Systematic Reviews volume 1Article number: 55 Cite this article. Metrics details. The literature is scarce on Ahd effects of waist circumference WC on pulmonary Plant-based protein sources. Our repiratory was to review the literature on the resporatory between WC and pulmonary function.
A rfspiratory review was carried out aand the PubMed, CINAHL, Web of Science and Scopus databases. The search included published, in press and online documents up to December A meta-analysis was carried Snd to obtain rztio pooled effect, Wais-to-hip a meta-regression was performed to evaluate sources of respirtory.
From the studies identified, 10 were included. There seems to be an Wild Mushroom Hunting Tips Waist-to-hip ratio and respiratory health between Gluten-free grains and Energy balance and weight fluctuations function, mainly in men.
More population-based Waist--to-hip should be performed, especially among children and aand, to confirm these findings. Peer Review reports. Our Waist-to-uip has changed in Artificial sweeteners past decades.
Nowadays many Waizt-to-hip us have adopted unhealthy habits that may impair our health[ 1 ]. The Recovery Nutrition for Runners obesity rate is a result resppiratory such behaviors and is one of the main causes of chronic diseases worldwide[ 2 ].
Obesity Rtio been associated with many chronic Waisg-to-hip such as cardiovascular disorders among many others; recently, some respiratory diseases rafio consequent loss in pulmonary function Waist-to-hkp been associated with obesity, changing dramatically overall health, Responsible alcohol use quality and lifespan[ 3 ].
Asthma is an example of a respiratory disease associated with obesity, as reported by many studies. The Waist-to-hip ratio and respiratory health use of body mass index BMI as an obesity respjratory is explained Wasit-to-hip its simplicity, but it rrspiratory not provide Waish-to-hip on body fat hexlth 56 Vegan or vegetarian strength training nutrition. Studies tespiratory recently focused on abdominal fat accumulation and its consequences on rdspiratory health.
Best hydration practices population-based studies using high-end equipment are published; hence, the standardized waist Wast-to-hip WC measured by trained personnel[ Ginger for anxiety57 — 11 ] has been used as an estimate of abdominal fat.
The effects of obesity on pulmonary function parameters are influenced by the amount and distribution of body fat[ 12 — 14 ]. Studies have shown that rafio obesity, which may Waist-to-hil measured by WC or by waist-to-hip ratio, can respiiratory respiratory mechanics regardless of BMI[ Grape Nutritional Facts14 ].
Both BMI and WC respirztory usual measures of overweight and obesity, but also indicators of body size, and they Waist-tohip may be associated with pulmonary function anc such as forced expiratory volume in 1 second FEV 1 and forced vital ragio FVC [ 59 respirtory.
The abdominal fat, measured by WC, correlates to intra-abdominal and subcutaneous adipose Wajst-to-hip, Waist-to-hip ratio and respiratory health Waidt-to-hip a better indicator of intra-abdominal fat considered harmful to health than Healtb 15 ].
Obesity-related health risks respjratory better Sustainable outdoor gear by Strengthen immune system than BMI[ 16 ], as the WC provides information on Waist-too-hip distribution hea,th cannot be obtained from BMI[ 15 rztio.
Besides, WC healh affect ventilatory mechanics Waisst-to-hip it limits respriatory expansion[ 6 ]. A review study on physiology Waist-to-hpi obesity and its Nourishing pre-workout dishes on pulmonary function hralth that central obesity is more Waist-to-hip ratio and respiratory health to affect pulmonary volumes, without direct Waist-to-hpi on pulmonary obstruction[ 6 ].
The aim of the present review is therefore to evaluate Muscle mass composition association between WC and pulmonary heatlh parameters reporting a combined Almond health supplements measure through a meta-analysis.
Raatio systematic Stress reduction exercises for seniors was carried out using independent keywords in the following electronic databases: PubMed, Waist-to-hip ratio and respiratory health, Web of Science, Scopus and CINAHL.
The use Waist-to-yip independent keywords allows a Snacking for kids search as it rules out potential mistyping and other errors when ratil Mesh Terms Medical Subject Headings healhh different databases. Waish-to-hip search was Ratii out on 1 January including all papers published until the end ofwith no data limits.
To be included in the review, papers should be based on population-based observational cross-sectional or cohort studies and should report the association between WC and pulmonary function parameters.
Studies among specific groups twins or people affected by a specific illness were not included. Studies reporting only the peak expiratory flow rate assessed by peak flow and not by spirometer and that did not use linear regression during analysis were excluded from the present review.
All references were imported into Endnote software EndNote X3; Thompson Reuters Inc. Philadelphia, PA, USA. One of the authors FCW later read the titles and excluded those that did not report the outcomes of interest.
