A plea for intra-laboratory reference limits. Part 2. A bimodal retrospective concept for determining reference limits from intra-laboratory databases demonstrated by catalytic activity concentrations of enzymes

Arzideh, Farhad; Wosniok, Werner; Gurr, Eberhard; Hinsch, W; Schumann, G.; Weinstock, N.; Haeckel, Rainer

doi:10.1515/cclm.2007.250

Cited by 101 publications

(75 citation statements)

References 19 publications

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“…The reproducibility of an OGTT may be reduced due to variation in the quality of the glucose measurements as well as intraindividual variations. In a systematic review of five studies, the reproducibility of a single test was 33–45% for IGT, 51–64% for IFG, and 73% for diabetes (Balion et al 2007). Another reason for low reproducibility and misclassification is regression to the mean (Yudkin and Stratton 1996), indicating that individuals selected because they have a single high measurement will include a disproportionate number of individuals whose measurement by chance was higher than its true value.…”

Section: Discussionmentioning

confidence: 99%

Long-Term Aircraft Noise Exposure and Body Mass Index, Waist Circumference, and Type 2 Diabetes: A Prospective Study

Eriksson¹,

Hilding

Pyko³

et al. 2014

Environ Health Perspect

102

105

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Background: Long-term aircraft noise exposure may increase the risk of cardiovascular disease, but no study has investigated chronic effects on the metabolic system.Objectives: The aim of this study was to investigate effects of long-term aircraft noise exposure on body mass index (BMI), waist circumference, and type 2 diabetes. Furthermore, we explored the modifying effects of sleep disturbance.Methods: This prospective cohort study of residents of Stockholm County, Sweden, followed 5,156 participants with normal baseline oral glucose tolerance tests (OGTT) for up to 10 years. Exposure to aircraft noise was estimated based on residential history. Information on outcomes and confounders was obtained from baseline and follow-up surveys and examinations, and participants who developed prediabetes or type 2 diabetes were identified by self-reported physician diagnosis or OGTT at follow-up. Adjusted associations were assessed by linear, logistic, and random-effects models.Results: The mean (± SD) increases in BMI and waist circumference during follow-up were 1.09 ± 1.97 kg/m2 and 4.39 ± 6.39 cm, respectively. The cumulative incidence of prediabetes and type 2 diabetes was 8% and 3%, respectively. Based on an ordinal noise variable, a 5-dB(A) increase in aircraft noise was associated with a greater increase in waist circumference of 1.51 cm (95% CI: 1.13, 1.89), fully adjusted. This association appeared particularly strong among those who did not change their home address during the study period, which may be a result of lower exposure misclassification. However, no clear associations were found for BMI or type 2 diabetes. Furthermore, sleep disturbances did not appear to modify the associations with aircraft noise.Conclusions: Long-term aircraft noise exposure may be linked to metabolic outcomes, in particular increased waist circumference.Citation: Eriksson C, Hilding A, Pyko A, Bluhm G, Pershagen G, Östenson CG. 2014. Long-term aircraft noise exposure and body mass index, waist circumference, and type 2 diabetes: a prospective study. Environ Health Perspect 122:687–694; http://dx.doi.org/10.1289/ehp.1307115

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Section: Discussionmentioning

confidence: 99%

Long-Term Aircraft Noise Exposure and Body Mass Index, Waist Circumference, and Type 2 Diabetes: A Prospective Study

Eriksson¹,

Hilding

Pyko³

et al. 2014

Environ Health Perspect

102

105

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“…These cutoff values, derived from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, predict adverse pregnancy outcomes with an odds ratio of 1.75 [18]. Challenges associated with using the IADPSG criteria for GDM diagnosis include a high prevalence of GDM (17.8% of all pregnancies in the HAPO study) and poor reproducibility [19]. Currently, both the Korean Diabetes Association and the American Diabetes Association (ADA) recommend both the one- and two-step approaches for the diagnosis of GDM [20,21].…”

Section: Diagnosis Of Gdm and Postpartum Diabetesmentioning

confidence: 99%

Prevention of type 2 diabetes mellitus in women with previous gestational diabetes mellitus

Moon

Kwak

Jang

2017

Korean J Intern Med

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Gestational diabetes mellitus (GDM), defined as any degree of glucose intolerance with onset or first recognition during pregnancy, is characterized by underlying maternal defects in the β-cell response to insulin during pregnancy. Women with a previous history of GDM have a greater than 7-fold higher risk of developing postpartum diabetes compared with women without GDM. Various risk factors for postpartum diabetes have been identified, including maternal age, glucose levels in pregnancy, family history of diabetes, pre-pregnancy and postpartum body mass index, dietary patterns, physical activity, and breastfeeding. Genetic studies revealed that GDM shares common genetic variants with type 2 diabetes. A number of lifestyle interventional trials that aimed to ameliorate modifiable risk factors, including diet, exercise, and breastfeeding, succeeded in reducing the incidence of postpartum diabetes, weight retention, and other obesity-related morbidities. The present review summarizes the findings of previous studies on the incidence and risk factors of postpartum diabetes and discusses recent lifestyle interventional trials that attempted to prevent postpartum diabetes.

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“…In this issue of Clinical Chemistry and Laboratory Medicine, two articles by Haeckel et al, the start of an announced series, try to bring concrete solutions and new light on this problem (7,8). The first article of the series is clear and educational (7).…”

Section: Interpretation Of Laboratory Results: the Reference Intervalmentioning

confidence: 99%

“…It necessitates extensive resources, notably the ready availability of a consistent database to allow implementation of the required selection criteria. The limits of such an approach appear obvious in reading their second article (8). The observed differences between laboratories' Reference Intervals are attributed to the population, but could, among other things, be due to inappropriate selection of the reference population.…”

Section: Interpretation Of Laboratory Results: the Reference Intervalmentioning

confidence: 99%

Interpretation of laboratory results: the Reference Intervals, a necessary evil?

Henny¹

2007

Clinical Chemical Laboratory Medicine

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A plea for intra-laboratory reference limits. Part 2. A bimodal retrospective concept for determining reference limits from intra-laboratory databases demonstrated by catalytic activity concentrations of enzymes

Abstract: Poor reproducibility of IGT and IFG classification suggests caution should be exercised when interpreting a single test result.

Cited by 101 publications

References 19 publications

Long-Term Aircraft Noise Exposure and Body Mass Index, Waist Circumference, and Type 2 Diabetes: A Prospective Study

Long-Term Aircraft Noise Exposure and Body Mass Index, Waist Circumference, and Type 2 Diabetes: A Prospective Study

Prevention of type 2 diabetes mellitus in women with previous gestational diabetes mellitus

Interpretation of laboratory results: the Reference Intervals, a necessary evil?

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