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. Author manuscript; available in PMC: 2022 Aug 1.
Published in final edited form as: Cancer. 2021 May 4;127(15):2762–2773. doi: 10.1002/cncr.33461

Consumption of sugar-sweetened beverages, artificially sweetened beverages, and breast cancer survival

Maryam S Farvid 1, Nicholas D Spence 2, Bernard A Rosner 3, Wendy Y Chen 3,4, A Heather Eliassen 1,3, Walter C Willett 1,3,5, Michelle D Holmes 1,3
PMCID: PMC8277662  NIHMSID: NIHMS1665426  PMID: 33945630

Abstract

Background:

The activation of insulin pathways is hypothesized to promote tumor growth and worsen breast cancer survival. Sugar-sweetened beverages (SSBs) can lead to higher risk of insulin resistance and may affect survival. The authors prospectively evaluated the relation of post-diagnostic SSB and artificially sweetened beverage (ASB) consumption with mortality among women with breast cancer.

Methods:

In total, 8,863 women with stage I through III breast cancer were identified during follow-up of the Nurses’ Health Study (NHS; 1980–2010) and Nurses’ Health Study II (NHSII; 1991–2011). Women completed a validated food frequency questionnaire every four years after diagnosis and were followed until death or end of follow-up (2014 for the NHS and 2015 for the NHSII). Multivariable Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of breast cancer-specific and all-cause mortality, after adjusting for measures of adiposity and other potential predictors of cancer survival.

Results:

With a median follow-up of 11.5 years, 2,482 deaths were prospectively documented, including 1,050 deaths from breast cancer. Compared with women who had no consumption, women who had SSB consumption after diagnosis had higher breast cancer-specific (>1 to 3 servings/week, HR=1.31; 95%CI=1.09–1.58; >3 servings/week, HR=1.35; 95%CI=1.12–1.62; Ptrend=0.001) and all-cause (>1 to 3 servings/week, HR=1.21; 95%CI=1.07–1.37; >3 servings/week, HR=1.28; 95%CI=1.13–1.45; Ptrend=0.0001) mortality. In contrast, ASB consumption was not associated with higher breast cancer-specific or all-cause mortality. Furthermore, replacing one serving/day of SSB consumption with one serving/day of ASB consumption was not associated with lower risk of mortality.

Conclusions:

Higher post-diagnostic SSB consumption among breast cancer survivors was associated with higher breast cancer-specific mortality and death from all causes.

Keywords: Sugar sweetened beverages, artificially sweetened beverages, Breast cancer, Breast cancer-specific mortality, All-cause mortality

Introduction

Sugar-sweetened beverages (SSBs), such as soft drinks, fruit-flavored drinks, punches, sports drinks, and energy drinks, are among major sources of added sugar in the US diet and can lead to a higher risk of many conditions, including insulin resistance, obesity, type 2 diabetes, and cardiovascular diseases (1–6). These conditions may contribute to a poor prognosis among women with breast cancer (7–14). High levels of insulin at time of diagnosis have been associated with a worse prognosis in nondiabetic women with breast cancer (15). Insulin treatment in breast cancer survivors with diabetes, has been associated with a poorer prognosis (16, 17). Thus, dietary factors that contribute to higher levels of circulating glucose and insulin may impact survival in women with breast cancer. This hypothesis was strengthened by our recent analyses of fruit juice consumption and dietary glycemic load among women with breast cancer in the Nurses’ Health Study (NHS) and Nurses’ Health Study II (NHSII), in which high consumption of fruit juice and adherence to dietary intake with high glycemic load were associated with higher risk of breast cancer-specific and all-cause mortality (18, 19). In addition, high intake of SSBs has been associated with a higher risk of mortality in healthy populations (20–23). However, it is unclear whether SSB consumption after a breast cancer diagnosis affects disease progression and survival. Although caffeine, an ingredient in some soft drinks, may suppress breast cancer tumor growth (24), play an antidiabetic role (25, 26), and decrease risk of mortality (27), survival benefits associated with post-diagnostic caffeinated versus caffeine-free soft drinks remain unclear among patients with breast cancer. Furthermore, individuals usually consider artificially sweetened beverages (ASBs) as healthy alternatives to SSBs; however, a higher risk of mortality has been reported with higher ASB consumption (22). The safety of ASBs has not been examined in women already diagnosed with breast cancer.

In this regard, we evaluated the associations between SSB and ASB consumption after diagnosis of breast cancer in relation to breast cancer-specific and all-cause mortality. Furthermore, we estimated the breast cancer-specific and all-cause mortality risk when substituting other beverages for SSBs.

Subjects and Methods

Study Population

The NHS is an ongoing, prospective cohort study that was created in 1976, with an enrollment of 121,700 female registered nurses, aged 30 to 55 years at inception, residing in 11 US states. The NHSII is an ongoing, prospective cohort study that was created in 1989, with an enrollment of 116,429 female registered nurses, aged 25 to 42 years at inception, residing in 14 US states. Participants were followed through biennial self-administered questionnaires to collect information on health lifestyle and clinical outcomes. We selected women who had a confirmed diagnosis of invasive breast cancer from 1980 to 2010 in the NHS, and from 1991 to 2011 in the NHSII. For this study, we excluded women from the analyses who were missing diet information ≥12 months after diagnosis, those who had a total energy intake <600 or >3500 kcal/day, those who left blank >70 food items on the food frequency questionnaire (FFQ), those who left blank items concerning SSB or ASB on the FFQ, those who were diagnosed with cancer (except nonmelanoma skin cancer) before breast cancer, those who had stage IV disease at diagnosis, and those who were missing information on disease stage. Thus, 8,863 women with stage I through III breast cancer were included in the analysis (Supplemental Figure S1). Completion of the questionnaire was considered to imply informed consent when the study protocol was approved in 1976 (NHS) and 1989 (NHSII) by the institutional review boards of the Brigham and Women’s Hospital and Harvard T.H. Chan School of Public Health (Boston, MA), and those of participating registries as required. The studies were conducted in accordance with recognized ethical guidelines (Declaration of Helsinki).

