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The Lancet Public Health
Birth Weight: Earliest, Non-Modifiable, Risk Factor for Non-Communicable Diseases
--Manuscript Draft--
Manuscript Number: thelancetpublichealth-D-20-00046
Article Type: Article (Original Research)
Keywords: Birth weight: BW; Low birth weight: LBW; Non-Communicable Diseases (NCD).
Corresponding Author: issa al salmi, MD(Trinity College),FRCPI,MRCP(UK),FRCP,MIPH,PHD,F
The Royal Hospital
Muscat, Muscat OMAN
First Author: issa al salmi
Order of Authors: issa al salmi
Suad Hannawi, MD, MRCP (UK), FRCP, MIPH, PHD AUS)
Manuscript Region of Origin: OMAN
Abstract: Background
Non-communicable diseases-NCD and low-birthweight-LBW are increasing world-wide
for the last few decades.
Method
AusDiab-study is a nationally representative cross-sectional study where baseline data
on 11,247 participants were recorded. All participants (n=10,788) who participated in
the baseline survey were invited back for re-testing and questions about birthweight
have been added. Participants were asked to state their birthweight, the likely accuracy
of the stated birthweight and the source of their stated birthweight.
Results
10,788 participants were eligible to participate in the five-year follow-up AusDiab study
and were asked to complete the birthweight-questionnaire. Of the 7,157 (66.3%) who
responded to our questionnaire, 4,502 (63%), reported information related to their
birthweight. People who reported their birthweight were younger and less likely to have
clinical and laboratory abnormalities. The birthweight was similar in those who obtained
it from medical-records and those got it from family-members. After adjustment for age
differences, there were no differences between people who obtained their birthweight
from medical-records and those who obtained it from family-members.
Conclusion
Birth-weight recall is quite-accurate with no difference between those obtained from
medical-records or from family-member. Birthweight may be the earliest risk-factors
that could be recorded for an individual as very important risk-factor for development of
chronic diseases. An early-strategy health program is of great importance to be
instituted to detect major risk-factors which may arise early in life in those with LBW.
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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Birth Weight: Earliest, Non-Modifiable, Risk Factor for
Non-Communicable Diseases
Manuscript
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Issa Al Salmi1 and Suad Hannawi2
1The Renal Medicine Department, the Royal Hospital, Muscat, Oman
2The Medicine Department, MOHAP, Dubai, UAE, PO Box 6552
Corresponding Author:
Dr. Issa Al Salmi, MD, BA, BAO, Bch, MB (Trinity College), FRCPI, MRCP (UK), FRCP,
MIPH, PhD (AUS), FASN (USA)
The Royal Hospital, 23 July Street, P O Box 1331, code 111, Muscat, Oman
Telephone: 968 92709000
Fax: 968 245 99966
Email: isa@ausdoctors.net
ORCID: 0000-0002-3443-5972
Research ID: J-4622-2014
Dr Suad Hannawi; BhS, MD, MRCP (UK), FRCP, MIPH, PHD (AUS); suad1@ausdoctors.netThe
Medicine Department, MOHAP, Dubai, UAE, PO Box 6552
Manuscript word count: 3000 words
Abstract word count: 230 words
Tables: 5
Figures: 1
Abbreviations:
Birth weight: BW
Low birth weight: LBW
Non-Communicable Diseases (NCD)
The authorship page:
All authors have participated in the drafting the work and all have approved the final version. All
authors have agreed to be accountable for all aspects of the work in ensuring that questions
related to the accuracy or integrity of any part of the work are appropriately investigated and
resolved.
Conflict of Interest (COI) statement: “The authors declare no conflicts of interest”
Financial Disclosure statement: None
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Abstract
Background: Non-communicable diseases-NCD and low-birthweight-LBW are increasing
world-wide for the last few decades.
Method: AusDiab-study is a nationally representative cross-sectional study where baseline data
on 11,247 participants were recorded. All participants (n=10,788) who participated in the baseline
survey were invited back for re-testing and questions about birthweight have been added.
Participants were asked to state their birthweight, the likely accuracy of the stated birthweight and
the source of their stated birthweight.
Results: 10,788 participants were eligible to participate in the five-year follow-up AusDiab study
and were asked to complete the birthweight-questionnaire. Of the 7,157 (66.3%) who responded
to our questionnaire, 4,502 (63%), reported information related to their birthweight. People who
reported their birthweight were younger and less likely to have clinical and laboratory
abnormalities. The birthweight was similar in those who obtained it from medical-records and
those got it from family-members. After adjustment for age differences, there were no differences
between people who obtained their birthweight from medical-records and those who obtained it
from family-members.
Conclusion: Birth-weight recall is quite-accurate with no difference between those obtained from
medical-records or from family-member. Birthweight may be the earliest risk-factors that could
be recorded for an individual as very important risk-factor for development of chronic diseases.
An early-strategy health program is of great importance to be instituted to detect major risk-factors
which may arise early in life in those with LBW.
