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Background: Gestational diabetes mellitus (GDM) poses risks to maternal and neonatal health, yet screening approaches vary in Europe. Cultural, socioeconomic, psychological, and healthcare factors impact adherence to the essential dietary management of GDM. This study aims to explore these factors to enhance dietary adherence among women with GDM in Europe. Aim: To investigate the factors promoting and hindering adherence to a healthy diet among women diagnosed with GDM or at risk of developing GDM in Europe. Methodology: A qualitative meta-synthesis with a meta-ethnographic analysis design (Noblit & Hare, 1988) was used in this study. 18 qualitative articles focusing on diet adherence experiences and perceptions of women with GDM risk or diagnosis in Europe were analyzed. Results: Five main themes were identified: Beliefs and Perceptions, Psychological impact and Coping, Environmental and Social Factors, Healthcare Services and Support and Knowledge and Awareness. The sub-themes included: beliefs about illness, beliefs about health, beliefs about healthcare, preliminary psychological impact, stigma, coping and building resilience, social and economic stressors, family life and domestic duties, service provision, relational interactions, understanding of GDM and awareness of future diabetes risks. Conclusion: The study underscores the complex interplay of socio-cultural, psychological, and healthcare factors affecting women with GDM or at risk in Europe. Adherence to a healthy diet is influenced by women's beliefs, emotional responses, financial constraints, social support, and healthcare experiences. Positive healthcare encounters enhance adherence, while knowledge gaps highlight the need for improved education and guidance. Holistically addressing these factors is crucial for effective dietary management in GDM.

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women, affecting their lives in many ways. PCOS is characterised by ovulatory dysfunction, polycystic ovary morphology and hyperandrogenism, either clinical or biochemical. Women with PCOS face a higher risk of obstetric complications than women without PCOS. There are many factors that contribute to these complications, such as metabolic disturbances, insulin resistance, chronic inflammation, hyperandrogenism and factors related to infertility. The overall aim of the research presented in this thesis was to study factors that might affect the association between PCOS and pregnancy complications. The thesis consists of matched cohort studies based on data from the Uppsala Biobank of Pregnant Women (Papers I and II) and national register-based cohort studies (Papers III and IV). In the first two studies, we included women with PCOS (n = 159) and BMI-matched controls (n = 320), and the aim was to study the effect of high anti-Müllerian hormone (AMH) and testosterone on pregnancy complications. The third study (n = 138 219) explored whether the association between PCOS and preeclampsia depends on treated clinical hyperandrogenism and whether PCOS is associated with different subtypes of preeclampsia. In the fourth study (n = 281 806), the aim was to explore association and risk estimates for pregnancy outcomes in women with either or both PCOS and gestational diabetes mellitus (GDM). The main results were that women with PCOS have higher levels of AMH and testosterone and a higher free androgen index during second trimester pregnancy than non-PCOS controls. High AMH levels were not associated with adverse pregnancy outcome or birthweight. PCOS women with the highest testosterone levels had the highest risk for preeclampsia. Compared to non-PCOS controls, women with PCOS have increased risk of preeclampsia, especially the more severe subtypes of preeclampsia, early onset or with a birth of an i

Background: Gestational diabetes mellitus (GDM) poses risks to maternal and neonatal health, yet screening approaches vary in Europe. Cultural, socioeconomic, psychological, and healthcare factors impact adherence to the essential dietary management of GDM. This study aims to explore these factors to enhance dietary adherence among women with GDM in Europe. Aim: To investigate the factors promoting and hindering adherence to a healthy diet among women diagnosed with GDM or at risk of developing GDM in Europe. Methodology: A qualitative meta-synthesis with a meta-ethnographic analysis design (Noblit & Hare, 1988) was used in this study. 18 qualitative articles focusing on diet adherence experiences and perceptions of women with GDM risk or diagnosis in Europe were analyzed. Results: Five main themes were identified: Beliefs and Perceptions, Psychological impact and Coping, Environmental and Social Factors, Healthcare Services and Support and Knowledge and Awareness. The sub-themes included: beliefs about illness, beliefs about health, beliefs about healthcare, preliminary psychological impact, stigma, coping and building resilience, social and economic stressors, family life and domestic duties, service provision, relational interactions, understanding of GDM and awareness of future diabetes risks. Conclusion: The study underscores the complex interplay of socio-cultural, psychological, and healthcare factors affecting women with GDM or at risk in Europe. Adherence to a healthy diet is influenced by women's beliefs, emotional responses, financial constraints, social support, and healthcare experiences. Positive healthcare encounters enhance adherence, while knowledge gaps highlight the need for improved education and guidance. Holistically addressing these factors is crucial for effective dietary management in GDM.

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women, affecting their lives in many ways. PCOS is characterised by ovulatory dysfunction, polycystic ovary morphology and hyperandrogenism, either clinical or biochemical. Women with PCOS face a higher risk of obstetric complications than women without PCOS. There are many factors that contribute to these complications, such as metabolic disturbances, insulin resistance, chronic inflammation, hyperandrogenism and factors related to infertility. The overall aim of the research presented in this thesis was to study factors that might affect the association between PCOS and pregnancy complications. The thesis consists of matched cohort studies based on data from the Uppsala Biobank of Pregnant Women (Papers I and II) and national register-based cohort studies (Papers III and IV). In the first two studies, we included women with PCOS (n = 159) and BMI-matched controls (n = 320), and the aim was to study the effect of high anti-Müllerian hormone (AMH) and testosterone on pregnancy complications. The third study (n = 138 219) explored whether the association between PCOS and preeclampsia depends on treated clinical hyperandrogenism and whether PCOS is associated with different subtypes of preeclampsia. In the fourth study (n = 281 806), the aim was to explore association and risk estimates for pregnancy outcomes in women with either or both PCOS and gestational diabetes mellitus (GDM). The main results were that women with PCOS have higher levels of AMH and testosterone and a higher free androgen index during second trimester pregnancy than non-PCOS controls. High AMH levels were not associated with adverse pregnancy outcome or birthweight. PCOS women with the highest testosterone levels had the highest risk for preeclampsia. Compared to non-PCOS controls, women with PCOS have increased risk of preeclampsia, especially the more severe subtypes of preeclampsia, early onset or with a birth of an i

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women, affecting their lives in many ways. PCOS is characterised by ovulatory dysfunction, polycystic ovary morphology and hyperandrogenism, either clinical or biochemical. Women with PCOS face a higher risk of obstetric complications than women without PCOS. There are many factors that contribute to these complications, such as metabolic disturbances, insulin resistance, chronic inflammation, hyperandrogenism and factors related to infertility. The overall aim of the research presented in this thesis was to study factors that might affect the association between PCOS and pregnancy complications. The thesis consists of matched cohort studies based on data from the Uppsala Biobank of Pregnant Women (Papers I and II) and national register-based cohort studies (Papers III and IV). In the first two studies, we included women with PCOS (n = 159) and BMI-matched controls (n = 320), and the aim was to study the effect of high anti-Müllerian hormone (AMH) and testosterone on pregnancy complications. The third study (n = 138 219) explored whether the association between PCOS and preeclampsia depends on treated clinical hyperandrogenism and whether PCOS is associated with different subtypes of preeclampsia. In the fourth study (n = 281 806), the aim was to explore association and risk estimates for pregnancy outcomes in women with either or both PCOS and gestational diabetes mellitus (GDM). The main results were that women with PCOS have higher levels of AMH and testosterone and a higher free androgen index during second trimester pregnancy than non-PCOS controls. High AMH levels were not associated with adverse pregnancy outcome or birthweight. PCOS women with the highest testosterone levels had the highest risk for preeclampsia. Compared to non-PCOS controls, women with PCOS have increased risk of preeclampsia, especially the more severe subtypes of preeclampsia, early onset or with a birth of an i

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women, affecting their lives in many ways. PCOS is characterised by ovulatory dysfunction, polycystic ovary morphology and hyperandrogenism, either clinical or biochemical. Women with PCOS face a higher risk of obstetric complications than women without PCOS. There are many factors that contribute to these complications, such as metabolic disturbances, insulin resistance, chronic inflammation, hyperandrogenism and factors related to infertility. The overall aim of the research presented in this thesis was to study factors that might affect the association between PCOS and pregnancy complications. The thesis consists of matched cohort studies based on data from the Uppsala Biobank of Pregnant Women (Papers I and II) and national register-based cohort studies (Papers III and IV). In the first two studies, we included women with PCOS (n = 159) and BMI-matched controls (n = 320), and the aim was to study the effect of high anti-Müllerian hormone (AMH) and testosterone on pregnancy complications. The third study (n = 138 219) explored whether the association between PCOS and preeclampsia depends on treated clinical hyperandrogenism and whether PCOS is associated with different subtypes of preeclampsia. In the fourth study (n = 281 806), the aim was to explore association and risk estimates for pregnancy outcomes in women with either or both PCOS and gestational diabetes mellitus (GDM). The main results were that women with PCOS have higher levels of AMH and testosterone and a higher free androgen index during second trimester pregnancy than non-PCOS controls. High AMH levels were not associated with adverse pregnancy outcome or birthweight. PCOS women with the highest testosterone levels had the highest risk for preeclampsia. Compared to non-PCOS controls, women with PCOS have increased risk of preeclampsia, especially the more severe subtypes of preeclampsia, early onset or with a birth of an i

