Early maternal age at first birth and elevated parity may have long-term consequences for the health of women as they age. Both are known risk factors for obstetrical complications with lifelong associated morbidities. They may also be related to diabetes and cardiovascular disease development.We examine the relationship between early maternal age at first birth, defined as ≤18 years of age, multiparity (>2 births), and poor physical performance  in community samples of women between 65 and 74 years of age from Canada, Albania, Colombia, and Brazil (N = 1040). Data were collected in 2012 to provide a baseline assessment for a longitudinal cohort called the International Mobility in Aging Study. We used logistic regression and general linear models to analyse the data.Early maternal age at first birth is significantly associated with diabetes, chronic lung disease, high blood pressure, and poor physical performance in women at older ages. Parity was not independently associated with chronic conditions and physical performance in older age. After adjustment for study site, age, education, childhood economic adversity and lifetime births, women who gave birth at a young age had 1.75 (95% CI: 1.17 – 2.64) the odds of poor SPPB compared to women who gave birth > 18 years of age. Adjustment for chronic diseases attenuated the association between early first birth and physical performance. Results were weaker in Colombia and Brazil, than Canada and Albania.This study provides evidence that adolescent childbirth may increase the risk of developing chronic diseases and physical limitations in older age. Results likely reflect both the biological and social consequences of early childbearing and if the observed relationship is causal, it reinforces the importance of providing contraception and sex education to young women, as the consequences of early pregnancy may be life-long. As populations age, physical decline, which includes loss of muscle strength, balance, and mobility, as well as decreased gait speed, constitutes an important public health concern. It is a major step in the disablement process and consequences of physical decline include diminished quality of life, increased healthcare expenditures, and death ,2. WorldA number of biological and social explanations are proposed to explain women’s relatively greater burden of physical decline and disability. On the one hand, it may arise from a higher cumulative burden of physiological dysregulation, especially in the postmenopausal period ,13, as wPregnancy fundamentally alters a woman’s physiology and increases metabolic demands on the body . When woWhile there is a growing body of evidence supporting a link between reproductive history and chronic disease, very little research has investigated a link between reproductive history and physical function in older age. Childbearing, especially in women with limited food supplies, can drain nutritional reserves ,23 that In this paper, we assess whether there is a link between reproductive history and physical function in older age. Specifically, we examine the associations between young maternal age at first birth and multi-parity on chronic diseases and poor physical function in older age in community-dwelling elderly from five research sites . We hypothesize that women who gave birth as teenagers and women who have had numerous children will have a greater prevalence of chronic diseases than women who gave birth older and had fewer children. We also hypothesize an independent association between early maternal age at first birth and elevated parity with poor physical function in older age. Finally, because women from the Latin American sites would have had less access to high quality obstetrical care during their childbearing years, we hypothesize that any relationship between early maternal age at first birth and parity with physical function will be more profound in Latin America than the Canadian and European sites.This research was conducted as part of a longitudinal study, called The International Mobility in Aging Study. The primary objective of IMIAS is to measure the magnitude of the sex/gender gap in mobility and to increase understanding of sex/gender differences in life-course exposures related to mobility. IMIAS is ongoing at five sites: Tirana (Albania), Natal (Brazil), Manizales (Colombia), Kingston  and Saint-Hyacinthe . These cities were chosen because each has a relatively homogenous elderly population in terms of life opportunities, religion, ethnic diversity and national origins. Across sites, they represent societies that vary considerably in gender equality. According to the United Nations 2012 Gender Inequality Index of 148 countries, Canada was 18th while Albania, Brazil, and Colombia were ranked 41st, 85th, and 88th, respectively . This diTirana, the capital of Albania, is a city of approximately 700,000 inhabitants. Albania is a post-communist republic and one of the poorest countries in Europe. During the 1960s, when most women in this cohort were giving birth, Albania experienced remarkable fertility decline, despite restricted access to birth control. Childbirth outside of marriage in Albania was exceedingly rare . Natal, This is a cross-sectional analysis of baseline data from IMIAS.The study is composed of community dwelling elderly people between 64 and 75 years of age. The sample was stratified by sex with an aim to recruit 200 men and 200 women from each site. The total sample size of women in the study is 1040.Baseline data were collected in 2012: from January to June in Manizales, Natal, and St Hyacinthe; from January to December in Kingston; and from September to December in Tirana. Follow-up data collection phases are planned for 2014 and 2016. In Tirana, Manizales and Natal, participants were recruited through neighbourhood primary care centers. At these sites, a random sample of elderly people registered at the health center was drawn and participants were approached directly by our interviewers to invite them to participate. Ethics’ committees at both Canadian Universities did not allow researchers to directly contact potential participants. Invitations to participate in the project were sent indirectly via family physicians. Potential participants received a letter from their family physician inviting them to contact our field coordinator for information about the study. Since Albania, Brazil and Canada have universal health care systems, more than 90% of the population aged 64 to 75 is registered at a health center or has a primary care physician. In Colombia, it is estimated that approximately 82% of individuals in this age group are registered in the public health system .Response rates were greater than 90% in Tirana and close to 100% in Natal and Manizales. In Kingston and St Hyacinthe, only 30% of people receiving a letter from their doctor contacted us. However, of those who telephoned to obtain more information about the study, 95% agreed to participate, resulting in overall response rate of 28%. At both Canadian research sites, responses rates were lower among men than women.Participants were excluded if they had 4 or more errors on the orientation scale of the Leganes Cognitive Test , which wGiven the principal objective of IMIAS, total sample size was calculated to estimate sex and site-specific prevalence, incidence, and recovery from mobility disability. Of relevance to the present study, we estimated the prevalence of mobility disability- a consequence of functional decline- to range between 16 and 27% in this age group. Thus, with 200 women at each site at baseline, we have the following level of precision for the prevalence of mobility disability: 27% ± 6%, n = 200. Prior to commencing IMIAS, sample size was also estimated to assess the sex-specific relationship between life-course disadvantage exposures, such as early maternal age at first birth, and chronic conditions. For a chronic condition like heart disease, we have 80% power to detect an odds ratio of 2, assuming a prevalence of heart disease of 10% and a prevalence of a life-course disadvantage of 20%.At all sites, study procedures were carried out at the participant’s home unless that person requested otherwise. In Manizales, physical performance was evaluated at the local hospital.http://www.imias.umontreal.ca). French, Portuguese and Spanish versions of the main scales were validated in two pilot studies conducted in Brazil, Colombia and Quebec [Interviewers at each site received the same standard training based on videotapes, protocol instructions and data entry forms. Assessments in Tirana were done by public health professionals and graduate students, in Natal by physiotherapists, in Manizales by local nurses, in Saint Hyacinthe by retired nurses and teachers, and in Kingston by retired professionals with at least a high school education. The principal investigators and the study coordinator trained all interviewers. The questionnaires, data collection documents and procedures manuals were available in the local languages: Albanian, Spanish, Portuguese, English and French. They are accessible at our web site . Sixty-four was the age at which a woman was eligible to participate in the study. Education was dichotomized as: 8 years of schooling or less and 9 or more years of education. As girls may drop out of school as a result of pregnancy, we chose to dichotomize education at an age at which most women would not become pregnant (13/14 years of age). In our sample, only eight women had children at 14 years of age or younger. Childhood economic adversity was measured with a scale varying from 0 to 3. A point was given for each of the following self-reported childhood circumstances: poverty, hunger, and parental unemployment. We did not adjust for adulthood measures of socio-economic status, such as income and occupation, because professional opportunities are affected by reproductive history and controlling for these attributes would lead to over-adjustment .Early maternal age at first birth and multiparity may be associated with chronic diseases that, in turn, may be associated with poor physical performance. Chronic diseases- osteoporosis, diabetes, chronic lung disease, high blood pressure, stroke, coronary heart disease, arthritis, and cancer- were self reported based on the question “Has a doctor or nurse ever told you that you have …”.Physical performance was assessed by the Short Physical Performance Battery (SPPB) ,38. The t-test and two-by-two tables were employed to describe exposure measures, covariates, and poor physical performance. Because chronic diseases were believed to be intermediate variables on the pathway between reproductive exposures and physical performance, we first used logistic regression to assess associations between exposure variables- age at first birth and parity- and reported chronic conditions, with adjustment for study site. Next, for the dichotomous SPPB outcome variable, we used three logistic regression models. In the first model, our independent variables were maternal age at first birth and the potential covariates: centred age variable, education, childhood economic adversity and study site. In our second model, we added parity as a possible intermediate variable and in the third model, we added chronic diseases as a possible pathway for the effects of age at first birth on physical function. Age at first birth and parity were not assessed simultaneously because parity may be a function of the age at first birth . An identical modeling strategy was used for the continuous SPPB outcome. Finally, using the continuous SPPB outcome, we assessed for multiplicative interaction between study site and age at first birth.Statistical analyses were conducted using STATA/SE 13. Student’s In the multivariate models with parity, we assessed different cut-off values for the variable. These included: 1) 0 births, 1–2 birth, 3 or more births; 2) 0 births, 1–2 births, 3–4 births, 5 or more births; 3) 0–4 births or 5 or more births.Figure Ethical approval for this project was obtained from the Research Centres of the University of Montreal Hospital Complex (CR-CHUM), the Albanian Institute of Public Health, and the research ethics boards of the Federal University of Rio Grande do Norte (Brazil), Queen’s University (Kingston) and University of Caldas (Columbia). All study participants provided written informed consent. In Brazil and Colombia, some participants could not read and write. The consent form was read to them, oral consent was obtained, and the participant placed a sign on the form to acknowledge agreement.Fertility history in Kingston and St. Hyacinthe was similar; few women gave birth at less than 18 years of age and most women had their first child at 24 or 25 years of age. In the Latin American countries, the average age of first birth was 21 or 22 and a third of women had their first child at 18 years of age or younger. In Albania, women had children a younger mean age than in Canada, but very few gave birth as