Four dietary patterns identified among Ghanaian people living in New York City - Principal Component Analysis

Sep 30, 2026

Specific dietary patterns can guide culturally tailored interventions to reduce chronic disease risk. The study administered the culturally adapted Ghanaian food frequency questionnaire (GUSI-FFQ) to Ghanaian residents in New York City and applied principal component analysis (PCA) to derive dietary patterns. A convenience sample of 96 Ghanaian immigrants completed the survey, with weekly intake across 26 food groups analyzed. Four patterns explained 40.3% of total variance, while certain items showed high uniqueness, indicating greater variation beyond the extracted patterns.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages1

Reading Time3 min

AccessFree to download

Aims

Methods

Participants and dietary assessment

PCA and parallel analysis

Results

Conclusions

2nd World Congress on Migration, Ethnicity, Race & Health Abstract Book vi121 Specific dietary patterns can inform culturally tailored interventions for chronic disease prevention. Funding Sources: Professional Staff Congress, City University of New York Grant TRADA-53-281, and Tow Faculty Research and Creativity Grant, 2023. Abstract citation ID: ckaf180.334 235 Four dietary patterns identified among Ghanaian people living in New York City: a principal component analysis Fiona Milton1, Sumera S. Subzwari2, Faustine Williams1, Luyue Zhang3, Margrethe Horlyck-Romanovsky4 1Department of Health and Nutrition Sciences, Brooklyn College, City University of New York, New York, United States 2Teachers College, Columbia University, New York, United States 3Department of Agriculture, Nutrition and Food Systems, University of New Hampshire, Durham, United States 4National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, United States EP1.4, e-Poster Terminal 1, September 4, 2025, 11:35-13:00 Aims: To a) administer a culturally adapted Ghanaian food frequency questionnaire (GUSI-FFQ) among Ghanaian people in New York City (NYC), and b) identify dietary patterns using principal component analysis (PCA) . Methods: A convenience sample of Ghanaian immigrants (n ¼ 96) completed the GUSI-FFQ. Intake of 26 food groups was assessed based on weekly consumption. PCA was applied to identify dietary patterns. Parallel analysis was conducted to determine the number of patterns to retain, with component loadings above 0.30 considered significant. Uniqueness scores assessed the proportion of variance unexplained by the extracted patterns. Results: Four major dietary patterns were identified, explaining 40.3% of total variance in dietary intake. Pattern 1 (12.1% variance) was characterized by a high intake of cereals/grains, fruits, dairy, and cultural beverages. Pattern 2 (11.8%) was high in fast food, meat, dairy, and sweet snacks. Pattern 3 (8.3%) was associated with legumes, fish, and fresh juice. Pattern 4 (8.1%) included rice, red/ orange vegetables, and unsweetened tea. Among the key food groups, uniqueness scores were lowest for legumes (0.331), fats/oil (0.445), dairy products (0.480), and fish/seafood (0.484), indicating that these foods were well captured within the identified patterns. Conversely, unsweetened/sweetened coffee, plantains/starch, nuts/ seeds, and nutritional shakes had high uniqueness scores (>0.7), suggesting that their consumption varied more and was not strongly associated with any one pattern. Conclusions: While additional dietary and lifestyle factors may contribute to eating behavior, these findings offer insight into differences in dietary patterns and potential variations of dietary acculturation among Ghanaian immigrants living in the US.

FAQs

What was the main goal of the study?

To administer a culturally adapted Ghanaian food frequency questionnaire among Ghanaian people in New York City and to identify dietary patterns using principal component analysis (PCA).

How were dietary patterns identified?

A convenience sample of 96 Ghanaian immigrants completed the GUSI-FFQ covering 26 food groups consumed weekly. PCA was used to extract patterns, with parallel analysis to decide how many to retain and significance set using component loadings above 0.30.

What dietary patterns were found and how much variance did they explain?

Four major patterns were identified, explaining 40.3% of total variance. Pattern 1 emphasized cereals/grains, fruits, dairy, and cultural beverages; Pattern 2 emphasized fast food, meat, dairy, and sweet snacks; Pattern 3 emphasized legumes, fish, and fresh juice; Pattern 4 included rice, red/orange vegetables, and unsweetened tea.

Sep 30, 2026

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