The association of neighborhood characteristics with obesity and metabolic conditions in older women

The Impact of Neighborhoods on Diabetes Risk and Outcomes: Centering Health Equity

Neighborhood environments significantly influence the development of diabetes risk factors, morbidity, and mortality throughout an individual's life. The social, economic, and physical environments of a neighborhood all affect the health risks of individuals and communities and also affect population health inequities. Factors such as access to healthy food, green spaces, safe housing, and transportation options can impact the health outcomes of residents. Social factors, including social cohesion and neighborhood safety, also play an important role in shaping neighborhood environments and can influence the development of diabetes. Therefore, understanding the complex relationships between neighborhood environments and diabetes is crucial for developing effective strategies to address health disparities and promote health equity. This review presents landmark findings from studies that examined associations between neighborhood socioeconomic, built and physical, and social environmental factors and diabetes-related risk and outcomes. Our framework emphasizes the historical context and structural and institutional racism as the key drivers of neighborhood environments that ultimately shape diabetes risk and outcomes. To address health inequities in diabetes, we propose future research areas that incorporate health equity principles and place-based interventions.

Neighborhood walkability and sex steroid hormone levels in women

BACKGROUND

Neighborhood walkability (NW) has been linked to increased physical activity, which in turn is associated with lower concentrations of sex hormones and higher concentration of SHBG in women. However, no study has directly examined the association of NW with female sex hormone levels.

OBJECTIVE

We conducted a cross-sectional study to evaluate the association between NW and circulating levels of sex hormones and SHBG in pre- and post-menopausal women.

METHODS

We included 797 premenopausal and 618 postmenopausal women from the New York University Women's Health Study (NYUWHS) who were healthy controls in previous nested case-control studies in which sex hormones (androstenedione, testosterone, DHEAS, estradiol and estrone) and SHBG had been measured in serum at enrollment. Baseline residential addresses were geo-coded and the Built Environment and Health Neighborhood Walkability Index (BEH-NWI) was calculated. Generalized Estimating Equations were used to assess the association between BEH-NWI and sex hormone and SHBG concentrations adjusting for individual- and neighborhood-level factors.

RESULTS

In premenopausal women, a one standard deviation (SD) increment in BEH-NWI was associated with a 3.5% (95% CI 0.9%-6.1%) lower DHEAS concentration. In postmenopausal women, a one SD increment in BEH-NWI was related to an 8.5% (95% CI 5.4%-11.5%) lower level of DHEAS, a 3.7% (95% CI 0.5%-6.8%) lower level of testosterone, a 1.8% (95% CI 0.5%-3.0%) lower level of estrone, and a 4.2% (95% CI 2.7%-5.7%) higher level of SHBG. However, the associations with respect to DHEAS and estrone became apparent only after adjusting for neighborhood-level variables. Sensitivity analyses using fixed effects meta-analysis and inverse probability weighting accounting for potential selection bias yielded similar results.

CONCLUSION

Our findings suggest that NW is associated with lower concentrations of androgens and estrone, and increased SHBG, in postmenopausal women, and lower levels of DHEAS in premenopausal women.

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018

BACKGROUND

Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent.

OBJECTIVE

To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment.

METHODS

The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum.

RESULTS

In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001).

CONCLUSION

Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Neighbourhood Socioeconomic Processes and Dynamics and Healthy Ageing: A Scoping Review

Elderly citizens are concentrated in urban areas and are particularly affected by the immediate residential environment. Cities are unequal and segregated places, where there is an intensification of urban change processes such as gentrification and displacement. We aimed to understand how neighbourhood socioeconomic processes and dynamics influence older people’s health. Three bibliographic databases—PubMed, Web of Science, and Scopus—were used to identify evidence of the influence of neighbourhood socioeconomic deprivation, socio-spatial segregation, urban renewal, and gentrification on healthy ageing. We followed the method of Arksey and O’Malley, Levac and colleagues, the Joanna Briggs Institute, and the PRISMA-ScR. The included studies (n = 122) were published between 2001 and 2021. Most evaluated neighbourhood deprivation (n = 114), followed by gentrification (n = 5), segregation (n = 2), and urban renewal (n = 1). Overall, older people living in deprived neighbourhoods had worse healthy ageing outcomes than their counterparts living in more advantaged neighbourhoods. Older adults pointed out more negative comments than positive ones for gentrification and urban renewal. As to segregation, the direction of the association was not entirely clear. In conclusion, the literature has not extensively analysed the effects of segregation, gentrification, and urban renewal on healthy ageing, and more quantitative and longitudinal studies should be conducted to draw better inferences.

