Wednesday, 14 February 2018

Factors associated with elevated blood pressure or hypertension in Afro-Caribbean youth: a cross-sectional study

PEER-REVIEWED Research articleCardiologyEpidemiologyGlobal HealthInternal MedicinePublic Health Trevor S. Ferguson​1, Novie O.M. Younger-Coleman1, Marshall K. Tulloch-Reid1, Nadia R. Bennett1, Amanda E. Rousseau1, Jennifer M. Knight-Madden1, Maureen E. Samms-Vaughan2, Deanna E. Ashley3, Rainford J. Wilks1 February 13, 2018 Author and article information Abstract Background Although several studies have identified risk factors for high blood pressure (BP), data from Afro-Caribbean populations are limited. Additionally, less is known about how putative risk factors operate in young adults and how social factors influence the risk of high BP. In this study, we estimated the relative risk for elevated BP or hypertension (EBP/HTN), defined as BP ≥ 120/80 mmHg, among young adults with putative cardiovascular disease (CVD) risk factors in Jamaica and evaluated whether relative risks differed by sex. Methods Data from 898 young adults, 18–20 years old, were analysed. BP was measured with a mercury sphygmomanometer after participants had been seated for 5 min. Anthropometric measurements were obtained, and glucose, lipids and insulin measured from a fasting venous blood sample. Data on socioeconomic status (SES) were obtained via questionnaire. CVD risk factor status was defined using standard cut-points or the upper quintile of the distribution where the numbers meeting standard cut-points were small. Relative risks were estimated using odds ratios (OR) from logistic regression models. Results Prevalence of EBP/HTN was 30% among males and 13% among females (p < 0.001 for sex difference). There was evidence for sex interaction in the relationship between EBP/HTN and some of risk factors (obesity and household possessions), therefore we report sex-specific analyses. In multivariable logistic regression models, factors independently associated with EBP/HTN among men were obesity (OR 8.48, 95% CI [2.64–27.2], p < 0.001), and high glucose (OR 2.01, CI [1.20–3.37], p = 0.008), while high HOMA-IR did not achieve statistical significance (OR 2.08, CI [0.94–4.58], p = 0.069). In similar models for women, high triglycerides (OR 1.98, CI [1.03–3.81], p = 0.040) and high HOMA-IR (OR 2.07, CI [1.03–4.12], p = 0.039) were positively associated with EBP/HTN. Lower SES was also associated with higher odds for EBP/HTN (OR 4.63, CI [1.31–16.4], p = 0.017, for moderate vs. high household possessions; OR 2.61, CI [0.70–9.77], p = 0.154 for low vs. high household possessions). Alcohol consumption was associated with lower odds of EBP/HTN among females only; OR 0.41 (CI [0.18–0.90], p = 0.026) for drinking <1 time per week vs. never drinkers, and OR 0.28 (CI [0.11–0.76], p = 0.012) for drinking ≥3 times per week vs. never drinkers. Physical activity was inversely associated with EBP/HTN in both males and females. Conclusion Factors associated with EBP/HTN among Jamaican young adults include obesity, high glucose, high triglycerides and high HOMA-IR, with some significant differences by sex. Among women lower SES was positively associated with EBP/HTN, while moderate alcohol consumption was associated lower odds of EBP/HTN. Cite this as Ferguson TS, Younger-Coleman NOM, Tulloch-Reid MK, Bennett NR, Rousseau AE, Knight-Madden JM, Samms-Vaughan ME, Ashley DE, Wilks RJ. (2018) Factors associated with elevated blood pressure or hypertension in Afro-Caribbean youth: a cross-sectional study. PeerJ 6:e4385 Main article text Introduction High blood pressure (BP) is the leading risk factor for the global burden of disease, accounting for approximately 7% of global disability adjusted life years (Lim et al., 2012). Recent studies suggest that while the prevalence of hypertension is decreasing in high-income countries, prevalence is increasing in low and middle-income countries, with the largest increase seen in countries in sub-Saharan Africa (Mills et al., 2016; NCD Risk Factor Collaboration, 2016). The adverse effect of high BP, particularly increased risk of coronary heart disease and stroke, is continuous and graded throughout the range of systolic blood pressure (SBP) and diastolic blood pressure (DBP), down to levels of 115 mmHg and 75 mmHg, respectively (Lewington et al., 2002). Additionally, it has been estimated that approximately 50% of disease burden attributable to high BP occurs at levels below the 140/90 mmHg cut-off point traditionally used to define hypertension (Poulter, Prabhakaran & Caulfield, 2015). Recently the American College of Cardiology and American Heart Association (ACC/AHA) proposed new guidelines for the evaluation and management of high BP (Whelton et al., 2017). In this guideline, normal BP is