Assessment of Dietary Intake

In the NHS, participants completed a semiquantitative FFQ with 61 items in 1980, followed by FFQs that were expanded to 116–130 items in 1984, 1986, and every four years thereafter until 2010. In the NHSII, a similar FFQ of approximately130 items was completed in 1991 and every four years thereafter through 2011 (questionnaires available at http://www.nurseshealthstudy.org/participants/questionnaires). Questionnaire items about SSBs included regular carbonated caffeinated soft drinks, regular carbonated caffeine-free soft drinks, and non-carbonated sweetened beverages (e.g., punch, lemonade, fruit drink, or sugared iced tea). ASBs included carbonated caffeinated low-calorie soft drinks and carbonated caffeine-free low-calorie beverages. Questions included the frequency of consumption over the past year for a standard 355 mL (12-ounce) serving (1 glass, can, or bottle) of each SSB or ASB. For each beverage, there were nine response categories ranging from “never or less than once/month” to “6 or more times/day.” Post-diagnostic SSB and ASB consumption data were collected from FFQs completed ≥12 months after diagnosis. The mean time from breast cancer diagnosis to the first post-diagnostic FFQ was 3.3±2.0 years (10th percentile=1.3 years and 90th percentile=4.9 years).

To reduce measurement error and within-person variation in the assessment of long term intake after diagnosis, we calculated the cumulative average of post-diagnostic SSB, ASB, total energy, and alcohol intake from all available FFQs after diagnosis (28). The FFQ has been extensively validated in our cohorts compared with more detailed methods (29–31) and biomarkers of intake (31).

Ascertainment of Breast Cancer and Death

Women reported a breast cancer diagnosis through the biennial questionnaires. Then, we requested permission from those women or next of kin to access medical records and pathology reports to confirm the diagnosis and collect data on treatment and tumor characteristics, including disease stage and ER/progesterone receptor (PR) status. For approximately 70% of women, breast cancer tissue was collected and tumor microarrays were performed to assess tumor characteristics by immunohistochemistry; details are described elsewhere (32–34). The immunohistochemical staining method was performed to determine the status of ER, PR, human epidermal growth factor receptor 2 (HER2), cytokeratin 5/6 (CK5/6), Ki-67, and epidermal growth factor receptor (EGFR) in tumors. In women for which tumor microarrays were not available, we extracted ER, PR, and HER2 status from their medical records. The following molecular subtypes were determined based on ER, PR, HER2, CK5/6, Ki-67, and EGFR status along with histologic grade: Luminal A [ER-positive and/or PR-positive, HER2-negative, and Ki-67-negative (or histologic grade 1 or 2)]; luminal B [ER-positive and/or PR-positive, and HER2-positive; or ER-positive, and/or PR-positive, HER2-negative, and Ki-67-positive (or histologic grade 3)]; HER2-enriched (ER-negative, PR-negative, and HER2-positive); basal-like (ER-negative, PR-negative, HER2-negative, and CK5/6-positive and/or EGFR-positive); unclassified tumors lacked expression for all five markers. Insulin receptor (IR) expression in tumors was measured in 2,480 women from the NHS using Definiens image analysis software (Tissue Studio, Definiens AG, Munich, Germany) (35).

Deaths were reported by family members or the postal service or were ascertained through a search of the National Death Index. The cause of death was determined by physician review of the death certificate and medical record.

Covariates

By using biennial questionnaires that were returned after breast cancer diagnosis, we obtained data on post-diagnostic body mass index (BMI), physical activity, smoking status, and aspirin use, all of which were updated every two or four years, if available. Because treatment may affect lifestyle factors, we only collected data that were reported ≥12 months after diagnosis. To minimize chances of reverse causation, cumulative averages of post-diagnostic BMI and physical activity were calculated using 4-year lagged data. Data on pre-diagnostic BMI were obtained from the last questionnaire that women returned before breast cancer diagnosis. Then, the change in BMI from pre-diagnosis to post-diagnosis was calculated. Information related to menopausal status, age at menopause, postmenopausal hormone use, and oral contraceptive use was collected from the last biennial questionnaire before diagnosis. In addition, we collected data related to breast cancer characteristics, including age at diagnosis, disease stage, and treatment with radiotherapy, chemotherapy, and hormones from reviewing medical records and supplemental questionnaires.

Statistical analysis

Women with stage I through III breast cancer were followed from the date of returning the first FFQ after diagnosis until death or until June 1, 2014 for the NHS and June 1, 2015 for the NHSII, whichever occurred first. Deaths from breast cancer and all causes were outcomes of the study.

We combined data from NHS and NHSII and used stratified Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Eligible participants were divided into four groups based on the number of servings/week of SSB or ASB consumption. We fit 2 models: in model 1, we stratified by cohort and adjusted for age at diagnosis and calendar year of diagnosis. In model 2 (multivariable model), we stratified by cohort and adjusted for age at diagnosis, calendar year of diagnosis, time between diagnosis and first FFQ after diagnosis, calendar year at start of follow-up of each-2-year questionnaire cycle, post-diagnostic total energy intake, and potential predictors of breast cancer survival including pre-diagnostic BMI, pre-diagnostic to post-diagnostic BMI change, post-diagnostic alcohol consumption, post-diagnostic smoking, post-diagnostic physical activity, post-diagnostic aspirin use, pre-diagnostic oral contraceptive use, pre-diagnostic menopausal status, age at menopause, postmenopausal hormone use, race, stage of disease, ER/PR status, radiotherapy, chemotherapy, and hormonal treatment. Women who had unknown menopausal status at time of diagnosis were categorized in the premenopausal group if they were <46 years for smokers or <48 years for never smokers and were categoried in the postmenopausal group if they were >54 years for smokers or >56 years for never smokers (36). For missing covariates, which comprised from less than 1% to 12.6% of total person-years, we used the missing indicator method. To address the potential confounding role of other dietary factors, we also evaluated the associations after additionally controlling for the post-diagnostic modified Alternate Healthy Eating Index (AHEI) (excluding SSB and alcohol scores) as well as intake of total fruit and vegetable, total red and processed meat, coffee, fruit juice, total protein, dietary glycemic index, or both fruit juice and dietary glycemic load. A restricted cubic spline analysis was used to assess the dose-response relation between SSB consumption and outcomes of interest (37). In addition, we examined breast cancer-specific and all-cause mortality risk after the cross-classification of participants based on pre- and post-diagnostic SSB intake (high/high, low/high, or high/low compared with low/low). Greater than 1 serving/week of SSB was categorized as high intake.

