Relation of arterial stiffness to left ventricular structure and function in healthy women

Jing Zhang
Philip J Chowienczyk
Tim D Spector
Benyu Jiang
Relation of arterial stiffness to left ventricular structure and function in healthy women
10.1186/s12947-018-0139-6R E S E A R C H Open Access
Background: Interactions between the left ventricular (LV) and the arterial system, (ventricular-arterial coupling)  are key determinants of cardiovascular function. However, most of studies covered multiple cardiovascular risk factors, which also contributed to the morphological and functional changes of LV. The aim of this study was to examine the relationship between arterial stiffness and LV structure and function in healthy women with a low burden of risk factors. Methods: Healthy women from the Twins UK cohort (n = 147, mean age was 54.07 ± 11.90 years) were studied. Arterial stiffness was evaluated by carotid-femoral pulse wave velocity (cf-PWV). LV structure and function were assessed by two-dimensional speckle tracking echocardiography. Results: cf-PWV was significantly associated with most measures of LV geometry and function, including relative wall thickness (RWT), E/e' ratio, global circumferential and radial strain, apical rotation and LV twist (each p < 0.05), but bore no relation to global longitudinal strain. After adjustment for age, body mass index, blood pressure and heart rate, cf-PWV was significantly correlated with RWT, global circumferential strain, apical rotation and LV twist (β = 0.011, − 0.484, 1.167 and 1.089, respectively, each p ≤ 0.05).Conclusions:In healthy women with a low burden of risk factors, elevated arterial stiffness was intimately interwoven with increased LV twisting even before LV dysfunction becomes clinically evident.

Background

Arterial stiffening and ventricular remodeling are considered features of cardiovascular ageing [1]. However, the extent to which ventricular remodeling and alteration in ventricular function may be secondary to arterial stiffening is uncertain. Previous studies suggested that aortic stiffening is associated with an increased risk for heart failure with preserved ejection fraction, even in the absence of cardiovascular risk factors [2,3]. Various associations between arterial stiffness and left ventricular (LV) structure and function have been demonstrated. However, most of these studies were conducted in subjects with multiple cardiovascular risk factors, such as hypertension, diabetes, aortic stenosis or obesity [4][5][6] that may independently influence LV and arteries. Therefore, studies are warranted to examine the relationship between arterial stiffness and LV structure and function in healthy populations without cardiovascular risk factors.

Although, several echocardiographic studies have shown the relationship between arterial stiffness and LV diastolic dysfunction in healthy populations [1,3], however, reports regarding the relationship between arterial stiffness and left ventricular myocardial deformation (stain and twist) in healthy populations are scarce. In the present study we examined the relationship between the arterial stiffness and LV structure, diastolic function, systolic stain and twist by using two-dimensional speckle tracking echocardiography in the healthy women with low burden of cardiovascular risk factors from the Twins UK cohort.

Methods

Study population

The study population was comprised of a sub-sample of 200 consecutively recruited women from the Twins UK cohort with characteristics similar to the general U.K. population [7] who participated in a longitudinal study on cardiovascular ageing. Women with risk factors requiring treatment, known ischemic heart disease, atrial fibrillation or significant valvular heart disease and those in whom adequate image quality could not be obtained were excluded, leaving 147 healthy women. Haemodynamic measurements were performed in a quiet temperature-controlled laboratory (22°C to 24°C). The study was approved by St. Thomas' Hospital Research Ethics Committee and written informed consent was obtained from all subjects.

Blood pressure and carotid-femoral pulse wave velocity (cf-PWV)

Brachial blood pressure was measured in duplicate, by using a validated oscillometric monitor (Omron 705 CP, Omron, Tokyo, Japan) after subjects had rested in a supine position for at least 10 min. cf-PWV was measured using sequential carotid-femoral ECG-referenced applanation tonometry using the SphygmoCor system (Atcor Medical, Sydney, Australia). The path distance between the carotid and femoral sites was estimated from the distance between the sternal notch and femoral artery at the point of applanation. At least two sequential measurements satisfying the inbuilt quality control criteria of the SphygmoCor system were obtained and the mean value was used for analysis.

Echocardiography

A transthoracic echocardiographic examination was performed in the left lateral decubitus position using a Vivid-7 ultrasound scanner with an M3S cardiac probe (General Electric Healthcare, Milwaukee, WI, USA). Two-dimensional views were obtained via the apical (4-, 2-chamber, and long-axis views) and parasternal (short-axis views at mitral valve, papillary muscle, and apical levels) approaches. Three consecutive cardiac cycles of each view were acquired during end-expiration breath holding and stored digitally on a hard disk for offline analysis. All images were obtained at a frame rate of 50 to 80 frames per second. Time of aortic valve closure was assessed by aortic valve motion in the apical long-axis view.

Echocardiographic measurements were obtained offline on a PC work-station by using a commercially available analysis software package (EchoPAC, version 11, GE Healthcare, Norway). LV end-diastolic dimension (LVED), end-systolic dimension (LVES), end-diastolic septal thickness (IVSd) and end-diastolic LV posterior wall thickness (LVPWd) were measured from a parasternal long-axis view in accordance with recommendations of the American Society of Echocardiography [8]. LV mass (LVM), LV mass index (LVMI) and relative wall thickness (RWT) were calculated according to standard formula. LV end-systolic, end-diastolic volumes and LV ejection fraction (LVEF) were measured using the biplane Simpson's method.

Transmitral flow velocity was obtained from the apical 4-chamber view using pulsed Doppler. The peak early diastolic velocity (E), peak atrial systolic velocity (A), and E/A ratio were measured. Peak motion velocity in early diastolic (e') and atrial contraction (a') were measured by tissue Doppler imaging (TDI) at all basal segments from apical 4-and 2-chamber views. Measurements were averaged over all segments.

Two-dimensional speckle tracking echocardiography

Two-dimensional speckle tracking imaging was performed on three apical views and parasternal short-axis views of the LV. The endocardial border of the LV was defined by placing several points along it and the width of interest was then adjusted to accommodate myocardial thickness. The image analysis software identified natural acoustic markers that moved with the tissue. Automatic frame-by-frame tracking of these markers during the cardiac cycle yielded a strain value and a strain rate. Each LV view was divided into 6 equal segments, providing strain and strain rate curves for these segments.

