overweight and obesity in pregnancy: …...maternal obesity is a growing health concern throughout...

For peer review only

OVERWEIGHT AND OBESITY IN PREGNANCY: HEALTH

SERVICE UTILISATION AND COSTS ON THE NHS

Journal: BMJ Open

Manuscript ID: bmjopen-2013-003983

Article Type: Research

Date Submitted by the Author: 09-Sep-2013

Complete List of Authors: Morgan, Kelly; Swansea University, School of Medicine Rahman, Muhammad; Swansea University, School of Medicine Macey, Steven; Swansea University, Institute of Life Sciences Atkinson, Mark; Swansea University, School of Medicine Hill, Rebecca; Swansea University, School of Medicine Khanom, Ashrafunnesa; Swansea University, School of Medicine Paranjothy, Shantini; Cardiff University, School of Medicine Husain, Muhammad; Keele University, Keele Management School

Brophy, Sinead; Swansea University, School of Medicine

<b>Primary Subject Heading</b>:

Public health

Secondary Subject Heading: Health economics, Obstetrics and gynaecology

Keywords: HEALTH ECONOMICS, PUBLIC HEALTH, Maternal medicine < OBSTETRICS

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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SERVICE UTILIZATION AND COSTS ON THE NHS

Kelly Morgan, College of Medicine, Swansea University, SA2 8PP, United Kingdom. Tel: 44

(0) 1795 606650. Fax no: 01792 513430 [email protected]

Kelly L Morgan, MSc1, Muhammad A Rahman, PhD

1, Steven Macey, PhD

2, Mark D

Atkinson, PhD1, Rebecca A Hill, PhD

1, Ashrafunnesa Khanom, MA

1, Shantini Paranjothy,

PhD3, Muhammad Jami Husain, PhD

4 and Sinead T Brophy, PhD

1

1. College of Medicine, Swansea University, United Kingdom.

2. Institute of Life sciences, Swansea University, United Kingdom.

3. Cardiff University, School of Medicine, United Kingdom

4. Keele Management School, Keele University, United Kingdom.

Cost of maternal overweight and obesity

Key words: Pregnancy, maternal, obesity, health service, cost

Word count: 3315

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Abstract

Objective: To estimate the direct healthcare cost of being overweight or obese throughout

pregnancy to the National Health Service (NHS) in Wales.

Design: Retrospective prevalence-based study.

Setting: Combined linked anonymised electronic datasets gathered on a cohort of women

enrolled on the Growing Up in Wales: Environments for Healthy Living (EHL) study.

Women were categorised into two groups: normal BMI (n=260) and overweight/obese

(BMI>25) (n=224).

Participants: 484 singleton pregnancies with available health service records and an

antenatal BMI.

Primary outcome measure: Total health service utilisation (comprising all General Practice

(GP) visits and prescribed medications, inpatient admissions and outpatient visits) and direct

healthcare costs for providing these services in the year 2011-2012. Costs are calculated as

cost of mother (no infant costs are included) and are related to health service usage

throughout pregnancy and two months following delivery.

Results: There was a strong association between health care usage cost and BMI (p<0.001).

Adjusting for maternal age, parity, ethnicity and co-morbidity, mean total costs were 23%

higher amongst overweight women (RR, 1.23; 95% CI, 1.230-1.233) and 37% higher

amongst obese women (RR, 1.39; 95% CI, 1.38-1.39) compared to women with normal

weight. Adjusting for smoking, consumption of alcohol, or the presence of any co-

morbidities did not materially affect the results. The total mean cost estimates were £3546.3

for normal weight, £4244.4 for overweight, and £4717.64 for obese women.

Conclusions: Increased health service usage and healthcare costs during pregnancy are

associated with increasing maternal BMI; this was apparent across all health services

considered within this study. Interventions costing less than £1171.34 per person could be

cost-effective if they reduce healthcare usage amongst obese pregnant women to levels

equivalent to that of normal weight women.

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ARTICLE SUMMARY

Article focus

• Compare health service utilisation of normal weight and overweight/obese women

throughout the course of pregnancy.

• Adopt an econometric approach to quantify the direct health service costs associated

with health service use amongst normal weight, overweight and obese women.

• Examine the impact of multiple confounders on any associations shown throughout

the study.

Key messages

• After adjusting for multiple confounding factors (age, ethnicity and parity),

overweight and obese women showed significantly greater healthcare usage of all

hospital services.

• Overweight and obese women cost an additional £698.1 and £1171.34 respectively

when comparing total health service costs with those of normal weight women.

Strengths and limitations of the study

• The ability to control for potential confounders and co-morbidities through data

collection, at the patient level, whilst using medically recorded BMI are evident

strengths of this study.

• Limitations of this study include; use of a BMI value recorded at a single time point,

challenges presented when quantifying health service utilisation and the disregard of

indirect and tangible health service costs.

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BACKGROUND

Maternal obesity is a growing health concern throughout the UK with approximately 1 in 20

women obese during pregnancy. Across the nations rates vary from 1 in 15 women living in

Wales to lower proportions of 1 in 29 women in London 1. Associated with increasing

problems throughout pregnancy 2, delivery complications

3-5 and poor neonatal outcomes

6 7,

maternal obesity is currently one of the biggest challenges presented to maternity services in

the UK 1. In a qualitative study in the UK, health professionals noted that obese expectant

mothers and offspring required significantly higher levels of care 8. Accompanying increasing

health service utilisation, cost repercussions are also eminent amongst the obese population.

Cost-of-illness studies provide a tool for quantifying this economic burden and estimate the

total cost savings which would ensue if obesity was absent 9.

Previous studies have shown a 2.3% increase in total direct healthcare costs for every unit

increase in body mass index (BMI) among non-pregnant women, with more hospitalizations,

higher rates of prescription drugs and greater outpatient visits in obese women 10. An earlier

study investigating healthcare costs relating to obesity at a patient level reported higher rates

of inpatient days, higher number and costs of outpatient visits, laboratory usage and overall

total costs, with mean annual costs 25% higher in obese individuals (BMI greater than or

equal to 30.0 kg/m2)

compared to those with a normal BMI (BMI of 20-24.9 kg/m

2)

11. A

recent systematic review focusing on the healthcare costs of obesity worldwide included 32

selected studies of which one was based in the UK 12. Studies were based on either

modelling or database analyses and despite varying methodologies all 32 studies were in

agreement that obesity placed a financial strain on health economics with direct healthcare

costs ranging between 0.7 and 2.8% of a country’s total healthcare expenditure. Limitations

apparent across many of the studies included use of self reported BMI, varying BMI cut-offs

for defining obesity, and population attributable risk designs. The UK based study was

deemed as having the lowest methodological quality due to its cross sectional design and use

of aggregate level data 13. Thus there is a need for higher quality UK-based studies.

To date, research focusing on healthcare costs accrued by obese expectant mothers in

comparison to non-obese counterparts is limited. Previous research within this area has

focused on prenatal care attendance amongst low-income working women 14, cost of high-

risk pregnancies receiving in-home nursing care 15 and costs associated with complicated

pregnancies 16. As highlighted by the Centre for Maternal and Child Enquiries (CMACE)

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report 1, there is currently a paucity of data on the cost of maternal overweight and obesity in

the UK.

Despite being scarce, research to date has shown the increasing demands of excess weight on

health service utilisation and resultant economic implications. The current economic climate

calls for careful management of healthcare funds 17. Interventions are therefore needed to

examine the effect of reducing healthcare use amongst women presenting a BMI above

normal. Previously described as a ‘powerful motivator’ pregnancy could represent the

optimal time for the adoption of positive lifestyle choices and ultimately impact maternal and

offspring health and well being 18. Accurately identifying the cost of healthcare usage by

overweight and obese women during pregnancy will enable future interventions to efficiently

devise cost effective methods targeting maternal obesity whilst reducing associated NHS

costs. No study to date has comprehensively analysed the NHS costs associated with

overweight and obesity during pregnancy. The aim of this paper is to provide an overview of

health service utilisation and accompanying costs amongst normal weight and

overweight/obese pregnant women with more precision. Direct healthcare costs associated

with general practice (GP) visits and prescriptions, inpatient admissions and outpatient visits

shall be calculated to provide a descriptive account of healthcare use.

RESEARCH METHODS AND DESIGN

Study sample

We conducted a retrospective prevalence-based study of pregnant women who took part in

the Growing Up in Wales: Environments for Healthy Living birth cohort study (EHL)19. All

pregnant women aged 16 and older receiving antenatal care (during the period 2010-2013)

through the Abertawe Bro Morgannwg University (ABMU) NHS Board were eligible to

participate in the EHL study. We excluded non-singleton pregnancies, mothers without a

recorded BMI in the antenatal records, mothers with pre-existing diabetes and mothers not

registered with a GP for longer than a year preceding the study period. A more in-depth

description of the study population has previously been described elsewhere19. Briefly, each

participant completed a questionnaire during pregnancy providing information on age,

ethnicity, education level, socioeconomic status, smoking status and alcohol consumption.

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BMI categories

Participant BMI was calculated by a midwife during the antenatal booking appointment

(around 12 weeks gestation) and recorded in the antenatal notes. For the purposes of this

study, women were categorised into two BMI groups: normal BMI (BMI of 18.5 - 24.9

kg/m2) (n=260) and overweight/obese BMI (BMI of >25.0 kg/m

2) (n=224).

Health services use data

Using the Secure Anonymised Information Linkage (SAIL) databank developed at Swansea

University 20, rroutinely collected electronic medical records were used to establish health

service utilisation, specifically throughout the course of pregnancy and two months post

delivery. Data concerning health service use (i.e. diagnoses, medications, investigations and

results) are coded within the databank using Read codes, the standard terminology system

used in the UK 21. Only Read codes relating to the healthcare of the mother were included.

The Primary Care dataset within SAIL provided the total number of visits to a general

practice (GP) for each participant over the defined time period and all records of any

prescribed medications. To calculate the total number of visits to a GP we: 1) only counted a

record as a visit to the GP if two Read codes were present on the same day, 2) only ever

counted one visit per day (i.e. if there was more than one record of an event on the same day,

only one GP visit was counted) and 3) excluded all read codes relating to medications

(indicated by GP Read codes starting with small letters a-z). The Patient Episode Database

for Wales (PEDW) was searched for inpatient admissions, inpatient durations, and outpatient

visits. For each visit record a distinct event was used e.g. if more than one outpatient record

was recorded on the same date, only one event was used in the analyses.

Economic analysis

This study adopted an econometric approach in order to compare the mean differences in

healthcare costs accrued in two groups based on BMI; normal (BMI <24.9kg/m2) and

overweight/obese (BMI>25 kg/m2). All health service costs are NHS-related only and

concern only health service utilisation associated with the mother. Costs concerning inpatient

and outpatient utilisation are extracted from the Welsh Costing Return 2011-2012 in which

costings are fully inclusive of any treatments, medications and operations, which may occur

during a patient event and are aggregated by specialty type. Supplementary tables 1 and 2

outline cost sources and exact values applied to each inpatient and outpatient event

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respectively based on specialty Read codes. Unit Costs of Health and Social Care 2011

provided a unit cost for each GP visit 22. For the purpose of this study, applied unit costs were

based on a clinic consultation lasting 17.2 minutes (including direct care staff costs and

qualifications). Costings of prescription drugs were determined using the British National

Formulary (BNF) November 2011 23 applying specific costs for each medication Read code.

Costs were not included in cases where medications referred to the treatment of infants and

Read codes not specifying medication dose were assigned the lowest unit price.

Co-morbidities

As obesity is often associated with a number of health problems, the presence of co-

morbidities in the Primary Care dataset were identified using the Charlson Index 24. A

complete list of all co-morbidities and accompanying Read version 2 codes (provided by

Khan et al., 25) are located in supplementary table 3. A time scale of 3 years prior to the date

of conception was used to identify co-morbidities.

Statistical analyses

Descriptive characteristics for normal weight and overweight/obese women were tabulated

alongside outcomes and covariates. Outcomes which were verified by a counting process (i.e.

number of GP visits, number of inpatient admissions, number of inpatient days and number

of outpatient visits) were analysed using a Poisson regression approach. Differences between

healthcare cost and BMI category were analysed using log linear models providing estimates

of rate ratios (RR), where the specifications included various control variables i.e. age,

ethnicity, parity and other confounders. STATA version 12.1 (STATA, Texas, USA) was

used for all statistical analyses and statistical significance was set at P<0.05 throughout. As

women with an existing co-morbidities may require greater need for surveillance during

pregnancy, outcomes were adjusted according to the presence of one or more conditions.

