Cancer Longitudinal Exploration

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Background

Cancer is a critical public health concern relating to mortality and morbidity globally. Diverse cancer type patients agonize from lingering comorbid circumstances that are a leading clinical problem for cancer handling and managing. Socioeconomic status, physical activity levels, age, and health burden magnitude dictate individuals’ chances of developing comorbid conditions that lead to cancer growth. Holistically, engaging in physical activities remains the ultimate option for combating different ill-health diseases.

Aim

This study’s primary goal was to investigate the comorbid conditions distribution in Australia and the associated predictors among the cancer patients between the 2007-2017 period.

Design

The study embraced a longitudinal design using information in the Domestic, Income, and Labor Subtleties in Commonwealth of Australian investigation. The longitudinal consequence was effectively apprehended through the fixed-effect adverse binominal reversion model, predicting the budding issues that enhanced the occurrence of chronic comorbid conditions.

Method

The data collection method that was used is interviewing, whereby the participants were interviewed subsequently over time.

Results

Sixty-one percent of the cancer victims incurred one or more enduring diseases over a specific period. Moreover, 21 percent of the participants incurred more than three chronic conditions. Patients living in low socioeconomic status conditions, do not engage in physical activities, burdened by health, and the elderly are at significant risk of developing comorbid conditions.

Conclusion

Overall, many cancer patients experience a significant health load of long-lasting comorbid situations. The diverse scopes of the cancer fighters critically affect their cancer burden trajectory. Therefore, it is prudent for healthcare professionals who manage the exceptional needs that encounter this populace to champion for evidence-based disease prevention interventions.

Introduction

Cancer is a leading and significant healthiness apprehension regarding mortality and morbidity in Australia and globally. Nearly 9.6 million persons die from cancer yearly. Arguably, Australia is not left behind, considering that in 100,000 people, 483 new case cases are discovered as per the year 2019. On average, more than 136 people die from cancer illness in the whole Australia yearly (Australian Institute of Health and Welfare, 2019). Cancer equally contributes to eighteen percent of Australia’s total disease burden, followed by cardiovascular diseases at fourteen percent, musculoskeletal conditions at thirteen percent, and mental illnesses at twelve percent (Australian Institute of Health and Welfare, 2015). Also, there are roughly one million cancer survivors in the country. Notably, numerous forms of cancer-related victims are ailing and grieve from comorbid circumstances that bring a key scientific test for cancer dealing and running. Therefore, it is worth noting that cancer is one of the biggest health challenges that are facing the people of Australia.

The five-year cancers fighters united have tremendously upgraded in Australia, beginning from 48 to 69 percent, comparing between the 2001 and the 2015 statistics. Hitherto, most cancer patients suffer from chronic conditions, which are commonly called comorbidity. Research indicates that comorbidity increased during the treatment process and the oncology periods of follow-up, which harmfully inspires handling and results (Australian Institute of Health and Welfare, 2015). Lasting comorbid circumstances among individuals with cancer subsidize to a significant clinical problem regarding a cancer diagnosis. Between the year 2014-15, approximately eleven million Aboriginal Australian testified having one chronic disease, whereby one out of four were having more than two chronic conditions (Australian Institute of Health and Welfare, 2016). The mentioned rate was pronounced among the people aged between the age of 65 and above. Ultimately, the comorbidity severity leads to an increased hospitalization rate, high death rates, financial constraints to patient’s family, and equally reduced status of health on the medical system (Mitchell et al., 2018). The condition adversely affects the individual admittance to progressive cancer handlings, including radiotherapy and chemotherapy, and the treatment efficiency, a prognostic factor for the long-term cancer survivors.

Objectives

The previous studies’ primary goal has been to scrutinize the circulation, design, disparity, and trend in comorbidity position amongst the individuals who have cancer once in view of a restricted array of variable quantity.

This research learning aims to inspect and comprehend the longitudinal nature of lasting comorbid situations among cancer victims in Australia.

The study aims to complement and positively contribute to the continuing cancer investigation to critically upsurge public consciousness and advance healthcare quality and resources for constant surveillance among cancer patients.

Lastly, this research investigates the distribution, associated burden, and potential predictors of chronic comorbid conditions among different patients suffering from the cancer disease. The study will use the HILDA’s longitudinal data (Home, Revenue, and Labor Undercurrents in Australia review.

Methods

The research information originated from the Domestic, Revenue and Labor Subtleties in Australia (HILDA) investigation. Historically, the HILDA review started in 2001 and is one of the nationwide representative-based pane studies which gives statistics on the live matters of the Australian populaces that are of the age eighteen and above.

