Poor Research Articles

Patient-Reported Social Determinants of Health in Patients With Heart Failure.

Social determinants of health (SDOH) complicate medical care and affect clinical outcomes, but the lack of a reliable structured interview for medical patients has impeded clinical assessment and research on SDOH. We assessed the reliability and validity of a newly developed SDOH Patient Interview Form and investigated SDOH in patients with heart failure. The SDOH Patient Interview Form was administered to recently hospitalized patients with heart failure between January 2021 and April 2024. The interviews were recorded, and 50 were randomly selected for the interrater reliability analysis. The sample included 367 participants (mean age, 61.2±12.1 years; 42.5% women; 57.7% minorities). The interrater reliability of SDOH Patient Interview Form categories (eg, Legal and Social Problems) was 100%. The κ reliability coefficients for individual items were ≥0.94. Higher lifetime SDOH counts were associated with lower age and income and higher New York Heart Association class and body mass index. Two distinct sets of problems were found to contribute to relatively high burdens of SDOH. The first originates with abuse in childhood and presents as severe socioeconomic deprivation in adulthood. The second includes losses of family members and occupational, financial, and caregiver stress along with difficulty affording medical care. The SDOH Patient Interview Form is a reliable instrument for assessing patient-reported SDOH in patients with heart failure. It is suitable for use in research and clinical contexts but requires further testing in other medical patient populations. This study revealed 2 distinct patterns of stressful problems that can contribute to a high overall burden of SDOH. URL: https://clinicaltrials.gov; Unique identifier: NCT04637776.

Older Worker's Job Search Activities and Employment Transition.

This study investigated job search patterns among American older workers. Data from the 2016-2018 Health and Retirement Study included 1501 individuals aged 50+ who were looking for jobs in 2016. Latent Class Analysis (LCA) was conducted to identify job search patterns based on nine types of job search activities. Multinomial logistic regression was then used to examine membership in each class. Five job search patterns emerged from the LCA analysis, including No Ads, Ads only, Friends & Ads, Phone & Ads, and Agencies & Ads. Employment transitions were related to job search patterns. Unemployed older workers, despite utilizing more diverse job search methods, were less likely to secure new jobs compared to their employed peers. These findings highlight the need for workforce development programs to focus on workplace skill-building training and educational opportunities before becoming unemployed and age-friendly workforce development tailored to older workers with low-skilled and low income.

Association between caregiving factors and depression symptoms in family caregivers of persons with disabilities during the COVID-19 pandemic in Hong Kong: a structural equation analysis.

Caregiving has been widely recognised as a potential risk factor for caregivers' psychological well-being in previous studies. The objective of this study is to examine the association between multiple factors of the caregiving process and the depression risk of caregivers, as well as the mediating effect of caregiver burden in these associations. Cross-sectional study. The Hong Kong Polytechnic University in Hong Kong Special Administrative Region, China. 597 family caregivers of persons with disabilities in December 2020 under the Hong Kong governmental initiative, 'Persons with Disabilities and Rehabilitation Program'. Indications of depression were assessed through the application of the World Health Organization-Five Well-being Index (1998 version). A structural equation model (SEM) was applied using Analysis of Moment Structure (AMOS) 28.0 to identify the association between a series of caregiving-related factors and depression risk, as well as test the mediating role of caregiver burden in these associations. 50% of care recipients needed assistance in all four care need categories, with daily living care being the most prominent (72.4%). Caregivers dedicated around 79.6 hours (SD: 52.2) per week on caregiving duties. Nearly 44% of the caregivers had at least one diagnosed disease. Only 5% of caregivers considered that they had a poor caregiving ability, whereas 87.2% of them reported heightened caregiving pressure during the COVID-19 pandemic. In this study, the average caregiver burden score was 6.6 (SD: 3.3), and the average depression score was 6.7 (SD: 5.1). The results of the SEM model showed that care needs of care recipients (ß (95% CI): -0.201 (-0.355, -0.083), p=0.001), weekly caregiving hours (ß (95% CI): -0.126 (-0.215, -0.067), p=0.001) and presence of emotional issues (ß (95% CI): -0.329 (-0.538, -0.184), p=0.001) were positively associated with depression risk of caregivers, fully mediated by caregiver burden. Additionally, caregivers' health status had both direct (ß (95% CI): -0.234 (-0.388, -0.101), p=0.001) and indirect (ß (95% CI): -0.126 (-0.215, -0.067), p=0.001) effects on depression, indicating that caregiver burden partially mediated this pathway (proportion mediation is 35%). A higher self-evaluation of caregiving ability was related to a lower risk of depression (ß (95% CI): 0.281 (0.169, 0.396), p=0.001), and caregiver burden did not mediate this pathway. Care needs of care recipients, weekly caregiving hours, caregivers' health status and presence of emotional issues during the COVID-19 pandemic were adversely associated with an increased depression risk for caregivers, and these were either fully or partially mediated by caregiver burden. Additionally, caregivers' lower self-evaluation of their caregiving ability was an independent factor that directly contributes to an increased depression risk.

