Evaluating the implementation potential of a transcultural tool for Tamil migrants with gestational diabetes mellitus living in Switzerland

2017 ◽  
Vol 2 (2) ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Online Survey ◽  
Healthcare Professionals ◽  
Binary Logistic Regression ◽  
Private Practices ◽  
Populations At Risk ◽  
Management Procedures

Background: Gestational diabetes mellitus is a condition that affects many pregnancies and ethnicity appears to be a risk factor. Data indicate that approximately 18% of Tamil women are diagnosed with gestational diabetes mellitus. Today, approximately 50,000 of Tamils live in Switzerland. To date, there is no official tool available in Switzerland that considers the eating and physical activity habits of this migrant Tamil population living in Switzerland, while offering a quick overview of gestational diabetes mellitus and standard dietetics management procedures. The NutriGeD project led by Bern University of Applied Sciences in Switzerland aimed at closing this gap. The aim of this present study was to evaluate the implementation potential of the tools developed in the project NutriGeD for dietetic counseling before their wide scale launch in Swiss hospitals, clinics and private practices. Method: An online survey was developed and distributed to 50 recruited healthcare professionals working in the German speaking region of Switzerland from October – December 2016 (31% response rate). The transcultural tools were sent to participants together with the link to the online survey. The evaluation outcome was analysed using binary logistic regression and cross tabulation analysis with IBM SPSS version 24.0, 2016. Results: 94% (N=47) respondents believed that the transcultural tools had good potential for implementation in hospitals and private practices in Switzerland. A binary logistic regression analysis revealed that the age of participants had a good correlation (42.1%) on recommending the implementation potential of the transcultural tool. The participants with age group 34- 54 years old where the highest group to recommend the implementation potential of the transcultural tool and this was found to be statistically significant (p=0.05). 74% (34 out of 50) of the respondents clearly acknowledged the need for transcultural competence knowledge in healthcare practices. 80% (N =40) of the respondents agreed that the information presented in the counseling display folder was important and helpful while 60% (N= 30) agreed to the contents being clinically applicable. 90% (N=45) participants recommended the availability of the evaluated transcultural tools in healthcare settings in Switzerland. Conclusion: The availability in healthcare practice of the evaluated transcultural tools was greatly encouraged by the Swiss healthcare practitioners participating in the survey. While they confirmed the need for these transcultural tools, feed-backs for minor adjustments were given to finalize the tools before their official launch in practice. The developed materials will be made available for clinical visits, in both hospitals and private practices in Switzerland. The Migmapp© transcultural tool can serve as a good approach in assisting healthcare professionals in all fields, especially professionals who practice in areas associated with diet - related diseases or disorders associated with populations at risk.

scholarly journals AB0302 FACTORS ASSOCIATED WITH GESTATIONAL DIABETES MELLITUS (GDM) IN A MULTI-ETHNIC SYSTEMIC LUPUS ERYTHEMATOSUS (SLE) COHORT

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1177.1-1177
Author(s):  
S. S. Shaharir ◽  
R. Mustafar ◽  
M. S. Mohamed Said ◽  
R. Abd Rahman
Keyword(s):  
Diabetes Mellitus ◽  
Systemic Lupus Erythematosus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Disease Activity ◽  
Lupus Erythematosus ◽  
Systemic Lupus ◽  
Factors Associated ◽  
In Pregnancy

