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Guion M, Mandereau-Bruno L, Goria S, Cosson E, Fosse-Edorh S. Eleven-year trends in socioeconomic inequalities in the prevalence and incidence of pharmacologically treated type 2 diabetes in France, 2010-2020. Diabetes Metab 2024; 50:101509. [PMID: 38216030 DOI: 10.1016/j.diabet.2024.101509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 12/20/2023] [Accepted: 12/29/2023] [Indexed: 01/14/2024]
Abstract
AIM This study aimed to describe the association between socioeconomic inequalities and the prevalence and incidence of pharmacologically-treated type 2 diabetes in European France over the 2010-2020 period. METHODS Diabetes cases were identified using a validated algorithm from the French National Health Data System. Analysis was restricted to adults aged 45 years and older to focus on type 2 diabetes. Socioeconomic inequalities were measured for all years in European France using the French deprivation index (FDep, 2015 version), which is an area-based deprivation indicator using population-weighted quintiles (Q1 corresponds to the least deprived municipalities). The relative risks of diabetes prevalence and incidence associated with FDep quintiles (Q1 as the reference) were estimated by sex using a log-linear Poisson model adjusted for year, age and French department. The study population was the French health consumers aged 45 years and over (from 24,228,526 in 2010 to 29,772,928 in 2020). RESULTS A positive gradient was observed in the relative risks of type 2 diabetes prevalence and incidence by FDep quintiles over the study period. The strength of the estimated associations increased over the last decade for prevalence among men and women and for incidence among men in the two most deprived quintiles. CONCLUSION Thus, type 2 diabetes prevention should include a proportionate universalism approach, proposing actions of greater intensity in the most deprived areas.
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Affiliation(s)
- Marie Guion
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France; Recherche en Epidémiologie Nutritionnelle (EREN), Université Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Bobigny, France.
| | | | - Sarah Goria
- Data science division, Santé Publique France, Saint-Maurice, France
| | - Emmanuel Cosson
- Recherche en Epidémiologie Nutritionnelle (EREN), Université Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Bobigny, France; Department of Endocrinology-Diabetology-Nutrition, Avicenne Hospital, University of Paris 13, Sorbonne Paris Cité, CRNH-IdF, CINFO, AP-HP, Bobigny, France
| | - Sandrine Fosse-Edorh
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
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Regnault N, Lebreton E, Tang L, Fosse-Edorh S, Barry Y, Olié V, Billionnet C, Weill A, Vambergue A, Cosson E. Maternal and neonatal outcomes according to the timing of diagnosis of hyperglycaemia in pregnancy: a nationwide cross-sectional study of 695,912 deliveries in France in 2018. Diabetologia 2024; 67:516-527. [PMID: 38182910 PMCID: PMC10844424 DOI: 10.1007/s00125-023-06066-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 11/02/2023] [Indexed: 01/07/2024]
Abstract
AIMS/HYPOTHESIS We aimed to assess maternal-fetal outcomes according to various subtypes of hyperglycaemia in pregnancy. METHODS We used data from the French National Health Data System (Système National des Données de Santé), which links individual data from the hospital discharge database and the French National Health Insurance information system. We included all deliveries after 22 gestational weeks (GW) in women without pre-existing diabetes recorded in 2018. Women with hyperglycaemia were classified as having overt diabetes in pregnancy or gestational diabetes mellitus (GDM), then categorised into three subgroups according to their gestational age at the time of GDM diagnosis: before 22 GW (GDM<22); between 22 and 30 GW (GDM22-30); and after 30 GW (GDM>30). Adjusted prevalence ratios (95% CI) for the outcomes were estimated after adjusting for maternal age, gestational age and socioeconomic status. Due to the multiple tests, we considered an association to be statistically significant according to the Holm-Bonferroni procedure. To take into account the potential immortal time bias, we performed analyses on deliveries at ≥31 GW and deliveries at ≥37 GW. RESULTS The study population of 695,912 women who gave birth in 2018 included 84,705 women (12.2%) with hyperglycaemia in pregnancy: overt diabetes in pregnancy, 0.4%; GDM<22, 36.8%; GDM22-30, 52.4%; and GDM>30, 10.4%. The following outcomes were statistically significant after Holm-Bonferroni adjustment for deliveries at ≥31 GW using GDM22-30 as the reference. Caesarean sections (1.54 [1.39, 1.72]), large-for-gestational-age (LGA) infants (2.00 [1.72, 2.32]), Erb's palsy or clavicle fracture (6.38 [2.42, 16.8]), preterm birth (1.84 [1.41, 2.40]) and neonatal hypoglycaemia (1.98 [1.39, 2.83]) were more frequent in women with overt diabetes. Similarly, LGA infants (1.10 [1.06, 1.14]) and Erb's palsy or clavicle fracture (1.55 [1.22, 1.99]) were more frequent in GDM<22. LGA infants (1.44 [1.37, 1.52]) were more frequent in GDM>30. Finally, women without hyperglycaemia in pregnancy were less likely to have preeclampsia or eclampsia (0.74 [0.69, 0.79]), Caesarean section (0.80 [0.79, 0.82]), pregnancy and postpartum haemorrhage (0.93 [0.89, 0.96]), LGA neonate (0.67 [0.65, 0.69]), premature neonate (0.80 [0.77, 0.83]) and neonate with neonatal hypoglycaemia (0.73 [0.66, 0.82]). Overall, the results were similar for deliveries at ≥37 GW. Although the estimation of the adjusted prevalence ratio of perinatal death was five times higher (5.06 [1.87, 13.7]) for women with overt diabetes, this result was non-significant after Holm-Bonferroni adjustment. CONCLUSIONS/INTERPRETATION Compared with GDM22-30, overt diabetes, GDM<22 and, to a lesser extent, GDM>30 were associated with poorer maternal-fetal outcomes.
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Affiliation(s)
- Nolwenn Regnault
- Santé Publique France, the national public health agency, Saint-Maurice, France
| | - Elodie Lebreton
- Santé Publique France, the national public health agency, Saint-Maurice, France
| | - Luveon Tang
- Santé Publique France, the national public health agency, Saint-Maurice, France
| | | | - Yaya Barry
- Santé Publique France, the national public health agency, Saint-Maurice, France
| | - Valérie Olié
- Santé Publique France, the national public health agency, Saint-Maurice, France
| | | | - Alain Weill
- EPI-PHARE Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM) and French National Health Insurance (CNAM), Saint-Denis, France
| | - Anne Vambergue
- Endocrinology, Diabetology, Metabolism and Nutrition Department, Lille University Hospital, European Genomics Institute for Diabetes, University of Lille, Lille, France
| | - Emmanuel Cosson
- Department of Diabetology-Endocrinology-Nutrition, CRNH-IdF, CINFO, Paris 13 University, Sorbonne Paris Cité, AP-HP, Avicenne Hospital, Bobigny, France.
- Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), Université Sorbonne Paris Nord and Université Paris CitéInserm, INRAE, CNAM, Bobigny, France.
