Low-carbohydrate, high-protein diet score and risk of incident cancer; a prospective cohort study

  • Lena Maria Nilsson1Email author,

    Affiliated with

    • Anna Winkvist2,

      Affiliated with

      • Ingegerd Johansson3,

        Affiliated with

        • Bernt Lindahl4,

          Affiliated with

          • Göran Hallmans4,

            Affiliated with

            • Per Lenner5 and

              Affiliated with

              • Bethany Van Guelpen6

                Affiliated with

                Nutrition Journal201312:58

                DOI: 10.1186/1475-2891-12-58

                Received: 12 February 2013

                Accepted: 2 May 2013

                Published: 7 May 2013

                Abstract

                Background

                Although carbohydrate reduction of varying degrees is a popular and controversial dietary trend, potential long-term effects for health, and cancer in specific, are largely unknown.

                Methods

                We studied a previously established low-carbohydrate, high-protein (LCHP) score in relation to the incidence of cancer and specific cancer types in a population-based cohort in northern Sweden. Participants were 62,582 men and women with up to 17.8 years of follow-up (median 9.7), including 3,059 prospective cancer cases. Cox regression analyses were performed for a LCHP score based on the sum of energy-adjusted deciles of carbohydrate (descending) and protein (ascending) intake labeled 1 to 10, with higher scores representing a diet lower in carbohydrates and higher in protein. Important potential confounders were accounted for, and the role of metabolic risk profile, macronutrient quality including saturated fat intake, and adequacy of energy intake reporting was explored.

                Results

                For the lowest to highest LCHP scores, 2 to 20, carbohydrate intakes ranged from median 60.9 to 38.9% of total energy intake. Both protein (primarily animal sources) and particularly fat (both saturated and unsaturated) intakes increased with increasing LCHP scores. LCHP score was not related to cancer risk, except for a non-dose-dependent, positive association for respiratory tract cancer that was statistically significant in men. The multivariate hazard ratio for medium (9–13) versus low (2–8) LCHP scores was 1.84 (95% confidence interval: 1.05-3.23; p-trend = 0.38). Other analyses were largely consistent with the main results, although LCHP score was associated with colorectal cancer risk inversely in women with high saturated fat intakes, and positively in men with higher LCHP scores based on vegetable protein.

                Conclusion

                These largely null results provide important information concerning the long-term safety of moderate carbohydrate reduction and consequent increases in protein and, in this cohort, especially fat intakes. In order to determine the effects of stricter carbohydrate restriction, further studies encompassing a wider range of macronutrient intakes are warranted.

                Keywords

                Diet Cancer Macronutrients Carbohydrate intake Protein intake Fat intake Cohort study

                Introduction

                In recent years, low-carbohydrate diets have emerged as a controversial and popular means of achieving weight loss and controlling diabetes. In Sweden, extensive positive media support for dietary carbohydrate restriction has occurred over the past 5–7 years [1]. During the same time period, in northern Sweden, a complete reversal of previous reductions in fat intake and cholesterol levels has been reported in the general population [2, 3]. Discerning the potential long-term health effects of carbohydrate restriction, not only of stringent low-carbohydrate diets but also of more modest carbohydrate reduction, is thus an important challenge in nutrition research today.

                For weight loss, low-carbohydrate diets, both extremely or more modestly reduced in carbohydrate (e.g. E% carbohydrates/protein/fat = 9/28/63 [4], and 44/18/38 [5], respectively) have been found to be at least as effective as traditional low-calorie/low-fat diets over a period of up to two years [57]. The results of randomized trials have also tended to support improved metabolic parameters and blood lipids [811], but elevated markers of stress and inflammation [1113] in subjects following a low-carbohydrate diet. These alterations might influence the risk of major chronic diseases such as cardiovascular disease and cancer [11, 14]. However, from a long-term perspective, the effects of carbohydrate reduction of varying degrees, and consequent increased consumption of various types of protein and/or fat, for health outcomes, and cancer in specific, are largely unknown.

                The results of previous epidemiological studies in general populations have suggested positive or null associations between low-carbohydrate diet scores, particularly scores representing diets higher in foods of animal origin, and all-cause, cardiovascular, and cancer mortality [1519]. Prospective studies of cardiovascular disease incidence have reported either an increased risk [20], or reduced risk for plant-based [21], carbohydrate-restricted diets. The only previous prospective study to address overall cancer incidence found null associations for both animal- and plant-based low-carbohydrate diets [22]. An increased risk of incident breast cancer has been observed for a dietary pattern characterized by a low intake of bread and fruit juice and a high intake of processed meat, fish, butter, other animal fats, and margarine [23]. In contrast, a plant-based, low-carbohydrate diet has been related to a reduced risk of estrogen-receptor-negative breast cancer [24].

                Given the high rates of overweight and obesity worldwide, and the widespread popularity of low-carbohydrate diets, evaluation of the long-term safety of carbohydrate restriction of varying degrees is crucial. The aim of the present study was to investigate macronutrient distribution, in particular a previously established low-carbohydrate, high-protein (LCHP) score [1620], in relation to the risk of incident cancer and specific types of cancer in a large, population-based cohort in northern Sweden.

