An eating pattern characterised by skipped or delayed breakfast is associated with mood disorders among an Australian adult cohort

Examining the association of breakfast skipping with sleep disturbance, mental health, and health-related quality of life: data from the 2018 Korean community health survey

Objectives: This study aimed to explore the relationship between breakfast skipping and its effects on sleep disorders, mental health, and health-related quality of life among Korean adults.Methods: Utilizing data from the 2018 Korea Community Health Survey, this cross-sectional analysis included 173,272 adults aged 19 years and older. Instruments used for assessment included the Patient Health Questionnaire-9 for depression, the EuroQol 5-dimension (EQ-5D) for health-related quality of life, and the Pittsburgh Sleep Quality Index for sleep disorders. The complex sample logistic regression analysis was employed to adjust for potential confounders.Results: Breakfast skipping was found to be significantly associated with delayed mid-sleep time, an increased propensity for daytime sleepiness, and a notable decline in sleep quality. Additionally, it was linked to a significant increase in depression risk, compromised health-related quality of life, and elevated stress levels across both genders. All five dimensions of the EQ-5D were negatively impacted by breakfast skipping.Discussion: The findings highlight the detrimental effects of skipping breakfast on sleep patterns, mental health, and overall quality of life, stressing the importance of regular breakfast consumption for enhancing these health outcomes. The study suggests the need for further research to uncover the mechanisms behind these associations and to devise targeted interventions to mitigate the negative impacts of breakfast skipping.

Breakfast skipping is linked to a higher risk of major depressive disorder and the role of gut microbes: a mendelian randomization study

BACKGROUND

Observational studies have indicated that breakfast skipping and gut microbiome dysbiosis are associated with a higher risk of major depressive disorder (MDD). However, it remains unknown whether the alteration of gut microbes is implicated in the associations between breakfast skipping and MDD.

METHODS

Leveraging genome-wide association studies (GWAS) on breakfast skipping, gut microbes, and MDD, we conducted a two-step Mendelian randomization (MR) study to determine the causal associations between breakfast skipping (N = 193,860) and MDD (N = 1,815,091), and evaluate the role of gut microbes (N = 18,340). Genetic variants with a P-value less than 5E-08 were selected as instrumental variables (IVs). The false discovery rate (FDR) method was employed to correct the P-values for multiple tests in gut microbes.

RESULTS

Breakfast skipping was associated with an increased risk of MDD (odds ratio [OR] = 1.36, 95%CI = 1.12-1.65, P = 0.002), but no effect of MDD on breakfast skipping was observed (β per doubling odds of MDD =-0.001, 95%CI=-0.024 to 0.023, P = 0.957). After adjusting for multiple comparisons, the MR analysis provided little evidence for an association between breakfast skipping and the abundance of any gut microbes (PFDR>0.05). Among the 21 gut microbes with IVs available, only the abundance of Class Actinobacteria was causally associated with a reduced risk of MDD (OR = 0.85, 95%CI = 0.75-0.97, PFDR=0.015).

CONCLUSIONS

Our findings demonstrated that breakfast skipping was associated with an increased risk of MDD, but provided little evidence supporting the role of the abundance of gut microbes in it. Further efforts with a large sample size are warranted to clarify the findings.

Chrononutrition and Cardiometabolic Health: An Overview of Epidemiological Evidence and Key Future Research Directions

Chrononutrition is a rapidly evolving field of nutritional epidemiology that addresses the complex relationship between temporal eating patterns, circadian rhythms, and metabolic health, but most prior research has focused on the cardiometabolic consequences of time-restricted feeding and intermittent fasting. The purpose of this topical review is to summarize epidemiological evidence from observational and intervention studies regarding the role of chrononutrition metrics related to eating timing and regularity in cardiometabolic health preservation and cardiovascular disease prevention. Observational studies are limited due to the lack of time-stamped diet data in most population-based studies. Findings from cohort studies generally indicate that breakfast skipping or the later timing of the first eating occasion, a later lunch and dinner, and a greater proportion of caloric intake consumed in the evening are associated with adverse cardiometabolic outcomes, including higher risk for coronary heart disease, hypertension, type 2 diabetes, obesity, dyslipidemia, and systemic inflammation. Randomized controlled trials are also limited, as most in the field of chrononutrition focus on the cardiometabolic consequences of time-restricted feeding. Overall, interventions that shift eating timing patterns to earlier in the day and that restrict evening caloric intake tend to have protective effects on cardiometabolic health, but small sample sizes and short follow-up are notable limitations. Innovation in dietary assessment approaches, to develop low-cost validated tools with acceptable participant burden that reliably capture chrononutrition metrics, is needed for advancing observational evidence. Culturally responsive pragmatic intervention studies with sufficiently large and representative samples are needed to understand the impact of fixed and earlier eating timing schedules on cardiometabolic health. Additional research is warranted to understand the modifiable determinants of temporal eating patterns, to investigate the role of chrononutrition in the context of other dimensions of diet (quantity, quality, and food and nutrition security) in achieving cardiometabolic health equity, and to elucidate underlying physiological mechanisms.

Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation

BACKGROUND

Depression is often accompanied by changes in behavior, including dietary behaviors. The relationship between dietary behaviors and depression has been widely studied, yet previous research has relied on self-reported data which is subject to recall bias. Electronic device-based behavioral monitoring offers the potential for objective, real-time data collection of a large amount of continuous, long-term behavior data in naturalistic settings.

OBJECTIVE

The study aims to characterize digital dietary behaviors in depression, and to determine whether these behaviors could be used to detect depression.

METHODS

A total of 3310 students (2222 healthy controls [HCs], 916 with mild depression, and 172 with moderate-severe depression) were recruited for the study of their dietary behaviors via electronic records over a 1-month period, and depression severity was assessed in the middle of the month. The differences in dietary behaviors across the HCs, mild depression, and moderate-severe depression were determined by ANCOVA (analyses of covariance) with age, gender, BMI, and educational level as covariates. Multivariate logistic regression analyses were used to examine the association between dietary behaviors and depression severity. Support vector machine analysis was used to determine whether changes in dietary behaviors could detect mild and moderate-severe depression.

RESULTS

The study found that individuals with moderate-severe depression had more irregular eating patterns, more fluctuated feeding times, spent more money on dinner, less diverse food choices, as well as eating breakfast less frequently, and preferred to eat only lunch and dinner, compared with HCs. Moderate-severe depression was found to be negatively associated with the daily 3 regular meals pattern (breakfast-lunch-dinner pattern; OR 0.467, 95% CI 0.239-0.912), and mild depression was positively associated with daily lunch and dinner pattern (OR 1.460, 95% CI 1.016-2.100). These changes in digital dietary behaviors were able to detect mild and moderate-severe depression (accuracy=0.53, precision=0.60), with better accuracy for detecting moderate-severe depression (accuracy=0.67, precision=0.64).

CONCLUSIONS

This is the first study to develop a profile of changes in digital dietary behaviors in individuals with depression using real-world behavioral monitoring. The results suggest that digital markers may be a promising approach for detecting depression.

Association of macronutrient consumption quality, food source and timing with depression among US adults: A cross-sectional study

BACKGROUND

Growing evidence suggests that meal timing may influence dietary choices and mental health. Thus, this study examined the association between macronutrient consumption quality, food source, meal timing, and depression prevalence in Americans.

METHODS

23,313 National Health and Nutrition Survey participants from 2007 to 2016 were included in this cross-sectional study. Macronutrient intake was calculated for all day, dinner, and breakfast and subtypes into 4 classes. Based on the Patient Health Questionnaire, depression was defined as a 9-item score ≥ 10 on the PHQ-9. The correlation between macronutrients and depression prevalence was estimated with multivariable logistic regression models and isocaloric substitution effects.

RESULTS

Low-quality carbohydrates (OR = 1.54, 95 % CI: 1.11, 2.12) were positively linked to depression compared with the lowest quartile, after adjusting for age and other covariates. In contrast, total high-quality carbohydrate (OR = 0.52, 95 % CI: 0.40, 0.66), total animal protein (OR = 0.60, 95 % CI: 0.45, 0.80), and total vegetable protein (OR = 0.61, 95 % CI: 0.43, 0.85) were negatively associated with depression was negatively associated. Replacing low-quality carbohydrates with high-quality carbohydrates throughout the day reduced the risk of depression by approximately 15 %.

LIMITATIONS

Cross-sectional data.

