Factors associated with mortality of the elderly due to ambulatory care sensitive conditions, between 2008 and 2018, in the Federal District, Brazil.

INTRODUCTION: In Brazil, the Unified Health System (Sistema Único de Saúde, or SUS) provides health care, and an aging population overwhelms the system due to the greater vulnerability of the elderly. In the Federal District, two models of primary care coexist-the traditional primary care and the family health strategy. The present study aimed to analyze the factors associated with mortality of the elderly due to conditions sensitive to ambulatory care in the Federal District, Brazil.
MATERIALS AND METHODS: This cross-sectional study investigated all deaths that occurred in people over 60 years old between 2008 and 2018. The variables studied were age at death, sex, marital status, education, race/color, death by condition sensitive to ambulatory care, and population coverage of primary care services. The Urban Well-Being Index (UWBI) was used, which includes the dimensions: mobility, environmental and housing conditions, infrastructure, and collective services, to analyze issues related to the place where the senior citizen resides.
RESULTS: The deaths 70,503 senior citizens were recorded during the study period. The factors associated with mortality in the elderly due to ambulatory care sensitive conditions were male, lower income, and less education. Residing in a place with poor UWBI presented a response gradient with higher mortality. Increased ambulatory care coverage was also associated with lower mortality.
CONCLUSIONS: The study evidenced an association between male gender, age, income, and education, and UWBI with lower mortality due to ambulatory care sensitive conditions, and these associations presented a response gradient. The study also found that increased coverage of the elderly population was associated with lower mortality from sensitive conditions.

Introduction

Due to the improved life expectancy, the increased number of senior citizens has pressured health systems for more efficient responses. In Brazil, the Unified Health System (Sistema Único de Saúde, or SUS) is tasked to guarantee the right to health care, through health promotion, protection, and recovery procedures, considering the social determinants of health. The strong and growing link between socio-economic aspects and health continues to increase, particularly in the elderly population that has diverse vulnerabilities [1].

Good primary health care (PHC) helps to reduce hospitalizations and can impact the mortality of the elderly [2]. PHC requires qualified professionals, service structure, and coordination with other levels of services.

In Brazil, PHC is configured in two models: the traditional primary care (TPC) consisting of specialist physicians (clinician, gynecologist, and pediatrician) and the Family Health Strategy (FHS) formed by a team with a doctor, nurse, nursing technician, and community health agent who works in the area with a registered population of at most 4,000 people [3].

Studies have shown that coverage by primary care contributes to the reduction of mortality in the population, including the elderly [4]. Mortality from ambulatory care sensitive causes is an important performance indicator [5]. In Brazil, Ordinance 221/2008 of the Ministry of Health created a list of avoidable hospitalizations by effective and accessible ambulatory care services to assess the quality of care provided; however, PHC remains scantly available to the elderly population [6]. Different countries have their own lists of ambulatory care sensitive conditions. A review showed a strong association between low socio-economic status and risk of hospitalization for sensitive conditions, thus the relationship between ambulatory care and population morbidity is internationally evidenced [7].

It is known that other general socio-economic, cultural, and environmental factors influence the risk of dying in groups according to the levels of income, education, profession, sex, place of residence, and other factors related to mortality in the elderly [8]. Worsening poverty and social exclusion have become increasingly evident since 2016 with economic austerity policies, especially in large urban centers, with greater social inequalities, increasing extreme poverty and hunger [9]. The issue of decent housing has been understood as a determinant of health and well-being, linked to patterns of illness, especially in communicable diseases, domestic accidents, and mental health [10].

Therefore, analysis in greater depth is needed on how these factors influence the mortality of the elderly due to ambulatory care sensitive conditions. This situation still needs further elucidation in the literature.

We hope that this study will increase understand about the influence of housing conditions and urban infrastructure, measured by the Urban Well-Being Index (UWBI), and primary care coverage on the mortality of the elderly. The hypothesis is that greater primary care coverage and better housing conditions can impact mortality by reducing deaths from conditions sensitive to ambulatory care.

This study analyzed the factors associated with mortality in the elderly due to ambulatory care sensitive conditions in the Federal District, Brazil, from 2008 to 2018.

