Article Figures & Data
Figures
- Figure 1a
Structural equation model predicting physical activity from CADA factors.
CADA = capability assessment for diet and activity; ε = correlated error
Note: Activity resources and activity conversion are scales from CADA instrument. Activity intentions is defined as the number of days the respondent intends to get physical activity in next week.
Moderate/vigorous activity minutes = sum of moderate+vigorous activity minutes as measured by the International Physical Activity Questionnaire.
n = 717
aP <.05
bP <.01
cP = .001
Model fit: Overall R2: 0.208. The model is just identified, so other fit statistics could not be calculated.
- Figure 1b
Structural equation model predicting diet quality from CADA factors.
CADA = capability assessment for diet and activity; STC = Starting the Conversation diet instrument; ε =correlated error
Note: Diet resources and diet conversion are scales from CADA instrument. Diet intentions is defined as the number of days the respondent intends to a eat healthy diet in next week.
n = 181
aP <.05
bP <.01
cP <.001
dP >.05
Model fit: Likelihood ratio for model vs saturated: χ2(10) = 10.74; P = .38.
Root mean square error of approximation: 0.020 CI (0.000-0.085)
Comparative Fit Index: 0.994
Overall R2: 0.130
Tables
- Table 1
Descriptive Statistics and Confirmatory Factor Analysis Factor Loadings for CADA Variables
Higher Order Factor First Order Factor Items No. Mean SD Factor Loadings Diet resources Diet opportunity Easy to shop for food 744 4.01 0.999 0.502 Can afford fresh fruit and vegetables 703 3.87 1.059 0.748 Can afford lean meat or fish 736 3.68 1.143 0.726 Fruit and vegetables high quality 739 3.82 0.928 0.380 Too expensive to buy groceries over entire month 741 2.94 1.343 0.586 Diet conversionfactors Diet barriers (higher order factor loading = 0.54) Illness gets in way of cooking meals 737 3.74 1.190 0.637 Too tired to cook my own meals 734 3.33 1.201 0.557 Feeling depressed keeps me from food shopping 737 3.54 1.196 0.645 Diet knowledge (higher order factor loading = 0.70) Know how to eat healthy foods 741 4.14 0.762 0.597 Know how to choose healthy meal at restaurant 739 3.85 0.924 0.655 Know where to shop for healthy food 712 3.96 0.900 0.670 Diet time (higher order factor loading = 0.44) Taking care of family leaves little time to cook 719 3.60 1.049 0.754 Schedule leaves little time for food shopping 728 3.56 1.111 0.759 Schedule gives me little time to cook 742 3.75 0.989 0.454 Physical activity resources Physical activity convenience (higher order factor loading = 0.92) Nearby places for outdoor physical activity 735 4.19 0.936 0.686 Places open when I want indoor activity 741 3.67 1.112 0.678 Can afford to join a gym 737 2.89 1.372 0.498 Neighborhood (higher order factor loading = 0.91) Easy to walk places in neighborhood 741 3.76 1.225 0.654 Places I can be active w/o needing to pay 744 3.66 1.130 0.690 Often see people walking in my neighborhood 744 3.89 1.116 0.584 People generally feel safe in my neighborhood 743 3.75 1.036 0.602 Neighborhood well lighted for evening activities 743 3.15 1.275 0.599 Physical activity conversion factors Physical activity barriers Illness gets in way of being active 737 3.14 1.363 0.932 Health limits my activities 741 3.17 1.381 0.637 Feeling depressed keeps me from being physically active 739 3.17 1.320 0.517 CADA = Capability Assessment for Diet and Activity.
Characteristic Value Sample size, No. 746 Mean age (range), y 44.4 (18–75) Female, % 67.7 Race/ethnicity, % Hispanic 54.3 Non-Hispanic white 30.6 Non-Hispanic black 11.5 Other 3.6 Survey language, % English 92.2 Spanish 7.8 Educational attainment, % 0–8 years 6.1 9–11 years 10.0 High school graduate/GED 25.0 Any college 58.9 Monthly income range, % <$1000 35.4 $1,000–1,499 14.4 $1500–1999 13.5 $2000–2499 9.0 $2500–3499 8.6 $3500–4999 9.3 ≥$5000 9.9 BMI > 25 kg/m2, % 78.1 Meeting CDC physical activity recommendations (150 minutes/week), % 54.8 Starting the Conversation-Diet score, mean (range) 15.2 (7–21) BMI = body mass index; CDC = Centers for Disease Control and Prevention; GED = general equivalency diploma.