defined having SBP <120 mmHg and DBP <80 mmHg; elevated BP is defined as SBP of 120-129 mmHg and DBP <80 mmHg; and hypertension defined as SBP ≥130 mmHg or DBP >80 mmHg. However, most of the available data on prevalence of hypertension have used the criteria from the Seventh Report of the Joint National Committee on the Prevention, Detection, Evaluation and Treatment of High Blood Pressure (JNC 7), where hypertension is defined as SBP ≥140 mmHg or DBP ≥90 mmHg, and SBP of 120-139 mmHg or DBP of 80-89 is classified as prehypertension (Chobanian et al., 2003). Studies reporting prevalence estimates for children or adolescents <18 years old often use criteria from The Fourth Report on the Diagnosis, Evaluation, and Treatment of High Blood Pressure in Children and Adolescents by the National High Blood Pressure Education Program (NHBPEP) (National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents, 2004). Reported prevalence of hypertension, using JNC 7 or NHBPEP criteria, in adolescents and young adults vary widely, with estimates generally ranging from about 2% among 15–34 year-olds in Italy up to 19% among young adults 24–34 years old in the USA (Battistoni et al., 2015). However, prehypertension appears to be common in adolescents and young adults, with prevalence estimates ranging from 12%–45% in various studies from countries such as India, Uganda, United States and Jamaica (Amma, Vasudevan & Akshayakumar, 2015; Ferguson et al., 2011b; Kayima et al., 2015; Kini et al., 2016; Redwine & Daniels, 2012). Given that high BP in childhood has been shown to track into adulthood (Bao et al., 1995; Chen & Wang, 2008), studies of high BP in youth provide essential information to inform interventions that would reduce the adverse effects of high BP on cardiovascular health. The aetiology of hypertension is multi-factorial, with complex interactions between genetic, environmental, behavioural and social factors (Lloyd-Jones & Levy, 2013; Poulter, Prabhakaran & Caulfield, 2015; Victor, 2015). Established risk factors for hypertension include increasing age, higher levels of adiposity, high dietary sodium, high alcohol consumption, family history of hypertension and lower socioeconomic status (Lloyd-Jones & Levy, 2013). Underlying mechanism include activation of the sympathetic nervous system, disorders of the renin-angiotensin aldosterone pathways, disorders of renal regulation of sodium balance, insulin resistance, inflammation, arterial stiffness and foetal programming (Acelajado, Calhoun & Oparil, 2013; Victor, 2015). Complications of hypertension vary with race/ethnicity and it is conceivable that the mechanisms underlying both aetiology and complications could vary similarly (Jones & Hall, 2006; Lackland, 2014). Additionally, less is known about how these factors operate in young African origin populations and how social factors, particularly in a developing country context, influence the risk of high BP. In Jamaica, the prevalence of hypertension (using the JNC 7 criteria) among persons 15–74 years old was estimated at 20% in 2001, and 25% in 2008 (Ferguson et al., 2011a). The prevalence of prehypertension was 30% in 2001 and 35% in 2008, and was shown to be associated with other cardiovascular disease (CVD) risk factors and high rates of progression to hypertension (Ferguson et al., 2011a; Ferguson et al., 2010c; Ferguson et al., 2008). Among 15–19 year-old youth, the prevalence of prehypertension in 2006 was 29% (Ferguson et al., 2011b). More recently, the Modeling the Epidemiological Transition Study reported prevalence of hypertension among urban Jamaicans 25–45 years old, with prevalence estimates of 6.8% among men and 10% among women (Cooper et al., 2015). This study also found that the prevalence of CVD risk factors was not always consistent with that expected, with Jamaican women having lower diabetes prevalence despite high obesity prevalence and South African men having higher prevalence of hypertension despite lower adiposity (Dugas et al., 2017). Given the high burden of hypertension and prehypertension in Jamaica, studies evaluating the relative contribution of various risk factors would provide necessary information to direct public health interventions. This paper therefore evaluates the association between putative risk factors and elevated BP or hypertension (EBP/HTN), defined as BP ≥120/80 mmHg, among Afro-Caribbean youth. Specifically, we aimed to estimate the relative risk for having EBP/HTN among participants with putative CVD risk factors, and to evaluate whether there were significant sex differences in risk factors for EBP/HTN. Methods Data sources We conducted a cross-sectional analysis using data from the third follow up of the Jamaica 1986 Birth Cohort Study (Ferguson et al., 2010a; McCaw-Binns et al., 