According to forecast data from Tellusant, approximately **** percent of the Indonesian population in 2024 would earn at least the equivalent of the top 40 percent of global earners in 2022 constant purchasing power parity. Meanwhile, around *** percent of the population were considered high-class consumers, earning the equivalent of the top ten percent of global earners in 2022 constant purchasing power parity.

In 2024, the number of people living in the middle class and above in Indonesia amounted to over ***** million. In Brunei, over ***** thousand people were middle class and above, accounting for 100 percent of the country's population that year.

In 2016, there were around *** million aspiring middle class, with an average monthly spending between *** to *********** Indonesian rupiah, recorded in Indonesia. Meanwhile, there were about ** million Indonesians, who were still living below poverty line. The growing middle class signifies that the economy in Indonesia is heading in a better direction.

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.

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 *** percent in Indonesia. The United States recorded the second-highest upper-class share of the G20 countries. However, looking at for instance China, approximately ** percent of the population counts as middle class or above, whereas just ***** percent counts as upper class or higher.

In 2020, the estimated size of the middle class population in the six selected Southeast Asian countries Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam amounted to around *** million. That year, approximately ** million people of Indonesia's total population were part of the middle class.

Indonesia can build on its impressive track-record of poverty reduction to tackle more ambitious poverty reduction targets. Indonesia has made impressive gains in reducing poverty, with previously lagging regions catching up, and the Government’s goal to eliminate extreme poverty by 2024 practically met. As an aspiring upper middle-income country, however, Indonesia may want to widen its focus beyond extreme poverty by moving from the US$ 1.90 2011 PPP poverty line to higher lines for middle-income countries. The focus should also include economically insecure households susceptible to falling back into poverty. Is Indonesia’s current effort ready for this challenge Human capital outcomes are disappointing and worrying geographic disparities remain. Low productivity still prevents households from becoming economically secure. Shocks, including from climate change, continue to threaten reversal in poverty gains. In this report the authors identify several major pathways to tackle these challenges in a comprehensive and sustainable manner.

Merchandise imports from low- and middle-income economies outside region (% of total merchandise imports) in Indonesia was reported at 11.66 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Indonesia - Merchandise imports from developing economies outside region (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Merchandise imports from low- and middle-income economies in East Asia & Pacific (% of total merchandise imports) in Indonesia was reported at 41.11 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Indonesia - Merchandise imports from developing economies in East Asia & Pacific (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

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.

Background: Breast cancer has become a public health concern in Indonesia. Regular breast self-examination (BSE) is considered an important first step for its early detection, especially in countries with limited healthcare access, as it is the case in Indonesia. This study aimed to confirm and assess the psychosocial determinants of intention to perform BSE and BSE performance. Methods: The cross-sectional study was conducted on 204 women aged 18–65 years in Surabaya, Indonesia. A 64-item survey was conducted, included variables from the Reasoned Action Approach, and the Health Belief Model, presented questions about demographics, breast cancer knowledge, and behavior related to BSE. Results: Most women (72.5%) expressed intention to perform BSE; however, only 7.8% and 2.9% performed BSE per week and per month, respectively, in the past year. Breast cancer knowledge and attitudes towards BSE were uniquely associated with BSE performance. Perceived behavioral control (PBC) and BSE attitudes were unique correlates of intention. Perceived benefits and barriers and subjective norms were significantly associated with intention and BSE behavior in bivariate analyses. Conclusions: Breast screening education should incorporate strategies for improving attitudes towards BSE, PBC, and breast cancer knowledge with perceived benefits and barriers and subjective norms as relevant targets.

Merchandise imports from low- and middle-income economies in South Asia (% of total merchandise imports) in Indonesia was reported at 3.2257 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Indonesia - Merchandise imports from developing economies in South Asia (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Indonesia E-commerce Market size was valued at USD 58.43 Billion in 2024 and is projected to reach USD 260.91 Billion by 2032, growing at a CAGR of 15.5% from 2026 to 2032. Key Market Drivers:Increasing Internet and Smartphone penetration: The rapid expansion of internet connectivity and smartphone usage in Indonesia is a significant driver of e-commerce. As of 2023, Indonesia had over 204 Million internet users, accounting for 73.7% of the total population. The smartphone penetration rate is predicted to exceed 90% by 2025, encouraging more people to shop online. Increasing Middle-Class Population: Indonesia's middle class is quickly expanding, and by 2023, nearly 52% of the population is considered middle class, increasing disposable money for online shopping. This increase in consumer spending is driving up demand for e-commerce.

In 2024, employees aged between 55 to 59 years old who were formally employed could expect a salary of around *** million Indonesian rupiah a month. The salaries in Indonesia in that year varied greatly, with those formally employed earning significantly more than those in casual employment. Employees in urban areas generally earned more than those in rural areas as well.

Indonesia Biohacking Market growth is driven by increasing internet penetration, wellness trends, and growing middle-class income levels.

