evidence from Hawaii

Over the past few decades, policy makers have considered employer mandates as a strategy for stemming the tide of declining health insurance coverage. In this paper we examine the long term effects of the only employer health insurance mandate that has ever been enforced in the United States, Hawaii's Prepaid Health Care Act, using a standard supply-demand framework and Current Population Survey data covering the years 1979 to 2005. During this period, the coverage gap between Hawaii and other states increased, as did real health insurance costs, implying a rising burden of the mandate on Hawaii's employers. We use a variant of the traditional permutation (placebo) test across all states to examine the magnitude and statistical properties of these growing coverage differences and their impacts on labor market outcomes, conditional on an extensive set of covariates. As expected, the coverage gap is larger for workers who tend to have low rates of coverage in the voluntary market (primarily those with lower skills). We also find that relative wages fell in Hawaii over time, but the estimates are statistically insignificant. By contrast, a parallel analysis of workers employed fewer than 20 hours per week indicates that the law significantly increased employers' reliance on such workers in order to reduce the burden of the mandate. We find no evidence suggesting that the law reduced employment probabilities.

Poverty and childhood undernutrition in developing countries: A multi-national cohort study

The importance of reducing childhood undernutrition has been enshrined in the United Nations' Millennium Development Goals. This study explores the relationship between alternative indicators of poverty and childhood undernutrition in developing countries within the context of a multi-national cohort study (Young Lives). Approximately 2000 children in each of four countries - Ethiopia, India (Andhra Pradesh), Peru and Vietnam - had their heights measured and were weighed when they were aged between 6 and 17 months (survey one) and again between 4.5 and 5.5 years (survey two). The anthropometric outcomes of stunted, underweight and wasted were calculated using World Health Organization 2006 reference standards. Maximum-likelihood probit estimation was employed to model the relationship within each country and survey between alternative measures of living standards (principally a wealth index developed using principal components analysis) and each anthropometric outcome. An extensive set of covariates was incorporated into the models to remove as much individual heterogeneity as possible. The fully adjusted models revealed a negative and statistically significant coefficient on wealth for all outcomes in all countries, with the exception of the outcome of wasted in India (Andhra Pradesh) and Vietnam (survey one) and the outcome of underweight in Vietnam (surveys one and two). In survey one, the partial effects of wealth on the probabilities of stunting, being underweight and wasting was to reduce them by between 1.4 and 5.1 percentage points, 1.0 and 6.4 percentage points, and 0.3 and 4.5 percentage points, respectively, with each unit (10%) increase in wealth. The partial effects of wealth on the probabilities of anthropometric outcomes were larger in the survey two models. In both surveys, children residing in the lowest wealth quintile households had significantly increased probabilities of being stunted in all four study countries and of being underweight in Ethiopia, India (Andhra Pradesh) and Peru in comparison to children residing in the highest wealth quintile households. Random effects probit models confirmed the statistical significance of increased wealth in reducing the probability of being stunted and underweight across all four study countries. We conclude that, although multi-faceted, childhood undernutrition in developing countries is strongly rooted in poverty.

The Effect of an Employer Health Insurance Mandate on Health Insurance Coverage and the Demand for Labor: Evidence from Hawaii

Over the past few decades, policy makers have considered employer mandates as a strategy for stemming the tide of declining health insurance coverage. In this paper we examine the long term effects of the only employer health insurance mandate that has ever been enforced in the United States, Hawaii's Prepaid Health Care Act, using a standard supply-demand framework and Current Population Survey data covering the years 1979 to 2005. During this period, the coverage gap between Hawaii and other states increased, as did real health insurance costs, implying a rising burden of the mandate on Hawaii's employers. We use a variant of the traditional permutation (placebo) test across all states to examine the magnitude and statistical properties of these growing coverage differences and their impacts on labor market outcomes, conditional on an extensive set of covariates. As expected, the coverage gap is larger for workers who tend to have low rates of coverage in the voluntary market (primarily those with lower skills). We also find that relative wages fell in Hawaii over time, but the estimates are statistically insignificant. By contrast, a parallel analysis of workers employed fewer than 20 hours per week indicates that the law significantly increased employers' reliance on such workers in order to reduce the burden of the mandate. We find no evidence suggesting that the law reduced employment probabilities.

DOES GUN PREVALENCE AFFECT TEEN GUN CARRYING AFTER ALL?*

Previous research suggests that American adolescents usually have ready access to guns, and that the extent of misuse of guns by adolescents is not much affected by local gun prevalence or regulation. This “futility” claim is based on one interpretation of survey data from several cities, but has not been tested directly. Here we do so using microdata from a nationally representative survey, the 1995 National Survey of Adolescent Males. Using the restricted geo‐coded version of these data, and conditioning on an extensive set of covariates, we find (among other results) that the likelihood of gun carrying increases markedly with the prevalence of gun ownership in the given community. We also analyze the propensity to carry other types of weapons, finding that it is unrelated to the local prevalence of gun ownership. The prevalence of youths carrying both guns and other weapons is positively related to the local rate of youth violence (as measured by the robbery rate), confirmatory evidence that weapons carrying by youths is motivated in part by self‐protection.