scholarly journals Cross-Sectional and Longitudinal Predictability of Mental Health Using Sense of Coherence: Estimation Using Linear Regression and Generalized Additive Models

2019 ◽  
Vol 28 (2) ◽  
pp. 175-178
Author(s):  
Takayoshi Kase ◽  
Yuki Ueno
Keyword(s):  
Mental Health ◽  
Linear Regression ◽  
Sense Of Coherence ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Cross Sectional ◽  
Coherence Estimation

scholarly journals Dose response association of objective physical activity with mental health in a representative national sample of adults: a cross-sectional study

2018 ◽  
Author(s):  
Paquito Bernard ◽  
Isabelle Doré ◽  
Romain Ahmed Jérôme ◽  
Gabriel Hains-Monfette ◽  
Kingsbury ◽  
...  
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Dose Response ◽  
Sedentary Time ◽  
Generalized Additive Models ◽  
National Sample ◽  
Additive Models ◽  
Curvilinear Relationship ◽  
Cross Sectional ◽  
Representative National Sample

Although higher physical activity (PA) levels are associated with better mental health, previous findings about the shape of the dose–response relationship between PA and mental health are inconsistent. Furthermore, this association may differ according to sedentary levels. We investigated the cross-sectional dose-response associations between objectively measured PA and mental health in a representative national sample of adults. We also examined whether sedentary time modified the PA - mental health associations. Based on 2007-2013 Canadian Health Measures Survey data, PA and sedentary time were measured using accelerometry among 8150 participants, aged 20 to 79 years. Generalized additive models with a smooth function were fitted to examine associations between minutes per day of moderate and vigorous PA (MVPA), light PA (LPA), daily steps (combined or not with sedentary time) and self-rated mental health. A significant curvilinear relationship between average daily minutes of MVPA and mental health was observed, with increasing benefits up to 50 minutes/day. For LPA, a more complex shape (monotonic and curvilinear) was found. For daily steps, inverted U-shaped curve suggested increasing benefits until a plateau between 5000 and 16000 steps. The MVPA-LPA combination was significantly associated with mental health but with a complex pattern. The tested PA-sedentary time combinations showed that increasing sedentary time decreased the positive PA-mental health associations. Non-linear dose-response patterns between the PA modalities and self-reported mental health were observed. Optimal doses of daily minutes of MVPA, LPA, MVPA combined with LPA and daily steps are independently associated with better mental health in adults. The results also suggest that PA-mental health associations could be hampered by daily sedentary time.

scholarly journals Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income

2019 ◽  
Vol 16 (20) ◽  
pp. 4009 ◽  
Author(s):  
Alexander Silbersdorff ◽  
Kai Sebastian Schneider
Keyword(s):  
Mental Health ◽  
Health Inequalities ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Mental Health Score ◽  
Cross Sectional ◽  
Regression Techniques ◽  
German Socioeconomic Panel ◽  
The Relationship ◽  
Distributional Regression

This study addresses the much-discussed issue of the relationship between health and income. In particular, it focuses on the relation between mental health and household income by using generalized additive models of location, scale and shape and thus employing a distributional perspective. Furthermore, this study aims to give guidelines to applied researchers interested in taking a distributional perspective on health inequalities. In our analysis we use cross-sectional data of the German socioeconomic Panel (SOEP). We find that when not only looking at the expected mental health score of an individual but also at other distributional aspects, like the risk of moderate and severe mental illness, that the relationship between income and mental health is much more pronounced. We thus show that taking a distributional perspective, can add to and indeed enrich the mostly mean-based assessment of existent health inequalities.

scholarly journals Non-Parametric Generalized Additive Models as a Tool for Evaluating Policy Interventions

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 299
Author(s):  
Jaime Pinilla ◽  
Miguel Negrín
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Trend ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Linear Regression Models ◽  
Non Linear ◽  
Nonlinear Trends ◽  
The Impact ◽  
Non Parametric

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.

scholarly journals Prevalence of internalizing disorders, symptoms, and traits across age using advanced nonlinear models

2021 ◽  
pp. 1-10
Author(s):  
Hanna M. van Loo ◽  
Lian Beijers ◽  
Martijn Wieling ◽  
Trynke R. de Jong ◽  
Robert A. Schoevers ◽  
...  
Keyword(s):  
Internalizing Symptoms ◽  
Nonlinear Models ◽  
Generalized Additive Models ◽  
Population Sample ◽  
Internalizing Disorders ◽  
Relative Difference ◽  
Additive Models ◽  
Point Prevalence ◽  
Cross Sectional ◽  
The Impact