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals and are commonly found in everyday items. PFAS have been linked to disrupting glucose homeostasis, however, whether they are associated with gestational diabetes mellitus (GDM) risk remains inconclusive. We examined prospective associations of PFAS concentrations measured twice in pregnancy with GDM risk. METHODS: In the PETALS pregnancy cohort, a nested case-control study which included 41 GDM cases and 87 controls was conducted. PFAS analytes were measured in blood serum collected in both early and mid-pregnancy (mean [SD]: 13.9 [2.2] and 20.2 [2.2] gestational weeks, respectively), with cumulative exposure calculated by the area-under-the-curve (AUC) to integrate both the PFAS concentration and the timing of the exposure. Individual adjusted weighted unconditional logistic regression models examined seven PFAS in association with GDM risk. P-values were corrected using the false-discovery-rate (FDR). Mixture models were analyzed with Bayesian kernel machine regression (BKMR). RESULTS: PFDA, PFNA and PFOA were individually associated with higher GDM risk per interquartile range (IQR) in early pregnancy (OR [95% CI]: 1.23 [1.09, 1.38]), 1.40 [1.24, 1.58]), and 1.15 [1.04, 1.27], respectively), mid-pregnancy (1.28 [1.15, 1.43], 1.16 [1.05, 1.28], and 1.20 [1.09, 1.33], respectively), and with cumulative exposure (1.23 [1.09, 1.38], 1.21 [1.07, 1.37], and 1.19 [1.09, 1.31], respectively). PFOS in mid-pregnancy and with cumulative exposure was associated with increased GDM risk (1.41 [1.17, 1.71] and 1.33 [1.06, 1.58], respectively). PFUnDA in early pregnancy was associated with lower GDM risk (0.79 [0.64, 0.98]), whereas mid-pregnancy levels were associated with higher risk (1.49 [1.18, 1.89]). PFHxS was associated with decreased GDM risk in early and mid-pregnancy (0.48 [0.38, 0.60] and 0.48 [0.37, 0.63], respectively) and with cumulative exposure (0.49 [0.38,0.63]). PFPeA was

Aim: The aim of this study was to explore the perceptions of women with gestational diabetes mellitus (GDM) in Denmark, with a particular focus on GDM-specific stigma. Method: We conducted semi-structured interviews with 20 women with GDM from January to May 2022. All interviews were transcribed and analysed abductively using Braun and Clarke's framework for applied reflexive analysis. Results: Five themes were identified, 1) victim-blaming narrative, 2) identity threat, 3) non-disclosure and anticipated stigma, 4) stigma in a clinical setting, and 5) stigma reduction in a clinical setting. Additionally, intersectionality was identified between GDM-specific stigma, notions of how to be a good mother, and stigma associated with having type 2 diabetes mellitus and overweight. Implications of GDM-specific stigma included suboptimal GDM care and management, i.e., not attending screening for GDM, and not wanting to disclose the diagnosis. Conclusion: The impact of GDM-specific stigma on the informants’ lives included some informants not accepting all services provided by the healthcare system, and some not wanting to identify with the diagnosis. These findings may help inform both healthcare personnel and future health promotion interventions to minimize the reproduction of a victim-blaming narrative and thereby promote well-being among women with GDM.

Aim: The aim of this study was to explore the perceptions of women with gestational diabetes mellitus (GDM) in Denmark, with a particular focus on GDM-specific stigma. Method: We conducted semi-structured interviews with 20 women with GDM from January to May 2022. All interviews were transcribed and analysed abductively using Braun and Clarke's framework for applied reflexive analysis. Results: Five themes were identified, 1) victim-blaming narrative, 2) identity threat, 3) non-disclosure and anticipated stigma, 4) stigma in a clinical setting, and 5) stigma reduction in a clinical setting. Additionally, intersectionality was identified between GDM-specific stigma, notions of how to be a good mother, and stigma associated with having type 2 diabetes mellitus and overweight. Implications of GDM-specific stigma included suboptimal GDM care and management, i.e., not attending screening for GDM, and not wanting to disclose the diagnosis. Conclusion: The impact of GDM-specific stigma on the informants’ lives included some informants not accepting all services provided by the healthcare system, and some not wanting to identify with the diagnosis. These findings may help inform both healthcare personnel and future health promotion interventions to minimize the reproduction of a victim-blaming narrative and thereby promote well-being among women with GDM.

Risk for atherosclerotic cardiovascular disease (ASCVD) shows considerable heterogeneity both in generally healthy persons and in those with known ASCVD. The foundation of preventive cardiology begins with assessing baseline ASCVD risk using global risk scores based on standard office-based measures. Persons at low risk are generally recommended for lifestyle management only and those at highest risk are recommended for both lifestyle and pharmacologic therapy. Additional "risk enhancing" factors, including both traditional risk factors and novel biomarkers and inflammatory factors can be used to further assess ASCVD risk, especially in those at borderline or intermediate risk. There are also female-specific risk enhancers, social determinants of health, and considerations for high-risk ethnic groups. Screening for subclinical atherosclerosis, especially with the use of coronary calcium screening, can further inform the treatment decision if uncertain based on the above strategies. Persons with pre-existing ASCVD also have variable risk, affected by the number of major ASCVD events, whether recurrent events have occurred recently, and the presence of other major risk factors or high-risk conditions. Current guidelines define high to very high risk ASCVD accordingly. Accurate ASCVD risk assessment is crucial for the appropriate targeting of preventive therapies to reduce ASCVD risk. Finally, the clinician-patient risk discussion focusing on lifestyle management and the risks and benefits of evidence-based pharmacologic therapies to best lower ASCVD risk is central to this process. This clinical practice statement provides the preventive cardiology specialist with guidance and tools for assessment of ASCVD risk with the goal of appropriately targeting treatment approaches for prevention of ASCVD events.

Gestational diabetes mellitus (GDM) has serious consequences for both maternal and neonatal health. The growing number of noncommunicable diseases and related risk factors as well as the introduction of new World Health Organization (WHO) diagnostic criteria for GDM are likely to impact the GDM prevalence in Bangladesh. Our study aimed to assess the national prevalence and identify the risk factors using the most recent WHO criteria. We used the secondary data of 272 pregnant women (weighted for sampling strategy) from the Bangladesh Demographic and Health Survey 2017-2018. Multivariate logistic regression was performed to determine the risk factors of GDM. The overall prevalence of GDM in Bangladesh was 35% (95/272). Increased odds of GDM were observed among women living in the urban areas (adjusted odds ratio (aOR) 2.74, 95% confidence interval (CI) 1.43-5.27) compared to rural areas and those aged >= 25 years (aOR 2.03, 95% CI 1.13-3.65). GDM rates were less prevalent in the later weeks of pregnancy compared to early weeks. Our study demonstrates that the national prevalence of GDM in Bangladesh is very high, which warrants immediate attention of policy makers, health practitioners, public health researchers, and the community. Context-specific and properly tailored interventions are needed for the prevention and early diagnosis of GDM.

Gestational diabetes mellitus (GDM) has serious consequences for both maternal and neonatal health. The growing number of noncommunicable diseases and related risk factors as well as the introduction of new World Health Organization (WHO) diagnostic criteria for GDM are likely to impact the GDM prevalence in Bangladesh. Our study aimed to assess the national prevalence and identify the risk factors using the most recent WHO criteria. We used the secondary data of 272 pregnant women (weighted for sampling strategy) from the Bangladesh Demographic and Health Survey 2017-2018. Multivariate logistic regression was performed to determine the risk factors of GDM. The overall prevalence of GDM in Bangladesh was 35% (95/272). Increased odds of GDM were observed among women living in the urban areas (adjusted odds ratio (aOR) 2.74, 95% confidence interval (CI) 1.43-5.27) compared to rural areas and those aged >= 25 years (aOR 2.03, 95% CI 1.13-3.65). GDM rates were less prevalent in the later weeks of pregnancy compared to early weeks. Our study demonstrates that the national prevalence of GDM in Bangladesh is very high, which warrants immediate attention of policy makers, health practitioners, public health researchers, and the community. Context-specific and properly tailored interventions are needed for the prevention and early diagnosis of GDM.

