Main

In the aftermath of the coronavirus disease 2019 (COVID-19) pandemic, the United Kingdom has witnessed a gradual recovery in economic activity. However, the cost of living has continued to rise due to exacerbated price inflation. Data from the Office for National Statistics (ONS) indicate that the price inflation rate in England increased from 1.5% to 6.2% from March 2020 to March 2022, and is now up to 8.9% as of March 2023, in contrast to the relatively stable rate of 0.7–3% observed between August 2016 and February 20201. This heightened price inflation has emerged as another crisis, profoundly impacting daily life.

Studies conducted during the 2008 economic recession revealed that it had adverse effects on mental health both in the United Kingdom and globally2,3,4,5,6,7,8,9. Previous research has also established associations between rising living costs and compromised mental health due to factors such as housing instability, fuel poverty and restricted access to food and transportation10,11,12. The potential consequences of rising living costs extend beyond those directly responsible for bill payments, with children in poverty facing an increased risk of adverse childhood experiences13, which may impact their mental health.

The British government’s primary response to alleviate the pressure resulting from increased living costs has been through various financial subsidies. However, there is a lack of empirical evidence to determine whether a statistically significant relationship exists between the mental health cases reported in the news and the rising cost of living in the current post-COVID-19 environment. Furthermore, it remains unclear which specific living costs are most closely associated with mental health in the general population.

Evidence is needed to better plan mental health support services or to target subsidies more carefully for the things impacting mental health. In this Article, we have investigated the association between price inflation and mental health conditions among the general population in England during the post-COVID-19 era. Given the widespread price inflation, the evidence we provided could benefit countries worldwide.

Results

Before the pandemic, there was either no or a significant negative time trend for most price indices and the number of people in contact with mental health services (Supplementary Fig. 1 and Supplementary Table 1). In contrast, during the post-COVID-19 era, there was a strong and significant positive time trend for certain price indices and the number of people in contact with mental health services (Supplementary Fig. 1 and Supplementary Table 1). After controlling for month, year and unemployment rate, Supplementary Table 2 indicates that, pre-COVID-19, there was no significant association or significantly negative associations between the price indices (including subitems) and the number of individuals in contact with mental health services (across different age groups).

Table 1 presents the results of how the time period (pre-COVID-19 versus post-COVID-19) moderated the association between price indices and the number of people in contact with mental health services. For children aged 0–18 years, compared with pre-COVID-19, the price inflations during the post-COVID-19 have no significant change on their associations with numbers of contact with mental health services (all P values >0.05) (Table 1).

Table 1 Moderating effects of the pre-and post-COVID-19 periods on the association between price index and mental health service contacts
Full size table

For adults aged 19–64 years, compared with pre-COVID-19, a 1% increase in the Consumer Prices Index including owner occupiers’ housing costs (CPIH) during the post-COVID-19 period was associated with a 56.14 (95% CI 20.89 to 91.39) thousand increase in the number of adults in contact with mental health services (Table 1). By items post-COVID-19, a 1% increase in the ‘food and non-alcoholic beverages’, ‘housing, water and fuels’ and ‘miscellaneous goods and services’ indices were associated with an 8.89 (95% CI 2.67 to 15.11), 35.88 (95% CI 8.36 to 63.40) and 24.43 (95% CI 8.55 to 40.31) thousand increase in the number of adults in contact with mental health services, respectively. Conversely, post-COVID-19, a 1% increase in the ‘alcoholic beverages, tobacco and narcotics’ and ‘hotels, cafes and restaurants’ indices were associated with a 41.97 (95% CI 14.94 to 69.00) and 50.55 (95% CI 12.80 to 88.30) thousand decreases in the number of adults in contact with mental health services, respectively. Additionally, a 1% increase in the ‘hotels, cafes and restaurants’ index had a 1 month lagged association and a decrease of 41.04 (95% CI 5.52 to 76.56) thousand adults in contact with mental health services.

For the elderly population aged 65 years and over, compared with pre-COVID-19, a 1% increase in the CPIH, ‘food and non-alcoholic beverages’ and ‘miscellaneous goods and services’ indices during the post-COVID-19 period were associated with 26.12 (95% CI 16.16 to 36.08), 3.58 (95% CI 0.94 to 6.22) and 7.33 (95% CI 1.83 to 12.82) thousand increases, respectively, in the number of the elderly population in contact with mental health services (Table 1).

Discussion

This study investigates the association between price inflation and mental health conditions among the general population in England during the post-COVID-19 era. The findings revealed that, compared with the pre-COVID-19 period, the number of people in contact with mental health services increased significantly with the rise in price inflation during the post-COVID-19 era. This trend was most clear among adults aged 19–64 years and the elderly population aged 65 years and over. The associations were more pronounced for specific price indices such as ‘food and non-alcoholic beverages’, ‘housing, water and fuels’ and ‘miscellaneous goods and services’. Perhaps surprisingly, a negative association was observed between the ‘alcoholic beverages, tobacco and narcotics’ and ‘hotels, cafes and restaurants’ indices and the number of adults in contact with mental health services during the post-COVID-19 period.

