Abstract
Background
Household solid fuel use is associated with a higher risk of a wide spectrum of health disorders. However, the sex-specific relationship between solid fuel use and incident stroke in older Chinese adults, as well as the potential mediating role of depressive symptoms, remains insufficiently explored.
Methods
This longitudinal study used data from the China Health and Retirement Longitudinal Study (CHARLS), including 13,928 Chinese participants aged 45 years or older who were free of stroke at baseline. Logistic regression models were used to assess the relationship between solid fuel use, depressive symptoms, and the risk of incident stroke. Mediation analyses were performed to quantify the potential mediation role of depressive symptoms in the association. All analyses were stratified by sex to assess sex-specific susceptibility.
Results
Of the 13,928 adults (mean age of 58, 47.26% male), 917 (6.58%) participants documented the incident stroke. Solid fuel use was significantly associated with a higher risk of incident stroke in the total population (OR = 1.26, 95% CI: 1.06–1.49) and female populations (OR = 1.39, 95% 1.09–1.77) in the fully adjusted model. In addition, depressive symptoms may partially mediate up to15.7% of the association between solid fuel use and incident stroke, and this finding was consistent whether depressive symptoms were defined as general depression or severe depression. The results of the stratified analysis also indicate that this mediating effect is present only among the female group.
Conclusion
Household solid fuel use was significantly associated with a higher risk of incident stroke, and depressive symptoms played a mediating role in the relationship. These findings highlight the need for integrated public health interventions in the areas of environmental pollution and mental health, with particular attention to women.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-026-26863-x.
Keywords: Household solid fuel use, Incident stroke, Depressive symptoms, Mediating effect, Cohort study
Introduction
Stroke remains a leading cause of disability and death among adults globally [1]. Despite substantial improvements in the management of traditional risk factors such as hypertension, diabetes, and smoking, the global incidence and mortality of stroke have not been effectively curbed [2, 3]. In China, the prevalence of stroke reached 26 million in 2021, marking a 104.26% increase compared to 1990 [4]. Moreover, studies have shown that women bear a significantly greater burden of stroke, characterized by higher incidence, disability, and mortality rates [5–7]. With population ageing and shifting risk profiles, identifying modifiable environmental factors and clarifying the potential sex-specific differences in susceptibility have become key priorities for stroke prevention.
Household solid fuels (e.g., coal and biomass) remain widely used in rural areas of low- and middle-income countries and persist in economically disadvantaged regions of China despite increasing access to clean energy [8]. Incomplete combustion generates high levels of household air pollutants, including PM₂․₅/PM₁₀, CO, nitrogen oxides, and polycyclic aromatic hydrocarbons, which accumulate indoors [9, 10]. Through pathways involving systemic inflammation, oxidative stress, endothelial dysfunction, and pro-thrombotic responses, exposure to these pollutants may plausibly contribute to cerebrovascular injury [11, 12]. Consistently, solid-fuel use has been associated with adverse cardiovascular outcomes, whereas switching to cleaner household energy sources is linked to a more favorable cardiovascular risk profile [13]. Because women often spend more time cooking and performing domestic activities, they may experience higher exposure than men [14], raising the possibility of sex-specific effects on stroke risk. However, to date, few studies have examined the sex-specific association between indoor fuel use and new-onset stroke in the Chinese elderly population, nor have they explored potential explanatory factors.
Depressive symptoms are common in later life and are more prevalent among women [15–17], which may contribute to sex differences in stroke risk. Evidence suggests that both ambient and household air pollution exposures are associated with increased risks of depression and related psychiatric outcomes [18, 19], potentially through neuroinflammation, oxidative stress, and dysregulated neurotransmitter and neuromodulatory processes [20]. Meanwhile, depressive symptoms have been associated with a higher risk of incident stroke [21], possibly via adverse health behaviors and cardiometabolic dysregulation [22–25]. Therefore, depressive symptoms may serve as a potential mediator in the association between solid fuel use and stroke.