CONCLUSION

All in all, diet plays a crucial role in the prevention and treatment of depression. Especially in terms of macronutrient intake, high-quality, moderate intake can reduce the risk of depression. However, different subtypes of macronutrient consumption may have different effects on depression, so it becomes crucial to carefully consider the selection and combination of macronutrients.

Associations between breakfast skipping and outcomes in neuropsychiatric disorders, cognitive performance, and frailty: a Mendelian randomization study

BACKGROUND

Prior studies have identified a correlation between breakfast skipping and a heightened risk of mental health issues. This investigation aimed to employ a Two-Sample Mendelian Randomization (MR) approach to explore the potential causal links between breakfast skipping and various psychiatric, neurological disorders, cognitive performance, and frailty.

METHODS

Utilizing data from genome-wide association studies within European demographics, this research scrutinized the association between breakfast habits and several neuropsychiatric conditions and physical health outcomes, including Alzheimer's disease (AD), Attention Deficit Hyperactivity Disorder (ADHD), Bipolar Disorder (BD), Major Depressive Disorder (MDD), Narcolepsy, Insomnia, cognitive performance, and frailty. In this MR analysis, the Inverse Variance Weighted (IVW) method was primarily utilized for evaluation. Outcomes were reported as Odds Ratios (OR) and regression coefficients (β), and underwent validation through False Discovery Rate (FDR) corrections, thereby offering a rigorous evaluation of the effects of breakfast habits on both mental and physical health dimensions.

RESULTS

Findings demonstrate a significant causal link between skipping breakfast and an increased risk of ADHD (OR = 2.74, 95%CI: 1.54-4.88, PFDR = 0.003) and MDD (OR = 1.7, 95%CI: 1.22-2.37, PFDR = 0.005). Conversely, no substantial causal associations were identified between breakfast skipping and AD, BD, narcolepsy, or insomnia (PFDR > 0.05). Moreover, a notable causal relationship was established between skipping breakfast and a reduction in cognitive performance (β = -0.16, 95%CI: -0.29-0.04, PFDR = 0.024) and an increase in frailty (β = 0.29, 95%CI: 0.12-0.45, PFDR = 0.003).

CONCLUSION

The MR analysis reveals that skipping breakfast is associated with an increased risk of ADHD, MDD, decreased cognitive performance, and greater frailty, while showing no associations were found with AD, BD, narcolepsy, or insomnia. These findings warrant further investigation into the underlying mechanisms and emphasize the importance of regular breakfast consumption for mental and physical well-being.

Dietary Intake Assessment Using a Novel, Generic Meal-Based Recall and a 24-Hour Recall: Comparison Study

BACKGROUND

Dietary intake assessment is an integral part of addressing suboptimal dietary intakes. Existing food-based methods are time-consuming and burdensome for users to report the individual foods consumed at each meal. However, ease of use is the most important feature for individuals choosing a nutrition or diet app. Intakes of whole meals can be reported in a manner that is less burdensome than reporting individual foods. No study has developed a method of dietary intake assessment where individuals report their dietary intakes as whole meals rather than individual foods.

OBJECTIVE

This study aims to develop a novel, meal-based method of dietary intake assessment and test its ability to estimate nutrient intakes compared with that of a web-based, 24-hour recall (24HR).

METHODS

Participants completed a web-based, generic meal-based recall. This involved, for each meal type (breakfast, light meal, main meal, snack, and beverage), choosing from a selection of meal images those that most represented their intakes during the previous day. Meal images were based on generic meals from a previous study that were representative of the actual meal intakes in Ireland. Participants also completed a web-based 24HR. Both methods were completed on the same day, 3 hours apart. In a crossover design, participants were randomized in terms of which method they completed first. Then, 2 weeks after the first dietary assessments, participants repeated the process in the reverse order. Estimates of mean daily nutrient intakes and the categorization of individuals according to nutrient-based guidelines (eg, low, adequate, and high) were compared between the 2 methods. P values of less than .05 were considered statistically significant.