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RESULTS

Demographics

Of the total EHL cohort population, 484 (66.9%) women met the inclusion criteria and were

included within this study. Ninety one percent of the population were of white ethnicity with

an even spread of women above and below age 30 years observed. Figure 1 highlights the

process for obtaining the study population, and descriptive statistics for both groups of

women are shown in Table 1. Forty six percent of women comprised the overweight group,

of whom 11% were obese (BMI>30 kg/m2). Across both groups, proportions of all four

ethnic categories and maternal age were similar. Proportions of unemployed women were

almost identical in the two groups (11.4% of normal vs. 11.5% of overweight group) whereas

the overweight group showed a higher proportion of women undertaking part-time/seasonal

work (30.1% vs. 19.7%, p<0.02). Overweight women were also more likely to have 2 or

more children in comparison to the normal weight group (p=0.05). No significant differences

were observed between the number of women smoking, consuming alcohol, having an

existing co-morbidity or mental distress between the two groups.

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Figure 1. Flow diagram displaying participant involvement throughout study selection

Participants of the EHL study

N= 724

Exclusions

Non-singleton pregnancies N= 9 (1.2 %)

Incomplete pregnancies N= 109 (15.1%)

No maternal BMI available N= 121

(16.7%)

Record of cancer N=1 (0.1%)

Total mother-child pairs

N= 484

Women with a BMI<25kg/m2

N= 260

Women with a BMI> 25 kg/m2

N= 224

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Table 1. Characteristics of study participants by BMI

Normal BMI Overweight plus

Characteristics (n) BMI 18.5 - 24.9 BMI >24.9

(N= 260) (N= 224 )

Age at delivery (yr) (n= 481)

18-19 8 (3.1) 8 (3.6)

20-25 51 (19.8) 37 (16.6)

26-30 70 (27.1) 66 (29.6)

31-35 66 (25.6) 49 (22)

36-40 56 (21.7) 54 (24.2)

>40 7 (2.7) 9 (4)

Ethnic group (n= 448)

White/European 223 (91.4) 185 (90.7)

African/Caribbean 1 (0.4) 4 (2)

Asian 10 (4.1) 8 (4)

Other 10 (4.1) 7 (3.4)

Annual Income (n= 400)

£0 to £9,999 18 (8.6) 24 (12.5)

£10,000 to £14,999 20 (9.5) 22 (11.4

£15,000 to £24, 999 32 (15.2) 32 (16.6)

£25,000 to £34,999 30 (14.3) 22 (11.4)

£35,000 to £39,999 20 (9.5) 16 (8.8)

£40,000 to £49,999 29 (13.8) 32 (16.6)

£50,000 to £99,999 45 (21.4) 29 (15)

£100,000+ 6 (2.9) 2 (1)

Don't know 10 (4.8) 13 (6.7)

Working status (n= 454)

Full-Time 115 (46.8) 78 (37.3)

Part-Time or casual 48 (19.7) 63 (30.1)

Unemployed 28 (11.4) 24 (11.5)

Homemaker 36 (14.6) 32 (15.3)

Student 9 (3.7) 3 (1.5)

Self-employed 6 (2.4) 4 (1.9)

Other 4 (1.6) 5 (2.4)

Parity (n= 484)

0 141 (54.2) 81 (36.2)

1 82 (31.5) 96 (42.9)

2 24 (9.2) 29 (12.9)

>3 13 (5.1) 18 (8)

Co morbidity within 3 years prior (n=484) 18 (6.3) 17 (7.6)

Smoker (n=409) 49 (20.2) 35 (17.1)

Alcohol consumption (n=411) 89 (36.3) 86 (41.7)

Depression score* >12 (n=449) 20 (51.3) 19 (48.7)

Results are expressed as number (%)

*based on a Kessler 6 score recorded during pregnancy visit

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Health service utilisation

The average number of inpatient admissions and outpatient visits (adjusted for age)

significantly varied between the two groups, with higher rates in the overweight group (Table

2). There was a general trend amongst each health service of utilisation rates increasing with

age of the participant. All healthcare services with the exception of outpatient visits revealed

a reduced rate of usage amongst the overweight group in the youngest age category (18-20

years), however this was not significant for inpatient days. Following adjustment for

confounding factors (age, ethnicity and parity), the usage rate of all healthcare services with

the exception of outpatient visits was higher for women in the overweight group compared to

the normal weight group (Table 3). Specifically, the overweight group experienced an 18%

higher rate of inpatient visits and a 36% higher rate of inpatient duration. Examining GP data,

a 17% higher visit rate and 14% higher prescription of medications were shown. Examining

the type of inpatient specialties accessed revealed no significant differences between groups.

The majority of visits for both groups were shown across maternity services (93.7% for

normal BMI vs. 90.2% for overweight and obese) whilst the overweight-obese group

presented higher numbers of medical specialty visits (6.3% vs. 3.7%). Further adjusting for

smoking and alcohol consumption did not result in a noticeable change to the adjusted (age,

ethnicity and parity) findings.

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Table 2. Use of Healthcare Services in relation to BMI and type of service (average use

throughout an 11 month period)

Age (yr) Normal BMI Ψ Overweight plus

BMI 18.5 - 24.9 BMI >24.9

Inpatient visits

18-19 4.1 (1.12) 0.52 (0.29-0.92)

20-25 2.1 (0.22) 1.54 (1.19-2.01)

26-30 2.49(0.19) 1.16 (0.94-1.42)

31-35 2.65 (0.30) 1.08 (0.86-1.35)

36-40 2.91 (0.34) 1.20 (0.98-1.48)

>40 3 (0.85) 1.07 (0.61-1.88)

All 2.63 (0.14) 1.16 (1.04-1.29)

Inpatient days

18-19 6.5 (1.86) 0.71 (0.47-1.08)

20-25 3.49 (0.40) 1.4 (1.14-1.72)

26-30 4.13 (0.47) 1.38 (1.18-1.61)

31-35 4.29 (0.46) 1.14 (0.96-1.35)

36-40 4.79 (0.56) 1.39 (1.19-1.63)

>40 4.85 (0.70) 1.24 (0.80-1.90)

All 4.3 (0.23) 1.29 (1.19-1.4)

Outpatient visits

18-19 2 (0.80) 2.19 (1.21-3.95)

20-25 3.12 (0.46) 0.75 (0.57-0.97)

26-30 3.11 (0.62) 1.32 (1.10-1.58)

31-35 2.72 (0.39) 1.09 (0.87-1.35)

36-40 3.34 (0.51) 1.07 (0.88-1.31)

>40 2.43 (1.7) 1.97 (1.12-3.45)

All 3.01 (0.24) 1.17 (1.06-1.29)

GP visits

18-19 16 (1.95) 0.76 (0.57-1.01)

20-25 12.94 (0.99) 0.90 (0.78-1.03)

26-30 13.72 (1.08) 1.22 (1.11-1.35)

31-35 12.81 (0.99) 0.96 (0.85-1.08)

36-40 12.43 (1.02) 1.16 (1.04-1.30)

>40 12.14 (2.90) 1.48 (1.14-1.93)

All 13.04 (0.49) 1.10 (1.04-1.16)

Medication counts

18-19 6.88 (1.38) 0.56 (0.36-0.88)

20-25 7.95 (1.37) 0.73 (0.61-0.86)

26-30 8.35 (1.54) 1.28 (1.13-1.43)

31-35 7.98 (1.18) 1.49 (1.31-1.69)

36-40 9.8 (2.11) 1.15 (1.02-1.29)

>40 4.8 (1.98) 2.99 (1.93-4.62)

All 8.40 (0.74) 1.20 (1.13-1.28)

Ψ Reference group for rate ratios, given as mean (SE)

Unless stated data are represented as rate ratios (95% confidence interval).

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Table 3: Adjusted Rate Ratios of healthcare usage

Risk factor Incidence RR 95%CI

Inpatient visits

Overweight 1.18 1.1-1.3

Mothers age 1 1.0-1.0

Ethnicity 0.99 0.9-1.0

Parity 0.99 0.9-1.0

Inpatient days

Overweight 1.36 1.24 - 1.48

Mothers age 1.01 1.0-1.0

Ethnicity 1. 01 1.0-1.0

Parity 0.9 0.9-0.9

Outpatient visits




Parity 1 1.0-1.1

GP visits




Parity 0.97 0.9-1.0

Medication




Parity 1.1 1.1-1.1

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Cost evaluation

There was a strong association between mean total costs and BMI, with the overweight group

costing on average 22% higher for all total mean costs (p<0.01). Table 4 provides a

breakdown of mean costs for each health service and each age category. As shown, the

overweight women aged 18-20 years had a considerably lower mean total cost (42% less). In

women age 20 and over, all mean total costs were greater among those women with a BMI of

25 or more.

We conducted a sub-set analysis obtaining adjusted (age, ethnicity and parity) estimates for

total health care costs of overweight (n=157) and obese (n=67, 10.4% had a BMI exceeding

40kg/m2) women (Table 5, model 1). In comparison to participants with a BMI less than 25,

overweight and obese women experienced 23% and 37% higher total health care costs

respectively (overweight RR, 1.23; 95% CI, 1.22-1.23, obese RR, 1.37; 95% CI, 1.38-1.39).

To assess the impact of existing co-morbidities on the variation of health service costs and

BMI, we further included co-morbidities as an independent variable alongside age, ethnicity

and parity (Table 5, model 2). The results showed that the rate ratio remained constant for

overweight women whilst the rate ratio of the obese group increased by 2%.

Table 6 shows the mean total cost for each BMI category revealing that obese women cost a

mean total of £1,171.24 (p=0.01) more than the normal weight group. Overweight women

also had a higher mean total cost in comparison to normal weight women, however this

finding was not statistically significant.

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Table 4. Relative rates of Total Health Service costs with BMI, by age (£’s/11 month)


BMI 18.5 - 24.9 BMI >24.9

Inpatient costs

18-19 3723.1 (3120) 0.75 (0.7-0.8)

20-25 2207 (1680) 1.31 (1.3-1.32)

26-30 2502.3 (2462.4) 1.4 (1.39-1.41)

31-35 2742.4 (2115.6) 1.1 (1.1-1.1)

36-40 2866.7 (2424.3) 1.33 (1.32-1.34)

>40 2845.9 (1142.6) 1.4 (1.38-1.43)

All 2644.09 (144.3) 1.27 (1.26-1.27)

Outpatient costs

18-19 361.1 (235.1) 2.23 (2.11-2.36)

20-25 459.1 (362.2) 0.74 (0.72-0.75)

26-30 585 (712.2) 1.32 (1.30-1.34)

31-35 462 (357.7) 1.10 (1.10-1.12)

36-40 534 (462) 1.05 (1.03-1.07)

>40 963.9 (403.2) 1.98 (1.87-2.08)

All 344.97 (29) 1.17 (1.16-1.18)

GP costs

18-19 848 (103.1) 0.76 (0.73-0.79)

20-25 685.8 (52.4) 0.90 (0.88-0.92)

26-30 727.1 (57.3) 1.22 (1.21-1.24)

31-35 678.7 (52.7) 0.96 (0.94-0.98)

36-40 659 (54.0) 1.16 (1.15-1.18)

>40 643.6 (153.6) 1.48 (1.43-1.54)

All 691.6(25.96) 1.10 (1.09-1.11)

Medication costs

18-19 6.8 (1.3) 0.77 (0.49-1.19)

20-25 8.4 (1.4) 0.70 (0.58-0.82)

26-30 9.3 (1.6) 1.20 (1.07-1.34)

31-35 8.5 (1.2) 1.46 (1.28-1.65)

36-40 10.1 (2.2) 1.09 (0.97-1.23)

>40 6 (2.0) 2.54 (1.64-3.93)

All 8.95 (0.8) 1.16 (1.09-1.23)

Total costs

18-19 4803.6 (1170.90) 0.79 (0.77-0.80)

20-25 3093.77 (286.54) 1.15 (1.14-1.16)

26-30 3497.89 (338.65) 1.36 (1.35-1.36)

31-35 3487.41 (296.0) 1.0 (1.0-1.01)

36-40 3838.6 (351.88) 1.21 (1.20-1.22)

>40 3768.25 (446.40) 1.34 (1.32-1.36)

All 4003.62 (184) 1.20 (1.19-1.20)



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Table 5. Total cost for all healthcare usage adjusted for confounders and co-morbidities

Model 1: Adjusted for age, ethnicity and parity

Model 2: Adjusted for age, ethnicity, parity and co-morbidity

Table 6. Total cost for normal BMI, overweight and obese women

Normal BMI

BMI<25

Overweight

24.9< BMI <30

Obese

BMI >30

Total mean cost (£) 3546.3 4244.4 4717.6

95%CI (3238.6-3854.0) (3647.7-4841.0) (4038.5-5396.8)*

Body Mass Index Model 1 Model 2

RR (95%CI) RR (95%CI)

<25 1 1

25-29.9 1.23 (1.230-1.233) 1.23 (1.22-1.23)

>29.9 1.37 (1.37-1.38) 1.39 (1.38-1.39)

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DISCUSSION

Various studies have reported the increasing number of adverse outcomes amongst obese

women during pregnancy 2-5, but few have quantified the healthcare costs associated with

increasing health service utilisation. Adopting an econometric approach, our findings have

shown that women who are overweight or obese at pregnancy booking are more likely to

accrue a higher number of health service visits and accompanying healthcare costs

throughout the course of pregnancy. An exception was shown amongst the youngest group of

overweight/obese women (aged 18-20 years) who revealed a significantly lower health

service cost in comparison to normal BMI counterparts. Specifically we found a 23% and

39% increase in total health service costs for overweight and obese women respectively.

