Fat intake and breast cancer risk in an area where fat intake is low: a case-control study in Indonesia

Kenji Wakaia, Drupadi S Dillonb, Yoshiyuki Ohnoa, Joedo Prihartonoc, Setyawati Budiningsihc, Muchlis Ramlid, Idral Darwisd, Didid Tjindarbumid, Gunawan Tjahjadie, Esti Soetrisnoe, Endang Sri Roostinie, Goi Sakamotof, Susilowati Hermang and Santoso Cornaine

a Department of Preventive Medicine, Nagoya University School of Medicine, Nagoya, Japan.
b Department of Nutrition,
c Community Medicine,
d Surgery, and
e Anatomic Pathology, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia.
f Department of Pathology, Cancer Institute, Tokyo, Japan.
g Research and Development Center for Nutrition, Ministry of Health, Bogor, Indonesia.


    Abstract
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Background Associations of fat and other macronutrients with breast cancer risk are not clear in areas where fat intake is low.

Methods We conducted a hospital-based case-control study from 1992 to 1995 in Jakarta, Indonesia.

Results The study, based on 226 cases and 452 age and socioeconomic status matched controls, provided the following findings. (a) In the pre-marriage period, the greater the fat or protein consumption, the larger the risk, whereas decreasing risk with increasing carbohydrate intake was detected. The odds ratio (OR) for the highest quartile of intake relative to the lowest was 8.47 (95% CI : 4.03–17.8) for fat, 2.19 (95% CI : 1.30–3.69) for protein, and 0.16 (95% CI : 0.08–0.31) for carbohydrate. A positive association with fat and a negative one with carbohydrate were also observed for the post-marriage period, but of weaker magnitude compared to the pre-marriage period. (b) The effects of macronutrient intakes were stronger among premenopausal than among postmenopausal women. (c) Most of the associations of protein and carbohydrate were insignificant after adjustment for fat intake.

Conclusions These findings suggest that fat intake might be an important determinant of breast cancer among populations with a low fat diet in Indonesia.

Keywords Breast cancer, fat, nutrition, case-control study, Indonesia

Accepted 21 June 1999


    Introduction
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
The hypothesis that dietary fat intake may be related to breast cancer risk has emerged from animal experiments and ecological studies. Experiments in rats or mice showed that higher fat intake elevated mammary tumour incidence.1 In international ecological studies, national per capita fat consumption is highly correlated with breast cancer incidence or mortality rates; the correlation coefficient between per capita fat intake and age-adjusted breast cancer incidence being as high as 0.76.2

Nevertheless, case-control or cohort studies on nutrition and breast cancer have not fully endorsed this hypothesis.3 Hunter et al. pooled the primary data from seven large-scale cohort studies on dietary fat and breast cancer and revealed no evidence of a positive association between total fat intake and breast cancer risk.4 Howe et al. summarized results from 12 case-control studies and related fat intake to risk, but the summary odds ratio (OR) for a 100 g increase in daily fat consumption was only 1.355 which suggests that the positive association is very weak if it exists. Most of these case-control or cohort studies, however, have been conducted in developed countries, where fat intake is relatively higher. It remains possible, therefore, that low fat intake may reduce risk of breast cancer.3,6

Thus, to elucidate the relationship of fat and other macronutrients with breast cancer risk in a setting where people consume relatively little dietary fat, we conducted a case-control study in Jakarta, Indonesia. From the food balance sheet in 1995 (available from the Food and Agriculture Organization database through the Internet), energy intake from fat was estimated to be 15–20% in Indonesia.

The incidence rate of female breast cancer is still low in Indonesia; the age-adjusted incidence rate (adjusted by the World Population7) in Semarang, Central Java, was 18.6 per 100 000 population in 1985–19898 while it was more than 50 in most Western developed countries circa 1985.9 Breast cancer, however, is known to be the second most common malignancy among Indonesian females after cervical cancer,10 and its incidence rate has recently been increasing; the age-adjusted incidence rate (adjusted by the World Population) in Semarang was 10.2 and 13.0 in 1970–1974 and 1980–1981, respectively.8 The proportion of deaths from cancer shows an upward trend in Indonesia. According to the Indonesian National Household Survey, cancer ranked the third among all causes of death, following infection and cardiovascular diseases in 1986.11 It is, therefore, of importance and significance to elucidate the common and country-specific risk factors of breast cancer, including nutritional variables, in Indonesia. In a preceding case-control study in Jakarta, the intake frequency of some selected foods, particularly fatty ones, was found to be associated with breast cancer risk.12


