Örebro University
School of Medical Sciences Degree project, 30 ECTS January 2016
Maternal factors, early pregnancy
anthropometry and gestational weight gain.
A population-based study in Matlab, Bangladesh.
Author: Fanny Hansson Supervisors: Lars-Åke Persson1, Anisur Rahman2 1Dpt of Women’s and Children’s Health; International Maternal and Child Health, Uppsala University, Uppsala, Sweden 2 Centre for Reproductive Health, International Centre for Diarrhoeal Disease Research (icddr,b), Dhaka, Bangladesh
ABSTRACT
Background: Widespread maternal undernutrition is considered the major cause behind the persistently
high prevalence of intra-uterine growth restriction and low birthweight in Bangladesh. Pre-pregnancy undernutrition and inadequate gestational weight gain (GWG) both contribute to impaired foetal growth. In addition to poverty, several maternal factors are believed to impede development towards adequate nutrition among Bangladeshi women. Methods: Through the use of data from a currently running pregnancy cohort study (the PreSSMat study), we reviewed early pregnancy anthropometry, the level of GWG and GWG adequacy (using guidelines from the American Institute of Medicine – IOM) among 208 women in Matlab, rural Bangladesh. We also analysed the association between anthropometry and
different maternal factors, i.e. age, parity and level of education. Results: 15% of women were
underweight in early pregnancy. The prevalence of overweight was higher than expected, 17%. The mean GWG was low (0.34 kg/week), with 120/207 women (58%) gaining less than IOM recommendations. Older age and higher parity were associated with low GWG. Pre-pregnancy BMI was a strong predictor of GWG adequacy: overweight women gaining more and underweight women gaining less than IOM recommendations. Maternal educational level had no association with BMI or GWG. Conclusions: Both undernutrition and overnutrition were prevalent among pregnant women in rural Bangladesh, indicating a fast nutrition transition. Also, a GWG outside the recommended ranges was common in this population. To avoid complications of impaired or excessive foetal growth, expanded preventive actions in maternal nutrition are needed in Bangladesh.
CONTENTS
Abbreviations………... 4
INTRODUCTION………...……….... 5
SUBJECTS AND METHODS………..……….. 6
The PreSSMat Study and Ethics Approval……….……….. 6
Study Design……….……….………... 7 Definitions……….……….……... 7 Data analysis……….… 8 RESULTS………...………. 8 DISCUSSION……….……...……….. 9 CONCLUSION………...………...… 11 Acknowledgements……… 11 REFERENCES………... 12
TABLES AND FIGURES………. 16
Figure 1……….. 16
Table 1……… 16
Table 2……… 17
Table 3……… 18
Table 4……… 19 APPENDIX 1: Research Protocol PreSSMat
Abbreviations
ANC visit – Antenatal clinic visit BMI – Body mass index
GW – Gestational week
GWG – Gestational weight gain
icddr,b – International Centre for Diarrhoeal Disease Research, Bangladesh IOM – (The American) Institute of Medicine
PreSSMat – Preterm and Stillbirth Study, Matlab WHO = World Health Organization
INTRODUCTION
In recent decades, Bangladesh has made substantial progress in several health-related areas but despite this, the burden of poverty remains a major obstacle to satisfactory nutrition [1,2].In contrast to the obesity epidemic in high-income countries, Bangladesh is still battling the widespread undernutrition in its population [3]. A so-called ”double burden of malnutrition”, which comprises both prevalent
underweight and overweight, do exist in Bangladesh today but it has not been as pronounced as in other low- and middle-income countries [4,5].
As a result of chronic undernutrition, more than one tenth of Bangladeshi women between the ages 15 to 49 years were stunted (low height), and one in four were underweight (body mass index < 18.5) in 2011 [3]. When these women enter pregnancy, the foetus has an increased risk of intrauterine growth restriction and low birthweight (<2500 grams). The weight of the offspring is also linked to the mother’s weight gain during pregnancy (gestational weight gain = GWG). A poorGWG increases the risk of intrauterine growth restriction and low birthweight, especially for women who are already stunted or underweight [6-8]. Also, girls who were born small are later more likely to give birth to small children themselves and in this way, undernutrition is transferred through generations [9]. The connection between maternal pre-pregnancy anthropometry, GWG and offspring birthweight has been confirmed in several systematic reviews [10-15].
In the mid-1990s, Ramalingswami et al. drew the attention to the discrepancy between South Asia’s high prevalence, and equally impoverished sub-Saharan Africa’s lower prevalence, of maternal and foetal undernutrition. They concluded that the disadvantageous position of women in South Asia is a major contributing factor behind this discrepancy and that interventions, which benefit women’s empowerment, are essential to put an end to what they called ”the Asian Enigma” [16,17]. Since then, the theory of an ”Asian Enigma” has been supported by other researchers, showing that gender discrimination affects female health throughout the reproductive cycle [18] and impedes a major reduction in maternal and foetal undernutrition rates in Bangladesh and other South Asian countries [19-21].
Female education is one important determinant of foetal growth [22-24]. Proposed mediators of this effect on foetal growth are the access to a greater proportion of the household’s joint food supply, a higher consumption of protein, and less strenuous physical labour during pregnancy [25]. An educated woman might also be more prone to disregard deleterious food taboos and to make other independent choices that have a positive effect on her nutritional status [26].