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Introduction
Undernutrition, occurring for whatever reason, slows cell division, either as a direct effect or
through altered concentrations of growth factors or hormones, and may permanently reduce the
number of cells in particular organs (1, 2). A less than ideal nutritious-diet in pregnancy can
bring about foetus adaptations that include everlasting alterations to cell numbers and type within
vital structure or organs and consequent modulation of expression of upon human cellular
structures (3). This undernutrition can have persisting flaws, which include decreased cell-
numbers in tissues and organs, altered organ-structure, selection of particular clones of cells and
transformed settings of key hormonal axes.
In recent years, there has been great interest in the early development of the foetus and the
impact of growth during the gestational period on the development of diseases in later life, and in
particular that termed a ‘critical period’ (4). The ‘critical period’ of growth of various tissues and
organs is the rapid growth period that starts from the ninth week of gestation onwards, which is
determined by rapid cell division. Disproportionate development of various structures and or
different organ systems in pre-natal life can occur because different tissues have different critical
periods of growth at different times of development in utero (5, 6).
In Oman, the incidence of LBW is reported to be 9%. LBW data from national health surveys in
Oman, and published reports from Oman's Ministry of Health and the World Health
Organization were collected and assessed between January and August 2014. Oman's LBW rate
has been increasing progressively over the last few decades. It was about 4% in 1980 and had
nearly doubled (8.1%) by 2000 and recently it has reached 10% (7, 8). In view of progressive
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transformation of socioeconomic status especially among female, it was reported that mothers
with an advanced level of education are more likely to have infants with LBW in Oman (8).
There are many reports that LBW, < 2.5 kg, predisposes to many diseases including
hypertension, diabetes, cardiovascular diseases and kidney diseases (9-13). However, most
previous studies found a significant relationship when adjustments were made for body mass
index (BMI) or current body weight. Also, many studies were criticised for not adjusting for
important confounders such as physical activity, smoking status, alcohol intake, family history
and socioeconomic factors (13-16).
This paper examines the reported birth weight data from a nationally representative cross-
sectional of the AusDiab study.
Method
The AusDiab study is a nationally representative cross-sectional study where baseline data on
11,247 participants were collected and participants were recruited from a stratified sample of
Australians aged ≥ 25 years, residing in 42 randomly selected urban and non-urban. In 2004-
2005, a 5-year follow-up survey was conducted. All eligible participants (n=10,788) who
participated in the baseline survey were invited back for re-testing. Those who were ineligible
for invitation (n=459) included people who either requested no further contact, were known to be
deceased, or who were too ill or had moved into a nursing facility classified as high care.
Questions about birthweight have been added to the second round of the AusDiab study, which
began in July 2004. Participants were asked to state their birthweight, the likely accuracy of the
stated birthweight and the source of their stated birthweight. Birthweights were recorded as
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pounds and ounces or in kilograms and grams. All values were converted to kilograms for
analyses. LBW was defined as birthweight less than 2.5 kg. Furthermore, they were also
categorized by quintiles with sex-specific birthweight for further analyses.
The following data are collected by questionnaire, clinical examination and laboratory
investigation;
Date of birth
Birthweight data by self-recall, and estimate of gestational age
Medical conditions, such as diabetes, hypertension, angina, coronary artery disease,
stroke, menarche abnormality, menopause abnormality, history of hysterectomy
History of anti-hypertensive agents, cholesterol lowering agents, and other treatment
agents obtained from the patient
Smoking status
Alcohol intake
Time spent on exercise activity and watching television in minutes per week
Socioeconomic status based on level of education, total financial income and dwelling
type
Current body weight, and height, and waist circumference and hip circumference
Bio-impedance examination for weight, fat mass, lean body mass, and total body water
Three blood pressure measurements, pulse rate
Urinary albumin, urinary creatinine, albumin/creatinine ratio, urinary protein/ creatinine
ratio
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Blood tests included fasting glucose, post-load glucose, glycosylated haemoglobin
(HbA1c), creatinine, fibrinogen, cholesterol, high density lipoprotein (HDL) low density
lipoprotein (LDL), triglyceride, and uric acid levels.
Height, weight, waist and hip circumferences were measured while the participants were
wearing light clothing and no footwear. All subjects underwent height/weight
measurement except those who were (i) chairbound, (ii) pregnant or (iii) too unsteady on
their feet.
Measurement of height was done to the nearest 0.5 cm with no shoes using a stadiometer.
Each individual erected fully on a fixed, flat surface with heels, buttocks and shoulders
resting lightly against a backing board so a line connecting the superior border of the
external auditory meatus with the infraorbital rim was horizontal (i.e. parallel to the
floor), the Frankfort plane.
Weight was measured on a firm, flat surface without shoes and excess clothing, using
digital weighing scales (Wedderburn Personal Digital Scales TI-HD316), and was
recorded to the nearest 0.1 kilogram (kg). The accuracy of the scales was checked daily
by using a 5 kg weight. The scales were not able to measure participants who weighed ≥
150 kg. BMI was calculated as weight (kg)/height (m)2.
