Despite mounting evidence linking neurological diseases with climate change, the link between autism spectrum disorder (ASD) and global warming has yet to be explored.

To examine the relationship between the incidence of ASD and global warming from 1990 to 2019 and estimate the trajectory of ASD incidence from 2020 to 2100 globally.

We extracted meteorological data from TerraClimate between 1990 and 2019. To estimate the association between global ASD incidence and temperature variation, we adopted a two-stage analysis strategy using a generalised additive regression model. Additionally, we projected future ASD incidence under four representative shared socioeconomic pathways (SSPs: 126, 245, 370 and 585) by bootstrapping.

Between 1990 and 2019, the global mean incidence of ASD in children under 5 years old was 96.9 per 100 000. The incidence was higher in males (147.5) than in females (46.3). A 1.0 °C increase in the temperature variation was associated with a 3.0% increased risk of ASD incidence. The association was stronger in boys and children living in a low/low-middle sociodemographic index region, as well as in low-latitude areas. According to the SSP585 scenario, by 2100, the children living in regions between 10 and 20° latitude, particularly in Africa, will experience a 68.6% increase in ASD incidence if the association remains. However, the SSP126 scenario is expected to mitigate this increase, with a less than 10% increase in incidence across all latitudes.

Our study highlights the association between climate change and ASD incidence worldwide. Prospective studies are warranted to confirm the association.

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

With the rapid development of higher education in China and the continuous expansion of enrollment in universities, the number of college graduates is rapidly increasing, and the employment situation is severe. Employment anxiety among college students not only affects their physical and mental health but also leads to difficulties in finding employment and social problems. In response to this situation, we aim to alleviate the employment anxiety of college students from the perspective of the development of innovation and entrepreneurship education.

Taking college students as the research object, a cross-sectional questionnaire survey method was used to explore the impact and mechanism of innovation and entrepreneurship education development on employment anxiety. The development of innovation and entrepreneurship education intervenes with high employment anxiety among college students and tests its effectiveness.

The overall employment anxiety of college students is at a moderate to high level, with a mean of 2.66 and a standard deviation of 0.63. The employment anxiety of students after innovation and entrepreneurship education was significantly lower than before intervention, P<0.001. The employment anxiety value of the post-test intervention group was significantly lower than that of the control group, with F=12.046, P<0.001.

Interventions in innovation and entrepreneurship education have a significant effect on alleviating employment anxiety among college students, and this effect can be maintained within a month.

Many studies suggest that both psychotherapy and drug therapy are effective in the treatment of bipolar disorders (BDs). However, the pathophysiology of both types of intervention has not been established definitively.

An activation likelihood estimation meta-analysis was performed to identify the distinct brain activity alterations between psychotherapy and drug therapy for the treatment of BDs. Articles were identified by searching databases including PubMed, Embase, Cochrane Library, and Web of Science databases. Eligible studies on BDs were published up until 10 June 2021.

21 studies were included and we conducted a meta-analysis for different therapies and imaging tasks. After receiving psychotherapy, BD patients showed increased activation in the inferior frontal gyrus (IFG) and superior temporal gyrus. While after taking drug therapy, BD patients displayed increased activation in the anterior cingulate cortex, medial frontal gyrus, IFG, and decreased activation in the posterior cingulate cortex. The regions of brain activity changes caused by psychotherapy were mostly focused on the frontal areas, while drug therapy mainly impacted on the limbic areas. Different type of tasks also affected brain regions which were activated.

Our comprehensive meta-analysis indicates that these two treatments might have effect on BD in their own therapeutic modes. Psychotherapy might have a top-down effect, while drug therapy might have a bottom-up effect. This study may contribute to differential diagnosis of BDs and would be helpful to finding more accurate neuroimaging biomarkers for BD treatment.

T long-term effects of cognitive therapy and behavior therapy (CTBT) for menopausal symptoms are unknown, and whether the effects are different between natural menopause and treatment-induced menopause are currently unclear. Therefore, we sought to conduct an accurate estimate of the efficacy of CTBT for menopausal symptoms.

We conducted searches of Cochrane Library, EMBASE, PsycINFO, PubMed, and Web of Science databases for studies from 1 January 1977 to 1 November 2021. Randomized controlled trials (RCTs) comparing intervention groups to control groups for menopausal symptoms were included. Hedge's g was used as the standardized between-group effect size with a random-effects model.

We included 14 RCTs comprising 1618 patients with a mean sample size of 116. CTBT significantly outperformed control groups in terms of reducing hot flushes [g = 0.39, 95% confidence interval (CI) 0.23–0.55, I2 = 45], night sweats, depression (g = 0.50, 95% CI 0.34–0.66, I2 = 51), anxiety (g = 0.38, 95% CI 0.23–0.54, I2 = 49), fatigue, and quality of life. Egger's test indicated no publication bias.

