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6. List of Contributors

Author

Afonso, C., primary, Beals, J.W., additional, Bell, A., additional, Burd, N.A., additional, Celis-Morales, C., additional, Conklin, A.I., additional, de Groot, L.C.P.G.M., additional, de Morais, C., additional, Dean, M., additional, Donini, L.M., additional, Fjellström, C., additional, Franco, O.H., additional, Gettings, M.A., additional, Grunert, K.G., additional, Janse, A., additional, Kiefte-De Jong, J.C., additional, Lara, J., additional, Livingstone, K.M., additional, Mak, Tsz Ning, additional, Mathers, J.C., additional, Mattsson Sydner, Y., additional, Monsivais, P., additional, Moschis, G.P., additional, Nordin, S., additional, Plastow, N.A., additional, Raats, M.M., additional, Schnettler, B., additional, Schoufour, J.D., additional, Shy, E.L., additional, Tapsell, L., additional, van Asselt, D., additional, van der Zanden, L.D.T., additional, van Orten-Luiten, A.C., additional, van Trijp, H.C.M., additional, Vaz de Almeida, M.D., additional, Voortman, T., additional, Walton, K., additional, and Witkamp, R., additional

Published
2017
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7. Vitamin D status during fetal life and childhood kidney outcomes

Author

Miliku, K., Voortman, T., Franco, O.H., McGrath, J.J., Eyles, D.W., Burne, T.H., Hofman, A., Tiemeier, H., and Jaddoe, V.W.V.

Subjects
Fetus -- Growth, Alfacalcidol -- Health aspects, Calcifediol -- Health aspects, Vitamin D -- Health aspects, Kidneys -- Health aspects, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Maternal vitamin D deficiency during pregnancy may influence offspring kidney health. We aimed to examine the associations of 25-hydroxyvitamin D (25(OH)D) blood levels during fetal life with kidney outcomes at school age. SUBJECTS/METHODS: This study was embedded in a population-based prospective cohort study among 4212 mother-child pairs. We measured maternal second trimester (18-25 weeks) and fetal cord blood (at birth) 25(OH)D levels. At a median age of 6.0 years, we measured children's combined kidney volume, glomerular filtration rate (eGFR) from creatinine and cystatin C serum levels, and microalbuminuria from albumin and creatinine urine levels. RESULTS: Of all mothers, 21.9% had severely deficient levels (25(OH)D < 25.0 nmol/l), 25.7% had deficient levels (25.0-49.9 nmol/l), 25% had sufficient levels (50.0-74.9 nmol/l) and 27.4% had optimal levels (≥ 75.0 nmol/l). Maternal 25(OH)D levels were not consistently associated with childhood combined kidney volume. Higher maternal 25(OH)D levels were associated with lower childhood eGFR (difference -0.94 ml/min per 1.73 [m.sup.2] (95% confidence interval, -1.73;-0.15) per 1 standard deviation (s.d.) increase in 25(OH)D). Maternal 25(OH)D levels were not associated with microalbuminuria. Cord blood 25(OH)D levels were not associated with childhood kidney outcomes. The associations of maternal 25(OH)D levels with childhood eGFR were partly explained by childhood vitamin D status. CONCLUSIONS: Our findings suggest that maternal 25(OH)D levels during pregnancy may influence childhood kidney outcomes. These results should be considered hypothesis generating. Further studies are needed to replicate the observations, to examine the underlying mechanisms and to identify the long-term clinical consequences. European Journal of Clinical Nutrition (2016) 70, 629-634; doi: 10.1038/ejcn.2015.216; published online 23 December 2015, INTRODUCTION Vitamin D deficiency is related to various adverse health outcomes in early and later life. (1-4) An accumulating body of evidence suggests that vitamin D status during pregnancy may [...]

Published
2016
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8. Adherence to the Dutch dietary guidelines is inversely associated with 20-year mortality in a large prospective cohort study

Author

van Lee, L., Geelen, A., Kiefte-de Jong, J.C., Witteman, J.C.M., Hofman, A., Vonk, N., Jankovic, N., Hooft van Huysduynen, E.J.C., de Vries, J.H.M., van 't Veer, P., Franco, O.H., and Feskens, E.J.M.

Subjects
Stroke (Disease) -- Statistics, Mortality -- Statistics -- Denmark, Cardiovascular diseases -- Statistics, Cancer -- Statistics, Diet -- Complications and side effects, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: The Dutch guidelines for a healthy diet aim to reduce major chronic diseases. However, supporting evidence on their overall association with all-cause and cause-specific mortality is limited. Recently, the Dutch Healthy Diet-index (DHD-index) has been developed to assess adherence to these guidelines. The aim was to examine the association between the DHD-index and all-cause mortality and deaths from cardiovascular disease (CVD), coronary heart disease (CHD), stroke and cancer. SUBJECTS/METHODS: We followed 3593 men and women aged 55 years and older enrolled in the Rotterdam Study, a populationbased prospective cohort study, from baseline in 1990-1993 to 2011. A validated 170-item food frequency questionnaire at baseline was used to calculate the DHD-index score (maximum 90 points). Cox proportional hazard models were used to estimate hazard ratios (HRs) adjusting for age, sex, total energy intake, smoking and educational level. RESULTS: During the 20-year follow-up, 1831 (51%) deaths were reported. Mean DHD-index score was 60.6 (s.d. 10.6). The score was inversely associated with all-cause mortality (highest vs lowest quartile HR 0.77;95% confidence interval (CI) 0.67, 0.89). Inverse but non-significant associations were observed for mortality due to CVD (HR 0.74;95% CI 0.55, 1.01), CHD (HR 0.60;95% CI 0.34, 1.06) and stroke (HR 0.67;95% CI 0.36,1.22), whereas no association was observed with cancer mortality (HR 0.99;95% CI 0.90,1.11). CONCLUSIONS: A higher level of adherence to the Dutch dietary guidelines, as assessed with the DHD-index, was associated with a lower risk of all-cause mortality, probably due to an inverse association with cardiovascular causes of death. European Journal of Clinical Nutrition (2016) 70, 262-268; doi:10.1038/ejcn.2015.163; published online 21 October 2015, INTRODUCTION Traditionally, nutritional epidemiology focused on investigating associations between energy, single nutrients, food products, or food groups, and diseases. However, several biological and statistical arguments have been put forward to [...]

Published
2016
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9. The associations of alcohol, coffee and tobacco consumption with gait in a community-dwelling population

Author

Verlinden, V.J.A, Maksimovic, A., Mirza, S.S., Ikram, M.A., Jong, J.C. Kiefte-de, Hofman, A., Franco, O.H., Tiemeier, H., and van der Geest, J.N.

Subjects
Falls (Accidents) -- Analysis -- Health aspects -- Physiological aspects -- Risk factors, Drinking of alcoholic beverages -- Analysis -- Health aspects, Coffee -- Health aspects, Gait disorders -- Physiological aspects, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Gait is an important health indicator, relating strongly to the risk of falling, morbidity and mortality. In a community-dwelling population, we investigated associations of alcohol, coffee and tobacco consumption with gait. SUBJECTS/METHODS: Two thousand forty-six non-demented participants from the Rotterdam Study underwent gait assessment by electronic walkway. We measured gait velocity and Global Gait, which is the average of seven gait domains: Rhythm, Phases, Variability, Pace, Tandem, Turning and Base of Support. Alcohol, coffee and tobacco consumption was assessed by questionnaires. With analysis of covariance, we investigated associations of consumption of alcoholic beverages, coffee consumption and smoking with Global Gait, gait velocity and the seven individual gait domains. RESULTS: In all, 81.9% of participants drank alcohol, 92.4% drank coffee, 17.3% were current smokers and 50.9% were past smokers. Moderate alcohol consumption (1-3 glasses per day) associated with better gait, as measured by Global Gait (0.20 standard deviations (s.d.) (95% confidence interval: 0.10;0.31)), gait velocity (2.65 cm/s (0.80;4.50)), Rhythm and Variability. Consuming high amounts of coffee (> 3 cups per day) associated with better Global Gait (0.18 s.d. (0.08;0.28)), gait velocity (2.63 cm/s (0.80;4.45)), Pace, Turning and Variability. Current smoking associated with worse Global Gait (-0.11 s.d. (-0.21;0.00)), gait velocity (-3.47 cm/s (-5.33;- 1.60)), Rhythm and Pace, compared with non-smokers. CONCLUSIONS: In a community-dwelling population, consuming > 1 cup of coffee and 1-3 glasses of alcohol relate to better gait, whereas smoking is related to worse gait. Further studies are required to evaluate whether interventions targeting substance consumption may aid to prevent or reduce gait deterioration and thereby related health problems. doi:10.1038/ejcn.2015.120;published online 29 July 2015, INTRODUCTION Alcohol, coffee and tobacco are widely consumed and have addictive properties. (1-6) These substances contain many different components, which have various effects on health with chronic use. (1-5,7-9) Although [...]

Published
2016
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10. Influence of breastfeeding on retinal vessel calibers in schoolage children. The Generation R Study

Author

Gishti, O., Jaddoe, V.W.V., Duijts, L., Franco, O.H., Hofman, A., Ikram, M.K., and Gaillard, R.

Subjects
Breast feeding -- Physiological aspects -- Health aspects, Cardiovascular diseases -- Physiological aspects -- Risk factors, Retina -- Blood-vessels, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: A shorter breastfeeding duration is associated with an increased risk of cardiovascular disease in adulthood. Early microvasculature structure adaptations may be part of the underlying mechanism. We examined the associations of ever breastfeeding, breastfeeding duration and exclusivity, and the timing of introduction of solid foods with retinal vessel calibers in children. SUBJECTS/METHODS: We performed a population-based prospective cohort study from fetal life onwards in the city of Rotterdam, the Netherlands. We obtained information on ever breastfeeding, breastfeeding duration and exclusivity, and age at introduction of solid foods from postal questionnaires at the ages of 2,6 and 12 months after birth. At the median age of 6.0 years (90% range: 5.7-6.8), we measured retinal arteriolar and venular calibers from digitized retinal photographs among 3220 children. Grader-specific s.d. scores (SDS) for both central retinal and arteriolar equivalents were constructed. RESULTS: We observed that in the models only adjusted for child's age, sex and ethnicity, children who were never breastfed had narrower retinal arteriolar and venular calibers in childhood as compared with children who were breastfed (differences in retinal arteriolar and venular calibers, respectively: -0.16 SDS (95% confidence interval (CI): -0.29, -0.03) and -0.18 SDS (95% CI: -0.32, -0.04)). After additional adjustment for maternal and childhood socio-demographic and lifestyle-related characteristics, never breastfeeding was only associated with narrower retinal venular caliber (difference: -0.15 SDS (95% CI: -0.29, -0.02)). We did not observe associations of breastfeeding duration or exclusivity, or age at introduction of solid foods with retinal vessel calibers. CONCLUSIONS: Children who were never breastfed tended to have narrower retinal venular calibers. We did not observe associations of breastfeeding duration with retinal vessel calibers. Family-based socio-demographic factors, maternal lifestyle-related factors and childhood factors only slightly influenced the observed associations. These results should be considered a hypothesis generating for further observational and experimental studies. doi:10.1038/ejcn.2015.113; published online 15 July 2015, INTRODUCTION A shorter breastfeeding duration and non-exclusivity in infancy have been associated with higher risks of hypertension in adulthood. (1) Studies in children have also shown that shorter duration of [...]

Published
2016
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11. Dietary vitamin A intake and bone health in the elderly: the Rotterdam study

Author

de Jonge, E.A.L., Kiefte-de Jong, J.C., Campos-Obando, N., Booij, L., Franco, O.H., Hofman, A., Uitterlinden, A.G., Rivadeneira, F., and Zillikens, M.C.

Subjects
Aged -- Health aspects, Vitamin A -- Health aspects, Bones -- Health aspects, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: High vitamin A intake may be associated with a decreased bone mineral density (BMD) and increased risk of fractures. Our objectives were to study whether dietary intake of vitamin A (total, retinol or beta-carotene) is associated with BMD and fracture risk and if associations are modified by body mass index (BMI) and vitamin D. SUBJECTS/METHODS: Participants were aged 55 years and older (n = 5288) from the Rotterdam Study, a population-based prospective cohort. Baseline vitamin A and D intake was measured by a food frequency questionnaire. BMD was measured by dual-energy X-ray absorptiometry at four visits between baseline (1989-1993) and 2004. Serum vitamin D was assessed in a subgroup (n = 3161). Fracture incidence data were derived from medical records with a mean follow-up time of 13.9 years. RESULTS: Median intake of vitamin A ranged from 684 retinol equivalents (REs)/day (quintile 1) to 2000 REs/day (quintile 5). After adjustment for confounders related to lifestyle and socioeconomic status, BMD was significantly higher in subjects in the highest quintile of total vitamin A (mean difference in BMD (95% confidence interval (CI)) = 11.53 (0.37-22.7) mg/[cm.sup.2]) and retinol intake (mean difference in BMD (95% CI) = 12.57 (1.10-24.05) mg/[cm.sup.2]) than in the middle quintile. Additional adjustment for BMI diluted these associations. Fracture risk was reduced in these subjects. Significant interaction was present between intake of retinol and overweight (BMI >25 kg/[m.sup.2]) in relation to fractures (P for interaction =0.05), but not BMD. Stratified analysis showed that these favourable associations with fracture risk were only present in overweight subjects (BMI >25 kg/[m.sup.2]). No effect modification by vitamin D intake or serum levels was observed. CONCLUSIONS: Our results suggest a plausible favourable relation between high vitamin A intake from the diet and fracture risk in overweight subjects, whereas the association between vitamin A and BMD is mainly explained by BMI. European Journal of Clinical Nutrition (2015) 69, 1360-1368;doi: 10.1038/ejcn.2015.154; published online 16 September 2015, INTRODUCTION Adequate nutrition is an important modifiable factor for maintaining bone mineral density (BMD). Although the emphasis in previous studies has been on the intake of calcium and vitamin D, [...]

Published
2015
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12. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Author

Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., Hoed, Marcel Den, Wang, Zhe, Emmerich, A., Pillon, N.J., Moore, T., Hemerich, D., Cornelis, M.C., Mazzaferro, E., Broos, S., Ahluwalia, T.S., Bartz, T.M., Bentley, A.R., Bielak, L.F., Chong, M., Chu, A.Y., Berry, D., Dorajoo, R., Dueker, N.D., Kasbohm, E., Feenstra, B., Feitosa, M.F., Gieger, C., Graff, M, Hall, L.M., Haller, T., Hartwig, F.P., Hillis, D.A., Huikari, V., Heard-Costa, N., Holzapfel, C., Jackson, A.U., Johansson, Å., Jørgensen, A.M., Kaakinen, M.A., Karlsson, R., Kerr, K.F., Kim, Boram, Koolhaas, C.M., Kutalik, Z., Lagou, V., Lind, P.A., Lorentzon, M., Lyytikäinen, L.P., Mangino, M., Metzendorf, C., Monroe, K.R., Pacolet, A., Pérusse, L., Pool, R., Richmond, R.C., Rivera, N.V., Robiou-du-Pont, S., Schraut, K.E., Schulz, C.A., Stringham, H.M., Tanaka, T., Teumer, A., Turman, C., Most, P.J. van der, Vanmunster, M., Rooij, F.J. van, Vliet-Ostaptchouk, J.V. Van, Zhang, Xiaoshuai, Zhao, J.H., Zhao, W, Balkhiyarova, Z., Balslev-Harder, M.N., Baumeister, S.E., Beilby, J., Blangero, J., Boomsma, D.I., Brage, S., Braund, P.S., Brody, J.A., Bruinenberg, M., Ekelund, U., Liu, C.T., Cole, J.W., Collins, F.S., Cupples, L.A., Esko, T., Enroth, S., Faul, J.D., Fernandez-Rhodes, L., Fohner, A.E., Franco, O.H., Galesloot, T.E., Gordon, S.D.S., Grarup, N., Hartman, C.A., Heiss, G., Hui, J., Illig, T., Jago, R., James, A., Joshi, P.K., Jung, T., Kähönen, M., Kilpeläinen, T.O., Koh, W.P., Kolcic, I., Kiemeney, L.A.L.M., Loos, R.J.F., and Hoed, Marcel Den

Abstract

Contains fulltext : 282313.pdf (Publisher’s version ) (Open Access), Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type II(A) muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Published
2022

13. Sugar-containing beverage intake in toddlers and body composition up to age 6 years: the Generation R Study

Author

Leermakers, E.T.M., Felix, J.F., Erler, N.S., Cerimagic, A., Wijtzes, A.I., Hofman, A., Raat, H., Moll, Ha, Rivadeneira, F., Jaddoe, V.W.V., Franco, O.H., and Kiefte-de Jong, J.C.

Subjects
Weight gain -- Risk factors, Body mass index -- Measurement, Child nutrition -- Research, Soft drinks -- Health aspects, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVE: Intake of sugar-containing beverages (SCBs) has been associated with higher body mass index (BMI) in childhood. The potential effect of SCB intake during infancy is unclear. We examined the association of SCB intake at 13 months with BMI development until 6 years and body composition at age 6 years. SUBJECTS/METHODS: This study included 2371 Dutch children from a population-based prospective cohort study. SCB intake at 13 months was assessed using a Food Frequency Questionnaire with validation against 24-h recalls and was standardized for total energy. BMI was calculated from repeated weight and height measurements, and age- and sex- specific s.d. scores were calculated. Adiposity was measured using Dual-energy X-ray absorptiometry. RESULTS: In girls, higher SCB intake at 13 months was significantly associated with higher BMI at ages 2, 3, 4 and 6 years (at age 6 years BMI (s.d. score) increase 0.11 (95% confidence interval (CI) +0.00;0.23), high versus low intake). We observed a tendency towards higher android/gynoid fat ratio in girls with high intake (s.d. increase 0.14 (95% CI - 0.02;0.29), versus low intake) but not with body fat percentage. In boys, there was no association with BMI or body composition, but boys with high SCB intake at 13 months were taller at age 6 years (s.d. increase 0.14 (95% CI +0.00; 0.27), versus low intake). CONCLUSIONS: Higher SCB intake at 13 months was associated with higher BMI up to age 6 years in girls but not in boys. Our results imply that the unfavorable effects of SCB intake start early in life and that dietary advice regarding limiting SCB intake should already be given early in life. European Journal of Clinical Nutrition (2015) 69, 314-321; doi: 10.1038/ejcn.2015.2; published online 4 February 2015, INTRODUCTION The prevalence of childhood obesity has increased dramatically over the past decades. In 2010, it was estimated to be 11.7% in the developed countries. (1) Similarly, intake of sugar-containing [...]

Published
2015
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14. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice

Author

Visseren, F.L.J. Mach, F. Smulders, Y.M. Carballo, D. Koskinas, K.C. Back, M. Benetos, A. Biffi, A. Boavida, J.-M. Capodanno, D. Cosyns, B. Crawford, C. Davos, C.H. Desormais, I. Di Angelantonio, E. Franco, O.H. Halvorsen, S. Richard Hobbs, F.D. Hollander, M. Jankowska, E.A. Michal, M. Sacco, S. Sattar, N. Tokgozoglu, L. Tonstad, S. Tsioufis, K.P. Van Dis, I. Van Gelder, I.C. Wanner, C. Williams, B.

