Lowest Poverty Rate Research Articles

Use of free preventive dental programme for children: 10 years of Lov'U'r Teeth, France.

Lov'U'r Teeth is a French oral health prevention programme targeting children. The programme offers an appointment with a dentist for oral examination and individual oral health advice. It covers any necessary primary dental care resulting from that examination. Despite being free, it was under-utilised at its previous evaluation 10 years ago. The study aims to identify the determinants of participation and their evolution since 2009. We worked on the General Beneficiary Sample, a medico-administrative database representative of the French population, including health-care consumption data. We selected individuals aged 6 to 15. We performed descriptive statistics and multivariate logistic regressions to analyse and compare the determinants of participation between 2009 and 2019. The final sample included 26 288 children. Lov'U'r Teeth participation rate increased by 4.2 percentage points from 2009 to 2019. Participation was highest at age 6 and declined as age increased. Children from households facing financial difficulties have a 72% lower probability of participating than other children. Over the study period, increasing poverty rates were consistently associated with lower participation. Children living in the areas with the highest poverty rates were up to 46% less likely to participate than those in areas with the lowest poverty rates. Participation in Lov'U'r Teeth has improved over the past 10 years, but the programme continues to reproduce social inequalities, as the determinants of using free preventive dental care mirror those of non-preventive care. Lov'U'r Teeth should enhance communication strategies to reach those in need and clarify the programme's benefits.

Impact of the COVID-19 Pandemic on Blood Lead Testing in Children in the United States.

The study objective was to evaluate the impact of the coronavirus disease (COVID-19) pandemic on pediatric blood lead testing in the United States. Clinical laboratory pediatric (ages <6 years) blood lead level (BLL) tests performed by Quest Diagnostics, January 2019-March 2022, were analyzed. Patients were categorized by age, by sex, and, through matching by ZIP code with US Census data, for race, ethnicity, pre-1950 housing, and poverty estimates. Over 2.8 million results from children (<6 years old) from all 50 states and the District of Columbia were included. Compared to March-May 2019, BLL testing was lower by 53.6% in March-May 2020 and lower by 14.6% in March-May 2021. Testing rebounded more for children in predominantly White non-Hispanic communities and among children living in communities, based on ZIP codes, with the least pre-1950 housing stock and lowest poverty rates. The proportion of children with BLL at or above the United States Centers for Disease Control and Prevention reference values of 3.5 and 5.0 µg/dL fell by 19% and 24%, respectively, in 2021 versus 2019. In conclusion, pediatric BLL testing has rebounded from sharp declines during the early pandemic period but unevenly. Declines in the proportion of children with elevated BLL should be interpreted with caution, as testing rebounds were less robust among communities with the highest risk of lead poisoning, notably communities with the oldest housing stock and higher poverty rates. More public health efforts are needed to address lead toxicity throughout the United States, especially in communities that did not experience a full rebound subsequent to the early COVID-19 pandemic period.

PENERAPAN MODEL GEOGRAPHICALLY WEIGHTED PANEL REGRESSION PADA TINGKAT KEMISKINAN DI PROVINSI KALIMANTAN SELATAN

South Kalimantan Province is one of the provinces in Indonesia which has the lowest poverty rate or percentage of poor people on the island of Kalimantan, even in Indonesia. The percentage of poor people in South Kalimantan Province in March 2022 was 4.49% or in the 2nd lowest poverty position in Indonesia, below the Bangka Belitung Islands Province and above the Bali Province. Geographically Weighted Panel Regression (GWPR) is a local regression model with repeated data at location points for each observation at different times. This study aims to estimate the GWPR model parameters and test the significance of the GWPR model parameters to determine the factors that influence poverty in South Kalimantan Province. The independent variables used affect the dependent variable in the form of the Percentage of Poor Population, namely Life Expectancy, Open Unemployment Rate, Economic Growth, Average Years of Schooling and Number of Crimes. The analysis in this study is descriptive analysis using thematic maps, panel data regression analysis to determine the global model and GWPR by combining the panel data model with the GWR model. The results of this study show that the fixed effect model is a global model and the fixed bisquare weighting function is the best weighting function for estimating the GWPR model. Based on the GWPR model formed, there are 7 model groups based on significant independent variables. Hulu Sungai Utara and Hulu Sungai Tengah districts are districts where poverty in these areas is influenced by many variables compared to other regions in South Kalimantan Province.