As mentioned earlier, the probability of obtaining an adequate GWG is influenced by the mother’s pre-pregnancy nutritional status. An already underweight woman needs to gain considerably more weight during her pregnancy to ensure that her offspring is born with a healthy body weight [27]. A poor GWG also affects foetal growth to a greater extent in women with chronic undernutrition than in women of
normal height and weight [6]. Furthermore, it is hypothesised that repeated and frequent childbearing in itself can constitute a challenge for women’s health and nutrition in low-income countries, since
pregnancy and lactation are considered depletion phases (negative energy and nutrient balance) and non-pregnancy is seen as a repletion phase (positive energy and nutrient balance). In the case of nutrient shortage, women might not catch up during the repletion phases and hence enter into the next depletion phase in a worsened nutritional condition [28].
Since foetal growth is strongly dependent on maternal nutrition before and during pregnancy [29], improvements in these areas areessential to combat the morbidity and mortality associated with intra-uterine growth restriction and low birthweight. These conditions pose not only immediate health risks to infants in low-income societies but also constitute risk factors for several adult diseases [30-32].
Furthermore, it constrains cognitive development potential, which can effect schooling and adult earnings [33,9]. Ameliorating female nutrition throughout her reproductive cycle would also combat the vicious cycle of ”inherited” undernutrition that exists in Bangladesh today.
The aim of this study was to examine early pregnancy anthropometry and GWG in a population of Bangladeshi women and to investigate whether these are associated with maternal background factors including level of education.
SUBJECTS AND METHODS
The PreSSMat Study and Ethics Approval
This study was nested into a large pregnancy cohort study (the PreSSMat study) at the iccdr,b
(International Centre for Diarrhoeal Disease Research, Bangladesh) field station in Matlab, a subdistrict of rural Bangladesh. In the mid-1960s, icddr,b initiated a health and demographic surveillance system in Matlab, which covers a 220,000 population in more than 140 villages, and it has served as a basis for PreSSMat and numerous other studies. Briefly, PreSSMat aims to increase the understanding of preterm delivery, and it includes a wide range of social and biological markers of adverse pregnancy outcomes among women in Matlab. PreSSMat is a prospective cohort study that plans to enrol 4700 eligible
participants, who are monitored throughout the course of pregnancy with an intended follow-up of mother and child throughout early childhood.
PreSSMat participants were not put at any medical risks that significantly differ from the risks inherent in the districts local obstetrical care. Confidentiality and data privacy were protected. Informed consent were sought from the potential participants. The ethical review committee at icddr,b has approved the PreSSMat study. Details of the methods used in the PreSSMat study have been described in the attached research protocol (Appendix 1).
Study Design
This study was made possible through the use of data from the PreSSMat Study and participation in fieldwork. At the time of data collection, a total of 735 participants had been recruited to the PreSSMat study. These participants had been enrolled between April 29 and November 30, 2015. The data matrix was inspected to avoid inclusion of data with evident registration errors. The following data were excerpted from the icddr,b databases: information on maternal date of birth and last menstrual period (date stated by the woman and date calculated using ultrasound), maternal anthropometry (height and weight at every scheduled antenatal clinic visit), level of education of the woman and data to adjust for possible confounding (age and parity).
Definitions
PreSSMat personnel collected maternal anthropometric measurements at repeated antenatal clinic (ANC) visits during pregnancy with the fourth and last visit at around gestational week (GW) 36. Height was measured without shoes and head coverings to the nearest 0.1 cm. Weight was measured without shoes and heavy clothing to the nearest 100 g. Body mass index (BMI) was calculated by dividing the body mass (in kilograms) by the square of the body height (in meters). The WHO cut off points for
underweight, normal range, overweight and obesity were used for BMI-classification. Maternal BMI at enrolment (around GW 15) was used as a proxy for pre-pregnancy BMI, which is considered appropriate since only approximately 1 kg is gained during the first trimester [34,35].
The level of weight gain per week (GWG) was calculated using the information on participant’s last menstrual period based on ultrasound assessment and the gestational ages in weeks and maternal body weights at enrolment and the 3rd ANC visit. The reason for choosing the 3rd visit as an endpoint instead of the 4th and last ANC visit was that only a minority of the study population attended the 4th clinic visit. Additionally, the small group of women with a 4th ANC visit constituted a selective group that showed significantly lower mean GWG throughout pregnancy as compared to those who lacked a 4th visit. Due to this reason, GWG was expressed as mean GWG per week and not the total GWG for the whole
pregnancy. Since the major part of weight is gained during the second trimester and first part of third trimester, this time span should be appropriate [34,36].
The American Institute of Medicine (IOM) guidelines were used to categorize GWG into inadequate, normal or excessive weight increase per week (Table 1). These guidelines, most recently revised in 2009, are used globally to assess excessive or inadequate GWG and were developed to prevent harm to mother and foetus during or after pregnancy [27,37]. The IOM guidelines were chosen for comparison and provide information on recommended GWG per week for the different BMI levels.
Information on educational level was obtained at home visits by trained interviewers using structured questionnaires (Appendix 1). The educational background of the women was expressed as years of schooling, which were categorized into three levels: no education, primary level (1-5 years) and secondary level or higher level of education (≥ 6 years).
