Obesity and associated health risks : outcomes of maternal early pregnancy obesity and child's cognition

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Department of Psychology and Logopedics Faculty of Medicine

University of Helsinki Finland

OBESITY AND ASSOCIATED HEALTH RISKS – OUTCOMES OF MATERNAL EARLY PREGNANCY

OBESITY AND CHILD ’S COGNITION

Satu Kumpulainen

ACADEMIC DISSERTATION

To be presented, with the permission of the Faculty of Medicine of the University of Helsinki, for public examination in lecture room XV,

University main building, on January 25^th 2019 at 12 noon.

Helsinki 2019

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Supervisors Academy Professor Katri Räikkönen-Talvitie, PhD Department of Psychology and Logopedics Faculty of Medicine

University of Helsinki, Finland

Docent Kati Heinonen-Tuomaala, PhD Department of Psychology and Logopedics Faculty of Medicine

University of Helsinki, Finland

Reviewers Professor Catharine Gale, PhD Department of Psychology

University of Edinburgh, United Kingdom

and

MRC Lifecourse Epidemiology Unit

University of Southampton, United Kingdom Professor Mirka Hintsanen, PhD

Unit of Psychology Faculty of Education University of Oulu, Finland

Opponent Professor Annick Bogaerts, PhD

Department of Development and Regeneration

KU Leuven, Belgium

and

The Faculty of Medicine and Health Sciences

University of Antwerp, Belgium

ISBN 978-951-51-4833-9 (pbk.) ISBN 978-951-51-4834-6 (PDF) Unigrafia

Helsinki 2019

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ABSTRACT

Alarming rates of the world’s adult population is meeting the criteria for obesity.

Moreover, increasing amount of women at reproductive age are entering pregnancy with overweight or obesity. Growing evidence suggests that excessive maternal weight during pregnancy does not only pose a risk for poorer maternal physical and mental health but is also resulting in adverse outcomes in offspring.

One of the proposed mechanisms linking maternal overweight and obesity with offspring health outcomes include the early life programming of hypothalamic- pituitary-adrenocortical (HPA) axis. Moreover, poorer childhood cognitive functioning is suggested as a risk factor for later life obesity and lower rates of physical activity, one of the key health behaviours linked with overweight and obesity.

The aim of this thesis was to examine the associations of maternal early pregnancy body mass index (BMI) with health related outcomes of mother and offspring and the effects of childhood cognitive ability on adulthood obesity and obesity-promoting health behaviours. Specifically, 1) whether maternal early pregnancy BMI is associated with maternal depressive symptoms throughout and after pregnancy, 2) whether maternal early pregnancy BMI is associated with adult offspring HPA axis functioning, and 3) whether childhood cognitive abilities are associated with body composition and physical activity in adulthood.

The participants came from two study cohorts. The Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study is a prospective, multicentre study consisting of 4777 Finnish women who gave a birth to a live-born infant between 2006 and 2010. Of the 4745 (99.3%) women with data on early pregnancy BMI derived from the Finnish Medical Birth Register, 3234 (68.2%) completed the Centre for Epidemiological Studies for Depression scale biweekly during pregnancy and at an average of 2.4 weeks and/or 28.2 weeks after pregnancy (Study I).

The Arvo Ylppö Longitudinal Study (AYLS) originally consisted of 2193 participants born in Helsinki between 1985 and 1986. Of these neonates, 1583 (72.2%) provided valid data on at least one of the four tests for cognitive ability at a mean age of 56 months. Between 2009 and 2012, 1136 (51.8%) individuals form the original cohort participated in the follow-up that included clinical and psychological examination at a mean age of 25 years. Of those 1136, 848 (74.6%) took part in salivary cortisol sampling, 988 (87%) went through clinical examination including a measurement of body composition with estimates of body fat percentage and 676 (59.5%) provided data on objectively measured physical activity. This resulted in 635 participants with data on maternal early pregnancy BMI extracted from health care records and valid data on salivary

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cortisol (Study II), 816 participants with data on childhood cognitive abilities and body composition (Study III) and 500 participants with data on childhood cognitive abilities and valid data on objectively measured physical activity (Study IV).

The results showed that both maternal early pregnancy overweight and obesity were associated with consistently higher levels of depressive symptoms and higher odds for reporting clinically relevant depressive symptoms throughout and after pregnancy (Study I). Furthermore, offspring born to mothers with higher early pregnancy BMI had lower diurnal salivary cortisol levels and lower morning cortisol levels in adulthood (Study II). The results showed that of the cognitive abilities assessed in early childhood, only lower visuomotor integration was associated with higher BF% in young adulthood (Study III) whereas higher general intelligence in childhood was associated with lower overall daily physical activity, less time spent in light physical activity and higher sedentary time in young adulthood (Study IV).

The results provide evidence for the adverse effects of maternal early pregnancy overweight and obesity on maternal mental health throughout and after pregnancy and suggests that higher maternal early pregnancy BMI may have programming effects on the offspring HPA-axis activity extending into adulthood.

Furthermore, the results challenge the view that lower childhood cognitive functioning poses a risk for adiposity and less physically active lifestyle in adulthood.

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TIIVISTELMÄ

Lihavuus on riskitekijä useille fyysisille ja psyykkisille sairauksille. Lihavien henkilöiden määrä maailman aikuisväestöstä on hälyttävä ja lisääntyvä määrä reproduktiivisessa iässä olevista naisista voidaan luokitella lihaviksi raskauden alussa. Lisääntyvä tutkimustieto osoittaa, että äidin alkuraskauden lihavuus ei lisää ainoastaan äitiin kohdistuvaa riskiä epäsuotuisille fyysisille ja psyykkisille sairauksille, vaan voi lisäksi aiheuttaa haitallisia terveysvaikutuksia jälkeläiselle, mukaan lukien heikommat kognitiiviset kyvyt. Varhaisen hypotalamus- aivolisäke-lisämunaiskuori-akselin (HPA-akseli) ohjelmoitumisen on ehdotettu olevan yksi välittävistä tekijöistä äidin alkuraskauden lihavuuden ja jälkeläisen terveyden välillä. Lisäksi, heikomman lapsuuden kognitiivisen kyvykkyyden on osoitettu olevan riskitekijä aikuisiän lihavuudelle sekä vähäisemmälle fyysiselle aktiivisuudelle, joka on yksi tärkeimmistä lihavuuteen liittyvistä elämäntapatekijöistä.

Tämän väitöskirjan tarkoitus oli selvittää äidin varhaisraskauden lihavuuden yhteyttä äidin ja aikuisen lapsen terveyteen liittyviin seurauksiin sekä lapsuusiän kognitiivisten kykyjen yhteyttä aikuisiän lihavuuteen ja elämäntapoihin, jotka edistävät lihavuutta. Erityisesti tavoitteena oli tutkia 1) äidin varhaisraskauden lihavuuden yhteyttä äidin kokemiin masennusoireisiin läpi raskauden sekä raskauden jälkeen, 2) äidin varhaisraskauden painoindeksin (kg/m²) yhteyttä aikuisen jälkeläisen HPA-akselin toimitaan, ja 3) lapsuusiän kognitiivisten kykyjen yhteyttä aikuisiän kehonkoostumukseen ja fyysiseen aktiivisuuteen.

Osallistujat ovat peräisin kahdesta tutkimuskohortista. The Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction Study (PREDO) on prospektiivinen tutkimus, joka koostuu 4777 suomalaisesta naisesta, jotka synnyttivät lapsen vuosien 2006 ja 2010 välillä. Niistä 4745 (99.3 %) naisesta, joilla oli suomalaisesta syntymärekisteristä saatu tieto varhaisraskauden painoindeksistä, 3234 (68.2 %) naista täytti Centre for Epidemiological Studies for Depression kyselyn joka toinen viikko raskauden ajan ja keskimäärin 2.4 viikkoa ja/tai 28.2 viikkoa raskauden jälkeen (Tutkimus I).

