Income Measures Research Articles

Economic inequalities in adolescents’ internalising symptoms: longitudinal evidence from eight countries

Research, mainly conducted in Europe and North America, has shown an inequitable burden of internalising mental health problems among adolescents from poorer households. We investigated whether these mental health inequalities differ across a diverse range of countries and multiple measures of economic circumstances. In this longitudinal observational cohort study, we analysed data from studies conducted in eight countries (Australia, Ethiopia, India, Mexico, Peru, South Africa, the UK, and Viet Nam) across five global regions. All studies had self-reported measures of internalising symptoms using a validated scale at two timepoints in adolescence; a measure of household income, household consumption expenditure, or subjective wealth; and data collected between 2000 and 2019. Household income (measured in four countries), consumption expenditure (six countries), and adolescents' subjective assessment of household wealth (five countries) were measured in mid-adolescence (14-17 years). The primary outcome (internalising symptoms, characterised by negative mood, affect, and anxiety) was measured later in adolescence between age 17 and 19 years. Analyses were linear regression models with adjustment. Effect estimates were added to random-effects meta-analyses to aid understanding of cross-country differences. The overall pooled sample of eight studies featured 18 910 adolescents (9568 [50·6%] female and 9342 [49·4%] male). Household income had a small or null association with adolescents' internalising symptoms. Heterogeneity (I2 statistic) was 71·04%, falling to 39·71% after adjusting for baseline symptoms. Household consumption expenditure had a stronger association with internalising symptoms (decreases of 0·075 SD in Peru [95% CI -0·136 to -0·013], 0·034 SD in South Africa [-0·061 to -0·006], and 0·141 SD in Viet Nam [-0·202 to -0·081] as household consumption expenditure doubled). The I2 statistic was 74·24%, remaining similar at 74·83% after adjusting for baseline symptoms. Adolescents' subjective wealth was associated with internalising symptoms in four of the five countries where it was measured. The I2 statistic was 57·09% and remained similar after adjusting for baseline symptoms (53·25%). We found evidence for cross-country differences in economic inequalities in adolescents' internalising symptoms, most prominently for inequalities according to household consumption expenditure. Subjective wealth explained greater variance in symptoms compared with the objective measures. Our study suggests that economic inequalities in adolescents' mental health are prevalent in many but not all countries and vary by the economic measure considered. Variation in the magnitude of inequalities suggests that the wider context within countries plays an important role in the development of these inequalities. Wellcome Trust.

Does perceived neighbourhood social cohesion moderate the effects of demographic changes on health?

Abstract Small-area characteristics changes over time may be associated with health. Various theories have been proposed to explain small-area effects on health, including those concerning social capital. The effect of small-area demographic changes on health are very little researched and hardly anything is known about their relationship with social cohesion. We use longitudinal data from the German Socio-Economic Panel linked to demographic measures at county level. We explore the association between 5-year changes in the proportion of over 65 and of 18-24 years-old and physical and mental health and the moderating effect of perceived neighbourhood social cohesion (SC) using random intercept models. Control variables include education, income, and relevant baseline measures. Included are all participants with a 6-year continuous exposure to their county of residence. The main outcomes are the physical and mental health components (PCS, MCS) of the SF-12. We included 21,239 persons up to 6 times in 399 counties. 5-year changes in the over 65, of 18-24 and measure of SC are associated to MCS and PCS. Significant interactions between the changes in over 65 and social cohesion are seen for MCS only in rural areas and some interactions are significant for PCS. For MCS there are no interactions between social cohesion and the changes in 18-24. Important interaction effects for PCS: for those exposed to a small decrease in 18-24, an increase in one unit of SC is associated with an increase of 1.71 (95% CI[1.38, 2.03]) PCS units. For those exposed to a large decrease this effect is lower by 0.88 PCS units. Exposition to some demographic changes have the effect to reduce the positive effects of perceived social cohesion on health. Thus, demographic changes appear to be health stressors. The evidence shown by this work need to be further developed by considering smaller scales but the evidence opens up a new range of possible intervention targets to reduce health inequalities. Key messages • County level demographic changes are associated with physical and mental health and certain exposition to changes reduce the positive effects of perceived neighbourhood social cohesion. • Social cohesion can be an intervention target to reduce small-area health inequalities, population changes can annulate positive effects. This must be accounted for in public health interventions.

