Poverty Ratio Research Articles

Sustainable development in African countries: evidence from the impacts of education and poverty ratio

This paper uses the autoregressive-distributed lag model to investigate the effects of education, poverty, trade volume, ICT development, and GDP per capita on sustainability in the 15 largest African economies from 1999 to 2019. The results show a positive correlation between higher tertiary education rates and sustainability, emphasizing the importance of investing in education for sustainable development. In contrast, higher poverty rates are linked to lower sustainability, highlighting the need for poverty reduction efforts. Increased trade volumes are associated with reduced sustainability, indicating the challenges of trade liberalization policies in achieving sustainability goals. However, ICT development has a significant positive impact on sustainability. Interestingly, higher GDP per capita is linked to lower sustainability, potentially due to unsustainable consumption patterns and social inequalities. Policy recommendations for promoting sustainable development in African countries include targeted measures focusing on education and poverty reduction. Gender-friendly policies and initiatives to eliminate educational disparities, especially among marginalized groups, can enhance human capital development. Additionally, promoting e-businesses and sustainable entrepreneurship, along with attracting foreign investment for sustainable education and employment initiatives, can drive economic growth while minimizing environmental impact and fostering inclusive development.

Unveiling Environmental Crime Trends and Intensity in the EU Countries Through a Sustainability Lens

AbstractEnvironmental crime poses a significant threat to global ecosystems, biodiversity, and human well-being, encompassing activities such as pollution, illegal waste disposal, trade in protected species, and natural resource degradation. Understanding the dynamics of these crimes is essential for devising effective mitigation strategies and promoting sustainability at micro, meso, and macro level. The aim of the study is to examine environmental crimes in the EU, focusing on their current trends, patterns, and Intensity, as well as the impact on sustainability across its three dimensions. Fourteen EU countries environmental crime data from 2016 to 2021were analysed to reveal variations and trends. Geographic information systems (GIS) utilized to identify countries with elevated environmental crime rates, emphasizing the need for interventions in pollution control, waste management, and resource conservation. Results indicate high environmental pollution intensity in Italy, Sweden, and Denmark. Moreover, Italy emerges as the epicentre of illegal waste dumping, with notable cases also present in Belgium and France. Additionally, France, Slovakia, and Italy show alarming levels of illegal wildlife trade. Furthermore, France and Sweden exhibit the highest density of natural resource degradation cases. In addition, the study unveiled a positive correlation ($$\:b>0$$) between environmental pollution, trade in protected species, and natural resource degradation with population growth, while waste disposal exhibited a negative correlation ($$\:b<0$$). Moreover, trade in protected species and resource degradation correlated negatively ($$\:b<0$$) with the poverty ratio. Addressing environmental crimes aligns with the pursuit of green justice, recognizing the interconnectedness of environmental, social, and economic factors. The findings offer valuable insights for policymakers, environmentalists, and communities, guiding interventions towards a sustainable and resilient future.

Association Between Secondhand Smoking and Cardiovascular Health Among the U.S. Adult Population Who Participated in the 2017-2018 NHANES Survey

The purpose of this study was to expand upon previous research by investigating the relationship between exposure to secondhand smoking and cardiovascular health in the general U.S. population across various demographic variables. Methods: Using a nationally representative sample, from the 2017-2018 NHANES survey, patterns of secondhand smoking and cardiovascular health issues were examined. This relationship was examined individually and in combination with other sociodemographic characteristics such as gender, family income/poverty, race, education level, birth country, U.S. citizenship status, and language of interview using multivariate logistic regression. Results: The data included 3882 subjects including 23.6% of participants who were exposed to secondhand smoking while 76.33% had not been exposed. Individuals who reported that they were not exposed to secondhand smoke had 32.1% lower odds (95% CI: 0.56-0.82) of having cardiovascular health issues compared to individuals who reported being exposed secondhand smoke, (95% CI: 0.56-0.82). Additionally, statistically significant associations between secondhand smoking and cardiovascular health were identified when factoring in various demographic factors such as gender, ratio of family income poverty, birth country, U.S. citizenship status, education level, and cardiovascular health issues. Conclusion: These results indicate that secondhand smoking exposure should be avoided to potentially reduce the risk of cardiovascular health issues