RESULTS

In total, 161 participants completed the study. For the 23 nutrient variables compared, the median percentage difference between the 2 methods was 7.6% (IQR 2.6%-13.2%), with P values ranging from <.001 to .97, and out of 23 variables, effect sizes for the differences were small for 19 (83%) variables, moderate for 2 (9%) variables, and large for 2 (9%) variables. Correlation coefficients were statistically significant (P<.05) for 18 (78%) of the 23 variables. Statistically significant correlations ranged from 0.16 to 0.45, with median correlation of 0.32 (IQR 0.25-0.40). When participants were classified according to nutrient-based guidelines, the proportion of individuals who were classified into the same category ranged from 52.8% (85/161) to 84.5% (136/161).

CONCLUSIONS

A generic meal-based method of dietary intake assessment provides estimates of nutrient intake comparable with those provided by a web-based 24HR but with varying levels of agreement among nutrients. Further studies are required to refine and improve the generic recall across a range of nutrients. Future studies will consider user experience including the potential feasibility of incorporating image recognition of whole meals into the generic recall.

Translating the user-avatar bond into depression risk: A preliminary machine learning study

Research has shown a link between depression risk and how gamers form relationships with their in-game figure of representation, called avatar. This is reinforced by literature supporting that a gamer's connection to their avatar may provide broader insight into their mental health. Therefore, it has been argued that if properly examined, the bond between a person and their avatar may reveal information about their current or potential struggles with depression offline. To examine whether the connection with an individuals' avatars may reveal their risk for depression, longitudinal data from 565 adults/adolescents (Mage = 29.3 years, SD = 10.6) were evaluated twice (six months apart). Participants completed the User-Avatar-Bond [UAB] scale and Depression Anxiety Stress Scale to measure avatar bond and depression risk. A series of tuned and untuned artificial intelligence [AI] classifiers analyzed their responses concurrently and prospectively. This allowed the examination of whether user-avatar bond can provide cross-sectional and predictive information about depression risk. Findings revealed that AI models can learn to accurately and automatically identify depression risk cases, based on gamers' reported UAB, age, and length of gaming involvement, both at present and six months later. In particular, random forests outperformed all other AIs, while avatar immersion was shown to be the strongest training predictor. Study outcomes demonstrate that UAB can be translated into accurate, concurrent, and future, depression risk predictions via trained AI classifiers. Assessment, prevention, and practice implications are discussed in the light of these results.

Depression and lifestyle: Focusing on nutrition, exercise, and their possible relevance to molecular mechanisms

Accumulating evidence has suggested the important role of lifestyle factors in depressive disorder. This paper aimed to introduce and outline recent research on epidemiological and intervention studies on lifestyle-related factors in depressive disorder with a special focus on diet. Evidence on exercise, sleep. and related behaviors is also described. Here, findings from meta-analytic studies are emphasized and related studies by the author's research group are introduced. Dietary factors that increase the risk of the illness include energy overload, skipping breakfast, unhealthy diet styles such as Western diet, inflammation-prone diet, and high consumption of ultraprocessed food (UPF). Nutritional imbalances such as inadequate intake of protein, fish (Ω3 polyunsaturated fatty acids), vitamins (folate and vitamin D), and minerals (iron and zinc) increases the risk of depression. Poor oral hygiene, food allergy, addiction to alcohol, and smoking constitute risk factors. Sedentary lifestyle and increased screen time (e.g. video games and the internet) confer the risk of depression. Insomnia and disturbed sleep-wake rhythm are also involved in the pathogenesis of depression. There is accumulating evidence at the meta-analysis level for interventions to modify these lifestyle habits in the protection and treatment of depressive disorder. Main biological mechanisms of the link between lifestyle factors and depression include monoamine imbalance, inflammation, altered stress response, oxidative stress, and dysfunction of brain-derived neurotrophic factor, although other players such as insulin, leptin, and orexin also play a role. To increase resilience to modern stress and ameliorate depression through modification of lifestyle habits, a list of 30 recommendable interventions is presented.

Characterizing eating behavioral phenotypes in mood disorders: a narrative review

Mood disorders, including depressive and bipolar disorders, represent a multidimensional and prevalent group of psychiatric illnesses characterized by disturbances in emotion, cognition and metabolism. Maladaptive eating behaviors in mood disorders are diverse and warrant characterization in order to increase the precision of diagnostic criteria, identify subtypes and improve treatment strategies. The current narrative review synthesizes evidence for Eating Behavioral Phenotypes (EBP) in mood disorders as well as advancements in pathophysiological conceptual frameworks relevant to each phenotype. Phenotypes include maladaptive eating behaviors related to appetite, emotion, reward, impulsivity, diet style and circadian rhythm disruption. Potential treatment strategies for each phenotype are also discussed, including psychotherapeutic, pharmacological and nutritional interventions. Maladaptive eating behaviors related to mood disorders are relevant from both clinical and research perspectives, yet have been somewhat overlooked thus far. A better understanding of this aspect of mood disorders holds promise to improve clinical care in this patient group and contribute to the subtyping of these currently subjectively diagnosed and treated disorders.