Background:The risks of insulin resistance and diabetes mellitus are elevated in systemic lupus erythematosus (SLE) patients. The use of glucocorticoid and anti-double stranded DNA antibodies positive are among the factors reported to be associated with the risk of gestational diabetes mellitus (GDM) in SLE patients. However, the relationship between GDM in Asian SLE patients is still obscure.Objectives:To determine the prevalence of gestational diabetes mellitus (GDM) in a multi-ethnic SLE cohort in Malaysia and the associated risk factors.Methods:This was a retrospective study of SLE pregnant women who have completed their antenatal care in Universiti Kebangsaan Malaysia Medical Centre (UKMMC) from 2004 until 2019. Screening and diagnosis of gestational diabetes mellitus (GDM) were as recommended in the guidelines by the Ministry of Health Malaysia. Information on SLE disease activity and treatment at 6 months before pregnancy and during pregnancy were determined from the medical records. Univariate and multi-variable logistic regression analyses were performed to determine the factors associated with GDM in the SLE patients.Results:A total of 89 patients with 202 pregnancies were included in the study. Malay was the predominant ethnic in this cohort (n=82, 67.2%), followed by Chinese (n=33,27.0%) and Indian (n=7, 5.7%). The most common system involvement of SLE was musculoskeletal (n=91, 74.6%), followed by haematological (n=78, 63.9%), lupus nephritis (54.9%, n=67) and mucocutaneous (n=66, 54.1%). The prevalence of GDM was 8.9% (n=18). More patients with GDM had positive anti-cardiolipin IgG antibody (aCL IgG) and lupus anticoagulant (LA) antibody as compared to the patients with no GDM, (55.6% vs 25.8%, p=0.01) and (50.0% vs 25.4%, p=0.05) respectively. On the other hand, the use of hydroxychloroquine (HCQ) in pregnancy was significantly lower in GDM patients (11.1%) as compared to no GDM group (39.1%), p=0.02. There was no significant difference in the ethnicity, SLE system involvement, disease activity status and immunosupressant use including steroid, azathioprine and cyclosporine A at 6 months before and during pregnancy between the GDM and non-GDM group. A forward logistic regression which include aCL IgG, LA and HCQ use in pregnancy, only the HCQ use remained significantly associated with lower risk of GDM in the model with OR= 0.12, 95% C.I = 0.02-0.94, p=0.04.Conclusion:Our study demonstrates the potential benefit of hydroxychloroquine in reducing the risk of gestational diabetes mellitus in SLE patients. The prevalence of antiphospholipid antibodies particularly aCL IgG and LA was found to be higher among patients with GDM. Further prospective studies are needed to confirm this association.References:[1]Dong Y, Dai Z, Wang Z, et al. Risk of gestational diabetes mellitus in systemic lupus erythematosus pregnancy: a systematic review and meta-analysis. BMC Pregnancy and Childbirth. 2019 May;19(1):179. DOI: 10.1186/s12884-019-2329-0.Disclosure of Interests:None declared

scholarly journals Geospatial Analysis of Birth Records to Target Programming for Mothers With Gestational Diabetes Mellitus in Michigan, 2013

2018 ◽  
Vol 134 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Elizabeth MacQuillan ◽  
Amy Curtis ◽  
Kathleen Baker ◽  
Rajib Paul
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Hot Spot ◽  
The United States ◽  
The State ◽  
Maternal Child Health ◽  
Birth Data ◽  
Birth Records

Objectives: The incidence of gestational diabetes mellitus (GDM) in the United States has increased during the past several decades. The objective of this study was to use birth records and a combination of statistical and geographic information system (GIS) analyses to evaluate GDM rates among subgroups of pregnant women in Michigan. Materials and Methods: We obtained data on maternal demographic and health-related characteristics and regions of residence from 2013 Michigan birth records. We geocoded (ie, matched to maternal residence) the birth data, calculated proportions of births to women with GDM, and used logistic regression models to determine predictors of GDM. We calculated odds ratios (ORs) from the exponentiated beta statistic of the logistic regression test. We also used kernel density estimations and local indicators of spatial association (LISA) analyses to determine GDM rates in regions in the state and identify GDM hot spots (ie, areas with a high GDM rate surrounded by areas with a high GDM rate). Results: We successfully geocoded 104 419 of 109 168 (95.6%) births in Michigan in 2013. Of the geocoded births, 5185 (5.0%) were to mothers diagnosed with GDM. LISA maps showed a hot spot of 8 adjacent counties with high GDM rates in southwest Michigan. Of 11 064 births in the Southwest region, 829 (7.5%) were to mothers diagnosed with GDM, the highest rate in the state and a result confirmed by geospatial analyses. Practice Applications: Birth data and GIS analyses may be used to measure statewide pregnancy-associated disease risk and identify populations and geographic regions in need of targeted public health and maternal–child health interventions.

