Bommer, Christian

[["dc.bibliographiccitation.artnumber","e067582"],["dc.bibliographiccitation.journal","BMJ"],["dc.contributor.author","Theilmann, Michaela"],["dc.contributor.author","Lemp, Julia M"],["dc.contributor.author","Winkler, Volker"],["dc.contributor.author","Manne-Goehler, Jennifer"],["dc.contributor.author","Marcus, Maja E"],["dc.contributor.author","Probst, Charlotte"],["dc.contributor.author","Lopez-Arboleda, William A"],["dc.contributor.author","Ebert, Cara"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Mathur, Maya"],["dc.contributor.author","Geldsetzer, Pascal"],["dc.date.accessioned","2022-09-01T09:50:48Z"],["dc.date.available","2022-09-01T09:50:48Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract\r\n \r\n Objectives\r\n To determine the prevalence and frequency of using any tobacco product and each of a detailed set of tobacco products, how tobacco use and frequency of use vary across countries, world regions, and World Bank country income groups, and the socioeconomic and demographic gradients of tobacco use and frequency of use within countries.\r\n \r\n \r\n Design\r\n Secondary analysis of nationally representative, cross-sectional, household survey data from 82 low and middle income countries collected between 1 January 2015 and 31 December 2020.\r\n \r\n \r\n Setting\r\n Population based survey data.\r\n \r\n \r\n Participants\r\n 1 231 068 individuals aged 15 years and older.\r\n \r\n \r\n Main outcome measures\r\n Self-reported current smoking, current daily smoking, current smokeless tobacco use, current daily smokeless tobacco use, pack years, and current use and use frequencies of each tobacco product. Products were any type of cigarette, manufactured cigarette, hand rolled cigarette, water pipe, cigar, oral snuff, nasal snuff, chewing tobacco, and betel nut (with and without tobacco).\r\n \r\n \r\n Results\r\n The smoking prevalence in the study sample was 16.5% (95% confidence interval 16.1% to 16.9%) and ranged from 1.1% (0.9% to 1.3%) in Ghana to 50.6% (45.2% to 56.1%) in Kiribati. The user prevalence of smokeless tobacco was 7.7% (7.5% to 8.0%) and prevalence was highest in Papua New Guinea (daily user prevalence of 65.4% (63.3% to 67.5%)). Although variation was wide between countries and by tobacco product, for many low and middle income countries, the highest prevalence and cigarette smoking frequency was reported in men, those with lower education, less household wealth, living in rural areas, and higher age.\r\n \r\n \r\n Conclusions\r\n Both smoked and smokeless tobacco use and frequency of use vary widely across tobacco products in low and middle income countries. This study can inform the design and targeting of efforts to reduce tobacco use in low and middle income countries and serve as a benchmark for monitoring progress towards national and international goals."],["dc.description.sponsorship"," http://dx.doi.org/10.13039/100000060 National Institute of Allergy and Infectious Diseases"],["dc.identifier.doi","10.1136/bmj-2021-067582"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113807"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-597"],["dc.relation.eissn","1756-1833"],["dc.rights.uri","http://creativecommons.org/licenses/by-nc/4.0/"],["dc.title","Patterns of tobacco use in low and middle income countries by tobacco product and sociodemographic characteristics: nationally representative survey data from 82 countries"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","e001175"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMJ Global Health"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Vollmer, Sebastian"],["dc.contributor.author","Subramanian, S V"],["dc.date.accessioned","2019-07-09T11:49:58Z"],["dc.date.available","2019-07-09T11:49:58Z"],["dc.date.issued","2019"],["dc.description.abstract","Introduction Reducing stunting is an important part of the global health agenda. Despite likely changes in risk factors as children age, determinants of stunting are typically analysed without taking into account age-related heterogeneity. We aim to fill this gap by providing an in-depth analysis of the role of socioeconomic status (SES) as a moderator for the stunting-age pattern. Methods Epidemiological and socioeconomic data from 72 Demographic and Health Surveys (DHS) were used to