In India, the share of the population that earned at least the equivalent of the highest ** percent of global income earners as of 2022 in purchasing power parity (PPP) terms was ** percent. Hyderabad topped the list with the highest share of middle-class and above category of consumers. Cities from south India topped the list with the first four ranks, followed by the national capital, Delhi.

In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

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).

This dataset is one which highlights the demographics of Upper-Middle Class people living in Gachibowli, Hyderabad, India and attempts to, through various methods of statistical analysis, establish a relationship between several of these demographic details.

In the financial year 2021, the number of super-rich households earning more than ** million Indian rupees went up to **** million from **** million in the financial year 2016. This was an annual growth of **** percent. The number is expected to grow to over **** million in the financial year 2031 and ** million households in the financial year 2047. This will be the fastest growth across all income categories. On the other hand, destitute classified Indian households with earnings of less than *** thousand annually decreased only marginally to ***** million in financial year 2021 from **** million in 2016. However, it is estimated that the number of destitute households will fall to just *** million by the financial year 2047.

Key information about Russia Household Income per Capita

• Russia Annual Household Income per Capita reached 8,179.123 USD in Dec 2024, compared with the previous value of 7,549.747 USD in Dec 2023.
• Russia Annual Household Income per Capita data is updated yearly, available from Dec 1992 to Dec 2024, with an averaged value of 5,882.623 USD.
• The data reached an all-time high of 9,660.697 USD in Dec 2013 and a record low of 183.584 USD in Dec 1992.
• In the latest reports, Retail Sales of Russia grew 5.200 % YoY in Dec 2024.

In the financial year 2021, the average annual saving of rich households in India was over *** thousand Indian rupees, a stark contrast to destitute category which saved only five thousand Indian rupees. The middle-class saved almost *** thousand Indian rupees annually. During the year, a rich household spent almost ** times that of a destitute household, eight times that of an aspirer household, and almost three times that of a middle-class household.

75% of households from the Bangladeshi ethnic group were in the 2 lowest income quintiles (after housing costs were deducted) between April 2021 and March 2024.

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.

Abstract (en): The Research on Early Life and Aging Trends and Effects (RELATE) study compiles cross-national data that contain information that can be used to examine the effects of early life conditions on older adult health conditions, including heart disease, diabetes, obesity, functionality, mortality, and self-reported health. The complete cross sectional/longitudinal dataset (n=147,278) was compiled from major studies of older adults or households across the world that in most instances are representative of the older adult population either nationally, in major urban centers, or in provinces. It includes over 180 variables with information on demographic and geographic variables along with information about early life conditions and life course events for older adults in low, middle and high income countries. Selected variables were harmonized to facilitate cross national comparisons. In this first public release of the RELATE data, a subset of the data (n=88,273) is being released. The subset includes harmonized data of older adults from the following regions of the world: Africa (Ghana and South Africa), Asia (China, India), Latin America (Costa Rica, major cities in Latin America), and the United States (Puerto Rico, Wisconsin). This first release of the data collection is composed of 19 downloadable parts: Part 1 includes the harmonized cross-national RELATE dataset, which harmonizes data from parts 2 through 19. Specifically, parts 2 through 19 include data from Costa Rica (Part 2), Puerto Rico (Part 3), the United States (Wisconsin) (Part 4), Argentina (Part 5), Barbados (Part 6), Brazil (Part 7), Chile (Part 8), Cuba (Part 9), Mexico (Parts 10 and 15), Uruguay (Part 11), China (Parts 12, 18, and 19), Ghana (Part 13), India (Part 14), Russia (Part 16), and South Africa (Part 17). The Health and Retirement Study (HRS) was also used in the compilation of the larger RELATE data set (HRS) (N=12,527), and these data are now available for public release on the HRS data products page. To access the HRS data that are part of the RELATE data set, please see the collection notes below. The purpose of this study was to compile and harmonize cross-national data from both the developing and developed world to allow for the examination of how early life conditions are related to older adult health and well being. The selection of countries for this study was based on their diversity but also on the availability of comprehensive cross sectional/panel survey data for older adults born in the early to mid 20th century in low, middle and high income countries. These data were then utilized to create the harmonized cross-national RELATE data (Part 1). Specifically, data that are being released in this version of the RELATE study come from the following studies: CHNS (China Health and Nutrition Study) CLHLS (Chinese Longitudinal Healthy Longevity Survey) CRELES (Costa Rican Study of Longevity and Healthy Aging) PREHCO (Puerto Rican Elderly: Health Conditions) SABE (Study of Aging Survey on Health and Well Being of Elders) SAGE (WHO Study on Global Ageing and Adult Health) WLS (Wisconsin Longitudinal Study) Note that the countries selected represent a diverse range in national income levels: Barbados and the United States (including Puerto Rico) represent high income countries; Argentina, Cuba, Uruguay, Chile, Costa Rica, Brazil, Mexico, and Russia represent upper middle income countries; China and India represent lower middle income countries; and Ghana represents a low income country. Users should refer to the technical report that accompanies the RELATE data for more detailed information regarding the study design of the surveys used in the construction of the cross-national data. The Research on Early Life and Aging Trends and Effects (RELATE) data includes an array of variables, including basic demographic variables (age, gender, education), variables relating to early life conditions (height, knee height, rural/urban birthplace, childhood health, childhood socioeconomic status), adult socioeconomic status (income, wealth), adult lifestyle (smoking, drinking, exercising, diet), and health outcomes (self-reported health, chronic conditions, difficulty with functionality, obesity, mortality). Not all countries have the same variables. Please refer to the technical report that is part of the documentation for more detail regarding the variables available across countries. Sample weights are applicable to all countries exc...