adolescents. Parity was also markedly higher at the Latin American sites with larger variation in the number births by these women, when compared to women from Canada and Albania. The majority of women in Latin America gave birth 3 or more times , followed by Manizales 26%), Albania (40%) and Natal (44%). The mean age of women in the sample was essentially the same at each site- 69 years  of the population diagnosed with high blood pressure, compared to the Canadian sites. In contrast, these sites had much lower proportions diagnosed with cancer (11–15% less). In Tirana, compared to the Canadian sites, all chronic conditions were more prevalent, except for cancer and stroke. In Manizales, similar proportions of the population were diagnosed with most of the chronic conditions, compared to the Canadian sites. However, fewer reported having been diagnosed with arthritis and cancer and more reported high blood pressure. Compared to the Canadian sites, Natal had less reported arthritis, cancer, and chronic lung disease, but there was more osteoporosis and high blood pressure. Not one of the chronic diseases was similarly prevalent across all five sites . Because the majority of women who gave birth at 18 years of age or less had 3 or more children, we further adjusted for age at first birth. The odds ratio for diabetes was 1.34  and the odds ratio for high blood pressure was 1.39 . In both models, age at first birth was highly significant (p = 0.01).In the sensitivity analyses, we assessed whether different cut-off values for parity affected the observed associations. Compared to women who never gave birth, women who gave birth five or more times had 2.63 the odds of diabetes (p = 0.01), 2.10 the odds of chronic heart disease (p = 0.03), and 1.76 the odds of high blood pressure (p = 0.03). The magnitude of the association between parity and these chronic diseases was stronger than when we dichotomized the variable as three or more births versus two or fewer births. However, once adjustment was made for maternal age at first birth, the associations were no longer significant. Other cut-off values for parity, and modeling parity as a continuous variable, did not provide any additional information.In models 1 – 2 of Table In both models shown in Table There was effect interaction between maternal age at first birth and study site. Figure In this study, we demonstrated that early maternal age at first birth was associated with poor physical performance in these women at older age, as well as an association between early maternal age at first birth and a number of chronic conditions: diabetes, chronic lung disease, and high blood pressure. Giving birth 3 or more times was associated with high blood pressure and chronic lung disease, but the relationship was not maintained after adjument for early maternal age at first birth. Thus, parity is likely on the causal pathway between age at first birth and these chronic conditions. We further demonstrated that part of the association between early maternal age at first birth and poor physical performance in older age was mediated by diabetes, chronic lung disease and possibly stroke. In the models using the continuous SPPB outcome, age at first birth was independently associated with SPPB, even after adjustment for chronic conditions. Women who gave birth at 18 years of age or younger scored, on average, half a point less on the SPPB than women who gave birth at 19 years of age or older. A half point less on the SPPB scale meaningfully reduces functional mobility . FinallyUnlike parity ,22,41-44The effects of early maternal age at first birth on chronic diseases likely reflect both the biological and social consequences of bearing children as a teenager. Pregnancy and childbirth are marked by physiological adaptations that include insulin resistance, atherogenic dyslipidemia, fat accretion, and inflammation. Some of these manifestations may persist after giving birth . For exaHaving a child at an early age may arise from and give rise to social consequences that increase the risk of developing chronic diseases and mobility loss in older age. For example, women who give birth as adolescents may not complete their educations because of childcare duties. Data from this study supports such a hypothesis. At all sites, women who gave birth at 18 years of age or less had lower educational attainment than women who gave birth at an older age. Compared to women who gave birth as adolescents, women who gave birth as adults had, on average, 4.6 years more education in Sainte Hyacinthe, 3.0 years more education in Tirana, 2.9 years more education in Kingston, 1.1 years more education in Manizales, and 1.0 more year of education in Natal. With less education, women have fewer employment opportunities and are at greater risk of poverty. Low educational attainment is also consistently associated with functional limitations -56. As fIn this study, heterogeneity across study sites in the association between early maternal age at first birth and physical performance was observed. Contrary to our hypothesis, the relationship was strongest in Canada and Albania. This finding may be attributable to survival bias at the Latin American sites. Most women in our study would have had their first child between 1955 and 1975 when maternal mortality was high in rural Latin American, but much lower in Albania and Canada. Childbirth at an early age is a known risk factor for maternal death , and linThe unexpected results in Latin America may also reflect societal attitudes about teenage pregnancy. When women in this study would have started childbearing, teenage pregnancy was not unusual in Colombia and Brazil. In fact, it was and continues to be a way of increasing social class and visibility . It is aThere are a number of strengths to this study. IMIAS is comprised of community-based representative samples from 5 distinctive research sites in four countries, maximizing variability in life-course exposures. The sample size of 1040 women is large enough for most statistical procedures, allowing for relatively precise confidence intervals around estimates. Further, the SPPB is an objective outcome measure and has been extensively validated, including in Brazil and Quebec ,37,38. AThere are limitations to this study. As mentioned above, there may be differential survival across study sites with the highest mortality expected from the Latin American sites. In Canada, the response rate was low (30%) since recruitment had to be done through contacts with family physicians to satisfy Canadian Ethics Review Boards. We thus compared educational attainment in our study samples from Canada with 2006 Canadian census data. Participants from Kingston had higher educational attainment than the reference population surveyed in the 2006 census, whereas differences were small in Saint-Hyacinthe. Given the consistently inverse association between educational attainment, chronic diseases, and poor physical performance, we may have under-sampled the group for which the association between early maternal age at first birth and poor physical performance is the most important. In other words, we may have underestimated the association in Kingston (Canada). Finally, exposure and covariate measures were self-reported. Among those with lower levels of education, it is possible that reports of provider-diagnosed chronic diseases were misunderstood or miscommunicated. To reduce misclassification, we described chronic diseases using both the medical and lay terms for each condition. We also assessed whether the associations between maternal age at first birth and high blood pressure, diabetes, and chronic lung disease were maintained in those with greater than 9 years of education compared to those with 8 or less years of education. Even when stratified by education, early maternal age at first birth was significantly association with each of these chronic diseases in both groups.This study provides evidence that women who give birth at a young age may be at greater risk of developing chronic diseases and physical limitations in older age. In our international study this was particularly true for women from Canada and Albania. These findings could improve the targeting of at-risk women by health professionals. If this relationship is causal, it reinforces the importance of providing contraception and sex education to young women, as some negative consequences of early pregnancy may be life-long.IMIAS: International Mobility in Aging Study; SPPB: Short Physical Performance Battery.The authors declare that they have no competing interests.MVZ and BA are principal investigators for the IMIAS study. CP and MVZ conceived of the present study and analysis plan. CP and ACPAS analyzed the data with feedback from all authors. CP also wrote the manuscript. All authors contributed to the interpretation of the data and to critical review of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/14/293/prepub


The foetal growth standards for Indian children which are available today suffer due to methodological problems. These are, for example, not adhering to the WHO recommendation to base gestational age on the number of completed weeks and secondly, not excluding mothers with risk factors. This study has addressed both the above issues and in addition provides birthweight reference ranges with regard to sex of the baby and maternal parity.nd, 3rd and 4th quadrants. In each successive year different months were included in each quadrant. Only those mothers aged 20–39 years and delivered between 24 to 42 weeks gestational age were considered. Those mothers with obstetric risk factors were excluded. The reference standards were fitted using the Generalized Additive Models for Location Scale and Shape (GAMLSS) method for Box – Cox t distribution with cubic spline smoothing.Data from the labour room register from 1996 to 2010 was obtained. A rotational sampling scheme was used i.e. the 12 months of the year were divided into 4 quadrants. All deliveries in January were considered to represent the first quadrant. Similarly all deliveries in April, July and October were considered to represent 2There were 41,055 deliveries considered. When women with risk factors were excluded 19,501 deliveries could be included in the final analysis. The male babies of term firstborn were found to be 45 g heavier than female babies. The mean birthweights were 2934 g and 2889.5 g respectively. Similarly, among the preterm babies, the first born male babies weighed 152 g more than the female babies. The mean birthweights were 1996 g and 1844 g respectively.In the case of later born babies, the term male babies weighed 116grams more than the females. The mean birth weights were 3085 grams and 2969 grams respectively. When considering later born preterm babies, the males outweighed the female babies by 111 grams. The mean birthweights were 2089 grams and 1978 grams respectively. There was a substantial agreement range from k=.883, (p<.01) to k=.943, (p<.01) between adjusted and unadjusted percentile classification for the subgroups of male and female babies and first born and later born ones.Birth weight charts were adjusted for maternal height using regression methods. The birth weight charts for the first born and later born babies were regrouped into 4 categories, including male and female sexes of the babies. Reference ranges were acquired both for term and preterm babies.With economic reforms, one expects improvement in birthweights. The mean (sd) birthweights of the year 1996 was 2846 (562) as compared to year 2010 (15 years later) which was 2907 (571). There was only a difference of 61 grams in the mean birthweights over one and a half decade.New standards are presented from a large number of deliveries over 15 years, customised to the maternal height, from a south Indian tertiary hospital. Reference ranges are made available separately for first born or later born babies, for male and female sexes and for term and preterm babies. Investigators and researchers have used the reference standards which were developed globally due to lack of availability of population or country specific standards. A decline in the use of these standards has been reported  as regioThe Christian Medical College and Hospital is a referral hospital in South India, which caters to 47,110 outpatients and 15,662 inpatients per year. The department of Obstetrics and Gynaecology on an average delivered 20 babies per day in 1996 and 40 babies per day in 2010. The data was obtained from the Labour room register which was maintained by the nursing personnel and supervised by the Head of Obstetrics department. This contains all the information about women who delivered in this institution. Permission was obtained from all the Obstetric departmental Unit Heads. This study was approved by the ethics committee of [IRB Min. No. 7109 dated 10.03.2010] Christian Medical College.The twelve months of the year were divided in to 4 quadrants. In the year 1996, all deliveries