relationship between obesity and hypertension pdf

Relationship between obesity and hypertension pdf

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Obesity and Hypertension in the Time of COVID-19

Obesity and hypertension

Obesity and hypertension

The imbalance between energy intake and expenditure is the main cause of excessive overweight and obesity. The latter constitutes the maximal healthful value for an individual that is calculated based chiefly on the height, age, build and degree of muscular development.

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To perform a meta-analysis of the association of obesity with hypertension and type 2 diabetes mellitus T2DM in India among adults. We restricted the analysis to studies with documentation of some measure of obesity namely; body mass index, waist-hip ratio, waist circumference and diagnosis of hypertension or diagnosis of T2DM. Heterogeneity was measured by I 2 statistic.

Funnel plot analysis has been done to assess the study publication bias. Of the studies screened, 18 met the eligibility criteria. The pooled odds ratio between obesity and hypertension was 3. Despite methodological differences, obesity showed significant, potentially plausible association with hypertension and T2DM in studies conducted in India. Being a modifiable risk factor, our study informs setting policy priority and intervention efforts to prevent debilitating complications.

Core tip: India with population explosion and high burden of non-communicable diseases NCDs poses a great challenge for the public health specialists to find the route cause for it. Indians have a higher burden of obesity and have relatively lower muscle mass compared to the whites [ 1 ]. Indians develop metabolic syndrome, hypertension, and type 2 diabetes mellitus T2DM earlier compared to whites, which is independent of BMI [ 2 , 3 ].

The available evidence suggests the age-adjusted prevalence of obesity has doubled in men and has increased three folds in women over two decades ss in India [ 4 ]. Subsequent economic reforms in India have initiated overpowering changes in the quality and quantity in a number of lifestyle factors in Indians [ 5 ]. For example, increased consumption of unhealthy food and lower levels of physical activity might likely have contributed to an increase in the prevalence of obesity and its comorbidities [ 6 ].

It is important to investigate the role of modifiable risk factors resulting in NCDs such as obesity, physical inactivity, tobacco use, and alcohol consumption [ 7 ]. Among these shared risk factors of NCDs, limiting the use of tobacco has fittingly received the greater attention of policy makers compared to other risk factors. However, the risk factors seldom act in isolation and it is important to alleviate the impact of their confluence.

It is, therefore, important to determine the quantum of the risk contribution by individual risk factor like obesity. Available evidence suggests strong associations between obesity and NCDs [ 8 , 9 ].

However, none of the earlier reviews have specifically evaluated the role of obesity in the etiology of hypertension and T2DM in India. The prevalence of obesity has increased significantly in India over the last few decades. About a third of the adult population in urban India is currently estimated to be overweight or obese. As a result, the number of persons with hypertension and T2DM could increase exponentially [ 10 ].

Apart from contributing to T2DM and hypertension, obesity is a major risk factor for pulmonary diseases, metabolic diseases, osteoarthritis, several cancers and serious psychiatric illness [ 9 , 11 ].

We limit our investigation to T2DM and hypertension. Specifically, we plan to systematically review studies exploring the plausible role of obesity in the etiology of hypertension and T2DM, synthesize the evidence, and perform a meta-analysis if appropriate.

Understanding the putative role of obesity and its impact on NCDs will inform future interventions to reduce the burden of these diseases.

The objective of our study is to estimate the association of obesity with hypertension and T2DM in Indian settings in adults.

We developed a protocol for conducting the meta-analysis; with the searching strategy encompassing key MeSH terms, selection of article based on inclusion and exclusion criteria, data extraction, quality assessment of the study, the summary of evidence and analysis. We included only studies published in English and are conducted in India. In addition, case-control studies must have compared participants with the disease T2DM or hypertension with controls without the disease.

We excluded intervention studies, as this was beyond the scope of our review. We contacted individual authors as necessary to clarify information and assess other relevant papers. We also reviewed cross-referenced papers cited in the assessed articles. Stage 1: Identification of studies for inclusion: As a preliminary step two authors Yamuna Ana and R Deepa independently assessed the study abstracts retrieved from electronic databases.

Stage 2: Choice of valid studies: Studies selected in stage 1 with necessary information were independently assessed against the inclusion criteria. We included only those studies which aided in the calculation of the relative risk or odds ratio of exposure obesity and outcome T2DM or hypertension. Stage 3: Quality assessment: The primary author Giridhara R Babu developed the protocol for the review and monitored the overall quality of the review at each step.

Two authors Yamuna Ana and R Deepa independently reviewed each article in its entirety for inclusion. The primary author Giridhara R Babu conducted random checks before data were extracted and tabulated. We employed the following set of criteria to evaluate the papers: 1 suitability of the study design; 2 appropriate sample size; 3 evidence regarding obesity and attributes of participants; and 4 accuracy of the tools used for quantifying obesity, diabetes and blood pressure.

We also reviewed controlling for confounding, selection bias, reduction of reporting errors and strategies employed to minimize measurement bias. For assessing eligibility, 2 authors Yamuna Ana and R Deepa individually reviewed the full-text papers. Discrepancies were resolved by agreement among both authors which arose during the selection of articles based on study inclusion criteria.