To address these gaps, we used longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) to prospectively examine the association between household solid fuel use and incident stroke in middle-aged and older Chinese adults. We also quantified the potential mediating role of depressive symptoms in this relationship and explored possible sex differences. This work may provide new insights into how environmental factors influence stroke risk through mental health, help identify particularly vulnerable subgroups, and inform the integration of pollution reduction and sex-sensitive mental health interventions into stroke prevention strategies.
Methods
Data source and study design
This study used data from the CHARLS, a nationally representative survey collecting high-quality longitudinal information on Chinese households and individuals. Data were obtained through face-to-face interviews supported by an integrated information system. The survey encompassed demographics, health status, healthcare access, insurance coverage, family structure, and health-related behaviors. The baseline survey (2011–2012) included 17,708 participants from 150 counties across 28 provinces, followed by biennial waves from 2013 to 2018. All data are publicly available on the CHARLS website (http://charls.pku.edu.cn/). Ethical approval was granted by the Peking University Biomedical Ethics Committee (IRB00001052–11015), and written informed consent was obtained from all participants. This study is a prospective cohort analysis using data from CHARLS from 2011 to 2018. Figure 1A shows the screening flowchart for the study sample. Among the original cohort of 17,708 participants from the 2011–2012 baseline survey, the following exclusion criteria were applied: (1) missing data on household solid fuel use (n = 243); (2) age < 45 years (n = 759); (3) missing data on depressive symptoms (n = 1409); (4) prevalent stroke at baseline (n = 487); and (5) withdrawn from the study (n = 882). Finally, a total of 13,928 eligible participants were included in the final analysis.
Fig. 1.
Study profile and hypothesized pathways. A Flowchart of the selection of study participants from CHARLS. B Hypothesized direct and indirect pathways linking solid fuel use to incident stroke through depressive symptoms. The total effect is decomposed into a natural direct effect (NDE, solid fuel use → stroke) and a natural indirect effect (NIE, solid fuel use → depression → stroke). All models were adjusted for age, sex, marital status, place of residence, household income, education level, smoking, alcohol consumption, body mass index, and history of hypertension, diabetes, and heart disease. NDE, natural direct effect; NIE, natural indirect effect
Assessment of incident stroke events
Incident stroke events were ascertained using longitudinal data from three follow-up waves (2013, 2015, and 2018) of the CHARLS. Stroke status was determined based on two standardized criteria: (1) self-reported physician-diagnosed stroke, assessed by the question “Have you ever been diagnosed with stroke by a doctor?”, and (2) self-reported use of stroke-related treatments, assessed by the question “Are you currently receiving any treatment (traditional Chinese medicine/Western medicine/physical therapy/acupuncture and moxibustion/occupational therapy) to control your stroke?”. Participants were classified as having an incident stroke if they newly reported either a physician diagnosis of stroke or initiation of stroke-related medication.
Assessment of depressive symptoms
Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CESD-10), a validated tool commonly applied to identify depressive status. Participants reported the frequency of depressive feelings during the past week on a 4-point scale: ‘rarely or none of the time (< 1 day)’, ‘some or a little of the time (1–2 days)’, ‘occasionally or a moderate amount of time (3–4 days)’, and ‘most or all of the time (5–7 days)’. Each item was scored from 0 to 3, yielding a total score between 0 and 30, where higher scores represent greater depressive symptom severity. A cut-off point of 10 was defined as depressive symptoms [26], and scores of 20 were classified as severe depressive symptoms.
Solid fuel use measurements
In the baseline survey, participants reported their households’ main energy sources for cooking and heating. According to self-reported data, crop residues, wood, and coal were categorized as solid fuels, whereas electricity, liquefied petroleum gas, natural gas, marsh gas, and solar energy were considered clean fuels due to their lower emissions of pollutants. Households using solid fuels for either cooking or heating were defined as the exposure group, while those relying exclusively on clean fuels for both purposes were classified as the clean-fuel group.
