To our knowledge, this is the first multilevel modelling study from any developing country to study the effects of neighbourhood formality and neighbourhood SES on self-rated health in trying to understand health inequalities between men and women. We found little evidence of clustering of poor SRH at the neighbourhood level. However, neighbourhood socioeconomic status (as measured by the number of household items owned) and formality were associated with the SRH of women but not men.
We found that as a proportion of the total variation, the variation between neighbourhoods in poor/normal self-rated health for females and males was small and non-significant. This is similar to what has been observed in other multilevel studies from western countries
We found that one measure of neighbourhood socioeconomic status (average number of household items owned) to be associated with SRH, as shown in previous research
[1, 2]. However, only in females were the relationship between neighbourhood average item ownership and SRH statistically significant. The results from this study support the notion that the place where a person lives in Aleppo affects men and women in different ways similar to high income countries
[25–29]. For example, in the UK Stafford et al.(2005) found that a range of neighbourhood characteristics, such as the socio-political environment, amenities, the physical environment and economic characteristics were more consistently associated with women’s self-rated health than of men’s
. However, the results here support results from an earlier study from Aleppo on individual determinants of SRH in men and women, which showed that individual socioeconomic status was a more important predictor of SRH in women compared to men
We postulate that the gender differences observed in this study in the health effects of neighbourhood SES can be explained by gender roles. In turn, gender roles in Aleppo are influenced by the culture of the largely traditional Muslim society, where the segregation of men and women is paralleled by a separation of social knowledge and the way they occupy their environment. Women in this setting are more likely to be economically inactive and are more likely to spend time in their home and neighbourhood doing domestic work. This in turn makes them more vulnerable to the effects of their local environment
[28, 29]. Additionally, our results show that formality was a significant predictor of women’s but not men’s self-rated health. All things being equal, a woman was more likely to have poor SRH if she lived in a formal neighbourhood than in an informal neighbourhood. It is important to understand the mechanisms behind this finding, given the poor environmental quality and limited neighbourhood resources and services in informal areas
[8, 13]. Is there something else in the characteristics of informal areas that make them protective of women’s self-rated health? The neighbourhoods that make up the informal zones in this study tended to be poorer with a relatively small spread of average household items, median 2.3, range 1.5 to 2.7 (inter-quartile range 2.0 to 2.4); whereas the neighbourhoods in the formal zone tended to be wealthier but with a wider spread of average items, median 3.0 range 2.0 to 5.4 (inter-quartile range 2.8 to 3.6) but with only 2 formal neighbourhoods with <2.5 items on average. Therefore, formality and neighbourhood SES, as measured by average item ownership, are closely related but remain independent measures (i.e. there is a part of formality that is not explained by neighbourhood SES). Could it be that neighbourhood formality is measuring another neighbourhood characteristic that has more influence on women’s health? Or is it that the larger socioeconomic inequality in formal areas compared to the informal exerts an influence on women’s health? These are questions that need to be addressed in further qualitative research from this setting.
Limitations and strengths
Firstly, this is a secondary analysis of cross-sectional data and hence it was not possible to consider changes over time in the explanatory or outcome variables. It therefore potentially suffers from the problem of self-selection, whereby people are selected into residential areas based on unmeasured individual characteristics that are relevant to health
[30, 31]. Findings from previous studies in the West show that people’s ratings of health depends on current health status as well as on changes over time in relation to socioeconomic status, chronic disease, functional disability and mental health
[32, 33]. Although the AHS included information on functional disability and chronic disease, these variables were not included in our analysis since these are measures which are highly correlated with self-rated health. Additionally, cross-sectional surveys do not include longitudinal and historical data on neighbourhoods which interact with, and are heavily influenced by, a multitude of macro-level factors such as social, cultural, economic and policy contexts of states
[34, 35]. They also change over time as a result of societal processes such as economic cycles or demographic shifts and migration
. This is a particular issue for informal areas, which may change on a day to day basis. The study also lacked data on neighbourhood SES which are not available in Syria. In the absence of such information the importance of contextual SES has been assessed by aggregating individual level indicators from the survey data to the neighbourhood level. For some neighbourhoods, aggregate SES measures were therefore based on the responses of only a few participants (as noted in the Results section, the lower quartile for achieved neighbourhood size was 9 for females and 10 for males). Such averaging of data from very few respondents might have introduced measurement error into the estimation of our neighbourhood level estimates. To explore the impact of these ‘small’ neighbourhoods on the estimation of the fixed effects at the neighbourhood level, the analyses were repeated omitting neighbourhoods with <10 respondents. The resultant final model ORs for neighbourhood level average item ownership were the same to one decimal place. Other authors have encountered similar numerical issues
. Those authors also observed a stronger relationship between an individual outcome variable and an aggregated contextual level variable than between the outcome variable and the corresponding individual level variable (as we do here for self-reported health and neighbourhood average item ownership among females). We conclude, like them, that this may represent a genuine contextual effect. However, further research via simulation studies, is needed to investigate the utility of aggregated neighbourhood level variables as measures of contextual effects. A further limitation of this study is the low statistical power to estimate between neighbourhood variation, mainly as a result of the small number of individuals available within a high proportion of the neighbourhoods
[31, 38, 39]. This may explain why as a proportion of the total variation, variation between neighbourhoods in poor/normal self-rated health for females and males was estimated from the model to be small and non-significant.
Despite these limitations, this study is unique in that it considers neighbourhood informality status which is a relevant neighbourhood characteristic for the health of urban residents in developing countries. Therefore, by using an integral measure of neighbourhood (defined as a feature of an area only measurable at an ecological level of neighbourhood) this study has avoided relying solely on a derived neighbourhood measure such as SES which is based on the aggregate characteristics of individuals
Additional strengths of this study include the way in which neighbourhoods were operationalised. Whist formal and informal areas correspond to administrative units that are defined by the local government, the way the neighbourhoods were measured corresponds to smaller, more homogenous clusters or units that are more likely to match people’s perceptions of their local neighbourhoods and hence could be more related to the way they rate their health
[2, 35]. Another strength of this study was the inclusion in the analysis of correlates of SRH, such as social support, physical activity and smoking status, that have been found to vary by gender in Aleppo