calculate stunting-age patterns by SES quartiles, derived from an index of household assets. We further investigated how differences in age-specific stunting rates between children from rich and poor households are explained by determinants that could be modified by nutrition-specific versus nutrition-sensitive interventions. Results While stunting prevalence in the pooled sample of 72 DHS is low in children up to the age of 5 months (maximum prevalence of 17.8% (95% CI 16.4;19.3)), stunting rates in older children tend to exceed those of younger ones in the age bracket of 6–20 months. This pattern is more pronounced in the poorest than in the richest quartile, with large differences in stunting prevalence at 20 months (stunting rates: 40.7% (95% CI 39.5 to 41.8) in the full sample, 50.3% (95% CI 48.2 to 52.4) in the poorest quartile and 29.2% (95% CI 26.8 to 31.5) in the richest quartile). When adjusting for determinants related to nutrition-specific interventions only, SES-related differences decrease by up to 30.1%. Much stronger effects (up to 59.2%) occur when determinants related to nutrition-sensitive interventions are additionally included. Conclusion While differences between children from rich and poor households are small during the first 5 months of life, SES is an important moderator for age-specific stunting rates in older children. Determinants related to nutrition-specific interventions are not sufficient to explain these SES-related differences, which could imply that a multifactorial approach is needed to reduce age-specific stunting rates in the poorest children."],["dc.identifier.doi","10.1136/bmjgh-2018-001175"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15820"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59665"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.rights","CC BY-NC 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by-nc/4.0"],["dc.subject.ddc","300"],["dc.subject.ddc","320"],["dc.title","How socioeconomic status moderates the stunting-age relationship in low-income and middle-income countries"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","423"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","The Lancet Diabetes & Endocrinology"],["dc.bibliographiccitation.lastpage","430"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Heesemann, Esther"],["dc.contributor.author","Sagalova, Vera"],["dc.contributor.author","Manne-Goehler, Jennifer"],["dc.contributor.author","Atun, Rifat"],["dc.contributor.author","Bärnighausen, Till"],["dc.contributor.author","Vollmer, Sebastian"],["dc.date.accessioned","2020-12-10T15:22:06Z"],["dc.date.available","2020-12-10T15:22:06Z"],["dc.date.issued","2017"],["dc.description.abstract","Background Differences in methods and data used in past studies have limited comparisons of the cost of illness of diabetes across countries. We estimate the full global economic burden of diabetes in adults aged 20-79 years in 2015, using a unified framework across all countries. Our objective was to highlight patterns of diabetes-associated costs as well as to identify the need for further research in low-income regions. Methods Epidemiological and economic data for 184 countries were used to estimate the global economic burden of diabetes, regardless of diabetes type. Direct costs were derived using a top-down approach based on WHO general health expenditure figures and prevalence data from the 2015 International Diabetes Federation Diabetes Atlas. Indirect costs were assessed using a human-capital approach, including diabetes-associated morbidity and premature mortality. Findings We estimate the global cost of diabetes for 2015 was US.31 trillion (95% CI 1.28-1.36) or 1.8% (95% CI 1.8-1.9) of global gross domestic product (GDP). Notably, indirect costs accounted for 34.7% (95% CI 34.7-35.0) of the total burden, although substantial variations existed both in the share and the composition of indirect costs across countries. North America was the most affected region relative to GDP and also the largest contributor to global absolute costs. However, on average, the economic burden as percentage of GDP was larger in middle-income countries than in high-income countries. Interpretation Our results suggest a substantial global economic burden of diabetes. Although limited data were available for