Global longitudinal strain (GLS) measurements were obtained on 3 apical views. The global circumferential and radial strain (GCS, GRS) measurements were acquired on the short-axis view at papillary muscle level. The systolic peak of strain values between aortic valve opening and closing was determined. Rotation parameters were measured in short-axis views at mitral valve level (basal rotation, BaseRot) and apical level (apical rotation, ApexRot). Basal-to-apical LV twist was defined as the net difference between apical and basal rotations at the aortic valve closing. Intra-and inter-observer variability of LV strain, rotation and twist were measured in 15 subjects.

Statistical analysis

Statistical analyses were performed using SPSS (version 16.0, SPSS, Inc., Chicago, Illinois). Continuous variables were presented as means ± standard deviation (SD). The sample was divided into 3 groups according to tertiles of the distribution of cf-PWV. Differences between groups were evaluated by one-way analysis of variance (ANOVA). Bivariate correlations between cf-PWV and LV structural and functional measurements were assessed by Pearson's correlation coefficient. Multivariate linear regression analysis was then applied to examine the independence of association between cf-PWV and LV measurements after adjustment for age, BMI, blood pressure (systolic blood pressure and pulse pressure) and heart rate. Intra-and inter-observer variability of LV strain and twist were assessed using intra-class correlation coefficients (ICC) with 95% confidence intervals and coefficient of variation (expressed as the mean ± standard deviation of the absolute differences between the two measurements divided by the mean value (%)). A p-value < 0.05 was considered statistically significant and all tests were 2-tailed.

Results

Demographic and clinical characteristics of the subjects are summarized in Table 1. Mean age was 54.1 ± 11.9 years, mean brachial systolic/diastolic blood pressure were 122 ± 12.5/75 ± 8.8 mmHg and mean cf-PWV was 8.70 ± 1.48 m/s. Echocardiographic parameters are shown in Table 2. To examine the association of arterial stiffness with LV structure and function, subjects were divided into 3 tertiles according to their cf-PWV. RWT, E/e' , GCS, ApexRot and LV twist rose with increasing cf-PWV across the groups (Fig. 1), whereas the E/A ratio and e'/a' ratio showed the opposite change. LVED, LVES, LVMI, LVEF, GRS, GLS and BaseRot were all similar among the 3 groups.

Pearson's correlation analysis showed that cf-PWV was correlated with most measures of LV geometry and function, including RWT, LVED, LVES, E/A, e'/a' , E/e' , GCS, GRS, ApexRot, and LV Twist, but bore no significant relation to LVMI, LVEF, GLS and BaseRot. Figure 2 demonstrated the relationship of cf-PWV to the parameters of LV strain and rotation. However, multivariable linear regression revealed that, when adjusted for age, BMI, systolic blood pressure, pulse pressure and heart rate, cf-PWV was only significantly correlated with RWT, GCS, ApexRot and LV Twist (β = 0.011, − 0.484, 1.167 and 1.089, respectively, each p < 0.05, Table 3).

There was a good reproducibility and consistency in the measurement of the LV strain and twist. Detailed inter-observer and intra-observer variability are shown in Table 4.

Discussion

Arterial stiffening is the hallmark of vascular ageing and, when measured by cf-PWV, is predictive of outcome independent of blood pressure components. cf-PWV is a major determinant of the pulsatile load on the ventricle up to the time of peak, myocardial wall stress and thus may have an effect on ventricular remodeling and ventricular function that is not captured by classical blood pressure components [9,10].

Consistent with previous results [11][12][13][14][15], this study demonstrated cf-PWV to be significantly positively correlated with RWT after adjustment for confounding factors, such as age and blood pressure, thereby supporting the hypothesis that elevated aortic impedance exerts a direct effect on LV concentric remodeling (i.e., increased RWT) in healthy women. With progressive stiffening of the elastic arteries, LV afterload increases because the reflected waves return earlier during systole, thus, leading to myocardial hypertrophy.

Currently, the noninvasive estimation of LV diastolic function is based on conventional echocardiographic and tissue Doppler measurements. LV diastolic dysfunction is mainly characterized by decreased E/A ratio, e'/a' ratio, and enhanced E/e' ratio. Arterial stiffness has been found to be associated with diastolic dysfunction in various populations [2,4,16,17]. However, our study showed that after adjustment for confounding factors, there existed no significant correlation between cf-PWV and LV diastolic dysfunction in women with a low burden of risk factors. This discrepancy may be explained by demographic differences of study subjects since the subjects in this study were younger and healthier with narrow PP and lower cf-PWV. In addition, other confounding factors, such as smoking habits, alcohol consumption, physical activity were not taken into account in our study but might also be contributors.

Results of previous studies on the relationship of arterial stiffness to LV systolic function have varied substantially according to the methods used and populations studied. Arterial stiffness has been associated with sub-clinical LV systolic dysfunction and impaired LV longitudinal function in patients with hypertension [18], type 1 diabetes mellitus [6], and in a general population [19]. However, Myung et al. [20]. found carotid artery stiffness parameter (β) not to correlate with LV systolic function in hypertensive patients.

LV strain and twist, due to their complicated helical myocardial fiber architecture, play important roles in ventricular systolic and diastolic performance. To understand the progression of LV systolic dysfunction at different stages of heart disease, it is important to analyze the BMI body mass index, BSA body surface area, pSBP brachial systolic blood pressure, pDBP brachial diastolic blood pressure, PP pulse pressure, HR heart rate, cf-PWV carotid-femoral pulse wave velocity various components involved in LV deformation. Recently, the angle-independent two-dimensional speckle tracking echocardiography has been successfully used for the measurement of myocardial deformational and rotational parameters. This technique tracks the motion of speckles within the myocardium, allowing complete and accurate assessment of myocardial deformation in all three spatial dimensions. In the present study, we measured LV longitudinal, radial, and circumferential strain and LV twist in healthy women by using speckle tracking echocardiography and found that cf-PWV bore no significant relation to LV longitudinal strain and basal rotation. However, there was a significant positive correlation between cf-PWV and circumferential strain, apical rotation and LV twist after adjustment for confounding factors. Consistent with our findings, previous studies also revealed an increase in LV twisting with increasing aortic stiffness in patients with diabetes, hypertension, and diastolic heart failure [11,21]. The precise mechanisms underlying increased LV twist remain unclear. LV twisting and rotational deformation are directly related to right-and left-handed helical orientations of LV myocardial fibers. Some investigators explained that during systole, counterclockwise rotation of the LV apex, is dictated mainly by the subepicardial fibers, generating high torque and dominates LV torsional forces. The clockwise rotation of the LV base is mainly determined by the subendocardial fibers, which may be vulnerable to increased cf-PWV and The data are expressed as mean ± SD RWT relative wall thickness, LVMI left ventricular mass index, LVEF left ventricular ejection fraction, E peak early diastolic transmitral flow velocity, A peak atrial systolic transmitral flow velocity, e' peak early diastolic mitral annular motion velocity, a' peak atrial systolic mitral annular motion velocity, GCS global circumferential strain, GRS global radial strain, GLS global longitutide strain, BaseRot rotation at basal level, ApexRot rotation at apical level°D egree   associated increased myocardial pressure load and oxygen consumption, resulting in subendocardial injury [22][23][24][25][26]. Such injury may accentuate both LV apical rotation and twist as the subepicardial torque is left unopposed. The discrepancies between our findings and previous studies about the relationship between arterial stiffness and LV GLS may be explained by a relatively low cf-PWV (mean cf-PWV was 8.85 ± 1.75 m/s) in our subjects and certain confounding factors, such as an effect of cardiovascular risk factors on the systolic function.