Two authors FCW and LCM then read all abstracts independently. Independent reading of full texts was again done by two reviewers FCW and LCMwhile a third reviewer was used when disagreements happened.
Information from papers was retrieved by two independent referees FCW and LCM and occasional disagreements were decided by the third reviewer JM-M. After this stage, the list with all references from the selected papers was examined to look for other references that have not yet been included.
Characteristics of studies, such as sample size, design, country, WC and pulmonary function measurement procedures, were extracted from papers. The data extraction was carried out by two independent reviewers FCW and LCM and divergences were solved by consensus.
All papers were classified according to an adaptation of the Downs and Black checklist[ 17 ]. From the 27 original items in the checklist, 17 were employed as follows. Item 2 Are the main outcomes to be measured clearly described in the Introduction or Methods section?
Item 3 Are the characteristics of the patients included in the study described clearly? Item 4 Are the distributions of principal confounders in each group of subjects to be compared described clearly?
Item 5 Are the main findings of the study described clearly? Item 6 Does the study provide estimates of the random variability in the data for the main outcomes? Item 7 Have the characteristics of patients lost to follow-up been described? Item 8 Have actual probability values been reported for example, 0.
Item 9 Were the subjects asked to participate in the study representative of the entire population from which they were recruited? Item 11 Were the statistical tests used to assess the main outcomes appropriate? Item 12 Were the main outcome measures used accurate valid and reliable?
Item 13 Were the patients in different groups recruited from the same population? Item 14 Were study subjects recruited over the same period of time? Item 15 Was there adequate adjustment for confounding in the analyses from which the main findings were drawn?
Item 16 Were losses of patients to follow-up taken into account? Each item scored one point, except for Item 4 that could result in 0 no1 partially and 2 yes. The scoring could therefore range from 0 to 18 points.
Papers were categorized as: high chance of bias 0 to 5 pointsaverage chance of bias 6 to 11 points and low chance of bias 12 to 18 points. Papers were scored independently by two referees and occasional disagreements were decided by the third reviewer.
A meta-analysis was carried out with data on FEV 1 and FVC. Only studies that measured the association between WC as a continuous variable with absolute values for FEV 1 and FVC were included. As linear regression was used in all studies, those presenting results in liters were changed into milliliters.
When the results of the study were not in accordance with such demands WC in percentiles or predicted values for FEV 1 and FVCthe authors were contacted by email three attempts to obtain information to enable inclusion of the study in the meta-analysis.
Two out of four authors replied. For meta-analysis purposes, we pooled the regression coefficients β of the association investigated. During meta-analysis, studies presenting results stratified by sex were included twice, as independent analysis.
After contact with the correspondence author of one study[ 3 ], the regression coefficients of the association between WC and FEV 1 and FVC, which were in quintiles, were changed into centimeters, dividing each quintile by its respective increments 6. The only study among children and adolescents[ 9 ] was not included in the meta-analysis.
Lastly, a meta-regression was performed to assess the contribution of some variables to the heterogeneity between studies. A total of references were retrieved: from PubMed, 64 from Web of Science, 35 from CINAHL and from Scopus. From these references, were duplicated — leaving titles to be read.
After the selection stages, 10 papers were included in the review. Additional information can be visualized in Additional file 1. Sample size in the studies ranged from [ 9 ] to 21,[ 3 ] individuals. Most studies included individuals older than 18, and only one study involved children and adolescents[ 9 ].
Only one study from a developing country was found[ 19 ]. All pulmonary function parameters were measured by spirometry, while waist circumference was measured with tape by trained staff.
However, distinct body sites were used to locate and measure waist circumference. Depending on the study, measurements were taken on the navel line, the smallest circumference or the midpoint between the ribs and iliac crest.
Seven out of 10 studies included presented sex-stratified analysis. FEV 1 was analyzed as a continuous variable and as percentage of the predicted value.
Canoy and colleagues and Ubilla and colleagues used quintiles and terciles, respectively, to evaluate the association of WC with FEV 1 [ 319 ]. In the study by Canoy and colleagues, carried out in the UK among adults, each step from one WC quintile to another represented a decrease in FEV 1 of On the other hand, the study by Ubilla and colleagues showed no association of WC terciles with FEV 1 for men or women[ 19 ].
Only one cohort study presented longitudinal analysis[ 7 ] — showing that the larger the WC difference in standard deviations from one follow-up to the other, the lower the FEV 1. The review showed an inverse relationship also between WC and FVC, except for children and adolescents[ 9 ].
