Prev med. 2010_mar_50(3)_106-11
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Transcripts - Prev med. 2010_mar_50(3)_106-11
Preventive Medicine 50 (2010) 106–111 Contents lists available at ScienceDirect Preventive Medicine j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / y p m e dDyslipidemia in seven Latin American cities: CARMELA studyRaul Vinueza a,⁎, Carlos Pablo Boissonnet b, Monica Acevedo c, Felipe Uriza d, Francisco Jose Benitez e,Honorio Silva a, Herman Schargrodsky f, Beatriz Champagne g, Elinor Wilson hand on behalf of the CARMELA Study Investigatorsa InterAmerican Foundation for Clinical Research, 708 Third Avenue, Sixth Floor, New York, NY 10017, USAb Coronary Care Unit, Centro de Educación Médica e Investigaciones Clínicas “Norberto Quirno,” Buenos Aires, Argentinac Department of Cardiovascular Diseases, Pontiﬁcia Universidad Catolica de Chile, Santiago, Chiled Pontiﬁcia Universidad Javeriana, Bogotá, Colombiae Chief of Cardiology Service, Hospital Metropolitano de Quito, Quito, Ecuadorf Department of Cardiology, Hospital Italiano de Buenos Aires, Buenos Aires, Argentinag InterAmerican Heart Foundation, Dallas, Texas, USAh Department of Community and Preventive Health, School of Medicine and Dentistry, University of Rochester, Rochester, New York, USAa r t i c l e i n f o a b s t r a c tAvailable online 23 December 2009 Objective. The objective of this study was to describe the prevalence of dyslipidemia in the CARMELA study population.Keywords: Methods. CARMELA was a cross-sectional study of cardiovascular risk conducted between SeptemberDyslipidemia 2003 and August 2005 in adults (aged 25 to 64 years) living in Barquisimeto (n = 1,824), Bogotá (n = 1,511),Urban population Buenos Aires (n = 1,412), Lima (n = 1,628), Mexico City (n = 1,677), Quito (n = 1,620), and SantiagoCross-sectional studiesLatin America (n = 1,605). Dyslipidemia was deﬁned as the presence of one or more of the following conditions: triglycerides ≥ 200 mg/dL, or total cholesterol (TC) ≥ 240 mg/dL, or HDL cholesterol b 40 mg/dL, or LDL cholesterol = not optimal, or currently taking antilipemic agents. Results. Prevalence rates of dyslipidemia in men and women were: 75.5% (CI: 71.9–79.1) and 48.7% (CI: 45.4–51.9) in Barquisimeto; 70% (CI: 66.2–73.8) and 47.7% (CI: 43.9–51.5) in Bogotá; 50.4% (CI: 46.8–54.0) and 24.1% (CI: 21.0–27.2) in Buenos Aires; 73.1% (CI: 69.3–76.8) and 62.8% (CI: 59.2–66.5) in Lima; 62.5% (CI: 58.5–66.5) and 37.5% (CI: 33.5–41.6) in Mexico City; 52.2% (CI: 47.9–56.5) and 38.1% (CI: 34.5–41.7) in Quito; and, 50.8% (CI: 47.1–54.4) and 32.8% (CI: 29.3–36.3) in Santiago. Conclusions. Dyslipidemia was disturbingly prevalent and varied across cities. The most frequent dyslipidemia was low HDL-C followed by high triglycerides. The high TC/HDL-C ratios and non-HDL-C levels suggest a high risk of cardiovascular disease. © 2009 Elsevier Inc. All rights reserved.Introduction recognition of the association between cardiovascular disease and serum cholesterol in the 1950s (Criqui and Golomb, 1998). Hyper- As the last century saw a decline in the burden of nutritional cholesterolemia currently causes 4.3 million deaths per year world-deﬁciency and infectious disease, the global burden of chronic disease, wide and 39 million disability-adjusted life years lost (Ezzati et al.,cardiovascular disease in particular, is increasing (Yusuf et al., 2001). 