scholarly journals First-Trimester Screening for Gestational Diabetes Mellitus Based on Maternal Characteristics and History

2014 ◽  
Vol 38 (1) ◽  
pp. 14-21 ◽  
Author(s):  
Argyro Syngelaki ◽  
Alice Pastides ◽  
Reena Kotecha ◽  
Alan Wright ◽  
Ranjit Akolekar ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Logistic Regression Model ◽  
Cross Validation ◽  
Nice Guidelines ◽  
Maternal Characteristics ◽  
History Of ◽  
Fold Cross Validation

Objectives: To develop and validate a prediction model for gestational diabetes mellitus (GDM) at 11-13 weeks' gestation based on maternal characteristics and history and to compare its performance with the method recommended by the National Institute of Health and Care Excellence (NICE) and five other published prediction models. Methods: A predictive logistic regression model for GDM was developed from 1,827 cases (2.4%) who developed GDM and 73,334 unaffected controls. A 5-fold cross-validation study was performed to validate this model and to compare its performance with those of the NICE guidelines and the previously published models. Results: In the logistic regression model, maternal age, weight, height, racial origin, family history of diabetes, use of ovulation drugs, birth weight, and previous history of GDM were found to be significant predictors of GDM. In screening for GDM in the 5-fold cross-validation study, detection rates (DRs) were higher (p < 0.0001) for the proposed model (DR = 83.2%) than for the NICE guidelines (DR = 77.5%) for a false positive rate of approximately 40% (determined by NICE). The area under the receiver operating characteristic curve of the new model was higher (p < 0.0001) than that of the previous five models (0.823 vs. 0.688-786). Conclusions: Early effective screening for GDM can be achieved based on maternal characteristics and history.

scholarly journals Lifestyle intervention to prevent gestational diabetes mellitus and adverse maternal outcomes among pregnant women at high risk for gestational diabetes mellitus

2020 ◽  
Vol 48 (12) ◽  
pp. 030006052097913
Author(s):  
Xueyan Lin ◽  
Ting Yang ◽  
Xueqin Zhang ◽  
Wei Wei
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
Lifestyle Intervention ◽  
Intervention Group ◽  
Control Group ◽  
Maternal Outcomes ◽  
Multivariate Logistic Regression

Objective We assessed the effects of a lifestyle intervention on gestational diabetes mellitus (GDM) incidence and risk of adverse maternal outcomes among pregnant women at high risk for GDM. Methods From July to December 2018, we enrolled 1822 eligible pregnant women; of these, 304 had at least one risk factor for GDM. Participants were randomly allocated to the intervention or control group. Usual prenatal care was offered to both groups; the intervention group also received individually modified education on diet, physical activity, and weight control. The GDM diagnosis was based on an oral glucose tolerance test at 24–28 gestational weeks. Multivariate logistic regression was used to evaluate the effects of the lifestyle intervention on risk of GDM and adverse maternal outcomes. Results A total of 281 women (139 in the intervention group and 142 controls) were included. Incidences of GDM and adverse maternal outcomes were all significantly lower in the intervention than in the control group. Multivariate logistic regression indicated that women in the intervention group had a lower risk of GDM and adverse maternal outcomes, after adjusting potential confounding factors. Conclusion The present lifestyle intervention was associated with lower risks of GDM and adverse maternal outcomes.

scholarly journals Establishment of a nomogram model to predict macrosomia in pregnant women with gestational diabetes mellitus

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yujiao Zou ◽  
Yan Zhang ◽  
Zhenhua Yin ◽  
Lili Wei ◽  
Bohan Lv ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Confidence Interval ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
External Validation ◽  
Amniotic Fluid Index ◽  
Independent Risk Factors

