Muscleness and fatness phenotypes for diabetes and hypertension prediction from the Chilean National Health Survey 2016-17

Introduction: diabetes and arterial hypertension are increasing in adults, where calf circumference and waist circumference are two clinical epidemiological markers poorly studied for predicting cardiometabolic risk. Objective: to characterize four phenotypical models in the Chilean adult population based on muscleness and fatness using both calf circumference and waist circumference outcomes. Methodology: An epidemiological observational cross-sectional representative study based on the Chilean National Health Survey 2016-17, where four phenotypes groups were analyzed; Low skeletal muscle mass and high-waist circumference (Lsmm-Hwc, n =140), low skeletal muscle mass and low waist circumference (Lsmm-Lwc, n =242), high skeletal muscle mass and high waist circumference (Hsmm-Hwc, n =1076), and high skeletal muscle mass and low waist circumference (Hsmm-Lwc, n =1358). These groups described information about diabetes, hypertension prevalence, including other risk factors. Results: the reference group Hsmm-Lwc group showed lower fasting plasma glucose (FPG) vs. Hsmm-Hwc (90,4 [95%CI] [89,0; 91,8] vs. 111,7 [109,1; 114,3]), and vs. Lsmm-Hwc (90,4 [89,0; 91,8] vs. 118.,3 [107,2; 129,4] mg/dL, both P<0,0001). Lower levels (i.e., appropriate) of FPG (R 2 4,8 %), glycated hemoglobin (R 2 2,6 %), systolic BP (R 2 19,0 %), and diastolic BP (R 2 2,5 %) were significantly associated (all, P<0,0001) with the Reference group Hsmm-Lwc. Conclusion: A high muscleness and low fatness phenotype is present in those who are younger adults, is associated with better glucose/blood pressure control, and reports low cardiovascular risk factors for diabetes and hypertension in Chilean adults.


INTRODUCTION
Physical activity (PA), nutrition, and sleep patterns among others (i.e., lifestyle) play a key role in modern societies in terms of maintenance of cardiometabolic health (i.e., that includes both cardiovascular and metabolic/endocrine systems) and avoiding diabetes and hypertension (HTN). (1)By contrast, physical inactivity (i.e., do not adhere to international PA guidelines of 150−300 min of low-to-moderate PA•week, or 75 to 150 of vigorous PA•week), (2) is associated with more diabetes and HTN prevalence in children/adolescents and adults.(3,4)   Before diabetes and HTN diagnosed, the adult population transit through previous and prevented health symptoms such as skeletal muscle mass decline (SMM, i.e., sarcopenia) and higher adiposity accumulation, as for example, calf circumference decreases (4) and waist circumference increases (WC) to each outcome respectively. (6)Thus, it is well known that a phenotypical model of low SMM decreases glucose control, promotes adiposity accumulation, (7) and subsequently increases diabetes risk by intramyocellular fatty acids accumulation. (8)By contrast, healthy adults who are physically active and adhere to a healthy lifestyle, report better SMM levels. (9)he SMM under insulin-stimulated conditions, account for more than 80 % of glucose disposal, (7) being important for young and adults the adherence to international PA guidelines with the aims of preventing diabetes and HTN risk factors. (10,11)ne of the common phenotypes in physically inactive populations, is the lower SMM in association with higher adiposity (i.e., fatness), or appropriate/higher SMM (i.e., muscleness) but in association with higher adiposity. (12)For example, previous studies of phenotypes, have shown that higher cardiorespiratory fitness (CRF, reported by the maximum oxygen consumption, VO 2max ) in combination with reduced body fat were associated with lower risk factors for HTN, metabolic syndrome, and dyslipidemia in adults. (12)t has also been corroborated similar phenotypes, where children/adolescents (age 12,2±2,7 years old, n=3,866) with higher CRF showed characteristics of better blood pressure control than peers with lower CRF. (13)ore recently, the sarcopenic-obesity phenotypical model based on the handgrip strength (HGS) together with the body mass index plus waist circumference reported that there is a pre-sarcopenic-obesity prevalence of 22,6 % in Chilean adults, based on the Chilean National Health Survey 2016-17 (NHS16-17). (14)owever, there is little knowledge about the association of a 'muscleness' or' fatness' human phenotype model by using SMM by calf circumference (CC), and waist circumference (WC) as adiposity markers based on Chilean NHS16-17 information.CC have been previously used as an early indicator of SMM loss in adults. (15,16)In Latin-American older adults, previous studies of CC have demonstrated sensitivity (71,5 %), and specificity (77,4 %) to detect SMM declining. (5)Other reports show that CC is also correlated with Dual X-ray absorptiometry, (17) and with the loss of autonomy. (18)his study aimed to characterize four phenotypical models in the Chilean Latin-American population based Salud, Ciencia y Tecnología.2024; 4:814 2 on muscleness and fatness using both CC and WC outcomes from the NHS16-17.There was hypothesized that phenotypes with higher SMM and lower WC show a better glucose and blood pressure control.The importance of this research consists in the possibility to propose the incorporation of future more robust equipment for body composition analyses into epidemiological cross-sectional studies as the NHS16-17 for an early prevention of these diseases.

