Sit-to-stand and treadmill desks may help sedentary office workers meet the physical activity guideline to “move more and sit less,” but little is known about their long-term impact on altering the accumulation patterns of physical behaviors. This study explores the impact of sit-to-stand and treadmill desks on physical behavior accumulation patterns during a 12-month multicomponent intervention with an intent-to-treat design in overweight and obese seated office workers. In total, 66 office workers were cluster randomized into a seated desk control (n=21, 32%; 8 clusters), sit-to-stand desk (n=23, 35%; 9 clusters), or treadmill desk (n=22, 33%; 7 clusters) group. Participants wore an activPAL (PAL Technologies Ltd) accelerometer for 7 days at baseline, 3-month follow-up (M3), 6-month follow-up (M6), and 12-month follow-up (M12) and received periodic feedback on their physical behaviors. Analyses of physical behavior patterns included total day and workday number of sedentary, standing, and stepping bouts categorized into durations ranging from 1 to 60 and >60 minutes and usual sedentary, standing, and stepping bout durations. Intervention trends were analyzed using random-intercept mixed linear models accounting for repeated measures and clustering effects. The treadmill desk group favored prolonged sedentary bouts (>60 min), whereas the sit-to-stand desk group accrued more short-duration sedentary bouts (<20 min). Therefore, compared with controls, sit-to-stand desk users had shorter usual sedentary bout durations short-term (total day ΔM3: −10.1 min/bout, 95% CI −17.9 to −2.2; P=.01; workday ΔM3: −20.3 min/bout, 95% CI −37.7 to −2.9; P=.02), whereas treadmill desk users had longer usual sedentary bout durations long-term (total day ΔM12: 9.0 min/bout, 95% CI 1.6-16.4; P=.02). The treadmill desk group favored prolonged standing bouts (30-60 min and >60 min), whereas the sit-to-stand desk group accrued more short-duration standing bouts (<20 min). As such, relative to controls, treadmill desk users had longer usual standing bout durations short-term (total day ΔM3: 6.9 min/bout, 95% CI 2.5-11.4; P=.002; workday ΔM3: 8.9 min/bout, 95% CI 2.1-15.7; P=.01) and sustained this long-term (total day ΔM12: 4.5 min/bout, 95% CI 0.7-8.4; P=.02; workday ΔM12: 5.8 min/bout, 95% CI 0.9-10.6; P=.02), whereas sit-to-stand desk users showed this trend only in the long-term (total day ΔM12: 4.2 min/bout, 95% CI 0.1-8.3; P=.046). The treadmill desk group accumulated more stepping bouts across various bins of duration (5-50 min), primarily at M3. Thus, treadmill desk users had longer usual stepping bout durations in the short-term compared with controls (workday ΔM3: 4.8 min/bout, 95% CI 1.3-8.3; P=.007) and in the short- and long-term compared with sit-to-stand desk users (workday ΔM3: 4.7 min/bout, 95% CI 1.6-7.8; P=.003; workday ΔM12: 3.0 min/bout, 95% CI 0.1-5.9; P=.04). Sit-to-stand desks exerted potentially more favorable physical behavior accumulation patterns than treadmill desks. Future active workstation trials should consider strategies to promote more frequent long-term movement bouts and dissuade prolonged static postural fixity. ClinicalTrials.gov NCT02376504; https://clinicaltrials.gov/ct2/show/NCT02376504

We apply the theory of collateral consequences and a social stress process framework to school discipline to examine whether exclusionary school discipline policies are associated with the mental health and wellbeing of adolescents who have never been suspended or expelled and whether this association varies across race/ethnicity. Data are from 8,878 adolescents in the National Longitudinal Study of Adolescent to Adult Health. Hierarchical linear models examined associations between discipline policies and adolescent depressive symptoms and school-connectedness, and modification by race/ethnicity. Schools had high levels of exclusionary discipline for both violent and non-violent infractions. More exclusionary policies were associated with higher levels of depressive symptoms ( b = 1.03, 95% CI: 0.15, 1.91, p < .05). Sense of school-connectedness was not associated with disciplinary policies. Neither association was modified by race/ethnicity.