2005). As lipid science has evolved, it has become evident that there isIn 2002, cardiovascular disease was responsible for 17 million deaths a complex interaction between serum lipid fractions, promptingworldwide (Yach et al., 2004); nearly three-quarters of these deaths medical societies and governmental organizations to establish guide-occurred in low and middle income countries. It has been estimated lines for assessment and treatment of dyslipidemia. The Nationalthat by 2010, cardiovascular disease will be the leading cause of death Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPin developing countries (WHO, 2007a, 2007b). III) guidelines (National Cholesterol Education Program, 2002), in Dyslipidemias are well-established risk factors for cardiovascular particular, are spread worldwide.disease; in particular, hypercholesterolemia has been of concern since Although assessments of cardiovascular risk factors have been primarily derived from wealthy, developed countries, variations among populations reveal the complexity of components that comprise the lipid proﬁle (Menotti et al., 1993). Both small and ⁎ Corresponding author. large studies (Ciruzzi et al., 2003; Lanas et al., 2007; Ezzati, 2004; E-mail address: firstname.lastname@example.org (R. Vinueza). Yusuf et al., 2004) conﬁrm that rates of myocardial infarction in Latin0091-7435/$ – see front matter © 2009 Elsevier Inc. All rights reserved.doi:10.1016/j.ypmed.2009.12.011
R. Vinueza et al. / Preventive Medicine 50 (2010) 106–111 107America reﬂect the contributions of multiple cardiovascular risk according to NCEP-ATP III criteria (National Cholesterol Education Program,factors. Latin America encompasses a wide variety of geographic, 2002).ethnic, and socioeconomic differences; thus, prevalence of risk factorswould be expected to reﬂect this diversity. The Cardiovascular Risk Statistical analysisFactor Multiple Evaluation in Latin America (CARMELA) study wasdesigned to evaluate and compare cardiovascular risk factor preva- Statistical processing addressed the non-equal probability character of the sample to generate data adjusted for the age and sex distribution of thelence in seven Latin American cities. Overall prevalence of cardiovas- population of each city. Therefore, weighted means and prevalence, alongcular risk factors has been reported previously (Schargrodsky et al., with their 95% conﬁdence intervals, were estimated by survey analysis2008); comparative lipid proﬁles and prevalence of dyslipidemia by procedures (SAS Software, Release 9.1, Cary, North Carolina, USA), taking intocity are reported here. account the multistage stratiﬁed sampling design via CLUSTER and STRATA statements. Overall prevalence was age-adjusted by the direct method, usingMethods the age distribution of the 2000 world population, to allow comparison between participant cities. A p-value b 0.05 was considered signiﬁcant. CARMELA was a cross-sectional, population-based, observational studyusing stratiﬁed multistage sampling. The study was carried out between ResultsSeptember 2003 and August 2005 in Barquisimeto (Venezuela), Bogotá(Colombia), Buenos Aires (Argentina), Lima (Peru), Mexico City (Mexico),Quito (Ecuador), and Santiago (Chile). The study was conducted according to A total of 11,550 participants between the ages of 25 and 64 yearsthe Declaration of Helsinki and the Good Clinical Practice Guidelines. were enrolled; lipid laboratory assessments were carried out in all Approximately 1600 participants, between 25 and 64 years old, were to enrolled subjects but LDL-C was not calculated in 273 subjects due tobe included per city. Based on an initial evaluation of costs, general Friedewalds formula limitation (triglycerides N 400 mg/dL). Nosuggestions for surveillance of non-communicable diseases (Bonita et al., imputations were applied for these missing values.2001) and acceptable levels of precision (95% CI: ±1 to ±6) it was decided tointerview a sample of 200 subjects per sex and 10-year age group. Lipid proﬁles To assure that any subject had a non-null and known beforehandprobability of being selected, the following steps were applied: 1) cities were Unique lipid proﬁles were found for each city (Table 1). Between-divided into strata (geographic sectors) and then into blocks; 2) all blocks city heterogeneity p-value was b0.0001 for all lipid values. TC, LDL-C,were identiﬁed by a sequential number in a map; 3) the total number ofhouseholds in each city and the absolute distribution of subjects for each 10- and triglycerides increased with age in all cities (p b 0.0001) whileyear age group, to calculate a sampling fraction, were obtained from the last HDL-C was relatively ﬂat across the age groups in all cities. Men hadavailable census; 4) the ﬁnal sample size to be selected was expanded based higher values of triglycerides in all cities (p b 0.0001) while womenon the non-response rate found during a pilot study, which served to had higher values of HDL-C in all cities (p b 0.0001). TC and LDL-Ccalculate the total number of households per age group needed to be visited; showed diverse patterns by sex groups within cities, men had higher7) the number of blocks to be selected in each stratum and then the number TC and LDL-C in Buenos Aires (p = 0.0007 and p b 0.0001) and higherof households to be selected in each block were calculated using predeﬁned TC in Quito (p = 0.0431), meanwhile women had higher TC informulas; 8) a set of blocks was selected by simple random sampling; 9) the Barquisimeto (p = 0.0295) and higher LDL-C in Barquisimetoselected blocks were visited and all households were identiﬁed and (p = 0.0075) and Lima (p = 0.437). There were no differences in TCregistered in a dataset; 10) the set of households at each block was randomly or LDL-C in the other cities.selected and placed in four categories based on the four age group sample In contrast to the relatively high values of TC and LDL-C in Buenosfractions and the number of households needed to be visited in each block,such that in Category 1, all residents 25–64 years old were interviewed; in Aires, Mexico City, Quito, and Santiago, HDL-C was higher in thoseCategory 2, only residents 35–64 years old were interviewed; in Category 3, same cities; lower HDL-C values were found in cities with relativelyonly residents 45–64 years old were interviewed; and in Category 4, only lower TC (Barquisimeto, Bogotá, and Lima). This variability wasresidents 55–64 years old were interviewed; and 11) the probability of being reﬂected in unique TC/HDL-C levels. For example, Lima, with both lowselected for a subject of the population was the result of multiplying three TC level and low HDL-C, had the highest value for TC/HDL-C.