Determining the Optimum Number of Clusters in Hierarchical Clustering Using Pseudo-F

Poverty refers to the condition where a person cannot meet the basic necessities based on the minimum living standards. Statistics Indonesia proxied an increase in the poverty rate in North Sumatra Province in 2021 from 8.75% to 9.01%. However, this increase is exclusive to North Sumatra Province, which has Indonesia's 3rd largest number of districts/cities. This study discussed mapping the North Sumatra Province region based on 10 poverty factor variables. The 10 variables are life expectancy, health complaints, poverty line, Gross Regional Domestic Product (GRDP), population growth rate, Expected Years of Schooling (EYS), Human Development Index (HDI), labor force participation rate, open unemployment rate, and district/city minimum wage. The Hierarchical Clustering analysis was employed to compare single, complete, and average linkage methods. The best method was determined based on the pseudo-F statistic value. 4 clusters had complete linkage methods, each of which possessed varied characteristics. Cluster 1 contains cities with the lowest poverty rate, including Medan City and Pematang Siantar City. Cluster 2 consists of cities with low poverty rates, while Cluster 3 consists of cities with high poverty rates. Cities that are included in Cluster 4 have very high poverty rates, including South Nias District and Pakpak Bharat District. The clusters present significant poverty rate gaps among North Sumatra Province regions.

Pengaruh Keuangan Daerah terhadap Tingkat Kemiskinan di Aceh

Poverty is one of the problems faced by Indonesia from the past until now. Various ways have been done to overcome the problem of poverty. One of the efforts that have been made by the Government of Indonesia is to issue a regional autonomy policy. The existence of this policy gives authority to local governments to regulate their own regions. This policy is given to all provinces in Indonesia, including Aceh. Aceh is the province with the highest poverty rate on the island of Sumatra, although it has a higher original regional income (PAD) than the province with the lowest poverty rate on the island of Sumatra. Aceh also has a greater natural resources revenue-sharing fund (DBH SDA) than the province of West Sumatra. In addition, Aceh also received special autonomy funds (DOK), which were only given to the provinces of Aceh, Papua, and West Papua. This study aims to analyze the effect of PAD, DBH SDA and DOK on the poverty rate of Aceh Province for the 2008-2020 period. This research uses panel data regression involving 23 districts/cities of Aceh Province. The results of the study show that only local real revenue has a significant and negative effect on poverty levels.

Worlds Apart: Postcodes with the Highest and Lowest Poverty Rates in Today’s Australia

Worlds Apart: Postcodes with the Highest and Lowest Poverty Rates in Today’s Australia

Analisis Pengaruh Indeks Pembangunan Manusia, Laju Pertumbuhan Penduduk, dan Tingkat Pengangguran Terbuka terhadap Kemiskinan di DKI Jakarta

The poverty rate has increased rapidly again due to the Covid-19 Pandemic. DKI Jakarta is one of the top 5 provinces with the lowest poverty rate in Indonesia, even though it has high complexity in administering its government. Because of these achievements, this study aims to find factors that influence poverty so that it can become a reference for other local governments in alleviating poverty. This research was conducted using panel data regression with a fixed effect model. The results showed that simultaneously poverty headcount index in the t-1 period, human development index (HDI), open unemployment rate, and population growth rate significantly affect the poverty headcount index. While partially, open unemployment and population growth rate positively and significantly affect the poverty headcount index. On the other hand, the poverty headcount index in the t-1 period and HDI positively and insignificantly affect the poverty headcount index. This research shows that local governments must focus more on policies to reduce unemployment and population growth rate in the context of alleviating poverty.

