Dermatology Associates 95 Main Street Reading Ma
Summary
Background
Depression 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 sugar restriction on mortality is controversial and could depend on whether dietary carbohydrate is replaced by plant-based or animal-based fat and poly peptide. We aimed to investigate the clan between carbohydrate intake and mortality.
Methods
We studied 15 428 adults aged 45–64 years, in four United states of america communities, who completed a dietary questionnaire at enrolment in the Atherosclerosis Gamble in Communities (ARIC) study (between 1987 and 1989), and who did non report extreme caloric intake (<600 kcal or >4200 kcal per day for men and <500 kcal or >3600 kcal per mean solar day for women). The primary issue was all-cause mortality. Nosotros investigated the association betwixt the percentage of energy from carbohydrate intake and all-cause bloodshed, accounting for possible non-linear relationships in this accomplice. We farther examined this clan, combining ARIC data with data for saccharide intake reported from seven multinational prospective studies in a meta-analysis. Finally, we assessed whether the substitution of creature or plant sources of fat and protein for carbohydrate affected mortality.
Findings
During a median follow-up of 25 years at that place were 6283 deaths in the ARIC cohort, and at that place were 40 181 deaths beyond all accomplice studies. In the ARIC accomplice, after multivariable adjustment, there was a U-shaped clan between the percentage of free energy consumed from carbohydrate (hateful 48·9%, SD nine·4) and mortality: a percentage of l–55% energy from saccharide was associated with the everyman risk of bloodshed. In the meta-analysis of all cohorts (432 179 participants), both depression carbohydrate consumption (<40%) and high sugar consumption (>70%) conferred greater bloodshed risk than did moderate intake, which was consistent with a U-shaped clan (pooled hazard ratio i·20, 95% CI 1·09–1·32 for low carbohydrate consumption; i·23, i·11–1·36 for high sugar consumption). Notwithstanding, results varied by the source of macronutrients: mortality increased when carbohydrates were exchanged for animal-derived fatty or protein (ane·eighteen, 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 bloodshed, with minimal risk observed at 50–55% carbohydrate intake. Low sugar dietary patterns favouring fauna-derived protein and fatty sources, from sources such as lamb, beefiness, 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 sugar intake and mortality.
Funding
National Institutes of Health.
Introduction
Some dietary guidelines take focused on lowering saturated and trans fatty but not total fat or overall macronutrient composition.
one
United states Department of Health and Human Services US Section of Agronomics
Dietary Guidelines for Americans 2015–2020. Eighth edition.
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Other guidelines continue to recommend lowering total fat (<30% of free energy from fat) in substitution for college carbohydrate intake.
In practice, nevertheless, low carbohydrate diets that exchange carbohydrates for a greater intake of protein or fat have gained substantial popularity because of their ability to induce short-term weight loss,
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despite incomplete and alien data regarding their long-term effects on health outcomes.
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Results from meta-analyses that included several large accomplice studies in North America and Europe accept suggested an clan between increased mortality and low saccharide intake.
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Nevertheless, the 2022 Prospective Urban Rural Epidemiology (PURE) study, of individuals from 18 countries beyond five continents (n=135 335, median follow upwards 7·4 years, 5796 deaths), reported that high carbohydrate intake was associated with increased hazard of mortality.
These data were interpreted as being reverse to previous work in the field, prompting calls for revisions to current nutrition guidelines.
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It is important to annotation, however, that nigh studies have reported mortality risk based on quantiles of carbohydrate intake that are specific to the populations studied. Thus, the furnishings of carbohydrate intake can depend on the internal reference range for a given population. Furthermore, most analyses of sugar intake have non accounted for the potential effects of specific food sources (ie, animal-based versus plant-based) that are used to replace carbohydrate intake in low carbohydrate intake settings.
Research in context
Testify before this study
Although many randomised controlled trials of low carbohydrate diets suggest beneficial short-term weight loss and improvements in cardiometabolic risk, mortality risk has typically non been investigated in calorie-free of the applied challenges posed past studies involving very long durations of follow-upwardly. Data from large prospective cohorts have been used to guess the long-term health effects of low carbohydrate diets, but have generated conflicting results. For case, the meta-analysis of large cohort studies in Due north America and Europe has suggested increased mortality associated with depression carbohydrate intake. Conversely, recently published multinational and Asian studies take reported increased bloodshed in clan with high saccharide intake. Most previous studies have reported the risk of bloodshed on the basis of the range of carbohydrate intake specific to the population studied, thus limiting both interpretability and generalisability. Furthermore, many previous studies of carbohydrate intake take not deemed for the potential effects of food source. We updated a previously published meta-assay by searching MEDLINE, Embase, ISI Web of Science, Cochrane Library, and ClinicalTrials.gov, using a combination of the keywords "low-carbohydrate diet" OR "sugar-restricted diet", AND "mortality" OR "survival", to identify relevant publications published between Sept 12, 2012, and Sept ane, 2017.
