Worksheet: Deshmukh-Taskar P, O'Neil C et al, 2009

Citation:
Deshmukh-Taskar PR, O'Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: The Bogalusa Heart Study. Public Health Nutrition. 2009; 12 (12): 2,493-2,503. PubMed ID: 19744354

Study Design:
Cross-Sectional Study

Class:
D - Click here for explanation of classification scheme.

Quality Rating:
POSITIVE: See Quality Criteria Checklist below.

Research Purpose:
To examine the association between dietary patterns and risk for metabolic syndrome, and to identify the differences in dietary patterns by socio-economic, demographic, and lifestyle factors.

Inclusion Criteria:
Subjects were between the ages of 19 and 39 years old, from a semi-rural community 70 miles north of New Orleans, Louisiana.

Exclusion Criteria:
Chose not to participate Did not meet inclusion criteria Had incomplete data.

Description of Study Protocol:

Recruitment

Recruitment of subjects was not specified, but all subjects were located in a semi-rural community north of New Orleans.

Design

A cross-sectional study design was used. Dietary intake from food frequency questionnaire (FFQ) was evaluated along with anthropometric and biochemical parameters.

Blinding used

Implied with measurements

Intervention

Not applicable

Statistical Analysis

Factor analysis was used to help identify the DP. Eigenvalues, the Scree test, and interpretability of derived factors were used to derive the DP.
Linear regression examined the association between DP and MetS risk factors
Analysis of covariance with Tukey-Kramer's post-hoc test was used to examine 1) ethnicity x gender differences in the occurrence of metabolic risk factors, and 2) differences in mean servings of foods from DP by socioeconomic status (SES)
Covariates used for each analysis varied and included age, energy intake, gender, ethnicity, ethnicity x gender, SES, marital status, physical activity, smoking, alcohol consumption and BMI
Statistical significance was set at the P≤0.05 level.

Data Collection Summary:

Timing of Measurements

Data for this study was collected during a follow-up post-high-school cross-sectional survey conducted in 1995-1996.

Dependent Variables

Anthropometrics were measured in duplicate and included: Height, weight, BMI was calculated and used to classify participants into normal or overweight/obese; waist circumference, hip circumference, and waist to hip ratio was calculated, triceps skin fold was measured.
Laboratory measurements included: Plasma glucose, indices of insulin sensitivity were calculated, insulin resistance (HOMA-IR), serum total cholesterol and TAG concentrations, LDL, and HDL
Metabolic syndrome (MetS) was classified by the ATP III criteria. Subjects were considered to have MetS if they had at least three of the following risk factors: i) abdominal obesity (waist circumference ≥102cm in males and ≥88cm in females); ii) high serum TAG (≥150 mg/dL); iii) low serum HDL-C (<40mg/dL in males, or <50mg/dL in females); iv) high blood pressure (≥130 or ≥85mmHg or those taking medications for hypertension); and v) high fasting plasma glucose (≥100mg/dL or those taking medications).

Independent Variables

Dietary pattern (DP) as measured by the youth/adolescent questionnaire (YAQ) for collecting data on food frequency.

Control Variables

Demographic information collected included: Age, gender, ethnicity, smoking status, marital status and alcohol intake
Socioeconomic status (SES) was determined using income and education levels
Physical activity outside of work was measured with a self-reported subjective rating.

Description of Actual Data Sample:

Initial N: 1,089 subjects were initially included in the Bogalusa Heart Study
Attrition (final N): 995 subjects were included in this section of the study. Those excluded were due to lack of complete data collection.
Age: Mean age was 30 years old (SD 5.1 years), with age ranges from 19 to 39 years
Ethnicity: 80% white and 20% black
Other relevant demographics: The final sample was 61% female, 39% male
Anthropometrics:
Location: The study took place in Bogalusa, LA.

Summary of Results:

Key Findings

Factor analysis found two specific dietary patterns (DP):

WDP (Western Dietary Pattern): Refined grains, French fries, high fat dairy, fried foods, dishes with cheese, red meats, processed meats, eggs, snacks, sweets and desserts, sweetened beverages and condiments
PDP (Prudent Dietary Pattern): Whole grains, legumes, vegetables, tomatoes, fruits, 100% fruit juices, low fat dairy, poultry, clear soups, and low fat salad dressings
The dietary pattern explained 31% of the dietary intake variance.

Metabolic profiles of young adults:

White females had the lowest energy intake, WC, waist to hip ratio, and SBP
White males had the highest waist circumference and waist to hip ratio, lowest serum HDL.
Black males had the highest SBP
Overall prevalence of MetS in young adults was 12.2% with 14.9% in males vs. 10.4% in females (P=0.03)
Based on ethnicity, prevalence of MetS was 12.8% in whites vs. 9.6% in blacks (P=0.22), thus no ethnic differences in the occurrence of MetS were noted
Black males did have a higher occurrence of MetS than black females (15.4% vs. 5.8%; P=0.03).

Covariate-adjusted associations between dietary patterns and components of MetS:

Waist circumference (P=0.02), triceps skinfold (P=0.01), plasma insulin (P=0.03) and the occurrence of MetS (P=0.03) were all inversely associated with PDP
Insulin sensitivity was positively associated with PDP (P<0.0005)
Serum TAG was negatively associated with both PDP and WDP
After adjusting for BMI, serum HDL was inversely associated with WDP
The overall occurrence of MetS did not differ between the two dietary patterns.

Covariate-adjusted demographic, socio-economic status and lifestyle differences in dietary patterns:

Young adults consumed more servings from the WDP than the PDP [mean 9.8 (SD 0.2) vs. 4.5 (0.2); P<0.001]
Blacks consumed more servings from the WDP than whites
Females consumed more servings from the PDP than males
Older young adults consumed more servings from the PDP than their younger age group.

Author Conclusion:
While more studies are warranted to analyze the impact of dietary patterns on incidence of MetS, a balanced dietary pattern may be helpful in preventing MetS in this sample of young adults.

Funding Source:

Government:	USDA, NHLBI
University/Hospital:	Baylor College of Medicine

Reviewer Comments:

Limitations noted by authors:

Sample may not be representative of the population as a whole
Within this population, the sample may have under-represented the black community
The cross-sectional study design cannot allow for causal inferences to be made
Youth/Adolescent Questionnaire (YAQ) was used for young adults; in comparison with a 24-hour dietary recall, the YAQ has been more helpful characterizing snack food consumption among young adults
Dietary data were collected over 10 years ago.

Strengths discussed included the use of factor analysis which lended support to other longitudinal and cross-sectional studies.

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?	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?	???
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 used? (Concurrent preferred over historical controls.)	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 or cross-sectional 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. Criterion may not be applicable in some cross-sectional studies.)	Yes
	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?	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?		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.)	Yes
	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?		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?	N/A
	6.4.	Was the amount of exposure and, if relevant, subject/patient compliance measured?	N/A
	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?	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?	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