Abstract
Background
Indoor air pollution has been recognized as a risk factor for mental health, particularly depression and anxiety symptoms. Indoor musty odors are considered a component of indoor air pollution. However, evidence on the associations between indoor musty odors and mental health among older adults is limited.
Methods
The current study utilized data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We employed self-reported data to ascertain indoor musty odors. Depression symptoms were evaluated utilizing the Center for Epidemiologic Studies Depression Scale-10 (CES-D-10), and anxiety symptoms were measured using the Generalized Anxiety Disorder Scale-7 (GAD-7). This study implemented logistic regression and linear regression to examine the associations of indoor musty odors with depression and anxiety symptoms.
Results
A total of 11,950 older adults (mean age = 83.11 ± 11.12 years) were included in this study. The study indicated that indoor musty odors were significantly associated with depression symptoms (adjusted odds ratio (OR) 1.83, 95% CI 1.58, 2.11) and anxiety symptoms (adjusted OR 2.12, 95% CI 1.78, 2.53).
Conclusions
These findings provide valuable insights of indoor musty odors into the potential health risks associated with older adults’ depression and anxiety symptoms.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-025-24096-y.
Keywords: Musty odors, Depression symptoms, Anxiety symptoms, Older adults
Introduction
Healthy aging is a critical issue that has garnered significant attention globally due to the demographic challenges posed by the aging population [1]. China is the country with the largest aging population, which has also raised concerns about the health of older adults [2]. Mental health has been consistently recognized as a crucial concern among the various health issues encountered by the age population, with depression and anxiety being pervasive and commonly encountered problems [3].
According to global statistics, the prevalence of depression and anxiety in older adults is approximately 7.0% and 3.8%, respectively [4]. However, this prevalence in China is higher than the global average. Specifically, evidence has revealed that this prevalence among older adults in China was 23.6% and 24.6%, respectively [5, 6]. Depression and anxiety issues among older adults in China deserve special attention. Numerous studies have indicated that depression and anxiety are associated with a range of negative physical outcomes in older adults, including insomnia [7], malnutrition [8], decreased immune function [9], cognitive decline [10], and exacerbation of cardiovascular diseases [11]. These disorders can also weaken older adults’ self-esteem [12], self-efficacy [13], and social support [14], leading to feelings of loneliness [15] and social isolation [16]. Furthermore, they can adversely affect older adults’ overall sense of well-being [17] and quality of life [18]. Given the high prevalence of depression and anxiety and their significant burdens on older adults, it is imperative to comprehend the factors associated with these mental health disorders to prevent their occurrence.
The mental disorders of depression and anxiety are complex and associated with multiple factors, such as sociodemographic factors [19], socioeconomic status [20], lifestyle behaviors [21], health status [22], and social support [23]. In addition, multiple studies have confirmed that depression and anxiety are also associated with environmental factors, including exposure to outdoor and indoor air pollution [24–26]. Musty odors are a common problem in indoor environments and are caused by the presence of mold and dampness [27].
Mold exposure has been associated with physical symptoms such as allergic reactions [28], respiratory problems [29], and neurological symptoms [30], but these studies have primarily focused on physical health outcomes, and research on the impact of mold or musty odors on the mental health of older adults remains limited. Existing evidence suggests that exposure to indoor musty odors constitutes a chronic psychological stressor, potentially contributing to the onset and worsening of mental health problems [31]. Several studies have indicated that indoor mold exposure may lead to mood disturbances [32] and attention deficits [33].
However, there is a notable scarcity of research investigating the associations between indoor musty odors and depression or anxiety, especially among older adults who spend substantial time indoors and are particularly vulnerable to adverse health effects from indoor environmental toxins. Importantly, most previous research has been conducted in specific regions outside China [34, 35], with limited generalizability to the Chinese context. Given China’s large aging population and unique environmental and cultural factors influencing indoor living conditions [36, 37], nationally representative data are essential to understand these associations within this context.
Therefore, the present study seeks to address this gap by examining the relationships between indoor musty odors and depression and anxiety symptoms in a large, nationally representative sample of Chinese older adults, providing valuable insights for targeted public health interventions.
