By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

Worldwide wealth

While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

The middle-class

The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

In G20 countries, the share of the population that earned at least the equivalent of the highest 10 percent of global income earners as of 2022 in purchasing power parity (PPP) terms varies from over two thirds in Australia to only 1.5 percent in Indonesia. The United States recorded the second-highest upper-class share of the G20 countries. However, looking at for instance China, approximately 80 percent of the population counts as middle class or above, whereas just eight percent counts as upper class or higher.

The dataset is a file of the raw interview scripts with my interviewees during the fieldwork conducted between 2021.6 to 2022.2.

This thesis investigates how urban middle-class working women with two children make sense of work, childcare, and self under the universal two-child policy of China. This thesis also explores how the idea of individual and family interact in these women's construction of a sense of self. On January 1st, 2016, the one-child policy was replaced by the universal two-child policy, under which all married couples in China are allowed to have two children. In the scholarships of motherhood, it is widely documented across cultures that it is a site of patriarchal oppression where women are expected to meet the unrealistic ideal of intensive mothering to be a good mother, suffer from the motherhood wage penalty and face more work-family conflict than fathers. Emprical studies of China also came to similar conclusions and such findings are not only widely regonized in scholarship but is also widespread in popular discourse in China. Despite that marriage and having children is still universal for the generation of the research target, women born in the 1970s and 1980s, due to compounding influence fo the one-child policy, increasing financial burden of raising a child etcs, having only one child has become widely acceptable and normal. Given this context, this study intend to investigate how these middle-class women, who are relatively empowered and resourceful, come to a decision that is seemingly against their own interest. Moreover, unlike in the west where the issue of childbearing and childcaring is mainly an issue of the conjugal couple and the gender realtions is at the center of the discussion, in China, extended family, especially grandparents also play a role in both the decision making process and the subsequent childcare arrangement. Therefore, to study the second-time mothers’ childcare and work experiences in contemporary urban China, we also need to situate them, as individuals, in their family. To investigate how they make sense of childcare and work is also to understand the tension between individual and family. By interviewing twenty-one parents from middle-class family in Guangzhou with a second child under six years old, this study finds that these urban working women with two children consider themselves as an individual unit and full-time paid employment is something that cannot be given up since it is the means of securing that independent self . However, they did not prioritize their personal interest to that of other family members, especially the elder child and thus the decision of having a second child is mainly for the sake of the elder child. Moreover, grandparents played an essential role to provide a childcare safety net, without which, these urban working women would not be able to work full-time and maintain the independent self as they defined it. The portrayal of these women’s experiences reflected the individualization process in China where people are indivdualized without individualism, and family are evoked as strategy to achieve personal as well as family goals. The findings of this study contributs to theories of motherhood by adding an intergenerational perspective to the existing gender perspective and also contributes to the studies of family by understanding the relation and interaction between individual and family in thse women’s construction of sense of self in the context of contemporary China.

Graph and download economic data for Population, Total for Lower Middle Income Countries (SPPOPTOTLLMC) from 1960 to 2023 about income and population.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Middle Taylor Township, Pennsylvania, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Middle Taylor township did not include 7-person households. Across the different household sizes in Middle Taylor township the mean income is $85,708, and the standard deviation is $32,607. The coefficient of variation (CV) is 38.04%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $28,975. It then further increased to $85,290 for 6-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/middle-taylor-township-pa-median-household-income-by-household-size.jpeg" alt="Middle Taylor Township, Pennsylvania median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Middle Taylor township median household income. You can refer the same here

Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2023 about personal income, personal, median, income, and USA.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Middle Smithfield Township, Pennsylvania, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Middle Smithfield township did not include 7-person households. Across the different household sizes in Middle Smithfield township the mean income is $88,416, and the standard deviation is $27,838. The coefficient of variation (CV) is 31.49%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $40,453. It then further increased to $80,329 for 6-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/middle-smithfield-township-pa-median-household-income-by-household-size.jpeg" alt="Middle Smithfield Township, Pennsylvania median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Middle Smithfield township median household income. You can refer the same here

