Structured Assessment of Modifiable Lifestyle Habits in Patients with Mental Illness in Primary Care
In this first part of the HEAD-MIP project, we made a basic description of the participants, adult patients seeking primary care for a mental illness. All participants in our study reported at least one modifiable lifestyle domain with an increased risk of cardiovascular disease or diabetes. WHR and physical inactivity showed elevated risk levels in 43% of patients studied. Other well-known risk factors like increased blood pressure, serum cholesterol, and elevated fasting blood sugar were also found in several participants, even in those with no known chronic disease before.
Comparison with other studies
Our results are comparable to the results of a screening project using the same method, carried out at the same time in 40-year-old individuals in the general population of southern Sweden, with 411 participants included.16. In our study, 88% of men and 71% of women were overweight or obese compared to 71% and 56% respectively in the screened population of 40-year-old individuals. Compared to the general 40-year-old population, HEAD-MIP participants showed an even higher proportion of high blood pressure (21% female, 29% male versus 2% female, 13% male) , abnormal fasting blood glucose values (21% women, 46% men vs 9% women, 21% men) or physical inactivity (23% women, 24% men vs 13 % women, 10% men). The cohorts may not be fully comparable, as the population in the present study was older (mean age 51.9 years) and all participants were included in the study due to psychiatric diagnoses. However, self-reported data from the 40-year-old screening project showed that 41% of women and 34% of men had felt depressed and about half of participants had sleep problems in the past year. . Many of our HEAD-MIP study participants were physically inactive. We believe that a targeted intervention with a focus on lifestyle improvement in the psychiatric patient group could be even more cost effective, as it has been shown that positive changes in life as better diet and increased physical activity increase remission rates of non-psychotic mental illnesses.17.18.
In older people, it has been revealed that lifestyle habits such as smoking or low levels of physical activity can indicate mental illness such as depression.19. The accumulation of several bad habits, smoking, heavy alcohol consumption, physical inactivity and poor diet, increases the risk of depression. Psychological well-being has also been shown to be influenced by lifestyle habits, with higher levels of psychological well-being in those who ate a healthy diet, were physically active and non-smokers.20.
Despite the small sample size of this study, it supports the hypothesis that this patient group needs more attention regarding lifestyle domains that might affect psychiatric well-being and increase risk. developing diabetes or cardiovascular disease. Detecting the patients most at risk allows targeted interventions to improve mental well-being but also to reduce cardiovascular risk and complications. We were able to show that more than 20% had either high blood sugar, cholesterol, blood pressure, or several altered measures. Even though some of the participants had previously been diagnosed with diabetes, hyperlipidemia, or hypertonia, the Health Dialogue helped uncover altered lab results, even in other participants with no known chronic conditions before.
The results indicate that Health Dialogues may be an effective method for detecting elevated blood sugar and blood pressure in patients with mental illness. Early detection allows monitoring combined with treatment using lifestyle interventions and, if necessary, even medication, to prevent or at least delay both a diagnosis of chronic disease and later complications.
To our knowledge, the use of a health dialogue has not yet been studied in a cohort of patients with mental illness. In the second part of the HEAD-MIP study, we seek to evaluate the effect of the Health Dialogue on the lifestyle habits of patients with mental illness.
Strengths and limitations
The study cohort is limited to a small sample of patients recruited from a primary health care center, thus with poor generalizability. A larger cohort with higher socio-demographic representation and multiple primary health care centers is planned. The screening project among 40-year-olds using the same method in the same primary care setting showed good feasibility in the general population as well as good cost-effectiveness. A major limitation of our study is that we were unable to study the inclusion rate, due to the mode of recruitment. Several caregivers (doctors, nurses and a psychologist) opportunistically included the patients after the first contact at the primary care center due to a psychiatric illness. However, we believe that the method of inclusion could have included a higher rate than letter-of-invitation screening in this group of patients, so a strength of the study is the opportunistic inclusion of patients, with patients seeing themselves recommend a lifestyle assessment by the caregiver, minimizing the risk of inclusion bias. Serious mental illness was not an exclusion criterion. However, patients with severe mental illness are generally not treated in primary care in Sweden and therefore none were included in this study. Our results are therefore not transferable to this group of patients, which constitutes a limitation of the study. Another limitation of the study is the lack of data on the socioeconomic status of the participants. Socioeconomic status is associated with increased prevalence of smoking, physical inactivity and poor diet21. Greater financial stress may also be associated with increased rates of mental illness. Even if the patients were listed in the same health care unit, which means that the socioeconomic status should be approximately the same at the group level, individual socioeconomic differences could have existed.
Several participants in our study had elevated levels of blood pressure and fasting blood sugar. Although these surrogate measures may indicate the possible development of a chronic disease such as high blood pressure or diabetes, the diagnosis requires multiple valid values repeated. Another limitation is the lack of data on drugs with potential side effects such as weight gain such as antipsychotics or certain antidepressants. Patients with pre-existing conditions such as diabetes or hypertension diagnosed prior to inclusion in this study likely received qualified lifestyle counseling from healthcare personnel at the time of diagnosis. Due to the limited number of patients in the present study, no subgroup analysis was performed. Future studies should take this aspect into account.