Amongst our study population this equated to an extra £698.1 for overweight and £1171.34

for obese women when compared to costs accrued by women with a normal BMI.

Specifically looking at the type of health services accessed, overweight and obese women had

approximately 15-20% greater healthcare usage of all hospital service, a 30% higher mean

number of days spent in hospital, and a 10% higher mean usage of GP services. Given the

variety of methodologies used by previous studies it is difficult to directly compare our

findings, however previous studies also highlight increasing health service usage and/or

healthcare costs according to increasing maternal BMI 14-16 26 27

. One prospective case-control

study reported average prenatal care costs as 5 times higher for women who were overweight

before pregnancy in comparison to normal-weight control women 26. Collecting data during

pregnancy and the postpartum period, the study also reported that overweight women had a

higher duration of day and night hospitalisation by 3.9 and 6.2-fold correspondingly. Denison

and colleagues 27 reported increasing costs from minor complications throughout pregnancy

as maternal BMI increased. In this study, retrospectively analysing antenatal notes and labour

ward records, costs concerning staff, facilities and consumables were calculated for the

National Health Service (NHS). In comparison to normal weight women, overweight and

obese women cost on average an extra £33.21 and £31.02 respectively when considering

costs associated with minor complications. Higher healthcare costs were attributed to

increasing medication usage with obese women requiring treatment for more minor

complications. Our finding that overweight/obese women under the age of 20 years accrued

less health care costs than normal weight women warrants further investigation to confirm

and explore this association, given the small number of women in our sample in this age

group.

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Maternal overweight and obesity have also been shown to negatively impact upon the

subsequent health of offspring. Enhanced risk of adverse perinatal outcomes 28, delayed

mental development 29 and the development of later obesity

30 have been reported. One study

reported offspring born to women with a BMI greater than 26 were 3.5 times more likely to

require admission to a neonatal ward 31 whilst another found a 15% increased risk of

offspring being obese at age 4 years amongst obese mothers 30. A report released in 2011

estimated that childhood obesity in London alone cost the NHS £7.1 million (year

2006/2007) for providing GP appointments, inpatient and outpatient care and medications to

treat conditions related to childhood obesity 32. Furthermore the report estimated future costs

at £110.8 million per year (including direct and indirect costs) if children became obese

adults. Consequently in addition to the healthcare costs estimated within this study, it is

important to acknowledge the perpetuating cycle of increasing healthcare costs from an

intergenerational effect of maternal obesity.

A strength of this study was the unique opportunity to control for important potential

confounders such as age, smoking status, socio demographic variables, alcohol consumption

and co-morbidities through data collection at the patient level. This enabled us to exclude one

participant with a record of cancer within the three years preceding conception. Often studies

using self-reported information have shown an underestimation when reporting chronic

conditions 33. A further strength of this study is the use of medically recorded BMI values.

As frequent misclassification especially amongst overweight and obese women has been

documented when using self-reported BMI measures 34 we have been able to minimise

uncertainty associated with recall-bias.

Several limitations of our study must be also considered. First, relying on a BMI value

recorded at a single time point, and early in pregnancy, may cause methodological issues

provided that women can alter weight status throughout pregnancy 12. Second, gestational

weight gain was not considered, yet women entering pregnancy with a higher BMI have been

shown to gain lower levels of weight compared to those with a lower BMI, and may even

lose weight during pregnancy 35-37

. Third, our study specifically adopted a prevalence-based

approach for examining health service utilisation over an 11 month period. Our reported cost

estimates are therefore likely to be conservative as they do not account for those costs that are

indirect (e.g. costs due to absenteeism, travel costs, household production, informal

healthcare costs) or intangible (e.g. costs of suffering to the individual). Furthermore, in

addition to these excluded costs, our findings do not consider back loaded costs which are

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likely to occur from subsequent pregnancies, given that obese women are more likely to be

heavier in subsequent pregnancies 38 and that associated co-morbidities develop after the

onset of obesity 39.

Fourth, relying on electronic health records presents difficulties when trying to quantify the

type of event occurring and the appropriate cost to be assigned. In some cases an individual

would have more than one health event record occurring on the same day within the GP data.

Methods currently used for recording data make it impossible to differentiate between an

actual GP consultation and an administration process (e.g. a letter sent to consultant or a

patient telephone call). It was therefore decided to utilise only one event per recorded date

and to assume that it was a GP consultation (after excluding medication Read codes).

Similarly, the outpatient data also revealed numerous events occurring on the same date

which could signify the movement of a patient across specialties. We opted to apply the

specialty cost equating to the first event code only. It is also important to note that we could

only ascertain medication usage from GP datasets, therefore this estimate is undervalued

without the use of hospital data. Fifth and finally, given the nature of our study population it

was likely that study participants received healthcare from a community midwife.

Unfortunately this contact was not included within the scope of this study, as data were not

available on community practices within the electronic records. Again, our findings are

therefore likely to provide a conservative cost estimate.

Despite these limitations, our study findings provide strong evidence for an increase in health

service utilisation and accompanying direct healthcare costs in women presenting with a BMI

higher than normal during pregnancy. Looking at the number of births in the UK in 2012

(812,920) and applying the findings from this study, an additional £144,818,104.9 would

have been spent on health care services for obese women during an 11 month period. This

amount of capital could become cost-effective if utilised to fund public health interventions

targeting maternal lifestyle and subsequently reduce the health care usage of obese women.

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Acknowledgments

The work was supported by NISCHR and Swansea University. This study makes use of

anonymised data held in the Secure Anonymised Information Linkage (SAIL) system, which

is part of the national e-health records research infrastructure for Wales. We would like to

acknowledge all the data providers who make anonymised data available for research. This

work is also part of the Growing Up in Wales EHL study.

Author Contribution

K.L.M and S.B conceived of and designed the study. K.L.M was the guarantor of this article

and responsible for the statistical analysis and writing process under the guidance of S.T.B,

M.J.H and S.P. M.A.R in conjunction with M.D.A was responsible for all data extraction

from the Secure Anonymised Information database. K.L.M, R.A.H and A.K were responsible

for data collection methods. All authors reviewed the final manuscript.

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Supplementary Table 1: WCR 1 resource unit costs used to calculate direct medical costs within the

inpatient sector

Inpatients Daycases

Specialties

Net

expenditure

(£)

Patient

days

Cost per

day (£)

Net

expenditure

(£)

Patient

days

Cost per

day (£)

Paediatrics 52,237,276 71,720 728.35 866,951 2,147 403.80

Geriatrics 112,633,815 416,915 270.16 10,365 40 259.13

Cardiology 50,773,641 109,204 464.94 7,201,444 7,051 1,021.34

Dermatology 2,153,882 3,486 617.87 740,871 2,761 268.33

Infectious diseases 2,638,233 8,573 307.74 0 0 0.00

Medical oncology 2,045,936 4,863 420.71 138,819 479 289.81

Neurology 7,619,109 16,532 460.87 267,763 851 314.65

Rheumatology 787,026 909 865.82 742,779 1,609 461.64

Gastroenterology 23,213,420 75,773 306.35 8,129,697 19,499 416.93

Haematology 9,851,801 23,651 416.55 1,313,006 4,942 265.68

Clinical immunology

and allergy 0 0 0.00 0 0 0.00

Thoracic medicine 25,875,376 81,255 318.45 975,817 1,253 778.78

Genito-urinary

medicine 29,756 88 338.14 136,854 1,313 104.23

Nephrology 9,507,237 27,563 344.93 288,255 1,383 208.43

Rehabilitation

medicine 52,315,987 220,137 237.65 10,886 150 72.58

Palliative medicine 9,739,419 16,569 587.81 24,044 32 751.38

Other medicine 238,524,984 823,264 289.73 9,586,046 20,658 464.04

General surgery 156,270,386 290,410 538.10 29,185,179 37,404 780.27

Urology 30,819,378 50,146 614.59 13,797,772 28,074 491.48

Orthopaedics 209,045,919 298,249 700.91 28,238,373 24,526 1,151.36

ENT 28,287,361 26,675 1,060.44 7,185,969 6,170 1,164.66

Ophthalmology 4,329,661 4,926 878.94 26,617,445 30,448 874.19

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Gynaecology 38,956,738 51,917 750.37 11,905,598 15,773 754.81

Dental specialities 12,934,698 10,080 1,283.20 4,662,328 6,796 686.04

Neuro-surgery 13,793,671 17,046 809.20 51,963 81 641.52

Plastic surgery 10,154,515 10,623 955.90 1,955,652 2,383 820.67

Cardiothoracic 19,629,745 20,130 975.15 23,664 29 816.02

Paediatric surgery 4,226,962 4,387 963.52 358,460 400 896.15

Obstetrics 76,200,264 122,139 623.88 21,133 42 503.16

General practice

(maternity) 3,278 10 327.83 0 0 0

Learning disabilities 29,676,728 41,916 708.00 467 1 466.85

Mental illness 79,774,195 254,276 313.73 1,196 2 597.79

Child and adolescent

psychiatry 5,381,548 6,567 819.48 0 0 0.00

Forensic psychiatry 5,870,962 23,323 251.72 0 0 0.00

Psychotherapy 0 0 0 0 0 0.00

Old age psychiatry 89,429,134 283,489 315.46 12,275 31 395.95

General practice

(other than

maternity) 32,932,711 114,382 287.92 57,778 57 1,013.65

Radiotherapy 11,133,262 25,380 438.66 741,677 2,640 280.94

Pathological

specialities and

radiology 21,514 61 352.68 267,826 951 281.63

Anaesthetics 178,048 309 576.21 4,797,702 4,070 1,178.80

A & E 1,876,009 5,176 362.44 822 3 274.05

Other 544,350 544 1,000.64 0 0 0.00

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outpatient sector

Outpatients

Specialties Net expenditure

(£)

Total

attendances*

Cost per

attendance (£)

Paediatrics 25,242,291 106,384 237.28

Geriatrics 6,622,902 33,450 197.99

Cardiology 13,063,787 133,409 97.92

Dermatology 13,484,477 166,638 80.92

Infectious diseases 61,878 613 100.94

Medical oncology 1,402,934 6,720 208.77

Neurology 5,744,846 33,706 170.44

Rheumatology 15,659,341 101,124 154.85

Gastroenterology 5,996,351 56,029 107.02

Haematology 13,195,306 127,668 103.36

Clinical immunology and allergy 0 0 0.00

Thoracic medicine 6,509,385 59,230 109.90

Genito-urinary medicine 14,008,180 98,371 142.40

Nephrology 7,406,077 41,593 178.06

Rehabilitation medicine 1,192,184 5,577 213.77

Palliative medicine 934,951 2,490 375.48

Other medicine 36,977,576 267,717 138.12

General surgery 24,802,255 124,0719 112.30

Urology 11,578,656 119,883.64 96.58

Orthopaedics 59,998,261 485,758.13 123.51

ENT 17,435,726 136,990.59 127.28

Ophthalmology 26,914,687 36,1374 74.48

Gynaecology 16,372,605 141,861.85 115.41

Dental specialities 13,684,356 90234.36 151.65

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Outpatients


(£)

Total

attendances*

Cost per

attendance (£)

Neuro-surgery 859,003 4,774 179.93

Plastic surgery 2,400,960 23,751 101.09

Cardiothoracic 1,010,776 5,786 174.69

Paediatric surgery 426,479 3,015 141.45

Obstetrics 16,847,079 155,168 108.57

General practice (maternity) 0 0 0

Learning disabilities 749,141 3,741 200.25

Mental illness 16,023,382 107,640 148.86

Child and adolescent psychiatry 10,569,437 60,787 173.88

Forensic psychiatry 64,831 1,319 49.15

Psychotherapy 613,875 3,974 154.47

Old age psychiatry 6,829,338 27,501 248.33

General practice (other than

maternity) 312,946 2611 119.86

Radiotherapy 15,948,452 99833 159.75

Pathological specialities and

radiology 701,265 10959 63.99

Anaesthetics 4,399,749 39622 111.04

Younger Physically Disabled 0 0 0.00

A & E 132,138 1094 120.78

Other 1,618,888 2611 16.34

* Includes new-, follow up and pre-op attendances

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Supplementary Table 3: Read version 2 codes used to identify the presence of co-morbidities amongst

the study population based on Khan et al., 25

Co-morbidities Read version 2 codes

Myocardial infarction G30.., G32.., G35..