The global luxury goods market, encompassing sectors like jewelry, apparel, watches, cosmetics, and more, is a high-value, high-growth industry. While precise figures for market size and CAGR are not provided, based on industry reports and the listed key players, we can infer substantial market size – likely exceeding several hundred billion USD in 2025, growing at a CAGR of perhaps 5-7% annually through 2033. This growth is fueled by several key drivers: the rising global middle class, particularly in emerging markets like China and India, exhibiting increased disposable income and a growing appetite for luxury brands; the increasing popularity of online luxury retail channels, providing greater accessibility and convenience; and a persistent trend towards experiential luxury, where consumers prioritize unique experiences and personalized services alongside product acquisition. The segments showing the strongest growth are likely to be online sales (driven by e-commerce expansion and digital marketing) and cosmetics, reflecting increasing consumer interest in personal care and beauty. However, certain restraints exist, including economic volatility (potentially impacting consumer spending on discretionary items) and geopolitical uncertainties which could disrupt supply chains and international trade. Competition is fierce, with established luxury conglomerates like LVMH, Kering, and Richemont dominating, while aspirational brands are constantly vying for market share. Regional distribution showcases North America and Europe as mature markets, while Asia-Pacific presents significant growth opportunities, propelled by the expanding Chinese and Indian luxury markets. The distribution of luxury goods is evolving, shifting from a reliance on traditional brick-and-mortar channels (supermarkets/hypermarkets and independent retailers) towards a greater online presence. This necessitates a strategic adaptation by luxury brands, demanding seamless omnichannel experiences that cater to diverse consumer preferences and digital fluency. The various product categories within the luxury market exhibit unique growth trajectories. For instance, while jewelry and watches maintain consistent demand, the cosmetic and apparel sectors show considerable dynamism, driven by trends, innovations, and celebrity endorsements. Understanding these nuanced dynamics is critical for businesses seeking success in this fiercely competitive landscape. The diverse range of companies—from established players like L'Oreal and Estee Lauder to emerging brands—highlights the competitive intensity and market potential, making strategic positioning and market segmentation crucial for long-term success.