Research type
The following is a cross-sectional study based on the Chilean NHS16-17 of Chile, which is a prevalence, multistage and representative study applied in at home with families using random, stratified-by-conglomerates methods.

Population
The data of the NHS16-17 of Chile includes a personal home-based visit to population ≥15 y old, with or without an ethnic origin, from urban/ rural areas of this country.Considering the total NHS16-17 sample reported by the NHS16-17 of (n=6,233) participants, the present study included (n=2j836) subjects who report the information of interest to the hypothesis test.The NHS16-17 included data of population of ≥15 years old, and all full criteria of inclusion can be found at the Epidemiological Unit of the Chilean Health Ministry (MINSAL) at http://epi.minsal.cl/encuesta-ens-descargable/To this descriptive study, we used the selected data that included the SMM and WC information including diabetes, HTN and other relevant outcomes reported as risk factors.The study protocol was approved by the Ethical Committee of the Escuela de Medicina de la Pontificia Universidad Católica de Chile (16-019), and all participants signed an informed consent. (18)

Diabetes and arterial hypertension markers (Main outcomes)
To glucose control, both fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) were measured.Both outcomes were measured with 8 h of fasting state and were measured similarly as reported in previous studies. (19)or blood pressure control, both systolic (SBP) and diastolic (DBP) were measured in the left arm three times and the average of these was registered.To the present study, there was used the current blood pressure categorization of the American Heart Association 2018; 'Normal BP' was defined as SBP/DBP less than 120/80 mmHg, 'elevated BP' (Ele) as SBP/DBP between 120-129/80 mmHg, 'stage 1 HTN' as SBP/DBP between 130-139/80-89 mmHg, and 'stage 2 HTN' as SBP/DBP greater than or equal to 140/90 mmHg. (20)The readings were taken using an automatic monitor (OMRON TM , model HEM 7114) similar to previously. (4)This test was developed by professional nursing at-home conditions.

Anthropometric measurements (Secondary outcomes)
The weight was measured by a digital electronic scale OMRON TM , model HBF-514C (OMRON Corporation, Kioto, Japon), (sensitivity of 100 g, maximum weight capacity ~150 kg), where height and waist circumference were measured by an inextensible tape.similar as previous studies. (21)The nutritional state was classified by the BMI using weight plus height, as follows; Underweight, Normal-weight, overweight, obesity I, obesity II, obesity III, and morbid obesity, and reported as (n = ) and percentage ( %) by each phenotypical model, following the WHO criteria. (22)

Physical activity measurement (Secondary outcome)
There was reported the amount (min•day) of PA of vigorous, moderate, and low-intensity using the Global Physical Activity Questionnaire (GPAQv2). (25)All measurements mentioned were applied following the application manual F2 of the NHS16-17.