Abstract Aim To establish a nomogram model to predict the risk of macrosomia in pregnant women with gestational diabetes mellitus in China. Methods We retrospectively collected the medical records of 783 pregnant women with gestational diabetes who underwent prenatal examinations and delivered at the Affiliated Hospital of Qingdao University from October 2019 to October 2020. The pregnant women were randomly divided into two groups in a 4:1 ratio to generate and validate the model. The independent risk factors for macrosomia in pregnant women with gestational diabetes mellitus were analyzed by multivariate logistic regression, and the nomogram model to predict the risk of macrosomia in pregnant women with gestational diabetes mellitus was established and verified by R software. Results Logistic regression analysis showed that prepregnancy body mass index, weight gain during pregnancy, fasting plasma glucose, triglycerides, biparietal diameter and amniotic fluid index were independent risk factors for macrosomia (P < 0.05). The areas under the ROC curve for internal and external validation of the model were 0.813 (95 % confidence interval 0.754–0.862) and 0.903 (95 % confidence interval 0.588–0.967), respectively. The calibration curve was a straight line with a slope close to 1. Conclusions In this study, we constructed a nomogram model to predict the risk of macrosomia in pregnant women with gestational diabetes mellitus. The model has good discrimination and calibration abilities, which can help clinical healthcare staff accurately predict macrosomia in pregnant women with gestational diabetes mellitus.

scholarly journals Association of Common Genetic Risk Variants With Gestational Diabetes Mellitus and Their Role in GDM Prediction

2021 ◽  
Vol 12 ◽  
Author(s):  
Polina V. Popova ◽  
Alexandra A. Klyushina ◽  
Lyudmila B. Vasilyeva ◽  
Alexandra S. Tkachuk ◽  
Elena A. Vasukova ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Regression Model ◽  
Genetic Risk ◽  
Logistic Regression Model ◽  
C Statistic ◽  
Risk Variants ◽  
Genetic Risk Variants

ObjectiveWe aimed to explore the associations between common genetic risk variants with gestational diabetes mellitus (GDM) risk in Russian women and to assess their utility in the identification of GDM cases.MethodsWe conducted a case-control study including 1,142 pregnant women (688 GDM cases and 454 controls) enrolled at Almazov National Medical Research Centre. The International Association of Diabetes and Pregnancy Study Groups criteria were used to diagnose GDM. A total of 11 single- nucleotide polymorphisms (SNPs), including those in HKDC1 (rs10762264), GCK (rs1799884), MTNR1B (rs10830963 and rs1387153), TCF7L2 (rs7903146 and rs12255372), KCNJ11 (rs5219), IGF2BP2 (rs4402960), IRS1 (rs1801278), FTO (rs9939609), and CDKAL1 (rs7754840) were genotyped using Taqman assays. A logistic regression model was used to calculate odds ratios (ORs) and their confidence intervals (CIs). A simple-count genetic risk score (GRS) was calculated using 6 SNPs. The area under the receiver operating characteristic curve (c-statistic) was calculated for the logistic regression model predicting the risk of GDM using clinical covariates, SNPs that had shown a significant association with GDM in our study, GRS, and their combinations.ResultsTwo variants in MTNR1B (rs1387153 and rs10830963) demonstrated a significant association with an increased risk of GDM. The association remained significant after adjustment for age, pre-gestational BMI, arterial hypertension, GDM in history, impaired glucose tolerance, polycystic ovary syndrome, family history of diabetes, and parity (P = 0.001 and P &lt; 0.001, respectively). After being conditioned by each other, the effect of rs1387153 on GDM predisposition weakened while the effect of rs10830963 remained significant (P = 0.004). The risk of GDM was predicted by clinical variables (c-statistic 0.712, 95 % CI: 0.675 – 0.749), and the accuracy of prediction was modestly improved by adding GRS to the model (0.719, 95 % CI 0.682 – 0.755), and more by adding only rs10830963 (0.729, 95 % CI 0.693 – 0.764).ConclusionAmong 11 SNPs associated with T2D and/or GDM in other populations, we confirmed significant association with GDM for two variants in MTNR1B in Russian women. However, these variants showed limited value in the identification of GDM cases.