Arvo Ylppö Longitudinal Study (AYLS) tutkimusaineisto koostuu alun perin 2193 osallistujasta, jotka syntyivät Uudenmaan alueella vuosien 1985 ja 1986 välillä. Näistä lapsista 1583:lla (72.2 %) oli käyttökelpoista dataa ainakin yhdestä niistä neljästä testistä, joilla kognitiivisia kykyjä mitattiin keskimäärin 56 kuukauden iässä. Vuosien 2009 ja 2012 välillä, 1136 (51.8 %) henkilöä alkuperäisestä kohortista osallistui jatkotutkimukseen, johon sisältyi kliininen ja psykologinen tutkimus keskimäärin 25 vuoden iässä. Näistä 1136 osallistujasta, 848 (74.6 %) otti osaa sylkinäytteiden keräämiseen, 988 (97.0 %) osallistui kliiniseen tutkimukseen, jossa mitattiin myös kehonkoostumus sisältäen arvion

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rasvaprosentista ja 676 (59.5 %) osallistui objektiivisesti mitatun liikuntadatan keräämiseen. Tämän tuloksena 635 osallistujalla oli tieto äidin alkuraskauden painoindeksistä sekä käyttökelpoista syljestä mitattua kortisoliaineistoa (Tutkimus II), 816 osallistujalla oli aineistoa lapsuusiän kognitiivista kyvyistä ja aikuisiän kehonkoostumuksesta (Tutkimus III) ja 500 osallistujalla oli aineistoa lapsuusiän kognitiivisista kyvyistä sekä käyttökelpoista objektiivisesti mitattua liikunta-aineistoa (Tutkimus IV).

Tulokset osoittivat, että sekä äidin varhaisraskauden ylipaino että lihavuus olivat yhteydessä korkeampiin masennusoireisiin ja suurempaan todennäköisyyteen raportoida kliinisesti merkittäviä masennusoireita läpi raskauden ja raskauden jälkeen (Tutkimus I). Lisäksi, äidin korkeampi alkuraskauden painoindeksi oli yhteydessä aikuisen jälkeläisen matalampiin päivittäisiin kortisolitasoihin ja matalampiin aamuajan kortisolitasoihin (Tutkimus II). Tulokset osoittivat, että lapsuusiässä mitatuista kognitiivisista kyvyistä vain matalampi visuomotorinen kyvykkyys oli yhteydessä korkeampaan rasvaprosenttiin nuoressa aikuisiässä (Tutkimus III) ja korkeampi lapsuuden yleinen älykkyys oli yhteydessä vähempään päivittäiseen fyysiseen aktiivisuuteen, lyhempään päivittäin käytettyyn aikaan kevyen liikunnan parissa sekä pidempään päivittäin istumiseen käytettävään aikaan (Tutkimus IV).

Tämän väitöskirjan tulokset lisäävät tieteellistä näyttöä äidin varhaisraskauden ylipainon ja lihavuuden haitallisista vaikutuksista äidin raskauden aikaiselle ja jälkeiselle psyykkiselle hyvinvoinnille sekä viittaavat siihen, että äidin korkeampi alkuraskauden painoindeksi saattaa vaikuttaa jälkeläisen HPA-akselin ohjelmoitumiseen ulottuen aikuisikään asti. Lisäksi, väitöskirjan tulokset kyseenalaistavat näkemyksen, jonka mukaan matalammat kognitiiviset kyvyt lapsuudessa lisäävät riskiä aikuisiän lihavuudelle ja fyysisesti epäaktiivisemmalle elämäntavalle.

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ACKNOWLEDGEMENTS

I started my PhD path in the Developmental Psychology Research group in 2013 with quite limited research skills and with lots of enthusiasm. Doing my PhD has not always been easy but I have enjoyed the challenges I have come across during the past five and a half years. I want to express my gratitude to my supervisor, Academy Professor Katri Räikkönen-Talvitie who has guided me through this process and helped me solve the challenges I have faced in my work. Katri, thank you for giving me the opportunity to work in your research group under your supervision with such extraordinary datasets. I remember you once said, while I was struggling and doubting my skills, that no one is born as a researcher but one has to learn it. This has been a great learning process for me in many ways.

I want to thank my second supervisor, Docent Kati Heinonen-Tuomaala, for her expertise and help during these years. Thank you Kati for your patience and ability to calm me down whenever I have been worried about doing something wrong.

I am grateful to the pre-examiners, Professor Catherine Gale and Professor Mirka Hintsanen, for their insightful comments and suggestions, which helped improve my thesis.

I want to express my gratitude to all my coauthors. The comments, questions and suggestions you have given have not only improved the articles I have worked on but have also been an important part of my learning. Thank you Drs Anu- Katriina Pesonen, Johan G Eriksson, Eero Kajantie, Sture Andersson, Dieter Wolke, Minna K Salonen, Aulikki Lano, Hannele Laivuori, Pia M Villa, Esa Hämäläinen, Rebecca M Reynolds and Nina Kaseva.

I have been privileged to work with the datasets from the Prediction and Prevention of Intrauterine Growth Restriction Study and from the Arvo Ylppö Longitudinal Study. I wish to thank all the study participants and the people who have been part of planning the studies, gathering the data and working on these data before me.

This research would not have been possible without funding from several institutions. This research was supported by the University of Helsinki Research Funds, Doctoral program of Psychology, Learning and Communication, Academy of Finland, European Commission, Federal Goverment of Germany, Ministry of Science and Technology, Finnish Foundation for Pediatric Research, Finska Läkaresällskapet, Signe and Ane Gyllenberg Foundation, Stiftelsen Dorothea Olivia, Karl Walter och Jarl Walter Perklens, Sigrid Jusélius Foundation, Emil Aaltonen Foundation, Novo Nordisk Foundation, Finnish Foundation for Pediatric Research, Finnish Foundation for Cardiovascular Research, Juho

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Vainio Foundation, Samfundet Folkhälsan, Päivikki and Sakari Sohlberg Foundation, Finska Läkaresällskapet, Tommy’s and British Heart Foundation.

I am deeply grateful to all my colleagues from the Depsy Research group. I want to express my gratitude to Docent Marius Lahti-Pulkkinen for his unquestionable help with all the concerns and questions related to my work I have come across during these years. I admire your patience, dedication and thorough way of working. I want to also thank Drs Riikka Pyhälä-Neuvonen, Jari Lahti, Elena Toffol, Soili Tikkanen, Alfredo Ortega-Alonso, Ilona Merikanto, and Siddheshwar Utge for your help and kindness.

Special thanks go to my fellow PhD students during the past years. It has been a privilege to share a PhD journey with such talented, intelligent, and supportive people. I could not have done this without you and many glasses of wine and beer, and the discussions about life and research we have shared, often accompanied by lots of laughs. Thank you Liisa, Polina, Sara, Anna, Katri, Silja, Soile, Tuomas, Ville And Risto. I wish to express a special thanks to Rachel, who kindly did a thorough language check on my thesis. I am forever grateful for meeting Elina and Kadri, the honoured members of the Angry Ruminators’ Society. We have shared the joys and sorrows of life and work and most of all, we have ruminated a lot. Elina, I want to thank you for your honesty, your wisdom and that you have always listened to my worries and stopped my jamming when needed. Kadri, thank you for your support and wisdom. I have always felt that you truly think that I am good the way I am and with what I am doing.

Life would not make much sense without my beloved friends. I am thankful for being surrounded by such smart and supportive friends. I wish to thank Anna, Eppu, Saara, and Liisa for keeping my head together during the past years.

I want to thank my twin sister and friend Heli, with whom we have experienced life together since the womb, and thus, words are often unnecessary.

Thank you for the closeness and sisterhood and that I am always welcome in your home.

