Multimorbidity and Its Impact on Workers: A Review of Longitudinal Studies

Cabral, Giorgione G.; Souza, Ana Clara Dantas de; Barbosa, Isabelle Ribeiro; Jerez-Roig, Javier; Souza, Dyego Leandro Bezerra de

doi:10.1016/j.shaw.2019.08.004

Cited by 39 publications

(46 citation statements)

References 24 publications

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“…Multimorbidity has a negative impact on the workforce, affecting productivity and increasing absenteeism. Employability also decreases with multimorbidity because employers tend not to hire those who are ill. All this also affects the quality of life of workers and deteriorates the overall country economy [5].…”

Section: Introductionmentioning

confidence: 99%

Multimorbidity in a cohort of middle-aged women: Risk factors and disease clustering

Blümel

Carrillo‐Larco

Vallejo³

et al. 2020

Maturitas

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We aimed to evaluate which risk factors in middle-aged women are associated with higher risk of multimorbidity in older age. Study design: We conducted a prospective cohort study from 1990 to 1993 in Santiago de Chile, Chile among women aged 40-59 (at baseline). Diagnosed illnesses were retrieved from national health records in 2020. Main outcome measures: : Clinical and laboratory evaluation was conducted. Results: 1066 women were followed-up for a mean of 27.8 years, after which 49.7% presented multimorbidity. These women, as compared with those without multimorbidity, were more likely at baseline to have had obesity (20.4% vs. 8.6%, p < 0.001); be post-menopause (47.2% vs. 40.5%; p < 0.03); have jobs that did not require a qualification (74.2% vs. 56.0%, p < 0.001); arterial hypertension (19.8% vs 14.4%, p < 0.018); lower HDLcholesterol (51.3 ± 12.9 vs. 53.6 ± 12.7 mg/dL, p < 0.005); and higher triglyceride levels (136.0 ± 65.0 vs. 127.0 ± 74.0 mg/dL, p = 0.028). Hypertension was associated in 22.0% of women with diabetes, in 20.9% with osteoarthritis and 14.0% with depression. Osteoarthritis was also associated with diabetes mellitus (8.3%) and depression (7.8%). Diabetes mellitus, in addition to hypertension and osteoarthritis, was associated with depression (6.4%). In a logistic regression model, we observed that obesity in middle-aged women was the strongest risk factor for multimorbidity in the elderly (OR: 2.48; 95% CI, 1.71-3.61), followed by having a job that did not require a qualification (OR: 2.18; 95% CI, 1.67-2.83) and having a low HDL-cholesterol level (OR: 1.31; 95% CI, 1.02-1.68). Conclusions: Multimorbidity was highly prevalent in this older female population. Obesity in middle-aged women was the strongest risk factor for multimorbidity at older age. These results are relevant for Chile and other countries with similar population profiles.

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Section: Introductionmentioning

confidence: 99%

Multimorbidity in a cohort of middle-aged women: Risk factors and disease clustering

Blümel

Carrillo‐Larco

Vallejo³

et al. 2020

Maturitas

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“…The global burden of multimorbidity is well-established [3]. Multimorbidity is significantly associated with lower worker productivity [4], higher risk of polypharmacy [5,6], impaired functioning [7], frailty [8], poor quality of life [9], substantial higher healthcare use [10][11][12], increased healthcare costs [13,14], and increased risk of death [15]. A systematic review has concluded that multimorbidity is highly prevalent [16].…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Multimorbidity among Asian Indian, Chinese, and Non-Hispanic White Adults in the United States

Zhang

Misra

Sambamoorthi

2020

IJERPH

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Asian Americans are the fastest-growing minority group in the United States, yet little is known about their multimorbidity. This study examined the association of Asian Indians, Chinese and non-Hispanic whites (NHWs) to multimorbidity, defined as the concurrent presence of two or more chronic conditions in the same individual. We used a cross-sectional design with data from the National Health Interview Survey (2012–2017) of Asian Indians, Chinese, and NHWs (N = 132,666). Logistic regressions were used to examine the adjusted association of race/ethnicity to multimorbidity. There were 1.9% Asian Indians, 1.8% Chinese, and 96.3% NHWs. In unadjusted analyses (p < 0.001), 17.1% Asian Indians, 17.9% Chinese, and 39.0% NHWs had multimorbidity. Among the dyads, high cholesterol and hypertension were the most common combination of chronic conditions among Asian Indians (32.4%), Chinese (41.0%), and NHWs (20.6%). Asian Indians (AOR = 0.73, 95% CI = (0.61, 0.89)) and Chinese (AOR = 0.63, 95% CI = (0.53, 0.75)) were less likely to have multimorbidity compared to NHWs, after controlling for age, sex, and other risk factors. However, Asian Indians and Chinese were more likely to have high cholesterol and hypertension, risk factors for diabetes and heart disease.