All subjects underwent measurement of waist and hip circumference except those who (i)
were chairbound, (ii) were pregnant or (iii) had a colostomy/ileostomy. Waist
circumference was measured using a W606PM Lufkin steel measuring tape, with
measurements made halfway between the lower border of the ribs and the iliac crest in a
horizontal plane. Hip circumference was measured at the widest point over the buttocks.
For individual waist and hip circumference, measurements were taken twice to the
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nearest 0.5 cm. A third measurement was obtained if the difference between the two
measurements was greater than 2 cm. The mean of the two closest measurements was
calculated. Waist to hip ratio (WHR) was obtained by dividing the mean waist
circumference by the mean hip circumference.
Blood pressure measurement was performed in a seated position after participants had
rested for at least 5 minutes. The most suitable size for the cuff was used, and the arm
was maintained by a resting table at the individual heart-level. Three readings were taken
at 1-minute intervals. The mean of the first two readings was recorded. If the difference
between the three readings was greater than 10 mmHg, the mean of the two closest
measurements was used.
A standard mercury sphygmomanometer was used in Victoria, where the first and fifth
Korotkoff sounds were recorded to the nearest 2 mmHg. In the other states, we used the
Dinamap semiautomatic oscillometric recorder A comparison study of the
sphygmomanometer and the Dinamap showed that an adjustment was required for
diastolic blood pressure readings recorded in Victoria. This was derived from a
regression analysis of the data in the comparison study. The adjustment was: Victorian
adjusted diastolic blood pressure = 4.636 + (0.905 × Victorian manual diastolic blood
pressure).
All subjects underwent bioimpedance measurements except those who (i) were
chairbound, (ii) were pregnant, (iii) had a colostomy/ileostomy, (iv) did not have a height
measurement, or (v) weighed > 150 kg. The scale for the bioimpedance machine (Tanita
TBF 105 Body Fat Analyser) was placed on a firm, flat surface and participants were
measured in light clothing and without shoes, socks or hosiery. If the body fat percentage
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was over 70% or impedance < 100, the process was repeated. If the 2nd reading was
within five percentage points, the data from the 2nd reading were recorded. If the 2nd
reading was not within five percentage points, the process was repeated until two
consecutive readings within five percentage points were obtained. Once obtained, all data
from the latter of these two readings were recorded.
BMI groups were classified according to World Health Organization criteria (17) as
follows: normal < 25.0 kg/m2, overweight 25.0 – 29.9 kg/m2 and obese ≥ 30.0 kg/m2.
Overweight was considered when the waist circumference was 94.0-101.9 cm in male
population and 80.0 - 87.9 cm in female population. Obesity was considered if
circumference was ≥ 102.0 cm in male and ≥ 88.0 cm in female population. Men with
WHR > 0.90 and women with WHR > 0.85 were classified as obese. We considered
adult height, adult current weight, waist circumference, hip circumference, lean body
mass and total body water to be ‘low’ if they were below the gender specific 10th
percentile and waist circumference, WHR and body fat parentage to be ‘high’ if they
were above the gender specific 90th percentile.
Urine protein and creatinine were measured on a morning spot urine sample. Urine
protein was measured using pyrogallol red-molybdate by the Olympus AU600 auto-
analyser; the coefficient of variation was < 4.1%. The modified kinetic Jaffe reaction was
used to measure creatinine level in the urine, using the Olympus AU600 auto-analyser
and the coefficient of variation was < 1.1%. Urine albumin was measured by rate
nephrelometry with the Beckman Array. The coefficient of variation was < 3.1%. All
determinations were performed at a central laboratory (HITECH Pathology, Melbourne,
Australia).
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Blood was collected by venepuncture after an overnight fast of at least 10 hours.
Specimens were collected into separate tubes in the following order: a plain tube for
measurement of total cholesterol, HDL, LDL and triglycerides, fluoride/oxalate tube for
plasma glucose and an EDTA tube for HbA1c. Blood specimens collected were
centrifuged on-site and transported daily with urine samples to the central laboratory
(HITECH Pathology). Serum creatinine was measured by the modified kinetic Jaffe
reaction using the Olympus AU600 auto-analyzer and the coefficient of variation was <
1.9%.
All participants, except those who were pregnant, those who failed to fast or those with
known diabetes who were taking oral hypoglycaemic medication and/or insulin for
diabetes, were given a 300 ml drink of 75 grams of glucose (Bicorp Australia Pty. Ltd.,
Victoria, Australia) to be used up in five-minutes. A second blood sample was taken by
venepuncture to determine plasma glucose (mmol/l) two hours after the glucose load.
Plasma glucose was determined enzymatically (Olympus AU600 analyser, Olympus
Optical Co. Ltd, Tokyo, Japan). Total glycosylated haemoglobin analysis used high
performance liquid chromatography (Bio-Rad Variant Hemoglobin Testing System, Bio-
Rad, Hercules, CA, USA) with standardized conversion to HbA1c values (normal 4.2-
6.3%). Fasting insulin was measured in participants aged 35 years and over by using
radiommunoassay (Linco Research Inc).