Data analyses
The participant flow in the study was analysed and described. Maternal characteristics at baseline of included and excluded participants were cross-tabulated and assessed by Chi2 tests with p-values. The prevalence of underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9) and overweight (BMI ≥25) was calculated for all levels of maternal background characteristics. The occurrence of underweight or overweight for different subgroups in relation to these maternal background factors were expressed as crude odds ratios (OR) with 95% confidence intervals (CI), and multivariable logistic regression was used to calculate adjusted OR including all other characteristics as covariates. The association between
selected maternal background factors (age, height, parity, educational level and pre-pregnancy BMI) and average GWG from enrolment to 3rd clinic visit was calculated. The level of mean GWG per week was compared with the IOM guidelines for the relevant BMI level of the individual woman. The association between maternal background factors and mean GWG per week was analysed by Analysis of Variance (ANOVA). The level of statistical significance was set at a p < 0.05. SPSS 21 (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.) was used for all analyses.
RESULTS
Of the 735 women recruited to the PreSSMat study from April 29 to November 30, 2015, 208 women were eligible for this study. In some analyses, one or two participants were excluded due to missing data, i.e. parity or date of birth of the woman (Fig. 1). Table 2 shows the baseline characteristics of the included and excluded women. The number of excluded participants varies from 297 to 527 because data on some characteristics had not yet been registered for all women at the time of data collection. There is a trend of included women being slightly less educated than excluded women, but overall the included and excluded women do not significantly differ in any of the baseline characteristics.
Half of the women were less than 25 years when entering pregnancy and a majority were expecting their first or second child. Overall, the participants were relatively well educated with 71% having six or more years of schooling. It was not uncommon among the participants to have completed higher
secondary level, i.e. 12 years of schooling. When using 145 cm as a cut-off value, stunting was observed in 8% of the women at baseline. In early pregnancy, 68% were of normal BMI, 15% had a low BMI, indicating chronic energy deficiency, and 17% were overweight (Table 2). Out of the participants with
overweight, only two were obese (BMI ≥ 30). Because of the small number of obese participants, overweight and obesity were merged into one category (BMI ≥ 25) in all analyses.
Younger women tended not to be overweight when entering pregnancy (aOR 0.21), but apart from this finding, there were no significant differences between the subgroups defined by the maternal background factors included in this study. The educational level had no association with pre-pregnancy BMI (Table 3).
To calculate the mean GWG per week in the second and third trimester, weight increase from enrolment to the 3rd ANC visit was used. These weights were recorded at 14.9 (SD 2.4) and 34.0 (SD 1.8) weeks, respectively. Mean GWG per week for the whole cohort was 0.34 ± 0.17 kg, 0.38 ± 0.12 for underweight, 0.34 ± 0.18 for normal weight and 0.28 ± 0.19 kg for overweight participants (p-value 0.055). Parity and age were both associated with mean GWG per week with tendencies to lower increases with higher parity or older age (p-values 0.002 and <0.001, respectively).
According to IOM guidelines, GWG was adequate for 41/207 (19.8%) of the participants, while 120/207 (58.0%) had an inadequate GWG and 46 (22.2%) had an excessive GWG. Pre-pregnancy BMI was significantly associated with being below, within or above these guidelines. Among underweight women 75.0% exhibited an inadequate GWG and among overweight women 34.3% exhibited an
excessive GWG (p-value 0.007). The level of education was neither associated with the mean GWG per week nor with a GWG either outside or within IOM guidelines (Table 4).
DISCUSSION
This study examined early pregnancy anthropometry in a population of Bangladeshi women and its association with maternal background factors (age, parity, height and educational level). Furthermore, we investigated the level of GWG in the same population and whether the rate of GWG was influenced by any of these maternal factors or pre-pregnancy BMI. We found that in early pregnancy, a significant part of the study population was underweight (15%) but, surprisingly, a relatively high proportion (17%) was overweight. The GWG was generally low (mean GWG 0.34 kg/week). Older age and higher parity were both significantly associated with a lower GWG. 58% of the women in our study had a GWG below IOM recommendations and the percentage was even higher when only looking at the already underweight women (75%). The level of education was neither associated with the woman’s BMI in early pregnancy nor with her GWG.
Overall, the data used in this study hold a high degree of validity but the lack of digital height
equipment generated some heaping of data on women’s height. However, this should have had minimal impact on the BMI values and no influence on GWG outcome. One commonly used confounder when studying GWG, smoking, was not included in this study since no women in Matlab smoke. Instead, the
habit of betel nut chewing is considerably more common, but information on this potential confounder was not available at the time of data analysis.
When comparing our figures on BMI in early pregnancy with a Matlab pregnancy cohort 12-14 years ago, a major change can be noticed. At that time, 27% of women were underweight in early pregnancy (GW 9) compared to 15% today, while the prevalence of overweight women was only 6% as compared to 17% in this study (LÅ Persson, personal communication). Rapid nutrition transitions have previously been described from other low- and middle-income countries that now face a double burden of
undernutrition and overnutrition [4]. The short period between the previous pregnancy cohort data from Matlab and our results suggests that this transition is happening very rapidly in Bangladesh.
A mean GWG of 0.34 kg per week is fairly low but consistent with the GWG reported from other low-income countries [38,39]. Disturbingly, underweight women were most likely to have an inadequate GWG (75% were not gaining the recommended 0.45-0.59 kg/week) while excessive GWG was more common among already overweight women (34% had a weight increase above the recommended 0.23-0.32 kg/week). The pattern of early pregnancy BMI as an important determinant of GWG adequacy is in line with previous findings [40,41] and it adds to the above-mentioned risk of a pronounced double burden. While pre-pregnancy undernutrition, especially combined with a low GWG, increases the risk of intrauterine growth restriction and low birthweight, pre-pregnancy overweight and high GWG are risk factors for macrosomia and various obstetrical complications [42]. Clearly, both inadequate and excessive maternal nutrition before and during pregnancy has potentially severe effects on the offspring.