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Tang L, Lebreton E, Vambergue A, Fosse-Edorh S, Olié V, Barry Y, Weill A, Cosson E, Regnault N. Cross-sectional study examining factors impacting on uptake of postpartum type 2 diabetes screening among women diagnosed with hyperglycaemia in pregnancy. Diabetes Res Clin Pract 2024; 208:111116. [PMID: 38266823 DOI: 10.1016/j.diabres.2024.111116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/16/2024] [Accepted: 01/21/2024] [Indexed: 01/26/2024]
Abstract
AIMS Early postpartum glucose screening of women with hyperglycaemia in pregnancy (HIP) can identify women who have the highest risk of developing impaired glucose tolerance and T2DM. This study examines the association between demographics, events during pregnancy, socioeconomic status and postpartum T2DM screening. METHODS Using the French National Health Data System, this cross-sectional study included all deliveries where the mother had HIP in France in 2015, (n = 76,862). The odds ratio (OR) for attending postpartum screening was calculated via multi-level logistic regression. RESULTS T2DM screening uptake at six months postpartum was 42·9% [95 % Confidence Interval: 42·6-43·3]. Several characteristics were associated with lower uptake: living in the most deprived area(OR = 0·78[0·74-0·83]); being < 25 years-old (reference age group 25-29;≤17: 0.53 [0·31-0·90];18-24: 0.73[0·69-0·78]); smoking (0·65[0·62-0·68]); obesity (0·93[0·89-0·97]); caesarean delivery (0·95[0·92-0·99]). Factors associated with higher uptake included primiparity (1·30[1·26-1·34]); having followed the French recommendations for HIP screening (1·24[1·20-1·28]); insulin prescription (1·75[1·69-1·81]) and pre-eclampsia (1·30[1·19-1·42]). p < 0.01 is justified due to sample size. CONCLUSION Improving identification of factors affecting postpartum T2DM screening uptake, such as demographics, socioeconomic context and events during pregnancy, may lead to development of target interventions to aide adherence to screening regime and thereby diagnosis of women with prediabetes or diabetes, for whom secondary and tertiary prevention is crucial.
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Affiliation(s)
- Luveon Tang
- Santé Publique France, French National Public Health Agency, S(t) Maurice, France.
| | - Elodie Lebreton
- Santé Publique France, French National Public Health Agency, S(t) Maurice, France
| | - Anne Vambergue
- Endocrinology, Diabetology, Metabolism and Nutrition Department, Lille University Hospital, European Genomics Institute for Diabetes, University of Lille, France
| | - Sandrine Fosse-Edorh
- Santé Publique France, French National Public Health Agency, S(t) Maurice, France
| | - Valérie Olié
- Santé Publique France, French National Public Health Agency, S(t) Maurice, France
| | - Yaya Barry
- Santé Publique France, French National Public Health Agency, S(t) Maurice, France
| | - Alain Weill
- EPI-PHARE Epidemiology of Health Products, French National Agency for Medicines and Health Products Safety (ANSM) and French National Health Insurance (CNAM), Saint-Denis, France; Paris 13 University, Sorbonne Paris Cité, AP-HP, Avicenne Hospital, Department of Endocrinology, CRNH-IdF, CINFO, Bobigny, France
| | - Emmanuel Cosson
- Paris 13 University, Sorbonne Paris Cité, UMR U557 INSERM/U11125 INRA, France
| | - Nolwenn Regnault
- Santé Publique France, French National Public Health Agency, S(t) Maurice, France
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Soyer J, Gabet A, Grave C, Piffaretti C, Verdot C, Salanave B, Deschamps V, Fosse-Edorh S, Carcaillon-Bentata L, Olié V. Need for improvement of cardiovascular health: a clustering method to identify cardiovascular health profiles. Eur J Public Health 2023:7187096. [PMID: 37255383 PMCID: PMC10393485 DOI: 10.1093/eurpub/ckad048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND In France, the overall trend in the incidence of cardiovascular disease is unfavourable, especially in young subjects. This highlights the need to promote cardiovascular health by targeting the main risk factors. Social marketing campaigns to improve cardiovascular health should identify unhealthy behaviour and understand the target audience. The objective of this study was to identify poor cardiovascular health profiles in the French population using a clustering method. METHODS Subjects aged 18-74 years with no history of cardiovascular disease were included from the Esteban cross-sectional survey (2014-16). To evaluate cardiovascular health, seven items were considered as defined by the American Heart Association: blood glucose, blood cholesterol, blood pressure, body mass index, cigarette smoking, diet and physical activity. Cardiovascular health profiles were identified from these seven items by combining multiple correspondence analysis with hierarchical clustering and partitioning. RESULTS A total of 1673 subjects were included in the main analysis. Five cardiovascular health profiles were identified: two profiles corresponded to subjects with poor cardiovascular health (mainly older men with a low socioeconomic status), two to subjects with intermediate cardiovascular health (one mainly comprised of young women with a low socioeconomic status and the other of young subjects with a high socioeconomic status) and one to subjects with good cardiovascular health (mainly older women). CONCLUSION This description of cardiovascular health profiles, which led to the identification and characterization of target audiences for future population-based prevention campaigns, should be the starting point for improving cardiovascular health in the French population.
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Affiliation(s)
- Jessica Soyer
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Amélie Gabet
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Clémence Grave
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Clara Piffaretti
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Charlotte Verdot
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Benoit Salanave
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Valérie Deschamps
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Sandrine Fosse-Edorh
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Laura Carcaillon-Bentata
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Valérie Olié
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
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Delepierre J, Fosse-Edorh S, Fillol C, Piffaretti C. Relation of urinary bisphenol concentration and diabetes or prediabetes in French adults: A cross-sectional study. PLoS One 2023; 18:e0283444. [PMID: 36996235 PMCID: PMC10062552 DOI: 10.1371/journal.pone.0283444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 03/08/2023] [Indexed: 04/01/2023] Open
Abstract
BACKGROUND International research has recently shown an association between exposure to bisphenol A (BPA) and the risk of diabetes, although limited results are available for exposure to bisphenol S (BPS) and bisphenol F (BPF). The aim of this study was to examine the relationships between impregnation with BPA, BPS, and BPF and the prevalence of diabetes or prediabetes in the French adult population. METHODS Based on the Esteban cross-sectional study, 852 adults aged 18 to 74 years living in France were included. To assess the link between urinary concentration of BPA, BPS and BPF and a state of dysglycemia (diabetes or prediabetes), logistic regression multivariable models were performed and adjusted for known risk factors for diabetes and urine creatinine concentration. RESULTS The percentage of included individuals with diabetes or prediabetes was 17.8% (95% CI = [15.3-20.4]). Urinary BPA concentration was significantly higher in people with diabetes or prediabetes, independent of the known risk factors for diabetes (OR for an increase of 0.1 units in log-transformed concentration of BPA (μg/L) = 1.12; 95%CI = [1.05-1.19], p < 0.001). However, we did not find any significant independent association between urinary BPS and BPF levels and the prevalence of diabetes or prediabetes. CONCLUSIONS In this sample, considering the diabetes risk factors, diabetes or prediabetes was positively associated with higher urinary BPA concentration but not with urinary BPS and BPF concentrations. However, analysis of prospective longitudinal studies are still necessary to demonstrate a causal link between bisphenol exposure and the risk of diabetes or prediabetes.