Notably, data were obtained through interviews, whereby the interviewer and the interviewee could meet face to face. Quantitative methods of research were put into practice while conducting the interviews.

Inclusion and Exclusion Criteria

The data collection formula incorporated the sampling formula that has been explained to bring the desired findings. The sampling method ensured that it incorporates previously diagnosed participants with cancer diseases, whereby the data was restricted to four waves. The waves include; waves 7, 9, 13, and 17 based on the ease of cancer data availability. Hitherto, wave three was subsequently excluded from the present analyses because of the cancer-related information paucity. Statistically, 2,066 participants led to the exercise’s success, whereby all are cancer victims. In other words, cancer was used as the inclusion and exclusion criteria, considering that individuals that had once been affected and consequently recovered from the cancer epidemic were used as subjects only.

Method and Design

Interviewing was used as the ultimate data collection method from the participants, who narrated their experiences and subsequently provided their suggestions regarding the comorbid conditions. The learning strategy is a longitudinal survey through a household-based panel between 2007 to 2017, a critical indicator of an extended period. Moreover, people who face the lethal problem of the cancer disease were vividly interviewed, focusing on the scale of the challenges affiliated with lingering comorbid situations.

Additionally, it is prudent to note that this learning utilizes evocative studies to compare different victims with chronic medical conditions and cancer critically. According to The Australian Bureau of Statistics (2016), the cancer survivors’ chronic comorbid conditions tendency was conducted through the Cochran-Armitage test trend. Notably, in the analytic examination, the attuned fixed-effect adverse binominal relapse model was used to classify and elucidate the issues that had a more momentous role in chronic comorbid conditions acquaintance (Carrao et al., 2018). In the relapse model, the dependent variables, including the quantity of lingering comorbid circumstances, were pigeonholed as a countermeasure.

Besides, this research considered the explanatory variables, including health, socioeconomic, and equally lifestyle-related variable quantity grounded on the theoretical outline, as putative chronic comorbid predictors (Ng et al., 2018). Interpretatively, the social-demographic factors, for example, age, employment status, educational achievement, sex, and marital status, were considered throughout the analysis. Moreover, lifestyle factors, including alcohol drinking, physical exercise, and smoking exposure, were equally considered whereby majority had a high body mass weight compared to their weight (Sharma et al.,2017). Ultimately, the physical activity level was pigeonholed into three clusters, that is, high, moderate, and low. Moreover, the life condition-related factors included employment satisfaction, social supports, and financial situation was equally measured. Besides, ethnic status was excellently defined between the Aboriginals and the non-Aboriginals (Hussain et al., 2018). The life quality index was calculated through the medical outcomes study form.

Results

Notably, the total number of 2,066 cancer patients were used to make the study a success. Rationally, 54 percent of participants were male, whereas 58 percent were married. Arguably, a higher proportion accounting for 46% of the total participants was senior citizens above sixty-five, and the middle-aged participants accumulated to 37%. Approximately 47 percent of the subjects had accomplished their mid and high school edification, with 316 cancer survivors, 15 percent, partaking university education certification. Sixty-three percent of the participants are jobless, whereas 45% had insufficient physical body engagement cases, with solitary 23 percent engaging in elevated physical activities weekly. Three-quarters of 75% of the subjects used alcohol recurrently. Also, 89 percent of the members reported extreme to moderate health burden, whereas 42 percent experienced severe to moderate levels of disability. Noteworthy, seventy-two of the participants received medication, and sixty-one percent live in urban areas.

The comorbid condition’s prevalence was reported by the participants who are cancer victims as follows; osteoporosis or arthritis (45%) and high blood pressure (39%). Overweightness (23%), anxiety or depression (22%), heart attacks (14%), and lastly, asthma taking thirteen percent. Forty-two percent of the patients were ailing from one or two chronic comorbid conditions, whereas twenty-one percent were experiencing at least one or two states of comorbidities. Understandably, the distribution of comorbid circumstances was tentatively dispersed by age. The mainstream of comorbidities developed the disease because of inadequate physical training. Further, participants who suffered from one or more comorbid conditions were allied with the degree of moderate to high fitness position problem (62 and 36 percent, respectively). Similarly, a rising drift of the margin of frailty echelons was evident, with an exponentially increasing sum of comorbid acquaintances amongst the cancer fighters from low backgrounds. Lastly, concerning the socioeconomic position, comorbid conditions levels were high among individuals that come from economically disadvantaged families. Statistically, 28 percent of the participants who subsisted in the lowest homes were more exposed to two or more prone to comorbid conditions.

Findings

Comorbid conditions, including hypertension, depression, obesity, among many other states, make individuals prone to cancer disease.