We estimated the effect of replacing one serving/day of SSB consumption with an isovolumetric serving (355 mL) of ASBs, fruit juice, coffee, tea, skim/low-fat milk, whole milk, and water on mortality by simultaneously including these beverage items as continuous variables in the multivariable model. The HRs and 95% CIs for the substitution effect were derived from the difference between the regression coefficients, variances, and covariances (38).

Furthermore, we calculated the population attributable risk percentage (PAR%) and 95% CI using a macro developed by Spiegelman et al. (39) to quantify the proportional reductions expected in breast cancer-specific mortality and all-cause mortality if women did not drink SSB after diagnosis or if all women drank ≤2 servings/month of SSBs after diagnosis. In this model, we set the low risk category as a reference group for covariates including cohort, age at diagnosis, calendar year of diagnosis, calendar year at the start of follow-up of each-2-year questionnaire cycle, pre-diagnostic BMI, pre-diagnostic to post-diagnostic BMI change, post-diagnostic smoking, post-diagnostic physical activity, post-diagnostic alcohol consumption, post-diagnostic energy intake, post-diagnostic aspirin use, pre-diagnostic menopausal status, age at menopause, postmenopausal hormone use, stage of disease, ER/PR status, radiotherapy, chemotherapy, and hormonal treatment. Covariates for the PAR analysis were selected using stepwise Cox proportional hazards regression. To estimate the risk difference, we used PROC GENMOD, with NORMAL working distribution and repeated in ID.

Stratified analyses were conducted to evaluate potential effect modification by including IR status (IR-positive/IR-negative), ER status (ER-positive/ER-negative), and molecular subtypes (luminal A/luminal B/HER2-enriched/basal-like). Furthermore, we evaluated the associations stratified by disease stage, post-diagnostic BMI, smoking status, alcohol consumption, and modified AHEI as secondary analyses. P values for heterogeneity were calculated using the Wald test.

All analyses were conducted using SAS software version 9.4 (SAS Institute, Cary, NC) with a two-sided P value of <0.05.

Results

During a median follow-up of 11.5 years, we documented 2,482 deaths from all-causes and 1,050 deaths from breast cancer among 8,863 eligible women who were diagnosed with breast cancer. The mean intake of SSBs after diagnosis was 0.25 serving/day (10th percentile=0 serving/day and 90th percentile=0.73 serving/day) and mean intake of ASBs was 0.49 serving/day (10th percentile=0 serving/day and 90th percentile=1.39 servings/day). Women who had higher SSB consumption after diagnosis were younger at time of diagnosis, more likely to smoke after diagnosis, and reported higher total energy intake (Table 1). They were less likely to be physically active after diagnosis, use aspirin after diagnosis, and use oral contraceptives before diagnosis. Women who had higher ASB consumption after diagnosis were younger at the time of diagnosis and had a higher BMI but a lower prevalence of smoking after diagnosis. They were more likely to use oral contraceptives before diagnosis.

Table 1.

Characteristics of women with breast cancer in the Nurses’ Health Study and Nurses’ Health Study II, according to consumption of sugar-sweetened and artificially sweetened beverages measured from the first food frequency questionnaire after diagnosis

Sugar-Sweetened Beverages Artificially-Sweetened Beverages
No consumption >0 to 1 serving/week >1 to 3 servings/week >3 servings/week No consumption >0 to 1 serving/week >1 to 3 servings/week >3 servings/week
Number 4,336 2,121 1,031 1,375 3,863 1,502 936 2,562
Mean
Sugar-sweetened beverage consumption, servings/day 0 0.1 0.3 1.3 0.4 0.2 0.2 0.2
Artificially-sweetened beverage consumption, servings/day 0.6 0.4 0.4 0.3 0 0.1 0.4 1.5
Coffee consumption, cups/day 1.7 1.7 1.7 1.4 1.6 1.7 1.8 1.6
Total fruit intake, servings/day 1.6 1.6 1.5 1.5 1.6 1.6 1.6 1.5
Total vegetable intake, servings/day 3.2 3.1 3.0 3.0 3.1 3.1 3.0 3.2
Alcohol consumption, g/day 6.3 5.4 5.0 4.6 5.6 5.9 6.2 5.5
Animal fat intake, % energy/day 14.2 14.8 14.7 14.1 13.9 14.4 14.7 15.0
Total fat intake, % energy/day 31.1 30.9 30.4 29.1 30.3 30.5 30.5 31.2
Total energy intake, kcal/day 1,596 1,729 1,816 2,016 1,724 1,679 1,715 1,749
Modified Alternative Healthy Eating Index*, score 49.7 47.3 45.4 43.2 48.5 48.1 47.3 46.0
Age at diagnosis, years 59.7 58.4 57.7 56.5 60.1 59.9 59.1 55.5
Body mass index, kg/m2 26.6 26.4 26.3 26.8 25.6 26.6 26.8 27.9
Physical activity, MET-hrs/wk 19.3 17.9 16.4 14.4 17.5 18.8 16.7 18.0
%
Current smokers 7 8 10 13 11 8 10 8
Ever oral contraceptive use 60 55 54 57 56 57 58 60
Ever hormone replacement therapy 47 49 49 47 48 48 50 47
Current use of aspirin 45 43 45 42 43 46 42 44
Premenopausal at diagnosis 26 26 27 26 27 27 26 26
Stage of breast cancer
I 61 59 56 59 59 60 61 60
II 29 30 33 31 30 30 29 30
III 10 11 11 10 11 10 10 10
Estrogen receptor status
Positive 78 77 74 76 77 76 77 77
Negative 16 17 20 18 17 18 16 17
Missing 6 6 6 6 6 6 7 6
Treatment
Radiotherapy 57 56 55 55 55 57 57 58
Chemotherapy 45 47 47 47 46 44 45 47
Hormone therapy 70 68 65 72 69 68 69 71
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*