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Affiliation(s)
- Julie Delepierre
- Santé Publique France, The French National Public Health Agency, Saint Maurice, France
| | - Sandrine Fosse-Edorh
- Santé Publique France, The French National Public Health Agency, Saint Maurice, France
| | - Clémence Fillol
- Santé Publique France, The French National Public Health Agency, Saint Maurice, France
| | - Clara Piffaretti
- Santé Publique France, The French National Public Health Agency, Saint Maurice, France
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Tomic D, Morton JI, Chen L, Salim A, Gregg EW, Pavkov ME, Arffman M, Balicer R, Baviera M, Boersma-van Dam E, Brinks R, Carstensen B, Chan JCN, Cheng YJ, Fosse-Edorh S, Fuentes S, Gardiner H, Gulseth HL, Gurevicius R, Ha KH, Hoyer A, Jermendy G, Kautzky-Willer A, Keskimäki I, Kim DJ, Kiss Z, Klimek P, Leventer-Roberts M, Lin CY, Lopez-Doriga Ruiz P, Luk AOY, Ma S, Mata-Cases M, Mauricio D, McGurnaghan S, Imamura T, Paul SK, Peeters A, Pildava S, Porath A, Robitaille C, Roncaglioni MC, Sugiyama T, Wang KL, Wild SH, Yekutiel N, Shaw JE, Magliano DJ. Lifetime risk, life expectancy, and years of life lost to type 2 diabetes in 23 high-income jurisdictions: a multinational, population-based study. Lancet Diabetes Endocrinol 2022; 10:795-803. [PMID: 36183736 PMCID: PMC10988609 DOI: 10.1016/s2213-8587(22)00252-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/21/2022] [Accepted: 08/22/2022] [Indexed: 10/31/2022]
Abstract
BACKGROUND Diabetes is a major public health issue. Because lifetime risk, life expectancy, and years of life lost are meaningful metrics for clinical decision making, we aimed to estimate these measures for type 2 diabetes in the high-income setting. METHODS For this multinational, population-based study, we sourced data from 24 databases for 23 jurisdictions (either whole countries or regions of a country): Australia; Austria; Canada; Denmark; Finland; France; Germany; Hong Kong; Hungary; Israel; Italy; Japan; Latvia; Lithuania; the Netherlands; Norway; Scotland; Singapore; South Korea; Spain; Taiwan; the UK; and the USA. Our main outcomes were lifetime risk of type 2 diabetes, life expectancy in people with and without type 2 diabetes, and years of life lost to type 2 diabetes. We modelled the incidence and mortality of type 2 diabetes in people with and without type 2 diabetes in sex-stratified, age-adjusted, and calendar year-adjusted Poisson models for each jurisdiction. Using incidence and mortality, we constructed life tables for people of both sexes aged 20-100 years for each jurisdiction and at two timepoints 5 years apart in the period 2005-19 where possible. Life expectancy from a given age was computed as the area under the survival curves and lifetime lost was calculated as the difference between the expected lifetime of people with versus without type 2 diabetes at a given age. Lifetime risk was calculated as the proportion of each cohort who developed type 2 diabetes between the ages of 20 years and 100 years. We estimated 95% CIs using parametric bootstrapping. FINDINGS Across all study cohorts from the 23 jurisdictions (total person-years 1 577 234 194), there were 5 119 585 incident cases of type 2 diabetes, 4 007 064 deaths in those with type 2 diabetes, and 11 854 043 deaths in those without type 2 diabetes. The lifetime risk of type 2 diabetes ranged from 16·3% (95% CI 15·6-17·0) for Scottish women to 59·6% (58·5-60·8) for Singaporean men. Lifetime risk declined with time in 11 of the 15 jurisdictions for which two timepoints were studied. Among people with type 2 diabetes, the highest life expectancies were found for both sexes in Japan in 2017-18, where life expectancy at age 20 years was 59·2 years (95% CI 59·2-59·3) for men and 64·1 years (64·0-64·2) for women. The lowest life expectancy at age 20 years with type 2 diabetes was observed in 2013-14 in Lithuania (43·7 years [42·7-44·6]) for men and in 2010-11 in Latvia (54·2 years [53·4-54·9]) for women. Life expectancy in people with type 2 diabetes increased with time for both sexes in all jurisdictions, except for Spain and Scotland. The life expectancy gap between those with and without type 2 diabetes declined substantially in Latvia from 2010-11 to 2015-16 and in the USA from 2009-10 to 2014-15. Years of life lost to type 2 diabetes ranged from 2·5 years (Latvia; 2015-16) to 12·9 years (Israel Clalit Health Services; 2015-16) for 20-year-old men and from 3·1 years (Finland; 2011-12) to 11·2 years (Israel Clalit Health Services; 2010-11 and 2015-16) for 20-year-old women. With time, the expected number of years of life lost to type 2 diabetes decreased in some jurisdictions and increased in others. The greatest decrease in years of life lost to type 2 diabetes occurred in the USA between 2009-10 and 2014-15 for 20-year-old men (a decrease of 2·7 years). INTERPRETATION Despite declining lifetime risk and improvements in life expectancy for those with type 2 diabetes in many high-income jurisdictions, the burden of type 2 diabetes remains substantial. Public health strategies might benefit from tailored approaches to continue to improve health outcomes for people with diabetes. FUNDING US Centers for Disease Control and Prevention and Diabetes Australia.
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Affiliation(s)
- Dunya Tomic
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
| | - Jedidiah I Morton
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Centre for Medicine Use and Safety, Monash University, Melbourne, VIC, Australia
| | - Lei Chen
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Agus Salim
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; School of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
| | - Edward W Gregg
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Meda E Pavkov
- Division of Diabetes Translation, Centers for Diseases Control and Prevention, Atlanta, GA, USA
| | - Martti Arffman
- Welfare State Research and Reform, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Ran Balicer
- Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel
| | - Marta Baviera
- Laboratory of Cardiovascular Prevention, Mario Negri Institute for Pharmacological Research, IRCCS, Milan, Italy
| | - Elise Boersma-van Dam
- Department of General Practice, Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Ralph Brinks
- Institute for Biometrics and Epidemiology, German Diabetes Center, Duesseldorf, Germany; Institute for Medical Biometry and Epidemiology, University Witten/Herdecke, Witten, Germany
| | - Bendix Carstensen
- Clinical Epidemiology, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Li Ka Shing Institute of Health Sciences, Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Yiling J Cheng
- Division of Diabetes Translation, Centers for Diseases Control and Prevention, Atlanta, GA, USA
| | - Sandrine Fosse-Edorh
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Sonsoles Fuentes
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Hélène Gardiner
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Hanne L Gulseth
- Department for Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway
| | - Romualdas Gurevicius
- Center of Health Information, Institute of Hygiene, Vilnius, Lithuania; Faculty of Public Governance and Business, Mykolas Romeris University, Vilnius, Lithuania
| | - Kyoung Hwa Ha
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, South Korea
| | - Annika Hoyer
- Biostatistics and Medical Biometry, Medical School EWL, Bielefeld University, Bielefeld, Germany
| | - György Jermendy
- Third Medical Department, Bajcsy-Zsilinszky Hospital, Budapest, Hungary
| | - Alexandra Kautzky-Willer
- Department of Medicine III, Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria; Gender Institute, Gars am Kamp, Austria
| | - Ilmo Keskimäki
- Welfare State Research and Reform, Finnish Institute for Health and Welfare, Helsinki, Finland; Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Dae Jung Kim
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, South Korea
| | - Zoltán Kiss
- Second Department of Medicine and Nephrological Center, University of Pécs, Pécs, Hungary
