Leila Cheraghi1,2, Parisa Amiri3, Golnaz Vahedi-Notash1, Sara Jalali-Farahani1, Davood Khalili2,4, Fereidoun Azizi5. 1. Research Center for Social Determinants of Health, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O.Box: 19395-4763, Tehran, Iran. 2. Department of Epidemiology and Biostatistics, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3. Research Center for Social Determinants of Health, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O.Box: 19395-4763, Tehran, Iran. amiri@endocrine.ac.ir. 4. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5. Endocrine Research Center, Research Institute for Endocrine Sciences, ShahidBeheshti University of Medical Sciences, Tehran, Iran.
Abstract
BACKGROUND: Non-participation in cohort studies, if associated with both the exposure and occurrence of the event, can introduce bias in the estimates of interest. This study aims to identify factors associated with follow-up participation in Tehran Lipid and Glucose Study, a large-scale community-based prospective study in West Asia. METHODS: A sample of 10,368 adults from TLGS was included in the analysis. All analyses were split according to sex and age groups (20-39, 40-59, and 60 years). The associations between socio-demographic, health, and lifestyle factors with response rate were identified using the Generalized Estimating Equations model. RESULTS: Over the median of 15.7 years of follow up the response rate was 64.5%. The highest response rate was observed in those aged 40-59 years for both sexes. Current smokers had lower odds of response in both sexes for all age groups, ranging from 0.51 to 0.74, p < 0.01. In young adults, being single (OR = 0.79, OR = 0.57, p ≤ 0.01, respectively for men and women) and unemployed (OR = 0.73, OR = 0.76, p ≤ 0.01, respectively for men and women) in both sexes, high physical activity in men (OR = 0.77, p < 0.01), high education (OR = 0.75, p = 0.02) and obesity (OR = 0.85, p = 0.05) in women were associated with lower response rate. For the middle-aged group, diabetes in men (OR = 0.77, p = 0.05) and hypertension (OR = 0.84, p = 0.05), and having a history of cancer (OR = 0.43, p = 0.03) in women were factors associated with lower response rates. Finally, interventions for both sexes (OR = 0.75, OR = 0.77, p ≤ 0.05, respectively for men and women) and being divorced/widow in women (OR = 0.77, p = 0.05) were the factors associated with the lower response rate in the elderly. CONCLUSIONS: Long-term participation was influenced by socio-demographic, health, and lifestyle factors in different sex- and age-specific patterns in TLGS. Recruitment strategies targeting these factors may improve participant follow-up in longitudinal studies.
BACKGROUND: Non-participation in cohort studies, if associated with both the exposure and occurrence of the event, can introduce bias in the estimates of interest. This study aims to identify factors associated with follow-up participation in Tehran Lipid and Glucose Study, a large-scale community-based prospective study in West Asia. METHODS: A sample of 10,368 adults from TLGS was included in the analysis. All analyses were split according to sex and age groups (20-39, 40-59, and 60 years). The associations between socio-demographic, health, and lifestyle factors with response rate were identified using the Generalized Estimating Equations model. RESULTS: Over the median of 15.7 years of follow up the response rate was 64.5%. The highest response rate was observed in those aged 40-59 years for both sexes. Current smokers had lower odds of response in both sexes for all age groups, ranging from 0.51 to 0.74, p < 0.01. In young adults, being single (OR = 0.79, OR = 0.57, p ≤ 0.01, respectively for men and women) and unemployed (OR = 0.73, OR = 0.76, p ≤ 0.01, respectively for men and women) in both sexes, high physical activity in men (OR = 0.77, p < 0.01), high education (OR = 0.75, p = 0.02) and obesity (OR = 0.85, p = 0.05) in women were associated with lower response rate. For the middle-aged group, diabetes in men (OR = 0.77, p = 0.05) and hypertension (OR = 0.84, p = 0.05), and having a history of cancer (OR = 0.43, p = 0.03) in women were factors associated with lower response rates. Finally, interventions for both sexes (OR = 0.75, OR = 0.77, p ≤ 0.05, respectively for men and women) and being divorced/widow in women (OR = 0.77, p = 0.05) were the factors associated with the lower response rate in the elderly. CONCLUSIONS: Long-term participation was influenced by socio-demographic, health, and lifestyle factors in different sex- and age-specific patterns in TLGS. Recruitment strategies targeting these factors may improve participant follow-up in longitudinal studies.