A Four Year Follow‐up Study of Low Socioeconomic Status, Latin American Children with Reading Difficulties

1995 ◽  
Vol 42 (3) ◽  
pp. 189-202 ◽  
Author(s):  
Luis Bravo‐Valdivieso
Keyword(s):  
Socioeconomic Status ◽  
Latin American ◽  
Low Socioeconomic Status ◽  
Reading Difficulties ◽  
Low Socioeconomic ◽  
Follow Up Study ◽  
American Children

scholarly journals Impact of Socioeconomic Status on Return to Work after Acute Ankle Fracture

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0020
Author(s):  
Alessandra L. Falk ◽  
Regina Hanstein ◽  
Chaiyaporn Kulsakdinun
Keyword(s):  
Socioeconomic Status ◽  
Return To Work ◽  
Low Socioeconomic Status ◽  
Ankle Fracture ◽  
Low Ses ◽  
Insurance Status ◽  
Low Socioeconomic ◽  
The Impact ◽  
Zip Code

Category: Ankle; Trauma Introduction/Purpose: Socioeconomic status has been recognized throughout the medical literature, both within orthopedics and beyond, as a factor that influences outcomes after surgery, and can result in substandard care. Within the foot and ankle subspecialty, there is limited data regarding socioeconomic status and post-operative outcomes, with the current literature focusing on outcomes for diabetic feet. However, ankle fractures are among the most common fractures encountered by orthopedic surgeons. While a few studies have explored the impact of ankle fractures on employment and disability status, the effect of socioeconomic status on return to work post operatively has not yet been investigated. The purpose of this study was to determine the impact of low socioeconomic status on return to work. Methods: We retrospectively reviewed 592 medical charts of patients with CPT code 27766, 27792, 27814, 27822, 27823, 27827, 27829, 27826, 27828 from 2015-2018. Included were patients >18 yrs of age who sustained an acute ankle fracture, were employed prior to the injury, and with information on return to work after ankle surgery, zip code, race, ethnicity and insurance status. Excluded were patients who were not employed prior to their injury. Socioeconomic status was either defined by insurance status - Medicaid/Medicare, commercial, or workman’s compensation -, or by assessing socioeconomic status (SES) using medial household per capita income by zip code as generated and reported by the US National Census Bureau’s 2013-2017 American Community Survey 5-Year Estimates. The national dataset was divided into quartiles with the lowest quartile defined as low SES. Patients who had income that fell within this income category were classified as low SES. Results: 174 patients were included with an average follow-up of 10.2months. 22/174 (12.6%) patients didn’t return to work post-operatively. Univariate analysis identified non-sedentary work to decrease the likelihood of return to work (HR:0.637; p=0.03). Patients with a low SES were more prevalent in the no return group compared to the return to work group (86% vs 60%; p=0.028). 95% of patients with low SES were a minority compared to 56% with average/high SES (p<0.005). Patients with low SES had a higher BMI (p=0.026), a longer hospitalization (p=0.04) and more wound complications (p=0.032). Insurance type didn’t affect return to work (p=0.158). Patients with workman’s compensation had a longer follow-up time and a longer time to return to work compared to other insurances (p<0.005 for each comparison). Conclusion: Low socioeconomic status based on income, not insurance type, affected return to work after an ankle fracture ORIF. Patients with workman’s compensation took a longer time to return to work compared to other insurance types. These findings warrants the need to consider socioeconomic status when allocating resources to treat these patients.

Follow-Up of Premature Infants Of Low Socioeconomic Status

1989 ◽  
Vol 38 (4) ◽  
pp. 246 ◽  
Author(s):  
LINA ZAHR ◽  
STEVEN PARKER ◽  
JEAN COLE ◽  
CINDY ENGLIER
Keyword(s):  
Socioeconomic Status ◽  
Premature Infants ◽  
Low Socioeconomic Status ◽  
Low Socioeconomic

scholarly journals Factors Associated with Low Socioeconomic Status Predict Poor Postoperative Follow-up after Meningioma Resection

