Association Between Indoor Ventilation Frequency and IADL Disability Among Chinese Older Adults
Abstract
Background: Indoor air quality (IAQ) is regarded as a significant factor influencing older adults’ health, and opening windows for ventilation can help improve IAQ. This study revealed the relationship between indoor ventilation frequency (IVF) and instrumental activities of daily living (IADL) in Chinese older adults for the first time.
Methods: Data were obtained from cross-sectional data published in the 2017–2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) database. A multifactor logistic regression model was used to analyze the association between IVF and IADL in Chinese people aged 65 and above, which was observed in different subgroups. Further propensity score matching (PSM) and three sensitivity analyses enhanced the robustness of the results.
Results: After adjusting for all covariates, moderate and high IVF was associated with 33.8% (OR = 0.662, 95% CI: 0.507–0.864) and 42.6% (OR = 0.574, 95% CI: 0.444–0.742) reduction in the risk of having an IADL disability, compared to the low one, respectively. Among the results, significant associations were found only between IVF in summer and winter and older adults’ risk of IADL disability. Subgroup analyses showed that the association between IVF and IADL was specific in different subgroup populations. The results of the interaction analyses indicated that drinking significantly modified the relationship between IVF and IADL disability (p for interaction < 0.05).
Conclusion: In this nationally representative sample analysis, a higher window opening frequency for indoor ventilation was statistically significantly associated with a decrease in IADL disability among Chinese older adults. These results provide an essential basis for relevant policy development and new health intervention strategies to lower older adults’ risk of disability.
1. Introduction
The health condition of older adults has always been a focus of social concern. The rising life expectancy has increased the quantity of older adults, with an increasing proportion of disability in older adults [1]. Disability refers to an individual’s inability to perform independent daily living activities, including basic activities of daily living (BADL) and instrumental activities of daily living (IADL) [2]. BADL is assessed through the Katz index, which evaluates older adults’ ability to bathe, dress, go to the toilet, perform indoor transfers, manage incontinence, and eat [3]. The IADL is generally assessed using the Lawton IADL scale to evaluate older adults’ ability to shop, cook, manage finances, use transportation, perform household chores, take medications, and make phone calls. If there are issues in completing these activities, it is defined as an IADL disability [4]. Relevant studies have indicated that the prevalence rate of IADL disability among Chinese older adults is as high as 60.8% [5]. Older adults with IADL disabilities will significantly increase the risk of depression, cognitive impairment, and even death [6–8]. Thus, early prevention and intervention of IADL disability in older adults is urgent. Modern geriatric medicine particularly emphasizes the importance of disease prevention, so exploring and identifying modifying factors related to disabilities in older adults has significant practical significance.
A large amount of research evidence in recent years has shown that airborne particulate matter (PM2.5) and others are related to a high prevalence rate of disability in older adults [9, 10]. In addition to these outdoor air pollutants, there is a growing concern about the human health risks of indoor air pollution. Evidence from relevant epidemiological studies has shown that the use of chemicals such as indoor pesticides, disinfectants, and the combustion of unclean energy sources contribute to indoor air pollution [11, 12], which adversely influences human health (e.g., depression, cognitive impairment, and disability) [13–15]. Older adults tend to spend more time having indoor activities than outdoors due to retirement and other reasons, which have become a critical hazardous population for indoor air pollution. It deserves further attention that indoor ventilation, which supplies air to indoor areas through natural or mechanical force (e.g., windows and air conditioners), reduces the concentration of indoor air pollutants, such as nitrogen dioxide (NO2) [16, 17]. This may have significant value in improving the condition of IADL disabilities in older adults. Through our search, we found that several recent studies have revealed the relationship between indoor ventilation frequency (IVF) and anxiety, depression, and cognitive impairment in older adults [12, 18]. Another important study also revealed a significant association between IVF and low muscle mass in Chinese older adults [19]. These studies all highlight the importance of indoor ventilation and emphasize the significant role of seasonality. However, up to now, there has been no epidemiological study to assess the relationship between IVF and IADL disability in older adults. Identifying this modifiable factor may have prominent significance for the prevention of disability in older adults.
To fill this research gap, we hypothesized that a high frequency of indoor ventilation among Chinese older adults could significantly reduce the risk of IADL disability and might exhibit heterogeneity due to different population characteristics and seasons. Therefore, we used a nationally representative sample, employing cross-sectional data from the 2017–2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), and utilized multivariable logistic regression models and propensity score matching (PSM) methods to explore the association between IVF and IADL disability among Chinese older adults aged 65 and above for the first time and to examine this association across different seasons. Subsequently, numerous subgroup analyses and interaction analyses revealed the heterogeneity of this association. The research results may provide new perspectives and strategies for improving the life quality of older adults and promoting healthy aging.
2. Materials and Methods
2.1. Participants
The data for this study were acquired from the CLHLS, which was organized under the leadership of the Centre for Healthy Ageing and Development Research of Peking University/National Institute for Development Research and was the first large-scale nationwide longitudinal survey to be conducted in a developing country [20, 21]. The CLHLS project covered 23 provinces, municipalities, and autonomous regions in China, and the questionnaire was used as the main form to collect relatively comprehensive health-related information on older adults aged 65 and above and their adult children aged 35–64. The most recent follow-up survey (2017–2018) interviewed a total of 15,874 older adults aged 65 and above and collected information on 2226 older adults who died during 2014–2018. Subjects were informed of the purpose, process, potential risks, and benefits of the study by a professional investigator before they were involved in this survey, and those who agreed to participate signed an informed consent. The CLHLS project received ethical approval from the Biomedical Ethics Committee of Peking University (IRB00001052-13074).
