Does pregnancy alter life-course lipid trajectories? Evidence from the HUNT Study in Norway
2018; Elsevier BV; Volume: 59; Issue: 12 Linguagem: Inglês
10.1194/jlr.p085720
ISSN1539-7262
AutoresAmanda R. Markovitz, Eirin B. Haug, Julie Horn, Abigail Fraser, Corrie Macdonald‐Wallis, Kate Tilling, Eric B. Rimm, Stacey A. Missmer, Paige L. Williams, Pål Romundstad, Bjørn Olav Åsvold, Janet W. Rich‐Edwards,
Tópico(s)Fatty Acid Research and Health
ResumoWe examined the association between pregnancy and life-course lipid trajectories. Linked data from the Nord-Trøndelag Health Study and the Medical Birth Registry of Norway yielded 19,987 parous and 1,625 nulliparous women. Using mixed-effects spline models, we estimated differences in nonfasting lipid levels from before to after first birth in parous women and between parous and nulliparous women. HDL cholesterol (HDL-C) dropped by −4.2 mg/dl (95% CI: −5.0, −3.3) from before to after first birth in adjusted models, a 7% change, and the total cholesterol (TC) to HDL-C ratio increased by 0.18 (95% CI: 0.11, 0.25), with no change in non-HDL-C or triglycerides. Changes in HDL-C and the TC/HDL-C ratio associated with pregnancy persisted for decades, leading to altered life-course lipid trajectories. For example, parous women had a lower HDL-C than nulliparous women at the age of 50 years (−1.4 mg/dl; 95% CI: −2.3, −0.4). Adverse changes in lipids were greatest after first birth, with small changes after subsequent births, and were larger in women who did not breastfeed. Findings suggest that pregnancy is associated with long-lasting adverse changes in HDL-C, potentially setting parous women on a more atherogenic trajectory than prior to pregnancy. We examined the association between pregnancy and life-course lipid trajectories. Linked data from the Nord-Trøndelag Health Study and the Medical Birth Registry of Norway yielded 19,987 parous and 1,625 nulliparous women. Using mixed-effects spline models, we estimated differences in nonfasting lipid levels from before to after first birth in parous women and between parous and nulliparous women. HDL cholesterol (HDL-C) dropped by −4.2 mg/dl (95% CI: −5.0, −3.3) from before to after first birth in adjusted models, a 7% change, and the total cholesterol (TC) to HDL-C ratio increased by 0.18 (95% CI: 0.11, 0.25), with no change in non-HDL-C or triglycerides. Changes in HDL-C and the TC/HDL-C ratio associated with pregnancy persisted for decades, leading to altered life-course lipid trajectories. For example, parous women had a lower HDL-C than nulliparous women at the age of 50 years (−1.4 mg/dl; 95% CI: −2.3, −0.4). Adverse changes in lipids were greatest after first birth, with small changes after subsequent births, and were larger in women who did not breastfeed. Findings suggest that pregnancy is associated with long-lasting adverse changes in HDL-C, potentially setting parous women on a more atherogenic trajectory than prior to pregnancy. Lipids predict future CVD (1.Di Angelantonio E. Sarwar N. Perry P. Kaptoge S. Ray K.K. Thompson A. Wood A.M. Lewington S. Sattar N. Packard C.J. Major lipids, apolipoproteins, and risk of vascular disease.JAMA. 2009; 302: 1993-2000Crossref PubMed Scopus (1979) Google Scholar). 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Hudes M. Daniels S. Biro F.M. Crawford P.B. Pregnancy during adolescence has lasting adverse effects on blood lipids: a 10-year longitudinal study of black and white females.J. Clin. Lipidol. 2012; 6: 139-149Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar, 8.van Stiphout W.A. Hofman A. Bruijn A.M.D. Serum lipids in young women before, during, and after pregnancy.Am. J. Epidemiol. 1987; 126: 922-928Crossref PubMed Scopus (74) Google Scholar, 10.Skilton M.R. Bonnet F. Begg L.M. Juonala M. Kähönen M. Lehtimäki T. Viikari J.S.A. Raitakari O.T. Childbearing, child-rearing, cardiovascular risk factors, and progression of carotid intima-media thickness.Stroke. 2010; 41: 1332-1337Crossref PubMed Scopus (24) Google Scholar). If adverse changes in lipids continue into midlife and beyond, it could provide insight into the early origins of subclinical CVD risk in women. In addition, few previous studies were able to characterize how lipid levels changed with time since pregnancy. Furthermore, few studies have considered breastfeeding as part of the peripartum year. Lactation is a modifiable factor that might minimize adverse changes in lipids postpartum and is associated with higher HDL-C levels (11.Knopp R.H. Walden C.E. Wahl P.W. Bergelin R. Chapman M. Irvine S. Albers J.J. Effect of postpartum lactation on lipoprotein lipids and apoproteins.J. Clin. Endocrinol. Metab. 