Covariates
Covariates considered in this study included sociodemographic factors (age, sex, marital status, education level, household income, and residential area), health-related behaviors (smoking and alcohol consumption), body mass index (BMI), and major comorbidities. The residential area was classified as urban or rural (based on the PSU information defined by the National Bureau of Statistics of the People’s Republic of China), and marital status as married or unmarried. Education was grouped into three levels: below lower secondary, upper secondary or vocational training, and tertiary education. Household income (10000 CNY/year) is the sum of all income at the household level, including income from earnings, capital income, pension income, income from government transfers, other income, and the total income from other household members. Smoking status was categorized as current, former, or never smoker, and alcohol consumption was defined as drinking alcohol within the past year. BMI (kg/m²) was calculated as weight divided by height squared and categorized as < 18.5, 18.5–24.9, 25.0–29.9, and ≥ 30. Physician-diagnosed comorbidities were self-reported and included hypertension, diabetes, and heart disease. Details on missing values and covariate proportions are provided in Table S1.
Statistical analysis
For study participant characteristics, we evaluated the normality of continuous variables using the Shapiro–Wilk test, and then we used median (P25–P75) to describe continuous variables and frequency (percentage) to describe categorical variables. The Wilcoxon rank-sum test (continuous data) and chi-square test (categorical data) were performed to make comparisons between two groups.
Multivariate logistic regression models were fitted to investigate the total and sex-specific associations of solid fuel use with incident stroke, depressive symptoms with incident stroke, and solid fuel use with depressive symptoms. All results were presented as ORs and 95% confidence intervals (CIs). The basic model (model 1) was adjusted for age, sex, marital status, place of residence, education level, and household income; while model 2 additionally adjusted for smoking, alcohol consumption, body mass index, history of hypertension, diabetes, and heart disease. The potential interaction of sex with solid fuel use was computed by fitting the interaction term to the model using likelihood ratio tests.
Mediation analysis was used to explore the potential mediating role of depressive symptoms on the association between solid fuel use and incident stroke. Estimates and 95% confidence intervals (95% CI) were then calculated for each pathway using the ‘mediation’ R package. Briefly, we decomposed the total effect of solid fuel use on incident stroke into (i) a direct effect of solid fuel use on incident stroke and (ii) an indirect effect mediated through depressive symptoms (solid fuel use → depressive symptoms → incident stroke). A schematic representation of the mediation analysis hypothesis is shown below (Fig. 1B). The term “effects” is adopted as standard mediation terminology and should not be interpreted as evidence of causality in this study. Reverse causal associations can be largely avoided due to the clear temporal sequence between exposure, mediator, and outcome in this study. To assess the mediating role of depressive symptoms in the association between solid fuel use and incident stroke, we conducted a mediation analysis. We estimated the total effect, the direct effect, and the indirect effect through depressive symptoms, and quantified the mediation proportion. The adjustment variables for the model 2 were kept as above.
To validate the robustness of the results, we conducted several sensitivity analyses. First, to account for potential bias introduced by missing data, we excluded participants with missing covariate values (less than 20%) and repeated the association analyses. Second, to reduce the reverse causality association, we excluded the stroke cases diagnosed within the preceding two years. Third, considering the applicability of the research findings, we repeated the primary analysis using a weighted regression approach. Finally, to strengthen causal inference in the mediation analyses, we performed a sensitivity analysis employing a ‘lagged mediator’—depressive symptoms measured in 2013, two years post-baseline, and then repeated the mediation analyses.
Statistical analyses were performed using SAS version 9.4 (SAS Institute; https://www.sas.com) and R software (version 4.4.3; https://www.r-project.org). All statistical tests were two-sided, and P < 0.05 was considered statistically significant.
Results
Table 1 summarizes the baseline characteristics of 13,928 participants, including 4355 clean fuel users and 9573 solid fuel users. The median age of participants was 58.0 years, with 47.26% male and 52.74% female. Compared to clean fuel users, solid fuel users had lower household income and educational attainment, were more likely to live in rural areas or be smokers, and had higher CESD-10 scores (all P < 0.001).
Table 1.