I wish to thank my parents for always considering education important and providing the possibility to pursue my dreams. I have not always been the easiest child but I think you did quite well – I have always felt that I can do things in my own way and most of all if I want something I am able to achieve it. Mom, you are the strongest woman I know and without you I think I would not be where I am today. Thank you for your wisdom and for pushing me forward when needed.

Markus, thank you for helping me through the most hopeless and darkest moments, and making my mornings a bit easier by preparing coffee. I am always thankful for your support and for always believing that I can do this. I love you.

This thesis is dedicated to my godson and nephew Kasper and my niece Lila who have been the best company to break away from my worries and with whom I am always fully living in the moment. You are precious and perfect the way you are.

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LIST OF ORIGINAL PUBLICATIONS

This thesis is based on the following publications:

I Kumpulainen, S.M., Girchenko, P., Lahti-Pulkkinen, M., Reynolds, R. M., Tuovinen, S., Pesonen, A-K., Heinonen, K., Kajantie, E., Villa, P.M., Hämäläinen, E., Laivuori, H., Raikkonen, K. (2018).

Maternal early pregnancy obesity and depressive symptoms during and after pregnancy. Psychological Medicine, 48(14), 2353–2363.

II Kumpulainen, S.M., Heinonen, K., Kaseva, N., Andersson, S., Lano, A., Reynolds, R. M., Wolke, D., Kajantie, E., Eriksson, J.G., Raikkonen, K. Maternal pre-pregnancy body mass index and offspring cortisol at adulthood. (under review in Psychoneuroendocrinology).

III Kumpulainen, S.M., Heinonen, K., Salonen, M.K., Andersson, S., Wolke, D., Kajantie, E., Eriksson, J.G., Raikkonen, K. (2016).

Childhood cognitive ability and body composition in adulthood.

Nutrition & Diabetes, 6(8):e223–.

IV Kumpulainen, S. M., Heinonen, K., Pesonen, A.-K., Salonen, M. K., Andersson, S., Lano, A., Wolke, D., Kajantie, E., Eriksson, J.G., Raikkonen, K. (2017). Childhood cognitive ability and physical activity in young adulthood. Health Psychology, 36(6), 587–597.

The publications are referred to in the text by their roman numerals. The original publications have been reprinted with the permission of the copyright holders.

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ABBREVIATIONS

ACTH Adrenocorticotropic hormone

AUCg Area under the curve with respect to ground

AUCi Area under the curve with respect to increase/change AYLS Arvo Ylppö Longitudinal Study

BF% Body fat percentage BIA Bioelectric impedance analysis BMI Body mass index

CES-D Center for Epidemiological Studies Depression Scale CHR Corticotrophin releasing hormone

CI Confidence interval

CPM Counts per minute

DALYs Disability-adjusted life years

DOHAD Developmental origins of health and disease GDM Gestational diabetes mellitus

GLM Generalized linear model

HPA Hypothalamic-pituitary-adrenocortical

IQ Intelligence quotient

IUGR Intrauterine growth restriction MBR Medical Birth Register

MD Mean difference

METs Metabolic equivalents

MVPA Moderate-to-vigorous physical activity OR Odds ratio

PA Physical activity

PREDO Prediction and Prevention of Preeclampsia and Intrauterine Growth

Restriction Study

SD Standard deviation

SES Socioeconomic status

ST Sedentary time

WHO World Health Organization

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1 INTRODUCTION

Obesity has increased dramatically during the last three decades around the world (Ng et al., 2014) and an alarming amount of world’s adult population meet the criteria for obesity or overweight (World Health Organization, 2014). In addition to general population, an increasing amount of women at reproductive age are affected by obesity (Devlieger et al., 2016).

It is well established that both overweight and obesity increase the risk for wide array of negative physical and mental health consequences. In addition to general vulnerability for common mental disorders among women at reproductive age (Farr, Bitsko, Hayes, & Dietz, 2010; Howard et al., 2014), maternal early pregnancy obesity carries an increased risk for physical and mental health hazards both during and after pregnancy, including depression (Mariona, 2016; Molyneaux, Poston, Ashurst-williams, & Howard, 2014).

Moreover, maternal early pregnancy obesity does not only compromise the health of the mother but is shown to result in adverse offspring physical and mental health consequences (Godfrey et al., 2017). There are a number of suggested pathways linking maternal obesity with these adverse outcomes, including the early life programming of the hypothalamic-pituitary- adrenocortical (HPA) axis (Reynolds, Labad, Buss, Ghaemmaghami, &

Räikkönen, 2013; Seckl & Meaney, 2004), a system that has an important role in regulation of cardiovascular, metabolic, and neurological systems (Moisiadis &

Matthews, 2014).

Furthermore , poorer childhood cognitive functioning has been identified as a novel risk factor for later life obesity (see for example Batty, Deary, & Macintyre, 2007; Chandola et al., 2006; Gale et al., 2009) and unfavourable health behaviours (Wraw, Der, Gale, & Deary, 2018) including undesirable levels of physical activity (PA) which is one of the key health behaviours related to overweight and obesity (Weinsier, Hunter, Heini, Goran, & Sell, 1998).

The aim of this thesis was to examine the associations of maternal early pregnancy body mass index (BMI) with the maternal and offspring health related outcomes and effects of childhood cognition on adulthood body composition and obesity-promoting health behaviours with focus on PA.

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2 REVIEW OF THE LITERATURE

2.1 EPIDEMIOLOGY OF OBESITY

2.1.1 DEFINITIONS AND MEASUREMENTS

Overweight and obesity are defined as abnormal or excessive fat accumulation in adipose tissue that poses a risk for health (World Health Organization, 2000).

Overweight and obesity are assessed by using different anthropometric measurements and techniques. These include BMI which is calculated as weight in kilograms divided by the square of height in meters (kg/m²) (World Health Organization, 2000). BMI is widely used in epidemiological studies as asurrogate for general overweight and obesity because it is simple to calculate from self- reported or measured height and weight (Okorodudu et al., 2010). Table 1 displays the World Health Organization (WHO) classification of BMI categories (World Health Organization, 2000). Overweight is defined as BMI between 25.00 kg/m² and 29.99 kg/m² and obesity as BMI ≥30.00 kg/m². Obesity can be further classified into obesity classes 1- 3 (Table 1).

Table 1. Classification of body mass index according to World Health Organization (World Health Organization, 2000).

Another used anthropometric measure is waist circumference which is a proxy for abdominal fat (World Health Organization, 2008). The cut-off points for waist circumference are gender and ethnic-specific (Alberti, Zimmet, & Shaw, 2006).

According to International Diabetes Federation (IFD), cut-off of >80 cm for Europid women and >94 cm for Europid men are indicative of central obesity (Alberti et al., 2006).

More direct measures of body fat and body fat distribution can be assessed by using instruments such as bioelectrical impedance analysis (BIA), magnetic resonance imaging, and dual energy X-ray absorptiometry (Lee & Gallagher,

Classification Body mass index kg/m²

Underweight <18.5

Normal weight 18.5-24.99

Overweight 25-29.99

Obese ≥30

Obese class 1 30-34.99

Obese class 2 35-39.99

Obese class 3 ≥40

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2008). Even though recommended BMI thresholds for overweight and obesity are well established, there is no clear consensus of the body fat percentage (BF%) thresholds for classifying overweight and obesity. Often used cut-off points to define excess body fat in epidemiological studies are BF% ≥25% for men and

≥35% for women (De Lorenzo et al., 2003; Goh, Tain, Tong, Mok, & Wong, 2004;

Romero-Corral et al., 2008).

2.1.2 PREVALENCE AND TRENDS

2.1.2.1 In general adult population

In 2014, 39% of the world’s adult population was overweight and 13% was obese.

In absolute numbers, this equals 1.9 billion and 600 million individuals, respectively (World Health Organization, 2014). More specifically, 40% of women and 39% of men were overweight (World Health Organization, 2014) and 15% of women and 11% of men were obese (NCD-RisC, 2016; World Health Organization, 2014). However, the prevalence of overweight and obesity differ between countries and by country income (Ng et al., 2014). Overall, overweight and obesity tend to increase along age and are more common among women than men (Ng et al., 2014). Weight gain is most rapid between ages of 20 and 40 year and in developed countries overweight and obesity peaks between 55 to 6o years of age (Ng et al., 2014).