Abstract Background Most epidemiological studies show a decrease of internalizing disorders at older ages, but it is unclear how the prevalence exactly changes with age, and whether there are different patterns for internalizing symptoms and traits, and for men and women. This study investigates the impact of age and sex on the point prevalence across different mood and anxiety disorders, internalizing symptoms, and neuroticism. Methods We used cross-sectional data on 146 315 subjects, aged 18–80 years, from the Lifelines Cohort Study, a Dutch general population sample. Between 2012 and 2016, five current internalizing disorders – major depression, dysthymia, generalized anxiety disorder, social phobia, and panic disorder – were assessed according to DSM-IV criteria. Depressive symptoms, anxiety symptoms, neuroticism, and negative affect (NA) were also measured. Generalized additive models were used to identify nonlinear patterns across age, and to investigate sex differences. Results The point prevalence of internalizing disorders generally increased between the ages of 18 and 30 years, stabilized between 30 and 50, and decreased after age 50. The patterns of internalizing symptoms and traits were different. NA and neuroticism gradually decreased after age 18. Women reported more internalizing disorders than men, but the relative difference remained stable across age (relative risk ~1.7). Conclusions The point prevalence of internalizing disorders was typically highest between age 30 and 50, but there were differences between the disorders, which could indicate differences in etiology. The relative gap between the sexes remained similar across age, suggesting that changes in sex hormones around the menopause do not significantly influence women's risk of internalizing disorders.

scholarly journals Mental Health, Sense of Coherence, and Interpersonal Violence during the COVID-19 Pandemic Lockdown in Germany

2020 ◽  
Vol 9 (11) ◽  
pp. 3708
Author(s):  
Stefanie Jung ◽  
Jonas Kneer ◽  
Tillmann H. C. Krüger
Keyword(s):  
Mental Health ◽  
Sense Of Coherence ◽  
Interpersonal Violence ◽  
Online Survey ◽  
Short Form ◽  
Well Being ◽  
Western Country ◽  
Cross Sectional ◽  
Substantial Impact ◽  
Patient Health

Preliminary data indicates that the Coronavirus SARS-CoV-2 disease (COVID-19) pandemic may have a substantial impact on mental health and well-being. We assessed mental health in response to the lockdown in Germany between 1 April 2020 and 15 April 2020 using a cross-sectional online survey (n = 3545) with a mixed-methods approach. We found increased levels of psychosocial distress (Patient Health Questionnaire (PHQ) stress module), anxiety, depressive symptoms (PHQ-4), irritability, and a decrease in overall well-being (WHO-Five Well-Being Index (WHO-5)), sense of coherence (Short Form of the Sense of Coherence Scale (SOC-L9)), sexual contentment, and sleep quality. The four-week-prevalence of interpersonal violence was yet at 5% and included verbal, physical, and sexual violence. Participants reported finding comfort in family, friends, conversation, exercise, and activity. Findings are also in line with research showing that women seem to have more trouble coping with the pandemic and lockdown measures. Our observations demonstrate that the COVID-19 pandemic and related measures lead to a mental health burden even in a highly developed Western country and should, therefore, be taken seriously. The findings for interpersonal violence are alarming. Thus, we should sharpen our focus on the matter and activate and enhance supporting systems to help protect those affected.

scholarly journals Association Between Waist Circumference and the Prevalence of (Pre) Hypertension Among 27,894 US Adults

2021 ◽  
Vol 8 ◽  
Author(s):  
Jin-Yu Sun ◽  
Yang Hua ◽  
Hua-Yi-Yang Zou ◽  
Qiang Qu ◽  
Yue Yuan ◽  
...  
Keyword(s):  
Waist Circumference ◽  
Confidence Intervals ◽  
Generalized Additive Models ◽  
Young Group ◽  
Cubic Spline ◽  
Normal Weight ◽  
Additive Models ◽  
Trend Test ◽  
Odds Ratios ◽  
Cross Sectional