                Methods

                Study design and cohort

                The Västerbotten Intervention Programme (VIP) is an ongoing, population-based, prospective cohort study and health intervention, including residents of the northern Swedish county of Västerbotten turning 40, 50 and 60 years of age. Until 1996, 30 year olds were also included. The VIP protocol, described in detail elsewhere [25, 26], includes a health examination, with measurement of a number of potential health risk factors, such as an oral glucose tolerance test, as well as a participant-administered diet and lifestyle questionnaire. For the period assessed in this study, 1990–2007, the average recruitment rate was 59% . The VIP food frequency questionnaire (FFQ) has been validated by 24-hour-recall interviews [27], and by biomarkers in blood samples collected from VIP participants [28, 29]. Cancer incidences comparable to those of the general population in Västerbotten indicate a truly population-based cohort [30], and no selection bias of importance has been demonstrated [31].

                As of December 31, 2007, when cases of incident cancer were identified for the present study, a total of 82,879 participation occasions (66,001 individuals) had been registered within the VIP cohort. From these we excluded 1,328 participation occasions with missing data for more than 10% of the items in the FFQ and/or portion size, 32 participation occasions with missing height or weight data, 9 participation occasions with a body mass index (BMI) <10, and 6,112 participation occasions with food intake level (FIL) in the lowest 5th percentile or the highest 2.5th percentile (specific to sex and FFQ version and based on the first sampling occasion for subjects with repeated measures), and 12,816 participants with more than one sampling occasion (most recent sampling occasion excluded). The final study population thus included 62,582 participants (31,397 men, 31,185 women).

                Identification of cancer cases

                A total of 3,059 incident, prospective cancer cases without previous cancer diagnosis, except non-melanoma skin cancer, were identified through linkage with the regional branch of the national cancer registry, with site-specific cancers defined according to the International Classification of Diseases, ICD-7 [32], as follows: prostate (177), breast (170), colorectum (153, 154.0), respiratory tract (161, 162), urinary tract (181), non-Hodgkin’s lymphoma (200, 202), endometrium (172), malignant melanoma (190), leukemia (204–207), pancreas (157), ovary 175.0), stomach (151), multiple myeloma (203) and renal cell (180.0, 180.9).

                Low-carbohydrate, high-protein score

                Dietary intake of macronutrients was calculated from food frequency questionnaires with 9 fixed response alternatives ranging from never to ≥4 times per day and including 84 (years 1990–1996) or 65 (years 1997–2007) food items, as well as photo-based portion-size estimations for meat/fish, potatoes/pasta/rice, and vegetables [26]. The 65-item FFQ was an abbreviated version of the 84-item FFQ, in which some food items had been merged and some deleted as described elsewhere [33] (p 26). All intake variables except ethanol were energy adjusted according to the residual method [34].

                Descending deciles, or tenths, of energy-adjusted carbohydrate and ascending deciles of energy-adjusted protein were labeled 1 to 10 and summed to create an LCHP score (2–20 points), a model employed in several previous studies [1620]. The LCHP score is independent of total energy intake, due to the isocaloric nature of carbohydrate and protein, and it allows separate consideration of the amount and quality of fat consumed. LCHP scores were also categorized into low (2–8 points), medium (9–13 points) and high (14–20 points), in order to approximate equally sized groups.

                Statistical analyses

                Differences in baseline characteristics of the study subjects according to LCHP score category were determined by the Kruskal-Wallis test. Spearman’s correlation coefficients were determined between LCHP score and intakes of fat and saturated fat and sex-specific analyses were done. Hazard ratios (HR) and 95% confidence intervals (CI) for overall cancer incidence and for all types of cancer with at least 50 cases were calculated by Cox proportional hazard regression models. HR are presented for medium and high versus low LCHP scores or per 1-point increase in LCHP score. p-trend were calculated per 1-point increase in LCHP score. Age and BMI deviated from the proportional hazard assumption according to Schoenfeld’s test. Age was thus examined in 10-year intervals, included as strata in the crude and multivariate models, and BMI was dichotomized according to obesity (BMI ≥30 kg/m2).

                Of an extensive list of potential confounding variables, only saturated fat intake altered any HR for LCHP by more than 10% when included in a bivariate model. The final multivariate model included age (10-year intervals, strata), obesity (BMI ≥ 30 kg/m2, yes/no), sedentary lifestyle (no physical activity in exercise clothes, yes/no), education (lack of postsecondary, yes/no), current smoking (yes/no), and intake of alcohol (g/day), saturated fat (energy-adjusted residual), and total energy intake (Kcal/day), all selected for their theoretical importance. Missing data, present only for some categorical covariates, i.e. education, N = 377 (0.6%), sedentary lifestyle, N = 1,751 (2.8%), smoking, N = 706 (1.1%), were treated as dummy variables.