The older and multiparous pregnant women in our study gained less weight per week than younger and nulliparous women. Theoretically, it could be related to maternal nutritional depletion similar to what has been reported from studies in Pakistan and Guatemala, where marginally nourished women had an overall weight loss during one full reproductive cycle compared to the well-nourished and more severely
malnourished women that experienced a slight weight gain during the same cycle [43,44]. These earlier findings, together with our data, suggest that maternal nutritional depletion might exist under certain circumstances.
The non-existent connection between the woman’s level of education and her BMI or GWG found in our study is surprising; two previous studies, conducted in Bangladesh, have shown that maternal education was significantly associated with the birthweight of the offspring, (which in turn may be
associated with pre-pregnancy BMI and GWG) [23,24]. The relationship between maternal education and infant birthweight has also been demonstrated in India and Ghana [45,46]. In Tanzania, a higher level of maternal education was shown to improve the chances of an adequate GWG [39]. Bangladesh’s recent advances towards education for all women in all social strata may partly explain the findings in our study. In 2007, only 32% of Bangladeshi women between 15 and 49 had six or more years of schooling, but in
2014 this proportion had increased to 57% [47,48]. The even higher figure in our study (71%) might be explained by a younger study population. It may also be noted that the proportion of underweight women in Bangladesh has decreased in parallel with an increase in educational level. On a national level, 34% of women in fertile age were underweight in 2004, compared to 30% in 2007 and 24% in 2011 [47,3]. The data used in this study was collected using well established routines in a health and demographic surveillance system. Data on participant age was obtained from the databases of this surveillance system in Matlab, where all women are registered and hold a unique identification code. The surveillance system runs frequent home visits, which implies that the information on last menstrual period is of high quality. Gestational age was also verified through ultrasonography. The PreSSMat participants included in our study do not differ significantly from the excluded PreSSMat participants at baseline, indicating no selection bias.
With this high level of participation, the data can be seen as representative of this and other rural areas in the delta-land of Bangladesh. The results may not apply to neighbouring countries because of
differences in the level of poverty and food insecurity as well as in their investments in education.
CONCLUSION
This study found that undernutrition still is widespread among pregnant women in rural Bangladesh but also that the proportion is decreasing. Instead, the prevalence of overweight is rapidly increasing, indicating a currently ongoing nutrition transition similar to what has been seen in many other low- and middle-income countries. Our results also show that GWG was low for this population and that older age and higher parity were associated with a lower GWG. Among underweight women, a majority did not reach a level of adequate GWG, increasing the risk of foetal undernutrition, which may have deleterious consequences. On the other hand, a third of overweight women gained more weight than recommended, which entails other possible negative health consequences for both mother and foetus. This evident
double burden of malnutrition among pregnant women should be addressed within the Bangladeshi health system and other sectors of society. Regarding prevention, ensuring access to education for all women seems to be one step in the right direction combined with efforts to advice pregnant women on
recommended weight gain and provide adequate nutrition.
Acknowledgements
First of all, I would like to thank all the women participating in the PreSSMat study in Bangladesh. I would also like to thank my supervisors Lars-Åke Persson and Anisur Rahman for their support and guidance throughout the process, and finally all the staff at icddr,b in Dhaka and Matlab for being so kind and helpful.
REFERENCES
1. Chowdhury AM, Bhuiya A, Chowdhury ME, Rasheed S, Hussain Z, Chen LC. The Bangladesh paradox: exceptional health achievement despite economic poverty. Lancet. 2013 Nov
23;382(9906):1734-1745.
2. Saha KK, Frongillo EA, Alam DS, Arifeen SE, Persson LA, Rasmussen KM. Household food security is associated with growth of infants and young children in Bangladesh. Public Health Nutr. 2009
Jun;12(6):884.
3. National Institute of Population Research and Training (NIPORT), Mitra and Associates, and ICF International. Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: NIPORT, Mitra and Associates, and IFC International; 2013. Available from: https://dhsprogram.com/pubs/pdf/FR265/FR265.pdf
4. Abdullah A. The double burden of undernutrition and overnutrition in developing countries: an update. Curr Obes Rep. 2015 Sep;4(3):337-349.
5. Khan SH, Talukder SH. Nutrition transition in Bangladesh: is the country ready for this double burden. Obes Rev. 2013 Nov;14(2):126-133.
6. Pickett K, Abrams B, Selvin S. Maternal height, pregnancy weight gain, and birthweight. Am J Hum Biol. 2000 Sep;12(5):682-687.
7. Haugen M. Brantsater AL, Winkvist A, Lissner L, Alexander J, Oftedal B, et al. Associations of pre-preganancy body mass index and gestational weight gain with pregnancy outcome and postpartum weight retention: a prospective observational cohort study. BMC Pregnancy Childbirth. 2014 Jun;14:201
8. Jeric M, Roje D, Medic N, Strinic T, Mestrovic Z, Vulic M. Maternal pre-pregnancy underweight and fetal growth in relation to institute of medicine recommendations for gestational weight gain. Early Hum Dev. 2013 May;89(5):277-281.
9. Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, et al. Maternal and child
undernutrition: consequences for adult health and human capital. Lancet. 2008 Jan 26;371(9609):340-57. 10. Yu Z, Han S, Zhu J, Sun X, Ji C, Guo X. Pre-pregnancy BMI in relation to infant birth weight and offspring overweight/obesity: a systematic review and meta-analysis. PLoS One. 2013 Apr
16;8(4):e61627.
11. Han Z, Mulla S, Beyene J, Liao G, McDonald SD. Maternal underweight and the risk of preterm birth and low birthweight: a systematic review and meta-analyses. Int J Epidemiol. 2011 Feb;40(1):65-101. 12. Han Z, Lutsiv O, Mulla S, McDonald SD. Maternal height and the risk of preterm birth and low birth weight: a systematic review and meta-analyses. J Obstet Gynaecol Can. 2012 Aug;34(8):721-746.
13. Siega-Riz AM, Viswanathan M, Moos MK, Deierlein A, Mumford S, Knaack J, et al. A systematic review of outcomes of maternal weight gain according to the institute of medicine recommendations: birthweight, fetal growth and postpartum weight retention. Am J Obstet Gynecol. 2009
Oct;201(4):339.e1-14.
14. Viswanathan M, Siega-Riz, Moos MK, Deierlein A, Mumford S, Knaack J, et al. Outcomes of maternal weight gain. Evid Rep Technol Assess. 2008 May;(168):1-223.
15. Han Z, Lutsiv O, Mulla S, Rosen A, Beyene J, McDonald SD, et al. Low gestational weight gain and the risk of preterm birth and low birthweight: a systematic review and meta-analyses. Acta Obstet Gynecol Scand. 2011 Sep;90(9):935-954.
16. Ramalingaswami V, Jonsson U, Rohde J. Malnutrition: a South Asian enigma. Katmandu: UNICEF Regional Office for South Asia; 1997. ROSA Publication No. 5. 1997:11-22.
17. Ramalingaswami V, Jonsson U, Rohde J. The Asian Enigma. New York: UNICEF; 1996. The progress of nations; 1996:11-17.
18. Fikree FF, Pasha O. Role of gender in health disparity: the South Asian context. BMJ. 2004 Apr 3;328(7443):823-826.
19. ACC/SCN. Fourth Report on the World Nutrition Situation. Geneva: ACC/SCN in collaboration with IFPRI; 2000. Available from: http://www.unscn.org/layout/modules/resources/files/rwns4.pdf
20. Gopalan C. Nutrition and developmental transition: lessons from Asian experience. NFI Bulletin. 1999;20:1-5.
21. Bhutta AZ. Why has so little changed in maternal and child health in south Asia? BMJ. 2000 Sep 30;321(7264):809-812.
22. Silva LM, Jansen PW, Steegers EA, Jaddoe VW, Arends, Tiemeier H, et al. Mother’s educational level and fetal growth: the genesis of health inequalities. Int J Epidemiol. 2010 Oct;39(5):1250-1261. 23. Karim E, Mascie-Taylor CG. The association between birthweight, sociodemographic variables and maternal antropometry in an urban sample from Dhaka, Bangladesh. Ann Hum Biol. 1997
Sep-Oct;24(5):387-401.
24. Khatun, Rahman M. Socio-economic determinants of low birth weight in Bangladesh: a multivariate approach. Bangladesh Med Res Counc Bull. 2008 Dec;34(3):81-86.
25. Ware H. Effects of maternal education, women’s roles and child care on child mortality. Popul Dev Rev. 1984;10:191-214.
26. Talukder B. Regional Differences of Child Undernutrition in Bangladesh. Yearb Popul Res Finl. 2013;48:189-201.
27. Rasmussen KM, Catalano PM, Yaktine AL. New guidelines for weight gain during pregnancy: what obstetrician/gynecologists should know. Curr Opin Obstet Gynecol. 2009 Dec;21(6):521-526.
28. Merchant K, Martorell R, Haas JD. Consequences for maternal nutrition of reproductive stress across consecutive pregnancies. Am J Clin Nutr. 1990 Oct;52(4):616-620.
29. Prada JA, Tsang RC. Biological mechanisms of environmentally induced causes of IUGR. Eur J Clin Nutr. 1998 Jan;52(1):21-28.
30. Barker DJP, Briksson JG, Forsen T, Osmond C. Fetal origins of adult disease: strength of effects and biological basis. Int J Epidemiol. 2002 Dec;31(6):1235-1239.
31. Barker DJP, Bull AR, Osmond C, Simmonds SJ. Fetal and placental size and risk of hypertension in adult life. BMJ. 1990 Aug;301(6746):259-262.
32. Leon DA, Lithell HO, Vagero D, Koupilová I, Mohsen R, Berglund L, et al. Reduced fetal growth rate and increased risk of death from ischaemic heart disease: cohort study of 15000 Swedish men and women born 1915-1929. BMJ. 1998 jul 25;317(7153):241-245.
33. Araújo LF, Giatti L, Chor D, Passos VM, Barreto SM. Maternal education, anthropometric markers of malnutrition and cognitive function (ELSA-Brasil). BMC Public Health. 2014 Jul 2;14:673.
34. Carmichael S, Abrams B, Selvin S. The pattern of maternal weight gain in women with good pregnancy outcomes. Am J Public Health. 1997 Dec;87(12):1984-1988.
