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eFigure 2. Average annual percent change of mortality rates due to hypertensive heart disease by states, 2000-15 eFigure 3. County-level (A) age-standardized hypertensive heart disease mortality rates, 2012-2015; (B) average annual percent change of hypertensive heart disease mortality rates, 2000-2015, and (C) multivariate quasi-Poisson regression by county-level risk factors 2012-15 eTable 1. Trends and age-standardized premature mortality (age 25-64 years) rates due to specific cardiovascular disease in the US, 2000-03 compared to 2012-15, rates per 100,000 eTable 2. Relative risk and 95% confidence intervals for county-level CVD premature mortality by country-level risk factors, adjusting for age and all five county-level risk factors, 2012-15 eTable 3. Relative risk and 95% confidence intervals (CI) for county-level premature mortality due to hypertensive heart disease by county-level risk factors, adjusting for age and all five county-level risk factors, 2012-15 Click here for additional data file.

Introduction Women with history of hypertensive disorders of pregnancy (HDP) have approximately a 2-fold increased risk of cardiovascular disease (CVD) compared with women with normotensive pregnancies. Hypertensive disorders of pregnancy and CVD share common modifiable risk factors, such as adiposity, hypertension, dyslipidemia, and hyperglycemia, that may be targets for prevention. In 2018, we observed that women with HDP already had more adiposity, higher blood pressure and glucose levels, and more adverse lipid levels before first pregnancy and that their cardiovascular risk factor levels remained higher than women without HDP through age 50 years and beyond. It is not known how much of the excess CVD risk in women with history of HDP is associated with these risk factors vs how much may be caused by HDP itself or other unidentified factors. This knowledge is crucial to inform preventive action in women with a history of HDP. In a population-based cohort with longitudinal information on cardiovascular risk factors and validated information on cardiovascular events, we used mediation analysis to examine how much of the excess cardiovascular risk in women with a history of HDP is associated with adverse levels of body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), blood pressure, and glucose and lipid levels.

ation on cardiovascular events, we used mediation analysis to examine how much of the excess cardiovascular risk in women with a history of HDP is associated with adverse levels of body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), blood pressure, and glucose and lipid levels. Methods All procedures performed in studies involving human participants were in accordance with the ethical standards of the Regional Committee for Medical and Health Research Ethics and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The Regional Committee for Medical and Health Research Ethics granted ethical approval of the study. In the initial Nord-Trøndelag Health Study (HUNT1), attendance and participation in questionnaires and clinical examination was considered as informed consent, and in HUNT2 and HUNT3, participants gave written consent. Study Population This study included 23 885 parous women participating in the HUNT in Norway. Using the unique identification number of all Norwegian citizens, we linked information from HUNT (1984-2008), the Medical Birth Registry of Norway (MBRN, 1967-2012), the Norwegian Cause of Death Registry (1984-2015), and validated cardiovascular events from the local hospitals (1987-2015). This linked data resource has previously been used to examine the added value of pregnancy complications in clinical CVD risk prediction. See the eAppendix and eFigure in the Supplement for a description of the sample selection and an overview of the study timeline with associated data sources.

l hospitals (1987-2015). This linked data resource has previously been used to examine the added value of pregnancy complications in clinical CVD risk prediction. See the eAppendix and eFigure in the Supplement for a description of the sample selection and an overview of the study timeline with associated data sources. Exposure and Covariates Exposure was defined as history of HDP (ever HDP) in the form of preeclampsia or gestational hypertension at 40 years or younger. Additionally, we subclassified the exposure as ever preeclampsia (with or without a history of gestational hypertension) and ever gestational hypertension (but no history of preeclampsia) at 40 years or younger. Details about the diagnoses of preeclampsia and gestational hypertension in the MBRN and their validity are presented in the eAppendix of the Supplement. We retrieved information about age at HUNT examination, self-reported ever daily smoking, highest obtained educational level, work titles, current use of antihypertensive medication, and family history of coronary heart disease (in sibling or parents) from the HUNT survey questionnaires and interviews. For 3530 women for whom educational level was not available, we deduced highest obtained educational level from their work titles based on recommendations from Statistics Norway. The MBRN provided information on mother’s age at birth and parity.

in sibling or parents) from the HUNT survey questionnaires and interviews. For 3530 women for whom educational level was not available, we deduced highest obtained educational level from their work titles based on recommendations from Statistics Norway. The MBRN provided information on mother’s age at birth and parity. Cardiovascular Risk Factors Information about the most recently measured cardiovascular risk factors prior to the cardiovascular event or censoring was obtained from clinical measurements and serum samples collected at HUNT examinations. Details about the cardiovascular risk factors measurements have been reported previously and are included in the eAppendix of the Supplement.

ntly measured cardiovascular risk factors prior to the cardiovascular event or censoring was obtained from clinical measurements and serum samples collected at HUNT examinations. Details about the cardiovascular risk factors measurements have been reported previously and are included in the eAppendix of the Supplement. Cardiovascular Events To obtain information about hospital-diagnosed cardiovascular events, medical records were retrieved for all study participants who had at least 1 record with an International Classification of Diseases, Ninth Revision (ICD-9) and/or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code indicating CVD in the electronic patient administrative systems of the 2 local hospitals serving Nord-Trøndelag county between September 1, 1987, and April 24, 2015. All medical records were reviewed by 1 of 2 cardiologists (B.K. and H.D.) who, according to established criteria, confirmed any valid cardiovascular diagnoses. Additional details about the diagnoses and validation are presented in the eAppendix of the Supplement. We also obtained information on dates and causes of death up until April 24, 2015, from the Norwegian Cause of Death Registry, which has recorded all deaths in Norway since 1951. Cardiovascular disease–related deaths were identified using ICD-9 and ICD-10 codes for the underlying cause of death (eTable 1 in the Supplement).

so obtained information on dates and causes of death up until April 24, 2015, from the Norwegian Cause of Death Registry, which has recorded all deaths in Norway since 1951. Cardiovascular disease–related deaths were identified using ICD-9 and ICD-10 codes for the underlying cause of death (eTable 1 in the Supplement). Statistical Analysis We used Cox proportional hazards models to estimate the hazard ratios (HRs) for first-time cardiovascular events (fatal or nonfatal) and, specifically, first-time myocardial infarction, heart failure, and cerebrovascular events, comparing women with and without a history of HDP. We used age as the time scale, and women entered the study on September 1, 1987, their first HUNT examination, or age 40 years, whichever came last. Women were followed up until the cardiovascular event of interest, emigration from Nord-Trøndelag county, death, or April 24, 2015, whichever came first. Hazard ratios were adjusted for age (model 1) and adjusted for age, maternal birth year, highest educational level, ever daily smoking, parity before age 40 years, and family history of coronary heart disease in sibling or parents (model 2). To assess the effect of death from causes other than CVD as a competing risk, subdistribution HRs were also estimated using Fine and Gray competing risk model. The Cox proportional hazards assumption was assessed by including interactions between independent variables and time. Violations of the Cox proportional hazards assumption were handled by estimating HRs within separate age intervals in which the assumption was met.

o estimated using Fine and Gray competing risk model. The Cox proportional hazards assumption was assessed by including interactions between independent variables and time. Violations of the Cox proportional hazards assumption were handled by estimating HRs within separate age intervals in which the assumption was met. In secondary analyses, we included only women whose first birth was recorded in the MBRN to avoid potential misclassification of women as normotensive who had earlier pregnancies not captured by the MBRN. Additionally, to avoid missing too many early cardiovascular events at younger than 40 years and owing to the complex association between parity and HDP, we examined HDP in first pregnancy as an exposure, starting exposure time at whichever came last: first birth, first HUNT participation, or September 1, 1987. In these analyses we additionally adjusted for mother’s age at first birth. Finally, because information on CVD subtypes in the Cause of Death Registry may have lower validity, we repeated the analyses using validated myocardial infarction, heart failure, and cerebrovascular events from the hospital records only.

