XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

Statistical Analysis with Missing Data

Individualism and collectivism

Subjective well-being (SWB) is evaluation of life in terms of satisfaction and balance between positive and negative affect; psychological well-being (PWB) entails perception of engagement with existential challenges of life. The authors hypothesized that these research streams are conceptually related but empirically distinct and that combinations of them relate differentially to sociodemographics and personality. Data are from a national sample of 3,032 Americans aged 25–74. Factor analyses confirmed the related-but-distinct status of SWB and PWB. The probability of optimal well-being (high SWB and PWB) increased as age, education, extraversion, and conscientiousness increased and as neuroticism decreased. Compared with adults with higher SWB than PWB, adults with higher PWB than SWB were younger, had more education, and showed more openness to experience. Research on well-being has flourished in recent decades (Diener, Suh, Lucas, & Smith, 1999; Kahneman, Diener, & Schwarz, 1999), with increasing recognition of the different streams of inquiry guiding this broad domain. Ryan and Deci’s (2001) integrative review organized the field of well-being into two broad traditions: one dealing with happiness (hedonic well-being), and one dealing with human potential (eudaimonic well-being; Ryan & Deci, 2001; see also Waterman, 1993). In the present study, we draw and extend these distinctions, which we refer to as traditions of research on subjective well-being (SWB) and psychological well-being (PWB). We use these terms to underscore the fact that studies of SWB have repeatedly included not only affective indicators of happiness (hedonic well-being) but also cognitive assessments of life satisfaction. In addition, some aspects of PWB (e.g., personal growth, purpose in life) but not others (e.g., positive relations with others, self-acceptance) reflect the self-fulfillment meanings of eudaimonic well-being. As described below, SWB and PWB are also the overarching phrases most frequently used in studies that constitute these traditions, both of which are fundamentally concerned with subjective accounts of well-being. Our specific empirical aims are to examine whether indicators of SWB and PWB constitute taxonomically distinct reflections of well-being in a national sample of U.S. adults. Although both approaches assess well-being, they address different features of what it means to be well: SWB involves more global evaluations of affect and life quality, whereas PWB examines perceived thriving vis-a `-vis the existential challenges of life (e.g., pursuing meaningful goals, growing and developing as a person, establishing quality ties to others). We further test the hypothesis that these distinct varieties of well-being are contoured by the broad categories of sociodemographic and personality factors. Specifically, we investigate the role of location in the life course (i.e., age) and position in the socioeconomic hierarchy (e.g., educational status) as well as personality traits in accounting for different profiles of well-being. To put the inquiry in historical context, we provide a brief summary of each tradition.

/pdf/optimizing-well-being-the-empirical-encounter-of-two-q6t0p4f74x.pdf

Optimizing well-being: the empirical encounter of two traditions.

Features of neighborhoods or residential environments may affect health and contribute to social and race/ethnic inequalities in health. The study of neighborhood health effects has grown exponentially over the past 15 years. This chapter summarizes key work in this area with a particular focus on chronic disease outcomes (specifically obesity and related risk factors) and mental health (specifically depression and depressive symptoms). Empirical work is classified into two main eras: studies that use census proxies and studies that directly measure neighborhood attributes using a variety of approaches. Key conceptual and methodological challenges in studying neighborhood health effects are reviewed. Existing gaps in knowledge and promising new directions in the field are highlighted.

/pdf/neighborhoods-and-health-4576uxzkt2.pdf

Neighborhoods and health.

The integration of temporal life course perspectives and current social context perspectives is considered as a framework for the understanding of mental health differences in early adulthood, a formative stage in the development of long-term mental health differences. Using data from the National Survey of Children and a cross-nested random effects model to simultaneously assess the effects of current and past neighborhood, the authors find a lagged effect of childhood neighborhood socioeco-nomic disadvantage on early adult mental health, while accounting for initial mental health status. This lagged effect also explains the apparent (bivariate) effect of current neighborhood. Four hypotheses are assessed to explain the lagged effect of neighborhood: contextual continuity, mental health continuity, life course stress accumulation, and ambient chronic stress in the neighborhood. Support is found for a cumulative mediating effect of both life course stress and ambient neighborhood stress as children grow up; together, these variables entirely explain the lagged effect of early neighborhood. Findings suggest the need for a more temporal life course approach to the specification of social context effects in general, focusing on the history of social contexts that individuals live in and move through. Temporal-contextual perspectives also encourage a focus on theoretical models that can differentially locate formative contextual influences at different stages in the life course

Space Meets Time: Integrating Temporal and Contextual Influences on Mental Health in Early Adulthood

Objective: The use of multilevel modelling with data from population-based surveys is often limited by the small number of cases per level-2 unit, prompting many researchers to use single-level techniques such as ordinary least squares regression. Design: Monte Carlo simulations are used to investigate the effects of data sparseness on the validity of parameter estimates in two-level versus single-level models. Setting: Both linear and non-linear hierarchical models are simulated in order to examine potential differences in the effects of small group size across continuous and discrete outcomes. Results are then compared with those obtained using disaggregated techniques (ordinary least squares and logistic regression). Main results: At the extremes of data sparseness (two observations per group), the group level variance components are overestimated in the two-level models. But with an average of only five observations per group, valid and reliable estimates of all parameters can be obtained when using a two-level model with either a continuous or a discrete outcome. In contrast, researchers run the risk of Type I error (standard errors biased downwards) when using single-level models even when there are as few as two observations per group on average. Bias is magnified when modelling discrete outcomes. Conclusions: Multilevel models can be reliably estimated with an average of only five observations per group. Disaggregated techniques carry an increased risk of Type I error, even in situations where there is only limited clustering in the data.

https://jech.bmj.com/content/jech/62/8/752.full.pdf

When can group level clustering be ignored? Multilevel models versus single-level models with sparse data

Using Google Earth to Conduct a Neighborhood Audit: Reliability of a Virtual Audit Instrument

Research on the effects of the built environment in the pathway from impairment to disability has been largely absent. Using data from the Chicago Community Adult Health Study (2001-2003), the authors examined the effect of built environment characteristics on mobility disability among adults aged 45 or more years (n = 1,195) according to their level of lower extremity physical impairment. Built environment characteristics were assessed by using systematic social observation to independently rate street and sidewalk quality in the block surrounding each respondent's residence in the city of Chicago (Illinois). Using multinomial logistic regression, the authors found that street conditions had no effect on outdoor mobility among adults with only mild or no physical impairment. However, among adults with more severe impairment in neuromuscular and movement-related functions, the difference in the odd ratios for reporting severe mobility disability was over four times greater when at least one street was in fair or poor condition (characterized by cracks, potholes, or broken curbs). When all streets were in good condition, the odds of reporting mobility disability were attenuated in those with lower extremity impairment. If street quality could be improved, even somewhat, for those adults at greatest risk for disability in outdoor mobility, the disablement process could be slowed or even reversed.

/pdf/mobility-disability-and-the-urban-built-environment-vkar2ew00z.pdf

Philippa Clarke

Papers

Space Meets Time: Integrating Temporal and Contextual Influences on Mental Health in Early Adulthood

When can group level clustering be ignored? Multilevel models versus single-level models with sparse data

Using Google Earth to Conduct a Neighborhood Audit: Reliability of a Virtual Audit Instrument

Mobility Disability and the Urban Built Environment

Environments for healthy ageing: a critical review.