Measuring Household Thermal Discomfort Time: A Japanese Case Study

This study proposes a metric to measure households’ discomfort related to thermal consumption time (hereafter referred to as t-discomfort). This metric relies on an ideal thermal consumption and calculates the gap between the usage times of thermal devices in vulnerable households compared to the ideal household. The t-discomfort is quantified using thermal data collected from 1298 households in the Tokyo and Oita prefectures in Japan. To create the ideal usage times of thermal devices, households are categorized into three clusters—Vulnerable (Vu), Semi-vulnerable (SVu), and Invulnerable (IVu)—based on their energy poverty ratio, and t-discomfort is subsequently calculated for each group. The IVu households are used as the ideal reference point for measuring thermal device usage in the other two categories. The findings of the study indicate that energy poverty does not necessarily lead to t-discomfort. Interestingly, the consumption time of heating devices among Vu households in both prefectures is longer than that of IVu households, despite the high energy prices. Conversely, SVu households, which do not experience severe energy poverty, tend to sacrifice their comfort by reducing their thermal consumption time. Additionally, the consumption time of cooling devices among Vu households in Oita is longer than that of IVu households, whereas in Tokyo, it is shorter. Two treatment strategies are evaluated to mitigate thermal discomfort in households without compromising resource availability. The first strategy integrates the thermal device consumption time with Japan’s current regulated time-of-use rates plan (daytime and nighttime). The results propose a three-tiered tariff plan (off-peak, mid-peak, and peak) to reduce the energy cost burden for Vu households. The second strategy recommends the installation of 12 rooftop solar panels for households in Tokyo and 11 panels for households in Oita. This strategy aims to maintain thermal comfort via a sustainable natural energy resource while minimizing energy costs.

Dual carbon economy modeling in advanced economies

Utilizing the cross-sectional fully modified OLS (FMOLS) method, this paper tackles the pressing need to address climate change disasters, particularly in the context of recent COVID-19 restrictions. By developing an econometric model specifically for advanced economies, the study aims to enhance understanding and reduce carbon emissions. Examining ten advanced economies from 1995 to 2019, it identifies a significant gap in the literature concerning the integration of demographic, social, economic, and political (DSEP) factors in dual carbon economy models. The results show that a 1% improvement in good governance is associated with a 0.23% reduction in carbon footprint, due to stricter environmental regulations. In contrast, a 1% increase in economic growth results in a 0.17% rise in carbon footprint, driven by industrial activities. Similarly, a 1% rise in electricity consumption leads to a 0.32% increase in carbon footprint, reflecting dependence on fossil fuels. Additionally, a 1% increase in population size corresponds to a 0.21% rise in carbon footprint, linked to higher urban energy consumption. Finally, a 1% increase in the poverty ratio results in a 0.17% rise in carbon footprint, underscoring the influence of socio-economic factors on sustainability. The paper advocates for a comprehensive approach to fostering a dual carbon economy, emphasizing green economic growth, smart, sustainable cities, social sustainability literacy, and sustainable governance.

