Multimorbidity frameworks impact prevalence and relationships with patient-important outcomes

\u3cp\u3eOBJECTIVES: To explore how different frameworks and categories of chronic conditions impact multimorbidity (defined as two or more chronic conditions) prevalence estimates and associations with patient-important functional outcomes. DESIGN: Baseline data from a population-based cohort study. SETTING: National sample of Canadians. PARTICIPANTS: A total of 51 338 community-living adults, aged 45 to 85 years. MAIN OUTCOME MEASURES: Chronic conditions from three commonly recognized frameworks were categorized as: (1) diseases, (2) risk factors, or (3) symptoms. Estimates of multimorbidity prevalence were compared among frameworks by age and sex. Separate weighted logistic regression models were used to explore the impact of the different frameworks and categories of chronic conditions on odds ratios (ORs) for multimorbidity for four patient-important functional outcomes: disability, social participation restriction, and self-rated physical and mental health. RESULTS: One framework included diseases and risk factors, and two frameworks included diseases, risk factors, and symptoms. The prevalence of multimorbidity differed among the frameworks, ranging from 33.5% to 60.6% having two or more chronic conditions. Including risk factors in frameworks increased prevalence estimates, while including symptoms increased prevalence estimates and associations with most patient-important outcomes. The two frameworks that included symptoms had the largest ORs for associations with disability, social participation restriction, and self-rated physical health but not self-rated mental health. Similar results were found when we compared ORs for patient-important outcome for multimorbidity based on three subframeworks: one including diseases only, one including diseases and risk factors, and one including diseases, risk factors, and symptoms. CONCLUSIONS: Including risk factors appeared to increase only the prevalence of multimorbidity without significantly altering relationships to outcomes. The inclusion of symptoms increased prevalence and associations with patient-important outcomes. These findings underscore the importance of considering not only the number, but also the category, of conditions included in multimorbidity frameworks, as simply counting the number of diagnoses may reduce sensitivity to outcomes that are important to individuals. J Am Geriatr Soc 67:1632–1640, 2019.\u3c/p\u3

Entrepreneurship ecosystems and women entrepreneurs: A social capital and network approach

This study investigates the effects of venture typology, race, ethnicity, and past venture experience on the social capital distribution of women entrepreneurs in entrepreneurial ecosystems. Social network data from two municipal ecosystems in Florida, USA (Gainesville and Jacksonville), suggest that network connectivity and the distribution of social capital are significantly different for men and women entrepreneurs. This difference is contingent on the venture type.Male entrepreneurs show higher comparative scores of bridging social capital in aggressive- and managed-growth venture networks, while women entrepreneurs surpass their male counterparts’ bridging capital scores in lifestyle and survival venture networks. Lastly, experienced women entrepreneurs that self-identified as white showed a higher degree of network connectivity and bridging social capital in the entrepreneurial ecosystem than less experienced non-white female entrepreneurs. Implications for entrepreneurship practice and new research paths are discussed.info:eu-repo/semantics/publishedVersio