Added value of this report
Nosotros studied a large prospective accomplice, with a median follow-upwardly of 25 years, to examine the association of sugar intake with mortality in iv US communities from various socioeconomic backgrounds. We used statistical methods that immune for the possibility of non-linear associations. We then contextualised our findings in a meta-assay, combining these information with those from other North American, European, Asian and multinational cohorts. We identified seven studies in improver to the index cohort (432 179 participants, 40 181 deaths). There was a U-shaped human relationship between carbohydrate intake and mortality in the Atherosclerosis Chance in Communities accomplice, a finding that was consistent in the meta-analysis combining these data with those from the other cohorts. When assessing full carbohydrate without regard to specific food source, diets with high (>70%) or low (<40%) percentage of energy from carbohydrates were associated with increased mortality, with minimal risk observed between 50–55%. Low saccharide dietary patterns that replaced carbohydrate with animate being-derived protein or fat were associated with greater bloodshed chance, whereas this association was inverse when energy from carbohydrate was replaced with establish-derived protein or fat. These findings were also corroborated in the meta-analysis.
Implications of all the bachelor bear witness
Our findings suggest a U-shaped relationship betwixt life expectancy and overall carbohydrate intake, in which lifespan is greatest amidst people with 50–55% sugar intake, a level that might be considered moderate in Northward America and Europe simply low in other regions, such equally Asia. These data provide further evidence that animal-based depression carbohydrate diets, which are more than prevalent in Due north American and European populations, should be discouraged. Alternatively, if restricting saccharide intake is a chosen approach for weight loss or cardiometabolic risk reduction, replacement of carbohydrates with predominantly found-based fats and proteins could exist considered as a long-term approach to promote healthy ageing.
Given the need for more evidence to assistance guide recommendations regarding optimal saccharide intake, we did a population-based study of overall carbohydrate consumption, allowing for the possibility of non-linear relationships. Specifically, nosotros investigated the association of sugar intake with bloodshed and residual lifespan in a large bi-racial accomplice of adults living in 4 United states communities, and and then combined these mortality data with previous data as function of a meta-assay to contextualise our findings. Nosotros and so studied whether the replacement of sugar for animal-based or constitute-based sources of fat and protein modified whatsoever observed associations.
Methods
Study design and participants
The Atherosclerosis Risk in Communities (ARIC) study is an ongoing, prospective observational study of cardiovascular risk factors in four US communities (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; and Washington County, MD), initially consisting of participants aged 45–64 years who were recruited between 1987 and 1989 (Visit 1).
Study participants were examined at follow-up visits, with the 2nd visit occurring between 1990 and 1992, the third between 1993 and 1995, the fourth between 1996 and 1998, the fifth between 2011 and 2013, and the 6th between 2022 and 2017. At each participating site, an institutional review board canonical the study protocol. Participants provided written informed consent at each examination. We excluded participants without complete dietary information or with extreme caloric intake (defined as <600 kcal or >4200 kcal per day for men and <500 kcal or >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,
at Visit one (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 than times per twenty-four hours). Standard portion sizes were provided equally a reference for intake interpretation, and pictures and food models were shown to the participants past the interviewer at each exam. We used the Harvard Nutrient Database to derive nutrient intakes from the FFQ responses.
Outcomes
The primary outcome was all-cause bloodshed, subsequent to the beginning 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-upward, linkage to the National Death Index.
Statistical analysis
We analysed the covariates of age, sex, race (self-reported), written report centre, education level (course school, high school without diploma, high school graduate, vocational school, higher graduate, graduate school or professional person school), cigarette smoking status (electric current, former, never), concrete activeness level (sport and practice activity and non-sport activity during leisure from Baecke questionnaire
), total free energy intake (kcal), ARIC examination centre location, and diabetes status (defined on the ground of employ of anti-diabetic medications, self-report of a doctor 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 activity). We used Cox proportional hazards regression models to calculate hazard ratios (HRs), to quantify the association betwixt carbohydrate intake and the chance of expiry. We used restricted cubic splines
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Regression modeling strategies: with applications to linear models, logistic regression, and survival assay.
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with iv knots to limited the potentially non-linear association between total energy from carbohydrate intake at Visit one and all-cause mortality. We adjusted the ARIC analyses for demographics (age, sex, self-reported race), free energy intake (kcal per day), report eye, 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 three, carbohydrate intake was calculated on the footing of responses from the baseline FFQ. From Visit 3 onwards, the cumulative boilerplate of saccharide intake was calculated on the footing of the mean of baseline and Visit iii FFQ responses. We did non update carbohydrate exposures of participants that developed centre illness, diabetes, and stroke earlier Visit 3, to reduce potential confounding from changes in diet that could arise from the diagnosis of these diseases. We did a hateful residue lifetime analysis using previously published methods.
We created actuarial estimates of the age-specific probabilities of death according to each category of sugar intake exposure, and used these estimates to obtain not-parametric historic period-based Kaplan-Meier estimates of the survival curve for participants at each twelvemonth of age in each carbohydrate intake category (>65%, 55–65%, 50–55%, forty–50%, thirty–40%, and <30%). The expected residual years of survival were estimated every bit the area nether the survival curve up to a maximum age of 93 years. We chose a reference grouping of fifty–55% for the analysis and we did a mail service-hoc sensitivity analysis using a reference group of 50–threescore%. We updated the previously published meta-assay (including papers published between Sept 12, 2012, when the previous meta-analysis concluded, and Sept 1, 2017) using previously described methods.
Briefly, papers were eligible for inclusion if they were a published full-text report, observational study, or randomised controlled trial with a minimum of 1 year follow-up, reporting relative risks (ie, HRs, adventure ratios, or odds ratios with CIs), and adjusted for at least three of the following factors: historic period, sex activity, obesity, smoking status, diabetes, hypertension, hypercholesterolaemia, history of cardio-vascular disease, and family history of cardiovascular disease. We assessed the quality of reports in reference to the CONSORT statement
and the STROBE statement.
