NNNS: Effect on Energy Balance (2010)
Individuals who were interviewed during the two follow-up surveys. The Pawtucket Heart Health Program (PHHP) is a community-based study of cardiovacular disease prevention conducted in Pawtucket, Rhode Island. PHHP has completed six biennial cross-sectional household health surveys and three follow-up surveys (from 1981 to 1982). Respondents to the first survey (1981 to 1982) were rexamined in 1986-1987 and again in 1991-1992.
- Pregnant
- Lacking body mass index measurements at either time period
- Subjects who had 10 or more missing items or extremely high or low scores for daily energy intakes on the baseline FFQ
- Diabetes.
Recruitment
- Protocol was approved for PHHP by the the Memorial Hospital of Rhode Island's institutional review board on human research. Survey participants were originally identified by randomly selecting households and then randomly selecting one participant, aged 18 to 64 years from each household using the methods of Kish and Deming.
Design
- The prospective association of nutrient consumption and weight change was examined in a randomly selected cohort examined four years apart.
Statistical Analysis
- SAS univariate statistics were calculated for all covariates of interest. Student's T-test for independent samples were used to test differences between persons who received the FFQ and people who did not receive the FFQ.
- Diet was logarithmically transformed because of the skewed distribution. Age-adjusted mean weight changes, age and energy-adjusted nutrient intakes were computed using analysis of variance. Multiple regression analyses were used to determine the associations of weight change with different nutrients after adjustment was made for age, smoking status, body mass index, aerobic activity and total energy. Analysis of the covariance model for men and women, combined, was run with gender-by-nutrient interaction to assess the differences between nutrients or food groups and weight change among men and women.
Timing of Measurements
Trained interviewers obtained information on demographic characteristics and on cardiovascular disease-related knowledge, attitudes and behaviors. Medication use was based on self-reporting in response to a series of questions. All currently used medications that were present in the home at the time of the interview were reviewed and recorded.
Food frequency questionnaire (FFQ): Administered to a random subsample of the PHHP survey respondents. FFQ listed food items with serving sizes and asked about the frequency of intake during the previous year. Intake was computed by multiplying the frequency of intake by the nutrient content of the food item. Foods were grouped into broad categories (all red meats, processsed meat, poultry and fish, all vegetables, all fruits) based on the National Research Council's Interim Dietary Guidelines and the American Cancer Society's recommendations. Additional food categories were developed by the authors for fats and oils, sweets and snacks and dairy products.
- Measured height (without shoes)
- Weight (in light clothing)
- Diabetes mellitus: Determined by use of hypoglycemic agents or insulin use.
- Smoking status: Determined by asking participants whether they are currently smoking cigarettes, whether they had quit smoking cigarettes in the past 12 months or whether they had never smoked cigarettes.
- Physical activity: Based on self-reporting. Subjects were asked if they were engaged in regular physical activity and how many days per week they were engaged in that activity.
- Definition of aerobic activity: If they participated in physical activity long enough to build up a sweat at least three days per week.
- Body mass index: Was calculated as weight (kg) divided by height (m).
Initial N
- Of 1,081 respondents to the 1981-1982 survey, 556 individuals completed the baseline food frequency questionnaire and were also interviewed four years later.
Attrition
- Final N: 176 men and 289 women
- 91 participants were excluded for the following reasons:
- Nine who were pregnant at either time point; because of possible eating patterns or weight changes
- Seven who were lacking body mass index measurements at either time period
- 23 who had 10 or more missing items or extremely high or low scores for daily energy intakes on the baseline FFQ
- 52 who had diabetes at either time period.
