In this study, we aimed to investigate the association between SES and MetS among adults in Nanjing, China, indicated with education and FAI. We stratify the analyses by gender because of the gender differences in the relationship between SES and MetS prevalence(11, 14). This study found that the prevalence of MetS was 19.7% in Nanjing and MetS was more prevalent in men compared to women (24.6% vs 15.1%). After controlling for covariates, we found a positive association between SES and the presence of MetS, that participants, with higher educational attainment or within higher FAI were less likely to have MetS compared to counterparts from a lower SES group. The negative associations have found between SES and components of MetS and in both genders.
Some of our findings, such as the gender difference in prevalence of MetS, differ to those from other study in China. Their results showed women had a significantly higher prevalence of MetS than men(12–14, 28), while we found that males were more likely to develop MetS compared to females, which is line with a few studies from HICs such as Korea (11). The reasons for this difference may be due to the differences in the definition of MetS, especially the option of the cut-off points of WC (< 80cm vs < 85cm for women).
This study found negative associations between individual educational level and family income per capita and MetS, which is line with a few studies from Beijing, China and Korea(10, 11, 14). However, a study in Jiangsu province, China which collected data from residents aged 35 to 74 in 2002, observed a positive relationship between FAI level and MetS(12). This variability in the risk of MetS was also documented in a study that conducted in a rural area of Shanxi province, China(13). Previous studies have found that the direction of the relationship between SES, especially FAI, and MetS differs globally depending on the stage of the social and economic development(11–14, 24). It is found that the pattern between SES and MetS changed from positive in developing areas to negative in developed societies. Our results suggested that the pattern in Nanjing were more in line with the city in developed societies.
The possible mechanisms behind the association between SES and MetS included that: (1) unhealthy lifestyles and behaviours such as unhealthy eating and insufficient physical activity; (2) inadequate access to health care resources; (3) illiteracy, and (4) psychological stress(29). It is apparent that different distributions of the risk factors across different SES groups changed at different stages of socioeconomic development. Several studies have shown that people with lower SES tend to be more likely to consume high-dense energy foods, to do insufficient physical activity and to be obese compared with their counterparts with high SES in developed societies(30–33), whereas in developing areas, compared to the residents with higher SES, those with lower SES are less likely to do these unhealthy behaviours and to be obese(34, 35). This may partly account for the different patterns of relationship between SES and MetS in different areas.
The SES disparity might change with social and economic development in developing countries, particularly in China, the most populous developing country in the world, which has been experiencing a great transition for economic and social structure. Therefore, it is necessary to well understand the SES-MetS relationship at different development stages, and this would help develop tailored public health implications for population-based MetS prevention for China and other developing countries. Then, the effectiveness of the population-based MetS prevention strategies can be conducted in vulnerable groups.
There were several strengths in this study. First, the data collection, as well as blood sample analysis, based on robust objective measures, standard methods and instruments. Second, the sample size of this study was large enough to identify sufficient cases of MetS. Third, the sensitive indicators of SES, education and FAI, were used to examine the relationship between SES and MetS. Finally, recognized potential confounders, including clustering effects by study areas, were considered in analysis.
The limitations of this study included: (1) since our study was a cross-sectional survey, no causal inferences could be drew; (2) the information about SES was self-reported, which might cause potential recall bias. However, the recall bias can be controlled to a great extent through taking a larger sample size in our study. In addition, as the indicators were categorized into thirds prior to analysis, any imprecise information provided by participants is likely to have had a minor effect on analysis.
In conclusion, education and family average income each was inversely related to MetS and its components prevalence in Nanjing, China, at the present stage of social and economic development. The findings of our study have important public health implications for population-based MetS prevention. That is, the tailored prevention strategies should be implemented for people with different socioeconomic status.