Risk Factors for Cardiovascular Disease, Metabolic Syndrome and Sleepiness in Truck Drivers

Abstract Background: Truck driver sleepiness is a primary cause of vehicle accidents. Several causes are associated with sleepiness in truck drivers. Obesity and metabolic syndrome (MetS) are associated with sleep disorders and with primary risk factors for cardiovascular diseases (CVD). We analyzed the relationship between these conditions and prevalence of sleepiness in truck drivers. Methods: We analyzed the major risk factors for CVD, anthropometric data and sleep disorders in 2228 male truck drivers from 148 road stops made by the Federal Highway Police from 2006 to 2011. Alcohol consumption, illicit drugs and overtime working hours were also analyzed. Sleepiness was assessed using the Epworth Sleepiness Scale. Results: Mean age was 43.1 ± 10.8 years. From 2006 to 2011, an increase in neck (p = 0.011) and abdominal circumference (p < 0.001), total cholesterol (p < 0.001), triglyceride plasma levels (p = 0.014), and sleepiness was observed (p < 0.001). In addition, a reduction in hypertension (39.6% to 25.9%, p < 0.001), alcohol consumption (32% to 23%, p = 0.033) and overtime hours (52.2% to 42.8%, p < 0.001) was found. Linear regression analysis showed that sleepiness correlated closely with body mass index (β = 0.19, Raj2 = 0.659, p = 0.031), abdominal circumference (β = 0.24, Raj2 = 0.826, p = 0.021), hypertension (β = -0.62, Raj2 = 0.901, p = 0.002), and triglycerides (β = 0.34, Raj2 = 0.936, p = 0.022). Linear multiple regression indicated that hypertension (p = 0.008) and abdominal circumference (p = 0.025) are independent variables for sleepiness. Conclusions: Increased prevalence of sleepiness was associated with major components of the MetS.

Sôbre uma propriedade da equação utilizada para interpolação da Lei de Mitscherlich

The author proves that equation, Σy n ΣZx | ΣxyZx ΣxZx ΣxZ2x | = 0, Σy ΣZx Σy2x | where Z = 10-cq and q is a numerical constant, used by Pimentel Gomes and Malavolta in several articles for the interpolation of Mitscherlih's equation y = A [ 1 - 10 - c (x + b) ] by the least squares method, always has a zero of order three for Z = 1. Therefore, equation A Zm + A1Zm -1 + ........... + Am = 0 obtained from that determinant can be divided by (Z-1)³. This property provides a good test for the correctness of the computations and facilitates the solution of the equation.

A lei de Mitscherlich aplicada a experimentos de adubação com vinhaça

The author studies, with the aid of Mitscherlich's law, two experiments of sugar cane fertilization with vinasse. The first one, carried out in Piracicaba, State of S. Paulo, by ARRUDA, gave the following yields. No vinasse 47.0 tons/ha. 76.0 tons/ha. 250 c.m./ha. of vinasse 75.0 do. 112.0 do. 500 do. 90.0 do. 112.0 do. 1000 do. 98.0 do. 107.0 do. Data without NPK were appropriate for the fitting of the law, the equation of which was found to be: y = 100.8 [1 - 10 -0.00132 (x + 206) ], where y is measured in metric tons/hectare, and x in cubic meters/hectare. The optimum amount of vinasse to be used is given by the formula x* = 117.2 + 1 log w u , ______ ____ 0.00132 250 t being u the response to the standard dressing of 250 cubic meters/hectare of vinasse, w the price per ton of sugar cane, and t the price per cubic meter for the transportation of vinasse. In Pernambuco, a 3(4) NPK vinasse experiment gave the following mean yields: No vinasse 41.0 tons/hectare 250 cm./ha. of vinasse 108.3 do. 500 do. 134.3 do. The equation obtained was now y = 150.7 [1 - 10 -000165 (x + 84)], being the most profitable level of vinasse x* = 115.2 + 1 log w u , _______ ____ 0.00165 250 t One should notice the close agreement of the coefficients c (0.00132 in S. Paulo and 0.00165 in Pernambuco). Given the prices of Cr$ 20.00 per cubic meter for the transportation of vinasse (in trucks) and Cr$ 250.00 per ton of sugar cane (uncut, in the fields) the most profitable dressings are: 236 c.m./ha. of vinasse in S. Paulo, and 434 c.m./ha. in Pernambuco.

