Increased Odds of Cognitive Impairment in Adults with Depressive Symptoms and Antidepressant Use.

INTRODUCTION: The relationship between antidepressant use and class with cognition in depression is unclear. This study aimed to evaluate the association of cognition with depressive symptoms and antidepressant use (class, duration, number). METHODS: Data from the National Health and Nutrition Examination Survey were examined for cognitive function through various tests and memory issues through the Medical Conditions questionnaire. Depressive symptoms were assessed using the Patient Health Questionnaire-9. RESULTS: A total of 2867 participants were included. Participants with depressive symptoms had significantly higher odds of cognitive impairment (CI) on the animal fluency test (aOR=1.89, 95% CI=1.30, 2.73, P=0.002) and Digit Symbol Substitution test (aOR=2.58, 95% CI=1.34, 4.9, P=0.007), as well as subjective memory issues (aOR=7.25, 95% CI=4.26, 12.32, P<0.001) than those without depression. There were no statistically significant associations between any of the CI categories and depressive symptoms treated with an antidepressant and antidepressant use duration. Participants who were using more than one antidepressant had significantly higher odds of subjective memory issues than those who were using one antidepressant. Specifically, users of atypical antidepressants, selective serotonin reuptake inhibitors, or tricyclic antidepressants (TCAs) had significantly higher odds of subjective memory issues in comparison to no antidepressants, with TCAs showing the largest odds (aOR=4.21, 95% CI=1.19, 14.86, P=0.028). DISCUSSION: This study highlights the relationship between depressive symptoms, antidepressant use, and CI. Future studies should further evaluate the mechanism underlying this phenomenon.

Depressive symptoms among adults is associated with decreased food security.

OBJECTIVE: We aim to evaluate the association of depressive symptoms, depressive symptoms severity and symptom cluster scores (i.e., cognitive-affective and somatic) with food security (FS). We will also evaluate the interaction effect of sex, income and ethnicity on these associations. METHODS: Data from the 2005-2018 National Health and Nutrition Examination Survey cycles were used in this study. Participants included survey respondents 20+ years who had completed Depression and Food Security questionnaires. Multivariable logistic regression was used to estimate the associations between depressive symptoms and FS. RESULTS: A total of 34,128 participants, including 3,021 (7.73%) with depressive symptoms, were included in this study. In both unadjusted and adjusted models, participants with depressive symptoms had lower odds of FS (aOR = 0.347, 95% CI: 0.307,0.391, p<0.001). Moreover, in both unadjusted and adjusted models, for each 1-point increase in cognitive-affective (aOR = 0.850, 95% CI = 0.836,0.864, p <0.001) and somatic symptoms (aOR = 0.847, 95% CI = 0.831,0.863, p <0.001), odds of high FS decreased correspondingly. Our study found no significant interaction effects of sex on depressive symptoms-FS association. Statistically significant interactions of ethnicity and poverty-to-income ratio on depressive symptoms-FS association were observed, revealing higher odds of FS among Non-Hispanic Black and Mexican American groups, and lower odds of FS in Non-Hispanic White and high-income subgroups. CONCLUSION: Our study demonstrated an association between depressive symptoms and decreased FS. Further research is required to deepen our understanding of the underlying mechanisms and to develop focused interventions.

Temporal associations of BMI and glucose parameters with depressive symptoms among US adults.

As the prevalence of obesity, diabetes, and depression increases, it is important to examine how their associations are changing overtime. We investigated the temporal trends in the association between depressive symptoms, body mass index (BMI) and glucose profile parameters using data from 2005 to 2018 National Health and Nutrition Examination Survey. Depressive symptoms were assessed using the Patient Health Questionnaire. A total of 32,653 participants were included. Risk of depressive symptoms increased with higher BMI (aOR = 1.586, 95 % CI [1.364, 1.843]), insulin (aOR = 1.327, 95 % CI [1.159, 1.519]), HbA1c (aOR = 1.330, 95 % CI [1.116, 1.585]), or fasting glucose (aOR = 1.565, 95 % CI [1.247, 1.964]) levels compared to those with low levels. Sex differences were found, as overweight males had lower odds of depressive symptoms compared to healthy males, while overweight and obese females had higher odds compared to healthy females. High BMI and glucose parameters were consistently associated with higher depressive symptoms prevalence over time. Temporal variations were observed in the depressive symptoms-BMI and depressive symptoms-HbA1c associations, particularly at the 2007-2008 cycle. This study provides analytic insights into population level trends concerning physical and mental health problems.

