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"Ancho" => 2511 "Tamanyo" => 170399 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Influence of the residence altitude on haemoglobin levels and the prevalence of anaemia according to WHO criteria corrected for altitude.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Anaemia is a public health problem that affects at least a quarter of the world's population, although there are great differences between developed and developing countries.<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">1</span></a> In routine practice, it is usually diagnosed according to the lower limits of haemoglobin (Hb) proposed by WHO in 1968<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">2</span></a> (men <13<span class="elsevierStyleHsp" style=""></span>g/dl, women <12<span class="elsevierStyleHsp" style=""></span>g/dl, pregnant <11<span class="elsevierStyleHsp" style=""></span>g/dl, for residents at sea level). At moderate altitudes, it is recommended to subtract 0.2<span class="elsevierStyleHsp" style=""></span>g/dl from 1000<span class="elsevierStyleHsp" style=""></span>m and 0.5<span class="elsevierStyleHsp" style=""></span>g/dl from 1500<span class="elsevierStyleHsp" style=""></span>m, but the correction increases progressively for high altitude resident populations.<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">3</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Most of the anaemia prevalence studies have been based on these criteria, nevertheless, obtaining these was not exempt from limitations.<a class="elsevierStyleCrossRefs" href="#bib0105"><span class="elsevierStyleSup">1–4</span></a> For example, they were established based on a population with very little representation of people over 65 years of age, a range of age that currently constitutes a significant proportion of the population in the developed world. Additionally, the correction for altitude has not been validated, and some researchers have already shown limitations and problems arising from its application. For example, it has been shown that the results may be misleading in individuals residing at high altitudes,<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">5–8</span></a> leading, for example, to false polycythaemia diagnoses.</p><p id="par0015" class="elsevierStylePara elsevierViewall">The most representative data on global anaemia prevalence were collected by WHO with these criteria more than 10 years ago,<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">1</span></a> at which time the global prevalence was estimated at 24.8% and at 23.9% in those over 60 years of age. However, there are limitations to generalize these data in our environment, because the European population coverage percentage in that study was low and, in addition, the proportion of population belonging to iron deficiency anaemia risk groups (pre-schoolers, pregnant women and non-pregnant fertile age women) was very high (2/3), with low coverage of men, schoolchildren and over 60 years of age. An additional deficiency that limits its usefulness is that no data were available for the subgroup of women aged 50–59. In any case, with the data from Spain collected in said study (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>43.379) a prevalence of anaemia was estimated at 17.6% in pregnant women, 16.3% in non-pregnant women of reproductive age (15–50 years) and 12.9% in pre-schoolers. These figures correspond to those considered risk groups for anaemia, and the report did not offer estimates of other population groups. Additional information on other groups in Spain can be extracted from another subsequent study with data from 1990 to 2010,<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">9</span></a> which reported a prevalence of anaemia of 2.1% in men between 15 and 59 years of age, and 9.4% from the age of 60; 10.9%, in women aged 15 to 59 and 10.3% from the age of 60.</p><p id="par0020" class="elsevierStylePara elsevierViewall">A weakness related to global epidemiological studies to date is the lack of attention to the elderly population: the studies include “elderly population” over 60 in general, and in large population studies no subgroups are studied above this age, increasingly present in our population and for which it is imperative to have management information.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">10–12</span></a> In addition, we lack specific data for some groups at essential periods of interest, such as during the menopause in women. There are nutritional studies in Spain, conducted in the Basque Country and Catalonia, which offer data on iron deficiency anaemia, but they exclude certain population groups, such as pregnant women, chronically ill patients or children. In addition, these reports are already quite old.<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">13,14</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">In the absence of information on some population groups and the lack of general studies with adequate representation of our environment, we considered analysing Hb levels and the prevalence of anaemia in the Spanish general population through an analysis based on recent data. In addition, taking advantage of the fact that our healthcare sector covers a varied orography, representative of other areas of the Iberian peninsula, we wanted to verify the effect of the residence altitude and the result of the correction proposed by WHO in the estimates, as well as review the prevalence calculated according to the WHO criteria and through epidemiological criteria (percentiles). The general objective was to obtain recent indicative data on Hb levels and prevalence of anaemia for all ages (14 onwards) and both sexes in the Spanish general population and to reconsider our routine practice for the diagnosis of iron deficiency anaemia and its implications in the management of patients.