## 3 Results
### Correlation Analysis: Key Variables  
Table 3 presents the Pearson correlation analyses that were performed to assess the relationship between six demographic and socio-economic variables, two housing and living conditions items, five environmental variables, two overall satisfaction items, and two health measures. The mean value of the physical health scores (PCS) was 52.22 \(\pm\) 6.28, and the mean score for mental health (MCS) was 50.14 \(\pm\) 9.97. The correlation analysis showed a significant negative correlation (\(p\) < 0.01) between overall air quality and thermal satisfaction, with both PCS (\(r\) = \(-\)0.250; \(r\) = \(-\)0.126) and MCS (\(r\) = \(-\)0.293; \(r\) = \(-\)0.192) emphasising the importance of IEQ for residents' health. This underscores the critical need for interventions aimed at enhancing air quality and thermal comfort within this setting to improve health outcomes. Additionally, alcohol consumption was negatively correlated (\(p\) < 0.01) with PCS (\(r\) = \(-\)0.145) and MCS (\(r\) = \(-\)0.127), suggesting that higher alcohol consumption may be associated with poorer health. Conversely, it was positively correlated with overall thermal (\(r\) = 0.173) and air quality (\(r\) = 0.130) satisfaction, indicating that individuals with higher alcohol consumption might have differing perceptions or use of alcohol as a coping mechanism for environmental dissatisfaction. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Variable** & **Item** & **\% of Respondents (n = 431)** \\ \hline \multirow{2}{*}{Responses by floor level} & 1–4 & 72.9 \\  & \(\geq\)9 & 27.1 \\ \hline \multirow{4}{*}{Frequency of personally adjusted items} & 1 item & 32.3 \\  & 2 items & 35.5 \\ \cline{1-1}  & 3 items & 16 \\ \cline{1-1}  & 4 items & 12.5 \\ \cline{1-1}  & 5 items & 3.2 \\ \cline{1-1}  & 7 items & 0.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Characteristics of built environment conditions in surveyed social housing. \begin{table}
\begin{tabular}{l c c c c c c c c c c c c c c c} \hline  & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** & **11** & **12** & **13** & **14** & **15** \\ \hline Age & 1 & & & & & & & & & & & & & & \\ Gender & 0.085 & 1 & & & & & & & & & & & & & & \\ Smo\_stat & 0.123* & \(-\)0.404** * & 1 & & & & & & & & & & & & \\ All\_stat & 0.163* & \(-\)0.217* & \(\pm\)0.495* * & 1 & & & & & & & & & & \\ Emp.stat & 0.043 & 0.160** & \(-\)0.014 & 0.018 & 1 & & & & & & & & & \\ Edu\_stat & 0.083 & 0.067 & 0.005 & 0.074 & 0.171** & 1 & & & & & & & \\ L\_during & 0.225** & 0.064 & \(-\)0.033 & 0.074 & \(-\)0.007 & \(-\)0.009 & 1 & & & & & & & \\ H\_floor & \(-\)0.034 & \(-\)0.040 & 0.008 & \(-\)0.041 & 0.007 & 0.069 & \(-\)0.042 & 1 & & & & & & \\ Num\_Tcontrol & \(-\)0.102 & 0.067 & 0.030 & \(-\)0.004 & \(-\)0.075 & \(-\)0.013 & \(-\)0.002 & 0.041 & 1 & & & & & \\ OS\_T & 0.068 & \(-\)0.040 & 0.068 & 0.173* & 0.025 & \(-\)0.039 & 0.015** * & 0.012 & \(-\)0.029 & 1 & & & & \\ Num\_Tdis & 0.040 & \(-\)0.030 & 0.099* & 0.069 & \(-\)0.030 & 0.017 & 0.022 & 0.078 & 0.260** * & 0.156** * & 1 & & & \\ CS\_AQ & 0.066 & 0.047 & \(-\)0.037 & 0.130** * & \(-\)0.021 & 0.014 & 0.155** * & \(-\)0.003 & \(-\)0.045 & 0.430** * & 0.185** * & 1 & & \\ Num\_Qdo & \(-\)0.087 & 0.005 & \(-\)0.009 & \(-\)0.012 & \(-\)0.054 & 0.012 & \(-\)0.082 & 0.027 & 0.197* & \(-\)0.132* & \(-\)0.204** * & 0.032 & 1 & \\ PCS & \(-\)0.234* & 0.028 & \(-\)0.184* & \(-\)0.145* & \(-\)0.080 & 0.039 & \(-\)0.067 & \(-\)0.004 & 0.008 & \(-\)0.126** * & \(-\)0.100** * & \(-\)0.250** * & 0.043 & 1 & \\ MCS & 0.025 & \(-\)0.028 & \(-\)0.019 & \(-\)0.122* & 0.037 & 0.039 & \(-\)0.103* & 0.001 & 0.019 & \(-\)0.192** * & \(-\)0.007 & \(-\)0.293* & \(-\)0.032 & 0.165** * & 1 \\ \hline \end{tabular}
\end{table} 
Table 3: Correlation analysis between 15 variables, including demographic and socio-economic, housing and environmental conditions, and health status (n = 431).