When is diabetes distress clinically meaningful?: establishing cut points for the Diabetes Distress Scale.

ObjectiveTo identify the pattern of relationships between the 17-item Diabetes Distress Scale (DDS17) and diabetes variables to establish scale cut points for high distress among patients with type 2 diabetes.Research design and methodsRecruited were 506 study 1 and 392 study 2 adults with type 2 diabetes from community medical groups. Multiple regression equations associated the DDS17, a 17-item scale that yields a mean-item score, with HbA(1c), diabetes self-efficacy, diet, and physical activity. Associations also were undertaken for the two-item DDS (DDS2) screener. Analyses included control variables, linear, and quadratic (curvilinear) DDS terms.ResultsSignificant quadratic effects occurred between the DDS17 and each diabetes variable, with increases in distress associated with poorer outcomes: study 1 HbA(1c) (P < 0.02), self-efficacy (P < 0.001), diet (P < 0.001), physical activity (P < 0.04); study 2 HbA(1c) (P < 0.03), self-efficacy (P < 0.004), diet (P < 0.04), physical activity (P = NS). Substantive curvilinear associations with all four variables in both studies began at unexpectedly low levels of DDS17: the slope increased linearly between scores 1 and 2, was more muted between 2 and 3, and reached a maximum between 3 and 4. This suggested three patient subgroups: little or no distress, <2.0; moderate distress, 2.0-2.9; high distress, ≥3.0. Parallel findings occurred for the DDS2.ConclusionsIn two samples of type 2 diabetic patients we found a consistent pattern of curvilinear relationships between the DDS and HbA(1c), diabetes self-efficacy, diet, and physical activity. The shape of these relationships suggests cut points for three patient groups: little or no, moderate, and high distress

Motivation and attitudes toward changing health (MATCH): A new patient-reported measure to inform clinical conversations.

ObjectiveTo identify and assess patient motivation to initiate or maintain behavior changes.MethodsAttitudinal statements were developed from structured patient interviews and translated into 18 survey items. Items were analyzed with exploratory factor analysis (EFA).ResultsAn EFA with 340 type 2 diabetes patients identified three areas of patient attitudes toward changing health behaviors: (1) willingness to make changes (3 items; α = 0.69), (2) perceived ability to make or maintain changes (3 items; α = 0.74), and (3) and feeling changes are worthwhile (3 items; α = 0.61). Greater perceived ability and feelings of worthwhileness were associated with positive psychosocial and behavioral management indicators. All three areas were associated with confidence and attitudes toward making a specific behavioral change (e.g., improve diet).ConclusionsMATCH is an internally consistent and valid 9-item scale that provides a profile of factors influencing motivation that can be used in clinical and research settings

Senior Recital: Danielle Fisher, Horn; Patricia Foltz, Piano; October 18, 2009

Kemp Recital HallOctober 18, 2009Sunday Evening7:30 p.m

Adaptability of Irrigation to a Changing Monsoon in India: How far can we go?

Agriculture and the monsoon are inextricably linked in India. A large part of the steady rise in agricultural production since the onset of the Green Revolution in the 1960’s has been attributed to irrigation. Irrigation is used to supplement and buffer crops against precipitation shocks, but water availability for such use is itself sensitive to the erratic, seasonal and spatially heterogeneous nature of the monsoon. Most attention in the literature is given to crop yields (Guiteras, 2009; Fishman, 2012; Auffhammer et al, 2011) and their ability to withstand precipitation shocks, in the presence of irrigation (Fishman, 2012). However, there remains limited evidence about how natural weather variability and realized irrigation outcomes are related. We provide new evidence on the relationship between monsoon changes, irrigation variability and water availability by linking a process based hydrology model with an econometric model for one of the world’s most water stressed countries. India uses more groundwater for irrigation than any other country, and there is substantial evidence that this has led to depletion of groundwater aquifers. First, we build an econometric model of historical irrigation decisions using detailed crop-wise agriculture and weather data spanning 35 years from 1970-2004 for 311 districts across 19 major agricultural states in India. The source of agricultural data comes from the Village Dynamics in South Asia database at the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT). Weather data is sourced from the only long term continental scale daily observationally gridded precipitation and temperature dataset called APHRODITE (Asian Precipitation- Highly Resolved Observational Data Integration Towards Evaluation of the Water Resources), that captures the spatial extent of the monsoon across the Himalayas, South and South-East Asia, and the Middle East in great detail. We use panel data approaches to control for unobserved and omitted variables that can confound the true impacts of weather variability on irrigation. Exploiting the exogenous inter-annual variability in the monsoon, our multivariate regression models reveal that for crops grown in the wet season, irrigation is sensitive to distribution and total monsoon rainfall but not to ground or surface water availability. For crops grown in the dry season, total monsoon rainfall matters most, and its effect is sensitive to groundwater availability but differentially so for shallow dug wells and deep tube wells. The historical estimates from the econometric model are used to calculate future irrigated areas using three different bias-corrected climate model projections of monsoon climate for the years 2010 – 2050 under the strongest warming scenario ( business as usual scenario) RCP-8.5 from the CMIP5 (Coupled Model Intercomparison Project) models. These projections are then used as input to a physical hydrology model, such as the Water Balance Model, that tracks water use and exchange between the ground, atmosphere, runoff and stream networks. This enables us to quantify supply of water required to meet irrigation needs from sustainable sources such as rechargeable shallow groundwater, rivers and reservoirs, as well as unsustainable sources such as non- rechargeable groundwater. Preliminary results show that the significant variation in monsoon projections lead to very different results. Crops grown in the dry season show particularly divergent trends between model projections, leading to very different groundwater resource requirements. By combining the strengths of the economic and hydrology components, this work highlights potential sustainable or unsustainable water use trajectories that different regions within India will face

Self-management support for chronic disease in primary care: frequency of patient self-management problems and patient reported priorities, and alignment with ultimate behavior goal selection.