The homeostasis model assessment (HOMA) model was used to yield an estimate of
insulin sensitivity and beta-cell function from fasting plasma insulin and glucose
concentration (18-20). Fasting glucose and fasting insulin (pmol/l) were used to calculate
HOMA_B and HOMA_S measurements on the downloadable “HOMA2” program.
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HOMA_B was defined as “beta cell function %” and HOMA_S was defined as “insulin
sensitivity %”. The association between serum insulin and glucose level in the basal state
imitates the equilibrium between hepatic-glucose output and pancreatic insulin-secretion,
which is kept by a feedback-loop between the pancreatic beta-cells and hepatic-cells (20).
Availability of Data and Materials
Authors do not wish to share their data as it belongs to the Australian Prospective Diabetes Study
Group.
Ethics approval and consent
Participants gave informed written consent. Ethics approval was provided by the Ethics
Committees of the International Diabetes Institute, Monash University, and Australian Institute
of Health and Welfare. The ethical approval for the Australian Prospective Diabetes Study was
obtained from The International Diabetes Federation Ethics Committee with a project number
3/2002. The AusDiab study committee was approached via Dr Steven Chadban on 9th July 2003.
Dr Jonathan Shaw, an AusDiab investigator, contacted us to discuss our proposal on 22nd July
2003. We proposed a questionnaire to be included in the AusDiab study and provided
background information of similar questionnaires that were used in the United Kingdom and
United States. A final approval for our questionnaire was accepted on 27th January 2004. The
AusDiab study in its second round started in July 2004 and will continue till November 2005.
The ethical approval for the overall AusDiab study was granted on 13th June 2003 and expiry
date was 13th June 2005.
Results
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10,788 participants were eligible to participate in the 2004-05 five-year follow-up AusDiab study
and were asked to complete our birthweight questionnaire. Of the 7,157 (66.3%) who responded
to our questionnaire, 4,502 (63% or 42% of the original cohort), reported information related to
their birthweight, with the other responders to the birthweight questionnaire were unable to give
a value.
Table 1 showed that people who reported their birthweight were younger than people who did
not know their birthweight, with means (SD) of 48 (12) years vs. 54 (12) years respectively, p<
0.001. The reported birthweights ranged from 0.4 to 7.0 kg with a mean (SD) of 3.37 (0.7) kg
and were similar for those reported from family members, 3.37 (0.7), with 95% CI of 3.35 - 3.40,
from medical records 3.35 (0.6), with 95% CI of 3.28 - 3.41 and for guessed 3.34 (0.6), with
95% CI of 3.28 - 3.41, with adjustment for age and sex, p= 0.46.
The mean birthweight was lower for females, 3.28 (3.26-3.31) kg, when compared to males, 3.5
(3.47-3.53) kg (Figure 1). The prevalence of low birthweight (<2.5 kg) was 8.5% (10.1% in
females and 6.1% in males), 1% had a birthweight less than 1.5 kg and less than 1% had a
birthweight of five Kg and over. 74% stated that they were full term at gestation. 9% stated that
they were born prematurely. However, 6% were born after term and 11% provided no
information of their gestational age.
Forty eight percent of respondents considered their birthweight report as very accurate, 44% as
fairly accurate and only 8% percent mentioned that their birthweights were based on a ‘guess’
(Table 1). Among those who reported their birthweight, 80% obtained their birthweight from a
family member, and 10% from medical records (Table 1). Seven percent obtained their data from
other sources and less than 3% provided no information about the source of their birthweight.
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Sixty seven percent of participants had a living natural mother (66.7% of females and 67.6% of
males) and 46% had a living natural father (45.9% of females and 45.2% of males).
Tables 2 and 3 show the comparison between those who reported their birthweight and those
who did not. Females (Table 2) were more likely to report their birthweight than males (Table 3).
Females and males who reported their birthweight were younger, taller and less likely to have
various clinical and laboratory abnormalities. For example, those who reported their birthweight
were less likely to have glycaemic dysregulation (impaired fasting glucose and impaired post-
load glucose), diabetes and kidney impairment than those who did not report their birthweight.
Tables 4 and 5 show no difference in birthweights between those who reported their birthweight
data from medical records and those who obtained it from a family member. Females (Table 4)
and males (Table 5) who reported their birthweights from medical records were younger.
Females who obtained their birthweight from a family member were shorter and had higher waist
circumference, WHR, systolic blood pressure, glycaemic abnormalities, dyslipidaemia, uric acid
and lower estimated glomerular filtration rate (GFR). Males who obtained their birthweights
from a family member only had higher WHR and lower estimated GFR. These differences did
not exist once adjustments were made for age.
DISCUSSION
People who reported their birthweight were younger and less likely to have clinical and
laboratory abnormalities. The birthweight was similar in those who obtained it from medical
records and those got it from family members. After adjustment for age differences, there were
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
no differences between people who obtained their birthweight from medical records and those
who obtained it from family members.
Our study used a self-recall questionnaire to obtain information related to birthweight. We opted
for this method as there were no readily available data banks of birthweight that cover the study
population. Many previously published studies have employed this technique (21-26), with
response rates that were often less than those described here. The British Telecom study had a
50% response rate and only 39.4% provided data on birthweight (23), The British Women’s
Heart and Health Study had a 60% response rate and 33% reported their birthweight (26, 27); the
Health Professional Follow-up Study (HPFS) had a 75% response rate and 59% of the
responders reported their birthweight (22).