    Subjects and Methods
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Study subjects
We conducted this study from February 1992 to September 1995 in metropolitan Jakarta, Indonesia. To be eligible as cases in the present study, patients had to have been initially and histopathologically diagnosed as having primary breast cancer in the Department of Surgery, Dr Cipto Mangunkusumo National Central General Hospital. Male patients with breast cancer were excluded from the study.

Controls were selected from female in/outpatients of the hospital, mainly from surgical departments. Two controls per case were recruited, matching for age (±3 years) and socioeconomic status. The socioeconomic status of the patients was matched based on the hospital room class which they used or they could afford to use. Those with a history of any malignancy or a palpable breast lump were excluded from the controls. Controls were recruited within 3 months after the interview of a corresponding case.

Data collection
Epidemiological information was collected by direct interview with the study subject using a standardized questionnaire, by well-trained dietitians. Nutrient intakes of respondents were assessed for two periods of life, namely before marriage and after marriage but before illness.13 The pre-marriage period presumably referred to that before first marriage.

To estimate intakes of selected nutrients among cases and controls, a food frequency questionnaire was developed specially for the present study.14 It included 98 food items most commonly found in the Indonesian diet. The dietitians asked subjects about frequency of intake and standard serving size for each food item. The interviews were conducted using food models to help respondents to estimate the serving size. This procedure was validated in advance against actual dietary intake provided by precise weighing method.14

Other epidemiological information collected at the interview included routine demographic variables such as age, marital status, and educational attainment; residential history; anthropometric factors; family history of cancer; reproductive history; contraceptive use; and smoking and drinking habits. Clinical stages of case patients were classified according to the international TNM Classification.15,16

Statistical methods
Food intake frequency and usual portion sizes among cases and controls were converted to nutrient intakes using INDONAP software based on the Indonesian Food Composition Table. Unfortunately, we could not divide total fat into saturated, monounsaturated and polyunsaturated fat, since a database for Indonesian foods was not available for these types of fat.

In the further analyses, all the nutritional variables were transformed to natural logarithm values in order to improve normality. Moreover, nutrient intakes were adjusted for energy using linear regression models. Energy-adjusted nutrient intakes were computed as the residuals from the regression model with total caloric intake as the independent variable and absolute nutrient intake as the dependent variable.17 Residuals have a mean of zero and include negative values and so do not provide an intuitive sense of actual nutrient intake. We therefore added the expected nutrient intake for the mean caloric intake of the study population to the residuals.17 The expected intake was computed using the regression model mentioned above.

The strength of the association between intake of fat/other macronutrients and breast cancer risk was measured as an odds ratio (OR). Subjects were divided into four groups according to the quartiles of calorie-adjusted nutrient intakes among controls, that is, controls were grouped into quartiles, and 25 percentiles, medians and 75 percentiles among them were used as cut points to categorize cases. The OR were obtained by conditional multiple logistic regression analyses,18 adjusting for potentially confounding covariates. Unconditional logistic models19 including age (continuous variable) and other covariates, however, were also used when analysing data by menopausal status. We used categorical values for the nutrients because they provide OR more easily interpreted. The analyses, however, were repeated using continuous variables for the energy-adjusted nutrient intakes and were compared with the categorical analyses.

The test for trend in the logistic regression analysis was performed using the score corresponding to the quartiles of nutrient intakes.20,21 Interactions between nutrient intakes and menopausal status were examined by including interaction terms in the logistic models: (the abovementioned score for nutrient intakes) x (menopausal status: yes = 1, no = 0). Subjects with missing information on the covariates were excluded from the multivariate analyses; only 3.4%, at most, of the subjects were eliminated by this procedure. Chi-square or Mantelextension test22 was used to detect case-control differences in background factors.


