Diabetes and the risk of cardiovascular events and all-cause mortality among older adults: an individual participant data analysis of five prospective studies.

BACKGROUND: Guidelines and studies provide conflicting information on whether type 2 diabetes (T2D) should be considered a coronary heart disease risk (CHD) equivalent in older adults. METHODS: We synthesized participant-level data on 82,723 individuals aged ≥65 years from five prospective studies in two-stage meta-analyses. We estimated multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of T2D (presence versus absence) on a primary composite outcome defined as cardiovascular events or all-cause mortality. Secondary outcomes were the components of the composite. We evaluated CHD risk equivalence by comparing outcomes between individuals with T2D but no CHD versus CHD but no T2D. RESULTS: The median age of participants was 71 years, 20% had T2D and 17% had CHD at baseline. A total of 29,474 participants (36%) experienced the composite outcome. Baseline T2D was associated with higher risk of cardiovascular events or all-cause mortality versus no T2D (HR 1.44, 95% CI [1.40-1.49]). The association was weaker in individuals aged ≥75 years versus 65-74 years (HR 1.32 [1.19-1.46] vs. 1.56 [1.50-1.62]; p-value for interaction = .032). Compared to individuals with CHD but no T2D, individuals with T2D but no CHD had a similar risk of the composite outcome (HR 0.95 [0.85-1.07]), but a lower risk of cardiovascular events (HR 0.76 [0.59-0.98]). CONCLUSIONS: T2D was associated with increased risk of cardiovascular events and all-cause mortality in older adults, but T2D without CHD conferred lower risk of cardiovascular events compared to CHD without T2D. Our results suggest that T2D should not be considered a CHD risk equivalent in older adults.

Educational inequalities in multimorbidity at older ages: a multi-generational population-based study.

BACKGROUND: Social inequalities in multimorbidity may occur due to familial and/or individual factors and may differ between men and women. Using population-based multi-generational data, this study aimed to (1) assess the roles of parental and individual education in the risk of multimorbidity and (2) examine the potential effect modification by sex. METHODS: Data were analysed from 62 060 adults aged 50+ who participated in the Survey of Health, Ageing and Retirement in Europe, comprising 14 European countries. Intergenerational educational trajectories (exposure) were High-High (reference), Low-High, High-Low and Low-Low, corresponding to parental-individual educational attainments. Multimorbidity (outcome) was ascertained between 2013 and 2020 as self-reported occurrence of ≥2 diagnosed chronic conditions. Inequalities were quantified as multimorbidity-free years lost (MFYL) between the ages of 50 and 90 and estimated via differences in the area under the standardized cumulative risk curves. Effect modification by sex was assessed via stratification. RESULTS: Low individual education was associated with higher multimorbidity risk regardless of parental education. Compared to the High-High trajectory, Low-High was associated with -0.2 MFYL (95% confidence intervals: -0.5 to 0.1), High-Low with 3.0 (2.4-3.5), and Low-Low with 2.6 (2.3-2.9) MFYL. This pattern was observed for both sexes, with a greater magnitude for women. This effect modification was not observed when only diseases diagnosed independently of healthcare-seeking behaviours were examined. CONCLUSIONS: Individual education was the main contributor to intergenerational inequalities in multimorbidity risk among older European adults. These findings support the importance of achieving a high education to mitigate multimorbidity risk.

[Digital environment and population health]. / Environnement digital et santé des populations.

Health and risk of disease are determined by exposure to the physical, socio-economic, and political environment and to this has been added exposure to the digital environment. Our increasingly digital lives have major implications for people's health and its monitoring, as well as for prevention and care. Digital health, which encompasses the use of health applications, connected devices and artificial intelligence medical tools, is transforming medical and healthcare practices. Used properly, it could facilitate patient-centered, inter-professional and data-driven care. However, its implementation raises major concerns and ethical issues, particularly in relation to privacy, equity, and the therapeutic relationship.