Barriers to and facilitators for attending dental care appointments among adults in low- and middle-income countries: a scoping review.

Oral diseases are a major public health concern in Low and Middle Income Countries (LMICs), where effective treatment requires multiple appointments. Despite its importance, limited research has explored appointment adherence among adults in these settings. This scoping review identifies the barriers and facilitators to attending dental care appointments in LMICs. The current review followed JBI Scoping Review Methodology. The Databases of Dentistry, Oral Sciences Source (EBSCO), MEDLINE (Ovid), Embase (Ovid), Cochrane CENTRAL, Scopus and grey literature sources were searched systematically from inception till November 2024. Two independent reviewers performed data extraction using a customized JBI data extraction form. The Theoretical Domains Framework categorized barriers and facilitators of dental appointment keeping. Findings were tabulated and synthesized narratively with recommendations to improve dental attendance. Ten articles met the inclusion criteria after being screened through 5571 titles, abstracts, and 210 full texts. Knowledge, social and professional roles and identity, beliefs about capabilities, consequences, memory, attention, decision-making processes, environmental context and resources, social influence, and emotion are the main domains under which barriers and facilitators were identified. Environmental context and resource constraints were the most common barriers, while social influence was the main facilitator. The dental appointment adherence issues were determined to be comparable in public practice and university settings. It is necessary to acknowledge the barriers and facilitators to dental appointment keeping to improve the effectiveness of the dental health system, ensure continuity of care, and encourage better patient-doctor relationships. Tailored interventions are required in the dental setting to effectively manage and reduce disparities in patient care.

Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies.

Converging evidence indicates an adolescent mental health crisis in Western societies that has developed and exacerbated over the past decade. The proposed driving factors of this trend include more screen time, physical inactivity, and social isolation, but their causal influence on mental health is insufficiently understood. The objective of this study is to test whether and based on which predictor variables the development of mental health in adolescents in the last decade can be predicted and to better understand the causal chain of factors at work. We implemented an interpretable machine learning pipeline based on gradient boosting regression with repeated cross-validation to assess the development of mental health throughout adolescence in members of 2 longitudinal cohort studies, the British Millenium cohort (MC; n=8599) and the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) cohort (n=1212). In total, 144 (MC) and 102 (KiGGS) predictors assessed at the age of around 13.8 years (MC) and 11.6 years (KiGGS) were used to assess mental health at the ages of around 16.7 years (MC) and 16.4 years (KiGGS). Based on these predictive models, we used permutation-based feature importance analyses to identify relevant predictors and predictor domains. Moreover, we performed partial dependence analyses in a causal inference framework to determine the direct effects of physical inactivity, screen time, and peer problems on the development of mental health. The average cross-validated Pearson correlation coefficient (r) between predicted and true mental health in late adolescence was 0.614 (MC) and 0.466 (KiGGS). Feature importance analyses indicated a strong impact of preexisting mental health and weaker impacts of sex (female as a risk factor), physical health (chronic disease as a risk factor), lifestyle, and socioeconomic and family factors (eg, low parental education, income, and mental health as risk factors). Causal inference analyses suggested a strong direct effect of peer relationships, but only a small direct effect of physical inactivity and a very small direct effect of screen time. Mental health development during adolescence can be assessed by a combination of variables from early adolescence. Peer problems represent an important direct cause of mental health development, and their deterioration may contribute to the current mental health crisis.

