A cross‐sectional analysis of physical activity and weight misreporting in diverse populations: The Seattle Obesity Study III

Abstract

Background: In-person assessments of physical activity (PA) and body weight can be burdensome for participants and cost prohibitive for researchers. This study examined self-reported PA and weight accuracy and identified patterns of misreporting in a diverse sample. Methods: King, Pierce and Yakima county residents, aged 21-59 years (n = 728), self-reported their moderate-to-vigorous PA (MVPA) and weight, in kilograms. Selfreports were compared with minutes of bout-level MVPA, from 3 days of accelerometer data, and measured weights. Regression models examined characteristics associated with underreporting and overreporting of MVPA and weight, the potential bias introduced using each measure and the relation between perceived and measured PA and weight. Results: MVPA underreporting was higher among males and college educated participants; however, there was no differential MVPA overreporting. Weight underreporting was higher among males, those age 40-49 years and persons with obesity. Weight overreporting was higher among Hispanic participants and those reporting stress, unhappiness and fair or poor health. The estimated PA-obesity relation was similar using measured and self-reported PA but not self-reported weight. Perceived PA and weight predicted measured values. Conclusion: Self-reported PA and weight may be useful should objective measurement be infeasible; however, though population-specific adjustment for differential reporting should be considered.

From the clinic to the community: Can health system data accurately estimate population obesity prevalence?

“…Though the rank ordering of census tracts was quite similar in BRFSS and UW data, estimates of obesity prevalence in each tract as computed from UW data were nearly always higher than that computed from BRFSS. This is likely to be an artifact of comparing self‐report data with clinical measurements: people tend to self‐report taller heights and lower weights than are identified in clinical assessments (39‐41), and such gaps between self‐reported and clinically assessed body habitus may be patterned demographically (42). Our results suggest that surveillance based on anthropometrics taken through health care visits and part of medical records systems may help somewhat correct for these self‐report artifacts in future surveillance estimates.…”

Inedible Food Waste Linked to Diet Quality and Food Spending in the Seattle Obesity Study SOS III

“…The SOS III was a population-based longitudinal study of 872 adult residents of King, Pierce, and Yakima Counties in WA State [ 13 , 14 ]. Participant recruitment was county specific, relying on address-based sampling schemes stratified by property values along with community outreach to ensure broad representation by socio-economic status and race/ethnicity.…”

Some Ultra-Processed Foods Are Needed for Nutrient Adequate Diets: Linear Programming Analyses of the Seattle Obesity Study

“…The SOS III was a population-based study of adult men and women living in King, Pierce, and Yakima Counties in Washington State [12]. County-specific recruitment schemes used address-based sampling stratified by residential property values along with community outreach to ensure broad representation by socioeconomic status and race/ethnicity.…”

“…There is also an economic dimension [10,11]. In the Seattle Obesity Study III (SOS III) [12], percent energy from ultra-processed foods was associated with lower diet quality but also with significantly lower food spending [10,11]. Study participants in the bottom decile of estimated diet cost ($216/person/month) derived 67.5% energy from ultra-processed foods as compared to 48.7% for those in the top decile ($370/person/month) [11].…”

“…All foods were assigned into NOVA categories. Observed dietary intakes for 857 male and female adults came from the Seattle Obesity Study III [12]. The goal was to create optimized 2000 kcal/d food patterns that met standards for 22 nutrients while respecting existing food habits of SOS III participants.…”