| | - Peter Klimek
- Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria; Complexity Science Hub Vienna, Vienna, Austria
| | - Maya Leventer-Roberts
- Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chun-Yi Lin
- General Clinical Research Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Paz Lopez-Doriga Ruiz
- Department for Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway; Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Li Ka Shing Institute of Health Sciences, Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China
| | - Stefan Ma
- Epidemiology and Disease Control Division, Public Health Group, Ministry of Health, Singapore
| | - Manel Mata-Cases
- CIBER of Diabetes and Associated Metabolic Diseases, Instituto de Salud Carlos III, Barcelona, Spain; Institut Català de la Salut, Unitat de Suport a la Recerca Barcelona Ciutat, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain
| | - Dídac Mauricio
- CIBER of Diabetes and Associated Metabolic Diseases, Instituto de Salud Carlos III, Barcelona, Spain; Institut Català de la Salut, Unitat de Suport a la Recerca Barcelona Ciutat, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain; Department of Endocrinology, Hospital de la Santa Creu I Sant Pau, Autonomous University of Barcelona, Barcelona, Spain
| | | | - Tomoaki Imamura
- Department of Public Health, Health Management and Policy, Nara Medical University, Nara, Japan
| | - Sanjoy K Paul
- Department of Medicine, University of Melbourne, Melbourne, VIC, Australia
| | - Anna Peeters
- Institute for Health Transformation, Deakin University, Melbourne, VIC, Australia
| | - Santa Pildava
- Research and Health Statistics Department, Centre for Disease Prevention and Control, Riga, Latvia
| | - Avi Porath
- Research Institute, Maccabi Healthcare Services, Tel Aviv, Israel; Faculty of Health Sciences, Ben Gurion University, Beer-Sheva, Israel
| | - Cynthia Robitaille
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Maria Carla Roncaglioni
- Laboratory of Cardiovascular Prevention, Mario Negri Institute for Pharmacological Research, IRCCS, Milan, Italy
| | - Takehiro Sugiyama
- Diabetes and Metabolism Information Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan; Institute for Global Health Policy Research, Bureau of International Health Cooperation, National Center for Global Health and Medicine, Tokyo, Japan; Department of Health Services Research, University of Tsukuba, Tsukuba, Japan
| | - Kang-Ling Wang
- General Clinical Research Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Sarah H Wild
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Naama Yekutiel
- Research Institute, Maccabi Healthcare Services, Tel Aviv, Israel
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Dianna J Magliano
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
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Donzeau A, Piffaretti C, Jossens A, Levaillant L, Bouhours-Nouet N, Amsellem-Jager J, Ghosn W, Rey G, Fosse-Edorh S, Coutant R. Time trend in excess mortality in children with type 1 diabetes from 1987 to 2016 in mainland France. Pediatr Diabetes 2022; 23:38-44. [PMID: 34881493 DOI: 10.1111/pedi.13298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/10/2021] [Accepted: 12/02/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Mortality risk for children with type 1 diabetes (T1D) is unknown in France and their causes of death are not well documented. AIM To determine the standardized mortality ratios (SMRs) and causes of death in children aged 1-14 years with T1D from 1987 to 2016. METHODS The French Center for Epidemiology on Medical Causes of Death collected all death certificates in mainland France. SMRs, corrected SMRs (accounting for missing cases of deaths unrelated to diabetes), and 95% confidence intervals were calculated. RESULTS Of 146 deaths with the contribution of diabetes, 97 were due to T1D. Mean age at death of the subjects with T1D was 8.8 ± 4.1 years (54% males). The cause of death was diabetic ketoacidosis (DKA) in 58% of the cases (70% in subjects 1-4 years), hypoglycemia or dead-in-bed syndrome in 4%, related to diabetes but not described in 24%, and unrelated to diabetes in 14%. The SMRs showed a significant decrease across the years, except for the 1-4 age group. In the last decade (2007-2016), the crude and corrected SMRs were significantly different from 1 in the 1-4 age group (5.4 [2.3; 10.7] and 6.1 [2.8; 11.5]), no longer significant in the 5-9 age group (1.7 [0.6; 4.0] and 2.1 [0.8; 4.5]) and borderline significant in the 10-14 age group (1.7 [0.8; 3.2] and 2.3 [1.2; 4.0]). CONCLUSIONS Children with T1D aged 1-4 years still had a high mortality rate. Their needs for early recognition and safe management of diabetes are not being met.
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Affiliation(s)
| | - Clara Piffaretti
- Santé publique France, The French National Public Health Agency, Saint Maurice, France
| | - Anne Jossens
- Department of Pediatrics, St Malo Hospital, Saint Malo, France
| | | | | | | | - Walid Ghosn
- Centre for Epidemiology on Medical Causes of Death, Inserm-CépiDc, Le Kremlin-Bicêtre, France
| | - Grégoire Rey
- Centre for Epidemiology on Medical Causes of Death, Inserm-CépiDc, Le Kremlin-Bicêtre, France
| | - Sandrine Fosse-Edorh
- Santé publique France, The French National Public Health Agency, Saint Maurice, France
| | - Régis Coutant
- Pediatric Diabetology, University Hospital, Angers, France
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8
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Haneef R, Kab S, Hrzic R, Fuentes S, Fosse-Edorh S, Cosson E, Gallay A. Use of artificial intelligence for public health surveillance: a case study to develop a machine Learning-algorithm to estimate the incidence of diabetes mellitus in France. ACTA ACUST UNITED AC 2021; 79:168. [PMID: 34551816 PMCID: PMC8456679 DOI: 10.1186/s13690-021-00687-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Accepted: 09/02/2021] [Indexed: 11/10/2022]
Abstract
BACKGROUND The use of machine learning techniques is increasing in healthcare which allows to estimate and predict health outcomes from large administrative data sets more efficiently. The main objective of this study was to develop a generic machine learning (ML) algorithm to estimate the incidence of diabetes based on the number of reimbursements over the last 2 years. METHODS We selected a final data set from a population-based epidemiological cohort (i.e., CONSTANCES) linked with French National Health Database (i.e., SNDS). To develop this algorithm, we adopted a supervised ML approach. Following steps were performed: i. selection of final data set, ii. target definition, iii. Coding variables for a given window of time, iv. split final data into training and test data sets, v. variables selection, vi. training model, vii. Validation of model with test data set and viii. Selection of the model. We used the area under the receiver operating characteristic curve (AUC) to select the best algorithm. RESULTS The final data set used to develop the algorithm included 44,659 participants from CONSTANCES. Out of 3468 variables from SNDS linked to CONSTANCES cohort were coded, 23 variables were selected to train different algorithms. The final algorithm to estimate the incidence of diabetes was a Linear Discriminant Analysis model based on number of reimbursements of selected variables related to biological tests, drugs, medical acts and hospitalization without a procedure over the last 2 years. This algorithm has a sensitivity of 62%, a specificity of 67% and an accuracy of 67% [95% CI: 0.66-0.68]. CONCLUSIONS Supervised ML is an innovative tool for the development of new methods to exploit large health administrative databases. In context of InfAct project, we have developed and applied the first time a generic ML-algorithm to estimate the incidence of diabetes for public health surveillance. The ML-algorithm we have developed, has a moderate performance. The next step is to apply this algorithm on SNDS to estimate the incidence of type 2 diabetes cases. More research is needed to apply various MLTs to estimate the incidence of various health conditions.
