Factor Analysis of International Cancer Mortality Data and per capita Food Consumption

Howell, Margaret A.

doi:10.1038/bjc.1974.75

Cited by 97 publications

(34 citation statements)

References 7 publications

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“…Note that the beef and " fat " consumption correlations are low (r -' 0.3) in contrast to the high (r 0.8) international correlations (Howell, 1974;Armstrong and Doll, 1975). This discrepancy has been discussed (Enstrom, 1975a).…”

Section: Confounding Variablesmentioning

confidence: 95%

Colorectal cancer and beer drinking

Enstrom¹

1977

Br J Cancer

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Section: Confounding Variablesmentioning

confidence: 95%

Colorectal cancer and beer drinking

Enstrom¹

1977

Br J Cancer

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“…Although potential dietary risk factors for high-fat and low-fibre foods have shown associations with prostate carcinoma in Western countries (Howell, 1974;Giovannucci et al, 1995;Whittemore et al, 1995;Parkin et al, 1999;Bostwick et al, 2004), their role remains unclear for Asian men. Investigation of the disease in populations with lower incidence may provide further insight into its aetiology with relation to diet, particularly as the food consumed in Taiwan is different from that in Western countries.…”

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confidence: 99%

Diet, vegetarian food and prostate carcinoma among men in Taiwan

Lin

et al. 2005

Br J Cancer

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In a case -control study in a veterans hospital in Taiwan, we compared 237 histology-confirmed prostate carcinoma cases with 481 controls, frequency matched by age, for their consumption of vegetarian food, namely soybean products, rice, wheat protein and other vegetables. The multivariable logistic regression analysis showed a significant association with such food (odds ratio 07, 3.30). Stratified analysis also showed that the consumption of fish/shellfish had an adverse association for men with higher BMI. This study suggests that the intake of the low fat local vegetarian food has a protective effect against prostate carcinoma for thin men in this study population.

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“…The first example we found of this was an international 'ecological' analysis of per capita food consumption and cancer mortality data, relating particular cancers to particular food choices=factors. 13 Factor analysis has been described as 'a multivariable method intended to explain relationships among several difficult-to-interpret, correlated variables in terms of a few conceptually meaningful, and relatively independent factors'. 14 The theory is that habitual intake of indicator foods (eg a subset of the dietary variables included in a food frequency questionnaire (FFQ)) is explained, to some extent, by a number of latent (ie not directly measurable) variables that influence the food intake.…”

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confidence: 99%

Food intake patterns and body mass index in observational studies

et al. 2001

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OBJECTIVE:To review studies of patterns of food intake, as assessed by diet index, factor analysis or cluster analysis, and their associations with body mass index or obesity (BMI=Ob). DESIGN: Systematic literature review MEDLINE search with crosscheck of references. STUDIES: Thirty observational studies relating food intake patterns to anthropometric information were identified and reviewed. Food intake patterns were defined using a diet index, factor or cluster analysis in 12, nine and nine studies, respectively. Measures of body mass were made concurrently with the diet assessment in all studies, and only in a few cases were the primary outcomes related to BMI=Ob. RESULTS: The food intake patterns identified could, in most factor or cluster analysis studies, be categorised as: (a) meat, fatty, sweet or energy dense foods; (b) vegetables, fruit, whole grain and low-fat foods; or (c) by high alcohol consumption. The diet indexes were designed to capture a high diversity and=or food combinations matching the recommendations. The relationships with BMI=Ob were inconsistent -ten studies found that intake patterns, which we categorised as fatty, sweet or energy dense were positively associated with BMI=Ob, while similar patterns in four other studies were negatively associated with BMI. The significant associations between diet index score and BMI=Ob were consistently negative, while the associations between factor scores or cluster membership and BMI=Ob were less clear in terms of food intake pattern. Men and women had similar food intake patterns, but food intake patterns were less often positively associated with BMI=Ob in women. In 11 studies, there were no significant associations between food intake pattern and BMI=Ob. CONCLUSION: This review showed that no consistent associations could be identified between BMI or Ob and food intake patterns, derived from diet index, factor analysis or cluster analysis. However, the heterogeneity of food intake patterns identified by such analyses and the lack of gold standards for the application of these techniques hampers consistent analysis of a relation between food intake patterns and health.

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Factor Analysis of International Cancer Mortality Data and per capita Food Consumption

Cited by 97 publications

References 7 publications

Colorectal cancer and beer drinking

Colorectal cancer and beer drinking

Diet, vegetarian food and prostate carcinoma among men in Taiwan

Food intake patterns and body mass index in observational studies

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