Physical activity and risk of bladder cancer among postmenopausal women.

Physical activity is associated with decreased risk for many cancers. Studies on the association between physical activity and risk of bladder cancer are limited, and findings are inconsistent. Postmenopausal women (mean age = 63.3) were recruited into the Women's Health Initiative from 1993 to 1998. Self-reported baseline information on physical activity and other covariates were available in 141 288 participants. Incident bladder cancer cases were collected through 2018 and centrally adjudicated. Hazard ratios (HRs) and 95% confidence intervals (CIs) were determined by Cox proportional hazard regression models. Effect modification due to smoking was assessed. During an average of 18.5 years of follow-up, 817 bladder cancer cases were identified. Compared to physically inactive women, those who engaged in ≥15 MET-hours/week of total physical activity, ≥8.75 MET-hours/week of walking or ≥11.25 MET-hours/week of moderate to vigorous physical activity had lower risk of bladder cancer (HR = 0.74, 95% CI: 0.59-0.94, P for linear trend = .02; HR = 0.79, 95% CI: 0.63-0.98, P for linear trend = .03; and HR = 0.76, 95% CI: 0.61-0.94, P for linear trend = .02, respectively). No effect modification was found by smoking status (P for interaction = .06, 0.91 and 0.27, respectively). We found that total physical activity, walking and moderate to vigorous physical activity were inversely associated with bladder cancer incidence among postmenopausal women in a dose-response manner. Physical activity may play a potential role in the primary prevention of bladder cancer. Further studies with objective measurements of physical activity are needed to confirm these findings.

The association between type 2 diabetes mellitus and bladder cancer risk among postmenopausal women.

INTRODUCTION: Evidence on the association between diabetes and risk of bladder cancer has been controversial. In addition, findings on the associations between duration of diabetes, diabetes treatment, and risk of bladder cancer have been inconsistent. METHODS: A total of 148,208 participants in Women's Health Initiative study were included. Information on diabetes status, diabetes duration, and treatment was collected both at baseline and during follow-up. Information on potential confounders including age, race/ethnicity, education, occupation, family history of cancer, smoking status, alcohol consumption, total physical activity, body mass index, and daily dietary intake were collected at baseline. Bladder cancer cases were collected and confirmed by a centralized review of pathology reports. Cox proportional hazard models with time-varying covariates were used to examine associations of diabetes status, duration of diabetes, and diabetes treatment with bladder cancer risk. RESULTS: During a median follow-up of 18.5 years, 865 bladder cancer cases were identified. There were no significant associations of diabetes, duration of diabetes, or diabetes treatment with risk of bladder cancer. Participants with prevalent diabetes did not have significantly higher risk of bladder cancer compared with those without diabetes. CONCLUSION: Diabetes was not significantly associated with risk of bladder cancer among postmenopausal women.

Smoking Cessation and the Risk of Bladder Cancer among Postmenopausal Women.

Smoking is the strongest established risk factor for bladder cancer. Former smokers have a lower risk of bladder cancer compared with current smokers, but findings on the dose-response relationship between years after quitting and the risk of bladder cancer are inconsistent. A total of 143,279 postmenopausal women from the Women's Health Initiative Study were included. Cox proportional hazards regression models were applied for estimating age- and multivariable-adjusted HRs and their 95% confidence intervals (CI). There were 870 bladder cancer cases identified over an average of 14.8 years of follow-up. After adjusting for pack-years of smoking, bladder cancer risk among former smokers declined by 25% within the first 10 years of cessation and continued to decrease as cessation time increased but remained higher than never smokers after 30 years of quitting (HR, 1.92; 95% CI, 1.43-2.58). Smokers who quit smoking had a lower risk of bladder cancer compared with current smokers (HR, 0.61; 95% CI, 0.40-0.94). We conclude that among postmenopausal women, there is a significant reduction in the risk of bladder cancer after quitting smoking. In addition to primary prevention, smoking cessation is critical to prevent the incidence of bladder cancer in older women.