2011). This study is a longitudinal study of persons, born in Jamaica in September and October of 1986, and who were a part of the Jamaica Perinatal Mortality Survey (Ashley, McCaw-Binns & Foster-Williams, 1988). Details on this cohort have been previously published (Bennett et al., 2014; McCaw-Binns et al., 2011). For this analysis, we used data from 409 males and 489 females, 18–20 years old, collected in the third follow up of the cohort between March 2005 and February 2007. The study was approved by the University of the West Indies/Faculty of Medical Sciences Ethics Committee. Participants provided written informed consent prior to measurements being done. Measurements and definitions All data collection and measurements were done by trained research nurses. We obtained data on demographic characteristics, general health, medical history, behavioural health risk factors and socioeconomic status via questionnaire. Additionally, we obtained anthropometric and BP measurements and performed venepuncture for analysis of blood glucose, lipids, insulin and creatinine. A timed urine sample was obtained for measurement of urinary albumin excretion. BP was measured with a mercury sphygmomanometer after the participant had been seated for 5 min. BP measurement followed a standardized protocol developed for the International Collaborative Study of Hypertension in Blacks (Ataman et al., 1996). Three BP measurements were taken at 1-minute intervals, with the mean of the second and third measurements being used for analysis. EBP/HTN was defined as SBP ≥120 mmHg or DBP of ≥80 mmHg, corresponding to the prehypertension and hypertension categories of JNC 7 and the elevated BP and hypertension categories of the 2017 ACC/AHA guidelines (Chobanian et al., 2003; Whelton et al., 2017). None of the participants were on medication for elevated blood pressure at the time of assessment. Weight was measured using a portable digital scale, which was calibrated daily. Height was measured using a portable stadiometer. Waist and hip circumference were measured using a non-stretchable nylon tape measure. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in metres and BMI categories defined using the World Health Organization categories: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5–24.9 kg/m2), overweight (BMI 25.0–29.9 kg/m2), obese (BMI ≥30 kg/m2) (World Health Organization, 1995). The normal weight category was used as the reference group. Central obesity was defined as a waist circumference ≥80 cm for women and ≥94 cm for men as recommended for African Origin populations in the 2009 Consensus Criteria for the Metabolic Syndrome (Alberti et al., 2009). Waist-to-hip ratio was calculated by dividing waist circumference by hip circumference. High waist-to-hip ratio was defined using cut-points recommended by Lean, Han & Morrison (1995) as ≥0.95 for males and ≥0.80 for females. Venous blood was collected after an overnight fast of at least eight hours. Samples were analysed using standard laboratory protocols for measurement of fasting glucose, lipids, fasting insulin and serum creatinine. White blood cell count and high sensitivity C-reactive protein (hsCRP) were measured as markers of inflammation. Details of laboratory procedures have been previously published (Bennett et al., 2014; Ferguson et al., 2010a; Rocke et al., 2015; Tulloch-Reid et al., 2010). In brief, glucose was measured using the glucose oxidase method (Alcyon, Analyzer); total cholesterol, triglycerides, and high density lipoprotein cholesterol (HDL) were measured directly using enzymatic methods (Abbott Spectrum Analyzer), while low density lipoprotein cholesterol (LDL) was calculated using the Friedewald equation (total cholesterol−HDL−[TG/2.18], with all concentrations given in mmol/L). Serum creatinine was measured using Jaffe’s reaction on the Alcyon 300 Chemistry Analyser (Abbott, Chicago, IL, USA), while fasting insulin was measured using a chemiluminescent immunoassay (IMMULITE; Diagnostic Products Corporation, Los Angeles, CA, USA); hsCRP was measured using an IMMULITE immunoassay (Siemens Medical Solution Diagnostics, Los Angeles, CA). Microalbumin was measured from a timed urine specimen using a chemiluminescent immunoassay method using the IMMULITE Immunoassay System (Siemens, Los Angeles, CA). Elevated glucose (≥5.6 mmol/L), elevated triglycerides (≥1.7 mmol/L) and low levels of high density lipoprotein cholesterol [HDL] (<1.0 mmol/L for males and <1.3 mmol/L for females) were defined using the metabolic syndrome criteria (Alberti et al., 2009). High total cholesterol (≥5.2 mmol/L) and high levels of low density lipoprotein [LDL] cholesterol (≥4.1 mmol/L) were defined using the National Cholesterol Education Program Adult Treatment Panel III (ATP III) criteria (Expert