Social Media Addiction and Cognitive Behavioral Physical Activity Among Adolescent Girls: A Cross-Sectional Study.

To measure a multivariate analysis of social media addiction and cognitive-behavioral physical activity associated with several sociodemographic characteristics in adolescent girls. A cross-sectional study. The sample consisted of adolescent girls studying in a vocational high-school in the Middle-Black-Sea region in Türkiye (n = 333). A questionnaire, Social Media Addiction Scale-for-Adolescents (SMAS-A), and Cognitive-Behavioral Physical Activity Questionnaire (CBPAQ) were used to collect the data. The mean age was 15.35(SD=1.15), and 29.4% were the ninth-class students. Of the adolescent girls, 85.9% were social-media users, 59.8% used the internet 2-hours-or-more/daily, 67.9% declared themselves as moderately-active. The mean scores of the SMAS-A and the CBPAQ were 3.40 (SD=1.61) and 21.03(SD=7.64), respectively. There was a significantly-negative correlation between cognitive-behavioral physical activity and social-media addiction levels. The One-Way MANOVA results showed significant differences in the academic level, family income, mother education, and physical activity measurement application usage affected to cognitive-behavioral physical activity. Social media usage habit affected to the social media addiction level. Daily internet usage time and self-declared physical activity level were the mutually affected factors. School nurses should act to improve healthy social media usage habits to promote well-being and encourage the positive attitudes towards regular physical activity in this population.

Falling sideways? Social status and the true nature of elite downward mobility

Downward mobility is an essential, but commonly overlooked component of social mobility. Existing estimates of downward mobility are routinely based on unidimensional measures of income and social class. This ignores the potential for substantial retention of advantage in other domains of stratification – particularly social status.In this paper, I use highly detailed occupational data from a representative UK sample to examine patterns of multidimensional mobility among those from the most advantaged backgrounds. I find that multidimensional measures reveal dramatically different patterns of downward mobility – particularly for women, who, when downwardly mobile in terms of social class, often retain privileged social status positions.I also find that those whose parents held jobs at the very top of the status distribution were much less likely to be downwardly mobile than previous mobility estimates have suggested – consistent with public perceptions of a ‘glass floor’.

Associations of serial negative income shock and all-cause mortality: a longitudinal study in China

IntroductionWith a precarious economic outlook and increasing income volatility in current times, understanding the association between negative income shock and health is crucial. However, few studies have examined such associations...

Combating Food Waste: Legal Analysis and Fiscal Solutions in the Italian and European Context

This contribution aims to analyze the new measure of Food Income, an Italian legislation that has been introduced recently to combat food poverty. This tool enables the free distribution of food parcels made from unsold commercial products, donated by participating businesses to people in absolute poverty. Beginning with the analysis of the measure, which is currently being tested in some Italian municipalities, the goal of this contribution is to provide a comprehensive overview of current practices and developments in addressing food waste within the Italian legal system, offering a comparative and multilevel perspective on the multiple purposes that can be served by a sustainable food chain.

Reconstruction of the doping profile in Vlasov–Poisson system

Abstract We study the inverse problem of recovering the doping profile in the stationary Vlasov–Poisson equation, given the knowledge of the incoming and outgoing measurements at the boundary of the domain. This problem arises from identifying impurities in the semiconductor manufacturing. Our result states that, under suitable assumptions, the doping profile can be uniquely determined through an asymptotic formula of the electric field that it generates.

Social Deprivation and Multimorbidity Among Community-Based Health Center Patients in the United States.

