2018/08/20

BBC News

アレックス・テリエン　BBCニュース健康担当記者

低炭水化物の食事は、寿命を最大4年縮める可能性があると示唆する研究が16日、発表された。

アトキンス・ダイエット（医学博士ロバート・アトキンス氏が提唱した食事法）を初めとする低炭水化物の食事は、体重を減らす方法として急速に有名となり、いくつかの病気のリスクを下げるのに有望ともされてきた。

しかし、25年分のデータを用いた米研究は、炭水化物を適度に摂取する、もしくは肉から植物性タンパク質や植物性脂肪に切り替えるほうが、より健康的だと示している。

研究は、調査対象者がどれぐらいの量の炭水化物を摂取したかの記憶を元に行われた。

「広く有名になった健康法」
公衆衛生の専門誌「ランセット・パブリック・ヘルス」に16日付で掲載された研究は、米国に住む1万5400人に、消費した食べ物と飲み物を、サイズも合わせて尋ねた質問票の回答を分析した。
https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30135-X/fulltext

質問票から、研究者は被験者の摂取カロリーにおける炭水化物、脂肪、タンパク質の割合を推計した。

被験者が提供したデータ25年分の平均から、摂取エネルギーのうち50%から55％を炭水化物から得ている人は、低炭水化物や高炭水化物の食事をとったグループよりも、脂肪リスクがわずかながら低いことを発見した。エネルギーの50%から55%を炭水化物から摂取するのは、英国が定める食事ガイドラインにも適合している。

炭水化物は野菜、果物や砂糖にも含まれるが、主な炭水化物の摂取源はジャガイモ、パン、米、パスタ、シリアルといったでんぷん質の食品だ。

炭水化物を中程度にとっているグループの50歳の人は、平均であと33年生き続けるのが期待できると、研究者は推計した。

他にも、炭水化物を中程度摂取したグループについては、以下のような調査結果が示された――。

中程度グループは、摂取エネルギーのうち炭水化物が30%かそれ以下という、超低炭水化物グループよりも、平均寿命が4年長い
摂取エネルギーのうち炭水化物が30%から40%という低炭水化物グループより、中程度グループは平均寿命が2.3年長い
摂取エネルギーのうち炭水化物が65%かそれ以上という高炭水化物グループより、中程度グループは平均寿命が1.1年長い
今回の調査結果は、20カ国以上の40万人以上を調査した同様の先行研究の結果とも類似しており、執筆者は論文内でこの先行研究も比較対象とした。

科学者らは次に、動物性タンパク質や脂質を多く含む低炭水化物食と、植物性タンパク質と脂質が多い低炭水化物食を比較した。

比較の結果、炭水化物の代わりに牛肉や羊肉、豚肉、鶏肉、チーズを多く食べることが、死亡リスクのわずかな上昇に関係していると明らかになった。

一方、炭水化物の野菜やナッツ類といった植物性タンパク質や植物性脂質への置き換えは、実は死亡リスクを少し減らすことも分かった。

米ボストンのブリガム・アンド・ウィメンズ病院で循環器内科の臨床および研究フェローを務めるサラ・サイデルマン博士が、この研究を主導した。サイデルマン博士は、「タンパク質あるいは脂肪を炭水化物と置き換える低炭水化物食は、健康で体重を減らす戦略として広い知名度を得ている」と述べた。

「しかし、北米や欧州で普及している動物性の低炭水化物食は、全体的な寿命の短縮に関連している可能性があり、推奨されるべきでないと、我々のデータは示している」

「低炭水化物食の実践を選びたい人は、その代わりに、植物性脂質や植物性タンパク質を低炭水化物と置き換えれば、健康に歳を取ることに長期的に実際役立つかもしれない」

「栄養素への注目だけでは不十分」
炭水化物を厳しく制限する西洋型の低炭水化物食はしばしば、野菜や果物、穀物の摂取を減らす結果になり、代わりに体の炎症や老化と関係する動物性タンパク質や脂質の大量消費を引き起こすと、論文の執筆者は推測する。

今回の研究には参加しなかった、英ケンブリッジ大学の医学研究局（MRC）疫学部門に所属するニタ・フォロウヒ教授は、「この研究からもたらされる本当に重要なメッセージは、栄養素への注目だけでは不十分で、動物と植物、どちら由来の栄養素なのかが大切だということ」と述べた。