BACKGROUND: Postoperative delirium is frequent in older adults and is associated with postoperative neurocognitive disorder (PND). Studies evaluating perioperative medication use and delirium have generally evaluated medications in aggregate and been poorly controlled; the association between perioperative medication use and PND remains unclear. We sought to evaluate the association between medication use and postoperative delirium and PND in older adults undergoing major elective surgery. METHODS: This is a secondary analysis of a prospective cohort study of adults ≥70 years without dementia undergoing major elective surgery. Patients were interviewed preoperatively to determine home medication use. Postoperatively, daily hospital use of 7 different medication classes listed in guidelines as risk factors for delirium was collected; administration before delirium was verified. While hospitalized, patients were assessed daily for delirium using the Confusion Assessment Method and a validated chart review method. Cognition was evaluated preoperatively and 1 month after surgery using a neurocognitive battery. The association between prehospital medication use and postoperative delirium was assessed using a generalized linear model with a log link function, controlling for age, sex, type of surgery, Charlson comorbidity index, and baseline cognition. The association between daily postoperative medication use (when class exposure ≥5%) and time to delirium was assessed using time-varying Cox models adjusted for age, sex, surgery type, Charlson comorbidity index, Acute Physiology and Chronic Health Evaluation (APACHE)-II score, and baseline cognition. Mediation analysis was utilized to evaluate the association between medication use, delirium, and cognitive change from baseline to 1 month. RESULTS: Among 560 patients enrolled, 134 (24%) developed delirium during hospitalization. The multivariable analyses revealed no significant association between prehospital benzodiazepine (relative risk [RR], 1.44; 95% confidence interval [CI], 0.85–2.44), beta-blocker (RR, 1.38; 95% CI, 0.94–2.05), NSAID (RR, 1.12; 95% CI, 0.77–1.62), opioid (RR, 1.22; 95% CI, 0.82–1.82), or statin (RR, 1.34; 95% CI, 0.92–1.95) exposure and delirium. Postoperative hospital benzodiazepine use (adjusted hazard ratio [aHR], 3.23; 95% CI, 2.10–4.99) was associated with greater delirium. Neither postoperative hospital antipsychotic (aHR, 1.48; 95% CI, 0.74–2.94) nor opioid (aHR, 0.82; 95% CI, 0.62–1.11) use before delirium was associated with delirium. Antipsychotic use (either presurgery or postsurgery) was associated with a 0.34 point (standard error, 0.16) decrease in general cognitive performance at 1 month through its effect on delirium (P = .03), despite no total effect being observed. CONCLUSIONS: Administration of benzodiazepines to older adults hospitalized after major surgery is associated with increased postoperative delirium. Association between inhospital, postoperative medication use and cognition at 1 month, independent of delirium, was not detected.

Rationale: It is unclear whether opioid use increases the risk of ICU delirium. Prior studies have not accounted for confounding, including daily severity of illness, pain, and competing events that may preclude delirium detection.Objectives: To evaluate the association between ICU opioid exposure, opioid dose, and delirium occurrence.Methods: In consecutive adults admitted for more than 24 hours to the ICU, daily mental status was classified as awake without delirium, delirium, or unarousable. A first-order Markov model with multinomial logistic regression analysis considered four possible next-day outcomes (i.e., awake without delirium, delirium, unarousable, and ICU discharge or death) and 11 delirium-related covariables (baseline: admission type, age, sex, Acute Physiology and Chronic Health Evaluation IV score, and Charlson comorbidity score; daily: ICU day, modified Sequential Organ Failure Assessment, ventilation use, benzodiazepine use, and severe pain). This model was used to quantify the association between opioid use, opioid dose, and delirium occurrence the next day.Measurements and Main Results: The 4,075 adults had 26,250 ICU days; an opioid was administered on 57.0% (n = 14,975), severe pain occurred on 7.0% (n = 1,829), and delirium occurred on 23.5% (n = 6,176). Severe pain was inversely associated with a transition to delirium (odds ratio [OR] 0.72; 95% confidence interval [CI], 0.53-0.97). Any opioid administration in awake patients without delirium was associated with an increased risk for delirium the next day [OR, 1.45; 95% CI, 1.24-1.69]. Each daily 10-mg intravenous morphine-equivalent dose was associated with a 2.4% increased risk for delirium the next day.Conclusions: The receipt of an opioid in the ICU increases the odds of transitioning to delirium in a dose-dependent fashion.