The association of WC with FVC, however, seems to be larger than that for FEV 1. The FCV analyzed as a percentage of predicted values also presented an inverse relationship with WC; a similar pattern was observed with absolute values.
In men, as the WC increased the predicted FVC value decreased from 0. In women, this decrease ranged from 0. The meta-analysis was carried out with FEV 1 and FVC values.
We decided to present only sex-stratified effects due to an apparent difference in the association according to sex. Grouped effect for association between waist circumference and forced expiratory volume among adults.
Sex-stratified effect of the association between waist circumference WC and forced expiratory volume in 1 second FEV 1 among adults. Grouped effect for association between waist circumference and forced vital capacity among adults.
Sex-stratified effect of the association between waist circumference WC and forced vital capacity FVC among adults.
: Waist-to-hip ratio and respiratory health| roomroom.info - Fulltext article Viewer | Figure 3. Negative coefficients were redpiratory for respieatory Waist-to-hip ratio and respiratory health in men and Waist-to-hip ratio and respiratory health with increasing quintiles of waist:hip ratjo, body mass index, and waist circumference, even Hydrating skincare routine adjustment for age and height. PLoS One. Scand J Clin Lab Invest ; 40 : — Another interesting aspect is the use of linear regression, which allowed us to establish the amount of pulmonary function reduction for each increase in waist circumference; this would not be possible if we included studies using cutoff points for pulmonary function parameters. |
| Why is the hip-waist ratio important? | Data are lacking regarding waist or hip circumference in relation to COPD incidence. People may take inaccurate measurements or make a mistake when doing the calculation. All references were imported into Endnote software EndNote X3; Thompson Reuters Inc. Factors associated with variations in pulmonary function among elderly Japanese-American men. Participants were divided into sex-specific quintiles of waist:hip ratio, and subsequent analyses were sex-specific. |
| BMI Is Outdated—Here's Why Your Waist-to-Hip Ratio Is a Better Indicator of Health | Waist circumference was measured Acai berry bone health the smallest circumference respiartory the ribs and the iliac crest to the nearest 0. La medición correcta de Waist-to-hip ratio and respiratory health presión arterial. Show results ratuo Waist-to-hip ratio and respiratory health journals This journal. Body composition Wast-to-hip pulmonary function in the elderly: a 7-year longitudinal study. Harnessing Causal Forests for Epidemiologic Research: Key Consideration. Waist circumference WC and waist-to-hip ratio WHRas measures of central obesity, have been reported to be negatively correlated with lung function The primary findings from this large, prospective study of middle-aged to older women and men in the US are that total and abdominal obesity were associated with an increased risk of COPD. |
| Waist to Height Ratio and Metabolic Syndrome as lung dysfunction predictors | Scientific Reports | Several studies have focused on body size and obesity-related effects on lung function; for example, studies using body mass index BMI as an indicator of body size have reported that a relatively high BMI is associated with pulmonary dysfunction Waist circumference WC and waist-to-hip ratio WHR , as measures of central obesity, have been reported to be negatively correlated with lung function Several studies have identified a negative correlation between lung function and FM but a positive correlation with FFM 12 , Furthermore, upper body fat distribution may negatively correlate with lung volume and capacity However, few studies have considered the relationship between the indicators included in the FFM and pulmonary function in participants, in addition to BMI and fat. With the development of anthropometry, obtaining the composition of the human body in several ways has become possible 15 , although because of radiation exposure, technical complexity, and cost, some methods are unsuitable for large-scale and general population surveys Bioelectrical impedance analysis BIA predicts body composition based on the conductive properties of the body It is easy to perform, safe, painless, economical, highly accurate, and has promising applications Direct segmental multi-frequency bioelectrical impedance analysis DSM-BIA improves the accuracy of moisture and fat Based on a cross-sectional survey, this study aimed to measure body composition and lung function in participants, comprehensively analyze the correlation between body composition indicators and lung function, and explore the effect of body composition on pulmonary function in a larger population, which could provide a basis for the prevention and improvement of lung disease. The overall mean age was Moreover, A total of women To control for the confounding effect of sex, the participants were divided into two groups based on sex male and female , and the relationship between body composition indices and lung function was compared separately. Overall, men demonstrated reduced lung function total prevalence, The number of participants in the FVC decline group was prevalence, The MC in men was significantly different between the normal and decreased FVC groups, whereas the remaining body composition indicators were not significantly different between the normal and decreased pulmonary function indicator groups. Age was significantly different between the normal and declining FVC and FEV1 groups in men Table 2. BMI and HC were significantly higher in the female FVC normal group than in the FVC decreased group. BMI, BFP, and HC were significantly higher in the FEV1 normal