not including SSB and alcohol scores

SSB and ASB consumption after diagnosis and survival

Post-diagnostic SSB consumption was associated with higher breast cancer-specific mortality (vs. no consumption, >1 to 3 servings/week, HR=1.31; 95%CI=1.09–1.58; >3 servings/week, HR=1.35; 95%CI=1.12–1.62; Ptrend=0.001) and all-cause mortality (vs. no consumption, >1 to 3 servings/week, HR=1.21; 95%CI=1.07–1.37; >3 servings/week, HR=1.28; 95%CI=1.13–1.45; Ptrend=0.0001) (Table 2). These associations were approximately linear (Figure S2–a and S2–b). After additional adjustment for modified AHEI (excluding SSB and alcohol scores), associations were somewhat attenuated for all-cause but not for breast cancer-specific mortality (Table 2). In addition, we observed similar associations after additional adjustment for intake of fruits and vegetables, total red and processed meat, coffee, fruit juice, total protein, dietary glycemic index, and both fruit juice and dietary glycemic load (Table S1). Among women who drank >3 servings/week of SSBs after diagnosis, there were 56.3 additional deaths per 10,000 person-years of follow-up compared with women who did not drink SSBs (risk difference=56.3 per 10,000 person-years, 95% CI: 26.8 to 85.8 per 10,000 person-years). The proportional reduction expected in breast cancer-specific mortality was 10.5% (95% CI: −1.0% to 21.7%) if all women did not drink SSBs after diagnosis and was 8.6% (95% CI: 0.4% to 16.8%) if all women drank ≤2 servings/month of SSBs after diagnosis. The PAR% for all-cause mortality was 10.4% (95% CI: 2.5% to 18.1%) if all women did not drink SSBs after diagnosis and was 6.6% (95% CI: 1.0% to 12.2%) if all women drank ≤2 servings/month of SSBs after diagnosis.

Table 2:

Post-diagnostic consumption levels of sugar-sweetened and artificially sweetened beverages in relation to mortality after breast cancer diagnosis (n=8,863) in the Nurses’ Health Study and Nurses’ Health Study II.

Consumption Levels Ptrend
No consumption >0 to 1 serving/week >1 to 3 servings/week >3 servings/week
Sugar-Sweetened Beverages
Breast cancer-specific mortality
No. of deaths 358 306 185 201
Person-year 35,936 31,541 17,002 16,622
 Model 1 1 0.88 (0.76–1.03) 0.99 (0.83–1.18) 1.17 (0.98–1.39) 0.01
 Model 2 1 1.07 (0.92–1.26) 1.31 (1.09–1.58) 1.35 (1.12–1.62) 0.001
 Model 2+ modified AHEI 1 1.07 (0.92–1.26) 1.30 (1.08–1.57) 1.34 (1.11–1.62) 0.002
All-cause mortality
No. of deaths 809 781 440 452
Person-year 35,936 31,541 17,002 16,622
 Model 1 1 1.07 (0.96–1.18) 1.13 (1.00–1.26) 1.32 (1.17–1.48) <0.0001
 Model 2 1 1.09 (0.99–1.21) 1.21 (1.07–1.37) 1.28 (1.13–1.45) 0.0001
 Model 2+ modified AHEI 1 1.07 (0.97–1.19) 1.17 (1.04–1.32) 1.22 (1.07–1.38) 0.003
Artificially Sweetened Beverages
Breast cancer-specific mortality
No. of deaths 394 208 117 331
Person-year 34,354 19,709 15,066 31,971
 Model 1 1 0.85 (0.72–1.01) 0.63 (0.51–0.77) 0.90 (0.77–1.04) 0.61
 Model 2 1 0.97 (0.82–1.15) 0.82 (0.66–1.01) 1.02 (0.87–1.19) 0.58
 Model 2+ modified AHEI 1 0.97 (0.82–1.16) 0.81 (0.66–1.01) 1.01 (0.86–1.18) 0.68
All-cause mortality
No. of deaths 905 526 340 711
Person-year 34,354 19,709 15,066 31,971
 Model 1 1 0.98 (0.88–1.09) 0.87 (0.77–0.99) 1.05 (0.95–1.16) 0.19
 Model 2 1 1.04 (0.93–1.16) 0.89 (0.79–1.02) 1.08 (0.97–1.20) 0.15
 Model 2+ modified AHEI 1 1.04 (0.93–1.16) 0.89 (0.78–1.02) 1.06 (0.95–1.18) 0.29
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Note. Model 1 was stratified by cohort and adjusted for age at diagnosis (year) and calendar year of diagnosis.