which took place in January were considered to represent the first quadrant. In the second quadrant, all deliveries in the month of April were considered. All deliveries in the months of July and October were considered to represent the deliveries in the third and fourth quadrants. In the second year of the study (1997) all deliveries which took place in February, May, August and November were taken to represent the first, second, third and fourth quarter of the year. In the third year of study (1998), all deliveries which took place in March, June, September and December were taken to represent the first, second, third and fourth quarter of the year. The above cycle was repeated for the next 3 years and continued until the year 2010 [Mothers aged 20 to 39 years and deliveries of gestational age between 24 weeks to 42 weeks were considered. The mothers, who had hypertensive disorders, gestational diabetes, diabetes mellitus, heart disease, and twin pregnancies, were excluded from the analyses. The gestational age specific birth weights which were above +3SD or below –3SD values were excluded from the analyses. The maternal height was regrouped into tertiles with categories as < 151 cm, 151 – 158 cm and > 158 cm based on the maternal height distribution of the mothers. Linear regression was employed to get the estimate of birthweight in relation to the maternal height. It showed a significant increase in birthweight of 135 grams. These 135 grams were added to the birthweight for shorter women and for taller women 135 grams were subtracted. Women with normal height (151–158 cm) did not have any adjustments in birthweight. These corrections yielded us the birthweights adjusted for maternal height.The modified birthweights were adjusted with gestational ages to produce the birthweight centiles for each of the four groups in the term as well as the preterm groups. .rd, 10th, 25th, 50th, 75th, 90th and 97th percentiles and mean and standard deviations were computed using R software. These centiles for birthweight adjusted for maternal height were done separately for firstborn males, females and later born males and females.The birth weights adjusted for maternal height for babies born from gestational age 24 weeks to 30 weeks had skewed distribution to the right side. However, as the number of deliveries increased in the subsequent gestational weeks, the birth weight distribution followed normal distribution. In the modelling we have assumed Box-Cox t distribution in order to get over this skewness. Cubic Spline smoothing has been applied using the Generalized Additive Models for Location Scale and Shape (GAMLSS) method using R software (Stasinopoulos and Rigby 2007) . The GAMData from the labour room register was entered using EPIINFO software. Completed weeks gestational age was considered for nomograms. The best estimate of gestation based on reliable menstrual history, early antenatal clinical examination and sonographic fetal biometry was used. Birth weights were measured to the nearest 50 g on a Braun electronic weighing scale within one hour of birth.In total, there were 41,055 deliveries considered. Of these, complete data were available for 25,090 deliveries. When women with risk factors were excluded , 19,501 deliveries could be included for analyses. Most of the women were in the age group 25 – 29 years 41.7% (8133). Close to this is the 20 to 24 years age group which constituted 40.1% (7817). Mothers more than 30 years constituted only 18.2% (3551).The maximum number of mothers who delivered belonged to the Hindu religion, and formed 82% (15933). Muslims formed 11.1% (2164), and Christians constituted 6.9% (1343).Most (91.8%) of the mothers were housewives. Professionals were a minority, 4.3% (844), and mothers trained for skilled work were only 1.4% (241). When considering education of the mothers, 28.6% (4961) were graduates or more highly educated. A small percent was illiterate 5.1% (895). Those who had primary education formed 6.2% (1085) and those with secondary education 13.6% (2367). Those who had high school and higher secondary education constituted 8099 (46.5%) of the mothers.When sub grouped into 3, based on the heights of the mothers, 24%, 48% and 28% of the mothers fell into the 3 groups ,whose height was <151 cm; 151-158 cm and >158 cm respectively.There were 2379 firstborn and 17,092 later born. There were 1236 (6.3%) male babies in the first born group and the first born females were 1143 (5.9%) in number. Among the later born babies, male babies were 8739 (44.9%) in number and females 8353 (42.9%).The male babies of term first born mothers were found to be 45 grams heavier than female babies. The mean birthweights were 2934 grams and 2889.5 grams respectively. Similarly, among the preterms, male babies weighed 152 grams more than the female babies. The mean birthweights were 1996 grams and 1844 grams respectively.In the case of later born babies, term male babies weighed 116 grams more than the females. The mean birth weights were 3085 grams and 2969 grams respectively. When considering preterm babies among the later born, the males outweighed the female babies by 111 grams. The mean birthweights were 2089 grams and 1978 grams respectively.rd, 10th, 25th, 50th, 75th, 90th, 97th percentile, mean and SD birth weights for male and female babies of primigravidae. Figures Table rd, 10th, 25th, 50th, 75th, 90th, 97th percentile, mean and SD birth weights for male and female babies of later born babies. Figures Table Table th percentile category was misclassified as 10–90th percentile category. Nearly 2% of the babies from 10–90th percentile category was misclassified as <10th and >90th percentile. Nearly 5% of the babies >90th percentile category was misclassified as 10–90th percentile. When considering female babies, there is a significant substantial agreement between the adjusted and unadjusted classifications . The misclassifications to the next category percentiles rates were the same as in the male babies.When considering first born male babies, there is significant agreement between adjusted and unadjusted percentile classification . However, 7% of the male babies in <10th percentile category was misclassified as 10–90th percentile category and 1.5% from 10–90th percentile category was misclassified as <10th and >90th percentile category. 2.8% of the >90th percentile category was misclassified as 10–90th percentile category. Similarly, among the later born female babies, there is a significant agreement between adjusted and unadjusted percentile classification . The misclassifications to the next category percentiles rates were nearly the same as among the male babies.There is a significant agreement between adjusted and unadjusted percentile classification  in later born male babies. However, 5% of the male babies in < 10The mean (sd) of birthweights of the year 1996 was 2846 g (562) as compared to year 2010 (15 years later) which was 2907 (571), there was only a difference of 61 grams in the mean birthweights over one and half decades.This is the biggest study ever from India, dealing with nearly 20,000 deliveries, including normal mothers with no antenatal risk factors from the same hospital covering 15 years. In addition to this, a major advantage is the reliance on early ultrasound-based estimates of gestational ages and appropriate statistical modelling using Box-Cox t distribution to get over the skewness of birth weight distribution and cubic spline smoothing. Therefore, we have established standards for first born and later born mothers for male and female babies separately. Some of the earlier standards have not done these adjustments  and someth percentile was misclassified as 10–90th percentile and nearly each 2% of 10–90th category was misclassified as <10th or >90th percentile category. A similar trend was obtained in female babies of first born and male and female babies of later born babies. Though there is very good agreement in general the highest misclassification rate was nearly 7.5%. Therefore the use of unadjusted percentiles may lead to unnecessary intervention and anxiety for the parents of babies whose weight fall in the range of lower and upper centiles according to adjusted centiles.This study also compared the unadjusted centiles to adjusted and smoothed centiles. With male babies of first born, 7% of the adjusted <10The limitation of the study is that the observations are cross-sectional. That is, birth weights of different babies were observed at different gestational ages at delivery. Ideally this has to be longitudinal in nature, that is, the same number of pregnancies and their birth weights have to be observed. Anthropometric measurements during gestation are feasible only using ultra-sound. However, the ultra-sound measurements have not been proved to be valid and reliable ,18. TempWith economic reforms, one expects improvement in birthweights. The mean (sd) of birthweights of the year 1996 was 2846 g (562) as compared to year 2010 (15 years later) which was 2907 (571), there was a difference of only 61 grams in the mean birthweights over one and half decades.New standards for birth weights of Indian newborns, both term and preterm have been established. In addition, birth weight standards based on the sex of the baby and maternal parity have also been brought out. These new standards will allow interventions to be based on Indian standards.Written informed consent was obtained from the patient for publication of this report.The authors declare that they have no competing interests.All authors  contributed to the design of the study and interpretation of data.  performed the data analysis.  drafted the manuscript. All authors  critically revised the manuscript and have approved the final version.The dataset will not be available for publishing online since further research has been planned.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2393/13/38/prepub


Birth defects and inborn errors of metabolism are related to variable poor perinatal and neonatal outcomes. Our aim was to explore the pattern and prevalence of birth defects and metabolic birth errors in Al-Ahsa Governorate in the Eastern Province of Saudi Arabia.This retrospective case control study was done from April 2006 to 2009. Children with any birth defect or metabolic errors of metabolism at birth or in the neonatology section were our sample for study. Control group was randomly selected from the cases with normal live births. Blood tests were performed for children suspected to suffer from genetic blood disorders. The principal BD as per the International Classification of Diseases-10 (ICD-10) code was also noted.Out of 38001 live births, birth defects were found in 1.14% and errors of metabolism were detected in 0.17%. The most common birth defects were craniofacial malformations. The 3-methylcrotonyl-CoA carboxylase deficiency was the most common inborn errors of metabolism. Consanguinity, rural residence and prematurity were associated with significant rise in birth defects. On the other hand, consanguinity and low birth weight were associated with significant rise in metabolic errors.First cousins consanguinity represented the most significant risk factor for birth defects and inborn errors of metabolism. High degree of inbreeding, consanguinity may exacerbate underlying recessive genetic risk factors. Birth defects are a major cause of perinatal and neonatal death . WorldwiEpidemiologic surveys of birth defects in various part of the world and among different ethnic groups with widely varying marital habits, socioeconomic status and environment not only help in understanding the frequency of malformations in specific areas but also contribute to the general knowledge about the predisposing factors and different patterns of birth defects. There may be regional variations in the rate and pattern of birth defects or these could vary over time . Birth dThe prevalence of hereditary blood disease has the highest incidence in Eastern province of KSA. Sickle cell disease is present throughout Saudi Arabia; particularly common in the eastern and southern provinces: Qatif (eastern region) 17.0 %, Gizan (southern region), 10.3%, Ula (Northern region) 8.1 % and Mecca (western region) 2.5 % .A cross-sectional study was done using multistage random probability sampling of Saudi population taken from the 13 regions of the Kingdom. The overall prevalence of consanguinity in the Kingdom of Saudi Arabia is high; 56% with the first-degree cousin 33.6%) being more common than all other relations (22.4%). The overall prevalence was significantly more common in rural (59.5%) than in urban settlements (54.7%) . It was .6% beingIn the current study, univariate analysis proved that rural residence was associated with significant rise in BDs; ORs (CI) 1.29 (1.03-1.61). The rural conditions may encourage more consanguineous marriage or may increase the exposure to waste of the different insecticides and pesticides. Migration to urban areas and the growth