The association between neighborhood social and economic environment and prevalent diabetes in urban and rural communities: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) study

Objective

The association between neighborhood disadvantage and health is well-documented. However, whether these associations may differ across rural and urban areas is unclear. This study examines the association between a multi-item neighborhood social and economic environment (NSEE) measure and diabetes prevalence across urban and rural communities in the US.

Methods

This study included 27,159 Black and White participants aged ≥45 years at baseline (2003–2007) from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Each participant's residential address was geocoded. NSEE was calculated as the sum of z-scores for six US Census tract variables (% of adults with less than high school education; % of adults unemployed; % of households earning <$30,000 per year; % of households in poverty; % of households on public assistance; and % of households with no car) and within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). NSEE was categorized as quartiles, with higher NSEE quartiles reflecting more disadvantage. Prevalent diabetes was defined as fasting blood glucose ≥126 mg/dL or random blood glucose ≥200 mg/dL or use of diabetes medication at baseline. Multivariable adjusted Poisson regression models were used to estimate prevalence ratios (PR) and 95% confidence intervals (CI) for the association between NSEE and prevalent diabetes across community types.

Results

The mean age was 64.8 (SD=9.4) years, 55% were women, 40.7% were non-Hispanic Black adults. The overall prevalence of diabetes was 21% at baseline and was greatest for participants living in higher density urban areas (24.5%) and lowest for those in suburban/small town areas (18.5%). Compared with participants living in the most advantaged neighborhood (NSEE quartile 1, reference group), those living in the most disadvantaged neighborhoods (NSEE quartile 4) had higher diabetes prevalence in crude models. After adjustment for sociodemographic factors, the association remained statistically significant for moderate density community types (lower density urban quartile 4 PR=1.50, 95% CI=1.29, 1.75; suburban/small town quartile 4 PR=1.54, 95% CI=1.24, 1.92). These associations were also attenuated and of smaller magnitude for those living in higher density urban and rural communities.

Conclusion

Participants living in the most disadvantaged neighborhoods had a higher diabetes prevalence in each urban/rural community type and these associations were only partly explained by individual-level sociodemographic factors. In addition to addressing individual-level factors, identifying neighborhood characteristics and how they operate across urban and rural settings may be helpful for informing interventions that target chronic health conditions.

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Neighborhood disadvantage significantly affects chronic disease conditions.

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Those living in the most disadvantaged neighborhoods had higher diabetes prevalence.

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The association remained statistically significant for lower density urban and suburban/small town communities.

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Identifying neighborhood characteristics across urban and rural settings may be helpful for informing public health programs.

The health potential of neighborhoods: A population-wide study in the Netherlands

BACKGROUND

While differences in population health across neighborhoods with different socioeconomic characteristics are well documented, health disparities across neighborhoods with similar socioeconomic characteristics are less well understood. We aimed to estimate population health inequalities, both within and between neighborhoods with similar socioeconomic status, and assessed the association of neighborhood characteristics and socioeconomic spillover effects from adjacent neighborhoods.

METHODS

Based on Dutch whole-population data we determined the percentage of inhabitants with good or very good self-assessed health (SAH) and the percentage of inhabitants with at least one chronic disease (CD) in 11,504 neighborhoods. Neighborhoods were classified by quintiles of a composite neighborhoods socioeconomic status score (NSES). A set of spatial models was estimated accounting for spatial effects in the dependent, independent, and error components of the model.

RESULTS

Substantial population health disparities in SAH and CD both within and between neighborhoods NSES quintiles were observed, with the largest SAH variance in the lowest NSES group. Neighborhoods adjacent to higher SES neighborhoods showed a higher SAH and a lower prevalence of CD. Projected impacts from the spatial regressions indicate how modest changes in NSES among the lowest socioeconomic neighborhoods can contribute to population health in both low- and high-SES neighborhoods.

