Heterogeneity in glycaemic control in children and adolescents with type 1 diabetes: A latent class trajectory analysis of Danish nationwide data.

AIMS: Suboptimal glycaemic control in children and adolescents with type 1 diabetes is prevalent and associated with increased risk of diabetes-related complications and mortality later in life. First, we aimed to identify distinct glycated haemoglobin (HbA1c) trajectories in children and adolescents (2-19 years) with type 1 diabetes. Second, we examined their associations with clinical and socio-demographic factors. METHODS: Data were obtained from the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids) comprising all Danish children and adolescents diagnosed with type 1 diabetes from 1996 to 2019. Subgroups of distinct mean trajectories of HbA1c were identified using data-driven latent class trajectory modelling. RESULTS: A total of 5889 children (47% female) had HbA1c measured a median of 6 times (interquartile range 3-8) and contributing to 36,504 measurements. We identified four mean HbA1c trajectories, referred to as 'Stable but elevated HbA1c' (83%), 'Increasing HbA1c' (5%), 'Late HbA1c peak' (7%), and 'Early HbA1c peak' (5%). Compared to the 'Stable but elevated HbA1c' group, the three other groups presented rapidly deteriorating glycaemic control during late childhood or adolescence, had higher HbA1c at study entry, and included fewer pump users, higher frequency of inadequate blood glucose monitoring, more severe hypoglycaemic events, lower proportions with Danish origin, and worse educational status of parents. The groups also represented significant differences by healthcare region. CONCLUSIONS: Children and adolescents with type 1 diabetes experience heterogenous trajectories with different timings and magnitudes of the deterioration of HbA1c levels, although the majority follow on average a stable, yet elevated HbA1c trajectory. The causes and long-term health implications of these heterogenous trajectories need to be addressed.

Towards precision medicine in diabetes? A critical review of glucotypes.

In response to a study previously published in PLOS Biology, this Formal Comment thoroughly examines the concept of 'glucotypes' with regard to its generalisability, interpretability and relationship to more traditional measures used to describe data from continuous glucose monitoring.

Body Mass Index Trajectories From Childhood to Adulthood and Age at Onset of Overweight and Obesity: The Influence of Parents' Weight Status.

We investigated the influence of parents' weight status on their children's growth trajectories and its association with age at onset of overweight and obesity. We used 16,396 height and weight records from 3,284 youths from the Panel Study of Income Dynamics, followed across childhood into adulthood (United States, 1997-2017). Across age groups, we modeled body mass index trajectories (ages 5-32 years) according to parents' weight status, using mixed-effect models to estimate age at onset of overweight and obesity and proportion with obesity from childhood to adulthood. There were large differences in growth patterns according to parents' weight status: Children of parents with obesity had, on average, overweight at age 6 (95% confidence interval (CI): 5, 7) and steep growth trajectories until age 12; children of normal-weight parents had slower increases in body mass index, reaching overweight on average at age 25 (95% CI: 24, 27). By age 30, 30% (95% CI: 28, 31) of youths had obesity. Differences in early-life growth persisted into adulthood: 48% (95% CI: 45, 52) of adult children of parents with obesity had obesity versus 16% (95% CI: 14, 19) of those of normal-weight parents. Trajectories to unhealthy weight were heavily influenced by parents' weight status, especially before age 12, children of parents with obesity having overweight 19 earlier in life than children of normal-weight parents.

Trajectory and predictors of HbA1c in children and adolescents with type 1 diabetes-A Danish nationwide cohort study.

