1. A higher cumulative power of antioxidants in the whole diet was linked with lower rates of depression in the sample of adolescent girls.
Evidence Rating Level: 2 (Good)
Depression is believed to become one of the top three most common disorders responsible for global disease burden by 2030. Adolescent girls have a prevalence of depression twofold of other age and sex groups. Oxidative stress may be a risk factor for depression and other psychological disorders. Antioxidants in the diet such as polyphenols, vitamins A, C and E help support the body’s antioxidant system and protect against oxidative damage and as such are hypothesized to have a positive effect in preventing such disorders. The dietary total antioxidant capacity (DTAC) is an indicator that determines the power of antioxidants in food against reactive compounds and has previously been found to be a protective factor for depression in postmenopausal women and healthy adults. This cross-sectional study consisted of 741 adolescent girls sampled from various areas in Iran. Students were aged 12-18 and had no chronic disease. Dietary intakes were evaluated using the food frequency questionnaire (FFQ), and DTAC was calculated using the Nutrient Data Laboratory of USDA database. The Persian version of Beck’s Depression Inventory (BDI) was used to determine depression status. The BDI is a questionnaire with 21 items that has a score from 0-63, in which a score of <13 indicates that the person is considered as not depressed, and a score of >13 means the person is considered depressed. This study concluded that the individuals in the highest quartiles of DTAC had lower depression scores compared to those in the lowest quartiles (9.05 ± 8.1 vs. 12.1 ± 9.4; P = 0.01). An inverse correlation was seen between DTAC and depression score in the unadjusted model (β standardized = -0.107; P value = 0.003) as well as in models that adjusted for confounding factors such as age and energy intake (β standardized = -0.114; P value = 0.002) age, energy intake, physical activity and menstruation (β standardized = -0.108; P value = 0.005), and all the previous factors plus BMI percentile (β standardized = -0.108; P value = 0.005). Limitations of this study include its cross-sectional design, resulting in an inability to assume a causal relationship, and the FFQ used in the study is also prone to measurement error. Additionally, specific symptoms of depression were not studied, limiting the interpretation of study results beyond incidence of depression and BDI score. This may benefit from further investigation, as specific features like appetite and fatigue may have associations with DTAC quartiles. Overall, this study found that a higher DTAC is associated with lower rates of depression in adolescent girls, suggesting a potential role of dietary changes as a means of depression prevention.
1. Total artificial sweetener intake associated with increased risk of cardiovascular disease.
2. Aspartame consumption was associated with increased cerebrovascular disease incidence whereas acesulfame potassium and sucralose were associated with increased coronary heart disease incidence.
Evidence Rating Level: 2 (Good)
Artificial sweeteners exist as an alternative to added sugar, contained in many foods worldwide including beverages, snacks, and low-calorie meals. More than 23000 products worldwide contain artificial sweeteners. Although there are studies that suggest artificial sweeteners as a preferable alternative to conventional sweeteners for cardiovascular outcomes, there is prior literature that have linked artificial sweetener consumption with adverse cardiovascular events. This study sought to further investigate the association between artificial sweeteners and the risk of cardiovascular disease (CVD) via a cohort study including 103 388 French adults aged 18 and over. Each participant initially completed online questionnaires’ about diet, health, anthropometric data, lifestyle, sociodemographic data, and physical activity. A dietary assessment including three non-consecutive days of 24-hour dietary records were assigned randomly over a 2-week period for baseline, and then every 7 months. Food additives including artificial sweeteners were assessed through the dietary record tool. To determine cardiovascular health, biannual health questionnaires and a personal health interface allowed participants to report health events, which would prompt further assessment by a physician. Participants with two valid dietary records during the first two years were included, patients with prevalent CVD and pre-existing diabetes were excluded, along with patients diagnosed with CVD during the first two years of follow-up to limit reverse causality. Over the median follow-up time of 9 years, 1502 CVD events occurred. Total artificial sweetener intake was associated with an increased risk of CVD (hazard ratio 1.09, 95% confidence interval 1.01 to 1.18, P=0.03), and was more particularly associated with cerebrovascular disease (1.18, 1.06 to 1.31, P=0.002; incidence rates 195 and 150). Subgroup analyses revealed that amongst the subtypes of artificial sweeteners, aspartame was associated with an increased risk of cerebrovascular events (1.17, 1.03 to 1.33, P=0.02; incidence rates 186 and 151), and acesulfame potassium and sucralose were associated with increased coronary heart disease risk (acesulfame potassium: 1.40, 1.06 to 1.84, P=0.02; incidence rates 167 and 164; sucralose: 1.31, 1.00 to 1.71, P=0.05; incidence rates 271 and 161). Limitations include the fact that the 24-hour dietary record days were decided in advance and could have influenced behaviour. Additionally, participants in the study were mostly female, with higher educational status and were more likely to have a health-conscious lifestyle. Study findings reveal that though artificial sweeteners may have been found to have favourable cardiovascular outcomes compared to conventional sweeteners in prior literature, their consumption may still be linked with adverse health outcomes.