Modifiable Host Factors for the Prevention and Treatment of COVID-19: Diet and Lifestyle/Diet and Lifestyle Factors in the Prevention of COVID-19

Many studies have shown that the immune system requires adequate nutrition to work at an optimal level. Not only do optimized nutritional strategies support the immune system, but they also reduce chronic inflammation. Nutritional supplements that are recommended for patients with critical illnesses are thought to also be effective for the coronavirus disease 2019 (COVID-19) patients in the intensive care unit. Some studies have recommended fresh fruits and vegetables, soy, nuts, and antioxidants, such as omega-3 fatty acids, to improve immune system activity. Although nutritional status is considered to be an important prognostic factor for patients with COVID-19, there is to date no sufficient evidence that optimal nutritional therapies can be beneficial for these patients. Some have argued that the COVID-19 pandemic is a good opportunity to test the effectiveness of nutritional intervention for infectious diseases. Many researchers have suggested that testing the proposed nutritional approaches for infectious diseases in the context of a pandemic would be highly informative. The authors of other review papers concluded that it is important to have a diet based on fresh foods, such as fruits, vegetables, whole grains, low-fat dairy products, and healthy fats (i.e., olive oil and fish oil), and to limit the intake of sugary drinks as well as high-calorie and high-salt foods. In this review, we discuss the clinical significance of functional food ingredients as complementary therapies potentially beneficial for the prevention or treatment of COVID-19. We believe that our review will be helpful to plan and deploy future studies to conclude these potentials against COVID-19, but also to new infectious diseases that may arise in the future.

Qualitative Differences in Attribution of Mental States to Other People in Autism and Schizophrenia: What are the Tools for Differential Diagnosis?

The differential diagnosis between schizophrenia spectrum disorders (SSD) and autism spectrum disorders (ASD) remains an important clinical question, because they have overlap in clinical diagnosis. This study explored the differences between ASD (n = 44) and SSD patients (n = 59), compared to typically developing peers (n = 63), in completing an advanced Theory of Mind (ToM) task. The outcome found several differences between groups. The SSD patients showed greater difficulty in understanding social scenarios, while ASD individuals understood the stories, but did not correctly identify the protagonist's intention. The interesting aspect of the results is that some ToM stories are more informative about the mentalistic reasoning of the two clinical groups, namely, the stories that investigate pretend, persuasion, double bluff and ironic joke constructs.

Associations between diet quality and DSM-IV mood disorders during young- to mid-adulthood among an Australian cohort

PURPOSE

Many studies have reported associations between diet and depression, but few have used formal diagnoses of mood disorder as the outcome measure. We examined if overall diet quality was associated cross-sectionally or longitudinally with DSM-IV mood disorders among an adult cohort.

METHODS

Participants from the Australian Childhood Determinants of Adult Health study were followed up during 2004-06 (n = 1974, age 26-36 years), 2009-11 (n = 1480, 31-41 years), and 2014-19 (n = 1191, 36-49 years). Dietary Guidelines Index (DGI) scores were calculated from food frequency questionnaires at each time-point (higher DGI reflects better diet quality). DSM-IV mood disorders (dysthymia or depression) during the periods between, and 12 months prior to each follow-up were determined using the Composite International Diagnostic Interview. Sex-stratified risk and prevalence ratios (PR) and 95% confidence intervals (CI) were estimated using log-binomial regression. Covariates included age, self-perceived social support index score, marital status, parenting status, education, occupation, physical activity, BMI, and usual sleep duration.