OBJECTIVES: Poor glycemic control in type 1 diabetes increases the risk of chronic complications and it is essential to identify life periods and predictors associated with deteriorating HbA1c . The aim was to describe specific HbA1c trajectories in Danish children and adolescents with type 1 diabetes and study associations with clinical and sociodemographic factors. RESEARCH DESIGN AND METHODS: 5889 children with type 1 diabetes were included from the nationwide Danish Registry of Childhood and Adolescent Diabetes with annual visits during 1996-2019. Trajectories of HbA1c were modeled with linear mixed-effects models (using age as time scale, included as cubic spline) and with an individual-specific random intercept and slope. The following cofactors were included stepwise into the model: sex, age at diagnosis, calendar year, parental education, immigrant status, health care region, blood glucose monitoring (BGM) frequency, treatment modalities: continuous subcutaneous insulin infusion (pump) versus multiple daily insulin injection therapy (pen) and continuous glucose monitoring. RESULTS: HbA1c overall increased during age while there was a significant decreasing secular trend. Older age at diagnosis was associated with a steeper trajectory, and non-Danish origin and shorter parental education were each associated with higher levels of HbA1c across age. A lower BGM frequency was associated with a markedly poorer HbA1c trajectory, while no significant differences were shown for different treatment modalities. CONCLUSIONS: Glycemic outcome worsened with age during childhood and adolescence, which is of clinical concern. Important predictors for a poorer glycemic trajectory were later age at diabetes diagnosis, shorter parental education, non-Danish origin and, in particular low BGM frequency.

Effect of familial diabetes status and age at diagnosis on type 2 diabetes risk: a nation-wide register-based study from Denmark.

AIMS/HYPOTHESIS: We assessed whether the risk of developing type 2 diabetes and the age of onset varied with the age at diabetes diagnosis of affected family members. METHODS: We performed a national register-based open cohort study of individuals living in Denmark between 1995 and 2012. The population under study consisted of all individuals aged 30 years or older without diagnosed diabetes at the start date of the cohort (1 January 1995) and who had information about their parents' identity. Individuals who turned 30 years of age during the observation period and had available parental identity information were also added to the cohort from that date (open cohort design). These criteria restricted the study population mostly to people born between 1960 and 1982. Multivariable Poisson regression models adjusted for current age and highest educational attainment were used to estimate incidence rate ratios (IRRs) of type 2 diabetes. RESULTS: We followed 2,000,552 individuals for a median of 14 years (24,034,059 person-years) and observed 76,633 new cases of type 2 diabetes. Compared with individuals of the same age and sex who did not have a parent or full sibling with diabetes, the highest risk of developing type 2 diabetes was observed in individuals with family members diagnosed at an early age. The IRR was progressively lower with a higher age at diabetes diagnosis in family members: 3.9 vs 1.4 for those with a parental age at diagnosis of 50 or 80 years, respectively; and 3.3 vs 2.0 for those with a full sibling's age at diagnosis of 30 or 60 years, respectively. CONCLUSIONS/INTERPRETATION: People with a family member diagnosed with diabetes at an earlier age are more likely to develop diabetes and also to develop it at an earlier age than those with a family member diagnosed in later life. This finding highlights the importance of expanding our understanding of the interplay between genetic diabetes determinants and the social, behavioural and environmental diabetes determinants that track in families across generations. Accurate registration of age at diagnosis should form an integral part of recording a diabetes family history, as it provides easily obtainable and highly relevant detail that may improve identification of individuals at increased risk of younger onset of type 2 diabetes. In particular, these individuals may benefit from closer risk factor assessment and follow-up, as well as prevention strategies that may involve the family.

Effect of duration and burden of microvascular complications on mortality rate in type 1 diabetes: an observational clinical cohort study.

AIMS/HYPOTHESIS: The role of burden and duration of multiple microvascular complications on mortality rate has not been explored in detail in type 1 diabetes. Taking complication burden and time-updated duration into account we aimed to quantify mortality rate in individuals with and without microvascular complications. METHODS: This observational clinical cohort included 3828 individuals with type 1 diabetes attending the Steno Diabetes Center Copenhagen in 2001-2013. We used information on mortality and detailed clinical measures of microvascular complications from electronic patient records. Poisson models were used to model mortality rates according to complication burden. RESULTS: During 26,665 person-years of follow-up, 503 deaths occurred. Compared with individuals without microvascular complications, the mortality rate ratio was 2.20 (95% CI 1.79, 2.69) for individuals with diabetic kidney disease, 1.72 (95% CI 1.39, 2.12) for individuals with neuropathy and 1.02 (95% CI 0.77, 1.37) for individuals with retinopathy, all adjusted for calendar time (year/month/day), age, duration of diabetes, sex, HbA1c, LDL-cholesterol, BMI, smoking status, systolic blood pressure, use of antihypertensive and lipid-lowering medication, and cardiovascular disease status. In individuals with two complications or more, the risk of mortality did not exceed the combined risk from each individual complication. Mortality rate ratios increased immediately after diagnosis of neuropathy and diabetic kidney disease. Mortality rate ratios were independent of the duration of neuropathy and retinopathy, while the mortality rate associated with diabetic kidney disease reached a stable level after approximately 3 years. CONCLUSIONS/INTERPRETATION: Neuropathy and diabetic kidney disease are strong and independent risk markers of mortality in type 1 diabetes, whereas no evidence of higher mortality rate was found for retinopathy. We found no indication that the mortality risk with multiple complications exceeds the risk conferred by each complication separately. The duration spent with microvascular complications had only a marginal effect on mortality.