Disparities in Quality of Life and Family Functioning 24Months After Diagnosis of a Childhood Brain Tumour: A Longitudinal Cohort Study.

Increases in survival for childhood brain tumour are evidence of improved care; however, survival is not the only outcome that matters. There has been little scholarly investigation into the psychosocial wellbeing of the diagnosed child and their parents/carers (caregivers) in the early years after diagnosis-fewer still have considered indicators for increased early support. The aim of the present study was to explore whether child and caregiver quality of life (QoL), and family functioning, change over the first 24months post-diagnosis, and whether this varies by clinical and sociodemographic factors. Ninety-six caregivers were recruited less than 3months after their child was diagnosed to complete surveys at five time points. Outcome measures were child QoL (caregiver-proxy), caregiver QoL, and family functioning; linear mixed models with random intercepts were used to assess predictors for each. Child and caregiver QoL did not improve with time, nor did family functioning. Those with a child who had a low-grade tumour at baseline who received chemotherapy and/or radiation consistently reported the worst QoL for themselves and their child. Household income was a predictor of all outcomes-those with a lower income (<AU$70,000) reported worse experiences. Time alone may not improve QoL and family functioning. Psychosocial support must be provided to all children with a brain tumour and their families, regardless of tumour grade. Families who have a child diagnosed with any brain tumour and who have a lower household income would likely benefit from intensive psychosocial support from diagnosis and beyond.

Calcul De L’esperance De Vie Des Chomeurs En Rrepublique Democratique Congo/Kinshasa (2021-2022) Par La Methode De Regression Logistique Binaire Floue.

The main objective of this research was to contribute to the empirical literature on the application of fuzzy binary logistic regression to the life expectancy of the unemployed in DRC/Kinshasa. Specifically, it aimed to evaluate the proportion of households living without employment (unemployed), identify the explanatory or determining factors of the life expectancy of the unemployed, and finally determine the effects of factors directly related to household living conditions. The data for this study were collected through a survey of 386 households in Kinshasa, selected using a non-probabilistic sampling method. Descriptive statistics, inferential statistics, and multiple regression based on the logistic model were used to identify the explanatory factors of the life expectancy of the unemployed. The results of this study reveal that most of the surveyed households are unemployed (92.49%). Logistic regression reveals that the explanatory factors that improve the life expectancy of the unemployed in Kinshasa are: level of education (secondary and graduate), parcel occupation status (owner), activity characteristics (informal), time allocated to informal activities, prioritized healthcare mode (modern medicine), income (medium and high), and access to drinking water. On the other hand, the factors that reduce the life expectancy of the unemployed are: low income and non-food expenditure (medium).

Strategi Pengurangan Ketimpangan Pendapatan di Jawa Barat Melalui Peningkatan Pendidikan dan Pengurangan Kemiskinan

Income inequality remains a major challenge in the economic development of West Java Province, despite positive economic growth in recent years. This study aims to analyze the effects of economic growth, education level, and poverty rate on income inequality across 27 regencies/cities in West Java during the 2019–2023 period. The method employed is panel data regression using 135 observations, analyzed through the Fixed Effect Model (FEM) based on the results of Chow and Hausman tests. The findings reveal that economic growth does not have a significant effect on income inequality. In contrast, education level and poverty rate are found to significantly influence income inequality. These results underscore the importance of enhancing education quality and reducing poverty as strategic efforts to mitigate income disparities. The study also indicates that non-inclusive economic growth alone is insufficient to reduce income inequality. Policy implications point to the need for improving access to education and implementing empowerment programs for the poor. This study is limited by the scope of variables and the relatively short time frame, suggesting the need for future research using a more comprehensive and extended approach

Disparities in prescriptions among Danish heart failure patients: a national longitudinal cohort study.

