Abstract

The Diet Quality Index (DQI) was developed to measure overall dietary patterns and to predict chronic disease risk. This study examined associations between DQI and short-term all-cause, all-circulatory-disease, and all-cancer mortality in the American Cancer Society Cancer Prevention Study II Nutrition Cohort, a cohort of US adults aged 50–79 years enrolled in a prospective study. After 4 years of follow-up (1992–1996), there were 869 deaths among 63,109 women and 1,736 deaths among 52,724 men. All study participants reported being disease free at baseline in 1992–1993. In age-adjusted Cox models, a higher DQI, which was indicative of a poorer quality diet, was positively related to all-cause and all-circulatory-disease mortality rates in both women and men and to cancer mortality in men only. However, in fully adjusted Cox models, only circulatory disease mortality was clearly positively related to DQI and only in women (medium-low-quality diet vs. highest-quality diet: rate ratio = 1.86, 95% confidence interval: 1.19, 2.89). Although trend tests indicated significant positive relations between DQI and all-cause mortality, effects were small (rate ratios ≤ 1.31), and confidence intervals were wide, generally including 1.0. DQI was unrelated to cancer mortality. As currently constructed, the DQI may have limited ability to predict mortality.

Received for publication July 13, 2001; accepted for publication January 6, 2003.

Few studies have examined risk of chronic disease in relation to the overall quality of a study population’s diet (18). In most studies, a single nutrient or food group has been examined. Studies have found evidence that certain dietary components (e.g., vegetables or saturated fat) may reduce or increase the risk of chronic diseases (e.g., coronary heart disease or cancer) (913). Data from these studies have been used to produce guidelines (1417) for overall dietary intake. Relations between risk of chronic disease and overall dietary intake require further investigation, especially for those diets that are in accord with recommended guidelines.

Only a few indexes of diet quality have been examined for associations with measures of health status. In each of 10 such studies, the index of diet quality predicted all-cause mortality in at least one gender group (1, 68, 1824). The dietary diversity score created by Kant et al. (22, 23) was associated with cardiovascular disease mortality in men and women and cancer mortality in men only. Kant’s Recommended Food Score (24) was associated with reduced cardiovascular disease and cancer mortality in women. Two recent cohort studies examined incidence of cardiovascular disease and cancer by Healthy Eating Index score (25, 26). Diet quality had a moderate inverse association with cardiovascular disease in men and was weakly associated with cardiovascular disease in women; it was not associated with cancer in either study.

The Diet Quality Index (DQI) was developed by Patterson et al. (5) in 1994 to measure overall dietary intake patterns and to use these patterns to predict chronic disease risk. As the DQI was constructed, a higher DQI was indicative of a poorer-quality diet and was therefore expected to be positively associated with increased mortality. For the current study, we assumed that a low-quality diet is positively associated with chronic disease risk. This assumption was based on the weight of evidence from studies of associations between individual foods and nutrients and chronic disease risk (913). The ability of the DQI to predict chronic disease morbidity or mortality has not yet been determined. The objective of this study was to investigate whether the DQI is positively associated with short-term all-cause, all-circulatory-disease, and all-cancer mortality while controlling for other known risk factors for mortality.

MATERIALS AND METHODS

Study population

The American Cancer Society Cancer Prevention Study II (CPS II) began in 1982, when approximately 1.2 million friends, neighbors, or relatives of American Cancer Society volunteers nationwide were enrolled in a prospective cohort study for examination of characteristics related to cancer and chronic disease mortality. This original cohort has been described in detail elsewhere (27). In 1992–1993, a self-administered questionnaire was mailed to a subgroup of women and men who were original CPS II participants and who resided in 21 states with population-based cancer registries. The questionnaire updated exposure information and included a 68-item food frequency questionnaire based on the brief 60-item Health Habits and History Questionnaire developed by Block et al. (28) at the National Cancer Institute.

The CPS II Nutrition Cohort included 184,193 women and men. For the current analyses, we limited the Nutrition Cohort to White and African-American women and men aged 50–79 years, because there were very few deaths among persons in other race and age strata. We excluded participants who reported a history of cancer, heart attack, or stroke on the 1992–1993 survey or who left more than 15 percent of the items on the food frequency questionnaire blank (table 1).

Diet Quality Index

The DQI is made up of eight components of diet that are presumed to be associated with health and disease risk (table 2). Scores for these eight components were calculated directly from the food frequency questionnaire or from Dietary Analysis Personal Computer System estimates (29, 30). If serving size for an item on the food frequency questionnaire was left blank but a frequency was given, a medium serving size was assumed. If serving size and frequency were both blank, we assumed that the item was never consumed. There were an average of 1.5 missing items per food frequency questionnaire. The scores for the individual components were summed for determination of each participant’s overall DQI score, which ranged from 0 to 16; a lower DQI score indicated a higher-quality diet. For the current analyses, DQI score was divided into five categories (table 3).

Guidelines for calcium intake have comprised the only significant change in the DQI since its development in 1994. In 1998, new Dietary Reference Intake guidelines were published (31) that specified 1,200 mg per day for women and men aged ≥51 years, with calcium intake being determined from both dietary and supplemental intakes. These new guidelines were used in the present study.

Mortality follow-up

Mortality follow-up for the cohort was complete through December 1996. Mortality and cause-of-death codes were determined through linkage with the National Death Index (32), and deaths were coded according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) (33). Between the time of the cohort’s baseline survey in 1992–1993 and December 1996, 869 women (1.4 percent) and 1,736 men (3.3 percent) died (table 4). The mortality analyses were not stratified by race, because there were very few deaths among African Americans.