CONCLUSION

Population health differs substantially among neighborhoods with similar socioeconomic characteristics, which can partially be explained by a spatial socio-economic spillover effect.

Urban social determinants of non-communicable diseases risk factors in Argentina

We examined associations of individual-, neighborhood- and city-level education -as proxies of SES at different levels-, with diabetes, hypertension, obesity, smoking and binge drinking (non-communicable disease risk factors -NCD/RF) among Argentinian adults. We estimated mixed models based on 21,415 individuals from the 2013 National Survey of Risk Factors, living in 2,698 neighborhoods and 33 cities. Gradients by individual-level education differed by gender and NCD/RF, and some were modified by city education. In addition, we identified contextual effects of neighborhood and city education on some NCD/RF. Urban efforts to tackle NCD/RF in Argentina should be context- and gender-sensitive, and mainly focused on socially disadvantaged groups.

Neighborhood Characteristics and Cardiovascular Biomarkers in Middle-Aged and Older Adults: the Baltimore Memory Study

Neighborhood greenness has been linked to better cardiovascular health, but little is known about its association with biomarkers related to cardiovascular risk. Adverse neighborhood conditions, such as disorder and socioeconomic disadvantage, are associated with higher cardiovascular biomarker levels, but these relationships may differ in neighborhoods with more greenness. This study evaluated cross-sectional associations of validated measures of neighborhood greenness, disorder, and socioeconomic disadvantage with cardiovascular biomarkers in middle-aged and older adults living in Baltimore City. The sample included 500 adults, aged 57-79 years, enrolled in the Baltimore Memory Study and living in Baltimore City during 2009-2010. Multi-level log-gamma regressions examined associations between the three neighborhood characteristics and seven cardiovascular biomarkers. Models additionally evaluated the effect modification by neighborhood greenness on associations of neighborhood disorder and socioeconomic disadvantage with the biomarkers. Adjusting for covariates and neighborhood greenness, greater neighborhood disorder was associated with higher C-reactive protein (exp β = 1.21, SE = 0.11, p = 0.035) and serum amyloid A (exp β = 1.28, SE = 0.12, p = 0.008), while greater neighborhood socioeconomic disadvantage was associated with higher tumor necrosis factor alpha (exp β = 1.24, SE = 0.12, p = 0.019). Higher neighborhood greenness was associated with lower soluble vascular cell adhesion molecule-1, accounting for disorder (exp β = 0.70, SE = 0.10, p = 0.010) and socioeconomic disadvantage (exp β = 0.73, SE = 0.10, p = 0.025). There was no evidence of effect modification among neighborhood characteristics. The findings suggest that neighborhood effects on cardiovascular health may be mediated through cardiovascular biomarker levels, and that socioeconomic disadvantage, disorder, and greenness may each be important features of neighborhoods.

Twitter-Derived Social Neighborhood Characteristics and Individual-Level Cardiometabolic Outcomes: Cross-Sectional Study in a Nationally Representative Sample

BACKGROUND

Social media platforms such as Twitter can serve as a potential data source for public health research to characterize the social neighborhood environment. Few studies have linked Twitter-derived characteristics to individual-level health outcomes.

OBJECTIVE

This study aims to assess the association between Twitter-derived social neighborhood characteristics, including happiness, food, and physical activity mentions, with individual cardiometabolic outcomes using a nationally representative sample.

METHODS

We collected a random 1% of the geotagged tweets from April 2015 to March 2016 using Twitter's Streaming Application Interface (API). Twitter-derived zip code characteristics on happiness, food, and physical activity were merged to individual outcomes from restricted-use National Health and Nutrition Examination Survey (NHANES) with residential zip codes. Separate regression analyses were performed for each of the neighborhood characteristics using NHANES 2011-2016 and 2007-2016.