Materials and methods

The study is based on secondary data obtained from the database of the Health Department of the Federal District. Confidentiality and anonymity were observed in accordance with the Resolution of the National Health Council (CNS) n° 466, of December 12, 2012. The project was approved by the Research Ethics Committee of the Faculty of Health at the University of Brasília, opinion n° 3,479,132; issued on July 31, 2019, Certificate of Presentation for Ethical Appraisal (CAAE) No. 08615719.3.0000.0030. The ethics committee waived the requirement for informed consent.

This is a cross-sectional study, based on mortality data of senior citizens over 60 years old, from 2008 to 2018 in the Federal District, Brazil. In Brazil, a senior citizen is defined as an individual aged 60 years or over [11].

Data were extracted from the mortality information system of the Health Department of the Federal District. This system is based on death certificates and is coordinated by Epidemiological Surveillance. The data are monitored and when inconsistencies are found, additional information is requested. Technicians monitor the information to ensure data quality. In addition, the Federal District has a Death Verification Service to assess deaths whose causes are not well elucidated.

The Federal District is in the Central Plateau of Brazil, located in the Center-Western region. The population in 2019 was estimated at 3,012,718, of which 328,379 were senior citizens [12]. The population studied consisted of all deaths that occurred in the Federal District in people 60 years old or more, between the years 2008 to 2018. Records referring to senior citizens who did not reside in the Federal District, or those with incomplete records were excluded.

Information on coverage of PHC was obtained from the Ministry of Health’s website for information and management of primary care is www.egestorab.saude.gov.br. Coverage data were standardized using as a reference December of each year of the analyzed historical series from 2008–2018.

The variables studied were: age at death (60–69, 70–79, >80), sex (male and female), marital status (single, married, widowed, separated/divorced, not stated), education (none, 0–3, 4–7, 8–11, >12 years of schooling), race/color (white, black, brown, Asian, indigenous, not stated) death by ambulatory care sensitive conditions, coverage by TPC and FHS. In other words, the deceased elderly person lived in a household attended by Primary Care in the traditional model or in the family health strategy model in Federal District.

The variable used to analyze housing and urban infrastructure issues was the UWBI, considering the location where the elderly person resided in Federal District. The UWBI is calculated by the address and consists of five dimensions: mobility, environmental conditions, housing conditions, infrastructure, and collective services. Each of these dimensions is calculated, and then the arithmetic mean is calculated. The result is a value ranging from 0 to 1, in which the UWBI is better the closer to 1 and worse the closer to 0 [13].

The diseases were classified as ambulatory care sensitive conditions according to the ordinance 221/2008 of the Ministry of Health [14]. The tenth version of the International Classification of Diseases (ICD), known as the ICD-10, was used.

The statistical analysis of the data initially relied on the bivariate analysis of the variables of interest to study the outcome (death by sensitive condition). In the next step, a multivariate logistic regression analysis was performed [15], which was built according to a hierarchical structure of three blocks (distal, medial, and proximal). The adjustment variables were sex and age group for the model as a whole but were not restricted to just one of the considered levels.

The first block (distal) included the income group, which also represents a regional characterization for the regions in the Federal District. The second block (medial) had the expression variables of urban well-being, expressed by the UWBI composite index, together with coverage of primary care (TPC) and family health teams (FHS). The third block contained education, marital status, and race/color, which are proximal characteristics.

Statistical analyzes of data were performed using the R [16] v program. 2.2.5019 R Core Team, 2019.

Results

There were 70,503 deaths among the elderly living in the Federal District between 2008 and 2018 (Table 1). Most deaths occurred in women (50.2%), with older seniors predominating (40.7%). Married individuals (38.4%) predominated, followed by widowers (31,3%). Most deaths occurred in seniors who were declared white (55,1%). A significant percentage of deaths resulted from ambulatory care sensitive conditions (29.2%).

Table 1

Distribution of deaths of the elderly according to sociodemographic characteristics and ambulatory care sensitive conditions.

Federal District, Brazil, 2008 to 2018.