1985; 60: 542-547Crossref PubMed Scopus (52) Google Scholar, 12.Erkkola R. Viikari J. Irjala K. Solakivi-Jaakkola T. One-year follow-up of lipoprotein metabolism after pregnancy.Biol. Res. Pregnancy Perinatol. 1986; 7: 47-51PubMed Google Scholar, 13.Kallio M.J. Siimes M.A. Perheentupa J. Salmenperä L. Miettinen T.A. 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Whitmer R.A. Quesenberry C.P. Sidney S. Lactation and changes in maternal metabolic risk factors.Obstet. Gynecol. 2007; 109: 729-738Crossref PubMed Scopus (110) Google Scholar). The population-based Nord-Trøndelag Health Study (HUNT), linked with the Medical Birth Registry of Norway, includes data on pregnancy, breastfeeding, and measured lipid values in women from before and up to 41 years after first birth, enabling an examination of changes in lipid levels pre- to postpregnancy. These data enable us to examine, for the first time, the impact of pregnancy on the ratio of TC to HDL-C, which performs as well as or better than other lipid measures in CVD risk prediction (18.Manickam P. Rathod A. Panaich S. Hari P. Veeranna V. Badheka A. Jacob S. Afonso L. Comparative prognostic utility of conventional and novel lipid parameters for cardiovascular disease risk prediction: do novel lipid parameters offer an advantage?.J. Clin. 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Med. 2003; 25: 50-57Abstract Full Text Full Text PDF PubMed Scopus (123) Google Scholar). Using these data, we investigated the association of first birth with short- and long-term changes in lipid levels. We also examined the impact of later births on lipid levels. Finally, we investigated the extent to which these changes differed by breastfeeding length. HUNT is a population-based open cohort study of adult Nord-Trøndelag county residents designed for a wide range of health-related research. County-wide surveys are conducted roughly every decade, with three completed at the time of this analysis. This analysis was restricted to the second and third surveys in which lipids were sampled: HUNT2 (1995–1997) and HUNT3 (2006–2008). During the surveys, participants received an extensive health assessment that included blood sampling, clinical measurements, and questionnaires (25.Krokstad S. Langhammer A. Hveem K. Holmen T.L. Midthjell K. Stene T.R. Bratberg G. Heggland J. Holmen J. Cohort profile: the HUNT Study, Norway.Int. J. Epidemiol. 2013; 42: 968-977Crossref PubMed Scopus (722) Google Scholar). All current county residents aged 20 years or older identified from the national population register were invited to participate in each survey, with participation rates among women of 76% in HUNT2 (26.Holmen J. Midthjell K. Krüger Ø. Langhammer A. Holmen T.L. Bratberg G.H. Vatten L. Lund-Larsen P.G. The Nord-Trøndelag Health Study 1995–97 (HUNT 2): Objectives, contents, methods and participation.Nor. Epidemiol. 2003; 13: 19-32Google Scholar) and 59% in HUNT3 (25.Krokstad S. Langhammer A. Hveem K. Holmen T.L. Midthjell K. Stene T.R. Bratberg G. Heggland J. Holmen J. Cohort profile: the HUNT Study, Norway.Int. J. Epidemiol. 2013; 42: 968-977Crossref PubMed Scopus (722) Google Scholar). Residents of Nord-Trøndelag county are predominantly white and generally representative of Norway as a whole (26.Holmen J. Midthjell K. Krüger Ø. Langhammer A. Holmen T.L. Bratberg G.H. Vatten L. Lund-Larsen P.G. The Nord-Trøndelag Health Study 1995–97 (HUNT 2): Objectives, contents, methods and participation.Nor. Epidemiol. 2003; 13: 19-32Google Scholar). We linked HUNT data to the Medical Birth Registry of Norway, which includes all births in Norway from 1967 (27.Irgens L.M. The Medical Birth Registry of Norway. Epidemiological research and surveillance throughout 30 years.Acta Obstet. Gynecol. Scand. 