Congestive heart failure

G1yz0, G2101, G2111, G21z1, G232., G234., G343.,

G5540, G5541, G554z, G555., G55y0, G55z., G557.,

G558., G58.., Q490.

Peripheral vascular disease G70.., G71.., G7310, G73y., G73z., G761., G717., G73y0,

J5771

Cerebrovascular disease G65.., G660., G661., G662., G663., G664., G665., G666.,

G6…, F4237

Chronic pulmonary disease

G4y.., G4z.., H30.., H310., H311., H313., H31z., H32..,

H3y.., H33.., H34.., H35.., H40.., H41.., H42.., H43..,

H44.., H45.., H450., H464., H4y1., H4y21

Diabetes C10..

Dementia Eu00., Eu01., Eu02., Eu02z, E003., E0011, E0041, F110.,

F112.

Rheumatic disease

N047., N04X., N041., N0421, N040N, N0420, G5yA.,

G5y8., F3964, G011., G010., F3712, N040P, N04y2,

N040Q, N0422, N04.., N200., N0003, N000., N004.,

N003X, N0031, N001., N20.., N0031

Peptic ulcer disease J11.., J12.., J13.., J14..

Mild liver disease

A707., J610., J617., J6120, J612., J613., J6353, J6354,

J6355, J6356, J614z, J61y4, J61y5, J61y6, J6160, J6161,

J616z, J615z, Jyu71, J6151, J61y1, J636., J634., J638.,

J63y0, PB6y9, J61z.,ZV427

Hemiplegia or paraplegia F038., F141., F2301, F231., F22.., F241., F240., F242.,

F243., F244., F245., F246., F24z.

Renal disease

G222., G233., K0A32, K0A33, K0A34, K0A35, K0A36,

K0A37, K03V., K03U., K03X., K03W., K05.., K06.., K080.,

ZV561, ZV560, ZV56y, ZV420, ZV451

Any malignancy

B0..., B1…, B2…, B30.., B32.., B232., B181., B2414,

BBPX., Byu50, Byu51, B61.., B627., B621., B622., B62x0,

B62x1, B62x2, B62xX, B627W, B601., BBg2., ByuDF,

BBmK., BBm6., BBmE., BBmG., B62x5, B630., BBn0.,

B631., B6300, B64.., B65.., B66.., B670., B671., BBrA5,

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BBrA0, B673., B674., BBs1., BBrA6, B675., BBrA7,

B67y0, BBr5., B68.., B625., BBm3., B623., B626., BBp..,

B480., B481., B482., B483., B487., B46.., B47.., B484.,

B485., B486., B48y., B4A0., B4A1., B4A2., B49.., B4A3.,

B4A4., B4Ay0, B4Az., B50.., B521., B523., B52X., B51..,

B522., B525., B520., B52W., B52z., B53.., B540., B541.,

B542., B543., B544., B545., B54X., B54z., B55.., B62x6,

BBm4., B6y.., B62.., B592., B33z0, B05z0, B59zX, B31z0,

B6z0., B592X, B524., B180., B18y., B182., B31.., B34..,

B35.., B451., B452., B453., B54y0, B454., B450., B41..,

B431., B4302, B4303, B4301, B432., B430z, B43z.,

B440., B441., B442., B443., B444., B44y., B44z., B45y.,

B45X., B45z., B42..

Moderate or severe liver disease

G850., G851., G857., G852., J6130, J6357, J637., J623.,

J624.

Metastatic solid tumour B56.., B57.., B58.., B59..

AIDS/HIV

A7890, A7891, A7892, A7893, A7894, AyuC4, A788z,

A7898, A7895, A7896, A7897, A789X, Eu024, A7899,

A789A, A7894

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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cohort studies

Section/Topic Item

# Recommendation Reported on page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 4

Objectives 3 State specific objectives, including any prespecified hypotheses 5

Methods

Study design 4 Present key elements of study design early in the paper 5

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data

collection

5

Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up 5

(b) For matched studies, give matching criteria and number of exposed and unexposed

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable

6-7

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe

comparability of assessment methods if there is more than one group

6-7

Bias 9 Describe any efforts to address potential sources of bias 6-7

Study size 10 Explain how the study size was arrived at 9

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and

why

7

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 7

(b) Describe any methods used to examine subgroups and interactions 7

(c) Explain how missing data were addressed 5

(d) If applicable, explain how loss to follow-up was addressed

(e) Describe any sensitivity analyses 7

Results

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Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed

8-9

(b) Give reasons for non-participation at each stage 9

(c) Consider use of a flow diagram 9

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders

8/10

(b) Indicate number of participants with missing data for each variable of interest 10

(c) Summarise follow-up time (eg, average and total amount)

Outcome data 15* Report numbers of outcome events or summary measures over time 11-15

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence

interval). Make clear which confounders were adjusted for and why they were included

12-13

(b) Report category boundaries when continuous variables were categorized 12

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 16

Discussion

Key results 18 Summarise key results with reference to study objectives 17

Limitations

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from

similar studies, and other relevant evidence

17-19

Generalisability 21 Discuss the generalisability (external validity) of the study results 19

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on

which the present article is based

20

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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Journal: BMJ Open

Manuscript ID: bmjopen-2013-003983.R1

Article Type: Research

Date Submitted by the Author: 10-Jan-2014

Complete List of Authors: Morgan, Kelly; Swansea University, School of Medicine Rahman, Muhammad; Swansea University, School of Medicine Macey, Steven; Swansea University, Institute of Life Sciences Atkinson, Mark; Swansea University, School of Medicine Hill, Rebecca; Swansea University, School of Medicine Khanom, Ashrafunnesa; Swansea University, School of Medicine Paranjothy, Shantini; Cardiff University, School of Medicine Husain, Muhammad; Keele University, Keele Management School

Brophy, Sinead; Swansea University, School of Medicine

<b>Primary Subject Heading</b>:

Public health

Secondary Subject Heading: Health economics, Obstetrics and gynaecology

Keywords: HEALTH ECONOMICS, PUBLIC HEALTH, Maternal medicine < OBSTETRICS


BMJ Open on N

ovember 17, 2020 by guest. P

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jopen.bmj.com

/B

MJ O

pen: first published as 10.1136/bmjopen-2013-003983 on 27 F

ebruary 2014. Dow

nloaded from









2, Mark D






1


2. Institute of Life Sciences, Swansea University, United Kingdom.





Word count: 3315

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Abstract

Objective: To estimate the direct healthcare cost of being overweight or obese throughout

pregnancy to the National Health Service (NHS) in Wales.

Design: Retrospective prevalence-based study.

Setting: Combined linked anonymised electronic datasets gathered on a cohort of women

enrolled on the Growing Up in Wales: Environments for Healthy Living (EHL) study.

Women were categorised into two groups: normal BMI (n=260) and overweight/obese

(BMI>25) (n=224).

Participants: 484 singleton pregnancies with available health service records and an

antenatal BMI.

Primary outcome measure: Total health service utilisation (comprising all General Practice

(GP) visits and prescribed medications, inpatient admissions and outpatient visits) and direct

healthcare costs for providing these services in the year 2011-2012. Costs are calculated as

cost of mother (no infant costs are included) and are related to health service usage

throughout pregnancy and two months following delivery.

Results: There was a strong association between health care usage cost and BMI (p<0.001).

Adjusting for maternal age, parity, ethnicity and co-morbidity, mean total costs were 23%

higher amongst overweight women (RR, 1.23; 95% CI, 1.230-1.233) and 37% higher

amongst obese women (RR, 1.39; 95% CI, 1.38-1.39) compared to women with normal

weight. Adjusting for smoking, consumption of alcohol, or the presence of any co-



Conclusions: Increased health service usage and healthcare costs during pregnancy are

associated with increasing maternal BMI; this was apparent across all health services

considered within this study. Interventions costing less than £1171.34 per person could be

cost-effective if they reduce healthcare usage amongst obese pregnant women to levels

equivalent to that of normal weight women.

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ARTICLE SUMMARY

Article focus


throughout the course of pregnancy and 2 months post-partum.




the study.

Key messages

• After adjusting for multiple confounding factors (e.g. age, ethnicity and parity),


hospital services.

• Overweight and obese women cost on average an additional £698.1 and £1171.34

respectively when comparing total health service costs with those of normal weight

women.


• Study strengths include the ability to control for potential confounders and co-

morbidities at the patient level, and the use of medically recorded early-pregnancy

BMI.

• Limitations of this study include the use of a BMI value recorded at a single time

point, challenges presented when quantifying health service utilisation, and the

disregard of indirect and intangible health service costs.

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BACKGROUND


women being obese during pregnancy. Varying considerably across nations, rates of maternal

obesity range from 1 in 15 women living in Wales to lower proportions of 1 in 29 women in

London 1. Associated with increasing problems throughout pregnancy

2, delivery

complications 3-5 and poor neonatal outcomes

6 7, maternal obesity is currently one of the

biggest challenges presented to maternity services in the UK 1. In a qualitative study in the

UK, health professionals noted that obese expectant mothers and offspring required

significantly higher levels of care 8. Accompanying increasing health service utilisation, cost

repercussions are also eminent amongst the obese population. Cost-of-illness studies provide

a tool for quantifying this economic burden and estimate the total cost savings which would

ensue if obesity was absent 9.









2)

11. A



modelling or database analyses and, despite varying methodologies, all 32 studies were in






of aggregate level data 13. Thus there is a need for higher quality UK-based studies, as

highlighted by the Centre for Maternal and Child Enquiries (CMACE) report 1.




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pregnancies 16. A recent study compared healthcare costs (including those related to neonatal

care) between women with and without gestational diabetes mellitus (GDM), of whom all

had a BMI greater than or equal to 25 kg/m² 17.Adjusting for age, education and BMI, the

authors reported greater inpatient costs (44% higher) amongst those women with GDM.

Based on participants’ from a Finnish prevention trial, the authors emphasise that they cannot

rule out any potential intervention effects on healthcare use.


health service utilisation and resultant economic implications. The current challenging

economic climate calls for careful management of healthcare funds 18. Interventions are

therefore needed to examine the effect of reducing healthcare use amongst women presenting

with a BMI above normal. Previously described as a ‘powerful motivator’, pregnancy could

represent the optimal time for the adoption of positive lifestyle choices and ultimately impact

maternal and offspring health and well being 19. Accurately identifying the cost of healthcare

usage by overweight and obese women during pregnancy shall enable future interventions to

efficiently devise cost effective methods targeting maternal obesity whilst reducing

associated NHS costs. No UK-based study to date has comprehensively analysed the costs to

the National Health Service (NHS) associated with overweight and obesity during pregnancy.

The aim of this paper is to investigate health service utilisation and accompanying costs

amongst normal weight and overweight/obese pregnant women. Direct healthcare costs

associated with general practice (GP) visits and prescriptions, inpatient admissions and

outpatient visits shall be calculated to provide a descriptive account of healthcare use. Our

hypothesis is that overweight/obese women have higher health service utilisation and

accompanying costs during pregnancy in comparison to normal weight women. This

difference in cost could be used to inform the amount that could be spent on public health

initiatives and still be cost saving.

