New standards for nutrition science, concepts and methods—novel approach to substantiate cause- and -effect relationships in nutritional science by ranking studies and subsequent statistical modelling

In any scientific field, demonstrating cause-and-effect relationships is of the utmost importance, however difficult to achieve. The present study aims to establish an objective approach to substantiate cause-and-effect relationships. Our approach consisted of ranking published studies and subsequently using the best performing studies to construct and validate a statistical model. For the first part, studies on the association between vitamin D status and COVID-19 severity (morbidity/mortality) in hospitalized patients were identified and ranked using a combination of physiological and statistical relevance, including dose-dependency, power evaluation, confounding, physiological mechanisms, and target population. The various ranking criteria were developed in an iterative process, taking into account the Bradford Hill criteria. For the second part, a two-step statistical modelling strategy was implemented. Firstly, a multivariate model was constructed and secondly, this model was validated using data from at least one other independent study with a similar design. The sensitivity (percentage of correctly detected cases by the model) and specificity (percentage of correctly detected non-cases by the model) was assessed in both studies, and the results of both studies (model-making and model-testing) were compared using the chi-square test with expectation. Five ranking criteria were defined with a maximum score of 67 points. Six studies were selected with scores ranging between 27 and 47 points [1–6]. The highest score was obtained by Hernandez et al., 2021 [1]. Unfortunately, it was not possible to obtain complete independent datasets of these studies. Therefore, to evaluate our approach in cause- and -effect relationships, two datasets were selected of studies on the effects of postbiotic intake on the incidence of pulmonary and gastrointestinal infections in children aged 1 to 4 years [7,8]. A logistic confounding model in combination with a discriminant analysis was applied on the first (model-making) study resulting in an internal sensitivity and specificity of 78% and 100%, respectively (p &lt; 0.001), showing a treatment effect on the reduction of infections (p &lt; 0.001). An external validation of the acquired model in a second independent (model-testing) study showed sensitivity and specificity of 76% and 80% (p &lt; 0.001), again showing a treatment effect (p &lt; 0.001). The sensitivity and specificity were not statistically different indicating similarity of the impact by the explanatory variables in both datasets. Overall, the combination of ranking studies and statistical modelling supports the validation of cause-and-effect relationships using objective criteria. Demonstrating consistency in associations by replication and robustness testing contributes to proof of concept in causative relations.<br/

New standards for nutrition science, concepts and methods—novel approach to substantiate cause- and -effect relationships in nutritional science by ranking studies and subsequent statistical modelling

In any scientific field, demonstrating cause-and-effect relationships is of the utmost importance, however difficult to achieve. The present study aims to establish an objective approach to substantiate cause-and-effect relationships. Our approach consisted of ranking published studies and subsequently using the best performing studies to construct and validate a statistical model. For the first part, studies on the association between vitamin D status and COVID-19 severity (morbidity/mortality) in hospitalized patients were identified and ranked using a combination of physiological and statistical relevance, including dose-dependency, power evaluation, confounding, physiological mechanisms, and target population. The various ranking criteria were developed in an iterative process, taking into account the Bradford Hill criteria. For the second part, a two-step statistical modelling strategy was implemented. Firstly, a multivariate model was constructed and secondly, this model was validated using data from at least one other independent study with a similar design. The sensitivity (percentage of correctly detected cases by the model) and specificity (percentage of correctly detected non-cases by the model) was assessed in both studies, and the results of both studies (model-making and model-testing) were compared using the chi-square test with expectation. Five ranking criteria were defined with a maximum score of 67 points. Six studies were selected with scores ranging between 27 and 47 points [1–6]. The highest score was obtained by Hernandez et al., 2021 [1]. Unfortunately, it was not possible to obtain complete independent datasets of these studies. Therefore, to evaluate our approach in cause- and -effect relationships, two datasets were selected of studies on the effects of postbiotic intake on the incidence of pulmonary and gastrointestinal infections in children aged 1 to 4 years [7,8]. A logistic confounding model in combination with a discriminant analysis was applied on the first (model-making) study resulting in an internal sensitivity and specificity of 78% and 100%, respectively (p &lt; 0.001), showing a treatment effect on the reduction of infections (p &lt; 0.001). An external validation of the acquired model in a second independent (model-testing) study showed sensitivity and specificity of 76% and 80% (p &lt; 0.001), again showing a treatment effect (p &lt; 0.001). The sensitivity and specificity were not statistically different indicating similarity of the impact by the explanatory variables in both datasets. Overall, the combination of ranking studies and statistical modelling supports the validation of cause-and-effect relationships using objective criteria. Demonstrating consistency in associations by replication and robustness testing contributes to proof of concept in causative relations.<br/

Longitudinal trajectories and psychological predictors of weight loss and quality of life until 3 years after metabolic and bariatric surgery