Statistical analysis

Cox proportional hazards modeling (34) was used to determine whether the DQI was significantly positively associated with short-term all-cause, all-circulatory-disease (ICD-9-CM codes 390–459), and all-cancer (ICD-9-CM codes 140–195 and 199–208) mortality. We compared mortality rates for people with low-, medium-low-, medium-, and medium-high-quality diets to those for people with a high-quality diet (the reference group). We also used Cox models to determine whether each component of the DQI was significantly positively associated with short-term all-cause, all-circulatory-disease, and all-cancer mortality, in order to better understand the strengths and weaknesses of the DQI. We compared mortality rates for people with a score of 2 or 1 to those for people with a score of zero. The PHREG procedure in the Statistical Analysis System, version 6.12 (35), was used for the Cox proportional hazards analyses.

We adjusted for age in all Cox models in these analyses by including single year of age at the baseline survey in the strata statement of the PHREG model. In multivariate-adjusted models, data were controlled for the following factors: race (White, African American), occupation (white-collar, blue-collar, homemaker, unknown), education (less than high school graduate, high school graduate, some college, college graduate, graduate school, unknown), smoking status (never, former smoker of <10 pack-years, former smoker of ≥10 pack-years who had quit smoking ≥10 years previously, former smoker of ≥10 pack-years who had quit smoking <10 years previously, current smoker, unknown), physical activity (metabolic equivalent hours per week: 0, 1–3.5, >3.5–14, >14–28, >28, unknown), alcohol intake (never, 1–3 drinks per week, >3 drinks per week to 1 drink per day, >1–2 drinks per day, >2 drinks per day, unknown), use of dietary supplements (never or <1 pill per week, 1–6 pills per week, ≥1 pill per day), use of aspirin (never or irregular use, regular use of <1 pill per day, regular use of 1 pill per day, regular use of >1 pill per day), and, for women only, mammography history (never or >3 years before, 1–3 years before, <1 year before, unknown) and hormone replacement therapy (ever or never). For women, level of physical activity and dietary supplement use were the most important correlates of diet quality. For men, level of physical activity and body mass index (weight (kg)/height (m)2) were the most important correlates of diet quality (Seymour, unpublished manuscript). We conducted additional analyses adjusting for the factors listed above and other factors (body mass index, high blood pressure, diabetes mellitus, elevated cholesterol, emphysema, and family history of cancer). These factors may have been on the causal pathway but they were also potential confounders of associations between diet quality and chronic disease risk, because they are only partly a result of a poor-quality diet and are influenced by other risk factors for chronic disease mortality. Inclusion of the additional covariates in the models had no effect on the findings except to reduce the weak positive association between DQI and all-cause mortality in men (data not shown). We conducted a trend test using the DQI as a continuous variable in the Cox models. We performed a diagnostic test to verify that the independent variables used in the multivariate survival models were not collinear (36).

Graphic techniques and time-extended Cox models were used to check the proportional hazards assumption for this study (37). No violations of this assumption were apparent. Multiplicative interaction terms between diet quality and each of the demographic and health-related variables were added to separate multivariate models for examination of possible interactions between diet quality and each variable. The likelihood ratio test (38) was used to determine whether interaction terms for each variable were statistically significant at the p ≤ 0.05 level. Few of the chronic disease risk factors significantly modified the relations between diet quality and mortality (data not shown). When statistically significant interactions did occur, they were fewer than would be expected by chance alone, and they lacked a discernible pattern of effect modification for any of the characteristics. Thus, there did not appear to be any strong modifiers of the relation between diet quality and all-cause, all-circulatory-disease, or all-cancer mortality.

RESULTS

Coronary heart disease comprised almost half of all circulatory disease deaths occurring in women and more than half of those occurring in men (table 4). Lung cancer was by far the most common cause of cancer death, followed by colon, pancreatic, breast, and ovarian cancer in women and pancreatic, colon, brain, esophageal, and prostate cancer in men (table 4). Many of the cancer deaths were from cancers with a low probability of survival (e.g., lung, pancreas) because of the short follow-up period used in this study.

In models that adjusted for age only, DQI was positively associated with all-cause and all-circulatory-disease mortality in both women and men and with all-cancer mortality in men (tables 5 and 6). The all-cause mortality rate ratio for women with the lowest-quality diet as compared with the highest-quality diet was 1.86 (95 percent confidence interval (CI): 1.28, 2.70), and for men it was 1.78 (95 percent CI: 1.43, 2.22). For circulatory disease, positive associations were found for medium, medium-low, and low DQI (versus high DQI) in women and for medium-low and low DQI in men. For cancer, a rate ratio of 1.49 (95 percent CI: 1.04, 2.14) was found for men with the lowest-quality diet.

These significant positive associations were greatly attenuated when additional covariates were added. In multivariate-adjusted models, there was a slightly significant increase in all-cause mortality (rate ratio = 1.31, 95 percent CI: 1.04, 1.65) and all-circulatory-disease mortality (rate ratio = 1.86, 95 percent CI: 1.19, 2.89) when a medium-low-quality diet was compared with a high-quality diet for women. The p value for trend was significant for both all-cause and all-circulatory-disease mortality but not for all-cancer mortality, where again there were no significant positive associations for women. For men, there was a weak but nonsignificant positive association between a low-quality diet and all-cause mortality (rate ratio = 1.19, 95 percent CI: 0.94, 1.49). The p value for the trend test was significant (p = 0.04). There was no association between diet quality and all-circulatory-disease or all-cancer mortality in men.