Published
2022

15. Does reproductive stage impact cardiovascular disease risk factors? Results from a population-based cohort in Lausanne (CoLaus study)

Author

Raguindin, P.F. Cardona, I. Muka, T. Lambrinoudaki, I. Gebhard, C. Franco, O.H. Marques-Vidal, P. Glisic, M.

Abstract

Context: Menopause has been associated with adverse cardiovascular disease (CVD) risk profile, yet it is unclear whether the changes in CVD risk factors differ by reproductive stage independently of underlying ageing trajectories. Design: The CoLaus study is a prospective population-based cohort study in Lausanne, Switzerland. Patients: We used data from women at baseline and follow-up (mean: 5.6 ± 0.5 years) from 2003 to 2012 who did not use hormone therapy. We classified women into (i) premenopausal, (ii) menopausal transition, (iii) early (≤5 years) and (iv) late (>5 years) postmenopausal by comparing their menstruation status at baseline and follow-up. Measurements: We measured fasting lipids, glucose and cardiovascular inflammatory markers. We used repeated measures (linear mixed models) for longitudinal analysis, using premenopausal women as a reference category. We adjusted analyses for age, medications and lifestyle factors. Results: We used the data from 1710 women aged 35–75 years. Longitudinal analysis showed that the changes in CVD risk factors were not different in the other three menopausal categories compared to premenopausal women. When age was used as a predictor variable and adjusted for menopause status, most CVD risk factors increased, while interleukin-6 and interleukin-1β decreased with advancing age. Conclusion: The current study suggests that women have a worsening cardiovascular risk profile as they age, and although menopausal women may have higher levels of cardiovascular risk factors compared to premenopausal women at any given time, the 5-year changes in cardiovascular risk factors may not depend on the reproductive stage. © 2022 The Authors. Clinical Endocrinology published by John Wiley & Sons Ltd.

Published
2022

16. Infant diet and metabolic outcomes in school-age children. the generation R study

Author

Gishti, O., Gaillard, R., Durmus, B., Hofman, A., Duijts, L., Franco, O.H., and Jaddoe, V.W.V.

Subjects
Medical research, Medicine, Experimental, Breast feeding -- Health aspects, Food/cooking/nutrition, Health
Abstract

BACKGROUND: Breastfeeding duration is associated with the risks of cardio- metabolic diseases in adulthood. We examined the associations of infant feeding patterns with metabolic outcomes in children and whether any association was explained by family-based socio-demographic, maternal lifestyle-related or childhood factors. SUBJECTS/METHODS: We performed a population-based prospective cohort study in 3417 children to examine the associations of breastfeeding duration and exclusivity and age at introduction of solid foods with blood levels of lipids, insulin and C-peptide and risk of clustering of cardio-metabolic risk factors at the median age of 6.0 years (90% range 5.7-6.8). RESULTS: We observed that, in the models only adjusted for child's age and sex, ever breastfeeding was not associated with childhood blood levels of lipids but was associated with higher insulin and C- peptide concentrations (P-value < 0.05). Breastfeeding duration and exclusivity were not consistently associated with metabolic outcomes. Early introduction of solid foods was associated with higher levels of total cholesterol (P-value < 0.05) but not with high- density lipoprotein and low-density lipoprotein cholesterol, triglycerides and insulin levels. Shorter breastfeeding duration and exclusive breastfeeding were associated with increased risks of clustering of cardio-metabolic risk factors. After additional adjustment for family, maternal and childhood factors, none of these associations remained significant. CONCLUSIONS: In conclusion, we found no consistent associations of infant feeding patterns with metabolic outcomes at school age, after taking into account family-based socio-demographic, maternal lifestyle-related or childhood factors. Whether infant diet composition influences metabolic outcomes in later life should be further studied. European Journal of Clinical Nutrition (2014) 68, 1008-1015; doi: 10.1038/ejcn.2014.81; published online 30 April 2014, INTRODUCTION Breastfeeding during infancy has been suggested to have a protective effect on the development of cardio-metabolic diseases and type 2 diabetes and their risk factors in later life. (1-6) [...]

Published
2014
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17. Nutrient-rich foods, cardiovascular diseases and all-cause mortality: the Rotterdam study

Author

Streppel, M.T., Sluik, D., van Yperen, J.F., Geelen, A., Hofman, A., Franco, O.H., Witteman, J.C.M., and Feskens, E.J.M.

Subjects
Mortality -- Research -- Netherlands, Cardiovascular research, Cardiovascular diseases -- Risk factors, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: The nutrient-rich food (NRF) index assesses nutrient quality of individual food items by ranking them according to their nutrient composition. The index reflects the nutrient density of the overall diet. We examined the associations between the NRF9.3 index--a score on the basis of nine beneficial nutrients (protein, fiber, vitamins and minerals) and three nutrients to limit (saturated fat, sugar and sodium)--incidence of cardiovascular disease (CVD) events and all-cause mortality. SUBJECTS/METHODS: A total of 4969 persons aged 55 and older from the Rotterdam Study, a prospective cohort study in the Netherlands, were studied. First, all foods were scored on the basis of their nutrient composition, resulting in an NRF9.3 score on food item level. Subsequently, they were converted into individual weighted scores on the basis of the amount of calories of each food item consumed by the subjects and the total energy intake. The hazard ratios (HRs) of the NRF9.3 index score were adjusted for age, gender, body mass index, smoking history, doctor-prescribed diet, alcohol consumption and education. RESULTS: Food groups that contributed most to the NRF9.3 index score were vegetables, milk and milk products, fruit, bread and potatoes. A high NRF9.3 index score was inversely associated with all-cause mortality (HR Q4 versus Q1: 0.84 (95% confidence interval: 0.74, 0.96)). Associations were stronger in women than in men. The NRF9.3 index score was not associated with incidence of CVD. CONCLUSION: Elderly with a higher NRF9.3 index score, indicating more beneficial components and/or less limiting components, had a lower risk of all-cause mortality. Consuming a nutrient-dense diet may improve survival. European Journal of Clinical Nutrition (2014) 68, 741-747; doi:10.1038/ejcn.2014.35;published online 19 March 2014, INTRODUCTION The Dietary Guidelines for Americans, 2010 recommend eating foods that are low in calories and to focus on consuming more nutrient-dense foods and beverages. (1) Diet quality scores, for [...]

Published
2014
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19. Factors associated with the timing of introduction of complementary feeding: the Generation R Study

Author

Tromp, I.I.M., Briede, S., Kiefte-de Jong, J.C., Renders, C.M., Jaddoe, V.W.V., Franco, O.H., Hofman, A., Raat, H., and Moll, H.A.

Subjects
Breast feeding -- Social aspects, Mother and child -- Health aspects, Social medicine -- Research, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Many parents do not follow recommendations for the timing of introduction of complementary feeding. The aim of this study was to identify determinants associated with the timing of introduction of complementary feeding in a multiethnic birth cohort. SUBJECTS/METHODS: Subjects were 3561 mothers and infants participating in a prospective cohort study. The timing of introduction of complementary feeding and maternal and infant characteristics were obtained by parent-derived questionnaires. Regression analyses were performed to identify determinants for the timing of introduction of complementary feeding ( RESULTS: In total, 62% of infants were introduced to complementary feeding before the age of 6 months. Determinants for very early ( CONCLUSIONS: This study confirmed determinants for the timing of introduction of complementary feeding that have been identified by previous studies, which may be appropriate targets for education and guidance. Moreover, mothers whose infants attend day care and have a family history of asthma, atopy or allergy to cow's milk may need guidance to follow infant feeding recommendations. European Journal of Clinical Nutrition (2013) 67, 625-630;doi: 10.1038/ejcn.2013.50; published online 6 March 2013 Keywords: introduction of solids; infant feeding; complementary feeding; weaning, INTRODUCTION The first year of life includes many transitions in food consumption. (1) Appropriate nutrition during infancy is essential for adequate growth, development and health. (2) The World Health Organization [...]

Published
2013
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20. Maternal fish consumption during pregnancy and risks of wheezing and eczema in childhood: The Generation R Study

Author

Leermakers, E.T.M., Sonnenschein-van der Voort, A.M.M., Heppe, D.H.M., de Jongste, J.C., Moll, H.A., Franco, O.H., Hofman, A., Jaddoe, V.W.V., and Duijts, L.

Subjects
Eczema -- Diagnosis -- Risk factors, Wheeze -- Health aspects, Fish as food -- Health aspects, Mothers -- Health aspects, Pregnant women -- Health aspects, Asthma -- Risk factors -- Diagnosis, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Maternal fish consumption during pregnancy might influence the fetal immune system through anti-inflammatory effects of omega-3 fatty acids, and might affect the risks of childhood asthma and atopy. In Generation R, a prospective cohort study in the Netherlands, we examined the associations of first trimester fish consumption with childhood wheezing and eczema in the first 4 years of life. METHODS: In total, 2976 mothers completed a 293-item semiquantitative food frequency questionnaire covering dietary intake in the first trimester. The occurrence of wheezing and eczema was yearly assessed by questionnaires. RESULTS: Median weekly fish consumption was 83 (95% range 0-316) grams per week. We observed no consistent associations of maternal total-, lean- or fatty-fish consumption during pregnancy with the risks of childhood wheezing. Maternal shellfish consumption of 1-13 g per week was associated with overall increased risks of childhood wheezing and eczema (OR 1.20 (1.04, 1.40) and OR 1.18 (1.01, 1.37), respectively). Maternal fatty fish consumption of 35-69 g per week was associated with increased overall risks of childhood eczema (OR 1.17 (1.00, 1.38)), but maternal total- or lean-fish consumption was not. CONCLUSIONS: During pregnancy, shellfish consumption was associated with increased risks of wheezing and eczema, while fatty fish consumption was associated with a higher risk of eczema only. Maternal total fish or lean fish consumption were not associated with wheezing or eczema. Further studies are needed to replicate these findings and to explore underlying mechanisms. European Journal of Clinical Nutrition (2013) 67, 353-359; doi: 10.1038/ejcn.2013.36; published online 27 February 2013 Keywords: pregnancy; fish consumption; asthma symptoms; eczema; cohort study; atopy, INTRODUCTION Specific adverse fetal and infant exposures might lead to the development of asthma and atopic disease. (1-3) Suboptimal maternal diet during pregnancy is one of these exposures, which might [...]

Published
2013
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21. Macronutrient intake and frailty: the Rotterdam Study

Author

Verspoor, E., Voortman, T., Rooij, F.J. van, Rivadeneira, F., Franco, O.H., Kiefte-de Jong, J.C., Schoufour, J.D., Verspoor, E., Voortman, T., Rooij, F.J. van, Rivadeneira, F., Franco, O.H., Kiefte-de Jong, J.C., and Schoufour, J.D.

Abstract

Contains fulltext : 229270.pdf (Publisher’s version ) (Open Access), PURPOSE: To investigate the longitudinal association between the macronutrient composition of the diet and frailty. METHODS: Data were obtained from 5205 Dutch middle-aged and older adults participating in the Rotterdam Study. Frailty was measured using a frailty index based on the accumulation of 38 health-related deficits, score between 0 and 100, and a higher score indicating more frailty. Frailty was assessed at baseline and 11 years later (range of 23 years). Macronutrient intake was assessed using food-frequency questionnaires. The association between macronutrients and frailty over time was evaluated using multivariable linear regression, adjusted for the frailty index at baseline, energy intake, and other relevant confounders. All analyses were performed in strata of BMI. RESULTS: Median frailty index score was 13.8 points (IQR 9.6; 19.1) at baseline and increased by a median of 2.3 points (IQR - 2.0; 7.6) after 11 years. Overall, we found no significant associations between intake of carbohydrates or fat and frailty over time. We did observe a significant positive association between an iso-energetic intake of 10 g protein and frailty over time (β 0.31 (95% CI 0.06; 0.55)) which was mainly driven by animal protein (β 0.31 (95% CI 0.07; 0.56)). It did not depend on whether it was substituted fat or carbohydrates. CONCLUSIONS: Our findings suggest that a reduction in the intake of animal protein may improve the overall health status over time in a relatively healthy population. More research is needed on the optimal macronutrient composition of the diet and frailty in more vulnerable populations.

Published
2020

22. Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Author

Hahn, J., Fu, Y. P., Brown, M.R., Bis, J.C. (Joshua), de Vries, PS, Feitosa, M.F. (Mary Furlan), Yanek, L.R. (Lisa), Weiss, S., Giulianini, F. (Franco), Smith, A.V. (Davey), Guo, X.., Bartz, TM, Becker, D.M. (Diane), Becker, L.C. (Lewis), Boerwinkle, E.A. (Eric), Brody, JA, Chen, Y.D. (Y.), Franco, O.H., Grove, M., Harris, T.B. (Tamara), Hofman, A. (Albert), Hwang, S.J., Kral, B.G., Launer, LJ, Markus, M.R.P. (Marcello R. P.), Rice, KM, Rich, S.S. (Stephen), Ridker, P.M. (Paul), Rivadeneira Ramirez, F. (Fernando), Rotter, J.I. (Jerome), Sotoodehnia, N. (Nona), Taylor, K.D. (Kent), Uitterlinden, A.G. (André), Völker, U., Völzke, H. (Henry), Yao, J, Chasman, D.I. (Daniel), Dörr, M., Guonason, V. (Vilmundur), Mathias, J. (Jasmine), Post, W., Psaty, B.M. (Bruce), Dehghan, A., O’Donnell, C.J., Morrison, A.C. (Alanna), Hahn, J., Fu, Y. P., Brown, M.R., Bis, J.C. (Joshua), de Vries, PS, Feitosa, M.F. (Mary Furlan), Yanek, L.R. (Lisa), Weiss, S., Giulianini, F. (Franco), Smith, A.V. (Davey), Guo, X.., Bartz, TM, Becker, D.M. (Diane), Becker, L.C. (Lewis), Boerwinkle, E.A. (Eric), Brody, JA, Chen, Y.D. (Y.), Franco, O.H., Grove, M., Harris, T.B. (Tamara), Hofman, A. (Albert), Hwang, S.J., Kral, B.G., Launer, LJ, Markus, M.R.P. (Marcello R. P.), Rice, KM, Rich, S.S. (Stephen), Ridker, P.M. (Paul), Rivadeneira Ramirez, F. (Fernando), Rotter, J.I. (Jerome), Sotoodehnia, N. (Nona), Taylor, K.D. (Kent), Uitterlinden, A.G. (André), Völker, U., Völzke, H. (Henry), Yao, J, Chasman, D.I. (Daniel), Dörr, M., Guonason, V. (Vilmundur), Mathias, J. (Jasmine), Post, W., Psaty, B.M. (Bruce), Dehghan, A., O’Donnell, C.J., and Morrison, A.C. (Alanna)

Abstract

Background Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. Methods and results Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both crosssectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and allcause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 ×

Published
2020
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23. Associations of Activity and Sleep With Quality of Life: A Compositional Data Analysis

Author

Verhoog, S. (Sanne), Braun, K.V.E. (Kim), Bano, A. (Arjola), Rooij, F.J.A. (Frank) van, Franco, O.H. (Oscar), Koolhaas, C.M. (Chantal), Voortman, R.G. (Trudy), Verhoog, S. (Sanne), Braun, K.V.E. (Kim), Bano, A. (Arjola), Rooij, F.J.A. (Frank) van, Franco, O.H. (Oscar), Koolhaas, C.M. (Chantal), and Voortman, R.G. (Trudy)

Abstract

Introduction: Associations between time spent on physical activity, sedentary behavior, and sleep and quality of life are usually studied without considering that their combined time is fixed. This study investigates the reallocation of time spent on physical activity, sedentary behavior, and sleep during the 24-hour day and their associations with quality of life. Methods: Data from the 2011–2016 Rotterdam Study were used to perform this cross-sectional analysis among 1,934 participants aged 51–94 years. Time spent in activity levels (sedentary, light-intensity physical activity, moderate-to-vigorous physical activity, and sleep) were objectively measured with a wrist-worn accelerometer combined with a sleep diary. Quality of life was measured using the EuroQoL 5D-3L questionnaire. The compositional isotemporal substitution method was used in 2018 to examine the association between the distribution of time spent in different activity behaviors and quality of life. Results: Reallocation of 30 minutes from sedentary behavior, light-intensity physical activity, or sleep to moderate-to-vigorous physical activity was associated with a higher quality of life, whereas reallocation from moderate-to-vigorous physical activity to sedentary behavior, light-intensity physical activity, or sleep was associated with lower quality of life. To illustrate this, a reallocation of 30 minutes from sedentary behavior to moderate-to-vigorous physical activity was associated with a 3% (95% CI=2, 4) higher quality of life score. By contrast, a reallocation of 30 minutes from moderate-to-vigorous physical activity to sedentary behavior was associated with a 4% (95% CI=2, 6) lower quality of life score. Conclusions: Moderate-to-vigorous physical activity is important with regard to the quality of life of middle-aged and elderly individuals. The benefits of preventing less time spent in moderate-to-vigorous physical activity were greater than the benefits of more time spent in moderate-to-vi

Published
2020
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24. Survival After Uncomplicated EVAR in Octogenarians is Similar to the General Population of Octogenarians Without an Abdominal Aortic Aneurysm

Author

Rueda-Ochoa, O.L. (Oscar), van Bakel, P. (Pieter), Hoeks, S.E. (Sanne), Verhagen, H.J.M. (Hence), Deckers, J. (Jaap), Rizopoulos, D. (Dimitris), Ikram, M.A. (Arfan), Rouwet, E.V. (Ellen), Ultee, K.H.J. (Klaas), Raa, S. (Sander) ten, Franco, O.H. (Oscar), Kavousi, M. (Maryam), Rijn, M.J.E. (Marie Josee) van, Rueda-Ochoa, O.L. (Oscar), van Bakel, P. (Pieter), Hoeks, S.E. (Sanne), Verhagen, H.J.M. (Hence), Deckers, J. (Jaap), Rizopoulos, D. (Dimitris), Ikram, M.A. (Arfan), Rouwet, E.V. (Ellen), Ultee, K.H.J. (Klaas), Raa, S. (Sander) ten, Franco, O.H. (Oscar), Kavousi, M. (Maryam), and Rijn, M.J.E. (Marie Josee) van

Abstract

Objective: Long term survival after endovascular aortic aneurysm repair (EVAR) in octogenarians remains unclear. This was evaluated by comparing octogenarians after EVAR with a matched group of octogenarians without an abdominal aortic aneurysm (AAA) from the Rotterdam Study (RS). The influence of complications after EVAR on survival was also studied with the aim of identifying risk factors for the development of complications in octogenarians. Methods: Using propensity score matching (PSM), 83 EVAR octogenarians were matched for comorbidities with 83 octogenarians from the RS, and survival was compared between these two groups using Cox proportional hazard analysis. Then, complications were studied, defined as cardiac or pulmonary, renal deterioration, access site bleeding, acute limb ischaemia or bowel ischaemia, within 30 days of surgery between 83 EVAR octogenarians and 475 EVAR non-octogenarians. Also, the difference in baseline characteristics between the octogenarians with and without complications after EVAR were studied, and survival was compared between the RS controls and the complicated and uncomplicated EVAR octogenarians separately. Results: The total EVAR octogenarian population did not show an increased mortality risk compared with RS octogenarian controls (hazard ratio [HR] 1.28, 95% confidence interval [CI] 0.84–1.97). Post-operative complications occurred in 22 octogenarians (27%) and 59 non-octogenarians (12.4%, p < .001), mainly cardiac, pulmonary, and bleeding complications. All baseline characteristics were similar in the complicated EVAR octogenarians compared with the uncomplicated EVAR octogenarians. After uncomplicated EVAR, octogenarians had a similar survival compared with the RS controls (HR 1.0