RESULTS

Individuals living in the zip codes with the two highest tertiles of happy tweets reported BMI of 0.65 (95% CI -1.10 to -0.20) and 0.85 kg/m2 (95% CI -1.48 to -0.21) lower than those living in zip codes with the lowest frequency of happy tweets. Happy tweets were also associated with a 6%-8% lower prevalence of hypertension. A higher prevalence of healthy food tweets was linked with an 11% (95% CI 2% to 21%) lower prevalence of obesity. Those living in areas with the highest and medium tertiles of physical activity tweets were associated with a lower prevalence of hypertension by 10% (95% CI 4% to 15%) and 8% (95% CI 2% to 14%), respectively.

CONCLUSIONS

Twitter-derived social neighborhood characteristics were associated with individual-level obesity and hypertension in a nationally representative sample of US adults. Twitter data could be used for capturing neighborhood sociocultural influences on chronic conditions and may be used as a platform for chronic outcomes prevention.

Association of neighbourhood socioeconomic status and diabetes burden using electronic health records in Madrid (Spain): the HeartHealthyHoods study

OBJECTIVE

To study the association between neighbourhood socioeconomic status and diabetes prevalence, incidence, and control in the entire population of northeastern Madrid, Spain.

SETTING

Electronic health records of the primary-care system in four districts of Madrid (Spain).

PARTICIPANTS

269 942 people aged 40 or older, followed from 2013 to 2014.

EXPOSURE

Neighbourhoodsocioeconomic status (NSES), measured using a composite index of seven indicators from four domains of education, wealth, occupation and living conditions.

PRIMARY OUTCOME MEASURES

Diagnosis of diabetes based on ICPC-2 codes and glycated haemoglobin (HbA1c %).

RESULTS

In regression analyses adjusted by age and sex and compared with individuals living in low NSES neighbourhoods, men living in medium and high NSES neighbourhoods had 10% (95% CI: 6% to 15%) and 29% (95% CI: 25% to 32%) lower prevalence of diabetes, while women had 27% (95% CI: 23% to 30%) and 50% (95% CI: 47% to 52%) lower prevalence of diabetes. Moreover, the hazard of diabetes in men living in medium and high NSES neighbourhoods was 13% (95% CI: 1% to 23%) and 20% (95% CI: 9% to 29%) lower, while the hazard of diabetes in women living in medium and high NSES neighbourhoods was 17% (95% CI: 3% to 29%) and 31% (95% CI: 20% to 41%) lower. Individuals living in medium and high SES neighbourhoods had 8% (95% CI: 2% to 15%) and 15% (95% CI: 9% to 21%) lower prevalence of lack of diabetes control, and a decrease in average HbA1c % of 0.05 (95% CI: 0.01 to 0.10) and 0.11 (95% CI: 0.06 to 0.15).

CONCLUSIONS

Diabetes prevalence, incidence and lack of control increased with decreasing NSES in a southern European city. Future studies should provide mechanistic insights and targets for intervention to address this health inequity.

Neighborhood Environments and Diabetes Risk and Control

PURPOSE OF REVIEW

The objective of this review is to highlight the evidence on the association between contextual characteristics of residential environments and type 2 diabetes, to provide an overview of the methodological challenges and to outline potential topics for future research in this field.

RECENT FINDINGS

The link between neighborhood socioeconomic status or deprivation and diabetes prevalence, incidence, and control is robust and has been replicated in numerous settings, including in experimental and quasi-experimental studies. The association between characteristics of the built environment that affect physical activity, other aspects of the built environment, and diabetes risk is robust. There is also evidence for an association between food environments and diabetes risk, but some conflicting results have emerged in this area. While the evidence base on the association of neighborhood socioeconomic status and built and physical environments and diabetes is large and robust, challenges remain related to confounding due to neighborhood selection. Moreover, we also outline five paths forward for future research on the role of neighborhood environments on diabetes.

Characterizing the neighborhood obesogenic environment in the Multiethnic Cohort: a multi-level infrastructure for cancer health disparities research

PURPOSE

We characterized the neighborhood obesogenic environment in the Multiethnic Cohort (MEC) by examining the associations of obesity with attributes of the social and built environment, establishing a multi-level infrastructure for future cancer research.