Among birthweight respondents, it was reassuring that the mean birthweight of those who
guessed their birthweight; 3.34 (0.6) was similar to those who obtained their birthweight from a
family member; 3.37 (0.6), or from medical records; 3.35 (0.7), p= 0.46. This was also the case
in the British Telecom Study (23). In addition, the mean recalled birthweight in our study, 3.37
(0.7) kg, is consistent with that reported in the United Kingdom in those born between 1931 and
1939 in Hertfordshire (28); with the 1946 national birth cohort (29); with the Health Professional
Follow up Study (22) and is similar to the recent average Australian birthweight of 3.36 kg (30).
The original, in utero, environment is very vital in defining the succeeding risk of the growth of
chronic diseases (31-33). LBW, which echoes adversative effects on the individual growth in
utero, donates to this phenomenon of disease programming in early life. It is not only the
presence or absence of genes that control our destiny, but the way in which gene expression may
be forever changed by, for example, the nutritional environment in early pre-natal life. Many
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epidemiological findings suggest that the risk of disease in adult life is programmed, and/or
imprinted by the environment encountered during prenatally.
The Barker theory states that there is an association between LBW and the development of
hypertension and cardiovascular disease in adult humans (31). It emphasises that adverse
influences encountered during foetal life have the dual effect of perturbing prenatal cell-growth
patterns and launching a pre-susceptibility to major disease in adult life. Barker and colleagues
found a similarity between the geographical distribution of mortality from cardiovascular disease
in England and Wales and a pattern of maternal and neonatal mortality (34, 35). They also
confirmed an association between those with the lowest weight at birth, or at 1 year of age, and
deaths from ischaemic heart disease in later life.
In Oman, the incidence and prevalence of CKD is increasing progressively overtime. The
incidence of those on RRT for end stage-CKD incidence was 21, 75, and 120 per million
population in 1983, 2001, and 2013, respectively. Similarly, the incidence of those on RRT for
end-stage CKD was 49, 916, and 2386 in 1983, 2001, and 2013 respectively (36, 37). The first,
in utero, environment is very important in determining the subsequent risk of the development of
chronic diseases (31-33). Low birth weight mirrors hostile in utero environment during the baby
development in the uterus. It contributes to this phenomenon of disease programming in early in-
utero-life. It is not only the existence or absenteeism of genes that governor our destiny, but the
way in which gene expression may be forever reformed by, for example, the nutritious
environment in early uterine-life. As such, many epidemiological findings advocate that the risk
of disease in adult life is programmed early in life, and/or imprinted by the uterine environment
met before post-natal life.
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The role of small size at birth with low number of cells may contribute to various NCD problem.
Post-natal environmental factors further compound such a metabolic demand on body organs that
lead to various organ function being overwhelmed with increase in metabolic rate. Hence, this
primes to upsurge demand upon many human organs or structures, such as pancreatic cells or
nephron with subsequent hyperfiltration, and therefore organ dysfunction ensues. Hence, an early
tactic health approach and maintenance of comprehensive health-program is of great importance
to be instituted to detect major risk factors which may arise early in life in those population of
LBW and or prematurity, which is progressively rising world-wide. The logistic and financial
requirement may not be huge to put such a strategy forward, but this strategy would in long term
delay or even ameliorate the progressive rise of NCD. Hence, endorsing healthier lifestyles, body
weight, blood pressure and enhancing the family physicians’ capability should be required to
reduce the burden of NCDs. Findings of various risk factors at early post-natal life, such as
proteinuria and treatment with angiotensin converting enzyme inhibitors, will help to better
manage this subset of our population that is increasing progressively with advancement of
medical care for small babies.
Conclusion:
Birthweight may be the earliest risk-factors that could be recorded for an individual as very
important risk-factor for development of chronic diseases. An early-strategy health program is of
great importance to be instituted to detect major risk-factors which may arise early in life in those
with LBW.
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It is prudent to enquiry about birth weight of an individual and to follow these children by their
family physicians in at least a yearly basis to examine their various risk factors and provide an
educational strategy from an early life in abide to ameliorate their pre-set disease evolution.
Acknowledgments
We thank the participants, Survey Team, and the Steering Committee of the AusDiab Study, as
comprehensively listed elsewhere (38). Also, we would like to thank all my colleagues at the
University of Queensland, Australia.