Livelihood Choice and Household Economic Wellbeing in Vietnam’s Northwest region

This paper examines factors affecting livelihood choices in the Northwest region, the country’s poorest one, populated mainly by ethnic minorities. We utilized secondary data from the Vietnam Household Living Standard Surveys (VHLSS) in 2016 and 2018, and applied micro-econometric analysis. Our cluster analysis results offer the initial classification into six livelihood groups characteristic of rural households. Bonferroni pairwise tests are used to compare per capita income and poverty rates across livelihood options. We discovered that households with nonfarm or formal wage-earning livelihoods had the highest levels of income and the lowest poverty rates, while those reliant on the cultivation of crops had the lowest income and the highest poverty levels. A multinomial logit model is used to explore factors affecting livelihood choice. We found that ownership of more cropland reduces the likelihood of choosing high-return livelihoods. Furthermore, household head education has a beneficial effect on the pursuit of profitable occupations, meaning that improved education could lead to households shifting away from low-return activities. We also discovered that households in communes with available transportation are more likely to adopt high-return livelihoods.

Cross-Sectional Analysis of Clinical Trial Availability and North Carolina Neighborhood Social Vulnerability.

Residents of communities facing social vulnerability (eg, poverty) have limited access to clinical trials, leaving them susceptible to experiencing poor health outcomes. We examined the association between North Carolina county-level social vulnerability and available multiple myeloma (MM) trials. Using a novel data linkage between ClinicalTrials.gov, the 2019 American Community Survey, and the Centers for Disease Control and Prevention's Social Vulnerability Index, we investigated at the county level (1) availability of MM trial sites and (2) the relationship between Social Vulnerability Index and MM trial site availability using logistic regression. Between 2002 and 2021, 229 trials were registered across 462 nonunique trial sites in 34 counties. Nearly 50% of trial sites were in academic medical centers, 80% (n = 372) of all trials were industry-sponsored, 60% (n = 274) were early-phase, and 50% (n = 232) were for patients with relapsed or refractory MM. Counties with low as opposed to high poverty rates had six times greater odds of having ≥ 1 MM trial sites (odds ratio [OR], 5.60; 95% CI, 1.85 to 19.64; P = .004). Counties with the lowest percentage of Black Indigenous Persons of Color and non-native English speakers had 77% lower odds (OR, 0.23; 95% CI, 0.07 to 0.69; P = .011) of having ≥ 1 trial sites. The effect remained significant after accounting for the presence of five academic medical centers (n = 95; OR, 0.18; 95% CI, 0.05 to 0.6; P = .008) and adjustment for metropolitan, suburban, or rural status (OR, 0.25; 95% CI, 0.07 to 0.81; P = .025). Counties with the lowest poverty rates had more MM trial sites, whereas those with the lowest percentage of Black Indigenous Persons of Color populations had fewer MM trial sites. Multilevel efforts are needed to improve the availability and access to trials for socially vulnerable populations.

Mapping the Poverty Rate of The South Sulawesi Region

This research purpose to presenting information on a smaller regional scale and comparing the conditions of each region. Researchers conducted a poverty mapping technique based on geospatial information. Utilizing the Geographic Information System (GIS) application, namely ArcMap with conversion tools techniques. Data collection techniques with literature study. The poverty level data is processed into tabulation form in the excel application. Meanwhile, the regional base map is first input into the ArcMap application to overlay all regions in one province. The product is a map of the poverty level of the district/city community in the administrative area of South Sulawesi Province. The map will show an image of the area by color category. The dark color gradation means the area with the highest poverty rate and the lightest color means the area with the lowest poverty rate. The results obtained indicate that the districts with the highest poverty rates are Makassar City and Bone District. Meanwhile, the areas with the lowest poverty rates are Barru Regency, Sidenreng Rappang Regency, Pare-Pare City and Palopo City.