                Subgroup analyses were conducted for metabolic risk profile, defined as at least one of, versus none of, obesity, diabetes or impaired glucose tolerance. Diabetes was defined as fasting plasma glucose ≥7.0 mmol/l and/or post-load plasma glucose ≥12.2 mmol/l, and impaired glucose tolerance was defined as fasting plasma glucose ≥6.1 mmol/l and/or post-load plasma glucose ≥8.9 mmol/l. Subgroups based on saturated fat intake (energy adjusted and stratified at the median) and energy reporting (adequate versus inadequate, according to the Goldberg cut-off, modified as described in our previous report [19]) were also examined. The subgroup analyses were limited to overall cancer incidence and cancer of the prostate, breast and colorectum, which were the most common sites. Heterogeneity was tested by Chi-square analysis. A sub-analysis was also performed for the time period prior to the shift in macronutrient intake in the VIP population [2] (follow-up to December 31, 2002). All tests were two-sided, and p-values <0.05 were considered statistically significant.

                Ethical considerations

                The study was approved by the Regional Ethical Review Board of Northern Sweden (dossier number 07-165 M). All study subjects provided written informed consent, and the study was conducted in accordance with the Declaration of Helsinki.

                Results

                Follow-up times ranged from 1 day to 17.9 years, median 9.7 years. Macronutrient intakes for the lowest to highest LCHP scores (2–20 points) ranged from median 60.9 to 38.9% of total energy intake for carbohydrate, 11.3 to 18.9% for protein, and 26.7 to 41.5% for fat. Relationships between baseline characteristics and LCHP score are presented in Table 1. High LCHP scores were associated with younger age (not apparent in medians due to sampling at 10-year age intervals) and higher BMI, prevalence of current smokers, sedentary lifestyle (women only) and alcohol intake. Lack of postsecondary education was more common in men with low LCHP scores and in women with high scores. LCHP scores were positively related to intake of animal protein, but negatively related to plant protein. For carbohydrate and fat, associations were consistent in sucrose and whole grain and saturated and unsaturated fat, respectively. Spearman correlation coefficients for LCHP score and energy-adjusted fat, saturated fat and unsaturated fat intakes were 0.51, 0.45, and 0.46, respectively.
                Table 1

                Baseline characteristics of Västerbotten Intervention Programme participants according to low-carbohydrate, high-protein (LCHP) score

                 

                n

                Low1, 2-8

                n

                Medium1, 9-13

                n

                High1, 14-20

                p2

                Men

                       

                Age at recruitment, years

                9,811

                50 (40–60)

                12,909

                50 (40–51)

                8,677

                40 (40–50)

                ≤0.001

                Follow-up time, years

                9,811

                9.4 (6.4-12.7)

                12,909

                9.6 (6.1-12.8)

                8,677

                9.6 (5.2-13.1)

                0.206

                BMI, kg/m 2

                9,811

                25.4 (23.7-27.5)

                12,909

                25.6 (23.8-27.8)

                8,677

                26.1 (24.1-28.4)

                ≤0.001

                Current smokers

                9,672

                1,579 (16.3)

                12,728

                2,218 (17.4)

                8,546

                1,672 (19.6)

                ≤0.001

                No postsecondary education

                9,753

                7,811 (80.1)

                12,844

                9,957 (77.5)

                8,626

                6,587 (76.4)

                ≤0.001

                Sedentary lifestyle3

                9,551

                6,633 (69.4)

                12,599

                8,731 (69.3)

                8,371

                5,860 (70.0)

                0.540

                Energy intake, kcal/day

                9,811

                2,002 (1,672-2,397)

                12,909

                2,001 (1,667-2,410)

                8,677

                2,004 (1,672-2,415)

                0.475

                Ethanol intake, g/day

                9,811

                4.3 (1.1-7.5)

                12,909

                4.9 (1.8-8.3)

                8,677

                5.3 (2.2-8.6)

                ≤0.001

                Carbohydrate intake,% of energy

                9,811

                53.5 (50.7-56.6)

                12,909

                48.1 (44.7-51.0)

                8,677

                43.6 (40.6-46.2)

                ≤0.001

                Whole grain intake,% of energy

                9,811

                16.5 (12.2-30.0)

                12,909

                15.3 (11.1-19.7)

                8,677

                13.3 (9.4-17.3)

                ≤0.001

                Sucrose intake,% of energy

                9,811

                8.3 (6.3-10.8)

                12,909

                6.2 (4.6-8.0)

                8,677

                4.8 (3.5-6.3)

                ≤0.001

                Protein intake,% of energy

                9,811

                12.8 (11.9-13.7)

                12,909

                14.4 (13.3-15.4)

                8,677

                16.2 (15.3-17.3)

                ≤0.001

                Animal protein intake,% of energy

                9,811

                8.3 (7.3-9.1)

                12,909

                10.2 (9.3-11.0)

                8,677

                12.4 (11.5-13.6)

                ≤0.001

                Plant protein intake,% of energy

                9,811

                4.5 (3.9-5.2)

                12,909

                4.1 (3.5-4.7)

                8,677

                3.7 (3.2-4.2)

                ≤0.001

                Fat intake,% of energy

                9,811

                32.7 (29.4-36.0)

                12,909

                36.7 (32.9-41.1)

                8,677

                39.4 (36.4-42.7)

                ≤0.001

                Saturated fat intake,% of energy

                9,811

                13.5 (11.7-15.4)

                12,909

                15.4 (13.4-17.7)

                8,677

                16.6 (14.9-18.5)

                ≤0.001

                Unsaturated fat intake,% of energy

                9,811

                18.9 (17.0-20.9)

                12,909

                21.1 (18.8-23.7)

                8,677

                22.6 (20.7-24.8)

