Neighborhood Unsafety, Discrimination, and Food Insecurity among Nigerians Aged 15-49.

We investigated the association between discrimination, neighborhood unsafety, and household food insecurity (FI) among Nigerian adults, as well as the gender-specific differences in these associations. Our analysis utilized data from the 2021 Multiple Indicator Cluster Survey (MICS), comprising 56,146 Nigerian adults aged 15-49 (17,346 males and 38,800 females). For bivariate analysis, we employed the Rao-Scott chi-square test to examine the relationship between predictors (discrimination, neighborhood unsafety, and a composite variable of both) and the outcome variable (FI). Food insecurity was assessed using both a dichotomous measure (food insecure vs. food secure) and a multinomial variable (food secure, mild FI, moderate FI, and severe FI). To model the association between predictors and FI while controlling for potential confounding factors, we utilized weighted binary and multinomial logistic regression. Among Nigerian adults, the prevalence of having ever experienced FI was 86.1%, with the prevalence of mild FI, moderate FI, and severe FI being 11.5%, 30.1%, and 44.5%, respectively. In the binary model, experiencing discrimination (OR = 1.36, 95% CI = 1.19-1.55), living in an unsafe neighborhood (OR = 1.33, 95% CI = 1.14-1.54), and facing both discrimination and unsafe neighborhood conditions (OR = 1.97, 95% CI = 1.57-2.48) were significantly associated with FI. In the multinomial model, discrimination, neighborhood unsafety, and experiencing both remained associated with moderate and severe FI. In the gender-specific models, discrimination and neighborhood unsafety were found to be significantly associated with FI in women but not in men. This study underscores the importance of implementing policies and programs that address the underlying causes of food insecurity, with specific attention to discrimination and neighborhood safety concerns, particularly for Nigerian women.

Food insecurity and delayed or forgone health care among pregnant and postpartum women in the United States, 2019-2021.

OBJECTIVE: Despite the growing food insecurity crisis in the United States, limited evidence exists about the effects of food insecurity on the unmet health care needs of peripartum (pregnant and postpartum) women. The aim of this study was to examine the association between food insecurity and delayed or forgone health care among peripartum women in the United States from 2019 to 2021. METHODS: We conducted a pooled cross-sectional analysis using data from the 2019, 2020, and 2021 National Health Interview Surveys. Food security status was defined by type (high/marginal, low, and very low). Descriptive analysis and multivariable logistic regression, adjusted for sociodemographic and health-related characteristics, were conducted to estimate the overall and specific delayed or forgone health care (yes or no) between the different categories of food security. RESULTS: Of the 1525 peripartum women (weighted, N = 5,580,186), 11% of peripartum women in the United States experienced suboptimal food security in the 12 mo between 2019 and 2021, with 5% experiencing low and 5% experiencing very low food security. This included 6% (95% confidence interval [CI], 5-8%) who reported delaying filling a medical prescription, 6% (95% CI, 5-8%) who required counseling or therapy from a mental health professional but did not receive it, 6% (5-8%) who delayed counseling or therapy from a mental health professional, 8% (95% CI, 6-10%) who needed medical care but did not receive it, and 9% (95% CI, 7-10%) who delayed medical care. Peripartum women with low and very food security were more likely to delay or forego health care due to cost concerns than food-secure peripartum women. In the multivariable analyses adjusted for predisposing, enabling, and need-based factors, women with low and very low food security had higher risk for delayed or forgone health care than those with marginal or high food security. CONCLUSION: This study demonstrated a positive association between food insecurity and cost-related unmet health care needs among peripartum women. Future empirical studies are needed to assess the effects of peripartum health care interventions targeting food insecurity on reducing health care access disparities associated with costs and improving peripartum health outcomes.

Examining ethno-racial attitudes of the public in Twitter discourses related to the United States Supreme Court Dobbs vs. Jackson Women's Health Organization ruling: A machine learning approach.

Background: The decision of the US Supreme Court to repeal Roe vs. Wade sparked significant media attention. Although primarily related to abortion, opinions are divided about how this decision would impact disparities, especially for Black, Indigenous, and people of color. We used advanced natural language processing (NLP) techniques to examine ethno-racial contents in Twitter discourses related to the overturn of Roe vs. Wade. Methods: We screened approximately 3 million tweets posted to Roe vs. Wade discussions and identified unique tweets in English-language that had mentions related to race, ethnicity, and racism posted between June 24 and July 10, 2022. We performed lexicon-based sentiment analysis to identify sentiment polarity and the emotions expressed in the Twitter discourse and conducted structural topic modeling to identify and examine latent themes. Results: Of the tweets retrieved, 0.7% (n = 23,044) had mentions related to race, ethnicity, and racism. The overall sentiment polarity was negative (mean = -0.41, SD = 1.48). Approximately 60.0% (n = 12,092) expressed negative sentiments, while 39.0% (n = 81,45) expressed positive sentiments, and 3.0% (n = 619) expressed neutral sentiments. There were 20 latent themes which emerged from the topic model. The predominant topics in the discourses were related to "racial resentment" (topic 2, 11.3%), "human rights" (topic 2, 7.9%), and "socioeconomic disadvantage" (topic 16, 7.4%). Conclusions: Our study demonstrates wide ranging ethno-racial concerns following the reversal of Roe and supports the need for active surveillance of racial and ethnic disparities in abortion access in the post-Roe era.

Sociodemographic and socioeconomic correlates of learning disability in preterm children in the United States.

BACKGROUND: In 2019, 1 in every 10 infants born in the United States was preterm. Prematurity has life-threatening consequences and causes a range of developmental disabilities, of which learning disability is a prevalent complication. Despite the availability of special services for children living with learning disability, gaps still exist in terms of access due to socioeconomic factors. The aim of this study is to evaluate socioeconomic and sociodemographic correlates of learning disability in preterm children. METHODS: This cross-sectional study used data from the 2016-2018 National Survey of Children's Health. Weighted multivariable analyses were conducted to ascertain the association of sociodemographic and socioeconomic factors on learning disability among preterm children. The main outcome variable was the presence of learning disability. RESULTS: Among 9555 preterm children in our study population, 1167 (12%) had learning disability. Learning disability was significantly associated with health insurance, food situation, and poverty level after adjustment for other variables. Children currently insured had lower odds of having learning disability compared to those without health insurance (OR = 0.79, 95% C.I. = 0.70-0.91). Also, children living in households that cannot afford nutritious meals are more likely to have learning disability compared to those that can afford nutritious meals at home (OR = 1.55, 95% C.I. = 1.22-1.97). CONCLUSION: These findings highlight the need for intervention efforts to target these children living with a learning disability to achieve the 2004 Individuals with Disabilities Education Act of promoting educational equality and empowerment of children living with a learning disability.