We further estimated the minimum sample size required for our study using the overall rate. By reviewing the literature, we found that the prevalence rate of IADL disability among Chinese older adults is 60.8% [5]. Therefore, we calculated the minimum sample size required for our study using a prevalence rate of 60.8%, and we set the allowable error at 0.1 of the prevalence rate, substituting into the formula . The final minimum sample size required for the study is 248 (where α is the significance level, taking α = 0.05, Uα/2 = 1.96, p is the prevalence rate, and δ is the allowable error).
We used the CLHLS 2017–2018 cross-sectional data to develop the following three inclusion criteria in conjunction with our study aims: (1) no abnormal or missing data on IADL, (2) no abnormal or missing information on seasonal indoor ventilation, and (3) no abnormal or missing information on covariates. The detailed data-cleaning process is shown in Figure 1. The final 6740 participants were included in this analysis.
2.2. Indoor Ventilation
IVF is obtained by measuring the frequency of window openings per week during different seasons, which is reliable in previous studies [22]. Specifically, participants were asked, “in the past 12 months, how often did you open windows for ventilation in your home?” Divided into four time points: spring, summer, autumn, and winter, with each season corresponding to the following options: not opening windows, 1–3 times per week, 3–5 times per week, and more than 5 times per week. We encode the responses as follows: not opening windows is assigned a value of 0, 1–5 times per week is assigned a value of 1, and more than 5 times per week is assigned a value of 2. The total score ranged from 0 to 8 to the scores from the four seasons. We used Lowess smooth plots to evaluate the unadjusted association between continuous IVF scores and IADL disability in order to determine the cutoff score of IVF. Therefore, we further classified the total ventilation frequency into low (0–3), medium (4–5), and high (6–8) [12].
2.3. IADL Disability
IADL disability in the CLHLS was measured by the Lawton IADL scale, which has been widely used in Chinese older adults. Specifics included the following eight instrumental activities: visiting outside, shopping outside, cooking independently, washing independently, walking continuously, lifting heavy objects continuously, squatting continuously, and taking transportation independently [4]. The results of each activity were dichotomized into “with difficulty” and “without difficulty,” and participants were considered to have IADL if they answered “with difficulty’” on at least one item.
2.4. Covariates
In order to eliminate the potential confounding of the research results, we conducted quality control on the covariates related to IVF and IADL based on a review of relevant literature [22, 23] and considerations of four aspects: sociodemographic characteristics, lifestyle characteristics, environmental characteristics, and health characteristics. Specifically, these covariates included gender, age, residence, household income, education, living arrangements, marital status, manual labor before retirement, smoking, drinking, exercise, BMI, hypertension, diabetes, heart disease, dementia, arthritis, rheumatism, mold exposure, distance of residence from the main road, house type, air cleaning devices, concentrations of PM2.5, concentrations of NO2, and type of cooking fuel. All variable assignments are shown in Table S1.
Measurements of dementia in CLHLS were based on two questions: (1) Are you suffering from dementia? (2) Have you been diagnosed with dementia by a physician? Only those who answered “yes” to both questions were considered as having a dementia [24]. If the interviewee was unable to answer these two questions, their closest relative or caregiver answered for them. By measuring the regional concentrations of PM2.5 and NO2, air quality is assessed. For NO2, in urban areas, a land use regression model corrected for satellite overpass time and cloud cover is used to obtain regional concentration data. In contrast, the concentration is adjusted using satellite data from ozone monitoring instruments in rural areas. For PM2.5, ground monitoring data from 1998 to 2020 were used, combined with data from various satellite instruments and chemical transport models, and calibrated to global ground observation data using geographically weighted regression to calculate regional concentration levels [25]. Finally, we used quartiles as the cutoff points to categorize PM2.5 and NO2 levels into four classes.
2.5. Statistical Analysis
In a dataset that ultimately contains no missing values, the basic characteristics of categorical variables were expressed as frequency and percentage (n(%)). The chi-square test was used to analyze the variability between participants’ total ventilation frequency and the underlying characteristics. Binary logistic regression models were used to explore the possible relationship between IVF and IADL. We fitted four binary logistic regression models to analyze after stratifying for covariates. Specifically, Model 1 did not cover any covariates. Model 2 included age, gender, residence, marital status, living arrangements, household income, and education as covariates. Model 3 further added manual labor before retirement, drinking, smoking, exercise, distance of residence from the main road, house type, air cleaning devices, type of cooking fuel, and mold exposure. Model 4 added BMI, hypertension, diabetes, heart disease, dementia, arthritis, rheumatism, concentrations of PM2.5, and concentrations of NO2 to Model 3. Considering that older adults with IADL disabilities may have limited mobility and thus more easily experience lower ventilation frequencies, we further used multiple logistic regression analysis to explore the impact of IADL on IVF. A variance inflation factor of less than 10 was considered to indicate that there is no multicollinearity problem between the variables [26].
To better explain the benefits of high ventilation frequency, we used PSM in order to minimize the impact of differences between covariates on the research results as much as possible. Based on previous research [27], we used a 1:1 nearest neighbor matching algorithm to match participants with low and high ventilation frequencies, with a caliper value of 0.1, to eliminate and control potential confounding variables as much as possible. Confounding factors included age, gender, residence, marital status, living arrangements, household income, education, manual labor before retirement, drinking, smoking, exercise, distance of residence from the main road, house type, air cleaning devices, BMI, hypertension, diabetes, heart disease, dementia, arthritis, rheumatism, concentrations of PM2.5, concentrations of NO2, type of cooking fuel, and mold exposure. The standardized mean difference (SMD) < 0.1 indicates that the imbalance between groups is acceptable [28]. After matching, we reanalyzed the relationship between ventilation frequency and IADL using the previous method.