Unveiling Poverty Dynamics in India: Examining Convergence and Determinants at Sub-National Level

ABSTRACT This paper tries to investigate the question of whether the poverty ratio across Indian states is converging in the post-2000s. We addressed this question of spatial convergence of the poverty ratio using unconditional convergence over the period 2004–05 to 2018–19 for 18 major states of India, considering both rural and urban regions. We used the unit-level data of NSSO’s Consumer Expenditure Surveys (CES) for the 61st, 68th and PLFS 2018–19 rounds for the analysis. Besides, we try to assess the driving factors of poverty through a panel regression model. The results reveal that in the first period from 2004–05 to 2011–12, Indian states experienced a divergence in the overall poverty ratio and rural poverty. However, the second period, 2011–12 to 2018–19, witnessed no specific trend of convergence or divergence across states. Again, in the case of urban poverty, there is no particular pattern of poverty convergence or divergence during both periods. The study shows that the Gini coefficient, educational expenditure, household size, infant mortality, literacy rate, MPCE, primary-sector income and per capita power availability are the significant determinants of poverty in India.

Developing equity-aware safety performance functions for identifying hotspots of pedestrian-involved crashes

Crashes are frequently disproportionally observed in disadvantaged areas. Despite the evident disparities in transportation safety, there has been limited exploration of quantitative approaches to incorporating equity considerations into road safety management. This study proposes a novel concept of equity-aware safety performance functions (SPFs), enabling a distinct treatment of equity-related variables such as race and income. Equity-aware SPFs introduce a fairness distance and integrate it into the log-likelihood function of the negative binomial regression as a form of partial lasso regularization. A parameter λ is used to control the importance of the regularization term. Equity-aware SPFs are developed for pedestrian-involved crashes at the census tract level in Virginia, USA, and then employed to compute the potential for safety improvement (PSI), a prevalent metric used in hotspot identification. Results show that equity-aware SPFs can diminish the effects of equity-related variables, including poverty ratio, black ratio, Asian ratio, and the ratio of households without vehicles, on the expected crash frequencies, generating higher PSIs for disadvantaged areas. Based on the results of Wilcoxon signed-rank tests, it is evident that there are significant differences in the rankings of PSIs when equity awareness is considered, especially for disadvantaged areas. This study adds to the literature a new quantitative approach to harmonize equity and effectiveness considerations, empowering more equitable decision-making in safety management, such as allocating resources for safety enhancement.

Contribution of agroforestry practices to income and poverty status of households in Northwestern Ethiopia

Agroforestry practices (AFPs) play a critical role in enhancing income and reducing poverty. This study assessed the effect of AFPs on income and poverty status of farmers in Lay Armachiho (LA), Bahir Dar Zuria (BDR), and Banja districts of Northwestern Ethiopia. 387 households, and 63 key informants were interviewed. Data were analyzed using descriptive statistics, FGT index, Gini coefficient, and multiple linear regression. About 49.35% of the respondents are categorized poor with a poverty gap of 18.93 and a poverty severity level of 9.7. Banja was the greatest with persons below poverty level (59.2%), followed by BDR (49.72%). Agroforestry practices contribute 28.43% to household income. Income from AFPs lowered the poverty ratio, poverty gap index, and poverty severity level of households by 13%, 9%, and 7%, respectively. Income from AFPs lowered the area between the line of equality and the Lorenz curve, as well as the Gini coefficient, by 7.97%. AFPs also lowered the income disparity of households in all districts. Age, AFPs land size, road accessibility, irrigation, AFPs experience, and AFPs types affect households AFPs income positively. Family size and membership to credit institutions had a negative effect. Thus, in order to lower poverty and raise household income, labor productivity, the credit service system, the road and irrigation infrastructure, and AFPs all need to be improved and scaled up.

Association between triglyceride glucose body mass index and cardiovascular disease in adults: evidence from NHANES 2011- 2020.