The observed associations suggest that the rising cost of living during the post-COVID-19 era contributed to the increased demand for mental health services among adults aged 19–64 years and the elderly population aged 65 years and over. These findings align with previous research conducted during the 2008 economic recession, which demonstrated adverse effects on mental health both in the United Kingdom and globally2,3,4,5,6,7,8,9. Our study further expands on this evidence by examining the associations between specific price indices and mental health service use in the general population during the post-COVID-19 era. Some previous studies have reported associations between rising living costs and poor mental health due to housing instability, fuel poverty and limited access to food and transportation10,11,12. However, our study not only provides a more comprehensive assessment of these relationships across different age groups and price indices, but also clearly points out which price indices do and do not associate with the use of mental health services under the current situation. The findings are important to inform the design of possible policy interventions.

The observed associations between price inflation and mental health conditions could be attributed to multiple factors. Increased living costs may lead to heightened financial stress, which in turn can exacerbate mental health issues such as anxiety and depression14. Financial struggles might force people to change their spending habits, possibly affecting their access to essential goods and services. This could result in poor nutrition, lower-quality housing and a lack of essential services—conditions that can harm mental health15,16. Inflation can also heighten feelings of inequality as it often widens the wealth gap. The resulting social comparisons and perceived injustices can lead to feelings of shame and low self-esteem, further increasing the risk of mental health issues17. The general uncertainty and insecurity caused by inflation could potentially trigger anxiety disorders18. Finally, to cope with the rising cost of living, individuals might take on more work or longer hours, increasing their stress levels and potentially contributing to mental health problems19.

The observed negative associations between the increase in prices for ‘alcoholic beverages, tobacco and narcotics’ and ‘hotels, cafes and restaurants’ and contacts with mental health services post-COVID-19 are both intriguing and counterintuitive. As costs for these items grow, individuals might reevaluate and reallocate their financial priorities. The elevated expenses related to potentially harmful substances such as alcohol and narcotics could deter their consumption, which may, in turn, reduce instances of immediate mental health crises. The finding concerning the association between the price of alcohol and tobacco products and mental health contacts raises pertinent questions about their treatment in economic considerations: Should alcohol and tobacco products be treated as ordinary commodities whose prices are susceptible to market fluctuations? Additionally, there is a pressing need to consider the broader implications of their pricing, especially given the potential impact on mental health. Similarly, as ‘hotels, cafes and restaurants’ become pricier, the reduced affordability could diminish individuals’ engagement in these recreational avenues, which were traditionally perceived as stress alleviators. Contrary to expectations, this reduced engagement did not correspond to a spike in mental health service contacts. One interpretation is that amidst rising leisure costs, individuals might lean toward alternative, cost-effective coping mechanisms, such as physical exercise or online support forums. Moreover, the 1 month lagged association following the inflation in the ‘hotels, cafes and restaurants’ sector implies a temporal dimension to the effects; individuals might initially limit their spending in light of heightened costs, with the mental health consequences only emerging subsequently. Additionally, the broader economic strain resulting from inflation across sectors might compel individuals to defer formal mental health consultations in favor of informal support channels. Such complexities necessitate a deeper dive into research, aiming to untangle the multifaceted relationship between economic challenges and mental health outcomes.

The practical implications of this research are notably substantial, especially for policymakers. Our results show that the rising costs of living, including food, housing and miscellaneous goods and services, are strongly associated with an increased number of individuals seeking mental health services during the post-COVID-19 period. This suggests the necessity for targeted subsidies in these particular areas to protect the mental health of the population. The current measures taken by the British government, such as subsidies for energy costs, appear to be inadequate given the scope of the problem, suggesting the need for possibly more substantial financial aid. Furthermore, differential policy approaches might be required based on age-specific needs. For instance, subsidies or financial support schemes for housing could be prioritized for adults aged 19–64 years, demographics facing the brunt of employment challenges, while older populations might find greater benefit from discounts on essential goods. Such age-tailored strategies can ensure that the support provided is both relevant and effective. More than just economic relief, our findings underscore the urgent need for comprehensive strategies that also focus on scaling up mental health protection and treatment services. This comprehensive approach is especially critical in the post-COVID-19 era, which has witnessed an overall surge in mental health service use. Consequently, our study calls for a rethink of current strategies and emphasizes the need for evidence-based, multifaceted policies that not only alleviate financial stress, but also bolster mental health support, thereby building resilient communities in times of economic turbulence.

One of the key strengths of our study is the use of data from official sources such as the ONS and the National Health Service (NHS), which enhances the reliability and generalizability of our findings. Moreover, the study covers a relatively long time period, allowing for a comprehensive assessment of the associations between price indices and mental health service use.