Nigeria's multidimensional poverty analysis: A subgroup and dimensional breakdown

This study is an attempt to analyze the nature of multidimensional poverty in Nigeria in the light of recent data. The study used data from the Nigerian standard of living and measurement survey (LSMS) 2018/2019 to estimate the overall MPI for Nigeria, which included six indices of deprivation from four dimensions: consumption, education, energy, and housing. The study also performed a decomposition of multidimensional poverty across Nigerian regions, as well as a dimensional breakdown of multidimensional poverty across Nigeria and across regions. According to the study, Nigeria's multidimensional poverty index is 0.34, with a headcount ratio of 0.64 when the deprivation cutoff is 1, implying that roughly 64 percent of Nigerians are poor in at least one of the four areas studied. The North West, North East, and North Central regions, on the other hand, account for the majority of Nigeria's multidimensional poverty, accounting for more than 70% of the country's total multidimensional poverty. The South West has the lowest poverty rate, followed by the South South and the South East. Deprivations in Education, Energy, Consumption, and Housing, according to the report, are the most significant contributors to MPI. The study recommends that policies aimed at reducing poverty must take into account the distribution of multidimensional poverty in Nigeria so as to be able to get to the targeted audience. Secondly, there is a need to improve investment in Education and Energy so as to reduce overall multidimensional poverty in Nigeria.

Effect of labor and number of micro and small enterprises (MSEs) on poverty rate in Indonesia

The study aims to analyze the poverty and micro and small enterprises in 34 provinces in Indonesia, and to analyze the effect of labor and the number of micro and small enterprises on poverty levels in Indonesia. The results indicate that Papua Province has the highest poverty rate and the DKI Jakarta Province has the lowest poverty rate. Central Java Province has the largest number of micro-enterprises, and West Papua Province has the lowest number of micro-enterprises. For small enterprises, Central Java Province has the highest number and West Papua Province has the lowest number. Meanwhile, Central Java Province as the largest number of micro-business workers, and West Papua Province has the lowest number workers. For small business workers, Central Java Province has the largest number and West Papua Province has the lowest number. The results of panel data regression show that some variables, such as small-enterprise worker and the number of micro enterprises, have a significantly negative effect on the poverty rate. On the other hand, micro-enterprise worker and the number of small enterprises have a positive and significant effect on poverty rate.

Dynamic Evolution of the Ecological Carrying Capacity of Poverty-Stricken Karst Counties Based on Ecological Footprints: A Case Study in Northwestern Guangxi, China.

The karst area in northwestern Guangxi is poor, underdeveloped, and ecologically fragile. It is experiencing rocky desertification, which creates challenges that are more severe than those of other regional ecological environments. In this paper, the ecological footprint (EF) model is used to analyze the ecological carrying capacity (EC) in northwestern Guangxi from 1995 to 2015, and the differences in karst counties with different poverty levels are discussed. The results show that (1) since 1995, the EC of northwestern Guangxi has continued to decrease, the EF has continued to increase, the ecological deficit (ED) has been expanding, and the status of the region has been unsustainable for a long time. (2) The evolutionary patterns, EF and EC of karst counties with different poverty levels are different. The county with the lowest poverty rate has the fastest growth rate of the per capita EF. The county with the largest proportion of karst area has the lowest EC. (3) It is recommended that different types of counties take different measures, including strengthening ecological environment protection, carrying out rocky desertification control and ecological resettlement projects, and reducing energy consumption. This study can provide information for the sustainable development of the karst region and provide decision support for regional poverty alleviation.

The 2030 Agenda for Sustainable Development: Where Does India Stand?

