Almost 300 genetic variants found to influence timing of menopause

The identification of 290 genetic variants associated with age at menopause is reported in a large genome-wide association study published in Nature. On average, most women will experience menopause between the ages of 50 and 52 years. As women approach menopause, their natural fertility reduces and the risk of conditions such as bone fractures or type 2 diabetes increases. International researchers, including Australians, analysed genetic data from 201 323 women of European ancestry in whom natural menopause occurred between the ages of 40 and 60 years. Examination of around 13.1 million genetic variants led to the identification of 290 determinants of ovarian ageing that were associated with delayed menopause. A wide range of DNA damage response genes were found to be associated with the age at natural menopause, operating throughout a woman’s lifespan to control ovarian function. Specific experimental manipulation of two of these genes — Chek1 and Chek2 — in mice was shown to affect fertility and reproductive lifespan. In humans, further genetic analyses suggested a causal relationship between delayed menopause and improved bone health, as well as a reduced likelihood of developing type 2 diabetes. However, delayed menopause was also associated with an increased risk of hormone-sensitive cancers. Although many influencers of reproductive age span — including non-genetic factors — remain unknown, the authors hope that these findings will inform future experimental studies into novel treatments to enhance female reproductive function and preserve fertility.

Australian mothers are having babies later in life

The number of Australian women giving birth after the age of 34 years is continuing to increase, a new report from the Australian Institute of Health and Welfare (AIHW) has found. The report, Older mothers in Australia 2019, shows one-quarter of all women giving birth in 2019 were aged 35 years or over, and two in seven (29%) of these were giving birth for the first time. The number of babies born to older mothers has been increasing over time. In 2019, there were more than 76 000 babies born to mothers aged 35 years or over, compared with almost 69 000 in 2009 and 42 000 births in 1999. The average maternal age has increased from 27.1 years in 1979 to 30.8 years in 2019 for all mothers. Since 1999, the rate of women aged 40–44 years giving birth has almost doubled, with 15.5 mothers per 1000 in 2019 compared with 8.4 mothers per 1000 women in 1999. The rate almost quadrupled among women aged 45–49 years with 1.1 mothers per 1000 women in 2019 compared with 0.3 mothers in 1999. Women who give birth later in life are more at risk of complications, such as gestational diabetes (18% of mothers aged 40 years and over compared with 10% aged 20–34 years), during pregnancy and birth. Other complications include increased risk of gestational hypertension, preterm birth and low birthweight babies. This is particularly seen for women giving birth for the first time. Older mothers were less likely than younger mothers to smoke, and the majority received antenatal care in the first trimester of pregnancy. They were are also more likely to live in major cities and less likely to live in low socio-economic areas.

Older people reluctant to seek help for mental health concerns

Research from Edith Cowan University, published in the Australian Journal of Psychology, has found that more than 40% of older Australians living with chronic disease would be unlikely to seek help for mental health conditions even if they needed it. The authors investigated help-seeking intentions for mental health services by older Western Australians living with chronic conditions such as cardiovascular disease; respiratory disease, including asthma; and type 2 diabetes. The study involved 108 people aged 65 years and older living with chronic disease. Participants were asked about their attitudes and beliefs towards seeking help for mental health concerns, and information on their past engagement with mental health services, quality of life, physical and mental health. The author found that 41% of older adults with chronic disease did not intend to seek help for their mental health, even if they needed to. The strongest predictor of whether people would access mental health support was their own beliefs about whether speaking with their doctor was likely to be personally beneficial. Participants were also asked about how they thought society would view them seeking help for mental health, and whether that would influence their decision. If they believed that family and friends would not support them, it was likely to prevent them from wanting to speak out about their mental health. Another barrier was whether they believed they were physically incapable of accessing services.

“Where does it hurt?” can predict pain outcomes

Pain distribution as reported on a body map, on its own, can be used to assign patients to distinct subgroups that are associated with differences in pain intensity, pain quality, pain impact and clinically relevant 3-month outcomes, according to a study published in PLOS ONE. Researchers analysed data on 21 658 patients seen at the seven pain management clinics of the University of Pittsburgh between 2016 and 2019. All patients completed a pain body map, in which areas of pain are selected on two side-by-side drawings of the front and back of the body, with 74 possible regions of pain. Other information on patients’ pain, health and outcomes was available in the electronic medical record. Eighty-three per cent of patients were white, 60% were female, 22% were insured by Medicaid, and 10% of patients had at least one comorbidity. Data from all patients revealed nine distinct groupings of pain distribution. Demographic and medical characteristics, pain intensity, pain impact, and neuropathic pain quality all varied significantly across cluster subgroups. For instance, the pain intensity of the “neck and shoulder” group was less than that of “lower back pain below knee” and “neck, shoulder and lower back pain” groups, while the group with the highest pain intensity consisted of patients with widespread heavy pain, also associated with low physical function, high anxiety and depression, and high sleep disturbance. In a subset of 7138 patients who completed 3-month follow-up questionnaires, subgroups predicted the likelihood of improvement in pain and physical function; those in the “abdominal pain” group were the most improved, with 49% self-reporting clinically significant improvements, while those in the “neck, shoulder and lower back pain” group were the least improved, with only 37% reporting improvements. The authors concluded that algorithmic clustering by pain distribution may, in the future, be an important facet of the personalisation of pain management.


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