However, our study also has several limitations. First, the observational nature of the study precludes the establishment of causal relationships between price inflation and mental health problems. Second, we relied on the number of people in contact with mental health services as a proxy for mental health status, which may not capture the full extent of mental health conditions in the population. Third, established studies consistently highlight that women often exhibit higher levels of mental health problems in comparison to men. This disparity is further magnified by societal roles, with many females predominantly engaged in family care, potentially making them more susceptible to the pressures of price inflation. However, gender-specific information was not available among children, adults and the elderly. Given the consequential role of gender in mental health research, it is imperative for future data release to encompass this dimension. Fourth, our study faces limitations regarding data granularity. We have regional mental health data, but lack regional price inflation data. This data mismatch may obscure regional nuances, limiting our ability to reveal potential regional differences in how mental health relates to price inflation. Fifth, although we controlled for the unemployment rate, other unmeasured factors related to the economic situation, such as personal income or debt levels, might have affected our findings, but these data are not available by month. Sixth, although we believe the measures we have taken, by excluding transition data from March 2021 to March 2022, help to disentangle the effects of price inflation from COVID-19’s ramifications, the long-term mental health consequences of the pandemic remain uncertain. Finally, people living in deprived areas may be more suffering from price inflation, and sex and race could also moderate the associations we identified, but our outcome variable is also not available by sex by race and by socioeconomic status.

Conclusions

Our study offers substantial insights for policymakers by clearly identifying which living costs have a significant association with mental health service use during the post-COVID-19 era in England. By elucidating the relationships between specific price indices and mental health service utilization across different age groups, our research provides valuable guidance for the development of targeted social and economic policies to address the potential causes of mental health issues.

Methods

Study design

An ecological study design was conducted due to the key measures or indicators (as follows) only available at aggregated level.

Measurements and data source

Price inflation is assessed using the CPIH. This metric, employed by various offices in the United Kingdom, offers a comprehensive perspective on inflation, capturing fluctuations in consumer expenditures1. The CPIH expands upon the CPI by incorporating housing costs incurred by owner occupiers. This inclusion is essential as it accounts for an important portion of household expenses that the standard CPI does not typically consider. Consequently, the CPIH provides a more accurate representation of the average household’s cost of living by including expenses such as mortgage interest payments, dwelling insurance, transaction costs and maintenance and repair expenditures. Values of the CPIH indicate the rate of inflation or deflation compared with the 2015 baseline. Monthly values of the CPIH in England were obtained from the ONS website1.

Mental health status was measured using the number of people in contact with mental health services, an official index maintained by the NHS20. An individual is deemed to be ‘in contact’ with services if they have an open referral with secondary mental health, learning disabilities or autism services. This index is available for three age groups: 0–18 years, 19–64 years and 65 years and over. In this study, values of mental health service contacts denote the absolute number, expressed in units of thousands. Monthly data were extracted from the NHS’s mental health services monthly statistics20.

The unemployment rate was considered as a confounder with its potential influence on mental health. Monthly data of the unemployment rate was also obtained from the ONS website21.

The study covers the period from August 2016 to February 2023. Due to the documented influence of COVID-19-related restrictions on mental health22,23,24, we excluded data from March 2020 to March 2022. England initiated its phased relaxation of restrictions in March 2021, and fully resuming regular operations by 1 April 202225. To circumvent the potential lagged impact of COVID-19, we also excluded data from March 2021 to March 2022. As a result, in our analysis, data from August 2016 through February 2020 represents the pre-COVID-19 period (serving as the control group), while data from 1 April 2022 onward constitutes the post-COVID-19 period.

The data are publicly available. The use of secondary deidentified data makes this study exempt from institutional review board review.

Data analysis

We have visualized the time trend of each price index and the time trend of the number of people in contact with mental health services in Supplementary Fig. 1. To test the influence of price inflation, we fitted the data by linear regression with the number of people in contact with mental health services as the outcome and the price index as the key predictor, controlling for the month, year, unemployment rate and a binary variable indicating time period (pre-COVID-19 versus post-COVID-19). Month and year were controlled due to the observable seasonal trend identified in the supplementary data. Considering the potential lagged influence of price inflation on mental health at the population level, we have added the lags of price inflation, and the optimal lag length was selected based on the Akaike information criterion26. To test the moderation of the time period on the association between price indices and the mental health service contacts, we also added an interaction between the price index as well as its potential lagged form and time period into the above linear model. Gauss–Markov assumptions for the linear model were tested extensively in Supplementary Table 3.

The above analyses were repeated for each price index and each outcome.

All analyses were finished in R (version 4.2.2), and packages stats (4.2.2), vars (1.5–9), AFR (0.3.4) and lmtest (0.9–40) were used. P < 0.05 was considered as significant.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.