Cardiovascular risk estimation (Secondary outcome)
The cardiovascular risk was categorized by scale punctuation in low (0-4 points), moderate (5 to 9 points) and high cardiovascular risk (≥10 points) using the metabolic syndrome outcomes (blood pressure, FPG, HDL-c, and Tg), including tobacco habit, alcohol consumption, dyslipidemia, sleep patterns, as well by the three questions included as follows; a) in the self-report on acute myocardial infarction ¿Has a doctor or physician ever told you had or suffered a heart attack?Being the prevalence from those who answered "Yes"; b) the question for the self-reported prevalence of stroke "Has a doctor or physician ever told you had or suffered a stroke?Or had or suffered a stroke or cerebral thrombosis (or stroke)?", and c) the question about the selfreported prevalence of peripheral venous disease "Has a doctor or physician ever told you had or suffered from peripheral vascular disease or to the arteries in your legs?". (26)

Statistical analyses
Data for continuous outcomes are shown as mean and (95 %CI), and for categorical outcomes as frequency (n = ) and ( %, percentage).The normality was tested using the Shapiro-Wilk test and using histograms and Q-Q plots.For continuous outcomes, the interaction of each main and secondary outcome among the four phenotypes (Lsmm-Hwc, Lsmm-Lwc, Hsmm-Hwc, and Hsmm-Lwc) was tested using analysis of covariance (ANCOVA) (groups, sex, and age) as covariables.The chi-square test was used to compare categorical outcomes.Bonferroni adjustments were used to confirm the differences across a phenotype group.Linear regression analyses were applied to test the association between diabetes and hypertension markers with the four muscleness and fatness phenotype models.The coefficient of determination R 2 in percentage (for predicting independent outcome), and r= Pearson correlation test was reported.To detect multicollinearity, there was used the diagnosed condition indices (CNI).Collinearity was determined if the largest CNI exceeded the 30 values.There was also tested sensitivity/specificity to FPG (77,7 % / 72,5 %), HbA1c (80,8 % / 76,5 %), SBP (58,5 % / 57,4 %), DBP (59,9 % / 53 %) using ROC analysis (data not shown).All statistical tests were carried out using the SPSS TM software 24 version for Windows (IBM SPSS Inc., Chicago, IL, USA).

RESULTS
Continuous (age, height, body mass, BMI, WC, CC, PA VI , PA MI , PA LI , HGS) and categorical outcomes (nutritional state by BMI, diabetes, arterial hypertension prevalence, and sleep patterns) showed significant interaction by the four groups of phenotypes (Table 1).

DISCUSIÓN
SMM is an important tissue for glucose and blood pressure control, (10,11) and physical inactivity increases the adiposity stores promoting more cardiometabolic risk for diabetes and HTN. (3)In the present study, there was clearly shown that the Ref. group of high-SMM and low-WC reported a better glucose control by FPG 90,4 mg/dL, and appropriate levels of blood pressure by SBP/DBP 117/70 mmHg, highlighting the relevance of maintaining a good SMM and lower levels of adiposity in Latin-American population for avoiding diabetes and HTN risk (Figure 1).Interestingly, the age of the Ref.Hsmm-Lwc group was lower (i.e., 42,1 years) in comparison with the other groups, however, independent of age, literature has shown that when adults and older adults are physically active, the SMM is minimally declined in older adults active, being more important than the chronological age, the PA promotion across the lifetime for sarcopenia prevention, (27) and thus as a pivotal result it is possible the reduction in diabetes (28) and HTN risk. (29)The fitness and fatness phenotypes have been previously explored

Figure 2 .
Figure 2. Dyslipidemia markers and coronary risk in Chilean adults by four different phenotypical models based on the National Health Survey 2016-17 of Chile.

Figure 3 .
Figure 3. Association between diabetes (panels A-B) and hypertension markers (panels C-D) with four different phenotypical models (based on calf circumference and waist circumference) of Latin-American participants of the Chilean National Health Survey 2016-2017.

Table 1 .
Characteristics of the Chilean population by each muscleness and fatness model based on the Chilean National Health Survey 2016-17

Table 2 .
Association between different cardiometabolic risk factors with four different models of muscleness and fatness based on calf circumference and waist circumference Data are shown as mean and (95 %CI) for continuous outcomes, and as frequency and ( % percentage) for categorical outcomes.(PA VI ) Physical activity of vigorous−intensity.(PA MI ) Physical activity of moderate−intensity.(PA LI ) Physical activity of low−intensity.Bold Pvalues denotes significant differences between groups at p .05 or less.(#) Analysis performed by Chi-square test at p .05.