Panel on Detection Evaluation and Treatment of High Blood Cholesterol in Adults, 2001). For analyses including glucose and triglycerides values in the upper quintile of the distribution were defined as elevated, because the proportion of participants meeting the metabolic syndrome cut-points was very small, thus resulting in too few participants for multivariable analyses. High hsCRP was defined as >3.0 mg/L, with values >10 mg/L set to missing, as recommended by the American Heart Association and Centers for Disease Control (Pearson et al., 2003). Insulin resistance was estimated using the Homeostasis Model Assessment (HOMA-IR) equations (Matthews et al., 1985). Values for HOMA-IR were log transformed to account for non-normal distribution. Elevated HOMA-IR was classified as being in the upper quintile of the log-HOMA-IR. For this paper we chose to dichotomize these characteristics in order to quantify the effect of being in an abnormal (high risk) category and facilitate the tailoring of public health messages aimed at risk reduction. Urine albumin and creatinine levels were used to calculate the albumin to creatinine ratio (ACR) and elevated urine albumin defined as ACR ≥30 mg/g as recommended by the 2012 Kidney Disease Improving Global Outcomes (KDIGO) Guidelines (Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group, 2013). Socioeconomic status was assessed using data collected using a locally developed questionnaire on parental education and occupation, and number of household possessions. The specific questionnaire items are included in the supplementary files available online. Data on education was collected as the highest level of education attained by either parent or guardian and then categorized as: post-secondary, secondary, or less than secondary. In Jamaica, children are required to complete a mandatory six years of elementary school (Grades 1–6) and five years of high school (Grades 7–11 or first to fifth form), after which they graduate from high school. Children may spend an extra two years in sixth form (Grades 12 and 13) before going on to university or college. In this classification, post-secondary education includes persons who completed college or university and persons with vocational training obtained after completing high school. Secondary education indicates persons who completed high school (up to grade 11) and less than secondary includes persons who did not complete high school (i.e., high school education up to grade 10 or below). Occupational categories were defined using the occupation of the household head and coded using the Jamaica Standard Occupational Classification (JSOC) (Statistical Institute of Jamaica, 1995). For this report occupation categories were classified as professionals or managers, office, service or trade workers, and semi-skilled or unskilled workers. For household possessions, participants were asked to indicate whether they had items from a list of 17 household possessions and given one point for each item. They were then classified in three possession score categories based on the distribution of items: low (0–9 items), moderate (10–14 items), and high (15–17 items). The list of items included in the possession score is shown Table S1. Cut-points for this classification was chosen based on the finding that the majority of participants had 10–14 items, so that the groups with 0–9 items would represent the lower end of the distribution and 15–17 items the upper end of the distribution. Data on physical activity, smoking (cigarettes or marijuana) and alcohol consumption were also collected via questionnaire. For smoking, participants were classified as current smokers or non-smokers, while for alcohol consumption participants were classified as: ‘never drank alcohol’, ‘rarely drinks alcohol’ (<1 time per week), ‘drinks alcohol 1–2 times per week’, or ‘drinks alcohol ≥3 times per week’. Physical activity was classified based on the time spent doing sports or exercise during leisure time using a locally developed questionnaire. Questionnaire items included questions on time spent doing active sports or other activities such as brisk walking, jogging, lifting weights, dance classes, and workout at a gym. The specific questionnaire items are included in the online supplementary files. Physical activity assessed using this questionnaire was shown to be more strongly associated with measures of obesity than the International Physical Activity Questionnaire (IPAQ) (Younger et al., 2007). Participants with no leisure time physical activity were classified as low physical activity level, those with <3.5 h per week as moderate physical activity level and those with 3.5 h or more per week as high physical activity level. Sample size and power Given that we had a fixed available