RESULTS

A 10-point higher DGI was cross-sectionally associated with lower prevalence of mood disorders at the third follow-up only (females PR = 0.73, 95% CI = 0.56, 0.95; males PR = 0.72, 95% CI = 0.53, 0.97), but was attenuated after covariate adjustment (females PR = 0.92, 95% CI = 0.73, 1.16; males PR = 0.92, 95% CI = 0.69, 1.22). Adjustment for social support in the final model had attenuated the association for both sexes from 18% reduced prevalence to 8%. DGI scores were not longitudinally associated with mood disorder risk.

CONCLUSIONS

Crude cross-sectional associations between diet quality and mood disorders at ages 36-49 years were explained by sociodemographic and lifestyle factors, particularly social support.

Sleep disorders and non-sleep circadian disorders predict depression: a systematic review and meta-analysis of longitudinal studies

Patients with depression often suffer from sleep disorders and non-sleep circadian disorders. However, whether they precede and predict subsequent depression is unclear. We conducted a meta-analysis of studies on sleep disorders and non-sleep circadian disorders. We found insomnia, hypersomnia, short and long sleep duration, obstructive sleep apnea, restless legs syndrome and eveningness orientation at baseline all led to subsequent depression. Those with propensity to late meal patterns, heightened levels of cortisol in awakening response and low robustness of rest-activity rhythm at baseline had higher risks for later depression. Among insomnia subtypes, difficulty initiating sleep and difficulty maintaining sleep predicted future depression. Notably, persistent insomnia at baseline contributed to more than two-fold risk of incident depression compared to insomnia. Moreover, insomnia symptom numbers showed dose-dependent relationship with the incident depression. In conclusion, different types of sleep disorders and non-sleep circadian disorders were proven to be risk factors of subsequent depression, and mechanisms underlying the relationship between sleep disorders, non-sleep circadian disorders and subsequent depression should be further elucidated in the future.

Sociodemographic and cultural determinants of mood disorders

PURPOSE OF REVIEW

The present review aims to examine, summarize and update information on the sociodemographic and cultural determinants of mood disorders.

RECENT FINDINGS

Known sociodemographic and cultural determinants continue to be good predictors of the risk of developing a mood disorder over the lifetime. Polygenic risk scores do not appear to offer any advantages over these determinants at present. There is also new and emerging understanding of the role of lifestyle and environmental factors in mediating vulnerability to mood disorder. The influence of ethnicity and migration, on the other hand, is far more complex than initially envisaged.

SUMMARY

Recent evidence on sociodemographic determinants of mood disorders confirms associations derived from existing literature. There is also new and emerging evidence on how quality of sleep, diet and the environment influence risk of mood disorders. Culture and ethnicity, depending on context, may contribute to both vulnerability and resilience. Socioeconomic deprivation may be the final common pathway through which several sociodemographic and cultural determinants of mood disorders act.

Skipping breakfast and mood: The role of sleep

BACKGROUND

Breakfast skipping has been related to poor mood, but the role of sleep in this relationship remains unclear.

AIM

To evaluate whether breakfast skipping associated with mood independently of sleep, and whether sleep interacted with breakfast skipping.

METHODS

During an in-person research visit, a sample of 329 adults completed questionnaires regarding last night's sleep, current morning breakfast intake, and mid-morning mood states. Sex-stratified linear regression models examined associations between breakfast skipping and mood and interactions with sleep.

RESULTS

Among males, those who did not consume breakfast had less vigor independent of sleep (β=-2.72 with 95% CI -4.91, -0.53). Among females, those who did not consume breakfast had higher feelings of anxiety (β=1.21 with 95% CI -0.04, 2.47). Interaction analyses revealed that males with longer time to fall asleep and longer night-time awake time had higher depression scores in the presence of breakfast skipping, and females with more night-time awake time and shorter duration had higher fatigue and less vigor if they were also breakfast skippers.

CONCLUSION

Breakfast skipping and poor sleep may jointly affect mood.

