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State-level estimates of obesity-attributable costs of absenteeism.

ABSTRACT: To provide state-level estimates of obesity-attributable costs of absenteeism among working adults in the United States.Nationally representative data from the National Health and Nutrition Examination Survey for 1998 to 2008 and from the Behavioral Risk Factor Surveillance System for 2012 are examined. The outcome is obesity-attributable workdays missed in the previous year because of health and their costs to states.Obesity, but not overweight, is associated with a significant increase in workdays absent, from 1.1 to 1.7 extra days missed annually compared with normal-weight employees. Obesity-attributable absenteeism among American workers costs the nation an estimated $8.65 billion per year.Obesity imposes a considerable financial burden on states, accounting for 6.5% to 12.6% of total absenteeism costs in the workplace. State legislatures and employers should seek effective ways to reduce these costs.

SUBMITTER: Andreyeva T

PROVIDER: S-EPMC4225558 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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State-level estimates of obesity-attributable costs of absenteeism.

Andreyeva Tatiana T Luedicke Joerg J Wang Y Claire YC

Journal of occupational and environmental medicine 20141101 11

<h4>Objective</h4>To provide state-level estimates of obesity-attributable costs of absenteeism among working adults in the United States.<h4>Methods</h4>Nationally representative data from the National Health and Nutrition Examination Survey for 1998 to 2008 and from the Behavioral Risk Factor Surveillance System for 2012 are examined. The outcome is obesity-attributable workdays missed in the previous year because of health and their costs to states.<h4>Results</h4>Obesity, but not overweight, ...[more]

PMID: 25376405

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Project description:BackgroundObesity leads to poor health outcomes and may adversely affect work productivity. This study, aimed to investigate the obesity- attributable costs of absenteeism among working adults in Portugal.MethodsThe study population included individuals actively working at baseline from the Epidemiology of Chronic Diseases Cohort (EpiDoC), a large Portuguese population-based prospective study. Body mass index was measured at baseline and in two follow-up interviews. Absenteeism in each wave of the EpiDoC was assessed by the question "Did you have a sick leave in the previous 12 months? yes/no", followed by "How many days did you miss work due to sickness in the previous twelve months?". Body mass index (BMI) was classified into underweight, normal weight, overweight, and obese, based on the standard World Health Organization definition. Association between obesity and absenteeism was estimated with the negative binomial regression model adjusted for BMI, chronic diseases, and lifestyle. Obesity- attributable costs were calculated using lost gross income during the time absent from work, through the human-capital approach.ResultsThe EpiDoC included 4338 working adults at baseline. Of these, 15.2% were obese at the beginning of the study and 22.7% of the population had been absent from work in the last 12 months. Participants with obesity missed 66% more days at work (IRR: 1.66; CI 95%:1.13-2.44; (p = 0.009.) than those with normal weight. The odds of having been absent from work were 1.4 times higher in obese compared to non-obese individuals (CI 95%: 1.18-1.67; p < 0.01) adjusted to sex and type of work. Obese individuals missed 3.8 more days per year than those with normal weight (95%CI: 3.1-4.5). Extrapolating to the entire Portuguese working population, absenteeism due to obesity incurred an additional cost of €238 million per year.ConclusionObesity imposes a financial burden due to absenteeism in Portugal. Employers and national health regulators should seek effective ways to reduce these costs.

Project description:BackgroundThe goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution.MethodsTo identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization.ResultsThe Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men.ConclusionsAlthough the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.

Project description:CONTEXT:The Public Health Workforce Interests and Needs Survey (PH WINS) was first fielded in 2014 and is the largest public health workforce survey in the nation. This article elucidates the methods used for the 2017 PH WINS fielding. PROGRAM OR POLICY:PH WINS was fielded to a nationally representative sample of State Health Agency Central Office (SHA-CO) staff, as well as local health department (LHD) staff. The instrument largely mirrored 2014, though the training needs section was revised, and a validated item measuring burnout in staff was added. IMPLEMENTATION:Staff lists were collected directly from all participating state and local agencies. Forty-seven state health agencies (SHAs), 26 large LHDs, and 71 midsize LHDs participated. All SHAs were surveyed using a census approach. The nationally representative SHA-CO frame is representative of all central office staff members. The nationally representative local frame was a complex survey design, wherein staff from LHDs were randomly sampled across 20 strata, based on agency size and geographic region. Staff were also contributed with certainty from large LHDs in nondecentralized states. The frame is representative of staff at LHDs serving more than 25 000 people and with 25 or more staff members. Other LHDs are excluded, and so PH WINS is not representative of smaller LHDs. Balanced repeated replication weights were used to adjust variance estimates for the complex design. EVALUATION:Overall, 47 604 people responded to PH WINS in 2017 across all frames. PH WINS 2017 achieved a response rate of 48%. The design effect for the SHA-CO frame was 1.46 and was 16.42 for the local frame. DISCUSSION:PH WINS now offers a nationally representative sample of both SHA-CO and LHD staff across 4 major domains: workplace environment, training needs, emerging concepts in public health, and demographics. Both practice and academia can use PH WINS to better understand the perceptions and needs of staff, address training gaps, and work to recruit and retain quality staff.

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State-level estimates of obesity-attributable costs of absenteeism.

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State-level estimates of obesity-attributable costs of absenteeism.

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