METHODS

For 102,906 African American, Japanese American, Latino, and white MEC participants residing predominately in Los Angeles County, baseline residential addresses (1993-1996) were linked to census and geospatial data, capturing neighborhood socioeconomic status (nSES), population density, commuting, food outlets, amenities, walkability, and traffic density. We examined neighborhood attributes and obesity (body mass index ≥ 30 kg/m2) associations using multinomial logistic regression, adjusting for individual-level (e.g., demographics, physical activity, and diet) and neighborhood-level factors.

RESULTS

NSES was associated with obesity among African Americans, Latinos, and whites (p-trend ≤ 0.02), with twofold higher odds (adjusted odds ratios, 95% confidence intervals) for living in the lowest versus highest quintile among African American women (2.07, 1.62-2.65), white men (2.11, 1.29-3.44), and white women (2.50, 1.73-3.61). Lower density of businesses among African American and white women and lower traffic density among white men were also associated with obesity (p-trends ≤ 0.02).

CONCLUSIONS

Our study highlights differential impacts of neighborhood factors across racial/ethnic groups and establishes the foundation for multi-level studies of the neighborhood context and obesity-related cancers.

Associations of Continuity and Change in Early Neighborhood Poverty With Adult Cardiometabolic Biomarkers in the United States: Results From the National Longitudinal Study of Adolescent to Adult Health, 1995-2008

Limitations of extant research on neighborhood disadvantage and health include general reliance on point-in-time neighborhood measures and sensitivity to residential self-selection. Using data from the US Census and the 1995-2008 National Longitudinal Study of Adolescent to Adult Health, we applied conventional methods and coarsened exact matching to assess how cardiometabolic health varies among those entering, exiting, or remaining in poor and nonpoor neighborhoods. Within the full sample (n = 11,767), we found significantly higher systolic and diastolic blood pressures among those who entered or consistently lived in poor neighborhoods relative to those who never lived in poor neighborhoods. Obesity was similarly more common among those who originated from poor neighborhoods than among those who originated from nonpoor neighborhoods. Having exited poor neighborhoods was associated with lower systolic blood pressure than was consistent residence in low-income communities. Among the matched sample (n = 9,727), results adjusted for confounders and residential self-selection revealed fewer significant contrasts. Compared with peers who had no neighborhood poverty exposure, those who consistently lived in poor neighborhoods had 46% and 52% higher odds of being obese or hypertensive, respectively. Those who exited neighborhood poverty had significantly higher diastolic blood pressures than those who had never lived in poor neighborhoods. These findings underscore the importance of past as well as current residential circumstances for cardiometabolic health.

The Association of Vitamin D Deficiency and Incident Frailty in Older Women: The Role of Cardiometabolic Diseases

OBJECTIVES

Evidence suggests vitamin D deficiency is associated with developing frailty. However, cardiometabolic factors are related to both conditions and may confound and/or mediate the vitamin D-frailty association. We aimed to determine the association of vitamin D concentration with incidence of frailty, and the role of cardiometabolic diseases (cardiovascular disease, diabetes, hyperlipidemia, hypertension) in this relationship.

DESIGN

Prospective longitudinal cohort study (7 visits from 1994-2008).

SETTING

Baltimore, Maryland.

PARTICIPANTS

Three hundred sixty-nine women from the Women's Health and Aging Study II aged 70-79 years, free of frailty at baseline.

MEASUREMENTS

Serum circulating 25-hydroxyvitamin D (25[OH]D) concentration was assessed at baseline and categorized as: <10; 10-19.9; 20-29.9; and ≥30 ng/mL. Frailty incidence was determined based on presence of three or more criteria: weight loss, low physical activity, exhaustion, weakness, and slowness. Cardiometabolic diseases were ascertained at baseline. Analyses included Cox regression models adjusted for key covariates.

RESULTS

Incidence rate of frailty was 32.2 per 1,000 person-years in participants with 25(OH)D < 10 ng/mL, compared to 12.9 per 1,000 person-years in those with 25(OH)D ≥ 30 ng/mL (mean follow-up = 8.5 ± 3.7 years). In cumulative incidence analyses, those with lower 25(OH)D exhibited higher frailty incidence, though differences were non-significant (P = .057). In regression models adjusted for demographics, smoking, and season, 25(OH)D < 10 ng/mL (vs ≥30 ng/mL) was associated with nearly three-times greater frailty incidence (hazard ratio (HR) = 2.77, 95% CI = 1.14, 6.71, P = .02). After adjusting for BMI, the relationship of 25(OH)D < 10 ng/mL (vs ≥30 ng/mL) with incident frailty persisted, but was attenuated after further accounting for cardiometabolic diseases (HR = 2.29, 95% CI = 0.92, 5.69, P = .07).