We further assessed quality using the Newcastle-Ottawa Scale,
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The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses.
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with a score of 5 or less (out of 8) suggesting a high risk of bias. If more than than a unmarried study published data from the aforementioned cohort with the aforementioned endpoint of all-crusade mortality, we included the study representing the nearly inclusive data on the population to avoid overlap. We calculated pooled HRs with 95% CIs using a random-furnishings model with inverse-variance weighting. We recreated the mortality versus pct of energy from saccharide spline from the PURE report
by extracting published co-ordinates; nosotros overlaid ARIC data on the graph using an identical reference point of 46·four% kcal from carbohydrate, and closely matched the covariates available in the ARIC cohort with those used in the PURE study, including waist-to-hip ratio.
Nosotros created animal-based and plant-based scores by dividing participants into deciles for either animal-derived or plant-derived fat and poly peptide, and carbohydrate intake, expressed equally a per centum of energy as previously described.
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For saccharide, participants in the lowest decile received 10 points, whereas participants in the highest decile received 1 indicate. The society was reversed for animal-derived or plant-derived fat and protein, then that the highest score represented low carbohydrate and high animal-derived or plant-derived fat and poly peptide intake. Nosotros used restricted cubic splines to determine the association of all-cause bloodshed with animal-based and plant-based scores. For meta-analysis of animal and institute-based scores, nosotros calculated pooled HRs with 95% CIs using a random-effects model with inverse-variance weighting for those cohorts that had these data available.
In postal service-hoc sensitivity analyses, we explored the consequence of cardiovascular expiry (defined using International Classification of Diseases [ICD]-9 codes 390–459 and ICD-10 codes I00–I99).
Role of the funding source
The funder of the study had no part in study pattern, information collection, information assay, data estimation, or writing of the study. The corresponding author had full access to all the data in the written report and had final responsibleness for the decision to submit for publication.
Results
Baseline characteristics of the ARIC report population, according to quantiles of percentage energy from sugar intake, are shown in table 1. Hateful saccharide intake was 48·9% (SD ix·4). Participants who consumed a relatively low percentage of full energy from carbohydrates (ie, participants in the lowest quantiles) were more likely to be young, male person, a self-reported race other than black, college graduates, take high body-mass alphabetize, do less during leisure time, have high household income, smoke cigarettes, and have diabetes. Overall, hateful consumption of energy from brute fat and protein was higher than from found fat and protein across all sugar quantiles (tabular array ane). Participants in the lowest carbohydrate quantile had higher average consumption of animal fat and poly peptide and lower average consumption of plant poly peptide and dietary fibre than participants in the other quantiles. Plant fat and full energy intake had reverse U-shaped or J-shaped relationships beyond carbohydrate quantiles: participants in both the first and fifth quantile had lower mean plant-derived fats and calorie consumption compared with those in the intermediate quantiles (table 1). Prevalence of hypertension was similar across carbohydrate quantiles. In that location was no significant departure in weight gain at 3-year or vi-twelvemonth timepoints beyond carbohydrate quantiles (tabular array one).
Table 1 Population characteristics in the Atherosclerosis Take chances in Communities study, by quantile
| Q1 (n=3086) | Q2 (north=3086) | Q3 (n=3085) | Q4 (north=3086) | Q5 (northward=3085) | p tendency | ||
|---|---|---|---|---|---|---|---|
| Median % of energy from saccharide | 37% (5·7) | 44% (2·5) | 49% (2·ii) | 53% (ii·viii) | 61% (6·3) | NA | |
| Mean age, years (SD) | 53·7 (5·vii) | 54·3 (5·seven) | 54·3 (five·8) | 54·3 (5·eight) | 54·3 (five·8) | <0·0001 | |
| Sex | <0·0001 | ||||||
| Men | 1635 (53%) | 1496 (48%) | 1379 (45%) | 1294 (42%) | 1112 (36%) | .. | |
| Women | 1451 (47%) | 1590 (52%) | 1706 (55%) | 1792 (58%) | 1973 (64%) | .. | |
| Race | <0·0001 | ||||||
| White | 2345 (76%) | 2320 (75%) | 2255 (73%) | 2203 (71%) | 2133 (69%) | .. | |
| Blackness | 731 (24%) | 764 (25%) | 822 (27%) | 875 (28%) | 932 (xxx%) | .. | |
| Asian | 4 (<1%) | 1 (<i%) | 6 (<1%) | half dozen (<1%) | 17 (ane%) | .. | |
| Native American | six (<1%) | 1 (<1%) | 2 (<1%) | 2 (<1%) | 3 (<1%) | .. | |
| Mean BMI, kg/thoutwo | 28·0 (0·1) | 27·ix (0·i) | 27·6 (0·1) | 27·6 (0·one) | 27·4 (0·i) | <0·0001 | |