We are most grateful to the following for their support of the study: The Commonwealth Dept of
Health and Aged Care, Abbott Australasia Pty Ltd, Alphapharm Pty Ltd, AstraZeneca, Aventis
Pharmaceutical, Bristol-Myers Squibb Pharmaceuticals, Eli Lilly (Aust) Pty Ltd,
GlaxoSmithKline, Janssen-Cilag (Aust) Pty Ltd, Merck Lipha s.a., Merck Sharp & Dohme
(Aust), Novartis Pharmaceutical (Aust) Pty Ltd, Novo Nordisk Pharmaceutical Pty Ltd,
Pharmacia and Upjohn Pty Ltd, Pfizer Pty Ltd, Roche Diagnostics, Sanofi Synthelabo (Aust) Pty
Ltd, Servier Laboratories (Aust) Pty Ltd, BioRad Laboratories Pty Ltd, HITECH Pathology Pty
Ltd, the Australian Kidney Foundation, Diabetes Australia, Diabetes Australia (Northern
Territory), Queensland Health, South Australian Department of Human Services, Tasmanian
Department of Health and Human Services, Territory Health Services, Victorian Department of
Human Services, the Victorian OIS program and Health Department of Western Australia. Also,
for their invaluable contribution to the setup and field activities of AusDiab, we are enormously
grateful to A. Allman, B. Atkins, S. Bennett, S. Chadban, S. Colagiuri, M. de Courten, M.
Dalton, M. D’Emden, T. Dwyer, D. Jolley, I. Kemp, P. Magnus, J. Mathews, D. McCarty, A.
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Meehan, K. O’Dea, P. Phillips, P. Popplewell, C. Reid, A. Stewart, R. Tapp, H. Taylor, T.
Welborn, and F. Wilson.
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Table 1: Analysis of birthweight report by accuracy, source and gestational age
Overall
Female
Male
Birthweight, kg
3.37 (0.67)
3.28 (0.66)
3.50 (0.68)
Accuracy
Very accurate
Fairly accurate
Guess & missing
2,136 (47.4%)
1,965 (43.7%)
401 (8.9%)
1,315 (48.5%)
1,175 (43.3%)
221 (8.2%)
821 (45.8%)
790 (44.1%)
180 (10.1%)
Source
Family member
Medical records
Others
missing
3,630 (80.6%)
420 (9.3%)
334 (7.4%)
118 (2.6%)
2,163 (79.8%)
274 (10.1%)
207 (7.6%)
67 (2.5%)
1,467 (81.9%)
146 (8.2%)
127 (7.1%)
51 (2.8%)
Gestational age
Full term
Pre term
Others
missing
3,312 (73.57%)
409 (9.08%)
298 (6.62%)
483 (10.73%)
1949 (71.89%)
271 (10%)
203 (7.49%)
288 (10.63%)
1363 (76.10%)
138 (7.71%)
95 (5.30%)
195 (10.89)
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Table 2: Characteristics of females who provided their birthweight and those who did not
provide their birthweight
With birthweight No birthweight* P
Number 2652 3410
Age, years 48.2 (47.7, 48.8) 53.6 (53.1, 54.1) <0.001
Height, cm 163.2 (163, 164) 161.2 (161,162) <0.001
Weight, kg 70.4 (69.8, 71.0) 70.3 (69.8, 70.9) 0.893
Waist circumference, cm 84.2 (83.7, 84.7) 86.5 (86.0, 86.9) <0.001
Hip circumference, cm 105 (104,105) 104 (104, 104) 0.020
Body mass index, kg/m2 26.6 (26.4, 26.8) 27.0 (26.8, 27.2) 0.005
Waist hip ratio 0.93 (0.92, 0.93) 0.94 (0.94, 0.94) <0.001
Systolic BP, mmHg 123.5 (123, 124) 128.9 (128, 130) <0.001
Diastolic BP, mmHg 66.2 (65.8, 66.6) 66.7 (65.8, 66.6) 0.078
Lean body mass, kg 41.1 (40.9, 41.3) 40.4 (40.2, 40.6) <0.001
Total body water, kg 30.1 (30.0, 30.2) 29.6 (29.5, 29.7) <0.001
Body fat, % 39.8 (39.4, 40.2) 40.3 (39.9, 40.7) 0.084
Fasting glucose, mmol/l 5.33 (5.29, 5.38) 5.51 (5.47, 5.55) <0.001
Post glucose, mmol 6.08 (5.99, 6.17) 6.63 (6.55, 6.70) <0.001
Hba1c, % 5.11 (5.08, 5.13) 5.23 (5.21, 5.56) <0.001
Diabetic, number (%) 128 (5.6%) 118 (11.8%) <0.001
Albumin creatinine ratio 0.74 (0.72, 0.76) 0.90 (0.87, 0.93) <0.001
Serum creatinine, µmol/l 78.0 (77.6, 78.3) 79.4 (78.8, 80.0) <0.001
GFR (CG), mls/min 88.0 (87.1, 88.9) 82.6 (81.7, 83.6) <0.001
GFR-lean, mls/min 71.4 (71.1, 71.7) 69.8 (69.4, 70.1) <0.001