		N° of deaths	%
Sex	Female	35.402	50.2
	Male	35.101	49.8
Age group	60 to 69 years old	18.993	26.9
	70 to 79 years old	22.820	32.4
	80 years old or above	28.690	40.7
Marital status	Single	12.467	17.7
	Married	27.105	38.4
	Widowed	22.052	31.3
	Separated/divorced	6.920	9.8
	Not indicated	1.959	2.8
Race/color	White	38.816	55.1
	Black	4.520	6.4
	Asian	437	0.6
	Brown	26.179	37.1
	Indigenous	43	0.1
	Not indicated	508	0.7
Sensitive Condition	Yes	20.606	29.2
	No	49.897	70.8

Source: Database of the Federal District Health Department

In Table 2, deaths in the elderly due to ambulatory care sensitive conditions were correlated with several factors. Men had a higher risk of dying from sensitive conditions. The data on the age group, adjusted for age, elucidated a gradient of greater risk of dying as the seniors’ age increased. Adjusted for sex and age, seniors with lower income exhibited a higher risk of death, but lower middle income had a slightly higher risk of dying than low income.

Table 2

Hierarchical model: Factors associated with deaths of the elderly from ambulatory care sensitive conditions, Distrito Federal, Brazil. 2008–2018.

Independent variables		Total	Sensitive condition		Model A (Block 1)				Model B (Block 2)				Model C (Block 3)
			Yes	No	Odds ratio	95% confidence interval		P-value	Odds ratio	95% confidence interval		P-valor	Odds ratio	95% confidence interval		P-valor
						Upper limit	Lower limit			Upper limit	Lower limit			Upper Limit	Lower limit
Sex	Female	35402	10953	24449	1.133	1.094	1.173	<0.001	1.135	1.095	1.175	<0.001	1.051	1.011	1.092	0.012
	Male (ref.)	35101	9653	25448
Age group (years)	60 to 69 (ref.)	18993	4431	14562
	70 to 79	22820	6615	16205	1.378	1.314	1.444	<0.001	1.380	1.316	1.447	<0.001	1.332	1.270	1.398	<0.001
	80 and over	28690	9560	19130	1.775	1.696	1.857	<0.001	1.794	1.714	1.877	<0.001	1.650	1.571	1.733	<0.001
Income	High (ref.)	13003	3010	9993
group	Upper middle	27206	7886	19320	1.435	1.363	1.511	<0.001
	Lower middle	26075	8387	17688	1.762	1.672	1.856	<0.001
	Lower	3935	1235	2700	1.748	1.605	1.903	<0.001
UWBI *	Very good (ref.)	11605	2654	8951
	Good	8951	2355	6596					1.148	1.052	1.254	0.002
	Average	25434	7689	17745					1.341	1.216	1.480	<0.001
	Bad	23906	7718	16188					1.429	1.269	1.609	<0.001
	Terrible	323	102	221					1.550	1.168	2.057	0.002
FHS Coverage **	%								0.995	0.991	0.999	0.011
TPC Coverage ***	%								0.996	0.994	0.999	0.001
Race/color	White (ref.)	38816	11045	27771
	Black	4520	1440	3080									1.067	0.992	1.148	0.080
	Brown	26179	7833	18346									1.007	0.968	1.047	0.736
	Others	480	149	331									1.048	0.841	1.304	0.678
Marital status	Single (ref.)	12467	3923	8544
	Married	27105	7045	20060									0.862	0.819	0.908	<0.001
	Widowed	22052	7209	14843									0.993	0.943	1.046	0.786
	Separated/ legally divorced	6920	1858	5062									0.945	0.880	1.014	0.114
Education	None	13848	4912	8936									1.465	1.354	1.584	<0.001
	1 to 3 years	20462	6345	14117									1.324	1.232	1.423	<0.001
	4 to 7 years	11638	3286	8352									1.216	1.128	1.311	<0.001
	8 to 11 years	10255	2527	7728									1.134	1.053	1.221	0.001
	12 years or more (ref.)	7922	1627	6295

* UWBI: urban well-being index

** FHS coverage: family health strategy coverage

*** TPC coverage: traditional practice care coverage.

For the UWBI, when adjusted for sex, age, and income, a dose-response relationship was observed–the worse the UWBI, the greater the risk of the senior dying due to sensitive conditions. An even lower risk of dying was noted related to primary care coverage, both in traditional TPC and in the FHS. The race/color of the senior, adjusted for sex, age, income, UWBI, and primary care coverage, did not obtain statistical significance in terms of the risk of dying. In the analysis of marital status, being married had a protective effect on the risk of dying for the elderly from sensitive conditions. Education had a dose-response effect–the lower the education level, the higher the risk of dying from the studied causes.