In multivariate-adjusted models examining individual components of the DQI (data not shown), the cholesterol component was positively associated with all-cause, all-circulatory-disease, and all-cancer mortality for both women and men, indicating that a higher intake of cholesterol was positively associated with increased mortality. For women only, the fruit and vegetable component was positively associated with all-circulatory-disease mortality and the calcium component was positively associated with all-cause mortality, indicating that lower intakes of fruits and vegetables and calcium were positively associated with mortality.

DISCUSSION

In this large prospective study, in models adjusted for age only, DQI was positively associated with all-cause and all-circulatory-disease mortality in women and men as well as all-cancer mortality in men, indicating that a poorer-quality diet was positively associated with increased mortality. However, after a number of potential confounders of diet quality–disease associations were taken into account, there were no significant positive associations between DQI and mortality for men. Only a nonsignificant positive association between diet quality and all-cause mortality remained. For women, positive associations between diet quality and all-cause mortality and all-circulatory-disease mortality remained.

Several previous studies of dietary indexes found small but significant inverse associations between high-quality diets and all-cause mortality (1, 68, 24). However, in each of these studies, only a few potentially confounding factors were included in multivariate models, and it is possible that the associations would have been greatly attenuated if additional potentially confounding factors had been taken into account. The recent examinations of the Healthy Eating Index (25, 26) were more comparable to the present work, although they examined incident disease rather than mortality. Data for many potentially confounding factors were included in multivariate-adjusted models as part of the evaluation of the Healthy Eating Index. No association was found between a high-quality diet, as measured by the Healthy Eating Index, and cancer, and only a weak, inverse relation was seen with cardiovascular disease.

The findings from examinations of the Healthy Eating Index and results of the current study suggest that recent dietary guidelines, as measured by dietary indexes, are not associated with cancer occurrence or mortality. Present dietary guidelines may not adequately describe intake that is associated with reduced risk of chronic disease. In this study, only the cholesterol component of the DQI was positively related to mortality in men; the cholesterol, fruits-and-vegetables, and calcium components were positively related to mortality in women. The majority of cohort participants met the dietary recommendation for cholesterol intake (92 percent of women and 74 percent of men). The cholesterol component may be capturing and acting as a proxy for a truly low-quality diet. It may be useful to develop an index of diet quality by first evaluating the individual components of the index for their association with morbidity and mortality. This process would identify the appropriate components to include in the final index.

Several explanations are possible regarding the general lack of a positive association between the DQI and risk of death in this cohort. The DQI may not separate dietary intake patterns into truly high-quality or low-quality dietary intakes. Total fat intake comprises a mixture of saturated and unsaturated (both mono- and polyunsaturated) fats. Studies have observed protective effects of unsaturated fats against certain chronic diseases, such as breast cancer and coronary heart disease (18, 3941). In addition, some of the components of the DQI may need to be more narrowly defined. Intake of fruits and vegetables has been associated with a lower risk of cardiovascular disease as well as a lower risk of many diet-related cancers, but fruits and vegetables vary in terms of how protective they are (9, 10). Dark green and deep yellow fruits and vegetables, citrus fruits, tomatoes, and cruciferous vegetables may be more highly associated with reduced risk of many chronic diseases than other fruits and vegetables such as iceberg lettuce and potatoes (9, 10). This distinction is not recognized in the DQI.

Some components of the DQI, such as protein, may have inappropriate scoring. A high protein intake does not appear to be positively associated with risk of circulatory disease or cancer (42, 43), but a low protein intake has been related to increased risk of chronic disease (44). The DQI’s current scoring favors a low protein intake, and thus it “rewards” people for activity that is not beneficial to diet quality. When we examined the protein component alone, higher consumption of protein among women was inversely related to all-cause and all-cancer mortality. This finding contradicts Patterson et al.’s (5) assumption that a lower protein intake, within the range of US consumption, is part of a high-quality diet. For men, high protein consumption—more than 150 percent of the Recommended Dietary Allowance (45)—was positively associated with all-cause and all-circulatory-disease mortality, but moderate protein consumption was not. Moderate protein intake, 100–150 percent of the Recommended Dietary Allowance, may be a more appropriate level for high-quality diets. Finally, some foods or nutrients that may be important in a high-quality diet were not included in the index. For example, fish intake and nut consumption have both been associated with lower risk of chronic disease (4649), but these dietary components were not measured by the DQI.

The current study had several limitations. Dietary data came from a 68-item food frequency questionnaire that was self-administered by Nutrition Cohort participants in 1992–1993. The original DQI, however, was constructed using a 2-day diet record and one 24-hour dietary recall. A food frequency questionnaire may not be able to capture enough detail on dietary intake to separate participants according to dietary quality. However, a recent study by Newby et al. (50) found that DQI assessed using two different food frequency questionnaires was reasonably valid (r = 0.65 and r = 0.61) when compared with DQI assessed using 2 weeks of diet records. Newby et al.’s study supports the use of a food frequency questionnaire to rank-order a population according to quality of dietary intake. Furthermore, the food frequency questionnaire used for the CPS II Nutrition Survey was found to be reasonably valid when assessed for validity with four 24-hour dietary recalls in a subset of the Nutrition Cohort. Correlation coefficients for the eight components of the DQI ranged from 0.33 to 0.66 for women, with four components above 0.6. For men, they ranged from 0.29 to 0.75, with five components above 0.57 (51). However, misclassification of diet quality from food frequency questionnaire information cannot be ruled out as a contributor to the failure to observe strong associations between diet quality and mortality in this study.

