Decomposing Racial and Ethnic Disparities in Nursing Home Influenza Vaccination

ObjectivesQuantify how observable characteristics contribute to influenza vaccination disparities among White, Black, and Hispanic nursing home (NH) residents.DesignRetrospective cohort.Setting and ParticipantsShort- and long-stay U.S. NH residents aged ≥65 years.MethodsWe linked Minimum Data Set (MDS) and Medicare data to LTCFocUS and other facility data. We included residents with 6-month continuous enrollment in Medicare and an MDS assessment between October 1, 2013, and March 31, 2014. Residents were classified as short-stay (<100 days in NH) or long-stay (≥100 days in NH). We fit multivariable logistic regression models to assess the relationships between 27 resident and NH-level characteristics and receipt of influenza vaccination. Using nonlinear Oaxaca-Blinder decomposition, we decomposed the disparity in influenza vaccination between White versus Black and White versus Hispanic NH residents. Analyses were repeated separately for short- and long-stay residents.ResultsOur study included 630,373 short-stay and 1,029,593 long-stay residents. Proportions vaccinated against influenza included 67.2% of White, 55.1% of Black, and 54.5% of Hispanic individuals among short-stay residents and 84.2%, 76.7%, and 80.8%, respectively among long-stay residents. Across 4 comparisons, the crude disparity in influenza vaccination ranged from 3.4 to 12.7 percentage points. By equalizing 27 prespecified characteristics, these disparities could be reduced 37.7% to 59.2%. Living in a predominantly White facility and proxies for NH quality were important contributors across all analyses. Characteristics unmeasured in our data (eg, NH staff attitudes and beliefs) may have also contributed significantly to the disparity.Conclusions and ImplicationsThe racial/ethnic disparity in influenza vaccination was most dramatic among short-stay residents. Intervening on factors associated with NH quality would likely reduce these disparities; however, future qualitative research is essential to explore potential contributors that were unmeasured in our data and to understand the degree to which these factors contribute to the overall disparity in influenza vaccination.     

Soft Drink Consumption and Mental Health in Adolescents: A Longitudinal Examination

PurposePrevious studies showed associations between soft drink consumption and mental health problems in adolescents, but the direction of these effects is unknown. This study examines the hypotheses that soft drink consumption predicts aggression and depressive symptoms over time and that these mental health problems predict soft drink consumption.MethodsInterviews were conducted with 5,147 children and their caregivers from three sites at child ages 11, 13, and 16. At each time point, youth reported on their frequency of consuming soft drinks, aggressive behavior, and depressive symptoms. An autoregressive cross-lagged path model tested reciprocal relationships between soft drink consumption, aggressive behavior, and depressive symptoms over time.ResultsMore frequent consumption of soft drinks was associated with more aggressive behavior at each time point and depressive symptoms at ages 11 and 13 (r = .04 to .18, p ≤ .002). After adjusting for covariates and stability of each behavior over time, soft drink consumption at ages 11 and 13 predicted more aggressive behavior at the next time point (β = .08 and .06, p < .001). Aggressive behavior at age 13 also predicted more soft drink consumption at age 16 (β = .06, p = .002). Soft drink consumption at age 13 predicted fewer depressive symptoms (β = ?.04, p = .007), but depressive symptoms did not predict soft drink consumption.ConclusionsMore frequent consumption of soft drinks may contribute to aggressive behavior in adolescents over time; there is some support for reciprocal relationships. There is no evidence for soft drink consumption contributing to adolescents' depression. Future research should examine longitudinal effects over shorter intervals.     

Association of Insulin Resistance and Higher Oncotype DX™ Recurrence Score

Annals of Surgical Oncology - Black women with breast cancer have a worse overall survival compared with White women; however, no difference in Oncotype DX? (ODX) recurrence scores has been...     

ASO Visual Abstract: Will It Play in Peoria? A Pilot Study of a Robotic Skills Curriculum for Surgical Oncology Fellows

Annals of Surgical Oncology -     

Eating patterns and unhealthy weight control behaviors are associated with loss-of-control eating following bariatric surgery

BackgroundLoss-of-control (LOC) eating is associated with poor weight-loss outcomes following bariatric surgery. It is not clear whether eating patterns (e.g., total number of daily meals/snacks, eating after suppertime, eating when not hungry) and unhealthy weight control behaviors (e.g., smoking, using laxatives) are associated with or predictive of LOC eating.ObjectivesTo examine whether eating patterns and unhealthy weight-control behaviors are associated with LOC eating and, if so, whether they predict LOC eating in bariatric patients.SettingMulticenter study, United States.MethodsThis is a secondary analysis of the Longitudinal Assessment of Bariatric Surgery–2 study. Assessments were conducted before surgery and at 12, 24, 36, 48, 60, and 84 months after surgery. Logistic mixed models were used to examine the longitudinal associations between eating patterns, unhealthy weight-control behaviors, and LOC eating. Time-lag techniques were applied to examine whether the associated patterns and behaviors predict LOC eating.ResultsThe participants (n = 1477) were mostly women (80%), white (86.9%), and married (62.5%). At the time of surgery, the mean age was 45.4 ± 11.0 years and the mean body mass index was 47.8 ± 7.5 kg/m². The total number of daily meals/snacks, food intake after suppertime, eating when not hungry, eating when feeling full, and use of any unhealthy weight-control behaviors were positively associated with LOC eating (P < .05). Food intake after suppertime, eating when not hungry, and eating when feeling full predicted LOC eating (P < .05).ConclusionMeal patterns and unhealthy weight control behaviors may be important intervention targets for addressing LOC eating after bariatric surgery.