Methods
Study population
The Chinese Longitudinal Healthy Longevity Survey (CLHLS) is a countrywide community-based, longitudinal investigation intended to study the health condition and determinants impacting longevity in the older population in China. The CLHLS initiated its baseline survey in 1998 and subsequently conducted follow-up surveys biennially or triennially. The CLHLS was carried out in a randomly selected half of the counties and cities within 23 out of the 31 provinces/municipalities in China, spanning over 85% of the Chinese population. The CLHLS used a multistage stratified cluster sampling design to select its sample. The first stage involved selecting counties/districts within each province/municipality based on their economic development level and geographic location. The second stage involved selecting communities within each county/district using probability proportional to size sampling. The third stage involved selecting households within each community using a combination of random and systematic sampling methods. Finally, all eligible individuals within selected households were asked to participate in the survey. The survey utilized a face-to-face interview method to collect data from participants, and interviews were conducted by trained survey staff who visited participants in their homes. The CLHLS employed rigorous quality control procedures to ensure the validity and reliability of the gathered data. These procedures included pretesting of survey instruments, training of survey staff, and regular monitoring of data quality [38].
This study utilized data from the 2018 wave of the CLHLS, which collected information from 15,874 participants through face-to-face interviews. We excluded those younger than 60 years old (n = 12), and those with missing data on indoor musty odors (n = 706), depressive symptoms (n = 3,136), or anxiety symptoms (n = 70). Only participants with complete and matched information on both exposure (indoor musty odors) and outcomes (depressive and anxiety symptoms) were retained, resulting in a final analytical sample of 11,950 individuals (Fig. 1). All data were collected within the same wave and survey interview session, ensuring consistency and alignment across variables.
Fig. 1.
Flow chart of inclusion of participants from the Chinese Longitudinal Healthy Longevity Survey
The CLHLS received ethical approval from the Biomedical Ethics Committee of Peking University (IRB00001052-13074). All participants provided written informed consent before completing the survey. Our study was conducted in accordance with the WMA Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Subjects.
Indoor musty odors
Indoor musty odors were evaluated utilizing the question, “Do you frequently smell musty odors within your indoor environment?” Response to indoor musty odors was categorized as no or yes.
Outcomes
The Center for Epidemiologic Studies Depression Scale-10 (CES-D-10) is used to evaluate participants’ depression symptoms [39]. Each item is scored on a 4-point scale of 0–3, ranging from “less than 1 day” to “5–7 days”. Summed scores on the CES-D-10 range from 0 to 30, with higher scores representing greater severity of the depression symptom. Following prior studies [40, 41], depression symptoms are defined with a cut-off score of 10 and above on the CES-D-10. The Cronbach’s α for the CES-D-10 of this study was 0.736.
The Generalized Anxiety Disorder Scale-7 (GAD-7) is used to measure participants’ anxiety symptoms [42]. Each item is scored on a 4-point scale of 0–3, ranging from “never” to “almost every day”. Summed scores on the GAD-7 range from 0 to 21, with higher scores indicating greater severity of the anxiety symptom. Following prior studies [43, 44], anxiety symptoms are defined with a cut-off score of 5 and above on the GAD-7. The Cronbach’s α for the GAD-7 of this study was 0.919.
Covariates
Based on previous studies [45, 46], we considered multiple potential confounding variables, including age (continuous variable), gender (male vs. female), urban‒rural distribution (urban vs. rural), education level (illiterate, primary school, and high school and above), having a spouse (no vs. yes), smoking status (no vs. yes), drinking alcohol (no vs. yes), living alone (no vs. yes), having chronic diseases (no vs. yes), regular exercise (no vs. yes), body mass index (continuous variable), fuel choice (clean fuel vs. solid fuel), indoor ventilation (no vs. yes), using air purification devices (no vs. yes), distance to the major roadway (≤ 100 m, 101–300 m, and > 300 m), annual household income (< 10,000 yuan, 10,000–50,000 yuan, and > 50,000 yuan), and cognitive impairment (absence vs. presence).
The Chinese Mini-Mental State Examination (CMMSE) is used to assess participants’ cognitive function [47]. The CMMSE consists of 24 items covering 7 cognitive domains: orientation, registration, naming foods, attention and calculation, copying a figure, recalling, and language. Summed scores on the CMMSE range from 0 to 30, with higher scores indicating better cognitive function. Following prior studies [48, 49], cognitive impairment is defined with a cut-off score of less than 18 on the CMMSE. The Cronbach’s α for the MMSE of this study was 0.865.