2000; 79: 435-439Crossref PubMed Google Scholar) through the end of our data collection in 2012. Because older women were unlikely to have their pregnancy history captured in this registry, we restricted analyses to women aged 20–60 years during lipid measurement. Figure 1 outlines the process of identifying two overlapping study populations. The first included parous and nulliparous women with similar age distributions to compare lipids trajectories between the two groups. The second included parous women to compare lipids before and after first birth. For the first population, we excluded women born before 1940 or after 1974 to prevent misclassification of women as nulliparous who had a birth before the birth registry started in 1967 or after the end of data collection in 2012. We applied this exclusion to parous women to achieve a comparable age distribution. For the second population of only parous women, we did not restrict based on birth year. All participants in HUNT signed an informed consent form allowing the use of their data and samples for research. This project was approved by the Central Norway Regional Committee for Medical and Health Research Ethics and was considered exempt from institutional review board review by the Harvard T. H. Chan School of Public Health. This study abides by the Declaration of Helsinki principles. Participants' ages ranged from 20 to 60 years during measurements. Among parous women, 2,488 women had at least 1 measurement before their first birth (with a total of 2,521 prepregnancy observations), including 747 women with measurements both before and after first birth (supplemental Fig. S1). Nonfasting lipids were measured from serum samples. For technical details about TC, HDL-C, and triglyceride measurements, see supplemental Table S1. We calculated non-HDL-C as TC minus HDL-C and the TC/HDL-C ratio. LDL cholesterol (LDL-C) was not analyzed because the Friedewald formula (28.Friedewald W.T. Levy R.I. Fredrickson D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.Clin. Chem. 1972; 18: 499-502Crossref PubMed Scopus (64) Google Scholar), typically used to calculate LDL-C, performs poorly in nonfasting samples (29.Scharnagl H. Nauck M. Wieland H. März W. The Friedewald formula underestimates LDL cholesterol at low concentrations.Clin. Chem. Lab. Med. 2001; 39: 426-431Crossref PubMed Scopus (114) Google Scholar, 30.Jun K.R. Park H-I. Chun S. Park H. Min W-K. Effects of total cholesterol and triglyceride on the percentage difference between the low-density lipoprotein cholesterol concentration measured directly and calculated using the Friedewald formula.Clin. Chem. Lab. Med. 2008; 46: 371-375Crossref PubMed Scopus (43) Google Scholar, 31.Lindsey C.C. Graham M.R. Johnston T.P. Kiroff C.G. Freshley A. A clinical comparison of calculated versus direct measurement of low-density lipoprotein cholesterol level.Pharmacotherapy. 2004; 24: 167-172Crossref PubMed Scopus (40) Google Scholar). At the time of lipid measurements, staff recorded the time since last meal in hour categories. Covariates were collected during HUNT surveys and were selected based on the causal diagram shown in supplemental Fig. S2. We used data from all HUNT questionnaires, including HUNT1 (1984–1986), to identify the following time-invariant covariates: 1) family history of CVD (any reported myocardial infarction or angina pectoris in siblings or parents); 2) smoking status at the age of 20 years, defined as ever versus never smoked daily prior to or at the age of 20 years, to approximate prepregnancy smoking behavior for parous women; and 3) highest obtained education level. HUNT3 did not collect education level and was instead derived from work titles for 13% of women based on recommendations from Statistics Norway (32.Statistics Norway.Standard classification of occupations. 1998; Google Scholar). We also included the following time-varying, or updated, covariates: 1) BMI, 2) smoking status, 3) alcohol use, 4) vigorous leisure-time physical activity, and 5) oral contraceptive use. Time-varying covariates were measured at the time of lipid assessment either from HUNT2 and HUNT3 clinical examinations (in the case of BMI) or HUNT2 and HUNT3 questionnaires (for all other covariates). We obtained additional information about first births, including maternal age and preterm status (<37 weeks gestation), from the birth registry and breastfeeding length after first birth (self-reported as 0, 6 months) from HUNT questionnaires. We additionally obtained self-reported information about menopause transition and hormone replacement therapy (never, previous, or current user) from