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Affiliation(s)
- Romana Haneef
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, 12 rue du Val d'Onse, 94415, Saint-Maurice, France.
| | - Sofiane Kab
- Population-Based Epidemiological Cohorts Unit, INSERM UMS 011, Villejuif, France
| | - Rok Hrzic
- Department of International Health, Care and Public Health Research Institute - CAPHRI, University of Maastricht University, Maastricht, The Netherlands
| | - Sonsoles Fuentes
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, 12 rue du Val d'Onse, 94415, Saint-Maurice, France
| | - Sandrine Fosse-Edorh
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, 12 rue du Val d'Onse, 94415, Saint-Maurice, France
| | - Emmanuel Cosson
- Department of Endocrinology-Diabetology-Nutrition, AP-HP, Avicenne Hospital, Paris 13 University, Sorbonne Paris Cité, CRNH-IdF, CINFO, Bobigny, France.,Sorbonne Paris Cité, UMR U1153 Inserm/U1125 Inra/Cnam/Université Paris 13, Bobigny, France
| | - Anne Gallay
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, 12 rue du Val d'Onse, 94415, Saint-Maurice, France
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Magliano DJ, Chen L, Islam RM, Carstensen B, Gregg EW, Pavkov ME, Andes LJ, Balicer R, Baviera M, Boersma-van Dam E, Booth GL, Chan JCN, Chua YX, Fosse-Edorh S, Fuentes S, Gulseth HL, Gurevicius R, Ha KH, Hird TR, Jermendy G, Khalangot MD, Kim DJ, Kiss Z, Kravchenko VI, Leventer-Roberts M, Lin CY, Luk AOY, Mata-Cases M, Mauricio D, Nichols GA, Nielen MM, Pang D, Paul SK, Pelletier C, Pildava S, Porath A, Read SH, Roncaglioni MC, Lopez-Doriga Ruiz P, Shestakova M, Vikulova O, Wang KL, Wild SH, Yekutiel N, Shaw JE. Trends in the incidence of diagnosed diabetes: a multicountry analysis of aggregate data from 22 million diagnoses in high-income and middle-income settings. Lancet Diabetes Endocrinol 2021; 9:203-211. [PMID: 33636102 PMCID: PMC10984526 DOI: 10.1016/s2213-8587(20)30402-2] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 11/24/2020] [Accepted: 11/26/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND Diabetes prevalence is increasing in most places in the world, but prevalence is affected by both risk of developing diabetes and survival of those with diabetes. Diabetes incidence is a better metric to understand the trends in population risk of diabetes. Using a multicountry analysis, we aimed to ascertain whether the incidence of clinically diagnosed diabetes has changed over time. METHODS In this multicountry data analysis, we assembled aggregated data describing trends in diagnosed total or type 2 diabetes incidence from 24 population-based data sources in 21 countries or jurisdictions. Data were from administrative sources, health insurance records, registries, and a health survey. We modelled incidence rates with Poisson regression, using age and calendar time (1995-2018) as variables, describing the effects with restricted cubic splines with six knots for age and calendar time. FINDINGS Our data included about 22 million diabetes diagnoses from 5 billion person-years of follow-up. Data were from 19 high-income and two middle-income countries or jurisdictions. 23 data sources had data from 2010 onwards, among which 19 had a downward or stable trend, with an annual estimated change in incidence ranging from -1·1% to -10·8%. Among the four data sources with an increasing trend from 2010 onwards, the annual estimated change ranged from 0·9% to 5·6%. The findings were robust to sensitivity analyses excluding data sources in which the data quality was lower and were consistent in analyses stratified by different diabetes definitions. INTERPRETATION The incidence of diagnosed diabetes is stabilising or declining in many high-income countries. The reasons for the declines in the incidence of diagnosed diabetes warrant further investigation with appropriate data sources. FUNDING US Centers for Disease Control and Prevention, Diabetes Australia Research Program, and Victoria State Government Operational Infrastructure Support Program.
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Affiliation(s)
- Dianna J Magliano
- Department of Diabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
| | - Lei Chen
- Department of Diabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Rakibul M Islam
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Bendix Carstensen
- Clinical Epidemiology, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Edward W Gregg
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Meda E Pavkov
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Linda J Andes
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ran Balicer
- Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel
| | - Marta Baviera
- Laboratory of Cardiovascular Prevention, Mario Negri Institute for Pharmacological Research IRCCS, Milan, Italy
| | - Elise Boersma-van Dam
- Department of General Practice, Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Gillian L Booth
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yi Xian Chua
- Epidemiology and Disease Control Division, Public Health Group, Ministry of Health, Singapore
| | - Sandrine Fosse-Edorh
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Sonsoles Fuentes
- Department of Non-Communicable Diseases and Trauma, Santé Publique France, Saint-Maurice, France
| | - Hanne L Gulseth
- Department for Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Romualdas Gurevicius
- Center of Health Information, Institute of Hygiene, Vilnius, Lithuania; Faculty of Public Governance and Business, Mykolas Romeris University, Vilnius, Lithuania
| | - Kyoung Hwa Ha
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, South Korea
| | - Thomas R Hird
- Department of Diabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - György Jermendy
- 3rd Medical Department, Bajcsy-Zsilinszky Hospital, Budapest, Hungary
| | - Mykola D Khalangot
- Komisarenko Institute of Endocrinology and Metabolism, National Academy of Medical Sciences, Kyiv, Ukraine; Endocrinology Department, Shupyk National Medical Academy of Postgraduate Education, Kyiv, Ukraine
| | - Dae Jung Kim
- Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, South Korea
| | - Zoltán Kiss
- 2nd Department of Medicine and Nephrological Center, Medical Faculty, University of Pécs, Pécs, Hungary
| | - Victor I Kravchenko
- Komisarenko Institute of Endocrinology and Metabolism, National Academy of Medical Sciences, Kyiv, Ukraine
| | - Maya Leventer-Roberts
- Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel; Department of Pediatrics and Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chun-Yi Lin
- General Clinical Research Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Manel Mata-Cases
- CIBER of Diabetes and Associated Metabolic Diseases, Instituto de Salud Carlos III, Barcelona, Spain; DAP-Cat Group, Institut Català de la Salut, Unitat de Suport a la Recerca Barcelona Ciutat, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain
| | - Didac Mauricio
- CIBER of Diabetes and Associated Metabolic Diseases, Instituto de Salud Carlos III, Barcelona, Spain; DAP-Cat Group, Institut Català de la Salut, Unitat de Suport a la Recerca Barcelona Ciutat, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain; Department of Endocrinology and Nutrition, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Barcelona, Spain
| | - Gregory A Nichols
- Science Programs Department, Kaiser Permanente Center for Health Research, Portland, OR, USA
| | - Mark M Nielen
- Department of General Practice, Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Deanette Pang
- Epidemiology and Disease Control Division, Public Health Group, Ministry of Health, Singapore
| | - Sanjoy K Paul
- Melbourne EpiCentre, University of Melbourne, Melbourne, VIC, Australia
| | - Catherine Pelletier
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Santa Pildava
- Research and Health Statistics Department, Centre for Disease Prevention and Control, Riga, Latvia
| | - Avi Porath
- Research Institute, Maccabi Healthcare Services, Tel Aviv, Israel; Faculty of Health, Ben Gurion University, Beer-Sheva, Israel
| | | | - Maria Carla Roncaglioni
- Laboratory of Cardiovascular Prevention, Mario Negri Institute for Pharmacological Research IRCCS, Milan, Italy
| | - Paz Lopez-Doriga Ruiz
- Department for Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway; Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | | | - Olga Vikulova
- Diabetes Institute, Endocrinology Research Center, Moscow, Russia
| | - Kang-Ling Wang
- General Clinical Research Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Sarah H Wild
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Naama Yekutiel
- Research Institute, Maccabi Healthcare Services, Tel Aviv, Israel
| | - Jonathan E Shaw
- Department of Diabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; School of Life Sciences, Latrobe University, Bundoora, VIC, Australia
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10
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Haneef R, Fuentes S, Hrzic R, Fosse-Edorh S, Kab S, Gallay A, Cosson E. Use of artificial intelligence to estimate population health indicators in France. Eur J Public Health 2020. [DOI: 10.1093/eurpub/ckaa165.267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
The use of artificial intelligence is increasing to estimate and predict health outcomes from large data sets. The main objectives were to develop two algorithms using machine learning techniques to identify new cases of diabetes (case study I) and to classify type 1 and type 2 (case study II) in France.