low-income and middle-income countries, our findings suggest that large diabetes-associated costs are not only a problem in high-income settings but also affect poorer world regions."],["dc.identifier.doi","10.1016/S2213-8587(17)30097-9"],["dc.identifier.isi","000401817500019"],["dc.identifier.issn","2213-8587"],["dc.identifier.pmid","28456416"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73276"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.issn","2213-8587"],["dc.title","The global economic burden of diabetes in adults aged 20–79 years: a cost-of-illness study"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","622"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","The Lancet Diabetes & Endocrinology"],["dc.bibliographiccitation.lastpage","667"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Atun, Rifat"],["dc.contributor.author","Davies, Justine I"],["dc.contributor.author","Gale, Edwin A M"],["dc.contributor.author","Bärnighausen, Till"],["dc.contributor.author","Beran, David"],["dc.contributor.author","Kengne, Andre Pascal"],["dc.contributor.author","Levitt, Naomi S"],["dc.contributor.author","Mangugu, Florence W"],["dc.contributor.author","Nyirenda, Moffat J"],["dc.contributor.author","Ogle, Graham D"],["dc.contributor.author","Ramaiya, Kaushik"],["dc.contributor.author","Sewankambo, Nelson K"],["dc.contributor.author","Sobngwi, Eugene"],["dc.contributor.author","Tesfaye, Solomon"],["dc.contributor.author","Yudkin, John S"],["dc.contributor.author","Basu, Sanjay"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Heesemann, Esther"],["dc.contributor.author","Manne-Goehler, Jennifer"],["dc.contributor.author","Postolovska, Iryna"],["dc.contributor.author","Sagalova, Vera"],["dc.contributor.author","Vollmer, Sebastian"],["dc.contributor.author","Abbas, Zulfiqarali G"],["dc.contributor.author","Ammon, Benjamin"],["dc.contributor.author","Angamo, Mulugeta Terekegn"],["dc.contributor.author","Annamreddi, Akhila"],["dc.contributor.author","Awasthi, Ananya"],["dc.contributor.author","Besançon, Stéphane"],["dc.contributor.author","Bhadriraju, Sudhamayi"],["dc.contributor.author","Binagwaho, Agnes"],["dc.contributor.author","Burgess, Philip I"],["dc.contributor.author","Burton, Matthew J"],["dc.contributor.author","Chai, Jeanne"],["dc.contributor.author","Chilunga, Felix P"],["dc.contributor.author","Chipendo, Portia"],["dc.contributor.author","Conn, Anna"],["dc.contributor.author","Joel, Dipesalema R"],["dc.contributor.author","Eagan, Arielle W"],["dc.contributor.author","Gishoma, Crispin"],["dc.contributor.author","Ho, Julius"],["dc.contributor.author","Jong, Simcha"],["dc.contributor.author","Kakarmath, Sujay S"],["dc.contributor.author","Khan, Yasmin"],["dc.contributor.author","Kharel, Ramu"],["dc.contributor.author","Kyle, Michael A"],["dc.contributor.author","Lee, Seitetz C"],["dc.contributor.author","Lichtman, Amos"],["dc.contributor.author","Malm, Carl P"],["dc.contributor.author","Mbaye, Maïmouna N"],["dc.contributor.author","Muhimpundu, Marie A"],["dc.contributor.author","Mwagomba, Beatrice M"],["dc.contributor.author","Mwangi, Kibachio Joseph"],["dc.contributor.author","Nair, Mohit"],["dc.contributor.author","Niyonsenga, Simon P"],["dc.contributor.author","Njuguna, Benson"],["dc.contributor.author","Okafor, Obiageli L O"],["dc.contributor.author","Okunade, Oluwakemi"],["dc.contributor.author","Park, Paul H"],["dc.contributor.author","Pastakia, Sonak D"],["dc.contributor.author","Pekny, Chelsea"],["dc.contributor.author","Reja, Ahmed"],["dc.contributor.author","Rotimi, Charles N"],["dc.contributor.author","Rwunganira, Samuel"],["dc.contributor.author","Sando, David"],["dc.contributor.author","Sarriera, Gabriela"],["dc.contributor.author","Sharma, Anshuman"],["dc.contributor.author","Sidibe, Assa"],["dc.contributor.author","Siraj, Elias S"],["dc.contributor.author","Syed, Azhra S"],["dc.contributor.author","Van Acker, Kristien"],["dc.contributor.author","Werfalli, Mahmoud"],["dc.date.accessioned","2020-12-10T15:22:07Z"],["dc.date.available","2020-12-10T15:22:07Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1016/S2213-8587(17)30181-X"],["dc.identifier.issn","2213-8587"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73277"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Diabetes in sub-Saharan Africa: from clinical care to