                ≤0.001

                Women

                       

                Age at recruitment, years

                9,985

                50 (40–60)

                12,430

                50 (40–50)

                8,770

                50 (40–50)

                ≤0.001

                Follow-up time, years

                9,985

                9.7 (6.7-12.8)

                12,430

                9.9 (6.6-13.0)

                8,770

                9.9 (5.9-13.2)

                0.206

                BMI, kg/m 2

                9,985

                24.4 (22.3-27.2)

                12,430

                24.4 (22.2-27.2)

                8,770

                24.7(22.4-27.8)

                ≤0.001

                Current smokers

                9,903

                1,661 (16.8)

                12,319

                2,325 (18.9)

                8,708

                2,152 (24.7)

                ≤0.001

                No postsecondary education

                9,913

                6,827 (68.9)

                12,357

                8,612 (69.7)

                8,712

                6,189 (71.0)

                0.005

                Sedentary lifestyle3

                9,749

                6,419 (65.8)

                12,116

                8,121 (67.0)

                8,445

                5,884 (69.7)

                ≤0.001

                Energy intake, kcal/day

                9,985

                1,509 (1,273-1,787)

                12,430

                1,531 (1,294-1,815)

                8,770

                1,510 (1,268-1,806)

                ≤0.001

                Ethanol intake, g/day

                9,985

                1.8 (0.1-3.4)

                12,430

                1.9 (0.2-3.8)

                8,770

                2.0 (0.2-4.0)

                ≤0.001

                Protein intake,% of energy

                9,985

                13.4 (12.4-14.2)

                12,430

                14.9 (13.9-15.8)

                8,770

                16.7 (15.8-17.8)

                ≤0.001

                Animal protein intake,% of energy

                9,985

                8.4 (7.5-9.3)

                12,430

                10.3 (9.5-11.1)

                8,770

                12.6 (11.6-13.7)

                ≤0.001

                Plant protein intake,% of energy

                9,985

                4.9 (4.3-5.5)

                12,430

                4.5 (3.9-5.0)

                8,770

                4.1 (3.6-4.6)

                ≤0.001

                Carbohydrate intake,% of energy

                9,985

                56.4 (53.8-59.3)

                12,430

                51.3 (48.3-53.8)

                8,770

                47.0 (44.2-49.4)

                ≤0.001

                Whole grain intake,% of energy

                9,985

                18.4 (13.5-23.6)

                12,430

                16.7 (12.3-21.4)

                8,770

                14.4 (10.3-18.9)

                ≤0.001

                Sucrose intake,% of energy

                9,985

                7.9 (6.2-10.0)

                12,430

                6.4 (5.0-7.9)

                8,770

                5.2 (4.0-6.6)

                ≤0.001

                Fat intake,% of energy

                9,985

                29.1 (25.9-32.2)

                12,430

                33.0 (29.4-37.1)

                8,770

                35.5 (32.7-38.7)

                ≤0.001

                Saturated fat intake,% of energy

                9,985

                11.8 (10.2-13.5)

                12,430

                13.7 (11.9-15.8)

                8,770

                14.9 (13.4-16.7)

                ≤0.001

                Unsaturated fat intake,% of energy

                9,985

                17.1 (15.3-19.0)

                12,430

                19.1 (17.1-21.5)

                8,770

                20.4 (18.6-22.4)

                ≤0.001

                1 LCHP scores were calculated separately for FFQ version and sex, and categorized into roughly equally sized groups: low (2–8 points), medium (9–13 points) and high (14–20 points). Values are medians (25th, 75th percentiles) or frequencies (percents).

                2 p-values were determined by the Kruskal-Wallis test.

                3 Defined as no regular physical activity in exercise clothes.

                There were no statistically significant associations between LCHP score and any cancer, with the exception of an increased risk of respiratory tract cancer for medium LCHP scores in men (multivariate HR for medium versus low LCHP scores 1.84; 95% CI 1.05-3.23; p-trend = 0.38) (Table 2). HR for high versus low LCHP scores for respiratory tract cancer were above one in both men and women, but not statistically significant.
                Table 2

                Associations between low-carbohydrate, high-protein (LCHP) score and incident all-cause and site-specific cancer in Västerbotten Intervention Programme participants

                Cancer type

                Sex

                LCHP score1

                n

                Model 12,3

                 

                Model 22,4

                 

                Cases

                HR (95% CI)

                p-trend5

                HR (95% CI)

                p-trend5

                All cancer sites

                Men

                low

                545

                1

                 

                1

                 

                n = 3,059

                 

                medium

                650

                1.12 (1.00-1.25)

                 

                1.10 (0.97-1.23)

                 
                  

                high

                327

                1.01 (0.88-1.16)

                0.678

                0.97 (0.83-1.12)

                0.973

                 

                Women

                low

                525

                1

                 

                1

                 
                  

                medium

                596

                1.00 (0.89-1.13)

                 

                1.00 (0.89-1.13)

                 
                  

                high

                416

                1.01 (0.89-1.15)

                0.776

                1.00 (0.86-1.15)

                0.777

                Prostate cancer

                Men

                low

                256

                1

                 

                1

                 

                n = 657

                 

                medium

                266

                1.02 (0.86-1.21)