Baseline characteristics of the study population
| level | Overall | Clean fuel | Solid fuel | P value |
|---|---|---|---|---|
| N | 13,928 | 4355 | 9573 | |
| Age (years) | 58 (51, 65) | 56 (50, 63) | 58 (52, 65) | < 0.0001 |
| Sex (%) | 0.8014 | |||
| Men | 6583 (47.26) | 2051 (47.10) | 4532 (47.34) | |
| Women | 7345 (52.74) | 2304 (52.90) | 5041 (52.66) | |
| Marital status (%) | 0.2118 | |||
| Married | 12,227 (87.79) | 3846 (88.31) | 8381 (87.55) | |
| Unmarried | 1701 (12.21) | 509 (11.69) | 1192 (12.45) | |
| Educational level (%) | < 0.0001 | |||
| Less than lower secondary | 12,313 (88.40) | 3424 (78.62) | 8889 (92.85) | |
| Upper secondary & vocational training | 1362 (9.78) | 720 (16.53) | 642 (6.71) | |
| Tertiary | 253 (1.82) | 211 (4.85) | 42 (0.44) | |
| Household income (10,000 CNY/year) | 1.20 (0.24, 3.37) | 3.00 (1.00, 5.50) | 0.80 (0.19, 2.51) | < 0.0001 |
| CESD-10 score | 7.00 (3.00, 12.00) | 5.00 (3.00, 9.00) | 8.00 (4.00, 13.00) | < 0.0001 |
| Body mass index (%) | < 0.0001 | |||
| < 18.5 | 792 (6.66) | 140 (4.08) | 652 (7.71) | |
| 18.5–25 | 7455 (62.71) | 2065 (60.24) | 5390 (63.70) | |
| 25–30 | 3050 (25.65) | 999 (29.14) | 2051 (24.24) | |
| > 30 | 592 (4.98) | 224 (6.53) | 368 (4.35) | |
| Area of residence (%) | < 0.0001 | |||
| Rural | 8548 (61.37) | 1437 (33.00) | 7111 (74.28) | |
| Urban | 5380 (38.63) | 2918 (67.00) | 2462 (25.72) | |
| Smoke status (%) | < 0.0001 | |||
| Never | 8476 (60.86) | 2788 (64.03) | 5688 (59.42) | |
| Ever | 1163 (8.35) | 363 (8.34) | 800 (8.36) | |
| Current | 4287 (30.78) | 1203 (27.63) | 3084 (32.22) | |
| Alcohol intake (%) | 0.3964 | |||
| Yes | 9332 (76.86) | 2888 (77.36) | 6444 (76.64) | |
| No | 2809 (23.14) | 845 (22.64) | 1964 (23.36) | |
| Hypertension (%) | 3664 (26.43) | 1185 (27.27) | 2479 (26.05) | 0.1385 |
| Diabetes (%) | 847 (6.14) | 301 (6.95) | 546 (5.76) | 0.0075 |
| Heart disease (%) | 1839 (13.26) | 562 (12.94) | 1277 (13.40) | 0.4747 |
Continuous variables are presented as median (P25–P75), and categorical variables are presented as n (%). P values were calculated using the Wilcoxon rank-sum test for continuous variables and the chi-square test for categorical variables
Table 2 shows that 917 incident stroke events occurred during the follow-up period, out of 13,928 participants, with an incidence of 6.58%. Compared to participants using clean fuels (248 events, incidence 5.69%), those using solid fuels (669 events, incidence 6.99%) had a higher risk of stroke. In Model 1, after adjusting for age, sex, marital status, place of residence, household income, and education, solid fuel use was associated with a 28% higher risk of stroke (OR = 1.28, 95% CI: 1.00-1.64). This association remained statistically significant and virtually unchanged after full adjustment for smoking, alcohol consumption, BMI, and a history of hypertension, diabetes, and heart disease, with an OR of 1.26 (95% CI: 1.06–1.49). However, subgroup analyses by sex revealed a moderate effect modification of the association between household solid fuel use and stroke risk (P for interaction = 0.098). Among men, the OR in model 2 was 1.12 (95% CI: 0.86–1.42), not reaching statistical significance. In contrast, among women, the incidence was 4.99% for clean-fuel users (n = 115) and 6.96% for those using solid fuels (n = 351). After full adjustment for the covariates, the OR for women was 1.39 (95% CI: 1.09–1.77), indicating a significant association.