As figure 1 shows, both overweight and obesity have increased during the last three decades dramatically. Worldwide, prevalence of overweight and obesity have increased by 27.5% between 1980 and 2013 (Ng et al., 2014). By the year 2030 overweight and obesity are expected to show a sharp increase: 2.2 billion individuals are expected to be overweight and 1.1 billion obese (Kelly, Yang, Chen, Reynolds, & He, 2008). These estimations are alarming because overweight and obesity are major contributors to the global burden of disease, resulting in four million deaths per year (The GBD 2015 Obesity Collaborators, 2017), mostly attributable to obesity-related complications including cardiovascular disease, diabetes and kidney disease (The GBD 2015 Obesity Collaborators, 2017).

Estimates indicate that 4.9% of total global disability-adjusted life years (DALYs) were attributed to overweight and obesity (The GBD 2015 Obesity Collaborators, 2017).

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Figure 1. Prevalence of age-standardized overweight (BMI 25-29.99 kg/m²) and obesity (BMI≥30 kg/m²) among adults between 1980 and 2014.

Data source: World Health Organisation, Global Health Observatory data repository.

http://apps.who.int/gho/data/node.main.

2.1.2.2 In women at reproductive age

Overweight and obesity are also affecting the population at childbearing age and increasing prevalence of overweight and obesity is a critical health problem among women in reproductive age (Devlieger et al., 2016). Today obesity is the most common comorbidity of pregnancy (Reynolds & Stirrat, 2014), the prevalence varying between 7% to 25% within European Union countries (Devlieger et al., 2016; Euro-Peristat, 2013) and 18 to 31% across United States (USA) (Branum, Kirmeyer, & Gregory, 2016; Deputy, Dub, & Sharma, 2018). The number of pregnant women who are overweight is high as well: 17-28% in European union countries (Euro-Peristat, 2013) and 23-28% in the United States (Deputy et al., 2018). As figure 2 shows, in 2010 nearly 23% of Finnish pregnant women were overweight and over 12% were obese. Between 2006 and 2008, 49%

of the women who died in United Kingdom due to causes directly or indirectly related to pregnancy were either overweight or obese (Cantwell et al., 2011).

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Figure 2. Prevalence of maternal overweight (BMI 25-29.99 kg/m²) and obesity (BMI≥30 kg/m²) in 2010.

Data source:http://www.europeristat.com/our-indicators/euro-peristat-perinatal-health-indicators- 2010.html

2.2 OBESITY AND HEALTH

2.2.1 IN GENERAL POPULATION

Both overweight and obesity increase the risk for mortality (Berrington de Gonzalez et al., 2010; The Global BMI Mortality Collaboration, 2016) and predispose to an array of several adverse physical and mental health consequences. Moreover, growing evidence suggest that excess weight is increasing the risk for multimorbidity (Booth, Prevost, & Gulliford, 2014) and thus people with increasing BMI are more likely to suffer from more than one adiposity-related co-morbid condition.

Overweight and obesity increase the risk for chronic diseases, such as cardiovascular disease (The GBD 2015 Obesity Collaborators, 2017), type 2 diabetes (Guh et al., 2009) and different types of cancers (Aune et al., 2016; Guh et al., 2009), as well as serious health conditions such as incidence of stroke (Strazzullo et al., 2010). In addition, adiposity is associated with osteoarthritis (Guh et al., 2009) and number of respiratory problems (Zammit, Liddicoat, Moonsie, & Makker, 2010). Furthermore, obesity in later life is associated with

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cognitive decline (Dahl & Hassing, 2013), and both overweight and obesity have been shown to increase the risk for dementia (Anstey, Cherbuin, Budge, & Young, 2011; Pedditizi, Peters, & Beckett, 2016) and Alzheimer’s disease (Anstey et al., 2011).

Overweight and obesity are also often comorbid with psychiatric disorders (McCrea, Berger, & King, 2012). Cross-sectional studies have shown associations between overweight and obesity and anxiety disorders (Petry, Barry, Pietrzak, &

Wagner, 2008), bipolar disorder (McElroy & Keck, 2012) and depression (Rajan

& Menon, 2017). Moreover, evidence from longitudinal studies have shown that obesity is increasing the risk for depression and vice versa (Luppino et al., 2010;

Rajan & Menon, 2017), and thus obesity and depression are suggested to have a bidirectional relationship (Luppino et al., 2010).

Overweight and obesity also have negative impact on the health-related quality of life and capacity to function in daily life (Fontaine & Barofsky, 2001).

Increase in BMI is associated with decreased physical functioning and increased bodily pain (Fontaine & Barofsky, 2001), especially low back pain and joint pain are common among individuals with obesity (Fontaine & Barofsky, 2001). Even though lower quality of life among obese persons may partly reflect the impairments caused by comorbid diseases, studies among healthy people have demonstrated that increase in obesity level is independently associated with lower quality of life (Jia & Lubetkin, 2005). Furthermore, overweight and obesity are also associated with impairments in psychological well-being (Evans et al., 2012;

Scott et al., 2008; Simon et al., 2006) which are partly reflecting weight discrimination and stigma experienced in daily life (Jackson, Beeken, & Wardle, 2015).

2.2.2 IN WOMEN AT REPRODUCTIVE AGE

2.2.2.1 Pregnancy and birth complications

Increased maternal BMI before and during pregnancy, particularly obesity, increases multiple health risk for the women during pregnancy and at delivery.

Overweight and obesity are often comorbid with pregnancy complications such as hypertensive and diabetic disorders (Vasudevan, Renfrew, & McGuire, 2011).

Diabetic disorders can be divided into pre-existing diabetes which include Type I and II diabetes and into gestational diabetes mellitus (GDM) (Lawrence, Contreras, Chen, & Sacks, 2008). Pre-pregnancy overweight and obesity are major risk factors for GDM (Torloni et al., 2009).

Overweight and obesity also increase the risk for hypertensive pregnancy disorders (Gaillard, Steegers, Hofman, & Jaddoe, 2011; Wang et al., 2013)

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including preeclampsia, chronic hypertension and gestational hypertension (Vest

& Cho, 2012). In addition, obese women are more likely to have excessive gestational weight gain (Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines, 2009) which is further increasing the risk for adverse health consequences (Catalano &

Shankar, 2017).

Moreover, maternal overweight and obesity increase the risk for birth complications, such as caesarean section (Poobalan, Aucott, Gurung, Smith, &

Bhattacharya, 2009) and preterm birth (McDonald, Han, Mulla, & Beyene, 2010).

In addition, increased maternal BMI is associated with stillbirth, and neonatal, perinatal, and infant death (Aune, Saugstad, Henriksen, & Tonstad, 2014).

2.2.2.2 Mental health during and after pregnancy

Women at reproductive age are at increased risk for common mental disorders (Farr et al., 2010; Howard et al., 2014) and studies suggest that women are especially vulnerable to suffer from depression during pregnancy and within the first year postpartum (Woolhouse, Gartland, Mensah, & Brown, 2015).

Prevalence of clinically relevant self-reported depressive symptoms in different stages during pregnancy is reported to vary between 7.4% to 20.4% (Bennett, Einarson, Taddio, Koren, & Einarson, 2004; Marcus, Flynn, Blow, & Barry, 2003;

Woolhouse et al., 2015) and after pregnancy between 1.9% and 82.1% (Norhayati, Nik Hazlina, Asrenee, & Wan Emilin, 2015).