Model 2 was stratified by cohort and adjusted for age at diagnosis (year), calendar year of diagnosis, time between diagnosis and first FFQ (year), calendar year at start of follow-up of each-2-year questionnaire cycle, pre-diagnostic BMI (<20, 20 to <22.5, 22.5 to <25, 25.0 to <30, 30 to <35, ≥35 kg/m2, missing), BMI change after diagnosis (no change (≥−0.5 to ≤0.5 kg/m2), decrease (<−0.5 kg/m2), increase (>0.5–2 kg/m2), increase (>2 kg/m2), missing), post-diagnostic smoking (never, past, current 1–14/day, current 15–24/day, current ≥25/day, missing), post-diagnostic physical activity (<5, 5 to <11.5, 11.5 to <22, ≥22 MET-h/week, missing), oral contraceptive use (ever, never), post-diagnostic alcohol consumption (<0.15, 0.15 to <2.0, 2.0 to <7.5, ≥7.5 g/day), post-diagnostic total energy intake (quintiles, kcal/day), pre-diagnostic menopausal status, age at menopause, and postmenopausal hormone use (premenopausal, postmenopausal and age at menopause<50 year and never postmenopausal hormone use, postmenopausal and age at menopause<50 year and past postmenopausal hormone use, postmenopausal and age at menopause<50 year and current postmenopausal hormone use, postmenopausal and age at menopause≥50 year and never postmenopausal hormone use, postmenopausal and age at menopause≥50 year and past postmenopausal hormone use, postmenopausal and age at menopause≥50 year and current postmenopausal hormone use, missing), post-diagnostic aspirin use (never, past, current, missing), race (non-Hispanic white, other), stage of disease (I, II, III), ER/PR status (ER/PR positive, ER positive and PR negative, ER/PR negative, missing), radiotherapy (yes, no, missing), chemotherapy (yes, no, missing), and hormonal treatment (yes, no, missing).

The mortality risk did not differ substantially by consumption of post-diagnostic carbonated and non-carbonated SSBs (Table S2). Furthermore, both post-diagnostic carbonated caffeinated and caffeine-free soft drinks were associated with a higher all-cause mortality risk (Table S3).

Post-diagnostic ASB consumption was not associated with higher risk of breast cancer-specific mortality (vs. no consumption, >3 servings/week, HR=1.02; 95%CI=0.87–1.19; Ptrend=0.58) or all-cause mortality (>3 servings/week, HR=1.08; 95%CI=0.97–1.20; Ptrend=0.15) (Table 2).

Associations for post-diagnostic consumption of SSBs and ASBs, and breast cancer-specific and all-cause mortality remained similar when SSBs and ASBs were mutually adjusted for each other. For SSBs, compared with no consumption, the association of consumption with breast cancer-specific mortality was as follows: the HR was 1.33 (95%CI=1.11–1.61) for women consuming >1 to 3 servings/week and 1.36 (95%CI=1.13–1.65) for those consuming >3 servings/week (Ptrend=0.0007); and for all-cause mortality, vs. no consumption, HR was 1.23 (95%CI=1.09–1.38) for women consuming >1 to 3 servings/week, and 1.31 (95%CI=1.15–1.48) for women consuming >3 servings/week (Ptrend<0.0001).

To examine changes in intake from the last FFQ reported before diagnosis to the FFQs reported after diagnosis, we cross-classified pre-diagnostic and post-diagnostic intake. Compared with women who reported low pre-diagnostic and low post-diagnostic SSB consumption, breast cancer-specific mortality was higher among women who had low pre-diagnostic and high post-diagnostic SSB consumption (HR=1.25, 95%CI=1.04–1.50), and among those who had high pre-diagnostic and high post-diagnostic SSB consumption (HR=1.33, 95%CI=1.12–1.58). We did not observe a significantly increased risk among women who had high pre-diagnostic and low post-diagnostic intake (Table 3). Associations were similar for all-cause mortality (Table 3).

Table 3.

Changes in sugar-sweetened beverage consumption from pre- to post-diagnosis in relation to mortality after breast cancer diagnosis (n=8,490).

Post-diagnostic sugar-sweetened beverage consumption
≤1 servings/week >1 servings/week
No. of deaths/ Person-year HR (95% CI) No. of deaths/ Person-year HR (95% CI)
Breast cancer-specific mortality
Pre-diagnostic sugar-sweetened beverage consumption ≤1 servings/week 504/52,846 1 157/14,329 1.25 (1.04–1.50)
>1 servings/week 122/11,299 1.00 (0.81–1.22) 206/17,426 1.33 (1.12–1.58)
All-cause mortality
Pre-diagnostic sugar-sweetened beverage consumption ≤1 servings/week 1,244/52,846 1 405/14,329 1.15 (1.02–1.29)
>1 servings/week 251/11,299 0.98 (0.85–1.12) 437/17,426 1.22 (1.08–1.36)
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Note. Models were stratified by cohort and adjusted for age at diagnosis (year), calendar year of diagnosis, time between diagnosis and first FFQ (year), calendar year at start of follow-up of each-2-year questionnaire cycle, pre-diagnostic BMI (<20, 20 to <22.5, 22.5 to <25, 25.0 to <30, 30 to <35, ≥35 kg/m2, missing), BMI change after diagnosis (no change (≥−0.5 to ≤0.5 kg/m2), decrease (<−0.5 kg/m2), increase (>0.5–2 kg/m2), increase (>2 kg/m2), missing), post-diagnostic smoking (never, past, current 1–14/day, current 15–24/day, current ≥25/day, missing), post-diagnostic physical activity (<5, 5 to <11.5, 11.5 to <22, ≥22 MET-h/week, missing), oral contraceptive use (ever, never), post-diagnostic alcohol consumption (<0.15, 0.15 to <2.0, 2.0 to <7.5, ≥7.5 g/day), post-diagnostic total energy intake (quintiles, kcal/day), pre-diagnostic menopausal status, age at menopause, and postmenopausal hormone use (premenopausal, postmenopausal and age at menopause<50 year and never postmenopausal hormone use, postmenopausal and age at menopause<50 year and past postmenopausal hormone use, postmenopausal and age at menopause<50 year and current postmenopausal hormone use, postmenopausal and age at menopause≥50 year and never postmenopausal hormone use, postmenopausal and age at menopause≥50 year and past postmenopausal hormone use, postmenopausal and age at menopause≥50 year and current postmenopausal hormone use, missing), post-diagnostic aspirin use (never, past, current, missing), race (non-Hispanic white, other), stage of disease (I, II, III), ER/PR status (ER/PR positive, ER positive and PR negative, ER/PR negative, missing), radiotherapy (yes, no, missing), chemotherapy (yes, no, missing), and hormonal treatment (yes, no, missing).