The food frequency questionnaire used for the current study was completed in 1992–1993 and assessed the respondent’s diet in the preceding year. The dietary data collected during this time period may not have captured the dietary intake that played a role in the disease process. The relevant exposure may actually have occurred 10–20 or more years prior to death. Because there were only 4 years of follow-up in this cohort, to be counted as deceased participants had to be diagnosed with a disease and then die within a 4-year period. Thus, most of the deaths recorded were due to very aggressive cancers and serious circulatory disease. The DQI may predict chronic disease mortality better with more years of follow-up, when there are sufficient numbers of deaths from more clearly diet-related chronic diseases.

All data from the CPS II and CPS II Nutrition Survey questionnaires were self-reported. This population is highly educated and therefore may be expected to accurately self-report health-related data. Conversely, this cohort is also fairly elderly, which may have affected memory or accuracy of recall (52).

The study had several strengths. The Nutrition Cohort is large, with 115,833 participants being included in the analysis cohort. The data for this study were collected in a population that was disease free at the time of survey completion, which eliminated the possibility of disease-related recall bias. Data were available for many potential confounders of diet quality–disease associations, whereas previous studies controlled for few covariates other than age, smoking, and physical activity. The availability of data on a wide array of covariates enabled us to control for many demographic and health-related factors that are likely to confound associations between diet quality and disease.

There is great interest in indexes of diet quality and their ability to predict chronic disease morbidity and mortality. This study and other studies conducted by McCullough et al. (25, 26) suggested that these indexes may not predict chronic disease morbidity and mortality as well as previously thought. Before more dietary indexes are produced, more research is needed to determine whether current indexes are valuable and for what purposes they should be used.

Correspondence to Dr. Jennifer Seymour, Division of Nutrition and Physical Activity, Centers for Disease Control and Prevention, 4770 Buford Highway NE, Mail Stop K-26, Atlanta, GA 30341-3717 (e-mail: zta4@cdc.gov).

TABLE 1.

Cohort eligible for analysis in the Cancer Prevention Study II Nutrition Cohort, 1992–1993

 No. of women No. of men 
Total cohort 97,788 86,405 
Exclusions   
Race other than White or African American 1,231 1,193 
Age <50 years or >79 years 2,036 841 
Prevalent cancer, other than nonmelanoma skin cancer 12,146 9,032 
Previous heart attack 14,436 17,812 
Previous stroke 1,247 1,440 
>15% of FFQ* items missing 3,583 3,363 
Analysis cohort 63,109 52,724 
 No. of women No. of men 
Total cohort 97,788 86,405 
Exclusions   
Race other than White or African American 1,231 1,193 
Age <50 years or >79 years 2,036 841 
Prevalent cancer, other than nonmelanoma skin cancer 12,146 9,032 
Previous heart attack 14,436 17,812 
Previous stroke 1,247 1,440 
>15% of FFQ* items missing 3,583 3,363 
Analysis cohort 63,109 52,724 

* FFQ, food frequency questionnaire.

TABLE 2.

Recommendations, scores, and cutpoints for the eight components of the Diet Quality Index*

Dietary recommendation Score Cutpoint Cohort distribution 
Women Men 
Reduce total fat intake to ≤30% of energy ≤30% 34.0 23.8 
 >30–40% 38.6 43.4 
 >40% 27.4 32.8 
Reduce saturated fatty acid intake to <10% of energy <10% 43.3 29.8 
 10–13% 31.9 33.9 
 >13% 24.8 36.2 
Reduce cholesterol intake to <300 mg/day <300 mg 92.1 74.0 
 300–400 mg 5.5 14.8 
 >400 mg 2.4 11.2 
Eat five or more servings daily of a combination of vegetables and fruits† ≥5 servings 45.8 43.4 
 3–4 servings 37.0 36.2 
 0–2 servings 17.2 20.4 
Eat six or more servings daily of breads, cereals, and legumes ≥6 servings 20.1 28.7 
 4–5 servings 30.6 32.0 
 0–3 servings 49.3 39.4 
Maintain protein intake at moderate levels (lower than twice the RDA‡)§ ≤100% RDA 42.6 41.0 
 >100–150% RDA 42.7 43.1 
 >150% RDA 14.7 15.9 
Limit total daily intake of sodium to ≤2,400 mg ≤2,400 mg 65.3 36.4 
 >2,400–3,400 mg 27.4 37.1 
 >3,400 mg 7.3 26.5 
Maintain adequate calcium intake (approximately DRI‡ levels)¶ ≥DRI 30.6 21.8 
 2/3 DRI–<DRI 24.3 29.5 
 <2/3 DRI 45.1 48.7 
Dietary recommendation Score Cutpoint Cohort distribution 
Women Men 
Reduce total fat intake to ≤30% of energy ≤30% 34.0 23.8 
 >30–40% 38.6 43.4 
 >40% 27.4 32.8 
Reduce saturated fatty acid intake to <10% of energy <10% 43.3 29.8 
 10–13% 31.9 33.9 
 >13% 24.8 36.2 
Reduce cholesterol intake to <300 mg/day <300 mg 92.1 74.0 
 300–400 mg 5.5 14.8 
 >400 mg 2.4 11.2 
Eat five or more servings daily of a combination of vegetables and fruits† ≥5 servings 45.8 43.4 
 3–4 servings 37.0 36.2 
 0–2 servings 17.2 20.4 
Eat six or more servings daily of breads, cereals, and legumes ≥6 servings 20.1 28.7 
 4–5 servings 30.6 32.0 
 0–3 servings 49.3 39.4 
Maintain protein intake at moderate levels (lower than twice the RDA‡)§ ≤100% RDA 42.6 41.0 
 >100–150% RDA 42.7 43.1 
 >150% RDA 14.7 15.9 
Limit total daily intake of sodium to ≤2,400 mg ≤2,400 mg 65.3 36.4 
 >2,400–3,400 mg 27.4 37.1 
 >3,400 mg 7.3 26.5 
Maintain adequate calcium intake (approximately DRI‡ levels)¶ ≥DRI 30.6 21.8 
 2/3 DRI–<DRI 24.3 29.5 
 <2/3 DRI 45.1 48.7 

* Adapted from Patterson et al. (5).

