Despite growing awareness of the mental health damage caused by air pollution, the epidemiologic evidence on impact of air pollutants on major mental disorders (MDs) remains limited. We aim to explore the impact of various air pollutants on the risk of major MD.

This prospective study analyzed data from 170 369 participants without depression, anxiety, bipolar disorder, and schizophrenia at baseline. The concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), particulate matter with aerodynamic diameter > 2.5 μm, and ≤ 10 μm (PM2.5–10), nitrogen dioxide (NO2), and nitric oxide (NO) were estimated using land-use regression models. The association between air pollutants and incident MD was investigated by Cox proportional hazard model.

During a median follow-up of 10.6 years, 9 004 participants developed MD. Exposure to air pollution in the highest quartile significantly increased the risk of MD compared with the lowest quartile: PM2.5 (hazard ratio [HR]: 1.16, 95% CI: 1.09–1.23), NO2 (HR: 1.12, 95% CI: 1.05–1.19), and NO (HR: 1.10, 95% CI: 1.03–1.17). Subgroup analysis showed that participants with lower income were more likely to experience MD when exposed to air pollution. We also observed joint effects of socioeconomic status or genetic risk with air pollution on the MD risk. For instance, the HR of individuals with the highest genetic risk and highest quartiles of PM2.5 was 1.63 (95% CI: 1.46–1.81) compared to those with the lowest genetic risk and lowest quartiles of PM2.5.

Our findings highlight the importance of air pollution control in alleviating the burden of MD.

This study aims to gain insight into each attribute as presented in the value of implantable medical devices, quantify attributes’ strength and their relative importance, and identify the determinants of stakeholders’ preferences.

A mixed-methods design was used to identify attributes and levels reflecting stakeholders’ preference toward the value of implantable medical devices. This design combined literature reviewing, expert’s consultation, one-on-one interactions with stakeholders, and a pilot testing. Based on the design, six attributes and their levels were settled. Among 144 hypothetical profiles, 30 optimal choice sets were developed, and healthcare professionals (decision-makers, health technology assessment experts, hospital administrators, medical doctors) and patients as stakeholders in China were surveyed. A total of 134 respondents participated in the survey. Results were analyzed by mixed logit model and conditional logit model.

The results of the mixed logit model showed that all the six attributes had a significant impact on respondents’ choices on implantable medical devices. Respondents were willing to pay the highest for medical devices that provided improvements in clinical safety, followed by increased clinical effectiveness, technology for treating severe diseases, improved implement capacity, and innovative technology (without substitutes).

The findings of DCE will improve the current evaluation on the value of implantable medical devices in China and provide decision-makers with the relative importance of the criteria in pricing and reimbursement decision-making of implantable medical devices.

Depression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).

The GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.

Two genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10−8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10−8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (preplication GWAS1 = 0.02, preplication GWAS2 = 2.71 × 10−3) in CFAP61, and rs11661122 (preplication GWAS1 = 8.16 × 10−3, preplication GWAS2 = 8.08 × 10−3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).

Our findings provide novel clues for understanding of the complex genetic architecture of depression.

Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety.

Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software.

We observed 51 common diet–gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10−4, Pdepression status = 5.86 × 10−4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet–gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10−3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10−4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB).

Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits–gut microbiome interactions with depression and anxiety.

The current study evaluated the associations between different forms and sources of Fe and breast cancer risk in Southern Chinese women.

Case–control study. We collected data on the consumption of Fe from different forms and food sources by using a validated FFQ. Multivariable logistic regression and restricted cubic spline (RCS) analysis was used to reveal potential associations between Fe intake and breast cancer risk.

A case-control study of women at three major hospitals in Guangzhou, China.

From June 2007 to March 2019, 1591 breast cancer cases and 1622 age-matched controls were recruited.

In quartile analyses, Fe from plants and Fe from white meat intake were inversely associated with breast cancer risk, with OR of 0·65 (95 % CI 0·47, 0·89, Ptrend = 0·006) and 0·76 (95 % CI 0·61, 0·96, Ptrend = 0·014), respectively, comparing the highest with the lowest quartile. No associations were observed between total dietary Fe, heme or non-heme Fe, Fe from meat or red meat and breast cancer risk. RCS analysis demonstrated J-shaped associations between total dietary Fe, non-heme Fe and breast cancer, and reverse L-shaped associations between heme Fe, Fe from meat and Fe from red meat and breast cancer.

Fe from plants and white meat were inversely associated with breast cancer risk. Significant non-linear J-shaped associations were found between total dietary Fe, non-heme Fe and breast cancer risk, and reverse L-shaped associations were found between heme Fe, Fe from meat or red meat and breast cancer risk.

This study aimed to explore the impacts of COVID-19 outbreak on mental health status in general population in different affected areas in China.

This was a comparative study including two groups of participants: (1) general population in an online survey in Ya'an and Jingzhou cities during the COVID-19 outbreak from 10–20 February 2020; and (2) matching general population selected from the mental health survey in Ya'an in 2019 (from January to May 2019). General Health Questionnaire (GHQ-12), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS) were used.

There were 1775 participants (Ya'an in 2019 and 2020: 537 respectively; Jingzhou in 2020: 701). Participants in Ya'an had a significantly higher rate of general health problems (GHQ scores ⩾3) in 2020 (14.7%) than in 2019 (5.2%) (p < 0.001). Compared with Ya'an (8.0%), participants in Jingzhou in 2020 had a significantly higher rate of anxiety (SAS scores ⩾50, 24.1%) (p < 0.001). Participants in Ya'an in 2020 had a significantly higher rate of depression (SDS scores ⩾53, 55.3%) than in Jingzhou (16.3%) (p < 0.001). The risk factors of anxiety symptoms included female, number of family members (⩾6 persons), and frequent outdoor activities. The risk factors of depression symptoms included participants in Ya'an and uptake self-protective measures.