Sustainable Development Goals (SDGs) is one of the most definite and widely accepted goals by United Nations (UNs) as a result of discourse and deliberations among the member States. The global goals that seek to consider three dimensions of poverty i.e., social, economic and environmental dimensions to improve people's lives and protect the planet for future generations. The article seeks to juxtapose 17 SDGs and the existing status of the goals of India in comparison with the South Asian countries. The study extensively used secondary sources of data to paint a quantitative picture of SDGs and the ranking given by various international agencies. Since the SDGs were adopted in September 2015, we may not get the impact as such. The purpose of the study is to give a summarised picture of goals so that future course of action can be drawn from the study. The study found nearly 21.9 per cent of the people in India live below poverty line. The situation of poverty is grim more particularly in rural areas, as around 25.7 per cent live below the poverty line. Among the South Asian countries, lowest poverty rate exists in Sri Lanka that stood at close to 7 per cent. The life expectancy rate of India is 68.3 years, which is even less than that of Bangladesh. The per capita income of India is $5,663 which is half of that of Sri Lanka. The literacy rate of India is 74 percent, Maldives on its way to achieve cent percent literacy rate. In the Human Development Index, India was ranked 131 among the list of countries. However, it is noteworthy that among South Asian countries, Sri Lanka and Maldives could figure themselves in 73 and 105, respectively. The Global Hunger Index report of 2016 ranking has placed India at 97 out of 118 countries. India performed poorly in the Gender Development Index, managed to perform better than Pakistan and Afghanistan. India will have go long way to achieve 100 per cent access to clean drinking water and electricity. Starting business in India still not a good proposition and huge inequality persists in the income distribution. India’s position in crime index and pollution index is also not up to the mark. Global collaboration, engaging with countries of expertise will help in addressing these issues.

Effects of Race/Ethnicity and Socioeconomic Status on Outcome in Childhood Acute Lymphoblastic Leukemia.

With modern therapy, overall survival (OS) for children with acute lymphoblastic leukemia approaches 90%. However, inferior outcomes for minority children have been reported. Data on the effects of ethnicity/race as it relates to socioeconomic status are limited. Using state cancer registry data from Texas and Florida, we evaluated the impact of neighborhood-level poverty rate and race/ethnicity on OS for 4719 children with acute lymphoblastic leukemia. On multivariable analysis, patients residing in neighborhoods with the highest poverty rate had a 1.8-fold increase in mortality compared with patients residing in neighborhoods with the lowest poverty rate (hazard ratio [HR], 1.8; 95% confidence interval [CI], 1.41-2.30). Hispanic and non-Hispanic black patients also had increased risk of mortality compared with non-Hispanic white patients (Hispanic: HR, 1.18; 95% CI, 1.01-1.39; non-Hispanic black: HR, 1.31; 95% CI, 1.03-1.66). On subgroup analysis, there was a 21.7% difference in 5-year OS when comparing non-Hispanic white children living in the lowest poverty neighborhoods (5-year OS, 91.2%; 95% CI, 88.6-93.2) to non-Hispanic black children living in the highest poverty neighborhoods (5-year OS, 69.5%; 95% CI, 61.5-76.1). To address such disparities in survival, further work is needed to identify barriers to cancer care in this pediatric population.

Distribution of selected healthcare resources for influenza pandemic response in Cambodia