La santé et le risque de maladies sont déterminés par l'exposition aux environnements physiques, socio-économiques et politiques, et à cela s'est ajouté l'exposition à l'environnement digital. Notre vie digitale a des implications majeures, d'une part, sur la santé des populations et son monitoring et, d'autre part, sur la prévention et les soins. Ainsi, la santé digitale (digital health), qui englobe l'utilisation d'applications de santé, d'appareils connectés, ou d'outils médicaux d'intelligence artificielle, modifie les pratiques médico-soignantes. Bien utilisée, elle pourrait faciliter les soins centrés sur le patient, interprofessionnels et guidés par les données. Cependant, sa mise en œuvre soulève d'importants craintes et enjeux éthiques en lien notamment avec la protection des données, l'équité et la relation thérapeutique.

[Effect of socioeconomic status on life expectancy From the population to patients]. / Effet du statut socioéconomique sur l'espérance de vie. De la population aux patients.

Life expectancy exists along a social gradient, where those with a high socioeconomic status (SES) live longer. The effect of SES can be explained via behavioral, material, and psychosocial pathways, which can be modified through social and public health policies. The behavioral pathway states that harmful health behaviors, like smoking, are more common among those of lower SES. The material pathway states that SES give access to different health-beneficial resources, like safe housing or healthy food. Finally, the psychosocial pathway states that a low SES causes a lack of autonomy leading to chronic stress. Understanding how SES affects life expectancy has clinical implications and is important to reduce socioeconomic health inequalities at the population level.

L'espérance de vie suit un gradient social, les personnes avec statut socioéconomique (SSE) élevé vivant plus longtemps. L'effet du SSE sur l'espérance de vie peut être expliqué par des mécanismes comportementaux, matériels et psychosociaux, modifiables par des politiques sociales et de santé publique. Ainsi, les comportements délétères pour la santé, comme le tabagisme, sont plus fréquents chez les personnes ayant un SSE relativement bas. D'un point de vue matériel, le SSE détermine l'accès à des ressources comme un logement de bonne qualité ou une alimentation saine. Enfin, d'un point de vue psychosocial, il est associé notamment au stress chronique. Comprendre comment le SSE affecte l'espérance de vie a des implications cliniques et offre des pistes pour réduire les inégalités en matière de santé à l'échelle de la population.

[Epidemiological signatures and surveillance bias in cancer]. / Signatures épidémiologiques et biais de surveillance du cancer.

Surveillance bias occurs when variations in cancer incidence are the result of changes in screening or diagnostic practices rather than increases in the true occurrence of cancer. This bias is linked to the issue of overdiagnosis and can be apprehended by looking at epidemiological signatures of cancer. We explain the concept of epidemiological signatures using the examples of melanoma and of lung and prostate cancer. Accounting for surveillance bias is particularly important for assessing the true burden of cancer and for accurately communicating cancer information to the population and decision-makers.

Le biais de surveillance se produit lorsque les variations d'incidence d'un cancer sont le résultat d'un changement dans les pratiques de dépistage ou de diagnostic plutôt que d'une augmentation de la fréquence réelle de ce cancer. Ce biais est lié au concept du surdiagnostic et peut être appréhendé en examinant les signatures épidémiologiques des cancers. Nous expliquons le concept de signature épidémiologique à l'aide des exemples du mélanome et des cancers du poumon et de la prostate. La prise en compte des biais de surveillance est particulièrement importante pour évaluer le fardeau réel du cancer et communiquer avec précision l'information sur le cancer à la population et aux décideurs.

Consequences of gestational diabetes mellitus on neonatal cardiovascular health: MySweetHeart Cohort study.