- Table 3
Structural Equation Model Estimates of Dietary and Activity Resources and Conversion Factors Predicting BMI
Predictor Regression Coefficient P Value Standardized Coefficient Model R2 w/Covariates Dietary model 0.143 Diet conversion −0.390 .014 −0.493 Diet resource 1.592 .296 0.201 Diet intention −0.282 .053 −0.072 Age 0.044 .010 0.094 Non-Hispanic black 2.258 .025 0.089 Hispanic −0.338 .603 −0.021 Non-Hispanic other −3.216 .047 −0.074 Monthly income 0.080 .584 0.021 Physical activity model 0.113 Activity conversion −1.215 <.001 −0.190 Activity resource −1.585 <.001 −0.200 Activity intention −0.192 .194 −0.049 Age 0.020 .256 0.042 Non-Hispanic black 2.536 .011 0.100 Hispanic 0.168 .794 0.011 Non-Hispanic Other −3.013 .060 −0.070 Monthly income 0.153 .292 0.041 BMI = body mass index; CFA = confirmatory factor analysis.
Note: Structural equation modeling included factors as specified in CFA measurement model (estimates not displayed here) and structural model as shown in the table. Non-Hispanic white is the reference group for ethnicity.
The Article in Brief
Practical Opportunities for Healthy Diet and Physical Activity: Relationship to Intentions, Behaviors, and Body Mass Index
Robert L. Ferrer , and colleagues
Background Diet and activity choices emerge from what people find feasible to do in their daily lives. When there are few opportunities, people often adjust their expectations downward. This study sets out to a) confirm a method of measuring practical opportunities for healthy diet and physical activity, and b) evaluate the utility of this new tool to understand the contexts for people's health behavior choices.
What This Study Found Practical opportunities for healthy diet and physical activity are measurable and predict behavioral intentions, diet quality, activity minutes and body mass index.
Implications
- These findings underline the need to understand the complexity of people's lives as part of promoting healthy behaviors.
- Assessing opportunities in health behavior management could lead to more effective, efficient and respectful interventions.
Annals Journal Club
Mar/Apr 2016: Individual Goals, Neighborhood Context
The Annals of Family Medicine encourages readers to develop a learning community of those seeking to improve health care and health through enhanced primary care. You can participate by conducting a RADICAL journal club and sharing the results of your discussions in the Annals online discussion for the featured articles. RADICAL is an acronym for Read, Ask, Discuss, Inquire, Collaborate, Act, and Learn. The word radical also indicates the need to engage diverse participants in thinking critically about important issues affecting primary care and then acting on those discussions.1
HOW IT WORKS
In each issue, the Annals selects an article or articles and provides discussion tips and questions. We encourage you to take a RADICAL approach to these materials and to post a summary of your conversation in our online discussion. (Open the article online and click on "TRACK Discussion: Submit a comment.") You can find discussion questions and more information online at: http://www.AnnFamMed.org/site/AJC/.
CURRENT SELECTION
Article for Discussion
Ferrer RL, Burge S, Palmer RF, Cruz I. Practical opportunities for healthy diet and physical activity: relationship to intentions, behaviors, and body-mass index. Ann Fam Med. 2016;14(2):109-116.
Discussion Tips
This article provides an opportunity to raise our gaze from trying to help individuals to make prudent choices in behaviors that affect their health, to consider the contextual factors that affect the practical constraints and opportunities that affect patients' choices.
Discussion Questions
- What question is asked by this study and why does it matter?
- How does this study advance beyond previous research and clinical practice on this topic?
- How does it build on prior work by these authors on this topic?2,3
- How strong is the study design for answering the question?
- To what degree can the findings be accounted for by:
- How patients were selected, excluded, or lost to follow-up?
- How the main variables were measured? (What do you think of the process used to refine the independent variable? Does the range of dependent outcome variables add to the robustness of the findings?)
- Confounding (false attribution of causality because 2 variables discovered to be associated actually are associated with a 3rd factor)?
- Chance?
- How the findings were interpreted?
- What are the main study findings?
- How comparable is the study sample to similar patients in your practice? What is your judgment about the transportability of the findings? (Note that the study was done in a practice-based research network of residency training practices.)
- What contextual factors are important for interpreting the findings?
- How might this study change your practice? Policy? Education? Research?
- Who are the constituencies for the findings, and how might they be engaged in interpreting or using the findings?
- What are the next steps in interpreting or applying the findings?
- What researchable questions remain?
References
- Stange KC, Miller WL, McLellan LA, et al. Annals Journal Club: It's time to get RADICAL. Ann Fam Med. 2006;4(3):196-197 http://annfammed.org/content/4/3/196.full.
- Ferrer RL, Carrasco AV. Capability and clinical success. Ann Fam Med 2010;8 (5):454-460. http://www.annfammed.org/content/8/5/454.full.
- Ferrer RL, Cruz I, Burge S, Bayles B, Castilla MI. Measuring capability for healthy diet and physical activity. Ann Fam Med. 2014;12(1):46-56. http://www.annfammed.org/content/12/1/46.full.