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Study sample


the ‘Growing Up in Wales: Environments for Healthy Living’ birth cohort study (EHL) 20.

All pregnant women aged 16 and older receiving antenatal care (during the period 2010-

2013) through the Abertawe Bro Morgannwg University (ABMU) NHS Board were eligible

to participate in the cohort. Providing health services for a population of 500,000 individuals,

ABMU NHS Board is the largest health board in Wales comprising of 18 hospitals and 77 GP

clinics. A more in-depth description of the study population has previously been described

elsewhere20. Briefly, each participant completed a questionnaire during pregnancy providing

information on age, ethnicity, education level, socioeconomic status, cigarette smoking and

alcohol consumption. Table 1 outlines all study variables and the source from which they

were obtained.

Exclusion criteria for the present study were; non-singleton pregnancies, incomplete

pregnancies, mothers without a recorded BMI in the antenatal records, mothers with pre-

existing diabetes, mothers with cancer and mothers not registered with a GP for longer than a

year preceding the study period.

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Table 1. Study variables and data sources

Variable Source Levels

Age at delivery Antenatal maternity notes 18-44, mean = 29.5

Ethnicity Study questionnaire White/European (91.1%),

African/Caribbean (1.1%), Asian (3.9%)

or other (3.9%)

Smoking status Study questionnaire Yes (18.8%) or No (81.2%)

Alcohol consumption Study questionnaire Yes (38.9%) or No (61.1%)

Employment Study questionnaire Full time (42.3%), Part-time (24.5%),

Unemployed (11.5%), Homemaker

(15%), Student (2.5%), Self-employed

(2.2%) and Other (2%)

Annual household income Study questionnaire £0 to £9,999 (10.4%), £10,000 to

£14,999 (10.4%), £15,000 to £24, 999

(15.9%), £25,000 to £34,999 (12.9%),

£35,000 to £39,999 (9.2%), £40,000 to

£49,999 (15.1%), £50,000 to £99,999

(18.4%), £100,000+ (2%) and don’t

know (5.7%)

Parity

Study questionnaire

0-4, mean = 0.8

Early pregnancy BMI Antenatal maternity notes Overweight/Obese (BMI> 25 kg/m²,

46.2%), or Normal (53.8%)

Non- specific psychological

distress

Study questionnaire 0-24, mean = 4.2 (Kessler 6 scale)

Co-morbidities (within 3 years

prior to conception)

Primary care dataset Charlson Index (see Supplementary

Table 1)

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BMI categories





2) (n=224).



University 21, routinely collected electronic medical records were used to establish health

service utilisation throughout the course of pregnancy and two months post delivery. Data

concerning health service use (i.e. diagnoses, medications, investigations and results) are

coded within the databank using Read codes, the standard terminology system used in the UK

22. Only Read codes relating to the healthcare of the mother were included. The Primary Care

dataset within SAIL provided the total number of visits to a general practice (GP) for each

participant over the defined time period and all records of any prescribed medications. The

methodology adopted to calculate the total number of visits to a GP was to: 1) count a record

as a visit to the GP if two Read codes were present on the same day, 2) count only one visit

per day (i.e. if there was more than one record of an event on the same day, only one GP visit

was counted) and 3) exclude all Read codes relating to medications (indicated by GP Read

codes starting with small letters a-z). The Patient Episode Database for Wales (PEDW) was

searched for inpatient admissions, inpatient durations, and outpatient visits. For each visit

record a distinct event was used e.g. if more than one outpatient record was recorded on the

same date, only one event was used in the analyses.

Economic analysis




concern health service utilisation associated with the mother only. Costs concerning inpatient

and outpatient utilisation are extracted from the Welsh Costing Return (WCR) 2011-2012 in

which costings are fully inclusive of any treatments, medications and operations, which may

occur during a patient event and are aggregated by specialty type23. Unit Costs of Health and

Social Care 2011 provided a unit cost for each GP visit 24. For the purpose of this study,

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applied unit costs were based on a clinic consultation lasting 17.2 minutes (including direct

care staff costs and qualifications). Costs of prescription drugs were determined by the British

National Formulary (BNF) November 2011 25 applying specific costs for each medication

Read code. Costs were not included in cases where medications referred to the treatment of

infants, and Read codes not specifying medication dose were assigned the lowest unit price.

Co-morbidities



located in supplementary table 1. A time scale of 3 years prior to the date of conception was

used to identify co-morbidities.










women with existing co-morbidities may require greater need for surveillance during


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RESULTS

Demographics

Of the total cohort population, 484 (66.9%) women met the inclusion criteria and were












existing co-morbidity or non-specific psychological distress between the two groups.

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Table 2. Characteristics of study participants by BMI (presented as number (%))



(N= 260) (N= 224 )


18-19 8 (3.1) 8 (3.6)

20-25 51 (19.8) 37 (16.6)

26-30 70 (27.1) 66 (29.6)

31-35 66 (25.6) 49 (22)

36-40 56 (21.7) 54 (24.2)

>40 7 (2.7) 9 (4)


White/European 223 (91.4) 185 (90.7)


Asian 10 (4.1) 8 (4)

Other 10 (4.1) 7 (3.4)


£0 to £9,999 18 (8.6) 24 (12.5)

£10,000 to £14,999 20 (9.5) 22 (11.4

£15,000 to £24, 999 32 (15.2) 32 (16.6)

£25,000 to £34,999 30 (14.3) 22 (11.4)

£35,000 to £39,999 20 (9.5) 16 (8.8)

£40,000 to £49,999 29 (13.8) 32 (16.6)

£50,000 to £99,999 45 (21.4) 29 (15)

£100,000+ 6 (2.9) 2 (1)

Don't know 10 (4.8) 13 (6.7)


Full-Time 115 (46.8) 78 (37.3)


Unemployed 28 (11.4) 24 (11.5)

Homemaker 36 (14.6) 32 (15.3)

Student 9 (3.7) 3 (1.5)


Other 4 (1.6) 5 (2.4)

Parity (n= 484)

0 141 (54.2) 81 (36.2)

1 82 (31.5) 96 (42.9)

2 24 (9.2) 29 (12.9)

>3 13 (5.1) 18 (8)


Smoker (n=409) 49 (20.2) 35 (17.1)


Non-specific psychological distress

score* >12 (n=449) 20 (51.3) 19 (48.7)

*based on a Kessler 6 score recorded during pregnancy

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Following adjustment for confounding factors (age, ethnicity and parity), the usage rate of all

healthcare services was higher for women in the overweight group compared to the normal

weight group (Table 3). Specifically, the overweight group experienced an 18% higher rate of

inpatient visits and a 36% higher rate of inpatient duration. Examining GP data, a 17% higher

visit rate and 14% higher prescription of medications were shown. Examining the type of

inpatient specialties accessed revealed no significant differences between groups. The

majority of visits for both groups were shown across maternity services (93.7% for normal

BMI vs. 90.2% for overweight and obese) whilst the overweight-obese group presented

higher numbers of medical specialty visits (6.3% vs. 3.7%). Further adjusting for smoking

and alcohol consumption did not result in a noticeable change to the adjusted (age, ethnicity

and parity) findings.

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Inpatient visits adjusted for




Parity 0.99 0.9-1.0

Inpatient days adjusted for

Overweight 1.36 1.24 - 1.48


Ethnicity 1. 01 1.0-1.0

Parity 0.9 0.9-0.9

Outpatient visits adjusted for




Parity 1 1.0-1.1

GP visits adjusted for




Parity 0.97 0.9-1.0

Medication adjusted for




Parity 1.1 1.1-1.1

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Cost evaluation



breakdown of mean costs for each health service, revealing that all mean total costs were

greater among those women with a BMI of 25 or more.



40kg/m2) women (Table 5, model 1). In comparison to participants with a normal BMI,







Table 6 shows the mean total cost for each BMI category calculated using 1) inpatient costs

2) outpatient costs 3) cost of GP visits and 4) cost of medications prescribed by the GP. As

shown obese women cost a mean total of £1,172 (p=0.01) more than the normal weight

group. Overweight women also had a higher mean total cost in comparison to normal weight

women, however this finding was not statistically significant.

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Table 4. Relative rates of Total Health Service costs with BMI (£s/11 month)

Health service Normal BMI Ψ Overweight plus

BMI 18.5 - 24.9 BMI >24.9

Inpatient 2644 (144.3) 1.27 (1.26-1.27)

Outpatient 345 (29) 1.17 (1.16-1.18)

GP 692 (25.96) 1.10 (1.09-1.11)

Medication 9 (0.8) 1.16 (1.09-1.23)

Total costs 4003 (184) 1.20 (1.19-1.20)







Normal BMI

BMI<25

Overweight

24.9< BMI <30

Obese

BMI >30

Total mean cost (£) 3546 4244 4718

95%CI (3238.6-3854.0) (3647.7-4841.0) (4038.5-5396.8)*


RR (95%CI) RR (95%CI)

<25 1 1

25-29.9 1.23 (1.230-1.233) 1.23 (1.22-1.23)

>29.9 1.37 (1.37-1.38) 1.39 (1.38-1.39)

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DISCUSSION








service cost in comparison to normal BMI counterparts. We found a 23% and 39% increase

in total health service costs for overweight and obese women respectively. Amongst our

study population this equated to an extra £698 for overweight and £1172 for obese women

when compared to costs accrued by women with a normal BMI.


approximately 15-20% greater healthcare usage of all hospital services, a 30% higher mean

number of days spent in hospital, and a 10% higher mean usage of GP services.

Consequently, the overweight and obese women accrued higher costs through generic use of

healthcare services, not through one particular area of health service. Given the variety of

methodologies used by previous studies it is difficult to directly compare our findings,

however previous studies also highlight increasing health service usage and/or healthcare

costs according to increasing maternal BMI 14-16 28 29

. One prospective case-control study

reported average prenatal care costs as 5 times higher for women who were overweight











complications.

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confounders such as age, socio demographic variables, smoking status, alcohol consumption

and co-morbidities through data collection at the patient level. This enabled us to exclude one

participant with a record of cancer within the three years preceding conception. Often studies

using self-reported information have shown an underestimation when reporting chronic

conditions 35. A further strength of this study is the use of medically recorded BMI values.

As frequent misclassification especially amongst overweight and obese women has been

documented when using self-reported BMI measures 36 we have been able to minimise

uncertainty associated with recall-bias.













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onset of obesity 41. It is important to note that there is no standard costing system used

throughout the UK NHS and as such the unit costs applied as part of this study merely reflect

an average of the resource costs borne in Wales over a certain period. This creates great

difficulty when trying to deduce actual resource utilisation at an individual hospital episode

level, and means that the unit costs used here may differ from those reported elsewhere in the

UK NHS. Nonetheless, the unit costs from the WCR accounts used throughout this study are

validated annually during the completion of the Welsh Benchmarking Summary (WBS),

providing a robust costing methodology.




















(812,920) and applying the findings from this study, an additional £144,818,105 would have

been spent on health care services for obese women during an 11 month period. This amount

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of capital could become cost-effective if utilised to fund public health interventions targeting

maternal lifestyle and subsequently reduce the health care usage of obese women. Future

planned work within the cohort population described shall investigate the reasons why

overweight and obese women accrue higher rates of health service use and accompanying

costs, with specific focus on the specialties accessed and timing of usage.


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Acknowledgments





work is also part of the ‘Growing Up in Wales: EHL’ study.

Funding

This work was funded by the Swansea University and NISCHR

Author Contribution






Competing Interests

None

Data Sharing Statement

Data are stored within the Secure Anonymised Information Linkage (SAIL) databank at the

Health Information Research Unit (HIRU) at Swansea University. All proposals to use SAIL

datasets must comply with HIRU’s Information Governance policy.

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References





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8. Heslehurst N, Lang R, Rankin J, et al. Obesity in pregnancy: a study of the impact of maternal

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Healthy Living (EHL) Wales cohort study. BMC Public Health, 2010:1-8.

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WCR1 Costing Returns. Wales, 2012.


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29. Denison FC, Norrie G, Graham B, et al. Increased maternal BMI is associated with an increased

risk of minor complications during pregnancy with consequent cost implications. BJOG: An

International Journal of Obstetrics & Gynaecology 2009;116(11):1467-72.