35. Fattah C, Farah N, Barry SC, O’Connor N, Stuart B, Turner MJ. Maternal weight and body composition in the first trimester of pregnancy. Acta Obstet Gynecol Scand. 2010 Jul;89(7):952-955. 36. Abrams B, Carmichael S, Selvin S. Factors associated with the pattern of maternal weight gain during pregnancy. Obstet Gynecol. 1995 Aug;86(2):170-176.
37. Abrams B, Altman SL, Pickett KE. Pregnancy weight gain: still controversial. Am J Clin Nutr. 2000 May;71(5 Suppl):1233S-1241S.
38. Siega-Riz AM, Adair LS. Biological determinants of pregnancy weight gain in a Filipino population. Am J Clin Nutr. 1993 Mar;57(3):365-372.
39. Changamire FT, Mwiru RS, Msamanga GI, Spiegelman D, Urassa W, Hertzmark E, et al. Macronutrient and sociodemographic determinants of gestational weight gain among HIV-negative women in Tanzania. Food Nutr Bull. 2014 May;35(1):43-50.
40. Chasan-Taber L, Schmidt MD, Pekow P, Sternfeld B, Solomon CG, Markenson G. Predictors of excessive and inadequate gestational weight gain in Hispanic women. Obesity (Silver Spring). 2008 Jul; 16(7):1657-1666.
41. Wells CS, Schwalberg R, Noonan G, Gabor V. Factors influencing inadequate and excessive weight gain in pregnancy: Colorado, 2000-2002. Matern Child Health J. 2006 Jan;10(1):55-62.
42. National Research Council and Institute of Medicine. Influence of Pregnancy Weight on Maternal and Child Health. Workshop report. Washington, DC: The National Academies Press; 2007. Available from: http://www.nap.edu/catalog/11817.html
43. Winkvist A, Habicht JP, Rasmussen KM. Linking maternal and infant benefits of a nutritional supplement during pregnancy and lactation. Am J Clin Nutr. 1998 Sep;68(3):656-661.
44. Winkvist A, Jalil F, Habicht JP, Rasmussen KM. Maternal energy depletion is buffered among malnourished women in Punjab, Pakistan. J Nutr. 1994 Dec;124(12):2376-2385.
45. Kader M, Perera Perera NKP. Socio-economic and nutritional determinants of low birth weight in India. N Am J Med Sci. 2014 Jul;6(7): 302-308.
46. Amegah AK, Damptey OK, Sarpong GA, Duah E, Vervoorn DJ, Jaakkola JJ. Malaria infection, poor nutrition and indoor air pollution mediate socioeconomic differences in adverse pregnancy outcomes in Cape Coast, Ghana. PloS One. 2013 Jul 22;8(7):e69181.
47. National Institute of Population Research and Training (NIPORT), Mitra and Associates, and Macro International. Bangladesh Demographic and Health Survey 2007. Dhaka, Bangladesh and Calverton, Maryland, USA: NIPORT, Mitra and Associates, and Macro International; 2009. Available from: http://dhsprogram.com/pubs/pdf/FR207/FR207%5BApril-10-2009%5D.pdf
48. National Institute of Population Research and Training (NIPORT), Mitra and Associates, and ICF International. Bangladesh Demographic and Health Survey 2014: Key Indicators. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT, Mitra and Associates, and ICF International; 2015. Available from: https://www.k4health.org/sites/default/files/bdhs_2014.pdf
TABLES AND FIGURES Underweight (≤ 18.5) Normalweight (18.5 – 24.9) Overweight (25.0 – 29.9) Obese (≥ 30.0) Recommended total GWG (kg) Recommended GWG per weeka (kg) 12.5 – 18.0 11.5 – 16.0 7.0 – 11.5 5.0 – 9.0 0.51 0.42 0.28 0.22 Pregnant women enroled in PreSSMat Study Apr 29 to
Nov 30 2015 after giving their informed consent (n=735)
PreSSMat participants eligible for this study (n=208)
Participants excluded because of no 3rd antenatal clinic visit or evident registration
errors (n=527).
Maximum study population (n=208) Patients excluded from some analyses because of missing data (n=2)
Figure 1: Study flow chart
Table 1: IOM Guideline for recommended gestational weight gain (GWG)
based on pre-pregnancy BMI.
a In second and third trimester
Table 2: Baseline characteristics of women enrolled in the PreSSMat study from April 29 to November 30. Pregnancy cohort in Matlab, Bangladesh, 2015.
Characteristic Includeda n/n2(%) Excludedb n/n2(%) P-value
Age (years) 15-24 25-29.9 ≥ 30 103/206 (50.0) 51/206 (24.8) 52/206 (25.2) 150/297 (50.5) 61/297 (20.5) 86/297 (29.0) 0.452 Parityc 0 1 ≥ 2 75/207 (36.2) 77/207 (37.2) 55/207 (26.6) 177/513 (34.5) 186/513 (36.3) 150/513 (29.2) 0.767 Education (years) 0 1-5 ≥ 6 27/208 (13.0) 34/208 (16.3) 147/208 (70.7) 38/489 (7.8) 99/489 (20.2) 352/489 (72.0) 0.066 Enrolment weight (kg) < 45 45-49.9 ≥ 50 67/208 (32.2) 44/208 (21.2) 97/208 (46.6) 159/527 (30.2) 141/527 (26.8) 227/527 (43.1) 0.288 Enrolment height (cm) < 150 150-154.9 ≥ 155 74/208 (35.6) 68/208 (32.7) 66/208 (31.7) 188/527 (35.7) 199/527 (37.8) 140/527 (26.6) 0.290 Enrolment BMI (kg/m2) ≤ 18.5 18.5 – 24.9 ≥ 25 32/208 (15.4) 141/208 (67.8) 35/208 (16.8) 86/527 (16.3) 345/527 (65.5) 96/527 (18.2) 0.833
a Included in present study b Excluded from present study c Number of previous live births
Table 3: Women’s characteristics and underweight and overweight in early pregnancy (around wk 15). Pregnancy cohort in Matlab, Bangladesh, 2015.