BACKGROUND: Hyperglycaemic disorders of pregnancy are associated with offspring cardiovascular alterations. METHODS: MySweetHeart cohort study aimed to assess the effect of maternal gestational diabetes (GDM) on offsprings' cardiovascular health. Newborns underwent clinical and echocardiographic examinations between 2016 and 2020. RESULTS: Compared to mothers without GDM (n = 141), mothers with GDM (n = 123) were more likely to have had GDM in previous pregnancies and had higher weight, BMI, blood glucose, and HbA1c. Newborns of both groups showed similar clinical characteristics. Echocardiography was performed on the 3rd (interquartile range, IQR, 2nd-4th) day of life in 101 offsprings of mothers without and 116 offsprings of mothers with GDM. Left ventricular (LV) mass was similar. Children born to mothers with GDM had a thicker posterior LV wall (z-score +0.15, IQR -0.38/0.62, versus +0.47, IQR -0.11/+1.1, p = 0.004), a smaller end-systolic (1.3 mL, IQR 1.0-1.5 mL, versus 1.4 mL, IQR 1.2-1.8 mL, p = 0.044) but a similar end-diastolic LV volume. They also had shorter tricuspid valve flow duration and aortic valve ejection time, lower tricuspid E-wave and pulmonary valve velocities. CONCLUSIONS: Newborns of mothers with or without GDM had similar clinical characteristics and LV mass. However, some echocardiographic differences were detected, suggesting an altered myocardial physiology among infants of mothers with GDM. REGISTRATION: ClinicalTrials.gov (NCT02872974). IMPACT: Hyperglycaemic disorders of pregnancy are known to be associated with offspring cardiovascular alterations. Clinical characteristics and estimated left ventricular (LV) mass were similar in children issued from mothers with and without gestational diabetes (GDM). Children born to mothers with GDM had a thicker posterior LV wall and a smaller end-systolic LV volume. Although LV mass is not different, myocardial physiology may be altered in these infants. Further studies should investigate the endothelial function of this population and the cardiovascular evolution of these children over time.

Seroprevalence trends of anti-SARS-CoV-2 antibodies and associated risk factors: a population-based study.

PURPOSE: We aimed to assess the seroprevalence trends of SARS-CoV-2 antibodies in several Swiss cantons between May 2020 and September 2021 and investigate risk factors for seropositivity and their changes over time. METHODS: We conducted repeated population-based serological studies in different Swiss regions using a common methodology. We defined three study periods: May-October 2020 (period 1, prior to vaccination), November 2020-mid-May 2021 (period 2, first months of the vaccination campaign), and mid-May-September 2021 (period 3, a large share of the population vaccinated). We measured anti-spike IgG. Participants provided information on sociodemographic and socioeconomic characteristics, health status, and adherence to preventive measures. We estimated seroprevalence with a Bayesian logistic regression model and the association between risk factors and seropositivity with Poisson models. RESULTS: We included 13,291 participants aged 20 and older from 11 Swiss cantons. Seroprevalence was 3.7% (95% CI 2.1-4.9) in period 1, 16.2% (95% CI 14.4-17.5) in period 2, and 72.0% (95% CI 70.3-73.8) in period 3, with regional variations. In period 1, younger age (20-64) was the only factor associated with higher seropositivity. In period 3, being aged ≥ 65 years, with a high income, retired, overweight or obese or with other comorbidities, was associated with higher seropositivity. These associations disappeared after adjusting for vaccination status. Seropositivity was lower in participants with lower adherence to preventive measures, due to a lower vaccination uptake. CONCLUSIONS: Seroprevalence sharply increased over time, also thanks to vaccination, with some regional variations. After the vaccination campaign, no differences between subgroups were observed.

Slow data public health.

Surveillance and research data, despite their massive production, often fail to inform evidence-based and rigorous data-driven health decision-making. In the age of infodemic, as revealed by the COVID-19 pandemic, providing useful information for decision-making requires more than getting more data. Data of dubious quality and reliability waste resources and create data-genic public health damages. We call therefore for a slow data public health, which means focusing, first, on the identification of specific information needs and, second, on the dissemination of information in a way that informs decision-making, rather than devoting massive resources to data collection and analysis. A slow data public health prioritizes better data, ideally population-based, over more data and aims to be timely rather than deceptively fast. Applied by independent institutions with expertise in epidemiology and surveillance methods, it allows a thoughtful and timely public health response, based on high-quality data fostering trustworthiness.

Cardiovascular mortality trends in Switzerland 1995-2018.

Mortality rates due to coronary heart disease (CHD) and stroke have declined in the last century in high-income countries, including Switzerland. However, these rates have plateaued in several countries. We assessed CHD and stroke mortality trends (1995-2018) in Switzerland. We estimated annual rate changes via JoinPoint regression. Rates decreased steadily in most sex and age groups; however, in those aged 60-74, stroke rates plateaued after 2012 among men and CHD rates plateaued after 2015 among women. Cardiovascular mortality continues to decrease in most of the Swiss population. Prevention efforts should be maintained, especially in individuals aged 60-74.