Evidence Rating Level: 3 (Average)
1. Machine learning combined with hormone levels including endocannabinoid anandamide (AEA), progesterone (P4) and b-human chorionic gonadotrophin (b-hCG) may help predict threatened miscarriage risk.
2. AEA was positively correlated with threatened miscarriage and P4 was negatively correlated with threatened miscarriage.
Despite advancements in obstetrical care, 11% of women will experience threatened miscarriage, with 50% of these pregnancies resulting in an inevitable miscarriage. Currently, our ability to risk stratify these individuals is lacking, with many patients only presenting asymptomatically until they experience first trimester vaginal bleeding. This case-control study aimed to address this gap in care, by combining the levels of hormones including endocannabinoid anandamide (AEA), progesterone (P4) and b-human chorionic gonadotrophin (b-hCG) with machine learning tools to predict the risk of threatened miscarriage. Researchers recruited 119 normal pregnancy women in their first trimester and 96 women with threatened miscarriages, with 58 cases with ongoing pregnancy and 38 with inevitable miscarriage. Inclusion criteria were: single intrauterine pregnancy <13 weeks gestational age, pregnancy-related vaginal bleeding in the threatened miscarriage group, and no pregnancy related vaginal bleeding in the normal pregnancy group, and age >20 years. b-hCG levels, P4 levels and AEA levels were detected. Six different machine learning tools were used to predict threatened miscarriage. These tools were: logistic regression (LR) model, random forest (RF) model, extreme gradient boosting (XGboost) model, k-nearest neighbors classifier (KNN) model, multilayer perceptron (MLP) neural network model and support vector machine (SVM) model. In the two groups, there were no significant differences in age, BMI, AEA and b-hCG. However, P4 levels were lower in the ongoing pregnancy group, AEA was found to be strongly positively correlated with threatened miscarriage (r = 0.38, p < 0.0001), while P4 was found to be negatively correlated with threatened miscarriage (r = − 0.23, p < 0.001). The LR model was found to have the highest accuracy and precision. Limitations to this study included small sample size, unbalanced sample size, and the ability to detect hormone levels only in the first trimester, not in the second or third. Despite this however, this study may highlight an important role of artificial intelligence in the use of predicting and preventing threatened miscarriages in the first trimester.
Evidence Rating Level: 2 (Good)
1. Greater psychological stress, as measured by the Patient Health Questionnaire (PHQ-4), prior to infection of COVID-19 may be a risk factor for long COVID / post-COVID-19 conditions.