The association between insulin resistance and cardiovascular diseases (CVD) is of significant interest. However, there is limited published research on the relationship between CVD and the triglyceride glucose-body mass index (TyG-BMI). This study aims to examine the association between TyG-BMI and CVD in US adults. We analyzed data from 11016 adults collected through the 2011-2020 NHANES. Employing weighted generalized linear models, subgroup analysis, sensitivity analysis, and receiver operating characteristic curves, we examined the association between the TyG-BMI index and CVD. Nonlinear associations were investigated using restricted cubic splines. Higher TyG-BMI values were significantly associated with an increased prevalence of CVD (P<0.001). Weighted generalized linear models consistently demonstrated a positive association across all models. Specifically, individuals in the highest tertile of TyG-BMI had a 38% higher CVD prevalence than those in the lowest quartile (OR=1.380; 95% CI=1.080, 1.763). Unweighted logistic regression models further confirmed these findings. Sex, race, education, family income to poverty ratio, smoking, hypertension, and diabetes did not modify this positive association (P for interaction >0.05). Incorporating the TyG-BMI index into traditional risk factor models marginally improved the prediction of CVD prevalence (P for comparison <0.05). The TyG-BMI index, an indicator of insulin resistance, is significantly positive associated with a higher prevalence of CVD. These findings underscore the importance of managing insulin resistance to prevent CVD and highlight the need for further research into the underlying mechanisms of this association.

Prevalence and trends in overactive bladder among men in the United States, 2005–2020

The purpose of present study was to examine the current prevalence and recent trends of overactive bladder (OAB) among US adult men and examine the correlations between OAB and several potential risk factors. The study used the nationally representative data between 2005 and 2020 from the National Health and Nutrition Examination Survey in the US. A total of 18,386 participants aged ≥ 20 years were included in the study. We divided the data into three groups: 2005–2008, 2009–2014 and 2015–2020 to investigate the trends in OAB prevalence. The weighted prevalence and corresponding 95% confidence intervals (CI) of OAB were calculated. The differences (95% CI) in prevalence between the surveys were calculated and multivariate-adjusted weighted logistic regression analysis was performed to determine the correlates of OAB. Among all US adult men, the overall prevalence of OAB increased slightly from 11.3% in 2005–2008 to 11.7% in 2009–2014 and significantly increased to 14.5% in 2015–2020 (difference, 3.2% [95% CI (1.9–4.4%)]; P < 0.05). Increases in OAB prevalence especially concentrated on those who were 40–59 years, non-Hispanic White, non-Hispanic Black and those who were overweight and obese. Older age, non-Hispanic Black, lower educational level and family poverty ratio, diabetes, depression, sleep disorder, other chronic comorbidities, less intense recreational activity, poorer health condition and unsafe food were independent risk factors of OAB. The contemporary prevalence of OAB was high, affecting 14.5% US men and the estimated overall prevalence significantly increased from 2005 to 2020. Therefore, future research should be focused to prevent and remedy this growing socioeconomic and individually troublesome malady.

Association between serum chloride levels and estimated glomerular filtration rate among US adults: evidence from NHANES 1999–2018

PurposeChloride, the predominant anion in extracellular fluid from humans, is essential to maintaining homeostasis. One important metric for thoroughly assessing kidney function is the estimated glomerular filtration rate (eGFR). However, the relationship between variations in serum chloride concentration and eGFR in general populations has been poorly studied. Therefore, the purpose of this study is to elucidate the correlation between serum chloride levels and eGFR within the United States’ adult population.MethodsThis cohort study was conducted using data from the National Health and Nutrition Examination Survey (NHANES), which covered the years 1999–2018. We employed multiple linear regression analysis and subgroup analysis to evaluate the correlation between serum chloride concentration and eGFR. To examine the nonlinear association between serum chloride levels and eGFR, restricted cubic spline analyses were employed.ResultsData from 49,008 participants in this cohort study were used for the chloride analysis. In the comprehensively adjusted model, a noteworthy inverse relationship was discovered between chloride plasma concentration and eGFR. Restricted cubic spline analyses revealed a significant nonlinear relationship between chloride levels and eGFR (P for overall < 0.001 and P for nonlinear < 0.001). A significant interaction was observed between eGFR and plasma chloride concentration (all P < 0.001 for interaction) among the subgroups characterized by sex, household income to poverty ratio, BMI, hypertension, and diabetes.ConclusionOur findings suggest that higher levels of chloride plasma concentration were linked to decreased eGFR. These findings underscore the significance of monitoring chloride plasma concentration as a potential indicator for identifying individuals at risk of developing chronic kidney disease (CKD).