30. Athukorala C, Rumbold AR, Willson KJ, et al. The risk of adverse pregnancy outcomes in women

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2, Mark D






1


2. Institute of Life Sciences, Swansea University, United Kingdom.





Word count: 3315

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Abstract

Objective

To estimate the direct healthcare cost of being overweight or obese during early pregnancy to

the National Health Service (NHS) in Wales. Costs are calculated as cost of mother (no infant

costs are included) and are related to health service usage throughout pregnancy and two

months following delivery.

Design

We applied a retrospective prevalence-based study of a cohort of pregnant women by

combining linked anonymised electronic datasets of 484 individuals enrolled on the

‘Growing Up in Wales: Environments for Healthy Living’ (EHL) study. Using antenatal

booking (at 12 weeks gestation) body mass index (BMI), women were categorised into two

groups: normal BMI (n=260) and overweight/obese (BMI>25) (n=224). Health service

utilisation comprised all General Practice (GP) visits, prescribed medications, inpatient

admissions and outpatient visits. Direct healthcare costs for providing these services over an

11 month period occurring 2011-2012 were calculated.

Results

There was a strong association between health care usage cost and early-pregnancy BMI

(p<0.001). Adjusting for maternal age, parity, ethnicity and co-morbidity, mean total costs

were 23% higher amongst overweight women (RR, 1.23; 95% CI, 1.230-1.233) and 37%

higher amongst obese women (RR, 1.39; 95% CI, 1.38-1.39) compared to women with

normal weight. Adjusting for smoking, consumption of alcohol, or the presence of any co-



Conclusion

Increased health service usage and healthcare costs during pregnancy are associated with

increasing maternal BMI; this was apparent across all health services considered within this

study. Interventions costing less than £1171.34 per person could be cost-effective if they

reduce healthcare usage amongst obese pregnant women to levels equivalent to that of

normal weight women.

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ARTICLE SUMMARY

Article focus


throughout the course of pregnancy and 2 months post-partum.




the study.

Key messages

• After adjusting for multiple confounding factors (e.g. age, ethnicity and parity),


hospital services.

• Overweight and obese women cost on average an additional £698.1 and £1171.34

respectively when comparing total health service costs with those of normal weight

women.


• Study strengths include the ability to control for potential confounders and co-

morbidities at the patient level, and the use of medically recorded early-pregnancy

BMI.

• Limitations of this study include the use of a BMI value recorded at a single time

point, challenges presented when quantifying health service utilisation, and the

disregard of indirect and intangible health service costs.

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BACKGROUND


women being obese during pregnancy. Varying considerably across nations, rates of

maternal obesity range from Across the nations rates vary from 1 in 15 women living in

Wales to lower proportions of 1 in 29 women in London 1. Associated with increasing

problems throughout pregnancy 2, delivery complications

3-5 and poor neonatal outcomes

6 7,

maternal obesity is currently one of the biggest challenges presented to maternity services in

the UK 1. In a qualitative study in the UK, health professionals noted that obese expectant

mothers and offspring required significantly higher levels of care 8. Accompanying increasing

health service utilisation, cost repercussions are also eminent amongst the obese population.

Cost-of-illness studies provide a tool for quantifying this economic burden and estimate the

total cost savings which would ensue if obesity was absent 9.









2)

11. A



modelling or database analyses and, despite varying methodologies, all 32 studies were in






of aggregate level data 13. Thus there is a need for higher quality UK-based studies, . as

highlighted by the Centre for Maternal and Child Enquiries (CMACE) report 1.




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pregnancies 16. A recent study compared healthcare costs (including those related to neonatal

care) between women with and without gestational diabetes mellitus (GDM), of whom all

had a BMI greater than or equal to 25 kg/m² 17.Adjusting for age, education and BMI, the

authors reported greater inpatient costs (44% higher) amongst those women with GDM.

Based on participants’ from a Finnish prevention trial, the authors emphasise that they cannot

rule out any potential intervention effects on healthcare use. As highlighted by the Centre for

Maternal and Child Enquiries (CMACE) report 1, there is currently a paucity of data on the

cost of maternal overweight and obesity in the UK.


health service utilisation and resultant economic implications. The current challenging

economic climate calls for careful management of healthcare funds 18. Interventions are

therefore needed to examine the effect of reducing healthcare use amongst women presenting

with a BMI above normal. Previously described as a ‘powerful motivator’, pregnancy could

represent the optimal time for the adoption of positive lifestyle choices and ultimately impact

maternal and offspring health and well being 19. Accurately identifying the cost of healthcare

usage by overweight and obese women during pregnancy willshall enable future

interventions to efficiently devise cost effective methods targeting maternal obesity whilst

reducing associated NHS costs. No UK-based study to date has comprehensively analysed

the costs to the National Health Service (NHS) associated with overweight and obesity during

pregnancy. The aim of this paper is to investigate health service utilisation and accompanying

costs amongst normal weight and overweight/obese pregnant women. Direct healthcare costs

associated with general practice (GP) visits and prescriptions, inpatient admissions and

outpatient visits shall be calculated to provide a descriptive account of healthcare use. Our

hypothesis is that overweight/obese women have higher health service utilisation and

accompanying costs during pregnancy in comparison to normal weight women. This

difference in cost could be used to inform the amount that could be spent on public health

initiatives and still be cost saving.

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Study sample


the ‘Growing Up in Wales: Environments for Healthy Living’ birth cohort study (EHL) 20.

All pregnant women aged 16 and older receiving antenatal care (during the period 2010-

2013) through the Abertawe Bro Morgannwg University (ABMU) NHS Board were eligible

to participate in the cohort. Providing health services for a population of 500,000 individuals,

ABMU NHS Board is the largest health board in Wales comprising of 18 hospitals and 77 GP

clinics's. We excluded non-singleton pregnancies, mothers without a recorded BMI in the

antenatal records, mothers with pre-existing diabetes and mothers not registered with a GP

for longer than a year preceding the study period. A more in-depth description of the study

population has previously been described elsewhere20. Briefly, each participant completed a

questionnaire during pregnancy providing information on age, ethnicity, education level,

socioeconomic status, cigarette smoking and alcohol consumption. Table 1 outlines all study

variables and the source from which they were obtained.

Exclusion criteria for the present study were; non-singleton pregnancies, incomplete

pregnancies, mothers without a recorded BMI in the antenatal records, mothers with pre-

existing diabetes, mothers with cancer and mothers not registered with a GP for longer than a

year preceding the study period.

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Table 1. Study variables and data sources

Variable Source Levels

Age at delivery Antenatal maternity notes 18-44, mean = 29.5

Ethnicity Study questionnaire White/European (91.1%),

African/Caribbean (1.1%), Asian (3.9%)

or other (3.9%)

Smoking status Study questionnaire Yes (18.8%) or No (81.2%)

Alcohol consumption Study questionnaire Yes (38.9%) or No (61.1%)

Employment Study questionnaire Full time (42.3%), Part-time (24.5%),

Unemployed (11.5%), Homemaker

(15%), Student (2.5%), Self-employed

(2.2%) and Other (2%)

Annual household income Study questionnaire £0 to £9,999 (10.4%), £10,000 to

£14,999 (10.4%), £15,000 to £24, 999

(15.9%), £25,000 to £34,999 (12.9%),

£35,000 to £39,999 (9.2%), £40,000 to

£49,999 (15.1%), £50,000 to £99,999

(18.4%), £100,000+ (2%) and don’t

know (5.7%)

Parity

Study questionnaire

0-4, mean = 0.8

Early pregnancy BMI Antenatal maternity notes Overweight/Obese (BMI> 25 kg/m²,

46.2%), or Normal (53.8%)

Non- specific psychological

distress

Study questionnaire 0-24, mean = 4.2 (Kessler 6 scale)

Co-morbidities (within 3 years

prior to conception)

Primary care dataset Charlson Index (see Supplementary

Table 1)

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BMI categories





2) (n=224).



University 21, rroutinely collected electronic medical records were used to establish health

service utilisation throughout the course of pregnancy and two months post delivery. Data

concerning health service use (i.e. diagnoses, medications, investigations and results) are

coded within the databank using Read codes, the standard terminology system used in the UK

22. Only Read codes relating to the healthcare of the mother were included. The Primary Care

dataset within SAIL provided the total number of visits to a general practice (GP) for each

participant over the defined time period and all records of any prescribed medications. The

methodology adopted to calculate the total number of visits to a GP was to: 1) count a record

as a visit to the GP if two Read codes were present on the same day, 2) count only one visit

per day (i.e. if there was more than one record of an event on the same day, only one GP visit

was counted) and 3) exclude all Rread codes relating to medications (indicated by GP Read

codes starting with small letters a-z). The Patient Episode Database for Wales (PEDW) was

searched for inpatient admissions, inpatient durations, and outpatient visits. For each visit

record a distinct event was used e.g. if more than one outpatient record was recorded on the

same date, only one event was used in the analyses.

Economic analysis




concern health service utilisation associated with the mother only. Costs concerning inpatient

and outpatient utilisation are extracted from the Welsh Costing Return (WCR) 2011-2012 in

which costings are fully inclusive of any treatments, medications and operations, which may

occur during a patient event and are aggregated by specialty type23. Supplementary tables 1

and 2 outline cost sources and exact values applied to each inpatient and outpatient event

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respectively based on specialty Read codes. Unit Costs of Health and Social Care 2011

provided a unit cost for each GP visit 24. For the purpose of this study, applied unit costs were

based on a clinic consultation lasting 17.2 minutes (including direct care staff costs and

qualifications). Costs of prescription drugs were determined by the British National

Formulary (BNF) November 2011 25 applying specific costs for each medication Read code.

Costs were not included in cases where medications referred to the treatment of infants, and

Read codes not specifying medication dose were assigned the lowest unit price.

Co-morbidities



complete list of all co-morbidities and accompanying Read version 2 codes (provided by

Khan et al., 27) are located in supplementary table 13. A time scale of 3 years prior to the date

of conception was used to identify co-morbidities.










women with existing co-morbidities may require greater need for surveillance during


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RESULTS

Demographics

Of the total cohort population, 484 (66.9%) women met the inclusion criteria and were












existing co-morbidity or non-specific psychological distress between the two groups.

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Cohort participants

N= 724

Exclusions

Non-singleton pregnancies N= 9 (1.2 %)

Incomplete pregnancies N= 109 (15.1%)

No maternal BMI available N= 121

(16.7%)

Record of cancer N=1 (0.1%)

Total mother-child pairs

N= 484

Women with a BMI<25kg/m2

N= 260

Women with a BMI> 25 kg/m2

N= 224

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Table 21. Characteristics of study participants by BMI (presented as number (%))



(N= 260) (N= 224 )


18-19 8 (3.1) 8 (3.6)

20-25 51 (19.8) 37 (16.6)

26-30 70 (27.1) 66 (29.6)

31-35 66 (25.6) 49 (22)

36-40 56 (21.7) 54 (24.2)

>40 7 (2.7) 9 (4)


White/European 223 (91.4) 185 (90.7)


Asian 10 (4.1) 8 (4)

Other 10 (4.1) 7 (3.4)


£0 to £9,999 18 (8.6) 24 (12.5)

£10,000 to £14,999 20 (9.5) 22 (11.4

£15,000 to £24, 999 32 (15.2) 32 (16.6)

£25,000 to £34,999 30 (14.3) 22 (11.4)

£35,000 to £39,999 20 (9.5) 16 (8.8)

£40,000 to £49,999 29 (13.8) 32 (16.6)

£50,000 to £99,999 45 (21.4) 29 (15)

£100,000+ 6 (2.9) 2 (1)

Don't know 10 (4.8) 13 (6.7)


Full-Time 115 (46.8) 78 (37.3)


Unemployed 28 (11.4) 24 (11.5)

Homemaker 36 (14.6) 32 (15.3)

Student 9 (3.7) 3 (1.5)


Other 4 (1.6) 5 (2.4)

Parity (n= 484)

0 141 (54.2) 81 (36.2)

1 82 (31.5) 96 (42.9)

2 24 (9.2) 29 (12.9)

>3 13 (5.1) 18 (8)


Smoker (n=409) 49 (20.2) 35 (17.1)


Non-specific psychological distress

score* >12 (n=449) 20 (51.3) 19 (48.7)

*based on a Kessler 6 score recorded during pregnancy

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The average number of inpatient admissions and outpatient visits (adjusted for age)

significantly varied between the two groups, with higher rates in the overweight group (Table

2). There was a general trend amongst each health service of utilisation rates increasing with

age of the participant. All healthcare services with the exception of outpatient visits revealed

a reduced rate of usage amongst the overweight group in the youngest age category (18-20

years), however this was not significant for inpatient days. Following adjustment for

confounding factors (age, ethnicity and parity), the usage rate of all healthcare services was

higher for women in the overweight group compared to the normal weight group (Table 3).