of the nuclear family has also been postulated to dilute the role of consanguinity and that could be the reason for the observed association of consanguinity with BD in our study .The current study has some limitations which should be considered before making extrapolation. It was a retrospective with multiple areas of uncontrolled bias either in enrollment or data finding. We didn’t include abortions and stillbirths, which may decrease the magnitude of the problem limiting the number of diagnosed cases. Absence of genetic maps limited our ability to trace all genetic errors in certain families. Finally, the different patterns and percentages of consanguinity decrease the extent of national generalization of results, but it does add a piece of information to what is currently present.First cousins consanguinity represented the most significant risk factor for birth defects and inborn errors of metabolism. High degree of inbreeding, consanguinity may exacerbate underlying recessive genetic risk factors. We shouldn’t neglect the positive aspects assumed to be in these marriages. They are claimed to be associated with more socially stable and economically beneficial, family fortune, with preserved extended family tribe. Putting all cons and pros together, should help in the awareness about early detection and lines of management of consanguinity related disorders.The authors read the manuscript and approved it. No conflict of interest was present. No source of funding.The authors jointly conceived and designed this study, collected data, analyzed, and interpreted the data. They also took part in drafting the article and revising it critically for important intellectual content; and finally approved this version to be published. AWH: Literature search, review of theresults, data interpretation and manuscript critical review. BMH: conception and design, literature search-data analysis and interpretation, manuscript editing and final review. MS: Design, literature search, manuscript drafting, and review. HI: Data acquisition and manuscript reviewThe authors would like to thank the MCH filing unit for nice documentation and help. All thanks are to the Department of Pediatrics, Neonatology section for their help and efforts in serving the local community and allowing collecting the data. Also, thanks to the efforts of the students, Talal Al Ma khlafy, Tarek Al Yahia, we could finalize our data collection accurately.


More than 30% of all pregnancies in the UK require some form of assistance at delivery, with one of the more severe forms of assistance being an emergency Caesarean section (ECS). Previously it has been shown that the likelihood of a delivery via ECS is positively associated with the birth weight and size of the newborn and negatively with maternal height. Paternal height affects skeletal growth and mass of the fetus, and thus might also affect pregnancy outcomes. We hypothesized that the effect of newborn birth weight on the risk of ECS would decrease with increasing maternal height. Similarly, we predicted that there would be an increase in ECS risk as a function of paternal height, but that this effect would be relative to maternal height . We used data from the Millennium Cohort Study: a large-scale survey  with data on babies born and their parents from the United Kingdom surveyed 9 to 12-months after birth. We found that in primiparous women, both maternal height and parental height differences interacted with birth weight and predicted the likelihood of an ECS. When carrying a heavy newborn, the risk of ECS was more than doubled for short women (46.3%) compared to tall women (21.7%), in agreement with earlier findings. For women of average height carrying a heavy newborn while having a relatively short compared to tall partner reduced the risk by 6.7%. In conclusion, the size of the baby, the height of the mother and parental height differences affect the likelihood of an ECS in primiparous women. Obstructed labor, a failure to progress due to a mismatch between fetal size and the mother's pelvis Short maternal stature is associated with adverse pregnancy outcomes, such as stillbirths Fetus size is also a well-known risk factor for obstructed labor. Heavier and larger newborns increase the likelihood of difficult deliveries  to test this hypothesis. In line with previous findings The Millennium Cohort Study (MCS) is a survey that gathered information from the parents of 18,819 babies born in the year 2000/2001 in the United Kingdom. Interviews were carried out when the babies were around 9–12 months. Detailed information on the pregnancy and birth was collected as well as anthropometric , social and economic information  from the mother and where possible from the father. Self-reported measures of height have been shown to be very reliable in women of reproductive age For the analyses presented here, we only included White parents for which height data were available who had their first, singleton child (of which the birth weight was available), leaving 4,365 cases. Only White parents were included in the analyses as ethnicity relates to maternal pelvic size, which might influence the risk of ECS We performed logistic regressions on our key dependent variable; whether the delivery was normal  or by ECS, leaving in total 3,165 cases. We excluded Caesarean delivery on request (N = 266), assisted breech delivery (N = 9), assisted forceps (N = 376), assisted vacuum extraction (N = 503), water births (N = 11) and other problems without specification (N = 5). However, including these cases  did not change our key results. To examine the effects of maternal and paternal height on birth weight, we performed a linear regression. All analyses were performed in SPSS 17.0.Occurrence of the various pregnancy outcomes in the Millennium cohort was comparable to national statistics. In our entire sample the occurrence of a normal vaginal delivery and ECS were 68.5% and 12.2% respectively, whereas the national statistics for England for 2000 to 2001 are 66.6% and 12.7% respectively Logistic regression revealed a quadratic effect of birth weight on the likelihood of having an ECS: both low and high birth weight newborns had an increased risk for ECS compared to average weight newborns . The lowControlling for birth weight, maternal height had a negative effect on the occurrence of ECS. Shorter women were more likely to have had ECS compared to taller women, and this was a decelerating pattern as indicated by a significant quadratic effect of height . MaternaHaving established that effects of previously identified risk factors  on ECS risk are present in the Millennium Cohort Study, we extended the analyses to examine the effects of parental height differences  on ECS risk. Logistic regression revealed that, when controlling for maternal height, birth weight and their interactions, there was no main effect of PHD on ECS risk . PHD didIn addition to the interaction of PHD with maternal height, PHD also interacted with birth weight . With inHaving a relatively tall compared to short partner increased the risk for ECS in average height women when carrying a heavy (from 25.9% to 32.6%) or average weighing newborn  to obtain clinical relevant estimates of the effects of maternal height and parental height differences. In line with the results above, logistic regressions revealed a significant squared effect of maternal height . A womanSimilarly, the interaction between maternal height and parental height differences (PHD) remained significant when excluding birth weight from the analyses . A womanIn this study, we have shown that the size of the newborn, the height of the mother and parental height differences all predict the risk of an emergency Caesarean section in primiparous women. We replicated the finding that both lower and higher birth weight newborns increase the risk of ECS Furthermore, to our best knowledge, we documented for the first time that the height of the father, specifically parental height differences, also affected the occurrence of ECS. The effect of the parental height differences on ECS was, however, dependent on the height of the mother and the birth weight of the newborn. Women with tall compared to short partners relative to their own height, had an increased ECS risk when carrying an average weight and heavy newborn, but not when carrying a light weight newborn, and this effect was most pronounced in average height and tall women. For shorter women, the overall ECS risk was highest, and parental height differences had little additional influence on ECS risk. Average height and tall women giving birth to a heavy newborn were at higher risk when their partners were relatively tall (respectively 32.6% and 25.0%) compared to short (respectively 25.9% and 19.4%). As the structural size of the baby has been shown to be more important in predicting problems at birth than birth weight The finding that differences in height between father and mother influence pregnancy outcomes partly explains the increased risk of assisted deliveries for shorter women. Shorter women have partners who are on average much taller than themselves and with increasing female height, the difference in height between partners decreases strongly. Thus, the higher risk for adverse pregnancy outcomes for shorter women is partly due to the fact that they are more likely to have a partner much taller than themselves.The finding that parental height differences predict the need for ECS is also consistent with a study investigating cross-national variation in height differences between the sexes A potential limitation of our study is the nature of the sample, in particular the oversampling of individuals from deprived areas. However, controlling for socio-economic status with several indicators  / National Statistics Socio-economic Classifications (NS-SEC)) did not change our results, which suggests that the effects of maternal and parental height differences on the risk of ECS are independent of socioeconomic status. Another limitation is that the data are self-reported, through interviews approximately 9 months after birth. However, national health statistics regarding rates of assisted deliveries for England in 2000–2001 are comparable to the rates in our sample. In addition, it seems unlikely that there is a systematic error in reporting problems at birth associated with height: there is little reason to assume that women of a certain height or women with a partner of a certain height would be more likely to over- or underreport complications such as an ECS.The incidence of ECS may be an imperfect index of obstructed labor, as a physician bias related to maternal height might have occurred From a functional perspective, documented preferences for partner height among men and women e.g.  are consFigure S1Model predictions for the effect of maternal height on the risk (%) of an emergency Caesarean section for mothers carrying low (mean − s.d.), average (mean) and high (mean + s.d.) birth weight newborns.(TIF)Click here for additional data file.Figure S2Model predictions for the effect of parental height differences on the risk (%) of an emergency Caesarean section for short (mean− s.d.), average (mean) and tall (mean + s.d.) mothers carrying an average birth weight newborn.(TIF)Click here for additional data file.Figure S3Model predictions for the effect of parental height differences on the risk (%) of an emergency Caesarean section for average height mothers carrying low (mean − s.d.), average (mean) and high (mean + s.d.) birth weight newborns.(TIF)Click here for additional data file.Table S1Characteristics (mean ± standard deviation or %) of the sample used for our analyses.(DOC)Click here for additional data file.Table S2Model predictions for the risk (%) of an emergency Caesarean section for low (mean − s.d.), average (mean) and high (mean + s.d.) birth weight newborns having (a) short (mean − s.d.), average height (mean), and tall (mean + s.d.) mothers and (b) small (mean − s.d.), average (mean), and large (mean + s.d.) parental height differences for short, average height (c) and tall mothers (d).(DOC)Click here for additional data file.Table S32, parental height differences (PHD), birth weight, their interactions, and control variables on the probability of an emergency Caesarean section.Logistic regression parameter estimates (± s.e.) of the effects of maternal height, height(DOC)Click here for additional data file.Table S42, birth weight (kg), birth weight2, parental height differences (cm) and their interactions, on the probability of an emergency Caesarean section when light birth weight newborns (<2.5 kg) are excluded.Logistic regression parameter estimates (± s.e.) of the effects of maternal height (cm), height(DOC)Click here for additional data file.Table S5Model predictions for the risk (%) of an emergency Caesarean section for short, average height, and tall mothers with small, average and large parental height differences (PHD).(DOC)Click here for additional data file.