ﬁgures: the probability that the block where the subject resides is chosen; Reciprocally, Buenos Aires, with high TC and high HDL-C, exhibitedthe probability that the household in the selected block is chosen; and the a relatively low TC/HDL-C ratio.probability that the subject is chosen, given that the subjects household has Subjects with hypertension (systolic ≥ 140mmHg or diasto-been selected. lic ≥ 90mmHG), diabetes (fasting glucose ≥ 126mg/dL or self- The selected subjects completed a single clinical visit at designated reported), obesity (BMI N 30) and abdominal obesity (waist N 102 cminstitutions in each city. After a 12–14 hour overnight fast, venous blood wasdrawn during morning hours. Blood samples were processed immediately in men, N88 cm in women), had consistently higher values of TC/HDL-using commercially available kits. Procedures were standardized before study C (p b 0.0001) in all cities. Similarly, subjects with hypertension,initiation and controlled for quality during the studys conduction by a central diabetes, abdominal obesity, and carotid artery plaque had higherreference laboratory. Total cholesterol (TC) was determined by the values of Non-HDL-C (p b 0.0001) in all cities. Besides the mentionedspectrophotometry cholesterol oxidase/peroxidase enzymatic method. conditions, when all cities were pooled together, TC/HDL-C showedSerum triglycerides (TG) and high density lipoprotein cholesterol (HDL-C) higher values in subjects with sedentary physical activity (p = 0.003),were determined by the glycerol enzymatic method and the precipitating low years of education (p = 0.0014), prior myocardial infarctionreactive method, respectively. Low density lipoprotein cholesterol (LDL-C) (p = 0.0001) or prior angina attack (p = 0.0356). Non-HDL-C alsowas calculated by the Friedewald formula (LDL-C = [TC − HDL-C] − [TG/5], showed higher values in subjects with sedentary physical activityvalid if TG b 400 mg/dL) (Friedewald et al., 1972); non-HDL-C (TC − HDL-C) (p = 0.0011), low years of education (p = 0.036) or prior myocardialand TC/HDL-C were calculated. infarction (p = 0.0017).Deﬁnitions Prevalence of dyslipidemia Dyslipidemia was deﬁned as the presence of one of more of the followingconditions: TG ≥ 200 mg/dL, TC ≥ 240 mg/dL, HDL-C b 40 mg/dL, LDL-C = not The classiﬁcation of lipids fractions according to the NCEP-ATP III isoptimal (LDL-C ≥ 100 mg/dL if Framingham 10-year risk score = high, or shown in Fig. 1 and weighted prevalence of dyslipidemia is presentedLDL-C ≥ 130 mg/dL if Framingham 10-year risk score = intermediate, or in Table 2. The overall prevalence of dyslipidemia was different in allLDL-C ≥ 160 mg/dL if Framingham 10-year risk score = low) (Wilson et al., cities, between-city heterogeneity p-value was b0.0001. Substantially1998), or currently taking antilipemic agents. Lipid values were classiﬁed more men than women had dyslipidemia in each city (p b 0.0001).