Angiotensin receptor-neprilysin inhibitors (ARNi) and sodium-glucose co-transporter 2 inhibitors (SGLT2i) have a Class I indication in the European Society of Cardiology's guidelines for the diagnosis and treatment of acute and chronic heart failure due to benefits in symptom management, rehospitalization rates, and mortality in heart failure. The aim of this study was to investigate demographic, geographic and socioeconomic disparities in prescriptions for ARNi and SGLT2i for heart failure patients in a universal healthcare system. We used national registers to identify all Danish heart failure patients who were diagnosed on or after the updated clinical guidelines by the European Society of Cardiology (14 July 2016 for ARNi and 27 August 2021 for SGLT2i). Patients were followed until redemption of prescription, emigration, death or censoring on 30 June 2022, whichever came first. The Aalen-Johansen estimator and Cox proportional hazard models were used for individual analysis of ARNi (n=43 625) and SGLT2i (n=2819). The following factors were associated with lack of prescriptions for ARNi and SGLT2i: being women, older age, living alone and being non-native Danish or descendant. HRs ranged from 0.31 (95% CI 0.28 to 0.36) to 0.86 (95% CI 0.80 to 0.93) for ARNi and 0.49 (95% CI 0.41 to 0.58) to 0.93 (95% CI 0.72 to 1.20) for SGLT2i. Prescriptions for both ARNi and SGLT2i showed a social gradient, with the gradient for ARNi being statistically significant. Substantial disparity was found in prescriptions for the potentially life-saving medications, with lack of prescriptions being associated with lower education, lower income and several demographic characteristics.

Multiple Long-Term Conditions-Multi-Morbidity and Socioeconomic Inequalities in the Adult Population in Brazil: A Gender Perspective

In a context of demographic and epidemiological transitions and significant ocioeconomic inequalities, Brazil is experiencing an increasing prevalence of chronic diseases. Based on the Brazilian National Health Survey 2019, the study analysed the impact of education and household income inequalities on multiple long-term chronic conditions (MLTC) in adults aged 18 and older from a gender perspective. In a sample of 86,831 participants, socioeconomic inequalities were assessed using regression- based measures. In the general population the prevalence of MLTC was 29. 5%, higher in women and older adults, raising concerns about increasing rates in young adults. Diferences between the observed and predicted MLTC prevalence rates were noted, with lower-income and educational attainment groups possibly experiencing under-diagnosis, while higher -income and educated groups may be over-diagnosed. The study found that education and income levels influenced the risk of MLTC, with varying ef ects based on gender and age. Women with lower education and household incomes had a higher risk, while in men, higher education and household income were associated with increased risk. The research emphasizes the need for preventive policies for young adults and further studies on risk factors, healthcare costs, and health coverage policies to reduce inequalities

Fertility counseling in early-onset colorectal cancer and the impact of patient characteristics.

This study evaluated how frequently patients with early onset colorectal cancer received fertility counseling and whether patient characteristics affected the likelihood of receiving such counseling. We conducted a single-center retrospective review of all new patients seen by medical oncology for colorectal cancer who were age 55years or younger for men and 50years or younger for women. Associations between patient demographics and clinical characteristics with receipt of fertility counseling were explored using univariate analyses and multivariable logistical regression analyses. A total of 194 patients were included, of whom 15.5% received fertility counseling. Using multivariate analysis, we found that age < 40 (OR 15.587, p < 0.0001, 95% CI 4.841-50.191) and female sex (OR 3.979, p = 0.0292, 95% CI 1.150-13.770) were correlated with increased likelihood of fertility counseling. Patients living in areas of higher household income were more likely to receive fertility counseling, with a statistically significant difference between the 3rd and 1st quartiles of income (p = 0.0369, 95% CI 1.161-115.940). A majority of patients with EOCRC did not receive fertility counseling despite the known toxicities of CRC treatment modalities on fertility. Older age, male sex, and residence in areas of lower income were associated with decreased likelihood of receiving fertility counseling.