OBJECTIVES: Social determinants of health may affect ICU outcome, but the association between social determinants of health and delirium remains unclear. We evaluated the association between three social determinants of health and delirium occurrence and duration in critically ill adults. DESIGN: Secondary, subgroup analysis of a cohort study. SETTING: Single, 36-bed mixed medical-surgical ICU in the Netherlands. PATIENTS: Nine hundred fifty-six adults consecutively admitted from July 2016 to February 2020. Patients admitted after elective surgery, residing in a nursing home, or not expected to survive greater than or equal to 48 hours were excluded. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Four factors related to three Center for Disease Control social determinants of health domains (social/community context [ethnicity], education access/quality [educational level], and economic stability [employment status and monthly income]) were collected at ICU admission from patients (or families). Well-trained ICU nurses evaluated patients without coma (Richmond Agitation Sedation Scale, –4, –5) and with the Confusion Assessment Method-ICU and/or a delirium day was defined by greater than or equal to 1 + Confusion Assessment Method-ICU and/or scheduled antipsychotic use. Multivariable logistic regression models controlling for ICU days and 10 delirium risk variables (before-ICU: age, Charlson, cognitive impairment, any antidepressant, antipsychotic, or benzodiazepine use; ICU baseline: Acute Physiology and Chronic Health Evaluation IV and admission type; daily ICU: Sequential Organ Failure Assessment, restraint use, coma, benzodiazepine, or opioid use) evaluated associations between each social determinant of health factor and both ICU delirium occurrence and duration. Delirium occurred in 393/956 patients (45.4%) for 2 days (1–5 d). Patients with low (vs high) income had more ICU delirium ( p = 0.05). Multivariate analyses revealed no social determinants of health to be significantly associated with increased delirium occurrence or duration. Low (vs high) income was weakly associated with increased delirium occurrence (adjusted odds ratio, 1.83; 95% CI, 0.91–3.89). Low (vs high) education (adjusted relative risk, 1.21; 95% CI, 0.97–1.53) was weakly associated with a longer delirium duration. CONCLUSIONS: Social determinants of health did not affect ICU delirium in one Dutch region. Additional research across different countries/regions and where additional social determinants of health are considered is needed to define the association between social determinants of health and ICU delirium.

Background: Conflicting results on associations between dietary quality and bone have been noted across populations, and this has been understudied in Puerto Ricans, a population at higher risk of osteoporosis than previously appreciated. Objective: To compare cross-sectional associations between 3 dietary quality indices [Dietary Approaches to Stop Hypertension (DASH), Alternative Health Eating Index (AHEI-2010), and Mediterranean Diet Score (MeDS)] with bone outcomes. Method: Participants (n = 865-896) from the Boston Puerto Rican Osteoporosis Study (BPROS) with complete bone and dietary data were included. Indices were calculated from validated food frequency data. Bone mineral density (BMD) was measured using DXA. Associations between dietary indices (z-scores) and their individual components with BMD and osteoporosis were tested with ANCOVA and logistic regression, respectively, at the lumbar spine and femoral neck, stratified by male, premenopausal women, and postmenopausal women. Results: Participants were 59.9 y +/- 7.6 y and mostly female (71%). Among postmenopausal women not taking estrogen, DASH (score: 11-38) was associated with higher trochanter (0.026 +/- 0.006 g/cm(2), P <0.001), femoral neck (0.022 +/- 0.006 g/cm(2), P <0.001), total hip (0.029 +/- 0.006 g/cm(2), P <0.001), and lumbar spine BMD (0.025 +/- 0.007 g/cm(2), P = 0.001). AHEI (score: 25-86) was also associated with spine and all hip sites (P <0.02), whereas MeDS (0-9) was associated only with total hip (P = 0.01) and trochanter BMD (P = 0.007) in postmenopausal women. All indices were associated with a lower likelihood of osteoporosis (OR from 0.54 to 0.75). None of the results were significant for men or premenopausal women. Conclusions: Although all appeared protective, DASH was more positively associated with BMD than AHEI or MeDS in postmenopausal women not taking estrogen. Methodological differences across scores suggest that a bone-specific index that builds on existing indices and that can be used to address dietary differences across cultural and ethnicminority populations should be considered.

