The association of obesity with health insurance coverage and demographic characteristics: a statewide cross-sectional study

Mylona, Evangelia K.; Benitez, Gregorio; Shehadeh, Fadi; Fleury, Elvira; Mylonakis, Sophia C.; Kalligeros, Markos; Mylonakis, Eleftherios

doi:10.1097/md.0000000000021016

Cited by 34 publications

(29 citation statements)

References 34 publications

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“…While we followed similar definitions and methods, our sample was not restricted to Medicare FFS patients, and post-IPTW, approximately one-third of our cohorts had a third-party payer. It is well understood that patients vary by insurance status in terms of sociodemographic and clinical characteristics such as race, age, income status, presence of comorbid conditions, receipt of treatment, and health outcomes [ 36 , 37 , 38 ]. For example, one study showed that patients with Medicare insurance constitute a greater percentage of influenza-related inpatient stays as compared to influenza-related ED visits [ 36 ].…”

Section: Discussionmentioning

confidence: 99%

“…For example, one study showed that patients with Medicare insurance constitute a greater percentage of influenza-related inpatient stays as compared to influenza-related ED visits [ 36 ]. Studies have found that the prevalence of obesity, diabetes, and other chronic conditions is higher in Medicare beneficiaries as compared to commercially insured adults [ 37 ]. Therefore, it is plausible that the inherent variations in sample characteristics between the two studies could be associated with differences in study outcomes.…”

Section: Discussionmentioning

confidence: 99%

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Evaluating the Relative Vaccine Effectiveness of Adjuvanted Trivalent Influenza Vaccine Compared to High-Dose Trivalent and Other Egg-Based Influenza Vaccines among Older Adults in the US during the 2017–2018 Influenza Season

et al. 2020

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The influenza-related disease burden is highest among the elderly. We evaluated the relative vaccine effectiveness (rVE) of adjuvanted trivalent influenza vaccine (aTIV) compared to other egg-based influenza vaccines (high-dose trivalent (TIV-HD), quadrivalent (QIVe-SD), and standard-dose trivalent (TIVe-SD)) against influenza-related and cardio-respiratory events among subjects aged ≥65 years for the 2017–2018 influenza season. This retrospective cohort analysis used prescription claims, professional fee claims, and hospital charge master data. Influenza-related hospitalizations/ER visits and office visits and cardio-respiratory events were assessed post-vaccination. Inverse probability of treatment weighting (IPTW) and Poisson regression were used to evaluate the adjusted rVE of aTIV compared to other vaccines. In an economic analysis, annualized follow-up costs were compared between aTIV and TIV-HD. The study was composed of 234,313 aTIV, 1,269,855 TIV-HD, 212,287 QIVe-SD, and 106,491 TIVe-SD recipients. aTIV was more effective in reducing influenza-related office visits and other respiratory-related hospitalizations/ER visits compared to the other vaccines. For influenza-related hospitalizations/ER visits, aTIV was associated with a significantly higher rVE compared to QIVe-SD and TIVe-SD and was comparable to TIV-HD. aTIV was also associated with a significantly higher rVE compared to TIVe-SD against hospitalizations/ER visits related to pneumonia and asthma/COPD/bronchial events. aTIV and TIV-HD were associated with comparable annualized all-cause and influenza-related costs. Adjusted analyses demonstrated a significant benefit of aTIV against influenza- and respiratory-related events compared to the other egg-based vaccines.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Evaluating the Relative Vaccine Effectiveness of Adjuvanted Trivalent Influenza Vaccine Compared to High-Dose Trivalent and Other Egg-Based Influenza Vaccines among Older Adults in the US during the 2017–2018 Influenza Season

et al. 2020

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“… 4 The rate of obesity has almost tripled globally in the last decades, with an estimated 1.9 billion adults overweight. 5 Although obesity has become a pandemic and a major burden in one of the high-income countries in Kingdom of Saudi Arabia. 6 Body Mass Index (BMI) is widely used for diagnosing obesity.…”

Section: Introductionmentioning

confidence: 99%

Relationship Between Serum Amyloid A1 (SAA1) Gene Polymorphisms Studies with Obesity in the Saudi Population