[Surveillance bias: when appearances are misleading]. / Biais de surveillance : quand les apparences sont trompeuses.

Public health surveillance is the ongoing collection and analysis of health-related data, followed by the timely dissemination of information useful for decisions. Surveillance bias occurs when differences in the frequency of a condition are due to variations in the modalities of detection rather than to changes in the actual risk of the condition. As a result, the true burden of diseases cannot be properly assessed. This is of growing concern because surveillance activity is more and more often based on data not designed primarily for surveillance, notably data from healthcare providers. Many diseases (such as COVID-19, prostate cancer, or hypertension) are prone to surveillance bias. It also hinders quality of care monitoring.

La surveillance en santé publique consiste à recueillir et à analyser en continu des données relatives à la santé, puis à les transformer en informations utiles pour la décision. On parle de biais de surveillance lorsque les différences de fréquence d'une maladie sont dues à des variations dans les modalités de détection plutôt qu'à des changements du risque réel de cette maladie dans la population. Ce biais est fréquent car l'activité de surveillance repose de plus en plus souvent sur des données qui ne sont pas collectées primairement pour la surveillance, notamment celles provenant des prestataires de soins de santé. De nombreuses maladies (comme le Covid-19, le cancer de la prostate ou l'hypertension) sont sujettes à un biais de surveillance. Ce biais nuit également à la surveillance de la qualité des soins.

[From evidence to quality improvement to provide high value and patient centered care]. / De la pratique fondée sur les preuves à l'amélioration de la qualité pour des soins de haute valeur centrés sur le patient.

Evidence-based practice and quality improvement should be at the heart of healthcare and public health. However, their implementation remains insufficient which is reflected in Switzerland in the high frequency of low-value care, in the wide regional variation in care practices, and in the absence of quality monitoring for the majority of healthcare processes. It is necessary to strengthen the monitoring of quality, particularly that perceived by patients, to help strengthening high-value and patient centered care. Because data do not speak for themselves, it is critical to organize how to use indicators for decision.

La pratique fondée sur les preuves et l'amélioration de la qualité devraient être au cœur des soins et de la santé publique. Leur implémentation reste néanmoins insuffisante et se traduit en Suisse par une fréquence élevée de soins de faible valeur, par d'importantes variations régionales dans la pratique de certains soins et par l'absence de monitoring de la qualité pour la majorité des processus de soins. Il faut renforcer le monitoring de la qualité, notamment celle perçue par les patients, pour faciliter la mise en œuvre de soins de haute valeur et centrés sur le patient. Les données ne parlant pas toutes seules, il faut organiser le processus qui va de la production des indicateurs à la décision.

[Polypharmacy and inappropriate medications in multimorbid elderly patients - What OPERAM taught us and will teach us]. / Polypharmacie et medicaments inappropriés chez les patients âgés multimorbides - Ce que l'étude OPERAM nous apprend et va nous apprendre.

Polypharmacy and inappropriate medication use are very common in multimorbid older patients. This population has unfortunately been excluded from most large, randomized studies. In a recent multicenter randomized study (OPERAM), we included over 2000 multimorbid patients. We found that 86% of the patients aged 70 years and more had inappropriate medications and that these medications could be discontinued without negative impact on the health of these patients. This cohort of multimorbid patients will be followed for 10 years to evaluate their prognosis, life expectancy, treatments and quality of life, with numerous projects to better understand the inappropriate prescribing of individual drugs and their consequences on the health of this population.

La polypharmacie et les médicaments inappropriés sont très fréquents chez les patients âgés multimorbides. Cette population a malheureusement été exclue de la plupart des grandes études randomisées. Dans une récente étude randomisée multicentrique (OPERAM), nous avons inclus plus de 2000 patients multimorbides. Celle-ci a montré que 86 % des patients âgés de 70 ans et plus avaient des médicaments inappropriés et qu'il était possible de stopper leur administration, sans répercussion négative sur leur santé. Ces patients multimorbides constituent une cohorte qui va être suivie sur 10 ans pour évaluer leurs pronostic, espérance de vie, traitements et qualité de vie. Cela permettra la réalisation de nombreux projets, notamment pour mieux comprendre les conséquences de la prescription inappropriée de médicaments.

