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.

Loneliness is increasingly recognised as a serious public health issue worldwide. However, there is scarce research addressing the association between loneliness and suicide in older adults in rural China. We set out to examine loneliness and other psychosocial factors in elderly suicide cases and explore their interaction effects.

Using a 1 : 1 matched case–control design, data were collected from 242 elderly suicide cases and 242 living community controls by psychological autopsy method in rural China, including demographic characteristics, loneliness, depression, hopelessness and social support. The chi-square automatic interaction detection (CHAID) tree model and multivariable logistic regression analysis were used to explore the relationships of these factors and suicide.

The CHAID tree model showed that loneliness, hopelessness and depressive symptoms were closely associated with completed suicide and that loneliness and hopelessness interacted with each other. The result of multivariable logistic regression showed that individuals who were unemployed [odds ratio (OR) = 2.344; 95% confidence interval (CI): 1.233–4.457], living alone (OR = 2.176; 95% CI: 1.113–4.254), had lower levels of subjective social support (OR = 2.185; 95% CI: 1.243–3.843), experienced depressive symptoms (OR = 6.700; 95% CI: 3.405–13.182), showed higher levels of hopelessness (OR = 7.253; 95% CI: 3.764–13.974) and felt higher levels of hopelessness × higher levels of loneliness (OR = 2.446; 95% CI: 1.089–5.492) were significantly associated with an elevated suicide risk in older people in rural China.

Regular evaluation of loneliness, hopelessness and depression can help detect older adults who are at risk of committing suicide. Interventions should target social support systems, particularly among people living alone, to alleviate feelings of loneliness and hopelessness. Treating depression is also key to preventing suicide among elderly people in rural China.

Older adults represent the segment of population most exposed to the risk of suicide nearly everywhere in the world. Previous studies showed that hopelessness was an important risk factor for suicide.

This study aimed to evaluate the reliability and validity of the four-item Beck Hopelessness Scale (BHS-4) in psychological autopsy study among Chinese rural elderly.

Two-stage stratified cluster sampling method was used to select research sites. Using case-control psychological autopsy study, face-to-face interviews were conducted to collected information.

A total of 242 elderly suicide deaths and 242 matched living comparisons were investigated, including 135 males and 107 females for each group. Intraclass Correlation Coefficients (ICC) of the controls were 0.682-0.713. The median score of BHS-4 among suicides was significantly higher than that among controls. The corrected correlation coefficient between items and total score were 0.184-0.723. Cronbach’s Alphas coefficient was 0.834. Only one common factor was precipitated by exploratory factor analysis and the cumulative variance contribution rates were 59.558% for suicides and 52.722% for living controls. The correlation coefficient between hopelessness and depression were 0.481 among suicide death and 0.617 among living controls.

The information provided by the informants through psychological autopsy method had high reliability to reflect the actual situation of suicides and controls. BHS-4 has good reliability and validity among Chinese rural elderly suicides. It is suitable for psychological autopsy study among Chinese rural elderly.

Suicide rate among rural elderly is the highest among all age groups in China, yet little is known about the suicide risks in this rapidly growing vulnerable population.

This matched case–control psychological autopsy study was conducted during June 2014 to September 2015. Consecutive samples of suicides aged 60 or above were identified in three provinces (Shandong, Hunan, and Guangxi) in China. Living comparisons were 1:1 matched with the suicides in age (±3 years old), gender, and living location. Risk factors included demographic characteristics, being left-behind, mental disorder, depressive symptoms, stressful life events, and social support.

A total of 242 suicides and 242 comparisons were enrolled: 135 (55.8%) were male, mean (s.d.) age was 74 (8) years. The most frequently used suicide means were pesticides (125, 51.7%) and hanging (95, 39.3%). Independent risks of suicide included unstable marital status [odds ratio (OR) 4.19, 95% confidence interval (CI) 1.61–10.92], unemployed (compared with employed, OR 4.43, 95% CI 1.09–17.95), depressive symptoms (OR 1.34, 95% CI 1.21–1.48), and mental disorder (OR 6.28, 95% CI 1.75–22.54). Structural equation model indicated that the association between being left-behind and suicide was mediated by mental disorder, depressive symptoms, stressful life events, and social support.

Unstable marital status, unemployed, depressive symptoms, and mental disorder are independent risk factors for suicide in rural elderly. Being left-behind can elevate the suicide risk through increasing life stresses, depressive symptoms, mental disorder, and decreasing social support. Elderly suicide may be prevented by restricting pesticides, training rural physicians, treating mental disorders, mitigating life stress, and enhancing social connection.