| Diabetes | 415 (13%) | 404 (13%) | 345 (11%) | 330 (eleven%) | 316 (10%) | <0·0001 | |
| Hypertension | 1095 (35%) | 1028 (33%) | 1046 (34%) | 1052 (34%) | 1148 (37%) | 0·4436 | |
| Smoking * Some missing values for this category. | <0·0001 | ||||||
| Current smoker | 1016/3083 (33%) | 821/3085 (27%) | 787/3083 (26%) | 707/3084 (23%) | 687/3084 (22%) | .. | |
| Former smoker | 1079/3083 (35%) | 1042/3085 (34%) | 995/3083 (32%) | 950/3084 (31%) | 899/3084 (29%) | .. | |
| Never smoker | 988/3083 (32%) | 1220/3085 (twoscore%) | 1301/3083 (42%) | 1427/3084 (46%) | 1496/3084 (48%) | .. | |
| Unknown | 0 | 2/3085 (<one%) | 0 | 0 | ii/3084 (<one%) | .. | |
| Highest exercise action (quantile 5) | 474 (fifteen%) | 534 (17%) | 575 (19%) | 581 (19%) | 614 (20%) | <0·0001 | |
| College graduates | 905 (29%) | 860 (28%) | 774 (25%) | 738 (24%) | 674 (22%) | <0·0001 | |
| Household income * Some missing values for this category. | <0·0001 | ||||||
| <$5000 | 154/2909 (5%) | 138/2913 (5%) | 154/2918 (5%) | 154/2905 (five%) | 174/2876 (half-dozen%) | .. | |
| $5000–$7999 | 118/2909 (4%) | 107/2913 (4%) | 108/2918 (4%) | 125/2905 (4%) | 164/2876 (6%) | .. | |
| $8000–$11 999 | 140/2909 (5%) | 160/2913 (5%) | 187/2918 (half dozen%) | 187/2905 (vi%) | 192/2876 (vii%) | .. | |
| $12 000–$15 999 | 185/2909 (half dozen%) | 203/2913 (7%) | 205/2918 (7%) | 229/2905 (eight%) | 239/2876 (8%) | .. | |
| $16 000–$24 999 | 406/2909 (14%) | 385/2913 (13%) | 453/2918 (16%) | 462/2905 (16%) | 480/2876 (17%) | .. | |
| $25 000–$34 999 | 456/2909 (16%) | 531/2913 (xviii%) | 524/2918 (18%) | 529/2905 (18%) | 553/2876 (xix%) | .. | |
| $35 000–$49 999 | 582/2909 (20%) | 587/2913 (20%) | 584/2918 (20%) | 558/2905 (19%) | 507/2876 (eighteen%) | .. | |
| >$fifty 000 | 868/2909 (30%) | 802/2913 (28%) | 703/2918 (24%) | 661/2905 (23%) | 567/2876 (20%) | .. | |
| Hateful full energy intake, kcal | 1558 (11) | 1655 (11) | 1660 (11) | 1646 (11) | 1607 (xi) | 0·0092 | |
| Mean animal protein % of energy | xvi·9% (0·1) | 14·viii% (0·1) | 13·5% (0·1) | 12·3% (0·1) | 10·1% (0·1) | <0·0001 | |
| Mean plant protein % of energy | 3·9% (0·02) | 4·3% (0·02) | 4·5% (0·02) | 4·6% (0·02) | 4·eight% (0·02) | <0·0001 | |
| Hateful animal fat % of free energy | 26·3% (0·i) | 22·iv% (0·1) | 19·9% (0·1) | 17·six% (0·one) | xiii·6% (0·1) | <0·0001 | |
| Mean plant fat % of energy | 12·five% (0·one) | 13·half-dozen% (0·i) | 13·6% (0·1) | xiii·2% (0·1) | 11·5% (0·i) | <0·0001 | |
| Mean dietary fibre, 1000 | 13·5 (0·1) | 16·5 (0·ane) | 17·vii (0·ane) | 18·seven (0·one) | xix·8 (0·ane) | <0·0001 | |
| Glycaemic index | 71·eight (0·one) | 74·1 (0·one) | 74·9 (0·1) | 76·0 (0·one) | 76·7 (0·one) | <0·0001 | |
| Glycaemic load | 100·six (ane·1) | 134·6 (1·1) | 151·i (1·1) | 166·8 (1·1) | 191·7 (1·ane) | <0·0001 | |
| Change in BMI | |||||||
| 3-year change | 0·36 (0·03) | 0·33 (0·03) | 0·31 (0·03) | 0·32 (0·03) | 0·41 (0·03) | 0·3878 | |
| 6-twelvemonth change | 0·94 (0·04) | 0·93 (0·04) | 0·86 (0·04) | 0·94 (0·04) | 0·92 (0·04) | 0·8206 | |
Data are median (IQR), mean (SE), n (%), or n/N (%), unless otherwise indicated. Standard errors are provided for age-adjusted and sex-adjusted values. Baseline characteristics are from the written report population (n=15428) at baseline Visit 1 (1987–89), according to quantiles of pct of energy from carbohydrate adapted for age and sex. Income is reported in US$. NA=not applicable. BMI=body-mass alphabetize.
* Some missing values for this category.
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The median length of follow-up was 25 years, during which there were 6283 deaths. The highest risk of mortality was observed in participants with the lowest carbohydrate consumption, in both unadjusted and adjusted models (p<0·001; figure ane; appendix p 8). However, the relationship between carbohydrate consumption and take chances of mortality was significantly not-linear (p<0·001), resulting in a U-shaped association, with the lowest observed risk associated with saccharide consumption of 50–55% (figure 1). At that place were corresponding significant differences in mean balance lifespan based on carbohydrate intake (appendix p 2). For example, we estimated that a 50-year-quondam participant with intake of less than thirty% of energy from sugar would have a projected life expectancy of 29·i years, compared with 33·1 years for a participant who consumed 50–55% of energy from carbohydrate (deviation 4·0 years [95% CI 2·six, 5·three]). Similarly, we estimated that a l-yr-old participant with high sugar intake (>65% of free energy from saccharide) would accept a projected life expectancy of 32·0 years, compared with 33·1 years for a participant who consumed l–55% of free energy from saccharide (difference 1·1 years [0·one, 2·0]). We did a sensitivity analysis using 50–lx% energy from carbohydrate as the comparison group, with similar findings (data not shown). The association of overall sugar 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, vi).