Association between family income to poverty ratio and nocturia in adults aged 20 years and older: A study from NHANES 2005-2010.

Nocturia, the most common lower urinary tract symptom (LUTS), significantly impacts socioeconomic factors and individuals' quality of life and is closely related to many diseases. This study utilized data from NHANES 2005-2010 to explore the relationship between family income to poverty ratio (PIR) and the presence of nocturia symptoms in adults aged 20 or older in the United States. Data from the National Health and Nutrition Examination Survey (NHANES) in 2005-2010, including 6,662 adults aged 20 or older, were utilized for this cross-sectional study. The baseline data was used to display the distribution of each characteristic visually. Multiple linear regression and smooth curve fitting were used to study the linear and non-linear correlations between PIR and nocturia. Subgroup analysis and interaction tests were conducted to examine the stability of intergroup relationships. Out of the 6,662 adult participants aged 20 or older, 1,300 households were categorized as living in poverty, 3,671 households had a moderate income, and 1,691 households were classified as affluent. Among these participants, 3,139 individuals experienced nocturia, representing 47.12% of the total, while 3,523 individuals were nocturia-free, constituting 52.88% of the total population. After adjusting for all other covariates, it was found that PIR was significantly negatively correlated with nocturia (OR: 0.875, 95%CI: 0.836-0.916 P<0.0001). This trend persisted when PIR was divided into three groups (PIR <1, PIR 1-4, PIR > 4) or quartiles. There was a non-linear negative correlation between PIR and nocturia. Our findings indicated that lower PlR was associated with a higher risk of nocturia in adults aged 20 or older in the United States. These findings highlight the importance of considering socioeconomic factors in preventing and managing nocturia. Nonetheless, further exploration of the causal nexus between these factors was precluded due to the constraints of a cross-sectional design.

Prevalence and Correlates of Unstable Housing Among US Children

Housing instability is an important public health issue, particularly for children. This study provides nationally representative estimates of unstable housing among US children. To examine unstable housing prevalence; differences by sociodemographic characteristics, health, and state of residence; and associations with other hardships. This survey study examined data from the 2022 National Survey of Children's Health, a population-based, nationally representative survey of randomly selected children whose parent or caregiver responded to an address-based mail or web-based survey. Participants were children aged 0 to 17 years living in households in the 50 US states and District of Columbia (N = 54 103). Bivariate analyses tested for observed differences in unstable housing between groups; logistic regression models tested for significant disparities. Associations between unstable housing and health care and food-related hardships, neighborhood conditions, and adverse childhood experiences were examined. Unstable housing experiences. Unstable housing, comprising 3 indicators: inability to pay mortgage or rent on time in the past 12 months, 2 or more moves in the past 12 months, and homelessness in the child's lifetime. Analyses were adjusted for child age and family poverty ratio. Secondary analyses examine caregiver-reported stress or worry about eviction, foreclosure, or condemned housing in the past 12 months. Weighted prevalence estimates accounted for probability of selection and nonresponse. In 2022, 17.1% (95% CI, 16.4%-17.8%) of children living in US households, representing more than 12.1 million children, experienced 1 or more forms of unstable housing: 14.1% (95% CI, 13.4%-14.7%) lived in households that were unable to pay mortgage/rent, 2.9% (95% CI, 2.6%-3.3%) moved frequently, and 2.5% (95% CI, 2.2%-2.8%) experienced lifetime homelessness. Additionally, 9.0% (95% CI, 8.5%-9.5%) of children had caregivers who reported stress/worry over housing. Prevalence of unstable housing varied across states (range, 12.0%-26.6%). Unstable housing was highest among American Indian or Alaska Native children (27.9%; 95% CI, 21.3%-35.6%), Black or African American children (30.4%; 95% CI, 27.8%-33.1%), and Native Hawaiian or Pacific Islander children (27.6%; 95% CI, 16.6%-42.1%) and also differed by special health care needs, family poverty ratio, caregiver education and unemployment status, and whether the family rented or owned their home. Unstable housing was associated with all other types of hardships examined. This study found that 1 in 6 US children experienced unstable housing, varying by state and sociodemographic factors. The prevalence is likely underestimated because the sample excluded children who are currently institutionalized or experiencing homelessness. Results may help move the field toward a unified national definition of unstable housing for families with children and lead to clinically appropriate and evidence-based screening and interventions to support housing stability and improve children's health.