About this dataset

Context

The dataset presents median household incomes for various household sizes in Middle Point, OH, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Middle Point did not include 5, or 7-person households. Across the different household sizes in Middle Point the mean income is $61,920, and the standard deviation is $18,851. The coefficient of variation (CV) is 30.44%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $39,408. It then further increased to $60,801 for 6-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/middle-point-oh-median-household-income-by-household-size.jpeg" alt="Middle Point, OH median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Middle Point median household income. You can refer the same here

The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple generalized theoretical model for establishing social hierarchy via pair-wise interactions between individuals and investigate its stability. In each interaction or fight, the probability of “winning” depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters. The first parameter represents how much can be lost, and the second parameter represents the degree to which even a small difference of status can guarantee a win for the higher-status individual. Depending on the parameters, the resulting status distributions reach either a continuous unimodal form or lead to a totalitarian end state with one high-status individual and all other individuals having status approaching zero. However, we find that in the latter case long-lived intermediary distributions often exist, which can give the illusion of a stable society. As we show, our model allows us to make predictions consistent with animal interaction data and their evolution over a number of years. Moreover, by implementing a simple, but realistic rule that restricts interactions to sufficiently similar-status individuals, the stable or long-lived distributions acquire high-status structure corresponding to a distinct high-status class. Using household income as a proxy for societal status in human societies, we find agreement over their entire range from the low-to-middle-status parts to the characteristic high-status “tail”. We discuss how the model provides a conceptual framework for understanding the origin of social hierarchy and the factors which lead to the preservation or deterioration of the societal structure.

Analysis of ‘ Decomposing World Income Distribution Database’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://datacatalog.worldbank.org/search/dataset/0041692/ on 21 November 2021.

--- Dataset description provided by original source is as follows ---

Using national income and expenditure distribution data from 119 countries, the authors decompose total income inequality between the individuals in the world, by continent and by "region" (countries grouped by income level). They use a Gini decomposition that allows for an exact breakdown (without a residual term) of the overall Gini by recipients. Looking first at income inequality in income between countries is more important than inequality within countries. Africa, Latin America, and Western Europe and North America are quite homogeneous continent, with small differences between countries (so that most of the inequality on these continents is explained by inequality within countries). Next the authors divide the world into three groups: the rich G7 countries (and those with similar income levels), the less developed countries (those with per capita income less than or equal to Brazil's), and the middle-income countries (those with per capita income between Brazil's and Italy's). They find little overlap between such groups - very few people in developing countries have incomes in the range of those in the rich countries.

--- Original source retains full ownership of the source dataset ---

India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

About this dataset

Context

The dataset presents median household incomes for various household sizes in Middle Inlet, Wisconsin, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Middle Inlet town did not include 6, or 7-person households. Across the different household sizes in Middle Inlet town the mean income is $78,798, and the standard deviation is $36,711. The coefficient of variation (CV) is 46.59%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $28,854. It then further increased to $125,251 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/middle-inlet-wi-median-household-income-by-household-size.jpeg" alt="Middle Inlet, Wisconsin median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Middle Inlet town median household income. You can refer the same here

In 2020, around 36 million people in Vietnam had average daily spending of 11 U.S. dollars to 30 U.S. dollars, while four million of them were classified as being in the established consuming class, spending between 30 U.S. dollars to 70 U.S. dollars per day. By 2030, according to the forecast, there will be around two million people living in Vietnam with a daily spending budget exceeding 70 U.S. dollars.

Cambodia Mthly Av H/Hold Income: Urban: Middle Fifth data was reported at 516.000 KHR/Person th in 2021. This stayed constant from the previous number of 516.000 KHR/Person th for 2020. Cambodia Mthly Av H/Hold Income: Urban: Middle Fifth data is updated yearly, averaging 516.000 KHR/Person th from Jun 2020 (Median) to 2021, with 2 observations. The data reached an all-time high of 516.000 KHR/Person th in 2021 and a record low of 516.000 KHR/Person th in 2021. Cambodia Mthly Av H/Hold Income: Urban: Middle Fifth data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Cambodia – Table KH.H002: Monthly Household Income: per Capita.