Table 2.
Association between household solid fuel use and the risk of stroke
| Cases | Incidence (%) | OR1 (95% CI) | P interaction | OR2 (95% CI) | P interaction | |
|---|---|---|---|---|---|---|
| Total population | 917 | 6.58 | ||||
| Clean fuel | 248 | 5.69 | Ref (1.00) | Ref (1.00) | ||
| Solid fuel | 669 | 6.99 | 1.28 (1.00, 1.64) | 1.26 (1.06, 1.49) | ||
| Men | 451 | 6.85 | 0.066 | 0.098 | ||
| Clean fuel | 133 | 6.48 | Ref (1.00) | Ref (1.00) | ||
| Solid fuel | 318 | 7.02 | 1.02 (0.71, 1.46) | 1.12 (0.86, 1.42) | ||
| Women | 466 | 6.34 | ||||
| Clean fuel | 115 | 4.99 | Ref (1.00) | Ref (1.00) | ||
| Solid fuel | 351 | 6.96 | 1.56 (1.10, 2.23) | 1.39 (1.09, 1.77) |
OR1 (95% CI) adjusted for age, sex, marital status, place of residence, household income, and education level
OR2 (95% CI) adjusted for age, sex, marital status, place of residence, household income, education level, smoking, alcohol consumption, body mass index, history of hypertension, diabetes, and heart disease
The association between household solid fuel use and incident stroke risk was further evaluated through sensitivity analyses to assess the robustness of our primary findings (Table S3). First, after excluding participants with missing covariate data, we observed a consistent positive association in the overall population, and sex-stratified analyses revealed a significant association among women (OR = 1.35, 95% CI: 1.03–1.77). Second, after excluding stroke incidents occurring within the first two years of follow-up, the fully adjusted model still showed a statistically significant positive association in the overall population (OR = 1.33, 95% CI: 1.11–1.60). This trend was consistent in sex-stratified analyses, with women exhibiting a stronger association (OR = 1.51, 95% CI: 1.17–1.97). Third, weighted regression confirmed the primary findings, revealing a positive association between solid fuel use and significant risk of incident stroke in women (OR = 1.45, 95% CI: 1.06–1.98).
The results of the mediation analysis examining the effect of household solid fuel use on stroke risk through depressive symptoms are summarized in Table 3. Detailed counts of participants, person-years, and incident cases for each pathway are provided in Table S2. When depressive symptoms were modeled as a continuous CESD-10 score, solid fuel use was associated with higher CESD-10 scores (β = 1.68, SE = 0.12). A one-point increase in CESD-10 was linked to higher odds of incident stroke (OR = 1.02, 95% CI: 1.01–1.03). The mediation proportion was 15.7% (P < 0.05), suggesting that depressive symptoms accounted for a modest but statistically significant portion of the total association between household solid fuel use and incident stroke. In addition, household solid fuel use was associated with higher CESD-10 scores in women (β = 1.83, SE = 0.17), with a significant mediation proportion of 13.5%.
Table 3.