2015 ◽  
Vol 77 (03) ◽  
pp. 226-230 ◽  
Author(s):  
Philip Brinson ◽  
Kyle Weaver ◽  
Reid Thompson ◽  
Lola Chambless ◽  
Arash Nayeri
Keyword(s):  
Socioeconomic Status ◽  
Low Socioeconomic Status ◽  
Low Socioeconomic ◽  
Factors Associated

Associations of rural residence and low socioeconomic status on the risk of new onset cardiovascular disease (CVD) in cancer patients.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 90-90
Author(s):  
Atul Batra ◽  
Shiying Kong ◽  
Rodrigo Rigo ◽  
Winson Y. Cheung
Keyword(s):  
Socioeconomic Status ◽  
Educational Attainment ◽  
Cancer Patients ◽  
Low Socioeconomic Status ◽  
Low Income ◽  
Low Ses ◽  
Rural Residence ◽  
Low Socioeconomic ◽  
Low Education

90 Background: Cancer patients are predisposed to CVD due to cancer treatments and shared risk factors (smoking/physical inactivity). We aimed to assess if rural residence and low socioeconomic status (SES) modify the risk of developing CVD. Methods: Patients diagnosed with non-metastatic solid organ cancers without baseline CVD in a large Canadian province from 2004 to 2017 were identified using the population-based registry. Postal codes were linked with Census data to determine rural residence as well as neighborhood-level income and educational attainment. Low income was defined as <46000 CAD/annum; low education was defined as a neighborhood in which <80% attended high school. Myocardial infarction, congestive heart failure, arrythmias and cerebrovascular accident constituted as CVD.We performed logistic regression analyses to examine the associations of rural residence and low SES with the development of CVD, adjusting for measured confounding variables. Results: We identified 81,275 patients diagnosed with cancer without pre-existing CVD. The median age was 62 years and 54.2% were women. The most prevalent cancer types included breast (28.6%), prostate (23.1%), and colorectal (14.9%). At a median follow-up of 68 months, 29.4% were diagnosed with new CVD. The median time from cancer diagnosis to CVD was 29 months. Rural patients (32.3 vs 28.4%,P < .001) and those with low income (30.4% vs 25.9%,P < .001) or low educational attainment (30.7% vs 27.6%,P < .001) experienced higher rates of CVD. After adjusting for baseline factors and treatment, rural residence (odds ratio[OR], 1.07; 95% confidence interval[CI], 1.04-1.11;P < .001), low income (OR,1.17;95%CI,1.12-1.21;P < .001) and low education (OR,1.08;95%CI,1.04-1.11;P < .001) continued to associate with higher odds of CVD. Further, patients with colorectal cancer were more likely to develop CVD compared with other tumors (OR,1.12;95% CI,1.04-1.16;P = .001). A multivariate Cox regression model showed that patients with low SES were more likely to die, but patients residing rurally were not. Conclusions: Approximately one-third of cancer survivors develop CVD on follow-up. Despite universal healthcare, marginalized populations experience different CVD risk profiles that should be considered when operationalizing lifestyle modification strategies and cardiac surveillance programs. [Table: see text]

scholarly journals Disseminating a Smoke-free Homes Program to Low Socioeconomic Status Households in the United States Through 2-1-1: Results of a National Impact Evaluation

2018 ◽  
Vol 22 (4) ◽  
pp. 498-505 ◽  
Author(s):  
Łucja T Bundy ◽  
Regine Haardörfer ◽  
Michelle C Kegler ◽  
Shadé Owolabi ◽  
Carla J Berg ◽  
...  
Keyword(s):  
United States ◽  
Socioeconomic Status ◽  
Low Socioeconomic Status ◽  
The United States ◽  
Outcome Evaluation ◽  
Smoking Ban ◽  
Dissemination And Implementation ◽  
Low Socioeconomic ◽  
Shs Exposure