Multimorbidity - having 2 or more chronic diseases - is a national public health concern that entails burdensome and costly care for patients, their families, and public health programs. Adults residing in socially deprived areas often have limited access to social and material resources. They also experience a greater multimorbidity burden. We conducted a retrospective cohort analysis of electronic health record (EHR) data from 678 community-based health centers (CHCs) in 27 states from the Accelerating Data Value Across a National Community Health Center (ADVANCE) Network, a clinical research network, from 2012-2019. We used mixed-effects Poisson regression to examine the relationship of area-level social deprivation (eg, educational attainment, household income, unemployment) to chronic disease accumulation among a sample of patients aged 45 years or older (N = 816,921) residing across 9,362 zip code tabulation areas and receiving care in safety-net health organizations. We observed high rates of chronic disease among this national sample. Prevalence of multimorbidity varied considerably by geographic location, both within and between states. People in more socially deprived areas with Social Deprivation Index (SDI) scores in quartiles 2, 3, and 4 had greater initial chronic disease counts - 17.1%, 17.7%, and 18.0%, respectively - but a slower rate of accumulation compared with people in the least-deprived quartile. Our findings were consistent for models of the composite SDI and those evaluating disaggregated measures of area-level educational attainment, household income, and unemployment. Social factors play an important role in the development and progression of multimorbidity, which suggests that an assessment and understanding of area-level social deprivation is necessary for developing public health strategies to address multimorbidity.

Abstract A114: Inequities in advanced stage at diagnosis of non-small cell lung cancer among people with and without HIV in the US

Abstract Background: Lung cancer is the leading cause of non-AIDS death among people with HIV (PWH). PWH are also more likely to die due to lung cancer compared to people with HIV. Late presentation at diagnosis due to barriers to lung cancer screening may contribute to disproportionate deaths among PWH. Our objective was to evaluate associations of HIV status with advanced stage at diagnosis and evaluate social determinants of health (SDoH) associated with advanced stage at diagnosis of lung cancer among PWH. Methods: We used data from the 2004-2020 National Cancer Database, including patients aged 18-89 years diagnosed with lung cancer (ICD-0-3 codes: C340-C349). PWH were identified using ICD9 (04200 to 04499, 07953, and V08) and ICD10 (B20 to B24, R75, Z21, B97.35).The primary outcome was advanced stage at diagnosis (stage 3/4). Our main SDoH exposures were quantified as quartiles (Q1-Q4) and included measures of area-level SDoH based on a patient’s zip code: (1) % of adults without a high school degree, or area-level education; (2) median household income of adults, or area-level income. We used hierarchical multivariable logistic regression models clustered by facility ID to estimate adjusted odds ratios(aOR) with 95% confidence intervals(95% CI), and evaluated each exposure separately adjusting for age, sex, year of diagnosis, and Charlson comorbidity score, and stratified by race/ethnicity and insurance status. Results: Overall, we identified 6,585 PWH and 1,665,030 without HIV. Seventy one percent of PWH were diagnosed with stage 3 or 4 lung cancer compared to 64.9% of people without HIV (p<0.001). PWH were more likely to be under the age of 60 (43.5% vs.15.1%, p<0.001), After adjustment for sex, age, and year of diagnosis, PWH had 15% higher odds of advanced stage at diagnosis compared to those without HIV (aOR: 1.15; 95% CI: 1.09-1.22). Residing in areas with larger proportions of the population without a HS diploma (Q4 vs. Q1: aOR:1.19; 95% CI: 1.01-1.41) and larger proportions with lower household income (Q1 vs. Q4: aOR: 1.15; 95% CI: 1.01-1.31) were positively associated with advanced stage-at-diagnosis of lung cancer. When we stratified by insurance status, only PWH who were Medicaid insured residing in the least educated areas (aOR: 1.84; 95% CI: 1.11-3.06) and in the lowest income areas (aOR: 1.86; 95% CI: 1.30-2.65) had higher odds of advanced stage at diagnosis with lung cancer. Conclusions: Living with HIV is independently associated with presenting at a later stage of lung cancer at diagnosis. Area-level measures of lower education and lower household income are significantly associated with advanced stage-at- diagnosis of lung cancer regardless, particularly among those who are Medicaid insured. Citation Format: Jessica Y Islam, Yi Guo, Kea Turner, Amir Alishahi Tabriz, Marlene Camacho-Rivera, Gita Suneja. Inequities in advanced stage at diagnosis of non-small cell lung cancer among people with and without HIV in the US [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A114.