Apnea of prematurity (AOP) is a common complication among preterm infants (<37 weeks gestation), globally. However, access to caffeine citrate (CC) that is a proven safe and effective treatment in high income countries is largely unavailable in low-and-middle income countries, where most preterm infants are born. Therefore, the overall aim of this study was to describe the demand, policies, and supply factors affecting the availability and clinical use of CC in LMICs. A mixed methods approach was used to collect data from diverse settings in LMICs including Ethiopia, Kenya, Nigeria, South Africa, and India. Qualitative semi-structured interviews and focus group discussions were conducted with different health care providers, policymakers, and stakeholders from industry. Additional data was collected using standard questionnaires. A thematic framework approach was used to analyze the qualitative data and descriptive statistics were used to summarize the quantitative data. The findings indicate that there is variation in in-country policies on the use of CC in the prevention and treatment of AOP and its availability across the LMICs. As a result, the knowledge and experience of using CC also varied with clinicians on Ethiopia having no experience of using it while those in India have greater knowledge and experience of using it. The in turn influenced the demand and our findings show that only 29% of eligible preterm infants are receiving CC in these countries. There is an urgent need to address the multilevel barriers to accessing CC for management of AOP in Africa. These include cost, lack of national policies and therefore lack of demand stemming from its clinical equivalency with aminophylline. Practical ways to reduce the cost of CC in LMICs could potentially increase its availability and use. Methods Study design, setting, population, sampling We conducted a landscape evaluation involving stakeholders in Africa (Ethiopia, Kenya, Nigeria, South Africa) and South Asia (India – five states of Delhi; Bihar, Uttar Pradesh, Telangana and Madhya Pradesh) on CC availability and use from 1 July 2022 to 31 December 2022. We used a mixed methods study design to understand the complexity of CC availability and use across these LMICs. We selected a geographically and culturally diverse countries with high annual preterm births (~200,000). The selection of stakeholders within each focus country was by convenience and/or purposive sampling. We selected health facilities providing care for preterm infants and were able to provide the data required to achieve the study’s objectives. Proximity and ease of data collection was also factored into selection by research teams. Data collection Qualitative The research teams conducted key informant interviews and focus group discussions (FGD’s) with stakeholders in newborn health. The interviews with healthcare providers sought to explore their experience of using CC as a treatment for AOP. Interviews with WHO and Ministry of Health officials sought to understand current global and national health policies and CC’s inclusion in the essential drug list for using CC to treat AOP. Interviews with major drug suppliers and distributors of CC aimed to determine the current local market pricing of CC and its alternatives within and between countries. Also, to evaluate the factors determining the end-customer price of CC. The available average end-customer price per country was used to determine the daily cost of managing AOP for aminophylline and CC. We compared the average daily cost between aminophylline and cc for both public and private hospitals in each country. The dosing regimen for CC was a loading dose of 20 mg/kg/dose and a daily maintenance dose of between 5 to 10 mg/kg/day. The dosing regimen for aminophylline was a loading dose of 6 mg/kg administered intravenously (IV), followed by a maintenance dose of 2.5 mg/kg/dose/IV administered every 8 hours. Interviews and FGD’s were done in person or virtually over video or audio teleconferencing based on the preferences of the participants. All interviews were conducted in English. teams were situated in each country of focus and had previous training and experience conducting qualitative interviews and FGDs and in qualitative data analysis. The interviews and FGDs were semi structured using guide with a set of open-ended questions, in a set order and allowing for in-depth insights into the subject area. These guides were pilot tested across the 3 countries prior to data collection. Quantitative Additional interviews were conducted using standard questionnaires and had been piloted and refined in these settings prior to being used for data collection.The research team surveyed 107 providers: 20 from Ethiopia, 18 from India, 23 from Kenya, 28 from Nigeria, and 18 from South Africa. Providers were from 45 private or public health facilities across the five study countries. Of these, 12 (27%) were primary or secondary public, 7 (16%) were primary or secondary private, 25 (56%) were tertiary public, and 1 (2%) tertiary private Demand forecast for caffeine citrate. A demand forecast was conducted to determine the amount of CC needed per country. Using data from demographic health survey data from each country, we estimated the proportion of infants who would be eligible for CC treatment. Given AOP risk can be as high as 80% in preterm infants with birthweight ≤1500g (very low birth weight (VLBW)), we estimated that all VLBW infants met eligibility criteria for treatment with CC. We limited this forecast to public facilities where limited government funding constrains drug availability. We applied country-specific policies and assumptions to determine the percentage of VLBW infants who received or had a missed opportunity for CC treatment. These assumptions included, availability of CC, VLBW infants born in secondary facilities will be transferred to a tertiary center capable of providing AOP treat; some transfers will be unsuccessful and even when successful, AOP treatment will be unavailable. Data management and analysis All interviews were transcribed verbatim by an experienced transcriber. Authors reviewed the interview transcripts for errors. A coding framework was generated, and an emergent thematic analysis approach was used to analyze the data, to identify patterns and themes. Descriptive statistics were used to summarize the quantitative data.

BackgroundThe prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach.Methods and findingsWe pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given (“treated”), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%–9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%–5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%–78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys.ConclusionsThe study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured.