1987. In these analyses we additionally adjusted for mother’s age at first birth. Finally, because information on CVD subtypes in the Cause of Death Registry may have lower validity, we repeated the analyses using validated myocardial infarction, heart failure, and cerebrovascular events from the hospital records only. Analogously to the study by Tanz et al, we have used a mediation approach to estimate the proportion of excess CVD risk in women with a history of HDP that is associated with conventional cardiovascular risk factors. Mediation analysis enables a decomposition of the association between exposure and outcome (called total effect) into a natural direct effect from exposure on outcome and a natural indirect effect from exposure on outcome through mediators. In our analysis, the natural indirect effect is best interpreted as the proportion of excess cardiovascular risk in women with history of HDP that is associated with conventional cardiovascular risk factors (mediators), while the natural direct effect is best understood as the proportion of excess cardiovascular risk in women who had HDP that is not associated with these factors. We estimated the part of the association between HDP and CVD that was associated with BMI, systolic and diastolic blood pressure, nonfasting serum glucose levels, and non–high-density lipoprotein (HDL) cholesterol levels (indirect effect) and the part that was not associated with these factors (direct effect) using an inverse odds ratio weighting mediation analysis method. A graphic and more detailed explanation of this mediation analysis is given in the Figure. Separate analyses were performed for each mediator and for the combination of BMI and blood pressure. In the mediation analysis, we additionally adjusted for the age at measurement of the mediator. Additionally, separate mediation analyses were conducted for preeclampsia and gestational hypertension as well as for CVD subtypes (myocardial infarction, heart failure, and cerebrovascular events). Mediators may have been measured before (maximum of 484 women [2%]) or after pregnancies complicated by HDP, but because we do not postulate the association between HDP and CVD to be causal and because the differences in cardiovascular risk factors between women with and without HDP are largely similar prepregnancy vs postpregnancy and throughout the age range from 20 years to older than 50 years in this study population, the timing of mediator measurement was less relevant.

tween HDP and CVD to be causal and because the differences in cardiovascular risk factors between women with and without HDP are largely similar prepregnancy vs postpregnancy and throughout the age range from 20 years to older than 50 years in this study population, the timing of mediator measurement was less relevant. In 2 separate sensitivity analyses, we excluded women who had their cardiovascular risk factors measured before their first pregnancy and restricted the mediation analysis to women who had mediators measured at older than 40 years, the time where we ended exposure follow-up. All analyses were performed using Stata IC, version 14 (StataCorp). The P value was 2-sided, and the level of statistical significance was .05.

sured before their first pregnancy and restricted the mediation analysis to women who had mediators measured at older than 40 years, the time where we ended exposure follow-up. All analyses were performed using Stata IC, version 14 (StataCorp). The P value was 2-sided, and the level of statistical significance was .05. Figure. Mediation Analysis Diagram of associations between hypertensive disorders of pregnancy (HDP); cardiovascular risk factors in the form of body mass index (BMI), blood pressure, and glucose and non–high-density lipoprotein (HDL) cholesterol levels; and cardiovascular disease. The dark blue arrows indicate proportion of excess cardiovascular risk in women with HDP that is associated with BMI, blood pressure, and glucose and non-HDL cholesterol levels (indirect effect). The blue arrows indicate proportion of excess cardiovascular risk in women with HDP that is not associated with BMI, blood pressure, and glucose and non-HDL cholesterol levels (direct effect). The light blue arrows indicate confounding of the association between HDP and cardiovascular disease and that between cardiovascular risk factors and cardiovascular disease by socioeconomic status, smoking, family history of coronary heart disease, parity at younger than 40 years, and maternal birth year.

rect effect). The light blue arrows indicate confounding of the association between HDP and cardiovascular disease and that between cardiovascular risk factors and cardiovascular disease by socioeconomic status, smoking, family history of coronary heart disease, parity at younger than 40 years, and maternal birth year. Results Of 23 885 women, 2119 (9%) had a history of HDP at younger than 40 years; 1391 had at least 1 occurrence of preeclampsia; and 728 experienced gestational hypertension only (Table 1). Women with history of HDP were less likely to report daily smoking and more likely to have first births captured by the MBRN than women with normotensive pregnancies (eTable 2 in the Supplement). The median ages at measurement of the cardiovascular risk factors included in the mediation analysis were 50 years for women with only normotensive pregnancies and 48 years for women with a history of HDP. Pregnancies complicated by HDP were more likely to result in preterm delivery or offspring born small for gestational age (eTable 2 in the Supplement). During a median follow-up of 18 years, 1688 women experienced at least 1 cardiovascular event, and 1565 (92.7%) had a cardiovascular event validated from hospital records. Five hundred fifty-three of 1688 women with cardiovascular events experienced a myocardial infarction, 233 had heart failure, and 878 experienced a cerebrovascular event.

-up of 18 years, 1688 women experienced at least 1 cardiovascular event, and 1565 (92.7%) had a cardiovascular event validated from hospital records. Five hundred fifty-three of 1688 women with cardiovascular events experienced a myocardial infarction, 233 had heart failure, and 878 experienced a cerebrovascular event. Table 1. Descriptive Characteristics of the Study Population Maternal Characteristic Pregnancy Status, No. (%)a Always Normotensive (n = 21 766) Ever Hypertensive Disorder (n = 2119) Gestational Hypertension Only (n = 728) Ever Preeclampsia (n = 1391) Birth y, median (IQR) 1954 (1946-1962) 1955 (1948-1963) 1953 (1946-1960) 1957 (1949-1964) Age at first birth, y 24 (21-27) 23 (21-27) 23 (21-27) 24 (21-27) Parity at younger than 40 y 1 4907 (23) 323 (15) 113 (16) 210 (15) 2 9149 (42) 887 (42) 300 (41) 587 (42) ≥3 7710 (35) 909 (43) 315 (43) 594 (43) First birth recorded in the MBRN No 4190 (19) 214 (10) 113 (16) 101 (7) Yes 17576 (81) 1905 (90) 615 (84) 1290 (93) Family history of coronary heart disease No 13991 (64) 1328 (63) 456 (63) 872 (63) Yes 7775 (36) 791 (37) 272 (37) 519 (37) Ever smoked daily No 8161 (37) 1041 (49) 336 (46) 705 (51) Yes 13605 (63) 1078 (51) 392 (54) 686 (49) Education Lower secondary 5562 (26) 517 (24) 211 (29) 306 (22) Upper secondary 9412 (43) 949 (45) 317 (44) 632 (45) Tertiary 6792 (31) 653 (31) 200 (27) 453 (33) Age at measurement of cardiovascular risk factors, y, median (IQR) 50 (41-59) 48 (40-56) 51 (41-58) 46 (39-55) Abbreviations: IQR, interquartile range; MBRN, Medical Birth Registry of Norway.

6) 517 (24) 211 (29) 306 (22) Upper secondary 9412 (43) 949 (45) 317 (44) 632 (45) Tertiary 6792 (31) 653 (31) 200 (27) 453 (33) Age at measurement of cardiovascular risk factors, y, median (IQR) 50 (41-59) 48 (40-56) 51 (41-58) 46 (39-55) Abbreviations: IQR, interquartile range; MBRN, Medical Birth Registry of Norway. a Pregnancy status designates presence of hypertensive disorder, preeclampsia, or gestational hypertension in births at younger than 40 years. Association Between HDP and CVD Because the proportional hazards assumption was violated, as indicated by an interaction between the history of HDP and time (β = 0.98; 95% CI, 0.96-1.00; P = .01), we estimated HRs within the age intervals (40-70 years and 70-88 years) separately. For the purpose of brevity and clarity, only fully adjusted HRs based on model 2 are hereafter described in the text. Women with a history of HDP had an increased risk of any cardiovascular event (HR, 1.57; 95% CI, 1.32-1.86) between ages 40 and 70 years compared with women with only normotensive pregnancies (Table 2). The corresponding HRs were 1.66 (95% CI, 1.34-2.06) for women experiencing preeclampsia and 1.43 (95% CI, 1.09-1.88) for women experiencing gestational hypertension only. For women older than 70 years, the association was reversed, and women with a history of HDP had a lower risk of any cardiovascular event (HR, 0.60; 95% CI, 0.34-1.04) compared with women with only normotensive pregnancies. The results were broadly similar for women with preeclampsia and gestational hypertension.

only. For women older than 70 years, the association was reversed, and women with a history of HDP had a lower risk of any cardiovascular event (HR, 0.60; 95% CI, 0.34-1.04) compared with women with only normotensive pregnancies. The results were broadly similar for women with preeclampsia and gestational hypertension. Table 2. Hazard Ratios for Cardiovascular Events in Women With Hypertensive Disorder of Pregnancy Event No. of Events/No.