Specifically, the overweight group experienced an 18% higher rate of inpatient visits and a

36% higher rate of inpatient duration. Examining GP data, a 17% higher visit rate and 14%

higher prescription of medications were shown. Examining the type of inpatient specialties

accessed revealed no significant differences between groups. The majority of visits for both

groups were shown across maternity services (93.7% for normal BMI vs. 90.2% for

overweight and obese) whilst the overweight-obese group presented higher numbers of

medical specialty visits (6.3% vs. 3.7%). Further adjusting for smoking and alcohol

consumption did not result in a noticeable change to the adjusted (age, ethnicity and parity)

findings.

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Table 2. Use of Healthcare Services in relation to BMI and type of service (average use

throughout an 11 month period)


BMI 18.5 - 24.9 BMI >24.9

Inpatient visits

18-19 4.1 (1.12) 0.52 (0.29-0.92)

20-25 2.1 (0.22) 1.54 (1.19-2.01)

26-30 2.49(0.19) 1.16 (0.94-1.42)

31-35 2.65 (0.30) 1.08 (0.86-1.35)

36-40 2.91 (0.34) 1.20 (0.98-1.48)

>40 3 (0.85) 1.07 (0.61-1.88)

All 2.63 (0.14) 1.16 (1.04-1.29)

Inpatient days

18-19 6.5 (1.86) 0.71 (0.47-1.08)

20-25 3.49 (0.40) 1.4 (1.14-1.72)

26-30 4.13 (0.47) 1.38 (1.18-1.61)

31-35 4.29 (0.46) 1.14 (0.96-1.35)

36-40 4.79 (0.56) 1.39 (1.19-1.63)

>40 4.85 (0.70) 1.24 (0.80-1.90)

All 4.3 (0.23) 1.29 (1.19-1.4)

Outpatient visits

18-19 2 (0.80) 2.19 (1.21-3.95)

20-25 3.12 (0.46) 0.75 (0.57-0.97)

26-30 3.11 (0.62) 1.32 (1.10-1.58)

31-35 2.72 (0.39) 1.09 (0.87-1.35)

36-40 3.34 (0.51) 1.07 (0.88-1.31)

>40 2.43 (1.7) 1.97 (1.12-3.45)

All 3.01 (0.24) 1.17 (1.06-1.29)

GP visits

18-19 16 (1.95) 0.76 (0.57-1.01)

20-25 12.94 (0.99) 0.90 (0.78-1.03)

26-30 13.72 (1.08) 1.22 (1.11-1.35)

31-35 12.81 (0.99) 0.96 (0.85-1.08)

36-40 12.43 (1.02) 1.16 (1.04-1.30)

>40 12.14 (2.90) 1.48 (1.14-1.93)

All 13.04 (0.49) 1.10 (1.04-1.16)

Medication counts

18-19 6.88 (1.38) 0.56 (0.36-0.88)

20-25 7.95 (1.37) 0.73 (0.61-0.86)

26-30 8.35 (1.54) 1.28 (1.13-1.43)

31-35 7.98 (1.18) 1.49 (1.31-1.69)

36-40 9.8 (2.11) 1.15 (1.02-1.29)

>40 4.8 (1.98) 2.99 (1.93-4.62)

All 8.40 (0.74) 1.20 (1.13-1.28)



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Inpatient visits adjusted for




Parity 0.99 0.9-1.0

Inpatient days adjusted for

Overweight 1.36 1.24 - 1.48


Ethnicity 1. 01 1.0-1.0

Parity 0.9 0.9-0.9

Outpatient visits adjusted for




Parity 1 1.0-1.1

GP visits adjusted for




Parity 0.97 0.9-1.0

Medication adjusted for




Parity 1.1 1.1-1.1

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Cost evaluation



breakdown of mean costs for each health service and each age category. As shown, the

overweight women aged 18-20 years had a considerably lower mean total cost (42% less). In

women age 20 and over, service, revealing that all mean total costs were greater among those

women with a BMI of 25 or more.



40kg/m2) women (Table 5, model 1). In comparison to participants with a normal BMI,







Table 6 shows the mean total cost for each BMI category calculated using 1) inpatient costs

2) outpatient costs 3) cost of GP visits and 4) cost of medications prescribed by the GP. As

shown revealing that obese women cost a mean total of £1,1721.24 (p=0.01) more than the

normal weight group. Overweight women also had a higher mean total cost in comparison to

normal weight women, however this finding was not statistically significant.

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Table 4. Relative rates of Total Health Service costs with BMI, by age (£’s/11 month)


BMI 18.5 - 24.9 BMI >24.9

Inpatient costs

18-19 3723.1 (3120) 0.75 (0.7-0.8)

20-25 2207 (1680) 1.31 (1.3-1.32)

26-30 2502.3 (2462.4) 1.4 (1.39-1.41)

31-35 2742.4 (2115.6) 1.1 (1.1-1.1)

36-40 2866.7 (2424.3) 1.33 (1.32-1.34)

>40 2845.9 (1142.6) 1.4 (1.38-1.43)

All 2644.09 (144.3) 1.27 (1.26-1.27)

Outpatient costs

18-19 361.1 (235.1) 2.23 (2.11-2.36)

20-25 459.1 (362.2) 0.74 (0.72-0.75)

26-30 585 (712.2) 1.32 (1.30-1.34)

31-35 462 (357.7) 1.10 (1.10-1.12)

36-40 534 (462) 1.05 (1.03-1.07)

>40 963.9 (403.2) 1.98 (1.87-2.08)

All 344.97 (29) 1.17 (1.16-1.18)

GP costs

18-19 848 (103.1) 0.76 (0.73-0.79)

20-25 685.8 (52.4) 0.90 (0.88-0.92)

26-30 727.1 (57.3) 1.22 (1.21-1.24)

31-35 678.7 (52.7) 0.96 (0.94-0.98)

36-40 659 (54.0) 1.16 (1.15-1.18)

>40 643.6 (153.6) 1.48 (1.43-1.54)

All 691.6(25.96) 1.10 (1.09-1.11)

Medication costs

18-19 6.8 (1.3) 0.77 (0.49-1.19)

20-25 8.4 (1.4) 0.70 (0.58-0.82)

26-30 9.3 (1.6) 1.20 (1.07-1.34)

31-35 8.5 (1.2) 1.46 (1.28-1.65)

36-40 10.1 (2.2) 1.09 (0.97-1.23)

>40 6 (2.0) 2.54 (1.64-3.93)

All 8.95 (0.8) 1.16 (1.09-1.23)

Total costs

18-19 4803.6 (1170.90) 0.79 (0.77-0.80)

20-25 3093.77 (286.54) 1.15 (1.14-1.16)

26-30 3497.89 (338.65) 1.36 (1.35-1.36)

31-35 3487.41 (296.0) 1.0 (1.0-1.01)

36-40 3838.6 (351.88) 1.21 (1.20-1.22)

>40 3768.25 (446.40) 1.34 (1.32-1.36)

All 4003.62 (184) 1.20 (1.19-1.20)



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Table 4. Relative rates of Total Health Service costs with BMI (£s/11 month)

Health service Normal BMI Ψ Overweight plus

BMI 18.5 - 24.9 BMI >24.9

Inpatient 2644 (144.3) 1.27 (1.26-1.27)

Outpatient 345 (29) 1.17 (1.16-1.18)

GP 692 (25.96) 1.10 (1.09-1.11)

Medication 9 (0.8) 1.16 (1.09-1.23)

Total costs 4003 (184) 1.20 (1.19-1.20)







Normal BMI

BMI<25

Overweight

24.9< BMI <30

Obese

BMI >30

Total mean cost (£) 3546.3 4244.4 47187.6

95%CI (3238.6-3854.0) (3647.7-4841.0) (4038.5-5396.8)*


RR (95%CI) RR (95%CI)

<25 1 1

25-29.9 1.23 (1.230-1.233) 1.23 (1.22-1.23)

>29.9 1.37 (1.37-1.38) 1.39 (1.38-1.39)

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DISCUSSION








service cost in comparison to normal BMI counterparts. Specifically wWe found a 23% and

39% increase in total health service costs for overweight and obese women respectively.

Amongst our study population this equated to an extra £698.1 for overweight and £11721.34

for obese women when compared to costs accrued by women with a normal BMI.


approximately 15-20% greater healthcare usage of all hospital services, a 30% higher mean

number of days spent in hospital, and a 10% higher mean usage of GP services.

Consequently, the overweight and obese women accrued higher costs through generic use of

healthcare services, not through one particular area of health service. Given the variety of

methodologies used by previous studies it is difficult to directly compare our findings,

however previous studies also highlight increasing health service usage and/or healthcare

costs according to increasing maternal BMI 14-16 28 29

. One prospective case-control study

reported average prenatal care costs as 5 times higher for women who were overweight











complications. Our finding that overweight/obese women under the age of 20 years accrued

less health care costs than normal weight women warrants further investigation to confirm

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and explore this association, given the small number of women in our sample in this age

group.
















confounders such as age, smoking status, socio demographic variables, smoking status,

alcohol consumption and co-morbidities through data collection at the patient level. This

enabled us to exclude one participant with a record of cancer within the three years preceding

conception. Often studies using self-reported information have shown an underestimation

when reporting chronic conditions 35. A further strength of this study is the use of medically

recorded BMI values. As frequent misclassification especially amongst overweight and obese

women has been documented when using self-reported BMI measures 36 we have been able

to minimise uncertainty associated with recall-bias.










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onset of obesity 41. It is important to note that there is no standard costing system used throughout

the UK NHS and as such the unit costs applied as part of this study merely reflect an average of the

resource costs borne in Wales over a certain period. This creates great difficulty when trying to

deduce actual resource utilisation at an individual hospital episode level, and means that the unit

costs used here may differ from those reported elsewhere in the UK NHS. Nonetheless, the unit

costs from the WCR accounts used throughout this study are validated annually during the

completion of the Welsh Benchmarking Summary (WBS), providing a robust costing methodology.




















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(812,920) and applying the findings from this study, an additional £144,818,1054.9 would

have been spent on health care services for obese women during an 11 month period. This

amount of capital could become cost-effective if utilised to fund public health interventions

targeting maternal lifestyle and subsequently reduce the health care usage of obese women.

Future planned work within the cohort population described shall investigate the reasons why

overweight and obese women accrue higher rates of health service use and accompanying

costs, with specific focus on the specialties accessed and timing of usage.

Acknowledgments





work is also part of the ‘Growing Up in Wales: EHL’ study.

Author Contribution






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References





Gynaecology 2011:578-88.







5. Sherrard A, Platt RW, Vallerand D, Usher RH, Zhang X, Kramer MS. Maternal anthropometric risk

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8. Heslehurst N, Lang R, Rankin J, Wilkinson JR, Summerbell CD. Obesity in pregnancy: a study of the

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17. Kolu P, Raitanen J, Rissanen P, Luoto R. Health care costs associated with gestational diabetes

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19. Welsh Government. A Strategic Vision for Maternity Services in Wales: Crown copyright 2011.:1-

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20. Hill R, Brophy S, Brunt H, Storey M, Thomas NE, Thornton CA, Palmer S, Dunstan F, Paranjothy S,

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22. Brooks CJ, Stephens JW, Price DE, Ford DV, Lyons RA, Prior SL, et al. Use of a patient linked data

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23. Welsh Government. Financial Information Strategy Programme.Consolidated Local Health Boards

WCR1 Costing Returns. Wales, 2012.


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Affairs 2002;21(2):245-53.