Growing evidence suggests that maternal obesity does not only increase the risk for physical health hazards, but is a risk factor for poorer mental health during and after pregnancy. Indeed, one meta-analysis (Molyneaux et al., 2014) showed that women with pre-pregnancy overweight had 19% and with obesity 43% higher odds for reporting clinically significant depressive symptoms during pregnancy than women with pre-pregnancy normal weight. The results also showed that women with pre-pregnancy overweight and obesity had 9% and 30%

increased odds for clinically relevant depressive symptoms after pregnancy compared to women with normal weight, respectively (Molyneaux et al., 2014).

In this meta-analysis, however, the possible confounding factors between obesity and depressive symptoms were not taken into account (Molyneaux et al., 2014).

Partly in line with the meta-analysis, the results of two more recent large-scale studies showed that women with obesity had 65% (Venkatesh, Riley, Castro, Perlis, & Kaimal, 2016) and 39% (Molyneaux, Poston, Khondoker, & Howard, 2016) higher odds for clinically relevant self-reported depressive symptoms during pregnancy compared to women with pre-pregnancy normal weight. While the first one of these studies (Venkatesh et al., 2016) reported that women with overweight had 31% higher odds for antenatal depressive symptoms compared to

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women with normal weight, in the latter study (Molyneaux, Poston, et al., 2016) (Molyneaux, Poston, et al., 2016), however, women with overweight did not differ in depressive symptoms from women with normal weight. Yet another large scale study (Molyneaux, Pasupathy, et al., 2016) reported that only women with obesity, but not with overweight within high socioeconomic status (SES) had 116% higher odds for clinically significant antenatal depressive symptoms than women with normal weight. There were no significant differences in depressive symptoms between women with obesity, overweight and normal weight in the low SES group or in combined high and low SES group (Molyneaux, Pasupathy, et al., 2016).

The more recent smaller scale studies from different countries and ethnic groups have shown a more mixed pattern of findings with some reporting associations between overweight and/or obesity and depressive symptoms during pregnancy (Bogaerts et al., 2013; Dotlic et al., 2014; Mina et al., 2015; Ruhstaller, Elovitz, Stringer, Epperson, & Durnwald, 2017; Salehi-Pourmehr, Mohammad- Alizadeh, Jafarilar-Agdam, Rafiee, & Farshbaf-Khalili, 2018), others reporting null associations (Ertel et al., 2015; Sahrakorpi et al., 2017) or associations with even lower levels of depressive symptoms during pregnancy (Ertel et al., 2015).

Similarly, in the studies focusing on postpartum depressive symptoms, some studies have reported associations between maternal early pregnancy overweight and/or obesity and depressive symptoms after pregnancy (Mina et al., 2015;

Salehi-Pourmehr et al., 2018) while other studies have reported that they are unrelated (Ruyak, Lowe, Corwin, Neu, & Boursaw, 2016; Sahrakorpi et al., 2017).

However, significant caveats in the previous studies hinder the conclusions about the validity of the findings. None of the previous studies examining the association between maternal obesity and depression during pregnancy have measured depressive symptoms throughout pregnancy in multiple time-points.

In addition, the often co-morbid hypertension-spectrum pregnancy disorders and/or gestational diabetes were taken into account in only one of the studies (Mina et al., 2015) focusing on depressive symptoms during pregnancy and in only two studies (Mina et al., 2015; Sundaram, Harman, Peoples-Sheps, Hall, &

Simpson, 2012) focusing on postpartum depressive symptoms. Hence, it remains unclear if the associations between early pregnancy obesity and depressive symptoms are explained by these disorders.

Moreover, depressive symptoms during pregnancy were taken into account in only seven (Ban et al., 2012; Christian, Iams, Porter, & Glaser, 2012; Ertel et al., 2012; Mina et al., 2015; Rallis, Pgd, Skouteris, Wertheim, & Paxton, 2007; Ruyak et al., 2016; Van Poppel, Hartman, Hosper, & Van Eijsden, 2012) of the studies examining the associations between early pregnancy obesity and postpartum depressive symptoms. However, antenatal depression is a well-recognized predictor of postnatal depression, as over 40% of women with clinically relevant depressive symptoms during pregnancy continue to suffer from these symptoms

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after pregnancy (Evans et al., 2012). Thus, it remains unclear if the effects of obesity on postpartum depressive symptoms reflect continuity of symptoms during pregnancy or if obesity is predictive of the onset of symptomatology after pregnancy. Finally, in only four (Fowles, Timmerman, Bryant, & Kim, 2011;

Lukose et al., 2014; Mina et al., 2015; Molyneaux, Pasupathy, et al., 2016) studies out of the 40 focusing on depressive symptoms during pregnancy, and in only one (Mina et al., 2015) of the studies out of the 20 focusing on postpartum depressive symptoms was weight measured [in two studies weight was measured in a subsample (Salehi-Pourmehr et al., 2018; Xuto, Sinsuksai, Piaseu, Nityasuddhi,

& Phupong, 2012)]; in the other studies it was self-reported, even years after delivery, which carries bias (Stommel & Schoenborn, 2009) and may result in misclassification of women into different BMI categories.

Thus, to address the above mentioned gaps in the knowledge, we examined whether maternal early pregnancy BMI calculated from measured weight and height was associated with depressive symptoms reported biweekly during pregnancy and twice after pregnancy. In addition, we studied if these associations were explained by often comorbid hypertensive or diabetic disorders.

2.3 MATERNAL OBESITY AND OFFSPRING HEALTH

2.3.1 DEVELOPMENTAL ORIGINS OF HEALTH AND DISEASE

Maternal early pregnancy obesity does not only compromise the health of a mother but can also result in detrimental transgenerational effects on the offspring health. The Developmental Origins of Health and Disease (DOHaD) hypothesis (Gluckman, Hanson, & Beedle, 2007) claims that exposure to environmental adversities, including maternal stress, depression, unfavourable health behaviours and nutrition during foetal and early life period (Monk, Spicer,

& Champagne, 2012; Padmanabhan, Cardoso, & Puttabyatappa, 2016) can lead to altered programming and developmental adaptations that produce susceptibility to certain diseases across the lifespan (Gluckman et al., 2007). The DOHaD paradigm has stemmed from the studies showing that low birth weight, a surrogate marker of an adverse intrauterine environment, is associated with later life unfavourable health outcomes (Barker & Osmond, 1988; Barker, Osmond, Winter, Margetts, & Simmonds, 1989). According to the hypothesis, prenatal life represents a sensitive period during which organs and systems of the body are plastic and sensitive to the environment (Gluckman & Hanson, 2004).

Thus, it has been suggested that events in utero, which reduce foetal growth, permanently alter the structure and physiology of the offspring (Gluckman &

Hanson, 2004). These adaptations are initially beneficial for survival but if there is a ‘mismatch’ between the early and later life environment these adaptations

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become maladaptive and increase the risk for subsequent disease outcomes (Gluckman, Hanson, & Spencer, 2005).

In recent years, the effects of maternal obesity on later life disease and health outcomes has gained more attention, as increasing amount of women are entering pregnancy with obesity and overweight. It has been suggested that maternal obesity also creates an adverse intrauterine environment (O’Reilly & Reynolds, 2013) which may translate into unfavourable programming effects resulting in adverse health outcomes for the offspring. Indeed, emerging evidence has linked maternal adiposity with several detrimental long-term consequences for the offspring. These include increased risk for respiratory disorders (Forno, Young, Kumar, Simhan, & Celedon, 2014; Harpsøe et al., 2013), congenital malformations (Persson et al., 2017; Stothard, Tennant, Bell, & Rankin, 2009), neurodevelopmental delay (Girchenko et al., 2018), poorer cognitive development (Álvarez-Bueno, Cavero-Redondo, Lucas-de la Cruz, Notario- Pacheco, & Martínez-Vizcaíno, 2017) and cognitive function in childhood (Contu

& Hawkes, 2017). Maternal obesity is also linked with neuropsychiatric disorders (Kong, Norstedt, Schalling, Gissler, & Lavebratt, 2018; Rivera, Christiansen, &

Sullivan, 2015), including attention deficit hyperactivity (Gardner et al., 2015;

Kong et al., 2018; A. Rodriguez et al., 2008; Alina Rodriguez, 2010), conduct (Kong et al., 2018), mood (Kong et al., 2018; Van Lieshout, Robinson, & Boyle, 2013), anxiety (Rivera et al., 2015), and autism spectrum disorders (Gardner et al., 2015; Kong et al., 2018; Xiang et al., 2015), psychosis (Kong et al., 2018) and schizophrenia (Khandaker, Dibben, & Jones, 2012).