                 

                1.01 (0.85-1.21)

                 
                  

                high

                135

                0.98 (0.79-1.21)

                0.671

                0.97 (0.78-1.22)

                0.588

                Breast cancer

                Women

                low

                195

                1

                 

                1

                 

                n = 581

                 

                medium

                232

                1.03 (0.85-1.24)

                 

                1.04 (0.85-1.28)

                 
                  

                high

                154

                0.96 (0.78-1.19)

                0.761

                1.00 (0.79-1.27)

                0.924

                <49 y at diagnosis

                Women

                low

                30

                1

                 

                1

                 

                n = 104

                 

                medium

                49

                1.15 (0.73-1.81)

                 

                1.26 (0.77-2.06)

                 
                  

                high

                25

                0.85 (0.50-1.45)

                0.948

                1.04 (0.57-1.89)

                0.343

                >55 y at diagnosis

                Women

                low

                73

                1

                 

                1

                 

                n = 184

                 

                medium

                71

                1.03 (0.74-1.42)

                 

                1.07 (0.76-1.50)

                 
                  

                high

                40

                0.96 (0.65-1.41)

                0.975

                1.02 (0.67-1.55)

                0.707

                Colorectum

                Men

                low

                66

                1

                 

                1

                 

                n = 329

                 

                medium

                75

                1.08 (0.78-1.51)

                 

                1.02 (0.72-1.44)

                 
                  

                high

                43

                1.12 (0.76-1.65)

                0.949

                1.00 (0.66-1.52)

                0.511

                 

                Women

                low

                53

                1

                 

                1

                 
                  

                medium

                58

                1.02 (0.70-1.48)

                 

                0.99 (0.67-1.47)

                 
                  

                high

                34

                0.88 (0.57-1.36)

                0.625

                0.83 (0.52-1.34)

                0.459

                Respiratory tract

                Men

                low

                19

                1

                 

                1

                 

                n = 143

                 

                medium

                42

                2.10 (1.22-3.61)

                 

                1.84 (1.05-3.23)

                 
                  

                high

                18

                1.64 (0.86-3.14)

                0.044

                1.24 (0.62-2.47)

                0.381

                 

                Women

                low

                18

                1

                 

                1

                 
                  

                medium

                27

                1.38 (0.76-2.51)

                 

                1.42 (0.76-2.66)

                 
                  

                high

                19

                1.39 (0.72-2.65)

                0.261

                1.37 (0.67-2.82)

                0.328

                Urinary tract

                Both sexes

                low

                40

                1

                 

                1

                 

                n = 116

                 

                medium

                47

                1.11 (0.73-1.69)

                 

                1.11 (0.72-1.73)

                 
                  

                high

                29

                1.11 (0.69-1.81)

                0.591

                1.15 (0.68-1.94)

                0.552

                Non-Hodgkins lymphoma

                Both sexes

                low

                44

                1

                 

                1

                 

                n = 111

                 

                medium

                40

                0.83 (0.54-1.28)

                 

                0.92 (0.59-1.44)

                 
                  

                high

                27

                0.90 (0.56-1.46)

                0.902

                1.10 (0.65-1.88)

                0.400

                Malignant melanoma

                Both sexes

                low

                34

                1

                 

                1

                 

                n = 105

                 

                medium

                50

                1.21 (0.78-1.87)

                 

                1.22 (0.77-1.93)

                 
                  

                high

                21

                0.76 (0.44-1.31)

                0.475

                0.76 (0.42-1.37)

                0.509

                Endometrium

                Women

                low

                30

                1

                 

                1

                 

                n = 103

                 

                medium

                41

                1.25 (0.78-2.01)

                 

                1.35 (0.83-2.21)

                 
                  

                high

                32

                1.42 (0.86-2.34)

                0.268

                1.60 (0.92-2.79)

                0.161

                Ovary

                Women

                low

                24

                1

                 

                1

                 

                n = 72

                 

                medium

                28

                1.03 (0.59-1.78)

                 

                1.01 (0.57-1.79)

                 
                  

                high

                20

                1.07 (0.59-1.94)

                0.710

                0.99 (0.51-1.92)

                0.927

                Leukemia

                Both sexes

                low

                25

                1

                 

                1

                 

                n = 70

                 

                medium

                23

                0.82 (0.46-1.44)

                 

                0.78 (0.43-1.40)

                 
                  

                high

                22

                1.20 (0.67-2.14)

                0.476

                1.14 (0.60-2.15)

                0.601

                Pancreas

                Both sexes

                low

                25

                1

                 

                1

                 

                n = 70

                 

                medium

                28

                1.03 (0.60-1.76)

                 

                0.88 (0.50-1.55)

                 
                  

                high

                17

                0.99 (0.53-1.84)

                0.771

                0.77 (0.39-1.50)

                0.584

                Stomach

                Both sexes

                low

                24

                1

                 

                1

                 

                n = 69

                 

                medium

                33

                1.27 (0.75-2.16)

                 

                1.35 (0.78-2.35)

                 
                  

                high

                12

                0.74 (0.37-1.49)

                0.301

                0.84 (0.40-1.79)

                0.526

                Multiple myeloma

                Both sexes

                low

                23

                1

                 

                1

                 

                n = 63

                 

                medium

                29

                1.13 (0.66-1.96)

                 

                0.94 (0.53-1.68)

                 
                  

                high

                11

                0.68 (0.33-1.40)

                0.692

                0.51 (0.24-1.10)

                0.211

                Renal cell

                Both sexes

                low

                21

                1

                 

                1

                 

                n = 50

                 

                medium

                21

                0.92 (0.50-1.69)

                 

                0.89 (0.47-1.68)

                 
                  

                high

                8

                0.56 (0.25-1.27)

                0.174

                0.54 (0.23-1.30)

                0.162

                1 LCHP scores were calculated separately for FFQ version and sex, and categorized into roughly equally sized groups: low (2–8 points), medium (9–13 points) and high (14–20 points).