Discussion

The present study found that being older and being male were factors associated with the mortality of senior citizens due to conditions sensitive to ambulatory care in the Federal District. These findings corroborate the results of other studies that showed a higher risk of dying among elderly men, who tend to have worse health indicators, probably due to their low adherence to preventive measures, and the consequent reduction in autonomy for activities of daily living and less involvement with community activities [17-19].

When the marital status of the senior citizens who passed away was analyzed, being married seemed to have a protective effect against death due to conditions sensitive to ambulatory care. Living with a spouse reduces the mortality of the elderly [20]. This effect can be explained by better financial conditions, better education, and premarital conditions observed in married elderly [21].

Income conditions increased the chance of seniors dying from conditions sensitive to ambulatory care. Poverty, as well as the deprivations resulting from it, has worsened in recent years, compromising the survival of the elderly [18]. In Japan, this situation was related to thousands of premature deaths [22]. In the state of Pará, a study observed that the purchasing power of the elderly as well as access to work and income were associated with greater survival of senior citizens and should be observed and promoted by public health policies [23].

A gradient effect was observed, in that mortality of the elderly due to sensitive conditions decreased inversely proportional to educational level. Higher education levels contribute to better self-care in the elderly, in addition to facilitating therapeutic adherence and understanding of health guidelines [24].

For the UWBI, when adjusted for sex, age, and income, a dose-response effect was observed in this study. The worse their UWBI, the greater their chance of dying from sensitive conditions. The data indicate that the great regional inequalities in the Federal District affect the elderly, which include poor housing, mobility, and environmental conditions as well as collective services. A study of the Federal District showed that the UWBI ranged from 0.26 to 0.97, and 19% of the regions had poor UVBI, while 6% were classified as very poor [13]. Senior citizens in these regions live in very precarious conditions, in informal housing, on unpaved streets, without sewage and running water, and with pollution. As shown by other studies, these conditions lead to several diseases, increasing the early mortality of the elderly [25-27].

The coverage of the population by primary care exhibited a protective effect on the mortality of the elderly due to sensitive conditions. The Federal District has had a significant increase in the number of family health teams in recent years, especially through the 2017 policy of converting traditional TPC teams to FHS [28]. In addition to increasing coverage, this policy focused on improving the care model, through investments in professional training and monitoring [29] and greater capacity to offer comprehensive and holistic care to all segments of the population, including the elderly. The family health teams benefited from the Programa Mais Médico (more doctors), which alleviated the problem of the chronic lack of doctors in peripheral regions and other areas with severe poverty [30].

Several studies reiterate that the good coverage of primary care facilitates access to medical appointments, complementary exams, and the dispensing of medications, which helps reduce mortality of the vulnerable elderly population, especially due to complications of chronic diseases [31-33].

Mortality studies can be impacted by the quality reporting of the causes of death. As this is an ecological study, an ecological bias is possible for all the studied relationships. This study analyzed proportional mortality, which may limit observations on risk of dying; however, it permits conclusions about the chance of association with mortality. Furthermore, the modeling of this study did not permit certification that the deceased elderly person used the PHC service. In addition, income and UWBI were estimated based on the place of residence, which may not correspond to the individual reality of the senior citizens investigated. Another limiting factor for the analysis was the change in the primary care model in 2017, which occurred near the end of the period studied.

Conclusions

The study evidenced an association between the sex, age, income, and education with mortality from ambulatory care sensitive conditions, with the strongest association between poor UWBI and the chance of dying in the elderly. These associations showed a response gradient. This finding indicates the need for public investments to improve urban living conditions to help reduce the death rate of this population. The study also found that increased PHC coverage of the elderly population was associated with lower mortality from sensitive conditions. Therefore, public policies to expand and strengthen primary care have the potential to protect and prolong the lives of the elderly.