Disagreements regarding the inclusion of article were resolved by consulting Giridhara R Babu. If there were multiple reports related to a single study, we included the report with the details relevant to obesity and the outcome of interest.

Stage 4: Extraction of the data and synthesis of results: We did a preliminary search of the electronic databases, after which we selected papers with a title and abstract that matched our criteria. We obtained additional articles from the references provided in the reviewed articles, downloaded the full texts of the article for review. We noted the following details; first author of the paper, year of publication, study design deployed, cut-off values for defining obesity, the prevalence of exposure obesity , relative risk and odds ratio for T2DM and hypertension.

We derived the summary estimate by combining estimates from all the selected studies [ 14 - 24 ]. Crosschecking of outputs for internal consistency has been done and we obtained the pooled odds ratios reported in selected studies using Generic Inverse variance for overall estimates. We strictly conformed to the guidelines for meta-analysis of observational studies used in epidemiology [ 26 ].

We used RevMan for developing flowcharts and for examining the quality of study methodology. We used funnel-plot analysis to assess small-study and publication bias. We calculated odds ratio for individual study from the data cell values. We calculated the pooled odds ratio using the individual unadjusted odds ratios of each study within each subgroup of case-control and cohort studies.

Hence the pooled odds ratio was also unadjusted. We measured heterogeneity using I 2 statistic. This describes the percentage of total variation across studies that is due to heterogeneity rather than mere chance alone producing this [ 28 ]. An advantage of I 2 is that it does not depend on the number of studies included in the meta-analysis [ 29 ].

To assess the risk of publication bias we constructed funnel plots for all the association between exposure and outcome variables. The initial search identified studies. After checking for duplicates, we screened studies and excluded that were not relevant. Hence we included studies for full article review and among those we excluded studies from the meta-analysis.

Of these, articles were not eligible due to non-availability of exposure or outcome criteria Figure 1. The ineligible studies were rejected for the following reasons: Exposure criteria were not defined 46 , obesity or overweight was not used as an exposure 26 , studies were conducted outside India 21 , T2DM or hypertension was not included in study 23 and data provided was insufficient to calculate odds ratio or relative risk Finally, 6 studies satisfying the review criteria for hypertension and 12 for T2DM were involved in the meta-analysis.

One cohort study was included 21 and rest were cross-sectional studies. The age groups of the participants ranged from 20 to Information regarding confounding factors is reported in all the studies and in 2 studies, the selection bias is discussed. In studies with hypertension as an outcome, all studies discussed measurement error vs 6 studies with T2DM as the outcome Tables 3 and 4. The funnel plot that depicts the publication bias showed an inverted funnel shape with studies of higher precision relatively closer to the pooled odds ratio.

This corroborates minimal publication bias Figures 2 and 3. We noticed substantial heterogeneity among these study estimates, with the I 2 statistic being Similarly, the pooled odds ratio of obesity and hypertension was 3. Our results show that the association between obesity and hypertension is strongly positive and T2DM is moderately positive compared with healthy non-obese adults in India. Through the synthesis of available evidence using random effects meta-analysis, we show that obesity in India is a formidable independent risk factor to mitigate; albeit the risk appears to be relatively less for T2DM.

With industrialization and urbanization, the prevalence of obesity has increased gradually in India, heightening the need to focus on the prevention of these NCDs. Our analysis suggests that after adjustment for covariates, obesity is significantly associated with hypertension. The findings concur with other studies linking body mass as an important risk factor to hypertension [ 31 - 33 ].

This also coincides with the observed trend of increasing prevalence of hypertension in India across different risk groups for obesity [ 34 - 37 ]. More specifically, the estimates of meta-analysis are analogous to the estimates from odds ratio, 3. The pathophysiology of developing hypertension in obese individuals is explained by elevated cardiac output, perhaps due to excess intravascular volume and reduced cardiac contractility [ 38 ].

Recent evidence suggests that among obese, alteration in nutritional status, gut microbiota, sunlight exposure and increased physical activity have an important role in the presence or absence of hypertension [ 39 ]. Future studies may provide more details on these variables, including possible mediation.

Our results indicate that obesity is only moderately associated with T2DM. Also, we observed considerable heterogeneity in studies involving T2DM. The results also indicate that this is not explained by differences in participant age, baseline characteristics, or study quality. Such heterogeneity might be seen for several reasons. The lean T2DM is a distinct clinical entity in India. Due to temporal ambiguity in cross-sectional studies, it is possible that loss of weight might have ensued after the diagnosis of T2DM.

This indicates that nearly half of the persons with T2DM in India are undiagnosed, and therefore, apart from other complications would have lost considerable weight by the time of diagnosis. Given this evidence, we estimate that nearly one-fourth of the undiagnosed persons with T2DM will have weight loss and therefore will spuriously indicate that obesity may not be a significant risk factor.