IntroductionHuman influenza infection poses a serious public health threat in Cambodia, a country at risk for the emergence and spread of novel influenza viruses with pandemic potential. Prior pandemics demonstrated the adverse impact of influenza on poor communities in developing countries. Investigation of healthcare resource distribution can inform decisions regarding resource mobilization and investment for pandemic mitigation.MethodsA health facility survey performed across Cambodia obtained data on availability of healthcare resources important for pandemic influenza response. Focusing on five key resources considered most necessary for treating severe influenza (inpatient beds, doctors, nurses, oseltamivir, and ventilators), resource distributions were analyzed at the Operational District (OD) and Province levels, refining data analysis from earlier studies. Resources were stratified by respondent type (hospital vs. District Health Office [DHO]). A summary index of distribution inequality was calculated using the Gini coefficient. Indices for local spatial autocorrelation were measured at the OD level using geographical information system (GIS) analysis. Finally, a potential link between socioeconomic status and resource distribution was explored by mapping resource densities against poverty rates.ResultsGini coefficient calculation revealed variable inequality in distribution of the five key resources at the Province and OD levels. A greater percentage of the population resides in areas of relative under-supply (28.5%) than over-supply (21.3%). Areas with more resources per capita showed significant clustering in central Cambodia while areas with fewer resources clustered in the northern and western provinces. Hospital-based inpatient beds, doctors, and nurses were most heavily concentrated in areas of the country with the lowest poverty rates; however, beds and nurses in Non-Hospital Medical Facilities (NHMF) showed increasing concentrations at higher levels of poverty.ConclusionsThere is considerable heterogeneity in healthcare resource distribution across Cambodia. Distribution mapping at the local level can inform policy decisions on where to stockpile resources in advance of and for reallocation in the event of a pandemic. These findings will be useful in determining future health resource investment, both for pandemic preparedness and for general health system strengthening, and provide a foundation for future analyses of equity in health services provision for pandemic mitigation planning in Cambodia.

Education America—“Welcome to My Nightmare”

Click to increase image sizeClick to decrease image size Notes An early version of this article appears as “Postscript: Education America—’Welcome to My Nightmare’” in Peters (2012 Peters , M. A. ( 2012 ). Obama, Education and the End of the American Dream . Rotterdam : Sense Publishers . [Google Scholar]). Youth unemployment rates in 2011 (approximately): Spain, 47%; Eurozone, 21%; United States, 17%; and Germany, 9%. The United States defines the poverty line as income of $22,314 a year for a family of four and $11,139 for an individual (U.S. Census Bureau 2011 Line , M. ( 2011 ). Providence Plans to Pink Slip All Teachers . http://liveshots.blogs.foxnews.com/2011/02/24/providence-plans-to-pink-slip-all-teachers/#ixzz1evnTU63G [Google Scholar]). The poverty rate for children under age 18 increased to 22% in 2010; the poverty rate for adults ages 18 to 64 rose to 13.7%; for people 65 and older, the poverty rate was barely changed at 9%. Non-Hispanic whites had the lowest poverty rate, 9.9% (Asians, 12.1%; Hispanic 26.6%), and blacks had the highest rate at 27.4%. About 14% of men were below the poverty line, compared to 16.2% of women. Families headed by a married couple had only a 6.2% poverty rate, whereas families with a single mother had a 31.6% rate, and families with a single father had a 15.8% rate. (Censky 2011 Censky , A. ( 2011 ). Poverty Rates Rise in America . http://money.cnn.com/2011/09/13/news/economy/poverty_rate_income/index.htm [Google Scholar]; U.S. Census Bureau 2011 Line , M. ( 2011 ). Providence Plans to Pink Slip All Teachers . http://liveshots.blogs.foxnews.com/2011/02/24/providence-plans-to-pink-slip-all-teachers/#ixzz1evnTU63G [Google Scholar]). On October 15, tens of thousands of demonstrators staged rallies in 900 cities around the world, including Auckland, Sydney, Hong Kong, Taipei, Tokyo, São Paulo, Paris, Madrid, Berlin, Hamburg, and Leipzig (http://en.wikipedia.org/wiki/Occupy_Wall_Street). Early Childhood: The Zero to Five Plan funds and helps states move toward voluntary, universal preschool education; expands Early Head Start and Head Start; provides affordable, and high-quality child care. K12: To reform No Child Left Behind; support high-quality schools and close low-performing charter schools; make math and science education a national priority; expand high-quality afterschool opportunities (21st century learning programs); support college outreach programs (e.g., GEAR UP, TRIO, and Upward Bound); support college credit initiatives; support English Language Learners; recruit, prepare, retain, and reward teachers. Higher education: To create the American Opportunity Tax Credit—universal and fully refundable credit will ensure that the first $4,000 of a college education is completely free for most Americans and will cover two-thirds the cost of tuition at the average public college or university and make community college tuition completely free for most students. Recipients of the credit will be required to conduct 100 hours of community service; simplify the application process for financial aid. (See http://change.gov/agenda/education_agenda/.)

