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Birth weight modifies the association between a healthy Nordic diet and office blood pressure in old age

Journal of Human Hypertension volume 35, pages 849–858 (2021)Cite this article

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Abstract

A healthy diet reduces risk for high blood pressure. A small body size at birth increases risk for high blood pressure. Our aim was to study whether birth weight modifies the association between a healthy Nordic diet, characterized by high intake of Nordic vegetables, fruits, and berries, whole-grain rye, oat, and barley, and rapeseed oil, and blood pressure. Finnish men and women (n = 960) born in 1934–1944 attended clinical visits including clinical measurements, and questionnaires in 2001–2004 and 2011–2013. Linear regression was applied to investigate the interactions between birth weight and Nordic diet (measured by the Baltic sea diet score (BSDS)) on blood pressure change during the 10-year follow-up. Baseline Nordic diet and birth weight showed a significant interaction on systolic blood pressure (SBP) (p = 0.02), and pulse pressure (PP) (p < 0.01) over a 10-year follow-up. In the lowest birth weight category (women < 2951 g, men < 3061 g), predicted SBP decreased across BSDS thirds (lowest (T1): 155 mmHg, highest (T3): 145 mmHg, p for linearity = 0.01) as did predicted PP (T1: 71 mmHg, T3: 63 mmHg, p < 0.01). In the middle birth weight category, predicted SBP increased across BSDS thirds (T1: 151 mmHg, T3: 155 mmHg, p = 0.02) as did predicted PP (T1: 67 mmHg, T3: 71 mmHg, p < 0.01). In the highest birth weight category, no associations were found. Higher adherence to a healthy Nordic diet was associated with lower SBP and PP in individuals with low birth weight but with higher SBP and PP in those with average birth weight.

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Fig. 1: Selection of the participants of the present study from the original cohort of Helsinki Birth Cohort Study.
Fig. 2: Systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), and mean arterial pressure (MAP) at follow-up (2011-2013) in thirds of Baltic sea diet score (2001–2004) (T1, T2, and T3) by birth weight categories (birth weight I: <2951 g in women, <3061 g in men; birth weight II: 2951 – 3810 g in women, 3061-3959 g in men; and birth weight III: > 3810 in women, > 3959 g in men) as well as p values for an interaction term BSDS × birth weight, and main effects of BSDS in each birth weight category.

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The dataset and code supporting the conclusions of this article is available upon a reasonable request from the authors.

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Funding

This study was supported by grants from Finska Läkaresällskapet, the Finnish Special Governmental Subsidy for Health Sciences, Academy of Finland (127437, 129306, 130326, 134791, 263924, and 315690), Samfundet Folkhälsan, Liv och Hälsa, EU FP7 [Developmental Origins of Healthy Aging (DORIAN)] project number 278603, and EU H2020-PHC-2014-DynaHealth grant 633595, Horizon2020 award No. 733206 LifeCycle. (all for the Helsinki Birth Cohort Study), European Commission, Horizon2020 award 733280 RECAP), Foundation for Cardiovascular Research, Foundation for Diabetes Research, Foundation for Pediatric Research, Novo Nordisk Foundation, Signe and Ane Gyllenberg Foundation, Sigrid Jusélius Foundation.

Author information

Authors and Affiliations

  1. Folkhälsan Research Center, Helsinki, Finland

    Jelena Meinilä, Mia-Maria Perälä, Minna Salonen & Johan Gunnar Eriksson

  2. Department of Gynecology and Obstetrics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

    Jelena Meinilä

  3. Department of Public Health, University of Helsinki, Helsinki, Finland

    Noora Kanerva

  4. Public Health Promotion Unit, National Institute for Health and Welfare, Helsinki, Finland

    Satu Männistö

  5. Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

    Niko Wasenius & Johan Gunnar Eriksson

  6. Public Health Promotion Unit, National Institute for Health and Welfare, Oulu, Finland

    Eero Kajantie

  7. PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland

    Eero Kajantie

  8. Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway

    Eero Kajantie

  9. Children’s Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland

    Eero Kajantie

  10. Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Johan Gunnar Eriksson

  11. Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research A*STAR, Singapore, Singapore

    Johan Gunnar Eriksson

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  1. Jelena Meinilä
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Supplementary information

41371_2020_423_MOESM1_ESM.docx

Supplemental Table S1. Coefficient, 95% CI, and p-values for missingness of use of blood pressure affecting medication data at follow-up (2011-2013) (0=data not missing/1=data missing) by one unit increase in a given variable (n=955).

41371_2020_423_MOESM2_ESM.docx

Supplemental Table S2. Coefficient, 95% CI, and p-values for missingness of maternal pre-delivery BMI data (1=missing data/0=data not missing) by one unit increase of a given variable (n=955).

41371_2020_423_MOESM3_ESM.docx

Supplemental Figure S3. Proportions of observed (n=823), imputed (n=137), and completed (n=960) values of blood pressure affecting medication use at follow-up (0 = data not missing, 1 = data missing) in each 10 imputed datasets. Multiple imputation (10 imputations) with logistic regression model included covariates age, sex, educational attainment, gestational age, smoking, leisure-time physical activity, BMI, weight change during follow-up, energy intake, Baltic sea diet score, sodium intake, use of blood-pressure affecting medication at baseline, household income, systolic blood pressure at baseline and at follow-up, diastolic blood pressure at baseline and at follow-up, and maternal pre-pregnancy BMI.

41371_2020_423_MOESM4_ESM.docx

Supplemental Figure S4. Proportions of observed (n=842), imputed (n=137), and completed (n=960) values of maternal pre-delivery BMI (0 = data not missing, 1 = data missing) in each 10 imputed datasets. Multiple imputations (10 imputations) with regression model included covariates age, sex, educational attainment, gestational age, smoking, leisure-time physical activity, BMI, weight change during follow-up, energy intake, Baltic sea diet score, sodium intake, use of blood-pressure affecting medication at baseline, household income, systolic blood pressure at baseline and at follow-up, diastolic blood pressure at baseline and at follow-up, and blood pressure affecting medication use during follow-up.

41371_2020_423_MOESM5_ESM.docx

Supplemental Table S5. F-values (df1, df2) and p-values for interaction between birth weight and Baltic sea diet score on blood pressure parameters at baseline (2001-2003).

41371_2020_423_MOESM6_ESM.docx

Supplemental Table S6. Association between baseline BSDS and blood pressure parameters at follow-up by BW in observed cases and completed cases (multiple imputation). F-values (f1, df2) and p-values for interaction term (BW x BSDS) on blood pressure parameters and predicted blood pressure parameters in thirds of Baltic sea diet score by birth weight.

41371_2020_423_MOESM7_ESM.docx

Supplemental Table S7. Regression coefficients and their 95 % confidence intervals for the association between BSDS components at baseline and systolic blood pressure and pulse pressure in 10-year follow-up.

41371_2020_423_MOESM8_ESM.docx

Supplemental Figure S8. Linear predictions of systolic blood pressure across birth weight deciles in thirds of the Baltic sea diet score. BSDS, Baltic sea diet score.

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Meinilä, J., Perälä, MM., Kanerva, N. et al. Birth weight modifies the association between a healthy Nordic diet and office blood pressure in old age. J Hum Hypertens 35, 849–858 (2021). https://doi.org/10.1038/s41371-020-00423-1

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