only. For women older than 70 years, the association was reversed, and women with a history of HDP had a lower risk of any cardiovascular event (HR, 0.60; 95% CI, 0.34-1.04) compared with women with only normotensive pregnancies. The results were broadly similar for women with preeclampsia and gestational hypertension. Table 2. Hazard Ratios for Cardiovascular Events in Women With Hypertensive Disorder of Pregnancy Event No. of Events/No. of Women Person-Years Model 1, HR (95% CI)a P Value Model 2, HR (95% CI)b P Value Any CVD event Age (40-70 y) Always normotensive 1155/21 752 37 4372 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 145/2117 34 802 1.45 (1.22-1.72) <.001 1.57 (1.32-1.86) <.001 Ever preeclampsia 91/1389 21 714 1.52 (1.23-1.88) <.001 1.66 (1.34-2.06) <.001 Ever gestational hypertension 54/728 13 088 1.34 (1.02-1.76) .04 1.43 (1.09-1.88) .01 Age (70-88 y) Always normotensive 375/3499 91 989 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 13/225 5957 0.59 (0.34-1.02) .06 0.59 (0.34-1.04) .07 Ever preeclampsia 8/129 3406 0.70 (0.35-1.42) .33 0.71 (0.35-1.43) .33 Ever gestational hypertension 5/96 2551 0.46 (0.19-1.12) .09 0.47 (0.20-1.15) .10 Myocardial infarction Age (40-70 y) Always normotensive 383/21 752 380 698 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 54/2117 35 533 1.64 (1.23-2.18) .001 1.86 (1.40-2.48) <.001 Ever preeclampsia 35/1389 22 119 1.78 (1.26-2.52) .001 2.08 (1.46-2.95) <.001 Ever gestational hypertension 19/728 13 413 1.43 (0.90-2.26) .13 1.56 (0.99-2.48) .06 Age (70-88 y) Always normotensive 112/3499 92 782 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 4/225 5997 0.58 (0.21-1.57) .29 0.66 (0.24-1.79) .41 Ever preeclampsia 2/129 3437 0.57 (0.14-2.30) .43 0.64 (0.16-2.61) .53 Ever gestational hypertension 2/96 2560 0.59 (0.15-2.40) .46 0.67 (0.17-2.73) .58 Heart failure Age (40-70 y) Always normotensive 140/21 752 383 087 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 16/2117 35 850 1.47 (0.86-2.52) .16 1.59 (0.92-2.73) .10 Ever preeclampsia 13/1389 22 316 1.83 (0.99-3.40) .06 2.00 (1.07-3.73) .03 Ever gestational hypertension 6/728 13 534 0.96 (0.35-2.60) .94 1.01 (0.37-2.75) .97 Age (70-88 y) Always normotensive 73/3499 92 975 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 4/225 5994 0.87 (0.35-2.14) .76 0.98 (0.39-2.44) .97 Ever preeclampsia 2/129 3441 0.97 (0.31-3.06) .96 1.07 (0.33-3.41) .91 Ever gestational hypertension 2/96 2553 0.76 (0.19-3.07) .70 0.87 (0.21-3.57) .85 Cerebrovascular disease Age (40-70 y) Always normotensive 617/21 752 378 902 1 [Reference] NA 1 [Reference

isorder 4/225 5994 0.87 (0.35-2.14) .76 0.98 (0.39-2.44) .97 Ever preeclampsia 2/129 3441 0.97 (0.31-3.06) .96 1.07 (0.33-3.41) .91 Ever gestational hypertension 2/96 2553 0.76 (0.19-3.07) .70 0.87 (0.21-3.57) .85 Cerebrovascular disease Age (40-70 y) Always normotensive 617/21 752 378 902 1 [Reference] NA 1 [Reference ] NA Ever hypertensive disorder 75/2117 35 324 1.40 (1.10-1.78) .006 1.47 (1.15-1.87) .002 Ever preeclampsia 46/1389 22 035 1.46 (1.08-1.97) .01 1.52 (1.13-2.06) .006 Ever gestational hypertension 29/728 13 289 1.32 (0.90-1.93) .15 1.38 (0.95-2.02) .10 Age (70-88 y) Always normotensive 178/3499 92581 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 8/225 5967 0.78 (0.40-1.52) .47 0.75 (0.38-1.48) .41 Ever preeclampsia 6/129 3411 0.98 (0.43-2.20) .95 0.93 (0.41-2.10) .86 Ever gestational hypertension 2/96 2555 0.56 (0.18-1.74) .31 0.55 (0.18-1.73) .31 Abbreviations: CVD, cardiovascular disease; HR, hazard ratio; NA, not applicable. a Adjusted for age. b Adjusted for age, highest obtained educational level, ever smoked daily, parity at younger than 40 years, maternal birth year, and family history of coronary heart disease.

] NA Ever hypertensive disorder 75/2117 35 324 1.40 (1.10-1.78) .006 1.47 (1.15-1.87) .002 Ever preeclampsia 46/1389 22 035 1.46 (1.08-1.97) .01 1.52 (1.13-2.06) .006 Ever gestational hypertension 29/728 13 289 1.32 (0.90-1.93) .15 1.38 (0.95-2.02) .10 Age (70-88 y) Always normotensive 178/3499 92581 1 [Reference] NA 1 [Reference] NA Ever hypertensive disorder 8/225 5967 0.78 (0.40-1.52) .47 0.75 (0.38-1.48) .41 Ever preeclampsia 6/129 3411 0.98 (0.43-2.20) .95 0.93 (0.41-2.10) .86 Ever gestational hypertension 2/96 2555 0.56 (0.18-1.74) .31 0.55 (0.18-1.73) .31 Abbreviations: CVD, cardiovascular disease; HR, hazard ratio; NA, not applicable. a Adjusted for age. b Adjusted for age, highest obtained educational level, ever smoked daily, parity at younger than 40 years, maternal birth year, and family history of coronary heart disease. Women with a history of HDP had an increased risk of myocardial infarction (HR, 1.86; 95% CI, 1.40-2.48), heart failure (HR, 1.59; 95% CI, 0.92-2.73), and cerebrovascular events (HR, 1.47; 95% CI, 1.15-1.87) in the age interval of 40 to 70 years compared with women with normotensive pregnancies (Table 2). These HRs were consistently higher among women with a history of preeclampsia than among women with a history of gestational hypertension only. At older than 70 years, women with a history of HDP had lower hazard rates for most subtypes of CVD compared with women with normotensive pregnancies, but limited observations and events for this age interval prevented precise estimates.

of preeclampsia than among women with a history of gestational hypertension only. At older than 70 years, women with a history of HDP had lower hazard rates for most subtypes of CVD compared with women with normotensive pregnancies, but limited observations and events for this age interval prevented precise estimates. Competing risk models gave virtually identical HRs to those estimated in the main analysis (results not shown), suggesting censoring was uninformative. Sensitivity analyses restricted to women who had their first birth recorded in the MBRN also yielded similar, but slightly lower and more imprecise HRs (eTables 3-6 in the Supplement). Sensitivity analyses restricted to validated diagnoses (eTables 7 and 8 in the Supplement) gave almost identical results to the main analyses.

vity analyses restricted to women who had their first birth recorded in the MBRN also yielded similar, but slightly lower and more imprecise HRs (eTables 3-6 in the Supplement). Sensitivity analyses restricted to validated diagnoses (eTables 7 and 8 in the Supplement) gave almost identical results to the main analyses. Contribution of Cardiovascular Risk Factors to CVD Risk in Women With History of HDP All associations between HDP and CVD described in this section are HRs based on the Cox proportional hazards model including person-time from 40 to 70 years. Because the associations between HDP and CVD were reversed for women older than 70 years, no mediation analyses were performed for this age interval. The associations between HDP and CVD differed slightly according to which cardiovascular risk factor was analyzed owing to variations in study population but fell within a fairly narrow range of 1.53 to 1.58 (Table 3). We calculated the percentage excess risk associated with each risk factor by dividing the β coefficient for the part of the association between HDP and CVD that was associated with the cardiovascular risk factor(s) with the β coefficient for the total association between HDP and CVD. The proportion of the association between HDP and CVD that was associated with BMI was 41%, corresponding to an HR of 1.19 (95% CI, 1.07-1.33). Systolic and diastolic blood pressure was associated with 60% and 73% of the association between HDP and CVD, corresponding to HRs of 1.30 (95% CI, 1.16-1.47) and 1.38 (95% CI, 1.23-1.55), respectively. Combining BMI with systolic and diastolic pressure in 2 separate mediation analyses showed that BMI together with systolic and diastolic blood pressure was associated with 67% and 79% of the excess cardiovascular risk in women with history of HDP, respectively (Table 3).