sample size of 409 males and 489 females and that we performed sex-specific analyses, we estimated the maximum detectable odds ratio instead of sample size. These estimates were computed for males and females, separately, using the power twoproportions command available in Stata 14 (StataCorp, 2015c). We estimated the prevalence of the outcome variable (EBP/HTN), from the sample at 30% for males and 13% for females, and used these and the available sample size to compute the maximum detectable odds ratio for exposures, with proportion exposed ranging from 0.1 to 0.5 for power of 80% at the 5% significance level. For males, the given sample size of 409 had 80% power to detect odds ratio of 1.84 if the proportion exposed was 0.5 and 2.13 if the proportion exposed was 0.2. For females the given sample size of 489 had 80% power to detect odds ratio of 2.02 if the proportion exposed was 0.5 and 2.34 if the proportion exposed was 0.2. Statistical methods We performed data analysis with Stata version 14 .1 software (Stata Corp., College Station, TX, USA). We obtained descriptive statistics (means and proportions) for outcome and explanatory variables within and across sex and blood pressure categories. If data were highly skewed, we reported the median and interquartile range instead of the mean and standard deviation. Proportions were compared using the Pearson’s chi-squared test or Fisher’s exact tests, as appropriate. Differences in means were compared using the unequal variance two sample t-test. Differences in medians were compared using the non-parametric equality of median test available in Stata (StataCorp, 2015a). Logistic regression and two-way analysis of variance (ANOVA) models were used to determine if there was evidence for sex interaction in the relationship between BP and some of the explanatory variables. Results for analyses assessing interaction using the logistic regression models are shown in Table S2. There was evidence for sex interaction in the relationship between EBP/HTN and some of risk factors (obesity, central obesity and household possessions), therefore we report sex-specific results for regression analyses. We used multiple imputation by chained equations to account for missing data for some explanatory variables. The proportion of complete cases, i.e., participants with no missing values for any of the variables of interest, was 43% (n = 384); The majority of incomplete cases (30% of participants) had only had one missing value; 14% had two missing values, 7% had three missing values and 7% had more than three missing values. Details on the number of missing values for each variable are shown in Table S3. A comparison of the complete cases vs. the incomplete cases revealed only minor differences. Participants with missing values were more likely to have albuminuria, fewer household possessions, lower physical activity and lower alcohol consumption, but had no statistically significant differences for any other characteristics. Given the proportion of participants with at least one missing value and the observed differences between complete and incomplete cases, multiple imputation was used to improve the power of the study and reduce bias that may be seen in the complete case analysis (Nguyen, Carlin & Lee, 2017; White, Royston & Wood, 2011). A stacked multiple imputed data set, consisting of the original dataset and 25 data sets with imputations for missing values, was created using Stata’s mi suite of commands (StataCorp, 2015b). We compared imputed variable values to the observed values to ensure that the imputed values were plausible; these data are shown in Table S4. Bivariate logistic regression was used to assess the association between EBP/HTN and individual explanatory variables. These bivariate models were estimated using Stata’s mi suite of commands and estimates combined by the software using Rubin rules (Marshall et al., 2009; StataCorp, 2015b). For use in model selection, we extracted the first of the 25 imputed data sets and performed regular binary logistic regression on the single-imputed data, as recommended by Wood, White and Royston (Wood, White & Royston, 2008). We used the backwards stepwise regression algorithm available in Stata to identify variables for inclusion in the final model. All variables hypothesized to be associated with the outcome were included in the first multivariable model and p-value > 0.2 was used to remove variables from the model. We then used the Pearson and Hosmer-Lemeshow tests for goodness-of-fit to assess the models. Finally, we used Akaike information criterion (AIC) to determine whether to include or exclude specific variables from the final models. Final multivariable models were then run on the multiple imputed data set with 25 imputations, using