Potential of education-based insulin therapy for achievement of good metabolic control: a real-life experience.

Diabet. Med. 28, 539-542 (2011) ABSTRACT: Aims  Achievement of good metabolic control in Type 1 diabetes is a difficult task in routine diabetes care. Education-based flexible intensified insulin therapy has the potential to meet the therapeutic targets while limiting the risk for severe hypoglycaemia. We evaluated the metabolic control and the rate of severe hypoglycaemia in real-life clinical practice in a centre using flexible intensified insulin therapy as standard of care since 1990. Methods  Patients followed for Type 1 diabetes (n = 206) or those with other causes of absolute insulin deficiency (n = 17) in our outpatient clinic were analysed in a cross-sectional study. Mean age (± standard deviation) was 48.9 ± 15.7 years, with diabetes duration of 21.4 ± 14.4 years. Outcome measures were HbA(1c) and frequency of severe hypoglycaemia. Results  Median HbA(1c) was 7.1% (54 mmol/mol) [interquartile range 6.6-7.8 (51-62 mmol/mol)]; a good or acceptable metabolic control with HbA(1c) < 7.0% (53 mmol/mol) or 7.5% (58 mmol/mol) was reached in 43.5 and 64.6% of the patients, respectively. The frequency of severe hypoglycaemic episodes was 15 per 100 patient years: 72.3% of the patients did not experience any such episodes during the past 5 years. Conclusions  Good or acceptable metabolic control is achievable in the majority of patients with Type 1 diabetes or other causes of absolute insulin deficiency in routine diabetes care while limiting the risk for severe hypoglycaemia.

Association of education and receiving social transfers with allostatic load in the Swiss population-based CoLaus study.

BACKGROUND: Allostatic load reflects cumulative exposure to stressors throughout lifetime and has been associated with several adverse health outcomes. It is hypothesized that people with low socioeconomic status (SES) are exposed to higher chronic stress and have therefore greater levels of allostatic load. OBJECTIVE: To assess the association of receiving social transfers and low education with allostatic load. METHODS: We included 3589 participants (1812 women) aged over 35years and under retirement age from the population-based CoLaus study (Lausanne, Switzerland, 2003-2006). We computed an allostatic load index aggregating cardiovascular, metabolic, dyslipidemic and inflammatory markers. A novel index additionally including markers of oxidative stress was also examined. RESULTS: Men with low vs. high SES were more likely to have higher levels of allostatic load (odds ratio (OR)=1.93/2.34 for social transfers/education, 95%CI from 1.45 to 4.17). The same patterns were observed among women. Associations persisted after controlling for health behaviors and marital status. CONCLUSIONS: Low education and receiving social transfers independently and cumulatively predict high allostatic load and dysregulation of several homeostatic systems in a Swiss population-based study. Participants with low SES are at higher risk of oxidative stress, which may justify its inclusion as a separate component of allostatic load.

Swain: Stata module to correct the SEM chi-square overidentification test in small sample sizes or complex models. Statistical Software Components S457617, Boston College Department of Economics.

Swain corrects the chi-square overidentification test (i.e., likelihood ratio test of fit) for structural equation models whethr with or without latent variables. The chi-square statistic is asymptotically correct; however, it does not behave as expected in small samples and/or when the model is complex (cf. Herzog, Boomsma, & Reinecke, 2007). Thus, particularly in situations where the ratio of sample size (n) to the number of parameters estimated (p) is relatively small (i.e., the p to n ratio is large), the chi-square test will tend to overreject correctly specified models. To obtain a closer approximation to the distribution of the chi-square statistic, Swain (1975) developed a correction; this scaling factor, which converges to 1 asymptotically, is multiplied with the chi-square statistic. The correction better approximates the chi-square distribution resulting in more appropriate Type 1 reject error rates (see Herzog & Boomsma, 2009; Herzog, et al., 2007).