By the middle of the 1990s, Indonesia had enjoyed over three decades of remarkable social, economic, and demographic change and was on the cusp of joining the middle-income countries. Per capita income had risen more than fifteenfold since the early 1960s, from around US$50 to more than US$800. Increases in educational attainment and decreases in fertility and infant mortality over the same period reflected impressive investments in infrastructure. In the late 1990s the economic outlook began to change as Indonesia was gripped by the economic crisis that affected much of Asia. In 1998 the rupiah collapsed, the economy went into a tailspin, and gross domestic product contracted by an estimated 12-15%-a decline rivaling the magnitude of the Great Depression. The general trend of several decades of economic progress followed by a few years of economic downturn masks considerable variation across the archipelago in the degree both of economic development and of economic setbacks related to the crisis. In part this heterogeneity reflects the great cultural and ethnic diversity of Indonesia, which in turn makes it a rich laboratory for research on a number of individual- and household-level behaviors and outcomes that interest social scientists. The Indonesia Family Life Survey is designed to provide data for studying behaviors and outcomes. The survey contains a wealth of information collected at the individual and household levels, including multiple indicators of economic and non-economic well-being: consumption, income, assets, education, migration, labor market outcomes, marriage, fertility, contraceptive use, health status, use of health care and health insurance, relationships among co-resident and non- resident family members, processes underlying household decision-making, transfers among family members and participation in community activities. In addition to individual- and household-level information, the IFLS provides detailed information from the communities in which IFLS households are located and from the facilities that serve residents of those communities. These data cover aspects of the physical and social environment, infrastructure, employment opportunities, food prices, access to health and educational facilities, and the quality and prices of services available at those facilities. By linking data from IFLS households to data from their communities, users can address many important questions regarding the impact of policies on the lives of the respondents, as well as document the effects of social, economic, and environmental change on the population. The Indonesia Family Life Survey complements and extends the existing survey data available for Indonesia, and for developing countries in general, in a number of ways. First, relatively few large-scale longitudinal surveys are available for developing countries. IFLS is the only large-scale longitudinal survey available for Indonesia. Because data are available for the same individuals from multiple points in time, IFLS affords an opportunity to understand the dynamics of behavior, at the individual, household and family and community levels. In IFLS1 7,224 households were interviewed, and detailed individual-level data were collected from over 22,000 individuals. In IFLS2, 94.4% of IFLS1 households were re-contacted (interviewed or died). In IFLS3 the re-contact rate was 95.3% of IFLS1 households. Indeed nearly 91% of IFLS1 households are complete panel households in that they were interviewed in all three waves, IFLS1, 2 and 3. These re-contact rates are as high as or higher than most longitudinal surveys in the United States and Europe. High re-interview rates were obtained in part because we were committed to tracking and interviewing individuals who had moved or split off from the origin IFLS1 households. High re-interview rates contribute significantly to data quality in a longitudinal survey because they lessen the risk of bias due to nonrandom attrition in studies using the data. Second, the multipurpose nature of IFLS instruments means that the data support analyses of interrelated issues not possible with single-purpose surveys. For example, the availability of data on household consumption together with detailed individual data on labor market outcomes, health outcomes and on health program availability and quality at the community level means that one can examine the impact of income on health outcomes, but also whether health in turn affects incomes. Third, IFLS collected both current and retrospective information on most topics. With data from multiple points of time on current status and an extensive array of retrospective information about the lives of respondents, analysts can relate dynamics to events that occurred in the past. For example, changes in labor outcomes in recent years can be explored as a function of earlier decisions about schooling and work. Fourth, IFLS collected extensive measures of health status, including self-reported measures of general health status, morbidity experience, and physical assessments conducted by a nurse (height, weight, head circumference, blood pressure, pulse, waist and hip circumference, hemoglobin level, lung capacity, and time required to repeatedly rise from a sitting position). These data provide a much richer picture of health status than is typically available in household surveys. For example, the data can be used to explore relationships between socioeconomic status and an array of health outcomes. Fifth, in all waves of the survey, detailed data were collected about respondents¹ communities and public and private facilities available for their health care and schooling. The facility data can be combined with household and individual data to examine the relationship between, for example, access to health services (or changes in access) and various aspects of health care use and health status. Sixth, because the waves of IFLS span the period from several years before the economic crisis hit Indonesia, to just prior to it hitting, to one year and then three years after, extensive research can be carried out regarding the living conditions of Indonesian households during this very tumultuous period. In sum, the breadth and depth of the longitudinal information on individuals, households, communities, and facilities make IFLS data a unique resource for scholars and policymakers interested in the processes of economic development.

