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Meals & nutrition

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Mature Women Samples !!TOP!!

Background: Emerging research indicates that binge eating (BE; consuming unusually large amounts of food in one siting while feeling a loss of control) is prevalent among older women. Yet, health correlates of BE in older adult populations are poorly understood. The original study aimed to investigate BE prevalence, frequency, and health correlates in a sample of older adult women. Based on results from this first study, we then sought to replicate findings in two additional samples of older adult women from separate studies.

mature women samples

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Method: Using self-reported frequencies of BE from three separate samples of older women with very different demographics, we compared BE prevalence, frequency, and health correlates among older women. Study 1 (N = 185) includes data collected online (86% White; 59% overweight/obese status). Study 2 (N = 64) was conducted in person at a local food pantry (65% Hispanic; 47% household income

Results: Per DSM-5 frequency criterion of BE at least weekly, we found prevalence rates ranging from 19 to 26% across the three samples. Correlates of BE frequency included elevated negative mood, worry, BMI, and less nutritious food consumption.

Conclusions: Across three very different samples in terms of race/ethnicity, education, food security status, measurements, and sampling methodology, we found fairly consistent rates of self-reported BE at least weekly (19-26%). Results suggest that BE is related to negative health indices among older women and support the need for more research in this population.

This study documented and compared mean steps/day, demographic predictors of steps/day, and pedometer reliability in two longitudinal investigations, one involving a population-based youth sample (N = 367) and the other targeting postmenopausal women with type 2 diabetes (N = 270). Individuals were asked to wear pedometers (Yamax model SW-701) at the waist for 7 days and record steps/per day. They were also asked to record daily physical activities, duration, and perceived intensity (1 = low/light, 2 = medium/moderate, 3 = high/hard) for the same 7 days. In addition, survey data regarding usual physical activity was collected. Analyses of variance (ANOVA) were conducted to determine whether there were significant differences in pedometer results according to sex, age, and body mass index. Repeated measures ANOVAs were used to examine potential differences in results among differing numbers of days.

Mean steps/day were 10,365 steps in the youth sample and 4,352 steps in the sample of older women. Girls took significantly fewer steps than boys, older women took fewer steps than younger women, and both youth and women with greater body mass took fewer steps than those with lower body mass. Reliability coefficients of .80 or greater were obtained with 5 or more days of data collection in the youth sample and 2 or more days in the sample of older women. Youth and older women were more active on weekdays than on weekends. Low but significant associations were found between step counts and self-report measures of physical activity in both samples.

Mean steps/day and reliability estimates in the two samples were generally consistent with previously published studies of pedometer use. Based on these two studies, unsealed pedometers were found to offer an easy-to-use and cost-effective objective measure of physical activity in both youth and older adult populations.

Research has linked pedometer data with participant characteristics, such as sex [3, 7, 6, 8, 4], age [7, 4], and body mass [8, 2, 14]. It was hypothesized in the present investigation that youth would take more steps/day than older women (and younger-age youth/women would take more steps/day than older-age youth/women), that boys would take more steps/day than girls, and that body mass would be negatively associated with steps/day.

The purpose of the current investigation is to add to the existing literature on pedometer assessment by documenting mean steps/day and pedometer reliability in two samples: a population-based youth sample and a sample of postmenopausal women with type 2 diabetes.

In the youth sample, target children completed in-home surveys under the supervision of research assistants to ensure privacy. In the adult sample, women completed surveys at a central assessment site. In both samples, trained assessors measured height (m) and weight (kg) of participants using calibrated, sensitive scales.

A 7-day physical activity record was developed specifically for these two studies based on our past experience. For 7 days, target children and women were asked to complete a daily record of physical activities. The form was structured so that each day participants could separately record the type of activities in which they engaged (e.g., walking, jogging, aerobic activity, swimming), the perceived intensity of each activity (1 = low/light, 2 = medium/moderate, 3 = high/hard), and the number of minutes engaged in each activity. Based on these reports, a physical activity summary variable was created by multiplying frequency by duration by intensity of activities. The use of diaries to collect activity data has well-documented limitations, including possible misinterpretation of questions, difficulty for participants in recalling the time or intensity of activities, or deliberate misrepresentation (over-reporting), but self-report techniques are low-cost, have low participant burden, and are an acceptable method of assessing physical activity behavior as long as the limitations are recognized and/or in concert with more objective measures [22].