Aims: This study aimed to investigate the association between waist circumference and the prevalence of (pre) hypertension.Methods: Cross-sectional data from the 2007–2018 National Health and Nutrition Examination Survey were analyzed. The historical trend of abdominal obesity was assessed by the Cochran–Armitage trend test. After preprocessed by the multiple imputation strategy, we used generalized additive models to assess the association of waist circumference with systolic/diastolic blood pressure and performed correlation analysis by the Spearman correlation coefficient. Moreover, we used multivariable logistic regression (non-adjusted, minimally adjusted, and fully adjusted models), restricted cubic spline, and sensitivity analysis to investigate the association between waist circumference and (pre) hypertension.Results: A total of 27,894 participants were included in this study. In the fully adjusted model, waist circumference was positively associated with (pre) hypertension with odds ratios (95% confidence intervals) of 1.28 (1.18–1.40) in the young group and 1.23 (1.15–1.33) in the old group. Restricted cubic spline showed a higher prevalence of (pre) hypertension with the increase of waist circumference. In the subgroup analysis, waist circumference showed a robust trend across all BMI categories with odds ratios (95% confidence intervals) of 3.33 (1.29–8.85), 1.35 (1.17–1.57), 1.27 (1.13–1.41), and 1.09 (1.01–1.17) in underweight, normal weight, overweight, and obese individuals, respectively.Conclusion: This study highlighted waist circumference as a significant biomarker to evaluate the risk of (pre) hypertension. Our results supported the measure of waist circumference regardless of BMI when evaluating the cardiometabolic risk related to fat distribution.

scholarly journals Telomere length is associated with growth in children in rural Bangladesh

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Audrie Lin ◽  
Andrew N Mertens ◽  
Benjamin F Arnold ◽  
Sophia Tan ◽  
Jue Lin ◽  
...  
Keyword(s):  
Telomere Length ◽  
Generalized Additive Models ◽  
Nutritional Intervention ◽  
Additive Models ◽  
P Value ◽  
Z Score ◽  
Cross Sectional ◽  
Telomere Attrition ◽  
Healthy Growth ◽  
Gates Foundation

Background: Previously, we demonstrated that a water, sanitation, handwashing, and nutritional intervention improved linear growth and was unexpectedly associated with shortened childhood telomere length (TL) (Lin et al., 2017). Here, we assessed the association between TL and growth. Methods: We measured relative TL in whole blood from 713 children. We reported differences between the 10th percentile and 90th percentile of TL or change in TL distribution using generalized additive models, adjusted for potential confounders. Results: In cross-sectional analyses, long TL was associated with a higher length-for-age Z score at age 1 year (0.23 SD adjusted difference in length-for-age Z score (95% CI 0.05, 0.42; FDR-corrected p-value = 0.01)). TL was not associated with other outcomes. Conclusions: Consistent with the metabolic telomere attrition hypothesis, our previous trial findings support an adaptive role for telomere attrition, whereby active TL regulation is employed as a strategy to address 'emergency states' with increased energy requirements such as rapid growth during the first year of life. Although short periods of active telomere attrition may be essential to promote growth, this study suggests that a longer overall initial TL setting in the first two years of life could signal increased resilience against future telomere erosion events and healthy growth trajectories. Funding: Funded by the Bill and Melinda Gates Foundation.

scholarly journals Effects of mobility restrictions on mental health among young adults in the context of COVID-19 pandemic. A cross-sectional study

2021 ◽  
Author(s):  
Tannia Valeria Carpio-Arias ◽  
Santiago Piedra ◽  
Tomas Marcelo Nicolalde-Cifuentes ◽  
Diana Carolina Mogrovejo-Arias ◽  
María Victoria Padilla-Samaniego ◽  
...  
Keyword(s):  
Mental Health ◽  
Young Adults ◽  
Sleep Quality ◽  
Eating Behavior ◽  
Healthy Eating ◽  
Sense Of Coherence ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Healthy Eating Behavior