Furthermore, based on the aforementioned Model 4, we further analyzed the impact of IVF on IADL across different seasons. Subgroup analyses were conducted to explore the association between IVF and IADL in different characteristic groups and to investigate whether there is an interaction through interaction analysis. To reduce the risk of increased Type I errors due to multiple comparisons, we adjusted the p values of the subgroup analyses using the false discovery rate (FDR) method [29]. Three sensitivity analyses assured the robustness of the results. Finally, we calculated the E value to assess the impact of potential unmeasured confounders on the study results [30].
All analyses were performed using R 4.3.0. For PSM, logistic regression analysis, and chained-equation multiple imputation analysis, we respectively implemented them using the MatchIt, glm, and MICE functions in R. A two-tailed p value of less than 0.05 was considered statistically significant.
3. Results
3.1. Basic Characteristics of the Sample
First, we conducted a basic statistical description of the 6740 participants included in the study, of whom 2404 (35.67%) were female and 4336 (64.33%) were male, and 68.12% of the participants were aged 80 and above, and 73.19% of the participants lived in urban areas. There were 530 participants with low IVF, 2003 with moderate frequency, and 4207 with high frequency.
The results of the difference analyses showed that under different indoor ventilation frequencies, there were significant statistical differences (p < 0.05) between different genders, residences, ages, household income, living arrangements, marital status, manual labor before retirement, exercise, BMI, distance of residence from the main road, house types, air cleaning devices, and types of cooking fuel. Specifically, among females, aged 65–79, living in urban areas, with a household income of ≥ 30,000, living with family, married, no manual labor before retirement, having exercise, with a BMI between 24 and 28, living in bungalows, with a distance of residence from the main road ≥ 200 m, no air cleaning devices, and nonclean energy for cooking, the proportion of those with high IVF is relatively high. Other detailed results are shown in Table 1.
| Variables | Total (n = 6740) | Low IVF (n = 530) | Intermediate IVF (n = 2003) | High IVF (n = 4207) | Statistic | p |
|---|---|---|---|---|---|---|
| Gender, n (%) | χ2 = 11.76 | 0.003 | ||||
| Female | 2404 (35.67) | 181 (7.53) | 658 (27.37) | 1565 (65.10) | ||
| Male | 4336 (64.33) | 349 (8.05) | 1345 (31.02) | 2642 (60.93) | ||
| Age, n (%) | χ2 = 9.08 | 0.011 | ||||
| 65–79 | 2149 (31.88) | 138 (6.42) | 646 (30.06) | 1365 (63.52) | ||
| ≥ 80 | 4591 (68.12) | 392 (8.54) | 1357 (29.56) | 2842 (61.90) | ||
| Residence, n (%) | χ2 = 83.18 | < 0.001 | ||||
| Rural | 1807 (26.81) | 198 (10.96) | 635 (35.14) | 974 (53.90) | ||
| Urban | 4933 (73.19) | 332 (6.73) | 1368 (27.73) | 3233 (65.54) | ||
| Household income, n (%) | χ2 = 6.90 | 0.032 | ||||
| < 30,000 | 2838 (42.11) | 219 (7.72) | 892 (31.43) | 1727 (60.85) | ||
| ≥ 30,000 | 3902 (57.89) | 311 (7.97) | 1111 (28.47) | 2480 (63.56) | ||
| Education, n (%) | χ2 = 2.72 | 0.606 | ||||
| 0 year | 2761 (40.96) | 234 (8.48) | 814 (29.48) | 1713 (62.04) | ||
| 1–6 years | 1655 (24.55) | 125 (7.55) | 487 (29.43) | 1043 (63.02) | ||
| ≥ 7 years | 2324 (34.48) | 171 (7.36) | 702 (30.21) | 1451 (62.44) | ||
| Living arrangements, n (%) | χ2 = 25.22 | < 0.001 | ||||
| Living with family | 5715 (84.79) | 411 (7.19) | 1693 (29.62) | 3611 (63.18) | ||
| Other | 1025 (15.21) | 119 (11.61) | 310 (30.24) | 596 (58.15) | ||
| Marital status, n (%) | χ2 = 8.47 | 0.014 | ||||
| Widowed/divorced/spinsterhood | 3835 (56.90) | 333 (8.68) | 1121 (29.23) | 2381 (62.09) | ||
| Married | 2905 (43.10) | 197 (6.78) | 882 (30.36) | 1826 (62.86) | ||
| Manual labor before retirement, n (%) | χ2 = 38.35 | < 0.001 | ||||
| No | 1824 (27.06) | 94 (5.15) | 499 (27.36) | 1231 (67.49) | ||