Sôbre uma fórmula para o cálculo da dose mais econômica de adubo

The authors discuss a formula for the determination of the most profitable level of fertilization (x*). This formula, presented by CAREY and ROBINSON (1953), can be written as: x*= (1/c) log cx u L10 + (1/c) log wu _______ ___ 1-10 x u t being c the growth factor in Mitscherlich's equation, x u a standard dressing of the nutrient, L 10 the Naeperian logarithm of 10, u the response to the standard dressing, w the unit price of the crop product, and i the unit price of the nutrient. This formula is a modification of one of the formulas of PIMENTEL GOMES (1953). One of its advantages is that is does not depend on A, the theoretical maximum harvest, which is not directly given by experimental data. But another advantage, proved in this. paper, is that the first term on the right hand side K= 1(/c) log cx u L 10 ____________ 1 - 10-cx u is practically independent of c, and approximately equivalent to (1/2) x u. So, we have approximately x* = (1/2) x u + (1/c) log wu . ____ x u t With experimental data we compute z = wu ____ x u t then using tables 1, 2 and 3, we may obtain Y - (1/c) log z and finally x* = (1/2) x u + Y. This is an easy way to determine the most profitable level of fertilization when experimental data on the response u to a dressing x u are available. Tables for the calculation of Y are included, for nitrogen, phosphorus, potash, and manure.

O problema técnico-econômico da adubação

The authors discuss from the economic point of view the use of a few functions intended to represent the yield y corresponding to a level xof the nutrient. They point out that under conditions of scarce capital what is actually most important is not to obtain the highest profit per hectare but the highest return per cruzeiro spent, so that we should maximize the function z = _R - C_ = _R_ - 1 , C C where R is the gross income and C the cost of production (fixed plus variable, both per hectare). Being C = M + rx, with r the unit price of the nutrient and Af the fixed cost of the crop, wo are led to the equation (M + rx)R' - rR = 0. With R = k + sx + tx², this gives a solution Xo = - Mt - √ M²t² - r t(Ms - Kr)- _____________________ rt on the other hand, with R = PyA [1 - 10-c(x + b)], x0 will be the root of equation (M + rx)cL 10 + r 10c(x + b) = 0 (12). Another solution, pointed out by PESEK and HEADY, is to maximize the function z = sx + tx² _________ m + rx where the numerator is the additional income due to the nutrient, and m is the fixed cost of fertilization. This leads to a solution x+ = - mt - √m²t² - mrst (13) _________________ rt However, we must have x+< _r_-_s_ I if we want to satisfy t _dy_ > r. dx This condition is satisfied only if we have m < _(s__-__r)² (14), - 4 t a restriction apparently not perceived by PESEK and HEADY. A similar reasoning using Mitscherlich's law leads to equation (mcL 10 + r) + cr(L 10)x - r 10cx = 0 (15), with a similar restriction. As an example, data of VIEGAS referring to fertilization of corn (maize) gave the equation y - 1534 + 22.99 x - 0. 1069 x², with x in kg/ha of the cereal. With the prices of Cr$ 5.00 per kilo of maize, Cr$ 26.00 per kilo of P2O3,. and M = Cr$ 5,000.00, we obtain x0 = 61 kg/ha of P(2)0(5). A similar reasoning using Mitscherlich's law leads to x0 = 53 kg/ha. Now, if we take in account only the fixed cost of fertilization m = Cr$ 600.00 per hectare, we obtain from (13) x+ = 51 kg/ha of P2O5, while (14) gives x+ - 41 kg/ha. Note that if m = Cr$ 5,000.00, we obtain by formula (13) x+ = 88 kg/ha of P2O5, a solution which is not valid, since condition (14) is not satisfied.

Estudos sôbre a Alimentação Mineral do Abacaxí (Ananas sativus) Sch

Pineapple plants when grown in the greenhouse by the sand culture technique in order to study the effects of deficiencies of macronutrients in growth, yield, leaf and fruit composition, the main results were the following. As a result of the several treatments, yield decreased in the order: Complete Minus Mg Minus S Minus Ca Minus K; nitrogen and phosphorus deficiente plants did not bear fruit. Leaf analyses (see Table 5-1) showed that the ommission of given element from the nutrient solution always caused a decrease in its level in the green tissue. As seen in Table 5-2 the lack of macronutrients had certain effects on fruit composition: acidity increased in all cases excet in the minus Mg fruits; ash usually decreased reaching its lowest valued in fruits from the minus K plants; when compared to fruits picked in the "normal" plants, those lacking K showed a marked decrease both in brix and in total sugars as well; sulfur deficiency also brought a net reduction in the sugar content. Table 5-1. Levels of macronutrients found in pinapple leaves. Elements Treatment Percent of dry matter Nitrogen (N) Complete 1.29 Minus N 0.78 Phosphorus (P) Complete 0.12 Minus P .05 Potassium (K) Complete 2.28 Minus K 0.16 Calcium (Ca) Complete 1.19 Minus Ca 1.10 Magnesium (Mg) Complete 0.41 Minus Mg .29 Sulfur (S) Complete 1.00 Minus S .65 Table 5-2. Effects of macronutrients deficiency in yield and fruit characteristics. Treatment Ave. weight of Acidity As per Brix Total sugars fruits (gm) per cent cent per cent Complete 1.031 1.16 0.40 14.7 10.8 Minus N no fruit was produced Minus P no fruit was produced Minus K 246 1.44 0.26 11.9 8.3 Minus Ca 513 1.40 0.35 17.8 14.3 Minus Mg 957 0.97 0.38 15.4 13.0 Minus S 576 1.42 0.46 17.1 6.5