.47) and 1.38 (95% CI, 1.23-1.55), respectively. Combining BMI with systolic and diastolic pressure in 2 separate mediation analyses showed that BMI together with systolic and diastolic blood pressure was associated with 67% and 79% of the excess cardiovascular risk in women with history of HDP, respectively (Table 3). Table 3. Association Between Hypertensive Pregnancy Disorders and Cardiovascular Disease and BMI, Blood Pressure, and Serum Glucose and Lipid Levels in Women Aged 40 to 70 Years Cardiovascular Risk Factors Women, No. Total Association Between HDP and CVD Part of Association Between HDP and CVD That Is Not Associated With the Examined Cardiovascular Risk Factors Part of Association Between HDP and CVD That Is Associated With the Examined Cardiovascular Risk Factors Proportion of Excess Cardiovascular Risk in Women Who Had HDP That Is Associated With Cardiovascular Risk Factor(s), %b HR (95% CI)a P Value HR (95% CI)a P Value HR (95% CI)a P Value BMI 23 508 1.54 (1.29-1.83) <.001 1.29 (1.06-1.56) .01 1.19 (1.07-1.33) .001 41 Systolic blood pressure 23 500 1.55 (1.29-1.86) <.001 1.19 (0.97-1.47) .10 1.30 (1.16-1.47) <.001 60 Diastolic blood pressure 23 501 1.55 (1.30-1.85) <.001 1.13 (0.92-1.38) .25 1.38 (1.23-1.55) <.001 73 Glucose 21 881 1.58 (1.30-1.92) <.001 1.40 (1.15-1.72) .001 1.12 (1.02-1.23) .01 25 Non-HDL cholesterol 21 517 1.53 (1.26-1.88) <.001 1.38 (1.12-1.69) .002 1.11 (1.02-1.21) .02 24 BMI and systolic blood pressure 23 453 1.53 (1.27-1.84) <.001 1.15 (0.91-1.44) .23 1.33 (1.16-1.53) <.001 67 BMI and diastolic blood pressure 23 454 1.53 (1.28-1.83) <.001 1.09 (0.88-1.36) .43 1.40 (1.22-1.61) <.001 79 Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CVD, cardiovascular disease; HDL, high-density lipoprotein; HDP, hypertensive disorders of pregnancy.

BMI and diastolic blood pressure 23 454 1.53 (1.28-1.83) <.001 1.09 (0.88-1.36) .43 1.40 (1.22-1.61) <.001 79 Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); CVD, cardiovascular disease; HDL, high-density lipoprotein; HDP, hypertensive disorders of pregnancy. a Estimates are adjusted for age, highest obtained educational level, ever smoked daily, parity at younger than age 40 years, maternal birth year, and family history of coronary heart disease. b We calculated the percentage excess risk associated with each risk factor by dividing the β coefficient for the part of the association between HDP and CVD that was associated with the cardiovascular risk factor(s) with the β coefficient for the total association between HDP and CVD. We had fewer observations of nonfasting glucose levels and non-HDL cholesterol levels because these risk factors were not routinely assessed in HUNT1. Glucose was associated with 25% and non-HDL cholesterol was associated with 24%, corresponding to HRs of 1.12 (95% CI, 1.02-1.23) and 1.11 (95% CI, 1.02-1.21), respectively (Table 3). All risk factors combined (BMI, blood pressure, glucose, and non-HDL cholesterol) did not have a greater association with excess cardiovascular risk than the combination of BMI and blood pressure (results not shown).

corresponding to HRs of 1.12 (95% CI, 1.02-1.23) and 1.11 (95% CI, 1.02-1.21), respectively (Table 3). All risk factors combined (BMI, blood pressure, glucose, and non-HDL cholesterol) did not have a greater association with excess cardiovascular risk than the combination of BMI and blood pressure (results not shown). Separate mediation analyses for history of preeclampsia and gestational hypertension suggested that blood pressure had a greater association with cardiovascular risk in women with gestational hypertension, where it was associated with all excess risk. In women with preeclampsia, the mediators were maximally associated with 79% of the excess risk (eTables 9 and 10 in the Supplement). Analyses of CVD subtypes indicated that blood pressure was associated with most of the excess risk of heart failure and cerebrovascular events in women with a history of HDP, but only up to 41% of the excess risk of myocardial infarction (eTables 11-13 in the Supplement). Excluding the 484 women who had their cardiovascular risk factors measured before first pregnancy did not substantially alter our results (results not shown). Among the approximately 18 000 women who had their cardiovascular risk factors measured at older than 40 years, the proportions of excess CVD risk in women with a history of HDP that was associated with the cardiovascular risk factors was moderately reduced compared with the overall study population and maximally were associated with 47% of the excess risk (eTable 14 in the Supplement).

k factors measured at older than 40 years, the proportions of excess CVD risk in women with a history of HDP that was associated with the cardiovascular risk factors was moderately reduced compared with the overall study population and maximally were associated with 47% of the excess risk (eTable 14 in the Supplement). Discussion In this population-based cohort study, women with a history of HDP had approximately 60% higher risk of CVD until age 70 years compared with women with normotensive pregnancies. About 79% of the excess CVD risk was associated with blood pressure and BMI, indicating that these risk factors are important targets for CVD prevention in these women. The relative risk of CVD was slightly larger for women who experienced preeclampsia compared with gestational hypertension and higher for myocardial infarction than for heart failure and cerebrovascular events. The proportion of excess CVD risk associated with blood pressure and BMI was moderately lower among women who had their cardiovascular risk factors measured at older than 40 years, suggesting that earlier measurements of cardiovascular risk factors is more informative about later CVD risk in women with history of HDP.

The proportion of excess CVD risk associated with blood pressure and BMI was moderately lower among women who had their cardiovascular risk factors measured at older than 40 years, suggesting that earlier measurements of cardiovascular risk factors is more informative about later CVD risk in women with history of HDP. To our knowledge, no previous mediation analysis has combined measurements of cardiovascular risk factors with validated cardiovascular events to examine this topic, but our results are supported by an abstract from the Nurses’ Health Study II showing that self-reported cardiovascular risk factors, in particular chronic hypertension, were associated with most of the excess CVD risk associated with HDP. Information on which modifiable factors explain the excess CVD risk in women with history of HDP is a key requisite to inform prevention of CVD in these women. Previous large Nordic studies have used data from national health registries to quantify the association between HDP and future CVD. However, some of them included fatal events only, few studies examined the risk of heart failure and cerebrovascular events, and none had measurements of cardiovascular risk factors to perform mediation analyses.

dies have used data from national health registries to quantify the association between HDP and future CVD. However, some of them included fatal events only, few studies examined the risk of heart failure and cerebrovascular events, and none had measurements of cardiovascular risk factors to perform mediation analyses. Our estimates of the associations between HDP and future CVD are generally consistent with those of previous studies, but our point estimates are on the lower end of the spectrum. Most studies and meta-analyses report a doubling in CVD risk for preeclampsia, but previous cohort studies in comparable study populations reported associations that are relatively similar to our results. For example, in a nationwide Norwegian study, preeclampsia was associated with an HR of 1.6 for CVD mortality and an HR of 2.1 for major coronary events, and gestational hypertension was associated with an HR of 1.8 for CVD. In a Swedish study population, women with gestational hypertension and mild and severe preeclampsia had relative risks of ischemic heart disease of 1.6, 1.9, and 2.8, respectively. Similar estimates for various CVD end points were observed in a Danish population. Fewer studies have examined the associations of HDP with heart failure and cerebrovascular events, but a history of preeclampsia was associated with a 3.6-fold increased risk of heart failure in a meta-analysis. Meta-analyses of the association between a history of preeclampsia and cerebrovascular disease have reported an HR of 2.0 and an odds ratio of 1.8. Most previous studies followed up the women from the time of pregnancy, whereas we could not follow up women between the start of the MBRN in 1967 and the introduction of electronic hospital records in 1987. In this younger age group, the relative risk of CVD in women with a history of HDP may be higher (even if the absolute risk is low), which could explain the lower HRs observed in our study. Although we did not have statistical power to make conclusive inferences about the association between HDP and CVD among women older than 70 years, the apparent reversal of the HRs at old age is similar to what has been observed between cardiovascular risk factors and mortality in elderly populations and may be a result of survivor bias.