Meal Pattern Analysis in Nutritional Science: Recent Methods and Findings

There is a scarcity of dietary intake research focusing on the intake of whole meals rather than on the nutrients and foods of which those meals are composed. This growing area of research has recently begun to utilize advanced statistical techniques to manage the large number of variables and permutations associated with these complex meal patterns. The aim of this narrative review was to evaluate those techniques and the meal patterns they detect. The 10 observational studies identified used techniques such as principal components analysis, clustering, latent class analysis, and decision trees. They examined meal patterns under 3 categories: temporal patterns (relating to the timing and distribution of meals), content patterns (relating to combinations of foods within a meal and combinations of those meals over a day), and context patterns (relating to external elements of the meal, such as location, activities while eating, and the presence or absence of others). The most common temporal meal patterns were the 3 meals/d pattern, the skipped breakfast pattern, and a grazing pattern consisting of smaller but more frequent meals. The 3 meals/d pattern was associated with increased diet quality compared with the other 2 patterns. Studies identified between 7 and 12 content patterns with limited similarities between studies and no clear associations between the patterns and diet quality or health. One study simultaneously examined temporal and context meal patterns, finding limited associations with diet quality. No study simultaneously examined other combinations of meal patterns. Future research that further develops the statistical techniques required for meal pattern analysis is necessary to clarify the relations between meal patterns and diet quality and health.

Unexpectedly High Prevalence of Breakfast Skipping in Low Body-Weight Middle-Aged Men: Results of the Kanagawa Investigation of Total Checkup Data from the National Data Base-7 (KITCHEN-7)

Breakfast skipping (BS) has been considered to be associated with obesity, particularly among younger generations. However, few studies have addressed this issue in a middle-aged population considering sex and the conditions prior to breakfast. Therefore, we investigated clinical parameters, self-reported BS, late-night dinner (LND) eating, and late-night snacking (LNS) in ten body mass index (BMI) categories in a cross-sectional study of 892,578 non-diabetic people aged 40-74 years old who underwent a checkup. BS and LND were more prevalent in men (20.7% and 40.5%, respectively) than women (10.9% and 17.4%), whereas LNS was more prevalent in women (15.0%) than men (12.2%; all p < 0.0001). The overall prevalence of BS increased linearly with increasing BMI. However, when subjects were divided into men and women, the prevalence of BS showed a U-shaped relationship with BMI in men (n = 479,203). When male subjects were restricted to those in their 40s or those reporting LND, the prevalence of BS further increased, maintaining a U-shaped form. Logistic regression analysis also showed a U-shaped relationship in the adjusted odds ratios of BMI categories for BS in men and a J-shaped curve in women. In conclusion, our study revealed an unexpectedly high prevalence of BS in middle-aged low-body-weight men.

Impact of the COVID-19 Epidemic on Lifestyle Behaviors and Their Association With Subjective Well-Being Among the General Population in Mainland China: Cross-Sectional Study

Background

The world is experiencing an unprecedented challenge due to the coronavirus disease (COVID-19) pandemic. However, it is unclear whether people’s lifestyles will change as a result.

Objective

The aim of this study is to explore perceived lifestyle changes after the outbreak of COVID-19 and their association with subjective well-being (SWB) among the general population in Mainland China.

Methods

An online survey was conducted in May 2020. Lifestyle behaviors including leisure-time physical exercise, leisure-time screen time, and dietary intake were self-reported. SWB was measured using the General Wellbeing Schedule (GWS). Other covariates including sociodemographic factors, self-rated physical health, perceived social support, and loneliness were also assessed by a structured questionnaire. A multivariate ordinal regression method was used to analyze the association between SWB and lifestyle behaviors as well as perceived lifestyle changes.

Results

A total of 1033 participants aged between 18 and 60 years were included in this study. The mean GWS score was 71.7 points. About 70% of the respondents reported spending more time looking at screens, whereas about 30% reported an increased frequency of vegetable and fruit intake after the outbreak of COVID-19. Inactive physical exercise (odds ratio [OR] 1.16, 95% CI 1.02-1.48), infrequent vegetable intake (OR 1.45, 95% CI 1.10-1.90), infrequent fruit intake (OR 1.31, 95% CI 1.01-1.70), and often skipping breakfast (OR 1.43, 95% CI 1.08-1.91) were associated with lower SWB after adjusting for sociodemographic factors, self-rated physical health, perceived social support, and loneliness. Moreover, participants who perceived a decrease in the frequency of vegetable, fruit, and breakfast intake were more likely to report lower SWB.

Conclusions

The COVID-19 pandemic may have positive and negative impacts on different aspects of lifestyle behaviors. Both unhealthy lifestyle behaviors and negative lifestyle changes were associated with lower SWB. These findings provide scientific evidence that can inform lifestyle guidelines and public mental health interventions during the COVID-19 outbreak.