The Impoverishing Effect of Tobacco Use in Indonesia.

Smoking households in Indonesia diverted a significant share of their budget to tobacco. Tobacco expenditure is deemed unproductive, as it crowds out resources from essential commodities and increases health care expenditure driven by tobacco-induced diseases. Therefore, despite having adequate resources, some smoking families in Indonesia may spend less on basic needs, which inadvertently puts their standard of living below the poverty line. Employing data from 2021 (March) Indonesia's Socioeconomic Survey (SUSENAS), this research aims to quantify the impoverishing effect of tobacco consumption in Indonesia, considering spending on tobacco and tobacco-attributable health care costs as unproductive expenditure. The de facto headcount poverty rate and poverty gap index are calculated by removing tobacco expenditures and tobacco-attributable health care expenditures from the household's total spending. Accounting for unproductive spending related to tobacco use, Indonesia's headcount poverty ratio in March 2021 would rise by 3.22 percentage points, equivalent to an additional 8.75 million people living below the poverty line. In addition, the poverty gap index would increase by 0.77 percentage points. The impoverishment effect of tobacco is larger among rural populations than their urban counterparts. Moreover, the impoverishment is mainly driven by direct tobacco spending rather than tobacco-attributable health care expenditure. Significant portions of Indonesia's population are exposed to secondary poverty due to tobacco use. A high level of cigarette spending among smoking households is the major source of the impoverishing effect of tobacco use. The study provides quantitative evidence of the true cost of smoking in Indonesia, where the de facto number of the poor population after accounting for tobacco-related spending is higher than what is published in the official statistics. The findings of this study support tobacco control policies in Indonesia, particularly to effectively reduce tobacco use and mitigate the impoverishing impact of tobacco use on low-income households.

Foreign Aid and Direct Effect of Poverty Reduction in Thailand

Abstract This study examines the effects of foreign aid on poverty reduction in Thailand dividing into ways. One is the direct effect of poverty reduction and the other is the indirect effect of economic growth. Dividing the effect of foreign aid into the direct effect of poverty reduction and the indirect effect through economic growth will contribute to a more efficient way of providing foreign aid by adjusting its purpose and method of foreign aid. The estimation results are summarized as follows: First, the relationship between the infant mortality rate, as a substitute for poverty reduction, and foreign aid from 1961 to 2022 was not significantly estimated using OLS or VAR (Vector Autoregression) models. Second, the relationship between the poverty ratio and foreign aid from 1988 to 2020 for every other year was also insignificant, although economic growth was estimated to be significantly positive. Based on these results, it can be inferred that foreign aid has no direct effect on poverty reduction in Thailand; rather, the indirect effect seems more important. JEL classification numbers: F35, O53. Keywords: Foreign Aid, Poverty, Thailand.

Impact of climatic factors and poverty on wheat yields via machine learning in a semi-arid region across West Asia.