At the assessment visit, target children and women were shown how to wear a pedometer and record the number of steps taken each day for 7 days. Children, who were usually assessed in the evening, were instructed to start wearing the pedometer the following day; women, who were usually assessed in the morning, were instructed to start wearing the pedometer immediately. In both studies, participants were instructed to clip the pedometer to the waistline above the right knee each morning, to wear the pedometer all day while doing usual activities, and to remove the pedometer and record the day's steps at night before resetting the device and going to bed. All pedometers were unsealed, as in Rowe et al. [3]. The Yamax Digiwalker SW-701 (Yamax Corporation, Japan) was chosen for these studies because an identical model with fewer features (SW-200) performed best in a research study when compared to other pedometers [23]. From the pedometer data, the first and last days were excluded because of partial data collection and an average steps/day variable was computed by summing the number of steps for up to 5 days and dividing by the number of days for which pedometer information was recorded (if 5 days of data were not provided, this construct was still calculated based on fewer days).

In the sample of older women, 24% had only a high school or lower education while 66% reported having at least some college. About half of the sample (54%) reported an annual income of less than $30,000 with the rest of the sample (46%) reporting an income of $30,000 or greater. Education and income data were not available in the youth sample.

Based on a 7-day physical activity diary, older women averaged a score of 14.6 (SD = 20.7) on the variable reflecting minutes of activity multiplied by intensity over the past week, indicating a low level of activity. The women averaged 5.0 (SD = 6.4) bouts of moderate activity per week and 16.7 (11.4) bouts of all activity per week, including sedentary activities, based on their CHAMPS survey responses estimating activity over the past 6 months.

Of 367 youth participants, 362 provided at least 1 day of pedometer data (N = 308 gave 5 full days, N = 31 provided 4 days, N = 19 provided 3 days, N = 2 gave 2 days, and N = 2 recorded 1 day). All of the women in the older adult sample provided at least 2 days of pedometer data (N = 212 provided all 5 days, N = 45 recorded 4 days, N = 11 provided 3 days, and N = 2 gave 2 days). In both samples, all participants (except the 2 youth with only 1 day of data) reported pedometer totals on at least 1 weekend day, most commonly Saturday, and 1 weekday. Mean steps/day measured by pedometers for the two samples are presented in Table 1. As shown, youth took 10,365 steps/day (SD = 4,178) compared to 4,352 steps/day (SD = 2,981) in the sample of chronically ill older women.

In the sample of older women, age was important (F(3,281) = 3.62, p = .014) in that women younger than 60 years of age recorded significantly more steps per day on their pedometers than older women.

In both samples, body mass index was strongly associated with pedometer results (youth sample: F(3,360) = 3.22, p = .023. sample of older women: F(3,280) = 15.93, p

Reliability results for pedometer data are presented in Table 2. Reliability coefficients ranged from .73 (2 days) to .82 (5 days) in the youth sample, and from .84 (2 days) to .87 (5 days) in the sample of older women.

Pedometers are easy to use and relatively inexpensive, which makes them attractive measurement tools for large-scale studies. More elaborate activity monitors, such as accelerometers, may cost 20 times as much and require special software. But questions remain about pedometer measurement, including norms for different populations, sources of variation, and instrument reliability. The present investigation sought to address these questions in a population-based youth sample and a sample of chronically ill older women. This is one of very few studies reporting pedometer results in which randomized sampling techniques were used for recruitment.

Mean steps/day in the two samples were generally consistent with previously published studies of pedometer use, and were consistent with our hypothesis that youth would take more steps/day than older women. 041b061a72


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