Age, Baseline Characteristics of Study Participants, 1986-1992
| Characteristic | Study Participant (N=465) |
| Female (percentage) | 94.0 |
| Female (percentage) | 62.2 |
| Education (percentage ≥12 years) | 69.7 |
| Married (percentage) | 66.5 |
| Employed (percentage) | 71.6 |
| Current smokers (percentage) | 23.0 |
| Physical activity (percentage yes) | 40.7 |
| Attempted weight loss in the past 12 months (percentage yes) | 54.6 |
| Age (years) | 46.6±13.5 |
| Weight (kg) | 71.9±15.9 |
| Height (m) | 1.64±0.1 |
| Body mass index (kg/m2) | 26.5±5.0 |
- Location: Southeastern New England.
Age-adjusted weight change during four years of follow-up: Significant differences were found between individuals who gained ≥1.03kg and individuals who had a slight weight loss. Individuals with BMI<26kg/m2 gained on average 1kg, while individuals with BMI of 26.0kg/m2 to 29.99kg/m2 had a slight weight loss on average. Overweight individuals with BMI>30kg/m2 had the greatest weight gains (>1.4kg).
Mean weight by tertiles of selected age and energy-adjusted baseline nutrients: Except for the association of mean baseline weight and saccharin, the association of both mean baseline weight and mean weight change and other nutrients were not significant. For saccharin consumption, individuals in the high tertile had the largest weight gain (1.4kg).
Mean Weight and Weight Change by Tertiles of Age-Adjusted Total Energy and Tertiles of Selected Age and Total Energy-Adusted Nutrients
| Dietary Factor (kg) | Mean Baseline Weight (kg) ± Standard Error | Mean Weight Change (kg) ± Standard Error |
| Total Energy (kJ/day) | ||
| <6,258.0 | 72.7±1.3 | 0.2±0.5 |
| 6,258.0-8,926.1 | 70.6±1.3 | 0.6±0.5 |
| >8,926.1 | 72.4±1.3 | 1.3±0.5 |
| Saccharin (g)a-c | ||
| 0 | 69.5±1.0 | 0.4±0.4 |
| 0.1-28.2 | 74.9±2.1 | 0.1±0.7 |
| >28.2 | 74.6±1.3 | 1.4±0.4 |
| Sucrose (g) | ||
| ≤36.0 | 74.3±1.5 | 0.5±0.5 |
| 36.1-57.0 | 70.6±1.3 | 1.3±0.5 |
| >57.0 | 70.8±1.6 | 0.3±0.6 |
A: P<0.02; Tertile One mean baseline weight vs. Tertile Two mean baseline weight
B: P<0.02; Tertile One mean baseline weight vs. Tertile Three mean baseline weight
C: P<0.06; Tertile One mean weight change vs. Tertile Three mean weight change.
The relationship between median intake of total energy and selected nutrients by tertiles of weight change also showed the only nutrient significantly associated with tertiles of weight change was saccharin. However, those gaining the most weight used saccharin and also continued to use sucrose.
Median Intake of Total Energy and Selected Nutrients Associated with Tertiles of Weight Change
| Tertile of Weight Changea | Tertile of Weight Change | Tertile of Weight Change | |
| Dietary Factor | One: N=158 | Two: N=154 | Three: N=153 |
| Total Energy (kcal/day) | 1,746.9 | 1,819.5 | 1,861.6 |
| Total Fatb | 58.4 | 63.2 | 64.3 |
| Animal Fatb | 32.8 | 36.5 | 40.3 |
| Vegetable Fat b | 24.2 | 26.3 | 25.6 |
| Carbohydrateb | 214.7 | 231.3 | 230.2 |
| Proteinb | 74.1 | 75.9 | 80.0 |
| Cholesterolb | 278.1 | 284.8 | 308.2 |
| Caffeineb | 172.9 | 189.9 | 172.9 |
| Saccharinbc | 0 | 0 | 13.8 |
| Sucroseb | 44.9 | 46.3 | 43.2 |
A: Tertile One ≤-1.59kg; Tertile Two >-1.59kg to +2.72kg; Tertile Three >+2.72kg
B: Grams per day
C: P≤0.05.