† Potatoes were included as vegetables (there was no significant change if potatoes were included as carbohydrates).

‡ RDA, Recommended Dietary Allowance; DRI, Dietary Reference Intake.

§ The RDA for protein among people aged ≥51 years is 50 g for women and 63 g for men (45).

¶ The DRI among people aged ≥51 years is 1,200 mg (calcium recommendations have changed from the RDA to the DRI since the Diet Quality Index was first created) (31).

TABLE 3.

The five categories of diet quality in the Cancer Prevention Study II Nutrition Cohort, 1992–1996

Diet quality DQI* score No. of women No. of men 
High 0–3 10,239 4,246 
Medium-high 4–5 16,987 10,102 
Medium 6–7 16,288 13,404 
Medium-low 8–10 17,152 18,349 
Low 11–16 2,443 6,623 
Diet quality DQI* score No. of women No. of men 
High 0–3 10,239 4,246 
Medium-high 4–5 16,987 10,102 
Medium 6–7 16,288 13,404 
Medium-low 8–10 17,152 18,349 
Low 11–16 2,443 6,623 

* DQI, Diet Quality Index.

TABLE 4.

Frequency of major causes of death through December 31, 1996, for women and men in the Cancer Prevention Study II Nutrition Cohort, 1992–1996

Cause of death ICD-9-CM* code(s) Women  Men 
No.  No. 
All circulatory disease 390–459 256 29.5  645 37.2 
Coronary heart disease 410–414 116 13.4  365 21.0 
Stroke 430–438 62 7.1  75 4.3 
Other circulatory disease†  78 9.0  205 11.8 
All cancer 140–195, 199–208 399 45.9  635 36.6 
Lung cancer 162 101 11.6  235 13.5 
Colorectal cancer 153–154 44 5.1  45 2.6 
Pancreatic cancer 157 39 4.5  45 2.6 
Prostate cancer 185    31 1.8 
Esophageal cancer 150 0.5  31 1.8 
Breast cancer 174–175 29 3.3    
Ovarian cancer 183 29 3.3    
Brain cancer 192 21 2.4  36 2.1 
Lymphoma 202 21 2.4  23 1.3 
Other cancer‡  111 12.8  189 10.9 
Other causes       
Respiratory disease 460–519 67 7.7  170 9.8 
External causes§ E800–E999 36 4.1  61 3.5 
Diabetes mellitus 250 10 1.2  28 1.6 
Digestive disease 520–579 18 2.1  51 2.9 
Other causes¶  83 9.6  146 8.4 
       
All causes  869 100.0  1,736 100.0 
Cause of death ICD-9-CM* code(s) Women  Men 
No.  No. 
All circulatory disease 390–459 256 29.5  645 37.2 
Coronary heart disease 410–414 116 13.4  365 21.0 
Stroke 430–438 62 7.1  75 4.3 
Other circulatory disease†  78 9.0  205 11.8 
All cancer 140–195, 199–208 399 45.9  635 36.6 
Lung cancer 162 101 11.6  235 13.5 
Colorectal cancer 153–154 44 5.1  45 2.6 
Pancreatic cancer 157 39 4.5  45 2.6 
Prostate cancer 185    31 1.8 
Esophageal cancer 150 0.5  31 1.8 
Breast cancer 174–175 29 3.3    
Ovarian cancer 183 29 3.3    
Brain cancer 192 21 2.4  36 2.1 
Lymphoma 202 21 2.4  23 1.3 
Other cancer‡  111 12.8  189 10.9 
Other causes       
Respiratory disease 460–519 67 7.7  170 9.8 
External causes§ E800–E999 36 4.1  61 3.5 
Diabetes mellitus 250 10 1.2  28 1.6 
Digestive disease 520–579 18 2.1  51 2.9 
Other causes¶  83 9.6  146 8.4 
       
All causes  869 100.0  1,736 100.0 

* ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification.

† Includes all ICD-9-CM circulatory disease codes except coronary heart disease and stroke codes.

‡ Includes all ICD-9-CM cancer codes except the site-specific codes listed above.

§ Accidents, suicides, and homicides.

¶ Includes all ICD-9-CM codes not listed elsewhere in the table.

TABLE 5.