| Yes | 4916 (72.94) | 436 (8.87) | 1504 (30.59) | 2976 (60.54) | ||
| Smoking, n (%) | χ2 = 2.69 | 0.261 | ||||
| No | 5379 (79.81) | 435 (8.09) | 1581 (29.39) | 3363 (62.52) | ||
| Yes | 1361 (20.19) | 95 (6.98) | 422 (31.01) | 844 (62.01) | ||
| Drinking, n (%) | χ2 = 1.09 | 0.579 | ||||
| No | 5509 (81.74) | 439 (7.97) | 1624 (29.48) | 3446 (62.55) | ||
| Yes | 1231 (18.26) | 91 (7.39) | 379 (30.79) | 761 (61.82) | ||
| Exercise, n (%) | χ2 = 109.95 | < 0.001 | ||||
| No | 4404 (65.34) | 395 (8.97) | 1458 (33.11) | 2551 (57.92) | ||
| Yes | 2336 (34.66) | 135 (5.78) | 545 (23.33) | 1656 (70.89) | ||
| BMI, n (%) | χ2 = 14.84 | 0.022 | ||||
| < 18.5 | 1290 (19.14) | 120 (9.30) | 375 (29.07) | 795 (61.63) | ||
| 18.5–23.9 | 3442 (51.07) | 284 (8.25) | 1030 (29.92) | 2128 (61.82) | ||
| 24–27.9 | 1524 (22.61) | 90 (5.91) | 444 (29.13) | 990 (64.96) | ||
| ≥ 28 | 484 (7.18) | 36 (7.44) | 154 (31.82) | 294 (60.74) | ||
| Hypertension, n (%) | χ2 = 3.03 | 0.219 | ||||
| No | 3878 (57.54) | 320 (8.25) | 1167 (30.09) | 2391 (61.66) | ||
| Yes | 2862 (42.46) | 210 (7.34) | 836 (29.21) | 1816 (63.45) | ||
| Diabetes, n (%) | χ2 = 0.79 | 0.673 | ||||
| No | 5830 (86.50) | 465 (7.98) | 1728 (29.64) | 3637 (62.38) | ||
| Yes | 910 (13.50) | 65 (7.14) | 275 (30.22) | 570 (62.64) | ||
| Heart disease, n (%) | χ2 = 4.30 | 0.117 | ||||
| No | 5429 (80.55) | 444 (8.18) | 1618 (29.80) | 3367 (62.02) | ||
| Yes | 1311 (19.45) | 86 (6.56) | 385 (29.37) | 840 (64.07) | ||
| Dementia, n (%) | χ2 = 2.87 | 0.238 | ||||
| No | 5742 (85.19) | 439 (7.65) | 1703 (29.66) | 3600 (62.70) | ||
| Yes | 998 (14.81) | 91 (9.12) | 300 (30.06) | 607 (60.82) | ||
| Arthritis, n (%) | χ2 = 1.81 | 0.405 | ||||
| No | 6114 (90.71) | 489 (8.00) | 1810 (29.60) | 3815 (62.40) | ||
| Yes | 626 (9.29) | 41 (6.55) | 193 (30.83) | 392 (62.62) | ||
| Rheumatism, n (%) | χ2 = 0.49 | 0.784 | ||||
| No | 6366 (94.45) | 502 (7.89) | 1886 (29.63) | 3978 (62.49) | ||
| Yes | 374 (5.55) | 28 (7.49) | 117 (31.28) | 229 (61.23) | ||
| Mold exposure, n (%) | ||||||
| No | 5827 (86.45) | 456 (7.83) | 1743 (29.91) | 3628 (62.26) | χ2 = 0.79 | 0.672 |
| Yes | 913 (13.55) | 74 (8.11) | 260 (28.48) | 579 (63.42) | ||
| Distance of residence from the main road, n (%) | χ2 = 12.44 | 0.002 | ||||
| < 200 m | 3141 (46.60) | 225 (7.16) | 994 (31.65) | 1922 (61.19) | ||
| ≥ 200 m | 3599 (53.40) | 305 (8.47) | 1009 (28.04) | 2285 (63.49) | ||
| House type, n (%) | χ2 = 361.88 | < 0.001 | ||||
| Detached house | 3705 (54.97) | 405 (10.93) | 2023 (54.60) | 1277 (34.47) | ||
| Bungalow | 667 (9.90) | 57 (8.55) | 359 (53.82) | 251 (37.63) | ||
| Apartment | 2368 (35.13) | 68 (2.87) | 1825 (77.07) | 475 (20.06) | ||
| Air cleaning devices, n (%) | χ2 = 6.67 | 0.036 | ||||
| No | 597 (8.86) | 35 (5.86) | 163 (27.30) | 399 (66.83) | ||
| Yes | 6143 (91.14) | 495 (8.06) | 1840 (29.95) | 3808 (61.99) | ||
| Concentrations of PM2.5, n (%) | ||||||
| < 40.2 μg/m3 | 1476 (21.90) | 128 (8.67) | 417 (28.25) | 931 (63.08) | χ2 = 7.11 | 0.310 |
| 40.2–51.1 μg/m3 | 1100 (16.32) | 79 (7.18) | 356 (32.36) | 665 (60.45) | ||
| 51.1–60.0 μg/m3 | 2023 (30.01) | 157 (7.76) | 586 (28.97) | 1280 (63.27) | ||
| ≥ 60.0 μg/m3 | 2141 (31.77) | 166 (7.75) | 644 (30.08) | 1331 (62.17) | ||
| Concentrations of NO2, n (%) | χ2 = 3.72 | 0.715 | ||||
| < 10.0 μg/m3 | 1361 (20.19) | 104 (7.64) | 405 (29.76) | 852 (62.60) | ||
| 10.0–19.8 μg/m3 | 1445 (21.44) | 121 (8.37) | 449 (31.07) | 875 (60.55) | ||
| 19.8–31.4 μg/m3 | 2040 (30.27) | 151 (7.40) | 602 (29.51) | 1287 (63.09) | ||
| ≥ 31.4 μg/m3 | 1894 (28.10) | 154 (8.13) | 547 (28.88) | 1193 (62.99) | ||
| Type of cooking fuel, n (%) | χ2 = 130.55 | < 0.001 | ||||
| Nonclean energy | 2952 (43.80) | 156 (5.28) | 736 (24.93) | 2060 (69.78) | ||
| Clean energy | 3788 (56.20) | 374 (9.87) | 1267 (33.45) | 2147 (56.68) |
- Abbreviations: χ2, chi-square test; BMI, body mass index; IVF, indoor ventilation frequency.