Alharbi¹,

Alshammary²,

Aljabri³

et al. 2021

DMSO

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Purpose: Limited studies have shown positive and negative associations of serum amylase A1 (SAA1) gene in childhood obesity, previously showed the relation with obesity in different ethnicity. The current study therefore investigated the impact of single nucleotide polymorphisms present in the SAA1 gene on subjects of Saudi obesity. Participants and Methods: In this case-control study, we selected 140 subjects of Saudi population and categorized them into 83 cases of obesity and 57 healthy controls. Genotyping was performed with quantitative/real time-polymerase chain reaction in the SAA1 gene for rs11603089A/G, rs4638289A/T and rs7131332A/G polymorphisms. Results: In rs11603089 polymorphism, co-dominant model (AG vs AA+GG; OR-2.23 [95% CI:1.02-4.86]; p=0.04) and rs4638289 polymorphism, a disparity in significance was observed between the homozygous variant (TT vs AA; OR-16.8 [95% CI: 2.06-136.8]; p=0.0009), dominant model (AT+TT vs AA; OR-2.57 [95% CI: 1.28-5.19]; p=0.007), recessive model (TT vs AA+AT; OR-11.36 [95% CI: 1.45-89.06]; p=0.004) and allelic frequency for (T vs A: OR-2.35 [95% CI: 1.39-3.98]; p=0.001) between the obesity cases and control subjects. However, statistical correlations did not reveal the rs7131332A/G polymorphism either (p>0.05). Conclusion:In conclusion, rs4638289 polymorphism was associated with risk allele and dominant model with obesity subjects. Further additional studies were warranted.

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“…Findings with respect to internet access [ 28 ] parallel those of the underserved in the United States. Moreover, not to imply that being on Medicaid causes poor health outcomes, there is literature suggesting that Medicaid beneficiaries have poorer health outcomes that can lead to long-term cardiovascular complications compared to privately insured individuals [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

Yang¹,

Yang²,

Lewis³

et al. 2021

J Med Internet Res

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Background Evidence suggests that eHealth tools adoption is associated with better health outcomes among various populations. The patterns and factors influencing eHealth adoption among the US Medicaid population remain obscure. Objective The objective of this study is to explore patterns of eHealth tools adoption among the Medicaid population and examine factors associated with eHealth adoption. Methods Data from the Health Information National Trends Survey from 2017 to 2019 were used to estimate the patterns of eHealth tools adoption among Medicaid and non-Medicaid populations. The effects of Medicaid insurance status and other influencing factors were assessed with logistic regression models. Results Compared with the non-Medicaid population, the Medicaid beneficiaries had significantly lower eHealth tools adoption rates for health information management (11.2% to 17.5% less) and mobile health for self-regulation (0.8% to 9.7% less). Conversely, the Medicaid population had significantly higher adoption rates for using social media for health information than their counterpart (8% higher in 2018, P=.01; 10.1% higher in 2019, P=.01). Internet access diversity, education, and cardiovascular diseases were positively associated with health information management and mobile health for self-regulation among the Medicaid population. Internet access diversity is the only factor significantly associated with social media adoption for acquisition of health information (OR 1.98, 95% CI 1.26-3.11). Conclusions Our results suggest digital disparities in eHealth tools adoption between the Medicaid and non-Medicaid populations. Future research should investigate behavioral correlates and develop interventions to improve eHealth adoption and use among underserved communities.

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The association of obesity with health insurance coverage and demographic characteristics: a statewide cross-sectional study

Abstract: Supplemental Digital Content is available in the text

Cited by 34 publications

References 34 publications

Evaluating the Relative Vaccine Effectiveness of Adjuvanted Trivalent Influenza Vaccine Compared to High-Dose Trivalent and Other Egg-Based Influenza Vaccines among Older Adults in the US during the 2017–2018 Influenza Season

Evaluating the Relative Vaccine Effectiveness of Adjuvanted Trivalent Influenza Vaccine Compared to High-Dose Trivalent and Other Egg-Based Influenza Vaccines among Older Adults in the US during the 2017–2018 Influenza Season

Relationship Between Serum Amyloid A1 (SAA1) Gene Polymorphisms Studies with Obesity in the Saudi Population

Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

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