Nutritional epidemiology and the Women's Health Initiative: a review

Macronutrient-differential dietary pattern impacts on body weight, hepatic inflammation, and metabolism

Introduction

Obesity is a multi-factorial disease frequently associated with poor nutritional habits and linked to many detrimental health outcomes. Individuals with obesity are more likely to have increased levels of persistent inflammatory and metabolic dysregulation. The goal of this study was to compare four dietary patterns differentiated by macronutrient content in a postmenopausal model. Dietary patterns were high carbohydrate (HC), high fat (HF), high carbohydrate plus high fat (HCHF), and high protein (HP) with higher fiber.

Methods

Changes in body weight and glucose levels were measured in female, ovariectomized C57BL/6 mice after 15 weeks of feeding. One group of five mice fed the HCHF diet was crossed over to the HP diet on day 84, modeling a 21-day intervention. In a follow-up study comparing the HCHF versus HP dietary patterns, systemic changes in inflammation, using an 80-cytokine array and metabolism, by untargeted liquid chromatography-mass spectrometry (LCMS)-based metabolomics were evaluated.

Results

Only the HF and HCHF diets resulted in obesity, shown by significant differences in body weights compared to the HP diet. Body weight gains during the two-diet follow-up study were consistent with the four-diet study. On Day 105 of the 4-diet study, glucose levels were significantly lower for mice fed the HP diet than for those fed the HC and HF diets. Mice switched from the HCHF to the HP diet lost an average of 3.7 grams by the end of the 21-day intervention, but this corresponded with decreased food consumption. The HCHF pattern resulted in dramatic inflammatory dysregulation, as all 80 cytokines were elevated significantly in the livers of these mice after 15 weeks of HCHF diet exposure. Comparatively, only 32 markers changed significantly on the HP diet (24 up, 8 down). Metabolic perturbations in several endogenous biological pathways were also observed based on macronutrient differences and revealed dysfunction in several nutritionally relevant biosynthetic pathways.

Conclusion

Overall, the HCHF diet promoted detrimental impacts and changes linked to several diseases, including arthritis or breast neoplasms. Identification of dietary pattern-specific impacts in this model provides a means to monitor the effects of disease risk and test interventions to prevent poor health outcomes through nutritional modification.

Compliance with the WCRF/AICR Recommendations in Qualitative Adaptation and the Occurrence of Breast Cancer: A Case-Control Study

PURPOSE

The aim of the study was twofold: (1) the qualitative adaptation of the 2018 WCRF/AICR (QAd-WCRF/AICR) score, and (2) the assessment of the association between the level of compliance with the WCRF/AICR recommendations and the occurrence of breast cancer in peri- and postmenopausal women.

METHODS

This case-control study involved 420 women, aged 40-79 years, from northeastern Poland, including 190 newly diagnosed breast cancer cases. Data related to the WCRF/AICR recommendations were collected in face-to-face interviews with 409 women, including 179 women with breast cancer. The frequency of food consumption data were collected using the FFQ-6® and KomPAN® questionnaires. Body weight, height, and waist circumference were measured. The QAd-WCRF/AICR score (range: 0-8 points) was calculated on the basis of eight components, including two components from to the WCRF/AICR recommendations: (1) body mass index (BMI), and (2) waist circumference, with six components expressed qualitatively: (3) overall physical activity, as well as the frequency of the consumption of (4) vegetables/fruits/whole grains/nuts/seeds/legumes, (5) highly processed foods, including fast foods/sweets/instant soups, (6) red/processed meat, (7) sweetened/energy drinks, and (8) alcohol. Logistic regression analysis was performed to assess the occurrence of breast cancer.

RESULTS

The moderate (4-5 points) and maximal (6-8 points) compliance with the qualitative adaptation of the WRCF/AICR recommendations reduced the odds of breast cancer by 54% and 72%, respectively, compared to the results noted for minimal compliance (≤3 points). Lower odds of breast cancer were associated with moderate or high physical activity, consumption of a minimum of four serving per day of vegetables/fruits/whole grains/nuts/seeds/legumes, and limiting the consumption of highly processed food/fast foods and red/processed meat to a maximum of 1-3 times/month. Higher odds of breast cancer were associated with a higher waist circumference and alcohol abstinence.

CONCLUSIONS

These findings may prove useful in establishing cancer prevention recommendations based on simple suggestions regarding the frequency of food consumption.