3.2. Association Between IVF and IADL
Logistic regression results indicated an apparent relationship between IVF and IADL disability in Chinese older adults, and detailed results are shown in Table 2. In Model 1, which did not include any covariates, compared with moderate and high indoor ventilation frequencies, the risk of disability with IADL was reduced, respectively, by 35.6% (OR = 0.644, 95% CI: 0.517–0.803) and 43.9% (OR = 0.561, 95% CI: 0.455–0.691) under the low indoor ventilation. In Model 4, which adjusted all the covariates, the risk of having an IADL disability decreased by 33.8% (OR = 0.662, 95% CI: 0.507–0.864) and 42.6% (OR = 0.574, 95% CI: 0.444–0.742). From Model 1 to Model 4, as more covariates were added, the effect of ventilation frequency on IADL disability changed slightly. Moreover, we used IVF as the dependent variable and IADL as the independent variable; the results of the multifactorial logistic regression analyses (Table S2) showed that older adults with IADL disabilities were more likely to have lower IVF (moderate IVF: OR = 0.648, 95% CI: 0.497–0.845; high IVF: OR = 0.560, 95% CI: 0.434–0.723).
| Model | Low IVF | Intermediate IVF | High IVF |
|---|---|---|---|
| OR (95% CI) | |||
| Model 1 | ref. | 0.644 (0.517, 0.803) ∗∗∗ | 0.561 (0.455, 0.691) ∗∗∗ |
| Model 2 | ref. | 0.661 (0.511, 0.856) ∗∗ | 0.515 (0.402, 0.658) ∗∗∗ |
| Model 3 | ref. | 0.660 (0.508, 0.858) ∗∗ | 0.572 (0.444, 0.736) ∗∗∗ |
| Model 4 | ref. | 0.662 (0.507, 0.864) ∗∗ | 0.574 (0.444, 0.742) ∗∗ |
- Note: Model 1: crude model. Model 2: adjusted for age, gender, residence, marital status, living arrangements, household income, and education. Model 3: further add manual labor before retirement, drinking, smoking, exercise, distance of residence from the main road, house type, air cleaning devices, type of cooking fuel, and mold exposure. Model 4: further add BMI, hypertension, diabetes, heart disease, dementia, arthritis, rheumatism, concentrations of PM2.5, and concentrations of NO2.
- Abbreviations: CI, confidence interval; IVF, indoor ventilation frequency; OR, odds ratio; ref.: reference.
- ∗∗p < 0.01. ∗∗∗p < 0.001.
3.3. Analysis of PSM Results
We further matched 1056 participants using PSM (Table S3). Among them, there were 680 males (64.39%) and 376 females (35.61%). The PSM results showed that the SMD between groups was less than 0.1, indicating that the groups were balanced. In addition, as shown in Figure 2, the data distribution after PSM was more balanced. We further analyzed the association between IVF and IADL in the matched dataset (Table S4). The results showed that after adjusting for all confounding factors, the association between IVF and IADL remained significant (OR = 0.619, 95% CI: 0.436–0.877).
3.4. Correlation Between Seasonal IVF and IADLs
We further explored the relationship between IVF in different seasons and IADL disability. The results showed the association between IVF and IADL only in summer and winter (Figure S1). In summer, compared to low IVF, high IVF reduced the risk of IADL disability by 43.8% (OR = 0.562, 95% CI: 0.345–0.915). In winter, the risk of IADL disability was reduced by 20.0% (OR = 0.800, 95% CI: 0.666–0.959) and 25.6% (OR = 0.744, 95% CI: 0.617–0.896) for moderate and high indoor ventilation frequencies compared to low IVF. The above results emphasized the importance of opening windows for ventilation in summer and winter.
3.5. Subgroup Analyses and Interaction Analyses
The results of the subgroup analyses and interaction analyses are shown in Figure 3. The results of subgroup analyses showed that there were significant associations between IVF and IADL disability in different genders, different ages, living in urban areas, different household incomes, education ≤ 6 years, living with family, being married, different manual labor before retirement, no smoking, no drinking, no exercise, different BMI classifications, no hypertension, different diabetes conditions, no heart disease, no dementia, no arthritis, no rheumatism, no mold exposure, different housing types, with a distance of residence from the main road < 200 m, having air cleaning devices, different uses of clean energy, PM2.5 ≥ 60.0 μg/m3, and different NO2 exposure levels (p < 0.05). Interaction analyses indicated that drinking significantly modified the relationship between IVF and IADL disability (p for interaction < 0.05).
3.6. Sensitivity Analyses
We completed two sensitivity analyses to ensure the robustness of the results. (1) We used a logistic regression model to test the randomness of the missing data [31]. Figure S2 shows the distribution of variables with missing data in our study. Since the probability of missing data was significantly associated with the observed variables, we considered the missing data to follow the missing at random (MAR) mechanism. Based on the above conclusion, we further used the chained-equation multiple imputation method to compensate for the information loss caused by directly excluding samples due to data missingness. Multiple chain equation imputation utilizes the conditional distribution relationships between variables to iteratively impute variables with missing data [32]. The results showed that in Model 4, which adjusted for all covariates, the risk of IADL disability was reduced by 29.8% (OR = 0.702, 95% CI: 0.598–0.825) and 32.8% (OR = 0.672, 95% CI: 0.575–0.786) for moderate and high indoor ventilation frequencies compared to low IVF, respectively (Table S5). (2) Older adults with dementia were excluded before conducting the correlation analyses, as those with dementia often report data with significant bias. The results showed that in Model 4, which adjusted for all covariates, the risk of IADL disability was reduced by 33.6% (OR = 0.664, 95% CI: 0.506–0.870) and 42.2% (OR = 0.578, 95% CI: 0.446–0.750) for moderate and high IVF compared to low IVF, respectively (Table S6). The results of these two sensitivity analyses both indicate a significant and stable statistical association between IVF and IADL. In addition, we used the E value to assess the effect of unmeasured confounding factors. E value (1.26) indicated that unmeasured confounders had a slight impact on the association between IVF and IADL.
