Additional file 1: of How well do general practitioners know their elderly patients’ social relations and feelings of loneliness?

GP questionnaire. (PDF 111 kb

Additional file 1: of Development and validation of a condition-specific diary to measure severity, bothersomeness and impact on daily activities for patients with acute urinary tract infection in primary care

Identified PROMs. (DOCX 27 kb

Additional file 1: of Measuring bothersome menopausal symptoms: development and validation of the MenoScores questionnaire

Appendix 1. Unique item-pool (separated into the suggested domains and the new items and domains generated in the interviews). (DOCX 28 kb

Additional file 2: of Measuring bothersome menopausal symptoms: development and validation of the MenoScores questionnaire

Appendix 2. Draft PROM. (DOCX 26 kb

Social disparities in diabetes care: a general population study in Denmark

<p><b>Objective:</b> We investigated the association between socioeconomic factors and the attainment of treatment goals and pharmacotherapy in patients with type 2 diabetes in Denmark.</p> <p><b>Design:</b> A cross-sectional population study.</p> <p><b>Setting:</b> The municipality of Naestved, Denmark.</p> <p><b>Subjects:</b> We studied 907 patients with type 2 diabetes identified from a random sample of 21,205 Danish citizens.</p> <p><b>Main outcome measures:</b> The proportion of patients who were not achieving goals for diabetes care based on their HbA_1c, LDL-cholesterol, blood pressure, and lifestyle, and the proportion of patients who were treated with antihypertensive and cholesterol- and glucose-lowering medication.</p> <p><b>Methods:</b> We investigated the association of the socioeconomic factors such as age, gender, education, occupation, income, and civil status and attainment of treatment goals and pharmacotherapy in logistic regression analyses. We investigated effect modification of cardiovascular disease and kidney disease.</p> <p><b>Results:</b> Middle age (40–65 years), low education level (i.e. basic schooling), and low household income (i.e. less than 21,400 € per year) were associated with nonattainment of goals for diabetes care. The association of socioeconomic factors with attainment of individual treatment goals varied. Patients with low socioeconomic status were more often obese, physically inactive, smoking, and had elevated blood pressure. Socioeconomic factors were not associated with treatment goals for hyperglycemia. Socioeconomic factors were inconsistently associated with pharmacotherapy. There was no difference in contacts to general practitioners according to SES.</p> <p><b>Conclusions:</b> In a country with free access to health care, the socioeconomic factors such as middle age, low education, and low income were associated with nonattainment of goals for diabetes care.KEY POINTS</p><p>Middle age, low education, and low income were associated with nonattainment of goals for diabetes care, especially for lifestyle goals.</p><p>Patients with low socioeconomic status were more often obese, physically inactive, smoking, and had elevated blood pressure.</p><p>Association of socioeconomic factors with pharmacotherapy was inconsistent.</p><p></p> <p>Middle age, low education, and low income were associated with nonattainment of goals for diabetes care, especially for lifestyle goals.</p> <p>Patients with low socioeconomic status were more often obese, physically inactive, smoking, and had elevated blood pressure.</p> <p>Association of socioeconomic factors with pharmacotherapy was inconsistent.</p

BOGDANOV-TAKENS BIFURCATIONS IN THREE COUPLED OSCILLATORS SYSTEM WITH ENERGY PRESERVING NONLINEARITY

looked at pdf abstract DOI : http://dx.doi.org/10.22342/jims.18.2.113.73-8

Weight change.

<p>This is an example of weight monitoring in one patient. For each patient weight change was modeled as a regression line through all the recorded weights. The exposure of interest in the present cohort study was the slope (the β coefficient) of this regression line. The exposure is a continuous variable that denotes the average yearly weight change (kg/year).</p

Additional file 5: of Socio-demographic determinants and effect of structured personal diabetes care: a 19-year follow-up of the randomized controlled study diabetes Care in General Practice (DCGP)

Table S4. The effect of structured personal care on behavioral, clinical, process of care and biochemical variables according to residence (Rural vs. Urban) (DOCX 37 kb

Timeline of the cohort study.

<p>Patients, newly diagnosed with diabetes, were included at year 0. The exposure of interest was weight change during year 0–6 (the monitoring period). Only patients surviving the monitoring period were included in the present analyses. The follow-up period was 13 years. The hazard ratios (HR) for mortality and morbidity were also estimated separately for the first 2 years of follow-up (year 6–8) and for the remaining 11 years (year 8–19), as bias from pathological weight loss was expected to be greater during the first two years of follow-up.</p

Additional file 3: of Socio-demographic determinants and effect of structured personal diabetes care: a 19-year follow-up of the randomized controlled study diabetes Care in General Practice (DCGP)

Table S2. The effect of structured personal care on behavioral, clinical, process of care and biochemical variables according to civil status (DOCX 37 kb