「食べ物から炭水化物の摂取を減らす場合、それが植物性脂質や植物性タンパク質の食物源と置き換えられるなら利益があるが、肉など動物性食物源と置き換えられる場合はそうならない」

ただ、この調査には限界もある。

調査結果は因果関係というより観察による関係性を示しており、被験者が食べたものは自己申告のデータに基づいており、正確でない可能性もある。

また、被験者の食事は調査開始時とそれから6年後に計測されただけで、食習慣はその後の19年間で変わった可能性があると、著者も認めている。

キングス・コレッジ・ロンドンのトム・サンダース栄養学および食品学名誉教授は、調査に使われた食事に関する質問票の使用が、被験者に自分が摂取したカロリーや脂質の過小評価を促しているとも指摘する。

「より高い死亡リスクを示しているかもしれない体重過多や肥満の人たちは、肉が多くて炭水化物が少ない、あるいは脂肪が少なくて炭水化物が多い、という2つの一般的な食生活に陥っているかもしれない、というのが、この研究や他の米研究での発見についてのあり得る説明の一つだ」とサンダース名誉教授は付け加えた。

テリエン記者のツイッターアカウントはこちら（英語）

（英語記事　Low-carb diets could shorten life, study suggests）
https://www.bbc.com/news/health-45195474

提供元：https://www.bbc.com/japanese/features-and-analysis-45219556

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ARTICLES|ONLINE FIRST
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Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis
• Sara B Seidelmann, MD
• Brian Claggett, PhD
• Susan Cheng, MD
• Mir Henglin, BA
• Amil Shah, MD
• Lyn M Steffen, PhD
• Aaron R Folsom, MD
• Eric B Rimm, ScD
• Walter C Willett, MD
• Scott D Solomon, MD
Open AccessPublished:August 16, 2018DOI:https://doi.org/10.1016/S2468-2667(18)30135-X
Open access funded by National Institutes of Health