    Results
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
A total of 333 eligible cases were identified during the study period. Of these patients, 226 (67.9%) were successfully interviewed. Clinical stages I, II, III and IV accounted for 2.2% (n = 5), 11.9% (27), 73.9% (167) and 11.9% (27) of cases, respectively. We obtained 452 controls with a response rate of almost 100%. Clinical diagnoses of control patients are shown in Table 1Go.


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Table 1 Clinical diagnoses of control patients
 
Table 2Go shows background factors of the study subjects. The mean age (±SD) was 46.4 ± 9.7 years for cases and 45.8 ± 10.1 for controls. The distribution of the longest place of residence and educational attainment was similar between cases and controls, which indicates that socioeconomic background was well matched in the control selection process. Cases were more likely to be separated than controls, while controls seemingly tended to be widowed more than cases. All the participants had got married at least once in their lifetime, and controls got married earlier than cases.


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Table 2 Background factors of the study subjects
 
The number of live births was negatively associated with breast cancer. Postmenopausal status was more common among cases than among controls. Body mass index, family history of breast cancer and age at menarche did not demonstrate a significant case-control difference in the present study.

Table 3Go summarizes the OR with 95% CI for breast cancer according to macronutrient intakes by period of life. For pre-marriage period, protein and fat consumption was positively correlated with breast cancer risk (trend P = 0.002 for protein and 6 x 10–9 for fat), while decreasing risk with increasing carbohydrate intake was detected (trend P = 4 x 10–8). The OR for the third and the highest quartiles of intakes relative to the lowest were 1.73 (95% CI : 1.02–2.92) and 2.19 (95% CI : 1.30–3.69) for protein, 6.05 (95% CI : 2.92–12.6) and 8.47 (95% CI : 4.03–17.8) for fat, and 0.50 (95% CI : 0.30–0.83) and 0.16 (95% CI : 0.08–0.31) for carbohydrate, respectively.


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Table 3 Odds ratios (OR) with 95% confidence intervals (CI) for breast cancer according to quartiles (Q1–Q4)a of macronutrient intakes by period of life
 
A positive association of fat intake with breast cancer emerged also for the post-marriage period (trend P = 1 x 10–5), but with much weaker magnitude as compared to the pre-marriage period; the OR being 2.50 (95% CI : 1.42–4.42) and 3.48 (1.96–6.17) for the third and the fourth quartiles of fat intake, respectively. The greater the carbohydrate intake, the smaller the OR (trend P = 0.0003). The risk reduction by carbohydrate consumption after marriage, however, was somewhat smaller than that before marriage. The OR (95% CI) were 0.61 (0.37–0.99) at the third quartile level, and 0.36 (0.21–0.62) at the highest one, compared with the lowest. Protein intake was not significantly linked to breast cancer risk in the post-marriage period. After adjustment for fat consumption, intakes of protein and carbohydrate were not significantly associated with either increased or decreased risk for both the pre- and post-marriage periods.

Tables 4 and 5GoGo demonstrate OR for breast cancer according to macronutrient consumption by period of life among pre- and post-menopausal women, respectively. In general, the associations of the nutrients with breast cancer risk were similar to those found for all subjects; positive associations for protein and fat, and a negative one for carbohydrate were observed, particularly for the pre-marriage period. Premenopausal women seemed to experience larger effects of macronutrient intakes than postmenopausal females. For example, the OR for the highest quartile of pre-marriage fat intake relative to the lowest was as high as 10.7 (95% CI : 3.86–29.7) for premenopausal women, while it was 4.34 (95% CI : 1.70–11.1) for postmenopausal women.


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Table 4 Odds ratios (OR) with 95% confidence intervals (CI) for breast cancer according to quartiles (Q1–Q4)a of macronutrient intakes by period of life among premenopausal women
 

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Table 5 Odds ratios (OR) with 95% confidence intervals (CI) for breast cancer according to quartiles (Q1–Q4)a of macronutrient intakes by period of life among postmenopausal women
 
Most of the interactions between macronutrient intakes and menopausal status, however, were not statistically significant. Protein intake seemed to be associated with breast cancer risk more strongly among premenopausal women than among postmenopausal females for the post-marriage period (P for interaction = 0.087), but other interaction terms between macronutrient intakes and menopausal status did not achieve statistical significance. P-values for the interactions were 0.18, 0.61 and 0.71 for protein, fat and carbohydrate in the pre-marriage period, and 0.48 and 0.27 for fat and carbohydrate in the post-marriage period, respectively.

