Interaction between plasma phospholipid odd-chain fatty acids and GAD65 autoantibodies on the incidence of adult-onset diabetes: the EPIC-InterAct case-cohort study.

AIMS/HYPOTHESIS: Islet autoimmunity may progress to adult-onset diabetes. We investigated whether circulating odd-chain fatty acids (OCFA) 15:0 and 17:0, which are inversely associated with type 2 diabetes, interact with autoantibodies against GAD65 (GAD65Ab) on the incidence of adult-onset diabetes. METHODS: We used the European EPIC-InterAct case-cohort study including 11,124 incident adult-onset diabetes cases and a subcohort of 14,866 randomly selected individuals. Adjusted Prentice-weighted Cox regression estimated HRs and 95% CIs of diabetes in relation to 1 SD lower plasma phospholipid 15:0 and/or 17:0 concentrations or their main contributor, dairy intake, among GAD65Ab-negative and -positive individuals. Interactions between tertiles of OCFA and GAD65Ab status were estimated by proportion attributable to interaction (AP). RESULTS: Low concentrations of OCFA, particularly 17:0, were associated with a higher incidence of adult-onset diabetes in both GAD65Ab-negative (HR 1.55 [95% CI 1.48, 1.64]) and GAD65Ab-positive (HR 1.69 [95% CI 1.34, 2.13]) individuals. The combination of low 17:0 and high GAD65Ab positivity vs high 17:0 and GAD65Ab negativity conferred an HR of 7.51 (95% CI 4.83, 11.69), with evidence of additive interaction (AP 0.25 [95% CI 0.05, 0.45]). Low dairy intake was not associated with diabetes incidence in either GAD65Ab-negative (HR 0.98 [95% CI 0.94, 1.02]) or GAD65Ab-positive individuals (HR 0.97 [95% CI 0.79, 1.18]). CONCLUSIONS/INTERPRETATION: Low plasma phospholipid 17:0 concentrations may promote the progression from GAD65Ab positivity to adult-onset diabetes.

Breakfast Size and Prevalence of Metabolic Syndrome in the European Prospective Investigation into Cancer and Nutrition (EPIC) Spanish Cohort.

BACKGROUND: Recent evidence suggest that energy distribution during the daytimecould be a potential determinant for the development of metabolic syndrome (MetS). OBJECTIVE: To cross-sectionally assess the association between breakfast size and the prevalence of MetS in Spanish adults. METHODS: Our study included a subset of 3644 participants from the European Prospective Investigation into Cancer and Nutrition Spain study recontacted between 2017-2018. Information on diet, sociodemographic, lifestyle, sleep quality, and chronotype was collected using standardized questionnaires, while anthropometric and blood pressure data were measured in a face-to-face personal interview by a nurse. MetS was defined according to the Adult Treatment Panel III (ATPIII) definition by measuring serum levels of total cholesterol, tryglycerides and glucose. Breakfast size was calculated as: (energy from breakfast/total energy intake) * 2000 kcal. To evaluate the association between breakfast size and MetS prevalence, a multivariable logistic regression model adjusted by potential confounders was used to estimate OR and 95% CI. RESULTS: Prevalence of MetS in our study was 40.7%. The mean breakfast size was 306.6 * 2000 kcal (15% of the total daily energy intake), with 14 (0.4%) participants skipping breakfast. Participants in the highest quartile of breakfast size had a lower MetS prevalence compared to participants in the lowest quartile (ORQ4vsQ1 = 0.62; 95% CI = 0.51-0.76; p-trend < 0.001). No modification of the estimated ORs by sex, breakfast time, and number of eating occasions per day were observed. CONCLUSION: Our results suggest that higher breakfast size is associated with lower prevalence of MetS in Spanish adults, supporting the importance of a high energy breakfast. Further prospective studies are necessary to confirm these findings.

[Contribution of Electronic Health Record in Surveillance of Notifiable Diseases]. / Aportación de la historia clínica digital a la vigilancia de enfermedades de declaración obligatoria.