Statistical analysis
First, the Kolmogorov‒Smirnov test was applied to assess the normality of continuous variables. The continuous variables were approximately normally distributed based on the visual examination of Q-Q plots. The descriptive statistics for continuous variables were reported as the mean and standard deviation (SD), while categorical variables were presented as numbers and percentages. The chi-squared test was conducted to compare the categorical variables, while variance analysis was employed to compare the continuous variables. Second, we utilized multivariable logistic regression models to examine the potential associations between indoor musty odors and depression and anxiety symptoms. We also employed multiple linear models to assess the associations of indoor musty odors with depression and anxiety symptom scores. In each analysis, three models were employed: Model 1 without covariate adjustment, Model 2 adjusting for age and gender, and Model 3 adjusting for all covariates. Third, we performed stratified and interaction analyses based on categorical variables to evaluate potential effect modifications.
We also performed three sensitivity analyses. First, we conducted multiple imputations via chained equations to account for missing data. Second, we excluded participants with cognitive impairment (n = 1,220), as they may have been subject to substantial recall bias when reporting information. Third, we calculated E-values to assess the likelihood that unmeasured confounders could explain our results [50].
A two-tailed P value < 0.05 indicated statistical significance. All statistical analyses in this study were conducted using Stata version 16.0 (StataCorp, College Station, TX, USA).
Results
Characteristics of participants
Among the participants, 10,355 participants reported that their indoors had no musty odors, and the remaining 1595 participants reported that their indoors had musty odors. The participants had a mean age of 83.11 years. Participants who reported indoor musty odors had higher mean scores for depression and anxiety symptoms than those who reported the absence of indoor musty odors. Participants reporting indoor musty odors tended to have a lower education level, live in rural areas, exercise irregularly, and be without indoor ventilation than those not reporting indoor musty odors (Table 1).
Table 1.
Characteristics of the study population
| Characteristic | Total | Indoor had no musty odors | Indoor had musty odors | P value |
|---|---|---|---|---|
| N | 11,950 | 10,355 | 1595 | |
| CES-D-10 scores, mean (SD) | 7.33 (4.42) | 7.07 (4.25) | 9.08 (5.12) | < 0.001 |
| Depression symptoms, n (%) | < 0.001 | |||
| Absence | 8738 (73.12) | 7795 (75.28) | 943 (59.12) | |
| Presence | 3212 (26.88) | 2560 (24.72) | 652 (40.88) | |
| GAD-7 scores, mean (SD) | 1.39 (2.73) | 1.24 (2.54) | 2.33 (3.56) | < 0.001 |
| Anxiety symptoms, n (%) | < 0.001 | |||
| Absence | 10,548 (88.27) | 9289 (89.71) | 1259 (78.93) | |
| Presence | 1402 (11.73) | 1066 (10.29) | 336 (21.07) | |
| Age (years), mean (SD) | 83.11 (11.12) | 83.16 (11.15) | 82.78 (10.91) | 0.249 |
| Gender, n (%) | 0.777 | |||
| Male | 5591 (46.79) | 4850 (46.84) | 741 (46.46) | |
| Female | 6359 (53.21) | 5505 (53.16) | 854 (53.54) | |
| Urban–rural distribution, n (%) | 0.009 | |||
| Urban | 6617 (55.37) | 5782 (55.84) | 835 (52.35) | |
| Rural | 5333 (44.63) | 4573 (44.16) | 760 (47.65) | |
| Education level, n (%) | < 0.001 | |||
| Illiterate | 4536 (44.40) | 3825 (43.23) | 711 (51.90) | |
| Primary school | 3516 (34.41) | 3066 (34.66) | 450 (32.85) | |
| High school and above | 2165 (21.19) | 1956 (22.11) | 209 (15.26) | |
