Complementary and alternative medicine use and absenteeism among individuals with chronic disease

Survey design

The U.S. Center for Disease Control’s National Center for Health Statistics used a
continuous sampling and interviewing design to obtain information on basic demographics,
general health, and current health topics through the cross-sectional U.S. National
Health Interview Survey (NHIS) 17]. Data were collected from the civilian non-institutionalized United States population,
oversampling African American and Hispanic populations. Individuals in the armed forces
and those living in institutional group quarters, long-term care institutions, correctional
facilities, and countries outside the U.S. were not included. From each household
sampled, one adult and one child (if there were any children) were interviewed and
provided information on the rest of the household. Beginning in 2002, the NHIS included
questions on 27 complementary health approaches every 5 years 18]. The conditional sample adult response rate for the 2012 NHIS was 79.7 % 19].

These analyses made use of the 2012 NHIS. NHIS data are available publically and permission
was not required for access. All individuals gave verbal consent prior to participating
in this study as indicated in the Field Representative Manual 17]. As this study made use of a de-identified publically available dataset, the study
was exempt from IRB oversight by the Columbia University Medical Center IRB.

Population

A total of 108,131 individuals participated in the 2012 NHIS and 34,525 participants
provided data on CAM use. Participants under age 18 and/or were eligible to receive
full retirement benefits in 2012 (age 66 and older) were excluded from analysis (n?=?40,050) 20]. Of the 20 conditions defined as chronic disease by the Multiple Chronic Conditions
working group within the Health and Human Services Office of the Assistant Secretary
of Health, the 2012 NHIS collected responses on 13 of these conditions 21]. Individuals were included if they answered yes to any of the following: ever having
either arthritis, cancer, chronic obstructive pulmonary disease, non-gestational diabetes,
hepatitis, high cholesterol, or being informed in the past twelve months of having
hypertension, hepatitis, coronary heart disease, asthma, chronic kidney disease, depression,
or substance abuse. Participants who did not have one or more chronic disease at the
time of the interview (n?=?43,448), had not worked for pay in the past week (n?=?10,500), or had reported missing 364 or more days from work in the past twelve
months (n?=?64) were excluded 22]. Working for pay in the past week was the best indicator of employment in the past
year opposed to ever having a job. Those who did not or refused to answer any of the
survey questions regarding CAM use were excluded from analysis (n?=?3,873). After removing observations with missing values for the number days missed
from job or business in the past twelve months and CAM use the final population size
was 10,196.

Assessment of CAM use

CAM practices considered for inclusion were determined by the National Center for
Complementary and Integrative Health’s (NCCIH) definition of “complementary health
approaches” for mind and body practices and natural products. Natural products were
included in our definition of CAM as these therapies are the most commonly used 9]. CAM practices included acupuncture, massage, meditation, movement therapies (does
not include general exercise), relaxation techniques, mind-body practices, vitamins
(excluding multi-vitamins), minerals, and herbs 13]. Participants reported not using any of the NCCIH defined practices were considered
non-users. CAM types of interest were categorized as either dietary supplements or
mind-body practices. Mind-body practices included biofeedback, mantra meditation/mindfulness
meditation/spiritual meditation/guided imagery/progressive relaxation, and yoga/tai-chi/qi-gong.
Dietary supplements included use of non-multivitamins, non-vitamin supplements, minerals,
and herbs.

Outcome of interest

The primary outcome was the self-reported number of days missed from job or business
in the past twelve months due to illness or injury (0–364 days), excluding maternity
leave. Participants who had self-reported working in the past week were asked during
the past twelve months, “about how many days were missed from a job or business due
to injury or illness,” with a possible range of 0–366 days.

Other variables

Demographic variables included race, age, gender, household income, and highest level
of education achieved. A priori hypothesized confounders included BMI (underweight:
18.5, normal: 18.5-24.9, overweight: 25.0-29.9, obese: 30.0+ kg/m
²
), marital status, smoking status, level of alcohol consumption, number of chronic
conditions, surgery in the past twelve months, self-perceived general health, health
insurance status, number of employees at job or business, class of worker, and reasons
for using the self-reported top three CAM therapies. Type of employment was categorized
as working for a privately owned company, any type of government (local, state, and
federal government), or for one’s self. Possible reasons for CAM use included for
general wellness or general disease prevention, to improve energy, to improve immune
function, and to improve memory or concentration.

Analysis

Univariable analysis was performed to determine the raw frequency, weighted percentage,
and significance of the association between each variable and either days missed from
job/business or CAM use. Using the chi-square test, variables associated with both
the main exposure and outcome at ??=?0.10 were treated as potential confounders. This
? level allowed more variables to be considered for modeling since the effects of
these variables on days missed from job or business are not well known. Multivariable
Poisson regression was used to evaluate the association between CAM use and days missed
from job/business due to illness or injury. The minimally adjusted model included
race, age, gender, income, and education as covariates. Potential confounders identified
in univariable analyses were included in the fully adjusted models if they modified
the beta coefficient of any CAM use in minimally adjusted model by 10 % or greater.
Age, BMI, and number of chronic conditions were kept as continuous variables for regression
analysis (categorized in Tables 1, 2 and 3). Eigenvalues and variance inflation factors were examined to determine any collinear
variables; none of the significant variables were collinear. To make results generalizable
to the U.S. population and to adjust for clustering, stratification, and oversampling
of specific population subgroups, weighted Poisson regression was performed using
final person-level weight which included design, ratio, non-response, and post-stratification
adjustments 23]. All analyses were performed using SAS 9.4 (Cary, NC). The SURVEYFREQ commands were
used with strata, cluster, and weight to determine weighted percentages. The final
model was constructed using PROC GENMOD for weighted regression using Poisson distribution.

Table 1. Population characteristics by days missed from job/business due to illness or injury

Table 2. CAM use in past 12 months

Table 3. CAM use and days missed from job or business in past 12 months