Methods
We selected the training data set from a cohort study linked with French national Health database (i.e., SNDS). Two final datasets were used to achieve each objective. A supervised machine learning method including eight following steps was developed: the selection of the data set, case definition, coding and standardization of variables, split data into training and test data sets, variable selection, training, validation and selection of the model. We planned to apply the trained models on the SNDS to estimate the incidence of diabetes and the prevalence of type 1/2 diabetes.
Results
For the case study I, 23/3468 and for case study II, 14/3481 SNDS variables were selected based on an optimal balance between variance explained and using the ReliefExp algorithm. We trained four models using different classification algorithms on the training data set. The Linear Discriminant Analysis model performed best in both case studies. The models were assessed on the test datasets and achieved a specificity of 67% and a sensitivity of 62% in case study I, and a specificity of 97 % and sensitivity of 100% in case study II. The case study II model was applied to the SNDS and estimated the prevalence of type 1 diabetes in 2016 in France of 0.3% and for type 2, 4.4%. The case study model I was not applied to the SNDS.
Conclusions
The case study II model to estimate the prevalence of type 1/2 diabetes has good performance and will be used in routine surveillance. The case study I model to identify new cases of diabetes showed a poor performance due to missing necessary information on determinants of diabetes and will need to be improved for further research.
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Affiliation(s)
- R Haneef
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, Saint Maurice, France
| | - S Fuentes
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, Saint Maurice, France
| | - R Hrzic
- Faculty of Health, Medicine and Life Sciences, International Health, School for Public Health and Prim Care, Maastricht University, Maastricht, Netherlands
| | - S Fosse-Edorh
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, Saint Maurice, France
| | - S Kab
- Population-Based Epidemiological Cohorts Unit, Inserm UMS 011, Villejuif, France
| | - A Gallay
- Department of Non-Communicable Diseases and Injuries, Santé Publique France, Saint Maurice, France
| | - E Cosson
- Department of Endocrinology-Diabetology-Nutrition, AP-HP, Avicenne Hospital, Paris 13 University, Sorbonne Paris Cité, CRNH-IdF, CINFO, Bobigny, France
- UMR U1153 Inserm/U1125 Inra/Cnam/Université Paris 13, Sorbonne Paris Cité, Bobigny, France
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11
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Lailler G, Piffaretti C, Fuentes S, Nabe HD, Oleko A, Cosson E, Fosse-Edorh S. Prevalence of prediabetes and undiagnosed type 2 diabetes in France: Results from the national survey ESTEBAN, 2014-2016. Diabetes Res Clin Pract 2020; 165:108252. [PMID: 32526264 DOI: 10.1016/j.diabres.2020.108252] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/27/2020] [Accepted: 06/04/2020] [Indexed: 01/03/2023]
Abstract
AIM To assess the prevalence of prediabetes, undiagnosed diabetes and diagnosed diabetes in France, among adults between 2014 and 2016 using data from the nationwide Esteban survey. METHODS National cross-sectional study conducted between 2014 and 2016 in metropolitan France. Individuals aged 18 to 74 were recruited with a 3-stage geographic sampling. They completed two face-to-face interviews, filled in a self-administered questionnaire and underwent a medical examination with the collection of biological samples. Their data were linked to the National Health Data System to identify anti-diabetic drugs reimbursement. Prediabetes and undiagnosed diabetes were defined as no diagnosis of diabetes and 6.1 mmol/l ≤ Fasting Plasma Glucose (FPG) < 7.0 mmol/l for prediabetes and FPG ≥ 7.0 mmol/l for undiagnosed diabetes. Non-pharmacologically treated diabetes and pharmacologically treated diabetes were defined as self-reported diabetes without or with self-reported or reimbursed antidiabetic medication, respectively. Estimated prevalence were weighted to take into account survey design and non-response. RESULTS The ESTEBAN survey recruited 3476 adults, 2270 were included in this analysis. The weighted prevalence was 1.7% [1.1 - 2.4] for undiagnosed diabetes (men: 2.7%, women; 0.9%), 9.9% [8.3 - 11.5] for prediabetes (men: 13.2%, women: 7.0%), 5.7% [4.3 - 7.1] for diagnosed diabetes. Among the diagnosed cases, 79% were pharmacologically treated. Among all diabetes cases, 23% were undiagnosed. CONCLUSION The prevalence of undiagnosed diabetes and prediabetes is increasing in France. Our results highlight the need to increase primary prevention and reinforce secondary prevention of diabetes.
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Affiliation(s)
- Grégory Lailler
- Santé Publique France, Department of Non-Communicable Diseases and Trauma
| | - Clara Piffaretti
- Santé Publique France, Department of Non-Communicable Diseases and Trauma
| | - Sonsoles Fuentes
- Santé Publique France, Department of Non-Communicable Diseases and Trauma
| | | | - Amivi Oleko
- Santé Publique France, Department of Environmental and Occupational Health, Saint-Maurice, France
| | - Emmanuel Cosson
- Department of Diabetology, Endocrinology and Metabolism, CRNH-IdF, CINFO, Paris 13 University, Sorbonne Paris cité, Avicenne Hospital, AP-HP, 93000 Bobigny, France; UMR U1153 Inserm, U1125 Inra, Cnam, Paris 13 University, Sorbonne Paris cité, 93000 Bobigny, France
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12
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Fuentes S, Mandereau-Bruno L, Regnault N, Bernillon P, Bonaldi C, Cosson E, Fosse-Edorh S. Is the type 2 diabetes epidemic plateauing in France? A nationwide population-based study. Diabetes Metab 2020; 46:472-479. [PMID: 31923577 DOI: 10.1016/j.diabet.2019.12.006] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 12/19/2019] [Accepted: 12/27/2019] [Indexed: 12/15/2022]
Abstract
AIM Nationwide data on the evolution of diabetes incidence and prevalence are scarce in France. For this reason, our objectives were to determine type 2 diabetes prevalence and incidence rates between 2010 and 2017, stratified by gender, age and region, and to assess annual time trends over the study period in adults aged≥45 years. METHODS Diabetes cases in the National Health Data System (SNDS), which covers the entire French population (66 million people), were identified through a validated algorithm. Gender- and age-specific prevalence and incidence rates were estimated. Negative binomial models, adjusted for gender, age and region, were used to assess annual time trends for prevalence and incidence throughout the study period. RESULTS During 2017, 3,144,225 diabetes cases aged≥45 years were identified. Over the study period, prevalence increased slightly (men from 11.5% to 12.1%, women from 7.9% to 8.4%) whereas incidence decreased (men from 11 to 9.7, women from 7.2 to 6.2 per 1000 person-years). In only four groups did prevalence rates decrease: men aged 45-65 years; women aged 45-60 years; women in Reunion; and women in Martinique. An increasing annual time trend was observed for prevalence (men: +0.9% [95% CI: +0.7%, +1%]; women: +0.4% [95% CI: +0.2%, +0.6%]) with a decreasing annual time trend for incidence in both genders (men: -2.6% [95% CI: -3.1%, -2.0%]; women: -3.9% [95% CI: -4.5%, -3.4%]). CONCLUSION Further efforts towards diabetes prevention are required to ensure that incidence rates in France continue to diminish, as the disorder continues to represent an important public-health burden.