Published
2020
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25. Egg consumption and cardiovascular risk: a dose–response meta-analysis of prospective cohort studies

Author

Godos, J. (Justyna), Micek, A. (Agnieszka), Brzostek, T. (Tomasz), Toledo, E. (Estefania), Iacoviello, L. (Licia), Astrup, A. (Arne), Franco, O.H. (Oscar), Galvano, F. (Fabio), Martinez-Gonzalez, M.A. (Miguel A.), Grosso, G. (Giuseppe), Godos, J. (Justyna), Micek, A. (Agnieszka), Brzostek, T. (Tomasz), Toledo, E. (Estefania), Iacoviello, L. (Licia), Astrup, A. (Arne), Franco, O.H. (Oscar), Galvano, F. (Fabio), Martinez-Gonzalez, M.A. (Miguel A.), and Grosso, G. (Giuseppe)

Abstract

Purpose: Cardiovascular disease (CVD) is a leading cause of mortality globally and is strongly influenced by dietary risk factors. The aim was to assess the association between egg consumption and risk of CVD risk/mortality, including coronary heart disease (CHD), stroke, and heart failure. Methods: MEDLINE, Embase, and Web of Science databases were searched through April 2020 for prospective studies. Two independent reviewers screened and extracted the data through standardized methods. Size effects were calculated as summary relative risks (SRRs) in a dose–response fashion through random-effects meta-analyses. Results: Thirty-nine studies including nearly 2 million individuals and 85,053 CHD, 25,103 stroke, 7536 heart failure, and 147,124 CVD cases were included. The summary analysis including 17 datasets from 14 studies conducted on CVD (incidence and/or mortality) showed that intake of up to six eggs per week is inversely associated with CVD events, when compared to no consumption [for four eggs per week, SRR = 0.95 (95% CI: 0.90; 1.00)]; a decreased risk of CVD incidence was observed for consumption of up to one egg per day [SRR = 0.94 (95% CI: 0.89; 0.99)]. The summary analysis for CHD incidence/mortality including 24 datasets from 16 studies showed a decreased risk up to two eggs per week [(SRR = 0.96 (95% CI: 0.91; 1.00)]. No associations were retrieved with risk of stroke. The summary analysis for heart failure risk including six datasets from four studies showed that intake of one egg per day was associated with increased risk raising for higher intakes compared to no consumption [for 1 egg per day, SRR = 1.15 (95% CI:1.02; 1.30)]. After considering GRADE criteria for strength of the evidence, it was rated low for all outcomes but stroke, for which it was moderate (yet referring to no risk). Conclusion: There is no conclusive evidence on the role of egg in CVD risk, despite the fact that higher quality studies are warranted to obtain stronger evidence for

Published
2020
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26. Unmet device reprogramming needs at the end of life among patients with implantable cardioverter defibrillator: A systematic review and meta-analysis

Author

Gonzalez-Jaramillo, V. (Valentina), Sobanski, P. (Piotr), Calvache, J.A. (Jose Andrés), Arenas-Ochoa, L.F. (Luisa F), Franco, O.H. (Oscar), Hunziker, L. (Lukas), Eychmüller, S. (Steffen), Maessen, M. (Maud), Gonzalez-Jaramillo, V. (Valentina), Sobanski, P. (Piotr), Calvache, J.A. (Jose Andrés), Arenas-Ochoa, L.F. (Luisa F), Franco, O.H. (Oscar), Hunziker, L. (Lukas), Eychmüller, S. (Steffen), and Maessen, M. (Maud)

Abstract

Background: Use of implantable cardioverter defibrillators is increasingly common. As patients approach the end of life, it is appropriate to deactivate the shock function. Aim: To assess the prevalence of implantable cardioverter defibrillator reprogramming to deactivate the shock function at the end of life and the prevalence of advance directives among this population. Design: Following a previously established protocol available in PROSPERO, we performed a narrative synthesis of our findings and used the logit transformat

Published
2020
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27. Repositioning of the global epicentre of non-optimal cholesterol