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Design and population</span><p id="par0030" class="elsevierStylePara elsevierViewall">A cross-sectional descriptive study was carried out which included all healthcare users of the province of Huesca (Spain), of both sexes and >14 years of age, who had at least one complete blood count between 1st January 2011 and 31st December 2015. The residence altitude was assigned according to the location of its municipality, according to the National Geographic Institute (IGN, <a href="http://www.ign.es/">www.ign.es</a>). The methodology envisaged compiling all eligible blood count reports, so a sample size calculation was not previously performed. The expectation was to reach more than 70,000 patients, representing 80% of the population belonging to the healthcare sector under study, according to data from the National Statistics Institute (INE, <a href="http://www.ine.es/">www.ine.es</a>). Adequately anonymised data was collected, and only authorized persons had access to it. This study was approved by the clinical research and bioethics committees of the San Jorge de Huesca Hospital.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Procedure for selecting haemoglobin values</span><p id="par0035" class="elsevierStylePara elsevierViewall">The main source of the data was the Modulab Gold® management package (IZASA, Barcelona, Spain) and the integrated Lab database (Haematology and Clinical Biochemistry) of the San Jorge Hospital, Huesca, available since May 2010. The correct registration and identification of all eligible patient entries was checked, and the repetitions were merged, unifying by the medical record number, as first option, or by the individual health card number if the first option was not possible. The Mayo Clinic, Olmsted County (Minnesota, USA) protocol was applied to extract the data.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> Briefly, the Hb value obtained on the date closest to the start of the study period was recorded for each participant. If there was no data for the first year, the search continued progressively in subsequent months and years up to 5 years (12-31-2015). In those cases, with more than one determination, the extreme values of each individual were excluded and the median Hb value was selected.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Variables</span><p id="par0040" class="elsevierStylePara elsevierViewall">For this analysis, basic demographic data (gender, age, Reference Health Centre, residence locality and altitude), and Hb level (g/dl) were collected. Under this project, other blood count values were collected for complementary purposes.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Anaemia diagnosis and prevalence estimation</span><p id="par0045" class="elsevierStylePara elsevierViewall">Anaemia cases were identified according to the WHO basic thresholds (Hb <12<span class="elsevierStyleHsp" style=""></span>g/dl women, <13<span class="elsevierStyleHsp" style=""></span>g/dl men)<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">2</span></a> after applying the correction for residence altitude (−0.2<span class="elsevierStyleHsp" style=""></span>g/dl for residents >1000<span class="elsevierStyleHsp" style=""></span>m and −0.5<span class="elsevierStyleHsp" style=""></span>g/dl for residents at >1500<span class="elsevierStyleHsp" style=""></span>m).<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">3</span></a> The estimate of anaemia prevalence was stratified by gender, age (in decades) and residence altitude.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Statistical analysis</span><p id="par0050" class="elsevierStylePara elsevierViewall">A descriptive analysis of the blood count values, and anaemia prevalence estimates was performed with measures of central tendency and dispersion, both with the global population and in the predefined subgroups by gender, age range or residence altitude. The possible association of the diagnosis of anaemia with the demographic characteristics studied was analyzed: after the corresponding bivariate tests, logistic regression was used to investigate the factors that are independently related to the presence of anaemia. The software used was SPSS 11.0® and STATA 12.0®.</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Population</span><p id="par0055" class="elsevierStylePara elsevierViewall">For data extraction, 583,856 blood count analyses were processed, of which 68,746 were excluded because the necessary criteria were not met. 515,110 valid blood counts corresponding to 90,800 patients of both sexes with an age range between 15 and 106 years were included, which represented a coverage of 89.1% of the healthcare sector in a census population of 101,899 inhabitants over 14 years of age. 99.7% were white and 54.6% women. The average age was 52.6 years (standard deviation: 20.4). The age ranges and residence altitudes are described in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>: the most represented ranges were 40–49 years (16.1%), 50–59 (16%) and 30–39 (15.5%). The altitudes of residence were located between 281<span class="elsevierStyleHsp" style=""></span>m (Ebro Valley) up to 1305<span class="elsevierStyleHsp" style=""></span>m (municipalities of the Pyrenees), although more than half of the population analyzed resided in the district of Huesca (52%).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Distribution of haemoglobin values</span><p id="par0060" class="elsevierStylePara elsevierViewall">The distribution of Hb values showed an important variation according to gender (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>), and the means were 15.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.5<span class="elsevierStyleHsp" style=""></span>g/dl for men and 13.