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Affiliation(s)
- S Fuentes
- Santé publique France, the French National Public Health Agency, 12, rue du Val d'Osne, 94415 Saint-Maurice, France.
| | - L Mandereau-Bruno
- Santé publique France, the French National Public Health Agency, 12, rue du Val d'Osne, 94415 Saint-Maurice, France
| | - N Regnault
- Santé publique France, the French National Public Health Agency, 12, rue du Val d'Osne, 94415 Saint-Maurice, France
| | - P Bernillon
- Santé publique France, the French National Public Health Agency, 12, rue du Val d'Osne, 94415 Saint-Maurice, France
| | - C Bonaldi
- Santé publique France, the French National Public Health Agency, 12, rue du Val d'Osne, 94415 Saint-Maurice, France
| | - E Cosson
- Department of diabetology, endocrinology and metabolism, CRNH-IdF, CINFO, Paris 13 university, Sorbonne Paris cité, Avicenne hospital, AP-HP, 93000 Bobigny, France; UMR U1153 Inserm, U1125 Inra, Cnam, Paris 13 university, Sorbonne Paris cité, 93000 Bobigny, France
| | - S Fosse-Edorh
- Santé publique France, the French National Public Health Agency, 12, rue du Val d'Osne, 94415 Saint-Maurice, France
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13
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Henry V, Piffaretti C, Saboni L, Gane J, Fosse-Edorh S. The Entred 3 study: a national representative sample of people with diabetes, 3rd edition-France-2019. Eur J Public Health 2019. [DOI: 10.1093/eurpub/ckz185.441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
In France, more than 3.3 million people are pharmacologically treated for diabetes. The 3rd edition of the Entred study was launched in 2019 in order to establish an overview of the epidemiological situation of diabetes since the last studies performed in 2001 and 2007. The main objectives are to describe and assess trends in characteristics of people pharmacologically treated for diabetes, in cost of care and clinical care pathways, in quality of care, in quality of life and in mortality and to focus on specific populations.
Methods
A sample of 13’000 adults has been randomly selected from the two majors French health insurance systems database. Those patients are invited by their health insurance provider to answer to a short phone-based questionnaire and then to a self-administered questionnaire (mailed or by Internet). With the agreement of those patients, their physicians are suggested to answer a questionnaire to collect information concerning their clinical and biological results. A passive follow-up of the sample is implemented by extraction of participants’ reimbursement and hospital discharge data from the SNDS (Système National des Données de Santé) for 20 years (the 10 years previous to and the 10 years following the sampling).
Results
Results expected will present first rates of participation for patients and their physician. Also, a first feedback on the innovative processes of the study, collaborations between institutions and partners will also be presented.
Conclusions
The expected results of this surveillance system based on a complementary approach (self-questionnaire, medical questionnaires and medico-administrative data) are: health status, therapeutics, economic burden, social and the quality of care pathways, the ways to improve medical practice and the quality of life of people with diabetes. Entred 3 would also be a valuable tool for orientating prevention policies that could be transposed to other countries.
Key messages
Entred combines data from people with diabetes, their care providers and extractions of health insurance data. This is a valuable tool for orientating care and prevention policies in diabetes. Entred 3 is the continuation of two previous editions and should provide important information not available in administrative database, is a major tool for all stakeholders involved in diabetes care.
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Affiliation(s)
- V Henry
- Santé Publique France, Saint Maurice, France
| | | | - L Saboni
- Santé Publique France, Saint Maurice, France
| | - J Gane
- Santé Publique France, Saint Maurice, France
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14
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Piffaretti C, Mandereau-Bruno L, Guilmin-Crepon S, Choleau C, Coutant R, Fosse-Edorh S. Trends in childhood type 1 diabetes incidence in France, 2010-2015. Diabetes Res Clin Pract 2019; 149:200-207. [PMID: 30439385 DOI: 10.1016/j.diabres.2018.11.005] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 10/24/2018] [Accepted: 11/05/2018] [Indexed: 01/21/2023]
Abstract
AIMS To estimate type 1 diabetes incidence in children in France and its evolution between 2010 and 2015, based on comprehensive medico-administrative databases. METHODS The algorithm built to identify new cases of type 1 diabetes selected children aged between 6 months and 14 years who had at least one hospital stay for diabetes, followed by their first insulin treatment, excluding children suffering from another form of diabetes. Age and sex specific annual incidence rates were estimated and time trend was analyzed using Poisson regression. RESULTS A total of 12 067 children were identified as newly diagnosed with type 1 diabetes and the annual incidence rates increased between 2010 and 2015 (from 15.4 [95% Confidence Interval: 14.7; 16.1] to 19.1 [18.3; 19.9] per 100 000 person-years), among boys and girls, and in each age group (4 and under, 5-9, 10-14 year olds). The annual rate of increase was 4.0% [3.4; 4.6]. This trend was not significantly different between each gender, and each age group. CONCLUSIONS Valid database information on disease incidence is essential for healthcare planning and provides a valuable resource for health research. An increase of the incidence rate of type 1 diabetes in children was highlighted in both sexes and in all age groups.
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Affiliation(s)
- Clara Piffaretti
- Santé publique France, The French National Public Health Agency, 12 rue du Val d'Osne, 94410 Saint Maurice, France.
| | - Laurence Mandereau-Bruno
- Santé publique France, The French National Public Health Agency, 12 rue du Val d'Osne, 94410 Saint Maurice, France
| | - Sophie Guilmin-Crepon
- Clinical Epidemiology Unit and Endocrinology and Diabetology Service, University Hospital Robert Debré at Assistance publique - Hôpitaux de Paris, 48 Bd Sérurier, 75019 Paris, France
| | - Carine Choleau
- AJD (Aide aux Jeunes Diabétiques), Help to the Young Diabetics, 38 Rue Eugène Oudiné, 75013 Paris, France
| | - Régis Coutant
- Pediatric Endocinology Service, University Hospital of Angers, 4 Rue Larrey, 49100 Angers, France
| | - Sandrine Fosse-Edorh
- Santé publique France, The French National Public Health Agency, 12 rue du Val d'Osne, 94410 Saint Maurice, France
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15
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Fosse-Edorh S, Rigou A, Morin S, Fezeu L, Mandereau-Bruno L, Fagot-Campagna A. [Algorithms based on medico-administrative data in the field of endocrine, nutritional and metabolic diseases, especially diabetes]. Rev Epidemiol Sante Publique 2017. [PMID: 28625707 DOI: 10.1016/j.respe.2017.05.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Abstract
BACKGROUND Medico-administrative databases represent a very interesting source of information in the field of endocrine, nutritional and metabolic diseases. The objective of this article is to describe the early works of the Redsiam working group in this field. METHODS Algorithms developed in France in the field of diabetes, the treatment of dyslipidemia, precocious puberty, and bariatric surgery based on the National Inter-schema Information System on Health Insurance (SNIIRAM) data were identified and described. RESULTS Three algorithms for identifying people with diabetes are available in France. These algorithms are based either on full insurance coverage for diabetes or on claims of diabetes treatments, or on the combination of these two methods associated with hospitalizations related to diabetes. Each of these algorithms has a different purpose, and the choice should depend on the goal of the study. Algorithms for identifying people treated for dyslipidemia or precocious puberty or who underwent bariatric surgery are also available. CONCLUSION Early work from the Redsiam working group in the field of endocrine, nutritional and metabolic diseases produced an inventory of existing algorithms in France, linked with their goals, together with a presentation of their limitations and advantages, providing useful information for the scientific community. This work will continue with discussions about algorithms on the incidence of diabetes in children, thyroidectomy for thyroid nodules, hypothyroidism, hypoparathyroidism, and amyloidosis.