                2 Hazard ratios were determined by Cox regression analyses.

                3 Including age strata.

                4 Further adjusted for obesity, sedentary lifestyle, lack of postsecondary education, current smoking, and intake of energy, alcohol, and saturated fat.

                5 p-trend were calculated per 1-point increase in LCHP score.

                Subgroup analyses based on metabolic risk profile, saturated fat intake, and energy reporting [19], had no material effects on results (Table 3). The only statistically significant finding was an inverse association between LCHP score and colorectal cancer risk in women with high saturated fat intakes (multivariate HR for a 1-point increase in LCHP score 0.92; 95% CI 0.87-0.98; p = 0.013; p-heterogeneity = 0.003). Constructing LCHP scores in which whole grain or sucrose replaced total carbohydrates, and in which vegetable or animal protein replaced total protein intake (data not shown), also did not differ from the main findings, except a statistically significant increased risk of colorectal cancer in men with higher LCHP scores based on vegetable protein (multivariate HR for a 1-point increase in LCHP score 1.07; 95% CI 1.01-1.14; p = 0.029; p-heterogeneity = 0.016).
                Table 3

                Associations between low-carbohydrate, high-protein (LCHP) score and incident all-cause and site-specific cancer in subgroups of participants in the Västerbotten Intervention Programme based on metabolic risk profile, saturated fat intake, and energy reporting

                Cancer type

                Sex

                n Cases

                HR1(95% CI)

                HR1(95% CI)

                p-heterogeneity 2

                Metabolic risk profile3

                 

                low/high

                Low

                High

                 

                All cancer

                Men

                1,251/371

                1.00 (0.98-1.02)

                0.99 (0.95-1.02)

                0.668

                 

                Women

                1,182/355

                1.00 (0.98-1.02)

                1.00 (0.97-1.03)

                1.000

                Prostate cancer

                Men

                549/108

                1.00 (0.97-1.02)

                0.98 (0.93 -1.03)

                0.513

                Breast cancer

                Women

                468/113

                1.00 (0.97-1.02)

                1.02 (0.97-1.07)

                0.509

                Colorectal cancer

                Men

                142/42

                0.98 (0.93-1.02)

                1.02 (0.94-1.11)

                0.419

                 

                Women

                110/35

                0.97 (0.92-1.02)

                1.04 (0.95-1.14)

                0.193

                Saturated fat intake 4

                 

                low/high

                Low

                High

                 

                All cancer

                Men

                817/705

                1.00 (0.99-1.02)

                1.00 (0.98-1.01)

                1.000

                 

                Women

                845/692

                1.01 (0.99-1.02)

                1.00 (0.98-1.02)

                0.493

                Prostate cancer

                Men

                375/282

                1.01 (0.98-1.03)

                0.99 (0.96-1.02)

                0.363

                Breast cancer

                Women

                320/261

                1.01 (0.98-1.04)

                0.99 (0.96-1.02)

                0.363

                Colorectal cancer

                Men

                89/95

                1.00 (0.95-1.06)

                0.97 (0.92-1.02)

                0.418

                 

                Women

                83/62

                1.03 (0.98-1.09)

                0.92 (0.87-0.98)

                0.003

                Energy reporting 5

                 

                adequate/inadequate

                adequate

                inadequate

                 

                All cancer

                Men

                548/846

                1.00 (0.97-1.02)

                1.00 (0.98-1.02)

                 
                 

                Women

                440/996

                1.00 (0.98-1.03)

                1.00 (0.98-1.01)

                1.000

                Prostate cancer

                Men

                250/353

                1.00 (0.97-1.03)

                1.00 (0.97-1.03)

                1.000

                Breast cancer

                Women

                192/360

                0.98 (0.95-1.02)

                1.01 (0.98-1.04)

                1.000

                Colorectal cancer

                Men

                59/108

                1.01 (0.94-1.08)

                1.00 (0.94-1.04)

                0.172

                 

                Women

                33/103

                1.03 (0.94-1.12)

                0.96 (0.92-1.01)

                0.837

                1 Hazard ratios per 1-point increase in LCHP score, determined by Cox regression and adjusted for age strata, obesity, sedentary lifestyle, lack of postsecondary education, current smoking, and intake of energy, alcohol, and saturated fat. Saturated fat intake was not included as a covariate in the subgroup analysis based on saturated fat.

                2 Comparison of subgroup HR by Chi-square test.

                3 Metabolic risk profile defined as having at least one of (high), versus none of (low), obesity, diabetes or impaired glucose tolerance.