Author

Taddei, C. (Cristina), Zhou, B. (Bin), Bixby, H. (Honor), Carrillo-Larco, R.M. (Rodrigo M.), Danaei, G. (Goodarz), Jackson, R.T. (Rod T.), Farzadfar, F. (Farshad), Sophiea, M.K. (Marisa K.), Di Cesare, M. (Mariachiara), Iurilli, M.L.C. (Maria Laura Caminia), Martinez, A.R. (Andrea Rodriguez), Asghari, G. (Golaleh), Dhana, K. (Klodian), Gulayin, P. (Pablo), Kakarmath, S. (Sujay), Santero, M. (Marilina), Voortman, R.G. (Trudy), Riley, L.M. (Leanne M.), Cowan, M.J. (Melanie J.), Savin, S. (Stefan), Bennett, J.E. (James E.), Stevens, G.A. (Gretchen A.), Paciorek, C.J. (Christopher J.), Aekplakorn, W. (Wichai), Cifkova, R. (Renata), Giampaoli, S. (Simona), Kengne, A.P. (Andre Pascal), Khang, Y.-H. (Young-Ho), Kuulasmaa, K. (Kari), Laxmaiah, A. (Avula), Margozzini, P. (Paula), Mathur, P. (Prashant), Nordestgaard, B.G. (Børge), Zhao, D. (Dong), Aadahl, M. (Mette), Abarca-Gómez, L. (Leandra), Rahim, H.A. (Hanan Abdul), Abu-Rmeileh, N.M. (Niveen M.), Acosta-Cazares, B. (Benjamin), Adams, R.J. (Robert J.), Agdeppa, I.A. (Imelda A.), Aghazadeh-Attari, J. (Javad), Aguilar-Salinas, C.A. (Carlos A.), Agyemang, C.O. (Charles), Ahluwalia, T.S. (Tarunveer Singh), Ahmad, N.A. (Noor Ani), Ahmadi, A. (Ali), Ahmadi, N. (Naser), Ahmed, S.H. (Soheir H.), Ahrens, W. (W.), Ajlouni, K. (Kamel), Alarouj, M. (Monira), AlBuhairan, F. (Fadia), AlDhukair, S. (Shahla), Ali, M.M. (Mohamed M.), Alkandari, A. (Abdullah), Alkerwi, A. (Ala’a), Aly, E. (Eman), Amarapurkar, D.N. (Deepak N.), Amouyel, P. (Philippe), Andersen, L.B. (Lars Bo), Anderssen, S.A. (Sigmund A.), Anjana, R.M. (Ranjit Mohan), Ansari-Moghaddam, A. (Alireza), Aounallah-Skhiri, H. (Hajer), Araújo, J. (Joana), Ariansen, I. (Inger), Aris, T. (Tahir), Arku, R.E. (Raphael E.), Arlappa, N. (Nimmathota), Aryal, K.K. (Krishna K.), Aspelund, T. (Thor), Assunção, M.C.F. (Maria Cecília F.), Auvinen, J. (Juha), Avdicová, M. (Mária), Azevedo, A. (Ana), Azizi, J. (Joshan), Azmin, M. (Mehrdad), Balakrishna, N. (Nagalla), Bamoshmoosh, M. (Mohamed), Banach, M. (Maciej), Bandosz, P. (Piotr), Banegas, J.R. (José R.), Barbagallo, C.M. (Carlo M.), Barceló, A. (Alberto), Barkat, A. (Amina), Bata, I. (Iqbal), Batieha, A.M. (Anwar M.), Batyrbek, A. (Assembekov), Baur, L.A. (Louise A.), Beaglehole, R. (Robert), Belavendra, A. (Antonisamy), Ben Romdhane, H. (Habiba), Benet, M. (Mikhail), Benn, M. (Marianne), Berkinbayev, S. (Salim), Bernabe-Ortiz, A. (Antonio), Bernotiene, G. (Gailute), Bettiol, H. (Heloisa), Bhargava, S.K. (Santosh K.), Bi, Y. (Yufang), Bienek, A. (Asako), Bikbov, M. (Mukharram), Bista, B. (Bihungum), Bjerregaard, P. (Peter), Bjertness, E. (Espen), Bjertness, M.B. (Marius B.), Björkelund, C. (Cecilia), Bloch, K.V. (Katia V.), Blokstra, A. (Anneke), Bo, S. (Simona), Boehm, B.O. (Bernhard O.), Boggia, J.G. (Jose G.), Boissonnet, C.P. (Carlos P.), Bonaccio, M. (Marialaura), Bongard, V. (Vanina), Borchini, R. (Rossana), Borghs, H. (Herman), Bovet, P. (Pascal), Brajkovich, I. (Imperia), Breckenkamp, J. (Juergen), Brenner, H. (Hermann), Brewster, L.M. (Lizzy), Bruno, G. (Graziella), Bugge, A. (Anna), Busch, M.A. (Markus A.), de León, A.C. (Antonio Cabrera), Cacciottolo, J. (Joseph), Can, G. (Günay), Cândido, A.P.C. (Ana Paula C.), Capanzana, M.V. (Mario V.), Capuano, E. (Eduardo), Capuano, V. (Vincenzo), Cardoso, V.C. (Viviane C.), Carvalho, J. (Joana), Casanueva, F.F., Censi, L. (Laura), Chadjigeorgiou, C.A. (Charalambos A.), Chamukuttan, S. (Snehalatha), Chaturvedi, N. (Nish), Chen, C.-J. (Chien-Jen), Chen, F. (Fangfang), Chen, S. (Shuohua), Cheng, C.-Y. (Ching-Yu), Cheraghian, B. (Bahman), Chetrit, A. (Angela), Chiou, S.-T. (Shu-Ti), Chirlaque, M.D. (M.), Cho, B. (Belong), Cho, Y. (Yumi), Chudek, J. (Jerzy), Claessens, F. (Frank), Clarke, J. (Janine), Clays, E. (Els), Concin, H. (Hans), Confortin, S.C. (Susana C.), Cooper, C. (Charles), Costanzo, S. (Simona), Cottel, D. (Dominique), Cowell, C. (Chris), Crujeiras, A.B. (Ana B.), Csilla, S. (Semánová), Cui, L. (Liufu), Cureau, F.V. (Felipe V.), D’Arrigo, G. (Graziella), d’Orsi, E. (Eleonora), Dallongeville, J., Damasceno, A. (Albertino), Dankner, R. (Rachel), Dantoft, T.M. (Thomas M.), Dauchet, L. (Luc), Davletov, K. (Kairat), Backer, G. (Guy) de, Bacquer, D. (Dirk) de, de Gaetano, G. (Giovanni), De Henauw, S. (Stefaan), de Oliveira, P.D. (Paula Duarte), De Ridder, D. (David), De Smedt, D. (Delphine), Deepa, M. (Mohan), Deev, A.D. (Alexander D.), Dehghan, A. (Abbas), Delisle, H. (Hélène), Dennison, E.M. (Elaine), Deschamps, V. (Valérie), Dhimal, M. (Meghnath), Di Castelnuovo, A.F. (Augusto F.), Dika, Z. (Zivka), Djalalinia, S. (Shirin), Dobson, A.J. (Annette J.), Donfrancesco, C. (Chiara), Donoso, S.P. (Silvana P.), Döring, A. (Angela), Dorobantu, M. (Maria), Dragano, N. (Nico), Drygas, W. (Wojciech), Du, Y. (Yong), Duante, C.A. (Charmaine A.), Duda, R.B. (Rosemary B.), Dzerve, V. (Vilnis), Dziankowska-Zaborszczyk, E. (Elzbieta), Eddie, R. (Ricky), Eftekhar, E. (Ebrahim), Eggertsen, R. (Robert), Eghtesad, S. (Sareh), Eiben, G. (Gabriele), Ekelund, U. (Ulf), El Ati, J. (Jalila), Eldemire-Shearer, D. (Denise), Eliasen, M. (Marie), Elosua, R. (Roberto), Erasmus, R.T. (Rajiv T.), Erbel, R. (Raimund), Erem, C. (Cihangir), Eriksen, L. (Louise), Hagen, K. (Knut), Escobedo-de la Peña, J. (Jorge), Eslami, S. (Saeid), Esmaeili, A. (Ali), Evans, A. (Alun), Faeh, D. (David), Fall, C.H. (Caroline H.), Faramarzi, E. (Elnaz), Farjam, M. (Mojtaba), Fattahi, M.R. (Mohammad Reza), Felix-Redondo, F.J. (Francisco J.), Ferguson, T.S. (Trevor S.), Fernández-Bergés, D. (Daniel), Ferrante, D. (Daniel), Ferrari, M. (Marika), Ferreccio, C. (Catterina), Ferrieres, J. (Jean), Föger, B. (Bernhard), Foo, L.H. (Leng Huat), Forslund, A.-S. (Ann-Sofie), Forsner, M. (Maria), Fouad, H.M. (Heba M.), Francis, D.K. (Damian K.), do Carmo Franco, M. (Maria), Franco, O.H. (Oscar H.), Frontera, G. (Guillermo), Fujita, Y. (Yuki), Fumihiko, M. (Matsuda), Furusawa, T. (Takuro), Gaciong, Z. (Zbigniew), Galvano, F. (Fabio), Gao, J. (Jingli), Garcia-de-la-Hera, M. (Manoli), Garnett, S.P. (Sarah P.), Gaspoz, J.-M. (Jean-Michel), Gasull, M. (Magda), Gazzinelli, A. (Andrea), Geleijnse, J.M. (Marianne), Ghanbari, A. (Ali), Ghasemi, E. (Erfan), Gheorghe-Fronea, O.-F. (Oana-Florentina), Ghimire, A. (Anup), Gianfagna, F. (Francesco), Gill, T.K. (Tiffany K.), Giovannelli, J. (Jonathan), Gironella, G. (Glen), Giwercman, A. (Aleksander), Goltzman, D. (David), Gonçalves, H. (Helen), Gonzalez-Chica, D.A. (David A.), Gonzalez-Gross, M. (Marcela), González-Rivas, J.P. (Juan P.), González-Villalpando, C. (Clicerio), González-Villalpando, M.E. (María Elena), Gonzalez, A.R. (Angel R.), Gottrand, F., Graff-Iversen, S. (Sidsel), Grafnetter, D. (Dušan), Gregor, R.D. (Ronald D.), Grodzicki, T. (Tomasz), Grøntved, A. (Anders), Grosso, G. (Giuseppe), Gruden, G. (Gabriella), Gu, D. (Dongfeng), Guallar-castillón, P. (Pilar), Guan, O.P. (Ong Peng), Gudmundsson, E.F. (Elias F.), Gudnason, V. (Vilmundur), Guerrero, R. (Ramiro), Guessous, I. (Idris), Gunnlaugsdottir, J. (Johanna), Gupta, R. (Rajeev), Gutierrez, L. (Laura), Gutzwiller, F. (Felix), Ha, S. (Seongjun), Hadaegh, F. (Farzad), Haghshenas, R. (Rosa), Hakimi, H. (Hamid), Hambleton, I.R. (Ian R.), Hamzeh, B. (Behrooz), Hantunen, S. (Sari), Kumar, R.H. (Rachakulla Hari), Hashemi-Shahri, S.M. (Seyed Mohammad), Hata, J. (Jun), Haugsgjerd, T. (Teresa), Hayes, A.J. (Alison J.), He, J. (Jiang), He, Y. (Yong), Hendriks, M.E. (Marleen), Henriques, A. (Ana), Herrala, S. (Sauli), Heshmat, R. (Ramin), Hill, A.G. (Allan G.), Ho, S.Y. (Sai Yin), Ho, S.C. (Suzanne C.), Hobbs, M. (Michael), Hofman, A. (Albert), Homayounfar, R. (Reza), Hopman, W.M. (Wilma M.), Horimoto, A.R.V.R. (Andrea R. V. R.), Hormiga, C.M. (Claudia M.), Horta, B.L. (Bernardo L.), Houti, L. (Leila), Howitt, C. (Christina), Htay, T.T. (Thein Thein), Htet, A.S. (Aung Soe), Htike, M.M.T. (Maung Maung Than), Huerta, J.M. (José María), Huhtaniemi, I.T. (I.), Huisman, M. (Martijn), Hunsberger, M.L. (Monica L.), Husseini, A. (Abdullatif), Huybrechts, I. (Inge), Hwalla, N. (Nahla), Iacoviello, L. (Licia), Iannone, A.G. (Anna G.), Ibrahim, M.M. (Mohsen), Wong, N.I. (Norazizah Ibrahim), Iglesia, I. (Iris), Ikeda, N. (Nayu), Ikram, M.A. (Arfan), Iotova, V. (Violeta), Irazola, V.E. (Vilma E.), Ishida, T. (Takafumi), Islam, M. (Muhammad), al-Safi Ismail, A. (Aziz), Iwasaki, M. (Masanori), Jacobs, J.M. (Jeremy M.), Jaddou, H.Y. (Hashem Y.), Jafar, T.H. (Tazeen), James, K. (Kenneth), Jamrozik, K., Janszky, I. (Imre), Janus, E. (Edward), Jarvelin, M.-R. (Marjo-Riitta), Jasienska, G. (Grazyna), Jelakovic, A. (Ana), Jelakovic, B. (Bojan), Jennings, G. (Garry), Jensen, G.B. (Gorm), Jeong, S.-L. (Seung-lyeal), Jha, A.K. (Anjani Kumar), Jiang, C.Q. (Chao Qiang), Jimenez, R.O. (Ramon O.), JöCkel, K.-H. (Karl-Heinz), Joffres, M. (Michel), Jokelainen, J.J. (Jari J.), Jonas, J.B. (Jost B.), Jorgensen, T. (Torben), Joshi, P. (Pradeep), Joukar, F. (Farahnaz), Józwiak, J. (Jacek), Juolevi, A. (Anne), Kafatos, A. (Anthony), Kajantie, E. (Eero), Kalter-Leibovici, O. (Ofra), Kamaruddin, N.A. (Nor Azmi), Kamstrup, P.R. (Pia R.), Karki, K.B. (Khem B.), Katz, J. (Joanne), Kauhanen, J. (Jussi), Kaur, P. (Prabhdeep), Kavousi, M. (Maryam), Kazakbaeva, G. (Gyulli), Keil, M. (Mark), Keinanen-Kiukaanniemi, S. (Sirkka), Kelishadi, R. (Roya), Keramati, M. (Maryam), Kerimkulova, A. (Alina), Kersting, M. (Mathilde), Khader, Y.S. (Yousef Saleh), Khalili, D. (Davood), Khateeb, M. (Mohammad), Kheradmand, M. (Motahareh), Khosravi, A. (Alireza), Kiechl-Kohlendorfer, U. (Ursula), Kiechl, S. (Stefan), Killewo, J. (Japhet), Kim, H.C. (Hyeon Chang), Kim, J. (Jeongseon), Kim, Y.-Y. (Yeon-Yong), Klumbiene, J. (Jurate), Knoflach, M. (Michael), Ko, S. (Stephanie), Kohler, H.-P. (Hans-Peter), Kohler, I.V. (Iliana V.), Kolle, E. (Elin), Kolsteren, P. (Patrick), König, J. (Jürgen), Korpelainen, R. (Raija), Korrovits, P. (Paul), Kos, J. (Jelena), Koskinen, S. (Seppo), Kouda, K. (Katsuyasu), Kowlessur, S. (Sudhir), Kratzer, W. (Wolfgang), Kriemler, S. (Susi), Kristensen, P.L. (Peter Lund), Krokstad, S. (Steiner), Kromhout, D. (Daan), Kujala, U.M. (Urho), Kurjata, P. (Pawel), Kyobutungi, C. (Catherine), Laamiri, F.Z. (Fatima Zahra), Laatikainen, T. (Tiina), Lachat, C. (Carl), Laid, Y. (Youcef), Lam, T.H. (Tai Hing), Lambrinou, C.-P. (Christina-Paulina), Lanska, V. (Vera), Lappas, G. (Georg), Larijani, B. (Bagher), Latt, T.S. (Tint Swe), Laugsand, L.E. (Lars E.), Lazo-Porras, M. (Maria), Lee, J. (Jeannette), Lee, J. (Jeonghee), Lehmann, N. (Nils), Lehtimäki, T. (Terho), Levitt, N.S. (Naomi S.), Li, Y. (Yanping), Lilly, C.L. (Christa L.), Lim, W.-Y. (Wei-Yen), Lima-Costa, M.F. (Maria Fernanda), Lin, H.-H. (Hsien-Ho), Lin, X. (Xu), Lin, Y.-T. (Yi-Ting), Kao, W.H.L. (Wen), Linneberg, A. (Allan), Lissner, L. (Lauren), Liu, J. (Jing), Loit, H.-M. (Helle-Mai), Lopez-Garcia, E. (Esther), Lopez, T. (Tania), Lotufo, P.A. (Paulo A), Lozano, J.E. (José Eugenio), Luksiene, D. (Dalia), Lundqvist, A. (Annamari), Lundqvist, R. (Robert), Lunet, N. (Nuno), Ma, G. (Guansheng), Machado-Coelho, G.L.L. (George L. L.), Machado-Rodrigues, A.M. (Aristides M.), Machi, S. (Suka), Madar, A.A. (Ahmed A.), Maggi, S. (Stefania), Magliano, D.J., Magriplis, E. (Emmanuella), Mahasampath, G. (Gowri), Maire, B. (Bernard), Makdisse, M. (Marcia), Malekzadeh, F. (Fatemeh), Malekzadeh, R. (Reza), Rao, K.M. (Kodavanti Mallikharjuna), Manios, Y., Mann, J.I. (Jim I.), Mansour-Ghanaei, F. (Fariborz), Manzato, E. (Enzo), Marques-Vidal, P. (Pedro), Martorell, R. (Reynaldo), Mascarenhas, L.P. (Luis P.), Mathiesen, E.B. (Ellisiv), Matsha, T.E. (Tandi E.), Mavrogianni, C. (Christina), McFarlane, S.R. (Shelly R.), McGarvey, S.T. (Stephen T.), McLachlan, S. (Stela), McLean, R.M. (Rachael M.), McLean, S.B. (Scott B.), McNulty, B.A. (Breige A.), Mediene-Benchekor, S. (Sounnia), Mehdipour, P. (Parinaz), Mehlig, K. (Kirsten), Mehrparvar, A.H. (Amir Houshang), Meirhaeghe, A. (Aline), Meisinger, C. (Christa), Menezes, A.M.B. (Ana M.B.), Menon, G.R. (Geetha R.), Merat, S. (Shahin), Mereke, A. (Alibek), Meshram, I.I. (Indrapal I.), Metcalf, P. (Patricia), Meyer, H.E. (Haakon E.), Mi, J. (Jie), Michels, N. (Nathalie), Miller, J.C. (Jody C.), Minderico, C.S. (Cláudia S.), Mini, G.K. (G. K.), Miquel, J.F. (Juan Francisco), Miranda, J.J. (J. Jaime), Mirjalili, M.R. (Mohammad Reza), Mirrakhimov, E. (Erkin), Modesti, P.A. (Pietro A.), Moghaddam, S.S. (Sahar Saeedi), Mohajer, B. (Bahram), Mohamed, M.K. (Mostafa K.), Mohammad, K. (Kazem), Mohammadi, Z. (Zahra), Mohammadifard, N. (Noushin), Mohammadpourhodki, R. (Reza), Mohan, V. (Viswanathan), Mohanna, S. (Salim), Yusoff, M.F.M. (Muhammad Fadhli Mohd), Mohebbi, I. (Iraj), Mohebi, F. (Farnam), Moitry, M. (Marie), Møllehave, L.T. (Line T.), Møller, N.C. (Niels C.), Molnár, D. (Dénes), Momenan, A. (Amirabbas), Mondo, C.K. (Charles K.), Monterrubio-Flores, E. (Eric), Moosazadeh, M. (Mahmood), Morejon, A. (Alain), Moreno, L. (Luis), Morgan, K. (Karen), Morin, S.N. (Suzanne N.), Moschonis, G. (George), Mossakowska, M. (Malgorzata), Mostafa, A. (Aya), Mota, J. (Jorge), Motlagh, M.E. (Mohammad Esmaeel), Motta, J. (Jorge), Msyamboza, K.P. (Kelias P.), Muiesan, M.L. (Maria Lorenza), Müller-Nurasyid, M. (Martina), Mursu, J. (Jaakko), Mustafa, N. (Norlaila), Nabipour, I. (Iraj), Naderimagham, S. (Shohreh), Nagel, G. (Gabriele), Naidu, B.M. (Balkish M.), Najafi, F. (Farid), Nakamura, H. (Harunobu), Námešná, J. (Jana), Nang, E.E.K. (Ei Ei K.), Nangia, V.B. (Vinay B.), Nauck, M. (Matthias), Neal, W.A. (William A.), Nejatizadeh, A. (Azim), Nenko, I. (Ilona), Nervi, F. (Flavio), Nguyen, N.D. (Nguyen D.), Nguyen, Q.N. (Quang Ngoc), Nieto-Martínez, R.E. (Ramfis E.), Nihal, T. (Thomas), Niiranen, T.J. (Teemu J.), Ning, G. (Guang), Ninomiya, T. (Toshiharu), Noale, M. (Marianna), Noboa, O.A. (Oscar A.), Noto, D. (Davide), Nsour, M.A. (Mohannad Al), Nuhoğlu, I. (Irfan), O’Neill, T.W. (Terence W.), O’Reilly, D. (Dermot), Ochoa-Avilés, A.M. (Angélica M.), Oh, K. (Kyungwon), Ohtsuka, R. (Ryutaro), Olafsson, Ö. (Örn), Olié, V. (Valérie), Oliveira, I.O. (Isabel O.), Omar, M.A. (Mohd Azahadi), Onat, A. (Altan), Ong, S.K. (Sok King), Ordunez, P. (Pedro), Ornelas, R. (Rui), Ortiz, P.J. (Pedro J.), Osmond, C. (Clive), Ostojic, S.M. (Sergej M.), Ostovar, A. (Afshin), Otero, J.A. (Johanna A.), Owusu-Dabo, E. (Ellis), Paccaud, F.M. (Fred Michel), Pahomova, E. (Elena), Pajak, A. (Andrzej), Palmieri, L. (Luigi), Pan, W.-H. (Wen-Harn), Panda-Jonas, S. (Songhomitra), Panza, F. (Francesco), Parnell, W.R. (Winsome R.), Patel, N.D. (Nikhil D.), Peer, N. (Nasheeta), Peixoto, S.V. (Sergio Viana), Peltonen, M. (Markku), Pereira, A. (A.), Peters, A. (Annette), Petersmann, A. (Astrid), Petkeviciene, J. (Janina), Peykari, N. (Niloofar), Pham, S.T. (Son Thai), Pichardo, R.N. (Rafael N.), Pigeot, I. (Iris), Pilav, A. (Aida), Pilotto, A. (Alberto), Piwonska, A. (Aleksandra), Pizarro, A.N. (Andreia N.), Plans-Rubió, P. (Pedro), Plata, S. (Silvia), Pohlabeln, H. (Hermann), Porta, M. (Miquel), Portegies, M.L.P. (Marileen), Poudyal, A. (Anil), Pourfarzi, F. (Farhad), Poustchi, H. (Hossein), Pradeepa, R. (Rajendra), Price, J.F. (Jacqueline F.), Providencia, R. (Rui), Puder, J.J. (Jardena J.), Puhakka, S.E. (Soile E.), Punab, M. (Margus), Qorbani, M. (Mostafa), Bao, T.Q. (Tran Quoc), Radisauskas, R. (Ricardas), Rahimikazerooni, S. (Salar), Raitakari, O. (Olli), Rao, S.R. (Sudha Ramachandra), Ramachandran, A. (Ambady), Ramos, E. (Elisabete), Ramos, R. (Rafel), Rampal, L. (Lekhraj), Rampal, S. (Sanjay), Redón, J. (Josep), Reganit, P.F.M. (Paul Ferdinand M.), Revilla, L. (Luis), Rezaianzadeh, A. (Abbas), Ribeiro, R. (Robespierre), Richter, A. (Adrian), Rigo, F. (Fernando), Rinke de Wit, T.F. (Tobias), Rodríguez Artalejo, F. (Fernando), del Cristo Rodriguez-Perez, M. (María), Rodríguez-Villamizar, L.A. (Laura A.), Roggenbuck, U. (Ulla), Rojas-Martinez, R. (Rosalba), Romaguera, D. (Dora), Romeo, E.L. (Elisabetta L.), Rosengren, A. (Annika), Roy, J.G.R. (Joel G. R.), Rubinstein, A. (Adolfo), Ruidavets, J.-B. (Jean-Bernard), Ruiz-Betancourt, B.S. (Blanca Sandra), Russo, P. (Paola), Rust, P. (Petra), Rutkowski, M. (Marcin), Sabanayagam, C. (Charumathi), Sachdev, H.S. (Harshpal S.), Sadjadi, A. (Alireza), Safarpour, A.R. (Ali Reza), Safiri, S. (Saeid), Saidi, O. (Olfa), Saki, N. (Nader), Salanave, B. (Benoit), Salmerón, D. (Diego), Salomaa, V. (Veikko), Salonen, J.T. (Jukka T.), Salvetti, M. (Massimo), Sánchez-Abanto, J. (Jose), Sans, S. (Susana), Santaliestra-Pasías, A.M. (Alba M.), Santos, D.A. (Diana A.), Santos, M.P. (Maria Paula), Santos, R. (Rute), Saramies, J.L. (Jouko L.), Sardinha, L.B. (Luis B.), Sarrafzadegan, N. (Nizal), Saum, K.-U. (Kai-Uwe), Savva, S., Sawada, N. (Norie), Sbaraini, M. (Mariana), Scazufca, M. (Marcia), Schaan, B.D. (Beatriz D.), Schargrodsky, H. (Herman), Scheidt-Nave, C. (C.), Schienkiewitz, A. (Anja), Schipf, S. (Sabine), Schmidt, C.O. (Carsten O.), Schöttker, B. (Ben), Schramm, S. (Sara), Sebert, S. (Sylvain), Sein, A.A. (Aye Aye), Sen, A. (Abhijit), Sepanlou, S.G. (Sadaf G), Servais, J. (Jennifer), Shakeri, R. (Ramin), Shalnova, S.A. (Svetlana A.), Shamah-Levy, T. (Teresa), Sharafkhah, M. (Maryam), Sharma, S.K. (Sanjib K.), Shaw, J.E., Shayanrad, A. (Amaneh), Shi, Z. (Zumin), Shibuya, K. (Kenji), Shimizu-Furusawa, H. (Hana), Shin, D.W. (Dong Wook), Shin, Y. (Youchan), Shirani, M. (Majid), Shiri, R. (Rahman), Shrestha, N. (Namuna), Si-Ramlee, K. (Khairil), Siani, A. (Alfonso), Siantar, R. (Rosalynn), Sibai, A.M. (Abla M.), Silva, D.A.S. (Diego Augusto Santos), Simon, M. (Mary), Simons, J. (Judith), Simons, L.A. (Leon A.), Sjöström, M. (Michael), Skaaby, T. (Tea), Slowikowska-Hilczer, J. (Jolanta), Slusarczyk, P. (Przemyslaw), Smeeth, L. (Liam), Snijder, M.B. (Marieke), Söderberg, S. (Stefan), Soemantri, A. (Augustinus), Sofat, R. (Reecha), Solfrizzi, V. (Vincenzo), Somi, M.H. (Mohammad Hossein), Sonestedt, E. (Emily), Sørensen, T.I.A. (Thorkild), Jérome, C.S. (Charles Sossa), Soumaré, A. (Aicha), Sozmen, K. (Kaan), Sparrenberger, K. (Karen), Staessen, J.A. (Jan), Stathopoulou, M.G. (Maria G), Stavreski, B. (Bill), Steene-Johannessen, J. (Jostein), Stehle, P. (Peter), Stein, A.D. (Aryeh D.), Stessman, J. (Jochanan), Stevanović, R. (Ranko), Stieber, J. (Jutta), Stöckl, D. (Doris), Stokwiszewski, J. (Jakub), Stronks, K. (Karien), Strufaldi, M.W. (Maria Wany), Suárez-Medina, R. (Ramón), Sun, C.-A. (Chien-An), Sundström, J. (Johan), Suriyawongpaisal, P. (Paibul), Sy, R.G. (Rody G.), Sylva, R.C. (René Charles), Szklo, M. (Moyses), Tai, E.S. (Shyong), Tamosiunas, A. (Abdonas), Tan, E.J. (Eng Joo), Tarawneh, M.R. (Mohammed Rasoul), Tarqui-Mamani, C.B. (Carolina B.), Taylor, A. (Anne), Taylor, J. (Julie), Tell, G.S. (Grethe S.), Tello, T. (Tania), Thankappan, K.R. (K. R.), Thijs, L. (Lutgarde), Thuesen, B.H. (Betina H.), Toft, U. (Ulla), Tolonen, H.K. (Hanna K.), Tolstrup, J.S. (Janne), Topbas, M. (Murat), Topór-Madry, R. (Roman), Tormo, M.J., Tornaritis, M.J. (Michael J.), Torrent, M. (Maties), Torres-Collado, L. (Laura), Traissac, P. (Pierre), Trinh, O.T.H. (Oanh T. H.), Truthmann, J. (Julia), Tsugane, S. (Shoichiro), Tulloch-Reid, M.K. (Marshall K.), Tuomainen, T.-P. (Tomi-Pekka), Tuomilehto, J. (Jaakko), Tybjaerg-Hansen, A. (Anne), Tzourio, C. (Christophe), Ueda, P. (Peter), Ugel, E. (Eunice), Ulmer, H. (Hanno), Unal, B. (Belgin), Uusitalo, H., Valdivia, G. (Gonzalo), Valvi, D. (Damaskini), Dam, R.M. (Rob) van, Schouw, Y.T. (Yvonne) van der, Van Herck, K. (Koen), Van Minh, H. (Hoang), Rossem, L. (Lenie) van, Schoor, N.M. (Natasja) van, Valkengoed, I. (Irene) van, Vanderschueren, D. (Dirk), Vanuzzo, D. (Diego), Varbo, A. (Anette), Varona-Pérez, P. (Patricia), Vasan, S.K. (Senthil K.), Vatten, L. (Lars), Vega, T. (Tomas), Veidebaum, T. (Toomas), Velasquez-Melendez, G. (Gustavo), Venero-Fernández, S.J. (Silvia J.), Veronesi, G. (Giovanni), Verschuren, W.M.M. (W. M. Monique), Victora, C.G. (Cesar G.), Vidiawati, D. (Dhanasari), Viet, L. (Lucie), Villalpando, S. (Salvador), Vioque, J. (Jesus), Virtanen, J.K. (Jyrki K.), Visvikis-Siest, S. (Sophie), Viswanathan, B. (Bharathi), Vlasoff, T. (Tiina), Vollenweider, P. (Peter), Voutilainen, A. (Ari), Wade, A.N. (Alisha N.), Wagner, A. (Aline), Walton, J. (Janette), Bebakar, W.M.W. (Wan Mohamad Wan), Mohamud, W.N.W. (Wan Nazaimoon Wan), Wang, M.-D. (Ming-Dong), Wang, N. (Ningli), Wang, Q. (Qian), Wang, Y.X. (Ya Xing), Wang, Y.-W. (Ying-Wei), Wannamethee, S.G. (Goya), Wedderkopp, N. (Niels), Wei, W. (Wenbin), Whincup, P.H. (Peter), Widhalm, K. (Kurt), Widyahening, I.S. (Indah S.), Wiecek, A. (Andrzej), Wijga, A.H. (Alet), Wilks, R.J. (Rainford J.), Willeit, J. (Johann), Willeit, P. (Peter), Wilsgaard, T. (Tom), Wojtyniak, B. (Bogdan), Wong-McClure, R.A. (Roy A.), Wong, A. (Andrew), Wong, T.Y. (Tien Yin), Woo, J. (Jean), Woodward, M. (Mark), Wu, F.C. (Frederick C.), Wu, S. (Shouling), Xu, H. (Haiquan), Xu, L. (Liang), Yan, W. (Weili), Yang, X. (Xiaoguang), Yasuharu, T. (Tabara), Ye, X. (Xingwang), Yeow, T.P. (Toh Peng), Yiallouros, P.K. (P.), Yoosefi, M. (Moein), Yoshihara, A. (Akihiro), You, S.-L. (San-Lin), Younger-Coleman, N.O. (Novie O.), Yusoff, A.F. (Ahmad Faudzi), Zainuddin, A.A. (Ahmad A.), Zakavi, S.R. (Seyed Rasoul), Zali, M.R. (Mohammad Reza), Zamani, F. (Farhad), Zambon, S. (Sabina), Zampelas, A. (Antonis), Zaw, K.K. (Ko Ko), Zdrojewski, T. (T.), Vrkic, T.Z. (Tajana Zeljkovic), Zhang, Z.