Abstract Winter-sown wheat is particularly vulnerable to high temperatures in spring. However, little is known concerning the impact of high temperatures and other climatic and non-climatic factors in combination on winter-sown wheat yields in arid and semi-arid regions. Therefore, in this study we investigate the impacts of high temperatures and other climatic indices, including evapotranspiration and aridity index during spring months, and non-climatic factors, including technology improvement and poverty ratio on irrigated and dryland wheat yields. We employed Random Forests a machine learning technique to our long-term data (1980-2010) and annual wheat yields (irrigated and dryland) for 27 provinces of Iran. The results show that technology improvement and poverty ratio are the most important variables which explain irrigated wheat yields variability. Temperatures above 31°C, evapotranspiration and aridity index are the other variables that alter irrigated whet yields in the region during the period 1980-2010. Dryland wheat yields mainly explained by temperatures above 31°C. Poverty ratio, technology improvement, evapotranspiration and aridity index ranked after high temperatures above 31°C, respectively. This study demonstrates that, although, in arid areas technological improvement and irrigation may avoid yield reduction due to high temperatures in spring months, in poor arid areas and dryland systems, high temperatures significantly reduce wheat yields.

Social Disadvantage and Multimorbidity Including Oral Conditions in the United States

Existing studies on multimorbidity have largely excluded oral diseases in multimorbidity prevalence estimates. The reason behind this is somewhat unclear, as chronic oral conditions are highly prevalent, affecting over half the global population. To address this gap, we examined the relationship between social disadvantage and multimorbidity, stratifying by the inclusion and exclusion of oral conditions. For participants aged 30 y and over (n = 3,693), cross-sectional analysis was carried out using the US National Health and Nutrition Survey (2013–2014). Multimorbidity was defined as having 2 or more chronic conditions. Five medical conditions were examined: diabetes, asthma, arthritis, cardiovascular disease, and depression, as well as 4 oral health conditions: caries, periodontal disease, number of teeth, and edentulousness. Education and income poverty ratio were selected as measures of social disadvantage. Multimorbidity prevalence estimates according to social disadvantage were analyzed on an absolute and relative scale using inverse probability treatment weighting (IPTW), adjusting for age, sex, and ethnicity. The inclusion of oral health conditions in the assessment of multimorbidity increased the overall prevalence of multimorbidity from 20.8% to 53.4%. Findings from IPTW analysis demonstrated clear social gradients for multimorbidity estimates stratified by the exclusion of oral conditions. Upon inclusion of oral conditions, the prevalence of multimorbidity was higher across all social groups for both education and income. Stratifying by the inclusion of oral conditions, the mean probability of multimorbidity was 27% (95% confidence interval [CI], 23%–30%) higher in the low-education group compared to the high-education group. Similarly, the mean probability of multimorbidity was 44% (95% CI, 40%–48%) higher in the low-income group. On a relative scale, low education was associated with a 1.52 times (95% CI, 1.44–1.61) higher prevalence of multimorbidity compared to high education. Low income was associated with a 2.18 (95% CI, 1.99–2.39) higher prevalence of multimorbidity. This novel study strongly supports the impact of chronic oral conditions on multimorbidity prevalence estimates.

Abstract P482: Associations Between Determinates of Food Choice and Healthy Eating Index-2015 in Adults: An NHANES 2017 - 2018 Analysis