Abstract A037: Understanding the role of neighborhood deprivation in racial and urban-rural disparities in triple negative breast cancer

Abstract Background: Triple negative breast cancer (TNBC) accounts for 15% of all breast cancers and is one of the most aggressive disease subtypes. Disparities in TNBC exist, where US Black women and women living in urban environments are more likely to be diagnosed with TNBC than their White or rural counterparts. Reasons for these disparities are not completely understood. Social determinants of health, such as the neighborhood environment, have been implicated as potential contributors to breast cancer disparities. To improve our understanding of disparities in TNBC, we examined neighborhood deprivation in relation to breast cancer subtype, according to race and rurality. Methods: We identified 40,095 non-Hispanic Black and White women diagnosed with invasive breast cancer in 2010-2017 in the Georgia Cancer Registry. Neighborhood deprivation was measured by the Neighborhood Deprivation Index (NDI), a composite measure of neighborhood poverty, income, housing, unemployment, occupation, and education derived through principal component analysis using 2011-2015 block group-level American Community Survey data. Georgia Department of Public Health data were used to measure county-level rurality. We estimated case-only multivariable odds ratios (OR) and 95% confidence intervals (CI) for the separate associations between NDI, in quintiles, and each breast cancer subtype (TNBC, ERBB2+, or luminal B vs. luminal A breast cancer), overall and according to race and rurality. Results: Of the 40,095 non-Hispanic Black (31.5%) and White (68.5%) women, 5,328 were diagnosed with TNBC, 1,926 with ERBB2+, 4,958 with luminal B, and 27,883 with luminal A breast cancer. Compared to living in the least deprived neighborhoods, living in the most deprived neighborhoods was associated with a 33% (OR= 1.33, 95% CI 1.19-1.48) increased odds of TNBC vs. luminal A breast cancer. Race and rurality did not modify the association. However, estimates were less pronounced among non-Hispanic Black (OR=1.18, 95% CI 1.00-1.39) compared to non-Hispanic White (OR=1.40, 95% CI 1.18- 1.65) women and among women living in urban (OR=1.33, 95% CI 1.18-1.50) compared to rural (OR=1.52, 95% CI 1.15-2.03) counties. Neighborhood deprivation was associated with an increase in ERBB2+ breast cancer (OR=1.19, 95% CI 1.00-1.40), which was confined to non- Hispanic White women (OR=1.29, 95% CI 1.00-1.66) and women living in urban counties (OR=1.25, 95% CI 1.04-1.52). The OR for luminal B breast cancer was 1.08 (95% CI 0.96- 1.21). Although race did not modify this relationship, an association was observed only among women living in urban counties (OR=1.14, 95% CI 1.00-1.29). Conclusions: In this population of Georgia breast cancer patients, neighborhood deprivation was associated with an increase in TNBC, regardless of race or rurality. The weaker associations among non-Hispanic Black women and women living in urban counties suggests that other factors, in addition to neighborhood deprivation, may play an important role in TNBC development among Black women and women residing in urban environments. Citation Format: Lauren E. Barber, Jasmine M. Miller-Kleinhenz, Maret L. Maliniak, Leah Moubadder, Jeffrey M. Switchenko, Lauren E. McCullough. Understanding the role of neighborhood deprivation in racial and urban-rural disparities in triple negative breast cancer [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A037.

Abstract A041: Assessing the impact of neighborhood structural racism on survival for African American men with prostate cancer; a population-based cancer registry study across eight US states

