Flexible distributed lag models and their application to geophysical data

Regression models with lagged covariate effects are often used in biostatistical and geo- physical data analysis. In the difficult and all-important subject of earthquake research, strong long-lasting rainfall is assumed to be one of many complex trigger factors that lead to earthquakes. Geophysicists interpret the rain effect with an increase of pore pressure due to the infiltra- tion of rain water over a long time period. Therefore, a sensible statistical regression model examining the influence of rain on the number of earthquakes on day t has to contain rain information of day t and of preceding days t − 1 to t − L. In the first part of this thesis, the specific shape of lagged rain influence on the number of earthquakes is modeled. A novel penalty structure for interpretable and flexible estimates of lag coefficients based on spline representations is presented. The penalty structure enables smoothness of the resulting lag course and a shrinkage towards zero of the last lag coefficient via a ridge penalty. This additional ridge penalty offers an approach to another problem neglected in previous work. With the help of the additional ridge penalty, a suboptimal choice of the lag length L is no longer critical. We propose the use of longer lags, as our simulations indicate that superfluous coefficients are correctly estimated close to zero. We provide a user-friendly implementation of our flexible distributed lag (FDL) ap- proach, that can be used directly in the established R package mgcv for estimation of generalized additive models. This allows our approach to be immediately included in com- plex additive models for generalized responses even in hierarchical or longitudinal data settings, making use of established stable and well-tested algorithms. We demonstrate the performance and utility of the proposed flexible distributed lag model in a case study on (micro-) earthquake data from Mount Hochstaufen, Bavaria with focus on the specific shape of the lagged rain influence on the occurrence of earthquakes in different depths. The complex meteorological and geophysical data set was collected and provided by the Geophysical Observatory of the Ludwig-Maximilians University Munich. The benefit of flexible distributed lag modeling is shown in a detailed simulation study. In the second part of the thesis, the penalization concept is extended to lagged non- linear covariate influence. Here, we extend an approach of Gasparrini et al. (2010), that was up to now unpenalized. Detailed simulation studies illustrate again the benefits of the penalty structure. The flexible distributed lag nonlinear model is applied to data of the volcano Merapi in Indonesia, collected and provided by the Geophysical Observatory in Fürstenfeldbruck. In this data set, the specific shape of lagged rain influence on the occurrence of block and ash flows is examined

Flexible distributed lag models and their application to geophysical data

Regression models with lagged covariate effects are often used in biostatistical and geo- physical data analysis. In the difficult and all-important subject of earthquake research, strong long-lasting rainfall is assumed to be one of many complex trigger factors that lead to earthquakes. Geophysicists interpret the rain effect with an increase of pore pressure due to the infiltra- tion of rain water over a long time period. Therefore, a sensible statistical regression model examining the influence of rain on the number of earthquakes on day t has to contain rain information of day t and of preceding days t − 1 to t − L. In the first part of this thesis, the specific shape of lagged rain influence on the number of earthquakes is modeled. A novel penalty structure for interpretable and flexible estimates of lag coefficients based on spline representations is presented. The penalty structure enables smoothness of the resulting lag course and a shrinkage towards zero of the last lag coefficient via a ridge penalty. This additional ridge penalty offers an approach to another problem neglected in previous work. With the help of the additional ridge penalty, a suboptimal choice of the lag length L is no longer critical. We propose the use of longer lags, as our simulations indicate that superfluous coefficients are correctly estimated close to zero. We provide a user-friendly implementation of our flexible distributed lag (FDL) ap- proach, that can be used directly in the established R package mgcv for estimation of generalized additive models. This allows our approach to be immediately included in com- plex additive models for generalized responses even in hierarchical or longitudinal data settings, making use of established stable and well-tested algorithms. We demonstrate the performance and utility of the proposed flexible distributed lag model in a case study on (micro-) earthquake data from Mount Hochstaufen, Bavaria with focus on the specific shape of the lagged rain influence on the occurrence of earthquakes in different depths. The complex meteorological and geophysical data set was collected and provided by the Geophysical Observatory of the Ludwig-Maximilians University Munich. The benefit of flexible distributed lag modeling is shown in a detailed simulation study. In the second part of the thesis, the penalization concept is extended to lagged non- linear covariate influence. Here, we extend an approach of Gasparrini et al. (2010), that was up to now unpenalized. Detailed simulation studies illustrate again the benefits of the penalty structure. The flexible distributed lag nonlinear model is applied to data of the volcano Merapi in Indonesia, collected and provided by the Geophysical Observatory in Fürstenfeldbruck. In this data set, the specific shape of lagged rain influence on the occurrence of block and ash flows is examined

Failure to Predict High-risk Kawasaki Disease Patients in a Population-based Study Cohort in Germany