HUNT questionnaires. We used linear mixed-effects models to estimate lipid trajectories as a function of age, accounting for the timing of a woman's first birth. Age was modeled using restricted cubic splines with four knots located at ages 23, 37, 46, and 57 years based on prespecified quantiles of the age distribution, as recommended by Harrell (33.Harrell, F. E., 2010. Springer, New York.Google Scholar). Two variables were used to estimate the effect of pregnancy. The first indicated whether measurement preceded or followed the first birth, providing an estimate of short-term change in lipids after first birth. The second indicated continuous time since first birth, providing an estimate of longer-term change in lipids postpartum. All models controlled for the participant's age at measurement, HUNT survey (HUNT2 vs. HUNT3), time since last meal, education, smoking initiation by the age of 20 years, and family history of CVD. First, we compared life-course lipid trajectories for parous and nulliparous women based on completed reproductive history. In this analysis (see supplemental Methods section 1), nulliparous women represented background age and secular trends independent of parity. These analyses included an indicator of final parity status (i.e., none vs. one or more births; covariate Pi in supplemental Methods equation 1) and an interaction between parity and the spline terms, allowing the age-related splines to differ throughout the life course based on final parity status. We chose final rather than updated parity status because nulliparous and parous women are likely to be different even before the latter give birth, given observed associations between infertility and lipid levels (34.Kim J.J. Choi Y.M. Dyslipidemia in women with polycystic ovary syndrome.Obstet. Gynecol. Sci. 2013; 56: 137-142Crossref PubMed Google Scholar, 35.Mahalingaiah S. Sun F. Cheng J.J. Chow E.T. Lunetta K.L. Murabito J.M. Cardiovascular risk factors among women with self-reported infertility.Fertil. Res. Pract. 2017; 3: 7Crossref PubMed Google Scholar). For these and other analyses controlling only for baseline covariates, we used a complete case analysis, excluding participants with missing data on education (0.6%) or smoking (2.5%). To present the trajectories graphically, predicted lipid trajectories were derived for hypothetical nulliparous women and parous women with a first birth occurring at the age of 23 years (the median age at first birth in the study population), setting all other covariates to their mean levels. Second, we used the same mixed-effects spline models among parous women (study population 2) to obtain estimates of the short-term effect of the first birth on lipid levels and to describe differences in this effect estimate by length of breastfeeding (supplemental Methods section 2). The short-term effect of the first birth was estimated based on the discontinuity between predicted trajectories before first birth and predicted trajectories after first birth (captured by the coefficient Iij in supplemental Methods equation 2). Fully adjusted results from these models included updated BMI, alcohol use, physical activity, and oral contraceptive use as well as maternal age and preterm status of first birth. Both baseline and updated covariates were multiply imputed using fully conditional specification (36.van Buuren S. Multiple imputation of discrete and continuous data by fully conditional specification.Stat. Methods Med. Res. 2007; 16: 219-242Crossref PubMed Scopus (1746) Google Scholar) with 25 iterations. Models investigating whether breastfeeding length moderated the change in lipid levels from before to after first birth included distinct indicator terms for the postpartum versus prepartum effect based on breastfeeding length. Approximately 99% of lipid measurements informing after first birth trends in our analysis occurred after breastfeeding ended; thus, the before versus after first birth effect we estimated would include changes associated with breastfeeding. We used F-tests to determine whether the postpartum versus prepartum effect differed by breastfeeding length (37.Li K-H. Meng X-L. Raghunathan T.E. Rubin D.B. Significance levels from repeated p-values with multiply-imputed data.Stat. Sin. 1991; 1: 65-92Google Scholar). Finally, we investigated the change in lipids after second