When fat consumption was included in the logistic models, significant associations of protein or carbohydrate intake with breast cancer disappeared, except for the negative association of protein intake for post-marriage period among postmenopausal females (trend P = 0.018, Table 5Go), which was not significant before adjustment for fat intake.

Table 6Go summarizes the OR for one-unit increment of nutrient intakes [loge(g/day)/loge(kcal/day)], which were computed in the analyses using continuous variables for the nutrients. These analyses disclosed associations of macronutrient intakes similar to those found in the categorical analyses.


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Table 6 Odds ratios (OR) with 95% confidence intervals (CI) for breast cancer per one-unit increment [loge(g/day)/loge(kcal/day)] of macronutrient intakes by menopausal status and period of life
 

    Discussion
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
One potential weakness of our study is that the controls were selected from the patients who visited the hospital. We could not set up population controls because of the inadequate registration system for residents in Jakarta. In a case-control study based on cases from one hospital, however, a random sample of the general population does not necessarily correspond to a random sample of the source population that gives rise to the cases, from which controls should be selected.23 It would rather be more appropriate to draw controls from patients in the hospital where the cases were identified, since referral patterns should be taken into account.

Referral patterns would be similar between cases and controls in the present study, because the controls were selected mainly from patients in the surgical departments of the hospital where the cases were recruited. Moreover, the control subjects were quite similar to the patients with breast cancer for residential history and educational attainment (Table 2Go). This essentially implied that the controls identified in the hospital compared well with the cases.

The major limitation in hospital controls is that the exposure in question might be associated with the control diseases.23 We re-analysed the data, therefore, excluding the controls with conditions potentially related to fat intake, i.e. atheroma, cholelithiasis and lipoma. The association of fat intake with breast cancer risk, however, was not substantially altered. The OR for the second, the third and the highest quartiles relative to the lowest were 4.85 (95% CI : 2.13–11.1), 5.98 (95% CI : 2.76– 13.0) and 9.59 (95% CI : 4.35–21.1) for the pre-marriage period (trend P = 2.3 x 10–8), and 1.64 (95% CI : 0.87–3.09), 2.46 (95% CI : 1.36–4.44) and 3.03 (95% CI : 1.64–5.58) for the post-marriage period (trend P = 0.0001), respectively. These controls therefore did not bias our findings. Nevertheless, some other control diseases might be related to fat intake, even though the relation has not been disclosed. Population-based case-control studies will be required to avoid this bias.

Another methodological issue in our investigation might be the validity of the dietary assessment for the pre-marriage period. Our food frequency questionnaire system was validated against actual dietary records by precise weighing,14 but we could not validate this method for the remote past such as the pre-marriage period, since the questionnaire was newly developed for the present study. The average interval (±SD) between first marriage and interview was as long as 25.4 ± 11.6 years among the participants. A substantial uncertainty, therefore, exists in the recall of diet before marriage.

In recent years, however, some food frequency methods have been reported to be useful for assessing diet in the remote past. At least, recalled food intakes appeared to be a better predictor of past intakes than was current diet,24–26 that is, it is better to use recall of past diet than just to adopt current diet as a surrogate in retrospective evaluation of diet.27 Most women who participated in our pilot study could clearly discriminate their food intake between pre- and post-marriage period, and time of marriage could be used as a milestone in recalling dietary patterns.13 It would be, therefore, possible to differentiate the pre-marriage period from post-marriage days for the effects of macronutrient intakes, although the limitations mentioned above should be kept in mind in interpreting the results.

Recall of diet might be different in women who know their breast cancer status compared to those who do not. In addition, their diet may have changed due to the disease because most of the case patients had advanced cancer (stage III and IV) at the interview. This would be reflected in the recall although we asked the subjects' diet before illness. Cohort studies are certainly required to corroborate our findings. Nevertheless, recall bias in the present study would be minimal since most women in Indonesia did not seem to know the fat/breast cancer hypothesis.