Our results showed that increased arterial stiffness might contribute to increased LV twist in healthy women with a low burden of risk factors. Given that LV twist is an important determinant of LV function and the change in twist always far precedes irreversible tissue damage [27,28], it can be postulated that increased LV twist might be a compensation for injured sub-endocardium, thereby preserving cardiac contractility. Furthermore, the change in LV twist may serve as an indicator for early LV dysfunction, even before LV diastolic dysfunction or LV GLS depression becomes clinically evident. On the other hand, our study showed a close interaction between cf-PWV and LV twist, thus cf-PWV may be a good tool to assess sub-clinical LV dysfunction, especially when it is used in healthy populations with a low burden of risk factors. More importantly, improving cf-PWV may be a good therapeutic approach to stop the progression of LV dysfunction or to prevent the development of heart failure with preserved ejection fraction. However, further multicenter and prospective studies are required to confirm our hypothesis.

Limitations

The study had some limitations. First, the subjects were limited to female twins, although their lifestyle was similar to the general population of women in the U.K. The applicability of our findings to men or other ethnicities, remains to be confirmed in future studies. Second, our study is cross-sectional, therefore observational nature and causal relationship cannot definitively be established. This is particularly relevant as some of the observed correlations are likely to be bidirectional. In addition, effects of other confounding factors, such as smoking habits, alcohol consumption and physical activity could not be eliminated. Further longitudinal studies are warranted. Third, the results of this study need to be further confirmed by large sample size studies. Moreover, several unproven assumptions are involved in assessment of the relationship between the arterial stiffness and LV dysfunction. Finally, we only used parasternal short-axis view at the level of the papillary muscle to evaluate GRS and GCS, and the exact locations of the basal and apical planes varied from individual to individual, which might cause intrinsic error in the calculation of LV twist.

Conclusions

This study demonstrates that in healthy women with a low burden of risk factors, increased aortic stiffening is associated with an increase in LV twist but is not significantly related to LV diastolic function and global longitudinal strain of LV myocardium. These findings suggest a close interaction between arterial remodeling and LV twisting even before LV dysfunction becomes clinically evident. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions JZ (first author) contributed to study design, images acquisition, data analysis and had a major contribution in writing the manuscript. TS helped in the

Fig. 1
1Comparison of RWT (a) and E/e' (b) in the population subdivided by tertile of cf-PWV Fig. 2 Linear correlation of cf-PWV with the GLS (a), GCS (b), ApexRot (c) and LV twist (d)

BaseRot,°-0.159 (− 0.322, 0.015) 0.072 0.082(− 0.476, 0.641) 0.771 ApexRot,°0.276 (0.108, 0.428) 0.002 1.167 (0.354, 1.980) 0.005 Twist,°0.343 (0.181, 0.487) < 0.001 1.089 (0.193, 1.985) 0.018 a Pearson's correlation analysis b models adjusted for age, BMI, pSBP, PP, HR.°D egree

A: Peak atrial systolic transmitral flow velocity; a': Peak atrial systolic mitral annular motion velocity; ApexRot: Rotation at apical level; BaseRot: Rotation at basal level; cf-PWV: carotid-femoral pulse wave velocity; E: Peak early diastolic transmitral flow velocity; e': Peak early diastolic mitral annular motion velocity; GCS: Global circumferential strain; GLS: Global longitudinal strain; GRS: Global radial strain; IVSd: End-diastolic septal thickness; LV: Left ventricular; LVED: LV end-diastolic dimension; LVEF: LV ejection fraction; LVES: LV end-systolic dimension; LVM: LV mass; LVMI: LV mass index; LVPWd: End-diastolic LV posterior wall thickness; RWT: Relative wall thickness; TDI: Tissue Doppler imaging Funding This work was supported by a British Heart Foundation Project Grant PG/06/032. The Twins UK study was funded by the Welcome Trust, European Community's Seventh Framework Programes (FP-7/2007-2013); and the Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's & St. Thomas' NHS Foundation Trust in partnership with King's College London.

Table 1
1Demographic and clinical characteristics of the study subjects (n = 147)Variable
Mean ± SD

Age, y
54.07 ± 11.90

Height, cm
162.31 ± 6.74

Weight, Kg
64.74 ± 9.55

BMI, Kg/m 2
24.59 ± 3.44

BSA, m 2
1.70 ± 0.14

pSBP, mmHg
122.39 ± 12.53

pDBP, mmHg
74.63 ± 8.79

PP, mmHg
47.91 ± 9.21

HR, bpm
61.54 ± 9.20

cf-PWV, m/s
8.70 ± 1.48

Table 2
2Echocardiographic parameters of the study subjects (n = 147)Variable
total (n = 147)
Lowest cfPWV (n = 49)
Mid cfPWV (n = 49)
Highest cfPW (n = 49)
p