                4 Stratified at sex-specific medians.

                5 Defined according to the Goldberg cut-off, modified as described previously [19].

                In analyses restricted to the time period up to and including December 31, 2002, there was a tendency towards a positive association between high LCHP scores and overall cancer risk in both men (multivariate HR for high versus low LCHP scores 1.25; 95% CI 0.86-1.80; p-trend = 0.093) and women, (multivariate HR for high versus low LCHP scores 1.39; 95% CI 0.98-1.96; p-trend = 0.020) (Table 4). For prostate, breast and colorectal cancers no significant associations were found.
                Table 4

                Associations between low-carbohydrate, high-protein (LCHP) score and incident all-cause and site-specific cancer in Västerbotten Intervention Programme participants in a subgroup with reduced follow-up until 2002

                Cancer type

                Sex

                LCHP score1

                n Cases

                Model 12,3HR (95% CI)

                p-trend5

                Model 22,4HR (95% CI)

                p-trend5

                All cancer sites

                Men

                low

                94

                1

                 

                1

                 

                n = 531

                 

                medium

                118

                1.20 (0.91-1.58)

                 

                1.35 (1.01-1.79)

                 
                  

                high

                55

                1.05 (0.75-1.46)

                0.599

                1.25 (0.86-1.80)

                0.093

                 

                Women

                low

                82

                1

                 

                1

                 
                  

                medium

                101

                1.10 (0.81-1.47)

                 

                1.15 (0.84-1.56)

                 
                  

                high

                81

                1.29 (0.95-1.76)

                0.049

                1.39 (0.98-1.96)

                0.020

                Prostate cancer

                Men

                low

                47

                1

                 

                1

                 

                n = 106

                 

                medium

                40

                0.86 (0.56-1.32)

                 

                0.98 (0.63-1.51)

                 
                  

                high

                19

                0.80 (0.47-1.38)

                0.261

                1.01 (0.57-1.80)

                0.871

                Breast cancer

                Women

                low

                29

                1

                 

                1

                 

                n = 91

                 

                medium

                33

                0.98 (0.59-1.62)

                 

                1.05 (0.62-1.78)

                 
                  

                high

                29

                1.24 (0.74-2.09)

                0.210

                1.38 (0.77-2.46)

                0.100

                Colorectum

                All

                low

                17

                1

                 

                1

                 

                n = 57

                 

                medium

                24

                1.38 (0.74-2.58)

                 

                1.48 (0.77-2.81)

                 
                  

                high

                16

                1.58 (0.79-3.13)

                0.320

                1.76 (0.83-3.73)

                0.245

                1 LCHP scores were calculated separately for FFQ version and sex, and categorized into roughly equally sized groups: low (2–8 points), medium (9–13 points) and high (14–20 points).

                2 Hazard ratios were determined by Cox regression analyses.

                3 Including age strata.

                4 Further adjusted for obesity, sedentary lifestyle, lack of postsecondary education, current smoking, and intake of energy, alcohol, and saturated fat.

                5 p-trend were calculated per 1-point increase in LCHP score.

                Discussion

                In this large population-based cohort study with a follow-up period of up to 17.9 years, a diet moderately low in carbohydrates and moderately high in protein was largely unrelated to overall and site-specific cancer incidence, regardless of the quantity and quality of fat intake.

                The one previous prospective study to report results for overall cancer incidence, from the Iowa Women’s Health Study, reported inverse risk relationships for isocaloric substitution of either animal or vegetable protein for carbohydrates [22]. However, the results were attenuated to null in multivariate analyses. Associations reported for overall cancer mortality have also been null, non-statistically significant, or unstable [15, 17, 19, 22]. Taken together, the evidence to date does not support a role for moderate carbohydrate reduction in determining the overall risk of cancer.

                Increasing LCHP scores were associated with an elevated risk of respiratory tract cancer in both men and women in the present study, but the relationship was not dose dependent and was only statistically significant for medium LCHP scores in men. Although these observations may be due to chance or reflect residual confounding due to smoking, they are consistent with a previous finding for lung cancer mortality [15]. Further study is therefore warranted.

                There are several mechanisms by which a carbohydrate-reduced diet could influence carcinogenesis, through specific food items or components, such as red and processed meat for example [35], or through effects on energy metabolism and body composition [3639]. In analyses considering macronutrient quality and metabolic profile at baseline, two statistically significant results were observed, an inverse association between LCHP score and colorectal cancer risk in women with high saturated fat intakes, and an increased risk of colorectal cancer in men with higher LCHP scores based on vegetable protein. These findings do not support the hypothesis that high animal protein intake increases the risk for these cancer types. Previously, we have reported a null association between LCHP score and colorectal cancer mortality [19], and a positive association has been noted for an animal-based, low-carbohydrate score and colorectal cancer mortality [15]. The latter finding is more consistent with the current understanding of the role of diet in colorectal cancer. For example, there is convincing evidence that a high consumption of protein sources such as red and processed meat is associated with increased colorectal cancer risk [35]. Furthermore, in a controlled trial, a LCHP weight-loss diet has been observed to reduce fecal cancer-protective metabolites and increase hazardous metabolites, which could increase the risk of colon cancer [40].