Abstract Background: African American (AA) men are more than twice as likely to die of prostate cancer (PC) compared to non-Hispanic White men in the US. Among AA men, we examined survival after PC diagnosis by neighborhood-level structural racism and whether its effects are mediated by neighborhood socioeconomic status (nSES). Methods: We pooled data for 133,241 AA men diagnosed with PC from 2000-2013 from ten population-based cancer registries across eight states (CA, Detroit, FL, GA, LA, NJ, NY, TX) of the RESPOND Study (Research on Prostate Cancer among African American Men). Residential addresses at PC diagnosis were geocoded and appended to census block-group measures of structural racism (contemporary redlining, racial/ethnic segregation typology, and racial bias in mortgage lending) and nSES, an index comprising measures of income, education, occupation, employment, and housing. We used Cox models and the %mediation SAS macro for causal mediation to assess overall and PC- specific survival according to structural racism and to quantify the extent to which survival differences were mediated by nSES. Models were adjusted for diagnosis year and age, state of residence, and marital status. Results: There were 46,830 deaths overall with 12,272 PC-specific deaths among the study population. Greater mortality risk was observed among AA men residing in neighborhoods in the highest compared to lowest quartile of redlining (total effect) for both overall survival (Hazards ratio [HR]=1.26; 95% CI=1.22, 1.31) and PC-specific survival (HR=1.30; 95% CI=1.21-1.39). Neighborhood SES mediated 59% and 47% of the effect of redlining, resulting in natural direct effects of HR=1.11 (95% CI=1.05, 1.17) and HR=1.16 (95% CI=1.04, 1.29) for overall and PC-specific survival, respectively. Compared to predominantly White neighborhoods, AA men residing in neighborhoods with all other racial/ethnic typologies had greater overall and PC-specific mortality risk, with largest risk for neighborhoods with predominantly AA or mixed with Hispanic and AA residents. Neighborhood SES completely mediated the effect of racial/ethnic typology on survival for all typologies except that of mixed Hispanic and Black residents (37% and 25% mediation by nSES for overall and PC-specific survival, respectively). There was no association between racial bias in mortgage lending and survival. Results from models additionally adjusted for prognosis (Prostate Cancer Cohort Consortium [PC3] classification of aggressive disease) and treatment (receipt of surgery, radiation, chemotherapy, or hormone therapy) were similar. Conclusions: Neighborhood SES explains substantial portions of the impact of redlining and racial/ethnic typology on overall and PC-specific survival among AA men across eight states in the US. Remaining survival differences for the most redlined neighborhoods and neighborhoods with a mix of Hispanic and Black residents independent of nSES suggest alternative pathways for the impact of neighborhood structural racism on mortality risk for AA men with PC. Citation Format: Mindy C. DeRouen, Meera Sangaramoorthy, Katherine Lin, Annie Vu, Dan Meltzer, Pushkar Inamdar, Yuhong Zhou, Kevin Ward, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Beebe-Dimmer, Anshu Shrestha, Aaron P. Thrift, Margaret Gates-Kuliszewski, Peter Kanetsky, Tamara Lotan, Anthony Colombo, David Conti, Christopher Haiman, Ann Hamilton, Kirsten Beyer, Joseph Gibbons, Iona Cheng, Salma Shariff-Marco, Scarlett Gomez. Assessing the impact of neighborhood structural racism on survival for African American men with prostate cancer; a population-based cancer registry study across eight US states [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A041.

National Experimental Wellbeing Statistics (NEWS)

The NEWS project is improving and expanding estimates of income, poverty, and other measures of economic wellbeing by linking survey, administrative, and commercial data. The initial release addressed biases from unit nonresponse through improved weights, missing income information in survey and administrative data through improved imputation, and misreporting by combining or replacing survey responses with administrative data.

Impact of Institutional and Non-institutional Agricultural Credit on Farmers-income and Constraint Analysis in Telangana, India

The present study is to analyse Impact of institutional and non-institutional Agricultural credit on farmers income and Constraint analysis. The study was conducted in 3 districts, 6 mandals, 12 villages and 120 sample farmers were selected for the study. Cost of cultivation (cost concepts) and income measures were used to analyse impact of agricultural credit on farm household income. Garette’s ranking technique was used to analyse the constraints faced by farmers in availing Agricultural credit. The cost of paddy cultivation was ₹78212.78 for institutional farmers and ₹80,726.78 for non-institutional farmers. ₹62050.96 is the Net Return for institutional farmers, whereas ₹54879.66 is for non-institutional farmers. Institutional farmers had a return on investment per rupee of 1.81, while non-institutional farmers had a return of 1.69. The major constraint faced by farmers is delays in loan disbursement. Agricultural credit has a positive impact on farm income. Therefore, the increase in institutional loans has improved the borrower farmers' economies. Timely disbursement of loans, simplifying the application procedure/documentation procedure and educating farmers about agricultural loans are suggested to improve crop loans availing in institutions.