ObjectiveThis study aimed to describe longitudinal trajectories of Total Weight Loss (%TWL), and mental and physical health related quality of life (HRQOL), as well as to identify preoperative psychological predictors of these trajectories.MethodsA prospective observational study including Dutch patients treated with metabolic and bariatric surgery (n = 420, age 44.8 ± 10.3 years, 78.6% females) was performed. Trajectories of %TWL and HRQOL from screening to 1-, 2-, and 3-years post-surgery were described using growth mixture modelling. Multivariable and lasso regression models were used to identify predictors.ResultsThree trajectories described %TWL, varying in the degree of first-year weight loss. No pre-surgical psychological factors were associated with %TWL trajectories. We identified four physical and five mental HRQOL trajectories. Approximately 25-30% of patients exhibited patterns of initial improvements followed by decline, or persistently low levels of HRQOL. Higher depressive symptoms were associated with these unfavourable physical HRQOL trajectories (OR 1.20, 95%CI 1.04-1.39), adjusted for confounders. Unfavourable mental HRQOL trajectories were predicted by depressive and anxiety symptoms, neuroticism, insecure attachment, and maladaptive coping. In contrast, self-esteem, extraversion, and conscientiousness were associated with favourable mental HRQOL trajectories.DiscussionPsychological factors did not predict weight loss, but they significantly impacted patient's HRQOL after metabolic and bariatric surgery. A subgroup with unsuccessful HRQOL after surgery was identified, who would benefit from tailored preoperative counselling to optimize surgery outcomes. Metabolic and bariatric surgery may not be universally beneficial for all patients, challenging the conventional approach to surgical interventions for severe obesity and advocating for a more nuanced, individualized assessment of potential candidates.</p

Monitoring recently acquired HIV infections in Amsterdam, The Netherlands:The attribution of test locations

Background:  Surveillance of recent HIV infections (RHI) using an avidity assay has been implemented at Dutch sexual health centres (SHC) since 2014, but data on RHI diagnosed at other test locations is lacking. Setting:  Implementation of the avidity assay in HIV treatment clinics for the purpose of studying RHI among HIV patients tested at different test locations. Methods: We retrospectively tested leftover specimens from newly diagnosed HIV patients in care in 2013–2015 in Amsterdam. Avidity Index (AI) values ≤0.80 indicated recent infection (acquired ≤6 months prior to diagnosis), and AI > 0.80 indicated established infection (acquired >6 months prior to diagnosis). An algorithm for RHI was applied to correct for false recency. Recency based on this algorithm was compared with recency based on epidemiological data only. Multivariable logistic regression analysis was used to identify factors associated with RHI among men who have sex with men (MSM).Results: We tested 447 specimens with avidity; 72% from MSM. Proportions of RHI were 20% among MSM and 10% among heterosexuals. SHC showed highest proportions of RHI (27%), followed by GPs (15%), hospitals (5%), and other/unknown locations (11%) (p < 0.001). Test location was the only factor associated with RHI among MSM. A higher proportion of RHI was found based on epidemiological data compared to avidity testing combined with the RHI algorithm. Conclusion:  SHC identify more RHI infections compared to other test locations, as they serve high-risk populations and offer frequent HIV testing. Using avidity-testing for surveillance purposes may help targeting prevention programs, but the assay lacks robustness and its added value may decline with improved, repeat HIV testing and data collection

Laboratoriumsurveillance van soa: van toegevoegde waarde?

Een van de doelstellingen van het Nationaal Actieplan soa, hiv en seksuele gezondheid 2017-2022 is dat er actuele en betrouwbare cijfers beschikbaar moeten zijn om de preventie en bestrijding van seksueel overdraagbare aandoeningen te versterken. (1) Hiervoor kan ook laboratoriumsurveillance ingezet worden en de huidige informatiesystemen van laboratoria zouden meer kunnen worden benut. Dit artikel beschrijft een onderzoek naar het opzetten van een landelijke laboratoriumsurveillance voor soa en de toegevoegde waarde ervan naast de al bestaande surveillancesystemen

Sex, drugs, and sexually transmitted infections: A latent class analysis among men who have sex with men in Amsterdam and surrounding urban regions, the Netherlands

Background: Men who have sex with men (MSM) are at high risk for sexually transmitted infections (STI) and often have sex while under the influence of drugs (sexualized drug use). We aimed to identify classes of MSM in Amsterdam and in surrounding urban regions with distinctive patterns of sexualized drug use and their association with STI. Methods: In this cross-sectional study, data on MSM were collected at STI clinics in the Netherlands between September-December 2017. Information on drug use, sociodemographics and sexual risk behavior, including lab-confirmed STI (chlamydia, gonorrhea, syphilis and HIV) was collected and compared between Amsterdam and surrounding urban regions. Latent class analysis was used to identify classes with similar drug use patterns, which were then linked to sexual behavior and STI. Results: We included 4461 MSM who were a median 35 years old (IQR = 27–47) and mostly Dutch (56.9 %). Use of all drugs was more often reported in Amsterdam compared to surrounding regions (p<0.001). We identified four different classes based on sexualized drug use among Amsterdam participants and three classes in surrounding regions. In both regions, polydrug use classes (compared to classes of no drug use; alcohol use; or few, various drugs) were defined by higher numbers of sexual partners (median range 8–15 vs 4–6, respectively) and higher STI prevalence (range 30.5%–31.8% vs 18.6%–22.8%, respectively). Conclusion: Given the high prevalence of risk behavior and STIs, MSM in urban settings partaking in sexualized polydrug use might benefit from tailored outreach, screening, and safe sex and drug use interventions