Background: The built environment, a key component of environmental health, may be an important contributor to health disparities, particularly for reproductive health outcomes.Objective: In this study we investigated the relationship between seven indices of residential built environment quality and adverse reproductive outcomes for the City of Durham, North Carolina (USA).Methods: We surveyed approximately 17,000 residential tax parcels in central Durham, assessing > 50 individual variables on each. These data, collected using direct observation, were combined with tax assessor, public safety, and U.S. Census data to construct seven indices representing important domains of the residential built environment: housing damage, property disorder, security measures, tenure (owner or renter occupied), vacancy, crime count, and nuisance count. Fixed-slope random-intercept multilevel models estimated the association between the residential built environment and five adverse birth outcomes. Models were adjusted for maternal characteristics and clustered at the primary adjacency community unit, defined as the index block, plus all adjacent blocks that share any portion of a line segment (block boundary) or vertex.Results: Five built environment indices  were associated with each of the five outcomes in the unadjusted context: preterm birth, small for gestational age (SGA), low birth weight (LBW), continuous birth weight, and birth weight percentile for gestational age . However, some estimates were attenuated after adjustment. In models adjusted for individual-level covariates, housing damage remained statistically significantly associated with SGA, birth weight, and BWPGA.Conclusion: This work suggests a real and meaningful relationship between the quality of the residential built environment and birth outcomes, which we argue are a good measure of general community health. A relatively new area of attention in environmental public health is the impact of the built environment on health outcomes. In this article, we evaluated the quality of the built environment in the City of Durham, North Carolina (USA), and link neighborhood attributes to pregnancy outcomes in the same areas. We focus on pregnancy outcomes because poor birth outcomes are leading causes of neonatal mortality, as well as short- and long-term morbidity , and havNeighborhood sociodemographic conditions have long been associated with adverse reproductive outcomes. Modest, consistent associations have been noted for area-level deprivation and preterm birth (PTB) , low birLittle prior work has explored built environment features and reproductive outcomes. Neighborhood characteristics may affect birth weight through effects on maternal behaviors, such as inappropriate weight gain . VinikooIn this article, we describe the application of an innovative and user-friendly technology for documenting multiple features that shape the built environment. We surveyed approximately 17,000 residential tax parcels in central Durham on each of 50 individual variables during the summer of 2008. These data, collected from direct observation, were combined with tax assessor, public safety, and U.S. Census data to construct indices measuring different built environment domains. Potential associations between these indices and birth outcomes were assessed using multivariable regression analysis.Study area. The area covered by the Community Assessment Project (CAP) comprises 29 Durham neighborhoods . Tenure  was abstracted for parcels in the CAP study area  by comparing the geographic address of the parcel to the owner’s address with an algorithm that allowed for minor errors in data entry and spelling. Addresses that matched were coded as owner-occupied residences; those that did not match were coded as renter occupied.Built environment data. The built environment data were collected by trained field staff from the Children’s Environmental Health Initiative at Duke University . Before data collection, a six-member field team attended sessions covering fundamental concepts of geographic information systems, use of the software package ArcGIS , and use of handheld Global Positioning System (GPS) units. During training, the team participated in trial assessments in predetermined areas to ensure variable coding, high interrater reliability, and GPS-unit competence.Data collection occurred on foot, for approximately 10 weeks, between 0700 and 1330 hours, from late May to early August 2008. Individual tax parcels were assessed based on visibility from the public right-of-way.http://dx.doi.org/10.1289/ehp.1103578).To construct the data collection instrument, Children’s Environmental Health Initiative investigators identified observable variables that represented community concerns, based on direct conversations with community leaders, and supplemented the variable list with those represented in the literature . Each paCrime data. We acquired crime data from the Crime Analysis Lab of the Durham Police Department. Data include the charge description and physical address of all reported crime incidents for 2006–2007. These data were geocoded and aggregated to the census block level. Each block was assigned a count for each crime type that occurred within that block: property, theft, vehicle, vice, violent, and total.Vital records data. The North Carolina Detailed Birth Record databases for Durham County residents were obtained for the years 2004–2008. Maternal addresses were parcel geocoded to the 2008 Durham County Tax Assessor database , with a geocoding match rate of 96%. Birth records were restricted to singleton, nonanomalous births occurring to women 15–44 years of age who self-identified as non-Hispanic white, non-Hispanic black, or Hispanic. Births were restricted to first through fourth births and to those occurring between 28 and 42 weeks’ gestation. Of the 16,783 live births that occurred to Durham County residents during this time period, 4,279 occurred to women who lived in the CAP study area and represent the analysis data set.Community definition. Because block-level data do not necessarily represent the most salient geography for effects on health outcomes, we constructed a new neighborhood unit, the primary adjacency community (PAC), to approximate each woman’s proximate community. A PAC includes the index block plus all adjacent blocks that share any portion of a line segment (block boundary) or vertex  each domain is unique and does not contain variables that overlap with another domain, and b) the specificity of the domains will help disentangle features of the built environment most closely associated with health.To summarize the data in a meaningful way, we grouped the built environment variables into five domains: housing damage, property disorder, nuisances (in public spaces only), security measures, and vacancy. We examined the variables for shared features of the built environment, determined whether they contributed to the same latent construct, and grouped them into domains. Because this is the first tool to use such an exhaustive list of variables to characterize the built environment, little prior research aided in constructing the domains. However, we note that The CAP directly-observed parcel domains were housing damage (12 variables), property disorder (11 variables), security measures (6 variables), vacancy (3 variables), and nuisances (25 variables) . Parcel-The block-level proportions were standardized  and summed at the PAC level to derive the PAC-level proportion of each variable. Proportions for each of the variables contained within a domain were added together and divided by the number of blocks contributing to that PAC to generate PAC-level domain-specific indices. For instance, the PAC-level security measures index = (standardized block-level proportion of security bars) + (standardized block-level proportion of barbed wire) + (standardized block-level no trespassing signs) + (standardized block-level beware of dog signs) + (standardized block-level security sign) + (standardized block-level fencing).For each index, the more instances of an attribute, the higher its value . For tenure, higher index values represent more rental properties. Principal components analysis indicated that each variable weight was similar, so a simple summation of each variable produced comparable—and more easily interpretable—results.Outcome variable construction. To be comparable with prior work on environmental contributors to birth outcomes  of the categorical variables and means ± SDs of the continuous variables were calculated on the merged CAP–birth record data. Cronbach’s α was used to assess the reliability of the standardized indices. Both Pearson and Spearman correlation estimates were similar; therefore, we report the Pearson correlations among the indices. Crude and adjusted fixed-slope random-intercept multilevel models were estimated to predict the association between birth outcomes and PAC-level indices, adjusted for maternal covariates. Multilevel logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the three dichotomous outcomes , and β-coefficients (and 95% CIs) from linear regression models are reported for birth weight and BWPGA. The indices were entered singly (one index at a time) in their continuous form, and the statistical models were clustered at the block level; we used p-value < 0.05 for statistical significance. All analyses were conducted in Stata .PAC descriptions. The mean ± SD proportion of each variable comprising each index at both the block and PAC levels are listed in Index correlations. Correlations between the PAC-level indices were low (0.1–0.3) or moderate (0.4–0.6) (r = 0.6), and the lowest correlation was between security measures and nuisances (–0.002), suggesting that each of the indices are capturing distinct latent constructs.0.4–0.6) . The higAssociations between PAC indices and birth outcomes. More than 40% of the women who resided in the CAP study area were black non-Hispanic, and nearly 40% were Hispanic. More than half the women were between 20 and 29 years of age at delivery. Of those who were ≥ 18 years of age, > 48% had less than a high school education. For most of the women, this was not their first pregnancy, and most were not married. Summary statistics on the women included in this analysis are presented in Residence in a PAC characterized by high amounts of housing damage and property disorder and more rental housing, vacant housing, and nuisances were associated with increased odds of PTB in unadjusted models . After aSimilar to the results for PTB, residence in a PAC with higher index values of housing damage, property disorder, tenure status, vacancy status, and nuisances was associated with increased odds of SGA in the unadjusted models . After aFor the LBW outcome, residence in a PAC with higher index values of housing damage, property disorder, tenure status, vacancy status, and nuisances was associated with increased odds of LBW, but these estimates were close to the null in the adjusted models . No assoWomen who live in PACs with more housing damage delivered infants of lower average birth weights and BWPGA, in both unadjusted and adjusted models . Birth wIncreasing attention has been paid to the potential role of the built environment in shaping health outcomes and determining health disparities. We found that five of the built environment indices  were associated with each of our five outcomes  before adjustment, but some of the estimates were attenuated after adjustment for maternal characteristics. After adjustment, housing damage remained statistically significantly associated with SGA, birth weight, and BWPGA. Thus, in this exploratory work, we found specific, measurable features of the built environment to be consistently associated with increased risk of adverse birth outcomes in unadjusted models and housing damage to be associated with SGA, birth weight, and BWPGA after confounder adjustment.The built environment is multidimensional, which makes it difficult to characterize any given area as having a “good” or “bad” built environment. In this article, we describe a geographically based approach to efficiently inventory the built environment at a highly resolved geographic scale, as well as methods for combining built environment data into seven different domains. These domains represent latent community health status and are conceptually