Gestational diabetes mellitus (GDM) has serious consequences for both maternal and neonatal health. The growing number of noncommunicable diseases and related risk factors as well as the introduction of new World Health Organization (WHO) diagnostic criteria for GDM are likely to impact the GDM prevalence in Bangladesh. Our study aimed to assess the national prevalence and identify the risk factors using the most recent WHO criteria. We used the secondary data of 272 pregnant women (weighted for sampling strategy) from the Bangladesh Demographic and Health Survey 2017-2018. Multivariate logistic regression was performed to determine the risk factors of GDM. The overall prevalence of GDM in Bangladesh was 35% (95/272). Increased odds of GDM were observed among women living in the urban areas (adjusted odds ratio (aOR) 2.74, 95% confidence interval (CI) 1.43-5.27) compared to rural areas and those aged >= 25 years (aOR 2.03, 95% CI 1.13-3.65). GDM rates were less prevalent in the later weeks of pregnancy compared to early weeks. Our study demonstrates that the national prevalence of GDM in Bangladesh is very high, which warrants immediate attention of policy makers, health practitioners, public health researchers, and the community. Context-specific and properly tailored interventions are needed for the prevention and early diagnosis of GDM.

Risk for atherosclerotic cardiovascular disease (ASCVD) shows considerable heterogeneity both in generally healthy persons and in those with known ASCVD. The foundation of preventive cardiology begins with assessing baseline ASCVD risk using global risk scores based on standard office-based measures. Persons at low risk are generally recommended for lifestyle management only and those at highest risk are recommended for both lifestyle and pharmacologic therapy. Additional "risk enhancing" factors, including both traditional risk factors and novel biomarkers and inflammatory factors can be used to further assess ASCVD risk, especially in those at borderline or intermediate risk. There are also female-specific risk enhancers, social determinants of health, and considerations for high-risk ethnic groups. Screening for subclinical atherosclerosis, especially with the use of coronary calcium screening, can further inform the treatment decision if uncertain based on the above strategies. Persons with pre-existing ASCVD also have variable risk, affected by the number of major ASCVD events, whether recurrent events have occurred recently, and the presence of other major risk factors or high-risk conditions. Current guidelines define high to very high risk ASCVD accordingly. Accurate ASCVD risk assessment is crucial for the appropriate targeting of preventive therapies to reduce ASCVD risk. Finally, the clinician-patient risk discussion focusing on lifestyle management and the risks and benefits of evidence-based pharmacologic therapies to best lower ASCVD risk is central to this process. This clinical practice statement provides the preventive cardiology specialist with guidance and tools for assessment of ASCVD risk with the goal of appropriately targeting treatment approaches for prevention of ASCVD events.

Gestational diabetes mellitus (GDM) has serious consequences for both maternal and neonatal health. The growing number of noncommunicable diseases and related risk factors as well as the introduction of new World Health Organization (WHO) diagnostic criteria for GDM are likely to impact the GDM prevalence in Bangladesh. Our study aimed to assess the national prevalence and identify the risk factors using the most recent WHO criteria. We used the secondary data of 272 pregnant women (weighted for sampling strategy) from the Bangladesh Demographic and Health Survey 2017-2018. Multivariate logistic regression was performed to determine the risk factors of GDM. The overall prevalence of GDM in Bangladesh was 35% (95/272). Increased odds of GDM were observed among women living in the urban areas (adjusted odds ratio (aOR) 2.74, 95% confidence interval (CI) 1.43-5.27) compared to rural areas and those aged >= 25 years (aOR 2.03, 95% CI 1.13-3.65). GDM rates were less prevalent in the later weeks of pregnancy compared to early weeks. Our study demonstrates that the national prevalence of GDM in Bangladesh is very high, which warrants immediate attention of policy makers, health practitioners, public health researchers, and the community. Context-specific and properly tailored interventions are needed for the prevention and early diagnosis of GDM.

Background: The high-temperature requirement A 1 (HtrA1) is a multidomain secretory protein with serine-protease activity, expressed in many tissues, including placenta, where its expression is higher in the first trimester, suggesting an association of this serine protease in early phases of human placenta development. In this study, we evaluated maternal serum HtrA1 levels in the first and third trimester of gestation. In particular, we evaluated a possible role of HtrA1 as an early marker of gestational diabetes mellitus (GDM) in the first trimester of gestation. Methods: We evaluated HtrA1 serum levels in the third trimester (36-40 weeks) in normal pregnancies (n = 20) and GDM pregnancies (n = 20) by using ELISA analysis. Secondly, we performed the same analysis by using the first trimester sera (10-12 weeks) of healthy pregnant women that will develop a normal pregnancy (n = 210) or GDM (n = 28) during pregnancy. Results: We found that HtrA1 serum levels in the third trimester were higher in pregnancies complicated by GDM. Interestingly, higher HtrA1 serum levels were also found in the first trimester in women developing GDM later during the second-third trimester. No significant differences in terms of maternal age and gestational age were found between cases and controls. Women with GDM shown significantly higher pre-pregnancy BMI values compared to controls. Moreover, the probability of GDM occurrence significantly increased with increasing HtrA1 levels and BMI values. The ROC curve showed a good accuracy in predicting GDM, with an AUC of 0.74 (95%CI: 0.64-0.92). Conclusions: These results suggest an important role of HtrA1 as an early predictive marker of GDM in the first trimester of gestation, showing a significative clinical relevance for prevention of this disease.

In 2020, the global health emergency situation accelerated companies’ digital transformation process. Digital channels became a fundamental aspect for managing relationships with their customers and stakeholders, so rethinking of structures and channel management requires more in-depth knowledge. This research analyses and explores the impact of digital channels in strategies of SMEs. The study is conducted on Italian medium-sized enterprises, also known as ‘micro-multinationals’ or ‘pocket multinationals’, considering the key industries that are part of the Made in Italy brand. The research investigates how marketing channels are transforming in Italian SMEs through impact of digital channels in terms of benefits and limits that influence direct and indirect marketing channels as well as how new technologies will impact the transformation of marketing channels in Italian SMEs. The grounded Delphi method is applied, combining aspects of the grounded theory with the Delphi method to explore current needs and future ones in perspective.

Gestational diabetes mellitus (GDM) has serious consequences for both maternal and neonatal health. The growing number of noncommunicable diseases and related risk factors as well as the introduction of new World Health Organization (WHO) diagnostic criteria for GDM are likely to impact the GDM prevalence in Bangladesh. Our study aimed to assess the national prevalence and identify the risk factors using the most recent WHO criteria. We used the secondary data of 272 pregnant women (weighted for sampling strategy) from the Bangladesh Demographic and Health Survey 2017-2018. Multivariate logistic regression was performed to determine the risk factors of GDM. The overall prevalence of GDM in Bangladesh was 35% (95/272). Increased odds of GDM were observed among women living in the urban areas (adjusted odds ratio (aOR) 2.74, 95% confidence interval (CI) 1.43-5.27) compared to rural areas and those aged >= 25 years (aOR 2.03, 95% CI 1.13-3.65). GDM rates were less prevalent in the later weeks of pregnancy compared to early weeks. Our study demonstrates that the national prevalence of GDM in Bangladesh is very high, which warrants immediate attention of policy makers, health practitioners, public health researchers, and the community. Context-specific and properly tailored interventions are needed for the prevention and early diagnosis of GDM.

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003–2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother’s residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM2.5 and NO2 exposures and the metabolic outcomes. Though not statistically significant, high PM2.5 exposure (≥25 µg/m3) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO2 exposure (≥39.8 µg/m3) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy.

Pistachio nuts are a nutrient-dense source of good quality plant protein, commonly consumed as a minimally processed snack food or ingredient. The present paper is based on a symposium held during the 13th FENS (Federation of European Nutrition Societies) 2019 conference in Dublin that explored recent research and practical applications of pistachios as a plant-based snack, in particular, for appetite control and healthy weight management; and for glycaemic control during pregnancy. Individual nut types, whilst similar in nutritional composition, have unique characteristics which may have a significant impact on potential health effects. Recognising this, the further purpose here is to explore future research needs for pistachios, based on work completed to date and the discussion that ensued among researchers at this event, in order to advance the full scope of health benefits from pistachios, in particular, taking into account of both sustainability and nutritional health.

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003–2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother’s residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM2.5 and NO2 exposures and the metabolic outcomes. Though not statistically significant, high PM2.5 exposure (≥25 µg/m3) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO2 exposure (≥39.8 µg/m3) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy.