The Indonesian real estate market, valued at $64.78 billion in 2025, is projected to experience robust growth, driven by a burgeoning middle class, increasing urbanization, and government initiatives promoting infrastructure development. A compound annual growth rate (CAGR) of 5.82% from 2025 to 2033 indicates a significant expansion of the market, reaching an estimated value of approximately $105 billion by 2033. This growth is fueled by strong demand across various property types, including residential, office, retail, and hospitality sectors. Jakarta and Bali remain key market drivers, attracting significant investment and exhibiting high property values. However, challenges such as land scarcity in prime locations, regulatory complexities, and fluctuating economic conditions pose potential restraints to market growth. The increasing popularity of sustainable and technologically advanced buildings is a notable trend shaping the market's future. Major players like Agung Podomoro Land, Tokyu Land Indonesia, and Lippo Group are actively shaping the landscape, competing for market share through large-scale projects and strategic partnerships. The diverse segments within the market – encompassing residential, office, retail, hospitality, and industrial properties across different Indonesian cities – provide ample opportunities for various investors and developers. The Indonesian real estate market’s resilience is underpinned by a long-term positive outlook for economic growth and population expansion. The government's focus on infrastructure development, including transportation and utilities, further enhances the attractiveness of the market. Furthermore, the rise of e-commerce and the need for modern logistics infrastructure are stimulating growth in the industrial and warehousing segments. The increasing adoption of smart city initiatives also contributes to the growth of technologically advanced properties. However, careful consideration needs to be given to potential risks associated with inflation, interest rate fluctuations, and geopolitical factors, which could affect investor confidence and project timelines. Understanding these dynamics is crucial for investors and stakeholders to navigate the complexities of this dynamic and promising market. This comprehensive report provides an in-depth analysis of the Indonesian real estate market, covering the historical period (2019-2024), base year (2025), and forecast period (2025-2033). It offers invaluable insights for investors, developers, and industry stakeholders seeking to navigate this dynamic and rapidly expanding sector. With a focus on key segments – residential, office, retail, hospitality, and industrial – across major cities like Jakarta and Bali, this report reveals the market's current state and future trajectory. Keywords: Indonesian Real Estate Market, Jakarta Real Estate, Bali Property Market, Indonesian Property Investment, Real Estate Development Indonesia, Indonesian Real Estate Trends. Key drivers for this market are: Growing Population, Increase in Demand for Residential Real Estate. Potential restraints include: Increase in Costs. Notable trends are: Jakarta Emerging as a Prime Rental Market.

The Indonesia Business Market is valued at USD 1.2 trillion, based on a five-year historical analysis. This growth is primarily driven by a combination of increasing foreign direct investment, a burgeoning middle class, and rapid digital transformation across various sectors.

Additional file 1. The dataset of healthcare-associated infection.

Merchandise exports to low- and middle-income economies within region (% of total merchandise exports) in Indonesia was reported at 40.79 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Indonesia - Merchandise exports to developing economies within region (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

The Indonesian retail industry, exhibiting a Compound Annual Growth Rate (CAGR) of 5.00%, presents a dynamic and expansive market. Driven by a burgeoning middle class, rising disposable incomes, and increasing urbanization, the sector shows strong potential for continued growth through 2033. The market's segmentation reveals a diverse landscape, with significant contributions from food and beverages, personal and household care, and apparel segments. Growth is further fueled by the expansion of e-commerce, offering convenient access to a wider range of products for consumers across the archipelago. Major players like PT Matahari Putra Prima Tbk and Alfamart are leading the charge, leveraging both brick-and-mortar and online channels to capture market share. However, challenges remain, including robust competition, infrastructure limitations in certain regions, and the need to adapt to evolving consumer preferences. The industry's resilience is evident in its ability to navigate these challenges, with continued investment in logistics, technology, and omnichannel strategies anticipated to drive future expansion. Despite the positive outlook, the Indonesian retail sector faces several constraints. These include managing supply chain complexities, maintaining competitive pricing in a market with diverse players, and adapting to evolving consumer behavior influenced by global trends. The ongoing development of robust e-commerce infrastructure is crucial, especially in reaching consumers in more remote areas. Successfully navigating these challenges will be key for retailers to achieve sustainable growth. The competitive landscape is further intensified by the entry of international brands and the rise of local online marketplaces, creating a dynamic environment that demands innovation and strategic adaptation. Successfully balancing both online and offline strategies will prove critical for long-term success in this burgeoning market. The overall outlook remains positive, driven by the country's robust economic growth and evolving consumer demographics. Recent developments include: In February 2021, Apparel retailer Giordano unveiled a large-scale store in the newly opened Bumi Raya City Mall in Pontianak, Indonesia.. Notable trends are: Online Retailing is Gaining More Traction, Yet Physical Retailing is Dominating the Market.