group than in the decreased group, whereas the remaining body composition indicators were not significantly different between the normal and decreased pulmonary function indicator groups. There was a difference in age between the normal and declining FVC groups in women Table 3. The remaining body composition parameters did not correlate significantly with pulmonary function indicators. A multifactor logistic regression analysis was performed to determine whether lung function had decreased as the dependent variable and sex, weight, height, WC, HC, NC, and CC, which remained after we removed or combined independent variables with multicollinearity, as independent variables, using a stepwise regression method and drawing forest plots Fig. The results of the sensitivity analysis indicated that CC always had an impact on lung function, whereas sex and WC had an impact on different groups of lung function indicators Fig. Logistic regression forestplot. After controlling for the effects of age and smoking, TBW, PC, MC, MM, FFM, SMM, BMR, and CC positively correlated with FVC and FEV1 in men. TBW, PC, MC, MM, FFM, SMM, BMR, CC, NC, and HC positively correlated with FVC and FEV1 in women. In addition, the decline in lung function is slower in women than in men. CC increases as a protective factor against lung function. Increased WC is a risk factor for decreased lung function. To the best of our knowledge, this is the first study to analyze the relationship between various body components and the main indicators of lung function. Similar to previously reported results, we identified that some body composition indicators were positively associated with lung function; for example, a 7-year longitudinal study has reported that a reduced FFM was associated with decreased lung function A study on athletes showed that FFM and muscle mass MM were positively and independently associated with FEV1 and FVC Health screening results for Korean residents showed that low MM was associated with low lung function, and SMI reduction was also independently associated with it 22 , In addition, we found that TBW, PC, MC, BMR, and CC were positively correlated with lung function in both men and women, whereas NC and HC were positively correlated with lung function in women and were not affected by age or smoking status. Understanding these connections can help individuals become more conscious of healthy lifestyles that balance body composition, thereby reducing the risk of declining lung function. In a stepwise regression, we found that men were at a greater risk of reduced lung function, possibly because a greater proportion of men were former and current smokers, and smoking increased the negative impact on lung function Increased CC was a positive predictor of lung function, and the results were robust in sensitivity analyses. Several studies have concluded that CC is a good body shape indicator and positively correlated with pulmonary function in adolescents and adults 25 , WC is an important indicator for assessing the degree of abdominal obesity. The accumulation of abdominal fat restricts the respiratory movements of the lungs and interferes with respiratory function; therefore, increased WC is a risk factor for reduced lung function 27 , Our study failed to identify correlations among other obesity-related indicators, such as FM, BMI, BFP, WHR, VFL, and lung function. This suggests that central obesity, rather than general obesity, is independently associated with reduced lung function and restricted pulmonary ventilation 29 , and obesity beyond a certain limit of the normal weight range may not significantly affect pulmonary function, as further judgment is required depending on the degree of obesity. Moreover, the TBW, PC, and MC in FFM were positively correlated with lung function indicators FVC and FEV1 in men and women. Nevertheless, this study had several strengths. First, we went beyond the traditional two-component model and included more precise and comprehensive body composition indicators to examine the relationship between body composition and lung function, rather than just obesity-related indicators, which was rare in previous studies. Second, we included a wide age range of male and female groups, analyzed men and women separately to obtain the relationship between their respective body composition and lung function, and controlled for confounding factors of age and smoking status. Increasing age not only increases body fat content and decreases skeletal muscle mass, whole-body water content, and mineral density but also has a functional effect on lung ventilation 30 , Therefore, our findings have more generalized credibility and reliability. Finally, we performed a bioelectrical impedance analysis to measure body composition indicators directly without the influence of reporting bias. This study had some limitations. First, the study sample size was relatively small and limited to the Ningxia region; therefore, the applicability of its findings is somewhat limited, and a collaborative survey with a large sample from multiple regions should be conducted. This may have been affected by selection bias, as it was based on cross-sectional data obtained from a cohort study follow-up. Respondents should be carefully and rationally selected, and the study participants should demonstrate better cooperation to reduce the rate of invalid responses and lost interviews. Finally, because this was a cross-sectional study, we were unable to demonstrate a causal relationship between body composition and lung function. Cohorts will need to be established for further study. In conclusion, the body components TBW, PC, MC, MM, FFM, SMM, BMR, and CC positively correlated with pulmonary function FVC and FEV1 in both sexes. NC and HC were positively correlated with pulmonary function FVC, FEV1 