Using cut-off points of BMI, WC and WHR as surrogates for percentage body fat in Indians, and thereby making classifications of obesity might have underestimated the overall measures [ 43 ]. The validity of universal cut-off points for Indians is uncertain; it would be better only to treat it continuous variable [ 8 ].

Future examinations should include analysis of the data sets from these studies for a continuous association.

The association of obesity with T2DM and hypertension is highly probable at lower levels than the cut-off points used in this paper. Therefore, we might have grossly underestimated the association between obesity and T2DM. Further, Survival bias might have resulted in underestimation; since, people with T2DM, who are dead, debilitated, disabled or have severe illness might not have captured by the cross-sectional studies [ 44 ].

Obesity and Hypertension in the Time of COVID-19

Current Issue. By Issue. By Subject. Keyword Index. This Authors Article. Prevalence of overweight and obesity and their associations with dietary habits among students from An-Najah National University: A cross-sectional study An- Najah National University, Nablus, Palestine. Amandi Bonaventure Egbujie.

Macmohan, J. Cutler, E. Brittain, M. The relationship between obesity and hypertension has been investigated in a large number of cross-sectional population studies and a smaller number of prospective, observational studies. The results indicate that in most populations, blood pressure increases linearly with increasing relative body weight or body mass index. The relationship is present across all subgroups, although the magnitude of the association appears greater in whites than blacks and greater in younger than older persons.

Request PDF | The relationship between obesity and hypertension: An updated comprehensive overview on vicious twins | Obesity is a.

Obesity and hypertension

The relationship between obesity and hypertension varies with geographical area, race and definitions of obesity. Our study aimed to investigate the prevalence of obesity using standard Chinese criteria based on the body mass index BMI and the waist circumference WC and to examine the association between obesity and hypertension among middle-aged and elderly people in Jinan city. This cross-sectional study examined 1, subjects from the blocks randomly selected from among the 6 communities of Jinan, China in — Multivariate logistic regression analyses were performed to assess the effects of general and central obesity on hypertension after adjusting for age or for education level, smoking, alcohol consumption, and continuous age. The prevalence of general obesity among people age 50 years and older was

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Metrics details. Although there has been a well-established association between overweight-obesity and hypertension, whether such associations are heterogeneous for South Asian populations, or for different socioeconomic groups is not well-known. We explored the associations of overweight and obesity using South Asian cut-offs with hypertension, and also examined the relationships between body mass index BMI and hypertension in various socioeconomic subgroups. The prevalence of hypertension using JNC7 cut-offs among participants increased by age in all three countries.

Obesity and hypertension

In this issue of JAMA, 2 reports 1 , 2 present cross-sectional data on the prevalence and trends for obesity and controlled hypertension from through based on data from the National Health and Nutrition Examination Survey, a federal program of nationally representative surveys designed to monitor the health and nutrition of adults and children in the US. At first glance, these 2 studies may appear to be addressing different issues. Ogden et al 1 describe the seemingly inexorable increase in obesity prevalence among both children and adults, a condition that has few preventive strategies that have proven effective on a population basis despite recognition of its adverse effect on health.

Obesity and hypertension

Obesity is a growing global health concern, with a rapid increase being observed in morbid obesity. Obesity is associated with an increased cardiovascular risk and earlier onset of cardiovascular morbidity. The growing obesity epidemic is a major source of unsustainable health costs and morbidity and mortality because of hypertension, type 2 diabetes mellitus, dyslipidemia, certain cancers and major cardiovascular diseases. Similar to obesity, hypertension is a key unfavorable health metric that has disastrous health implications: currently, hypertension is the leading contributor to global disease burden, and the direct and indirect costs of treating hypertension are exponentially higher. Poor lifestyle characteristics and health metrics often cluster together to create complex and difficult-to-treat phenotypes: excess body mass is such an example, facilitating a cascade of pathophysiological sequelae that create such as a direct obesity-hypertension link, which consequently increases cardiovascular risk. Consequently, a comprehensive and exhaustive investigation of this relationship should analyze the pathogenetic factors and pathophysiological mechanisms linking obesity to hypertension as they provide the basis for a rational therapeutic strategy in the aim to fully describe and understand the obesity-hypertension link and discuss strategies to address the potential negative consequences from the perspective of both primordial prevention and treatment for those already impacted by this condition.

Hypertension is one of the major risk factors of cardiovascular diseases, but despite a century of clinical and basic research, the discrete etiology of this disease is still not fully understood. The same is true for obesity, which is recognized as a major global epidemic health problem nowadays. Obesity is associated with an increasing prevalence of the metabolic syndrome, a cluster of risk factors including hypertension, abdominal obesity, dyslipidemia, and hyperglycemia. Epidemiological studies have shown that excess weight gain predicts future development of hypertension, and the relationship between BMI and blood pressure BP appears to be almost linear in different populations. There is no doubt that obesity-related hypertension is a multifactorial and polygenic trait, and multiple potential pathogenetic mechanisms probably contribute to the development of higher BP in obese humans.


  • Matthew B. 11.04.2021 at 12:36

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