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Summary
Background
Low carbohydrate diets, which restrict carbohydrate in favour of increased protein or fat intake, or both, are a popular weight-loss strategy. However, the long-term effect of carbohydrate restriction on mortality is controversial and could depend on whether dietary carbohydrate is replaced by plant-based or animal-based fat and protein. We aimed to investigate the association between carbohydrate intake and mortality.
Methods
We studied 15 428 adults aged 45–64 years, in four US communities, who completed a dietary questionnaire at enrolment in the Atherosclerosis Risk in Communities (ARIC) study (between 1987 and 1989), and who did not report extreme caloric intake (4200 kcal per day for men and 3600 kcal per day for women). The primary outcome was all-cause mortality. We investigated the association between the percentage of energy from carbohydrate intake and all-cause mortality, accounting for possible non-linear relationships in this cohort. We further examined this association, combining ARIC data with data for carbohydrate intake reported from seven multinational prospective studies in a meta-analysis. Finally, we assessed whether the substitution of animal or plant sources of fat and protein for carbohydrate affected mortality.
Findings
During a median follow-up of 25 years there were 6283 deaths in the ARIC cohort, and there were 40 181 deaths across all cohort studies. In the ARIC cohort, after multivariable adjustment, there was a U-shaped association between the percentage of energy consumed from carbohydrate (mean 48·9%, SD 9·4) and mortality: a percentage of 50–55% energy from carbohydrate was associated with the lowest risk of mortality. In the meta-analysis of all cohorts (432 179 participants), both low carbohydrate consumption (70%) conferred greater mortality risk than did moderate intake, which was consistent with a U-shaped association (pooled hazard ratio 1·20, 95% CI 1·09–1·32 for low carbohydrate consumption; 1·23, 1·11–1·36 for high carbohydrate consumption). However, results varied by the source of macronutrients: mortality increased when carbohydrates were exchanged for animal-derived fat or protein (1·18, 1·08–1·29) and mortality decreased when the substitutions were plant-based (0·82, 0·78–0·87).
Interpretation
Both high and low percentages of carbohydrate diets were associated with increased mortality, with minimal risk observed at 50–55% carbohydrate intake. Low carbohydrate dietary patterns favouring animal-derived protein and fat sources, from sources such as lamb, beef, pork, and chicken, were associated with higher mortality, whereas those that favoured plant-derived protein and fat intake, from sources such as vegetables, nuts, peanut butter, and whole-grain breads, were associated with lower mortality, suggesting that the source of food notably modifies the association between carbohydrate intake and mortality.
Funding
National Institutes of Health.
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Introduction
Some dietary guidelines have focused on lowering saturated and trans fat but not total fat or overall macronutrient composition.
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Other guidelines continue to recommend lowering total fat (4200 kcal per day for men and 3600 kcal per day for women).
Procedures
Participants completed an interview that included a 66-item semi-quantitative food frequency questionnaire (FFQ), modified from a 61-item FFQ designed and validated by Willett and colleagues,
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at Visit 1 (1987–89) and Visit 3 (1993–95). Participants reported the frequency with which they consumed particular foods and beverages in nine standard frequency categories (extending from never or less than one time per month, to six or more times per day). Standard portion sizes were provided as a reference for intake estimation, and pictures and food models were shown to the participants by the interviewer at each examination. We used the Harvard Nutrient Database to derive nutrient intakes from the FFQ responses.
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Outcomes
The primary outcome was all-cause mortality, subsequent to the first visit, until the end of 2013. Number of deaths was determined with annual (or later, semi-annual) telephone calls, linkage to local hospital and state health department records, or for those lost to follow-up, linkage to the National Death Index.
Statistical analysis
We analysed the covariates of age, sex, race (self-reported), study centre, education level (grade school, high school without diploma, high school graduate, vocational school, college graduate, graduate school or professional school), cigarette smoking status (current, former, never), physical activity level (sport and exercise activity and non-sport activity during leisure from Baecke questionnaire
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), total energy intake (kcal), ARIC test centre location, and diabetes status (defined on the basis of use of anti-diabetic medications, self-report of a physician diagnosis, fasting glucose value ≥126 mg/dL or a non-fasting glucose of ≥200).
We tested the association of baseline characteristics of the ARIC cohort with quantiles of total energy from carbohydrate using linear regression and χ2 tests for categorical variables (adjusting for age and sex). We used Cox proportional hazards regression models to calculate hazard ratios (HRs), to quantify the association between carbohydrate intake and the risk of death. We used restricted cubic splines
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with 4 knots to express the potentially non-linear association between total energy from carbohydrate intake at Visit 1 and all-cause mortality. We adjusted the ARIC analyses for demographics (age, sex, self-reported race), energy intake (kcal per day), study centre, education, exercise during leisure activity, income level, cigarette smoking, and diabetes. We did a time-varying sensitivity analysis: between baseline ARIC Visit 1 and Visit 3, carbohydrate intake was calculated on the basis of responses from the baseline FFQ. From Visit 3 onwards, the cumulative average of carbohydrate intake was calculated on the basis of the mean of baseline and Visit 3 FFQ responses. We did not update carbohydrate exposures of participants that developed heart disease, diabetes, and stroke before Visit 3, to reduce potential confounding from changes in diet that could arise from the diagnosis of these diseases. We did a mean residual lifetime analysis using previously published methods.
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We created actuarial estimates of the age-specific probabilities of death according to each category of carbohydrate intake exposure, and used these estimates to obtain non-parametric age-based Kaplan-Meier estimates of the survival curve for participants at each year of age in each carbohydrate intake category (>65%, 55–65%, 50–55%, 40–50%, 30–40%, and $50 000 868/2909 (30%) 802/2913 (28%) 703/2918 (24%) 661/2905 (23%) 567/2876 (20%) ..
Mean total energy intake, kcal 1558 (11) 1655 (11) 1660 (11) 1646 (11) 1607 (11) 0·0092
Mean animal protein % of energy 16·9% (0·1) 14·8% (0·1) 13·5% (0·1) 12·3% (0·1) 10·1% (0·1) 65% of energy from carbohydrate) would have a projected life expectancy of 32·0 years, compared with 33·1 years for a participant who consumed 50–55% of energy from carbohydrate (difference 1·1 years [0·1, 2·0]). We did a sensitivity analysis using 50–60% energy from carbohydrate as the comparison group, with similar findings (data not shown). The association of overall carbohydrate intake with cardiovascular and non-cardiovascular mortality is shown in the appendix (pp 3, 4). There were similar results when we used dietary information from Visit 1 and Visit 3 in the sensitivity analysis (appendix pp 5, 6).