Long COVID is defined as signs and symptoms consistent with COVID-19 that last beyond 4 weeks from onset of infection. These can include fatigue, brain fog, dyspnea, digestive issues, loss of taste and smell, and depression. Currently, the pathophysiology of long COVID is poorly understood, and there is a scarcity of literature to allow for the identification of at-risk individuals. As there is prior literature associating psychological distress with greater severity of acute respiratory tract infections, it has been hypothesized that psychological distress may be associated with adverse post-COVID outcomes. This prospective cohort study sought to address this gap in literature and aimed to examine if preinfection psychological distress was associated with an increased risk of developing long COVID. These distresses include depression, anxiety, loneliness, perceived stress and worry. Three large longitudinal studies were used to recruit participants: Nurses’ Health Study II (NHSII), Nurses’ Health Study 3 (NHS3), and the Growing Up Today Study (GUTS). Participants completed an online COVID-19 questionnaire, and received monthly surveys afterward, with participants actively working in health care settings completing weekly questionnaires. 54 960 of the 105 662 original participants were included in the analysis as they did not report a positive COVID-19 test at baseline. During the 19 months of follow-up, 3193 participants tested positive and completed a post-COVID-19 questionnaire. Distress was measured at baseline using a 4-item Patient Health Questionnaire (PHQ-4), which consists of a 2-item depression measure (PHQ-2) and a 2-item anxiety measure (2-item Generalized Anxiety Disorder scale [GAD-2]). Responses ranged from 0 (not at all) to 3 (nearly every day). Scores of 3 or higher on the PHQ-2 or GAD-2 indicated probable depression or probable anxiety. Worry about COVID-19 was assessed with the item, “How worried are you about COVID-19?” Response options were not at all, not very worried, somewhat worried, and very worried. Participants who were not active health care workers had two additional types of distress assessed using a 4-item Perceived Stress Scale. 3-item UCLA Loneliness Scale was used to determine the feeling of lack of companionship, being left out, and isolated from others, ranging from 1-3. Long term COVID-symptoms were asked, and if yes, participants were asked to give further details on these symptoms. All types of distress were significantly associated with increased risk of post–COVID-19 conditions in a dose-dependent manner after adjustment for demographic factors (probable depression, RR, 1.39 [95% CI, 1.19-1.63]; probable anxiety, RR, 1.47 [95% CI, 1.27-1.70]; very worried about COVID-19, RR, 1.43 [95% CI, 1.22-1.68]; highest quartile of perceived stress, RR, 1.50 [95% CI, 1.21-1.86]; lonely some of the time or often, RR, 1.35 [95% CI, 1.11-1.65]; all P < .01 for trend). More types of distress were associated with higher risk of developing post-COVID-19 conditions (≥2 types vs none, RR, 1.54; 95% CI, 1.28-1.86). Additionally, all symptoms with the exception of persistent cough or smell/taste problems were more prevalent in participants with distress. The study had several limitations. Due to the recruitment process, participants were mostly white, female and health care workers, and data collection also relied purely on self-reporting. Though the study findings still provide valuable insight into risk factors contributing to long COVID, this may limit the external validity of findings. Overall, this study suggests pre-existing psychological distress is associated with a greater risk of developing post-COVID-19 conditions.
Evidence Rating Level: 2 (Good)
1. The COVID-19 Pandemic was associated with higher gestational weight gain and a higher risk of excessive gestational weight gain for pregnant women in a cross-sectional study.
Weight gain in adults, children and adolescents has been associated with the COVID-19 pandemic. Currently however, there is limited data to identify whether this has been the case for gestational weight gain for pregnant women as well. This cross-sectional study sought to address this gap in literature, and aimed to determine if gestational weight gain (GWG) changes were associated with the pandemic. The COVID-19 pandemic was defined as the time period from March 1 to December 31, 2020. Excessive GWG was defined as weight gain above the BMI specific Institute of Medicine recommendations. This analysis included 2 847 592 singleton births in 2020 and compared this group with 2 847 592 singleton births in 2018. Covariates were adjusted for and pre-pandemic trends in GWG were excluded. This study found an increase of 0.06 kg (95% CI, 0.04-0.07 kg) in GWG, with more pronounced increases in pregnant individuals younger than 25 years (net change, 0.22; 95% CI, 0.19-0.26), non-Hispanic Black individuals (net change, 0.12; 95% CI, 0.07-0.16), unmarried individuals (net change, 0.16; 95% CI, 0.13-0.19), individuals who had obesity before pregnancy (net change, 0.17; 95% CI, 0.14-0.21), and individuals who used Medicaid to pay for delivery (net change, 0.17; 95% CI, 0.15-0.20). Excessive GWG was also found to be associated with the pandemic (ratio of odds ratio, 1.01; 95% CI, 1.01-1.02). Overall, this study suggested that the COVID-19 pandemic was associated with higher GWG and higher risk of excessive GWG in more vulnerable populations. Study findings may be used to further inform health practitioners caring for at-risk individuals during their pregnancy to provide further tailored dietary, lifestyle, and medical recommendations during this time period.
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