Also, older people over the age of 65 are developing conditions and cancer compared to their young and youthful counterparts.

Notwithstanding, another finding is that physical activities and the general lifestyle dictate the probability of individuals developing comorbid conditions, leading to cancer development.

The risk of developing conditions of chronic comorbidity among the cancer victims who live in the lowliest households are high equated inversely with those that live in wealthy estates. The burden of cancer is associated with the socioeconomic status of individuals (Yu et al., 2017). Individuals from rich backgrounds can treat quickly attend diagnoses and pay for the subsequent treatment bills if found with the disease. Connectedly, the socioeconomic status determines the cancer ordeals in various households.

Discussion

This study results critically exemplify that around 63 percent of the cancer victims agonized from more than one lasting illness. The most comorbid circumstances were osteoporosis or arthritis, hypertension, depression, obesity, asthma, or heart disease. These were suggestively augmented in the existence of anxiety, heart disease, cerebral illness, and diabetes. In the accustomed archetypal, older participants, the health burden scale, and inadequate physical activity levels are affiliated with cancer (Schranz et al., 2016). Healthcare utilization and patients living in low socioeconomic backgrounds are critical predictors linked with sophisticated risks of developing comorbid situations.

Furthermore, aged cancer patients over the age of 65 are 1.15 times more at risk of developing lingering comorbid circumstances than junior patients. Arguably, this finding verses with preceding educations about comorbid situations and age. The elderly with health complications require regular and excellent healthcare adherence. Therefore, young people are at a lower risk of contracting different comorbid diseases than their elderly counterparts.

Moreover, cancer patients who perform lower-intensity physical exercises are heavily affiliated with extreme levels of chronic comorbidities compared to engaging in high-level practices (Ng et al., 2018). This discovery relates to the finding that physical activity levels are related to developing chronic comorbid conditions. Thus, engaging in high-level exercises reduces the chances of people developing cancer disease.

Limitations and Conclusion

Conclusively, it is paramount noting that this research has some evident limitations. The first limitation of this study is that the survey used eighteen years and above participants, excluding the other young individuals from the analysis. Arguably, this study accessed the HILDA review participants, which concealments health, income, employment, and economic paradigms only. There is a need to include people across different aspects, including age in the study, as long as they have experienced the cancer ordeals. Another limitation is that the course’s length might have led to unrestrained prejudice since vicissitudes in the health position are non-instantaneous since they might appear after a given time. Distinctively, this research presents an understanding that there is a definite chronic comorbid condition burden among Australian cancer patients. The elderly, the health burden magnitude, inadequate physical activities, middle and low-socioeconomic status lead to comorbid conditions development. Above all, there is a need for Australians and people worldwide to embrace excellent lifestyles free of alcohol and other foods and equally engage in vigorous physical activities to defeat the cancer disease.

References

Australian Institute of Health and Welfare. (2015). Australian Burden of Disease series Canberra: AIHW. Web.

Australian Institute of Health and Welfare. (2019). AIHW. Web.

Australian Institute of Health and Welfare (AIHW). (2016). AIHW. Web.

Calao, M., Wilson, J. L., Spelman, L., Billot, L., Rubel, D., Watts, A. D., & Jemec, G. B. (2018). . PloS one, 13(7). Web.

Hussain, M. A., Katzenellenbogen, J. M., Sanfilippo, F. M., Murray, K., & Thompson, S. C. (2018).PLoS One, 13(8), e0201496. Web.

Mitchell, R. J., Herkes, G., Nikpour, A., Bleasel, A., Shih, P., Vagholkar, S., & Rapport, F. (2018). Epilepsy & Behavior, 79, 9-16. Web.

Ng, H. S., Koczwara, B., Roder, D., & Vitry, A. (2018). Cancer Epidemiology, 54, 56-62. Web.

Schranz, N. K., Olds, T., Boyd, R., Evans, J., Gomersall, S. R., Hardy, L., Hesketh, K., Lubans R.D., Ridgers, D.N., Straker, L., Ziviani, J., Tomkinson, R.G., & Vella, S. (2016). Journal of Physical Activity and Health, 13(s2), S87-S94. Web.

Sharma, Y., Thompson, C., Kaambwa, B., Shahi, R., & Miller, M. (2017).Asia Pacific Journal of Clinical Nutrition, 26(6), 994. Web.

The Australian Bureau of Statistics. (2016). (SEIFA) [2016]. Web.

Yu, X. Q., Luo, Q., Kahn, C., Grogan, P., O’Connell, D. L., & Jemal, A. (2017). Lung Cancer, 108, 55-61. Web.

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