Citations

Background: We recently developed an index of socioeconomic status (SES) termed HOUSES ( HOU sing-based index of S ocio E conomic S tatus) to overcome the absence of SES measures in common data sources. HOUSES has been associated with various childhood health outcomes to a similar extent as other measures of SES. Whether it is associated with outcomes in adults is unknown. To address this question, we assessed whether HOUSES was associated with mortality after MI. Methods: We conducted a population-based cohort study among all Olmsted County, MN residents with MI who were prospectively identified using predetermined criteria from November 1, 2002 to May 31, 2006. HOUSES was formulated based on a z-score for housing value, actual square footage, and numbers of bedrooms and bathrooms and categorized into quartiles. The 1-year mortality rate post MI was compared among subjects with different SES by HOUSES based on a log-rank test. Results: Among 696 patients with MI; 623 (90%) were successfully geo-coded to address and real property data. Of these 623 subjects, 594 (95%) were white and 263 (42%) female; the mean age was 68±15 years. Spearman correlation coefficient between HOUSES and education level was 0.23 (p<0.001). Mortality rates at 1 year following MI were 20% (95%CI: 13 - 26), 18% (11 - 24), 14% (8 - 19), and 16% (10 - 21) for patients in the first (lowest SES), second, third, and fourth quartiles (highest SES) of the HOUSES index, respectively (p=0.032). This association between HOUSES and mortality after MI was primarily explained by age and comorbid conditions which were associated with HOUSES. Cardioprotective drugs such as aspirin, beta-blocker, and statins were not associated with HOUSES nor accounted for the association between HOUSES and mortality after MI. Conclusions: Despite the lack of a strong correlation with other SES measure (i.e. no redundancy), HOUSES may be useful for overcoming the paucity of conventional SES measures in commonly used datasets in epidemiological research concerning cardiovascular disease among adults.

P46 While heart failure (HF), an emerging epidemic, complicates myocardial infarction (MI), little is known on the predictors of HF post-MI, in particular the impact of reperfusion therapy. This population-based study was undertaken to examine the association between clinical characteristics and post-MI HF between 1979 and 1994. Hospitalized incident MIs were validated using enzymes, chest pain, and Minnesota coding of the ECG. Framingham criteria were used to ascertain both in- and outpatient HF. Proportional hazard regression was used to identify predictors of CHF. In the study period, 1657 patients (pts.) (mean age 67.2 ± 13.9 years, 43% women) had an incident MI. History of diabetes, hypertension and prior HF was found in 19%, 54% and 11% of pts respectively. After 5 years, 43% of pts had experienced HF. Factors independently associated with HF were (see table). There was a 2% decline per year in occurrence of HF. Adding reperfusion therapy in the model attenuated the association between year and HF (adjusted RR for reperfusion 0.67, 95% CI 0.53, 0.84, p=0.006; adjusted for year 0.99; 95% CI 0.97, 1.01, p=0.37). Thus, while remaining frequent post-MI CHF has declined over time. Reperfusion therapy accounted for most of the effect of year. Table 1.

Purpose The purpose of this pilot feasibility project was to examine the potential effectiveness of a digital storytelling intervention designed through a community-based participatory research (CBPR) approach for immigrants and refugees with type 2 diabetes mellitus (T2DM). Methods The intervention was a 12-minute culturally and linguistically tailored video consisting of an introduction, 4 stories, and a concluding educational message. A structured interview was used to assess the intervention for acceptability, interest level, and usefulness among 25 participants with T2DM (15 Latino, 10 Somali) across 5 primary care clinical sites. After watching the video, participants rated their confidence and motivation about managing T2DM as a result of the intervention. Baseline A1C and follow-up values (up to 6 months) were abstracted from medical records. Results All participants reported that the intervention got their attention, was interesting, and was useful; 96% reported that they were more confident about managing their T2DM than before they watched the video, and 92% reported that the video motivated them to change a specific behavior related to T2DM self-management. The mean baseline A1C level for the intervention participants was 9.3% (78 mmol/mol). The change from baseline to first follow-up A1C level was −0.8% (−10 mmol/mol) ( P < .05). Conclusions Implementation of a digital storytelling intervention for T2DM among immigrant populations in primary care settings is feasible and resulted in self-rated improvement in psychosocial constructs that are associated with healthy T2DM self-management behaviors, and there was some evidence of improvement in glycemic control. A large-scale efficacy trial of the intervention is warranted.

The prevalence of childhood obesity has increased over the past 3 decades. This study was designed to understand how childhood body mass index (BMI) influences later risk of obesity. We calculated BMIs for children residing in Olmsted County, Minnesota, between January 1, 2005 and December 31, 2012 using medical records data. We defined homogenous BMI trajectory clusters using a nonparametric hill-climbing algorithm. Overall, 16,538 (47%) children had >3 weight assessments at least 1 year apart and were included in the analyses. Within the 8-year follow-up period, children who were younger than 2 years and overweight had a 3- fold increase of obesity (adjusted hazard ratio [HR] = 3.24; 95% confidence interval [CI] = 2.69-3.89) and those aged 5 years and overweight had a 10-fold increased risk of obesity (adjusted HR = 9.97, 95% CI = 8.55-11.62). Three distinct BMI trajectories could be distinguished prior to 5 years of age. The risk of developing obesity in those who are overweight increased dramatically with increasing age. Interventions to prevent obesity need to occur prior to school age to prevent children from entering unhealthy BMI trajectories.