-Y. (Zhen-Yu), Zhao, W. (Wenhua), Zhen, S. (Shiqi), Zheng, Y. (Yingfeng), Zholdin, B. (Bekbolat), Zhussupov, B. (Baurzhan), Zoghlami, N. (Nada), Cisneros, J.Z. (Julio Zuñiga), Gregg, E.W. (Edward W.), Ezzati, M. (Majid), Taddei, C. (Cristina), Zhou, B. (Bin), Bixby, H. (Honor), Carrillo-Larco, R.M. (Rodrigo M.), Danaei, G. (Goodarz), Jackson, R.T. (Rod T.), Farzadfar, F. (Farshad), Sophiea, M.K. (Marisa K.), Di Cesare, M. (Mariachiara), Iurilli, M.L.C. (Maria Laura Caminia), Martinez, A.R. (Andrea Rodriguez), Asghari, G. (Golaleh), Dhana, K. (Klodian), Gulayin, P. (Pablo), Kakarmath, S. (Sujay), Santero, M. (Marilina), Voortman, R.G. (Trudy), Riley, L.M. (Leanne M.), Cowan, M.J. (Melanie J.), Savin, S. (Stefan), Bennett, J.E. (James E.), Stevens, G.A. (Gretchen A.), Paciorek, C.J. (Christopher J.), Aekplakorn, W. (Wichai), Cifkova, R. (Renata), Giampaoli, S. (Simona), Kengne, A.P. (Andre Pascal), Khang, Y.-H. (Young-Ho), Kuulasmaa, K. (Kari), Laxmaiah, A. (Avula), Margozzini, P. (Paula), Mathur, P. (Prashant), Nordestgaard, B.G. (Børge), Zhao, D. (Dong), Aadahl, M. (Mette), Abarca-Gómez, L. (Leandra), Rahim, H.A. (Hanan Abdul), Abu-Rmeileh, N.M. (Niveen M.), Acosta-Cazares, B. (Benjamin), Adams, R.J. (Robert J.), Agdeppa, I.A. (Imelda A.), Aghazadeh-Attari, J. (Javad), Aguilar-Salinas, C.A. (Carlos A.), Agyemang, C.O. (Charles), Ahluwalia, T.S. (Tarunveer Singh), Ahmad, N.A. (Noor Ani), Ahmadi, A. (Ali), Ahmadi, N. (Naser), Ahmed, S.H. (Soheir H.), Ahrens, W. (W.), Ajlouni, K. (Kamel), Alarouj, M. (Monira), AlBuhairan, F. (Fadia), AlDhukair, S. (Shahla), Ali, M.M. (Mohamed M.), Alkandari, A. (Abdullah), Alkerwi, A. (Ala’a), Aly, E. (Eman), Amarapurkar, D.N. (Deepak N.), Amouyel, P. (Philippe), Andersen, L.B. (Lars Bo), Anderssen, S.A. (Sigmund A.), Anjana, R.M. (Ranjit Mohan), Ansari-Moghaddam, A. (Alireza), Aounallah-Skhiri, H. (Hajer), Araújo, J. (Joana), Ariansen, I. (Inger), Aris, T. (Tahir), Arku, R.E. (Raphael E.), Arlappa, N. (Nimmathota), Aryal, K.K. (Krishna K.), Aspelund, T. (Thor), Assunção, M.C.F. (Maria Cecília F.), Auvinen, J. (Juha), Avdicová, M. (Mária), Azevedo, A. (Ana), Azizi, J. (Joshan), Azmin, M. (Mehrdad), Balakrishna, N. (Nagalla), Bamoshmoosh, M. (Mohamed), Banach, M. (Maciej), Bandosz, P. (Piotr), Banegas, J.R. (José R.), Barbagallo, C.M. (Carlo M.), Barceló, A. (Alberto), Barkat, A. (Amina), Bata, I. (Iqbal), Batieha, A.M. (Anwar M.), Batyrbek, A. (Assembekov), Baur, L.A. (Louise A.), Beaglehole, R. (Robert), Belavendra, A. (Antonisamy), Ben Romdhane, H. (Habiba), Benet, M. (Mikhail), Benn, M. (Marianne), Berkinbayev, S. (Salim), Bernabe-Ortiz, A. (Antonio), Bernotiene, G. (Gailute), Bettiol, H. (Heloisa), Bhargava, S.K. (Santosh K.), Bi, Y. (Yufang), Bienek, A. (Asako), Bikbov, M. (Mukharram), Bista, B. (Bihungum), Bjerregaard, P. (Peter), Bjertness, E. (Espen), Bjertness, M.B. (Marius B.), Björkelund, C. (Cecilia), Bloch, K.V. (Katia V.), Blokstra, A. (Anneke), Bo, S. (Simona), Boehm, B.O. (Bernhard O.), Boggia, J.G. (Jose G.), Boissonnet, C.P. (Carlos P.), Bonaccio, M. (Marialaura), Bongard, V. (Vanina), Borchini, R. (Rossana), Borghs, H. (Herman), Bovet, P. (Pascal), Brajkovich, I. (Imperia), Breckenkamp, J. (Juergen), Brenner, H. (Hermann), Brewster, L.M. (Lizzy), Bruno, G. (Graziella), Bugge, A. (Anna), Busch, M.A. (Markus A.), de León, A.C. (Antonio Cabrera), Cacciottolo, J. (Joseph), Can, G. (Günay), Cândido, A.P.C. (Ana Paula C.), Capanzana, M.V. (Mario V.), Capuano, E. (Eduardo), Capuano, V. (Vincenzo), Cardoso, V.C. (Viviane C.), Carvalho, J. (Joana), Casanueva, F.F., Censi, L. (Laura), Chadjigeorgiou, C.A. (Charalambos A.), Chamukuttan, S. (Snehalatha), Chaturvedi, N. (Nish), Chen, C.-J. (Chien-Jen), Chen, F. (Fangfang), Chen, S. (Shuohua), Cheng, C.-Y. (Ching-Yu), Cheraghian, B. (Bahman), Chetrit, A. (Angela), Chiou, S.-T. (Shu-Ti), Chirlaque, M.D. (M.), Cho, B. (Belong), Cho, Y. (Yumi), Chudek, J. (Jerzy), Claessens, F. (Frank), Clarke, J. (Janine), Clays, E. (Els), Concin, H. (Hans), Confortin, S.C. (Susana C.), Cooper, C. (Charles), Costanzo, S. (Simona), Cottel, D. (Dominique), Cowell, C. (Chris), Crujeiras, A.B. (Ana B.), Csilla, S. (Semánová), Cui, L. (Liufu), Cureau, F.V. (Felipe V.), D’Arrigo, G. (Graziella), d’Orsi, E. (Eleonora), Dallongeville, J., Damasceno, A. (Albertino), Dankner, R. (Rachel), Dantoft, T.M. (Thomas M.), Dauchet, L. (Luc), Davletov, K. (Kairat), Backer, G. (Guy) de, Bacquer, D. (Dirk) de, de Gaetano, G. (Giovanni), De Henauw, S. (Stefaan), de Oliveira, P.D. (Paula Duarte), De Ridder, D. (David), De Smedt, D. (Delphine), Deepa, M. (Mohan), Deev, A.D. (Alexander D.), Dehghan, A. (Abbas), Delisle, H. (Hélène), Dennison, E.M. (Elaine), Deschamps, V. (Valérie), Dhimal, M. (Meghnath), Di Castelnuovo, A.F. (Augusto F.), Dika, Z. (Zivka), Djalalinia, S. (Shirin), Dobson, A.J. (Annette J.), Donfrancesco, C. (Chiara), Donoso, S.P. (Silvana P.), Döring, A. (Angela), Dorobantu, M. (Maria), Dragano, N. (Nico), Drygas, W. (Wojciech), Du, Y. (Yong), Duante, C.A. (Charmaine A.), Duda, R.B. (Rosemary B.), Dzerve, V. (Vilnis), Dziankowska-Zaborszczyk, E. (Elzbieta), Eddie, R. (Ricky), Eftekhar, E. (Ebrahim), Eggertsen, R. (Robert), Eghtesad, S. (Sareh), Eiben, G. (Gabriele), Ekelund, U. (Ulf), El Ati, J. (Jalila), Eldemire-Shearer, D. (Denise), Eliasen, M. (Marie), Elosua, R. (Roberto), Erasmus, R.T. (Rajiv T.), Erbel, R. (Raimund), Erem, C. (Cihangir), Eriksen, L. (Louise), Hagen, K. (Knut), Escobedo-de la Peña, J. (Jorge), Eslami, S. (Saeid), Esmaeili, A. (Ali), Evans, A. (Alun), Faeh, D. (David), Fall, C.H. (Caroline H.), Faramarzi, E. (Elnaz), Farjam, M. (Mojtaba), Fattahi, M.R. (Mohammad Reza), Felix-Redondo, F.J. (Francisco J.), Ferguson, T.S. (Trevor S.), Fernández-Bergés, D. (Daniel), Ferrante, D. (Daniel), Ferrari, M. (Marika), Ferreccio, C. (Catterina), Ferrieres, J. (Jean), Föger, B. (Bernhard), Foo, L.H. (Leng Huat), Forslund, A.-S. (Ann-Sofie), Forsner, M. (Maria), Fouad, H.M. (Heba M.), Francis, D.K. (Damian K.), do Carmo Franco, M. (Maria), Franco, O.H. (Oscar H.), Frontera, G. (Guillermo), Fujita, Y. (Yuki), Fumihiko, M. (Matsuda), Furusawa, T. (Takuro), Gaciong, Z. (Zbigniew), Galvano, F. (Fabio), Gao, J. (Jingli), Garcia-de-la-Hera, M. (Manoli), Garnett, S.P. (Sarah P.), Gaspoz, J.-M. (Jean-Michel), Gasull, M. (Magda), Gazzinelli, A. (Andrea), Geleijnse, J.M. (Marianne), Ghanbari, A. (Ali), Ghasemi, E. (Erfan), Gheorghe-Fronea, O.-F. (Oana-Florentina), Ghimire, A. (Anup), Gianfagna, F. (Francesco), Gill, T.K. (Tiffany K.), Giovannelli, J. (Jonathan), Gironella, G. (Glen), Giwercman, A. (Aleksander), Goltzman, D. (David), Gonçalves, H. (Helen), Gonzalez-Chica, D.A. (David A.), Gonzalez-Gross, M. (Marcela), González-Rivas, J.P. (Juan P.), González-Villalpando, C. (Clicerio), González-Villalpando, M.E. (María Elena), Gonzalez, A.R. (Angel R.), Gottrand, F., Graff-Iversen, S. (Sidsel), Grafnetter, D. (Dušan), Gregor, R.D. (Ronald D.), Grodzicki, T. (Tomasz), Grøntved, A. (Anders), Grosso, G. (Giuseppe), Gruden, G. (Gabriella), Gu, D. (Dongfeng), Guallar-castillón, P. (Pilar), Guan, O.P. (Ong Peng), Gudmundsson, E.F. (Elias F.), Gudnason, V. (Vilmundur), Guerrero, R. (Ramiro), Guessous, I. (Idris), Gunnlaugsdottir, J. (Johanna), Gupta, R. (Rajeev), Gutierrez, L. (Laura), Gutzwiller, F. (Felix), Ha, S. (Seongjun), Hadaegh, F. (Farzad), Haghshenas, R. (Rosa), Hakimi, H. (Hamid), Hambleton, I.R. (Ian R.), Hamzeh, B. (Behrooz), Hantunen, S. (Sari), Kumar, R.H. (Rachakulla Hari), Hashemi-Shahri, S.M. (Seyed Mohammad), Hata, J. (Jun), Haugsgjerd, T. (Teresa), Hayes, A.J. (Alison J.), He, J. (Jiang), He, Y. (Yong), Hendriks, M.E. (Marleen), Henriques, A. (Ana), Herrala, S. (Sauli), Heshmat, R. (Ramin), Hill, A.G. (Allan G.), Ho, S.Y. (Sai Yin), Ho, S.C. (Suzanne C.), Hobbs, M. (Michael), Hofman, A. (Albert), Homayounfar, R. (Reza), Hopman, W.M. (Wilma M.), Horimoto, A.R.V.R. (Andrea R. V. R.), Hormiga, C.M. (Claudia M.), Horta, B.L. (Bernardo L.), Houti, L. (Leila), Howitt, C. (Christina), Htay, T.T. (Thein Thein), Htet, A.S. (Aung Soe), Htike, M.M.T. (Maung Maung Than), Huerta, J.M. (José María), Huhtaniemi, I.T. (I.), Huisman, M. (Martijn), Hunsberger, M.L. (Monica L.), Husseini, A. (Abdullatif), Huybrechts, I. (Inge), Hwalla, N. (Nahla), Iacoviello, L. (Licia), Iannone, A.G. (Anna G.), Ibrahim, M.M. (Mohsen), Wong, N.I. (Norazizah Ibrahim), Iglesia, I. (Iris), Ikeda, N. (Nayu), Ikram, M.A. (Arfan), Iotova, V. (Violeta), Irazola, V.E. (Vilma E.), Ishida, T. (Takafumi), Islam, M. (Muhammad), al-Safi Ismail, A. (Aziz), Iwasaki, M. (Masanori), Jacobs, J.M. (Jeremy M.), Jaddou, H.Y. (Hashem Y.), Jafar, T.H. (Tazeen), James, K. (Kenneth), Jamrozik, K., Janszky, I. (Imre), Janus, E. (Edward), Jarvelin, M.-R. (Marjo-Riitta), Jasienska, G. (Grazyna), Jelakovic, A. (Ana), Jelakovic, B. (Bojan), Jennings, G. (Garry), Jensen, G.B. (Gorm), Jeong, S.-L. (Seung-lyeal), Jha, A.K. (Anjani Kumar), Jiang, C.Q. (Chao Qiang), Jimenez, R.O. (Ramon O.), JöCkel, K.-H. (Karl-Heinz), Joffres, M. (Michel), Jokelainen, J.J. (Jari J.), Jonas, J.B. (Jost B.), Jorgensen, T. (Torben), Joshi, P. (Pradeep), Joukar, F. (Farahnaz), Józwiak, J. (Jacek), Juolevi, A. (Anne), Kafatos, A. (Anthony), Kajantie, E. (Eero), Kalter-Leibovici, O. (Ofra), Kamaruddin, N.A. (Nor Azmi), Kamstrup, P.R. (Pia R.), Karki, K.B. (Khem B.), Katz, J. (Joanne), Kauhanen, J. (Jussi), Kaur, P. (Prabhdeep), Kavousi, M. (Maryam), Kazakbaeva, G. (Gyulli), Keil, M. (Mark), Keinanen-Kiukaanniemi, S. (Sirkka), Kelishadi, R. (Roya), Keramati, M. (Maryam), Kerimkulova, A. (Alina), Kersting, M. (Mathilde), Khader, Y.S. (Yousef Saleh), Khalili, D. (Davood), Khateeb, M. (Mohammad), Kheradmand, M. (Motahareh), Khosravi, A. (Alireza), Kiechl-Kohlendorfer, U. (Ursula), Kiechl, S. (Stefan), Killewo, J. (Japhet), Kim, H.C. (Hyeon Chang), Kim, J. (Jeongseon), Kim, Y.-Y. (Yeon-Yong), Klumbiene, J. (Jurate), Knoflach, M. (Michael), Ko, S. (Stephanie), Kohler, H.-P. (Hans-Peter), Kohler, I.V. (Iliana V.), Kolle, E. (Elin), Kolsteren, P. (Patrick), König, J. (Jürgen), Korpelainen, R. (Raija), Korrovits, P. (Paul), Kos, J. (Jelena), Koskinen, S. (Seppo), Kouda, K. (Katsuyasu), Kowlessur, S. (Sudhir), Kratzer, W. (Wolfgang), Kriemler, S. (Susi), Kristensen, P.L. (Peter Lund), Krokstad, S. (Steiner), Kromhout, D. (Daan), Kujala, U.M. (Urho), Kurjata, P. (Pawel), Kyobutungi, C. (Catherine), Laamiri, F.Z. (Fatima Zahra), Laatikainen, T. (Tiina), Lachat, C. (Carl), Laid, Y. (Youcef), Lam, T.H. (Tai Hing), Lambrinou, C.-P. (Christina-Paulina), Lanska, V. (Vera), Lappas, G. (Georg), Larijani, B. (Bagher), Latt, T.S. (Tint Swe), Laugsand, L.E. (Lars E.), Lazo-Porras, M. (Maria), Lee, J. (Jeannette), Lee, J. (Jeonghee), Lehmann, N. (Nils), Lehtimäki, T. (Terho), Levitt, N.S. (Naomi S.), Li, Y. (Yanping), Lilly, C.L. (Christa L.), Lim, W.-Y. (Wei-Yen), Lima-Costa, M.F. (Maria Fernanda), Lin, H.-H. (Hsien-Ho), Lin, X. (Xu), Lin, Y.-T. (Yi-Ting), Kao, W.H.L. (Wen), Linneberg, A. (Allan), Lissner, L. (Lauren), Liu, J. (Jing), Loit, H.-M. (Helle-Mai), Lopez-Garcia, E. (Esther), Lopez, T. (Tania), Lotufo, P.A. (Paulo A), Lozano, J.E. (José Eugenio), Luksiene, D. (Dalia), Lundqvist, A. (Annamari), Lundqvist, R. (Robert), Lunet, N. (Nuno), Ma, G. (Guansheng), Machado-Coelho, G.L.L. (George L. L.), Machado-Rodrigues, A.M. (Aristides M.), Machi, S. (Suka), Madar, A.A. (Ahmed A.), Maggi, S. (Stefania), Magliano, D.J., Magriplis, E. (Emmanuella), Mahasampath, G. (Gowri), Maire, B. (Bernard), Makdisse, M. (Marcia), Malekzadeh, F. (Fatemeh), Malekzadeh, R. (Reza), Rao, K.M. (Kodavanti Mallikharjuna), Manios, Y., Mann, J.I. (Jim I.), Mansour-Ghanaei, F. (Fariborz), Manzato, E. (Enzo), Marques-Vidal, P. (Pedro), Martorell, R. (Reynaldo), Mascarenhas, L.P. (Luis P.), Mathiesen, E.B. (Ellisiv), Matsha, T.E. (Tandi E.), Mavrogianni, C. (Christina), McFarlane, S.R. (Shelly R.), McGarvey, S.T. (Stephen T.), McLachlan, S. (Stela), McLean, R.M. (Rachael M.), McLean, S.B. (Scott B.), McNulty, B.A. (Breige A.), Mediene-Benchekor, S. (Sounnia), Mehdipour, P. (Parinaz), Mehlig, K. (Kirsten), Mehrparvar, A.H. (Amir Houshang), Meirhaeghe, A. (Aline), Meisinger, C. (Christa), Menezes, A.M.B. (Ana M.B.), Menon, G.R. (Geetha R.), Merat, S. (Shahin), Mereke, A. (Alibek), Meshram, I.I. (Indrapal I.), Metcalf, P. (Patricia), Meyer, H.E. (Haakon E.), Mi, J. (Jie), Michels, N. (Nathalie), Miller, J.C. (Jody C.), Minderico, C.S. (Cláudia S.), Mini, G.K. (G. K.), Miquel, J.F. (Juan Francisco), Miranda, J.J. (J. Jaime), Mirjalili, M.R. (Mohammad Reza), Mirrakhimov, E. (Erkin), Modesti, P.A. (Pietro A.), Moghaddam, S.S. (Sahar Saeedi), Mohajer, B. (Bahram), Mohamed, M.K. (Mostafa K.), Mohammad, K. (Kazem), Mohammadi, Z. (Zahra), Mohammadifard, N. (Noushin), Mohammadpourhodki, R. (Reza), Mohan, V. (Viswanathan), Mohanna, S. (Salim), Yusoff, M.F.M. (Muhammad Fadhli Mohd), Mohebbi, I. (Iraj), Mohebi, F. (Farnam), Moitry, M. (Marie), Møllehave, L.T. (Line T.), Møller, N.C. (Niels C.), Molnár, D. (Dénes), Momenan, A. (Amirabbas), Mondo, C.K. (Charles K.), Monterrubio-Flores, E. (Eric), Moosazadeh, M. (Mahmood), Morejon, A. (Alain), Moreno, L. (Luis), Morgan, K. (Karen), Morin, S.N. (Suzanne N.), Moschonis, G. (George), Mossakowska, M. (Malgorzata), Mostafa, A. (Aya), Mota, J. (Jorge), Motlagh, M.E. (Mohammad Esmaeel), Motta, J. (Jorge), Msyamboza, K.P. (Kelias P.), Muiesan, M.L. (Maria Lorenza), Müller-Nurasyid, M. (Martina), Mursu, J. (Jaakko), Mustafa, N. (Norlaila), Nabipour, I. (Iraj), Naderimagham, S. (Shohreh), Nagel, G. (Gabriele), Naidu, B.M. (Balkish M.), Najafi, F. (Farid), Nakamura, H. (Harunobu), Námešná, J. (Jana), Nang, E.E.K. (Ei Ei K.), Nangia, V.B. (Vinay B.), Nauck, M. (Matthias), Neal, W.A. (William A.), Nejatizadeh, A. (Azim), Nenko, I. (Ilona), Nervi, F. (Flavio), Nguyen, N.D. (Nguyen D.), Nguyen, Q.N. (Quang Ngoc), Nieto-Martínez, R.E. (Ramfis E.), Nihal, T. (Thomas), Niiranen, T.J. (Teemu J.), Ning, G. (Guang), Ninomiya, T. (Toshiharu), Noale, M. (Marianna), Noboa, O.A. (Oscar A.), Noto, D. (Davide), Nsour, M.A. (Mohannad Al), Nuhoğlu, I. (Irfan), O’Neill, T.W. (Terence W.), O’Reilly, D. (Dermot), Ochoa-Avilés, A.M. (Angélica M.), Oh, K. (Kyungwon), Ohtsuka, R. (Ryutaro), Olafsson, Ö. (Örn), Olié, V. (Valérie), Oliveira, I.O. (Isabel O.), Omar, M.A. (Mohd Azahadi), Onat, A. (Altan), Ong, S.K. (Sok King), Ordunez, P. (Pedro), Ornelas, R. (Rui), Ortiz, P.J. (Pedro J.), Osmond, C. (Clive), Ostojic, S.M. (Sergej M.), Ostovar, A. (Afshin), Otero, J.A. (Johanna A.), Owusu-Dabo, E. (Ellis), Paccaud, F.M. (Fred Michel), Pahomova, E. (Elena), Pajak, A. (Andrzej), Palmieri, L. (Luigi), Pan, W.-H. (Wen-Harn), Panda-Jonas, S. (Songhomitra), Panza, F. (Francesco), Parnell, W.R. (Winsome R.), Patel, N.D. (Nikhil D.), Peer, N. (Nasheeta), Peixoto, S.V. (Sergio Viana), Peltonen, M. (Markku), Pereira, A. (A.), Peters, A. (Annette), Petersmann, A. (Astrid), Petkeviciene, J. (Janina), Peykari, N. (Niloofar), Pham, S.T. (Son Thai), Pichardo, R.N. (Rafael N.), Pigeot, I. (Iris), Pilav, A. (Aida), Pilotto, A. (Alberto), Piwonska, A. (Aleksandra), Pizarro, A.N. (Andreia N.), Plans-Rubió, P. (Pedro), Plata, S. (Silvia), Pohlabeln, H. (Hermann), Porta, M. (Miquel), Portegies, M.L.P. (Marileen), Poudyal, A. (Anil), Pourfarzi, F. (Farhad), Poustchi, H. (Hossein), Pradeepa, R. (Rajendra), Price, J.F. (Jacqueline F.), Providencia, R. (Rui), Puder, J.J. (Jardena J.), Puhakka, S.E. (Soile E.), Punab, M. (Margus), Qorbani, M. (Mostafa), Bao, T.Q. (Tran Quoc), Radisauskas, R. (Ricardas), Rahimikazerooni, S. (Salar), Raitakari, O. (Olli), Rao, S.R. (Sudha Ramachandra), Ramachandran, A. (Ambady), Ramos, E. (Elisabete), Ramos, R. (Rafel), Rampal, L. (Lekhraj), Rampal, S. (Sanjay), Redón, J. (Josep), Reganit, P.F.M. (Paul Ferdinand M.), Revilla, L. (Luis), Rezaianzadeh, A. (Abbas), Ribeiro, R. (Robespierre), Richter, A. (Adrian), Rigo, F. (Fernando), Rinke de Wit, T.F. (Tobias), Rodríguez Artalejo, F. (Fernando), del Cristo Rodriguez-Perez, M. (María), Rodríguez-Villamizar, L.A. (Laura A.), Roggenbuck, U. (Ulla), Rojas-Martinez, R. (Rosalba), Romaguera, D. (Dora), Romeo, E.L. (Elisabetta L.), Rosengren, A. (Annika), Roy, J.G.R. (Joel G. R.), Rubinstein, A. (Adolfo), Ruidavets, J.-B. (Jean-Bernard), Ruiz-Betancourt, B.S. (Blanca Sandra), Russo, P. (Paola), Rust, P. (Petra), Rutkowski, M. (Marcin), Sabanayagam, C. (Charumathi), Sachdev, H.S. (Harshpal S.), Sadjadi, A. (Alireza), Safarpour, A.R. (Ali Reza), Safiri, S. (Saeid), Saidi, O. (Olfa), Saki, N. (Nader), Salanave, B. (Benoit), Salmerón, D. (Diego), Salomaa, V. (Veikko), Salonen, J.T. (Jukka T.), Salvetti, M. (Massimo), Sánchez-Abanto, J. (Jose), Sans, S. (Susana), Santaliestra-Pasías, A.M. (Alba M.), Santos, D.A. (Diana A.), Santos, M.P. (Maria Paula), Santos, R. (Rute), Saramies, J.L. (Jouko L.), Sardinha, L.B. (Luis B.), Sarrafzadegan, N. (Nizal), Saum, K.-U. (Kai-Uwe), Savva, S., Sawada, N. (Norie), Sbaraini, M. (Mariana), Scazufca, M. (Marcia), Schaan, B.D. (Beatriz D.), Schargrodsky, H. (Herman), Scheidt-Nave, C. (C.), Schienkiewitz, A. (Anja), Schipf, S. (Sabine), Schmidt, C.O. (Carsten O.), Schöttker, B. (Ben), Schramm, S. (Sara), Sebert, S. (Sylvain), Sein, A.A. (Aye Aye), Sen, A. (Abhijit), Sepanlou, S.G. (Sadaf G), Servais, J. (Jennifer), Shakeri, R. (Ramin), Shalnova, S.A. (Svetlana A.), Shamah-Levy, T. (Teresa), Sharafkhah, M. (Maryam), Sharma, S.K. (Sanjib K.), Shaw, J.E., Shayanrad, A. (Amaneh), Shi, Z. (Zumin), Shibuya, K. (Kenji), Shimizu-Furusawa, H. (Hana), Shin, D.W. (Dong Wook), Shin, Y. (Youchan), Shirani, M. (Majid), Shiri, R. (Rahman), Shrestha, N. (Namuna), Si-Ramlee, K. (Khairil), Siani, A. (Alfonso), Siantar, R. (Rosalynn), Sibai, A.M. (Abla M.), Silva, D.A.S. (Diego Augusto Santos), Simon, M. (Mary), Simons, J. (Judith), Simons, L.A. (Leon A.), Sjöström, M. (Michael), Skaaby, T. (Tea), Slowikowska-Hilczer, J. (Jolanta), Slusarczyk, P. (Przemyslaw), Smeeth, L. (Liam), Snijder, M.B. (Marieke), Söderberg, S. (Stefan), Soemantri, A. (Augustinus), Sofat, R. (Reecha), Solfrizzi, V. (Vincenzo), Somi, M.H. (Mohammad Hossein), Sonestedt, E. (Emily), Sørensen, T.I.A. (Thorkild), Jérome, C.S. (Charles Sossa), Soumaré, A. (Aicha), Sozmen, K. (Kaan), Sparrenberger, K. (Karen), Staessen, J.A. (Jan), Stathopoulou, M.G. (Maria G), Stavreski, B. (Bill), Steene-Johannessen, J. (Jostein), Stehle, P. (Peter), Stein, A.D. (Aryeh D.), Stessman, J. (Jochanan), Stevanović, R. (Ranko), Stieber, J. (Jutta), Stöckl, D. (Doris), Stokwiszewski, J. (Jakub), Stronks, K. (Karien), Strufaldi, M.W. (Maria Wany), Suárez-Medina, R. (Ramón), Sun, C.-A. (Chien-An), Sundström, J. (Johan), Suriyawongpaisal, P. (Paibul), Sy, R.G. (Rody G.), Sylva, R.C. (René Charles), Szklo, M. (Moyses), Tai, E.S. (Shyong), Tamosiunas, A. (Abdonas), Tan, E.J. (Eng Joo), Tarawneh, M.R. (Mohammed Rasoul), Tarqui-Mamani, C.B. (Carolina B.), Taylor, A. (Anne), Taylor, J. (Julie), Tell, G.S. (Grethe S.), Tello, T. (Tania), Thankappan, K.R. (K. R.), Thijs, L. (Lutgarde), Thuesen, B.H. (Betina H.), Toft, U. (Ulla), Tolonen, H.K. (Hanna K.), Tolstrup, J.S. (Janne), Topbas, M. (Murat), Topór-Madry, R. (Roman), Tormo, M.J., Tornaritis, M.J. (Michael J.), Torrent, M. (Maties), Torres-Collado, L. (Laura), Traissac, P. (Pierre), Trinh, O.T.H. (Oanh T. H.), Truthmann, J. (Julia), Tsugane, S. (Shoichiro), Tulloch-Reid, M.K. (Marshall K.), Tuomainen, T.-P. (Tomi-Pekka), Tuomilehto, J. (Jaakko), Tybjaerg-Hansen, A. (Anne), Tzourio, C. (Christophe), Ueda, P. (Peter), Ugel, E. (Eunice), Ulmer, H. (Hanno), Unal, B. (Belgin), Uusitalo, H., Valdivia, G. (Gonzalo), Valvi, D. (Damaskini), Dam, R.M. (Rob) van, Schouw, Y.T. (Yvonne) van der, Van Herck, K. (Koen), Van Minh, H. (Hoang), Rossem, L. (Lenie) van, Schoor, N.M. (Natasja) van, Valkengoed, I. (Irene) van, Vanderschueren, D. (Dirk), Vanuzzo, D. (Diego), Varbo, A. (Anette), Varona-Pérez, P. (Patricia), Vasan, S.K. (Senthil K.), Vatten, L. (Lars), Vega, T. (Tomas), Veidebaum, T. (Toomas), Velasquez-Melendez, G. (Gustavo), Venero-Fernández, S.J. (Silvia J.), Veronesi, G. (Giovanni), Verschuren, W.M.M. (W. M. Monique), Victora, C.G. (Cesar G.), Vidiawati, D. (Dhanasari), Viet, L. (Lucie), Villalpando, S. (Salvador), Vioque, J. (Jesus), Virtanen, J.K. (Jyrki K.), Visvikis-Siest, S. (Sophie), Viswanathan, B. (Bharathi), Vlasoff, T. (Tiina), Vollenweider, P. (Peter), Voutilainen, A. (Ari), Wade, A.N. (Alisha N.), Wagner, A. (Aline), Walton, J. (Janette), Bebakar, W.M.W. (Wan Mohamad Wan), Mohamud, W.N.W. (Wan Nazaimoon Wan), Wang, M.-D. (Ming-Dong), Wang, N. (Ningli), Wang, Q. (Qian), Wang, Y.X. (Ya Xing), Wang, Y.-W. (Ying-Wei), Wannamethee, S.G. (Goya), Wedderkopp, N. (Niels), Wei, W. (Wenbin), Whincup, P.H. (Peter), Widhalm, K. (Kurt), Widyahening, I.S. (Indah S.), Wiecek, A. (Andrzej), Wijga, A.H. (Alet), Wilks, R.J. (Rainford J.), Willeit, J. (Johann), Willeit, P. (Peter), Wilsgaard, T. (Tom), Wojtyniak, B. (Bogdan), Wong-McClure, R.A. (Roy A.), Wong, A. (Andrew), Wong, T.Y. (Tien Yin), Woo, J. (Jean), Woodward, M. (Mark), Wu, F.C. (Frederick C.), Wu, S. (Shouling), Xu, H. (Haiquan), Xu, L. (Liang), Yan, W. (Weili), Yang, X. (Xiaoguang), Yasuharu, T. (Tabara), Ye, X. (Xingwang), Yeow, T.P. (Toh Peng), Yiallouros, P.K. (P.), Yoosefi, M. (Moein), Yoshihara, A. (Akihiro), You, S.-L. (San-Lin), Younger-Coleman, N.O. (Novie O.), Yusoff, A.F. (Ahmad Faudzi), Zainuddin, A.A. (Ahmad A.), Zakavi, S.R. (Seyed Rasoul), Zali, M.R. (Mohammad Reza), Zamani, F. (Farhad), Zambon, S. (Sabina), Zampelas, A. (Antonis), Zaw, K.K. (Ko Ko), Zdrojewski, T. (T.), Vrkic, T.Z. (Tajana Zeljkovic), Zhang, Z.-Y. (Zhen-Yu), Zhao, W. (Wenhua), Zhen, S. (Shiqi), Zheng, Y. (Yingfeng), Zholdin, B. (Bekbolat), Zhussupov, B. (Baurzhan), Zoghlami, N. (Nada), Cisneros, J.Z. (Julio Zuñiga), Gregg, E.W. (Edward W.), and Ezzati, M. (Majid)

