Does Fish Farming Improve Household Nutritional Status? Evidence from Bangladesh

In the present study, nutritional status was assessed using dietary diversity of fish and non-fish farming households in Mymensingh district of Bangladesh. It has determined the incidence of poverty in fish and non-fish farm households through a comparative analysis of family profile, food consumption, calories, and protein intake. A total of 420 farms were selected for data collection using structured questionnaires with 210 fish and 210 non-fish farm families. The study using both descriptive and functional analysis revealed that the respondent age of both farms was 45.10 years, family size was 5.70, average education was 4.64 schooling years, and average farm size was 0.514 hectares. As a result, due to the increase in household income, fish farm families improved their food consumption, calories, and protein intake in comparison with non-fish farms. On a direct calorie intake (DCI) basis, the overall absolute and hardcore poverty levels of fish farm households were 32 percent and 18 percent, respectively, while those of non-fish farm households were 22 percent and 10 percent, respectively. Therefore, the incidence of poverty was higher in non-fish farming families than in fish farming families. In principle, provision of various forms of government assistance through the Department of Fisheries (DOF) will further intensify and strengthen fish farming, which will easily bring fallow and uncultivated lands of the area under fish farming. Moreover, it is possible to inspire the younger generation through this research that will help them to become a fish farm-based entrepreneur. The main conclusion of the present study is that fish farming is more positively related to household income, family food intake, and nutritional status than any other type of farming.

Socio-economic inequalities in adolescent mental health in the UK: multiple socio-economic indicators and reporter effects

There are socio-economic inequalities in the experience of mental ill-health. However, less is known about the extent of inequalities by different indicators of socio-economic position (SEP). This is relevant for insights into the mechanisms by which these inequalities arise. For young people's mental health there is an additional layer of complexity provided by the widespread use of proxy reporters. Using data from the UK Millennium Cohort Study (N=10,969), we investigated the extent to which five objective SEP indicators (parent education, household income, household wealth, parent occupational status, and relative neighbourhood deprivation) predict adolescent internalising mental health and how this varies as a function of reporter. Both parent report and adolescent self-report were considered. Regression models demonstrated that whilst all five SEP indicators were associated with parent-reported adolescent mental health (regression coefficients for the most disadvantaged groups and adolescent mental health: parent education β=0.53 [0.44;0.62], household income β=0.56 [0.50;0.62], household wealth β=0.18 [0.10;0.27], parent occupational status β=0.40 [0.35;0.46], and relative neighbourhood deprivation β=0.41 [0.33;0.49]), only income (β=0.11 [0.04;0.17]), wealth (β=0.12 [0.02;0.21]), and occupational status (β=0.08 [0.03;0.13]) were associated with self-reported mental health. The magnitude of these effects was greater for parent-reported than self-reported adolescent internalising symptoms: SEP indicators jointly predicted 5.2% of the variance in parent-reported compared to 1.4% of the variance in self-reported internalising mental health. Income predicted the most variance in both parent (4.2% variance) and self-reported internalising symptoms (0.5% variance). Interestingly, the gradient of parent-reported adolescent mental health across SEP indicators mirrors that of parent's own mental health (for example, income predicted 7.3% variance). Our findings highlight that the relevance of different SEP indicators to adolescent internalising mental health differs between parent and adolescent reports. Therefore, it is important to consider the various perspectives of mental health inequalities gained from different types of reporters.

Socio-economic determinants of healthcare costs in early life: a register-based study in the Netherlands