Mediating role of depressive symptoms in the association between household solid fuel use and the risk of stroke
| Solid fuel use to depression (Beta, SE/OR, 95% CI) | Depression to stroke (OR, 95% CI) | Mediation proportion (%) | |
|---|---|---|---|
| Depression: CESD-10 score | |||
| Total population | 1.68 (0.12) | 1.02 (1.01, 1.03) | 15.7 (6.4, 68.0)* |
| Men | 1.48 (0.16) | 1.02 (0.99, 1.03) | 11.1 (-169.4, 163.8) |
| Women | 1.83 (0.17) | 1.03 (1.01, 1.04) | 13.5 (4.1, 50.1)* |
| Depression: CESD-10 score ≥ 10 | |||
| Total population | 1.80 (1.65, 1.97) | 1.25 (1.08, 1.44) | 11.5 (2.7, 45.7)* |
| Men | 1.83 (1.59, 2.11) | 1.25 (1.01, 1.54) | 14.0 (-177.0, 267.2) |
| Women | 1.78 (1.58, 2.00) | 1.23 (1.01, 1.50) | 7.3 (1.4, 32.2)* |
| Depression: CESD-10 score ≥ 20 | |||
| Total population | 2.12 (1.74, 2.61) | 1.36 (1.06, 1.73) | 5.6 (1.0, 24.5)* |
| Men | 2.13 (1.50, 3.10) | 1.43 (0.93, 2.12) | 5.9 (-70.8, 94.9) |
| Women | 2.11 (1.66, 2.70) | 1.28 (0.94, 1.72) | 3.5 (-1.9, 17.3) |
Models adjusted for age, sex, marital status, place of residence, household income, education level, smoking, alcohol consumption, body mass index, history of hypertension, diabetes, and heart disease
*For statistical significance
When we defined the presence of depressive symptoms as a CESD-10 score ≥ 10, solid fuel use was significantly associated with a higher risk of depressive symptoms (OR = 1.80, 95% CI: 1.65–1.97). The presence of depressive symptoms (CESD-10 ≥ 10) was associated with a higher risk of stroke (OR = 1.25, 95% CI: 1.08–1.44), and the mediation proportion was 11.5% (P < 0.05). In sex-stratified analyses, the indirect effect was statistically significant in women (mediation proportion = 7.3%, P < 0.05), but not in men (mediation proportion = 14.0%). Similar results were obtained when defining the severe depressive symptoms with the cut-off value of 20 score of CESD-10.
Sensitivity analyses were conducted using lagged depressive symptoms as the mediator to assess the stability of the mediation results (Table S4). When using the continuous CESD-10 score, the indirect effect through lagged depressive symptoms remained statistically significant in the total population (mediation proportion = 9.7%) and among women (mediation proportion = 9.0%), but not in men (mediation proportion = 9.4%), with wide confidence intervals indicating substantial statistical uncertainty. A consistent pattern was observed when defining depression as a CESD-10 score ≥ 10, with significant mediation proportions in the total population (8.3%) and in women (7.9%). These findings are consistent with depressive symptoms as a potential mediator in the association between household solid fuel use and incident stroke, particularly in females.
Discussion
Based on the data of the ten thousand Chinese population, our findings indicate a significant association between household solid fuel use and incident stroke risk in middle-aged and older Chinese adults. In addition, depressive symptoms may account for up to 15.7% of the association between household solid fuel use and incident stroke in the total population. Furthermore, additional analysis revealed moderate heterogeneity in these associations across sexes. These findings provide new empirical evidence for the potential psychological pathways linking solid fuel use and stroke, highlighting the importance of addressing mental health in studies of environmental risk and cerebrovascular disease.
The positive association between household solid fuel use and incident stroke in this study was generally consistent with previous studies. Multiple studies have shown that household air pollution from the use of solid fuels has a significant adverse impact on cardiovascular health. For example, a study in the Putuo District of Shanghai found that household use of solid fuels was significantly associated with an increased risk of stroke, hypertension, coronary heart disease, and diabetes [27]. Similarly, a large-scale epidemiological study covering 11 countries and 467 urban and rural communities found that the use of solid fuels for cooking and heating was closely related to higher mortality rates and an increased risk of cardiovascular diseases, including stroke [28]. Previous studies have primarily examined the association between household solid fuel use and overall cardiovascular outcomes [13, 29], with limited attention to stroke as a specific health outcome. Based on a nationally representative prospective cohort, our study investigated the relationship between household solid fuel use and incident stroke, showing that exposure to solid fuel combustion was associated with a 26% higher risk of stroke among middle-aged and older individuals compared with those unexposed.