Reversion from prediabetes to normoglycaemia and risk of cardiovascular disease and mortality: the Whitehall II cohort study.

AIMS/HYPOTHESIS: Reversion from prediabetes to normoglycaemia is accompanied by an improvement in cardiovascular risk factors, but it is unclear whether this translates into a reduction in risk of cardiovascular disease (CVD) events or death. Hence, we studied the probability of reversion from prediabetes to normoglycaemia and the associated risk of future CVD and death using data from the Whitehall II observational cohort study. METHODS: Three glycaemic criteria for prediabetes (fasting plasma glucose [FPG] 5.6-6.9 mmol/l, 2 h plasma glucose [2hPG] 7.8-11.0 mmol/l, and HbA1c 39-47 mmol/mol [5.7-6.4%]) were assessed in 2002-2004 and 2007-2009 for 5193 participants free of known diabetes at enrolment. Among participants with prediabetes in the first examination, we calculated the probability of reversion to normoglycaemia by re-examination according to each glycaemic criterion. Poisson regression analysis was used to estimate and compare incidence rates of a composite endpoint of a CVD event or death in participants with prediabetes who did vs did not revert to normoglycaemia. Analyses were adjusted for age, sex, ethnicity and previous CVD. RESULTS: Based on the FPG criterion, 820 participants had prediabetes and 365 (45%) of them had reverted to normoglycaemia in 5 years. The corresponding numbers were 324 and 120 (37%) for the 2hPG criterion and 1709 and 297 (17%) for the HbA1c criterion. During a median follow-up of 6.7 (interquartile range 6.3-7.2) years, 668 events of non-fatal CVD or death occurred among the 5193 participants. Reverting from 2hPG-defined prediabetes to normoglycaemia vs remaining prediabetic or progressing to diabetes was associated with a halving in event rate (12.7 vs 29.1 per 1000 person-years, p = 0.020). No association with event rate was observed for reverting from FPG-defined (18.6 vs 18.2 per 1000 person-years, p = 0.910) or HbA1c-defined prediabetes to normoglycaemia (24.5 vs 22.9 per 1000 person-years, p = 0.962). CONCLUSIONS/INTERPRETATION: Most people with HbA1c-defined prediabetes remained prediabetic or progressed to diabetes during 5 years of follow-up. In contrast, reversion to normoglycaemia was frequent among people with FPG- or 2hPG-defined prediabetes. Only reversion from 2hPG-defined prediabetes to normoglycaemia was associated with a reduction in future risk of CVD and death.

Spousal cardiometabolic risk factors and incidence of type 2 diabetes: a prospective analysis from the English Longitudinal Study of Ageing.