Background Children with low socioeconomic status (SES) have an increased risk of a suboptimal start in life with ensuing higher healthcare costs. This study aims to investigate the effects of individual- (monthly household income) and contextual-level SES (household income and neighborhood deprivation), and perinatal morbidity (preterm birth and small for gestational age ((<10th percentile), SGA)) on healthcare costs in early life (0–3 years of age). Methods Individual-linked data from three national registries (Perinatal Registry Netherlands, Statistics Netherlands, and Healthcare Vektis) were obtained of all children born between 2011 and 2014 (N = 480,471) in the Netherlands. Binomial logistic regression was used to model annual healthcare costs as a function of their household income (per €1000), neighborhood deprivation index (range − 13.26 – 10.70), their perinatal morbidity and demographic characteristics. Annual healthcare cost were dichotomized into low healthcare costs (Q1-Q3 below €1000) and high healthcare costs (Q4 €1000 or higher). Results Children had a median of €295 annual healthcare costs, ranging from €72 to €4299 (5–95%). Binomial logistic regression revealed that for every €1000 decrease in monthly household income, the OR for having high healthcare costs is 0.99 (0.99–0.99). Furthermore, for every one-unit increase in neighborhood deprivation the OR for having high healthcare costs increase 1.02 (1.01–1.02). Finally, the model revealed an OR of 2.55 (2.48–2.61) for preterm born children, and an OR of 1.44 (1.41–1.48) for children SGA, to have high healthcare costs compared to their healthy peers. Conclusion More neighborhood deprivation was directly related to higher healthcare costs in young children. On top of this, lower household income was consistently and independently related to higher healthcare costs. By optimizing conditions for low SES populations, the impact of low SES circumstances on their healthcare costs can be positively influenced. Additionally, policies that influence more timely and appropriate healthcare use in low SES populations can reduce healthcare costs further.

Trends in Glycemic among Youth with Diabetes: The SEARCH for Diabetes in Youth Study

<b>OBJECTIVES: </b>To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. <p><b>RESEARCH DESIGN AND METHODS: </b>The study included 6,492 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods 2002-2007, 2008-2013 and 2014-2019, diabetes durations of 1-4, 5-9, and 10+ years, and age groups 1-9, 10-14, 15-19, 20-24, 25+ years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A_1c (HbA_1c) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen and diabetes duration, overall and stratified for each duration and age group.</p> <p><b>RESULTS: </b>Adjusted mean HbA_1c for the 2014-2019 cohort of YYA with type 1 diabetes was 8.8%±0.04%. YYA with type 1 diabetes in the 10-14, 15-19, and 20-24 age groups from the 2014-2019 cohort had worse glycemic control than the 2002-2007 cohort. Race/ethnicity, household income and treatment regimen predicted differences in glycemic control in 2014-2019 type 1 diabetes participants. Adjusted mean HbA1c was 8.6%±0.12% for 2014-2019 YYA with type 2 diabetes. Participants age 25+ with type 2 diabetes had worse glycemic control relative to the 2008-2013 cohort. Only treatment regimen was associated with differences in glycemic control in type 2 diabetes participants.</p> <p><b>CONCLUSIONS: </b>Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.</p> <br>

Trends in Glycemic among Youth with Diabetes: The SEARCH for Diabetes in Youth Study

<b>OBJECTIVES: </b>To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes. <p><b>RESEARCH DESIGN AND METHODS: </b>The study included 6,492 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods 2002-2007, 2008-2013 and 2014-2019, diabetes durations of 1-4, 5-9, and 10+ years, and age groups 1-9, 10-14, 15-19, 20-24, 25+ years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A_1c (HbA_1c) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen and diabetes duration, overall and stratified for each duration and age group.</p> <p><b>RESULTS: </b>Adjusted mean HbA_1c for the 2014-2019 cohort of YYA with type 1 diabetes was 8.8%±0.04%. YYA with type 1 diabetes in the 10-14, 15-19, and 20-24 age groups from the 2014-2019 cohort had worse glycemic control than the 2002-2007 cohort. Race/ethnicity, household income and treatment regimen predicted differences in glycemic control in 2014-2019 type 1 diabetes participants. Adjusted mean HbA1c was 8.6%±0.12% for 2014-2019 YYA with type 2 diabetes. Participants age 25+ with type 2 diabetes had worse glycemic control relative to the 2008-2013 cohort. Only treatment regimen was associated with differences in glycemic control in type 2 diabetes participants.</p> <p><b>CONCLUSIONS: </b>Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.</p> <br>

Household Income as a Predictor for Surgical Outcomes and Opioid Use After Spine Surgery in the United States