Pistachio nuts are a nutrient-dense source of good quality plant protein, commonly consumed as a minimally processed snack food or ingredient. The present paper is based on a symposium held during the 13th FENS (Federation of European Nutrition Societies) 2019 conference in Dublin that explored recent research and practical applications of pistachios as a plant-based snack, in particular, for appetite control and healthy weight management; and for glycaemic control during pregnancy. Individual nut types, whilst similar in nutritional composition, have unique characteristics which may have a significant impact on potential health effects. Recognising this, the further purpose here is to explore future research needs for pistachios, based on work completed to date and the discussion that ensued among researchers at this event, in order to advance the full scope of health benefits from pistachios, in particular, taking into account of both sustainability and nutritional health.

Despite extensive study, the role of air pollution in gestational diabetes remains unclear, and there is limited evidence of the beneficial impact of residential greenness on metabolic dysfunction during pregnancy. We used data from mothers in the Spanish INfancia y Medio Ambiente (INMA) Project from 2003–2008. We obtained spatiotemporally resolved estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) exposures in early pregnancy and estimated residential greenness using satellite-based Normal Difference Vegetation Index (NDVI) within 100, 300 and 500 m buffers surrounding the mother’s residence. We applied logistic regression models to evaluate associations between each of the three exposures of interest and (a) glucose intolerance and (b) abnormal lipid levels. We found limited evidence of associations between increases in PM2.5 and NO2 exposures and the metabolic outcomes. Though not statistically significant, high PM2.5 exposure (≥25 µg/m3) was associated with increased odds of glucose intolerance (OR = 1.16, 95% CI: 0.82, 1.63) and high cholesterol (OR = 1.14, 95% CI: 0.90, 1.44). High NO2 exposure (≥39.8 µg/m3) was inversely associated with odds of high triglycerides (OR = 0.70, 95% CI: 0.45, 1.08). Whereas NDVI was not associated with glucose intolerance, odds of high triglycerides were increased, although the results were highly imprecise. Results were unchanged when the air pollutant variables were included in the regression models. Given the equivocal findings in our study, additional investigations are needed to assess effects of air pollution and residential greenness on metabolic dysfunction during pregnancy.

[Abstract] Aim: To understand spatial-temporal changes (beta-diversity) in coastal communities and their drivers in the context of climate change. Coastal ecosystems are extremely exposed and dynamic, where changes in seaweed assemblages have been associated with changing water temperatures. However, at local scale, the effects of changes in the upwelling events and related stressors seek further exploration. Location: Galicia rías, North West of the Iberian Peninsula. Methods: Using data collected in 42 sampling localities in Galicia rias and over two time periods (1998 and 2014), we analysed changes in the seaweed community's composition through time and space. We calculated the temporal beta-diversity index and spatial beta-diversity as the pairwise composition differences between sampling localities. We use generalized dissimilarity models, to identify local environmental drivers of spatial and temporal beta-diversity. Results: We found a significant change in seaweed communities of Galicia rias, between 1998 and 2014 (temporal beta-diversity). They were mostly related to species loss rather than to species replacement. The dissimilarity among localities (spatial beta-diversity) was significantly higher in 2014 than in 1998. Nitrate concentration was consistently predicted as the main driver of both temporal and spatial beta-diversity patterns. Main conclusions: Unlike other studies in marine ecosystems, our results suggest that observed changes in the structure of perennial seaweed assemblages in Galicia Rias might lead to a local biotic heterogenization, indirectly linked to climate change through changes in nutrients availability and the upwelling intensity. Changes in Galicia seaweed communities call scientific attention to the importance of local stressors in climate change studies.

Gestational diabetes mellitus is one of the common problem during pregnancy due to altered life style  and diet pattern. Prevalence of GDM has been greatly increased since 10 yrs, in which 90% of diabetes  in pregnant women is gestational and 10% is pre gestational. Healthy state of pregnancy could be  possible by adopting Garbhadhana vidhi. Garbhini paricharya. Further samsodhana followed by  rasayana, vajikarana as a part of Garbhadhana vidhi prevents possibilities of different ailments during  pregnancy. Similarly, Garbhini paricharya that includes aahara, vihara, oushadha prescribed with  monthly variations may also prevent several ailments during pregnancy. Any violations in the said  regimen may lead to Atiyoga, Ayoga and Mithya yoga resulting in to diseases such as madhumeha particularly santarpana janya vikara and aavaranajanya madhumeha. In Madhu kosa vyakhya, it is  explained that women with irregular menstruation are more prone to diabetes in their future pregnancy.Concept of Asta vidha aahara vishesha ayatana also plays a role in prevention of diabetes. Aahara  vidhi also varies from sthula pramehi to krusha pramehi. viharas such as yoga and pranayama during pregnancy helps to reduce anxiety and endocrine measures. Finally, there is need to adopt for safer  management of GDM through Ayurvedic principles.  &nbsp

The study aims to analyze the association between gestational diabetes mellitus (GDM) and other risk factors of cesarean delivery using machine learning (ML). The dataset used for the analysis is from the pregnancy risk assessment survey (PRAMS), considered in two scenarios, i.e., all the data is taken, and all the data of the women who developed GDM. Further, the data is developed in two groups Data-I and Data-II by considering multiparous and primiparous women details, respectively. The correlation analysis and major classification algorithms are applied to the data. It is founded that the top risk factors for the first time cesarean delivery are the age, height, weight, race of the women, presence of hypertension and gestational diabetes mellitus. The major risk factor for repeated cesarean delivery is the previous cesarean delivery. The presence of GDM is also one of the risk factors for cesarean delivery.

Gestational diabetes Mellitus (GDM), a condition involving abnormal levels of glucose in the blood plasma has seen a rapid surge amongst the gestating mothers belonging to different regions and ethnicities around the world. Cur- rent method of screening and diagnosing GDM is restricted to Oral Glucose Tolerance Test (OGTT). With the advent of machine learning algorithms, the healthcare has seen a surge of machine learning methods for disease diag- nosis which are increasingly being employed in a clinical setup. Yet in the area of GDM, there has not been wide spread utilization of these algorithms to generate multi-parametric diagnostic models to aid the clinicians for the aforementioned condition diagnosis.In literature, there is an evident scarcity of application of machine learn- ing algorithms for the GDM diagnosis. It has been limited to the proposed use of some very simple algorithms like logistic regression. Hence, we have attempted to address this research gap by employing a wide-array of machine learning algorithms, known to be effective for binary classification, for GDM classification early on amongst gestating mother. This can aid the clinicians for early diagnosis of GDM and will offer chances to mitigate the adverse out- comes related to GDM among the gestating mother and their progeny.We set up an empirical study to look into the performance of different ma- chine learning algorithms used specifically for the task of GDM classification. These algorithms were trained on a set of chosen predictor variables by the ex- perts. Then compared the results with the existing machine learning methods in the literature for GDM classification based on a set of performance metrics. Our model couldn’t outperform the already proposed machine learning mod- els for GDM classification. We could attribute it to our chosen set of predictor variable and the under reporting of various performance metrics like precision in the existing literature leading to a lack of informed, Graviditetsdiabetes Mellitus (GDM), ett tillstånd som involverar onormala ni- våer av glukos i blodplasma har haft en snabb kraftig ökning bland de drab- bade mammorna som tillhör olika regioner och etniciteter runt om i världen. Den nuvarande metoden för screening och diagnos av GDM är begränsad till Oralt glukosetoleranstest (OGTT). Med tillkomsten av maskininlärningsalgo- ritmer har hälso- och sjukvården sett en ökning av maskininlärningsmetoder för sjukdomsdiagnos som alltmer används i en klinisk installation. Ändå inom GDM-området har det inte använts stor spridning av dessa algoritmer för att generera multiparametriska diagnostiska modeller för att hjälpa klinikerna för ovannämnda tillståndsdiagnos.I litteraturen finns det en uppenbar brist på tillämpning av maskininlär- ningsalgoritmer för GDM-diagnosen. Det har begränsats till den föreslagna användningen av några mycket enkla algoritmer som logistisk regression. Där- för har vi försökt att ta itu med detta forskningsgap genom att använda ett brett spektrum av maskininlärningsalgoritmer, kända för att vara effektiva för binär klassificering, för GDM-klassificering tidigt bland gesterande mamma. Det- ta kan hjälpa klinikerna för tidig diagnos av GDM och kommer att erbjuda chanser att mildra de negativa utfallen relaterade till GDM bland de dödande mamma och deras avkommor.Vi inrättade en empirisk studie för att undersöka prestandan för olika ma- skininlärningsalgoritmer som används specifikt för uppgiften att klassificera GDM. Dessa algoritmer tränades på en uppsättning valda prediktorvariabler av experterna. Jämfört sedan resultaten med de befintliga maskininlärnings- metoderna i litteraturen för GDM-klassificering baserat på en uppsättning pre- standametriker. Vår modell kunde inte överträffa de redan föreslagna maskininlärningsmodellerna för GDM-klassificering. Vi kunde tillskriva den valda uppsättningen prediktorvariabler och underrapportering av olika prestanda- metriker som precision i befintlig litterat

This thesis involved three interrelated studies examining the management of gestational diabetes. Health care professionals in Queensland and Australia were surveyed, Queensland pregnancy data was used to understand how changing the screening and diagnostic recommendations have impacted mothers and their infants, and a dietitian-led model of care was developed, implemented and evaluated to improve the management of gestational diabetes. Australian clinicians lack a consistent approach for gestational diabetes management and changing the diagnostic criteria does not appear to have improved important maternal and infant outcomes. A dietitian-led model of care is a feasible way to manage women with gestational diabetes.

