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This study investigated the associations between income, income-associated social identify, health and mass incidents in Chongqing, a Chinese city. A representative sample of mass-incident participants from Chongqing, aged 18 years and over, participated using a questionnaire. In addition, the public servants working in letters and visit offices were invited to participate in the study. A sample of 2,000 officers working in letter and visit offices, with 1,938 returns, represented a high response rate 96.9%. Of the 480 mass-incident participants, 465 (88%) surveys were usable. Logistic regression analysis was used to estimate the relationship between income and poor-to-fair health status; all individual-level variables (i.e. age, sex, marital status, education, and type of job) were included in the model.

Income displayed significant linkages to self-rated health. Most participants are farmers and most of them are from low socioeconomic areas and status; in urban area and southeast of Chongqing region, military and unemployed consisted of the majority of mass-incident participants. The sense of identity of these people is having impaired employment opportunities, having unsuitable housing arrangements and living in a deprived community with a low socioeconomic level in comparison with other areas and provinces in China.

Income is a significant predictor of poor health outcome. This is linked to the sense of identity. This deprivation can challenge the cultural identity of individuals who, they feel, they are inferior in socioeconomic terms to others who own resources, powers and wealth. Income as an indicator of social inequality revealed its significant predictive role in the occurrence of mass incidents through its impact on sense of deprivation. Further follow-up study is needed to determine the causal relationship between income and social identity.

The association between income distribution and measures of health has been well established such that societies with smaller income differences between rich and poor people have increased longevity (Wilkinson, 1996). While more egalitarian societies tend to have better health, in most developed societies people lower down the social scale have death rates two to four times higher than those nearer the top. Inequities in income distribution and the consequent disparities in health status are particularly problematic for many women, including single mothers, older women, and women of colour. The feminization of poverty is the rapidly increasing proportion of women in the adult poverty population (Doyal, 1995; Fraser, 1987).

A number of multidimensional poverty measures that respect the ordinal nature of dimensions have recently been proposed within the counting approach framework. Besides ensuring a reduction in poverty, however, it is important to monitor distributional changes to ensure that poverty reduction has been inclusive in reaching the poorest. Distributional issues are typically captured by adjusting a poverty measure to be sensitive to inequality among the poor. This approach, however, has certain practical and conceptual limitations. It conflicts, for example, with some policy-relevant measurement features, such as the ability to decompose a measure into dimensions post-identification and does not create an appropriate framework for assessing disparity in poverty across population subgroups. In this chapter, we propose and justify the use of a separate decomposable inequality measure – a positive multiple of “variance” – to capture the distribution of deprivations among the poor and to assess disparity in poverty across population subgroups. We demonstrate the applicability of our approach through two contrasting inter-temporal illustrations using Demographic Health Survey data sets for Haiti and India.

This paper examines several measures of poverty and hardship for the United States to illustrate how a single measure of poverty may identify different groups of people as “in need.” Individuals and families may encounter difficulty meeting needs on many dimensions and there are a variety of measures designed to identify those who experience poverty or difficulty making ends meet. In general, there is agreement that all of the approaches capture different pieces of the puzzle while no single indicator can yield a complete picture. To understand this multidimensional aspect of poverty, several measures are examined in this paper: the official U.S. poverty measure, a relative poverty measure, a new supplemental measure that follows recommendations of the U.S. National Academy of Sciences (NAS), an index of material hardship, a measure of household debt, and responses to a question about inability to meet expenses. This study uses the 2008 panel of the Survey of Income and Program Participation (SIPP) and updates a similar analysis that used the 1996 panel of SIPP (Short, 2005). The SIPP is a longitudinal survey that allows us to examine all of these various indicators for the same people over the period from 2009 to 2010. The study uses regression analysis to assess the relationship among several indicators of economic hardship. Results suggest that an understanding of relationships between various indicators can allow only one indicator of poverty alone to be interpreted more appropriately and used more wisely to target the needs of the disadvantaged.