AIMS/HYPOTHESIS: In the UK, more than one million people have undiagnosed diabetes and an additional five million are at high risk of developing the disease. Given that early identification of these people is key for both primary and secondary prevention, new screening approaches are needed. Since spouses resemble each other in cardiometabolic risk factors related to type 2 diabetes, we aimed to investigate whether diabetes and cardiometabolic risk factors in one spouse can be used as an indicator of incident type 2 diabetes in the other spouse. METHODS: We analysed data from 3649 men and 3478 women from the English Longitudinal Study of Ageing with information on their own and their spouse's diabetes status and cardiometabolic risk factors. We modelled incidence rates and incidence rate ratios with Poisson regression, using spousal diabetes status or cardiometabolic risk factors (i.e. BMI, waist circumference, systolic and diastolic BP, HDL- and LDL-cholesterol and triacylglycerols) as exposures and type 2 diabetes incidence in the index individual as the outcome. Models were adjusted for two nested sets of covariates. RESULTS: Spousal BMI and waist circumference were associated with incident type 2 diabetes, but with different patterns for men and women. A man's risk of type 2 diabetes increased more steeply with his wife's obesity level, and the association remained statistically significant even after adjustment for the man's own obesity level. Having a wife with a 5 kg/m2 higher BMI (30 kg/m2 vs 25 kg/m2) was associated with a 21% (95% CI 11%, 33%) increased risk of type 2 diabetes. In contrast, the association between incident type 2 diabetes in a woman and her husband's BMI was attenuated after adjusting for the woman's own obesity level. Findings for waist circumference were similar to those for BMI. Regarding other risk factors, we found a statistically significant association only between the risk of type 2 diabetes in women and their husbands' triacylglycerol levels. CONCLUSIONS/INTERPRETATION: The main finding of this study is the sex-specific effect of spousal obesity on the risk of type 2 diabetes. Having an obese spouse increases an individual's risk of type 2 diabetes over and above the effect of the individual's own obesity level among men, but not among women. Our results suggest that a couples-focused approach may be beneficial for the early detection of type 2 diabetes and individuals at high risk of developing type 2 diabetes, especially in men, who are less likely than women to attend health checks. DATA AVAILABILITY: Data were accessed via the UK Data Service under the data-sharing agreement no. 91400 ( https://discover.ukdataservice.ac.uk/catalogue/?sn=5050&type=Data%20catalogue ).

Glucose patterns during an oral glucose tolerance test and associations with future diabetes, cardiovascular disease and all-cause mortality rate.

AIMS/HYPOTHESIS: In addition to blood glucose concentrations measured in the fasting state and 2 h after an OGTT, intermediate measures during an OGTT may provide additional information regarding a person's risk of future diabetes and cardiovascular disease (CVD). First, we aimed to characterise heterogeneity of glycaemic patterns based on three time points during an OGTT. Second, we compared the incidences of diabetes and CVD and all-cause mortality rates among those with different patterns. METHODS: Our cohort study included 5861 participants without diabetes at baseline from the Danish Inter99 study. At baseline, all participants underwent an OGTT with measurements of plasma glucose levels at 0, 30 and 120 min. Latent class mixed-effects models were fitted to identify distinct patterns of glycaemic response during the OGTT. Information regarding incident diabetes, CVD and all-cause mortality rates during a median follow-up time of 11, 12 and 13 years, respectively, was extracted from national registers. Cox proportional hazard models with adjustment for several cardiometabolic risk factors were used to compare the risk of diabetes, CVD and all-cause mortality among individuals in the different latent classes. RESULTS: Four distinct glucose patterns during the OGTT were identified. One pattern was characterised by high 30 min but low 2 h glucose values. Participants with this pattern had an increased risk of developing diabetes compared with participants with lower 30 min and 2 h glucose levels (HR 4.1 [95% CI 2.2, 7.6]) and participants with higher 2 h but lower 30 min glucose levels (HR 1.5 [95% CI 1.0, 2.2]). Furthermore, the all-cause mortality rate differed between the groups with significantly higher rates in the two groups with elevated 30 min glucose. Only small non-significant differences in risk of future CVD were observed across latent classes after confounder adjustment. CONCLUSIONS/INTERPRETATION: Elevated 30 min glucose is associated with increased risk of diabetes and all-cause mortality rate independent of fasting and 2 h glucose levels. Therefore, subgroups at high risk may not be revealed when considering only fasting and 2 h glucose levels during an OGTT.

Trajectories of glycaemia, insulin sensitivity and insulin secretion in South Asian and white individuals before diagnosis of type 2 diabetes: a longitudinal analysis from the Whitehall II cohort study.