CTBT is an effective psychological treatment for menopausal symptoms, with predominantly small to moderate effects. The efficacy is sustained long-term, although it declines somewhat over time. The efficacy was stronger for natural menopause symptoms, such as vasomotor symptoms, than for treatment-induced menopause symptoms. These findings provide support for treatment guidelines recommending CTBT as a treatment option for menopausal symptoms.

To determine which set of BMI cut-offs is the most appropriate to define child and adolescent obesity in urban China.

A cross-sectional study was carried out between 1 November and 31 December in 2017.

Community Healthcare Center in Minhang District, Shanghai, China.

A total of 12 426 children and adolescents aged 7–17 years were selected by cluster random sampling. Bioelectrical impedance analysis was the gold standard to measure body composition.

Comparisons of three sets of BMI cut-offs by sensitivity and κ value revealed that the Working Group on Obesity in China (WGOC) (sensitivity 39·9–84·0 %; κ 0·51–0·79) and WHO (sensitivity 25·5–74·5 %; κ 0·35–0·78) cut-offs were not superior to the International Obesity Task Force (IOTF) (sensitivity 47·9–92·4 %; κ 0·58–0·85) cut-offs across all subgroups. The WGOC and WHO cut-offs yielded higher misclassification rates, in the worst case, categorising 11·2 % of girls with high adiposity as normal and 44·4 % of them as overweight, while the IOTF cut-offs categorised 2·3 % as normal and 30·7 % as overweight. Individuals who were classified by the IOTF cut-offs as overweight had the lowest ratios of high adiposity (4·2–41·6 %) than by the BMI cut-offs for each subgroup. Among pubertal girls, none of the BMI-based cut-offs indicated excellent agreement with body fat percentage, and κ value of the WHO cut-offs (0·35 (95 % CI 0·29, 0·41)) was lower than the other two sets of BMI cut-offs (all P < 0·001).

The IOTF cut-offs for Asian should be recommended for child obesity screening in urban China. Pubertal individuals need a more accurate indicator of obesity screening.

Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.

The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.

We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.

Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.

The present study investigated the association between dietary patterns and hypertension applying the Chinese Dietary Balance Index-07 (DBI-07).

A cross-sectional study on adult nutrition and chronic disease in Inner Mongolia. Dietary data were collected using 24 h recall over three consecutive days and weighing method. Dietary patterns were identified using principal components analysis. Generalized linear models and multivariate logistic regression models were used to examine the associations between DBI-07 and dietary patterns, and between dietary patterns and hypertension.

Inner Mongolia (n 1861).

A representative sample of adults aged ≥18 years in Inner Mongolia.

Four major dietary patterns were identified: ‘high protein’, ‘traditional northern’, ‘modern’ and ‘condiments’. Generalized linear models showed higher factor scores in the ‘high protein’ pattern were associated with lower DBI-07 (βLBS = −1·993, βHBS = −0·206, βDQD = −2·199; all P < 0·001); the opposite in the ‘condiments’ pattern (βLBS = 0·967, βHBS = 0·751, βDQD = 1·718; all P < 0·001). OR for hypertension in the highest quartile of the ‘high protein’ pattern compared with the lowest was 0·374 (95 % CI 0·244, 0·573; Ptrend < 0·001) in males. OR for hypertension in the ‘condiments’ pattern was 1·663 (95 % CI 1·113, 2·483; Ptrend < 0·001) in males, 1·788 (95 % CI 1·155, 2·766; Ptrend < 0·001) in females.

Our findings suggested a higher-quality dietary pattern evaluated by DBI-07 was related to decreased risk for hypertension, whereas a lower-quality dietary pattern was related to increased risk for hypertension in Inner Mongolia.

To revise an abbreviated version of the Silhouettes subtest of the Visual Object and Space Perception (VOSP) battery in order to recognize mild cognitive impairment (MCI) and determine the optimal cutoffs to differentiate among cognitively normal controls (NC), MCI, and Alzheimer’s Disease (AD) in the Chinese elderly.

A cross-sectional validation study.

Huashan Hospital, Shanghai, China.

A total of 591 participants: Individuals with MCI (n = 211), AD (n = 139) and NC (n = 241) were recruited from the Memory Clinic, Huashan Hospital, Shanghai, China.

Baseline neuropsychological battery (including VOSP) scores were collected from firsthand data. An abbreviated version of silhouettes test (Silhouettes-A) was revised from the original English version more suitable for the elderly, including eight silhouettes of animals and seven silhouettes of inanimate objects, with a score ranging from 0 to 15.

Silhouettes-A was an effective test to screen MCI in the Chinese elderly with good sensitivity and specificity, similar to the Montreal cognitive assessment and superior to other single tests reflecting language, spatial, or executive function. However, it had no advantage in distinguishing MCI from AD. The corresponding optimal cutoff scores of Silhouettes-A were 10 for screening MCI and 8 for AD.

Silhouettes-A is a quick, simple, sensitive, and dependable cognitive test to distinguish among NC, MCI, and AD patients.