Association between doubly labelled water-calibrated energy intake and objectively measured physical activity with mortality risk in older adults

BACKGROUND

Physical activity or biomarker-calibrated energy intake (EI) alone is associated with mortality in older adults; the interaction relationship between the combined use of both factors and mortality has not been examined. We evaluated the relationship between mortality and calibrated EI and step counts in older adults.

METHODS

This prospective study included 4,159 adults aged ≥65 years who participated in the Kyoto-Kameoka study in Japan and wore a triaxial accelerometer between 1 April and 15 November 2013. The calibrated EI was calculated based on a previously developed equation using EI biomarkers. The step count was obtained from the accelerometer ≥ 4 days. Participants were classified into the following four groups: low EI (LEI)/low step counts (LSC) group (EI: <2,400 kcal/day in men and <1,900 kcal/day in women; steps: <5,000 /day), n = 1,352; high EI (HEI)/LSC group (EI: ≥2,400 kcal/day in men and ≥1,900 kcal/day in women; steps: <5,000 /day), n = 1,586; LEI/high step counts (HSC) group (EI: <2,400 kcal/day in men and < 1,900 kcal/day in women; steps: ≥5,000 /day), n = 471; and HEI/HSC group (EI: ≥2,400 kcal/day in men and ≥1,900 kcal/day in women; steps: ≥5,000 /day), n = 750. Mortality-related data were collected until 30 November 2016. We performed a multivariable Cox proportional hazard analysis.

RESULTS

The median follow-up period was 3.38 years (14,046 person-years), and 111 mortalities were recorded. After adjusting for confounders, the HEI/HSC group had the lowest all-cause mortality rate compared to other groups (LEI/LSC: reference; HEI/LSC: hazard ratio [HR]: 0.71, 95% confidence interval [CI]: 0.41-1.23; LEI/HSC: HR: 0.59, 95% CI: 0.29-1.19; and HEI/HSC: HR: 0.10, 95% CI: 0.01-0.76). No significant interaction was observed between the calibrated EI and steps with mortality. The spline model showed that 35-42 kcal/100 steps/day of EI/100 steps was associated with the lowest mortality risk.

CONCLUSIONS

HR mortality risk was lowest at 35-42 kcal/100 steps/day, suggesting that very high (≥56 kcal) or low (<28 kcal) EI/100 steps are not inversely associated with mortality. Adherence to optimal EI and adequate physical activity may provide sufficient energy balance to explain the inverse association with mortality among older Japanese adults.

Distribution of water turnover by sex and age as estimated by prediction equation in Japanese adolescents and adults: the 2016 National Health and Nutrition Survey, Japan

BACKGROUND

Although water is essential to the maintenance of health and life, standard values for human water requirements are yet to be determined. This study aimed to evaluate the distribution of water turnover (WT) according to sex and age, estimated using a prediction equation, in Japanese adolescents and adults.

METHODS

This cross-sectional study used data from the 2016 National Health and Nutrition Survey, Japan. Data were obtained from electronically available aggregated reports in the survey's official website. Participants aged between 15 and 80 years (10,546 men, 12,355 women) were selected using stratified random sampling. WT was calculated considering lifestyle and environmental factors, and using an equation (coefficient of determination = 0.471) previously developed by the international doubly labelled water (DLW) database group. As data on physical activity levels (PAL) were not collected in the survey, we used two evaluation methods: (1) energy intake assessed by dietary records and (2) total energy expenditure measured by the DLW method reported in previous Japanese studies, divided by basal metabolic rate predicted using the equation. We evaluated the relationship between WT and age using a restricted cubic spline model.

RESULTS

The average WT for the 15-19, 20-29, 30-39, 40-49, 50-59, 60-69, and ≥ 70 years was 3291, 3151, 3213, 3243, 3205, 3104, and 2790 ml/day, respectively in men, and 2641, 2594, 2741, 2739, 2753, 2707, and 2482 ml/day, respectively in women. In the spline model, WT showed an inverse association with age in men older than 50 years, whereas women showed a reverse U-shaped relationship between WT and age (p for non-linearity < 0.001), although results differed with body weight adjustment. Similar results were found for both PAL evaluation methods, and the range of WT per body weight was 45-56 ml/day for both sexes.

CONCLUSIONS

We determined the standard values of WT in Japanese population using a prediction equation and national large-scale survey data. These findings may be useful for setting water requirements for dietary guidelines in future.

