The effect of a very low calorie diet on subjective depressive symptoms and anxiety: meta-analysis and systematic review

Ein, Natalie; Armstrong, Bonnie; Vickers, Kristin S.

doi:10.1038/s41366-018-0245-4

Cited by 21 publications

(37 citation statements)

References 45 publications

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“…However, the effect of these diets on weight changes is discussible regarding weight influence on mood . Based on a systematic review and meta‐analysis on 11 studies, very low calorie diets that contain low amounts of carbohydrate and lead to weight loss decreased depressive symptoms and improved psychological well‐being . Additionally, low‐calorie diets significantly improved sleep apnea and blood pressure in overweight patients with obstructive sleep apnea syndrome .…”

Section: Discussionmentioning

confidence: 99%

Association between a low‐carbohydrate diet and sleep status, depression, anxiety, and stress score

et al. 2020

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BACKGROUND Dietary intakes, especially carbohydrates, play an important role in blood glucose control in patients with diabetes. It is suggested that carbohydrate amounts may be effective in diabetes complications. This study aimed to reveal the association of low‐carbohydrate diet (LCD) and sleep and mental status among patients with diabetes. METHODS This cross‐sectional study was conducted among 265 women with type 2 diabetes. Anthropometric measures, as well as biochemical tests, were recorded. Dietary intakes were recorded using a validated food‐frequency‐questionnaire to calculate LCD score. To assess mental disorders and sleep quality, the Depression, Anxiety and Stress Scale and the Pittsburgh Sleep Quality Index were used respectively. RESULTS Patients in the highest LCD quartile were the ones with the lowest carbohydrate consumption. There was no significant association between cardiovascular risk factors and LCD score even after controlling confounder variables (P > 0.05). Subjects in the highest quartile of LCD score compared with those within the lowest quartile had a 69% lower risk of poor sleep after adjusting confounders. The odds of depressive symptoms were negatively related to the highest quartile of LCD score in the crude model and even after full‐adjusted model (odds ratio: 0.42; 95% confidence interval: 0.17–1.01). Participants in the highest quartile of LCD score compared with those in the lowest quartile had a 73% lower risk of anxiety. CONCLUSION It seems that patients who consumed lower carbohydrate have better sleep status and are less involved with mental disorders. However, regarding the nature of the present study, well‐designed cohort studies are suggested to be conducted in the future. © 2020 Society of Chemical Industry

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Section: Discussionmentioning

confidence: 99%

Association between a low‐carbohydrate diet and sleep status, depression, anxiety, and stress score

et al. 2020

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“…For the remaining three outcomes (salivary cortisol and affect [positive and negative]), we did not receive any responses. Thus, a conservative correlation of r = 0.50 was used as the correlation coefficient for salivary cortisol and affect (positive and negative) due to lack of information [31–32]. It was also important to determine effect direction in relation to the hypothesis.…”

Section: Methodsmentioning

confidence: 99%

“…Each article was given a study rigour rating of weak, moderate, or strong. To assess study rigour, the following information was extracted and classified into five assessment categories: (1) sample size, (2) randomization of conditions, (3) use of subjective and physiological measures of stress response, (4) information about the intervention (description and theory), and (5) statistical testing [31].…”

Section: Methodsmentioning

confidence: 99%

“…Lastly, a score of two was assigned in each category if: (1) the sample size was 20 or above per condition, (2) randomization of the intervention and control conditions occurred, (3) both subjective and physiological stress measures were used, (4) there was clear and detailed information about the intervention used and theory behind the intervention, and (5) there was clear/appropriate information about the statistical tests performed. After each of the assessment categories were recorded, the scores were tallied [31]. Studies received a rigour rating based on this tallied score: weak (total score between 0 to 5), moderate (total score between 6 to 7), or strong (total score of 8 or more; S1 Table).…”