[Strengthening the culture of public health surveillance and population health monitoring]. / Renforcer la culture de la surveillance sanitaire et du monitoring de la santé des populations.

Public health surveillance is the systematic and ongoing collection, analysis and interpretation of data to produce information useful for decision-making. With the development of data science, surveillance methods are evolving through access to big data. More data does not automatically mean more information. For example, the massive amounts of data on Covid-19 was not easily transformed in useful information for decision-making. Further, data scientists have often difficulties to make their analyses useful for decision-making. For the implementation of evidence-based and data-driven public health practice, the culture of public health surveillance and population health monitoring needs to be strengthened.

La surveillance sanitaire est la collecte, l'analyse et l'interprétation ­ systématiques et continues ­ de données pour produire des informations utiles à la décision en santé publique. Avec le développement de la science des données, les méthodes de la surveillance évoluent par l'accès à des données massives (big data). Plus de données ne signifie pas automatiquement plus d'informations. Ainsi, les données massives sur le Covid-19 n'ont pas permis de produire facilement de l'information utile pour la décision. De plus, les spécialistes des données peinent souvent à rendre leurs analyses utiles pour la décision en santé publique. Pour la mise en œuvre d'une santé publique pratique fondée sur les preuves et guidée par les données, il faut renforcer la culture de la surveillance sanitaire et du monitoring de la santé des populations.

[How to fight infodemic and health obscurantism]. / Contrer l'infodémie et la désinformation sanitaire.

Physicians, pharmacists and caregivers, as well as public health officials and citizens, must sort through the enormous amount of information circulating about the pandemic. This crisis is accompanied by a real « infodemic ¼ via multiple media, digital and otherwise. Is circulating a mixture of reliable information but also of misinformation, fed by the obscurantism jeopardizing the implementation of interventions such as vaccination or mask-wearing. To address this infodemic, evidence-based and data-driven public health should be strengthened. Debuting rumors - « see something, say something ¼ - and promoting credible information limit misinformation. Strengthening people's knowledge in population health science would also help.

Médecins, pharmaciens et soignants, ainsi que responsables de la santé publique et citoyens, doivent faire le tri dans l'énorme quantité d'informations qui circulent sur la pandémie. Cette crise s'accompagne d'une véritable « infodémie ¼ via en particulier de multiples supports digitaux. Circulent un mélange d'informations fiables mais aussi de désinformations, nourries par un obscurantisme qui met en danger la mise en œuvre de mesures telles que la vaccination ou le port du masque. Pour faire face à cette infodémie, il faut renforcer la santé publique fondée sur les preuves et guidée par les données. Contrer les rumeurs ­ « see something, say something ¼ ­ et promouvoir l'information crédible limitent la désinformation. Renforcer les connaissances générales en science de la santé des populations est aussi nécessaire pour contrer la désinformation.

[How the life course perspective transforms epidemiology]. / Comment la perspective des parcours de vie transforme l'épidémiologie.

The life course epidemiology is an interdisciplinary approach to health resulting from the convergence of centres of interest in social epidemiology, natural sciences (biology, genetics) and social sciences (psychology, sociology, history). It examines the origin of chronic diseases in the past of individuals, considering the duration and timing of exposure to different risk factors, throughout the life of the individual, from gestation to an advanced age. The life course epidemiology is interested as much in bio-psycho-social determinants as in environmental and societal influences on the trajectories of health and various diseases, either somatic or psychic.

La perspective dite des parcours de vie en épidémiologie (life course epidemiology) est une approche interdisciplinaire de la santé fruit de la convergence de l'épidémiologie sociale, des sciences naturelles (biologie, génétique) et des sciences sociales (psychologie, sociologie, histoire). Elle invite à considérer l'origine des maladies chroniques dans le passé des individus, en tenant compte de la durée et du timing de l'exposition à différents facteurs de risque, ceci tout au long de la vie de l'individu, de la gestation à un âge avancé. Dans cette perspective des parcours de vie, l'épidémiologie s'intéresse autant aux déterminants bio-psychosociaux qu'aux influences environnementales et sociétales sur les trajectoires de santé et de différentes maladies tant somatiques que psychiques.