All-cause, all-circulatory-disease, and all-cancer mortality, by category of diet quality, for women in the Cancer Prevention Study II Nutrition Cohort, 1992–1996

Cause of death and DQI* category  No. of deaths Person-years of follow-up RR*,† 95% CI* RR‡  95% CI 
All causes       
High 114 38,366 1.00  1.00  
Medium-high 206 64,091 1.17 0.93, 1.47 1.09 0.87, 1.38 
Medium 222 61,787 1.35 1.07, 1.69 1.15 0.91, 1.45 
Medium-low 290 65,194 1.76 1.41, 2.18 1.31 1.04, 1.65 
Low 37 9,395 1.86 1.28, 2.70 1.23 0.84, 1.81 
p for trend   <0.0001 0.02 
All circulatory disease       
High 29 38,366 1.00  1.00  
Medium-high 58 64,091 1.31 0.84, 2.04 1.29 0.82, 2.02 
Medium 70 61,787 1.70 1.10, 2.62 1.58 1.01, 2.47 
Medium-low 88 65,194 2.16 1.42, 3.29 1.86 1.19, 2.89 
Low 11 9,395 2.26 1.12, 4.54 1.81 0.88, 3.72 
p for trend   <0.0001 0.003 
All cancer       
High 66 38,366 1.00  1.00  
Medium-high 105 64,091 1.02 0.75, 1.39 0.93 0.68, 1.27 
Medium 97 61,787 1.00 0.73, 1.37 0.84 0.61, 1.16 
Medium-low 120 65,194 1.23 0.91, 1.67 0.91 0.66, 1.25 
Low 11 9,395 0.93 0.49, 1.77 0.61 0.32, 1.18 
p for trend   0.24 0.28 
Cause of death and DQI* category  No. of deaths Person-years of follow-up RR*,† 95% CI* RR‡  95% CI 
All causes       
High 114 38,366 1.00  1.00  
Medium-high 206 64,091 1.17 0.93, 1.47 1.09 0.87, 1.38 
Medium 222 61,787 1.35 1.07, 1.69 1.15 0.91, 1.45 
Medium-low 290 65,194 1.76 1.41, 2.18 1.31 1.04, 1.65 
Low 37 9,395 1.86 1.28, 2.70 1.23 0.84, 1.81 
p for trend   <0.0001 0.02 
All circulatory disease       
High 29 38,366 1.00  1.00  
Medium-high 58 64,091 1.31 0.84, 2.04 1.29 0.82, 2.02 
Medium 70 61,787 1.70 1.10, 2.62 1.58 1.01, 2.47 
Medium-low 88 65,194 2.16 1.42, 3.29 1.86 1.19, 2.89 
Low 11 9,395 2.26 1.12, 4.54 1.81 0.88, 3.72 
p for trend   <0.0001 0.003 
All cancer       
High 66 38,366 1.00  1.00  
Medium-high 105 64,091 1.02 0.75, 1.39 0.93 0.68, 1.27 
Medium 97 61,787 1.00 0.73, 1.37 0.84 0.61, 1.16 
Medium-low 120 65,194 1.23 0.91, 1.67 0.91 0.66, 1.25 
Low 11 9,395 0.93 0.49, 1.77 0.61 0.32, 1.18 
p for trend   0.24 0.28 

* DQI, Diet Quality Index; RR, rate ratio; CI, confidence interval.

† Adjusted for age.

‡ Adjusted for age, race, occupation, education, smoking status, physical activity, alcohol intake, dietary supplement use, aspirin use, mammography history (all-cause and all-cancer mortality only), and hormone replacement therapy (all-cause and all-circulatory-disease mortality only).

TABLE 6.

All-cause, all-circulatory-disease, and all-cancer mortality, by category of diet quality, for men in the Cancer Prevention Study II Nutrition Cohort, 1992–1996

Cause of death and DQI* category No. of deaths Person-years of follow-up RR*,† 95% CI* RR‡  95% CI 
All causes       
High 117 16,315 1.00  1.00  
Medium-high 293 39,027 1.13 0.91, 1.39 1.06 0.85, 1.31 
Medium 418 51,925 1.25 1.02, 1.54 1.08 0.88, 1.33 
Medium-low 659 71,162 1.52 1.25, 1.85 1.17 0.96, 1.44 
Low 249 25,752 1.78 1.43, 2.22 1.19 0.94, 1.49 
p for trend   <0.0001  0.04  
All circulatory disease       
High 41 16,315 1.00  1.00  
Medium-high 125 39,027 1.37 0.96, 1.95 1.29 0.91, 1.85 
Medium 154 51,925 1.32 0.93, 1.86 1.13 0.80, 1.61 
Medium-low 237 71,162 1.56 1.12, 2.17 1.19 0.85, 1.68 
Low 88 25,752 1.79 1.23, 2.60 1.18 0.80, 1.74 
p for trend   0.0012  0.83  
All cancer       
High 46 16,315 1.00  1.00  
Medium-high 97 39,027 0.94 0.66, 1.33 0.85 0.60, 1.21 
Medium 168 51,925 1.26 0.91, 1.74 1.04 0.75, 1.45 
Medium-low 238 71,162 1.35 0.98, 1.85 0.99 0.72, 1.38 
Low 86 25,752 1.49 1.04, 2.14 0.92 0.63, 1.34 
p for trend   0.0004  0.81  
Cause of death and DQI* category No. of deaths Person-years of follow-up RR*,† 95% CI* RR‡  95% CI 
All causes       
High 117 16,315 1.00  1.00  
Medium-high 293 39,027 1.13 0.91, 1.39 1.06 0.85, 1.31 
Medium 418 51,925 1.25 1.02, 1.54 1.08 0.88, 1.33 
Medium-low 659 71,162 1.52 1.25, 1.85 1.17 0.96, 1.44 
Low 249 25,752 1.78 1.43, 2.22 1.19 0.94, 1.49 
p for trend   <0.0001  0.04  
All circulatory disease       
High 41 16,315 1.00  1.00  
Medium-high 125 39,027 1.37 0.96, 1.95 1.29 0.91, 1.85 
Medium 154 51,925 1.32 0.93, 1.86 1.13 0.80, 1.61 
Medium-low 237 71,162 1.56 1.12, 2.17 1.19 0.85, 1.68 
Low 88 25,752 1.79 1.23, 2.60 1.18 0.80, 1.74 
p for trend   0.0012  0.83  
All cancer       
High 46 16,315 1.00  1.00  
Medium-high 97 39,027 0.94 0.66, 1.33 0.85 0.60, 1.21 
Medium 168 51,925 1.26 0.91, 1.74 1.04 0.75, 1.45 
Medium-low 238 71,162 1.35 0.98, 1.85 0.99 0.72, 1.38 
Low 86 25,752 1.49 1.04, 2.14 0.92 0.63, 1.34 
p for trend   0.0004  0.81  