AIMS/HYPOTHESIS: South Asian individuals have reduced insulin sensitivity and increased risk of type 2 diabetes compared with white individuals. Temporal changes in glycaemic traits during middle age suggest that impaired insulin secretion is a particular feature of diabetes development among South Asians. We therefore aimed to examine ethnic differences in early changes in glucose metabolism prior to incident type 2 diabetes. METHODS: In a prospective British occupational cohort, subject to 5 yearly clinical examinations, we examined ethnic differences in trajectories of fasting plasma glucose (FPG), 2 h post-load plasma glucose (2hPG), fasting serum insulin (FSI), 2 h post-load serum insulin (2hSI), HOMA of insulin sensitivity (HOMA2-S) and secretion (HOMA2-B), and the Gutt insulin sensitivity index (ISI0,120) among 120 South Asian and 867 white participants who developed diabetes during follow-up (1991-2013). We fitted cubic mixed-effects models to longitudinal data with adjustment for a wide range of covariates. RESULTS: Compared with white individuals, South Asians had a faster increase in FPG before diagnosis (slope difference 0.22 mmol/l per decade; 95% CI 0.02, 0.42; p = 0.03) and a higher FPG level at diagnosis (0.27 mmol/l; 95% CI 0.06, 0.48; p = 0.01). They also had higher FSI and 2hSI levels before and at diabetes diagnosis. South Asians had a faster decline and lower HOMA2-S (log e -transformed) at diagnosis compared with white individuals (0.33; 95% CI 0.21, 0.46; p < 0.001). HOMA2-B increased in both ethnic groups until 7 years before diagnosis and then declined; the initial increase was faster in white individuals. ISI0,120 declined steeply in both groups before diagnosis; levels were lower among South Asians before and at diagnosis. There were no ethnic differences in 2hPG trajectories. CONCLUSIONS/INTERPRETATION: We observed different trajectories of plasma glucose, insulin sensitivity and secretion prior to diabetes diagnosis in South Asian and white individuals. This might be due to ethnic differences in the natural history of diabetes. South Asian individuals experienced a more rapid decrease in insulin sensitivity and faster increases in FPG compared with white individuals. These findings suggest more marked disturbance in beta cell compensation prior to diabetes diagnosis in South Asian individuals.

Prediction of First Cardiovascular Disease Event in Type 1 Diabetes Mellitus: The Steno Type 1 Risk Engine.

BACKGROUND: Patients with type 1 diabetes mellitus are at increased risk of developing cardiovascular disease (CVD), but they are currently undertreated. There are no risk scores used on a regular basis in clinical practice for assessing the risk of CVD in type 1 diabetes mellitus. METHODS AND RESULTS: From 4306 clinically diagnosed adult patients with type 1 diabetes mellitus, we developed a prediction model for estimating the risk of first fatal or nonfatal CVD event (ischemic heart disease, ischemic stroke, heart failure, and peripheral artery disease). Detailed clinical data including lifestyle factors were linked to event data from validated national registers. The risk prediction model was developed by using a 2-stage approach. First, a nonparametric, data-driven approach was used to identify potentially informative risk factors and interactions (random forest and survival tree analysis). Second, based on results from the first step, Poisson regression analysis was used to derive the final model. The final CVD prediction model was externally validated in a different population of 2119 patients with type 1 diabetes mellitus. During a median follow-up of 6.8 years (interquartile range, 2.9-10.9) a total of 793 (18.4%) patients developed CVD. The final prediction model included age, sex, diabetes duration, systolic blood pressure, low-density lipoprotein cholesterol, hemoglobin A1c, albuminuria, glomerular filtration rate, smoking, and exercise. Discrimination was excellent for a 5-year CVD event with a C-statistic of 0.826 (95% confidence interval, 0.807-0.845) in the derivation data and a C-statistic of 0.803 (95% confidence interval, 0.767-0.839) in the validation data. The Hosmer-Lemeshow test showed good calibration (P>0.05) in both cohorts. CONCLUSIONS: This high-performing CVD risk model allows for the implementation of decision rules in a clinical setting.