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inpatient sector

Inpatients Daycases

Specialties

Net

expenditure

(£)

Patient

days

Cost per

day (£)

Net

expenditure

(£)

Patient

days

Cost per

day (£)

Paediatrics 52,237,276 71,720 728.35 866,951 2,147 403.80

Geriatrics 112,633,815 416,915 270.16 10,365 40 259.13

Cardiology 50,773,641 109,204 464.94 7,201,444 7,051 1,021.34

Dermatology 2,153,882 3,486 617.87 740,871 2,761 268.33

Infectious diseases 2,638,233 8,573 307.74 0 0 0.00

Medical oncology 2,045,936 4,863 420.71 138,819 479 289.81

Neurology 7,619,109 16,532 460.87 267,763 851 314.65

Rheumatology 787,026 909 865.82 742,779 1,609 461.64

Gastroenterology 23,213,420 75,773 306.35 8,129,697 19,499 416.93

Haematology 9,851,801 23,651 416.55 1,313,006 4,942 265.68

Clinical immunology

and allergy 0 0 0.00 0 0 0.00

Thoracic medicine 25,875,376 81,255 318.45 975,817 1,253 778.78

Genito-urinary

medicine 29,756 88 338.14 136,854 1,313 104.23

Nephrology 9,507,237 27,563 344.93 288,255 1,383 208.43

Rehabilitation

medicine 52,315,987 220,137 237.65 10,886 150 72.58

Palliative medicine 9,739,419 16,569 587.81 24,044 32 751.38

Other medicine 238,524,984 823,264 289.73 9,586,046 20,658 464.04

General surgery 156,270,386 290,410 538.10 29,185,179 37,404 780.27

Urology 30,819,378 50,146 614.59 13,797,772 28,074 491.48

Orthopaedics 209,045,919 298,249 700.91 28,238,373 24,526 1,151.36

ENT 28,287,361 26,675 1,060.44 7,185,969 6,170 1,164.66

Ophthalmology 4,329,661 4,926 878.94 26,617,445 30,448 874.19

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Gynaecology 38,956,738 51,917 750.37 11,905,598 15,773 754.81

Dental specialities 12,934,698 10,080 1,283.20 4,662,328 6,796 686.04

Neuro-surgery 13,793,671 17,046 809.20 51,963 81 641.52

Plastic surgery 10,154,515 10,623 955.90 1,955,652 2,383 820.67

Cardiothoracic 19,629,745 20,130 975.15 23,664 29 816.02

Paediatric surgery 4,226,962 4,387 963.52 358,460 400 896.15

Obstetrics 76,200,264 122,139 623.88 21,133 42 503.16

General practice

(maternity) 3,278 10 327.83 0 0 0

Learning disabilities 29,676,728 41,916 708.00 467 1 466.85

Mental illness 79,774,195 254,276 313.73 1,196 2 597.79

Child and adolescent

psychiatry 5,381,548 6,567 819.48 0 0 0.00

Forensic psychiatry 5,870,962 23,323 251.72 0 0 0.00

Psychotherapy 0 0 0 0 0 0.00

Old age psychiatry 89,429,134 283,489 315.46 12,275 31 395.95

General practice

(other than

maternity) 32,932,711 114,382 287.92 57,778 57 1,013.65

Radiotherapy 11,133,262 25,380 438.66 741,677 2,640 280.94

Pathological

specialities and

radiology 21,514 61 352.68 267,826 951 281.63

Anaesthetics 178,048 309 576.21 4,797,702 4,070 1,178.80

A & E 1,876,009 5,176 362.44 822 3 274.05

Other 544,350 544 1,000.64 0 0 0.00

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outpatient sector

Outpatients


(£)

Total

attendances*

Cost per

attendance (£)

Paediatrics 25,242,291 106,384 237.28

Geriatrics 6,622,902 33,450 197.99

Cardiology 13,063,787 133,409 97.92

Dermatology 13,484,477 166,638 80.92

Infectious diseases 61,878 613 100.94

Medical oncology 1,402,934 6,720 208.77

Neurology 5,744,846 33,706 170.44

Rheumatology 15,659,341 101,124 154.85

Gastroenterology 5,996,351 56,029 107.02

Haematology 13,195,306 127,668 103.36

Clinical immunology and allergy 0 0 0.00

Thoracic medicine 6,509,385 59,230 109.90

Genito-urinary medicine 14,008,180 98,371 142.40

Nephrology 7,406,077 41,593 178.06

Rehabilitation medicine 1,192,184 5,577 213.77

Palliative medicine 934,951 2,490 375.48

Other medicine 36,977,576 267,717 138.12

General surgery 24,802,255 124,0719 112.30

Urology 11,578,656 119,883.64 96.58

Orthopaedics 59,998,261 485,758.13 123.51

ENT 17,435,726 136,990.59 127.28

Ophthalmology 26,914,687 36,1374 74.48

Gynaecology 16,372,605 141,861.85 115.41

Dental specialities 13,684,356 90234.36 151.65

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Outpatients


(£)

Total

attendances*

Cost per

attendance (£)

Neuro-surgery 859,003 4,774 179.93

Plastic surgery 2,400,960 23,751 101.09

Cardiothoracic 1,010,776 5,786 174.69

Paediatric surgery 426,479 3,015 141.45

Obstetrics 16,847,079 155,168 108.57

General practice (maternity) 0 0 0

Learning disabilities 749,141 3,741 200.25

Mental illness 16,023,382 107,640 148.86

Child and adolescent psychiatry 10,569,437 60,787 173.88

Forensic psychiatry 64,831 1,319 49.15

Psychotherapy 613,875 3,974 154.47

Old age psychiatry 6,829,338 27,501 248.33

General practice (other than

maternity) 312,946 2611 119.86

Radiotherapy 15,948,452 99833 159.75

Pathological specialities and

radiology 701,265 10959 63.99

Anaesthetics 4,399,749 39622 111.04

Younger Physically Disabled 0 0 0.00

A & E 132,138 1094 120.78

Other 1,618,888 2611 16.34

* Includes new-, follow up and pre-op attendances

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Supplementary Table 13: Read version 2 codes used to identify the presence of co-morbidities

amongst the study population based on Khan et al., 27




G1yz0, G2101, G2111, G21z1, G232., G234., G343.,

G5540, G5541, G554z, G555., G55y0, G55z., G557.,

G558., G58.., Q490.


J5771


G6…, F4237


G4y.., G4z.., H30.., H310., H311., H313., H31z., H32..,

H3y.., H33.., H34.., H35.., H40.., H41.., H42.., H43..,

H44.., H45.., H450., H464., H4y1., H4y21

Diabetes C10..


F112.

Rheumatic disease

N047., N04X., N041., N0421, N040N, N0420, G5yA.,

G5y8., F3964, G011., G010., F3712, N040P, N04y2,

N040Q, N0422, N04.., N200., N0003, N000., N004.,

N003X, N0031, N001., N20.., N0031


Mild liver disease

A707., J610., J617., J6120, J612., J613., J6353, J6354,

J6355, J6356, J614z, J61y4, J61y5, J61y6, J6160, J6161,

J616z, J615z, Jyu71, J6151, J61y1, J636., J634., J638.,

J63y0, PB6y9, J61z.,ZV427


F243., F244., F245., F246., F24z.

Renal disease

G222., G233., K0A32, K0A33, K0A34, K0A35, K0A36,

K0A37, K03V., K03U., K03X., K03W., K05.., K06.., K080.,

ZV561, ZV560, ZV56y, ZV420, ZV451

Any malignancy

B0..., B1…, B2…, B30.., B32.., B232., B181., B2414,




B631., B6300, B64.., B65.., B66.., B670., B671., BBrA5,

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B480., B481., B482., B483., B487., B46.., B47.., B484.,

B485., B486., B48y., B4A0., B4A1., B4A2., B49.., B4A3.,

B4A4., B4Ay0, B4Az., B50.., B521., B523., B52X., B51..,

B522., B525., B520., B52W., B52z., B53.., B540., B541.,

B542., B543., B544., B545., B54X., B54z., B55.., B62x6,


B6z0., B592X, B524., B180., B18y., B182., B31.., B34..,

B35.., B451., B452., B453., B54y0, B454., B450., B41..,

B431., B4302, B4303, B4301, B432., B430z, B43z.,

B440., B441., B442., B443., B444., B44y., B44z., B45y.,

B45X., B45z., B42..


G850., G851., G857., G852., J6130, J6357, J637., J623.,

J624.


AIDS/HIV

A7890, A7891, A7892, A7893, A7894, AyuC4, A788z,

A7898, A7895, A7896, A7897, A789X, Eu024, A7899,

A789A, A7894

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196x165mm (300 x 300 DPI)

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Supplementary Table 1: Read version 2 codes used to identify the presence of co-morbidities amongst

the study population based on Khan et al., 27




G1yz0, G2101, G2111, G21z1, G232., G234., G343.,

G5540, G5541, G554z, G555., G55y0, G55z., G557.,

G558., G58.., Q490.


J5771


G6…, F4237


G4y.., G4z.., H30.., H310., H311., H313., H31z., H32..,

H3y.., H33.., H34.., H35.., H40.., H41.., H42.., H43..,

H44.., H45.., H450., H464., H4y1., H4y21

Diabetes C10..


F112.

Rheumatic disease

N047., N04X., N041., N0421, N040N, N0420, G5yA.,

G5y8., F3964, G011., G010., F3712, N040P, N04y2,

N040Q, N0422, N04.., N200., N0003, N000., N004.,

N003X, N0031, N001., N20.., N0031


Mild liver disease

A707., J610., J617., J6120, J612., J613., J6353, J6354,

J6355, J6356, J614z, J61y4, J61y5, J61y6, J6160, J6161,

J616z, J615z, Jyu71, J6151, J61y1, J636., J634., J638.,

J63y0, PB6y9, J61z.,ZV427


F243., F244., F245., F246., F24z.

Renal disease

G222., G233., K0A32, K0A33, K0A34, K0A35, K0A36,

K0A37, K03V., K03U., K03X., K03W., K05.., K06.., K080.,

ZV561, ZV560, ZV56y, ZV420, ZV451

Any malignancy

B0..., B1…, B2…, B30.., B32.., B232., B181., B2414,




B631., B6300, B64.., B65.., B66.., B670., B671., BBrA5,

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B480., B481., B482., B483., B487., B46.., B47.., B484.,

B485., B486., B48y., B4A0., B4A1., B4A2., B49.., B4A3.,

B4A4., B4Ay0, B4Az., B50.., B521., B523., B52X., B51..,

B522., B525., B520., B52W., B52z., B53.., B540., B541.,

B542., B543., B544., B545., B54X., B54z., B55.., B62x6,


B6z0., B592X, B524., B180., B18y., B182., B31.., B34..,

B35.., B451., B452., B453., B54y0, B454., B450., B41..,

B431., B4302, B4303, B4301, B432., B430z, B43z.,

B440., B441., B442., B443., B444., B44y., B44z., B45y.,

B45X., B45z., B42..


G850., G851., G857., G852., J6130, J6357, J637., J623.,

J624.


AIDS/HIV

A7890, A7891, A7892, A7893, A7894, AyuC4, A788z,

A7898, A7895, A7896, A7897, A789X, Eu024, A7899,

A789A, A7894

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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cohort studies

Section/Topic Item

# Recommendation Reported on page #

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 2

(b) Provide in the abstract an informative and balanced summary of what was done and what was found 2

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 4

Objectives 3 State specific objectives, including any prespecified hypotheses 5

Methods

Study design 4 Present key elements of study design early in the paper 5

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data

collection

5

Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up 5

(b) For matched studies, give matching criteria and number of exposed and unexposed

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if

applicable

6-7

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe

comparability of assessment methods if there is more than one group

6-7

Bias 9 Describe any efforts to address potential sources of bias 6-7

Study size 10 Explain how the study size was arrived at 9

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and

why

7

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 7

(b) Describe any methods used to examine subgroups and interactions 7

(c) Explain how missing data were addressed 5

(d) If applicable, explain how loss to follow-up was addressed

(e) Describe any sensitivity analyses 7

Results

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Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed

8-9

(b) Give reasons for non-participation at each stage 9

(c) Consider use of a flow diagram 9

Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential

confounders

8/10

(b) Indicate number of participants with missing data for each variable of interest 10

(c) Summarise follow-up time (eg, average and total amount)

Outcome data 15* Report numbers of outcome events or summary measures over time 11-15

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence

interval). Make clear which confounders were adjusted for and why they were included

12-13

(b) Report category boundaries when continuous variables were categorized 12

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses 16

Discussion

Key results 18 Summarise key results with reference to study objectives 17

Limitations

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from

similar studies, and other relevant evidence

17-19

Generalisability 21 Discuss the generalisability (external validity) of the study results 19

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on

which the present article is based

20

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE

checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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