- Physical acitvity by tertiles and relationship to weight: No significant differences.
- Regression models of relationship between selected nutrients and weight change (men and women were combined, adjusting for age, bseline BMI, smoking, physical activity level and total energy): None of the nutrients were significantly associated with weight gain, although age was negatively associated (P<0.001) with weight gain, while total energy was postitively related to weight gain (P=0.05). The relationship between food groups and weight change was not significantly associated with weight gain.
| Nutrient | Estimated Regression Coefficient | Standard Error | P-Value |
| Linoleic Acid (g) | -7.0458 | 4.2660 | 0.09 |
| Total Fat (g) | 2.3049 | 6.2753 | 0.71 |
| Animal Fat (g) | 4.8509 | 4.2819 | 0.26 |
| Vegetable Fat (g) | -5.2189 | 3.6569 | 0.15 |
| Protein (g) | 7.7519 | 6.4352 | 0.22 |
| Carbohydrate (g) | 0.5988 | 7.7676 | 0.94 |
| Cholesterol (g) | 4.8958 | 3.9009 | 0.21 |
| Caffeine (g) | 0.1426 | 1.0036 | 0.88 |
| Saccharin (g) | 0.3731 | 0.2485 | 0.13 |
| Sucrose (g) | 2.5961 | 3.1911 | 0.41 |
|
Fats and Oils (Servings Per Week) |
-0.3334 | 0.3849 | 0.38 |
| Red meats (Servings Per Week) | 0.2450 | 0.8489 | 0.77 |
| Fish and chicken (Servings Per Week) | 0.6408 | 0.6754 | 0.34 |
| Dairy (Servings Per Week) | -0.0974 | 0.322 | 0.76 |
| Fruits (Servings Per Week) | 0.4001 | 0.2973 | 0.17 |
| Vegetables (Servings Per Week) | -0.0502 | 0.3487 | 0.89 |
| Sweets (Servings Per Week) | -0.3057 | 0.4751 | 0.52 |
A: A separate model was fitted for each nutrient or food group which included age, body mass index, smoking status, physical activity, total energy and the nutrient or food group as predictor variables and weight changes as the dependent variable.
B: All nutrients and total energy have been log transformed (base 10)
C: Coefficient for age; B=-0.2398, P<0.001
D: Coefficient for total energy; B=7.1526, P=0.05.
- These findings indicate that weight gain increased with increasing baseline total energy intake, particularly in the young. Future research is required to determine ways of decreasing energy intake in younger individuals.
- The results showed a positive association of weight gain with artificial sweeteners. However, the results must be interpreted with caution, since there was no information on changes in consumption of saccharin and whether saccharin consumption was the cause or effect of the weight gain.
- Limitations: Nutrient intake assessments were based on self-reports, which may result in measurement error. Because total nutrient intake was measured, variations in patterns of food intake could not be assessed. The data also did not give the caloric distribution throughout the day or the number of snacks or meals consumed and lack of precision in assessment of aerobic activity and attempted weight loss may explain the findings that these factors were not significant independent predictors of weight gain in multivariate models.
- Bias: Participants' differences in baseline characteristics (namely better educated, more physically active, lower baseline BMI and more attempts to lose weight in the previous 12 months), compared to the excluded participants, may limit the interpretation of the data.