Examining the provisional guidelines for weight gain in twin pregnancies: a retrospective cohort study.

BACKGROUND: Weight gain during pregnancy has an important impact on maternal and neonatal health. Unlike the Institute of Medicine (IOM) recommendations for weight gain in singleton pregnancies, those for twin gestations are termed "provisional", as they are based on limited data. The objectives of this study were to determine the neonatal and maternal outcomes associated with gaining weight below, within and above the IOM provisional guidelines on gestational weight gain in twin pregnancies, and additionally, to explore ranges of gestational weight gain among women who delivered twins at the recommended gestational age and birth weight, and those who did not. METHODS: A retrospective cohort study of women who gave birth to twins at ≥20 weeks gestation, with a birth weight ≥ 500 g was conducted in Nova Scotia, Canada (2003-2014). Our primary outcome of interest was small for gestational age (<10th percentile). In order to account for gestational age at delivery, weekly rates of 2nd and 3rd trimester weight gain were used to categorize women as gaining below, within, or above guidelines. We performed traditional regression analyses for maternal outcomes, and to account for the correlated nature of the neonatal outcomes in twins, we used generalized estimating equations (GEE). RESULTS: A total of 1482 twins and 741 mothers were included, of whom 27%, 43%, and 30% gained below, within, and above guidelines, respectively. The incidence of small for gestational age in these three groups was 30%, 21%, and 20%, respectively, and relative to gaining within guidelines, the adjusted odds ratios were 1.44 (95% CI 1.01-2.06) for gaining below and 0.92 (95% CI 0.62-1.36) for gaining above. The gestational weight gain in women who delivered twins at 37-42 weeks with average birth weight ≥ 2500 g and those who delivered twins outside of the recommend ranges were comparable to each other and the IOM recommendations. CONCLUSIONS: While gestational weight gain below guidelines for twins was associated with some adverse neonatal outcomes, additional research exploring alternate ranges of gestational weight gain in twin pregnancies is warranted, in order to optimize neonatal and maternal outcomes.

Are women who quit smoking at high risk of excess weight gain throughout pregnancy?

BACKGROUND: Smoking cessation has been reported to be associated with high total gestational weight gain (GWG), which itself is a risk factor for adverse maternal-infant outcomes. Recent studies have criticized conventional single measures of GWG, since they may lead to biased results. Therefore, we aimed to compare patterns of GWG based on serial antenatal weight measurements between women who: never smoked, quit during pregnancy, continued to smoke. METHODS: Participants (N = 509) of our longitudinal study were recruited from seven antenatal clinics in Southwestern Ontario. Serial GWG measurements were abstracted from medical charts, while information on smoking status was obtained from a self-administered questionnaire at a median gestational age of 32 (27-37) weeks. GWG patterns were assessed by fitting piecewise mixed-effects models. First trimester weight gains and weekly rates for the last two trimesters were compared by smoking status. RESULTS: During the first trimester, women who never smoked and those who quit during pregnancy gained on average 1.7 kg (95 % CI: 1.4-2.1) and 1.2 kg (0.3-2.1), respectively, whereas women who continued smoking gained more than twice as much (3.5 kg, 2.4-4.6). Weekly rate of gain in the second and third trimesters was highest in women who quit smoking (0.60 kg/week, 0.54-0.65), approximately 20 and 50 % higher than in women who never smoked and those who smoked during pregnancy, respectively. CONCLUSIONS: In this longitudinal study to examine GWG by smoking status based on serial GWG measurements, we found that women who quit smoking experienced a rapid rate of gain during the last two trimesters, suggesting that this high-risk group may benefit from targeted interventions.

Age trajectories of glycaemic traits in non-diabetic South Asian and white individuals: the Whitehall II cohort study.

