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For the purposes of today,

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I would think since very briefly only cover the context and the background objectives and methods and spend most of my time talking about

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the key lessons that we learnt from that work to pull out the messages that I think may be transferable to other resource settings.

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So that's the outgoing. After talking about the key lessons, I'm also going to talk very briefly about upcoming work, which I'm just embarking on,

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which will be looking at perinatal mental disorders in India within the three network, which I'll describe later.

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So I don't need to convince this audience about the importance of mental health and perinatal depression,

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but like depression in all other walks of life, it's common and the burden is in equitably distributed.

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So it's a low and middle income countries bear the significant bulk of the burden, perhaps different from depression at other times of life.

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Depression during pregnancy or the perinatal period has, I would argue, more far reaching consequences.

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And not only does it affect women themselves and their relationships and their ability to work and function in society.

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But there's a lot of evidence now that depression and in mothers during pregnancy and after the very can have adverse effects on their infants,

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and that physical adverse physical effects and stunting increased risk of diarrhoeal disorder,

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diarrhoeal infections and other infections, but also cognitive impairments, emotional impairment.

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And there's even evidence now that children of depressed mothers are more likely to have emotional problems as adolescents themselves.

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So, especially in low income settings, there's a real risk of intergenerational effects of depression.

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And it's a treatable condition so many people are very worried about, you know,

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treating women who are pregnant or breastfeeding, but there are actually safe ways of of treating this condition.

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So to give a little bit of context to the geographic setting.

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So Myanmar has had civil conflict since 1984, and that's mainly between the UM, the central government,

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which consists mainly of the ethnic majority Burman Group and multiple smaller ethnic groups.

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Very. So this shows all the different ethnic groups that are all fighting, either for autonomy or some degree of independence,

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and many of them are armed, so this has led to displacement of populations to all the surrounding countries.

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And where I was based in this town called myself and I work with a group with a research unit called SMI, the Shukla Malaria Research Unit.

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And along this border, it's estimated so between Myanmar and Thailand.

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It's estimated that those 200000 migrants and about 150000 refugees.

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And these were the populations that I was working with. So they were two distinct groups of the population.

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So they were refugees who live in an established refugee camps.

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And this is an example of one of the biggest refugee camps, which is home to about 40000 people.

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And refugee camps offer a certain degree of safety.

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Because everybody gets a house, everybody gets food ration, their NGOs that provide education and health services.

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But you give up a lot of freedom of movement.

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So once you within these camps, you're not you're not really allowed to leave until you get formally resettled to another country.

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The migrant population is slightly different, so they don't live within these refugee camps.

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They live in villages along the border, making a living in agriculture or in service industries or in manufacturing.

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And they make the trips. This is some migrant women arriving to the smart health clinic, and they often commute back and forth.

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So this river that you see here is the Mighty River, which is the border between Thailand and Myanmar.

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So you can see on that side is already Myanmar. So it's physically not a long distance.

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So they are very mobile group the migrants. So the objective is the work that I did was to find a tool that we could use to assess

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perinatal depression in the setting because mental health in general was is very,

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very much neglected in this area hasn't really been assessed before.

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So the first objective was to find a tool that we could actually use then to use that

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tool to look at to find the prevalence and risk factors for perinatal depression.

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I also wanted very much to add a qualitative component,

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so we wanted to explore women's own experiences and then look at treatment options for this setting.

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So it was a mixed methods study. The big part the first part of it was a cohort study where we recruited women in pregnancy and then followed

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them up to one month postpartum and assessed depression status at multiple time points throughout.

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We had five hundred and sixty eight women for that part,

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and then I did an in-depth qualitative component with 11 women who had very severe depression.

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OK, so that's very briefly just providing the context, and I know I've skipped over the methods,

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so please ask if you want to know more, but I thought I'd spend most of the time just talking about what we found.

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So the things I wanted to talk about here are the prevalence that we found, the risk factors, the importance of qualitative narratives,

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which I think is an area that, especially for people from medical or public health backgrounds, is quite a neglected area.

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The importance of finding the right tool to use and then putting screening or some kind of case identification into practise.

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So our first finding was that prenatal depression was very common in this setting.

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Um, this is the prevalence of depression across the different time points that we looked at.

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If you just look at one months postpartum. This is the cumulative prevalence that I'm showing here.

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So it goes up over time. So at the at the time point of one month's postpartum,

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so by the time we'd followed women up from the first trimester of pregnancy through to one month postpartum,

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seventeen point three percent of women have experienced moderate to severe depression and moderate to severe depression.

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We defined as mild, sorry, minor or major depression using the DSM criteria.

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But one of our big findings, and that was quite interesting to me was that.

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So the difference between these two bars is that this is just moderate to severe depression and the yellow bars is any form of depression.

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So the difference in the column height is basically those people who are experiencing a mild severity of depression.

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And it was striking to me that if you look at most kind of psychiatric research, this group of women, so the mild,

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mildly depressed people with mild mild depression are completely neglected when actually the women we spoke to,

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even if they were in that mild category, were having significant difficulties in their lives.

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Another interesting finding, which was which was somewhat unexpected,

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or at least something that we hadn't set out to look at systematically was that suicidal ideation was very common.

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So almost a third of women that we spoke to had suicidal ideation and five percent had made first attempts.

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And actually, when we went back and looked at data, we found that over the past five years,

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half of all maternal deaths had been due to suicide, and that was something that had.

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Despite it being so common,

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had never really been picked up in the in a systematic way or highlighted as being one of the major causes of maternal deaths.