* DQI, Diet Quality Index; RR, rate ratio; CI, confidence interval.

† Adjusted for age.

‡ Adjusted for age, race, occupation, education, smoking status, physical activity, alcohol intake, dietary supplement use, and aspirin use.

References

1.
Trichopoulos A, Kouris-Blazos A, Wahlqvist ML, et al. Diet and overall survival in elderly people.
BMJ
 
1995
;
311
:
1457
–60.
2.
Haines PS, Siega-Riz AM, Popkin BM. The Diet Quality Index Revised: a measurement instrument for populations.
J Am Diet Assoc
 
1999
;
99
:
697
–704.
3.
Kennedy ET, Ohls J, Carlson S, et al. The Healthy Eating Index: design and applications.
J Am Diet Assoc
 
1995
;
95
:
1103
–8.
4.
Kant AK. Indexes of overall diet quality: a review.
J Am Diet Assoc
 
1996
;
96
:
785
–91.
5.
Patterson RE, Haines PS, Popkin BM. Diet Quality Index: capturing a multidimensional behavior.
J Am Diet Assoc
 
1994
;
94
:
57
–64.
6.
Farchi G, Fidanza F, Grossi P, et al. Relationship between eating patterns meeting recommendations and subsequent mortality in 20 years.
Eur J Clin Nutr
 
1995
;
49
:
408
–19.
7.
Huijbregts P, Feskens E, Rasanen L, et al. Dietary pattern and 20 year mortality in elderly men in Finland, Italy, and the Netherlands: longitudinal cohort study.
BMJ
 
1997
;
315
:
13
–17.
8.
Osler M, Schroll M. Diet and mortality in a cohort of elderly people in a North European community.
Int J Epidemiol
 
1997
;
26
:
155
–9.
9.
Block G, Patterson B, Subar A. Fruit, vegetables, and cancer prevention: a review of the epidemiological evidence.
Nutr Cancer
 
1992
;
18
:
1
–29.
10.
Steinmetz KA, Potter JD. Vegetables, fruit, and cancer prevention: a review.
J Am Diet Assoc
 
1996
;
96
:
1027
–39.
11.
Cheng KK, Day NE. Nutrition and esophageal cancer.
Cancer Causes Control
 
1996
;
7
:
33
–40.
12.
Gillman MW, Cupples LA, Gagnon D, et al. Protective effect of fruits and vegetables on development of stroke in men.
JAMA
 
1995
;
273
:
1113
–17.
13.
Hardman T. Dietary fat and risk of coronary heart disease in men: study gives clear message about diet. (Letter).
BMJ
 
1996
;
313
:
1258
.
14.
American Cancer Society. Guidelines on diet, nutrition, and cancer prevention: reducing the risk of cancer with healthy food choices and physical activity.
CA Cancer J Clin
 
1996
;
46
:
325
–41.
15.
Committee on Diet and Health, Food and Nutrition Board, National Research Council. Diet and health: implications for reducing chronic disease risk. Washington, DC: National Academy Press, 1989.
16.
Krauss RM, Deckelbaum RJ, Ernst N, et al. Dietary guidelines for healthy American adults: a statement for health professionals from the Nutrition Committee, American Heart Association.
Circulation
 
1996
;
94
:
1795
–800.
17.
Center for Nutrition Policy and Promotion, US Department of Agriculture. Dietary guidelines for Americans. Washington, DC: US Department of Agriculture, 1995:1–43.
18.
Kushi LH, Lew RA, Stare FJ, et al. Diet and 20-year mortality from coronary heart disease: The Ireland-Boston Diet-Heart Study.
N Engl J Med
 
1985
;
312
:
811
–18.
19.
Gage TB, O’Connor K. Nutrition and the variation in level and age patterns of mortality.
Hum Biol
 
1994
;
66
:
77
–103.
20.
Farchi G, Mariotti S, Menotti A, et al. Diet and 20-y mortality in two rural population groups of middle-aged men in Italy.
Am J Clin Nutr
 
1989
;
50
:
1095
–103.
21.
Nube M, Kok FJ, Vandenbrouke JP, et al. Scoring of prudent dietary habits and its relation to 25-year survival.
J Am Diet Assoc
 
1987
;
87
:
171
–5.
22.
Kant AK, Schatzkin A, Harris T, et al. Dietary diversity and subsequent mortality in the First National Health and Nutrition Examination Survey Epidemiologic Follow-up Study.
Am J Clin Nutr
 
1993
;
57
:
434
–40.
23.
Kant AK, Schatzkin A, Ziegler R. Diet diversity and subsequent cause-specific mortality.
J Am Coll Nutr
 
1995
;
14
:
233
–8.
24.
Kant AK, Schatzkin A, Graubard BI, et al. A prospective study of diet quality and mortality in women.
JAMA
 
