Package 'obcost'

Obesity Cost Database

Description

This database contains necessary data relevant to medical costs on obesity throughout the United States. This database, in form of an R package, could output necessary data frames relevant to obesity costs, where the clients could easily manipulate the output using difference parameters, e.g. relative risks for each illnesses.

So far the functions included in the package are:

• data_load generate the essential four tables that concerns obesity

• data_produce load all critical values in a returned list format

• rel_risk_fun update the relative risks (or the constants) when crucial data needs updating

The database is composed of the following main tables:

• constant Relative risks for a given disease group with a risk factor of obesity.

• obesity_cost_disease Supplementary output with all variables related to individual disease groups in a given state and year.

• obesity_cost_full Complete output with all variables used to make cost calculations, as well as cost calculations in a given state and year.

• obesity_cost_national_summary National summary cost calculations in a given year.

• full_data Necessary raw data for generating new tables with user input

This package contributes to parts of our published journal named "Modeling the Economic Cost of Obesity Risk and Its Relation to the Health Insurance Premium in the United States: A State Level Analysis" Please use the following citation for the journal: Woods Thomas, Tatjana Miljkovic. 2022. Modeling the Economic Cost of Obesity Risk and Its Relation to the Health Insurance Premium in the United States: A State Level Analysis. Risks 10: 197. <doi:10.3390/risks10100197>

Package:	obcost
Type:	Package
Version:	0.1.0
Date:	2022-10-23
License:	public
LazyData:	no

Note

Please make sure that packages of dplyr and tidyr is applied

Author(s)

Tianyue Zang ([email protected])([email protected]) Thomas Woods, Tatjana Miljkovic

Maintainer: Tianyue Zang ([email protected])([email protected])

References

State Population Totals. 2020. State Population Totals and Components of Change: 2010–2019. Suitland: U.S. Census Bureau. Available online: www.census.gov (accessed on 20 July 2021).

Current Population Survey Annual Social and Economic Supplements. 2020. Income and Poverty in the United States: 2019. Available online: www.census.gov (accessed on 20 July 2021).

Disability Characteristics. 2020. American Community Survey (acs). Available online: www.census.gov (accessed on 20 July 2021).

Characteristics of the Employed. 2020. Current Population Survey (cps). Available online: www.bls.gov (accessed on 20 July 2021).

Employer Costs for Employee Compensation. 2021. Archived News Releases. Available online: www.bls.gov (accessed on 20 July 2021).

Table of Overweight and Obesity (BMI). 2020. Behavioral Risk Factor Surveillance System. Available online: www.cdc.gov (accessed on 21 July 2021).

Premium, Schedule T., and Annuity Considerations. 2020. Total Health Industry Schedule T Allocated by States and Territories. Available online: www.spglobal.com (accessed on 29 October 2021).

Murray, Christopher J. L., Aleksandr Y. Aravkin, Peng Zheng, Cristiana Abbafati, Kaja M. Abbas, Mohsen Abbasi-Kangevari, Foad Abd-Allah, Ahmed Abdelalim, Mohammad Abdollahi, Ibrahim Abdollahpour, and et al. 2020. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: A systematic analysis for the global burden of disease study 2019. The Lancet 396: 1223–249. [CrossRef]

Consumer Price Index. 2021. All Urban Consumers (Current Series). Available online: www.bls.gov (accessed on 21 July 2021).

---

Default Input of Relative Risk

Description

This dataset gives default input of Relative Risk, however could be updated latter by the user

cvd

Relative Risk for cardiovascular disease

diabetes

Relative Risk for diabetes

cancer

Relative Risk for cancer

copd_asthma

Relative Risk for chronic obstructive pulmonary disease or asthma

osteoarthritis

Relative Risk for osteoarthritis

hypertension

Relative Risk for hypertension

kidney

Relative Risk for kidney diseases

g_p_l

Relative Risk for gallbladder, liver, and pancreatic diseases

stroke

Relative Risk for strokes

Usage

constant

Format

An object of class tbl_df (inherits from tbl, data.frame) with 9 rows and 2 columns.