A determinação do teor total de cobre, ferro, aluminio, manganês e fósforo do solo

Uma técnica de ataque de 250 ou 500 mg de amostras de solo, devidamente preparadas, com ácido perclórico e ácido fluorídrico é descrita. O resíduo do ataque com HClO4 e HF é tratado com 10 ml de solução de HC1 1,0 N e o volume é completado a 25 ou 50 ml, de acordo com o peso da amostra trabalhada, 250 ou 500 mg. As determinações executadas no extrato obtido com solução de HCl 1,0 N foram as seguintes: cobre, pelo método colorimétrico de dietilditiocarbamato; ferro, pelo método colori métrico da 1,10-fenantrolina; alumínio, pelo método colorimétrico do aluminon; manganês, pelo método colorimétrico do permanganato; e fósforo, pelo método colorimétrico do azul de molibdênio, empregando-se o acido ascorbico como redutor.

Nutrição mineral das plantas ornamentais: III. absorção de nutrientes pela rainha Margarida (Callestephus chinensis)

No sentido de aquilatar a extração dos macro e micronutrientes, com exceção do Cl e Mo, aliada ao crescimento da planta, amostragens de rainha margarida (Callestephus chinensis) foram executadas aos 0, 18, 34, 46, 59 e 77 dias após o transplante. As plantas foram divididas em raiz, caule, folhas, botões florais, flores analisadas para N, R, K, Ca, Mg, S, B, Cu, Fe, Mn e Zn. Observou-se que o crescimento da rainha margarida é contínuo, acentuando-se após os 59 dias de transplante. O teor porcentual dos nutrientes aos 34-46 dias, na matéria seca, oscilou em torno de 4,09% - 4,40% para N; 0,44% - 0,46% para P; 1,65% - 3,19% para K; 1,01% - 1,10% para Ca; 0,34% - 0,45% para Mg; 0,42% - 0,43% para S. Para os micronutrientes os valores encontrados, na mesma época, foram em ppm: B - 23-36; Cu - 18-20; Fe - 105-150; Mn - 115-135; Zn - 64-111. Uma planta de rainha-margarida aos 77 dias contem: 2.049,9 mg de N; 212,5 mg de P; 2.496,6 mg de K; 915,7 mg de Ca; 356,6 mg de Mg; 159,1 mg de S; 2.140 ug de B; 3.070 ug de Cu; 17.142 ug de Fe; 6.946 ug de Mn; 3.931 ug de Zn.

Resistência do morangueiro (Fragaria híbridos) à Mycosphaerella fragariae (TUL.) LIND. (Ramularia tulasnei SACC.)

Foram testados 49 clones de morangueiro quanto a reação à incidência natural de Ramularia tulasnei sob condições de campo, em Piracicaba, SP. A avaliação foi realizada de acordo com uma escala de 1 (ausência de sintomas) a 6 (severa incidência) na fase de maior severidade da doença e os clones classificados em resistentes (1,00 a 2,30), moderadamente resistentes (2,31 a 3,70) e suscetíveis (3,71 a 5,00). Identificaram-se 11 clones resistentes, 31 moderadamente resistentes e 7 suscetíveis. Os resistentes foram "I-2008" (grau 1,00 ± 0,00), "IAC-2713", "Camanducaia (IAC-3530)", "A. Brucknner (I-2492)","IAC-3113 x (IAC-2712 x 1-2008-1)10", "IAC-4326", "IAC-3530 x IAC-2747-2", "Kon-woy (1-3846)", "Atibaia (IAC-4325)", "1-4896 -4" e "IAC-4749" e o mais suscetível foi "Jundiaí (IAC-4204)" (grau 5,00 ± 0,41).