| Had a spouse, n (%) | 0.760 | |||
| No | 6160 (52.07) | 5343 (52.12) | 817 (51.71) | |
| Yes | 5671 (47.93) | 4908 (47.88) | 763 (48.29) | |
| Smoking status, n (%) | 0.013 | |||
| No | 9880 (83.49) | 8596 (83.82) | 1284 (81.32) | |
| Yes | 1954 (16.51) | 1659 (16.18) | 295 (18.68) | |
| Drinking alcohol, n (%) | 0.830 | |||
| No | 9912 (84.30) | 8588 (84.33) | 1324 (84.12) | |
| Yes | 1846 (15.70) | 1596 (15.67) | 250 (15.88) | |
| Lived alone, n (%) | < 0.001 | |||
| No | 9753 (82.79) | 8545 (83.77) | 1208 (76.41) | |
| Yes | 2028 (17.21) | 1655 (16.23) | 373 (23.59) | |
| Chronic diseases, n (%) | < 0.001 | |||
| No | 3558 (29.77) | 3142 (30.34) | 416 (26.08) | |
| Yes | 8392 (70.23) | 7213 (69.66) | 1179 (73.92) | |
| Regular exercise, n (%) | < 0.001 | |||
| No | 7721 (65.53) | 6613 (64.81) | 1108 (70.22) | |
| Yes | 4061 (34.47) | 3591 (35.19) | 470 (29.78) | |
| Body mass index (kg/m2), mean (SD) | 22.53 (3.87) | 22.58 (3.86) | 22.22 (3.92) | < 0.001 |
| Fuel choice, n (%) | < 0.001 | |||
| Clean fuel | 8600 (73.29) | 7654 (75.19) | 946 (60.84) | |
| Solid fuel | 3135 (26.71) | 2526 (24.81) | 609 (39.16) | |
| Indoor ventilation, n (%) | < 0.001 | |||
| No | 1061 (8.93) | 747 (7.26) | 314 (19.82) | |
| Yes | 10,815 (91.07) | 9545 (92.74) | 1270 (80.18) | |
| Used air purification devices, n (%) | 0.019 | |||
| No | 10,918 (91.83) | 9435 (91.59) | 1483 (93.33) | |
| Yes | 972 (8.17) | 866 (8.41) | 106 (6.67) | |
| Distance to the major roadway (meters), n (%) | 0.192 | |||
| ≤ 100 | 3796 (34.14) | 3304 (34.23) | 492 (33.56) | |
| 101–300 | 2227 (20.03) | 1954 (20.24) | 273 (18.62) | |
| > 300 | 5095 (45.83) | 4394 (45.52) | 701 (47.82) | |
| Annual household income (yuan), n (%) | < 0.001 | |||
| < 10,000 | 5086 (46.38) | 4184 (43.94) | 902 (62.38) | |
| 10,000–50,000 | 2273 (20.73) | 2037 (21.39) | 236 (16.32) | |
| > 50,000 | 3608 (32.90) | 3300 (34.66) | 308 (21.30) | |
| Cognitive impairment, n (%) | 0.001 | |||
| Absence | 10,730 (89.79) | 9334 (90.14) | 1396 (87.52) | |
| Presence | 1220 (10.21) | 1021 (9.86) | 199 (12.48) |
Total percentages within categories may not equal 100% due to rounding. Continuous variables are presented as mean (standard deviation); categorical variables are presented as counts (percentages). Group comparisons were conducted using independent t-tests for continuous variables and chi-square tests for categorical variables
Association of indoor musty odors with depression symptoms
In unadjusted logistic regression analysis, there was a significant association between indoor musty odors and depression symptoms (odds ratio (OR): 2.11, 95% confidence interval (CI): 1.89, 2.35). After adjusting for the covariates of age and gender in the logistic regression analysis, the association remained consistent in terms of direction but was enhanced in terms of magnitude (OR: 2.14, 95% CI: 1.92, 2.39). This association was attenuated but persisted with statistical significance in the fully adjusted logistic regression analysis (OR: 1.83, 95% CI: 1.58, 2.11). The results of the unadjusted linear regression analysis indicated a significant association between indoor musty odors and depression symptom scores compared to no indoor musty odors (coefficient (β): 2.01, 95% CI: 1.78, 2.24). After adjusting for the covariates of age and gender in the linear regression analysis, the association remained consistent in terms of direction but was enhanced in terms of magnitude (β: 2.02, 95% CI: 1.79, 2.25). This association was attenuated but persisted with statistical significance in the fully adjusted linear regression analysis (β: 1.67, 95% CI: 1.39, 1.94) (Table 2).