Effigy 1 U-shaped association betwixt percentage of free energy from carbohydrate and all-cause mortality in the ARIC cohort
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The reference level is fifty% energy from saccharide. Results are adjusted for age, sex, race, ARIC exam heart, total energy consumption, diabetes, cigarette smoking, physical activity, income level, and education. ARIC=Atherosclerosis Risk in Communities.
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Nosotros updated a meta-analysis
published in 2012, by identifying ii additional studies that had since been published and that met inclusion criteria, using previously defined methods;
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we likewise added results from ARIC because they met previously defined inclusion criteria
(table 2). Including data from the ARIC cohort, there were 432 179 participants in eight cohort studies investigating carbohydrate intake, with 40 181 (9·iii%) deaths reported. Considering in that location was significantly lower consumption of sugar in European and North American regions compared with Asian countries, low-income countries, and multinational cohorts (p<0·001), studies fell into two categories in the meta-analysis: North American and European studies (mean carbohydrate intake approximately l%) that compared low carbohydrate diets with primarily moderate carbohydrate consumption as the reference (figure 2A), and Asian and multinational studies (mean carbohydrate intake approximately 61%) that compared high carbohydrate consumption with moderate carbohydrate consumption as the reference (effigy 2B; table 2). The association betwixt carbohydrate consumption and mortality was dependent on the range of sugar intake. Figure 2 illustrates the significantly increased risk of all-cause mortality among participants with depression carbohydrate versus moderate carbohydrate consumption (pooled Hour 1·20, 95% CI one·09–1·32; p<0·0001). This relationship remained significant if the ARIC study was excluded from the analysis (ane·31, 1·07–1·58; p=0·007). High carbohydrate consumption was associated with a significantly higher risk of all-cause mortality compared with moderate sugar consumption (1·23, 1·11–1·36; p<0·0001; effigy two).
Table 2 Meta-assay written report characteristics
| Accomplice | State or region | Follow-up, years | Total number of participants (proportion of women) | Age, years | Proportion of patients with diabetes | Proportion of patients with previous cardiovascular illness | Animal and plant score | All-cause death (n) | |
|---|---|---|---|---|---|---|---|---|---|
| This study | ARIC | United states | 25 (median) | 15 428 (56%) | 45–64 | 12% | 4% | Yeah | 6283 |
| Lagiou et al 10
Low sugar-high poly peptide diet and mortality in a cohort of Swedish women.
| Scandinavian Women'southward Lifestyle and Health Cohort | Sweden | 12 (mean) | 42 237 (100%) | 30–49 | Patients excluded | Patients excluded | No | 588 |
| Trichopoulou et al 11
Depression-carbohydrate-high-protein diet and long-term survival in a general population cohort.
| Epic | Greece | 4·9 (mean) | 22 944 (59%) | 20–86 | Patients excluded | Patients excluded | No | 455 |
| Fung et al 9
Depression-carbohydrate diets and all-crusade and cause-specific mortality: two cohort studies.
| NHS | USA | 26 | 85 168 (100%) | 34–59 | Patients excluded | Patients excluded | Yes | 12 555 |
| Fung et al 9
Low-carbohydrate diets and all-cause and crusade-specific mortality: two cohort studies.
| HPFS | USA | 20 | 44 548 (0%) | 40–75 | Patients excluded | Patients excluded | Yes | 8678 |
| Nilsson et al 8
Depression-carbohydrate, high-protein score and mortality in a northern Swedish population-based accomplice.
| Västerbotten Intervention Programme | Sweden | 10 (median) | 77 319 (51%) | 49 (median) | 3% | NR | No | 2383 |
| Nakamura et al 24
Low-carbohydrate diets and cardiovascular and full mortality in Japanese: a 29-year follow-up of Nihon DATA80.
| NIPPON DATA80 | Japan | 29 | 9200 (56%) | 51 (hateful) | NR | NR | Yep | 3443 |
| Dehghan et al xiii
Associations of fats and carbohydrate intake with cardiovascular illness and mortality in 18 countries from v continents (PURE): a prospective cohort study.
| PURE | Multinational | 7·4 (median) | 135 335 (58%) | 50·three (hateful) | 7·1% | NR | No | 5796 |
ARIC=Atherosclerosis Take a chance in Communities. EPIC=European Prospective Investigation into Cancer and Diet. NHS=Nurses Health Report. HPFS=Health Professionals Follow-up Study. NR=non recorded. NIPPON DATA80 National Integrated Project for Prospective Observation of Non-catching Disease and its Trends in the Anile. PURE=Prospective Urban Rural Epidemiology.