Echocardiographic Characteristics

RWT
0.37 ± 0.07
0.34 ± 0.06
0.36 ± 0.06
0.41 ± 0.07
< 0.001

LVMI, g/m 2
71.82 ± 13.09
69.71 ± 13.43
70.33 ± 13.66
75.38 ± 11.63
0.084

LVED, cm
4.53 ± 0.39
4.60 ± 0.36
4.55 ± 0.40
4.44 ± 0.39
0.132

LVES, cm
2.97 ± 0.33
3.05 ± 0.31
2.94 ± 0.35
2.92 ± 0.32
0.125

LVEF, %
65.38 ± 5.77
64.50 ± 5.00
65.09 ± 6.10
66.29 ± 5.99
0.479

E/A
1.28 ± 0.37
1.44 ± 0.36
1.28 ± 0.40
1.12 ± 0.29
< 0.001

e' / a'
1.21 ± 0.41
1.51 ± 0.37
1.23 ± 0.35
0.93 ± 0.28
< 0.001

E/e'
7.29 ± 1.89
6.56 ± 1.63
7.02 ± 1.50
8.30 ± 2.11
< 0.000

2D Speckle-Tracking Imaging

GCS, %
−22.95 ± 2.81
− 21.92 ± 2.40
−23.08 ± 2.86
−23.75 ± 2.85
0.009

GRS, %
42.86 ± 14.64
45.82 ± 13.32
41.96 ± 13.81
40.97 ± 16.33
0.260

GLS, %
−21.51 ± 1.65
−21.73 ± 1.64
−21.78 ± 1.89
−21.84 ± 1.41
0.955

BaseRot,°−5.91 ± 3.27
−5.22 ± 3.72
−5.96 ± 2.59
−6.50 ± 3.38
0.192

ApexRot,°9.85 ± 4.90
9.08 ± 4.95
9.06 ± 4.72
11.30 ± 4.78
0.046

Twist,°15.72 ± 5.50
14.24 ± 4.81
14.97 ± 4.83
17.78 ± 6.14
0.006

Table 3
3Bivariate correlation and multivariate linear regression between cf-PWV and LV parametersEcho
parameters

Univariate analysis a
Multivariate analysis b

r (95%CI)
p value
β (95%CI)
p value

LV Structure

Table 4
4Interobserver and Intraobserver variability ICC intraclass correlation coefficients, CoV coefficient of variation;Variable
Interobserver
Intraobserver

ICC(95% CI)
CoV(%)
ICC(95% CI)
CoV(%)

GLS
0.896(0.709-0.965)
4.05 ± 2.97
0.895(0.725-0.962)
6.31 ± 4.78

GRS
0.891(0.695-0.964)
18.19 ± 10.72
0.891(0.708-0.962)
15.05 ± 7.51

GCS
0.902(0.723-0.964)
10.93 ± 6.28
0.914(0.771-0.969)
11.89 ± 8.79

BaseRot
0.893(0.687-0.966)
17.38 ± 11.60
0.913(0.760-0.970)
18.87 ± 10.94

ApexRot
0.910(0.734-0.972)
10.93 ± 5.17
0.925(0.815-0.971)
12.02 ± 7.62

Twist
0.921(0.762-0.975)
13.22 ± 11.15
0.959(0.896-0.984)
11.91 ± 7.69

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Effect of age and gender on left ventricular rotation and twist in a large group of normal adults--a multicenter study. J P Sun, Y Y Lam, C Q Wu, X S Yang, R Guo, J S Kwong, Int J Cardio. 167Sun JP, Lam YY, Wu CQ, Yang XS, Guo R, Kwong JS, et al. Effect of age and gender on left ventricular rotation and twist in a large group of normal adults--a multicenter study. Int J Cardio. 2013;167:2215-21.

Effect of aging on twist-displacement loop by 2-dimensional speckle tracking imaging. H Nakai, M Takeuchi, T Nishikage, M Kokumai, S Otani, R M Lang, J Am Soc Echocardiogr. 19Nakai H, Takeuchi M, Nishikage T, Kokumai M, Otani S, Lang RM. Effect of aging on twist-displacement loop by 2-dimensional speckle tracking imaging. J Am Soc Echocardiogr. 2006;19:880-5.

Effects of non-dipper blood pressure pattern on left ventricular rotational mechanics in hypertensive patients with type 2 diabetes mellitus: a speckle tracking study. T Gökdeniz, E Kalaycıoğlu, A Ç Aykan, İ Gül, F Boyacı, M O Gürsoy, Int J Cardiovasc Imaging. 30Gökdeniz T, Kalaycıoğlu E, Aykan AÇ, Gül İ, Boyacı F, Gürsoy MO. Effects of non-dipper blood pressure pattern on left ventricular rotational mechanics in hypertensive patients with type 2 diabetes mellitus: a speckle tracking study. Int J Cardiovasc Imaging. 2014;30:57-65.

Left ventricular twist mechanics and its relation with aortic stiffness in chronic kidney disease patients without overt cardiovascular disease. S Sulemane, V F Panoulas, K Konstantinou, A Bratsas, F W Tam, E A Brown, Cardiovasc Ultrasound. 910Sulemane S, Panoulas VF, Konstantinou K, Bratsas A, Tam FW, Brown EA, et al. Left ventricular twist mechanics and its relation with aortic stiffness in chronic kidney disease patients without overt cardiovascular disease. Cardiovasc Ultrasound. 2016;9:10.

Left ventricular twisting modifications in patients with left ventricular concentric hypertrophy at increasing after-load conditions. A Santoro, F Alvino, G Antonelli, V Zacà, S Benincasa, S Lunghetti, Echocardiography. 31Santoro A, Alvino F, Antonelli G, Zacà V, Benincasa S, Lunghetti S, et al. Left ventricular twisting modifications in patients with left ventricular concentric hypertrophy at increasing after-load conditions. Echocardiography. 2014;31:1265-73.

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BMC Public Health Who is maintaining weight in a middle-aged population in Sweden? A longitudinal analysis over 10 years

Anne N Nafziger
Ordway Research Institute Drug Development Center
Ordway Research Institute
1365 Washington Avenue, Suite 20112206-1066AlbanyNYUSA

The Research Institute
Bassett Healthcare
One Atwell Road13326-1394CooperstownNYUSA

Kristina Lindvall email@example.com
Margareta Norberg firstname.lastname@example.com
Hans Stenlund email@example.com
Stig Wall email@example.com
Paul L Jenkins
The Research Institute
Bassett Healthcare
One Atwell Road13326-1394CooperstownNYUSA

Thomas A Pearson
Department of Community & Preventive Medicine
University of Rochester Medical Center
601 Elmwood AvenueBox 64414642RochesterNYUSA

Lars Weinehall firstname.lastname@example.com
National Institute of Public Health -Sweden
SE-103 52StockholmSweden