There were some errors in the variables in this paper.

OBJECTIVES Methods for pharmacoepidemiologic studies of large-scale data repositories are established. Although clinical cohorts of older adults often contain critical information to advance our understanding of medication risk and benefit, the methods best suited to manage medication data in these samples are sometimes unclear and their degree of validation unknown. We sought to provide researchers, in the context of a clinical cohort study of delirium in older adults, with guidance on the methodological tools to use data from clinical cohorts to better understand medication risk factors and outcomes. DESIGN Prospective cohort study. SETTING The Successful Aging After Elective Surgery (SAGES) prospective cohort. PARTICIPANTS A total of 560 older adults (aged >= 70 years) without dementia undergoing elective major surgery. MEASUREMENTS Using the SAGES clinical cohort, methods used to characterize medications were identified, reviewed, analyzed, and distinguished by appropriateness and degree of validation for characterizing pharmacoepidemiologic data in smaller clinical data sets. RESULTS Medication coding is essential; the American Hospital Formulary System, most often used in the United States, is not preferred over others. Use of equivalent dosing scales (e.g., morphine equivalents) for a single medication class (e.g., opioids) is preferred over multiclass analgesic equivalency scales. Medication aggregation from the same class (e.g., benzodiazepines) is well established; the optimal prevalence breakout for aggregation remains unclear. Validated scale(s) to combine structurally dissimilar medications (e.g., anticholinergics) should be used with caution; a lack of consensus exists regarding the optimal scale. Directed acyclic graph(s) are an accepted method to conceptualize causative frameworks when identifying potential confounders. Modeling-based strategies should be used with evidence-based, a priori variable-selection strategies. CONCLUSION As highlighted in the SAGES cohort, the methods used to classify and analyze medication data in clinically rich cohort studies vary in the rigor by which they have been developed and validated.

Abstract Background While delirium prevalence and duration are each associated with increased 30-day, 6-month, and 1-year mortality, the association between incident ICU delirium and mortality remains unclear. We evaluated the association between both incident ICU delirium and days spent with delirium in the 28 days after ICU admission and mortality within 28 and 90 days. Methods Secondary cohort analysis of a randomized, double-blind, placebo-controlled trial conducted among 1495 delirium-free, critically ill adults in 14 Dutch ICUs with an expected ICU stay ≥2 days where all delirium assessments were completed. In the 28 days after ICU admission, patients were evaluated for delirium and coma 3x daily; each day was coded as a delirium day [≥1 positive Confusion Assessment Method for the ICU (CAM-ICU)], a coma day [no delirium and ≥ 1 Richmond Agitation Sedation Scale (RASS) score ≤ − 4], or neither. Four Cox-regression models were constructed for 28-day mortality and 90-day mortality; each accounted for potential confounders (i.e., age, APACHE-II score, sepsis, use of mechanical ventilation, ICU length of stay, and haloperidol dose) and: 1) delirium occurrence, 2) days spent with delirium, 3) days spent in coma, and 4) days spent with delirium and/or coma. Results Among the 1495 patients, 28 day mortality was 17% and 90 day mortality was 21%. Neither incident delirium (28 day mortality hazard ratio [HR] = 1.02, 95%CI = 0.75–1.39; 90 day mortality HR = 1.05, 95%CI = 0.79–1.38) nor days spent with delirium (28 day mortality HR = 1.00, 95%CI = 0.95–1.05; 90 day mortality HR = 1.02, 95%CI = 0.98–1.07) were significantly associated with mortality. However, both days spent with coma (28 day mortality HR = 1.05, 95%CI = 1.02–1.08; 90 day mortality HR = 1.05, 95%CI = 1.02–1.08) and days spent with delirium or coma (28 day mortality HR = 1.03, 95%CI = 1.00–1.05; 90 day mortality HR = 1.03, 95%CI = 1.01–1.06) were significantly associated with mortality. Conclusions This analysis suggests neither incident delirium nor days spent with delirium are associated with short-term mortality after ICU admission. Trial registration ClinicalTrials.gov , Identifier NCT01785290 Registered 7 February 2013.