Introduction: Previous work in nationally representative US samples has focused on associations between single determinants of food choice and diet quality assessed by the Health Eating Index-2015 (HEI-2015). Limited research has examined the relationship between multiple domains of food choice and diet quality. A greater understanding of the association between individual-level determinants of food choice and diet quality may inform the development of interventions to improve diet quality. Aim: The aim was to examine the association between potentially modifiable factors known to affect individual-level food choice and HEI-2015. Methods: This cross-sectional analysis included adult participants in NHANES 2017 - 2018. Determinates of individual-level food choice were based on a previously proposed framework. Variables assessed in NHANES were mapped to the following four domains: 1) food-external factors (use of nutrition labels, hours worked weekly, typical work schedule); 2) personal-state factors (health status, consumption of food away from home); 3) cognitive factors (perceived diet quality, knowledge of MyPlate); 4) society-related features (monthly grocery expenditures, food security status, income to poverty ratio). Univariate regression assessed the relationship between food choice determinates and HEI-2015 score. Statistically significant variables were entered into multivariate regression models predicting HEI-2015 score. Significant variables from the final model were used in multivariate regression models predicting adequacy and moderation component sub scores of HEI-2015. All models were adjusted for non-modifiable determinates of food choice, including age, sex, race, BMI, education, and relationship status. All analyses were survey weighted. Results: The weighted mean HEI-2015 score for the sample (N=1467) was 51.69 points (95% CI 49.55, 53.84; weighted n=95.6 million). In the final model, perceived diet quality, food away from home, and use of nutrition labels were significant predictors of HEI-2015 (R 2 adj =0.25, p&lt;0.001). Those with excellent/very good perceived diet quality had a 4.88-pt higher HEI-2015 score than those with fair/poor perceived diet quality (p&lt;0.001). Consuming food away from home ≥5 times per week resulted in a 5.92-pt lower HEI-2015 score than 0 times per week (p=0.02). Always/most of the time using nutrition labels was associated with a 7.85-pt higher HEI-2015 score compared to rarely/never using labels (p&lt;0.001). Variables accounted for a higher proportion of variance in adequacy score (R 2 adj =0.10, p&lt;.001) than moderation score (R 2 adj =0.24, p&lt;.001). Conclusion: Food-external, personal-state, cognitive, and socio-cultural factors are associated with diet quality. Future research should consider multiple individual-level food-choice determinates when developing interventions to improve diet quality.

Political Economy of Resource Allocation in Balochistan: Assessing the Role of Government Policies and Bureaucratic Mechanisms

Paper critically evaluates the political economy of resources distribution in Balochistan by using a balanced panel approach from 2008-09 to 2018-19. The study has been conducted to highlight the key causes of irregular distribution of development funds in Balochistan and find out their serious implications for people in general. To get the authentic and validated results, a rich dataset has been obtained from the various sources of Government of Balochistan, non-governmental organizations and federal agencies. The results of the study reveal that political groups and top-level bureaucracy influence resource allocations during the course of budget making process. Politicians and other top bureaucracies keep their own interests in mind and divert public resources to develop their own districts. The districts which are poor in socio-economic indicators, are supposed to be allocated more funds but they are ignored. The study has tried to answer the question that what factors are involved in the proper distribution of provincial funds and how to address the issue. However, the study reveals that there is a serious influential impact of senior ministers of cabinets who have always dominated the provincial development funds which ultimately result in the enhanced poverty ratio, and backwardness in other districts of Balochistan which lack proper and influential representatives.

Association between systemic immune-inflammation index and post-stroke depression: a cross-sectional study of the national health and nutrition examination survey 2005-2020.

Less research has linked the Systemic Immune Inflammatory Index (SII) with post-stroke depression (PSD). This study aims to look at any potential connections between SII and PSD. The National Health and Nutrition Examination Survey (NHANES), conducted in a population that embodied complete SII and stroke data from 2005 to 2020, was used to perform the current cross-sectional survey. A fitted smoothed curve was used to depict the nonlinear link between SII and PSD, and multiple linear regression analysis demonstrated a positive correlation between SII and PSD. Multiple linear regression analysis showed that SII and PSD were markedly related [1.11(1.05, 1.17)]. Interaction tests showed that the association between SII and PSD was not statistically different between strata, and age, sex, BMI, income poverty ratio, education level, smoking status, diabetes mellitus, coronary heart disease, and heart failure did not have a significant effect on this positive association (p > 0.05 for interaction). In addition, a nonlinear association between SII and PSD was found using a two-stage linear regression model. The results of our research support the existence of a significant positive correlation between SII levels and PSD. Further prospective trials are required to comprehend SII, which is for the PSD thoroughly.