No one-size-fits-all solution. Effects of social policies on in-work poverty

Abstract The paper studies effects of social policies on in-work poverty risks, distinguishing between measures that either intervene in labour market processes - i.e. predistribution policies - or redistribute towards those with low incomes. The analyses use data from EU-SILC and macro-level indicators from various sources to estimate general as well as household-typespecific effects using longitudinal methods. Results reveal important differences between specific policies: increasing minimum wages contributes to reducing low-wage risks, but has no significant effect on in-work poverty risks. In contrast, there is a negative effect of strict employment protection legislation across almost all household types on in-work poverty, which is consistent with the positive role this measure plays for supporting earnings that are sufficient to provide not only for one person, but also potential dependants in the household. With respect to redistributional policies, both unemployment benefits and benefits to low earners reduce poverty due to their contribution to public poverty-reduction. However, whereas unemployment benefits only reduce in-work poverty among couple households, benefits to low earners mainly contribute to lower poverty risks among employed single parents. Overall, the results underscore that predistributional and redistributional as well as universal and targeted interventions cannot easily substitute each other.

A sleep staging model based on adversarial domain generalized residual attention network

To solve the problem of poor generalization ability of the model on unknown data and the difference of physiological signals between different subjects. A sleep staging model based on Adversarial Domain Generalized Residual Attention Network (ADG-RANet) is designed. The model is divided into three parts: feature extractor, domain discriminator and label classifier. In the feature extractor part, the channel attention network is combined with the residual block to selectively enhance the important features and the correlation between multi-channel physiological signals. Inspired by the idea of U-shaped network, the details and context information in the input data are effectively captured through up-sampling and skip connection operations. The Bi-GRU network is used to further extract the deep temporal features. A Gradient Reversal Layer (GRL) is introduced between the domain discriminator and the feature extractor to promote the feature extractor to obtain the invariant features between different subjects through the adversarial training process. The label classifier uses the deep features learned by the feature extractor to perform sleep staging. According to the AASM sleep staging criterion, the five-classification accuracy of the model on the ISRUC-S3 dataset was 82.51%, the m-F1 score was 0.8100, and the Kappa coefficient was 0.7748. By observing the test results of each fold and comparing with the benchmark model, it is verified that the proposed model has better generalization on unknown data.

Heat-related rest-break recommendations for farmworkers in California based on wet-bulb globe temperature

Extreme heat is a global public health concern that is becoming more frequent and severe in recent periods. Translating Earth science data into policy-relevant metrics, such as rest breaks, is challenging but needed to protect outdoor workers from heat stress. Here, we determine rest-break requirements for the farmworkers of the Imperial and Coachella Valleys in southern California, which have a high poverty rate and the highest heat-illness rates in California. We used high-resolution outputs from a validated Weather Research and Forecasting Model (WRF) at 1-km grid resolution that includes irrigation, a key modulator of heat stress in the study region. We calculated exceedances of heat stress indicators under three existing policy guidelines that use wet-bulb globe temperature (WBGT), heat index (HI), or dry-bulb temperature (DBT), and translated them into rest breaks needed for farmworker safety. WBGT-based rest minutes are most sensitive to the spatiotemporal variation in heat exposure compared to DBT or HI and vary with acclimatization status, season, and work shifts. Recommended rest breaks to protect farmworkers from heat stress range from 2 to 32 min per work-hour between April and August. Although results are specific to California, our method is adaptable for calculating region-specific rest break requirements worldwide.