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And what we found was that. So this so when we looked at those women who were having who had suicidal ideation,

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this is looking at all the women in the first trimester of pregnancy who said who

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who had suicidal ideation and looking at what depression category they fell into.

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And the key message of this pie chart is that.

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A quarter of the women who had suicidal ideation fell into this moderate or severe depression category, actually,

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three quarters of women who are experiencing suicidal thoughts have either only very mild depression

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as per the diagnosis or are completely negative in the interview for any depressive symptoms.

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So it made us think,

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is there something happening around suicidal ideation that is completely separate from the notion of depression as a as a disorder?

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Risk factors only go briefly the main.

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So this was a multivariable regression analysis, these were the factors that remained significantly associated with perinatal depression.

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The main message here was that like and this was just alluding to a lot of the

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factors that were associated with perinatal depression were psychosocial factors,

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and they were things outside the remit of kind of biomedicine.

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So not having enough social support, having experienced trauma, having experienced interpersonal or domestic violence.

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So, yeah, that just made it clear to us that actually we're working within a whole social system of issues.

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Qualitative narrative, so we spoke in depth to women who had experienced severe depression and.

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I'll read you some quotes. Every day, my children ask me to buy them sweets, but I cannot because I have no money.

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I cannot buy shoes for them. It makes me feel sad and pity for them.

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It's about violence, so there was a high there was a lot of interpersonal violence between couples.

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When I fight with my husband, I feel sad for a whole day. He hits me a lot.

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Even without drinking alcohol, he hits me. So men drinking alcohol and then that leading to domestic violence was extremely common.

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I worry about my children and their future. I feel so sad I can't breathe.

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I cry when I think about my daughter in Burma, but I cannot cry, I lock it up inside and then I get chest pain.

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My husband is in Bangkok, I cannot contact him every night, I cry for him.

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Sometimes I think I don't want to stay in this world anymore. Sometimes I just want to close my eyes forever.

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I feel weak. I have no more strength. I don't have the energy to even open my eyes.

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So I wanted to highlight Anna's presentation by video.

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Earlier, she said something about numbers not doing justice to the depth of the unmet need.

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And I feel very strongly that often when you read quotes like this, they mean a lot more than seeing what the prevalence is in terms of percentages.

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And that I think it's very important in these contexts to actually get the participants,

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the people who are experiencing mental health issues to express in their own words and get across what they're feeling and what they're experiencing.

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So finding the right tool, I could talk for a whole hour just on this, and I will try to keep it brief,

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but we had a very difficult time figuring out what tool we would actually use to identify depression amongst people.

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So the most commonly used tool, as you may know in perinatal women, is the Edinburgh postnatal depression scale.

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It's been used widely translated into many, many different languages.

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We found it just didn't work, so our population was a very low literacy population.

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It's a very oral culture. And these tick boxes and these criteria of.

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You know, asking someone to distinguish between hardly ever and sometimes, and it just it didn't work, it was very confusing.

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Women just didn't like it and it was extremely time consuming.

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We tried the Q9 nine, which has a bit of a more structured and and slightly more simplified scoring system,

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but that also was not did not go down well.

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And in the end, what was a real game changer to us was that we tried administering the structured clinical interview,

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which is an open ended diagnostic tool, which is something that is not a screening tool.

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It's a diagnostic instrument, and it's classically seen as the gold standard with which you validate screening tools.

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But this completely changed everything for us because suddenly, instead of.

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You know, myself and one of the local councillors kind of interrogating women,

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it felt like almost all of these other parts were these screening tools and trying to get them to pick one tick box.

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We were actually starting to have conversations and suddenly getting so much more information,

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and it was like putting flesh on the bones of this conversation.

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So in the end, unconventionally we stuck with this structured clinical interview for assessing depression throughout our study.

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But I thought this was an important point to make, just because I think it's really essential that you get the right tool before you go out and

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start trying to identify depression and or other mental disorders in different settings.

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So putting screening into practise in a way,

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the perinatal period is an ideal time at which to identify depression and other mental disorders

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because it's a time when there is increased contact between women and health care services,

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whether that's in primary care or antenatal or in hospital.

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But even in low income settings, there tends to be more contact between health professionals and women at that point in time.

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In Thailand, where I was,

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the way it worked was that the women would all arrive to the clinic en masse in a big truck that would pick them up from different locations,

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bring them to the clinic, and they would sit there for four or five hours before the truck would then take them back home again,

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so they would wait for everybody to be seen.

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And then they would all go home, be taken home again so that those that four or five hours was a perfect window of opportunity.

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To not only do the study that we did, but more generally to do health promotion about mental health and to potentially introduce screening.

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So this is another picture of the setting,

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so people sitting around waiting and because they're not doing anything else is just a convenient time to introduce screening programmes.

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OK, so very, very briefly, the project that I'm now embarking on is with the Mazzarri platform,

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which is the maternal and perinatal health research collaboration India.

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It's a collaboration that was established by Manisha Now, who works at the National Perinatal Epidemiology Unit here in Oxford.

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And it's a network of 14 hospitals across four states in India.

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And the primary aim of the network was to look at severe complications of pregnancy.

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So not mental health related, but looking at things like anaemia and pregnancy and heart failure and pregnancy.

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And I will be sorry. This is the this is the.

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The institutions that are involved in the network and the project that I will be working on will be using that platform,

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but looking at mental health in women during pregnancy and after delivery.

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And again, we're hoping we're hoping to identify and validate a screening tool and then determine

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prevalence and risk factors for the perinatal from perinatal mental disorders.

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We're still liaising with a different partner hospitals to see which sites I'm going to be using,

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and we're planning to start that in the middle of next year.

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And she.