In the sex-stratified analysis, the association between household solid fuel use and incident stroke remained significant only among women, suggesting that females may be more susceptible to the adverse health effects of such exposure. This finding is consistent with a quantitative study on the impact of air pollution on years lived with disability and years of life lost across the Asia-Pacific region from 1990 to 2019, which showed that women are more vulnerable to household air pollution, while men face a higher mortality risk from exposure to atmospheric particulate matter [30]. Additionally, another study found that women exposed to a 10 µg/m3 increase in PM10 concentration had a significantly higher stroke risk (HR = 2.16, 95% CI: 1.15–4.06), whereas no significant increase was observed in men (HR = 1.07, 95% CI: 0.61–1.86) [31]. This sex difference may reflect biological susceptibility, as females appear more physiologically vulnerable to the adverse effects of air pollution [32]. In households relying primarily on solid fuels, greater domestic involvement and longer indoor residence among females can lead to prolonged and higher cumulative exposure, thereby amplifying risk. The higher stroke risk observed in women highlights the importance of sex-sensitive public health interventions, particularly those aimed at reducing exposure to household solid fuel combustion among women, who may bear a disproportionate cerebrovascular and cardiovascular burden from such exposure. On the other hand, the lack of a significant association in men may be attributed to smaller sample sizes and shorter exposure times due to factors such as migration for work, which could have limited the statistical power to detect the association. Future research with larger male cohorts is necessary to further determine whether the absence of a significant association in men reflects a true null effect or is due to statistical limitations.
Our study identified a significant mediating effect of depression in the association between household solid fuel use and incident stroke. Combustion of household solid fuels is a major source of household air pollution [8]. Previous studies have demonstrated that air pollution is associated with adverse mental health outcomes. For example, a meta-analysis of 39 studies reported that long-term exposure to PM2.5 and NO2 significantly increased the risk of depression [33]. Similarly, a prospective cohort of 389,000 adults from the UK Biobank found that long-term joint exposure to multiple pollutants—including PM2.5, PM2.5−10, NO2, and NO—was associated with higher risks of incident depression and anxiety, even at relatively low concentrations [34]. In our study, a robust and consistent positive association was observed between household solid fuel use and depressive symptoms across both continuous and categorical measures of depression. In addition, it is widely recognized that depression constitutes an independent risk factor for stroke [35, 36]. However, in previous research, much attention has been given to post-stroke depression, while the emotional and psychological changes prior to stroke have been largely overlooked [37, 38]. In our prospective cohort study, higher depressive symptom scores were significantly associated with a higher risk of incident stroke. Given that depression was linked to both household solid fuel use and stroke risk in our study, we speculate that it may act as an intermediate role. Further mediation analyses found that depression plays a significant mediating role between household solid fuel use and incident stroke, with a stronger association observed in women compared to men. However, caution should be exercised when interpreting the mediation analysis results for the male cohort, as the estimated mediation proportion is unstable and its confidence interval is extremely wide—primarily due to the small and statistically insignificant overall effect of household solid fuel use on stroke incidence within this subgroup. Existing studies have not thoroughly explored whether depression plays a mediating role between air pollution and incident stroke. However, existing studies have demonstrated that depression can act as a mediator across various health conditions. For instance, both depression and social relationships have been reported to mediate the association between frailty and cognitive function [39]. Similarly, depression has been shown to mediate the link between adverse childhood experiences and chronic lung diseases [40], and its mediating role between sedentary behavior and social frailty has also been confirmed in previous research [41]. Unlike previous studies, our research systematically evaluated multiple approaches to assessing depressive symptoms, including both continuous scores and binary classifications using different cutoffs (e.g., CESD-10 ≥ 10 and ≥ 20). The results consistently revealed a robust mediating role of depressive symptoms in the association between household solid fuel use and incident stroke. These findings highlight that, regardless of depression severity, evaluating individuals’ living environments—particularly their exposure to indoor air pollution attributed to solid fuel combustion —is essential for preventing stroke onset.