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11 Apr 2022

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First of all, I congratulate you on the study carried out. This is a relevant topic and your publication can contribute to a greater understanding of the literature. The text is written in a clear and concise manner, organized and complete in accordance with good scientific writing practices.

I enclose the reviewed manuscript with some suggested adjustments markings. Here I highlight three topics of greatest importance.

First, the unit of analysis of the study is not clear. From the shared database, it is supposed that you worked with a single unit of spatial analysis, the Federal District itself. This information must be in the Methods section.

The second topic refers to the methodological decision to use proportional mortality. For this purpose, the use of the odds ratio (OR) statistic was appropriate, both for performing the logarithmic regression and for the association test without knowledge of incidences. However, at different moments of the discussion and conclusion of the work, these statistics are interpreted as risk, which is not appropriate. I suggest revising the text and correcting all passages that make this mention.

Finally, I suggest further detailing the work limitations section, especially for the topics:

- it is an ecological study, therefore, subject to ecological bias for all relationships studied;

- depending on the size of the analysis unit, the statistical analysis may have lost power.

- use of proportional mortality does not allow conclusions regarding the risk of death, and other studies with adequate methodology are necessary to reach this conclusion.

I wish you success with the publication. Best regards.

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Reviewer #1: Yes: Marcelo Pellizzaro Dias Afonso

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Submitted filename: PONE-D-21-36313_reviewer.pdf

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29 Apr 2022

Response to Reviewers

Thank you for reviewing our article entitled “FACTORS ASSOCIATED WITH MORTALITY OF THE ELDERLY DUE TO AMBULATORY CARE SENSITIVE CONDITIONS, BETWEEN 2008 AND 2018, IN THE FEDERAL DISTRICT, BRAZIL”. The suggested changes were made and certainly helped substantially improve our work.

The answers are below:

1) The database of deaths belonging to the Government Health Department of the Federal District was used and monitored by the technical team of the Epidemiological Surveillance. It is a robust database that has been using the same software since 1998. Technicians evaluate the death certificates received, and if the data are inconsistent, additional information is requested from the hospitals or health units where the declarations were filled out. In addition, the Federal District has Death Verification Services (DVS) where professionals evaluate bodies whose cause of death is not well understood to define the cause of death. DVS performs autopsies in the following situations: diseases with mandatory notification, cases without definition of the underlying cause of death, and deaths in less than 24 hours of hospital admission, without diagnosis. The technicians for the death database of the Federal District meet weekly to ensure completeness of the data.

2) The choice of variables occurred after reviewing the database, correlating with the objectives of the article. Initially, the classic variables, such as sex, age, marital status, and race/color, were analyzed. We list the causes of death and indicate those that occurred due to conditions sensitive to ambulatory care, according to Ordinance No. 221 of April 17, 2008, by the Ministry of Health of Brazil. To correlate with primary care, we investigated the coverage by the health service, differentiating between the traditional primary care model and the family health strategy model according to the address of the deceased elderly person. We wanted to understand the importance of social inequalities in the deaths of the elderly. Once the deaths of the elderly in the Federal District were studied, different socioeconomic realities in the same geographic unit were analyzed. There are elderly people with high economic power, living in the best urban conditions, and very poor elderly people living in places with poor infrastructure. To understand the influence of socioeconomic factors, we correlated it with the Urban Well-Being Index (UWBI).

This index is composed of five dimensions: mobility, environmental, and housing conditions, infrastructure, and collective services. Each of these dimensions is calculated, and then the arithmetic mean is calculated. The result is a value that ranges from 0 to 1. The UWBI is better the closer it is to 1 and worse the closer it is to 0. The address of the deceased elderly person was considered. We reiterate that all analyzed variables are plausible and previously had a possible causal relationship.

As for the expected results, the primary researcher, who is a family and community physician and works in the poorest region of the Federal District, wanted, among other things, to understand how the conditions of the place of residence influence the mortality of the elderly. We hypothesized that the analysis would show that the inequalities, expressed in our article by the UWBI, impact the mortality of the elderly, as the main researcher has empirically observed this phenomenon in his routine of care.

3) We chose to use the ecological variables primary care coverage and UWBI in our analysis. These variables were shown to be adequate for the hierarchical modeling of the article, since they analyze the context of the geographic, urban, and housing conditions of individuals. We indicate as a possible limitation of the study that this modeling can be impacted by the ecological bias. These variables in the article do not work as a period-time control.

