Said Shahtahmasebi, PhD
[citation: Shahtahmasebi, Said. (2019) Editorial: Survival of the fittest. DHH; 6(4):http://www.journalofhealth.co.nz/?page_id=1958.]
1. Old age
Average life expectancy has been increasing around the world (https://www.nih.gov/news-events/news-releases/worlds-older-population-grows-dramatically), which poses new dilemmas for society and policy makers. As more people live to a ripe old age more resources from formal and informal care support networks are needed.
However, we often fail to distinguish between old age survivors influenced by our perception of old age that equates aging to high levels of dependency. For example, some people grow to a ripe old age, while some become frail sooner and retire early, or require looking after post retirement, and some may die within years of retiring. Some researchers have investigated the timing of retirement as a possible indicator of longevity in old age (e.g. whether early retirement improves longevity, see (Haynes, et al., 1978; Tsa, et al., 2005)). However, in such cases higher rates of mortality after early retirement are most likely due to a selection bias whereby people with poor health tend to retire early and/or die early within a few years of retiring. But, having survived the post-pension period the probability of survival appears to increase. In other words, survivaql in old age is due to a selection bias whereby people who are more independent and mobile and active tend to live longer. So from a social and health care policy development we need to have an idea of how (in)dependency in old age is distributed.
Clearly physical health is one main factor that may influence the probability of survival and at the same time affect mental wellbeing and quality of life. The reverse can also be true with quality of life having an impact on the physical health, or, perception of health, thus affecting the probability of survival. An obvious assumption may be to associate the improved life expectancy to advances in medical technology, food production practices and food security. However, we know that such an assumption may not hold because despite advances in medical technologies, the same diseases (e.g. CHD, cancer, suicide) are still the top 10 killers globally.
We also know that, elderly people strongly prefer to live and die in their own home (Wenger, 1984). A feedback effect of the wish to remain in one’s own home was the fear of being taken to hospital or to a care home and thus never return to their home. Mental wellbeing may have been influenced by loneliness, morale, size of support network, and so on. For many elderly, every day contact with service deliveries such as the postman, the milkman, and meals on wheels had become a means for company and a way out of loneliness. The knowledge that the next-door neighbours could be summoned to help by simply knocking on the wall was a source of reassurance not to leave one’s home. Unfortunately, this level of company has been eradicated due to the advances in internet technology over the last couple of decades, leading to a major reduction in service deliveries. More elderly people are moved out of their homes and into residential care and secure village style housing where paid help may be available.
It is not clear whether quality of life improves longevity or not, but such basic social activities that improve quality of life will surely have a positive effect on mental wellbeing. Policy development must take into account that while health care interventions are essential in old age, what is more important is overall wellbeing, (see article 2 in this issue, also see (Shahtahmasebi, et al., 1992; Wenger, et al., 1995; Wenger, et al., 1996)).
On the other hand, the end of life is not always due to old age or illness. In a proportion of the population death occurs by the person’s own choice.
To some extent suicide has been social conditioning that death could be the answer to life adversities, problems, trauma and such like. For example, in examining the portrayal of suicide in literature and religious documents, Pridmore and Pridmore conclude that life’s adversities rather than a mental illness has consistently been equated to suicide (Pridmore, 2019).
Since the medicalisation of suicide, and without substantive theory and statistical evidence, the public has been conditioned to believe that suicide is the result of a mental illness (Shahtahmasebi, 2013, 2014). Every year, substantial resources are poured into mental illness services globally, specifically, for suicide prevention, but suicide rates have followed their own pattern. For example, In New Zealand, suicide numbers for 2018-19 reached a record high for the fifth consecutive year since 2008, and no one has been held responsible for the failures of this policy. It seems that the medicalisation of suicide has removed accountability from the government, their policy makers and their advisors. If anything, after each failure, the government pledges even more resources! Where is the wisdom in this policy?! These results in any other funded department or organisation would lead to the removal of officials and advisors, and more importantly, would have questioned the approach.
However, the last five years is not the only period where the suicide rates went up. Over a much longer period – cycles of up-down in suicide rates can clearly be observed. Even over a shorter period such as 2008-19 the suicide trend clearly describes a cyclic pattern, e.g. cycles are described in the following news item:
“…We did have quite high numbers back in the 80s and 90s, and in the late 90s things started to go back down, and once we hit the mid-2000s they started rising again.” (Radio New Zealand, 2019a).
It can be seen that when overall suicide rates is broken doen into various subgroups such as males, females, age-group, suicide rates for these subgroups also follow a cyclic pattern. It can also be observed that these cycles do not have start and finish at the same time; some groups’ trend has a lead whilst others lag behind. So while suicide trends for one group begins a downturn another group’s may be still trending up (lag) and another group’s may be trending down (lead). The problem is that the “experts” highlight the groups with a lagging trend as those who did not receive or uptake mental illness services. For example in recent years, farmers and men have been targeted. In particular, there has been an emphasis on reversing male chauvinism in order to encourage more men to talk about their, problems and feelings. This will pass once the lagging trends catch up.