EXPLORING THE ROLE OF PARENTAL CARE AND OVERPROTECTION IN PREDICTING ERECTILE DYSFUNCTION: A MACHINE LEARNING APPROACH

EXPLORING THE ROLE OF PARENTAL CARE AND OVERPROTECTION IN PREDICTING ERECTILE DYSFUNCTION: A MACHINE LEARNING APPROACH

Urban poverty and rural poverty in different countries: A systematic literature review

The complex issues on poverty is widespread globally and affecting countries at various levels of economic development. This study examines urban and rural poverty disparities using measurement, comparison, multidimensional analysis, and identifying contributing factors. Rural poverty shows significant reduction, while urban poverty is more complex. Cross-country comparisons reveal widespread rural poverty, influenced by human resources, nutrition, housing, and reproduction. India, China, and Indonesia have conducted more poverty-related research. Poverty reduction exhibits an inverted U-pattern relationship between Urban-Rural Income Ratio (URI) and rural poverty in several countries, with non-agricultural productivity impacting urban areas. Sustainable public policies and managing urban population growth are essential for poverty alleviation. Urban and rural poverty impact children's cognitive abilities and food consumption. Integrated policies are crucial, necessitating further research and community engagement. Longitudinal research and cross-country comparisons provide insights into effective poverty policies in diverse contexts.

Socioeconomic differences in discharge against medical advice and hospital admission among emergency department visits associated with substance use in the United States

BackgroundDischarge against medical advice (DAMA) and inpatient admission (IA) among emergency department (ED) visits are two important outcomes in hospital utilization, while the first one has been mainly considered a negative outcome.AimsThis study aimed to examine the association of socioeconomic factors with DAMA and IA among ED visits with substance use (age 12–64 years) before and after the COVID-19 pandemic.MethodsThe study retrospectively analyzed the Nationwide Emergency Department Sample (NEDS) from 2019 to 2020. The International Classification of Diseases 10th Revision (ICD-10) codes were used to identify opioid, cannabis, and alcohol use, and smoking.ResultsThe pandemic was significantly associated with higher odds of IA (OR 1.04, CI 1.02–1.06). Female gender and rural hospitals were adversely associated with both DAMA and IA, but lower household incomes were positively and negatively associated with DAMA and IA, respectively. Race and health insurance were partly differently associated with these outcomes. Asian patients exhibited significantly lower odds (OR 0.82, CI 0.71–0.88) regarding DAMA. Black (OR 0.79, CI 0.78–0.80) and Native American patients (OR 0.87, CI 0.82–0.90) exhibited lower odds, and Hispanic (OR 1.05, CI 1.03–1.06) and Asian patients (OR 1.40, CI 1.33–1.44) had higher odds compared to White patients in terms of AI. Except for self-pay, which was associated with lower odds of IA, Medicaid, self-pay, and free care were significantly associated with higher odds of DAMA and IA. Our results also showed that the COVID-19 pandemic affected the association of health insurance with IA, but not with DAMA.ConclusionThese findings highlight the complex association of socioeconomic factors with DAMA and IA. By addressing these differences within the hospital setting, providers can mitigate the negative consequences of substance use on patient health and reduce the burden on healthcare systems.

Multilevel Analysis of Factors Underlying in‐Work Poverty: Evidence From Türkiye

ABSTRACTIn‐work poverty is a prevalent phenomenon in many countries and creates significant challenges from various aspects. This study investigates the underlying factors of in‐work poverty utilizing Türkiye as a case study and using the latest available (2022) microdata from the Survey of Income and Living Conditions (SILC). It first measures the at risk of poverty or social exclusion rate (AROPE) among the working population, revealing that 22.13% of workers suffer from poverty and there is a considerable sectoral variation. Subsequently, the underlying demographic characteristics, along with job‐related and regional factors of in‐work poverty, are examined through multilevel logistic regression analysis. Among demographic characteristics, being older and having higher education levels are associated with lower probabilities of in‐work poverty, while household dependency raises this risk. Analyzing the association between in‐work poverty and job characteristics indicates that public sector employment and social security registration lower the probability of in‐work poverty. Furthermore, compared to the self‐employed, employers are much less likely to be poor, while employees are more vulnerable. Finally, living in a region with a higher GDP per capita lowers the probability of working poverty, whereas regions with higher Gini indices, unemployment rates, and Syrian refugee rates are associated with higher poverty risks.

