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Jeffrey L Carson

Biographic Data

ID5486422
NAMEJeffrey L Carson
GIVEN NAMESJeffrey L
FAMILY NAMECarson
SIGNATURECARSON J L
AFFILIATIONSJohnson University
ORCID0000-0001-5466-2833
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS2
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR1994
LATEST PUBLICATION YEAR2024
H-INDEX1
  • Age and Hair Cortisol Levels as Predictors of Sars-CoV-2 Infection

    Open Access•Nancy Fiedler, Pamela Ohman‐Strickland et al.•ARTICLE•International Journal of…•2024

    Chronic psychosocial stress is known to adversely impact immune function. During the SARS-CoV-2 pandemic, occupational stress among workers in healthcare was at an unprecedented level due to risks of infection and work demands. We performed a nested case-control study to investigate the associations between chronic stress and the risks of contracting SARS-CoV-2. We collected 3 cm of hair from employees at an academic medical center who tested pos…

  • Modeling all-cause mortality

    Louise B Russell, Jeffrey L Carson et al.•ARTICLE•American Journal of Public Health•1998•Cited by: 2•References: 6

    OBJECTIVES: A model that relates clinical risk factors to subsequent mortality was used to simulate the impact of smoking cessation. METHODS: Survivor functions derived from multivariate hazard regressions fitted to data from the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Followup Study, a longitudinal survey of a representative sample of US adults, were used to project deaths from all causes. RESULTS: Validat…

  • Biomedical Risk Factors for Hospital Admission in Older Adults

    Jane Miller, Jane E Miller et al.•ARTICLE•Medical Care•1998•References: 21

    OBJECTIVES: This study examines the influence of risk factors such as cigarette smoking, blood pressure, serum cholesterol, or chronic illness on frequency of hospital admission in a population-based sample. METHODS: Data from the National Health and Nutrition Examination Survey I Epidemiologic Followup Study for 6,461 adults aged 45 years and older were used to assess the influence of risk factors measured by interview, physical examination, and…

  • Does Physician Performance Explain Interspecialty Differences in Malpractice Claim Rates

    Mark I Taragin, Frank A Sonnenberg et al.•ARTICLE•Medical Care•1994

    Physician specialty has been consistently associated with different malpractice claim rates, with neurosurgery, orthopedics, and obstetrics and gynecology having the highest rates. Whether these differences reflect physician performance or other aspects of patient care that are unique for each specialty is unclear. A retrospective cohort study was performed including 12,829 physicians involved in 8,221 closed cases from 1977 to 1991. For each cas…

  • Modeling all-cause mortality

    Louise B Russell, Jeffrey L Carson et al.•ARTICLE•American Journal of Public Health•1998•Cited by: 2•References: 6

    OBJECTIVES: A model that relates clinical risk factors to subsequent mortality was used to simulate the impact of smoking cessation. METHODS: Survivor functions derived from multivariate hazard regressions fitted to data from the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Followup Study, a longitudinal survey of a representative sample of US adults, were used to project deaths from all causes. RESULTS: Validat…

  • Does Physician Performance Explain Interspecialty Differences in Malpractice Claim Rates

    Mark I Taragin, Frank A Sonnenberg et al.•ARTICLE•Medical Care•1994

    Physician specialty has been consistently associated with different malpractice claim rates, with neurosurgery, orthopedics, and obstetrics and gynecology having the highest rates. Whether these differences reflect physician performance or other aspects of patient care that are unique for each specialty is unclear. A retrospective cohort study was performed including 12,829 physicians involved in 8,221 closed cases from 1977 to 1991. For each cas…

  • Modeling all-cause mortality

    Louise B Russell, Jeffrey L Carson et al.•ARTICLE•American Journal of Public Health•1998•Cited by: 2•References: 6

    OBJECTIVES: A model that relates clinical risk factors to subsequent mortality was used to simulate the impact of smoking cessation. METHODS: Survivor functions derived from multivariate hazard regressions fitted to data from the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Followup Study, a longitudinal survey of a representative sample of US adults, were used to project deaths from all causes. RESULTS: Validat…

  • Biomedical Risk Factors for Hospital Admission in Older Adults

    Jane Miller, Jane E Miller et al.•ARTICLE•Medical Care•1998•References: 21

    OBJECTIVES: This study examines the influence of risk factors such as cigarette smoking, blood pressure, serum cholesterol, or chronic illness on frequency of hospital admission in a population-based sample. METHODS: Data from the National Health and Nutrition Examination Survey I Epidemiologic Followup Study for 6,461 adults aged 45 years and older were used to assess the influence of risk factors measured by interview, physical examination, and…

  • Age and Hair Cortisol Levels as Predictors of Sars-CoV-2 Infection

    Open Access•Nancy Fiedler, Pamela Ohman‐Strickland et al.•ARTICLE•International Journal of…•2024

    Chronic psychosocial stress is known to adversely impact immune function. During the SARS-CoV-2 pandemic, occupational stress among workers in healthcare was at an unprecedented level due to risks of infection and work demands. We performed a nested case-control study to investigate the associations between chronic stress and the risks of contracting SARS-CoV-2. We collected 3 cm of hair from employees at an academic medical center who tested pos…

Medicine (4 works) · Internal Medicine (3 works) · Demography (2 works) · Internal Medicine (2 works) · Anesthesia (1 work) · Anesthesiology (1 work) · Body mass index (1 work) · Case-control study (1 work) · Certification (1 work) · Chronic Disease Management Strategies (1 work)

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