MDRD GFR, mls/min 134.8 (134, 136) 130.2 (129, 131) <0.001
Cholesterol, mmol/l 5.57 (5.53, 5.60) 5.74 (5.71, 5.78) <0.001
Triglyceride, mmol/l 1.32 (1.29, 1.36) 1.48 (1.45, 1.51) <0.001
Uric acid, mmol/l 0.246 (0.24, 0.25) 0.264 (0.26, 0.27) <0.001
Fibrinogen, mmol/l 3.60 (3.57, 3.64) 3.72 (3.69, 3.75) <0.001
GFR (CG): glomerular filtration rate using the Cockcroft Gault formula
GFR-lean: glomerular filtration rate using the lean body mass formula
MDRD GFR: glomerular filtration rate using the Modification of Diet in Renal Disease formula
*Participants who did not provide their birthweight include (i) those who did not respond to the
birthweight questionnaire (n= 4090) and (ii) those who answered the questionnaire but could not
recall their birthweight (n=2655)
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Table 3: Characteristics of males who provided their birthweight and those who did not
provide their birthweight
With birthweight No birthweight* P
Number 1781 3235
Age, years 48.3 (47.7, 48.8) 53.6 (53.1, 54.1) <0.001
Height, cm 177.0 (177, 177) 175.0 (175, 175) <0.001
Weight, kg 85.5 (84.9, 86.2) 83.2 (82.7, 83.7) <0.001
Waist circumference, cm 97.1 (96.6, 97.6) 97.8 (97.4, 98.2) 0.028
Hip circumference, cm 105 (105, 105) 106 (105, 106) 0.107
Body mass index, kg/m2 27.3 (27.1, 27.5) 27.2 (27.1, 27.3) 0.496
Waist hip ratio 0.80 (0.80, 0.80) 0.82 (0.82, 0.82) <0.001
Systolic BP, mmHg 130.5 (130, 131) 134.4 (134, 135) <0.001
Diastolic BP, mmHg 74.2 (73.7, 74.7) 74.8 (74.4, 75.2) 0.079
Lean body mass, kg 63.5 (63.2, 63.8) 61.9 (61.7, 62.1) <0.001
Total body water, kg 46.5 (46.3, 46.7) 45.3 (45.2, 45.5) <0.001
Body fat, % 24.8 (24.5, 25.2) 24.6 (24.3, 24.8) 0.201
Fasting glucose, mmol/l 5.68 (5.62, 5.74) 5.87 (5.82, 5.91) <0.001
Post glucose, mmol 6.04 (5.92, 6.16) 6.43 (6.34, 6.52) <0.001
Hba1c, % 5.20 (5.17, 5.24) 5.33 (5.31, 5.36) <0.001
Diabetic, number (%) 126 (8.7%) 148 (13.8%) <0.001
Albumin creatinine ratio 0.53 (0.51, 0.55) 0.73 (0.70, 0.76) <0.001
Serum creatinine, µmol/l 94.8 (94.2, 95.3) 95.9 (95.2, 96.5) 0.022
GFR (GC), mls/min 103.6 (102, 105) 95.0 (94.0, 96.0) <0.001
GFR-lean, mls/min 101.3 (101, 102) 98.2 (97.7, 98.7) <0.001
MDRD GFR, mls/min 144.4 (143, 146) 139.7 (139, 141) <0.001
Cholesterol, mmol/l 5.64 (5.59, 5.69) 5.65 (5.61, 5.69) 0.793
Triglyceride, mmol/l 1.75 (1.68, 1.81) 1.73 (1.69, 1.77) 0.700
Uric acid, mmol/l 0.344 (0.34, 0.347) 0.345 (0.34, 0.348) 0.656
Fibrinogen, mmol/l 3.42 (3.39, 3.46) 3.55 (3.52, 3.58) <0.001
GFR (CG): glomerular filtration rate using the Cockcroft Gault formula
GFR-lean: glomerular filtration rate using the lean body mass formula
MDRD GFR: glomerular filtration rate using the Modification of Diet in Renal Disease formula
* Participants who did not provide their birthweight include (i) those who did not respond to the
birthweight questionnaire (n= 4090) and (ii) those who answered the questionnaire but could
not recall their birthweight (n=2655)
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Table 4: Comparison between people with birthweight from medical records and those
from family for females
Medical records Family member P
Number 274 2163
Age, years 40.8 (9) 48.4 (12) < 0.001
Birthweight, kg 3.26 (3.2, 3.3) 3.28 (3.2, 3.3) 0.654
Height, cm 164.2 (163.4, 165.1 163.1 (162.8, 163.4) 0.007
Weight, kg 70.3 (68.4, 72.2) 70.6 (69.9, 71.2) 0.804
Waist, cm 82.3 (80.7, 83.9) 84.5 (83.9, 85.0) 0.013
Hip, cm 104.9 (103.5, 106.3) 105.1 (104.6, 105.5) 0.845
BMI, kg/m2 26.1 (25.4, 26.8) 26.5 (26.3, 26.8) 0.196
Waist hip ratio 0.78 (0.77, 0.79) 0.80 (0.80, 0.81) < 0.001