---

data_load function

Description

The function "data_load" would load all critical values in a returned list format

Usage

data_load()

Value

a list(dataframe) of pop (population), gdp (global gdp), mi (median income), bmi (body mass index), disab (disability rate), employ (employment rate), med_cost (medical conditions cost), med_prev (medical conditions prevalence cost), natl_med_prev (national medical conditions prevalence), rel_risk (relative risk), benefits, and insurance

Examples

raw_data <- data_load()
population <- raw_data$pop

---

data_produce function

Description

The data_produce function would generate the essential four tables that concerns obesity including 1. Relative Risks (constant): Relative risks for a given disease group with a risk factor of obesity. 2. Disease Cost (obesity_cost_disease): Supplementary output with all variables related to individual disease groups in a given state and year. 3. Full Cost (obesity_cost_full): Complete output with all variables used to make cost calculations, as well as cost calculations in a given state and year. 4. National Summary (obesity_cost_national_summary): National summary cost calculations in a given year.

Usage

data_produce(rr = c())

Arguments

rr	the relative risks of diseases – Cardiovascular disease, diabetes, cancer, Chronic obstructive pulmonary disease or asthma, osteoarthritis, hypertension, kidney diseases, (Gallbladder, Liver, Pancreatic) diseases, and strokes.

Value

a list (dataframe) of constant, obesity_cost_disease, obesity_cost_full, and obesity_cost_national_summary

Examples

new_data <- data_produce(rr = c(1,2,3,4,5,6,7,8,9.1))
cnst <- new_data$constant

---

Necessary Raw Data for Generating New Tables With User Input

Description

This dataset gives users opportunities to update the outputs with there own input of relative risks

pop

Population

gdp

GDP 1963-2020 in millions of current dollars

mi

Median Income 1967-2019

bmi

BMI 1996-2019

disab

Disability 1981-2019

employ

Employment Rate 1950-2020

med_cost

Medical Conditions Cost 1996-2018

med_prev

Medical Conditions Prevalence 1996-2019

natl_med_prev

Medical Conditions National Prevalence 2996-2019

rel_risk

Relative Risks

benefits

Employee Benefits 1996-2018

insurance

insurance_data

Usage

full_data

Format

An object of class list of length 12.

---

Relevant Data for Obesity, Cost, and Diseases

Description

This dataset gives supplementary output with all variables related to individual disease groups in a given state and year.

State

state of interest

Year

year of interest

pi_it

obesity prevalence in state i and year t

cause

disease group

rr_j

relative risk of disease group j on obesity

psi_jt

national cost of disease group j in year t

rho_jit

population-attributable risk percent of disease group j in state i and year t

DC_jit

direct cost for disease group j in state i and year t

Usage

obesity_cost_disease

Format

An object of class data.frame with 10350 rows and 8 columns.

---

Relevant Data for Obesity, Cost, and Diseases

Description

Complete output with all variables used to make cost calculations, as well as cost calculations in a given state and year.

State

state of interest

Year

year of interest

m_t

median income in year t

d_t

work-impacting disability prevalence in year t

e_t

employment average ration in year t

b_t

employment benefit in year t

p_it

population in state i and year t

pi_it

obesity prevalence in state i and year t

tau_t

total employee benefits in year t

varphi_it

gross domestic product of state i in year t

DC_it

direct cost of state i in year t

M_it

excess mortality cost of state i in year t

A_it

absenteeism cost of state i in year t

D_it

disability cost of state i in year t

IC_it

indirect cost of state i in year t

TC_it

total cost of state i in year t

Usage

obesity_cost_full

Format

An object of class data.frame with 1150 rows and 16 columns.

---

National summary cost calculations in a given year

Description

National summary cost calculations in a given year

Year

year of interest

DC_t

direct cost in year t

M_t

excess mortality cost in year t

A_t

absenteeism cost in year t

D_t

disability cost in year t

IC_t

indirect cost in year t

TC_t

total cost in year t

p_t

total population in year t

pi_t

average obesity rate in year t

Usage

obesity_cost_national_summary

Format

An object of class data.frame with 23 rows and 9 columns.

---

rel_risk_fun function

Description

The "rel_risk_fun" could update the relative risks (or the constants) when crucial data needs updating

Usage

rel_risk_fun(rr)

Arguments

rr	the relative risks of diseases – Cardiovascular disease, diabetes, cancer, Chronic obstructive pulmonary disease or asthma, osteoarthritis, hypertension, kidney diseases, (Gallbladder, Liver, Pancreatic) diseases, and strokes.

Value

a list (dataframe) of relative risks

Examples

key <- rel_risk_fun(rr = c(1,2,3,4,5,6,7,8,1.2))
key$rr

---