Figure 1U-shaped association between percentage of energy from carbohydrate and all-cause mortality in the ARIC cohort
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We updated a meta-analysis
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published in 2012, by identifying two additional studies that had since been published and that met inclusion criteria, using previously defined methods;
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we also added results from ARIC because they met previously defined inclusion criteria
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(table 2). Including data from the ARIC cohort, there were 432 179 participants in eight cohort studies investigating carbohydrate intake, with 40 181 (9·3%) deaths reported. Because there was significantly lower consumption of carbohydrate in European and North American regions compared with Asian countries, low-income countries, and multinational cohorts (p70% of energy from carbohydrate) consumption were associated with increased mortality risk and shorter residual lifespan, with minimum risk observed with 50–55% of energy from carbohydrate. These findings reflect a U-shaped relationship between carbohydrate intake and mortality, and were corroborated by data from other North American, European, Asian and multinational cohorts, combined as part of a meta-analysis. However, low carbohydrate dietary patterns that replaced energy from carbohydrate with energy from animal-derived protein or fat were associated with greater risk. However, this association was reversed when energy from carbohydrate was replaced with plant-derived protein or fat.
In this study, the association of carbohydrate intake with mortality was dependent on the range of carbohydrate intake. The range of carbohydrate intake differs by geographical and socioeconomic factors; percentage of energy from carbohydrates have been lower in North American and European cohort studies (mean values generally ≤50%) than in Asian or multinational cohorts, which are largely comprised of low-income and middle-income countries (mean values >60%). Overall, there was a U-shaped relationship between carbohydrate intake and mortality, but the North American and European cohorts primarily represented the left side of the U-shaped curve whereas Asian and less economically advanced nations (as included in the PURE study) represented the right side of the curve. North American and European cohort studies have compared true low carbohydrate dietary patterns (in terms of absolute value of 70% of total energy).
Findings from this study suggest that previous analyses of carbohydrate intake that focused on quantiles of consumption and then searched for a trend across those quantiles seem to have overlooked valuable information. Using the carbohydrate intake data continuously provides more granular information and allowed us to identify a more U-shaped relationship between carbohydrate consumption and risk, which might otherwise not have been evident. Continuous data have not been published for North American or European cohorts; several previous studies only showed a linear relationship,
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whereas others that reported quantiles were suggestive of U-shaped or J-shaped relationships.
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,
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The relationship between dietary carbohydrate and mortality was reported as a continuous relationship in the PURE study, with intake ranging primarily from moderate to high carbohydrate, but still fell within the confidence intervals of what we observed in ARIC, with intake ranging primarily from low to moderate carbohydrate, further supporting a U-shaped relationship between carbohydrate intake and mortality. Although this study included quantile-based analyses to the extent that previous work has used such analyses, and we illustrate how the ARIC data fit in that context, the continuous analyses probably reflect a much closer representation of the true relationship between carbohydrate intake and mortality.
To further examine the potential effects of protein and fat sources supplanting carbohydrate intake, we investigated animal-based and plant-based diets in the ARIC cohort. We found that low carbohydrate dietary patterns favouring animal-derived protein and fat sources were associated with higher mortality, in accordance with results from the Nurses' Health Study and Health Professionals Follow up Study.
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However, low carbohydrate diets that favoured plant-derived protein and fat intake were associated with lower mortality, also consistent with previous results.
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These data suggest that the source of the protein and fat substituted for carbohydrates in the diet might notably modify the relationship between carbohydrate intake and mortality. Previous work has shown a less consistent relationship between overall carbohydrate intake and cardiovascular death by comparison with all-cause mortality.
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However, in our analysis, when carbohydrate is substituted for higher animal fat or protein intake it is associated with both higher cardiovascular and non-cardiovascular death, whereas plant-based substitutions are associated with both lower cardiovascular and non-cardiovascular death, indicating that food source could be an important consideration for both causes of mortality.
There are several possible explanations for our main findings. Low carbohydrate diets have tended to result in lower intake of vegetables, fruits, and grains and increased intakes of protein from animal sources,
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as observed in the ARIC cohort, which has been associated with higher mortality. It is likely that different amounts of bioactive dietary components in low carbohydrate versus balanced diets, such as branched-chain amino acids, fatty acids, fibre, phytochemicals, haem iron, and vitamins and minerals are involved.