BackgroundTo enable delivery of high quality patient-centered care, as well as to allow primary care health systems to allocate appropriate resources that align with patients' identified self-management problems (SM-Problems) and priorities (SM-Priorities), a practical, systematic method for assessing self-management needs and priorities is needed. In the current report, we present patient reported data generated from Connection to Health (CTH), to identify the frequency of patients' reported SM-Problems and SM-Priorities; and examine the degree of alignment between patient SM-Priorities and the ultimate Patient-Healthcare team member selected Behavioral Goal.MethodsCTH, an electronic self-management support system, was embedded into the flow of existing primary care visits in 25 primary care clinics and was used to assess patient-reported SM-Problems across 12 areas, patient identified SM-Priorities, and guide the selection of a Patient-Healthcare team member selected Behavioral Goal. SM-Problems included: BMI, diet (fruits and vegetables, salt, fat, sugar sweetened beverages), physical activity, missed medications, tobacco and alcohol use, health-related distress, general life stress, and depression symptoms. Descriptive analyses documented SM-Problems and SM-Priorities, and alignment between SM-Priorities and Goal Selection, followed by mixed models adjusting for clinic.Results446 participants with ≥ one chronic diseases (mean age 55.4 ± 12.6; 58.5% female) participated. On average, participants reported experiencing challenges in 7 out of the 12 SM-Problems areas; with the most frequent problems including: BMI, aspects of diet, and physical activity. Patient SM-Priorities were variable across the self-management areas. Patient- Healthcare team member Goal selection aligned well with patient SM-Priorities when patients prioritized weight loss or physical activity, but not in other self-management areas.ConclusionParticipants reported experiencing multiple SM-Problems. While patients show great variability in their SM-Priorities, the resulting action plan goals that patients create with their healthcare team member show a lack of diversity, with a disproportionate focus on weight loss and physical activity with missed opportunities for using goal setting to create targeted patient-centered plans focused in other SM-Priority areas. Aggregated results can assist with the identification of high frequency patient SM-Problems and SM-Priority areas, and in turn inform resource allocation to meet patient needs.Trial registrationClinicalTrials.gov ID: NCT01945918

Invisible water, visible impact: How unsustainable groundwater use challenges sustainability of Indian agriculture under climate change

India is one of the world’s largest food producers, making the sustainability of its agricultural system of global significance. Groundwater irrigation underpins India’s agriculture, currently boosting crop production by enough to feed 170 million people. Groundwater overexploitation has led to drastic declines in groundwater levels, threatening to push this vital resource out of reach for millions of small-scale farmers who are the backbone of India’s food security. Historically, losing access to groundwater has decreased agricultural production and increased poverty. We take a multidisciplinary approach to assess climate change challenges facing India’s agricultural system, and to assess the effectiveness of large-scale water infrastructure projects designed to meet these challenges. We find that even in areas that experience climate change induced precipitation increases, expansion of irrigated agriculture will require increasing amounts of unsustainable groundwater. The large proposed national river linking project has limited capacity to alleviate groundwater stress. Thus, without intervention, poverty and food insecurity in rural India is likely to worsen

Redundant Gs-coupled serotonin receptors regulate amyloid-β metabolism in vivo

BACKGROUND: The aggregation of amyloid-β (Aβ) into insoluble plaques is a hallmark pathology of Alzheimer’s disease (AD). Previous work has shown increasing serotonin levels with selective serotonin re-uptake inhibitor (SSRI) compounds reduces Aβ in the brain interstitial fluid (ISF) in a mouse model of AD and in the cerebrospinal fluid of humans. We investigated which serotonin receptor (5-HTR) subtypes and downstream effectors were responsible for this reduction. RESULTS: Agonists of 5-HT(4)R, 5-HT(6)R, and 5-HT(7)R significantly reduced ISF Aβ, but agonists of other receptor subtypes did not. Additionally, inhibition of Protein Kinase A (PKA) blocked the effects of citalopram, an SSRI, on ISF Aβ levels. Serotonin signaling does not appear to change gene expression to reduce Aβ levels in acute timeframes, but likely acts within the cytoplasm to increase α-secretase enzymatic activity. Broad pharmacological inhibition of putative α-secretases increased ISF Aβ and blocked the effects of citalopram. CONCLUSIONS: In total, these studies map the major signaling components linking serotonin receptors to suppression of brain ISF Aβ. These results suggest the reduction in ISF Aβ is mediated by a select group of 5-HTRs and open future avenues for targeted therapy of AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13024-016-0112-5) contains supplementary material, which is available to authorized users