Objectives: To assess whether country-level urban population growth is associated with the magnitude of the urban-rural disparity in under-five mortality (U5M) using ecologic and multilevel analyses. Methods: We used data from 2010 to 2015 Demographic and Health Surveys and World Bank data from 30 sub-Saharan African countries (n = 411,054 women). Country-level linear regressions determined associations between urban population growth and economic growth between 2005 and 2010 on U5M risk differences. Multilevel logistic regression models were used to determine the impact of urban population growth on the urban advantage in U5M, adjusting for child and maternal factors. Results: Countries with greater urban population growth and low economic growth had greater disparities in U5M between urban and rural areas. After adjusting for known U5M risk factors in multilevel analyses, interactions between country-level urban population growth and urbanicity were identified. Conclusions: Continued efforts to evaluate and address disparities in child mortality outcomes in sub-Saharan Africa should acknowledge urbanicity in context, as well as socioeconomic and geographic realities of families, mothers and children. Low-resource, demographically shifting environments require novel strategies to decrease child mortality.

Despite indications that there are differences in rates of child maltreatment (CM) cases in the child protection system between urban and rural areas, there are no published studies examining the differences in self-reported CM prevalence and its correlates by urbanicity. The present study aimed to: (1) identify the distribution of self-reported childhood experiences of maltreatment by urbanicity, (2) assess whether differences by urbanicity persist after adjusting for known risk factors, and (3) explore whether the associations between these risk factors and CM are modified by urban-rural designation. Using nationally representative data from waves I and III of the National Longitudinal Study of Adolescent to Adult Health, the prevalence of six maltreatment outcomes was estimated for rural, minor urban, and major urban areas (N = 14,322). Multivariable logistic models were estimated identifying if risk associated with urbanicity persisted after adjusting for other risk factors. Interactions between urbanicity and main effects were explored. Prevalence estimates of any CM, poly-victimization, supervision neglect, and physical abuse were significantly higher in major urban areas. Those from major urban areas were more likely to report any maltreatment and supervision neglect even after adjusting for child and family risk factors. The association between race/ethnicity, welfare receipt, low parental educational attainment, and disability status and CM were modified by urbanicity. Significant differences in the prevalence and correlates of CM exist between urban and rural areas. Future research and policy should use self-reported prevalence, in conjunction with official reports, to inform child maltreatment prevention and intervention.

ABSTRACT Historically, osteoporosis has not been considered a public health priority for the Hispanic population. However, recent data indicate that Mexican Americans are at increased risk for this chronic condition. Although it is well established that there is heterogeneity in social, lifestyle, and health-related factors among Hispanic subgroups, there are currently few studies on bone health among Hispanic subgroups other than Mexican Americans. The current study aimed to determine the prevalence of osteoporosis and low bone mass (LBM) among 953 Puerto Rican adults, aged 47 to 79 years and living on the US mainland, using data from one of the largest cohorts on bone health in this population: The Boston Puerto Rican Osteoporosis Study (BPROS). Participants completed an interview to assess demographic and lifestyle characteristics and bone mineral density measures. To facilitate comparisons with national data, we calculated age-adjusted estimates for osteoporosis and LBM for Mexican American, non-Hispanic white, and non-Hispanic black adults, aged ≥50 years, from the National Health and Nutrition Examination Survey (NHANES). The overall prevalence of osteoporosis and LBM were 10.5% and 43.3% for participants in the BPROS, respectively. For men, the highest prevalence of osteoporosis was among those aged 50 to 59 years (11%) and lowest for men ≥70 years (3.7%). The age-adjusted prevalence of osteoporosis for Puerto Rican men was 8.6%, compared with 2.3% for non-Hispanic white, and 3.9% for Mexican American men. There were no statistically significant differences between age-adjusted estimates for Puerto Rican women (10.7%), non-Hispanic white women (10.1%), or Mexican American women (16%). There is a need to understand specific factors contributing to osteoporosis in Puerto Rican adults, particularly younger men. This will provide important information to guide the development of culturally and linguistically tailored interventions to improve bone health in this understudied and high-risk population. © 2017 American Society for Bone and Mineral Research.

