Natalie Jo Hawes1, Amanda T Wiggins1, Deborah B Reed1, Frances Hardin-Fanning2. 1. University of Kentucky College of Nursing, University of Kentucky, Lexington, Kentucky. 2. University of Alabama Capstone College of Nursing, University Boulevard East, Tuscaloosa, Alabama.
Abstract
BACKGROUND: Farmers' work schedules can result in inconsistent sleep patterns which negatively impact health. PURPOSE: To explore the relationships between sleep, obesity, and depression in working, older farmers and their spouses. Covariates included body mass index (BMI), age, and gender. METHODS: Sleep quality, BMI, and depression were assessed in farmers (n = 1,394) 50 years and older. Bivariate associations among all covariates (i.e., age, gender, BMI, sleep) and dependent variable (i.e., depression) were analyzed using Pearson's correlation. Multivariable associations of the Center for Epidemiologic Studies Depression Scale (CESD). BMI with other study variables were assessed using linear regression. RESULTS: BMI was positively associated with sleep apnea symptoms (p ≤ 0.0001) and CESD scores (p = 0.0006). Participants with difficulty falling asleep were more likely to have poor sleep quality (p ≤ 0.0001) and higher CESD scores (p ≤ 0.0001). Poor sleep quality was associated with higher CESD scores (p ≤ 0.0001). Increased age, female gender, higher BMI, sleep apnea symptoms, and poorer sleep quality were all predictive of higher depressive symptoms. DISCUSSION: Farmers have unique lifestyles that increase the risk of poor sleep. Screening for sleep pattern disruption and understanding its impact could result in lower rates of depression and obesity in this group of high-risk individuals.
BACKGROUND: Farmers' work schedules can result in inconsistent sleep patterns which negatively impact health. PURPOSE: To explore the relationships between sleep, obesity, and depression in working, older farmers and their spouses. Covariates included body mass index (BMI), age, and gender. METHODS: Sleep quality, BMI, and depression were assessed in farmers (n = 1,394) 50 years and older. Bivariate associations among all covariates (i.e., age, gender, BMI, sleep) and dependent variable (i.e., depression) were analyzed using Pearson's correlation. Multivariable associations of the Center for Epidemiologic Studies Depression Scale (CESD). BMI with other study variables were assessed using linear regression. RESULTS: BMI was positively associated with sleep apnea symptoms (p ≤ 0.0001) and CESD scores (p = 0.0006). Participants with difficulty falling asleep were more likely to have poor sleep quality (p ≤ 0.0001) and higher CESD scores (p ≤ 0.0001). Poor sleep quality was associated with higher CESD scores (p ≤ 0.0001). Increased age, female gender, higher BMI, sleep apnea symptoms, and poorer sleep quality were all predictive of higher depressive symptoms. DISCUSSION: Farmers have unique lifestyles that increase the risk of poor sleep. Screening for sleep pattern disruption and understanding its impact could result in lower rates of depression and obesity in this group of high-risk individuals.