Although the molecular mechanisms linking air pollution to stroke and depression have been studied, they are not fully understood. Evidence suggests that fine PM2.5 can enter the brain directly via the olfactory, trigeminal, and vagus nerves, or indirectly through the lungs and bloodstream, triggering systemic and brain inflammation and oxidative stress [20, 42]. These processes can cause endothelial damage, release of inflammatory mediators, and thrombosis, contributing to stroke [11, 12]. Persistent inflammation and oxidative stress can also disrupt the hypothalamic-pituitary-adrenal axis, impair hippocampal neurogenesis, and damage dopaminergic neurons [34]. In addition, activation of the indoleamine 2,3-dioxygenase pathway accelerates tryptophan degradation [43], reduces serotonin synthesis, and disrupts the balance between serotonin and norepinephrine, promoting depression [44, 45]. Importantly, depression itself can further increase stroke risk by amplifying inflammation, disturbing neuroendocrine balance, and encouraging unhealthy behaviors such as smoking, alcohol use, and physical inactivity [46].
This prospective cohort analysis helps clarify the temporal relationship between household solid fuel use, depressive symptoms, and the occurrence of stroke, and provides a more reliable basis for exploring their potential causal associations. However, this study has several limitations. First, data on depressive symptoms and stroke outcomes relied on self-reported questionnaires, which may introduce information bias. Second, the assessment of household solid fuel use in this study relied on participants’ self-reported household cooking and heating fuel types. However, it did not collect information on kitchen or room ventilation conditions, stove types and performance, cooking duration and frequency, or air purification device usage, which may introduce some degree of misclassification bias. Additionally, this study did not directly measure the specific composition of indoor pollutants, such as PM2.5, PM10, carbon monoxide, or polycyclic aromatic hydrocarbons. Future studies should incorporate more refined exposure assessment, including objective monitoring of indoor pollutant concentrations and systematic characterization of household energy-use behaviors, to better quantify pollutant–stroke associations. Third, although several covariates were controlled for in the analysis, unaccounted confounders could not be ruled out. Fourth, our mediation analysis relies on a presumed causal pathway in which household solid fuel use increases indoor combustion-related pollution, which may contribute to depressive symptoms and ultimately raise stroke risk. We did not use genetic or quasi-experimental methods to confirm causality. Still, evidence from Mendelian randomization suggests that air pollution can causally be associated with a higher stroke risk [47, 48], lending biological plausibility to this association.
Conclusion
This study showed a significant positive association between household solid fuel use and the risk of incident stroke in middle-aged and older Chinese adults. In addition, depressive symptoms were found to mediate the relationship. Furthermore, compared to men, women exhibited greater sensitivity to the impact. Our findings suggest that public health policies aiming to reduce the stroke burden should implement an integrated approach, simultaneously promotes household clean energy transition, mitigates indoor air pollution, and strengthens community-based mental health services, especially for women.
Supplementary Information
Acknowledgements
The authors thank the China Health and Retirement Longitudinal Study (CHARLS) team for providing data.
Authors’ contributions
CS, BL, NR and YS designed the study concepts; CS and NR participated in the drafting or revising of manuscript; CS performed statistical analysis and interpretation; CS integrated the entire study; BL and YZ edited the manuscript and approved the final version. All authors approved the submission of the final manuscript.
Funding
The Jinshan Hospital Affiliated to Fudan University Youth Scientific Research Initiation Fund (grant numbers: JYQN-LC-202310).
Data availability
The datasets used and analyzed in the current study are available upon reasonable request from the official CHARLS application.
Declarations
Ethics approval and consent to participate
This study was carried out based on data extracted from the CHARLS public database, and all methods were performed according to the relevant guidelines and regulations. Written informed consent was obtained from all participants or their legal agents before the commencement of any study process. The ethics approval for the collection of CHARLS data has been approved by the Peking University Biomedical Ethics Review Committee (IRB00001052-11015). The use of CHARLS data was approved by the Human Research Ethics Committee of the University of Newcastle (H-2015-0290).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Chenqin Si and Ningna Ren contributed equally to this work and shared the first authorship.
Contributor Information
Yunpeng Zhang, Email: zhangyunpeng2019@163.com.
Bing Li, Email: li_bing@fudan.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and analyzed in the current study are available upon reasonable request from the official CHARLS application.