have statistical power to make conclusive inferences about the association between HDP and CVD among women older than 70 years, the apparent reversal of the HRs at old age is similar to what has been observed between cardiovascular risk factors and mortality in elderly populations and may be a result of survivor bias. Strengths and Limitations Our study was, with a median follow-up of 18 years, longer than the follow-up reported in the other Nordic studies. We started follow-up time after women largely finished reproducing at age 40 years to avoid introducing immortal time bias. Compared with most other studies relying on registry or administrative event data only, our study had the advantage of having clinically measured information about conventional cardiovascular risk factors and having validated 93% of the cardiovascular outcomes, thus ensuring high specificity of the outcome variables. However, we acknowledge that the available tests for CVD have changed throughout our study period and that this could potentially have affected our estimates. We also acknowledge that we may have missed nonfatal events where the patient was not admitted to hospital, but owing to the excellent public access to health care in Norway throughout the study period, this number is expectedly very low. Also, any misclassification would expectedly not depend on HDP or the examined mediators, and we consider it unlikely that this may have substantially influenced our results. Additionally, we had access to a broad range of relevant confounders from the HUNT study, enabling analyses of the association of these cardiovascular risk factors with the excess cardiovascular risk in women with history of HDP. For this purpose, we used a novel approach to mediation analysis that allowed us to perform formal mediation analyses for single and joint effects of several cardiovascular risk factors on the association between HDP and CVD in a survival setting while adjusting for multiple confounders. Our mediation results are probably generalizable to other populations where, as in Norway, access to health care is free and clinical follow-up is generally good. However, the association of these cardiovascular risk factors with later CVD risk may be lower in our and similar populations compared with populations where no or little medical treatment of cardiovascular risk factors takes place, ie, in populations where health care access is more limited.

llow-up is generally good. However, the association of these cardiovascular risk factors with later CVD risk may be lower in our and similar populations compared with populations where no or little medical treatment of cardiovascular risk factors takes place, ie, in populations where health care access is more limited. Conclusions Our study has shown that women with history of HDP have an increased risk of CVD that is to a large extent associated with increased levels of conventional, modifiable cardiovascular risk factors. Blood pressure plays a substantial role in driving the excess cardiovascular risk in women who experienced preeclampsia and an even larger role in women who experienced gestational hypertension. The association of conventional risk factors, in particular blood pressure and BMI, with the development of CVD in women with history HDP indicate that preventive efforts aimed at decreasing the levels of these risk factors could reduce cardiovascular risk in women with history of HDP. Supplement. eAppendix. eTable 1. ICD Codes for Fatal Cardiovascular Events in the Cause of Death Registry eFigure. Timeline of Follow-Up With Data Sources eTable 2. Descriptive Characteristics of Included Pregnancies in Main Analysis eTable 3. Hazard Ratios (HRs) For Any CVD Event and Myocardial Infarction in women With Hypertensive Disorder of Pregnancy and Whose First Birth Was Recorded in the Medical Birth Registry of Norway

eFigure. Timeline of Follow-Up With Data Sources eTable 2. Descriptive Characteristics of Included Pregnancies in Main Analysis eTable 3. Hazard Ratios (HRs) For Any CVD Event and Myocardial Infarction in women With Hypertensive Disorder of Pregnancy and Whose First Birth Was Recorded in the Medical Birth Registry of Norway eTable 4. Hazard ratios (HRs) For Heart Failure and Cerebrovascular Disease Events in Women With Hypertensive Disorder of Pregnancy and Whose First Birth was Recorded in the Medical Birth Registry of Norway. eTable 5. Hazard ratios (HRs) For Any CVD Event and Myocardial Infarction in Women With Hypertensive Disorder in Their First Pregnancy eTable 6. Hazard ratios (HRs) For Heart Failure and Cerebrovascular Disease in Women With Hypertensive Disorder in Their First Pregnancy eTable 7. Hazard Ratios for Any Validated CVD Event and Validated Myocardial Infarction in Women With Hypertensive Disorder of Pregnancy eTable 8. Hazard Ratios For Validated Heart Failure and Cerebrovascular Disease Events in Women With Hypertensive Disorder Of Pregnancy eTable 9. Association Between Preeclampsia and Cardiovascular Disease Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Glucose and Lipids on Cardiovascular Disease in Women eTable 10. Association Between Gestational Hypertension and Cardiovascular Disease Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Glucose And Lipids on Cardiovascular Disease in Women

eTable 9. Association Between Preeclampsia and Cardiovascular Disease Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Glucose and Lipids on Cardiovascular Disease in Women eTable 10. Association Between Gestational Hypertension and Cardiovascular Disease Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Glucose And Lipids on Cardiovascular Disease in Women eTable 11. Association Between Hypertensive Pregnancy Disorders and myocardial Infarction Decomposed into Parts Not Explained by and Explained by Through BMI, Blood Pressure, Glucose and Lipids in Women eTable 12. Association Between Hypertensive Pregnancy Disorders and Heart Failure Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Glucose and Lipids in Women eTable 13. Association Between Hypertensive Pregnancy Disorders and Cerebrovascular Disease Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Glucose and Lipids on Cerebrovascular Disease in Women eTable 14. Association Between Hypertensive Pregnancy Disorders and Cardiovascular Disease Decomposed into Parts Not Explained by and Explained by BMI, Blood Pressure, Serum Glucose and Lipids Measured After Age 40 in Women Click here for additional data file.

Introduction Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity in the United States, accounting for more than 900 000 deaths and 14 million disability-adjusted life-years in 2016 alone.1 Substantial progress has been made in combating CVD over the past 40 years, with mortality rates falling from 507 in 100 000 in 1980 to 253 in 100 000 in 2014.2 However, considerable disparities by race/ethnicity and geographic region persist.2,3,4 The American Heart Association has set a strategic goal of reducing deaths from CVD by 20% during 2010 to 2020.5 Similar goals have been proposed as part of the Million Hearts Initiative, which aims to prevent a million cardiovascular events during 2017 to 2022.6

es by race/ethnicity and geographic region persist.2,3,4 The American Heart Association has set a strategic goal of reducing deaths from CVD by 20% during 2010 to 2020.5 Similar goals have been proposed as part of the Million Hearts Initiative, which aims to prevent a million cardiovascular events during 2017 to 2022.6 Nevertheless, recent evidence suggests that progress made against premature mortality from heart disease has stagnated and rates have even increased in some US subgroups over the past 15 years.7 However, it remains unclear how trends in the specific type of CVD vary across population subgroups as well as the associated contributions of specific risk factors to CVD mortality. To better characterize 2000 to 2015 trends in rates of CVD premature mortality in the United States, we describe trends and patterns in cardiovascular deaths among people age 25 to 64 years by type of CVD, age group, sex, race/ethnicity, state, and county-level characteristics, including education, rurality, and the prevalence of smoking, obesity, and diabetes. The selection of this group is because (1) CVD death rates continue to decline among individuals 65 years and older in the United States8 and (2) the reduction of premature mortality is one of the United Nations Sustainable Development Goals9 and CVD mortality in the United States is divergent. A more detailed characterization of trends over time may provide insight into factors associated with increases and decreases in CVD deaths, which ultimately may inform the prioritization of prevention strategies at local and national levels.

nable Development Goals9 and CVD mortality in the United States is divergent. A more detailed characterization of trends over time may provide insight into factors associated with increases and decreases in CVD deaths, which ultimately may inform the prioritization of prevention strategies at local and national levels. Methods Data Sources Causes of death and demographics were ascertained from national death certificate data from the Surveillance, Epidemiology, and End Results data set, which contains national mortality data from 2000 to 2015. Institutional review board approval and informed consent were waived because the study used publicly available deidentified data. This analysis focused on premature deaths due to CVD, defined based on the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes: all CVD (I00-02, I05-09, I10-15, I20-I25, I26-I28, I60-69, I70-79, and I30-51), including ischemic heart disease (I20-25), cerebrovascular disease (I60-69), rheumatic heart disease (I00-02 and I05-09), hypertensive heart disease (I10-15), peripheral arterial disease (I70-79), heart failure (I42, I43, I50), cardiac arrest (I46), arrhythmia (I44-49), and endocarditis (I33 and I38). Age-, sex-, and race/ethnicity–specific data were ascertained from the US Census intercensal populations.

eart disease (I00-02 and I05-09), hypertensive heart disease (I10-15), peripheral arterial disease (I70-79), heart failure (I42, I43, I50), cardiac arrest (I46), arrhythmia (I44-49), and endocarditis (I33 and I38). Age-, sex-, and race/ethnicity–specific data were ascertained from the US Census intercensal populations. County Attributes We assessed the contribution of 5 county-level risk factors to CVD premature mortality: population with a bachelor degree (%), rurality, prevalence of smoking, diabetes, and obesity (defined as a body mass index [calculated as weight in kilograms divided by height in meters squared] of ≥30). We selected these 5 county-level factors based on their association with CVD mortality. Cardiovascular deaths vary by socioeconomic status. Therefore, we included county-level bachelor degree and rurality as proxies for socioeconomic status. We also included smoking, obesity, and diabetes prevalence because they are common risk factors for CVD and mortality.