Replacing one serving/day of SSB consumption with an isovolumetric serving (355 mL) of ASBs, fruit juice, skim/low-fat milk, or whole milk was not associated with changes in breast cancer-specific or all-cause mortality risk (Figure 1). However, replacing one serving/day of SSB consumption with an isovolumetric serving of coffee or tea was associated with 18% and 15% lower risk of breast cancer-specific mortality, respectively. Replacing one serving/day of SSB consumption with an isovolumetric serving of coffee, tea, or water was associated with 19%, 17% and 9% lower risk of all-cause mortality, respectively.

Figure 1.

Figure 1.

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Multivariable hazard ratios and 95% confidence intervals for breast cancer-specific and all-cause mortality associated with replacement of sugar-sweetened beverages by other beverages

We also examined whether the associations of SSBs and ASBs with mortality differed by tumor IR status, ER status, or molecular subtypes. We observed stronger associations between post-diagnostic SSB consumption and all-cause mortality among women who had IR-negative tumors compared with those who had IR-positive tumors (p for heterogeneity=0.04) (Table 4). The association between SSB or ASB consumption and mortality did not differ by ER status (Table 4) or molecular subtypes (Table5).

Table 4:

Post-diagnostic consumption levels of sugar-sweetened and artificially sweetened beverages in relation to mortality after breast cancer diagnosis in the Nurses’ Health Study and Nurses’ Health Study II, stratified by insulin receptor (n=2,480) and estrogen receptor (n=8,322) status.

No. of deaths Consumption Levels Ptrend P for Heterogeneity
No consumption >0 to 1 serving/week >1 to 3 servings/week >3 servings/week
Sugar-Sweetened Beverages
Breast cancer-specific mortality
Insulin receptor positive 172 1 1.20 (0.81–1.79) 1.32 (0.83–2.08) 1.11 (0.65–1.91) 0.83
Insulin receptor negative 212 1 0.74 (0.51–1.08) 0.91 (0.59–1.41) 1.43 (0.93–2.18) 0.01 0.32
Estrogen receptor positive 755 1 1.12 (0.93–1.34) 1.26 (1.00–1.57) 1.39 (1.11–1.72) 0.005
Estrogen receptor negative 209 1 0.86 (0.58–1.27) 1.65 (1.11–2.45) 1.75 (1.15–2.67) 0.001 0.64
All-cause mortality
Insulin receptor positive 457 1 1.13 (0.89–1.44) 1.20 (0.91–1.59) 1.07 (0.77–1.47) 0.86
Insulin receptor negative 543 1 0.91 (0.72–1.14) 1.04 (0.80–1.36) 1.52 (1.16–1.99) 0.0001 0.04
Estrogen receptor positive 1,817 1 1.10 (0.98–1.24) 1.19 (1.03–1.37) 1.37 (1.19–1.58) <0.0001
Estrogen receptor negative 440 1 1.19 (0.92–1.55) 1.64 (1.22–2.21) 1.55 (1.14–2.10) 0.009 0.66
Artificially Sweetened Beverages
Breast cancer-specific mortality
Insulin receptor positive 172 1 1.35 (0.89–2.04) 0.82 (0.48–1.39) 0.72 (0.47–1.10) 0.03
Insulin receptor negative 212 1 1.02 (0.68–1.53) 1.10 (0.69–1.74) 1.13 (0.79–1.61) 0.49 0.02
Estrogen receptor positive 755 1 0.92 (0.75–1.12) 0.78 (0.60–1.00) 0.98 (0.82–1.18) 0.78
Estrogen receptor negative 209 1 1.06 (0.72–1.55) 1.00 (0.62–1.61) 1.08 (0.74–1.57) 0.74 0.61
All-cause mortality
Insulin receptor positive 457 1 1.12 (0.87–1.44) 0.75 (0.54–1.03) 0.87 (0.67–1.14) 0.16
Insulin receptor negative 543 1 1.07 (0.83–1.38) 1.13 (0.87–1.48) 1.23 (0.98–1.55) 0.08 0.02
Estrogen receptor positive 1,817 1 0.98 (0.86–1.11) 0.87 (0.74–1.01) 1.06 (0.94–1.19) 0.20
Estrogen receptor negative 440 1 1.26 (0.97–1.64) 1.15 (0.84–1.57) 1.06 (0.81–1.39) 0.84 0.56
Open in a new tab

Note. Models were stratified by cohort and adjusted for age at diagnosis (year), calendar year of diagnosis, time between diagnosis and first FFQ (year), calendar year at start of follow-up of each-2-year questionnaire cycle, pre-diagnostic BMI (<20, 20 to <22.5, 22.5 to <25, 25.0 to <30, 30 to <35, ≥35 kg/m2, missing), BMI change after diagnosis (no change (≥−0.5 to ≤0.5 kg/m2), decrease (<−0.5 kg/m2), increase (>0.5–2 kg/m2), increase (>2 kg/m2), missing), post-diagnostic smoking (never, past, current 1–14/day, current 15–24/day, current ≥25/day, missing), post-diagnostic physical activity (<5, 5 to <11.5, 11.5 to <22, ≥22 MET-h/week, missing), oral contraceptive use (ever, never), post-diagnostic alcohol consumption (<0.15, 0.15 to <2.0, 2.0 to <7.5, ≥7.5 g/day), post-diagnostic total energy intake (quintiles, kcal/day), pre-diagnostic menopausal status, age at menopause, and postmenopausal hormone use (premenopausal, postmenopausal and age at menopause<50 year and never postmenopausal hormone use, postmenopausal and age at menopause<50 year and past postmenopausal hormone use, postmenopausal and age at menopause<50 year and current postmenopausal hormone use, postmenopausal and age at menopause≥50 year and never postmenopausal hormone use, postmenopausal and age at menopause≥50 year and past postmenopausal hormone use, postmenopausal and age at menopause≥50 year and current postmenopausal hormone use, missing), post-diagnostic aspirin use (never, past, current, missing), race (non-Hispanic white, other), stage of disease (I, II, III), ER/PR status (ER/PR positive, ER positive and PR negative, ER/PR negative, missing), radiotherapy (yes, no, missing), chemotherapy (yes, no, missing), and hormonal treatment (yes, no, missing). For Estrogen receptor status analyses, we did not adjust for ER/PR status.