Aims/hypothesis: The aim of this work was to examine the progression to type 1 and type 2 diabetes after gestational diabetes mellitus (GDM) in a 23 year follow-up study. Methods: We carried out a cohort study of 391 women with GDM diagnosed by an OGTT or the use of insulin treatment during pregnancy, and 391 age- and parity-matched control participants, who delivered in 1984–1994 at the Oulu University Hospital, Finland. Diagnostic cut-off levels for glucose were as follows: fasting, ≥4.8 mmol/l; 1 h, ≥10.0 mmol/l; and 2 h, ≥8.7 mmol/l. Two follow-up questionnaires were sent (in 1995–1996 and 2012–2013) to assess the progression to type 1 and type 2 diabetes. Mean follow-up time was 23.1 (range 18.7–28.8) years. Results: Type 1 diabetes developed (5.7%) during the first 7 years after GDM pregnancy and was predictable at a 2 h OGTT value of 11.9 mmol/l during pregnancy (receiver operating characteristic analysis: AUC 0.91, sensitivity 76.5%, specificity 96.0%). Type 2 diabetes increased linearly to 50.4% by the end of the follow-up period and was moderately predictable with fasting glucose (AUC 0.69, sensitivity 63.5%, specificity 68.2%) at a level of 5.1 mmol/l (identical to the fasting glucose cut-off recommended by the International Association of Diabetes and Pregnancy Study Groups [IADPSG) and WHO]). Conclusions/interpretation: All women with GDM should be intensively monitored for a decade, after which the risk for type 1 diabetes is minimal. However, the incidence of type 2 diabetes remains linear, and therefore individualised lifelong follow-up is recommended.

Gestational diabetes Mellitus (GDM), a condition involving abnormal levels of glucose in the blood plasma has seen a rapid surge amongst the gestating mothers belonging to different regions and ethnicities around the world. Cur- rent method of screening and diagnosing GDM is restricted to Oral Glucose Tolerance Test (OGTT). With the advent of machine learning algorithms, the healthcare has seen a surge of machine learning methods for disease diag- nosis which are increasingly being employed in a clinical setup. Yet in the area of GDM, there has not been wide spread utilization of these algorithms to generate multi-parametric diagnostic models to aid the clinicians for the aforementioned condition diagnosis.In literature, there is an evident scarcity of application of machine learn- ing algorithms for the GDM diagnosis. It has been limited to the proposed use of some very simple algorithms like logistic regression. Hence, we have attempted to address this research gap by employing a wide-array of machine learning algorithms, known to be effective for binary classification, for GDM classification early on amongst gestating mother. This can aid the clinicians for early diagnosis of GDM and will offer chances to mitigate the adverse out- comes related to GDM among the gestating mother and their progeny.We set up an empirical study to look into the performance of different ma- chine learning algorithms used specifically for the task of GDM classification. These algorithms were trained on a set of chosen predictor variables by the ex- perts. Then compared the results with the existing machine learning methods in the literature for GDM classification based on a set of performance metrics. Our model couldn’t outperform the already proposed machine learning mod- els for GDM classification. We could attribute it to our chosen set of predictor variable and the under reporting of various performance metrics like precision in the existing literature leading to a lack of informed, Graviditetsdiabetes Mellitus (GDM), ett tillstånd som involverar onormala ni- våer av glukos i blodplasma har haft en snabb kraftig ökning bland de drab- bade mammorna som tillhör olika regioner och etniciteter runt om i världen. Den nuvarande metoden för screening och diagnos av GDM är begränsad till Oralt glukosetoleranstest (OGTT). Med tillkomsten av maskininlärningsalgo- ritmer har hälso- och sjukvården sett en ökning av maskininlärningsmetoder för sjukdomsdiagnos som alltmer används i en klinisk installation. Ändå inom GDM-området har det inte använts stor spridning av dessa algoritmer för att generera multiparametriska diagnostiska modeller för att hjälpa klinikerna för ovannämnda tillståndsdiagnos.I litteraturen finns det en uppenbar brist på tillämpning av maskininlär- ningsalgoritmer för GDM-diagnosen. Det har begränsats till den föreslagna användningen av några mycket enkla algoritmer som logistisk regression. Där- för har vi försökt att ta itu med detta forskningsgap genom att använda ett brett spektrum av maskininlärningsalgoritmer, kända för att vara effektiva för binär klassificering, för GDM-klassificering tidigt bland gesterande mamma. Det- ta kan hjälpa klinikerna för tidig diagnos av GDM och kommer att erbjuda chanser att mildra de negativa utfallen relaterade till GDM bland de dödande mamma och deras avkommor.Vi inrättade en empirisk studie för att undersöka prestandan för olika ma- skininlärningsalgoritmer som används specifikt för uppgiften att klassificera GDM. Dessa algoritmer tränades på en uppsättning valda prediktorvariabler av experterna. Jämfört sedan resultaten med de befintliga maskininlärnings- metoderna i litteraturen för GDM-klassificering baserat på en uppsättning pre- standametriker. Vår modell kunde inte överträffa de redan föreslagna maskininlärningsmodellerna för GDM-klassificering. Vi kunde tillskriva den valda uppsättningen prediktorvariabler och underrapportering av olika prestanda- metriker som precision i befintlig litterat

Rationale: The incidence of gestational diabetes mellitus (GDM) is increasing worldwide. However, whether and how GDM exposure induces fetal programming of adult cardiac dysfunctional phenotype, especially the underlying epigenetic molecular mechanisms and theranostics remain unclear. To address this problem, we developed a late GDM rat model. Methods: Pregnant rats were made diabetic on day 12 of gestation by streptozotocin (STZ). Experiments were conducted in 6 weeks old offspring. Results: There were significant increases in ischemia-induced cardiac infarction and gender-dependent left ventricular (LV) dysfunction in male offspring in GDM group as compared to controls. Exposure to GDM enhanced ROS level and caused a global DNA methylation in offspring cardiomyocytes. GDM attenuated cardiac Sirt 1 protein and p-Akt/Akt levels, but enhanced autophagy-related proteins expression (Atg 5 and LC3 II/LC3 I) as compared to controls. Ex-vivo treatment of DNA methylation inhibitor, 5-Aza directly inhibited Dnmt3A and enhanced Sirt 1 protein expression in fetal hearts. Furthermore, treatment with antioxidant, N-acetyl-cysteine (NAC) in offspring reversed GDM-mediated DNA hypermethylation, Sirt1 repression and autophagy-related gene protein overexpression in the hearts, and rescued GDM-induced deterioration in heart ischemic injury and LV dysfunction. Conclusion: Our data indicated that exposure to GDM induced offspring cardiac oxidative stress and DNA hypermethylation, resulting in an epigenetic down-regulation of Sirt1 gene and aberrant development of heart ischemia-sensitive phenotype, which suggests that Sirt 1-mediated signaling is the potential therapeutic target for the heart ischemic disease in offspring.