Metabolomics-Based Biomarker for Dietary Fat and Associations with Chronic Disease Risk in Postmenopausal Women

BACKGROUND

The Women's Health Initiative (WHI) randomized, controlled Dietary Modification (DM) trial of a low-fat dietary pattern suggested intervention benefits related to breast cancer, coronary heart disease (CHD), and diabetes. Here, we use WHI observational data for further insight into the chronic disease implications of adopting this type of low-fat dietary pattern.

OBJECTIVES

We aimed to use our earlier work on metabolomics-based biomarkers of carbohydrate and protein to develop a fat intake biomarker by subtraction, to use the resulting biomarker to develop calibration equations that adjusts self-reported fat intake for measurement error, and to study associations of biomarker-calibrated fat intake with chronic disease risk in WHI cohorts. Corresponding studies for specific fatty acids will follow separately.

METHODS

Prospective disease association results are presented using WHI cohorts of postmenopausal women, aged 50-79 y when enrolled at 40 United States clinical centers. Biomarker equations were developed using an embedded human feeding study (n = 153). Calibration equations were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with cancer, cardiovascular diseases, and diabetes incidence in WHI cohorts (n = 81,954) over an approximate 20-y follow-up period.

RESULTS

A biomarker for fat density was developed by subtracting protein, carbohydrate, and alcohol densities from one. A calibration equation was developed for fat density. Hazard ratios (95% confidence intervals) for 20% higher fat density were 1.16 (1.06, 1.27) for breast cancer, 1.13 (1.02, 1.26) for CHD, and 1.19 (1.13, 1.26) for diabetes, in substantial agreement with findings from the DM trial. With control for additional dietary variables, especially fiber, fat density was no longer associated with CHD, with hazard ratio (95% confidence interval) of 1.00 (0.88, 1.13), whereas that for breast cancer was 1.11 (1.00, 1.24).

CONCLUSIONS

WHI observational data support prior DM trial findings of low-fat dietary pattern benefits in this population of postmenopausal United States women.

TRIAL REGISTRATION NUMBER

This study is registered with clinicaltrials.gov identifier: NCT00000611.

Have safety and efficacy assessments of bioactives come of age?

This article describes why the safety and efficacy assessment of non-nutrient bioactives for reducing chronic disease risk is so complicated, especially for dietary supplements and traditional medicines. Scientists, regulators, and the public have different and sometimes opposing perspectives about bioactives. Drug, food, and traditional medicine models used for bioactive safety assessment are based on different assumptions and use different processes. Efficacy assessment is seldom based on clinical trials of boactives' effects in reducing chronic disease risk. It usually consists of application of quality assurance measures and evaluation of label claims and commercial speech about ingredients or products to ensure conformity to regulations. Harmonization of safety and efficacy assessment on a global basis is difficult because of differences within and between regulatory systems. The recommendations provided may open the way for bioactives to play a larger health role in the future, fill gaps in data needed for crafting authoritative dietary guidance on intakes, and speed harmonization of global standards.

Doubly labelled water-calibrated energy intake associations with mortality risk among older adults

BACKGROUND

The body mass index (BMI) is closely related to mortality risk, and energy intake (EI) is essential for maintaining energy balance in weight control. However, self-reported EI has been shown to lead to a systematic underestimation. Total energy expenditure measured using the doubly labelled water (DLW) method is considered an objective biomarker of EI and the gold standard for its estimation in individuals with stable body weight. We aimed to examine the association between DLW-calibrated EI and BMI on overall mortality risk in older adults.

METHODS

A prospective cohort study was performed using data of 8051 (4267 women and 3784 men) Japanese older adults from the Kyoto-Kameoka Study in Japan. Calibrated EI was calculated from the estimated EI using a food frequency questionnaire and equation developed based on DLW. Participants were classified by quartiles based on their EI stratified by sex. BMI was calculated using self-reported height and body weight. Mortality data were collected between 30 July 2011 and 30 November 2016. Statistical analysis was performed using the multivariable-adjusted Cox proportional hazard model with a restricted cubic spline.