and third births among women with multiple births. We performed sensitivity analyses among women with measurements at both HUNT2 and HUNT3 (47% of women) to verify that our main results, which included some women with only one measurement, were consistent with within-woman changes in lipids observed among women with more than one lipid measurement. First, we replicated the lipid trajectory models among women with repeated measures to verify that our results could be interpreted as within-woman life-course trajectories. Second, we compared the within-woman change in lipid levels from HUNT2 to HUNT3 for women who had one or more births during the ∼11 year interval to the within-woman lipid changes for women who remained nulliparous during the interval using a difference-in-differences approach (38.Imbens G.W. Wooldridge J.M. Recent developments in the econometrics of program evaluation.J. Econ. Lit. 2009; 47: 5-86Crossref Scopus (2274) Google Scholar). We additionally performed sensitivity analyses controlling for menopause transition and hormone replacement therapy to see whether this differentially affected life-course lipid trajectories for parous compared with nulliparous women. All analyses were performed using Stata IC 13 (StataCorp, College Station, TX) and MLwiN (39.Rasbash J. Charlton C. Browne W.J. Healy M. Cameron B. MLwiN Ver. 2.34.Centre for Multilevel Modelling, University of Bristol Bristol. 2009; Google Scholar) version 2.34. Among 21,312 study participants born between 1940 and 1974 (study population 1), 8% were nulliparous throughout the follow-up period, at which point the youngest were 38 years old. Nulliparous and parous women had similar age distributions, but nulliparous women were less likely to smoke or consume alcohol and more likely to participate in vigorous physical activity (Table 1). Nulliparous women were slightly more likely to be obese and had greater levels of nonparticipation and missing data.TABLE 1Description of covariates at the individual and observational level based on final parity status among HUNT2 and HUNT3 study participants born between 1940 and 1974 (n = 21,312 women)Final Parity StatusNulliparousParousWomen (n)1,62519,687Birth year [median (IQR)]1959 (1951–1967)1958 (1951–1966)Smoking status at the age of 20 years [n (%)]Never smoked daily919 (57)9,043 (46)Ever smoked daily653 (40)10,166 (52)Not reported53 (3)478 (2)Education [n (%)]Lower secondary309 (19)3,164 (16)Upper secondary672 (41)9,185 (47)Tertiary604 (37)7,244 (37)Missing40 (2)94 (0)Family history of CVD [n (%)]504 (31)6,611 (34)HUNT exam participation [n (%)]Only HUNT2751 (46)6,827 (35)Only HUNT3288 (18)3,333 (17)Both HUNT2 and 3586 (36)9,527 (48)Age in years at first birth [median (IQR)]N/A23 (20–26)Births [n (%)]1N/A2,171 (11)2N/A8,804 (45)≥3N/A8,712 (44)Breastfeeding length of first birth [n (%)]Did not breastfeedN/A1,120 (6) 6 monthsN/A7,462 (38)MissingN/A2,516 (13)Preterm first birth [n (%)]N/A1,187 (6)Observations aObservations reflect HUNT survey periods. Individual women who participated in both HUNT2 and HUNT3 contributed two observations. (n)3,32931,743BMI at HUNT exam [n (%)]<25 kg/m21,674 (50)15,728 (50)25–29.9 kg/m2963 (29)10,826 (34)≥30 kg/m2665 (20)5,136 (16)Not available27 (1)53 (0)Alcohol consumption [n (%)]<1 glasses per 2 weeks1,162 (35)9,277 (29)1–4 glasses per 2 weeks1,167 (35)14,797 (47)≥5 glasses per 2 weeks932 (28)7,221 (23)Missing68 (2)448 (1)Vigorous physical activity [n (%)]<1 h per week1,669 (50)18,327 (58)≥1 h per week1,183 (36)9,921 (31)Missing477 (14)3,495 (11)Oral contraceptive use [n (%)]Nonuser2,024 (61)22,716 (72)Current user564 (17)2,961 (9)Missing741 (22)6,066 (19)a Observations reflect HUNT survey periods. Individual women who participated in both HUNT2 and HUNT3 contributed two observations. Open table in a new tab Predicted life-course lipid trajectories, based on multivariable models, suggested higher HDL-C levels among parous women before first birth compared with nulliparous women (Fig. 2A), with a difference of 2.0 mg/dl (95% CI: −0.1, 4.2) at the age of 20 years (Table 2). However, the HDL-C levels of parous women dropped at first pregnancy and thereafter were lower or equal to those of nulliparous women (Table 2). HDL-C in parous women after their first birth never returned to the same level
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