IntroductionDigital interventions are increasingly regarded as a potential solution for the inaccessibility of mental health treatment across low-and-middle-income settings, especially for common mental disorders. Step-by-Step (SbS) is a digital, guided self-help intervention for depression found effective in two Randomized Controlled Trials (RCTs) in Lebanon. For research implementation and further scale-up, this paper reports the results of a qualitative evaluation of SbS among the Lebanese and others and displaced Syrians in Lebanon.MethodsThirty-four Key Informant Interviews (KIIs) were executed with participants of the RCTs, SbS staff members, and external stakeholders. Questions garnered feedback about the feasibility, acceptability, enabling factors, and barriers to adhering to the research, implementation, and the SbS intervention. A thematic analysis was conducted using NVivo, and key themes, topics, and recommendations, on research methods and the intervention itself, were generated and reported.ResultsResults showed a high level of acceptability of SbS among Lebanese and Syrians and identified sub-groups for whom acceptance or use might be lower, such as older adults and people with limited access to the internet or smartphones. Furthermore, interviews identified the main enabling factors and barriers to adherence related to the research design, content, and delivery approach. Barriers related to feasibility included lengthy assessments as part of the RCTs, and mistrust related to delays in study compensations. Other common challenges were forgetting login credentials, poor internet connection, being busy and competing needs. Enabling factors and best practices included motivating participants to use the intervention through the weekly support provided by helpers, setting an oral contract for commitment, and dividing the compensations into several installments as part of the RCTs. Recommendations regarding sustainability were given.DiscussionThe findings show that overall, SbS is feasible, acceptable, and much needed in Lebanon among the Lebanese and Syrians. This assessment identifies reasons for low adherence to the research and the intervention and presents improvement solutions. Recommendations generated in this paper inform the upscale of SbS and the planning, design, and implementation of future digital interventions in research and service provision settings in the mental health field.

This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

In 2023, inflation severely impacted on Italians belonging to the lower middle-class and to the working class. Almost half of the lower middle-class members reduced spending on shopping, energy and leisure. The majority of the underclass individuals more evidently adopted new purchasing practices. More than 70 percent of the citizens diminished unnecessary shopping and limited energy consumption, while, surprisingly, 60 percent of them curtailed grocery shopping. This latter measure impacted on only 40 percent of the lower-middle class and 15 percent of the middle-class. Hence, Italians with some economic resources preferred not cutting spending on groceries, and only the poorest resorted to this choice. However, two out of five members of the middle-class had to reduce general shopping and electricity consumption.

In the 3 years to March 2021, black households were most likely out of all ethnic groups to have a weekly income of under £600.

Table 4. The average monetary expenditures (€/a) of the no-cars group and the motorized on transport and the overall annual expenditures among the middle-income segment. Abstract The relationship between urban form and greenhouse gas (GHG) emissions has been studied extensively during the last two decades. The prevailing paradigm arising from these studies is that a dense or compact urban form would best enable low-carbon living. However, the vast majority of these studies have actually concentrated on transportation and/or housing energy, whereas a growing number of studies argue that the GHG implications of other consumption should be taken into account and the relationships evaluated. With this two-part study of four different area types in Finland we illustrate the importance of including all the consumption activities into the GHG assessment. Furthermore, we add to the discussion the idea that consumption choices, or lifestyles, and the resulting GHGs are not just a product of the values of individuals but actually tied to the form of the surrounding urbanization: that is, lifestyles are situated. In part I (Heinonen et al 2013 Environ. Res. Lett. 8 025003) we looked into this situation in Finland, showing how the residents of the most urbanized areas bring about the highest GHG emissions due to their higher consumption volumes and the economies-of-scale advantages in the less urbanized areas. In part II here, we concentrate only on the middle-income segment and look for differences in the lifestyles when the budget constraints are equal. Here we also add the variables housing type and motorization into the assessment. The same time-use and private expenditure data as in part I and the same GHG assessment method are used here to maintain high transparency and comparability between the two parts. The results of the study imply that larger family sizes and economies-of-scale effects in the less dense areas offset the advantages of more dense living when the emissions are assessed on per capita basis. Also, at equal income levels the carbon footprints vary surprisingly little due to complementary effects of the majority of low-carbon lifestyle choices. Motorization was still found to increase the emissions, but a similar pattern regarding housing type was not found.