Purpose:Neonates born to mothers with obesity or gestational diabetes mellitus (GDM) have an increased chance of various metabolic disorders later in life. In India, it is unclear whether maternal obesity or GDM is related to offspring adiposity. We aimed to understand the independent effect of maternal obesity and GDM with neonatal adiposity and whether GDM has a mediating effect between maternal obesity and neonatal adiposity. Methods:We recruited a cohort of 1120 women (between April 2016 and February 2019) from the public hospitals in Bangalore, India, who voluntarily agreed to participate and provided written informed consent. The primary outcome was neonatal adiposity, defined as the sum of skinfold thickness >85th percentile. Exposure included maternal obesity, defined as >90th percentile of skinfold thickness. GDM, the potential mediator, was classified using the World Health Organization criteria by oral glucose tolerance test. Binary logistic regression was applied to test the effect of maternal obesity and GDM on neonatal adiposity, adjusting for potential confounders. We used Paramed command in STATA version 14 for analyzing mediating effects. Results:We found that maternal obesity (odds ratio (OR)=2.16, 95% CI 1.46, 3.18) and GDM (OR=2.21, 95% CI1.38, 3.52) have an independent effect on neonatal adiposity. GDM significantly mediates 25.2% of the total effect between maternal obesity and neonatal adiposity, (natural direct effect OR = 1.16 95% CI 1.04, 1.30) with significant direct effect of maternal obesity (natural direct effect OR = 1.90 95% CI 1.16, 3.10) and significant total effect (OR=2.20 95% CI 1.35, 3.58). Conclusion:We showed that maternal obesity and GDM are independently associated with offspring adiposity. Also, GDM mediates the association of maternal obesity on adiposity in children. Interventions focused on obesity prevention in women, and effective screening and management of GDM may contribute to reducing childhood obesity in Ind

We conducted a qualitative study to explore the risk perceptions, health beliefs and behaviours of women with a previous history of gestational diabetes mellitus (GDM). Women aged between 18 to 40 years (at the time of pregnancy) with a previous history of GDM, registered at The Royal Liverpool University Hospital, United Kingdom, participated in individual, semi-structured, face-to-face interviews. Qualitative data from seven participants were collected until data saturation and were analysed by thematic analysis. Participants had a low-risk perception of the future risk of developing diabetes. Some believed that their risk was the same as that of any other woman without a history of GDM, and some other participants were not aware of the risk at all and perceived GDM as a temporary health condition with no long-term risks. Participants showed some understanding of a healthy lifestyle in general. However, most of the information was self-acquired by participants and not linked to the future risk of developing diabetes. The findings of this research also indicated a contrast between the high perception of the immediate risks of complications during the pregnancy and low long-term risk of developing diabetes after pregnancy associated with GDM. Participants received healthy lifestyle advice during their pregnancy, but none of them reported involvement in any postnatal health education, intervention or counselling as recommended by 2008 and 2014 NICE guidelines. The low-risk perception impedes positive health behaviour required to overcome the barriers against a healthy lifestyle. This was a small research project but the findings warrant scope for more research in this field. A larger study might promote the development of a well-structured, long-term follow-up health intervention programme, incorporating a reminder system for annual diabetes screenings to improve the risk perception and reduce the risk for the development of type 2 diabetes in this population.

Rationale: The incidence of gestational diabetes mellitus (GDM) is increasing worldwide. However, whether and how GDM exposure induces fetal programming of adult cardiac dysfunctional phenotype, especially the underlying epigenetic molecular mechanisms and theranostics remain unclear. To address this problem, we developed a late GDM rat model. Methods: Pregnant rats were made diabetic on day 12 of gestation by streptozotocin (STZ). Experiments were conducted in 6 weeks old offspring. Results: There were significant increases in ischemia-induced cardiac infarction and gender-dependent left ventricular (LV) dysfunction in male offspring in GDM group as compared to controls. Exposure to GDM enhanced ROS level and caused a global DNA methylation in offspring cardiomyocytes. GDM attenuated cardiac Sirt 1 protein and p-Akt/Akt levels, but enhanced autophagy-related proteins expression (Atg 5 and LC3 II/LC3 I) as compared to controls. Ex-vivo treatment of DNA methylation inhibitor, 5-Aza directly inhibited Dnmt3A and enhanced Sirt 1 protein expression in fetal hearts. Furthermore, treatment with antioxidant, N-acetyl-cysteine (NAC) in offspring reversed GDM-mediated DNA hypermethylation, Sirt1 repression and autophagy-related gene protein overexpression in the hearts, and rescued GDM-induced deterioration in heart ischemic injury and LV dysfunction. Conclusion: Our data indicated that exposure to GDM induced offspring cardiac oxidative stress and DNA hypermethylation, resulting in an epigenetic down-regulation of Sirt1 gene and aberrant development of heart ischemia-sensitive phenotype, which suggests that Sirt 1-mediated signaling is the potential therapeutic target for the heart ischemic disease in offspring.

PurposeNeonates born to mothers with obesity or gestational diabetes mellitus (GDM) have an increased chance of various metabolic disorders later in life. In India, it is unclear whether maternal obesity or GDM is related to offspring adiposity. We aimed to understand the independent effect of maternal obesity and GDM with neonatal adiposity and whether GDM has a mediating effect between maternal obesity and neonatal adiposity.MethodsWe recruited a cohort of 1120 women (between April 2016 and February 2019) from the public hospitals in Bangalore, India, who voluntarily agreed to participate and provided written informed consent. The primary outcome was neonatal adiposity, defined as the sum of skinfold thickness >85th percentile. Exposure included maternal obesity, defined as >90th percentile of skinfold thickness. GDM, the potential mediator, was classified using the World Health Organization criteria by oral glucose tolerance test. Binary logistic regression was applied to test the effect of maternal obesity and GDM on neonatal adiposity, adjusting for potential confounders. We used Paramed command in STATA version 14 for analyzing mediating effects.ResultsWe found that maternal obesity (odds ratio (OR)=2.16, 95% CI 1.46, 3.18) and GDM (OR=2.21, 95% CI1.38, 3.52) have an independent effect on neonatal adiposity. GDM significantly mediates 25.2% of the total effect between maternal obesity and neonatal adiposity, (natural direct effect OR = 1.16 95% CI 1.04, 1.30) with significant direct effect of maternal obesity (natural direct effect OR = 1.90 95% CI 1.16, 3.10) and significant total effect (OR=2.20 95% CI 1.35, 3.58).ConclusionWe showed that maternal obesity and GDM are independently associated with offspring adiposity. Also, GDM mediates the association of maternal obesity on adiposity in children. Interventions focused on obesity prevention in women, and effective screening and management of GDM may contribute to reducing childhood obesity in India.

We conducted a qualitative study to explore the risk perceptions, health beliefs and behaviours of women with a previous history of gestational diabetes mellitus (GDM). Women aged between 18 to 40 years (at the time of pregnancy) with a previous history of GDM, registered at The Royal Liverpool University Hospital, United Kingdom, participated in individual, semi-structured, face-to-face interviews. Qualitative data from seven participants were collected until data saturation and were analysed by thematic analysis. Participants had a low-risk perception of the future risk of developing diabetes. Some believed that their risk was the same as that of any other woman without a history of GDM, and some other participants were not aware of the risk at all and perceived GDM as a temporary health condition with no long-term risks. Participants showed some understanding of a healthy lifestyle in general. However, most of the information was self-acquired by participants and not linked to the future risk of developing diabetes. The findings of this research also indicated a contrast between the high perception of the immediate risks of complications during the pregnancy and low long-term risk of developing diabetes after pregnancy associated with GDM. Participants received healthy lifestyle advice during their pregnancy, but none of them reported involvement in any postnatal health education, intervention or counselling as recommended by 2008 and 2014 NICE guidelines. The low-risk perception impedes positive health behaviour required to overcome the barriers against a healthy lifestyle. This was a small research project but the findings warrant scope for more research in this field. A larger study might promote the development of a well-structured, long-term follow-up health intervention programme, incorporating a reminder system for annual diabetes screenings to improve the risk perception and reduce the risk for the development of type 2 diabetes in this population.

AimsGestational diabetes mellitus (GDM) is a major risk factor for type 2 diabetes. The incidence of both GDM and type 2 diabetes is exceedingly high in South Asian populations. However, the risk of type 2 diabetes after GDM in South Asian women in the United States is unknown.MethodsSouth Asians aged 40 to 84 years without known cardiovascular disease were enrolled in a community-based cohort called Mediators of Atherosclerosis in South Asians Living in America study. A history of GDM was elicited through self-report, and type 2 diabetes was ascertained by an oral glucose tolerance test. We performed a multivariable logistic regression analysis to examine the odds of type 2 diabetes after GDM history in this cross-sectional analysis.ResultsAbout 9.7% of women in the Mediators of Atherosclerosis in South Asians Living in America study self-reported a history of GDM, and were significantly younger, with higher mean diastolic blood pressure and self-reported weight at age 20 and 40 years than women without a history of GDM. In a model adjusted for age, weight at age 40, family history of diabetes, education, income, physical activity, caloric intake, alcohol use, and cigarette smoking, women with a history of GDM had increased odds of having type 2 diabetes compared with women without GDM (OR 3.2; 95% CI 1.3, 7.5).ConclusionsA history of GDM further increases the risk of type 2 diabetes in US South Asian women. Our findings underscore the importance of early postpartum screening in a population at high risk for type 2 diabetes.