CONCLUSION

Low serum vitamin D concentration is associated with incident frailty in older women; interestingly, the relationship is no longer significant after accounting for the presence of cardiometabolic diseases. Future studies should explore mechanisms to explain this relationship.

Trend of Body Compositions with Aging among Chinese Adolescents, Adults and Elders

INTRODUCTION

Rare reports can be found about sex- and age-specific body composition survey among Chinese population. The aim of this study is to explore the change of sex-specific body compositions with aging among Chinese adolescents, adults and elders.

METHODS

In a large-scale population survey about physiological constants and health conditions, 75,714 subjects who aged from 8 to 80 completed body composition array. Body mass index (BMI), percentage body fat (PBF), water percentage of body weight (WPBW), water percentage of lean body mass (WPLBM), fat-free mass index (FFMI) and basic metabolic rate were examined with Biodynamics BI-310 body composition analyzer. General obesity is defined as BMI equal to or greater than 28 kg/m2.

RESULTS

The prevalence rates of general obesity were 9.4% for males and 7.7% for females respectively. With aging, PBF and FMI showed a U-shape curvilinear trend and WPBW showed a parabolic trend for males. At same age group: 18-19 age groups, PBF and FMI declined to the valley and WPBW rose to the peak. For females, PBF, WPBW and FMI changed in a linear trend. The values of WPLBM and FFMI showed same curvilinear trend for two genders. WPLBM changed in a U-shape trend and touched the valley in twenties for males and in 18-19 age groups for females. The value of FFMI was larger for older age groups in the younger generation but smaller in the older generation. A parabolic trend peaking was seen in the thirties for males and in the forties for females. Regression models with age as independent variable showed that the larger rate of increase of PBF and smaller rates of increase for WPBM and WPLBM with aging for males.

CONCLUSION

This study presents detailed data about sex-specific body composition conditions. Different change trend with aging was found about body composition conditions.

Effects of handgrip exercise or inorganic nitrate supplementation on 24-h ambulatory blood pressure and peripheral arterial function in overweight and obese middle age and older adults: A pilot RCT

INTRODUCTION

Hypertension is a major contributor to the global burden of cardiovascular diseases and its prevalence increases progressively with ageing. Therefore the identification of effective, age-friendly exercise and nutritional interventions which lower blood pressure (BP) is a research priority.

OBJECTIVE

To undertake a pilot RCT examining the efficacy of isometric handgrip exercise (IHGE) and beetroot juice (a rich source of inorganic nitrate) consumption in modifying clinic and 24-h ambulatory BP (24-h ABP), peripheral arterial function and plasma asymmetric dimethylarginine (ADMA) in older overweight and obese adults.

DESIGN

Thirty middle age and older adults (62±5 years) were randomised to: (a) bilateral IHGE at 50% of maximal voluntary contraction (8 min/day), (b) 140 ml/day of concentrated beetroot juice, or (c) no-intervention (control group), for 7 days. All groups followed a standardised diet to control nitrate intake. Clinic and 24-h ABP, peripheral arterial function quantified by pulse wave velocity (PWV) and arterial volume distensibility were assessed before and after intervention.

SETTING

Clinical ageing research unit, Newcastle University.

RESULTS

At baseline, there were no between-group differences in age, handgrip strength, clinic or 24-h ABP, BMI, waist circumference, fat mass, physical activity level, energy intake or urinary and plasma nitrate concentrations. After intervention, there were no significant effects on clinic systolic and diastolic BP or 24-h ABP, PWV (p=0.54), arterial volume distensibility (p=0.89), or ADMA (p=0.45).

CONCLUSIONS

IHGE or beetroot juice consumption for 7 days did not affect BP or peripheral arterial function in overweight and obese middle age and older adults. Ageing may reduce the effects of these interventions on vascular function and studies are needed to test this hypothesis.