Problematic Internet Use and Personality Traits: Results in Working Age Adults.

INTRODUCTION: Problematic Internet use has become a growing problem worldwide; several factors, including personality, play an essential role in understanding this disorder. The Big Five personality traits and their association with problematic Internet use were examined in a large and diverse population. METHODS: A survey was applied to a total of 1,109 adults of working age. Each answered the Big Five Inventory and the Internet Addiction Test. RESULTS: Problematic Internet use was found in 10.6% of them (n=112). The personality traits extraversion and openness to experience were significantly associated with those with the disorder. With adjustment models, a positive association was found between these traits and being single and higher education. CONCLUSIONS: This study represents the largest of its kind in the Spanish-speaking population, highlighting the importance of recognising the factors involved in problematic Internet use.

Naturalistic Study of Depression Associated with Parkinson's Disease in a National Public Neurological Referral Center in Mexico.

Major depressive disorder (MDD) is a major health problem in Parkinson's disease (PD) patients. We described the clinical and sociodemographic factors of MDD among patients with PD at a national neurological referral center in Mexico. One hundred patients with PD + MDD were included in the study. All the patients were evaluated during the "ON" treatment phase of PD. Clinical scales for cognition (MMSE and MoCA) and MDD (MADRS) were applied. The mean age was 58.49 ± 11.02 years, and 57% of the sample was male. The most frequent symptom of PD was tremor (67%), and onset was more frequent on the right side (57%). Additionally, 49% of the patients with PD had moderate to severe (M/S) MDD. Selective serotonin reuptake inhibitors were the most frequent antidepressant treatment (69%). The scores of the scales were MADRS 21.33 ± 5.49, MoCA 21.06 ± 4.65, and MMSE 26.67 ± 1.20. The females had lower MMSE scores compared to the males (p = 0.043). The patients with M/S MDD had more rigidity at the beginning of PD (p = 0.005), fewer march alterations (p = 0.023), and a greater prevalence of left-side initial disease (p = 0.037). Rigidity was associated with M/S MDD (OR 3.75 p = 0.013). MDD was slightly more frequent in the males than in the females. The MDD symptoms and cognitive impairment were worse in the female population.

Deep Multi-OMICs and Multi-Tissue Characterization in a Pre- and Postprandial State in Human Volunteers: The GEMM Family Study Research Design.

Cardiovascular disease (CVD) and type 2 diabetes (T2D) are increasing worldwide. This is mainly due to an unhealthy nutrition, implying that variation in CVD risk may be due to variation in the capacity to manage a nutritional load. We examined the genomic basis of postprandial metabolism. Our main purpose was to introduce the GEMM Family Study (Genetics of Metabolic Diseases in Mexico) as a multi-center study carrying out an ongoing recruitment of healthy urban adults. Each participant received a mixed meal challenge and provided a 5-hours' time course series of blood, buffy coat specimens for DNA isolation, and adipose tissue (ADT)/skeletal muscle (SKM) biopsies at fasting and 3 h after the meal. A comprehensive profiling, including metabolomic signatures in blood and transcriptomic and proteomic profiling in SKM and ADT, was performed to describe tendencies for variation in postprandial response. Our data generation methods showed preliminary trends indicating that by characterizing the dynamic properties of biomarkers with metabolic activity and analyzing multi-OMICS data it could be possible, with this methodology and research design, to identify early trends for molecular biology systems and genes involved in the fasted and fed states.