Impact of Droughts on Served Drinking Water Disparities in California, 2007-2020.

Objectives. To quantify the impact of droughts on drinking water arsenic and nitrate levels provided by community water systems (CWSs) in California and to assess whether this effect varies across sociodemographic subgroups. Methods. I integrated CWS characteristics, drought records, sociodemographic data, and regulatory drinking water samples (n = 83 317) from 2378 water systems serving 34.8 million residents from 2007 to 2020. I analyzed differential drought effects using fixed-effect regression analyses that cumulatively accounted for CWS-level trends, income, and agricultural measures. Results. CWSs serving majority Latino/a communities show persistently higher and more variable drinking water nitrate levels. Drought increased nitrate concentrations in majority Latino/a communities, with the effect doubling for CWSs with more than 75% Latino/a populations served. Arsenic concentrations in surface sources also increased during drought for all groups. Differential effects are driven by very small (< 500) and privately owned systems. Conclusions. Impending droughts driven by climate change may further increase drinking water disparities and arsenic threats. This underscores the critical need to address existing inequities in climate resilience planning and grant making. (Am J Public Health. 2024;114(9):935-945. https://doi.org/10.2105/AJPH.2024.307758).

A study on cost of cultivation and various income measures of pea in Jhansi district of Bundelkhand region of Uttar Pradesh

A study on cost of cultivation and various income measures of pea in Jhansi district of Bundelkhand region of Uttar Pradesh

Slavcho Zagorov (1898–1970), A forgotten pioneer of energy and ecological economics

This article aims to rediscover a relatively unknown author to the general public, Slavcho Zagorov, and to revive his ideas. Zagorov was a Bulgarian economist and statistician whose main works date back to 1954 and are mainly devoted to the concept of energy flows in the economy and human metabolism explained through the prism of thermodynamics. His work and career are reminiscent of another Balkan economist, Nicholas Georgescu-Roegen. We first present Zagorov's theoretical work on the importance of energy in economic activity and secondly on the measurement of national income and productivity through energy. Thirdly, we show the relation he establishes between energy and utility. Finally, we discuss his texts in relation to his professional and personal trajectory and point out some preliminary elements of comparison with Georgescu-Roegen's work.

Economic Inequality, Life Expectancy, and Interpersonal Violence in London Neighborhoods.

Positive associations between levels of socioeconomic inequality and homicide rates have been reported at various geographical levels (e.g., between countries, states, cities, and neighborhoods within a city). However, the extent to which inequality predicts levels of non-lethal violence has been less frequently studied. The present study was conducted to investigate the association between socioeconomic inequality and levels of non-lethal interpersonal violence across neighborhoods of London during the period 2010 to 2012, using two independent data sources: Metropolitan Police service recorded violent crime and London Ambulance Service recorded assaults. Mean income per person and local life expectancy were included as additional predictors. Following exclusions due to census boundary changes, across 533 London wards, there were positive bivariate associations between both violence measures and a measure of inequality between neighborhoods (census lower layer super output areas [LSOAs]) within a ward. Moreover, there were negative bivariate associations between violence rates and both ward mean income and life expectancy measures for males and females. However, in a regression analysis only inequality and male life expectancy were consistent predictors of rates of interpersonal violence across outcome measures. The results of the present study provide further evidence of an association between levels of economic inequality and rates of interpersonal violence. The findings, for variation in rates of non-lethal violence across small geographical areas (neighborhoods), build on previous research that has mostly focused on rates of lethal violence and has tended to use aggregate measures across larger geographical areas.

The TBI Model Systems Neighborhood Socioeconomic Disadvantage Index (TBIMS-NSDI): Development and Comparison to Individual Socioeconomic Characteristics.