Moreover, maternal early pregnancy obesity is linked with an increased risk for offspring obesity from childhood to adulthood (O’Reilly & Reynolds, 2013) and poorer cardio-metabolic profile (higher BMI, fat mass, blood pressure, lipids, inflammation) (Eriksson, Sandboge, Salonen, Kajantie, & Osmond, 2015; Godfrey et al., 2017; Kaseva et al., 2018). The adverse adult outcomes additionally include increased risk for diabetes (Drake & Reynolds, 2010; Eriksson, Sandboge, Salonen, Kajantie, & Osmond, 2014), cardiovascular disease morbidity and mortality (Eriksson et al., 2014; Reynolds, Allan, et al., 2013) and all-cause mortality (Reynolds, Allan, et al., 2013).

2.3.2 DEVELOPMENTAL ORIGINS OF HPA AXIS

One of the proposed key mechanisms that may link maternal overweight and obesity with adverse offspring outcomes is early life glucocorticoid-mediated programming of the HPA axis (Reynolds, Labad, et al., 2013; Seckl & Meaney, 2004) which has a critical role in the regulation of cardiovascular, metabolic, and neurological systems (Moisiadis & Matthews, 2014).

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HPA axis regulates the production and secretion of corticosteroids under chronic and acute stress and has an important role in maintaining body homeostasis (Moisiadis & Matthews, 2014). HPA axis activation begins by the release of corticotrophin releasing hormone (CHR) and vasopressin from the paraventricular nucleus of hypothalamus, stimulating the secretion of adrenocorticotropic hormone (ACTH) from pituitary gland (Moisiadis &

Matthews, 2014). The ACTH then stimulates the production and release of glucocorticoids which is cortisol in humans, from the adrenal cortex. Further, glucocorticoids bind to the glucocorticoid receptors and mineralocorticoid receptors in different regions of the HPA axis and brain and modulate further HPA axis activity by inhibiting ACTH and CHR release (Moisiadis & Matthews, 2014).

Cortisol concentration follows a natural diurnal pattern, fluctuating throughout the day as well as in response to stress (Incollingo Rodriguez et al., 2015). Normally cortisol secretion increases and peaks within an approximately 30 to 45 minutes after awakening, followed by rapid drop in subsequent hours and then steadily declining throughout the day until the nadir reached around bedtime (Weitzman et al., 1971).

Together with the development of the brain, HPA axis maturates rapidly during the foetal period and is highly susceptible to alterations in maternal HPA axis reactivity (Duthie & Reynolds, 2013). During healthy pregnancy, maternal production and release of glucocorticoids undergoes remarkable changes essential for the normal foetal maturation and development (Duthie & Reynolds, 2013). Studies examining the effects of adverse prenatal adversity indicated by birth weight and/or size on cortisol secretion later at life have shown that prenatal environmental adversity is resulting in both hyper-and hypoactivity of the HPA axis (Kajantie et al., 2002; Kajantie & Räikkönen, 2010; Reynolds et al., 2005) suggesting the alterations in HPA axis reactivity may result from the intrauterine programming of HPA axis (Duthie & Reynolds, 2013). Thus, this may result in detrimental health outcomes as dysregulation of HPA axis is linked with several physical and mental health diseases, including depression (Watson & Mackin, 2006), obesity (Incollingo Rodriguez et al., 2015), cardiovascular disease and diabetes (Rosmond & Bjorntorp, 2000).

2.3.2.1 Maternal early pregnancy obesity and offspring HPA axis functioning

HPA axis dysregulation is recognized among individuals with overweight and obesity. While several studies have demonstrated that adiposity is associated with increased cortisol levels (Incollingo Rodriguez et al., 2015) there are studies showing that overweight and/or obesity are related with lower morning levels of

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plasma cortisol (Praveen et al., 2011), lower salivary cortisol levels in response to awakening (Champaneri et al., 2013) and blunted diurnal salivary cortisol pattern (Champaneri et al., 2013; Kumari, Chandola, Brunner, & Kivimaki, 2010).

Evidence suggests that these alterations in HPA axis activity are maintained in overweight and obese pregnancies. Indeed, women who were overweight, obese or severely obese (BMI ≥40 kg/m²) in early pregnancy were found to have lower total serum or plasma cortisol (Berglund et al., 2016; Luiza, Gallaher, &

Powers, 2015; Stirrat et al., 2016), lower free cortisol and lower morning salivary cortisol (Aubuchon-Endsley, Bublitz, & Stroud, 2014; Stirrat et al., 2016) during pregnancy. There is also evidence that women who were severely obese in early pregnancy had lower levels of hormones that regulate circulating cortisol levels, namely corticotrophin binding globulin, corticosteroid releasing hormone and oestrogens (Stirrat et al., 2016). Thus, the alterations in cortisol secretion during overweight and obese pregnancy may affect the programming of the offspring HPA axis function, resulting in alterations of cortisol secretion and response to stress (Reynolds et al., 2007).

However, only a handful of studies have focused upon associations between maternal overweight and obesity during pregnancy and offspring HPA axis activity in humans, showing mixed findings. In 0ne study, severe maternal obesity (BMI ≥40 kg/m²) in early pregnancy predicted higher salivary cortisol reactivity in pre-school aged offspring (Mina et al., 2017). In contrast, in two other studies maternal early pregnancy BMI was not associated with offspring diurnal salivary cortisol profile or stress reactivity at preschool age (Elhassan, Miller, Vazquez, & Lumeng, 2015) or with offspring fasting plasma cortisol levels at school age (Phillips et al., 2005). Another study demonstrated that maternal severe obesity in early pregnancy was not associated with offspring cortisol measured from cord blood (Stirrat et al., 2017).

The inconsistent findings of the previous studies (Elhassan et al., 2015; Mina et al., 2017; Phillips et al., 2005; Stirrat et al., 2017) may reflect differences in study set up. Further, the sample sizes have been small and follow ups have been limited to childhood. As the HPA axis may undergo age-related changes (Gunnar, Wewerka, Frenn, & Griggs, 2014; Lupien, McEwen, Gunnar, & Heim, 2009) it is important to know if any adverse effects of maternal overweight and obesity on offspring HPA axis activity persist into adulthood. Thus, we studied whether maternal early pregnancy BMI was associated with diurnal salivary cortisol, a marker of HPA axis activity, in young adult offspring.

2.4 CHILDHOOD RISK FACTORS FOR OBESITY

As discussed earlier, maternal adiposity has been linked with poorer offspring cognitive development and function in childhood (Álvarez-Bueno et al., 2017;

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Contu & Hawkes, 2017). As childhood cognitive functioning is suggested to predict later life health outcomes (Calvin et al., 2017) we examined whether early childhood cognitive ability is linked with adulthood adiposity and physical activity, one of the key health behaviours associated with overweight and obesity (Weinsier et al., 1998).

2.4.1 CHILDHOOD COGNITIVE ABILITY AND OBESITY IN ADULTHOOD Effects of the childhood cognitive ability test scores on later life health, morbidity and mortality are studied in the field of cognitive epidemiology (Deary, 2010) and nowadays it is well established that children with lower intelligence test scores are more likely to suffer from various physical diseases, including cardiovascular disease (Hart et al., 2004; Power, Jefferis, & Manor, 2010) and mental disorders (Hatch et al., 2007; Koenen et al., 2009) later in life.