Background: Diverse scores on high-risk Kawasaki disease (KD) patients have proven a good prognostic validity in the Japanese population. However, data on non-Japanese have been inconclusive. Do the Kobayashi, Egami and Sano scores or application of up-to-date statistical methods (Random Forest) predict response to standard intravenous immunoglobulin (IVIG) therapy and the risk of persistent coronary artery aneurysm (CAA) in patients with KD in a mainly Caucasian population in Germany? Methods: Data on 442 children (German population-based survey, 2013 and 2014) were used to assess the prognostic validity of the Kobayashi, Egami and Sano scores for being refractory to IVIG treatment and for predicting the risk of persistent CAA. Additionally, an up-to-date statistical approach (Random Forest) was applied to identify a potentially more valid score. Results: A total of 301 children were eligible for assessment of their response to IVIG treatment. Among those, 177 children were followed-up for 1 year to identify persistent CAA. Although all scores were significantly associated with being refractory to IVIG (relative risk range between 2.32 and 3.73), the prognostic properties were low (likelihood ratio positive: 1.83-4.57;sensitivity in the range of 0.28-0.53). None of the scores was a significant predictor of CAA 1 year after acute illness. Application of statistical analysis such as Random Forest did not yield a more valid score. Conclusions: None of the available scores appears to be appropriate for identifying high-risk Caucasian children with KD who might need intensified therapy

Comparison of a pediatric practice-based therapy and an interdisciplinary ambulatory treatment in social pediatric centers for migraine in children: a nation-wide randomized-controlled trial in Germany: \textquotedblmoma - modules on migraine activity\textquotedbl

BACKGROUND Migraine is common in childhood, peaks in adolescents and persists into adulthood in at least 40% of patients. There is need for early interventions to improve the burden of disease and, if possible, reduce chronification. The aim of the project is to compare two types of ambulatory treatment strategies regarding their effect on headache days and quality of life in 6 to 11 year old children with migraine: 1) the routine care in pediatricians' practices (intervention group A) and 2) a structured interdisciplinary multimodal intervention administered at social pediatric centers (intervention group B). METHODS The study is a nation-wide cluster-randomized study. Based on the postal codes the regions are randomly assigned to the two intervention-strategies. Children with migraine are recruited in the pediatric practices, as common outpatient-care in the German health-care system. Parents rate headache frequency, intensity and acute medication intake at a daily basis via a digital smartphone application specifically designed for the study. Migraine-related disability and quality of life are assessed every 3 months. Study duration is 9 months for every participant: 3 months of baseline at the pediatric practice (both groups); 3 months of intervention at the pediatric practice (intervention group A) or at the social pediatric center (intervention group B), respectively; 3 months of follow-up at the pediatric practice (both groups). DISCUSSION Results of the planned comparison of routine care in pediatric practices and interdisciplinary social pediatric centers will be relevant for treatment of children with migraine, both for the individual and for the health care system. TRIAL REGISTRATION The study was approved by the ethics committee at the Ludwig-Maximilians-University Munich (number 18-804) and was retrospectively registered on 27 April 2021 in the WHO approved German Clinical Trials Register (number DRKS00016698 )

Migraine and the development of additional psychiatric and pain disorders in the transition from adolescence to adulthood

Introduction: The transition from childhood to adolescence and from adolescence to adulthood are vulnerable phases in life. In these phases, late or insufficient treatment of diseases may lead to chronification and favor development of additional disorders. In adolescents, migraine often has a highly negative impact on school performance and everyday life. The hypothesis of the present study was that adolescents with migraine have a higher risk for developing additional disorders such as psychiatric disorders or other pain syndromes in the course of the disease. Materials and methods: In this study, we analyzed health insurance data of 56,597 German adolescents at the age of 15 years in the year 2006. By using the International Classification of Diseases (ICD 10), we determined a group with migraine diagnosis in the year 2006 and a control group without any headache diagnosis in 2006. We then compared both groups regarding the development of additional disorders (based on the ICD 10) during the following 10 years (2007 to 2016). Results: Adolescents with migraine had a 2.1 fold higher risk than persons without migraine diagnosis to develop an additional affective or mood disorder, a 1.8 fold higher risk to obtain neurotic, stress-related and somatoform disorders, a 1.8 fold higher risk to subsequently suffer from behavioral syndromes, a 1.6 higher risk to get back pain and a 1.5 fold higher risk for irritable bowel syndrome during the next 10 years. Conclusion: Adolescents with migraine are at risk for developing additional disorders later. Considering and addressing the patient’s risks and potential medical and psychosocial problems might improve the long-term outcome significantly

Reduction of Portion Size and Eating Rate Is Associated with BMI-SDS Reduction in Overweight and Obese Children and Adolescents: Results on Eating and Nutrition Behaviour from the Observational KgAS Study