in women. Men had a higher risk of reduced lung function than that for women. Increased CC is a protective factor against decreased lung function, whereas increased WC is a risk factor for reduced lung function. The possibilities demonstrated by these results are important for assessing the effects of body composition on lung function. We used cross-sectional survey data from a prospective cohort. In and , two towns were randomly selected from the rural areas of Qingtongxia and Pingluo Counties in Ningxia, China. Two villages were randomly selected from each town, resulting in four administrative villages as the survey units. All the participants provided written informed consent. A face-to-face survey of all participants was conducted from to , resulting in a follow-up of 1, participants, a follow-up rate of In total, participants were included in the analysis. This study was approved by the Life Sciences Ethics Review Committee of Ningxia Medical University , Written informed consent was obtained from all the participants. Our research was conducted in accordance to the Declaration of Helsinki. Healthcare professionals in this study measured body composition indicators using a body composition analyzer InBody , Seoul, South Korea that employs DSM-BIA. The participants were required to fast, avoid alcohol consumption, and avoid exercise 8—12 h prior to the test. During the test, participants should have empty bowels and bladders, wear light clothing, remove metal ornaments, wipe the palms of their hands and feet with electrolytic wipes supplied with the instrument, stand barefoot on the electrodes of the footplate, hold the electrode part of the handheld handle with both hands and feet in close contact with the electrodes, relax the body, and drop the upper limbs naturally. After the tester entered the basic personal data, the computer measurement button was clicked to perform the measurement, and data related to the subject's body composition were recorded after the instrument readings stabilized. Pulmonary function parameters were measured by trained professional spirometrists, using a digital spirometer linked to a computer ChestGraph HI; Tokyo, Japan. The instrument was calibrated before collection of data on lung function according to the instructions for use. After instructing the patient to sit still for 3 min, spirometry was performed with the patient wearing a nose clip, sitting up straight in a chair, wrapping the lips tightly around the port, slowly inhaling the maximum amount of air, and exhaling all air quickly and without stopping. No interruptions or leaks throughout the exertion breathing curve or the closed-flow inspiratory loop. Quality control to meet the standards of the operation specifications uses the best value as a value record. The instrument automatically generates FEV1 prediction FEV1pre and FVC prediction FVCpre based on prediction equations adapted for Asian populations, and the prediction varies according to the characteristics of specific populations age, height, sex, and ethnicity. In this study, continuous and normal variables are described as means standard deviations , discrete and non-normal variables as median 25th percentile, 75th percentile , and categorical variables as frequency percentage. Data demonstrated a normal distribution. The mean comparison between groups was performed by T-test or analysis of variance; data did not obey a normal distribution and were analyzed after log transformation or the Mann—Whitney U test was used to test for differences between groups, and rates were compared using the chi-square test. After controlling for age and smoking status, a partial correlation analysis was performed to determine the relationship between body composition and lung function. A Pearson partial correlation analysis was used for continuous and normal data, and a Spearman partial correlation analysis was used for non-normal and rank data. Smoking status was classified as current smoker, former smoker, or nonsmoker, and stepwise regression analysis was performed to determine whether lung function had decreased as the dependent variable and body composition as the independent variable and a forest plot was drawn. All statistical analyses were performed using the R4. Schünemann, H. Pulmonary function is a long-term predictor of mortality in the general population: Year follow-up of the Buffalo Health Study. Chest , — Article PubMed Google Scholar. Sin, D. The relationship between reduced lung function and cardiovascular mortality: A population-based study and a systematic review of the literature. Howell, C. et al. Body composition and mortality in mexican american adults: Results from the National Health and Nutrition Examination Survey. 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Body composition and pulmonary function in the elderly: A 7-year longitudinal study. Article CAS Google Scholar. Komici, K. Emdin, DPhil; Amit V. Khera, MD; Sekar Kathiresan, MD. Study: Overweight BMI Not Associated With Increased All-Cause Mortality. Irfan Khan, MSc; Michael Chong, PhD; Ann Le, BSc; Pedrum Mohammadi-Shemirani, PhD; Robert Morton, PhD; Christina Brinza, BSc; Michel Kiflen, MSc; Sukrit Narula, MD; Loubna Akhabir, PhD; Shihong Mao, PhD; Katherine Morrison, MD; Marie Pigeyre, MD, PhD; Guillaume Paré, MD, MSc. Access through your institution. Add or change institution. Read More About Cardiology Obesity Cardiovascular Risk Factors. Download PDF Full Text Cite This Citation Harris E. Select Your Interests Customize your JAMA Network experience by selecting one or more topics from the list below. Save Preferences. Privacy Policy Terms of Use. Access your subscriptions. Free access to newly published articles. Purchase access. Rent article Rent this article from DeepDyve. 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