Stata’s mi suite of commands and estimates combined by the software using Rubin rules (Marshall et al., 2009; StataCorp, 2015b). To assess the potential impact of the imputed values on the final conclusions we also re-ran the final models without imputations (i.e., complete case analysis); these results are shown in Table S5. Results Summary statistics for demographic and biomedical measurements are shown in Table 1. Mean age at the time of the study was 18.8 years (SD = 0.61), with no sex difference. Compared to females, males had higher mean weight, height, SBP, DBP, fasting glucose, triglycerides and creatinine, while females had higher mean total cholesterol, LDL and HDL cholesterol. Females also had higher median hsCRP, fasting insulin concentration and HOMA-IR. Comparisons of participants’ characteristics by BP categories are shown in Table S6. Overall, participants with EBP/HTN tended to have higher mean values of CVD risk factors. Table 1: Mean or median values for participant characteristics and putative hypertension risk factors for males, females and both sexes. Characteristic Male n = 409 Mean ± SD Female n = 489 Mean ± SD Both sexes N = 898 Mean ± SD Age (years) 18.8 ± 0.59 18.8 ± 0.62 18.8 ± 0.61 Weight (kg)*** 71.1 ± 14.2 62.4 ± 15.5 66.4 ± 15.5 Height (cm)*** 176.8 ± 6.5 163.6 ± 6.1 169.6 ± 9.1 Body mass index (kg/m2) 22.7 ± 4.3 23.3 ± 5.6 23.0 ± 5.0 Systolic blood pressure (mmHg)*** 113.9 ± 10.4 107.4 ± 8.8 110.3 ± 10.1 Diastolic blood pressure (mmHg)*** 69.2 ± 10.3 66.9 ± 9.2 67.9 ± 9.8 Waist circumference (cm) 75.2 ± 10.8 73.9 ± 12.1 74.5 ± 11.5 Hip circumference (cm)** 94.4 ± 8.9 96.5 ± 11.0 95.5 ± 10.2 Waist-to-Hip ratio*** 0.80 ± 0.08 0.77 ± 0.14 0.78 ± 0.12 White blood cell count (cells × 109/L)*** 5.3 ± 1.6 6.4 ± 2.0 5.9 ± 1.9 Fasting glucose (mmol/L)*** 4.7 ± 0.6 4.4 ± 0.4 4.6 ± 0.5 Total cholesterol (mmol/L)*** 4.1 ± 0.8 4.5 ± 0.9 4.3 ± 0.9 HDL cholesterol (mmol/L)*** 1.1 ± 0.2 1.2 ± 0.3 1.2 (0.3) LDL cholesterol (mmol/L)*** 2.7 ± 0.7 3.0 ± 0.8 2.9 ± 0.8 Triglycerides (mmol/L)* 0.60 ± 0.26 0.56 ± 0.26 0.58 ± 0.26 Creatinine (µmol/L)*** 80.5 ± 16.0 56.9 ± 25.5 67.7 ± 24.7 Median (IQR) Median (IQR) Median (IQR) Urinary albumin (mg/g)* 3.9 (2.5, 7.4) 4.9 (2.5, 10.7) 4.1 (2.5, 9.2) hsCRP (mg/L)*** 0.5 (0.3, 1.3) 0.9 (0.3, 2.3) 0.7 (0.3, 1.8) Fasting insulin (pmol/L)*** 4.4 (2.7, 7.1) 6.8 (4.1, 10.1) 5.8 (3.3, 8.8) HOMA-IR*** 0.6 (0.3, 0.9) 0.9 (0.5, 1.3) 0.7 (0.4, 1.1) DOI: 10.7717/peerj.4385/table-1 Notes: *p < 0.05. **p < 0.01. ***p < 0.001. SD standard deviation HDL high density lipoprotein LDL low density lipoprotein IQR interquartile range (values correspond to the 25th and 75th centiles) hsCRP high sensitivity C-reactive protein HOMA-IR Homeostasis Model Assessment—Insulin Resistance Differences in means were compared using the two-sample t test with unequal variances, while the differences in medians were computed using the nonparametric equality-of-medians test. Proportions of participants with EBP/HTN and other CVD risk factors, expressed as categorical variables, are shown is Table 2. Overall prevalence of EBP/HTN was 21% and was twice as high in men compared to women (30% vs. 13%, p < 0.001). The prevalence of elevated BP (SBP 120–129 mmHg, DBP <80 mmHg) was 9% (13% among males and 5% among females, p < 0.001), while hypertension (BP ≥130/80 mmHg) prevalence was 12% (17% among males and 8% among females, p < 0.001). Prevalence of obesity was 8% (6% among males and 10% among females, p = 0.008). The majority of participants were from middle-income households, with the household head having completed secondary level education and working as office, service, or trade workers. Low physical activity level was reported by 34% of participants and high physical activity by 24%. There were significant sex differences in physical activity among males compared to females (p < 0.001) with 47% of females reporting low physical activity levels compared to 18% among males, while high physical activity was reported by 38% of males compared to 13% among females. Cigarette smoking was reported by 14% of males and 6% of females (p < 0.001), while 31% of males and 7% of females smoked marijuana (p < 0.001). Males also reported higher levels of moderate (≥3 times/week) alcohol consumption (38% vs. 19%, p < 0.001). Similar analyses stratified by BP category are shown in Table S7. Significant difference by blood pressure category were seen for BMI categories, central obesity and waist-to-hip ratio among males, and for number of household possessions among females. Table 2: Proportion of participants in categories for blood pressure and other CVD risk factors for males, females and both sexes. Characteristic Male n = 409 % (n) Female n = 489 % (n) Both sexes N = 898 % (n) Elevated BP or hypertension (BP ≥120/80 