and empirically distinct from each other. Housing damage and property disorder both capture the physical state of a property but focus on separate features. Security measures also describes a parcel but describe measures taken by residents or land owners to delineate property boundaries and protect ownership. Tenure and vacancy describe who, if anyone, is occupying a parcel, and crime captures the quantity and type of crime occurring within a resident’s community. Nuisances capture the detritus that results from human activity and reflects both treatment and monitoring of the local environment.Despite limited research assessing the association between the built environment and health outcomes, our findings are consistent with prior work. Both Although novel, this work is not without limitations. Birth records have been criticized for data quality limitations, but we limited our analyses to data elements with demonstrated reliability . AdditioOne important strength of this work is our unique, thorough, and easily replicable data collection methodology. By collecting these directly-observed data using a geospatial approach, we were able to audit a large number of tax parcels in a relatively short amount of time and with modest resources. Further, we collected data on geographically contiguous communities, not just a sample of streets, resulting in complete exposure ascertainment. We extend prior built environment work by breaking physical incivilities into its constituent parts  and adding additional indices for consideration. Further, our exposure assessment was independent of the outcome.Despite its limitations, this work suggests a robust relationship between the quality of the built environment and birth outcomes, which we argue is a good measure of general community health. Expanding the scope of environmental health research beyond traditional measures of pollutant exposure to include the built environment is critical to more fully understanding environmental etiologies of human disease.(193 KB) PDFClick here for additional data file.


In an analysis of four datasets from East Africa, Tanya Marchant and colleagues investigate the neonatal mortality risk associated with preterm birth and how this changes with weight for gestational age. Low birth weight and prematurity are amongst the strongest predictors of neonatal death. However, the extent to which they act independently is poorly understood. Our objective was to estimate the neonatal mortality risk associated with preterm birth when stratified by weight for gestational age in the high mortality setting of East Africa.Members and collaborators of the Malaria and the MARCH Centers, at the London School of Hygiene & Tropical Medicine, were contacted and protocols reviewed for East African studies that measured (1) birth weight, (2) gestational age at birth using antenatal ultrasound or neonatal assessment, and (3) neonatal mortality. Ten datasets were identified and four met the inclusion criteria. The four datasets  contained 5,727 births recorded between 1999–2010. 4,843 births had complete outcome data and were included in an individual participant level meta-analysis. 99% of 445 low birth weight  babies were either preterm (<37 weeks gestation) or small for gestational age . 52% of 87 neonatal deaths occurred in preterm or small for gestational age babies. Babies born <34 weeks gestation had the highest odds of death compared to term babies (odds ratio [OR] 58.7 [95% CI 28.4–121.4]), with little difference when stratified by weight for gestational age. Babies born 34–36 weeks gestation with appropriate weight for gestational age had just three times the likelihood of neonatal death compared to babies born term, (OR 3.2 [95% CI 1.0–10.7]), but the likelihood for babies born 34–36 weeks who were also small for gestational age was 20 times higher (OR 19.8 [95% CI 8.3–47.4]). Only 1% of babies were born moderately premature and small for gestational age, but this group suffered 8% of deaths. Individual level data on newborns are scarce in East Africa; potential biases arising due to the non-systematic selection of the individual studies, or due to the methods applied for estimating gestational age, are discussed.Moderately preterm babies who are also small for gestational age experience a considerably increased likelihood of neonatal death in East Africa.Please see later in the article for the Editors' Summary. Worldwide, every year around 3.3 million babies die within their first month of life and the proportion of under-five child deaths that are now in the neonatal period (the first 28 days of life) has increased in all regions of the world and is currently estimated at 41%. Of these deaths, over 90% occur in low- and middle-income countries, and a third of all neonatal deaths occur in sub-Saharan Africa. Low birth weight  is one of the biggest risk factors associated with neonatal deaths but it is the causes of low birth weight, rather than the low weight itself that is thought to lead to neonatal deaths. The two main causes of low birth weight are preterm birth (delivery before 37 weeks gestation) and/or restricted growth in the womb (intra-uterine growth retardation), resulting in babies who are small for their dates .Despite growing international attention focused on neonatal mortality in recent years, the relative importance of low birth weight, small for gestational age, and preterm birth in causing newborn deaths remains unclear. So in this study, the researchers investigated these relationships by calculating the risk of neonatal mortality associated with preterm birth after adjusting for weight for gestational age by conducting a meta-analysis (synthesis of the data) using information from studies reporting neonatal mortality conducted in sub-Saharan Africa.The researchers identified potential African datasets and selected four out of a possible ten to include in their analysis as these studies included three essential birth outcomes: birth weight; gestational age measured using antenatal ultrasound, or neonatal assessment on the day of birth; and neonatal mortality. These four studies were conducted in Kenya, Tanzania, and Uganda, all in East Africa. The researchers analysed each study separately but also conducted a pooled statistical analysis on all four studies. To give a more detailed analysis, the researchers categorized babies into six groups taking into account whether the babies were moderately preterm (born at 34–36 weeks) or very preterm (born before 34 weeks) and whether their weight was appropriate for their gestational age.The researchers included a total of 4,843 live births in their analysis and found that overall, 9.2% of babies were low birth weight, 4.0% were preterm, and 20.4% were small for gestational age. Amongst low birth weight babies, 26.1% were preterm, 85.0% were small for gestational age, and 98.8% were either preterm or small for gestational age. In their detailed analysis, the researchers found that the odds (chance) of death in the first 28 days of life were seven times higher for babies born low birth weight compared to those with normal birth weight, with low birth weight infants experiencing a neonatal mortality rate of 80.9/1,000 live births. The odds of death were twice as high for babies born small for gestational age compared to those born appropriate for gestational age, giving a neonatal mortality rate of 29.3/1,000 live births. Furthermore, compared to those born at term, the odds of death were over six times higher for babies born moderately preterm and almost 60 times higher for babies born very preterm with almost half of all very preterm babies dying in the first 28 days of life, giving a neonatal mortality rate 473.6/1,000 live births. However, moderately preterm babies who were small for gestational age had a much greater odds of death than moderately preterm babies who were of the appropriate weight for their gestational age.These findings from East Africa show that babies born either small for gestational age or preterm contributed 52% of neonatal deaths. The detailed analysis suggests that babies born preterm are at the greatest risk of death, but size for gestational age also plays an important role especially in moderately preterm babies. The results from this study emphasize the pressing need to find ways to prevent preterm delivery and intra-uterine growth retardation and also illustrate the importance of measuring and reporting outcomes of individual babies.http://dx.doi.org/10.1371/journal.pmed.1001292.Please access these Web sites via the online version of this summary at PLOS Medicine study by Oestergaard et al. has the latest global figures on neonatal mortalityA recent UNICEF provides information on neonatal mortalitythe causes of neonatal mortality, including preterm birthThe World Health Organization (WHO) provides factsheets on  Low birth weight  is one of the strongest predictors of neonatal mortality (death in the first 28 d of life), is routinely collected and reported in health literature, and is associated with a complex set of fetal and maternal characteristics There is an absence of data to explain the way in which low birth weight, small for gestational age, and preterm risks interact with neonatal mortality in high mortality burden settings. In the United States, where the neonatal mortality rate (NMR) is relatively low at 5/1,000 live births In contrast, the NMR in sub-Saharan Africa is persistently high at an estimated 41/1,000 live births, translating to around 1.2 million deaths in 2008, which represents around one-third of all global neonatal deaths In a meta-analysis of individual level data collected across East Africa, we estimated the odds of neonatal mortality associated with preterm birth after adjusting for weight for gestational age. We accessed data from studies over a 10-y period that collected high quality birth weight and gestational age data, and which reported newborn survival to at least 28 d of life.Approval was obtained from the following: (1) Institutional Review Board, Kenya Medical Research Institute, and US Centers for Disease Control and Prevention; (2) National Medical Research Coordinating Committee (Tanzania), and London School of Hygiene & Tropical Medicine; (3) The Uganda National Council for Science and Technology, and London School of Hygiene & Tropical Medicine; (4) National Medical Research Coordinating Committee (Tanzania).http://cherg.org/).The methodology was developed in partnership with colleagues at the Child Health Epidemiology Reference Group , whether the birth took place at home or in a health facility, and parity of the mother. The availability of maternal malaria infection indicators was explored across all datasets but was not a criterion for selection.The search for eligible datasets was conducted October–December 2010 by TM, JAS, and BW. To our knowledge, no studies have been designed or published from Africa with the specific aim of answering our research question, thus the sampling strategy was convenience, not systematic, taking two stages. First we contacted all members of the Malaria Center, and of the Maternal Reproductive and Child Health Center (MARCH) at the London School of Hygiene & Tropical Medicine (LSHTM) to enquire about eligible African datasets, also extending the enquiry to their international collaborators. Second, we reviewed protocols of studies identified to ensure that our eligibility criteria had been met.A total of 10 possible African datasets were identified, four of which were defined as eligible and are described below. These four were all from East Africa, were completed within an 11-y interval (1999–2010), included all newborn outcome and maternal explanatory variables, and measured peripheral maternal malaria infection at delivery. Six datasets did not meet our criteria for gestational age or birth weight .A summary of methods used by each study when measuring newborn outcomes is provided in The Asembo Bay Cohort Project in Siaya District, western Kenya (completed 1999) 19 villages were included for longitudinal follow-up of pregnant women and their newborns and these cohort observations are included here. A monthly census identified pregnant women who were recruited and prospectively followed to birth and for at least 1 y thereafter.2p<0.001), and had a higher prevalence of preterm birth (X2p<0.02)  were included in this analysis. Because