Abstract Purpose: To explore the effects of mobility restriction on the mental health of Ecuadorian young adults. Methods: The current is a cross-sectional study that included 8426 young adults. Socio-demographic and mental health data were collected through an online survey during May and June 2020 in Ecuador. Data on mobility was extracted from Google Mobility Reports. Four aspects of the participants’ mental health were evaluated: eating behavior (emotional eating), depression, sleep quality and sense of coherence using previously validated instruments. Data were analyzed using linear regression using R. Results: Mean age of the participants was 22.85 (SD = 4.43), most of whom were women (n = 5943, 70.53%). During mandatory confinement, mobility due to retail and recreation, to groceries and pharmacies, to parks, to transit stations, to workplaces were reduced by nearly 50%. In contrast, mobility to places of residence increased by nearly 20%. A reduction in mobility to workplaces was associated to less healthy eating behavior, depression and worse sleep quality. Less healthy eating behavior was also associated to decreased mobility due to recreation and retail and increased mobility to transit stations. Sense of coherence was not associated to changes on mobility. Women and youngsters more often showed depression, less healthy eating behavior, worse quality of sleep and lower sense of coherence. Conclusion: Mobility restrictions during COVID-19 pandemic has negative effects on people's mental health. Prevention and health promotion measures directed to ameliorate the effects of confinement on mental health should target risk populations including women and youngsters.

scholarly journals Sense of Coherence and Mental Health in College Students After Returning to School During COVID-19: The Moderating Role of Media Exposure

2021 ◽  
Vol 12 ◽  
Author(s):  
Man Li ◽  
Zhansheng Xu ◽  
Xinyue He ◽  
Jiahui Zhang ◽  
Rui Song ◽  
...  
Keyword(s):  
Mental Health ◽  
College Students ◽  
Sense Of Coherence ◽  
Media Exposure ◽  
Self Report ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Epidemic Period ◽  
Information Exposure ◽  
Returning To School

The COVID-19 pandemic not only threatens people’s physical health, but also affects their mental health in the long term. Although people had returned to work and school, they are closely monitoring the development of the epidemic and taking preventive measures. This study attempted to examine the relationship between media exposure, sense of coherence (SOC) and mental health, and the moderating effect of media exposure in college students after returning to school. In the present study, we conducted a cross sectional survey on 424 college students returning to school around May 2020. Self-report questionnaires were used to assess media exposure scale, SOC, depression, anxiety and stress. Correlation and moderation analysis was conducted. The results showed that (1) negative epidemic information exposure, rather than positive epidemic information exposure, was significantly associated with depression, anxiety, and stress. (2) SOC was also associated with depression, anxiety, and stress. (3) The effect of SOC on depression was modified by negative epidemic information exposure. With the increase of negative epidemic information exposure, the predictive effect of SOC on depression is increasing gradually. These findings demonstrated that negative epidemic information exposure was associated with an increased psychological distress in the sample. A high SOC played a certain protective role in the adaptation of college students in the post-epidemic period. It is important to find more ways to increase the colleges’ SOC level and avoid negative information exposure.

scholarly journals The impact of air pollution on COVID-19 pandemic varied within different cities in South America using different models

2021 ◽  
Author(s):  
Haining Huang ◽  
Congtian Lin ◽  
Xiaobo Liu ◽  
Liting Zhu ◽  
Ricardo David Avellán-Llaguno ◽  
...  
Keyword(s):  
Air Pollution ◽  
Linear Regression ◽  
South America ◽  
Multiple Linear Regression ◽  
Generalized Additive Models ◽  
Environmental Pollutants ◽  
Additive Models ◽  
Local Conditions ◽  
Multiple Regions ◽  
The Impact

Abstract There is a rising concern that air pollution plays an important role in the COVID-19 pandemic. However, the results weren’t consistent on the association between air pollution and the spread of COVID-19. In the study, air pollution data and the confirmed cases of COVID-19 were both gathered from five severe cities across three countries in South America. Daily real-time population regeneration (Rt) were calculated to assess the spread of COVID-19. Two frequently used model, generalized additive models (GAM) and multiple linear regression, were both used to explore the impact of environmental pollutants on the epidemic. Wide ranges of all the six air pollutants were detected across the five cities. Spearman's correlation analysis confirmed the positive correlation within six pollutants. Rt value showed a gradual decline in all the five cities. Further analysis showed that the association between air pollution and COVID-19 varied across five cities. Multiple linear regression and GAM did not give the same trend in a specific city. For example, in Sao Paulo, the GAM model shows that PM10 has a nonlinear negative correlation with Rt, while PM10 has no significant correlation in the multiple linear model. According to our research results, even for the same region, varied models gave inconsistent results. Moreover, in the case of multiple regions, current used models should be selected according to local conditions.

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