4) The work performed a hierarchical modeling. In this model, we used age at the distal level (block A). The age effect was tested at this level, and in fact showed an association between older age and higher mortality from conditions sensitive to ambulatory care (OR: 1.775, p<0.001). The age variable was used to adjust the following variables at the medial level (block B) and at the proximal level (block C) to ensure better reliability.

Our study analyzed a common outcome for all research participants, the death of the elderly. To answer the hypotheses of the study, the outcome was classified as a binary variable: death from a sensitive condition – yes or no. The categorization of the outcome variable as binary would make the modeling resulting from counting unfeasible. Thus, we believe that the hierarchical model is more adequate for our objective.

Excellent colocation by the reviewer; however, the modeling performed answered our research question. Nevertheless, if the analysis suggested by the editor is essential, we would be willing to carry it out.

5) We made the change suggested by the editor, and we changed it to chance (odds).

We await the final answer and are available for any clarifications.

Sincerely.

The authors.

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8 Jun 2022

4 Jul 2022

Response to Reviewers

Dear reviewers

Thank you for reviewing our article entitled “FACTORS ASSOCIATED WITH MORTALITY OF THE ELDERLY DUE TO AMBULATORY CARE SENSITIVE CONDITIONS, BETWEEN 2008 AND 2018, IN THE FEDERAL DISTRICT, BRAZIL”. PONE-D-21-36313R1 The suggested changes were answered and definitely contributed to substantially improve our work.

The answers are as follows:

1- Coverage and urban well-being do not vary by individual, they only vary by period of time. What is the limitation of doing this? Does it act as a control for period?

We appreciate the comment. We do not see any major limitation in the use of variables that may have changed over the period covered by the study, since for each death we associate what we believe to be the most appropriate value for that point in time. Well-being has only one measure for the period, so we had no choice of which value to use for each event. Primary Care coverage was defined for each death considering the address where the elderly person resided, who was covered by either Traditional Primary Care or Family Health Strategy in December of each year of the study period. This study was cross-sectional, and the variables mentioned were not included in order to control for the period, but rather to assess whether changes in their levels lead to an increase or decrease in the chance that the outcome of interest occurs. As it is not possible at the ecological level to have different values of these factors at the same moment in time, the only way to assess their effects was to analyze the set of deaths over several years, within the proposed methodological design.

2- Mortality increases with age - there are more deaths at older ages than any other age. Thus, it is expect that we see deaths increasing with your age in the analysis. One alternative is to model age specific mortality rates. One can obtain population by sex and age from IBGE or other sources. Then, you could model death rates or apply a poisson model on the counts of death. I believe modeling only death counts without a exposure measure limits the discussion of the results and might be affecting your results.

As noted by the reviewer, we believed that age could impact the chance of dying. To adjust for the effect of age, it was included in the distal level of the hierarchical model, which allows us to interpret all coefficients at the same level and at subsequent levels (intermediate and proximal) as independent effects of the variables, already adjusted for age. Our objectives were to investigate possible predictors of dying from ambulatory care sensitive conditions in the age group of the study. For this reason, we opted for logistic regression (binary outcome) with the hierarchical approach already mentioned.

As indicated in the answer to item 1, this is a cross-sectional study, and the correction is already explained in the materials and methods section.

We appreciate the considerations and are available to conduct any additional analyzes requested by the reviewer.

We await the final answer and are available for any clarifications.

Sincerely.

The authors.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

25 Jul 2022

FACTORS ASSOCIATED WITH MORTALITY OF THE ELDERLY DUE TO AMBULATORY CARE SENSITIVE CONDITIONS, BETWEEN 2008 AND 2018, IN THE FEDERAL DISTRICT, BRAZIL

PONE-D-21-36313R2

Dear Dr. Marques da Costa,

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Reviewers' comments:

28 Jul 2022

PONE-D-21-36313R2

Factors associated with mortality of the elderly due to ambulatory care sensitive conditions, between 2008 and 2018, in the Federal District, Brazil

Dear Dr. Marques da Costa:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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on behalf of

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