health policy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","108072"],["dc.bibliographiccitation.journal","Diabetes Research and Clinical Practice"],["dc.bibliographiccitation.volume","162"],["dc.contributor.author","Williams, Rhys"],["dc.contributor.author","Karuranga, Suvi"],["dc.contributor.author","Malanda, Belma"],["dc.contributor.author","Saeedi, Pouya"],["dc.contributor.author","Basit, Abdul"],["dc.contributor.author","Besançon, Stéphane"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Esteghamati, Alireza"],["dc.contributor.author","Ogurtsova, Katherine"],["dc.contributor.author","Zhang, Ping"],["dc.contributor.author","Colagiuri, Stephen"],["dc.date.accessioned","2021-04-14T08:26:50Z"],["dc.date.available","2021-04-14T08:26:50Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1016/j.diabres.2020.108072"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82093"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.issn","0168-8227"],["dc.title","Global and regional estimates and projections of diabetes-related health expenditure: Results from the International Diabetes Federation Diabetes Atlas, 9th edition"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","104604"],["dc.bibliographiccitation.journal","Journal of Public Economics"],["dc.bibliographiccitation.volume","208"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Dreher, Axel"],["dc.contributor.author","Perez-Alvarez, Marcello"],["dc.date.accessioned","2022-09-01T09:49:43Z"],["dc.date.available","2022-09-01T09:49:43Z"],["dc.date.issued","2022"],["dc.identifier.doi","10.1016/j.jpubeco.2022.104604"],["dc.identifier.pii","S0047272722000068"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113507"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-597"],["dc.relation.issn","0047-2727"],["dc.rights.uri","https://www.elsevier.com/tdm/userlicense/1.0/"],["dc.title","Home bias in humanitarian aid: The role of regional favoritism in the allocation of international disaster relief"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","53"],["dc.bibliographiccitation.journal","Journal of Clinical Epidemiology"],["dc.bibliographiccitation.lastpage","66"],["dc.bibliographiccitation.volume","89"],["dc.contributor.author","Bärnighausen, Till"],["dc.contributor.author","Oldenburg, Catherine"],["dc.contributor.author","Tugwell, Peter"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Ebert, Cara"],["dc.contributor.author","Barreto, Mauricio"],["dc.contributor.author","Djimeu, Eric"],["dc.contributor.author","Haber, Noah"],["dc.contributor.author","Waddington, Hugh"],["dc.contributor.author","Rockers, Peter"],["dc.contributor.author","Sianesi, Barbara"],["dc.contributor.author","Bor, Jacob"],["dc.contributor.author","Fink, Günther"],["dc.contributor.author","Valentine, Jeffrey"],["dc.contributor.author","Tanner, Jeffrey"],["dc.contributor.author","Stanley, Tom"],["dc.contributor.author","Sierra, Eduardo"],["dc.contributor.author","Tchetgen, Eric Tchetgen"],["dc.contributor.author","Atun, Rifat"],["dc.contributor.author","Vollmer, Sebastian"],["dc.date.accessioned","2020-12-10T14:25:00Z"],["dc.date.available","2020-12-10T14:25:00Z"],["dc.date.issued","2017"],["dc.description.abstract","Quasi-experimental designs are gaining popularity in epidemiology and health systems research—in particular for the evaluation of health care practice, programs, and policy—because they allow strong causal inferences without randomized controlled experiments. We describe the concepts underlying five important quasi-experimental designs: Instrumental Variables, Regression Discontinuity, Interrupted Time Series, Fixed Effects, and Difference-in-Differences designs. We illustrate each of the designs with an example from health research. We then describe the assumptions required for each of the designs to ensure valid causal inference and discuss the tests available to examine the assumptions."],["dc.identifier.doi","10.1016/j.jclinepi.2017.02.017"],["dc.identifier.issn","0895-4356"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/72403"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Department für Volkswirtschaftslehre (VWL)"],["dc.title","Quasi-experimental study designs series—paper 7: assessing the assumptions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","submitted_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","345"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Annual