This is called shifting the blame onto the victims. The claim that men are not good at talking, or won’t talk about their problems/feelings is total nonsense. Men do talk and ask for help but very few hear them and those who do hear them are unable to listen. The reason is the absence of a suicide discourse that empowers the public to engage with the affected person rather an automatic assumption of mental illness that makes suicide the property of an specialist. Thus, the public’s only way of response is either to avoid the situation or advise the person to call their doctor. Doctors are not equipped to deal with life crises, or financial and social problems. Furthermore, men do not wish to be labelled mentally ill should they express their thoughts. Even if they seek medical help, medical professionals will diagnose a mental illness – they do not address suicide. Because society has been conditioned to automatically believe mental illness/depression and suicide are one and the same. Therefore, a call for help may be through subtle changes in behaviour, out of character behaviour, mood swings, or, expressing feelings in coded conversations and hints.
As a result, over the last century or so – more and more resources have been directed at mental illness. During the cycle downturn the policy is hailed as a success, but, during the cycle upturn the “experts” blame undiagnosed mental illness and a lack of service uptake for the failure of the policy.
The century long experience of perpetual up-down suicide trends provides strong evidence that preventing suicide by targeting mental illness has not worked. Furthermore, it also suggests that suicide trends may be, at least in part, independent of mental illness.
So why do various governments insist on pouring resources into mental illness services? More specifically, it is criminal to knowingly pursue and commit resources to a policy that does not work.
In the era of information technology the “experts”, researchers and governments have failed the public through their national suicide prevention strategies where there is no good quality information on suicide. From currently available the data it is not possible to answer fairly simple questions such as:
- What proportion of those hospitalised due to suicide attempt were repeat hospitalisations, or first time attempters?
- What proportion were repeat attempters?
- What proportion received psychiatric care and for how long?
- What proportion received any medical care in the community and for how long?
- What proportion had completed suicide since hospitalisation?
- What proportion never attempted?
And so on.
How is the New Zealand government going to justify spending $9 million on a nine months inquiry that was restricted to mental illness rather than suicide, then commit $1.9 billion to mental health services, of which $40 million was allocated for suicide prevention including the establishment of a national office for suicide prevention that has no clear idea of what suicide prevention should be (Radio New Zealand, 2019a) while more and more families are bereaved by suicide?
Furthermore, how is the government going to justify allocating a miserly $1 million to Maori suicide prevention while claiming that proportionally Maori suicide rate is higher than any other population?
The New Zealand governments’ solution appears to be a perpetual pledge of funding, and, waiting for the downturn in the suicide trend cycle in order to claim success. And then to do all it all over again!
In the absence of accountability, ignorance and corrupt thinking thrives and prevents the prioritising of public wellbeing (e.g. the conflict between empowered and powerless, see Radio New Zealand, 2019b).
Saxby Pridmore & William Pridmore (2019). Suicide In Writing Across Time And Place. In Shahtahmasebi & Omar (Eds). The Broader View of Suicide. Cambridge Scholar Publishing, Cambridge, UK:forthcoming.
Radio New Zealand, (2019). Will a new suicide plan bring down the numbers? rnz.co.nz: 21 November 2019, accessed 4 December, 2019: https://www.rnz.co.nz/programmes/the-detail/story/2018723151/will-a-new-suicide-plan-bring-down-the-numbers.
Haynes, S., McMichael, A., & Tyroler, H. (1978). Survival after early and normal retirement. J Gerontol, 33(2), 269-278. doi: 10.1093/geronj/33.2.269
Pridmore, S. (2019). Suicide: A Disease or a (Flawed) Choice? Dynamics of Human Behaviour (DHH), 6(1), http://www.journalofhealth.co.nz/?page_id=1745.
Radio New Zealand. (2019a). Will a new suicide plan bring down the numbers? rnz.co.nz, 21 November 2019(accessed 4 December: https://www.rnz.co.nz/programmes/the-detail/story/2018723151/will-a-new-suicide-plan-bring-down-the-numbers).
Radio New Zealand, (2019b). Medical ethics boss urges Mike King’s charity to destroy suicide letters. https://www.rnz.co.nz/national/programmes/checkpoint/audio/2018722750/medical-ethics-boss-urges-mike-king-s-charity-to-destroy-suicide-letters: accessed 19 November 2019.
Shahtahmasebi, S. (2013). Examining the claim that 80-90% of suicide cases had depression. Front. Public Health, 1(62). doi: 10.3389/fpubh.2013.00062
Shahtahmasebi, S. (2014). Suicide Research: Problems with Interpreting Results. British Journal of Medicine and Medical Research, 5(9), 1147-1157. doi: 10.9734/BJMMR/2014/12802
Shahtahmasebi, S., Davies, R., & Wenger, C. (1992). A longitudinal analysis of factors related to survival in old age. The Gerontologist, 333, 404-413.
Tsa, S. P., Wendt, J. K., Donnelly, R. P., Jong, G. d., & Ahmed, F. S. (2005). Age at retirement and long term survival of an industrial population: prospective cohort study. BMJ, 331(7523), 995. doi: 10.1136/bmj.38586.448704.E0
Wenger, G. C. (1984). The Supportive Network – coping with old age. London: George Allen and Unwin.
Wenger, G. C., Davies, R., & Shahtahmasebi, S. (1995). Morale in Old Age: Refining the Model. International Journal of Geriatric Psychiatry, 10, 933-943.
Wenger, G. C., Davies, R., Shahtahmasebi, S., & Scott, A. (1996). Social isolation and loneliness in old age: Review and model refinement. Ageing and Society, 16, 333-358.