Pakistan is vulnerable to climate change, and extreme climatic conditions are threatening food security. This study examines the effects of climate change (e.g., maximum temperature, minimum temperature, rainfall, relative humidity, and the sunshine) on the major crops of Pakistan (e.g., wheat, rice, maize, and sugarcane). The methods of feasible generalized least square (FGLS) and heteroscedasticity and autocorrelation (HAC) consistent standard error were employed using time series data for the period 1989 to 2015. The results of the study reveal that maximum temperature adversely affects wheat production, while the effect of minimum temperature is positive and significant for all crops. Rainfall effect towards the yield of a selected crop is negative, except for wheat. To cope with and mitigate the adverse effects of climate change, there is a need for the development of heat- and drought-resistant high-yielding varieties to ensure food security in the country.

The present study attempts to explore the correlation between carbon dioxide emissions (CO₂ e), gross domestic product (GDP), land under cereal crops (LCC) and agriculture value-added (AVA) in Pakistan. The study exploits time-series data from 1961 to 2014 and further applies descriptive statistical analysis, unit root test, Johansen co-integration test, autoregressive distributed lag (ARDL) model and pairwise Granger causality test. The study employes augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests to check the stationarity of the variables. The results of the analysis reveal that there is both short- and long-run association between agricultural production, economic growth and carbon dioxide emissions in the country. The long-run results estimate that there is a positive and insignificant association between carbon dioxide emissions, land under cereal crops, and agriculture value-added. The results of the short-run analysis point out that there is a negative and statistically insignificant association between carbon dioxide emissions and gross domestic product. It is very important for the Government of Pakistan’s policymakers to build up agricultural policies, strategies and planning in order to reduce carbon dioxide emissions. Consequently, the country should promote environmentally friendly agricultural practices in order to strengthen its efforts to achieve sustainable agriculture.

An emerging body of literature has implied that perceived social support is known as an upstream element of cognitive health. Various dimensions of perceived social support may have divergent influence on physical and cognitive health in later life. The present study aimed to investigate the mediating role of perceived social support on the relationship between physical disability and symptoms of depression in senior citizens of Pakistan. The data were collected from three metropolitan cities (Lahore, Faisalabad, Multan) in the Punjab province of Pakistan and 100 participants were approached from each city with a total sample size of 300. The results demonstrated that family support, friends’ support, and significant others’ support mediated the association between physical disability and symptoms of depression, with an indirect effect of 0.024, 0.058, and 0.034, respectively. The total direct and indirect effect was 0.493. Physical disability was directly associated with symptoms of depression and greater physical disability predicted a higher level of symptoms of depression. Perceived social support, including family support, friends’ support, and significant others’ support, showed an indirect association with symptoms of depression. Furthermore, family support and friends’ support were more significantly associated with symptoms of depression as compared to significant others’ support. The research discoveries have better implications for health care professionals, hospice care workers, and policy makers. A holistic approach is required to prevent senior citizens from late-life mental disorders.

This study aims to explore the casual relationship between agricultural production, economic growth and carbon dioxide emissions in Pakistan. An autoregressive distributed lag (ARDL) model is applied to examine the relationship between agricultural production, economic growth and carbon dioxide emissions using time series data from 1960 to 2014. The Augmented Dickey–Fuller (ADF), Phillips–Perron (PP) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests are used to check the stationarity of variables. The results show both short-run and long-run relationships between agricultural production, gross domestic product (GDP) and carbon dioxide emissions in Pakistan. From the short-run estimates, it is found that a 1% increase in barley and sorghum production will decrease carbon dioxide emissions by 3% and 4%, respectively. The pairwise Granger causality test shows unidirectional causality of cotton, milled rice, and sorghum production with carbon dioxide emissions. Due to the aforementioned cause, it is essential to manage the effects of carbon dioxide emissions on agricultural production. Appropriate steps are needed to develop agricultural adaptation policies, improve irrigation facilities and introduce high-yielding and disease-resistant varieties of crops to ensure food security in the country.