Table 5:

Post-diagnostic consumption levels of sugar-sweetened and artificially sweetened beverages in relation to mortality after breast cancer diagnosis in the Nurses’ Health Study and Nurses’ Health Study II, stratified by molecular subtypes of breast cancer.

No. of deaths Consumption Levels Ptrend P for Heterogeneity
No consumption >0 to 1 serving/week >1 to 3 servings/week >3 servings/week
Sugar-Sweetened Beverages
Breast cancer-specific mortality
Luminal A 305 1 1.16 (0.86–1.56) 1.32 (0.92–1.89) 1.61 (1.13–2.29) 0.009
Luminal B 153 1 0.90 (0.59–1.37) 1.19 (0.73–1.95) 0.96 (0.57–1.63) 0.93
HER2-enriched 45 1 1.14 (0.40–3.23) 2.51 (0.72–8.67) 1.95 (0.55–6.87) 0.30
Basal-like 45 1 0.90 (0.29–2.82) 1.21 (0.39–3.74) 5.58 (1.85–16.88) 0.0004 0.88
All-cause mortality
Luminal A 793 1 1.04 (0.86–1.24) 1.21 (0.97–1.50) 1.42 (1.13–1.78) 0.0009
Luminal B 341 1 1.05 (0.79–1.38) 1.09 (0.78–1.53) 1.07 (0.76–1.51) 0.73
HER2-enriched 83 1 0.88 (0.45–1.72) 1.16 (0.51–2.60) 1.15 (0.50–2.68) 0.63
Basal-like 99 1 1.62 (0.78–3.35) 1.59 (0.75–3.36) 2.50 (1.16–5.42) 0.04 0.74
Artificially Sweetened Beverages
Breast cancer-specific mortality
Luminal A 305 1 0.82 (0.59–1.12) 0.79 (0.54–1.15) 0.73 (0.54–0.98) 0.08
Luminal B 153 1 1.25 (0.77–2.03) 0.96 (0.54–1.69) 1.23 (0.82–1.84) 0.40
HER2-enriched 45 1 0.76 (0.26–2.19) 1.70 (0.49–5.93) 0.30 (0.08–1.08) 0.06
Basal-like 45 1 0.90 (0.29–2.74) 0.96 (0.25–3.61) 1.20 (0.46–3.14) 0.56 0.25
All-cause mortality
Luminal A 793 1 0.93 (0.77–1.13) 0.81 (0.64–1.03) 0.98 (0.81–1.18) 0.91
Luminal B 341 1 1.14 (0.82–1.59) 1.22 (0.87–1.72) 1.36 (1.03–1.81) 0.04
HER2-enriched 83 1 0.86 (0.43–1.72) 1.34 (0.60–2.96) 0.52 (0.24–1.16) 0.14
Basal-like 99 1 1.13 (0.56–2.28) 1.09 (0.49–2.40) 1.49 (0.79–2.82) 0.19 0.33
Open in a new tab

Note. Models were stratified by cohort and adjusted for age at diagnosis (year), calendar year of diagnosis, time between diagnosis and first FFQ (year), calendar year at start of follow-up of each-2-year questionnaire cycle, pre-diagnostic BMI (<20, 20 to <22.5, 22.5 to <25, 25.0 to <30, 30 to <35, ≥35 kg/m2, missing), BMI change after diagnosis (no change (≥−0.5 to ≤0.5 kg/m2), decrease (<−0.5 kg/m2), increase (>0.5–2 kg/m2), increase (>2 kg/m2), missing), post-diagnostic smoking (never, past, current 1–14/day, current 15–24/day, current ≥25/day, missing), post-diagnostic physical activity (<5, 5 to <11.5, 11.5 to <22, ≥22 MET-h/week, missing), oral contraceptive use (ever, never), post-diagnostic alcohol consumption (<0.15, 0.15 to <2.0, 2.0 to <7.5, ≥7.5 g/day), post-diagnostic total energy intake (quintiles, kcal/day), pre-diagnostic menopausal status, age at menopause, and postmenopausal hormone use (premenopausal, postmenopausal and age at menopause<50 year and never postmenopausal hormone use, postmenopausal and age at menopause<50 year and past postmenopausal hormone use, postmenopausal and age at menopause<50 year and current postmenopausal hormone use, postmenopausal and age at menopause≥50 year and never postmenopausal hormone use, postmenopausal and age at menopause≥50 year and past postmenopausal hormone use, postmenopausal and age at menopause≥50 year and current postmenopausal hormone use, missing), post-diagnostic aspirin use (never, past, current, missing), race (non-Hispanic white, other), stage of disease (I, II, III), radiotherapy (yes, no, missing), chemotherapy (yes, no, missing), and hormonal treatment (yes, no, missing).

Sensitivity analyses

We examined associations with the first post-diagnostic measure of SSB intake, rather than cumulative updating (Table S4). There was a high correlation between first post-diagnostic SSB consumption and the cumulative average of post-diagnostic SSB consumption (r=0.90) and the results were similar to those provided Table 2. We also evaluated the associations with simple updates of dietary intake (Table S5) as well as accounting for left truncation time since diagnosis (Table S6). The results were very similar across several different analytic approaches.