Abstract

High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiov

Published
2020
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28. Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

Author

Meddens, S.F.W. (Fleur), Vlaming, R. (Ronald) de, Bowers, P. (Peter), Burik, C.A.P. (Casper A. P.), Linnér, R.K. (Richard Karlsson), Lee, C. (Chanwook), Okbay, A. (Aysu), Turley, P. (Patrick), Rietveld, C.A. (Cornelius A.), Fontana, M.A. (Mark Alan), Ghanbari, M. (Mohsen), Imamura, F. (Fumiaki), McMahon, G. (George), Most, P.J. (Peter) van der, Voortman, R.G. (Trudy), Wade, K.H. (Kaitlin H.), Anderson, E.L. (Emma L.), Braun, K.V.E. (Kim), Emmett, P.M. (Pauline M.), Esko, T. (Tõnu), Gonzalez, J.R. (Juan), Kiefte-de Jong, J.C. (Jessica), Langenberg, C. (Claudia), Luan, J. (Jian’an), Muka, T. (Taulant), Ring, S.M. (Susan), Rivadeneira, F. (Fernando), Snieder, H. (Harold), Rooij, F.J.A. (Frank) van, Wolffenbuttel, B.H.R. (Bruce), Smith, G.D. (George Davey), Franco, O.H. (Oscar H.), Forouhi, N.G. (Nita), Ikram, M.A. (Arfan), Uitterlinden, A.G. (André), van Vliet-Ostaptchouk, J.V. (Jana V.), Wareham, N.J. (Nick), Cesarini, D. (David), Harden, K.P. (K. Paige), Lee, J.J. (James J.), Benjamin, D.J. (Daniel J.), Chow, C.C. (Carson C.), Koellinger, P.D. (Philipp D.), Meddens, S.F.W. (Fleur), Vlaming, R. (Ronald) de, Bowers, P. (Peter), Burik, C.A.P. (Casper A. P.), Linnér, R.K. (Richard Karlsson), Lee, C. (Chanwook), Okbay, A. (Aysu), Turley, P. (Patrick), Rietveld, C.A. (Cornelius A.), Fontana, M.A. (Mark Alan), Ghanbari, M. (Mohsen), Imamura, F. (Fumiaki), McMahon, G. (George), Most, P.J. (Peter) van der, Voortman, R.G. (Trudy), Wade, K.H. (Kaitlin H.), Anderson, E.L. (Emma L.), Braun, K.V.E. (Kim), Emmett, P.M. (Pauline M.), Esko, T. (Tõnu), Gonzalez, J.R. (Juan), Kiefte-de Jong, J.C. (Jessica), Langenberg, C. (Claudia), Luan, J. (Jian’an), Muka, T. (Taulant), Ring, S.M. (Susan), Rivadeneira, F. (Fernando), Snieder, H. (Harold), Rooij, F.J.A. (Frank) van, Wolffenbuttel, B.H.R. (Bruce), Smith, G.D. (George Davey), Franco, O.H. (Oscar H.), Forouhi, N.G. (Nita), Ikram, M.A. (Arfan), Uitterlinden, A.G. (André), van Vliet-Ostaptchouk, J.V. (Jana V.), Wareham, N.J. (Nick), Cesarini, D. (David), Harden, K.P. (K. Paige), Lee, J.J. (James J.), Benjamin, D.J. (Daniel J.), Chow, C.C. (Carson C.), and Koellinger, P.D. (Philipp D.)

Abstract

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10−8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10−5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15–0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1–0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈−0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.

Published
2020
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29. Fetal sex and maternal pregnancy outcomes: a systematic review and meta-analysis

Author

Broere-Brown, Z.A. (Zoe), Adank, M.A. (Muriel), Benschop, H.A.M. (Laura), Tielemans, M.J. (Myrte), Muka, T. (Taulant), Gonçalves, R. (Romy), Bramer, W.M. (Wichor), Schoufour, J.D. (Josje), Voortman, R.G. (Trudy), Steegers, E.A.P. (Eric), Franco, O.H. (Oscar H.), Schalekamp-Timmermans, S. (Sarah), Broere-Brown, Z.A. (Zoe), Adank, M.A. (Muriel), Benschop, H.A.M. (Laura), Tielemans, M.J. (Myrte), Muka, T. (Taulant), Gonçalves, R. (Romy), Bramer, W.M. (Wichor), Schoufour, J.D. (Josje), Voortman, R.G. (Trudy), Steegers, E.A.P. (Eric), Franco, O.H. (Oscar H.), and Schalekamp-Timmermans, S. (Sarah)

Abstract

BACKGROUND: Since the placenta also has a sex, fetal sex-specific differences in the occurrence of placenta-mediated complications could exist. OBJECTIVE: To determine the association of fetal sex with multiple maternal pregnancy complications. SEARCH STRATEGY: Six electronic databases Ovid MEDLINE, EMBASE, Cochrane Central, Web-of-Science, PubMed, and Google Scholar were systematically searched to identify eligible studies. Reference lists of the included studies and contact with experts were also used for identification of studies. SELECTION CRITERIA: Observational studies that assessed fetal sex and the presence of maternal pregnancy complications within singleton pregnancies. DATA COLLECTION AND ANALYSES: Data were extracted by 2 independent reviewers using a predesigned data collection form. MAIN RESULTS: From 6522 original references, 74 studies were selected, including over 12,5 million women. Male fetal sex was associated with term pre-eclampsia (pooled OR 1.07 [95%CI 1.06 to 1.09]) and gestational diabetes (pooled OR 1.04 [1.02 to 1.07]). All other pregnancy complications (i.e., gestational hypertension, total pre-eclampsia, eclampsia, placental abruption, and post-partum hemorrhage) tended to be associated with male fetal sex, except for preterm pre-eclampsia, which was more associated with female fetal sex. Overall quality of the included studies was good. Between-study heterogeneity was high due to differences in study population and outcome definition. CONCLUSION: This meta-analysis suggests that the occurrence of pregnancy complications differ according to fetal sex with a higher cardiovascular and

Published
2020
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30. Prevalence of overweight and metabolic syndrome, and associated sociodemographic factors among adult Ecuadorian populations: the ENSANUT-ECU study

Author

Pérez-Galarza, J. (J.), Baldeón, L. (L.), Franco, O.H. (O. H.), Muka, T. (Taulant), Drexhage, H.A. (Hemmo), Voortman, R.G. (Trudy), Freire, W.B. (W. B.), Pérez-Galarza, J. (J.), Baldeón, L. (L.), Franco, O.H. (O. H.), Muka, T. (Taulant), Drexhage, H.A. (Hemmo), Voortman, R.G. (Trudy), and Freire, W.B. (W. B.)