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.3<span class="elsevierStyleHsp" style=""></span>g/dl for women. The percentiles were established in the general population and by gender (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Differences were also detected according to age range, highlighting the considerable decrease in Hb levels above 60 in men and 70 in women (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). An increase in linear trend of Hb averages was observed as the usual residence altitude increased (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Prevalence of anaemia according to WHO criteria</span><p id="par0065" class="elsevierStylePara elsevierViewall">Applying the WHO criteria with altitude correction, the overall prevalence of anaemia in this population was 8.99% (95% CI: 8.80–9.18%; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>8165 cases). It is 10.01% in women (95% CI: 9.74–10.27%; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>4958/49,547) and 7.77% in men (95% CI: 7.51–8.03%; <span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>3207/41,253) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). This higher prevalence in women is maintained until an age between 50 and 59 years, and is reversed in that range, to be higher in men from that age onwards. In fact, as can be seen in <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>, the prevalence varies significantly with age, and increases with exponential tendency from the age of 70, with 27.5% in men aged 80–89 years.</p><p id="par0070" class="elsevierStylePara elsevierViewall">Finally, despite having applied the correction for residence altitude proposed by WHO, the prevalence of anaemia according to these criteria is significantly reduced with residence altitude. The estimate among residents over 1000<span class="elsevierStyleHsp" style=""></span>m altitude was less than 4% vs. ≥8% in populations between 281 and 600<span class="elsevierStyleHsp" style=""></span>m (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>).</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Demographic factors associated with the onset of anaemia</span><p id="par0075" class="elsevierStylePara elsevierViewall">Gender, age and residence altitude were independent factors related to the prevalence of anaemia (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>) in this population. The logistic model applying these 3 variables correctly predicted 93% of the diagnoses of anaemia. On average, it is 1.6 times more common in women, regardless of age and residence altitude (95% CI: 1.5–1.7). Its prevalence is multiplied by 1.02 for each additional year of age, and by 0.99 for each additional metre of the residence altitude.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">This study was raised due to the lack of recent representative data of the general population in Spain and the absence of data for certain groups or age ranges, particularly the elderly, whose proportion increases progressively in our population. In addition, it was considered very important to verify the diagnosis of anaemia in clinical practice, both for epidemiological reasons and for the objections expressed by some authors<a class="elsevierStyleCrossRefs" href="#bib0120"><span class="elsevierStyleSup">4–8,15</span></a> regarding the origin and usefulness of the thresholds proposed by WHO and the corrections for altitude. Our results suggest certain approaches that could be extended to other areas of Spain and Europe, which have a significant proportion of residents living at altitudes close to or over 1000<span class="elsevierStyleHsp" style=""></span>m and take into consideration the general ageing of the population. In this sense, the population studied here can offer some indicative data, which could be confirmed with studies in other national geographical areas, which might confirm that their ethnic composition, lifestyle and nutritional habits are similar.</p><p id="par0085" class="elsevierStylePara elsevierViewall">If we consider the male component without age differences, the data on the prevalence of anaemia in this study reveal global figures that agree with previous estimates by Kassebaum et al.<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">9</span></a> for Spain. However, it should be remembered that estimates on the prevalence of anaemia in that study and ours have been made by establishing the diagnosis according to the thresholds defined by WHO, which have been maintained without a critical review until recently. One of the first questions we asked ourselves was the reflection of some authors on the validity of these criteria that started from a document based on rather scarce and inadequately obtained data.<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">4</span></a> On this, Beutler and Waalen stated that, judging by the sources of data and the brief and imprecise way (without decimals) of communicating these figures, in their opinion it was not the intention of the WHO Committee to establish a standard, let alone one with so much scope in medical practice and science. The WHO table also indicates what are the limits regarding the population living at sea level,<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">2</span></a> something important to consider in laboratories, which should at least apply the proposed correction for altitude. Making a correct diagnosis of anaemia is not a trivial matter, otherwise it may be leading, as an example, to unnecessary studies prompted by an erroneous suspicion of a chronic myeloproliferative syndrome,<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">7</span></a> or prescribing unnecessary treatments due to misdiagnosis of anemia.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">16</span></a> These authors proposed that a more appropriate way to estimate anaemia in the population would be analysing the distribution of Hb values in it,<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">4</span></a> something which is now possible in the era of <span class="elsevierStyleItalic">big data.</span> To illustrate their arguments, they performed a data analysis of the NHANES-<span class="elsevierStyleSmallCaps">III</span> database from the USA, taking values of the 2.5 and 5 percentiles to establish the lower limit of normality (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). We have performed a similar analysis with this study's data, and <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows how the thresholds vary using these criteria instead of WHO's. It can also be observed that the thresholds obtained differ from those of the NHANES database, so the variations in ethnic composition, altitude and other lifestyle variables might make a difference. Therefore, we propose to make a comprehensive study of the population of our country, taking advantage of the availability of large databases, to obtain the correct reference according to the demographic composition of our healthcare users.</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0090" class="elsevierStylePara elsevierViewall">The importance of demographic composition leads us to the following reflection on the significant combined influence of gender and age. The analysis of both factors simultaneously in this study has allowed us to obtain data on all the age ranges of our population from the age of 14 and observe the significant increase in the proportion of anaemia (according to WHO) in those over 60 years of age, with a very important increase among elderly men. Anaemia in the elderly has attracted the attention of various authors for some years, who have argued the need to define normal values according to age groups<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">17,18</span></a> and also the need to understand the impact of anaemia on the survival, general condition and quality of life of these patients.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">10–12,17–19</span></a> Along these lines, our data support the fact that special attention should be given to the upper age groups while keeping in mind the proportion of the population that may have anaemia. This is necessary in order to adequately address the nutritional needs and pathologies underlying anaemia in the elderly.<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">11,12,19,20</span></a> However, despite the fact that 37.6% of the sample in this study was over 59 years of age (although with a very high population coverage, which gives some reliability to our estimates), large studies are still necessary in order to verify these data.</p><p id="par0095" class="elsevierStylePara elsevierViewall">Finally, an additional point of discussion is the effect that altitude has on Hb levels and its consequences on the prediction of anaemia and polycythaemia based on established WHO thresholds combined with an unvalidated altitude correction. We could observe that the proposed correction is inadequate, offering differences in the prevalence of anaemia according to the residence altitude that are unlikely in an otherwise homogeneous population (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). Therefore, we are in a situation in which routinely used thresholds may be leading to possible diagnostic or suspicion errors, something that, to date, had only been described in high-altitude resident populations.<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">7,8</span></a> The data shown here suggests that the necessary correction in Hb levels of residents above 1000<span class="elsevierStyleHsp" style=""></span>m in our population should be approximately 0.5<span class="elsevierStyleHsp" style=""></span>mg/dl, and not 0.2<span class="elsevierStyleHsp" style=""></span>mg/dl as proposed by WHO, and in any case it is an adjustment that should be made according to the corresponding population, since the observations in this regard have been different in Andean, Ethiopian and Tibetan ethnicities.<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">6</span></a></p><p id="par0100" class="elsevierStylePara elsevierViewall">As a first approach to a population study on Hb levels and prevalence of anaemia in Spain, this study has the benefit of an important sample size and a high level of coverage in the population studied. In addition, the methodology used was selected to minimize the influence of potential biases caused by the existence of disease in a specific subject during the study period. It is a global study, which has included all adult ages and, as far as we know, the most representative analysis of the European population to date. However, it is limited to a single region, so the approaches that these data suggest require further studies to reach final conclusions that can be applied to clinical practice.</p><p id="par0105" class="elsevierStylePara elsevierViewall">In conclusion, in addition to providing the first recent data on Hb levels and prevalence of anaemia in the general population in Spain, the results shown here should prompt us to reflect on the diagnosis of anaemia in routine practice and the corrections applied to it. Also, the significant increase in the prevalence of anaemia in the elderly population, a population sector constantly increasing in Spain and Europe and an age group mostly absent in previous studies, points to the need of conducting further studies in people over 80, so that their management can be effective. It is of great importance to make a correct estimation of Hb levels as a predictor of various pathologies so as to avoid the misuse of health resources, whether due to unnecessary confirmatory test requests, or for errors in the management of our patients, with negative consequences for their health and well-being. Obtaining national data in larger studies could provide conclusive data to issue appropriate criteria and updated recommendations in this regard, for this, merging haematology laboratory databases and promoting a large study would be of great value.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Authors/collaborators</span><p id="par0110" class="elsevierStylePara elsevierViewall">All authors contributed to the study design, data collection, analysis and interpretation and writing and correcting the article.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conflict of interests</span><p id="par0115" class="elsevierStylePara elsevierViewall">Dr. García Erce has managed grants, given talks, moderated at conferences and meetings or organized courses with scholarships or funding from Alexion, Amgen, Braun, Celgene, Ferrer, GSK, Inmucor, Jansen, Novartis, Octapharma, Sanofi, Sandoz, Terumo, Vifor, Zambon. The rest of the authors declare no conflict of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1270251" "titulo" => "Abstract" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Objectives" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Material and methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1175587" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1270250" "titulo" => "Resumen" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Objetivos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Material y métodos" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0050" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1175588" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Design and population" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Procedure for selecting haemoglobin values" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Variables" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Anaemia diagnosis and prevalence estimation" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Population" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "Distribution of haemoglobin values" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "Prevalence of anaemia according to WHO criteria" ] 3 => array:2 [ "identificador" => "sec0060" "titulo" => "Demographic factors associated with the onset of anaemia" ] ] ] 7 => array:2 [ "identificador" => "sec0065" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0070" "titulo" => "Authors/collaborators" ] 9 => array:2 [ "identificador" => "sec0075" "titulo" => "Conflict of interests" ] 10 => array:2 [ "identificador" => "xack435990" "titulo" => "Acknowledgements" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-11-09" "fechaAceptado" => "2019-02-07" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1175587" "palabras" => array:6 [ 0 => "Haemoglobin" 1 => "Ageing" 2 => "Anaemia" 3 => "Diagnostic threshold" 4 => "Prevalence" 5 => "Altitude" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1175588" "palabras" => array:6 [ 0 => "Hemoglobina" 1 => "Envejecimiento" 2 => "Anemia" 3 => "Umbral diagnóstico" 4 => "Prevalencia" 5 => "Altitud" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">There are gaps in our knowledge of the normative levels of haemoglobin and the prevalence of anaemia in our geographical area, and in certain population subgroups.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Objectives</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">To study the mean values of haemoglobin in a mountainous Spanish region, according to sex, age range and residence altitude, and the prediction of anaemia according to the WHO thresholds and other proposals.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Material and methods</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Cross-sectional descriptive study of all patients aged >14 residents in the Huesca healthcare Sector with ≥1 laboratory report in the 5 years of inclusion; multivariate analysis to determine the influence of demographic factors on haemoglobin values.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">583,856 laboratory reports of 90,800 patients (coverage 89.1%) residing between 281 and 1305<span class="elsevierStyleHsp" style=""></span>m: 54.6% female; mean age 52.6 years. Hb mean: 14.1<span class="elsevierStyleHsp" style=""></span>g/dl (males: 15.0/females: 13.4). Prevalence of anaemia: 8.99% (males: 7.8%/females: 10.0%). It was more frequent in women (1.6 times) and increased markedly with age: >65 years: 16.5%; ≥75 years: 21.7%; ≥80 years: 25.7%; >90 years 35%. It increased 1.02 times per year, and 0.99 times per metre of altitude. In residents ≥1000<span class="elsevierStyleHsp" style=""></span>m, anaemia prevalence fell by half.</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusions</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">We obtained data from sub-populations that were previously not well described; anaemia in the elderly requires consideration. The influence of altitude does not seem to be fully considered within the correction framework proposed by WHO. Broader studies should be planned in order to obtain adequate parameters for the elderly and residents at high altitudes in Spain, as both groups represent an important proportion of the population, to avoid potential underdiagnosis of anaemia and overdiagnosis of other pathologies.</p></span>" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Objectives" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Material and methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Introducción</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Existen lagunas respecto a los niveles normativos de hemoglobina y la prevalencia de anemia en nuestro entorno y en determinados subgrupos de población.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Objetivos</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Examinar los valores medios de hemoglobina en una región española de orografía montañosa, según sexo, rango de edad y altitud de residencia, y la predicción de anemia según umbrales de la OMS y otras propuestas.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Material y métodos</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Estudio descriptivo transversal de todos los pacientes > 14 años del Sector Huesca con ≥ 1 analítica en los 5 años de inclusión; análisis multivariado para determinar la influencia de los factores demográficos en los valores de hemoglobina.</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Resultados</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Se incluyeron 583.856 informes analíticos de 90.800 pacientes (cobertura 89,1%) residentes entre 281 y 1.305 metros de altitud: 54,6% mujeres; edad media 52,6 años. Hemoglobina media: 14,1 g/dl (hombres:15,0/mujeres:13,4). Prevalencia de anemia: 8,99% (hombres: 7,8%/mujeres: 10,0%). Resultó más frecuente en mujeres (1,6 veces), y aumentaba llamativamente con la edad: > 65 años: 16,5%; ≥ 75 años: 21,7%; ≥ 80 años: 25,7%; > 90 años: 35%. Aumentaba 1,02 veces por cada año, y 0,99 veces por cada metro de altitud. En residentes a ≥ 1.000 m, descendía a la mitad.</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Conclusiones</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Se obtuvieron datos de subpoblaciones previamente poco descritas; la anemia en población mayor requiere consideración. La influencia de la altitud no parece suficientemente abordada con la corrección de la OMS. Se deben plantear estudios amplios para definir criterios apropiados para edades avanzadas y residentes en altura en España, pues ambos grupos constituyen una proporción importante, para evitar incurrir potencialmente en infradiagnóstico de anemia y supradiagnóstico de otras patologías.</p></span>" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Objetivos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Material y métodos" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0050" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Please cite this article as: García-Erce JA, Lorente-Aznar T, Rivilla-Marugán L. Influencia del sexo, la edad y la altitud de residencia en los niveles de hemoglobina y la prevalencia de anemia. Med Clin (Barc). 153;2019:424–429.</p>" ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1369 "Ancho" => 2501 "Tamanyo" => 248608 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Distribution of haemoglobin values by gender and percentile calculation.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1013 "Ancho" => 2496 "Tamanyo" => 223025 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Influence of gender on haemoglobin levels and the prevalence of anaemia according to WHO criteria. Figures on the prevalence of anaemia are shown according to gender in those over 60 years of age.</p>" ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 963 "Ancho" => 2511 "Tamanyo" => 170399 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Influence of the residence altitude on haemoglobin levels and the prevalence of anaemia according to WHO criteria corrected for altitude.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="3" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Age (years)</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="3" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Residence altitude (m)</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Proportion (%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Altitude \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Proportion (%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14–19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4032 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">281 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5156 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20–29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9448 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">332 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3617 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30–39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14,074 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">456 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3293 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">40–49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14,572 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">470 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35,543 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50–59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14,566 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">582 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1489 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60–69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12,181 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">655 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">904 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70–79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10,359 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">780 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5846 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80–89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9437 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">833 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">853 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90–99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2080 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">850 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7789 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≥100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">860 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1292 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">905 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">854 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1040 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">215 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1091 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">27 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1185 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">286 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1305 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">516 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2172963.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Distribution by age and residence altitude of the population studied (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>90,800).</p>" ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">B \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">ET \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Wald \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Gl \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Sig. \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">Exp (B) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95% CI for Exp (B)</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Lower \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Higher \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gender (reference: males) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.470 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.033 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">206.989 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.600 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.501 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.706 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years old) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.029 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1317.228 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.029 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.028 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.031 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Residence Altitude (m) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42.309 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.999 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.999 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.000 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Constant \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−4.398 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.075 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3457.516 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.012 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2172962.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Factors independently associated to the onset of anaemia.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">F: females; <span class="elsevierStyleSmallCaps">M</span>: males.</p><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Haemoglobin levels were calculated for the application of the cut-off point according to WHO criteria<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">2</span></a> and the percentile criteria proposed by Beutler and Waalen.<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">4</span></a></p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Criterion \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Cut-off point</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Prevalence of anaemia in this population \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">WHO crude</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Females: 12<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F: 10.01% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Males: 13<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleSmallCaps">M</span>: 7.77% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cut-off point in NHANES (USA)<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cut-off point in this population \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean – (1.65<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>SD): 5% percentile</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F: 12.2<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F: 11.2<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">The prevalence of anaemia is 5% and 2.5%, respectively, following these criteria</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleSmallCaps">M</span>: 13.8<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleSmallCaps">M</span>: 12.3<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean – (2.0<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>SD): 2.5% percentile</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F: 11.9<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F: 10.4<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleSmallCaps">M</span>: 13.4<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleSmallCaps">M</span>: 11.2<span class="elsevierStyleHsp" style=""></span>g/dl \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2172961.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Cut-off point according to percentiles in males aged 20–59 years and females aged 20–49 years (for older people they are <span class="elsevierStyleSmallCaps">M</span>: 13.2<span class="elsevierStyleHsp" style=""></span>g/dl and F: 12.2<span class="elsevierStyleHsp" style=""></span>g/dl in the 5th percentile).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Cut-off point for diagnosis of anaemia and estimate of prevalence in this population according to WHO crude criteria (without altitude correction) and epidemiological criteria (percentiles).</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:20 [ 0 => array:3 [ "identificador" => "bib0105" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Worldwide 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The authors wish to thank Dr. Carlos Jericó Alba and Dr. Blanca Piedrafita for their review and critical comments on the manuscript and Mrs. Visitación Ortega, librarian of the San Jorge Hospital (Huesca), for her invaluable help with the literature references. In memory of Mrs. Maite Erce Lizarraga (10-02-1947 to 25-08-2018).</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/23870206/0000015300000011/v1_201911300659/S2387020619304905/v1_201911300659/en/main.assets" "Apartado" => array:4 [ "identificador" => "43310" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/23870206/0000015300000011/v1_201911300659/S2387020619304905/v1_201911300659/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2387020619304905?idApp=UINPBA00004N" ]
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