                The limited variability in macronutrient distribution in the study population may have prevented the detection of associations with cancer risk. In particular, the role of stricter carbohydrate restriction could not be assessed. This is an issue common to both the present and previous studies [15, 17, 19, 22]. Interindividual differences, such as gene-nutrient interactions and epigenetics, both emerging research fields [36], may also complicate the relationship between macronutrient distribution and cancer risk. Furthermore, carbohydrate restriction might have different roles in different stages of tumorigenesis, making it difficult to detect overall effects on incidence. For example, putative mechanisms for a role for carbohydrate in the progression from premalignant lesion to cancer diagnosis include metabolic reprogramming of cancer cells resulting in increased glycolysis and glucose requirements, the so-called Warburg effect, as well as the stimulatory effect of insulin-like growth factor on proliferating cells [37, 41].

                In northern Sweden, a rapid decline in fat intake and hypercholesterolemia occurred between the years 1986–1992 [42], attributed in part to the cardiovascular disease prevention activities of the VIP [42]. Today fat intake has reached the peak levels of the 1980’s, and carbohydrate intake is decreasing [2]. LCHP scores have increased in VIP participants with repeated samples 10 years apart [19]. Furthermore, blood cholesterol concentrations in the northern Swedish population are increasing, despite increasing use of cholesterol-lowering drugs [3]. These temporal changes may have attenuated our results, as indicated by the positive association between a high LCHP score and overall cancer incidence in the sub-analysis restricted to the time period 1990–2002, when LCHP score was relatively stable in the VIP population. In the present study, roughly equal amounts of saturated and unsaturated fat replaced most of the carbohydrate reduction in subjects with high LCHP scores, and the excess protein consumed by subjects with high LCHP scores was primarily of animal origin. In Sweden, extensive positive media focus for carbohydrate-restricted diets in recent years has largely promoted fat, often animal fat, rather than protein, as the substitute for carbohydrates [1, 43]. The general enthusiasm for carbohydrate reduction, and the apparent preference for animal-based replacement foods in Sweden, thus underscores the importance of evaluating potential long-term implications for health.

                The main strengths of this study were the large, population-based cohort, the extensive data available, such as an oral glucose tolerance test and BMI measured by health professionals, and the long, essentially complete, follow-up. In addition, the prospective study design reduced the risk of recall bias and reverse causation. We used an established LCHP score, which has been employed in previous studies [1618]. The LCHP score does not include fat intake. However, unlike macronutrient scores that incorporate fat, the LCHP score is independent of total energy intake. It is also simple, both to calculate and interpret, and it allowed separate consideration of the amount and quality of fat consumed. Food frequency questionnaires like the one employed is this study have inherent weaknesses, such as being a relatively inexact tool for the measurement of total nutrient and energy intake, but they are generally adequate for ranking and are an accepted and practical tool for large-scale epidemiological studies. Although several potential confounders were accounted for, residual confounding due to factors not measured (such as food items not included in the FFQ) or not adequately estimated (such as history of tobacco use) was likely present. Since we consider this study to be exploratory, the results were not corrected for multiple testing. The risk of chance findings should therefore be acknowledged. Numbers of cases were also low for some cancer types and in some subgroup analyses.

                Conclusion

                In conclusion, the results of this population-based, cohort study do not support an important role for a diet moderately low in carbohydrates and moderately high in protein, regardless of the quantity and quality of fat consumed, in determining the overall, long-term risk of cancer, although a possible increased risk of respiratory cancer was observed and a tendency of an increased general cancer risk over shorter time. Given the current widespread popularity of carbohydrate-restricted diets, and the limited data concerning potential long-term health effects of carbohydrate reduction and consequent increases in protein and/or fat intakes, these findings are important. In order to evaluate the role of more stringent carbohydrate restriction, investigations encompassing a wider range of macronutrient intakes, such as multicenter studies, will be needed.

                Abbreviations

                BMI: 

                Body mass index

                CI: 

                Confidence interval

                FIL: 

                Food intake level

                HR: 

                Hazard ratio

                FFQ: 

                Food frequency questionnaire

                LCHP: 

                Low-carbohydrate high-protein

                VIP: 

                The västerbotten intervention programme.

                Declarations

                Acknowledgments

                This work was supported by grants from the Cancer Research Foundation in Northern Sweden, Nordic Health and Whole grain Food (HELGA)/Nordforsk, the Swedish Research Council and the Västerbotten County Council. We also acknowledge the Västerbotten Intervention Programme participants and the VIP diet database team.

                Funding

                This work was supported by grants from the Cancer Research Foundation in Northern Sweden, Nordic Health and Whole grain Food (HELGA)/Nordforsk, the Swedish Research Council and the Västerbotten County Council.

                Authors’ Affiliations

                (1)
                Department of Public Health and Clinical Medicine,Nutritional Research, Umeå University
                (2)
                Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg
                (3)
                Department of Odontology, Umeå University
                (4)
                Department of Public Health and Clinical Medicine, Umeå University
                (5)
                Department of Oncology and Radiation Sciences, Oncological Center, Umeå University
                (6)
                Department of Medical Biosciences, Pathology, Umeå University

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                Copyright

                © Nilsson et al.; licensee BioMed Central Ltd. 2013

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.