Abstract

Background: Obesity and metabolic syndrome (MetS) are key risk factors for type 2 diabetes and cardiovascular disease. Little information exists on the prevalence of obesity and MetS in Latin America and specifically in Ecuador. We aimed to estimate the prevalence of overweight, obesity, and MetS among adults in Ecuador. Methods: We analyzed data from a nation-wide population-based survey in Ecuador (ENSANUT-ECU) among 10,318 participants (3684 men, 6634 women; age range: 18–59 years) conducted in 2012. Data related to residential location (urban versus rural), altitude (< 500, 500–1500 or > 1500 m above sea level (MASL)), region (highland, coast, amazon, or Galápagos), and socioeconomic status were collected. BMI, waist circumference, blood lipids, glucose, and blood pressure were measured by trained fieldworkers following standardized procedures. Results: The age-standardized prevalence of overweight was 39.5%; 22.3% was obese; and 31.2% had MetS. The prevalence of obesity, low HDL-cholesterol, and abdominal obesity were higher in women than in men, whereas men had a higher prevalence of hypertension (p < 0.05). Sex differences were not observed regarding the prevalence of combined MetS. Prevalence of both obesity and MetS was higher in urban areas, at low altitude regions (coast and Galapagos), and at high socioeconomic status (all p < 0.05). Conclusions: Prevalence of obesity and MetS in Ecuador are high. There are important demographic differences in the prevalence of MetS between Ecuadorian subpopulations that requires targeted research and prevention efforts, to hold and reduce the current public health problem of metabolic disorders.

Published
2020
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31. Dynamic interventions to control COVID-19 pandemic

Author

Chowdhury, R. (Rajiv), Heng, K. (Kevin), Shawon, M.S.R. (Md Shajedur Rahman), Goh, G. (Gabriel), Okonofua, D. (Daisy), Ochoa Rosales, C.P. (Carolina), Gonzalez-Jaramillo, V. (Valentina), Bhuiya, A. (Abbas), Reidpath, D. (Daniel), Prathapan, S. (Shamini), Shahzad, S. (Sara), Althaus, C.L. (Christian L.), Gonzalez-Jaramillo, N. (Nathalia), Franco, O.H. (Oscar H.), Chowdhury, R. (Rajiv), Heng, K. (Kevin), Shawon, M.S.R. (Md Shajedur Rahman), Goh, G. (Gabriel), Okonofua, D. (Daisy), Ochoa Rosales, C.P. (Carolina), Gonzalez-Jaramillo, V. (Valentina), Bhuiya, A. (Abbas), Reidpath, D. (Daniel), Prathapan, S. (Shamini), Shahzad, S. (Sara), Althaus, C.L. (Christian L.), Gonzalez-Jaramillo, N. (Nathalia), and Franco, O.H. (Oscar H.)

Abstract

To date, non-pharmacological interventions (NPI) have been the mainstay for controlling the coronavirus disease-2019 (COVID-19) pandemic. While NPIs are effective in preventing health systems overload, these long-term measures are likely to have significant adverse economic consequences. Therefore, many countries are currently considering to lift the NPIs—increasing the likelihood of disease resurgence. In this regard, dynamic NPIs, with intervals of relaxed social distancing, may provide a more suitable alternative. However, the ideal frequency and duration of intermittent NPIs, and the ideal “break” when interventions can be temporarily relaxed, remain uncertain, especially in resource-poor settings. We employed a multivariate prediction model, based on up-to-date transmission and clinical parameters, to simulate outbreak trajectories in 16 countries, from diverse regions and economic categories. In each country, we then modelled the impacts on intensive care unit (ICU) admissions and deaths over an 18-month period for following scenarios: (1) no intervention, (2) consecutive cycles of mitigation measures followed by a relaxation period, and (3) consecutive cycles of suppression measures followed by a relaxation period. We defined these dynamic interventions based on reduction of the mean reproduction number during each cycle, assuming a basic reproduction number (R0) of 2.2 for no intervention, and subsequent effective reproduction numbers (R) of 0.8 and 0.5 for illustrative dynamic mitigation and suppression interventions, respectively. We found that dynamic cycles of 50-day mitigation followed by a 30-day relaxation reduced transmission, however, were unsuccessful in lowering IC

Published
2020
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32. Trajectories of BMI Before Diagnosis of Type 2 Diabetes: The Rotterdam Study

Author

Nano, J. (Jana), Dhana, K. (Klodian), Asllanaj, E. (Eralda), Sijbrands, E. (Eric), Ikram, M.A. (Arfan), Dehghan, A. (Abbas), Muka, T. (Taulant), Franco, O.H. (Oscar H.), Nano, J. (Jana), Dhana, K. (Klodian), Asllanaj, E. (Eralda), Sijbrands, E. (Eric), Ikram, M.A. (Arfan), Dehghan, A. (Abbas), Muka, T. (Taulant), and Franco, O.H. (Oscar H.)

Abstract

Objective: People with diabetes show great variability in weight gain and duration of obesity at the time of diagnosis. BMI trajectories and other cardiometabolic risk factors prior to type 2 diabetes were investigated. Methods: A total of 6,223 participants from the Rotterdam Study cohort were included. BMI patterns before diagnosis of diabetes were identified through latent class trajectories. Results: During a mean follow-up of 13.7 years, 565 participants developed type 2 diabetes. Three distinct trajectories of BMI were identified, including the “progressive overweight” group (n = 481, 85.1%), “progressive weight loss” group (n = 59, 10.4%), and “persistently high BMI” group (n = 25, 4.4%). The majority, the progressive overweight group, was characterized by a steady increase of BMI in the overweight range 10 years before diabetes diagnosis. The progressive weight loss group had fluctuations of glucose and marked beta cell function loss. The persistently high BMI group was characterized by a slight increase in insulin levels and sharp increase of insulin resistance accompanied by a rapid decrease of beta cell function. Conclusions : Heterogeneity of BMI changes prior to type 2 diabetes was found in a middle-aged and elderly white population. Prevention strategies should be tailored rather than focusing only on high-risk individuals.

Published
2020
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33. Development and external validation of a deep learning algorithm for prognostication of cardiovascular outcomes

Author

Cho, I.-J. (In-Jeong), Sung, J.M. (Ji Min), Kim, H.C. (Hyeon Chang), Lee, S.-E. (Sang-Eun), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), Min, J.K. (James K.), Chang, H.-J. (Hyuk-Jae), Cho, I.-J. (In-Jeong), Sung, J.M. (Ji Min), Kim, H.C. (Hyeon Chang), Lee, S.-E. (Sang-Eun), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), Min, J.K. (James K.), and Chang, H.-J. (Hyuk-Jae)

Abstract

Background and Objectives: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. Methods: Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): A Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. Results: Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NRI], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). Conclusions: A DL algorithm exhibited greater discriminative accuracy than Cox model approaches.

Published
2020
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34. Healthy lifestyle and life expectancy free of cancer, cardiovascular disease, and type 2 diabetes: prospective cohort study

Author

Li, Y. (Yanping), Schoufour, J.D. (Josje), Wang, D.D. (Dong D.), Dhana, K. (Klodian), Pan, A. (Amy), Liu, X. (Xiaoran), Song, M. (Mingyang), Liu, G. (Gang), Shin, H.J. (Hyun Joon), Sun, Q. (Qi), Al-Shaar, L. (Laila), Wang, M. (Molin), Rimm, E.B. (Eric B.), Hertzmark, E. (Ellen), Stampfer, M.J. (Meir), Willett, W.C. (Walter C.), Franco, O.H. (Oscar H.), Hu, F.B. (Frank B.), Li, Y. (Yanping), Schoufour, J.D. (Josje), Wang, D.D. (Dong D.), Dhana, K. (Klodian), Pan, A. (Amy), Liu, X. (Xiaoran), Song, M. (Mingyang), Liu, G. (Gang), Shin, H.J. (Hyun Joon), Sun, Q. (Qi), Al-Shaar, L. (Laila), Wang, M. (Molin), Rimm, E.B. (Eric B.), Hertzmark, E. (Ellen), Stampfer, M.J. (Meir), Willett, W.C. (Walter C.), Franco, O.H. (Oscar H.), and Hu, F.B. (Frank B.)

Abstract

OBJECTIVE: To examine how a healthy lifestyle is related to life expectancy that is free from major chronic diseases. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: The Nurses' Health Study (1980-2014; n=73 196) and the Health Professionals Follow-Up Study (1986-2014; n=38 366). MAIN EXPOSURES: Five low risk lifestyle factors: never smoking, body mass index 18.5-24.9, moderate to vigorous physical activity (≥30 minutes/day), moderate alcohol intake (women: 5-15 g/day; men 5-30 g/day), and a higher diet quality score (upper 40%). MAIN OUTCOME: Life expectancy free of diabetes, cardiovascular diseases, and cancer. RESULTS: The life expectancy free of diabetes, cardiovascular diseases, and cancer at age 50 was 23.7 years (95% confidence interval 22.6 to 24.7) for women who adopted no low risk lifestyle factors, in contrast to 34.4 years (33.1 to 35.5) for women who adopted four or five low risk factors. At age 50, the life expectancy free of any of these chronic diseases was 23.5 (22.3 to 24.7) years among men who adopted no low risk lifestyle factors and 31.1 (29.5 to 32.5) years in men who adopted four or five low risk lifestyle factors. For current male smokers who smoked heavily (≥15 cigarettes/day) or obese men and women (body mass index ≥30), their disease-free life expectancies accounted for the lowest proportion (≤75%) of total life expectancy at age 50. CONCLUSION: Adherence to a healthy lifestyle at mid-life is associated with a longer life expectancy free of major chronic diseases.

Published
2020
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35. Serum insulin levels are associated with vulnerable plaque components in the carotid artery: the Rotterdam Study

Author

Mujaj, B. (Blerim), Bos, D. (Daniel), Kavousi, M. (Maryam), Lugt, A. (Aad) van der, Staessen, J.A. (Jan A.), Franco, O.H. (Oscar H.), Vernooij, M.W. (Meike), Mujaj, B. (Blerim), Bos, D. (Daniel), Kavousi, M. (Maryam), Lugt, A. (Aad) van der, Staessen, J.A. (Jan A.), Franco, O.H. (Oscar H.), and Vernooij, M.W. (Meike)

Abstract

Background: To investigate the association between fasting serum insulin and glucose levels with atherosclerotic plaque composition in the carotid artery. Impaired insulin and glucose levels are implicated in the etiology of cardiovascular disease; however, their influence on the formation and composition of atherosclerotic plaque

Published
2020
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36. Muscle mass heavily influences creatinine-based renal function estimation: a 12-year longitudinal general population-based cohort study

Author

Groothof, D, primary, Post, A, additional, Polinder-Bos, H.A, additional, Kieneker, L.M, additional, Flores-Guerrero, J.L, additional, Kootstra-Ros, J.E, additional, De Borst, M.H, additional, Gansevoort, R.T, additional, Spycher, B.D, additional, Erler, N.S, additional, Bano, A, additional, Muka, T, additional, Franco, O.H, additional, and Bakker, S.J.L, additional

Published
2020
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39. Validated inference of smoking habits from blood with a finite DNA methylation marker set

Author

Maas, S.C.E., Vidaki, A., Wilson, R., Teumer, A., Liu, F., Meurs, J.B.J. van, Uitterlinden, A.G., Boomsma, D.I., Geus, E.J.C. de, Willemsen, G., Dongen, J. van, Kallen, C.J.H. van der, Slagboom, P.E., Beekman, M., Heemst, D. van, Berg, L.H. van den, Duijts, L., Jaddoe, V.W.V., Ladwig, K.H., Kunze, S., Peters, A., Ikram, M.A., Grabe, H.J., Felix, J.F., Waldenberger, M., Franco, O.H., Ghanbari, M., Kayser, M., and BIOS Consortium

Subjects
DNA methylation, Epidemiology, Epigenetics, Smoking inference, Forensics
Abstract

Inferring a person's smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 +/- 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUC(crossvalidation) 0.925 +/- 0.021, AUC(externalvalidation)0.914), former (0.766 +/- 0.023, 0.699) and never smoking (0.830 +/- 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 +/- 0.068, 0.796; 15 pack-years 0.767 +/- 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 +/- 0.024, 0.760; 10 years 0.766 +/- 0.033, 0.764; 15 years 0.767 +/- 0.020, 0.754). Model application to children revealed highly accurate inference of the true non- smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications.

Published
2019

40. Dietary Factors and Modulation of Bacteria Strains of Akkermansia muciniphila and Faecalibacterium prausnitzii: A Systematic Review

Author

Verhoog, S., Taneri, P.E., Roa Díaz, Z.M., Marques-Vidal, P., Troup, J.P., Bally, L., Franco, O.H., Glisic, M., and Muka, T.

Subjects
Diet, Faecalibacterium prausnitzii/drug effects, Gastrointestinal Microbiome, Humans, Verrucomicrobia/drug effects, Akkermansia muciniphila, Faecalibacterium prausnitzii, dietary interventions, microbiome, randomized controlled trials, systematic review
Abstract

Akkermansia muciniphila and Faecalibacterium prausnitzii are highly abundant human gut microbes in healthy individuals, and reduced levels are associated with inflammation and alterations of metabolic processes involved in the development of type 2 diabetes. Dietary factors can influence the abundance of A. muciniphila and F. prausnitzii, but the evidence is not clear. We systematically searched PubMed and Embase to identify clinical trials investigating any dietary intervention in relation to A. muciniphila and F. prausnitzii. Overall, 29 unique trials were included, of which five examined A. muciniphila, 19 examined F. prausnitzii, and six examined both, in a total of 1444 participants. A caloric restriction diet and supplementation with pomegranate extract, resveratrol, polydextrose, yeast fermentate, sodium butyrate, and inulin increased the abundance of A. muciniphila, while a diet low in fermentable oligosaccharides, disaccharides, monosaccharides, and polyols decreased the abundance of A. muciniphila. For F. prausnitzii, the main studied intervention was prebiotics (e.g. fructo-oligosaccharides, inulin type fructans, raffinose); seven studies reported an increase after prebiotic intervention, while two studies reported a decrease, and four studies reported no difference. Current evidence suggests that some dietary factors may influence the abundance of A. muciniphila and F. prausnitzii. However, more research is needed to support these microflora strains as targets of microbiome shifts with dietary intervention and their use as medical nutrition therapy in prevention and management of chronic disease.

Published
2019

41. Mediterranean Diet and Incidence of Advanced Age-Related Macular Degeneration: The EYE-RISK Consortium

Author

Merle, B.M.J., Colijn, J.M., Cougnard-Gregoire, A., Koning-Backus, A.P.M. de, Delyfer, M.N., Kiefte-de Jong, J.C., Meester-Smoor, M., Feart, C., Verzijden, T., Samieri, C., Franco, O.H., Korobelnik, J.F., Klaver, C.C.W., Delcourt, C., Ajana, S., Arango-Gonzalez, B., Armento, A., Arndt, V., Bhatia, V., Bhattacharya, S.S., Biarnes, M., Borrell, A., Buhren, S., Calado, S.M., Dammeier, S., Jong, E.K. de, Cerda, B. de la, Hollander, A.I. den, Diaz-Corrales, F.J., Diether, S., Emri, E., Endermann, T., Ferraro, L.L., Garcia, M., Heesterbeek, T.J., Honisch, S., Hoyng, C.B., Kersten, E., Kilger, E., Langen, H., Lengyel, I., Luthert, P., Maugeais, C., Mones, J., Nogoceke, E., Peto, T., Pool, F.M., Rodriguez, E., Ueffing, M., Bartz-Schmidt, K.U.U., Leeuwen, E.M. van, Zumbansen, M., Vasiliev, V., and EYE-RISK Consortium

Published
2019

42. Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits

Author

Harris, S.E., Corley, J., Wojczynski, M.K., Nauck, M., Levy, D., Gu, C., Sorensen, T.I.A., Noordam, R., Guo, X., Hill, W.D., Chen, Y.-D.I., Liu, C., Yao, J., Kraja, A.T., Daw, E.W., Irvin, M.R., Christensen, C., Newman, A.B., Hansen, T., Hudson, G., Zeng, D., Wu, H., Uitterlinden, A.G., Wareham, N.J., Perls, T.T., Grarup, N., Broeckel, U., Luan, J., Fu, M., Hemani, G., de Mutsert, R., Lin, S.J., Wilson, J.G., Jorgensen, M.E., Witte, D.R., Have, C.T., Ribel-Madsen, R., Wang, Y., Love-Gregory, L.D., Bowden, D.W., Province, M.A., Rotter, J.I., Taylor, A.M., Hunt, S.C., Thyagarajan, B., Goodarzi, M.O., Ridker, P.M., Torp-Pedersen, C., Ligthart, S., Starr, J.M., Feitosa, M.F., Arnett, D.K., de Haan, H.G., Jorgensen, T., Weeke, P.E., Graff, M., de las Fuentes, L., Justice, A.E., Hayward, C., Kerrison, N.D., Pedersen, O., Bonnelykke, K., Perry, J.A., Fetterman, J.L., Hai, Y., Malik, A.N., Vestergaard, H., Cropp, C.D., Ryan, K.A., Christensen, K., The Population Sciences Branch, NHLBI/NIH, Armasu, S.M., Langenberg, C., Forouhi, N.G., Yang, W., Teumer, A., Rodriguez, S., Kardia, S.L.R., Qi, Q., Becker, D.M., Baranski, T.J., Yanek, L.R., Rao, D.C., Fernandez, E.P., Lin, K.-H., Li-Gao, R., Sofer, T., Nohr, E.A., Larson, N.B., Sheu, W.H.-H., Elliott, P., An, P., Schnurr, T.M., Gu, Z., Taylor, K.D., Davies, G., Kilpelainen, T.O., Lee, W.-J., Patki, A., Barve, R.A., Brandslund, I., Sandow, K., Weiss, S., Wang, L., Stergiakouli, E., Mathias, R.A., Ghanbari, M., Tiwari, H.K., Rivadeneira, F., Davila-Roman, V.G., de Andrade, M., North, K.E., Richardson, T.G., Horta, B.L., Bielinski, S.J., Linneberg, A., Young, K., Argos, M., Dehghan, A., Chasman, D.I., Mook-Kanamori, D.O., Vaidya, D., Petersmann, A., Scott, R.A., Meigs, J.B., Ahluwalia, T.S., Gao, H., Rosendaal, F.R., Chakravarti, A., van Heemst, D., Cox, S.R., Williams, C., Pankow, J., Giulianini, F., Weir, B.S., Jonsson, A.E., Hartwig, F.P., Rohde, R., Ikram, M.A., Homuth, G., Lee, J.H., Deary, I.J., Erzurumluoglu, A.M., Chu, A.Y., Emery, L.S., Franco, O.H., Ong, K.K., Arking, D.E., Loos, R.J.F., Tzoulaki, I., Pattie, A., Timpson, N.J., and Turner, S.T.