[Leveraging data from electronic medical record to improve quality of outpatient care]. / Exploiter les données du dossier médical informatisé pour améliorer la qualité des soins en ambulatoire.

Healthcare providers need indicators to monitor the quality of ambulatory care by making the best use of routinely collected data ; the goal is to provide high-value, patient-centered, evidence-based, and data-informed health care. While it may seem simple to produce indicators via the electronic medical record (EMR), these data do not speak by themselves. Indeed, it is necessary to : a) make the data usable ; b) define relevant indicators ; and c) ensure the dissemination of these indicators to patients and healthcare providers. In this article, we explain how the EMR can be used to produce indicators of quality of ambulatory care, using the example of hypertension and diabetes.

Les professionnels de santé souhaitent des indicateurs pour monitorer la qualité des soins ambulatoires en exploitant au mieux les données récoltées de routine ; la finalité est de fournir des soins de haute valeur, centrés sur le patient, fondés sur l'évidence et orientés par les données. Alors que cela semble simple de produire des indicateurs via le dossier médical informatisé (DMI), ces données ne parlent pas toutes seules. En effet, il faut : a) rendre les données exploitables ; b) définir des indicateurs pertinents et c) assurer la diffusion de ces indicateurs auprès des patients et professionnels de santé. Dans cet article, nous explicitons comment le DMI peut être utilisé pour produire des indicateurs de qualité des soins ambulatoires en prenant l'exemple de l'hypertension et du diabète.

Risk factors during first 1,000 days of life for carotid intima-media thickness in infants, children, and adolescents: A systematic review with meta-analyses.

BACKGROUND: The first 1,000 days of life, i.e., from conception to age 2 years, could be a critical period for cardiovascular health. Increased carotid intima-media thickness (CIMT) is a surrogate marker of atherosclerosis. We performed a systematic review with meta-analyses to assess (1) the relationship between exposures or interventions in the first 1,000 days of life and CIMT in infants, children, and adolescents; and (2) the CIMT measurement methods. METHODS AND FINDINGS: Systematic searches of Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) were performed from inception to March 2019. Observational and interventional studies evaluating factors at the individual, familial, or environmental levels, for instance, size at birth, gestational age, breastfeeding, mode of conception, gestational diabetes, or smoking, were included. Quality was evaluated based on study methodological validity (adjusted Newcastle-Ottawa Scale if observational; Cochrane collaboration risk of bias tool if interventional) and CIMT measurement reliability. Estimates from bivariate or partial associations that were least adjusted for sex were used for pooling data across studies, when appropriate, using random-effects meta-analyses. The research protocol was published and registered on the International Prospective Register of Systematic Reviews (PROSPERO; CRD42017075169). Of 6,221 reports screened, 50 full-text articles from 36 studies (34 observational, 2 interventional) totaling 7,977 participants (0 to 18 years at CIMT assessment) were retained. Children born small for gestational age had increased CIMT (16 studies, 2,570 participants, pooled standardized mean difference (SMD): 0.40 (95% confidence interval (CI): 0.15 to 0.64, p: 0.001), I2: 83%). When restricted to studies of higher quality of CIMT measurement, this relationship was stronger (3 studies, 461 participants, pooled SMD: 0.64 (95% CI: 0.09 to 1.19, p: 0.024), I2: 86%). Only 1 study evaluating small size for gestational age was rated as high quality for all methodological domains. Children conceived through assisted reproductive technologies (ART) (3 studies, 323 participants, pooled SMD: 0.78 (95% CI: -0.20 to 1.75, p: 0.120), I2: 94%) or exposed to maternal smoking during pregnancy (3 studies, 909 participants, pooled SMD: 0.12 (95% CI: -0.06 to 0.30, p: 0.205), I2: 0%) had increased CIMT, but the imprecision around the estimates was high. None of the studies evaluating these 2 factors was rated as high quality for all methodological domains. Two studies evaluating the effect of nutritional interventions starting at birth did not show an effect on CIMT. Only 12 (33%) studies were at higher quality across all domains of CIMT reliability. The degree of confidence in results is limited by the low number of high-quality studies, the relatively small sample sizes, and the high between-study heterogeneity. CONCLUSIONS: In our meta-analyses, we found several risk factors in the first 1,000 days of life that may be associated with increased CIMT during childhood. Small size for gestational age had the most consistent relationship with increased CIMT. The associations with conception through ART or with smoking during pregnancy were not statistically significant, with a high imprecision around the estimates. Due to the large uncertainty in effect sizes and the limited quality of CIMT measurements, further high-quality studies are needed to justify intervention for primordial prevention of cardiovascular disease (CVD).