Cognitive ability term is used in literature often parallel with terms such as intelligence, mental abilities, cognitive functions or intelligence quotient (IQ) (Deary & Batty, 2007) which are describing the capability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience (Deary, Penke, & Johnson, 2010; Gottfredson, 1997). Further, individuals differ in their cognitive ability and these differences are measured by using psychometric tests. Different domains of cognitive ability, such as reasoning, verbal, spatial and processing speed, are sometimes considered to be independent but it is established that approximately half of the variance in different domains of cognitive abilities is accounted for by a general cognitive factor/intelligence, often designated as ‘g’ (Deary et al., 2010). Cognitive abilities are shown to be inheritable (Deary et al., 2010) and are also suggested to be highly stable throughout life (Deary, Pattie, & Starr, 2013; Deary, Whalley, Lemmon, Crawford, & Starr, 2000).

Research conducted over the past decade in the field of cognitive epidemiology has identified childhood cognitive ability as a novel risk factor for obesity. Two of the previous studies showed that lower childhood general intelligence measured at 11 years of age was associated with obesity calculated from measured height and weight at age of 70 (Corley, Gow, Starr, & Deary, 2010) and 79 years (Aslan, Starr, Pattie, & Deary, 2015). A set of studies have demonstrated that lower childhood cognitive ability test scores measured between ages 7 to 16 were associated with higher odds for obesity at ages from 30 to 42 years (Batty, Deary,

& Macintyre, 2007; Chandola et al., 2006; Gale et al., 2009) and with higher BMI between ages 45 to 52 years (Kanazawa, 2013; Lawlor, Clark, Davey Smith, &

Leon, 2006; Power et al., 2010). Furthermore, in one study those with lower verbal reasoning at 3 years of age had higher risk for being obese at the age of 38 years (Belsky et al., 2013). Two studies also reported that lower childhood

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intelligence test scores were associated with weight gain between age 16 to 51 years (Kanazawa, 2013) and with greater gain in BMI between age 16 and 42 years (Chandola et al., 2006). In the latter study (Chandola et al., 2006), the association between childhood IQ and weight gain was largely mediated by education and dietary characteristics. However, two existing studies reported no association between childhood cognitive ability measured at 11 years of age and adulthood BMI (Harris, Brett, Deary, & Starr, 2016; Hart et al., 2004).

While previous studies have provided valuable information on the early life risk factors for overweight and obesity, all of the previous studies have solely used BMI as an indicator for overweight and obesity. Further, only four of these studies have consistently calculated BMI from measured (Aslan et al., 2015; Belsky et al., 2013; Corley et al., 2010; Hart et al., 2004) rather than self-reported or a mixture of measured and self-reported (Batty, Deary, & Macintyre, 2007; Chandola et al., 2006; Gale et al., 2009; Harris et al., 2016; Kanazawa, 2013; Lawlor et al., 2006;

Power et al., 2010) weight and height. The problem with BMI is that it does not distinguish between fat-free and fat tissue, although a higher amount of fat-free tissue, such as muscle, is associated with health benefits, whereas excess fat is harmful (Heitmann, Erikson, Ellsinger, Mikkelsen, & Larsson, 2000). The diagnostic performance of measured BMI to detect people with excess BF% is highly specific, but measured BMI has a poor sensitivity as it fails to identify nearly half of the people with excess BF% (Okorodudu et al., 2010). Furthermore, sensitivity and specificity of self-reported BMI to detect people with excess BF%

are even poorer, as self-reports suffer from under-estimation bias (Connor Gorber, Tremblay, Moher, & Gorber, 2007; Hattori & Sturm, 2013).

Thus, it remains unclear if childhood cognitive ability is also associated with body fat later in life. Hence, our study add to the literature by examining the associations between childhood cognitive abilities and BF% assessed by BIA in young adulthood.

2.4.1.1 Childhood cognitive ability and physical activity in adulthood One possible mechanism between childhood cognitive ability and obesity is lifestyle behaviors, such that people with higher intelligence might interpret and respond to health advice differently and hence engage in healthier behaviors (Deary & Batty, 2007). Studies have provided some evidence for this mechanism showing that higher cognitive ability in childhood is associated with a healthier diet (Batty, Deary, Schoon, & Gale, 2007; Kanazawa, 2013), reduced risk of smoking initiation (Daly & Egan, 2017; Kubička, Matějček, Dytrych, & Roth, 2001; Martin, Fitzmaurice, Kindlon, & Buka, 2004) and higher likelihood of smoking cessation (Daly & Egan, 2017; Taylor et al., 2003). While findings with alcohol consumption are more mixed (Batty et al., 2008; Hatch et al., 2007;

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Kubička et al., 2001; Wennberg, Andersson, & Bohman, 2002), some studies have shown that higher childhood cognitive ability is associated with an increased odds for being a non-drinker in adulthood (Mortensen, Sorensen, & Gronbaek, 2005) and with a lower likelihood of experiencing alcohol-induced hangovers in midlife (Batty, Deary, & Macintyre, 2006).

One of the key health behaviours associated with overweight and obesity is PA (Weinsier et al., 1998). Today, 31.1% of world’s adult population is inactive (Hallal et al., 2012) and it has become increasingly clear that low levels of PA and high levels of time spent in sedentary behaviours, including sitting, lying down, and screen-based entertainments (Pate, O’Neill, & Lobelo, 2008) are associated with overweight and obesity. In high-income countries physical inactivity is also the sixth leading risk factor for burden of disease as measured by disability adjusted life years (DALYS): it accounts for 4.1% of DALYs, 5 million per year (World Health Organization, 2009).

The extent to which childhood cognitive ability is related to PA and sedentary behaviours in adulthood is less well known and only three previous studies exist.

The result from the first study showed that verbal and non-verbal ability at 1o years of age were associated with higher likelihood of taking exercise and exercising more intensively at the age of 30 years (Batty, Deary, Schoon, et al., 2007). The second study showed that general intelligence combined from test scores taken at 7, 11 and 16 years of age was associated with more frequent exercising at ages 33, 42, 47 and 51 years (Kanazawa, 2013). Finally, the third study showed that higher general intelligence averaged across ages 7, 9, 11, and 13 years predicted a decreased likelihood of being a sedentary adult, and in the nonsedentary group higher general intelligence in childhood predicted higher levels of leisure-time PA (Belsky et al., 2015).

However, in all of the previous studies (Batty et al., 2007; Belsky et al., 2015;

Kanazawa, 2013) PA has been measured by self-reports which hinder the conclusions of the studies as self-reports of PA are vulnerable for response bias and over-and underestimation of true PA and sedentary time (ST) (Prince et al., 2008). Hence, to expand the literature, we examined whether childhood cognitive ability is associated with objectively measured PA and ST in young adulthood.

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3 AIMS OF THE STUDY

The overall aim of this study was to examine the associations of maternal early pregnancy BMI with health related outcomes of the mother and adult offspring and the effects of childhood cognitive ability on adulthood body composition and PA.

Growing evidence suggests that maternal early pregnancy obesity increases maternal depressive symptoms during and after pregnancy. However, a number of gaps in the previous studies hinder the validity of the findings. Further, it is suggested that the harmful health related effects of maternal early pregnancy obesity might be passed down to the next generation via early life programming of HPA axis. Previous studies have demonstrated that adverse intrauterine environment is resulting in perturbations in offspring HPA axis functioning. Yet, evidence linking maternal overweight and obesity with offspring HPA axis activity is scarce and limited to childhood follow-ups. Based on the previous studies, I hypothesized that maternal early pregnancy overweight and obesity are associated with depressive symptoms during and after pregnancy and with alterations in adult offspring HPA axis functioning.