Abstract

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E−04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E−03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E−06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

Published
2019
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44. Intake of Vegetables, Fruit, and Fish is Beneficia for Age-Related Macular Degeneration

Author

Koning-Backus, Alexandra P.M. De, Buitendijk, Gabrielle H. S., Jong, Jessica C.Kiefte-De, Colijn, J.M., Hofman, Albert, Vingerling, J.R., Franco, O.H., Klaver, C.C.W., Koning-Backus, Alexandra P.M. De, Buitendijk, Gabrielle H. S., Jong, Jessica C.Kiefte-De, Colijn, J.M., Hofman, Albert, Vingerling, J.R., Franco, O.H., and Klaver, C.C.W.

Abstract

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Published
2019

45. Maternal vomiting during early pregnancy and cardiovascular risk factors at school age: the Generation R Study

Author

Bahadoer, S.P., Jaddoe, V.W.V. (Vincent), Gishti, O., Grooten, IJ, Franco, O.H., Hofman, A. (Albert), Steegers, E.A.P. (Eric), Gaillard, R. (Romy), Bahadoer, S.P., Jaddoe, V.W.V. (Vincent), Gishti, O., Grooten, IJ, Franco, O.H., Hofman, A. (Albert), Steegers, E.A.P. (Eric), and Gaillard, R. (Romy)

Abstract

Background: Evidence suggests that low birth weight and fetal exposure to extreme maternal undernutrition is associated with cardiovascular disease in adulthood. Hyperemesis gravidarum, a clinical entity characterized by severe nausea and excess vomiting leading to a suboptimal maternal nutritional status during early pregnancy, is associated with an increased risk of adverse pregnancy outcomes. Several studies also showed that different measures related to hyperemesis gravidarum, such as maternal daily vomiting or severe weight loss, are associated with increased risks of adverse fetal pregnancy outcomes. Not much is known about long-term offspring consequences of maternal hyperemesis gravidarum and related measures during pregnancy. We examined the associations of maternal daily vomiting during early pregnancy, as a measure related to hyperemesis gravidarum, with childhood cardiovascular risk factors. Methods: In a population-based prospective cohort study from early pregnancy onwards among 4,769 mothers and their children in Rotterdam, the Netherlands, we measured childhood body mass index, total fat mass percentage, android/gynoid fat mass ratio, preperitoneal fat mass area, blood pressure, lipids, and insulin levels. We used multiple regression analyses to assess the associations of maternal vomiting during early pregnancy with childhood cardiovascular outcomes. Results: Compared with the children of mothers without daily vomiting during early pregnancy, the children of mothers with daily vomiting during early pregnancy had a higher childhood total body fat mass (difference 0.12 standard deviation score [SDS]; 95% confidence interval [CI] 0.03–0.20), android/gynoid fat mass ratio (difference 0.13 SDS; 95% CI 0.04– 0.23), and preperitoneal fat mass area (difference 0.10 SDS; 95% CI 0–0.20). These associations were not explained by birth characteristics but partly explained by higher infant growth. Maternal daily vomiting during early pregnancy was not associated

Published
2019
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46. Sarcopenia in COPD: a systematic review and meta-analysis

Author

Benz, E. (Elizabeth), Trajanoska, K. (Katerina), Lahousse, L. (Lies), Schoufour, J.D. (Josje), Terzikhan, N. (Natalie), Roos, E.W. (Emmely) de, de Jonge, G.B. (Gerdien B.), Williams, R. (Ross), Franco, O.H. (Oscar), Brusselle, G.G. (Guy), Rivadeneira, F. (Fernando), Benz, E. (Elizabeth), Trajanoska, K. (Katerina), Lahousse, L. (Lies), Schoufour, J.D. (Josje), Terzikhan, N. (Natalie), Roos, E.W. (Emmely) de, de Jonge, G.B. (Gerdien B.), Williams, R. (Ross), Franco, O.H. (Oscar), Brusselle, G.G. (Guy), and Rivadeneira, F. (Fernando)

Abstract

COPD is associated with a progressive loss of muscle mass and function. However, there is an unmet need to define and standardise methods to estimate the prevalence of sarcopenia in COPD patients.We performed a systematic review and meta-analysis of the prevalence of this extrapulmonary manifestation in COPD patients. We searched Embase, Medline (Ovid), CINAHL (EBSCO), Web of Science, Scopus and Google Scholar for studies published up to January 17, 2019, assessing sarcopenia in COPD patients based on low muscle mass and decreased muscle function. Interventional studies, in vitro experiments, protocols or reviews and meta-analyses were excluded. We estimated heterogeneity (I2) and assessed significance (Q) using a Chi-squared test for estimates obtained from random-effects models.4465 articles were initially identified. After removing the duplicates and applying the selection criteria, we reviewed 62 full-text articles. Finally, 10 articles (n=2565 COPD patients) were included in this systematic review and meta-analyses. Overall, the prevalence of sarcopenia in patients with COPD was 21.6% (95% CI 14.6-30.9%, I2=94%), ranging from 8% in population-based to 21% in clinic-based studies, and 63% in COPD patients residing in nursing homes.Sarcopenia is frequently observed in COPD patients, with varying prevalence across population settings. Sarcopenia in COPD should be assessed using standardised tests and cut-off points from sarcopenia consensus criteria for clinical practice and international comparisons.

Published
2019
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47. Progression of conventional cardiovascular risk factors and vascular disease risk in individuals: insights from the PROG-IMT consortium

Author

Bahls, M. (Martin), Lorenz, M.W. (Matthias W.), Dörr, M. (Marcus), Gao, L. (Lu), Kitagawa, K. (Kazuo), Tuomainen, T.-P. (Tomi-Pekka), Agewall, S. (Stefan), Berenson, G. (Gerald), Catapano, A.L. (Alberico), Norata, G.D. (Giuseppe), Bots, M.L. (Michiel), Gilst, W.H. (Wiek) van, Asselbergs, F.W. (Folkert), Brouwers, F.P. (Frank P), Uthoff, H. (Heiko), Sander, D. (Dirk), Poppert, H. (Holger), Hecht Olsen, M. (Michael), Empana, J.P. (Jean Philippe), Schminke, U. (Ulf), Baldassarre, D. (Damiano), Veglia, F. (Fabrizio), Franco, O.H. (Oscar), Kavousi, M. (Maryam), Groot, E. (Eric) de, Mathiesen, E.B. (Ellisiv), Grigore, L. (Liliana), Polak, J. (Joseph), Rundek, T. (Tatjana), Stehouwer, C.D. (Coen), Skilton, M.R. (Michael R), Hatzitolios, A.I. (Apostolos I), Savopoulos, C. (Christos), Ntaios, G. (George), Plichart, M. (Matthieu), McLachlan, S. (Stela), Kao, W.H.L. (Wen), Willeit, P. (Peter), Steinmetz, H. (Helmuth), Desvarieux, M. (Moise), Ikram, M.A. (Arfan), Johnsen, S.H., Schmidt, C. (Caroline), Willeit, J. (Johann), Ducimetiere, P. (P.), Price, J.F. (Jackie F), Bergström, G. (Göran), Kauhanen, J. (Jussi), Kiechl, S. (Stefan), Sitzer, M. (Matthias), Bickel, H. (Horst), Muir, K.W. (Keith), Hofman, A. (Albert), Völzke, H. (Henry), Thompson, S.G. (Simon G), Bahls, M. (Martin), Lorenz, M.W. (Matthias W.), Dörr, M. (Marcus), Gao, L. (Lu), Kitagawa, K. (Kazuo), Tuomainen, T.-P. (Tomi-Pekka), Agewall, S. (Stefan), Berenson, G. (Gerald), Catapano, A.L. (Alberico), Norata, G.D. (Giuseppe), Bots, M.L. (Michiel), Gilst, W.H. (Wiek) van, Asselbergs, F.W. (Folkert), Brouwers, F.P. (Frank P), Uthoff, H. (Heiko), Sander, D. (Dirk), Poppert, H. (Holger), Hecht Olsen, M. (Michael), Empana, J.P. (Jean Philippe), Schminke, U. (Ulf), Baldassarre, D. (Damiano), Veglia, F. (Fabrizio), Franco, O.H. (Oscar), Kavousi, M. (Maryam), Groot, E. (Eric) de, Mathiesen, E.B. (Ellisiv), Grigore, L. (Liliana), Polak, J. (Joseph), Rundek, T. (Tatjana), Stehouwer, C.D. (Coen), Skilton, M.R. (Michael R), Hatzitolios, A.I. (Apostolos I), Savopoulos, C. (Christos), Ntaios, G. (George), Plichart, M. (Matthieu), McLachlan, S. (Stela), Kao, W.H.L. (Wen), Willeit, P. (Peter), Steinmetz, H. (Helmuth), Desvarieux, M. (Moise), Ikram, M.A. (Arfan), Johnsen, S.H., Schmidt, C. (Caroline), Willeit, J. (Johann), Ducimetiere, P. (P.), Price, J.F. (Jackie F), Bergström, G. (Göran), Kauhanen, J. (Jussi), Kiechl, S. (Stefan), Sitzer, M. (Matthias), Bickel, H. (Horst), Muir, K.W. (Keith), Hofman, A. (Albert), Völzke, H. (Henry), and Thompson, S.G. (Simon G)

Abstract

Aims: Averaged measurements, but not the progression based on multiple assessments of carotid intima-media thickness, (cIMT) are predictive of cardiovascular disease (CVD) events in individuals. Whether this is true for conventional risk factors is unclear. Methods and results: An individual participant meta-analysis was used to associate the annualised progression of systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with future cardiovascular disease risk in 13 prospective cohort studies of the PROG-IMT collaboration (n = 34,072). Follow-up data included information on a combined cardiovascular disease endpoint of myocardial infarction, stroke, or vascular death. In secondary analyses, annualised progression was replaced with average. Log hazard ratios per standard deviation difference were pooled across studies by a random effects meta-analysis. In primary analysis, the annualised progression of total cholesterol was marginally related to a higher cardiovascular disease risk (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.00 to 1.07). The annualised progression of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol was not associated with future cardiovascular disease risk. In secondary analysis, average systolic blood pressure (HR 1.20 95% CI 1.11 to 1.29) and low-density lipoprotein cholesterol (HR 1.09, 95% CI 1.02 to 1.16) were related to a greater, while high-density lipoprotein cholesterol (HR 0.92, 95% CI 0.88 to 0.97) was related to a lower risk of future cardiovascular disease events. Conclusion: Averaged measurements of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol displayed significant linear relationships with the risk of future cardiovascular disease events. However, there was no clear association between the annualised progression of these conventional risk factors in

Published
2019
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48. Kidney Function and Arterial Calcification in Major Vascular Beds

Author

Sedaghat, S. (Sanaz), Hoorn, E.J. (Ewout), Ikram, M.A. (Arfan), Koop-Nieuwelink, C. (Carolien), Kavousi, M. (Maryam), Franco, O.H. (Oscar), Lugt, A. (Aad) van der, Vernooij, M.W. (Meike), Bos, D. (Daniel), Sedaghat, S. (Sanaz), Hoorn, E.J. (Ewout), Ikram, M.A. (Arfan), Koop-Nieuwelink, C. (Carolien), Kavousi, M. (Maryam), Franco, O.H. (Oscar), Lugt, A. (Aad) van der, Vernooij, M.W. (Meike), and Bos, D. (Daniel)

Abstract

Background-—The purpose of this study was to investigate the association between kidney function and arterial calcification in major vascular beds and to establish whether arterial calcification mediates the relation between kidney function measures and cardiovascular disease (CVD) incidence. Methods and Results-—In 2241 participants from the Rotterdam Study (mean age 69 years, 52% female), kidney function was assessed using the estimated glomerular filtration rate and urine albumin-to-creatinine ratio. All participants underwent noncontrast computed tomography to quantify the amount of arterial calcification in the coronary arteries, aortic arch, extracranial, and intracranial internal carotid arteries. We used linear regression models, adjusted for age, sex, and cardiovascular risk factors, to evaluate the association between kidney function and arterial calcification volume in the 4 vessel beds. Incidence rate of CVD was calculated in 3 groups of participants based on their kidney function and presence of arterial calcification. We conducted mediation analysis to evaluate whether arterial calcification mediates this association. We found that in age- and sex-adjusted models, lower estimated glomerular filtration rate and higher albumin-to-creatinine ratio were associated with larger calcification volumes in all 4 vascular beds. Adjusting for cardiovascular risk factors attenuated the effect estimates. CVD incidence was higher in participants with estimated glomerular filtration rate <60 mL/min per 1.73 m2 and presence of arterial calcification compared with individuals with estimated glomerular filtration rate >60 and no calcification. After adjusting for cardiovascular risk factors, arterial calcification did not mediate the association between kidney function measures and CVD incidence. Conclusions-—The association of impaired kidney function and larger volumes of arterial calcification is partly explained by cardiovascular risk factors. Arterial calcification

Published
2019
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49. Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease

Author

Tzoulaki, I., Castagne, R. (Raphaële), Boulange, C. L., Karaman, I., Chekmeneva, E., Evangelou, E. (Evangelos), Ebbels, T., Kaluarachchi, M. R., Chadeau-Hyam, M, Mosen, D., Dehghan, A., Moayyeri, A. (Alireza), Ferreira, D. L. S., Guo, X. (Xiuqing), Rotter, J.I. (Jerome), Taylor, K.D. (Kent), Kavousi, M. (Maryam), de Vries, PS, Lehne, B, Loh, M, Hofman, A., Nicholson, J.K., Chambers, J. (John), Gieger, C. (Christian), Holmes, E., Tracy, R, Kooner, J, Greenland, P. (Philip), Franco, O.H. (Oscar), Herrington, D, Lindon, J. C., Elliott, P.M. (Perry), Tzoulaki, I., Castagne, R. (Raphaële), Boulange, C. L., Karaman, I., Chekmeneva, E., Evangelou, E. (Evangelos), Ebbels, T., Kaluarachchi, M. R., Chadeau-Hyam, M, Mosen, D., Dehghan, A., Moayyeri, A. (Alireza), Ferreira, D. L. S., Guo, X. (Xiuqing), Rotter, J.I. (Jerome), Taylor, K.D. (Kent), Kavousi, M. (Maryam), de Vries, PS, Lehne, B, Loh, M, Hofman, A., Nicholson, J.K., Chambers, J. (John), Gieger, C. (Christian), Holmes, E., Tracy, R, Kooner, J, Greenland, P. (Philip), Franco, O.H. (Oscar), Herrington, D, Lindon, J. C., and Elliott, P.M. (Perry)

Abstract

Aims To characterize serum metabolic signatures associated with atherosclerosis in the coronary or carotid arteries and subsequently their association with incident cardiovascular disease (CVD). ................................................................................................................................................................................................... Methods and results We used untargeted one-dimensional (1D) serum metabolic profiling by proton nuclear magnetic resonance spectroscopy (1 H NMR) among 3867 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), with replication among 3569 participants from the Rotterdam and LOLIPOP studies. Atherosclerosis was assessed by coronary artery calcium (CAC) and carotid intima-media thickness (IMT). We used multivariable linear regression to evaluate associations between NMR features and atherosclerosis accounting for multiplicity of comparisons. We then examined associations between metabolites associated with atherosclerosis and incident CVD available in MESA and Rotterdam and explored molecular networks through bioinformatics analyses. Overall, 30 1 H NMR measured metabolites were associated with CAC and/or IMT, P= 1.3 10-14 to 1.0 10-6 (discovery) and P= 5.6 10-10 to 1.1 10-2 (replication). These associations were substantially attenuated after adjustment for conventional cardiovascular risk factors. Metabolites associated with atherosclerosis revealed disturbances in lipid and carbohydrate metabolism, branched chain, and aromatic amino acid metabolism, as well as oxidative stress and inflammatory pathways. Analyses of incident CVD events showed inverse associations with creatine, creatinine, and phenylalanine, and direct associations with mannose, acetaminophen-glucuronide, and lactate as well as apolipoprotein B (P< 0.05). .....................................................................................................................................................

Published
2019
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50. Development and verification of prediction models for preventing cardiovascular diseases

Author

Sung, J.M. (Ji Min), Cho, I.-J. (In-Jeong), Sung, D. (David), Kim, S. (Sunhee), Kim, H.C. (Hyeon Chang), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), Chang, H.-J. (Hyuk-Jae), Sung, J.M. (Ji Min), Cho, I.-J. (In-Jeong), Sung, D. (David), Kim, S. (Sunhee), Kim, H.C. (Hyeon Chang), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), and Chang, H.-J. (Hyuk-Jae)

Abstract

Objectives Cardiovascular disease (CVD) is one of the major causes of death worldwide. For improved accuracy of CVD prediction, risk classification was performed using national time-series health examination data. The data offers an opportunity to access deep learning (RNN-LSTM), which is widely known as an outstanding algorithm for analyzing time-series datasets. The objective of this study was to show the improved accuracy of deep learning by comparing the performance of a Cox hazard regression and RNN-LSTM based on survival analysis. Methods and findings We selected 361,239 subjects (age 40 to 79 years) with more than two health examination records from 2002–2006 using the National Health Insurance System-National Health Screening Cohort (NHIS-HEALS). The average number of health screenings (from 2002–2013) used in the analysis was 2.9 ± 1.0. Two CVD prediction models were developed from the NHIS-HEALS data: a Cox hazard regression model and a deep learning model. In an internal validation of the NHIS-HEALS dataset, the Cox regression model showed a highest time-dependent area under the curve (AUC) of 0.79 (95% CI 0.70 to 0.87) for in females and 0.75 (95% CI 0.70 to 0.80) in males at 2 years. The deep learning model showed a highest time-dependent AUC of 0.94 (95% CI 0.91 to 0.97) for in females and 0.96 (95% CI 0.95 to 0.97) in males at 2 years. Layer-wise Relevance Propagation (LRP) revealed that age was the variable that had the greatest effect on CVD, followed by systolic blood pressure (SBP) and diastolic blood pressure (DBP), in that order. Conclusion The performance of the deep learning model for predicting CVD occurrences was better than that of the Cox regression model. In addition, it was confirmed that the known risk factors shown to be important by previous clinical studies were extracted from the study results using LRP.

Published
2019
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