Population biomonitoring of micronutrient intakes in children using urinary spot samples.

PURPOSE: Urinary spot samples are a promising method for the biomonitoring of micronutrient intake in children. Our aim was to assess whether urinary spot samples could be used to estimate the 24-h urinary excretion of potassium, phosphate, and iodine at the population level. METHODS: A cross-sectional study of 101 children between 6 and 16 years of age was conducted. Each child collected a 24-h urine collection and three urinary spot samples (evening, overnight, and morning). Several equations were used to estimate 24-h excretion based on the urinary concentrations of each micronutrient in the three spot samples. Various equations and spot combinations were compared using several statistics and plots. RESULTS: Ninety-four children were included in the analysis (mean age: 10.5 years). The mean measured 24-h urinary excretions of potassium, phosphate, and iodine were 1.76 g, 0.61 g, and 95 µg, respectively. For potassium, the best 24-h estimates were obtained with the Mage equation and morning spot (mean bias: 0.2 g, correlation: 0.27, precision: 56%, and misclassification: 10%). For phosphate, the best 24-h estimates were obtained with the Mage equation and overnight spot (mean bias: - 0.03 g, correlation: 0.54, precision: 72%, and misclassification: 10%). For iodine, the best 24-h estimates were obtained with the Remer equation and overnight spot (mean bias: - 8 µg, correlation: 0.58, precision: 86%, misclassification: 16%). CONCLUSIONS: Urinary spot samples could be a good alternative to 24-h urine collection for the population biomonitoring of iodine and phosphate intakes in children. For potassium, spot samples were less reliable.

Monitoring caffeine intake in children with a questionnaire and urine collection: a cross-sectional study in a convenience sample in Switzerland.

PURPOSE: The objectives of this study were (1) to estimate caffeine intake and identify the main sources of intake using a dietary questionnaire, (2) to assess 24-h urinary excretion of caffeine and its metabolites, and (3) to assess how self-reported intake estimates correlates with urinary excretion among children in Switzerland. METHODS: We conducted a cross-sectional study of children between 6 and 16 years of age in one region of Switzerland. The participants filled in a dietary questionnaire and collected a 24-h urine sample. Caffeine intake was estimated with the questionnaire. Caffeine, paraxanthine, theophylline, and theobromine excretions were measured in the urine sample. Correlations between questionnaire-based intake and urinary excretion estimates were assessed using Spearman correlation coefficients. RESULTS: Ninety-one children were included in the analysis (mean age 10.6 years; 43% female). The mean daily caffeine intake estimate derived from the diet questionnaire was 39 mg (range 0-237), corresponding, when related to body weight, to 1.2 mg/kg (range 0.0-6.3). Seven children (8%) had a caffeine intake above the upper recommended level of 3 mg/kg per day. The main sources of caffeine intake were cocoa milk (29%), chocolate (25%), soft drinks (11%), mocha yogurt (10%), tea (8%), and energy drinks (8%). The 24-h urinary excretion of caffeine was 0.3 mg (range 0.0-1.5), paraxanthine 1.4 mg (range 0.0-7.1), theophylline 0.1 mg (range 0.0-0.6), and theobromine 14.8 mg (range 0.3-59.9). The correlations between estimates of caffeine intake and the 24-h urinary excretion of caffeine was modest (ρ = 0.21, p = 0.046) and with the metabolites of caffeine were weak (ρ = 0.09-0.11, p = 0.288-0.423). CONCLUSIONS: Caffeine intake in a sample of children in a region of Switzerland was relatively low. The major sources of intake were cocoa milk, chocolate and soft drinks. Self-reported caffeine intake correlated weakly with urinary excretion of caffeine and some of its main metabolites. TRIAL REGISTRATION NUMBER: NCT02900261.