AIMS/HYPOTHESIS: South Asian individuals have an increased prevalence of type 2 diabetes, but little is known about the development of glycaemic traits in this ethnic group. We compared age-related changes in glycaemic traits between non-diabetic South Asian and white participants. METHODS: In a prospective British occupational cohort with 5-yearly clinical examinations (n = 230/5,749 South Asian/white participants, age 39-79 years at baseline), age-related trajectories of fasting glucose (FG) and 2 h post-load glucose (PLG), log-transformed fasting insulin (FINS) and 2 h post-load insulin (PLINS), HOMA insulin sensitivity (HOMA2-%S) and HOMA insulin secretion (HOMA2-%B) were fitted for South Asian and white individuals who remained free of diabetes between 1991 and 2009. RESULTS: In sex-adjusted multilevel models, FG was stable in white participants but increased with age in South Asians (0.12 [SE = 0.04] mmol/l per decade). PLG, FINS and PLINS levels were lower among white participants (by 0.271 [SE = 0.092] mmol/l, 0.306 [SE = 0.046] log pmol/l, 0.707 [SE = 0.059] log pmol/l at age 50, respectively) compared with South Asians, although their age-related trajectories were parallel. HOMA2-%S was higher (0.226 [SE = 0.038] at age 50) and HOMA2-%B lower (by 0.189 [SE = 0.026] at age 50) among white than South Asian participants. The age-related decline in HOMA2-%S was similar in these groups, but the age-related increase in HOMA2-%B was greater in white participants (0.04 [SE = 0.02] per decade). This difference was explained by obesity, lifestyle and social status. CONCLUSIONS/INTERPRETATION: Findings from a diabetes-free population suggest an inadequate pancreatic beta cell reserve in South Asians, as a significantly steeper age-related increase in FG was observed in this ethnic group compared with white individuals.

The use of regression methods for the investigation of trends in suicide rates in Hungary between 1963 and 2011.

PURPOSE: Suicide rates in Hungary have been analyzed from different aspects in recent decades. However, only descriptive rates have been reported. The aim of our epidemiological study was to characterize the pattern of annual rates of suicide in Hungary during the period 1963-2011 by applying advanced statistical methods. METHODS: Annual suicide rates per 100,000 population (>6 years) for gender, age group and suicide method were determined from published frequency tables and reference population data obtained from the Hungarian Central Statistical Office. Trends and relative risks of suicide were investigated using negative binomial regression models overall and in stratified analyses (by gender, age group and suicide method). Joinpoint regression analyses were additionally applied to characterize trends and to find turning points during the period 1963-2011. RESULTS: Overall, 178,323 suicides (50,265 females and 128,058 males) were committed in Hungary during the investigated period. The risk of suicide was higher among males than females overall, in all age groups and for most suicide methods. The annual suicide rate exhibited a significant peak in 1982 and remained basically constant after 2006. Different segmented patterns were observed for the suicide rates in the various age groups. CONCLUSIONS: Suicide rates revealed segmented linear pattern. This is the first detailed trend analysis with risk estimates obtained via joinpoint and negative binomial regression methods simultaneously for age-specific suicide frequencies in Hungary.

Effect of gestational diabetes on fetal growth rate and later overweight in the offspring.

CONTEXT: Children of women with gestational diabetes (GDM) are often born with a higher birthweight and have an increased risk of overweight during childhood. High fetal growth rate is also associated with being overweight in childhood. OBJECTIVE: To examine excessive fetal growth rate as a mediator between GDM and overweight in the offspring. METHODS: This was a longitudinal cohort study, using routinely collected data on children born 2008-2014 in Aarhus, Denmark. Fetal biometrics were extracted from the patient records at Aarhus University Hospital and childhood weight from the health records at Aarhus Municipality Healthcare Service. We calculated growth trajectories for fetuses affected by GDM and for unaffected fetuses using cubic mixed model regression. We extracted individual fetal growth rate and estimated the contributing effect of fetal growth rate on the risk of being overweight in the 5-9 year-old offspring. RESULTS: We included 6794 mother-child pairs, 295 with GDM. Fetal growth was higher in women with GDM from week 25, and the offspring had an increased risk of being overweight (OR: 2.02 (95%CI: 1.44 - 2.84)). When adjusting for fetal growth rate in week 28 the effect attenuated by 15%, and to 1.10 (95%CI: 0.76 - 1.60) when further adjusting for pre-pregnancy BMI. CONCLUSION: Pregnancies affected by GDM had higher fetal growth rate and the offspring had a higher risk of being overweight at 5-9 years. Fetal growth rate in early third trimester was a mediator of up to 15% of this association, but pre-pregnancy BMI contributed strongly as well.

