Nearly all participants, daughters of NHSII nurses, are white (95%). At baseline, 12.7% were overweight (85th–95th percentile on CDC BMI charts), 4.8% were obese (>95th percentile), and 4.7% were very lean (<5th%ile). In 2001, when data were collected on our 4 exposures, 16% of the girls were aged 14–15yr, 38% were 16–17yr, 34% were 18–19yr, and 12% were 20–21yr. At that time, 52% of girls were spending 1–5 hours/week on the computer for recreation (34%, even more hours), only 31.3% were sleeping 8 or more hours/night, 36% drank coffee, and 35% drank alcohol. The mean annual BMI gains, from year 2000 (when girls were aged 13–20yr) to 2001, declined with age, except for age 18 to 19yr (+0.47kg/m2), which may reflect weight increases as girls begin college. Beginning at age 18yr, mean alcohol intakes (0.22 servings/day) exceeded mean coffee intakes (0.15 servings/day).
Correlations among the 4 exposures were highly significant, except for coffee with Internet time (R=+0.009, p=0.54), demonstrating the importance of joint multivariate analyses of these exposures in relation to weight gain. The other correlations (all P<0.0001) were: Internet with sleep R=−0.093, Internet with alcohol R=+0.086, sleep with coffee R=−0.102, sleep with alcohol R=−0.116, and coffee with alcohol R=+0.111.
Girls spending more time on the Internet had significantly greater BMI increases during the same year (, top row), whether Internet time was measured categorically (6–10hrs/wk and 16+hrs/week) or continuously (hours/day). When we further included past year physical activity and TV/videos/computer-games in the model, the Internet effect was weaker. Adjusting for TV may be over-control as girls watch television at the same time as checking email, Instant Messaging or surfing the Internet. For girls aged 18+ years, the Internet effects were further weakened and not statistically significant. Older girls are likely also spending substantial non-recreational time on the computer for college or employment (data not collected), which may have diminished our estimates.
TABLE I Past-yr recreational Internet use (2001 report) and its estimated association (β, se) with BMI change (kg/m2), 2000 to 2001. Models of categorical Internet time appear in middle 5 columns, and continuous Internet models are on right. Models adjust (more ...)
Associations between sleep and BMI gain were summarized similarly (). Estimates shown in the top row were obtained from the same two multivariate models that provided estimates for , , and . A significant inverse trend was present even after adjusting for physical activity and TV/videos/computer-games. The strongest effects were on the older girls (18+). Those who slept 5 or fewer hours/night gained significantly more BMI (+0.322 kg/m2) during the year compared with those sleeping 8 hours.
TABLE II Usual sleep (hours/night), reported in 2001, and its estimated association (β, se) with BMI change (kg/m2) from 2000 to 2001. Models of categorical sleep time appear in middle five columns, and continuous sleep models are on right. Models adjust (more ...)
TABLE III Past-yr coffee intake (not decaf, 2001 report) and its estimated association (β, se) with BMI change (kg/m2), 2000 to 2001. Models of categorical coffee intake appear in middle five columns, and continuous coffee models are on right. Models adjust (more ...)
TABLE IV Past-yr alcohol consumption (2001 report) and its estimated association (β, se) with BMI change (kg/m2), 2000 to 2001. Models of categorical alcohol intake appear in middle three columns, and continuous alcohol models appear on far right. Models (more ...)
None of the coffee models () provided evidence that drinking coffee promotes weight gain. In fact, though not significant, the bulk of the evidence (see 5+cups/week and continuous model estimates) suggested protection against weight gain.
Girls who typically consumed 2+servings/week of alcoholic beverages gained significantly more weight than those who consumed the least (). Statistically significant linear trends were observed, as well. For the older girls (18+yrs), the estimated effect (β =+0.115) for the 2+servings/week group, though only marginally significant (p<0.07), was larger than the significant effect (β=+0.108) from the full group of girls (both older and younger than 18yr).
To illustrate the effect of modifying all 4 exposures simultaneously, we compare 2 hypothetical girls who are identical (age 19, same prior BMI, same physical activity and same TV/videos/computer-games) except in the four exposures. One girl had no recreational Internet time, slept 8 hours nightly, consumed no alcohol, and drank a cup of coffee daily. The other girl was on the Internet 6–10 hours/week, slept 5 hours/night, drank no coffee but regularly consumed 2+ alcohol servings/week. The latter girl gained (according to the categorical exposures model, bottom of , , , and ) +0.65 more BMI over 1 year. For a 19-yr-old of average height and weight, this represents a nearly 4 pound weight gain.