Global, regional, and national burden of nutritional deficiencies spanning from 1990 to 2021, with a focus on the impacts observed during the COVID-19 pandemic

BackgroundThe United Nations has recognized nutritional deficiencies as a critical health issue that necessitates urgent eradication. This study aimed to provide a comprehensive analysis of the spatial distribution and temporal trends of the global disease burden associated with nutritional deficiencies and their four subtypes from 1990 to 2021, with a particular focus on the impact of the COVID-19 pandemic.MethodsThis study primarily employs the most recent data from the Global Burden of Disease (GBD) 2021 to conduct a thorough analysis of the distribution trends of incidence, mortality, and disability-adjusted life years (DALYs) associated with nutritional deficiencies and their four subtypes from 1990 to 2021, incorporating detailed subgroup analyses categorized by sex, age, and region. In comparison to the GBD 2019, the GBD 2021 update places a particular emphasis on supplementing disease burden data for the period of the COVID-19 pandemic (2019–2021). Furthermore, this study investigates the primary risk factors contributing to disability-adjusted life years (DALYs) linked to nutritional deficiencies.ResultsBetween 1990 and 2021, the global burden of nutritional deficiencies experienced a substantial decline, evidenced by a 54.9% reduction in the age-standardized incidence rate (ASIR), a 72.2% decrease in the age-standardized death rate (ASDR), and a 51.9% reduction in the age-standardized DALY rate. However, it is noteworthy that the burden of iodine deficiency (ASIR: 137.72 vs. 75.49; Age-standardized DALY rate: 35.43 vs. 19.98) and dietary iron deficiency (Age-standardized DALY rate: 597.97 vs. 253.05) is considerably greater in women than in men. Moreover, in regions characterized by a low social demographic index (SDI) and lower income levels, the burden of diseases associated with nutritional deficiencies remains substantial. In contrast, the COVID-19 pandemic has not markedly changed the epidemiological profile of nutritional deficiencies compared to the pre-2019 period, and the global burden of nutritional deficiencies has continued its gradual decline.ConclusionsDespite a decline in the global burden of nutritional deficiencies over time, significant disparities related to gender, region, and age persist. Fortunately, the COVID-19 pandemic has had a relatively limited impact on the global burden of nutritional deficiencies. Healthcare institutions must formulate more targeted strategies aimed at alleviating the adverse effects of nutritional deficiencies on global public health.

THE MANY FACES OF POVERTY: A COMPREHENSIVE ANALYSIS ON MEASUREMENT OF POVERTY IN TÜRKİYE

Although poverty statistics serve as crucial economic and social indicators, their measurement varies depending on the chosen definition of poverty. This study examines whether poverty estimations in Türkiye significantly differ based on the definition used and explores which concept of poverty is most appropriate. Utilizing the SILC micro datasets from 2014 to 2021, the study estimates two absolute poverty measures, a subjective poverty measure, and a multidimensional poverty measure. The findings reveal that poverty rates are highly sensitive to the definition applied. For instance, while the updated absolute poverty line from TurkStat identifies less than 20% of the population as poor, the subjective poverty line and the absolute poverty line defined by TÜRK-İŞ classify approximately 60% and 70% of the population as poor, respectively. Furthermore, while 43% of the population was considered multidimensionally poor in 2014, this figure declined to 31% in 2021. A significant concentration of poverty is observed in the Southeastern and Eastern regions across all measurement approaches. Finally, the study conducts a comparative analysis of various poverty definitions by examining trends in poverty rates, the overlap of poor households, regional rankings, pairwise correlations, and the demographic profile of individuals living in poverty.