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DFA: Linoleic Acid (LA) and Intermediate Health Outcomes (2011)

Citation:

Van Dam RM, Willett WC, Rimm EB, Stampfer MJ, Hu FB. Dietary fat and meat intake in relation to risk of type 2 diabetes in men. Diabetes Care. 2002 Mar; 25 (3): 417-424. PMID: 11874924.

PubMed ID: 11874924
 
Study Design:
Prospective Cohort Study
Class:
B - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
Research Purpose:

To examine dietary fat and meat intake in relation to risk of type 2 diabetes in men.

Inclusion Criteria:
  • Participant in the Health Professionals Follow-up Study
  • Male health professional
  • 40 years to 75 years of age in 1986.
Exclusion Criteria:
  • Men who did not satisfy the a priori criteria of a reported daily energy intake between 3.3mJ and 17.6mJ (800kcal and 4,200kcal) and blank responses for fewer than 70 of 131 food items on the diet questionnaire
  • Report of diabetes, cardiovascular disease (myocardial infarction, angina pectoris, coronary artery surgery or stroke) or cancer (except non-melanoma skin cancer) at baseline.
Description of Study Protocol:
  • Recruitment: Participant in the Health Professional Follow-up Study
  • Design: Prospective cohort
  • Intervention: Grouped according to fat and meat intake.

Statistical Analysis

  • Analyses adjusted for age and energy intake were based on incidence rates of type 2 diabetes, using person-months of follow-up
  • Participants contributed follow-up time from the return of the 1986 questionnaire until diagnosis of type 2 diabetes, death or the end of the study period
  • Relative risks were calculated by dividing the incidence rate of type 2 diabetes among men in each category of intake by the rate in the lowest category
  • The Mantel-Haenzel estimator was used to adjust for age (across five-year categories) and total energy intake. Linear trends were tested with the Mantel Extension test.
  • Pooled logistic regression analyses were used with two-year intervals to estimate multivariate-adjusted RRs for each category of intake, as compared with the lowest category. With short time-intervals and low rates of events, this approach gives results very similar to Cox proportional hazards analyses (ref 35)
  • Participants who died or were diagnosed with diabetes during a two-year cycle were censored at the end of that two-year period and were not entered in any subsequent two-year cycle
  • To reduce within-subject variation and best represent long-term diet, the cumulative average of dietary intakes from all available dietary questionnaires was used up to the start of each two-year follow-up interval. The 1986 intake was used for the follow-up between 1986 and 1990; the average of the 1986 and 1990 intake was used for the follow-up between 1990 and 1994; the average of the 1986, 1990 and 1994 intakes was used for the follow-up between 1994 and 1998.
  • Updates of diet were stopped at the beginning of the time-interval during which individuals developed hypertension, hypercholesterolemia, cancer (except non-melanoma skin cancer) or cardiovascular diseases (as mentioned in the exclusion criteria) because changes in diet after development of these end-points may confound the relationship between diet and diabetes
  • To reduce residual confounding, the same cumulative updating approach was used for physical activity and alcohol intake, using the information from all the available assessments
  • BMI and smoking status were also updated during follow-up, using the most recent data for each two-year interval
  • Categorical variables were included in the models as binary indicator variables
  • Linear trends were tested for across categories of dietary intake by assigning each participant the median value for the category and modeling this value as a continuous variable
  • In addition, analyses were conducted with dietary intake and potential confounders (age, BMI and physical activity) modeled as continuous variables
  • Tests for statistical interaction were conducted by including cross-product terms of continuous variables in a multivariate logistic regression model
  • All P-values are two-sided.
Data Collection Summary:

Timing of Measurements

Two-year intervals from 1986 through 1998.

Dependent Variables

  • Risk of type 2 diabetes: Every two years, questionnaires were mailed to update information on exposures and to identify new cases of type 2 diabetes and other diseases
  • A supplementary questionnaire on symptoms, diagnostic tests and medication was mailed to all men who reported a diagnosis of diabetes on any of the biennial follow-up questionnaires
  • Confirmation of diabetes required at least one of the following
    1. An elevated plasma glucose concentration (fasting plasma glucose at least 7.8mmol per L, random plasma glucose at least 11.1mmol per L or plasma glucose at least 11.1mmol per L after at least two hours during an oral glucose tolerance test), plus at least one classic symptom (excessive thirst, polyuria, weight lossor hunger)
    2. At least two elevated plasma glucose concentrations on different occasions
    3. Treatment with insulin or oral hypoglycemic medication.
  • Men who reported type 1 diabetes were excluded
  • Criteria were consistent with Who in 1985; ADA classification was not used, as majority of cases occurred before these criteria were published
  • Validity was verified by a blinded physician with medical records in a sub-sample of 71 participants of the cohort.

Independent Variables

  • Dietary assessment used a 131-item semiquantitative food frequency questionnaire. For each food, a commonly-used unit or portion size was specified and participants were asked to indicate for each food how often, on average, they had consumed the amount specified during the past year. The questionnaire also included questions about the types of fat commonly used for cooking and at the table and there was an open-ended section for foods that were not listed. Nutrient intakes were computed by multiplying the consumption frequency of each food used by the nutrient content in the specified portion. Values for the nutrient amounts in foods were obtained from the Harvard University Food Composition database, derived from USDA sources and supplemented with information from manufacturers and published literature. The validity and reproducibility of the food-frequency questionnaire was assessed among 127 participants of this cohort.
  • Fat intake: Total fat, saturated fat, oleic acid, trans-fat, linoleic acid, alpha-linolenic acid, long-chain n-3 fat; quintiles of intake
  • Meat consumption: Frequency of consumption of total processed meat (bacon, hot dogs, other processed meats).