Review of Resource Economics"],["dc.bibliographiccitation.lastpage","366"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Mittal, Nitya"],["dc.contributor.author","Vollmer, Sebastian"],["dc.date.accessioned","2021-04-14T08:27:24Z"],["dc.date.available","2021-04-14T08:27:24Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1146/annurev-resource-110519-093256"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82282"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1941-1359"],["dc.relation.issn","1941-1340"],["dc.title","The Impact of Nutritional Interventions on Child Health and Cognitive Development"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","312"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","International Journal of Epidemiology"],["dc.bibliographiccitation.lastpage","323"],["dc.bibliographiccitation.volume","46"],["dc.contributor.author","Vollmer, Sebastian"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Krishna, Aditi"],["dc.contributor.author","Harttgen, Kenneth"],["dc.contributor.author","Subramanian, S. V."],["dc.date.accessioned","2018-11-07T10:27:36Z"],["dc.date.available","2018-11-07T10:27:36Z"],["dc.date.issued","2017"],["dc.description.abstract","Background: Most existing research on the association of parental education with childhood undernutrition focuses on maternal education and often ignores paternal education. We systematically investigate differences in maternal and paternal education and their association with childhood undernutrition. Methods: One hundred and eighty Demographic and Health Surveys from 62 countries performed between 1990 and 2014 were analysed. We used linear-probability models to predict childhood undernutrition prevalences, measured as stunting, underweight and wasting, for all combinations of maternal and paternal attainment in school. Models were adjusted for demographic and socio-economic covariates for the child, mother and household, country-level fixed effects and clustering. Additional specifications adjust for local area characteristics instead of country fixed effects. Results: Both higher maternal and paternal education levels are associated with lower childhood undernutrition. In regressions adjusted for child age and sex as well as country-level fixed effects, the association is stronger for maternal education than for paternal education when their combined level of education is held constant. In the fully adjusted models, the observed differences in predicted undernutrition prevalences are strongly attenuated, suggesting a similar importance of maternal and paternal education. These findings are confirmed by the analysis of composite schooling indicators. Conclusions: We find that paternal education is similarly important for reducing childhood undernutrition as maternal education and should therefore receive increased attention in the literature."],["dc.identifier.doi","10.1093/ije/dyw133"],["dc.identifier.isi","000402724100041"],["dc.identifier.pmid","27501820"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/43265"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1464-3685"],["dc.relation.issn","0300-5771"],["dc.title","The association of parental education with childhood undernutrition in low- and middle-income countries: comparing the role of paternal and maternal education"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","963"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Diabetes Care"],["dc.bibliographiccitation.lastpage","970"],["dc.bibliographiccitation.volume","41"],["dc.contributor.author","Bommer, Christian"],["dc.contributor.author","Sagalova, Vera"],["dc.contributor.author","Heesemann, Esther"],["dc.contributor.author","Manne-Goehler, Jennifer"],["dc.contributor.author","Atun, Rifat"],["dc.contributor.author","Bärnighausen, Till"],["dc.contributor.author","Davies, Justine"],["dc.contributor.author","Vollmer, Sebastian"],["dc.date.accessioned","2020-12-10T18:43:45Z"],["dc.date.available","2020-12-10T18:43:45Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.2337/dc17-1962"],["dc.identifier.eissn","1935-5548"],["dc.identifier.issn","0149-5992"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78223"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]