Body fat, % 38.5 (37.2, 39.8) 39.9 (39.4, 40.3) 0.056
Lean body mass, kg 41.6 (41.0, 42.1) 41.0 (40.8, 41.3) 0.109
Total body water, kg 30.4 (30.0, 30.9) 30.0 (29.9, 30.2) 0.109
Systolic BP, mmHg 118.7 (117, 120.4) 123.5 (122.7, 124.2) < 0.001
Diastolic BP, mmHg 66.0 (64.7, 67.3) 66.2 (65.8, 66.7) 0.775
FPG, mmol/l 5.19 (5.12, 5.26) 5.34 (5.30, 5.38) 0.012
PLG, mmol/l 5.63 (5.44, 5.82) 6.10 (6.01, 6.19) < 0.001
HbA1c, mmol/l 5.02 (4.97, 5.06) 5.11 (5.09, 5.13) 0.003
Albumin creat ratio 0.69 (0.63, 0.76) 0.74 (0.71, 0.76) 0.243
Creatinine, mmol/l 76.8 (75.8, 77.8) 78.0 (77.6, 78.4) 0.062
GFR (CG), ml/min 95.4 (92.5, 98.4) 88.0 (87.0, 89.0) < 0.001
GFR (MDRD), ml/min 144.4 (141.5, 147) 134.5 (133.5, 135.6) < 0.001
GFR (LBM), ml/min 72.5 (71.4, 73.5) 71.3 (70.9, 71.7) 0.048
Cholesterol, mmol 5.35 (5.23, 5.46) 5.59 (5.54, 5.63) < 0.001
Triglyceride, mmol/l 1.20 (1.10, 1.30) 1.33 (1.29, 1.37) 0.018
Fibrinogen, mmol/l 3.64 (3.54, 3.74) 3.60 (3.56, 3.63) 0.417
Uric acid, mmol/l 0.24 (0.23, 0.24) 0.25 (0.24, 0.25) 0.036
BMI: body mass index
FPG: fasting plasma glucose
HbA1c: glycosylated haemoglobin
GFR (CG): glomerular filtration rate using the Cockcroft Gault formula
GFR-lean: glomerular filtration rate using the lean body mass formula
MDRD GFR: glomerular filtration rate using the Modification of Diet in Renal Disease formula
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
Table 5: Comparison between people with birthweight from medical records and those
from family for males
Medical records Family member
Number 146 1467
Age, years 42.7 (10) 48.3 (12) < 0.001
Birthweight, kg 3.46 (3.4, 3.6) 3.52 (3.5, 3.6) 0.261
Height, cm 177.8 (176.7, 178.9) 177.0 (176.6, 177.5) 0.179
Weight, kg 85.2 (82.9, 87.5) 85.8 (85.1, 86.5) 0.632
Waist, cm 95.4 (93.6, 97.3) 97.3 (96.7, 97.8) 0.064
Hip, cm 104.4 (103.0, 105.8) 104.8 (104.4, 105.2) 0.535
BMI, kg/m2 27.0 (26.3, 27.6) 27.4 (27.2, 27.6) 0.247
Waist hip ratio 0.91 (0.90, 0.92) 0.93 (0.92, 0.93) 0.011
Body fat, % 24.5 (23.3, 25.7) 25.0 (24.6, 25.4) 0.420
Lean body mass, kg 63.6 (62.5, 64.7) 63.6 (63.2, 63.9) 0.928
Total body water, kg 46.6 (45.8, 47.4) 46.5 (46.3, 46.8) 0.940
Systolic BP, mmHg 129.5 (126.9, 132) 130.2 (129.4, 131) 0.570
Diastolic BP, mmHg 74.6 (72.7, 76.4) 74.0 (73.5, 74.6) 0.545
FPG, mmol/l 5.61 (5.47, 5.74) 5.67 (5.62, 5.73) 0.468
PLG, mmol/l 5.76 (5.45, 6.08) 6.02 (5.90, 6.14) 0.204
HbA1c, mmol/l 5.19 (5.10, 5.29) 5.19 (5.16, 5.22) 0.968
Albumin creat ratio 0.50 (0.44, 0.57) 0.53 (0.50, 0.55) 0.522
Creatinine, mmol/l 93.5 (91.9, 95.1) 94.8 (94.3, 95.4) 0.177
GFR (CG), ml/min 111.0 (106.8, 115) 103.9 (102.7, 105) 0.001
GFR (MDRD), ml/min 152.7 (148.7, 156.7) 144.2 (143, 145.5) < 0.001
GFR (LBM), ml/min 102.1 (100.3, 104) 101.4 (100.8, 102) 0.423
Cholesterol, mmol 5.56 (5.4, 5.71) 5.64 (5.59, 5.69) 0.365
Triglyceride, mmol/l 1.68 (1.50, 1.86) 1.73 (1.66, 1.80) 0.654
Fibrinogen, mmol/l 3.33 ( 3.22, 3.45) 3.42 (3.38, 3.46) 0.217
Uric acid, mmol/l 0.34 (0.33, 0.35) 0.35 (0.34, 0.35) 0.185
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
BMI: body mass index
FPG: fasting plasma glucose
HbA1c: glycosylated haemoglobin
GFR (CG): glomerular filtration rate using the Cockcroft Gault formula
GFR-lean: glomerular filtration rate using the lean body mass formula
MDRD GFR: glomerular filtration rate using the Modification of Diet in Renal Disease formula
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
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Figure 1- Birthweight distribution for females and males’ participants
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3520085