mmHg)*** 29.8 (122) 13.4 (66) 20.9 (188) Elevated BP (SBP120–129 & DBP <80 mmHg)*** 13.2 (54) 5.3 (26) 8.9 (80) Hypertension (BP ≥130/80)*** 16.6 (68) 8.2 (40) 12.0 (108) Stage 1 hypertension (BP 130–139/80–89)*** 14.7 (60) 7.4 (36) 10.7 (96) Stage 2 hypertension (BP ≥140/90) 2.0 (8) 0.8 (4) 1.3 (12) Albuminuria 5.1 (20) 8.3 (39) 6.8 (59) Body mass index categories*** Underweight (<18.5 kg/m2) 6.1 (25) 14.5 (71) 10.7 (96) Normal weight (18.5–24.9 kg/m2) 76.3 (308) 55.2 (270) 64.4 (578) Overweight (25–29.9 kg/m2) 13.0 (53) 19.8 (87) 16.7 (150) Obese (≥30 kg/m2) 5.6 (23) 10.4 (51) 8.2 (74) Central obesitya,*** 5.1 (21) 24.4 (119) 15.6 (140) High waist-to-hip ratiob,*** 1.0 (4) 20.3 (99) 11.5 (103) Highest Education of Parent/Guardianc Post-secondary 26.2 (89) 29.8 (131) 28.2 (220) Secondary 61.8 (210) 55.4 (243) 58.2 (453) Less than secondary 12.1 (41) 14.8 (65) 13.6 (106) Occupation of household head Professionals/Managers 23.5 (88) 24.7 (114) 24.1 (202) Office, service or trade workers 49.3 (185) 50.9 (235) 50.2 (420) Semi-skilled/Unskilled workers 27.2 (102) 24.5 (113) 25.7 (215) Number of household possession High (15–17 items) 16.9 (69) 13.7 (67) 15.2 (136) Moderate (10–14 items) 56.9 (232) 54.2 (265) 55.4 (497) Low (0–9 items) 26.2 (107) 32.1 (157) 29.4 (264) Physical activity level*** High 37.5 (153) 13.1 (64) 24.2 (217) Moderate 44.4 (181) 39.5 (193) 41.7 (374) Low 18.1 (74) 47.4 (232) 34.1 (306) Current cigarette smoking*** 13.7 (56) 6.1 (30) 9.6 (86) Current marijuana smoking*** 31.3 (127) 7.2 (35) 18.1 (162) Alcohol consumption*** Never drank alcohol 6.4 (26) 13.2 (64) 10.1 (90) Rarely drinks alcohol 26.4 (107) 45.2 (219) 36.6 (326) Drinks alcohol 1–2 times/week 29.1 (118) 22.3 (108) 25.4 (226) Drinks alcohol≥3 times/week 38.0 (154) 19.4 (94) 27.9 (248) DOI: 10.7717/peerj.4385/table-2 Notes: *p < 0.05. **p < 0.01. ***p < 0.001. BP blood pressure SBP systolic blood pressure DBP diastolic blood pressure CVD cardiovascular disease aCentral obesity defined as waist circumference ≥94 cm in males and ≥80 cm in females. bHigh waist-to-hip ratio ≥0.95 for males and ≥0.80 for females. cEducation category “post-secondary” includes persons with vocational training, college, or university education; secondary corresponds to high school (up to grade 11); less than secondary corresponds to persons who had only elementary school education or persons who did not complete high school (i.e., high school grade 10 or below). The results from bivariate analyses yielding sex specific odds ratios for the relationship between correlates and putative risk factors for EBP/HTN are shown in Table 3. Factors associated with EBP/HTN among males in bivariate analyses were: age, obesity, central obesity, high glucose, high triglycerides and high HOMA-IR. Among females, significant correlates were age, height, high triglycerides, high HOMA-IR and number of household possessions. There were no significant associations for general or central obesity among females, and no significant associations for measures of inflammation (hsCRP and white blood cell count) or urine albumin excretion in either sex. Table 3: Odds ratio for elevated blood pressure or hypertension for putative risk factors among male and female participants in the 1986 Jamaica Birth Cohort. Males n = 409 Females n = 489 Variable Odds ratio 95% CI P-value Odds ratio 95% CI P-value Age (years) 1.48 1.03–2.12 0.034 2.16 1.41–3.31 <0.001 Height (cm) 1.02 0.98–1.05 0.305 1.06 1.01–1.11 0.009 BMI Category Normal weight (18.5 –24.9 kg/m2) 1.0 – – 1.0 – – Underweight (<18.5 kg/m2) 0.52 0.17–1.58 0.250 1.31 0.61–2.83 0.489 Overweight (25–29.9 kg/m 2) 1.54 0.83–2.85 0.169 1.58 0.82–3.05 0.172 Obese (≥30 kg/m2) 7.81 2.98–20.48 <0.001 1.95 0.89-4.29 0.097 Central obesitya 6.57 2.48–17.36 <0.001 1.54 0.88–2.72 0.132 High glucose (upper quintile) 2.14 1.35–3.39 0.001 1.20 0.48–3.01 0.693 High cholesterol (≥5.2 mmol/l) 1.77 0.88–3.56 0.110 1.62 0.88–2.97 0.120 High LDLb (≥4.1 mmol/l) 1.31 0.43–4.00 0.634 1.25 0.53–2.94 0.611 Low HDLc 1.11 0.67–1.83 0.694 1.24 0.71–2.17 0.449 High triglycerides (upper quintile) 1.80 1.08–2.99 0.024 1.96 1.10–3.51 0.023 Creatinine (µmol/L) 0.99 0.98–1.01 0.421 1.00 0.99–1.01 0.840 HOMA-IRd (log, upper quintile) 3.46 1.83–6.57 <0.001 1.81 1.01–3.26 0.046 White blood cell count 1.02 0.89–1.17 0.781 1.12 0.99–1.27 0.084 Albuminuria 1.25 0.49–3.17 0.641 1.14 0.46–2.82 0.784 High hsCRPe 1.00 0.44–2.28 1.000 1.51 0.79–2.88 0.214 Parental education Post–secondary 1.0 – – 1.0 – – Secondary 0.92 0.54–1.59 0.777 1.29 0.68–2.46 0.433 Less than secondary 0.90 0.40–2.05 0.800 1.22 0.52–2.89 0.646 Occupation of household head Professionals/Managers 1.0 – – 1.0 Office, service or trade 0.74 0.43–1.28 0.279 1.36 0.65–2.83 0.416 Semi–skilled/Unskilled 0.89 0.48–1.63 0.702 1.83 0.95–4.50 0.067 