Study Design Cross-Sectional Study Objectives Socioeconomic status (SES) is a fundamental root of health disparities, however, its effect on surgical outcomes is often difficult to capture in clinical research, especially in spine surgery. Here, we present a large single-center study assessing whether SES is associated with cause-specific surgical outcomes. Methods Patients undergoing spine surgery between 2015 and 2019 were assigned income in accordance with the national distribution and divided into quartiles based on the ZIP code-level median household income. We performed univariate, chi-square, and Analysis of Variance (ANOVA) analysis assessing the independent association of SES, quantified by household income, to operative outcomes, and multiple metrics of opioid consumption. Results 1199 patients were enrolled, and 1138 patients were included in the analysis. Low household income was associated with the greatest rates of 3-month opioid script renewal (OR:1.65, 95% CI:1.14-2.40). In addition, low-income was associated with higher rates of perioperative opioid consumption compared to higher income including increased mean total morphine milligram equivalent (MME) 252.25 (SD 901.32) vs 131.57 (SD 197.46) (P < .046), and inpatient IV patient-controlled analgesia (PCA) MME 121.11 (SD 142.14) vs 87.60 (SD 86.33) (P < .023). In addition, household income was independently associated with length of stay (LOS), and emergency room (ER) revisits with low-income patients demonstrating significantly longer postop LOS and increasing postoperative ER visits. Conclusions Considering the comparable surgical management provided by the single institution, the associated differences in postoperative outcomes as defined by increased morbidities and opioid consumption can potentially be attributed to health disparities caused by SES.

Development and Implementation of a Hybrid Online and In-Person Food Sovereignty and Nutrition Education Curriculum for Native American Parents: The FRESH Study

The Food Resource Equity and Sustainability for Health (“FRESH”) study is an Indigenous-led intervention to increase vegetable and fruit intake among Native American children. As part of this study, we developed a hybrid (online and in-person) food sovereignty and nutrition education curriculum for the parents of these children. This 16-week curriculum was developed to promote household- and community-level healthy eating and food sovereignty practices to parents of preschool-aged children residing in Osage Nation, Oklahoma. A total of 81 parent/caregivers participated in the curriculum component of the FRESH study, with a median age of 34 years (range: 23–54 years). Most study participants were female (88.9%) and less than half (45.7%) had an annual household income of more than US$50,000. Most were married or had a significant other (76.5%) and worked full-time (65.4%). The median total number of children in the home <18 years of age was three (range: 1–8). Participation among the 94 parents was 56% during the first week and was 12% in the final week. Having some college or technical training (vs. having a college degree) and having an annual household income of US$20,000–US$50,000 (vs. more than US$50,000) were associated with fewer sessions attended ( p = 0.004 and 0.02, respectively) Being married (vs. not) was associated with higher attendance ( p < .0001). Participation in a hybrid food sovereignty and nutrition education curriculum for parents was generally low, but income, education, and marital status were associated with curriculum participation. Our research adds to the literature by describing the development and implementation of this curriculum and recommendations for future research incorporating Indigenous approaches to health.

SARS-CoV-2 Transmission Dynamics in Households With Children, Los Angeles, California

Objectives: Studies of household transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) focused on households with children are limited. We investigated household secondary attack rate (SAR), transmission dynamics, and contributing factors in households with children.Materials and Methods: In this prospective case-ascertained study in Los Angeles County, California, all households members were enrolled if ≥1 member tested positive for SARS-CoV-2 by polymerase chain reaction (PCR). Nasopharyngeal PCRs, serology, and symptom data were obtained over multiple visits.Results: A total of 489 individuals in 105 households were enrolled from June to December 2020. The majority (77.3%) reported a household annual income of &lt;$50,000, and most (92.9%) were of Hispanic/Latinx ethnicity. Children &lt;18 years old accounted for 46.9% index cases, of whom 45.3% were asymptomatic. Household index cases were predominantly children during low community transmission and adults during the high community transmission period (χ2 = 7.647, p = 0.0036. The mean household SAR was 77.0% (95% CI: 69.4–84.6%). Child and adult index cases both efficiently transmitted SARS-CoV-2 within households [81.9%, (95% CI: 72.1–91.9%) vs. 72.4% (95% CI: 59.8–85.1%), p = 0.23]. Household income and pets were significantly associated with higher SAR in the multivariable analysis of household factors (p = 0.0013 and 0.004, respectively).Conclusions: The SAR in households with children in an urban setting with a large ethnic minority population is much higher than previously described. Children play important roles as index cases. SAR was disproportionately impacted by household income. Vaccination and public health efforts need special focus on children and vulnerable communities to help mitigate SARS-CoV-2 spread.