# The Combined Effect of Indoor Air Quality and Socioeconomic Factors on Health in Northeast China
## 4 Discussion
### Strengths and Limitations  
This study was successful in its approach, resulting in an association model between the residential indoor air quality, socioeconomic factors, and health based on the'real-world' data (field measurement data). The model reflected the combined effect of residential indoor air quality and socioeconomic factors on health. Moreover, indoor air quality and socioeconomic factors were measured by the combination of multiple factors.  
However, some limitations in this study should be noted. First, the model results may not reflect all residential indoor environment conditions in Northeast China because of the sampling error. In fact, it is difficult to carry out the large-scale measurement of residential indoor environment because of the privacy and funding. Considering the lifestyle of residents and climate in Northeast China was partly similar, this study selected 81 residences in six densely populated cities. Second, the measurement of occupants' health status was only performed by self-reporting. There are differences between respondents' self-reported health and their actual health status. But self-reported health is a widely used measure to predict health outcomes [57]. It has been consistently shown to predict morbidity and mortality, even after accounting for objective health status, behavioral risk  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Item** & **Content** & **SES\(\rightarrow\)Health** & **IAQ\(\rightarrow\)Health** & **SES\(\rightarrow\)IAQ** \\ \hline \multirow{4}{*}{Gender} & Men & 0.427 & 0.217 & 0.337 \\  & Women & 0.318 & 0.114 & 0.304 \\  & Average & 0.373 & 0.166 & 0.321 \\  & SD & 0.055 & 0.052 & 0.017 \\ \hline \multirow{4}{*}{Age} & \(\leq\)30 years & 0.427 & 0.141 & 0.440 \\  & 30 \(\sim\) 50 years & 0.381 & 0.116 & 0.343 \\  & \(\geq\)50 years & 0.405 & 0.210 & 0.295 \\  & Average & 0.404 & 0.156 & 0.359 \\  & SD & 0.023 & 0.040 & 0.060 \\ \hline \multirow{4}{*}{Length of residence} & \(<\)5 years & 0.467 & 0.173 & 0.333 \\  & 5–10 years & 0.454 & 0.136 & 0.374 \\ \cline{1-1}  & \(>\)10 years & 0.354 & 0.107 & 0.336 \\ \cline{1-1}  & Average & 0.408 & 0.138 & 0.347 \\ \cline{1-1}  & SD & 0.062 & 0.029 & 0.029 \\ \cline{1-1}  & The initial model & 0.413 & 0.105 & 0.381 \\ \hline \hline \end{tabular} Note: SES— socioeconomic status; IAQ— indoor air quality; SD—standard deviation “\(\rightarrow\)”—direction of the effect.  
\end{table}
Table 6: The distributions of path coefficients for gender, age, and length of residence.  
factors, and sociodemographic characteristics [58], and mortality is considered as the most objective measurement of the general health of an individual [59]. Moreover, self-rated health has been found to be a reliable measurement of general health, since respondents rated the same general health assessment within a period where their health was unlikely to change [60]. However, it should be noted that health effects are seldom momentaneous. Most effects do not appear at the first exposure and do not disappear immediately after the exposure stops. The same was true for the 'health effects' measured in this study. Hence, there may be a risk that this study overestimated factors which would not change in a short time (such as socioeconomic factors) compared with those which would change over time (such as indoor air pollution factors). This problem will be considered in future studies. In addition, it is necessary to emphasize that this study identified the association model between residential indoor air quality, socioeconomic factors and self-reported health using the SEM method. But the association is not synonymous with causality. The causality of identified relations should also be confirmed in future research.