4. Discussion
The results suggested that there is a significant statistical association between IVF and IADL disability in Chinese older adults aged 65 and above. Ventilation is a key factor in regulating indoor air pollutant levels. Good ventilation can effectively reduce the concentrations of indoor volatile organic compounds (VOCs), PM2.5, NO2, and other pollutants by introducing fresh outdoor air and expelling stale indoor air. Most VOCs have unpleasant odors that are toxic and irritating, and the indoor volatile organic compounds are the ones that humans come into contact with the most [33]. When the concentration of VOCs in a room reaches a certain level, it can cause symptoms such as nasal congestion, coughing, and headache. The resulting cellular damage may even lead to abnormal neuronal function, influencing the transmission of nerve signals and causing serious consequences for the brain and nervous system, such as memory loss [34]. Certain VOCs can also interfere with the body’s normal hormonal balance [35], and the disruption of the endocrine system can influence various physiological processes such as metabolism. Hormonal imbalances can lead to issues such as physical fatigue and mood swings [36], influencing the daily activities of older adults. Good indoor ventilation reduces VOC concentrations, which helps maintain the stability of the endocrine system, thereby benefiting the maintenance of IADL abilities in older adults. Previous studies have indicated that the frequency of indoor ventilation is associated with the physical health of older adults, including aspects such as cognition and depression [7, 8]. This association may be attributed to the fact that opening windows for ventilation can reduce indoor air pollution caused by the use of solid fuels. Additionally, prior research has demonstrated the relationship between the use of solid fuels and disability or physical function among older adults [37]. The combustion of solid fuels can release various harmful air pollutants such as carbon monoxide, PM2.5, and nitrogen oxides [38], and long-term exposure to polluted environments can influence older adults’ health. Due to the small size of PM2.5, it can penetrate deeper into the respiratory system, leading to a decline in lung function [39]. Additionally, inhaled PM2.5 can irritate the respiratory tract and cause inflammatory responses in the respiratory system, worsening the condition of asthma patients [39]. Previous studies have confirmed that cognitive function plays an important role in IADL disability [40], and toxic compounds adsorbed on PM2.5 can reach the brain and influence neurons, leading to central nervous system inflammation and impacting cognitive function [41]. Research indicates that NO2 increases pneumonia mortality rates in older adults. NO2 increases susceptibility to bacterial pathogens by damaging epithelial cells and reducing mucociliary clearance, thereby increasing the risk of pneumonia [42]. Additionally, long-term exposure to NO2 environments can have negative effects on the heart. A study found that for every 13 μg/m3 increase in NO2 levels per year, cardiovascular deaths increase by 13% [43]. When indoor air circulation is poor, these pollutants tend to accumulate inside the home, creating a potential health threat. However, in the absence of outdoor air pollution and favorable weather, indoor ventilation can improve indoor air quality and decrease pollutants effectively [44]. Studies have shown that only natural ventilation can lower indoor particulate matter by 80%–90% [45], opening a 30-cm window and a 10-cm door for 30 min lowers indoor CO2 concentration up to about 1/3 and in about 1 h up to about 1/10, and adding the number of openings is more effective than adding the degree of the opening window and door in the same area reduction [46]. Therefore, ventilation strategies need to be flexibly adjusted based on outdoor air quality. Moreover, our research also found a significant bidirectional relationship between IVF and IADL. Older adults with limited IADL may reduce the frequency of opening windows or maintenance of mechanical ventilation systems due to their limited mobility, leading to the accumulation of indoor pollutants (such as PM2.5 and VOCs), which further damages heart and lung functions. Conversely, frequent ventilation may maintain or enhance IADL abilities by improving indoor air quality, reducing inflammatory responses, and mitigating neurobehavioral damage.
The results indicated an apparent association between the frequency of indoor ventilation and IADL in summer and winter, and this finding had important public health significance. Many research reports indicated that air quality was related to the seasonal variations of many air pollutants [47, 48]. Ozone, as one of the air pollutants, typically reaches its peak concentration in summer [49]. The coexistence of ozone and high temperatures has a particularly significant impact on the health of older adults. A study found that long-term exposure to ozone environments increased the risk of death from respiratory diseases [50]. In addition, high temperature and high humidity are typical climatic characteristics of summer. Although opening windows for ventilation will introduce hot and humid air from outside, it helps with the exchange of indoor and outdoor air, alleviating the stuffiness indoors to some extent. If windows are not opened for ventilation for a long time, high temperature and humidity limit the evaporation of human sweat, and prolonged exposure to higher humidity increases the risk of cardiovascular disease and coronary heart disease [51], which in turn might influence IADL capacity. For instance, cardiovascular diseases may lead to a decline in the physical endurance of older adults, making it difficult for them to perform activities that require a certain level of physical strength, such as shopping and cooking. A high ventilation frequency can promptly expel humid indoor air, reducing humidity and minimizing adverse effects on older adults’ health, thereby lowering the risk of IADL disability. At the same time, high ventilation frequency can effectively reduce the concentration of indoor pollutants such as ozone [52], thereby decreasing the risk of respiratory diseases caused by long-term exposure to ozone environments and indirectly maintaining the IADL abilities of older adults. In winter, when the temperature is low, people tend to close doors and windows tightly to keep indoors warm, which leads to low indoor air circulation and accumulation of harmful substances. Opening windows may introduce cold air from outside, causing a sharp drop in indoor temperature. For vulnerable groups such as older adults, their tolerance to low temperatures is poor, and low-temperature stimuli can trigger vasoconstriction [53], increasing the burden on the heart and potentially leading to the onset of cardiovascular diseases. The unstable state of cardiovascular diseases can severely influence the IADL abilities of older adults, making it more difficult for them to perform daily living activities. High ventilation frequency reduces the irritation of harmful substances to the respiratory tract by improving indoor air quality and lowers the risk of respiratory infections, indirectly protecting the cardiovascular system of older adults and improving their IADL abilities. In addition, some people use wood stoves as heating equipment in winter. A study in the United States indicated that in indoor environments heated with wood stoves, the concentration of PM2.5 significantly increased. Such high concentrations of indoor air pollution can have adverse effects on human health [54]. Therefore, appropriate opening of windows for ventilation is crucial for maintaining IADL capacity in older adults.