Economic conditions of female-headed households in Taiwan in comparison with the United States and Sweden

This study investigated the economic conditions of female-headed households in Taiwan and compared them with those in the United States and Sweden in 2000. At the descriptive level, we investigated the socioeconomic backgrounds of the households, the rate of poverty, distributive effects of public and private transfers, and Gini coefficients at each stage of income distribution. We then conducted logistic regression analyses of the poverty rate at the last stage of income distribution. The major finding was that within the context of a small welfare state, Taiwan had the lowest poverty rate before transfers and the second lowest poverty rate after transfers of the three countries we studied. Moreover, at the last stage of income distribution, only two independent variables (education and work status of the household head) affected the poverty rate. We conclude that Taiwan, as one of the developmental welfare regimes in Asia, had created a different way of enhancing the economic wellbeing of female-headed ...

Societal shifts and changed patterns of poverty

Fritzell J, Ritakallio VM. Societal shifts and changed patterns of povertyInt J Soc Welfare 2010: ••: ••–••© 2010 The Author(s), Journal compilation © 2010 Blackwell Publishing Ltd and International Journal of Social Welfare.This article uses data from the Luxembourg Income Study to analyse cross‐national and cross‐temporal poverty risks in 11 Western countries. We show that poverty risks have tended to increase from the early 1980s to 2000. In line with what we would expect based on the welfare state literature, the Nordic countries tend to have the lowest poverty rates. However, the proportion of the national population with a market income below the poverty threshold has increased in all countries and the cross‐national variation in market income poverty is not apparently related to the type of welfare state regime. We perform a simulation analysis to test whether structural factors, that is, compositional differences in age, family and labour market behaviour, could account for the cross‐national variation found. Our results demonstrate the increasing importance of household labour market attachment for alleviating poverty risks, as well as for explaining the cross‐national variation in these risks.

Immigration and Adult Transitions

Almost 30 percent of the more than 68 million young adults aged eighteen to thirty-four in the United States today are either foreign born or of foreign parentage. As these newcomers make their transitions to adulthood, say Rubén Rumbaut and Golnaz Komaie, they differ significantly not only from one another but also from their native-parentage counterparts, including blacks and whites. The authors document the demographic changes in the United States over the past forty years and describe the ways in which generation and national origin shape the experiences of these newcomers as they become adults. Rumbaut and Komaie point out that immigrant groups experience gaps in social, economic, and legal status that are even greater than the gaps between native whites and blacks. By far the most-educated (Indians) and the least-educated (Mexicans) groups in the United States today are first-generation immigrants, as are the groups with the lowest poverty rate (Filipinos) and the highest poverty rate (Dominicans). These social and economic divides reflect three very different ways immigrants enter the country: through regular immigration channels, without legal authorization, or as state-sponsored refugees. For many ethnic groups, significant progress takes place from the first to the second generation. But, say the authors, for millions of young immigrants, a lack of legal permanent residency status blocks their prospects for social mobility. Having an undocumented status has become all the more consequential with the failure of Congress to pass comprehensive federal immigration reforms. In the coming two decades, as the U.S. native-parentage labor force continues to shrink, immigrants and their children are expected to account for most of the growth of the nation's labor force, with the fastest-growing occupations requiring college degrees. Rumbaut and Komaie stress that one key to the nation's future will be how it incorporates young adults of immigrant origin in its economy, polity, and society, especially how it enables these young adults to have access to, and to attain, postsecondary education and its manifold pyoffs.