Maternal early pregnancy obesity is also associated with poorer offspring cognitive functioning in childhood. Furthermore, lower childhood cognitive ability is suggested to be a risk factor for subsequent obesity and obesity promoting health behaviors, such as lower levels of PA. Previous studies, however, have used BMI as a proxy for adiposity and used self-reports to assess PA. Based on the cognitive epidemiology framework, I hypothesized that lower childhood cognitive ability is associated with unfavorable adulthood body composition and less beneficial patterns of PA which is one of the key health behaviors linked with obesity.

The specific goals of the thesis were:

1: To study the associations between maternal early pregnancy BMI and maternal depressive symptoms during and after pregnancy (Study I).

2: To study the association between maternal early pregnancy BMI and offspring HPA axis functioning indicated by diurnal salivary cortisol measured at 25 years of age (Study II).

3: To study the associations between childhood cognitive ability at 56 months of age and body composition and physical activity at 25 years of age (Studies III and IV).

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4 METHODS

4.1 PREDICTION AND PREVENTION OF PREECLAMPSIA AND INTRAUTERINE GROWTH RESTRICTION

(PREDO) STUDY

4.1.1 PARTICIPANTS

Study I of the thesis is based on the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study which is a prospective, multicentre study of Finnish women and their children (Girchenko et al., 2017).

5332 women with a singleton, intrauterine pregnancy, who visited antenatal clinics of the 10 study hospitals for their first ultrasound screening at 12+0–13+6 weeks + days of gestation, were recruited in the study. Of the recruited women, 4785 (89.7%) were eligible and consented to participate, and 4777 women gave a birth to a live-born infant between 2006 and 2010. The study protocol was approved by the Ethics Committee of Obstetrics and Gynaecology and Children and Psychiatry of the Helsinki and Uusimaa Hospital District and by the participating hospitals. All participants provided written informed consent.

The study comprises two arms: pregnant women with a known clinical risk factor status for preeclampsia and intrauterine growth restriction (IUGR;

N=1079) and pregnant women who volunteered to participate regardless of their risk factor status for preeclampsia and IUGR (N=3698). The study participants attended up to four visits at the antenatal study clinics and completed a baseline study questionnaire during pregnancy. They also completed prenatal stress- related questionnaires, including a questionnaire of depressive symptoms, biweekly throughout pregnancy. Questionnaires were completed at the follow- ups taking place 2 weeks and 6 months postpartum.

Of the 4777 women, data on early pregnancy BMI was available on 4745 (99.3%) women, as well as on hypertensive and diabetic pre-pregnancy and pregnancy disorders. Of these 4745 women, 3372 (71.1%) had data on depressive symptoms during pregnancy and 3286 (69.3%) up to 12.5 months postpartum.

3234 (68.2%) women had depressive symptoms data available both during pregnancy and at an average of 2.4 (SD=1.2) weeks and/or 28.2 (SD=4.2) weeks after pregnancy. These 3234 women formed the analytical sample of Study I.

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4.1.2 MATERNAL EARLY PREGNANCY BODY MASS INDEX (STUDY I) Early pregnancy BMI was derived from the Finnish Medical Birth Register (MBR) (Gissler & Haukka, 2004). BMI was calculated from weight and height measured by a nurse at the first visit to the antenatal clinic, in our sample on average 8+4 (SD=1+3) weeks + days of gestation when pregnancy weight gain is still minimal.

BMI was categorized into underweight (<18.5 kg/m²), normal weight (18.5-24.99 kg/m²), overweight (25-29.99kg/m²), and obese (≥30 kg/m²) groups according to the WHO criteria (World Health Organization, 2000).

4.1.3 DEPRESSIVE SYMPTOMS DURING AND AFTER PREGNANCY (STUDY I)

Depressive symptoms were measured using the Center for Epidemiological Studies for Depression scale (CES-D) (Radloff, 1977) which is a self-report scale containing 20 items. The 20 CES-D questions were rated on a scale from none (0) to all the time (3), resulting in a range of possible total scores from 0 to 60. Higher scores indicate more depressive symptoms during the past week and a sumscore of ≥16 indicates clinically relevant depressive symptoms (Radloff, 1977; Vilagut, Forero, Barbaglia, & Alonso, 2016). The CES-D has been used extensively and validated in pregnant populations (Maloni, Park, Anthony, & Musil, 2005; Nast, Bolten, Meinlschmidt, & Hellhammer, 2013). In our sample, the CES-D (Cronbach`s α=.88 to .92 in the 14 biweekly measurement points during pregnancy and the two measurement points after pregnancy) showed high internal consistency (Lahti et al., 2017).

Women completed the scale biweekly up to 14 times throughout pregnancy starting from 12+0-13+6 gestation weeks + days until 38+0-39+6 gestation weeks + days or delivery. After pregnancy the scale was completed at an average at 2 weeks and 6 months postpartum.

4.1.4 COVARIATES AND CONFOUNDERS (STUDY I)

Data on hypertensive and diabetic pre-pregnancy and pregnancy disorders, including GDM, preeclampsia, gestational hypertension, type 1 diabetes and chronic hypertension, were extracted from the Finnish MBR (Gissler & Haukka, 2004) and/or the maternity care cards and hospital records. Each individual diagnosis was further verified by a clinical jury for the subsample (n=969) recruited based on their increased risk of preeclampsia and intrauterine growth restriction.

GDM was defined as fasting, 1h or 2h plasma glucose during a 75g oral glucose tolerance test ≥5.1, 10.0 or 8.5 mmol/L, respectively; preeclampsia as blood pressure ≥140 mmHg systolic and/or ≥90 mmHg diastolic in two consecutive

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measurements and proteinuria ≥0.3 g/24 hours; gestational hypertension as blood pressure ≥140 mmHg systolic and/or ≥90 mmHg diastolic in a women who were normotensive before 20 weeks of gestation. Women with type 1 diabetes and with chronic hypertension defined as blood pressure ≥140 mmHg systolic and/or

≥90 mmHg diastolic or medication for hypertension before 20 weeks of gestation were identified.

Data on maternal age at delivery (years), smoking during pregnancy (did not smoke/quit during first trimester/smoked throughout pregnancy), parity (primiparous/multiparous), child’s gestational age (weeks), birth weight (grams) and sex (girl/boy) were extracted from medical records and/or MBR.

Women reported in early pregnancy alcohol consumption during pregnancy (yes/no), maternal leisure-time PA (combined into three categories: not at all/less than once a month/1 to 2 times per month; approximately once a week/2 to 3 times per week; 4 to 5 times per week/approximately every day) and educational level (lower secondary or less; upper secondary; tertiary).

4.2 ARVO YLPPÖ LONGITUDINAL STUDY

4.2.1 PARTICIPANTS

Studies II, III and IV of the thesis are based on the Arvo Ylppö Longitudinal Study (AYLS), the Finnish arm of the Bavarian Longitudinal Study (BLS) (Heinonen et al., 2008; Riegel, Ohrt, Wolke, & Österlund, 1995; Wolke, Sohne, Riegel, Ohrt, &

Osterlund, 1998). Figure 3 presents the flow chart of the participants and attrition of the studies II-IV. The participants of the AYLS were recruited between March 15, 1985 and March 14, 1986 from the seven maternity hospitals in Southern Finland in the county of Uusimaa. Of the 15311 babies born in the area during the study period, 2193 (1193 boys) were recruited to the study. 1535 (867 boys) of the recruited babies were admitted to the neonatal wards of the obstetric units, or transferred to the Neonatal Intensive Care Unit of the Children’s Hospital within ten days of birth because the infant needed brief inpatient observation and treatment due to illnesses and complications. An additional 658 (326 boys) infants not admitted to neonatal wards were prospectively recruited from births after every second hospitalized infant in the three largest maternity hospitals of the study area during the same period. The childhood study protocol was approved by the ethics committees of the Helsinki City Maternity Hospital, the Helsinki University Central Hospital, and the Jorvi Hospital and in adulthood by the Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District. An informed consent was obtained from parents (childhood) and participants (adulthood).

Obesity and associated health risks : outcomes of maternal early pregnancy obesity and child's cognition