BACKGROUND: In 2009 a system was introduced for the automatic import (AI) of cases with suspected notifiable diseases (ND) from electronic medical record (EMR) to RedAlerta, an application for surveillance in Andalusia. At present, the contribution of this system to classical active statement has not been determined enough. The main objective of this study is to evaluate the usefulness of IA in the province of Granada, between 2009 and 2014. METHODS: During the study period (2009-2014), an epidemiologist assessed whether AI met declaration criteria or not. We calculate the contribution of AI to RedAlerta and the percentage of validation of AI, estimating 95% CI. RESULTS: The contribution of AI was 17.3% (95% CI 16.1 to 18.5); and type of statement, 5.2% (95% CI 4.1 to 6.5) for urgent and 24.4% (95% CI 22.7 to 26.2) for ordinary. The contribution was higher (more than 45%) in Lyme disease, congenital hypothyroidism, genital herpes, hepatitis C and other viral hepatitis. 30% (95% CI 28.1 to 32) of AI were validated; 39.9% (95% CI 33 to 47.2) urgent and 29.1% (95% CI 27.2 to 31.2%) ordinary. The percentage of validation was higher than 45% (between 47.5 and 100%) in vaccine-preventable diseases, sexually transmitted infections and low incidence. CONCLUSIONS: Although not replace manual reporting and requires verification, the AI system is useful and increases the completeness of the epidemiological surveillance system.

Aportación de la historia clínica digital a la vigilancia de enfermedades de declaración obligatoria / Contribution of electronic health record in surveillance of notifiable diseases

Fundamentos: En 2009 se implantó el sistema para la importación automática (IA) de casos con sospecha de enfermedad de declaración obligatoria (EDO) desde la historia clínica digital (HCD) a la RedAlerta, aplicación informática para la vigilancia epidemiológica en Andalucía. Hasta ahora, la contribución de este sistema a la clásica declaración activa no se ha determinado suficientemente. El principal objetivo de este estudio es evaluar la utilidad de IA en la provincia de Granada, entre 2009 y 2014. Métodos: Durante el periodo de estudio (2009-2014), un epidemiólogo validó si las EDO importadas satisfacían el criterio de declaración o no. Se halló la contribución de la IA a la RedAlerta y el porcentaje de validación de IA, estimando su IC 95%.Resultados: La contribución de la IA fue del 17,3% (IC95%: 16,1-18,5). Por tipo de declaración el 5,2% (IC95%:4,1-6,5) fueron las urgentes y 24,4% (IC95%: 22,7-26,2) fueron ordinarias. La contribución fue superior al 45% en la enfermedad de Lyme, hipotiroidismo congénito, herpes genital, hepatitis C y otras hepatitis víricas. El 30% (IC95%:28,1-32) de las IA fueron validadas de las cuales el 39,9% (IC95%:33–47,2) fueron urgentes y el 29,1% (IC95%:27,2–31,2%) ordinarias. El porcentaje de validación fue superior al 45% (entre el 47,5 y el 100%) en enfermedades vacunables, en las de transmisión sexual y en las de baja incidencia. Conclusiones: Si bien no sustituye la declaración manual y requiere de un proceso de verificación, el sistema de incorporación automática es útil e incrementa la exhaustividad del sistema de vigilancia epidemiológica (AU)

Background: In 2009 a system was introduced for the automatic import (AI) of cases with suspected notifiable diseases (ND) from electronic medical record (EMR) to RedAlerta, an application for surveillance in Andalusia. At present, the contribution of this system to classical active statement has not been determined enough. The main objective of this study is to evaluate the usefulness of IA in the province of Granada, between 2009 and 2014. Methods: During the study period (2009-2014), an epidemiologist assessed whether AI met declaration criteria or not. We calculate the contribution of AI to RedAlerta and the percentage of validation of AI, estimating 95% CI. Results: The contribution of AI was 17.3% (95% CI 16.1 to 18.5); and type of statement, 5.2% (95% CI 4.1 to 6.5) for urgent and 24.4% (95% CI 22.7 to 26.2) for ordinary. The contribution was higher (more than 45%) in Lyme disease, congenital hypothyroidism, genital herpes, hepatitis C and other viral hepatitis. 30% (95% CI 28.1 to 32) of AI were validated; 39.9% (95% CI 33 to 47.2) urgent and 29.1% (95% CI 27.2 to 31.2%) ordinary. The percentage of validation was higher than 45 % (between 47.5 and 100%) in vaccine-preventable diseases, sexually transmitted infections and low incidence. Conclusions: Although not replace manual reporting and requires verification, the AI system is useful and increases the completeness of the epidemiological surveillance system (AU)

Historia de salud digital (Diraya): un recurso en la vigilancia epidemiológica / The electronic health record (Diraya): a resource in epidemiological surveillance

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