Charac-teristic Levels
BMI Underweight Overweight
< 18.5 18.5-24.9 > 25.0 OR (95% CI) ORadj (95% CI) OR (95% CI) ORadj (95% CI) All 32/207 (15.5) 140/207 (67.6) 35/207 (16.9) Education 0 4/27 (14.8) 19/27 (70.4) 4/27 (14.8) 0.98 (0.31-3.11) 1.24 (0.37-4.17) 0.80 (0.26-2.52) 0.61 (0.18-2.13) 1-5 6/34 (17.6) 23/34 (67.6) 5/34 (14.7) 1.21 (0.45-3.26) 1.42 (0.49-4.14) 0.80 (0.28-2.25) 0.59 (0.19-1.85) > 6 22/146 (15.1) 98/146 (67.1) 26/146 (17.8) 1.0 1.0 1.0 1.0 Age <25 yrs 19/103 (18.4) 76/103 (73.8) 8/103 (7.8) 2.71 (0.87-8.45) 1.53 (0.35-6.81) 0.19 (0.08-0.48) 0.21 (0.07-0.65) 25-29.9 9/51 (17.6) 31/51 (60.8) 11/51 (21.6) 2.57 (0.74-8.96) 2.83 (0.75-10.6) 0.62 (0.25-1.51) 0.49 (0.19-1.29) > 30 4/52 (7.7) 32/52 (61.5) 16/52 (30.8) 1.0 1.0 1.0 1.0 Parity 0 19/74 (25.7) 51/74 (68.9) 4/74 (5.4) 2.37 (0.92-6.12) 2.56 (0.65-9.99) 0.21 (0.06-0.68) 0.54 (0.13-2.31) 1 6/77 (7.8) 52/77 (67.5) 19/77 (24.7) 0.58 (0.18-1.83) 0.56 (0.15-2.04) 1.17 (0.52-2.67) 2.01 (0.76-5.31) > 2 7/55 (12.7) 36/55 (65.5) 12/55 (21.8) 1.0 1.0 1.0 1.0 Height < 150 cm 11/73 (15.1) 49/73 (67.1) 13/73 (17.8) 0.80 (0.33-1.96) 0.75 (0.29-1.89) 1.57 (0.61-4.07) 1.66 (0.60-4.56) 150-154.9 9/68 (13.2) 45/68 (66.2) 14/68 (20.6) 0.69 (0.27-1.76) 0.72 (0.27-1.93) 1.88 (0.73-4.83) 1.57 (0.58-4.27) > 155 12/66 (18.2) 46/66 (69.7) 8/66 (12.1) 1.0 1.0 1.0 1.0
BMI group data are n/n (%). OR provided with 95% Confidence Interval. ORadj is adjusted for all other characteristics.
Table 4: Women’s characteristics and mean GWG (kg/week) in 2nd and 3rd trimester and proportions below, within or above recommended GWG according to IOM recommendations for BMI groups (<18.5, 18.5-24.9 and >25 kg/m2). Pregnancy cohort in Matlab, Bangladesh, 2015.
Charac-teristic Levels n (%)
Mean GWG kg/week (SD)
p-valuea GWG below IOM guideline n (%) GWG within IOM guideline n (%) GWG above IOM guideline n (%) p-valueb All 207(100) 0.34 (0.17) 120 (58.0) 41 (19.8) 46 (22.2) Education 0 years 27 (13.0) 0.34 (0.14) 0.105 17 (63.0) 3 (11.1) 7 (25.9) 0.147 1-5 34 (16.4) 0.28 (0.14) 25 (73.5) 6 (17.6) 3 (8.8) > 6 146 (70.5) 0.35 (0.19) 78 (53.4) 32 (21.9) 36 (24.7) Age <25 years 103 (49.8) 0.38 (0.15) <0.001 52 (50.5) 23 (22.3) 28 (27.2) 0.209 25-29.9 52 (25.1) 0.30 (0.17) 33 (63.5) 8 (15.4) 11 (21.2) > 30 52 (251.1) 0.27 (0.19) 35 (67.5) 10 (19.2) 13 (13.5) Parity 0 74 (35.7) 0.36 (0.15) 0.002 40 (54.1) 16 (21.6) 18 (24.3) 0.069 1 78 (37.7) 0.36 (0.20) 41 (52.6) 14 (17.9) 23 (29.5) > 2 55 (26.6) 0.26 (0.15) 39 (70.9) 11 (20.0) 5 (9.1) Height < 150 cm 73 (35.3) 0.32 (0.13) 0.453 44 (54.1) 13 (17.8) 16 (21.9) 0.766 150-154.9 68 (32.9) 0.32 (0.21) 37 (54.4) 17 (25.0) 14 (20.6) > 155 66 (31.9) 0.36 (0.19) 39 (59.1) 11 (16.7) 16 (24.1) BMI <18.5 kg/m2 32 (15.5) 0.38 (0.12) 0.055 24 (75.0) 6 (18.8) 2 (6.3) 0.007 18.5-24.9 140 (67.6) 0.34 (0.18) 84 (60.0) 24 (17.1) 32 (22.9) >25 35 (16.9) 0.28 (0.19) 12 (34.3) 11 (31.4) 12 (34.3)
aAnalysis of Variance, F, p-value. bChi square, p-value.