OBJECTIVES:Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer screening. Risk stratification for advanced colorectal neoplasia (ACN) might facilitate more effective shared decision making when selecting an appropriate screening option. Our objective was to develop and validate a clinical index for estimating the probability of ACN at screening colonoscopy. METHODS:We conducted a cross-sectional analysis of 3,543 asymptomatic, mostly average-risk patients 50-79 years of age undergoing screening colonoscopy at two urban safety net hospitals. Predictors of ACN were identified using multiple logistic regression. Model performance was internally validated using bootstrapping methods. RESULTS:The final index consisted of five independent predictors of risk (age, smoking, alcohol intake, height, and a combined sex/race/ethnicity variable). Smoking was the strongest predictor (net reclassification improvement (NRI), 8.4%) and height the weakest (NRI, 1.5%). Using a simplified weighted scoring system based on 0.5 increments of the adjusted odds ratio, the risk of ACN ranged from 3.2% (95% confidence interval (CI), 2.6-3.9) for the low-risk group (score ≤2) to 8.6% (95% CI, 7.4-9.7) for the intermediate/high-risk group (score 3-11). The model had moderate to good overall discrimination (C-statistic, 0.69; 95% CI, 0.66-0.72) and good calibration (P=0.73-0.93). CONCLUSIONS:A simple 5-item risk index based on readily available clinical data accurately stratifies average-risk patients into low- and intermediate/high-risk categories for ACN at screening colonoscopy. Uptake into clinical practice could facilitate more effective shared decision-making for CRC screening, particularly in situations where patient and provider test preferences differ.

Several cross-sectional studies have reported on the association between serum 25-hydroxy vitamin D concentrations (25(OH)D) and body mass index (BMI). We examined the longitudinal effect of BMI on serum 25(OH)D concentrations among 866 Puerto Rican adults living in the Greater Boston area: 246 men and 620 women, aged 45-75 years at baseline and 2 year. Our analyses showed negative correlations at two time points between BMI and serum 25(OH)D concentrations. The multivariate analysis showed that when predicting the change of serum 25(OH)D concentrations, baseline-BMI had significant inverse association (P<0.04) controlling for age, sex, and baseline-BMI. This association remained significant after adjusting for vitamin D supplement use, smoking, miles walked/day and alcohol intake (P<0.01). In conclusion, the major findings of the present study are obesity (1) was inversely associated with 25(OH)D at baseline; (2) with the change in serum 25(OH)D at 2-year in this population of older Puerto Rican adults living in the Boston area. This article is part of a Special Issue entitled '16th Vitamin D Workshop'.

Background Substantial geographical clustering of Clostridium difficile infection (CDI) outbreaks in hospitals in the USA have previously been demonstrated. Aim To test the hypothesis that hospital burden of CDI is associated with admission from and discharge to long-term care facilities (LTCFs). Methods Hospital discharge data from 19 states in the USA were used to identify all patients discharged with a diagnosis of CDI from 1 January 2002 to 31 December 2004. For every hospital, the proportion of discharges with a diagnosis of CDI was calculated, and those above the 90th percentile were classified as ‘high CDI’ hospitals. We tested the association between this measure of hospital burden of CDI and the rates of admission from and discharges to LTCFs. We adjusted for other hospital level characteristics, case-complexity and local population characteristics. Findings We identified 38,372,951 discharges during the three-year study period. Of all discharges, 274,311 (0.71%) had a primary or secondary diagnosis of CDI. Hospitals had a mean CDI burden of 7.8 cases per 1000 discharges. High CDI hospitals (N = 610; 10.0%) had a mean CDI burden of 34.8 cases per 1000 discharges. Compared to other hospitals, high CDI hospitals were more likely to have a high proportion of admissions from or discharges to LTCFs. This association persisted after adjustments for other hospital characteristics, case-complexity, and area population characteristics. Conclusion A high rate of admission from or discharge to LTCFs is associated with an increased hospital burden of CDI.

Introduction: Few large-scale studies have evaluated the variability of glycemic index (GI) value determinations among individuals, particularly on the basis of biological parameters such as sex, a...