108 R. Vinueza et al. / Preventive Medicine 50 (2010) 106–111Table 1Weighted mean lipid values (mg/dLa) (95% conﬁdence interval). CARMELA study, September 2003–August 2005. TC LDL-C HDL-C TG Non-HDL-C TC/HDL-C Barquisimeto n = 1848 n = 1784 n = 1848 n = 1848 n = 1848 n = 1848 All 174.2 (171.8–176.5) 104.6 (102.4–106.3) 40.1 (39.4–40.9) 150.7 (144.8–156.6) 134.1 (131.9–136.2) 4.6 (4.5–4.7) Men 171.7 (168.6–174.8) 101.9 (99.2–104.6) 35.8 (35.0–36.7) 177.1 (166.2–187.9) 135.9 (132.9–138.9) 5.1 (4.9–5.2) Women 175.8 (172.9–178.7) 106.3 (104.2–108.4) 42.9 (42.1–43.8) 133.4 (128.4–138.5) 132.9 (130.2–135.5) 4.3 (4.2–4.4) Bogotá n = 1553 n = 1472 n = 1553 n = 1553 n = 1553 n = 1553 All 193.7 (191.4–196.1) 120.4 (118.2–122.7) 42.2 (41.6–42.9) 164.7 (157.9–171.5) 151.5 (149.0–154.0) 4.9 (4.8–5.0) Men 195.2 (192.0–198.5) 119.8 (116.7–122.9) 39.2 (38.4–39.9) 200.0 (190.2–209.9) 156.1 (152.6–159.5) 5.2 (5.1–5.4) Women 192.5 (189.5–195.6) 120.9 (118.1–123.7) 44.6 (43.8–45.5) 136.8 (129.4–144.3) 147.9 (144.9–150.9) 4.6 (4.5–4.7) Buenos Aires n = 1482 n = 1461 n = 1482 n = 1482 n = 1482 n = 1482 All 201.0 (198.5–203.5) 126.1 (123.8–128.4) 52.5 (51.7–53.3) 114.3 (110.4–118.2) 148.6 (146.0–151.1) 4.1 (4.0–4.1) Men 205.0 (201.4–208.6) 132.2 (128.9–135.4) 46.6 (45.7–47.5) 134.9 (128.2–141.6) 158.4 (155.0–161.8) 4.6 (4.5–4.7) Women 197.7 (194.3–201.1) 121.1 (118.4–123.8) 57.5 (56.4–58.5) 96.9 (91.7–102.1) 140.2 (137.0–143.4) 3.6 (3.5–3.7) Lima n = 1652 n = 1619 n = 1652 n = 1652 n = 1652 n = 1652 All 188.4 (186.2–190.7) 121.5 (119.8–123.3) 39.4 (38.8–40.0) 140.3 (135.2–145.4) 148.6 (146.0–151.1) 5.0 (4.9–5.1) Men 187.3 (184.4–190.1) 119.7 (117.3–122.0) 37.4 (36.6–38.1) 155.3 (147.6–163.0) 149.9 (147.0–152.8) 5.2 (5.1–5.3) Women 189.5 (186.3–192.8) 123.3 (120.8–125.8) 41.3 (40.5–42.2) 125.5 (119.8–131.2) 148.2 (145.4–151.1) 4.7 (4.7–4.8) Mexico City n = 1722 n = 1631 n = 1722 n = 1722 n = 1722 n = 1722 All 202.9 (200.2–205.5) 118.7 (116.9–120.6) 49.2 (48.3–50.1) 183.9 (175.2–192.6) 153.7 (150.9–156.4) 4.3 (4.3–4.4) Men 204.3 (200.9–207.6) 120.6 (118.1–123.1) 44.1 (43.2–45.0) 214.3 (204.2–224.4) 160.2 (156.9–163.5) 4.8 (4.7–4.9) Women 201.6 (198.2–205.0) 117.2 (114.5–119.8) 53.7 (52.6–54.7) 157.2 (148.8–165.6) 147.9 (144.4–151.5) 3.9 (3.8–4.0) Quito n = 1638 n = 1582 n = 1638 n = 1638 n = 1638 1638 All 207.3 (204.6–210.0) 126.6 (124.3–128.9) 49.0 (48.3–49.7) 162.5 (156.1–168.9) 158.3 (155.5–161.1) 4.4 (4.3–4.5) Men 209.6 (206.0–213.2) 127.8 (124.6–130.9) 46.6 (45.7–47.5) 181.9 (172.8–191.1) 163.0 (159.3–166.8) 4.7 (4.6–4.8) Women 205.0 (201.5–208.4) 125.5 (122.6–130.9) 51.4 (50.5–52.2) 143.2 (136.4–150.0) 153.6 (150.1–157.1) 4.2 (4.1–4.3) Santiago n = 1655 n = 1595 n = 1655 n = 1655 n = 1655 n = 1655 All 199.1 (196.7–201.5) 119.6 (117.7–121.4) 49.4 (48.7–50.0) 159.6 (149.2–170.0) 149.8 (147.4–152.2) 4.3 (4.2–4.3) Men 199.0 (196.0–201.9) 119.9 (117.4–122.5) 45.5 (44.7–46.3) 177.1 (167.0–187.2) 153.5 (150.4–156.5) 4.6 (4.5–4.7) Women 199.3 (196.2–202.4) 119.2 (116.8–121.6) 52.9 (51.9–53.9) 143.6 (126.7–160.6) 146.4 (143.3–149.4) 4.0 (3.9–4.0)TC = total cholesterol; LDL-C = low density lipoprotein cholesterol, calculated; HDL-C = high density lipoprotein cholesterol; TG = triglycerides; non-HDL-C = non-high densitylipoprotein cholesterol, calculated; TC/HDL-C = total cholesterol/HDL-C ratio, calculated. a Except TC/HDL-C, ratio reported without units. Due to the wide variation in lipid proﬁles among cities, the relative NCEP-ATP III guidelines suggest that as a secondary