The prevalence of psychological symptoms has increased sharply in general population during the COVID-19 outbreak. People in COVID-19 severely affected areas may have higher scores of GHQ and anxiety symptoms. Culture-specific and individual-based psychosocial interventions should be developed for those in need during the COVID-19 outbreak.

Birth weight influences not only brain development, but also mental health outcomes, including depression, but the underlying mechanism is unclear.

The phenotypic data of 12,872–91,009 participants (59.18–63.38% women) from UK Biobank were included to test the associations between the birth weight, depression, and brain volumes through the linear and logistic regression models. As birth weight is highly heritable, the polygenic risk scores (PRSs) of birth weight were calculated from the UK Biobank cohort (154,539 participants, 56.90% women) to estimate the effect of birth weight-related genetic variation on the development of depression and brain volumes. Finally, the mediation analyses of step approach and mediation analysis were used to estimate the role of brain volumes in the association between birth weight and depression. All analyses were conducted sex stratified to assess sex-specific role in the associations.

We observed associations between birth weight and depression (odds ratio [OR] = 0.968, 95% confidence interval [CI] = 0.957–0.979, p = 2.29 × 10−6). Positive associations were observed between birth weight and brain volumes, such as gray matter (B = 0.131, p = 3.51 × 10−74) and white matter (B = 0.129, p = 1.67 × 10−74). Depression was also associated with brain volume, such as left thalamus (OR = 0.891, 95% CI = 0.850–0.933, p = 4.46 × 10−5) and right thalamus (OR = 0.884, 95% CI = 0.841–0.928, p = 2.67 × 10−5). Additionally, significant mediation effects of brain volume were found for the associations between birth weight and depression through steps approach and mediation analysis, such as gray matter (B = –0.220, p = 0.020) and right thalamus (B = –0.207, p = 0.014).

Our results showed the associations among birth weight, depression, and brain volumes, and the mediation effect of brain volumes also provide evidence for the sex-specific of associations.

The effect of dietary vitamin D, calcium and dairy products intake on colorectal cancer risk is controversial. This study aims to investigate the associations between dietary vitamin D, calcium, dairy products intake and colorectal cancer risk among Chinese population.

During July 2010 to December 2018, 2380 incident, first primary, histologically confirmed colorectal cancer cases and 2389 sex and age-matched (5-year interval) controls were recruited. Dietary intake information was collected by face-to-face interviews using a validated food frequency questionnaire. Energy and other nutrient intakes such as dietary calcium were computed on the basis of the 2002 Chinese Food Composition Table, and the dietary vitamin D intake was calculated according to the United States Department of Agriculture Food Composition Database. Unconditional multivariable logistic regression models were used to calculate the odds ratios (ORs) and 95% confidence interval (CI) after adjusting for various confounders, including socio-demographic characteristics, lifestyle factors, BMI, family history of cancer, energy intake and several nutrient intakes.

The energy-adjusted mean dietary vitamin D, calcium and total dairy products intakes were 5.69μg/d, 406.94mg/d, 4.02g/d for cases and 6.81μg/d, 468.21mg/d, 9.50g/d for controls. Compared with the controls, cases had a lower intake of dietary vitamin D, calcium and total dairy (P < 0.001). A higher intake of dietary vitamin D and calcium was found to be associated with 43% and 51% reduction in colorectal cancer. The ORs of the highest quartile compared with the lowest quartile intake were 0.57 (95% CI: 0.46, 0.70, Ptrend < 0.001) for dietary vitamin D and 0.49 (95% CI: 0.39, 0.61, Ptrend < 0.001) for dietary calcium. We observed a statistically significant inverse association of dairy products intake with colorectal cancer risk. Compared with the lowest tertile, the adjusted ORs for the highest tertile were 0.31 (95% CI: 0.26, 0.38, Ptrend < 0.001) for total dairy. The inverse associations of dietary vitamin D, calcium and dairy products intakes with colorectal cancer risk were observed in both men and women, colon and rectal cancer.

Our study indicated that higher dietary vitamin D, calcium and dairy products intakes were associated with a lower colorectal cancer risk.

As an emerging infectious disease, COVID-19 has involved many countries and regions. With the further development of the epidemic, the proportion of clusters has increased.

In our study, we collected information on COVID-19 clusters in Qingdao City. The epidemiological characteristics and clinical manifestations were analyzed.

Eleven clusters of COVID-19 were reported in Qingdao City between January 29, and February 23, 2020, involving 44 confirmed cases, which accounted for 73.33% of all confirmed cases. From January 19 to February 2, 2020, the cases mainly concentrated in the district that had many designated hospitals. Patients aged 20-59 y old accounted for the largest proportion (68.18%) of cases; the male-to-female sex ratio was 0.52:1. Three cases were infected from exposure to confirmed cases. The average incubation period was 6.28 d. The median number of cases per cluster was 4, and the median duration time was 6 d. The median cumulative number of exposed persons was 53.

More attention should be paid to the epidemic of clusters in prevention and control of COVID-19. In addition to isolating patients, it is essential to track, screen, and isolate those who have come in close contact with patients. Self-isolation is the key especially for healthy people in the epidemic area.