A substantial body of evidence suggests that indoor mold exposure is a cause of allergic and respiratory diseases in humans. While models exist for assessing the risk of mold growth on building materials, few study the characteristics of mold growth after germination. This study conducted mold growth experiments in a constant temperature chamber, using four temperature settings of 15, 20, 25 and 30 °C, and three relative humidities of 56 to 61%, 75 to 76% and 83 to 86%. A mold growth prediction model was established using temperature and relative humidity. The accuracy of the model was verified by comparing the sampling and the predicted values in a laboratory environment. The results indicated that reducing the environmental temperature and relative humidity could significantly inhibit the growth of mold, although the inhibitory effects varied. Temperature might play a more critical role. At higher temperatures (25 °C and 30 °C), the growth rate and lag time of mold tended to be consistent and there were differences in the maximum diameter. In the predictive model, the polynomial secondary model for the maximum growth rate and lag time and the Arrhenius–Davey secondary model for the maximum diameter (A) had good predictive effects (Adj.R² > 0.850). It is speculated that temperature is the key factor affecting the maximum growth diameter of mold. The mold growth prediction model could better predict the growth of mold in actual environments without wind Adj.R² > 0.800), but the accuracy of the model decreased under windy conditions (wind velocity < 1 m/s). The mold growth predictive model we established could be used to predict the growth characteristics of mold in windless environments. It also provides control suggestions for the regulation of temperature and relative humidity in indoor environments, supporting indoor thermal environment management and pollutant control, and ensuring indoor human health.

Indoor heating methods may influence the prevalence of respiratory and allergic diseases among preschool children. However, limited research has explored the relationship between indoor heating methods and childhood illnesses over time or on a large urban scale, and particularly the relationship between heating methods and asthma or allergic rhinitis among preschoolers from 2010 to 2019. This study conducted cross-sectional investigations in two northern cities (Taiyuan and Urumqi) and two southern cities (Chongqing and Changsha) in China during two periods: Period I (2010) and Period II (2019). Using Pearson’s chi-squared tests, we analyzed the associations between four indoor heating methods—convective heating (CH), convective and radiant heating (CH&RH), radiant heating (RH), and polluting heating (PH)—and nine respiratory and allergic diseases. Logistic regression models were employed to explore the relationships between heating methods and disease prevalence. The results revealed substantial differences in heating method choices between northern and southern Chinese cities (p < 0.001). These differences were significantly associated with the prevalence of respiratory and allergic diseases in preschoolers. Heating behaviors may have contributed to a decrease in the lifetime prevalence of asthma, pneumonia, rhinitis, and the 12-month prevalence of eczema in preschool children. In southern households, CH was linked to a lower risk of lifetime asthma (AOR: 0.63) and 12-month wheezing (AOR: 0.53). However, RH in southern households increased disease risks (AOR: 0.53). This study provides insights into the associations between heating methods and the prevalence of diseases among preschoolers across two periods in China. The findings offer new perspectives and guidance for families in selecting appropriate heating methods.

Environmental differences between climate zones may affect arthritis risk. This study aims to explore how winter HVAC use impacts arthritis symptoms in young older adults across four Chinese cities: Chongqing, Beijing, Guangzhou, and Kunming. We surveyed 3579 participants aged 60–74 and used partial least squares-structural equation modeling (PLS-SEM) to explore relationships between HVAC habits, indoor environmental exposure, and arthritis outcomes. Results reveal that distinct climate-specific HVAC usage patterns and their differing relationships with indoor environmental exposures and arthritis symptoms. In Beijing, widespread heating is linked to fewer symptoms (28.6%), while greater reliance on air conditioning or ventilation in humid southern cities corresponds to higher prevalence (33.3–44.9%). The favorable association between HVAC habits and arthritis outcomes was strongest in Beijing, whereas the adverse association between indoor environmental exposures and arthritis was strongest in Chongqing. Mediation analysis suggested that these associations were largely explained through indoor environmental conditions, particularly reduced cold exposure (72.32% in Chongqing) and reduced damp exposure (44.71% in Guangzhou). The strength of this indirect association varied across cities, ranking as Chongqing > Guangzhou > Beijing > Kunming. These findings highlight the importance of climate-responsive HVAC strategies and suggest that improving indoor environmental conditions may support healthier ageing in winter.