Section: Methodsmentioning

confidence: 99%

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The efficacy of stress reappraisal interventions on stress responsivity: A meta-analysis and systematic review of existing evidence

et al. 2019

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Background The beliefs we hold about stress play an important role in coping with stressors. Various theoretical frameworks of stress point to the efficacy of reframing stress-related information through brief reappraisal interventions in order to promote adaptive coping. Purpose The goal of the current meta-analysis and systematic review is to substantiate the efficacy of reappraisal interventions on stress responsivity compared to control conditions. Differences in experimental methodologies (e.g., type of stressor used, timing of reappraisal intervention, and content of intervention instructions) will be examined to further delineate their effects on intervention outcomes. Methods The literature searches were conducted on May 16, 2018 using PsycINFO, ProQuest Dissertations and Theses, and PILOTS databases with no date restriction. The search terms included stress, reframing, reappraisal, mindset and reconceptualising. A total of 14 articles with 36 independent samples were included in the meta-analysis, while 22 articles with 46 independent samples were included in the systematic review. Random-effects model was used to test the null hypothesis using two-tailed significance testing. Fisher’s Z value was reported for each corresponding test. Heterogeneity tests are reported via Cochran’s Q-statistics. Results Findings from both the meta-analysis and systematic review revealed that overall, reappraisal interventions are effective in attenuating subjective responsivity to stress. Standard differences in means across groups are 0.429 ( SE = 0.185, 95% CI = 0.067 to 0.791; z = 2.320, p = .020). However, reappraisal intervention groups did not outperform control groups on measures of physiological stress, with standard differences of -0.084 ( SE = 0.135, 95% CI = -0.349 to 0.180; z = -0.627, p = .531). Moderator analysis revealed heterogeneous effects suggesting large variability in findings. Conclusions On one hand, findings may suggest a promising avenue for the effective management of self-reported stress and optimization of stress responses. However, more research is needed to better elucidate the effects, if any, of reappraisal interventions on stress physiology. Implications for the use of reappraisal interventions on stress optimization are discussed in the context of theoretical frameworks and considerations for future studies.

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“…Obesity is a risk factor for diabetes and also a continuing risk factor for complications in those with established diabetes. A report by Ein et al [12] showed that diabetic patients had inherited the disease from either of the parents. Bommer et al [6] also found that type 2 diabetes had a hereditary factor from a close family and was associated with gene mutations that are transferred to the genetic line of the family.…”

Section: Risk Factors Associated With Typementioning

confidence: 99%

Prevalence and Risk Factors Associated with Type 2 Diabetes in Elderly Patients Aged 45-80 Years at Kanungu District

Asiimwe

Mauti

Kiconco

2020

Journal of Diabetes Research

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Background. Type 2 diabetes is a worldwide disaster including in Uganda, specifically in Kanungu District which had a rise in diabetic patients in 2018/2019 as compared to the 2017/2018 financial year. This research was determined to access the prevalence and risk factors associated with type 2 diabetes on elderly patients aged 45-80 years attending Kanungu Health Centre IV, Kanungu District. Methods. A cross-sectional study was conducted among patients aged 45-80 years attending Kanungu Health Centre IV from June to August 2019. The prevalence of type 2 diabetes was determined by the blood sugar of patients. Questionnaires were used to collect data for factors associated with type 2 diabetes. Data were statistically analyzed using the statistical package for social sciences (SPSS) version 25 (SPSS Inc., USA) at P<0.05. Results. The overall prevalence of type 2 diabetes was 18.7% among the tested patients. 22.8% of diabetic patients were females as 7.8% were males. The age group most affected by diabetes was 61-65 years. Alcoholism, smoking, body mass index (BMI), and family history were found to be significantly associated with type 2 diabetes at P value < 0.05. Conclusion. There was a high prevalence of type 2 diabetes observed in this study compared to studies done in previous years which raise a public health concern. This study also found that females and patients aged 61-65 years were most affected by diabetes. Lastly, the presence of family history for diabetes, overweight, and being obese increases the chances of acquiring type 2 diabetes.

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The effect of a very low calorie diet on subjective depressive symptoms and anxiety: meta-analysis and systematic review

Cited by 21 publications

References 45 publications

Association between a low‐carbohydrate diet and sleep status, depression, anxiety, and stress score

Association between a low‐carbohydrate diet and sleep status, depression, anxiety, and stress score

The efficacy of stress reappraisal interventions on stress responsivity: A meta-analysis and systematic review of existing evidence

Prevalence and Risk Factors Associated with Type 2 Diabetes in Elderly Patients Aged 45-80 Years at Kanungu District

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