2000
;
283
:
2109
–15.
25.
McCullough M, Feskanich D, Rimm EB, et al. Adherence to the dietary guidelines for Americans and risk of major chronic disease in men.
Am J Clin Nutr
 
2000
;
72
:
1223
–31.
26.
McCullough M, Feskanich D, Stampfer M, et al. Adherence to the dietary guidelines for Americans and risk of major chronic disease in women.
Am J Clin Nutr
 
2000
;
72
:
1214
–22.
27.
Stellman SD, Garfinkel L. Smoking habits and tar levels in a new American Cancer Society prospective study of 1.2 million men and women.
J Natl Cancer Inst
 
1986
;
76
:
1057
–63.
28.
Block G, Hartman AM, Naughton D. A reduced dietary questionnaire: development and validation.
Epidemiology
 
1990
;
1
:
58
–64.
29.
Block G, Coyl L, Smucker R, et al. Health Habits and History Questionnaire: diet history and other risk factors. Personal computer system documentation. Bethesda, MD: Division of Cancer Prevention and Control, National Cancer Institute, 1989.
30.
National Cancer Institute. HHHQ-DietSys analysis software. Version 3.8. Bethesda, MD: National Cancer Institute, 1993.
31.
Standing Committee on the Scientific Evaluation of Dietary Reference Intakes, Food and Nutrition Board, Institute of Medicine. Dietary reference intakes for calcium, phosphorus, magnesium, vitamin D and fluoride. Washington, DC: National Academy Press, 1997.
32.
Calle EE, Terrell DD. Utility of the National Death Index for ascertainment of mortality among Cancer Prevention Study II participants.
Am J Epidemiol
 
1993
;
137
:
235
–41.
33.
Health Care Financing Administration. International classification of diseases. Ninth Revision, clinical modification. 3rd ed. Washington, DC: US Department of Health and Human Services, 1989. (DHHS publication no. (PHS) 89-1260).
34.
Cox DR. Regression models and life tables (with discussion).
J R Stat Soc B
 
1972
;
34
:
187
–220.
35.
SAS Institute Inc. SAS/STAT user’s guide. Cary, NC: SAS Institute, Inc, 1989.
36.
Kleinbaum DG, Kupper LL, Muller KE. Applied regression analysis and other multivariable methods. Belmont, CA: Duxbury Press, 1988.
37.
Kleinbaum DG. Survival analysis: a self-learning text. New York, NY: Springer Publishing Company, Inc, 1996.
38.
Kleinbaum DG, Kupper LL, Morgenstern H. Epidemiologic research: principles and quantitative methods. New York, NY: Van Nostrand Reinhold Company, 1982.
39.
Hu FB, Stampfer MJ, Manson JE, et al. Dietary fat intake and the risk of coronary heart disease in women.
N Engl J Med
 
1997
;
337
:
1491
–9.
40.
Trichopoulos A, Katsouyanni K, Stuver S, et al. Consumption of olive oil and specific food groups in relationship to breast cancer risk in Greece.
J Natl Cancer Inst
 
1995
;
87
:
110
–16.
41.
Willett WC, Hunter DJ, Stampfer MJ, et al. Dietary fat and fiber in relationship to risk of breast cancer: an eight year follow-up.
JAMA
 
1992
;
268
:
2037
–44.
42.
Willett WC, Trichopoulos D. Nutrition and cancer: a summary of the evidence.
Cancer Causes Control
 
1996
;
7
:
178
–80.
43.
Kaplan S, Novikov I, Modan B. Nutritional factors in the etiology of brain tumors: potential role of nitrosamines, fat, and cholesterol.
Am J Epidemiol
 
1997
;
146
:
832
–41.
44.
Hu FB, Stampfer MJ, Manson JE, et al. Dietary protein and risk of ischemic heart disease in women.
Am J Clin Nutr
 
1999
;
70
:
221
–7.
45.
Subcommittee on the Tenth Edition of the RDAs, Food and Nutrition Board, Commission on Life Sciences, National Research Council. Recommended dietary allowances. Washington, DC: National Academy Press, 1989.
46.
Daviglus ML, Stamler J, Orencia AJ, et al. Fish consumption and the risk of fatal myocardial infarction.
N Engl J Med
 
1997
;
336
:
1046
–53.
47.
Kromhout D. Fatty acids, antioxidants, and coronary heart disease from an epidemiological perspective.
Lipids
 
1999
;
34(suppl)
:
S27
–31.
48.
Fraser GE. Nut consumption, lipids, and risk of a coronary event.
Clin Cardiol
 
1999
;
22(suppl)
:
III11
–15.
49.
Sabate J. Nut consumption, vegetarian diets, ischemic heart disease risk, and all-cause mortality: evidence from epidemiologic studies.
Am J Clin Nutr
 
1999
;
70(suppl)
:
500S
–3S.
50.
Newby PK, Hu FB, Rimm E, et al. The reproducibility and validity of the Diet Quality Index assessed by a food frequency questionnaire. (Abstract 654.8).
FASEB J
 
1999
;
13
:
A866
.
51.
Flagg EW, Coates RJ, Calle EE, et al. Validation of the American Cancer Society Cancer Prevention Study II Nutrition Survey Cohort food frequency questionnaire.
Epidemiology
 
2000
;
11
:
462
–8.
52.
Dwyer JT, Krall EA, Coleman KA. The problem of memory in nutritional epidemiology research.
J Am Diet Assoc
 
1987
;
87
:
1509
–12.