scholarly journals The Relationship Between Hypertriglyceridemic Waist Circumference Phenotype and Gestational Diabetes Mellitus

2020 ◽  
Author(s):  
Xiao-jiao Jia ◽  
Jia-xin Wang ◽  
Li-wei Bai ◽  
Tian-shu Hua ◽  
Zhong-hou Han ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Waist Circumference ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Logistic Regression Analysis ◽  
Hypertriglyceridemic Waist ◽  
Group A ◽  
The Relationship

Abstract Background: To investigate the correlation between hypertriglyceridemic waist circumference (HTWC) phenotype and gestational diabetes mellitus (GDM).Methods: A total of 1083 patients with gestational age ≤8 weeks were divided into four groups: normal triglyceride and waist circumference group (group A, n=575), simple abdominal obesity group (group B, n=317), simple high triglyceride group (group C, n=125), and HTWC group (group D, n=66). General information and serum biochemical indicators were measured and recorded. Analysis of variance (ANOVA) and logistic regression analysis were used to evaluate the relationship between HTWC with GDM.Results: The prevalence of GDM in the HTWC group was significantly greater than in the other three groups. After adjustment by multivariate logistic regression analysis, the proportion of GDM in the HTWC group was 1.753 times higher than in group A.Conclusion: These findings suggest that there is a significant correlation between HTWC phenotype and GDM, indicating that the HTWC phenotype could be applied as a simple marker for identifying GDM risk factors.

scholarly journals First Trimester Combined Test (FTCT) as a Predictor of Gestational Diabetes Mellitus

2019 ◽  
Vol 16 (19) ◽  
pp. 3654 ◽  
Author(s):  
Federica Visconti ◽  
Paola Quaresima ◽  
Eusebio Chiefari ◽  
Patrizia Caroleo ◽  
Biagio Arcidiacono ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
First Trimester ◽  
Maternal Serum ◽  
Fetal Aneuploidy ◽  
Combined Test ◽  
Β Hcg

Background—The first trimester combined test (FTCT) is an effective screening tool to estimate the risk of fetal aneuploidy. It is obtained by the combination of maternal age, ultrasound fetal nuchal translucency (NT) measurement, and the maternal serum markers free β-human chorionic gonadotropin (β-hCG) and pregnancy-associated plasma protein A (PAPP-A). However, conflicting data have been reported about the association of FTCT, β-hCG, or PAPP-A with the subsequent diagnosis of gestational diabetes mellitus (GDM). Research design and methods—2410 consecutive singleton pregnant women were retrospectively enrolled in Calabria, Southern Italy. All participants underwent examinations for FTCT at 11–13 weeks (plus 6 days) of gestation, and screening for GDM at 16–18 and/or 24–28 weeks of gestation, in accordance with current Italian guidelines and the International Association Diabetes Pregnancy Study Groups (IADPSG) glycemic cut-offs. Data were examined by univariate and logistic regression analyses. Results—1814 (75.3%) pregnant women were normal glucose tolerant, while 596 (24.7%) were diagnosed with GDM. Spearman univariate analysis demonstrated a correlation between FTCT values and subsequent GDM diagnosis (ρ = 0.048, p = 0.018). The logistic regression analysis showed that women with a FTCT <1:10000 had a major GDM risk (p = 0.016), similar to women with a PAPP-A <1 multiple of the expected normal median (MoM, p = 0.014). Conversely, women with β-hCG ≥2.0 MoM had a reduced risk of GDM (p = 0.014). Conclusions—Our findings indicate that GDM susceptibility increases with fetal aneuploidy risk, and that FTCT and its related maternal serum parameters can be used as early predictors of GDM.

Sign in / Sign up

Export Citation Format

Share Document