Table 2.
Association of indoor musty odors with depression symptoms
| Model | Indoor had no musty odors | Indoor had musty odors | P value |
|---|---|---|---|
| Logistic regression, odds ratio of depression symptoms (95% CI) | |||
| Model 1 | Reference | 2.11 (1.89, 2.35) | < 0.001 |
| Model 2 | Reference | 2.14 (1.92, 2.39) | < 0.001 |
| Model 3 | Reference | 1.83 (1.58, 2.11) | < 0.001 |
| Linear regression, coefficient for depression symptom scores (95% CI) | |||
| Model 1 | Reference | 2.01 (1.78, 2.24) | < 0.001 |
| Model 2 | Reference | 2.02 (1.79, 2.25) | < 0.001 |
| Model 3 | Reference | 1.67 (1.39, 1.94) | < 0.001 |
Model 1 was unadjusted
Model 2 was adjusted for age and gender
Model 3 was adjusted for age, gender, urban–rural distribution, education level, whether having a spouse, smoking status, drinking alcohol, whether living alone, whether having chronic diseases, regular exercise, body mass index, fuel choice, indoor ventilation, whether using air purification devices, distance to the major roadway, annual household income, and cognitive impairment
Association of indoor musty odors with anxiety symptoms
The unadjusted logistic regression analysis showed a significant association between indoor musty odors and anxiety symptoms, with an OR of 2.33 (95% CI: 2.03, 2.66). Adjusting for age and gender in the logistic regression analysis strengthened the association between indoor musty odors and anxiety symptoms in terms of magnitude while maintaining its direction (OR: 2.34, 95% CI: 2.04, 2.68). After controlling for all potential confounders, the association remained significant (OR: 2.12, 95% CI: 1.78, 2.53). The unadjusted linear regression analysis showed a significant association between indoor musty odors and anxiety symptom scores (β: 1.09, 95% CI: 0.95, 1.23). After adjustment for age and gender, the magnitude and direction of this association remained consistent (β: 1.09, 95% CI: 0.94, 1.23). This association was attenuated but remained statistically significant in the fully adjusted linear regression analysis (β: 0.92, 95% CI: 0.74, 1.09) (Table 3).
Table 3.
Association of indoor musty odors with anxiety symptoms
| Model | Indoor had no musty odors | Indoor had musty odors | P value |
|---|---|---|---|
| Logistic regression, odds ratio of anxiety symptoms (95% CI) | |||
| Model 1 | Reference | 2.33 (2.03, 2.66) | < 0.001 |
| Model 2 | Reference | 2.34 (2.04, 2.68) | < 0.001 |
| Model 3 | Reference | 2.12 (1.78, 2.53) | < 0.001 |
| Linear regression, coefficient for anxiety symptom scores (95% CI) | |||
| Model 1 | Reference | 1.09 (0.95, 1.23) | < 0.001 |
| Model 2 | Reference | 1.09 (0.94, 1.23) | < 0.001 |
| Model 3 | Reference | 0.92 (0.74, 1.09) | < 0.001 |
Model 1 was unadjusted
Model 2 was adjusted for age and gender
Model 3 was adjusted for age, gender, urban–rural distribution, education level, whether having a spouse, smoking status, drinking alcohol, whether living alone, whether having chronic diseases, regular exercise, body mass index, fuel choice, indoor ventilation, whether using air purification devices, distance to the major roadway, annual household income, and cognitive impairment
Stratified and interaction analyses
The results of stratified analyses by categorical variables (gender, urban‒rural distribution, education level, having a spouse, smoking status, drinking alcohol, living alone, having chronic diseases, regular exercise, fuel choice, indoor ventilation, using air purification devices, distance to the major roadway, annual household income, and cognitive impairment) are shown in Supplementary Table 1 (dependent variables are categorical variables) and 2 (dependent variables are continuous variables). The associations of indoor musty odors with depression and anxiety symptoms were generally persistent in these subgroups. The interaction results showed that the distance to the major roadway and annual household income had significant interactions with indoor musty odors on depression symptoms or depression symptom scores (P interaction < 0.05). Using air purification devices had significant interactions with indoor musty odors on anxiety symptoms or anxiety symptom scores (P interaction < 0.05).