To create a census-based composite neighborhood socioeconomic deprivation index (NSDI) from geocoded residential addresses and to quantify how NSDI aligns with individual-level socioeconomic factors among people with traumatic brain injury (TBI). Community. People enrolled in the TBI Model Systems National Database (TBIMS NDB). Secondary analysis of a longitudinal cohort study. The TBIMS-NSDI was calculated at the census tract level for the United States population based on a principal components analysis of eight census tract-level variables from the American Community Survey. Individual socioeconomic characteristics from the TBIMS NDB were personal household income, education (years), and unemployment status. Neighborhood:Individual NSDI residuals represent the difference between predicted neighborhood disadvantage based on individual socioeconomic characteristics versus observed neighborhood disadvantage based on the TBIMS-NSDI. A single principal component was found to encompass the eight socioeconomic neighborhood-level variables. It was normally distributed across follow-up years 2, 5, and 10 post-injury in the TBIMS NDB. In all years, the TBIMS-NDSI was significantly associated with individual-level measures of household income and education but not unemployment status. Males, persons of Black and Hispanic background, Medicaid recipients, persons with TBI caused by violence, and those living in urban areas, as well as in the Northeast or Southern regions of the United States, were more likely to have greater neighborhood disadvantage than predicted based on their individual socioeconomic characteristics. The TBIMS-NSDI provides a neighborhood-level indicator of socioeconomic disadvantage, an important social determinant of outcomes from TBI. The Neighborhood:Individual NSDI residual adds another dimension to the TBIMS-NSDI by summarizing how a person's socioeconomic status aligns with their neighborhood socioeconomics. Future studies should evaluate how both measures affect TBI recovery and life quality. Research studying neighborhood socioeconomic disadvantage may improve our understanding of how systemic adversity influences outcomes after TBI.

Negative life events, sleep quality, and depression among older adults in Shandong Province, China: A conditional process analysis based on economic income.

Negative life events have been reported as a risk factor for depression. However, the mechanism between negative life events and depression is still unclear. This study aimed to explore the mediating role of sleep quality and the moderating role of economic income in the association between negative life events and depression among older adults aged 60 years and over. A multi-stage stratified sampling method was used to select elderly individuals over 60 years old in Shandong, China, making use of the Household Health Interview Survey (2020). In total, 3868 older adults completed the measures of negative life events, sleep quality, depression, and economic income. Negative life events positively predicted depression among the elderly (proportion of direct effect, 55.12%), and poor sleep quality could mediate this association (proportion of indirect effect, 44.87%). Economic income played a moderating role in the relationship between negative life events, sleep quality, and depression (the first and second half of the mediating effect, the direct effect of negative life events on depression). Both effects were weaker among the elderly with higher economic incomes. Negative life events had positive effects on depression in older adults. Economic income moderated the direct effect of negative life events and the mediating effect (first and second half) of sleep quality on depression. When the elderly experience negative life events, interventions for improving their sleep quality and financial support could effectively prevent depression. Geriatr Gerontol Int 2024; 24: 751-757.

Aerodynamic performance and flow field characteristics of wind turbines under shear incoming flow conditions

Abstract With the large size of the units, wind farms are evaluated in order to improve the accuracy of the incoming flow measurement and to improve the unit control strategy. In this paper, the turbulent wind field generated by autoregressive linear filtering using a large eddy simulation turbulence model is used to study the wind speed-induced zone under shear incoming flow conditions. At the same time, the wake and aerodynamic performances of the wind turbine under different incoming flow conditions are investigated, and conclusions are obtained. 1) The larger the shear index is, the larger the amplitude is at the first frequency component of the power and the thrust, and the larger the fatigue load is for the wind turbine. 2) For the wind turbine wake flow in the case of smaller wind turbine size, the wake velocity profiles at different shear indices cross and overlap in the transition and far wake regions. At position 0.5 D, the turbulence profiles with different shear indices basically overlap; the larger the shear index is, the more intense the wake flow exchange is and the greater the turbulence intensity in the wake region will be. 3) For the wind speed-induced region, at position −0.1 D, the incoming flow velocity distribution is subject to the combined effect of induction and shear, and the induction effect of the wind turbine wheel is a little larger. The larger the shear index, the greater the turbulence intensity.