based on their association with CVD mortality. Cardiovascular deaths vary by socioeconomic status. Therefore, we included county-level bachelor degree and rurality as proxies for socioeconomic status. We also included smoking, obesity, and diabetes prevalence because they are common risk factors for CVD and mortality. Because county-level socioeconomic status (SES) characteristics from 2011 to 2015 have been reported to be most relevant to current mortality rates,10 we ascertained the percentage of individuals with a bachelor degree (based on a population 25 years or older) from the 2011 to 2015 Census American Community Survey.11 The rurality of counties was defined based on the 2013 Rural-Urban Continuum codes that were developed by the US Department of Agriculture.12 Data on county-level smoking prevalence during 2008 to 2010 for 18 years or longer were ascertained from the Behavioral Risk Factor Surveillance System and the National Health Interview Survey.13,14 County-level obesity and diabetes prevalence for a population 20 years or older were estimated based on the Institute for Health Metrics and Evaluation.15

alence during 2008 to 2010 for 18 years or longer were ascertained from the Behavioral Risk Factor Surveillance System and the National Health Interview Survey.13,14 County-level obesity and diabetes prevalence for a population 20 years or older were estimated based on the Institute for Health Metrics and Evaluation.15 Statistical Analysis We estimated age-standardized mortality rates (ASRs) overall and stratified by calendar period (2000–2003 and 2012–2015), age group (25-49 years and 50-64 years), sex, and race/ethnicity (non-Hispanic white [ie, white], non-Hispanic black [ie, black], Asian and Pacific Islander, American Indian and Alaska Native, and Latinx) using the standard 2000 US population in 5-year age groups as the reference. The selection of these 2 age groups was based on published data examining premature all-cause mortality in the United States by county using the US death certificate data.10 We restricted estimates for American Indian/Alaska Native individuals to contract health services delivery areas to reduce racial/ethnic misclassification.16 We also estimated the average annual percentage change (AAPC) in rates during 2000 to 2015 by age group, sex, state, and race/ethnicity stratified by CVD types. Analyses were conducted using SEER*Stat software (National Cancer Institute).

tract health services delivery areas to reduce racial/ethnic misclassification.16 We also estimated the average annual percentage change (AAPC) in rates during 2000 to 2015 by age group, sex, state, and race/ethnicity stratified by CVD types. Analyses were conducted using SEER*Stat software (National Cancer Institute). We then estimated age-standardized CVD mortality rates during 2012 to 2015 among white, black, and Latinx individuals by each county-level factor. We categorized counties by the following county-level factors: (1) percentage with a bachelor degree (1%-20%, 21%-26%, 27%-30%, 31%-37%, and 38%-79%), (2) rurality (metropolitan areas with ≥1 million people, metropolitan areas with 250 000 to <1 million people, metropolitan areas of <250 000 people, urban areas with ≥20 000 people, urban areas with 2500 to <20 000 people, and completely rural populations with <2500 people), (3) smoking prevalence (6%-20%, 21%-23%, 24%-26%, 27%-29%, and 30%-43%), (4) obesity prevalence (18%-34%, 35%-36%, 37%-38%, 39%-40%, and 41%-53%), and (5) diabetes prevalence (5%-8.5%, 8.6%-9.7%, 9.8%-10.6%, 10.7%-11%, and 12%-21%). Missing values were categorized to a separate group. Because we aggregated counties, we included all counties regardless of population size and number of deaths. We also estimated the annual percentage change in mortality rates during 2000 to 2015 by the level of each county-level factor.

0.6%, 10.7%-11%, and 12%-21%). Missing values were categorized to a separate group. Because we aggregated counties, we included all counties regardless of population size and number of deaths. We also estimated the annual percentage change in mortality rates during 2000 to 2015 by the level of each county-level factor. We then conducted a multivariate quasi-Poisson regression, adjusting for age (5-year age group) and 5 county-level factors to examine the associations of these risk factors with recent CVD mortality rates (rates in 2012-2015), including all CVD, ischemic heart disease, and hypertensive heart disease. Because the total number of events was too sparse for certain races/ethnicities after stratifying by county-level risk factors, we restricted the regression analyses to white and black individuals. Regression analyses were conducted using the R program, version 3.4.2 (R Foundation) and statistical significance was set at P < .05. Results CVD Mortality During 2000 to 2015, more than 2.3 million CVD deaths occurred among individuals aged 25 to 64 years in the United States. Among women, the ASR declined by 20% from 60 in 100 000 during 2000 to 2003 to 48 in 100 000 during 2012 to 2015 (AAPC, −1.9%). Similarly, among men, the ASR declined by 20% from 130 in 100 000 during 2000 to 2003 to 104 in 100 000 during 2012 to 2015 (AAPC, −1.8%).

individuals aged 25 to 64 years in the United States. Among women, the ASR declined by 20% from 60 in 100 000 during 2000 to 2003 to 48 in 100 000 during 2012 to 2015 (AAPC, −1.9%). Similarly, among men, the ASR declined by 20% from 130 in 100 000 during 2000 to 2003 to 104 in 100 000 during 2012 to 2015 (AAPC, −1.8%). There was substantial variation in total CVD mortality rates and trends by racial/ethnic and age groups. Among women, black individuals had the highest ASR during 2012 to 2015 (101/100 000), followed by American Indian/Alaska Native (74/100 000), white (44/100 000), and Latinx individuals (28/100 000). Asian Pacific Islander individuals had the lowest ASR (19/100 000). Similarly, in men, ASR during 2012 to 2015 were highest among black individuals (190/100 000), followed by American Indian/Alaska Native (161/100 000), white (100/100 000), Latinx (69/100 000), and Asian Pacific Islander individuals (55/100 000) (Table).

ian Pacific Islander individuals had the lowest ASR (19/100 000). Similarly, in men, ASR during 2012 to 2015 were highest among black individuals (190/100 000), followed by American Indian/Alaska Native (161/100 000), white (100/100 000), Latinx (69/100 000), and Asian Pacific Islander individuals (55/100 000) (Table). Table. Trends and Age-Standardized Premature Mortality (Age 25 to 64 Years) Rates Because of All Cardiovascular Disease in the United States During 2000 to 2003 Compared With 2012 to 2015a Race/Ethnicity Age 25-49 y Age 50-64 y Overall 2000-2003 per 100 000 2012-2015 per 100 000 Average Annual % Change 2000-2003 per 100 000 2012-2015 per 100 000 Average Annual % Change 2000-2003 per 100 000 2012-2015 per 100 000 Average Annual % Change Women White 19 19 0.05 129 104 −1.8 51 44 −1.3 Black 62 46 −2.5 341 237 −3.0 143 101 −2.9 Latinx 14 11 −2.0 108 72 −3.3 41 28 −3.0 Asian Pacific Islander 10 7 −2.0 75 49 −3.6 28 19 −3.2 American Indian/Alaska Native 31 40 2.1 185 158 −1.2 75 74 −0.1 Overall 24 21 −1.1 149 114 −2.2 60 48 −1.9 Men White 47 41 −1.1 305 247 −1.7 121 100 −1.9 Black 102 85 −1.6 619 450 −2.7 251 190 −2.4 Latinx 31 26 −1.6 241 176 −2.6 92 69 −2.3 Asian Pacific Islander 26 23 −0.9 168 133 −2.0 67 55 −1.7 American Indian/Alaska Native 67 77 1.3 381 368 −0.2 157 161 0.3 Overall 51 43 −1.4 327 258 −2.0 130 105 −1.8 a Rates per 100 000.

en White 47 41 −1.1 305 247 −1.7 121 100 −1.9 Black 102 85 −1.6 619 450 −2.7 251 190 −2.4 Latinx 31 26 −1.6 241 176 −2.6 92 69 −2.3 Asian Pacific Islander 26 23 −0.9 168 133 −2.0 67 55 −1.7 American Indian/Alaska Native 67 77 1.3 381 368 −0.2 157 161 0.3 Overall 51 43 −1.4 327 258 −2.0 130 105 −1.8 a Rates per 100 000. Black individuals showed statistically significant declines in ASR during 2000 to 2015 for women and men (AAPC, −2.9% in women; −2.4% in men), along with Latinx (−3.0% in women; −2.3% in men), Asian Pacific Islander (−3.2% in women; −1.7% in men), and white individuals (−1.3% in women; -1.9% in men). In contrast, ASR increased significantly among American Indian/Alaska Native individuals age 25 to 49 years (AAPC: women, 2.1%; men, 1.3%), and ASR among white women aged 25 to 49 years plateaued (AAPC, 0.05%) (Table). The analysis of state-specific trends was limited to black and white individuals because of sparse data in other racial/ethnic groups. During 2000 to 2015, most groups of black and white individuals showed significant declines in CVD mortality, particularly among men aged 50 to 64 years; whereas white men had significant declines in all states, black men had more pronounced declines in most states, except Utah (AAPC = 2.8%) (Figure 1). However, compared with other groups, white women aged 25 to 49 years showed considerable variations in trends, with AAPCs ranging from −3.3% in Oregon to 2.3% in Alabama (eFigure 1 in the Supplement).