Objectives Socioeconomic status (SES) is a well-established risk factor for many health outcomes. Recently, we developed an SES measure based on 4 housing-related characteristics (termed HOUSES) and demonstrated its ability to assess health disparities. In this study, we aimed to evaluate whether fewer housing-related characteristics could be used to provide a similar representation of SES. Study setting and participants We performed a cross-sectional study using parents/guardians of children aged 1–17 years from 2 US Midwestern counties (n=728 in Olmsted County, Minnesota, and n=701 in Jackson County, Missouri). Primary and secondary outcome measures For each participant, housing-related characteristics used in the formulation of HOUSES (assessed housing value, square footage, number of bedrooms and number of bathrooms) were obtained from the local government assessor's offices, and additional SES measures and health outcomes with known associations to SES (obesity, low birth weight and smoking exposure) were collected from a telephone survey. Housing characteristics with the greatest contribution for predicting the health outcomes were added to formulate a modified HOUSES index. Results Among the 4 housing characteristics used in the original HOUSES, the strongest contributions for predicting health outcomes were observed from assessed housing value and square footage (combined contribution ranged between 89% and 96%). Based on this observation, these 2 were used to calculate a modified HOUSES index. Correlation between modified HOUSES and other SES measures was comparable to the original HOUSES for both locations. Consistent with the original HOUSES formula, the strongest association with modified HOUSES was observed with smoking exposure (OR=0.24 with 95% CI 0.11 to 0.49 for comparing participants in highest HOUSES vs lowest group; overall p<0.001). Conclusions The modified HOUSES requires only 2 readily available housing characteristics thereby improving the feasibility of using this index as a proxy for SES in multiple communities, especially in the US Midwestern region.

Objective The goal of this study was to identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an ageing population and to determine social and behavioural factors associated with frailty trajectories. Design Population-based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota residents aged 60–89 in 2005. Primary outcome measure Changes in frailty over an 8-year period from 2005 to 2012, measured by constructing a yearly frailty index. Frailty trajectories by decade of age were determined using k-means cluster modelling for longitudinal data. Results After adjustment for age and sex, all social and behavioural factors (education, marital status, living arrangements, smoking status and alcohol use) were significantly associated with frailty trajectories in those aged 60–69 and 70–79 years. After further adjustment for baseline frailty, the likelihood of being in the high frailty trajectory was greatest among those reporting concerns from relatives/friends about alcohol consumption (OR (95% CI) 2.26 (1.19 to 4.29)) and those with less than a high school education (OR (95% CI) 1.98 (1.32 to 2.96)) in the 60–69 year olds. In the 70–79 year olds, the largest associations were observed among those with concerns from oneself about alcohol consumption (OR (95% CI) 1.92 (1.23 to 3.00)), those with less than a high school education (OR (95% CI) 1.57 (1.12 to 2.22)), and those living with family (vs spouse; OR (95% CI) 1.76 (1.05 to 2.94)). No factors remained associated with frailty trajectories in the 80–89 year olds after adjustment for baseline frailty. Conclusions Social and behavioural factors are associated with frailty, with stronger associations observed in younger ages. Recognition of social and behavioural factors associated with increasing frailty may inform interventions for individuals at risk of worsening frailty, specifically when targeted at younger individuals.

Objectives To identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an aging population and to estimate associations between frailty trajectories and emergency department visits, hospitalizations, and all‐cause mortality. Design Population‐based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota residents aged 60–89 in 2005. Measurements Longitudinal changes in frailty between 2005 and 2012 were measured by constructing a yearly Rockwood frailty index incorporating body mass index, 17 comorbidities, and 14 activities of daily living. The frailty index measures variation in health status as the proportion of deficits present of the 32 considered (range 0–1). Results Of the 16,443 Olmsted County residents aged 60–89 in 2005, 12,270 (74.6%) had at least 3 years of frailty index measures and were retained for analysis. The median baseline frailty index increased with age (0.11 for 60–69, 0.14 for 70–79, 0.19 for 80–89). Three distinct frailty trajectories were identified in individuals aged 60–69 at baseline and two trajectories in those aged 70–79 and 80–89. Within each decade of age, increasing frailty trajectories were associated with greater risks of emergency department visits, hospitalization, and all‐cause mortality, even after adjustment for baseline frailty index. Conclusion The number of frailty trajectories differed according to age. Within each age group, those in the highest frailty trajectory had greater healthcare use and worse survival. Frailty trajectories may offer a way to target aging individuals at high risk of hospitalization or death for therapeutic or preventive interventions.

Background: To assess whether the individual housing-based socioeconomic status (SES) measure termed HOUSES was associated with post-myocardial infarction (MI) mortality. Methods: The study was designed as a population-based cohort study, which compared post-MI mortality among Olmsted County, Minnesota, USA, residents with different SES as measured by HOUSES using Cox proportional hazards models. Subjects’ addresses at index date of MI were geocoded to real property data to formulate HOUSES (a z-score for housing value, square footage, and numbers of bedrooms and bathrooms). Educational levels were used as a comparison for the HOUSES index. Results: 637 of the 696 eligible patients with MI (92%) were successfully geocoded to real property data. Post-MI survival rates were 60% (50–72), 78% (71–85), 72% (60–87), and 87% (81–93) at 2 years for patients in the first (the lowest SES), second, third, and fourth quartiles of HOUSES, respectively (p < 0.001). HOUSES was associated with post-MI all-cause mortality, controlling for all variables except age and comorbidity (p = 0.036) but was not significant after adjusting for age and comorbidity (p = 0.24). Conclusions: Although HOUSES is associated with post-MI mortality, the differential mortality rates by HOUSES were primarily accounted for by age and comorbid conditions. HOUSES may be useful for health disparities research concerning cardiovascular outcomes, especially in overcoming the paucity of conventional SES measures in commonly used datasets.