Aims: To investigate how glucose levels at diagnosis of gestational diabetes (GDM) are associated with infant birth weight and long-term risk of manifest diabetes mellitus in the mother. Methods: In a case control study GDM pregnancies (n = 2085) were compared with non-GDM pregnancies matched for day of delivery and obstetric unit (n = 3792). GDM was defined as capillary blood glucose (cB-glucose) >9.0 mmol/l (plasma glucose >10.0 mmol/l) after a 75 g oral glucose tolerance test (OGTT). The GDM cohort were followed up 8.5-13.5 yrs after initial diagnosis with a questionnaire, answered by 1324 GDM women (65%). Results: GDM women had higher mean infant birth-weight compared with controls (3682 g vs. 3541 g, P < 0.001). In multiple linear regression analysis, birth weight was positively correlated to fasting cB-glucose at GDM diagnosis (P < 0.001), increased week of gestation (P < 0.001) and BMI before pregnancy (P < 0.003), while 2 h OGTT cB-glucose values >= 9.0 mmol/l were not related. Infants born to mothers with fasting cB-glucose >= 4.5 mmol/l had no increased mean birth-weight or macrosomia (>= 4500 g) compared to controls. In the follow up 334/1324 women (25%) of the GDM women had developed diabetes, 215 type 2 diabetes, 46 type 1 diabetes and 72 unclassified diabetes. In logistic regression fasting cB-glucose and 2 h OGTT cB-glucose at diagnosis of GDM as well as BMI >25 and origin outside Europe were risk factors for manifest diabetes. Conclusions: Fasting blood glucose at diagnosis of GDM gives important information besides 2 h OGTT glucose about pregnancy outcome and future risk for maternal diabetes.

Aims: To investigate how glucose levels at diagnosis of gestational diabetes (GDM) are associated with infant birth weight and long-term risk of manifest diabetes mellitus in the mother. Methods: In a case control study GDM pregnancies (n = 2085) were compared with non-GDM pregnancies matched for day of delivery and obstetric unit (n = 3792). GDM was defined as capillary blood glucose (cB-glucose) >9.0 mmol/l (plasma glucose >10.0 mmol/l) after a 75 g oral glucose tolerance test (OGTT). The GDM cohort were followed up 8.5-13.5 yrs after initial diagnosis with a questionnaire, answered by 1324 GDM women (65%). Results: GDM women had higher mean infant birth-weight compared with controls (3682 g vs. 3541 g, P < 0.001). In multiple linear regression analysis, birth weight was positively correlated to fasting cB-glucose at GDM diagnosis (P < 0.001), increased week of gestation (P < 0.001) and BMI before pregnancy (P < 0.003), while 2 h OGTT cB-glucose values >= 9.0 mmol/l were not related. Infants born to mothers with fasting cB-glucose >= 4.5 mmol/l had no increased mean birth-weight or macrosomia (>= 4500 g) compared to controls. In the follow up 334/1324 women (25%) of the GDM women had developed diabetes, 215 type 2 diabetes, 46 type 1 diabetes and 72 unclassified diabetes. In logistic regression fasting cB-glucose and 2 h OGTT cB-glucose at diagnosis of GDM as well as BMI >25 and origin outside Europe were risk factors for manifest diabetes. Conclusions: Fasting blood glucose at diagnosis of GDM gives important information besides 2 h OGTT glucose about pregnancy outcome and future risk for maternal diabetes.

AIMS: To investigate how glucose levels at diagnosis of gestational diabetes (GDM) are associated with infant birth weight and long-term risk of manifest diabetes mellitus in the mother. METHODS: In a case control study GDM pregnancies (n=2085) were compared with non-GDM pregnancies matched for day of delivery and obstetric unit (n=3792). GDM was defined as capillary blood glucose (cB-glucose) ≥9.0mmol/l (plasma glucose ≥10.0mmol/l) after a 75g oral glucose tolerance test (OGTT). The GDM cohort were followed up 8.5-13.5yrs after initial diagnosis with a questionnaire, answered by 1324 GDM women (65%). RESULTS: GDM women had higher mean infant birth-weight compared with controls (3682g vs. 3541g, P<0.001). In multiple linear regression analysis, birth weight was positively correlated to fasting cB-glucose at GDM diagnosis (P<0.001), increased week of gestation (P<0.001) and BMI before pregnancy (P<0.003), while 2h OGTT cB-glucose values ≥9.0mmol/l were not related. Infants born to mothers with fasting cB-glucose ≤4.5mmol/l had no increased mean birth-weight or macrosomia (≥4500g) compared to controls. In the follow up 334/1324 women (25%) of the GDM women had developed diabetes, 215 type 2 diabetes, 46 type 1 diabetes and 72 unclassified diabetes. In logistic regression fasting cB-glucose and 2h OGTT cB-glucose at diagnosis of GDM as well as BMI >25 and origin outside Europe were risk factors for manifest diabetes. CONCLUSIONS: Fasting blood glucose at diagnosis of GDM gives important information besides 2h OGTT glucose about pregnancy outcome and future risk for maternal diabetes.

Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis and a simulation of oceanic islands. Methods: We describe the causal relationships between evolutionary and ecological processes implied by the GDM, implement them as a computer simulation and use this to simulate two alternative geological scenarios. Results: The dynamics of species richness and rates of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity of evolutionary dynamics to attributes of island geology. Main conclusions: We argue that the GDM of oceanic island biogeography has the potential to provide a unified framework for island biogeography, integrating geological, ecological and evolutionary processes. Our simulations highlight how the geological dynamics of distinct island types are predicted to lead to markedly different evolutionary dynamics. This sets the stage for a more predictive theory incorporating the processes governing temporal dynamics of species diversity on islands.

Résumé : L’aggravation de certaines caractéristiques cliniques des femmes enceintes (âge, poids) et l’augmentation de la prévalence du diabète gestationnel (DG) poussent à dépister le DG le plus tôt possible pour éviter chez la mère et le fœtus les complications à court et à long terme. Le dépistage du DG est recommandé à 24-28 semaines de grossesse, et le plus souvent un test de tolérance à 50g de glucose (TTG) est réalisé. Pour les femmes qui ont des facteurs de risque, ce test doit être effectué plus précocement, habituellement pendant le premier trimestre de la grossesse. Cette dernière recommandation est peu suivie, d’autant qu’il n’y a pas de consensus international sur le dépistage du DG pendant le premier trimestre de la grossesse. Objectifs. 1) Définir au premier trimestre de la grossesse la valeur de la glycémie du TTG qui prédit le diagnostic de DG à 24-28 semaines avec une sensibilité et une spécificité optimales à l’aide d’une courbe ROC. 2) Déterminer si la glycémie du TTG au premier trimestre est un facteur prédictif indépendant du DG. Méthodes. Étude prospective de cohorte. Les facteurs d'inclusion étaient : âge ≥ 18 ans et âge gestationnel entre 6 et 13 semaines après la dernière menstruation. Les TTG ont été effectués à la première visite prénatale. Une deuxième visite était programmée à 24-28 semaines pour faire une hyperglycémie provoquée par voie orale (HGPO) et donc un éventuel diagnostic de DG. Les critères utilisés pour ce diagnostic étaient ceux de l’Association américaine du diabète. Résultats. Les TTG ont été faits à 9,1±2,0 semaines et les HGPO à 26.5±1.1semaines chez 1180 femmes (28,2±4,4 ans, IMC : 25,2±5,5 kg/m[indice supérieur 2]). Un DG a été diagnostiqué chez 100 (8,4%) participantes. La valeur de glycémie du TTG à 5,6 mmol/L a prédit le DG avec une sensibilité de 84,1% et une spécificité de 62,3%, tandis que la valeur prédictive positive était de 0,121 et la valeur prédictive négative de 0,985. Cette valeur de 5,6 était indépendamm, The changes in clinical characteristics of pregnant women and an increase in the prevalence of gestational diabetes mellitus (GDM) warrant the importance of screening as early as possible in order to possibly prevent short and long-term complications in both the mother and fetus. GDM screening is recommended at 24-28 weeks of pregnancy, using a 50g glucose challenge test (GCT) although women with multiple risk factors are expected to be assessed “early” in pregnancy, a recommendation poorly followed. Most importantly, there is no universal agreement currently in place for GDM screening, particularly during the first trimester of pregnancy. Objectives. 1) To define the cut-off value of GCT during the first trimester in order to predict GDM diagnosed at 24-28 weeks of gestation with optimal sensitivity and specificity using ROC curve. 2) To determine if GCT during the first trimester of pregnancy is an independent predictor of GDM diagnosed at 24-28 weeks gestation. Methods. This is a prospective cohort study. Women were recruited at their first prenatal visit. Inclusion factors were: age ≥ 18 years and gestational age between 6 and 13 weeks from their last menstrual period. GCT were performed at the first prenatal visit. The second visit was scheduled at 24-28 weeks for the diagnostic 75g oral glucose tolerance test (OGTT). GDM diagnosis was made in accordance with the American Diabetes Association guidelines. A variety of statistical analysis including multivariate logistic regression models and ROC curve were used to address the aims of the study. Results. Participants (n=1180, age: 28.2±4.4 years, BMI: 25.2±5.5 kg/m[superscript 2]) underwent GCT at 9.1±2.0 weeks and OGTT at 26.5±1.1 weeks of gestation. GDM was diagnosed in 100 (8.4%) women. The cut-off value of 5.6 mmol/L predicted GDM with 84.1% (75.4-92.7) sensitivity, 62.3% (59.5-65.1) specificity, while the positive predictive value was 0.121 (0.091-0.150) and the negative predictive value was 0.985