Subgroup analyses indicated that the association between IVF and IADL was heterogeneous in each subgroup. We observed a significant association between IVF and IADL in both female and male groups. Female over 65 years old experience significant changes in their psychological and physiological state with aging. At this stage, females may be going through or have gone through menopause, and the decline in estrogen levels in the body not only influences the reproductive system but also has widespread repercussions on many aspects of the mind and body. Psychologically, they may be more prone to mood swings, anxiety, depression, and other emotional problems, and their interest and participation in daily life may decline [55]. Physiologically, there is a progressive decline in bone health, muscle strength, and function of the cardiovascular system, increasing the risk of falls and chronic diseases [56, 57]. These changes further influence their ability to perform IADL. For males, some studies have indicated that sex steroids promote muscle function, and androgens may be the main sex steroids regulating male muscle homeostasis [19]. Previous studies have confirmed that with increasing age, the physical function and mobility of older adults significantly reduce with normal aging [58, 59]. Our research also found a significant association between IVF and IADL in the 65–79 age group and the ≥ 80 age group. This may be because ventilation can have a positive impact on IADL across different age groups by improving respiratory health, supporting cognitive function, and enhancing immunity. In the population aged 80 and above, despite the decline in physiological functions, ventilation can still indirectly improve IADL by reducing pathogen exposure and the risk of acute episodes of chronic diseases [60]. In our research, we observed a significant statistical association between IVF and IADL among urban residents. Cities are hot spots for air pollution. Urban residents have relatively closed indoor environments with poor air circulation due to living in high buildings. In addition, urban residents who live at a fast pace and work under high pressure may neglect the importance of indoor ventilation. Being in a confined environment for a long time may have a negative impact on psychological states, such as feeling anxious and depressed, which in turn influences IADL ability. In the study by Jing Du et al. [12], it was found that the frequency of indoor ventilation also impacts the health status of rural residents. However, the specific mechanisms underlying this effect require further investigation. Some studies suggest that the level of education can influence the cognitive function of older adults, meaning that the higher the level of education, the higher the level of cognitive function [61]. We observed a significant association between IVF and IADL in the education of 0–6 years. This may be because individuals with low education levels have limited cognitive reserves, making them more prone to executive function and memory decline when exposed to a large amount of air pollutants due to poor ventilation, thereby reducing their cognitive abilities required for managing finances, shopping, and other IADLs. We observed a significant association between IVF and IADL in the group living with family. The hypothalamic–pituitary–adrenal axis is an important neuroendocrine regulatory system in the human body, which secretes hormones such as cortisol under stress conditions [62]. Long-term exposure to an environment of loneliness and lack of care leads to the hypothalamic–pituitary–adrenal axis being continuously activated in older adults, resulting in elevated cortisol levels [63]. High levels of cortisol can have a negative impact on hippocampal outcomes and cognitive function [64], thereby influencing the ability to perform IADLs. At the same time, due to the decline in their physical functions, older adults often find it difficult to independently carry out ventilation activities such as opening windows [65]. In the case of living with family, older adults are more likely to receive attention and care from their family members, including good ventilation conditions. This good ventilation environment helps improve the living conditions of older adults, thereby having a positive impact on their IADL abilities, which in turn makes the association between IVF and IADL evident in this group. In the married group, we found a significant statistical association between the frequency of indoor ventilation and IADL. Studies have shown that married women report better mental health, especially in terms of anxiety, insomnia, and depression, compared to single women [66]. Married men have a relatively lower risk of hypertension compared to unmarried men [67]. It can be seen that the physical and mental health of married individuals is relatively better, which may drive them to pursue a higher quality of life and be more likely to recognize the importance of indoor ventilation in improving air quality. As a result, they are more likely to take proactive ventilation measures to reduce the impact of indoor air pollution. We observed a significant association between IVF and IADL in the nonsmoking group. This might be due to the fact that in smokers, tobacco smoke becomes the dominant source of pollution [68], and the effects of toxic components (such as acrolein) far exceed the emission reduction effect of improved ventilation, leading to the masking of the association between IVF and IADL. In the subgroup of chronic diseases (diabetes, hypertension, and heart disease), we observed a statistical association between IVF and IADL in the group without diabetes, hypertension, or heart disease. The potential complications and adverse effects of diabetes as a chronic disease may extend to the patient’s ability to perform daily living tasks. Some studies suggested that diabetes advances the onset of IADL disability by 7 years [69]. This suggests we should pay more attention to the overall health management of diabetic patients to minimize the impairment of their ability to perform IADL. In the subgroup of rheumatism and arthritis, we found a statistically significant difference in the relationship between IVF and IADL among older adults without rheumatism or arthritis. Although IADL function continuously declines with the aging of older adults, the IADL impairment is more severe in older adults with rheumatism or arthritis [70]. If not treated promptly, it may restrict the older adults’ daily activities and lead to physical problems such as joint deformities. There is a statistical association between IVF and IADL among people with indoor air purifiers. Air purifiers can improve indoor air quality and reduce the levels of air pollutants generated by cooking with solid fuels [71], thereby having a positive impact on reducing IADL disabilities. Previous studies have shown that house type is associated with changes in physical activity among