nt declines in all states, black men had more pronounced declines in most states, except Utah (AAPC = 2.8%) (Figure 1). However, compared with other groups, white women aged 25 to 49 years showed considerable variations in trends, with AAPCs ranging from −3.3% in Oregon to 2.3% in Alabama (eFigure 1 in the Supplement). Figure 1. Average Annual Percentage Change of Cardiovascular Disease Mortality Rates Among White and Black Men Aged 50 to 64 Years by State, 2000 to 2015 Ischemic heart disease (54% of all CVD premature deaths), cerebrovascular disease (13%), and hypertensive heart disease (10%) contributed to the largest fraction of CVD premature deaths from 2000 to 2015. Declines in ASR due to ischemic heart disease were the primary contributor to the decline in overall CVD mortality, with decreases in most age and racial/ethnic groups (AAPC: range, −4.7 to −0.5%). Mortality declines in ASR were also observed for cerebrovascular disease (−4.5% to −0.4%), peripheral arterial disease (−5.5% to −0.1%), and rheumatic heart disease (−6.6% to −0.3%) (eTable 1 in the Supplement). In contrast, ASRs of ischemic heart disease increased among American Indian/Alaska Native women aged 25 to 49 years (AAPC: 1.7%) and were stagnant for white women aged 25 to 49 years (eTable 1 in the Supplement).

terial disease (−5.5% to −0.1%), and rheumatic heart disease (−6.6% to −0.3%) (eTable 1 in the Supplement). In contrast, ASRs of ischemic heart disease increased among American Indian/Alaska Native women aged 25 to 49 years (AAPC: 1.7%) and were stagnant for white women aged 25 to 49 years (eTable 1 in the Supplement). During 2000 to 2015, ASR from hypertensive heart disease, which was the third most common cause of CVD deaths in 2012 to 2015, increased in most racial/ethnic groups (Figure 2). Compared with other groups, white women aged 25 to 49 years had the highest increase in hypertensive heart disease mortality. An additional analysis of trends showed increases in ASR of hypertensive heart disease in most states (AAPC, from 0.4% in South Carolina to 19.7% in South Dakota), except Washington, DC (−2.5%) and Vermont (−1.6%) (eFigure 2 in the Supplement). The ASR of endocarditis increased significantly in white individuals aged 25 to 49 years (AAPC: women, 3.9%; men, 3.7%) and American Indian/Alaska Native men (5.6%) (Figure 2).

(AAPC, from 0.4% in South Carolina to 19.7% in South Dakota), except Washington, DC (−2.5%) and Vermont (−1.6%) (eFigure 2 in the Supplement). The ASR of endocarditis increased significantly in white individuals aged 25 to 49 years (AAPC: women, 3.9%; men, 3.7%) and American Indian/Alaska Native men (5.6%) (Figure 2). Figure 2. Cardiovascular Disease (CVD) Mortality Average Annual Percentage Change Stratified by Age Group, Sex, and Race/Ethnicity Across Types of Disease, 2000 to 2015 CVD Mortality by County-Level Factors Recent CVD premature mortality rates (2012–2015) varied substantially by county-level risk factors. The ASRs were consistently higher in counties with lower socioeconomic factors (ie, lower education levels and rural areas). The ASRs were also generally higher in counties with a high prevalence of diabetes, obesity, and smoking. These increases followed a gradient across quintiles of county-level factors and were more pronounced in white than black and Latinx individuals (Figure 3A). During 2000 to 2015, ASR among black and Latinx individuals declined over time across counties regardless of county-level factors. In contrast, ASR among white women aged 25 to 49 years predominantly increased among counties with a lower percentage of bachelor degrees, and a higher prevalence of diabetes, obesity, and smoking and among more rural counties (Figure 3B). A multivariate quasi-Poisson regression confirmed associations between county-level factors and the risk of CVD mortality, in which county-level diabetes prevalence showed the strongest effect (Figure 4). The associations were more pronounced in white individuals aged 25 to 49 years than black (Figure 4). For example, for women aged 25 to 49 years, compared with counties with a diabetes prevalence of 5% to 8.5%, the risk of CVD mortality was 1.4 times higher among white individuals and 1.3 times higher among black individuals who lived in counties with a diabetes prevalence of 9.8% to 10.6%; the risk of CVD mortality was 1.8 times higher among white individuals and 1.4 times higher among black individuals in counties with a diabetes prevalence of 12% to 21% (Figure 4 and eTable 2 in the Supplement).

1.3 times higher among black individuals who lived in counties with a diabetes prevalence of 9.8% to 10.6%; the risk of CVD mortality was 1.8 times higher among white individuals and 1.4 times higher among black individuals in counties with a diabetes prevalence of 12% to 21% (Figure 4 and eTable 2 in the Supplement). Figure 3. County-Level Mortality Rates A, Age-standardized all cardiovascular disease (CVD) mortality rates, 2012 to 2015. B, Average annual percentage change of all CVD mortality rates, 2000 to 2015. Figure 4. Multivariate Quasi-Poisson Regression by County-Level Risk Factors, 2012 to 2015 As mortality rates of hypertensive heart disease increased significantly across most age, sex, and racial/ethnic groups, we further examined rates and trends by county-level factors. Age-standardized mortality rates of hypertensive heart disease were generally higher in counties with a high prevalence of diabetes and obesity, but the associations between county-level smoking prevalence and education levels and mortality rates were less pronounced (eFigure 3 in the Supplement). Increases occurred across many types of counties but generally followed a gradient across quintiles of county-level factors, although these patterns were less clear among black and Latinx individuals (eFigure 3 in the Supplement). The multivariate quasi-Poisson regression showed a predominant association between county-level diabetes prevalence and hypertensive heart disease mortality (eFigure 3 and eTable 3 in the Supplement).

evel factors, although these patterns were less clear among black and Latinx individuals (eFigure 3 in the Supplement). The multivariate quasi-Poisson regression showed a predominant association between county-level diabetes prevalence and hypertensive heart disease mortality (eFigure 3 and eTable 3 in the Supplement). Discussion During 2000 to 2015, we observed significant declines in CVD premature mortality rates for black, Latinx, and Asian and Pacific Islander individuals but significant increases in rates among American Indians/Alaska Native individuals age 25 to 49 years; rates plateaued among white women aged 25 to 49 years. These increases were driven by a lack of progress against mortality from ischemic heart disease and increases in mortality from hypertensive heart disease and endocarditis.

cant increases in rates among American Indians/Alaska Native individuals age 25 to 49 years; rates plateaued among white women aged 25 to 49 years. These increases were driven by a lack of progress against mortality from ischemic heart disease and increases in mortality from hypertensive heart disease and endocarditis. The American Heart Association has set a strategic goal for reducing deaths from CVD by 20% from 2010 to 2020.5 While there was an overall 28% decrease in CVD mortality rates in the United States during 2003 to 2015,17 reflecting the progress made in prevention and advances in cardiovascular disease treatment, equivalent declines have not been observed across age groups.18 Improvements in mortality also vary by race/ethnicity. A recent US Centers for Disease Control and Prevention report examining mortality trends found that heart disease death rates increased for white people aged 45 to 64 years during 2009 to 2017 and for black individuals aged 45 to 64 years during 2011 to 2017 despite an overall of 22% of decline in rates from 1999 to 2011.19 In this study, we compared premature mortality due to all CVD during 2012 to 2015 with rates from 2000 to 2003. While we observed declines in CVD mortality, we found stagnation in ischemic heart disease mortality among young white women and significant increases in mortality from hypertensive heart disease across most races/ethnicities. This highlights the importance of understanding the diversity and disparities in CVD mortality by risk factors among different groups.