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Long-term effects of a low carbohydrate diet with typically low plant and increased animal protein and fat consumption have been hypothesised to stimulate inflammatory pathways, biological ageing, and oxidative stress. On the other end of the spectrum, high carbohydrate diets, which are common in Asian and less economically advantaged nations, tend to be high in refined carbohydrates, such as white rice; these types of diets might reflect poor food quality
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,
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and confer a chronically high glycaemic load that can lead to negative metabolic consequences.
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There are limitations to this study that merit consideration. This study represents observational data and is not a clinical trial; however, randomised trials of low carbohydrate diets on mortality are not practical because of the long duration of study required. Another limitation of this study is that diet was only assessed at two time intervals, spanning a 6-year period, and dietary patterns could change during 25 years. However, because participants are able to increase or decrease their consumption of carbohydrates during the course of follow-up, any dietary changes that occur after the described assessments would be expected to attenuate any observed associations. Our conclusions about animal fat and protein might have less generalisability to Asian cultures, which often feature very high carbohydrate consumption but with a primary meat source that is often from fish. In fact, the plant score calculated in the Japanese cohort, NIPPON DATA80,
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included fish as a source of protein as well. Hence, animal scores reported here are composed largely of beef, pork, and fowl, in addition to fish. An additional limitation is that the international data
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about very high carbohydrate intakes, largely derived from China, are, on average, higher than the national data,
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for unclear reasons. However, the advantage of these data is that they include multi-racial and ethnic groups across a spectrum of socioeconomic groups, and they are representative of many high quality cohorts. Given the relatively small number of individuals adhering to low carbohydrate diets with mainly plant-based protein and fat sources of macronutrients, this study could not definitively examine the relative benefits of this diet compared with other dietary patterns. Our study focused on general carbohydrate intake, which represents a heterogeneous group of dietary components. Any number and combination of dietary components could have been considered and adjusted for in this analysis; therefore, some confounders might have been unadjusted for. Ideally, it would be preferable to do an individual-level meta-analysis in a collaborative effort that would have allowed for consistent adjustment for confounders in pooled analysis. Finally, some degree of measurement error is unavoidable for all dietary assessment methods, and the absolute intakes need to be interpreted cautiously.
Our findings suggest a negative long-term association between life expectancy and both low carbohydrate and high carbohydrate diets when food sources are not taken into account. These data also provide further evidence that animal-based low carbohydrate diets should be discouraged. Alternatively, when restricting carbohydrate intake, replacement of carbohydrates with predominantly plant-based fats and proteins could be considered as a long-term approach to promote healthy ageing.
Contributors
SBS led all stages of the work with the academic guidance of SDS, WCW, EBR, SC, AS, LMS, ARF, and BC. SDS and the advisory group provided counsel in the study design and data interpretation. MH aided data analysis and preparation of figures. All authors contributed to drafting and critical revision of the manuscript for intellectual content.
Declaration of interests
LMS receives grant funding from the California Walnut Commission and Dairy Management Inc, which was not used for this project. SC reports grants from the National Institutes of Health (NIH), and personal fees from Novartis and Zogenix, outside the submitted work. All other authors have no competing interests.
Acknowledgments
The ARIC Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN26820110000 9C, HHSN268201100010C, HHSN268201100011C, and HHSN26820 1100012C). The authors thank the staff and participants of the ARIC study for their important contributions. SBS is supported by NIH grant number 2T32HL094301-06. SC was supported by NIH grants R01-HL134168 and R01-HL131532.
Supplementary Material
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Supplementary appendix
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Article Info
Publication History
Published: August 16, 2018
IDENTIFICATION
DOI: 10.1016/S2468-2667(18)30135-X
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© 2018 The Author(s). Published by Elsevier Ltd.
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Figures
•
Figure 1U-shaped association between percentage of energy from carbohydrate and all-cause mortality in the ARIC cohort
•
Figure 2Carbohydrate intake and mortality risk across multiple cohort studies
•
Figure 3U-shaped association between percentage of energy from carbohydrate and all-cause mortality in the ARIC and PURE cohort studies
Tables
• Table 1Population characteristics in the Atherosclerosis Risk in Communities study, by quantile
• Table 2Meta-analysis study characteristics
• Table 3Association between diets that substitute carbohydrates for animal-based or plant-based protein and fat with mortality in multiple cohort studies
Related Specialty Collection
This article can be found in the following collections:
• Obesity
• Nutrition & metabolism-other
• Public Health