Maternal fair/poor self-rated health and adverse infant birth outcomes.

We conducted a cross-sectional, correlational analysis of the West Virginia Birth Score Program database examining the relationship between maternal self-rated health (SRH) and infant low birth weight (LBW), preterm birth, and small for gestational age (SGA). We found that, after controlling for covariates, mothers reporting fair/poor SRH were more likely to deliver an LBW infant (OR = 1.35, 95% CI = 1.14, 1.59), to deliver preterm (OR = 1.38, 95% CI = 1.17, 1.63), and to deliver an SGA infant (OR = 1.20, 95% CI = 1.05, 1.38). Given these results, further research is warranted to analyze maternal SRH during pregnancy, thereby exploring its potential predictive ability in regards to adverse birth outcomes.

Anesthesia staffing and anesthetic complications during cesarean delivery: a retrospective analysis.

BACKGROUND: Obstetrical anesthesia services may be provided by Certified Registered Nurse Anesthetists (CRNAs), anesthesiologists, or a combination of the two providers. Research is needed to assist hospitals and anesthesia groups in making cost-effective staffing choices. OBJECTIVES: To identify differences in the rates of anesthetic complications in hospitals whose obstetrical anesthesia is provided solely by CRNAs compared to hospitals with only anesthesiologists. METHODS: Washington State hospital discharge data were obtained from 1993 to 2004 for all cesarean sections, and were merged with a survey of hospital obstetrical anesthesia staffing. Anesthetic complications were identified via International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Resulting rates were risk-adjusted using regression analysis. RESULTS: Hospitals with CRNA-only staffing had a lower rate of anesthetic complications than those with anesthesiologist staffing (0.58% vs. 0.76%, p=.0006). However, after regression analysis, this difference was not significant (odds ratio for CRNA vs. anesthesiologist complications: 1.046 to 1, 95% confidence interval 0.649-1.658, p=.85). DISCUSSION: There is no difference in rates of complications between the two types of staffing models. As a result, hospitals and anesthesiology groups may safely examine other variables, such as provider availability and costs, when staffing for obstetrical anesthesia. Further study is needed to validate the use of ICD-9-CM codes for anesthesia complications as an indicator of quality.

Social capital and risk for chronic illnesses.

OBJECTIVES: This study used an ecological model of social capital to examine the relationship between social capital and chronic illness. The model hypothesizes that personal social support and collective social capital are related to risk for chronic illnesses. METHODS: Data were taken from the American Changing Lives public use database. Seven hundred and sixty-nine persons meeting inclusion criteria were included. Dependent variables were the reported presence of hypertension and diabetes. Logistic regression analysis was used to identify correlates of these chronic illnesses, including demographic variables, and social capital and social support variables measured at both the personal and collective levels. RESULTS: Significant results were usually consistent with model hypotheses; that is, measures of social capital and social support were related to the presence of diabetes and hypertension in expected ways. However, in other cases, the hypothesized relationships were not statistically significant, due to limitations in the model or data. DISCUSSION: Social support and social capital both serve as protective factors against chronic illness. Development of social capital may proceed from the personal family and social environment to collective measures of trust and engagement, and this suggests that family relationships are the foundation on which to base efforts to build social capital.

Social capital and trust in providers.

Trust in providers has been in decline in recent decades. This study attempts to identify sources of trust in characteristics of health care systems and the wider community. The design is cross-sectional. Data are from (1) the 1996 Household Survey of the Community Tracking Study, drawn from 24 Metropolitan Statistical Areas; (2) a 1996 multi-city broadcast media marketing database including key social capital indicators; (3) Interstudy; (4) the American Hospital Association; and (5) the American Medical Association. Independent variables include individual socio-demographic variables, HMO enrollment, community-level health sector variables, and social capital. The dependent variable is self-reported trust in physicians. Data are merged from the various sources and analyzed using SUDAAN. Subjects include adults in the Household Survey who responded to the items on trust in physicians (N=17,653). Trust in physicians is independently predicted by community social capital (p<0.001). Trust is also negatively related to HMO enrollment and to many individual characteristics. The effect of HMOs is not uniform across all communities. Social capital plays a role in how health care is perceived by citizens, and how health care is delivered by providers. Efforts to build trust and collaboration in a community may improve trust in physicians, health care quality, access, and preserve local health care control.