In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about *** percent were worth more than *********** dollars that year. India The Republic of India is one of the world’s largest and most economically powerful states. India gained independence from Great Britain on August 15, 1947, after having been under their power for 200 years. With a population of about *** billion people, it was the second most populous country in the world. Of that *** billion, about **** million lived in New Delhi, the capital. Wealth inequality India suffers from extreme income inequality. It is estimated that the top 10 percent of the population holds ** percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

India’s per capita net national income or NNI was around *** thousand rupees in financial year 2025. The annual growth rate was *** percent as compared to the previous year. National income indicators   While GNI (Gross National Income) and NNI are both indicators for a country’s economic performance and welfare, the GNI is related to the GDP plus the net receipts from abroad, including wages and salaries, property income, net taxes and subsidies receivable from abroad. On the other hand, the NNI of a country is equal to its GNI net of depreciation. In 2020, India ranked second amongst the Asia Pacific countries in terms of its gross national income. This has been possible due to a favorable GDP growth in India. Measuring wealth versus welfare   National income per person or per capita is often used as an indicator of people's standard of living and welfare. However, critics object to this by citing that since it is a mean value, it does not reflect the real income distribution. In other words, a small wealthy class of people in the country can skew the per capita income substantially, even though the average population has no change in income. This is exemplified by the fact that in India, the top one percent of people, control over 40 percent of the country’s wealth.

Between the financial year 2016 and 2021, the high income class rural households grew faster than urban super rich households. There was a growth of over ** percent in rural super rich households. On the other hand, destitute classified urban households grew by *** percent.

By 2030, the middle-class population in Asia-Pacific is expected to increase from **** billion people in 2015 to **** billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from *** million in 2015 to *** 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 ** percent of the world’s population had assets valued at less than 10,000 U.S. dollars, while less than *** percent had assets of more than one million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percentage 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 among 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 2023, the gross median household income for Asian households in the United States stood at 112,800 U.S. dollars. Median household income in the United States, of all racial and ethnic groups, came out to 80,610 U.S. dollars in 2023. Asian and Caucasian (white not Hispanic) households had relatively high median incomes, while the median income of Hispanic, Black, American Indian, and Alaskan Native households all came in lower than the national median. A number of related statistics illustrate further the current state of racial inequality in the United States. Unemployment is highest among Black or African American individuals in the U.S. with 8.6 percent unemployed, according to the Bureau of Labor Statistics in 2021. Hispanic individuals (of any race) were most likely to go without health insurance as of 2021, with 22.8 percent uninsured.

The average salary for male employees in urban area was the highest during the months of April to June 2020 at about ** thousand Indian rupees. The average salary drawn by female workers was the highest in the months of April to June 2020, however, lesser compared to their male counterparts. Unsurprisingly, the urban earnings in terms of wages and salaries are always higher than rural employees. Urban versus rural employment The gender gap in salaries was more prominent in rural areas, where, the male workers earned nearly an average of *** times more. However, urban employees just earn a few thousands more than their rural counterpart, while, the cost of living in cities is twice as expensive as villages. Moreover, a majority of the Indian households belonged to the middle-income bracket and this is expected to increase in the future. Wage disparity Wage inequalities are present in almost every sector and widens with higher skill levels. With the evident gender disparity in the country, women with lower educational qualifications, such as a high school diplomas continue working despite the pay gap. This is among women who primarily come from the lower economic sector. Moreover, the social mobility index for fair wage distribution was **** as of 2020, indicating a need for improvement.

Consumer spending across India amounted to 27.2 trillion rupees by the end of the first quarter of 2025. It reached an all-time high during the fourth quarter of 2024, with a value of 28.4 trillion rupees. What is consumer spending? Consumer spending refers to the total money spent on final goods and services by individuals and households in an economy. It is an important metric that directly impacts the GDP of a country. Items that qualify as consumer spending include durable and nondurable goods and services. Various factors such as debt held by consumers, wages, supply and demand, taxes, and government-based economic stimulus can impact consumer spending in a country. Positive consumer outlook in India India’s consumer spending reflects a positive outlook with renewed consumer confidence post-COVID. Its consumer market is set to become one of the largest in the world as the number of middle- to high-income households rises with increasing amounts of disposable incomes. The country’s young demographic is also considered a driving force for increased consumer spending.