| Government: | NIDDK |
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Quality Criteria Checklist: Primary Research
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| Relevance Questions | |||
| 1. | Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) | Yes | |
| 2. | Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? | Yes | |
| 3. | Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? | Yes | |
| 4. | Is the intervention or procedure feasible? (NA for some epidemiological studies) | Yes | |
| Validity Questions | |||
| 1. | Was the research question clearly stated? | Yes | |
| 1.1. | Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? | Yes | |
| 1.2. | Was (were) the outcome(s) [dependent variable(s)] clearly indicated? | Yes | |
| 1.3. | Were the target population and setting specified? | Yes | |
| 2. | Was the selection of study subjects/patients free from bias? | Yes | |
| 2.1. | Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? | Yes | |
| 2.2. | Were criteria applied equally to all study groups? | Yes | |
| 2.3. | Were health, demographics, and other characteristics of subjects described? | Yes | |
| 2.4. | Were the subjects/patients a representative sample of the relevant population? | Yes | |
| 3. | Were study groups comparable? | Yes | |
| 3.1. | Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) | N/A | |
| 3.2. | Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? | Yes | |
| 3.3. | Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) | No | |
| 3.4. | If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? | Yes | |
| 3.5. | If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) | N/A | |
| 3.6. | If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? | N/A | |
| 4. | Was method of handling withdrawals described? | Yes | |
| 4.1. | Were follow-up methods described and the same for all groups? | Yes | |
| 4.2. | Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) | Yes | |
| 4.3. | Were all enrolled subjects/patients (in the original sample) accounted for? | Yes | |
| 4.4. | Were reasons for withdrawals similar across groups? | Yes | |
| 4.5. | If diagnostic test, was decision to perform reference test not dependent on results of test under study? | N/A | |
| 5. | Was blinding used to prevent introduction of bias? | Yes | |
| 5.1. | In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? | N/A | |
| 5.2. | Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) | N/A | |
| 5.3. | In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? | Yes | |
| 5.4. | In case control study, was case definition explicit and case ascertainment not influenced by exposure status? | N/A | |
| 5.5. | In diagnostic study, were test results blinded to patient history and other test results? | N/A | |
| 6. | Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? | No | |
| 6.1. | In RCT or other intervention trial, were protocols described for all regimens studied? | N/A | |
| 6.2. | In observational study, were interventions, study settings, and clinicians/provider described? | Yes | |
| 6.3. | Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? | No | |
| 6.4. | Was the amount of exposure and, if relevant, subject/patient compliance measured? | No | |
| 6.5. | Were co-interventions (e.g., ancillary treatments, other therapies) described? | N/A | |
| 6.6. | Were extra or unplanned treatments described? | N/A | |
| 6.7. | Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? | N/A | |
| 6.8. | In diagnostic study, were details of test administration and replication sufficient? | N/A | |
| 7. | Were outcomes clearly defined and the measurements valid and reliable? | Yes | |
| 7.1. | Were primary and secondary endpoints described and relevant to the question? | Yes | |
| 7.2. | Were nutrition measures appropriate to question and outcomes of concern? | Yes | |
| 7.3. | Was the period of follow-up long enough for important outcome(s) to occur? | Yes | |
| 7.4. | Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? | Yes | |
| 7.5. | Was the measurement of effect at an appropriate level of precision? | No | |
| 7.6. | Were other factors accounted for (measured) that could affect outcomes? | Yes | |
| 7.7. | Were the measurements conducted consistently across groups? | Yes | |
| 8. | Was the statistical analysis appropriate for the study design and type of outcome indicators? | Yes | |
| 8.1. | Were statistical analyses adequately described and the results reported appropriately? | Yes | |
| 8.2. | Were correct statistical tests used and assumptions of test not violated? | Yes | |
| 8.3. | Were statistics reported with levels of significance and/or confidence intervals? | Yes | |
| 8.4. | Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? | N/A | |
| 8.5. | Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? | Yes | |
| 8.6. | Was clinical significance as well as statistical significance reported? | No | |
| 8.7. | If negative findings, was a power calculation reported to address type 2 error? | N/A | |
| 9. | Are conclusions supported by results with biases and limitations taken into consideration? | N/A | |
| 9.1. | Is there a discussion of findings? | Yes | |
| 9.2. | Are biases and study limitations identified and discussed? | Yes | |
| 10. | Is bias due to study's funding or sponsorship unlikely? | N/A | |
| 10.1. | Were sources of funding and investigators' affiliations described? | Yes | |
| 10.2. | Was the study free from apparent conflict of interest? | Yes | |