RESULTS

The 8051 participants' mean (standard deviation) age and BMI were 73.5 (6.1) years and 22.6 (3.0) kg/m² , respectively. The mean (standard deviation) EI with and without calibration was 1909 (145) kcal/day and 1569 (358) kcal/day in women and 2383 (160) kcal/day and 1980 (515) kcal/day in men, respectively. During the median 4.75 years of follow-up (36 552 person-years), 661 deaths were recorded. In both women (hazard ratio [HR], 0.63; 95% confidence interval [CI] [0.41, 0.98]) and men (HR, 0.62; 95% CI [0.44, 0.87]), after adjusting for confounders, the top quartile as compared with the bottom calibrated EI quartile showed a negative association with risk of all-cause mortality. The lowest HR for all-cause mortality was 1900-2000 kcal/day in women and 2400-2600 kcal/day in men. However, after adjusting for BMI, no significant association was observed between the calibrated EI and the risk of death. These associations could not be confirmed in the uncalibrated EI. The HR for mortality was minimal at a BMI of 23 kg/m² in both men and women, with or without adjustment for the calibrated EI.

CONCLUSIONS

Calibrated EI was negatively associated with mortality risk but not uncalibrated EI. This may be mediated by an increase in body weight over time. Caution is required when interpreting the association between EI and mortality risk without adjusting for self-reported measurement errors and outcomes.

Contributions of the Women's Health Initiative to Cardiovascular Research: JACC State-of-the-Art Review

The WHI (Women's Health Initiative) enrolled 161,808 racially and ethnically diverse postmenopausal women, ages 50-79 years, from 1993 to 1998 at 40 clinical centers across the United States. In its clinical trial component, WHI evaluated 3 randomized interventions (menopausal hormone therapy; diet modification; and calcium/vitamin D supplementation) for the primary prevention of major chronic diseases, including cardiovascular disease, in older women. In the WHI observational study, numerous clinical, behavioral, and social factors have been evaluated as predictors of incident chronic disease and mortality. Although the original interventions have been completed, the WHI data and biomarker resources continue to be leveraged and expanded through ancillary studies to yield novel insights regarding cardiovascular disease prevention and healthy aging in women.

Biomarker-Calibrated Red and Combined Red and Processed Meat Intakes with Chronic Disease Risk in a Cohort of Postmenopausal Women

BACKGROUND

The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet.

OBJECTIVES

We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women.

METHODS

Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020).

RESULTS

Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption.

CONCLUSIONS

A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

Leveraging Observational Cohorts to Study Diet and Nutrition in Older Adults: Opportunities and Obstacles

By 2060, the number of adults aged ≥65 y is expected to double, and the ≥85 y segment of the population is expected to triple in the United States. US federal nutrition guidance is based on the premise that healthy diets contribute to delaying the onset and progression of many age-related diseases and disability. Yet, little is known about the dietary intakes or nutritional needs across the older adulthood age span. This review aims to identify community-based cohorts that collected information on dietary intake of adults ≥65 y in the United States. Thirty-two cohorts met all inclusion criteria. We summarized information on the cohorts' design, demographics, and diet assessment. We also identified key gaps in the existing databases that, if filled, could enhance their utility to address certain research questions. This review serves as a valuable inventory of cohorts that can be leveraged to answer key questions about the diet and nutritional needs of the oldest old, who represent the fastest growing segment of the population in the United States.

Dietary Fat Intake: Associations with Dietary Patterns and Postmenopausal Breast Cancer-A Case-Control Study

The aim of this study was to assess the associations of dietary fat intake with BC occurrence and dietary patterns. This case-control study involved 420 women aged 40−79 years from northeastern Poland, including 190 newly diagnosed BC cases. Dietary data were collected using a food frequency questionnaire (62-item FFQ-6®). The Quick Food Scan of the National Cancer Institute and the Percentage Energy from Fat Screener scoring procedures were used to estimate the percentage energy from dietary fat (Pfat). The odds of BC occurrence was three times higher in the Pfat > 32%. The Pfat > 32% was positively associated with the ‘Non-Healthy’ DP and inversely associated with the Polish-aMED® score, ‘Prudent’ DP, and ‘Margarine and Sweetened Dairy’ DP. This case-control study suggests that a higher dietary fat intake (>32%) may contribute to an increased occurrence of peri- and postmenopausal breast cancer in women. Given the obtained results, an unhealthy dietary pattern characterized by the consumption of highly processed, high in sugar foods and animal fat foods should be avoided to reduce fat intake. Instead, the frequent consumption of low-processed plant foods, fish, and moderate consumption of low-fat dairy should be recommended since this pro-healthy diet is inversely associated with dietary fat intake.

Metabolomics Meets Nutritional Epidemiology: Harnessing the Potential in Metabolomics Data

Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a "black box" approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.