Address: 1 Epidemiology and Public Health Sciences
Department of Public Health and Clinical Medicine
Umeå University
SE-90185Umeå, Sweden

BMC Public Health Who is maintaining weight in a middle-aged population in Sweden? A longitudinal analysis over 10 years
10.1186/1471-2458-7-108BioMed Central Page 1 of 10 (page number not for citation purposes) Research article * Corresponding author
Background: Obesity has primarily been addressed with interventions to promote weight loss and these have been largely unsuccessful. Primary prevention of obesity through support of weight maintenance may be a preferable strategy although to date this has not been the main focus of public health interventions. The aim of this study is to characterize who is not gaining weight during a 10 year period in Sweden.Methods: Cross-sectional and longitudinal studies were conducted in adults aged 30, 40, 50 and 60 years during the Västerbotten Intervention Programme in Sweden. Height, weight, demographics and selected cardiovascular risk factors were collected on each participant. Prevalences of obesity were calculated for the 40, 50 and 60 year olds from the crosssectional studies between 1990 and 2004. In the longitudinal study, 10-year non-gain (lost weight or maintained body weight within 3% of baseline weight) or weight gain (≥ 3%) was calculated for individuals aged 30, 40, or 50 years at baseline. A multivariate logistic regression model was built to predict weight non-gain.Results: There were 82,927 adults included in the cross-sectional studies which had an average annual participation rate of 63%. Prevalence of obesity [body mass index (BMI) in kg/m 2 ≥ 30] increased from 9.4% in 1990 to 17.5% in 2004, and 60 year olds had the highest prevalence of obesity. 14,867 adults with a BMI of 18.5-29.9 at baseline participated in the longitudinal surveys which had a participation rate of 74%. 5242 adults (35.3%) were categorized as non-gainers. Older age, being female, classified as overweight by baseline BMI, later survey year, baseline diagnosis of diabetes, and lack of snuff use increased the chances of not gaining weight.Conclusion: Educational efforts should be broadened to include those adults who are usually considered to be at low risk for weight gain -younger individuals, those of normal body weight, and those without health conditions (e.g. diabetes type 2) and cardiovascular risk factors -as these are the individuals who are least likely to maintain their body weight over a 10 year period. The importance of focusing obesity prevention efforts on such individuals has not been widely recognized.

Background

Obesity is associated with the development of multiple chronic health conditions and a variety of psychological disorders [1]. In 2002, the Swedish Council on Technology Assessment in Health Care (SBU; Statens beredning för medicinsk utvärdering) estimated that the direct costs for obesity related diseases in Sweden were approximately 2% (approximately 3 billion SEK/year) of the total cost for medical care [2]. Not only is obesity a problem, but increments of increased weight above a normal body weight are also associated with increased risk of numerous health problems [3,4]. Because of these facts, a great deal of effort has been focused on interventions to address the obesity epidemic.

The World Health Organization has recommended prevention of weight gain and promotion of weight maintenance as the first two basic steps in the effective control of obesity [5], but most efforts address secondary and tertiary prevention. While many investigators and public health advocacy groups have tried to develop strategies to assist in weight reduction, fewer have considered how to provide support for weight maintenance [6]. Because public health and health care system efforts in secondary prevention (promotion of weight loss) have been largely unsuccessful, a closer look should be taken at factors related to maintenance of healthy weight as a way to prevent weight gain and obesity.

The prevalence of obesity is increasing rapidly in Sweden [7]. From a primary prevention perspective, shifting the focus from lowering a high risk weight to maintaining low risk weight may be a more effective response to the obesity epidemic. This is not a new concept, but rather a neglected one. Burke et al. have suggested that diabetes prevention (via prevention of weight gain) should target normal and overweight individuals as they make up the majority of incident diabetes cases [8]. The idea that the most benefit can be gained by modest changes among the majority has been applied in the setting of other chronic conditions such as physical inactivity [9,10] and prehypertension [11].

The observation was recently made within a longitudinal study of a Swedish population, that individuals with diabetes type 2 were the most likely to maintain a normal body mass index (BMI) over a ten-year interval [12]. Emmelin et al. found that some survey participants believed they received less attention and less health advice because of a lack of identifiable risk factors [13]. This suggests that the current approach of identifying individuals with a greater risk factor burden and placing the focus primarily on them may be missing those who might get the most benefit from weight maintenance counseling -those who are not yet obese and those without identified cardiovascular risk factors. This led us to explore the characteristics of those who maintain their body weight over time.

The aim of this study was to examine a free-living cohort of middle-aged adults in order to identify and characterize the factors that differentiate individuals who will maintain (or lose) body weight over a 10 year period, from those who will gain, in order to identify those who would benefit from being the target of obesity primary prevention strategies.

Methods

During the 1970s, Västerbotten County had Sweden's highest cardiovascular disease mortality in ages below 75. These epidemiological data gave rise to a long-term community intervention program, the Västerbotten Intervention Programme (VIP), to reduce major risk factors for cardiovascular disease and diabetes. VIP used both individual-and population-oriented approaches to risk factor reduction [14,15]. Between 1985 and 1991, regional health centers gradually joined the study. By 1990, a uniform protocol for data collection was being used in all participating health centers.

Initially, all citizens were invited to an educational health screening and counseling the year they become 30, 40, 50 and 60 years of age, thus creating annual, consecutive cross-sectional surveys. Because of funding limitations, the County Council discontinued surveys of 30 year olds after 1995, and therefore only 8874 30-year olds contributed data for the cross-sectional analyses from 1990-1995. For the longitudinal surveys, baseline ages were 30, 40 and 50 during 1990-1994 and 10 year follow-up occurred during 2000-2004. Each participant gave written informed consent prior to participation. District nurses conducted the health surveys that included standardized measurements. Weight was measured in light indoor clothing and recorded to the nearest 0.5 kg. Height was measured without shoes and recorded to the nearest centimeter [16]. Blood pressure measurements, fasting blood work and an oral glucose tolerance test were obtained according to standardized procedures [16,17]. Participants completed a questionnaire that included questions on age, education, civil status, use of tobacco products, physical activity, use of certain medications for certain diseases, hypertension, presence of known heart disease and diabetes, and family history of cardiovascular disease and diabetes.