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Figure 2 Carbohydrate intake and mortality risk across multiple cohort studies
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Mean values of percentage of free energy from carbohydrate (% saccharide) reported in previously studied cohorts from lowest to highest quantiles. Adjusted HRs are from analyses of low sugar scores versus high carbohydrate scores (n=432 179, all-cause deaths=forty 181). Dotted lines indicate cutoffs for low saccharide (<40%) and loftier carbohydrate (>70%). (A) Low carbohydrate versus moderate carbohydrate (twoscore–lxx%) reference group. (B) High saccharide versus moderate carbohydrate reference grouping. HR=hazard ratio. ARIC=Atherosclerosis Risk in Communities. NHS=Nurses Health Study. HPFS=Health Professionals Follow-up Study.
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The ARIC and PURE studies were the simply two cohorts for which data were published or available most the continuous percentage of energy from sugar. Figure 3 shows the overlapping and continuous relationship betwixt percentage of energy from carbohydrate intake and mortality in these cohorts. By comparison with ARIC, the PURE report
assessed participants primarily at the high end of the overall range of per centum of energy from sugar consumption (Figure ii, Figure iii). However, the associations between primarily loftier carbohydrate intake and mortality in the PURE report still fell inside the confidence intervals of those observed in ARIC (effigy 3).
Figure 3 U-shaped association between percentage of energy from sugar and all-cause mortality in the ARIC and PURE accomplice studies
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The reference level is 46·iv% energy from carbohydrate. ARIC results are adjusted for age, sex, teaching, waist-to-hip ratio, smoking, concrete activeness, diabetes, ARIC test centre, and energy intake. PURE results are are adjusted for historic period, sexual activity, educational activity, waist-to-hip ratio, smoking, physical activeness, diabetes, urban or rural location, eye, geographical regions, and energy intake.
The mean percentage of energy from saccharide in ARIC is 49%, and from PURE it is 61%. ARIC=Atherosclerosis Risk in Communities. PURE=Prospective Urban Rural Epidemiology.
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To explore the association betwixt mortality and the source of fatty and protein alternatives to saccharide intake, we compared studies that assessed animal-based and plant-based scores, which represented increasing commutation of creature-based or institute-based fat and protein for carbohydrate intake (table 2). Baseline characteristics of the ARIC study population, according to animal-based or establish-based low carbohydrate diet scores, are shown in the appendix (pp ix–11). The establish-based low sugar dietary score was associated with higher average intake of vegetables but lower fruit intake (appendix p 11). Past contrast, the animal-based depression saccharide dietary score was associated with lower average intake of both fruit and vegetables (appendix pp 9, 10). Both low carbohydrate diets were associated with higher fat intake in exchange for carbohydrate, although the plant-based low sugar nutrition had higher average polyunsaturated fat and lower saturated fat intake compared with the animal-based low sugar diet (appendix pp 9–11). Overall, total protein intake was college in the animal-based nutrition (appendix p 9). We determined the five foods that differed virtually significantly between the highest and everyman quantiles of animal-based and plant-based depression saccharide dietary score. The creature-based low carbohydrate diet had more servings per twenty-four hour period than did higher carbohydrate diets of beef, pork, and lamb as the main dish; beef, pork, and lamb equally a side dish; craven with the peel on; chicken with the peel off; and cheese (appendix p 10). The plant-based low carbohydrate nutrition had more servings per day of nuts, peanut butter, dark or grain breads, chocolate, and white bread than did higher carbohydrate diets (appendix p eleven). Both low carbohydrate diets were lower in average regular soft potable intake (appendix pp 10, 11). In the ARIC cohort and in meta-assay, increased consumption of creature-based poly peptide and fat instead of sugar was associated with a significant increase in all-cause bloodshed (p<0·0001; table 3). Alternatively, increased consumption of institute-based protein and fat instead of sugar was associated with a significant decrease in all-cause mortality (p<0·0001; table iii). The beast and establish-based findings were consistent for cardiovascular and non-cardiovascular mortality (appendix pp three, four). Sensitivity analysis of plant-specific and animal-specific findings, using dietary information from Visit 1 and Visit 3, yielded like results (appendix pp six, 7). Similarly, in the meta-assay, mortality increased when animal-derived fat and poly peptide were substituted for carbohydrate, and decreased when these substitutions were establish-based (table iii). In the post-hoc sensitivity assay, we assessed all meta-analyses using a fixed-effects model, with similar findings. Additionally, to minimise the likelihood of opposite causation, we did a sensitivity assay whereby individuals with cardio-vascular affliction, diabetes, or cancer at baseline were excluded from the analyses. These mail-hoc analyses too yielded like results.
Table 3 Association between diets that substitute carbohydrates for animal-based or constitute-based poly peptide and fat with bloodshed in multiple cohort studies
| Written report | HR (95% CI) | |
|---|---|---|
| Exchange of saccharide for fauna protein and fat | ||
| Depression-to-moderate carbohydrate consumption | Fung et al nine
Low-carbohydrate diets and all-cause and cause-specific bloodshed: 2 accomplice studies.
| i·31 (i·xix–1·44) |
| Low-to-moderate carbohydrate consumption | Fung et al 9
Low-carbohydrate diets and all-crusade and cause-specific bloodshed: two cohort studies.
| 1·17 (1·08–1·26) |
| Low-to-moderate carbohydrate consumption | ARIC | i·twenty (1·09–ane·32) |
| Low-to-moderate carbohydrate consumption | Combined low-to-moderate cohorts | ane·22 (1·fourteen–1·31) |
| Moderate-to-high carbohydrate consumption | Nakamura et al 24
Depression-carbohydrate diets and cardiovascular and total mortality in Japanese: a 29-year follow-up of Japan DATA80.