Predicting rehospitalization and outpatient services from administration and clinical databases.

The study tests whether psychiatric services utilization may be predicted from administrative databases without clinical variables equally as well as from databases with clinical variables. Persons with a psychiatric hospitalization at an urban medical center were followed for 1 year postdischarge (N = 1384.) Dependent variables included statewide rehospitalization and the number of hours of outpatient services received. Three linear and logistic regression models were developed and cross-validated: a basic model with limited administrative independent variables, an intermediate model with diagnostic and limited clinical indicators, and a full model containing additional clinical predictors. For rehospitalization, the clinical cross-validated model accounted for twice the variance accounted by the basic model (adjusted R2 = .13 and .06, respectively). For outpatient hours, the basic cross-validated model performed as well as the clinical model (adjusted R2 = .36 and .34, respectively). Clinical indicators such as assessment of functioning and co-occurring substance use disorder should be considered for inclusion in predicting rehospitalization.

Service use among patients with schizophrenia in psychoeducational multiple-family group treatment.

OBJECTIVES: Outpatient and inpatient mental health service outcomes for outpatients with schizophrenia or schizoaffective disorder who received psychoeducational multiple-family group treatment were compared with outcomes for similar patients who received standard care. METHODS: A total of 106 outpatients with schizophrenia or schizoaffective disorder who were receiving services from a large community mental health center were randomly assigned to receive standard care or standard care plus multiple-family group treatment. The two-year multiple-family intervention consisted of weekly group sessions designed to educate patients and their family members about the biological basis of mental illness and treatment, to improve illness management and coping skills, and to provide social support. The group sessions were conducted by two clinicians using a standardized protocol. Each multiple-family group included five to eight families and consumers. Service records for the year before and after random assignment to the study groups were examined in an intent-to-treat analysis. RESULTS: During the year after random assignment to study groups, multiple-family group treatment was associated with a lower rate of psychiatric hospitalization than standard care. It was only marginally associated with lower use of crisis services, and it was not associated with the amount of outpatient service time. CONCLUSIONS: The findings suggest that implementation of multiple-family group treatment in a capitated community mental health setting improves hospitalization outcomes without increasing the overall volume of outpatient mental health services.

Access to health care and community social capital.

OBJECTIVE: To test the hypothesis that variation in reported access to health care is positively related to the level of social capital present in a community. DATA SOURCES: The 1996 Household Survey of the Community Tracking Study, drawn from 22 metropolitan statistical areas across the United States (n = 19,672). Additional data for the 22 communities are from a 1996 multicity broadcast media marketing database, including key social capital indicators, the 1997 National Profile of Local Health Departments survey, and Interstudy, American Hospital Association, and American Medical Association sources. STUDY DESIGN: The design is cross-sectional. Self-reported access to care problems is the dependent variable. Independent variables include individual sociodemographic variables, community-level health sector variables, and social capital variables. DATA COLLECTION/EXTRACTION METHODS: Data are merged from the various sources and weighted to be population representative and are analyzed using hierarchical categorical modeling. PRINCIPAL FINDINGS: Persons who live in metropolitan statistical areas featuring higher levels of social capital report fewer problems accessing health care. A higher HMO penetration rate in a metropolitan statistical area was also associated with fewer access problems. Other health sector variables were not related to health care access. CONCLUSIONS: The results observed for 22 major U.S. cities are consistent with the hypothesis that community social capital enables better access to care, perhaps through improving community accountability mechanisms.