Hemoglobin A1c Trajectories During Pregnancy and Adverse Outcomes in Women With Type 2 Diabetes: A Danish National Population-Based Cohort Study.

OBJECTIVE: To identify and characterize groups of pregnant women with type 2 diabetes with distinct hemoglobin A1c (HbA1c) trajectories across gestation and to examine the association with adverse obstetric and perinatal outcomes. RESEARCH DESIGN AND METHODS: This was a retrospective Danish national cohort study including all singleton pregnancies in women with type 2 diabetes, giving birth to a liveborn infant, between 2004 and 2019. HbA1c trajectories were identified using latent class linear mixed-model analysis. Associations with adverse outcomes were examined with logistic regression models. RESULTS: A total of 1,129 pregnancies were included. Three HbA1c trajectory groups were identified and named according to the glycemic control in early pregnancy (good, 59%; moderate, 32%; and poor, 9%). According to the model, all groups attained an estimated HbA1c <6.5% (48 mmol/mol) during pregnancy, with no differences between groups in the 3rd trimester. Women with poor glycemic control in early pregnancy had lower odds of having an infant with large-for-gestational-age (LGA) birth weight (adjusted odds ratio [aOR] 0.57, 95% CI 0.40-0.83), and higher odds of having an infant with small-for-gestational age (SGA) birth weight (aOR 2.49, 95% CI 2.00-3.10) and congenital malformation (CM) (aOR 4.60 95% CI 3.39-6.26) compared with women with good glycemic control. There was no evidence of a difference in odds of preeclampsia, preterm birth, and caesarean section between groups. CONCLUSIONS: Women with poor glycemic control in early pregnancy have lower odds of having an infant with LGA birth weight, but higher odds of having an infant with SGA birth weight and CM.

Large Language Models for Epidemiological Research via Automated Machine Learning: Case Study Using Data From the British National Child Development Study.

Background: Large language models have had a huge impact on natural language processing (NLP) in recent years. However, their application in epidemiological research is still limited to the analysis of electronic health records and social media data. objectives: To demonstrate the potential of NLP beyond these domains, we aimed to develop prediction models based on texts collected from an epidemiological cohort and compare their performance to classical regression methods. Methods: We used data from the British National Child Development Study, where 10,567 children aged 11 years wrote essays about how they imagined themselves as 25-year-olds. Overall, 15% of the data set was set aside as a test set for performance evaluation. Pretrained language models were fine-tuned using AutoTrain (Hugging Face) to predict current reading comprehension score (range: 0-35) and future BMI and physical activity (active vs inactive) at the age of 33 years. We then compared their predictive performance (accuracy or discrimination) with linear and logistic regression models, including demographic and lifestyle factors of the parents and children from birth to the age of 11 years as predictors. Results: NLP clearly outperformed linear regression when predicting reading comprehension scores (root mean square error: 3.89, 95% CI 3.74-4.05 for NLP vs 4.14, 95% CI 3.98-4.30 and 5.41, 95% CI 5.23-5.58 for regression models with and without general ability score as a predictor, respectively). Predictive performance for physical activity was similarly poor for the 2 methods (area under the receiver operating characteristic curve: 0.55, 95% CI 0.52-0.60 for both) but was slightly better than random assignment, whereas linear regression clearly outperformed the NLP approach when predicting BMI (root mean square error: 4.38, 95% CI 4.02-4.74 for NLP vs 3.85, 95% CI 3.54-4.16 for regression). The NLP approach did not perform better than simply assigning the mean BMI from the training set as a predictor. Conclusions: Our study demonstrated the potential of using large language models on text collected from epidemiological studies. The performance of the approach appeared to depend on how directly the topic of the text was related to the outcome. Open-ended questions specifically designed to capture certain health concepts and lived experiences in combination with NLP methods should receive more attention in future epidemiological studies.