Sensitivity analyses
In the first sensitivity analysis, we imputed the key covariates that participants were missing. The results remained consistent (all P < 0.05) (Supplementary Tables 3 and 4). In the second sensitivity analysis, we assessed the impact of excluding participants with cognitive impairment. For all analyses, the exclusion of participants with cognitive impairment did not change the statistical significance of the associations (all P < 0.05) (Supplementary Tables 5 and 6). In the third sensitivity analysis, we generated the E-values to assess the sensitivity to unmeasured confounding factors. The E-values of this study were 3.06, 2.92, 3.66, and 3.06 for depression symptoms, depression symptom scores, anxiety symptoms, and anxiety symptom scores, respectively. Based on the E-values, unmeasured confounding is unlikely to fully explain our results.
Discussion
To our knowledge, this population-based study is the first to explore the associations of indoor musty odors with depression and anxiety symptoms among older adults in China. The results revealed a significant association of indoor musty odors with depression and anxiety symptoms among older adults.
Our findings support earlier studies that have found an association between indoor mold and depression symptoms. A study by Shenassa et al. [51] demonstrated an association of mold with depression symptoms, independent of demographic or housing-related variables. Two studies employing a combination of subjective and objective measures to evaluate mold and dampness observed significant associations with depression and self-reported emotional distress [52, 53]. Hopton et al. have identified independent associations between inhabiting damp and mold-infested housing and mental distress [54]. In addition, a study from England also found that mold and dampness were associated with depression symptoms [34]. As visible mold is not exactly equal to musty smell. Our findings contribute to the extant evidence demonstrating the association of indoor mold with depression symptoms from the perspective of smell.
Our findings showed an association of indoor musty odors with anxiety symptoms among older adults in China. This result was consistent with the findings of prior studies that had shown an association of exposure to indoor molds with mental health, including anxiety-like behavior [35]. Several studies have also shown an association between spending time in moldy buildings and self-reported anxiety symptoms [55, 56]. The findings of this study add to the growing body of evidence highlighting the importance of indoor air quality and its potential association with mental health, particularly among older adults. The negative association between indoor musty odors and anxiety symptoms suggests that exposure to indoor molds may have significant implications for the mental health of older adults. The results of the interaction also showed that distance to the major road and using air purification devices had interactions with indoor musty odors on depression or anxiety symptoms. Residential properties located near main roads are typically exposed to higher levels of pollution resulting from traffic, which can impede the airflow inside buildings and reduce indoor ventilation [57]. Additionally, the noise pollution caused by traffic may lead residents to close their windows or install sealed windows and doors to mitigate noise disturbances, further limiting indoor air circulation [58]. Considering these findings, it is important to prioritize interventions aimed at improving indoor air quality, particularly in settings where older adults tend to allocate substantial portions of their time, such as long-term care facilities and residential homes. Such interventions may include the use of air purifiers, improved ventilation systems, and regular maintenance and cleaning to prevent the growth of indoor molds and other pollutants.
Several biological mechanisms have been postulated to elucidate the underlying reasons and mechanisms through which exposure to indoor musty odors may be associated with the development of depression and anxiety symptoms. One potential mechanism is the impact of indoor air pollutants on the immune system. Exposure to mold and other indoor air pollutants may induce an inflammatory response in the body, leading to the production of cytokines that have been linked to the development of depression and anxiety symptoms [59, 60]. In addition, indoor musty odors may also affect the neuroendocrine system, leading to alterations in the levels of stress hormones such as cortisol and norepinephrine. Elevated levels of these hormones have been associated with the development of anxiety and depression [61, 62]. Furthermore, exposure to indoor air pollutants may lead to oxidative stress, which has also been implicated in the pathophysiology of depression and anxiety [63, 64]. Another possible mechanism is the impact of indoor air quality on the respiratory system. Exposure to indoor musty odors and other pollutants may exacerbate respiratory symptoms and allergies, which have been associated with the development of depression and anxiety symptoms [65, 66]. Additionally, poor indoor air quality may contribute to sleep disturbances, which have also been linked to the development of mood disorders [67, 68]. It is noteworthy that the biological mechanisms underlying the association between indoor musty odors and depression and anxiety symptoms are likely multifaceted and complex. Future research is warranted to enhance comprehension of the specific pathways through which indoor air pollutants may be associated with mental health outcomes and to identify effective interventions to reduce exposure to indoor pollutants and promote healthy aging.
