Findings from the Quebec Family Study on the Etiology of Obesity: Genetics and Environmental Highlights

Abstract

The Quebec Family Study (QFS) was an observational study with three cycles of data collection between 1979 and 2002 in Quebec City, Canada. The cohort is a mixture of random sampling and ascertainment through obese individuals. The study has significantly contributed to our understanding of the determinants of obesity and associated disease risk over the past 35 years. In particular, the QFS cohort was used to investigate the contribution of familial resemblance and genetic effects on body fatness and behaviors related to energy balance. Significant familial aggregation and genetic heritability were reported for total adiposity, fat-free mass, subcutaneous fat distribution, abdominal and visceral fat, resting metabolic rate, physical activity level and other behavioral traits. The resources of QFS were also used to study the contribution of several nontraditional (non-caloric) risk factors as predictors of excess body weight and gains in weight and adiposity over time, including low calcium and micronutrient intake, high disinhibition eating behavior trait, and short sleep duration. An important finding relates to the interactions between dietary macronutrient intake and exercise intensity on body mass and adiposity.

Keywords: Calcium; Cohort; Diet; Eating behavior; Environment; Genes; Longitudinal study; Nutrition; Obesity; Observational study; Physical activity; Quebec Family Study; Sleep.

Fig. 1

Associations between risk factors and adult overweight/obesity in the cross-sectional sample. Logistic regression was used and ORs were determined for the “at risk” compared to the “reference” groups of risk factors for the odds of having a body mass index greater than 25 kg/m². Model adjusted for age, sex, and socioeconomic status. Legend of the x axis: 1 = high alcohol intake (≥10 g/day vs. 0 g/day), 2 = high dietary lipid intake (≥40 % fat/day vs. <30 % fat/day), 3 = non-consumption of multivitamin and dietary supplements (vs. consumer), 4 = high dietary restraint behavior (≥8 restraint score vs. ≤4 restraint score), 5 = non-participation in high-intensity physical activity (vs. ≥30 min/day), 6 = high susceptibility to hunger behavior (≥5 hunger score vs. ≤2 hunger score), 7 = low dietary calcium intake (<600 mg/day vs. ≥1,000 mg/day), 8 = high disinhibition eating behavior (≥6 disinhibition score vs. ≤3 disinhibition score) and 9 = short sleep duration (<6 hours/day vs. 7–8 h/day). OR, odds ratio; CI, confidence interval. n = 537 (230 men and 307 women). *P < 0.01; **P < 0.05. Figure adapted from Chaput et al. [58]

Fig. 2

Mean weight gain above baseline weight over the 6-year follow-up period for individuals with the risk factor relative to the reference category. Model adjusted for age, sex, baseline body mass index, length of follow-up, socioeconomic status, and all other risk factors. Legend of the x axis: 1 = high alcohol intake (≥10 g/day vs. 0 g/day), 2 = high dietary lipid intake (≥40 % fat/day vs. <30 % fat/day), 3 = non-consumption of multivitamin and dietary supplements (vs. consumer), 4 = high dietary restraint behavior (≥8 restraint score vs. ≤4 restraint score), 5 = non-participation in high-intensity physical activity (vs. ≥30 min/day), 6 = high susceptibility to hunger behavior (≥5 hunger score vs. ≤2 hunger score), 7 = low dietary calcium intake (<600 mg/day vs. ≥1,000 mg/day), 8 = high disinhibition eating behavior (≥6 disinhibition score vs. ≤3 disinhibition score) and 9 = short sleep duration (<6 hours/day vs. 7–8 h/day). CI, confidence interval. n = 283. Figure adapted from Chaput et al. [58]