Confounding by reproductive factors28 might not be completely removed in the analyses because of the incomplete collection of reproductive history; ages at first birth (or full-term pregnancy) and menopause were not requested, and age at first marriage was included as a surrogate of age at first birth. However, the strength of the observed associations was substantially reduced when reproductive factors were not considered in the multivariate models. This finding indicated that the residual confounding effects by reproductive variables might have diluted the associations and that our findings could not be explained by this confounding. For example, the OR for the highest quartile of fat intake among all women were computed as 7.84 and 3.03 for the pre- and post-marriage periods without adjustment for reproductive factors, but were 8.47 and 3.48 with the adjustment.

Dietary fat was most strongly and consistently associated among macronutrients in the present study. When fat intake was adjusted, most of the associations with protein/carbohydrate intake turned to be insignificant, while fat consumption was correlated with breast cancer risk among all subjects even after adjustment for protein and carbohydrate intake. For the pre-marriage period, the OR for the highest quartile of fat intake compared with the lowest were 9.32 (95% CI : 4.07–21.3) or 8.13 (95% CI : 1.84–36.0) when adjusted for protein or carbohydrate consumption, respectively. The corresponding figures for post-marriage age were 4.20 (95% CI : 2.24–7.90) and 5.97 (95% CI : 1.72–20.8).

It is quite reasonable, therefore, to suppose from the present findings that fat would be a relevant nutrient, though some unknown factors related to fat intake itself can not be excluded. Alcohol consumption might be a potential confounder,3 but this confounding would be minimal, if any, since only 1.3% of women had ever drunk among the respondents. Most people in Jakarta are Moslem, and they seldom drink for religious reasons.

An animal study suggests that a threshold may occur between 16 and 22% of energy intake from fat, below which the promoting effects of fat is turned off.29 It would be of significance, therefore, that the positive association of fat intake with breast cancer risk was observed in such areas as Jakarta, where fat consumption is rather low. The median energy intake from fat among the control group in the present study was about 15% of calories, while the lowest cut points for fat intake in most of the available prospective studies were more than 25%.3 Even the lowest cut point in the pooled analysis of cohort studies by Hunter et al. was 20% of total energy intake,4 which was still higher than the Indonesian standard.

Hunter and Willett claim that no association between fat and breast cancer would be found even in a setting where fat intake is low, because international ecological studies suggest a linear correlation between per capita fat intake and breast cancer incidence and give no evidence for a threshold.3 Nevertheless, even if this association is linear, a higher relative risk or a greater OR would be theoretically observed for a given increment of fat intake among populations with a low fat diet than among those with a high fat one.

Fat intake was related to breast cancer risk more strongly for the pre-marriage period than for the post-marriage one. In animal studies, high dietary fat increases mammary epithelial cell proliferation, particularly hormonally driven hyperproliferation during breast growth. The maximum effects of high fat diet on breast carcinogenesis, therefore, may be during puberty and adolescence, namely the pre-marriage period, when the mammary gland is actively growing and developing.30 However, further investigations, such as case-control studies with improved techniques to assess nutrient intakes in the distant past, or very long-term cohort studies, are undoubtedly needed to confirm this hypothesis, since our methods for measuring diet during the pre-marriage period had some limitations as previously noted.

Stronger associations of macronutrient intakes were detected among premenopausal women than among postmenopausal females in the present study, although most of the interactions between intakes of the nutrients and menopausal status were not statistically significant. This finding is not consistent with that from the combined analysis of case-control studies by Howe et al.5 Their analysis related fat intake to an increased risk only in postmenopausal women, although only premenopausal females experienced an elevated risk associated with saturated fat in one case-control study.31 Effects of macronutrients by menopausal status, including those of protein, should be considered in the future investigations.

In short, our study suggested that consumption of macronutrients, particularly fat intake, might be an important determinant for breast cancer risk in Indonesia. More detailed investigations, prospective studies in particular, among populations with a low fat diet, will be warranted to determine whether low fat intake actually reduces the risk.


    Acknowledgments
 
The authors are grateful to the nurses and dietitians for their excellent care of cases and controls, and collection of epidemiological and nutritional data. This work was supported by Monbusho (Ministry of Education, Science, Sports and Culture of Japan) International Scientific Research Program, Special Cancer Research Grants (01042007, 04042013, 06042006 and 07042004).


    References
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 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
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