No. of household possession High (15–17 items) 1.0 – – 1.0 – – Moderate (10–14 items) 0.58 0.33–1.02 0.061 4.36 1.31–14.51 0.016 Low (0–9 items) 0.81 0.43–1.53 0.515 2.76 0.79–9.72 0.113 Physical activity level High 1.0 – – 1.0 – – Moderate 0.83 0.52–1.32 0.425 0.82 0.38–1.75 0.605 Low 0.71 0.38–1.32 0.280 0.63 0.30–1.36 0.243 Current cigarette smoking 1.05 0.57–1.94 0.879 0.99 0.33–2.92 0.978 Current marijuana smoking 0.99 0.63–1.57 0.991 0.82 0.28–2.39 0.711 Alcohol consumption Never drank alcohol 1.0 – – 1.0 — – Rarely drinks alcohol 1.01 0.39–2.67 0.978 0.60 0.29–1.24 0.166 Drinks 1–2 times/week 1.35 0.52–3.48 0.534 0.58 0.26–1.34 0.205 Drinks≥3 times/week 1.16 0.45–2.94 0.762 0.47 0.19–1.14 0.095 DOI: 10.7717/peerj.4385/table-3 Notes: aCentral obesity defined as waist circumference ≥ 94 cm in males and ≥80 cm in females. bLDL, low density lipoprotein cholesterol. Estimates for high LDL did not include imputed values, due to high correlation with high cholesterol leading to potential problems with perfect prediction in imputation models. cHDL, high density lipoprotein; Low HDL defined as <1.0 mmol/L for males and <1.3 mmol/L for females. dHOMA-IR, Homeostasis Model Assessment–Insulin Resistance. ehsCRP, high sensitivity C-reactive protein; absolute value for odds ratio for males = 0.9998. We did not compute odds ratios for elevated waist-to-hip ratio given the very small number of males (n = 4) with high waist to hip ratio. Results from the multivariable regression models are shown in Table 4. Models included variables as shown in the table and were done separately for males and females. Modifiable risk factors associated with higher odds of EBP/HTN among males were: obesity (OR 8.48, 95%CI [2.64–27.2], p < 0.001) and high glucose (OR 2.01, CI [1.20–3.37], p = 0.008). High HOMA-IR was also associated with higher odds of EBP/HTN among males, but did not achieve statistical significance (OR 2.08, CI [0.94–4.58], p = 0.069). Among females, modifiable risk factors associated with higher odds of EBP/HTN were: high triglycerides (OR 1.98, CI [1.03–3.81], p = 0.040), high HOMA-IR (OR 2.07, CI [1.03–4.12], p = 0.039) and lower SES (OR 4.63, CI [1.31–16.4], p = 0.017 [moderate vs. high household possessions]. OR for low vs. high household possessions was 2.61, CI [0.70–9.77], p = 0.154. The point estimates for obesity among females suggested higher odds of EBP/HTN, but this was not statistically significant (OR 1.44 CI [0.58–3.56], p = 0.436). Additionally, age was positively associated with EBP/HTN in both sexes and height in females only. Physical activity was inversely associated with EBP/HTN in both males and females with OR of 0.49 (CI [0.24–0.97]) and 0.42 (CI [0.18–0.97]) for low vs high physical activity level for males and females, respectively. Among women only, alcohol consumption was inversely related to EBP/HTN. Compared to those who never drank alcohol odds ratio for alcohol consumption <1 time per week was 0.41 (CI [0.18–0.90], p = 0.026), while for those report alcohol consumption ≥3 times per week odds ratio were 0.28 (CI [0.11–0.76] p = 0.012). Findings for the complete case analysis with models including 306 males and 409 females (Table S5) were generally similar to that obtained with multiple imputation, however estimates had wider confidence intervals and larger p-values, several of which did not achieve statistical significance. Table 4: Factors associated with elevated blood pressure or hypertension (BP ≥120/80) in multivariable logistic regression models among male and female young adults in the Jamaica 1986 Birth Cohort. Males (n = 409) Females (n = 489) Variable Odds ratio 95% CI P-value Odds ratio 95% CI P-value Age (years) 1.74 1.16–2.61 0.007 2.55 1.60–4.08 <0.001 Height (cm) – – – 1.07 1.02–1.12 0.003 BMI category Normal weight (18.5–24.9 kg/m2) 1.0 – – 1.0 – – Underweight (<18.5 kg/m2) 0.64 0.20–2.00 0.441 1.70 0.74–3.91 0.211 Overweight (25–29.9 kg/m2) 1.76 0.90–3.43 0.096 1.31 0.63–2.72 0.461 Obese (≥30 kg/m2) 8.48 2.64–27.2 <0.001 1.44 0.58–3.56 0.436 High Glucose (upper quintile) 2.01 1.20–3.37 0.008 – – – High Triglycerides (upper quintile) – – – 1.98 1.03–3.81 0.040 HOMA-IR (log transformed, upper quintile) 2.08 0.94–4.58 0.069 2.07 1.03–4.12 0.039 High hsCRP 0.45 0.17–1.17 0.101 – – – White blood cell count – – 1.14 0.99–1.31 0.076 Household possessions High (15–17 items) 1.0 – – 1.0 – – Moderate (10–14 items) 0.62 0.33–1.18 0.147 4.63 1.31–16.4 0.017 Low (0–9 items) 1.21 0.59–2.45 0.604 2.61 0.70–9.77 0.154 Physical activity level High physical activity level 1.0 – – 1.0 – – Moderate physical activity level 0.55 0.33–0.93 0.026 0.71 0.31–1.65 0.429 Low physical activity level 0.49 0.24–0.97 0.042 0.42 0.18–0.97 0.043 Alcohol consumption Never drank alcohol – - – 1.0 – – Rarely drinks alcohol (