ty, we found stagnation in ischemic heart disease mortality among young white women and significant increases in mortality from hypertensive heart disease across most races/ethnicities. This highlights the importance of understanding the diversity and disparities in CVD mortality by risk factors among different groups. Disparities in CVD mortality by SES have been well established in the United States.20 Important risk factors, including smoking, obesity, and diabetes, are more prevalent among lower-SES counties compared with higher-SES counties.21 As observed previously,2,7 we found substantial differences in mortality rates by age, sex, and racial/ethnic groups across different types of counties. For example, CVD mortality rates were generally lower in high-SES counties and more urban areas. These findings highlight potential opportunities among states to target public health resources for primary and secondary CVD prevention toward counties based on SES status and rurality.22

cross different types of counties. For example, CVD mortality rates were generally lower in high-SES counties and more urban areas. These findings highlight potential opportunities among states to target public health resources for primary and secondary CVD prevention toward counties based on SES status and rurality.22 In contrast to the trends for overall CVD mortality, we found marked increases in premature mortality associated with hypertensive heart disease across most age and racial/ethnic groups. This increase occurred across the country, although gradients by county characteristics were noted. Previous data suggest that only half of US individuals with hypertension had their condition effectively controlled.23 Consistent with our data, the proportion of US mortality rates attributable to hypertension increased by 10.5% from 2005 to 2015 and the absolute number of deaths attributable to hypertension rose by 37.5%.24 Hypertension is common in patients with diabetes25 and patients with diabetes and hypertension experience more severe cardiovascular outcomes than patients with either condition alone.25 We found that compared with other risk factors, diabetes prevalence had the strongest association with premature mortality from hypertensive heart disease.

in patients with diabetes25 and patients with diabetes and hypertension experience more severe cardiovascular outcomes than patients with either condition alone.25 We found that compared with other risk factors, diabetes prevalence had the strongest association with premature mortality from hypertensive heart disease. Without widespread intervention, continued increases in diabetes prevalence in the United States will likely exacerbate the adverse trends observed here. Coupled with this, increases in premature mortality associated with hypertensive heart disease are most concerning given the change in the hypertension definition in the 2017 clinical guidelines.26 The new guidelines markedly reset the diagnosis and treatment of hypertension, which potentially results in more individuals receiving a hypertension diagnosis.27 Public health policies to mitigate these trends in CVD mortality will need to focus on diagnosis, treatment, and control of hypertension in younger populations, particularly in lower-resourced, underserved communities. In addition, continuously monitoring mortality from hypertensive heart disease is important to evaluate the effect of changes in the clinical guideline and how this may shape the CVD mortality rates overall.

t, and control of hypertension in younger populations, particularly in lower-resourced, underserved communities. In addition, continuously monitoring mortality from hypertensive heart disease is important to evaluate the effect of changes in the clinical guideline and how this may shape the CVD mortality rates overall. The significant increase in premature mortality that is associated with endocarditis among young white individuals and young American Indian and Alaska Native men is also worrisome, despite relatively few deaths. Coincident with the marked rise in deaths from opioid use, increase in endocarditis among certain groups may be associated with the opioid epidemic. Although this study could not directly address this hypothesis, a disproportionate increase in deaths from endocarditis has been found among young white individuals who inject drugs.28 In 2016, approximately 1 million people used heroin in the United States, which was 2-fold higher than the total number of heroin users in the period over 2002 to 2013.29 Consequently, many of the population were at risk of bacteremia from contaminated needles and subsequent endocarditis. Future studies investigating the association of injection drug use with trends in endocarditis are needed.

ich was 2-fold higher than the total number of heroin users in the period over 2002 to 2013.29 Consequently, many of the population were at risk of bacteremia from contaminated needles and subsequent endocarditis. Future studies investigating the association of injection drug use with trends in endocarditis are needed. Strengths and Limitations A strength of this study was the stratification of the analysis by age groups, allowing us to identify trends that would be missed across the full age range by age standardization. Another strength of this study was the estimation and comparison of county-level CVD risk factors. County-level estimates enable the identification of local trends and patterns of CVD mortality that are associated with important risk factors. However, as macro-level estimates, county-level risk factors do not represent the factors of specific individuals who died of CVD nor age- and sex-specific variations within each county. Additionally, county-level risk factor estimates were restricted to white, black, and Latinx individuals as there were fewer deaths occurring among other groups, which precluded systematic examination by county.

the factors of specific individuals who died of CVD nor age- and sex-specific variations within each county. Additionally, county-level risk factor estimates were restricted to white, black, and Latinx individuals as there were fewer deaths occurring among other groups, which precluded systematic examination by county. Another limitation of this study is the use of death certificate data. Racial/ethnic misclassification is a main concern, as race/ethnicity data on death certificates are typically recorded by funeral directors, whereas self-reported information on the census is used to calculate the denominators in this study. Nevertheless, race/ethnicity recording on death certificates has been reported as highly accurate for white and black individuals, and misclassification in Latinx and Asian and Pacific Islander individuals is minor.30 To reduce misclassification in American Indian and Alaska Native individuals, we restricted the analysis to contract health services delivery areas.16 There are also concerns about the possible misclassification of CVD and changes in coding over time. Use of these data for CVD in aggregate has been validated and reduces the potential for misclassification.31,32 However, we should be cautious regarding examining trends in hypertensive heart disease and other types. For example, with increasing emphasis on blood pressure control, deaths from heart failure, coronary artery disease, and stroke may be misclassified as hypertensive heart disease. This misclassification may overestimate the effect of hypertensive heart disease, but it may also underestimate the effect of other heart diseases. Despite this, the use of death certificate data is the most feasible current method to conduct this type of analysis on the US population, as opposed to community-based cohorts in which the findings would have limited generalizability. Additionally, as CVD in aggregate includes several diseases with distinct etiologies, it is important to explore the contributions of individual types of CVD to the overall picture over time.

analysis on the US population, as opposed to community-based cohorts in which the findings would have limited generalizability. Additionally, as CVD in aggregate includes several diseases with distinct etiologies, it is important to explore the contributions of individual types of CVD to the overall picture over time. Identifying groups with increasing CVD mortality rates is important to guide targeted prevention efforts. Recent work identifies important areas of research to better understand the high rates of CVD mortality among American Indian and Alaska Native populations, including work to elucidate the association of adverse childhood experiences and other psychosocial factors with CVD in these communities.33 Future interventions, policies, and systems approaches to promote healthy behaviors and reduce CVD risk are needed among American Indian and Alaska Native youth. For younger women at risk for CVD, including young white women, screening for CVD risk factors must be considered across medical specialties that regularly care for women.34 Tailored interventions to promote cardiovascular health may most easily reach women outside of the clinical setting by leveraging social media and mobile health technology.35

r CVD, including young white women, screening for CVD risk factors must be considered across medical specialties that regularly care for women.34 Tailored interventions to promote cardiovascular health may most easily reach women outside of the clinical setting by leveraging social media and mobile health technology.35 Conclusions Despite the marked progress that has been made in preventing cardiovascular deaths in the United States, substantial increases in CVD mortality rates have occurred among American Indians and Alaska Native individuals aged 25 to 49 years and rates have plateaued among young white women, reflecting a lack of progress against mortality from ischemic heart disease and increases in mortality rates from hypertensive heart disease and endocarditis in these groups. Mortality from hypertensive heart disease is a growing concern that affects most groups. Counties with a high prevalence of obesity, diabetes, and smoking have continued to experience higher rates of CVD mortality and should be targeted for intervention. Although CVD risk factors are modifiable, sustained efforts at such interventions are needed. Without rapid and sustained progress against cardiovascular risk factors, public health goals to further reduce the burden of cardiovascular disease mortality in the United States are unlikely to be met. Supplement. eFigure 1. Average annual percent change of CVD mortality rates by states, stratified by race/ethnicity, sex, and age groups, 2000-15 eFigure 2. Average annual percent change of mortality rates due to hypertensive heart disease by states, 2000-15

Conclusions Despite the marked progress that has been made in preventing cardiovascular deaths in the United States, substantial increases in CVD mortality rates have occurred among American Indians and Alaska Native individuals aged 25 to 49 years and rates have plateaued among young white women, reflecting a lack of progress against mortality from ischemic heart disease and increases in mortality rates from hypertensive heart disease and endocarditis in these groups. Mortality from hypertensive heart disease is a growing concern that affects most groups. Counties with a high prevalence of obesity, diabetes, and smoking have continued to experience higher rates of CVD mortality and should be targeted for intervention. Although CVD risk factors are modifiable, sustained efforts at such interventions are needed. Without rapid and sustained progress against cardiovascular risk factors, public health goals to further reduce the burden of cardiovascular disease mortality in the United States are unlikely to be met. Supplement. eFigure 1. Average annual percent change of CVD mortality rates by states, stratified by race/ethnicity, sex, and age groups, 2000-15 eFigure 2. Average annual percent change of mortality rates due to hypertensive heart disease by states, 2000-15 eFigure 3. County-level (A) age-standardized hypertensive heart disease mortality rates, 2012-2015; (B) average annual percent change of hypertensive heart disease mortality rates, 2000-2015, and (C) multivariate quasi-Poisson regression by county-level risk factors 2012-15