of the community-based design of the study, the data represent rural infants born at home and in the local clinics. Newborn measures not taken within 72 h of birth were excluded from our analysis. The likely effect was to miss very early deaths and therefore underestimate the incidence of adverse outcomes. The excluded population had a higher NMR 51.7 per 1,000 compared to 13 per 1,000 in those included (Xp<0.02) .The Antenatal Syphilis Screening and Treatment project in Mwanza, northwest Tanzania (completed 2000) Syphilis screening was carried out for all women attending the antenatal clinic. Eligible antenatal attendees with syphilis (defined by positive rapid plasma reagin test [RPR]), followed by the next two eligible antenatal attendees without syphilis, were recruited. Hospital and home deliveries were followed up actively, and for at least 28 d thereafter.2p<0.03). Compared with included babies, excluded babies were more frequently born at home, had a higher prevalence of low birth weight (X2p<0.007), and were born to less educated mothers  were included in this analysis. The mortality rate of those excluded  was almost double that of infants included  in the analysis  (completed 2006) Women attending antenatal services for the first time that pregnancy, and who were estimated to be ≤28 wk gestation, were enrolled and examined. Women with severe anemia (Hb<70 g/l), or other severe disease, were excluded and referred for treatment, and those who developed severe anemia during follow-up were withdrawn from the study and treated. All women were visited at home 1 wk after enrolment at antenatal clinic, at approximately 36 wk gestation, and at term. Women who subsequently delivered at home were visited within 7 d after birth and are not included in this analysis.2p<0.001) and had lower mean birth weight (t-test p = 0.03); the NMR amongst included infants was 16.9/1,000 and was not available for those excluded  of whom had complete data and are included in this analysis. The excluded babies born in health facilities had more twin births (Xexcluded .www.stoppam.org) The Strategies to Prevent Pregnancy Associated Malaria project . One quarter of the excluded births (46/184) did not have mortality follow-up to the 28th day of life; the NMR amongst those included was 32.8/1,000 but only 7.6/1,000 amongst those excluded, although this difference did not reach statistical significance (X2p<0.11)  had complete information for this analysis. There were more home births amongst excluded infants (Xp<0.11) .NMR was calculated as observed deaths within 28 d divided by observed live births. Low birth weight was defined as weight less than 2,500 g. Gestational age at birth was categorized as: term (≥37 completed weeks of gestation), moderately preterm (34–36 wk), very preterm (<34 wk). Small weight for gestational age was defined as being below the tenth percentile of weight for gestation of a US-based reference population I2 statistic l2 statistic were calculated using the user generated i2ci.ado command in STATA Taken together the four eligible studies provide strength to answer this research question, but were individually small and no previous attempt had been made to conduct this analysis. Odds ratios (ORs) and corresponding 95% CIs for neonatal mortality with relation to the exposures of low birth weight (compared to not low birth weight), moderate or very preterm (compared to term), small for gestational age , and weight for gestational age stratified by preterm , were calculated in each of the four datasets individually, using logistic regression. Individual measures of effect and uncertainty measures from the four studies were then included in fixed effects meta-analyses, using the metan commands in STATA. Study estimates were combined using inverse variance weighting, and pooled ORs were summarised with Mantel-Haenszel methods. Between study heterogeneity was investigated using the To inform whether ORs included within meta-analyses should be crude or adjusted, sub-group investigation for confounding of the relationship with neonatal mortality was carried out within each of the four included studies using available covariates .t-tests, and proportions using Chi-squared tests. All analyses were carried out using STATA version 11 (Stata Corporation).Additionally, in order to investigate the influence of exclusions due to incomplete data, sensitivity analyses comparing characteristics of included and excluded infants were conducted. Continuous variables were compared using The proportional distribution of newborn deaths for preterm stratified by weight for gestational age was calculated. Finally, we estimated the proportion of neonatal deaths associated with risk factors [/overall NMR], and the mortality that could be attributed to different weight for gestational age and preterm outcomes, i.e. the attributable risk percent [1-(NMR amongst babies without the risk factor/NMR amongst babies with the risk factor)]. Both of these estimates rest on the assumption that avoiding the risk factors preterm birth or low birth weight percentile for gestational age would not affect any other factor.From these four studies 5,727 live births were observed, of whom 4,843 (85%) had a complete set of outcome data and were included in the analysis . The morIn the individual studies, between 6.9% and 11.3% of babies were low birth weight, being 9.2% (95% CI 8.4–10.0) for all studies combined. Between 2.7% and 5.7% of babies were preterm, being 4.0% (95% CI 3.5–4.6) for all studies combined. Between 9.9% and 26.4% of babies were small for gestational age, being 20.4% (95% CI 19.3–21.6) for all studies combined . AmongstI2 values  to 87% (high heterogeneity) Forest plots of results of meta-analyses showing ORs and 95% CIs for each study, and the pooled measure of effect and corresponding 95% CIs, are shown in The odds of death in the first 28 d of life were seven times higher for babies born low birth weight compared to those with normal birth weight , and low birth weight infants experienced a NRM of 80.9/1,000 live births ; Table 4Using babies born with weight appropriate for gestational age and at term as reference, the odds for neonatal mortality were three times higher for those born appropriate for gestational age at 34–36 wk , but 75 times higher for those born appropriate for gestational age at <34 wk  ; Table 4After stratifying by method of assessing gestational age, ultrasound or neonatal assessment, the direction of these findings remains consistent, although the CIs are wide . In part23%  of the live births, but 53% (45/87) of the newborn deaths were amongst newborns born either small for gestational age or preterm. Less than 1%  of live births, but 20% (17/87) of deaths, were amongst very preterm infants (<34 wk). Just 1%  of live births, but 8% (7/87) of deaths, were amongst those born moderately preterm (34–36 wk) and small for gestational age.Overall, 28% of neonatal mortality was associated with being born preterm [(18 – 12.9)/18 * 100], and 39% of neonatal mortality was associated with being born either preterm or small for gestational age [(18.0−11.0)/18 * 100], assuming that all babies would have the same risk of neonatal death if they were born term and appropriate for gestational age .98% of the mortality risk (the attributable risk percent) of babies born appropriate for gestational age at <34 wk was attributed to them having been born very preterm [(466.7−11.0)/466.7 * 100]. Over 90% of the neonatal mortality risk of all small for gestational age and preterm babies (<37 wk) was attributed to them being born small for gestational age and preterm .99% of low birth weight babies were either small for gestational age or preterm. Just 23% of babies were born either small for gestational age or preterm but they contributed 52% of the neonatal deaths. The 4% of babies who were born preterm were at highest likelihood of death, accounting for 30% of the neonatal deaths, with over 90% of their mortality risk being attributed to being preterm. However this analysis of data from East Africa revealed that weight for gestational age played an important role for moderately preterm babies. The odds of neonatal mortality of babies born 34–36 wk gestation and appropriate weight for gestational age was just three times higher than term babies of appropriate weight, but was 20 times higher amongst babies born 34–36 wk gestation and small for gestational age.Preterm birth is a direct cause of mortality but also aggravates the effect of other risk factors; small for gestational age may arise because of intra-uterine growth retardation which has been shown to increase the risk of mortality and morbidity Previous studies have reported the mortality risk associated with separate measures of birth outcome in East Africa Nonetheless, there are three inter-related limitations in this study, each a reflection of the difficulty of obtaining high quality individual level birth outcome data in this setting. First, there was selection bias in that 70% of the included babies were born in a health facility, compared to only 24% of excluded babies, and an expected 50% at the population level for East Africa; thus the included mothers may be better health seekers than those excluded. These study findings may be an underestimate of the true population level effects.The second limitation, consistent with the first, was the exclusion of around 15% of live births because of missing data for birth weight or gestational age information, or survival to 28 d of life. In our sensitivity analysis there was evidence of bias in that, for three of the four studies, neonatal mortality of those excluded was far higher than of those included, as was the prevalence of preterm birth. The most likely explanation for this finding is that some very early deaths were excluded or classified as lost to follow-up because babies died before birth weight or gestational age could be estimated . Again, this limitation may have led to underestimation of the mortality risks, especially in the first days of life, associated with low birth weight, preterm, and small for gestational age. Imputation was considered as an approach to address the problem of missing data, a key factor being to have gestational age where birth weight was missing. However, given the quantity of missing gestational age data we did not feel confident that there were enough good covariates with which to make a sensible prediction model.www.intergrowth21.org.uk) that aims to address this is on-going and results are expected to be available in 2014. Some data from individual studies exist, for example in 2011 a study in Botswana developed standard values there and found that Botswana-born preterm infants had higher average birth weights than US-born infants Finally, there may be measurement error for gestational age  because of the methods used to determine gestational age, and there may also be misclassification of size for gestational age because of the use of US-based reference population for standardised birth weight by gestational age values Indeed, gestational age data across Africa are scarce, and what data exist are prone to bias—most markedly for preterm newborns who are at highest mortality risk Reflecting on the implications of these uncertainties for the principal findings, we observed an increase in odds of neonatal mortality to be consistently larger when gestational age was assessed by ultrasound compared to neonatal assessment, but both methods show results in the same direction, and the lower limit of confidence around the estimates was very close for both . We alsoThree issues particularly exacerbate interventions to prevent preterm and small births in the East African setting: (1) the aetiology of small for gestational age and preterm birth is multi-factorial Preterm or small for gestation births accounted for 52% of newborn deaths in this analysis of data from East Africa. Preterm birth had the strongest association with death, but there was also an additional risk for moderately preterm babies born small for gestational age compared to those born moderately preterm and appropriate for gestational age. 8% of babies who died were born moderately preterm and small for gestational age: if this was extrapolated to the estimated 1.2 million neonatal deaths in sub-Saharan Africa in 2008 this finding would translate to 96,000 African newborns lost.