target of therapy,importance of speciﬁc lipid factors ﬂuctuated. In Lima, Barquisimeto, a reasonable goal for non-HDL would be 30 mg/dL higher than theand Bogotá, low HDL-C characterized dyslipidemia, while in Mexico LDL-C goal (i.e. 130, 160 or 190 mg/dL, depending of the CHD risk). InCity, high triglycerides were the most frequent. In contrast, preva- the CARMELA study the mean values of non-HDL-C ranged from 133.8lence of abnormally high TC, LDL-C or triglycerides or low HDL-C was mg/dL in Barquisimeto to 183.1 mg/dL in Mexico City, suggesting thatrelatively similar in Quito, Santiago, and Buenos Aires. an important number of subjects would be above their target levels Despite high prevalence of hypercholesterolemia, pharmacologic across cities.treatment among the patients who were prescribed antilipemic The TC/HDL-C ratio has been correlated with the development ofagents was not common and varied across cities; Buenos Aires acute coronary events and it is considered to give the most predictivereported 45% and Chile 42% at the top tier, followed by Mexico City lipid value (Assmann et al., 1998; Castelli 1996; Kinosian et al., 1994).22%, Lima 20%, and Bogotá 18%, at the middle tier, and Barquisimeto It is of note that the mean TC/HDL-C in all CARMELA cities was above8% and Quito 8% at the lowest tier. the suggested goal for this ratio, b4 (Criqui and Golomb, 1998), which implies that an important segment of the CARMELA population wouldDiscussion be at higher risk of cardiovascular disease. Furthermore, in the CARMELA study, subjects with previous myocardial infarction and Dyslipidemia was highly prevalent in the seven assessed cities. The angina episodes showed signiﬁcantly higher values of TC/HDL-C thanmain dyslipidemia factors were low HDL-C and high triglycerides, patients without them.event though high TC and LDL-C were vastly prevalent. The lipid Comparisons of CARMELA with other Latin American studies areproﬁles were heterogeneous across cities, sex and age groups difﬁcult due to methods and time differences. The World Health(p N 0.0001) but shared some remarkable patterns. The low rate of Organization cites TC values for the 7 countries in the CARMELA studyantilipemic therapy is also of note, given the substantial evidence that ranging from 174 mg/dL (Venezuela) to 240 mg/dL (Colombia)cholesterol reduction is valuable in reducing cardiovascular disease (WHO, 2007a, 2007b). In the CARMELA study, which used a sampling(Grundy et al., 2004). approach intended to represent city-wide values, TC was also lowest Abnormally high TC and LDL-C levels correlate with increasing in Barquisimeto, Venezuela (174 mg/dL). However, highest meancardiovascular risk. However, the predictive power of a given TC value values for TC were found in Quito, Ecuador (207 mg/dL). Anothermay be inﬂuenced by genetic, cultural, and environmental factors recent study, based on a non-representative sample, reported higher(Criqui and Golomb, 1998; Grover et al 1994; and Law et al., 1994). TC, LDL-C, and HDL-C values than the ones reported in the CARMELAConversely, high HDL-C is considered a protective factor (Assmann study (Touboul et al, 2006).and Gotto, 2004; Gordon et al., 1989). Paradoxically, in the CARMELA Turning to hypercholesterolemia (TC ≥ 240 mg/dL), WHOstudy, the highest