Sociodemographic properties provided racial self-category (light otherwise non-white e.grams. black colored, brownish, yellow, or native), host to household (metropolitan or outlying), schooling (0–cuatro, 5–8, 9–eleven, or ? twelve age), and month-to-month home money for each and every capita in the tertiles (lower, middle, otherwise highest). The latest metropolitan–outlying classification was in accordance with the steps used by the newest Brazilian Institute away from Topography and you can Statistics (from inside the Portuguese Soca internet brides, IBGE) inside the 2010 people census from administrative limitations establish because of the regional legislation. Inside for each municipality’s limitations, these types of local laws and regulations expose a fictional range named “urban fringe”. The census tracts located for the “urban edge” is termed urban, whereas the residual components is designated rural. The other recommendations was received courtesy a face-to-face interview at the participant’s home.
Anthropometric parameters
Height was measured in centimeters (cm) using a portable vertical stadiometer (NutriVida®, Brazil) with the participants barefoot with legs and feet parallel, weight distributed on both feet, arms relaxed at the sides, palms facing the body, and head in the Frankfurt horizontal plane. Weight was measured in kilograms (kg) using a portable digital scale (SECA®, Germany) with participants barefoot. Body mass index (BMI) was calculated as the ratio between weight in kilograms (kg) and height in square meters (m 2 ). BMI cutoff points were based on the World Health Organization recommendation: underweight (< 18.5> 94 cm in men and > 80 cm in women were considered “increased” since they are associated with a higher risk of metabolic complications . All anthropometric variables were measured twice during the home visit by trained interviewers and the mean of the measurements was used in the analyses. Further information can be seen in the handbook on the survey homepage (
Analytical analysis
Additionally, we provided information on the most prevalent chronic diseases diagnosed by a physician in our sample. Secondly, fractional polynomial regression models were fitted to estimate the percentiles (P5, P10, P20, P25, P50, P75, P90, and P95) of HGS by age group and sex. This method provides smooth centile curves and explicit formulae for the percentile estimates. Diagnostic tests were used to evaluate the model fit (normal plot of the Z-scores, Shapiro–Wilk test, and residuals plot). The model was fitted by maximum likelihood, which accounts for non-normal skewness and/or kurtosis in the data . Thirdly, HGS centile curves for men and women were plotted in charts. Finally, unadjusted and adjusted logistic regression models separate for men and women were created to investigate the sociodemographic and anthropometric variables associated with muscle weakness, being estimated the odds ratio (OR) with 95%CI. Variables with p < 0.20>
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Figure 1 describes the flow chart of the participants throughout the study. Our analytical sample was composed of 7905 participants aged 50–101 years (63.1 ± 9.1 years): 3162 men (63.2 ± 8.7 years) and 4743 women (63.1 ± 9.4 years). The excluding participants were similar to including participants regarding sex (p = 0.092), schooling (p = 0.813), and monthly household income per capita (p = 0.189) but tended to be older (? 80 years: 11.8% vs. 6.5%, respectively, p < 0.001).
The characteristics of your analysis professionals because of the sex is visible inside Table 1. Both in sexes, most members were non-white, lived in the fresh new town, had 0–cuatro years of schooling, and you will showed improved waist circumference. In regards to the Body mass index, overweight are the most prevalent class for men (42.9%), if you find yourself obese and obesity got nearly comparable wavelengths for women (thirty-six.9% and thirty five.4%, respectively). Away from persistent sickness, forty two.1% out of members reported with a healthcare analysis regarding arterial blood pressure level, 17.4% from diabetic issues mellitus, 11.5% out of osteoporosis, 7.4% off heart disease (angina, myocardial infarction, and you can center incapacity), and you can 5.7% out of breathing problems (symptoms of asthma and you can chronic obstructive pulmonary disease).