Abstract Introduction Given homes are now a primary source of secondhand smoke (SHS) exposure in the United States, research-tested interventions that promote smoke-free homes should be evaluated in real-world settings to build the evidence base for dissemination. This study describes outcome evaluation results from a dissemination and implementation study of a research-tested program to increase smoke-free home rules through US 2-1-1 helplines. Methods Five 2-1-1 organizations, chosen through a competitive application process, were awarded grants of up to $70 000. 2-1-1 staff recruited participants, delivered the intervention, and evaluated the program. 2-1-1 clients who were recruited into the program allowed smoking in the home, lived in households with both a smoker and a nonsmoker or child, spoke English, and were at least 18 years old. Self-reported outcomes were assessed using a pre-post design, with follow-up at 2 months post baseline. Results A total of 2345 households (335–605 per 2-1-1 center) were enrolled by 2-1-1 staff. Most participants were female (82%) and smokers (76%), and half were African American (54%). Overall, 40.1% (n = 940) reported creating a full household smoking ban. Among the nonsmoking adults reached at follow-up (n = 389), days of SHS exposure in the past week decreased from 4.9 (SD = 2.52) to 1.2 (SD = 2.20). Among the 1148 smokers reached for follow-up, 211 people quit, an absolute reduction in smoking of 18.4% (p &lt; .0001), with no differences by gender. Conclusions Among those reached for 2-month follow-up, the proportion who reported establishing a smoke-free home was comparable to or higher than smoke-free home rates in the prior controlled research studies. Implications Dissemination of this brief research-tested intervention via a national grants program with support from university staff to five 2-1-1 centers increased home smoking bans, decreased SHS exposure, and increased cessation rates. Although the program delivery capacity demonstrated by these competitively selected 2-1-1s may not generalize to the broader 2-1-1 network in the United States, or social service agencies outside of the United States, partnering with 2-1-1s may be a promising avenue for large-scale dissemination of this smoke-free homes program and other public health programs to low socioeconomic status populations in the United States.

Associations of Socioeconomic Status and Rurality With New-Onset Cardiovascular Disease in Cancer Survivors: A Population-Based Analysis

2021 ◽  
pp. OP.20.01053
Author(s):  
Atul Batra ◽  
Shiying Kong ◽  
Winson Y. Cheung
Keyword(s):  
Cardiovascular Disease ◽  
Socioeconomic Status ◽  
Cancer Survivors ◽  
Low Socioeconomic Status ◽  
Low Income ◽  
Population Based ◽  
Rural Residence ◽  
Low Socioeconomic ◽  
New Onset

PURPOSE: Patients with cancer are predisposed to develop new-onset cardiovascular disease (CVD). We aimed to assess if rural residence and low socioeconomic status modify such a risk. METHODS: Patients diagnosed with solid organ cancers without any baseline CVD and on a follow-up of at least 1 year in a large Canadian province from 2004 to 2017 were identified using the population-based registry. We performed logistic regression analyses to examine the associations of rural residence and low socioeconomic status with the development of CVD. RESULTS: We identified 81,418 patients eligible for the analysis. The median age was 62 years, and 54.3% were women. At a median follow-up of 68 months, 29.4% were diagnosed with new CVD. The median time from cancer diagnosis to CVD diagnosis was 29 months. Rural patients (32.3% v 28.5%; P < .001) and those with low income (30.4% v 25.9%; P < .001) or low educational attainment (30.7% v 27.6%; P < .001) experienced higher rates of CVD. After adjusting for baseline factors and treatment, rural residence (odds ratio [OR], 1.07; 95% CI, 1.04 to 1.11; P < .001), low income (OR, 1.17; 95% CI, 1.12 to 1.21; P < .001), and low education (OR, 1.08; 95% CI, 1.04 to 1.11; P < .001) continued to be associated with higher odds of CVD. A multivariate Cox regression model showed that patients with low socioeconomic status were more likely to die, but patients residing rurally were not. CONCLUSION: Despite universal health care, marginalized populations experience different CVD risk profiles that should be considered when operationalizing lifestyle modification strategies and cardiac surveillance programs for the growing number of cancer survivors.

scholarly journals MNGO-12FACTORS ASSOCIATED WITH LOW SOCIOECONOMIC STATUS PREDICT POOR POSTOPERATIVE FOLLOW-UP AFTER MENINGIOMA RESECTION

2015 ◽  
Vol 17 (suppl 5) ◽  
pp. v132.3-v132
Author(s):  
Arash Nayeri ◽  
Philip Brinson ◽  
Marc Prablek ◽  
Lola Chambless
Keyword(s):  
Socioeconomic Status ◽  
Low Socioeconomic Status ◽  
Low Socioeconomic
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