HDL-C levels were found in cities with the highest reported prevalence of 20% and 10% in Argentina and Venezuela,TC levels, conﬁrming that speciﬁc lipid factors taken alone do not respectively (WHO, 2007a, 2007b). The disparity between countries isuniformly reﬂect risk in a population. similar to that found in corresponding cities in the CARMELA study. The non-HDL-C has been suggested as better predictor of Other studies in Latin America reported different trends, onecardiovascular disease than LDL-C and easier to calculate (Cui et al., conducted in Bucaramanga, Colombia (Bautista et al., 2006) reported2001; Bittner et al., 2002; Pischon et al., 2005; Ridker et al., 2005). prevalence of hypercholesterolemia of 15.7% in men and 19.7% in
R. Vinueza et al. / Preventive Medicine 50 (2010) 106–111 109 Fig. 1. Weighted prevalence of normal and abnormal lipid values based on NCEP-ATP III classiﬁcations by city. CARMELA study, September 2003–August 2005.women; another study in Puriscal, Costa Rica (Campos et al 1992) a Brazilian city, hypercholesterolemia was lower than the one in thereported 7.2% in men and 9.2% in women; meanwhile the pooled CARMELA study (4% vs 14%) (de Souza et al., 2003). In the latter study,CARMELA population found 14.2% in men and 13.6% in women; and in overall dyslipidemia (24%), deﬁned similarly to those in CARMELA,Table 2Weighted prevalence (%) (95% conﬁdence interval) of dyslipidemia. CARMELA study, September 2003–August 2005. Barquisimeto Bogotá Buenos Aires Lima Mexico City Quito Santiago Dyslipidemiaa n = 1848 n = 1553 n = 1482 n = 1652 n = 1722 n = 1638 n = 1655 Overall 59.6 (56.7–62.6) 58.2 (55.2–61.3) 38.7 (36.2–41.2) 68.1 (65.5–70.8) 50.1 (46.9–53.3) 45.7 (42.7–48.6) 42.7 (40.0–45.3) Men 75.7 (72.1–79.3) 70.5 (66.8–74.2) 52.4 (48.8–56.0) 73.4 (69.7–77.0) 63.3 (59.4–67.2) 52.6 (48.3–56.8) 51.5 (47.9–55.1) Women 49.1 (45.9–52.4) 48.6 (44.8–52.4) 27.1 (23.9–30.3) 63.0 (59.4–66.6) 34.6 (33.5–42.5) 38.1 (34.5–41.7) 34.6 (31.2–38.0) TC ≥240 mg/dL n = 1848 n = 1553 n = 1482 n = 1652 n = 1722 n = 1638 n = 1655 Overall 5.7 (4.7–6.7) 11.7 (10.2–13.2) 18.7 (16.7–20.7) 11.6 (10.1–13.1) 16.4 (14.2–18.7) 20.2 (18.0–22.3) 15.3 (13.4–17.2) Men 4.5 (2.9–6.0) 11.8 (9.3–14.3) 19.3 (16.5–22.1) 9.8 (7.9–11.7) 16.9 (14.0–19.9) 21.7 (18.3–25.1) 15.8 (13.2–18.4) Women 6.4 (5.0–7.9) 11.1 (9.0–13.2) 16.9 (14.3–19.6) 12.4 (10.3–14.6) 15.2 (12.2–18.1) 18.6 (15.9–21.4) 14.3 (11.8–16.9) LDL-C = not optimal n = 1784 n = 1472 n = 1461 n = 1619 n = 1631 n = 1582 n = 1595 Overall 9.8 (8.4–11.2) 19.1 (16.7–21.5) 24.7 (22.2–27.1) 17.7 (15.9–19.4) 25.6 (23.3–27.9) 23.9 (21.2–26.6) 19.9 (17.9–21.9) Men 10.1 (8.0–12.3) 21.7 (19.0–24.5) 34.0 (30.5–37.6) 17.4 (14.9–19.9) 30.8 (26.0–35.6) 26.6 (22.9–30.4) 23.7 (20.5–26.8) Women 9.7 (7.7–11.6) 17.1 (14.1–20.2) 17.0 (14.3–19.7) 17.9 (15.2–20.6) 21.5 (18.8–24.2) 21.4 (17.8–25.0) 16.6 (14.2–19.0) HDL-C b40 mg/dL n = 1848 n = 1553 n = 1482 n = 1652 n = 1722 n = 1638 n = 1655 Overall 52.2 (49.1–55.4) 45.6 (42.1–49.1) 16.9 (15.1–18.8) 56.9 (53.7–60.0) 22.6 (20.1–25.1) 21.6 (19.0–24.2) 21.2 (18.8–23.5) Men 70.7 (66.8–74.5) 59.0 (54.8–63.2) 29.4 (26.2–32.5) 64.5 (60.4–68.5) 35.2 (31.7–38.8) 27.7 (24.3–31.2) 31.1 (27.9–34.4) Women 40.2 (36.7–43.7) 35.1 (31.0–39.1) 6.4 (4.4–8.4) 49.3 (45.0–53.6) 11.5 (8.7–14.4) 15.5 (12.6–18.3) 12.1 (9.2–14.9) TG ≥200 mg/dL n = 1848 n = 1553 n = 1482 n = 1652 n = 1722 n = 1638 n = 1655 Overall 20.2 (17.9–22.4) 23.2 (20.8–25.5) 9.8 (8.6–11.1) 19.5 (17.6–21.5) 32.5 (29.4–37.5) 23.8 (21.4–26.3) 22.7 (20.5–24.9) Men 27.9 (24.2–31.7) 33.8 (30.8–36.9) 16.0 (13.5–18.5) 25.1 (22.1–28.1) 43.3 (39.1–47.5) 29.7 (26.2–33.3) 30.0 (26.9–33.1) Women 15.1 (12.9–17.4) 14.8 (12.1–17.4) 4.6 (3.0–6.2) 14.0 (11.6–16.4) 23.1 (20.1–26.0) 18.0 (15.1–20.8) 16.0 (13.5–18.6) Current therapy n = 241 n = 196 n = 153 n = 114 n = 186 n = 219 n = 112 Allb 8.2 (4.6–11.7) 18.1 (11.9–24.4) 44.5 (35.7–53.3) 19.9 (11.5–28.2) 21.7 (14.7–28.8) 8.3 (4.1–12.4) 41.9 (32.1–51.7) Menb 9.0 (1.8–16.2) 20.2 (9.8–30.7) 42.9 (29.1–56.7) 23.5 (5.7–41.3) 23.6 (13.2–34.0) 23.6 (13.2–34.0) 32.8 (18.8–46.7) Womenb 7.8.(4.3–11.2) 16.7 (10.0–23.5) 46.0 (34.0–57.9) 17.4 (10.9–23.9) 19.9 (8.6–31.2) 19.9 (8.6–31.2) 48.9 (36.8–60.9) a Presence of dyslipidemia was deﬁned by the following criteria: triglycerides ≥200 mg/dL, or TC ≥240 mg/dL, HDL-C b40 mg/dL or LDL-C = not optimal (LDL-C ≥100 mg/dL ifFramingham 10-year risk score = high, or LDL-C ≥ 130 mg/dL if Framingham 10-year risk score = intermediate, or LDL-C ≥ 160 mg/dL if Framingham 10-year risk score = low)13 orcurrently taking antilipemic agents. b Subjects currently taking antilipemic agents among all subjects who were prescribed antilipemic therapy.
110 R. Vinueza et al. / Preventive Medicine 50 (2010) 106–111was also lower than all seven CARMELA cities, illustrating the general Buitrón and Jesús Ramírez-Martínez at the Instituto Mexicano dedissimilarity in lipid proﬁles across Latin American cities. Seguridad Social; Francisco Benítez, María Velasco and Luis Falconí at Evaluating other regions, a Saudi Arabian study observed the Hospital Metropolitano de Quito; Ximena Berrios-Carrasola,variations in patterns of lipid proﬁles across 5 geographic regions; Beatriz Guzmán and Mónica Acevedo at the Pontiﬁcia Universidadthe authors noted that these variations were not entirely consistent Católica de Santiago de Chile. The authors would like to thank Martawith the concept that more developed areas had a higher prevalence Torres for compiling clinical laboratory analysis; Héctor Rosso forof dyslipidemia, and that other factors might contribute to this database design and administration; Fabio Pellegrini, MSC andvariation (al-Nuaim, 1997). Indeed, despite the common attribution Alejandro Macchia, MD of Mario Negri Institute for statistical support;of hypercholesterolemia as a “disease of afﬂuence,” it has been and Javier Valenzuela administrative and communication assistance.recently suggested that body mass index and cholesterol increase Editorial support was provided by Beth Young, PhD and Lynn Rudich,rapidly with national income, and after leveling off, eventually MD at Envision Pharma and was funded by Pﬁzer Inc.decline, reﬂecting change in energy consumption at much earlier Funding: The CARMELA study was funded by Pﬁzer Inc.stages of economic development than previously recognized (Ezzatiet al., 2005). Variations along the spectrum of economic development References(International Money Found, 2007) might well be reﬂected in thedistinct variations in lipid proﬁles among the 7 CARMELA cities. al-Nuaim, A.R., 1997. 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