older adults [72]. Our study also found that IVF and IADL showed significant associations in the subgroups of detached houses, apartments, and bungalows. This may be related to the characteristics of the living environment of these house types and their impact on residents’ behavior and health. Detached houses, apartments, and bungalows usually have better ventilation conditions and residents’ ability to independently control their living environment. For example, independent houses often have more windows and more spacious areas [73], which facilitate natural ventilation. Good ventilation can improve indoor air quality and reduce the accumulation of pollutants and pathogens, thereby lowering the risk of residents falling ill and enhancing their overall health. Our analyses determined that IVF has a significant protective effect on IADL in the context of increased PM2.5 concentrations. During periods of high pollutant exposure, enhanced ventilation can reduce indoor pollutant concentrations by improving air exchange [19], thereby lowering pollutant levels and demonstrating measurable protective effects. Furthermore, we observed a significant association and interaction between IVF-IADL and the drinking status of the drinking population. Related research has found that long-term alcohol consumption can influence emotional and behavioral changes in older adults, while increasing IVF may reduce the risk of depression symptoms in older adults with regular drinking habits [22]. Compared to nondrinkers, drinkers exhibit higher smoking rates and longer indoor exposure [19], and their IADL may be more easily influenced by changes in ventilation. This means that maintaining a healthy lifestyle away from excessive alcohol in the long term has a positive impact on reducing or delaying the difficulties or disabilities that older adults may face when performing complex daily tasks (such as shopping, managing finances, and using the phone) [74].
5. Conclusion
To our knowledge, this is the first time that a large nationally representative sample has been used to explore the association between IVF and IADL disability in older adults. The research observed that a higher frequency of opening windows for ventilation was significantly associated with a lower risk of IADL disability, but the causal explanation of this association depends on further verification through longitudinal studies or intervention trials. Further seasonal analyses revealed an association between IVF and IADL disability only during summer and winter. Moreover, the relationship between IVF and IADL varies across different subgroups. This suggests that, when conducting policies on IVF as an intervention to improve IADL in older adults, strategies should be more targeted in terms of seasonal and subgroup characteristics. At the same time, we should also pay more attention to the ventilation conditions of older adults who already have IADL disabilities to improve their quality of life. Specifically, the government can use various channels such as community publicity and social media to educate older adults about the importance of ventilation and the correct methods of ventilation, such as choosing appropriate times to open windows for ventilation and ensuring proper ventilation when using air conditioning. At the same time, communities and nursing homes should establish regular indoor air quality monitoring mechanisms to promptly identify and address ventilation issues. For older adults with IADL disabilities living at home, community staff can regularly check the use of ventilation devices and provide necessary maintenance and replacement services. The government can increase support for home ventilation guarantees for older adults with IADL disabilities, thereby improving their living environment quality.
6. Limitations
Our study also has some limitations. First, our research results have only established the association between IVF and IADL. The causal relationship needs to be clarified in further cohort or intervention studies. Second, during the process of including variables and deleting missing data, there may be selection bias. Third, the data for independent variables, dependent variables, and covariates all come from self-reported questions, which may introduce certain recall biases and social desirability biases. Although previous studies have demonstrated the reliability of retrospective measurement issues [12], we have also tested the robustness of the results by excluding patients with dementia, but these biases cannot be ignored. Meanwhile, different diagnostic criteria (such as dementia and IADL) may all lead to certain error rates. In future studies, the use of more precise diagnostic results should be considered. Fourth, although we have considered numerous covariates to control for the influence of confounding factors, due to the limitations of secondary data, there are still some possible factors that have not been taken into account, such as ventilation frequency measurements (window size, opening duration, outdoor wind direction and speed), environment (community environment, duration of housing use, some outdoor pollutants), care support, cultural variables (such as regional differences in climate, urban vs. rural settings, and cultural practices around ventilation), and behavioral factors (such as cultural norms, perceived risks, physical limitations, personal preferences for ventilation, concerns about the safety of opening windows, and physical limitations that hinder window opening). Although our further calculations of the E values have indicated that other factors have a lower impact, it is still worthwhile to collect the original data of these variables in future research and further explore them using qualitative methods. Finally, our research conclusions are only applicable to Chinese older adults. Considering the cultural and environmental differences in global ventilation practices, the applicability of these conclusions in other countries should be further verified.
Ethics Statement
This study was conducted with the approval of the ethics committee at the Biomedical Ethics Committee of Peking University (IRB00001052–13074). All participants were included in the study after providing written informed consent.
Consent
The authors have nothing to report.
Conflicts of Interest
The authors declare no conflicts of interest.
Author Contributions
Xiaobing Xian: writing—original draft, writing—review and editing, supervision. Xiaoli Fan: data curation, writing—original draft. Xiaoyu Wang: validation, writing—review and editing. Shiwei Cao: formal analysis, methodology. Xiaowei Wei: resources, data curation. Yue Zhang: resources, validation. Kun Shen: conceptualization, project administration, validation.
Funding
No funding was received for this manuscript.
Open Research
Data Availability Statement
Publicly available datasets were analyzed in this study. This data can be found here: https://opendata.pku.edu.cn/dataverse/CHADS.