Higher SSB consumption was associated with higher breast cancer-specific and all-cause mortality risk among women with stage I or II breast cancer. However, there was no significant interaction (Table S7). Higher SSB consumption was associated with a higher breast cancer-specific mortality risk among women who had a post-diagnostic BMI ≥25 kg/m2 (vs. no consumption, > 3 servings/week, HR=1.46, 95% CI=1.14–1.86), but not among those who had a post-diagnostic BMI<25 kg/m2 (vs. no consumption, > 3 servings/week, HR =1.15, 95% CI=0.85–1.54), (P for heterogeneity 0.05) (Table S8). High consumption of SSBs was associated with higher risk of breast cancer-specific and all-cause mortality among both never smokers and ever smokers (Table S9). Furthermore, the associations between post-diagnostic SSB or ASB consumption and mortality did not differ by alcohol consumption (Table S10) or AHEI after diagnosis (Table S11).

Discussion

This large prospective study with long time follow-up showed that higher SSB consumption after breast cancer diagnosis was associated with higher breast cancer-specific and overall mortality risk among breast cancer survivors. These findings are similar to what Malik et al. observed in a prior analysis among cancer-free women using the NHS data (21). In contrast, higher ASB consumption was not associated with higher breast cancer-specific or all-cause mortality risk among women with breast cancer. Replacing SSBs with an isovolumetric serving of ASBs, fruit juice, skim/low-fat milk, or whole milk was not associated with lower mortality risk. Replacement of SSBs with an isovolumetric serving of coffee or tea was associated with lower risk of breast-cancer specific mortality and replacement with coffee, tea, or water was associated with a lower risk of overall mortality.

High SSB consumption increases postprandial blood glucose and insulin levels (40). Substantial evidence suggests a possible link between hyperglycemia and hyperinsulinemia and a poorer breast cancer prognosis (7, 8, 13). In nondiabetic women with breast cancer (15), high levels of circulating insulin (>13 μIU/ml) before breast cancer treatment were associated with worse disease progression. Hyperglycemia increases tumor cell migration which affects cancer survival (41). In addition, increased insulin secretion in response to glucose acts as a growth factor and results in tumor growth (42). Thus, the elevation in postprandial glucose associated with SSB consumption may affect tumor cell growth. However, our results were significant after adjusting for dietary glycemic index and glycemic load. Overweight and obesity also have been associated with a poorer breast cancer prognosis (9, 10), and because SSB consumption is associated with weight gain (43), it could further increase the risk of breast cancer mortality by this pathway. Our results were significant when we adjusted for prediagnostic BMI and postdiagnostic weight change, However, we observed higher risk of mortality among women with overweight or obesity. Further confirmatory studies are warranted.

Finally, we found that replacing SSBs with coffee, tea, or water was associated with a lower risk of mortality. However, substituting other low- or high-calorie beverages including ASBs, fruit juice, skim/low-fat milk, or whole milk for SSBs was not associated with significantly improved survival. Our recent study among breast cancer survivors showed that higher coffee consumption after diagnosis was associated with lower breast cancer and all-cause mortality, and higher tea consumption after diagnosis was associated with lower all-cause mortality (44). Replacing SSBs or fruit juice with water, coffee, tea, ASBs, or low-fat milk was also associated with lower weight gain among healthy participants (45). In addition, replacing SSBs with coffee was associated with lower risk of diabetes (5). Given the biological link between obesity, diabetes, and poor breast cancer outcomes (9–12), changing beverage drinking patterns by replacing SSBs with water, coffee, or tea, and reducing SSB consumption, may be a potentially practical strategy to reduce mortality among women with breast cancer.

Evaluating cumulative SSB and ASB consumption every 4 years from self-reported dietary intake before and after diagnosis as well as the large number of breast cancer survivors, with medical confirmation of cancer endpoints and long duration of follow-up, are strengths of our study. In addition, we controlled for a comprehensive list of key predictors of breast cancer survival, including lifestyle factors and extensive medical history.

Potential limitations of our study need to be considered. Despite controlling for several factors that may affect the association between SSB or ASB consumption and survival, we cannot rule out the possibility of residual confounding in our observational study. In addition, the NHS and NHSII participants were predominately non-Hispanic white and educated. Women with higher SSB consumption tended to have unhealthy dietary intake and lifestyle habits, which could overestimate the association between SSB consumption and mortality. However, adjusting for lifestyle factors resulted in stronger associations with breast cancer-specific mortality. Furthermore, the mean time from breast cancer diagnosis to the first post-diagnostic FFQ was 3.3 years, and we were not able to look at survival shortly after diagnosis.

In this study we observed that higher SSB consumption after a breast cancer diagnosis was associated with greater breast cancer-specific and all-cause mortality. Replacing SSBs with coffee, tea, or water may help women with early stage breast cancer to improve life expectancy. Given our findings and other evidence (21), it is prudent for practitioners and public health officials to promote limiting or eliminating SSB consumption to reduce breast cancer mortality in the US and worldwide. Further research is needed to understand the pathways driving these associations.

Supplementary Material

Supplementary material

Acknowledgments

We would like to thank the participants and staff of the NHS and NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY.

Funding information: The study was supported by the National Institutes of Health Grants (U01 CA176726, UM1 CA186107), American Institute for Cancer Research (AICR) to MSF, and the Breast Cancer Research Foundation (BCRF) to WCW. The study sponsors were not involved in the study design and collection, analysis and interpretation of data, or the writing of the article or the decision to submit it for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors were independent from study sponsors and assume full responsibility for analyses and interpretation of the data.

Footnotes

The abstract of the manuscript has been presented at the American Institute for Cancer Research Conference, 2019.

Competing interests: Michelle D. Holmes reports grants from FHI Solutions, personal fees from Arla Foods, and nonfinancial support from Bayer AG, all outside the submitted work. The remaining authors made no disclosures.

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