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Affiliation(s)
- S Fosse-Edorh
- Santé publique France, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France.
| | - A Rigou
- Santé publique France, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France
| | - S Morin
- Haute Autorité de santé, 93210 Saint-Denis, France
| | - L Fezeu
- Inserm (U1153), Inra (U1125), université Paris 13, équipe de recherche en épidémiologie nutritionnelle (EREN), centre de recherche en épidémiologie et statistiques, Cnam, COMUE, Sorbonne Paris Cité, 93000 Bobigny, France
| | - L Mandereau-Bruno
- Santé publique France, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France
| | - A Fagot-Campagna
- Caisse nationale d'assurance maladie des travailleurs salariés, 75020 Paris, France
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16
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Mandereau-Bruno L, Fagot-Campagna A, Rey G, Latouche A, Fosse-Edorh S. CO-03: Évolution de la surmortalité des personnes diabétiques traitées pharmacologiquement entre 2002-2006 et 2007-2012 – Cohortes Entred2001 et Entred2007. Diabetes & Metabolism 2016. [DOI: 10.1016/s1262-3636(16)30021-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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17
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Fosse-Edorh S, Fagot-Campagna A, Detournay B, Bihan H, Eschwege E, Gautier A, Druet C. Impact of socio-economic position on health and quality of care in adults with Type 2 diabetes in France: the Entred 2007 study. Diabet Med 2015; 32:1438-44. [PMID: 25884777 DOI: 10.1111/dme.12783] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/15/2015] [Indexed: 11/26/2022]
Abstract
AIM To describe the association between socio-economic position, health status and quality of diabetes care in people with Type 2 diabetes in France, where people may receive full healthcare coverage for chronic disease. METHODS Data from a national cross-sectional survey performed in people pharmacologically treated for diabetes were used. They combined data from medical claims, hospital discharge, questionnaires for patients (n = 3894 with Type 2 diabetes) and their physicians (n = 2485). Socio-economic position was assessed using educational level (low, intermediate, high) and ability to make ends meet (financial difficulties vs. financially comfortable). RESULTS People with diabetes reporting financial difficulties were more likely to be smokers (adjusted odds ratio 1.4; 95% CI 1.1-1.6) and obese (adjusted odds ratio 1.3; 95% CI 1.2-1.6) and to have poorer glycaemic control (HbA1c > 64 mmol/mol (8%); adjusted odds ratio 1.4; 95% CI 1.1-1.8), than those who were financially comfortable. They were more likely to have their diabetes diagnosed because of complications (adjusted odds ratio 1.6; 95% CI 1.3-2.0). They were also more likely to have coronary and podiatric complications (adjusted odds ratios 1.3; 95% CI 1.1-1.6 and 1.7; 95% CI 1.4-2.2, respectively). They benefited more often from full coverage (adjusted odds ratio 1.3; 95% CI 1.1-1.6), visited general practitioners more often (ratio of estimated marginal means 1.2; 95% CI 1.1-1.2) but specialists less often (adjusted odds ratio 0.7; 95% CI 0.6-0.8 for a visit to private ophthalmologist). They also felt less well informed about their condition. CONCLUSIONS Despite frequent access to full healthcare coverage, socio-economic position has an impact on the diagnosis of diabetes, health status and quality of diabetes care in France.
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Affiliation(s)
- S Fosse-Edorh
- Department of Chronic Diseases and Injuries, French Institute for Public Health Surveillance, Saint-Maurice, France
| | - A Fagot-Campagna
- Strategy and Research Department, National Health Insurance, Île-de-France, Paris, France
| | | | - H Bihan
- Department of Endocrinology, Diabetology and Metabolic Disease, Avicenne Hospital, Paris XIII University and Assistance Publique-Hôpitaux de Paris, Bobigny, France
| | | | - A Gautier
- National Institute for Prevention and Health Education, Saint-Denis, France
| | - C Druet
- Department of Chronic Diseases and Injuries, French Institute for Public Health Surveillance, Saint-Maurice, France
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18
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Regnault N, Mandereau-Bruno L, Denis P, Fagot-Campagna A, Fosse-Edorh S. O31 Évolution de la prévalence du diabète traité pharmacologiquement, France, 2006-2013. Diabetes & Metabolism 2015. [DOI: 10.1016/s1262-3636(15)30031-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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19
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Fosse-Edorh S, Fagot-Campagna A, Detournay B, Bihan H, Gautier A, Dalichampt M, Druet C. Type 2 diabetes prevalence, health status and quality of care among the North African immigrant population living in France. Diabetes Metab 2014; 40:143-50. [PMID: 24447725 DOI: 10.1016/j.diabet.2013.11.005] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2013] [Revised: 11/26/2013] [Accepted: 11/27/2013] [Indexed: 10/25/2022]
Abstract
AIM This report is an overview of type 2 diabetes (DT2) in the North African immigrant population living in France. METHODS Data were collected in two separate cross-sectional national surveys. DT2 prevalence was estimated using a population-based survey involving 13 959 people aged ≥ 45 years (EDS), while health status and quality of care were evaluated using a sample of 3894 DT2 patients (ENTRED). RESULTS Prevalence of DT2 and obesity was 14.0% [CI 95%: 9.9; 18.0] and 20.5% [15.7; 25.3], respectively, in participants born in North Africa (BNA) and 7.5% [7.0; 8.0] and 15.8% [14.7; 16.8], respectively, in those born in France (BIF). DT2 was associated with region of birth in women after adjusting for age, body mass index and income or occupation, but not after adjusting for education level. In men, DT2 was not associated with region of birth. BNA and BIF patients with diabetes frequently benefited from free medical coverage (88% vs. 84%, respectively), although BNA diabetic patients visited a general practitioner less frequently than BIF (8.5 vs. 9.0 visits/year, respectively). The percentage of BNA vs. BIF diabetes patients tested three times a year for HbA1c was lower (39% vs. 44%), while HbA1c was higher in BNA vs. BIF diabetics (> 8%: 30% vs. 15%). Ophthalmological complications were also more frequent in BNA vs. BIF patients with diabetes (25% vs. 18%, respectively). CONCLUSION The greater prevalence of DT2 in BNA women and the poorer glycaemic control observed in the BNA population overall both probably contribute to disparity in diabetes mortality compared with BIF diabetics, a fact that has been observed in previous studies.
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Affiliation(s)
- S Fosse-Edorh
- Department of Chronic Diseases and Injuries, French Institute for Public Health Surveillance, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France.
| | - A Fagot-Campagna
- Department of Chronic Diseases and Injuries, French Institute for Public Health Surveillance, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France; Strategy and Research Department, National Health Insurance, Île-de-France, Paris, France
| | | | - H Bihan
- Department of Endocrinology, Diabetology and Metabolic Disease, Avicenne Hospital, Paris XIII University and Assistance Publique-Hôpitaux de Paris, Bobigny, France
| | - A Gautier
- National Institute for Prevention and Health Education, Saint-Denis, France
| | - M Dalichampt
- Department of Chronic Diseases and Injuries, French Institute for Public Health Surveillance, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France
| | - C Druet
- Department of Chronic Diseases and Injuries, French Institute for Public Health Surveillance, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France
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