Gestational diabetes mellitus (GDM) is related to neonatal macrosomia and an increased risk of vascular events. We hypothesized that GDM exerts qualitative effects on neonatal high-density lipoprotein (HDL). HDL was isolated from control (n = 11) and GDM maternal/neonatal donors (n = 9) and subjected to shotgun proteomics. Differences in HDL mobility were assessed by FPLC and native gel-electrophoresis. Paraoxonase (PON1) activity, cholesterol ester-transfer protein (CETP) mass and activity, phospholipid, triglyceride and cholesterol concentrations were quantified with commercial kits. Total anti-oxidative capacity and cholesterol efflux capability of HDLs were measured. Four proteins involved in lipid metabolism, inflammation and innate immunity were differentially expressed between controls and GDM neonates. ApoM (decreased, p lt 0.05) and SAA1 (increased, p lt 0.05) showed the same differences on both, maternal and neonatal GDM HDL Lower PON1 protein expression was corroborated by lower activity (p lt 0.05) which in turn was associated with attenuated anti-oxidant capacity of GDM HDL Protein changes were accompanied by increased levels of triglycerides and decreased levels of cholesterol esters, respectively. The observed differences in GDM HDL lipid moiety may be related to CETP mass and activity alterations. The rate of cholesterol efflux from term trophoblasts to maternal and from placental endothelial cells to neonatal GDM HDL was impaired (p lt 0.05). In conclusion, GDM causes changes in HDL composition and is intimately associated with impaired cholesterol efflux capability as well as diminished anti-oxidative particle properties. Remodeling of neonatal GDM HDL in utero supports the hypothesis that maternal conditions in pregnancy impact neonatal lipoprotein metabolism.

BackgroundWomen with gestational diabetes (GDM) are at high risk of developing diabetes later in life. After a GDM diagnosis, women receive prenatal care to control their blood glucose levels via diet, physical activity and medications. Continuing such lifestyle skills into early motherhood may reduce the risk of diabetes in this high risk population. In the Gestational Diabetes' Effects on Moms (GEM) study, we are evaluating the comparative effectiveness of diabetes prevention strategies for weight management designed for pregnant/postpartum women with GDM and delivered at the health system level.Methods/designThe GEM study is a pragmatic cluster randomized clinical trial of 44 medical facilities at Kaiser Permanente Northern California randomly assigned to either the intervention or usual care conditions, that includes 2,320 women with a GDM diagnosis between March 27, 2011 and March 30, 2012. A Diabetes Prevention Program-derived print/telephone lifestyle intervention of 13 telephonic sessions tailored to pregnant/postpartum women was developed. The effectiveness of this intervention added to usual care is to be compared to usual care practices alone, which includes two pages of printed lifestyle recommendations sent to postpartum women via mail. Primary outcomes include the proportion of women who reach a postpartum weight goal and total weight change. Secondary outcomes include postpartum glycemia, blood pressure, depression, percent of calories from fat, total caloric intake and physical activity levels. Data were collected through electronic medical records and surveys at baseline (soon after GDM diagnosis), 6 weeks (range 2 to 11 weeks), 6 months (range 12 to 34 weeks) and 12 months postpartum (range 35 to 64 weeks).DiscussionThere is a need for evidence regarding the effectiveness of lifestyle modification for the prevention of diabetes in women with GDM, as well as confirmation that a diabetes prevention program delivered at the health system level is able

Population health data suggests that the development of metabolic disease is influenced by early life events. Gestational diabetes (GDM) is a common complication of pregnancy, but its effects on the offspring are poorly understood. It is hypothesized that a diet high in fat and sucrose will cause excessive weight gain and obesity during pregnancy accompanied by hyperglycemia and hyperinsulinemia that are characteristic of GDM. It is also hypothesized that gestational exposure to GDM will cause obesity, hepatic steatosis and insulin resistance in the offspring when compared to the offspring from metabolically healthy, lean mothers.

Population health data suggests that the development of metabolic disease is influenced by early life events. Gestational diabetes (GDM) is a common complication of pregnancy, but its effects on the offspring are poorly understood. It is hypothesized that a diet high in fat and sucrose will cause excessive weight gain and obesity during pregnancy accompanied by hyperglycemia and hyperinsulinemia that are characteristic of GDM. It is also hypothesized that gestational exposure to GDM will cause obesity, hepatic steatosis and insulin resistance in the offspring when compared to the offspring from metabolically healthy, lean mothers.

Aims/hypothesis Genetic and epidemiological studies suggest an association between gestational diabetes mellitus and type 2 diabetes. Both are polygenic multifactorial disorders characterised by beta cell dysfunction and insulin resistance. Our aim was to investigate whether common genetic variants that have previously been associated with type 2 diabetes or related phenotypes would also confer risk for gestational diabetes mellitus. Materials and methods In 1,881 unrelated pregnant Scandinavian women (649 women with gestational diabetes mellitus, 1,232 non-diabetic control subjects) we genotyped the transcription factor 7-like 2 (TCF7L2 rs7903146), adiponectin (ADIPOQ +276G>T), peroxisome-proliferator activated receptor, gamma 2 (PPARG Pro12Ala), PPARGcoactivator, 1 alpha (PPARGC1A Gly482Ser), forkhead box C2 (FOXC2 −512C>T) and β3-adrenergic receptor (ADRB3 Trp64Arg) polymorphisms using TaqMan allelic discrimination assay or RFLP. Results The CC, CT and TT genotype frequencies of the TCF7L2 rs7903146 variant differed significantly between women with gestational diabetes mellitus and control women (46.3, 43.6 and 10.1% vs 58.5, 35.3 and 6.2%, p=3.7×10−6, corrected p value [Pc] for multiple testing Pc=2.2×10−5). The T-allele was associated with an increased risk of gestational diabetes mellitus (odds ratio 1.49 [95% CI 1.28–1.75], p=4.9×10−7 [Pc=2.8×10−6]). Compared with wild-type CC-genotype carriers, heterozygous (CT-genotype) and homozygous (TT-genotype) carriers had a 1.6-fold (95% CI 1.26–1.93, p=3.7×10−5 [Pc=0.0002]) and a 2.1-fold (95% CI 1.41–2.99, p=0.0001 [Pc=0.0008]) increased risk of gestational diabetes mellitus, respectively. The other polymorphisms studied were not significantly associated with gestational diabetes mellitus (ADIPOQ +276G>T: 1.17 [1.01–1.36], p=0.039 [Pc=0.23]; PPARG Pro12Ala: 1.06 [0.87–1.29], p=0.53; PPARGC1A Gly482Ser: 0.96 [0.83–1.10], p=0.54; FOXC2 −512C>T: 1.01 [0.87–1.16], p=0.94; and ADRB3 Trp64Arg: 1.22 [0.95–1.56], p=0.12). C

Aims/hypothesis Impaired beta cell function is the hallmark of gestational diabetes mellitus (GDM) and MODY. In addition, women with MODY gene mutations often present with GDM, but it is not known whether common variants in MODY genes contribute to GDM. Subjects and methods We genotyped five common variants in the glucokinase (GCK, commonly known as MODY2), hepatocyte nuclear factor 1-α (HNF1A, commonly known as MODY3) and 4-α (HNF4A commonly known as MODY1) genes in 1,880 Scandinavian women (648 women with GDM and 1,232 pregnant non-diabetic control women). Results The A allele of the GCK −30G→A polymorphism was more common in GDM women than in control subjects (odds ratio [OR] 1.28 [95% CI 1.06−1.53], p=0.008, corrected p value, p=0.035). Under a recessive model [AA vs GA+GG], the OR increased further to 2.12 (95% CI 1.21−3.72, p=0.009). The frequency of the L allele of the HNF1A I27L polymorphism was slightly higher in GDM than in controls (1.16 [95% CI 1.001−1.34], p=0.048, corrected p value, p=0.17). However, the OR increased under a dominant model (LL+IL vs II; 1.31 [95% CI 1.08−1.60], p=0.007). The rs2144908, rs2425637 and rs1885088 variants, which are located downstream of the primary beta cell promoter (P2) of HNF4A, were not associated with GDM. Conclusions/interpretation The −30G→A polymorphism of the beta-cell-specific promoter of GCK and the I27L polymorphism of HNF1A seem to increase the risk of GDM in Scandinavian women.