Control Variables

  • Age
  • BMI
  • Physical activity (MET hours per week)
  • Smoking status.
Description of Actual Data Sample:

Initial N

51,529 men.

Attrition (Final N)

  • 42,504
  • The follow-up rate as a proportion of the total potential person-years of follow-up was approximately 97% for non-fatal events.

Age

Ranged from 52.5 years to 54.8 years.

Ethnicity

Predominantly white.

Other Relevant Demographics

Participants lived in all 50 US states.

Anthropometrics

Ranged from 24.6 to 26.0.

Location

Participants lived throughout the USA.

Summary of Results:

 Key Findings

  • Men with higher intakes of saturated fat had a higher BMI, a lower level of physical activity, were more likely to smoke cigarettes and were less likely to have hypercholesterolemia
  • A higher intake of saturated fat was associated with lower intakes of alcohol, cereal fiber and magnesium
  • Similar associations were observed for intake of oleic acid, trans-fat and total fat
  • High intakes of long-chain n-3 fatty acids were associated with a healthier lifestyle
  • Associations of fat and meat intake with the risk of developing diabetes were attenuated when adjusted for age, energy intake, magnesium and cereal fiber intake
  • Intakes of total fat (RR for extreme quintiles, 1.27; 95% CI 1.04-1.55; P for trend, 0.02) and saturated fat (1.34; 1.09-1.66; P for trend, 0.01) remained significantly associated with risk of type 2 diabetes after the previous adjustments, but these associations disappeared after further adjustment for BMI
  • No association with risk of type 2 diabetes was observed for animal fat (RR, 1.12; 95% CI, 0.91-1.38; P for trend, 0.22), vegetable fat (0.89; 0.74-1.06; P for trend, 0.08), cholesterol (1.12; 0.92-1.35; P for trend, 0.11) and the ratio of n-3 to n-6 polyunsaturated fat (1.10; 0.92-1.31; P for trend, 0.73) after multivariate adjustment
  • Greater intake of linoleic acid was significantly associated with a lower risk of diabetes among men younger than 65 years (RR, 0.74; 95% CI, 0.60-0.92 for highest vs. lowest quintile; P for trend, 0.01) and among non-overweight men (0.53; 0.33-0.85; P for trend, 0.006)
  • The interactions terms for age and linoleic acid intake (P=0.03) and for BMI and linoleic acid intake (P=0.05) were statistically significant
  • In 1986, 19% of total fat was from unprocessed red meat, 7% from poultry and 5% from processed meat
  • After adjustment for risk factors and intake of cereal fiber and magnesium, men who consumed processed meat at least five times a week had a RR for type 2 diabetes of 1.46 (95% CI, 1.14-1.86; P for trend, <0.0001), as compared with men who consumed processed meats less than once a month
  • In a model with continuous variables, the RR for a one-serving-per-day higher intake of processed meat was RR 1.34 (95% CI, 1.17-1.53)
  • Consumption of unprocessed red meat (RR, 1.05; 95% CI, 0.85-1.30 for highest vs. lowest quintile) and of poultry (1.12; 0.95-1.32) was not substantially associated with risk for type 2 diabetes
  • Only consumption of the three processed meat items and hamburgers (RR, 1.27; 95% CI, 0.99-1.62 for at least two weeks vs. less than one month) was appreciable associated with diabetes risk.

Other Findings

  • Intakes of linoleic acid, trans-fat, alpha-linolenic acid and long-chain n-3 fat were not appreciably associated with risk of type 2 diabetes in any of the models
  • The results were similar when fat intakes and covariables were modeled as continuous variables or were modeled simultaneously
  • The associations were essentially the same if only symptomatic (N=810) or only asymptomatic (N=511) cases were studied as an end point
  • Consumption of beef, lamb or pork as a main dish or a mixed dish; chicken or turkey with or without skin; or major non-meat sources of fat (high-fat dairy and nuts) was not substantially associated with risk of type 2 diabetes.
Author Conclusion:
  • Potential limitations as discussed by the authors:
    • Recall bias, bias caused by loss of follow-up, surveillance bias and residual confounding were minimized or ruled out
    • Confounding by health consciousness may create an association between fat intake and BMI; persons who strive to be lean and restrain energy intake because they believe it to be healthy may also consume a lower-fat diet because they have been told that is healthy.
  • Total and saturated fat intake was associated with a higher risk of type 2 diabetes, but these associations were not independent of BMI
  • Higher intakes of linoleic acid may reduce risk of type 2 diabetes, especially among leaner and younger men
  • Frequent consumption of processed meats may increase risk of type 2 diabetes.
Funding Source:
Government: NIH CA-55075; HL-35464
Not-for-profit
FBH partly supported by American Diabetes Association
Other non-profit:
Reviewer Comments:
Quality Criteria Checklist: Primary Research
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) N/A
  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) N/A
 
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? N/A
  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? ???
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? N/A
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) N/A
  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? N/A
  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? N/A
  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? No
  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? No
  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? Yes
  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? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? Yes
  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? Yes
  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? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? N/A
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? Yes
  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? Yes
  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? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes