Document Detail

Maternal sociodemographic parameters: impact on trace element status and pregnancy outcomes in Nigerian women.
Jump to Full Text
MedLine Citation:
PMID:  21608425     Owner:  NLM     Status:  MEDLINE    
To determine the impact of socioeconomic status on plasma trace element status and pregnancy outcomes, 349 pregnant women, aged 15-40 years (mean 27.04 +/- 2.75 years), recruited at < or = 25 weeks (mean 21.76 +/- 3.12 weeks) gestational age, were followed up till delivery during which maternal and foetal outcomes were recorded. Plasma copper, iron, and zinc were determined using atomic absorption spectrophotometer while maternal sociodemographic data were obtained using a questionnaire. Except for copper, lower plasma iron and zinc were significantly (p < 0.05) higher in women from socioeconomically-disadvantaged groups. Both adverse maternal health and foetal outcomes also seemed to be more prevalent in socioeconomically-disadvantaged women, although without a definite trend. This study has shown that, in economically-disadvantaged setting of developing countries, maternal socioeconomic status impacts on maternal trace element (copper, iron, and zinc) status and health and foetal outcomes.
Emmanuel I Ugwuja; Emmanuel I Akubugwo; Udu A Ibiam; Onyechi Obidoa
Related Documents :
17046385 - Monoclonal anti-leukemia inhibitory factor antibody inhibits blastocyst implantation in...
21637365 - Body mass index impacts in vitro fertilization stimulation.
22077175 - Can fertility be estimated from current pregnancy data?
21935285 - The first case of postpartum acquired hemophilia a in korea.
15016725 - Between-method variation in human chorionic gonadotropin test results.
16394095 - Weight loss reduces adipose tissue cathepsin s and its circulating levels in morbidly o...
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of health, population, and nutrition     Volume:  29     ISSN:  1606-0997     ISO Abbreviation:  J Health Popul Nutr     Publication Date:  2011 Apr 
Date Detail:
Created Date:  2011-05-25     Completed Date:  2011-06-09     Revised Date:  2013-06-28    
Medline Journal Info:
Nlm Unique ID:  100959228     Medline TA:  J Health Popul Nutr     Country:  Bangladesh    
Other Details:
Languages:  eng     Pagination:  156-62     Citation Subset:  IM    
Department of Chemical Pathology, Faculty of Clinical Medicine, Ebonyi State University, PMB 053 Abakaliki, Nigeria.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
African Continental Ancestry Group
Analysis of Variance
Anemia, Iron-Deficiency / epidemiology
Copper / blood
Follow-Up Studies
Iron / blood,  deficiency
Maternal Nutritional Physiological Phenomena*
Nigeria / epidemiology
Nutritional Status
Pregnancy Outcome*
Socioeconomic Factors*
Trace Elements / blood*
Young Adult
Zinc / blood,  deficiency
Reg. No./Substance:
0/Trace Elements; 7439-89-6/Iron; 7440-50-8/Copper; 7440-66-6/Zinc

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): J Health Popul Nutr
Journal ID (pmc): JHPN
ISSN: 1606-0997
ISSN: 2072-1315
Publisher: International Centre for Diarrhoeal Disease Research, Bangladesh
Article Information
Download PDF
Print publication date: Month: 4 Year: 2011
Volume: 29 Issue: 2
First Page: 156 Last Page: 162
ID: 3126988
PubMed Id: 21608425
Article Id: jhpn0029-0156

Maternal Sociodemographic Parameters: Impact on Trace Element Status and Pregnancy Outcomes in Nigerian Women
Emmanuel I. Ugwuja1
Emmanuel I. Akubugwo2
Udu A. Ibiam3
Onyechi Obidoa4
1Department of Chemical Pathology, Faculty of Clinical Medicine, Ebonyi State University, PMB 053 Abakaliki, Nigeria
2Department of Biochemistry, Abia State University, Uturu, Nigeria
3Department of Biochemistry, Faculty of Biological Sciences, Ebonyi State University, PMB 053 Abakaliki, Nigeria
4Department of Medical Biochemistry, University of Nigeria, Nsukka, Nigeria
Correspondence: Correspondence and reprint requests should be addressed to: Dr. Emmanuel I. Ugwuja, Department of Chemical Pathology, Faculty of Clinical Medicine, Ebonyi State University, PMB 053 Abakaliki, Nigeria, Email:


Maternal socioeconomic status and non-modifiable, non-biological factors that affect mental and physical well-being (1) have been associated with maternal nutrition and pregnancy outcomes (2, 3). Although it is increasingly acknowledged that societal factors play a significant role in micronutrient status and pregnancy outcomes (1, 3), studies on impacts of socioeconomic status on pregnancy outcomes have produced conflicting results (4, 5). For instance, the risk of preterm birth has been reported in mothers of low socioeconomic status (6). In Danish and Norwegian populations, the risk of preterm birth was reported to have an inverse association with educational level of mothers (7). Morgen et al. did not find any association between risk of preterm birth and other indicators of socioeconomic status, such as household income and parental occupation (2). A study in Germany found that women with the lowest level of education had a significantly-elevated risk of small-for-gestational age newborns compared to women with the highest level of education (8), with the distribution of factors known to influence intrauterine growth varying with educational level. There has also been controversy over the influence of unemployment in the family on pregnancy outcomes. While some studies have shown associations of unemployment with preterm delivery (9, 10), low birthweight (LBW) (11), small-for-gestational age (12), and a higher perinatal mortality rate (11), others have shown opposite results (13, 14). Additionally, deficiencies of trace elements, including copper and zinc, have been associated with maternal morbidity, such as hypertension (copper), infections, and diabetes mellitus (zinc) without significant effects on foetal outcomes (15). Adverse foetal outcomes have been recognized to constitute an important public-health problem because several chronic diseases of public-health significance have been traced to adverse intrauterine and early life (16, 17). Although a high prevalence of deficiencies of trace elements (copper, iron, and zinc) has been reported among Nigerian pregnant women (18), there is a paucity of data on the role of maternal socioeconomic status on plasma levels of these trace elements and pregnancy outcomes. The present study was, therefore, conducted to determine the impact of maternal sociodemographic parameters on plasma iron, copper and zinc level and pregnancy outcomes in Nigerian pregnant women.

Study settings and sample

The study was conducted among pregnant women attending the antenatal clinic of the Department of Obstetrics and Gynaecology of the Federal Medical Centre, Abakaliki, one of the referral tertiary health institutions in southeastern Nigeria, with an average delivery of 400 per annum. Abakaliki and the environs are inhabited mainly by subsistence-level population. Their main occupation is subsistence-level farming—mainly yam and cassava—with some animal husbandry. Other professions and/or activities, such as civil service, trading, artisanry, and stone quarrying, are also practised. The transmission of malaria is intense and occurs throughout the year (perennial). Three hundred and fifty-one consecutive women, aged 15-40 years (gestational age ≤25 weeks), who gave their consent to participate in the study, were recruited during July 2007–September 2008. Women with chronic disease, women who were HIV-seropositive, and women with multiple pregnancies were excluded from the study.

Sets of structured questionnaire were used for collecting sociodemographic data of the participants. Their weights and heights (metre) were measured in light clothing without shoes and standing erect against a pre-marked scale attached to the weighing balance, and body mass index (BMI) (kg/m2) was calculated. Five mL of fasting venous blood collected at recruitment, during 08.00-10.00 hours, were dispensed into trace element-free heparinized plastic bottles (3.0 mL) and EDTA bottles (2.0.mL) for biochemical and haematological analyses. The heparinized blood samples were centrifuged at 2,000 g for five minutes for the isolation of plasma. The plasma samples were frozen until these were analyzed. The participants were regularly followed up, based on appointment with their consultants till delivery. At every follow-up, the attending obstetricians evaluated them for anaemia (Hb <11.0 g/dL) (19), hypertension (blood pressure <140/90 mmHg), diabetes (fasting plasma glucose >7.8 mmol/L), infection due to Helicobacter pylori (seropositive to H. pylori antibody), concomitant illness, such as malaria (positive thin or thick film), upper respiratory tract infection (presence of cough/or catarrh), and urinary tract infection (UTI; positive urine protein, nitrite, and leucocytes). At delivery, baby's birth outcomes, such as weight, length, and head-circumference and for stillbirth, mode of delivery, and gestation age at delivery, were recorded. Birthweight was determined using an electronic weighing balance and recorded to the nearest 0.05 kg with the scale checked periodically throughout the study for accuracy while birth-length and head-circumference were determined by a measuring tape to the nearest 0.1 cm. A baby was considered underweight if the birthweight was ≤2.5 kg (20) and preterm if delivered at ≤37 weeks. Plasma copper, iron, and zinc were determined using atomic absorption spectrophotometric method while maternal haemoglobin concentration was estimated using cyanmethaemoglobin method (21). Plasma levels of <5.0 µmol/L (zinc), 8.0 µmol/L(copper), and 10.0 µmol/L (iron) were considered low (22).

Analysis of data

All data, including sociodemographic and obstetrics data, were analyzed using the SPSS software for Windows (version 7.5). The differences between groups were compared using one-way analysis of variance (ANOVA). Data were expressed either as mean and standard deviation or proportion/percentage. The statistical significance was set at the p value of ≤0.05.

Ethical approval

The Ethics and Research Committee of the Federal Medical Centre, Abakaliki, Nigeria, approved the protocol for this study.


Table 1 shows the general characteristics of the pregnant women recruited at 25 weeks gestation and those of the neonates at delivery. Although 351 pregnant women were recruited, one (0.3%) died early into the study, remaining 350 (99.7%). Data of women were available but samples were obtained from 349 participants as one participant declined to participate. At delivery, data of 319 (91.4%) women and their neonates were available. Data were either incomplete or were not available for the remaining 30 (8.6%) women.

Although, in general, the women were not deficient in any of the three trace elements evaluated (mean 9.59±9.42, 10.25±7.69, and 9.19±9.16 µmol/L for copper, iron, and zinc respectively), the ranges of the trace elements varied from very low levels to very high concentrations, with copper, iron, and zinc concentrations from 0.89, 1.79, and 0.70 µmol/L to values as high as 45.36, 45.12, and 67.32 mmol/L respectively. The participants were generally anaemic with the mean haemoglobin concentration of 10.21±1.26, which is lower than the 11.0 g/dL cut-off point recommended by the World Health Organization.

Table 2 shows the impact of maternal parity and indices of maternal socioeconomic status (living accommodation, educational level, and occupation) on plasma copper, iron and zinc concentrations. Although there was no definite trend of the impact of parity and other indices of socioeconomic status on the plasma levels of copper, iron, and zinc among the pregnant women in this population, higher levels of these trace elements were found in economically-advantaged groups (e.g. women whose living accommodation were flats, women with secondary/tertiary education, and women who were civil servants/artisans), with lower plasma level found in multiparous women. Except for copper, the prevalence of lower plasma iron and zinc decreased with increased maternal education; these were not significant (p>0.05). Only 25% of the women without formal education had low plasma iron and zinc (mean 6.89±0.79 and 1.89±1.49 µmol/L respectively).

Without a definite trend, maternal morbidity during pregnancy was found to be significantly more in women with lower educational level, except for H. pylori infection which was reported in significantly (p<0.05) higher proportions in women with higher educational level (Table 3). No definite trend of the impact of maternal education on foetal outcomes was observed, although most adverse outcomes were absent in women without formal education (Table 3). In the same vein, neither maternal morbidities nor foetal outcomes showed any specific trend in relation to maternal living accommodation, although women whose living accommodation was single rooms experienced more concomitant illnesses than women from other living accommodations (Table 3).

With the exception of pregnancy-induced hypertension found in significantly (p<0.05) higher proportions in women whose occupation was civil service, women whose occupation was farming had a significantly higher prevalence of anaemia, H. pylori infection, and other concomitant illnesses (Table 3). Significantly more adverse foetal outcomes were recorded in women who were housewives and farmers when compared with women who were civil servants and artisans.


There seemed to be a wide nutritional disparity in this population as evidenced by wide variations in the levels of trace elements. Although the reason for this disparity is obscure, contamination of water source cannot be ruled out as contamination of water supply has been found to be one of the causes of acute toxicity of trace elements in the general population (23). Again, differential bioavailability of trace elements due to nutrient-nutrient interactions (24, 25) may be a contributory factor to the wide differences in concentrations of trace elements in this population. This has important public-health implications for mothers and their infants as this may reflect in differential plasma levels of these elements and maternal and foetal outcomes.

This study has documented a significantly higher prevalence of maternal morbidities (malaria, upper respiratory tract infection (UTI), anaemia, UTI plus malaria) among women from disadvantaged socioeconomic status as represented by women whose occupation was farming, women without formal education or primary education, and women whose living accommodation was single room, thus suggesting that maternal socioeconomic status impacts negatively on maternal health during pregnancy. This is consistent with the significant roles played by psychosocial factors, such as poverty and socioeconomic status in pregnancy outcomes earlier reported by Chandra (1).

In developing countries, socioeconomic status is a complex term generally used for defining social inequalities and usually measured by income/educational level/occupation/living accommodation. However, maternal hypertension was recorded in a higher proportion of civil servants/artisans. This suggests that civil servants and women who were artisans in this environment were more exposed to risk factors for hypertension (including stress) than other occupational groups. Stress has been related to hormonal changes, and occupational strain may result in shortened duration of pregnancy and babies who were small for their gestational age (26, 27).

The role of social factors on pregnancy outcomes, such as preterm, LBW, spontaneous abortion, alterations in foetal development, and long-term health of offspring, have been widely acknowledged (1). Significantly more post-term deliveries among housewives, more surgical deliveries among housewives and civil servants, and significantly more deliveries of LBW babies among civil servants and farmers respectively showed that housewives, farmers and civil servants were at increased risk of adverse foetal outcomes. While higher post-term delivery among housewives may be partly attributed to maternal inactivity, higher surgical delivery among housewives and civil servants may be due to maternal awareness and access to medical care (28). Delivery of LBW babies among farmers and civil servants may be partly attributed to either stress or/and nutritional deficiencies as evidenced by lower plasma levels of copper, iron, and zinc in women who were civil servants in the present study. It has been suggested that women who are employed as exemplified by civil servants/farmers may be at a risk of nutritional deficiencies because of reduced time for shopping and cooking (29). Moreover, working women who worked standing are less likely to eat three meals per day than women who worked in occupation that did not require long standing (30).

Deficit of trace elements, including zinc deficiency, has been associated with LBW (31). Additionally, increased physical activity, as measured by work in farms or fetching of water, for example, has been associated with LBW infants, smaller head-circumference, smaller mid-upper arm circumference, and lower placental weight (32). For example, maternal stress due to poverty is associated with preterm delivery via increased levels of epinephrine (33), increased oxytocin (34), and change in maternal habits (35).

Although maternal education did not display any trend in relation to maternal morbidities, the higher prevalence of maternal morbidities, such as anaemia, malaria, and UTI in women with lower educational level is in agreement with earlier studies (8). This is quite understandable as educational attainment has been established as a social variable that often displays the largest socioeconomic influence (36) because it affects both income and occupation. Educated women are also more likely to understand public-health message (37) and to maintain high personal hygiene than less-educated women. Educated women also belong to high social class and have access to adequate medicare and nutrition during pregnancy. However, a higher prevalence of H. pylori infection among women with higher educational level in the present finding supports the urban nature of the organism (38).

Ironical as it may sound, women without formal education had the lowest adverse foetal outcomes when compared with women with one form of education or the other. This is in contrast to other findings (2, 5) where women with the lowest education level had almost twice the odds of delivering a small-for-gestational age newborn compared to mothers in the highest education-category. The reason for this disparity is not clear but it may not be unconnected with the number of subjects (n=8) when compared with other groups. Koupilova et al. reported a birthweight gradient between women with primary and tertiary education (38).

A higher incidence of maternal morbidities and adverse foetal outcomes was reported in women whose living accommodation was a single room than other accommodation groups who also affirmed the role of maternal socioeconomic status on pregnancy outcomes. Although, in this population, living accommodation of women may not accurately indicate maternal socioeconomic status because of family dislocation due to job locations of spouses, women in lower socioeconomic strata have more adverse pregnancy outcomes (1).

In the present study, although maternal socioeconomic status appeared to influence maternal morbidity and pregnancy outcomes (via trace element nutriture), the effects were not clearly defined. This may be due to indices of maternal socioeconomic status used. For example, most women who were living in a single room were from higher educational level, and the reason given for such living accommodation was family dislocation as a result of job locations between couples. A high rate of unemployment may also contribute to invalidating maternal educational status—an indicator of socioeconomic status in the present study as some women educated to tertiary level still remained unemployed and lived in a single room. We, however, suggest that, in socioeconomically-disadvantaged population of developing countries, maternal occupation may be the more appropriate indicator for the assessment of maternal socioeconomic status.


The authors acknowledge the staff of the Department of Obstetrics and Department of Gynaecology and Medical Records of the Federal Medical Centre for logistic support.

1. Chandra DC. Societal factors and pregnancy outcome (editorial)Nepal J Obstet GynaecolYear: 2008313
2. Morgen CS,Bjork C,Andersen PK,Mortensen LH,Andersen AMN. Socioeconomic position and the risk of preterm birth: a study within the Danish National Birth CohortInt J EpidemiolYear: 20083711092018577529
3. Aydemir F,Cavdar AO,Soylemez F,Cengiz B. Plasma zinc levels during pregnancy and its relationship to maternal and neonatal characteristics: a longitudinal studyBiolog Trace Element ResYear: 200391193202
4. Tuntiseranee P,Olsen J,Chongsuvivatwong V,Limbutara S. Socioeconomic and work related determinants of pregnancy outcome in southern ThailandJ Epidemiol Communiy HealthYear: 19995362429
5. Parker JD,Schoendorf KC,Kiely JL. Association between measures of socioeconomic status and low birth weight, small-for-gestational age, and premature delivery in the United StatesAnn EpidemiolYear: 1994427187921316
6. Steer P,Flint C. ABC of labour care: preterm labour and premature rupture of membraneBMJYear: 199931810596210205109
7. Thompson JMD,Irgens LM,Rasmussen S,Dalveit AK. Secular trends in socio-economic status and the implications for preterm birthPaediatr Perinat EpidemiolYear: 200620182716629692
8. Raum E,Arabin B,Schlaud M,Walter U,Schwartz FW. The impact of maternal education on intrauterine growth: a comparison of former West and East GermanyInt J EpidemiolYear: 20013081711171862
9. Ancel RL,Saurel-Cubizolles MJ,Di Renzo GC,Papiernik E,Breart G. Social differences of very preterm birth in Europe: interaction with obstetric history. Europop groupAm J EpidemiolYear: 19991499081510342799
10. Hanke W,Saurel-Cubizolles MJ,Sobala W,Kalinka J. Employment status of pregnant women in central Poland and the risk of preterm delivery and small-for-gestational age infantsEur J Public HealthYear: 20011123811276567
11. Murphy JF,Dauncey M,Newcombe R,Garcia J,Elbourne D. Employment in pregnancy: prevalence, maternal characteristics perinatal outcomeLancetYear: 19841116366144885
12. Raatikainen K,Heiskanen N,Heinonen S. Does unemployment in family affect pregnancy outcomes in condition of high quality maternity care?BMC Public HealthYear: 200664616504118
13. Henriksen TB,Savitz DA,Hedegaard M,Secher NJ. Employment during pregnancy in relation to risk factors and pregnancy outcomeBr J Obstet GynaecolYear: 1994101858657999687
14. Wildschut HI,Nas T,Golding J. Are sociodemographic factors predictive of preterm birth? A reappraisal of the 1958 British perinatal mortality surveyBr J Obstet GynaecolYear: 199710457638988698
15. Ugwuja EI,Akubugwo EI,Ibiam AU,Obidoa O. Impact of maternal copper and zinc on pregnancy outcomes in a population of pregnant NigeriansPakistan J NutrYear: 2010967882
16. Ugwuja EI,Akubugwo EI,Ibiam AU,Obidoa O. Ugwu NC. Plasma copper and zinc among pregnant women in Abakaliki, southeastern Nigeria.Internet J Nutr WellnessYear: 2010101
17. Ben SY,Kuh D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectivesInt J EpidemiolYear: 2002312859311980781
18. Harding JE. The nutritional basis of the foetal origins of adult diseaseInt J EpidemiolYear: 200130152311171842
19. World Health OrganizationThe prevalence of anaemia in women: a tabulation of available informationYear: 1992GenevaWorld Health Organization6
20. Fawzi WW,Msamanga GI,Urassa W,Hertzmark E,Petraro PM,Willett WC,et al. Vitamins and perinatal outcomes among HIV-negative women in TanzaniaNew Engl J MedYear: 200735614233117409323
21. Dacie JV,Lewis SM. Practical haematology, 8th ed.Year: 1994EdinburgChurchill Livingstone4959
22. Robets WL,McMillin GA,Burtis CA,Bruns DE. Burtis CA,Ashwood ER,Bruns DEReference information for clinical laboratory.Tietz Textbook of clinical chemistry and molecular diagnosis, 4th ed.Year: 2006St. Louis, MissouriSaunders2251302
23. Bremner I. Manifestations of copper excessAm J Clin NutrYear: 1998675 Suppl1069S73S9587154
24. Sandstrom B. Micronutrient interactions: effects on absorption and bioavailabilityBr J NutrYear: 200185Suppl 2S181511509108
25. Turnlund JR. Shils ME,Shike M,Ross AC,Caballero B,Cousins RJCopper.Modern nutrition in health and disease, 10th ed.Year: 2006PhiladelphiaLippincott Williams & Wilkins28699
26. Kramer MS,Goulet L,Lydon J,Seguin L,McNamara H,Dassa C,et al. Socio-economic disparities in preterm birth: causal pathways and mechanismsPaediatr Perinat EpidemiolYear: 200115Suppl 21042311520404
27. Henriksen TB,Hedegaard M,Secher NJ. The relation between psychosocial job strain, and preterm delivery and low birthweight for gestational ageInt J EpidemiolYear: 199423764748002191
28. Filho FL,Assunção AN Jr,Silva AAM,Lamy ZC,Barbieri MA,Bettilo H. Social inequality and perinatal health: comparison of three Brazilian cohortsBrazilian J Med Biolog ResYear: 200740117786
29. Zuckerman BS,Frank DA,Hingson R,Morelock S,Kayne HL. Impact of maternal work outside the home during pregnancy on neonatal outcomePaediatrYear: 19867745964
30. Arntzen A,Andersen AM. Social determinants for infant mortality in the Nordic countries 1980–2001Scand J Public HealthYear: 200432381915513672
31. Pathak P,Kapil U. Role of trace elements zinc, copper and magnesium during pregnancy ant its outcomesIndian Paediatr7110035
32. Shaw GM. Strenuous work, nutrition and adversepregnancy outcomes: a brief reviewJ NutrYear: 20031331718S721S12730489
33. Lobel M,Dunkel-Schetter C,Scrimshaw SCM. Prenatal maternal stress and prematurity: a prospective study of socio-economically disadvantaged womenHealth PsycholYear: 19921132401559532
34. Wadhuta PD,Sandman CA,Porto M,Dunkel-Schetter C,Garite TJ. The association between prenatal stress and infant birthweight and gestational age at birth: a prospective investigationAm J Obstet GynaecolYear: 199316985865
35. Khashan KS,Mcnamee RM,Abel KM,Mortensen PB,Kenny LC,Pedersen MG,et al. Rates of preterm birth following antenatal maternal exposure to severe life events: a population-based cohort studyHuman ReproductYear: 20092442937
36. Andersen AMN,Mortensen LH. Socioeconomic inequality in birth outcomes: what do the indicators tell us, and where do we find the dataCMAJYear: 200617414293016682710
37. Ugwuja EI,Ugwu NC. Helicobacter pylori in uninvestigated dyspepsia in primary health cares in Abakaliki, NigeriaOnline J Health Allied SciYear: 200714
38. Koupilova I,Bobak M,Holcik J,Pikhart H,Leon DA. Increasing social variation in birth outcomes in the Czeh Republic after 1989Am J Public HealthYear: 199888134379736874

[TableWrap ID: T1] Table 1. 

General characteristics of pregnant women at ≤25 weeks gestation and their neonates at delivery

Parameter No. Mean SD Range
Age (years) 350 27.04 4.75 15-40
BMI (kg/m2) 350 27.3 4.3 17.8-42.6
Parity 350 1.41 1.46 0-4
Gestational age (weeks) 350 21.76 3.12 11-25
Copper (µmol/L) 349 9.59 9.42 0.89-45.36
Iron (µmol/L) 349 10.25 7.69 1.79-45.12
Zinc (µmol/L) 349 9.19 9.16 0.7-67.32
Haemoglobin (g/dL) 349 10.21 1.26 6.5-13.3
Antenatal attendance 343 7.01 2.52 1-14
Duration of pregnancy (weeks) 319 39.14 1.73 33-43
Birthweight (cm) 319 3.06 0.50 2.00-4.50
Birth-length (cm) 319 50.93 4.66 41.0-80.0
Head-circumference (cm) 319 33.66 2.68 26.0-48.0

BMI=Body mass index; SD=Standard deviation

[TableWrap ID: T2] Table 2. 

Prevalence of low plasma copper, iron, and zinc in relation to sociodemographic/obstetric data

Maternal parameter No. Copper Mean±SD Iron Mean±SD Zinc Mean±SD
  0 140 82 (58.6) 3.14±1.71 88 (62.8) 5.99±1.92 68 (48.6) 2.71±1.21
  1 66 36 (54.5) 3.48±2.02 47 (71.2) 5.80±2.04 27 (40.9) 2.84±1.18
  2 53 35 (66.0) 3.44±1.88 35 (66.0) 5.60±1.76 19 (35.8) 2.78±1.14
  3 40 23 (57.5) 2.96±1.73 23 (57.5) 6.31±1.78 24 (60.0) 2.36±1.13
  >3 50 27 (54.0) 3.29±1.78 29 (58.0) 5.80±1.59 22 (44.0) 2.45±1.06
  Total 349 203 (58.2) 3.25±1.80 222 (63.6) 5.90±1.85 160 (45.8) 2.65±1.16
Living accommodation
  Single room 189 115 (60.8) 3.30±1.90 123 (65.1) 5.95±1.90 82 (43.4) 2.63±1.18
  Flat 135 72 (53.3) 3.33±1.72 82 (60.7) 5.89±1.87 64 (47.4) 2.71±1.19
  Bungalow 24 15 (62.5) 2.40±1.80 16 (66.7) 5.64±1.45 13 (54.2) 2.57±0.97
  Total 348 202 (58.1) 3.24±1.80 221 (63.5) 5.90±1.85 159 (45.7) 2.65±1.16
Educational level
  None 8 5 (62.5) 2.03±0.74 2 (25) 6.89±0.79 2 (25) 1.89±1.49
  Primary 42 24 (57.1) 2.79±1.65 24 (57.1) 6.22±1.92 17 (40.5) 2.59±1.13
  Secondary 171 97 (56.7) 3.27±1.81 111 (64.9) 6.02±1.86 82 (48.0) 2.62±1.18
  Tertiary 120 71 (59.2) 3.60±1.87 80 (66.7) 5.59±1.82 55 (45.8) 2.74±1.19
  Total 341 197 (57.8) 3.30±1.81 217 (63.6) 5.89±1.86 156 (45.8) 2.65±1.17
  Housewife 53 31 (58.5) 3.45±1.90 32 (60.4) 6.01±1.85 28 (52.8) 2.77±1.18
  Student 61 40 (65.6) 3.16±1.89 40 (65.6) 5.99±1.80 29 (47.5) 3.0 ± 1.18
  Civil servant 143 64 (44.8) 3.27±1.76 92 (64.3) 5.77±1.83 65 (45.5) 2.50± 1.14
  Artisan 87 44 (50.6) 3.30±1.67 56 (64.4) 5.89±1.94 36 (41.4) 2.52±1.12
  Farmer 5 4 (80.0) 3.20±1.62 2 (40.0) 8.04±0.83 2 (40.0) 3.19±1.99
  Total 349 203 (58.2) 3.25±1.80 222 (63.6) 5.90±1.85 160 (45.8) 2.65±1.16

Figures in parentheses indicate percentages. SD=Standard deviation

[TableWrap ID: T3] Table 3. 

Prevalence of adverse maternal and foetal outcomes in relation to maternal sociodemographic data*

Maternal sociodemographic data Maternal outcomes Foetal outcomes
Anaemia Illnesses H. pylori HTN DM Assisted delivery Surgical delivery LBW Post-term
Educational level
  None 87.5† 37.5† 25† 14.3† - - - 12.5 -
  Primary 71.4†† 64.3†† 16.7†† 21.4†† 2.5†† 15.4†† 37.7† 15.4 5.1
  Secondary 59.9¶ 58.5†† 19.8†† 7.7¶ 1.8¶ 6.9 5.0†† 12.0 8.2
  Tertiary 64.2¶ 68.8†† 33.3¶ 13.7† 7.8§ 10.2†† 4.6†† 17.6 6.5
  Total 69.3 61.2 24.3 11.6 3.9 8.9 5.1 14.4 7.0
Living accommodation
  Single room 63.0 63.0† 20.1 12.0 3.8 9.9† 4.7† 12.9† 7.6
  Flat 65.2 61.0† 29.6 11.1 3.8 8.7† 5.5† 12.6† 6.3
  Bungalow 66.7 45.8†† 20.8 8.7 4.3 4.8†† 9.5†† 33.3†† 4.8
  Total 64.1 61.0 23.9 11.4 3.8 9.1 5.3 14.2 6.9
  Housewife 56.6† 64.2† 22.6† 3.8† 1.9† 5.9† 7.8† 18.0† 10.0
  Civil servant 65.0†† 69.7† 25.9† 16.3†† 5.8†† 8.6† 7.0† 18.8† 7.0
  Artisan 60.9†† 54.7†† 24.1† 12.8†† 3.5¶ 8.4† 2.4†† 6.0†† 4.8
  Student 68.9†† 45.8¶ 19.7† 6.9† 1.8† 15.1†† 3.8†† 11.3¶ 7.5
  Farmer 100.0¶ 80.0§ 40.0†† - - - - 20.0† -
  Total 63.9 61.2 24.1 11.7 3.8 9.1 5.3 14.1 6.9

TF3-001*Values are expressed as percentages. Values with different superscript are statistically different (p<0.05)

DM=Diabetes mellitus; HTN=Hypertension; LBW=Low birthweight

Article Categories:
  • Original Papers

Keywords: Key words: Maternal nutrition, Morbidity, Pregnancy outcomes, Socioeconomic status, Trace elements, Nigeria.

Previous Document:  Prevalence of vitamin D deficiency among adult population of Isfahan City, Iran.
Next Document:  Type, content, and source of social support perceived by women during pregnancy: evidence from Matla...