| i·00 (0·87–one·19) |
| Meta-analysis (pooled result) | .. | one·18 (one·08–1·29); p<0·0001 |
| Commutation of carbohydrate for plant protein and fat | ||
| Low-to-moderate carbohydrate consumption | Fung et al 9
Depression-carbohydrate diets and all-cause and cause-specific bloodshed: two accomplice studies.
| 0·81 (0·74–0·89) |
| Low-to-moderate carbohydrate consumption | Fung et al 9
Low-carbohydrate diets and all-cause and cause-specific mortality: two cohort studies.
| 0·79 (0·73–0·85) |
| Low-to-moderate carbohydrate consumption | ARIC | 0·86 (0·75–0·99) |
| Depression-to-moderate carbohydrate consumption | Combined depression-to-moderate cohorts | 0·81 (0·76–0·85) |
| Moderate-to-high saccharide consumption | Nakamura et al 24
Low-saccharide diets and cardiovascular and total mortality in Japanese: a 29-twelvemonth follow-up of NIPPON DATA80.
| 0·92 (0·80–ane·09) |
| Meta-analysis (pooled result) | .. | 0·82 (0·78–0·87); p<0·0001 |
Data are for 154 344 participants and 30 959 deaths. Hr=hazard ratio. HPFS=Health Professionals Follow-upwardly Study. NHS=Nurses Health Written report. ARIC=Atherosclerosis Risk in Communities.
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Discussion
In a large cohort of adults living in four various The states communities, with more two decades of follow-up, mid-life dietary patterns marked by both low carbohydrate (<40% of free energy from sugar) and loftier carbohydrate (>70% of energy from carbohydrate) consumption were associated with increased mortality risk and shorter residue lifespan, with minimum risk observed with 50–55% of free energy from carbohydrate. These findings reflect a U-shaped relationship between carbohydrate intake and bloodshed, and were corroborated past information from other Due north American, European, Asian and multinational cohorts, combined as role of a meta-analysis. Nevertheless, low carbohydrate dietary patterns that replaced energy from carbohydrate with energy from brute-derived protein or fatty were associated with greater take a chance. However, this association was reversed when energy from saccharide was replaced with plant-derived protein or fat.
In this written report, the association of sugar intake with mortality was dependent on the range of carbohydrate intake. The range of saccharide intake differs by geographical and socioeconomic factors; percent of free energy from carbohydrates accept been lower in North American and European cohort studies (hateful values mostly ≤50%) than in Asian or multinational cohorts, which are largely comprised of depression-income and heart-income countries (mean values >threescore%). 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 (equally included in the PURE written report) represented the correct side of the curve. North American and European cohort studies take compared true depression carbohydrate dietary patterns (in terms of absolute value of <twoscore% of total energy intake) and consistently plant a modest yet significantly increased relative run a risk of all-crusade death when compared with the highest quantile (generally nevertheless falling in a moderate carbohydrate range of xl–seventy%). The Nippon DATA80
and PURE
studies correspond the correct side of the curve for absolute intake of percentage of free energy from sugar, and consistently show a modest nevertheless significantly decreased relative risk of all-cause death when comparison moderate (45–55% of total energy) to the highest quantile (>70% of total free energy).
Findings from this report advise 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 data. Using the saccharide intake data continuously provides more granular data and allowed u.s. to place a more U-shaped relationship betwixt 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 human relationship,
,
,
whereas others that reported quantiles were suggestive of U-shaped or J-shaped relationships.
,
The relationship between dietary carbohydrate and bloodshed was reported every bit a continuous relationship in the PURE study, with intake ranging primarily from moderate to loftier carbohydrate, but withal fell inside the conviction intervals of what we observed in ARIC, with intake ranging primarily from depression to moderate carbohydrate, farther supporting a U-shaped human 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 truthful relationship between carbohydrate intake and mortality.
To further examine the potential effects of protein and fatty sources supplanting saccharide intake, we investigated beast-based and plant-based diets in the ARIC cohort. We found that low carbohydrate dietary patterns favouring animal-derived protein and fatty sources were associated with higher bloodshed, in accord with results from the Nurses' Health Study and Health Professionals Follow upwards Study.
However, depression carbohydrate diets that favoured plant-derived protein and fat intake were associated with lower mortality, too consistent with previous results.
,
These data advise that the source of the protein and fatty substituted for carbohydrates in the nutrition might notably modify the human relationship betwixt carbohydrate intake and mortality. Previous piece of work has shown a less consequent human relationship between overall sugar intake and cardiovascular death by comparing with all-cause mortality.
Withal, in our analysis, when carbohydrate is substituted for higher creature fat or protein intake information technology is associated with both college cardiovascular and non-cardiovascular death, whereas establish-based substitutions are associated with both lower cardiovascular and non-cardiovascular death, indicating that food source could exist an of import consideration for both causes of mortality.
There are several possible explanations for our main findings. Depression carbohydrate diets have tended to result in lower intake of vegetables, fruits, and grains and increased intakes of protein from creature sources,
,
,
,
every bit observed in the ARIC accomplice, which has been associated with higher bloodshed. It is likely that different amounts of bioactive dietary components in low saccharide versus balanced diets, such every bit branched-chain amino acids, fatty acids, fibre, phytochemicals, haem iron, and vitamins and minerals are involved.
Long-term effects of a low carbohydrate diet with typically low plant and increased beast protein and fatty 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 exist high in refined carbohydrates, such as white rice; these types of diets might reflect poor food quality
,
and confer a chronically high glycaemic load that can lead to negative metabolic consequences.