The VIP interventions were designed with both individual interventions and community components [18]. Adults were targeted for screening (via the health survey) and this was accompanied by counseling when cardiovascular risk factors were identified. Because the VIP surveys were conducted in the primary health clinic, the participant's doctor was aware of identified risk factors. At the same time, public health messages about healthy diet and alcohol consumption, smoking, the benefits of physical activity, and healthy psychosocial conditions were being conveyed to the local community. There was a particular focus on reducing dietary saturated fat, as elevated cholesterol was the most prevalent cardiovascular risk factor in the population. The community components were low-budget and designed primarily to use existing community resources. The goal was reduction of CVD risk factors and ultimately CVD [19], and neither obesity prevention messages nor obesity treatments were included.

Participants were categorized according to baseline body mass index (BMI; kg/m 2 ). The longitudinal analysis was restricted to those with a baseline BMI of 18.5 to 29.9; those who were underweight (BMI <18.5) or obese (BMI ≥ 30) were excluded (see Figure 1). The remaining participants were then categorized according to weight loss of >3.0%, weight maintenance +/-3.0%, or weight gain of >3.0% of baseline weight [20]. They were further categorized as non-gainers (weight loss or weight maintenance) or gainers (weight gain).

Impaired glucose tolerance was defined as a fasting capillary plasma glucose of <7.0 mmol/L and a 2-hour capillary plasma glucose after a 75 g glucose load (oral glucose tolerance test) of ≥ 8.9 to <12.2 mmol/L and without a diagnosis of diabetes type 2 [21]. Diabetes mellitus type 2 was defined as self-report, fasting capillary plasma glucose of ≥7.0 mmol/L, or 2-hour capillary plasma glucose (oral glucose tolerance test) of ≥12.2 mmol/L [21]. Hypertension was defined as a mean blood pressure of ≥140/90 mmHg or self-reported use of a medication for hypertension. Hypercholesterolemia was defined as a fasting total cholesterol of ≥7.5 mmol/L. Participants were classified as smokers (yes/no) and snuff users (Swedish moist snuff (snus); yes/no) based on self-report. Family history of myocardial infarction or stroke before the age of 60 years, or family history of diabetes was reported in first degree relatives as "yes/no". A six-level variable was formed to allow comparison by age-sex group (e.g. 30-year old men, 40-year old men, 50-year old men, 30-year old women, etc.) and 30-year old men were used as the reference group.

Prevalences for obesity were calculated from the cross-sectional data and incidences were calculated from the longitudinal data. Chi-square tests were used to compare differences in binomial proportions. Two sample independent t-tests were used to compare continuous variables between groups.

Univariate logistic regression analyses identified significant baseline predictors of weight non-gain. A multivariate logistic regression model was built by adding predictors significant in the univariate analyses, one variable at a time. The model evaluated predictors of weight non-gain over 10 years; gainers vs. non-gainers was the dependent variable. All two-way and three-way interactions were tested. Goodness of fit for the final model was evaluated with Hosmer-Lemeshow test.

The Västerbotten County Council was responsible for maintaining a single database of all the collected data. The Research Ethics Committee at Umeå University approved the study, the National Computer Data Inspection Board approved the data handling procedures, and the study was carried out in compliance with the Helsinki Declaration.

Results

Cross-sectional surveys

Between 1985 and 1989, pilot surveys were conducted. Those participants are excluded from this analyses as they were not drawn from the entirety of Västerbotten County. Between 1990 and 2004, 92,366 people participated in the surveys and they are the basis of the cross-sectional survey results presented. See Figure 2. The annual survey response rates averaged 63%. In total, there were 91,801 adults aged 30 to 60 years, including 4361, 13,600, 14,519, and 11,556 men aged 30, 40, 50 and 60 yr, respectively, and 4513, 14,706, 15,617, and 12,929 women aged 30, 40, 50 and 60 yr, respectively. There were a smaller number of 30 year olds because they were only surveyed during 1990-1995, as noted above.

Västerbotten Intervention Programme longitudinal study par-ticipants according to body mass index and weight change category Figure 1 Västerbotten Intervention Programme longitudinal study participants according to body mass index and weight change category.  Figure 4 (women). The 60 year olds had the highest obesity prevalences and the 30 year olds had the lowest. The differences between age groups were greater for the women than for the men. Prevalences of obesity increased for all groups with advancing survey years, except among 60 year old women where the prevalences were stable after 1993 (see Figure 4).  30,40 or 50 years at baseline, and had a measured BMI of 18.5-29.9 at the baseline survey. See Figure 1. Participants who lacked a BMI were also excluded. Participants with an initial BMI <18.5 or ≥30 kg/m 2 were excluded from this analysis. A comparison of baseline factors for participants versus non-participants is shown in Table 1. The non-participants were more likely to be younger, men, have higher education, have higher serum cholesterol levels, physically inactive, diabetics, and use nicotine.

Longitudinal surveys

In the longitudinal study, 5242 adults were categorized as non-gainers (weight gain of <3%) and 9625 were categorized as gainers (weight change of ≥3%). The incidence of overweight was 316/1000. This included those of normal BMI (18.5-24.9 kg/m 2 ) who became overweight (BMI 25-29.9 kg/m 2 ). The incidence of obesity was 107/1000. This included those of normal or overweight BMI (18.5-29.9) who became obese (BMI ≥ 30 kg/m 2 ). BMI, weight, and baseline characteristics by sex are shown for nongainers and gainers in   Data are presented as mean (± SD) unless otherwise noted. 1 Non-gain was defined as weight loss or maintenance of body weight within 3% of baseline weight. Gain was defined as an increase in weight of ≥3%.  29.5% (99 th percentile). The mean (± SD) percent changes in weight were 5.5 ± 6.9 % and 6.6 ± 9.1 % for men and women, respectively. A cohort effect was seen for weight maintenance with greater proportions of people maintaining or losing weight in the later cohorts (Figures 5 and  6).

In univariate analyses, older age, being a woman, low educational attainment, higher baseline BMI, glucose intolerance or diabetes, hypertension, higher serum cholesterol, lack of current snuff use, and later survey year predicted non-gain. See Table 3.

The final multivariate logistic regression model is presented in Table 4. Older age, being female, classified as overweight by baseline BMI, later survey year and baseline diagnosis of diabetes increased the chances of not gaining weight. Those who did not use snuff also were more likely to be non-gainers. The model showed goodness-of-fit and there were no significant interaction terms.