Prior studies have found that unpleasant odors may be associated with depression and anxiety symptoms [69, 70], which further supports our findings. Neuroscientific research has indicated that there is a close association between the olfactory system and emotional regulation [71]. Unpleasant odors can activate the emotional center, inducing negative emotional reactions such as sadness and anxiety [72]. Additionally, there is a strong connection between the olfactory system and memory [73], and unpleasant odors may trigger unpleasant memories, thereby increasing emotional burden [74]. Therefore, when individuals are exposed to an unpleasant odor environment, it may induce depressive and anxious emotional reactions. These findings underscore the necessity of more closely attending to the influence of unpleasant odors on human mental health and shed light on the need to better manage our living environments to avoid exposure to unpleasant odors, which can further help maintain individual mental health.
Several limitations of this study require acknowledgement. First, the cross-sectional design limits causal inference. Although indoor musty odor exposure and both depression and anxiety symptoms were assessed concurrently in the 2018 CLHLS, the only wave that included anxiety assessment, this limits our ability to examine temporal or cumulative exposure effects. Prior research has demonstrated that environmental exposures, including ambient air pollution, may exert delayed or cumulative effects on health outcomes across extended timeframes [75]. Future research with multi-wave exposure and outcome assessments is warranted to clarify causal relationships and better capture potential long-term impacts. Second, this study used depression and anxiety screening tools (i.e., the CES-D-10 and GAD-7 scales) to assess symptoms instead of employing clinical diagnostic interviews. Third, exposure to indoor musty odors was assessed through self-reported data, which may be subject to multiple sources of bias. Specifically, the perception of musty odors may be influenced by participants’ individual olfactory sensitivity and cognitive function, particularly among older adults. Although we adjusted for age and cognitive impairment in our models and conducted a sensitivity analysis excluding individuals with cognitive impairment, residual bias cannot be fully excluded. Fourth, unlike pollutants such as PM2.5 or NO₂, indoor musty odors are difficult to quantify objectively, and our dataset lacked information on important exposure-related variables such as the duration of musty odor exposure and length of residence. As a result, we were unable to assess potential dose-response relationships or cumulative exposure. This limitation underscores the need for future studies to incorporate objective environmental monitoring and more detailed exposure assessments. Finally, although E-value analysis suggested that unmeasured confounding was unlikely to fully account for our findings, the possibility of residual bias cannot be entirely ruled out.
Conclusions
The results of this study demonstrate associations of indoor musty odors with elevated risks of experiencing symptoms of depression and anxiety. These findings supplement the expanding corpus of evidence highlighting the importance of indoor environmental quality in maintaining mental health, specifically emphasizing the need to safeguard older adults from experiencing symptoms of depression and anxiety arising from exposure to indoor air pollution. This study provides support for the national blueprint of ecological civilization and strategic preparations for an aging society.
Supplementary Information
Acknowledgements
Not applicable.
Authors’ contributions
X.W. and S.Z. designed the study. X.W. controlled the quality of the data and performed statistical analysis. X.W., Z.Y., Q.G., Y.S., and S.Z. managed and checked all the data. X.W. wrote the main manuscript text. X.W. prepared figure 1. X.W., Z.Y., Q.G., Y.S., H.X., and S.Z. contributed to manuscript review. X.W., Z.Y., Q.G., Y.S., H.X., and S.Z. read, checked, and approved the final manuscript.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Data availability
Publicly available datasets were analyzed in this study. This data can be found here: https://opendata.pku.edu.cn/dataverse/CHADS.
Declarations
Ethics approval and consent to participate
The CLHLS received ethical approval from the Biomedical Ethics Committee of Peking University (IRB00001052-13074). All participants provided written informed consent before completing the survey. Our study was conducted in accordance with the WMA Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Subjects.
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.
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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
Publicly available datasets were analyzed in this study. This data can be found here: https://opendata.pku.edu.cn/dataverse/CHADS.