There are limitations to this report that merit consideration. This study represents observational information and is not a clinical trial; even so, randomised trials of low carbohydrate diets on mortality are non practical because of the long duration of study required. Another limitation of this written report is that diet was only assessed at 2 time intervals, spanning a half-dozen-yr 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, whatsoever dietary changes that occur after the described assessments would be expected to attenuate any observed associations. Our conclusions near animal fatty and protein might have less generalisability to Asian cultures, which often characteristic very high carbohydrate consumption just with a primary meat source that is oftentimes from fish. In fact, the plant score calculated in the Japanese cohort, NIPPON DATA80,
included fish as a source of protein as well. Hence, animate being scores reported hither are composed largely of beefiness, pork, and fowl, in addition to fish. An additional limitation is that the international data
about very high sugar intakes, largely derived from Cathay, are, on average, college than the national data,
thirty
- Shen X
- Fang A
- He J
- et al.
Trends in dietary fatty and fatty acid intakes and related food sources among Chinese adults: a longitudinal study from the China Health and Nutrition Survey (1997–2011).
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for unclear reasons. Even so, the reward of these information is that they include multi-racial and indigenous groups across a spectrum of socioeconomic groups, and they are representative of many loftier quality cohorts. Given the relatively small number of individuals adhering to low carbohydrate diets with mainly institute-based poly peptide and fat sources of macronutrients, this written report could non definitively examine the relative benefits of this nutrition compared with other dietary patterns. Our written report focused on general carbohydrate intake, which represents a heterogeneous group of dietary components. Whatsoever 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 exist preferable to do an private-level meta-analysis in a collaborative try 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 accented intakes demand to be interpreted cautiously.
Our findings suggest a negative long-term association between life expectancy and both depression carbohydrate and loftier carbohydrate diets when food sources are non taken into account. These data also provide further show that animal-based low carbohydrate diets should be discouraged. Alternatively, when restricting saccharide intake, replacement of carbohydrates with predominantly plant-based fats and proteins could be considered as a long-term approach to promote good for you 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 informational 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 past National Heart, Lung, and Claret Establish 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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Article Info
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Published: August 16, 2018
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DOI: https://doi.org/10.1016/S2468-2667(eighteen)30135-X
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Nutrition research initially focused almost entirely on conditions of nutritional deficiencies (eg, scurvy, beriberi, pellagra). By the 1950s, with the increment in coronary heart disease in loftier-income countries, attention shifted to a range of so-chosen diet-heart hypotheses.1 These included the putative and harmful furnishings of fats (especially saturated fats) and the protective furnishings of the and so-called Mediterranean diet to explicate why individuals in the U.s.a., northern Europe, and the Uk were more prone to coronary heart disease, whereas those in European countries around the Mediterranean (or Nihon) seemed to take lower risks.
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There are several problematic issues in the Article by Seidelmann and colleagues.1 First, the quality of the dietary data is weak, since they are based only on two samples. The food frequency questionnaire that they used appears not to have been independently validated, and information technology independent only 66 questions and excluded several pop items, such as pizza.i Food was clearly underreported, equally evidenced by a reported average free energy intake of roughly 1500 kcal per solar day.
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Nosotros appreciate the interest in our work. We found that in long-term observational studies, low carbohydrate dietary intake (<40% of total energy from carbohydrates) was associated with higher bloodshed when beast-based fat and protein were substituted for sugar.one Nonetheless, when plant-based sources of fat and poly peptide such every bit whole grains, legumes, and nuts are incorporated into low carbohydrate diets, they were associated with lower mortality. We fully acknowledge the limitations of observational studies, while recognising the difficulties associated with long-term randomised trials in the expanse.
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- Dietary carbohydrate intake and bloodshed: reflections and reactions
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In their Article in The Lancet Public Health (September 2018), Sara Seidelmann and colleaguesone use data from a long-term prospective cohort study and do a meta-assay of other related cohorts to assess the clan betwixt carbohydrate intake and bloodshed. Our main problem with this Commodity1 was regarding the confounders that are related to an private's consumption of carbohydrates and to that individual'due south associated bloodshed. Some of these confounders were included as control variables, but since it is incommunicable to business relationship for all possible confounders, some confounders necessarily went unobserved.
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I read Sara Seidelmann and colleagues study1 with interest, and there are several shortcomings that deserve attending. Although, the authors appropriately acknowledge the limitations of data collection by questionnaire, in their report, participants were expected to recall their food intake over 25 years, in item, over two sessions.
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The Article by Sara Seidelmann and colleagues1 presents the analysis from the Atherosclerosis Risk in Communities study of adults aged 45–64 years over a median duration of 25 years, at half-dozen timepoints. The mean caloric intake by each developed was 1558–1655 kcal per day. I take several problems with this study. Showtime, this analysis seems to ignore the fact that, afterwards 25 years, participants are anile 70–89 years, which is older than the 2022 estimate of life expectancy by the US Centers for Disease Command and Prevention: 78·half-dozen years.
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Even if the Food Frequency Questionnaire had been robust and accurately reflective of what people had eaten during the whole 25-year study, a mean calorie intake of 1560–1660 kcal per day had been explained, and people had been allocated correctly to groups that reflected their actual sugar consumption afterwards a health diagnosis.
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Source: https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30135-X/fulltext
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