Discussion

Cross sectional surveys

Using cross-sectional data, we can calculate the prevalence of normal BMI in the population (or in contrast, the prevalence of obesity). The cross-sectional data suggest a gradual, steady increase in the prevalence of obesity within this middle-aged population during the time period from 1990-2004. An increase in the mean weight, with a resultant increase in obesity prevalence, was common in each of the sex and age groups studied. Among the women, those 40 and 50 years old had increasing prevalences of obesity but the 60 year old women had a relatively stable prevalence. In the U.S., the prevalence of obesity in women has been noted to be leveling off [22] while continuing to increase in men and children. This is consistent with our finding that women have a higher likelihood of maintaining body weight. A study in 70-year old Swedes also found that prevalences of obesity were higher in later cohorts [23].

Longitudinal surveys

By employing longitudinal data, we can identify the characteristics of those who are maintaining or losing weight. The longitudinal study reveals a different picture of the obesity epidemic and those who are avoiding weight gain than do the cross-sectional surveys. Overall, only 35% of the middle-aged population who were normal or overweight was able to maintain or lose body weight over ten years, with the remainder becoming heavier. The 30 yr olds were least likely to maintain or lose weight. There are numerous reasons why 30 year olds might have an increased risk of gaining weight. These include pregnancy [24], changes in lifestyle related to career development (e.g., working overtime) [25], or dissatisfaction with the need to combine work and family life [25]. Our data do not allow us to explore these types of underlying reasons.

Individuals with glucose intolerance identified during their baseline survey, or those with diabetes type 2, were the most likely to avoid weight gain. Increased body weight is a well recognized risk factor for diabetes [8], and the majority of individuals with diabetes type 2 are overweight or obese. The observation that individuals with diabetes were less likely to gain weight over the ten year interval may be attributable to increased intervention efforts (i.e. secondary prevention) on the part of the primary care system or to poorly controlled diabetes. Similar results have been reported by others [26]. The mean fast-

Proportion of women maintaining weight in the Västerbotten

Intervention Programme longitudinal studies between 1990 and 2004 by age group Figure 6 Proportion of women maintaining weight in the Västerbotten Intervention Programme longitudinal studies between 1990 and 2004 by age group. ing glucose among diabetics was only 7.2 mmol/L, making poorly controlled diabetes an unlikely explanation for an increased probability of non-gain. Since the best way to prevent diabetes is likely by preventing weight gain among normal weight and overweight people [8], from a public health perspective it is preferable to have effective primary prevention strategies and therefore have reduced need for secondary prevention efforts.

The classification of who is maintaining weight in this study may be generous. We chose to use the recommendations of Steven et al [20] because of the importance of publishing data that can be compared to the work of others.

Definitions of weight maintenance and weight change are often not standardized between studies. Using cut points based on gain of < 3% body weight should allow for differences in body size, measurement error, clothing weight and fluid balance [20], and change in height (e.g. with aging).

A limitation of the current study is that participation rates were not optimal. In a separate analysis from the Swedish Census, the differences were minimal with regard to education, income and employment types between participants and non-participants [27]. However, in the longitudinal study the participants were more likely to be of older age, women, lower education, lower baseline BMI and less likely to have cardiovascular risk factors. Overall, the differences between participants and non-participants should have resulted in more conservative odds ratios in our final model.

Community intervention effects versus secular trends

We noted a cohort effect, with a higher proportion of each age group maintaining weight as time progressed ( Figures  5 and 6). This could mean that a slowing of the obesity epidemic is occurring but is not yet evident in the crosssectional prevalence. The higher numbers of weight maintainers may also be the consequence of local community interventions to reduce cardiovascular disease risk.

The population studied in VIP has been participating in a program to reduce cardiovascular risk since the early 1990s. Programs intended to reduce cardiovascular risk could reduce obesity risk, although this has never been shown. Other community intervention programs for cardiovascular disease risk have been successful in altering cardiovascular risk but have failed to prevent weight gain [28][29][30]. The VIP interventions to encourage low fat diets, increase physical activity and control of other cardiovascular risk factors may provide an explanation for our findings. However, it should be noted that the goal of decreasing dietary saturated fat was intended to lower serum cholesterol, not reduce caloric intake. In addition, obesity as an important Swedish health problem, has only recently received wide recognition [31]. VIP was designed and implemented at the local, primarily rural, level and has been sustained for more than 20 years. This duration is longer than others with such a large intervention group. A longer, sustained intervention may be more successful although effects on weight gain have not been specifically evaluated.

One explanation for our findings may be that those with a chronic disease or identified risk factor are more attentive to weight maintenance and weight loss, while those without risk factors are not placing a priority on maintaining or losing weight. An alternative explanation may be that there are secular changes taking place that are slowing weight gain but that are not necessarily the direct result of interventions. A third possibility is that public health programs and medical care focus educational efforts on those with risk factors or chronic diseases rather than those who are perceived to be healthy (the young and lean) and therefore thought to be at low risk for future health problems.

Unexpected weight maintainers

We expected that individuals with normal BMI at baseline would be the most likely to maintain their body weight. Instead, we found that it is the people with normal body weight who are most likely to gain. Being younger, leaner and free of health problems increases the risk for weight gain by up to 150%. The finding that older adults are more likely to maintain weight is not unique to our population. An epidemiologic study from Norway also found that weight maintenance is more likely among those who are of older age [32]. Being overweight was associated with lower risk of weight gain, possibly because these individuals have been identified as at risk and are the recipients of secondary prevention from public health interventions or health care providers. The association between glucose intolerance identified at baseline and lack of weight gain supports this interpretation. Another possibility is that those who are overweight are paying more attention to their weight and/or working to avoid weight gain.

Conclusion

Efforts to assist people in losing weight have been largely unsuccessful [33,34]. Because increases in BMI above the normal range are associated with increases in the risk of many health conditions, poorer quality of life and mortality [35], the time to intervene is before weight gain occurs. Researchers and public health officials have been actively working to identify interventions that can be globally implemented for population-wide changes to dietary behaviors and physical activity [36]. In the U.S., there have been programs supported by the government, academic research community, and public health organizations but none have been successful in curtailing obesity [37].

The suggestion has been made that the public should learn about the body weight that is optimal for health, although it is unclear what type of educational programs should be implemented. By its longitudinal design, VIP gives further opportunities to provide data on weight maintenance, and thereby adds on to our present base of knowledge of what kind of preventive initiatives are likely to contribute and support people to maintain an optimal body weight. A developed perspective on maintaining weight in primary prevention does not replace or decrease secondary prevention efforts, but should rather be seen as a complement.