ETHICAL CONSIDERATIONS
Informed consent is fundamental in all kinds of medical research that involves humans. In the setting of a low-income country, obtaining informed consent can prove to be challenging. Participants are to a greater extent illiterate or not formally educated. More emphasis will have to be put on explaining the purpose of the study, the study procedure and potential risks and benefits to participants. In countries with scarce healthcare resources, it is also important to make sure that the potential participants do not feel forced to consent in order to get necessary healthcare and treatment.
In the PreSSMat study in Bangladesh, participation is completely voluntary and both verbal and written informed consent is sought before enrolment of an eligble woman. In addition to a prepared consent form translated into Bengali, study nurses with extensive experience of research in this community are responsible for
answering questions about the study procedures. To ensure that illiterate participants receive all necessary information, a literate unbiased witness must oversee the full consent process. Participants are free to withdraw from the study at any time without stating a reason. Whether a woman chooses to participate or not participate in the study, does not affect her access to health services.
In those parts of the study I attended, there were no invasive procedures, but in PreSSMat as a whole, various types of sampling are included (blood samples, vaginal swabs and rectal swabs). These may cause mild discomfort but can also be beneficial to the patient i.e. screening for anemia and genital infections. Since a large number of research projects has been implemented in the sub-district Matlab during the last decades, the local healthcare system has become more developed as compared to other parts of the country. Through this established collaboration between science and healthcare, health problems identified through research can also be dealt with. The PreSSMat study is not a clinical trial and all study participants are treated equally. The purpose of PreSSMat, as well as my embedded study on gestational wieght gain, is to get more knowledge about what causes adverse pregnancy outcomes affecting a large proportion of women in Bangladesh and other low-income countries. By doing so, new guidelines, procedures and treatments in obstetrical care can be developed for the benefit of all women.
Jan 3, 2015
Corresponding author:
Fanny Hansson School of Medical Sciences Örebro University, Sweden Tel. +46 (0) 733 43 73 72 Email: fanhah101@studentmail.oru.se
COVER LETTER – PUBLIC HEALTH NUTRITION (PHN)
Dear Dr X,
Please find attached our manuscript titled ”Maternal factors, early pregnancy
anthropometry and gestational weight gain in Matlab, Bangladesh”, which we would like to submit for publication as a Research Article in Public Health Nutrition.
Maternal undernutrition before and during pregnancy is common in Bangladesh and it is considered the main cause behind the country’s high prevalence of impaired foetal growth. Our data are the first to be analysed from a currently running
pregnancy cohort (the PreSSMat study) in Matlab, Bangladesh, and our results show that among women in early pregnancy, underweight was less prevalent and
overweight was more prevalent than expected. Weight gain during pregnancy was inadequate for a majority of the women. Maternal factors significantly associated with inadequate gestational weight gain were older age and higher parity.
We believe that our findings are of interest within the field of public health nutrition since they are the first to identify the rapid nutrition transition among pregnant
women in rural Bangladesh. Since maternal nutrition is crucial for foetal development and later health, our results point at the need of surveillance of nutritional status for this population. Our data also present maternal factors possibly affecting nutritional status before and during pregnancy in a low-income country setting.
We certify that this is an original manuscript, which has not been published elsewhere and is not under consideration by another journal.
We hope to hear from you at your earliest convenience.
Yours sincerely, Fanny Hansson
PRESSMEDDELANDE
--- ÖVERVIKT ALLT VANLIGARE BLAND GRAVIDA I BANGLADESH Bangladesh, ett utav världens fattigaste länder, har länge brottats med utbredd undervikt men en ny studie från Örebro Universitet visar att övervikt nu är minst lika vanligt som undervikt bland gravida kvinnor i landet.
Både undervikt och övervikt under graviditeten påverkar fostrets tillväxt vilket i sin tur kan få konsekvenser för barnets hälsa senare i livet. Bland underviktiga mödrar är det vanligare med låg tillväxt hos fostret medan överviktiga mödrar oftare föder barn med för hög födelsevikt.
I Bangladesh och många andra länder i Sydasien har en utbredd fattigdomen lett till att undervikt varit vanligt bland gravida kvinnor, men siffor från en ny studie som publiceras i dagarna visar att detta är påväg att förändras. För cirka tretton år sedan var drygt en fjärdedel av gravida kvinnor på landsbygden i Bangladesh underviktiga men denna andel har nu sjunkit till knappt en femtedel. Parallellt med denna
minskning har dock andelen överviktiga ökat dramatiskt, från 6 till 17%.
En liknande utveckling har tidigare rapporterats från andra låg- och
medelinkomstländer som nu utöver hälsoproblem kopplade till utbredd fattigdom även måste tampas med en ökad förekomst av vällevnadssjukdomar som t.ex. diabetes typ 2. När det gäller just gravida, innebär både undervikt och övervikt en förhöjd risk för komplikationer under graviditet och förlossning samt senare sjukdom hos barnet.
Studien från Örebro Universitet är en del av ett större forskningsprojekt kring graviditet som genomförs av en lokal forskningsorganisation i Bangladesh.