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“…The following variables were included as covariates: year, age, gender, marital status (married and partnered, and otherwise), residency (rural or urban), Hukou (household registration system) status (agricultural Hukou or non-agricultural Hukou), geographical region (east China, middle China, west China, northeast China), family size, education (illiterate, primary school, secondary school, college and above), SES quartile (using household consumption expenditures per capita as a proxy of permanent income, Q1 being the poorest and Q4 being the richest), and work type (farming, formally employed, self-employed, family business, unemployed, retired, never worked). The included socio-demographic characteristics are those demonstrated to be associated with disability and productivity outcomes in the literature [ 3 , 24 , 27 , 41 ].…”

Section: Methodsmentioning

confidence: 99%

“…The literature on the economic impact of mental-physical multimorbidity is relatively sparse in a LMIC setting, where the prevalence and pattern of mental-physical multimorbidity, and the ability of its health care system and social support service (such as health insurance, unemployment insurance, sick leave benefits) in mitigating the potential combined impact of physical illness and mental disorder on health and economic outcomes might be different. A recent systematic review that examined the effect of multimorbidity on productivity [ 27 ], showed that almost all previous studies were from high-income countries except one from Egypt [ 28 ]. However, the study in Egypt did not examine the combined effect of mental and physical chronic conditions on work productivity.…”

Section: Introductionmentioning

confidence: 99%

The association between mental-physical multimorbidity and disability, work productivity, and social participation in China: a panel data analysis

et al. 2021

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Background The co-occurrence of mental and physical chronic conditions (mental-physical multimorbidity) is a growing and largely unaddressed challenge for health systems and wider economies in low-and middle-income countries. This study investigated the independent and combined (additive or synergistic) effects of mental and physical chronic conditions on disability, work productivity, and social participation in China. Methods Panel data study design utilised two waves of the China Health and Retirement Longitudinal Study (2011, 2015), including 5616 participants aged ≥45 years, 12 physical chronic conditions and depression. We used a panel data approach of random-effects regression models to assess the relationships between mental-physical multimorbidity and outcomes. Results After adjusting for socio-economic and demographic factors, an increased number of physical chronic conditions was independently associated with a higher likelihood of disability (Adjusted odds ratio (AOR) = 1.39; 95% CI: 1.33, 1.45), early retirement (AOR = 1.37 [1.26, 1.49]) and increased sick leave days (1.25 days [1.16, 1.35]). Depression was independently associated with disability (AOR = 3.78 [3.30, 4.34]), increased sick leave days (2.18 days [1.72, 2.77]) and a lower likelihood of social participation (AOR = 0.57 [0.47, 0.70]), but not with early retirement (AOR = 1.24 [0.97, 1.58]). There were small and statistically insignificant interactions between physical chronic conditions and mental health on disability, work productivity and social participation, suggesting an additive effect of mental-physical multimorbidity on productivity loss. Conclusion Mental-physical multimorbidity poses substantial negative health and economic effects on individuals, health systems, and societies. More research that addresses the challenges of mental-physical multimorbidity is needed to inform the development of interventions that can be applied to the workplace and the wider community in China.

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Multimorbidity and Its Impact on Workers: A Review of Longitudinal Studies

Cited by 39 publications

References 24 publications

Multimorbidity in a cohort of middle-aged women: Risk factors and disease clustering

Multimorbidity in a cohort of middle-aged women: Risk factors and disease clustering

Prevalence of Multimorbidity among Asian Indian, Chinese, and Non-Hispanic White Adults in the United States

The association between mental-physical multimorbidity and disability, work productivity, and social participation in China: a panel data analysis

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