IMPORTANCE Social isolation and loneliness are increasing public health concerns and have been associated with increased risk of cardiovascular disease (CVD) among older adults. OBJECTIVE To examine the associations of social isolation and loneliness with incident CVD in a large cohort of postmenopausal women and whether social support moderated these associations. DESIGN, SETTING, AND PARTICIPANTSThis prospective cohort study, conducted from March 2011 through March 2019, included community-living US women aged 65 to 99 years from the Women's Health Initiative Extension Study II who had no history of myocardial infarction, stroke, or coronary heart disease.EXPOSURES Social isolation and loneliness were ascertained using validated questionnaires. MAIN OUTCOMES AND MEASURESThe main outcome was major CVD, which was physician adjudicated using medical records and included coronary heart disease, stroke, and death from CVD.Continuous scores of social isolation and loneliness were analyzed. Hazard ratios (HRs) and 95% CIs for CVD were calculated for women with high social isolation and loneliness scores (midpoint of the upper half of the distribution) vs those with low scores (midpoint of the lower half of the distribution) using multivariable Cox proportional hazards regression models adjusting for age, race and ethnicity, educational level, and depression and then adding relevant health behavior and health status variables. Questionnaire-assessed social support was tested as a potential effect modifier. RESULTS Among 57 825 women (mean [SD] age, 79.0 [6.1] years; 89.1% White), 1599 major CVD events occurred over 186 762 person-years. The HR for the association of high vs low social isolation scores with CVD was 1.18 (95% CI, 1.13-1.23), and the HR for the association of high vs low loneliness scores with CVD was 1.14 (95% CI, 1.10-1.18). The HRs after additional adjustment for health behaviors and health status were 1.08 (95% CI, 1.03-1.12; 8.0% higher risk) for social isolation and 1.05 (95% CI, 1.01-1.09; 5.0% higher risk) for loneliness. Women with both high social isolation and high loneliness scores had a 13.0% to 27.0% higher risk of incident CVD than did women with low social isolation and low loneliness scores. Social support was not a significant effect modifier of the associations (social isolation × social support: r, -0.18; P = .86; loneliness × social support: r, 0.78; P = .48). CONCLUSIONS AND RELEVANCEIn this cohort study, social isolation and loneliness were independently associated with modestly higher risk of CVD among postmenopausal women in the US, and women with both social isolation and loneliness had greater CVD risk than did those with either exposure alone. The findings suggest that these prevalent psychosocial processes merit increased attention for prevention of CVD in older women, particularly in the era of COVID-19.

Recently, it has been shown how to estimate model-adjusted risks, risk differences, and risk ratios from complex survey data based on risk averaging and SUDAAN (Research Triangle Institute, Research Triangle Park, North Carolina). The authors present an alternative approach based on marginal structural models (MSMs) and SAS (SAS Institute, Inc., Cary, North Carolina). The authors estimate the parameters of the MSM using inverse weights that are the product of 2 terms. The first term is a survey weight that adjusts the sample to represent the unstandardized population. The second term is an inverse-probability-of-exposure weight that standardizes the population in order to adjust for confounding; it must be estimated using the survey weights. The authors show how to use the MSM parameter estimates and contrasts to test and estimate effect-measure modification; SAS code is provided. They also explain how to program the previous risk-averaging approach in SAS. The 2 methods are applied and compared using data from the 2007 Florida Behavioral Risk Factor Surveillance System Survey to assess effect modification by age of the difference in risk of cost barriers to health care between persons with disability and persons without disability.

Background Studies show that active smoking may be associated with cognitive decline. However, the consequence of secondhand smoke on cognitive and physical performance remains unclear. The purpose of this study was to assess the association of secondhand smoke with cognitive performance and physical function using a population-based sample. Methods Data of 2,542 non-smoking participants from the 1999–2002 National Health and Nutrition Examination Survey were analyzed. Secondhand smoke exposure level was estimated using blood cotinine concentrations. Cognitive performance was assessed with the Digit Symbol Substitution Test and self-reported confusion/memory problems. Physical performance was analyzed using visual gait speed (m/s) and self-reported physical function. Multivariate linear and logistic regression models were used to assess the association. Results In never smokers, cognitive performance score decreased by 2.03 points (95% confidence interval (CI): −3.00, −1.05) per one unit increase in log-transformed blood cotinine level. After adjusting for potential confounders, including diabetes, hypertension, body mass index, alcohol, and blood lead level, change in cognitive performance score was still statistically significant (−1.17 95% CI: −2.32, −0.02). Similar trends were observed in former smokers. Gait speed decreased by 0.02 m/s for one unit increase in log-transformed blood cotinine level. This was evident in both never and former smokers. The relationship remained significant after adjusting for potential confounders in former smokers. Conclusions Our study suggests that secondhand smoke may contribute to cognitive decline in never and former smokers. Considering the cross-sectional design and the limitations of this study, the relationship warrants further assessment.

BackgroundTo develop a screening tool to enhance elder abuse and neglect detection and reporting rates among emergency medical technicians (EMTs). Our primary aim was to identify the most salient indicators of elder abuse and neglect for potential inclusion on a screening tool. We also sought to identify practical elements of the tool that would optimize EMT uptake and use in the field, such as format, length and number of items, and types of response options available.MethodsQualitative data were collected from 23 EMTs and Adult Protective Services (APS) caseworkers that participated in one of five semi-structured focus groups. Focus group data were iteratively coded by two coders using inductive thematic identification and data reduction. Findings were subject to interpretation by the research team.ResultsEMTs and APS caseworks identified eight domains of items that might be included on a screening tool: (1) exterior home condition; (2) interior living conditions; (3) social support; (4) medical history; (5) caregiving quality; (6) physical condition of the older adult; (7) older adult’s behavior; and, (8) EMTs instincts. The screening tool should be based on observable cues in the physical or social environment, be very brief, easily integrated into electronic charting systems, and provide a decision rule for reporting guidance to optimize utility for EMTs in the field.ConclusionsWe described characteristics of a screening tool for EMTs to enhance detection and reporting of elder abuse and neglect to APS. Future research should narrow identified items and evaluate how these domains positively predict confirmed cases of elder abuse and neglect.Electronic supplementary materialThe online version of this article (doi:10.1186/s12873-016-0084-3) contains supplementary material, which is available to authorized users.

Background: Elder abuse and neglect are highly under-reported in the United States. This may be partially attributed to low incidence of reporting among emergency medical technicians' (EMTs), despite state-mandated reporting of suspected elder abuse. Innovative solutions are needed to address under-reporting. The objective was to describe EMTs' experience detecting and reporting elder abuse. Methods: Qualitative data were collected from 11 EMTs and 12 Adult Protective Services (APS) caseworkers that participated in one of five semi-structured focus groups. Focus group data were iteratively coded by two coders.Results: Findings suggest a number of barriers prevent EMTs from reporting elder abuse to APS. Participants suggested that limited training on elder abuse detection or reporting has been provided to them. EMTs suggested that training, creation of an automated reporting system or brief screening tool could be used to enhance EMT's ability to detect and communicate suspected cases of elder abuse to APS.