Obstructive sleep apnea and dyslipidemia are common medical disorders that independently increase vascular morbidity and mortality. Current animal and human data show that, indeed, obstructive sleep apnea may mediate pathological alterations in cholesterol and triglyceride metabolism. The mechanisms involved are increased lipolysis, decreased lipoprotein clearance, and enhanced lipid output from the liver. Human evidence shows that the treatment of obstructive sleep apnea with continuous positive airway pressure leads to an improvement of postprandial hyperlipidemia. However, more studies are needed, to clarify the pathophysiology of the interrelationship between obstructive sleep apnea and dyslipidemia and whether treatment of obstructive sleep apnea will lead to an improvement in the lipid profile and, more importantly, reduce hyperlipidemia-related vascular outcomes. Obstructive sleep apnea (OSA) is a common medical disorder affecting up to 24% of the general US population . The disCurrent evidence suggests that OSA disturbs fundamental biochemical processes and is associated with low-grade systemic inflammation and oxidative stress . Indeed,Dyslipidemia, on the other hand, is the group of disorders of cholesterol (Ch) and/or triglyceride (TG) metabolism with a well-known detrimental impact on increased cardiovascular risk . FurtherThe goal of this paper is to summarize the current knowledge on the pathogenesis of the potential interrelationship between OSA and dyslipidemia. Firstly, we will briefly overview the metabolism of Ch and TG. Secondly, we will discuss the data on increased lipid delivery to the liver in OSA models, including data on increased lipolysis. Thirdly, data on abnormal lipid clearance in OSA will be reviewed. Finally, we will discuss the evidence regarding how OSA may increase lipid synthesis in the liver.A detailed discussion of Ch and TG metabolism is beyond the scope of this paper and can be found elsewhere . The aimThere are two main pathways of lipid metabolism: exogenous and endogenous. We will briefly review the exogenous pathway first, and then discuss the endogenous one.The endogenous lipid pathway starts from the intestinal absorption of dietary TG and Ch, which will be bound to locally synthesized  chylomicrons. Chylomicrons contain apolipoprotein (apo) B48 and will acquire apo C II and apo E in the bloodstream from other lipoprotein particles, particularly from HDL. Apo C II serves as a ligand for the enzyme lipoprotein lipase (LPL), which is located predominantly in the adipose tissue. LPL will hydrolase the TG content of chylomicrons to form glycerol and free fatty acids (FFA), which will be taken up by adipocyte for storage. Subsequently, smaller chylomicron particles can transfer some proteins to HDL and finally be taken up by the liver for Ch and TG turnover.The exogenous lipid pathway starts in the liver and is believed to be more clinically relevant to the initiation and progression of the atherosclerotic process. Similar to the endogenous pathway, the process starts with the formation of lipoproteins rich in TG, particularly, very low-density lipoproteins (VLDL). VLDL are smaller particles than chylomicrons and contain apo B100 instead of apo B48. In addition to apo B100, VLDL contain apo CII, apo C III, and apo E. Similarly, apo C II activates LPL for the hydrolyzation of the TG content, resulting in the formation of intermediate density lipoproteins (IDLs). IDLs can be either taken up by the liver through apo B 100 and apo E ligands or can be converted into low-density lipoproteins (LDLs) by hepatic lipase and cholesterol transfer from HDL. Thereafter, Ch can be used in bile acid synthesis, the production of steroid hormones, or can be taken up by macrophages via scavenger receptors with the subsequent formation of foam cells in the arterial bed. In addition to this LDL can be oxidized in the arterial wall and initiate proinflammatory cascade, which is known to be one of the major steps in the pathogenesis for atherosclerosis .HDL, which is formed in the liver and intestine, contains apo A I, apo A II, apo A IV, apo C I–III, apo D, and apo E. Some of these apolipoproteins will be transferred to other particles, such as apo C II and apo E to chylomicrons. HDL is capable of removing Ch from tissues via apo A I and to a lesser extent via apo A-IV- and apo CI-mediated activation of the lecithin cholesterol acyl transferase (LCAT) enzyme. Ch carried on HDL can be transferred to apo B-containing lipoproteins. It is generally believed that HDL is protective against atherosclerosis and vascular disease; however, some controversy exists regarding the so-called protective role of HDL, mainly because no benefit is seen in terms of cardiovascular protection with increased HDL in clinical trials .Repetitive episodes of apneas and hypopneas lead to a state of intermittent hypoxia (IH), which further alters a myriad of key biochemical processes . Indeed,Indeed, catecholamine hormones via their insulin-antagonizing effects modulate the activity of hormone sensitive lipase (HSL) in the adipose tissue, leading to the breakdown of TG into FFA and glycerol, which then will be resynthesized in the liver and form VLDL . BarcelóSubsequent FFA influx into the liver may lead to the assembly of TG-rich VLDL and their further efflux into the systemic circulation . AfterwaLDL cholesterol is notoriously known for its strong association with excessive cardiovascular morbidity and mortality . Indeed,As it was previously mentioned, lipoproteins rich in TG are cleared from the bloodstream via LPL-mediated hydrolysis. It is known that LPL activity is maintained by insulin and decreased by hormones such as cortisol and epinephrine that oppose the actions of insulin .α) [α is a nuclear receptor implicated in the regulation of transcriptional activity of multiple genes responsible for lipid metabolism, including LPL. CD 36 is another PPAR-α-regulated factor responsible for FFA uptake into cells. It has been shown that IH decreases CD36 and LPL activity via the downregulation of PPAR-α transcription [Jun et al. recently showed that IH downregulates TG clearance via a decrease in the activity of peroxisome proliferator-activated receptor-alpha (PPAR-α) . PPAR-α cription .α adrenergic receptors [A human study performed by Luyster et al. showed that OSA is associated with the LDL subclass B, which is known to be more resistant to clearance from the bloodstream . Therefoeceptors .Current scientific evidence suggests that OSA is associated with oxidative stress , which mOn the molecular level, IH activates HIF, leading to a variety of fundamental alterations relevant to both physiological adaptation and disease . Li et aFurthermore, researchers from Johns Hopkins University in the USA showed that the severity of IH is directly related to hyperlipidemia and liver oxidative stress in a mouse model of OSA . Diet-inOSA and dyslipidemia are common medical disorders that independently increase vascular morbidity and mortality. Current animal and human data show that, indeed, OSA may mediate pathological alterations in cholesterol and triglyceride metabolism. The mechanisms involved are increased lipolysis, decreased lipoprotein clearance, and enhanced lipid output from the liver. A simplified overview of OSA-mediated hyperlipidemia is presented in Human evidence shows that the treatment of OSA with continuous positive airway pressure leads to an improvement of postprandial hyperlipidemia. However, more studies are needed, to clarify the pathophysiology of the interrelationship between OSA and dyslipidemia and whether treatment of OSA will lead to an improvement in the lipid profile and, more importantly, reduce hyperlipidemia-related vascular outcomes.