Educational efforts should be broadened to include those adults who are usually considered to be at low risk for weight gain -younger individuals of normal body weight, and those who are without health conditions (e.g. diabetes type 2) or cardiovascular risk factors -as these are the individuals who are least likely to maintain their body weight over a 10 year period. This does not negate the importance of continuing effective secondary prevention strategies. The importance of preventing weight gain earlier in life rather than later has been emphasized by others [5,8], but the importance of focusing obesity prevention efforts on those without risk factors has not been widely recognized.

List of abbreviations used

BMI, body mass index VIP, Västerbotten Intervention Programme

Declaration of competing interests

The author(s) declare that they have no competing interests.

Figure 2
2Västerbotten Intervention Programme study design showing survey years, age and number of participants, and cross-sectional and longitudinal study populations. obesity among men participating in the Väster-botten Intervention Programme cross-sectional studies between 1990 and 2004 Figure 3 Prevalence of obesity among men participating in the Västerbotten Intervention Programme cross-sectional studies between 1990 and 2004. 30 year olds were not surveyed after 1995.

of men maintaining weight in the Västerbotten Intervention Programme longitudinal studies between 1990 and 2004 by age group Figure 5 Proportion of men maintaining weight in the Västerbotten Intervention Programme longitudinal studies between 1990 and 2004 by age group.

Prevalence of obesity (BMI ≥ 30 kg/m 2 ) progressively increased from 9.4% in 1990 to 17.5% in 2004. Obesity prevalences by sex and 10 year age group are shown inFigure 3(men) and+

Lost weight,

>3% body weight

n=1545

(10.4%)

Participants with 10-
yr follow up

n=16,492

BMI 18.5-29.9

n=14,867

(91.0%)

BMI ≥30

n=1334

(8.0%)

Maintained weight,

-3% to +3% body weight

n= 3697

(24.9%)

Gained weight,

>3% body weight

n=9,625

(64.7%)

BMI <18.5

n=161

(1.0%)

Lacked BMI at
baseline or follow
up

n=130

10 yr follow up and
BMI data

n=16,362

Participants between
1990-1994

N=23,863

Non-participants in
10-year follow up

n=5, 799

Ineligible for 10-
year follow up

n=1,572

Participants eligible for
10-year follow up

n=22,291

Between 1990 and 1994, 23,863 individuals participated in the surveys that formed the basis of the 10-year longitudinal study. Of those, 22,291 were eligible for the longitudinal study and 16,492 participated in the 10-year follow-up survey. See Figure 2. The ineligible included 1062 participants who moved out of the county, 503 individuals who died, and 7 who could not be located because of assignment of an anonymous civil number. The overall follow-up rate was 68.1%; the response rate among the eligible was 74%. Included in this analysis were 14,867 adults [7056 (47.5%) men and 7811 (52.4%) women] who were aged

Table 2 .
2Ten-year percent change inPrevalence of obesity among women participating in the Väs-
terbotten Intervention Programme cross-sectional studies
between 1990 and 2004
Figure 4
Prevalence of obesity among women participating in the Väs-
terbotten Intervention Programme cross-sectional studies
between 1990 and 2004. 30 year olds were not surveyed
after 1995.

0%

5%

10%

15%

20%

25%

1990-1992
1993-1995
1996-1998
1999-2001
2002-2004

Survey Year

Prevalence of BMI
≥ 30 kg/m 2

30 yr women
40 yr women
50 yr women
60 yr women

Table 2 :
2Baseline and 10-year follow up characteristics of men and women in the Västerbotten Intervention Programme longitudinal study, 1990-2004, by weight gain or non-gain status. 1Baseline characteristic

Table 1 :
1Comparison of baseline characteristics for participants and non-participants in the 10-year longitudinal study within theVästerbotten Intervention Programme surveys, 1990-1994.1 Baseline characteristic

Table 3 :
3Odds ratios for univariate analyses of baseline characteristics and 10-year weight non-gain.1 Baseline Characteristic

Table 4 :
4Odds ratios for the multivariate model of baseline characteristics and 10-year weight non-gain.1 Baseline Characteristic

(page number not for citation purposes)
This table includes only those eligible for the longitudinal study. *differed by p < 0.05 between participants and non-participants; † differed by <0.01 between participants and non-participants; § differed by <0.001 between participants and non-participants
Weight non-gain included individuals who lost weight and those who maintained their body weight within 3% of the baseline weight.2 Using a logistic regression model with weight gain of >3% body weight versus no weight gain. 3 A six-level age-sex variable was created, using 30 year old men as the reference group.4 Fasting glucose <7.0 mmol/L and 2-hour capillary plasma glucose after a 75 g glucose load (oral glucose tolerance test) ≥ 8.9 to <12.2 mmol/L and without diagnosis of diabetes type 2[21]. 5 Diabetes mellitus defined as self-report, fasting blood glucose of ≥7.0 mmol/ L, or 2-hour capillary plasma glucose (oral glucose tolerance test) of ≥12.2 mmol/L[21].
Weight non-gain included individuals who lost weight and those who maintained their body weight within 3% of the baseline weight.2 Using a logistic regression model with weight gain of >3% body weight versus no weight gain. The model showed goodness-of-fit by Hosmer-Lemeshow test. There were no main effect interactions. 3 A six-level age-sex variable was created, using 30 year old men as the reference group.4 Fasting glucose <7.0 mmol/L and 2-hour capillary plasma glucose after a 75 g glucose load (oral glucose tolerance test) ≥ 8.9 to <12.2 mmol/L and without diagnosis of diabetes type 2[21]. 5 Diabetes mellitus defined as self-report, fasting blood glucose of ≥7.0 mmol/L, or 2-hour capillary plasma glucose (oral glucose tolerance test) of ≥12.2 mmol/L[21].
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AcknowledgementsThe authors wish to thank AFA-Insurance Sweden for provision of funding for this study through a research grant. The authors also wish to thank the Västerbotten Intervention Programme investigators for their careful collection of the data, and the County Council of Västerbotten for maintaining the intervention program and making the surveys possible.Authors' contributionsANN conceived the study, carried out the statistical analyses and drafted the manuscript. KL and MN provided critical revisions. HS and PLJ provided guidance on the statistical analyses. SW and LW conceived the study and provided critical review. TAP provided conceptual guidance and critical review.Pre-publication historyThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/7/108/pre pub
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