Objective: Treatment of paediatric obesity focuses on changes of nutrition and eating behaviour and physical activity. The evaluation of the patient education programme by KgAS was utilised to analyse the association of changes of portion size, eating rate and dietary habits with BMI-SDS reductions. Methods: Patients (n = 297) were examined at the beginning and at the end of treatment and after 1-year follow-up at different out-patient centres. Their parents completed questionnaires including estimation of children's portion size, eating rate and frequency of food intake. Associations of 1- and 2-year changes in BMI-SDS and behaviour were calculated for patients with complete data in BMI-SDS, portion size, eating rate, frequency of green, yellow and red food intake (n = 131) by multiple linear regression models. Results: Significant changes were found in the desired direction for BMI-SDS, portion size, eating rate and the intake of unfavourable red food items both after 1 and 2 years as well as for the consumption of favourable green food items after 1 year. Significant positive associations with BMI-SDS reduction after 1 and 2 years were detected for portion size (Cohen's f2 0.13 and 0.09) and eating rate (Cohen's f2 0.20 and 0.10), respectively. Conclusion: Reduced portion sizes and eating rates are associated with BMI-SDS reduction after 1 and 2 years. These findings suggest to focus on appropriate portion sizes and reduced eating rates in patient education programmes

Late-pregnancy dysglycemia in obese pregnancies after negative testing for gestational diabetes and risk of future childhood overweight: An interim analysis from a longitudinal mother-child cohort study

BACKGROUND Maternal pre-conception obesity is a strong risk factor for childhood overweight. However, prenatal mechanisms and their effects in susceptible gestational periods that contribute to this risk are not well understood. We aimed to assess the impact of late-pregnancy dysglycemia in obese pregnancies with negative testing for gestational diabetes mellitus (GDM) on long-term mother-child outcomes. METHODS AND FINDINGS The prospective cohort study Programming of Enhanced Adiposity Risk in Childhood-Early Screening (PEACHES) (n = 1,671) enrolled obese and normal weight mothers from August 2010 to December 2015 with trimester-specific data on glucose metabolism including GDM status at the end of the second trimester and maternal glycated hemoglobin (HbA1c) at delivery as a marker for late-pregnancy dysglycemia (HbA1c \geq 5.7% 39 mmol/mol). We assessed offspring short- and long-term outcomes up to 4 years, and maternal glucose metabolism 3.5 years postpartum. Multivariable linear and log-binomial regression with effects presented as mean increments (\textgreek{D}) or relative risks (RRs) with 95{\%} confidence intervals (CIs) were used to examine the association between late-pregnancy dysglycemia and outcomes. Linear mixed-effects models were used to study the longitudinal development of offspring body mass index (BMI) z-scores. The contribution of late-pregnancy dysglycemia to the association between maternal pre-conception obesity and offspring BMI was estimated using mediation analysis. In all, 898 mother-child pairs were included in this unplanned interim analysis. Among obese mothers with negative testing for GDM (n = 448), those with late-pregnancy dysglycemia (n = 135, 30.1{\%}) had higher proportions of excessive total gestational weight gain (GWG), excessive third-trimester GWG, and offspring with large-for-gestational-age birth weight than those without. Besides higher birth weight (\textgreek{D} 192 g, 95{\%} CI 100-284) and cord-blood C-peptide concentration (\textgreek{D} 0.10 ng/ml, 95{\%} CI 0.02-0.17), offspring of these women had greater weight gain during early childhood (\textgreek{D} BMI z-score per year 0.18, 95{\%} CI 0.06-0.30, n = 262) and higher BMI z-score at 4 years (\textgreek{D} 0.58, 95{\%} CI 0.18-0.99, n = 43) than offspring of the obese, GDM-negative mothers with normal HbA1c values at delivery. Late-pregnancy dysglycemia in GDM-negative mothers accounted for about one-quarter of the association of maternal obesity with offspring BMI at age 4 years (n = 151). In contrast, childhood BMI z-scores were not affected by a diagnosis of GDM in obese pregnancies (GDM-positive: 0.58, 95{\%} CI 0.36-0.79, versus GDM-negative: 0.62, 95{\%} CI 0.44-0.79). One mechanism triggering late-pregnancy dysglycemia in obese, GDM-negative mothers was related to excessive third-trimester weight gain (RR 1.72, 95{\%} CI 1.12-2.65). Furthermore, in the maternal population, we found a 4-fold (RR 4.01, 95{\%} CI 1.97-8.17) increased risk of future prediabetes or diabetes if obese, GDM-negative women had a high versus normal HbA1c at delivery (absolute risk: 43.2{\%} versus 10.5{\%}). There is a potential for misclassification bias as the predominantly used GDM test procedure changed over the enrollment period. Further studies are required to validate the findings and elucidate the possible third-trimester factors contributing to future mother-child health status. CONCLUSIONS Findings from this interim analysis suggest that offspring of obese mothers treated because of a diagnosis of GDM appeared to have a better BMI outcome in childhood than those of obese mothers who-following negative GDM testing-remained untreated in the last trimester and developed dysglycemia. Late-pregnancy dysglycemia related to uncontrolled weight gain may contribute to the development of child overweight and maternal diabetes. Our data suggest that negative GDM testing in obese pregnancies is not an {\textquotedbl}all-clear signal{\textquotedbl} and should not lead to reduced attention and risk awareness of physicians and obese women. Effective strategies are needed to maintain third-trimester glycemic and weight gain control among otherwise healthy obese pregnant women